International Journal of Reliability Quality and Safety Engineering最新文献_第8页

Research on Edge Detection and Image Segmentation of Cabinet Region Based on Edge Computing Joint Image Detection Algorithm 基于边缘计算联合图像检测算法的橱柜区域边缘检测与图像分割研究

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International Journal of Reliability Quality and Safety Engineering Pub Date : 2022-09-21 DOI: 10.1142/s0218539322400022

Gao Huixin, Zhou Gang, Cao Yang, Luo Zhiyuan, Shen Zhicheng, A. J. Gnana Malar

{"title":"Research on Edge Detection and Image Segmentation of Cabinet Region Based on Edge Computing Joint Image Detection Algorithm","authors":"Gao Huixin, Zhou Gang, Cao Yang, Luo Zhiyuan, Shen Zhicheng, A. J. Gnana Malar","doi":"10.1142/s0218539322400022","DOIUrl":"https://doi.org/10.1142/s0218539322400022","url":null,"abstract":"Image segmentation (IE) in several disciplines of image processing and computer vision is an essential topic. Segmentation splits a picture into the areas or items that it constitutes. Image segmentation may be achieved with many approaches, some easier than others because of sophisticated programming requirements. The most common technique for segmenting pictures is edge detection (ED) based on sudden (locomotive) intensity fluctuations. This paper aims to study edge detection approaches for the division of images and acquired experimental findings, Sobel, Prewitt, Robert, CannyLoG (Laplacian of Gaussian). It is vital to ensure that picture segmentation algorithms deliver correct results quickly and efficiently for computer vision to reach its full potential. Computer vision approaches require more investigation in hierarchical architectural IoT networks created for seeing the world. In this work, the new way to provide joint image detection (JID) algorithm is to provide multi-scaling approaches for edge detection and segmentation using IoT edge computing (EC). This JID-EC method avoids the requirement to choose and track the edge explicitly. This study provides an overview of fundamental ideas, techniques, and algorithms common to segment images and edge detection, focusing on the segmentation and visualization of joint-articular cartilage images. The reason for this failure is that it is an image noise-sensitive high pass filter. The need for improved algorithms to meet a suitable value of low and high thresholds should thus be stressed for picture noise such as a canny edge, and the performance is achieved with an efficiency of 95.2%.","PeriodicalId":45573,"journal":{"name":"International Journal of Reliability Quality and Safety Engineering","volume":"95 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2022-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83692158","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}

引用次数: 2

Reliability and Sensitivity Analyses of an Unreliable Retrial Machine Repair System with Warm Standby Switching Failure 热备切换故障下不可靠重审机维修系统的可靠性和灵敏度分析

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International Journal of Reliability Quality and Safety Engineering Pub Date : 2022-08-31 DOI: 10.1142/s0218539321410084

Kuo-Hsiung Wang, T. Yen, Chia-Huang Wu

引用次数: 2

Preface: Special Issue of Reliability Modeling and Applications 前言:可靠性建模与应用特刊

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International Journal of Reliability Quality and Safety Engineering Pub Date : 2022-08-01 DOI: 10.1142/s0218539322020016

Xufeng Zhao, C. Qian

引用次数: 0

Research and Application of Tobacco Based on Leaf Nicotine Value to Realize Redrying Homogenization Processing 基于烟叶烟碱值实现再干燥均质加工的研究与应用

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International Journal of Reliability Quality and Safety Engineering Pub Date : 2022-07-30 DOI: 10.1142/s0218539322400034

Hao Liu, Xubin Xiao, Hongguang Liu, Zhihua Li, XiaoJian He

{"title":"Research and Application of Tobacco Based on Leaf Nicotine Value to Realize Redrying Homogenization Processing","authors":"Hao Liu, Xubin Xiao, Hongguang Liu, Zhihua Li, XiaoJian He","doi":"10.1142/s0218539322400034","DOIUrl":"https://doi.org/10.1142/s0218539322400034","url":null,"abstract":"The main component is the manufacturing process of actual tobacco crushing and the redrying procedure. As a result, it requires a high level of overall stability. People should make sure the maintenance and repair system is appropriately considered as a significant task in redrying. Various flavors, including black and green, were tested for tobacco consumption. According to the researchers who tested for tobacco consumption, the amount of nicotine in tea leaves is proved to be highly varying in some cases, much higher than that found in Solanaceae fruits. Here, describing inexpensive redrying purification for homogenization process (IRPHP), with this technique, colicins can be recovered with a higher detection rate and nicotine levels can be reduced that can be used on food. After [Formula: see text]-means cluster verification, one nicotine leaf may be precisely split into several zones for redrying the distribution of exhaust tobacco aroma components (TACs) in various global locations. In general, these findings give essential information to aid in the efficient harvesting and redrying of tobacco plants. Additionally, these data imply that this approach may be used to determine the chemical distributions in leaves that do not have the same arrangement as tobacco leaves.","PeriodicalId":45573,"journal":{"name":"International Journal of Reliability Quality and Safety Engineering","volume":"1 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2022-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90867422","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}

引用次数: 0

A new fault diagnosis method for quality control of electromagnet based on T-S fault tree and grey relation 基于T-S故障树和灰色关联的电磁铁质量控制故障诊断新方法

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International Journal of Reliability Quality and Safety Engineering Pub Date : 2022-07-19 DOI: 10.1142/s0218539321410060

J. Pang, Jinkun Dai, Yong Li

引用次数: 0

Algorithm for Computing the System Signatures of Linear and Circular Connected-(1,2)-or-(2,1)-out-of-(m,n):F Lattice Systems 线性和圆形连接-(1,2)-或-(2,1)-out-of-(m,n):F格系系统签名的计算算法

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International Journal of Reliability Quality and Safety Engineering Pub Date : 2022-07-19 DOI: 10.1142/s0218539321410072

Taishin Nakamura, Hisashi Yamamoto

引用次数: 1

Analysis of social integration through inspection policy 通过检查政策分析社会整合

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International Journal of Reliability Quality and Safety Engineering Pub Date : 2022-07-19 DOI: 10.1142/s0218539321410059

Takahito Araki, M. Kimura, T. Nakagawa

引用次数: 0

An approach to improve asset maintenance and management priorities using machine learning techniques 一种使用机器学习技术改善资产维护和管理优先级的方法

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International Journal of Reliability Quality and Safety Engineering Pub Date : 2022-07-03 DOI: 10.1080/09617353.2022.2142011

A. H. Nithin, Michael Hobbs, S. Sriramula, Yaji Sripada

{"title":"An approach to improve asset maintenance and management priorities using machine learning techniques","authors":"A. H. Nithin, Michael Hobbs, S. Sriramula, Yaji Sripada","doi":"10.1080/09617353.2022.2142011","DOIUrl":"https://doi.org/10.1080/09617353.2022.2142011","url":null,"abstract":"Abstract Numerous services are available today to develop an optimised asset management solution to enhance asset operations by improving the system availability, decreasing down-time and operation and maintenance costs. Three cases of engineering problems are explored in this paper, with data-driven machine learning solutions proposed for these problems. The first case refers to the labour-intensive nature of criticality analysis which are used in asset management to prioritise assets. A machine learning solution is proposed by the development of a trained criticality analysis model, with a classification error of 12.35%, which could help in a better prediction of the end result by automating the process i.e. training the model. The second case looks at an application of machine learning on asset health prediction by analysing failure patterns and parameters for a machine. The model was evaluated with an error loss of 0.0024. The third case looks at an integration of the priorities related to asset maintenance and management through the development of a text classification machine learning service selector (landscape) tool and explores improvising the end-user selection of the services based on their challenges and perceived pain-points related to asset management. The model was evaluated with an accuracy of 84%.","PeriodicalId":45573,"journal":{"name":"International Journal of Reliability Quality and Safety Engineering","volume":"3 1","pages":"151 - 169"},"PeriodicalIF":0.8,"publicationDate":"2022-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82419262","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}

引用次数: 0

Scheming of reliability sampling plans with some lifetime distributions based on percentiles estimation using intervened Poisson characteristics 基于介入泊松特征的基于百分位数估计的寿命分布可靠性抽样方案的设计

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International Journal of Reliability Quality and Safety Engineering Pub Date : 2022-07-03 DOI: 10.1080/09617353.2022.2121478

Pradeepa Veerakumari Kumarasamy, Asif T. Thottathil

{"title":"Scheming of reliability sampling plans with some lifetime distributions based on percentiles estimation using intervened Poisson characteristics","authors":"Pradeepa Veerakumari Kumarasamy, Asif T. Thottathil","doi":"10.1080/09617353.2022.2121478","DOIUrl":"https://doi.org/10.1080/09617353.2022.2121478","url":null,"abstract":"Abstract In industry, the practice of determining the performance of a product by intervening with the normal working conditions of the manufacturing process is an acceptable method. When reliability is a key quality factor, the reliability single sampling plan is generally used to optimise sample size and estimate time characteristics. The application of Intervened Poisson Distribution (IPD) and some of the lifetime distributions are used in this article to implement a reliability sampling plan. The IPD can be used as a model for counting the defective items in an appropriate situation and the defectiveness will be determined with the help of lifetime distributions. The minimum sample size required to accept a lot and the estimation of the true percentile time of the accepted lots according to the magnitude of the intervention parameter can be found using IPD associated with the Rayleigh Distribution (RD), Exponentiated Rayleigh Distribution (ERD) and Inverse Rayleigh Distribution (IRD). The minimum sample size is necessary to ensure the specified life percentile is obtained under a consumer risk. The operating characteristic (OC) values and estimated percentile time of an accepted lot are presented.","PeriodicalId":45573,"journal":{"name":"International Journal of Reliability Quality and Safety Engineering","volume":"21 1","pages":"170 - 192"},"PeriodicalIF":0.8,"publicationDate":"2022-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75206594","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}

引用次数: 0

Managing Editor’s remarks 总编辑评论

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International Journal of Reliability Quality and Safety Engineering Pub Date : 2022-07-03 DOI: 10.1080/09617353.2022.2166704

Jacqueline A. Ward

引用次数: 0