La usabilidad y las metodologías ágiles son dos enfoques orientados al usuario que contribuyen a mejorar el producto desarrollado, pero existen ciertas tensiones para integrarlos como parte de un mismo proceso. En esta tesis, se observa, a través de un caso de estudio, la forma de integrar las prácticas de usabilidad dentro de la metodología ágil más usada, Scrum, en el contexto del desarrollo de una aplicación para medir el ruido. Los resultados del estudio indican que prácticas de usabilidad como el prototipado, encuestas y evaluaciones heurísticas se pueden integrar como tareas dentro de las iteraciones de Scrum mientras que las pruebas de usabilidad deben ser un proceso separado posterior a la ejecución de cada iteración. Asimismo, se observa que la integración de técnicas de usabilidad a lo largo de las iteraciones contribuye con la reducción de la gravedad de los problemas de usabilidad. / Tesis

Alcohol abuse is the third leading lifestyle-related cause of death for individuals in the United States, causing 88,000 deaths each year in the United States from 2006-2010. Existing smartphone applications allow users to manually record their alcohol consumption or take cognitive tests to estimate intoxication levels; however, no smartphone application passively determines one's level of intoxication. After gathering smartphone sensor data from 34 "intoxicated" subjects, we generated time and frequency domain features such as sway area (gyroscope) and cadence (accelerometer), which were then classified using a supervised machine learning framework. Other novel contributions explored include feature normalization to account for differences in walking styles and automatic outlier elimination to reduce the effect of accidental falls by identifying and removing the top and bottom of a chosen percentage of the data. Various machine learning classifier types such as Random Forest and Bayes Net were compared, and J48 classifier was the most accurate, classifying user gait patterns into BAC ranges of [0.00-0.08), [0.08-0.15), [0.15-0.25), [0.25+) with an accuracy of 89.45%. This best performing classifier was used to build an intelligent smartphone app that will detect the user's intoxication level in real time.

Master of Science / Department of Computer Science / Mitchell L. Neilsen / Smart glasses, like smart phones, have separate operating systems, and can execute many different kinds of software and games. Smart glasses can be used to add a schedule, map navigation, interact with friends, take photos and videos, and make video calls with friends through voice control. They can support wireless network access through a mobile communication network. Bluetooth is a radio technology that supports short-range communication between of the devices. It can exchange information between devices including mobile phones, wireless headsets, laptops, etc. Bluetooth technology can effectively simplify the communication between mobile devices. This thesis focuses on smart glasses applications for high-throughput phenotyping which requires a data monitor, data synchronization, Bluetooth service, and voice control between devices. On the Android side, the application, which is extended, is called Field Book. The new software called Field Book AR, includes a data monitor module and a Bluetooth server module to achieve data exchange with smart glasses. On the smart glasses side, the application is called DataReceiver. It receives voice commands from users and controls the actions of Field Book AR. Also, when Field Book detects data changing, it accepts new data and shows changes to the users.

Secured long-distance communication has always been an important topic for people handling sensitive information. Now with the arrival of ``intelligent`` mobile phones eavesdropping and information gathering is as easy as never. Luckily smartphones present not only problems in terms of security but also an opportunity to protect ones privacy. This thesis attempts to construct a generic software architecture of a communicator which could be capable of transferring voice, video and other various forms of binary data in a secure way. It will analyse and use different communication channels to reach a maximum level of data authenticity, integrity and confidentiality in an environment where a central security element needs to be avoided. The resulting architecture will be tested on a Voice-over-IP (VoIP) application prototype for the mobile Google Android platform to show whether the approach is practically usable on currently available phones.

Tese de mestrado. Multimédia. Faculdade de Engenharia. Universidade do Porto. 2012

The objective of this masters project is to develop a working application for Android devices. This is an application intended to be used by CSUSB. It has its own database, which has information about most of the facilities on campus. There are many GPS applications on the market, however I chose to design and implement WiN GPS, short for Walking GPS, because it will allow the possibility of a personalized GPS for the school and for users should they choose to use it. In order to develop Win GPS it was necessary to research the available tools and to become familiar with the ones that were selected. These tools such as map application providers, i.e. Google-maps, integrated development environments, database managers, software development kits, and mobile device emulators were analysed and compared. Once the tools were selected. It was necessary to study, to become familiar with and to learn how to use them. Finally an application is developed and its main functions/code will be explained. This masters project will allow potentially Android developers to evaluate possible barriers, such as price and limitations of map applications providers, so they can make an informed decision.

Indoor Positioning System (IPS) focuses on locating objects inside Buildings. Till date, GPS has helped us obtain accurate locations outdoors. These locations have helped us in many ways like navigating to a destination point, tracking people etc. Indoor Positioning System aims at navigating and tracking objects inside buildings. [1] IndoorAtlas is a technology that works on the theory of Indoor Positioning System. Book-Hunt is an Android mobile application which majorly makes use of IndoorAtlas therefore making use of the technique of indoor tracking. This Android mobile application is designed for Libraries. It is designed specifically for John M. Pfau Library, CSUSB, to help the students locate a book in the Library. When a student selects a book, a marker is pointed towards the book and also on the student’s current location. This application aims at saving time for student searching a particular book in the Library. Book- Hunt makes use of three tools Android Studio, Google Maps and IndoorAtlas

With advances in mobile phone hardware, the demand for mobile applica- tions has risen drastically. This has resulted in mobile phones becoming a pop- ular new medium for application development. However, the body of knowledge for contextual examples and tutorials leaves much to be desired. As of January 2010, California Polytechnic State University has offered a mobile development class that teaches students how to write applications for phones running Google’s Android platform. This class aims at taking advantage of students’ current in- terest in mobile applications to teach them about difficult computer science topics. As a corollary, the class hopes to foster and encourage a sense of inde- pendence and entrepreneurship through having students design, implement, and publish their own applications to the Android Application Marketplace. The main contribution of this thesis project comes in the form of a series of detailed educational laboratory exercises and a system for grading student submissions in an automated fashion. These labs are designed to supplement the Android documentation by providing contextual examples, activities, and tutorials. It is therefore the goal of this thesis project to aid in transforming the class of mobile development students into a group of successful, practicing, mobile developers.

Mobile and web application security, particularly concerning the area of data privacy, has received much attention from the public in recent years. Most applications are installed without disclosing full information to users and clearly stating what they have access to. This often raises concerns when users become aware of unnecessary information being collected or stored. Unfortunately, most users have little to no technical knowledge in regard to what permissions should be granted and can only rely on their intuition and past experiences to make relatively uninformed decisions. DroidNet, a crowdsource based Android recommendation tool and framework, is a proposed avenue for the technically incapable. DroidNet alleviates privacy concerns and presents users with permission recommendations of high confidence based on the decisions from expert users on the network who are using the same applications. The framework combines an interactive user interface, used for data collection and presenting permission recommendations to users, with a transitional Bayesian inference model and multiple algorithms used for rating users based on their respective expertise levels. As a result, the recommendations that are provided to users are based on aggregated expert responses and their confidence levels. This work presents the completed DroidNet project in its entirety, including the implementation of the application, algorithms, and user interface itself. Additionally, this thesis presents and utilizes a unique collection of real-world data from actual Android users. The primary goal of this work is to evaluate the effectiveness and accuracy of DroidNet's recommendations and to show that regular mobile device users can benefit from crowdsourcing.

This dissertation presents a new approach to static analysis for security vetting of Android apps, and a general framework called Argus-SAF. Argus-SAF determines points-to information for all objects in an Android app component in a flow and context-sensitive (user-configurable) way and performs data-flow and data dependence analysis for the component. Argus-SAF also tracks inter-component communication activities. It can stitch the component-level information into the app- level information to perform intra-app or inter-app analysis. Moreover, Argus-SAF is NDK/JNI- aware and can efficiently track precise data-flow across language boundary. This dissertation shows that, (a) the aforementioned type of comprehensive app analysis is utterly feasible in terms of computing resources with modern hardware, (b) one can easily leverage the results from this general analysis to build various types of specialized security analyses – in many cases the amount of additional coding needed is around 100 lines of code, and (c) the result of those specialized analyses leveraging Argus-SAF is at least on par and often exceeds prior works designed for the specific problems, which this dissertation demonstrate by comparing Argus-SAF’s results with those of prior works whenever the tool can be obtained. Since Argus-SAF’s analysis directly handles intercomponent and inter-language control and data flows, it can be used to address security problems that result from interactions among multiple components from either the same or different apps and among java code and native code. Argus-SAF’s analysis is sound in that it can assure the absence of the specified security problems in an app with well-specified and reasonable assumptions on Android runtime system and its library.