32 results on '"Pavel Vazan"'
Search Results
2. Comparison of the Scalarization Approaches in Many-Objective Simulation-Based Optimization in Production System Control.
- Author
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Pavel Vazan and Zuzana Cervenanska
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- 2018
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3. Proactive Simulation in Production Line Control.
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Pavel Vazan, Jaroslav Znamenak, and Martin Juhás
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- 2018
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4. Pattern Recognition for Predictive Analysis in Automotive Industry.
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Veronika Simoncicova, Lukas Hrcka, Lukás Spendla, Pavol Tanuska, and Pavel Vazan
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- 2017
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- View/download PDF
5. Using Text Mining Methods for Analysis of Production Data in Automotive Industry.
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Lukas Hrcka, Veronika Simoncicova, Ondrej Tadanai, Pavol Tanuska, and Pavel Vazan
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- 2017
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6. The Simulation of the Assembling Production Process.
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Róbert Paulicek, Tomás Haluska, and Pavel Vazan
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- 2012
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7. Implementation of Heterogeneous Multirobotic Cell Control Using Visualization Techniques
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Martin Juhas, Bohuslava Juhasova, and Pavel Vazan
- Published
- 2022
8. The vulnerability of securing IoT production lines and their network components in the Industry 4.0 concept
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Pavol Tanuska, Zuzana Cervenanska, Jan Janosik, Pavel Vazan, Ladislav Huraj, and Tibor Horak
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0209 industrial biotechnology ,Industry 4.0 ,Computer science ,Wireless network ,business.industry ,Network packet ,020208 electrical & electronic engineering ,Denial-of-service attack ,02 engineering and technology ,Computer security ,computer.software_genre ,Networking hardware ,020901 industrial engineering & automation ,Control and Systems Engineering ,0202 electrical engineering, electronic engineering, information engineering ,The Internet ,business ,computer ,Vulnerability (computing) ,Anonymity - Abstract
IoT systems are an integral part of every modern industrial enterprise Industry 4.0. IoT is the term for modern remote devices controlled via the Internet. Internet of Things is the name of technologies that allow cheap wireless connection and communication of various sensors and devices to automate, accelerate and streamline processes. In the interconnected world of Industry 4.0, there are many potential resources existing for infiltration. Cybercriminals could take control of manufacturing industries, manipulate machines, or could do an industrial espionage. This type of attack is called Denial of Service. In the second case, the attack preserves the attacker’s anonymity through an IP address by using a potentially innocent third party (a reflector) that is indirectly involved in the attack. Through this attack, the attacker forwards the flow of attacking data to the target victim. The attacker sends the packets with a fake spoof source IP address set to the victim’s IP address to the reflector, thus indirectly overloading the target with the packets, or it will intrude into a network device through a faulty WPS implementation. The simulation model of the production line and the IoT security system Fibaro were used to investigate these attacks. The article demonstrates the possibility of attacks on network devices and the misuse of IoT devices in order to compromise production machines which use DRDoS and Brute-force attacks.
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- 2020
9. Using data mining methods for manufacturing process control
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Pavol Tanuska, Pavel Vazan, Michal Kebisek, Zuzana Cervenanska, and D. Janikova
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0209 industrial biotechnology ,Computer science ,Manufacturing process ,Process (engineering) ,Control (management) ,02 engineering and technology ,Manufacturing systems ,computer.software_genre ,020901 industrial engineering & automation ,Control and Systems Engineering ,0202 electrical engineering, electronic engineering, information engineering ,Predictive Model Markup Language ,Production (economics) ,020201 artificial intelligence & image processing ,Data mining ,computer - Abstract
The Industry 4.0 concept assumes that modern manufacturing systems generate huge amounts of data that must be collected, stored, managed and analysed. The case study is focused on predicting the manufacturing process behaviour according to production data. The paper presents the way of gaining knowledge about the future behaviour of manufacturing system by data mining predictive tasks. The proposed simulation model of the real manufacturing process was designed to obtain the data necessary for the control process. The predictions of the manufacturing process behaviour were implemented varying the input parameters using selected methods and techniques of data mining. The predicted process behaviour was verified using the simulation model. The authors analysed different methods. The neural network method was selected for deploying new data by PMML files in the final phases. The objectives of the research are to design and verify the data mining tools in order to support the manufacturing system control by aiming at improving the decisionmaking process. Based on the prediction of the goal production outcomes, the actual control strategies can be precisely modified. Then they can be used in real manufacturing system without risks.
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- 2017
10. The impact of selected priority rules on production goals
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Pavel Vazan, Gabriela Krizanova, Janette Kotianová, and Zuzana Cervenanska
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0209 industrial biotechnology ,Job shop scheduling ,Operations research ,Least slack time scheduling ,Computer science ,05 social sciences ,Scheduling (production processes) ,Flexible manufacturing system ,02 engineering and technology ,020901 industrial engineering & automation ,FIFO and LIFO accounting ,Due date ,0502 economics and business ,Discrete event simulation ,Queue ,050203 business & management - Abstract
The paper presents the outcome of a study that dealt with scheduling of operations and in particular with the impact of selected priority rules on production goals. The impact of the priority rules was examined on a simulation model of the smart flexible manufacturing system with interchangeable workplaces. These problems are characterized as job shop scheduling problems. The study documents the influence of the five selected priority rules FIFO (First in First out), EDD (Earliest Due Date), STR (Slack Time Remaining), STR/OP (Slack Time Remaining per Operation) and SQNO (Shortest Queue at the Next Operation) on chosen production objectives. The effect of applied priority rule has been studied at a different production system loading. The evaluation of experimental results and their synthesis conduce to the formulation of knowledge for the real use of these priority rules in the scheduling of operations.
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- 2019
11. Proactive Simulation in Production Line Control
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Jaroslav Znamenak, Pavel Vazan, and Martin Juhas
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Production line ,Service (systems architecture) ,Computer science ,Process (engineering) ,Production control ,Control (management) ,Production (economics) ,Plan (drawing) ,Line (text file) ,Reliability engineering - Abstract
This paper deals with proposal of a proactive simulation model for a hybrid production system with an integrated MES used for safety, security, control, maintenance and service training with equipment similar to one utilized in a real industrial process. A proactive planning methodology can use information about real time changes in input data used for planning and determine a revised plan and line control. The proposed proactive procedure in this paper demonstrates a way to acquire data from an existing manufacturing process, which will be used to reach a production plan based on a combination of a simulation model and data acquired from MES. The revised control procedure will be send back to the MES to update the manufacturing process.
- Published
- 2018
12. Comparison of the Scalarization Approaches in Many-Objective Simulation-Based Optimization in Production System Control
- Author
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Zuzana Cervenanska and Pavel Vazan
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Mathematical optimization ,Simulation-based optimization ,Computer science ,Simulated annealing ,Brute-force search ,Production (economics) ,A priori and a posteriori ,Performance indicator ,Metaheuristic ,Multi-objective optimization - Abstract
Complex manufacturing systems control, involving contradictory production goals, is a challenge in spite of many multi-objective optimization decision-making strategies. In this article we demonstrate an application of the scalarization approach with a priori articulated preferences in the multiobjective optimization via discrete-event simulation in the field of the manufacturing product control. Especially, we focus on the effect of the used scalarizing multi-criteria function form combining all considering production goals using user-supplied weights. Four key performance indicators: costs per part unit, an average flow time, machines utilization and an amount of production for studied production system were finding by simulation in simulator Witness and optimized simultaneously under specific constraints. Metaheuristics like Thermoadaptive Simulated Annealing and Random Solutions and at last a brute force algorithm were used as optimization methods for finding global minimum of scalar functions generated by different methods of scalarization.
- Published
- 2018
13. Mathematical Approach to Security Risk Assessment
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Marcel Abas, Michal Elias, Pavel Vazan, Michal Kebisek, Pavol Tanuska, Zuzana Sutova, Robert Vrabel, and Dusan Pavliak
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Flammable liquid ,Engineering ,Article Subject ,business.industry ,lcsh:Mathematics ,General Mathematics ,General Engineering ,Risk management tools ,Nuclear power ,lcsh:QA1-939 ,Computer security ,computer.software_genre ,chemistry.chemical_compound ,Risk analysis (engineering) ,chemistry ,lcsh:TA1-2040 ,Hazardous waste ,Threat model ,lcsh:Engineering (General). Civil engineering (General) ,business ,Risk assessment ,computer ,Countermeasure (computer) ,Risk management - Abstract
The goal of this paper is to provide a mathematical threat modeling methodology and a threat risk assessment tool that may assist security consultants at assessing the security risks in their protected systems/plants, nuclear power plants and stores of hazardous substances: explosive atmospheres and flammable and combustible gases and liquids, and so forth, and at building an appropriate risk mitigation policy. The probability of a penetration into the protected objects is estimated by combining the probability of the penetration by overcoming the security barriers with a vulnerability model. On the basis of the topographical placement of the protected objects, their security features, and the probability of the penetration, we propose a model of risk mitigation and effective decision making.
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- 2015
14. Design of Portal for Improvement Controlling Sales Channel
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Pavel Vazan, Matus Peci, and Vladimir Surka
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Engineering ,Process management ,business.industry ,Business process ,General Medicine ,Customer relationship management ,Appropriate technology ,computer.software_genre ,Software deployment ,Operating system ,Process control ,Web application ,Performance indicator ,business ,computer ,Communication channel - Abstract
This paper presents design of portal that improves controlling of sales channel at initial conditions. The customer needed to display key performance indicators on the portal and thus significantly improve the efficiency of business processes after the deployment of Microsoft Dynamics CRM 2011. The aim of this paper is to choose appropriate technology to create a portal and design possible architecture of solution. Microsoft Dynamics CRM 2011 with Web Application Microsoft SharePoint platform provide a solution for process control of business processes in company that is primarily offered like as the best solution. On the other hand, we found the possibility of open source content management system DotNetNuke, which meets customer's requirements and therefore, there is a possibility to reduce financial costs when selecting this system. Finally, we evaluated considered technologies, prepared more price variations of architecture and compared advantages and disadvantages of these variations.
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- 2014
15. Input Control in Production System by Simulation Optimization
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Lukas Hrcka, Pavel Vazan, Julia Kurnatova, and Dominika Jurovatá
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Simulation optimization ,Mathematical optimization ,Control theory ,Computer science ,Simulated annealing ,Production (economics) ,General Medicine ,Interval (mathematics) ,Input control ,Realization (systems) ,Production system - Abstract
The paper deals with the problem of simulation optimization and presents its usage for input control in a production system. The paper gives an overview of typical concepts of input control. Authors propose different approaches. The basic principles of simulation optimization are explained. A general procedure with each step is defined and this procedure is explained by an example. The solution is focused on the minimization of the production costs, which is included in the objective function. Realization of the simulation optimization is based on the combination of three different algorithms: Adaptive Thermostatistical Simulated Annealing, Random Solution and All Combination algorithm. The proposed procedure definitely leads to exact determination of input interval for given production system and short time period.
- Published
- 2014
16. Data integration and transformation proposal for big data analyses in automotive industry
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Lukas Spendla, Lukas Hrcka, Pavel Vazan, Pavol Tanuska, and Michal Kebisek
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business.industry ,Process (engineering) ,Computer science ,Big data ,Automotive industry ,computer.software_genre ,Data structure ,Manufacturing engineering ,Data set ,Transformation (function) ,Computer data storage ,business ,computer ,Data integration - Abstract
In our paper, we have focused on data integration and transformation process in the automotive industry, with emphasis on production data collected from the shop floor. One of the main issues addressed, is that the data are not stored in a central data storage, but in individual devices and systems, utilising different data formats. Our paper briefly describes the main tasks, required to collect production data into the big data storage and transform them into a unified data structure. We have also provided results of the initial analyses that were performed on the integrated and transformed data set.
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- 2017
17. Using Text Mining Methods for Analysis of Production Data in Automotive Industry
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Veronika Simoncicova, Pavel Vazan, Lukas Hrcka, Ondrej Tadanai, and Pavol Tanuska
- Subjects
0209 industrial biotechnology ,business.industry ,Process (engineering) ,Computer science ,05 social sciences ,Automotive industry ,02 engineering and technology ,Data science ,Field (computer science) ,Identification (information) ,020901 industrial engineering & automation ,Text mining ,Analytics ,Production (economics) ,0509 other social sciences ,050904 information & library sciences ,business - Abstract
Text mining is the process of extracting useful and high-quality information from unstructured textual data through the identification and exploration of interesting patterns. Text mining also referred to as text data mining, roughly equivalent to text analytics. RapidMiner is unquestionably the world-leading open-source system for this analytics, it is the most powerful and easy to use. Acquiring information from text is a requested area of research in automotive industry. This paper aims at presenting the use of text mining in this industry field. The article is focused on working with text attributes “ResponsibleEmp”, which is crucial for text mining analysis. The outcome of this article is the number of breakdowns and name of a specific employee responsible for breakdowns. The presented analysis is provided as a partial result of the research and will serve to further investigation in the problem area.
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- 2017
18. A Heat Transfer Approach to the Calculation of Residual Power of Used Nuclear Fuel
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Pavel Vazan, Pavol Tanuska, Peter Schreiber, and Robert Vrabel
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Nuclear and High Energy Physics ,Scale (ratio) ,business.industry ,020209 energy ,Nuclear engineering ,02 engineering and technology ,Condensed Matter Physics ,Residual ,Spent nuclear fuel ,Power (physics) ,020303 mechanical engineering & transports ,Software ,0203 mechanical engineering ,Nuclear Energy and Engineering ,Container (abstract data type) ,Heat transfer ,0202 electrical engineering, electronic engineering, information engineering ,Environmental science ,business - Abstract
In this paper, we develop a new method for determining the residual power of used nuclear fuel (UNF). The method is based on the heat transfer analysis of UNF in a C-30 transport container with a KZ-48 compact storage cask. We compare the results achieved by the currently used SCALE 6 software packages based on nuclear physics calculations and the results from our method.
- Published
- 2014
19. Implementation of manufacturing resource planning issues in practice
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Pavel Vazan, Jaroslav Znamenak, Miriam Iringová, Vladimir Surka, and Gabriela Krizanova
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Material requirements planning ,Risk analysis (engineering) ,Computer-integrated manufacturing ,Point (typography) ,Computer science ,0502 economics and business ,05 social sciences ,Factory (object-oriented programming) ,Production (economics) ,050211 marketing ,Manufacturing resource planning ,050203 business & management ,Manufacturing engineering - Abstract
The paper provides a view of Material Resource Planning implementation. The authors describe the MRP II implementation techniques and define the necessary requirements for its successful implementation. Possible practical implementation doubts are being pointed out on an actual real-world example. Issues can appear especially in the warm-up period of implementation. The rapid grow of inventory levels issue is particularly analyzed by the authors, who point out the inaccuracy in data in the given bills of materials and in particular the production output data provided by the shop floor. The newly implemented MRP II system reacts to these inaccurate data by acquiring more manufacturing material for production, which leads to the grow of inventory levels in a factory.
- Published
- 2016
20. The impact of reducing setup costs on the lot size and objectives of manufacturing
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Jaroslav Znamenak, Dominika Jurovatá, and Pavel Vazan
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050210 logistics & transportation ,Engineering ,Mathematical optimization ,021103 operations research ,business.industry ,05 social sciences ,0211 other engineering and technologies ,Flexible manufacturing system ,02 engineering and technology ,Maximization ,Work in process ,Manufacturing systems ,Industrial engineering ,Reduction (complexity) ,Machine utilization ,0502 economics and business ,Minification ,business ,Throughput (business) - Abstract
This paper points out the significance of setup costs reduction on the decrease of lot size. The authors demonstrate this phenomenon on a flexible manufacturing system simulation model. The research focus was to fully understand the relationships between the lot size and setup costs. The aim of research was to show an impact of lot size on the selected manufacturing objectives. For each series of experiments, the setup costs were continuously reduced, and then the optimal lot size was determined by simulation optimization. The procedure for lot size determination was proposed by the authors and is based on a simulation optimization method. The authors have expressed their hypothesis of the positive impact of the optimal lot size on the objective parameters fulfilment of a manufacturing system, especially the minimization of costs per unit, throughput time and work in progress and the maximization of number of finished products and machine utilization. The hypothesis was confirmed by the gained simulation experiment results.
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- 2016
21. Retracted: Matlab Simulation of Photon Propagation in Three-Layer Tissue
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Dominika Jurovatá, Julia Kurnatova, Pavel Vazan, and Peter Husar
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Photon ,business.industry ,Computer science ,Near-infrared spectroscopy ,Radiation ,Optics ,Transmittance ,Diffuse reflection ,Specular reflection ,business ,MATLAB ,Penetration depth ,computer ,Simulation ,computer.programming_language - Abstract
This paper deals with the simulation of photon propagation in the maternal abdomen. Authors focused on the light transport, photon trajectory and their radiation in three-layer tissue. The main aim of this study is to observe the behaviour of photon in three-layer tissue. A simulation model has been implemented in Matlab. The photon interaction with tissue was observed. This model was realized for the project aimed to non-invasive pulse oximetry measurement of fetal oxygen saturation in the maternal abdomen. One of the fundamental challenges is to ensure a sufficient penetration depth which covers maternal and fetal tissue. This contribution investigates the photon trajectories and compares the results of specular reflectance, diffuse reflectance, absorbed fraction and transmittance in three-layer tissue with regard to the thickness of the third layer. Simulations have been performed at three depths fetal (2.5, 3.7, 4.9 cm).
- Published
- 2014
22. Knowledge Discovery From Production Databases For Hierarchical Process Control
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Pavol Tanuska, Pavel Vazan, Michal Kebisek, and Dominika Jurovata
- Subjects
Hierarchical process control ,neural network ,knowledge discovery from databases - Abstract
The paper gives the results of the project that was oriented on the usage of knowledge discoveries from production systems for needs of the hierarchical process control. One of the main project goals was the proposal of knowledge discovery model for process control. Specifics data mining methods and techniques was used for defined problems of the process control. The gained knowledge was used on the real production system thus the proposed solution has been verified. The paper documents how is possible to apply the new discovery knowledge to use in the real hierarchical process control. There are specified the opportunities for application of the proposed knowledge discovery model for hierarchical process control., {"references":["","U. M. Fayyad, \"Data Mining and Knowledge Discovery: Making Sense Out of Data\". IEEE Expert/Intelligent Systems & Their Applications, \npp. 20–26, 1996.","U. M. Fayyad, G. Piatetski–Shapiro, G. P. Smyth, \"From Data Mining to Knowledge Discovery: An Overview\". Advances in Knowledge Discovery and Data Mining, MIT Press, pp. 1–37, 1996.","R. Halenar, \"Matlab Routines Used for Real Time ETL Method\". Applied Mechanics and Materials, pp. 2125-2129, 2012.","R. Halenar, \"Real Time ETL Improvement\". International Journal of Computer Theory and Engineering. vol. 4, no. 3, pp. 405-409, 2012.","J. Jadlovsky, \"Proposal of distribution control system of FMS\" \nin International Conference Cybernetics and Informatics, Vysna Boca 2010.","P. Mydlo, T. Skulavik, P. Schreiber, \"The fuzzy PI controller`s chosen parametres influence on the regulation process\" in Process Control 2010, University of Pardubice, pp. C055a1-8, 2010.","M. A. Schwarz, Introduction to software engineering for secure and reliable software – Einführung in die Softwaretechnik für sichere und verlässliche Software. Institut für Informatik im Paderbom, 2004.","A. Trnka, \"Classification and Regression Trees as a Part of Data Mining in Six Sigma Methodology\" in World Congress on Engineering and Computer Science, Hong Kong: International Association of Engineers, \npp. 449-453, 2010.","A.-W. Sheer, CIM Computer Integrated Manufacturing. Berlin: Springer-Verlag, 2011.\n\n "]}
- Published
- 2013
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23. Data Mining Model Building as a Support for Decision Making in Production Management
- Author
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Oliver Moravcik, Peter Schreiber, Pavol Tanuska, Pavel Vazan, and Michal Kebisek
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Decision support system ,Decision engineering ,Computer science ,Production manager ,Intelligent decision support system ,Production (economics) ,Data mining ,computer.software_genre ,Model building ,computer ,Data warehouse ,R-CAST - Abstract
The paper gives the next stages of the project that is oriented on the use of data mining techniques and knowledge discoveries from production systems through them. They have been used in the management of these systems. Production data was obtained in previous stages of project. This production data are stored in data warehouse that was proposed and developed by authors. Data mining model has been created by using specific methods and selected techniques for defined problems of production system management. The main focus of our article is the proposal of data mining model.
- Published
- 2012
24. The Data Mining Usage In Production System Management
- Author
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Pavel Vazan, Pavol Tanuska, and Michal Kebisek
- Abstract
The paper gives the pilot results of the project that is oriented on the use of data mining techniques and knowledge discoveries from production systems through them. They have been used in the management of these systems. The simulation models of manufacturing systems have been developed to obtain the necessary data about production. The authors have developed the way of storing data obtained from the simulation models in the data warehouse. Data mining model has been created by using specific methods and selected techniques for defined problems of production system management. The new knowledge has been applied to production management system. Gained knowledge has been tested on simulation models of the production system. An important benefit of the project has been proposal of the new methodology. This methodology is focused on data mining from the databases that store operational data about the production process.
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- 2011
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25. The Data Warehouse Suggestion for Production System
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Pavel Vazan, Michal Kebisek, Pavol Tanuska, and Dominika Jurovata
- Published
- 2011
26. The integration of processes within IT resources control
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Pavel Vazan, Pavol Tanuska, and Maros Zobok
- Subjects
SQL ,Database ,business.industry ,Computer science ,Business data processing ,Control (management) ,Information technology ,computer.software_genre ,Interim ,business ,computer ,Electronic data interchange ,Data transmission ,computer.programming_language - Abstract
The article provides the general overview and base proposal of solution in the area of controlling the IT resources within the company. It points out some common deficits of integrating systems and running data transfers. Lack of functionality in some large systems is supplemented by using interim database and proposed SQL processing prior to data loads. Interim database is also used for storing the import result status and log functionality.
- Published
- 2010
27. Determination of the Residual Power of the Fissionable Fuel by Modeling
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Stanislav Barton, Pavol Tanuska, Pavel Vazan, and Peter Schreiber
- Subjects
Modeling and simulation ,Nuclear fuel ,Nuclear engineering ,Container (abstract data type) ,Environmental science ,Nuclide ,Electric power ,Residual ,Temperature measurement ,Spent nuclear fuel - Abstract
The today's determination of residual power of nuclear fuel in containers bases on differential equations, which describe the creation and the destruction of nuclides in the fuel. The Nuclear Regulatory of Slovak Republic requires the verification of present methodology alternatively. The new methodology and achieved results in determination of residual power of spent nuclear fuel by temperature measuring of the container are described in this article. The solution bases on modeling and simulation: The container without fuel was heated by electrical resistant spirals with known electrical power, which simulates the residual power of the transported nuclear fuel. The temperature of defined points of the container’s surface and in environment was measured. The measured data were used for the design of the thermic mathematical model of the container. This model can be backwards used for the determination of the power of transported fuel in real container's operation.
- Published
- 2010
28. Simulation of Photon Propagation in Tissue Using Matlab
- Author
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Peter Husar, Sebastian Ley, Pavel Vazan, Julia Kurnatova, Dominika Jurovatá, and Daniel Laqua
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Physics ,Photon ,business.industry ,Quantitative Biology::Tissues and Organs ,Physics::Medical Physics ,Monte Carlo method ,Fetal tissue ,Radiation ,Photon propagation ,Optics ,Trajectory ,MATLAB ,Penetration depth ,business ,computer ,computer.programming_language - Abstract
This paper deals with the light transport, photon trajectory and its radiation in tissue. A model based on Monte Carlo simulation has been implemented in Matlab to get inside into photon interaction with tissue. The project is aimed to non-invasive pulse oximetry measurement of fetal oxygen saturation in the maternal abdomen. One of the fundamental challenges is to ensure a sufficient penetration depth which covers maternal and fetal tissue. This contribution investigates the photon trajectories and analyse the number of photons which stayed in tissue and their radiation distribution. The principle and photon propagation rules, needed for simulation, are presented in this article. Finally the results are compared with literature.
- Published
- 2013
29. Multi-Criteria Optimization in Operations Scheduling Applying Selected Priority Rules
- Author
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Zuzana Červeňanská, Pavel Važan, Martin Juhás, and Bohuslava Juhásová
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multi-criteria optimization ,simulation optimization ,production control ,multiple flexible job shop scheduling ,priority rules ,Technology ,Engineering (General). Civil engineering (General) ,TA1-2040 ,Biology (General) ,QH301-705.5 ,Physics ,QC1-999 ,Chemistry ,QD1-999 - Abstract
The utilization of a specific priority rule in scheduling operations in flexible job shop systems strongly influences production goals. In a context of production control in real practice, production performance indicators are evaluated always en bloc. This paper addresses the multi-criteria evaluating five selected conflicting production objectives via scalar simulation-based optimization related to applied priority rule. It is connected to the discrete-event simulation model of a flexible job shop system with partially interchangeable workplaces, and it investigates the impact of three selected priority rules—FIFO (First In First Out), EDD (Earliest Due Date), and STR (Slack Time Remaining). In the definition of the multi-criteria objective function, two scalarization methods—Weighted Sum Method and Weighted Product Method—are employed in the optimization model. According to the observations, EDD and STR priority rules outperformed the FIFO rule regardless of the type of applied multi-criteria method for the investigated flexible job shop system. The results of the optimization experiments also indicate that the evaluation via applying multi-criteria optimization is relevant for identifying effective solutions in the design space when the specific priority rule is applied in the scheduling operations.
- Published
- 2021
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30. Comparison of Heat Demand Prediction Using Wavelet Analysis and Neural Network for a District Heating Network
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Szabolcs Kováč, German Micha’čonok, Igor Halenár, and Pavel Važan
- Subjects
artificial neural networks ,data analysis ,signal decomposition ,district heating ,forecasting ,Technology - Abstract
Short-Term Load Prediction (STLP) is an important part of energy planning. STLP is based on the analysis of historical data such as outdoor temperature, heat load, heat consumer configuration, and the seasons. This research aims to forecast heat consumption during the winter heating season. By preprocessing and analyzing the data, we can determine the patterns in the data. The results of the data analysis make it possible to form learning algorithms for an artificial neural network (ANN). The biggest disadvantage of an ANN is the lack of precise guidelines for architectural design. Another disadvantage is the presence of false information in the analyzed training data. False information is the result of errors in measuring, collecting, and transferring data. Usually, trial error techniques are used to determine the number of hidden nodes. To compare prediction accuracy, several models have been proposed, including a conventional ANN and a wavelet ANN. In this research, the influence of different learning algorithms was also examined. The main differences were the training time and number of epochs. To improve the quality of the raw data and remove false information, the research uses the technology of normalizing raw data. The basis of normalization was the technology of the Z-score of the data and determination of the energy‒entropy ratio. The purpose of this research was to compare the accuracy of various data processing and neural network training algorithms suitable for use in data-driven (black box) modeling. For this research, we used a software application created in the MATLAB environment. The app uses wavelet transforms to compare different heat demand prediction methods. The use of several wavelet transforms for various wavelet functions in the research allowed us to determine the best algorithm and method for predicting heat production. The results of the research show the need to normalize the raw data using wavelet transforms. The sequence of steps involves following milestones: normalization of initial data, wavelet analysis employing quantitative criteria (energy, entropy, and energy‒entropy ratio), optimization of ANN training with information energy–entropy ratio, ANN training with different training algorithms, and evaluation of obtained outputs using statistical methods. The developed application can serve as a control tool for dispatchers during planning.
- Published
- 2021
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31. Multi-Objective Optimization of Production Objectives Based on Surrogate Model
- Author
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Zuzana Červeňanská, Janette Kotianová, Pavel Važan, Bohuslava Juhásová, and Martin Juhás
- Subjects
multi-objective optimization ,metamodel ,surrogate model ,manufacturing system ,simulation-based optimization ,Technology ,Engineering (General). Civil engineering (General) ,TA1-2040 ,Biology (General) ,QH301-705.5 ,Physics ,QC1-999 ,Chemistry ,QD1-999 - Abstract
The article addresses an approximate solution to the multi-objective optimization problem for a black-box function of a manufacturing system. We employ the surrogate of the discrete-event simulation model of a batch production system in an analytical form. Integration of simulation, Design of Experiments methods, and Weighted Sum and Weighted Product multi-objective methods are used in an arrangement of a priori defined preferences to find a solution near the Pareto optimal solution in a criterion space. We compare the results obtained through the analytical approach to the outcomes of simulation-based optimization. The observed results indicate a possibility to apply the suitable analytical model for quickly finding the acceptable approximate solution close to the Pareto optimal front.
- Published
- 2020
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32. Právní úprava věci hromadné, souboru věcí a dopad jejich právní úpravy do praxe
- Author
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Pavel Vážan
- Subjects
Hromadná věc ,soubor věcí ,občanský zákoník. ,Law - Abstract
Příspěvek reaguje na pojem věci hromadné a souboru věcí, vymezení jejich vztahu s ohledem na současné pojetí těchto dvou pojmů a zejména pak na jejich praktické dopady ve světle zákona č. 89/2012 Sb., občanský zákoník. Cílem příspěvku není podat jednoznačnou a vyčerpávající odpověď na sporné otázky s těmito pojmy související, ale zhodnotit právní úpravu de lege lata, její dopad do právní praxe a případně vyvolat možné úvahy de lege ferenda.
- Published
- 2017
- Full Text
- View/download PDF
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