i++ School Newsletter

Week commencing 16 March 2009

Previous Newsletters

IEEE United Nations Humanitarian Technology Project

Professor Hani Hagras has recently been invited as world leading expert in Computational Intelligence and energy management to participate in the Humanitarian Technology Challenge project which is a partnership between the IEEE and the United Nations Foundation (UN) targeted at developing technological solutions to some of the greatest challenges facing public health and disaster response workers today.  This is the first time that a technology association like the IEEE and a major humanitarian organization like the UN have formed an up-front collaborative relationship.

The objective is to create sustainable solutions that can be implemented locally, within the environmental, cultural, structural, political and socio-economic conditions where they will be deployed. This will be done by bringing together IEEE experts, other technologists, and humanitarians around the world to collaborate for the benefit of humanity. Five potential needs have been prioritised for consideration as “challenges” to be addressed which are;

• Reliable Electricity – Availability of power for electronic devices
• Data Connectivity of Rural District Health Offices --  Capability of exchanging data between central health facilities and remote field offices
• Local Management and Tracking of Supply Distribution – Ensure that supplies are getting to the people that need them in order to maximize the impact of assistance
• Incident Tracking – Determine locations and extent to medical problems in order to focus resources
• Patient ID and Tie to Health Records – Maintain consistent patient records, including when patients visit different clinics and when they relocate.

Professor Hagras will be working with the reliable electricity challenge, where he will be working with other colleagues to employ computational intelligence techniques to provide better energy management and savings in addition to the provision of reliable electricity.

Conference to honour physicists

Two long-standing members of staff at the University of Essex are to be honoured at a conference hosted to mark their retirement and contribution to the study of physics.

Professors Brian Ridley and Rodney Loudon, who combined have worked at the University for more than 80 years, are leaders in the field of semiconductor and optics research. Between them they have won some of the most prestigious international physics awards.

The conference, to be held at Wivenhoe House Hotel on 20 March, is expected to attract up to 60 current and former colleagues of Professors Ridley and Loudon as well as students working in the field. Topics for discussion include ‘Laser Physics: A 50 Year Odyssey,’ ‘Hot Electrons Fifty Years Ago,’ and ‘Holographic Ghost Imaging.’

The event is being organised by Professors Naci Balkan and Mike Adams. Professor Adams said: ‘Together, Brian and Rodney have made a tremendous contribution to the study of physics. Specialists in the field greatly value Brian’s theory on the transferred electron effect which is used in a range of applications including collision avoidance radar, vehicle ABS and burglar alarms; while Rodney’s paper ‘Squeezed Light’ has been cited 1,015 times according to the Web of Science.’

Professor Brian Ridley joined the University in 1964 and was awarded a professorship in 1986. He was one of three founding members of the University’s former Department of Physics and is best known for his research on electron transport in semiconductors. He is a Fellow of the Royal Society and in 2001 received the Institute of Physics Paul Dirac Medal and Prize which is awarded for outstanding contributions to theoretical physics.

Professor Rodney Loudon has been a member of University staff since 1967 and has also held visiting professorial posts at Yale and École Polytechnique, Lausanne. He is best known for his research on quantum optics but his research interests also include spontaneous emission and noise in optical amplifiers and lasers, applications of quantum optics theory in information technology, and forces exerted on dielectrics by laser light. He is also a Fellow of the Royal Society and has been the recipient of a number of awards including the Institute of Physics Thomas Young Medal and Prize (1987) and the Optical Society of America Max Born Award (1992).

The conference, entitled 50 Years of Semiconductor and Optics Research, is being supported by Rank Prize Funds and the Institute of Physics.

EU Shoal Project attracts Worldwide Media Attention

The Essex-based SHOAL Project has been featured in various international media publications during the last week. The project was recently awarded a share of £2.5 million to develop a school of advanced robotic fish to analyse contaminants in ports. The  full story appeared in i++ two weeks ago and further developments have been highlighted in The Telegraph and on Yahoo News. 

Computer Science and Electronic Engineering Conference

The Computer Science and Electronic Engineering Conference (CEEC), is organised by student researchers for student researchers and provides an ideal venue for people from the disciplines of Mathematics, Computer Science, Engineering, Biology and Finance to create a forum in which they may work together, discuss, compare and debate different innovative ideas and solutions. The Conference takes place on 3 July 2009 at the School of Computer Science and Electronic Engineering here at the University of Essex, with an exact location to be confirmed.

Important dates
Paper Submission deadline: 31 May 2009
Notification: Monday 16 June 2009
Camera-ready Manuscript: 21 June 2009
Registration deadline: 30 June 2009
Conference day : 3 July 2009

Paper Accepted

B. Awwad Shiekh Hasan and J.Q. Gan, Unsupervised adaptive GMM for BCI, International IEEE EMBS Conf. on Neural Engineering, Antalya, Turkey, 2009.

Abstract - An unsupervised adaptive Gaussian mixture model is introduced for online brain-computer interfaces (BCI). The method is tested on two BCI data sets, demonstrating significant performance improvement in comparison with a static model.