Seja por meio de novas metodologias, por novas ferramentas, ou pela simples presença nas salas de aula, as Tecnologias de Informação e Comunicação estão alterando profundamente as práticas educativas. Este trabalho se debruça sobre a interação entre as teorias de aprendizagem e as diferentes ferramentas computacionais para educação. Apontando uma incompatibilidade metodológica entre os modelos de avaliação do aluno existentes em Learning Management Systems e em ontologias computacionais frente a metodologias de ensino cognitivistas, propõe-se um novo modelo computacional de avaliação para representar aspectos cognitivos e comportamentais dos alunos. Chamado de grafos de avaliação, é um modelo baseado na área de sistemas de suporte à tomada de decisões em grupo, desenvolvida usando uma metodologia orientada ao consenso junto ao Projeto Amora do Colégio de Aplicação da UFRGS. Espera-se que esse trabalho possa servir de base para a construção de ferramentas de avaliação computacional adequadas para essas metodologias. / Through the use of new methodologies and tools, or by its simple presence in classrooms, Information and Communication Technologies are radically changing educational practices. In this context, this work focuses on issues manifested in computational tools through the scope of different learning theories. It points out a methodological incompatibility among traditional student assessment tools available in current Learning Management Systems and some Computational Ontologies concerning cognitivist learning theories. Therefore, a new computational technique is proposed to evaluate cognitive and behavioral aspects of students. Called evaluation graphs, it is a Decision Support System developed as a consensus-driven methodology to be used in the AMORA project that is being conducted in the application school at UFRGS. It is expected that this new model will serve as the basis to build new student assessment tools compatible with these methodologies.

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.

The environmental uncertainty of federal politics and acquisition outsourcing in competitive markets requires an adaptive decision-analysis structure. Practitioners oriented toward exclusively static methods face severe challenges in understanding qualitative aspects of organizational governance. The purpose of this grounded theory study was to examine and understand behavioral relationship attributes within intuitive, choice, judgment, or preference decision-making processes. The problem addressed in this study was the detrimental effects of organizational citizenship behavior (OCB), compulsory citizenship behavior (CCB), and social exchange theory (SET) on the acquisition management relationship The OCB, CCB, SET dictates that sound business development, relationship acumen, emotional intelligence and perceptiveness transcend pure numerical quantification. Exhibition of relationship-based attributes influence and drive long-term contractual relationships and the sustainability of business organizations. The data collected included historical data and survey responses. Approximately 34,000 acquisition professionals comprised the population-sampling frame. The study sample consisted of 378 survey responses that yielded 294 qualifying respondents with 94 disqualifications that produced a 78% response rate. The Carnegie-Mellon behavioral survey guidelines underpinned questionnaire construction and affirmation of themes. Strauss and Corbin grounded theory and theme generation addressed behavioral decision making under the additive model that inform the development of an organizational social operations and business framework that accounts for intuitive judgment. The study may contribute to positive social change by orienting managers toward behavioral decision making, ensuring responsiveness to the public and federal governance

Architecting e-business applications is a complex design activity. This is mainly due to the numerous architectural decisions to be made, including the selection of alternative technologies, software components, design strategies, patterns, standards, protocols, platforms, etc. Further complexities arise due to the fact that these alternatives often vary considerably in their support for different quality attributes. Moreover, there are often different groups of stakeholders involved, with each having their own quality goals and criteria. Furthermore, different architectural decisions often include interdependent alternatives, where the selection of one alternative for one particular decision impacts the selections to be made for alternatives from other different decisions. There have been several research efforts aiming at providing sufficient mechanisms and tools for facilitating the architectural evaluation and design process. These approaches, however, address architectural decisions in isolation, where they focus on evaluating a limited set of alternatives belonging to one architectural decision. This has been the primary motivation behind the development of the Architectural DEcision-Making Support (ADEMS) framework, which basically aims at supporting stakeholders and architects during the architectural decision-making process by helping them determining a suitable combination of architectural alternatives. ADEMS framework is an iterative process that leverages rigorous quantitative decision-making techniques available in the literature of Management Science, particularly Multiple Attribute Decision-Making (MADM) methods and Integer Programming (IP). Furthermore, due to the number of architectural decisions involved as well as the variety of available alternatives, the architecture design space is expected to be huge. For this purpose, a query language has been developed, known as the Architecture Query Language (AQL), to aid architects in exploring and analyzing the design space in further depth, and also in examining different ???what-if??? architectural scenarios. In addition, in order to support leveraging ADEMS framework, a support tool has been implemented for carrying out the sophisticated set of mathematical computations and comparisons of the large number of architectural combinations, which might otherwise be hard to conduct using manual techniques. The primary contribution of the tool is in its help to identify, evaluate, and rank all potential combinations of alternatives based on their satisfaction to quality preferences provided by the different stakeholders. Finally, to assess the feasibility of ADEMS, three different case studies have been conducted relating to the architectural evaluation of different e-business and enterprise applications. Results obtained for the three case studies were quite positive as they showed an acceptable accuracy level for the decisions recommended by ADEMS, and at a reasonable time and effort costs for the different system stakeholders.

In this study, four real-life problem situations were used to explore the challenges of developing and implementing decision support tools for planning and management within an urban water utility. The study sought to explore how the degree of adoption of formal decision support tools in practice, generally perceived to be low, could be improved. In the study, an Action Research (AR) approach was used. AR is an inquiry process that involves partnership between researchers and practitioners for the purpose of addressing a real-life problem issue, while simultaneously generating scientific knowledge. Unlike other research methods where the researcher seeks to study organizational phenomena but not to change them, the action researcher attempts to create organizational change and simultaneously to study the process. During the study, a number of prototype data management tools were developed. GIS-based spatial analysis and visualisation tools were extensively used to inform and enhance the processes of participatory problem identification and structuring, while a number of modelling tools were applied in the generation and evaluation of alternative solutions. As an outcome of the study, a prototype framework for the application of decision support tools within an urban water supply planning and management context was proposed. The study highlighted the challenges of embedding formal decision support processes within existing work systems in organizations, and recommendations were made on how best to achieve this. The AR approach was found to be useful in bridging the gap between academic research and technological practice, supporting the development of computerised planning and decision support tools of practical benefit to organizations. / QC 20100723

We investigate the unsupervised K-means clustering and the semi-supervised hidden Markov model (HMM) to automatically detect anomalous motion patterns in groups of people (crowds). Anomalous motion patterns are typically people merging into a dense group, followed by disturbances or threatening situations within the group. The application of K-means clustering and HMM are illustrated with datasets from four surveillance scenarios. The results indicate that by investigating the group of people in a systematic way with different K values, analyze cluster density, cluster quality and changes in cluster shape we can automatically detect anomalous motion patterns. The results correspond well with the events in the datasets. The results also indicate that very accurate detections of the people in the dense group would not be necessary. The clustering and HMM results will be very much the same also with some increased uncertainty in the detections. / <p>Funding Agencies|Vinnova (Swedish Governmental Agency for Innovation Systems) under the VINNMER program||</p>

Breaking Through the First Cost Barriers of Sustainable Planning, Design, and Construction John W. Mogge Jr. 377 Pages Directed by Dr. Rita Oberle The research integrates elements of the bodies of knowledge for sustainability, planning, design, and construction to create an understanding of green project first cost drivers. It extends conceptual models for sustainable infrastructure and the built environment process by creating a framework based linkage to analyze first cost impacts of sustainable project planning, design, and construction decisions. The framework functions as an analytical bridge between the built environment process and sustainability and is the principal contribution of this research. Through a preliminary analysis of fourteen projects, the work draws out relevant planning, materials and methods, and estimating and scheduling best practices and guiding principles. The work then proposes a first cost impact framework derived from the preliminary analysis as a decision support tool and tests the framework using an expert system derived linguistic database. The test results support the functionality of the framework. The test linguistic database was developed through an interdisciplinary professional expert practitioner interview process using common green project planning, design and construction strategies. The qualitative, interpretative, multi-criteria analysis of the data used fuzzy set theory and presents findings helpful in understanding green project first cost drivers. The work concludes with an assessment and a discussion of parallel research, and ten recommended areas for further research.

This thesis focuses on the developing of statistical methodology in reliability and quality engineering, and to assist the decision-makings at enterprise level, process level, and product level. In Chapter II, we propose a multi-level statistical modeling strategy to characterize data from spatial logistics systems. The model can support business decisions at different levels. The information available from higher hierarchies is incorporated into the multi-level model as constraint functions for lower hierarchies. The key contributions include proposing the top-down multi-level spatial models which improve the estimation accuracy at lower levels; applying the spatial smoothing techniques to solve facility location problems in logistics. In Chapter III, we propose methods for modeling system service reliability in a supply chain, which may be disrupted by uncertain contingent events. This chapter applies an approximation technique for developing first-cut reliability analysis models. The approximation relies on multi-level spatial models to characterize patterns of store locations and demands. The key contributions in this chapter are to bring statistical spatial modeling techniques to approximate store location and demand data, and to build system reliability models entertaining various scenarios of DC location designs and DC capacity constraints. Chapter IV investigates the power law process, which has proved to be a useful tool in characterizing the failure process of repairable systems. This chapter presents a procedure for detecting and estimating a mixture of conforming and nonconforming systems. The key contributions in this chapter are to investigate the property of parameter estimation in mixture repair processes, and to propose an effective way to screen out nonconforming products. The key contributions in Chapter V are to propose a new method to analyze heavily censored accelerated life testing data, and to study the asymptotic properties. This approach flexibly and rigorously incorporates distribution assumptions and regression structures into estimating equations in a nonparametric estimation framework. Derivations of asymptotic properties of the proposed method provide an opportunity to compare its estimation quality to commonly used parametric MLE methods in the situation of mis-specified regression models.

Complex man-made systems are ubiquitous in modern technological society. The national air transportation infrastructure and the aircraft that operate within it, the highways stretching coast-to-coast and the vehicles that travel on them, and global communications networks and the computers that make them possible are all complex systems. It is impossible to fully validate a systems analysis or a design process. Systems are too large, complex, and expensive to build test and validation articles. Furthermore, the operating conditions throughout the life cycle of a system are impossible to predict and control for a validation experiment. Error is introduced at every point in a complex systems design process. Every error source propagates through the complex system in the same way information propagates, feedforward, feedback, and coupling are all present with error. As with error propagation through a single analysis, error sources grow and decay when propagated through a complex system. These behaviors are made more complex by the complex interactions of a complete system. This complication and the loss of intuition that accompanies it make proper error propagation calculations even more important to aid the decision maker. Error allocation and fidelity trade decisions answer questions like: Is the fidelity of a complex systems analysis adequate, or is an improvement needed, and how is that improvement best achieved? Where should limited resources be invested for the improvement of fidelity? How does knowledge of the imperfection of a model impact design decisions based on the model and the certainty of the performance of a particular design? In this research, a fidelity trade environment was conceived, formulated, developed, and demonstrated. This development relied on the advancement of enabling techniques including error propagation, metamodeling, and information management. A notional transport aircraft is modeled in the fidelity trade environment. Using the environment, the designer is able to make design decisions while considering error and he is able to make decisions regarding required tool fidelity as the design problem continues. These decisions could not be made in a quantitative manner before the fidelity trade environment was developed.

Along with knowledge of the interactions unique to microscale devices, designers of microelectromechanical systems (MEMS) require information about complex fabrication and packaging techniques in order to fully complete a successful design. To that end, the successful design of MEMS requires the collaboration of experts and designers in a variety of engineering fields. From the decision-based design perspective, MEMS designers require a means to sort the input and information generated in a collaborative design process. While the potential for the use of languages and part libraries have been addressed in the literature as a means to solve this problem, a means to embody these principles has not been addressed. The use of modular, executable, decision-centric templates to rapidly compose, solve, archive, and reuse compromise Decision Support Problems (cDSP) for specific design problems has been proposed in the literature. The result of this work is a means of separating procedural design knowledge from declarative knowledge and parsing the cDSP into a set of computer-interpretable templates. A stated need in this work is the extension of the templates to accommodate the coupled solution of two cDSPs utilizing game theoretic principles. In this thesis, the theoretical structures of decision-centric templates are applied to the needs of MEMS designers. Computer interpretable, decision-centric templates, used to save, reuse, and aid in design decisions, are extended to permit MEMS designers and fabricators to collaborate via coupled cDSPs, using game theoretic principles of cooperative, noncooperative, and leader-follower games. This approach is illustrated through its application to the design and prototype fabrication of microscale gas chromatography separation channels. The outcome of this work is twofold: first, MEMS designers and fabricators will have a means to compose, collaboratively solve, archive, and reuse compromise Decision Support Problems in a computer interpretable manner, and second, decision templates will be extended through the use of game theoretic principles.