El texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado. / This analysis proposes a decision tree for selecting cross-device communication technologies for iOS and Android mobile devices. This tree accelerates the selection of cross-device technologies by taking into account known use cases of interaction. Five different communication technologies were tested (Real-time Multiplayer, Nearby Messages, PeerJS, iBeacon and Eddystone) by means of 13 proof of concept applications distributed between both operating systems (Android-iOS, iOS-iOS, Android-Android) and the design of 20 architecture diagrams of three types: sequence (connection to services and message sending), deployment and component. The decision tree was validated by mobile development experts resulting in a maximum reduction of up to 30 days of technology selection research. The effectiveness of the tree as a tool is 60%, its usefulness 80% and its ease of comprehension 90%, according to the results obtained from the experts. / Revisión por pares

Nowadays Android operating system based mobile phones and tablets are widely used and had millions of users around the world. The popularity of this operating system is due to its multi-tasking, ease of access and diverse device options. “Java Programming Speech Recognition Application” is an Android application used for handicapped individuals who are not able or have difficultation to type on a keyboard. This application allows the user to write a compute program (in Java Language) by dictating the words and without using a keyboard. The user needs to speak out the commands and symbols required for his/her program. The program has been designed to pick up the Java constant keywords (such as ‘boolean’, ‘break’, ‘if’ and ‘else’), similar to the word received by the speech recognizer system in the application. The “Java Programming Speech Recognition Application” contains external plug-ins such as programming editor and a speech recognizer to record and write the program. These plug-ins come in the form of libraries and pre-coded folders which have to be attached to the main program by the developer.

<p>Ova disertacija se bavi istraživanjem u oblasti integracije servisa digitalne televizije u moderne uređaje potrošačke elektronike. Cilj teze je da razvije pristup za sistemsko proširenje Android operativnog sistema servisima digitalne televizije, i da predloži rešenje koje omogućuje rad u realnom vremenu. Kvalitet rešenja se ocenjuje odgovarajućim metrikama preko ocene kvaliteta implementirane Java objektno orijentisane sprege za TV servise. Osnovni doprinos teze se ogleda u definisanju jedinstvene programske sprege servisa digitalne televizije na platformama koje prate paradigmu virtuelne mašine. Predloženo rešenje omogućuje razvoj aplikacija optimizovanih za izvršavanje na TV uređajima i dalje sprezanje podataka TV servisa sa ostatkom Android ekosistema.</p> / <p>This PhD dissertation addresses the problem of integration of the digital TV services inside modern consumer electronic devices. The main focus of the dissertation is a development of systematic approach for extension of Android operating system with support for digital television. Combined with this, the dissertation describes solution in form of hardware platform with accompanying software that closely follows this approach and achieves real-time performance. Quality of proposed solution is benchmarked using metrics for measuring quality of object-oriented program code. The main contribution of the dissertation is unification of system software API for digital television on Android-based platforms. Proposed solution allows development of TV-centric software capable of real-time performance, and further native integration of data coming from DVB broadcast into Android ecosystem.</p>

Baigiamajame magistro darbe yra apžvelgti metodai, naudojami veidų atpažinimui bei išanalizuotas jų veikimas. Apžvelgus veidų atpažinimo metodus buvo pasirinkti trys algoritmai (tikrinių veidų, Fišerio veidų ir 2D–DCT+SOM), kurie išsamiai išanalizuoti ir įgyvendinti MATLAB aplinkoje bei ištirti įvairus jų parametrai. Pagal gautus rezultatus buvo išrinktas optimalus algoritmas, tinkantis įgyvendinimui Android operacinėje sistemoje ir ten įgyvendintas. Baigiamajame darbe taip pat buvo apžvelgtos ir išanalizuotos problemos, su kuriomis susiduriama perkeliant algoritmą į Android operacinę sistemą, pateikti siūlymai algoritmo patobulinimui bei išvados. Visi užsibrėžti tikslai buvo pasiekti, o uždaviniai – išspręsti. Veido atpažinimo algoritmų tyrimas ir įgyvendinimas operacinėje Android sistemoje. Magistro baigiamasis darbas informatikos inžinerijos laipsniui. Vilniaus Gedimino technikos universitetas. Vilnius, 2012, 187 p., 49 iliustr., 6 lent., 74 bibl., 6 priedai. / The main goal of Master degree thesis is to review face recognition algorithms and analyze their performance. After this survey three face recognition algorithms (eigenfaces, fisherfaces and 2D–DCT+SOM) have been chosen for detailed analysis and investigation of their various parameters in MATLAB environment. According to the results obtained during this research only one algorithm, which is optimal for implementation in Android operating system, has been implemented on the mobile platform. This Master degree thesis also includes problems and suggestions regarding eigenface’s algorithm implementation in Android operating system, proposals for algorithm improvement and detailed conclusions. All the objectives have been achieved and all problems – solved. Analysis of face recognition algorithms and implementation in Android operating system. Master Thesis for Informatics Engineering degree. Vilnius Gediminas Technical University. Vilnius, 2012, 187 p., 49 figures, 6 tables, 74 references, 6 appendices.