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 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

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

Development Journey of QADPZ - A Desktop Grid Computing Platform

In this paper we present QADPZ, an open source system for desktop grid computing, which enables users of a local network or Internet to share resources. QADPZ allows a centralized management and use of the computational resources of idle computers from a network of desktop computers. QADPZ users can submit compute-intensive applications to the system, which are then automatically scheduled for execution. The scheduling is performed according to the hardware and software requirements of the application. Users can later monitor and control the execution of the applications. Each application consists of one or more tasks. Applications can be independent, when the composing tasks do not require any interaction, or parallel, when the tasks communicate with each other during the computation. The paper describes both QADPZ functionality and the process of design and implementation, with focus on requirements, architecture, user interface and security. Some future work ideas are also presented

Driving Style Analysis Using Data Mining Techniques

This paper investigates the modeling of the personal driving style of various vehicle drivers based on several driving parameters. The purpose of such an endeavor is to classify the drivers according to their risk-proneness within the larger context of increasing traffic safety, which is a major concern worldwide. This information is valuable especially for those involved in fleet management and it can be used to improve and to make safer the driving style of various individuals who serve within that fleet. Equally important, such information could help any driver to see the danger within his or her driving style. Cluster and principal component analyses from exploratory statistics have been used to identify and explain drivers grouping according to their driving behavior. The driving parameters (behavioral indices) are collected from urban traffic by an in-house developed GPS-based device and sent to a data server for analysis

Levels of Detail: An Overview

This paper overviews some aspects of using different levels of accuracy and complexity for the visualization of large data sets. Current status of the volume of data sets that can be generated is presented, together with some of the inherent problems due to such large data volumes, visualization requirements, and display limitations of existing hardware graphics. Some methods for selecting, generating and implementing different levels of detail are presented