An evaluation of viability of public private partnerships in social infrastructure procurement projects in Queensland, Australia

Public private partnerships (PPP) have been widely used as a method for public infrastructure project delivery not only locally and internationally, however the adoption of PPPs in social infrastructure procurement has still been very limited. The objective of this paper is to investigate the potential of implementation of current PPP framework in social affordable housing projects in South East Queensland. Data were collected from 22 interviewees with rich experiences in the industry. The findings of this study show that affordable housing investment have been considered by the industry practitioners as a risky business in comparison to other private rental housing investment. The main determents of the adoption of PPPs in social infrastructure project are the tenant-related factors, such as the inability of paying rent and the inability of caring the property. The study also suggests the importance of seeking strategic partnership with community-based organisation that has experiences in managing similar tenants’ profiles. Current PPP guideline is also viewed as inappropriate for the affordable housing projects, but the principle of VFM framework and risk allocation in PPPs still be applied to the affordable housing projects. This study helps to understand the viability of PPP in social housing procurement projects, and point out the importance of developing guideline for multi-stakeholder partnership and the expansion of the current VFM and PPPs guidelines.

Internships : effective work integrated learning for law students

Work experience which is integrated into an undergraduate law degree has a vital role to play in assisting law students to develop the skills and attributes they need in order to be effective legal practitioners. Work integrated learning provides a context for students to develop their skills, to see the link between theory and practice and supports students in making the transition from university to practice. The literature in Australian legal education has given little consideration to the design of legal internship subjects (as distinct from legal clinic programs). Accordingly the design of internship subjects needs to be carefully considered to ensure alignment of learning objectives, learning tasks and assessment. This paper will examine the literature relating to internships, particularly in a legal context, and will propose some principles for the design of legal internships. These principles will be considered in light of an evaluation of a newly designed undergraduate legal internship subject.

A Conceptualisation of Courseware Development Process in Malaysian Educational Context

Multimedia-based learning has been accepted as an effective learning tool and has broadly prevailed in various types of education around the world. The Malaysian ministry of education has also adopted this information communication technology (ICT) as the means of an education reformation project called, ‘Smart School’ since 1998, aiming to improve all Malaysian Primary and Secondary students’ learning ability, attitudes, achievement, and further enhance teachers’ teaching performance. As a result, Malaysian Ministry of Education has distributed a number of interactive courseware of the key learning domains such as Mathematics, Science, Bahasa Melayu (Malay language), and English. According to recent reports by Malaysian Ministry of Education (MOE), however, the courseware has not been effectively used in schools, and many researchers point out there are vital issues concerning the interface and interaction design. Within this context, this paper presumes that one of the main reasons could derive from a structural aspect of the course development process that is devaluing or ignoring the importance of interface and interaction design. Therefore, it is imperative to conceptualise the courseware development process in terms of creating interactive and quality learning experiences through defining the stakeholders’ needs in terms of better learning and teaching. Within this context, this paper reviews the current development process and proposes a new concept called the interactive communication component which enables courseware developers to embed interactive and quality learning experiences into their courseware development process. The key objective is to provide opportunities to discuss the courseware development process from the different stakeholders’ perspectives of the educational courseware in a Malaysian context.

A conceptual framework for a systematic mapping of layout design principles by using Yin and Yang theory

There are various principles for layout design such as balance, rhythm, unity and harmony, but each principle has often been introduced as a separate concept rather than within an integrated and systematic structure, so that designers and design students have to keep practices for the acquisition of skills. The paper seeks to develop a conceptual framework for a systematic mapping of layout design principles by using Yin and Yang and the Five Elements. Yin and Yang theory explains all natural phenomena with its own conceptual model and facilitates finding harmony and balance between the visual elements in terms of systematic and organic relations. Most common and well-known layout design principles are defined with 10 different resources such as design books and articles, and have been remapped following with the structure of Yin and Yang and the Five Elements. A systematic framework explaining the relationships of design principles was created and 32 design students participated in its efficiency test. The outcome suggests there is a high possibility that the framework can be used in professional fields and design education.

Reflective learning through social network sites in design education

Reflective learning is vital for successful practice-led education such as animation, multimedia design and graphic design, and social network sites can accommodate various learning styles for effective reflective learning. In this paper, the researcher studies reflective learning through social network sites with two animation units. These units aim to provide students with an understanding of the tasks and workflows involved in the production of style sheets, character sheets and motion graphics for use in 3D productions for film and television and game design. In particular, an assessment in these units requires students to complete their online reflective journals throughout the semester. The reflective learning has been integrated within the unit design and students are encouraged to reflect weekly learning processes and outcomes. A survey evaluating for students’ learning experience was conducted, and its outcomes indicate that social network site based reflective learning will not be effective without considering students’ learning circumstances and designing peer-to-peer interactions.

Intelligent prognostics of machinery health utilising suspended condition monitoring data

The ability to forecast machinery failure is vital to reducing maintenance costs, operation downtime and safety hazards. Recent advances in condition monitoring technologies have given rise to a number of prognostic models for forecasting machinery health based on condition data. Although these models have aided the advancement of the discipline, they have made only a limited contribution to developing an effective machinery health prognostic system. The literature review indicates that there is not yet a prognostic model that directly models and fully utilises suspended condition histories (which are very common in practice since organisations rarely allow their assets to run to failure); that effectively integrates population characteristics into prognostics for longer-range prediction in a probabilistic sense; which deduces the non-linear relationship between measured condition data and actual asset health; and which involves minimal assumptions and requirements. This work presents a novel approach to addressing the above-mentioned challenges. The proposed model consists of a feed-forward neural network, the training targets of which are asset survival probabilities estimated using a variation of the Kaplan-Meier estimator and a degradation-based failure probability density estimator. The adapted Kaplan-Meier estimator is able to model the actual survival status of individual failed units and estimate the survival probability of individual suspended units. The degradation-based failure probability density estimator, on the other hand, extracts population characteristics and computes conditional reliability from available condition histories instead of from reliability data. The estimated survival probability and the relevant condition histories are respectively presented as “training target” and “training input” to the neural network. The trained network is capable of estimating the future survival curve of a unit when a series of condition indices are inputted. Although the concept proposed may be applied to the prognosis of various machine components, rolling element bearings were chosen as the research object because rolling element bearing failure is one of the foremost causes of machinery breakdowns. Computer simulated and industry case study data were used to compare the prognostic performance of the proposed model and four control models, namely: two feed-forward neural networks with the same training function and structure as the proposed model, but neglected suspended histories; a time series prediction recurrent neural network; and a traditional Weibull distribution model. The results support the assertion that the proposed model performs better than the other four models and that it produces adaptive prediction outputs with useful representation of survival probabilities. This work presents a compelling concept for non-parametric data-driven prognosis, and for utilising available asset condition information more fully and accurately. It demonstrates that machinery health can indeed be forecasted. The proposed prognostic technique, together with ongoing advances in sensors and data-fusion techniques, and increasingly comprehensive databases of asset condition data, holds the promise for increased asset availability, maintenance cost effectiveness, operational safety and – ultimately – organisation competitiveness.

A sequencing approach for creating new train timetables

Train scheduling is a complex and time consuming task of vital importance. To schedule trains more accurately and efficiently than permitted by current techniques a novel hybrid job shop approach has been proposed and implemented. Unique characteristics of train scheduling are first incorporated into a disjunctive graph model of train operations. A constructive algorithm that utilises this model is then developed. The constructive algorithm is a general procedure that constructs a schedule using insertion, backtracking and dynamic route selection mechanisms. It provides a significant search capability and is valid for any objective criteria. Simulated Annealing and Local Search meta-heuristic improvement algorithms are also adapted and extended. An important feature of these approaches is a new compound perturbation operator that consists of many unitary moves that allows trains to be shifted feasibly and more easily within the solution. A numerical investigation and case study is provided and demonstrates that high quality solutions are obtainable on real sized applications.

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.