Supporting scientists in re-engineering sequential programs to parallel using model-driven engineering

Developing complex computational-intensiveand data-intensive scientific applications requires effectiveutilization of the computational power of the availablecomputing platforms including grids, clouds, clusters, multicoreand many-core processors, and graphical processingunits (GPUs). However, scientists who need to leverage suchplatforms are usually not parallel or distributed programmingexperts. Thus, they face numerous challenges whenimplementing and porting their software-based experimentaltools to such platforms. In this paper, we introduce asequential-to-parallel engineering approach to help scientistsin engineering their scientific applications. Our approach isbased on capturing sequential program details, plannedparallelization aspects, and program deployment details usinga set of domain-specific visual languages (DSVLs). Then, usingcode generation, we generate the corresponding parallelprogram using necessary parallel and distributedprogramming models (MPI, OpenCL, or OpenMP). Wesummarize three case studies (matrix multiplication, N-Bodysimulation, and signal processing) to evaluate our approach.

An evaluation of streaming digital video resources in on-and off-campus engineering management education

A recent television documentary on the Columbia space shuttle disaster was converted to streaming digital video format for educational use by on- and off-campus students in an engineering management study unit examining issues in professional engineering ethics. An evaluation was conducted to assess the effectiveness of this new resource. Use of the video was optional, and about half of the class reported using the video, though usage was 90.0% for off-campus students. Most on-campus students accessed the video on-line, while all off-campus students accessed the video via CD-ROM. Off-campus students rated the educational value of the video higher than on-campus students, and were more likely to indicate that the video helped them understand the issues being studied. Most students were able to view the videos without any technical playback problems.

Where did we go wrong? An examination of students treatment of experimental error in engineering mechanics laboratories

The ability of engineers and applied scientists to undertake experimental measurements is a fundamental requirement of the profession. However, it is not simply good enough to be able to perform experiments if we are not able to interpret the results. In this study, reports prepared by mechanical engineering students were examined to determine how students dealt with the disparity between experimental measurements and theoretical results in their Engineering Mechanics laboratories. Analysis of the reports, and discussions with students in their laboratory classes, revealed a superficial understanding or regard for experimental error. This superficial treatment of experimental error is, most likely, due to a number of factors that are discussed. Some possible strategies for addressing the issue are also examined.

Online discussion in engineering education : student responses and learning outcomes

A ubiquitous and widely used feature of online learning environments is the asynchronous discussion board. This chapter presents a case study of the introduction and evaluation of student use of an online discussion in an engineering management study unit. We introduced an assessable assignment task based on student use of an online discussion, in response to falling student unit evaluation results after we initially moved the unit to wholly online delivery mode. Both quantitative and qualitative unit evaluation data suggest that students perceive value in the online discussion activities. A regression analysis based on discussion usage data suggests that students derived significant learning outcome benefit toward their final unit grade from making reflective postings in the online discussion.

Modern enhancements in teaching design theories to mechanical engineering students

This paper describes the application of computer aided design (CAD) in teaching advanced design methodologies to fourth-year undergraduate students majoring in mechanical engineering. This involves modern enhancements in teaching strategies for subjects such as design-for-X (DFx) and failure mode effect analysis (FMEA) concepts, which are traditionally categorised as advanced design methodologies. The main subsets of DFx including design-for-assembly (DFA), design-for-disassembly (DFD), design-for-manufacturing (DFM), design-for-environment (DFE) and design-for-recyclability (DFR) were covered by studying various engineering and consumer products. The unit was designed as a combination of practical hands-on workshop-based classes along with a software-based evaluation of different products. In addition to CAD, finite element modelling techniques were utilised to enhance the students’ understanding of design faults and failures. The inquiry into teaching practice and design of this fourth-year unit was carried out during past two years and it revealed some interesting outcomes from our teaching practice in terms of students’ learning experiences. Finally, the paper discusses some critical factors in the context of teaching advanced design methodologies to the undergraduates in mechanical engineering and even manufacturing engineering.

Video driven traffic modelling in ParamicsTM

With urbanization and vehicle availability, there exist many traffic problems including congestion, environmental impact and safety. In order to address these problems, we propose a video driven traffic modelling system in this paper. The system can simulate real-world traffic activities in a computer, based on traffic data recorded in videos. Video processing is employed to estimate metrics such as traffic volumes. These metrics are used to update the traffic system model, which is then simulated using the Paramics™ traffic simulation platform. Video driven traffic modelling has widespread potential application in traffic systems, due to the convenience and reduced costs of model development and maintenance. Experiments are conducted in this paper to demonstrate the effectiveness of the proposed system.

Robust network traffic classification

As a fundamental tool for network management and security, traffic classification has attracted increasing attention in recent years. A significant challenge to the robustness of classification performance comes from zero-day applications previously unknown in traffic classification systems. In this paper, we propose a new scheme of Robust statistical Traffic Classification (RTC) by combining supervised and unsupervised machine learning techniques to meet this challenge. The proposed RTC scheme has the capability of identifying the traffic of zero-day applications as well as accurately discriminating predefined application classes. In addition, we develop a new method for automating the RTC scheme parameters optimization process. The empirical study on real-world traffic data confirms the effectiveness of the proposed scheme. When zero-day applications are present, the classification performance of the new scheme is significantly better than four state-of-the-art methods: random forest, correlation-based classification, semi-supervised clustering, and one-class SVM.

A framework for managing learning teams in engineering

BACKGROUND: Team learning is an integral part of engineering education today and teamwork knowledge, teamwork skills and teamwork product have been included as one of the major components of engineering graduate outcomes in undergraduate engineering course/program curriculum. In spite of enormous research advances in theoretical aspects of learning and working in teams, anecdotal evidence suggests that most engineering academic staff are inundated by student complaints of not being able to work in a learning team due to numerous reasons. In addition to student complaints, most engineering academic staff are non-expert in team learning theories and methodologies and hence are unsure of specific learning outcomes of a teamwork, approaches to achieve those learning outcomes, suitability of team learning in a particular unit/subject, planning required for implementing teamwork, implementation and monitoring teamwork and teamwork reflection. Too often engineering academic staff include teamwork, yet without adequate preparation and with little understanding about how to use their time to achieve the greatest gains for themselves or for their students. Hence, there is a clear need for a framework for managing learning teams in engineering units.
PURPOSE OR GOAL: This study develops a framework for managing learning teams in engineering units through extensive review of existing literature and anecdotal practices. The focus is to provide step-by-step procedure so that the problems of team learning in engineering can be reduced. Depending upon the time and resources available to academic staff, the framework would help to choose an optimal path and associated strategies.
APPROACH: This study uses evidence-based literature knowledge to develop a framework that help to manage engineering students’ learning teams. The literature information are discussed in reference to anecdotal practices from undergraduate engineering classrooms.
DISCUSSION: The literature review suggests that for better management of learning teams, engineering academic staff need to focus on specifying learning outcomes of a teamwork, identifying appropriate approaches to achieve these learning outcomes, judging the suitability of team learning in a particular learning context, developing a clear plan for implementing teamwork, implementing and monitoring teamwork and reflecting and re-evaluating teamwork. Elaborated discussions regarding these issues can help academic staff to manage learning teams effectively and efficiently.
RECOMMENDATIONS/IMPLICATIONS/CONCLUSION: Depending upon the availability of time and resources and the suitability of a particular educational context, managing engineering learning teams can be both simple as well as complex. The developed framework may assist engineering academic staff to manage teamwork in their engineering units. For further research, the framework need to implemented, monitored, evaluated and revised.

Simplified framework for managing team learning in engineering subjects

Teamwork has been included as a major component of graduate attributes in all engineering programs at universities. In spite of enormous research advances in theoretical aspects of learning and working in teams, anecdotal evidence suggests that most engineering academic staff are inundated by student complaints of not being able to learn and work in teams due to numerous reasons. In order to facilitate engineering academic staff and engineering schools, this study develops a simplified framework for managing learning teams in engineering subjects that integrates theoretical conceptions, empirical evidences and anecdotal practices by reviewing a substantial body of existing literature. The framework identifies that in addition to managing student complaints about learning and working in teams more effectively and efficiently, engineering academic staff and engineering schools need to focus on specifying learning outcomes of teamwork, identifying appropriate approaches to achieve these learning outcomes, judging the suitability of teamwork-based learning in a particular educational context, developing a clear plan for implementing teamwork, implementing and monitoring teamwork, and reflecting and re-evaluating teamwork. The developed framework can be a useful tool to help understand these essential components and complexities of team learning.

Australasian partnership in a first-year engineering course: Deakin University and Wuhan University of Science and Technology

This paper presents the results of domestic Chinese undergraduate engineering course taught by international Australasian teaching staff. The project is a part of a teaching collaboration between Deakin University and Wuhan University of Science and Technology. The cohort of students from Wuhan was a freshman undergraduate engineering course in mechanical engineering. The particular subject was a freshman engineering-materials course taught in English. The course covered an introduction to material-science principles and practices. A survey was used for evaluating student perceptions. It is aimed that this study will help academics from Deakin University to better understand student experiences, and to identify the current challenges and barriers faced in student learning. Analysis of the survey has shown that 90% of students agreed that they were motivated to learn and achieve the learning goals through this collaborative program. Around 90% of students found that group-based practical activities were helpful in achieving learning goals. Overall, 90% of students strongly agreed they were satisfied with the method of teaching.

Control layer resource management in SDN-IoT networks using multi-objective constraint

Software Defined Networking (SDN) and Internet of Things (IoT) integration has thrown many critical challenges. Specifically, in heterogeneous SDN-IoT ecosystem, optimized resources utilization and effective management at the control layer is very difficult. This mainly affects the application specific Quality of Service (QoS) and energy consumption of the IoT network. Motivated from this, we propose a new Resource Management (RM) method at the control layer, in distributed SDN-IoT networks. This paper starts with reasons that why at control layer RM is more complex in the SDN-IoT ecosystem. After-that, we highlight motivated examples that necessitate to investigate new RM methods in SDN-IoT context. Further, we propose a novel method to compute controller performance. Theoretical analysis is conducted to prove that the proposed method is better than the existing methods.

Comparative academic performance of engineering and technology students at Deakin University, Australia

Students completing three-year engineering technology and four-year professional engineering undergraduate courses may undertake a number of common study units. To gain an objective understanding of the academic performance characteristics of both student groups in the engineering and technology programs at Deakin University (Australia), a study was  undertaken of close to 9000 unit enrollments. It was found that: overall the BTech withdrawal rate was about 20% higher than for BE students; the rate of withdrawal was significantly different between the two student groups; the grade distribution for completing students was not significantly different between the two groups; the mean final grade was not significantly different between the two student groups; the failure rate was not significantly different between the two student groups; and the overall wastage rate (withdrawn rate plus fail rate) was significantly higher for BTech students. Other related results are also reported.

Distance learning for laboratory practical work in microcontrollers

This paper presents a simple and relatively straightforward solution to the problems of equity in laboratory practical exposure between distance-education students and their traditional, on-campus, fellow cohort. This system has been implemented for the past five years in a university that is amongst the leaders in distance education delivery and has proved to be extremely successful and very well accepted by all students. While the intention was to allow distance education students easy access to the required laboratory practical content of the course, the solution found has proved to have many advantages for the on-campus students. Although this specific implementation is based upon microcontroller technology units in an engineering degree course, the methodology is easily transferable to other disciplines and courses.

Authenticity in assessment : reflecting undergraduate study and professional practice

The literature suggests that assessment is a powerful tool for influencing student study habits. It is also recognized that there is a tension between traditional forms of assessment and newer forms of assessment that offer a more authentic representation of practice, but are more complex and expensive to administer. The international trend in undergraduate engineering course accreditation to move to demonstration of attainment of graduate attributes poses new challenges in assessment of learning. A case study based on integrating assessment practices across the year levels of an engineering management studies stream in an undergraduate course is presented. Key features of the assessment portfolio include: the use of assessment in the first year as a foundational tool to establish student study habits and skills; the evolution of assessment tasks by the fourth year to reflect the world of professional practice and to allow students to demonstrate their integration of knowledge and skills; the weighting of assessment tasks to indicate the value attached to particular tasks; the structured inclusion of group work; a concern for student and staff workloads; the recognition of student diversity, in particular the needs of off-campus and mature-age students; and the matching of assessment tasks to professional accreditation requirements.

Fuzzy logic based metric in software testing

How to provide cost-effective strategies for Software Testing has been one of the research focuses in Software Engineering for a long time. Many researchers in Software Engineering have addressed the effectiveness and quality metric of Software Testing, and many interesting results have been obtained. However, one issue of paramount importance in software testing – the intrinsic imprecise and uncertain relationships within testing metrics – is left unaddressed. To this end, a new quality and effectiveness measurement based on fuzzy logic is proposed. The software quality features and analogy-based reasoning are discussed, which can deal with quality and effectiveness consistency between different test projects. Experimental results are also provided to verify the proposed measurement.