检索结果-内蒙古大学图书馆

8th IEEE International Conference for Convergence in Technology, I2CT 2023

作者： Reddy, Ravula Tarun Basa Pati, Peeta Deepa, K. Sangeetha, S. Tresa Amrita Vishwa Vidyapeetham Amrita School of Computing Department of Computer Science and Engineering Bengaluru India Amrita Vishwa Vidyapeetham Amrita School of Engineering Department of Electrical and Electronics Engineering Bengaluru India University of Technology and Applied Sciences Department of Engineering Al Musannah Oman

ISBN: (纸本)9798350334012

The prediction of flight delay can be considered as one of the most challenging problems to solve. Delay of an aircraft is not only a problem for an airline but also for the passengers. Flights can be delayed due to several reasons, the weather being the primary one. In this paper, our focus is to predict the delay of the flights due to bad weather. The dataset used consists of flight data from JFK airport from the sources Bureau of Transportation statistics and weather data from the National Centers for Environmental Information. The results of different machine learning algorithms like Linear Regression, SVR, Decision Tree Regressor, Random Forest Regressor, Ridge, and Lasso Regressor, for prediction of flight delay, are compared. XGboost regressor had the best performance in all the scenarios with least RMSE score of 0.81. © 2023 IEEE.

关键词： Decision trees

来源：评论

学校读者我要写书评

暂无评论

Recent Advancements in Solid State Transformer-based EV Fast Charging Stations 14

Recent Advancements in Solid State Transformer-based EV Fast...

引用

14th IEEE International Conference on Power Electronics and Drive Systems, PEDS 2023

作者： De Seram, Ruvini Golder, Anindita Williamson, Sheldon S. Department of Electrical and Computer Engineering Faculty of Engineering and Applied Science Ontario Tech University OshawaONL1G 0C5 Canada

ISBN: (纸本)9798350399967

Growing deployments of ultra fast charging stations (XFCS) are putting a stress on the existing line-frequency transformer (LFT)-based medium voltage (MV) grid due to the high charging demands of exponentially growing electric vehicles (EV). The conventional LFT occupies a large space in the XFCS installation which introduces challenges in facilitating the XFCS infrastructure. As a result, solid-state transformer (SST)-based XFCS are being developed which can be directly connected to the MV grid and several advantages over LFT-based systems such as compactness, intelligence and availability of the DC link to connect renewable energy sources and storage system can be realized. As such, a detailed analysis of current developments in SST-based XFCS is presented and compared with one another in this paper. The challenges associated with the configurations are examined and direction for future research is identified. © 2023 IEEE.

关键词： Electric vehicles

来源：评论

学校读者我要写书评

暂无评论

MAXIMIZING BIG DATA FOR DATA-DRIVEN DECISION MAKING: AN IN-DEPTH ASSESSMENT

MAXIMIZING BIG DATA FOR DATA-DRIVEN DECISION MAKING: AN IN-D...

引用

2024 International Conference on Sustainable Computing and Integrated Communication in Changing Landscape of AI, ICSCAI 2024

作者： Kumar, Maneesh Kaur, Dilrajpreet Sanghi, Akash Yuvaraj, K. Mukuntharaj, C. Tamkhade, Jayashree School of Engineering and Computer Dev Bhoomi Uttarakhand University Uttarakhand 248007 India Department of Physics School of Basic & Applied Sciences K. R. Mangalam University Haryana Gurugram122103 India Department of Computer Science & Engineering Invertis University Uttar Pradesh Bareilly243123 India Department of Computer Science Karpagam Academy of Higher Education Coimbatore641021 India Department of Electronics and Communication Engineering Karpagam College of Engineering Coimbatore641032 India E&TC Vishwakarma Institute of Information Technology Pune India

ISBN: (纸本)9798350355338

In this essay, we examine the history and current condition. We begin by outlining the history of big information reviewing similar technologies including centers, and Hadoop. The four stages of the chain-data production, data capture, - are then the main emphasis. [1] We lay out the overall context, talk about the difficulties, and cover the most recent developments for each step. Finally, we look at a number of exemplary big business. These conversations are meant a thorough introduction and overall picture of this fascinating field. A discussion of unresolved issues and prospective directions follows this survey's conclusion. © 2024 IEEE.

关键词： Data centers

来源：评论

学校读者我要写书评

暂无评论

A Novel Inherited Modeling Structure of Automatic Brain Tumor Segmentation from MRI

引用

computers, Materials & Continua 2022年第11期73卷 3983-4002页

作者： Abdullah AAsiri Tariq Ali Ahmad Shaf Muhammad Aamir Muhammad Shoaib Muhammad Irfan Hassan A.Alshamrani Fawaz F.Alqahtani Osama M.Alshehri Radiological Sciences Department College of Applied Medical SciencesNajran UniversityNajran61441Saudi Arabia Department of Computer Science COMSATS University IslamabadSahiwal CampusSahiwal57000Pakistan Department of Informatics and Systems University of Management and TechnologyLahore54000Pakistan Electrical Engineering Department College of EngineeringNajran UniversityNajran61441Saudi Arabia Department of Clinical Laboratory Sciences Collage of Applied Medical ScienceNajran UniversityNajranSaudi Arabia

Brain tumor is one of the most dreadful worldwide types of cancer and affects people leading to *** resonance imaging methods capture skull images that contain healthy and affected *** checked the affected tissue in the slice-by-slice manner,which was timeconsuming and hectic ***,auto segmentation of the affected part is needed to facilitate ***,we have considered a hybrid model that inherits the convolutional neural network(CNN)properties to the support vector machine(SVM)for the auto-segmented brain tumor *** CNN model is initially used to detect brain tumors,while SVM is integrated to segment the tumor region *** proposed method was evaluated on a publicly available BraTS2020 *** statistical parameters used in this work for the mathematical measures are precision,accuracy,specificity,sensitivity,and dice ***,our method achieved an accuracy value of 0.98,which is most prominent than existing ***,the proposed approach is more suitable for medical experts to diagnose the early stages of the brain tumor.

关键词： Brain tumor support vector machine convolutional neural network BraTS classification

来源：评论

学校读者我要写书评

暂无评论

Multimedia Classification via Tensor Linear Discriminant Analysis

引用

IEEE Transactions on Broadcasting 2024年第4期70卷 1139-1152页

作者： Chang, Shih-Yu Wu, Hsiao-Chun Yan, Kun Chih-Hao Huang, Scott Wu, Yiyan San Jose State University Department Of Applied Data Science San JoseCA95192 United States Louisiana State University School Of Electrical Engineering And Computer Science Baton RougeLA70803 United States Yuan Ze University Innovation Center For Ai Applications Taoyuan32003 Taiwan Guilin University Of Electronic Technology Guangxi Key Laboratory Of Wireless Wideband Communication And Signal Processing Department Of Information And Telecommunication Guilin541004 China National Tsing Hua University Department Of Electrical Engineering Hsinchu300 Taiwan Western University Department Of Electrical And Computer Engineering LondonONN6A 3K7 Canada

Linear discriminant analysis (LDA) is a well-known feature-extraction technique for data analytic and pattern classification. As the dimensionality of multimedia data has increased in this big era, it is often to characterize data by tensors. Over the past two decades, researchers have thus explored to extend LDA to the general tensor space, especially in two common ways: LDA of tensors using tensor decomposition methods (by conversion of tensors to matrices) and LDA of tensors built upon the T-product. However, both of the aforementioned approaches have restrictions thereby. A critical problem about how to carry out LDA of arbitrary scatter tensors based on the Einstein product still remains unsolved by the existing methods. Therefore, we propose a novel tensor LDA (a.k.a. TLDA) approach, which can carry out the LDA of arbitrary-dimensional scatter-tensors without any need of tensor decomposition. Besides, for reducing the computation time, we also design a parallel paradigm to execute our proposed TLDA in this work. Numerical experiments conducted over real multimedia data demonstrate the efficacy of our proposed new TLDA in terms of classification accuracy. Moreover, the comparison of the classification accuracies, computational-complexities, and memory-complexities of our proposed novel TLDA scheme and other existing tensor-based LDA methods is made. By leveraging TLDA for high-dimensional feature extraction, segmentation, and user-item interaction data processing, future multimedia recommendation systems can facilitate more accurate, engaging, and satisfactory user experience over the Internet. © 1963-12012 IEEE.

关键词： Tensors

来源：评论

学校读者我要写书评

暂无评论

Integrated Energy-Efficient Distributed Link Stability Algorithm for UAV Networks

引用

computers, Materials & Continua 2024年第11期81卷 2357-2394页

作者： Altaf Hussain Shuaiyong Li Tariq Hussain Razaz Waheeb Attar Farman Ali Ahmed Alhomoud Babar Shah School of Computer Science and Technology Chongqing University of Posts and TelecommunicationsChongqing400065China Key Laboratory of Industrial Internet of Things and Networked Control Ministry of EducationChongqing University of Posts and TelecommunicationsChongqing400065China School of Computer Science and Information Engineering Zhejiang Gongshang UniversityHangzhou310018China Management Department College of Business AdministrationPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Applied AI School of ConvergenceCollege of Computing and InformaticsSungkyunkwan UniversitySeoul03063Republic of Korea Department of Computer Science College of ScienceNorthern Border UniversityArar91431Saudi Arabia College of Technological Innovation Zayed UniversityDubai19282United Arab Emirates

Ad hoc networks offer promising applications due to their ease of use,installation,and deployment,as they do not require a centralized control *** these networks,nodes function as senders,receivers,and *** such network is the Flying Ad hoc Network(FANET),where nodes operate in three dimensions(3D)using Unmanned Aerial Vehicles(UAVs)that are remotely *** the integration of the Internet of Things(IoT),these nodes form an IoT-enabled network called the Internet of UAVs(IoU).However,the airborne nodes in FANET consume high energy due to their payloads and low-power *** optimal routing approach for communication is essential to address the problem of energy consumption and ensure energy-efficient data transmission in *** paper proposes a novel energy-efficient routing protocol named the Integrated Energy-Efficient Distributed Link Stability Algorithm(IEE-DLSA),featuring a relay mechanism to provide optimal routing with energy efficiency in *** energy efficiency of IEE-DLSA is enhanced using the Red-Black(R-B)tree to ensure the fairness of advanced energy-efficient *** link stability,transmission loss avoidance,delay awareness with defined threshold metrics,and improving the overall performance of the proposed protocol are the core functionalities of *** simulations demonstrate that the proposed protocol performs well compared to traditional FANET routing *** evaluation metrics considered in this study include network delay,packet delivery ratio,network throughput,transmission loss,network stability,and energy consumption.

关键词： FANET UAV internet of UAVs relay mechanism energy consumption routing IEE-DLSA

来源：评论

学校读者我要写书评

暂无评论

Thermal-Aware Communication

引用

IEEE Transactions on Information Theory 2025年第6期71卷 4145-4155页

作者： Chee, Yeow Meng Etzion, Tuvi Schouhamer Immink, Kees A. Thanh Nguyen, Tuan Khu Vu, Van Weber, Jos H. Yaakobi, Eitan Singapore University of Technology and Design Tampines 119077 Singapore Technion—Israel Institute of Technology Department of Computer Science Haifa3200003 Israel National University of Singapore Department of Industrial Systems Engineering and Management Queenstown 117576 Singapore Turing Machines Inc. DK Rotterdam3016 Netherlands Science Mathematics and Technology Cluster Singapore University of Technology and Design Tampines 487372 Singapore Delft University of Technology Department of Applied Mathematics CD Delft2628 Netherlands

Temperature control is of utmost importance in transmission systems. In this paper, a binary channel model is considered in which the transmission of a one causes a temperature increase while communicating a zero causes a temperature drop. By putting constraints on the input sequences, it is guaranteed that the channel temperature will not exceed a certain pre-determined maximum. In the asymptotic regime, the capacity of such a channel is studied. For the non-asymptotic regime, fixed-length codes are presented, with the property that codewords can be freely cascaded without violating the temperature constraint. Optimization of the code size is investigated and codewords are enumerated using generating functions. © 1963-2012 IEEE.

关键词： Channel capacity

来源：评论

学校读者我要写书评

暂无评论

Physics-informed neural networks for classical and quantum communication with multimode fibers

Physics-informed neural networks for classical and quantum c...

引用

2024 Frontiers in Optics, FiO 2024

作者： Zhang, Qian Sun, Jiali Rothe, Stefan Czarske, Jürgen Faculty of Electrical and Computer Engineering TU Dresden Dresden01069 Germany Department of Applied Physics Yale University New HavenCT06520 United States Institute of Applied Physics School of Science TU Dresden Germany

Physics-informed neural networks provide mode decomposition based on intensity-only images in high-dimensional quantum communication using multimode fibers. © Optica Publishing Group 2024, © 2024 The Author(s)

关键词： Multimode fibers

来源：评论

学校读者我要写书评

暂无评论

Detection of Stage of Cancer Using Machine Learning and Deep Learning 5th

Detection of Stage of Cancer Using Machine Learning and Deep...

引用

5th International Conference on Advances in Information Communication Technology and Computing, AICTC 2024

作者： Ashtagi, Rashmi Akkalkot, Afsha Imran Kotecha, Ketan Maginmani, Umme Habiba Patil, Pushpalata Patil, Abhijeet Computer Engineering Department Vishwakarma Institute of Technology Pune India Computer Engineering Department College of Engineering Pune Technological University Pune India Symbiosis Centre for Applied Artificial Intelligence Symbiosis Institute of Technology Symbiosis International University Pune411045 India Computer Science and Engineering SECAB Institute of Engineering and Technology Affiliated to Visvesvaraya Technological University Vijayapur India Computer Science and Engineering Faculty of Engineering and Technology Exclusively for Women Sharnbasva University Kalburagi India RPD PU College of Arts and Commerce Belagavi India

ISBN: (纸本)9789819761029

Melanoma, an aggressive form of skin cancer known for its rapid spread, poses a significant threat and is responsible for a substantial number of fatalities. The accurate classification of cancer stages is crucial for effective diagnosis, particularly during surgical treatment. This paper introduces two methods for categorizing melanoma cancer stages. Initial system distinguishes between stage 1 and stage 2, while the second system extends the classification to include stage 3 melanoma. Leveraging a Convolutional Neural Network (CNN) algorithm, the proposed system incorporates the Similarity Measure for Text Processing (SMTP) as a loss function. The experimental results showcase the efficacy of different loss functions, with a particular focus on the proposed SMTP loss function, which outperforms several others designed for classification problems. This algorithm stands out as a more efficient approach for melanoma stage classification. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Detection and Replay of Distributed Denial of Service Attacks in Smart Cities Using a Hybrid Deep Learning Approach 2

Detection and Replay of Distributed Denial of Service Attack...

引用

2nd International Conference on Business Analytics for Technology and Security, ICBATS 2023

作者： Iqbal, Muhammad Waseem Issa, Ghassan F. Yousif, Muhammad Atif, Muhammad Superior University Department of Software Engineering Lahore Pakistan Skyline University College School of Information Technology Sharjah United Arab Emirates Department of Computer Science NCBAE Lahore Pakistan Applied Science Research Center Applied Science Private University Amman11937 Jordan

ISBN: (纸本)9798350335644

Infrastructure for smart cities is presently being built, mostly because of the (IoT) platform, which connects a wide variety of things by using the website's underlying infrastructure. As a result, it is possible to employ a uniform platform to automate the services that are delivered. Smart city infrastructure, on the other hand, is susceptible to cyberattacks owing to security flaws in IoT networks. Distributing denial of service (DDoS) and replay assaults, for example, violate the requirements for certification in smart cities. The lack of citations in this part backs up many of the statements it makes. Who needs a citation? Both assaults have the potential to substantially damage smart city infrastructure, which might also cost money and even result in human fatalities. This paper covers the creation of a blended deep- learning algorithm for replay and DDoS intrusion prevention on a growth-oriented smart city platform. This is made possible by combining proven machine-learning approaches with more recent advances in artificial intelligence. We simulate scattered denial of service and replay attacks on three datasets acquired from real-world smart cities to assess the efficacy of the proposed hybrid strategy on environmental, smart river, and smart soil dataset. The suggested model has shown excellent rates of accuracy. The ecosystem collection has an accuracy level of 98.37%, the smart riverbed dataset must have an accuracy of 98.13%, and the smart mud dataset must have an accuracy of 99.51%. The findings demonstrated that the proposed model outperformed past instances of evolutionary computation and machine learning techniques employed in the corpus of academic literature. © 2023 IEEE.

关键词： Internet of things

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：