检索结果-内蒙古大学图书馆

Student’s Health Exercise Recognition Tool for E-Learning Education

Intelligent Automation & Soft Computing 2023年第1期35卷 149-161页

作者： Tamara al Shloul Madiha Javeed Munkhjargal Gochoo Suliman AAlsuhibany Yazeed Yasin Ghadi Ahmad Jalal Jeongmin Park Department of Humanities and Social Science Al Ain UniversityAl Ain15551UAE Department of Computer Science Air UniversityIslamabad44000Pakistan Department of Computer Science and Software Engineering United Arab Emirates UniversityAl Ain15551UAE Department of Computer Science College of ComputerQassim UniversityBuraydah51452Saudi Arabia Department of Computer Science and Software Engineering Al Ain UniversityAl Ain15551UAE Department of Computer Engineering Korea Polytechnic UniversitySiheung-siGyeonggi-do237Korea

Due to the recently increased requirements of e-learning systems,multiple educational institutes such as kindergarten have transformed their learning towards virtual *** student health exercise is a difficult task but an important one due to the physical education needs especially in young *** proposed system focuses on the necessary implementation of student health exercise recognition(SHER)using a modified Quaternion-basedfilter for inertial data refining and data fusion as the pre-processing ***,cleansed data has been segmented using an overlapping windowing approach followed by patterns identification in the form of static and kinematic signal ***,these patterns have been utilized to extract cues for both patterned signals,which are further optimized using Fisher’s linear discriminant analysis(FLDA)***,the physical exercise activities have been categorized using extended Kalmanfilter(EKF)-based neural *** system can be implemented in multiple educational establishments including intelligent training systems,virtual mentors,smart simulations,and interactive learning management methods.

关键词： E-learning exercise recognition online physical education student’s healthcare

来源：评论

学校读者我要写书评

暂无评论

A machine learning approach for skin lesion classification on iOS: implementing and optimizing a convolutional transfer learning model with Create ML

引用

International Journal of computers and Applications 2024年第8期46卷 666-685页

作者： Benedek Szabo, Aron Katona, Jozsef Department of Software Development and Application Institute of Computer Engineering University of Dunaujvaros Dunaujvaros Hungary Department of Instrumentation and Automation Institute of Electronics and Communication Systems Kandó Kálmán Faculty of Electrical Engineering Obuda University Budapest Hungary Department of Informatics GAMF Faculty of Engineering and Computer Science Kecskemét Hungary

The integration of machine learning (ML) into mobile applications presents unique challenges, particularly in resource-constrained environments such as iOS devices. Skin lesion classification is a critical task in dermatology, where accurate and efficient diagnostic tools can significantly aid in early detection of malignant lesions. This study aims to implement a machine learning-based iOS mobile application and develop a binary classification model for skin lesion images to determine whether a lesion is malignant. The research utilized Create ML to develop a convolutional neural network optimized for iOS, employing a transfer learning approach. A logistic regression model was cascaded with the convolutional neural network N to enhance classification accuracy. The model's performance was assessed through various validation metrics, ensuring its robustness and efficiency within the constraints of mobile hardware. A curated dataset from the International Skin Imaging Collaboration archive was used for training and testing. The model achieved an accuracy of 92%, a precision of 90%, a recall of 93%, and an F1-score of 91% in classifying skin lesions. These metrics validate the model's efficacy in identifying malignant lesions. Data curation involved collecting, labeling, and preparing a dataset from publicly available sources, ensuring the inclusion of diagnostically relevant features. The final model was integrated into an iOS application using Core ML and Vision frameworks. The developed application demonstrates reliable performance in classifying skin lesions with high accuracy on iOS devices. The inclusion of comprehensive performance metrics justifies the efficacy of the proposed approach. Future work will explore enhancements in model architecture and object detection capabilities to further improve diagnostic precision and application usability. © 2024 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Image recognition

来源：评论

学校读者我要写书评

暂无评论

Tracking daily paths in home contexts with RSSI fingerprinting based on UWB through deep learning models

引用

Multimedia Tools and Applications 2024年 1-25页

作者： Polo-Rodríguez, A. Valera, J.C. Peral, J. Gil, D. Medina-Quero, J. Department of Computer Engineering Automation and Robotics University of Granada Granada18071 Spain Alicante03690 Spain Department of Software and Computing Systems University of Alicante Alicante03690 Spain

The field of human activity recognition has evolved significantly, driven largely by advancements in Internet of Things (IoT) device technology, particularly in personal devices. This study investigates the use of ultra-wideband (UWB) technology for tracking inhabitant paths in home environments using deep learning models. UWB technology estimates user locations via time-of-flight and time-difference-of-arrival methods, which are significantly affected by the presence of walls and obstacles in real environments, reducing their precision. To address these challenges, we propose a fingerprinting-based approach utilizing received signal strength indicator (RSSI) data collected from inhabitants in two flats (60 m2 and 100 m2) while performing daily activities. We compare the performance of convolutional neural network (CNN), long short-term memory (LSTM), and hybrid CNN+LSTM models, as well as the use of Bluetooth technology. Additionally, we evaluate the impact of the type and duration of the temporal window (future, past, or a combination of both). Our results demonstrate a mean absolute error close to 50 cm, highlighting the superiority of the hybrid model in providing accurate location estimates, thus facilitating its application in daily human activity recognition in residential settings. © The Author(s) 2024.

关键词： Ultra-wideband (UWB)

来源：评论

学校读者我要写书评

暂无评论

Edge Cloud Selection in Mobile Edge Computing(MEC)-Aided Applications for Industrial Internet of Things(IIoT)Services

引用

computer Systems Science & engineering 2023年第11期47卷 2049-2060页

作者： Dae-Young Kim SoYeon Lee MinSeung Kim Seokhoon Kim Department of Computer Software Engineering Soonchunhyang UniversityAsan31538Korea Department of Software Convergence Soonchunhyang UniversityAsan31538Korea

In many IIoT architectures,various devices connect to the edge cloud via gateway *** data processing,numerous data are delivered to the edge *** data to an appropriate edge cloud is critical to improve IIoT service *** are two types of costs for this kind of IoT network:a communication cost and a computing *** service efficiency,the communication cost of data transmission should be minimized,and the computing cost in the edge cloud should be also ***,in this paper,the communication cost for data transmission is defined as the delay factor,and the computing cost in the edge cloud is defined as the waiting time of the computing *** proposed method selects an edge cloud that minimizes the total cost of the communication and computing *** is,a device chooses a routing path to the selected edge cloud based on the *** proposed method controls the data flows in a mesh-structured network and appropriately distributes the data processing *** performance of the proposed method is validated through extensive computer *** the transition probability from good to bad is 0.3 and the transition probability from bad to good is 0.7 in wireless and edge cloud states,the proposed method reduced both the average delay and the service pause counts to about 25%of the existing method.

关键词： Industrial Internet of Things(IIoT)network IIoT service mobile edge computing(MEC) edge cloud selection MEC-aided application

来源：评论

学校读者我要写书评

暂无评论

State-of-the-Art in Cyber-Physical Security for Dynamic Wireless Charging of Electric Vehicles 50

State-of-the-Art in Cyber-Physical Security for Dynamic Wire...

引用

50th Annual Conference of the IEEE Industrial Electronics Society, IECON 2024

作者： Yazdanipour, Samaneh Oruganti, V.S.R. Varaprasad Son, Jeonggi Arani, Mohammadreza F.M. Williamson, Sheldon S. Toronto Metropolitan University Department of Electrical Computer and Biomedical Engineering Toronto Canada Ontario Tech University Department of Electrical Computer and Software Engineering Oshawa Canada

ISBN: (纸本)9781665464543

Dynamic Wireless Charging systems for electric vehicles offers a revolutionary approach to EV charging, enabling vehicles to charge while in motion and overcoming the limitations of stationary wireless charging. Despite their efficiency and convenience, dynamic wireless charging systems introduce complex security vulnerabilities that must be addressed to ensure system reliability and safety. This paper provides a comprehensive review of the cyber-physical security challenges associated with electric vehicle dynamic wireless charging systems, examining potential threats such as cyber attacks and physical tampering. It identifies specific vulnerabilities in communication protocols, hardware, and software, and discusses various mitigation strategies such as encryption and physical layer security enhancements. Furthermore, the paper highlights recent advancements in security technologies and outlines future research directions to enhance the resilience of dynamic wireless charging systems. By addressing these security challenges, stakeholders can foster a safer environment for the deployment of dynamic wireless charging, thereby promoting the broader adoption of electric vehicles and advancing sustainable transportation solutions. © 2024 IEEE.

关键词： State of charge

来源：评论

学校读者我要写书评

暂无评论

A Model-Driven Framework for Water Supply Management System (MWS) 20

A Model-Driven Framework for Water Supply Management System ...

引用

20th International Conference on Frontiers of Information Technology, FIT 2023

作者： Azhar, Marukh Azam, Farooque Anwar, Waseem Amjad, Anam Rasheed, Yawar College of Electrical and Mechanical Engineering Department of Computer & Software Engineering Islamabad Pakistan

ISBN: (纸本)9798350395785

Systems for managing water supplies are intricate, requiring a range of models to manage water resources efficiently. These models can be designed and manipulated using a Model-Driven Architecture (MDA), which will increase the efficiency of managing the water supply. This research concept is particularly interesting since it has the potential to revolutionize water supply management. We can develop virtual representations of the entire system using model-driven architecture, allowing us to simulate and analyze numerous situations without incurring significant expenses and hazards. In this paper, we offer a model-driven framework. Our method entails transforming the model into textual representation, followed by verification with Uppaal. A model-to-text transformation is performed by creating a transformation engine in Acceleo® that converts software models into timed automata models. Timed automata are useful for modeling and analyzing the timing behavior of complicated systems. A real-time case study of the Mirpur City of Pakistan validates the framework's effectiveness, showing its capability to model water supply management systems. Incorporating formal verification improves the system's dependability by assuring standardization and reducing possible flaws. Moreover, system reliability will increase with early detection and rectification. © 2023 IEEE.

关键词： software architecture

来源：评论

学校读者我要写书评

暂无评论

Comprehensive analysis of multiple machine learning techniques for rock slope failure prediction

引用

Journal of Rock Mechanics and Geotechnical engineering 2024年第11期16卷 4386-4398页

作者： Arsalan Mahmoodzadeh Abed Alanazi Adil Hussein Mohammed Hawkar Hashim Ibrahim Abdullah Alqahtani Shtwai Alsubai Ahmed Babeker Elhag Department of Civil Engineering University of HalabjaHalabjaKurdistan Region46018Iraq Department of Computer Science College of Computer Engineering and Sciences in Al-KharjPrince Sattam bin Abdulaziz UniversityP.O.Box 151Al-Kharj11942Saudi Arabia Department of Communication and Computer Engineering Faculty of EngineeringCihan University-ErbilKurdistan RegionIraq Department of Civil Engineering College of EngineeringSalahaddin University-Erbil44002ErbilKurdistan RegionIraq Software Engineering Department College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityP.O.Box 151Al-Kharj11942Saudi Arabia Department of Civil Engineering College of EngineeringKing Khalid UniversityAbha61413Saudi Arabia

In this study,twelve machine learning(ML)techniques are used to accurately estimate the safety factor of rock slopes(SFRS).The dataset used for developing these models consists of 344 rock slopes from various open-pit mines around Iran,evenly distributed between the training(80%)and testing(20%)*** models are evaluated for accuracy using Janbu's limit equilibrium method(LEM)and commercial tool GeoStudio *** assessment metrics show that the random forest model is the most accurate in estimating the SFRS(MSE=0.0182,R2=0.8319)and shows high agreement with the results from the LEM *** results from the long-short-term memory(LSTM)model are the least accurate(MSE=0.037,R2=0.6618)of all the models ***,only the null space support vector regression(NuSVR)model performs accurately compared to the practice mode by altering the value of one parameter while maintaining the other parameters *** is suggested that this model would be the best one to use to calculate the SFRS.A graphical user interface for the proposed models is developed to further assist in the calculation of the SFRS for engineering *** this study,we attempt to bridge the gap between modern slope stability evaluation techniques and more conventional analysis methods.

关键词： Rock slope stability Open-pit mines Machine learning(ML) Limit equilibrium method(LEM)

来源：评论

学校读者我要写书评

暂无评论

Framework for Agent-Based Multistage Application Partitioning Algorithm in Mobile Cloud Computing

引用

SN computer Science 2024年第4期5卷 330页

作者： Kanwal, Asia Amjad, Tehmina Ashraf, Humaira Department of Computer Science and Software Engineering International Islamic University H10 Islamabad 44000 Pakistan

The idea of computational offloading is quickly catching on in the world of mobile cloud computing (MCC). Today’s applications have heavy demands on power and computing resources, creating issues with energy consumption, storage capacity, and mobile device performance. Mobile devices may efficiently offload their calculations to cloud servers using the offloading paradigm and then get the processed results back onto the device. The investigation relates to identifying the specific application components that should be offloaded and run remotely and which parts are supposed to be treated locally. The applications need to be partitioned to differentiate between remote and local codes. In this paper, an agent-based multistage graph partitioning (ABMP) scheme is proposed. The framework of the scheme is based on three-tier architecture that includes mobile, cloudlet, and cloud for the execution of application tasks. The main goal is to provide an efficient partitioning and offloading scheme in the mobile cloud computing area. The results show that incorporating both agent-based multistage graph partitioning and offloading algorithms yields superior performance as compared to previous methods in terms of reducing execution costs and conserving battery life for mobile devices. © The Author(s) 2024.

关键词： Agent-based partitioning Application partitioning Edge computing Mobile cloud computing Multistage graph partitioning Ready time partitioning offloading

来源：评论

学校读者我要写书评

暂无评论

Comparison of Current Metaheuristics for Solving engineering Problems

Comparison of Current Metaheuristics for Solving Engineering...

引用

2024 Innovations in Intelligent Systems and Applications Conference, ASYU 2024

作者： Tufan, Elif Arslan, Sibel Computer Engineering Department Sivas Cumhuriyet University Sivas Turkey Software Engineering Department Sivas Cumhuriyet University Sivas Turkey

ISBN: (纸本)9798350379433

Nowadays, with the increasing number of metaheuristic, different strategies for solving engineering problems have been introduced. In this study, the Crayfish Optimizer Algorithm (COA), Spider Wasp Optimizer (SWO) and Goose Algorithm (Goose) are compared among the current metaheuristics inspired by the unique behaviors and survival functions of different animals in nature. To the best of our knowledge, this is the first study to compare the performance of these algorithms on three popular engineering problems (pressure vessel design, welded beam design and tension-compression design problems). When the experimental results and convergence rates are evaluated, it is observed that all metaheuristics exhibit very high performance. SWO, inspired by the hunting and nesting behavior strategies of spider wasps, is the most successful metaheuristic. SWO is followed by COA, modeled from the natural behavior of crayfish, and Goose, developed by imitating the flocking behavior of goose. The statistical significance of the results was assessed using t-tests, which demonstrate the superiority of SWO. In future studies, it is aimed that other metaheuristics, especially SWO, can be used in solving different engineering problems. © 2024 IEEE.

关键词： Invertebrates

来源：评论

学校读者我要写书评

暂无评论

Profit Maximization of Delay-Sensitive, Differential Accuracy Inference Services in Mobile Edge Computing

引用

IEEE Transactions on Mobile Computing 2025年第7期24卷 6209-6224页

作者： Zhang, Yuncan Liang, Weifa Xu, Zichuan Jia, Xiaohua Yang, Yuanyuan City University of Hong Kong Department of Computer Science Hong Kong Hong Kong Dalian University of Technology School of Software Dalian China Stony Brook University Department of Electrical and Computer Engineering Stony BrookNY United States

The integration of Artificial Itelligence (AI) and edge computing has sparked significant interest in edge inference services. In this paper, we consider delay-sensitive, differential accuracy inference services in a Mobile Edge Computing (MEC) network while meeting user stringent delay and accuracy requirements. We formulate two novel profit maximization problems under static and dynamic settings of service request arrivals, with the aim of maximizing the accumulative profit of admitted requests. We assign differential accuracy service requests to the corresponding resolution instances of their requested service models, assuming that each resolution instance can serve up to L≥ 1 the same type of service requests. Since the profit maximization problem is NP-hard, we first formulate an Integer Linear Program (ILP) solution if the problem size is small or medium;otherwise, we devise a constant randomized algorithm with high probability. Then, we consider dynamic service request admissions without the knowledge of future request arrivals for a given finite time horizon, for which we develop a simple yet effective prediction mechanism to accurately predict the number of different resolution instances of each model needed, and pre-deploy the predicted number of resolution instances into cloudlets to reduce instantiating delays. We then devise an online algorithm with a provable competitive ratio for the dynamic profit maximization problem by leveraging the primal-dual dynamic updating technique. Finally, we evaluate the performance of the proposed algorithms by simulations. The simulation results demonstrate that the proposed algorithms are promising. © 2002-2012 IEEE.

关键词： Mobile edge computing

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：