Int. J. Perform. Eng.最新文献

{"title":"Real-Time Prediction of Car Driver's Emotions using Facial Expression with a Convolutional Neural Network-based Intelligent System","authors":"Pawan Wawage, Y. Deshpande","doi":"10.56578/ataiml010104","DOIUrl":"https://doi.org/10.56578/ataiml010104","url":null,"abstract":"When driving, the most crucial factor to consider is your own safety. Driver’s must be kept under observation for any potential harmful act, whether intentional or inadvertent, in order to ensure a safe navigation for a driver. As a result, a real-time emotion detection system for a driver has been developed to detect, exploit, and evaluate the driver's emotional state. This paper discusses how to recognize emotions using facial expressions for application in active security systems for drivers. We discuss our research and development of a Convolutional Neural Network-based intelligent system for face image-based expression classification in this paper.","PeriodicalId":262007,"journal":{"name":"Int. J. Perform. Eng.","volume":"306 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122538975","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Probit Regressive Tversky Indexed Rocchio Convolutive Deep Neural Learning for Legal Document Data Analytics","authors":"Divya Mohan, L. Nair","doi":"10.18201/ijisae.2021.238","DOIUrl":"https://doi.org/10.18201/ijisae.2021.238","url":null,"abstract":"Legal documents data analytics is a very significant process in the field of computational law.Semantically analyzing the documents is more challenging since it’s often more complicated than open domain documents. Efficient document analysis is crucial to current legal applications, such as case-based reasoning, legal citations, and so on. Due to the extensive growth of documents of data, several statistical machine learning methods have been developed for Legal documents data analytics. However, documents are large and highly complex, so the traditional machine learning-based classification models are inefficient for accurate data analytics with minimum time. In order to improve the accurate legal documents data analytics with minimum time, an efficient technique called Probit Regressive Tversky Indexed Rocchio Convolutive Deep Neural Learning (PRTIRCDNL) is introduced. The PRTIRCDNL technique uses the Convolutive Deep neural learning concept to learn the given input with help of many layers and provides accurate classification results. Convolutive Deep Neural Learning uses two different processing steps such as keyword extraction and classification in the different layers such as input, two hidden layers and output layer. Initially, large numbers of legal documents are collected from the dataset. Then the collected legal documents are sent to the input layer of the convolutive deep neural learning. The input legal documents are transferred into the first hidden layer where the keyword extraction process is carried out by applying the Target projective probit Regression. Then the regression function extracts the keywordsbased on frequent occurrence score.Then the extracted keywords are transferred into the second hidden layer where the document classification is performed using the Tversky similarity indexive Rocchio classifier. Likewise, all the legal documents are classified into different classes. The experimental evaluation is carried out using different performancemetrics such as accuracy, precision, recall,F-measure and computational time with respect to the number of legaldocuments collected from the dataset.The observed results confirmed that the presented PRTIRCDNL techniqueprovides the better performance interms of achieving higher accuracy, precision, recall and F-measure with minimum computation time.","PeriodicalId":262007,"journal":{"name":"Int. J. Perform. Eng.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133721458","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reliability Analysis of a Metro Braking Control System based on Fuzzy GO Method","authors":"Zheng Li, Jianwei Yang, Dechen Yao, Jinhai Wang, Qicheng Pang","doi":"10.23940/ijpe.20.11.p14.18261834","DOIUrl":"https://doi.org/10.23940/ijpe.20.11.p14.18261834","url":null,"abstract":"","PeriodicalId":262007,"journal":{"name":"Int. J. Perform. Eng.","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132126580","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Online Lithium Battery Fault Diagnosis based on Least Square Support Vector Machine Optimized by Ant Lion Algorithm","authors":"Sibo Li, Yongqin Zhou, Ran Li, Zhao Xu","doi":"10.23940/ijpe.20.10.p15.16371645","DOIUrl":"https://doi.org/10.23940/ijpe.20.10.p15.16371645","url":null,"abstract":"","PeriodicalId":262007,"journal":{"name":"Int. J. Perform. Eng.","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130401525","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Node Evaluation Method based on Multiple Types of Node Status Characteristics in Virtual Network Function Placement","authors":"Ying Hu","doi":"10.23940/ijpe.20.10.p5.15351547","DOIUrl":"https://doi.org/10.23940/ijpe.20.10.p5.15351547","url":null,"abstract":"","PeriodicalId":262007,"journal":{"name":"Int. J. Perform. Eng.","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123246483","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Framework to Facilitate Automated Assembly Sequence Planning in Design Strategies","authors":"Kolur Deepak Kumar, Sanju Yadav, Anil Kumar Gulvindala, M. R. Bahubalendruni","doi":"10.23940/ijpe.20.10.p3.15171524","DOIUrl":"https://doi.org/10.23940/ijpe.20.10.p3.15171524","url":null,"abstract":"","PeriodicalId":262007,"journal":{"name":"Int. J. Perform. Eng.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130158432","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Clustering-based Approach to Segment a Pavement Markings Line","authors":"M. Redondin, L. Bouillaut, D. Daucher","doi":"10.23940/ijpe.20.10.p1.14971508","DOIUrl":"https://doi.org/10.23940/ijpe.20.10.p1.14971508","url":null,"abstract":"The maintenance of road infrastructure is a classic social challenge, especially in the context of a decreasing maintenance budget and the advent of autonomous vehicle traffic. Road markings need an accurate replacement strategy to guarantee that the markings remain perceptible. The retroreflective luminance of markings is currently dynamically quantifiable only by using a retroreflectometer such as the Ecodyn from MLPC. The main objective of this research is to construct a performance-based approach for retroreflective marking replacement adapted to a given road network. This approach involves three main tasks: localize the strategic area based on past inspections, determine an adapted decay model for a given area, and evaluate the economic impact of replacing markings. This paper focuses on the first task. We apply the Agglomerative Hierarchical Clustering (AHC) method to a given dataset to obtain a suitable markings line segmentation. Markings whose retroreflective luminance exhibits similar evolution over time are interpreted to belong to a specific area of the road network. When no follow-up replacement has occurred, a replacement detector deduces the date at which markings were laid from the clusters. The broken center line of the French National Road 4 illustrates the proposed approach; the road is divided into 5 clusters and 34 lifecycles. A study of markings laid in 2008 and replaced in 2012 shows important variations in the decay of the retroreflective luminance as identified by the clustering approach. Even for a single road, an optimal replacement strategy for retroreflective road markings is necessary and is composed of several local maintenance strategies.","PeriodicalId":262007,"journal":{"name":"Int. J. Perform. Eng.","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126297590","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prediction of Order Effects for Landing Signal Officer Guidance Decision-Making based on Quantum Interference","authors":"Hui Li","doi":"10.23940/ijpe.20.09.p7.13831392","DOIUrl":"https://doi.org/10.23940/ijpe.20.09.p7.13831392","url":null,"abstract":"","PeriodicalId":262007,"journal":{"name":"Int. J. Perform. Eng.","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116877835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Using Interpretive Structural Modelling, Fuzzy Analytical Network Process, and Evidential Reasoning to Estimate Fire Risk Onboard Ships","authors":"Sunay P. Pai, R. Gaonkar","doi":"10.23940/ijpe.20.09.p1.13211331","DOIUrl":"https://doi.org/10.23940/ijpe.20.09.p1.13211331","url":null,"abstract":"","PeriodicalId":262007,"journal":{"name":"Int. J. Perform. Eng.","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114576865","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Square-Root Variable Step Size with a lp-Norm Penalty LMS Algorithm for Sparse Channel Estimation","authors":"Aihua Zhang, Wanming Hao, Qiyu Zhou, Bing Ning","doi":"10.23940/ijpe.20.09.p6.13741382","DOIUrl":"https://doi.org/10.23940/ijpe.20.09.p6.13741382","url":null,"abstract":"","PeriodicalId":262007,"journal":{"name":"Int. J. Perform. Eng.","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126881511","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}