Introducing Game Development into the Computing Curriculum: a Progressive Methodology

The Computer Game industry is big business, the demand for graduates is high, indeed there is a continuing shortage of skilled employees. As with most professions, the skill set required is both specific and diverse. There are currently over 30 Higher Education Institutions (HEIs) in the UK offering Computer games related courses. We expect that as the demand from the industry is sustained, more HEIs will respond with the introduction of game-related degrees. This is quite a considerable undertaking involving many issues from integration of new modules or complete courses within the existing curriculum, to staff development. In this paper we share our experiences of introducing elements of game development into our curriculum. This has occurred over the past two years, starting with the inclusion of elements of game development into existing programming modules, followed by the validation of complete modules, and culminating in a complete degree course. Our experience is that our adopting a progressive approach to development, spread over a number of years, was crucial in achieving a successful outcome.

Optimatization of hybrid renewable energy systems on isolated microgrids : a smart grid approach

Tese de doutoramento, Sistemas Sustentáveis de Energia, Universidade de Lisboa, Faculdade de Ciências, 2016

Supporting dynamic parameter sweep applications in workflows: lessons learnt from the CancerGrid project

A vast majority of scientific grid applications are either parameter sweep applications or a significant subpart of these applications belong to class of parameter sweep activities. The paper describes a new graphical workflow language in which any node of the DAG-based workflow can be a parameter sweep node and the execution of these nodes are transparently executed either in service grids or in desktop grids depending on the computational complexity of the workflow node. The new concept is supported by the CancerGrid portal that has been established for a chemist community.

Business Models for Cloud Computing: Experiences from Developing Modeling & Simulation as a Service Applications in Industry

The potential of cloud computing is gaining significant interest in Modeling & Simulation (M&S). The underlying concept of using computing power as a utility is very attractive to users that can access state-of-the-art hardware and software without capital investment. Moreover, the cloud computing characteristics of rapid elasticity and the ability to scale up or down according to workload make it very attractive to numerous applications including M&S. Research and development work typically focuses on the implementation of cloud-based systems supporting M&S as a Service (MSaaS). Such systems are typically composed of a supply chain of technology services. How is the payment collected from the end-user and distributed to the stakeholders in the supply chain? We discuss the business aspects of developing a cloud platform for various M&S applications. Business models from the perspectives of the stakeholders involved in providing and using MSaaS and cloud computing are investigated and presented.

Analyzing and Modeling Medical Data on Distributed Computing Infrastructures

Researchers want to analyse Health Care data which may requires large pools of compute and data resources. To have them they need access to Distributed Computing Infrastructures (DCI). To use them it requires expertise which researchers may not have. Workflows can hide infrastructures. There are many workflow systems but they are not interoperable. To learn a workflow system and create workflows in a workflow system may require significant effort. Considering these efforts it is not reasonable to expect that researchers will learn new workflow systems if they want to run workflows of other workflow systems. As a result, the lack of interoperability prevents workflow sharing and a vast amount of research efforts is wasted. The FP7 Sharing Interoperable Workflow for Large-Scale Scientific Simulation on Available DCIs (SHIWA) project developed the Coarse-Grained Interoperability (CGI) to enable workflow sharing. The project created the SHIWA Simulation Platform (SSP) to support CGI as a production-level service. The paper describes how the CGI approach can be used for analysis and simulation in Health Care.

Affective Computing to Enhance E-Learning in Segregated Societies

According to UN Women, to build stronger economies, it is essential to empower women to participate fully in economic life across all sectors. Increasing women and girls’ education enhances their chances to participate in the labor market. In certain cultures, like in Saudi Arabia, women contribution to the public economy growth is very limited. According to the World Bank, less than 20 percent of the female population participate in the labor force. This low participation rate has many reasons. One of them, is the educational level and educational quality for females. Although Saudi Arabia has about thirty three universities, opportunities are still limited for women because of the restrictions of access put upon them. A mixture of local norms, traditions, social beliefs, and principles preventing women from receiving full benefits from the educational system. Gender segregation is one of the challenges that limits the women access for education. It causes a problem due to the shortage of female faculty throughout the country. To overcome this problem, male faculty are allowed to teach female students under certain regulations and following a certain method of education delivery and interaction. However, most of these methods lack face-to-face communication between the teacher and students, which lowers the interactivity level and, accordingly, the students’ engagement, and increases the need for other alternatives. The e-learning model is one of high benefit for female students in such societies. Recognizing the students’ engagement is not straightforward in the e-learning model. To measure the level of engagement, the learner’s mood or emotions should be taken into consideration to help understanding and judging the level of engagement. This paper is to investigate the relationship between emotions and engagement in the e-learning environment, and how recognizing the learner’s emotions and change the content delivery accordingly can affect the efficiency of the e-learning process. The proposed experiment alluded to herein should help to find ways to increase the engagement of the learners, hence, enhance the efficiency of the learning process and the quality of learning, which will increase the chances and opportunities for women in such societies to participate more effectively in the labor market.

Off Grid

Doctor Watson Architects joined with Samir Pandya and a select group of architecture students to work with line, colour and thread as a means of achieving a psycho-dynamic suspension of matter form and space in the newly opened studios on the 4th & 5th floors of the University of Westminster's Marylebone Block.

Distributed Agent-Based Load Balancer for Cloud Computing

In this paper we present a concept of an agent-based strategy to allocate services on a Cloud system without overloading nodes and maintaining the system stability with minimum cost. To provide a base for our research we specify an abstract model of cloud resources utilization, including multiple types of resources as well as considerations for the service migration costs. We also present an early version of simulation environment and a prototype of agent-based load balancer implemented in functional language Scala and Akka framework.

A Meta-Heuristic Load Balancer for Cloud Computing Systems

This paper introduces a strategy to allocate services on a cloud system without overloading the nodes and maintaining the system stability with minimum cost. We specify an abstract model of cloud resources utilization, including multiple types of resources as well as considerations for the service migration costs. A prototype meta-heuristic load balancer is demonstrated and experimental results are presented and discussed. We also propose a novel genetic algorithm, where population is seeded with the outputs of other meta-heuristic algorithms.

Estudo de adoção de tecnologias de cloud computing no contexto das PMES portuguesas

A sociedade atual é marcada por uma crescente competição entre as organizações, as quais para garantirem a sua sobrevivência têm que evoluir e utilizar a tecnologia de informação mais adequada. Num período em que as PMES portuguesas necessitam de reduzir custos e concentrarem-se mais no seu processo de negócio surge um novo paradigma tecnológico, a Computação na Nuvem, esta ainda é um paradigma bastante recente, onde os recursos de TI que apresentam características de elasticidade e dinâmicas são oferecidos ao cliente como um serviço, no qual este paga apenas o que consome (pagamento por utilização). A Cloud Computing com o seu novo paradigma permite às organizações, principalmente às PMES reduzirem custos, concentrarem-se no seu processo de negócio sem se preocuparem com a parte informática (cópias de segurança, assistência e perda de dados) e obter um retorno mais rápido do seu investimento. Este trabalho consiste no Estudo da Adoção Individual da Cloud Computing no contexto das PMEs Portuguesas, o qual apresenta como principais objetivos obter uma melhor compreensão do conceito Cloud Computing, entender a sua importância para os indivíduos das PMES, identificar os seus fatores de sucesso e insucesso e identificar as limitações sentidas de uma forma generalizada e de uma forma específica para as PMES Portuguesas. Para cumprir os objetivos mencionados anteriormente, efetuou-se uma extensa revisão de literatura, propôs-se um modelo conceptual de investigação com adaptações à Teoria Unificada de Aceitação e Uso de Tecnologia (UTAUT) e utilizou-se como instrumento de recolha de dados um questionário que foi enviado às PMES Portuguesas.

Grid structure impact in sparse point representation of derivatives

In the Sparse Point Representation (SPR) method the principle is to retain the function data indicated by significant interpolatory wavelet coefficients, which are defined as interpolation errors by means of an interpolating subdivision scheme. Typically, a SPR grid is coarse in smooth regions, and refined close to irregularities. Furthermore, the computation of partial derivatives of a function from the information of its SPR content is performed in two steps. The first one is a refinement procedure to extend the SPR by the inclusion of new interpolated point values in a security zone. Then, for points in the refined grid, such derivatives are approximated by uniform finite differences, using a step size proportional to each point local scale. If required neighboring stencils are not present in the grid, the corresponding missing point values are approximated from coarser scales using the interpolating subdivision scheme. Using the cubic interpolation subdivision scheme, we demonstrate that such adaptive finite differences can be formulated in terms of a collocation scheme based on the wavelet expansion associated to the SPR. For this purpose, we prove some results concerning the local behavior of such wavelet reconstruction operators, which stand for SPR grids having appropriate structures. This statement implies that the adaptive finite difference scheme and the one using the step size of the finest level produce the same result at SPR grid points. Consequently, in addition to the refinement strategy, our analysis indicates that some care must be taken concerning the grid structure, in order to keep the truncation error under a certain accuracy limit. Illustrating results are presented for 2D Maxwell's equation numerical solutions.