Abstract
This paper discusses a novel collective sensing approach using autonomous sensors specially designed to monitor gas leaks and search for gas sources. The proposed collective behavior aims to improve the gas-source search by sharing information between mobile sensors and reducing the risks associated with gas leakage. The group acts as a composite sensor that can move independently to search for an optimal sensing zone. The autonomous searching behavior is bio-inspired by colonies of bacteria that continuously seek energy sources throughout their existence. Each sensor makes its own autonomous search decision, considering the group sense, to move in the direction of a better energy source. The collective approach is based on autonomous agents sharing information to achieve a collective sense of gas perception and utilizes more intelligent searching. The method is evaluated in a cyber-physical system specially developed to safely experiment with gases and mobile sensors while reproducing the realistic dynamic behavior of the gas. Experiments are performed to clarify the collective gas-sensing contributions, and the gas search is compared through multiple mobile sensors with and without collective sensing. The proposed approach is evaluated in an unhealthy environment to elucidate its effectiveness. In addition to presenting the related differences between collective and individual sensory approaches, this work contributes with analyzes of the scalability of mobile gas sensing systems. This work also contributed as a simulated semi-physical experimental system to test algorithms' performance before applying it to practice.

Abstract

Abstract
Computer network attacks are vast and negatively impact the infrastructure and its applicational services. From a cyber offensive and defensive perspective, there are a plethora of tools to craft and inject customized malicious packets in the network and exploit operating systems and application vulnerabilities. Those tools are however hard to operate by practitioners with less knowledge on networking fundamentals and students in the early stage of their studies. This paper proposes an easy-to-use application tool that can produce customized Denial of Service (DoS) and spoofing attacks. It was developed in Python and takes advantage of scapy library to process and inject network packets. A set of experiments was made, and the results obtained show the efficiency and accuracy of the attacks, by impairing the proper functioning of the victim's machines.

Abstract
Purpose This study aims to understand why young people are interested in buying frugal innovations. Design/methodology/approach Data were collected with a survey administered to 534 university students enrolled in various fields of study (e.g. sciences, technology, economics and fine arts). Using the Tata Nano car as an example of frugal innovation, a model based on the unified theory of acceptance and use of technology was developed using partial least squares structural equation modeling. Findings The model's results reveal that effort expectancy, performance expectancy and facilitating conditions are critical factors that explain university students' intention to buy Tata Nano. Originality/value Although frugal innovations are often introduced first in developing countries, frugal innovations could be highly relevant to users in developed nations as these innovations can provide market opportunities in terms of cost-conscious, relatively low-income and sustainability-conscious consumers.

Abstract
O trabalho desenvolvido tem como objetivos identificar e compreender que estratégias de autorregulação e corregulação das aprendizagens foram adotadas pelos estudantes de programação de computadores no ensino a distância na transição entre iniciantes e proficientes. Este estudo decorreu na Unidade Curricular “Laboratório de Desenvolvimento de Software” (LDS) do 2.º semestre do 2.º ano da Licenciatura de Engenharia Informática da Universidade Aberta, com alunos heterogéneos em idade, residência, habilitações académicas e profissão. Adotou-se uma metodologia de investigação qualitativa por análise de conteúdo (Amado, 2014) de reflexões quinzenais solicitadas aos estudantes, sobre o processo de aprendizagem. A construção das matrizes de análise de conteúdo baseou-se no modelo teórico de Zimmerman (2013). Os resultados apontam para uma maior incidência na adoção de estratégias de autorregulação de aprendizagem de organização e planeamento. As menos frequentes foram a procura de ajuda e a consciência das dificuldades. Nas de corregulação de aprendizagem, as mais evidenciadas foram as de gestão do trabalho em equipa e planeamento. As menos evidentes foram a consciência das dificuldades e a procura de ajuda.

Abstract