Spartan Daily, April 18, 1983

Volume 80, Issue 48https://scholarworks.sjsu.edu/spartandaily/7030/thumbnail.jp

Examining the issues & challenges of email & e-communications. 2nd Northumbria Witness Seminar Conference, 24-25 Oct 2007 Northumbria University, Newcastle upon Tyne.

These proceedings capture the content of the second Witness Seminar hosted by Northumbria University’s School of Computing, Engineering and Information Sciences. It followed the success of the first witness seminar in terms of its format and style but differed in that it focused on one topic - managing email and other electronic communications technologies from a records perspective. As before the witnesses were invited to share their views and opinions on a specific aspect taking as their starting point a pertinent published article(s). Three seminars explored the business, people and technology perspectives of email and e-communications, asking the following questions: What are the records management implications and challenges of doing business electronically? Are people the problem and the solution? Is technology the problem or panacea? The final seminar, 'Futurewatch', focused on moving forward, exploring new ways of working, potential new technologies and what records professionals and others need to keep on their radar screens

Towards Parallel Educational Worlds

Proceedings of: 2011 IEEE Global Engineering Education Conference (EDUCON 2011): Learning Environments and Ecosystems in Engineering Education. Amman, Jordan, 4-6 April 2011.Augmented Reality, 3D virtual worlds, etc.: the technology has evolved tremendously and so has its application to the field of education. Digital technologies have advanced to the point, where we are reproducing digitally more and more aspects of our life. We have parallel worlds: on the one hand the real world, and on the other virtual worlds, that can in fact be linked to the real one. They have different properties, but they can enrich and complement each other. In this paper, we explore the possibilities and challenges of these parallel worlds for educational uses.The eMadrid Excellence Network is being funded by the Madrid Regional Government (Comunidad de Madrid) with grant No. S2009/TIC-165. We wish to acknowledge stimulating discussions with our partners in the context of the network. Partial support has also been received from the Learn3 project (TIN2008-05163) and the SOLITE project (CYTED 508AC0341).Publicad

Hypergraph Partitioning in the Cloud

The thesis investigates the partitioning and load balancing problem which has many applications in High Performance Computing (HPC). The application to be partitioned is described with a graph or hypergraph. The latter is of greater interest as hypergraphs, compared to graphs, have a more general structure and can be used to model more complex relationships between groups of objects such as non-symmetric dependencies. Optimal graph and hypergraph partitioning is known to be NP-Hard but good polynomial time heuristic algorithms have been proposed. In this thesis, we propose two multi-level hypergraph partitioning algorithms. The algorithms are based on rough set clustering techniques. The first algorithm, which is a serial algorithm, obtains high quality partitionings and improves the partitioning cut by up to 71\% compared to the state-of-the-art serial hypergraph partitioning algorithms. Furthermore, the capacity of serial algorithms is limited due to the rapid growth of problem sizes of distributed applications. Consequently, we also propose a parallel hypergraph partitioning algorithm. Considering the generality of the hypergraph model, designing a parallel algorithm is difficult and the available parallel hypergraph algorithms offer less scalability compared to their graph counterparts. The issue is twofold: the parallel algorithm and the complexity of the hypergraph structure. Our parallel algorithm provides a trade-off between global and local vertex clustering decisions. By employing novel techniques and approaches, our algorithm achieves better scalability than the state-of-the-art parallel hypergraph partitioner in the Zoltan tool on a set of benchmarks, especially ones with irregular structure. Furthermore, recent advances in cloud computing and the services they provide have led to a trend in moving HPC and large scale distributed applications into the cloud. Despite its advantages, some aspects of the cloud, such as limited network resources, present a challenge to running communication-intensive applications and make them non-scalable in the cloud. While hypergraph partitioning is proposed as a solution for decreasing the communication overhead within parallel distributed applications, it can also offer advantages for running these applications in the cloud. The partitioning is usually done as a pre-processing step before running the parallel application. As parallel hypergraph partitioning itself is a communication-intensive operation, running it in the cloud is hard and suffers from poor scalability. The thesis also investigates the scalability of parallel hypergraph partitioning algorithms in the cloud, the challenges they present, and proposes solutions to improve the cost/performance ratio for running the partitioning problem in the cloud. Our algorithms are implemented as a new hypergraph partitioning package within Zoltan. It is an open source Linux-based toolkit for parallel partitioning, load balancing and data-management designed at Sandia National Labs. The algorithms are known as FEHG and PFEHG algorithms

Developing an API to Supply Third-party Applications with Environmental Data

In healthcare, weather-sensitivity and the effect of environmental factors on various diseases were subject to extensive research in the last decades. Mostly without discovering statistically significant relationships between diseases and environmental parameters. This is often attributed to a lack of scale for existing studies. Currently, there are no openly available solutions that can support surveys in this regard.Such solutions should be easy to integrate with an existing study platform. In turn, environmental data needs to be fetched for multiple users. This fact led to studies restricting participants in terms of their location or other factors. Consequently, this also meant, that the size of the studies was limited due to the placed constraints. Through the advance of technology, it is now possible to easily retrieve additional information from participants via their mobile smart devices which can be used to fetch various other types of data. These circumstances led to the creation of an environmental data API described in this thesis. It provides functionality to retrieve environmental data from various data sources for a given tuple of latitude, longitude, and timestamp. The API facilitates adding new data sources by simply extending the provided examples. There are no restrictions in terms of spatial or temporal resolution or even source of the data. The resulting API fetches environmental data from multiple sources. It also facilitates obtaining data from other data sources and querying by researchers - including options to filter the data by various parameters. Finally, the API also supports converting between different units