tuProlog su piattaforma Android: reingegnerizzazione in ottica Modern UI e fruibilità "as a service"

Questa tesi si occupa principalmente della revisione grafica in ottica Modern UI dell'app tuProlog Android, nella prospettiva di renderlo in futuro disponibile anche in modalità as-a-service. Dopo una attenta analisi preliminare dell'architettura di tuProlog in generale e in particolare della struttura dell'app tuProlog preesistente e del relativo progetto in ambiente Eclipse, ci si è focalizzati sulla riprogettazione dell'app, dall'analisi dei requisiti - ivi incluso il nuovo strumento di sviluppo da utilizzare, Android Studio - alla successiva analisi e progettazione della nuova soluzione, seguita da implementazione e collaudo.

Home Manager Application su Android ART: progetto e realizzazione in ottica modern UI

Questa tesi si occupa della realizzazione, in ottica Modern UI, di una nuova interfaccia per l'applicazione Android del sistema domotico Home Manager. Dopo una prima fase di analisi preliminare, si affronta la progettazione dell'app, dall'analisi dei requisiti - ivi incluso il nuovo strumento di sviluppo da utilizzare, Android Studio - alla successiva analisi e progettazione della nuova soluzione, seguita da implementazione e collaudo.

State-of-the-Art Multihoming Protocols and Support for Android

Il traguardo più importante per la connettività wireless del futuro sarà sfruttare appieno le potenzialità offerte da tutte le interfacce di rete dei dispositivi mobili. Per questo motivo con ogni probabilità il multihoming sarà un requisito obbligatorio per quelle applicazioni che puntano a fornire la migliore esperienza utente nel loro utilizzo. Sinteticamente è possibile definire il multihoming come quel processo complesso per cui un end-host o un end-site ha molteplici punti di aggancio alla rete. Nella pratica, tuttavia, il multihoming si è rivelato difficile da implementare e ancor di più da ottimizzare. Ad oggi infatti, il multihoming è lontano dall’essere considerato una feature standard nel network deployment nonostante anni di ricerche e di sviluppo nel settore, poiché il relativo supporto da parte dei protocolli è quasi sempre del tutto inadeguato. Naturalmente anche per Android in quanto piattaforma mobile più usata al mondo, è di fondamentale importanza supportare il multihoming per ampliare lo spettro delle funzionalità offerte ai propri utenti. Dunque alla luce di ciò, in questa tesi espongo lo stato dell’arte del supporto al multihoming in Android mettendo a confronto diversi protocolli di rete e testando la soluzione che sembra essere in assoluto la più promettente: LISP. Esaminato lo stato dell’arte dei protocolli con supporto al multihoming e l’architettura software di LISPmob per Android, l’obiettivo operativo principale di questa ricerca è duplice: a) testare il roaming seamless tra le varie interfacce di rete di un dispositivo Android, il che è appunto uno degli obiettivi del multihoming, attraverso LISPmob; e b) effettuare un ampio numero di test al fine di ottenere attraverso dati sperimentali alcuni importanti parametri relativi alle performance di LISP per capire quanto è realistica la possibilità da parte dell’utente finale di usarlo come efficace soluzione multihoming.

Relation entre une ischémie cardiaque transmurale ou partielle (sous-endocardique) et les changements ECG chez le porc : implication des substances vasoactives

Thèse numérisée par la Direction des bibliothèques de l'Université de Montréal.

Relation entre une ischémie cardiaque transmurale ou partielle (sous-endocardique) et les changements ECG chez le porc : implication des substances vasoactives

Thèse numérisée par la Direction des bibliothèques de l'Université de Montréal.

Computational Methods for Identifying Hypertrophic Cardiomyopathy using 12-lead ECG

Hypertrophic cardiomyopathy (HCM) is a cardiovascular disease where the heart muscle is partially thickened and blood flow is - potentially fatally - obstructed. It is one of the leading causes of sudden cardiac death in young people. Electrocardiography (ECG) and Echocardiography (Echo) are the standard tests for identifying HCM and other cardiac abnormalities. The American Heart Association has recommended using a pre-participation questionnaire for young athletes instead of ECG or Echo tests due to considerations of cost and time involved in interpreting the results of these tests by an expert cardiologist. Initially we set out to develop a classifier for automated prediction of young athletes’ heart conditions based on the answers to the questionnaire. Classification results and further in-depth analysis using computational and statistical methods indicated significant shortcomings of the questionnaire in predicting cardiac abnormalities. Automated methods for analyzing ECG signals can help reduce cost and save time in the pre-participation screening process by detecting HCM and other cardiac abnormalities. Therefore, the main goal of this dissertation work is to identify HCM through computational analysis of 12-lead ECG. ECG signals recorded on one or two leads have been analyzed in the past for classifying individual heartbeats into different types of arrhythmia as annotated primarily in the MIT-BIH database. In contrast, we classify complete sequences of 12-lead ECGs to assign patients into two groups: HCM vs. non-HCM. The challenges and issues we address include missing ECG waves in one or more leads and the dimensionality of a large feature-set. We address these by proposing imputation and feature-selection methods. We develop heartbeat-classifiers by employing Random Forests and Support Vector Machines, and propose a method to classify full 12-lead ECGs based on the proportion of heartbeats classified as HCM. The results from our experiments show that the classifiers developed using our methods perform well in identifying HCM. Thus the two contributions of this thesis are the utilization of computational and statistical methods for discovering shortcomings in a current screening procedure and the development of methods to identify HCM through computational analysis of 12-lead ECG signals.

Two-Path All-pass Based Half-Band Infinite Impulse Response Decimation Filters and the Effects of Their Non-Linear Phase Response on ECG Signal Acquisition

This paper is based on the novel use of a very high fidelity decimation filter chain for Electrocardiogram (ECG) signal acquisition and data conversion. The multiplier-free and multi-stage structure of the proposed filters lower the power dissipation while minimizing the circuit area which are crucial design constraints to the wireless noninvasive wearable health monitoring products due to the scarce operational resources in their electronic implementation. The decimation ratio of the presented filter is 128, working in tandem with a 1-bit 3rd order Sigma Delta (ΣΔ) modulator which achieves 0.04 dB passband ripples and -74 dB stopband attenuation. The work reported here investigates the non-linear phase effects of the proposed decimation filters on the ECG signal by carrying out a comparative study after phase correction. It concludes that the enhanced phase linearity is not crucial for ECG acquisition and data conversion applications since the signal distortion of the acquired signal, due to phase non-linearity, is insignificant for both original and phase compensated filters. To the best of the authors’ knowledge, being free of signal distortion is essential as this might lead to misdiagnosis as stated in the state of the art. This article demonstrates that with their minimal power consumption and minimal signal distortion features, the proposed decimation filters can effectively be employed in biosignal data processing units.

Towards automated Android app collusion detection

Android OS supports multiple communication methods between apps. This opens the possibility to carry out threats in a collaborative fashion, c.f. the Soundcomber example from 2011. In this paper we provide a concise definition of collusion and report on a number of automated detection approaches, developed in co-operation with Intel Security.

N-opcode analysis for android malware classification and categorization

Malware detection is a growing problem particularly on the Android mobile platform due to its increasing popularity and accessibility to numerous third party app markets. This has also been made worse by the increasingly sophisticated detection avoidance techniques employed by emerging malware families. This calls for more effective techniques for detection and classification of Android malware. Hence, in this paper we present an n-opcode analysis based approach that utilizes machine learning to classify and categorize Android malware. This approach enables automated feature discovery that eliminates the need for applying expert or domain knowledge to define the needed features. Our experiments on 2520 samples that were performed using up to 10-gram opcode features showed that an f-measure of 98% is achievable using this approach.

Dynalog: an automated dynamic analysis framework for characterizing android applications

Android is becoming ubiquitous and currently has the largest share of the mobile OS market with billions of application downloads from the official app market. It has also become the platform most targeted by mobile malware that are becoming more sophisticated to evade state-of-the-art detection approaches. Many Android malware families employ obfuscation techniques in order to avoid detection and this may defeat static analysis based approaches. Dynamic analysis on the other hand may be used to overcome this limitation. Hence in this paper we propose DynaLog, a dynamic analysis based framework for characterizing Android applications. The framework provides the capability to analyse the behaviour of applications based on an extensive number of dynamic features. It provides an automated platform for mass analysis and characterization of apps that is useful for quickly identifying and isolating malicious applications. The DynaLog framework leverages existing open source tools to extract and log high level behaviours, API calls, and critical events that can be used to explore the characteristics of an application, thus providing an extensible dynamic analysis platform for detecting Android malware. DynaLog is evaluated using real malware samples and clean applications demonstrating its capabilities for effective analysis and detection of malicious applications.

AR-park för Android : Augmented Reality park i Sundsvall

Målet med detta projekt är att ta fram en applikationsprototyp för Androidenheter som ska locka användare av applikationen till och tillbaka till broparken i Skönsberg med hjälp av augmented-reality. Applikationen ska känna av om användaren befinner sig inom eller utanför parkens område och visa olika bilder/modeller på specifika GPS-koordinater i det digitala lagret beroende på användarens positionering. Arbetet har genomförts i samarbete med Dohi på uppdrag av Sundsvalls kommun där regelbundna möten hafts med uppdragsgivaren. Utvecklingen av applikationen sker i PhoneGap med Wikitude-plugin. Projektet har resulterat i en applikationsprototyp som använder ActionRanges, som är en typ av GeoFence, för att presentera olika bilder hämtade från en egen server i det digitala lagret beroende på användarens position. Användarna har inom parkens område möjlighet att själv påverka de bilder som visas i det digitala lagret genom att i applikationen ta en bild som laddas upp till servern där bilderna lagras och där bilden som tagits även visar det digitala lagret.

JChord : An Android application helping people learn guitar chords

Nowadays, a lot of interesting and useful and imaginative applications are springing to Android software market. And for guitar fans, some related apps bring great connivence to them, like a guitar tuner can save people from carrying a entity tuner all the time, some apps can simulate a real guitar, and some apps provide some simple lessons allowing people to learn some basic things. But these apps which can teach people, they can't really “monitor ” people, that is, they just give some instructions and hope people would follow them. So my project is to design an app which can detect if users are playing wrong and right real-timely. Guitar chords are always the first for new guitar beginners to learn, and a chord is a set of notes combined together in a regulated way ( get from the music theory having millions of developing ), and 'pitch' is the term for determining if the note different from other notes or noise, so the problem here is to manage the multi-pitch analysis in real time. And it's necessary to know some basics of digital signal processing ( DSP ) because digital signals are always more convenient for computers to analyze compared to analog signals. Then I found an audio processing Java library – TarsosDSP, and try to apply it to my Android project.

Desenvolvimento de um dispensador automático de medicamentos e controlo através de uma plataforma móvel Android

O incumprimento na ingestão da medicação é um dos principais fatores para o insucesso no tratamento de diversas doenças e uma das principais dificuldades para controlar enfermidades crónicas [1], cardiovasculares [1, 3, 4] e psiquiátricas [4] que necessitam de uma ingestão correta e constante dos medicamentos. Estas tomas irregulares acabam por provocar desperdícios e gastos adicionais em tratamentos complementares e mais exames para análise do atual estado da doença [5]. De forma a prevenir falhas de adesão à terapêutica, foram desenvolvidos diversos equipamentos que ajudam os pacientes a gerir a sua medicação diária. No entanto estes dispositivos apresentam ainda algumas limitações, nomeadamente, ao permitirem apenas um utilizador e necessitarem da preparação prévia das tomas. Ao longo deste projeto foi desenvolvido um sistema de dispensa automática de medicamentos, assim como a plataforma de controlo através de um dispositivo móvel Android. As principais vantagens deste equipamento são o seu funcionamento em modo multiutilizador e a combinação automática de medicamentos para cumprir as tomas prescritas pelo médico. O dispositivo desenvolvido e a sua utilização foi validado durante 5 dias no Centro Clínico-Académico do Hospital de Braga recorrendo a utentes de várias faixas etárias, bem como em casa de 2 participantes num caso de estudo. O sistema de dispensa automático de medicamentos foi testado em ambos os perfis de utilizadores: utente e cuidador. Foram criados registos de novos utentes e efetuadas várias dispensas de medicamentos de forma a testar a fiabilidade do dispositivo para utilização em contexto real. Os resultados destes testes permitiram comprovar a funcionalidade e fiabilidade do sistema desenvolvido.