Į baigiamojo darbo sudėtį įeina SQL Server 2005, Reporting Services, bei kitų numatomų instrumentinių priemonių ir technologijų analizė, reikalavimų sistemai išgavimas, taip pat sistemos modulių projektavimas bei apjungimas ir realizacija. Sistema supruojektuota ir realizuota remiantis sudaryta specifikacija. Sistemos realizacijai naudojami Microsoft SQL Server 2005 bei Microsoft Visual Studio 2005 programavimo paketai. Taip pat pateikiama, jau realizuotos sistemos testavimo rezultatai ir išvados. / This final work includes SQL Server 2005, Reporting Services and other instrumental tools or technology analysis, requirement for the system extraction and also modules of the system projection, integration to one unit and realization. The system was designed and implemented in accordance with specification. To implement the system was used Microsoft SQL Server 2005 and Microsoft Visual Studio 2005 programming packages. Also there are the testing results of the system and final conclusions.

Statistikos departamentas siekdamas užtikrinti statistinės informacijos kokybę vadovaujasi Europos statistikos sistemos kokybės deklaracijos ir Europos statistikos praktikos kodekso nuostatomis. Tuo tarpu Pramonės statistikos skyrius savo skelbiamos informacijos kokybę pagerinti gali padidinus pirminių statistinių duomenų kontrolių ir klaidų „išgaudymo“ skaičiumi. Taigi, vienas iš pagrindinių šio darbo uždavinių ir buvo – gerinti Pramonės statistikos skyriaus skelbiamų duomenų (apie pagrindinių gaminių gamybos ir pardavimo apimtis ir jų pokyčius) kokybę, t.y. automatizuoti įmonių pramoninių gaminių gamybos ataskaitose loginių klaidų paiešką. Loginių klaidų „išgaudymui“ buvo pasiūlytos programos, kurių veikimas buvo patikrintas su pirminių (duomenys iki antrinio redagavimo) duomenų rinkiniu, o gauti rezultatai – tai įmonių, padariusių vienokio ar kitokio tipo loginę klaidą, sąrašas. Atlikus logistinę regresiją, buvo gauta, kad klaidos atsiradimą įtakoja ataskaitos pateikimo būdas (t.y. elektroninės formos siuntimas), gaminio kodo agregavimo lygis (t.y. tie kodai, kurie išsiskaido į smulkesnius kodus) bei matavimo vienetai kai jie yra „-“. / In order to warrant the quality of statistical information the Department of Statistics to the Government of the Republic of Lithuania follows Quality declaration of the European Statistical System and Code of practice for European statistics. The Division of statistics on industry, accordingly, in order to improve the quality of information it publishes may increase the number of primary statistical data controls and error eliminations. Thus, the primary aim of this thesis is to improve the quality of data (on the amount and changes of production and trade of major products) that is published by the Division of statistics on industry, i.e. to automate the search for the logical errors in the reports on the production of industry products at enterprises. A software application was developed for the elimination of logical errors. It was tested with the set of primary statistical data (the data before the secondary editing) and it provided as its result a list of companies that have made some kind of mistake. By means of logistic regression it was found that the appearance of a mistake is conditioned by the method of submission of the report (i.e., the uploading of an electronic form), by the level of aggregation of a product code (i.e., the codes that resolve into smaller codes) and by the measures when they are “-”.

This thesis has been performed for the company System Andersson as a part of the bachelors degree in information technology at the School of Engineering in Jönköping. The thesis is based on the development of an iPhone application. System Andersson has an application for Android that is being used for their MPS system (material and production control system). Their customers, however, have also showed interest in being able to use this application for iPhone. The students handle the subject of iOS developing, including the design of the application, the use of the development language Objective-C, the use of the scripting language of Json used for server connections and SQL. The primary goal with this thesis has been to improve the students knowledge in such subjects as application development for mobile platforms, in such areas as Xcode, which is the development platform that Apple uses and Objective-C, which is the development language being used.   The result of this thesis is an almost fully functional iOS application, similar to the Android application with some functionality missing. / Detta examensarbete har utförts åt företaget System Andersson i samband med utbildningen på Tekniska Högskolan i Jönköping. Arbetet gick ut på att utveckla en applikation för iPhone. System Andersson har sedan tidigare en applikation kopplad till sitt MPS-system (material och-produktionsstyrningssystem) för operativsystemet Android och deras kunder har visat intresse för en liknande applikation för iOS. Studenterna går i denna rapport igenom utvecklingen av en applikation för iOS, samt designen, med hjälp av utvecklingsspråket Objektive-C, skriptspråket Json och SQL. Målet med detta examensarbete var främst att få bra kännedom om att utveckla mobila applikationer, att lära känna utvecklingsmiljön som Apple använder samt att få kunskap om Objective-C. Resultatet av examensarbetet har blivit en näst intill fullt fungerande applikation, som dock i dagsläget saknar vissa funktioner.

During development of information system, we have problems to choose appropriate architecture, technologies and methods. The conception of information system, designing methods, problems, related with information system development is given in this work. There are mentioned the main security requirement for hospital information system. We analyze created system “Information system of psychophysiology rehabilitation patients”. There are mentioned the main cases why client/server architecture, new technology adaptation were selected. The comparison of methods for data interface realization: PL/SQL language written in stored procedures and query generation is given. The selected method rating - how it speed system developing and how it influence system performance are evaluated. There are given experiments, which decrease system performance by selected methods.

Šis darbas nagrinėja naftos išsiliejimų atviruose vandens telkiniuose problematiką, tokių išsiliejimų atpažinimo iš gautų radaro vaizdų algoritmus, jų veiksmingumą, false-alarm identifikavimą, ir klasifikavimo metodiką, bei taikymus praktikoje. Vienas šio darbo tikslų – sukurti įrankį, leidžiantį analizuoti naftos dėmių sekimo ir atpažinimo sistemos charakteristikas ir nustatyti atpažinimo metodiką, leidžiančią efektyviausiai atpažinti naftos dėmes duotomis sąlygomis, bei ją algoritmizuoti ir taikyti automatiškai. / This paper examines problematics of oil spill detection in open water, detection of such oil spills from given radar images, their breakdown into categories, identification of false alarms and the use of specific algorithms to detect oil spills not only from static, but also from dynamic radar images. One of the main purposes of this work is to create a tool, which would allow to locate and analyze oil spill detections from given sensor data in given conditions, to define an efficient method for oil spill detection, to express this method algorithmycally and to adjust it for automatic application.

Human learning and classification is a nebulous area in computer science. Classic decisioning problems can be solved given enough time and computational power, but discrete algorithms cannot easily solve fuzzy problems. Fuzzy decisioning can resolve more real-world fuzzy problems, but existing algorithms are often slow, cumbersome and unable to give responses within a reasonable timeframe to anything other than predetermined, small dataset problems. We have developed a database-integrated highly scalable solution to training and using fuzzy decision models on large datasets. The Fuzzy Decision Tree algorithm is the integration of the Quinlan ID3 decision-tree algorithm together with fuzzy set theory and fuzzy logic. In existing research, when applied to the microRNA prediction problem, Fuzzy Decision Tree outperformed other machine learning algorithms including Random Forest, C4.5, SVM and Knn. In this research, we propose that the effectiveness with which large dataset fuzzy decisions can be resolved via the Fuzzy Decision Tree algorithm is significantly improved when using a relational database as the storage unit for the fuzzy ID3 objects, versus traditional storage objects. Furthermore, it is demonstrated that pre-processing certain pieces of the decisioning within the database layer can lead to much swifter membership determinations, especially on Big Data datasets. The proposed algorithm uses the concepts inherent to databases: separated schemas, indexing, partitioning, pipe-and-filter transformations, preprocessing data, materialized and regular views, etc., to present a model with a potential to learn from itself. Further, this work presents a general application model to re-architect Big Data applications in order to efficiently present decisioned results: lowering the volume of data being handled by the application itself, and significantly decreasing response wait times while allowing the flexibility and permanence of a standard relational SQL database, supplying optimal user satisfaction in today's Data Analytics world. We experimentally demonstrate the effectiveness of our approach.

CA, Univ., Diss--Stanford.

Thesis (M.S.)--Rochester Institute of Technology, 1989. / Includes bibliographical references (leaves 67-68).

Stuttgart, Univ., Diss., 2000.

Chemnitz, Techn. Univ., Diplomarb., 1999.