Diss. (sammanfattning) Stockholm : Karolinska institutet, 2009. / Härtill 4 uppsatser.

Thesis (Ph.D.)--Mississippi State University. Department of Industrial and Systems Engineering. / Title from title screen. Includes bibliographical references.

Αυτή η διδακτορική διατριβή αφορά στην εννοιολογική και λειτουργική ολοκλήρωση των Συστημάτων Υποστήριξης Ομαδικών Αποφάσεων και Διαχείρισης Οργανωσιακής Γνώσης. Η προτεινόμενη προσέγγιση αποτελεί μια καινοτόμο προσπάθεια συγκερασμού και διεύρυνσης των δυνατοτήτων που παρέχονται από υπάρχουσες τεχνικές και των δύο παραπάνω επιστημονικών περιοχών, με στόχο τόσο την πληρέστερη κάλυψη των ολοένα αυξανόμενων αναγκών των χρηστών που εμπλέκονται σε σχετικά προβλήματα, όσο και την αποτελεσματικότερη αξιοποίηση της γνώσης ενός οργανισμού. Λαμβάνοντας υπόψη τη διατυπωμένη ανάγκη για μια ολοκληρωμένη προσέγγιση, η διατριβή επιχειρεί τη σύνθεση αρχών και τεχνικών από διάφορα πεδία έρευνας, υποστηρίζοντας ότι η διαχείριση γνώσης και η λήψη αποφάσεων δε θα πρέπει να αντιμετωπίζονται ως χωριστές διαδικασίες. Προς αυτή την κατεύθυνση, προτείνεται ένα πλαίσιο ολοκλήρωσής τους. Αναγνωρίζοντας ότι σε αυτού του είδους τα περιβάλλοντα σημαντικό ρόλο παίζει η ενεργή συμμετοχή των ληπτών αποφάσεων στις διαδικασίες διανομής της γνώσης, η προτεινόμενη προσέγγιση προτείνει επίσης ένα πλαίσιο ενίσχυσης της συμμετοχής τους στις σχετικές διαδικασίες. Το προτεινόμενο πλαίσιο ολοκλήρωσης υποστηρίζεται από ένα πρωτότυπο εργαλείο λογισμικού, το οποίο αναπτύχθηκε στα πλαίσια της διατριβής. Στο προτεινόμενο εργαλείο, η ολοκλήρωση των διαδικασιών λήψης ομαδικών αποφάσεων και διαχείρισης οργανωσιακής γνώσης επιτυγχάνεται μέσω ενός Γράφου Συζήτησης, ο οποίος απεικονίζει το διάλογο που αναπτύσσεται μεταξύ των εμπλεκομένων στη λήψη μιας απόφασης. Ο βασισμένος σε επιχειρηματολογία διάλογος δομείται και αξιολογείται βάσει κοινά αποδεκτών Πλαισίων Λήψης Αποφάσεων και Μηχανισμών Αξιολόγησης. Οι λειτουργίες του προτεινόμενου εργαλείου, καθώς και η οργάνωση των σχετικών δεδομένων και γνώσης βασίζονται σε ένα πρωτότυπο μοντέλο οντολογίας, το οποίο επίσης αναπτύχθηκε στα πλαίσια της διατριβής. Η συνολική προσέγγιση υποστηρίζει και διευκολύνει τόσο την ομαδική λήψη αποφάσεων, όσο και την απόκτηση, εκμαίευση, επεξεργασία, αποθήκευση και διανομή της οργανωσιακής γνώσης. / Decision making is widely considered as a fundamental organizational activity that comprises a series of knowledge management tasks. Admitting that the quality of a decision depends on the quality of the knowledge used to make it, it has been widely argued that the enhancement of the decision making efficiency and effectiveness is strongly related to the appropriate exploitation of all possible organizational knowledge resources. Taking the above remarks into account, this PhD thesis presents a human-centred, multidisciplinary approach for the integration of Group Decision Support and Organizational Knowledge Management Systems. Towards this end, a conceptual framework that properly interweaves concepts, theories and practices from the Knowledge Management, Argumentation Theory, Decision Making and Multicriteria Decision Aid disciplines is first introduced. Acknowledging that in collaborative settings the decision makers’ active participation in the knowledge sharing processes is of major importance, the proposed approach also introduces a framework for the leveraging of their participation in the related processes. Furthermore, in order to functionally integrate the decision support and knowledge management processes, a software tool that fully supports the above two frameworks was developed. The core component of the proposed tool is a Discourse Graph that serves the visualization of the argumentative discourses taking place between the involved parties. In order to better support decision making, these discourses are structured and evaluated according to a set of commonly accepted Decision Making Frameworks and a set of Scoring Mechanisms that comply with broadly used Multicriteria Decision Aid models and techniques. Being based on a well-defined ontology model, the proposed approach enables the members of a group to collaborate and accomplish a common understanding. Furthermore, it facilitates the capturing of the organizational knowledge in order to augment teamwork in terms of knowledge acquisition, elicitation, processing, storage and sharing, thus further enhancing the decision making quality.

The research presented here attempts to bridge science and policy through the quantification of climate change impacts and the analysis of a science-fed participatory process to face a sustainability challenge in the San Pedro Basin (Arizona). Paper 1 presents an assessment of a collaborative development process of a decision support system model between academia and a multi-stakeholder consortium created to solve water sustainability problems in a local watershed. This study analyzes how science-fed multi-stakeholder participatory processes lead to sustainability learning promoting resilience and adaptation. Paper 2 presents an approach to link an ensemble of global climate model outputs with a hydrological model to quantify climate change impacts in the hydrology of a basin, providing a range of uncertainty in the results. Precipitation projections for the current century from different climate models and IPCC scenarios are used to obtain recharge estimates as inputs to a groundwater model. Quantifying changes in the basin's water budget due to changes in recharge, evapotranspiration (ET) rates are assumed to depend only on groundwater levels. Picking on such assumption, Paper 3 explores the effects of a changing climate on ET. Using experimental eddy covariance data from three riparian sites, it analyzes seasonal controls on ET. An approach to quantify evapotranspiration rates and growing season length under warmer climates is proposed. Results indicate that although atmospheric demand will be greater, increasing pan and reference crop evaporation, ET rates at the studied field sites will remain unchanged due to stomatal regulation. However, the length of the growing season will increase, mainly with an earlier leaf-out and at a lesser level by a delayed growing season end. These findings - implying decreased aquifer recharge, increased riparian water use and a lesser water balance - are very relevant for water management in semi-arid regions. Paper 4, in which I am second author, explores the theory relating changes in area-average and pan evaporation. Using the same experimental data as Paper 3, it corroborates a previous theoretical relationship and discusses the validity of Bouchet's hypothesis.

In this thesis, a framework for market-based resource allocation in manufacturing is developed and described. The most salient feature of the proposed framework is that it builds on a foundation of well-established economic theory and uses the theory to guide both the agent and market design. There are two motivations for introducing the added complexity of the market metaphor into a decision-making environment that is traditionally addressed using monolithic, centralized techniques. First, markets are composed of autonomous, self-interested agents with well defined boundaries, capabilities, and knowledge. By decomposing a large, complex decision problem along these lines, the task of formulating the problem and identifying its many conflicting objectives is simplified. Second, markets provide a means of encapsulating the many interdependencies between agents into a single mechanism—price. By ignoring the desires and objectives of all other agents and selfishly maximizing their own expected utility over a set of prices, the agents achieve a high degree of independence from one another. Thus, the market provides a means of achieving distributed computation. To test the basic feasibility of the market-based approach, a prototype, system is used to generate solutions to small instances of a very general class of manufacturing scheduling problems. The agents in the system bid in competition with other agents to secure contracts for scarce production resources. In order to accurately model the complexity and uncertainty of the manufacturing environment, agents are implemented as decision-theoretic planners. By using dynamic programming, the agents can determine their optimal course of action given their resource requirements. Although each agent-level planning problem (like the global level planning problem) induces an unsolvably large Markov Decision Problem, the structured dynamic programming algorithm exploits sources of independence within the problem and is shown to greatly increase the size of problems that can be solved in practice. In the final stage of the framework, an auction is used to determine the ultimate allocation of resource bundles to parts. Although the resulting combinational auctions are generally intractable, highly optimized algorithms do exist for finding efficient equilibria. In this thesis, a heuristic auction protocol is introduced and is shown to be capable of eliminating common modes of market failure in combinational auctions.

For local authorities to manage land policies effectively data bases of land use information that are current and mirror development on the ground are required. At present local authorities have no mechanisms in place to acquire maintain and spatially link land use information. Detailed land use information is not generally available at the local level. Generally little attention is paid to maintaining the expensive data which is assembled when planning schemes, development plans or projects are prepared. Land use planning has traditionally focussed on the control rather than the facilitation of development. Details of the actual land use on the ground are generally ignored as tariffs for tax purposes are set on the zoning of the land or a flat rate rather than the actual land use. This lack of land use information, which is exacerbated by informal settlement, causes delays in approving new land uses. There is generally no data available for informal areas and land use and tenure is subject to the informal rules that have evolved with such settlements. If these areas are to be included in the formal land management systems, ways of including and maintaining land use information about these settlements must be developed. By reviewing land information theory, the South African legal land development framework and using a small town as a case study, I have shown that provided certain conditions are met a Spatial Decision Support System (SDSS), designed to record and maintain the land use data necessary to support land use planning in both formal and informal contexts, could be a valuable land management tool. Such a system should be implemented in partnership with local communities and should; • support local level land use decision making and regulation • serve as a land management tool to integrate formal and informal communities • have mechanisms to keep land use information current • be transparent about the type of land use information • develop linkages with regional government to provide detailed land information over time. / Thesis (M.Sc.Sur.)-University of Natal, Durban, 2002.

Forecasting systems are usually based on data warehouses for data strorage, and OLAP tools for historical and predictive data visualization. Aggregated predictive data could be modified. Hence, the research issue can be described as the propagation of an aggregate-based modification in hirarchies and dimensions in a data warehouse enironment. Ther exists a great number of research works on related view maintenance problems. However, to our knowledge, the impact of interactive aggregate modifications on raw data was not investigated. This CIFRE thesis is supported by ANRT and the company Anticipeo. The application of Anticipeo is a sales forecasting system that predicts future sales in order to draw appropriate business strategy in advance. By the beginning of the thesis, the customers of Anticipeo were satisfied the precision of the prediction results, but not with the response time. The work of this thesis can be generalized into two parts. The first part consists in au audit on the existing application. We proposed a methodology relying on different technical solutions. It concerns the propagation of an aggregate-based modification in a data warehouse. the second part of our work consists in the proposition of a newx allgorithms (PAM - Propagation of Aggregated-baseed Modification) with an extended version (PAM II) to efficiently propagate in aggregate-based modification. The algorithms identify and update the exact sets of source data anf other aggregated impacted by the aggregated modification. The optimized PAM II version archieves better performance compared to PAM when the use of additional semantics (e.g. dependencies) is possible. The experiments on real data of Anticipeo proved that the PAM algorithm and its extension bring better perfiormance when a backward propagation.

Main reason of this study is to set forth the internal paradox of the basic approach of the artificial intelligence in the medical field to by discussing on the theoretical and application levels and to suggest solutions in theory and practice against that. In order to rule out the internal paradox in the medical decision support systematic, a new medical model is suggested and based on this, concepts such as disease, health, etiology, diagnosis and treatment are questioned. Meanwhile, with the current scientific data, a simple application sample based on how a decision making system which was set up by fuzzy logic and which is based on the perception of human as a complex adaptive system has been explained. Finally, results of the research about accuracy and validity of this application, current improvements based on the current model and the location on the artificial intelligence theory is discussed.

The care of individuals with concerns about development, health, and wellness is often a difficult, complicated task and may rely on a team of diverse caregivers. There are many decisions that caregivers must make to help ensure that the best care and health monitoring are administered. For my dissertation work, I have explored the use of embedded capture and access to support decision-making for caregivers. Embedded capture and access integrates simple and unobtrusive capture and useful access, including trending information and rich data, into existing work practices. I hypothesized that this technology encourages more frequent access to evidence, increased collaboration amongst caregivers, and decisions made with higher confidence. I have explored this technology through real world deployments of new embedded capture and access applications in two domains. For the first domain, I have developed two applications to support decision-making for caregivers administering therapy to children with autism. The first application, Abaris, supports therapists working with a single child in a home setting, and the second application, Abaris for Schools, extends the ideas of Abaris for use in a school setting for many teachers working with multiple children. The second domain I have explored is decision-making for parents of newborn children. In particular, I developed and evaluated embedded capture and access technology to support parents, pediatricians, and secondary childcare providers in making decisions about whether a child s development is progressing normally in order to promote the earlier detection of developmental delays.

An individual s decision to place a close family member in a nursing home is both difficult and crucial. To assist consumers with such a decision, several initiatives have led to the creation of public websites designed to communicate quality indicators for nursing homes. However, a majority of consumers fail to fully utilize this information for various reasons, such as the multidimensionality, complexity, and uncertainty of the information. Some of the difficulties may be alleviated by information visualization (InfoVis) techniques. However, several unsuccessful attempts in applying InfoVis to decision making suggest that a thorough understanding of the user s perspective is necessary. Accordingly, the author has developed an InfoVis tool for the decision domain of choice of a nursing home. First, a framework of overarching InfoVis and decision theories, called the visualized decision making (VDM) framework, has been developed and contextualized within the selection of a nursing home. Second, a decision-support tool using several InfoVis techniques such as the weighting slider bar and the distribution view have been designed for application within the framework, and the designed tool, called VDM, was implemented. Third, VDM was empirically tested through a web-based experiment and follow-up interviews. The results of this study showed that individuals faced with the decision of selecting a nursing home could make fairly high quality decisions when they used VDM. Though the effects of proposed InfoVis techniques were not evident, this study provided the theoretical framework and empirical results which may help other designers of InfoVis techniques because this work addresses several issues consumers face when choosing a nursing home that can be generalized to other decision making contexts.