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23rd International Arab Conference on Information technology, ACIT 2022

作者： Darwish, Omar Herzallah, Sarah Maabreh, Majdi Al-Eidi, Shouroq Al-Maani, Mahmoud Tashtoush, Yahya Eastern Michigan University Information Security and Applied Computing YpsilantiMI United States Eastern Michigan University Electrical and Computer Engineering YpsilantiMI United States The Hashemite University Department of Information Technology Zarqa Jordan Tafila Technical University Computer Science Department Tafila Jordan Jordan University of Science and Technology Department of Computer Science Irbid Jordan

ISBN: (纸本)9798350320244

One of the most crucial considerations, when considering security vulnerabilities, is network traffic. There is still potential for more research on the inter-arrival time side, even though some studies concentrate on network traffic from the perspective of the packet fields such as packet length and packet number. Inter-arrival timings are crucial to investigate because there are numerous attacks, such as Covert Timing Channels attacks, that heavily rely on them. In this article, we conduct a statistical analysis of the TCP inter-arrival times of two major key streaming programs (Zoom and Skype), which are frequently used, particularly during and following the COVID-19 pandemic. Using two internet-connected devices and the statistical measures of TCP, a dataset of 18,371 instances is created for this use. Five machine learning algorithms are evaluated on balanced and imbalanced forms of the dataset. The results revealed that the traffic of Zoom and Skype calls can be identified by machine learning algorithms with an accuracy of up to 99% by random forest. © 2022 IEEE.

关键词： Transmission control protocol

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Solutions of stationary McKean-Vlasov equation on a high-dimensional sphere and other Riemannian manifolds

arXiv

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arXiv 2024年

作者： Shalova, Anna Schlichting, André Department of Mathematics and Computer Science Eindhoven University of Technology Netherlands Institute of Applied Analysis Ulm University Germany

We study stationary solutions of McKean-Vlasov equation on a high-dimensional sphere and other compact Riemannian manifolds. We extend the equivalence of the energetic problem formulation to the manifold setting and characterize critical points of the corresponding free energy functional. On a sphere, we employ the properties of spherical convolution to study the bifurcation branches around the uniform state. We also give a sufficient condition for an existence of a discontinuous transition point in terms of the interaction kernel and compare it to the Euclidean setting. We illustrate our results on a range of system, including the particle system arising from the transformer models and the Onsager model of liquid crystals. Copyright © 2024, The Authors. All rights reserved.

关键词： Spheres

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Energy-Efficient Transmission in Wireless Networks Using Resnet with Gravitational Search Algorithm 2

Energy-Efficient Transmission in Wireless Networks Using Res...

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2nd International Conference on Disruptive Technologies, ICDT 2024

作者： Rajakumari, S. Hc, Kantharaju Ahmad, Shadab Sharma, Rupa Rani Sudha, S. Ramesh, T. R.M.D. Engineering College Department of Mathematics India Vemana Institute of Technology Department of Ai & Ml Karnataka Bengaluru India Samara University Department of Electrical and Computer Engineering Afar region Ethiopia G.L Bajaj Institute of Technology and Management Department of Applied Science Uttar Pradesh Greater Noida India Sri Ranganathar Institute of Engineering and Technology Department of Ece Tamilnadu Coimbatore India R.M.K Engineering College Department of Computer Science and Engineering India

ISBN: (纸本)9798350371055

Although wireless networks are extremely important in modern communication, one of the most significant challenges they face is the quantity of energy that they use. Within this study, a new way of sending data over wireless networks is suggested. The gravitational search algorithm (GSA) and residue networks of the ResNet type are used together in this method. By using wireless networks, the main goal of this method is to find answers to problems that come up with using energy more efficiently. The creation and use of a hybrid ResNet-GSA model for wireless communication is one of the most important parts of our method. Because it follows the rules of gravity, GSA can quickly look through the solution space to find the right parameter values. At the same time, the network works better when the deep learning features of ResNet are used. The results of our research show that there are big improvements in how much energy is used compared to using traditional ways. If you want to cut down on the amount of energy used, the ResNet-GSA strategy that was suggested also works well. The findings demonstrate that optimisation techniques and deep learning methodologies are not only compatible with one another but also perform effectively together to make wireless networks more environmentally friendly. © 2024 IEEE.

关键词： Energy Efficiency Gravitational Search Algorithm Residual Networks Transmission Optimization

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Evaluating the Performance of Subjective Weighting Methods for Multi-Criteria Decision-Making using a novel Weights Similarity Coefficient 27

Evaluating the Performance of Subjective Weighting Methods f...

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27th International Conference on Knowledge Based and Intelligent Information and Engineering Sytems, KES 2023

作者： Shekhovtsov, Andrii Research Team on Intelligent Decision Support Systems Department of Artificial Intelligence and Applied Mathematics Faculty of Computer Science and Information Technology West Pomeranian University of Technology in Szczecin ul. Zolnierska 49 Szczecin71-210 Poland

In every decision-making problem which involves two or more criteria, there is to identify the relative importance of those criteria in order to make a proper decision. Very often, a decision-makers employee, for this purpose, subjective weighting methods, such as Analytic Hierarchy Process (AHP) or RANking COMparison (RANCOM). However, there is no simple way to compare the quality of the weights identification using different methods. To address this issue, this paper proposes a simple but efficient Weights Similarity Coefficient, which allows us to evaluate the relative performance of different subjective weighting methods. Furthermore, we propose a framework that utilizes the proposed coefficient in order to provide more complete comparison results. To demonstrate the applicability and effectiveness of the proposed framework, a case study is performed to compare two popular weighting methods: AHP and RANCOM. The results of the comparison prove that proposed coefficient with the combination of the proposed framework is an efficient instrument for weighing methods comparison. © 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0)

关键词： AHP Criteria weights Manhattan distance MCDA RANCOM SPOTIS

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Through-Wall Human Sensing Using mmWave FMCW Radar 4

Through-Wall Human Sensing Using mmWave FMCW Radar

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4th Research, Invention, and Innovation Congress: Innovative Electricals and Electronics, RI2C 2023

作者： Phaisiri, Kritthee Boonpoonja, Akkarat Kittiyanpunya, Chainarong Kaemarungsi, Kamol Chudpooti, Nonchanutt Department of Electrical and Computer Engineering Faculty of Engineering King Mongkut’s University of Technology North Bangkok Bangkok Thailand Department of Mechatronics Engineering Faculty of Engineering Rajamangala University of Technology Rattanakosin Nakhon Pathom Thailand National Electronics and Computer Technology Center National Science and Technology Development Agency Pathumthani Thailand Department of Industrail Physics and Medical Instrumentation Faculty of Applied Science King Mongkut’s University of Technology North Bangkok Bangkok Thailand

ISBN: (纸本)9798350330618

This paper experimentally demonstrates the through wall sensing to detect human movement using a mmwave FMCW radar operating in the 60 GHz to 64 GHz band. The mmWave radar data processing framework focuses on the generation of point cloud data. Each human movement is illustrated with point cloud data, whose represents the position and orientation of pose, usually in 3D-cartesian coordinate system. In experiments, point cloud data from sensing through two different walls were collected for three activities into a 3 m by 3 m room. The data was analyzed through a comparison between the position of point cloud data and the position of the actual posture movement. The results prove that a mmWave radar placed behind the wall of the room is suitable for human detection and tracking in indoor environments, in terms of consistency with the actual posture. . ©2023 IEEE.

关键词： Frequency modulation

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A Comparative Analysis of IoT Data Using Machine Learning Algorithms 15th

A Comparative Analysis of IoT Data Using Machine Learning Al...

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15th International Conference on Soft Computing and Pattern Recognition, SoCPaR 2023 and 14th World Congress on Nature and Biologically Inspired Computing, NaBIC 2023

作者： Nagashree, B.A. Satheesh Kumar, S. Muthukumaran, V. Munrathnam, Meram Angeline Kavitha, M. Department of Computer Science and Applications School of CSA REVA University Bangalore India Department of Computer Science School of Applied Sciences REVA University Bangalore India Department of Mathematics College of Engineering and Technology SRM Institute of Science and Technology Chennai India Department of Mathematics Rajiv Gandhi University of Knowledge Technologies R.K. Valley Kadapa District Andhra Pradesh Idupulapaya516330 India Department of Mathematics Voorhees College Vellore632001 India

ISBN: (纸本)9783031889912

IoT (Internet of Things) is revolutionizing the commercial environment by acquiring vast amounts of data from various sources. However, processing and analyzing this data is challenging due to the large volume of IoT devices. AI-powered IoT creates intelligent machines that mimic human intelligence, aiding decision-making with minimal human input. Both individuals and professionals’ benefit from this combination, as IoT is concerned with communicating online, but AI allows machines to learn from data and experience. This study demonstrates the analysis of IoT data using machine learning algorithms and compares the accuracy of various machine learning algorithms used. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Contrastive Learning

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UX Design and Evaluation: Holism versus Reductionism Approaches - Which is Better? 2

UX Design and Evaluation: Holism versus Reductionism Approac...

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2nd IEEE International Conference on Interdisciplinary Approaches in technology and Management for Social Innovation, IATMSI 2024

作者： Mkpojiogu, Emmanuel O.C. Abdullahi, Monday Jubrin Okeke-Uzodike, Obianuju E. Universiti Utara Malaysia Uum Sintok06010 Malaysia Veritas University Department of Software Engineering Abuja Nigeria Airforce Institute of Technology Department of Computer Science Kaduna State Kaduna Nigeria Durban University of Technology Department of Applied Management KwaZulu-Natal Pietermaritzburg South Africa

ISBN: (纸本)9798350360523

A literature content analysis strategy was used to synthesize extant literature sources to comprehend and capture the approaches to the design, evaluation and modeling of user experience. From the analysis, two main methods were identified for the UX research. These paradigms are holism and reductionism. The holist approach stresses on sense making and interpretative approaches to user experience, leading to construction and reconstruction of users' quality perceptions about their experiences with technological artifacts. This paradigm is design based. Conversely, the reductionism approach is concerned with the deconstruction of users' experiences. This approach conceives experiences as a model that can be broken down into aspects and dimensions that facilitates understanding of user experience. The debate among researchers on these differing viewpoints conceived and drove this study. The findings of the research show that the two paradigms are insightful, rich and unique and can be independently used in UX research, nevertheless, as both approaches a limited and address the peculiar concerns of the two respective paradigms, this paper advocates and endorses the use of a mixed paradigm especially in longitudinal studies to amalgamate the rich components of both varying approaches, thus implying the interdependent use of the two paradigms in UX research. © 2024 IEEE.

关键词： User experience

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Comparing the Performance of Different Architectures for Predicting Steering Angles of Cars

Comparing the Performance of Different Architectures for Pre...

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Disruptive Technologies (ICDT), International Conference on

作者： Aman Kumar Singh Pragati Singh Palak Shandil Department of Applied Computer Science G.L.BAJAJ Institute of Technology and Management Uttar Pradesh India Department of Computer Science G.L.BAJAJ Institute of Technology and Management Uttar Pradesh India

Accurately predicting the steering angles of cars is a crucial task in the development of autonomous driving systems. Deep learning models have shown significant improvements in this area, with various neural network architectures being proposed for this task. In this paper, we implemented and compared three different models for predicting steering angles from images in the context of autonomous driving. Mean squared error (MSE) and mean absolute error (MAE) are two metrics that were used to assess the performance of the three models.

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Vehicular Data Retrieval System

Vehicular Data Retrieval System

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New Frontiers in Communication, Automation, Management and Security (ICCAMS), International Conference on

作者： Shaeif Thajudheen Shanmugarathinum G Angelin Gladys Jesudoss Dept. of Computer Science Presidency University Bengaluru India Dept. of Computer Science University of Technology and Applied Sciences Ibri Oman

ISBN: (数字)9798350317060

ISBN: (纸本)9798350317077

The Vehicular Data Retrieval System is comprehensive research that focuses on collecting real-time data from vehicles and transmitting it to a remote server for storage and later visualization in a web application. The system incorporates advanced technologies such as GPS (Global Positioning System) for precise location tracking and data capturing. The primary aim of this research is to create an efficient and scalable solution that enables the retrieval of essential vehicular parameters including speed, engine temperature, fuel level, and coordinates. By harnessing this data, it becomes possible to visualize and analyze vehicle performance over time, leading to valuable insights for various applications, such as fleet management, transportation optimization, and environmental monitoring. This paper presents a detailed analysis of the research’s requirements, an extensive literature review, an evaluation of existing systems, and the proposed system design and implementation. Furthermore, the paper discusses testing methodologies, the achieved outcomes, and recommendations for future enhancements to further enrich the vehicular data retrieval and visualization system.

关键词： Temperature sensors Temperature measurement Smart cities Urban planning Data visualization Transportation Real-time systems

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Stochastic Triangular Fuzzy Number (S-TFN) Normalization: A New Approach for Nonmonotonic Normalization 27

Stochastic Triangular Fuzzy Number (S-TFN) Normalization: A ...

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27th International Conference on Knowledge Based and Intelligent Information and Engineering Sytems, KES 2023

作者： Kizielewicz, Bartlomiej Dobryakova, Larisa Research Team on Intelligent Decision Support Systems Department of Artificial Intelligence and Applied Mathematics Faculty of Computer Science and Information Technology West Pomeranian University of Technology in Szczecin ul. Zolnierska 49 Szczecin71-210 Poland

Data normalization is essential in many fields, such as speech recognition, deep learning, machine learning, and optimization. Many researchers focus on developing various normalization techniques, such as min-max, score-based, maximum, vector, or sum, on processing data efficiently. However, classical normalization methods may need to be improved in Multi-Criteria Decision-Analysis (MCDA), where criteria are often non-monotonic. This paper proposes a new approach for identifying and normalizing non-monotonic criteria in MCDA. The method combines a stochastic optimization technique - a genetic algorithm - with normalization based on triangular fuzzy numbers. This paper compares the proposed approach with classical normalization techniques, such as min-max, maximum, vector, or non-linear, using the classical MCDA method - the Technique of Order Preference Similarity to the Ideal Solution (TOPSIS). The study results showed that the proposed approach to normalizing non-monotonic criteria yields a better match between decision preferences and the actual reference model than traditional normalization methods. Optimization using the genetic algorithm helps identify the means of triangular fuzzy numbers, which generate more accurate results. Analysis of the R2 coefficient confirms a very good fit of the proposed model. Therefore, the new non-linear normalization approach in MCDA presented in this work has great potential in adjusting decision preferences to non-monotonic criteria. Future research should continue on the accuracy of this approach in identifying non-linear decision models and apply it to other MCDA methods and real-world decision problems. © 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0)

关键词： Decision analysis Fuzzy sets MCDA Normalization TOPSIS

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