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Multiphysics Analysis of Thermal Deformation Effects on a Waveguide Bandpass Filter

IEEE Access 2025年 13卷 71447-71455页

作者： Guarnera, Davide Mauro, Giorgio S. Pavone, Santi Concetto Isernia, Tommaso Sorbello, Gino Mediterranea University of Reggio Calabria DIIES Reggio Calabria89122 Italy University of Catania Department of Electrical Electronics and Computer Engineering Catania95123 Italy Catania95125 Italy

In this paper, we propose a multiphysics analysis of thermal deformation effects on the frequency response of a Chebyshev bandpass filter designed for C-band satellite communications (SATCOM). Indeed, the design of microwave devices for SATCOM must account for the effects of thermal gradients on frequency response and incorporate suitable compensation techniques. The proposed analysis consists of appropriate sequence of electromagnetic, thermal, and mechanical simulations to evaluate the filter thermal profile as a function of input power, the resulting mechanical deformations, and the consequent effect on the filter frequency response. The results obtained are related to the filter equivalent circuit model to obtain deeper insight of the involved physical phenomena and useful information for the design of the most suitable compensation strategy. Finally, to demonstrate the effectiveness of multiphysics analysis in the optimal design of devices robust to thermal gradients, a thermally compensated bandpass filter using passive heat sinks is designed and validated. © 2013 IEEE.

关键词： Chebyshev filters

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Entanglement Distribution Delay Optimization in Quantum Networks With Distillation

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IEEE Journal on Selected Areas in Communications 2025年第5期43卷 1871-1886页

作者： Chehimi, Mahdi Goodenough, Kenneth Saad, Walid Towsley, Don Zhou, Tony X. American University of Beirut Department of Electrical and Computer Engineering Beirut1107 2020 Lebanon University of Massachusetts Amherst Manning College of Information and Computer Sciences AmherstMA01003 United States Virginia Tech University Department of Electrical and Computer Engineering ArlingtonVA24061 United States Massachusetts Institute of Technology Research Laboratory of Electronics CambridgeMA02139 United States

Quantum networks (QNs) enable secure distributed quantum computing and sensing over next-generation optical communication networks by distributing entangled states over optical channels. However, quantum switches (QSs) in such QNs, which perform entanglement distribution, have limited resources, e.g., single-photon sources (SPSs) and quantum memories, which are sensitive to noise and losses. Efficient QS resource allocation is needed to minimize entanglement distribution delay. This paper proposes a QS resource allocation framework that jointly optimizes the average entanglement distribution delay and entanglement distillation operations to improve end-to-end (e2e) fidelity and meet user-specific rate and fidelity requirements. The proposed framework accounts for realistic QN noise and imperfections, deriving analytical expressions for quantum memory decoherence noise and resulting e2e fidelity after distillation. It also considers practical deployment factors, allowing QSs to control 1) nitrogen-vacancy (NV) center SPS types based on their isotopic decomposition, and 2) nuclear spin regions based on coupling strength and distance from NV center’s electron spin. The QS resource allocation optimization problem is solved using a simulated annealing algorithm. Simulation results show that the proposed framework manages to satisfy all users rate and fidelity requirements, unlike existing distillation-agnostic, minimal distillation, and physics-agnostic frameworks which do not perform distillation, perform minimal distillation, and do not control the physics-based NV center characteristics, respectively. Furthermore, the proposed framework results in significant reductions in the average e2e entanglement distribution delay, along with enhancements in the average e2e fidelity compared to the aforementioned existing frameworks. © 1983-2012 IEEE.

关键词： Simulated annealing

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A Multi-Modal Smart Switching Based Image Transmission Using Semantic Communication 17

A Multi-Modal Smart Switching Based Image Transmission Using...

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17th International Conference on COMmunication Systems and NETworkS, COMSNETS 2025

作者： Tiwari, Sanjana Tripathi, Sharda Joshi, Sandeep Bhatt, Priyanshu Natarajan, Balasubramaniam Birla Institute of Technology & Science Pilani Department of Electrical & Electronics Engineering 333031 India Kansas State University Department of Electrical & Computer Engineering 66506 United States

ISBN: (纸本)9798331531195

The conventional paradigm of communication primarily concentrates on the transmission of raw data, often disregarding its contextual meaning. However, to tackle the exponential growth in data demands along with the limited availability of transmission bandwidth, there is an increasing need to transition from Shannon's classical information-theoretic communication to a more advanced framework centered on semantics. This work presents a multi-modal semantic-based communication method for the transmission of high-definition images aimed at optimizing the transmitted data volume while maintaining a high throughput and mean intersection over union score. To this end, two architectural models are explored: a denser ResNet-based and a lightweight U-Net-based. Depending on the required QoS and resource availability, the raw image is either semantically segmented to obtain a fine-grained, pixel-level classification of the image or represented as label semantics, which provides only a higher-level, object-based, or region-based classification prior to its transmission. The experimental results show that such an adaptive semantic image processing approach leads to around 63% reduction in the transmitted data volume without compromising on the quality of image reconstruction. © 2025 IEEE.

关键词： Semantic Segmentation

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Analysis of Microgrids Electric Vehicles Charging Stations with Hybrid Energy Storage System Algorithm with AI

Analysis of Microgrids Electric Vehicles Charging Stations w...

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International Conference on Computational Intelligence and Smart Technologies in electrical engineering, CISTEE 2023

作者： Tiwari, Prakash Narayan Tiwari, Kaushal Prasad Dixit, Anshu Bohre, Aashish Kumar Shah, Nand Lal Gupta, Sanjeev Kumar Department of Electrical and Electronics Engineering Rabindranath Tagore University Bhopal India Department of Computer Science and Engineering Bansal Institute of Science and Technology Bhopal India Department of Electrical and Electronics Engineering NIT Durgapur West Bengal Durgapur India

ISBN: (纸本)9789819604753

Renewable energy sources, such as hydropower, solar power, and wind power, have the capacity to efficiently supply their respective portions of the world’s energy needs. Since then, the use of renewable energy in electric cars (EVs) has garnered a lot of attention. Significant advancements in lithium-ion batteries have expedited the development of electric vehicles. The issue is that as the number of EVs increases, so does the need for electricity, increasing the burden on the power system. This promotes research into alternative and sustainable energy sources for recharging electric vehicles. In this study, a solar energy system is used to build an EV charging station. The charging station uses many connectors to supply a DC bus with a constant voltage. Power balance and constant current/constant voltage charging are the foundations of the charging controllers. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Hybrid vehicles

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Laser Triangulation and Optical Computed Tomography 3D Scanner

Laser Triangulation and Optical Computed Tomography 3D Scann...

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2025 IEEE International Students' Conference on electrical, electronics and computer Science, SCEECS 2025

作者： Estrellado, Vien Louei P. Dela Cruz, Jennifer C. Mapua University Electrical Electronics and Computer Engineering Manila Philippines Mapua University School of Eece Manila Philippines

ISBN: (纸本)9798331529833

3D scanning encounters challenges when scanning objects with complex optical properties, such as translucency. To address the issue, the research developed an improved 3D scanner by integrating Laser Triangulation with Optical Computed Tomography (OPCT). The prototype was tested on various object shapes and sizes, and its accuracy was evaluated using Root Mean Square Error (RMSE) and Mean Absolute Deviation (MAD). The results demonstrated an overall accuracy of 95.85%, with consistent point cloud generation when proper calibration was maintained. While the prototype had an average scan duration 28.43% longer than that of an industrial scanner, its integrated scanning technique provided reliable performance for both opaque and translucent objects. The findings underscore the potential of combining Laser Triangulation and OPCT to create a versatile and effective 3D scanning solution for objects with complex optical properties. © 2025 IEEE.

关键词： Triangulation

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Impact of fraud on revenue loss, detection features, and energy fraud identification 1st

Impact of fraud on revenue loss, detection features, and ene...

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1st International Conference on Applications of AI in 5G and IOT, ICAAI5GI 2024

作者： Indarjit, Elisha Balyan, Vipin Adonis, Marco Department of Electrical Electronics and Computer Engineering Cape Peninsula University of Technology Cape Town Bellville South Africa

ISBN: (纸本)9781032874036

The increase of fraudsters and fraud attacks on the communication network plays a major role in the loss of revenue, network abuse, and degradation of services. Communication and cloud networks belong to separate companies and consist of handover points from one network to another. The scope is to bring the communication and cloud networks closer and understand network traffic profiles using Software-Defined Networking (SDN) concept. The SDN controller will serve to route the extracted tapped data to a central server instead of making use of the live network. To apply policies to the traffic and identify which user traffic is a fraud case, and further to send a block signal to the network charging element on the communication network. The flow process will be automated, and to protect the network from fraud attacks, using the SDN controller in a seamless approach and maintaining the performance of the network. The article defines the impact of fraud and fraud case detection. At which Smart Grid leverages intelligent communication technologies to modernize the electric infrastructure and raises new vectors for cyber risks and energy frauds. While services on the network require a secure platform that serves to block fraudster. The main purpose is to achieve a higher energy/service fraud detection rate than similar work in the field, to provide a solution that integrates within the traditional network, and further blocks the fraud within the network. © 2025 the Author(s).

关键词： Cloud network Communication network Detection Fraud Software-Defined Network

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Performance Analysis of Denoising Filters for Ultrasound Fetal Head Images

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SN computer Science 2025年第2期6卷 1-13页

作者： Prasad, Kauleshwar Patnaik, Pawan Kumar Agrawal, Anupam Department of Computer Science and Engineering Bhilai Institute of Technology Chhattisgarh Durg India Department of Electrical and Electronics Engineering Bhilai Institute of Technology Chhattisgarh Durg India

Deep learning has significantly advanced image processing in the medical domain, including the analysis of ultrasound (US) fetal images for prediction of fetal growth retardation. Before analysis of fetal images there is need of correction since they are usually adulterated by noise during acquisition of image. In the recent years, there are various deep learning based denoising methods in which U-Net have attracted the attention of many researchers. This paper describes the comparative study of different filters such as mean filter, gaussian filter, anisotropic diffusion, non-local means (NLM) filter and U-Net based on their performance on denoising fetal images prior to the prediction of fetal growth retardation (FGR). In this article peak signal to noise ratio (PSNR), mean square error (MSE), similarity index measure (SSIM), peak signal to interference ratio (PSIM) and multi scale structural similarity index measure (MSIM) values are analyzed for the performance of these filters. This paper reveals that U-Net performs better in image quality evaluation when compared to other filtering algorithms, based on testing and analytical findings. We have also discussed the significance of MSE, PSNR, SSIM, PSIM, MSIM and U-Net in this article. This article also covers the advantages, disadvantages, and characteristics of different filtering methods, including U-Net. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024.

关键词： Deep learning Denoising techniques Fetal growth retardation U-Net

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Sunflower Seed Variety and Quantity Identification Using YOLOv8 and DeepSORT Algorithm 19

Sunflower Seed Variety and Quantity Identification Using YOL...

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19th International Conference on Ubiquitous Information Management and Communication, IMCOM 2025

作者： Isles, Melor Christian A. Pagkaliwangan, Dylan Lyle A. Caya, Meo Vincent C. School of Electrical Electronics and Computer Engineering Mapúa University Muralla St. Intramuros Manila1002 Philippines

ISBN: (纸本)9798331507817

The field of agriculture has slowly been integrating the use of technology with their daily operations to its advantage. Sunflower seeds, which are a popular mass-produced agricultural product, also employ these emerging techniques. This research aims to introduce a computer vision-based system designed to automate the classification and counting of sunflower seeds by leveraging YOLOv8 and DeepSORT algorithms. The system aims to identify and quantify three distinct seed varieties: Giant, Dwarf F1, and Mammoth Grey seeds using a Raspberry Pi-powered hardware setup. This setup was also used to capture high-quality images of the sunflower seeds which made up the dataset used. The researchers will utilize, along with the Raspberry Pi. a USB webcam to capture the video feed of the sunflower seeds and an LCD monitor to display the seed count and seed variety. Upon running multiple trials and utilizing a confusion matrix to analyse the system accuracy, the system was able to achieve an overall accuracy of 91.11% for its classification and 97.56% for its counting accuracy. © 2025 IEEE.

关键词： computer Vision DeepSORT Algorithm Raspberry Pi Sunflower Seeds YOLOv8

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Review of the latest techniques that address network fraud detection and proposed architectures 1st

Review of the latest techniques that address network fraud d...

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1st International Conference on Applications of AI in 5G and IOT, ICAAI5GI 2024

作者： Indarjit, Elisha Balyan, Vipin Adonis, Marco Department of Electrical Electronics and Computer Engineering Cape Peninsula University of Technology Cape Town Bellville South Africa

ISBN: (纸本)9781032874036

The increase of fraudsters and fraud attacks on the communication network plays a major role in the loss of revenue, network abuse, and degradation of services. Communication and cloud networks belong to separate companies and consist of handover points from one network to another. The scope is to bring communication and cloud networks closer and understand network traffic profiles using the Software-Defined Networking (SDN) concept. The SDN controller will serve to route the extracted tapped data to a central server instead of making use of the live network to route traffic. To apply policies to the traffic and identify which user traffic is a fraud case, and further to send a block signal to the network charging element on the communication network. The flow process will be automated, and to protect the network from fraud attacks, using the SDN controller in a seamless manner and maintaining the performance of the network, The journal article explores traditional fraud detection techniques and will define a new framework for communication and cloud providers to enable the detection and blocking of fraud. The research solution will propose three network architectures for the identification of fraud and integration within communication and cloud networks. The aim of the study is to perform real-time data classification, reporting of fraudulent subscribers, applications, and protocols;real-time analytics, and real-time blocking of data that is classified as fraudulent activity within the mobile data network. The main purpose is to achieve a higher energy/service fraud detection rate than similar work in the field, to provide a solution that integrates within the traditional network, and to further block fraud within the network. © 2025 the Author(s).

关键词： cloud network communication network detection fraud software-defined network

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All-Rounder: A Flexible AI Accelerator With Diverse Data Format Support and Morphable Structure for Multi-DNN Processing

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IEEE Transactions on Very Large Scale Integration (VLSI) Systems 2025年第5期33卷 1264-1277页

作者： Noh, Seock-Hwan Lee, Seungpyo Shin, Banseok Park, Sehun Jang, Yongjoo Kung, Jaeha Department of Electrical Engineering and Computer Science Daegu42988 Korea Republic of DGIST Daegu42988 Korea Republic of Fitogether Seoul04323 Korea Republic of Samsung Electronics Suwon16677 Korea Republic of Korea University School of Electrical Engineering Seoul02841 Korea Republic of

Recognizing the explosive increase in the use of artificial intelligence (AI)-based applications, several industrial companies developed custom application-specific integrated circuits (ASICs) (e.g., Google TPU, IBM RaPiD, and Intel NNP-I/NNP-T) and constructed a hyperscale cloud infrastructure with them. These ASICs perform operations of the inference or training process of AI models which are requested by users. Since the AI models have different data formats and types of operations, the ASICs need to support diverse data formats and various operation shapes. However, the previous ASIC solutions do not or less fulfill these requirements. To overcome these limitations, we first present an area-efficient multiplier, named all-in-one multiplier, which supports multiple bit-widths for both integer (INT) and floating-point (FP) data types. Then, we build a multiply-and-accumulation (MAC) array equipped with these multipliers with multiformat support. In addition, the MAC array can be partitioned into multiple blocks that can be flexibly fused to support various deep neural network (DNN) operation types. We evaluate the practical effectiveness of the proposed MAC array by making an accelerator out of it, named All-rounder. According to our evaluation, the proposed all-in-one multiplier occupies 1.49x smaller area compared to the baselines with dedicated multipliers for each data format. Then, we compare the performance and energy efficiency of the proposed All-rounder with three different accelerators showing consistent speedup and higher efficiency across various AI benchmarks from vision to large language model (LLM)-based language tasks. © 1993-2012 IEEE.

关键词： Application specific integrated circuits

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