Feasibility studies on using microwave-heating techniques for recycling lead waste

Lead is present everywhere in the environment and has been defined as one of the greatest threats to the human health. In this paper, attempts have been made to study a way of recycling the lead produced from waste usage and disposed of in such a way as to avoid degrading the surrounding environment. In order to contain the waste, recycled asphalt material is mixed with the lead and then heated with microwave energy. This is an attempt to solidify and reduce the lead contaminants and use the final product as sub-base material in road pavement construction. The microwave heating of the specimens is carried out with 30%, 50%, 80% and 100% of power at 800W. The optimum power mode is used to compare with the conventional heating of asphalt with sulfur additive. The results are characterized by compact density, permeability, and subjected to toxicity test with regards to lead concentration. A mechanical test to evaluate the stability is also performed on the three methods of solidification and to prove that microwave zapping method allow to convert into an environmentally stable material for recycling without having to be deposited in a landfill site.

Effective web service discovery using a combination of a semantic model and a data mining technique

With the advent of Service Oriented Architecture, Web Services have gained tremendous popularity. Due to the availability of a large number of Web services, finding an appropriate Web service according to the requirement of the user is a challenge. This warrants the need to establish an effective and reliable process of Web service discovery. A considerable body of research has emerged to develop methods to improve the accuracy of Web service discovery to match the best service. The process of Web service discovery results in suggesting many individual services that partially fulfil the user’s interest. By considering the semantic relationships of words used in describing the services as well as the use of input and output parameters can lead to accurate Web service discovery. Appropriate linking of individual matched services should fully satisfy the requirements which the user is looking for. This research proposes to integrate a semantic model and a data mining technique to enhance the accuracy of Web service discovery. A novel three-phase Web service discovery methodology has been proposed. The first phase performs match-making to find semantically similar Web services for a user query. In order to perform semantic analysis on the content present in the Web service description language document, the support-based latent semantic kernel is constructed using an innovative concept of binning and merging on the large quantity of text documents covering diverse areas of domain of knowledge. The use of a generic latent semantic kernel constructed with a large number of terms helps to find the hidden meaning of the query terms which otherwise could not be found. Sometimes a single Web service is unable to fully satisfy the requirement of the user. In such cases, a composition of multiple inter-related Web services is presented to the user. The task of checking the possibility of linking multiple Web services is done in the second phase. Once the feasibility of linking Web services is checked, the objective is to provide the user with the best composition of Web services. In the link analysis phase, the Web services are modelled as nodes of a graph and an allpair shortest-path algorithm is applied to find the optimum path at the minimum cost for traversal. The third phase which is the system integration, integrates the results from the preceding two phases by using an original fusion algorithm in the fusion engine. Finally, the recommendation engine which is an integral part of the system integration phase makes the final recommendations including individual and composite Web services to the user. In order to evaluate the performance of the proposed method, extensive experimentation has been performed. Results of the proposed support-based semantic kernel method of Web service discovery are compared with the results of the standard keyword-based information-retrieval method and a clustering-based machine-learning method of Web service discovery. The proposed method outperforms both information-retrieval and machine-learning based methods. Experimental results and statistical analysis also show that the best Web services compositions are obtained by considering 10 to 15 Web services that are found in phase-I for linking. Empirical results also ascertain that the fusion engine boosts the accuracy of Web service discovery by combining the inputs from both the semantic analysis (phase-I) and the link analysis (phase-II) in a systematic fashion. Overall, the accuracy of Web service discovery with the proposed method shows a significant improvement over traditional discovery methods.

Final report : feasibility study linking best value procurement assessment to outcome performance indicators

This feasibility study was established to investigate the application of the concept of ‘best value’ in construction procurement in Australia. In the case of ‘best value’ in the business enterprise, ‘best value’ is that which returns greatest value to the business enterprise’s shareholders. However, in the case of the public sector, ‘best value’ is more complex. For that reason, this research project focuses mainly on public sector construction project procurement.

A feasibility study for model based estimating for concrete bridges.

Designing and estimating civil concrete structures is a complex process which to many practitioners is tied to manual or semi-manual processes of 2D design and cannot be further improved by automated, interacting design-estimating processes. This paper presents a feasibility study for the development an automated estimator for concrete bridge design. The study offers a value proposition: an efficient automated model-based estimator can add value to the whole bridge design-estimating process, i.e., reducing estimation errors, shortening the duration of success estimates, and increasing the benefit of doing cost estimation when compared with the current practice. This is then followed by a description of what is in an efficient automated model-based estimator and how it should be used. Finally the process of model-based estimating is compared with the current practice to highlight the values embedded in the automated processes.

On feasibility of regional frequency-based emergency control plans

Decentralized and regional load-frequency control of power systems operating in normal and near-normal conditions has been well studied; and several analysis/synthesis approaches have been developed during the last few decades. However in contingency and off-normal conditions, the existing emergency control plans, such as under-frequency load shedding, are usually applied in a centralized structure using a different analysis model. This paper discusses the feasibility of using frequency-based emergency control schemes based on tie-line measurements and local information available within a control area. The conventional load-frequency control model is generalized by considering the dynamics of emergency control/protection schemes and an analytic approach to analyze the regional frequency response under normal and emergency conditions is presented.

Race and equity in higher education : A harder path for Indigenous academics

Our experiences as Indigenous academics within universities often reflects the experiences we have as Indigenous people in broader society, yet I am still surprised and angered when it is others working in higher education who espouse notions of justice and equity with whom we experience tension and conflict in asserting our rights, values and cultural values. At times it is a constant struggle even when universities have Reconciliation Statements as most of them do now, Indigenous recruitment or employment strategies and university wide anti-racism and anti-discrimination policies and procedures.

Effects and feasibility of a multi-disciplinary orientation program for newly registered cancer patients : design of a randomised controlled trial

Background Diagnosis and treatment of cancer can contribute to psychological distress and anxiety amongst patients. Evidence indicates that information giving can be beneficial in reducing patient anxiety, so oncology specific information may have a major impact on this patient group. This study investigates the effects of an orientation program on levels of anxiety and self-efficacy amongst newly registered cancer patients who are about to undergo chemotherapy and/or radiation therapy in the cancer care centre of a large tertiary Australian hospital. Methods The concept of interventions for orienting new cancer patients needs revisiting due to the dynamic health care system. Historically, most orientation programs at this cancer centre were conducted by one nurse. A randomised controlled trial has been designed to test the effectiveness of an orientation program with bundled interventions; a face-to-face program which includes introduction to the hospital facilities, introduction to the multi-disciplinary team and an overview of treatment side effects and self care strategies. The aim is to orientate patients to the cancer centre and to meet the health care team. We hypothesize that patients who receive this orientation will experience lower levels of anxiety and distress, and a higher level of self-efficacy. Discussion An orientation program is a common health care service provided by cancer care centres for new cancer patients. Such programs aim to give information to patients at the beginning of their encounter at a cancer care centre. It is clear in the literature that interventions that aim to improve self-efficacy in patients may demonstrate potential improvement in health outcomes. Yet, evidence on the effects of orientation programs for cancer patients on self-efficacy remains scarce, particularly with respect to the use of multidisciplinary team members. This paper presents the design of a randomised controlled trial that will evaluate the effects and feasibility of a multidisciplinary orientation program for new cancer patients.

Robot path planning in dynamic environments using a simulated annealing based approach

Mobile robots are widely used in many industrial fields. Research on path planning for mobile robots is one of the most important aspects in mobile robots research. Path planning for a mobile robot is to find a collision-free route, through the robot’s environment with obstacles, from a specified start location to a desired goal destination while satisfying certain optimization criteria. Most of the existing path planning methods, such as the visibility graph, the cell decomposition, and the potential field are designed with the focus on static environments, in which there are only stationary obstacles. However, in practical systems such as Marine Science Research, Robots in Mining Industry, and RoboCup games, robots usually face dynamic environments, in which both moving and stationary obstacles exist. Because of the complexity of the dynamic environments, research on path planning in the environments with dynamic obstacles is limited. Limited numbers of papers have been published in this area in comparison with hundreds of reports on path planning in stationary environments in the open literature. Recently, a genetic algorithm based approach has been introduced to plan the optimal path for a mobile robot in a dynamic environment with moving obstacles. However, with the increase of the number of the obstacles in the environment, and the changes of the moving speed and direction of the robot and obstacles, the size of the problem to be solved increases sharply. Consequently, the performance of the genetic algorithm based approach deteriorates significantly. This motivates the research of this work. This research develops and implements a simulated annealing algorithm based approach to find the optimal path for a mobile robot in a dynamic environment with moving obstacles. The simulated annealing algorithm is an optimization algorithm similar to the genetic algorithm in principle. However, our investigation and simulations have indicated that the simulated annealing algorithm based approach is simpler and easier to implement. Its performance is also shown to be superior to that of the genetic algorithm based approach in both online and offline processing times as well as in obtaining the optimal solution for path planning of the robot in the dynamic environment. The first step of many path planning methods is to search an initial feasible path for the robot. A commonly used method for searching the initial path is to randomly pick up some vertices of the obstacles in the search space. This is time consuming in both static and dynamic path planning, and has an important impact on the efficiency of the dynamic path planning. This research proposes a heuristic method to search the feasible initial path efficiently. Then, the heuristic method is incorporated into the proposed simulated annealing algorithm based approach for dynamic robot path planning. Simulation experiments have shown that with the incorporation of the heuristic method, the developed simulated annealing algorithm based approach requires much shorter processing time to get the optimal solutions in the dynamic path planning problem. Furthermore, the quality of the solution, as characterized by the length of the planned path, is also improved with the incorporated heuristic method in the simulated annealing based approach for both online and offline path planning.