The perception of incorporating digital information into online educational systems and the ideal of developing digital schools for lifelong learning have drawn much attention of the governments, academia, and industries around the world. The techniques of interactive learning have become a primary research topic in E-learning. However, most existing E-learning systems provide static instructional materials. The techniques of dynamic learning content management that adaptive to individual user knowledge level and learning goals have been tough challenges for the related research communities. The resulting repetitive and blind learning phenomena have significantly reduced user performance and motivation. We hypothesized that new algorithms of adaptive learning based on the integration of current information technologies, the use of fuzzy theory to express the uncertainty features of the user knowledge, and the exploitation of clustering techniques to analyze the knowledge of a user for the comprehended areas of the domain knowledge will effectively improve user satisfaction. In this study, a prototype system is developed, implemented, and experimented by using SCORM run-time environment. The knowledge of teaching domain and the features of the learner behavior are modeled by ontology to represent the hierarchy and relationship of the learning concepts. To quantify user knowledge and learning ability, fuzzy sets are applied with multiple analysis dimensions based on the pedagogical strategies and user learning experiences. The performance of a user for learning knowledge concepts is then evaluated. In particular, an algorithm is designed to extract the existing learning paths of a user by the relative position of the concepts that the user attains in the domain knowledge. Furthermore, the candidate direction types for recommending concepts are inferred and the candidate learning concepts that are appropriate or inappropriate to learn followed up can be identified by rules. Moreover, the candidate learning concepts are scheduled to construct customizable learning routes by clustering techniques. The personalized learning contents that best matching user learning intention would then be presented to the user. Simulations study in the uniform and normal distributions for the grades of users is conducted to evaluate the tutoring model for three levels of users. The experimental results show that the proposed model helps different levels of users to learn the domain knowledge effectively and the accuracy of recommending the relevant learning object contents is superior than the random selection method. With a richer description of user knowledge and features, the proposed adaptive system for online learning assistance may better diagnose the understanding of a learner and enhance the pertinence of the retrieved courses to user intended learning to improve the service quality for the user.

In an ad hoc networks, it is an important problem about how to increase the bandwidth utilization and guarantee Quality-of-Service. In order to increase the bandwidth utilization under the situation of limited bandwidth, we want to achieve the target by using the bitty residual bandwidth in the ad hoc networks. Hence we integrate several single paths into a multi-path that satisfies QoS requirement. In this paper, we present a policy to look up, maintain, and reroute the virtual circuit in the ad hoc networks. From the result of simulation, we obtain that our proposal indeed can increase the bandwidth utilization of ad hoc networks. But the condition of splitting also increases the overhead of connection, and affects the forced terminated ratio and packets lost ratio under mobility.

Software testing is a vital part of the software development process and is used for the purposes of quality assurance, reliability estimation and verification and validation. However, software testing is extremely costly and time consuming. For instance, prior research indicated that more than 50% of the software development cost is devoted to testing. Due to the increased use of the Unified Modeling Language (UML) and model driven architecture approach in systems analysis and design, Model-Based Testing has been discussed as a prominent solution for software testing to address the above problems. This study presents a methodology for determining the test path which can then be further used to determine the test case for Model-Based Testing. Three real-world cases are used to test the usability (including the concepts, application, and advantages) of the proposed methodology. With this approach, software errors can be found at the systems analysis and design stage and thereby reduce the cost of software testing and enhance the efficiency of system development.

Measurement of performance is important to the construction sector as an additional way of improving and sustaining competitiveness in the long-term. Most large construction organisations in the United Kingdom (UK) practise performance measurement because they believe it affects their business positively in the longer-term. Performance measurement is thus, recognised as an important way of keeping an organisation on track in achieving its strategic objectives. However, there are still construction organisations that believe performance measurement does not aid in creating and developing appropriate strategies for their organisations, but helps organisations in identifying areas where they did or did not perform well. The improvements in performance thus, can only be brought about through step-by-step strategic guidance to organisations to achieve their performance targets. The first step towards achieving these targets comprises the following: understand the performance measurement process of organisations, and identify the appropriate criteria that need to be measured to improve business; identify strengths and opportunities, which in turn can create a way to maximise profits for an organisation. Such an approach would help organisations target relevant performance measurements and embed them in their organisational strategy in a structured step-by-step manner. Premised on the foregoing, this research project aims to investigate potential tools for improving performance measurement practices in the construction industry. In addition, this research aims to assist organisations in implementing performance measurement in a proper manner and to help them understand the performance measurement process. The first step (objective 1) of this research is to review the generic body of literature in performance measurement to understand key concepts, definitions and existing practices and identify commonly used performance measurement tools. It is noted that there are several definitions of performance measurement. However, at its basic level, performance measurement is a process of determining how successful organisations or individuals have been in attaining their objectives and strategies. To achieve this, the outputs of an organisation's strategic and operational processes are measured in a quantifiable form; the results are used to monitor closely the performance of the organisation, internally and externally. Findings of the review (and later those of objectives 2 and 3) reveal that the Balanced Scorecard (BSC) and the European Foundation for Quality Management (EFQM) Excellence Model are the two most widely known and used tools, in all sectors including construction, to measure an organisation s performance. Semi-structured interviews (objectives 2 and 3) were conducted with performance measurement directors and managers in large UK construction companies. The interviews revealed that performance measurement is being practised in organisations directly or indirectly to help improve businesses and profits. The purpose of interviews was to seek the organisations views on how they approach and conduct performance measurement and derive benefits from it. All organisations agreed that the financial aspects such as profit margins and growth, as well as non-financial aspects such as health and safety and customer satisfaction are important criteria to be measured. Both financial and non-financial criteria need to be considered and included in an organisation's strategy; they are important considerations for any future strategy development. Findings of the interviews and the literature review suggest the best way to create an organisation's strategy as the following: understand the performance measurement process of organisations and identify the appropriate criteria, which need to be measured to improve business; identify strengths and opportunities, which in turn can create a way to maximise profits for an organisation. This led to the development of a Framework (also called the Performance Measurement Migration Path) (objective 4), which would help organisations target relevant performance measurements and embed them in their organisational strategy in a structured step-by-step manner. Its implementation in organisations can make performance measurement processes easy and smooth. Evaluation (objective 5) of the framework confirms its suitability and acceptability to industry players for the use in improving the implementation of performance measurement.

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Interaction with the world is necessary for both animals and robots to complete tasks. This interaction requires a sense of self, or the orientation of the robot or animal with respect to the world. Creating and maintaining this model is a task which is easily maintained by animals, however can be difficult for robots due to the uncertainties in the world, sensing, and movement of the robot. This estimation difficulty is increased in sensory deprived environments, where no external, inputs are available to correct the estimate. Therefore, self generated cues of movement are needed, such as vestibular input in an animal, or accelerometer input in a robot. In spite of the difficulties, animals can easily maintain this model. This leads to the question of whether we can learn from nature by examining the biological mechanisms for pose estimation in animals. Previous work has shown that neural fields coupled with a mechanism for updating the estimate can be used to maintain a pose estimate through a sustained area of activity called a packet. Analysis of this mechanism however has shown conditions where the field can provide unexpected results or break down due to high accelerations input into the field. This analysis illustrates the challenges of controlling the activity packet size under strong inputs, and a limited speed capability using the existing mechanism. As a result of this, a novel weight combination method is proposed to provide a higher speed and increased robustness. The results of this is an increase of over two times the existing speed capability, and a resistance of the field to break down under strong rotational inputs. This updated neural field model provides a method for maintaining a stable pose estimate. To show this, a novel comparison between the proposed neural field model and the Kalman filter is considered, resulting in comparable performance in pose prediction. This work shows that an updated neural field model provides a biologically plausible pose prediction model using Bayesian inference, providing a biological analogue to a Kalman filter.

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