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检索条件"任意字段=20th Conference on System Modeling and Optimization"

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A Computationally Efficient Method for Modelling of Circulating Current Loss in Electrical Machines with Stranded Windings

A Computationally Efficient Method for Modelling of Circulat...

引用

Electromagnetic Field Computation-Long papers (CEFC-LONG), IEEE Biennial conference on

作者： Yapeng Jiang Yunjun Guo Qingyu Yang Junquan Chen Kai Bo Dong Wang National Key Laboratory of Science and Technology on Vessel Integrated Power System Naval University of Engineering Wuhan China Hubei East Lake Laboratory Wuhan China

For high-speed electrical machines, the AC copper loss caused by high electrical frequency is very considerable. this paper presents a computationally efficient method for evaluating the circulating current between parallel strands in electrical machines with stranded windings. Firstly, the lumped parameter circuit model is introduced, and then the key parameters, namely the mutual slot-leakage inductance matrix, are calculated by the proposed non-strand finite element model. Compared with the traditional parameter extraction method, the time consumption of the proposed model is greatly reduced. Finally, the accuracy of the method is validated by FE simulations.

关键词： Inductance Computational modeling Windings Computational efficiency Finite element analysis Copper Integrated circuit modeling

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MVDC solid-state breaker Control optimization by Real Time Control Hardware in the Loop tests

MVDC solid-state breaker Control Optimization by Real Time C...

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20th IEEE International conference on Environment and Electrical Engineering (EEEIC) / 4th IEEE Industrial and Commercial Power systems Europe conference (I and CPS Europe)

作者： Clerici, Alessio Chiumeo, Riccardo Gandolfi, Chiara RSE Spa Transmiss & Distribut Dept Milan Italy

ISBN: (纸本)9781728174556

this work presents the optimization process of real time control equipment for a Medium Voltage Direct Current (MVDC) static switch-limiter device. Description of the control strategy and its implementation into a microcontroller programmable board are described. system performances have been analyzed by real time Control Hardware in the Loop (CHIL) simulations. Initial results did not match expected performances. Control has been optimized by hardware and software features, like interrupt routines and low- level programming. Final tests showed a substantial improvement of system performances, like speed response and current limitation accuracy.

关键词： optimization CHIL real-time interrupts MVDC

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VM Performance optimization Virtual Machine Migration Method Based on Ant Colony optimization in Cloud

VM Performance Optimization Virtual Machine Migration Method...

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IEEE International conference on High Performance Computing and Communications (HPCC)

作者： Hui Zhao Shangshu Li Jing Wang Jianhua Li Xidian University China Key Laboratory of Smart Human-Computer Interaction and Wearable Technology of Shaanxi Province China

Virtual machine migration (VMM) is one of the most commonly used technologies in cloud platforms. However, the existing VMM methods did not try to optimize VM performance for cloud users when migrating VMs, so as to affect the users' experiences. In this paper, a VM Performance optimization Virtual Machine Migration method (POVMM) is proposed, which can bring benefits to both cloud users and cloud service providers. It first takes the workload of PM into account to establish an improved workload-based VM performance model, and then uses the trained model to predict VM performance after migration. then it formulates VMM as a multi-objective optimization problem, whose optimization objectives include maximizing VM performance, minimizing migration costs of all migrat-ed VMs and reducing the number of working PMs in cloud. Lastly, an ACO-based (ant colony optimization) algorithm, POVMM, is proposed to obtain the approximate optimal solution of the VMM problem. the simulation experiment is completed on the cloud simulation software, CloudSim. through comparing with the other VMM algorithms, the POVMM algorithm has better results, which proves the effectiveness of the POVMM algorithm.

关键词： Cloud computing Ant colony optimization Virtual machine monitors Computational modeling Software algorithms Predictive models Approximation algorithms

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JITBULL: Securing JavaScript Runtime with a Go/No-Go Policy for JIT Engine

JITBULL: Securing JavaScript Runtime with a Go/No-Go Policy ...

引用

International conference on Dependable systems and Networks (DSN)

作者： Jean-Baptiste Decourcelle Boris Teabe Daniel Hagimont IRIT Université de Toulouse CNRS Toulouse INP UT3 France

ISBN: (数字)9798350341058

ISBN: (纸本)9798350341065

Nowadays, most services are delivered through the web and thus heavily rely on JavaScript (JS). To accommodate the need for more performance, JS runtimes integrated Just-In-Time (JIT) compilation engines, which compile frequently-called portions of code for faster execution. To produce efficient machine code, the JIT applies complex optimization passes on the code in question. However, inadequate modeling of the side effects of these optimizations can introduce vulnerabilities in certain optimization passes. Such vulnerabilities are regularly discovered, and often have a high impact. Once a vulnerability is identified, it is eventually patched, but not without involving several steps (development, testing, release, user consent), leaving the system vulnerable for a relatively long period: the vulnerability window. We propose JITBULL, a solution that secures the JIT engines of JS runtimes during the vulnerability window by leveraging a vulnerability's demonstrator codes. To that end, JITBULL extracts the effects of JIT compiler optimization passes on said vulnerability demonstrator codes. For every subsequent JITed code, JITBULL compares the effects of its optimization passes with those on the demonstrator codes. If similarities are detected, JITBULL assumes that the currently executing script may be malicious and disables the related optimization passes, or if that's not possible, the whole JIT engine. We implemented JITBULL in Firefox's JS runtime (SpiderMonkey) and tested it against several known vulnerabilities with public demonstrator codes. Our results demonstrate that JITBULL consistently safeguards the JIT engine against exploitation by a variant of a known vulnerability. Moreover, we show that JITBULL exhibits a false positive rate of less than 5 % on the JS Octane benchmark suite, while causing an acceptable overhead of less than 20 %.

关键词： Codes Runtime Benchmark testing Browsers Security Engines optimization

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Characterization of Human Trust in Robot through Multimodal Physical and Physiological Biometrics in Human-Robot Partnerships

Characterization of Human Trust in Robot through Multimodal ...

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IEEE International conference on Automation Science and Engineering (CASE)

作者： Jesse Parron Rui Li Weitian Wang Mengchu Zhou School of Computing Montclair State University Montclair NJ USA Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ USA

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

Trust is an attribute that many people use daily, whether consciously thinking of it or not. Although commonly designated as a firm belief in reliability, trust is more complex than many think. It is not just physical, but rather an emotion, feeling, or choice that has many layers, and can be influenced in a variety of ways. As robotics and artificial intelligence grow, humans have to deliberate whether they trust working with these technical counterparts or not. In this work, we build computational models to quantitatively characterize and analyze humans' trust in robots using multimodal physical and physiological biometric data based on the TrustBase we have created through user studies in human-robot collaborative tasks. During human-robot collaborative processes, we have collected physical and physiological attribute data of human subjects as well as the users' trust levels for each interaction. this data is used to develop a database known as TrustBase. With the data from TrustBase, computational and analytical approaches are used to investigate the correlation between robot performance factors and humans' trust levels and to characterize humans' trust in robots during human-robot collaboration. Results and their analysis suggest the effectiveness of the developed models, providing new findings to the human factors and cognitive ergonomics in human-robot interaction. Future research directions are also discussed.

关键词： Biometrics Analytical models Computational modeling Biological system modeling Human-robot interaction Collaboration Human factors Reliability engineering Physiology Robots

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Ensemble-based Cyber Intrusion Detection for Robust Smart City Protection

Ensemble-based Cyber Intrusion Detection for Robust Smart Ci...

引用

International conference on Distributed Computing in Sensor systems (DCOSS)

作者： Alaa Alhowaide Izzat Alsmadi Belal Alsinglawi Computer Science Faculty of Science Memorial University of Newfoundland Canada Computing Engineering and Mathematical Sciences Texas A&M San Antonio San Antonio USA Computational Systems Zayed University Abu Dhabi United Arab Emirates

ISBN: (数字)9798350369441

ISBN: (纸本)9798350369458

the rapid rise of 5G networks has accelerated the integration of smart cities, marking the emergence of increased intelligence in urban environments, often referred to as Smart Cities. this swift integration has interconnected a wide range of devices and systems, thereby exposing them to potential vulnerabilities. As a result, a smart urban landscape has emerged where valuable and sensitive information is shared without adequate attention to security considerations. Given these challenges, it is essential to implement an effective cloud-based Intrusion Detection system (IDS) for the security of smart cities. this work examines the reliability and robustness of various ensemble learning models, focusing on evaluating the performance and efficiency of an IDS strategy based on machine learning to enhance the security of IoT in smart urban networks. We conducted experimental procedures on three commonly used datasets to achieve the objectives of our study. the results obtained from these procedures are crucial for developing practical IDS solutions that address the ever-changing challenges posed by diverse, smart, cloud-based network traffic systems in smart cities.

关键词： Measurement Cloud computing Smart cities Biological system modeling Intrusion detection Focusing Robustness

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Intelligent system for Distributed Deep Learning Training Traffic optimization

Intelligent System for Distributed Deep Learning Training Tr...

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IEEE International conference on High Performance Computing and Communications (HPCC)

作者： Weipeng Lu Shuang Wu Junhui Ou Bing Niu Jin He Kevin Song Xinwei Zheng USTC Hefei China Vmware Beijing China

Distributed training crossing multiple computing nodes and accelerators has been the mainstream solution for large model training. Precedent work on distributed deep learning (DDL) training acceleration has focused on improving the efficiency of communication and GPU resource scheduling, with little attention given to network bandwidth usage. However, due to cluster GPU fragmentation, more than one training job is frequently assigned to the same node to reduce waiting time. the competition for network bandwidth among various distributed training jobs becomes a problem that cannot be overlooked, and this competition results in a considerable reduction in training speed. We propose a system deployed in cluster nodes that includes traffic monitoring, classification, and prediction of DDL training status and implement a priority-based traffic scheduling policy that considers DDL training features. We demonstrate that this policy is beneficial compared to Linux's default policy, which can increase training speed by approximately 18%. Additionally, we increase the training speed by approximately 20% in the case of continuous background traffic by increasing the bandwidth priority during DDL training.

关键词： Training Deep learning Processor scheduling Linux Computational modeling Graphics processing units Bandwidth

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DRL-based Task Offloading for Networked UAVs with Random Mobility and Collision Avoidance

DRL-based Task Offloading for Networked UAVs with Random Mob...

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IEEE International conference on Wireless and Mobile Computing, Networking And Communications (WiMob)

作者： Xixin Zhang Junfei Xie Department of Electrical and Computer Engineering University of California San Diego San Diego State University La Jolla USA Department of Electrical and Computer Engineering San Diego State University San Diego USA

ISBN: (数字)9798350387445

ISBN: (纸本)9798350387452

Unmanned Aerial Vehicles (UAVs) have gained widespread use across various fields due to their flexibility and multifunctionality. However, their limited onboard computing capacity is often criticized for hindering their ability to execute complex tasks in real-time. To address this challenge, Networked Airborne Computing (NAC) has emerged, which leverages the collective computing power of multiple UAVs to enable efficient handling of large-scale data processing, real-time analytics, and complex mission coordination. Despite its potential, research in this area is still in its infancy. In this paper, we consider a typical NAC scenario where multiple UAVs with collision avoidance capabilities share resources while moving randomly within an area. Without prior knowledge of the system models, we aim to optimize task allocation among UAVs with uncertain mobility. To achieve this, we propose a Deep Reinforcement Learning algorithm based on the Twin Delayed Deep Deterministic Policy Gradient (TD3). Simulation results demonstrate that our approach significantly speeds up task execution compared to existing methods.

关键词： Wireless communication Uncertainty Simulation Computational modeling system performance Performance gain Autonomous aerial vehicles Real-time systems Resource management Collision avoidance

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A Blockchain and Self-Sovereign Identity-Based Platform for Electronic Health Records Management Under GDPR

A Blockchain and Self-Sovereign Identity-Based Platform for ...

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IEEE International conference on Wireless and Mobile Computing, Networking And Communications (WiMob)

作者： Hela Makina Asma Ben Letaifa Abderrezak Rachedi MEDIATRON Lab. Sup'Com University of Carthage Tunis Tunisia COMPUTER SCIENCE Lab. Univ. Gustave Eiffel CNRS Marne-la-Vallée France

ISBN: (数字)9798350387445

ISBN: (纸本)9798350387452

this paper presents a novel framework for secure management of Electronic Health Records (EHRs). It addresses the challenges of privacy protection, data ownership, and regulatory compliance. By adopting a patient-centric approach, the architecture ensures compliance with international regulations while providing efficient data security and access control mechanisms. Leveraging blockchain technology, smart contracts, De-centralized Identifiers (DIDs) and InterPlanetary File system (IPFS), the model facilitates decentralized au-thentication and authorization, ensuring patients full ownership and enabling multiple user access to medical records. Blockchain technolgy and IPFS ensure data integrity and immutability and transaction transparency and auditability. Smart contracts are implemented to leverage multiple transcations to grant, get, delegate, and revoke access to eHealth data. As a proof of concept, we implemented the proposed architecture on a polygon blockchain and integrate the *** API for DID generation, enabling the patient with the right to grant and revoke access for his own records. the proposed architecture aligns with General Data Protection Regulation (GDPR) directives concerning personal data privacy, guaranteeing both data security and transaction transparency and traceability.

关键词： Data privacy Data security Smart contracts Unified modeling language Regulation Blockchains Electronic healthcare InterPlanetary File system General Data Protection Regulation Electronic medical records

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20th Sustainable, Environment and Architecture

20th Sustainable, Environment and Architecture

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20th Sustainable, Environment and Architecture, SENVAR 2020

the proceedings contain 80 papers. the topics discussed include: thermal environment control of buildings using installation of plants and metal panels on brick walls;thermal comfort of the outdoor transition space in the dean's office building;thermal comfort analysis of residential home in coastal city based on physiological equivalent temperature (PET) index and operative temperature zone;thermal and visual comfort analysis using CBE tools and Velux simulation of classroom in R.21 in Gedung Kuliah Bersama V University of Bengkulu;design of sustainability of solar panel integration in a green building complex of Wonogiri regent office;the influence of the sound absorber application to the acoustics conditions and the thermal transfer value of the building envelope in open plan office;optimization of thermal comfort in Rifain digital printing: vertical garden with water wall system concept;energy efficiency in church building based on Sefaira energy use intensity standard;and estimation of energy consumption efficiency in office rooms cooling systems to create thermal comfort for the user.

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