Relevant bibliographies by topics / Diagnostics support

Academic literature on the topic 'Diagnostics support'

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Published: 10 March 2023

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Journal articles on the topic "Diagnostics support"

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Gondzarova, Barbora, and Viera Berzakova. "The Global Diagnostics and Diagnostics of Support Activities." Global Journal of Business, Economics and Management: Current Issues 6, no. 2 (November 4, 2016): 238–42. http://dx.doi.org/10.18844/gjbem.v6i2.1384.

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The article is focused on the business diagnostics and facility management. The aim is to measure the impact of supporting activities in total business results. Selected method of business diagnostics is financial analysis. In the article is performed a shortened financial analysis with focus on the impact which have the supporting activities on the items in balance sheet and on the total costs.© 2015 The Authors. Published by Elsevier B.V. Peer-review under responsibility of Academic World Research and Education Center. Keywords: facilities, costs, analysis, diagnostics, assets
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Nikitin, Yury, Pavol Božek, and Jozef Peterka. "Logical–Linguistic Model of Diagnostics of Electric Drives with Sensors Support." Sensors 20, no. 16 (August 8, 2020): 4429. http://dx.doi.org/10.3390/s20164429.

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The presented paper scientifically discusses the progressive diagnostics of electrical drives in robots with sensor support. The AI (artificial intelligence) model proposed by the authors contains the technical conditions of fuzzy inference rule descriptions for the identification of a robot drive’s technical condition and a source for the description of linguistic variables. The parameter of drive diagnostics for a robotized workplace that is proposed here is original and composed of the sum of vibration acceleration amplitudes ranging from a frequency of 6.3 Hz to 1250 Hz of a one-third-octave filter. Models of systems for the diagnostics of mechatronic objects in the robotized workplace are developed based on examples of CNC (Computer Numerical Control) machine diagnostics and mechatronic modules based on the fuzzy inference system, concluding with a solved example of the multi-criteria optimization of diagnostic systems. Algorithms for CNC machine diagnostics are implemented and intended only for research into precisely determined procedures for monitoring the lifetime of the mentioned mechatronic systems. Sensors for measuring the diagnostic parameters of CNC machines according to precisely determined measuring chains, together with schemes of hardware diagnostics for mechatronic systems are proposed.
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Choukou, M. A., B. Jarlot, A. Arfaoui, S. Bourelle, and R. Taiar. "Infrared thermograms: Orthopedic diagnostics support." Annals of Physical and Rehabilitation Medicine 56 (October 2013): e285. http://dx.doi.org/10.1016/j.rehab.2013.07.734.

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KOZLOVA, Valeria. "ECONOMIC DIAGNOSTICS IN THE SYSTEM OF INFORMATION SUPPORT FOR MANAGEMENT DECISION-MAKING." Herald of Khmelnytskyi National University. Economic sciences 312, no. 6(2) (December 29, 2022): 196–201. http://dx.doi.org/10.31891/2307-5740-2022-312-6(2)-33.

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The article updates the problem of the role, place and informative possibilities of economic diagnostics for making managerial decisions regarding the innovative development of the enterprise. A significant number of scientific publications of Ukrainian and foreign economists devoted to various aspects of managerial innovations were considered, and the need for a systematic search for ways of innovative transformation of managerial decision-making for the effective development of enterprises was revealed. Analytical models of managerial decision-making based on knowledge were analyzed, the necessity of using business analytics for multi-criteria decision-making was revealed. The factors of the impact of analytical information on the quality of management decisions regarding innovative development, technological improvement, productivity growth and value creation in the organizational environment are analyzed. The need to develop a system of information and analytical support for enterprise management using an analysis mechanism, the implementation of which is based on monitoring the achievement of predetermined evaluation criteria, is substantiated. The role of economic diagnostics in increasing the efficiency of management of the enterprise’s activities has been clarified. It is proposed to consider economic diagnostics as a leading element of the information support system of the management decision-making process, both to identify the causes of disagreements and to find factors for accelerating innovative transformations. The established diagnostic indicators of the system of innovative development of the enterprise are considered and the author’s approach to determining the factors of coordination is proposed. Thus, it was established that the use of economic diagnostics in the management of innovative development allows to increase the informative relevance for making conceptual management decisions.. Further research is proposed to focus on the development of methodological principles for the introduction of economic diagnostics into the system of management decision-making in operational, tactical and strategic directions.
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Salvo, Marissa. "In Support of Teaching Basic Diagnostics." American Journal of Pharmaceutical Education 78, no. 3 (April 17, 2014): 64. http://dx.doi.org/10.5688/ajpe78364.

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Kim, Sunwha, and Choongrak Kim. "Influence Diagnostics in Support Vector Machines." Journal of the Korean Statistical Society 49, no. 3 (January 1, 2020): 757–78. http://dx.doi.org/10.1007/s42952-019-00037-5.

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Hegde, G. G., and Peter Kubat. "Diagnostics design: A product support strategy." European Journal of Operational Research 38, no. 1 (January 1989): 35–43. http://dx.doi.org/10.1016/0377-2217(89)90466-9.

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Sotnyk, Anhelina. "ORGANIZATIONAL AND METHODOLOGICAL SUPPORT BUSINESS DIAGNOSTICS OF PRODUCTION AND COMMERCIAL ACTIVITY OF INDUSTRIAL ENTERPRISE." Economic Analysis, no. 31(4) (2021): 65–74. http://dx.doi.org/10.35774/econa2021.04.065.

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The article considers the issues of determining the essence of business diagnostics of industrial and commercial activities of industrial enterprises and the formation of organizational and methodological support for the implementation of the diagnostic process, due to the need to establish content and sequence of preventive measures against internal and external threats effective current activities to achieve the strategic objectives of the entity. The purpose of the study is the formation of organizational and methodological support for business diagnostics of industrial and commercial activities of industrial enterprises. The research methodology includes methods of analysis and synthesis - to study the essence of industrial and commercial activities of industrial enterprises, abstract-logical method - to establish stages of business diagnostics of industrial and commercial activities of industrial enterprises, method of systematic approach - to form principles of diagnostic procedure and diagnostic indicators. , graphic method - for visual presentation of the material. Results. The article stipulates that the purpose of conducting business diagnostics of production and commercial activities of an industrial enterprise is to obtain and apply in practice relevant data on the level of efficiency of the business entity, the reasons for deviations from the strategic direction of development. The algorithm of business diagnostics is substantiated, which provides: coordination of the chosen strategy of the enterprise and current activity, assessment of the actual state of efficiency of production and commercial activity, determination of the gap between actual and planned indicators, development of measures to increase efficiency, control over measures. It is established that the diagnostics of production and commercial activities of an industrial enterprise examines the main business processes. The article summarizes the requirements for the formation of a system of indicators that provides a reasonable conclusion on the effectiveness of production and commercial activities of the enterprise. It is proved that for successful carrying out of diagnostic procedure the methodical basis which provides observance of principles, use of scientific methods of calculation, the analysis and forecasting of the formed set of diagnostic indicators, presence of information maintenance should be formed.
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Kohlmann, Alexander, Giovanni Martinelli, Mary Alikian, Valentina Artusi, Bernd Auber, Monika Belickova, Ilaria Bronzini, et al. "The Interlaboratory Robustness Of Next-Generation Sequencing (IRON) Study Phase II: Deep-Sequencing Analyses Of Hematological Malignancies Performed In 8,867 Cases By An International Network Involving 27 Laboratories." Blood 122, no. 21 (November 15, 2013): 743. http://dx.doi.org/10.1182/blood.v122.21.743.743.

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Abstract Introduction Amplicon deep-sequencing using second-generation sequencing technology is an innovative molecular diagnostic technique and enables a highly-sensitive detection of mutations. As an international consortium we had investigated previously the robustness, precision, and reproducibility of 454 amplicon next-generation sequencing (NGS) across 10 laboratories from 8 countries (Leukemia, 2011;25:1840-8). Aims In Phase II of the study, we established distinct working groups for various hematological malignancies, i.e. acute myeloid leukemia (AML), acute lymphoblastic leukemia (ALL), chronic lymphocytic leukemia (CLL), chronic myelogenous leukemia (CML), myelodysplastic syndromes (MDS), myeloproliferative neoplasms (MPN), and multiple myeloma. Currently, 27 laboratories from 13 countries are part of this research consortium. In total, 74 gene targets were selected by the working groups and amplicons were developed for a NGS deep-sequencing assay (454 Life Sciences, Branford, CT). A data analysis pipeline was developed to standardize mutation interpretation both for accessing raw data (Roche Amplicon Variant Analyzer, 454 Life Sciences) and variant interpretation (Sequence Pilot, JSI Medical Systems, Kippenheim, Germany). Results We will report on the design, standardization, quality control aspects, landscape of mutations, as well as the prognostic and predictive utility of this assay in a cohort of 8,867 cases. Overall, 1,146 primer sequences were designed and tested. In detail, for example in AML, 924 cases had been screened for CEBPA mutations. RUNX1 mutations were analyzed in 1,888 cases applying the deep-sequencing read counts to study the stability of such mutations at relapse and their utility as a biomarker to detect residual disease. Analyses of DNMT3A (n=1,041) were focused to perform landscape investigations and to address the prognostic relevance. Additionally, this working group is focusing on TET2, ASXL1, and TP53 analyses. A novel prognostic model is being developed allowing stratification of AML into prognostic subgroups based on molecular markers only. In ALL, 1,124 pediatric and adult cases have been screened, including 763 assays for TP53 mutations both at diagnosis and relapse of ALL. Pediatric and adult leukemia expert labs developed additional content to study the mutation incidence of other B and T lineage markers such as IKZF1, JAK2, IL7R, PAX5, EP300, LEF1, CRLF2, PHF6, WT1, JAK1, PTEN, AKT1, IL7R, NOTCH1, CREBBP, or FBXW7. Further, the molecular landscape of CLL is changing rapidly. As such, a separate working group focused on analyses including NOTCH1, SF3B1, MYD88, XPO1, FBXW7 and BIRC3. Currently, 922 cases were screened to investigate the range of mutational burden of NOTCH1 mutations for their prognostic relevance. In MDS, RUNX1 mutation analyses were performed in 977 cases. The prognostic relevance of TP53 mutations in MDS was assessed in additional 327 cases, including isolated deletions of chromosome 5q. Next, content was developed targeting genes of the cellular splicing component, e.g. SF3B1, SRSF2, U2AF1, and ZRSR2. In BCR-ABL1-negative MPN, nine genes of interest (JAK2, MPL, TET2, CBL, KRAS, EZH2, IDH1, IDH2, ASXL1) have been analyzed in a cohort of 155 primary myelofibrosis cases searching for novel somatic mutations and addressing their relevance for disease progression and leukemia transformation. Moreover, an assay was developed and applied to CMML cases allowing the simultaneous analysis of 25 leukemia-associated target genes in a single sequencing run using just 20 ng of starting DNA. Finally, nine laboratories are studying CML, applying ultra-deep sequencing of the BCR-ABL1 tyrosine kinase domain. Analyses were performed on 615 cases investigating the dynamics of expansion of mutated clones under various tyrosine kinase inhibitor therapies. Conclusion Molecular characterization of hematological malignancies today requires high diagnostic sensitivity and specificity. As part of the IRON-II study, a network of laboratories analyzed a variety of disease entities applying amplicon-based NGS assays. Importantly, the consortium not only standardized assay design for disease-specific panels, but also achieved consensus on a common data analysis pipeline for mutation interpretation. Distinct working groups have been forged to address scientific tasks and in total 8,867 cases had been analyzed thus far. Disclosures: Kohlmann: Roche Diagnostics: Honoraria; MLL Munich Leukemia Laboratory: Employment. Martinelli:Roche Diagnostics: Research Support Other. Alikian:Roche Diagnostics: Research Support Other. Auber:Roche Diagnostics: Research Support Other. Belickova:Roche Diagnostics: Research Support Other. Bronzini:Roche Diagnostics: Research Support Other. Cazzaniga:Roche Diagnostics: Research Support Other. Chiaretti:Roche Diagnostics: Research Support Other. Ernst:Roche Diagnostics: Research Support Other. Fuellgrabe:Roche Diagnostics: Research Support Other. Gabriel:Roche Diagnostics: Research Support Other. Hernandez:Roche Diagnostics: Research Support Other. Jansen:Roche Diagnostics: Research Support Other. Iacobucci:Roche Diagnostics: Research Support Other. Lion:Roche Diagnostics: Research Support Other. Lode:Roche Diagnostics: Research Support Other. Martinez-Lopez:Roche Diagnostics: Research Support Other. Mills:Roche Diagnostics: Research Support Other. Mossner:Roche Diagnostics: Research Support Other. Machova Polakova:Roche Diagnostics: Research Support Other. Porret:Roche Diagnostics: Research Support Other. Pospisilova:Roche Diagnostics: Research Support Other. Preudhomme:Roche Diagnostics: Research Support Other. Sayitoglu:Roche Diagnostics: Research Support Other. Soverini:Roche Diagnostics: Research Support Other. Spinelli:Roche Diagnostics: Research Support Other. Thiede:Roche Diagnostics: Research Support Other. Vandenberghe:Roche Diagnostics: Research Support Other. Yeoh:Roche Diagnostics: Research Support Other. Hochhaus:Roche Diagnostics: Research Support Other. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership; Roche Diagnostics: Research Funding.
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Sangiorgio, Valentino, Silvia Martiradonna, Fabio Fatiguso, and Giuseppina Uva. "Historical masonry churches diagnosis supported by an analytic-hierarchy-process-based decision support system." ACTA IMEKO 10, no. 1 (March 31, 2021): 6. http://dx.doi.org/10.21014/acta_imeko.v10i1.793.

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<p class="Abstract"><span lang="EN-GB">The structural and anti-seismic performances of historical masonry churches are related not only to structural damage and masonry quality but also to other criticalities that can jeopardise the connections, wooden elements, and non-structural elements. As such, the technical and scientific communities are interested in the development of fast visual-survey approaches for assessing these issues and for performing exhaustive diagnostics by considering all the parameters affecting the building performance.</span></p><p class="Abstract"><span lang="EN-GB">In this paper, a new procedure for performing rapid visual surveys and the diagnostics of masonry buildings using a set of condition ratings is proposed. The proposed novel approach includes three synergistically related techniques: i) the analytic hierarchy process method for measuring and analysing both qualitative and quantitative data during a visual survey, ii) a suitable survey form to perform a rapid visual inspection implementable in a decision support system (DSS), and iii) a DSS procedure to provide a powerful computerised tool that would be useful in large-scale data acquisition. Finally, to demonstrate the potential of the proposed approach, the Romanesque masonry church SS. Salvatore in Capurso, Italy,</span><span lang="EN-GB">is analysed. A comparison with a standard diagnostic workflow is also presented to validate the procedure and to emphasise the advantages of the novel diagnostics.</span></p><p class="Abstract"> </p>
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Dissertations / Theses on the topic "Diagnostics support"

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Zenkin, M., and Y. Golovanova. "Ensuring the reliability of technical diagnostics of vehicles during maintenance and repair." Thesis, Київський національний університет технологій та дизайну, 2019. https://er.knutd.edu.ua/handle/123456789/14640.

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Lindberg, Martin. "Decision Support Systems: Diagnostics and Explanation methods : In the context of telecommunication networks." Thesis, Umeå universitet, Institutionen för fysik, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-73666.

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This thesis work, conducted at Ericsson Software Research, aims to recommend a system setup for a tool to help troubleshooting personal at network operation centres (NOC) who monitors the telecom network. This thesis examines several different artificial intelligence algorithms resulting in the conclusion that Bayesian networks are suitable for the aimed system. Since the system will act as a decision support system it needs to be able to explain how recommendations have been developed. Hence a number of explanation methods have been examined. Unfortunately no satisfactory method was found and thus a new method was defined, modified explanation tree (MET) which visually illustrates the variables of most interest in a so called tree structure. The method was implementation and after some initial testing the method has gained some positive first feedback from stakeholders. Thus the final recommendation consists of a system based on a Bayesian model where the gathered training data is collected earlier from the domain. The users will thus obtain recommendations for the top ranked cases and afterwards get the option to get further explanation regarding the specific cause. The explanation aims to give the user situation awareness and help him/her in the final action to solve the problem.
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Story, David Lee Jr. "Autonomous Multi-Sensor and Web-Based Decision Support for Crop Diagnostics in Greenhouse." Diss., The University of Arizona, 2013. http://hdl.handle.net/10150/306925.

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An autonomous machine vision guided plant sensing and monitoring system was designed and constructed to continuously monitor plant related features: color (red-green-blue, hue-saturation-luminance, and color brightness), morphology (top projected canopy area), textural (entropy, energy, contrast, and homogeneity), Normalized Difference Vegetative Index (NDVI) (as well as other similar indices from the color and NIR channels), and thermal (plant and canopy temperature). Several experiments with repeated water stress cycles, using the machine vision system, was conducted to evaluate the machine vision system's performance to determine the timeliness of induced plant water stress detection. The study aimed at identifying significant features separating the control and treatment from an induced water stress experiment and also identifying, amongst the plant canopy, the location of the emerging water stress with the found significant features. Plant cell severity had been ranked based on the cell's accumulated feature count and converted to a color coded graphical canopy image for the remote operator to evaluate. The overall feature analysis showed that the morphological feature, Top Projected Canopy Area, was found to be a good marker for the initial growth period while the vegetation indices (ENDVI, NDVIBlue, and NDVIRed) were more capable at capturing the repeated stress occurrences during the various stages of the lettuce crop. Furthermore, the crop's canopy temperature was shown to be a significant and dominant marker to timely detect the water stress occurrences. The graphical display for the remote user showed the severity of summed features to equal the detection of the human vision. Capabilities and limitations of the developed system and stress detection methodology were documented with recommendations for future improvements for the crop monitoring/production system. An example web based decision support platform was created for data collection, storage, analysis, and display of the data/imagery collected for a remote operator.
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Москаленко, Альона Сергіївна, Алена Сергеевна Москаленко, and Alona Serhiivna Moskalenko. "Intelligent decision support system for renal radionuclide imaging." Thesis, Sumy State University, 2016. http://essuir.sumdu.edu.ua/handle/123456789/46806.

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Radionuclide imaging of kidneys has a special place in nuclear medicine. It allows to register functional changes, far earlier than the structural and anatomical changes. Therefore, it is indispensable at early diagnosis. The reliability of data interpretation of renal scintigraphy studies depends on the level of doctor-diagnostician’s professional qualification and on the presence of their practical experience.
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Spooner, Scott G. "An energy analysis of the pseudo Wigner-Ville distribution in support of machinery monitoring and diagnostics." Thesis, Monterey, California. Naval Postgraduate School, 1992. http://hdl.handle.net/10945/23877.

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Witzel, Benjamin [Verfasser], and Christof [Akademischer Betreuer] Schulz. "Application of Optical Diagnostics to Support the Development of Industrial Gas Turbine Combustors / Benjamin Witzel ; Betreuer: Christof Schulz." Duisburg, 2016. http://d-nb.info/1119705681/34.

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Kan, Man Shan. "Multi-sensor condition monitoring of bearings using support vector machines." Thesis, Queensland University of Technology, 2017. https://eprints.qut.edu.au/110621/1/Man%20Shan_Kan_Thesis.pdf.

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This thesis presents a study on bearing condition monitoring under variable operating conditions using Support Vector Machines. Data collected from multiple sensors including accelerometers, acoustic emission sensors and tachometers are used for the studies presented in this thesis. This work has successfully demonstrated acoustic emission's superiority in bearing incipient fault detection; and the prognostic study has developed an effective prognostic approach to capture the system's dynamics with speed variations and make accurate predictions.
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Vervier, Kevin. "Méthodes d’apprentissage structuré pour la microbiologie : spectrométrie de masse et séquençage haut-débit." Thesis, Paris, ENMP, 2015. http://www.theses.fr/2015ENMP0081/document.

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L'utilisation des technologies haut débit est en train de changer aussi bien les pratiques que le paysage scientifique en microbiologie. D'une part la spectrométrie de masse a d'ores et déjà fait son entrée avec succès dans les laboratoires de microbiologie clinique. D'autre part, l'avancée spectaculaire des technologies de séquençage au cours des dix dernières années permet désormais à moindre coût et dans un temps raisonnable de caractériser la diversité microbienne au sein d'échantillons cliniques complexes. Aussi ces deux technologies sont pressenties comme les piliers de futures solutions de diagnostic. L'objectif de cette thèse est de développer des méthodes d'apprentissage statistique innovantes et versatiles pour exploiter les données fournies par ces technologies haut-débit dans le domaine du diagnostic in vitro en microbiologie. Le domaine de l'apprentissage statistique fait partie intégrante des problématiques mentionnées ci-dessus, au travers notamment des questions de classification d'un spectre de masse ou d'un “read” de séquençage haut-débit dans une taxonomie bactérienne.Sur le plan méthodologique, ces données nécessitent des développements spécifiques afin de tirer au mieux avantage de leur structuration inhérente: une structuration en “entrée” lorsque l'on réalise une prédiction à partir d'un “read” de séquençage caractérisé par sa composition en nucléotides, et un structuration en “sortie” lorsque l'on veut associer un spectre de masse ou d'un “read” de séquençage à une structure hiérarchique de taxonomie bactérienne
Using high-throughput technologies is changing scientific practices and landscape in microbiology. On one hand, mass spectrometry is already used in clinical microbiology laboratories. On the other hand, the last ten years dramatic progress in sequencing technologies allows cheap and fast characterization of microbial diversity in complex clinical samples. Consequently, the two technologies are approached in future diagnostics solutions. This thesis aims to play a part in new in vitro diagnostics (IVD) systems based on high-throughput technologies, like mass spectrometry or next generation sequencing, and their applications in microbiology.Because of the volume of data generated by these new technologies and the complexity of measured parameters, we develop innovative and versatile statistical learning methods for applications in IVD and microbiology. Statistical learning field is well-suited for tasks relying on high-dimensional raw data that can hardly be used by medical experts, like mass-spectrum classification or affecting a sequencing read to the right organism. Here, we propose to use additional known structures in order to improve quality of the answer. For instance, we convert a sequencing read (raw data) into a vector in a nucleotide composition space and use it as a structuredinput for machine learning approaches. We also add prior information related to the hierarchical structure that organizes the reachable micro-organisms (structured output)
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Kim, Hack-Eun. "Machine prognostics based on health state probability estimation." Thesis, Queensland University of Technology, 2010. https://eprints.qut.edu.au/41739/1/Hack-Eun_Kim_Thesis.pdf.

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The ability to accurately predict the remaining useful life of machine components is critical for machine continuous operation and can also improve productivity and enhance system’s safety. In condition-based maintenance (CBM), maintenance is performed based on information collected through condition monitoring and assessment of the machine health. Effective diagnostics and prognostics are important aspects of CBM for maintenance engineers to schedule a repair and to acquire replacement components before the components actually fail. Although a variety of prognostic methodologies have been reported recently, their application in industry is still relatively new and mostly focused on the prediction of specific component degradations. Furthermore, they required significant and sufficient number of fault indicators to accurately prognose the component faults. Hence, sufficient usage of health indicators in prognostics for the effective interpretation of machine degradation process is still required. Major challenges for accurate longterm prediction of remaining useful life (RUL) still remain to be addressed. Therefore, continuous development and improvement of a machine health management system and accurate long-term prediction of machine remnant life is required in real industry application. This thesis presents an integrated diagnostics and prognostics framework based on health state probability estimation for accurate and long-term prediction of machine remnant life. In the proposed model, prior empirical (historical) knowledge is embedded in the integrated diagnostics and prognostics system for classification of impending faults in machine system and accurate probability estimation of discrete degradation stages (health states). The methodology assumes that machine degradation consists of a series of degraded states (health states) which effectively represent the dynamic and stochastic process of machine failure. The estimation of discrete health state probability for the prediction of machine remnant life is performed using the ability of classification algorithms. To employ the appropriate classifier for health state probability estimation in the proposed model, comparative intelligent diagnostic tests were conducted using five different classifiers applied to the progressive fault data of three different faults in a high pressure liquefied natural gas (HP-LNG) pump. As a result of this comparison study, SVMs were employed in heath state probability estimation for the prediction of machine failure in this research. The proposed prognostic methodology has been successfully tested and validated using a number of case studies from simulation tests to real industry applications. The results from two actual failure case studies using simulations and experiments indicate that accurate estimation of health states is achievable and the proposed method provides accurate long-term prediction of machine remnant life. In addition, the results of experimental tests show that the proposed model has the capability of providing early warning of abnormal machine operating conditions by identifying the transitional states of machine fault conditions. Finally, the proposed prognostic model is validated through two industrial case studies. The optimal number of health states which can minimise the model training error without significant decrease of prediction accuracy was also examined through several health states of bearing failure. The results were very encouraging and show that the proposed prognostic model based on health state probability estimation has the potential to be used as a generic and scalable asset health estimation tool in industrial machinery.
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Khawaja, Taimoor Saleem. "A Bayesian least squares support vector machines based framework for fault diagnosis and failure prognosis." Diss., Georgia Institute of Technology, 2010. http://hdl.handle.net/1853/34758.

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A high-belief low-overhead Prognostics and Health Management (PHM) system is desired for online real-time monitoring of complex non-linear systems operating in a complex (possibly non-Gaussian) noise environment. This thesis presents a Bayesian Least Squares Support Vector Machine (LS-SVM) based framework for fault diagnosis and failure prognosis in nonlinear, non-Gaussian systems. The methodology assumes the availability of real-time process measurements, definition of a set of fault indicators, and the existence of empirical knowledge (or historical data) to characterize both nominal and abnormal operating conditions. An efficient yet powerful Least Squares Support Vector Machine (LS-SVM) algorithm, set within a Bayesian Inference framework, not only allows for the development of real-time algorithms for diagnosis and prognosis but also provides a solid theoretical framework to address key concepts related to classication for diagnosis and regression modeling for prognosis. SVM machines are founded on the principle of Structural Risk Minimization (SRM) which tends to nd a good trade-o between low empirical risk and small capacity. The key features in SVM are the use of non-linear kernels, the absence of local minima, the sparseness of the solution and the capacity control obtained by optimizing the margin. The Bayesian Inference framework linked with LS-SVMs allows a probabilistic interpretation of the results for diagnosis and prognosis. Additional levels of inference provide the much coveted features of adaptability and tunability of the modeling parameters. The two main modules considered in this research are fault diagnosis and failure prognosis. With the goal of designing an efficient and reliable fault diagnosis scheme, a novel Anomaly Detector is suggested based on the LS-SVM machines. The proposed scheme uses only baseline data to construct a 1-class LS-SVM machine which, when presented with online data, is able to distinguish between normal behavior and any abnormal or novel data during real-time operation. The results of the scheme are interpreted as a posterior probability of health (1 - probability of fault). As shown through two case studies in Chapter 3, the scheme is well suited for diagnosing imminent faults in dynamical non-linear systems. Finally, the failure prognosis scheme is based on an incremental weighted Bayesian LS-SVR machine. It is particularly suited for online deployment given the incremental nature of the algorithm and the quick optimization problem solved in the LS-SVR algorithm. By way of kernelization and a Gaussian Mixture Modeling (GMM) scheme, the algorithm can estimate (possibly) non-Gaussian posterior distributions for complex non-linear systems. An efficient regression scheme associated with the more rigorous core algorithm allows for long-term predictions, fault growth estimation with confidence bounds and remaining useful life (RUL) estimation after a fault is detected. The leading contributions of this thesis are (a) the development of a novel Bayesian Anomaly Detector for efficient and reliable Fault Detection and Identification (FDI) based on Least Squares Support Vector Machines , (b) the development of a data-driven real-time architecture for long-term Failure Prognosis using Least Squares Support Vector Machines,(c) Uncertainty representation and management using Bayesian Inference for posterior distribution estimation and hyper-parameter tuning, and finally (d) the statistical characterization of the performance of diagnosis and prognosis algorithms in order to relate the efficiency and reliability of the proposed schemes.
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Books on the topic "Diagnostics support"

1

Spooner, Scott G. An energy analysis of the pseudo Wigner-Ville distribution in support of machinery monitoring and diagnostics. Monterey, Calif: Naval Postgraduate School, 1992.

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J, Jacobson Edwin, ed. Common medical diagnoses: An algorithmic approach. 2nd ed. Philadelphia: W.B. Saunders, 1994.

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J, Jacobson Edwin, ed. Common medical diagnoses: An algorithmic approach. Philadelphia: Saunders, 1990.

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J, Jacobson Edwin, ed. Common medical diagnoses: An algorithmic approach. 4th ed. Philadelphia: Saunders Elsevier, 2006.

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Hunink, Maria Gabriella Margaretha. Applications of decision analysis in diagnostic radiology. [Rotterdam?: s.n., 1989.

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United States. Dept. of Energy. Nuclear Safety Diagnostic Division., ed. Diagnostic evaluation of engineering and technical support at the Pantex Plant. Washington, D.C: U.S. Dept. of Energy, Office of the Assistant Secretary for Defense Programs, Office of Self-Assessment and Emergency Management, Safety Diagnostic Division, 1991.

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Kuz'min, Nikolay, and Aleksandr Kustikov. Diagnostics of modern cars. ru: INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1078766.

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The textbook contains the main provisions of the theory of automobile diagnostics, methods and characteristic technological processes for diagnosing automobile engines, structural elements of the transmission, chassis, bodywork, and active safety systems. The theoretical material is supported by the description of practical technologies for conducting diagnostics of modern car systems. Meets the requirements of the federal state educational standards of higher education of the latest generation. Recommended for undergraduates and bachelors of all forms of education in the areas of training 23.04.03 and 23.03.03 "Operation of transport and technological machines and complexes".
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Morgan, Graham Scott. Radiography support workers: An investigation into the requirements of diagnostic imaging department managers for training imaging support staff. Uxbridge: Brunel University, 1994.

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Doherty, Neil. Knowledge-based diagnostic support for a building management system: An organisational perspective. Loughborough, Leics: Loughborough University Business School, 1994.

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Society for Computer Applications in Radiology, ed. Decision support in the digital medical enterprise. Great Falls, Va: Society for Computer Applications in Radiology, 2005.

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Book chapters on the topic "Diagnostics support"

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Nowicki, Ryszard, Roman Słowiński, and Jerzy Stefanowski. "Analysis of Diagnostic Symptoms in Vibroacoustic Diagnostics by Means of the Rough Sets Theory." In Intelligent Decision Support, 33–48. Dordrecht: Springer Netherlands, 1992. http://dx.doi.org/10.1007/978-94-015-7975-9_3.

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Embrey, D. E., and T. G. Wolfmaier. "Design Principles For Diagnostics Decision Support Systems." In Failsafe Control Systems, 41–46. Dordrecht: Springer Netherlands, 1991. http://dx.doi.org/10.1007/978-94-009-0429-3_4.

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Korzynska, Anna, Jakub Zak, Krzysztof Siemion, Lukasz Roszkowiak, and Dorota Pijanowska. "CNN Support to Diagnostics in Sjögren’s Syndrome." In Advances in Intelligent Systems and Computing, 72–81. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-29885-2_7.

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Kundu, Palash Kumar, and Madhusree Kundu. "Diagnostics and Decision Support for Cardiovascular System." In Disruptive Trends in Computer Aided Diagnosis, 155–74. New York: Chapman and Hall/CRC, 2021. http://dx.doi.org/10.1201/9781003045816-9.

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Methlie, Leif B. "On Knowledge-Based Decision Support Systems for Financial Diagnostics." In Decision Support Systems: Theory and Application, 335–71. Berlin, Heidelberg: Springer Berlin Heidelberg, 1987. http://dx.doi.org/10.1007/978-3-642-83088-4_12.

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Scherrer, Alexander, Michael Helmling, Christian Singer, Sinan Riedel, and Karl-Heinz Küfer. "Artificial Intelligence-Based Decision Support in Laboratory Diagnostics." In Operations Research Proceedings 2021, 229–35. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-08623-6_35.

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Lahrache, Achraf, Marco Cocconcelli, and Riccardo Rubini. "Knife Diagnostics with Clustering Techniques and Support Vector Machines." In Applied Condition Monitoring, 81–90. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-61927-9_8.

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Barrett, Leslie, and Anthony R. Davis. "Diagnostics for Determining Compatibility in English Support-Verb-Nominalization Pairs." In Computational Linguistics and Intelligent Text Processing, 85–90. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/3-540-36456-0_9.

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Gaindric, Constantin, Svetlana Cojocaru, Olga Popcova, Serghei Puiu, and Iulian Secrieru. "Emergency-SonaRes: A System for Ultrasound Diagnostics Support in Extreme Cases." In Improving Disaster Resilience and Mitigation - IT Means and Tools, 283–92. Dordrecht: Springer Netherlands, 2014. http://dx.doi.org/10.1007/978-94-017-9136-6_18.

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Syfert, M., P. Wnuk, and J. M. Kościelny. "Introduction to DiaSter – Intelligent System for Diagnostics and Automatic Control Support." In Mechatronics, 385–93. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-23244-2_47.

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Conference papers on the topic "Diagnostics support"

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Hokkanen, Ari P., Joona Koponen, Kai Kolari, and Ingmar Stuns. "Active silicon support for DNA diagnostics." In Micromachining and Microfabrication, edited by Holger Becker and Peter Woias. SPIE, 2003. http://dx.doi.org/10.1117/12.472735.

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Cooper, D. W., F. P. Veitch, M. M. Anderson, and M. J. Clifford. "Adaptive diagnostics and personalized technical support (ADAPTS)." In 1999 IEEE Aerospace Conference. Proceedings. IEEE, 1999. http://dx.doi.org/10.1109/aero.1999.789773.

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Bielecki, Marcin, Salvatore Costagliola, and Piotr Gebalski. "Support Vibration Diagnostics and Limits in Gas Turbines." In ASME Turbo Expo 2016: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/gt2016-56548.

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The paper deliberates vibration limits for non-rotating parts in application to industrial gas turbines. As a rule such limits follow ISO 10816-4 or API616, although in field operation it is not well known relationship between these limits and failure modes. In many situations, the reliability function is not well-defined, and more comprehensive methods of determining the harmful effects of support vibrations are desirable. In the first part, the undertaken approach and the results are illustrated based on the field and theoretical experience of the authors about the failure modes related to alarm level of vibrations. Here several failure modes and diagnostics observations are illustrated with the examples of real-life data. In the second part, a statistical approach based on correlation of support vs. shaft vibrations (velocity / displacement) is demonstrated in order to assess the risk of the bearing rub. The test data for few gas turbine models produced by General Electric Oil & Gas are statistically evaluated and allow to draw an experimentally based transfer function between vibrations recorded by non-contact and seismic probes. Then the vibration limit with objectives like bearing rub is scrutinized with aid of probabilistic tools. In the third part, the attention is given to a few examples of the support vibrations — among other gas turbine with rotors supported on flexible pedestals and baseplate. Here there is determined a transfer coefficient between baseplate and bearing vibrations for specific foundation configurations. Based on the test data screening as well as analysis and case studies thereof, the conclusions about more specific vibration limits in relation to the failure modes are drawn.
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MANSFIELD, BRUCE, and HAROLD HAWLEY. "System modeling in support of automation-assisted diagnostics." In 7th Computers in Aerospace Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1989. http://dx.doi.org/10.2514/6.1989-3104.

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Eltyshev, D. K., and V. V. Boyarshinova. "Intelligent decision support in the electrical equipment diagnostics." In 2016 XIX IEEE International Conference on Soft Computing and Measurements (SCM). IEEE, 2016. http://dx.doi.org/10.1109/scm.2016.7519714.

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Kurmi, Indrajit, Sukanya Mukherjee, Ritwik Barman, Prasanta K. Panigrahi, Sabyasachi Mukhopadhyay, Sawon Pratiher, and Nirmalya Ghosh. "Efficacy of hidden markov model over support vector machine on multiclass classification of healthy and cancerous cervical tissues." In Optical Diagnostics and Sensing XVIII: Toward Point-of-Care Diagnostics, edited by Gerard L. Coté. SPIE, 2018. http://dx.doi.org/10.1117/12.2291485.

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Nikulin, M. A., V. A. Ivannikov, V. N. Bukhtoyarov, A. P. Novikov, A. N. Shvyrev, K. A. Yakovlev, and A. V. Latynin. "Optimization of diagnostic technology LPG/CNG vehicles. decision support system for diagnostics gas-fueled system." In PROCEEDINGS OF THE 10TH WORKSHOP ON METALLIZATION AND INTERCONNECTION FOR CRYSTALLINE SILICON SOLAR CELLS. AIP Publishing, 2022. http://dx.doi.org/10.1063/5.0105585.

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Redmer, Benjamin, Philip Schargus, Saidurga Karthikeyan, Bodo Nestler, and Stefan Müller. "Determination of hemoglobin derivatives in unaltered whole blood samples using Support Vector regression in the spectral range from 450 to 700nm." In Optical Diagnostics and Sensing XX: Toward Point-of-Care Diagnostics, edited by Gerard L. Coté. SPIE, 2020. http://dx.doi.org/10.1117/12.2544806.

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Juricic, Dani, Pavle Boskoski, Janko Petrovcic, and Bojan Musizza. "A platform for diagnostics, prognostics and e-maintenance support." In 2013 Conference on Control and Fault-Tolerant Systems (SysTol). IEEE, 2013. http://dx.doi.org/10.1109/systol.2013.6693958.

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Novotny, Zdenek, Jan Mares, and Petr Dolezel. "Diagnostics support of musculoskeletal diseases using artificial neural network." In 2021 International Conference on Applied Electronics (AE). IEEE, 2021. http://dx.doi.org/10.23919/ae51540.2021.9542877.

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Reports on the topic "Diagnostics support"

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Bowman, Craig T. Graduate Student Support in Supersonic Diagnostics and Flow, (FY91 AASERT). Fort Belvoir, VA: Defense Technical Information Center, July 1995. http://dx.doi.org/10.21236/ada297936.

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Melton, Lynn A. Student Support in Connection with Fluorescent Diagnostics and Fundamental Droplet Processes. Fort Belvoir, VA: Defense Technical Information Center, May 2001. http://dx.doi.org/10.21236/ada394226.

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Anderson, R. A., and S. D. Nelson. EM field and instrumentation diagnostics in support of the LFT&E HPM methodology testing. Office of Scientific and Technical Information (OSTI), September 1997. http://dx.doi.org/10.2172/3401.

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Research Institute (IFPRI), International Food Policy. The role of food systems and value chains to improve diets in low income settings: Diagnostics to support intervention design in Malawi. Washington, DC: International Food Policy Research Institute, 2018. http://dx.doi.org/10.2499/1041943078.

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Honig, A. Temperature-dependent tensile strength, surface roughness diagnostics, and magnetic support and positioning of polymer ICF shells. Final report, October 1, 1993--April 30, 1995. Office of Scientific and Technical Information (OSTI), December 1995. http://dx.doi.org/10.2172/184296.

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Honig, A. Temperature-dependent tensile strength, surface roughness diagnostics, and magnetic support and positioning of polymer ICF shells. Final report, April 17, 1995--July 31, 1996. Office of Scientific and Technical Information (OSTI), August 1997. http://dx.doi.org/10.2172/531094.

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Schroeder, J. E. Hydraulic fracture model and diagnostics verification at GRI/DOE multi-site projects and tight gas sand program support. Final report, July 28, 1993--February 28, 1997. Office of Scientific and Technical Information (OSTI), December 1997. http://dx.doi.org/10.2172/639755.

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Cirigliano, R., E. Franco, L. Koppel, B. Rodrigues, and J. Smith. Novette diagnostic support. Final report. Office of Scientific and Technical Information (OSTI), February 1985. http://dx.doi.org/10.2172/5544838.

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Sillah, Bukhari. Country Diagnostic Study – United Arab Emirates. Islamic Development Bank Institute, November 2021. http://dx.doi.org/10.55780/rp21002.

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The Country Diagnostic Study (CDS) for United Arab Emirates (U.A.E.) uses the Hausmann-Rodrik-Velasco growth diagnostics model to identify the binding constraints being faced in its quest for higher economic growth and make recommendations to relax these constraints. Hence, the findings of the CDS can help the Islamic Development Bank in identifying areas where it can have a greater impact and provide an evidence basis to support the development of the Member Country Partnership Strategy. U.A.E.’s development journey has been painstakingly crafted over time, with the latest being Vision 2021. Launched in 2010 and in the aftermath of the global financial crisis (GFC), Vision 2021 was designed to place the U.A.E. among the best nations in the world. It has achieved several targets under the competitive knowledge pillar of the Vision, but some key targets related to economic growth, innovation, and knowledge workers are yet to be fully realized. This is because growth has been low and inadequate with relatively low private investment since the 2008–2009 GFC, leading to a lower than potential real GDP trend. To bring in private investment and improve growth, both quantity and quality of human capital may need to be scaled up through improving the education system and spending on research and development to support industry-university collaboration on innovations. Efficient institutional governance in the areas of corruption control, regulatory quality and conducive bureaucracy is necessary for the vibrant functioning of the private sector.
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Diop, Ahmed. Country Diagnostic Study – Senegal. Islamic Development Bank Institute, October 2021. http://dx.doi.org/10.55780/rp21003.

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The Country Diagnostic Study (CDS) for Senegal uses the Hausmann-Rodrik-Velasco growth diagnostics model to identify the binding constraints being faced in its quest for higher and more sustained economic growth and make recommendations to relax these constraints. Hence, the findings of the CDS can help the Islamic Development Bank in identifying areas where it can have a greater impact and provide an evidence-basis to support the development of the Member Country Partnership Strategy. After decades of subdued and highly volatile economic growth due to heavy dependence on primary commodities and low productivity, Senegal experienced an unprecedented growth acceleration from 2014 to 2019. However, there appeared to be a weak correlation between economic growth and jobs creation. In addition, about 90 percent of non-agricultural employment is estimated to be informal. The national poverty rate decreased by 5 percentage points between 2011 and 2018. Nonetheless, the absolute number of poor people has increased. Furthermore, regional disparities are persistent. Despite the country’s solid performance in the field of governance, further simplification and transparency of business procedures and regulations will be critical in addressing the challenge of informality. Efforts to address informality in the economy should also target the issue of access to finance through the design of financing mechanisms based on specific needs assessment and risk management tools. Senegal will also need to create the conditions for higher competitiveness and follow upgrading trajectories in global and regional value chains. In this respect, both physical and digital connectivity will be essential.
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