Leading Undergraduate Students to Big Data Generation

People are facing a flood of data today. Data are being collected at unprecedented scale in many areas, such as networking, image processing, virtualization, scientific computation, and algorithms. The huge data nowadays are called Big Data. Big data is an all encompassing term for any collection of data sets so large and complex that it becomes difficult to process them using traditional data processing applications. In this article, the authors present a unique way which uses network simulator and tools of image processing to train students abilities to learn, analyze, manipulate, and apply Big Data. Thus they develop students handson abilities on Big Data and their critical thinking abilities. The authors used novel image based rendering algorithm with user intervention to generate realistic 3D virtual world. The learning outcomes are significant

You can lead a horse to water… are clinical students getting the message about the library and information skills support that is available?

Cambridge University Library is the recipient of a grant from the Arcadia Trust to investigate issues and challenges in delivering academic library services in the digital era. One project under this auspice has been IRIS: Induction, Research and Information Skills, which attempted to map the information skills and needs of students at Cambridge University. The results of this study will be used to provide information in planning future services and facilities for students. Students were invited to complete an online survey asking about which online information resources they use most frequently, from whom they hear about new resources, and where they go for help with information-seeking. Librarians across the tripartite Cambridge system, in 60 college, department, and University libraries, were also surveyed with regard to what training, induction, and support they offered and to whom. This article will focus on the responses of 115 medical students who participated in the survey, accounting for 6.5% of the total survey responses. While acknowledging that student respondents were self-selecting, the results raise questions about how well the librarians’ message is getting across and how librarians can better serve students in the digital age

Engineering at San Jose State University, Winter 2014

https://scholarworks.sjsu.edu/engr_news/1012/thumbnail.jp

Research and Education in Computational Science and Engineering

Over the past two decades the field of computational science and engineering (CSE) has penetrated both basic and applied research in academia, industry, and laboratories to advance discovery, optimize systems, support decision-makers, and educate the scientific and engineering workforce. Informed by centuries of theory and experiment, CSE performs computational experiments to answer questions that neither theory nor experiment alone is equipped to answer. CSE provides scientists and engineers of all persuasions with algorithmic inventions and software systems that transcend disciplines and scales. Carried on a wave of digital technology, CSE brings the power of parallelism to bear on troves of data. Mathematics-based advanced computing has become a prevalent means of discovery and innovation in essentially all areas of science, engineering, technology, and society; and the CSE community is at the core of this transformation. However, a combination of disruptive developments---including the architectural complexity of extreme-scale computing, the data revolution that engulfs the planet, and the specialization required to follow the applications to new frontiers---is redefining the scope and reach of the CSE endeavor. This report describes the rapid expansion of CSE and the challenges to sustaining its bold advances. The report also presents strategies and directions for CSE research and education for the next decade.Comment: Major revision, to appear in SIAM Revie

Benefits to the U.S. from Physicists Working at Accelerators Overseas

We illustrate benefits to the U.S. economy and technological infrastructure of U.S. participation in accelerators overseas. We discuss contributions to experimental hardware and analysis and to accelerator technology and components, and benefits stemming from the involvement of U.S. students and postdoctoral fellows in global scientific collaborations. Contributed to the proceedings of the Snowmass 2013 Community Summer Study.Comment: 23 pages, 1 figur

Skills and Knowledge for Data-Intensive Environmental Research.

The scale and magnitude of complex and pressing environmental issues lend urgency to the need for integrative and reproducible analysis and synthesis, facilitated by data-intensive research approaches. However, the recent pace of technological change has been such that appropriate skills to accomplish data-intensive research are lacking among environmental scientists, who more than ever need greater access to training and mentorship in computational skills. Here, we provide a roadmap for raising data competencies of current and next-generation environmental researchers by describing the concepts and skills needed for effectively engaging with the heterogeneous, distributed, and rapidly growing volumes of available data. We articulate five key skills: (1) data management and processing, (2) analysis, (3) software skills for science, (4) visualization, and (5) communication methods for collaboration and dissemination. We provide an overview of the current suite of training initiatives available to environmental scientists and models for closing the skill-transfer gap

The future of research universities. Is the model of research-intensive universities still valid at the beginning of the twenty-first century?

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