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3D printing facilities available

3D modelSYS Consulting, the consultancy arm of CMP, offer an in-house 3D printing facility which can be used to create solid objects from a digital image. The team have the expertise to laser scan objects and create robust digital models which can then be used for 3D printing.

For further details visit 3D facilities printing offer

To discuss an idea for a 3D model contact Dr Stephen Laycock


Virtual 3D models of 6 castles from the East of England and Normandy

image courtesy of EDPA team of computing scientists and historians from the schools of Computing and History, part of the VIRTUAL PAST collaboration between CMP and HIS, is taking just months to assemble Virtual 3D models of castles from across the East of England and Normandy in France.  The models will include Norwich, Rochester, Colchester and Hastings Castles, plus Falaise and Caen of Northern France.
 
Virtual Past successfully obtained a grant for an estimated £120,000 to create the 3D model of the six castles. The Norfolk museums and archaeology service intends to exhibit the 3D virtual tour of Norwich Castle by the end of summer.
 
For more information, download We’re bringing history to life (PDF, 216 Kb) or go to  EDP 24 news article 

Smart Phone App Detects Emotion in Voice

A local company is working with researchers in CMP to develop a smart-phone app that can detect emotion in a voice signal.  EI Technologies of Saffron Walden are developing an app that can "listen" all the time to its owner's voice and extract features from the audio signal, which can then be analysed off-line to determine the speaker's emotional state at any time.
smartphone 350px
These features include things such as the pitch, intensity and duration of speech sounds and are known as paralinguistic features. The target application for this technology is people who are undergoing treatment for depression.  They are usually asked to keep a diary of their emotional state, but many people find this very difficult to maintain.  By monitoring their voice throughout the day, their physician can pinpoint exactly when they felt depressed, angry, sad etc. and discuss with them what external (or internal) factors led to this state: this information is vital in understanding the causes of their condition.
 
Prof. Stephen Cox, who is acting as scientific adviser to the company, said that paralinguistics is currently a hot area of research in computer speech processing.  "Interest in this area grew considerably in 2009 when there was an 'Emotion Challenge' workshop at an international conference in Brighton, UK, at which researchers defined tasks and data to be used in these studies.  The technology is possible because of advances in machine-learning algorithms, which enable computers to discover automatically what features in a signal are important for discriminating between different emotions."  Crucially, there are no privacy issues involved, because the features collected by the app whilst it is “listening” cannot be used to reconstruct the speech.
 
EI Technologies and Prof. Cox have been awarded a Technology Strategy Board grant of £150k to develop the technology further.

CMP PhD Student wins IBM Mainframe Contest 2012

David Cutting
The IBM Mainframe Contest is an annual contest run by IBM for students to learn and experience mainframe skills. Although thought of by some as out-dated in fact Mainframe systems remain at the core of many large business operations such as banks and insurance companies. The Mainframe challenge is an opportunity for students to develop some skills in the use of zOS and other associated Mainframe technologies such as CICS.
 
The competition has three stages of increasing complexity with only a certain number of students progressing from one to the next. David Cutting, a CMP PhD student with a large amount of cross-platform knowledge, was a winner of all three parts of the 2012 challenge which ran from October to December 2012. To win he had to dust off his vi and C skills as well as use new technologies such as DB2.

IET present around the world competition

CHristopher APplegateCongratulations to CMP's Christopher Applegate for winning this year's closely contested IET present around the world competition. Tom Le-Cornu came a very close second. Both winners were awarded £150 and £75 respectively.Thank you to all those that participated. The judges were very impressed with the quality of the presentations. The event is a good opportunity to promote the university and we hope that it continues to be hosted at UEA in the future.


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From measurements to patterns. New algorithms for the analysis of sRNA datasets.

Location: D'Arcy Thompson Room (School of Computing Sciences, UEA)
Research Group: Computational Biology Group
Date: 15 Mar 2013, 14:00-15:00
SpeakerDr. Irina Mohorianu
Organiser: Dr. Katharina Huber
InstitutionSchool of Computing Sciences, UEA
 
Abstract
Small RNAs (sRNAs) are 20-30nt non coding RNAs that act as guides for the sequence specific regulatory mechanism known as RNA silencing. Recent developments in high throughput sequencing revealed a highly complex and diverse population of sRNAs. However, only a small proportion of the reads could be assigned to known classes of sRNAs such as microRNAs, trans acting siRNAs, heterochromatin RNAs.
 
The analysis of the un-annotated sRNA like reads in S. Lycopersicum samples led to the development of quality check procedures and machine learning techniques adapted to the characteristics of sRNA data. To evaluate the quality of the samples, the complexity and sample similarity indexes were proposed. Also, to diminish technical biases, several normalization procedures were investigated. The outcome of the QC consisted of expression profiles assigned to each sRNA. The step towards patterns was conducted using unsupervised learning (clustering with a non-standard correlation based  distance), simplified correlation based on patterns and a novel loci detection approach based on genome location, expression profile and size class distribution.
 
The analysis revealed novel characteristics of sRNAs in a developmental system and helped a better understanding of the mode of action of known classes of sRNAs, such as miRNAs.