Gotowe bibliografie tematyczne / Evolutionary programming (computer science)

Gotowa bibliografia na temat „Evolutionary programming (computer science)”

Autor: Grafiati

Data publikacji: 4 czerwca 2021

Data aktualizacji: 30 lipca 2024

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Artykuły w czasopismach na temat "Evolutionary programming (computer science)"

Vitányi, Paul. "A discipline of evolutionary programming". Theoretical Computer Science 241, nr 1-2 (czerwiec 2000): 3–23. http://dx.doi.org/10.1016/s0304-3975(99)00263-7.

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Doerr, Benjamin, Anton Eremeev, Frank Neumann, Madeleine Theile i Christian Thyssen. "Evolutionary algorithms and dynamic programming". Theoretical Computer Science 412, nr 43 (październik 2011): 6020–35. http://dx.doi.org/10.1016/j.tcs.2011.07.024.

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DU, Haifeng. "Adaptive chaos clonal evolutionary programming algorithm". Science in China Series F 48, nr 5 (2005): 579. http://dx.doi.org/10.1360/04yf0458.

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Ji, Mingjun, Huanwen Tang i Juan Guo. "A single-point mutation evolutionary programming". Information Processing Letters 90, nr 6 (czerwiec 2004): 293–99. http://dx.doi.org/10.1016/j.ipl.2004.03.002.

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English, T. M. "Evolutionary Programming VI[Book Reviews]". IEEE Transactions on Evolutionary Computation 1, nr 3 (wrzesień 1997): 218–19. http://dx.doi.org/10.1109/tevc.1997.661555.

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Kushchu, I. "Genetic programming and evolutionary generalization". IEEE Transactions on Evolutionary Computation 6, nr 5 (październik 2002): 431–42. http://dx.doi.org/10.1109/tevc.2002.805038.

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Nölting, Bengt, Dennis Jülich, Winfried Vonau i Karl Andert. "Evolutionary Computer Programming of Protein Folding and Structure Predictions". Journal of Theoretical Biology 229, nr 1 (lipiec 2004): 13–18. http://dx.doi.org/10.1016/j.jtbi.2004.02.016.

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Jong-Hwan Kim i Kwang-Choon Kim. "Multicriteria fuzzy control using evolutionary programming". Information Sciences 103, nr 1-4 (grudzień 1997): 71–86. http://dx.doi.org/10.1016/s0020-0255(97)00050-9.

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Mallipeddi, R., S. Mallipeddi i P. N. Suganthan. "Ensemble strategies with adaptive evolutionary programming". Information Sciences 180, nr 9 (maj 2010): 1571–81. http://dx.doi.org/10.1016/j.ins.2010.01.007.

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Farach, Martin, i Mikkel Thorup. "Sparse Dynamic Programming for Evolutionary-Tree Comparison". SIAM Journal on Computing 26, nr 1 (luty 1997): 210–30. http://dx.doi.org/10.1137/s0097539794262422.

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Rozprawy doktorskie na temat "Evolutionary programming (computer science)"

Tati, Kiran Kumar Smilkstein Tina Harriet. "General purpose evolutionary algorithm testbed". Diss., Columbia, Mo. : University of Missouri--Columbia, 2009. http://hdl.handle.net/10355/5359.

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The entire thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file; a non-technical public abstract appears in the public.pdf file. Title from PDF of title page (University of Missouri--Columbia, viewed on January 19, 2010). Thesis advisor: Dr. Tina Smilkstein. Includes bibliographical references.

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Job, Dominic Edward. "Case-based reasoning and evolutionary computation techniques for FPGA programming". Thesis, Edinburgh Napier University, 2001. http://researchrepository.napier.ac.uk/Output/4272.

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A problem in Software Reuse (SR) is to find a software component appropriate to a given requirement. At present this is done by manual browsing through large libraries which is very time consuming and therefore expensi ve. Further to this, if the component is not the same as, but similar to a requirement, the component must be adapted to meet the requirements. This browsing and adaptation requires a skilled user who can comprehend library entries and foresee their application. It is expensive to train users and to produce these documented libraries. The specialised software design domain, chosen in this thesis, is that of Field Programmable Gate Arrays (FPGAs) programs. FPGAs are user programmable microchips that have many applications including encryption and control. This thesis is concerned with a specific technique for FGPA programming that uses Evolutionary Computing (EC) techniques to synthesize FPGA programs. Evolutionary Computing (EC) techniques are based on natural systems such as the life cycle of living organisms or the formation of crystalline structures. They can generate solutions to problems without the need for complete understanding of the problem. EC has been used to create software programs, and can be used as a knowledge-lean approach for generating libraries of software solutions. EC techniques produce solutions without documentation. To automate SR it has been shown that it is essential to understand the knowledge in the software library. In this thesis techniques for automatically documenting EC produced solutions are illustrated. It is also helpful to understand the principles at work in the reuse process. On examination of large collections of evolved programs it is shown that these programs contain reusable modules. Further to this, it is shown that by studying series of similar software components, principles of scale can be deduced. Case Based Reasoning (CBR) is a problem solving method that reuses old solutions to solve new problems and is an effective method of automatically reusing software libraries. These techniques enable automated creation, documentation and reuse of a software library. This thesis proposes that CBR is a feasible method for the reuse of EC designed FPGA programs. It is shown that EC synthesised FPGA programs can be documented, reused, and adapted to solve new problems, using automated CBR techniques.

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Davis, Edward V. "Software testing for evolutionary iterative rapid prototyping". Monterey, California : Naval Postgraduate School, 1990. http://handle.dtic.mil/100.2/ADA232555.

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Thesis (M.S. in Computer Science)--Naval Postgraduate School, December 1990.
Thesis Advisor(s): Shimeall, Timothy J. Second Reader: Barnes, Patrick D. "December 1990." Description based on title screen as viewed on March 29, 2010. DTIC Identifier(s): Computer Program Verification, Prototypes, Software Engineering, User Manuals. Author(s) subject terms: Software Testing, Software Prototyping, Rapid Prototyping, Reusable Components, Requirements-based Testing, Software Testing Tools. Includes bibliographical references (p. 276-281). Also available in print.

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Heinze, Glenn. "Application of evolutionary algorithm strategies to entity relationship diagrams /". View PDF document on the Internet, 2004. http://library.athabascau.ca/scisthesis/Heinze.pdf.

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Schwartz, Bonnie Jo. "An Evolutionary Programming Algorithm for Automatic Chromatogram Alignment". Wright State University / OhioLINK, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=wright1175715183.

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Wilkerson, Joshua Lee. "Co-evolutionary automated software correction: a proof of concept". Diss., Rolla, Mo. : Missouri University of Science and Technology, 2008. http://scholarsmine.mst.edu/thesis/pdf/Wilkerson_09007dcc80642bb4.pdf.

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Thesis (M.S.)--Missouri University of Science and Technology, 2008.
Vita. The entire thesis text is included in file. Title from title screen of thesis/dissertation PDF file (viewed June 18, 2009) Includes bibliographical references (p. 62-64).

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Gramz, James. "Using Evolutionary Programming to increase the accuracy of an ensemble model for energy forecasting". Thesis, Marquette University, 2014. http://pqdtopen.proquest.com/#viewpdf?dispub=1554240.

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Natural gas companies are always trying to increase the accuracy of their forecasts. We introduce evolutionary programming as an approach to forecast natural gas demand more accurately. The created Evolutionary Programming Engine and Evolutionary Programming Ensemble Model use the current GasDay models, along with weather and historical flow to create an overall forecast for the amount of natural gas a company will need to supply to their customers on a given day. The existing ensemble model uses the GasDay component models and then tunes their individual forecasts and combines them to create an overall forecast.

The inputs into the Evolutionary Programming Engine and Evolutionary Programming Ensemble Model were determined based on currently used inputs and domain knowledge about what variables are important for natural gas forecasting. The ensemble model design is based on if-statements that allow different equations to be used on different days to create a more accurate forecast, given the expected weather conditions.

This approach is compared to what GasDay currently uses based on a series of error metrics and comparisons on different types of weather days and during different months. Three different operating areas are evaluated, and the results show that the created Evolutionary Programming Ensemble Model is capable of creating improved forecasts compared to the existing ensemble model, as measured by Root Mean Square Error (RMSE) and Standard Error (Std Error). However, the if-statements in the ensemble models were not able to produce individually reasonable forecasts, which could potentially cause errant forecasts if a different set of if-statements are true on a given day.

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Hong, Libin. "Hyper-heuristic approaches to automatically designing heuristics as mutation operators for evolutionary programming on function classes". Thesis, University of Nottingham, 2018. http://eprints.nottingham.ac.uk/52348/.

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A hyper-heuristic is a search method or learning mechanism for selecting or generating heuristics to solve computational search problems. Researchers classify hyper-heuristics according to the source of feedback during learning: Online learning hyper-heuristics learn while solving a given instance of a problem; Offline learning hyper-heuristics learn from a set of training instances, a method that can generalise to unseen instances. Genetic programming (GP) can be considered a specialization of the more widely known genetic algorithms (GAs) where each individual is a computer program. GP automatically generates computer programs to solve specified tasks. It is a method of searching a space of computer programs. GP can be used as a kind of hyper-heuristic to be a learning algorithm when it uses some feedback from the search process. Our research mainly uses genetic programming as offline hyper-heuristic approach to automatically design various heuristics for evolutionary programming.

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Nwamba, André Chidi. "Automated offspring sizing in evolutionary algorithms". Diss., Rolla, Mo. : Missouri University of Science and Technology, 2009. http://scholarsmine.mst.edu/thesis/pdf/Nwamba_09007dcc8068c83d.pdf.

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Thesis (M.S.)--Missouri University of Science and Technology, 2009.
Vita. The entire thesis text is included in file. Title from title screen of thesis/dissertation PDF file (viewed August 10, 2009) Includes bibliographical references (p. 49-51).

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Skolicki, Zbigniew Maciej. "An analysis of island models in evolutionary computation". Fairfax, VA : George Mason University, 2007. http://hdl.handle.net/1920/2954.

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Thesis (Ph. D.)--George Mason University, 2007.
Title from PDF t.p. (viewed Jan. 22, 2008). Thesis director: Kenneth A. De Jong. Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Computer Science. Vita: p. 422. Includes bibliographical references (p. 413-421). Also available in print.

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Książki na temat "Evolutionary programming (computer science)"

Conference on Evolutionary Programming (4th 1995 San Diego, Calif.). Evolutionary programming IV: Proceedings of the Fourth Annual Conference on Evolutionary Programming. Cambridge, Mass: MIT Press, 1995.

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Conference on Evolutionary Programming (5th 1996 San Diego, Calif.). Evolutionary programming V: Proceedings of the Fifth Annual Conference on Evolutionary Programming. Cambridge, Mass: MIT Press, 1996.

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Fogel, Lawrence J. Intelligence through simulated evolution: Forty years of evolutionary programming. New York: Wiley, 1999.

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Yu, Xinjie. Introduction to evolutionary algorithms. London: Springer, 2010.

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Kramer, Oliver. Self-adaptive heuristics for evolutionary computation. Berlin: Springer, 2008.

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Spears, William M. Evolutionary algorithms: The role of mutation and recombination. Berlin: Springer, 2000.

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1979-, Chiong Raymond, red. Nature-inspired informatics for intelligent applications and knowledge discovery: Implications in business, science, and engineering. Hershey, PA: Information Science Reference, 2009.

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W, Porto V., IEEE Neural Networks Council i Conference on Evolutionary Programming (7th : 1998 : San Diego, Calif.), red. Evolutionary programming VII: 7th international conference, EP98, San Diego, California, USA, March 25-27, 1998 : proceedings. Berlin: Springer, 1998.

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1949-, Dumitrescu D., red. Evolutionary computation. Boca Raton, FL: CRC Press, 2000.

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Branke, Jürgen. Evolutionary optimization in dynamic environments. Boston: Kluwer Academic Publishers, 2002.

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Części książek na temat "Evolutionary programming (computer science)"

Bo, Cheng, Guo Zhenyu, Bai Zhifeng i Cao Binggang. "Parallel Chaos Immune Evolutionary Programming". W Lecture Notes in Computer Science, 224–32. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11941439_26.

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Yao, Xin, i Yong Liu. "Scaling up evolutionary programming algorithms". W Lecture Notes in Computer Science, 103–12. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/bfb0040764.

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Fogel, David B., i Lawrence J. Fogel. "An introduction to evolutionary programming". W Lecture Notes in Computer Science, 21–33. Berlin, Heidelberg: Springer Berlin Heidelberg, 1996. http://dx.doi.org/10.1007/3-540-61108-8_28.

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Liu, Yong. "Measurements in Fast Evolutionary Programming". W Communications in Computer and Information Science, 79–86. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16388-3_9.

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Shum, Wing-Ho, Kwong-sak Leung i Man-Leung Wong. "Co-evolutionary Rule-Chaining Genetic Programming". W Lecture Notes in Computer Science, 546–54. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11508069_71.

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Zhu, Shinin, i Robert G. Reynolds. "Fuzzy cultural algorithms with evolutionary programming". W Lecture Notes in Computer Science, 209–18. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/bfb0040774.

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Liu, Yong. "Self-adaptation in Fast Evolutionary Programming". W Communications in Computer and Information Science, 232–39. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04962-0_27.

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Myung, Hyun, i Jong-Hwan Kim. "Lagrangian-based evolutionary programming for constrained optimization". W Lecture Notes in Computer Science, 35–44. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/bfb0028519.

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Liang, Ko-Hsin, Xin Yao, Charles Newton i David Hoffman. "Solving cutting stock problems by evolutionary programming". W Lecture Notes in Computer Science, 755–64. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/bfb0040826.

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Wong, Kit Po, i Jason Yuryevich. "Optimal Power Flow Method Using Evolutionary Programming". W Lecture Notes in Computer Science, 405–12. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/3-540-48873-1_52.

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Streszczenia konferencji na temat "Evolutionary programming (computer science)"

Chansareewittaya, Suppakarn. "Optimal Allocations of FACTS Controllers for Economic Dispatch using Evolutionary Programming". W 2017 21st International Computer Science and Engineering Conference (ICSEC). IEEE, 2017. http://dx.doi.org/10.1109/icsec.2017.8443901.

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Ji, Dou, i Xiang-jun Wang. "An Efficient Evolutionary Programming". W 2008 International Symposium on Information Science and Engineering (ISISE). IEEE, 2008. http://dx.doi.org/10.1109/isise.2008.313.

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Liu, Yong. "Evolutionary Programming with Operator Adaptation". W 7th IEEE International Conference on Computer and Information Technology (CIT 2007). IEEE, 2007. http://dx.doi.org/10.1109/cit.2007.165.

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Zirui Ma. "Function optimization research based on evolutionary programming". W IET International Conference on Information Science and Control Engineering 2012 (ICISCE 2012). Institution of Engineering and Technology, 2012. http://dx.doi.org/10.1049/cp.2012.2391.

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Siqing Xue i Jie Wu. "Gene expression programming based on symbiotic evolutionary algorithm". W 2011 2nd International Conference on Artificial Intelligence, Management Science and Electronic Commerce (AIMSEC). IEEE, 2011. http://dx.doi.org/10.1109/aimsec.2011.6010439.

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Vu, Tuong Manh, Charlotte Probst, Joshua M. Epstein, Alan Brennan, Mark Strong i Robin C. Purshouse. "Toward inverse generative social science using multi-objective genetic programming". W GECCO '19: Genetic and Evolutionary Computation Conference. New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3321707.3321840.

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Hoorfar, A., F. Ahmad i C. Thajudeen. "Synthesis of wideband imaging beamformers using evolutionary programming". W 2008 IEEE Antennas and Propagation Society International Symposium and USNC/URSI National Radio Science Meeting. IEEE, 2008. http://dx.doi.org/10.1109/aps.2008.4619366.

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Xu, Cao-cao, i Qi-ming Yang. "Decoupling the Lookaside Buffer from Simulated Annealing in Evolutionary Programming". W 2015 International Industrial Informatics and Computer Engineering Conference. Paris, France: Atlantis Press, 2015. http://dx.doi.org/10.2991/iiicec-15.2015.389.

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Hajebi, Maryam, i Ahmad Hoorfar. "A Multi-Resolution Evolutionary Programming Technique For GPR Applications". W 2019 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting. IEEE, 2019. http://dx.doi.org/10.1109/apusncursinrsm.2019.8888763.

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Kalluri, Charulatha, Sathyanarayana S. Rao i Nelatury Sudarshan Rao. "Using evolutionary programming for reconstruction of an irregularly sampled bandlimited sequence". W International Symposium on Optical Science and Technology, redaktorzy Bruno Bosacchi, David B. Fogel i James C. Bezdek. SPIE, 2001. http://dx.doi.org/10.1117/12.448336.

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Raporty organizacyjne na temat "Evolutionary programming (computer science)"

Anderson, Loren James, i Marion Kei Davis. Functional Programming in Computer Science. Office of Scientific and Technical Information (OSTI), styczeń 2016. http://dx.doi.org/10.2172/1237221.

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Proskura, Svitlana L., i Svitlana H. Lytvynova. The approaches to Web-based education of computer science bachelors in higher education institutions. [б. в.], lipiec 2020. http://dx.doi.org/10.31812/123456789/3892.

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The problem of organizing of Web-based education of bachelors, and the bachelors of computer science in particular, is relevant for higher education institutions. The IT industry puts forward new requirements for future IT professionals training. This, in its turn, requires the educational process modernization: content specification, updating of forms, methods and means of training to meet the demands of socio-economic development of the society in general and bachelors of computer science in particular. The article analyzes and clarifies the notion of Web-based education of bachelors; as well as a line of approaches, such as approaches to the organization of Web-based learning for A La Carte, Station Rotation, Lab Rotation, Individual Rotation, Flipped Learning scenario; the necessity of cloud computing and virtual classroom use as a component of Web-based learning is substantiated. It is established that with the advent of a large number of cloud-based services, augmented and virtual realities, new conditions are created for the development of skills to work with innovative systems. It is noted that the implementation of the approaches to the organization of student Web-based education is carried out on international level, in such projects as Erasmus+ “Curriculum for Blended Learning” and “Blended learning courses for teacher educators between Asia and Europe”. The article features the results of programming students survey on the use of Web-based technologies while learning, namely the results of a new approach to learning organization according to the formula – traditional (30%), distance (50%) and project (20%) training.

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Hlushak, Oksana M., Volodymyr V. Proshkin i Oksana S. Lytvyn. Using the e-learning course “Analytic Geometry” in the process of training students majoring in Computer Science and Information Technology. [б. в.], wrzesień 2019. http://dx.doi.org/10.31812/123456789/3268.

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As a result of literature analysis the expediency of free access of bachelors majoring in Computer Sciences and Information Technologies to modern information educational resources, in particular, e-learning courses in the process of studying mathematical disciplines is substantiated. It was established that the e-learning course is a complex of teaching materials and educational services created for the organization of individual and group training using information and communication technologies. Based on the outlined possibilities of applying the e-learning course, as well as its didactic functions, the structure of the certified e-learning course “Analytic Geometry” based on the Moodle platform was developed and described. Features of application of cloud-oriented resources are considered: Desmos, Geogebra, Wolfram|Alpha, Sage in the study of the discipline “Analytic Geometry”. The results of the pedagogical experiment on the basis of Borys Grinchenko Kyiv University and A. S. Makarenko Sumy State Pedagogical University are presented. The experiment was conducted to verify the effectiveness of the implementation of the e-learning course “Analytic Geometry”. Using the Pearson criterion it is proved that there are significant differences in the level of mathematical preparation of experimental and control group of students. The prospect of further scientific research is outlined through the effectiveness of the use of e-learning courses for the improvement of additional professional competences of students majoring in Computer Sciences and Information Technologies (specialization “Programming”, “Internet of Things”).

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Tkachuk, Viktoriia V., Vadym P. Shchokin i Vitaliy V. Tron. The Model of Use of Mobile Information and Communication Technologies in Learning Computer Sciences to Future Professionals in Engineering Pedagogy. [б. в.], listopad 2018. http://dx.doi.org/10.31812/123456789/2668.

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Research goal: the research is aimed at developing a model of use of mobile ICT in learning Computer Sciences to future professionals in Engineering Pedagogy. Object of research is the model of use of mobile ICT in learning Computer Sciences to future professionals in Engineering Pedagogy. Results of the research: the developed model of use of mobile ICT as tools of learning Computer Sciences to future professionals in Engineering Pedagogy is based on the competency-based, person-centered and systemic approaches considering principles of vocational education, general didactic principles, principles of Computer Science learning, and principles of mobile learning. It also takes into account current conditions and trends of mobile ICT development. The model comprises four blocks: the purpose-oriented block, the content-technological block, the diagnostic block and the result-oriented block. According to the model, the learning content of Computer Sciences consists of 5 main units: 1) Fundamentals of Computer Science; 2) Architecture of Modern Computers; 3) Fundamentals of Algorithmization and Programming; 4) Software of Computing Systems; 5) Computer Technologies in the Professional Activity of Engineer-pedagogues.

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Markova, Oksana M., Serhiy O. Semerikov, Andrii M. Striuk, Hanna M. Shalatska, Pavlo P. Nechypurenko i Vitaliy V. Tron. Implementation of cloud service models in training of future information technology specialists. [б. в.], wrzesień 2019. http://dx.doi.org/10.31812/123456789/3270.

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Leading research directions are defined on the basis of self-analysis of the study results on the use of cloud technologies in training by employees of joint research laboratory “Сloud technologies in education” of Kryvyi Rih National University and Institute of Information Technology and Learning Aids of the NAES of Ukraine in 2009-2018: cloud learning technologies, cloud technologies of blended learning, cloud-oriented learning environments, cloud-oriented methodological systems of training, the provision of cloud-based educational services. The ways of implementation SaaS, PaaS, IaaS cloud services models which are appropriate to use in the process of studying the academic disciplines of the cycles of mathematical, natural science and professional and practical training of future specialists in information technology are shown, based on the example of software engineering, computer science and computer engineering. The most significant advantages of using cloud technologies in training of future information technology specialists are definite, namely, the possibility of using modern parallel programming tools as the basis of cloud technologies. Conclusions are drawn; the direction of further research is indicated: designing a cloud-oriented learning environment for future specialists in computer engineering, identifying trends in the development of cloud technologies in the professional training and retraining of information technology specialists, developing a methodology for building the research competencies of future software engineering specialists by using cloud technologies.

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Striuk, Andrii M., i Serhiy O. Semerikov. The Dawn of Software Engineering Education. [б. в.], luty 2020. http://dx.doi.org/10.31812/123456789/3671.

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Designing a mobile-oriented environment for professional and practical training requires determining the stable (fundamental) and mobile (technological) components of its content and determining the appropriate model for specialist training. In order to determine the ratio of fundamental and technological in the content of software engineers’ training, a retrospective analysis of the first model of training software engineers developed in the early 1970s was carried out and its compliance with the current state of software engineering development as a field of knowledge and a new the standard of higher education in Ukraine, specialty 121 “Software Engineering”. It is determined that the consistency and scalability inherent in the historically first training program are largely consistent with the ideas of evolutionary software design. An analysis of its content also provided an opportunity to identify the links between the training for software engineers and training for computer science, computer engineering, cybersecurity, information systems and technologies. It has been established that the fundamental core of software engineers’ training should ensure that students achieve such leading learning outcomes: to know and put into practice the fundamental concepts, paradigms and basic principles of the functioning of language, instrumental and computational tools for software engineering; know and apply the appropriate mathematical concepts, domain methods, system and object-oriented analysis and mathematical modeling for software development; put into practice the software tools for domain analysis, design, testing, visualization, measurement and documentation of software. It is shown that the formation of the relevant competencies of future software engineers must be carried out in the training of all disciplines of professional and practical training.

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Modlo, Yevhenii O., Serhiy O. Semerikov, Pavlo P. Nechypurenko, Stanislav L. Bondarevskyi, Olena M. Bondarevska i Stanislav T. Tolmachev. The use of mobile Internet devices in the formation of ICT component of bachelors in electromechanics competency in modeling of technical objects. [б. в.], wrzesień 2019. http://dx.doi.org/10.31812/123456789/3264.

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Computer simulation of technical objects and processes is one of the components of the system of professional training of a modern electromechanics engineer. It has been established that despite the fact that mobile Internet devices (MID) are actively used by electrical engineers, the methods of using them in the process of bachelor in electromechanics training is considered only in some domestic scientific studies. The article highlights the components of the methods of using MID in the formation of the ICT component of the competence of the bachelor in electromechanics in modeling of technical objects, providing for students to acquire basic knowledge in the field of Computer Science and modern ICT and skills to use programming systems, math packages, subroutine libraries, and the like. For processing tabular data, it is proposed to use various freely distributed tools that do not significantly differ in functionality, such as Google Sheets, Microsoft Excel, for processing text data – QuickEdit Text Editor, Google Docs, Microsoft Word. For 3D-modeling and viewing the design and technological documentation, the proposed comprehensive use of Autodesk tools in the training process.

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Balyk, Nadiia, Svitlana Leshchuk i Dariia Yatsenyak. Developing a Mini Smart House model. [б. в.], luty 2020. http://dx.doi.org/10.31812/123456789/3741.

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The work is devoted to designing a smart home educational model. The authors analyzed the literature in the field of the Internet of Things and identified the basic requirements for the training model. It contains the following levels: command, communication, management. The authors identify the main subsystems of the training model: communication, signaling, control of lighting, temperature, filling of the garbage container, monitoring of sensor data. The proposed smart home educational model takes into account the economic indicators of resource utilization, which gives the opportunity to save on payment for their consumption. The hardware components for the implementation of the Mini Smart House were selected in the article. It uses a variety of technologies to conveniently manage it and use renewable energy to power it. The model was produced independently by students involved in the STEM project. Research includes sketching, making construction parts, sensor assembly and Arduino boards, programming in the Arduino IDE environment, testing the functioning of the system. Research includes sketching, making some parts, assembly sensor and Arduino boards, programming in the Arduino IDE environment, testing the functioning of the system. Approbation Mini Smart House researches were conducted within activity the STEM-center of Physics and Mathematics Faculty of Ternopil Volodymyr Hnatiuk National Pedagogical University, in particular during the educational process and during numerous trainings and seminars for pupils and teachers of computer science.

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Shamonia, Volodymyr H., Olena V. Semenikhina, Volodymyr V. Proshkin, Olha V. Lebid, Serhii Ya Kharchenko i Oksana S. Lytvyn. Using the Proteus virtual environment to train future IT professionals. [б. в.], luty 2020. http://dx.doi.org/10.31812/123456789/3760.

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Based on literature review it was established that the use of augmented reality as an innovative technology of student training occurs in following directions: 3D image rendering; recognition and marking of real objects; interaction of a virtual object with a person in real time. The main advantages of using AR and VR in the educational process are highlighted: clarity, ability to simulate processes and phenomena, integration of educational disciplines, building an open education system, increasing motivation for learning, etc. It has been found that in the field of physical process modelling the Proteus Physics Laboratory is a popular example of augmented reality. Using the Proteus environment allows to visualize the functioning of the functional nodes of the computing system at the micro level. This is especially important for programming systems with limited resources, such as microcontrollers in the process of training future IT professionals. Experiment took place at Borys Grinchenko Kyiv University and Sumy State Pedagogical University named after A. S. Makarenko with students majoring in Computer Science (field of knowledge is Secondary Education (Informatics)). It was found that computer modelling has a positive effect on mastering the basics of microelectronics. The ways of further scientific researches for grounding, development and experimental verification of forms, methods and augmented reality, and can be used in the professional training of future IT specialists are outlined in the article.

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Striuk, Andrii M. Software engineering: first 50 years of formation and development. [б. в.], grudzień 2018. http://dx.doi.org/10.31812/123456789/2880.

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The article analyzes the main stages of software engineering (SE) development. Based on the analysis of materials from the first SE conferences (1968-1969), it was determined how the software crisis prompted scientists and practitioners to join forces to form an engineering approach to programming. Differences in professional training for SE are identified. The fundamental components of the training of future software engineers are highlighted. The evolution of approaches to the design, implementation, testing and documentation of software is considered. The system scientific, technological approaches and methods for the design and construction of computer programs are highlighted. Analysis of the historical stages of the development of SE showed that despite the universal recognition of the importance of using the mathematical apparatus of logic, automata theory and linguistics when developing software, it was created empirically without its use. The factor that led practitioners to turn to the mathematical foundations of an SE is the increasing complexity of software and the inability of empirical approaches to its development and management to cope with it. The training of software engineers highlighted the problem of the rapid obsolescence of the technological content of education, the solution of which lies in its fundamentalization through the identification of the basic foundations of the industry. It is determined that mastering the basics of computer science is the foundation of vocational training in SE.

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