دانلود و نمایش مقالات مرتبط با Reliability::صفحه 5
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نتیجه جستجو - Reliability

تعداد مقالات یافته شده: 421
ردیف عنوان نوع
41 Accounting for uncertainties due to high-impact low-probability events in power system development
محاسبه عدم قطعیت های ناشی از رویدادهای با احتمال کم تاثیر زیاد در توسعه سیستم قدرت-2021
In the long-term development of the electric power system, system operators should consider the socio-economic balance between grid investment costs and security of supply, including the risk of power supply interruptions. Cost-benefit analyses conducted for this purpose are associated with many uncertainties but have traditionally focused on the expected value of the net socio-economic benefits of risk-reducing measures. This article focuses on the large uncertainties that are associated with the possible occurrence of high-impact low-probability interruption events (HILP events). The objective is to quantify and visualize the implications of uncertainties due to HILP events in the context of power system development. More specifically, this article describes a method- ology accounting for uncertainties in socio-economic cost-benefit analysis of measures for reducing the risk of HILP events. The methodology accounts for the contributions of both aleatory and epistemic uncertainties and comprises a hybrid probabilistic-possibilistic uncertainty analysis method. Applying the methodology to a real case involving a grid investment decision, it is demonstrated how it provides additional insight compared to conventional cost-benefit analyses considering expected values where uncertainties are not accounted for explicitly. It is furthermore discussed how these results can help to better inform grid development decisions.
keywords: برنامه ریزی سیستم قدرت | تحلیل ریسک | آسیب پذیری | قابلیت اطمینان سیستم قدرت | رویدادهای فوق العاده | Power system planning | Risk analysis | Vulnerability | Power system reliability | Extraordinary events
مقاله انگلیسی
42 Concurrent validity of a custom computer vision algorithm for measuring lumbar spine motion from RGB-D camera depth data
اعتبار همزمان یک الگوریتم بینایی ماشین سفارشی برای اندازه گیری حرکت ستون فقرات کمری از داده های عمق دوربین RGB-D-2021
Using RGB-D cameras as an alternative motion capture device can be advantageous for biomechanical spine motion assessments of movement quality and dysfunction due to their lower cost and complexity. In this study, we evaluated RGB-D camera performance relative to gold-standard optoelectronic motion capture equipment. Twelve healthy young adults (6M, 6F) were recruited to perform repetitive spine flexion-extension, while wearing infrared reflective marker clusters placed over their T10-T12 spinous processes and sacrum, and motion capture data were recorded simultaneously by both systems. Custom computer vision algorithms were developed to extract spine angles from depth data. Root mean square error (RMSE) was calculated for continuous Euler angles, and intra class correlation coefficients (ICC2,1) were calculated between minimum and maximum angles and range of motion in all movement planes. RMSE was low (RMSE ≤ 2.05◦ ) and reliability was good to excellent(0.849 ≤ ICC2,1 ≤ 0.979) across all movement planes. In conclusion, the proposed algorithm for tracking 3Dlumbar spine motion during a sagittal movement task from one RGB-D camera is reliable in comparison to gold- standard motion tracking equipment. Future research will investigate accuracy and validity in a wider variety of movements, and will also investigate the development of novel methods to measure spine motion without using infrared reflective markers.
Keywords: RGB-D cameras | Computer vision | Depth camera | Low back pain | Movement quality
مقاله انگلیسی
43 Strategies for ensuring required service level for COVID-19 herd immunity in Indian vaccine supply chain
راهکارهایی برای اطمینان از سطح خدمات مورد نیاز برای مصونیت گله COVID-19 در زنجیره تأمین واکسن هند-2021
Post COVID-19 vaccine development, nations are now getting ready to face another challenge: how to effectively distribute vaccines amongst the masses to quickly achieve herd immunity against the infection. According to some experts, herd immunity for COVID-19 can be achieved by inoculating 67% of the population. India may find it difficult to achieve this service level target, owing to several infrastructural deficiencies in its vaccine supply chain. Effect of these deficiencies is to cause frequent lead time disruptions. In this context, we develop a novel modelling approach to identify few nodes, which require additional inventory allocations (strategic inventory reserves) to ensure minimum service level (67%) under the possibility of lead time disruptions. Later, through an illustrative case study on distribution of Japanese Encephalitis vaccine, we identify conditions under which strategic inventory reserve policy cannot be practically implemented to meet service level targets. Nodes fulfilling these conditions are termed as critical nodes and must be overhauled structurally to make the implementation of strategic inventory policy practically viable again. Structural overhauling may entail installation of better cold storage facilities, purchasing more quality transport vans, improving reliability of transport network, and skills of cold storage manager by training. Ideally, conditions for identifying critical nodes for COVID-19 vaccine distribution must be derived separately by substituting COVID-19 specific parametric values in our model. In the absence of the required data for COVID-19 scenario, JE specific criteria can be used heuristically to identify critical nodes and structurally overhaul them later for efficiently achieving service level targets.
Keywords: Humanitarian logistics (O) | Structural resilience | COVID-19 | Lead time disruption | Herd immunity | Vaccine supply chain
مقاله انگلیسی
44 A Machine Vision Based Automated Quality Control System for Product Dimensional Analysis
سیستم کنترل کیفیت خودکار مبتنی بر بینایی ماشین برای تجزیه و تحلیل ابعاد محصول-2021
Quality control (QC) in manufacturing processes is critical to ensuring consumers receive products with proper functionality and reliability. Faulty products can lead to additional costs for the manufacturer and damage trust in a brand. A growing trend in QC is the use of machine vision (MV) systems because of their noncontact inspection, high repeatability, and relatively low cost. This paper presents a robust MV system developed to perform comparative dimensional inspection on diversely shaped samples, including additive manufacturing products. The algorithm used performs dimensional inspection on a base product considered to have acceptable dimensions. The perimeter, area, rectangularity, and circularity of the base product are determined using blob analysis on a calibrated camera. These parameters are then used as the standard with which to judge additional products. Each product following is similarly inspected and compared to the base product parameters. A likeness score is calculated for each product, which provides a single value tracking all parameter differences. Finally, the likeness score is considered on whether it is within a threshold, and the product is considered to be acceptable or defective. The proposed MV system has achieved satisfactory results, as discussed in the results section, that would allow it to serve as a dependable and accurate QC inspection system in industrial settings.© 2021 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0)Peer-review under responsibility of the scientific committee of the Complex Adaptive Systems Conference, June 2021.
Keywords: Machine Vision | Quality Control | Dimensional Analysis | Digital Quality | Rectangularity | Circularity | Production | Manufacturing
مقاله انگلیسی
45 The use of fishers’ knowledge to assess benthic resource abundance across management regimes in Chilean artisanal fisheries
استفاده از دانش ماهیگیران برای ارزیابی فراوانی منابع بنیادی در رژیم های مدیریت در شیلات صنایع شیلی-2021
Globally, marine fisheries remain largely unassessed, particularly small-scale fisheries in developing countries. Fishers’ knowledge has proven to be valuable to help fill gaps of information in otherwise unassessed fisheries. This study tested the reliability of fishers’ knowledge to estimate the abundance of two benthic resources, locos (Concholepas concholepas) and keyhole limpets (Fissurella spp.), across two management regimes, territorial user rights for fisheries (TURF) and open access areas (OAA), over ~500 km of coastline in central Chile. Fishers’ knowledge (FK) was quantified using systematic interviews and compared to direct assessments (DA). Addi- tionally, resource abundance was compared between the fishing regimes, considering regions with different concentration of TURFs (and consequently different availability of OAAs). The results show that abundances estimated by the two methods were highly consistent for the most valuable resource (the loco) and quite reliable for the keyhole limpet (for 67% of the comparisons). Abundances of both resources were higher in TURFs than in OAAs, a pattern detected by both FK and DA. The results clearly show the potential of this approach to be applied for the Chilean benthic fisheries over large scales. Interestingly, the results also show significantly lower abundance of locos in OAAs than in TURFs at coves immersed in zones with low availability of open access fishing grounds, suggesting the influence of effort displacement after the implementation of TURFs. This ancillary result highlights the need for seascape management plans that consider the potential, unintended ef- fects of TURFs on resources beyond their boundaries. These findings are of both local and global interest, sup- porting the use of FK to inform management in unassessed small-scale fisheries.
keywords: ادراک فیشر | گرفتن هر واحد تلاش | حقوق کاربر ارضی | جابجایی تلاش | ماهیگیری در مقیاس کوچک | خرگوش | Fishers’ perception | Catch per unit of effort | Territorial user rights | Effort displacement | Small-scale fisheries | Shellfish
مقاله انگلیسی
46 The use of management accounting information by boards of directors to oversee strategy implementation
استفاده از اطلاعات حسابداری مدیریت توسط هیئت مدیره برای نظارت بر استراتژی-2021
Past research has overlooked the specific informational needs and uses of management accounting information by boards of directors, which constitute a distinctive unit of analysis, focusing mainly on organizational actors within the boundaries of the firm. The aim of this study is to examine the use of management accounting information to oversee strategy implementation in the context of governance. Specifically, we intend to establish theoretical properties and propose a measurement model that captures the use of budget, financial and non-financial performance indicators by boards of directors to oversee the strategic plan. To develop the measurement instrument, conceptual specifications of constructs have been established based on a matrix approach that combines (i) the information conveyed by the three management accounting practices, along with (ii) two theoretical properties reflecting board activities, namely monitoring implementation of the strategic plan, and questioning of the strategic plan. The validity and reliability of the instrument have been evaluated and discussed using a rigorous multi-method integrated approach that includes a literature review, exploratory interviews, consultation of experts in management accounting and governance, and survey data collected from three samples of boards of directors.
keywords: استفاده از اطلاعات حسابداری مدیریت | پیاده سازی استراتژی | هیئت مدیره | بودجه | شاخص های عملکرد | حکومت | توسعه یک ابزار نظرسنجی | Use of management accounting information | Strategy implementation | Boards of directors | Budget | Performance indicators | Governance | Development of a survey instrument
مقاله انگلیسی
47 ResTS: Residual Deep interpretable architecture for plant disease detection
ResTS: Residual Deep interpretable architecture for plant disease detection-2021
Recently many methods have been induced for plant disease detection by the influence of Deep Neural Networks in Computer Vision. However, the dearth of transparency in these types of research makes their acquisition in the real-world scenario less approving. We pro- pose an architecture named ResTS (Residual Teacher/Student) that can be used as visualization and a classification technique for diagnosis of the plant disease. ResTS is a tertiary adaptation of formerly suggested Teacher/Student architecture. ResTS is grounded on a Convolutional Neural Network (CNN) structure that comprises two classifiers (ResTeacher and ResStudent) and a decoder. This architecture trains both the classifiers in a reciprocal mode and the conveyed representation between ResTeacher and ResStudent is used as a proxy to envision the dominant areas in the image for categorization. The experiments have shown that the proposed structure ResTS (F1 score: 0.991) has surpassed the Tea- cher/Student architecture (F1 score: 0.972) and can yield finer visualizations of symptoms of the disease. Novel ResTS architecture incorporates the residual connections in all the constituents and it executes batch normalization after each convolution operation which is dissimilar to the formerly proposed Teacher/Student architecture for plant disease diag- nosis. Residual connections in ResTS help in preserving the gradients and circumvent the problem of vanishing or exploding gradients. In addition, batch normalization after each convolution operation aids in swift convergence and increased reliability. All test results are attained on the PlantVillage dataset comprising 54 306 images of 14 crop species.© 2021 China Agricultural University. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. This is an open access article under the CC BY-NC-ND license(http://creativecommons.org/licenses/by-nc-nd/4.0/).
Keywords: Autoencoders | Xception | Deep Learning | Computer Vision | Agriculture
مقاله انگلیسی
48 Accounting for Safety Barriers Degradation in the Risk Assessment of Oil and Gas Systems by Multistate Bayesian Networks
حسابداری برای تخریب موانع ایمنی در ارزیابی ریسک سیستم های نفت و گاز توسط شبکه های چندگانه بیزی-2021
In this paper, a multistate Bayesian Network (BN) is proposed to model and evaluate the functional performance of safety barriers in Oil and Gas plants. The nodes of the BN represent the safety barriers Health States (HSs) and the corresponding conditional Failure Probability (FP) values are assigned. HSs are assessed on the basis of specific Key Performance Indicators (KPIs) related to the barrier characteristics (i.e., technical, procedural or organizational, continuously monitored or event-based characterized). FP values are estimated from failure datasets (for technical barriers), evaluated by Human Reliability Analysis (HRA) (for operational and organi- zational barriers) and assigned by expert elicitation (for barriers lacking data or information). For illustration, the multistate BN model is developed for preventive barriers and applied to a case study related to the potential release of flammable material in the slug catcher of a representative O&G Upstream plant which may lead to major accident scenarios (fire, explosion, toxic dispersion). The results from the case study demonstrate that the multistate BN model is able to account for the safety barriers HS and their associated functional performance.
keywords: ارزیابی ریسک کمی | ارزیابی خطر زندگی | شبکه بیزی | مانع ایمنی | شاخص عملکرد کلیدی | حاشیه ایمنی احتمالی | Quantitative Risk Assessment | Living Risk Assessment | Bayesian Network | Safety Barrier | Key Performance Indicator | Probabilistic Safety Margins
مقاله انگلیسی
49 A knowledge based system for the management of a time stamped uncertain observation set with application on preserving mobility
یک سیستم مبتنی بر دانش برای مدیریت یک زمان، مشاهدات نامطمئن مهر و موم شده با استفاده از کاربرد در حفظ تحرک-2021
The aim of this study is to maintain up-to-date information about the current state of elderly people that are medically followed for risks of fall. Our proposal consists of an individual information database management system that can provide information ondemand on various variables. Such a system has to deal with several sources of uncertainty: lack of information, evolving information and reliability of the information sources. We consider that the features of the person may evolve with time causing uncertainty due to obsolete information. Our context includes new information received bit by bit, with no possibility to collect all required information at once. This paper establishes a first proposal to manage a set of uncertain observations, in order to reduce erroneous and obsolete information while keeping the benefit of previously collected information. We propose an architecture of the system based on a probabilistic knowledge model about the characteristics of interest, a set of decay functions that help to evaluate the confidence degree in previous observations, and a reasoning module to manage new observations, maintain the compatibility and the quality of the observation set. We detail the algorithms of the reasoning module, and the algorithm to update the confidence degree of the observations.
keywords: پیری اطلاعات | اطلاعات نامشخص | کیفیت اطلاعات | مدل گرافیکی احتمالی | سیستم مبتنی بر دانش | استدلال با عدم اطمینان | Information aging | Uncertain information | Information quality | Probabilistic graphical model | Knowledge based system | Reasoning with uncertainty
مقاله انگلیسی
50 Backtracking and prospect on LNG supply chain safety
پیگیری و چشم انداز ایمنی زنجیره تامین LNG-2021
The safety issues of Liquefied Natural Gas (LNG) in production, storage, loading/unloading, transportation/ shipping, and re-gasification have became a major concern, since an accident in the LNG industry would be very costly. Understanding the threat of LNG not only contributes to the process safety and reliability in the research and development (R&D) system, but improves the efficiency of loss prevention, fire protection and emergency responses. As of April 2019, in order to obtain the present status and trend of LNG safety research, basing 1122 documents of the Web of Science database about safety research of LNG as a data source, Cite Space and VOS viewer were used for network knowledge map analysis. A comprehensive knowledge map of LNG safety field was obtained from several research aspects including scientific research power, research hot spots and trends, research knowledge base and frontier. According to the study results, the development of LNG safety research was divided into four stages from 1970s to 2019, China and South Korea made a lot of contributions, and the United States is the most influential. Among them, the research from 2005 to 2019 was the most representative. Current research results indicate that a combination of Formal Safety Assessment (FSA) methodology and Dynamic Procedure for Atypical Scenarios Identification (DyPASI) will fully identify risks; The PHAST and TerEx programs quickly define safety zones. Computational Fluid Dynamics (CFD) software package can provide ac- curate quantitative data for the study of LNG safety. Research on quantitative risk assessment (QRA) and LNG evaporated gas (BOG) has been a hot topic and trend in this field. The application of expansion foam in LNG accident mitigation covers most of the research content in this field, and the optimization of LNG liquefaction process has a great influence on this industry. As the international demand for LNG energy output increases, floating liquefied natural gas (FLNG) will have considerable development, and increasingly researchers attach vital importance to the safety of LNG offshore production integrated unit.
Keywords: Liquefied natural gas | Supply chain | Safety | FLNG | CiteSpace | VOS viewer
مقاله انگلیسی
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