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IEEE Region 10 Symposium

作者： Daiki Deguchi Toshiro Nunome Department of Engineering Computer Science Program Graduate School of Engineering Nagoya Institute of Technology Nagoya Japan

ISBN: (数字)9798350364866

ISBN: (纸本)9798350364873

This paper compares video and audio QoE of OFDMA multi-user transmission and reliable groupcast over wireless LAN. We assume video and audio transmission to several terminals simultaneously. As a reliable groupcast method, we employ Unsolicited Retry, a technique of IEEE 802.11aa GroupCast with Retries. We utilize IEEE 802.11ax for OFDMA transmission. We evaluate application-level QoS by computer simulation. We then assess QoE through a subjective experiment with video and audio streams generated by the output timing obtained from the simulation. We notice that each method has a situation to be applied appropriately.

关键词： Degradation Wireless LAN Receivers Quality of service Streaming media Media Timing Reliability Quality of experience Streams

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Characterization of Néel relaxation time in multicore magnetic nanoparticles

Characterization of Néel relaxation time in multicore magne...

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2023 IEEE International Magnetic Conference - Short Papers, INTERMAG Short Papers 2023

作者： Goto, Haruki Futagawa, Masato Takemura, Yasushi Ota, Satoshi Shizuoka University Electrical and Electronic Engineering Course Graduate School of Integrated Science and Technology Hamamatsu432-8561 Japan Shizuoka University Department of Electrical and Electronic Engineering Hamamatsu432-8561 Japan Yokohama National University Department of Electrical and Computer Engineering Yokohama240-8501 Japan

ISBN: (纸本)9798350338362

Magnetic nanoparticles are developed for the biomedical applications such as hyperthermia and magnetic particle imaging. Magnetic relaxation determines the performance of magnetic nanoparticles in these applications. The magnetic relaxation was divided into two types as the Néel relaxation and Brown relaxations. In this research, the magnetization response associated with the Néel relaxation was observed by applying a pulse magnetic field in magnetic nanoparticles of the multicore structure. The measured Neel relaxation were roughly divided into fast and slow responses. The slow response was dominant compared to the fast part, which is consistent with the distribution of the particle core size of measured magnetic nanoparticles. Elucidating the Néel relaxation time of magnetic nanoparticles guide the design of particles suitable for the biomedical applications and determines the optimal magnetic field conditions. © 2023 IEEE.

关键词： Medical applications

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Prediction of Geopolymer Concrete Compressive Strength Using Convolutional Neural Networks

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computer Modeling in engineering & sciences 2024年第5期139卷 1455-1486页

作者： Kolli Ramujee Pooja Sadula Golla Madhu Sandeep Kautish Abdulaziz S.Almazyad Guojiang Xiong Ali Wagdy Mohamed Department of Civil Engineering VNR Vignana Jyothi Institute of Engineering and TechnologyHyderabadTelangana500090India Department of Information Technology VNR Vignana Jyothi Institute of Engineering and TechnologyHyderabadTelangana500090India Department of Computer Science LBEF Campus(Asia Pacific University of Technology&InnovationMalaysia)Kathmandu44600Nepal Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Saudi Arabia Guizhou Key Laboratory of Intelligent Technology in Power System College of Electrical EngineeringGuizhou UniversityGuiyang550025China Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Applied Science Research Center Applied Science Private UniversityAmmanJordan

Geopolymer concrete emerges as a promising avenue for sustainable development and offers an effective solution to environmental *** attributes as a non-toxic,low-carbon,and economical substitute for conventional cement concrete,coupled with its elevated compressive strength and reduced shrinkage properties,position it as a pivotal material for diverse applications spanning from architectural structures to transportation *** this context,this study sets out the task of using machine learning(ML)algorithms to increase the accuracy and interpretability of predicting the compressive strength of geopolymer concrete in the civil engineering *** achieve this goal,a new approach using convolutional neural networks(CNNs)has been *** study focuses on creating a comprehensive dataset consisting of compositional and strength parameters of 162 geopolymer concrete mixes,all containing Class F fly *** selection of optimal input parameters is guided by two distinct *** first criterion leverages insights garnered from previous research on the influence of individual features on compressive *** second criterion scrutinizes the impact of these features within the model’s predictive *** to enhancing the CNN model’s performance is the meticulous determination of the optimal *** a systematic trial-and-error process,the study ascertains the ideal number of epochs for data division and the optimal value of k for k-fold cross-validation—a technique vital to the model’s *** model’s predictive prowess is rigorously assessed via a suite of performance metrics and comprehensive score ***,the model’s adaptability is gauged by integrating a secondary dataset into its predictive framework,facilitating a comparative evaluation against conventional prediction *** unravel the intricacies of the CNN model’s learning trajectory,a loss plot is deployed to elucidate its learning rat

关键词： Class F fly ash compressive strength geopolymer concrete prediction deep learning convolutional neural network

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QoE Enhancement of Multi-View Video Transmission Over ICN/CCN by Means of Cache Control Method

QoE Enhancement of Multi-View Video Transmission Over ICN/CC...

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IEEE Games Media Entertainment (GEM)

作者： Yoshiyuki Takada Toshiro Nunome Department of Engineering Computer Science Program Graduate School of Engineering Nagoya Institute of Technology Nagoya Japan

ISBN: (数字)9798350374537

ISBN: (纸本)9798350374544

This paper considers multi-view video and audio transmission on ICN (Information-Centric Networking)/CCN (Content-Centric Networking). Routers in ICN/CCN can cache content. Besides, the capacity of routers' caches is finite, so various cache control schemes have been proposed to improve cache efficiency. This paper presents and evaluates a new and suitable control scheme for multi-view video and audio transmission. For this purpose, we construct a network environment with Cefore. We assess application-level QoS (Quality of Service) and QoE (Quality of Experience). We then show the effectiveness of the proposed control scheme.

关键词： Information-centric networking Entertainment industry Quality of service Media Quality of experience Frequency control

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Short Wave Infrared Upconversion Imager with Electron Blocking Layer to Screen Electron Injection into Photosensitive Layer 5

Short Wave Infrared Upconversion Imager with Electron Blocki...

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5th IEEE International Conference on Flexible and Printable Sensors and Systems, FLEPS 2023

作者： Shin, Chanho Li, Ning Ng, Tse Nga University of California San Diego Material Science and Engineering Program La Jolla United States University of California San Diego Department of Electrical and Computer Engineering La Jolla United States

ISBN: (纸本)9781665457330

In this work, we demonstrated upconversion imagers integrated with shortwave infrared photodetectors paired with an electron blocking layer. The use of electron blocking layer screened charge injection to prevent recombination in photosensitive layer. The characteristics of each electron blocking layer were analyzed in aspects of noise and detectivity. For the optimized device, the parasitic luminance in the dark was efficiently suppressed, and the photon-to-photon efficiency was increased. The electron blocking layer used in this work is generally applicable for upconversion imagers using different absorption and emitting materials. © 2023 IEEE.

关键词： Photodetectors

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High-Performance Face Identification using Hyperspectral Imaging to Counteract Deep Fake Biometrics

High-Performance Face Identification using Hyperspectral Ima...

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IEEE International Conference on Robotic Computing (IRC)

作者： Sota Furusawa Chinthaka Premachandra Dept. of Electrical Engineering and Computer Science Graduate School of Engineering and Science Shibaura Institute of Technology Tokyo Japan

ISBN: (数字)9798331521554

ISBN: (纸本)9798331521561

This research addresses the security challenges posed by Generative Adversarial Networks (GANs) in biometric authentication, focusing particularly on the use of Hyperspectral Imaging (HSI) to counteract the threat of deep fake biometrics created by GANs. We sought solutions to the issues identified in a previous study, such as the inability to handle images of individuals not previously trained and the high time consumption required for identification. In this paper, we first reduced the dimensionality of hyperspectral face data used for training, and then conducted a binary classification of “target subject (class)” and “nontarget subjects (classes).” A discriminator, based on the Least Squares Generative Adversarial Network (LSGAN) model, was developed using HSI for each class for binary classification. The proposed method significantly reduced identification time and achieved very high accuracy in identification.

关键词： Training Deepfakes Face recognition Biological system modeling Focusing Generative adversarial networks Security Robots Hyperspectral imaging Principal component analysis

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Evaluation of magnetization response of magnetic nanoparticles internalized into cultured adherent cells

Evaluation of magnetization response of magnetic nanoparticl...

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2023 IEEE International Magnetic Conference - Short Papers, INTERMAG Short Papers 2023

作者： Nishida, Minoru Futagawa, Masato Takemura, Yasushi Ota, Satoshi Shizuoka University Graduate School of Integrated Science and Technology Electrical and Electronic Engineering Course Hamamatsu432-8561 Japan Shizuoka University Department of Electrical and Electronic Engineering Hamamatsu432-8561 Japan Yokohama National University Department of Electrical and Computer Engineering Yokohama240-8501 Japan

ISBN: (纸本)9798350338362

To develop the biomedical application using magnetic nanoparticles, the magnetization properties associated with the magnetic relaxation with respect to magnetic nanoparticles internalized into cells were important. In this study, magnetization properties of magnetic nanoparticles internalized into the cultured adherent cells were measured by evaluating harmonic intensities derived from the magnetization response, which were compared to the magnetization of magnetic nanoparticles dispersed in liquid and fixed with epoxy resin. In particular, the nano-volt harmonic signals were obtained in intracellular magnetic nanoparticles. It is indicated that the particle aggregation reduced the magnetization, and the particle physical rotation was inhibited in the intracellular environment. © 2023 IEEE.

关键词： Cells

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Heart Disease Prediction Using Novel Ensemble and Blending Based Cardiovascular Disease Detection Networks: EnsCVDD-Net and BlCVDD-Net

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IEEE Access 2024年 12卷 109230-109254页

作者： Khan, Hira Javaid, Nadeem Bashir, Tariq Akbar, Mariam Alrajeh, Nabil Aslam, Sheraz Department of Electrical and Computer Engineering COMSATS University Islamabad Islamabad44000 Pakistan Department of Computer Science COMSATS University Islamabad Islamabad44000 Pakistan International Graduate School of Artificial Intelligence National Yunlin University of Science and Technology Yunlin Douliu64002 Taiwan Department of Biomedical Technology College of Applied Medical Sciences King Saud University Riyadh11633 Saudi Arabia Cyprus University of Technology Limassol3036 Cyprus

Cardiovascular Diseases (CVDs) have emerged as a significant physiological condition, being a primary contributor to mortality. Timely and precise diagnosis of heart disease is crucial to safeguard patients from additional harm. Recent studies show that the usage of data driven approaches, such as Deep Learning (DL) and Machine Learning (ML) techniques, in the field of medical science is highly useful in accurately diagnosing heart disease in less time. However, statistical learning and traditional ML approaches require feature engineering to generate robust and effective features from data, which are then used in the prediction models. In the case of large complex data, both processes pose many challenges. Whereas, DL techniques are capable of learning features automatically from the data and are effective at handling large and intricate datasets while outperforming the ML models. This study focuses on the accurate prediction of CVDs, considering the patient’s health and socio-economic conditions while mitigating the challenges presented by imbalanced data. The Adaptive Synthetic Sampling Technique is used for data balancing, while the Point Biserial Correlation Coefficient is used as a feature selection technique. In this study, two DL models, Ensemble based Cardiovascular Disease Detection Network (EnsCVDD-Net) and Blending based Cardiovascular Disease Detection Network (BlCVDD-Net), are proposed for accurate prediction and classification of CVDs. EnsCVDD-Net is made by applying an ensemble technique to LeNet and Gated Recurrent Unit (GRU), and BlCVDD-Net is made by blending LeNet, GRU and Multilayer Perceptron. SHapley Additive exPlanations is used to provide a clear understanding of the influence different factors have on CVD diagnosis. The network’s performance is evaluated on the basis of various performance metrics. The results indicate that the EnsCVDD-Net outperforms all base models with 88% accuracy, 88% F1-score, 91% precision, 85% recall, and 777s execu

关键词： Heart

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Grating Coupled Attachment of Optical Fiber Arrays for in situ Photonics Experimentation

Grating Coupled Attachment of Optical Fiber Arrays for in si...

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2024 Conference on Lasers and Electro-Optics, CLEO 2024

作者： Arnold, Kellen P. Slaby, Joel B. Dattilo, Hannah M. Kaylor, C. Alex Schrimpf, Ronald D. Fleetwood, Daniel M. Ralph, Stephen E. Reed, Robert Weiss, Sharon M. Interdisciplinary Materials Science Program Vanderbilt University 2201 West End Ave NashvilleTN37235 United States School of Electrical and Computer Engineering Georgia Institute of Technology AtlantaGA30332 United States Department of Electrical and Computer Engineering Vanderbilt University 2201 West End Ave NashvilleTN37235 United States

We report a simple, vacuum-compatible fiber attach process for in situ study of grating-coupled photonic devices. The robustness of this technique is demonstrated on grating-coupled waveguides exposed to multiple X-ra... 详细信息

ISBN: (纸本)9781957171395

关键词： X ray lasers

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Implementation and Performance Evaluation of Collective Communications Using CIRCUS on Multiple FPGAs

Implementation and Performance Evaluation of Collective Comm...

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2023 International Conference on High Performance Computing in Asia-Pacific Region Workshops, HPC Asia 2023

作者： Kikuchi, Kohei Fujita, Norihisa Kobayashi, Ryohei Boku, Taisuke Master's Program in Computer Science Degree Programs in Systems and Information Engineering Graduate School of Science and Technology University of Tsukuba Tsukuba Japan Center for Computational Sciences University of Tsukuba Tsukuba Japan

ISBN: (纸本)9781450399890

In the high-performance computing domain, Field programmable Gate Array (FPGA) is a novel accelerator that exhibits high flexibility and performance characteristics distinct from other accelerators such as the Graphics Processing Unit (GPU). Recent advanced high-end FPGA is equipped with multiple channels of high speed optical link up to 100Gbps performance for each. This is a crucial feature when we construct PC clusters with FPGAs as accelerators, however it is not easy to utilize from user kernels because this feature is implemented in low level and simple direct communication between neighboring FPGAs. In order to provide the communication feature between FPGAs for accelerated PC clusters, we developed a communication system named CIRCUS which implies a user-friendly API from OpenCL and is equipped with routing function over multi-hop communication on multi-dimensional torus network of FPGAs. However, current CIRCUS only provides a point-to-point communication between source and destination FPGAs. In ordinary parallel processing environment such as MPI, the user program the message passing with various collective communication functions for parallel algorithm, for instance Allreduce, Allgather, etc. In this paper, we implement the collective communication function over CIRCUS for user-friendly programming of ordinary parallel algorithms on FPGAs. As the first target, we implement Allreduce function which is the most essential and important function. The paper describes the CIRCUS system briefly followed by the design, implementation and preliminary performance evaluation on Intel Stratix10 FPGAs. © 2023 ACM.

关键词： Field programmable gate arrays (FPGA)

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