A DSL for querying building data streams of energy, eeather and occupation data

The superfluous consumption of energy is faced by the modern society as a Socio-Economical and Environmental problem of the present days. This situation is worsening given that it is becoming clear that the tendency is to increase energy price every year. It is also noticeable that people, not necessarily proficient in technology, are not able to know where savings can be achieved, due to the absence of accessible awareness mechanisms. One of the home user concerns is to balance the need of reducing energy consumption, while producing the same activity with all the comfort and work efficiency. The common techniques to reduce the consumption are to use a less wasteful equipment, altering the equipment program to a more economical one or disconnecting appliances that are not necessary at the moment. However, there is no direct feedback from this performed actions, which leads to the situation where the user is not aware of the influence that these techniques have in the electrical bill. With the intension to give some control over the home consumption, Energy Management Systems (EMS) were developed. These systems allow the access to the consumption information and help understanding the energy waste. However, some studies have proven that these systems have a clear mismatch between the information that is presented and the one the user finds useful for his daily life, leading to demotivation of use. In order to create a solution more oriented towards the user’s demands, a specially tailored language (DSL) was implemented. This solution allows the user to acquire the information he considers useful, through the construction of questions about his energy consumption. The development of this language, following the Model Driven Development (MDD) approach, took into consideration the ideas of facility managers and home users in the phases of design and validation. These opinions were gathered through meetings with experts and a survey, which was conducted to the purpose of collecting statistics about what home users want to know.

Comparateive analysis: Public and private school management systems

The Portuguese educational system has counted, for many years, with the co-existence of both public and private schools. In fact, the country’s growth and development led, in the past, to an increasing demand for free of charge public education that could only be matched through the creation of “publicly-subsidized and privately owned and managed schools”. Still, the demographic evolution of Portugal recently generated a decrease on the demand for public educational services. This situation has raised doubts about the true contribution of this type of school for the public education system. This paper aims at answering this question by isolating the impact of different property and management schemes on the performance of students, resorting to cross-section data on 9th grade students from 2010. The results corroborate the well known result on the relevance of the family socio-economic background for students’ performance, but do also sustain the existence of a significant positive impact of private ownership and management schemes on the overall performance of students. These results suggest that there might be gains associated with the expansion of such schemes within the public education system.

Mapping the Pasture Steppe in Bayankhongor, Mongolia: comparison of classification methods, using Landsat-8 and geophysical data

Grasslands in semi-arid regions, like Mongolian steppes, are facing desertification and degradation processes, due to climate change. Mongolia’s main economic activity consists on an extensive livestock production and, therefore, it is a concerning matter for the decision makers. Remote sensing and Geographic Information Systems provide the tools for advanced ecosystem management and have been widely used for monitoring and management of pasture resources. This study investigates which is the higher thematic detail that is possible to achieve through remote sensing, to map the steppe vegetation, using medium resolution earth observation imagery in three districts (soums) of Mongolia: Dzag, Buutsagaan and Khureemaral. After considering different thematic levels of detail for classifying the steppe vegetation, the existent pasture types within the steppe were chosen to be mapped. In order to investigate which combination of data sets yields the best results and which classification algorithm is more suitable for incorporating these data sets, a comparison between different classification methods were tested for the study area. Sixteen classifications were performed using different combinations of estimators, Landsat-8 (spectral bands and Landsat-8 NDVI-derived) and geophysical data (elevation, mean annual precipitation and mean annual temperature) using two classification algorithms, maximum likelihood and decision tree. Results showed that the best performing model was the one that incorporated Landsat-8 bands with mean annual precipitation and mean annual temperature (Model 13), using the decision tree. For maximum likelihood, the model that incorporated Landsat-8 bands with mean annual precipitation (Model 5) and the one that incorporated Landsat-8 bands with mean annual precipitation and mean annual temperature (Model 13), achieved the higher accuracies for this algorithm. The decision tree models consistently outperformed the maximum likelihood ones.

Development of an integrated approach to reliability management and operation

The research described in this thesis has been developed as a part of the Reliability and Field Data Management for Multi-component Products (REFIDAM) Project. This project was founded under the Applied Research Grants Scheme administered by Enterprise Ireland. The project was a partnership between Galway-Mayo Institute of Technology and Thermo King Europe. The project aimed to develop a system in order to manage the information required for reliability assessment and improvement of multi-component products, by establishing information flows within the company and information exchange with fleet users.

Association between Spirituality and Adherence to Management in Outpatients with Heart Failure

Abstract Background: Spirituality may influence how patients cope with their illness. Objectives: We assessed whether spirituality may influence adherence to management of outpatients with heart failure. Methods: Cross sectional study enrolling consecutive ambulatory heart failure patients in whom adherence to multidisciplinary treatment was evaluated. Patients were assessed for quality of life, depression, religiosity and spirituality utilizing validated questionnaires. Correlations between adherence and psychosocial variables of interest were obtained. Logistic regression models explored independent predictors of adherence. Results: One hundred and thirty patients (age 60 ± 13 years; 67% male) were interviewed. Adequate adherence score was observed in 38.5% of the patients. Neither depression nor religiosity was correlated to adherence, when assessed separately. Interestingly, spirituality, when assessed by both total score sum (r = 0.26; p = 0.003) and by all specific domains, was positively correlated to adherence. Finally, the combination of spirituality, religiosity and personal beliefs was an independent predictor of adherence when adjusted for demographics, clinical characteristics and psychosocial instruments. Conclusion: Spirituality, religiosity and personal beliefs were the only variables consistently associated with compliance to medication in a cohort of outpatients with heart failure. Our data suggest that adequately addressing these aspects on patient’s care may lead to an improvement in adherence patterns in the complex heart failure management.

Aggregation and errors in management accounting

Il est important pour les entreprises de compresser les informations détaillées dans des sets d'information plus compréhensibles. Au chapitre 1, je résume et structure la littérature sur le sujet « agrégation d'informations » en contrôle de gestion. Je récapitule l'analyse coûts-bénéfices que les comptables internes doivent considérer quand ils décident des niveaux optimaux d'agrégation d'informations. Au-delà de la perspective fondamentale du contenu d'information, les entreprises doivent aussi prendre en considération des perspectives cogni- tives et comportementales. Je développe ces aspects en faisant la part entre la comptabilité analytique, les budgets et plans, et la mesure de la performance. Au chapitre 2, je focalise sur un biais spécifique qui se crée lorsque les informations incertaines sont agrégées. Pour les budgets et plans, des entreprises doivent estimer les espérances des coûts et des durées des projets, car l'espérance est la seule mesure de tendance centrale qui est linéaire. A la différence de l'espérance, des mesures comme le mode ou la médiane ne peuvent pas être simplement additionnés. En considérant la forme spécifique de distributions des coûts et des durées, l'addition des modes ou des médianes résultera en une sous-estimation. Par le biais de deux expériences, je remarque que les participants tendent à estimer le mode au lieu de l'espérance résultant en une distorsion énorme de l'estimati¬on des coûts et des durées des projets. Je présente également une stratégie afin d'atténuer partiellement ce biais. Au chapitre 3, j'effectue une étude expérimentale pour comparer deux approches d'esti¬mation du temps qui sont utilisées en comptabilité analytique, spécifiquement « coûts basés sur les activités (ABC) traditionnelles » et « time driven ABC » (TD-ABC). Au contraire des affirmations soutenues par les défenseurs de l'approche TD-ABC, je constate que cette dernière n'est pas nécessairement appropriée pour les calculs de capacité. Par contre, je démontre que le TD-ABC est plus approprié pour les allocations de coûts que l'approche ABC traditionnelle. - It is essential for organizations to compress detailed sets of information into more comprehensi¬ve sets, thereby, establishing sharp data compression and good decision-making. In chapter 1, I review and structure the literature on information aggregation in management accounting research. I outline the cost-benefit trade-off that management accountants need to consider when they decide on the optimal levels of information aggregation. Beyond the fundamental information content perspective, organizations also have to account for cognitive and behavi¬oral perspectives. I elaborate on these aspects differentiating between research in cost accounti¬ng, budgeting and planning, and performance measurement. In chapter 2, I focus on a specific bias that arises when probabilistic information is aggregated. In budgeting and planning, for example, organizations need to estimate mean costs and durations of projects, as the mean is the only measure of central tendency that is linear. Different from the mean, measures such as the mode or median cannot simply be added up. Given the specific shape of cost and duration distributions, estimating mode or median values will result in underestimations of total project costs and durations. In two experiments, I find that participants tend to estimate mode values rather than mean values resulting in large distortions of estimates for total project costs and durations. I also provide a strategy that partly mitigates this bias. In the third chapter, I conduct an experimental study to compare two approaches to time estimation for cost accounting, i.e., traditional activity-based costing (ABC) and time-driven ABC (TD-ABC). Contrary to claims made by proponents of TD-ABC, I find that TD-ABC is not necessarily suitable for capacity computations. However, I also provide evidence that TD-ABC seems better suitable for cost allocations than traditional ABC.

Iowa Department of Transportation Office of Research & Analytics Guidance on Data Management Plan (DMP) Requirements for Federally Funded Research Projects

The Iowa Department of Transportation Office of Research & Analytics has created this Guide to help researchers and contractors of the Iowa DOT attain compliance with Federal and Iowa DOT Public Access Policies for transportation-related research publications and datasets. This guide provides direction for filling out the data management plan template (also attached to this record) that will help satisfy Iowa DOT and U.S. DOT requirements.

Methadone maintenance treatment in the Swiss Canton of Vaud: demographic and clinical data on 1,782 ambulatory patients.

Using data from the Public Health Service, we studied the demographic and clinical characteristics of 1,782 patients enrolled in methadone maintenance treatment (MMT) during 2001 in the Swiss Canton of Vaud, comparing our findings with the results of a previous study from 1976 to 1986. In 2001, most patients (76.9%) were treated in general practice. Mortality is low in this MMT population (1%/year). While patient age and sex profiles were similar to those found in the earlier study, we did observe a substantial increase in the number of patients and the number of practitioners treating MMT patients, probably reflecting the low-threshold governmental policies and the creation of specialized centers. In conclusion, easier access to MMT enhances the number of patients, but new concerns about the quality of management emerge: benzodiazepine as a concomitant prescription; low rates of screening for hepatitis B, C and HIV, and social and psychiatric preoccupations.

Data Consistency by a Metadata Management Solution

This thesis consists of three main theoretical themes: quality of data, success of information systems, and metadata in data warehousing. Loosely defined, metadata is descriptive data about data, and, in this thesis, master data means reference data about customers, products etc. The objective of the thesis is to contribute to an implementation of a metadata management solution for an industrial enterprise. The metadata system incorporates a repository, integration, delivery and access tools, as well as semantic rules and procedures for master data maintenance. It targets to improve maintenance processes and quality of hierarchical master data in the case company’s informational systems. That should bring benefits to whole organization in improved information quality, especially in cross-system data consistency, and in more efficient and effective data management processes. As the result of this thesis, the requirements for the metadata management solution in case were compiled, and the success of the new information system and the implementation project was evaluated.

Evaluating the Maturity of Data Management Practices in a Major Energy Provider Company

Data is the most important asset of a company in the information age. Other assets, such as technology, facilities or products can be copied or reverse-engineered, employees can be brought over, but data remains unique to every company. As data management topics are slowly moving from unknown unknowns to known unknowns, tools to evaluate and manage data properly are developed and refined. Many projects are in progress today to develop various maturity models for evaluating information and data management practices. These maturity models come in many shapes and sizes: from short and concise ones meant for a quick assessment, to complex ones that call for an expert assessment by experienced consultants. In this paper several of them, made not only by external inter-organizational groups and authors, but also developed internally at a Major Energy Provider Company (MEPC) are juxtaposed and thoroughly analyzed. Apart from analyzing the available maturity models related to Data Management, this paper also selects the one with the most merit and describes and analyzes using it to perform a maturity assessment in MEPC. The utility of maturity models is two-fold: descriptive and prescriptive. Besides recording the current state of Data Management practices maturity by performing the assessments, this maturity model is also used to chart the way forward. Thus, after the current situation is presented, analysis and recommendations on how to improve it based on the definitions of higher levels of maturity are given. Generally, the main trend observed was the widening of the Data Management field to include more business and “soft” areas (as opposed to technical ones) and the change of focus towards business value of data, while assuming that the underlying IT systems for managing data are “ideal”, that is, left to the purely technical disciplines to design and maintain. This trend is not only present in Data Management but in other technological areas as well, where more and more attention is given to innovative use of technology, while acknowledging that the strategic importance of IT as such is diminishing.

Data management as a part of performance management: Case study about production reporting development project

Because of the increased availability of different kind of business intelligence technologies and tools it can be easy to fall in illusion that new technologies will automatically solve the problems of data management and reporting of the company. The management is not only about management of technology but also the management of processes and people. This thesis is focusing more into traditional data management and performance management of production processes which both can be seen as a requirement for long lasting development. Also some of the operative BI solutions are considered in the ideal state of reporting system. The objectives of this study are to examine what requirements effective performance management of production processes have for data management and reporting of the company and to see how they are effecting on the efficiency of it. The research is executed as a theoretical literary research about the subjects and as a qualitative case study about reporting development project of Finnsugar Ltd. The case study is examined through theoretical frameworks and by the active participant observation. To get a better picture about the ideal state of reporting system simple investment calculations are performed. According to the results of the research, requirements for effective performance management of production processes are automation in the collection of data, integration of operative databases, usage of efficient data management technologies like ETL (Extract, Transform, Load) processes, data warehouse (DW) and Online Analytical Processing (OLAP) and efficient management of processes, data and roles.

Research Data Management in the Cloud

Workshop at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Data Management [in eprints] for arts research: the experience at University of the Arts London

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

From KAPTUR to VADS4R: Exploring Research Data Management in the Visual Arts

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

From KAPTUR to VADSR: Exploring Research Data Management in the Visual Arts

Poster at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014