Writing: An Essential and Powerful Communication Tool for Today’s ‘Three Dimensional’ Engineering Graduate

Today’s engineers are expected to be versatile, necessitating a bold shift in the direction of Australian undergraduate engineering education. Alongside the capacity for technical analysis, core engineering graduate attributes emphasise non-technical skills: (i) the ability to communicate effectively, (ii) the ability to function as reflective practitioners on multidisciplinary teams, and (iii) the broad education necessary to understand the impact of engineering solutions within a global, economic, and environmental context. Increasingly, students are coming from a diversity of backgrounds – academic, cultural, and professional – and academics are being required to meet the complex professional demands they bring. Recognition of the need for literacy support where cohorts comprise a high percentage of students from a non-English-speaking background with strong science/math competence, yet little experience of writing academic English, is challenging. Effective literacy support requires early identification of problems in large undergraduate cohorts. Evidence demonstrates that literacy support is most effective when closely integrated with core assignments and relevant to dynamic professional practice

Building information modelling (BIM) for facilities management (FM): The MediaCity case study approach

Facilities Management (FM) as the total management of all services supports the core businesses of an organisation in a building. However, today’s buildings are increasingly sophisticated and the need for information to operate and maintain them is vital. Facility Managers have to acquire, integrate, edit, and update diverse facility information ranging from building elements, fabric data, operational costs, contract types, room allocation, logistics, maintenance, etc. However, FM professionals face challenges resulting in cost and time related productivity, efficiency and effectiveness losses. Building Information Modelling (BIM), that seeks to integrate the building lifecycle, can provide improvements and help to overcome those challenges. Thus, the paper explores how BIM can contribute to and improve the FM profession. It uses the MediaCityUK project as a case study, which is a regeneration project aiming to attract media institutions locally and worldwide and establish itself as an international centre for excellence. For this purpose, the key FM tasks are identified and a BIM model for the new university building in MediaCityUK is developed and experimented with the FM tasks by a group of FM experts. As a result, the paper explains how BIM can support FM tasks in an itemised manner

Automated Negotiation Among Web Services

Software as a service is well accepted software deployment and distribution model that is grown exponentially in the last few years. One of the biggest benefits of SaaS is the automated composition of these services in a composite system. It allows users to automatically find and bind these services, as to maximize the productivity of their composed systems, meeting both functional and non-functional requirements. In this paper we present a framework for modeling the dependency relationship of different Quality of Service parameters of a component service. Our proposed approach considers the different invocation patterns of component services in the system and models the dependency relationship for optimum values of these QoS parameters. We present a service composition framework that models the dependency relations ship among component services and uses the global QoS for service selection

Predicting large scale fine grain energy consumption

Today a large volume of energy-related data have been continuously collected. Extracting actionable knowledge from such data is a multi-step process that opens up a variety of interesting and novel research issues across two domains: energy and computer science. The computer science aim is to provide energy scientists with cutting-edge and scalable engines to effectively support them in their daily research activities. This paper presents SPEC, a scalable and distributed predictor of fine grain energy consumption in buildings. SPEC exploits a data stream methodology analysis over a sliding time window to train a prediction model tailored to each building. The building model is then exploited to predict the upcoming energy consumption at a time instant in the near future. SPEC currently integrates the artificial neural networks technique and the random forest regression algorithm. The SPEC methodology exploits the computational advantages of distributed computing frameworks as the current implementation runs on Spark. As a case study, real data of thermal energy consumption collected in a major city have been exploited to preliminarily assess the SPEC accuracy. The initial results are promising and represent a first step towards predicting fine grain energy consumption over a sliding time window

SocIoTal - The development and architecture of a social IoT framework

In this paper the development and architecture of the SocIoTal platform is presented. SocIoTal is a European FP7 project which aims to create a socially-aware citizen-centric Internet of Things infrastructure. The aim of the project is to put trust, user-control and transparency at the heart of the system in order to gain the confidence of everyday users and developers. By providing adequate tools and mechanisms that simplify complexity and lower the barriers of entry, it will encourage citizen participation in the Internet of Things. This adds a novel and rich dimension to the emerging IoT ecosystem, providing a wealth of opportunities for the creation of new services and applications. These services and applications will be able to address the needs of society therefore improving the quality of life in cities and communities. In addition to technological innovation, the SocIoTal project sought to innovate the way in which users and developers interact and shape the direction of the project. The project worked on new formats in obtaining data, information and knowledge. The first step consisted of gaining input, feedback and information on IoT as a reality in business. This led to a validated iterative methodology which formed part of the SocIoTal toolkit.This work was supported by the SocIoTal project under grant agreement No 609112

Reverse Logistics in Micro Businesses : An Exploratory Study

There has been growth in managing supply chain processes for enhancing both economic and environmental benefits. Consequently, new dimensions in the supply chain have been added, with one of them being reverse logistics. Reverse logistics deals with the backward flow of goods which help firms to recover and reinstate discarded products, helping firms to realise their economic and environmental initiatives. Reverse logistics has now become a matter of strategic importance, helping to bring sustainable competitive advantage to the firm. This study recognises the inclination of the current research in reverse logistics to focus on larger firms. Hence, this research explores how smaller businesses, specifically micro enterprises, pursue reverse logistics to understand the related capabilities they have, and also to understand the way they address/perceive the related costs; this has the potential to contribute towards the development of the reverse logistics concept in micro firms. The two theoretical lenses of Resource Based View and Transaction Cost Economics are employed, both of which have the potential to explain the capabilities and the cost situation, respectively. An exploratory case study methodology is employed, and research is made on six micro retail firms. A semi-structured interview is used as the primary data collection method, supported by participant observation. The findings indicate that micro businesses may not possess all the relevant capabilities but pursue reverse logistics in their own unique way which, however, needs further development and refinement. The findings also suggest that micro businesses have developed the capabilities for reverse logistics, they however are not aware of all the benefits they can achieve through this capability. The findings also show that various cost facets prevail in the reverse logistics cost situation of the studied businesses. Not having a clear understanding of the various cost situation has again prohibited these businesses from making an optimal cost decision. This thesis realises the need to study the related capabilities and costs in the micro business context. As being small and resource constrained in nature, a phenomenon like reverse logistics – which is resource intense – can be a challenging aspect to pursue for these businesses. The study contributes to knowledge in both the reverse logistics and micro business research fields, by recognising key gaps within the related combined literature, critiquing current theory, and developing new and unique theoretical perspectives

A case-based reasoning approach to improve risk identification in construction projects

Risk management is an important process to enhance the understanding of the project so as to support decision making. Despite well established existing methods, the application of risk management in practice is frequently poor. The reasons for this are investigated as accuracy, complexity, time and cost involved and lack of knowledge sharing. Appropriate risk identification is fundamental for successful risk management. Well known risk identification methods require expert knowledge, hence risk identification depends on the involvement and the sophistication of experts. Subjective judgment and intuition usually from par1t of experts’ decision, and sharing and transferring this knowledge is restricted by the availability of experts. Further, psychological research has showed that people have limitations in coping with complex reasoning. In order to reduce subjectivity and enhance knowledge sharing, artificial intelligence techniques can be utilised. An intelligent system accumulates retrievable knowledge and reasoning in an impartial way so that a commonly acceptable solution can be achieved. Case-based reasoning enables learning from experience, which matches the manner that human experts catch and process information and knowledge in relation to project risks. A case-based risk identification model is developed to facilitate human experts making final decisions. This approach exploits the advantage of knowledge sharing, increasing confidence and efficiency in investment decisions, and enhancing communication among the project participants