Computer experiment – a case study for modelling and simulation of manufacturing systems

Deterministic computer simulation of physical experiments is now a common technique in science and engineering. Often, physical experiments are too time consuming, expensive or impossible to conduct. Complex computer models or codes, rather than physical experiments lead to the study of computer experiments, which are used to investigate many scientific phenomena. A computer experiment consists of a number of runs of the computer code with different input choices. The Design and Analysis of Computer Experiments is a rapidly growing technique in statistical experimental design. This paper aims to discuss some practical issues when designing a computer simulation and/or experiments for manufacturing systems. A case study approach is reviewed and presented.

Some practical issues in the design and analysis of computer experiments

Deterministic computer simulations of physical experiments are now common techniques in science and engineering. Often, physical experiments are too time consuming, expensive or impossible to conduct. Complex computer models or codes, rather than physical experiments lead to the study of computer experiments, which are used to investigate many scientific phenomena of this nature. A computer experiment consists of a number of runs of the computer code with different input choices. The Design and Analysis of Computer Experiments is a rapidly growing technique in statistical experimental design. This thesis investigates some practical issues in the design and analysis of computer experiments and attempts to answer some of the questions faced by experimenters using computer experiments. In particular, the question of the number of computer experiments and how they should be augmented is studied and attention is given to when the response is a function over time.

Vocational education in science, technology, engineering and maths (STEM) : Curriculum innovation through school industry partnerships

Governments have recognised that the technological trades rely on knowledge embedded traditionally in science, technology, engineering and mathematics (STEM) disciplines. However, there is substantial evidence that students are turning away from these subjects in schools because the school curriculum is seen as irrelevant, with clear implications for not just vocational education but also higher education. In this paper, we report preliminary findings on the development of two curricula that attempt to integrate science and mathematics with workplace knowledge and practices. We argue that these curricula provide educational opportunities for students to pursue their preferred career pathways. These curricula were co-developed by industry and educational personnel across three industry sectors, namely, mining industry, aerospace and wine tourism. The aim was to provide knowledge appropriate for students moving from school to the workplace as trade apprentices in the respective industries. The analysis of curriculum and associated policy documents reveals that the curricula adopt applied learning orientations through teaching strategies and assessment practices which focus on practical skills. However, although key theoretical science and maths concepts have been well incorporated, the extent to which knowledge deriving from workplace practices is included varies across the curricula. The extent to which applications of concepts are included in the models depends on a number of factors not least the relevant expertise of the teacher as a practitioner in the industry. Our findings highlight the importance of teachers having substantial practical industry experience and the role that whole school policies play in attempts to align the range of learning experiences with the needs of industry.

Social engineering in social networking sites : phase-based and source-based models

Social networking sites (SNSs), with their large numbers of users and large information base, seem to be perfect breeding grounds for exploiting the vulnerabilities of people, the weakest link in security. Deceiving, persuading, or influencing people to provide information or to perform an action that will benefit the attacker is known as “social engineering.” While technology-based security has been addressed by research and may be well understood, social engineering is more challenging to understand and manage, especially in new environments such as SNSs, owing to some factors of SNSs that reduce the ability of users to detect the attack and increase the ability of attackers to launch it. This work will contribute to the knowledge of social engineering by presenting the first two conceptual models of social engineering attacks in SNSs. Phase-based and source-based models are presented, along with an intensive and comprehensive overview of different aspects of social engineering threats in SNSs.

Starting out in STEM : a study of young men and women in first year science, technology, engineering and mathematics courses

In late 2011, first year university students in science, technology, engineering and mathematics (STEM) courses across Australia were invited to participate in the international Interests and Recruitment in Science (IRIS) study. IRIS investigates the influences on young people's decisions to choose university STEM courses and their subsequent experiences of these courses. The study also has a particular focus on the motivations and experiences of young women in courses such as physics, IT and engineering given the low rates of female participation in these fields. Around 3500 students from 30 Australian universities contributed their views on the relative importance of various school and non-school influences on their decisions, as well as insights into their experiences of university STEM courses so far. It is hoped that their contributions will help improve recruitment, retention and gender equity in STEM higher education and careers.

Vocational education in science technology, engineering and maths (STEM) : Curriculum innovation through industry school partnerships

Governments have recognised that the technological trades rely on knowledge embedded traditionally in science, technology, engineering and mathematics (STEM) disciplines. In this paper, we report preliminary findings on the development of two curricula that attempt to integrate science and mathematics with workplace knowledge and practices. We argue that these curricula provide educational opportunities for students to pursue their preferred career pathways. These curricula were co-developed by industry and educational personnel across two industry sectors, namely, mining and aerospace. The aim was to provide knowledge appropriate for students moving from school to the workplace in the respective industries. The analysis of curriculum and associated policy documents reveals that the curricula adopt applied learning orientations through teaching strategies and assessment practices which focus on practical skills. However, although key theoretical science and maths concepts have been well incorporated, the extent to which knowledge deriving from workplace practices is included varies across the curricula. Our findings highlight the importance of teachers having substantial practical industry experience and the role that whole school policies play in attempts to align the range of learning experiences with the needs of industry.

Sex differences in the perceived value of outreach and museums/science centres in students' decisions to enrol in university science, technology and engineering courses

This paper reports a number of findings from the Interests and Recruitment in Science (IRIS) study carried out in Australia in 2011. The findings concern the perceptions of first year university students in science, technology and engineering courses about the influence of museums/science centres and outreach activities on their choice of course. The study found that STE students in general tended to rate museums/science centres as more important in their decisions than outreach activities. However, a closer examination showed that females in engineering courses were significantly more inclined to rate outreach activities as important than were males in engineering courses or females in other courses. The implications of this finding for strategies to encourage more young women into engineering are discussed.

Science, Technology, Engineering, and Maths (STEM)

"Historically, science had a place in education before the time of Plato and Aristotle (e.g., Stonehenge). Technology gradually increased since early human inventions (e.g., indigenous tools and weapons), rose up dramatically through the industrial revolution and escalated exponentially during the twentieth and twenty-first centuries, particularly with the advent of the Internet. Engineering accomplishments were evident in the constructs of early civil works, including roads and structural feats such as the Egyptian pyramids. Mathematics was not as clearly defined BC (Seeds 2010), but was utilized for more than two millennia (e.g., Archimedes, Kepler, and Newton) and paved its way into education as an essential scientific tool and a way of discovering new possibilities. Hence, combining science, technology, engineering, and mathematics (STEM) areas should not come as a surprise but rather as a unique way of packaging what has been ..."--Publisher Website

Design of a tablet sized human-computer interface and its effect on situation awareness

Emergency Response Teams increasingly use interactive technology to help manage information and communications. The challenge is to maintain a high situation awareness for different interactive devices sizes. This research specifically compared a handheld interactive device in the form of an iPad with a large interactive multi-touch tabletop. A search and rescue inspired simulator was designed to test operator situation awareness for the two sized devices. The results show that operators had better situation awareness on the tabletop device when the operation related to detecting of moving targets, searching target locations, distinguishing target types, and comprehending displayed information.

A survey of indian logic from the point of view of computer science

Indian logic has a long history. It somewhat covers the domains of two of the six schools (darsanas) of Indian philosophy, namely, Nyaya and Vaisesika. The generally accepted definition of Indian logic over the ages is the science which ascertains valid knowledge either by means of six senses or by means of the five members of the syllogism. In other words, perception and inference constitute the subject matter of logic. The science of logic evolved in India through three ages: the ancient, the medieval and the modern, spanning almost thirty centuries. Advances in Computer Science, in particular, in Artificial Intelligence have got researchers in these areas interested in the basic problems of language, logic and cognition in the past three decades. In the 1980s, Artificial Intelligence has evolved into knowledge-based and intelligent system design, and the knowledge base and inference engine have become standard subsystems of an intelligent system. One of the important issues in the design of such systems is knowledge acquisition from humans who are experts in a branch of learning (such as medicine or law) and transferring that knowledge to a computing system. The second important issue in such systems is the validation of the knowledge base of the system i.e. ensuring that the knowledge is complete and consistent. It is in this context that comparative study of Indian logic with recent theories of logic, language and knowledge engineering will help the computer scientist understand the deeper implications of the terms and concepts he is currently using and attempting to develop.

Treewidth: theory and applications to computer science

This report is an introduction to the concept of treewidth, a property of graphs that has important implications in algorithms. Some basic concepts of graph theory are presented in the first chapter for those readers that are not familiar with the notation. In Chapter 2, the definition of treewidth and some different ways of characterizing it are explained. The last two chapters focus on the algorithmic implications of treewidth, which are very relevant in Computer Science. An algorithm to compute the treewidth of a graph is presented and its result can be later applied to many other problems in graph theory, like those introduced in the last chapter.