检索结果-内蒙古大学图书馆

International Conference on Advancements in Computational Sciences (ICACS)

作者： Ummama Aslam Arslan Shaukat Basim Azam Dept. of Computer and Software Engineering College of Electrical and Mechanical Engineering (CEME) National University of Sciences and Technology (NUST) Islamabad Pakistan Institute of Integrated and Intelligent Systems Griffith University Brisbane Australia

Image deblurring techniques that uses deep learning have shown great potential but due to low generalizability, noise immunity and the correlation among different pixels is not addressed in detail that results in unwanted artifact that appears in the deblurred image. To tackle this problem an end-to-end approach is proposed for the recovery of sharp image from blurred one without the estimation of blur kernel. A special type of attention module known as crosshatch attention is used after Residual Block of Generator model for removing noise and for the collection of correlation of different pixels in an image. Hybrid Loss function is defined which focus on different part of image and improve edges and texture details. The performance of the model for deblurring is measured on GoPro dataset. Our proposed model has slightly higher objective and subjective evaluation i-e PSNR, SSIM value and the visual results.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Neural Network-based System Identification Model to Predict Output Current and Voltage of Solar Photovoltaic Panels

A Neural Network-based System Identification Model to Predic...

引用

Science, Engineering and Business for Sustainable Development Goals (SEB-SDG), International Conference on

作者： Emmanuel Adetiba Olumide O. Oluleye Ayodele H. Ifijeh Victoria Oguntosin Olatayo M. Olaniyan Olubunmi Adewale Akinola Gbenga Afolabi Jacob O. Odetola. Abdultaofeek Abayomi Dept. of Electrical & Information Engineering Covenant University Ota Ogun State Nigeria HRA Institute for -Systems Science Durban University of Technology Durban South Africa Dept. of Computer Engineering Federal University Oye-Ekiti Ekiti State Nigereia Dept. of Information and Communication Technology Mangosuthu University of Technology Durban South Africa

Solar irradiance is the energy per unit area received by the Sun as electromagnetic radiation. It is one of the most important renewable energy sources. Photovoltaic or other solar technologies are used to generate power more accurately than direct sun irradiation. Solar irradiance research and measurement have a variety of critical applications, including forecasting power generation from solar power plants, climate modeling, and weather forecasting. This paper presents a neural network-based system identification model developed using measured parameters from solar panels with various wattage specifications, namely, 10W, 20W, 40W, and 100W. The parameters that were measured to train the ANN model for the prediction of the output current and voltage include the angle of panel orientation, panel temperature, ambient temperature, irradiance, and wattage. Several training experiments were conducted and the best ANN model produced at 500 epochs gave an accuracy of 99.81% and a loss of 0.1940. The model was deployed into an intelligent Web App that was also developed in this study. This app could be a potential tool for renewable energy engineers and researchers.

关键词： Temperature measurement Renewable energy sources Voltage measurement Current measurement Weather forecasting Solar energy Predictive models

来源：评论

学校读者我要写书评

暂无评论

Token Based Energy-efficient Offloading Schemes for IoV Networks

Token Based Energy-efficient Offloading Schemes for IoV Netw...

引用

IEEE Annual International computer Software and Applications Conference (COMPSAC)

作者： Pranshu Srivastava Kaustubh Ijardar Anuj Joshi Nikumani Choudhury Anakhi Hazarika Dept. of Computer Science and Information Systems Birla Institute of Technology &#x0026 Science Pilani Hyderabad India Dept. of ECE Indian Institute of Information Technology Guwahati India

ISBN: (数字)9781665488105

ISBN: (纸本)9781665488112

The emergence of applications in vehicles requires computational capability which poses a major challenge in mo-bile edge computing. In this paper, we have proposed the token-based predictive offloading scheme with the aim of providing the optimal cost of offloading and reducing the average delay. Specifically, the proposed scheme uses a token-based approach for offloading the data from vehicles to MEC(Mobile Edge Computing) server. We have designed a separate table for MEC servers to show the status of consumed tokens and available tokens and another table for vehicles to store the status for another vehicle for vehicle to vehicle (V 2 V) communication. Dedicated Short Range Service (DSRC) technology is used to facilitate the communication between vehicle to vehicle and vehicle to infrastructure(*** gate). Extensive simulations are conducted in highway scenarios and the results demonstrate the superiority of this offloading scheme. The proposed scheme achieves low delay performance and decreased computation cost over other competing schemes in typical urban and highway scenarios.

关键词： Road transportation Costs Logic gates Software Delays Internet Servers

来源：评论

学校读者我要写书评

暂无评论

Foreword to the 6th International Workshop on Engineering and Cybersecurity of Critical systems (EnCyCriS)

Foreword to the 6th International Workshop on Engineering an...

引用

Engineering and Cybersecurity of Critical systems (EnCyCriS), IEEE/ACM International Workshop on

作者： Coralie Esnoul Eunkyoung Jee John Eidar Simensen Ita Ryan Mary Sánchez-Gordón Nathan Lau Risk and Safety Department Institute for Energy Technology Halden Norway School of Computing Korea Advanced Institute of Science and Technology Daejeon Republic of Korea University College Cork Cork Ireland Dept. of Computer Science and Communication Østfold University College Halden Norway Dept. of Industrial and Systems Engineering Virginia Tech Virginia USA

ISBN: (数字)9798331538101

ISBN: (纸本)9798331538118

This marks the 6th edition of the International Workshop on Engineering and Cybersecurity of Critical systems (EnCyCriS) at the ICSE conference. For industrial critical systems, although the previous premises of increasing system interconnectivity, decentralization, and introduction of new, more intelligent technologies still hold true, there is an increased societal awareness with regards to cybersecurity. This has led to clearer regulation, sharper requirements, and higher expectations for industry. At the same time, the availability of readily deployable competence, methods, tools, and solutions is lacking, which should be considered a critical societal risk. In the current international political climate, cyber security, and safety of critical infrastructures across industry, are more important than ever before. The EnCyCriS workshop facilitates discourse and discussion amongst researchers, practitioners, and students who are working on challenges and solutions related to industrial critical infrastructure. It has a particular focus on sharing industry experience and project results pertaining to cyber threats on critical systems, secure systems engineering, and attack detection and response mechanisms.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Dynamic Optimizations in GPU Using Roofline Model

Dynamic Optimizations in GPU Using Roofline Model

引用

IEEE International Symposium on Circuits and systems

作者： Winnie Thomas Suryakant Toraskar Virendra Singh Computer Architecture and Dependable Systems Laboratory Dept. of Electrical Engineering Indian Institute of Technology Bombay India

ISBN: (纸本)9781728192017;9781728192024

Massively parallel processors such as graphics processing units (GPUs) often face the challenge of resource underutilization due to varying resource proclivity of workloads. Running multiple applications on a GPU has been an efficient and known alternative to mitigate underutilization. This paper proposes a multi-application oriented framework that carries out dynamic optimizations based on the operational intensities of various applications. Our framework analyzes applications based on operational intensities to identify their bottleneck resources using Roofline model. We demonstrate that the proposed optimizations improve the utilization and system-wide throughput of the GPU co-running applications with irregular resource demands. The dynamic optimizations improve the performance by 14.8% on average and up to 72.4% over a state-of-the-art spatial multitasking technique.

关键词： Heuristic algorithms Graphics processing units Throughput Multitasking Resource management Optimization Faces

来源：评论

学校读者我要写书评

暂无评论

A Demonstrative Study on Prediction of Disease Using Bayesian Machine Learning Techniques

A Demonstrative Study on Prediction of Disease Using Bayesia...

引用

IEEE International Conference on System, Computation, Automation and Networking (ICSCAN)

作者： R. Dhanalakshmi N. Vijayaraghavan S. Narasimhan R Rajesh Centre for Cyber Physical Systems School. of Computer Science and Engineering Vellore Institute of Technology Chennai India Dept. of Mathematics KCG College of Technology Chennai India School. of Computer Science and Engineering Vellore Institute of Technology Chennai India

With the rapid advancement of biological information, accurate analysis of treatment data aids in early disease detection. To uncover knowledge for medical research, advanced Machine Learning algorithms are applied. Here in this research paper, to determine if a patient is affected by any Infectious disorders, we use the Naive Bayes Algorithm method.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Teaching DevOps Security Education with Hands-on Labware: Automated Detection of Security Weakness in Python

arXiv

引用

arXiv 2023年

作者： Akter, Mst Shapna Rodriguez-Cardenas, Juanjose Rahman, Md Mostafizur Shahriar, Hossain Rahman, Akond Wu, Fan Dept. of Intelligence and Robotics Systems University of West Florida United States Dept. of Information Technology Kennesaw State University United States Dept. of Information Technology University of West Florida United States Center of Cyber Security University of West Florida United States Dept. of Computer Science and Software Engineering Auburn University Auburn United States Dept of Computer Science Tuskegee University Tuskegee United States

The field of DevOps security education necessitates innovative approaches to effectively address the ever-evolving challenges of cybersecurity. In adopting a student-centered approach, there is the need for the design and development of a comprehensive set of hands-on learning modules. In this paper, we introduce hands-on learning modules that enable learners to be familiar with identifying known security weaknesses, based on taint tracking to accurately pinpoint vulnerable code. To cultivate an engaging and motivating learning environment, our hands-on approach includes a pre-lab, hands-on and post lab sections. They all provide introduction to specific DevOps topics and software security problems at hand, followed by practicing with real world code examples having security issues to detect them using tools. The initial evaluation results from a number of courses across multiple schools show that the hands-on modules are enhancing the interests among students on software security and cybersecurity, while preparing them to address DevOps security vulnerabilities. © 2023, CC BY.

关键词： computer aided instruction

来源：评论

学校读者我要写书评

暂无评论

Enhancing Facial Recognition in Visual Prostheses using Region of Interest Magnification and Caricaturing

Enhancing Facial Recognition in Visual Prostheses using Regi...

引用

International Conference on computer and Applications (ICCA)

作者： Hesham M. Moneer Reham H. Elnabawy Seif Eldawlatly Digital Media Eng. and Technology Dept. German University in Cairo Cairo Egypt Computer and Systems Eng. Dept. Ain Shams University Cairo Egypt Computer Science and Eng. Depr. The American University in Cairo Cairo Egypt

Blindness is a prevalent disability with significant personal and societal consequences. While medical advancements offer treatment options, severe damage to the retina, optic nerve, or brain may remain untreated. Visual prostheses are implantable medical devices that aim at providing limited vision to such individuals. However, such prostheses offer low spatial resolution making activities like reading, facial recognition, and navigation challenging. This work aims to enhance implantees’ ability to recognize faces through real-time scene preprocessing, machine learning and computer vision techniques. Virtual-reality visual models simulating prosthetic vision were tested on normally/corrected sighted subjects, investigating the use of histogram equalization for contrast enhancement, facial region magnification, and caricaturing of facial features. Results revealed that histogram equalization with magnification increases facial recognition accuracy by 60%, distinguishability accuracy by 50%, and accuracy of seeing facial details by 90%. In contrast, adding facial caricaturing improved the accuracies by 66.66%, 25%, and 75% for recognizability, distinguishability, and seeing facial details, respectively. Consequently, the combination of visual field histogram equalization, face magnification, and optional caricaturing can be considered as a promising enhancement approach that could enhance the quality of vision perceived through visual prostheses.

关键词：

来源：评论

学校读者我要写书评

暂无评论

POCS-based Image Compression: An Empirical Examination

POCS-based Image Compression: An Empirical Examination

引用

International Conference on Green technology and Sustainable Development (GTSD)

作者： Truong-Dong Do Le-Anh Tran Thanh-Dat Nguyen Nghe-Nhan Truong Dong-Chul Park My-Ha Le Dept. of Aerospace Systems Engineering Sejong University Seoul South Korea Dept. of Electronics Engineering Myongji University Yongin South Korea Dept. of Research and Development OCST Co. Ltd. Seoul South Korea Dept. of Computer Science & Engineering Sejong University Seoul South Korea Dept. of Electrical & Electronics Engineering HCMC University of Technology & Education Ho Chi Minh City Vietnam

ISBN: (数字)9798350386073

ISBN: (纸本)9798350386080

This paper investigates the applicability of the Pro-jection onto Convex Set (POCS)-based clustering algorithm to image compression tasks. The POCS-based clustering approach treats all data points in a given dataset as non-intersecting convex sets and performs POCS-based parallel projections from each cluster prototype onto corresponding member data points to minimize an objective function and update cluster prototypes. The POCS-based clustering algorithm has been proven to be able to yield promising results against other prevailing clustering approaches in terms of convergence time and clustering error on general clustering tasks. In this study, a comparison of various clustering schemes for image compression applications has been conducted. The evaluations and analyses on various standard test images verify that the POCS-based clustering algorithm can perform competitively against other conventional clustering methods in image compression problems.

关键词： Image coding Clustering methods Clustering algorithms Prototypes Linear programming Sustainable development Standards

来源：评论

学校读者我要写书评

暂无评论

An Efficient GPU-based Implementation for Noise Robust Sound Source Localization

arXiv

引用

arXiv 2025年

作者： Lin, Zirui Takigahira, Masayuki Terakado, Naoya Gulzar, Haris Busto, Monikka Roslianna Eda, Takeharu Itoyama, Katsutoshi Nakadai, Kazuhiro Amano, Hideharu Dept. of Systems and Control Engineering School of Engineering Tokyo Institute of Technology Tokyo Japan Honda Research Institute Japan Co. Ltd. Saitama Japan NTT Software Innovation Center Tokyo Japan Dept. of Information and Computer Science Keio University Kanagawa Japan

Robot audition, encompassing Sound Source Localization (SSL), Sound Source Separation (SSS), and Automatic Speech Recognition (ASR), enables robots and smart devices to acquire auditory capabilities similar to human hearing. Despite their wide applicability, processing multi-channel audio signals from microphone arrays in SSL involves computationally intensive matrix operations, which can hinder efficient deployment on Central Processing Units (CPUs), particularly in embedded systems with limited CPU resources. This paper introduces a GPU-based implementation of SSL for robot audition, utilizing the Generalized Singular Value Decomposition-based Multiple Signal Classification (GSVD-MUSIC), a noise-robust algorithm, within the HARK platform, an open-source software suite. For a 60-channel microphone array, the proposed implementation achieves significant performance improvements. On the Jetson AGX Orin, an embedded device powered by an NVIDIA GPU and ARM®Cortex™-A78AE v8.2 64-bit CPUs, we observe speedups of 4645.1× for GSVD calculations and 8.8× for the SSL module, while speedups of 2223.4× for GSVD calculation and 8.95× for the entire SSL module on a server configured with an NVIDIA A100 GPU and AMD EPYC™ 7352 CPUs, making real-time processing feasible for large-scale microphone arrays and providing ample capacity for real-time processing of potential subsequent machine learning or deep learning tasks. © 2025, CC BY-NC-ND.

关键词： Acoustic generators

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：