Predicting freeway pavement construction cost using a back-propagation neural network : a case study in Henan, China

The objective of this research was to develop a model to estimate future freeway pavement construction costs in Henan Province, China. A comprehensive set of factors contributing to the cost of freeway pavement construction were included in the model formulation. These factors comprehensively reflect the characteristics of region and topography and altitude variation, the cost of labour, material, and equipment, and time-related variables such as index numbers of labour prices, material prices and equipment prices. An Artificial Neural Network model using the Back-Propagation learning algorithm was developed to estimate the cost of freeway pavement construction. A total of 88 valid freeway cases were obtained from freeway construction projects let by the Henan Transportation Department during the period 1994−2007. Data from a random selection of 81 freeway cases were used to train the Neural Network model and the remaining data were used to test the performance of the Neural Network model. The tested model was used to predict freeway pavement construction costs in 2010 based on predictions of input values. In addition, this paper provides a suggested correction for the prediction of the value for the future freeway pavement construction costs. Since the change in future freeway pavement construction cost is affected by many factors, the predictions obtained by the proposed method, and therefore the model, will need to be tested once actual data are obtained.

A 4D automatic simulation tool for construction resource planning: A case study

Purpose Traditional construction planning relies upon the critical path method (CPM) and bar charts. Both of these methods suffer from visualization and timing issues that could be addressed by 4D technology specifically geared to meet the needs of the construction industry. This paper proposed a new construction planning approach based on simulation by using a game engine. Design/methodology/approach A 4D automatic simulation tool was developed and a case study was carried out. The proposed tool was used to simulate and optimize the plans for the installation of a temporary platform for piling in a civil construction project in Hong Kong. The tool simulated the result of the construction process with three variables: 1) equipment, 2) site layout and 3) schedule. Through this, the construction team was able to repeatedly simulate a range of options. Findings The results indicate that the proposed approach can provide a user-friendly 4D simulation platform for the construction industry. The simulation can also identify the solution being sought by the construction team. The paper also identifies directions for further development of the 4D technology as an aid in construction planning and decision-making. Research limitations/implications The tests on the tool are limited to a single case study and further research is needed to test the use of game engines for construction planning in different construction projects to verify its effectiveness. Future research could also explore the use of alternative game engines and compare their performance and results. Originality/value The authors proposed the use of game engine to simulate the construction process based on resources, working space and construction schedule. The developed tool can be used by end-users without simulation experience.

The role of microcomputer-based laboratory display in supporting the construction of new understanding in kinematics

Teachers' failure to utilise MBL activities more widely may be due to not recognising their capacity to transform the nature of laboratory activities to be more consistent with contemporary constructivist theories of learning. This research aimed to increase understanding of how MBL activities specifically designed to be consistent with a constructivist theory of learning support or constrain student construction of understanding. The first author conducted the research with his Year 11 physics class of 29 students. Dyads completed nine tasks relating to kinematics using a Predict-Observe-Explain format. Data sources included video and audio recordings of students and teacher during four 70-minute sessions, students' display graphs and written notes, semi-structured student interviews, and the teacher's journal. The study identifies the actors and describes the patterns of interactions in the MBL. Analysis of students' discourse and actions identified many instances where students' initial understanding of kinematics were mediated in multiple ways. Students invented numerous techniques for manipulating data in the service of their emerging understanding. The findings are presented as eight assertions. Recommendations are made for developing pedagogical strategies incorporating MBL activities which will likely catalyse student construction of understanding.

Skill development for innovative procurement environments in construction

The construction industry should be a priority to all governments because it impacts economically and socially on all citizens. Sector turnover in industrialised economies typically averages 8-12% of GDP. Further, construction is critical to economic growth. Recent Australian studies estimate that a 10% gain in efficiency in construction translates to a 2.5% increase in GDP Inefficiencies in the Australian construction industry have been identified by a number of recent studies modelling the building process. They have identified potential savings in time of between 25% and 40% by reducing non-value added steps in the process. A culture of reform is now emerging in the industry – one in which alternate forms of project delivery are being trialed. Government and industry have identified Alliance Contracting as a means to increase efficiency in the construction industry as part of a new innovative procurement environment. Alliance contracting requires parties to form relationships and work cooperatively to provide a more complete service. This is a significant cultural change for the construction industry, with its well-known adversarial record in traditional contracting. Alliance contracts offer enormous potential benefits, but the Australian construction industry needs to develop new skills to effectively participate in the new relationship environment. This paper describes a collaborative project identifying skill needs for clients and construction professionals to more effectively participate in an increasingly sophisticated international procurement environment. The aim of identifying these skill needs is to assist industry, government, and skill developers to prepare the Australian construction workforce for the future. The collaborating Australian team has been fortunate to secure the Australian National Museum in Canberra as its live case study. The Acton Peninsula Development is the first major building development in the world awarded on the basis of a joint alliance contract.

A Low Cost Controller Board for Teaching Robotics

This paper presents the Smarty Board; a new micro-controller board designed specifically for the robotics teaching needs of Australian schools. The primary motivation for this work was the lack of commercially available and cheap controller boards that would have all their components including interfaces on a single board. Having a single board simplifies the construction of programmable robots that can be used as platforms for teaching and learning robotics. Reducing the cost of the board as much as possible was one of the main design objectives. The target user groups for this device are the secondary and tertiary students, and hobbyists. Previous studies have shown that equipment cost is one of the major obstacles for teaching robotics in Australia. The new controller board was demonstrated at high-school seminars. In these demonstrations the new controller board was used for controlling two robots that we built. These robots are available as kits. Given the strong demand from high-school teachers, new kits will be developed for the next robotic Olympiad to be held in Australia in 2006.