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10th International Conference on engineering and Emerging Technologies, ICEET 2024

作者： Nurgali, Raiymbek Ahmad, Jawad Hashmi, Mohammad School of Engineering and Digital Science Nazarbayev University Department of Electrical and Computer Engineering Astana Kazakhstan

ISBN: (纸本)9798331532895

This paper presents a novel millimeter-wave (mmWave) antenna design for 5G applications, featuring a parasitic elliptical patch antenna with beam-switching capabilities and coaxial feeding. The antenna was initially designed as a single-element patch antenna for the 28 GHz mmWave band, demonstrating favorable impedance matching and broadside radiation patterns. Circular parasitic patches with and without vias were strategically placed around the main radiator to enhance the radiation pattern and gain. The single-element design achieved an impedance bandwidth of 2.7 GHz (26.8-29.5 GHz) and a gain of 7.5 dBi at 28 GHz. The optimized parasitic structure, consisting of carefully positioned open and short circular patches, significantly improved the antenna's performance. The parasitic design exhibited an enhanced return loss of -30.5 dB, indicating excellent impedance matching, and a gain of approximately 8 dBi. The proposed antenna exhibits enhanced performance characteristics in terms of gain, return loss, and beam steering capabilities, and it is suitable for next-generation wireless communication systems. © 2024 IEEE.

关键词： Slot antennas

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AI-Based Automatic System for Assessing Upper-Limb Spasticity of Patients With Stroke Through Voluntary Movement

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IEEE Journal of Biomedical and Health Informatics 2024年第2期28卷 742-752页

作者： Lee, I-Jung Hu, Yu Hen Hsiao, Pei-Chi Yang, Shu-Yu Lin, Hsin-Te Chen, Yu-Chung Lin, Bor-Shing National Taipei University College of Electrical Engineering and Computer Science New Taipei City237303 Taiwan University of Wisconsin-Madison Department of Electrical and Computer Engineering MadisonWI53706 United States Chi-Mei Medical Center Department of Physical Medicine and Rehabilitation Tainan71004 Taiwan Chi Mei Hospital Department of Physical Medicine and Rehabilitation Tainan73657 Taiwan National Taipei University Department of Computer Science and Information Engineering New Taipei City237303 Taiwan

Spasticity is a common complication for patients with stroke, but only few studies investigate the relation between spasticity and voluntary movement. This study proposed a novel automatic system for assessing the severity of spasticity (SS) of four upper-limb joints, including the elbow, wrist, thumb, and fingers, through voluntary movements. A wearable system which combined 19 inertial measurement units and a pressure ball was proposed to collect the kinematic and force information when the participants perform four tasks, namely cone stacking (CS), fast flexion and extension (FFE), slow ball squeezing (SBS), and fast ball squeezing (FBS). Several time and frequency domain features were extracted from the collected data, and two feature selection approaches based on recursive feature elimination were adopted to select the most influential features. The selected features were input into five machine learning techniques for assessing the SS for each joint. The results indicated that using CS task to assess the SS of elbow and fingers and using FBS task to assess the SS of thumb and wrist can reach the highest weighted-average F1-score. Furthermore, the study also concluded that FBS is the optimal task for assessing all the four upper-limb joints. The overall result shown that the proposed automatic system can assess four upper-limb joints through voluntary movements accurately, which is a breakthrough of finding the relation between spasticity and voluntary movement. © 2013 IEEE.

关键词： Learning systems

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A Low-Complexity Diversity-Preserving Universal Bit-Flipping Enhanced Hard Decision Decoder for Arbitrary Linear Codes

IEEE Open Journal of Vehicular Technology

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IEEE Open Journal of Vehicular Technology 2024年 5卷 1-22页

作者： Bere, Praveen Sai Khan, Mohammed Zafar Ali Hanzo, Lajos Department of Electrical Engineering Indian Institute of Technology Hyderabad Hyderabad India School of Electronics and Computer Science University of Southampton Southampton United Kingdom

V2X (Vehicle-to-everything) communication relies on short messages for short-range transmissions over a fading wireless channel, yet requires high reliability and low latency. Hard-decision decoding sacrifices the preservation of diversity order, leading to pronounced performance degradation in fading channels. By contrast, soft-decision decoding retains diversity order, albeit at the cost of increased computational complexity. We introduce a novel enhanced hard-decision decoder termed as the Diversity Flip decoder (DFD) designed for preserving the diversity order. Moreover, it exhibits ‘universal’ applicability to all linear block codes. For a $\mathscr {C}(n,k)$ code having a minimum distance ${d_{\min }}$, the proposed decoder incurs a worst-case complexity order of $2^{({d_{\min }}-1)}-1$. Notably, for codes having low ${d_{\min }}$, this complexity represents a significant reduction compared to the popular soft and hard decision decoding algorithms. Due to its capability of maintaining diversity at a low complexity, it is eminently suitable for applications such as V2X (Vehicle-to-everything), IoT (Internet of Things), mMTC (Massive Machine type Communications), URLLC (Ultra-Reliable Low Latency Communications) and WBAN (Wireless Body Area Networks) for efficient decoding with favorable performance characteristics. The simulation results provided for various known codes and decoding algorithms validate the performance versus complexity benefits of the proposed decoder. Authors

关键词： Vehicle to vehicle communications

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Optimal Virtual Inertia Placement Considering Battery Degradation Cost in Microgrids 28

Optimal Virtual Inertia Placement Considering Battery Degrad...

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28th International electrical Power Distribution Conference, EPDC 2024

作者： Sarableh, Ali Mohammadi Khorsandi, Amir Hosseinian, Seyed Hossein Maleki, Ali Department of Electrical Engineering Tehran Iran Washington State University Department of Electrical Engineering & Computer Science Pullman United States

ISBN: (纸本)9798350385502

Decreasing system inertia in microgrids due to high penetration of inverter-based resources necessitates enhancing system stability with virtual inertia. Optimal placement of virtual inertia significantly impacts system frequency behavior, making it a crucial consideration in virtual inertia provision. While some studies have employed relatively comprehensive storage device models for optimal virtual inertia placement, they often overlook the cost of battery degradation. The cost of battery degradation should be considered in optimization problem with respect to the importance of battery lifetime. This paper formulates an optimal cost function integrating virtual inertia technology costs, including installation, operation, battery degradation, and replacement. Incorporating battery degradation costs enhances battery health within the grid and provides a more accurate cost estimate for virtual inertia provision. By addressing the non-linearity of optimal virtual inertia placement, previous studies used genetic algorithms to find optimal solutions. with linear optimization methods thereby reducing non-linearity. In this paper replaced genetic algorithms with linear optimization methods to simplify the process of determining the optimal placement of virtual inertia, thereby linearized model for optimal virtual inertia placement problem. © 2024 IEEE.

关键词： Cost functions

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Feature-oriented Digital Twins for Life Cycle Phases Using the Example of Reliable Museum Analytics 8th

Feature-oriented Digital Twins for Life Cycle Phases Using t...

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8th International Symposium on Reliability engineering and Risk Management, ISRERM 2022

作者： Luther, W. Auer, E. Sacher, D. Baloian, N. Department of Computer Science and Applied Cognitive Science University of Duisburg-Essen Germany Electrical Engineering and Computer Science Wismar University of Applied Sciences Germany Department of Computer Science University of Chile Santiago Chile

ISBN: (纸本)9789811851841

In this paper, we consider partial, feature-oriented digital twins of several virtual museums and formulate an approach to assessing them from the viewpoint of their reliability. Although the formulation specifically concerns the chosen application, it can be extended to any kind of feature-oriented digital twin. The features of a virtual museum that define its scope and focus fit into three broad categories: content, communication and collaboration. Moreover, any virtual museum needs to be risk-informed, that is, seek to support the communication and perception of different types of risks from a variety of threat categories. At the same time, appropriate algorithms should identify and analyze different types of risks for museums’ buildings, visitors, exhibitions, and pieces of art with the help of sensor data, operating rules and standards, in this way supporting stakeholders’ decision making. Using comprehensible quality criteria and their metrics, formal assessment can be carried out with the help of formulated requirements, ground truth data and related standards from the involved professional associations. Additionally, empirical assessment based on user surveys can be conducted during the museum’s lifetime. Aside from various realizations or interactive learning systems, the use cases we base our analysis on are a joint project with the Museo de Arte Contemporâneo (MAC, Santiago de Chile);a digital representation of largely destroyed works by German-Jewish sculptor Leopold Fleischhacker, a joint project initiated by the Salomon Ludwig Steinheim-Institute in Essen, presented onsite at the Düsseldorf Memorial to the Victims of Persecution;and the virtual Khachkar Museum dedicated to endangered Armenian cross stones in cooperation with the American University of Armenia. © 2022 ISRERM Organizers. Published by Research Publishing, Singapore.

关键词： Risk assessment

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Relationship of IQ with Causal Connections Between Brain Salient Network Regions 31

Relationship of IQ with Causal Connections Between Brain Sal...

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31st National and 9th International Iranian Conference on Biomedical engineering, ICBME 2024

作者： Ghoorchian, Mina Soltanian-Zadeh, Hamid Pedram, Mir Mohsen Sadeghi, Mohsen Mir Mohammad Institute for Cognitive Science Studies Department of Cognitive Science Tehran Iran University of Tehran School of Electrical and Computer Engineering Tehran Iran Kharazmi University Department of Electrical and Computer Engineering Faculty of Engineering Tehran Iran

ISBN: (纸本)9798331529710

IQ is one of the indicators that has always been of interest to psychiatrists, doctors and cognitive science researchers. Since this index plays a key role in people's lives and also in the occurrence of brain abnormalities, many studies have been conducted on it. In this paper, we used the resting state magnetic resonance imaging data available in the HCP database to classify people into three groups with low, medium, and high IQ and applied machine learning methods on the matrix of causal connections between related network regions. We applied brain highlights. We calculated the matrix of causal relationships in this network by the spDCM algorithm and then obtained the differences of the three groups using the ANOVA statistical test and 6 edges out of 169 edges with p-value © 2024 IEEE.

关键词： Support vector regression

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Accurate State of Health Estimation of Lithium-ion Batteries: An Efficient ResNet-LSTM Approach 4

Accurate State of Health Estimation of Lithium-ion Batteries...

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4th International Conference on Smart Grid and Renewable Energy, SGRE 2024

作者： Eddin, Ez Eddin Ez Massaoudi, Mohamed Ghrayeb, Ali Qatar University Computer Science and Engineering Qatar Texas A&M University Department of Electrical and Computer Engineering College Station United States Texas A&M University at Qatar Department of Electrical and Computer Engineering Doha Qatar

ISBN: (纸本)9798350306262

Accurate estimation of the state of health (SoH) of lithium-ion battery (LIB) application systems is a critical concern in the domain of electric vehicles (EVs). Precise SoH holds significance due to its direct impact on the performance, longevity, and safety of LIBs. This paper proposes an efficient deep learning (DL) method for SoH estimation. The proposed DL model incorporates a residual neural network (ResNet) with long short-term memory (LSTM), extracting spatial-temporal features from LIB data. The ResNet-LSTM approach ensures high accuracy in SoH prediction. Extensive experimental results derived from real-world LIBs are presented, demonstrating the model's superiority and competitiveness in score measures when compared to existing SoH estimation models. The key contributions of this paper include (1) the simulation of a highly effective model explicitly tailored for SoH estimation in LIBs for EVs;(2) empirical verification of the effectiveness and superiority of the proposed model on the widely used NASA battery dataset. Simulation results are carried out to demonstrate the generalization and feasibility of the ResNet-LSTM model in SOH estimation with an overall root-mean-squared error of 0.69%. © 2024 IEEE.

关键词： Long short-term memory

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Energy Efficient Green Routing for UAVs Ad-Hoc Network

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Intelligent Automation & Soft Computing 2023年第7期37卷 1111-1127页

作者： M.Muthukumar Rajasekar Rangasamy Irshad Hussain Salman A.AlQahtani Department of Computer Science and Engineering Sree Sowdambika College of EngineeringTamil NaduIndia Department of Computer Science and Engineering-AI&ML School of EngineeringMalla Reddy UniversityHyderabadIndia Faculty of Electrical and Computer Engineering University of Engineering and Technology Peshawar25000PeshawarPakistan Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Kingdom of Saudi Arabia

The purpose of this article is to propose Stability-based Energy-Efficient Link-State Hybrid Routing(S-ELHR),a low latency routing proto-col that aims to provide a stable mechanism for routing in unmanned aerial vehicles(UAV).The S-ELHR protocol selects a number of network nodes to create a Connected Dominating Set(CDS)using a parameter known as the Stability Metric(SM).The SM considers the node’s energy usage,connectivity time,and node’s *** the highest SM nodes are chosen to form *** node declares a Willingness to indicate that it is prepared to serve as a relay for its neighbors,by employing its own energy state.S-ELHR is a hybrid protocol that stores only partial topological information and routing tables on CDS *** of relying on the routing information at each intermediary node,it uses source routing,in which a route is generated on-demand,and data packets contain the addresses of the nodes the packet will transit.A route recovery technique is additionally utilized,which first locates a new route to the destination before forwarding packets along *** simulation for various network sizes and mobility speeds,the efficiency of S-ELHR is *** findings demonstrate that S-ELHR performs better than Optimized Link State Routing(OLSR)and Energy Enhanced OLSR(EE-OLSR)in terms of packet delivery ratio,end-to-end delay,and energy consumption.

关键词： Connected dominatingset hybridrouting UAVAdhocnetworks link state stability

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Enhanced Deep Learning Model for Superior Multi-Class Classification Performance

Enhanced Deep Learning Model for Superior Multi-Class Classi...

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2024 International Conference on Microelectronics, ICM 2024

作者： Aydoghmishi, Faezeh Mohammadi Abdel-Raheem, Esam Rueda, Luis University of Windsor Department of Electrical and Computer Engineering WindsorON Canada School of Computer Science University of Windsor WindsorON Canada

ISBN: (纸本)9798350379396

Skin cancer is a highly prevalent form of cancer worldwide. The clinical assessment of skin lesions is crucial for evaluating the disease's characteristics. However, this assessment is often hindered by the variability in interpretations and lengthy timelines, resulting in delayed diagnoses. An advanced computer-aided diagnosis (CAD) system is needed to improve patient survival rates. This paper presents a Multi-class Skin Cancer Classification system using an enhanced VGG-16 model to improve the diagnosis of skin cancer. Our approach focuses on classifying multiple skin lesions types, specifically Melanocytic Nevus (NV), Basal Cell Carcinoma (BCC), Melanoma (MEL), and Vascular Lesions (VASC). The system was trained and evaluated on the Human Against Machine with 10,000 training images (HAM10000) dataset. We have conducted a comparative study between our method and several previously introduced techniques on the International Skin Image Collaboration (ISIC) dataset, and the results show that the proposed model outperforms previously proposed techniques. © 2024 IEEE.

关键词： Lung cancer

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Distributed Page Table: Harnessing Physical Memory as an Unbounded Hashed Page Table 57

Distributed Page Table: Harnessing Physical Memory as an Unb...

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57th Annual IEEE/ACM International Symposium on Microarchitecture, MICRO 2024

作者： Kwon, Osang Lee, Yongho Park, Junhyeok Jang, Sungbin Tak, Byungchul Hong, Seokin Sungkyunkwan University Department of Electrical and Computer Engineering Korea Republic of School of Computer Science and Engineering Kyungpook National University Korea Republic of

ISBN: (纸本)9798350350579

Virtual memory systems rely on the page table, a crucial component that maps virtual addresses to physical addresses (i.e., address translation). While the Radix Page Table (RPT) has traditionally been used for this task, its limitations have become more apparent with the rise of memory-intensive applications. Recently, Hashed Page Tables (HPTs) have been explored as an alternative page table structure to offer faster address translation. However, the HPT introduces its own set of challenges particularly in resizing the page table and allocating contiguous physical memory space for storing the table. To tackle the fundamental problem of the existing HPT designs, this paper introduces Distributed Page Table (DPT), a novel approach that utilizes the physical memory as a huge hashed page table. DPT distributes Page Table Entries (PTEs) across the entire physical memory space, significantly reducing the hash collisions while avoiding the table resizing overheads. When distributing the PTEs across the physical memory, they can be mapped to memory locations already allocated to data pages. This new type of collision, referred to as address collision, may reduce the effectiveness of the DPT. This paper showcases that the DPT can effectively resolve the address collision with three simple yet efficient techniques: Strided Open Addressing (SOA), Collision-Aware Virtual Address Allocation (CVA) and Collided Page Displacement (CPD). Our experimental results demonstrate that DPT achieves average performance improvements of 12.6%, 11.6%, and 8.7% compared to traditional RPT, the latest large-coverage TLB design, and state-of-the-art HPTs, respectively. © 2024 IEEE.

关键词： Virtual addresses

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