检索结果-南通市图书馆

Comprehensive Review and Analysis on Facial Emotion Recognition:Performance Insights into Deep and Traditional Learning with Current Updates and Challenges

引用

Computers, Materials & Continua 2025年第1期82卷 41-72页

作者： Amjad Rehman Muhammad Mujahid Alex Elyassih Bayan AlGhofaily Saeed Ali Omer Bahaj Artificial Intelligence&Data Analytics Lab College of Computer&Information SciencesPrince Sultan UniversityRiyadh11586Saudi Arabia MIS department college of business administration Prince Sattam Bin Abdulaziz UniversityAlKharj11942Saudi Arabia

In computer vision and artificial intelligence,automatic facial expression-based emotion identification of humans has become a popular research and industry *** demonstrations and applications in several fields,including computer games,smart homes,expression analysis,gesture recognition,surveillance films,depression therapy,patientmonitoring,anxiety,and others,have brought attention to its significant academic and commercial *** study emphasizes research that has only employed facial images for face expression recognition(FER),because facial expressions are a basic way that people communicate meaning to each *** immense achievement of deep learning has resulted in a growing use of its much architecture to enhance *** review is on machine learning,deep learning,and hybrid methods’use of preprocessing,augmentation techniques,and feature extraction for temporal properties of successive frames of *** following section gives a brief summary of assessment criteria that are accessible to the public and then compares them with benchmark results the most trustworthy way to assess FER-related research topics *** this review,a brief synopsis of the subject matter may be beneficial for novices in the field of FER as well as seasoned scholars seeking fruitful avenues for further *** information conveys fundamental knowledge and provides a comprehensive understanding of the most recent state-of-the-art research.

关键词： Face emotion recognition deep learning hybrid learning CK+ facial images machine learning technological development

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

A Comprehensive Survey on Federated Learning Applications in Computational Mental Healthcare

引用

Computer Modeling in Engineering & Sciences 2025年第1期142卷 49-90页

作者： Vajratiya Vajrobol Geetika Jain Saxena Amit Pundir Sanjeev Singh Akshat Gaurav Savi Bansal Razaz Waheeb Attar Mosiur Rahman Brij B.Gupta Institute of Informatics and Communication University of DelhiDelhi110021India Maharaja Agrasen college University of DelhiDelhi110096India Computer Engineering Ronin InstituteMontclairNJ 07043USA department of Research and Innovation Insights2TechinfoJaipur302001India university Centre for Research and Development(UCRD) Chandigarh UniversityChandigarh140413India Management department College of Business AdministrationPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia CCRI&department of Computer Science and information Engineering Asia UniversityTaichung413Taiwan Symbiosis Centre for information Technology(SCIT) Symbiosis International UniversityPune411057India Center for Interdisciplinary Research University of Petroleum and Energy Studies(UPES)Dehradun248007India

Mental health is a significant issue worldwide,and the utilization of technology to assist mental health has seen a growing *** aims to alleviate the workload on healthcare professionals and aid *** applications have been developed to support the challenges in intelligent healthcare ***,because mental health data is sensitive,privacy concerns have *** learning has gotten some *** research reviews the studies on federated learning and mental health related to solving the issue of intelligent healthcare *** explores various dimensions of federated learning in mental health,such as datasets(their types and sources),applications categorized based on mental health symptoms,federated mental health frameworks,federated machine learning,federated deep learning,and the benefits of federated learning in mental health *** research conducts surveys to evaluate the current state of mental health applications,mainly focusing on the role of Federated Learning(FL)and related privacy and data security *** survey provides valuable insights into how these applications are emerging and evolving,specifically emphasizing FL’s impact.

关键词： Depression emotional recognition intelligent healthcare systems mental health federated learning stress detection sleep behaviour

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Hybridizing Artificial Bee Colony with Bat Algorithm for Web Service Composition

引用

Computer systems Science & Engineering 2023年第8期46卷 2429-2445页

作者： Tariq Ahamed Ahanger Fadl Dahan Usman Tariq department of Management information systems College of Business AdministrationPrince Sattam Bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia department of Management information systems College of Business Administration-Hawtat Bani TamimPrince Sattam Bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia department of Computer Sciences Faculty of Computing and Information Technology Al-TurbahTaiz UniversityTaiz9674Yemen

In the Internet of Things(IoT),the users have complex needs,and the Web Service Composition(WSC)was introduced to address these *** WSC’s main objective is to search for the optimal combination of web services in response to the user needs and the level of Quality of Services(QoS)*** challenge of this problem is the huge number of web services that achieve similar functionality with different levels of QoS *** this paper,we introduce an extension of our previous works on the Artificial Bee Colony(ABC)and Bat Algorithm(BA).A new hybrid algorithm was proposed between the ABC and BA to achieve a better tradeoff between local exploitation and global *** bat agent is used to improve the solution of exhausted bees after a threshold(limits),and also an Elitist Strategy(ES)is added to BA to increase the convergence *** performance and convergence behavior of the proposed hybrid algorithm was tested using extensive comparative experiments with current state-ofthe-art nature-inspired algorithms on 12 benchmark datasets using three evaluation criteria(average fitness values,best fitness values,and execution time)that were measured for 30 different *** datasets are created from real-world datasets and artificially to form different scale sizes of WSC *** results show that the proposed algorithm enhances the search performance and convergence rate on finding the near-optimal web services combination compared to *** signed-rank significant test is usedwhere the proposed algorithm results significantly differ fromother algorithms on 100%of datasets.

关键词： Internet of things artificial bee colony bat algorithm elitist strategy web service composition

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Item-level Forecasting for E-commerce Demand with High-dimensional Data Using a Two-stage Feature Selection Algorithm

引用

Journal of systems Science and systems Engineering 2022年第2期31卷 247-264页

作者： Hongyan Dai Qin Xiao Nina Yan Xun Xu Tingting Tong business School Central University of Finance and EconomicsBeijing 100081China department of Management Operationsand MarketingCollege of Business AdministrationCalifornia State UniversityStanislausTurlockCA95382United States Institute of Supply Chain Analytics&International business college Dongbei University of Finance and EconomicsDalian 116025China

With the rapid development of information technology and fast growth of Internet users,e-commerce nowadays is facing complex business environment and accumulating large-volume and highdimensional *** brings two challenges for demand ***,e-merchants need to find appropriate approaches to leverage the large amount of data and extract forecast features to capture various factors affecting the ***,they need to efficiently identify the most important features to improve the forecast accuracy and better understand the key drivers for demand *** solve these challenges,this study conducts a multi-dimensional feature engineering by constructing five feature categories including historical demand,price,page view,reviews,and competition for e-commerce demand forecasting on *** then propose a two-stage random forest-based feature selection algorithm to effectively identify the important features from the high-dimensional feature set and avoid *** test our proposed algorithm with a large-scale dataset from the largest e-commerce platform in *** numerical results from 21,111 items and 109 million sales observations show that our proposed random forest-based forecasting framework with a two-stage feature selection algorithm delivers 11.58%,5.81%and 3.68%forecast accuracy improvement,compared with the Autoregressive Integrated Moving Average(ARIMA),Random Forecast,and Random Forecast with one-stage feature selection approach,respectively,which are widely used in literature and *** study provides a useful tool for the practitioners to forecast demands and sheds lights on the B2C e-commerce operations management.

关键词： Forecasting e-commerce high-dimensional feature feature selection

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Waste sorting and its effects on carbon emission reduction:Evidence from China

引用

Chinese Journal of Population,Resources and Environment 2020年第1期18卷 26-34页

作者： Hongping Lian Dechuan Wang Hui Li School of Government Beijing Normal UniversityBeijing100875China department of Public administration College of Business Administration and Public PolicyCalifornia State UniversityThe United States

Considering the importance of waste sorting and treatment in the development of an ecological civilization,empirically evaluating the environmental impact of such programs is particularly *** study uses Xiao'er Township in Gong County,Sichuan Province,China as a case study to analyze and estimate the carbon emission reduction effects of the township's pilot waste sorting *** the five-point sampling method,samples of waste are collected,reviewed,and measured for their major components and other key ***,questionnaire surveys and interviews are conducted in the township,along with investigations into existing records and other relevant *** study adopts the solid waste management-greenhouse gas(SWM-GHG)calculator to study the township *** case study results imply that proper waste sorting and treatment methods in villages and townships could play a major role in the reduction of carbon ***,after implementing waste sorting in Xiao'er,annual carbon emissions were reduced by 2081 tons—equivalent to the electricity consumption of a family of three people for 1718 years,or the amount of CO_(2)emitted by 2641.6L vehicles driving once around the *** the optimal scenario simulation,increasing the recycling of wet waste and recyclable waste further,the level of carbon emission reduction in Xiao'er could reach up to 4482 tons per *** to the international general carbon trade price,this is equivalent to adding 44,820 US dollars to the GDP,or to an annual saving of 5.71 million *** these waste management methods are expanded to villages and townships across China,then the carbon emissions reduced in a year would be equal to the CO_(2)emitted from electricity generation in Beijing for over a *** on these findings,this paper provides three policy recommendations for effective carbon emission reduction:increasing residents'environmental protection awareness over the long term,boosting

关键词： Township waste sorting and treatment Carbon emission reduction SWM-GHG calculator China Xiao'er township

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

A Novel Hybrid Architecture for Superior IoT Threat Detection through Real IoT Environments

引用

Computers, Materials & Continua 2024年第11期81卷 2299-2316页

作者： Bassam Mohammad Elzaghmouri Yosef Hasan Fayez Jbara Said Elaiwat Nisreen Innab Ahmed Abdelgader Fadol Osman Mohammed Awad Mohammed Ataelfadiel Farah H.Zawaideh Mouiad Fadeil Alawneh Asef Al-Khateeb Marwan Abu-Zanona department of Computer Science Faculty of Computer Science and Information TechnologyJerash UniversityJerash26150Jordan Computer Engineering department College of Engineering&Information Technology Buraydah CollegesBuraydah51418Saudi Arabia Faculty of Architecture and Design Al-Zaytoonah University of JordanAmman11733Jordan department of Computer Science and information systems College of Applied SciencesAlMaarefa UniversityDiriyahRiyadh13713Saudi Arabia Applied college King Faisal UniversityAl-Ahsa31982Saudi Arabia department of business Intelligence and Data Analysis Faculty of Financial Sciences and BusinessIrbid National UniversityIrbid21110Jordan Faculty of information Technology Ajloun National UniversityAjlun26810Jordan department of Management information systems College of Business AdministrationKing Faisal UniversityAl-Ahsa31982Saudi Arabia

As the Internet of Things(IoT)continues to expand,incorporating a vast array of devices into a digital ecosystem also increases the risk of cyber threats,necessitating robust defense *** paper presents an innovative hybrid deep learning architecture that excels at detecting IoT threats in real-world *** proposed model combines Convolutional Neural Networks(CNN),Bidirectional Long Short-Term Memory(BLSTM),Gated Recurrent Units(GRU),and Attention mechanisms into a cohesive *** integrated structure aims to enhance the detection and classification of complex cyber threats while accommodating the operational constraints of diverse IoT *** evaluated our model using the RT-IoT2022 dataset,which includes various devices,standard operations,and simulated *** research’s significance lies in the comprehensive evaluation metrics,including Cohen Kappa and Matthews Correlation Coefficient(MCC),which underscore the model’s reliability and predictive *** model surpassed traditional machine learning algorithms and the state-of-the-art,achieving over 99.6%precision,recall,F1-score,False Positive Rate(FPR),Detection Time,and accuracy,effectively identifying specific threats such as Message Queuing Telemetry Transport(MQTT)Publish,Denial of Service Synchronize network packet crafting tool(DOS SYN Hping),and Network Mapper Operating System Detection(NMAP OS DETECTION).The experimental analysis reveals a significant improvement over existing detection systems,significantly enhancing IoT security *** our experimental analysis,we have demonstrated a remarkable enhancement in comparison to existing detection systems,which significantly strength-ens the security standards of *** model effectively addresses the need for advanced,dependable,and adaptable security solutions,serving as a symbol of the power of deep learning in strengthening IoT ecosystems amidst the constantly evolving cyber threat *** achievemen

关键词： A hybrid deep learning model IoT threat detection real IoT environments cybersecurity attention mechanism

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

OPTIMAL MAINTENANCE AND REPLACEMENT OF EXTRACTION MACHINERY

引用

Journal of systems Science and systems Engineering 2008年第4期17卷 416-431页

作者： Suresh P. SETHI Hong-Mo YEH Rong ZHANG Andrew K.S. JARDINE School of Management the University of Texas at Dallas USA department of information Management Fu Jen Catholic University Taiwan China college of Economics and business administration Chongqing University Chongqing China department of Mechanical and lndustrial Engineering University of Toronto Canada

This paper considers a problem of optimal preventive maintenance and replacement schedule of equipment devoted to extracting resources from known deposits. Typical examples are oil drills, mine shovels, etc. At most one replacement of the existing machinery by a new one is allowed. The problem is formulated as an optimal control problem subject to the state constraint that the remaining deposit at any given time is nonnegative. We show that the optimal preventive maintenance, production rates, and the replacement and salvage times of the existing machinery and the new one, if required, can be obtained by solving sequentially a series of free-end-point optimal control problems. Moreover, an algorithm based on this result is developed and used to solve two illustrative examples.

关键词： Maintenance and replacement optimal control the maximum principle extraction machinery exhaustible resource

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Recent Developments in Authentication Schemes Used in Machine-Type Communication Devices in Machine-to-Machine Communication: Issues and Challenges

引用

Computers, Materials & Continua 2024年第4期79卷 93-115页

作者： Shafi Ullah Sibghat Ullah Bazai Mohammad Imran Qazi Mudassar Ilyas Abid Mehmood Muhammad Asim Saleem Muhmmad Aasim Rafique Arsalan Haider Ilyas Khan Sajid Iqbal Yonis Gulzar Kauser Hameed department of Computer Engineering Balochistan University of Information TechnologyEngineering and Management SciencesQuetta87300Pakistan department of information Technology Balochistan University of Information TechnologyEngineeringand Management SciencesQuetta87300Pakistan department of information systems College of Computer Sciences and Information TechnologyKing Faisal UniversityHofuf in Al-Ahsa31982Saudi Arabia department of Management information systems College of Business AdministrationKing Faisal UniversityHofuf in Al-Ahsa31982Saudi Arabia department of Software Engineering College of ComputingRiphah International UniversityFaisalabad44000Pakistan department of Electrical Engineering Balochistan university of information Technology Engineeringand Management SciencesQuetta87300Pakistan department of Mathematics College of Science Al-ZulfiMajmaah UniversityAl-Majmaah11952Saudi Arabia

Machine-to-machine (M2M) communication plays a fundamental role in autonomous IoT (Internet of Things)-based infrastructure, a vital part of the fourth industrial revolution. Machine-type communication devices(MTCDs) regularly share extensive data without human intervention while making all types of decisions. Thesedecisions may involve controlling sensitive ventilation systems maintaining uniform temperature, live heartbeatmonitoring, and several different alert systems. Many of these devices simultaneously share data to form anautomated system. The data shared between machine-type communication devices (MTCDs) is prone to risk dueto limited computational power, internal memory, and energy capacity. Therefore, securing the data and devicesbecomes challenging due to factors such as dynamic operational environments, remoteness, harsh conditions,and areas where human physical access is difficult. One of the crucial parts of securing MTCDs and data isauthentication, where each devicemust be verified before data transmission. SeveralM2Mauthentication schemeshave been proposed in the literature, however, the literature lacks a comprehensive overview of current M2Mauthentication techniques and the challenges associated with them. To utilize a suitable authentication schemefor specific scenarios, it is important to understand the challenges associated with it. Therefore, this article fillsthis gap by reviewing the state-of-the-art research on authentication schemes in MTCDs specifically concerningapplication categories, security provisions, and performance efficiency.

关键词： Authentication cyber security internet of things machine-type communication devices machine-to-machine communication

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

A Deep Two-state Gated Recurrent Unit for Particulate Matter (PM_(2.5)) Concentration Forecasting

引用

Computers, Materials & Continua 2022年第5期71卷 3051-3068页

作者： Muhammad Zulqarnain Rozaida Ghazali Habib Shah Lokman Hakim Ismail Abdullah Alsheddy Maqsood Mahmud Faculty of Computer Science and information Technology Universiti Tun Hussein Onn MalaysiaBatu PahatJohorMalaysia college of Computer Science King Khalid UniversityAbhaSaudi Arabia college of Computer and information Sciences Imam Mohammad Ibn Saud Islamic UniversityRiyadhSaudi Arabia department of Management information systems College of Business AdministrationImam Abdulrahman Bin Faisal University31441DammamSaudi Arabia

Air pollution is a significant problem in modern societies since it has a serious impact on human health and the *** Matter(PM_(2.5))is a type of air pollution that contains of interrupted elements with a diameter less than or equal to 2.5 *** risk assessment and epidemiological investigations,a better knowledge of the spatiotemporal variation of PM_(2.5) concentration in a constant space-time area is *** spatiotemporal interpolation approaches commonly relying on robust presumption by limiting interpolation algorithms to those with explicit and basic mathematical expression,ignoring a plethora of hidden but crucial manipulating *** advanced deep learning approaches have been proposed to forecast Particulate Matter(PM_(2.5)).Recurrent neural network(RNN)is one of the popular deep learning architectures which is widely employed in PM_(2.5) concentration *** this research,we proposed a Two-state Gated Recurrent Unit(TS-GRU)for monitoring and estimating the PM_(2.5) concentration forecasting *** proposed algorithm is capable of considering both spatial and temporal hidden affecting elements *** tested our model using data from daily PM_(2.5) dimensions taken in the contactual southeast area of the United states in *** the studies,three evaluation matrices were utilized to compare the overall performance of each algorithm:Mean Absolute Error(MAE),Root Mean Square Error(RMSE),and Mean Absolute Percentage Error(MAPE).The experimental results revealed that our proposed TS-GRU model outperformed compared to the other deep learning approaches in terms of forecasting performance.

关键词： Deep learning PM_(2.5)forecasting air pollution two-state GRU

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

DESIGNING A HYBRID INTELLIGENT MINING SYSTEM FOR CREDIT RISK EVALUATION

引用

Journal of systems Science & Complexity 2008年第4期21卷 527-539页

作者： Lean YU Shouyang WANG Fenghua WEN Kin Keung LAI Shaoyi HE Institute of systems Science Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing 100190 China. School of Economy and Management Changsha University of Science ~ Technology Changsha 410076 China. department of Management Sciences City University of Hong Kong Tat Chee Avenue Kowloon Hong Kong. department of information systems and Operations Management College of Business Administration Cali fornia State University San Marcos San Marcos CA 92096-0001 USA.

In this study, a novel hybrid intelligent mining system integrating rough sets theory and support vector machines is developed to extract efficiently association rules from original information table for credit risk evaluation and analysis. In the proposed hybrid intelligent system, support vector machines are used as a tool to extract typical features and filter its noise, which are different from the previous studies where rough sets were only used as a preprocessor for support vector machines. Such an approach could reduce the information table and generate the final knowledge from the reduced information table by rough sets. Therefore, the proposed hybrid intelligent system overcomes the difficulty of extracting rules from a trained support vector machine classifier and possesses the robustness which is lacking for rough-set-based approaches. In addition, the effectiveness of the proposed hybrid intelligent system is illustrated with two real-world credit datasets.

关键词： Credit risk evaluation hybrid intelligent system rough sets support vector machine.

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

欢迎您,

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

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

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

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

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：