Fault diagnosis and prognosis of industrial equipment become increasingly important for improving the quality of manufacturing and reducing the cost for product testing. This paper advocates that computer-based diagno...
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Fault diagnosis and prognosis of industrial equipment become increasingly important for improving the quality of manufacturing and reducing the cost for product testing. This paper advocates that computer-based diagnosis systems can be built based on sensor information and by using case-based reasoning methodology. The intelligent signal analysis methods are outlined in this context. We then explain how case-based reasoning can be applied to support diagnosis tasks and four application examples are given as illustration. Further, discussions are made on how CBR systems can be integrated with machine learning techniques to enhance its performance in practical scenarios. Fault Diagnostics, Case-based Reasoning, Sensors, Signal Processing, Feature Extraction, Crack Detection, Process Monitoring, Artificial.
Force between static point particles coupled to a classical ultramassive scalar field is calculated. The field potential is proportional to the modulus of the field. It turns out that the force exactly vanishes when t...
Force between static point particles coupled to a classical ultramassive scalar field is calculated. The field potential is proportional to the modulus of the field. It turns out that the force exactly vanishes when the distance between the particles exceeds certain finite value. Moreover, each isolated particle is surrounded by a compact cloud of the scalar field that completely screens its scalar charge.
We propose algorithms for efficiently maintaining a constant-approximate minimum connected dominating set (MCDS) of a geometric graph under node insertions and deletions, and under node mobility. Assuming that two nod...
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This paper discusses the unification of service composition based on formal specifications. The approach aims for a unified execution of service compositions that can be modeled by various specification languages cove...
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This paper discusses the unification of service composition based on formal specifications. The approach aims for a unified execution of service compositions that can be modeled by various specification languages covering different modeling paradigms. The unification of service composition models is realized based on formal grammars whereas the unification of service composition execution is realized based on formal queued automata. The approach introduces a classification of context-sensitive grammars for determining an optimized automaton class for the execution of service compositions. Finally, a prototype providing transformations of various modeling languages to formal grammars as well as the grammar-based execution of service compositions is presented.
作者：
Janakiraman MoorthyRangin LahiriNeelanjan BiswasDipyaman SanyalJayanthi RanjanKrishnadas NanathPulak Ghosh(Coordinator) Director and Professor of Marketing at the Institute of Management Technology
Dubai. Earlier he was Professor of Marketing at the IIM Calcutta and IIM Lucknow. He received his PhD from IIM Ahmedabad. His recent research papers were published in the leading scholarly ournals such as Marketing Science British Food Journal Journal of Information Technology Case and Application Research Journal of Database Marketing & Customer Strategy Management. He has wide experience in the banking and investment industry. He was earlier the Global Research and Project Director of the Institute for Customer Relationship Management Atlanta USA. He was the Convener of the prestigious CAT Exam 2011. e-mail: Practice Director
leading Atos India's CRM practice while supporting Strategic Business Development for North American Market. With an experience of more than 15 years Rangin has worked extensively as a Business Consultant in Information Technology (Sales Automation Marketing & Service Management area) Customer Data Management and CRM Analytics. e-mail: Business Consultant at Atos with extensive experience in Business Analysis
Risk Management Analytics Business Development Presales Solution Ideation on Enterprise Data Management Enterprise Reference Data and Master Data Management area. e-mail: founder and CEO of dono consulting
a boutique quantitative analytics and investment research firm. He has worked for leading financial firms in New York and India including Dow Jones Blackstone Sorin Capital (VP Quantitative Modeling) and Thomson Reuters (Head of Real Estate Analytics). A CFA charter holder and Commonwealth Scholar Deep has an MS (Applied Economics) from University of Texas Dallas and an MA (Economics) from Jadavpur University e-mail: Professor in the Information Systems Group of the Institute of Management Technology
Ghaziabad. Her PhD is in the field of data mining from Jamia Millia Islamia Central University India. She has published five edited books. She is serving on the editorial b
For some graph classes, most notably real-world road networks, shortest path queries can be answered very efficiently if the graph is preprocessed into a contraction hierarchy. The preprocessing algorithm contracts no...
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In this paper, two approaches, Hierarchical Fuzzy Signature (HFS) and Neuro-Fuzzy Hierarchical Hybrid (NFHH), have been proposed for piloting a Quality Management System (QMS). These approaches have been applied for r...
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In this paper, two approaches, Hierarchical Fuzzy Signature (HFS) and Neuro-Fuzzy Hierarchical Hybrid (NFHH), have been proposed for piloting a Quality Management System (QMS). These approaches have been applied for real company which presents a major problem for controlling the quality level of production. HFS structure has reduced complexity in the number of input and output meta-levels of hierarchy. Also NFHH model has presented better performance in terms of precision and number of parameters without losing the universal approximation property of neural networks (NN) and fuzzy systems.
In this article the authors propose the neural network (NN) classifier for identification of brain perfusion abnormality type and its localization in CBF and CBV dynamic brain perfusion maps. The approach is based on ...
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This article presents an innovative GPU-based solution for visualization of perfusion abnormalities detected in dynamic brain perfusion computer tomography (dpCT) maps in an augmented-reality environment. This new gra...
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The main contribution of this article is a new method of segmentation of carotid artery based on original authors inner path finding algorithm and active contours without edges segmentation method for vessels wall det...
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