The mobile phone has been regarded as one of the most significant inventions in the field of communications and information technology over the past decade. Due to the rapid growth of mobile phone subscribers, hundreds of phone models have been introduced. Therefore, customers may find it difficult to select the most appropriate mobile phone because of information overload. The aim of this study is to investigate web support for customers who are selecting a mobile phone. Firstly, all the models of mobile phones in the New Zealand market were identified by visiting shops and local websites. Secondly, a list of all the features of these mobile phones was collated from local shops, websites and magazines. This list was categorised into mobile phone properties and performance criteria. An experiment then compared three different selection support methods: A (mobile phone catalogue), B (mobile phone property selection) and C (mobile phone property and performance criteria selection). The results of the experiment revealed that selection support methods B and C had higher overall satisfaction ratings than selection support method A; both methods B and C had similar satisfaction ratings. The results also suggested that males and females select their mobile phones differently, though there was no gender preference in selection support methods.

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>

Noting how organizations today are increasingly dependent on IT for a broad range of organizational activities, the thesis starts from the observation that many IT-related endeavors nevertheless fail. In tracing part of the problem to the inability of many organizations to cope with changes in the surrounding material and social context, the emphasis is put on the processes by which IT-artifacts are adapted and re-adapted, after they have been put into daily use. Assuming human sensemaking as a good basis for coping with the changes, qualitative data from two organizations — a Swedish social services department and a software firm — provides an empirical context for assessing how sensemaking processes affect IT-adaptation. Conceptually, the thesis draws on Karl Weick's thinking, introducing the "double interact" and the "response repertoire" as sensitizing concepts with which to understand the mechanisms generating adaptation of IT-artifacts. Methodologically, the interpretive case study is employed, using the "hermeneutic circle" as the guiding principle for the research process. The thesis draws some specific implications concerning how IT-adaptation can be understood in organizations. The generic IT-adaptation process can be divided into two elementar}- phases, exploration and exploitation. During the exploration phase, several individual interpretations of a particular IT-artifact co-exist, occasioning ambiguity about its meaning in organizational daily activity. During the exploitation phase, the IT-artifact itself is in the background of matters of attention, providing organizational actors, who pursue individual goals and desires, the opportunity to exploit the shared and taken-for-granted meaning they see in the artifact. While the exploitation phase is important for organizational efficacy, there is nevertheless a risk that the meaning exploited becomes outdated by surrounding socio-material changes over time. Among other proposals, the thesis therefore suggests that triggering sensemaking processes can be important for meaningful IT-adaptation. In addition, it suggests the activity of searching for the interlacing areas of professional identity of actor groups, as a means to make IT-artifacts meaningful in organizing endeavors. / <p>[8] s., s. 1-64: sammanfattning, s. 65-168: 6 uppsatser</p> / digitalisering@umu

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.

Data centers are computing infrastructure facilities used by industries with large data processing needs and the rapid increase in power density of high performance computing equipment has caused many thermal issues in these facilities. Systems-level thermal management requires modeling and analysis of complex fluid flow and heat transfer processes across several decades of length scales. Conventional computational fluid dynamics and heat transfer techniques for such systems are severely limited as a design tool because their large model sizes render parameter sensitivity studies and optimization impractically slow. The traditional proper orthogonal decomposition (POD) methodology has been reformulated to construct physics-based models of turbulent flows and forced convection. Orthogonal complement POD subspaces were developed to parametrize inhomogeneous boundary conditions and greatly extend the use of the existing POD methodology beyond prototypical flows with fixed parameters. A flux matching procedure was devised to overcome the limitations of Galerkin projection methods for the Reynolds-averaged Navier-Stokes equations and greatly improve the computational efficiency of the approximate solutions. An implicit coupling procedure was developed to link the temperature and velocity fields and further extend the low-dimensional modeling methodology to conjugate forced convection heat transfer. The overall reduced-order modeling framework was able to reduce numerical models containing 105 degrees of freedom (DOF) down to less than 20 DOF, while still retaining greater that 90% accuracy over the domain. Rigorous a posteriori error bounds were formulated by using the POD subspace to partition the error contributions and dual residual methods were used to show that the flux matching procedure is a computationally superior approach for low-dimensional modeling of steady turbulent convection. To efficiently model large-scale systems, individual reduced-order models were coupled using flow network modeling as the component interconnection procedure. The development of handshaking procedures between low-dimensional component models lays the foundation to quickly analyze and optimize the modular systems encountered in electronics thermal management. This modularized approach can also serve as skeletal structure to allow the efficient integration of highly-specialized models across disciplines and significantly advance simulation-based design.