检索结果-内蒙古大学图书馆

3rd International Conference on Integrated Circuits and Communication Systems, ICICACS 2025

作者： Tamilselvan, K. Senthil, T. Buvaneswari, B. Santhiya, S. Soni, Mukesh Avs Engineering College Department of Information Technology Salem India Sreenivasa Institute of Technology and Management Studies Department of Computer Science and Engineering chittoor India Panimalar Engineering College Department of Information Technology Chennai India Excel Engineering College Department of Computer Science and Engineering Namakkal India Lovely Professional University Department of Division of Research and Development Phagwara India

ISBN: (纸本)9798331508456

Reducing the availability of spectrum, as well as the nature of allocating channels in the present wireless telecommunication networks, is one of the critical issues facing modern wireless technology. Such spectrum sensing methods may not be highly flexible or efficient in environments where the radio spectrum undergoes frequent changes. This work proposes an improved deep learning spectrum sensing model based on CNN with reinforcement learning. The proposed system design calls for a pioneering dual mechanism, incorporating both spectrum analysis and a resource allocation learning model. The framework achieved remarkable performance metrics: 96 The spectrum sensing method achieved a 3% occurrence rate, a 94.8% precision rate for resource allocation, and a 92.7% efficiency in dynamic spectrum use. In the present investigation, we have employed it for different topologies and got 45% improvement in spectrum efficiency and 87% less interference than the conventional techniques. The work challenges deep learning-based spectrum sensing as well as management and indicates that they are prepared for the following generation of the wireless communication network. © 2025 IEEE.

关键词： Cognitive radio

来源：评论

学校读者我要写书评

暂无评论

Optimal Stopping Theory Based Online Node Selection in IoT Networks for Multi-Parameter Federated Learning

IEEE Transactions on Machine Learning in Communications and ...

引用

IEEE Transactions on Machine Learning in Communications and Networking 2025年 3卷 659-676页

作者： Dogan-Tusha, Seda Bouanani, Faissal El Qaraqe, Marwa Hamad Bin Khalifa University Qatar Foundation Division of Information and Computing Technology College of Science and Engineering Doha Qatar Mohammed V University Department of Computer Science Rabat10000 Morocco

Federated Learning (FL) has attracted the interest of researchers since it hinders inefficient resource utilization by developing a global learning model based on local model parameters (LMP). This study introduces a novel optimal stopping theory (OST) based online node selection scheme for low complex and multi-parameter FL procedure in IoT networks. Global model accuracy (GMA) in FL depends on the accuracy of the LMP received by the central entity (CE). It is therefore essential to choose trusty nodes to guarantee a certain level of global model accuracy without inducing additional system complexity. For this reason, the proposed technique in this study utilizes the secretary problem (SP) approach as an OST to perform node selection considering both received signal strength (RSS) and local model accuracy (LMA) of available nodes. By leveraging the SP, the proposed technique employs a stopping rule that maximizes the probability of selecting the node with the best quality, and thereby avoids testing all candidate nodes. To this end, this work provides a mathematical framework for maximizing the selection probability of the best node amongst candidate nodes. Specifically, the developed framework has been used to calculate the weighting coefficients of the RSS and LMA to define the node quality. Comprehensive analysis and simulation results illustrate that the OST based proposed technique outperforms state-of-the-art methods including the random node selection and the offline node selection (exhaustive search methods) in terms of GMA and computational complexity, respectively. © 2023 CCBY.

关键词： Federated learning

来源：评论

学校读者我要写书评

暂无评论

A Secure Method for Data Storage and Transmission in Sustainable Cloud Computing

引用

computers, Materials & Continua 2023年第5期75卷 2741-2757页

作者： Muhammad Usman Sana Zhanli Li Tayybah Kiren Hannan Bin Liaqat Shahid Naseem Atif Saeed College of Computer Science and Technology Xi’an University of Science and TechnologyXi’anShaanxi710054China Department of Computer Science(RCET Campus) University of Engineering and TechnologyLahore39161Pakistan Department of Information Sciences Division of Science&TechnologyUniversity of EducationLahore54700Pakistan Department of Computer Science COMSATS UniversityIslamabadLahore54700Pakistan

Cloud computing is a technology that provides secure storage space for the customer’s massive data and gives them the facility to retrieve and transmit their data efficiently through a secure network in which encryption and decryption algorithms are being *** cloud computation,data processing,storage,and transmission can be done through laptops andmobile *** Storing in cloud facilities is expanding each day and data is the most significant asset of *** important concern with the transmission of information to the cloud is security because there is no perceivability of the client’s *** have to be dependent on cloud service providers for assurance of the platform’s *** security and privacy issues reduce the progression of cloud computing and add ***;most of the data that is stored on cloud servers is in the form of images and photographs,which is a very confidential form of data that requires secured *** this research work,a public key cryptosystem is being implemented to store,retrieve and transmit information in cloud computation through a modified Rivest-Shamir-Adleman(RSA)algorithm for the encryption and decryption of *** implementation of a modified RSA algorithm results guaranteed the security of data in the cloud *** enhance the user data security level,a neural network is used for user authentication and ***;the proposed technique develops the performance of detection as a loss function of the bounding *** Faster Region-Based Convolutional Neural Network(Faster R-CNN)gets trained on images to identify authorized users with an accuracy of 99.9%on training.

关键词： Cloud computing data security RSA algorithm Faster R-CNN

来源：评论

学校读者我要写书评

暂无评论

Recurring Multi-layer Moving Window Approach to Forecast Day-ahead and Week-ahead Load Demand Considering Weather Conditions

引用

Journal of Modern Power Systems and Clean Energy 2022年第6期10卷 1552-1562页

作者： Dao H.Vu Kashem M.Muttaqi Ashish P.Agalgaonkar Arian Zahedmanesh Abdesselam Bouzerdoum School of Electrical Computer and Telecommunications EngineeringUniversity of WollongongWollongongAustralia Information and Computing Technology Division College of Science and EngineeringHamad Bin Khalifa UniversityDohaQatar IEEE

The incorporation of weather variables is crucial in developing an effective demand forecasting model because electricity demand is strongly influenced by weather *** dependence of demand on weather conditions may change with time during a ***,the time stamped weather information is *** this paper,a multi-layer moving window approach is proposed to incorporate the significant weather variables,which are selected using Pearson and Spearman correlation *** multi-layer moving window approach allows the layers to adjust their size to accommodate the weather variables based on their significance,which creates more flexibility and adaptability thereby improving the overall performance of the proposed ***,a recursive model is developed to forecast the demand in multi-step *** electricity demand data for the state of New South Wales,Australia are acquired from the Australian Energy Market Operator and the associated results are reported in the *** results show that the proposed approach with dynamic incorporation of weather variables is promising for day-ahead and week-ahead load demand forecasting.

关键词： Autoregressive(AR)model load forecasting multi-layer moving window Pearson correlation Spearman correlation

来源：评论

学校读者我要写书评

暂无评论

Comparison of Dynamic DES with Existing Symmetric Key Algorithms 9

Comparison of Dynamic DES with Existing Symmetric Key Algori...

引用

9th International Conference on Smart Computing and Communications, ICSCC 2023

作者： Sunny, Leya Elizabeth Paul, Varghese Soe Cochin University of Science and Technology Division of Information Technology Kochi India Rajagiri School of Engineering and Technology Department of Computer Science and Engineering Kochi India

ISBN: (纸本)9798350314090

The concept of security is fundamental to networking. The basic objective of security is to defend against various types of assaults on these networks that hold sensitive data. By altering criteria such as key size, altering the number of iterations and ultimately using confusion box as the S-box, the security of cryptographic algorithms can be increased. Data exists in different forms such as text, images, audio and video. In DES, S-boxes are used to increase the security of the data. All of these 8 S-boxes have 64 elements. Unique numbers in the 0-15 range can be found in each row. These S- boxes are generated dynamically by our suggested system depending on the key and no storage of these elements are required. The comparison of Dynamic DES with other symmetric algorithms like DES, AES and Blowfish yields better results for Dynamic DES in terms of Balance, Bit difference, Time and Memory needed for Execution. © 2023 IEEE.

关键词： Cryptography

来源：评论

学校读者我要写书评

暂无评论

Breast Cancer Detection using Domain-Adversarial Training (DANN) with Invariant Risk Minimization (IRM) Hybrid Approach 3

Breast Cancer Detection using Domain-Adversarial Training (D...

引用

3rd International Conference on Electronics and Renewable Systems, ICEARS 2025

作者： Akash, K.V. Daniel, Esther Seetha, S. Durga, S. Karunya Institute of Technology and Sciences Division of Computer Science and Engineering Coimbatore India Cmr Institute of Technology Department of Information Science & Engineering India Amrita Vishwa Vidyapeetham Tifac Core in Cyber Security Amrita School of Engineering India

ISBN: (纸本)9798331509675

The breast cancer detection performs a key function in the health care network. The precise and early detection of cancer in the breast could aid to save life of the sufferer. The traditional machine learning methods struggle due to the data used to train is different from data used later this is known as Domain shifts. This project uses a hybrid model known as Domain-Adversarial Training of Neural Networks (DANN) with Invariant Risk Minimization (IRM) Hybrid Method to identification of the tumor in the breast. Through integrating the (DANN) and IRM works perfectly among the various type of data and also with the various image from the various sources. This model is more precise and reliable than any other older *** that this model act as an effective tool for detecting the breast cancer in the early stages. © 2025 IEEE.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

DMSS:An Attention-Based Deep Learning Model for High-Quality Mass Spectrometry Prediction

引用

Big Data Mining and Analytics 2024年第3期7卷 577-589页

作者： Yihui Ren Yu Wang Wenkai Han Yikang Huang Xiaoyang Hou Chunming Zhang Dongbo Bu Xin Gao Shiwei Sun Key Lab of Intelligent Information Processing Institute of Computing TechnologyChinese Academy of SciencesBeijing 100190Chinaand with University of Chinese Academy of SciencesBeijing 100049China Syneron Technology Guangzhou 510000China College of Information and Electrical Engineering China Agricultural UniversityBeijing 100083China Computer Science Program ComputerElectrical and Mathematical Sciences and Engineering DivisionKing Abdullah University of Science and Technology(KAUST)Thuwal 23955-6900Kingdom of Saudi Arabia Insitute of Computing Technology Chinese Academy of SciencesBeijing 100190China with Western Institute of Computing Technology Chongqing 400000China

Accurate prediction of peptide spectra is crucial for improving the efficiency and reliability of proteomic analysis,as well as for gaining insight into various biological *** this study,we introduce Deep MS Simulator(DMSS),a novel attention-based model tailored for forecasting theoretical spectra in mass *** has undergone rigorous validation through a series of experiments,consistently demonstrating superior performance compared to current methods in forecasting theoretical *** superior ability of DMSS to distinguish extremely similar peptides highlights the potential application of incorporating our predicted intensity information into mass spectrometry search engines to enhance the accuracy of protein *** findings contribute to the advancement of proteomics analysis and highlight the potential of the DMSS as a valuable tool in the field.

关键词： mass spectrometry proteomics machine learning deep learning

来源：评论

学校读者我要写书评

暂无评论

A hybrid channel transmission method for effective spectrum access in cognitive radio networks

引用

International Journal of Ad Hoc and Ubiquitous Computing 2023年第4期44卷 221-232页

作者： Dhurandher, Sanjay Kumar Kumar, Bhoopendra Woungang, Isaac Chao, Han-Chieh Department of Information Technology Netaji Subhas University of Technology New Delhi India National Institute of Electronics and Information Technology Delhi Centre New Delhi India CAITFS Division of Information Technology Netaji Subhas Institute of Technology University of Delhi Delhi India KIET Group of Institutions Delhi-NCR Ghaziabad India Department of Computer Science Ryerson University TorontoON Canada Department of Electrical Engineering National Dong Hwa University Hualien Taiwan Department of Computer Science and Information Engineering National Ilan University I-Lan Taiwan Institute of Computer Science and Innovation UCSI University Kuala Lumpur Malaysia

Cognitive radio is considered as a very influencing technique and has the great potential to solve the problem of shortage of the radio spectrum. A secondary user also called as a cognitive user may access the primary channel(s) with a certain restrictions in a cognitive radio network. Spectrum sensing is a very important activity during the process of spectrum access. This paper proposes a Markov chain-based proactive hybrid spectrum access method for maximising the radio spectrum usage by optimising the channel sensing process and establishing the channel switching conditions. Using the OMNeT++ simulator, the proposed method (proactive hybrid access) is compared against that of the conventional (reactive hybrid access), overlay, and underlay access methods, showing its superiority by about 20% in terms of performance improvement with respect to throughput, service delay, and PU detection probability. Copyright © 2023 Inderscience Enterprises Ltd.

关键词： Cognitive radio

来源：评论

学校读者我要写书评

暂无评论

Shared Memory Model over a Switchless PCIe NTB Interconnect Network

引用

Journal of information Processing Systems 2022年第1期18卷 159-172页

作者： Lim, Seung-Ho Cha, Kwangho Division of Computer Engineering Hankuk University of Foreign Studies Yongin Korea Republic of Division of Supercomputing Korea Institute of Science and Technology Information Daejeon Korea Republic of

The role of the interconnect network, which connects computing nodes to each other, is important in highperformance computing (HPC) systems. In recent years, the peripheral component interconnect express (PCIe) has become a promising interface as an interconnection network for high-performance and cost-effective HPC systems having the features of non-transparent bridge (NTB) technologies. OpenSHMEM is a programming model for distributed shared memory that supports a partitioned global address space (PGAS). Currently, little work has been done to develop the OpenSHMEM library for PCIe-interconnected HPC systems. This paper introduces a prototype implementation of the OpenSHMEM library through a switchless interconnect network using PCIe NTB to provide a PGAS programming model. In particular, multi-interrupt, multi-thread-based data transfer over the OpenSHMEM shared memory model is applied at the implementation level to reduce the latency and increase the throughput of the switchless ring network system. The implemented OpenSHMEM programming model over the PCIe NTB switchless interconnection network provides a feasible, cost-effective HPC system with a PGAS programming model. © 2022. KIPS

关键词： Data transfer

来源：评论

学校读者我要写书评

暂无评论

An Insight Survey on Sensor Errors and Fault Detection Techniques in Smart Spaces

引用

computer Modeling in engineering & Sciences 2024年第3期138卷 2029-2059页

作者： Sheetal Sharma Kamali Gupta DeepaliGupta Shalli Rani Gaurav Dhiman Chitkara University Institute of Engineering and Technology Chitkara UniversityPunjab140401India PG Department of Information Technology Goswami Ganesh Dutta Sanatan Dharma CollegeChandigarh160030India Department of Computer Science Government Bikram College of CommercePatialaIndia Department of Electrical and Computer Engineering Lebanese American UniversityByblosLebanon University Centre for Research and Development Department of Computer Science and EngineeringChandigarh UniversityMohali140413India Department of Computer Science and Engineering Graphic Era Deemed to be UniversityDehradun248002India Division of Research and Development Lovely Professional UniversityPunjab144001India

The widespread adoption of the Internet of Things (IoT) has transformed various sectors globally, making themmore intelligent and connected. However, this advancement comes with challenges related to the effectiveness ofIoT devices. These devices, present in offices, homes, industries, and more, need constant monitoring to ensuretheir proper functionality. The success of smart systems relies on their seamless operation and ability to handlefaults. Sensors, crucial components of these systems, gather data and contribute to their functionality. Therefore,sensor faults can compromise the system’s reliability and undermine the trustworthiness of smart *** address these concerns, various techniques and algorithms can be employed to enhance the performance ofIoT devices through effective fault detection. This paper conducted a thorough review of the existing literature andconducted a detailed *** analysis effectively links sensor errors with a prominent fault detection techniquecapable of addressing them. This study is innovative because it paves theway for future researchers to explore errorsthat have not yet been tackled by existing fault detection methods. Significant, the paper, also highlights essentialfactors for selecting and adopting fault detection techniques, as well as the characteristics of datasets and theircorresponding recommended techniques. Additionally, the paper presents amethodical overview of fault detectiontechniques employed in smart devices, including themetrics used for evaluation. Furthermore, the paper examinesthe body of academic work related to sensor faults and fault detection techniques within the domain. This reflectsthe growing inclination and scholarly attention of researchers and academicians toward strategies for fault detectionwithin the realm of the Internet of Things.

关键词： Error fault detection techniques sensor faults outliers 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：