Thesis (M.S.)--California Polytechnic State University, 2009. / Title from PDF title page; viewed on January 11, 2010. Major professor: Franz Kurfess, Ph.D. "Presented to the faculty of California Polytechnic State University, San Luis Obispo." "In partial fulfillment of the requirements for the degree [of] Master of Science in Computer Science." "December 2009." Includes bibliographical references (p. 67-72).

Artificial Intelligence Lab, Department of MIS, University of Arizona / The Kohonen Self-Organizing Map (SOM) is an unsupervised learning technique for summarizing high-dimensional data so that similar inputs are, in general, mapped close to one another. When applied to textual data, SOM has been shown to be able to group together related concepts in a data collection and to present major topics within the collection with larger regions. Research in which properties of SOM were validated, called the Proximity and Size Hypotheses,is presented through a user evaluation study. Building upon the previous research in automatic concept generation and classification, it is demonstrated that the Kohonen SOM was able to perform concept clustering effectively, based on its concept precision and recall7 scores as judged by human experts. A positive relationship between the size of an SOM region and the number of documents contained in the region is also demonstrated.

Thesis (M.S.) in Spatial Information Science and Engineering--University of Maine, 2003. / Includes vita. Includes bibliographical references (leaves 93-99).

<p>Successful project selection and management requires optimal supervision of corporate resources within specifications for time, cost, and performance. We developed a model and algorithm to support decisions on these three dimensions for project managers. It combines the advantages of the Program Evaluation and Review Technique (PERT) and the Critical Path Method (CPM). Our methodology leads to more accurate results than PERT/CPM, which typically results in optimistic planning due to less than actual completion time estimates that do not consider the possibility of more than one longest (critical) path. We also estimate performance measured by the Internal Rate of Return (IRR) of the project and the tradeoffs between time/cost and performance. We allow decision makers to calculate the probability that each activity will be critical, an indication of their relative importance for managerial purposes, in polynomial time. Furthermore, our methodology provides the means to obtain the optimal time/cost schedule of expected completion times as well as the variability in these time, cost, and performance estimates. We can apply our equations to rank the desirability of projects in a proposed portfolio, thus aiding in the portfolio selection process. A stochastic extension to the Analytic Hierarchy Process (AHP) is also used in conjunction with our methodology to demonstrate the application of uncertainty calculations in managerial group choice situations.</p> / Doctor of Philosophy (PhD)

<p>Negotiation is an important part of the life in many organizations. Many works have been undertaken to build tools for conducting negotiations, such as theoretical models and computerized support systems. Some of the existing computerized support systems provide suggestions and solution alternatives to the users. Other systems support the negotiation process, including: support for communications, structuring the process, and managing the documentation. The advent of the World Wide Web as widely available networking platform, the Client/Server as a computing architecture, and Java language as a programming language for the Web, creates new and promising ways to conduct negotiations as an alternative if face-to-face negotiations are not possible. This article describes the design, implementation, and validation of a computerized process support for negotiation, a Web-based Collective Bargaining Support System (CBSS). This system is implemented on Microsoft's Windows 95 environment, written in Java (Sun's JAVA SDK version 1.0), and accessed through the Web. Simulated union-management contract negotiations were conducted in an experiment to test the validity of CBSS as a negotiation stool, and to investigate the effectiveness and the efficiency of this negotiation support system. The data analysis (of questionnaires distributed during the experiment) shows that CBSS is a valid alternative, both when face-to-face negotiation is not possible and when it is combined with face-to-face negotiations. It is also concluded from the experiment that, although CBSS is perceived to be slower than face-to-face negotiation, it is an effective tool for negotiators, and it does not negatively affect bargaining outcomes.</p> / Doctor of Philosophy (PhD)

<p>The management area includes a large class of pattern recognition (classification) problems. Traditionally, these problems have been solved by using statistical methods or expert systems. In practice, however, statistical assumptions about the probability distributions of the pattern variables are often not verifiable, and expertise concerning the correct classification is often not explicitly available. These obstacles may make statistical methods and expert system techniques difficult to apply. Since the early 1980s neural network techniques have been widely used in pattern recognition, especially after Rumelhart's back propagation learning algorithm was adapted to the solution of these problems. The standard neural network, using the back propagation learning algorithm, requires no statistical assumptions but uses training sample data to generate classification boundaries, allowing it to perform pattern recognition.</p> <p>In this dissertation the neural network's behavior in classification boundary generation is analyzed. Based on this analysis, three models are developed. The first model improves the classification performance of neural networks in managerial pattern recognition by modifying the training algorithm through the use of monotonicity. Using simulated and real data, the developed model is tested and verified. The second model solves bias problems caused by small sample size in neural network classification results. The third model develops multi-architecture neural networks to supply decision makers with more natural pattern recognition information, based on fuzzy theory.</p> / Doctor of Philosophy (PhD)

<p>The provision of software support for conceptual model design processes has been an important issue in Model Management Systems research. This study examines the issue by empirically studying design behaviour and the techniques used during design, with a focus on the use of abstraction in the design process.</p> <p>A framework that explains the relationships between the use of abstraction and the output of the design process is proposed. We classify abstraction into vertical, horizontal and general abstraction techniques. We then propose that three dimensions of a design: the completeness of the design, higher level concepts in design, and the organization of the design, are affected by effective use of these abstractions. We also propose aids to support these three types of abstraction, and develop measures to evaluate their effectiveness.</p> <p>A software prototype was developed to illustrate the implementation of the proposed abstraction aids. A pilot study was also conducted to test the effectiveness of these aids using different versions of the prototype.</p> <p>Three hypotheses that test the effectiveness of the proposed abstraction aids were tested in an experimental study with treatments that included three design environments and two training methods. The three design environments were two which were supported by pencil and paper design, and one which was supported by a software prototype. The two training methods used were based on our proposed abstraction aids. The results of the experiment indicate some significant differences in the performance of the participants in different treatment groups.</p> / Doctor of Philosophy (PhD)

<p dir="ltr">In my dissertation, I delve into the moderation and economic dynamics of online platforms. With the proliferation of platforms facilitating user interaction, it becomes imperative to grasp the mechanisms underlying content creation and the economic ramifications of such policies on diverse user groups. Comprising three essays, my dissertation examines the influence of crowd-sourced misinformation monitoring, the effects of privacy on content creation by fact-checkers, and the likelihood of platform acquisition.</p><p dir="ltr">In the first essay, I investigate the impacts of crowd-based misinformation monitoring programs by examining how implementing crowd-based monitoring affects both the quality and quantity of user-generated content. Using data from Twitter's Birdwatch program, I find that content quality, measured subjectively through cognition, improves, while objective measures like user engagement show no significant change. Additionally, there's a decrease in sentiment extremity and machine-learning-calculated misinformation, indicating a potential improvement in overall content quality and reduction in misinformation. However, the program's launch leads to fewer tweets suggesting a trade-off with reduced content volume. </p><p dir="ltr">In my second essay, I analyze how privacy measures affect fact-checkers' content creation. Using Twitter's Birdwatch program, which assigns aliases to fact-checkers, I study the impact of anonymity on their behavior. The results show that privacy measures lead to more content creation on the main platform without any impact to fact-checking activity. Additionally, the content becomes more neutral and less negative. Users also feel more comfortable discussing political topics on Twitter afterward. These findings underscore the importance of privacy measures for effective misinformation monitoring.</p><p dir="ltr">In my third essay, I examine the likelihood of platform company acquisitions, a trend on the rise. These companies' multi-sided nature increases their complexity, presenting both challenges and opportunities in acquisitions. While complexity can lead to information asymmetry, it also enhances attractiveness as an acquisition target. Analyzing Crunchbase data, I find a positive correlation between platform company complexity and acquisition likelihood. </p>

No description available.

A basic requirement of all CAD systems, is that the facilities offered remain relevant to the current needs of users. A characteristic of CAD system users is that their requirements continually change or, to be more accurate, evolve, as their understanding of the design problem and available technology develops. This trait is exemplified by their inability to articulate requirements, both immediate and future with any degree of confidence. Industrial experience of using the traditional methods for developing information systems, which are based upon the Linear Life Cycle (LLC) concept, has proven to be unsuitable for CAD applications. Its failure results from the premise that users' requirements may be accurately stated at the start of the cycle and will not change with time. The need for a new development strategy which supports the evolving requirements of CAD system users is therefore evident. This research resulted in the formulation of such a development strategy. It is based upon an evolutionary approach to system development in which the users' requirements are initially satisfied by the design and implementation of a pilot sub-system which in turn forms the basis for evolution by, its incremental modification and/or extension. The success of this approach principally lies in the ability to modify the software as required with tbe minimum of resources. A major factor determining the degree to which a system may be modified was identified to beits software configuration. A number of design techniques were proposed which contributed to highly flexible configurations, principally through the criteria for functional partitioning, decoupling of functional modules from data storage and the method of organising the data. A new type of data structure was also devised which enabled new data entities and relationships to be added with no modification to the software structure. The development methods resulting from this research were extensively validated during the design and implementation of a large scale industrial CAD system.