Preprint
|
|
|
Mathematics & Computer Science, Computational Mathematics; expression; analytic property; Fuss–Catalan number; Catalan–Qi function; Catalan number; monotonicity; logarithmic convexity; complete monotonicity; minimality; inequality
Online: 15 August 2017 (08:36:23 CEST)
|
|
Share this article with
×
In the paper, the authors express the Fuss–Catalan numbers as several forms in terms of the Catalan–Qi function, find some analytic properties, including the monotonicity, logarithmic convexity, complete monotonicity, and minimality, of the Fuss–Catalan numbers, and derive a double inequality for bounding the Fuss–Catalan numbers.
Preprint
|
|
|
Mathematics & Computer Science, Information Technology & Data Management; EMR; data preprocessing; text mining; information extraction; medical decision support system
Online: 15 August 2017 (05:46:43 CEST)
|
|
Share this article with
×
At present, medical institutes generally use EMR to record patient's condition, including diagnostic information, procedures performed and treatment results. EMR has been recognized as a valuable resource for large scale analysis. However, EMR has the characteristics of diversity, incompleteness, redundancy and privacy, which make it difficult to carry out data mining and analysis directly. Therefore, it is necessary to preprocess the source data in order to improve data quality and improve the data mining results. Different types of data require different processing technologies. Most structured data commonly needs classic preprocessing technologies, including data cleansing, data integration, data transformation and data reduction. For semi-structured or unstructured data, such as medical text, containing more health information, it requires more complex and challenging processing methods. The task of information extraction for medical texts mainly includes NER (Named Entity Recognition) and RE (Relation Extraction). In this paper, we introduce the process of EMR processing, including data collection, data preprocessing, data mining, evaluation and knowledge application, analyze the current status of the key technologies, such as data preprocessing and data mining, and provide an overview of the application domains and prospects of EMR mining technologies. Finally, we summarize the existing problems in the research of EMR mining, and review the development trends.
Preprint
|
|
|
Mathematics & Computer Science, Applied Mathematics; air- or iron-cored coil; polar coordinates; fourier analysis; two-dimensional; subdomain technique
Online: 14 August 2017 (06:07:40 CEST)
|
|
Share this article with
×
This paper presents a new scientific contribution on the two-dimensional (2-D) subdomain technique in polar coordinates taking into account the finite relative permeability of the ferromagnetic material. The constant relative permeability corresponds to linear part of the nonlinear B(H) curve. As in conventional technique, the method of separation of variables and the Fourier’s series are used for the resolution of magnetostatic Maxwell’s equations in each region. Although, the general solutions of magnetic field in the subdomains and boundary conditions (BCs) between regions are different in the conventional and proposed method. In this later, the magnetic field solution in each subdomain is a superposition of two magnetic quantities in the two directions (i.e., r- and Q-axis) and the BCs between two regions are also in both directions. For example, the scientific contribution has been applied to an air- or iron-cored coil supplied by a constant current. The distribution of local quantities (i.e., the magnetic vector potential and flux density) has been validated by a corresponding 2-D finite-element analysis (FEA). The obtained semi-analytical results are in very good agreement with those of numerical method.
Preprint
|
|
|
Mathematics & Computer Science, Analysis; identity; Bell polynomial; unnamed polynomial; explicit formula; inversion theorem; Stirling number; binomial coefficient
Online: 11 August 2017 (13:51:05 CEST)
|
|
Share this article with
×
In the paper, using two inversion theorems for the Stirling numbers and binomial coecients, employing properties of the Bell polynomials of the second kind, and utilizing a higher order derivative formula for the ratio of two di erentiable functions, the authors present two explicit formulas, a determinantal expression, and a recursive relation for a sequence of unnamed polynomials, derive two identities connecting the sequence of unnamed polynomials with the Bell polynomials, and recover a known identity connecting the sequence of unnamed polynomials with the Bell polynomials.
Preprint
|
|
|
Mathematics & Computer Science, Other; fuzzy set; ordered category; category of fuzzysets
Online: 9 August 2017 (06:39:47 CEST)
|
|
Share this article with
×
In modern mathematics, many concepts and ideas are described in terms of category theory. From this viewpoint, it is desirable to analyze what can be determined if, instead of the basic category of sets, we consider a similar category of fuzzy sets. In this paper, we describe a natural fuzzy analog of the category of sets and functions, and we show that, in this category, fuzzy relations (a natural fuzzy analogue of functions) can be determined in category terms -- of course, modulo 1-1 mapping of the corresponding universe of discourse and 1-1 re-scaling of fuzzy degrees.
Preprint
|
|
|
Mathematics & Computer Science, Analysis; simplification; coefficient; ordinary differential equation; higher order Bernoulli number of the second kind; Stirling number of the first kind; Stirling number of the second kind; inversion formula; Bell polynomial of the second kind; Faà di Bruno formula.
Online: 8 August 2017 (07:59:57 CEST)
|
|
Share this article with
×
In the paper, by virtue of the Faà di Bruno formula, some properties of the Bell polynomials of the second kind, and an inversion formula for the Stirling numbers of the first and second kinds, the authors establish meaningfully and significantly two identities which simplify coefficients in a family of ordinary differential equations associated with higher order Bernoulli numbers of the second kind.
Preprint
|
|
|
Mathematics & Computer Science, Algebra & Number Theory; identity; inverse matrix; explicit formula; generating function; Chebyshev polynomials of the second kind; Catalan number; triangular matrix; classical hypergeometric function; integral representation
Online: 7 August 2017 (15:49:11 CEST)
|
|
Share this article with
×
In the paper, the authors establish two identities to express the generating function of the Chebyshev polynomials of the second kind and its higher order derivatives in terms of the generating function and its derivatives each other, deduce an explicit formula and an identities for the Chebyshev polynomials of the second kind, derive the inverse of an integer, unit, and lower triangular matrix, present several identities of the Catalan numbers, and give some remarks on the closely related results including connections of the Catalan numbers respectively with the Chebyshev polynomials, the central Delannoy numbers, and the Fibonacci polynomials.
Preprint
|
|
|
Mathematics & Computer Science, Other; real‐time reconstruction; SLAM; kinect sensors; depth cameras; open source
Online: 7 August 2017 (11:03:23 CEST)
|
|
Share this article with
×
Given a stream of depth images with a known cuboid reference object present in the scene, we propose a novel approach for accurate camera tracking and volumetric surface reconstruction in real-time. Our contribution in this paper is threefold: (a) utilizing a priori knowledge of the cuboid reference object, we keep drift-free camera tracking without explicit global optimization; (b) we improve the fineness of the volumetric surface representation by proposing a prediction-corrected data fusion strategy rather than simple moving average, which enables accurate reconstruction of high-frequency details such as sharp edges of objects and geometries of high curvature; (c) we introduce a benchmark dataset CU3D containing both synthetic and real-world scanning sequences with ground-truth camera trajectories and surface models for quantitative evaluation of 3D reconstruction algorithms. We test our algorithm on our dataset and demonstrate its accuracy compared with other state-of-the-art algorithms. We release both our dataset and code as opensource1 for other researchers to reproduce and verify our results.
Preprint
|
|
|
Mathematics & Computer Science, Analysis; simplification; coefficient; ordinary differential equation; higher order Frobenius–Euler number; Fa`a di Bruno formula; Bell polynomial of the second kind; inversion formula
Online: 4 August 2017 (15:47:44 CEST)
|
|
Share this article with
×
In the paper, by virtue of the Fa`a di Bruno formula, some properties of the Bell polynomials of the second kind, and the inversion formulas of binomial numbers and the Stirling numbers of the first and second kinds, the authors simplify meaningfully and significantly coefficients in two families of ordinary differential equations associated with higher order Frobenius–Euler numbers.
Preprint
|
|
|
Mathematics & Computer Science, Computational Mathematics; identity; generating function; Eulerian polynomial; higher order Eulerian polynomial; Stirling number; open problem
Online: 2 August 2017 (17:03:00 CEST)
|
|
Share this article with
×
In the paper, the authors establish two identities, which can be regarded as nonlinear differential equations, for the generating function of Eulerian polynomials, find two identities for the Stirling numbers of the second kind, and present two identities for Eulerian polynomials and higher order Eulerian polynomials, pose two open problems about summability of two finite sums involving the Stirling numbers of the second kind. Some of these conclusions meaningfully and significantly simplify several known results.
Preprint
|
|
|
Mathematics & Computer Science, Artificial Intelligence & Robotics; stylometry; author identification; author verification; authorprofiling; stylistic inconsistency; text analysis; supervised learning; unsupervised learning; classification; forensics
Online: 2 August 2017 (12:38:17 CEST)
|
|
Share this article with
×
Electronic text stylometry is a collection of forensics methods that analyze the writing styles of input electronic texts in order to extract information about authors of the input electronic texts. Such extracted information could be the identity of the authors, or aspects of the authors, such as their gender, age group, ethnicity, etc. This survey paper presents the following contributions: 1) A description of all stylometry problems in probability terms, under a unified notation. To the best of our knowledge, this is the most comprehensive definition to date. 2) A survey of key methods, with a particular attention to data representation (or feature extraction) methods. 3) An evaluation of 23,760 feature extraction methods, which is the most comprehensive evaluation of feature extraction methods in the literature of stylometry to date. The importance of this evaluation is two fold. First, identifying the relative effectiveness of the features (since, currently, many are not evaluated jointly; e.g. syntactic n-grams are not evaluated against k-skip n-grams, and so forth). Second, thanks to our generalizations, we could evaluate novel grams, such as what we name compound grams. 4) The release of our associated Python feature extraction library, namely Fextractor. Essentially, the library generalizes all existing n-gram based feature extraction methods under the "at least l-frequent, dir-directed, k-skipped n-grams'', and allows grams to be diversely defined, including definitions that are based on high-level grammatical aspects, such as POS tags, as well as lower-level ones, such as distribution of function words, word shapes, etc. This makes the library, by far, the most extensive in this domain to date. 5) The construction, evaluation, and release of the first dataset for Emirati social media text. This evaluation represents the first evaluation of author identification against Emirati social media texts. Interestingly, we find that, when using our models and feature extraction library (Fextractor), authors could be identified significantly more accurately than what is reported with similarly sized datasets. The dataset also contains sub-datasets that represent other languages (Dutch, English, Greek and Spanish), and our findings are consistent across them.
Preprint
|
|
|
Mathematics & Computer Science, Applied Mathematics; portfolio optimization; Kelly criterion; differential evolution; mean-variance
Online: 31 July 2017 (11:22:09 CEST)
|
|
Share this article with
×
Kelly's Criterion is well known among gamblers and investors as a method for maximizing the returns one would expect to observe over long periods of betting or investing. These ideas are conspicuously absent from portfolio optimization problems in the financial and automation literature. This paper will show how Kelly's Criterion can be incorporated into standard portfolio optimization models. The model developed here combines risk and return into a single objective function by incorporating a risk parameter. This model is then solved for a portfolio of 10 stocks from a major stock exchange using a differential evolution algorithm. Monte Carlo calculations are used to verify the accuracy of the results obtained from differential evolution. The results show that evolutionary algorithms can be successfully applied to solve a portfolio optimization problem where returns are calculated by applying Kelly's Criterion to each of the assets in the portfolio.
Preprint
|
|
|
Mathematics & Computer Science, Numerical Analysis & Optimization; physical layer security; semi-infinite programming; amplify-and-forward two-way relay; imperfect CSI; robust optimization
Online: 31 July 2017 (08:59:04 CEST)
|
|
Share this article with
×
This paper considers a two-way relay network, where two source nodes exchange messages through several relays in the presence of an eavesdropper, and the channel state information (CSI) of the eavesdropper is imperfectly known. The amplify-and-forward relay protocol is used and the relay beamforming weights are designed. The model is built up to minimize the total relay transmit power while guaranteeing the quality of service at users and preventing the eavesdropper from decoding the signals. Due to the imperfect CSI, a semi-infinite programming problem is obtained. An algorithm is proposed to solve the problem, and the iterative points are updated through the linesearch technique, where the feasibility are preserved during iterations. The optimality property is analyzed. The obtained subproblems are quadratic constrained quadratic programming problems, either with less than $4$ constraints or with only one variable, which are solved optimally. Simulation results demonstrate the importance of the proposed model, and imply that the proposed algorithm is efficient and converges very fast, where more than 85% of the problems are solved optimally.
Preprint
|
|
|
Mathematics & Computer Science, General & Theoretical Computer Science; dynamic algorithms; distributed shortest paths; communication networks; routing protocols; power-law networks
Online: 28 July 2017 (06:06:35 CEST)
|
|
Share this article with
×
Efficiently solving the problem of computing, in a distributed fashion, the shortest paths of a graph whose topology dynamically changes over time is a core functionality of many today’s digital infrastructures, probably the most prominent example being communication networks. Many solutions have been proposed over the years for this problem that can be broadly classified into two categories, namely Distance-Vector and Link-State algorithms. Distance-Vector algorithms are widely adopted solutions when scalability and reliability are key issues or when nodes have either limited hardware resources, as they result in being very competitive approaches in terms of both the memory and the computational point of view. In this paper, we first survey some of the most established solutions of the Distance-Vector category. Then, we discuss some recent algorithmic developments in this area. Finally, we propose a new experimental study, conducted on a prominent category of network instances, namely generalized linear preference (GLP) power-law networks, to rank the performance of such solutions.
Preprint
|
|
|
Mathematics & Computer Science, Applied Mathematics; S degree; S indices; topological indices; QSAR; QSPR
Online: 25 July 2017 (04:31:48 CEST)
|
|
Share this article with
×
Topological indices have been used to modeling biological and chemical properties of molecules in quantitive structure property relationship studies and quantitive structure activity studies. All the degree based topological indices have been defined via classical degree concept. In this paper we define a novel degree concept for a vertex of a simple connected graph: S degree. And also we define S indices of a simple connected graph by using the S degree concept. We compute the S indices for well-known simple connected graphs such as paths, stars, complete graphs and cycles.
Preprint
|
|
|
Mathematics & Computer Science, Applied Mathematics; Gauss-exponential distribution; Gauss-Laplace distribution; stochastic vector representation; geometric measure representation; (p,q)-generalized polar coordinates; (p,q)-arc length; dynamic intersection proportion function; (p,q)-generalized Box-Muller simulation method; (p,q)-spherical uniform distribution; dynamic geometric disintegration
Online: 19 July 2017 (04:35:06 CEST)
|
|
Share this article with
×
For evaluating probabilities of arbitrary random events with respect to a given multivariate probability distribution, specific techniques are of great interest. An important two-dimensional high risk limit law is the Gauss-exponential distribution whose probabilities can be dealt with based upon the Gauss-Laplace law. The latter will be considered here as an element of the newly introduced family of (p,q)-spherical distributions. Based upon a suitably defined non-Euclidean arc-length measure on (p,q)-circles we prove geometric and stochastic representations of these distributions and correspondingly distributed random vectors, respectively. These representations allow dealing with the new probability measures similarly like with elliptically contoured distributions and more general homogeneous star-shaped ones. This is demonstrated at hand of a generalization of the Box-Muller simulation method. En passant, we prove an extension of the sector and circle number functions.
Preprint
|
|
|
Mathematics & Computer Science, Artificial Intelligence & Robotics; smartphone accelerometers; dataset; human activity recognition; fall detection
Online: 18 July 2017 (13:16:10 CEST)
|
|
Share this article with
×
Smartphones, smartwatches, fitness trackers, and ad-hoc wearable devices are being increasingly used to monitor human activities. Data acquired by the hosted sensors are usually processed by machine-learning-based algorithms to classify human activities. The success of those algorithms mostly depends on the availability of training (labeled) data that, if made publicly available, would allow researchers to make objective comparisons between techniques. Nowadays, publicly available data sets are few, often contain samples from subjects with too similar characteristics, and very often lack of specific information so that is not possible to select subsets of samples according to specific criteria. In this article, we present a new smartphone accelerometer dataset designed for activity recognition. The dataset includes 11,771 activities performed by 30 subjects of ages ranging from 18 to 60 years. Activities are divided in 17 fine grained classes grouped in two coarse grained classes: 9 types of activities of daily living (ADL) and 8 types of falls. The dataset has been stored to include all the information useful to select samples according to different criteria, such as the type of ADL performed, the age, the gender, and so on. Finally, the dataset has been benchmarked with two different classifiers and with different configurations. The best results are achieved with k-NN classifying ADLs only, considering personalization, and with both windows of 51 and 151 samples.
Preprint
|
|
|
Mathematics & Computer Science, Analysis; generalized functions; tempered distributions; regular functions; local functions; regularization-localization duality; regularity; Heisenberg’s uncertainty principle
Online: 17 July 2017 (06:25:18 CEST)
|
|
Share this article with
×
In this paper, we relate Poisson’s summation formula to Heisenberg’s uncertainty principle. They both express Fourier dualities within the space of tempered distributions and these dualities are furthermore the inverses of one another. While Poisson’s summation formula expresses a duality between discretization and periodization, Heisenberg’s uncertainty principle expresses a duality between regularization and localization. We define regularization and localization on generalized functions and show that the Fourier transform of regular functions are local functions and, vice versa, the Fourier transform of local functions are regular functions.
Preprint
|
|
|
Mathematics & Computer Science, Algebra & Number Theory; prime graph; simple group; orthogonal groups; quasirecognition
Online: 10 July 2017 (09:01:04 CEST)
|
|
Share this article with
×
Let G be a finite group. The prime graph Γ(G) of G is defined as follows: The set of vertices of Γ(G) is the set of prime divisors of |G| and two distinct vertices p and p' are connected in Γ(G), whenever G has an element of order pp'. A non-abelian simple group P is called recognizable by prime graph if for any finite group G with Γ(G)=Γ(P), G has a composition factor isomorphic to P. In [4] proved finite simple groups 2Dn(q), where n ≠ 4k are quasirecognizable by prime graph. Now in this paper we discuss the quasirecognizability by prime graph of the simple groups 2D2k(q), where k ≥ 9 and q is a prime power less than 105.
Preprint
|
|
|
Mathematics & Computer Science, Artificial Intelligence & Robotics; human activity analysis; human intention understanding; affective computing; data visualisation; depth data; head pose estimation; emotion recognition
Online: 10 July 2017 (08:26:31 CEST)
|
|
Share this article with
×
Affective computing in general and human activity and intention analysis in particular, is a rapidly growing field of research. Head pose and emotion changes, present serious challenges when applied to player’s training and ludology experience in serious games or analysis of customer satisfaction regarding broadcast and web services or monitoring a driver’s attention. Given the increasing prominence and utility of depth sensors, it is now feasible to perform large-scale collection of three-dimensional (3D) data for subsequent analysis. Discriminative random regression forests was selected in order to rapidly and accurately estimate head pose changes in unconstrained environment. In order to complete the secondary process of recognising four universal dominant facial expressions (happiness, anger, sadness and surprise), emotion recognition via facial expressions (ERFE) was adopted. After that, a lightweight data exchange format (JavaScript Object Notation-JSON) is employed, in order to manipulate the data extracted from the two aforementioned settings. Motivated by the need of generating comprehensible visual representations from different sets of data, in this paper we introduce a system capable of monitoring human activity through head pose and emotion changes, utilising an affordable 3D sensing technology (Microsoft Kinect sensor).
Preprint
|
|
|
Mathematics & Computer Science, General & Theoretical Computer Science; Internet of Things; data mining algorithms; GPU cluster; performance; energy consumption; reliability
Online: 6 July 2017 (12:40:22 CEST)
|
|
Share this article with
×
This paper aims to develop a low-cost, high-performance and high-reliability computing system to process large-scale data using common data mining algorithms in the Internet of Things computing. Considering the characteristics of IoT data processing, similar to mainstream high performance computing, we use a GPU cluster to achieve better IoT services. Firstly, we present an energy consumption calculation method (ECCM) based on WSN. Then, using the CUDA Programming model, we propose a Two-level Parallel Optimization Model (TLPOM) which exploits reasonable resource planning and common compiler optimization techniques to obtain the best blocks and threads configuration considering the resource constraints of each node. The key to this part is dynamic coupling Thread-Level Parallelism (TLP) and Instruction-Level Parallelism (ILP) to improve the performance of the algorithms without additional energy consumption. Finally, combining the ECCM and the TLPOM, we use the Reliable GPU Cluster Architecture (RGCA) to obtain a high-reliability computing system considering the nodes’ diversity, algorithm characteristics, etc. The results show that the performance of the algorithms significantly increased by 34.1%, 33.96% and 24.07% for Fermi, Kepler and Maxwell on average with TLPOM and the RGCA ensures that our IoT computing system provides low-cost and high-reliability services.
Preprint
|
|
|
Mathematics & Computer Science, Numerical Analysis & Optimization; Fuzzy forecasting, fuzzy-fluctuation trend, particle swarm optimization, fuzzy time series, fuzzy logical relationship
Online: 4 July 2017 (16:35:22 CEST)
|
|
Share this article with
×
Most of existing fuzzy forecasting models partition historical training time series into fuzzy time series and build fuzzy-trend logical relationship groups to generate forecasting rules. The determination process of intervals is complex and uncertainty. In this paper, we present a novel fuzzy forecasting model based on high-order fuzzy-fluctuation trends and the fuzzy-fluctuation logical relationships of the training time series. Firstly, we compare each data with the data of its previous day in historical training time series to generate a new fluctuation trend time series(FTTS). Then, fuzzify the FTTS into fuzzy-fluctuation time series(FFTS) according to the up, equal or down range and orientation of the fluctuations. Since the relationship between historical FFTS and the fluctuation trend of future is nonlinear, Particle Swarm Optimization (PSO) algorithm is employed to estimate the required parameters. Finally, use the acquired parameters to forecast the future fluctuations. In order to compare the performance of the proposed model with that of the other models, we apply the proposed method to forecast the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) time series datasets. The experimental results and the comparison results show that the proposed method can be successfully applied in stock market forecasting or such kinds of time series. We also apply the proposed method to forecast Shanghai Stock Exchange Composite Index (SHSECI) to verify its effectiveness and universality.
Preprint
|
|
|
Mathematics & Computer Science, Other; big data； body area network；body sensor network；edge computing；Fog Computing； Medical Cyberphysical Systems； medical internet-of-things；telecare； tele-treatment；wearable devices
Online: 26 June 2017 (06:24:07 CEST)
|
|
Share this article with
×
In the era when the market segment of Internet of Things (IoT) tops the chart in various business reports, it is apparently envisioned that the field of medicine expects to gain a large benefit from the explosion of wearables and internet-connected sensors that surround us to acquire and communicate unprecedented data on symptoms, medication, food intake, and daily-life activities impacting one’s health and wellness. However, IoT-driven healthcare would have to overcome many barriers, such as: 1) There is an increasing demand for data storage on cloud servers where the analysis of the medical big data becomes increasingly complex; 2) The data, when communicated, are vulnerable to security and privacy issues; 3) The communication of the continuously collected data is not only costly but also energy hungry; 4) Operating and maintaining the sensors directly from the cloud servers are non-trial tasks.This book chapter defined Fog Computing in the context of medical IoT. Conceptually, Fog Computing is a serviceoriented intermediate layer in IoT, providing the interfaces between the sensors and cloud servers for facilitating connectivity, data transfer, and queryable local database. The centerpiece of Fog computing is a low-power, intelligent, wireless, embedded computing node that carries out signal conditioning and data analytics on raw data collected from wearables or other medical sensors and offers efficient means to serve telehealth interventions. We implemented and tested an fog computing system using the Intel Edison and Raspberry Pi that allows acquisition, computing, storage and communication of the various medical data such as pathological speech data of individuals with speech disorders, Phonocardiogram (PCG) signal for heart rate estimation, and Electrocardiogram (ECG)-based Q, R, S detection. The book chapter ends with experiments and results showing how fog computing could lessen the obstacles of existing cloud-driven medical IoT solutions and enhance the overall performance of the system in terms of computing intelligence, transmission, storage, configurable, and security. The case studies on various types of physiological data shows that the proposed Fog architecture could be used for signal enhancement, processing and analysis of various types of bio-signals.
Preprint
|
|
|
Mathematics & Computer Science, Information Technology & Data Management; big data,；Hadoop； visualization； model
Online: 26 June 2017 (06:07:51 CEST)
|
|
Share this article with
×
In era of ever-expanding data and knowledge, we lack a centralized system that maps all the faculties to their research works. This problem has not been addressed in the past and it becomes challenging for students to connect with the right faculty of their domain. Since we have so many colleges and faculties this lies in the category of big data problem. In this paper, we present a model which works on the distributed computing environment to tackle big data. The proposed model uses apache spark as an execution engine and hive as database. The results are visualized with the help of Tableau that is connected to Apache Hive to achieve distributed computing.
Preprint
|
|
|
Mathematics & Computer Science, Numerical Analysis & Optimization; fractional neutral integro-differential equations; initial value problem; Caputo fractional derivative; Krasnoselskii's fixed point theorem
Online: 20 June 2017 (03:42:54 CEST)
|
|
Share this article with
×
In this paper, by means of the Banach fixed point theorem and the Krasnoselskii's fixed point theorem, we investigate the existence of solutions for some fractional neutral functional integro-differential equations involving infinite delay. This paper deals with the fractional equations in the sense of Caputo fractional derivative and in the Banach spaces. Our results generalize the previous works on this issue. Also, an analytical example is presented to illustrate our results.
Preprint
|
|
|
Mathematics & Computer Science, Applied Mathematics; generalized triangular intuitionistic fuzzy geometric aggregation operator; triangular intuitionistic fuzzy number; intuitionistic fuzzy set; multi-criteria decision-making; attitudinal character; flexibility
Online: 14 June 2017 (05:55:52 CEST)
|
|
Share this article with
×
Intuitionistic fuzzy set, which can be represented using the triangular intuitionistic fuzzy number (TIFN), is a more generalized platform for expressing imprecise, incomplete and inconsistent information when solving multi-criteria decision-making problems, as well as for reflecting the evaluation information exactly in different dimensions. In this paper, the TIFN has been applied for solving some multi-criteria decision-making problems by developing a new triangular intuitionistic fuzzy geometric aggregation operator, that is the generalized triangular intuitionistic fuzzy ordered weighted geometric averaging (GTIFOWGA) operator, and defining some triangular intuitionistic fuzzy geometric aggregation operators including the triangular intuitionistic fuzzy weighted geometric averaging (TIFWGA) operator, the ordered weighted geometric averaging (TIFOWGA) operator and the hybrid geometric averaging (TIFHWGA) operator. Based on these operators, a new approach for solving multicriteria decision-making problems when the weight information is fixed has been proposed. Finally, the proposed method has been compared with some similar existing computational approaches by virtue of a numerical example to verify its feasibility and rationality.
Preprint
|
|
|
Mathematics & Computer Science, Information Technology & Data Management; two-factor authentication; online training; biological and behavioral features; mimic control method with sound intensity
Online: 6 June 2017 (09:04:47 CEST)
|
|
Share this article with
×
This study examines the evolution of the two-factor authentication method and its adaptability to the online education system. Two-factor authentication is a security measure used especially in areas where information such as banking is valuable. Parallel to technological developments, it has developed as much as daily. It aims to take security one step forward because it is composed of two phases. Today, banking, IOT devices, public transport tickets and many other areas are used. Two-factor authentication methods against security attacks in the field of information are also being updated. In recent years, new technologies such as biometric (iris pattern, retinal pattern, etc.) or behavioral biometry (location tracking, walking information, touch speed etc.) were studied. Instead of physically studying somewhere like going to a course in modern society, online trainings become more advantageous. Most of these online trainings are given certificates such as participation certificate, success certificate, etc. The main problem here is whether the person who is being certified is true. In the study conducted in line with these details, there is a proposal for the application of the Mimic Control Method with Sound Intensity (MCMSI) method for on-line training by examining the two-factor authentication techniques up to the day.
Preprint
|
|
|
Mathematics & Computer Science, Other; pumped storage hydro unit; guide vane closing schemes; multi-objective optimization; enhanced multi-objective bacterial-foraging chemotaxis gravitational search algorithm (EMOBCGSA); hydraulic and mechanical constraints
Online: 2 June 2017 (07:56:05 CEST)
|
|
Share this article with
×
The optimization of guide vane closing schemes (OGVCS) of pumped storage hydro unit (PSHU) is the research field of cooperative control and optimal operation of pumped storage, wind power and solar power generation. This paper presents a OGVCS model of PSHU considering the rise rate of the unit rotational speed and the specific node pressure of each hydraulic unit, as well as various complicated hydraulic and mechanical constraints. OGVCS model is formulated as a multi-objective optimization problem to optimize conflictive objectives, i.e., unit rotational speed and water hammer pressure criteria. In order to realize the efficient solution of the OGVCS model, an enhanced multi-objective bacterial-foraging chemotaxis gravitational search algorithm (EMOBCGSA) is proposed to solve this problem, which adopts population reconstruction, adaptive selection chemotaxis operator of local searching strategy and Elite archive set to efficiently solve the multi-objective problem. Especially, novel constraints-handling strategy with eliminating and local search based on violation ranking is used to balance various hydraulic and mechanical constraints. Finally, simulation cases of complex extreme operating conditions (i.e., load rejection and pump outage) of ‘single tube-double units’ type PSHU system are conducted to verify the feasibility and effectiveness of the proposed EMOBCGSA in solving OGVCS problem. The simulation results indicate that the proposed EMOBCGSA can provide lower rise rate of the unit rotational speed and smaller water hammer pressure than other method established recently while considering various complex constraints in OGVCS problem.
Preprint
|
|
|
Mathematics & Computer Science, General & Theoretical Computer Science; line extraction; morphological image processing; player tracking; sport videos
Online: 2 June 2017 (06:04:57 CEST)
|
|
Share this article with
×
Sports video analysis is an interesting and emerging field in the domain of computer vision. It has become a very popular subject among scholars all over the world in the last decade due to the need of automated classification of events such as offsides, in/out situations, goals and so on. The most important problem in sports video analysis is detection and tracking of ball and players. Extraction of court lines is also another important problem since it is necessary in the classification of aforementioned events. In this study, considering some of the previous work on the subject, we develop a method for tracking the ball and players in tennis videos where the camera position and orientation is supposed fixed.
Preprint
|
|
|
Mathematics & Computer Science, Information Technology & Data Management; probability; inference; information theory; Bayesian; generalized mean
Online: 1 June 2017 (05:49:21 CEST)
|
|
Share this article with
×
An approach to the assessment of probabilistic inference is described which quantifies the performance on the probability scale. From both information and Bayesian theory, the central tendency of an inference is proven to be the geometric mean of the probabilities reported for the actual outcome and is referred to as the “Accuracy.” Upper and lower error bars on the accuracy are provided by the arithmetic mean and the -2/3 mean. The arithmetic is called the “Decisiveness” due to its similarity with the cost of a decision and the -2/3 mean is called the “Robustness”, due to its sensitivity to outlier errors. Visualization of inference performance is facilitated by plotting the reported model probabilities versus the histogram calculated source probabilities. The visualization of the calibration between model and source is summarized on both axes by the arithmetic, geometric, and -2/3 means. From information theory, the performance of the inference is related to the cross-entropy between the model and source distribution. Just as cross-entropy is the sum of the entropy and the divergence; the accuracy of a model can be decomposed into a component due to the source uncertainty and the divergence between the source and model. Translated to the probability domain these quantities are plotted as the average model probability versus the average source probability. The divergence probability is the average model probability divided by the average source probability. When an inference is over/under-confident, the arithmetic mean of the model increases/decreases, while the -2/3 mean decreases/increases, respectively.
Preprint
|
|
|
Mathematics & Computer Science, Information Technology & Data Management; vehicle to vehicle communications; vehicle to infrastructure communications; network security; mobile ad-hoc networks
Online: 1 June 2017 (04:51:57 CEST)
|
|
Share this article with
×
Vehicle to vehicle (V2V) and Vehicle to infrastructure (V2I) or briefly V2X communications are the one of hot topics in automotive industry. Therefore, this situation is providing many advantages of connected vehicles and infrastructures which bring to human life. For instance, vehicles and road infrastructures which shares information with each other, provides a neat flow regulation, more ordered traffic flow and therefore jammed traffic dependent accident’s percentage will be decreased. On the other hand, security is the most important issue for these systems because the operation of V2X networks is completely dependent on uninterrupted and accurate information sharing. In the light of these information, in this paper we review security issues and current solution architectures. We also propose some open problems in this lively field.
Preprint
|
|
|
Mathematics & Computer Science, Analysis; extended Mittag–Leffler function; Wright-type hypergeometric functions; extended Wright-type hypergeometric functions
Online: 31 May 2017 (15:58:34 CEST)
|
|
Share this article with
×
The main aim of this paper is to establish two generalized integral formulas involving the extended Mittag–Leffler function based on the well known Lavoie and Trottier integral formula and the obtain results are express in term of extended Wright-type function. Also, we establish certain special cases of our main result.
Preprint
|
|
|
Mathematics & Computer Science, Information Technology & Data Management; digital forensic tool, mobile application forensics, geolocation, Upsight, Pokémon GO, Pokémon GO Plus
Online: 29 May 2017 (11:21:56 CEST)
|
|
Share this article with
×
As the geolocation capabilities of smartphones continue to improve, developers have continued to create more innovative applications that rely on this location information for their primary function. This can be seen with Niantic's release of Pokémon GO, which is a massively multiplayer online role playing and augmented reality game. This game became immensely popular within just a few days of its release. However, it also had the propensity to be a distraction to drivers resulting in numerous accidents, and was used to as a tool by armed robbers to lure unsuspecting users into secluded areas. This facilitates a need for forensic investigators to be able to analyze the data within the application in order to determine if it may have been involved in these incidents. Because this application is new, limited research has been conducted regarding the artifacts that can be recovered from the application. In this paper, we aim to fill the gaps within the current research by assessing what forensically relevant information may be recovered from the application, and understanding the circumstances behind the creation of this information. Our research focuses primarily on the artifacts generated by the Upsight analytics platform, those contained within the bundles directory, and the Pokémon Go Plus accessory. Moreover, we present our new application specific analysis tool that is capable of extracting forensic artifacts from a backup of the Android application, and presenting them to an investigator in an easily readable format. This analysis tool exceeds the capabilities of UFED Physical Analyzer in processing Pokémon GO application data.
Preprint
|
|
|
Mathematics & Computer Science, Other; mathematics; videogame; education; self-competency; randomized controlled trial
Online: 29 May 2017 (10:32:30 CEST)
|
|
Share this article with
×
Development of early math skills is linked to future success in mathematics and other academics. Educational videogames have been shown to promote academic achievement; however, few rigorous studies have evaluated the use of educational videogames in supporting math development, especially in early primary education. In the current study, an open-label randomized controlled trial was conducted involving 134 first grade students to determine, using standardized assessments, the impact of the educational mathematics tablet-based videogame, Knowledge Battle, on math scores and self-competency. Overall, Knowledge Battle did improve math skills in participants who played the game. Among those with lower pre-game math skills, the Knowledge Battle group’s mean math score increased more than the control group’s mean math score (9.7 vs. 6.0; p=0.02). There was no association between perceived sense of self-competency and total math score (p=0.8141). However, players who had a higher sense of self-competency were more likely to enjoy playing the game. In conclusion, our findings suggest that Knowledge Battle was an acceptable and enjoyable educational mathematical videogame for first grade students, and may be most impactful for those with low math skills.
Preprint
|
|
|
Mathematics & Computer Science, Applied Mathematics; Boiling Water Reactors; density wave oscillations; stability monitor; Shannon Entropy; noise-assisted Empirical Mode Decomposition variants; mode-mixing; Hilbert-Huang transform; instantaneous frequency
Online: 29 May 2017 (10:28:28 CEST)
|
|
Share this article with
×
There are currently around 78 Nuclear Power Plants (NPP) in the world based on Boiling Water Reactors (BWR). The current parameter to assess BWR instability issues is the linear Decay Ratio (DR). However, it is well known that BWRs are complex non-linear dynamical systems that may even exhibit chaotic dynamics that normally preclude the use of the DR when the BWR is working at a specific operating point during instability. In this work a novel methodology based on an adaptive Shannon Entropy estimator and on Noise Assisted Empirical Mode Decomposition variants is presented. This methodology was developed for real-time implementation of a stability monitor. This methodology was applied to a set of signals stemming from several NPPs reactors (Ringhals-Sweden, Forsmark-Sweden and Laguna Verde-Mexico) under commercial operating conditions, that experienced instabilities events, each one of a different nature
Preprint
|
|
|
Mathematics & Computer Science, General Mathematics; long-range dependence; Hurst effect; fractionallydifferenced models; Mandelbrot
Online: 26 May 2017 (18:36:50 CEST)
|
|
Share this article with
×
Long memory plays an important role in many fields by determining the behaviour and predictability of systems; for instance, climate, hydrology, finance, networks and DNA sequencing. In particular, it is important to test if a process is exhibiting long memory since that impacts the accuracy and confidence with which one may predict future events on the basis of a small amount of historical data. A major force in the development and study of long memory was the late Benoit B. Mandelbrot. Here we discuss the original motivation of the development of long memory and Mandelbrot's influence on this fascinating field. We will also elucidate the sometimes contrasting approaches to long memory in different scientific communities
Preprint
|
|
|
Mathematics & Computer Science, General & Theoretical Computer Science; wireless sensor network; object tracking; dual sink; data collection
Online: 26 May 2017 (04:58:00 CEST)
|
|
Share this article with
×
Continuous object tracking in WSNs, such as monitoring of mud-rock flows, forest fires etc., is a challenging task due to characteristic nature of continuous objects. They can appear randomly in the network field, move continuously, and can change in size and shape. Monitoring such objects in real-time generally require tremendous amount of messaging between sensor nodes to synergistically estimate object’s movement and track its location. In this paper, we propose a novel twofold-sink mechanism, comprising of a mobile and a static sink node. Both sink nodes gather information about boundary sensor nodes, which is then used to uniformly distribute energy consumption across all network nodes, thus helping in saving residual energy of network nodes. Numerous object tracking schemes, using mobile sink, have been proposed in the literature. However, existing schemes employing mobile sink cannot be applied to track continuous objects, because of momentous variation of network topology. Therefore, we present in this paper a mechanism, transformed from K-means algorithm, to find the best sensing location of the mobile sink node. It helps to reduce transmission load on the intermediate network nodes situated between static sink node and the ordinary network sensing nodes. The simulation results show that the proposed scheme can distinctly improve life time of the network, compared to one-sink protocol employed in continuous object tracking.
Preprint
|
|
|
Mathematics & Computer Science, Artificial Intelligence & Robotics; accuracy; depth data; RMS error; 3D vision sensors; stereo disparity
Online: 23 May 2017 (09:20:27 CEST)
|
|
Share this article with
×
We propose an approach for estimating the error in depth data provided by generic 3D sensors, which are modern devices capable of generating an image (RGB data) and a depth map (distance) or other similar 2.5D structure (e.g. stereo disparity) of the scene. Our approach starts capturing images of a checkerboard pattern devised for the method. Then proceed with the construction of a dense depth map using functions that generally comes with the device SDK (based on disparity or depth). The 2D processing of RGB data is performed next to find the checkerboard corners. Clouds of corner points are finally created (in 3D), over which an RMS error estimation is computed. We come up with a multi-platform system and its verification and evaluation has been done, using the development kit of the board nVIDIA Jetson TK1 with the MS Kinects v1/v2 and the Stereolabs ZED camera. So the main contribution is the error determination procedure that does not need any data set or benchmark, thus relying only on data acquired on-the-fly. With a simple checkerboard, our approach is able to determine the error for any device. Envisioned application is on 3D reconstruction for robotic vision, with a series of 3D vision sensors embarked in robots (UAV of type quadcopter and terrestrial robots) for high-precision map construction, which can be used for sensing and monitoring.
Preprint
|
|
|
Mathematics & Computer Science, Applied Mathematics; evolutionary stable strategies (ESS); Markov decision evolutionary games (MDEG); Hawk-Dove game; evolutionary dynamics; evolutionary game theory
Online: 18 May 2017 (03:34:39 CEST)
|
|
Share this article with
×
A new evolutionary game is introduced which incorporates states and actions into the strategies of the organisms of the evolving populations. The game centrally features actions that result in demographic flow between states that may not conserve organism numbers. It is by this feature that the game encapsulate a range of other evolutionary games, and can encode almost very complex interactions between organisms, species and populations. The game's formalism is expounded and the nature of the game's equilibrium is discussed. This discussion leads to an algorithm for numerically determining the stable equilibrium points which is exemplified in the context of a modified Hawk-Dove game. The game's flexibility for modeling population dynamics is evaluated and compared with other evolutionary games.
Preprint
|
|
|
Mathematics & Computer Science, General & Theoretical Computer Science; linear programming; optimization; quantum algorithms; complexity
Online: 17 May 2017 (06:22:36 CEST)
|
|
Share this article with
×
Quantum computers are machines that are designed to use quantum mechanics in order to improve upon classical computers by running quantum algorithms. One of the main applications of quantum computing is solving optimization problems. For addressing optimization problems, we can use linear programming. Linear programming is a method to obtain the best possible outcome in a special case of mathematical programming. Application areas of this problem consist of resource allocation, production scheduling, parameter estimation, etc. In our study, we look at quantum speedup ratios of HHL Algorithm for different scenarios of linear programming. In a first scenario we look quantum speedup ratio (S(N)) as a function of phase transition and the ratio (κ) between the greatest and smallest eigenvalues of the matrix in linear equation system. As a second scenario, we investigate the changes in S(N) as a function of κ and s, which is the coefficient for defining the matrix as s-sparse.
Preprint
|
|
|
Mathematics & Computer Science, General & Theoretical Computer Science; Mobile device threats; mobile device malware; reverse proxy server; cyber security; android security; ios security; abuse of local area network; DNS spoofing; DNS hijacking
Online: 16 May 2017 (13:23:18 CEST)
|
|
Share this article with
×
Mobile devices have become tools we spend our free time where we carry them with us every moment, they allow us to interact with the environment, we immortalize the moment when necessary. These devices which we spend most of our daily life become very common in recent years and even there are unique business areas emerged. It was announced that the number of people using smartphones is over than 2.5 billion in the first quarter of 2016. As people become more addicted to mobile technology, they become the target of malevolent people. A huge increase in the number of mobile malware is observed as the number of the users increase. Billions of users at risk day by day due to the development of the methods. We have addressed the recent methods used and the types of malware that target mobile devices in our study. We have mentioned the proxy server and reverse proxy server operation logic. We discuss the method of turning mobile devices into reverse proxy servers, risks involved and protection methods.
Preprint
|
|
|
Mathematics & Computer Science, General & Theoretical Computer Science; linear programming; optimization; quantum algorithms; complexity
Online: 16 May 2017 (12:31:40 CEST)
|
|
Share this article with
×
Quantum computers are machines that are designed to use quantum mechanics in order to improve upon classical computers by running quantum algorithms. One of the main applications of quantum computing is solving optimization problems. For addressing optimization problems we can use linear programming. Linear programming is a method to obtain the best possible outcome in a special case of mathematical programming. Application areas of this problem consist of resource allocation, production scheduling, parameter estimation, etc. In our study, we looked at the duality of resource allocation problems. First, we chose a real world optimization problem and looked at its solution with linear programming. Then, we restudied this problem with a quantum algorithm in order to understand whether if there is a speedup of the solution. The improvement in computation is analysed and some interesting results are reported.
Preprint
|
|
|
Mathematics & Computer Science, General & Theoretical Computer Science; quantum discord; entanglement; negativity; violation of Bell inequalities; decoherence
Online: 11 May 2017 (16:05:33 CEST)
|
|
Share this article with
×
Quantum Correlations are studied extensively in quantum information domain. Entanglement Measures and Quantum Discord are good examples of these actively studied correlations. Detection of violation in Bell inequalities is also a widely active area in quantum information theory world. In this work, we revisit the problem of analyzing the behavior of quantum correlations and violation of Bell inequalities in noisy channels. We extend the problem defined in a recent study by observing the changes in negativity measure, quantum discord and a modified version of Horodecki measure for violation of Bell inequalities under amplitude damping, phase damping and depolarizing channels. We report different interesting results for each of these correlations and measures. All these correlations and measures decrease under decoherence channels, but some changes are very dramatical comparing to others. We investigate also separability conditions of example studied states.
Preprint
|
|
|
Mathematics & Computer Science, Other; user authentication; multi server; internet of things; formal verification; security
Online: 9 May 2017 (04:38:37 CEST)
|
|
Share this article with
×
In recent years, the internet of things has been widely utilized in various fields, such as in smart factories or connected cars. As its domain of application has expanded, it has begun to be employed using multi-server architectures for a more efficient use of resources. However, because users wishing to receive IoT services connect to multi-servers over wireless networks, this can expose systems to various attacks and result in serious security risks. To protect systems (and users) from potential security vulnerabilities, a secure authentication technology is necessary. In this paper, we propose a smart card-based authentication protocol, which performs the authentication for each entity by allowing users to go through the authentication process using a smart card transmitted from an authentication server, and to login to a server connected to the IoT. Furthermore, the security of our proposed authentication protocol is verified by simulating a formal verification scenario using AVISPA, a security protocol-verification tool.
Preprint
|
|
|
Mathematics & Computer Science, Other; Android permissions; Android IoT platform; Android update; Android application
Online: 9 May 2017 (04:30:47 CEST)
|
|
Share this article with
×
The Android-based IoT platform just like the existing Android provides an environment that makes it easy to utilize Google's infrastructure services including development tools and APIs through which it helps to control the sensors of IoT devices. Applications running on the Android-based IoT platform are often UI free and are used without the user’s consent to registered permissions. It is difficult to respond to the misuse of permissions as well as to check them when they are registered indiscriminately while updating applications. This paper analyzes the versions of before and after an application the update running on the Android-based IoT platform and the collected permission lists. It aims to identify the same permissions before and after the update, and deleted and newly added permissions after the update were identified, and thereby respond to security threats that can arise from the permissions that is not needed for IoT devices to perform certain functions.
Preprint
|
|
|
Mathematics & Computer Science, Information Technology & Data Management; Bayesian reliability analysis; Bayesian hierarchical model; MCMC method; scale mixtures of log-normal failure time model; stochastic constraint; two-stage MaxEnt prior.
Online: 4 May 2017 (16:26:10 CEST)
|
|
Share this article with
×
This paper develops Bayesian inference in reliability of a class of scale mixtures of log-normal failure time (SMLNFT) models with stochastic (or uncertain) constraint in their reliability measures. The class is comprehensive and includes existing failure time (FT) models (such as log-normal, log-Cauchy, and log-logistic FT models) as well as new models that are robust in terms of heavy-tailed FT observations. Since classical frequency approaches to reliability analysis based on the SMLNFT model with stochastic constraint are intractable, the Bayesian method is pursued utilizing a Markov chain Monte Carlo (MCMC)
sampling based approach. This paper introduces a two-stage maximum entropy (MaxEnt) prior, which elicits a priori uncertain constraint and develops Bayesian hierarchical SMLNFT model by using the prior. The paper also proposes an MCMC method for Bayesian inference in the SMLNFT model reliability and calls attention to properties of the MaxEnt prior that are useful for method development. Finally, two data sets are used to illustrate how the proposed methodology works.
Preprint
|
|
|
Mathematics & Computer Science, Analysis; Lévy--Khintchine representation; integral representation; bivariate mean; bivariate complex geometric mean; reciprocal; Heronian mean; application
Online: 4 May 2017 (08:44:25 CEST)
|
|
Share this article with
×
In the paper, the authors survey integral representations (including the Lévy--Khintchine representations) and applications of some bivariate means (including the logarithmic mean, the identric mean, Stolarsky's mean, the harmonic mean, the (weighted) geometric means and their reciprocals, and the Toader--Qi mean) and the multivariate (weighted) geometric means and their reciprocals, derive integral representations of bivariate complex geometric mean and its reciprocal, and apply these newly-derived integral representations to establish integral representations of Heronian mean of power 2 and its reciprocal.
Preprint
|
|
|
Mathematics & Computer Science, Artificial Intelligence & Robotics; image segmentation; wireless sensor node deployment; plant growth simulation algorithm; disaster management
Online: 4 May 2017 (06:02:31 CEST)
|
|
Share this article with
×
The use of unmanned aerial vehicle (UAV) during emergency response of a disaster has been widespread in recent years and the terrain images captured by the cameras on board these vehicles are significant sources of information for such disaster monitoring operations. Thus, analyzing such images are important for assessing the terrain of interest during such emergency response operations. Further, these UAVs are mainly used in disaster monitoring systems for the automated deployment of sensor nodes in real time. Therefore, deploying and localizing the wireless sensor nodes optimally, only in the regions of interest that are identified by segmenting the images captured by UAVs, hold paramount significance thereby effecting their performance. In this paper, the highly effective nature-inspired Plant Growth Simulation Algorithm (PGSA) has been applied for the segmentation of such terrestrial images and also for the localization of the deployed sensor nodes. The problem is formulated as a multi-dimensional optimization problem and PGSA has been used to solve it. Furthermore, the proposed method has been compared to other existing evolutionary methods and simulation results show that PGSA gives better performance with respect to both speed and accuracy unlike other techniques in literature.
Preprint
|
|
|
Mathematics & Computer Science, Other; neutrosophic sets; neutrosophic logic; bézier curve
Online: 27 April 2017 (02:54:02 CEST)
|
|
Share this article with
×
In this paper, a geometric model is introduced for Neutrosophic data problem for the first time. This model is based on neutrosophic sets and neutrosophic relations. Neutrosophic control points are defined according to these points, resulting in neutrosophic Bézier curves.
Preprint
|
|
|
Mathematics & Computer Science, Information Technology & Data Management; Hierarchical search; Image retrieval; Multi-feature fusion
Online: 26 April 2017 (18:51:42 CEST)
|
|
Share this article with
×
Aiming at the problems that are poor generalization performance, low retrieval accuracy and large time consumption of existing content-based image retrieval system, the hierarchical image retrieval method based on multi feature fusion is proposed in this paper. The retrieval accuracy rates on Corel5K, UKbeach and Holidays are 68.23(Top 1), 3.73(N-S) and 88.20(mAp), respectively. The experimental results show that the method proposed in this paper can effectively improve the deficiency of single feature retrieval and save time significantly in the premise of a small amount of loss of accuracy.
Preprint
|
|
|
Mathematics & Computer Science, Artificial Intelligence & Robotics; AI Agents; emotive layer; judgement; behaviour; probability; decision-making; gameplay; backpropagation.
Online: 21 April 2017 (12:07:53 CEST)
|
|
Share this article with
×
AI is often looked at as a logical rational way to develop a games agent that methodically looks at options and delivers rational solutions. This paper is based on developing an AI agent that plays a game with a similar emotive content like a human. The purpose of the study was to see if the incorporation of this emotive content would influence the outcomes within the game Love Letter. In order to do this an AI agent with an emotive layer was developed to paly the game over a million times. A lower win/loss ratio demonstrates that to some extent this methodology was vindicated and a 100 per cent win for the AI agent did not happen. Machine learning techniques were modelled purposely so as to match extreme models of behavioural change. The results demonstrated a win/loss ration of 0.67 for the AI agent and in many ways reflectd the frustration that a normal player would exhibit during game play. As was hypothesised the final agent investment value was, on average, lower after matchplay than its initial value.
Preprint
|
|
|
Mathematics & Computer Science, General & Theoretical Computer Science; quantum information; entanglement; entaglement measures; entanglement monotones
Online: 21 April 2017 (08:47:32 CEST)
|
|
Share this article with
×
Quantum information theory and quantum computing are theoritical basis of quantum computers. Thanks to entanglement, quantum mechanical systems are provisioned to realize many information processing problems faster than classical counterparts. For example, Shor’s factorization algorithm, Grover’s search algorithm, quantum Fourrier transformation, etc. Entanglement, is the theoretical basis providing the expected speedups. It can be view in bipartite or multipartite forms. In order to quantify entanglement, some measures are defined. On the other hand, a general and accepted criterion, which can measure the amount of entanglement of multilateral systems, has not yet been found. In this work, we make a short review of recent research on the topic entanglement monotones and measures with an analitical approach.
Preprint
|
|
|
Mathematics & Computer Science, General & Theoretical Computer Science; quantum metrology; quantum fisher ınformation; decoherence; optimization
Online: 21 April 2017 (06:17:36 CEST)
|
|
Share this article with
×
Entanglement is at the heart of quantum technologies such as quantum information and quantum metrology. Providing larger quantum Fisher information (QFI), entangled systems can be better resources than separable systems in quantum metrology. QFI topic is a very active research area and it has many possible usage areas in quantum information domain. In this study, we review quantum Fisher information research with both from theoritical and application perspective.
Preprint
|
|
|
Mathematics & Computer Science, Artificial Intelligence & Robotics; HTN planning; real-time strategy game; plan repair
Online: 19 April 2017 (04:41:22 CEST)
|
|
Share this article with
×
Real-time strategy (RTS) game has proposed many challenges for AI research for its large state spaces, enormous branch factors, limited decision time and dynamic adversarial environment. To tackle above problems, the method called Adversarial Hierarchical Task Network planning (AHTN) has been proposed and achieves favorable performance. However, the HTN description it used cannot express complex relationships among tasks and impacts of environment on tasks. Moreover, the AHTN cannot handle task failures during plan execution. In this paper, we propose a modified AHTN planning algorithm named AHTNR. The algorithm introduces three elements essential task, phase and exit condition to extend the HTN description. To deal with possible task failures, the AHTNR first uses the extended HTN description to identify failed tasks. And then a novel task repair strategy is proposed based on historical information to maintain the validity of previous plan. Finally, empirical results are presented for the μRTS game, comparing AHTNR to the state-of-the-art search algorithms for RTS games.
Preprint
|
|
|
Mathematics & Computer Science, Information Technology & Data Management; Body sensor network; Smart home, knowledge discovery in BSN data; frequent patterns; periodic patterns and productive pattern.
Online: 18 April 2017 (18:15:50 CEST)
|
|
Share this article with
×
The understanding of various health-oriented vital sign data generated from body sensor networks (BSN) and discovery of the association between the generated parameters is an important task that may assist and promote important decision making in healthcare. For example, in a smart home scenario where the occupants’ health status is continuously monitored remotely, it is essential to provide required assistance when an unusual or critical situation is detected in their vital sign data. In this paper, we present an efficient approach to mine the incomplete (partial) periodic patterns obtained from BSN data. In addition, we employ a correlation test on the generated patterns and introduce the productive-associated partial periodic frequent patterns as the set of correlated partial periodical frequent items. The combination of these measures has the advantage of empowering healthcare providers and patients for quality of diagnosis, and also for better treatment and smart care, especially for the elderly people at smart home. We developed an efficient algorithm named PPFP-Growth (Productive Periodic Frequent Pattern growth) to discover all productive associated partial periodic patterns using these measures. PPFP-Growth is efficient, and the productiveness measure removes uncorrelated periodic items. An experimental evaluation on synthetic and real datasets shows the efficiency of the proposed PPFP-Growth algorithm, and can filter a huge number of partial periodic patterns to reveal only the correlated ones.
Preprint
|
|
|
Mathematics & Computer Science, Other; symmetric nonnegative matrix factorization; similarity network fusion; human microbiome; multi-view clustering
Online: 18 April 2017 (03:31:04 CEST)
|
|
Share this article with
×
Integration of multi-view datasets which are comprised of heterogeneous sources or different representations is challenging to understand the subtle and complex relationship in data. Such data integration methods attempt to combine efficiently the complementary information of multiple data types to construct a comprehensive view of underlying data. Nonnegative matrix factorization (NMF), an approach that can be used for signal compression and noise reduction, has aroused widespread attention in the last two decades. The Kullback–Leibler divergence (or relative entropy) information distance can be used to measure the loss function of NMF. In this article, we propose a fast and robust framework (RSNMF) based on symmetric nonnegative matrix factorization (SNMF) and similarity network fusion (SNF) for clustering human microbiome data including functional, metabolic and phylogenetic profiles. Many existing methods typically utilize all the information provided by each view to create a consensus representation, which often suffers a lot from noise in data and cannot provide a precise representation of the latent data structures. In contrast, RSNMF combines the strength of SNMF and the advantage of SNF to form a robust clustering indicator matrix thus can reduce the noise influence. We conduct experiments on one synthetic and two real dataset (microbiome data, text data) and the results show that the proposed RSNMF has better performance over the baseline and the state-of-art methods, which demonstrates the potential application of RSNMF for microbiome data analysis.
Preprint
|
|
|
Mathematics & Computer Science, General & Theoretical Computer Science; clustering algorithm; k-prototypes algorithm, partial distance computation
Online: 17 April 2017 (11:08:26 CEST)
|
|
Share this article with
×
The k-means is one of the most popular and widely used clustering algorithm, however, it is limited to only numeric data. The k-prototypes algorithm is one of the famous algorithms for dealing with both numeric and categorical data. However, there have been no studies to accelerate k-prototypes algorithm. In this paper, we propose a new fast k-prototypes algorithm that gives the same answer as original k-prototypes. The proposed algorithm avoids distance computations using partial distance computation. Our k-prototypes algorithm finds minimum distance without distance computations of all attributes between an object and a cluster center, which allows it to reduce time complexity. A partial distance computation uses a fact that a value of the maximum difference between two categorical attributes is 1 during distance computations. If data objects have m categorical attributes, maximum difference of categorical attributes between an object and a cluster center is m. Our algorithm first computes distance with only numeric attributes. If a difference of the minimum distance and the second smallest with numeric attributes is higher than m, we can find minimum distance between an object and a cluster center without distance computations of categorical attributes. The experimental shows proposed k-prototypes algorithm improves computational performance than original k-prototypes algorithm in our dataset.
Preprint
|
|
|
Mathematics & Computer Science, Artificial Intelligence & Robotics; Dynamic vehicle routing problem, Harmony Search Algorithm, Variable Neighbourhood Search
Online: 17 April 2017 (05:41:00 CEST)
|
|
Share this article with
×
The Vehicle Routing Problem (VRP) is a classical combinatorial optimization problem. It is usually modelled in a static fashion; however, in practice, new requests by customers arrive after the initial workday plan is in progress. In this case, routes must be re-planned dynamically. This paper investigates the Dynamic Vehicle Routing Problem with Time Windows (DVRPTW) in which customers’ requests can be either known at the beginning of working day or occur dynamically over time. We propose a hybrid heuristic algorithm that combines the Harmony Search (HS) algorithm and the Variable Neighborhood Descent (VND) algorithm. It uses the HS to provide global exploration capabilities and uses the VND for its local search capability. In order to prevent premature convergence of the solution, we evaluate the population diversity by using entropy. Computational results on the Lackner benchmark problems show that the proposed algorithm is competitive with the best existing algorithms from the literature.
Preprint
|
|
|
Mathematics & Computer Science, Information Technology & Data Management; inter-subjective objectivity; complexity measure; computational complexity; criticality; citizen science; open complex system;
Online: 14 April 2017 (10:51:07 CEST)
|
|
Share this article with
×
Recently emerging data-driven citizen sciences need to harness increasing amount of massive data with varying quality. This paper develops essential theoretical frameworks and example models and examine its computational complexity for interactive data-driven citizen science within the context of guided self-organization. We first define a conceptual model that incorporates quality of observation in terms of accuracy and reproducibility, ranging between subjectivity, inter-subjectivity, and objectivity. Next, we examine the database's algebraic and topological structure in relation to informational complexity measures, and evaluate its computational complexities with respect to exhaustive optimization. Conjectures of criticality are obtained on self-organizing processes of observation and dynamical model development. Example analysis is demonstrated with the use of biodiversity assessment database, the process that inevitably involves human subjectivity for the management in open complex systems.
Preprint
|
|
|
Mathematics & Computer Science, Information Technology & Data Management; privacy; anonymity risk; dynamic user profile, online footprints
Online: 13 April 2017 (04:46:21 CEST)
|
|
Share this article with
×
Websites and applications use personalisation services to profile their users, collect their patterns and activities and eventually use this data to provide tailored suggestions. User preferences and social interactions are therefore aggregated and analysed. Every time a user publishes a new post or creates a link with another entity, either another user, or some on-line resource, new information is added to the user profile. Exposing private data does not only reveal information about single users' preferences, increasing their privacy risk, but can expose more about their network that single actors intended. This mechanism is self-evident on \emph{social networks} where users receive suggestions based on their friends' activity. We propose an information theoretic approach to measure the differential update of the anonymity risk for time-varying user profiles. This expresses how privacy is affected when new content is posted and how much third party services get to know about the users when a new activity is shared. We use real Facebook data to show how our model can be applied on a real world scenario.
Preprint
|
|
|
Mathematics & Computer Science, Numerical Analysis & Optimization; observed information; fisher information; averaged information splitting; approximate information
Online: 7 April 2017 (12:21:27 CEST)
|
|
Share this article with
×
Linear mixed models are frequently used for analysing heterogeneous data in a broad range of applications. The restricted maximum likelihood method is often preferred to estimate co-variance parameters in such models due to its unbiased estimation of the underlying variance parameters. The restricted log-likelihood function involves log determinants of a complicated co-variance matrix. An efficient statistical estimate of the underlying model parameters and quantifying the accuracy of the estimation requires the first derivatives and the second derivatives of the restricted log-likelihood function, i.e., the observed information. Standard approaches to compute the observed information and its expectation, the Fisher information, is computationally prohibitive for linear mixed models with thousands random and fixed effects. Customized algorithms are of highly demand to keep mixed models analysis scalable for increasing high-throughput heterogeneous data sets. In this paper, we explore how to leverage an averaged information splitting technique and dedicate matrix transform to significantly reduce computations and to accelerate computing. Together with a fill-in reducing multi-frontal sparse direct solver, the averaged information splitting approach improves the performance of the computation process.
Preprint
|
|
|
Mathematics & Computer Science, Analysis; Catalan number; integral representation; equivalent relation; application; sum of power series; Catalan--Qi function; Catalan--Qi number; beta function
Online: 7 April 2017 (04:27:13 CEST)
|
|
Share this article with
×
In the paper, the authors survey integral representations of the Catalan numbers and the Catalan–Qi function, discuss equivalent relations between these integral representations, supply alternative and new proofs of several integral representations, collect applications of some integral representations, and present sums of several power series whose coefficients involve the Catalan numbers.
Preprint
|
|
|
Mathematics & Computer Science, Artificial Intelligence & Robotics; Automatic localization; human visual mechanism; superpixel contrast feature; ultrasound breast tumor.
Online: 5 April 2017 (15:50:40 CEST)
|
|
Share this article with
×
Human visual system (HVM) can quickly localize the most salient object in scenes, which has been widely applied on natural image segmentation [15]-[19]. In ultrasound (US) breast images, compared with background areas, tumor is more salient because of its higher contrast. In this paper, we develop a novel automatic localization method based on HVM for automatic segmentation of ultrasound (US) breast tumors.
First, the input image is smoothed by convolution with a linearly separable Gaussian filter and then subsampled into a 9-layer Gaussian pyramid. Then intensity, blackness ratio, and superpixel contrast features are combined to compute saliency map, in which Winner Take All algorithm is used to localize the most salient region, presenting with a circle on the localized target. Finally the circle is taken as the initial contour of CV level set to finish the extraction of breast tumor.
The localization method has been tested on 400 US beast images, among which 378 images have higher saliency than background areas and succeed in localization, with high accuracy 92.00%. The HVM localization method can be used to localize the tumors, combined with this method, CV level set can achieve the fully automatic segmentation of US breast tumors.
By combing intensity, blackness ratio and superpixel contrast features, the proposed localization method can successfully avoid the interference caused by background areas with low echo and high intensity. Moreover, multi-object localization of US breast images can be considered in future employment.
Preprint
|
|
|
Mathematics & Computer Science, Analysis; simple form; explicit form; differential equation; Lerch transcendent; logarithmic function
Online: 4 April 2017 (16:53:18 CEST)
|
|
Share this article with
×
In the note, the authors find several simple and explicit forms for a family of inhomogeneous linear ordinary differential equations studied in "D. Lim, Differential equations for Daehee polynomials and their applications, J. Nonlinear Sci. Appl. 10 (2017), no. 4, 1303-1315; Available online at http://dx.doi.org/10.22436/jnsa.010.04.02".
Preprint
|
|
|
Mathematics & Computer Science, General & Theoretical Computer Science; entanglement; relative entropy of entanglement; negativity; bell inequalities violation; quantum fisher information; optimization
Online: 31 March 2017 (08:14:32 CEST)
|
|
Share this article with
×
The violation of Bell's theorem is a very simple way to see that there is no underlying classical interpretation of quantum mechanics. The measurements made on the photons shows that light signal (information) could travel between them, hence completely eliminating any chance that the result was due to anything other than entanglement. Entanglement has been studied extensively for understanding the mysteries of non-classical correlations between quantum systems. It was found that violation of Bell's inequalities could be trivially calculated and for sets of nonmaximally entangled states of two qubits, comparing these entanglement measures may lead to different entanglement orderings of the states. On the other hand, although it is not an entanglement measure and not monotonic under local operations, due to its ability of detecting multipartite entanglement, quantum Fisher information (QFI) has recently received an intense attraction generally with entanglement in the focus. In this work, we visit violation of Bell's inequalities problem with a different approach. Generating a thousand random quantum states and performing an optimization based on local general rotations of each qubit, we calculate the maximal QFI for each state. We analyze the maximized QFI in comparison with violation in Bell's inequalities and we make similar comparison of this violation with commonly studied entanglement measures, negativity and relative entropy of entanglement. We show that there are interesting orderings for system states.
Preprint
|
|
|
Mathematics & Computer Science, General & Theoretical Computer Science; entanglement; qubit; qutrit; concurrence; negativity; relative entropy of entanglement
Online: 30 March 2017 (11:47:17 CEST)
|
|
Share this article with
×
Quantum Computers are provisioned as very high performance computers using quantum mechanical aspects for information processing. Quantum Information Theory and Quantum Computing topics are popular topics in academia aiming the construction of theoretical background of Quantum Computers. The information processing units for Quantum Computers are defined as qubits but for some problems three level (trinary) systems may be applied as well. We call these three level systems as qutrits. The scope of this work is the analysis of well-defined entanglement measures Negativity and Relative Entropy of Entanglement (REE) for two qutrit (3- level/trinary) quantum systems. In this manner, for randomly generated 1000 two qutrit and 1000 two qubit states the mentioned measures are calculated and these values are compared. These comparisons are analyzed and for quantum state ordering problem, some interesting results are reported.
Preprint
|
|
|
Mathematics & Computer Science, Algebra & Number Theory; closed expression; Fibonacci number; Fibonacci polynomial; tridiagonal determinant; Hessenberg determinant
Online: 28 March 2017 (03:11:06 CEST)
|
|
Share this article with
×
In the paper, the authors nd a new closed expression for the Fibonacci polynomials and, consequently, for the Fibonacci numbers, in terms of a tridiagonal determinant.
Preprint
|
|
|
Mathematics & Computer Science, Algebra & Number Theory; explicit formula; recursive formula; generalized Motzkin number; Motzkin number; restricted hexagonal number; Catalan number; generating function
Online: 27 March 2017 (11:02:41 CEST)
|
|
Share this article with
×
In the paper, the authors find two explicit formulas and recover a recursive formula for the generalized Motzkin numbers. Consequently, the authors deduce two explicit formulas and a recursive formula for the Motzkin numbers, the Catalan numbers, and the restricted hexagonal numbers respectively.
Preprint
|
|
|
Mathematics & Computer Science, Analysis; nonlinear ordinary differential equation; Stirling number of the first kind; simplifying; technique; combinatorial analysis
Online: 24 March 2017 (18:30:21 CET)
|
|
Share this article with
×
In the paper, by virtue of techniques in combinatorial analysis, the authors simplify two families of nonlinear ordinary differential equations in terms of the Stirling numbers of the first kind.
Preprint
|
|
|
Mathematics & Computer Science, Information Technology & Data Management; High-dimensional data analysis, Multiple hypothesis testing, False discovery rate, Optimum significance threshold, Maximum for reasonable number of rejected hypotheses, Big data analysis
Online: 24 March 2017 (18:29:35 CET)
|
|
Share this article with
×
This paper identifies a criterion for choosing the largest set of rejected hypotheses in high-dimensional data analysis where Multiple Hypothesis testing is used in exploratory research to identify significant associations among many variables. The method neither requires predetermined thresholds for level of significance, nor uses presumed thresholds for false discovery rate. The upper limit for number of rejected hypotheses is determined by finding maximum difference between expected true hypotheses and false hypotheses among all possible sets of rejected hypotheses. Methods of choosing a reasonable number of rejected hypotheses and application to non-parametric analysis of ordinal survey data are presented.
Preprint
|
|
|
Mathematics & Computer Science, General Mathematics; Riemann Hypothesis; Dirichlet eta function; Zeta function; prime numbers; number theory; critical-line; critical-strip; symmetry breaking
Online: 22 March 2017 (04:48:57 CET)
|
|
Share this article with
×
Euler’s product formula over the primes and Euler’s zeta function equate to enshrine the Fundamental Theorem of Arithmetic that every integer > 1 is the product of a unique set of primes. The product formula has no zero, and with a domain ≤1 Euler’s zeta diverges. Dirichlet’s eta function η(s), negates alternate terms of zeta, permitting convergence when s∈C and Re(s) < 1, and its non-trivial zeros {ρ}, have a deep relationship with the distribution of the primes. The Riemann Hypothesis is that all the non-trivial zeros have Re(ρ) = 1/2. This work examines the symmetries in a partial Euler’s zeta series with a complex domain equating it to the difference between two finite vector series whose matched terms have mirror-image arguments, but whose magnitudes differ when Re(s) ≠ 1/2. Analytical continuation generates a modified eta series ηl(s), in which every lth term is multiplied by (1-l). If the integer l is appropriately determined by the Im(s), similar paired finite vector series have a difference that closely follows ηl (s) and their terminal vectors intersect in a unique way permitting zeros only when Re(s) = 1/2. Furthermore, those vectors tracking the derivatives of the series, have a special relationship permitting zeros of the differential only when Re(s) > 1/2.
Preprint
|
|
|
Mathematics & Computer Science, Other; identity over time; Bayesian networks; multi-information; entity; persistence; integration; emergence; naturalising agency
Online: 21 March 2017 (16:23:00 CET)
|
|
Share this article with
×
We present a first formal analysis of specific and complete local integration. Complete local integration was previously proposed as a criterion for detecting entities or wholes in distributed dynamical systems. Such entities in turn were conceived to form the basis of a theory of emergence of agents within dynamical systems. Here, we give a more thorough account of the underlying formal measures. The main contribution is the disintegration theorem which reveals a special role of completely locally integrated patterns (what we call ι-entities) within the trajectories they occur in. Apart from proving this theorem we introduce the disintegration hierarchy and its refinement-free version as a way to structure the patterns in a trajectory. Furthermore we construct the least upper bound and provide a candidate for the greatest lower bound of specific local integration. Finally, we calculate the i-entities in small example systems as a first sanity check and find that ι-entities largely fulfil simple expectations.
Preprint
|
|
|
Mathematics & Computer Science, General & Theoretical Computer Science; object detection; background subtraction; video surveillance; Kinect sensor fusion
Online: 20 March 2017 (10:21:40 CET)
|
|
|
Share this article with
×
Depth-sensing technology has led to broad applications of inexpensive depth cameras that can capture human motion and scenes in 3D space. Background subtraction algorithms can be improved by fusing color and depth cues, thereby allowing many issues encountered in classical color segmentation to be solved. In this paper, we propose a new fusion method that combines depth and color information for foreground segmentation based on an advanced color-based algorithm. First, a background model and a depth model are developed. Then, based on these models, we propose a new updating strategy that can eliminate ghosting and black shadows almost completely. Extensive experiments have been performed to compare the proposed algorithm with other, conventional RGB-D algorithms. The experimental results suggest that our method extracts foregrounds with higher effectiveness and efficiency.
Preprint
|
|
|
Mathematics & Computer Science, Information Technology & Data Management; deep convolutional neural networks; identification; semi-verification; multi-scale features; face verification
Online: 20 March 2017 (09:06:18 CET)
|
|
Share this article with
×
Face verification for unrestricted faces in the wild is a challenging task. This paper proposes a method based on two deep convolutional neural networks(CNN) for face verification. In this work, we explore to use identification signal to supervise one CNN and the combination of semi-verification and identification to train the other one. In order to estimate semi-verification loss at a low computation cost, a circle, which is composed of all faces, is used for selecting face pairs from pairwise samples. In the process of face normalization, we propose to use different landmarks of faces to solve the problems caused by poses. And the final face representation is formed by the concatenating feature of each deep CNN after PCA reduction. What's more, each feature is a combination of multi-scale representations through making use of auxiliary classifiers. For the final verification, we only adopt the face representation of one region and one resolution of a face jointing Joint Bayesian classifier. Experiments show that our method can extract effective face representation with a small training dataset and our algorithm achieves 99.71% verification accuracy on LFW dataset.
Preprint
|
|
|
Mathematics & Computer Science, Applied Mathematics; Unsteady 3-D axisymmetric nanofluid; Entropy generation; Spectral quasi-linearization method.
Online: 17 March 2017 (15:10:32 CET)
|
|
Share this article with
×
We investigate entropy generation in unsteady three-dimensional axisymmetric MHD nanofluid flow over a non-linearly stretching sheet. The flow is subject to thermal radiation and a chemical reaction. The conservation equations were solved using the spectral quasi-linearization method. The novelty of the work is in the study of entropy generation in three-dimensional axisymmetric MHD nanofluid and the choice of the spectral quasilinearization method as the solution method. The effects of Brownian motion and thermophoresis are also taken into account when the nanofluid particle volume fraction on the boundary in passively controlled. The results show that as the Hartman number increases, both the Nusselt number and the Sherwood number decrease whereas the skin friction increases. It is further shown that an increase in the thermal radiation parameter corresponds to a decrease in the Nusselt number. Moreover, entropy generation increases with the physical parameters.
Preprint
|
|
|
Mathematics & Computer Science, General & Theoretical Computer Science; Refinement; operators; theories; self-recovering; NoC; Event-B; VHDL
Online: 16 March 2017 (11:41:58 CET)
|
|
|
Share this article with
×
The need for high performance, available and reliable embedded systems has made computing systems increasingly complex. Formal methods have the ability to produce critical systems for large industrial projects, and this by creating an original mathematical model that can be formally refined in levels until the final refinement which contains enough of details for an implementation. This work is a first step of VHDL code generation process, it represents how to elaborate formally an embedded system using Abstract data type in a form of theories (NoC, WNoC, colored graph, VHDL) and how to ensure in systematic way all the details and complexity of this system using operators of refinement (Create, Rename, Restrict, Enrich)that are recently proposed for the Event-B method. All the theories are deployed, discharged and used in Event-B models to represent and enhance the performance of this self-organization reliability solution for the wireless sensors network of NoC-based system. This paper summerize the fruit of using new proposed approach for the Event-B formal method that persist the NoC-based ditributed system instead of consuming more than 70% of realization time with any analytic method.
Preprint
|
|
|
Mathematics & Computer Science, Analysis; Lévy–Khintchine representation; integral representation; Bernstein function; Stieltjes function; Toader–Qi mean; weighted geometric mean; Bessel function of the first kind; probabilistic interpretation; probabilistic interpretation; application in engineering; inequality
Online: 16 March 2017 (11:31:31 CET)
|
|
Share this article with
×
In the paper, by virtue of a Lévy–Khintchine representation and an alternative integral representation for the weighted geometric mean, the authors establish a Lévy–Khintchine representation and an alternative integral representation for the Toader–Qi mean. Moreover, the authors also collect an probabilistic interpretation and applications in engineering of the Toader–Qi mean.
Preprint
|
|
|
Mathematics & Computer Science, Algebra & Number Theory; homomorphism; Grassmannian; generalized geometry; cathelineau's complex
Online: 15 March 2017 (08:04:30 CET)
|
|
Share this article with
×
In this article, a generalization of the geometry of Grassmannian chain complex of free abelian groups generated by the projective configuration of points and Cathelineau's infinitesimal complex of polylogarithmic groups is proposed. Firstly, homomorphisms for weight n =2 up to weight n=6 will be introduced to connect sub-complexes of Grassmannian and Cathelineau. Lately, generalization of these morphisms will be shown for weight n=N. The associated diagrams will also be proven to be commutative and bi-complex.
Preprint
|
|
|
Mathematics & Computer Science, Analysis; blow-up; semilinear pseudo-parabolic equations; critical initial energy; conical degeneration
Online: 13 March 2017 (09:56:13 CET)
|
|
Share this article with
×
In this paper, we study the semilinear pseudo-parabolic equations $\displaystyle u_{t} - \triangle_{\mathbb{B}}u - \triangle_{\mathbb{B}}u_{t} = \left|u\right|^{p-1}u$ on a manifold with conical singularity, where $\triangle _{\mathbb{B}}$ is Fuchsian type Laplace operator investigated with totally characteristic degeneracy on the boundary $x_{1} = 0$. Firstly, we discuss the invariant sets and the vacuum isolating behavior of solutions with the help of a family of potential wells. Then, we derive a threshold result of existence and nonexistence of global weak solution: for the low initial energy $J(u_{0})<d$, the solution is global in time with $I(u_{0}) >0$ or $\displaystyle\Vert \nabla_{\mathbb{B}}u_{0}\Vert_{L_{2}^{\frac{n}{2}}(\mathbb{B})} = 0$ and blows up in finite time with $I(u_{0}) < 0$; for the critical initial energy $J(u_{0}) = d$, the solution is global in time with $I(u_{0}) \geq0$ and blows up in finite time with $I(u_{0}) < 0$. The decay estimate of the energy functional for the global solution and the estimates of the lifespan of local solution are also given.
Preprint
|
|
|
Mathematics & Computer Science, Other; Smartphone sensing; mobile-social integration; automatic recognition; social data; long-term health monitoring
Online: 10 March 2017 (17:32:31 CET)
|
|
Share this article with
×
Over the past decades, overweight and obesity has become a global epidemic and the leading threat for death. To prevent the serious risk, an overweight or obese individual must apply a long-term weight-management strategy to control food intake and physical activities, which is however, not easy. Recently, with the advances of information technology, more and more people can use wearable devices and smartphones to obtain physical activity information, while they can also access various health-related information from Internet online social networks (OSNs). Nevertheless, there is a lack of an integrated approach that can combine these two methods in an efficient way. In this paper, we address this issue and propose a novel mobile-social framework for health recognition and recommendation, namely, H-Rec2. The main ideas of H-Rec2 include (1) to recognize the individual's health status using smartphone as a general platform, and (2) to recommend physical activity and food intake based on personal health information, life science principles, and health-related information obtained from OSNs. To demonstrate the potentials of the H-Rec2 framework, we develop a prototype that consists of four important components: (1) an activity recognition module that senses physical activity using accelerometer, (2) a health status modeling module that applies a novel algorithm to generate personalized health status index, (3) a restaurant information collection module that collects relevant information from OSN, and (4) a restaurant recommendation module that provides personalized and context-aware recommendation. To evaluate the prototype, we conduct both objective and subjective experiments, which confirm the performance and effectiveness of the proposed system.
Preprint
|
|
|
Mathematics & Computer Science, Analysis; closed form; Stirling polynomial; Stirling number; Bernoulli number; Faá di Bruno's formula; Bell polynomial
Online: 10 March 2017 (10:28:19 CET)
|
|
Share this article with
×
In the paper, by virtue of the Faá di Bruno formula and two identities for the Bell polynomial of the second kind, the authors find a closed form for the Stirling polynomials in terms of the Stirling numbers of the first and second kinds.
Preprint
|
|
|
Mathematics & Computer Science, Analysis; series identity; Catalan number; Catalan function; Riemanian zeta function; alternative Hurwitz zeta function; digamma function
Online: 6 March 2017 (07:01:20 CET)
|
|
Share this article with
×
In the paper, the authors discover several series identities involving the Catalan numbers, the Catalan function, the Riemanian zeta function, and the alternative Hurwitz zeta function.
Preprint
|
|
|
Mathematics & Computer Science, Information Technology & Data Management; GPS trajectory; GPS sensor; trajectory similarity measure; spatial-temporal data
Online: 6 March 2017 (06:51:37 CET)
|
|
Share this article with
×
With the rapid spread of built-in GPS handheld smart devices, the trajectory data from GPS sensors has grown explosively. Trajectory data has spatio-temporal characteristics and rich information. Using trajectory data processing techniques can mine the patterns of human activities and the moving patterns of vehicles in the intelligent transportation systems. A trajectory similarity measure is one of the most important issues in trajectory data mining (clustering, classification, frequent pattern mining, etc.). Unfortunately, the main similarity measure algorithms with the trajectory data have been found to be inaccurate, highly sensitive of sampling methods, and have low robustness for the noise data. To solve the above problems, three distances and their corresponding computation methods are proposed in this paper. The point-segment distance can decrease the sensitivity of the point sampling methods. The prediction distance optimizes the temporal distance with the features of trajectory data. The segment-segment distance introduces the trajectory shape factor into the similarity measurement to improve the accuracy. The three kinds of distance are integrated with the traditional dynamic time warping algorithm (DTW) algorithm to propose a new segment–based dynamic time warping algorithm (SDTW). The experimental results show that the SDTW algorithm can exhibit about 57%, 86%, and 31% better accuracy than the longest common subsequence algorithm (LCSS), and edit distance on real sequence algorithm (EDR) , and DTW, respectively, and that the sensitivity to the noise data is lower than that those algorithms.
Preprint
|
|
|
Mathematics & Computer Science, Applied Mathematics; Solvency II; Standard Formula; Risk Measure; Diversification; Aggregation; Monotony; Homogeneity; Subadditivity; Euler's Principle; Capital Allocation
Online: 1 March 2017 (08:53:59 CET)
|
|
Share this article with
×
The core of risk aggregation in the Solvency II Standard Formula is the so-called square root formula. We argue that it should be seen as a means for the aggregation of different risks to an overall risk rather than being associated with variance-covariance based risk analysis. Considering the Solvency II Standard Formula from the viewpoint of linear geometry, we immediately find that it defines a norm and therefore provides a homogeneous and sub-additive tool for risk aggregation. Hence Euler's Principle for the reallocation of risk capital applies and yields explicit formulas for capital allocation in the framework given by the Solvency II Standard Formula. This gives rise to the definition of diversification functions, which we define as monotone, subadditive, and homogeneous functions on a convex cone. Diversification functions constitute a class of models for the study of the aggregation of risk, and diversification. The aggregation of risk measures using a diversification function preserves the respective properties of these risk measures. Examples of diversification functions are given by seminorms, which are monotone on the convex cone of non-negative vectors. Each Lp norm has this property, and any scalar product given by a non-negative positive semidefinite matrix does as well. In particular, the Standard Formula is a diversification function and hence a risk measure that preserves homogeneity, subadditivity, and convexity.
Preprint
|
|
|
Mathematics & Computer Science, Other; robust diffusion estimation; self-adjusting step-size; non-Gaussian noise; wireless sensor networks
Online: 28 February 2017 (12:38:25 CET)
|
|
Share this article with
×
In wireless sensor networks (WSNs), each sensor node can estimate the global parameter from the local data in distributed manner. This paper proposed a robust diffusion estimation algorithm based on minimum error entropy criterion with self-adjusting step-size, which are referred to as diffusion MEE-SAS (DMEE-SAS) algorithm. The DMEE-SAS algorithm has fast speed of convergence and is robust against non-Gaussian noise in the measurements. The detailed performance analysis of the DMEE-SAS algorithm is performed. By combining the DMEE-SAS with diffusion minimum error entropy (DMEE) algorithms, an Improving DMEE-SAS algorithm is proposed, in non-stationary environment where tracking is very important. The Improving DMEE-SAS algorithm can avoid insensitivity of the DMEE-SAS algorithm due to the small effective step-size near the optimal estimator, and obtain a fast convergence speed. Numerical simulations are given to verify the effectiveness and advantages of these proposed algorithms.
Preprint
|
|
|
Mathematics & Computer Science, Artificial Intelligence & Robotics; self-organization; downward causation; autocatalytic set; goal-oriented behaviour; autopoiesis; biological computing
Online: 28 February 2017 (12:08:07 CET)
|
|
Share this article with
×
Using insights from cybernetics and an information-based understanding of biological systems, a precise, scientifically inspired, definition of free-will is offered and the essential requirements for an agent to possess it in principle are set out. These are: a) there must be a self to self-determine; b) there must be a non-zero probability of more than one option being enacted; c) there must be an internal means of choosing among options (which is not merely random, since randomness is not a choice). For (a) to be fulfilled, the agent of self-determination must be organisationally closed (a `Kantian whole'). For (c) to be fulfilled: d) options must be generated from an internal model of the self which can calculate future states contingent on possible responses; e) choosing among these options requires their evaluation using an internally generated goal defined on an objective function representing the overall `master function' of the agent and f) for `deep free-will', at least two nested levels of choice and goal (d-e) must be enacted by the agent. The agent must also be able to enact its choice in physical reality. The only systems known to meet all these criteria are living organisms, not just humans, but a wide range of organisms. The main impediment to free-will in present-day artificial robots, is their lack of being a Kantian whole. Consciousness does not seem to be a requirement and the minimum complexity for a free-will system may be quite low and include relatively simple life-forms that are at least able to learn.
Preprint
|
|
|
Mathematics & Computer Science, Analysis; suspension bridges; fourth order wave equation; nonlinear damping; source term; existence; blow up
Online: 24 February 2017 (09:06:57 CET)
|
|
Share this article with
×
In this paper, we consider a fourth-order suspension bridge equation with nonlinear damping term |ut|m-2ut and source term |u|p-2u. We give necessary and sufficient condition for global existence and energy decay results without considering the relation between m and p. Moreover, when p>m, we give sufficient condition for finite time blow-up of solutions. The lower bound of the blow-up time Tmax is also established. It worth to mention that our obtained results extend the recent results of Wang (J. Math. Anal. Appl., 2014) to the nonlinear damping case.
Preprint
|
|
|
Mathematics & Computer Science, Applied Mathematics; general stability;laminated beam;infinite memory;multiplier technique;energy method
Online: 22 February 2017 (16:56:19 CET)
|
|
Share this article with
×
In this work, we consider a one-dimensional laminated beam in the case of non-equal wave speeds with only one infinite memory on the effective rotation angle. In this case, we establish the general decay result for the energy of solution without any kind of internal or boundary control. The main result is obtained by applying the method used in Guesmia et al. (Electron. J. Differential Equations 193: 1-45, 2012) and the second-order energy.
Preprint
|
|
|
Mathematics & Computer Science, Analysis; secured hashes; symmetric key encryption; energy optimization
Online: 21 February 2017 (10:28:30 CET)
|
|
Share this article with
×
In this work we study the energy consumption by various modern secured hash functions (MD2, MD5, SHA-1, and SHA-2) and modern symmetric key encryption protocols (Blowfish, DES, 3DES, and AES) from the algorithmic perspective. We identify various parameters that moderate energy consumption of these hashes and protocols. Our work is directed towards redesigning or modifying these algorithms to make them consume lesser energy. As a first step, we try to determine the applicability of the asymptotic energy complexity model by Roy et. al. on these hashes and protocols. Specifically, we try to observe whether parallelizing the access of blocks of data in these algorithms reduces their energy consumption based on the energy model. Our results confirm the applicability of the energy model on these hashes and protocols. Our work is motivated by the relevance and importance of cryptographic hashes and symmetric key protocols for modern ICT (Information and Communication Technology), and ICT enabled industry to keep them protected from dynamically changing threat scenarios. Hence the design of more energy efficient hashes and protocols will definitely contribute in reducing the ICT energy consumption that is continuously increasing.
Preprint
|
|
|
Mathematics & Computer Science, General & Theoretical Computer Science; Zernike moment, Multi-class support vector machine, Query Engine, SPARQL
Online: 20 February 2017 (18:07:11 CET)
|
|
Share this article with
×
In this paper, a new approach to retrieve semantic images based on shape and geometric features of image in conjunction with multi-class support vector machine is proposed. Zernike moment as shape feature is to verify the invariance of objects for silhouette image. In addition, a set of geometrical features is to explore the objects shape using two features of rectangularity and circularity. Then the extracted features are normalized and employed for multi-class support vector machine either for learning or retrieving processes. The retrieving process relies on three main tasks which namely Query Engine, Matching Module and Ontology Manger, respectively. Query Engine is to build the input text or image query using SPARQL language. The matching module extracts the shape and geometric features of image’s objects and employ them to Ontology Manger which in turn inserts them in ontology knowledge base. Benchmark mammals have been conducted to empirically conclude the outcome of proposed approach. Our experiment on text and image retrieval yields efficient results to problematic phenomena than previously reported.
Preprint
|
|
|
Mathematics & Computer Science, Analysis; thermoelastic Timoshenko beam; global existence; exponential stability; second sound
Online: 20 February 2017 (06:36:23 CET)
|
|
Share this article with
×
In this paper, we study the global existence and exponential decay for a dynamic contact problem between a Timoshenko beam with second sound and two rigid obstacles, of which the heat flux is given by Cattaneo's law instead of the usual Fourier's law. The main difficulties arise from the irregular boundary terms, from the low regularity of the weak solution and from the weaker dissipative effects of heat conduction induced by Cattaneo's law. By considering related penalized problems, proving some a priori estimates and passing to the limit, we prove the global existence of the solutions. By considering the approximate framework, constructing some new functionals and applying the perturbed energy method, we obtain the exponential decay result for the approximate solution, and then prove the exponential decay rate to the original problem by utilizing the weak lower semicontinuity arguments.
Preprint
|
|
|
Mathematics & Computer Science, Information Technology & Data Management; network; systems; cloud computing; data centre; performance; software-defined; virtual machine; scheduling; admission control; application-aware;
Online: 20 February 2017 (04:56:24 CET)
|
|
Share this article with
×
Cloud computing refers to applications delivered as services over the Internet. Cloud systems employ policies that are inherently dynamic in nature and that depend on temporal conditions defined in terms of external events, such as the measurement of bandwidth, use of hosts, intrusion detection or specific time events. In this paper, we investigate an optimized resource management scheme named v-Mapper. The basic premise of v-Mapper is to exploit application-awareness concepts using software-defined networking (SDN) features. This paper makes three key contributions to the field: (1) We propose a virtual machine (VM) placement scheme that can effectively mitigate the VM placement issues for data-intensive applications; (2) We propose a validation scheme that will ensure that a service is entertained only if there are sufficient resources available for its execution and (3) We present a scheduling policy that aims to eliminate network load constraints. An evaluation was carried out with various benchmarks and demonstrated that v-Mapper shows improved performance over other state-of-the-art approaches in terms of average task completion time, service delay time and bandwidth utilization. Given the growing importance of supporting large-scale data processing and analysis in datacentres, the v-Mapper system has the potential to make a positive impact in improving datacentre performance in the future.
Preprint
|
|
|
Mathematics & Computer Science, Computational Mathematics; ordinal patterns; Permutation entropy; Approximate entropy;Sample entropy; Conditional entropy of ordinal patterns;Kolmogorov-Sinai entropy; classification
Online: 17 February 2017 (16:41:32 CET)
|
|
Share this article with
×
During the last years some new variants of Permutation entropy have been introduced and applied to EEG analysis, among them a conditional variant and variants using some additional metric information or being based on entropies different from the Shannon entropy. In some situations it is not completely clear what kind of information the new measures and their algorithmic implementations provide. We discuss the new developments and illustrate them for EEG data.
Preprint
|
|
|
Mathematics & Computer Science, Applied Mathematics; laminated beam; Fourier's law; exponential stability; lack of exponential stability; polynomial stability
Online: 16 February 2017 (08:52:57 CET)
|
|
Share this article with
×
In this paper, we study the well-posedness and the asymptotic behavior of a one-dimensional laminated beam system, where the heat conduction is given by Fourier's law effective in the rotation angle displacements. We show that the system is well-posed by using the Hille-Yosida theorem and prove that the system is exponentially stable if and only if the wave speeds are equal. Furthermore, we show that the system is polynomially stable provided that the wave speeds are not equal.
Preprint
|
|
|
Mathematics & Computer Science, Information Technology & Data Management; protein–protein interaction networks; protein function module; simplified swarm optimization
Online: 15 February 2017 (10:17:35 CET)
|
|
Share this article with
×
Proteomics research has become one of the most important topics in the fields of life science and natural science. At present, research on protein–protein interaction networks (PPINs) mainly focuses on detecting protein complexes or function modules. However, existing approaches are either ineffective or incomplete. In this paper, we investigate function module detection mechanisms in PPIN, including open databases, existing detection algorithms and recent solutions. After that, we describe the proposed solution based on simplified swarm optimization (SSO) algorithm and gene ontology knowledge. The proposed solution implements SSO algorithm for clustering proteins with similar function, and imports biological gene ontology knowledge for further identifying function complexes and improving detection accuracy. Furthermore, we use four different categories of species dataset for experiment: Fruitfly, Mouse, Scere, and Human. The testing and analysis result show that the proposed solution is feasible, efficient and could achieve a higher accuracy of prediction than existing approaches.
Preprint
|
|
|
Mathematics & Computer Science, Numerical Analysis & Optimization; Non-linear equations, Monotone equations , Spectral Gradient method , Projection method.
Online: 13 February 2017 (15:03:16 CET)
|
|
Share this article with
×
In this work, we proposed a combination of a positive spectral gradient-like method and projection method for solving nonlinear monotone equations. The spectral gradient-like coefficient is obtained using a convex combination of two different positive spectral coefficients. Under the monotonicity and Lipschitz continuity assumptions the method is shown to be globally convergent. We show the efficiency of the method numerically by comparing it with the existing methods.
Preprint
|
|
|
Mathematics & Computer Science, Logic; neutrosophy; neutrosophic logic; neutrosophic alethic modalities; neutrosophic possibility; neutrosophic necessity; neutrosophic impossibility; neutrosophic temporal modalities; neutrosophic epistemic modalities; neutrosophic doxastic modalities; neutrosophic deontic modalities
Online: 5 February 2017 (09:41:31 CET)
|
|
Share this article with
×
I introduce now for the first time the neutrosophic modal logic. The Neutrosophic Modal Logic includes the neutrosophic operators that express the modalities. It is an extension of neutrosophic predicate logic, and of neutrosophic propositional logic. In order for the paper to be self-contained, I also recall the etymology and definition of neutrosophy and of neutrosophic logic. Several examples are presented as well.
Preprint
|
|
|
Mathematics & Computer Science, Other; sustainability; ecotourism; System Dynamic; tourism; biodiversity; communities
Online: 3 February 2017 (03:53:56 CET)
|
|
Share this article with
×
The sustainability of ecotourism is the backbone of tourism development of a country. Ecotourism can contribute to both conservation and development in which involves dynamic relationship between tourism, biodiversity and communities, facilitate by great management. The purpose of this study is to analyze the dimensions of the socio-economic and environmental impacts of ecotourism in communities surrounding the Tasik Kenyir in Terengganu, Malaysia. This study provides a framework for the development and evaluation of ecotourism. The framework will determine if the relationships between indicators are positively correlated which will result in positive contribution to the other by using System Dynamic. Socio-cultural and economic data will be collected through interviews and group discussions in selected communities in Tasik Kenyir. Data on wildlife will be extracted from secondary data from Kenyir Research Institute, Universiti Malaysia Terengganu. The data analysis will explore the socio-cultural and economic differences between and within different communities due to ecotourism development, the contribution of ecotourism to conservation activities, local support for conservation and ecotourism as well as the influence of tourist activities on the distribution of wildlife species in Tasik Kenyir. This study aims to contribute toward understanding the natural resource community-ecotourism inter-relationship and help to bridge the knowledge gap that hinders biodiversity conservation initiatives. The findings will be used as a base for further development of ecotourism and will recommend alternative management options where necessary for the study area.
Preprint
|
|
|
Mathematics & Computer Science, Applied Mathematics; stochastic differential equation; numerical simulation; real option; renewable energy; Egypt
Online: 30 January 2017 (12:04:34 CET)
|
|
Share this article with
×
Recently, there has been a growing interest in the production of electricity from renewable energy sources (RES). The RES investment is characterized by uncertainty, which is long-term, costly, depend on feed-in-tariff and support schemes. In this paper, we address the real option valuation (ROV) of a solar power plant investment. The real option framework is investigated. This framework considers the renewable certificate price, furthermore the cost of delay between establishing and operating the solar power plant. The optimal time of launching the project and assess the value of deferred option are discussed. The new three stage numerical methods are constructed, the Lobatto3C-Milstein (L3CM) methods. The numerical methods are integrated with concept of Black-Scholes option pricing theory, and applied in option valuation for solar energy investment with uncertainty. The numerical results of L3CM, finite difference and Monte Carlo methods are compared to show the efficiency of our methods. Our data set refers to the Arab Republic of Egypt.
Preprint
|
|
|
Mathematics & Computer Science, Computational Mathematics; Regular polyhedra, reflection group, fundamental region, invariant mapping
Online: 26 January 2017 (10:35:59 CET)
|
|
|
Share this article with
×
A fast algorithm is established to transform points of the unit sphere into fundamental region symmetrically. With the resulting algorithm, a flexible form of invariant mappings is achieved to generate aesthetic patterns with symmetries of the regular polyhedra. This method avoids the order restriction of symmetry groups, which can be similarly extended to treat regular polytopes in n-dimensional space for n>=4.