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European Control Conference (ECC)

作者： Giovanna Amorim María Santos Shinkyu Park Alessio Franci Naomi Ehrich Leonard Dept. of Mechanical and Aerospace Engineering Princeton Univ. Princeton NJ USA Computer Electrical and Math. Science and Eng. Div. King Abdullah Univ. of Science and Technology (KAUST) Thuwal Saudi Arabia Department of Electrical Engineering and Computer Science University of Liege Liége Belgium WEL Research Institute Wavre Belgium

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

We propose a threshold decision-making frame-work for controlling the physical dynamics of an agent switching between two spatial tasks. Our framework couples a nonlinear opinion dynamics model that represents the evolution of an agent's preference for a particular task with the physical dynamics of the agent. We prove the bifurcation that governs the behavior of the coupled dynamics. We show by means of the bifurcation behavior how the coupled dynamics are adaptive to the physical constraints of the agent. We also show how the bifurcation can be modulated to allow the agent to switch tasks based on thresholds adaptive to environmental conditions. We illustrate the benefits of the approach through a multi-robot task allocation application for trash collection.

关键词： Adaptation models Decision making Europe Switches Bifurcation Control systems Resource management

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Multiband highly sensitive metamaterial-based THz absorber for edible oil adulteration sensing

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Optik 2024年 307卷

作者： Anowarul Haque, S.M. Sohayeb Hossain, Md Alqahtani, Abdulrahman Islam, Mohammad Tariqul Moniruzzaman, Md. Samsuzzaman, Md. Dept. of Electrical Electronic and Systems Engineering Faculty of Engineering and Built Environment Universiti Kebangsaan Malaysia Selangor Bangi43600 Malaysia Dept. of Electrical and Electronic Engineering Mymensingh Engineering College Bangladesh Department of Biomedical Technology College of Applied Medical Sciences in Al-Kharj Prince Sattam Bin Ab-dulaziz University Al-Kharj11942 Saudi Arabia Department of Medical Equipment Technology College of Applied Medical Science Majmaah University Majmaah City11952 Saudi Arabia Dept. of Electrical and Electronic Engineering College of Engineering and Technology International University of Business Agriculture and Technology Dhaka Uttara1230 Bangladesh Dept. of Computer and Communication Engineering Faculty of Computer Science and Engineering Patuakhali Science and Technology University Bangladesh Faculty of Graduate Studies Daffodil International University Daffodil Smart City Birulia Dhaka Savar1216 Bangladesh

A terahertz (THz) wave technology is very appealing for applications in detection in biomedicine, biological spectroscopy, material characterization, detection, imaging, sensing, and other convenient applications. Metamaterials (MMs) are artificial structures that have structures in a regular periodic arrangement and don't exist in nature. By utilizing a proposed terahertz metamaterial absorber, a broad spectrum of adulterated lubricants can be detected. It is an efficient detection process that enables the development of a THz detection approach by making use of the metamaterial as a sensor. The proposed terahertz absorber is analyzed and optimized using the CST Microwave Studio 2019 software. The article proposed a multiband THz metamaterial absorber with a unit size of 70 µm. According to the demonstrated results, we can achieve five narrow absorption peaks with perfect absorption within the frequency range between (0.2–4.2) Terahertz. Also, the result shows that, the average absorbance of 99.07% at the resonance frequencies of 0.56, 1.42, 2.676, 3.14, and 3.89 THz. The E (electric) and H (magnetic)-field distributions on the resonator at different resonance frequencies were also analyzed as well as. The recommended metamaterial absorber has a good sensing capability at different resonant frequencies, with refractive index sensitivities of 80 GHz/RIU, 240 GHz/RIU, 480 GHz/RIU, 480 GHz/RIU, and 520 GHz/RIU obtained by modifying the refractive index of the sample holder or the analytic layer, respectively. As a result, the proposed detector has a high refractive index sensitivity, high Q-factor, and high FOM, making it suitable for detecting oil adulteration. © 2024 Elsevier GmbH

关键词： Metamaterials

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An IoHT System Utilizing Smart Contracts for Machine Learning -Based Authentication

An IoHT System Utilizing Smart Contracts for Machine Learnin...

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International Conference on Emerging Trends in Networks and computer Communications (ETNCC)

作者： Kamal Upreti Prashant Vats Gauri Borkhade Ranjana Dinkar Raut Sheela Hundekari Jyoti Parashar Dept. of Computer Science CHRIST(Deemed to be University) Delhi NCR Ghaziabad India Dept. of CSE SCSE Manipal University Jaipur Jaipur Rajasthan India Dept. of Electronics & Telecommunication Engg Bharati Vidyapeeth College of Engineering Navi Mumbai Maharashtra India PGTD Applied Electronics Sant Gadge Baba Amravati University Amravati Maharashtra India MIT ADT University Loni Kalbhor Pune Pune India Dept. of Computer Science & Engg. ADGITM New Delhi India

The Internet of Healthcare Things (IoHT) and blockchain technologies have made it feasible to share data in a secure and effective manner, but it is still challenging to ensure the data's veracity and privacy. This paper presents a blockchain authentication method that utilizes Machine Learning (ML) techniques that use smart contracts to ensure the security and privacy of IoHT data. The process utilizes smart contracts to manage access control and ensure data integrity, and deep learning algorithms to identify and validate the accuracy of user data. Furthermore, the approach improves the resilience and dependability of the authentication process and permits secure data ex-change between multiple IoHT systems. The proposed approach provides a potentially revolutionary solution to enhance the safety and confidentiality of IoHT data. It has the potential to fundamentally change how healthcare is provided in the future.

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Simheuristics: An Introductory Tutorial

Simheuristics: An Introductory Tutorial

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Simulation Winter Conference

作者： Angel A. Juan Yuda Li Majsa Ammouriova Javier Panadero Javier Faulin Dept. of Applied Statistics and Operations Research Universitat Politècnica de València Alcoy SPAIN Dept. of Computer Science Universitat Oberta de Catalunya Barcelona SPAIN Institute of Smart Cities Dept. of Statistics Computer Science and Mathematics Public University of Navarre Pamplona SPAIN

ISBN: (纸本)9781665476621

Both manufacturing and service industries are subject to uncertainty. Probability techniques and simulation methods allow us to model and analyze complex systems in which stochastic uncertainty is present. When the goal is to optimize the performance of these stochastic systems, simulation by itself is not enough and it needs to be hybridized with optimization methods. Since many real-life optimization problems in the aforementioned industries are NP-hard and large scale, metaheuristic optimization algorithms are required. The simheuristics concept refers to the hybridization of simulation methods and metaheuristic algorithms. This paper provides an introductory tutorial to the concept of simheuristics, showing how it has been successfully employed in solving stochastic optimization problems in many application fields, from production logistics and transportation to telecommunication and insurance. Current research trends in the area of simheuristics, such as their combination with fuzzy logic techniques and machine learning methods, are also discussed.

关键词： Uncertainty Metaheuristics Stochastic processes Transportation Tutorials Machine learning Manufacturing

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A Distributed Blockchain Based PKI (BCPKI) architecture to enhance privacy in VANET 2

A Distributed Blockchain Based PKI (BCPKI) architecture to e...

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2nd International Workshop on Human-Centric Smart Environments for Health and Well-Being, IHSH 2020

作者： Moussaoui, Djilali Kadri, Benamar Feham, Mohammed Ammar Bensaber, Boucif University of Tlemcen Telecomunication Dept. Tlemcen Algeria Uqtr University LAboratoire de Mathématiques et Informatique Appliquée Computer Science Dept Trois Rivières Canada

ISBN: (纸本)9781665440844

Among the important challenges for Vehicular Adhoc Network (VANET) Security and Privacy. Most of the solutions for privacy in vanet are based on pseudonyms. And the pseudonyms are digital certificates with very limited information, valid for a short time, and hide the identity of the vehicle. The pseudonym operations (issuing, changing, and revoking) are centralized by a certification authority. In our paper, we propose a fully distributed management for pseudonyms in VANETs. We use the blockchain technology to perform the different operations related to pseudonyms. Our proposal use two blockchains, one for registering pseudonyms, the second for revoked ones. The vehicles are considered as miners in the blockchain. Our approach makes the vehicles in VANET more autonomous in managing the security, and reduce the exchanged data with a centralized authority (Certificate Authority-CA). © 2021 IEEE.

关键词： Blockchain

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Analysis of the Indian IT sector–investigating the role of technology for software process improvement through knowledge management 10

Analysis of the Indian IT sector–investigating the role of ...

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10th IEEE International Conference on Communication Systems and Network Technologies, CSNT 2021

作者： Chugh, Mitali Bhadoria, Robin Singh Uttarakhand Technical University Uttarakhand Dehradun India UPES Uttarakhand Dehradun India Dept. of Computer Science and Engineering Birla Institute of Applied Sciences Bhimtal Uttarakhand 263136 India

ISBN: (纸本)9780738105239

Knowledge is progressively recognized as an important organizational resource offering a competitive advantage. Information Technology (IT) in Knowledge Management (KM) is vital for any organization desiring to exploit developing technologies for managing their knowledge resources. KM primarily comprises knowledge creation and/or acquisition, knowledge storage and retrieval, knowledge transfer, and knowledge application. IT aids progression and helps sustain organizational knowledge. The creation and sharing of experience bases is enabled in a simplified way with the help of IT. Information System researchers introduced a class of Information System referred to as Knowledge Management Systems (KMS). KMS are functional for management of several KM processes. IT can support KM in diverse ways, and there are various technologies comprising KMS. This research discusses the role and the relevance of latest technology in the field of knowledge management and uncovers the state of technology-mediated KM in Indian IT sector through a survey. © 2021 IEEE.

关键词： Knowledge management

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Simulation-based evaluation of a synchronous transaction model for time-sensitive software-defined networks

arXiv

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arXiv 2021年

作者： Haugg, Tobias Soltani, Mohammad Fazel Häckel, Timo Meyer, Philipp Korf, Franz Schmidt, Thomas C. Dept. Computer Science Hamburg University of Applied Sciences Germany

Real-time networks based on Ethernet require robust quality-of-service for time-critical traffic. The Time-Sensitive Networking (TSN) collection of standards enables this in real-time environments like vehicle on-board networks. Runtime reconfigurations in TSN must respect the deadlines of real-time traffic. Software-Defined Networking (SDN) moves the control plane of network devices to the SDN controller, making these networks programmable. This allows reconfigurations from a central point in the network. In this work, we present a transactional model for network reconfigurations that are synchronously executed in all network devices. We evaluate its performance in a case study against non-transactional reconfigurations and show that synchronous transactions enable consistency for reconfigurations in TSN without increased latencies for real-time frames. Copyright © 2021, The Authors. All rights reserved.

关键词： Software defined networking

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Technical Debt Management: The Road Ahead for Successful Software Delivery

arXiv

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arXiv 2024年

作者： Avgeriou, Paris Ozkaya, Ipek Chatzigeorgiou, Alexander Ciolkowski, Marcus Ernst, Neil A. Koontz, Ronald J. Poort, Eltjo Shull, Forrest Dept. of Computing Science University of Groningen Groningen Netherlands Software Engineering Institute Carnegie Mellon University PittsburghPA United States Dept. of Applied Informatics University of Macedonia Thessaloniki Greece QAware GmbH München Germany Department of Computer Science University of Victoria Victoria Canada The Boeing Company MesaAZ United States CGI Rotterdam Netherlands

Technical Debt, considered by many to be the 'silent killer' of software projects, has undeniably become part of the everyday vocabulary of software engineers. We know it compromises the internal quality of a system, either deliberately or inadvertently. We understand Technical Debt is not all derogatory, often serving the purpose of expediency. But, it is associated with a clear risk, especially for large and complex systems with extended service life: if we do not properly manage Technical Debt, it threatens to "bankrupt" those systems. Software engineers and organizations that develop softwareintensive systems are facing an increasingly more dire future state of those systems if they do not start incorporating Technical Debt management into their day to day practice. But how? What have the wins and losses of the past decade of research and practice in managing Technical Debt taught us and where should we focus next? In this paper, we examine the state of the art in both industry and research communities in managing Technical Debt;we subsequently distill the gaps in industrial practice and the research shortcomings, and synthesize them to define and articulate a vision for what Technical Debt management looks like five years hence. © 2024, CC BY-NC-ND.

关键词： Industrial research

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Potential of Simulation Effort Reduction by Intelligent Simulation Budget Management for Multi-Item and Multi-Stage Production Systems 22

Potential of Simulation Effort Reduction by Intelligent Simu...

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Proceedings of the Winter Simulation Conference

作者： Wolfgang Seiringer Klaus Altendorfer Juliana Castaneda Lisardo Gayan Angel A. Juan School of Business and Management University of Applied Sciences Upper Austria Steyr AUSTRIA Computer Science Department Universitat Oberta de Catalunya Barcelona SPAIN Dept. of Applied Statistics and Operations Research Universitat Politcnica de Valncia Alcoy SPAIN

Simulation is utilized to analyze multi-item and multi-stage production systems that are driven by material requirements planning (MRP). The range of possible parameter combinations and solutions increases as the model of the production system includes more components. In simulation experiments with a fixed number of replications per iteration, it might be unfeasible to test a large range of these MRP parameters. This paper discusses how to efficiently manage the simulation budget, to avoid wasting it in exploring non-promising solutions. Therefore, intelligent simulation budget management (SBM) is applied, where the results of the current iteration's replications are compared to the average results of the previous iterations. The current iteration is skipped if its average overall cost is outside the defined percentile boundaries. A simulation study using two multi-item and multi-stage MRP systems is performed to evaluate SBM potential. The results show that the SBM methodology leads to significantly reduced simulation efforts.

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Explainable RNN Classification of Right Ventricular Dysfunction from Echocardiogram Reports

Explainable RNN Classification of Right Ventricular Dysfunct...

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IEEE International Conference on Big Data

作者： Arun Rajaratanam Roberto Corizzo Zois Boukouvalas Adult and Family Medicine Mid-Atlantic Permanente Group Alexandria VA USA Department of Computer Science American University Washington DC USA Dept. of Math and Statistics American University Washington D.C USA

ISBN: (数字)9798350362480

ISBN: (纸本)9798350362497

Accurately identifying patients with Right Ventricular Dysfunction (RVD) is critical for timely diagnosis and treatment, yet it remains a significant challenge in clinical practice due to the complexity and variability of echocardiography text reports. In this study, we address this crucial problem by evaluating the effectiveness of recurrent neural networks (RNNs) in classifying patients with and without RVD from echocardiography text reports. We demonstrate that our model exhibits strong performance, with high recall and precision in identifying RVD, underscoring its potential utility in clinical settings. Furthermore, we enhance the interpretability of the framework by leveraging the Local Interpretable Model-Agnostic Explanations (LIME) framework. This approach allows us to extract and validate meaningful semantic information related to RVD, providing deeper insights into the model’s local predictive capabilities and improving transparency in decision-making.

关键词： Deep learning Recurrent neural networks Echocardiography Semantics Decision making Predictive models Data models Complexity theory Reliability Data mining

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