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5th International Conference on engineering Technology and its Applications, IICETA 2022

作者： Waleed, Jumana Almaameri, Ihab Mahdi Abduldaim, Areej M. Al-Azzawi, Waleed University of Diyala College of Science Department of Computer Science Iraq The Islamic University College of Technical Engineering Department of Computer Technical Engineering Najaf54001 Iraq University of Technology Mathematics and Computer Applications Applied Sciences Department Baghdad Iraq Al-Farahidi University Medical Technical College Baghdad Iraq

ISBN: (纸本)9781665472159

With the evolution of social networks, the necessitate of providing information security methods becomes increasingly significant. Therefore, these methods should be studied and analyzed for presenting more secure and appropriate techniques. Since the images represent the most common and widely utilized visual formats, an optimized approach of image steganography based on algebraic matrix decomposition has been proposed in this paper. In particular, matrix decomposition methods represent a significant tool for increasing the security of the whole blent of digital steganographic approaches. In this paper, two stages of the Hessenberg matrix decomposition are implemented on the original image using modulo operation to show the impact of the matrix decomposition in the steganographic process. Additionally, a Chameleon Swarm optimization (CSO) algorithm is utilized to appoint the optimal positions in the embedding stage. The obtained results have been evaluated to show the difference between the utilization of decomposition or not. © 2022 IEEE.

关键词： Matrix algebra

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A Deep Multi-Task Learning Network for Activity Recognition and User Identification Using Smartphone Sensors

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Procedia computer Science 2025年 256卷 1350-1357页

作者： Sakorn Mekruksavanich Wikanda Phaphan Anuchit Jitpattanakul Department of Computer Engineering School of Information and Communication Technology University of Phayao Phayao 56000 Thailand Research Group in Statistical Learning and Inference Department of Applied Statistics Faculty of Applied Science King Mongkut’s University of Technology North Bangkok Bangkok 10800 Thailand Intelligent and Nonlinear Dynamic Innovations Research Center Department of Mathematics Faculty of Applied Science King Mongkut’s University of Technology North Bangkok Bangkok 10800 Thailand

Human activity recognition (HAR) and user identification utilizing smartphone sensors are crucial in domains such as wellness tracking, tailored services, and security. Conventional approaches handle these activities as distinct entities, leading to less-than-ideal performance and restricted applicability. This research presents a novel deep multi-task learning network that simultaneously performs activity recognition and user identification using smartphone sensor data. By leveraging shared representations and task-specific information, the network enhances accuracy. It combines a shared convolutional neural network (CNN) with bidirectional long short-term memory (BiLSTM) layers to extract features from raw sensor data. The CNN identifies patterns, while the BiLSTM captures sequential dependencies and contextual information. These features are processed by fully connected layers for both activity recognition and user identification. A multi-task loss function is proposed to optimize both tasks based on their complexity and importance. The approach is tested on the UCI-HAR dataset, containing diverse activities from multiple users. Experimental results show that the proposed CNN-BiLSTM model achieves 97.64% accuracy in activity recognition and 82.59% in user identification, surpassing current state-of-the-art methods. This demonstrates the effectiveness of the multi-task learning framework and the advantage of using the shared CNN-BiLSTM architecture for improving both tasks.

关键词： human activity recognition user identification multi-task learning deep learning smartphone sensors

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Risks and Challenges Associated with the Chain of Custody of Cryptographic Assets in Law Enforcement Operations 6th

Risks and Challenges Associated with the Chain of Custod...

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6th International Congress on Blockchain and Applications, BLOCKCHAIN 2024

作者： Abad, Jesús Martín Guardeño, David Arroyo Casino, Fran Universidad Autónoma de Madrid Madrid Spain Madrid Spain Department of Computer Engineering and Mathematics Rovira i Virgili University Tarragona Spain Information Management Systems Institute of Athena Research Center Artemidos 6 Marousi151 25 Greece

ISBN: (纸本)9783031819278

The emergence of cryptocurrencies represents a radical change in the transmission of value in a disintermediated manner, which, in many cases, means that they are beyond the control of regulators and law enforcement bodies. This circumstance, together with the growing training in the use of crypto-asset management resources, has led to an increase in their popularity, and it is becoming increasingly common to find these crypto-assets in criminal operations. From a law enforcement perspective, the use of crypto-currency poses a challenge in terms of the procedure for investigating crimes involving the use of crypto-assets. Indeed, in addition to the problem of tracking and attribution, there is the complex issue of interception, custody and, if the investigation concludes that there is no criminal activity, the refund of the cryptographic asset to its owner. This paper analyses the challenges facing law enforcement investigation of criminal events involving cryptocurrencies that have been intercepted. In particular, it addresses the difficulties in achieving adequate protection to the chain of custody of crypto-assets, all by the inalienable criterion of the presumption of innocence that must govern all criminal proceedings. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Cybersecurity

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Study of Factors Influencing on Mental Health and Their Relationships, of IT Sector Employees in Colombo District, Sri Lanka 5

Study of Factors Influencing on Mental Health and Their Rela...

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5th International Conference on Advancements in Computing, ICAC 2023

作者： Dias, S.P.L. Lokuliyana, S. University of Sabaragamuwa Faculty of Applied Sciences Department of Physical Sciences and Technology Belihuloya Sri Lanka Sri Lanka Institute Information Technology Faculty of Graduate Studies and Research Department of Computer Systems and Engineering Malabe Sri Lanka

ISBN: (纸本)9798350358131

This study focused on the mental health of IT sector employees in Colombo, using quantitative research methods and data from 300 participants (162 males and 138 females) using the DASS 21 questionnaire and self-administered surveys through convenience sampling. Correlation analysis, chi-square tests, and regression analysis were utilized to examine the data. It found significant correlations between mental health outcomes (stress, anxiety, and depression) and factors like work-life balance, workload, working conditions, and physical fitness. Work-life balance, working environment, and workload were identified as the most significant predictors of mental health outcomes. Physical fitness was associated with stress, depression, and anxiety but had a limited overall impact on mental health. Differences in depression, stress, and anxiety levels were observed based on marital status, age group, work experience, salary, and gender. These findings emphasize the importance of addressing work-life balance and working conditions to enhance the mental health of IT sector employees in Colombo. They provide valuable insights for organizations and policymakers to develop strategies and interventions that promote employee well-being and productivity, underscoring the need to prioritize mental health and create a supportive work environment. © 2023 IEEE.

关键词： Regression analysis

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Genetic Algorithm with Ant Colony Optimization to Enhance Multi-Hop Routing Efficiency in Wireless Ad Hoc Network 2

Genetic Algorithm with Ant Colony Optimization to Enhance Mu...

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2nd International Conference on Augmented Intelligence and Sustainable Systems, ICAISS 2023

作者： Sumitra, V. Sumathi, V. Fernandes, J. Bennilo Sasi Kumar, C. R.M.K. Engineering College Department of Electronics and Communication Engineering Tamil Nadu Chennai India Sri Sairam Engineering College Department of Mathematics Tamil Nadu Chennai India Kalasalingam Academy of Research and Education Department of Electronics and Communication Engineering Tamil Nadu Virudhunagar India Shree Sathyam College of Engineering and Technology Department of Computer Science and Engineering Tamil Nadu Salem India

ISBN: (纸本)9798350325799

Wireless Ad Hoc Networks (WANETs) develop multi-hop communication to transmit data packets. The unique features of WANETs make it difficult for mobile nodes to communicate reliably. Most physical routing systems do not consider stable connections during packet transmission to manage high mobility and environmental impediments, which results in increased network latency and packet loss. This paper presents a Genetic with Ant Colony Optimization (GACO) Algorithm to enhance multi-hop routing efficiency in WANET. The GACO is a hybrid model by fusing the Genetic Algorithm (GA) and Ant Colony Optimization (ACO) models. The GACO computes the fitness function to improve the accuracy for selecting the best hop. This approach uses the ACO algorithm to make a multi-hop route by applying parameters like buffer availability, loss rate, and channel load factors. In order to simulate tests of GACO performance, Network Simulator-3 is used. Comparing GACO to the baseline technique, the routing performs better. © 2023 IEEE.

关键词： Ant colony optimization

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An Artificial Intelligence Approach for Solving Stochastic Transportation Problems

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computers, Materials & Continua 2022年第1期70卷 817-829页

作者： Prachi Agrawal Khalid Alnowibet Talari Ganesh Adel F.Alrasheedi Hijaz Ahmad Ali Wagdy Mohamed Department of Mathematics and Scientific Computing National Institute of Technology HamirpurHimachal Pradesh177005India Statistics and Operations Research Department College of ScienceKing Saud UniversityRiyadh11451Kingdom of Saudi Arabia Section of Mathematics International Telematic University UninettunoRoma00186Italy Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Wireless Intelligent Networks Center(WINC) School of Engineering and Applied SciencesNile UniversityGizaEgypt

Recent years witness a great deal of interest in artificial intelligence(AI)tools in the area of *** has developed a large number of tools to solve themost difficult search-and-optimization problems in computer science and operations ***,metaheuristic-based algorithms are a sub-field of *** study presents the use of themetaheuristic algorithm,that is,water cycle algorithm(WCA),in the transportation problem.A stochastic transportation problem is considered in which the parameters supply and demand are considered as random variables that follow the Weibull *** the parameters are stochastic,the corresponding constraints are *** are converted into deterministic constraints using the stochastic programming *** this study,we propose evolutionary algorithms to handle the difficulties of the complex high-dimensional optimization *** is influenced by the water cycle process of how streams and rivers flow toward the sea(optimal solution).WCA is applied to the stochastic transportation problem,and obtained results are compared with that of the new metaheuristic optimization algorithm,namely the neural network algorithm which is inspired by the biological nervous *** is concluded that WCA presents better results when compared with the neural network algorithm.

关键词： Artificial intelligence metaheuristic algorithm stochastic programming transportation problem water cycle algorithm weibull distribution

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Explainable-AI-based two-stage solution for WSN object localization using zero-touch mobile transceivers

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Science China(Information Sciences) 2024年第7期67卷 27-45页

作者： Kai FANG Junxin CHEN Han ZHU Thippa Reddy GADEKALLU Xiaoping WU Wei WANG School of Mathematics and Computer Science Zhejiang A&F University School of Software Dalian University of Technology Faculty of Applied Sciences Macao Polytechnic University Department of Electrical and Computer Engineering Lebanese American University School of Information Engineering Huzhou University Guangdong-Hong Kong-Macao Joint Laboratory for Emotional Intelligence and Pervasive Computing Artificial Intelligence Research Institute Shenzhen MSU-BIT University

Artificial intelligence technology is widely used in the field of wireless sensor networks(WSN).Due to its inexplicability, the interference factors in the process of WSN object localization cannot be effectively eliminated. In this paper, an explainable-AI-based two-stage solution is proposed for WSN object localization. In this solution, mobile transceivers are used to enlarge the positioning range and eliminate the blind area for object localization. The motion parameters of transceivers are considered to be unavailable,and the localization problem is highly nonlinear with respect to the unknown parameters. To address this,an explainable AI model is proposed to solve the localization problem. Since the relationship among the variables is difficult to fully include in the first-stage traditional model, we develop a two-stage explainable AI solution for this localization problem. The two-stage solution is actually a comprehensive consideration of the relationship between variables. The solution can continue to use the constraints unused in the firststage during the second-stage, thereby improving the performance of the solution. Therefore, the two-stage solution has stronger robustness compared to the closed-form solution. Experimental results show that the performance of both the two-stage solution and the traditional solution will be affected by numerical changes in unknown parameters. However, the two-stage solution performs better than the traditional solution, especially with a small number of mobile transceivers and sensors or in the presence of high noise. Furthermore,we have also verified the feasibility of the proposed explainable-AI-based two-stage solution.

关键词： explainable AI object localization semidefinite relaxation mobile transceiver two-stage solution closed-form solution

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Dynamic Heat Price: A Promising Approach to Unlock Energy Flexibility of District Heating Networks

SSRN

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SSRN 2024年

作者： Mokhtari, Reza Junker, Rune Grønborg Madsen, Henrik Li, Rongling Department of Civil and Mechanical Engineering Technical University of Denmark Lyngby Denmark Department of Applied Mathematics and Computer Science Technical University of Denmark Lyngby Denmark

Current district heating systems are still relying on fossil fuels as their critical source of energy. Transition to green technologies will not be achieved in this sector unless renewable energy and other clean sources of energy surrogate fossil fuels. However, the intermittent production of renewable energy makes this action challenging. To include renewable energy in district heating networks, mismatches between the demand and supply should first be addressed. Lessons learned through the development of the electricity market underscore that energy flexibility can serve as a viable solution to address this issue. This paper investigates the effectiveness of dynamic heat price in unlocking the energy flexibility of neighborhoods and gives an insight into its challenges. The underlying approach relies on using nonlinear flexibility function to characterize the energy flexibility of a residential neighborhood in Sønderborg, Denmark. First, a detailed white-box model of the neighborhood is created using Modelica and validated based on measurements. Then, an inverse optimization problem is solved to find the optimum day-ahead price schedule for the neighborhood. Results show that a dynamic price scheme can be beneficial for both consumers and district heating operators. Accordingly, buildings could decrease their cost by 46.6% by complying with the varying price through a direct change in indoor thermostat setting compared to a fixed thermostat setting. On the other side, using the dynamic price could change the neighborhood demand profile to a desired reference profile with an error of 16.6%. In addition, the proposed methodology was shown to be robust to errors in load predictions. © 2024, The Authors. All rights reserved.

关键词： District heating

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Modeling and Analysis of Induction Machine Considering the Effects of Saturation

Modeling and Analysis of Induction Machine Considering the E...

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Circuit, Systems and Communication (ICCSC), International Conference on

作者： Es-Semyhy Mustapha Ba-Razzouk Abdellfattah El Haroussi Mustapha Department of Applied Physics Mathematics Computer and Engineering Sciences Laboratory (MISI) Systems Analysis and Information Processing Team (ASTI) Settat Morocco

ISBN: (数字)9798350365306

ISBN: (纸本)9798350365313

This paper focuses on the modeling of an induction machine, with a specific emphasis on saturation of the main path. The model, formulated in a two-axis system, considers the saturation effect to accurately represent the behavior of the machine. Two scenarios are studied namely nominal and high-level saturation cases. All parameters of the machine are treated as variables, and a comprehensive discussion is provided regarding the effects of certain parameters, shedding light on their influence on the induction machine’s dynamic performance. Simulation work is carried out using the MATLAB/Simulink environment, providing valuable insights into the system’s dynamic behavior under different saturation conditions.

关键词： Analytical models Torque Stators Observers Motors Mathematical models Induction machines

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Generalized Quantum Computing K-Fibonacci Sequence

Generalized Quantum Computing K-Fibonacci Sequence

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2024 International Conference on Science, engineering and Business for Driving Sustainable Development Goals, SEB4SDG 2024

作者： Rajiniganth, P. Suresh, K. Aparna, T. Oyetepo, T. Oluwayemi, M.O. Dhanalakshmi Srinivasan University School of Engineering and Technology Department of Mathematics Samayapuram621112 India St. Joseph's College of Enginering Department of Mathematics Tamil Nadu Chennai119 India Federal University of Allied Health Sciences Department of Applied Sciences Enugu400001 Nigeria Margaret Lawrence University Department of Mathematics and Statistics Galilee Delta State Nigeria Landmark University Sdg 4 Quality Education Research Group Kwara State Omu-Aran Nigeria Landmark University Department of Physical Sciences Mathematics Programme Kwara State Omu-Aran Nigeria

ISBN: (数字)9798350358155

ISBN: (纸本)9798350358155

In this study, we present a generalized quantum computing Fibonacci sequence derived through a third order quantum k-difference operator and its equations, from which we deduce some algebraic identities, some theorems, and lemmas with Fibonacci numbers and solutions of quantum k-difference equations. To demonstrate our findings, a suitable example that has been verified by MATLAB is *** Subject Classification:39A10, 47B39, 39A70. © 2024 IEEE.

关键词： Quantum computers

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