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Preprint REVIEW | doi:10.20944/preprints202305.1635.v1

Ransomware Detection using Machine Learning: Survey

Amjad Raizza, Abdulmohsen Algarni

Subject: Computer Science And Mathematics, Computer Science Keywords: Machine Learning; Ransomware Techniques; Cybersecurity; Ransomware Detection; Ransomware Attacks

Online: 23 May 2023 (10:09:59 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.1523.v1

Towards an Effective Service Allocation in Fog Computing

Rayan A. Alsemmeari, Mohamed Yehia Dahab, Badraddin Alturki, Abdulaziz A. Alsulami, Raed Alsini

Subject: Computer Science And Mathematics, Computer Science Keywords: IoT; IoMT; fog computing; service allocation; optimisation; Cloud Computing

Online: 22 May 2023 (12:23:58 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.1488.v1

Improving Bug Assignment and Developer Allocation in Soft-ware Engineering through Interpretable Machine Learning Models

Mina Samir Shenouda, Nada H. Sherief, Walid M. Abdelmoez

Subject: Computer Science And Mathematics, Computer Science Keywords: Explainability; Explainable AI; XAI; Recommendation; Bugs

Online: 22 May 2023 (09:42:14 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.0999.v1

Performance Analysis of CHAID Algorithm for Accuracy

Yeling Yang, Feng Yi, Chuancheng Deng, Guang Sun

Subject: Computer Science And Mathematics, Computer Science Keywords: CHAID algorithm; Chi-square detection; Decision tree algorithm; Branching principle

Online: 15 May 2023 (07:53:11 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.0965.v1

Chinese Document-Level Emergency Event Extraction Dataset and Corresponding Methods

Kongbin Chu, Wenzhong Yang, Fuyuan Wei, Jiangtao Shi

Subject: Computer Science And Mathematics, Computer Science Keywords: candidate entity extraction; document-level event extraction; role overlapping

Online: 15 May 2023 (02:52:04 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.0862.v1

Mastering Air Combat Game With Deep Reinforcement Learning

Jingyu Zhu, Minchi Kuang, Wenqing Zhou, Heng Shi, Jihong Zhu, Hongli Zhang, Xinkai Li, Xun Han

Subject: Computer Science And Mathematics, Computer Science Keywords: Air combat; MCLDPPO; Interruption mechanism; Digital twin; Distributed system

Online: 11 May 2023 (13:42:45 CEST)

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Reinforcement learning is used for air combat problems in recent years, and the idea of curriculum learning is often used for reinforcement learning, but traditional curriculum learning suffers from the problem of plasticity loss in neural networks. Plasticity loss is the difficulty of learning new knowledge after the network has converged. To this end, we propose a motivational curriculum learning distributed proximal policy optimization (MCLDPPO) algorithm, through which agents trained can significantly outperform the predictive game tree and mainstream reinforcement learning methods. The motivational curriculum learning is to help the agent gradually improve their combat ability by observing the agent's unsatisfactory performance and providing corresponding rewards as a guide. Additionally, a complete tactical maneuver is encapsulated based on existing air combat knowledge, and through the flexible use of these maneuvers, some tactics beyond human knowledge can be realized. In addition, we designed an interruption mechanism for the agent to increase the frequency of decision-making when the agent faces an emergency. When the number of threats the agent receives changes, the current action will be interrupted to reacquire observations and make decisions again. Using the interruption mechanism can significantly improve the ability of the agent. To simulate actual air combat better, we built an air combat environment based on digital twin technology to create an air combat engine core such as missiles and radars. Based on this environment, we develop a distributed intelligent training system that employs Redis as the cache and obtains the data generated in the distributed environment through a multi-threaded TCP/IP protocol, which significantly increases the training data throughput and helps the agent accelerates convergence. The experimental results demonstrate that the agent can fully exploit the situational information to make reasonable decisions and affords air combat tactical adaption, verifying the effectiveness of the algorithmic framework proposed in this paper.

Preprint ARTICLE | doi:10.20944/preprints202305.0856.v1

Research on the Evaluation Model of School Management Quality in the Compulsory Education Stage Based on Big Data Technology

Guanghui Min, Muhui Lin, Ying Liu, Zhe Li

Subject: Computer Science And Mathematics, Computer Science Keywords: quality evaluation of school management; compulsory education stage; big data technology; visualization techniques; evaluation models

Online: 11 May 2023 (13:26:38 CEST)

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Preprint REVIEW | doi:10.20944/preprints202305.0839.v1

A Taxonomic Survey of Physics-Informed Machine Learning

Preetam Ghosh, Joseph Pateras, Pratip Rana

Subject: Computer Science And Mathematics, Computer Science Keywords: multiphysics modeling; physics-informed neural networks; physics-informed machine learning; data-driven machine learning

Online: 11 May 2023 (10:26:35 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.0740.v1

Non-Face-to-Face P2P (peer-to-peer) Real-time Token Payment Blockchain System

Hyug-Jun Ko, Seong-Soo Han

Subject: Computer Science And Mathematics, Computer Science Keywords: Blockchain; Symverse; Ethereum; Payment; gas; voice fishing; fin-tech

Online: 10 May 2023 (10:39:23 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.0525.v1

The Expansion of Data Science: Datasets Standardization

Nuno Pessanha Santos

Subject: Computer Science And Mathematics, Computer Science Keywords: datasets; standards; standardization; guidelines; framework; interoperability.

Online: 8 May 2023 (10:49:34 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.0145.v1

WASP - A Web Application to Support Syntactically and Semantically Correct SNOMED CT Postcoordination

Cora Drenkhahn, Tessa Ohlsen, Joshua Wiedekopf, Josef Ingenerf

Subject: Computer Science And Mathematics, Computer Science Keywords: Semantic interoperability; clinical terminology; SNOMED CT; biomedical ontology; postcoordination; expression templates

Online: 3 May 2023 (11:27:53 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.0118.v1

A Software Verification Method for Internet of Things and Cyber-Physical Systems

Yuriy Manzhos, Yevheniia Sokolova

Subject: Computer Science And Mathematics, Computer Science Keywords: CPS; IoT; software quality; physical dimension; physical orientation; formal verification; metaprogramming

Online: 3 May 2023 (08:47:27 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.0049.v1

Analysis of Concurrent Systems Based on Interval Order

Yang Xu, YE Chen, Chen Yi Jun

Subject: Computer Science And Mathematics, Computer Science Keywords: concurrent systems、,Mazurkiewicz traces、,interval order、,Petri net with Data

Online: 2 May 2023 (03:13:37 CEST)

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Preprint REVIEW | doi:10.20944/preprints202305.0036.v1

A Review of Transformer Fault Diagnosis Based on Information System Theory and Machine Learning

Xiaoli Huang, Yumiao Yuan, Jingyu Li

Subject: Computer Science And Mathematics, Computer Science Keywords: transformer fault diagnosis; information system theory; information entropy; machine learning

Online: 2 May 2023 (01:27:29 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202304.0678.v1

Experimental Design and Validation of an Adjustable Guide Grass Structure for a Grain Combine Harvester Thresher Based on a Material Movement Model

Luofa Wu, Daogen Chen, Xieqing Xu, Yanqi Wu

Subject: Computer Science And Mathematics, Computer Science Keywords: Motion model; Grain combine harvester; threshing device; guide grass

Online: 21 April 2023 (07:51:58 CEST)

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Threshing device is the core component of grain combine harvester, and its working performance determines the working quality and production efficiency of the harvester to a great extent. The straw guide plate plays an important role in the threshing device to dredge the threshing matter and control the threshing time of the combine harvester matter in the threshing chamber. In the past, the guiding structure of threshing device could not optimize the working performance of the machine by adjusting the spiral angle, that is, most cereal combine harvester may not be fed smoothly or even clogged when operating under different crop types, yield differences and operating environments, a kind of threshing device with adjustable guide straw board was studied. In this study, the movement model of the straw on the straw guide plate was analyzed, and it was found that the spiral angle “α”of the straw guide was 0<α<58°.Three-factor and three-level response surface method was used to carry out field experiment on drum speed, working speed and guide grass plate spiral angle, and the experimental data were analyzed by quadratic polynomial regression.The results show that the drum speed, working speed and the spiral angle of the guide grass plate have significant effects on the loss rate (PLR) , impurity content (PIR) and breakage rate (PBR) , the drum speed and working speed have an interactive effect on the impurity ratio (PIR) , and the working speed and the helical angle of the guide grass plate have an interactive effect on the loss ratio (PLR) and breakage ratio (PBR) , there is an interaction between the rotary speed of the roller and the helical angle of the guide grass plate on the crushing rate (PBR) .Further optimization analysis showed that the predicted value was PLR = 1.18% , PIR = 0.72% , PBR = 0.53% , the experimental verification value was PLR = 1.26% , PIR = 0.73% , PBR = 0.61% . The absolute error between the experimental value and the predicted value was very small, however, the optimized field test verified value decreased by 8.31% , 50.04% and 60.30% respectively, which indicated that the optimized harvester had better operation quality, in particular, PIR, PBR and other two indicators have a greater increase in the effect.

Preprint CASE REPORT | doi:10.20944/preprints202304.0437.v1

Self-Directed and Self-Designed Learning: Integrating Imperative Topics with Case - COVID-19

Alireza Ebrahimi

Subject: Computer Science And Mathematics, Computer Science Keywords: Self-Directed Learning,; Pedagogy,; Visualization Plan; Web Analysis,; Big Data; Pattern Matching; Covid-19

Online: 17 April 2023 (09:58:27 CEST)

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Preprint REVIEW | doi:10.20944/preprints202304.0426.v1

Literature Review: Clinical Data Interoperability Models

Rachida Ait Abdelouahid, Olivier Debauche, Saïd Mahmoudi, Abdelaziz Marzak

Subject: Computer Science And Mathematics, Computer Science Keywords: Internet of Medical Things (IoMT); data exchange: healthcare; medical data; interoperability

Online: 17 April 2023 (08:02:19 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202304.0007.v1

Utilizing Semi-structured Complex Numbers to Develop the First Division by Zero Calculator

Peter Jean Paul, Shanaz Wahid

Subject: Computer Science And Mathematics, Computer Science Keywords: Semi-structured complex numbers; Division by zero; computer science; Calculator; Exception handling

Online: 3 April 2023 (04:26:06 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202303.0545.v1

Surfaces Intersection and Flattening in 3D Models Through Computer Extended Descriptive Geometry (CeDG)

Manuel Prado-Velasco, Laura García-Ruesgas

Subject: Computer Science And Mathematics, Computer Science Keywords: Descriptive Geometry; Computer Graphic Parametric Modelling; CAD; CeDG; Dynamic Geometry Software

Online: 31 March 2023 (08:24:51 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202303.0322.v1

Peptide Hemolytic Activity Analysis using Visual Data Mining of Similarity-based Complex Networks

Kevin Castillo-Mendieta, Guillermin Agüero-Chapin, Nelson Santiago Vispo, Edgar A. Márquez, Yunierkis Perez-Castillo, Stephen J. Barigye, Yovani Marrero-Ponce

Subject: Computer Science And Mathematics, Computer Science Keywords: Hemolytic peptide; Network science; Half-Space Proximal Networks; Metadata Networks; Visual mining; Cluster analysis; Motif discovery; StarPep toolbox; Peptide drug discovery

Online: 17 March 2023 (10:05:05 CET)

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Preprint ARTICLE | doi:10.20944/preprints202302.0275.v2

An Efficient Gaussian Mixture Model and Its Application to Neural Network

Weiguo Lu, Deng Ding, Fengyan Wu, Gangnan Yuan

Subject: Computer Science And Mathematics, Computer Science Keywords: Neural Network, Uncertainties , GMM, Density approximation

Online: 16 March 2023 (02:21:19 CET)

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Preprint ARTICLE | doi:10.20944/preprints202303.0100.v1

1-Click Gamer Network Optimization Tool

Poh Soon JosephNg, Tze Hooi Ho, Koo Yuen Phan

Subject: Computer Science And Mathematics, Computer Science Keywords: Gaming; network optimization; troubleshooting & management

Online: 6 March 2023 (07:45:17 CET)

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Preprint ARTICLE | doi:10.20944/preprints202302.0317.v1

SBOannotator: a Python Tool for the Automated Assignment of Systems Biology Ontology Terms

Nantia Leonidou, Elisabeth Fritze, Alina Renz, Andreas Dräger

Subject: Computer Science And Mathematics, Computer Science Keywords: SBOannotator; ontologies; SBO terms; Python; software; automated assignment; computational modeling; systems biology

Online: 20 February 2023 (03:57:56 CET)

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Preprint ARTICLE | doi:10.20944/preprints202302.0299.v1

Using Ensemble Convolutional Neural Network to Detect Deepfakes Using Periocular Data

David Johnson, Xiaohonh Yuan, Kaushik Roy

Subject: Computer Science And Mathematics, Computer Science Keywords: deepfake detection; CNN; deep neural network; computer vision; scale invariant feature transform; histogram of oriented gradients

Online: 17 February 2023 (06:51:37 CET)

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Preprint ARTICLE | doi:10.20944/preprints202302.0275.v1

An Efficient Gaussian Mixture Model and It's Application to Neural Network

Weiguo Lu, Deng Ding, Fengyan Wu, Gangnan Yuan

Subject: Computer Science And Mathematics, Computer Science Keywords: Neural Network, Uncertainties , GMM, Density approximation

Online: 16 February 2023 (06:59:43 CET)

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Preprint ARTICLE | doi:10.20944/preprints202302.0092.v1

Analysis of Adaptive Algorithms Based on Least-Mean-Square Applied to Hand Tremors Suppression Control

Rafael Silfarney Alves Araújo, Jessica Cristina Tironi, Wemerson Delcio Parreira, Renata Coelho Borges, Juan Francisco De Paz Santana, Valderi Reis Quietinho Leithardt

Subject: Computer Science And Mathematics, Computer Science Keywords: Adaptive Algorithm; Tremor Suppression; LMS; Parkinson

Online: 6 February 2023 (09:09:01 CET)

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Preprint ARTICLE | doi:10.20944/preprints202302.0077.v1

aeroBERT-Classifier: Classification of Aerospace Requirements using BERT

Archana Tikayat Ray, Bjorn F. Cole, Olivia J. Pinon Fischer, Ryan T. White, Dimitri N. Mavris

Subject: Computer Science And Mathematics, Computer Science Keywords: Requirements Engineering; Natural Language Processing; NLP; BERT; Requirements Classification; Text Classification

Online: 6 February 2023 (02:26:56 CET)

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Preprint ARTICLE | doi:10.20944/preprints202302.0004.v1

Online Hybrid Neural Network for Stock Prices Prediction: A Case Study of High-frequency Stock Trading in China Market

Chengyu Li, Luyi Shen, Guoqi Qian

Subject: Computer Science And Mathematics, Computer Science Keywords: High-frequency Limit Order Book; Online Fast Prediction; Hybrid Neural Network

Online: 1 February 2023 (02:37:46 CET)

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Preprint ARTICLE | doi:10.20944/preprints202301.0502.v1

Flexible Working Memory Model in Spiking Neural Network With Two Types of Plasticity

Natalia S. Kovaleva, Valery V. Matrosov, Mikhail Mishchenko

Subject: Computer Science And Mathematics, Computer Science Keywords: working memory; STDP; short-term plasticity; spiking neural network; flexible cluster formation

Online: 27 January 2023 (10:32:08 CET)

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Preprint ARTICLE | doi:10.20944/preprints202301.0254.v1

Quickening Data-Aware Conformance Checking through Temporal Algebras

Giacomo Bergami, Samuel Appleby, Graham Morgan

Subject: Computer Science And Mathematics, Computer Science Keywords: Logic Artificial Intelligence; Knowledge Bases; Query Plan; Temporal Logic; Conformance Checking; Temporal Data Mining; Intraquery Parallelism

Online: 13 January 2023 (11:07:20 CET)

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Preprint ARTICLE | doi:10.20944/preprints202301.0030.v1

Implementing Playing Cards BlackJack Game using OpenCV

Tauheed Khan Mohd, Anas Akkar, Justin Cassens, Samuel Cregan, Maame Araba Vander-Pallen

Subject: Computer Science And Mathematics, Computer Science Keywords: OpenCV; Python; objects; object detection; card

Online: 3 January 2023 (09:40:17 CET)

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Preprint ARTICLE | doi:10.20944/preprints202212.0532.v1

DEHA-Net: Dual-Encoder based Hard Attention Network with Adaptive ROI Mechanism for Lung Nodule Segmentation

Muhammad Usman, Yeong Gil Shin

Subject: Computer Science And Mathematics, Computer Science Keywords: lung nodule segmentation; 3D segmentation; dual-encoder-based CNN; hard attention

Online: 28 December 2022 (09:03:49 CET)

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Preprint ARTICLE | doi:10.20944/preprints202212.0141.v1

Soil Moisture Prediction Based on the LSTM Neural Network Integrating Particle Swarm Optimization

Xiaoyi Huang, Jianlong Wu, Jizheng Chu

Subject: Computer Science And Mathematics, Computer Science Keywords: Soil moisture prediction; LSTM; PSO

Online: 8 December 2022 (02:28:04 CET)

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Preprint ARTICLE | doi:10.20944/preprints202211.0537.v2

Symmetric Encoding-decoding Framework without Backpropagation

Pengyuan Zhai

Subject: Computer Science And Mathematics, Computer Science Keywords: Backpropagation-free Network, Information Theory, Maximal Coding Rate Reduction

Online: 29 November 2022 (08:13:27 CET)

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Preprint ARTICLE | doi:10.20944/preprints202211.0537.v1

Symmetric Encoding-decoding Framework without Backpropagation

Pengyuan Zhai

Subject: Computer Science And Mathematics, Computer Science Keywords: Backpropagation-free Network, Information Theory, Maximal Coding Rate Reduction

Online: 29 November 2022 (07:07:56 CET)

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Preprint REVIEW | doi:10.20944/preprints202211.0531.v1

Current Technologies for Detection of COVID-19: Biosensors, Artificial Intelligence and Internet of Medical Things (IoMT): Review

Abdullahi Umar Ibrahim, Yeni Wahyuni Hartati, Chidi Wilson Nwenko, Fadi Al-Turjman

Subject: Computer Science And Mathematics, Computer Science Keywords: Biosensors; COVID-19; Artificial Intelligence; Computer-aided Detection (CAD) Internet of Medical Things (IoMT).

Online: 29 November 2022 (03:44:17 CET)

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Preprint ARTICLE | doi:10.20944/preprints202211.0495.v1

A Standardized Approach for Skin Detection: Analysis of the Literature and Case-Studies

Loris Nanni, Andrea Loreggia, Alessandra Lumini, Alberto Dorizza

Subject: Computer Science And Mathematics, Computer Science Keywords: skin classification; skin detection; skin segmentation; skin database; neural networks

Online: 28 November 2022 (05:16:35 CET)

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Preprint ARTICLE | doi:10.20944/preprints202211.0304.v1

CGAN Assists the Styles & Features Renovation of Street Facade —A Case Study of Wuyi Area in Fujian, China

Lei Zhang, Liang Zheng, Yile Chen, Lei Huang, Shihui Zhou

Subject: Computer Science And Mathematics, Computer Science Keywords: CGAN; Styles & Features Renovation; Street Façade; world heritage city; Wuyi area

Online: 16 November 2022 (09:55:23 CET)

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Preprint ARTICLE | doi:10.20944/preprints202211.0278.v1

LSTM Applied for Commodity Futures Price Forecast

Gabriel Schneider de Jesus, Aurélio Faustino Hoppe, Andreza Sartori, Valderi Reis Quietinho Leithardt

Subject: Computer Science And Mathematics, Computer Science Keywords: Long Short-Term Memory; time series forecasting; commodities; technical analysis

Online: 15 November 2022 (07:00:55 CET)

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Preprint ARTICLE | doi:10.20944/preprints202211.0115.v1

Simulation as a Tool for Understanding Experimental Observations --- Ion Beam Extraction from an ECRIS

Peter Spädtke

Subject: Computer Science And Mathematics, Computer Science Keywords: ECRIS; ion beam; extraction; ion beam transport; space-charge; simulation

Online: 7 November 2022 (10:06:02 CET)

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Preprint ARTICLE | doi:10.20944/preprints202211.0017.v1

Performance Comparison of TTS Models for Brazilian Portuguese to Establish a Baseline

Wilmer Lobato, Felipe Farias, William Cruz, Marcellus Amadeus

Subject: Computer Science And Mathematics, Computer Science Keywords: text-to-speech; naturalness; intelligibility; Brazilian Portuguese

Online: 1 November 2022 (04:37:04 CET)

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Preprint ARTICLE | doi:10.20944/preprints202210.0467.v1

Visual Abnormality Detection in Surface based on Energy Variations in Multi Direction Co-occurrence Matrixes

Faeze Kiani

Subject: Computer Science And Mathematics, Computer Science Keywords: abnormality detection; surface defect detection; feature extraction; gray level co-occurrence matrix; energy variations

Online: 31 October 2022 (06:26:06 CET)

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Preprint ARTICLE | doi:10.20944/preprints202210.0426.v1

Effective One-Class Classifier Model for Memory Dump Malware Detection

Mahmoud Al-Qudah, Zein Ashi, Mohammad Alnabhan, Qasem Abu Al-Haija

Subject: Computer Science And Mathematics, Computer Science Keywords: novelty-class; one online-Class SVM (OCSVM); memory dump; Malware; Principal Component Analysis (PCA); dimensionality reduction

Online: 27 October 2022 (08:17:43 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202210.0355.v1

A Lightweight Reconstruction Network for Surface Defect Inspection

Chao Hu, Jian Yao, Weijie Wu, Weiibin Qiu, Liqiang Zhu

Subject: Computer Science And Mathematics, Computer Science Keywords: Auto encoder; surface defects; abnormal defects; visual inspection; unsupervised defect

Online: 24 October 2022 (07:56:04 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202209.0366.v2

Evaluation of Domestic and Foreign Research Status in the Field of Engine Vibration Detection by Bibliometrics

Mai Xin, Zhifeng Ye, Xiong Pan, Xing Liu, Tong Zhang, Longlong Liu, Hailang Ge

Subject: Computer Science And Mathematics, Computer Science Keywords: Vibration Detection; Progress; Power Plant; Bibliometrics; Visual Analysis

Online: 17 October 2022 (10:50:11 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202210.0224.v1

Ensemble of Networks for Multilabel Classification

Loris Nanni, Luca Trambaiollo, Sheryl Brahnam, Xiang Guo, Chancellor Woolsey

Subject: Computer Science And Mathematics, Computer Science Keywords: multilabel; ensemble; incorporating multiple clustering centers; gated recurrent neural networks; temporal convolutional neural networks; long short-term memory

Online: 17 October 2022 (04:06:31 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202210.0197.v1

A Quantitative Assessment of Rubrics Using a Soft Computing Approach

Siddhartha Bhattacharyya, Sourav De, Leo Mrsic, Indrajit Pan, Khan Muhammad, Anirban Mukherjee, Debanjan Konar

Subject: Computer Science And Mathematics, Computer Science Keywords: OBE; OBTE; graduate attributes; rubrics; fuzzy sets.

Online: 14 October 2022 (02:18:02 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202210.0132.v1

Inner-cycle Phases can be Estimated from a Single Inertial Sensor by Long Short-term Memory Neural Network in Roller Ski Skating

Meyer Frédéric, Magne Lund-Hansen, Trine M. Seeberg, Jan Kocbach, Øyvind Sandbakk, Andreas Austeng

Subject: Computer Science And Mathematics, Computer Science Keywords: cross country skiing; IMU; wearable sensors; LSTM; neural network

Online: 11 October 2022 (03:04:09 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202210.0076.v1

Performance Analysis of the Impact of Time to Leave on Different Drop Policies for Delay Tolerant Networks

Siham Hasan, Ali H Al-Bayatti, Sarmadullah Khan, Youssef Harrati, El Arbi Abdellaoui Alaoui, Ali Algaddafi

Subject: Computer Science And Mathematics, Computer Science Keywords: Delay-Tolerant Network (DTNs); Vehicular Delay-Tolerant networks (VDTNs); Store Carries and Forward (SCF)

Online: 7 October 2022 (08:33:14 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202210.0027.v1

Terra Luna and the Future of Internet Investments: Towards a Framework for Investors’ Protections

Dimitar Kyosev, Dimitar Anastasovski, Mirko Kikovic, Orfefs Voutyras

Subject: Computer Science And Mathematics, Computer Science Keywords: cross-disciplinary; AI; blockchain; investment; protection

Online: 5 October 2022 (04:04:40 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202208.0440.v2

Empirical Network Structure of Malicious Programs

John Musgrave, Alina Campan, Temesguen Messay-Kebede, David Kapp, Anca Ralescu

Subject: Computer Science And Mathematics, Computer Science Keywords: malware analysis; graphs; network science; security

Online: 26 September 2022 (04:24:48 CEST)

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Preprint BRIEF REPORT | doi:10.20944/preprints202209.0366.v1

Evaluation of Domestic and Foreign Research Status in the Field of Engine Vibration Detection by Bibliometrics

Mai Xin, Zhifeng Ye, Xiong Pan, Xing Liu, Tong Zhang, Longlong Liu, Hailang Ge

Subject: Computer Science And Mathematics, Computer Science Keywords: Vibration Detection; Progress; Power Plant; Bibliometrics; Visual Analysis

Online: 23 September 2022 (09:24:21 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202209.0311.v1

A Dialogue System that Models User's Opinion Based on Information Content

Yoshiki Ohira, Takahisa Uchida, Takashi Minato, Hiroshi Ishiguro

Subject: Computer Science And Mathematics, Computer Science Keywords: opinion model; user modeling; information content; dialogue strategy; dialogue system

Online: 21 September 2022 (02:27:12 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202209.0276.v1

Towards Interpretable Camera and LiDAR data fusion for Unmanned Autonomous Vehicles Localisation

Haileleol Tibebu, Varuna De-Silva, Corentin Artaud, Rafael Pina, Xiyu Shi

Subject: Computer Science And Mathematics, Computer Science Keywords: Sensor fusion; Camera and LiDAR fusion; Odometry; Explainable AI

Online: 19 September 2022 (10:27:42 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202209.0210.v1

Few-Shot Continuous Authentication for Mobile-Based Biometrics

Kensuke Wagata, Andrew Beng Jin Teoh

Subject: Computer Science And Mathematics, Computer Science Keywords: continuous authentication; touch-gesture biometrics; few-shot anomaly detection; data augmentation; temporal convolution network

Online: 14 September 2022 (15:39:03 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202209.0008.v1

A Multi-agent Approach to Predict Long-Term Glucose Oscillation in Individuals with Type 1 Diabetes

João Paulo Aragão Pereira, Anarosa Alves Franco Brandão, Joyce da Silva Bevilacqua, Maria Lúcia Cardillo Côrrea-Giannella

Subject: Computer Science And Mathematics, Computer Science Keywords: Glucose Oscillation; Prediction; Multi-agent; Type 1 Diabetes; Personalized; Recommendation

Online: 1 September 2022 (07:13:20 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202208.0523.v1

A Novel Framework to Detect Irrelevant Software Requirements Based on MultiPhiLDA as the Topic Model

Daniel Siahaan, Brian Risqi Paradisiaca Darnoto

Subject: Computer Science And Mathematics, Computer Science Keywords: angle-based outlier detection: percentile-based outlier detection; multiphilda, noise; irrelevant software requirements

Online: 30 August 2022 (11:25:24 CEST)

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Preprint REVIEW | doi:10.20944/preprints202208.0483.v1

Digital-Twins Towards Cyber-Physical Systems: A Brief Survey

Amir Parnianifard, Lunchakorn Wuttisittikulkij

Subject: Computer Science And Mathematics, Computer Science Keywords: Digital Twins; Cyber-Physical Systems; Control; Communication; Computation; 5G; Artificial Intelligence; Machine Learning; Computational Intelligence

Online: 29 August 2022 (09:51:49 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202208.0440.v1

Empirical Network Structure of Malicious Programs

John Musgrave, Alina Campan, Temesguen Messay-Kebede, David Kapp, Anca Ralescu

Subject: Computer Science And Mathematics, Computer Science Keywords: malware analysis; graphs; network science; security

Online: 26 August 2022 (03:50:01 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202208.0377.v1

Persuasion Strategies in Advertisements: Dataset, Modeling, and Baselines

Yaman Singla, Rajat Jha, Arunim Gupta, Milan Aggarwal, Aditya Garg, Ayush Bhardwaj, Tushar -, Balaji Krishnamurthy, Rajiv Ratn Shah, Changyou Chen

Subject: Computer Science And Mathematics, Computer Science Keywords: persuasion; persuasion strategies; influence; advertising; advertisements, adobe

Online: 22 August 2022 (07:51:33 CEST)

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Preprint SHORT NOTE | doi:10.20944/preprints202208.0330.v1

Optima and Simplicity in Nature

Kamaludin Dingle

Subject: Computer Science And Mathematics, Computer Science Keywords: Optimisation; simplicity; Kolmogorov complexity; physics

Online: 18 August 2022 (03:51:21 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202208.0238.v1

A Simple Survey of Pre-trained Language Models

Zhenyi Zhu

Subject: Computer Science And Mathematics, Computer Science Keywords: NLP; PLTMs; benchmarks

Online: 12 August 2022 (11:43:50 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202208.0197.v1

An Ontological Knowledge Base of Poisoning Attacks on Deep Neural Networks

Majed Altoub, Fahad AlQurashi, Tan Yigitcanlar, Juan Corchado, Rashid Mehmood

Subject: Computer Science And Mathematics, Computer Science Keywords: Deep neural networks; Adversarial Attacks; Poisoning; Backdoors; Trojans; Taxonomy; Ontology; Knowledge Base; Explainable AI; Green AI

Online: 10 August 2022 (09:39:07 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202208.0188.v1

User Authentication and Authorization Framework in IoT Protocols

Hasan Al-refai, Ali Alawneh

Subject: Computer Science And Mathematics, Computer Science Keywords: Internet of Things; security protocol; authentication; authorization; networks

Online: 10 August 2022 (04:11:00 CEST)

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The Internet of Things (IoT) has become one of the most attractive domains nowadays. It works by creating a special network between physical devices such as vehicles, home equipment, and other items. In recent days, the common technologies of communication such as Wi-Fi and 2G/3G/4G cellular are insufficient for the IoT networks because they are designed to serve appliances with immense processing capabilities such as laptops and PCs. Moreover, most of these technologies are centralized and use an existing infrastructure. Currently, the new communication technologies such as Z-Wave, 6LowPAN, and Thread are dedicated to the IoT and have been developed to meet its requirements. These technologies can handle many factors such as range, data requirements, security, power demands, and battery life. Nevertheless, the security issues in IoT systems have major concerns and matters because vulnerabilities in such systems may result in fatal catastrophes. In this paper, an enhanced IoT security framework for authentication and authorization is proposed and implemented to protect the IoT protocols from different types of attacks such as man-in-the-middle attack, reply attack, and brute force attack. The proposed framework combines an enhanced token authentication that has identity verification capabilities and a new sender verification mechanism on the IoT device side based on time stamp, which in turn can mitigate the need for local identity verification methods in IoT devices. The proposed IoT security framework is tested using security analysis with different types of attacks compared with previous related frameworks. The analysis shows the high capability of the proposed framework to protect IoT networks against many types of attacks compared with current available security frameworks. Finally, the proposed framework is developed using Windows application to simulate the framework phases, check its validity through the real network, and calculate the payload time is adds.

Preprint ARTICLE | doi:10.20944/preprints202208.0044.v1

Fault Diagnosis Method for Aircraft EHA based on FCNN and MSPSO Hyperparameter Optimization

Xudong Li, Yanjun Li, Yuyuan Cao, Shixuan Duan, Xingye Wang, Zejian Zhao

Subject: Computer Science And Mathematics, Computer Science Keywords: Electro Hydrostatic Actuator; Fusion Convolutional Neural Networks; Particle Swarm Optimization; Gram Angle Difference Field

Online: 2 August 2022 (07:45:42 CEST)

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Preprint BRIEF REPORT | doi:10.20944/preprints202207.0407.v1

Anomaly Detection over Time Series Data

Zhenyi Zhu

Subject: Computer Science And Mathematics, Computer Science Keywords: Anomaly Detection; Time Series; EWMA

Online: 26 July 2022 (10:50:27 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202207.0308.v1

Multimodal Micro-video Classification Based on 3D Convolutional Neural Network

Yueyue Sun, Bin Chen, Fang Wei, Xinyue Chen, Qiang Gong, Peng Zhang

Subject: Computer Science And Mathematics, Computer Science Keywords: micro-video classification; 3D CNN; multi-modal

Online: 21 July 2022 (03:09:34 CEST)

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Along with the popularity of the Internet, people are exposed to more and more ways of micro-videos, and a huge amount of micro-video data has emerged. micro-videos have gradually become the Internet content preferred by the public, and a large number of micro-video apps have also emerged, such as Tiktok and Kwai. Intelligent classification and mining of micro-videos can greatly enhance user experience, improve business operation efficiency and enhance user experience. Through deep intelligent analysis and mining of micro-videos, important information in micro-videos can be extracted to provide an important basis for beautifying videos, content appreciation, video recommendation, content search, etc. In the past, content understanding for short videos often used human work annotation, but in recent years, with the great success of deep convolutional neural networks in image recognition, short video content understanding based on this method has gradually developed. Nowadays, most recognition algorithms extract the feature representation of each frame independently and then fuse them. However, while extracting the feature representation, some low-level semantic features are lost, which makes the algorithm unable to accurately distinguish the category of the video. At present, the algorithm of micro-video recognition based on deep learning has surpassed the iDT algorithm, making these traditional methods fade out of people’s view. In this paper according to the micro-video classification task, a new network model is proposed to concatenate features of each modality into the overall features of various modalities through the network, and then fuse the various modal features with the attention mechanism to obtain the whole micro-video features, which will be used for classification. In order to verify the effectiveness of the algorithm proposed in this paper, experiments are conducted in the public dataset, and it is shown the effectiveness of our model.

Preprint CONCEPT PAPER | doi:10.20944/preprints202207.0294.v1

Comparative Study of Convolution Neural Network with GLCM Approach and Superpixel based Spectral Clustering for Brain Tumor Detection

Gagandeep Kaur, Shivani Sharma

Subject: Computer Science And Mathematics, Computer Science Keywords: CNN; brain tumor; GLCM; segmentation; superpixel; spectral clustering

Online: 20 July 2022 (05:28:57 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202207.0283.v1

Impact of Information Technology on Society in the New Century

Muhammad Azam, Muhammad Nouman, Ahsan Rehman Gill

Subject: Computer Science And Mathematics, Computer Science Keywords: information technology; impact; society; future

Online: 19 July 2022 (09:50:27 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202207.0279.v1

Experiments with B92 Quantum Key Distribution Algorithm Implementation

Ayush Gopal

Subject: Computer Science And Mathematics, Computer Science Keywords: quantum cryptography; quantum physics; quantum key distribution (QKD); B92 protocol; eavesdropper detection method; qubit; photon polarization

Online: 19 July 2022 (07:10:30 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202207.0131.v1

Use of Deep Learning to Detect the Maternal Heart Rate and False Signals on Fetal Heart Rate Recordings

Samuel Boudet, Agathe Houzé de l'Aulnoit, Laurent Peyrodie, Romain Demailly, Denis Houzé de l'Aulnoit

Subject: Computer Science And Mathematics, Computer Science Keywords: fetal heart rate; maternal heart rate; cardiotocogram; gated recurrent unit; deep learning

Online: 8 July 2022 (05:01:43 CEST)

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We have developed deep learning models for automatic identification of the maternal heart rate (MHR) and, more generally, false signals (FSs) on fetal heart rate (FHR) recordings. The models can be used to preprocess FHR data prior to automated analysis or as a clinical alert system to assist the practitioner. Three models were developed and used to detect (i) FSs on the MHR channel (the FSMHR model), (ii) the MHR and FSs on the Doppler FHR sensor (the FSDop model), and (iii) FSs on the scalp ECG channel (the FSScalp model). The FSDop model was the most important because FSs are far more frequent on the Doppler FHR channel. All three models were based on a multilayer symmetric gated recurrent unit and were trained on data recorded during the first and second stages of delivery. The FSMHR and FSDop models were also trained on antepartum recordings. The training dataset contained 1030 expert-annotated periods (mean duration: 36 min) from 635 recordings. In an initial evaluation of routine clinical practice, 30 fully annotated recordings for each sensor type (mean duration: 5 h for MHR and Doppler sensors, and 3 h for the scalp ECG sensor) were analyzed.The sensitivity, positive predictive value (PPV) and accuracy were respectively 62.20%, 87.1% and 99.90% for the FSMHR model, 93.1%, 95.6% and 99.68% for the FSDop model, and the 44.6%, 87.2% and 99.93% for the FSScalp model. We built a second test dataset with a more solid ground truth by selecting 45 periods (lasting 20 min, on average) on which the Doppler FHR and scalp ECG signals were recorded simultaneously. Using the scalp ECG data, the experts estimate the true FHR value more reliably and thus annotated the Doppler FHR channel more precisely. The models achieved a sensitivity of 53.3%, a PPV of 62.4%, and an accuracy of 97.29%. In comparison, two experts (blinded to the scalp ECG data) achieved a sensitivity of 15.7%, a PPV of 74.3%, and an accuracy of 96.91% for expert 1 and a sensitivity of 60.7%, a PPV of 83.5% and an accuracy of 98.24% for expert 2; hence, the model performed better than one expert and worse than the other. Hence, the models performed at expert level, although a well-trained expert with good knowledge of FSs could probably do better in some cases. The models and datasets have been included in the Fetal Heart Rate Morphological Analysis open source MATLAB toolbox and can be used freely for research purposes.

Preprint ARTICLE | doi:10.20944/preprints202207.0070.v1

Indoor Scene Recognition via Object Detection and TF-IDF

Edvard Heikel, Leonardo Espinosa-Leal

Subject: Computer Science And Mathematics, Computer Science Keywords: scene recognition; object detection; scene classification; TF-IDF

Online: 5 July 2022 (08:38:17 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202207.0050.v1

The Leading Role of Digital Technologies in the Development of the Smart City Concept in Azerbaijan

Arzu Huseynova, Ophelya Mazanova

Subject: Computer Science And Mathematics, Computer Science Keywords: Smart City; smart technology; internet of things; cloud technologies; mobile applications; innovation system; smart city concept; smart ecosystem

Online: 4 July 2022 (10:18:11 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202207.0042.v1

A Novel Web-Based eMemo for Tertiary Institutions in Developing Nations: From Conceptualization to Implementation

Olusola Olabanjo

Subject: Computer Science And Mathematics, Computer Science Keywords: e-record; COVID-19 era; electronic memorandum; e-memo; ICT; university administration

Online: 4 July 2022 (08:51:23 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202206.0397.v1

Improve Ubiquitination-site Prediction Using Physicochemical Properties and Machine Learning with Grid Search

Xiaoye Mo, Samuel Cho, Xia Jiang

Subject: Computer Science And Mathematics, Computer Science Keywords: ubiquitination; ubiquitination-site; PCP; protein physicochemical properties; prediction; machine learning; grid search

Online: 29 June 2022 (07:48:46 CEST)

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ABSTRACT Background Ubiquitination plays an important role in protein post-translational processes and has been found to be involved in a number of regulatory functions including proteasome degradation, DNA repair, transcription, signal transduction, endocytosis, and sorting. As the identification of ubiquitination site is critical to furthering our understanding of the mechanism of ubiquitination, various experimental and machine learning methods have been used to conduct this task. It has been an important but challenging task to improve the accuracy of ubiquitination site prediction. In this research, we explore the possibility of improving the prediction performance of machine learning by incorporating grid search in the training process. Method We developed grid search procedures for each of six widely used machine learning methods including NB, LR, DT, SVM, LASSO, and KNN, and applied them to ubiquitination site prediction using the six PCP datasets that were previously developed. For each of the ML methods, we developed a set of values for each of the tunable hyperparameters available to the method. These sets of values then can be combined to form a large grid of hyperparameter settings, and each of these settings is used in the grid search. We integrated 5-fold cross-validation in grid search to train and test ML models and applied an additional independent validation procedure by conducting a pre-training 80-20 sample split. We evaluated the performance of the six methods by comparing them side by side for each of the six datasets. We also compared the grid search results with the results that were previously published without doing grid search. To optimize the prediction performance, we trained 1.1 million ML models in total through grid search. Results We compared the overall prediction performance of these six methods, as well as their prediction performance when working with balanced vs. imbalanced data, and large-scale vs. small-scale data. From the perspective of dataset, we find that the overall performance of every PCP dataset has been significantly improved in this study compared to the previous study, with the percentage increase of the average AUC of all six datasets ranging from 7.9% (PCP-4) up to 17.0% (PCP-1). From the perspective of method, we find that three out of four methods significantly benefit from grid search comparing to their previously published non-grid search results, with the maximum AUC improvement as high as 47% (LASSO on PCP-5), 43.3% (NB on PCP-1), and 33.7% (SVM on PCP-6). SVM overall ranks number one, followed by KNN as the number two performer based on their average AUCs on all datasets. But these two also ranked the top two (KNN 76 days and SVM 15 days) in terms of the total running time that they need to do grid search. We also find that SVM, KNN, and DT tend to handle small-scale and imbalanced datasets better, while LR, and LASSO are doing well with large-scale and balanced datasets. NB is more sensitive to data imbalance while less sensitive to the size of a dataset. Conclusions Our results show that using grid search has improved the performance of ubiquitination prediction significantly. We find that the performance of a method is closely related to its hyperparameter setting and the type of data it handles. Even though SVM is on average an outperformer, none of the methods can provide the best performance for all datasets. When sufficient computing resources are well accessible, grid search is an effective way to identify both a top performing model for a machine learning method and a suitable machine learning method for a particular dataset.

Preprint ARTICLE | doi:10.20944/preprints202206.0368.v1

A 3DCNN-LSTM Multi-Class Temporal Segmentation for Hand Gesture Recognition

Letizia Gionfrida, Wan M.R. Rusli, Angela E. Kedgley, Anil A. Bharath

Subject: Computer Science And Mathematics, Computer Science Keywords: hand gesture classification; transfer learning; three-dimensional convolutional; LSTM network

Online: 27 June 2022 (13:36:40 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202206.0315.v1

Transformers Improve Breast Cancer Diagnosis from Unregistered Multi-View Mammograms

Xuxin Chen, Ke Zhang, Ximin Wang, Neman Abdoli, Patrik W. Gilley, Hong Liu, Bin Zheng, Yuchen Qiu

Subject: Computer Science And Mathematics, Computer Science Keywords: Transformer; mammogram; multi-view; self-attention; computer-aided diagnosis; breast cancer; classification; deep learning

Online: 22 June 2022 (10:11:58 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202206.0217.v1

A Frame Work Design of Chicken-Sine Cosine Algorithm-based Deep Belief Network for Lung Nodule Segmentation and Cancer Detection

Beena Bethel GN, N. Sirisha, B. Kezia Rani, Srikanth Bethu

Subject: Computer Science And Mathematics, Computer Science Keywords: Chicken-sine Cosine algorithm; Deep Belief Network; Lung nodule detection

Online: 15 June 2022 (09:02:28 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202206.0112.v1

A Comparison of Computer-Aided Diagnosis Schemes Optimized Using Radiomics and Deep Transfer Learning Methods

Gopichandh Danala, Sai Kiran Maryada, Warid Islam, Rowzat Faiz, Meredith Jones, Yuchen Qiu, Bin Zheng

Subject: Computer Science And Mathematics, Computer Science Keywords: computer-aided diagnosis (CAD) schemes; radiomics; deep transfer learning; breast lesion classi-fication; assessment of CAD performance

Online: 8 June 2022 (04:01:03 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202206.0079.v1

Improving RENet by Introducing Modified Cross Attention for Few-Shot Classification

Ching-Han Chang, Tian-Li Yu

Subject: Computer Science And Mathematics, Computer Science Keywords: few-shot classification; attention

Online: 6 June 2022 (09:42:13 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202205.0147.v1

Predicting Climatic Variables on Local Level with SARIMA, LSTM and Hybrid Techniques

Antonios Parasyris, George Alexandrakis, Georgios V. Kozyrakis, Katerina Spanoudaki, Nikolaos A. Kampanis

Subject: Computer Science And Mathematics, Computer Science Keywords: SARIMA; Artificial Neural Networks (ANN); LSTM; hybrid methodologies; prediction

Online: 11 May 2022 (05:50:41 CEST)

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The choice of holiday destinations is highly depended on climate considerations. Nowadays, since the effects of climate crisis are being increasingly felt, the need of accurate weather and climate services for hotels is crucial. Such a service could be beneficial for both the future planning of tourists’ activities and destinations and for hotel managers as it could help in decision making about the planning and expansion of the touristic season, due to a prediction of higher temperatures for a longer time span, thus causing increased revenue for companies in the local touristic sector. The aim of this work is to calculate predictions on climatic variables using statistical techniques as well as Artificial Intelligence (AI) for a specific area of interest utilising data from in situ meteorological station, and produce valuable and reliable localised predictions with the most cost-effective method possible. This investigation will answer the question of the most suitable prediction method for time series data from a single meteorological station that is deployed in a specific location. As a result, an accurate representation of the microclimate in a specific are is achieved. To achieve this high accuracy in situ measurements and prediction techniques are used. As prediction techniques, Seasonal Auto Regressive Integrated Moving Average (SARIMA), AI techniques like the Long-Short-Term-Memory (LSTM) Neural Network and hybrid combinations of the two are used. Variables of interest are divided in the easier to predict temperature and humidity that are more periodic and less chaotic, and the wind speed as an example of a more stochastic variable with no known seasonality and patterns. Our results show that the examined Hybrid methodology performs the best at temperature and wind speed forecasts, closely followed by the SARIMA whereas LSTM perform better overall at the humidity forecast, even after the correction of the Hybrid to the SARIMA model.

Preprint ARTICLE | doi:10.20944/preprints202205.0134.v1

Will Artificial Intelligence Become Conscious? Can Thermodynamics Explain the Evolution of Intellect?

Eva Deli

Subject: Computer Science And Mathematics, Computer Science Keywords: deep neural networks; artificial intelligence; intelligent computation; orthogonal transformation; entropy; Carnot cycle

Online: 10 May 2022 (10:05:26 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202205.0016.v1

State-of-the-art in Open-domain Conversational AI: A Survey

Tosin Adewumi, Foteini Liwicki, Marcus Liwicki

Subject: Computer Science And Mathematics, Computer Science Keywords: conversational systems; chatbots; SotA

Online: 4 May 2022 (14:19:47 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202204.0234.v1

Automatic Detection of Stop Words for Texts in the Uzbek Language

Khabibulla Madatov, Shukurla Bekchanov, Jernej Vičič

Subject: Computer Science And Mathematics, Computer Science Keywords: stop word detection; Uzbek language; agglutinative language; algorithm

Online: 26 April 2022 (10:30:54 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202204.0227.v1

Allowing Differently Strong Chess Players to Play at An Equal Level

Arend Hintze

Subject: Computer Science And Mathematics, Computer Science Keywords: chess; elo; evaluation; equal play; handicap

Online: 26 April 2022 (04:41:40 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202204.0033.v1

Face Spoof Attack Detection using Deep Background Subtraction

Azeddine Benlamoudi, Salah Eddine Bekhouche, Maarouf Korichi, Khaled Bensid, Abdeldjalil Ouahabi, Abdenour Hadid, Abdelmalik Taleb-Ahmed

Subject: Computer Science And Mathematics, Computer Science Keywords: Biometrics; Face spoofing; CNN; BS; ResNet-50

Online: 6 April 2022 (07:55:23 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202204.0027.v1

A Network Embedding Approach for Annotating Protein Structures

Barbara Puccio, Luisa Di Paola, Ugo Lo Moio, Pierangelo Veltri, Pietro Hiram Guzzi

Subject: Computer Science And Mathematics, Computer Science Keywords: Protein Contact Network

Online: 5 April 2022 (12:02:35 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202204.0026.v1

SATLabel: A Framework for Sentiment and Aspect Terms Based Automatic Topic Labeling

Khandaker Tayef Shahriar, Mohammad Ali Moni, Mohammed Moshiul Hoque, Muhammad Nazrul Islam, Iqbal H. Sarker

Subject: Computer Science And Mathematics, Computer Science Keywords: Data-driven Framework; LDA; Sentiment Terms; Aspect Terms; Unigrams; Soft Cosine Similarity; Topic; Automatic labeling

Online: 5 April 2022 (11:58:02 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202203.0172.v1

SCD: Stacked Carton Scene Detection

Jinrong Yang, Shengkai Wu, Lijun Gou, Hangcheng Yu, Chenxi Lin, Jiazhuo Wang, Pan Wang, Minxuan Li, Xiaoping Li

Subject: Computer Science And Mathematics, Computer Science Keywords: object detection; larger-scale dataset; stacked carton

Online: 11 March 2022 (15:48:23 CET)

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Preprint ARTICLE | doi:10.20944/preprints202202.0346.v1

Crypto-Preservation and the Ghost of Andy Warhol

Jon Ippolito

Subject: Computer Science And Mathematics, Computer Science Keywords: digital art; Andy Warhol; Yves Klein; Pop art; blockchain; NFT; digital preservation; variable media; authenticity; net-worked storage; migration; cryptocurrency; Amiga

Online: 28 February 2022 (03:29:03 CET)

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Preprint ARTICLE | doi:10.20944/preprints202202.0326.v1

A Dynamic Mechanistic Model of Perceptual Binding

Pavel Kraikivski

Subject: Computer Science And Mathematics, Computer Science Keywords: Binding Problem; Perceptual Binding; Consciousness; Perception

Online: 25 February 2022 (08:46:39 CET)

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Preprint ARTICLE | doi:10.20944/preprints202202.0282.v1

FastTest Plugin: a New Plugin to Generate Moodle Quiz XML Files

Milagros Huerta, Manuel Alejandro Fernandez-Ruiz

Subject: Computer Science And Mathematics, Computer Science Keywords: content creation tools; plugin; Moodle; e-learning technologies; LMS; XML file; quiz

Online: 22 February 2022 (16:23:33 CET)

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Preprint ARTICLE | doi:10.20944/preprints202202.0234.v1

Disinformation in Social Networks and Bots: Simulated Scenarios of Its Spread from System Dynamics

Alfredo Guzmán Rincón, Ruby Lorena Carrillo Barbosa, Nuria Segovia-García, David Ricardo Africano-Franco

Subject: Computer Science And Mathematics, Computer Science Keywords: Disinformation; social networks; bots; model

Online: 18 February 2022 (11:37:09 CET)

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Preprint ARTICLE | doi:10.20944/preprints202202.0233.v1

Ethical Issues in AI-enabled Disease Surveillance: Perspectives from Global Health

Ann Borda, Andreea Molnar, Cristina Neesham, Patty Kostkova

Subject: Computer Science And Mathematics, Computer Science Keywords: AI; disease surveillance; pandemics; global public health; ethics

Online: 18 February 2022 (10:36:04 CET)

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Preprint ARTICLE | doi:10.20944/preprints202202.0111.v1

Wearable Sensor Based Human Activity Recognition with Transformer

Iveta Dirgová Luptáková, Martin Kubovčík, Jiří Pospíchal

Subject: Computer Science And Mathematics, Computer Science Keywords: Transformer; human activity recognition; time series; sequence-to-sequence prediction

Online: 8 February 2022 (13:09:21 CET)

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Preprint ARTICLE | doi:10.20944/preprints201902.0252.v3

Optimal Covert Communication Technology

Moses Okello

Subject: Computer Science And Mathematics, Computer Science Keywords: Steganography; Cryptography; Algorithm; Combinatorial; Permutation

Online: 31 January 2022 (12:57:32 CET)

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Preprint ARTICLE | doi:10.20944/preprints202112.0132.v3

Mind Your Outcomes: The ∆Q approach to Quality-Centric Systems Development and Its Application to a Blockchain Case-Study

Seyed Hossein HAERI, Peter Thompson, Neil Davies, Peter Van Roy, Kevin Hammond, James Chapman

Subject: Computer Science And Mathematics, Computer Science Keywords: formal semantics; quality attenuation; distributed systems; system design; scalability; performance; feasibility; blockchain; ΔQ.

Online: 24 January 2022 (11:43:32 CET)

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Preprint ARTICLE | doi:10.20944/preprints202201.0313.v1

Event-Based Clustering with Energy Data

Kieran Greer, Yaxin Bi

Subject: Computer Science And Mathematics, Computer Science Keywords: stochastic clustering; energy prediction; disaggregation

Online: 20 January 2022 (20:40:54 CET)

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Preprint COMMUNICATION | doi:10.20944/preprints202201.0246.v1

High precision voltage measurement for optical quantum computation

Kamil Wereszczyński, Agnieszka Michalczuk, Marcin Paszkuta, Jacek Gumiela

Subject: Computer Science And Mathematics, Computer Science Keywords: quantum computing; quantum optics; quantum optimization; photon entanglement; coincidence measure; photodiodes current measure; voltage measurement

Online: 17 January 2022 (17:27:41 CET)

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Preprint ARTICLE | doi:10.20944/preprints202201.0018.v1

Guidance to Pre-tokeniztion for SacreBLEU: Meta-Evaluation in Korean

Ahrii Kim, Jinhyun Kim

Subject: Computer Science And Mathematics, Computer Science Keywords: NMT Evaluation, Meta-Evaluation, SacreBLEU, Korean

Online: 4 January 2022 (20:24:43 CET)

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Computer Science and Mathematics