SOFT – generating highly flexible object code from XML specifications

Many code generation tools exist to aid developers in carrying out common mappings, such as from Object to XML or from Object to relational database. Such generated code tends to possess a high binding between the Object code and the target mapping, making integration into a broader application tedious or even impossible. In this paper we suggest XML technologies and the multiple inheritance capabilities of interface based languages such as Java, offer a means to unify such executable specifications, thus building complete, consistent and useful object models declaratively, without sacrificing component flexibility.

Web-based course support systems: an essential tool for supporting flexible learning environment

In Higher Education web-based course support systems are essential for supporting flexible learning environments. They provide tools to enable the interaction between student and tutor to reinforce transfer of theory to understanding particularly in an academic environment, therefore this paper will examine issues associated with the use of curriculum and learning resources within Web-based course support systems and the effectiveness of the resulting flexible learning environments This paper is a general discussion about flexible learning and in this case how it was applied to one of the courses at undergraduate level one. The first section will introduce what is flexible learning and the importance of flexible learning in Higher Education followed by the description of the course and why the flexible learning concepts is important in such a course and finally, how the flexibility was useful for this particular instance.

La Web Semántica y los archivos de televisión: estado de la cuestión

Se analizan y describen las principales líneas de trabajo de la Web Semántica en el ámbito de los archivos de televisión. Para ello, se analiza y contextualiza la web semántica desde una perspectiva general para posteriormente analizar las principales iniciativas que trabajan con lo audiovisual: Proyecto MuNCH, Proyecto S5T, Semantic Television y VideoActive.

An extended framework for evidential reasoning systems

Based on the Dempster-Shafer (D-S) theory of evidence and G. Yen's (1989), extension of the theory, the authors propose approaches to representing heuristic knowledge by evidential mapping and pooling the mass distribution in a complex frame by partitioning that frame using Shafter's partition technique. The authors have generalized Yen's model from Bayesian probability theory to the D-S theory of evidence. Based on such a generalized model, an extended framework for evidential reasoning systems is briefly specified in which a semi-graph method is used to describe the heuristic knowledge. The advantage of such a method is that it can avoid the complexity of graphs without losing the explicitness of graphs. The extended framework can be widely used to build expert systems

Interacting software-agents to support a kind of expert supervision systems

Expert supervision systems are software applications specially designed to automate process monitoring. The goal is to reduce the dependency on human operators to assure the correct operation of a process including faulty situations. Construction of this kind of application involves an important task of design and development in order to represent and to manipulate process data and behaviour at different degrees of abstraction for interfacing with data acquisition systems connected to the process. This is an open problem that becomes more complex with the number of variables, parameters and relations to account for the complexity of the process. Multiple specialised modules tuned to solve simpler tasks that operate under a co-ordination provide a solution. A modular architecture based on concepts of software agents, taking advantage of the integration of diverse knowledge-based techniques, is proposed for this purpose. The components (software agents, communication mechanisms and perception/action mechanisms) are based on ICa (Intelligent Control architecture), software middleware supporting the build-up of applications with software agent features

Noves tècniques de gestió per a l'empresa promotora constructora

En el sector de la promoció construcció, i en especial, en el subsector de la promoció construcció d'habitatges, l'empresari ha de tenir un bon coneixement de les variables d'entorn ja que la consideració de les mateixes seran fonamentals a l'hora de prendre decisions sobre planificació estratègica. En l'actualitat vivim una fase de canvis socioeconòmics que dificulten la previsió del comportament futur de les variables d'entorn. Per tant, el subjecte decisor es troba en un ambient d'incertesa que s'aguditza per la majoritària presència de factors qualitatius difícils de quantificar. Llavors, l'empresari promotor constructor haurà de recórrer a tècniques operatives de gestió que tinguin present aquesta situació i això serà possible a partir de les eines que ens ofereix la lògica borrosa. Aquesta tesi s'ha estructurat en tres parts: En la primera part, exposem les característiques específiques i l'evolució del sector. En la segona part, expliquem la metodologia i, en la tercera part, exposem diverses aplicacions de la metodologia borrosa per l'establiment de noves estratègies de gestió aplicades al sector objecte d'estudi.

Achieving quality through statistical prediction for building services systems

The application of prediction theories has been widely practised for many years in many industries such as manufacturing, defence and aerospace. Although these theories are not new, their application has not been widely used within the building services industry. Collectively, the building services industry should take a deeper look at these approaches in comparison with the traditional deterministic approaches currently being practised. By extending the application into this industry, this paper seeks to provide the industry with an overview of how simplified stochastic modelling coupled with availability and reliability predictions using historical data compiled from various sources could enhance the quality of building services systems.

Comparing machine learning classifiers in potential distribution modelling

Species` potential distribution modelling consists of building a representation of the fundamental ecological requirements of a species from biotic and abiotic conditions where the species is known to occur. Such models can be valuable tools to understand the biogeography of species and to support the prediction of its presence/absence considering a particular environment scenario. This paper investigates the use of different supervised machine learning techniques to model the potential distribution of 35 plant species from Latin America. Each technique was able to extract a different representation of the relations between the environmental conditions and the distribution profile of the species. The experimental results highlight the good performance of random trees classifiers, indicating this particular technique as a promising candidate for modelling species` potential distribution. (C) 2010 Elsevier Ltd. All rights reserved.

Expert system to calculate the cofficient of friction : an approach to enhance traffic safety

Friction plays a key role in causing slipperiness as a low coefficient of friction on the road may result in slippery and hazardous conditions. Analyzing the strong relation between friction and accident risk on winter roads is a difficult task. Many weather forecasting organizations use a variety of standard and bespoke methods to predict the coefficient of friction on roads. This article proposes an approach to predict the extent of slipperiness by building and testing an expert system. It estimates the coefficient of friction on winter roads in the province of Dalarna, Sweden using the prevailing weather conditions as a basis. Weather data from the road weather information system, Sweden (RWIS) was used. The focus of the project was to use the expert system as a part of a major project in VITSA, within the domain of intelligent transport systems

The use of remote sensing imagery for monitoring recovery in the aftermath of a natural disaster: the Hurricane Katrina Case

Although Recovery is often defined as the less studied and documented phase of the Emergency Management Cycle, a wide literature is available for describing characteristics and sub-phases of this process. Previous works do not allow to gain an overall perspective because of a lack of systematic consistent monitoring of recovery utilizing advanced technologies such as remote sensing and GIS technologies. Taking into consideration the key role of Remote Sensing in Response and Damage Assessment, this thesis is aimed to verify the appropriateness of such advanced monitoring techniques to detect recovery advancements over time, with close attention to the main characteristics of the study event: Hurricane Katrina storm surge. Based on multi-source, multi-sensor and multi-temporal data, the post-Katrina recovery was analysed using both a qualitative and a quantitative approach. The first phase was dedicated to the investigation of the relation between urban types, damage and recovery state, referring to geographical and technological parameters. Damage and recovery scales were proposed to review critical observations on remarkable surge- induced effects on various typologies of structures, analyzed at a per-building level. This wide-ranging investigation allowed a new understanding of the distinctive features of the recovery process. A quantitative analysis was employed to develop methodological procedures suited to recognize and monitor distribution, timing and characteristics of recovery activities in the study area. Promising results, gained by applying supervised classification algorithms to detect localization and distribution of blue tarp, have proved that this methodology may help the analyst in the detection and monitoring of recovery activities in areas that have been affected by medium damage. The study found that Mahalanobis Distance was the classifier which provided the most accurate results, in localising blue roofs with 93.7% of blue roof classified correctly and a producer accuracy of 70%. It was seen to be the classifier least sensitive to spectral signature alteration. The application of the dissimilarity textural classification to satellite imagery has demonstrated the suitability of this technique for the detection of debris distribution and for the monitoring of demolition and reconstruction activities in the study area. Linking these geographically extensive techniques with expert per-building interpretation of advanced-technology ground surveys provides a multi-faceted view of the physical recovery process. Remote sensing and GIS technologies combined to advanced ground survey approach provides extremely valuable capability in Recovery activities monitoring and may constitute a technical basis to lead aid organization and local government in the Recovery management.

Organisational learning - a critical systems thinking discipline

Original Paper European Journal of Information Systems (2001) 10, 135–146; doi:10.1057/palgrave.ejis.3000394 Organisational learning—a critical systems thinking discipline P Panagiotidis1,3 and J S Edwards2,4 1Deloitte and Touche, Athens, Greece 2Aston Business School, Aston University, Aston Triangle, Birmingham, B4 7ET, UK Correspondence: Dr J S Edwards, Aston Business School, Aston University, Aston Triangle, Birmingham, B4 7ET, UK. E-mail: j.s.edwards@aston.ac.uk 3Petros Panagiotidis is Manager responsible for the Process and Systems Integrity Services of Deloitte and Touche in Athens, Greece. He has a BSc in Business Administration and an MSc in Management Information Systems from Western International University, Phoenix, Arizona, USA; an MSc in Business Systems Analysis and Design from City University, London, UK; and a PhD degree from Aston University, Birmingham, UK. His doctorate was in Business Systems Analysis and Design. His principal interests now are in the ERP/DSS field, where he serves as project leader and project risk managment leader in the implementation of SAP and JD Edwards/Cognos in various major clients in the telecommunications and manufacturing sectors. In addition, he is responsible for the development and application of knowledge management systems and activity-based costing systems. 4John S Edwards is Senior Lecturer in Operational Research and Systems at Aston Business School, Birmingham, UK. He holds MA and PhD degrees (in mathematics and operational research respectively) from Cambridge University. His principal research interests are in knowledge management and decision support, especially methods and processes for system development. He has written more than 30 research papers on these topics, and two books, Building Knowledge-based Systems and Decision Making with Computers, both published by Pitman. Current research work includes the effect of scale of operations on knowledge management, interfacing expert systems with simulation models, process modelling in law and legal services, and a study of the use of artifical intelligence techniques in management accounting. Top of pageAbstract This paper deals with the application of critical systems thinking in the domain of organisational learning and knowledge management. Its viewpoint is that deep organisational learning only takes place when the business systems' stakeholders reflect on their actions and thus inquire about their purpose(s) in relation to the business system and the other stakeholders they perceive to exist. This is done by reflecting both on the sources of motivation and/or deception that are contained in their purpose, and also on the sources of collective motivation and/or deception that are contained in the business system's purpose. The development of an organisational information system that captures, manages and institutionalises meaningful information—a knowledge management system—cannot be separated from organisational learning practices, since it should be the result of these very practices. Although Senge's five disciplines provide a useful starting-point in looking at organisational learning, we argue for a critical systems approach, instead of an uncritical Systems Dynamics one that concentrates only on the organisational learning practices. We proceed to outline a methodology called Business Systems Purpose Analysis (BSPA) that offers a participatory structure for team and organisational learning, upon which the stakeholders can take legitimate action that is based on the force of the better argument. In addition, the organisational learning process in BSPA leads to the development of an intrinsically motivated information organisational system that allows for the institutionalisation of the learning process itself in the form of an organisational knowledge management system. This could be a specific application, or something as wide-ranging as an Enterprise Resource Planning (ERP) implementation. Examples of the use of BSPA in two ERP implementations are presented.

Expert System for Decision-Making Problem in Economics

An expert system (ES) is a class of computer programs developed by researchers in artificial intelligence. In essence, they are programs made up of a set of rules that analyze information about a specific class of problems, as well as provide analysis of the problems, and, depending upon their design, recommend a course of user action in order to implement corrections. ES are computerized tools designed to enhance the quality and availability of knowledge required by decision makers in a wide range of industries. Decision-making is important for the financial institutions involved due to the high level of risk associated with wrong decisions. The process of making decision is complex and unstructured. The existing models for decision-making do not capture the learned knowledge well enough. In this study, we analyze the beneficial aspects of using ES for decision- making process.

Building resilience for social-ecological sustainability in Atlantic Europe

This thesis argues that complex adaptive social–ecological systems (SES) theory has important implications for the design of integrated ocean and coastal governance in the EU. Traditional systems of governance have struggled to deal with the global changes, complexity and uncertainties that challenge a transition towards sustainability in Europe’s maritime macro-regions. There is an apparent disconnect between governance strategies for sustainability in Europe’s maritime macro-regions and a sound theoretical basis for them. My premise is that the design of governance architecture for maritime regional sustainability should be informed by SES theory. Therefore, the aim of this research was to gain insight into a multilevel adaptive governance architecture that combines notions of sustainability and development in the context of the Atlantic Europe maritime macro-region. The central research question asked whether it is possible to achieve this insight by using a SES as a framework and analytical tool. This research adopted social ecology and sustainability science as a foundation for understanding society–nature relations. Concepts from complex adaptive systems, SES and resilience theories were integrated into a conceptual framework that guided the investigation and analysis. A study was conducted to conceptualise the European Atlantic social–ecological system (EASES). This was used to represent and understand the Atlantic Europe macro-region as a SES. The study examined the proposition that governance can be focused on building SES resilience to help achieve maritime regional sustainability. A workbook method was developed and used to elicit expert opinion regarding EASES. The study identified sources of resilience and resilience dynamics that require management in the context of multilevel adaptive governance. This research found that the Atlantic Europe macro-region is a key focal level for multilevel adaptive governance architecture. The majority of the findings are specific to Atlantic Europe and not generalisable to other maritime macro-regions in Europe.

Sustainability Evaluation of Green Building Certification Systems

The attention on green building is driven by the desire to reduce a building’s running cost over its entire life cycle. However, with the use of sustainable technologies and more environmentally friendly products in the building sector, the construction industry contributes significantly to sustainable actions of our society. Different certification systems have entered the market with the aim to measure a building’s sustainability. However, each system uses its own set of criteria for the purpose of rating. The primary goal of this study is to identify a comprehensive set of criteria for the measurement of building sustainability, and therefore to facilitate the comparison of existing rating methods. The collection and analysis of the criteria, identified through a comprehensive literature review, has led to the establishment of two additional categories besides the 3 pillars of sustainability. The comparative analyses presented in this thesis reveal strengths and weaknesses of the chosen green building certification systems - LEED, BREEAM, and DGNB.