An Extended Event Reasoning Framework for Decision Support under Uncertainty

To provide in-time reactions to a large volume of surveil- lance data, uncertainty-enabled event reasoning frameworks for CCTV and sensor based intelligent surveillance system have been integrated to model and infer events of interest. However, most of the existing works do not consider decision making under uncertainty which is important for surveillance operators. In this paper, we extend an event reasoning framework for decision support, which enables our framework to predict, rank and alarm threats from multiple heterogeneous sources.

Predictive Maintenance for Improved Sustainability - An Ion Beam Etch Endpoint Detection System Use Case

In modern semiconductor manufacturing facilities maintenance strategies are increasingly shifting from traditional preventive maintenance (PM) based approaches to more efficient and sustainable predictive maintenance (PdM) approaches. This paper describes the development of such an online PdM module for the endpoint detection system of an ion beam etch tool in semiconductor manufacturing. The developed system uses optical emission spectroscopy (OES) data from the endpoint detection system to estimate the RUL of lenses, a key detector component that degrades over time. Simulation studies for historical data for the use case demonstrate the effectiveness of the proposed PdM solution and the potential for improved sustainability that it affords.

Connectivity and Physical Activity: Using Footpath Networks to Measure the Walkability of Built Environments

There is now a strong body of research that suggests that the form of the built environment can influence levels of physical activity, leading to an increasing interest in incorporating health objectives into spatial planning and regeneration policies and projects. There have been a number of strands to this research, one of which has sought to develop ���objective��� measurements of the built environment using Geographic Information Science (GIS) involving measures of connectivity and proximity to compare the relative ���walkability��� of different neighbourhoods. The development of the ���walkability index��� (e.g. Leslie et al 2007, Frank et al 2010) has become a popular indicator of spatial distribution of those features of the built environment that are considered to have the greatest positive influence on levels of physical activity. The success of this measure is built on its ability to succinctly capture built environment correlates of physical activity using routinely available spatial data, which includes using road centre lines as a basis of a proxy for connectivity. <br/><br/>This paper discusses two key aspects of the walkability index. First, it follows the suggestion of Chin et al (2008) that the use of a footpath network (where available), rather than road centre lines, may be far more effective in evaluating walkability. This may be particularly important for assessing changes in walkability arising from pedestrian-focused infrastructure projects, such as greenways. Second, the paper explores the implication of this for how connectivity can be measured. The paper takes six different measures of connectivity and first analyses the relationships between them and then tests their correlation with actual levels of physical activity of local residents in Belfast, Northern Ireland. The analysis finds that the best measurements appear to be intersection density and metric reach and uses this finding to discuss the implications of this for developing tools that may better support decision-making in spatial planning.<br/>

A survey of location inference techniques on Twitter

The increasing popularity of the social networking service, Twitter, has made it more involved in day-to-day communications, strengthening social relationships and information dissemination. Conversations on Twitter are now being explored as indicators within early warning systems to alert of imminent natural disasters such earthquakes and aid prompt emergency responses to crime. Producers are privileged to have limitless access to market perception from consumer comments on social media and microblogs. Targeted advertising can be made more effective based on user profile information such as demography, interests and location. While these applications have proven beneficial, the ability to effectively infer the location of Twitter users has even more immense value. However, accurately identifying where a message originated from or author���s location remains a challenge thus essentially driving research in that regard. In this paper, we survey a range of techniques applied to infer the location of Twitter users from inception to state-of-the-art. We find significant improvements over time in the granularity levels and better accuracy with results driven by refinements to algorithms and inclusion of more spatial features.

LS-ADT: Lightweight and Scalable Anomaly Detection for Cloud Datacentres

Cloud data centres are implemented as large-scale clusters with demanding requirements for service performance, availability and cost of operation. As a result of scale and complexity, data centres typically exhibit large numbers of system anomalies resulting from operator error, resource over/under provisioning, hardware or software failures and security issus anomalies are inherently difficult to identify and resolve promptly via human inspection. Therefore, it is vital in a cloud system to have automatic system monitoring that detects potential anomalies and identifies their source. In this paper we present a lightweight anomaly detection tool for Cloud data centres which combines extended log analysis and rigorous correlation of system metrics, implemented by an efficient correlation algorithm which does not require training or complex infrastructure set up. The LADT algorithm is based on the premise that there is a strong correlation between node level and VM level metrics in a cloud system. This correlation will drop significantly in the event of any performance anomaly at the node-level and a continuous drop in the correlation can indicate the presence of a true anomaly in the node. The log analysis of LADT assists in determining whether the correlation drop could be caused by naturally occurring cloud management activity such as VM migration, creation, suspension, termination or resizing. In this way, any potential anomaly alerts are reasoned about to prevent false positives that could be caused by the cloud operator���s activity. We demonstrate LADT with log analysis in a Cloud environment to show how the log analysis is combined with the correlation of systems metrics to achieve accurate anomaly detection.

Systematically retrieving research in the digital age: Case study on the topic of social networking sites and young people���s mental health

Online information seeking has become normative practice among both academics and the general population. This study appraised the performance of eight databases to retrieve research pertaining to the influence of social networking sites on the mental health of young people. A total of 43 empirical studies on young people���s use of social networking sites and the mental health implications were retrieved. Scopus and SSCI had the highest sensitivity with PsycINFO having the highest precision. Effective searching requires large<br/>generic databases, supplemented by subject-specific catalogues. The methodology developed here may provide inexperienced searchers, such as undergraduate students, with a framework to define a realistic scale of searching to undertake for a particular literature review or similar project.

Rede social de leitores e escritores juniores: portal Biblon: a integra����o social on-line como catalisador da leitura, cria����o, express��o e partilha

Com enquadramento nas ��reas de Ci��ncia da Informa����o, Tecnologias de Informa����o e Comunica����o e Educa����o, o estudo em voga visa formular propostas para o uso de rede social on-line de literatura infantil, em torno da biblioteca, para a educa����o b��sica, fundamentadas na teoria de comunidades de pr��tica. O estudo de caso recaiu sobre quatro escolas, do 1�� ciclo, da Educa����o B��sica, do Agrupamento de Escolas de Aveiro-Portugal, tendo como instrumento para o experimento o Portal Biblon. A an��lise dos dados permite afirmar que a leitura de livros on-line n��o est�� inclusa nas atividades habituais da comunidade escolar pesquisada e, assim, o aluno encontra-se sem referencial para inserir esta pr��tica cultural em suas rotinas e momentos de ��cio. O cen��rio escolar atual n��o estimula a conflu��ncias da pr��tica da leitura liter��ria e da escrita dos alunos com as redes sociais on-line. O estudo aponta que, em uma rede social on-line, o livro de literatura infantil tem o papel de interagente, agregando leitores, em intera����o, em torno de si e que nas redes sociais on-line tem-se a presen��a dos ���mediadores sociais centrais��� que propiciam refor��o e sustenta����o das pr��ticas de leitura, atrav��s do cont��gio e da influ��ncia social e s��o propulsionadores da estrutura e do dinamismo da rede. Como conclus��o geral tem-se que os utilizadores do Biblon desenvolvem experi��ncias de leituras e escritas atrav��s da intera����o social, por meio de pr��ticas, rotinas, di��logos e atividades comuns constru��das na rede. A intera����o dentro da rede influencia o uso das ferramentas e o aprendizado para manuse��-las ocorre com as pr��ticas. Assim, os la��os associativos e as rea����es individuais envolvendo a leitura conduzem �� forma����o de rede social em torno dos livros e os comportamentos e as prefer��ncias dos atores motivam a leitura e a escrita. Dessa forma, o Portal Biblon configura-se como um instrumento para forma����o de rede social on-line em torno da literatura infantil.

Conceptions of subject analysis: a metatheoretical investigation

Thesis (Ph. D.)--University of Washington, 2005.

ESEIG Mobile: an m-learning approach in a superior school

In recent years, mobile learning has emerged as an educational approach to decrease the limitation of learning location and adapt the teaching-learning process to all type of students. However, the large number and variety of Web-enabled devices poses challenges for Web content creators who want to automatic get the delivery context and adapt the content to mobile devices. In this paper we study several approaches to adapt the learning content to mobile phones. We present an architecture for deliver uniform m-Learning content to students in a higher School. The system development is organized in two phases: firstly enabling the educational content to mobile devices and then adapting it to all the heterogeneous mobile platforms. With this approach, Web authors will not need to create specialized pages for each kind of device, since the content is automatically transformed to adapt to any mobile device capabilities from WAP to XHTML MP-compliant devices.

Odin: a service for gamification of learning activities

Existing gami���cation services have features that preclude their use by e-learning tools. Odin is a gami���cation service that mimics the API of state-of-the-art services without these limitations. This paper describes Odin, its role in an e-learning system architecture requiring gami���cation, and details its implementation. The validation of Odin involved the creation of a small e-learning game, integrated in a Learning Management System (LMS) using the Learning Tools Interoperability (LTI) speci���cation.

Contributions towards smart cities : exploring block level census data for the characterization of change in Lisbon

The interest in using information to improve the quality of living in large urban areas and its governance efficiency has been around for decades. Nevertheless, the improvements in Information and Communications Technology has sparked a new dynamic in academic research, usually under the umbrella term of Smart Cities. This concept of Smart City can probably be translated, in a simplified version, into cities that are lived, managed and developed in an information-saturated environment. While it makes perfect sense and we can easily foresee the benefits of such a concept, presently there are still several significant challenges that need to be tackled before we can materialize this vision. In this work we aim at providing a small contribution in this direction, which maximizes the relevancy of the available information resources. One of the most detailed and geographically relevant information resource available, for the study of cities, is the census, more specifically the data available at block level (Subsec����o Estat��stica). In this work, we use Self-Organizing Maps (SOM) and the variant Geo-SOM to explore the block level data from the Portuguese census of Lisbon city, for the years of 2001 and 2011. We focus on gauging change, proposing ways that allow the comparison of the two time periods, which have two different underlying geographical bases. We proceed with the analysis of the data using different SOM variants, aiming at producing a two-fold portrait: one, of the evolution of Lisbon during the first decade of the XXI century, another, of how the census dataset and SOM���s can be used to produce an informational framework for the study of cities.