The difficulty of projecting ecological impacts, as well as the increasing familiarity of planners with Geographical Information Systems and other software technology has led to an increase in the use of Planning Support Systems (PSS) by city and regional planners. Due to their newness and rapid development, there is, of yet, a lack of a comprehensive peer-reviewed literature on the design and implementation of these systems. This thesis proposes and applies a rating framework for PSS in order to facilitate accessibility to and critical investigation of PSS. The rating framework’s criteria are based on the “seven sins” of comprehensive land use models identified by Douglass Lee’s 1973 article “Requiem for Large-Scale Models." / text

There has been increasing research interest in recent years in using the power of computers to support group work. There have been two main areas of research: experimental research into GDSS supported group work in laboratory settings, and research designed to develop GDSSs which are effective, efficient and acceptable to their users. However, there have been some contradictory findings from these two areas of research. The developmental effort has shown great promise in relatively controlled developmental settings. At the same time, experimental research has indicated that GDSSs may not provide the hoped for increases in effectiveness and efficiency while being accepted by their users. This study has attempted to clarify this situation by using a field study to assess the implementation of a GDSS in an operational environment. The setting for this study was a large engineering and manufacturing site of a large electronics company. A GDSS which had been developed at the University of Arizona was installed at the host company's site, and it was assessed for the first nine months of its use. Results indicate that the system was perceived to be effective, efficient and acceptable for use by its intended users.

The purpose of greenhouse crop systems is to generate a high quality product at high production rates, consistently, economically, efficiently and in a sustainable way. To achieve this level of productivity, accurate monitoring and control of some processes of the entire biophysical system must be implemented. In addition, the proper selection of actions at the strategic, tactical and operational management levels must be implemented.Greenhouse management relies largely on human expertise to adjust the appropriate optimum values for each of the production and environmental parameters, and most importantly, to verify by observation the desired crop responses. The subjective nature of observing the plant responses, directly affects the decision-making process (DMP) for selecting these `optimums'. Therefore, in this study several decision support systems (DSS) were developed to enhance the DMP at each of the greenhouse managerial levels.A dynamic greenhouse environment model was implemented in a Web-based interactive application which allowed for the selection of the greenhouse design, weather conditions, and operational strategies. The model produced realistic approximations of the dynamic behavior of greenhouse environments for 28-hour simulation periods and proved to be a valuable tool at the strategic and operational level by evaluating different design configurations and control strategies.A Web-based crop monitoring system was developed for enhancing remote diagnosis. This DSS automatically gathered and presented graphically environmental data and crop-oriented parameters from several research greenhouses. Furthermore, it allowed for real-time visual inspection of the crop.An intelligent DSS (i-DSS) based on crop records and greenhouse environment data from experimental trials and from commercial operations was developed to characterize the growth-mode of tomato plants with fuzzy modeling. This i-DSS allowed the discrimination of "reproductive", "vegetative" and "balanced" growth-modes in the experimental systems, and the seasonal growth-mode variation on the commercial application.An i-DSS based on commercial operation data was developed to predict the weekly fluctuations of harvest rates, fruit size and fruit developing time with dynamic neural networks (NN). The NN models accurately predicted weekly and seasonal fluctuations of each variable, having correlation coefficients (R) of 0.96, 0.87 and 0.94 respectively, when compared with a dataset used for independent validation.

This thesis is focusing on designing a DSS to facilitate Human Resource Management decisions for the Hellenic Navy. A mathematical, multi-criteria optimization model was designed and a software environment implemented employing this model to make job assignment decisions. The rationale was to develop a software solution able to adapt in the most automated way possible to different issues concerning HRM. Assigning HRM resources in an optimal way while considering multiple criteria is a very difficult task. There are many attributes to be taken into account some of which contradict each other. The human mind has limitations when dealing with multi attribute problems and the associated set of multiple tradeoffs. Providing a mathematical solution to the problem with the ability to evaluate tradeoffs could provide useful insight to decision makers and help reduce bias in the overall HRM assignment process. Design and implementation of such a system is the purpose of this thesis.

<p>Human use of the oceans is increasingly in conflict with conservation of endangered species. Methods for managing the spatial and temporal placement of industries such as military, fishing, transportation and offshore energy, have historically been post hoc; i.e. the time and place of human activity is often already determined before assessment of environmental impacts. In this dissertation, I build robust species distribution models in two case study areas, US Atlantic (Best et al. 2012) and British Columbia (Best et al. 2015), predicting presence and abundance respectively, from scientific surveys. These models are then applied to novel decision frameworks for preemptively suggesting optimal placement of human activities in space and time to minimize ecological impacts: siting for offshore wind energy development, and routing ships to minimize risk of striking whales. Both decision frameworks relate the tradeoff between conservation risk and industry profit with synchronized variable and map views as online spatial decision support systems.</p><p>For siting offshore wind energy development (OWED) in the U.S. Atlantic (chapter 4), bird density maps are combined across species with weights of OWED sensitivity to collision and displacement and 10 km2 sites are compared against OWED profitability based on average annual wind speed at 90m hub heights and distance to transmission grid. A spatial decision support system enables toggling between the map and tradeoff plot views by site. A selected site can be inspected for sensitivity to a cetaceans throughout the year, so as to capture months of the year which minimize episodic impacts of pre-operational activities such as seismic airgun surveying and pile driving.</p><p>Routing ships to avoid whale strikes (chapter 5) can be similarly viewed as a tradeoff, but is a different problem spatially. A cumulative cost surface is generated from density surface maps and conservation status of cetaceans, before applying as a resistance surface to calculate least-cost routes between start and end locations, i.e. ports and entrance locations to study areas. Varying a multiplier to the cost surface enables calculation of multiple routes with different costs to conservation of cetaceans versus cost to transportation industry, measured as distance. Similar to the siting chapter, a spatial decisions support system enables toggling between the map and tradeoff plot view of proposed routes. The user can also input arbitrary start and end locations to calculate the tradeoff on the fly.</p><p>Essential to the input of these decision frameworks are distributions of the species. The two preceding chapters comprise species distribution models from two case study areas, U.S. Atlantic (chapter 2) and British Columbia (chapter 3), predicting presence and density, respectively. Although density is preferred to estimate potential biological removal, per Marine Mammal Protection Act requirements in the U.S., all the necessary parameters, especially distance and angle of observation, are less readily available across publicly mined datasets.</p><p>In the case of predicting cetacean presence in the U.S. Atlantic (chapter 2), I extracted datasets from the online OBIS-SEAMAP geo-database, and integrated scientific surveys conducted by ship (n=36) and aircraft (n=16), weighting a Generalized Additive Model by minutes surveyed within space-time grid cells to harmonize effort between the two survey platforms. For each of 16 cetacean species guilds, I predicted the probability of occurrence from static environmental variables (water depth, distance to shore, distance to continental shelf break) and time-varying conditions (monthly sea-surface temperature). To generate maps of presence vs. absence, Receiver Operator Characteristic (ROC) curves were used to define the optimal threshold that minimizes false positive and false negative error rates. I integrated model outputs, including tables (species in guilds, input surveys) and plots (fit of environmental variables, ROC curve), into an online spatial decision support system, allowing for easy navigation of models by taxon, region, season, and data provider.</p><p>For predicting cetacean density within the inner waters of British Columbia (chapter 3), I calculated density from systematic, line-transect marine mammal surveys over multiple years and seasons (summer 2004, 2005, 2008, and spring/autumn 2007) conducted by Raincoast Conservation Foundation. Abundance estimates were calculated using two different methods: Conventional Distance Sampling (CDS) and Density Surface Modelling (DSM). CDS generates a single density estimate for each stratum, whereas DSM explicitly models spatial variation and offers potential for greater precision by incorporating environmental predictors. Although DSM yields a more relevant product for the purposes of marine spatial planning, CDS has proven to be useful in cases where there are fewer observations available for seasonal and inter-annual comparison, particularly for the scarcely observed elephant seal. Abundance estimates are provided on a stratum-specific basis. Steller sea lions and harbour seals are further differentiated by ‘hauled out’ and ‘in water’. This analysis updates previous estimates (Williams & Thomas 2007) by including additional years of effort, providing greater spatial precision with the DSM method over CDS, novel reporting for spring and autumn seasons (rather than summer alone), and providing new abundance estimates for Steller sea lion and northern elephant seal. In addition to providing a baseline of marine mammal abundance and distribution, against which future changes can be compared, this information offers the opportunity to assess the risks posed to marine mammals by existing and emerging threats, such as fisheries bycatch, ship strikes, and increased oil spill and ocean noise issues associated with increases of container ship and oil tanker traffic in British Columbia’s continental shelf waters.</p><p>Starting with marine animal observations at specific coordinates and times, I combine these data with environmental data, often satellite derived, to produce seascape predictions generalizable in space and time. These habitat-based models enable prediction of encounter rates and, in the case of density surface models, abundance that can then be applied to management scenarios. Specific human activities, OWED and shipping, are then compared within a tradeoff decision support framework, enabling interchangeable map and tradeoff plot views. These products make complex processes transparent for gaming conservation, industry and stakeholders towards optimal marine spatial management, fundamental to the tenets of marine spatial planning, ecosystem-based management and dynamic ocean management.</p> / Dissertation

Medication management constitutes a large part of registered nurses' (RNs) daily work in municipal elderly care. They are responsible for monitoring multimorbid older persons with extensive treatments, and they often work alone, without daily access to physicians. RNs’ drug monitoring is, in this thesis, based on the concept of pharmacovigilance. Pharmacovigilance is about the science and the activities that aim to improve patient care and safety in drug use, that is, to detect, assess, understand and prevent drug-related problems. The overall aim was to explore conditions for pharmacovigilance from a nursing perspective, focusing on implications of RNs’ competence and use of a computerized decision support system (CDSS). Both quantitative and qualitative research methods were used, including a questionnaire (I), focus group discussions (II), individual interviews (III) and an intervention study (IV). In total 216 RNs and 54 older persons participated from 13 special accommodations, located in three different regions. RNs who had completed further training in pharmacovigilance rated their medication competence higher than those who had not. However, there was no difference between groups in the number of pharmacovigilant activities they performed in clinical practice (I). The RNs appeared to act as “vigilant intermediaries” in drug treatment. They depended on the nursing staff's observations of drug-related problems. The RNs continuously controlled the work of staff and physicians, and attempted to compensate for shortcomings in competence, accessibility and continuity (II). RNs’ use of a CDSS was found to affect drug monitoring, including aspects of time, responsibility, standardization of the work, as well as access to knowledge and opportunities for evidence-based care (III). The CDSS detected significantly more drug-related problems when conducting medication reviews, than the RNs did. Nevertheless, this did not result in any significant improvement in the quality of drug use in the follow up, three and six months later (IV). This thesis contributes to the recognition of pharmacovigilance from a nursing perspective. Increased medication competence seems to be insufficient to generate pharmacovigilant activities. RNs depend on other health care professionals and organizational conditions in order to perform their work. A CDSS has the potential to support RNs, both in structured medication reviews and in daily clinical practice. Inter-professional collaboration is crucial, with or without a CDSS, and the entire team needs to be aware of and take responsibility. Other important conditions is the existence of well-functioning communication channels, competence across the team, and established procedures based on current guidelines.

Responsável pela recuperação de dados a partir de várias fontes, por analisar e dar apoio à decisão através de procedimentos computacionais e análises estatísticas, Analytics vem conquistando grande interesse da comunidade científica e também no atual mercado de negócios. Através da enorme oferta de ferramentas tecnológicas e do grande entusiasmo relacionado com a evolução das tecnologias da informação, a implementação de Analytics, na ausência de planejamento estruturado pode ocasionar baixo desempenho do projeto e agregar pouco valor ao negócio, apo ponto de trazer prejuízos para a organização. Esta pesquisa tem como objetivo investigar os fatores críticos deste tipo de implementação na literatura científica e analisar como estes se manifestam nas organizações. A pesquisa constrói um quadro teórico conceitual a partir da revisão de literatura do tema para a análise da evolução deste nas discussões acadêmicas, através da aplicação de análises bibliométricas. Fatores são selecionados com base na literatura, referentes ao sucesso da implementação de Analytics relacionados aos sistemas de apoio à decisão, sendo divididos em construtos de Gestão de Negócios e Tecnologia da Informação. A pesquisa qualitativa, através do uso do método de estudo de caso, analisou quatro organizações de diferentes segmentos e projetos de implementação de soluções de Analytics. O trabalho conclui que há aderência aos fatores depreendidos da literatura e que haja reações distintas do alinhamento da Tecnologia da Informação com a estratégia do negócio de acordo com o tipo de solução implementada na organização. / Responsible for retrieving data from several fonts, for analyzing and providing support decision through computational procedures and statistical and for descriptive and predictive analysis, Analytics has been achieving great interest from scientific community and in the today\'s business market. Through the huge offer of technological tools and the great enthusiasm related to the information technology evolution, the implementing of Analytics in the absence of structured planning may cause low performance of the project and add low value to the business, and even bring loss to the organization. This research aims to investigate the critical actors of this kind of implementing and evaluate how they manifest on organizations. The methodology adopted focus on conceptual theoretical model built from the literature review followed by the analysis of the evolution of the topic in academic discussions through a bibliometric analysis application. Several factors are selected based on scientific production, all related to the success of implementing Analytics based on knowledge from other decision support system literature, divided in two constructs, Business Management and Information Technology. The qualitative research, with the use of case study method, analyzed four organizations from distinct market and products, as well as distinct Analytics implementation projects. The research concludes that there are strong relationship between the factors extracted from literature and shows that there are dissimilar reactions regarding the alignment between Information Technology and the business\' strategy, being related to the type of Analytics solution implemented in the organization.

O objeto deste trabalho é a análise do aproveitamento múltiplo do reservatório de Barra Bonita, localizado na confluência entre os rios Piracicaba e Tietê, no estado de São Paulo e pertencente ao chamado sistema Tietê-Paraná. Será realizada a otimização da operação do reservatório, através de programação linear, com o objetivo de aumentar a geração de energia elétrica, através da maximização da vazão turbinada. Em seguida, a partir dos resultados da otimização da geração de energia, serão utilizadas técnicas de simulação computacional, para se obter índices de desempenho conhecidos como confiabilidade, resiliência e vulnerabilidade, além de outros fornecidos pelo próprio modelo de simulação a ser utilizado. Estes índices auxiliam a avaliação da freqüência, magnitude e duração dos possíveis conflitos existentes. Serão analisados os possíveis conflitos entre a navegação, o armazenamento no reservatório, a geração de energia e a ocorrência de enchentes na cidade de Barra Bonita, localizada a jusante da barragem. / The aim of this study is to analyze the multiple use of the Barra Bonita reservoir, which is located in the confluence of the Piracicaba river and the Tietê river, in the state of São Paulo, and belongs to the called Tietê-Paraná system. The reservoir operation will be optimized, through linear programming, aiming to increase the hydropower generation, by maximizing the water flow through turbines. In sequence, on the hydropower generation optimization results, computer simulation techniques will be used, in order to obtain performance rates as reliability, resilience and vulnerability, in addiction to other rates provided by the simulation model itself. These rates can assist to evaluate the frequency, the magnitude and the duration of possible conflicts that may occur. The navigation, the water storage in the reservoir, the hydropower generation and the occurrence of floods in Barra Bonita, a city located downstream the dam, will be analyzed.

Submitted by Jaqueline Silva (jtas29@gmail.com) on 2014-09-04T19:36:30Z No. of bitstreams: 2 Walid Abdala Rfaei Jradi.pdf: 10830820 bytes, checksum: 605fdfee3d5d31cec3e54ce425a7ab68 (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) / Made available in DSpace on 2014-09-04T19:36:30Z (GMT). No. of bitstreams: 2 Walid Abdala Rfaei Jradi.pdf: 10830820 bytes, checksum: 605fdfee3d5d31cec3e54ce425a7ab68 (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) Previous issue date: 2008-09-23 / The present work proposes an architecture of a Decision Support System for modelling, simulating and visualizing urban traffic, using a mathematical model adjusted to the reality of the Brazilian transit, as well as an appropriate choice of data for this context. To prove the viability of the architecture, an interactive tool, called PET-Gyn, was implemented, with a Web graphical interface. The simulation of the traffic was based on algorithms already existing in the literature, with proven effectiveness, but with adaptations that had been shown necessary. The data applied to the urban traffic is composed of information obtained from GoogleMaps API, data on the road mesh and the collection of the traffic demands measured in a region of the city of Goiânia-GO. The tool allows the visualization of basic information about the traffic in a city and offers forms of interaction to simulate the effect of possible reorganizations of the road net. / O presente trabalho propõe uma arquitetura de Sistema de Apoio à Decisão para modelar, simular e visualizar o tráfego urbano, usando um modelo matemático adequado à realidade do trânsito brasileiro, bem como uma modelagem de dados apropriada a esse contexto. Para comprovar a viabilidade da arquitetura, foi implementado uma ferramenta interativa, chamada PET-Gyn, com interface gráfica para a Web. A simulação do tráfego foi baseada em algoritmos existentes na literatura de comprovada eficácia, mas com adaptações que se mostraram necessárias. A modelagem de dados aplicada ao tráfego urbano é composta de informações retiradas da API do GoogleMaps, de dados sobre a malha viária e da coleta das demandas de tráfego medido em uma região da cidade de Goiânia-GO. A ferramenta permite a visualização de informações básicas sobre o tráfego em uma cidade e oferece formas de interação para simular o efeito de possíveis reestruturações da rede viária.

O objeto deste trabalho é a análise do aproveitamento múltiplo do reservatório de Barra Bonita, localizado na confluência entre os rios Piracicaba e Tietê, no estado de São Paulo e pertencente ao chamado sistema Tietê-Paraná. Será realizada a otimização da operação do reservatório, através de programação linear, com o objetivo de aumentar a geração de energia elétrica, através da maximização da vazão turbinada. Em seguida, a partir dos resultados da otimização da geração de energia, serão utilizadas técnicas de simulação computacional, para se obter índices de desempenho conhecidos como confiabilidade, resiliência e vulnerabilidade, além de outros fornecidos pelo próprio modelo de simulação a ser utilizado. Estes índices auxiliam a avaliação da freqüência, magnitude e duração dos possíveis conflitos existentes. Serão analisados os possíveis conflitos entre a navegação, o armazenamento no reservatório, a geração de energia e a ocorrência de enchentes na cidade de Barra Bonita, localizada a jusante da barragem. / The aim of this study is to analyze the multiple use of the Barra Bonita reservoir, which is located in the confluence of the Piracicaba river and the Tietê river, in the state of São Paulo, and belongs to the called Tietê-Paraná system. The reservoir operation will be optimized, through linear programming, aiming to increase the hydropower generation, by maximizing the water flow through turbines. In sequence, on the hydropower generation optimization results, computer simulation techniques will be used, in order to obtain performance rates as reliability, resilience and vulnerability, in addiction to other rates provided by the simulation model itself. These rates can assist to evaluate the frequency, the magnitude and the duration of possible conflicts that may occur. The navigation, the water storage in the reservoir, the hydropower generation and the occurrence of floods in Barra Bonita, a city located downstream the dam, will be analyzed.