Tai teorinis meno praktinis darbas, kuriame analizuojamas dirbtinio intelekto reiškinys, jo vaidmuo sociume bei įtaka šiuolaikiniam medijų menui. Temos vizualizavimui pasirintas performansas ir video projekcija, sukurta „Rutt Etra“ metodu. Šiuo būdu kuriama realaus laiko manipuliacija gyvu vaizdu. „Rutt Etra“ metodu sukurti vaizdiniai atveria naujas galimybes tyrinėti dirbtinio intelekto reiškinį visiškai naujoje plotmėje. Išradimas kontroliuoja elektros įtampą ir signalo variacijas, kurios sukelia atskirų skenavimo linijų iškraipymus. Priešingai nei įprastas sintezatorius, šis generuoja vaizdą ir garsą, susiedamas skirtingus objektus. Procesorius analizuoja mažiausius video vienetus, bangų formos principu. Darbe aptariama dirbtinio intelekto diskurso teorinė ir praktinė raida. DI kuria naują gyvybės formą. Šis reiškinys įsiliejęs daugybėje gyvenimo sričių. / This is theoretical – practical in terms of art paper, which focuses on analysis of phenomenon of artificial intelligence, its role within the socium and its influence concerning the contemporary media arts. Performance and video projection, created by “Rutt Etra” method, are chosen to visualise the topic of the present research. This way the real time manipulation with the help of the lively picturing is being created. The pictures created with the help of “Rutt Etra” method provide new grounds for analysis of Artificial intelligence in a completely new space The invention controls the voltage strain and variations of the signal which are responsible for creating distortions in lines of scanning. Contrary to the nature of the ordinary synthesizer, this one generates pictures and sounds, bounding different objects together. Processor analyzes the smallest video units by principle of wave form. In this work both theoretical and practical evolution of Artificial intelligence discourse is overviewed. AI creates new form of life. This phenomenon has entangled itself into many domains of ordinary life.

Pagrindinis darbo tikslas yra pritaikant dirbtinio intelekto algoritmus sukurti ranka rašyto teksto atpažinimo įrankį. Siekiant šio tikslo buvo apžvelgti dirbtinio intelekto atpažinimo metodai, atlikta teksto atpažinimo algoritmų analizė. Remiantis analizės rezultatais, sukurta ranka rašyto teksto atpažinimo programa, kurioje teksto segmentavimo operacija atliekama „lašelio aptikimo“ algoritmu. Teksto atpažinimo operacijai atlikti naudojamas bitų masyvų analizės algoritmas. / The aim of this work is to create an application for handwritten text recognition using artificial intelligence algorithms. For this purpose a number of recognition methods based on artificial intelligence were reviewed. Based on the review information an application was created for the purpose of recognizing handwritten text. The text segmentation was implemented using a blob detection algorithm. Text recognition was performed using bit array analysis algorithm. During the implementation and testing stage the main problem areas of such application were identified.

Magistro baigiamajame darbe išnagrinėtas automatinio šnekos emocijų atpažinimo uždavinys. Nors pastaruoju metu šios srities populiarumas yra smarkiai išaugęs, tačiau vis dar trūksta literatūros aprašančios konkrečių požymių ar požymių rinkinių efektyvumą kalbos emocijoms atpažinti. Ši problema suformavo magistro baigiamojo darbo tikslą – ištirti akustinių požymių taikymą šnekos emocijoms atpažinti. Darbo metu buvo atlikta požymių sistemų analizė, sukurta emocijų požymių sistemų (rinkinių) testavimo sistema, kuria atliktas požymių rinkinių tyrimas. Tyrimo metu gauti rezultatai yra labai panašūs arba šiek tiek lenkia pastaruoju metu paskelbtus emocijų atpažinimo rezultatus naudojant Berlyno emocingos kalbos duomenų bazę. Remiantis gautais eksperimentų rezultatais, buvo sudarytos požymių rinkinių formavimo rekomendacijos. Magistro baigiamasis darbas informatikos inžinerijos laipsniui. Vilniaus Gedimino technikos universitetas. Vilnius, 2014. / This Master's thesis has examined the automatic speech emotion recognition task. Recently, the popularity of this area is greatly increased, but there is still a lack of literature describing specific acoustic features (or feature sets) performance in automatic emotion recognition task. This issue formed the purpose of this work - to explore suitable acoustic feature sets for emotion recognition task. This work includes analysis of emotion feature systems and development of speech emotion characteristics testing system. Using developed system, investigation experiments of speech emotion parameters were accomplished. The study results are very similar, or slightly ahead to recently published results of emotion recognition using the Berlin emotional speech database. According to the results of the experiments, recommendations for creating effective speech emotion feature sets were concluded. Master's degree thesis in informatics engineering. Vilnius Gediminas Technical University. Vilnius, 2014.

Many discussions on the legal regulation of artificial fertilization are taking place in Lithuania though consensus is not yet achieved. Services of assisted reproduction cause fierce scientific, ethical, legal, and religious disputes in Lithuania and elsewhere. It is important to emphasize that legalization of in vitro fertilization at the international as well as national levels is not going to solve the problem. To do this, it is necessary to plan a mechanism of the implementation of the law which would cover many spheres of the legal regulation. The major problem becomes the shortage of scientific studies on legal regulation of artificial fertilization in Lithuania and the rest of the world. The author analyzes the issues of legal regulation of artificial fertilization in Lithuania providing a theoretical model of regulation of the procedure and implementation of the law. The analytical part of the study includes an analysis of the existing bills on artificial fertilization which reveals that both the first and the alternative bills are not quite finished yet and require improvement. Nevertheless the regulation scheme and the content of the Project IXP – 1966(2)A satisfy the main scientific paradigms defined in the theoretical part of the thesis.

At the moment social exclusion is a topical problem in a whole Europe. That’s why innovative decisions are prompted for social exclusive group of people in order to facilitate their integration process into the labour market. The stepping-stone of this work is e-advisor for choosing possibilities within social isolation environment. This e-advisor is created in accordance with artificial neural network and considering to individual person’s features give suggestions for the most suitable professions. Also in this work is presented disease diagnostic model, which is defined by artificial neural network.

Game Artificial Intelligence (AI) is the code in game that makes the computer-controlled opponents (agents) to make smart decisions in game world. There are some AI problems that are essential in games: pathfinding, decision making, generating player’s characteristics, game’s logic management. However these problems are gameplay dependant. The main goal of this study – to generalize AI problems’ solutions for games of many kinds, that is, to make AI solutions gameplay independent. We have achieved this goal by using data-driven design in our solutions. We separated the game logic and the game code levels by using this approach. Such separation gave us an opportunity to manipulate game logic and data freely. We have examined our decision making system and determined that it is flexible and is easy of use.

Bajeso metodo taikymas kreditų rizikos valdyme: atlikta įvairių egzistuojančių metodų rizikai valdyti tyrimas, pateiktas analitinėje dalyje, aprašyti kai kurie plačiau naudojami mašininio mokymo ir matematiniai modeliai. Paiūlytas modelis eksperimentui atlikti, atliktas empirinis tyrimas ir pateikti gauti rezultatai, pateiktos išvados ir ateities perspektyvos. / Baysan Method for a Credit Risk Management This paper presents a method combining popular machine learning technique for classification, genetic search as a feature selection method for relevant attribute selection and Altman Z-Score discriminant technique for credit risk evaluation. Bayesian method based classifiers (Naïve Bayes, Bayesian Networks) were explored and used in this article to train classifiers. This method was applied to different sectors in service and industry. Its performance was evaluated using weighted mean accuracy and weighted mean error techniques. In theoretical part several methods were analyzed and described, in the end conclusions and suggestions were pointed.

Šiame darbe buvo pasiūlyti dirbtinio intelekto pritaikymo būdai bei metodai, kompiuterinio žaidimo personažui, dviejų personažų koviniam žaidimui. Pasiūlytais būdais bei metodais buvo bandoma pritaikyti dirbtinį intelektą kompiuterinio žaidimo personažui, šio tipo žaidimui. Buvo tiriama ar pasliūlyti būdai ir metodai tinka šiai kompiuterinių žaidimų klasei. Taip pat buvo tiriamas agento mokymosi greitis, nuo ko jis priklauso bei ieškomi faktoriai, kurie lemia tokio tipo žaidimo personažams sparčiau mokintis ir naudingiau naudotis įgytomis žiniomis. Atrastus ir ištirtus faktorius buvo stengiamasi suderinti taip, kad mokomas personažas balansuotų tarp greitai besimokančio ir tinkamai besinaudojančio išmoktomis žiniomis. / In this work was offered an adjustments of techniques and methods of artificial intelligence for computer player, in two-players combat games. There was tried to adapt the artificial intelligence to the computer player, with those proposed techniques and methods in this type of games. Also was investigated whether those proposed techniques and methods suits for this class of computer games. In this work also was analyzed agent learning speed, on what depends it and explored the factors that determines the rapid learning speed and efficient use of agent knowledge. Discovered and investigated factors were fitted to the rapid learning speed and efficient use of agent knowledge.

Šis magistrinis darbas aprašo plačiausiai naudojamus dirbtinio intelekto metodus ir galimybes juos taikyti kredito rizikos, kuri yra viena svarbiausių sričių bankininkystėje ir finansuose, vertinime. Pagrindinė problema yra rizikos, atsirandančios kreditoriui išduodant kreditą tam tikram individui ar bendrovei, vertinimas, naudojant įvairius matematinius, statistinius ar kitus metodus. Ši rizika atsiranda tada, kai skolininkas negali laiku grąžinti skolos kreditoriui, kas reiškia papildomus nuostolius. Ji gali pasireikšti, priklausomai nuo skolininko tipo (individas, bendrovė ar užsienio vyriausybė) bei finansinio instrumento tipo ar su juo atliekamo veiksmo (skolos teikimas, finansinių derivatyvų tranzakcijos ir kt.), todėl finansinės institucijos jos įvertinimui bei valdymui naudoja įvairius metodus nuo vertinimo balais bei skirtingų faktorių, tokių kaip valdymo bei veiklos strategijos bei politika, įvertinimo iki klasifikavimo pagal įvairius kriterijus, naudojant modernius ir sudėtingus metodus, tiek matematinius, tiek dirbtinio intelekto. Ši sritis plačiai tiriama ir daug naujų metodų bei sprendimų pastoviai randama. Šio darbo tyrimas sukoncentruotas į atraminių vektorių mašinų (angl.Support Vector Machines, sutr. SVM) metodų, kuris yra viena populiariausių dirbtinio intelekto bei mašininio mokymo metodų ir kurio efektyvumas daugeliu atveju įrodytas. Šiuo tyrimo tikslas yra ištirti galimybes pritaikyti SVM metodą čia aprašomai problemai bei realizuoti sistemą, naudojančią... [toliau žr. visą tekstą] / This master work describes the most widely used artificial intelligence methods and the possibilities to apply them in credit risk evaluation which is one of the most important fields in banking and in finance. The main problem here is to evaluate the risk arising when a creditor gives a credit to a particular individual or an enterprise, using various mathematical, statistical or other methods and techniques. This risk arises when the debtor isn’t able to pay for the loan to the creditor in time which means additional loss. It can appear in many forms depending on the type of debtor (individ-ual, enterprise, government of an abroad country) and type of financial instrument or action that is done with it (giving of a loan, transactions of financial derivatives, etc.), this is the reason why fi-nancial institutions and for it’s evaluation and management use various different methodologies which comprise a lot of methods and techniques from credit scoring (evaluating by a particular formula, usually linear) and evaluating different factors, like management and business strategies or policies, to classification by various criterions by using modern and sophisticated methods, either algebraic, either artificial intelligence and machine learning. This field is widely researched and many new techniques are being found. The research here is concentrated mainly on Support Vector Machines (abbr. SVM) which is one of the most popular artificial intelligence and machine learning... [to full text]

This postgraduate thesis investigates legal aspects of human assisted reproduction‘s reimbursement from the Public Health Insurance Fund‘s Budget. Nowadays human assisted reproduction is not covered by the State Budget in Lithuania. That‘s why this thesis presents hypothetical model of reimbursement. The model is substantiated using historical anglysis of the probleme, worldwide practice in biomedicine and health care management. Legal aspects are analysed from the standpoint of intersection in different branches of sciences. The emphasis lays on imperfect legislation and controversies of reproductive health care, it‘s close connections with ethical problemes in human relationships, on human life and traditional family protection as priority in Lithuania‘s Fundamental Law. Legal propositions are linked with Evidence Based Medicine Gudelines (EBMG) and efficient assesment of State Budget resources as a basis of Public Health Insurance.