4 research outputs found

    Life and scientific research of professor W艂adys艂aw Pe艂czewski

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    On the 100th anniversary of his birth, Professor W艂adys艂aw Pe艂czewski was recognized by polish electricians and the Board of the Polish Society of Theoretical and Applied Electrical Engineering (resolution of December 12, 2016 ) as the patron of the year 2017. Professor W艂adys艂aw Pe艂czewski worked at the Faculty of Electrical Engineering of the Lodz University of Technology (now the Faculty of Electrical Engineering, Electronics, Computer Science and Automation) since October 1945. He began his work at the Lodz University of Technology as a student, taking up the position of junior assistant in the Chair of Electrical Machines and Transformers organized by prof. Boleslaw Dubicki. He has gone through all the levels of a scientific career. Professor W艂adys艂aw Pe艂czewski was a eminent scientist and engineer in the field of automation and electrical engineering. His research interests included electrical machines, electrical automation and the theory and application of automatic control with particular focus on optimal control of plants with external disturbances, constraints and changes in parameters. He was the creator of the Lodz school of automatic control of electrical drives and his scientific achievements are known and valued in Poland and throughout the world. He presented his work as visiting professor at universities in Toulouse, Rome, Bologna, Siegen, Paris, Grenoble, Padua, Darmstadt, Munich, Zurich, Milan, Stockholm, Glasgow and Delft.W 100 rocznic臋 urodzin uchwa艂膮 Zarz膮du G艂贸wnego Polskiego Towarzystwa Elektrotechniki Teoretycznej i Stosowanej (z dnia 12 grudnia 2016 roku), profesor W艂adys艂aw Pe艂czewski zosta艂 uznany przez polskich elektryk贸w za Patrona Roku 2017. Profesor W艂adys艂aw Pe艂czewski pracowa艂 na Wydziale Elektrycznym Politechniki 艁贸dzkiej (obecnie Wydzia艂 Elektrotechniki, Elektroniki, Informatyki i Automatyki) od pa藕dziernika 1945 roku. Prac臋 w Politechnice 艁贸dzkiej rozpocz膮艂 jeszcze jako student obejmuj膮c stanowisko m艂odszego asystenta w katedrze Maszyn Elektrycznych i Transformator贸w zorganizowanej przez prof. Boles艂awa Dubickiego. Przeszed艂 wszystkie szczeble kariery naukowej. Profesor W艂adys艂aw Pe艂czewski by艂 wybitnym naukowcem i in偶ynierem w dziedzinie automatyki i elektrotechniki. Jego zainteresowania naukowe dotycz膮 zagadnie艅 zwi膮zanych z maszynami elektrycznymi, automatyzacj膮 nap臋du elektrycznego oraz z teori膮 i zastosowaniem automatyki ze szczeg贸lnym uwzgl臋dnieniem sterowania optymalnego obiekt贸w poddanych zak艂贸ceniom zewn臋trznym, zmianom parametr贸w i ograniczeniom. By艂 tw贸rc膮 艂贸dzkiej szko艂y naukowej automatyki nap臋d贸w elektrycznych, a jego osi膮gni臋cia naukowe s膮 znane i cenione w kraju i za granic膮. Wyniki swoich prac przedstawia艂 jako visiting professor na uniwersytetach w Tuluzie, Rzymie, Bolonii, Siegen, Pary偶u, Grenoble, Padwie, Darmstadt, Monachium, Zurychu, Mediolanie, Sztokholmie, Glasgow i Delft

    Impact of data indexing on the speed of execution of SQL queries

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    Przedmiotem pracy jest analiza do艣wiadczalna wp艂ywu wybranych metod indeksowania na czas wykonania polecenia SQL. Badaniom poddano baz臋 testow膮 wydzielon膮 z rzeczywistego systemu bankowego. Pomiary czasu wykonania zapytania SQL wykonano dla tabel zawieraj膮cych do 1000000 rekord贸w. Badania przeprowadzono dla tabel nie zawieraj膮cych indeks贸w oraz tabel zawieraj膮cych indeksy. Do bada艅 wykorzystano relacyjny system zarz膮dzania baz膮 danych oparty na Oracle 9. Wyniki bada艅 do艣wiadczalnych pozwoli艂y na modernizacj臋 pracy systemu bankowego.The subject of the study is to analyse the impact of selected experimental methods of crawling on the execution time of SQL commands. The study involved test database separate from the actual banking system. Measurements runtime SQL queries made for tables containing up to 1000000 records. The study was conducted for tables that do not contain indexes and tables with indexes. The study used relational database management system based on Oracle. The experimental results have enabled the modernization work of the banking system. Analysis of the results showed that the use of indices in most of the cases can significantly reduce the waiting time for the results of SQL queries, especially for tables containing a large amount of records. In the cases studied to reduce the time it was even more than 6few hundred times

    Establishment of The Lodz Department of PTETiS

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    W artykule przedstawiono histori臋 powo艂ania do 偶ycia Oddzia艂u 艁贸dzkiego Polskiego Towarzystwa Elektrotechniki Teoretycznej i Stosowanej (PTETiS) na tle dziej贸w i powstawania Wydzia艂u Elektrycznego Politechniki 艁贸dzkiej i osi膮gni臋膰 za艂o偶ycieli Oddzia艂u.The article presents the story of creating the Lodz Department of the Polish Society for Theoretical and Applied Electrical Engineering (PTETiS) against a backdrop of the formation of the Faculty of Electrical Engineering of the Lodz University of Technology and the achievements of the founders of the Department. The development of technical sciences including electrical engineering in the academic community at the end of the sixties became the basis for the establishment of a society, which would aim to promote and support work in the field of electrical engineering theory and its applications. The idea of establishing the Society for Theoretical and Applied Electrical Engineering matured in the academic community of Polish electricians

    Adaptive database's performance tuning based on reinforcement learning

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    Database (DB) performance tuning is a difficult task that requires a vast amount of skill, experience and efforts in tweaking a DB for optimum results. With the hundreds of parameters to be considered under the diverse application configurations, business logic and software technology, getting a true global optimum setting is difficult for a DB administrator. We propose a novel approach based on Reinforcement Learning to tune a DB adaptively with minimum risk to the production setup. It results in a new set of parameters tailored to the production DB. Empirical results show that there is a significant gain in performance for the DB in its overall efficiency while reducing the IO overheads, based on a set of key performance statistics collected before and after the optimization process
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