Thesis (M.Phil.)--Hong Kong University of Science and Technology, 2006. / Includes bibliographical references (leaves 109-110). Also available in electronic version.

Ph.D. / Information technology (IT) system development faces increasing challenges as a result of the complexity involved in the large number of interacting, distributed and concurrently executing components of systems. These components range from operating systems and virtual machines, through to the various frameworks, servers and libraries. To continue delivering on the current trend in resource requirements, hardware is increasingly parallel. The parallelisation of hardware indicates that software systems must be enabled to exploit these multicore, symmetric multiprocessing and distributed architectures as they become more mainstream. Parallelisation of IT systems adds to the number, distribution and concurrency of interacting components. In addition, dynamic self-optimising, selfhealing, self-configuring and self-protecting characteristics are required if systems are to continue operating effectively. The environment into which a system is eventually deployed is often either unknown or dynamic. An unknown environment is one where the exact details of resource availability, along with knowledge or control over concurrently executing systems, is not available beforehand. Added to this is a lack of foreknowledge surrounding the system’s environment, which may be dynamic, meaning it is likely to change during the system’s lifetime. Changes to the system’s environment include new infrastructure, different architectures, replacing old hardware and installing or upgrading software. The current approaches to overcoming unknown and dynamic environments tend to be top-down and centralised as is seen in the use of control theory by autonomic computing. There is, however, a growing realisation that centralised approaches add to the brittleness and complexity of the systems. What is needed is the self-adaptivity of an agent based approach, which is able to overcome these challenges relating to unknown and dynamic environments. Nature has dealt with the same challenges in a far more robust way by employing the principles of self-organising systems underpinning the control of complex adaptive systems. An example of nature’s solution is the self-organising system presented by the gene regulatory system coupled to cell fate and the cell cycle in multicellular organisms. Organisms are self-healing, self-protecting, self-optimising and self-configuring. They are also able, through ontogenesis, to self-adapt to their environments and grow to maximise their performance whilst still maintaining function.

M.Sc. / We live in a modern world in which visual perception has become an absolute necessity. Navigating and walking around in a city without getting lost is a difficult enough task when using all senses, but if you are visually disabled, this becomes a near impossible task. All around us are signs, billboards, motorcars, buildings, computers, and other similar signs of modern times, which are most effectively observed visually. The next logical step in assisting the visually disabled to experience the world around them more freely, is to make more effective use of the technology that has created the shift to the visual world in the first place. It now appears possible to design a framework to incorporate not only current, but also future hardware and software into a solution to the above-mentioned problems. Such a framework has to be flexible to allow it to keep up not only with hardware, but software advances as well. Furthermore, it needs to take into account the needs of a typical blind user. One way of implementing this framework is to make use of a form of sensereplacement. Where the visual sense is impaired, technology can be used to analyze and interpret the visual world, obtain meaningful information from the scene, and then re-route this information to another sense. This dissertation is divided into three sections. The first section will provide an overview of the rest of the dissertation. It will also investigate similar research that is currently being undertaken, and provide a model for a possible solution to the above-mentioned problems. The second section will provide the background study needed to make informed decisions when implementing a prototype system. The third section will investigate the implementation of a prototype model, as well as the construction of a pilot project.

M.Sc. / The manufacturing sector has produced a wide variety of techniques in its attempts to find the ultimate solution for the manufacturing process, with these techniques ranging from material requirements planning, just-in-time production, total-quality management, flexible manufacturing systems and computer integrated manufacturing to advanced planning and scheduling. Given the fact that the technique entitled "advanced planning and scheduling" in the manufacturing environment is primarily aimed at resource planning and scheduling during the production process, however, a clamant need was created for manufacturing companies to broaden their focus in order to include all the processes involved in the production environment, as well as the external processes impacting on productivity. A large area that came into focus owing to the latter paradigm shift is known as "supply chain management". Supply chain management is concerned with the integration of and communication between the various elements in the entire supply chain, including elements such as demand planning and forecasting, scheduling, customer sales, supplier purchases, production planning and forecasting, resource planning and warehouse management. This research study will be devoted to an investigation into the issues surrounding supply chain management and all its manifestations, including its basic components and their integration and interaction. This investigation will also cover research into scheduling systems up to current reactive constraintbased scheduling systems, since scheduling is deemed to be the core of the supply chain in terms of the influence it exerts on most other components, be it directly or indirectly. The investigation will also take us into the realm of an exciting new technology whose exponents are known as "intelligent software agents", which agents are aimed at providing autonomy to the objects within a system and which agents are characterised by their behaviour and decision processes. The said agents can be used to perform highly specialised tasks during the manufacturing process, such as scheduling and forecasting. A prototype system will be developed in the course of the research in a bid to illustrate the integration, evaluation and monitoring of the supply chain elements through the use of intelligent agents. By endowing the system with intelligence, the researchers hope to identify many future uses for intelligent agents in the various segments of the supply chain.

Electronic commerce markets are becoming increasingly popular forums for commerce. As those markets mature, buyers and sellers will both vigorously seek techniques to improve their performance. The Internet lends itself to the use of agents to work on behalf of buyers and sellers. Through simulation, this research examines different implementations of buyers' agents (shopbots) and sellers' agents (pricebots) so that buyers, sellers, and agent builders can capitalize on the evolution of e-commerce technologies. Internet markets bring price visibility to a level beyond what is observed in traditional brick-and-mortar markets. Additionally, an online seller is able to update prices quickly and cheaply. Due to these facts, there are many pricing strategies that sellers can implement via pricebot to react to their environments. The best strategy for a particular seller is dependent on characteristics of its marketplace. This research shows that the extent to which buyers are using shopbots is a critical driver of the success of pricing strategies. When measuring profitability, the interaction between shopbot usage and seller strategy is very strong - what works well at low shopbot usage levels may perform poorly at high levels. If a seller is evaluating strategies based on sales volume, the choice may change. Additionally, as markets evolve and competitors change strategies, the choice of most effective counterstrategies may evolve as well. Sellers need to clearly define their goals and thoroughly understand their marketplace before choosing a pricing strategy. Just as sellers have choices to make in implementing pricebots, buyers have decisions to make with shopbots. In addition to the factors described above, the types of shopbots in use can actually affect the relative performance of pricing strategies. This research also shows that varying shopbot implementations (specifically involving the use of a price memory component) can affect the prices that buyers ultimately pay - an especially important consideration for high-volume buyers. Modern technology permits software agents to employ artificial intelligence. This work demonstrates the potential of neural networks as a tool for pricebots. As discussed above, a seller's best strategy option can change as the behavior of the competition changes. Simulation can be used to evaluate a multitude of scenarios and determine what strategies work best under what conditions. This research shows that a neural network can be effectively implemented to classify the behavior of competitors and point to the best counterstrategy. / Ph. D.

published_or_final_version / abstract / Industrial and Manufacturing Systems Engineering / Doctoral / Doctor of Philosophy

I utilized a design science approach to create an automated kiosk that uses embodied intelligent agents to interview individuals and detect changes in arousal, behavior, and cognitive effort by using psychophysiological information systems. This dissertation achieves three primary purposes.First, I describe the creation of this new Information Technology artifact, discuss design choices, and show the completed prototype.Second, related to this new system, I propose a unique class of intelligent agents, which are described as Special Purpose Embodied Conversational Intelligence with Environmental Sensors (SPECIES). I outline a system model that frames the conceptual components of SPECIES agents, provide design principles for developing SPECIES agents, and discuss some of the research implications of the various components in the model.Third, based on the SPECIES paradigm, I present five studies that evaluate different parts of the model. These studies form the foundational research for the development of the automated kiosk. In the first study, participants interacted with an automated interviewing agent via a chat-based modality (108 participants). The study clearly demonstrates the strong, positive correlation of both response time and the number of times a message is edited to deceitful responses. The software developed became the heart of the kiosk. The second study evaluated changing human decision-making by including influence tactics in decision aids (41 participants). This paper-based decision experiment showed that framing decision aids as appeals to individuals' values possibly change individuals' decisions and was the basis for study 4. The third study examined human-computer interaction and how SPECIES agents can change perceptions of information systems by varying appearance and demeanor (88 participants). Instantiations that had the agents embodied as males were perceived as more powerful, while female embodied agents were perceived as more likeable. Similarly, smiling agents were perceived as more likable than neutral demeanor agents. The fourth study assessed how incorporating impression management techniques into embodied conversational agents can influence human perceptions of the system (88 participants). The impression management techniques proved to be very successful in changing user perceptions. Specifically, agents that performed self-promotion were perceived as more powerful, trustworthy and expert. Agents that performed ingratiation were perceived as more attractive. In the fifth study, I used an embodied agent to interview people who had either constructed a fake bomb and packed it into a bag or had only packed clothes into a bag (60 participants). The agent used eye-tracking technology to capture pupil dilation and gaze behavior. When combined with vocal measurements, the kiosk technology was able to achieve over 93% accuracy in one trial.

Business Intelligence (BI) techniques provide the potential to not only efficiently manage but further analyse and apply the collected information in an effective manner. Benefiting from research both within industry and academia, BI provides functionality for accessing, cleansing, transforming, analysing and reporting organisational datasets. This provides further opportunities for the data to be explored and assist organisations in the discovery of correlations, trends and patterns that exist hidden within the data. This hidden information can be employed to provide an insight into opportunities to make an organisation more competitive by allowing manager to make more informed decisions and as a result, corporate resources optimally utilised. This potential insight provides organisations with an unrivalled opportunity to remain abreast of market trends. Consequently, BI techniques provide significant opportunity for integration with Decision Support Systems (DSS). The gap which was identified within the current body of knowledge and motivated this research, revealed that currently no suitable framework for BI, which can be applied at a meta-level and is therefore tool, technology and domain independent, currently exists. To address the identified gap this study proposes a meta-level framework: - ‘KDDS-BI’, which can be applied at an abstract level and therefore structure a BI investigation, irrespective of the end user. KDDS-BI not only facilitates the selection of suitable techniques for BI investigations, reducing the reliance upon ad-hoc investigative approaches which rely upon ‘trial and error’, yet further integrates Knowledge Management (KM) principles to ensure the retention and transfer of knowledge due to a structured approach to provide DSS that are based upon the principles of BI. In order to evaluate and validate the framework, KDDS-BI has been investigated through three distinct case studies. First KDDS-BI facilitates the integration of BI within ‘Direct Marketing’ to provide innovative solutions for analysis based upon the most suitable BI technique. Secondly, KDDS-BI is investigated within sales promotion, to facilitate the selection of tools and techniques for more focused in store marketing campaigns and increase revenue through the discovery of hidden data, and finally, operations management is analysed within a highly dynamic and unstructured environment of the London Underground Ltd. network through unique a BI solution to organise and manage resources, thereby increasing the efficiency of business processes. The three case studies provide insight into not only how KDDS-BI provides structure to the integration of BI within business process, but additionally the opportunity to analyse the performance of KDDS-BI within three independent environments for distinct purposes provided structure through KDDS-BI thereby validating and corroborating the proposed framework and adding value to business processes.

Many of the contemporary routing algorithms use simple mechanisms such as flooding or broadcasting to disseminate the routing information available to them. Such routing algorithms cause significant network resource overhead due to the large number of messages generated at each host/router throughout the route update process. Many of these messages are wasteful since they do not contribute to the route discovery process. Reducing the resource overhead may allow for several algorithms to be deployed in a wide range of networks (wireless and ad-hoc) which require a simple routing protocol due to limited availability of resources (memory and bandwidth). Motivated by the need to reduce the resource overhead associated with routing algorithms a new implementation of distance vector routing algorithm using an agent-based paradigm known as Agent-based Distance Vector Routing (ADVR) has been proposed. In ADVR, the ability of route discovery and message passing shifts from the nodes to individual agents that traverse the network, co-ordinate with each other and successively update the routing tables of the nodes they visit.

This thesis details the development and validation procedures of the experiment control software to be used on the NPSAT1. The software developed for a standard Linux kernel instead of an expensive proprietary space computer system includes functions for satellite orbit prediction, precise satellite location, and adaptive experiment scheduling using inputs from the electrical power system, sub-satellite position, and sub-satellite local time.