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LSTM Based Neural Network Model for Anomaly Event Detection in Care-Independent Smart Homes

Computer Modeling in Engineering & Sciences 2024年第9期140卷 2689-2706页

作者： Brij B.Gupta Akshat Gaurav Razaz Waheeb Attar Varsha Arya Ahmed Alhomoud Kwok Tai Chui Department of Computer Science and Information Engineering Asia UniversityTaichung413TaiwanChina Symbiosis Centre for Information Technology(SCIT) Symbiosis International UniversityPune411057India Center for Interdisciplinary Research University of Petroleum and Energy Studies(UPES)Dehradun248007India Computer Engineering Ronin InstituteMontclairNJ 07043USA Management Department College of Business AdministrationPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of business administration Asia UniversityTaichung413TaiwanChina Department of Electrical and Computer Engineering Lebanese American UniversityBeirut1102Lebanon Department of Computer Sciences Faculty of Computing and Information TechnologyNorthern Border UniversityRafha91911Saudi Arabia School of Science and Technology Hong Kong Metropolitan University(HKMU)Hong KongChina

This study introduces a long-short-term memory(LSTM)-based neural network model developed for detecting anomaly events in care-independent smart homes,focusing on the critical application of elderly fall *** balances the dataset using the Synthetic Minority Over-sampling Technique(SMOTE),effectively neutralizing bias to address the challenge of unbalanced datasets prevalent in time-series classification *** proposed LSTM model is trained on the enriched dataset,capturing the temporal dependencies essential for anomaly *** model demonstrated a significant improvement in anomaly detection,with an accuracy of 84%.The results,detailed in the comprehensive classification and confusion matrices,showed the model’s proficiency in distinguishing between normal activities and *** study contributes to the advancement of smart home safety,presenting a robust framework for real-time anomaly monitoring.

关键词： LSTM neural networks anomaly detection smart home health-care elderly fall prevention

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Optimized Phishing Detection with Recurrent Neural Network and Whale Optimizer Algorithm

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Computers, Materials & Continua 2024年第9期80卷 4895-4916页

作者： Brij Bhooshan Gupta Akshat Gaurav Razaz Waheeb Attar Varsha Arya Ahmed Alhomoud Kwok Tai Chui Department of Computer Science and Information Engineering Asia UniversityTaichung413Taiwan Symbiosis Centre for Information Technology(SCIT) Symbiosis International UniversityPuneMaharashtra411057India Center for Interdisciplinary Research University of Petroleum and Energy Studies(UPES)Dehradun248007India Ronin Institute MontclairNJ 07043USA Management Department College of Business AdministrationPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of business administration Asia UniversityTaichung413Taiwan Department of Electrical and Computer Engineering Lebanese American UniversityBeirut1102Lebanon Department of Computer Sciences Faculty of Computing and Information TechnologyNorthern Border UniversityRafha91911Saudi Arabia Department of Electronic Engineering and Computer Science Hong Kong Metropolitan University(HKMU)HomantinHong KongChina

Phishing attacks present a persistent and evolving threat in the cybersecurity land-scape,necessitating the development of more sophisticated detection *** machine learning approaches to phishing detection have relied heavily on feature engineering and have often fallen short in adapting to the dynamically changing patterns of phishingUniformResource Locator(URLs).Addressing these challenge,we introduce a framework that integrates the sequential data processing strengths of a Recurrent Neural Network(RNN)with the hyperparameter optimization prowess of theWhale Optimization Algorithm(WOA).Ourmodel capitalizes on an extensive Kaggle dataset,featuring over 11,000 URLs,each delineated by 30 *** WOA’s hyperparameter optimization enhances the RNN’s performance,evidenced by a meticulous validation *** results,encapsulated in precision,recall,and F1-score metrics,surpass baseline models,achieving an overall accuracy of 92%.This study not only demonstrates the RNN’s proficiency in learning complex patterns but also underscores the WOA’s effectiveness in refining machine learning models for the critical task of phishing detection.

关键词： Phishing detection Recurrent Neural Network(RNN) Whale Optimization Algorithm(WOA) cybersecurity machine learning optimization

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Optimal Machine Learning Enabled Intrusion Detection in Cyber-Physical System Environment

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Computers, Materials & Continua 2022年第9期72卷 4691-4707页

作者： Bassam A.Y.Alqaralleh Fahad Aldhaban Esam A.AlQarallehs Ahmad H.Al-Omari MIS Department College of Business AdministrationUniversity of Business and TechnologyJeddah21448Saudi Arabia School of Engineering Princess Sumaya University for TechnologyAmman11941Jordan Faculty of Science Computer Science DepartmentNorthern Border UniversityArar91431Saudi Arabia

Cyber-attacks on cyber-physical systems(CPSs)resulted to sensing and actuation misbehavior,severe damage to physical object,and safety *** learning(ML)models have been presented to hinder cyberattacks on the CPS environment;however,the non-existence of labelled data from new attacks makes their detection quite *** Detection System(IDS)is a commonly utilized to detect and classify the existence of intrusions in the CPS environment,which acts as an important part in secure CPS *** developments in deep learning(DL)and explainable artificial intelligence(XAI)stimulate new IDSs to manage cyberattacks with minimum complexity and high *** this aspect,this paper presents an XAI based IDS using feature selection with Dirichlet Variational Autoencoder(XAIIDS-FSDVAE)model for *** proposed model encompasses the design of coyote optimization algorithm(COA)based feature selection(FS)model is derived to select an optimal subset of ***,an intelligent Dirichlet Variational Autoencoder(DVAE)technique is employed for the anomaly detection process in the CPS ***,the parameter optimization of the DVAE takes place using a manta ray foraging optimization(MRFO)model to tune the parameter of the *** order to determine the enhanced intrusion detection efficiency of the XAIIDS-FSDVAE technique,a wide range of simulations take place using the benchmark *** experimental results reported the better performance of the XAIIDSFSDVAE technique over the recent methods in terms of several evaluation parameters.

关键词： Cyber-physical systems explainable artificial intelligence deep learning security intrusion detection metaheuristics

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Optimal Deep Learning Based Inception Model for Cervical Cancer Diagnosis

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Computers, Materials & Continua 2022年第7期72卷 57-71页

作者： Tamer AbuKhalil Bassam A.Y.Alqaralleh Ahmad H.Al-Omari Computer Science Department Faculty of Information TechnologyAl Hussein bin Talal UniversityMa’an71111Jordan MIS Department College of Business AdministrationUniversity of Business and TechnologyJeddah21448Saudi Arabia Faculty of Science Computer Science DepartmentNorthern Border UniversityArar91431Saudi Arabia

Prevention of cervical cancer becomes essential and is carried out by the use of Pap smear *** smear test analysis is laborious and tiresome work performed visually using a ***,automated cervical cancer diagnosis using automated methods are *** paper designs an optimal deep learning based Inception model for cervical cancer diagnosis(ODLIM-CCD)using pap smear *** proposed ODLIM-CCD technique incorporates median filtering(MF)based pre-processing to discard the noise and Otsu model based segmentation ***,deep convolutional neural network(DCNN)based Inception with Residual Network(ResNet)v2 model is utilized for deriving the feature ***,swallow swarm optimization(SSO)based hyperparameter tuning process is carried out for the optimal selection of ***,recurrent neural network(RNN)based classification process is done to determine the presence of cervical cancer or *** order to showcase the improved diagnostic performance of the ODLIM-CCD technique,a series of simulations occur on benchmark test images and the outcomes highlighted the improved performance over the recent approaches with a superior accuracy of 0.9661.

关键词： Median filtering convolutional neural network pap smear cervical cancer

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Trends of Temperature Extremes in Summer and Winter during 1971–2013 in China

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Atmospheric and Oceanic Science Letters 2015年第4期8卷 220-225页

作者： HUANG Ling CHEN Ai-Fang ZHU Yun-Hua WANG Hong-Lin HE Bin college of Global Change and Earth System Science Beijing Normal University college of business administration Huaqiao University

The diurnal temperature range(DTR) has decreased dramatically in recent decades, but it is not yet obvious whether the extreme values of DTR have also reduced. Based on the daily maximum and minimum temperature data of 653 stations in China, a set of monthly indices of warm extremes, cold extremes, and DTR extremes in summer(June, July, August) and winter(December, January, February) were studied for spatial and temporal features during the period 1971–2013. Results show that the incidence of warm extremes has been increasing in most parts of China, while the opposite trend was found in the cold extremes for summer and winter months. Both increasing and decreasing trends of monthly DTR extremes were identified in China for both seasons. For high DTR extremes, decreasing trends were identified in northern China for both seasons, but increasing trends were found only in southern China in summer, while in winter, they were found in central China. Monthly low DTR extreme indices demonstrated consistent positive trends in summer and winter, while significant increases(P < 0.05) were identified for only a few stations.

关键词： temperature extremes diurnal temperature range temperature trend spatial and temporal features China

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Dynamic connectedness between stock markets in the presence of the COVID‑19 pandemic:does economic policy uncertainty matter?

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Financial Innovation 2021年第1期7卷 273-299页

作者： Manel Youssef Khaled Mokni Ahdi Noomen Ajmi college of business administration Northern Border UniversityArar 91431Saudi Arabia Institut Superieur de Gestion de Gabes Gabes University6002 GabesTunisia Department of business administration College of Science and Humanities in SlayelPrince Sattam Bin Abdulaziz UniversityAl‑KharjSaudi Arabia ESC de Tunis Manouba UniversityManoubaTunisia

This study investigates the dynamic connectedness between stock indices and the effect of economic policy uncertainty(EPU)in eight countries where COVID-19 was most widespread(China,Italy,France,Germany,Spain,Russia,the US,and the UK)by implementing the time-varying VAR(TVP-VAR)model for daily data over the period spanning from 01/01/2015 to 05/18/*** showed that stock markets were highly connected during the entire period,but the dynamic spillovers reached unprecedented heights during the COVID-19 pandemic in the first quarter of ***,we found that the European stock markets(except Italy)transmitted more spillovers to all other stock markets than they received,primarily during the COVID-19 *** analysis using a nonlinear framework showed that the dynamic connectedness was more pronounced for negative than for positive ***,findings showed that the direction of the EPU effect on net connectedness changed during the pandemic onset,indicating that information spillovers from a given market may signal either good or bad news for other markets,depending on the prevailing economic *** results have important implications for individual investors,portfolio managers,policymakers,investment banks,and central banks.

关键词： Stock markets Dynamic connectedness COVID-19 pandemic Economic policy uncertainty TVP-VAR model

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国外消费者涉入度的实证文献述评——以清真食品为例

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世界农业 2016年第9期 73-79页

作者：王瑜 Mohammed Rawwas 北方民族大学商学院 university of northern iowa college of business administration

通过对2003—2013年的57篇国外关于清真食品消费者涉入度实证研究的文献述评,从衡量纬度、建模方法与影响因素3个方面对这些文献进行了总结、归纳和分析。对于尚处于研究起步阶段的中国而言,这有助于形成对少数民族消费者心理、认知过... 详细信息

通过对2003—2013年的57篇国外关于清真食品消费者涉入度实证研究的文献述评,从衡量纬度、建模方法与影响因素3个方面对这些文献进行了总结、归纳和分析。对于尚处于研究起步阶段的中国而言,这有助于形成对少数民族消费者心理、认知过程、行为决策规律及其实证研究的基本认识和研究方向。

关键词：消费者涉入度清真食品实证文献述评

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A Frisch-Newton Algorithm for Sparse Quantile Regression

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Acta Mathematicae Applicatae Sinica 2005年第2期21卷 225-236页

作者： Roger Koenker Pin Ng Department of Economics University of Illinois at Urbana-Champaign IL 61820 USACollege of Business Administration Northern Arizona University 70 McConnell Dr P.O. Box 15066 FlagstaffAZ 86011-5066. USA.

Recent experience has shown that interior-point methods using a log barrierapproach are far superior to classical simplex methods for computing solutions to large parametricquantile regression problems. In many large empirical applications, the design matrix has a verysparse structure. A typical example is the classical fixed-effect model for panel data where theparametric dimension of the model can be quite large, but the number of non-zero elements is quitesmall. Adopting recent developments in sparse linear algebra we introduce a modified version of theFrisch-Newton algorithm for quantile regression described in Portnoy and Koenker[28]. The newalgorithm substantially reduces the storage (memory) requirements and increases computational *** modified algorithm also facilitates the development of nonparametric quantile regressionmethods. The pseudo design matrices employed in nonparametric quantile regression smoothing areinherently sparse in both the fidelity and roughness penalty components. Exploiting the sparsestructure of these problems opens up a whole range of new possibilities for multivariate smoothingon large data sets via ANOVA-type decomposition and partial linear models.

关键词： Quantile regression interior-point algorithm sparse linear algebra

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少数民族特需品的消费者零售商选择影响因素研究

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技术经济与管理研究 2018年第3期 20-24页

作者：王瑜 Mohammed Rawwas 北方民族大学商学院 university of northern iowa college of business administration

清真牛羊肉作为民族特需商品,在民族地区经济发展中起着越来越重要的作用。文章通过对甘肃、宁夏和青海三个省区进行抽样调查,建立计量模型,实证分析了消费者对生鲜类清真牛羊肉产品零售商选择的影响因素。结果表明,消费者个人特征、消... 详细信息

清真牛羊肉作为民族特需商品,在民族地区经济发展中起着越来越重要的作用。文章通过对甘肃、宁夏和青海三个省区进行抽样调查,建立计量模型,实证分析了消费者对生鲜类清真牛羊肉产品零售商选择的影响因素。结果表明,消费者个人特征、消费者搜寻属性和信任属性三类特征因素在统计学上有较高的显著性。说明少数民族消费者更倾向于到品牌专卖店和超市选购清真牛羊肉,然而城乡和地区差异也造成了消费者对于零售商的选择差异。

关键词：民族特需品零售商品牌专卖行为选择

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Increasing Wages,Factor Substitution,and Cropping Pattern Changes in China

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China & World Economy 2023年第5期31卷 190-214页

作者： Zhoufu Yan Shurui Zhang Fangwei Wu Binlei Gong college of Economics and Management Shanghai Ocean UniversityChina. School of business administration Northeastern UniversityChina Institute for Urban-Rural Development Shanghai University of Finance and EconomicsChina China Academy for Rural Development and School of Public Affairs Zhejiang UniversityChina

This article analyzed the influence of increasing wages on cropping patterns from theoretical and empirical *** results showed that the increasing labor cost provided a significant incentive to adjust the grain cropping pattern,which increased the production of the three major cereal grains but reduced the production of other grain *** wages had a significant negative impact on cash *** laborintensive cash crops experienced a larger negative impact in the context of increasing *** increase in labor costs also had a negative impact on the proportion of vegetables produced,which was more evident in northern China.A further mechanism test indicated that factor substitution was a significant reason for cropping pattern changes;this illustrated the substitution of labor by machinery not only between grain crops and cash crops but also among different cash crops.

关键词： cropping pattern changes factor substitution increasing wages production transformation

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