Towards Effective and Efficient Data Management in Embedded Systems and Internet of Things

The majority of today low-end and low-cost embedded devices work in dynamic environments under several constraints such as low power, reduced memory, limited processing and communication, etc. Therefore, their data management is critical. We introduce here a general method for data representation, storage, and transmission in embedded systems based on a compact representation scheme and some heuristics. This method has been implemented, tested, and evaluated within a vehicle tracking system that uses an in-house very low cost microcontroller-based telemetry device, which provides for near-real-time remote vehicle monitoring, energy consumption, ubiquitous health, etc. However, our method is general and can be used for any type of low-cost and resource-constrained embedded device, where data communication from the device to the Internet (or cloud) is involved. Its efficiency and effectiveness are proven by significant reductions of mobile data transmitted, as our case study shows. Further benefits are reducing power consumption and transmission costs

Towards a Systematic Approach of Relational Database Watermarking

Nowadays more and more data of socio-technical systems become available online to anyone interested to access it or process it (without data alteration or copyright infringement). Generally, these data are stored in relational databases. However, to comply with this new paradigm new models of data access and security are necessary. One upcoming trend for relational databases is to watermark the database instance, i.e. to compute a secret code, which can be either embedded directly into the database or registered to a trusted authority. Current watermarking schemes only apply to either a particular database relation or index and, generally, distort the data. In this paper, we propose a methodology for distortion-free watermarking of both the database schema and instance that takes into account the database semantics, its dynamic, and also ensuring various security levels within the database. A possible scenario on using this methodology on a real-world database is also available

Towards Building Creative Collaborative Learning Groups Using Reinforcement Learning

Increasing creative skills in collaborative groups is of huge interest for stakeholders in education, industry, policy making etc. However, construction of “the most” creative groups given a cohort of people and a set of common goals and tasks to perform is challenging. The complexity of this undertaking is amplified by the necessity to first understand and then measure what “the most” creative means in a particular situation. We present here our method of semi-automatic building of “the most” creative learning groups given a cohort of students and a particular learning context based on reinforcement learning (an adapted Q-learning algorithm). Various attributes that influence individual and group creativity may be considered. A case study on using this method with our Computer Science students is also included. However, the method is general and can be used for building collaborative groups in any situation, with the appropriate “the most” creative goal and attributes

Career Tracks and Job Requirements in Information Systems vs. ACM/AIS IS 2010 Curriculum Guidelines: An Empirical Study

There is always a gap between what the job market expects from both undergraduates and graduates and what academic education actually provides. Keeping this gap is important in our view, because universities have to put first the best interest of their students as persons, in the long run, i.e. to prepare them to live a fulfilled life, in all the aspects that count, by both empowering them with the best possible knowledge, skills, attitudes, and values and helping them discover their innate abilities. However, finding the right job is an important coordinate of the multifaceted life nowadays, and academia is ought to empower them in this direction too. Our main goal here is to determine what are the most sought after job types (in line with the career tracks of ACM/AIS IS 2010 Curriculum Guidelines for undergraduates) and job requirements (per job type), in Information Systems in our country. However, in our view, this research has more than local interest given that our IS job market is very dynamic due to the consistent presence of both major corporations and active firms in this field

Towards Construction of Creative Collaborative Teams Using Multiagent Systems

Group creativity and innovation are of chief importance for both collaborative learning and collaborative working, as increasing the efficiency and effectiveness of groups of individuals performing together specific activities to achieve common goals, in given contexts, is of crucial importance nowadays. Nevertheless, construction of “the most” creative and innovative groups given a cohort of people and a set of common goals and tasks to perform is challenging. We present here our method for semi-automatic construction of “the most” creative and innovative teams given a group of persons and a particular goal, which is based on unsupervised learning and it is supported by a multiagent system. Individual creativity and motivation are both factors influencing group creativity used in the experiments performed with our Computer Science students. However, the method is general and can be used for building the most creative and innovative groups in any collaborative situation