检索结果-内蒙古大学图书馆

2002 International Symposium on Distributed Computing and Applications for Business engineering and Science

作者： Joseph W.Haus Majeed M.Hayat Electro-Optics Program The University of Dayton Dayton OH45469-0245 Department of Electrical & Computer Engineering The University of New Mexico Albuquerque NM87131-1356

We report the OpenMP parallel implementation of a finite difference time domain (FDTD) method for computational electrodynamics. We have identified several time-intensive procedures in the program and parallelized the major loops within them after careful examination. Different loop scheduling schemes have been used and tested in order to reduce computation times. The final parallelized version speeds up the computation by nearly a factor of four between the single processor and eight processor test runs on an SGI Origin 2000 parallel system. The speedup plateaus after eight CPUs, but we expect better scalability will be achieved if larger problem sizes are used. Besides the advantage of reduced execution times, our parallel program can also solve FDTD problems of much larger sizes than the sequential code due to much larger memory space available to us on parallel systems.

关键词： domain OpenMP Parallel Implementation of Finite Difference Time Domain Electromagnetism Application

来源：评论

学校读者我要写书评

暂无评论

Enhancing Acute Ischemic Stroke Diagnosis Using IoMT and Deep Learning Technologies

Enhancing Acute Ischemic Stroke Diagnosis Using IoMT and Dee...

引用

Telecommunications Conference (ITC-Egypt), International

作者： Mohamed M. El-Sheikh Aya Bayoumy Nada M. Ahmed Amany Mohamed Eldeeb Fatma I. Rabea Amira A. Nawar Mohamed G. Khattap Hend Galal Eldeen Mohamed Ali Hassan Mariam Mostafa Nayra Ibrahim Reem Ramadan Yomna Refaat Mennatallah Khaled Ali Maher Mohamed Abd Elaziz Ahmed Gamal Abdellatif Ibrahim Radiology and Medical Imaging Faculty of Applied Health Sciences Galala University Suez Egypt Biomedical Informatics Faculty of Computer Science and Engineering Galala University Suez Egypt Artificial Intelligence Science Program Faculty of Computer Science and Engineering Galala University Suez Egypt Department of Electronics and Electrical Communications Engineering Air Defense College Alexandria Egypt

ISBN: (数字)9798350351408

ISBN: (纸本)9798350351415

This paper introduces an alternative technique for diagnosing Acute Ischemic Stroke within the IoMT environment. In the proposed approach, the collected data is transmitted to a cloud-based center where the technique utilizes EfficientNet, a deep learning model, designed to extract features from MRI images thereby enhancing the detection of acute ischemic infarctions. The performance of EfficientNet is compared against two other models, CNN and MobileNet, demonstrating its superior efficacy through metrics such as accuracy, precision, recall, and F1-score, which stand at 92.31%, 92.28%, 92.33%, and 92.30%, respectively.

关键词： Deep learning Accuracy Magnetic resonance imaging Soft sensors Medical services Feature extraction Regulation

来源：评论

学校读者我要写书评

暂无评论

Multi-Layered Alert Filtration and Feedback Cycle using Brahms Model

Multi-Layered Alert Filtration and Feedback Cycle using Brah...

引用

International Conference on Advanced computer Science Applications and Technologies

作者： Abid Ghaffar Mohamed Ridza Wahiddin Asadullah Shaikh Akhlaq Ahmad Department of Computer Science Foundation Year Program Umm Al-Qura University Department of Computer Science Kulliyyah of Information and Communication Technology International Islamic University Malaysia Department of Computer Science and Information Systems Najran University College of Engineering and Islamic Architecture Umm Al Qura University

ISBN: (纸本)9781509004256

Customer service improvement is directly related with organizational standards and productivity. Employees activities have certain objectives to be followed but sometimes outcomes are different than expected. Human error while performing regular job activities cause sufficient losses and difficult to address. Management faces real challenges while dealing with employee related issues and sometimes becomes unproductive. We propose Brahms Model with multi layered alert filtration and feedback cycle which would address the human error in the system and generate the filtered alerts in the form of sms or by emails. This is especially useful for Human-computer Interfacing (HCI) Scenarios. Controlling human error and addressing real issues may protect any institution from severe damage and losses. Efficiency of a customer service department can be improved and maximized by multi-layered alert filtration system using Brahms Model.

关键词： Brahms Model Customer Service Improvement Context Aware Applications Alert Generation and Filtration Organizational behaviour Human computer Interfacing

来源：评论

学校读者我要写书评

暂无评论

Neural estimation of scatterer density in ultrasound

Neural estimation of scatterer density in ultrasound

引用

International Joint Conference on Neural Networks (IJCNN)

作者： R. Smolikova M.P. Wachowiak G.D. Tourassi J.M. Zurada Institute for Research and Applications of Fuzzy Modeling University of Ostrava Ostrava Czech Republic Computer Science and Engineering Program University of Louisville Louisville KY USA Department of Radiology Duke University Medical Center Durham NC USA Department of Electrical and Computer Engineering University of Louisville Louisville KY USA

Ultrasonic backscatter can provide information on the density of scatterers within biological media, and is therefore an important tool in tissue characterization. In this paper, a novel neural network approach to estimate scatterer density from generalized entropy is proposed. Neural estimation compares favorably with nonlinear least-squares models.

关键词： Ultrasonic imaging Rayleigh scattering Acoustic scattering Entropy Backscatter Signal to noise ratio Biomedical engineering Biomedical imaging Biological system modeling Ultrasonic transducers

来源：评论

学校读者我要写书评

暂无评论

Enhanced data-driven Damage Detection for Structural Health Monitoring Systems

Enhanced data-driven Damage Detection for Structural Health ...

引用

International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)

作者： Marwa Chaabane Ahmed Ben Hamida Majdi Mansouri Hazem Nounou Mohamed Nounou University of Sfax National School of Engineers of Sfax Advanced Technologies for Medicine and Signals LR17ES10 Sfax Tunisia Electrical and Computer Engineering Program Texas A&M University at Qatar Doha Qatar Chemical Engineering Program Texas A&M University at Qatar Doha Qatar

ISBN: (数字)9781728175133

ISBN: (纸本)9781728175140

In structural engineering, it is essential to monitor the operation condition of an aging structure. Thus, damage detection is widely used for structure monitoring. The aim of this work is to propose an adaptive kernel PLS based GLRT chart to improve the detection of damage in civil structural systems. The proposed technique aims to integrate the advantages of the adaptive nonlinear input-output model (kernel PLS) with those of GLRT chart. This technique will be tested using a simulated benchmark structure through the surveillance model variables. The technique based on adaptive representation is found to be more effective over the conventional technique.

关键词： Kernel Monitoring Adaptation models Principal component analysis Data models Aerospace electronics Computational modeling

来源：评论

学校读者我要写书评

暂无评论

Dividing and Conquering a BlackBox to a Mixture of Interpretable Models: Route, Interpret, Repeat

arXiv

引用

arXiv 2023年

作者： Ghosh, Shantanu Yu, Ke Arabshahi, Forough Batmanghelich, Kayhan Department of Electrical and Computer Engineering Boston University MA United States Intelligent Systems Program University of Pittsburgh PA United States MetaAI MenloParkCA United States

ML model design either starts with an interpretable model or a Blackbox and explains it post hoc. Blackbox models are flexible but difficult to explain, while interpretable models are inherently explainable. Yet, interpretable models require extensive ML knowledge and tend to be less flexible and underperforming than their Blackbox variants. This paper aims to blur the distinction between a post hoc explanation of a Blackbox and constructing interpretable models. Beginning with a Blackbox, we iteratively carve out a mixture of interpretable experts (MoIE) and a residual network. Each interpretable model specializes in a subset of samples and explains them using First Order Logic (FOL), providing basic reasoning on concepts from the Blackbox. We route the remaining samples through a flexible residual. We repeat the method on the residual network until all the interpretable models explain the desired proportion of data. Our extensive experiments show that our route, interpret, and repeat approach (1) identifies a diverse set of instance-specific concepts with high concept completeness via MoIE without compromising in performance, (2) identifies the relatively "harder" samples to explain via residuals, (3) outperforms the interpretable by-design models by significant margins during test-time interventions, and (4) fixes the shortcut learned by the original Blackbox. The code for MoIE is publicly available at: https://***/batmanlab/ ICML-2023-Route-interpret-repeat. © 2023, CC BY.

关键词： Iterative methods

来源：评论

学校读者我要写书评

暂无评论

Recent Advances in Detection of Ochratoxin-A

引用

Open Journal of Applied Biosensor 2013年第1期2卷 1-11页

作者： Ajeet Kaushik Sunil K. Arya Abhay Vasudev Shekhar Bhansali Bioelectronics Program Institute of Microelectronics A*STAR (Agency for Science Technology and Research) 11 Science Park Road Singapore Science Park II Singapore 117685 Singapore Bio-MEMS and Microsystems Lab Department of Electrical and Computer Engineering Florida International University Miami USA Bio-MEMS and Microsystems Lab Department of Electrical and Computer EngineeringFlorida International University Miami USA Department of Biomedical Engineering Florida International University Miami USA

Ochratoxin-A[7-(L-β-phenylalanylcarbonyl)-carboxyl-5-chloro-8-hydroxy-3,4-dihydro-3R-methyl-isocumarin, OTA] is a common food contaminant mycotoxin that enters the human body through the consumption of improperly stored food products. Upon ingestion, it leads to immuno-suppression and immuno-toxicity. OTA has been known to produce nephrotoxic, teratogenic, and carcinogenic activity (via oxidative DNA damage) in several species. This review introduces potentials of electrochemical biosensor to provide breakthroughs in OTA detection through improved selectivity and sensitivity and also the current approaches for detecting OTA in food products.

关键词： Biopolymer Mycotoxins Ochratoxin-A Chitosan Organic-Inorganic Hybrid Nanocomposite Biosensors

来源：评论

学校读者我要写书评

暂无评论

Deep Learning Model for Classifying Public Opinions on Energy Sector IHSG Stocks on the Twitter Social Media Platform

Deep Learning Model for Classifying Public Opinions on Energ...

引用

Artificial Intelligence Robotics, Signal and Image Processing (AIRoSIP), International Conference on

作者： Bambang Sulistio Yaya Heryadi Lukas Wayan Suparta Ilvico Sonata Computer Science Department Binus Graduate Program – Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Cognitive Engineering Research Group Universitas Katolik Indonesia Atma Jaya Jakarta Indonesia Department of Electrical Engineering Faculty of Industrial Technology Institut Teknologi Nasional Yogyakarta Yogyakarta Indonesia

ISBN: (数字)9798350327472

ISBN: (纸本)9798350327489

Capital market transactions provide an opportunity for investors to acquire ownership of company shares and capital gains, as well as dividends. However, alongside the benefits, there are risks of capital loss and liquidation, leading to stress and depression due to profit targets and decision-making errors. To mitigate the risk of decision-making errors in investment, data analysis is needed, including sentiment analysis, which influences stock prices. This study aims to develop a new deep learning model to classify Indonesian public opinion on JCI stocks, especially the Energy sector, obtained from the Twitter social media platform. The model will perform sentiment analysis and categorize opinions as negative, neutral, or positive. We created a dataset that was trained using Bidirectional Encoder Representations from Transformers (BERT) to summarize the analysis of public sentiment above so that it can assist investors in studying public sentiment as a reference for investing with a yield precision of 76%, Recall of 77%, and F1-score on 76%.

关键词： Deep learning Sentiment analysis Analytical models Social networking (online) Blogs Decision making Text categorization Bidirectional control Transformers Encoding

来源：评论

学校读者我要写书评

暂无评论

Intrinsic synaptic plasticity of ferroelectric field effect transistors for online learning

arXiv

引用

arXiv 2021年

作者： Saha, Arnob Nafiul Islam, A.N.M. Zhao, Zijian Deng, Shan Ni, Kai Sengupta, Abhronil School of Electrical Engineering & Computer Science Pennsylvania State University University ParkPA16802 United States Microsystems Engineering Ph.D. program Rochester Institute of Technology RochesterNY14623 United States

Nanoelectronic devices emulating neuro-synaptic functionalities through their intrinsic physics at low operating energies is imperative toward the realization of brain-like neuromorphic computers. In this work, we leverage the non-linear voltage dependent partial polarization switching of a ferroelectric field effect transistor to mimic plasticity characteristics of biological synapses. We provide experimental measurements of the synaptic characteristics for a 28nm high-k metal gate technology based device and develop an experimentally calibrated device model for large-scale system performance prediction. Decoupled read-write paths, ultra-low programming energies and the possibility of arranging such devices in a cross-point architecture demonstrate the synaptic efficacy of the device. Our hardware-algorithm co-design analysis reveals that the intrinsic plasticity of the ferroelectric devices has potential to enable unsupervised local learning in edge devices with limited training data. Copyright © 2021, The Authors. All rights reserved.

关键词： E-learning

来源：评论

学校读者我要写书评

暂无评论

Manhattan Nonnegative matrix factorization using the alternating direction method of multipliers

Manhattan Nonnegative matrix factorization using the alterna...

引用

International Workshop on Advanced Computational Intelligence (IWACI)

作者： Chan Cao Shuyu Tang Nian Zhang Xiangguang Dai Wei Zhang Yuming Feng Jiang Xiong Jinkui Liu Lara Thompson Chongqing Three Gorges University Wanzhou China Department of Electrical and Computer Engineering University of the District of Columbia Washington D.C. USA Department of Mechanical Engineering Biomedical Engineering Program University of the District of Columbia Washington D.C. USA

Nonnegative matrix factorization (NMF) was a classic model for dimensional reduction. Manhattan NMF is a variant version of NMF that uses a L 1 -norm cost function as the objective function instead of the L 2 -norm cost function. Manhattan NMF can be formulated as a nonconvex nonsmooth optimization problem. An algorithm framework for solving the Manhattan NMF problem based on the alternating direction method of multiplication is presented to us. Compared with the existed algorithm, our proposed algorithm is more effective by experiments on synthetic and real data sets.

关键词：

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：