Relevant bibliographies by topics / Basic automatic diagnosis

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Basic automatic diagnosis'

Author: Grafiati
Published: 11 January 2025

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Journal articles on the topic "Basic automatic diagnosis"

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Ono, Yumie, Naoko Kasai, Atsushi Ishiyama, T. Miyashita, and Y. Terada. "A basic study on algorithm for automatic diagnosis by magnetocardiography." Physica C: Superconductivity 368, no. 1-4 (2002): 45–49. http://dx.doi.org/10.1016/s0921-4534(01)01138-8.

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Harbi, Zainab. "Automatic Diagnosis of Ovarian Cancer Based on Relative Entropy and Neural Network." Wasit Journal for Pure sciences 2, no. 3 (2023): 108–18. http://dx.doi.org/10.31185/wjps.172.

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Ovarian Cancer is one of the most common causes of death for women in developing countries. Screening and early diagnoses of OC are urgently needed. Early diagnosis would help in consequence procedures and treatment. Mass spectrometry (MS) data is been used as an effective component of cancer diagnosis tools. However, these valuable data have a large number of dimensions that can affect the learning process in addition to time-consuming considerations. Feature selection plays an important role in reducing information redundancy, and deals with the invalidation that occurs in basic classificati
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Wang, Zhi Song, Li Wei Tang, Wen Wen Yu, and Jin Hua Cao. "Antiaircraft Gun Automatic Fusion Diagnosis Based on D-S Evidence Theory." Applied Mechanics and Materials 241-244 (December 2012): 288–92. http://dx.doi.org/10.4028/www.scientific.net/amm.241-244.288.

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Antiaircraft gun automatic is irrotational machine, its motion presents characteristic of stage, so we proposed a fault diagnosis fusion model based on Dempster-Shafer (D-S) evidence theory. At first, feature parameters are extracted from test data of multi-sensor, then, we propose a revised Minkowski distance to create evidences. Finally, we fuse basic belief assignments according to Dempster combination rule, and the analysis result verifies the effectiveness and feasibility of proposed fault diagnosis method.
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Tang, Gong Min, Fu Jun Liu, and Xiang Bin Sun. "Research and Design on SOA-Based Equipment ATS Architecture." Applied Mechanics and Materials 513-517 (February 2014): 403–7. http://dx.doi.org/10.4028/www.scientific.net/amm.513-517.403.

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By analyzing the current problems in equipment automatic test system, we describe the concept, the basic working principle and advantages of service-oriented architecture (SOA), then introduce the web service architecture and the standards of establishing service-oriented architecture. The architecture model of automatic test system on SOA-based equipment was designed, and was used to realize the unified description of equipment automatic test (including fault diagnosis) information. This effectively improves the equipment's capability in performance detection and maintenance support.
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Xu, Bo, Li Wei Guo, and Jin Song Yu. "Software Platform for General Purpose Test and Diagnosis." Applied Mechanics and Materials 241-244 (December 2012): 284–87. http://dx.doi.org/10.4028/www.scientific.net/amm.241-244.284.

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This paper centers on the software reuses of Automatic Test Systems (ATS) and the integration of test and diagnosis to reduce maintenance costs. Based on the research into the basic framework, data services, packages and definition of interfaces, we present an integrated software platform for test and diagnosis system. The platform achieves the separation between the user interface and test logic, the combination of fault modeling and diagnostic reasoning, and the integration of test and diagnosis.
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Lu, Zhi Li, Shi Guang Hu, Tai Yong Wang, Dong Xiang Chen, and Qing Jian Liu. "Remote Monitoring and Intelligent Fault Diagnosis Technology Research Based on Open CNC System." Advanced Materials Research 819 (September 2013): 234–37. http://dx.doi.org/10.4028/www.scientific.net/amr.819.234.

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In modem manufacturing,the various and complex requirement of industry makes the CNC machine tools more and more automatic and networking.While a remote monitoring and intelligent fault diagnosis system is the basic and indispensable unit for automatic and networking machine tools.This paper is focused on open CNC system,the condition monitoring, and fault diagnosis technology are researched of open CNC system. Integration achieved the CNCmachine tools' status remote monitoring and intelligent fault diagnosis, and detailed analysis of the key technologies for the components of the system. Thro
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Meng, Fan Jun, Li Hong Liu, Li Guo Lai, et al. "Intrinsically Safe for Continuous Automated Production Safety Technology of Unitary Detonating Powder." Applied Mechanics and Materials 496-500 (January 2014): 1568–73. http://dx.doi.org/10.4028/www.scientific.net/amm.496-500.1568.

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Production of unitary detonating powder is great danger, to protect the operation of the safety of workers, reducing labor intensity, no one is reaching a dangerous place to operate, this paper used IPC, PLC, field bus technology, industrial television monitoring, fault diagnosis techniques for successful implementation of unitary detonating powder continuous automated production safety. This paper discussed the key technological breakthrough situation such as continuous automated production safety technology of unitary detonating powder, security technology, precise control of many parameters
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Peng, Dong Hui, Fei Ye, Xin Wang, and Chuan Hai Jiao. "The Research of the Grass-Roots Level Radar Equipment Maintenance and Detecting Expert System Model." Applied Mechanics and Materials 602-605 (August 2014): 1793–96. http://dx.doi.org/10.4028/www.scientific.net/amm.602-605.1793.

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In view of the grass-roots level radar equipment maintenance and testing difficulty is big, the efficiency is low, limited technical conditions, etc, put forward a kind of intelligent fault diagnosis expert system model suitable for the radar equipment, and focus on the basic structure of the model, knowledge acquisition and the relevant reasoning mechanism. According to the characteristics of the grass-roots level radar fault diagnosis, the system combines automatic test technology and expert system and can improve the efficiency and reliability of fault diagnosis.
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GK, Srushti, and Sumana K R. "Comparative Study of Prediction of IDBP values for Hemodialysis using Deep Learning." International Journal for Research in Applied Science and Engineering Technology 10, no. 7 (2022): 4749–53. http://dx.doi.org/10.22214/ijraset.2022.46077.

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Abstract: The field of medicine is expanding rapidly as new diseases appear regularly, necessitating the development of appropriate treatment options. A precise and efficient method of operation is necessary for correct diagnosis and treatment. Blood pressure (BP) is a vital sign that provides basic information about patients' health. During the clinical operation of hemodialysis, blood pressure (BP) variability affects significant global risks and secondary complications associated with adverse mortality. In patients with hypertension, continuous BP monitoring is important. If the scheme is a
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Płudowski, Jakub, and Jan Mulawka. "Machine Learning in Recognition of Basic Pulmonary Pathologies." Applied Sciences 12, no. 16 (2022): 8086. http://dx.doi.org/10.3390/app12168086.

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Nowadays, during the diagnosis process, the doctor is able to obtain access to much information describing the patient’s condition using appropriate tools. However, there are always two sides to the coin. The doctor has certain limitations regarding the amount of data they can process at once. Information technology comes to the rescue, which with the help of computers is able to quickly and effectively separate important information from redundant information and support the doctor in making a diagnosis. In this work, a decision-making system was created to diagnose common lung pathologies in
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Dissertations / Theses on the topic "Basic automatic diagnosis"

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Yang, Hongyu. "Automatic Fault Diagnosis of Rolling Element Bearings Using Wavelet Based Pursuit Features." Thesis, Queensland University of Technology, 2005. https://eprints.qut.edu.au/16062/1/Hongyu_Yang_Thesis.pdf.

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Today's industry uses increasingly complex machines, some with extremely demanding performance criteria. Failed machines can lead to economic loss and safety problems due to unexpected production stoppages. Fault diagnosis in the condition monitoring of these machines is crucial for increasing machinery availability and reliability. Fault diagnosis of machinery is often a difficult and daunting task. To be truly effective, the process needs to be automated to reduce the reliance on manual data interpretation. It is the aim of this research to automate this process using data from machinery
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Yang, Hongyu. "Automatic Fault Diagnosis of Rolling Element Bearings Using Wavelet Based Pursuit Features." Queensland University of Technology, 2005. http://eprints.qut.edu.au/16062/.

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Today's industry uses increasingly complex machines, some with extremely demanding performance criteria. Failed machines can lead to economic loss and safety problems due to unexpected production stoppages. Fault diagnosis in the condition monitoring of these machines is crucial for increasing machinery availability and reliability. Fault diagnosis of machinery is often a difficult and daunting task. To be truly effective, the process needs to be automated to reduce the reliance on manual data interpretation. It is the aim of this research to automate this process using data from machinery
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Nkengue, Marc Junior. "Développement d'un vêtement intelligent pour le suivi et diagnostic en temps-réel de patients atteints de COVID-19 long." Electronic Thesis or Diss., Centrale Lille Institut, 2024. http://www.theses.fr/2024CLIL0013.

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En s'appuyant sur les résultats (prototypes textiles souples, capteurs et algorithmes) obtenus dans les projets scientifiques développés au sein de l’équipe de recherche (IOTFetMov (ANR), E-TexWeld (H2020)), cette thèse doctorale a pour objectif de développer un nouveau vêtement intelligent et connecté, afin de réaliser en temps-réel la détection et le suivi des symptômes du patient atteint de COVID-19 Long. De façon automatique, il s’agit de poser un pré-diagnostic basique à partir du traitement de signaux pertinents par des techniques intelligentes comme un outil d’aide à la décision à desti
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Wilson, Odell D. "An Automated Diagnostic Test and Tutorial Package for Basic Skills of Mathematics in Post Secondary Vocational Education of Kentucky: Construction and Validation." Digital Commons @ East Tennessee State University, 1987. https://dc.etsu.edu/etd/2996.

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The purpose of this research study was to determine characteristics of entering vocational students in Kentucky Area/State vocational schools and to develop a computerized diagnostic instrument and tutorial package for assisting students in the mastery of necessary basic skills in mathematics. After specific math skills were identified in which proficiency is required of vocational education students, item pools were constructed for each skill. The skill item pools were validated using approximately 500 public school students throughout the grades of four through eight in public schools of Har
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Books on the topic "Basic automatic diagnosis"

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Shoemaker, William C. Diagnostic Methods in Critical Care: Automated Data Collection and Interpretation (Basic and Clinical Cardiology Series, Vol 9). Marcel Dekker Inc, 1987.

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Ocampo, José Antonio. Resetting the International Monetary (Non)System. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198718116.001.0001.

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This book provides an analysis of the global monetary system and the necessary reforms that it should undergo to play an active role in the twenty-first century. As its title indicates, its basic diagnosis is that it is an ad hoc framework rather than a coherent system—a ‘non-system’—which evolved after the breakdown of the original Bretton Woods arrangement in the early 1970s. The book places a special focus on the asymmetries that emerging and developing countries face within the current system, and therefore on the development dimensions of the global monetary system and of global monetary
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Walsh, Thomas, ed. Visual Fields. Oxford University Press, 2010. http://dx.doi.org/10.1093/oso/9780195389685.001.0001.

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Visual Fields: Examination and Interpretation, 3rd edition contains revisions and updates of earlier material as well as a discussion of newer techniques for assessing visual field disorders. The book begins with a short history of the field of perimetry and goes on to present basic clinical aspects of examination and diagnosis of visual field defects in the optic nerve, optic disc, chorioretina, optic chiasm, optic tract, lateral geniculate field bodies, and the calcarine complex. Additional aspects of visual field examination are explored including those of monocular, binocular, and junction
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Ufimtseva, Nataliya V., Iosif A. Sternin, and Elena Yu Myagkova. Russian psycholinguistics: results and prospects (1966–2021): a research monograph. Institute of Linguistics, Russian Academy of Sciences, 2021. http://dx.doi.org/10.30982/978-5-6045633-7-3.

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The monograph reflects the problems of Russian psycholinguistics from the moment of its inception in Russia to the present day and presents its main directions that are currently developing. In addition, theoretical developments and practical results obtained in the framework of different directions and research centers are described in a concise form. The task of the book is to reflect, as far as it is possible in one edition, firstly, the history of the formation of Russian psycholinguistics; secondly, its methodology and developed methods; thirdly, the results obtained in different research
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Book chapters on the topic "Basic automatic diagnosis"

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Xu, Song, Lina Wang, and Jingjing Liu. "Sparse Model Identification for Nonstationary and Nonlinear Neural Dynamics Based on Multiwavelet Basis Expansion." In Recent Advances in AI-enabled Automated Medical Diagnosis. CRC Press, 2022. http://dx.doi.org/10.1201/9781003176121-14.

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Kawasaki, Yusuke, Hiroyuki Uga, Satoshi Kagiwada, and Hitoshi Iyatomi. "Basic Study of Automated Diagnosis of Viral Plant Diseases Using Convolutional Neural Networks." In Advances in Visual Computing. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-27863-6_59.

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Kolodenkova, Anna E., and Alexander I. Dolgiy. "Diagnosing of Devices of Railway Automatic Equipment on the Basis of Methods of Diverse Data Fusion." In Advances in Intelligent Systems and Computing. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-01821-4_29.

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Kovalev, Sergey M., Anna E. Kolodenkova, and Vladislav S. Kovalev. "Diagnostic Data Fusion Collected from Railway Automatics and Telemechanics Devices on the Basis of Soft Computing Technologies." In Advances in Intelligent Systems and Computing. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-39216-1_28.

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Tang, Xin, Katja Upadyaya, Hiroyuki Toyama, Mika Kasanen, and Katariina Salmela-Aro. "Assessing and Tracking Students’ Wellbeing Through an Automated Scoring System: School Day Wellbeing Model." In AI in Learning: Designing the Future. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-09687-7_4.

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AbstractThe assessment of student wellbeing has been often static and lagged behind for the intervention/diagnostic purpose. In this chapter, we aim to introduce an automated school wellbeing scoring dynamic real-time system, School Day Wellbeing Model. With Artificial Intelligence (AI)-based item sampling methods and answers scoring and reporting systems, the School Day Wellbeing Model can collect wellbeing data at low cognitive cost, track wellbeing real time at multiple levels (e.g., individual-, class-, school-level), and give immediate feedback. The model is constructed on the basis of the School Wellbeing Model, Study Demand-Resource Model, and OECD Social-Emotional Skill Model. In the book chapter, the wellbeing assessments, including AI-based assessments, are reviewed so that the strengths of the School Day Wellbeing Model are highlighted. User experiences are collected to show the utility of the model. During the COVID-19 pandemic, the need for such a model is imperatively high as students’ wellbeing has been largely dampened. As a result, the model has been appreciated by users and has served about 55,000 students so far in the globe. The future development of the model is also discussed.
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Yang, Dejun. "Intelligent Monitoring and Fault Diagnosis in Automatic Production." In Frontiers in Artificial Intelligence and Applications. IOS Press, 2024. http://dx.doi.org/10.3233/faia241085.

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In order to analyze the faults of equipment in the process of operation in time and feed them back to the information system synchronously, and provide decision-making information for the setting of maintenance scheme, the method of intelligent monitoring and fault diagnosis in textile automatic production is put forward. The condition monitoring system of textile machinery can monitor the signal parameters of textile equipment in operation, and then analyze the failure problems faced by textile equipment in the current control mode by comparing the system reference parameters. Based on this, taking vibration signal analysis as the breakthrough point, this paper expounds the condition monitoring signal analysis and fault diagnosis of textile machinery. The results show that the monitoring times are 8 times, and then the actual efficiency of fault diagnosis is obtained by analyzing the data, and the false alarm rate is less than 0.5%. Conclusion: The monitoring system based on vibration signal analysis has higher monitoring accuracy, which can accurately identify the fault problems and provide basic guarantee for the subsequent operation and maintenance work.
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Zhou, Xiangrong, and Hiroshi Fujita. "Automatic Organ Localization on X-Ray CT Images by Using Ensemble-Learning Techniques." In Machine Learning in Computer-Aided Diagnosis. IGI Global, 2012. http://dx.doi.org/10.4018/978-1-4666-0059-1.ch019.

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Location of an inner organ in a CT image is the basic information that is required for medical image analysis such as image segmentation, lesion detection, content-based image retrieval, and anatomical annotation. A general approach/scheme for the localization of different inner organs that can be adapted to suit various types of medical image formats is required. However, this is a very challenging problem and can hardly be solved by using traditional image processing techniques. This chapter introduces an ensemble-learning-based approach that can be used to solve organ localization problems. This approach can be used to generate a fast and efficient organ-localization scheme from a limited number of training samples that include both original images and target locations. This approach has been used for localizing five different human organs in CT images, and the accuracy, robustness, and computational efficiency of the designed scheme were validated by experiments.
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Yadav, Ashwani Kumar, Vaishali, Raj Kumar, and Archek Praveen Kumar. "Texture Segmentation and Features of Medical Images." In Research Anthology on Improving Medical Imaging Techniques for Analysis and Intervention. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-6684-7544-7.ch042.

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Texture analysis is one of the basic aspects of human visual system by which one can differentiate the objects and homogenous areas in an image. Manual diagnosis is not possible for huge database of images. Automatic diagnosis is required for greater accuracy in a shorter time. Texture analysis is required for effective diagnosis of medical images like functional MRI (magnetic resonance image) and diffusion tensor MRI, where only visualization is not sufficient to get the pathological information. This chapter explains the basic concepts of texture analysis and features available for analysis of medical images. Specifically, the intense review of texture segmentation and texture feature extraction and entropy measures of medical images have been done. The chapter also explores the available techniques for it. Common findings, comparative analysis, and gaps identified have also been mentioned on both issues.
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Yadav, Ashwani Kumar, Vaishali, Raj Kumar, and Archek Praveen Kumar. "Texture Segmentation and Features of Medical Images." In Handbook of Research on Disease Prediction Through Data Analytics and Machine Learning. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-2742-9.ch023.

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Texture analysis is one of the basic aspects of human visual system by which one can differentiate the objects and homogenous areas in an image. Manual diagnosis is not possible for huge database of images. Automatic diagnosis is required for greater accuracy in a shorter time. Texture analysis is required for effective diagnosis of medical images like functional MRI (magnetic resonance image) and diffusion tensor MRI, where only visualization is not sufficient to get the pathological information. This chapter explains the basic concepts of texture analysis and features available for analysis of medical images. Specifically, the intense review of texture segmentation and texture feature extraction and entropy measures of medical images have been done. The chapter also explores the available techniques for it. Common findings, comparative analysis, and gaps identified have also been mentioned on both issues.
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Sathees, Prabha. "Dental Image Segmentation Using Clustering Techniques and Level Set Methods." In Research Anthology on Improving Medical Imaging Techniques for Analysis and Intervention. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-6684-7544-7.ch031.

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Segmentation is necessary for dental images for finding the parts of the teeth, surrounding tissues, and bones. The human identification system in dental methodology is a tedious and time-consuming process. The automatic identification system is the best solution for dental diagnosis and dental treatment systems. Choosing an appropriate region of interest with high accuracy and success rate is a challenging one. This can be attained with the help of proper segmentation methodologies. The segmentation techniques proposed for the root canal treatment are analyzed and compared. Clustering techniques and level set methods with different edge maps are implemented for the proper analysis of segmentation in dental images. Finally, the integration of coherence-enhanced diffusion filtering in basic level set segmentation methodology seems to be effective in improving the segmentation performance of dental images.
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Conference papers on the topic "Basic automatic diagnosis"

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Hishida, Hirotoshi, Yuhiro Muroya, Hayato Tojo, and Tomomi Koide. "Basic Research on the Development of an Automatic Heart Sound Diagnosis System - Adding Another Lesion Data in AI Learning -." In 27th World Multi-Conference on Systemics, Cybernetics and Informatics. International Institute of Informatics and Cybernetics, 2023. http://dx.doi.org/10.54808/wmsci2023.01.32.

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Flanagan, Michael A., Carsten Andersson, and Peter Surland. "Effective Automatic Expert Systems for Dynamic Predictive Maintenance Applications." In ASME 1997 International Gas Turbine and Aeroengine Congress and Exhibition. American Society of Mechanical Engineers, 1997. http://dx.doi.org/10.1115/97-gt-064.

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As the need for specialist decision-making has increased with the volume of data produced by modern monitoring systems, and the current trend towards downsizing and external sourcing (for example, specialist consultant companies) has continued, the demand for computer-based expert systems for automatic machine condition (vibration and process) analysis and diagnosis has intensified. Various levels of success have been achieved, but most expert systems available today do not reflect the actual reasoning process of a human expert; are inherently obsolete for the continuous learning capability re
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Wu, Zhenhua, and Sheng-Jen Hsieh. "Design and Validation of Fault Diagnoser Based on Finite State Automaton and Sequential Function Chart for PLC Based Manufacturing System." In ASME/ISCIE 2012 International Symposium on Flexible Automation. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/isfa2012-7159.

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In ISFA-2010, we proposed a fault diagnoser design based on finite state automaton and sequential function chart to diagnose programmable logic controller (PLC) based manufacturing systems. A deficiency for that paper is that it only laid down a theoretical framework but lacking a detailed implementation and experiment validation. This paper aims at remedying the deficiency with detailed system design to diagnose discrete event system (DES) faults. Systematic diagnosis approach including modeling the plant, mapping output states with sensor readings, and designing diagnoser, was illustrated in
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Hishida, Hirotoshi, Koichi Tokuuye, Keiko Hishida, Hayato Tojo, Yasuhiro Hishida, and Tomomi Koide. "Basic Research on the Development of an Automatic Heart Sound Diagnosis System - Analysis of Heart Sounds for Learning Policy and Experiment for Prototype of Auscultation Part -." In 27th World Multi-Conference on Systemics, Cybernetics and Informatics. International Institute of Informatics and Cybernetics, 2023. http://dx.doi.org/10.54808/wmsci2023.01.24.

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El-Shafei, A., and N. Rieger. "Automated Diagnostics of Rotating Machinery." In ASME Turbo Expo 2003, collocated with the 2003 International Joint Power Generation Conference. ASMEDC, 2003. http://dx.doi.org/10.1115/gt2003-38453.

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This paper provides an overview of the current available technologies for automated machinery condition evaluation and fault diagnosis within an overall plant asset management system. The paper presents a basic overview of an integrated plant asset management system, and focuses on the available technologies for automated diagnostics including statistical analysis of data, parametric model diagnosis, non-parametric model diagnosis (artificial neural networks), and rule-based diagnostics including expert systems and fuzzy logic. The current state-of-the-art and the expected realistic future dev
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Reddy, T. Agami. "Comparison of Two Model Based Automated Fault Detection and Diagnosis Methods for Centrifugal Chillers." In ASME 2008 2nd International Conference on Energy Sustainability collocated with the Heat Transfer, Fluids Engineering, and 3rd Energy Nanotechnology Conferences. ASMEDC, 2008. http://dx.doi.org/10.1115/es2008-54002.

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Research has been ongoing during the last several years on developing robust automated fault detecting and diagnosing (FDD) methods applicable for process faults in chillers used in commercial buildings. These FDD methods involve using sensor data from available thermal, pressure and electrical measurements from commercial chillers to compute characteristic features (CF) which allow more robust and sensitive fault detection than using the basic sensor data itself. One of the proposed methods is based on the analytical redundancy approach using polynomial black-box multiple linear regression mo
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Loukis, E., K. Mathioudakis, and K. Papailiou. "A Methodology for the Design of Automated Gas Turbine Diagnostic Systems." In ASME 1993 International Gas Turbine and Aeroengine Congress and Exposition. American Society of Mechanical Engineers, 1993. http://dx.doi.org/10.1115/93-gt-047.

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A methodology for the design of automated diagnostic systems for Gas Turbines is presented. The first stage of the proposed methodology consists in an initial selection of instruments and measuring positions on the engine, based on a basic knowledge of the engine itself and previous experience, as well as modelling capabilities of the phenomena happening in it. It is followed by a stage of “learning” experiments. One purpose of these experiments is to provide measurement data, on which a final selection of instruments will be based. The instruments most suitable for the fault cases of interest
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Nesterenko, Andrii, and Maryna Filippova. "AUTOMATED DIAGNOSTIC OF TECHNOLOGICAL PROCESSES BY METHODS OF HIERARCHICAL MODELING AND DIAGNOSTIC PROCEDURES." In 17th IC Measurement and Control in Complex Systems. VNTU, 2024. https://doi.org/10.31649/mccs2024.2-04.

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The main aspects of the implementation of diagnostic systems using hierarchical modeling and diagnostic procedures are considered. Further directions of work for the construction of an effective diagnostic system are outlined. The basic idea of diagnostic models is based on components, where a system is defined as a set of components and relationships between them. Diagnostics of such a component system is carried out in two stages: detection of malfunctions and localization of problems. A large number of approaches and models are used to analyze malfunctions in automated systems. Most often,
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Boukhamla, Assia, Mohamed Hatem Bouziane, Akram Laib, et al. "GANs Investigation for Multimodal Medical Data Interpretation : Basic Architectures and Overview." In 2023 International Conference on Control, Automation and Diagnosis (ICCAD). IEEE, 2023. http://dx.doi.org/10.1109/iccad57653.2023.10152386.

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Prochazka, Michal, Robert Pinkas, Michal Janku, Josef Stryk, and Jiri Grosek. "AUTOMATED DETECTION OF PAVEMENT DEFECTS USING COMPUTER VISION." In 22nd SGEM International Multidisciplinary Scientific GeoConference 2022. STEF92 Technology, 2022. http://dx.doi.org/10.5593/sgem2022/2.1/s10.33.

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Road managers are obliged by law to regularly monitor the condition of road pavements as part of road inspections. Visual inspections provide basic information on the condition of the road and regular assessments are the basis for planning maintenance and repairs. These inspections are usually carried out from a dedicated car and recorded manually by an operator or done by special sophisticated and very costly devices with cameras and various sensors. Inspections are done in defined periods based on road class and type of inspection. This paper presents a pilot test of a new method of monitori
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Reports on the topic "Basic automatic diagnosis"

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Seginer, Ido, Louis D. Albright, and Robert W. Langhans. On-line Fault Detection and Diagnosis for Greenhouse Environmental Control. United States Department of Agriculture, 2001. http://dx.doi.org/10.32747/2001.7575271.bard.

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Background Early detection and identification of faulty greenhouse operation is essential, if losses are to be minimized by taking immediate corrective actions. Automatic detection and identification would also free the greenhouse manager to tend to his other business. Original objectives The general objective was to develop a method, or methods, for the detection, identification and accommodation of faults in the greenhouse. More specific objectives were as follows: 1. Develop accurate systems models, which will enable the detection of small deviations from normal behavior (of sensors, contro
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Bogdanov, Sergey I. Electronic educational resource "Basic aspects of narcology". SIB-Expertise, 2024. http://dx.doi.org/10.12731/er0783.29012024.

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The electronic educational resource (hereinafter referred to as EER) “Basic aspects of narcology” is designed for 36 training hours. This distance learning course aims to develop communicative competence, prepare for solving standard problems of professional activity using information resources, medical and biological terminology, and is also aimed at optimizing the educational process at the university, creating conditions for achieving the required level of modern education and comprehensive development of the personality of students . The EER was developed in accordance with the Federal Sta
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3

Paule, Bernard, Flourentzos Flourentzou, Tristan de KERCHOVE d’EXAERDE, Julien BOUTILLIER, and Nicolo Ferrari. PRELUDE Roadmap for Building Renovation: set of rules for renovation actions to optimize building energy performance. Department of the Built Environment, 2023. http://dx.doi.org/10.54337/aau541614638.

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In the context of climate change and the environmental and energy constraints we face, it is essential to develop methods to encourage the implementation of efficient solutions for building renovation. One of the objectives of the European PRELUDE project [1] is to develop a "Building Renovation Roadmap"(BRR) aimed at facilitating decision-making to foster the most efficient refurbishment actions, the implementation of innovative solutions and the promotion of renewable energy sources in the renovation process of existing buildings. In this context, Estia is working on the development of infer
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4

Bogdanov, Sergey I. Electronic educational resource "Ambulance and emergency medical care for mental disorders and behavioral disorders at the prehospital stage". SIB-Expertise, 2024. http://dx.doi.org/10.12731/er0784.29012024.

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Abstract:
The Electronic educational resource (hereinafter referred to as EER) “Basic aspects of narcology” is designed for 36 training hours. This distance learning course aims to develop communicative competence, prepare for solving standard problems of professional activity using information resources, medical and biological terminology, and is also aimed at optimizing the educational process at the university, creating conditions for achieving the required level of modern education and comprehensive development of the personality of students . The EER was developed in accordance with the Federal Sta
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5

Muldavin, Esteban, Yvonne Chauvin, Teri Neville, et al. A vegetation classi?cation and map: Guadalupe Mountains National Park. National Park Service, 2024. http://dx.doi.org/10.36967/2302855.

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A vegetation classi?cation and map for Guadalupe Mountains National Park (NP) is presented as part of the National Park Service Inventory & Monitoring - Vegetation Inventory Program to classify, describe, and map vegetation communities in more than 280 national park units across the United States. Guadalupe Mountains NP lies in far west Texas and contains the highest point in the state, Guadalupe Peak (8,751 ft; 2,667 m). The mountain escarpments descend some 5,000 ft (1,500 m) to the desert basins below forming a complex geologic landscape that supports vegetation communities ranging from
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