The Innovative Use of Personal Smart Devices by Students to Support their Learning

Research into the autonomous use of MP3 audio recorders by students in UK Higher Education demonstrated that students were innovative in their autonomous use of the devices. They used them to capture learning conversations from formal and informal situations to personalise and enhance their learning. However, today smartphones and other smart devices have replaced the necessity for students to carry multiply mobile devices including MP3 recorders. This chapter builds upon the earlier work and presents a small qualitative study into how students are autonomously using their smart devices to support their learning. The research explores the hypothesis that students are being innovative in the ways in which they are use their smart devices to support their formal and informal learning. The study involved five students who own smart devices who were invited to discuss their ownership of smartphone and tablet technologies and the ways they used them in their studies. The students first completed a short questionnaire and were then interviewed in small groups. The results agree with previous research into the student use of smart devices and describe autonomous engagement facilitated by personally owned smart technologies. The study identifies continuous patterns of pervasive engagement by students and concludes that more thought should be given to disruptive innovation, digital literacy and employability

Opportunistic Sensing: Security Challenges for the New Paradigm

We study the security challenges that arise in Opportunistic people-centric sensing, a new sensing paradigm leveraging humans as part of the sensing infrastructure. Most prior sensor-network research has focused on collecting and processing environmental data using a static topology and an application-aware infrastructure, whereas opportunistic sensing involves collecting, storing, processing and fusing large volumes of data related to everyday human activities. This highly dynamic and mobile setting, where humans are the central focus, presents new challenges for information security, because data originates from sensors carried by people— not tiny sensors thrown in the forest or attached to animals. In this paper we aim to instigate discussion of this critical issue, because opportunistic people-centric sensing will never succeed without adequate provisions for security and privacy. To that end, we outline several important challenges and suggest general solutions that hold promise in this new sensing paradigm

DJ-MC: A Reinforcement-Learning Agent for Music Playlist Recommendation

In recent years, there has been growing focus on the study of automated recommender systems. Music recommendation systems serve as a prominent domain for such works, both from an academic and a commercial perspective. A fundamental aspect of music perception is that music is experienced in temporal context and in sequence. In this work we present DJ-MC, a novel reinforcement-learning framework for music recommendation that does not recommend songs individually but rather song sequences, or playlists, based on a model of preferences for both songs and song transitions. The model is learned online and is uniquely adapted for each listener. To reduce exploration time, DJ-MC exploits user feedback to initialize a model, which it subsequently updates by reinforcement. We evaluate our framework with human participants using both real song and playlist data. Our results indicate that DJ-MC's ability to recommend sequences of songs provides a significant improvement over more straightforward approaches, which do not take transitions into account.Comment: -Updated to the most recent and completed version (to be presented at AAMAS 2015) -Updated author list. in Autonomous Agents and Multiagent Systems (AAMAS) 2015, Istanbul, Turkey, May 201

A Multi-modal Approach to Fine-grained Opinion Mining on Video Reviews

Despite the recent advances in opinion mining for written reviews, few works have tackled the problem on other sources of reviews. In light of this issue, we propose a multi-modal approach for mining fine-grained opinions from video reviews that is able to determine the aspects of the item under review that are being discussed and the sentiment orientation towards them. Our approach works at the sentence level without the need for time annotations and uses features derived from the audio, video and language transcriptions of its contents. We evaluate our approach on two datasets and show that leveraging the video and audio modalities consistently provides increased performance over text-only baselines, providing evidence these extra modalities are key in better understanding video reviews.Comment: Second Grand Challenge and Workshop on Multimodal Language ACL 202

An information assistant system for the prevention of tunnel vision in crisis management

In the crisis management environment, tunnel vision is a set of bias in decision makers’ cognitive process which often leads to incorrect understanding of the real crisis situation, biased perception of information, and improper decisions. The tunnel vision phenomenon is a consequence of both the challenges in the task and the natural limitation in a human being’s cognitive process. An information assistant system is proposed with the purpose of preventing tunnel vision. The system serves as a platform for monitoring the on-going crisis event. All information goes through the system before arrives at the user. The system enhances the data quality, reduces the data quantity and presents the crisis information in a manner that prevents or repairs the user’s cognitive overload. While working with such a system, the users (crisis managers) are expected to be more likely to stay aware of the actual situation, stay open minded to possibilities, and make proper decisions

SMEs: ERP or virtual collaboration teams

Small firms are indeed the engines of global economic growth. Small and Medium Enterprises (SMEs) play an important role to promote economic development. SMEs in the beginning of implementing new technologies always face capital shortage and need technological assistance. Available ERP systems do not fulfil the specific requirements of Small firms. SMEs has scarce resources and manpower therefore many SMEs don?t have the possessions to buy and operate an ERP System. On the other hand competition and competitiveness of SMEs have to be strengthened. This paper briefly reviews the existing perspectives on virtual teams and their effect on SMEs management. It also discusses the main characteristics of virtual teams and clarifies the differences aspects of virtual team application in SMEs. After outlining some of the main advantages and pitfall of such teams, it concentrates on comparing of ERP and virtual collaborative teams in SMEs. Finally, it provides evidence for the need of ?Software as a Service (SaaS)? where an application is hosted as a service provided to customers across the web for SMEs as an alternative of ERP. It has been widely argued that ERP disadvantage in SMEs such as administrative expenditure and cost, isolated structure, severe lack of software flexibility, insufficient support of SMEs business and high operating cost, lead SMEs to use virtual collaborative team which is net work base solution