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IEEE Latin American Symposium on Circuits and systems (LASCAS)

作者： José A. Apolinário Cláudio A. B. Saunders Filho Antonio L. L. Ramos Program of Electrical Engineering Military Institute of Engineering (IME) Rio de Janeiro Brazil Department of Science and Industry Systems (IRI) TNM University of South-Eastern Norway (USN) Kongsberg Norway

ISBN: (数字)9798331522124

ISBN: (纸本)9798331522131

This paper investigates mutual coupling in narrow-band uniform linear antenna arrays through Thévenin network modeling. After an in-depth analysis, we derive a Thévenin network representing a given mutual coupling matrix and develop a method to achieve an equivalent decoupled model that significantly reduces computational and memory requirements in practical applications.

关键词： Mutual coupling Analytical models Circuits and systems Array signal processing Computational modeling Memory management Linear antenna arrays Integrated circuit modeling Narrowband

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On the Estimation Performance of Generalized Power Method for Heteroscedastic Probabilistic PCA

arXiv

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arXiv 2023年

作者： Wang, Jinxin Jiang, Chonghe Liu, Huikang So, Anthony Man-Cho Department of Systems Engineering and Engineering Management The Chinese University of Hong Kong Hong Kong Research Institute for Interdisciplinary Sciences School of Information Management and Engineering Shanghai University of Finance and Economics China

The heteroscedastic probabilistic principal component analysis (PCA) technique, a variant of the classic PCA that considers data heterogeneity, is receiving more and more attention in the data science and signal processing communities. In this paper, to estimate the underlying low-dimensional linear subspace (simply called ground truth) from available heterogeneous data samples, we consider the associated non-convex maximum-likelihood estimation problem, which involves maximizing a sum of heterogeneous quadratic forms over an orthogonality constraint (HQPOC). We propose a first-order method—generalized power method (GPM)—to tackle the problem and establish its estimation performance guarantee. Specifically, we show that, given a suitable initialization, the distances between the iterates generated by GPM and the ground truth decrease at least geometrically to some threshold associated with the residual part of certain "population-residual decomposition". In establishing the estimation performance result, we prove a novel local error bound property of another closely related optimization problem, namely quadratic optimization with orthogonality constraint (QPOC), which is new and can be of independent interest. Numerical experiments are conducted to demonstrate the superior performance of GPM in both Gaussian noise and sub-Gaussian noise settings. Copyright © 2023, The Authors. All rights reserved.

关键词： Maximum likelihood estimation

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Classification Of Ornamental Fish Types Using CNN Method With VGG-16 And U-NET Architecture

Classification Of Ornamental Fish Types Using CNN Method Wit...

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Consumer Technology (ICCT-Pacific), International Conference on

作者： Ni Luh Wiwik Sri Rahayu Ginantra Christina Purnama Yati I Gusti Ayu Agung Diatri Indradewi I Komang Agus Yudiawan Technology and Informatics Informatics Engineering Institut Bisnis dan Teknologi Indonesia (INSTIKI) Denpasar Indonesia Department of Informatics Engineering Information Systems Study Program Faculty of Engineering and Vocational Studies Universitas Pendidikan Ganesha (UNDIKSHA) Denpasar Indonesia

ISBN: (数字)9798331504120

ISBN: (纸本)9798331504137

Ornamental fish are a type of fish that live in freshwater or seawater habitats and are typically maintained for aesthetic purposes, often in ornamental ponds or as household pets. The diversity of colors, shapes, and patterns observed in ornamental fish presents a challenge in their classification. Therefore, a method capable of accurately recognizing the visual characteristics of these fish is required. The objective of this study is to evaluate the performance of two Convolutional Neural Network (CNN) architectures, specifically VGG-16 and U-Net, using five distinct types of ornamental fish, namely Angel Fish, Betta Fish, Clown Fish, Gold Fish, and Guppy Fish. The dataset comprises 3.240 images that have been processed using TensorFlow and Keras on Google Collaboratory. The results demonstrated that U-Net demonstrated superior performance in segmentation, with an Average Intersection over Union (IoU) of 58.91 % and an Average Dice Coefficient of 73.72%. In contrast, VGG-16 exhibited signs of overfitting, as evidenced by lower evaluation metrics. To enhance the efficacy of the transfer learning model, further optimization is recommended.

关键词： Measurement Image segmentation Visualization Shape Transfer learning Fish Internet Convolutional neural networks Optimization Overfitting

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A Federated Learning Approach to Banking Loan Decisions

A Federated Learning Approach to Banking Loan Decisions

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

作者： Azzedin, Farag Ghaleb, Mustafa El-Alfy, Yasser Katib, Raed Hossain, M.D. King Fahd University of Petroleum and Minerals Information & Computer Science Department Dhahran Saudi Arabia Interdisciplinary Research Center for Intelligent Secure Systems King Fahd University of Petroleum and Minerals Saudi Arabia King Fahd University of Petroleum and Minerals Computer Engineering Department Dhahran Saudi Arabia

ISBN: (纸本)9798350335590

Machine Learning (ML) techniques for decision-making have become a topic of popular interest for many organizations. Such models, however, depend on data availability which is not always possible. Banks, for example, often have limited data about their customers. While this data could be supplemented with information from other banks, data sharing leads to privacy concerns due to regulations such as the General Data Protection Regulation (GDPR) and the California Customer Privacy Act (CCPA). An alternative method proposed to solve such a problem is Federated Learning (FL), where the data is not shared, but the models created by each entity are shared to keep privacy. FL has been applied across various sectors and industries, but not all. In this paper, we implement an FL algorithm in a new sector, namely, banking and loans. We used an architecture where multiple banks within the same country, each possessing different customer information, want to evaluate eligibility for loan provision. Our objective is to design an FL model where the banks share the data without exposing any customer hidden information. We implemented our FL model using Flower on the publicly available Loan dataset on Kaggle. Our model achieved an accuracy of 81%. © 2023 IEEE.

关键词： Risk assessment

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Low-dose intrapulmonary drug delivery device for studies on next-generation therapeutics in mice

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Journal of Controlled Release 2023年第1期359卷 287-301页

作者： Gracioso Martins, Ana Maria Snider, Douglas B. Popowski, Kristen D. Schuchard, Karl G. Tenorio, Matias Akunuri, Sandip Wee, Junghyun Peters, Kara J. Jansson, Anton Shirwaiker, Rohan Cheng, Ke Freytes, Donald O. Cruse, Glenn P. Department of Molecular Biomedical Sciences College of Veterinary Medicine North Carolina State University RaleighNC United States Comparative Medicine and Translational Research Training Program North Carolina State University RaleighNC United States Comparative Medicine Institute North Carolina State University RaleighNC United States Joint Department of Biomedical Engineering College of Engineering North Carolina State University & University of North Carolina-Chapel Hill NC United States Edward P. Fitts Department of Industrial and Systems Engineering North Carolina State University RaleighNC United States Department of Mechanical and Aerospace Engineering North Carolina State University RaleighNC United States Analytical Instrumentation Facility Monteith Research Center North Carolina State University RaleighNC United States

Although nebulizers have been developed for delivery of small molecules in human patients, no tunable device has been purpose-built for targeted delivery of modern large molecule and temperature-sensitive therapeutics to mice. Mice are used most of all species in biomedical research and have the highest number of induced models for human-relevant diseases and transgene models. Regulatory approval of large molecule therapeutics, including antibody therapies and modified RNA highlight the need for quantifiable dose delivery in mice to model human delivery, proof-of-concept studies, efficacy, and dose-response. To this end, we developed and characterized a tunable nebulization system composed of an ultrasonic transducer equipped with a mesh nebulizer fitted with a silicone restrictor plate modification to control the nebulization rate. We have identified the elements of design that influence the most critical factors to targeted delivery to the deep lungs of BALB/c mice. By comparing an in silico model of the mouse lung with experimental data, we were able to optimize and confirm the targeted delivery of over 99% of the initial volume to the deep portions of the mouse lung. The resulting nebulizer system provides targeted lung delivery efficiency far exceeding conventional nebulizers preventing waste of expensive biologics and large molecules during proof-of-concept and pre-clinical experiments involving mice. (Word Count =207). © 2023 Elsevier B.V.

关键词： Molecules

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Dynamic channel estimation-aware routing protocol in mobile cognitive radio networks for smart IIoT applications

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Digital Communications and Networks 2023年第2期9卷 367-382页

作者： Qusay M.Salih Md Arafatur Rahman A.Taufiq Asyhari Muhammad Kamran Naeem Mohammad Patwary Ryan Alturki Mohammed Abdulaziz Ikram Faculty of Computing Universiti Malaysia Pahang26300GambangPahangMalaysia School of Engineering Computing and Mathematical SciencesUniversity of WolverhamptonUK Data Science Program Monash UniversityIndonesiaand Birmingham City UniversityB47XGUK Department of Information Science College of Computer and Information SystemsUmm Al-Qura UniversitySaudi Arabia Computer Science Department Al Jumoum University CollegeUmm Al-Qura UniversitySaudi Arabia

Cognitive Radio Networks(CRNs)have become a successful platform in recent years for a diverse range of future systems,in particularly,industrial internet of things(IIoT)*** order to provide an efficient connection among IIoT devices,CRNs enhance spectrum utilization by using licensed ***,the routing protocol in these networks is considered one of the main problems due to node mobility and time-variant channel ***,the channel selection for routing protocol is indispensable in CRNs to provide an adequate adaptation to the Primary User(PU)activity and create a robust routing *** study aims to construct a robust routing path by minimizing PU interference and routing delay to maximize throughput within the IIoT ***,a generic routing framework from a cross-layer perspective is investigated that intends to share the information resources by exploiting a recently proposed method,namely,Channel Availability ***,a novel cross-layer-oriented routing protocol is proposed by using a time-variant channel estimation *** protocol combines lower layer(Physical layer and Data Link layer)sensing that is derived from the channel estimation ***,it periodically updates and stores the routing table for optimal route ***,in order to achieve higher throughput and lower delay,a new routing metric is *** evaluate the performance of the proposed protocol,network simulations have been conducted and also compared to the widely used routing protocols,as a *** simulation results of different routing scenarios demonstrate that our proposed solution outperforms the existing protocols in terms of the standard network performance metrics involving packet delivery ratio(with an improved margin of around 5–20%approximately)under varying numbers of PUs and cognitive users in Mobile Cognitive Radio Networks(MCRNs).Moreover,the cross-layer routing protocol successfully achiev

关键词： Channel selection Cross-layer design Mobile cognitive radio networks Routing protocol IIoT applications

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Arabic text sentiment analysis and emotion classification using transformers

Arabic text sentiment analysis and emotion classification us...

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Electronics, Communications, and Computations (JAC-ECC), International Japan-Africa Conference on

作者： Nada Mossad Youssef Mohamed A Fares Ahmed B. Zaky Egypt-Japan University of Science and Technology (E-JUST) Alexandria Egypt The Department of Electrical Engineering The Computer Systems Engineering Program Faculty of Engineering at Shoubra Benha University

Sentiment analysis and emotion classification are two crucial components of natural language processing (NLP), which have been widely explored in recent years due to their broad applications. Sentiment analysis aims to identify the polarity of written texts, ranging from positive to negative. Meanwhile, emotion classification is focused on recognizing and categorizing the emotional states expressed in the text. To achieve a deeper understanding of sentiments and emotions, it's essential to utilize models like BERT transformers that can effectively interpret the context. The process begins with data preprocessing, including tokenization and noise removal, followed by fine-tuning techniques to adapt the BERT model to the proposed tasks. We employed the BERT model on four datasets obtained from various sources, including Twitter, news websites, and restaurant reviews, where each dataset represents a distinct Arabic dialect. Our proposed model outperforms commonly used techniques like LSTM and CNN, yielding superior results. Despite the progress made, there are still challenges to overcome, such as dealing with Arabic diacritics, the new Arabic Arabizi, which uses Latin characters, and handling Arabic idioms. Further research is required to address these challenges adequately.

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Benoxacor is enantioselectively metabolized by microsomes and cytosol from the human liver

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Emerging Contaminants 2023年第1期9卷 10-19页

作者： Derek Simonsen Jacob Heffelfinger David M.Cwiertny Hans-Joachim Lehmler Department of Occupational and Environmental Health The University of IowaIowa CityIA52242United States Interdisciplinary Graduate Program in Human Toxicology The University of IowaIowa CityIA52242United States IIHR Hydroscience and Engineering The University of IowaIowa CityIA52242United States Department of Civil and Environmental Engineering The University of IowaIowa CityIA52242United States Center for Health Effects of Environmental Contamination The University of IowaIowa CityIA52242United States

Benoxacor is a safener added to current-use herbicide formulations to protect the target crop from herbicidal *** is an emerging environmental contaminant that has been detected in surface waters,raising the possibility of human exposure via drinking *** it is not subject to the same regulations as active pesticide ingredients,its metabolism and toxicity in humans have not been *** we investigate the enantioselective metabolism of benoxacor in human subcellular *** human liver microsomes(pHLM)and cytosol(pHLC)were incubated with racemic benoxacor for up to *** chromatographic analyses were used to measure the enantioselective depletion of *** with and without nicotinamide adenine dinucleotide phosphate(NADPH,co-factor for cytochrome P450 enzymes[CYPs])and pHLC with glutathione(GSH,co-factor for glutathione Stransferases[GSTs])metabolized *** results demonstrate that microsomal CYPs,microsomal carboxylesterase(CESs),and cytosolic GSTs metabolize *** were predicted to have a higher clearance of benoxacor by GSTs than *** and female pHLM incubations with NADPH showed enrichment of the first eluting benoxacor enantiomer(E1-benoxacor).pHLM incubations without NADPH and pHLC incubations with GSH showed an enrichment of the second eluting enantiomer of benoxacor(E2-benoxacor).Our results indicate that human hepatic microsomal and cytosolic enzymes enantioselectively metabolize benoxacor,a fact that needs to be considered when investigating human exposures and toxicities of benoxacor.

关键词： cor metabolism depletion

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Hardware Implementation of a Sliding Detection Algorithm for Robotic Hands Using Force Sensors

Hardware Implementation of a Sliding Detection Algorithm for...

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Symposium on Integrated Circuits and systems Design (SBCCI)

作者： Jose Mendoza-Peñaloza Daniel M. Muñoz Department of Mechanical Engineering Mechatronics Systems Graduate Program Automation and Control Group/GRACO Faculty of Gama Electronics Engineering Undergraduate Program University of Brasilia Brasilia DF Brazil

In this work, a sliding detection algorithm was proposed for a previously developed robotic hand through the utilization of force sensors. Previous works have designed several hardware architectures to filter sensor data, implement dynamic control, and machine learning models for controlling the robotic fingers using a single Field programmable Gate Arrays (FPGA) chip. In this regard, the slip detection algorithm was developed to comprise three stages, each with a low computational cost, including a moving average filter, a first-order derivative, and a peak detection algorithm. A reference model was constructed and validated through an experimental protocol employing daily use objects to create a database. Subsequently, the slip detection algorithm was mapped onto hardware utilizing previously developed floating-point arithmetic IP cores and implemented using a Zynq 7020 device. The FPGA implementation was characterized in terms of resource occupation, power consumption, execution time, and numerical error with the reference model.

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Low Power Consumption of Non-Volatile Memory Device by Tunneling Process engineering

SSRN

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SSRN 2024年

作者： Wang, Fucheng Chu, Mengmeng Chen, Jingwen Pan, Zhong Kim, Yongsang Song, Jang Kun Yi, Junsin Khokhar, Muhammad Quddamah Department of Electrical and Computer Engineering Sungkyunkwan University Suwon16419 Korea Republic of Interdisciplinary Program in Photovoltaic System Engineering Sungkyunkwan University Suwon16419 Korea Republic of College of Information and Communication Engineering Sungkyunkwan University Suwon16419 Korea Republic of

Compared with Si3N4 and Al2O3, SiO2 grown using thermal oxidation process as tunneling layer has the advantages of high bandgap and well interface contact with the surface of silicon wafer, which can be a great solution to the leakage current problem of metal-insulator-semiconductor (MIS) devices. This study investigates the effect of improving the SiO2 tunnel layer on the operating voltage of MIS devices with a SiO2/HfAlOx/Al2O3 structure. The result shows the operating voltage changes as the tunneling layer thickness decreases, with a minimum of only 12 V for a 1.5 nm tunneling layer thickness. In addition, we found that pinholes are generated on the film surface when annealing a 1.5 nm SiO2 tunnel layer at 850 °C N2, in which case the operating voltage of the device is reduced to only 10 V, though it was also accompanied by the deterioration of the retention characteristics. © 2024, The Authors. All rights reserved.

关键词： Silicon wafers

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