An intelligent clustering scheme for distributed intrusion detection in vehicular cloud computing

In recent years, vehicular cloud computing (VCC) has emerged as a new technology which is being used in wide range of applications in the area of multimedia-based healthcare applications. In VCC, vehicles act as the intelligent machines which can be used to collect and transfer the healthcare data to the local, or global sites for storage, and computation purposes, as vehicles are having comparatively limited storage and computation power for handling the multimedia files. However, due to the dynamic changes in topology, and lack of centralized monitoring points, this information can be altered, or misused. These security breaches can result in disastrous consequences such as-loss of life or financial frauds. Therefore, to address these issues, a learning automata-assisted distributive intrusion detection system is designed based on clustering. Although there exist a number of applications where the proposed scheme can be applied but, we have taken multimedia-based healthcare application for illustration of the proposed scheme. In the proposed scheme, learning automata (LA) are assumed to be stationed on the vehicles which take clustering decisions intelligently and select one of the members of the group as a cluster-head. The cluster-heads then assist in efficient storage and dissemination of information through a cloud-based infrastructure. To secure the proposed scheme from malicious activities, standard cryptographic technique is used in which the auotmaton learns from the environment and takes adaptive decisions for identification of any malicious activity in the network. A reward and penalty is given by the stochastic environment where an automaton performs its actions so that it updates its action probability vector after getting the reinforcement signal from the environment. The proposed scheme was evaluated using extensive simulations on ns-2 with SUMO. The results obtained indicate that the proposed scheme yields an improvement of 10 % in detection rate of malicious nodes when compared with the existing schemes.

A Methodology for Creating an Adapted Command Language for Driving an Intelligent Wheelchair

Intelligent wheelchairs (IW) are technologies that can increase the autonomy and independence of elderly people and patients suffering from some kind of disability. Nowadays the intelligent wheelchairs and the human-machine studies are very active research areas. This paper presents a methodology and a Data Analysis System (DAS) that provides an adapted command language to an user of the IW. This command language is a set of input sequences that can be created using inputs from an input device or a combination of the inputs available in a multimodal interface. The results show that there are statistical evidences to affirm that the mean of the evaluation of the DAS generated command language is higher than the mean of the evaluation of the command language recommended by the health specialist (p value = 0.002) with a sample of 11 cerebral palsy users. This work demonstrates that it is possible to adapt an intelligent wheelchair interface to the user even when the users present heterogeneous and severe physical constraints.

Six thinking hats: A novel metalearner for intelligent decision support in electricity markets

The energy sector has suffered a significant restructuring that has increased the complexity in electricity market players' interactions. The complexity that these changes brought requires the creation of decision support tools to facilitate the study and understanding of these markets. The Multiagent Simulator of Competitive Electricity Markets (MASCEM) arose in this context, providing a simulation framework for deregulated electricity markets. The Adaptive Learning strategic Bidding System (ALBidS) is a multiagent system created to provide decision support to market negotiating players. Fully integrated with MASCEM, ALBidS considers several different strategic methodologies based on highly distinct approaches. Six Thinking Hats (STH) is a powerful technique used to look at decisions from different perspectives, forcing the thinker to move outside its usual way of thinking. This paper aims to complement the ALBidS strategies by combining them and taking advantage of their different perspectives through the use of the STH group decision technique. The combination of ALBidS' strategies is performed through the application of a genetic algorithm, resulting in an evolutionary learning approach.

Building anonymised database samples

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Ontology methodology building criteria for crowdsourcing innovation intermediaries

Crowdsourcing innovation intermediaries are organizations that mediate the communication and relationship between companies that aspire to solve some problem or to take advantage of any business opportunity with a crowd that is prone to give ideas based on their knowledge, experience and wisdom. A significant part of the activity of these intermediaries is carried out by using a web platform that takes advantage of web 2.0 tools to implement its capabilities. Thus, ontologies are presented as an appropriate strategy to represent the knowledge inherent to this activity and therefore the accomplishment of interoperability between machines and systems. In this paper we present an ontology roadmap for developing crowdsourcing innovation ontology of the intermediation process. We start making a literature review on ontology building, analyze and compare ontologies that propose the development from scratch with the ones that propose reusing other ontologies, and present the criteria for selecting the methodology. We also review enterprise and innovation ontologies known in literature. Finally, are taken some conclusions and presented the roadmap for building crowdsourcing innovation intermediary ontology.

Building Smarter Cities through Social Entrepreneurship

The objective of the present study is to examine the extent to which social ventures are able to increase the smartness of the cities. To achieve this goal, we adopt a qualitative approach, based on the case study method to obtain valuable insights about different characteristics and strategies of Cais (a non-profit association dedicated to help disadvantaged people in urban areas). By focusing on the analysis of the Cais activities, we assess whether its social intervention match the dimensions proposed by Giffinger et al. (2007) to rank smart cities’ performance, namely if it has smart: (i) economy; (ii) people; (iii) governance; (iv) mobility; (v) environment; and (vi) living. The research shows that the action pursued comprises elements from all the above mentioned dimensions. Further, the analysis reveals that Cais reinforces the smartness of the city where it acts (attributes such as living, economy, people, and environment).

GIS capacity building for risk management to help developing countries:Case of climate change problem in Amhara rural region (Ethiopia)

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Design and implementation of 3D buildings integration for a Webgl-Based Virtual Globe: a case study of Valencian Cadastre and Fide Building Mode

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Human activity recognition for an intelligent knee orthosis

Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica

Building clusters for CRM strategies by mining airlines customer data

Trabalho de Projeto apresentado como requisito parcial para obtenção do grau de Mestre em Estatística e Gestão de Informação

Evaluating Dynamic Signage for Emergency Evacuation using an Immersive Video Environment

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Primary and hospitalar health care: Building a happy marriage

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

Building information modeling como ferramenta de visualização de realidade aumentada em obras de reabilitação – um caso de estudo

Congresso Construção 2012 - 4º Congresso Nacional/17, 18 e 19 Dezembro

Customer Lifetime Value: a framework for application in the insurance industry - Building a Business Process to Generate and Maintain an Automatic Estimation Agent

Research Project submited as partial fulfilment for the Master Degree in Statistics and Information Management

The role of electron transfer in DNA building blocks: evaluation of strand breaks and their implications

Dissertação para obtenção do Grau de Doutor em Engenharia Física