With the widespread use and adoption of mobile platforms like Android a new software quality concern has emerged - energy consumption. However, developing energy-efficient software and applications requires knowledge and like-wise proper tooling to support mobile developers. To this aim, we present an approach to examine the energy evolution of software revisions based on their API interactions. The approach stems from the assumption that the utilization of an API has direct implications on the energy being consumed during runtime. Based on an empirical evaluation, we show initial results that API interactions serve as a flexible, lightweight, and effective way to compare software revisions regarding their energy evolution. Given our initial results we envision that in future using our approach mobile developers will be able to gain insights on the energy implications of changes in source code in the course of the software development life-cycle.

The development and diffusion of smartphones has paved the way for several trends, among them an alternative payment solution in the form of mobile payment. Mobile payment is part of the overarching concept of mobile transactions, and experiences varied acceptance and adoption. This paper analyzes drivers and factors determining consumers' acceptance and adoption of mobile payment. For this reason, we examine the contribution of the two basic approaches, i.e. the "technology acceptance model" and the "unified theory of acceptance and use of technology" in the context of mobile payment. Based on empirical evidence, we identified several factors, which were found to have impact on primary adoption; a compelling user experience turned out to be the main driver of long-term usage.

Background: Third-party software libraries often serve as fundamental building blocks for developing applications. However, depending on such libraries for development raises a new concern, energy consumption, which has become of increased interest for the software engineering community in recent years. Understanding the energy implications of software design choices is an ongoing research challenge, especially when working with mobile devices that are constrained by limited battery life. Aims: Our goal is to research approaches, which will support software developers to better comprehend the energy implications of software design choices on Android. For this study, we particularly focus on APIs from third-party libraries for which we research methods that will enable estimating the energy consumption without the need for specific measurement hardware and laborious measurements. Method: To achieve the stipulated goal we introduce System API Utilization Profiles (uAPI) which are based on the general assumption that the actual energy consumption of a library is directly tied to its utilization of the underlying System API. We provide a formal definition and implementation of the proposed uAPI profiles that are calculated based on dynamic call graphs obtained from a library under test. To further show the connection between our proposed uAPI profiles and energy consumption, we empirically examined their correlation using two experiments. The first one is dedicated to Android I/O operations, the second one examines uAPI profiles based on a popular open-source library for JSON document processing. Results: In our empirical evaluation, we collected 1052 individual call graphs which we used as an input to evaluate the our model and compare it with the actual energy consumption measured. For each call graph, we measured the energy consumption with special hardware and attributed the measurements to individual methods. Based on that data, we examined a strong linear correlation between the proposed uAPI profiles and the actual measured energy consumption. Conclusions: uApi profiles serve as a lightweight and feasible approach to characterize the energy characteristics of third-party libraries. Their computation does not involve any special hardware, and there are no alterations on the target mobile device required. For future work, we investigate possibilities to use the proposed uAPI profiles as a foundation for a regression model, which would allow us to predict the energy consumption development of a library over time.

The development and diffusion of smartphones has led to many new trends, among them a new payment solution in the form of mobile payment. This paper places its focus on factors influencing consumer adoption of mobile payment. The basis for this is often the technology acceptance model and unified theory of acceptance and use of technology. Several factors including perceived ease of use, perceived usefulness, performance expectancy and social influence were found to influence primary adoption while a compelling user experience, usability and enjoyment were found to be a main driver of long-term usage.

In knowledge organizations or a knowledge society learning processes are inherently social and distributed. To enable these processes knowledge artifacts need to be created, updated, and consumed decentralized. Social Micro-Learning is an example for an approach following that paradigm. By proposing a flexible service architecture, this paper addresses the diverse demands that Social Micro-Learners have throughout their learning process. It allows integrating information retrieval, recommender systems, workflow engines and spaced repetition algorithms through a single stream data model. Consequently, we can reuse user interface implementations and provide a consistent, recognizable view. Our evaluations show a good system usability, and stable results across different services. We conclude that our service design can serve as a blueprint for social e-learning systems.

With the advent of mobile application development a new software quality concern - energy consumption - was introduced. For mobile software developers knowledge about software and algorithm design choices and their implications on energy consumption is crucial. However, software developers either lack this knowledge or tools to support them in estimating the energy consumption of their applications and therefore are unable to reflect on their design choices. In this empirical study we examine the energy consumption of 12 sorting algorithms and the resulting energy impact when used with different data types. We propose a methodology to obtain energy readings and relate them to application execution traces. Our results show that the choice of data type together with algorithm design can have significant impact on the energy profile of an application.

This paper tackles the problem of constantly monitoring customer satisfaction. The goal is to reason about customer satisfaction automatically using data provided from a large software system customers are interacting with. The system under study is a mobile application which allows users to track their pets. The application and underlying system collect a large amount of data, including user interactions with the app and technical data related to the quality of the tracking process. The question is if those data can be efficiently exploited in order to determine customer satisfaction. Based on existing approaches to model customer satisfaction, we investigate relevant data sources with supposedly influence the satisfaction level of customers. We compare two different approaches, a hypothesis driven approach and a machine learning approach. The approaches are evaluated on an extracted dataset from a real world case study.

This paper reports on two design experiments conducted in a semi-public space: the first enabled collaborative writing in situ via mobile phones and the second provided additional ex-situ access through a web-based platform. Our analysis revealed that (i) in-situ engagement through mobile phones is a trigger that supports participation and (ii) ex-situ action via web-applications increases engagement in a collaborative writing process linked to a semi-public space. Hence, we propose a conceptual design for a hybrid Participatory Information Technology (PIT) that combines these two technologies. With the hybrid PIT we address one of the most common critiques in the context of today's semi-public leisure spaces -- namely that visitors lack support in gaining both a stronger connection to the place and a sense of ownership of related activities and their outcomes. Our conceptual design gives participants continuous access to the process of collaborative writing from locations of their preference (i.e., either collocated in a semi-public space or remote) and allows them to author a text both synchronously and asynchronously.

Social Bots are software robots implementing algorithms that autonomously produce content and interact with users of social networks or mimic the behavior of humans in multiple other forms of digital communication. If they act on behalf of a specific user of party in the communication, this user is sometimes called the "owner" of the bot. Social bots are typically designed to be, benevolent and even useful but some of them are built to manipulate and deceive social users. Since spring 2016 Microsoft provides the technology Microsoft Bot Framework. With this framework developers can create own social bot applications easily in Visual Studio with the language C#. The bot application can be connected to various social channels like Facebook, Twitter, Microsoft Groups or an Office 365 accounts.

When designing interactive web applications and services, understanding the situated nature of interaction and investigating technology appropriation experiences in the context of real-world use deserve special attention. In this paper, we report on experiences with technology appropriation of an e-Deliberation platform that we designed to support collaborative interpretation in an art gallery. Our qualitative study is based on interviews with 23 participants to explore a) visitors' practices when commenting on and interpreting art and b) how these practices are shaped by interaction with an e-Deliberation platform for collaborative writing that imposes strict regulations. An analysis of 12 hours of interview data yielded two particular appropriation practices related to the demand to satisfy additional visitors' communication needs, such as exchanging their ideas and thoughts face-to-face before writing an interpretation. Although the designers anticipated these specific needs, users also appropriated the e-Deliberation platform in unanticipated ways. These practices lead to a better understanding of the situated nature of ex-situ interaction when using interactive web applications to support remote collaboration in the art gallery context.

Current trends in graph analytics show a trend towards analysing networks of ever growing size and a strong interest of analysing chronological development in networks. This paper provides a brief introduction to possible processing paradigms for large-scale temporal graphs and a real-world implementation called DynamoGraph. The paper motivates the necessity of further research in this area by highlighting three use-case scenarios. It is elaborated how the click-behavior of users visiting the web can be used to better understand the structure of the actively used web, it shows how temporal graphs provide a model for social network analysis over online discourse, and it provides first insight in how temporal graph analytics can help us better understand social learning networks.

In February 2011, Watson (IBM super computer) managed to beat two past grand champions on the TV quiz show Jeopardy!. Watson was able to answer questions that require intelligence when done by humans. This marked the first machine to pass the Turing test and started a new era of computing called cognitive computing where computers (modeled after the human brain) learn and interact naturally with people to extend what either humans or machine could do on their own. Google, Amazon, Facebook, etc., using big data technologies, smart Machine Learning and AI algorithms were able to tap into our intensions by predicting what we click, buy, like, dislike, shop, surf, etc.,. This marked the era of smart Web or predictive intelligence where Turing test is reversed and machines now try to figure out who we are, our information needs, our behavioral patterns, the activities we are engaged in and our goals. Together with the torrents of data we leave behind us every time we communicate with the digital eco-system, a new era of human-machine cooperation is starting that gives us millions of potential insights into user experience, marketing, personal tastes, and human behavior. In this talk, we are going to illustrate through motivating cases and research directions the main characteristics of this era and how it can transform the way we interact with the Web to ultimately improve the quality of our lives and gain valuable insights into our affective, mental and physical states.

Every time, we search the Web, click a link, send/receive email/SMS, place/receive a phone call, like or follow a social network, etc., we are collectively (deliberately or incidentally) leaving torrents of data that is waiting to be processed and analyzed. Companies like Google, Facebook, Amazon among others are collecting this data to automatically capture our physical, social, behavioral, and infomational contexts. This context is used through big data technologies, smart Machine Learning and AI algorithms to engineer systems that are aware of our information needs, our behavioral patterns, the activities we are engaged in and our goals and intentions. Thus moving from systems that require us to manually search, sort, sift data to find meaning and make sense of the world around us to systems that observe our actions-in-context and deliver information to help us connect the dots and live a better life. In this talk, we are going to show how big data and contextual intelligence can be used to process and analyze the "digital exhaust" we leave behind us every time we interact with the Web or use a mobile device to design systems that automatically recognize our affective, mental and physical states and automatically respond to them in the most effective and "human" way possible.

Large-scale temporal graphs can serve as a model in many application scenarios. Recently, due to the popularity of online social networks and increased research interest in reality mining i.e. gathering and analyzing data about human behavior and interaction in the real world, temporal graphs gain traction in social network analysis and more specifically in the analysis of dynamic processes in social networks. However, current methods for social network analysis either require data to be processed offline, lack support for temporal graphs, or support datasets of limited size only. In this work we present a cloud-based distributed processing framework designed for large-scale temporal graphs. By using computing resources in the cloud this system is scaleable and already constructed for the massive datasets that occur in social network analysis.

This paper highlights how the domain of Smart Cities is often modeled by ontologies to create applications and services that are highly flexible, (re)configurable, and inter-operable. However, ontology repositories and their accompanying reasoning and rule languages face the disadvantage of bad runtime behavior, especially if the models grow large in size. We propose an architecture that uses tools and methods from the domain of Big Data processing in conjunction with an ontology repository and a rule engine to overcome potential performance bottlenecks that will occur in this scenario.

The Motorola RAZR was first developed in July 2003 and released to the market in 2004 exactly around the same time MoMM conference series was launched by Johannes Kepler University Linz. The introduction of the Motorola RAZR became the most iconic device to be the epitome of the smart phone Era. With its slim form factor and sleek appearance which drove a big demand around the world, selling over 100 million units, to become the second-best-selling mobile phone of all time. The same happened when Steve Jobs announced the release of the first iPhone in June, 2007. In less than four months after its release, sales of the iPhone surpassed the 2 million figure making it the bestselling mobile device in the world. There are almost 10 years between Motorola RAZR and the most recent sixth-generation iPhone 5 which was released on September 21, 2012. Tracing the way back from Motorola RAZR to iPhone5, we see technological advances in hardware and software. Phones become slimmer, lighter, are equipped with higher-resolution, wider screens, more powerful processors and offer support for NGN. But we also observe solutions to the problems that were facing the mobile ecosystem, from how people interact with their phones, to where they buy them, to what type of applications they install and are willing to pay money for, to the level of technology standards they can support on resource-constrained devices.

In the past, research and education have been the major tasks and duties of Universities for centuries. Research was considered to be what we call today basic research, i.e. the systematic attempts to gain new insights and findings using scientific methods, education was the dissemination of the knowledge gained from research to the students. Only recently, i.e. in the last decade, aspects of exploitation of knowledge and technology transfer both, into industry as well as into society, came into play. Universities were seen as the sources of knowledge generation, industry should take up those ideas and transform them into practice in innovation pipelines. Universities had to justify and orient their research on the grand challenges of our modern societies, leading to applied research on the one hand and marketing-like activities of the Universities on the other hand. Also education changed with an increasing number of students entering Universities and new ways of teaching and learning such as distance education or blended learning. Nowadays, Universities are expected to be a central entity in the so called knowledge triangle, which described the process of exchange and the interplay between education, knowledge and innovation.

In ubiquitous environments a vast amount of mobile human and software entities, each with limited resources and knowledge, needs to interact with each other to achieve common and/or individual goals within a specific context. Due to their autonomy, proactiveness, mobility, social capability, and the successful implementation of agent mediated applications and services over the Web, different scenarios have been proposed in literature for the use of agents in ubiquitous environments for a wide range of applications such as user interfaces, mobile computing, information retrieval and filtering, smart messaging, telecommunication and m-commerce. In this paper, we address the problem of energy efficiency in ubiquitous environments from customer satisfaction, customer awareness and energy savings points of view. We propose an agent-based information system in which agents act on behalf of the users, are situated within the appliances, sensors and actuators, or represent different stakeholders in the energy market. Different scenarios have been proposed as the basis for the proposed information system.

What we call the world wide web nowadays has its origins in a system designed to share and distribute information among scientists. It took less then a decade and "the web" evolved into an omnipresent medium for information sharing, communication and even collaboration and cooperation. A multitude of new standards, protocols, and services has been proposed, some of them became a success, others died even before they had the chance to lift up.

TV goes rapidly digital, and more and more content formats are entering the consumer market. Currently there exist many approaches towards the development of more social, more collaborative, and interactive TV formats and systems. Within the scope of this paper we present latest case studies and provide a simple categorization according narration character, content types, and interactivity types of program formats. We also present systems supporting social and collaborative functionalities. The paper rounds up with a discussion sections, where an evaluation of the discussed projects can be found.

What we call the world wide web nowadays has its origins in a system designed to share and distribute information among scientists. It took less then a decade and "the web" evolved into an omnipresent medium for information sharing, communication and even collaboration and cooperation. A multitude of new standards, protocols, and services has been proposed, some of them became a success, others died even before they had the chance to lift up.

The Internet, respectively the applications and services known as the Web, is undergoing significant changes. Mobile communication has enabled us with an omnipresent access to the Web, technologies such as grid computing and Web services allow us to use the Web far beyond its initial intention of document and information sharing, and intelligent agents and semantic systems aim to automate the tasks and better support us in interacting with the Web. Considering all those advances, one might ask the question how users can keep pace with all those developments and more specifically, how technology itself can help us in keeping pace. In this paper we investigate context aware adaptation and personalization as potential solutions.

Context is considered by research community in pervasive computing, and particularly in context awareness, to be subject to the available environmental sensors to retrieve the suitable information to the user. For example, the users context is based on location information or even based on other deterministic information, such as time (morning, evening, 11:00 am, etc.). The challenge is to also consider the user as a parameter influencing the context in addition to environmental information collected by sensors. This implies that human factors should be highly considered in order to formalize the ldquouser profilerdquo as an input to context awareness (context reasoning) and also as an output to the context adaptation. This vision, which we have adopted in this paper, implied to investigate both, the user actions acting in his or her living environment (Human behavior, preferences, etc.), and the context reasoning sensitive to human factors.

In this paper a general algorithm for a computer vision unit for supporting a Micro Unmanned Aerial Vehicle's autonomous flight through an unknown environment is presented. It is shown that the data generated from an image sequence taken by a single camera can be used as a supplementary measurement for an inertial measurement unit.

A three-tier information management architecture for mobile grid environments and ad-hoc networks is presented in this paper. We address a key challenge in such highly dynamic environments with a high degree of fluctuation in the hardware infrastructure: how to store information consistently, persistently, and at the same time efficiently. Most currently available approaches are based on replication strategies. These strategies achieve persistency even in highly dynamic environments, but have to pay a high price in terms of redundancy. Our proposed architecture is based on the adaptation of fault-tolerant data distribution strategies utilizing erasure codes, such as RAID or Reed-Solomon, and thus combines consistency and persistency with high storage efficiency.

In cyberworlds as well as in real world environments there is a need to enable cooperation and communication. While IT support has enabled us to overcome the barriers of time and place in communication over distance, there is still the problem of bridging the gap across different cultures. In this paper we will study the possibility of IT support for "sharing culture", i.e. for communication across different cultures. Our attempt to realize this goal is the creation of a learning, proactive agent that keeps track of the communication in virtual environments. We try to support the communication partners during their interactions by providing information based on the type and content of the communication. The information provided by the agent is based on cultural differences that could lead to potential misunderstandings within a communication scenario. The idea is to design a pluggable agent to support cross-cultural communication for virtual communities in distributed environments.

The simulation of computer systems requires representative, reliable workload models. When simulating computer systems or components that are influenced by user behavior, this very behavior has to be modeled by using mathematical means. In this article, we propose a user behavior model framework that is constructed in a top-down manner consisting of various layers. The layers offer services to the next higher layer and require services from the layers below. The framework is meant to enable the modeler to plug in his own models at the layers of his choice, thus choosing the right balance between the simulation complexity and creating representative results. We give a description of the layered framework and the corresponding methodology. The approach is then demonstrated on modeling HTTP traffic, to be used in network traffic simulation.

Self-managing systems able to dynamically re-configure with respect to time-varying workload mixes and changing system resource availability are of growing importance in heterogeneous multicomputer environments. Advanced performance evaluation techniques are needed to induce and assess the impact of such re-configurations where guaranteeing timeliness of reconfiguration activities is particularly challenging. A whole new class of methods supporting "pro-active" adaptivity based on the predicted system state at the re-configuration instant are needed to alleviate the shortcomings of "re-active" systems which bring reconfigurations in effect after the system state has changed. In this paper we argue for self-contained performance management of distributed applications, i.e. integrated performance tuning with the ability to automatically adapt the application behavior to the performance characteristics of the execution environment. Particularly, we study pro-active performance management for distributed simulation based on the Time Warp protocol executing on a network of workstations (NOWs).