iOS Technologies & Frameworks

Apple’s mobile platform — iOS — currently generates the largest amount of revenue out of all mobile app stores. The majority of iDevices run the latest major iOS version (iOS 10) due to Apple users’ tendency to update their devices. Consequently, iOS developers are pressured into keeping their apps up to date. Advantages to updating apps consist of new features and adapting apps to the platform’s hardware and software evolution. However, this does not always happen. There are apps, some popular (with many users), which either receive slow updates, or not at all. The main consequence of developers not updating to the latest tendencies (i.e. user interface or API changes) is the degradation of their apps’ user experience. This subpar user experience leads to a decrease in the number of installs (and sales) and a search for alternatives that have been updated to support the latest firmware iteration fully. We identified a common pattern amongst ten apps which have subpar reviews on the App Store: excessive battery consumption and lack of user onboarding were just a few of the ssues. Above all, almost all those apps belong to the top 1% of apps (which generate 94% of the App Store’s revenue), so the lack of focus on the user experience is unfortunate considering their massive user bases. We listed the available resources for those wanting to develop or improve iOS apps. Given these requisites, we studied the possibility of developing a mobile app that adopted good engineering practices and, above all, focused on delivering an excellent user experience in a given timeframe of six months. The app’s idea consisted of a wish list management app called Snapwish that allows the user to take photos of objects they want, create wish lists, and share them with family and friends. The app allows for offline usage, with data syncing automatically (in real-time) without user intervention when the app’s Internet connection is present. We tested Snapwish thoroughly to measure the quality of its implementation. Profiling helped assert that core metrics like CPU and memory usage, network data requests and energy consumption were within acceptable values while unit and user interface tests served to validate our code functionally. Furthermore, our team of five beta testers provided valuable feedback and suggestions. Ultimately, the six-month timeframe proved to be insufficient in regards to a release on the App Store, as Snapwish remains in the latter beta stages at the time of writing. This delay is mostly attributed to a lengthy testing process. Thus, we plan on releasing it in the first trimester of 2017.Hoje em dia, a plataforma móvel da Apple — iOS — é a que tem maior revenue em aplicações móveis. A maior parte dos dispositivos móveis iOS corre a versão mais atual (iOS 10), devido à tendência dos seus utilizadores em atualizar o sistema operativo com frequência. Consequentemente, os desenvolvedores da plataforma são pressionados para manterem as suas apps atualizadas. Algumas das vantagens das atualizações consiste em adicionar novas funcionalidades e adaptar as apps à evolução do hardware e do software da plataforma. Contudo, isto nem sempre e verifica. Existem muitas apps, algumas “populares” (com muitas instalações) cuja atualização demora ou não acontece. A principal consequência da não atualização das apps às tendências atuais, quer em termos de interação, quer em termos de mecanismos de proteção de dados, consumo de bateria e outros, é a degradação da experiência de quem as utiliza, consequentemente, a diminuição do número de instalações (e vendas) e a crescente procura de alternativas que tenham estes princípios em conta. Foi identificado um padrão comum em dez aplicações cujas classificações na App Store são medíocres: um consumo exagerado de bateria e falta de user onboarding foram apenas alguns dos problemas. Acima de tudo, quase todas pertencem ao 1% de aplicações que geram 94% das receitas da App Store. A falta de foco na experiência do utilizador é infeliz considerando as enormes bases de utilizadores dessas aplicações. Foram listados os recursos disponíveis para quem pretende desenvolver ou melhorar uma aplicação iOS. Dadas essas premissas, foi estudada a possibilidade de desenvolver uma aplicação móvel que adote boas práticas de engenharia e, acima de tudo, foque na experiência do utilizador, num período de seis meses. A ideia para a aplicação consistiu num gestor de listas de desejos designada Snapwish que permite tirar fotos de objetos que o utilizador deseja, criar listas, e partilhá-las com amigos e familiares. Além disso, a app permite o uso offline e os dados são sincronizados em tempo real sem intervenção do utilizador quando a app dispõe de uma conexão à Internet. A nossa aplicação foi testada extensivamente para medir o nível de qualidade da sua implementação. O profiling ajudou em constatar que métricas fundamentais como o consumo de CPU e memória, pedidos de dados de rede e de consumo de energia (bateria) estavam dentro dos parâmetros aceitáveis. Além disso, uma equipa de cinco beta-testers contribuiu com comentários e sugestões de grande valor. Em última análise, o prazo de seis meses revelou-se insuficiente em relação ao lançamento da app na App Store. O Snapwish permanece numa fase beta avançada (no momento da escrita desta tese). Este atraso é principalmente atribuído a um extenso processo de testes. Assim, pretendemos lançar a aplicação no primeiro trimestre de 2017

Building Community and Collaboration Applications for MMOGs

Supporting collaborative activities among the online players are one of the major challenges in the area of Massively Multiplayer Online Games (MMOG), since they increase the richness of gaming experience and create more engaged communities. To this direction, our study has focused on the provision of services supporting and enhancing the players' in-game community and collaboration activities. We have designed and implemented innovative tools exploiting a game adaptation technology, namely, the In-game Graphical Insertion Technology (IGIT), which permits the addition of web-based applications without any need from the game developers to modify the game at all, nor from the game players to change their game installation. The developed tools follow a design adapted to the MMOG players' needs and are based on the latest advances on Web 2.0 technology. Their provision is performed through the core element of our system, which is the so-called Community Network Game (CNG) Server. One of the important features provided by the implemented system's underlying framework is the utilization of enhanced Peer-to-Peer (P2P) technology for the distribution of user-generated live video streams. In this paper, we focus on the architecture of the CNG Server as well as on the design and implementation of the online community and collaboration tools

Digital Forensic Tools & Cloud-Based Machine Learning for Analyzing Crime Data

Digital forensics is a branch of forensic science in which we can recreate past events using forensic tools for legal measure. Also, the increase in the availability of mobile devices has led to their use in criminal activities. Moreover, the rate at which data is being generated has been on the increase which has led to big data problems. With cloud computing, data can now be stored, processed and analyzed as they are generated. This thesis documents consists of three studies related to data analysis. The first study involves analyzing data from an android smartphone while making a comparison between two forensic tools; Paraben E3: DS and Autopsy. At the end of the study, it was concluded that most of the activities performed on a rooted android device can be found in its internal memory. In the second study, the Snapchat application was analyzed on a rooted Android device to see how well it handles privacy issues. The result of the study shows that some of the predefined activities performed on the Snapchat application as well as user information can be retrieved using Paraben E3: DS forensic tool. The third study, machine learning services on Microsoft Azure and IBM Watson were used in performing predictive analysis to uncover their performance. At the end of the experiments, the Azure machine learning studio was seen to be more user friendly and builds models faster compared to the SSPS Modeler in the IBM Watson Studio. This research is important as data needs to be analyzed in order to generate insights that can aid organizations or police departments in making the best decisions when analyzing crime data

Exploratory Study of Visual Enhancement to Display Smart Apps on Android Phones for Selasar Imaji Library

The attractive appearance of the system applications on the Android phone is quite important. There is an initial premise that the "Imaji Library" application that the Selasar Imaji Library owns is less attractive to users because it is not attractive. This study aims to explore an attractive appearance based on studies that are filtered to application users. Through Research and Development (R&D) activities, by 1) capturing questionnaire results from users to find out what is less attractive from the application display; 2) study of the search for the preferred visual appearance; 3) designing applications; and 4) application testing to librarians. The results of the exploration activities are in the form of (1) a new prototype design of the "Imaji Library" application display, (2) the development of application features in terms of procurement, processing, tracking, and member and circulation management activities. The implication of this research is helpful for librarians' convenience in managing libraries

SERVICE QUALITY, SATISFACTION, CONTINUOUS USAGE INTENTION, AND PURCHASE INTENTION TOWARD FREEMIUM APPLICATIONS: THE MODERATING EFFECT OF PERCEIVED VALUE

This study aimed to analyze factors that could influence continuous usage intention on freemium applications and purchase intention of premium services among students. Non-probability purposive sampling was used to determine the respondent. The criteria for the sample for this study were students who used freemium applications. Data were analyzed using Partial Least Square. The results confirmed that only reliability and responsiveness positively impacted customer satisfaction among the service quality dimensions, while assurance and empathy showed no effect. Only assurance and responsiveness were found to affect continuous usage intention positively, while empathy and reliability were found to have no effect. There was no evidence of the effect of the dimensions of service quality on purchase intention. Perceived value failed to moderate the effect of service quality on customer satisfaction. While there was a significant positive impact of customer satisfaction towards continuous usage intention, no effect has been found towards purchase intention. Continuous usage intention was confirmed to have a positive impact on purchase intention.JEL: O32, M31, L11ABSTRAKTujuan dari penelitian ini adalah untuk menganalisis faktor-faktor yang dapat mempengaruhi continuous usage intention dan purchase intention pada aplikasi yang memiliki layanan premium pada mahasiswa. Non-probability purposive sampling digunakan untuk menentukan jenis responden. Kriteria sampel pada penelitian ini adalah mahasiswa yang menggunakan aplikasi freemium. Data dianalisa menggunakan Partial Least Square. Hasil menunjukkan bahwa diantara dimensi service quality, hanya reliability dan responsiveness yang berpengaruh positif terhadap customer satisfaction sedangkan assurance dan empathy tidak berpengaruh. Hanya assurance dan responsiveness yang ditemukan berpengaruh positif terhadap continuous usage intention sedangkan empathy dan reliability ditemukan tidak berpengaruh. Seluruh dimensi service quality ditemukan tidak berpengaruh terhadap purchase intention. Perceived value tidak mampu memoderasi pengaruh service quality terhadap customer satisfaction. Customer satisfaction ditemukan berpengaruh positif terhadap continuous usage intention tetapi tidak terhadap purchase intention. Continuous usage intention ditemukan berpengaruh positif terhadap purchase intention.Kata Kunci: kualitas layanan, persepsi nilai, kepuasan, niata

Design Knowledge for Virtual Learning Companions from a Value-centered Perspective

The increasing popularity of conversational agents such as ChatGPT has sparked interest in their potential use in educational contexts but undermines the role of companionship in learning with these tools. Our study targets the design of virtual learning companions (VLCs), focusing on bonding relationships for collaborative learning while facilitating students’ time management and motivation. We draw upon design science research (DSR) to derive prescriptive design knowledge for VLCs as the core of our contribution. Through three DSR cycles, we conducted interviews with working students and experts, held interdisciplinary workshops with the target group, designed and evaluated two conceptual prototypes, and fully coded a VLC instantiation, which we tested with students in class. Our approach has yielded 9 design principles, 28 meta-requirements, and 33 design features centered around the value-in-interaction. These encompass Human-likeness and Dialogue Management, Proactive and Reactive Behavior, and Relationship Building on the Relationship Layer (DP1,3,4), Adaptation (DP2) on the Matching Layer, as well as Provision of Supportive Content, Fostering Learning Competencies, Motivational Environment, and Ethical Responsibility (DP5-8) on the Service Layer

FreeLib: A Self-Sustainable Peer-to-Peer Digital Library Framework for Evolving Communities

The need for efficient solutions to the problem of disseminating and sharing of data is growing. Digital libraries provide an efficient solution for disseminating and sharing large volumes of data to diverse sets of users. They enable the use of structured and well defined metadata to provide quality search services. Most of the digital libraries built so far follow a centralized model. The centralized model is an efficient model; however, it has some inherent problems. It is not suitable when content contribution is highly distributed over a very large number of participants. It also requires an organizational support to provide resources (hardware, software, and network bandwidth) and to manage processes for collecting, ingesting, curating, and maintaining the content. In this research, we develop an alternative digital library framework based on peer-to-peer. The framework utilizes resources contributed by participating nodes to achieve self-sustainability. A second key contribution of this research is a significant enhancement of search performance by utilizing the novel concept of community evolution. As demonstrated in this thesis, bringing users sharing similar interest together in a community significantly enhances the search performance. Evolving users into communities is based on a simple analysis of user access patterns in a completely distributed manner. This community evolution process is completely transparent to the user. In our framework, community membership of each node is continuously evolving. This allows users to move between communities as their interest shifts between topics, thus enhancing search performance for users all the time even when their interest changes. It also gives our framework great flexibility as it allows communities to dissolve and new communities to form and evolve over time to reflect the latest user interests. In addition to self-sustainability and performance enhancements, our framework has the potential of building extremely large collections although every node is only maintaining a small collection of digital objects