TLAD 2010 Proceedings:8th international workshop on teaching, learning and assesment of databases (TLAD)

This is the eighth in the series of highly successful international workshops on the Teaching, Learning and Assessment of Databases (TLAD 2010), which once again is held as a workshop of BNCOD 2010 - the 27th International Information Systems Conference. TLAD 2010 is held on the 28th June at the beautiful Dudhope Castle at the Abertay University, just before BNCOD, and hopes to be just as successful as its predecessors.The teaching of databases is central to all Computing Science, Software Engineering, Information Systems and Information Technology courses, and this year, the workshop aims to continue the tradition of bringing together both database teachers and researchers, in order to share good learning, teaching and assessment practice and experience, and further the growing community amongst database academics. As well as attracting academics from the UK community, the workshop has also been successful in attracting academics from the wider international community, through serving on the programme committee, and attending and presenting papers.This year, the workshop includes an invited talk given by Richard Cooper (of the University of Glasgow) who will present a discussion and some results from the Database Disciplinary Commons which was held in the UK over the academic year. Due to the healthy number of high quality submissions this year, the workshop will also present seven peer reviewed papers, and six refereed poster papers. Of the seven presented papers, three will be presented as full papers and four as short papers. These papers and posters cover a number of themes, including: approaches to teaching databases, e.g. group centered and problem based learning; use of novel case studies, e.g. forensics and XML data; techniques and approaches for improving teaching and student learning processes; assessment techniques, e.g. peer review; methods for improving students abilities to develop database queries and develop E-R diagrams; and e-learning platforms for supporting teaching and learning

TLAD 2010 Proceedings:8th international workshop on teaching, learning and assesment of databases (TLAD)

This is the eighth in the series of highly successful international workshops on the Teaching, Learning and Assessment of Databases (TLAD 2010), which once again is held as a workshop of BNCOD 2010 - the 27th International Information Systems Conference. TLAD 2010 is held on the 28th June at the beautiful Dudhope Castle at the Abertay University, just before BNCOD, and hopes to be just as successful as its predecessors.The teaching of databases is central to all Computing Science, Software Engineering, Information Systems and Information Technology courses, and this year, the workshop aims to continue the tradition of bringing together both database teachers and researchers, in order to share good learning, teaching and assessment practice and experience, and further the growing community amongst database academics. As well as attracting academics from the UK community, the workshop has also been successful in attracting academics from the wider international community, through serving on the programme committee, and attending and presenting papers.This year, the workshop includes an invited talk given by Richard Cooper (of the University of Glasgow) who will present a discussion and some results from the Database Disciplinary Commons which was held in the UK over the academic year. Due to the healthy number of high quality submissions this year, the workshop will also present seven peer reviewed papers, and six refereed poster papers. Of the seven presented papers, three will be presented as full papers and four as short papers. These papers and posters cover a number of themes, including: approaches to teaching databases, e.g. group centered and problem based learning; use of novel case studies, e.g. forensics and XML data; techniques and approaches for improving teaching and student learning processes; assessment techniques, e.g. peer review; methods for improving students abilities to develop database queries and develop E-R diagrams; and e-learning platforms for supporting teaching and learning

Fiscal-monetary-financial stability interactions in a data-rich environment

In this paper, we shed some light on the mutual interplay of economic policy and the financial stability objective. We contribute to the intense discussion regarding the influence of fiscal and monetary policy measures on the real economy and the financial sector. We apply a factor-augmented vector autoregression model to Czech macroeconomic data and model the policy interactions in a data-rich environment. Our findings can be summarized in three main points: First, loose economic policies (especially monetary policy) may translate into a more stable financial sector, albeit only in the short term. In the medium term, an expansion-focused mix of monetary and fiscal policy may contribute to systemic risk accumulation, by substantially increasing credit dynamics and house prices. Second, we find that fiscal and monetary policy impact the financial sector in differential magnitudes and time horizons. And third, we confirm that systemic risk materialization might cause significant output losses and deterioration of public finances, trigger deflationary pressures, and increase the debt service ratio. Overall, our findings provide some empirical support for countercyclical fiscal and monetary policies.Web of Science18322419

Case Teknos Group Oy Paint Store Transaction Data

Companies operating in challenging business environments, characterized by the proliferation of disruptive technologies and intensifying competition, are obliged to re-evaluate their strategic approach. This has become the norm in the retail industry and traditional brick-and-mortar stores. Particularly local market players with scarce resources are looking into alternative solutions to delivering a unique customer experience with the intention to preserve their profitability. Customer experience has been an integral topic within academic research for decades, and has also substantiated its value in pragmatic contexts. Recent developments in this field have triggered the constitution of customer experience management functions, which aim to adopt a holistic approach to the customer experience. This enforces a quantitative perspective highlighting the role of customer transaction data. Association analysis is one of the most well-known methodology used to detect underlying patterns hidden in large transaction data sets. It uses machine learning techniques to firstly identify frequently purchased product combinations and secondly, to discover concealed associations among the products. The association rules derived and evaluated during the process can potentially reveal implicit, yet interesting customer insight, which may translate into actionable implications. The practical consequences in the framework of this study are referred to as sales increasing strategies, namely targeted marketing, cross-selling and space management. This thesis uses Python programming language in Anaconda’s Jupyter Notebook environment to perform association analysis on customer transaction data provided by the case company. The Apriori algorithm is applied to constitute the frequent itemsets and generate association rules between these itemsets. The interestingness and actionability of the rules will be evaluated based on various scoring measures computed for each rule. The outcomes of this study contribute to finding interesting customer insight and actionable recommendations for the case company to support their success in demanding market conditions. Furthermore, this research describes and discusses the relative success factors from the theoretical point of view and demonstrates the process of association rule mining when applied to customer transaction data

A Method based on Association Rules to Construct Product Line Model

International audienceThe success of a product line is the ability to improve application engineering, heavily depends on the quality of Product Line Models (PLMs). This paper reports on our effort to develop a method that exploits mining techniques such as the apriori algorithm, independence tests and the like to automate the construction of a PLM specified with FORE, starting from a collection of Product Models (PMs). Using these techniques, the proposed method guides the identification of candidate features, group cardinalities and dependencies. These can be used to progressively construct the PLM consistently with the existing PMs. The method was developed and tested in an industry setting starting with bills of materials as a collection of PMs. One interesting lesson learn from this experiment is that while the PLM is constructed, the domain engineer discovers errors in PMs. We believe that this advocates for a tighter intertwining between domain engineering and application engineering

The strategic use of patents and its implications for enterprise and competition policies

This report was commissioned as a study into the strategic use of patents. In the course of its case investigations and legislative reviews the European Commission became aware of changes in the use of intellectual property, in particular the use of patents. It was noted that firms’ uses of intellectual property are becoming increasingly strategic. This raised concerns about the implications of firms’ patenting behaviour for enterprise and competition policy. The following report contains a comprehensive review of patenting behaviour, the extent to which patenting is becoming more strategic and the implications this has for competition and enterprise policies