Substance Use and Misuse : Adolescent Substance Use in the context of the family ; a qualitative study of young people's views on parent child attachments , parenting style and parental substance use

Introduction and Aims. While the role of the family in adolescent substance use has been well documented, few studies have attempted to explore in-depth youth perceptions of how these familial processes/dynamics influence teenage substance use. This paper reports the findings from a study exploring risk and protective factors for teenage substance use within the context of the family as perceived by young people with a view to informing current and future family based prevention and education interventions.
Design and Methods. Data collection took place in nine post-primary schools across Northern Ireland. Nine focus groups using participatory techniques were facilitated with a purposive sample of sixty-two young people (age 13-17 years). Data were transcribed verbatim and analysed using a content/thematic analysis.
Results. Three broad themes/aspects of the family emerged from the data, which may serve to protect or attenuate the risk of substance use among young people. Parent-child attachment was a major theme identified in protecting adolescents from substance use in addition to effective parenting particularly an authoritative style of parenting supplemented by parental monitoring and good parent-child communication to encourage child disclosure. Family substance use was deemed to impact on children’s substance use if exposed at an early age and the harms associated with PSM were discussed in detail.
Discussion and Conclusions. The qualitative approach provides insight into current understanding of youth perceptions of substance use in the context of family dynamics. A number of recommendations are outlined. Family based (preventive) interventions/parenting programmes may benefit from components on effective parenting including authoritative styles, parental monitoring, effective communication, spending time together (building attachments), parent-child conflict, adolescent development and factors which impact on parenting. Parenting programmes tailored to mothers and fathers may be beneficial. School based interventions targeting children/adolescents may be best placed to target children living with parental substance misuse.
Keywords: substance/substance related disorders, focus groups, young people/adolescent,

U-TRACER® - the use of communication technology in higher education - an information visualization tool for the context of Portuguese public higher education

Information Visualization is gradually emerging to assist the representation and comprehension of large datasets about Higher Education Institutions, making the data more easily understood. The importance of gaining insights and knowledge regarding higher education institutions is little disputed. Within this knowledge, the emerging and urging area in need of a systematic understanding is the use of communication technologies, area that is having a transformative impact on educational practices worldwide. This study focused on the need to visually represent a dataset about how Portuguese Public Higher Education Institutions are using Communication Technologies as a support to teaching and learning processes. Project TRACER identified this need, regarding the Portuguese public higher education context, and carried out a national data collection. This study was developed within project TRACER, and worked with the dataset collected in order to conceptualize an information visualization tool U-TRACER®. The main goals of this study related to: conceptualization of the information visualization tool U-TRACER®, to represent the data collected by project TRACER; understand higher education decision makers perception of usefulness regarding the tool. The goals allowed us to contextualize the phenomenon of information visualization tools regarding higher education data, realizing the existing trends. The research undertaken was of qualitative nature, and followed the method of case study with four moments of data collection.The first moment regarded the conceptualization of the U-TRACER®, with two focus group sessions with Higher Education professionals, with the aim of defining the interaction features the U-TRACER® should offer. The second data collection moment involved the proposal of the graphical displays that would represent the dataset, which reading effectiveness was tested by end-users. The third moment involved the development of a usability test to the UTRACER ® performed by higher education professionals and which resulted in the proposal of improvements to the final prototype of the tool. The fourth moment of data collection involved conducting exploratory, semi-structured interviews, to the institutional decision makers regarding their perceived usefulness of the U-TRACER®. We consider that the results of this study contribute towards two moments of reflection. The challenges of involving end-users in the conceptualization of an information visualization tool; the relevance of effective visual displays for an effective communication of the data and information. The second relates to the reflection about how the higher education decision makers, stakeholders of the U-TRACER® tool, perceive usefulness of the tool, both for communicating their institutions data and for benchmarking exercises, as well as a support for decision processes. Also to reflect on the main concerns about opening up data about higher education institutions in a global market.

Big data warehouse framework for smart revenue management

Revenue Management’s most cited definitions is probably “to sell the right accommodation to the right customer, at the right time and the right price, with optimal satisfaction for customers and hoteliers”. Smart Revenue Management (SRM) is a project, which aims the development of smart automatic techniques for an efficient optimization of occupancy and rates of hotel accommodations, commonly referred to, as revenue management. One of the objectives of this project is to demonstrate that the collection of Big Data, followed by an appropriate assembly of functionalities, will make possible to generate a Data Warehouse necessary to produce high quality business intelligence and analytics. This will be achieved through the collection of data extracted from a variety of sources, including from the web. This paper proposes a three stage framework to develop the Big Data Warehouse for the SRM. Namely, the compilation of all available information, in the present case, it was focus only the extraction of information from the web by a web crawler – raw data. The storing of that raw data in a primary NoSQL database, and from that data the conception of a set of functionalities, rules, principles and semantics to select, combine and store in a secondary relational database the meaningful information for the Revenue Management (Big Data Warehouse). The last stage will be the principal focus of the paper. In this context, clues will also be giving how to compile information for Business Intelligence. All these functionalities contribute to a holistic framework that, in the future, will make it possible to anticipate customers and competitor’s behavior, fundamental elements to fulfill the Revenue Management

Planning and management of marine protected areas : methodological approaches to cope with data scarcity

Tese de doutoramento, Biologia (Biologia Marinha e Aquacultura), Universidade de Lisboa, Faculdade de Ciências, 2015

Typical load profiles in the smart grid context – a clustering methods comparison

The present research paper presents five different clustering methods to identify typical load profiles of medium voltage (MV) electricity consumers. These methods are intended to be used in a smart grid environment to extract useful knowledge about customer’s behaviour. The obtained knowledge can be used to support a decision tool, not only for utilities but also for consumers. Load profiles can be used by the utilities to identify the aspects that cause system load peaks and enable the development of specific contracts with their customers. The framework presented throughout the paper consists in several steps, namely the pre-processing data phase, clustering algorithms application and the evaluation of the quality of the partition, which is supported by cluster validity indices. The process ends with the analysis of the discovered knowledge. To validate the proposed framework, a case study with a real database of 208 MV consumers is used.

Using data mining techniques to support DR programs definition in smart grids

In recent years, Power Systems (PS) have experimented many changes in their operation. The introduction of new players managing Distributed Generation (DG) units, and the existence of new Demand Response (DR) programs make the control of the system a more complex problem and allow a more flexible management. An intelligent resource management in the context of smart grids is of huge important so that smart grids functions are assured. This paper proposes a new methodology to support system operators and/or Virtual Power Players (VPPs) to determine effective and efficient DR programs that can be put into practice. This method is based on the use of data mining techniques applied to a database which is obtained for a large set of operation scenarios. The paper includes a case study based on 27,000 scenarios considering a diversity of distributed resources in a 32 bus distribution network.

Intelligent energy resources management in the context of smart grids

Smart grids are envisaged as infrastructures able to accommodate all centralized and distributed energy resources (DER), including intensive use of renewable and distributed generation (DG), storage, demand response (DR), and also electric vehicles (EV), from which plug-in vehicles, i.e. gridable vehicles, are especially relevant. Moreover, smart grids must accommodate a large number of diverse types or players in the context of a competitive business environment. Smart grids should also provide the required means to efficiently manage all these resources what is especially important in order to make the better possible use of renewable based power generation, namely to minimize wind curtailment. An integrated approach, considering all the available energy resources, including demand response and storage, is crucial to attain these goals. This paper proposes a methodology for energy resource management that considers several Virtual Power Players (VPPs) managing a network with high penetration of distributed generation, demand response, storage units and network reconfiguration. The resources are controlled through a flexible SCADA (Supervisory Control And Data Acquisition) system that can be accessed by the evolved entities (VPPs) under contracted use conditions. A case study evidences the advantages of the proposed methodology to support a Virtual Power Player (VPP) managing the energy resources that it can access in an incident situation.

Data mining applications in power systems - case-studies and future trends

Presently power system operation produces huge volumes of data that is still treated in a very limited way. Knowledge discovery and machine learning can make use of these data resulting in relevant knowledge with very positive impact. In the context of competitive electricity markets these data is of even higher value making clear the trend to make data mining techniques application in power systems more relevant. This paper presents two cases based on real data, showing the importance of the use of data mining for supporting demand response and for supporting player strategic behavior.

Categorical data clustering using a minimum message length criterion

Research on cluster analysis for categorical data continues to develop, new clustering algorithms being proposed. However, in this context, the determination of the number of clusters is rarely addressed. We propose a new approach in which clustering and the estimation of the number of clusters is done simultaneously for categorical data. We assume that the data originate from a finite mixture of multinomial distributions and use a minimum message length criterion (MML) to select the number of clusters (Wallace and Bolton, 1986). For this purpose, we implement an EM-type algorithm (Silvestre et al., 2008) based on the (Figueiredo and Jain, 2002) approach. The novelty of the approach rests on the integration of the model estimation and selection of the number of clusters in a single algorithm, rather than selecting this number based on a set of pre-estimated candidate models. The performance of our approach is compared with the use of Bayesian Information Criterion (BIC) (Schwarz, 1978) and Integrated Completed Likelihood (ICL) (Biernacki et al., 2000) using synthetic data. The obtained results illustrate the capacity of the proposed algorithm to attain the true number of cluster while outperforming BIC and ICL since it is faster, which is especially relevant when dealing with large data sets.

Some reflections on acquisition, processing and analysis of statistical data in forest soils

Beyond the classical statistical approaches (determination of basic statistics, regression analysis, ANOVA, etc.) a new set of applications of different statistical techniques has increasingly gained relevance in the analysis, processing and interpretation of data concerning the characteristics of forest soils. This is possible to be seen in some of the recent publications in the context of Multivariate Statistics. These new methods require additional care that is not always included or refered in some approaches. In the particular case of geostatistical data applications it is necessary, besides to geo-reference all the data acquisition, to collect the samples in regular grids and in sufficient quantity so that the variograms can reflect the spatial distribution of soil properties in a representative manner. In the case of the great majority of Multivariate Statistics techniques (Principal Component Analysis, Correspondence Analysis, Cluster Analysis, etc.) despite the fact they do not require in most cases the assumption of normal distribution, they however need a proper and rigorous strategy for its utilization. In this work, some reflections about these methodologies and, in particular, about the main constraints that often occur during the information collecting process and about the various linking possibilities of these different techniques will be presented. At the end, illustrations of some particular cases of the applications of these statistical methods will also be presented.

Using Baseline Methods to Identify Non-technical Losses in the Context of Smart Grids

Demand response has gained increasing importance in the context of competitive electricity markets and smart grid environments. In addition to the importance that has been given to the development of business models for integrating demand response, several methods have been developed to evaluate the consumers’ performance after the participation in a demand response event. The present paper uses those performance evaluation methods, namely customer baseline load calculation methods, to determine the expected consumption in each period of the consumer historic data. In the cases in which there is a certain difference between the actual consumption and the estimated consumption, the consumer is identified as a potential cause of non-technical losses. A case study demonstrates the application of the proposed method to real consumption data.

Information professionals in business context: new professionals, old skills

This communication aims to present some reflections regarding the importance of information in organizational context, especially in business context. The ability to produce and to share expertise and knowledge among its employees is now a key factor in the success of any organization. However, it’s also true that workers are increasingly feeling that too much information can hurt their performance. The existence of skilled professionals able to organize, evaluate, select and disseminate information in organizations appears to be a prerequisite for success. The skills necessary for the formation of a professional devoted to the management of information and knowledge in the context of business organizations will be analysed. Then data collected in two focus group discussion with students from a graduate course in Business Information, from Polytechnic Institute of Porto, Portugal, a will be examined.

The effectiveness of the “Processo Especial de Revitalização” as an instrument of corporate restructuring in the context of the current economic crisis

This work project intends to evaluate the effectiveness of the Portuguese Government’s strategy to promote the orderly deleveraging of the corporate sector in the context of the current economic crisis. The recommendations of the Troika and the commitments assumed under the Memorandum of Understanding signed by the Government in 2011 required the creation of formal processes to avoid disorderly deleveraging. Conclusions and recommendations were drawn based on past experiences of large-scale corporate restructuring strategies in other countries and on the analysis of financial and statistical data on companies applying for “Programa Especial de Revitalização”.

Context costs and comparative advantages in the telecommunications sector in Portugal and China

This Work Project aims to discuss the Context Costs and Comparative Advantages of the Telecommunications sector both in Portugal and China. The work was built mostly on primary research by interviews with relevant people (business persons, University Professors and Agencies directors), and by economic data publicly available. A list of context costs and comparative advantages was drawn for each country and possible resolutions suggestions were made in the end. The context costs depend heavily on the economic situation of the countries and it should be taken into account when assessing the degree of magnitude of each cost of context. The competitive advantages of each country were drawn in comparison with one another. Some key results stand out: firstly, Portugal’s costs of context depend mainly on governmental decisions, uncertainties and instability and China’s cost of context depend primarily on cultural norms, mainly the Guanxi; second, the telecommunications sector shares most of its context costs and advantages with other sectors; third, China as an economic power could use the telecommunications sector as a way to further develop and boost its economy.

Ontario high school sport : an investigation of organizational design and its context

In 2002, The Ontario Federation of School Athletic Associations (OFSAA) identified that in providing extracurricular sport programs schools are faced with the 'new realities' of the education system. Although research has been conducted exploring the pressures impacting the provision of extracurricular school sport (Donnelly, Mcloy, Petherick, & Safai, 2000), few studies within the field have focused on understanding extracurricular school sport from an organizational level. The focus of this study was to examine the organizational design (structure, systems, and values) of the extracurricular sport department within three Ontario high schools, as well as to understand the context within which the departments exist. A qualitative multiple case study design was adopted and three public high schools were selected from one district school board in Ontario to represent the cases under investigation. Interviews, observations and documents were used to analyze the extracurricular sport department design of each case and to better understand the context within which the departments exist. As the result of the analysis of the structure, systems and values of each case, two designs emerged- Design KT1 and Design KT2. Differences in the characteristics of design archetype KT1 and KT2 centered on the design dimension of values, and therefore this study identified that contrasting organizational values reflect differences in design types. The characteristics of the Kitchen Table archetype were found to be transferable to the sub-sector of extracurricular school sport, and therefore this research provides a springboard for further research in organizational design within the education sector of extracurricular high school sport. Interconnections were found between the data associated with the external and internal contexts within which the extracurricular sport departments exist. The analysis of the internal context indicated the important role played by organizational members in shaping the context within which the departments exist. The analysis of the external context highlighted the institutional pressures that were present within the education environment. Both political and cultural expectations related to the role of extracurricular sport within schools were visible and were subsequently used by the high schools to create legitimacy and prestige, and to access resources.