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IEEE Conference on Global Communications (GLOBECOM)

作者： Khai Doan Wesley Araujo Evangelos Kranakis Ioannis Lambadaris Yannis Viniotis Department of Systems and Computer Engineering Carleton University Ottawa ON Canada Carleton University School of Computer Science Ottawa ON Canada Department of Electrical and Computer Engineering North Carolina State University Raleigh NC USA

Task offloading in mobile edge computing systems is subject to various random factors including the connection to external servers, new task requests from users, and the availability of local processing services. However, statistical information is often not available in practical scenarios. To tackle the issue, we adopt a Q-learning-based approach that learns the optimal task offloading policy through observations of random events. Traditional Q-learning methods may face challenges such as long training times and high memory usage due to the large state and action space. To overcome this problem, we propose a novel method that leverages the concept of adjacent state sequence. In this type of sequence, we can infer the optimal offloading decision of a system state from other states. This method aims to improve the convergence speed and memory efficiency of the learning model by reducing the number of parameters that need to be learned and stored. Those eliminated parameters instead can be computed via a derived linear expression. We conduct experiments to demonstrate the enhancement of our proposed method compared to the traditional $\mathbf{Q}-$ learning in the studied problem.

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engineering synthetic gauge fields through the coupling phases in cavity magnonics

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Physical Review Applied 2024年第6期21卷 064033-064033页

作者： Alan Gardin Guillaume Bourcin Jeremy Bourhill Vincent Vlaminck Christian Person Christophe Fumeaux Giuseppe C. Tettamanzi Vincent Castel School of Physics Lab-STICC UMR CNRS 6285 ARC Centre of Excellence for Engineered Quantum Systems and ARC Centre of Excellence for Dark Matter Particle Physics Department of Physics School of Electrical Engineering and Computer Science School of Chemical Engineering and Advanced Materials

Cavity magnonics, which studies the interaction of light with magnetic systems in a cavity, is a promising platform for quantum transducers and quantum memories. At microwave frequencies, the coupling between a cavity photon and a magnon, the quasiparticle of a spin-wave excitation, is a consequence of the Zeeman interaction between the cavity’s magnetic field and the magnet’s macroscopic spin. For each photon-magnon interaction, a coupling phase factor exists, and this is often neglected in simple systems; however, in “loop-coupled” systems, where there are at least as many couplings as modes, the coupling phases become relevant for the physics and lead to synthetic gauge fields. We present experimental evidence of the existence of such coupling phases by considering two spheres made of yttrium-iron-garnet and two different re-entrant cavities. We predict numerically the values of the coupling phases, and we find good agreement between the theory and the experimental data. These results show that in cavity magnonics, one can engineer synthetic gauge fields, which can be useful for cavity-mediated coupling and engineering dark-mode physics.

关键词： Magnetic coupling Magnons Optical & microwave phenomena Ferrimagnets Ferromagnetic resonance Gauge symmetries Holstein-Primakoff method Microwave techniques

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A New Noise-Tolerant Dual-Neural-Network Scheme for Robust Kinematic Control of Robotic Arms With Unknown Models

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IEEE/CAA Journal of Automatica Sinica 2022年第10期9卷 1778-1791页

作者： Ning Tan Peng Yu Zhiyan Zhong Fenglei Ni IEEE the School of Computer Science and Engineering&Key Laboratory of Machine Intelligence and Advanced Computing Ministry of EducationSun Yat-sen UniversityGuangzhou 510006China the School of Automation Guangdong Polytechnic Normal UniversityGuangzhou 510665China the State Key Laboratory of Robotics and Systems Harbin Institute of Technology(HIT)Harbin 150080China

Taking advantage of their inherent dexterity,robotic arms are competent in completing many tasks *** a result of the modeling complexity and kinematic uncertainty of robotic arms,model-free control paradigm has been proposed and investigated ***,robust model-free control of robotic arms in the presence of noise interference remains a problem worth *** this paper,we first propose a new kind of zeroing neural network(ZNN),i.e.,integration-enhanced noise-tolerant ZNN(IENT-ZNN)with integration-enhanced noisetolerant ***,a unified dual IENT-ZNN scheme based on the proposed IENT-ZNN is presented for the kinematic control problem of both rigid-link and continuum robotic arms,which improves the performance of robotic arms with the disturbance of noise,without knowing the structural parameters of the robotic *** finite-time convergence and robustness of the proposed control scheme are proven by theoretical ***,simulation studies and experimental demonstrations verify that the proposed control scheme is feasible in the kinematic control of different robotic arms and can achieve better results in terms of accuracy and robustness.

关键词： Dual zeroing neural networks(ZNN) finite-time convergence model-free robot control robustness analysis

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Hybrid Schrödinger-Ginzburg-Landau (Sch-GL) approach in study of superconducting integrated structures

arXiv

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arXiv 2023年

作者： Stojewski, Bartosz Pomorski, Krzysztof Cracow University of Technology Faculty of Electrical and Computer Engineering Poland Cracow University of Technology Faculty of Computer Science and Telecommunications Poland Quantum Hardware Systems

Various superconducting lattices were simulated and can be treated as lattices of superconducting atoms with preimposed symmetry in 1, 2 and 3 dimensions. Hybrid Schrödinger-Ginzburg-Landau approach is based on the fact of the mathematical similarity of Ginzburg-Landau (GL) and Schrödinger formalisms. Starting from Schrödinger approach by change of term V (x) - E with term α(x) + β(x)|ψ(x)|2we arrived at the Ginzburg-Landau equation. In the presented relaxation algorithm we use one and two dimensional ground energy solutions of Schrödinger equation and placed them as starting trial solution for GL relaxation method. In consecutive steps we increase the nonlinear term in the GL equation which results in achieving a stable approach of solution of GL equation. The obtained numerical results and used methodology form simulation platform bases for study of superconducting integrated structures that can model various superconducting devices. In general, one can model time-dependent geometry of superconducting structures. © 2023, CC0.

关键词： Simulation platform

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Atrocious Impinging of COVID-19 Pandemic on Software Development Industries

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computer systems science & engineering 2021年第2期36卷 323-338页

作者： Wajdi Alhakami Ahmed Binmahfoudh Abdullah Baz Hosam Alhakami Md Tarique Jamal Ansari Raees Ahmad Khan Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Computer Engineering College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Computer Engineering College of Computer and Information SystemsUmm Al-Qura UniversityMakkah21955Saudi Arabia Department of Computer Science College of Computer and Information SystemsUmm Al-Qura UniversityMakkah21955Saudi Arabia Department of Information Technology Babasaheb Bhimrao Ambedkar UniversityLucknow226025India

COVID-19 is the contagious disease transmitted by *** majority of people diagnosed with COVID-19 may suffer from moderate-tosevere respiratory illnesses and stabilize without preferential *** who are most likely to experience significant infections include the elderly as well as people with a history of significant medical issues including heart disease,diabetes,or chronic breathing *** novel Coronavirus has affected not only the physical and mental health of the people but also had adverse impact on their emotional *** months on end now,due to constant monitoring and containment measures to combat COVID-19,people have been forced to live in isolation and maintain the norms of social distancing with no community *** ties,experiences,and partnerships are not only integral part of work life but also form the basis of human ***,COVID-19 brought all such communication to a grinding *** interactions have failed to support the fervor that one enjoys in face-to-face *** COVID-19 disease outbreak has triggered dramatic changes in many sectors,and the main among them is the software *** paper aims at assessing COVID-19’s impact on Software *** impact of the COVID-19 disease outbreak has been measured on the basis of some predefined criteria for the demand of different software applications in the software *** the stated analysis,we used an approach that involves the application of the integrated Fuzzy ANP and TOPSIS strategies for the assessment of the impact of COVID-19 on the software *** of this research study indicate that Government administration based software applications were severely affected,and these applications have been the major apprehensions in the wake of the pandemic’s ***,COVID-19 has had a considerable impact on software industry,yet the damage is not irretrievable and the world’s societies can emerge out

关键词： Coronavirus software industry safety COVID-19 monitoring fuzzy ANP-TOPSIS

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Embedding SDGs in Higher Education Curricula: A Case Study

Embedding SDGs in Higher Education Curricula: A Case Study

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IEEE WIC ACM International Conference on Web Intelligence (WI)

作者： Sri Devi Ravana Myat Noe Win Nasa Zata Dina Maria Fasli Department of Information Systems Faculty of Computer Science & Information Technology Universiti Malaya Kuala Lumpur Malaysia School of Computer Science and Electronic Engineering University of Essex Colchester United Kingdom

Data analytics has enabled evidence-based decision-making, monitoring, and implementation across multiple sectors, making datasets easier to collect, analyze, and understand. Data analytics presents an opportunity for the application of advanced techniques to address challenges in the real world including at the global level such as those associated with the Sustainable Development Goals (SDGs). In educating the next generation of professionals, instilling them with the desire to use technologies for public good and support the implementation of SDGs is highly desirable, but how to do this in higher education settings so as to develop talents and future professionals who can create meaningful impacts towards a nation's and global sustainable growth is not clear. It is still challenging to transform students' perspectives from seeing data analytics projects as purely academic exercises to developing real-world solutions that can have an impact on policy and sustainable development. This paper describes a case study on developing students as professionals and their understanding of SDGs utilizing the Data Analytics Group Project curriculum at the University of Malaya. With the findings, this paper intends to inspire academics to consider how SDGs can be included in the curriculum so that students as trained professionals can adopt a holistic viewpoint of their professional contributions to society and the SDGs in particular, taking into account the cultural, economic, and environmental influences on a country's sustainable development initiatives.

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Information and Education Technology (ICIET), International Conference on

作者： Daniel M. Muepu Atsushi Shirafuji Md Faizul Ibne Amin Yutaka Watanobe Graduate Department of Computer and Information Systems The University of Aizu Aizu-Wakamatsu Japan Department of Computer Science and Engineering The University of Aizu Aizu-Wakamatsu Japan

This paper proposes a recommendation model for similar programming problems to support programming education. In the proposed model, problem similarity is determined according to the similarity of source codes, in terms of the term frequency-inverse document frequency and the effort required to solve the given problem, as calculated according to Halstead metrics. The proposed model can be used to improve student understanding of a programming concept by solving many similar problems simultaneously. In addition, teachers can diversify similar programming problems during practical exercises, assignments, quizzes, and exams. The first experiment carried out in the Aizu Online Judge showed that the user’s accuracy when solving a problem was correlated to the user’s accuracy for a similar problem and, the second experiment showed a matching rate of 70% between the result of our recommendation model and the observations of a teaching assistant involved in programming classes.

关键词： Measurement Source coding Education Programming profession

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Enhancing Parking Online Reservation with a Recommendation System based on User Preferences: A hybrid Approach

Enhancing Parking Online Reservation with a Recommendation S...

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ACS/IEEE International Conference on computer systems and Applications

作者： Serine Guellab Imane Benkhelifa Dept. of Computer Science USTHB University Algiers Algeria Dept. of Computer Systems’Therories and Engineering CERIST Research Center Algiers Algeria

In response to the pressing challenges in parking online reservation platforms, the primary issue this paper addresses is the need for a user-centric parking reservation experience. To tackle this problem, the study aims to develop a recommendation system that enhances user satisfaction and streamlines the parking reservation *** provide personalized parking recommendations, a hybrid multimodal recommendation system is designed, grounded in distance-based recommendation and content-based filtering, and taking into account user preferences and feedback, history behavior and proximity to preferred tourist attractions and points of *** leveraging a rich dataset comprising 1804 parking items, results indicate a notable improvement and more user-centric user experience, as the system suggests parking lots in line with user preferences and points of interest. User feedback mechanisms are seamlessly integrated, facilitating continuous adaptation and refinement based on user convenience and past *** work shows significant potential in enhancing user satisfaction and streamlining the user experience in parking online reservation systems.

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Late-Fusion Multimodal Human Detection Based on RGB and Thermal Images for Robotic Perception

Late-Fusion Multimodal Human Detection Based on RGB and Ther...

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European Conference on Mobile Robots (ECMR)

作者： Elísio Sousa Kennedy O. S. Mota Iago P. Gomes Luís Garrote Denis F. Wolf Cristiano Premebida Department of Electrical and Computer Engineering Institute of Systems and Robotics University of Coimbra Portugal Institute of Mathematics and Computer Science University of São Paulo Brazil

This paper addresses the problem of detecting humans in RGB and Thermal (long-wave IR) images taken by cameras mounted onboard a mobile robot. Human/Pedestrian detection is currently one of the most pertinent object detection problems, mainly due to safety concerns in autonomous vehicles. The majority of approaches apply deep-learning techniques based solely on RGB images. However, they have a few shortcomings, namely that during foggy weather, nighttime, and low-light scenarios, these images may not contain sufficient information. To address these issues, this work studies the use of thermal cameras as a complementary source of information for human detection in indoor and outdoor environments. The proposed approach uses YOLOv5 to detect pedestrians in both thermal and RGB images. Moreover, the different modalities are combined using early and late fusion techniques. Evaluation of the proposed approach is carried out in the FLIR Aligned dataset and in a new in-house dataset. Results indicate that the use of fusion techniques highlights a promising way to improve the overall performance in this application domain.

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Revolutionizing Connectivity and Data Processing in IoT Ecosystems through Edge Computing

Revolutionizing Connectivity and Data Processing in IoT Ecos...

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2024 IEEE International Conference on Recent Advances in science and engineering Technology, ICRASET 2024

作者： Kumari, V. Sheeja Pillai, N. Muthuvairavan Jayarin, P.Jesu David, D. Beulah Jenin, J.S. Saveetha Institute of Medical and Technical Sciences Saveetha University Saveetha School of Engineering Department of Computational Intelligence Thandalam Tamil Nadu Chennai India R.M.D Engineering College Department of Computer Science and Business Systems Tamil Nadu Thiruvallur India Saveetha Institute of Medical and Technical Sciences Saveetha University Saveetha School of Engineering Department of Information Technology Thandalam Tamil Nadu Chennai India Care College of Engineering Department of Electronics and Communication Engineering Tamil Nadu Trichy India

ISBN: (纸本)9798350388602

This work, which explores the performance of the existing five IoT sensor classification algorithms and develops five more algorithms, intends to later compare the obtained classification accuracies. In this evaluation, the algorithms included are Decision Tree, Random Forest, K-Nearest Neighbors, Support Vector Machine, and Naive Bayes, while the proposed ones are called EdgeNet, IoTBoost, EdgeSVM, DeepEdge, and EdgeFusionNet. The performances are evaluated using the key measures of precision and processing time. Results show that the algorithms under study are usually more accurate than well-known ones, with EdgeFusionNet reaching 94% accuracy which is the highest accuracy. In the selection of algorithms, existing ones show different performance but the Decision Tree and Naive Bayes demonstrate relatively faster processing times compared to the Random Forest and the Support Vector Machine. Yet, the proposed EdgeSVM algorithm shows almost the fastest processing time which exceeds Zokfl2 and other algorithms onference. On top of that, extra measures comprise memory usage, energy efficiency, scalability, model size, and robustness are evaluated for the suggested algorithms. Thus, the results may be inferred that the suggested algorithms provide the advanced solutions for the IoT sensor data classification, that have higher accuracy and comparable or better time complexity in comparison with the existing ones. These outcomes give useful information for researchers as well as technicians that using IoT techniques for the sake of various applications purposes. © 2024 IEEE.

关键词： Support vector machines

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