检索结果-内蒙古大学图书馆

10th International Conference on Software Defined systems, SDS 2023

作者： Musa, Ahmed Halloush, Rami Salamah, Haythem Bany Awwad, Rami Bani Alnabelsi, Sharhabeel H. Benkhelifa, Elhadj Yarmouk University Department of Telecommunications Engineering Irbid Jordan Al Ain University Artificial Intelligence Research Center Al Ain United Arab Emirates Al Ain University Department of Computer Engineering Al Ain United Arab Emirates Al-Balqa Applied University Faculty of Engineering Technology Department of Computer Engineering Al-Salt19117 Jordan Staffordshire University Smart Systems AI and Cybersecurity Research Center United Kingdom

ISBN: (纸本)9798350382235

The growing demand for wireless applications has driven research on technologies that can meet these needs. Cognitive radio (CR) is one such technology that enables shared spectrum usage. Communication in CR networks (CRNs) de-pends on the capabilities of the device, which can be full-duplex (FD) or half-duplex (HD). However, optimal routing for FD CRNs remains a challenge. This paper presents a routing protocol to improve network performance by minimizing time-sharing sessions using out-of-band FD (OBFD) communication. The protocol finds loop-free paths, computes transmission rates, and Probability of Success (POS) for each path, selecting the one with the highest POS. This optimization problem is converted from a binary quadratic problem (BQP) to a more solvable binary linear programming problem (BLP) using a polynomial-time sequential fixing method. The simulation results reveal that the proposed routing protocol significantly outperforms existing routing algorithms in terms of end-to-end throughput. © 2023 IEEE.

关键词： Cognitive radio

来源：评论

学校读者我要写书评

暂无评论

Neighborhood Modularization‑based Artificial Bee Colony Algorithm for Disassembly Planning with Operation Attributes

引用

Chinese Journal of Mechanical engineering 2022年第6期35卷 165-177页

作者： Hongfei Guo Linsheng Zhang Yaping Ren Leilei Meng Zhongwei Zhou Jianqing Li GBA and B&R International Joint Research Center for Smart Logistics School of Intelligent Systems Science and EngineeringInstitute of Physical InternetJinan University(Zhuhai Campus)Zhuhai 519070China School of Computer Science Liaocheng UniversityLiaocheng 252059China Faculty of Information Technology Macao University of Science and TechnologyMacao 999078China

The recycling and remanufacturing of end-of-life products are significant for environmental protection and resource *** is an essential process of remanufacturing end-of-life *** disassembly plans help improve disassembly efficiency and reduce disassembly *** paper studies a disassembly planning problem with operation attributes,in which an integrated decision of the disassembly sequence,disassembly directions,and disassembly tools are ***,a mathematical model is formulated with the objective of minimizing the penalty cost caused by the changing of operation ***,a neighborhood modularization-based artificial bee colony algorithm is developed,which contains a modular optimized ***,two case studies with different scales and complexities are used to verify the performance of the proposed approach,and experimental results show that the proposed algorithm outperforms the two existing methods within an acceptable computational time.

关键词： End-of-life products Disassembly planning Artificial bee colony Neighborhood modularization

来源：评论

学校读者我要写书评

暂无评论

Revolutionizing Road Safety: YOLOv8-Powered Driver Fatigue Detection

Revolutionizing Road Safety: YOLOv8-Powered Driver Fatigue D...

引用

2023 International Conference on Sustainable Technology and engineering, i-COSTE 2023

作者： Xie, Shuaiyue Chuah, Joong Huang Ting Chai, Grace Mei University of Southampton Electronics and Computer Science SouthamptonSO171BJ United Kingdom University of Malaya Faculty of Engineering Department of Electrical Engineering Kuala Lumpur50603 Malaysia University of Southampton Malaysia Smart Manufacturing Systems Research Group Iskandar Puteri Johor79100 Malaysia

ISBN: (纸本)9798350329711

Driver fatigue is a significant cause of road accidents. Effective real-time fatigue detection systems are necessary to improve road safety. Utilizing a lightweight and fast model and creating an effective fatigue judgment rule is important in detecting fatigue in real-time. In this research, we propose a fatigue detection model based on You Look Only Once version 8 (YOLOv8) model to detect driver's facial features and use percentage of eyelid closure over the pupil over time (PERCLOS) and Percentage of Open Mouth (POM) indicators to identify fatigue. This research is divided into two parts. The first part involves creating, labeling, and preprocessing the dataset. We use the YawDD dataset as the original dataset and manually label a new dataset using the Roboflow platform. We then preprocessed the new dataset to train the YOLOv8 model for face features detection. In the second part, we established a multi-indicator fatigue determination rule that uses PERCLOS and POM indicators and set a threshold to determine whether the driver is fatigue. By combining the YOLOv8 model with the fatigue determination rules based on PERCLOS and POM, we successfully built a model to identify a driver's fatigue. Finally, the fatigue detection model based on YOLOv8 achieves a high accuracy rate of 96.9% and a high speed of 11.4 ms/frame in face features detection, surpassing other traditional models and previous generations of YOLO models. This model can effectively detect fatigue in both driver-driving pictures and videos. © 2023 IEEE.

关键词： Roads and streets

来源：评论

学校读者我要写书评

暂无评论

Moss-Based Biotechnological Air Purification Control System

Moss-Based Biotechnological Air Purification Control System

引用

2022 International Conference on Electrical and Computing Technologies and Applications, ICECTA 2022

作者： Kusdavletov, Sanzhar Sapargali, Abdulla Yedilkhan, Didar Yermekov, Altynbek Astana IT University Department of Intelligent Systems and Cybersecurity Astana Kazakhstan Astana IT University Department of Computer Engineering Astana Kazakhstan Astana IT University 'Smart City' Research Center Astana Kazakhstan

ISBN: (数字)9781665456005

ISBN: (纸本)9781665456005

Nowadays, air pollution is one of the acute problems that humanity faces as the world further develops and more technology comes into use. Pollution is produced both outside and inside buildings mostly from the machinery we use for convenience. In this paper, a non-standard approach is being explored to solve the problem at hand. Since excessive ventilation can lead to more pollution and infection, and is also a loss of energy, it was decided to focus not on ventilation, but on air purification. To purify the air, a filter created by living plants has been used. For the project, we chose moss, which is unpretentious and small, unlike trees and bushes. Due to the autonomy and scale, our solution is easy to use and brings enormous ecological and social impact. During the research, a biotechnological prototype is created, where it is possible to observe and control moss growth and its productivity. For the algorithm to work correctly, data about the environment is required. For this reason, in this paper, we have described not only the modeling of the system we suggest but also the process of collecting information from the biofilter. By reducing pollution, we will shortly save and stabilize the ecological situation. In this project, the effective biofilter is developed based on various solutions from biology, control engineering, as well as internet of things fields. © 2022 IEEE.

关键词： Control systems

来源：评论

学校读者我要写书评

暂无评论

Multi-objective Feature Attribution Explanation for Explainable Machine Learning

引用

ACM Transactions on Evolutionary Learning and Optimization 2024年第1期4卷 1-32页

作者： Wang, Ziming Huang, Changwu Li, Yun Yao, Xin Research Institute of Trustworthy Autonomous Systems Guangdong Provincial Key Laboratory of Brain-inspired Intelligent Computation Departmentof Computer Science and Engineering Southern University of Science and Technology Shenzhen518055 China The Advanced Cognitive Technology Lab Huawei Technologies Co. Ltd Shanghai201206 China School of Computer Science University of Birmingham BirminghamB15 2TT United Kingdom

The feature attribution-based explanation (FAE) methods, which indicate how much each input feature contributes to the model's output for a given data point, are one of the most popular categories of explainable machine learning techniques. Although various metrics have been proposed to evaluate the explanation quality, no single metric could capture different aspects of the explanations. Different conclusions might be drawn using different metrics. Moreover, during the processes of generating explanations, existing FAE methods either do not consider any evaluation metric or only consider the faithfulness of the explanation, failing to consider multiple metrics simultaneously. To address this issue, we formulate the problem of creating FAE explainable models as a multi-objective learning problem that considers multiple explanation quality metrics simultaneously. We first reveal conflicts between various explanation quality metrics, including faithfulness, sensitivity, and complexity. Then, we define the considered multi-objective explanation problem and propose a multi-objective feature attribution explanation (MOFAE) framework to address this newly defined problem. Subsequently, we instantiate the framework by simultaneously considering the explanation's faithfulness, sensitivity, and complexity. Experimental results comparing with six state-of-The-Art FAE methods on eight datasets demonstrate that our method can optimize multiple conflicting metrics simultaneously and can provide explanations with higher faithfulness, lower sensitivity, and lower complexity than the compared methods. Moreover, the results have shown that our method has better diversity, i.e., it provides various explanations that achieve different tradeoffs between multiple conflicting explanation quality metrics. Therefore, it can provide tailored explanations to different stakeholders based on their specific requirements. © 2024 Copyright held by the owner/author(s). Publication rights licensed

关键词： Machine learning

来源：评论

学校读者我要写书评

暂无评论

A Distributed Framework for Large-scale Protein-protein Interaction Data Analysis and Prediction Using MapReduce

引用

IEEE/CAA Journal of Automatica Sinica 2022年第1期9卷 160-172页

作者： Lun Hu Shicheng Yang Xin Luo Huaqiang Yuan Khaled Sedraoui MengChu Zhou School of Computer Science and Technology Dongguan University of TechnologyDongguan 523808China School of Computer Science and Technology Wuhan University of TechnologyWuhan 430070China Chongqing Engineering Research Center of Big Data Application for Smart Cities and Chongqing Key Laboratory of Big Data and Intelligent ComputingChongqing Institute of Green and Intelligent TechnologyChinese Academy of SciencesChongqing 400714China Xinjiang Technical Institute of Physics and Chemistry Chinese Academy of SciencesUrumqi 830000China Center of Research Excellence in Renewable Energy and Power Systems and the Department of Electrical and Computer EngineeringFaculty of EngineeringKing Abdulaziz UniversityJeddah 21589Saudi Arabia Department of Electrical and Computer Engineering New Jersey Institute of TechnologyNewarkNJ 07102 USA

Protein-protein interactions are of great significance for human to understand the functional mechanisms of *** the rapid development of high-throughput genomic technologies,massive protein-protein interaction(PPI)data have been generated,making it very difficult to analyze them *** address this problem,this paper presents a distributed framework by reimplementing one of state-of-the-art algorithms,i.e.,CoFex,using *** do so,an in-depth analysis of its limitations is conducted from the perspectives of efficiency and memory consumption when applying it for large-scale PPI data analysis and *** solutions are then devised to overcome these *** particular,we adopt a novel tree-based data structure to reduce the heavy memory consumption caused by the huge sequence information of *** that,its procedure is modified by following the MapReduce framework to take the prediction task distributively.A series of extensive experiments have been conducted to evaluate the performance of our framework in terms of both efficiency and *** results well demonstrate that the proposed framework can considerably improve its computational efficiency by more than two orders of magnitude while retaining the same high accuracy.

关键词： Distributed computing large-scale prediction machine learning MapReduce protein-protein interaction(PPI)

来源：评论

学校读者我要写书评

暂无评论

Channel Aging-Aware LSTM-Based Channel Prediction for Satellite Communications

IEEE Networking Letters

引用

IEEE Networking Letters 2024年第3期6卷 183-187页

作者： Abbasi, Omid Kaddoum, Georges Carleton University Non-Terrestrial Networks Lab Department of Systems and Computer Engineering OttawaONK1S 5B6 Canada Université du Québec École de Technologie Supérieure Department of Electrical Engineering MontrealQCH3C 1K3 Canada Lebanese American University Cyber Security Systems and Applied Ai Research Center Beirut2801 Lebanon

Satellite communication systems encounter channel aging issues due to the substantial distance that separates users and satellites. In such systems, the estimated channel state at a given time slot reflects the channel state from several time slots in the past. This letter proposes a long short-term memory (LSTM)-based architecture for channel prediction to mitigate the channel aging problem. The proposed scheme predicts the next time slot's channel based on a block of estimated channel state information (CSI) from previous time slots. We consider the effect of channel aging in the training phase so that channel prediction in the testing phase is performed based on available data. We demonstrated through simulation experiments on new radio non-terrestrial network tapped delay line (NR NTN TDL) channel models, that our proposed scheme can effectively mitigate channel aging, and that it performs better than outdated channels. The proposed scheme improves the reliability and efficiency of satellite communication systems with long propagation delays. © 2019 IEEE.

关键词： Satellite communication systems

来源：评论

学校读者我要写书评

暂无评论

Empowering Object Detection in Dynamic Environments with AI-Driven MIMO Radar Technology

Empowering Object Detection in Dynamic Environments with AI-...

引用

IEEE Region 10 Symposium

作者： N S S V Praneeth T Sathya Narayana B Rupphak Sai Kiran Mirza Rizwan Baig Gandhiraj R Anandaselvakarthik T Department of Electronics and Communication Engineering Smart Integrated Electronics Radiating Systems (SIERS) Research Lab Amrita School of Engineering Coimbatore Amrita Vishwa Vidyapeetham India

ISBN: (数字)9798350364866

ISBN: (纸本)9798350364873

Millimeter-wave radars are increasingly used for surveillance and automotive applications, as optical-based systems have a hard time in complex environments such as night, fog, etc. These applications use advanced object detection and classification algorithms that require huge amounts of datasets for training and testing, which is hard to obtain considering that they utilize the same radar configuration and contain required scenarios that enhance your model accuracy. Moreover, in signal processing perspective, angular resolution is constrained by the number of receivers present in the radar. So, to account for these problems, we propose a virtual radar that can generate datasets through code, which can be used to train and test a model, and an AI model that won't be constrained by angular resolution.

关键词： Training Surveillance Radar detection Object detection Radar signal processing Optical receivers Vehicle dynamics Optical signal processing Signal resolution Testing

来源：评论

学校读者我要写书评

暂无评论

Distributed consensus-based voltage and frequency control for isolated microgrids with fault-induced delayed voltage recovery mitigation

引用

Frontiers in Energy research 2024年 12卷

作者： Alghamdi, Baheej Smart Grids Research Group Center of Research Excellence in Renewable Energy and Power Systems King Abdulaziz University Jeddah Saudi Arabia Department of Electrical and Computer Engineering King Abdulaziz University Jeddah Saudi Arabia

This paper presents a distributed consensus-based voltage and frequency control (VFC) strategy for isolated microgrids with distributed energy resources (DERs) and induction motor loads. The proposed controller coordinates the DERs to regulate microgrid frequency and voltage while mitigating fault-induced delayed voltage recovery (FIDVR), a phenomenon where system voltage remains depressed for several seconds after fault clearance due to induction motor stalling. The VFC loop adjusts DER voltage setpoints based on frequency deviation and voltage level to regulate voltage and mitigate FIDVR events, while the active power control loop maintains frequency stability by coordinating active power sharing among DERs and compensating for the constant power load behavior of stalled induction motors. A proximity-based reactive power support prioritization and a distributed voltage estimator enhance the controller’s response to FIDVR events. Coordination between the VFC and active power control loops is achieved through adaptive gain adjustment and a voltage recovery coordination term. Simulation results demonstrate the effectiveness of the proposed controller in maintaining microgrid stability, ensuring fast voltage recovery, and providing robust performance under various operating conditions, including communication delays and different fault durations. Copyright © 2025 Alghamdi.

关键词： Microgrids

来源：评论

学校读者我要写书评

暂无评论

In situ construction of PtSe_(2)/Ge Schottky junction array with interface passivation for broadband infrared photodetection and imaging

引用

InfoMat 2024年第4期6卷 37-46页

作者： Xue Li Shuo-En Wu Di Wu Tianxiang Zhao Pei Lin Zhifeng Shi Yongtao Tian Xinjian Li Longhui Zeng Xuechao Yu School of Physics and Microelectronics Key Laboratory of Material Physics Ministry of EducationZhengzhou UniversityZhengzhouHenanthe People's Republic of China Department of Electrical and Computer Engineering University of CaliforniaLa JollaCaliforniaUSA National Research Center for Optical Sensors/Communications Integrated Networks School of Electronic Science and EngineeringSoutheast UniversityNanjingJiangsuthe People's Republic of China Key Laboratory of Multifunctional Nanomaterials and Smart Systems Suzhou Institute of Nano-Tech and Nano-BionicsChinese Academy of SciencesSuzhouJiangsuthe People's Republic of China

Infrared(IR)detection is vital for various military and civilian *** research has highlighted the potential of two-dimensional(2D)topological semimetals in IR detection due to their distinctive advantages,including van der Waals(vdW)stacking,gapless electronic structure,and Van Hove singularities in the electronic density of ***,challenges such as large-scale patterning,poor photoresponsivity,and high dark current of photodetectors based on 2D topological semimetals significantly impede their wider applications in low-energy photon ***,we demonstrate the in situ fabrication of PtSe_(2)/Ge Schottky junction by directly depositing 2D PtSe_(2) films with a vertical layer structure on a Ge substrate with an ultrathin AlOx *** to high quality junction,the photodetector features a broadband response of up to 4.6μm,along with a high specific detectivity of�1012 Jones,and operates with remarkable stability in ambient conditions as ***,the highly integrated device arrays based on PtSe_(2)/AlOx/Ge Schottky junction showcases excellent Mid-IR(MIR)imaging capability at room *** findings highlight the promising prospects of 2D topological semimetals for uncooled IR photodetection and imaging applications.

关键词： broadband photodetection imaging platinum diselenide Schottky junction van der Waals integration

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：