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Preprint ARTICLE | doi:10.20944/preprints202305.0797.v1

Graph Neural Network Based Efficient Subgraph Embedding 2 Method for Link Prediction in Mobile Edge Computing

XiaoLong Deng, JuFeng Sun, JunWen Lu

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: link prediction; graph neural network; graph embedding

Online: 11 May 2023 (05:24:00 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202304.1025.v1

An Improved Salp Swarm Algorithm for Solving Node Coverage Optimization problem in WSN

Jiaming Wang, Zhengli Zhu, Fuquang Zhang, Yanxiong Liu

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: wireless sensor network (WSN); Salp Swarm Algorithm (SSA); T-distribution; tent chaotic se-quence

Online: 27 April 2023 (04:05:52 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202304.0242.v2

A Simulation Based Solution Approach for the Capacitated Lot-Sizing Problem With Remanufacturing

Luis Rocha

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: Simulation based optimization; capacitated lot-sizing problem; heuristics; remanufacturing

Online: 20 April 2023 (05:21:25 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202304.0242.v1

A Simulation Based Solution Approach for the Capacitated Lot-Sizing Problem With Remanufacturing

Luis Rocha

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: CLSP; Simulation; Heuristikl; algorithms

Online: 12 April 2023 (04:55:56 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202301.0219.v2

When to Use Large Language Model: Upper Bound Analysis of BM25 Algorithms in Reading Comprehension Task

Tingzhen Liu, Qianqian Xiong, Shengxi Zhang

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: Large Language Model; natural language processing; reading comprehension; computational lin-guistics; information retrieval; BM25

Online: 30 March 2023 (03:51:37 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202303.0056.v1

Efficient Use of Quantum Linear System Algorithms in Interior Point Methods for Linear Optimization

Mohammadhossein Mohammadisiahroudi, Ramin Fakhimi, Tamás Terlaky

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: Quantum Interior Point Method; Linear Optimization; Quantum Linear System Algorithm; Iterative Refinement

Online: 3 March 2023 (04:06:57 CET)

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Preprint ARTICLE | doi:10.20944/preprints202303.0031.v1

A Mixed Clustering Approach for Real Time Anomaly Detection

Fokrul Alom Mazarbhuiya, Mohamed Shenify

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: Data instances, Real time systems, k-means algorithm, Agglomerative hierarchical algorithm, Similarity measure, merge function

Online: 2 March 2023 (04:15:10 CET)

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Preprint ARTICLE | doi:10.20944/preprints202303.0023.v1

Application of Variational AutoEncoder (VAE) Model and Image Processing Approaches in Game Design

Hugo Wai Leung Mak, Runze Han, Hoover H.F. Yin

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: Game Design; Variational AutoEncoder (VAE); Image and Video Generation; Bayesian Algorithm; Loss Function; Data Clustering; Data and Image Analytics; MNIST database; Generator and Discriminator

Online: 1 March 2023 (11:17:12 CET)

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Preprint COMMUNICATION | doi:10.20944/preprints202302.0189.v1

Infant Biometric Data Acquisitions: The Lessons Learnt

Norman Nelufule, Yaseen Moolla, Sthembile Ntshangase, Anton De Kock

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: Infant Biometrics; Longitudinal data collection; infant fingerprint; infant iris; infant's ear

Online: 10 February 2023 (08:46:12 CET)

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Preprint ARTICLE | doi:10.20944/preprints202301.0551.v1

CH-CC: A Chinese Multimodal Classroom Atmosphere Analysis Dataset Based on Teachers’ Behavior and Voice

Zicen Liao

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: multimodal dataset; sentiment analysis; classroom atmosphere; intelligent education

Online: 30 January 2023 (09:49:12 CET)

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Preprint ARTICLE | doi:10.20944/preprints202301.0533.v1

Improving Deep Echo State Network with Neuronal Similarity-based Iterative Pruning Merging Algorithm

Qingyu Shen, Hanwen Zhang, Yao Mao

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: reservoir computing; deep echo state network; neuronal similarity-based iterative pruning merging algorithm; chaotic time series forecast

Online: 30 January 2023 (02:34:13 CET)

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Preprint ARTICLE | doi:10.20944/preprints202301.0522.v1

Autonomous Vehicle Dataset with Real Multi-Driver Scenes and Biometric Data

Francisca Rosique, Pedro J. Navarro, Leanne Miller, Eduardo Salas

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: autonomous vehicle; data set; multidriver; biometric

Online: 28 January 2023 (07:55:36 CET)

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Preprint ARTICLE | doi:10.20944/preprints202301.0486.v1

Based on the Improved Yolov5 Cotton Top Bud Recognition Algorithm

Guangze Xi, Jianping Zhou, Yan Xu, Xiaorong Wang

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: YOLOv5s; Gz-ShuffleNetv2; XIoU; Attention Mechanis; Interface system

Online: 27 January 2023 (06:11:27 CET)

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Preprint ARTICLE | doi:10.20944/preprints202301.0219.v1

When to Use Large Language Model: Upper Bound Analysis of BM25 Algorithms in Reading Comprehension Task

Tingzhen Liu, Qianqian Xiong, Shengxi Zhang

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: Large Language Model; Natural Language Processing; Reading Comprehension; Computational linguistics; Information Retrieval; BM25

Online: 12 January 2023 (08:58:03 CET)

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Preprint ARTICLE | doi:10.20944/preprints202205.0215.v3

Qluster: An Easy-to-Implement Generic Workflow for Robust Clustering of Health Data

Cyril Esnault, Melissa Rollot, Pauline Guilmin, Jean-Daniel Zucker

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: clustering; robustness; generic; workflow; algorithms

Online: 6 January 2023 (01:55:19 CET)

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Preprint ARTICLE | doi:10.20944/preprints202211.0561.v1

Lightweight Tennis Ball Detection Algorithm Based on Robomaster EP

Yuan Zhao, Ling Lu, Wu Yang, QiZheng Li, Xiujie Zhang

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: Tennis ball detection algorithm; Lightweight; Convolutional coordinate attention; Feature fusion; Loss function; Activation function

Online: 30 November 2022 (03:53:21 CET)

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To address the problems of poor recognition, low detection accuracy, a large number of model parameters and computation, complex network structure, and unfavorable portability to embedded devices in traditional tennis ball detection algorithms, this study proposes a lightweight tennis ball detection algorithm YOLOv5s-Z based on Robomater EP. The main work is as follows: Firstly, constructing lightweight G-Backbone and G-Neck network layers to reduce the number of parameters and computation of the network structure. Secondly, the convolutional coordinate attention is incorporated in G-Backbnone to embed the location information into the channel attention, which makes the network obtain the location information in a larger area through multiple convolutions and enhances the expression ability of the mobile network learning features. In addition, the Concat module in the original feature fusion is modified into a weighted bi-directional feature pyramid W-BiFPN with settable learning weights to improve the feature fusion capability and achieve efficient weighted feature fusion and bi-directional cross-scale connectivity. The EIOU loss is introduced to split the influence factor of aspect ratio and calculate the length and width of the target frame and anchor frame respectively, combined with Focal-EIOU Loss to solve the problem of imbalance between difficult and easy samples. The activation function Meta-ACON is introduced to achieve an adaptive selection of whether to activate the neurons and improve the detection accuracy. Finally, the experimental results show that compared with the original algorithm, the YOLOv5s-Z algorithm reduces the number of parameters and computation by 42$\%$ and 44$\%$, the model size by 39$\%$, and 2$\%$ improvement in average accuracy mean value, which verifies the effectiveness of the improved algorithm and the light weight of the model to meet the deployment requirements of embedded devices, and adapts Robomaster EP for accurate detection and real-time recognition of tennis balls.

Preprint ARTICLE | doi:10.20944/preprints202211.0252.v1

Modifed SIC Algorithm based on Lattice Reduction Aided for MIMO OFDM Detection

Haitao Liu, Fan Feng, Xuchao Cheng, Liguo Wang

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: MIMO OFDM; SIC; Log-likelihood ratio(LLR); SQRD

Online: 14 November 2022 (10:47:34 CET)

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Preprint ARTICLE | doi:10.20944/preprints202211.0103.v1

The Hypervolume Newton Method for Constrained Multi-objective Optimization Problems

Hao Wang, Michael Emmerich, André Deutz, Víctor Adrián Sosa Hernández, Oliver Schütze

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: multi-objective optimization; hypervolume indicator; Newton method; evolutionary algorithms; constraint handling; hypervolume scalarization

Online: 7 November 2022 (04:20:09 CET)

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Preprint ARTICLE | doi:10.20944/preprints202210.0472.v1

Data-Driven Deep Journalism to Discover Age Dynamics in Multi-Generational Labour Markets from LinkedIn Media

Abeer Abdullah Alaql, Fahad AlQurashi, Rashid Mehmood

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: media; journalism; deep journalism; labor markets; Great Resignation; Quiet Quitting; Millennials; Generation Z; Big Data Analytics; Natural Language Processing (NLP)

Online: 31 October 2022 (08:33:34 CET)

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We live in the information age and, ironically, meeting the core function of journalism – i.e., to provide people access to unbiased information – has never been more difficult. This paper explores deep journalism, our data-driven Artificial Intelligence (AI) based journalism approach to study how the LinkedIn media could be useful for journalism. Specifically, we apply our deep journalism approach to LinkedIn to automatically extract and analyse big data to provide the public with information about labour markets, people’s skills and education, and businesses and industries from multi-generational perspectives. The Great Resignation and Quiet Quitting phenomena coupled with rapidly changing generational attitudes are bringing unprecedented and uncertain changes to labour markets and our economies and societies, and hence the need for journalistic investigations into these topics is highly significant. We combine big data and machine learning to create a whole machine learning pipeline and a software tool for journalism that allows discovering parameters for age dynamics in labour markets using LinkedIn data. We collect a total of 57,000 posts from LinkedIn and use it to discover 15 parameters by Latent Dirichlet Allocation algorithm (LDA) and group them into five macro-parameters, namely Generations-Specific Issues, Skills & Qualifications, Employment Sectors, Consumer Industries, and Employment Issues. The journalism approach used in this paper can automatically discover and make objective, cross-sectional, and multi-perspective information available to all. It can bring rigour to journalism by making it easy to generate information using machine learning and can make tools and information available so that anyone can uncover information about matters of public importance. This work is novel since none of the earlier works have reported such an approach and tool and leveraged it to use LinkedIn media for journalism and to discover multigenerational perspectives (parameters) for age dynamics in labour markets. The approach could be extended with additional AI tools and other media.

Preprint ARTICLE | doi:10.20944/preprints202210.0301.v1

MERP: A Dataset of Emotion Ratings for Full-Length Musical Songs with Profile Information of Raters

Enyan Koh, Kin Wai Cheuk, Kwan Yee Heung, Kat R Agres, Dorien Herremans

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: Emotion prediction; music; music emotion dataset; affective computing

Online: 20 October 2022 (08:33:49 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202210.0081.v1

A Model Selection Algorithm for Complex Multi-Domain Cnn Systems Based on Feature-Weights Relation in Deep Learning

Eyad Alsaghir, Xiyu Shi, Varuna De Silva

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: CNN; AI; Causality; Understandability; Object Features; Excitation Weight; Multi-model Neural Network; Model Selection

Online: 7 October 2022 (14:58:09 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202209.0256.v1

Development of Evolutionary Systems based on Quantum Petri Nets

Tiberiu Stefan Letia, Elenita Maria Durla-Pasca, Dahlia Al-Janabi, Octavian Petru Cuibus

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: quantum computing; genetic algorithms; Petri nets; Quantum Petri nets; software development; analysis and verification

Online: 19 September 2022 (03:41:37 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202209.0226.v1

A Survey of GNN in Bioinformation Data

Zhenyi Zhu

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: Graph Neural Networks, Non-Euclidean Data, Bioinformation

Online: 15 September 2022 (08:49:51 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202208.0314.v1

CHAGSKODE Algorithm for Solving Real World Constrained Optimization Problems

Debanjan Saha, Karam M. Sallam, Shuvodeep De, Ali W. Mohamed

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: Differential Evolution; APGSK algorithm; Constrained Optimization; transformation; parameter adaptation; multi-operator; Evolutionary Algorithms

Online: 17 August 2022 (09:47:59 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202208.0307.v1

Framework of Ensemble Parmeter Adapted Evolutionary Algorithm for Solving Constrained Optimization Problems

Debanjan Saha, Karam M. Sallam, Shuvodeep De, Ali W. Mohamed

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: constrained optimization; multi-operator; multi-parameter adaptation; ensemble constraint handling techniques; Evolutionary Algorithms

Online: 17 August 2022 (08:35:44 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202208.0109.v1

Effects of Data Augmentations on Speech Emotion Recognition

Bagus Tris Atmaja, Akira Sasou

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: speech emotion recognition; affective computing; data augmentations; wav2vec 2.0; SVM

Online: 4 August 2022 (14:09:21 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202205.0215.v2

Qluster: An Easy-to-Implement Generic Workflow for Robust Clustering of Health Data

Cyril Esnault, Melissa Rollot, Pauline Guilmin, Jean-Daniel Zucker

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: clustering; robustness; generic; workflow; algorithms

Online: 7 July 2022 (10:49:33 CEST)

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Preprint DATA DESCRIPTOR | doi:10.20944/preprints202205.0230.v1

SEN2VENµS, a Dataset for the Training of Sentinel-2 Super-Resolution Algorithms

Julien Michel, Juan Vinasco-Salinas, Jordi Inglada, Olivier Hagolle

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: Single Image Super-Resolution; Sentinel-2; VENµS; remote sening

Online: 17 May 2022 (11:13:47 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202205.0215.v1

Qluster: An Easy-to-Implement Generic Workflow for Robust Clustering of Health Data

Cyril Esnault, Melissa Rollot, Pauline Guilmin, Jean-Daniel Zucker

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: clustering; robustness; generic; workflow; algorithms

Online: 17 May 2022 (03:10:48 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202204.0244.v1

A Fuzzy Consensus Clustering Algorithm for MRI Brain Tissue Segmentation

Aruna Kumar S. V., Ehsan Yaghoubi, Hugo Proença

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: Brain Tissue Segmentation; Consensus Clustering; Segmentation; Magnetic Resonance Image

Online: 26 April 2022 (14:11:52 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202204.0167.v1

Interpolating Strange Attractors via Fractional Brownian Bridges

Sebastian Raubitzek, Thomas Neubauer, Jan Friedrich, Andreas Rauber

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: time series interpolation; phase space reconstruction; takens’ theorem; interpolation; stochastic interpolation; genetic algorithm; time series data; preprocessing; strange attractor; attractor; attractor reconstruction

Online: 18 April 2022 (11:02:00 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202202.0075.v1

What Should I Notice? Using Alogithmic Information Theory to Evaluate the Memorability of Events in Smart Homes

Étienne Houzé, Jean-Louis Dessalles, Ada Diaconescu, David Menga

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: Kolmogorov Complexity; Algorithmic Information Theory; Simplicity; Abduction; Memorability

Online: 4 February 2022 (14:11:31 CET)

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Preprint ARTICLE | doi:10.20944/preprints202201.0465.v1

Genetic Algorithm-based Optimal Deep Neural Network for Detecting Network Intrusions

Sourav Adhikary, Md. Musfique Anwar, Mohammad Jabed Morshed Chowdhury, Iqbal H. Sarker

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: genetic algorithm; deep neural network; hidden layer; optimal architecture; intrusion detection

Online: 31 January 2022 (13:26:18 CET)

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Preprint ARTICLE | doi:10.20944/preprints202201.0445.v1

Internet of Things-Driven Data Mining for Smart Crop Production Prediction in the Peasant Farming Domain

Luis Omar Colombo-Mendoza, Mario Andrés Paredes-Valverde, María del Pilar Salas-Zárate, Rafael Valencia-García

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: data mining; predictive analytics; Internet of Things; peasant farming; smart farming system; crop production prediction

Online: 31 January 2022 (10:58:30 CET)

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Preprint ARTICLE | doi:10.20944/preprints202201.0130.v1

Metaheuristic Algorithms Based on Compromise Programming for Multi-Objective Urban Shipment Problem

Son Tung Ngo, Jafreezal Jaafar, Izzatdin Abdul Aziz, Muhammad Umar Aftab, Giang Hoang Nguyen, Ngoc Anh Bui

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: multi objective optimization; VRP; compromise programming; genetic algorithm; tabu search; local search; metaheuristics; combinatorial optimization

Online: 10 January 2022 (18:38:55 CET)

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Preprint ARTICLE | doi:10.20944/preprints202112.0506.v1

On the Distributional Characterization of Graph Models of Water Distribution Networks in Wasserstein Spaces

Antonio Candelieri, Andrea Ponti, Francesco Archetti

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: multi-objective; evolutionary algorithms; Pareto optimality; Wasserstein distance; network vulnerability; resilience; sensor placement.

Online: 31 December 2021 (11:01:51 CET)

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This paper is focused on two topics very relevant in water distribution networks (WDNs): vulnerability assessment and the optimal placement of water quality sensors. The main novelty element of this paper is to represent the data of the problem, in this case all objects in a graph underlying a water distribution network, as discrete probability distributions. For vulnerability (and the related issue of re-silience) the metrics from network theory, widely studied and largely adopted in the water research community, reflect connectivity expressed as closeness centrality or, betweenness centrality based on the average values of shortest paths between all pairs of nodes. Also network efficiency and the related vulnerability measures are related to average of inverse distances. In this paper we propose a different approach based on the discrete probability distribution, for each node, of the node-to-node distances. For the optimal sensor placement, the elements to be represented as dis-crete probability distributions are sub-graphs given by the locations of water quality sensors. The objective functions, detection time and its variance as a proxy of risk, are accordingly represented as a discrete e probability distribution over contamination events. This problem is usually dealt with by EA algorithm. We’ll show that a probabilistic distance, specifically the Wasserstein (WST) distance, can naturally allow an effective formulation of genetic operators. Usually, each node is associated to a scalar real number, in the optimal sensor placement considered in the literature, average detection time, but in many applications, node labels are more naturally expressed as histograms or probability distributions: the water demand at each node is naturally seen as a histogram over the 24 hours cycle. The main aim of this paper is twofold: first to show how different problems in WDNs can take advantage of the representational flexibility inherent in WST spaces. Second how this flexibility translates into computational procedures.

Preprint ARTICLE | doi:10.20944/preprints202112.0452.v1

A Fast Electrical Resistivity-Based Algorithm to Measure and Visualize Two-Phase Swirling Flows

Muhammad Awais Sattar, Matheus Martinez Garcia, Luis M Portela, Laurent Babout

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: Electrical Resistance Tomography (ERT); Raw Data Processing; Inline Swirl Separator; Geometrical Parameter Extraction

Online: 28 December 2021 (14:42:44 CET)

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Preprint ARTICLE | doi:10.20944/preprints202111.0215.v1

School Timetabling Optimisation Using Artificial Bee Colony Algorithm Based on a Virtual Searching Space Method

Kaixiang Zhu, Lily D Li, Michael Li

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: educational timetable; school timetabling; constraint satisfaction problem; optimisation; artificial bee colony algorithm

Online: 12 November 2021 (11:34:55 CET)

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Preprint REVIEW | doi:10.20944/preprints202110.0247.v1

A Survey on Awesome Korean NLP Datasets

Byunghyun Ban

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: natural language; NLP; Korean; dataset

Online: 18 October 2021 (14:33:41 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202109.0407.v1

A Cloud Computing-Based Modified Symbiotic Organisms Search Algorithm for Ecosystem Sustainability

Ajoze Abdulraheem Zubair, Shukor Bin Abd Razak, Md. Asri Bin Ngadi

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: cloud computing; cloud resource management; task scheduling; ecosystem; geometric mean; symbiotic organisms search algorithm; convergence speed

Online: 23 September 2021 (12:31:06 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202106.0654.v1

A Hybrid Deep Learning Model to Predict the Impact of COVID-19 on Mental Health form Social Media Big Data

Tapotosh Ghosh, Md. Hasan Al Banna, Md. Jaber Al Nahian, Kazi Abu Taher, M Shamim Kaiser, Mufti Mahmud

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: COVID-19; Mental Health; Depression; Big data; Social media.

Online: 28 June 2021 (13:50:49 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202012.0563.v2

Binary Particle Swarm Optimization Algorithm for Kidney Exchanges Acceleration using Parallel MATLAB

Wael M. F. Abdel-Rehim

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: kidney exchange; Particle Swarm; Meta-heuristics; Optimization

Online: 14 May 2021 (11:03:30 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202104.0523.v1

Comparison of Backpropagation and Kalman Filter-based Training for Neural Networks

Laurin Luttmann, Paolo Mercorelli

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: Backpropagation Algorithm; Kalman Filter; Neural Networks

Online: 20 April 2021 (08:49:55 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202101.0142.v1

A Polynomial Algorithm for Sequencing Jobs with Release and Delivery Times on Uniform Machines

Nodari Vakhania, Frank Werner

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: scheduling; uniform machines; release time; delivery time; time complexity; algorithm

Online: 8 January 2021 (10:59:29 CET)

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Preprint ARTICLE | doi:10.20944/preprints202001.0328.v2

Energy Efficient Multi-Path Routing Algorithm Using Gray System Theory for Improvement of Routing and Network Stability in Internet of Things

Rogayye Khaleghnasab, Karamolah Bagherifard, Samad Nejatian, Bahman Ravaei

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: Internet of Things; multi-path routing; Gray System Theory; network stability; RMPGST-IoT

Online: 25 November 2020 (14:46:42 CET)

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Preprint ARTICLE | doi:10.20944/preprints202009.0424.v1

Entropic Ranks: A Methodology for Enhanced, Threshold-Free, Information-Rich Data Partition and Interpretation

Hector - Xavier de Lastic, Irene Liampa, Alexandros G. Georgakilas, Michalis Zervakis, Aristotelis Chatziioannou

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: data analysis; threshold-free; differential analysis

Online: 18 September 2020 (09:11:04 CEST)

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Background: Traditional omic analysis relies on p-value and fold change as selection criteria. There is an ongoing debate on their effectiveness in delivering systemic and robust interpretation, due to their dependence on assumptions of conformity with various parametric distributions.Here, we propose a threshold-free selection method based on robust, non-parametric statistics, ensuring independence from the statistical distribution properties and broad applicability. Such methods could adapt to different initial data distributions, contrary to statistical techniques based on fixed thresholds. Methods: Our work extends the Rank Products methodology with a neutral selection method of high information-extraction capacity. We introduce the calculation of the RP distribution’s entropy to isolate the features of interest by their contribution to the distribution’s information content. The aim is a methodology performing threshold-free identification of the differentially expressed features, which are highly informative about the phenomenon under scrutiny. Conclusions: Applying the proposed method on microarray (transcriptomic and DNA methylation) and RNAseq count data of varying sizes and noise presence, we observe robust convergence for the different parameterisations to stable cutoff points. Functional analysis through BioInfoMiner and EnrichR was used to evaluate the information potency of the resulting feature lists. Overall, the derived functional terms provide a systemic description highly compatible with the results of traditional statistical hypothesis testing techniques. The methodology behaves consistently across different data types. The feature lists are compact and information-rich, indicating phenotypic aspects specific to the tissue and biological phenomenon i nvestigated. Selection by information content measures efficiently addresses problems, emerging from arbitrary thresholding, thus facilitating the full automation of the analysis.

Working Paper ARTICLE

Generating Fake ECGs using GANs for Anonymizing Healthcare Data

Esteban Piacentino, Alvaro Guarner, Cecilio Angulo

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: GAN; ECG; anonymization; healthcare data; sensors; data transformation

Online: 3 September 2020 (05:26:01 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202008.0241.v1

Technique of Gene Expression Profiles Extraction based on the Complex Use of Clustering and Classification Methods

Sergii Babichev, Jiří Škvor

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: gene expression profiles; lung cancer; clustering; classification; binary classifiers; SOTA clustering algorithm; clustering quality criteria; ROC analysis; fuzzy inference system

Online: 10 August 2020 (08:01:10 CEST)

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In this paper, we present the results of the research concerning extraction of informative gene expression profiles from high-dimensional array of gene expressions considering the state of patients' health using clustering method, ensemble of binary classifiers and fuzzy inference system. Applying of the proposed stepwise procedure can allow us to extract the most informative genes taking into account both the subtypes of disease or state of the patient's health for further reconstruction of gene regulatory networks based on the allocated genes and following simulation of the reconstructed models. We used the publicly available gene expressions data as the experimental ones which were obtained using DNA microarray experiments and contained two types of patients' gene expression profiles: the patients with lung cancer tumor and healthy patients. The stepwise procedure of the data processing assumes the following steps: in beginning, we reduce the number of genes by removing non-informative genes in terms of statistical criteria and Shannon entropy; then, we perform the stepwise hierarchical clustering of gene expression profiles at hierarchical levels from 1 to 10 using SOTA clustering algorithm with correlation distance metric. The quality of the obtained clustering was evaluated using complex clustering quality criterion which is considered both the gene expression profiles distribution relative to center of the clusters were these gene expression profiles are allocated and the centers of the clusters distribution. The result of this stage execution was selection of the optimal cluster at each of the hierarchical levels which corresponded to minimum value of the quality criterion. At the next step, we have implemented classification procedure of the examined objects using four well known binary classifiers: logistic regression, support-vector machine, decision trees and random forest classifier. The effectiveness of the appropriate technique was evaluated based on the use of ROC analysis using criteria included as the components the errors of both the first and the second kinds. The final decision concerning extraction of the most informative subset of gene expression profiles was taken based on the use of fuzzy inference system, the inputs of which are the results of the appropriate single classifiers operation and output is the final solution concerning state of the patient's health. To our mind, the implementation of the proposed stepwise procedure of the informative gene expression profiles extraction create the conditions for increasing effectiveness of the further procedure of gene regulatory networks reconstruction and the following simulation of the reconstructed models considering the subtypes of the disease and/or state of the patient’s health.

Preprint REVIEW | doi:10.20944/preprints202007.0153.v1

A Hitchhiker’s Guide to Working with Large, Open-Source Neuroimaging Datasets

Corey Horien, Stephanie Noble, Abigail Greene, Kangjoo Lee, Daniel Barron, Siyuan Gao, Dave O'Connor, Mehraveh Salehi, Javid Dadashkarimi, Xilin Shen, Evelyn Lake, R. Todd Constable, Dustin Scheinost

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: Open-science; big data; fMRI; data sharing; data management

Online: 8 July 2020 (11:53:33 CEST)

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Preprint ARTICLE | doi:10.3390/sci2020047

Images of Roman Imperial Denarii: A Curated Data Set for the Evaluation of Computer Vision Algorithms Applied to Ancient Numismatics, and an Overview of Challenges in the Field

Ognjen Arandjelović, Marios Zachariou

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: coins; review; problems; data corpus; grade; preservation; condition

Online: 14 June 2020 (00:00:00 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202006.0028.v1

Genetic Algorithm: Reviews, Implementations, and Applications

Tanweer Alam, Shamimul Qamar, Amit Dixit, Mohamed Benaida

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: genetic algorithm; search techniques; random tests; evolution; applications

Online: 4 June 2020 (07:44:03 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202005.0173.v1

Grey Wolf Based Wang’s Demons for Retinal Image Registration

Sayan Chakraborty, Ratika Pradhan, Amira S. Ashour, Luminita Moraru, Nilanjan Dey

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: demons registration; firefly algorithm; cuckoo search; grey-wolf optimization; correlation; image registration

Online: 10 May 2020 (16:11:54 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202004.0403.v1

Can Compact Optimisation Algorithms Be Structurally Biased?

Anna V. Kononova, Fabio Caraffini, Hao Wang, Thomas Bäck

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: structural bias; compact algorithm; continuous optimisation; estimation of distribution algorithm; infeasible solution

Online: 23 April 2020 (04:49:23 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202004.0273.v1

Cooperative Multi-Simplex Algorithm: An Innovation from Localization to Globalization

Javaid Ali

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: Nelder-Mead algorithm; cooperative multi-simplex algorithm; simplex-fitness; system of nonlinear equations

Online: 16 April 2020 (12:54:15 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202003.0381.v1

The SOS Platform: Designing, Tuning and Statistically Benchmarking Optimisation Algorithms

Fabio Caraffini

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: algorithmic design; metaheuristic optimisation; evolutionary computation; swarm intelligence; memetic computing; parameter tuning; fitness trend; Wilcoxon Rank-Sum; Holm-Bonferroni; benchmark suite

Online: 26 March 2020 (04:03:41 CET)

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Preprint ARTICLE | doi:10.3390/sci2010015

Images of Roman Imperial Denarii: A Curated Data Set for the Evaluation of Computer Vision Algorithms Applied to Ancient Numismatics, and an Overview of Challenges in the Field

Ognjen Arandjelović

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: coins; review; problems; data corpus; grade; preservation; condition

Online: 16 March 2020 (00:00:00 CET)

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Preprint ARTICLE | doi:10.20944/preprints202002.0277.v1

Can Single Solution Optimisation Methods Be Structurally Biased?

Anna V. Kononova, Fabio Caraffini, Hao Wang, Thomas Bäck

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: structural bias; algorithmic design; hypothesis testing; single solution methods; constraint handling

Online: 19 February 2020 (11:37:08 CET)

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Preprint ARTICLE | doi:10.20944/preprints202001.0149.v1

Automatic Neume Transcription of Medieval Music Manuscripts using CNN/LSTM-Networks and the segmentation-free CTC-Algorithm

Christoph Wick, Frank Puppe

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: Optical Music Recognition; Historical Document Analysis; Medieval manuscripts; neume notation; CNN; LSTM; CTC

Online: 15 January 2020 (12:11:25 CET)

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Working Paper REVIEW

Datasets for Machine Reading Comprehension: A Literature Review

Vaishali Ingale, Pushpender Singh, Aditi Singh

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: Reading Comprehensio; Descriptive Answer; Extractive answer; Multiple-choice answers; Datasets

Online: 8 October 2019 (10:40:09 CEST)

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Working Paper ARTICLE

An Improved EigenAnt Algorithm That Achieves a Balance between Intensification and Diversification

Mahan Mahrueyan, Amit Bhaya

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: EigenAnt; parameter impact analysis; intensification and diversification balance; routing networks

Online: 17 June 2019 (04:06:33 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201905.0296.v1

Iterative Positioning Algorithm of the Target Node Based on Distance Correction in WSN

Jing Chen, Shixin Wang, Mingsan Ouyang, Yudi Chen, Yuting Xuan

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: iterative positioning algorithm; distance correction; RSSI; noise impact factor; distance deviation coefficient

Online: 24 May 2019 (12:36:07 CEST)

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Working Paper ARTICLE

Sparse Coded Autoencoder Features for Chemometric Data Analysis

Muhammad Bilal, Mohib Ullah

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: Chemometric data,sparse autoencoder, gaussian process regressor, pareto optimization.

Online: 9 May 2019 (11:31:46 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201904.0270.v1

Infeasibility and Structural Bias in Differential Evolution

Fabio Caraffini, Anna Kononova, David Corne

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: structural bias, algorithmic design, differential evolution, population-based algorithms, optimisation

Online: 24 April 2019 (12:16:42 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201904.0252.v1

Multi-Agent Task Planning Based on Distributed Resource Scheduling under Command and Control Architecture

Jie Zhang, Gang Wang, Yafei Song

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: multi-agent; HTN; distributed architecture; command and control model; algorithm performance comparison

Online: 23 April 2019 (11:01:03 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201812.0123.v1

An Improved EigenAnt Algorithm That Achieves a Balance between Intensification and Diversification

Mahan Mahrueyan, Amit Bhaya

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: EigenAnt; parameter impact analysis; intensification and diversification balance; routing networks

Online: 11 December 2018 (10:18:40 CET)

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Preprint ARTICLE | doi:10.20944/preprints201811.0583.v1

A Detection algorithm based on Convolutional Neural Network

Fei Rong, Li Shasha, Xu Qingzheng, Liu Kun

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: Station logo; Convolutional Neural Network; Detection

Online: 26 November 2018 (10:57:17 CET)

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Preprint ARTICLE | doi:10.20944/preprints201811.0581.v1

Implementation of Fuzzy C-Means and Possibilistic C-Means Clustering Algorithms, Cluster Tendency Analysis and Cluster Validation

Md. Abu Bakr Siddique, Rezoana Bente Arif, Mohammad Mahmudur Rahman Khan, Zahidun Ashrafi

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: Two-dimensional clustering, Soft clustering, Fuzzy c-means(FCM), Possibilistic c-means (PCM), cluster tendency, VAT algorithm, cluster validation, PC, DI, DBI, noise point

Online: 26 November 2018 (10:19:05 CET)

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Preprint ARTICLE | doi:10.20944/preprints201810.0464.v1

Novel Risk Assessment Methodology for Keyhole Neurosurgery with Genetic Algorithm for Trajectory Planning

Iván Villanueva-Naquid, Carlos Soubervielle-Montalvo, Ruth M. Aguilar-Ponce, Saúl Tovar-Arriaga, Juan C. Cuevas-Tello, Cesar A. Puente-Montejano, Marcela Mejia-Carlos, Jaime G. Torres-Corzo

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: genetic algorithms; trajectory planning; keyhole neurosurgery; risk assessment; medical imaging

Online: 22 October 2018 (04:40:10 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201810.0326.v1

Optimal Rescue Ship Locations Using Image Processing and Clustering

Cho-Young Jung, Sang-Lok Yoo

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: clustering-based optimization; location optimization; flood-filling algorithm; marine accident; rescue ship; shortest distance

Online: 15 October 2018 (16:53:32 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201809.0495.v1

A Cooperation of Multileader Fruit Fly and the Probabilistic Random Walk with Adaptive Normalization for Solving Solution of the Unconstrained Optimization Problems

Wirote Apinantanakon, Khamron Sunat, Sirapat Chiewchanwattana

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: nature-inspired optimization algorithm; fruit fly optimization algorithm; multileader strategy; random walk; cooperative algorithm

Online: 26 September 2018 (04:16:45 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201809.0182.v1

A Novel Geo-Inspired Earthquake Optimization Algorithm

Efrain Mendez, Alexandro Ortiz, Pedro Ponce, Arturo Molina

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: optimization; metaheuristic; earthquake algorithm; bat algorithm; particle swarm optimization; PID controller; DC motor; fuzzy logic; mamdani; geo-inspired computing

Online: 11 September 2018 (04:57:11 CEST)

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Preprint REVIEW | doi:10.20944/preprints201809.0007.v1

Particle Swarm Optimization: A survey of Historical and Recent Developments with Hybridization Perspectives

Saptarshi Sengupta, Sanchita Basak, Richard Alan Peters

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: Particle Swarm Optimization; Swarm Intelligence; Evolutionary Computation; Intelligent Agents; Optimization; Hybrid Algorithms; Heuristic Search; Approximate Algorithms; Robotics and Autonomous Systems; Applications of PSO

Online: 2 September 2018 (15:29:55 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201804.0209.v2

An Efficient Preprocessing Algorithm for Image-based Plant Phenotyping

Hesam Attari, Ali Ghafari-Beranghar

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: plant phenotyping; noise filtering; binarization; accuracy evaluation; connected components

Online: 24 April 2018 (17:02:18 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201804.0227.v1

Converting Ensemble Clustering Problem to a Mathematical Optimization Problem and Providing an Approach to Solve Based on Optimization Toolbox

Simintaj Salehpour, Hamid Parvin

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: Ensemble clustering; cluster stability; F-measure; co-association matrix; genetic algorithm

Online: 17 April 2018 (15:58:22 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201804.0209.v1

An Efficient Preprocessing Algorithm for Image-based Plant Phenotyping

Hesam Attari, Ali Ghafari-Beranghar

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: plant phenotyping; noise filtering; binarization; accuracy evaluation; connected components

Online: 16 April 2018 (11:42:27 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201804.0192.v1

Automated Hertbeat Abnormality Detection Using Realtime R-Assisted Lightweight Feature Extraction Algorithm

Diptangshu Pandit, Chengyu Liu, Li Zhang

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: abnormal ECG; ECG processing, feature extraction; heart beat classification, abnormality detection

Online: 16 April 2018 (06:28:25 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201801.0243.v1

An Efficient Heuristic Algorithm for Solving Connected Vertex Cover Problem in Graph Theory

Yongfei Zhang, Jun Wu, Liming Zhang, Peng Zhao, Junping Zhou, Minghao Yin

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: Heuristic algorithm; connected vertex cover; GRASP

Online: 25 January 2018 (12:42:20 CET)

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Preprint REVIEW | doi:10.20944/preprints201710.0117.v1

Trends in Computer-Aided Diagnosis Using Deep Learning Techniques: A Review of Recent Studies on Algorithm Development

Bosede Iyiade Edwards, Nosiba Hisham Osman Khougali, Adrian David Cheok

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: computer-aided diagnosis; CAD algorithms; deep neural networks; medical diagnosis; review

Online: 17 October 2017 (11:57:17 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201710.0073.v1

Application of Multi Network Alignment Algorithms for Connectomes Study

Marianna Milano, Pietro Hiram Guzzi, Mario Cannataro

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: graph alignment; brain network; human connectome

Online: 12 October 2017 (04:07:33 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201708.0086.v1

Forecasting Algorithms for Recurrent Patterns in Consumer Demand

Tetiana Boiko, Oleg Karpenkov, Bulat Rakhimberdiev

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: seasonality; forecasting; pull and push models; denoising

Online: 25 August 2017 (08:21:40 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201706.0033.v2

UniMiB SHAR: A Dataset for Human Activity Recognition Using Acceleration Data from Smartphones

Daniela Micucci, Marco Mobilio, Paolo Napoletano

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: smartphone accelerometers; dataset; human activity recognition; fall detection

Online: 18 July 2017 (13:16:10 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201706.0003.v2

Bringing Depth Data Alive: Conceive Human Intention through Web Visualisations of Head Pose and Emotion Changes ^†

Grigorios Kalliatakis, Alexandros Stergiou, Nikolaos Vidakis

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: 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)

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Preprint ARTICLE | doi:10.20944/preprints201706.0033.v1

UniMiB SHAR: A Dataset for Human Activity Recognition Using Acceleration Data from Smartphones

Daniela Micucci, Marco Mobilio, Paolo Napoletano

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: smartphone accelerometers; dataset; human activity recognition; fall detection

Online: 6 June 2017 (07:59:54 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201706.0003.v1

Bringing Depth Data Alive: Conceive Human Intention through Web Visualisations of Head Pose and Emotion Changes ^†

Grigorios Kalliatakis, Alexandros Stergiou, Nikolaos Vidakis

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: human activity analysis; human intention understanding; affective computing; data visualisation; depth data; head pose estimation; emotion recognition

Online: 1 June 2017 (06:14:53 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201705.0170.v1

A Generic Approach for Error Estimation of Depth Data from (Stereo and RGB-D) 3D Sensors

Luis Fernandez, Viviana Avila, Luiz Goncalves

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: accuracy; depth data; RMS error; 3D vision sensors; stereo disparity

Online: 23 May 2017 (09:20:27 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201705.0032.v1

Autonomous Terrestrial Image Segmentation and Sensor Node Localization for Disaster Management using Plant Growth Simulation Algorithm

Deblina Bhattacharjee, Anand Paul, Won-Hwa Hong, HyunCheol Seo, Karthik S.

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: image segmentation; wireless sensor node deployment; plant growth simulation algorithm; disaster management

Online: 4 May 2017 (06:02:31 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201704.0030.v1

Automatic Localization Algorithm for Ultrasound Breast Tumors Based on Human Visual Mechanism

Yuting Xie, Ke Chen, Jiangli Lin

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: Automatic localization; human visual mechanism; superpixel contrast feature; ultrasound breast tumor.

Online: 5 April 2017 (15:50:40 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201612.0088.v1

A Weakly Pareto Compliant Quality Indicator

Emanuele Dilettoso, Santi Agatino Rizzo, Nunzio Salerno

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: multiple criteria analysis; algorithms performance; Pareto optimality; quality indicator

Online: 16 December 2016 (08:31:29 CET)

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Preprint ARTICLE | doi:10.20944/preprints201612.0077.v1

Learning Parsimonious Classification Rules from Gene Expression Data Using Bayesian Networks with Local Structure

Jonathan Lyle Lustgarten, Jeya Balaji Balasubramanian, Shyam Visweswaran, Vanathi Gopalakrishnan

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: rule based models; gene expression data; bayesian networks; parsimony

Online: 15 December 2016 (08:21:24 CET)

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The comprehensibility of good predictive models learned from high-dimensional gene expression data is attractive because it can lead to biomarker discovery. Several good classifiers provide comparable predictive performance but differ in their abilities to summarize the observed data. We extend a Bayesian Rule Learning (BRL-GSS) algorithm, previously shown to be a significantly better predictor than other classical approaches in this domain. It searches a space of Bayesian networks using a decision tree representation of its parameters with global constraints, and infers a set of IF-THEN rules. The number of parameters and therefore the number of rules are combinatorial to the number of predictor variables in the model. We relax these global constraints to a more generalizable local structure (BRL-LSS). BRL-LSS entails more parsimonious set of rules because it does not have to generate all combinatorial rules. The search space of local structures is much richer than the space of global structures. We design the BRL-LSS with the same worst-case time-complexity as BRL-GSS while exploring a richer and more complex model space. We measure predictive performance using Area Under the ROC curve (AUC) and Accuracy. We measure model parsimony performance by noting the average number of rules and variables needed to describe the observed data. We evaluate the predictive and parsimony performance of BRL-GSS, BRL-LSS and the state-of-the-art C4.5 decision tree algorithm, across 10-fold cross-validation using ten microarray gene-expression diagnostic datasets. In these experiments, we observe that BRL-LSS is similar to BRL-GSS in terms of predictive performance, while generating a much more parsimonious set of rules to explain the same observed data. BRL-LSS also needs fewer variables than C4.5 to explain the data with similar predictive performance. We also conduct a feasibility study to demonstrate the general applicability of our BRL methods on the newer RNA sequencing gene-expression data.

Preprint ARTICLE | doi:10.20944/preprints201611.0070.v1

Grouped Bees Algorithm: A Grouped Version of the Bees Algorithm

Hamid Reza Nasrinpour, Amir Massah Bavani, Mohammad Teshnehlab

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: bees algorithm; swarm intelligence; evolutionary optimization; grouped bees algorithm

Online: 14 November 2016 (04:48:54 CET)

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Preprint ARTICLE | doi:10.20944/preprints201610.0038.v1

Research on an SVM Coupling Algorithm of Image Recognition

Ai-Min Yang, Yang Han, Jin-Ze Li, Yu-Hang Pan, Lei-Jie Shen, Yan Long, Yu-Zhu Zhang

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: Face Recognition; Intelligent Coupling Algorithm; Robustnes; Accuracy; Speed

Online: 11 October 2016 (14:42:02 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201607.0015.v1

Design and analysis of the redundancy allocation problem using a greedy technique

Souradeep Nanda, SIDDHARTH SHARMA, Kundnani Piyush, ANAND SHANKER DEB, C. Vijayalakshmi

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: Redundancy Allocation Problem, Genetic Algorithm, Simulated Annealing, Greedy Algorithm

Online: 9 July 2016 (05:13:42 CEST)

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Computer Science and Mathematics