Στην παρούσα διπλωματική εργασία υλοποιήθηκε ένα ολοκληρωμένο σύστημα απεικόνισης κινδύνων πλημμυρών για τον ποταμό Ευρώτα. Η εργασία χωρίζεται σε δύο ενότητες: την Ενότητα 1, Θεωρητικό Πλαίσιο και την Ενότητα 2, Υλοποίηση. Στην Ενότητα 1 αρχικά παρουσιάζονται κάποια εισαγωγικά στοιχεία. Πιο συγκεκριμένα, δίνεται ο ορισμός της πλημμύρας και των αιτίων που την προκαλούν. Στην συνέχεια γίνεται μία αναφορά σε διαχρονικά προβλήματα και στις έννοιες του κινδύνου και της κρίσης, καθώς επίσης στους τρόπους αντιμετώπισης τους από τους αρμόδιους φορείς. Έπειτα γίνεται μία αναφορά στις σύγχρονες ανάγκες. Συνεχίζουμε με την ανάλυση των αισθητήρων που χρησιμοποιούνται στο ποταμό και πως αξιοποιείται το σύστημα λήψης αποφάσεων. Επίσης αναλύουμε τα γεωγραφικά πληροφοριακά συστήματα, τις αρχιτεκτονικές τους , τον τρόπο ανάπτυξη τους καθώς επίσης και την ανάγκη ύπαρξης τους στο διαδίκτυο. Λίγο πριν τελειώσουμε κάνουμε μία αναφορά στις τεχνολογίες που χρησιμοποιούμε και παραθέτουμε και μερικά στατιστικά στοιχεία .Τέλος δίνουμε μερικά παραδείγματα παρόμοιων έργων και των κυριοτέρων υπηρεσιών που προσφέρουν Στην Ενότητα 2 περιγράφεται η δικτυακή πύλη που υλοποιήθηκε, πληρώντας όλες τις προϋποθέσεις που έχουν τεθεί από την Ενότητα 1. Πιο συγκεκριμένα γίνεται αναφορά στις δικτυακές υπηρεσίες που αναπτύχθηκαν, τον τρόπο που λειτουργούν καθώς επίσης και μερικές φορές επεξηγούνται κάποια σημαντικά κομμάτια κώδικα. / This Diploma Dissertation presents a complete system depiction of dangerous floods for the river Eurotas. The dissertation is separated in two units. In Unit 1 initially are represented certain introductive elements such as the definition and the causes of flood, the use of sensors, the decision support system. Also, we analyze Geographic Information Systems (GIS), their architectures as well as their need of existence in the internet. Finally, we finish with a report in the technologies that we use and mention certain statistical elements. In Unit 2, the network gate that was materialised, filling the conditions that have been placed by Unit 1, is described. Particularly, we give a report in the network services that were developed, the way that they function as well as explanation of certain important code.

Thesis (MTech (Business Information Systems))--Cape Peninsula University of Technology, 2016. / The emergence of big data (BD) has rendered existing conventional business intelligence (BI) tools inefficient and ineffective for real-time decision support systems (DSS). The inefficiency and ineffectiveness is perceived when business users need to make decisions based on stale and sometimes, incomplete data sets, which potentially leads to slow and poor decision making. In recent years, industry and academia have invented new technologies to process BD such as Hadoop, Spark, in-memory databases and NOSQL databases. The appearance of these new technologies have escalated to an extent, that organisations are faced with the challenge of determining most suitable technologies that are appropriate for real-time DSS requirements. Due to BD still being a new concept, there are no standard guidelines or frameworks available to assist in the evaluation and comparing of BD technologies. This research aims to explore factors that influence the selection of technologies appropriate for real-time DSSs in a BD environment. In addition, it further proposes evaluation criteria that can be used to compare and select these technologies. To achieve this aim, a literature analysis to understand the concept of BD, real-time DSSs and related technologies is conducted. Qualitative as well as quantitative research techniques are used after interviews are conducted with BI experts who have BD knowledge and experience. Experimental research in a computer laboratory is also conducted. The purpose of the interviews is to ascertain which technologies are being used for BD analytics and in addition, which evaluation criteria organisations use when choosing such a technology. Furthermore, a comparative computer laboratory experiment is conducted to compare three tools which run on Hadoop namely; Hive, Impala and Spark. The purpose of the experiment is to test if system performance is different for the three tools when analysing the same data set and the same computer resources. The impirical results reveals nine main factors which impact the selection of technologies appropriate for real-time DSS in a BD environment, and ten application independent evaluation criteria. Furthermore, the experiment results indicate that system performance in terms of latency, is significantly different among the three tools compared.

Please read the abstract in the section 00front of this document / Dissertation (MCom (Computer Auditing))--University of Pretoria, 2008. / Accounting / MCom / unrestricted

A consumer health decision support system (CDSS) is being developed at the South African Medical Research Council (MRC). It is a software program intended to help members of the public decide when they may be at risk of some common but serious illnesses like tuberculosis and hypertension. It would be ideal for a public health kiosk or e-health programs of the government. The program has been built as an expert system. Its knowledge base consists of rules which are used in assessing the risk of illness. The rules were given by medical experts who took part in the development of the CDSS. The study proposes a method for the evaluation of the rule base of the CDSS using FCA methods. It is important to evaluate the knowledge base of an expert system, because if its knowledge base is of broad scope and is accurate then it can be expected that the expert system will be good at giving advice and hence potentially useful. FCA is a mathematical framework which can be used to investigate causal relations in data. The study explored its utility in the evaluation of the CDSS knowledge base. FCA implications and the FCA formulation of the JSM method were two FCA methods that were selected. The FCA methods were used to generate rules from actual patient data, and these were compared to the rules initially given by the experts. The motivation to use FCA data analysis as well as experts’ knowledge in the development of the CDSS program is that FCA data analysis may discover some things that the experts may have overlooked. Or at least the experts can review their expertise against actual field data which has been analysed by FCA methods. A system like the CDSS cannot be built using FCA data analysis techniques only, involvement of experts is very important. The two FCA methods were chosen so as to compare their results, and it was also thought that they may perhaps complement each other. Preliminarily it was found that FCA implications and the FCA formulation of the JSM method can be used in the evaluation of the rule base of the CDSS. / Dissertation (MSc (Computer Science))--University of Pretoria, 2008. / Computer Science / unrestricted

One of the most significant keys to value creation comes from placing emphasis on producing knowledge. The production of knowledge must a major part of the production strategy. This study aims to harness the concept of knowledge management (KM) as an essential element in the creation of sustainable competitive advantage for organisations. Accordingly, this research seeks to highlight the concept of knowledge management systems (KMS) as an essential element, in which the decision support system (DSS) and organisational performance (OP) are elements that control the survival of organisations in the marketplace. The industry requires creative thinking to generate innovation, learning and excellence in knowledge cognition and knowledge inertia, as well as knowledge acquisition (KA), and spending in three types of DSS: the group decision support system (GDSS), executive support system (ESS) and the expert system (ES). It also requires investment in experience inertia and in work teams for the purpose of access to cross-pollination of the information between the employees and to find new ideas about the industry. This study aims to investigate the issues and factors which affect the utilisation of KM as a tool for effective decision-making (DM).Therefore, decision models and DSSs which enhance effective utilisation of this approach will be investigated. Accordingly, a conceptual model based on the literature review and consultations with knowledge workers was developed. Studies of collaborating organisations which are active in manufacturing in Iraq and the UK were performed to validate the conceptual model and facilitate exploratory investigation regarding the relationships. Data was collected using personal interviews with managers and knowledge workers at the enterprises, in addition to use of the questionnaire which was distributed to samples within these firms. A case study method was used in the data collection stage. These case studies could also be implemented for the mechanical, systems engineering, and manufacturing industries. This is because the findings have been tested where the primary objectives of this study investigate KM gaps in the manufacturing industries generally. This study has also addressed the examined objectives by providing an explanation of several issues, identifying the key sources of KM and the corresponding factors. According to the study, KM is found to occur most strongly over the stages of manufacturing and on which high level KM mainly occurs. Furthermore, this study ties together the concepts of KM, DSS and performance as a way of creating sustinable competitive advantage for the firms. Similarly, the study examines the current use of KM tools and assesses the most prominent methods. This study explores the role of KM in industrial firms and the limitation of obstacles to avoid the gaps. Thus, this study proposes a businesslike framework and creative method, explaining comprehensively how KM must adjust in order to align employees' ideas with the firm's larger goals effectively and strategically, which will reduce the lack of harmonisation between the polarisation and implementation of KMS to those firms. The study identifies high correlation between KM and OP, in addition to identifying high correlation between computer-based DSS and OP.

Call number: LD2668 .T4 1979 F37 / Master of Business Administration

Statement of the problem: The risk-benefit profile of warfarin anticoagulation in hemodialysis (HD) patients differs compared to the non-HD population. Computerized decision support systems (CDSS) to assist with anticoagulation management are safe and effective in the non-HD population but had not previously been studied in HD outpatients. Methods of investigation: A before – after study compared anticoagulation control during pre-existing, nephrologist-led anticoagulation management to that following implementation of a pharmacist-led, CDSS-assisted strategy, in HD patients on warfarin at The Ottawa Hospital. Results: Forty-two patients were included. Following implementation of the CDSS-assisted strategy, median time-in-range increased by 3.7% (IQR, -9.5% - 20.6%; p = 0.247). Median frequency of INR tests per day decreased: -0.040 (IQR, -0.074 to –0.0008; P = 0.0001). Adverse events were similar. Conclusion: A CDSS-assisted strategy for anticoagulation management in HD patients is effective, safe and may lead to cost savings related to less frequent INR testing.

Please read the abstract in the section 00front of this document / Thesis (DCom (Financial Management))--University of Pretoria, 2006. / Financial Management / unrestricted

Since much more than the implementation of IT solutions is frequently required to produce actionable intelligence output, the unlocking of actionable Business Intelligence (BI) for decision-making based on both internal and external information sources, is proving to be a real challenge for SA banking institutions. Although all the major banking institutions in South Africa produce and use BI in some form or the other, the concept is often not clearly defined, and not enough emphasis is placed on the use of recognized intelligence processes to provide intelligence output that is both accurate and actionable. The aim of this research was to determine whether SA banking institutions applied recognized intelligence processes, or components thereof, while conducing BI assignments. Whilst the typical four- or five-stage intelligence process, as discussed in BI literature, was commonly accepted by the banking institutions that participated in this research as a benchmark in conducting BI, the researcher established that these institutions placed more emphasis on executing some stages, whilst other stages were executed in an ad hoc manner. In this regard it was found that, while emphasis was placed on the collection stage of the BI process during the ‘analysis stage’, which is one of the most important stages of the process, no specific step-by-step procedure was followed. In the analysis stage of the process, emphasis was typically placed on the application of the specific methods of analysis. In the stages of the BI processes that deal with BI requirements definition and dissemination of BI products, formal BI processes were also found to be lacking. This prompted the researcher to suggest a practical step-by-step process for dealing with each stage of the BI process. In the final chapter of this dissertation, the researcher provides a summary of the key findings in relation to the research problem and identifies a number of areas in which further research should be conducted. Finally, it is important to note that BI will remain a critical business issue for SA banking institutions in their efforts to become more profitable, more customer centred, and ultimately more competitive in the face of dynamic and challenging market conditions. In this regard BI processes provide a critical framework for the conduct of BI assignments in SA banking institutions. he full text of this thesis/dissertation is not available online. Please contact us if you need access Since much more than the implementation of IT solutions is frequently required to produce actionable intelligence output, the unlocking of actionable Business Intelligence (BI) for decision-making based on both internal and external information sources, is proving to be a real challenge for SA banking institutions. Although all the major banking institutions in South Africa produce and use BI in some form or the other, the concept is often not clearly defined, and not enough emphasis is placed on the use of recognized intelligence processes to provide intelligence output that is both accurate and actionable. The aim of this research was to determine whether SA banking institutions applied recognized intelligence processes, or components thereof, while conducing BI assignments. Whilst the typical four- or five-stage intelligence process, as discussed in BI literature, was commonly accepted by the banking institutions that participated in this research as a benchmark in conducting BI, the researcher established that these institutions placed more emphasis on executing some stages, whilst other stages were executed in an ad hoc manner. In this regard it was found that, while emphasis was placed on the collection stage of the BI process during the ‘analysis stage’, which is one of the most important stages of the process, no specific step-by-step procedure was followed. In the analysis stage of the process, emphasis was typically placed on the application of the specific methods of analysis. In the stages of the BI processes that deal with BI requirements definition and dissemination of BI products, formal BI processes were also found to be lacking. This prompted the researcher to suggest a practical step-by-step process for dealing with each stage of the BI process. In the final chapter of this dissertation, the researcher provides a summary of the key findings in relation to the research problem and identifies a number of areas in which further research should be conducted. Finally, it is important to note that BI will remain a critical business issue for SA banking institutions in their efforts to become more profitable, more customer centred, and ultimately more competitive in the face of dynamic and challenging market conditions. In this regard BI processes provide a critical framework for the conduct of BI assignments in SA banking institutions. / Dissertation (MA)--University of Pretoria, 2003. / Information Science / unrestricted

Software agents have been heralded as the most important emerging technology of the decade. As software development firms eagerly attempt to integrate these autonomous programs into their products, researchers attempt to define the concept of agency and to develop architectures that will improve agent capabilities. Decision Support System (DSS) researchers have been eager to integrate agents into their applications, and exploratory works in which agents have been used within a DSS have been documented. This dissertation attempts to further this exploration by studying the agent features and underlying architectures that can lead to the successful integration of agents in DSS. This exploration is carried out in three parts. In the first part, a review of the relevant research streams is provided. The history and current status of software agents is first discussed. Similarly, a historical and current view of DSS research is provided. Lastly, a historical and tutorial-type of discussion is provided on the topic of Artificial Intelligence (AI) planning. This review of the relevant literature provides a general background for the conceptual analyses and implementations that are carried out in the next two sections. In the second part, the literature on software agents is synthesized to develop a definition of agency applicable to DSS. Using this definition, an agent-integrated DSS that supports variance-analysis is designed and developed. Following this implementation, a general framework for agent-enabling DSS is suggested. The use of this framework promises to raise some DSS to a new level of capability whereby "what-if" systems are transformed into real-time, proactive systems. The third part utilizes this general framework to agent-enable a corporate-planning system DSS and extends the framework in the second section through the introduction of an automated-planning agent. The agent uses AI planning to generate decision-making alternatives, providing a means to integrate and sequence the models in the DSS. The architecture used to support this planning agent is described. This new kind of DSS enables not only the monitoring of goals, but also the maintenance of these goals through agent-generated plans. The conclusion summarizes the contributions of this work and outlines in considerable detail potential research opportunities in the realm of software agents, DSS, and planning. / Ph. D.