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2023 IEEE International Conference on Big Data, BigData 2023

作者： Marek, Dariusz Paszkuta, Marcin Szygula, Jakub Biernacki, Piotr Domanski, Adam Szczygiel, Marta Krol, Marcel Wojciechowski, Konrad Silesian University of Technology Dept. of Distributed Systems and Informatic Devices Warsaw Poland Polish-Japanese Academy of Information Technology ul. Koszykowa 86 Warsaw02-008 Poland Silesian University of Technology Dept. of Computer Graphics Vision and Digital Systems Warsaw Poland Institute of Theoretical and Applied Informatics Polish Academy of Sciences Warsaw Poland Silesian University of Technology Warsaw Poland

ISBN: (纸本)9798350324457

In the presented paper, detailed schematics and descriptions concerning communication in the context of swarm drone control are introduced. Methods and technologies behind them are discussed. The implementation of the presented concept was verified through a series of tests. Simulation results which confirm the effectiveness and efficiency of the proposed solutions are presented. The obtained results prove the correctness implementation of the presented methods and also demonstrate the benefits derived from the proposed approach. The presented concept of controlling a swarm of drones represents the current state of knowledge and technology in the field of drones and their control. By utilizing advanced communication technologies, positioning, and analysis of communication structures, this work makes a significant contribution to the UAV (Unmanned Aerial Vehicle) field. © 2023 IEEE.

关键词： Control Concepts Industrial Environment Industry 4.0 simulation environments Swarm of Drones UAV

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A Tangible E-Learning Solution for Early Childhood Development 13

A Tangible E-Learning Solution for Early Childhood Developme...

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13th International Conference on Computing Communication and Networking Technologies, ICCCNT 2022

作者： Cholitha Hettiarachchi, Thiwanka Sathyajith Semasinghe, Lakisuru De Silva, Rajitha Lokuliyana, Shashika Gamage, Narmada Ratnasuriya, Manisha Sri Lanka Institute of Information Technology Dept. of Computer Systems Engineering Sri Lanka University of Lincoln United Kingdom

ISBN: (数字)9781665452625

ISBN: (纸本)9781665452625

Exploration and manipulation of physical objects are essential for early childhood learning. TangiGuru is an e-Learning platform that allows children to engage with real-world physical objects to provide that essential experience within an e-Learning application. TangiGuru consists of 12 tangible, manipulative objects known as TangiCubes, which are used as a tangible user interface between children and the e-Learning application. It can carry out cognitive learning activities related to colors, languages, shapes and basic math by dynamically varying assigned values by changing the external appearance of TangiCubes. This dynamic nature of the TangiCubes makes it possible to use the same tangibles with endless possibilities compared to traditional tangible learning solutions with static value for each tangible. With the initial observations of how children interact with computers, laptops, and mobile devices, the goal is to provide a playful interface for children by taking the approach to embedding and integrating technology into the children's daily activities. After the prototyping phase, children were evaluated with the traditional tangible learning solutions compared to TangiGuru. They concluded that the more interactive tangible interfaces could make the children perform activities more engagingly. © 2022 IEEE.

关键词： E-learning

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Physics-Based Spatio-Temporal Modeling With Machine Learning for the Prediction of Oceanic Internal Waves 19

Physics-Based Spatio-Temporal Modeling With Machine Learning...

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2022 IEEE SmartWorld, 19th IEEE International Conference on Ubiquitous Intelligence and Computing, 2022 IEEE International Conference on Autonomous and Trusted Vehicles Conference, 22nd IEEE International Conference on Scalable Computing and Communications, 2022 IEEE International Conference on Digital Twin, 8th IEEE International Conference on Privacy Computing and 2022 IEEE International Conference on Metaverse, SmartWorld/UIC/ATC/ScalCom/DigitalTwin/PriComp/Metaverse 2022

作者： Wu, Song Zhang, Xiaojiang Dong, Wei Wang, Senzhang Li, Xiaoyong Bao, SenLiang Li, Kai National University of Defense Technology Dept. College of Computer Science and Technology Changsha China National University of Defense Technology Dept. College of Meteorology and Oceanography Changsha China Central South University School of Computer Science and Engineering Changsha China National University of Defense Technology Dept. College of Systems Engineering Changsha China

ISBN: (纸本)9798350346558

Accurately predicting the occurrence of oceanic internal waves in the northeastern South China Sea is of great importance to marine ecosystems, and economy. The traditional physics-based models for monitoring the occurrence of internal waves require complex parameterization, and the partial differential equations (PDEs) are relatively difficult to solve. The emergence of integrating physical knowledge and data-driven models brings light to solving the problem, which improves interpretability and meets the physical consistency. It not only inherits the advantages of machine learning in massive data processing but also makes up for the 'black box' characteristics. In this paper, we propose a physics-based spatio-temporal data analysis model based on the widely used LSTM framework to achieve oceanic internal wave prediction. The results show higher prediction accuracy compared with the traditional LSTM model, and the introduction of physical laws can improve data utilization while enhancing interpretability. © 2022 IEEE.

关键词： Forecasting

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Detection of Autism Spectrum Disorder in Children Using Efficient Pre-Processing and Machine Learning Techniques

Detection of Autism Spectrum Disorder in Children Using Effi...

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Decision Aid Sciences and Application (DASA), International Conference on

作者： Anas D. Sallibi Khattab M. Ali Alheeti Dept. dept. of Computer Sciences College of Computer and Information Technology (University of Anbar) Anbar Iraq Dept. of Computer Networking Systems College of Computer and Information Technology (University of Anbar) Anbar Iraq

Early diagnosis of the brain condition known as autism spectrum disorder (ASD) could significantly reduce the high healthcare costs typically involved with treating ASD. Autism's fiscal toll emphasizes the importance of developing easy and effective detection instruments. Therefore, a quick ASD evaluation is essential to helping healthcare professionals and letting people know if they should seek a formal clinical diagnosis. Currently, there are very few autism datasets related to screening accessible, most of which are based on genetics. To expose critical information about autism screening, this work suggests applying a novel machine learning framework that contains vital characteristics and performing predictive analysis utilising a Support vector machine, logistic regression, K-nearest neighbour, and random forest. The main objective of this study is to develop a system for the early detection of children at risk for autism spectrum disorders (ASD).

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A Novel Classification of Attacks on Blockchain Layers: Vulnerabilities, Attacks, Mitigations, and Research Directions

arXiv

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arXiv 2024年

作者： Dwivedi, Kaustubh Agrawal, Ankit Bhatia, Ashutosh Tiwari, Kamlesh Dept. of Computer Science and Information Systems Birla Institute of Technology and Science Pilani333031 India

The widespread adoption of blockchain technology has amplified the spectrum of potential threats to its integrity and security. The ongoing quest to exploit vulnerabilities emphasizes how critical it is to expand on current research initiatives. Thus, using a methodology based on discrete blockchain layers, our survey study aims to broaden the existing body of knowledge by thoroughly discussing both new and known attack vectors inside the blockchain ecosystem. This survey proposes a novel classification of blockchain attacks and an in-dept. investigation of blockchain data security. In particular, the paper provides a thorough discussion of the attack techniques and vulnerabilities that are specific to each tier, along with a detailed look at mitigating techniques. We reveal the deep dynamics of these security concerns by closely investigating the fundamental causes of attacks at various blockchain tiers. We clarify mitigation methods for known vulnerabilities and offer new information on recently developed attack vectors. We also discuss the implications of quantum computing in blockchain and the weaknesses in the current technology that can be exploited in the future. Our study advances the field of blockchain security and privacy research while also contributing to our understanding of blockchain vulnerabilities and attacks. This survey paper is a useful tool for readers who want to learn more about the intricacies of blockchain security. It also invites researchers to help strengthen blockchain privacy and security, paving the way for further developments in this dynamic and ever-evolving field. Copyright © 2024, The Authors. All rights reserved.

关键词： Blockchain

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Email Armour: A Multi-Layered Email Defense Solution

Email Armour: A Multi-Layered Email Defense Solution

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International Conference on Information technology Research (ICITR)

作者： K.T.A.U Lakmal L.M.C Perera S.P.K Padmika S.P.A De Silva Dinithi Pandithage Deemantha Siriwardana Dept. computer systems engineering Sri Lanka institute of information technology Malabe Sri Lanka

ISBN: (数字)9798331511425

ISBN: (纸本)9798331511432

Phishing and spam emails are evolving threats in today's digital landscape, posing significant risks to small and medium-sized businesses (SMBs). Despite the growing demand for email security solutions, SMBs often face barriers such as high costs and complexity. To address this gap, this study introduces a cost-effective, multi-layered email security solution leveraging machine learning. The proposed system comprises four core components: (1) spam detection using natural language processing (NLP) to analyze email content, (2) phishing URL and QR code detection by identifying malicious patterns and attributes, (3) attachment security analysis to detect malware and harmful scripts, and (4) suspicious URL detection focusing on JavaScript obfuscation. The model was trained and validated on publicly available datasets, achieving an overall accuracy of 85% and demonstrating effectiveness in identifying diverse email threats. Designed as an email client, this tool empowers SMBs to secure communication with an accessible and robust defense against email-based attacks

关键词： Uniform resource locators Unsolicited e-mail Phishing Focusing Machine learning QR codes Natural language processing Malware Security Information technology

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SB-AGT: A stochastic beam search-enhanced attention-based Gumbel tree framework for drug-drug interaction extraction from biomedical literature

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computers in Biology and Medicine 2025年 189卷 110011-110011页

作者： Saad, Eman Kishk, Sherif Ali-Eldin, Amr Saleh, Ahmed I. Communication and Information Technology Center Mansoura University Egypt Electronics and Communication Engineering Dept. Mansoura University Egypt Computer Engineering & Control Systems Dept. Mansoura University Egypt

Drug-Drug Interactions (DDI) and Chemical-Protein Interactions (CPI) detection are crucial for patient safety, as unidentified interactions may lead to severe Adverse Drug Reactions (ADRs). While extensive DDI and CPI information exists within biomedical literature, manual extraction by experts proves time-intensive and resource-demanding. This study presents SB-AGT: Stochastic Beam Search-enhanced Attention-based Gumbel Tree an innovative approach to automated DDI and CPI extraction through an attention-based architecture incorporating a modified Gumbel-Tree method with stochastic beam search optimization. SB-AGT leverages multi-head attention mechanisms and enhanced latent tree structures to effectively capture complex syntactic features and drug relationship patterns. Also, the methodology includes comprehensive preprocessing protocols and addresses dataset imbalance through hybrid sampling techniques. Experimental validation on the DDIExtraction 2013 and CHEMPROT datasets demonstrates the model's effectiveness, achieving precision, surpassing traditional approaches and showing competitive performance compared to contemporary pre-trained models. Through parametric analysis, we establish optimal beam search configurations that maximize the model's extraction accuracy. © 2025 Elsevier Ltd

关键词： Stochastic models

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On the (in)Security and Weaknesses of Commonly Used Applications on Large-Scale Distributed systems 24

On the (in)Security and Weaknesses of Commonly Used Applicat...

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24th International Conference on Control systems and computer Science, CSCS 2023

作者： Abate, Andrea Francesco Castiglione, Aniello Cimmino, Lucia De Angelis, Davide Flauto, Sara Volpe, Alberto University of Salerno Department of Computer Science Fisciano Italy University of Salerno Dept. of Management and Innovation Systems Fisciano Italy University of Naples Parthenope Department of Science and Technology Naples Italy

ISBN: (纸本)9798350313390

The modern use of communication, the information they contain and their protection at all stages (creation, storage, sending and receiving) have resulted in infrastructures that exponentially grow year by year and that must be accurately protected if we want to communicate with our interlocutors without others interfering (on purpose or unintentionally), intercepting, modifying or damaging our communication fraudulently. Today most of the information flowing over the Internet is transported over large-scale distributed systems by the secure version of the HTTP protocol (the HTTPS protocol). The use of Cryptography within the HTTPS protocol provides a fair level of security that makes users sleep peacefully and, even worse/better (depending on the point-of-view), trust the entire communication flow passing through the large-distributed systems. The paper shows how it is possible to analyze web applications that use the TLS protocol for protecting the communications, with the main purpose of doing reverse engineering on it and try to do a kind of Vulnerability Assessmentaimed at improving the security of such web applications. Authors discovered serious flaws in several large-scale distributed systems/applications: those flaws were exploited for reading and modifying messages sent over a secure HTTPS communication channel or, on the other side, that can be used for understanding the inner functioning of a given application. Authors show that it is quite common to see login/passwords in clear-text going back and forth over the network. Last but not least, the proposed approach undermines the basis of the mutual trust between institutions when such trust is based on the principle of the federated identity within institutions. © 2023 IEEE.

关键词： Network security

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HisDataTJ: ImageJ Plugin for Global Thresholding with Application in Bread Porosity Evaluation 3

HisDataTJ: ImageJ Plugin for Global Thresholding with Applic...

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3rd International Conference on Communications, Information, Electronic and Energy systems, CIEES 2022

作者： Bosakova-Ardenska, A.D. Danev, A. Gogova, T. University of Food Technologies Dept. of Computer Systems And Technologies Plovdiv Bulgaria University of Food Technologies Dept. of Technology of Cereals Fodder Bread And Confectionery Products Plovdiv Bulgaria

ISBN: (数字)9781665491495

ISBN: (纸本)9781665491495

It is developed a plugin for ImageJ that performs global thresholding through four innovative thresholding algorithms, which are designed last five years. These algorithms are HisMedian, SubMedian-1, SubMedian-2, and HisAnalysis. The algorithm SubMedian-2 uses secondary median value in the sub-histogram as a threshold and it is applied for white bread porosity evaluation. The algorithm HisAnalysis uses as a threshold a color with maximal frequency in image histogram and it is applied for brown bread porosity evaluation. It is implemented also an algorithm (MedHASM-2) that combines methods for threshold finding which are used by HisAnalysis and SubMedian-2 algorithms. This paper presents a research of possibilities for application of global thresholding algorithms in wheat bread type "Dobrudzha"porosity evaluation. Four samples of different brands of wheat bread are used for experiments. The porosity of tested samples is measured through physicochemical analysis. The results are compared with results of image processing through correlation analysis. The highest correlation coefficients are calculated for results of thresholding with algorithms HisAnalysis and MedHASM-2. Based on the results of statistical data processing it is proposed an equation for calculation of the bread porosity using the ratio of white pixels to all in binary images. The average error for bread porosity calculated with the proposed equation is about 1% using the algorithm MedHASM-2 and about 3% using the algorithm HisAnalysis. © 2022 IEEE.

关键词： Porosity

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Predicting Lifespan of Ground-to-Air Multipath Components in mmWave UAV Channels

arXiv

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arXiv 2025年

作者： Khawaja, Wahab Jacobsen, Rune H. Hussain, Sajid Guvenc, Ismail Dept. Electrical and Computer Engineering Aarhus University Aarhus8000 Denmark Dept. Computer Systems Engineering Mirpur Univ. Science and Technology AJK Mirpur10250 Pakistan

In mobile ground-to-air (GA) propagation channels, the birth and death of multipath components (MPCs) are frequently observed, and the wide-sense stationary uncorrelated scattering (WSSUS) assumption does not always hold. Several methods exist for tracking the birth and death of MPCs, however, to the best of knowledge of authors, there is no existing literature that addresses the prediction of the lifespan of the MPCs in non-WSSUS GA propagation channels. In this work, we consider the GA channel as non-WSSUS and individual MPCs across receiver positions are represented as time series based on the Euclidean distance between channel parameters of the MPCs. These time series representations, referred to as path bins, are analyzed using a semi-Markov chain model. The channel parameter variations and dependencies between path bins are used to predict the lifespan of path bins using weighted sum method, machine learning classifiers, and deep neural networks. For comparison, the birth and death of path bins are also modeled using a Poisson distribution and a Markov chain. Simulation results demonstrate that deep neural networks offer highly accurate predictions for the lifespan (including death) of MPC path bins in the considered GA propagation scenario. © 2025, CC BY.

关键词： Markov chains

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