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23rd International Conference of the European Society for Precision engineering and Nanotechnology, EUSPEN 2023

作者： Yeh, Hao-Ping Rotari, Marta Shan, Shuo Meinert, Kenneth Ælkær Hattel, Jesper Henri Kulahci, Murat Pedersen, David Bue Calaon, Matteo Department of Civil and Mechanical Engineering Technical University of Denmark Kgs. Lyngby Denmark Department of Applied Mathematics and Computer Science Technical University of Denmark Kgs. Lyngby Denmark Department of Business Administration Technology and Social Sciences Luleå University of Technology Luleå Sweden

ISBN: (纸本)9781998999132

Additive manufacturing is a revolutionary method that relieves industries from the geometrical restrictions of their products. In this area, the Selective thermoplastic electrophotographic process (STEP) is a breakthrough approach that can obtain fast and highvolume production. Despite the STEP's excellent characteristics and achievements, the final products present dimensional defects which significantly impact their mechanical qualities. This study presents a prediction model of deformation behaviour by a finite element-based thermo-mechanical model. Additionally, a dimensional study was conducted on various STEP manufactures products. The work presents an analysis of the results of the dimensional measurements, highlighting the position of the products on the building plate. The dimensional evaluation of the STEP's products supports the thermo-mechanical model results. © 2023 Euspen Headquarters.

关键词： Defects

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The Advanced Encryption Standard with a Dynamic S-Box Using the RC4 Key Schedule 4

The Advanced Encryption Standard with a Dynamic S-Box Using ...

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4th IEEE International Conference on Electrical, computer, and Energy Technologies, ICECET 2024

作者： Altigani, Abdelrahman Ghalib, Muhammad Rukunuddin Elshoush, Huwaida T. Elsadig, Muawia A. Alrefai, Nashat Naserelden, Shiraz Higher Colleges of Technology Computer Information Science Al Ain United Arab Emirates School of Engineering & Computing De Monfort University Dubai United Arab Emirates University of Khartoum Faculty of Mathematical Sciences and Informatics Computer Science Department Khartoum Sudan College of Computer Science and Information Technology Imam Abdulrahman bin Faisal University Dammam Saudi Arabia College of Science Imam Abdulrahman Bin Faisal University Basic and Applied Scientific Research Center Imam Abdulrahman Bin Faisal University Department of Mathematics Dammam Saudi Arabia Faculty of Science Universiti Teknologi Malaysia Department of Mathematical Sciences Johor Malaysia

ISBN: (纸本)9798350395914

Since the inception of secure communication, safeguarding data confidentiality has been paramount. With the increased reliance on technology, the need for robust security mechanisms is more critical than ever. This paper explores confidentiality in cybersecurity, focusing on symmetric encryption algorithms. While symmetric encryption, particularly the Advanced Encryption Standard (AES), is in wide use, concerns arise regarding its static nature. Therefore, the paper introduces a dynamic cipher, augmenting AES security by introducing a key-dependent S-Box. By leveraging the RC4 key schedule, the proposed cipher generates unique S-Boxes for each encryption key, significantly increasing security against non-generic attacks. Theoretical analysis demonstrates the proposed cipher is capable of resisting brute force, linear cryptanalysis, and differential cryptanalysis. Furthermore, its adaptability to existing AES implementations ensures practicality and ease of adoption. © 2024 IEEE.

关键词： Ciphertext

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A Dynamic Approach for Handling UAV in Crowded Environment Using Deep Q-Networks

A Dynamic Approach for Handling UAV in Crowded Environment U...

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Global Conference for Advancement in Technology (GCAT)

作者： Yash Upadhyay Muskan Gahlawat S. Nivetha Saurabh Rana B Natarajan Pratik Gupta Department of Computer Science and Engineering (AIE) Amrita School of Computing Amrita Vishwa Vidyapeetham Chennai India Department of Computer Science and Engineering RVS College of Engineering & Technology Coimbatore Department of Mathematics Chandigarh University Department of Computer Science and Engineering (AIE) Amrita Vishwa Vidyapeetham Chennai India Department of Applied Mathematics Gautam Buddha University Noida

The demand for wireless connections is rising, and the advent of mobile internet has sparked a hunt for fresh, creative ways to expand the capacity and reach of cellular networks. One strategy to provide ground mobile users with long-term communication coverage is to employ Unmanned Aerial vehicles (UAV) as mobile base stations. The proposed method incorporates a Deep Reinforcement Learning (DRL) method to address the challenges that persist with traditional approaches. We introduced Deep Q-Learning with an attention mechanism-based multi-agent model to develop an energy-efficient control system for UAVs in cellular networks. Due to the proposed strategy’s dynamic nature, it efficiently handles the crowded environment by resolving scalability and mobility issues. The researchers evaluated the proposed model using the benchmark dataset, producing promising results. Further, the researchers tested the proposed model using the sum rate metric to analyze the capability of the proposed algorithm to provide a reasonable throughput rate.

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Majority Spanning Trees, Cotrees and Their Applications 15th

Majority Spanning Trees, Cotrees and Their Applications

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15th International Conference on Algorithms and Computation, WALCOM 2021

作者： Kaykobad, Mohammad Salzborn, F.J.M. Department of Computer Science and Engineering BRAC University Dhaka Bangladesh Department of Applied Mathematics University of Adelaide Adelaide Australia

ISBN: (纸本)9783030682101

We show that in any digraph on an underlying connected graph with non-negative weights on its edges, there is a Majority Spanning Tree for which sum of weights of edges of a fundamental cutset, running along each edge of the spanning tree determining the cutset, is not less than sum of those running in opposite direction. Similarly, there is a Majority Cotree, each fundamental cycle of which has non-negative weight. We further prove simultaneous existence of majority spanning trees and majority cotrees in any non-negative weighted digraph. We have shown how these structures can be used to solved scheduling transports by minimizing sum of weighted connection times, ranking round-robin tournaments by minimizing number of upsets, in settling multiple debts and in construction of transport networks with unbalanced road capacity. © 2021, Springer Nature Switzerland AG.

关键词： Trees (mathematics)

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UAV-Aided Data Acquisition Using Gaining-Sharing Knowledge Optimization Algorithm

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computers, Materials & Continua 2022年第9期72卷 5999-6013页

作者： Rania M Tawfik Hazem A.A.Nomer M.Saeed Darweesh Ali Wagdy Mohamed Hassan Mostafa Wireless Intelligent Networks Center(WINC) School of Engineering and Applied SciencesNile UniversityGiza12677Egypt School of Information Technology and Computer Science(ITCS) Nile UniversityGiza12677Egypt Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Department of Mathematics and Actuarial Science School of Science and EngineeringThe American University in CairoEgypt Electronics and Communications Engineering Department Cairo UniversityEgypt University of Science and Technology Nanotechnology and Nanoelectronics ProgramZewal City of Science and TechnologyOctober Gardens6th of OctoberGiza12578Egypt

Unmanned Aerial Vehicles(UAVs)provide a reliable and energyefficient solution for data collection from the Narrowband Internet of Things(NB-IoT)***,the UAV’s deployment optimization,including locations of the UAV’s stop points,is a necessity to minimize the energy consumption of the UAV and the NB-IoT devices and also to conduct the data collection *** this regard,this paper proposes GainingSharing Knowledge(GSK)algorithm for optimizing the UAV’s *** GSK,the number of UAV’s stop points in the three-dimensional space is encapsulated into a single individual with a fixed length representing an entire *** superiority of using GSK in the tackled problem is verified by simulation in seven *** provides significant results in all seven scenarios compared with other four optimization algorithms used before with the same ***,the NB-IoT is proposed as the wireless communication technology between the UAV and IoT devices.

关键词： NB-IoT UAV GSK stop points optimization

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Bounded Future MS-TCN++ for Surgical Gesture Recognition 17th

Bounded Future MS-TCN++ for Surgical Gesture Recognition

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17th European Conference on computer Vision, ECCV 2022

作者： Goldbraikh, Adam Avisdris, Netanell Pugh, Carla M. Laufer, Shlomi Applied Mathematics Department Technion – Israel Institute of Technology Haifa3200003 Israel School of Computer Science and Engineering The Hebrew University of Jerusalem Jerusalem Israel School of Medicine Stanford Stanford University StanfordCA United States Faculty of Industrial Engineering and Management Technion – Israel Institute of Technology Haifa3200003 Israel

ISBN: (纸本)9783031250651

In recent times there is a growing development of video-based applications for surgical purposes. Part of these applications can work offline after the end of the procedure, other applications must react immediately. However, there are cases where the response should be done during the procedure but some delay is acceptable. In the literature, the online-offline performance gap is known. Our goal in this study was to learn the performance-delay trade-off and design an MS-TCN++-based algorithm that can utilize this trade-off. To this aim, we used our open surgery simulation data-set containing 96 videos of 24 participants that perform a suturing task on a variable tissue simulator. In this study, we used video data captured from the side view. The Networks were trained to identify the performed surgical gestures. The naive approach is to reduce the MS-TCN++ depth, as a result, the receptive field is reduced, and also the number of required future frames is also reduced. We showed that this method is sub-optimal, mainly in the small delay cases. The second method was to limit the accessible future in each temporal convolution. This way, we have flexibility in the network design and as a result, we achieve significantly better performance than in the naive approach. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Gesture recognition

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A Convolutional Neural Network for Ultra-Wideband Radar-Based Hand Gesture Recognition

A Convolutional Neural Network for Ultra-Wideband Radar-Base...

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2023 International Technical Conference on Circuits/Systems, computers, and Communications, ITC-CSCC 2023

作者： Mekruksavanich, Sakorn Jantawong, Ponnipa Tancharoen, Datchakorn Jitpattanakul, Anuchit School of Information and Communication Technology University of Phayao Department of Computer Engineering Phayao Thailand Panyapiwat Institute of Management Faculty of Engineering and Technology Nonthaburi Thailand Intelligent and Nonlinear Dynamic Innovations Research Center King Mongkut's University of Technology North Bangkok Faculty of Applied Science Department of Mathematics Bangkok Thailand

ISBN: (纸本)9798350326413

New developments in sensing technology have enabled the creation of improved assistive devices that enhance daily eldercare routines and offer personalized care to users. Wearable or ambient sensors can now detect a person's behavior, but the need for constant recharging due to their high energy consumption makes wearing such devices around the clock difficult. In this paper, a new sensing technique based on deep learning (DL) approaches for hand gesture recognition (HGR) using an ultra-wideband (UWB) radar sensor is introduced. The study examines the recognition performance of a convolutional neural network (CNN) for HGR and utilizes the UWB-gestures dataset to train and test the DL networks in various experiments with different scenarios. The experimental results demonstrate that the CNN achieved the highest F1-score of 97.19%. © 2023 IEEE.

关键词： Convolutional neural networks

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A Hybrid Deep Neural Network with Attention Mechanism for Human Activity Recognition Based on Smartphone Sensors 7

A Hybrid Deep Neural Network with Attention Mechanism for Hu...

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7th International Conference on Information Technology, InCIT 2023

作者： Mekruksavanich, Sakorn Tancharoen, Datchakorn Jitpattanakul, Anuchit University of Phayao School of Information and Communication Technology Department of Computer Engineering Phayao Thailand Panyapiwat Institute of Management Faculty of Engineering and Technology Nonthaburi Thailand Faculty of Applied Science King Mongkut's University of Technology North Bangkok Intelligent and Nonlinear Dynamic Innovations Research Center Department of Mathematics Bangkok Thailand

ISBN: (纸本)9798350358698

Human activity recognition (HAR) is an area of study that seeks to automatically and precisely detect an individual's behavior by analyzing bio-signal data. Bio-signal data can be acquired using sensing technology integrated into smartphones and other worn intelligent gadgets. Nevertheless, collecting sensor data tagged with activity information employing individual smartphones can result in data being analyzed in varying contexts, potentially compromising the accuracy of machine learning prediction methodologies. This paper introduces a novel HAR approach via smartphone sensors. The proposed method incorporates a hybrid deep neural network architecture enhanced with an attention mechanism. The deep learning model under consideration is referred to as the Att-CNN-BLSTM network. This particular network can autonomously extract significant features from smartphone sensor data. This feature extraction aims to effectively classify different human actions with a high degree of accuracy. In order to assess the efficacy of the hybrid model, a series of investigations were undertaken utilizing a publically accessible HAR dataset. This dataset was employed for training and testing purposes, employing a 5-fold cross-validation approach. We additionally carried out an analytical comparison utilizing state-of-the-art deep learning models from prior research. The findings from our experimentation demonstrate superior performance of the Att-CNN-BLSTM model over other advanced AI algorithms, with the highest accuracy rate of 90.54% and top F1-score of 86.88% attained. © 2023 IEEE.

关键词： Smartphones

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A Framework for Controllable Pareto Front Learning with Completed Scalarization Functions and its Applications

arXiv

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arXiv 2023年

作者： Tuan, Tran Anh Hoang, Long P. Le, Dung D. Thang, Tran Ngoc School of Applied Mathematics and Informatics Hanoi University of Science and Technology Hanoi Viet Nam College of Engineering and Computer Science VinUniversity Hanoi Viet Nam

Pareto Front Learning (PFL) was recently introduced as an efficient method for approximating the entire Pareto front, the set of all optimal solutions to a Multi-Objective Optimization (MOO) problem. In the previous work, the mapping between a preference vector and a Pareto optimal solution is still ambiguous, rendering its results. This study demonstrates the convergence and completion aspects of solving MOO with pseudoconvex scalarization functions and combines them into Hypernetwork in order to offer a comprehensive framework for PFL, called Controllable Pareto Front Learning. Extensive experiments demonstrate that our approach is highly accurate and significantly less computationally expensive than prior methods in term of inference time. Copyright © 2023, The Authors. All rights reserved.

关键词： Multiobjective optimization

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THE WEIGHTED AND SHIFTED SEVEN-STEP BDF METHOD FOR PARABOLIC EQUATIONS

arXiv

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arXiv 2024年

作者： Akrivis, Georgios Chen, Minghua Yu, Fan Department of Computer Science and Engineering University of Ioannina Ioannina451 10 Greece Institute of Applied and Computational Mathematics FORTH Heraklion Crete700 13 Greece School of Mathematics and Statistics Gansu Key Laboratory of Applied Mathematics and Complex Systems Lanzhou University Lanzhou730000 China

Stability of the BDF methods of order up to five for parabolic equations can be established by the energy technique via Nevanlinna–Odeh multipliers. The nonexistence of Nevanlinna–Odeh multipliers makes the six-step BDF method special;however, the energy technique was recently extended by the authors in [Akrivis et al., SIAM J. Numer. Anal. 59 (2021) 2449–2472] and covers all six stable BDF methods. The seven-step BDF method is unstable for parabolic equations, since it is not even zero-stable. In this work, we construct and analyze a stable linear combination of two non zero-stable schemes, the seven-step BDF method and its shifted counterpart, referred to as WSBDF7 method. The stability regions of the WSBDFq, q 6 7, with a weight ϑ > 1, increase as ϑ increases, are larger than the stability regions of the classical BDFq, corresponding to ϑ = 1. We determine novel and suitable multipliers for the WSBDF7 method and establish stability for parabolic equations by the energy technique. The proposed approach is applicable for mean curvature flow, gradient flows, fractional equations and nonlinear equations. Copyright © 2024, The Authors. All rights reserved.

关键词： Nonlinear equations

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