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Precision Multiband Terahertz Metamaterial Biosensor With Targeted Spectral Selectivity for Early Detection of MCF-7 Breast Cancer Cells

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IEEE Sensors Journal 2025年第9期25卷 14970-14987页

作者： Hamza, Musa N. Alibakhshikenari, Mohammad Virdee, Bal S. Lavadiya, Sunil Ud Din, Iftikhar Cavalcante De Souza Sanches, Bruno Koziel, Slawomir Iffat Naqvi, Syeda Panda, Abinash Farmani, Ali Rashid, Nasr Kouhalvandi, Lida Shariatifar, Milad University of Raparin College of Science Department of Physics Sulaymaniyah46012 Iraq University of Rome Tor Vergata Department of Electronics Engineering Rome00133 Italy London Metropolitan University Department of Center for Communications Technology LondonN7 8DB United Kingdom Marwadi University Department of Information and Communication Technology Gujarat Rajkot360003 India University of Engineering and Technology Department of Telecommunication Engineering Mardan23200 Pakistan Escola Politécnica da Universidade de São Paulo Department of Electronic Systems Engineering São Paulo05508 Brazil Reykjavik University Engineering Optimization and Modeling Center Reykjavik102 Iceland Gdansk University of Technology Faculty of Electronics Telecommunications and Informatics Gdansk80-233 Poland University of Engineering and Technology Department of Telecommunication Engineering Taxila34109 Pakistan CMR Institute of Technology Department of Electronics and Communication Engineering Bengaluru560037 India Lorestan University Department of Electronics engineering Khorramabad68151-44316 Iran Jouf University College of Engineering Department of Electrical Engineering Sakaka72388 Saudi Arabia Al-Azhar University Faculty of Engineering Department of Electrical Engineering Cairo11884 Egypt Dogus University Department of Electrical and Electronics Engineering Istanbul34775 Turkey

Cancer remains one of the leading causes of mortality worldwide, with breast cancer (BC) being a particularly prevalent form. Projections estimate nearly 20 million new cases globally over the next two decades. Early detection is critical for effective treatment;however, conventional diagnostic techniques often lack the necessary sensitivity and specificity, with some methods being invasive and labor-intensive. Recent advancements in microwave imaging (MWI) have shown significant potential as efficient, noninvasive tools for monitoring various cancer types. MWI operating in the terahertz (THz) range has emerged as a promising approach for biosensing, offering the precision needed to differentiate between healthy and cancerous tissues by analyzing small-scale biological features. Among the methods for BC detection, the identification and analysis of MCF-7 BC cells are particularly significant. THz waves interact uniquely with the intrinsic properties of MCF-7 cells, making THz-based biosensors ideal candidates for diagnostic tools. However, many existing sensors are limited in key performance areas, including operating bandwidth and absorption efficiency. This study introduces a novel multiband metamaterial (MTM)-based biosensor specifically designed for the detection of MCF-7 BC cells. The sensor features a compact geometry composed of multiple resonators made from 200-nm-thick aluminum (Al) layers on a 50-$\mu $ m-thick polyethylene terephthalate (PET) substrate. With dimensions of only $198\times 198μ $ m2, the proposed device is exceptionally compact. It operates in the 0.5-1.6-THz frequency range and achieves near-perfect absorption rates (>99%) across multiple bandwidths. These results are achieved through precise tuning of the sensor's geometry and architectural optimization, significantly enhancing its sensitivity for cancer detection. Comprehensive validation of the sensor is performed using full-wave electromagnetic analysis, which includes evaluating elect

关键词： Terahertz waves

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Comparative Analysis of Transport Layer Protocols for File Transfer and Video Streaming

Comparative Analysis of Transport Layer Protocols for File T...

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Digital Signal Processing and its Applications (DSPA), International Conference on

作者： Igor Kartashevskiy Denis Yakupov Scientific research laboratory of «Innovative projects» Povolzhskiy State University of Telecommunication and Informatics Samara Russia Department of Software Engineering Povolzhskiy State University of Telecommunication and Informatics Samara Russia

ISBN: (数字)9798331518752

ISBN: (纸本)9798331518769

This paper presents the results of comparative performance analysis of QUIC, TCP and UDP transport layer protocols. QUIC and TCP are compared for file transfer time of different file sizes. QUIC and UDP are compared during video streaming. The characteristics compared are peak signal to noise ratio and structural similarity index of transmitted video for both protocols.

关键词： Protocols PSNR Digital signal processing Streaming media Performance analysis Indexes

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A DNN Framework on Waveform Design for Over-the-Air Computation

A DNN Framework on Waveform Design for Over-the-Air Computat...

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IEEE Conference on Wireless Communications and Networking

作者： Nikos G. Evgenidis Nikos A. Mitsiou Sotiris A. Tegos Panagiotis D. Diamantoulakis Panagiotis Sarigiannidis George K. Karagiannidis Department of Electrical and Computer Engineering Aristotle University of Thessaloniki Thessaloniki Greece Department of Informatics and Telecommunication Engineering University of Western Macedonia Kozani Greece

ISBN: (数字)9798350368369

ISBN: (纸本)9798350368376

One of the main applications expected to be enabled by next-generation networks is computing. The goal-oriented nature of computing allows the use of different implementation techniques, with over-the-air (OTA) computation being one of the main proposed schemes due to its effective resource management and computational efficiency. In this work, we aim at optimizing the waveform of the system in the presence of intersymbol interference (ISI) and sampling error. To this end, we propose a deep neural network (DNN) framework that generates an optimal waveform that minimizes the mean square error (MSE) of the OTA computation system. To ensure that the generated waveform exhibits the same behavior as other common waveforms, weighted energy and spectrum constraints are included in the loss function of the training phase. To better mitigate ISI, the spectrum constraint integrates the roll-off factor of the waveform, allowing for the generation of different waveforms. Simulation results verify that the desired constraints are met and show a significant performance gain over state-of-the-art waveforms.

关键词： Training Wireless networks Simulation Intersymbol interference Artificial neural networks Mean square error methods Performance gain Computational efficiency Resource management Next generation networking

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Split Computing in Autonomous Mobility for Efficient Semantic Segmentation using Transformers

Split Computing in Autonomous Mobility for Efficient Semanti...

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Computational Intelligence for Energy, Transport and Environmental Sustainability (CIETES), IEEE Symposia on

作者： Chris Ulicny Robert Rauch Juraj Gazda Zdenek Becvar Department of Computers and Informatics Technical University of Kosice Slovakia Department of Telecommunication Engineering Faculty of Electrical Engineering Czech Technical University in Prague Czech Republic

ISBN: (数字)9798331508258

ISBN: (纸本)9798331508265

With the advancement of deep learning in Connected Autonomous Vehicles (CAVs), real-time semantic segmentation has emerged as a crucial task. The integration of semantic segmentation vision transformers into CAV perception systems capitalizes on the efficiency of the vision transformers and their capacity to capture a global context. To further optimize transformer’s performance, we propose the integration of a Split Computing (SC) into the transformer architecture to enable the processing of the computation related to transformers to be distributed between the CAVs and an Edge Computing Server (ECS). The objective of our work is to evaluate SC efficiency in minimizing latency of intensive computational tasks of the transformers with minimal loss in semantic segmentation’s accuracy. Simulations demonstrate that vision transformer architectures are well-suited for the SC integration and outperform both ECSOnly and CAV-Only baseline approaches in various scenarios, offering an acceptable latency-accuracy trade-offs. Specifically, our findings indicate that SC outperforms baseline methods in terms of latency by up to 79.36%, incurring a minor accuracy reduction. This makes them particularly suitable for applications where real-time processing and minimal latency are critical considerations.

关键词： Computer vision Accuracy Semantic segmentation Semantics Computer architecture Transformers Real-time systems Servers Autonomous vehicles Edge computing

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Hybrid Heuristic Optimization of Deep Learning Models for Robust Plant Disease Detection

Hybrid Heuristic Optimization of Deep Learning Models for Ro...

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Emerging Smart Computing and informatics (ESCI), Conference on

作者： K. Ananthajothi Pravin R. Kshirsagar Tan Kuan Tak Kailash Kumar Department of Computer Science and Engineering Rajalakshmi Engineering College Chennai India Department of Electronics & Telecommunication Engineering J D College of Engineering & Management Nagpur India Electrical Power Engineering Programme Singapore Institute of Technology Singapore College of Computing and Informatics Saudi Electronic University Riyadh Kingdom of Saudi Arabia

ISBN: (数字)9798331515683

ISBN: (纸本)9798331515690

Plant diseases directly affect farm output by lowering grain, fruit, and vegetable quality, threatening global food security. Thus, farmers inspect plant leaves with their eyes. Plant leaf monitoring is unreliable and error-prone. A multitude of deep learning algorithms have been developed to detect plant leaf diseases; however, most rely on low-resolution photos utilizing convolutional neural nets (CNNs). This research seeks to create an improved nine-layer the CNN network model for the accurate classification of leaf-related illnesses. A contrast enhancement approach is used to pre-process plant leaf pictures. Following binary thresholding, the pre-processed pictures are separated into leaf images and abnormality segmented using the "Enhanced U-Net (EU-Net)" approach. A Multilevel Feature Fusion Network Convolutional Neural Network (MFFN-CNN) is employed to categorize illnesses of leaves based on segmented images. The "Hybrid Leader Cat Swarm Optimization(HLCSO)" method improves U-Net parameter optimization. The effectiveness of the leaf diagnostic model is demonstrated experimentally employing a variety of factors through the use of numerous baseline approaches.

关键词： Deep learning Plant diseases Image segmentation Computational modeling Neural networks Convolutional neural networks Particle swarm optimization informatics Optimization Monitoring

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On Performance of NOMA-empowered HCN: A Stochastic Geometry Approach Considering Imperfect SIC and CSI

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IEEE Wireless Communications Letters 2025年

作者： Baghel, Amit Parihar, Abhinav Singh Bhatia, Vimal Krejcar, Ondrej Choi, Kwonhue Indian Institute of Technology Indore Department of Electrical Engineering Indore453552 India Jabalpur Engineering College Department of Electronics and Telecommunication Jabalpur482011 India National Sun Yat-sen University Institute of Communications Engineering Kaohsiung80424 Taiwan Soochow University School of Electronic and Information Engineering China Skoda Auto University Mlada Boleslav293 01 Czech Republic University of Hradec Kralove Faculty of Informatics and Management Hradec Kralove500 03 Czech Republic Yeungnam University Department of Information and Communication Engineering Gyeongsan38541 Korea Republic of

In a multi-tier heterogeneous cellular network (HCN) with macro-base station (MBS) and pico-base station (PBS), non-orthogonal multiple access (NOMA) is used to boost spectral efficiency and achieve higher data rates in the sixth-generation wireless networks. This study investigates HCN-NOMA performance under practical consideration of imperfect successive interference cancellation (i-SIC) and imperfect channel state information (i-CSI) using stochastic geometry. This study compares OMA and NOMA, evaluating outage probability, asymptotic outage probability, system throughput, and energy efficiency for both perfect and i-SIC scenarios in multi-tier HCN. Despite i-SIC and i-CSI in NOMA, noticeable performance improvements of up to 57% are observed. © 2012 IEEE.

关键词： Base stations

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MAPSM: Mobility Aware Proactive Service Migration Framework for Mobile Edge Computing in Consumer Internet of Vehicles

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IEEE Transactions on Consumer Electronics 2025年

作者： Zhao, Xuhui Shi, Yan Chen, Shanzhi Liu, Jianghui Ji, Baofeng Mumtaz, Shahid Henan University of Science and Technology Luoyang471023 China Beijing University of Posts and Telecommunications Beijing China Beijing University of Posts and Telecommunications State Key Laboratory of Networking and Switching Technology Beijing China China Academy of Telecommunication Technology National Engineering Research Center of Mobile Communications and Vehicular Networks State Key Laboratory of Wireless Mobile Communications Beijing China Department of Applied Informatics Silesian University of Technology Akademicka16 Gliwice44-100 Poland Department of Engineering Nottingham Trent University United Kingdom

Mobile edge computing is considered as a key technology for consumer Internet of Vehicles networks, which provides low-latency, high-reliability network services for end-users. Service migration need to address where to migrate and how to implement service migration procedure based on user mobility. The existing reactive migrating solutions lead to overlong service migration time and end to end latency. The proactive service migration method obtains the target server in advance through mobility prediction, and the service migration procedure starts before communication handover. Based on the above observation, a Mobility Aware Proactive edge Service Migration framework (MAPSM) is proposed in this paper. MAPSM includes the key aspects: 1) predicting the next location of an end user based on ensemble learning method combining recurrent neural networks and geographical embedding markov chain predictors;2) using the mobility prediction result to determine the target edge server of service migration, a proactive migration-handover coordinated method is proposed by performing container pre-migration, memory state migration and communication handover. The time planning scheme in the procedure is also designed. Experimental results demonstrate that MAPSM can greatly improve migration performance, effectively reduce end-to-end latency and significantly reduce service migration time. MAPSM outperforms other baseline service migration approaches. © 1975-2011 IEEE.

关键词： Mobile edge computing

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Online generation of constant mulitplication accelerators

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Journal of engineering Science and Technology Review 2016年第5期9卷 171-175页

作者： Dasygenis, M. Petrousov, I. Department of Informatics and Telecommunication Engineering University of Western Macedonia Kozani50100 Greece

The rising complexity of embedded digital applications and the growing importance of time-to-market require EDA tools to automate the design and implementation process of various IP blocks. One very important class of EDA tools is the generation of hardware descriptions for popular IP blocks. The multiplication by an integer constant is a special type of problem that is required in a plethora of situations. Here, we present an online tool that can generate HDL descriptions constant multiplication intellectual property blocks, using only elementary operations, like shifting and addition. Our synthesized circuits on Xilinx Virtex 6 FPGA XC6VLX760, operate up to 589 Mhz. © 2016 Eastern Macedonia and Thrace Institute of Technology.

关键词： Intellectual property Internet protocols Computational complexity Time to market (New products) Computer operators

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Design and analysis of FTTH -GEPON for high rise building 8

Design and analysis of FTTH -GEPON for high rise building

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2014 8th International Conference on telecommunication Systems Services and Applications, TSSA 2014

作者： Nusantara, Hardi Dairianta, Freyskania Department of Telecommunication Engineering School of Electrical Engineering and Informatics-ITB Bandung Indonesia

ISBN: (纸本)9781479974474

This paper is about analysis and design of fiber access network systems using GEPON technology for HRB. GPON for HRB are designed to comply both for power budget and rise time budget standard. From analysis, G.652 and G.657 fiber type and also the SC connector is suitable in this design.. The design result recommended only using 1 stage splitting method with maximum splitting ratio of 132 and 116 splitter. The margin link power budget is above 0 and the value of rise time budget is still below the 70% NRZ. © 2014 IEEE.

关键词： Fiber to the x

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Discovery and assessment of gene-disease associations by integrated analysis of scientific literature and microarray data

Discovery and assessment of gene-disease associations by int...

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10th International Conference on Information Technology and Applications in Biomedicine: Emerging Technologies for Patient Specific Healthcare, ITAB 2010

作者： Faro, Alberto Giordano, Daniela Spampinato, Concetto Department of Informatics and Telecommunication Engineering University of Catania 95125 Catania Italy

ISBN: (纸本)9781424465606

The paper outlines a methodology and presents a tool to help biomedical researchers in interpreting complex experiments by automatically discovering gene networks and underlying biological processes (revealed by gene-expression patterns) that usually are extracted manually using existing tools. The proposed method, first, starts by mining specialized medical literature available on the Web to discover possible associations between genes and diseases. Discovered genedisease associations are subsequently explored by analyzing abnormally expressed genes using microarray data analysis. Afterwards, relevant gene networks are built by clustering these genes on the basis of the similarity of their profile expressions in microarrays data. Finally, molecular, biological processes, cellular components and molecular functions, which may have a role in the disease, are pointed out by querying the Gene Ontology (GO) database. The methodology is illustrated by a case study on neuromuscular disorders. © 2010 IEEE.

关键词： Gene Ontology

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