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2nd International Conference on Information and Communication Technology for Sustainable Development, ICICT4SD 2023

作者： Meem, Rahtul Jannat Haque, Md Rakibul Khan, Mohammad Monirujjaman Rahman, H M Arifur North South University Department of Electrical and Computer Engineering Dhaka Bangladesh

ISBN: (纸本)9798350358667

the use of smart wearable gadgets has exponentially increased due to wireless technology advancements. The demand for wireless bandwidth is increasing, and millimeter-sized bands are gradually becoming more prominent. This study presents an analog 28 GHz manufactured F-slotted patch antenna for body-centric communications. The F-slot is carved on a 9.74 mm by 8.5 mm square patch. On top of the slotted patch is a 1.6-mm-dense FR-4 (flame-retardant) substrate with an approximate 4.3. The inclusive dimensions are 12 × 12 × 1.6 (mm), with a packed ground plane the same as the substrate. The antenna has been designed and assessed in a microwave studio using computer simulation technology (CST). A virtual human body model was created within the 3D computer-simulated environment, and simulations were repeated with four equally spaced distances taken into account to more precisely identify the antenna and its behavior. This was done to support the eligibility of this design for WBAN applications. Even when positioned at any distance higher than 2 mm to the human body. © 2023 IEEE.

关键词： Microstrip antennas

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Transceiver Design for Secure Wireless Communication Networks with IRS using Deep Learning: A Survey

Transceiver Design for Secure Wireless Communication Network...

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2023 International Conference on Digital Applications, Transformation and Economy, ICDATE 2023

作者： Wong, Yik Heng Chiong, Choo W. R. Curtin University Malaysia Department of Electrical and Computer Engineering Miri Malaysia

ISBN: (纸本)9798350310689

With the ability to adjust the electric and magnetic properties of its surface, an intelligent reflecting surface (IRS) is a programmable device that can manipulate the propagation of electromagnetic waves. This characteristic makes IRS a valuable technology in the context of sixth-generation (6G) communication networks. However, implementing IRS in wireless networks is still a challenging problem due to high system complexity and this has led to the widespread adoption of machine learning (ML) techniques. This article presents a comprehensive literature review of IRS-assisted wireless communications, covering basic IRS concepts, and transceiver design for wireless communication with and without the IRS. Additionally, a review and classification of system models with IRS proposed by the papers and the use of machine learning in IRS-enhanced wireless networks are included. Finally, the article concludes by outlining the challenges, offering insightful recommendations, and highlighting open research problems for future extensions in the field of IRS-assisted wireless communication networks. © 2023 IEEE.

关键词： Wireless networks

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Full-Speed Sensorless Control Scheme for Permanent Magnet Synchronous Motor Using Artificial Neural Network

Full-Speed Sensorless Control Scheme for Permanent Magnet Sy...

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2023 IEEE International Symposium on Sensorless Control for electrical Drives, SLED 2023

作者： Al-Kaf, Hasan Ali Gamal Mohammed, Sadeq Ali Qasem Lee, Kyo-Beum Ajou University Department of Electrical and Computer Engineering Suwon Korea Republic of

ISBN: (纸本)9798350335422

Extended back electromotive force (EEMF) has been widely used as speed estimation of permanent magnet synchronous motors (PMSMs) due to its excellent performance at medium and high speeds. However, at low speed, EEMF method has low estimation accuracy. Several sensorless methods have combined EEMF with different accurate low-speed estimation techniques to attain a satisfactory estimation performance in the whole speed range. However, the transition between EEMF and low-speed estimation methods is a crucial step that requires two separate speed estimators with different structures. This leads to increased design complexity. Therefore, in this paper, a single sensorless full-speed control is proposed using an artificial neural network (ANN). The proposed ANN method does not require any transition method compared with hybrid full-speed sensorless methods. Simulation results show that proposed ANN can estimate rotor position for full speed compared with EEMF which estimates the rotor speed at medium and high speed. © 2023 IEEE.

关键词： Electromotive force

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An Efficient Method for Dynamic Hosting Capacity of Distribution Grids 4

An Efficient Method for Dynamic Hosting Capacity of Distribu...

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4th Annual IEEE Kansas Power and Energy Conference, KPEC 2023

作者： Khan, Mohammad Asif Iqbal Savasci, Alper Paudyal, Sumit Florida International University Department of Electrical and Computer Engineering United States

ISBN: (纸本)9798350335408

As the penetration of distributed energy resources (DERs) and flexible loads are increased, it is valuable to ensure that the coordination does not violate network operational constraints while maximizing grid utilization. Based on the grid measurements, the distribution feeder utilization can be enhanced using simple algorithms that allow additional DERs and flexible loads to be accommodated on the feeder. In this context, an efficient dynamic hosting capacity computation method is developed that guarantees distribution grid operational feasibility. By using the IEEE 13-node test feeder, we demonstrate the maximization of hosting capacity using the proposed scheme. © 2023 IEEE.

关键词： Energy resources

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Resource Allocation in NR-V2X Mode 2 Using Multi Agent DQN 14

Resource Allocation in NR-V2X Mode 2 Using Multi Agent DQN

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14th International Conference on Ubiquitous and Future Networks, ICUFN 2023

作者： Lee, Insung Kim, Duk Kyung Inha University Department of Electrical and Computer Engineering Incheon Korea Republic of

ISBN: (纸本)9798350335385

V2X communication has been studied to increase road safety and traffic efficiency, and the most recently standardized technology is NR-V2X developed by third generation partnership project (3GPP). NR-V2X supports two modes of communication mode 1 and mode 2. In mode 2, vehicles reserve the resources based on their local observations using semi-persistent scheduling (SPS). In this method, if two or more vehicles select the same resource, a continuous resource collision occurs, and it makes communication performance greatly degraded. To overcome this, we propose a resource allocation method using multi-agent reinforcement learning (MARL). As agents, vehicles that transmit periodic cooperative awareness messages (CAM) are modeled. The state is composed of the received signals strength indicator (RSSI) that the agents received from each resource, and we set the total sum rate of all agents as the shared reward. The proposed method is compared with the random resource allocation in a highway scenario. The results show that the proposed method outperforms in terms of throughput performance. © 2023 IEEE.

关键词： Resource allocation

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A Low-Latency and Lightweight FPGA-Based Engine for Softmax and Layer Normalization Acceleration

A Low-Latency and Lightweight FPGA-Based Engine for Softmax ...

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2023 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2023

作者： Jeong, Seongho Seo, Minseok Nguyen, Xuan Truong Lee, Hyuk-Jae Seoul National University Department of Electrical and Computer Engineering Korea Republic of

ISBN: (纸本)9798350344318

Vector operations such as GELU, softmax, and layer normalization are essential for transformers, but generally consume long latency on general-purpose CPU and GPU due to their low arithmetic intensities and high nonlinearity. In this study, we propose a low-latency FPGA-based architecture for accelerating the vector operations. Specifically, the proposed design includes processing elements for micro-instructions and a controller that decomposes and executes vector operations into in-order low-level instructions effectively. Experiments show that an FPGA implementation of the proposed design achieves a latency of 1.31us for softmax and 3.76us for layer normalization, while consuming 385 DSPs, 16 BRAMs, 71k FFs, and 57k. LUTs. © 2023 IEEE.

关键词： Field programmable gate arrays (FPGA)

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SADA: Unsupervised Domain Adaptation for Reliable Scene Awareness 59

SADA: Unsupervised Domain Adaptation for Reliable Scene Awar...

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59th Annual Conference on Information Sciences and Systems, CISS 2025

作者： Maghsoumi, Hossein Fallah, Yaser P. Atia, George University of Central Department of Electrical and Computer Engineering OrlandoFL United States University of Central Department of Computer Science OrlandoFL United States

ISBN: (纸本)9798331513269

Although deep neural networks are extensively employed in autonomous driving, they must be adjusted to handle unforeseen environmental conditions that were not included in their initial training. Unsupervised domain adaptation (UDA) techniques have proven effective in transferring learned knowledge from one domain to another when the labels in the target domain are unavailable. However, their potential application in scene awareness remains underexplored. This paper introduces SADA (Scene Awareness with Unsupervised Domain Adaptation), a novel approach designed to enhance the reliability of drivable area and lane detection tasks in autonomous driving systems. We leverage UDA techniques in unified multi-task networks to address domain shift challenges, ensuring robust feature extraction under diverse and complex conditions. The proposed technique is evaluated on different real-world datasets and the results demonstrate that the proposed methods outperform the baseline scheme in terms of detection accuracy and consistency. © 2025 IEEE.

关键词： Deep neural networks

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A Preemption Method for QoS Based on Time-Sensitive Network

A Preemption Method for QoS Based on Time-Sensitive Network

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

作者： Kim, Jong Hun Do, Young Soo Lee, Jung Ju Jeon, Jae Wook Sungkyunkwan University Department of Electrical and Computer Engineering Suwon Korea Republic of

ISBN: (纸本)9798350326413

In-vehicle networks are increasingly using complex functions to enhance user convenience. This has led to a rise in both the number of Electronic Control Units (ECUs) and the bandwidth between data traffic. Ethernet communication has been adopted to address this issue in a network where multimedia and control traffic coexists. However, a solution was still required to maintain Quality-of-Service (QoS), which led to the emergence of the Time-Sensitive Network (TSN). In this situation, TSN, which defines rules for real-time, reliability, etc., is gaining attention. In this paper, we compare the performance of Time Aware Shaper (TAS) and frame preemption methods for real-time scheduling among TSN protocols. Furthermore, we propose a method to enhance QoS by predicting overhead and flexibly selecting preemption size. © 2023 IEEE.

关键词： Quality of service

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Evaluation of Machine Learning Models to Forecast Inflation: Bangladesh as a Case Study

Evaluation of Machine Learning Models to Forecast Inflation:...

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2023 International Symposium on Networks, computers and Communications, ISNCC 2023

作者： Ismail, Labiba Binte Joytu, Mahira Ibnath Plabon, Tasnim Islam Oshman, Muhammad Shafayat North South University Department of Electrical and Computer Engineering Dhaka Bangladesh

ISBN: (纸本)9798350335590

In Bangladesh, inflation is a paramount factor that significantly impacts governmental and non-governmental policies. It intricately links the financial value of money and the economy's stability. The decline of a fiat currency's purchasing power over time is referred to as inflation. It is essential to the creation of global central banks' macroeconomic policies. When growth rates are high, inflation increases, and deflation occurs when they are low or negative. We conducted a study to determine the relationship between inflation and the CPI (Consumer Price Index). To determine the historical pattern of inflation, we have put up some approaches based on machine learning to help us predict inflation. Despite the constraints caused by the lack of pertinent data, we conducted a thorough analysis using various machine learning models, including Support Vector Regression (SVR), ARIMA, LSTM, Prophet, XGBoost, and GRU. Each model was rigorously evaluated with different metrics to find the accuracy. This research clarifies the intricate connection between inflation and the CPI and emphasizes the crucial role that data accessibility plays in the development of predictive models. Our findings will encourage further research in this area, resulting in future economic forecasts that are more precise and insightful. © 2023 IEEE.

关键词： Forecasting

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Gait Disorder Assessment Based on a Large-Scale Clinical Trial: WiFi vs. Video vs. Doctor's Visual Inspection

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IEEE Internet of Things Journal 2025年第12期12卷 20988-21000页

作者： Parsay, Alireza Torun, Mert Delio, Philip R. Mostofi, Yasamin University of California Department of Electrical and Computer Engineering Santa Barbara United States Neurology Associates of Santa Barbara United States Santa Barbara Cottage Hospital United States

Neurological gait disorders affect a large population, significantly reducing life quality. This paper brings a foundational understanding to the potentials of emerging sensing modalities (e.g., WiFi) for gait disorder assessment, via conducting a one-year-long clinical trial in collaboration with the Neurology Associates of Santa Barbara. Our medical campaign encompasses 114 real subjects and a wide spectrum of disorders (e.g., Parkinson's, Neuropathy, Post Stroke, Dementia, Arthritis). We then develop the first WiFi-based gait disorder sensing system of its kind, distinguished by its scope of validation with a large and diverse patient cohort. To ensure generalizability, we mainly leverage publicly-accessible online videos of gait disorders for training, and develop a video-to-RF pipeline to convert them to synthetic RF training data. We then extensively test the system in a neurology center (i.e., the Neurology Associates of Santa Barbara). Additionally, we provide a 1-1 comparison with a vision-based system, by developing a vision-based gait assessment system under identical conditions, a first-of-its-kind comparison to our knowledge. We finally contrast both systems with neurologists' accuracy when basing evaluation solely on visual gait inspection, by designing/distributing a large survey to 70 neurologists, offering the first apples-to-apples comparison of these three sensing modalities. Our findings can help integrate these sensing systems into medical practice, working towards equitable healthcare. © 2014 IEEE.

关键词： Neurodegenerative diseases

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