Peer Mentoring and Professionalism

Peer mentoring has been a success for everyone involved resulting in a ‘win-win-win’ situation for mentors, mentees and university schools and departments (Andrews and Clark, 2011). Mentors have the opportunity to develop key transferable skills such as communication and leadership, which in turn can enhance their employability opportunities. There is also potential to increase and develop social and academic confidence. For mentees the benefits include the opportunity to gain advice, encouragement and support during the transition period from school/college/work to university along with the opportunity to gain an insight into the stages of university life by learning the "rules of the game". Through peer mentor schemes University schools and departments are meeting the demand to support student success while assisting student transition and reducing attrition. This paper will focus on the peer mentor scheme set up in the School of Electronics, Electrical Engineering and Computer Science at Queen’s University Belfast specifically the development of employability skills through company involvement in the scheme.

How Good Am I? Crude Self-Assessment vs. Examination

With the new academic year structure encouraging more in-term assessment to replace end-of-year examinations one of the problems we face is assessing students and keeping track of individual student learning without overloading the students and staff with excessive assessment burdens.
In the School of Electronics, Electrical Engineering and Computer Science, we have constructed a system that allows students to self-assess their capability on a simple Yes/No/Don’t Know scale against fine grained learning outcomes for a module. As the term progresses students update their record as appropriately, including selecting a Learnt option to reflect improvements they have gained as part of their studies.
In the system each of the learning outcomes are linked to the relevant teaching session (lectures and labs) and to online resources that students can access at any time. Students can structure their own learning experience to their needs and preferences in order to attain the learning outcomes.
The system keeps a history of the student’s record, allowing the lecturer to observe how the students’ abilities progress over the term and to compare it to assessment results. The system also keeps of any of the resource links that student has clicked on and the related learning outcome.
The initial work is comparing the accuracy of the student self-assessments with their performance in the related questions in the traditional end-of-year examination.

Multiuser dual-hop relaying over hybrid RF/FSO links

The performance of multiuser dual-hop relaying over mixed radio frequency/free-space optical (RF/FSO) links is investigated. RF links are used for the simultaneous data transmission from m single-antenna sources to the relay, which is equipped with n ≥ m receive antennas and a photo-aperture transmitter. The relay operates under the decode-and-forward protocol and utilizes the popular ordered V-BLAST technique to successively decode each user's transmitted stream. A common norm-based ordering approach is adopted, where the streams are decoded in an ascending order. After the V-BLAST decoding, the relay retransmits the initial information to the destination, which is equipped with a photo-detector, via a point-to-point FSO link in m consecutive timeslots. Analytical expressions for the end-to-end outage probability and average symbol error probability of each user are derived. Some engineering insights are manifested, such as the diversity order, the impact of the pointing error displacement on the FSO link and the severity on the turbulence-induced channel fading.

Management of public water supply to reduce energy cost and improve wind power uptake

This paper presents a study on the implementation of Real-Time Pricing (RTP) based Demand Side Management (DSM) of water pumping at a clean water pumping station in Northern Ireland, with the intention of minimising electricity costs and maximising the usage of electricity from wind generation. A Genetic Algorithm (GA) was used to create pumping schedules based on system constraints and electricity tariff scenarios. Implementation of this method would allow the water network operator to make significant savings on electricity costs while also helping to mitigate the variability of wind generation.

Management of public water supply to reduce energy cost and improve wind power uptake

This paper presents a study on the implementation of Real-Time Pricing (RTP) based Demand Side Management (DSM) of water pumping at a clean water pumping station in Northern Ireland, with the intention of minimising electricity costs and maximising the usage of electricity from wind generation. A Genetic Algorithm (GA) was used to create pumping schedules based on system constraints and electricity tariff scenarios. Implementation of this method would allow the water network operator to make significant savings on electricity costs while also helping to mitigate the variability of wind generation.

Detecting stealthy attacks: Efficient monitoring of suspicious activities on computer networks

Stealthy attackers move patiently through computer networks - taking days, weeks or months to accomplish their objectives in order to avoid detection. As networks scale up in size and speed, monitoring for such attack attempts is increasingly a challenge. This paper presents an efficient monitoring technique for stealthy attacks. It investigates the feasibility of proposed method under number of different test cases and examines how design of the network affects the detection. A methodological way for tracing anonymous stealthy activities to their approximate sources is also presented. The Bayesian fusion along with traffic sampling is employed as a data reduction method. The proposed method has the ability to monitor stealthy activities using 10-20% size sampling rates without degrading the quality of detection.

Management of public water supply to reduce power cost and improve wind power uptake

This paper presents a study on the implementation of Real-Time Pricing (RTP) based Demand Side Management (DSM) of water pumping at a clean water pumping station in Northern Ireland, with the intention of minimising electricity costs and maximising the usage of electricity from wind generation. A Genetic Algorithm (GA) was used to create pumping schedules based on system constraints and electricity tariff scenarios. Implementation of this method would allow the water network operator to make significant savings on electricity costs while also helping to mitigate the variability of wind generation.

Proposing the deep dynamic Bayesian network as a future computer based medical system

The development of new learning models has been of great importance throughout recent years, with a focus on creating advances in the area of deep learning. Deep learning was first noted in 2006, and has since become a major area of research in a number of disciplines. This paper will delve into the area of deep learning to present its current limitations and provide a new idea for a fully integrated deep and dynamic probabilistic system. The new model will be applicable to a vast number of areas initially focusing on applications into medical image analysis with an overall goal of utilising this approach for prediction purposes in computer based medical systems.