Abstract.Within education, concepts such as distance learning, and open universities, are now becoming more widely used for teaching and learning. However, due to the nature of the subject domain, the teaching of Science, Technology, and Engineering are still relatively behind when using new technological approaches (particularly for online distance learning). The reason for this discrepancy lies in the fact that these fields often require laboratory exercises to provide effective skill acquisition and hands-on experience. Often it is difficult to make these laboratories accessible for online access. Either the real lab needs to be enabled for remote access or it needs to be replicated as a fully software-based virtual lab. We argue for the latter concept since it offers some advantages over remotely controlled real labs, which will be elaborated further in this paper.We are now seeing new emerging technologies that can overcome some of the potential difficulties in this area. These include: computer graphics, augmented reality, computational dynamics, and virtual worlds. This paper summarizes the state of the art in virtual laboratories and virtual worlds in the fields of science, technology, and engineering. The main research activity in these fields is discussed but special emphasis is put on the field of robotics due to the maturity of this area within the virtual-education community. This is not a coincidence; starting from its widely multidisciplinary character, robotics is a perfect example where all the other fields of engineering and physics can contribute. Thus, the use of virtual labs for other scientific and non-robotic engineering uses can be seen to share many of the same learning processes. This can include supporting the introduction of new concepts as part of learning about science and technology, and introducing more general engineering knowledge, through to supporting more constructive (and collaborative) education and training activities in a more complex engineering topic such as robotics. The objective of this paper is to outline this problem space in more detail and to create a valuable source of information that can help to define the starting position for future research.Key words: virtual laboratory, dynamics based virtual reality, virtual world, distance learning for engineering/STEM education, immersive education IntroductionRecently we have seen a number of new ideas appearing in the literature concerned with the future of education and in particular for the teaching of Science, Technology, and Engineering (STE 1 ). Some of these notions are novel while others are a re-imagining of existing ideas but in a new context. Technological examples most relevant for this study are: distance learning, elearning, virtual laboratories, virtual reality and virtual worlds, avatars, dynamics-based virtual systems, and the overall new concept of immersive education that integrates many of these ideas together. Many highly reputable institutions 2 have gathered around this challenging concept, withi...
The GO annotation dataset provided by the UniProt Consortium (GOA: http://www.ebi.ac.uk/GOA) is a comprehensive set of evidenced-based associations between terms from the Gene Ontology resource and UniProtKB proteins. Currently supplying over 100 million annotations to 11 million proteins in more than 360 000 taxa, this resource has increased 2-fold over the last 2 years and has benefited from a wealth of checks to improve annotation correctness and consistency as well as now supplying a greater information content enabled by GO Consortium annotation format developments. Detailed, manual GO annotations obtained from the curation of peer-reviewed papers are directly contributed by all UniProt curators and supplemented with manual and electronic annotations from 36 model organism and domain-focused scientific resources. The inclusion of high-quality, automatic annotation predictions ensures the UniProt GO annotation dataset supplies functional information to a wide range of proteins, including those from poorly characterized, non-model organism species. UniProt GO annotations are freely available in a range of formats accessible by both file downloads and web-based views. In addition, the introduction of a new, normalized file format in 2010 has made for easier handling of the complete UniProt-GOA data set.
Quickly solving product yield and quality problems in a complex manufacturing process is becoming increasingly more difficult. The "low hanging fruit" has been plucked using process control, statistical analysis, and design of experiments which have established a solid base for a well tuned manufacturing process. However, the dynamic "higher-tier" problems coupled with quicker time to market expectations is making finding and resolving problems quickly an overwhelming task. These dynamic "higher tier" problems include: multi-factor & nonlinear interactions; intermittent problems; dynamically changing processes; installing new processes; multiple products; and, of course, the increasing volumes of data. Data mining technology can increase product yield and quality to the next higher level by quickly finding and solving these tougher problems. Case studies of semiconductor wafer manufacturing problems are presented. A combination of self-organizing neural networks and rule induction is used to identify the critical poor yield factors from normally collected wafer manufacturing data. Subsequent controlled experiments and process changes confirmed the solutions. Wafer yield problems were solved 10x faster than standard approaches; yield increases ranged from 3% to 15%; endangered customer product deliveries were saved. This approach is flexible and can be appropriate for a number of complex manufacturing processes
In this paper we describe how the iClassroom and other technologies are providing the testbed through which we are able to design, develop, and research future intelligent environments. We describe the process of distinguishing between the technical and pedagogical aspects of immersive learning environments, while simultaneously considering both in the redefinition of effective intelligent learning spaces. This paper describes how our laboratory is working on specific projects that increase our understanding of the distinct advantages of technical design elements, like immersive visual displays, and pedagogical design elements that need to be in place as we go through the process of structuring learning situations that create constructivist, collaborative experiences. We describe specific technologies and their design across these multiple dimensions and the ways in which they are helping us better understand how to maximize technological affordances for increased positive learning outcomes. Finally, through this design research process, as we begin to better understand the affordances and iteratively create design guidelines, our hope is that eventually a prescriptive framework emerges that informs both the practice of embedded technology development and the deliberate incorporation of technical attributes into both the educational space and the pedagogy through which students learn.
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