When deploying a wireless sensor network (WSN) identifying optimal locations for the nodes is challenging, especially so if the environment is either (i) unknown or (ii) obstacle-rich. We proposes BISON (Bio-Inspired Self-Organizing Network), a variant of the Voronoi algorithm to address this challenge. Among the features of the approach are the restrictions placed upon the abilities of the nodes: (i) all information is sensed locally as well as (ii) subject to communication noise. Performance is measured as (i) the percentage of area covered, (ii) the total distance traveled by the nodes, (iii) the cumulative energy consumption and (iv) the uniformity of nodes’ distribution. Obstacle constellations and noise levels are studied systematically and a collision-free recovery strategy for failing nodes is proposed. Results obtained from extensive simulations show the algorithm outperforming previously reported approaches in both, convergence speed, as well as deployment cost.

In the area of applied optimisation, heuristics are a popular means to address computational problems of high complexity.Modelling the problem and mapping all variations of its solution into a so-called solution space are integral parts of this process.Representing solutions as graphs is common and, for a special type of graph, Pr üfer Code (PC) offers a computationally efficient mapping (algorithms of Θ(n)-complexity are known) to n-2 dimensional Euclidean space.However, this encoding does not preserve properties such as e.g.locality and therefore PC has been shown to be a bad choice for entire classes of problems.We argue that PC does allow the preservation of some properties (e.g.degree of branching and branching vertices) and that these are sufficiently relevant for certain types of problems to motivate encoding them in PC.We present our investigations and provide an example where PC has been shown to be a useful encoding.

Global demographic trends place an increasing demand on the efficient and customizable design of large scale buildings and digital services offered within. Indoor wireless access has become standard and ensuring a thorough and economically sound wireless signal coverage throughout the building is not a trivial problem. An In-building Distributed Antenna System (IB-DAS) extends the wireless access from the base station to distributed antennas through a complex network of coaxial cables and power splitters. For high rise buildings and other multi-unit complexes, the initial cost of IB-DAS (cabling and splitters) and the running costs of powering the network are quite significant, hence the optimal design of an IB-DAS network is critical. Our proposition here is a novel In-Building DAS optimization model that utilizes Particle Swarm Optimization (PSO) to provide near optimal network topology that simultaneously minimizes the cost of the cabling and equipment for the whole building. Our PSO model uses Prufer number representation to efficiently traverse through different spanning tree solutions. As opposed to other approaches which solve this problem only partially (either equipment or cabling), typically considering a building as a single floor unit, our approach is a complete proposition for DAS optimization that is scalable and robust to deliver IB-DAS designs even for the tallest buildings beyond one hundred floors. We demonstrate that our model is capable of obtaining optimal solutions for small buildings and near optimal solutions for tall buildings.

Interactive learning through computer quiz games has been introduced to improve teaching and learning in a freshman engineering chemistry course. This is accomplished through a series of JAVA-based, weekly general chemistry quiz games, developed and implemented as a supplemental and augmentative tool in delivering freshmen chemistry for engineering majors. The introduction of quiz game is anticipated to increase the engagement of students in chemistry classes by improving their attitudes towards chemistry and their overall chemistry achievements. Kolb's four-stage learning cycle is introduced as a possible model for a role the computer quiz games could have in the overall learning process, where the games are anticipated to serve as alternate mode of learning and as an additional motivational tool. In addition to introducing weekly computer quiz games, we report on the effort made to assess their effectiveness. For this purpose, we propose a novel chemistry achievement test developed in this study, Freshman Engineering Chemistry Aptitude Test (FECAT), which aims to comprehensively cover the freshmen engineering chemistry course. Additionally, we implemented an attitude questionnaire. The findings of this pilot study help to advance our understanding of the practical contribution of game-based learning to students' achievement in chemistry and also their attitudes towards learning chemistry at university. At the time of the pilot implementation, we hypothesized that the major benefit of the interactive game would be an increase in students' overall interest in chemistry, with an associated improvement in achievements in the course.

Learning theory in education has progressed dramatically with the rapid development of modern technologies. Modern learning theory has found that learning performance can be improved effectively through cooperative/ collaborative learning. How to group students in one class based on their different learning capabilities is a key to success in education. Two grouping types of homogeneous and heterogeneous have been applied into class grouping. Research proves that homogeneous groups are good at specific goal and heterogeneous groups are better in expanded tasks. Learning efficiency is affected in both group level and individual level by different grouping method. However grouping students in an optimal way is a difficult NP-hard research problem with high complexity; and to achieve the best results, such grouping can be very time consuming and tedious for the teachers to perform manually, especially when local cultural context (for instance, gender parameter) has to be taken into account, such as in the Middle East region. So the ability of allowing educators to define rules describing groups is very important for both homogeneous and heterogeneous grouping capabilities. This paper thus describes a smart grouping tool portal which is easy to access and user friendly, and aims to assist teachers to automatically group students based on different criteria. This portal has been trialled at Khalifa University of Science, Technology & Research (KUSTAR). A case study of the trial has also been analyzed to illustrate the derivative benefits of our smart grouping tool portal.