Dashboard for Well-Arranged Displaying Company Data

Import 23/08/2017Cílem této bakalářské práce je vytvoření funkčního klienta informačního systému pro operační systém Windows 10 pomocí technologie Universal Windows Platform. Aplikace má za úkol přehledně zobrazit data pomocí grafů a tabulek, a jejich filtraci pomocí několika druhů filtrů. Data jsou stahována z webových služeb společnosti K2 atmitec. Dále program umožňuje stahování notifikací a příjem push notifikací systému Windows.The purpose of this bachelor thesis is creation of functional client of information system for operation system Windows 10 with Universal Windows Platform technology. The task of application is to show data in well-arranged manner using charts and tables, and filtration of data by several types of filters. Data are downloaded from web services created by company K2 atmitec. Another task of application is to download notification and allow receiving of push notification by Windows system.460 - Katedra informatikyvelmi dobř

Natural Deduction System for the TIL-Script Language

V mé práci se zabývám vytvořením interaktivního nástroje pro dokazování pomocí přirozené dedukce v jazyce TIL-Script. Pro použití nástroje shrnu základy logických kalkulů, teorie Transparentní intenzionální logiky a její komputační variantu TIL-Script. V práci uvádím úplný seznam všech pravidel pro přirozenou dedukci, které je možno v nástroji použít a výslednou analýzu, návrh a implementaci nástroje.My work is to create an interactive tool for proving using natural deduction in TIL-Script language, To use the tool I will summarize the basics of logical calculus, the theory of Transparent intensional language and it’s computational variant TIL-Script. In the work I present complete list of all the rules for natural deduction that can be used in the tool and final analysis, design and implementation of the tool.460 - Katedra informatikyvýborn

Refining concepts by machine learning

DOI nefunkční (25.11.2019)In this paper we deal with machine learning methods and algorithms applied in learning simple concepts by their refining or explication. The method of refining a simple concept of an object O consists in discovering a molecular concept that defines the same or a very similar object to the object O. Typically, such a molecular concept is a professional definition of the object, for instance a biological definition according to taxonomy, or legal definition of roles, acts, etc. Our background theory is Transparent Intensional Logic (TIL). In TIL concepts are explicated as abstract procedures encoded by natural language terms. These procedures are defined as six kinds of TIL constructions. First, we briefly introduce the method of learning with a supervisor that is applied in our case. Then we describe the algorithm 'Framework' together with heuristic methods applied by it. The heuristics is based on a plausible supply of positive and negative (near-miss) examples by which learner's hypotheses are refined and adjusted. Given a positive example, the learner refines the hypothesis learnt so far, while a near-miss example triggers specialization. Our heuristic methods deal with the way refinement is applied, which includes also its special cases generalization and specialization.Web of Science23395894