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Journal articles on the topic 'Creation of Diagnostic Mode'
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1
Hlinomazová, Zuzana, and Ivo Hrazdira. "Standardisation in Ultrasonography: Principle and Diagnostic Significance." Acta Medica (Hradec Kralove, Czech Republic) 47, no. 4 (2004): 305–8. http://dx.doi.org/10.14712/18059694.2018.112.
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Disadvantage of ultrasonography is its dependence on subjective assessment of displayed images. The way how to minimize both intraobserver and interobserver differences is creation of standard conditions for examination including a quantitative approach to evaluation of tissue reflectivity. The oldest mode of standardisation is standardised A- scan, used in ophthalmology. It enables differentiation of echoes, reflected from different ocular structures and is helpful in assessment of extraocular muscle thickness. Standardisation of B- scan depends on the type of diagnostic device and is based on quantification of image echogenicity. In our study reference values of grey-level histogram were established for some thyroid diseases using standard setting of imaging parameters. Results indicate that both standardised A- and B- scan should be helpful in differential diagnostics.
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Randles, Theodore J., Prof Zhe Zhang, and William Johnson Miller. "The SccoB Process." International Journal of Strategic Decision Sciences 9, no. 4 (October 2018): 16–31. http://dx.doi.org/10.4018/ijsds.2018100102.
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Based on qualities of the four-stroke engine and the medical diagnostic process, five characteristics of knowledge were identified and serve as the basis of a self-sustaining knowledge creation process. The SccoB process forms a complementary relation with the firm's existing processes and provides a counterweight to its existing mode of thought. This is done through an internal, counter-culture research institute and the creation of stress and profound insights through the identification and analysis of operational anomalies. SccoB is also a mapping process which moves the organization to greater quality and agility and to more advanced forms of mapping, such as the mapping of technical skills, complex diagnostic problem spaces, business process knowledge requirements, and cognitive force.
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Kluczyk, Marcin, Andrzej Grządziela, and Tomislav Batur. "Diagnostic Model of the Marine Propulsion System." Applied Mechanics and Materials 817 (January 2016): 57–63. http://dx.doi.org/10.4028/www.scientific.net/amm.817.57.
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Naval propulsion systems are characterized by a high degree of complexity within a single system and a large variation between the solutions applied to individual vessels. In this situation, issues relating to the comprehensive diagnostic is a serious problem. Diagnostics models are useful to made the this problem easier. It should be emphasized that it is impossible to develop a universal model correct for all types of vessels. The paper presents general guidelines for the creation of diagnostic models. The results of first stage of studies on diagnostic model covers unit equipped with a twin-engine twin-shaft drive system had been presented.Introduction Changes of technical state of the machine occur as a result of its response to changes in the energy emitted by them. If qualitative and quantitative parameters of this energy are known diagnostician after proper analysis is able to determine the technical condition of the machine. It can be concluded that the technical diagnostics is a test of object response to the impact of energy causing change of its technical condition [9]. As far as the destruction of the object model is concerned we find that the degree of wear of the machine is proportional to the energy dissipated from it.
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Ahmed, Heersh, and Boris Osipov. "MULTI-MODE IDENTIFICATION OF OBTAINING THE ADEQUATE MODEL OF TURBOJET ENGINE TJ-100A-Z FOR DIAGNOSTICS BY THERMALGASDYNAMIC PARAMETERS." Perm National Research Polytechnic University Aerospace Engineering Bulletin, no. 60 (2020): 5–14. http://dx.doi.org/10.15593/2224-9982/2020.60.01.
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When monitoring and diagnosing the state of gas turbine engines by thermodynamic parameters, adequate mathematical models of these engines are used. This name means diagnostic methods based on special processing and analysis of the values of thermogasdynamic and other parameters measured on a working turbojet engine [1] using its mathematical model. The most important in the system of technical diagnostics is the mathematical model of the engine. Its creation is a problem since, as a rule, the specifications of engine components are not given in the technical documentation. In this regard, obtaining complete mathematical models of engines for diagnostic purposes is an urgent task. There are various approaches to obtaining the characteristics of nodes and one of them is the use of generalized characteristics, for example, developed at the N.E. Zhukovsky Air Force Engineering Academy at the Department 201 "Theory of Air-Jet Engines" under the direction of Professor Nechayev Yu.N. Experience using such characteristics has shown that such characteristics can be used, but in a fairly narrow range of throttle modes. As a rule, this range was limited to no more than 40 % of the calculated (nominal) mode, which significantly limits the capabilities of the mathematical model of turbojet engines when implementing diagnostics using thermodynamic and dynamic parameters. This article proposes an algorithm developed by the authors a lot of mode identification, implemented as a computer program. As an object of study used turbojet engine TJ-100A-Z manufactured in the Czech Republic. For this, the turbojet engine obtained the characteristics of the main components (compressor, combustion chamber, turbine and nozzle) using the throttle characteristics given in the technical conditions. The calculation results are presented in the form of tables and graphs with error analysis in the calculation before and after identification. The comparison of the errors of the parameters of the throttle characteristics with the errors of the sensors for measuring these parameters is given.
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Zimovets, V. I., S. V. Shamatrin, D. E. Olada, and N. I. Kalashnykova. "Functional Diagnostic System for Multichannel Mine Lifting Machine Working in Factor Cluster Analysis Mode." Journal of Engineering Sciences 7, no. 1 (2020): E20—E27. http://dx.doi.org/10.21272/jes.2020.7(1).e4.
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The primary direction of the increase of reliability of the automated control systems of complex electromechanical machines is the application of intelligent information technologies of the analysis of diagnostic information directly in the operating mode. Therefore, the creation of the basics of information synthesis of a functional diagnosis system (FDS) based on machine learning and pattern recognition is a topical task. In this case, the synthesized FDS must be adaptive to arbitrary initial conditions of the technological process and practically invariant to the multidimensionality of the space of diagnostic features, an alphabet of recognition classes, which characterize the possible technical states of the units and devices of the machine. Besides, an essential feature of FDS is the ability to retrain by increasing the power of the alphabet recognition classes. In the article, information synthesis of FDS is performed within the framework of information-extreme intellectual data analysis technology, which is based on maximizing the information capacity of the system in the process of machine learning. The idea of factor cluster analysis was realized by forming an additional training matrix of unclassified vectors of features of a new recognition class obtained during the operation of the FDS directly in the operating mode. The proposed algorithm allows performing factor cluster analysis in the case of structured feature vectors of several recognition classes. In this case, additional training matrices of the corresponding recognition classes are formed by the agglomerative method of cluster analysis using the k-means procedure. The proposed method of factor cluster analysis is implemented on the example of information synthesis of the FDS of a multi-core mine lifting machine. Keywords: information-extreme intelligent technology, a system of functional diagnostics, multichannel mine lifting machine, machine learning, factor cluster analysis.
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Тамаргазин, Александр Анатолиевич, Людмила Борисовна Приймак, and Валерий Владиславович Шостак. "Methods of clustering parameters in the creation of neural network multi-mode dynamic models of aircraft engines." Aerospace technic and technology, no. 4sup2 (August 27, 2021): 71–78. http://dx.doi.org/10.32620/aktt.2021.4sup2.09.
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The presence on modern aviation gas-turbine engines of dozens and even hundreds of sensors for continuous registration of various parameters of their operation makes it possible to collect and process large amounts of information. This stimulates the development of monitoring and diagnostic systems. At the same time the presence of great volumes of information is not always a sufficient condition for making adequate managerial decisions, especially in the case of evaluation of the technical condition of aviation engines. Thus it is necessary to consider, that aviation engines it is objects which concern to individualized, i.e. to such which are in the sort unique. Therefore, the theory of creating systems to assess the technical state of aircraft engines is formed on the background of the development of modern neural network technology and requires the formation of specific methodological apparatus. From these positions in the article the methods which are used at carrying out clustering of the initial information received at work of modern systems of an estimation and forecasting of a technical condition of aviation gas-turbine engines are considered. This task is particularly relevant for creating neural network multimode models of aircraft engines used in technical state estimation systems for identification of possible failures and damages. Metric, optimization and recurrent methods of input data clustering are considered in the article. The main attention is given to comparison of clustering methods in order to choose the most effective of them for the aircraft engine condition evaluation systems and suitable for implementation of systems with meta-learning. The implementation of clustering methods of initial data allows us to breakdown diagnostic images of objects not by one parameter, but by a whole set of features. In addition, cluster analysis, unlike most mathematical-statistical methods do not impose any restrictions on the type of objects under consideration, and allows us to consider a set of raw data of almost arbitrary nature, which is very important when assessing the technical condition of aircraft engines. At the same time cluster analysis allows one to consider a sufficiently large volume of information and sharply reduce, compress large arrays of parametrical information, make them compact and visual.
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Arhun, S., Yu Borodenko, A. Hnatov, A. Popova, H. Hnatova, N. Kunicina, A. Ziravecka, A. Zabasta, and L. Ribickis. "Choice of Parameters for the Electrodrive Diagnostic System of Hybrid Vehicle Traction." Latvian Journal of Physics and Technical Sciences 57, no. 4 (August 1, 2020): 3–11. http://dx.doi.org/10.2478/lpts-2020-0017.
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AbstractWhen operating a hybrid vehicle (HEV), it is important to reduce maintenance and repair costs. The HEV electric drive (ED) consists of electronic, electrical and mechanical parts and is considered a complex diagnostic model. The availability of an electrical part greatly simplifies the process of monitoring and obtaining information about the state of the system. In order to create a hybrid diesel-electric propulsion system (HDEPS), the choice of structural and functional parameters as diagnostic ones is justified, the control points are chosen, and the necessary accuracy and unambiguity of measurements are determined. Qualitative evaluations of the electrical processes occurring in the power supply circuit of ED from a high-voltage accumulator battery for the selection of diagnostic parameters according to the criteria of sensitivity, informative character, stability and manufacturability of measurements are presented. It has been revealed that during HDEPS diagnostics both stable and transient modes of operation of electric machines should be considered; for analysis of ED technical state it is necessary to have information about current mode of HDEPS load; for measurement of instantaneous values of supply voltage and consumption current it is necessary to select the sensors with short response time and linear conversion function. In terms of sensitivity to structural changes in the circuit and parametric deviations, it is necessary to choose, as diagnostic parameters, the voltage or current, depending on the mode of operation of the ED and the point of measurement of the electrical value. The obtained results are the basis for creating a new system of diagnostics of electric power supply HDEPS in this direction.
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Volobuev, Andrei N., Vasiliy F. Pyatin, Natalya P. Romanchuk, Petr I. Romanchuk, and Svetlana V. Bulgakova. "Modeling of stochastic brain function in artificial intelligence." Science and Innovations in Medicine 4, no. 3 (September 15, 2019): 8–14. http://dx.doi.org/10.35693/2500-1388-2019-4-3-8-14.
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Objectives -research of stochastic brain function in respect to creation of artificial intelligence. Material and methods. Mathematical modeling principles were used for simulation of brain functioning in a stochastic mode. Results. Two types of brain activity were considered: determinated type, usually modeled using the perceptron, and stochastic type. It is shown, that stochastic brain function modeling is the necessary condition for AI to become capable of creativity, generation of new knowledge. Mathematical modeling of a neural network of the cerebral cortex, consisting of the set of the cyclic neuronal circuits (memory units), was performed for the stochastic mode of brain functioning. Models of "two-dimensional" and "one-dimensional" brain were analyzed. The pattern of excitation in memory units was calculated in the "one-dimensional" brain model. Conclusion. Relying on the knowledge of the stochastic mode of brain function, a way of creation of AI can be offered. а-rhythm of a patient is a recommended focus of the therapist's attention in diagnostics and treatment of brain disorders. It was noted, that the alpha wave amplitude and frequency could indicate the cognitive, creative and intuitive abilities of a person.
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МАМЕДОВ, Р. К., and Е. К. РАГИМОВА. "MATHEMАTICAL MODEL OF THE RESPIRATORY SYSTEM." Transport development, no. 1(1) (September 27, 2017): 155–60. http://dx.doi.org/10.33082/td.2017.1-1.18.
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Modeling of organs and structures of the human body, in particular, the development of a mathematical model of gas exchange of the respiratory system, makes it possible to predict critical situations, to clarify the mecha-nisms of pathology formation. This, in turn, expands the scope of application of diagnostic methods and devices and is a prerequisite for the creation of automated diagnostic tools.
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Chen, Tom, Shirley Ou Yang, and Cheryl Leo. "The beginning of value co-creation: understanding dynamics, efforts and betterment." Journal of Service Theory and Practice 27, no. 6 (November 13, 2017): 1145–66. http://dx.doi.org/10.1108/jstp-12-2015-0257.
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Purpose The purpose of this paper is to understand the beginning of value co-creation by uncovering the roles, efforts, and desired outcomes of employees and how they affect employees’ responses to their firm’s co-creation initiatives. Design/methodology/approach This study applies a single case study to explore micro-level processes at the beginning of value co-creation informed by a case about how a Taiwanese firm moved from a conventional to a co-creative business model. Findings The case study findings affirm nine subthemes that underlie three key themes: co-creation dynamics, efforts, and betterment. The authors provide a value co-creation framework that is informed by nine subthemes derived from interview data. Research limitations/implications Current literature on understanding value co-creation processes focuses on formalized co-creation processes which produce diverse and contextually dependent findings. The authors contribute to current value co-creation literature by offering convergent insights into the interplay of dynamics, efforts, and betterment experienced by employees transitioning to a value co-creation process. Practical implications The authors offer a diagnostic value co-creation checklist and propose three benefits of using the checklist, which can help managers mitigate the uncertainty that arises during the transition from a conventional to a co-creation firm. Originality/value The study responds to calls for research to investigate where and when the co-creation of value emerges, value co-creation behavior from employees’ point of view, and employees’ roles in the co-creation of value.
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Xiao, Lingfei, Yanbin Du, Jixiang Hu, and Bin Jiang. "Sliding Mode Fault Tolerant Control with Adaptive Diagnosis for Aircraft Engines." International Journal of Turbo & Jet-Engines 35, no. 1 (March 26, 2018): 49–57. http://dx.doi.org/10.1515/tjj-2016-0023.
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AbstractIn this paper, a novel sliding mode fault tolerant control method is presented for aircraft engine systems with uncertainties and disturbances on the basis of adaptive diagnostic observer. By taking both sensors faults and actuators faults into account, the general model of aircraft engine control systems which is subjected to uncertainties and disturbances, is considered. Then, the corresponding augmented dynamic model is established in order to facilitate the fault diagnosis and fault tolerant controller design. Next, a suitable detection observer is designed to detect the faults effectively. Through creating an adaptive diagnostic observer and based on sliding mode strategy, the sliding mode fault tolerant controller is constructed. Robust stabilization is discussed and the closed-loop system can be stabilized robustly. It is also proven that the adaptive diagnostic observer output errors and the estimations of faults converge to a set exponentially, and the converge rate greater than some value which can be adjusted by choosing designable parameters properly. The simulation on a twin-shaft aircraft engine verifies the applicability of the proposed fault tolerant control method.
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Slapa, Rafal Z., Antoni Piwowonski, Wieslaw S. Jakubowski, Jacek Bierca, Kazimierz T. Szopinski, Jadwiga Slowinska-Srzednicka, Bartosz Migda, and R. Krzysztof Mlosek. "Shear Wave Elastography May Add a New Dimension to Ultrasound Evaluation of Thyroid Nodules: Case Series with Comparative Evaluation." Journal of Thyroid Research 2012 (2012): 1–6. http://dx.doi.org/10.1155/2012/657147.
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Although elastography can enhance the differential diagnosis of thyroid nodules, its diagnostic performance is not ideal at present. Further improvements in the technique and creation of robust diagnostic criteria are necessary. The purpose of this study was to compare the usefulness of strain elastography and a new generation of elasticity imaging called supersonic shear wave elastography (SSWE) in differential evaluation of thyroid nodules. Six thyroid nodules in 4 patients were studied. SSWE yielded 1 true-positive and 5 true-negative results. Strain elastography yielded 5 false-positive results and 1 false-negative result. A novel finding appreciated with SSWE, were punctate foci of increased stiffness corresponding to microcalcifications in 4 nodules, some not visible on B-mode ultrasound, as opposed to soft, colloid-inspissated areas visible on B-mode ultrasound in 2 nodules. This preliminary paper indicates that SSWE may outperform strain elastography in differentiation of thyroid nodules with regard to their stiffness. SSWE showed the possibility of differentiation of high echogenic foci into microcalcifications and inspissated colloid, adding a new dimension to thyroid elastography. Further multicenter large-scale studies of thyroid nodules evaluating different elastographic methods are warranted.
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Suleimenov, Batyrbek A., Laura A. Sugurova, Alibek B. Suleimenov, Aituar B. Suleimenov, and Oxana V. Zhirnova. "Synthesis of the equipment health management system of the turbine units' of thermal power stations." Mechanics & Industry 19, no. 2 (2018): 209. http://dx.doi.org/10.1051/meca/2017056.
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The aim of the research is the development of technical diagnostics subsystem with the possibility of its further integration into the automated system of equipment health management, which will improve the efficiency of data ware, hardware and software. Synthesis of intellectual diagnostic models was produced a by using the Matlab graphical agents. At the same time, there were synthesized models of three types: fuzzy, neural-network and model built by planning the full factorial experimental method. Was proposed the concept of the three-stage procedure of the diagnosis of the thermal power station's turbine unit, instead of the creation of diagnosis mathematical models and failure models of objects, immediately begin to develop an algorithm of diagnosis using advanced intelligent technologies. The technique of creating a sub-line diagnostics status of the turbine unit, which includes three main stages: identification of diagnostic features based on expert method; the synthesis of diagnostic model of the facility technical condition; research models on the stability, sensitivity and uniqueness, was proposed. The main diagnostic features of assessing the state of turbine equipment, which, in accordance with the concept developed, allow forming a matrix of planning a full factorial experiment. The proposed techniques and concepts were subjected to experimental verification. The intellectual diagnostic model of turbine unit equipment health was proposed, synthesized and investigated. It was found that the best model is the model, built using neuro-fuzzy algorithms. The simulation was provided for neuro-fuzzy algorithms and confirmed their effectiveness and compliance with the laws of the physical functioning of the HPC. The results of this research have been used in the development of Almaty CHP-2 turbine equipment health management subsystems, allow the further development of the theoretical foundations of intellectual systems, and demonstrate the possibility of using modern concepts to solve important technical problems. Subsystem of operative diagnosis and the following software implementation in a complex of automated technological process of thermal power control system allows one to make an early diagnosis of the equipment health. This significantly reduces the maintenance costs, improves reliability and security, as well as the effectiveness of the control system. In this regard, the results of this study provide further development of the theoretical foundations of the intellectual systems and demonstrate the possibility of modern concepts usage to determinate the important technical problems.
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Singh, J. K., Ritika Nagpal, and S. K. J. Pacif. "Statefinder diagnostic for modified Chaplygin gas cosmology in f(R,T) gravity with particle creation." International Journal of Geometric Methods in Modern Physics 15, no. 03 (February 20, 2018): 1850049. http://dx.doi.org/10.1142/s0219887818500494.
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In this paper, we have studied flat Friedmann–Lemaître–Robertson–Walker (FLRW) model with modified Chaplygin gas (MCG) having equation of state [Formula: see text], where [Formula: see text], [Formula: see text] and [Formula: see text] is any positive constant in [Formula: see text] gravity with particle creation. We have considered a simple parametrization of the Hubble parameter [Formula: see text] in order to solve the field equations and discussed the time evolution of different cosmological parameters for some obtained models showing unique behavior of scale factor. We have also discussed the statefinder diagnostic pair [Formula: see text] that characterizes the evolution of obtained models and explore their stability. The physical consequences of the models and their kinematic behaviors have also been scrutinized here in some detail.
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Ostapenko, Andrei Aleksandrovich. "The model of full-time school: Ukrainian variant." Педагогика и просвещение, no. 4 (April 2020): 198–209. http://dx.doi.org/10.7256/2454-0676.2020.4.33370.
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This peer review analyzes the monograph published in Ukraine by Professors N. P. Lebedik and V. F. Morgun “The creation of full-time hub school as an educational complex". The work continues the traditions of the graduates of Poltava School of Pedagogy A. S. Makarenko, V. A. Sukhomlinsky, I. A. Zyazyun. The book offers the original variant of the model of an educational complex “A Full-time Boarding School”, and describes the normative legal, organizational-methodological and diagnostic approaches towards creation of such schools. The book is characterized by elaboration of all aspects of the school life: from detailed description of schedule to the options of school menu. The novelty of the proposed model consists in the following: a) the original unchangeable schedule of classes for the school day; b) nonstandard variants of organization of extended activities; c) models of combining different types of educational institutions; d) authorial outlook upon the arrangement of pedagogical activity in the cognate pedagogical systems. Particular attention deserves the proposed comprehensive diagnostics of social maturity of students as the integral indicator of school performance. Special place is held by description of the original health-saving invention of one of the authors – anti-scoliosis desk for either sedentary or standing work.
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Sultanov, Makhsud, Elena Zenina, Peter Shamigulov, Valentina Lunenko, and Olga Zhelyaskova. "Ensuring timely repair of power transformers based on data of complex diagnostics." E3S Web of Conferences 288 (2021): 01034. http://dx.doi.org/10.1051/e3sconf/202128801034.
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Timely diagnosis of power transformers is an essential component of ensuring reliable and safe operation of power stations and substations, on which the reliability of the power system depends. Detection of defects in the initial stage allows to maintain reliable operation of transformers, helps to define the "life cycle" and simplify the planning of their replacement. The paper presents an analysis of existing approaches to the creation of power equipment diagnostics systems using the example of power transformers. A neural network model has been developed, demonstrating the possibility of using power transformers to estimate the current residual resource based on the analysis of available diagnostic data.
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Khalyasmaa, Alexandra. "Machine learning as a tool of high-voltage electrical equipment lifecycle control enhancement." Proceedings of Irkutsk State Technical University 24, no. 5 (October 2020): 1093–104. http://dx.doi.org/10.21285/1814-3520-2020-5-1093-1104.
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The purpose of the study is to analyze the practical implementation of high-voltage electrical equipment technical state estimation subsystems as a part of solving the lifecycle management problem based on machine learning methods and taking into account the effect of the adjacent power system operation modes. To deal with the problem of power equipment technical state analysis, i.e. power equipment state pattern recognition, XGBoost based on gradient boosting decision tree algorithm is used. Its main advantages are the ability to process gapped data and efficient operation with tabular data for solving classification and regression problems. The author suggests the formation procedure of correct and sufficient initial database for high-voltage equipment state pattern recognition based on its technical diagnostic data and the algorithm for training and testing sets creation in order to improve the identification accuracy of power equipment actual state. The description and justification of the machine learning method and corresponding error metrics are also provided. Based on the actual states of power transformers and circuit breakers the sets of technical diagnostic parameters that have the greatest impact on the accuracy of state identification are formed. The effectiveness of using power systems operation parameters as additional features is also confirmed. It is determined that the consideration of operation parameters obtained by calculation as a part of the training set for high-voltage equipment technical state identification makes it possible to improve the tuning accuracy. The developed structure and approaches to power equipment technical state analysis supplemented by power system operation mode data and diagnostic results provide an information link between the tasks of technological and dispatch control. This allows us to consider the task of power system operation mode planning from the standpoint of power equipment technical state and identify the priorities in repair and maintenance to eliminate power network “bottlenecks”.
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Andrejevic-Stosovic, Miona, and Vanco Litovski. "Hierarchical approach to diagnosis of electronic circuits using ANNs." Journal of Automatic Control 20, no. 1 (2010): 45–52. http://dx.doi.org/10.2298/jac1001045a.
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In this paper, we apply artificial neural networks (ANNs) to the diagnosis of a mixed-mode electronic circuit. In order to tackle the circuit complexity and to reduce the number of test points hierarchical approach to the diagnosis generation was implemented with two levels of decision: the system level and the circuit level. For every level, using the simulation-before-test (SBT) approach, fault dictionary was created first, containing data relating the fault code and the circuit response for a given input signal. Also, hypercomputing was implemented, i.e. we used parallel simulation of large number of replicas of the original circuit with faults inserted to achieve fast creation of the fault dictionary. ANNs were used to model the fault dictionaries. At the topmost level, the fault dictionary was split into parts simplifying the implementation of the concept. During the learning phase, the ANNs were considered as an approximation algorithm to capture the mapping enclosed within the fault dictionary. Later on, in the diagnostic phase, the ANNs were used as an algorithm for searching the fault dictionary. A voting system was created at the topmost level in order to distinguish which ANN output is to be accepted as the final diagnostic statement. The approach was tested on an example of an analog-to-digital converter.
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Panaskin, Denis V., Yelyzaveta O. Bilokon, and Oleksii O. Piddiachyi. "Methods for Improving the Efficiency of Diagnostic Systems in the Neural Network-based Sound Analysis." International Journal of Biology and Biomedical Engineering 15 (July 30, 2021): 325–33. http://dx.doi.org/10.46300/91011.2021.15.39.
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The study of the possibilities of modelling the use of neural networks while increasing the efficiency of diagnostic systems consists of creating a standard that would satisfy the conditions for maintaining the sound quality. At the same time, the effectiveness of diagnostic systems can be considered when applied both in a technological environment and in a virtual space. The relevance of the study is determined by the possibilities of using the reference sound, which forms and uses the basis of the neural networks. The scientific novelty of the study is determined by the fact that an adaptive method for creating standards of units of measurable quantities with specified accuracy characteristics is proposed, subject to limited resources. The first version of the mathematical model of the measurement procedure is formed during reproduction, storage and transmission of a unit of measurement developed on the basis of a physical model, which, in turn, is built in accordance with a priori information on the principle of reproduction (storage and transmission) of a unit of measurement, a list of informative parameters and influential quantities when measuring. The authors have developed the necessary accuracy characteristics, specified by the technical specifications and determined the resources allocated for the creation of the standard. The practical significance of the study lies in the establishment of distributed networks for sound quality measurement, mainly within the structures of the study of sound transmission between high-tech devices.
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Зимовець, Вікторія Ігорівна, Олександр Сергійович Приходченко, and Микита Ігорович Мироненко. "ІНФОРМАЦІЙНО-ЕКСТРЕМАЛЬНИЙ КЛАСТЕР-АНАЛІЗ ВХІДНИХ ДАНИХ ПРИ ФУНКЦІОНАЛЬНОМУ ДІАГНОСТУВАННІ." RADIOELECTRONIC AND COMPUTER SYSTEMS, no. 4 (December 25, 2019): 105–15. http://dx.doi.org/10.32620/reks.2019.4.12.
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The study aims to increase the functional efficiency of machine learning of the functional diagnosis system of a multi-rope shaft hoist through cluster analysis of diagnostic features. To achieve the goal, it was necessary to solve the following tasks: formalize the formulation of the task of information synthesis, capable of learning a functional diagnosis system, which operates in the cluster-analysis mode of diagnostic signs; to propose a categorical model and, on its basis, to develop an algorithm for information-extreme cluster analysis of diagnostic signs in the process of information-extreme machine learning of a functional diagnostic system; carry out fuzzification of input fuzzy data by optimizing the geometric parameters of hyperspherical containers of recognition classes that characterize the possible technical conditions of the diagnostic object; to develop an algorithm and implement it on the example of information synthesis of the functional diagnostics system of a multi-rope mine hoisting machine. The object of the study is the processes of information synthesis of a functional diagnostic system capable of learning, integrated into the automated control system of a multi-rope mine hoisting machine. The subject of the study is categorical models, an information-extremal machine learning algorithm of a functional diagnostic system that operates in the cluster analysis model of diagnostic signs and constructs decision rules. The research methods are based on the ideas and methods of information-extreme intellectual data analysis technology, a theoretical-informational approach to assessing the functional effectiveness of machine learning and on the geometric approach of pattern recognition theory. As a result, the following results were obtained: a categorical model was proposed, and on its basis, an algorithm for information-extremal machine learning of the functional diagnostics system for a multi-rope mine hoist was developed and implemented, which allows you to automatically generate an input classified fuzzy training matrix, which significantly reduces time and material costs when creating incoming mathematical description. The obtained result was achieved by cluster analysis of structured vectors of diagnostic signs obtained from archival data for three recognition classes using the k-means procedure. As a criterion for optimizing machine learning parameters, we considered a modified Kullback measure in the form of a functional on the exact characteristics of diagnostic solutions and distance criteria for the proximity of recognition classes. Based on the optimal geometric parameters of the containers of recognition classes obtained during machine learning, decisive rules were constructed that allowed us to classify the vectors of diagnostic features of recognition classes with a rather high total probability of making the correct diagnostic decisions. Conclusions. The scientific novelty of the results obtained consists in the development of a new method for the information synthesis of the functional diagnostics system of a multi-rope mine hoisting machine, which operates in the cluster analysis model, which made it possible to automatically form an input classified fuzzy training matrix with its subsequent dephasification in the process of information-extreme machine learning system.
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Beegle-Krause, J. "GENERAL NOAA OIL MODELING ENVIRONMENT (GNOME): A NEW SPILL TRAJECTORY MODEL." International Oil Spill Conference Proceedings 2001, no. 2 (March 1, 2001): 865–71. http://dx.doi.org/10.7901/2169-3358-2001-2-865.
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ABSTRACT The General NOAA Oil Modeling Environment (GNOME) is a standard Eulerian/Lagrangian spill-trajectory model designed to meet the needs of planners and expert responders through three different user modes: Standard, GIS Output, and Diagnostic. Spills are modeled by Lagrangian Elements (LEs or splots) within continuous flow fields. GNOME supports the National Oceanic and Atmospheric Administration (NOAA)/Hazardous Materials Response Division (HAZMAT) standard for Best Guess and Minimum Regret trajectories by providing information about where the spill is most likely to go (Best Guess solution) and the uncertainty bound (Minimum Regret solution). The public, including spill responders, industry, and students, can use GNOME in Standard or GIS Output mode to prepare spill scenario-related products and for intuition building. These GNOME modes require a Location File that contains a regional trajectory model with a Mini-Expert System to aid in setting up the model. The Mini-Expert System sets up the trajectory model based on user input via dialog boxes. Information sources also are provided to help users answer the dialog questions. Responders can use GNOME's Diagnostic mode to quickly set up custom trajectory models for any area, as HAZMAT does during spill response. GNOME's Diagnostic model can accept circulation patterns from any hydrodynamic model (from two-dimensional steady-state to three-dimensional time-dependent models) with proper formatting. GNOME allows all users to save their work in files and create QuickTime movies. In GIS Output and Diagnostic modes, users can export the model results to GNOME Analyst to convert the data from LEs or splots to oil-concentration contours. Both the splots and contours can be exported to a GIS system (HAZMAT provides an ArcView extension). HAZMAT presently is creating Location Files for U.S. Coast Guard and NOAA priority locations with a design philosophy to allow users significant control over the model setup without requiring extensive spill modeling experience. GNOME, all Location Files, and documentation are available for download from NOAA's Office of Response and Restoration Web site1 under Aids for Oil Spill Responders.
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Kożusznik, Barbara, Anita Pollak, Dominik Adamek, and Damian Grabowski. "Development and Validation of the Influence Regulation and Deinfluentization Scale (DEI-beh)." Polish Journal of Applied Psychology 13, no. 4 (December 1, 2015): 91–108. http://dx.doi.org/10.1515/pjap-2015-0044.
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Abstract Our article presents work on the development and validation of Influence Regulation and Deinfluentization Scale (DEI-beh). Reviewing concepts regarding its influence constitutes an introduction to the original deinfluentization concept coined by Barbara Kożusznik. The author’s theory has provided the basis for creating a diagnostic tool. The elaborated DEI-beh method consists in evaluating conditions which determine managerial effectiveness and shape reciprocal influences among team members. Our article describes this tool’s creation and its validation procedure. Positive relationships between DEI-beh’s individual dimensions and temperament characteristics, defined in Pavlov’s concept (1952), and selected personality traits, proposed in the Five-Factor Model Personality by Costa and McCrae (1992), confirm the tool’s external validity.
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Leskin, Sergey, Dmitry Shvetsov, Evgeny Trykov, and Aleksey Puzakov. "Analysis of acoustic leak signals for enhancing sensitivity of control due to the creation of effective diagnostic indicators." Nuclear Energy and Technology 4, no. 2 (November 26, 2018): 141–47. http://dx.doi.org/10.3897/nucet.4.30775.
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Acoustic leak control systems (for instance, SAKT) are used at present for controlling leak tightness of equipment and pipelines, as well as for detecting in timely manner coolant leaks from the primary cooling circuit of nuclear reactor installations (NRI) during operation of power unit on different power levels in the modes of normal operation and during disturbances of normal operation. Time averaged dispersion of acoustic signal is used as the main diagnostic indicator for detecting leaks in these systems. Sensitivity of this indicator is determined by the exceedance by the signal of the preset threshold value which is defined in accordance with the background. Here, background values of acoustic signal depend on the operational modes of the equipment and do not allow in many cases determining coolant leak during early stages of leak development. New approach to the formation of diagnostic indicators for detecting loss of sealing in the circuit during early stage of development of coolant leak is suggested. Methodology for obtaining diagnostic indicators is based on the processing in different frequency bands of acoustic signal accompanying coolant leakage from the pipeline using the method of principal components. Efficiency of the developed methodology of coolant leak detection is illustrated by processing acoustic signals for experimental facility modeling coolant leakage in case of loss of sealing of the circuit. Even in the presence of significant acoustic background sensitivity of the method allows detecting leaks with significantly lower flow rates (up to five times smaller) than the conventional processing of acoustic signals. Implementation of the developed methodology will not require significant expenditures for upgrading already existing leak control systems operated at present on different NPPs.
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Tabaszewski, Maciej, and Czeslaw Cempel. "Similarity measures for diagnostic symptom evolution." Grey Systems: Theory and Application 6, no. 1 (February 1, 2016): 51–63. http://dx.doi.org/10.1108/gs-10-2015-0072.
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Purpose – The observed diagnostic symptoms are often characterized by local fluctuations of their values. Hence, instead of direct observation of symptoms it is worth observing their grey models and research similarity between life curves, which can enable to guess the nature of wear. The purpose of this paper is to find useful measures of similarity of diagnostics symptoms modeled by GM(1,1). Design/methodology/approach – Measures of similarity may be used to determine the character of wear of the diagnosed object by way of comparison with known examples, which have previously been obtained and identified. A methodology for creation of such comparisons based on pre-smoothing by means of a GM(1,1) model with rolling window has been proposed. The process of smoothing enables to eliminate local fluctuations of a symptom. Their existence makes it difficult to compare symptoms. Application of a rolling window enables in turn to map the symptom properly, which may be difficult in the case of relatively short period of accelerated wear and changes of symptom values. To compare the life curves it is also necessary to normalize the life curves, so that they are represented by the same number of measurements (compression or extension of the measure of operation). Findings – The paper concerns the similarity measures for symptom life curves obtained during vibration monitoring of fan mills working at a heat and power station. Similarity measures of symptoms were proposed and applied to the acquired data from the machines. Practical implications – The method of symptom modeling and life curve comparing can be used to discover type of wear of the machine and eventually estimation of the remaining useful life. Originality/value – The proposed method is very important for development of condition monitoring.
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Stepanov, Sergei Yurievich, Pavel Alexandrovich Orzhekovskiy, and Inna Borisovna Mishina. "Creative-digital diagnostics and reflexive development of school students in the course of studying Natural Sciences." SHS Web of Conferences 117 (2021): 04003. http://dx.doi.org/10.1051/shsconf/202111704003.
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The authors of the article raises an issue that is relevant from the perspective of modern education connected with difficulties of using the results of psychological diagnostics of students’ creative thinking carried out with the help of traditional testing techniques within the framework of the actual learning process. To address this issue, it is recommended to use the solutions suggested by the “forming” and “reflexive” approaches to this problem and conduct a synthesis of these two approaches using modern digital technologies. This way, it will provide us with an opportunity to turn developing (forming) procedures into diagnostic and turn diagnostic means into developing. Such a conceptual and technological symbiosis allowed us to create a computer networking system “CREO DATUM” enabling its users to carry out creative-digital diagnostics and psycho-pedagogical support of reflexive development of students’ creative potential at the same time based on the material of one of the natural sciences taught within the school curriculum, namely chemistry. This system includes a database of domain-specific creative tasks by solving which students demonstrate their thinking abilities; digitalization of this process in the online mode allows teachers to monitor and assess the dynamics of such parameters of their creative potential as divergence and criticality. This tool enables the teacher and student to predict the area of future development promptly and select further creative tasks on the subject via “CREO DATUM” taking into consideration the strengths and weaknesses of previous creative efforts. Experimental testing of the “CREO DATUM” system allowed us to categorize the students who took part in the research. Four groups have been identified: children with high creative potential, ones with low creative potential, divergents, and analysts. Methodological recommendations have been developed for each category of students based on the material of a natural science subject aimed at psychological and pedagogical support of their development.
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Liao, Xue Bing, Hui Qun Shan, Zhen Zhong Quan, and Lei Peng. "The Design and Implementation of Automatic Fire Extinguishing and Explosion Suppression System's Testing Equipment." Applied Mechanics and Materials 543-547 (March 2014): 1192–96. http://dx.doi.org/10.4028/www.scientific.net/amm.543-547.1192.
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According to the automatic fire extinguishing equipment requirements for explosion suppression platform system, this paper using the flexible neural tree and the clonal selection principle, describes the creation method of flexible neural tree model, embedded virtual instrument technology, to solve the nonlinear system fault diagnosis problem, realize the fire (explosion) detection system control components, improves the diagnostic sensitivity and accuracy. After the trial, the equipment illustrates high integrity, good versatility and high stability.
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TROCHIMIAK, BARBARA. "Application of the Three Aspects of Form model in pedagogical diagnosis." Interdyscyplinarne Konteksty Pedagogiki Specjalnej, no. 24 (March 15, 2019): 189–210. http://dx.doi.org/10.14746/ikps.2019.24.11.
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Barbara Trochimiak, Application of the Three Aspects of Form model in pedagogical diagnosis. Interdisciplinary Contexts of Special Pedagogy, no. 24, Poznań 2019.Pp. 189-210. Adam Mickiewicz University Press. ISSN 2300-391X. DOI: https://doi.org/10.14746/ikps.2019.24.11
The article presents a model of conducting activities in pedagogical diagnostics in accordance with the assumptions of the author’s method, called Three Aspects of Form (TAF). The concept expands the paradigm of diagnostic activities with therapeutic elements. Universal analytical categories for use in the study of processes with active human involvement are described. The most important element of the TAF model is discussed – a set of four tasks for the pedagogue-diagnostician, under which a simplified version of the first stage of didactic therapy is implemented. The idea of categorical trio-action as a foundation of the Three Aspects of Form of method, its relation to the creation of cultural and mental development are also presented. The scales of phenomenological, missionary and cultural activity as well as the principles of their modification are presented as well.
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Trevisan, Giovani, Kent J. Schwartz, Eric R. Burrough, Bailey Arruda, Rachel J. Derscheid, Michael C. Rahe, Edison de Souza Magalhães, Marcelo N. Almeida, Rodger G. Main, and Daniel C. L. Linhares. "Visualization and application of disease diagnosis codes for population health management using porcine diseases as a model." Journal of Veterinary Diagnostic Investigation 33, no. 3 (March 10, 2021): 428–38. http://dx.doi.org/10.1177/1040638721995782.
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Accurate and timely results of diagnostic investigations and laboratory testing guide clinical interventions for the continuous improvement of animal health and welfare. Infectious diseases can severely limit the health, welfare, and productivity of populations of animals. Livestock veterinarians submit thousands of samples daily to veterinary diagnostic laboratories (VDLs) for disease diagnosis, pathogen monitoring, and surveillance. Individual diagnostic laboratory reports are immediately useful; however, aggregated historical laboratory data are increasingly valued by clinicians and decision-makers to identify changes in the health status of various animal populations over time and geographical space. The value of this historical information is enhanced by visualization of trends of agent detection, disease diagnosis, or both, which helps focus time and resources on the most significant pathogens and fosters more effective communication between livestock producers, veterinarians, and VDL professionals. Advances in data visualization tools allow quick, efficient, and often real-time scanning and analysis of databases to inform, guide, and modify animal health intervention algorithms. Value is derived at the farm, production system, or regional level. Visualization tools allow client-specific analyses, benchmarking, formulation of research questions, and monitoring the effects of disease management and precision farming practices. We present here the approach taken to visualize trends of disease occurrence using porcine disease diagnostic code data for the period 2010 to 2019. Our semi-automatic standardized creation of a visualization platform allowed the transformation of diagnostic report data into aggregated information to visualize and monitor disease diagnosis.
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Cattani, Carlo, Olga Doubrovina, Sergei Rogosin, Sergei L. Voskresensky, and Elena Zelianko. "On the Creation of a New Diagnostic Model for Fetal Well-Being on the Base of Wavelet Analysis of Cardiotocograms." Journal of Medical Systems 30, no. 6 (September 14, 2006): 489–94. http://dx.doi.org/10.1007/s10916-006-9037-9.
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Molodov, V. A., A. I. Maksimov, I. V. Kiselevskaya-Babinina, V. Y. Kiselevskaya-Babinina, N. A. Karasyov, and I. A. Tyrov. "Simulation Modeling As a Tool of Decision Support During Reorganization of the Diagnostic Department of a Multidisciplinary Hospital." Russian Sklifosovsky Journal "Emergency Medical Care" 9, no. 1 (October 20, 2020): 27–34. http://dx.doi.org/10.23934/2223-9022-2020-9-1-27-34.
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Abstract Steadily growing flow of patients and a constant increase in the requirements for the quality of medical care more and more often lead to the need to reorganize the work of various departments of medical hospitals. However, such actions are very costly and do not always give the desired result. One of the effective methods of preliminary planning, as well as predicting the results of proposed transformations, is the method of simulation modeling of medical and diagnostic processes based on a specially created model. In this article we describe the original data on the operation of the admission and diagnostics department (ADD) of N.V. Sklifosovsky Institute, which served as one of the grounds for its reorganization, as well as the creation of a simulation model of ADD, reconstructed on the principles of a patient-oriented approach. We considered all stages of the model construction in detail and thereby justified its structure and the qualitative and quantitative parameters which formed the basis therein. The temporal and numerical results of modeling the flow of patients through the ADD, as well as the flow of changes in the parameters of the model to the throughput of the ADD are presented. Thus, specific examples show how problem areas of the existing diagnostic and treatment process can be identified, and what options are available for its optimization and modernization. In addition, suggestions are made for further improvement of the created model and options for its use, for example, for the study of various contingencies and emergencies, mass revenues, etc.
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AMPUŁA, Dariusz. "Prediction of Post-Diagnostic Decisions for Tested Hand Grenades’ Fuzes Using Decision Trees." Problems of Mechatronics Armament Aviation Safety Engineering 12, no. 2 (June 30, 2021): 39–54. http://dx.doi.org/10.5604/01.3001.0014.9332.
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The article presents a brief history of creation of decision trees and defines the purpose of the undertaken works. The process of building a classification tree, according to the CHAID method, is shown paying particular attention to the disadvantages, advantages, and characteristics features of this method, as well as to the formal requirements that are necessary to build this model. The tree’s building method for UZRGM (Universal Modernised Fuze of Hand Grenades) fuzes was characterized, specifying the features of the tested hand grenade fuzes and the predictors used that are necessary to create the correct tree model. A classification tree was built basing on the test results, assuming the accepted post-diagnostic decision as a qualitative dependent variable. A schema of the designed tree for the first diagnostic tests, its full structure and the size of individual classes of the node are shown. The matrix of incorrect classifications was determined, which determines the accuracy of incorrect predictions, i.e., correctness of the performed classification. A sheet with risk assessment and standard error for the learning sample and the v-fold cross-check were presented. On the selected examples, the quality of the resulting predictive model was assessed by means of a graph of the cumulative value of the lift coefficient and the "ROC" curve
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Cellmer, Radosław. "USE OF SPATIAL AUTOCORRELATION TO BUILD REGRESSION MODELS OF TRANSACTION PRICES." Real Estate Management and Valuation 21, no. 4 (December 1, 2013): 65–74. http://dx.doi.org/10.2478/remav-2013-0038.
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Abstract This paper presents the principles of studying global spatial autocorrelation in the land property market, as well as the possibilities of using these regularities for the construction of spatial regression models. Research work consisted primarily of testing the structure of the spatial weights matrix using different criteria and conducting diagnostic tests of two types of models: the spatial error model and the spatial lag model. The paper formulates the hypothesis that the application of spatial regression models greatly increases the accuracy of transaction price prediction while forming the basis for the creation of cartographic documents including, among others, maps of land value.
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Adamović, Katarina, Arso Vukićević, Radun Vulović, Smiljana Đorović, Radivoje Radaković, Gordana Jovičić, and Nenad Filipović. "Assessment of a knee resistance by applying the computational methods." Fizicka kultura 74, no. 1 (2020): 57–64. http://dx.doi.org/10.5937/fizkul2001057a.
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In tennis, the complex serving motions produce high mechanical stresses on player's musculoskeletal, tendon and ligament joints. In this paper, different cognitive methods have been integrated in order to non-invasively assess the knee's bone and cartilage resistance at the maximum power tennis serve. The proposed methodology is based on the creation of patientspecific biomechanical model, as well as on the tracking the knee's kinematics, ground force measurement, inverse dynamics modelling and analysis of the knee using the Finite Element Method with aim to assess the knee resistance of a tennis player, considering acute deformations and potential injuries. The main objective of this paper is development of the optimised computational technology and creation of practical diagnostic tool for non-invasive assessment of the knee function during specific moves and motions in tennis. It is expected that this approach can provide prediction and injury prevention in training and competitive tennis to a significant extent.
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Slabej, Martin, Michal Grinč, Peter Kotek, Matúš Kováč, and Martin Decký. "Utilization of Advanced Diagnostic Methods for Texture and Rut Depth Analysis on a Testing Pavement Section." Civil and Environmental Engineering 11, no. 1 (May 1, 2015): 21–28. http://dx.doi.org/10.1515/cee-2015-0003.
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Abstract Qualitative characteristics of pavement in wide range reflects the pavement serviceability, which is a summary of the characteristics of the pavement, providing a fast, smooth, economical and especially safe driving of motor-vehicles. The target factor of pavement serviceability and safety of roads represents the quality of their surface properties. In the framework of research activities performed in the Research Centre founded under the auspices of University of Žilina, individual parameters of pavement serviceability were monitored by pavement surface scanning. This paper describes the creation of a 3D - road surface model and its analysis and evaluation from the viewpoint of two pavement serviceability parameters - the rut depth and texture. Measurements were performed on an experimental pavement section used contemporary in an Accelerated Pavement Testing experiment. The long-term goal is to ascertain functions predicting degradation of these two pavement serviceability parameters.
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Cooksey, Elizabeth C., and Phil Brown. "Spinning on its Axes: DSM and the Social Construction of Psychiatric Diagnosis." International Journal of Health Services 28, no. 3 (July 1998): 525–54. http://dx.doi.org/10.2190/1c4d-b7xt-blly-wh4x.
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Through a critical examination of the psychiatric profession's heavy reliance on the Diagnostic and Statistical Manual of Mental Disorders, the authors explore the central role of diagnosis in the theory and practice of psychiatry. The set of beliefs that have guided the psychiatric profession since the creation of DSM-III are viewed as being tied to the new extension of the biopsychiatric medical model. From a sociological perspective, the authors address the issue of psychiatric nosology with reference to practice styles and professional dominance, and consider the impact of DSM's intrinsic social biases both within and outside psychiatry's traditionally drawn boundaries. They conclude that working solely within the confines of a medical framework of diagnosis, with little attention to the wider social and cultural contexts that should surround diagnostic practice, psychiatry will be unable to understand and explain the changing needs of its clientele.
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Oleksii, K. B., T. V. Savaryn, and I. I. Vorona. "GENERALIZED MODEL OF INTEGRATED TECHNOLOGY OF MEDICAL STUDENTS’ INDIVIDUAL WORK MANAGEMENT IN LEARNING A FOREIGN LANGUAGE." Медична освіта, no. 3 (December 3, 2019): 144–49. http://dx.doi.org/10.11603/me.2414-5998.2019.3.10659.
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Different approaches to the study of the system of students’ individual work management have been analyzed. The peculiarity of the proposed integrative technology of students’ individual work management is that the management effectiveness is achieved through the organization of the students’ individual work with diagnostic objectives, the achievement of which is subject to a clear description and definition.
Structural components of integrated technology are: goals, content, methods, organizational forms and functional components.
It has been proved that the effectiveness of management of students’ individual work depends on the goals and methods of achieving them; internal motivation and cognitive interests of students; quality of the content aspect of educational information for self-study; creation of favorable conditions for self-realization of a student; the methodological provision of the discipline, its precise planning, organization and management, student’s free time; the competent use of various forms of current and periodic control.
Integrated technology develops intellectual and creative students’ abilities, helps to make decisions. This circumstance is especially important, as in modern science, there is an increasingly evident tendency to the synthesis of knowledge, to the awareness and disclosure of the collectivity of cognition objects.
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Fung-Kee-Fung, M., D. E. Maziak, J. R. Pantarotto, J. Smylie, L. Taylor, T. Timlin, T. Cacciotti, et al. "Regional process redesign of lung cancer care: a learning health system pilot project." Current Oncology 25, no. 1 (February 28, 2018): 59. http://dx.doi.org/10.3747/co.25.3719.
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Background The Ottawa Hospital (toh) defined delay to timely lung cancer care as a system design problem. Recognizing the patient need for an integrated journey and the need for dynamic alignment of providers, toh used a learning health system (lhs) vision to redesign regional diagnostic processes. A lhs is driven by feedback utilizing operational and clinical information to drive system optimization and innovation. An essential component of a lhs is a collaborative platform that provides connectivity across silos, organizations, and professions.Methods To operationalize a lhs, we developed the Ottawa Health Transformation Model (ohtm) as a consensus approach that addresses process barriers, resistance to change, and conflicting priorities. A regional Community of Practice (cop) was established to engage stakeholders, and a dedicated transformation team supported process improvements and implementation.Results The project operationalized the lung cancer diagnostic pathway and optimized patient flow from referral to initiation of treatment. Twelve major processes in referral, review, diagnostics, assessment, triage, and consult were redesigned. The Ottawa Hospital now provides a diagnosis to 80% of referrals within the provincial target of 28 days. The median patient journey from referral to initial treatment decreased by 48% from 92 to 47 days.Conclusions The initiative optimized regional integration from referral to initial treatment. Use of a lhs lens enabled the creation of a system that is standardized to best practice and open to ongoing innovation. Continued transformation initiatives across the continuum of care are needed to incorporate best practice and optimize delivery systems for regional populations.
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Fedorenko, Mykola Ivanovych. "MODELS OF GENERATION OF INPUT DATA OF TRAINING OF NEURAL NETWORK MODULES FOR DIAGNOSTIC OF DISEASES IN UROLOGY." RADIOELECTRONIC AND COMPUTER SYSTEMS, no. 4 (December 25, 2019): 116–22. http://dx.doi.org/10.32620/reks.2019.4.13.
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The subject of the research presented in the article is neural network modules (NNMs), which are used to solve problems in the practice of diagnosing diseases in urology. This work aims to develop a mathematical model for generating a multitude of uroflowmetric parameters, in particular, graphs of uroflowrograms of the required volume, used as input data for NNM training. Objective: to develop a mathematical model for the formation of uroflowmetric parameters using a probabilistic approach based on a uniform "white noise". To develop an effective algorithm for the procedure for generating new parameter values and tools for its implementation. Methods used: NNM training methods, mathematical modeling methods, digital signal processing methods, tools for generating and processing random numerical sequences, digital data filtering methods. The following results were obtained: when creating and implementing a mathematical model for generating a large amount of training data, the requirements of randomness are taken into account when obtaining new values of uroflowmetric parameters. And at the same time, the obtained noise values are filtered to values of a given range, which are percentage-wise comparable to the amplitude value of the uroflowmetric parameter. Conclusions. The scientific novelty of the results is as follows: the NNM training method for recognizing diseases in urology has been improved by developing a mathematical model to generate uroflowmetric parameters for NNM training. The presented model allows you to create the necessary amount of data for training neural network modules in the course of experimental research on the recognition of diseases. The generation of uroflowmetric parameters is based on adding noise to the parameter values. This allows you to change the input data of the NNM training in a given range. This ensures the creation of the required input volume of the NNM training procedure. In the future, this contributes to the testing process of trained neural network modules with reliable information on the diagnosis of diseases in urology.
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Zavedeev, A. I. "Increasing of Reliability of Spacecraft Control System on Base of Robust Diagnostic Models and Division Principle in Parity Space." Mekhatronika, Avtomatizatsiya, Upravlenie 21, no. 4 (April 11, 2020): 249–56. http://dx.doi.org/10.17587/mau.21.249-256.
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Different directions of creation high reliability integrate spacecraft control system are discussed on base of robust diagnostic models and division principle in parity space. Problems of synthesis spacecraft control system algorithms are examined with incomplete apriory and distorted current information, action of uncontrolled and random factors, information losses and equipment failures. The structure of onboard attitude control system is synthesized and control algorithms are chosen, which guarantee robust stability and failure stability in presence indignant factors and obstacles. An instrumental structure and operational modes of spacecraft attitude control system are described. Methods of dynamic research, computer technology and modeling particularities are indicated. Diagnostic and reconfiguration algorithms for onboard complex of connection, navigation, geodesy satellites and earth inspectoral satellite in prolonged space flight utilization are proposed. Testing procedure is contains two stage: discovering and eliminating faults. Given mathematical system model is researched by means of difference signals, which forms with arise at fault emergence. The failure character is established by deciding rules on base difference signals and measures to it eliminating are took. Questions of onboard spacecraft control system failure stable improving are discussed on base principle reconfiguration with apply to adaptive logic in testing and diagnostic algorithms. The mathematical system model is researching with implementation of analytic reserving. Difference signals are formed, which arise at fault appearance. The adaptive approach to development testing and diagnostic systems provide for realization of flexible logic of control system function to take into account factual onboard equipment state. Special attention is devote to problem influence liquid fuel reactive engine agility on spacecraft control attitude system dynamic characteristics and precision. The effectiveness of prepositional approaches and algorithms is confirmed by mathematical modeling results for several actual technical systems. Recommendations to their practical applications are given.
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Sevryugina, Nadezhda, and Pavel Kapyrin. "Triad model: simulation - functional tensometry - information database in the assessment of the reliability of technological machines." E3S Web of Conferences 263 (2021): 04063. http://dx.doi.org/10.1051/e3sconf/202126304063.
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The concept of a multidisciplinary approach to assessing the resource of individual components of the machine by combining database information based on simulation techniques and functional tensomethration is proposed. Simulations determine the reperative points of the tendometric sensors. The creation of a diagnostic model using basic concepts of information theory has allowed the development of a synergistic model for the recognition of the area of displacement of areas of uncertainty, which will ensure the identification of the defect (risk-denial). The formation of an electronic database of parametric data on the nature of loads as a diagnostic indicator of the change in the accuracy of pairing in machine systems is justified. Experimental studies were conducted on the model of the quick-capler. Hierarchical structuring of the machine to the level of mating parts with digital control of the criticality of the magnitude of external and internal loads ensures reliability control throughout the entire service life of the machine. When disposing of machines, this data allows you to obtain information about the residual resources of the elements for their reuse or the feasibility of restoration. This, in turn, will ensure the environmental friendliness and economy of the process.
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Delegou, Ekaterini T., Georgia Mourgi, Elisavet Tsilimantou, Charalabos Ioannidis, and Antonia Moropoulou. "A Multidisciplinary Approach for Historic Buildings Diagnosis: The Case Study of the Kaisariani Monastery." Heritage 2, no. 2 (April 20, 2019): 1211–32. http://dx.doi.org/10.3390/heritage2020079.
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In this work, a multi-disciplinary approach regarding diagnostic study processes is presented, using as an example the Catholicon of Kaisariani Monastery in Attica, Greece. Kaisariani Monastery is considered one of the most important Byzantine architectural complexes in Greece. The Catholicon of Kaisariani Monastery was built during the middle Byzantine period, and has undergone many reconstructions during the centuries. It is a semi-complex, four-columned, cross-in-square church, with a cloisonné masonry. The suggested diagnostic processes included the creation of multidisciplinary thematic maps in Computer Aided Design (CAD) environment, which incorporated: (a) data of historical and architectural documentation; (b) data of geometric documentation; and (c) data of building materials characterization and decay diagnosis. The historical and general architectural data were acquired by thorough bibliographical/archival research. Geometric documentation data were acquired by three-dimensional (3D) laser scanner for the creation of the Catholicon section drawings, whereas image based photogrammetric techniques were utilized for the creation of a 3D textured model, from which orthoimages and architectural drawings of the Catholicon façades were developed. In parallel, characterization of building materials and identification of decay patterns took place after the onsite application of the nondestructive techniques of digital microscopy, infrared thermography and ground penetrating radar. These vast array kinds of data were elaborated and integrated into the architectural drawings, developing thematic maps that record and represent the current preservation state of the monument, a concerning major construction phases, the most important conservation intervention projects, building materials and decay. Furthermore, data quantification regarding the extent of building materials and decay at each monument’s façade took place. Therefore, correlation and better understanding of the environmental impact on building materials according to façade orientation and historical data, e.g., construction phases, was accomplished. In conclusion, the presented processes are multidisciplinary tasks that require collaboration among architects, surveyor engineers and materials scientists/engineers. They are also prerequisites for the planning and application of compatible and efficient conservation/restoration interventions, for the ultimate goal of the sustainable protection of a monument.
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Petrosov, Sergey, Michael Lemeshko, and Alexander Kozhemyachenko. "The robotized stand for the diagnosing compression refrigerating machines." MATEC Web of Conferences 224 (2018): 02088. http://dx.doi.org/10.1051/matecconf/201822402088.
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The process of creation and improvement of small refrigerating machines, the way of increasing their energy efficiency and reducing costs should be provided with reliable means and effective technologies of technical diagnosing these machines. One of the methods for achieving this goal is the creation of robotic research complexes. The authors, using the example of the automated research stand, show a possible variant of solving research problems when the researcher needs to make a measurement program, including a program of varying experimental conditions. Long-term tests with recording measurement results are performed in automatic mode without the operator-researcher’s participation. The robotic stand usually replaces the research operator, and ensures the effective results of long-term studies as they can be carried out more qualitatively and deeply, with simultaneous evaluation of results and adjustments of the measurement plans. The scheme and description of the developed stand are given. The significant advantages of a robotic stand are shown in comparison with the known analogous means of technical diagnostics of small refrigerating machines.
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Pena, Gil Patrus, and Joséde Souza Andrade-Filho. "How Does a Pathologist Make a Diagnosis?" Archives of Pathology & Laboratory Medicine 133, no. 1 (January 1, 2009): 124–32. http://dx.doi.org/10.5858/133.1.124.
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Abstract A pathologic diagnosis is the result of a complex series of activities, mastered by the pathologist. The nature of these activities is, however, rarely talked about in depth. The medical literature occasionally discusses aspects of the pathologic diagnosis processes, generally departing from the pathologic practice. The lack of a model makes discussions about the subject a matter of preference or personal style. Educational programs are largely based on the apprenticeship model, and the development of specific abilities rests on the personal aspects of both apprentice and mentor. A model for the pathologic diagnostic process is proposed. The process of diagnosis can be viewed as an action plan, encompassing 4 domains: (1) cognitive, (2) communicative, (3) normative, and (4) medical conduct. The cognitive domain involves processes of perception, attention, memory, search, hypothesis creation, and verification, among others. Communicative skills consist of providing arguments in support of a diagnostic conclusion, with adequate clinical and relevant pathologic information. Pathologic diagnosis is also subject to technical rules (based on empirical experiences), rules of rational choice (strategies aiming at definite goals), and consensual rules among peers. Finally, the pathologic diagnosis has to be evaluated in the sphere of medical conduct, from the perspectives of both the pathologist and the referring clinician. An understanding of the diagnostic process from a theoretic perspective will benefit pathology as a science and a medical specialty because it provides the basis for understanding diagnostic variations and discrepancies. Pathologic difficulties or errors can be mapped, allowing the institution of specific remedies. This model may also enhance training and educational strategies because specific emphasis can be directed toward a particular difficulty.
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Svenson, Nanette. "Capacity Diagnostics for Advancing Higher Education in the Developing World: A Case Study from the Republic of Panama." Investigación y Pensamiento Crítico 5, no. 1 (April 30, 2017): 5–16. http://dx.doi.org/10.37387/ipc.v5i1.61.
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Vol. 7 Núm. 1 (2019): Investigación y Pensamiento Críticoenero-abril 2017
The past decade of global development has witnessed extensive use of capacity diagnostics for improving the systems and skills needed for national, institutional and organizational development. Little of this experience, however, has been applied to higher education. This paper presents a model for adapting capacity diagnostics to creation of tools for (1) documenting existing resources in higher education institutions or academic areas, and (2) detailing perceptions in the labor market of current assets and gaps to facilitate better planning for and development of required curricular, research and personnel capacities. This model is illustrated with a case study from the Republic of Panama where a North-South research partnership between the National Secretariat for Science, Technology and Innovation (SENACYT) and Tulane University applied the diagnostic to an assessment of the country’s higher education and research in the social sciences. Findings suggest significant discrepancies between the present academic offer and the skills and knowledge required by the productive sector; they also highlight specific institutional and policy adjustments that would strengthen the university system overall and preparation in the social sciences at all levels. This paper refers to the Panama case in a broader discussion of how this research approach may be applied more broadly to inform policy for countries’ higher education systems, particularly in developing regions. As higher education becomes increasingly important for emerging economies’ competitiveness, potential for adoption of this model worldwide is considerable.
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Ismailova, Nazaket. "Management of the Forest Soils Fertility Based on Ecological Models in the South-Eastern Part of the Great Caucasus." Natural Systems and Resources, no. 1 (October 2019): 5–10. http://dx.doi.org/10.15688/nsr.jvolsu.2019.1.1.
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The bloks which are a structural part of the ecological fertility model in the mountain-forest brown and mountain-forest brown soils on the south-eastern slope of the Great Caucasus besides an importance of the ecological models composition have been analyzed in the article. By the main purpose of the given investigations a creation of ecological models of fertility was mountain-forest brown soils (middle mountain broken) and mountainforest brown soils (low mountain (mean broken), interrelation and dependence of biocenosis condition on the environment factors are studied a role of the main parameters (climate, relief, soil and etc) is revealed, the real and optimal parameters of the environment are established for the ecological models blocks creation. The model consists of 7 (seven) blocks: agroecological block soil structure block, soil regimes block, soil features block. value block, agromelioration block and forests biometric block. During the model blocks compiling the main diagnostic indiced as a granulometric composition, humus quantity and supply, water suspension pH, NPK, bulky mass, porosity and water-stable aggregates (> 0,25mm and > 1,00mm) in the mountain-forest brown and mountain-forest brown soils have been taken into account. A comparative character of the ecological fertility models in two different soil types which are dominant in forest ecosystems has been given.
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Сherkasov, Volodymyr. "Model of formation of readyness of future teachers of fine arts for use of computer graphics in professional activity." Academic Notes Series Pedagogical Science 1, no. 189 (August 2020): 85–90. http://dx.doi.org/10.36550/2415-7988-2020-1-189-85-90.
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The model of formation of readiness of future teachers of fine arts to use computer graphics in professional activity in the context of a subject field of our research contains three blocks, namely: methodological and target (the purpose, tasks, approaches, principles); content-procedural (stages, content, forms, methods, technologies); diagnostic and effective (criteria, indicators, levels of readiness). Сomputer graphics are used in almost all areas of human life, and above all, in art education, in the creation of images and processing of visual information obtained during the study of various arts, communication with various arts. With this approach, we consider it appropriate to determine the essence of computer graphics in the scientific environment and its place in the system of disciplines. At present, it is worth noting that computer graphics is a component of computer science and is studying the means and methods of creating and processing graphic images using computer technology. Computer graphics is a scientific discipline that develops a set of tools and techniques for automating coding and decoding graphic information. Computer graphics studies the methods of digital synthesis and processing of visual content. Our proposed model of forming the readiness of future teachers of fine arts to use computer graphics in professional activities contains three blocks: methodological-target, content-procedural and diagnostic-effective. For liquidity of research and experimental work the purpose is defined, tasks are developed, approaches and principles of the specified phenomenon of research are substantiated. The second block proposes the stages, content, forms, methods and technologies of forming the readiness of future teachers of fine arts to use computer graphics. In addition, at the diagnostic and effective stage of the experimental study, the criteria, indicators and levels of readiness are motivated. In addition, we have proposed pedagogical conditions aimed at improving the effectiveness of this phenomenon, including: purposeful motivation of future teachers of fine arts to use computer graphics in professional activities in the study of professional disciplines; mastering by future teachers of fine arts theoretical knowledge about the essence, content of computer graphics and methods of its use; improving practical skills and abilities to form the readiness of future teachers of fine arts to use computer graphics in professional activities.
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Kleiman, L. A., and V. I. Freyman. "IMPROVING THE FUNCTIONING RELIABILITY OF THE INFORMATION MANAGEMENT SYSTEM ELEMENTS, USING BUILT-IN DIAGNOSTIC TOOLS." Radio Electronics, Computer Science, Control 1, no. 1 (March 30, 2021): 158–71. http://dx.doi.org/10.15588/1607-3274-2021-1-16.
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Context. In the modern world, information management systems have become widespread. This make it possible to automate the technological processes of enterprises of various sizes. Many information management systems include wireless and autonomous elements. Autonomy, in this case, means the ability of the system elements to function for a certain time without additional energy supply. In this regard, such a parameter of operational reliability as the battery life of a system element becomes one of the most important. One of the main tools for improving the reliability and fault tolerance of information management system elements – is the use of a modern diagnostic system.
Objective. The aim of the work is to develop a method for increasing the reliability of the functioning of autonomous elements of information management systems. It includes the creation of a model of an information management system and an algorithm for reasonable redistribution of diagnostic functions, as well as a software implementation of the developed algorithm, which confirms its higher reliability indicators in comparison with other algorithms.
Methods. The basic model was the Preparata-Metz-Chen model. On its basis, a new model of the system was built, including the structural and logical description of the elements and the determination of the way of their interaction. The elements were classified by the degree of criticality of the functions performed in the system. On the basis of the developed model and description of the elements, an algorithm was developed for the reasonable redistribution of the diagnostic load, which made it possible to reduce the average energy consumption of the elements and thereby improve the reliability indicators. A software implementation of the developed algorithm was created, which allows to numerically evaluate its advantages. The developed and existing algorithms were compared.
Results. A model of information management system has been developed. In such a system, it is proposed to use an integrated test diagnostics system. This diagnostic system implements algorithms for redistributing the diagnostic load. To determine the importance of the characteristics taken into account, a linear criterion was chosen, as the most studied and fastest in application. A software model, that implements the developed algorithm and makes it possible to compare it with existing algorithms, has been developed. A study of the software model with various parameters was carried out and, based on the results of the software simulation, conclusions were drawn about the possibilities of improving the algorithm and directions for further scientific research were formulated.
Conclusions. The usage of the developed algorithm makes it possible to increase such a characteristic of the reliability of the elements of the information and control system as the mean time of failure-free operation (mean time between failures) by increasing the operating time of autonomous elements without recharging. When carrying out software modeling of the developed and existing algorithms, the advantages of the first were confirmed, and theoretical possibilities for its improvement were formulated.
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Yesaulov, S., О. Babicheva, and M. Kovalik. "INCREASING THE EFFICIENCY OF THERMAL DIAGNOSTIC CONTROL OF ELECTRIC MOTORS." Municipal economy of cities 4, no. 157 (September 25, 2020): 163–71. http://dx.doi.org/10.33042/2522-1809-2020-4-157-163-171.
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The article considers the cause of electromechanical equipment heating (EMЕ) during its operation. It has been reflected the well-known malfunctions of electric motors, that lead to overheating and failure of their individual components. Based on the analysis of existing methods of thermal diagnostics, It has been considered the trends in the creation of devices for monitoring thermal processes and it has been noted the reasons that restrain the use of technical diagnostics tools for thermal faults during the operation of EME. The purpose of this work was to increase the efficiency of the formation of initial information messages. Using the experimental data in the implementation of the EME working cycles, value of the thermal process velocity accompanying the variable technological modes with the bipolar behavior of the output ordinate were determined. Compared to the heating temperature, the rate of value change with a more noticeable contrast reflected the thermal events in the EME, thus determining the priority of this parameter to increase the efficiency of the measuring device. It has been considered methods of forming an array of initial data using a remote transducer sensor to control the heating temperature of equipment with a modulator. It has been proposed algorithms for the electronic formation of an array of initial values and their sorting according to the “principle of flotation”, when a select variables, belonging to the heating processes or cooling of equipment, is provided. A way and an algorithm for determining the rate of temperature change based on current data using a D-shaper are considered. Experimental studies of the electronic components of the diagnostic device with the D-shaper of the initial data array elements confirmed their physical implementation possibility by hardware and software. The results of data arrays formation, taking into account digital sequences in int format with an error of ± 1 Hz, in contrast to the most controlled parameter – float with an error of ± 0.08 ° C, did not change the properties of information messages, but made it possible to reduce the requirements for a microcalculator or a computing device. The results, obtained using the proposed technical solution, confirmed the possibility of increasing the efficiency of thermal and diagnostic control, contributing to a more accurate identification of possible electric motor malfunctions in the EME. The work presents illustrations confirming the suitability of mathematical descriptions and algorithms for processing the initial data for their practical application in electronic measuring instruments for monitoring and diagnosing malfunctions based on thermal events. Keywords: artificial neural network, remote control, modeling, parameter converter, modulator, transport, traction motor, identification, programming.
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Slagstad, Ketil. "Society as Cause and Cure: The Norms of Transgender Social Medicine." Culture, Medicine, and Psychiatry 45, no. 3 (June 22, 2021): 456–78. http://dx.doi.org/10.1007/s11013-021-09727-4.
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AbstractThis article analyzes how trans health was negotiated on the margins of psychiatry from the late 1970s and early 1980s. In this period, a new model of medical transition was established for trans people in Norway. Psychiatrists and other medical doctors as well as psychologists and social workers with a special interest and training in social medicine created a new diagnostic and therapeutic regime in which the social aspects of transitioning took center stage. The article situates this regime in a long Norwegian tradition of social medicine, including the important political role of social medicine in the creation of the postwar welfare state and its scope of addressing and changing the societal structures involved in disease. By using archival material, medical records and oral history interviews with former patients and health professionals, I demonstrate how social aspects not only underpinned diagnostic evaluations but were an integral component of the entire therapeutic regime. Sex reassignment became an integrative way of imagining and practicing psychiatry as social medicine. The article specifically unpacks the social element of these diagnostic and therapeutic approaches in trans medicine. Because the locus of intervention and treatment remained the individual, an approach with subversive potential ended up reproducing the norms that caused illness in the first place: “the social” became a conformist tool to help the patient integrate, adjust to and transform the pathology-producing forces of society.
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Shakurova, R. Z., S. O. Gaponenko, and A. E. Kondratiev. "Technique for operational diagnosis of pipelines of energy systems and complexes." Power engineering: research, equipment, technology 22, no. 6 (March 26, 2021): 188–201. http://dx.doi.org/10.30724/1998-9903-2020-22-6-188-201.
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THE PURPOSE. To consider the problems of reliability of pipeline systems of housing and communal services. To analyze existing methods for assessing the technical condition of pipelines. To develop an improved technique that allows you to search for various types of defects in pipelines. To develop a device for inertial excitation of low-frequency diagnostic vibration vibrations. To develop software in the LabVIEW environment for collecting, storing and processing signals from a sensitive sensor (piezoelectric sensor) installed on a pipeline. To conduct a series of experimental studies to te st the proposed methodology. METHODS. The method of inertial excitation of vibrations was used to excite vibrations in the wall of the investigated pipeline. To search for the natural frequencies of vibrations of the pipeline under study, mathematical mode ling methods were used, implemented in the ANSYS software package. During the experiments, the fast Fourier transform method was used to process the signals coming from the piezoelectric sensor. RESULTS. The article presents a technique for assessing the t echnical condition of pipelines, as well as a device for inertial excitation of vibrations. The article presents the results of experimental studies on a fiberglass pipeline, the results showed that when an oscillatory wave passes through the wall of a defect-free pipeline, its amplitude changes insignificantly. If there is a defect in the wall of the investigated pipeline, the vibration amplitude will be much weaker due to the dissipation of vibrational energy in the place of the defect. Thereby, it is pos sible to determine not only the presence of a defect, but also its size by the degree of attenuation of the signal amplitude CONCLUSION. The proposed technique is the basis for the creation of a new measuring and diagnostic complex for vibration control of pipelines.