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2021 IEEE International Symposium on Antennas and Propagation and North American Radio science Meeting, APS/URSI 2021

作者： Liao, Hanguang Bilal, Rana Muhammad Shamim, Atif Electrical and Computer Engineering Program King Abdullah University of Science and Technology Thuwal Saudi Arabia

ISBN: (纸本)9781728146706

Sensing and retrieving data from ocean to land are challenging and expensive tasks, while the Internet of Sea (IoS) concept can help to monitor ocean environment in a low-cost way. In this paper, an Electrically Small (ES) dual-band monopole antenna is proposed for the IoS application. Dual-band operation (GSM-900, LoRa, and BLE bands) and vertical polarization are maintained in a very compact size. The proposed antenna operates as a folded monopole antenna at 900MHz, and as a simple monopole antenna at 2.4 GHz, by combining the top-loaded folded monopole antenna and the 2-layer monopole feeding structure. The proposed antenna has ka of 0.45 at the LB, with a decent polarization purity and radiation efficiency of 54%. The proposed antenna is designed with a low-cost additive manufacturing material system. © 2021 IEEE.

关键词： Monopole antennas

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A linear time algorithm for pricing european sequential barrier options

A linear time algorithm for pricing european sequential barr...

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13th Computing: The Australasian Theory Symposium, CATS2007

作者： Gao, Peng van der Meyden, Ron School of Computer Science and Engineering UNSW and Formal Methods Program National ICT Australia Australia

ISBN: (纸本)1920682465

Financial derivatives are contracts concerning rights and obligations to engage in future transactions on some underlying financial instrument. A major con-cern in financial markets is to compute an expected value of such contracts as a basis for trading decisions. The Cox, Ross and Rubinstein (CRR) binomial tree model is a popular discrete approach to such compu-tations, which requires time quadratic in the number of discrete temporal steps to contract termination. Lyuu has shown that barrier options can be valued with respect to the CRR model in linear time, us-ing a combinatorial method. The paper develops a generalization of Lyuu's result, showing that a class of more complex options comprised of a sequence of barriers can be valued in linear time. © 2007, Australian computer Society, Inc.

关键词： Clustering algorithms

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Biomedical data and AI

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science China Life sciences 2025年第5期68卷 1536-1540页

作者： Hao Xu Shibo Zhou Zefeng Zhu Vincenzo Vitelli Liangyi Chen Ziwei Dai Ning Yang Luhua Lai Shengyong Yang Sergey Ovchinnikov Zhuoran Qiao Sirui Liu Chen Song Jianfeng Pei Han Wen Jianfeng Feng Yaoyao Zhang Zhengwei Xie Yang-Yu Liu Zhiyuan Li Fulai Jin Hao Li Mohammad Lotfollahi Xuegong Zhang Ge Yang Shihua Zhang Ge Gao Pulin Li Qi Liu Jing-Dong Jackie Han Peking-Tsinghua Center for Life Sciences (CLS) Academy for Advanced Interdisciplinary StudiesPeking University Center for Quantitative Biology (CQB) Academy for Advanced Interdisciplinary StudiesPeking University Peking University-Tsinghua University-National Institute of Biological Sciences Joint Graduate Program Academy for Advanced Interdisciplinary StudiesPeking University Department of Physics University of Chicago School of Life Sciences Southern University of Science and Technology Peking University Chengdu Academy for Advanced Interdisciplinary Biotechnologies College of Chemistry and Molecular Engineering Peking University Department of Biotherapy Cancer Center and State Key Laboratory of BiotherapyWest China HospitalSichuan University Department of Biology Massachusetts Institute of Technology Lambic Therapeutics Inc. Changping Laboratory Al for Science Institute Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence Fudan University Department of Obstetrics and Gynecology West China Second University HospitalSichuan University Peking University International Cancer Institute and Peking University-Yunnan Baiyao International Medical Institute and State Key Laboratory of Natural and Biomimetic Drugs Department of Molecular and Cellular PharmacologySchool of Pharmaceutical SciencesPeking University Health Science CenterPeking University Channing Division of Network Medicine Department of MedicineBrigham and Women's Hospital and Harvard Medical School Center for Artificial Intelligence and Modeling the Carl R.Woese Institute for Genomic BiologyUniversity of Illinois Urbana-Champaign Department of Genetics and Genome Sciences School of Medicine and Department of Computer and Data Sciences and Department of Population and Quantitative Health SciencesCase Western Reserve University Department of Biochemistry and Biophysics University of California Sanger Institute Department of Automation Tsinghua University State Key Laboratory of Multimodal Artificial Intelligence Systems I

The development of artificial intelligence(AI) and the mining of biomedical data complement each other. From the direct use of computer vision results to analyze medical images for disease screening, to now integrating biological knowledge into models and even accelerating the development of new AI based on biological discoveries, the boundaries of both are constantly expanding, and their connections are becoming closer.

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Optimal Placement of Software Monitors Aiding Systematic Testing

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IEEE Transactions on Software engineering 1975年第4期SE-1卷 403-411页

作者： Ramamoorthy, C.V. Kim, K.H. Chen, W.T. Computer Science Division Department of Electrical Engineering and Computer Sciences University of California Berkeley Calif 94720 United States Department of Electrical Engineering Systems and Computer Science Program University of Southern California Los Angeles Calif. United States

The usefulness of software monitors in testing large ‘programs is discussed. Several types of testing strategies based on the use of monitors are surveyed. Since there is a computational overhead involved in employing monitors, attempts are made to minimize the number of monitors employed. This optimization problem is formulated and analyzed in graph-theoretic terms. Implementation aspects are considered through both discussion and examples. Copyright © 1975 by The Institute of Electrical and Electronics Engineers, Inc.

关键词： Optimal placement overhead program testing software monitor test-input test-output test-path test-run

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IEEE Transactions on Cloud Computing 2025年

作者： Shayesteh, Behshid Fu, Chunyan Ebrahimzadeh, Amin Glitho, Roch Concordia University Concordia Institute of Information System Engineering (CIISE) Montréal H3G 1M8 Canada Research Ericsson Montréal QC H4S 0B6 Canada Concordia University CIISE Montréal QC H3G 1M8 Canada University of Western Cape Computer Science Program Cape Town 7535 South Africa

Applications deployed in clouds are susceptible to performance degradation due to diverse underlying causes such as infrastructure faults. To maintain the expected availability of these applications, Machine Learning (ML) models can be used to predict the impending application performance degradations to take preventive measures. However, the prediction accuracy of these ML models, which is a key indicator of their performance, is influenced by several factors, including training data size, data sampling intervals, input window and prediction horizon. To optimize these data-related parameters, in this paper, we propose a surrogate-assisted multi-objective optimization algorithm with the objective to maximize prediction model accuracy while minimizing the resources consumed for data collection and storage. We evaluated the proposed algorithm through two use cases focusing on the prediction of Key Performance Indicators (KPIs) for a 5 G core network and a web application deployed in two Kubernetes-based cloud testbeds. It is demonstrated that the proposed algorithm can achieve a normalized hypervolume of 99.5% relative to the optimal Pareto front and reduce search time for the optimal solution by 0.6 hours compared to other surrogates and by 3.58 hours compared to using no surrogates. © 2013 IEEE.

关键词： Clouds fault prediction machine learning multi-objective optimization

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Compact Model Build Upon Dynamic Weighting Artificial Neural Network Approach for Complementary Field Effect Transistors

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IEEE Transactions on Electron Devices 2024年第1期71卷 246-253页

作者： Butola, Rajat Li, Yiming Kola, Sekhar Reddy National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Electrical Engineering and Computer Science International Graduate Program Hsinchu300093 Taiwan Institute of Pioneer Semiconductor Innovation The Institute of Artificial Intelligence Innovation National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Electrical Engineering and Computer Science International Graduate Program The Institute of Communications Engineering the Institute of Biomedical Engineering Department of Electronics and Electrical Engineering Hsinchu300093 Taiwan

In this work, a dynamic weighting-artificial neural network (DW-ANN) methodology is presented for quick and automated compact model (CM) generation. It takes advantage of both TCAD simulations for high accuracy and SPICE simulations for cost-effectiveness. This methodology is developed for gate-all-around (GAA) silicon (Si) nanosheet (NS) complementary field effect transistor (CFET), a potential candidate for future CMOS technology due to its innate properties. The critical process variation (PV) sources that severely degrade the CFET performance are estimated using DW-ANN. It reduces the computation cost and predicts the effects of PV sources with less than 1% error. Furthermore, a compact DW-ANN-based Verilog-A model has been developed that captures the dc as well as transient behavior accurately for circuit-level analysis. CFET-based circuits such as inverter, 6T-static random access memory (SRAM), and ring oscillator (RO) are characterized and implemented using DW-ANN-based CM. The overall average error of the model is reported as less than 2%. Therefore, the proposed device and circuit modeling approach provides a feasible solution for the rapid compact modeling of new emerging devices with good convergence and high accuracy. © 1963-2012 IEEE.

关键词： Neural networks

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Enhancing safety with an AI-empowered assessment and monitoring system for BSL-3 facilities

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Heliyon 2025年第1期11卷 e40855页

作者： Fan, Yi-Ling Hsu, Ching-Han Wu, Ju-Yu Tsai, Ying-Ying Chen, Wei J. Lee, Min-Shi Hsu, Fang-Rong Liao, Lun-De Institute of Biomedical Engineering and Nanomedicine National Health Research Institutes 35 Keyan Road Miaoli County Zhunan Town 350 Taiwan Department of Biomedical Engineering & Environmental Sciences National Tsing-Hua University Hsinchu Taiwan Doctoral Program in Tissue Engineering and Regenerative Medicine National Chung Hsing University Taichung Taiwan Center for Neuropsychiatric Research National Health Research Institutes 35 Keyan Road Miaoli County Zhunan Town 350 Taiwan National Institute of Infectious Diseases and Vaccinology National Health Research Institutes 35 Keyan Road Miaoli County Zhunan Town 350 Taiwan Department of Information Engineering and Computer Science Feng Chia University Taichung 407 Taiwan

Introduction: The COVID-19 pandemic has created an urgent demand for research, which has spurred the development of enhanced biosafety protocols in biosafety level (BSL)-3 laboratories to safeguard against the risks associated with handling highly contagious pathogens. Laboratory management failures can pose significant hazards. Methods: An external system captured images of personnel entering a laboratory, which were then analyzed by an AI-based system to verify their compliance with personal protective equipment (PPE) regulations, thereby introducing an additional layer of protection. A deep learning model was trained to detect the presence of essential PPE items, such as clothing, masks, hoods, double-layer gloves, shoe covers, and respirators, ensuring adherence to World Health Organization (WHO) standards. The internal laboratory management system used a deep learning model to delineate alert zones and monitor compliance with the imposed safety protocols. Results: The external detection system was trained on a dataset consisting of 4112 images divided into 15 PPE compliance classes. The model achieved an accuracy of 97.52 % and a recall of 97.03 %. The identification results were presented in real time via a visual interface and simultaneously stored on the administrator's dashboard for future reference. We trained the internal management system on 3347 images, achieving 90 % accuracy and 85 % recall. The results were transmitted in JSON format to the internal monitoring system, which triggered alerts in response to violations of safe practices or alert zones. Real-time notifications were sent to the administrators when the safety thresholds were met. Conclusion: The BSL-3 laboratory monitoring system significantly reduces the risk of exposure to pathogens for personnel during laboratory operations. By ensuring the correct use of PPE and enhancing adherence to the imposed safety protocols, this system contributes to maintaining the integrity of BSL-3 facilities

关键词： Bioengineering Biomedical instrumentation Biomedical laboratory safety Biosafety level-3 laboratory

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Uncovering response biases in recommendation 28

Uncovering response biases in recommendation

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28th AAAI Conference on Artificial Intelligence, AAAI 2014

作者： Park, Kyung-Wha Kim, Byoung-Hee Park, Tae-Suh Zhang, Byoung-Tak Department of Computer Science and Engineering 'Brain Science Program Seoul National University Seoul151-742 Korea Republic of

ISBN: (纸本)9781577356714

An user-specific tendency of biased movie rating is investigated, leading six identified types of rating pattern in a massive movie rating dataset. Based on the observed bias assumption, we propose a rescaling method of preferential scores by considering the rating types. Experimental results show significant enhancement for movie recommendation systems. © Copyright 2014, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Motion pictures

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Into 3D-Reconstructed Apparel over Virtual Try-On with Virtual Reality

Into 3D-Reconstructed Apparel over Virtual Try-On with Virtu...

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2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023

作者： Doungtap, Surasachai Petchhan, Jirayu Phanichraksaphong, Varinya Wang, Jenq-Haur International Graduate Program of Electrical Engineering and Computer Science Taiwan National Taiwan University of Science & Technology Dept. of Electrical Engineering Taiwan National Taipei University of Technology Department of Computer Science and Information Engineering Taiwan

ISBN: (纸本)9798350324174

Virtualization technologies are still growing bigger and faster. Despite the greatness of its advancement, the costume industry is still very accessible when it comes to real trials. Off-the-shelf stuff are inadequate details for the desired individual to assess its in-depth utility for each garment trying on for a second, including custom stuff are much harder to try out right away. To this end, 2D image-based 3D reconstruction inclusive of touchable-virtualized space is accessible easier to stuff details for mans' decision making in purchasing. We establish the overall end-to-end pipeline from reconstruction until visualization for one instance to be triable on its stuff for a moment. As an expectation, our proposed approach can bring objects into the experimental area and use them immediately without any obstacle. © 2023 IEEE.

关键词： Virtual reality

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SIMPLE APPROACH TO REFLECTANCE ANALYSIS OF BIREFRINGENT STRATIFIED FILMS

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APPLIED OPTICS 1991年第28期30卷 4017-4018页

作者： KNOESEN, A []The author is with the Department of Electrical Engineering Computer Science Organized Research Program on Polymeric Ultrathin Film Systems University of California Davis Davis California 95616

A simple analysis is presented of reflectance from a stratified uniaxial media with the optic axes parallel or perpendicular to the plane of incidence.

关键词： UNIAXIAL FILMS POLED POLYMERS THIN FILM BIREFRINGENT

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