Structural and Electrical Investigation of C 60 –Graphene Vertical Heterostructures

Graphene, with its unique electronic and structural qualities, has become an important playground for studying adsorption and assembly of various materials including organic molecules. Moreover, organic/graphene vertical structures assembled by van der Waals interaction have potential for multifunctional device applications. Here, we investigate structural and electrical properties of vertical heterostructures composed of C60 thin film on graphene. The assembled film structure of C60 on graphene is investigated using transmission electron microscopy, which reveals a uniform morphology of C60 film on graphene with a grain size as large as 500 nm. The strong epitaxial relations between C60 crystal and graphene lattice directions are found, and van der Waals ab initio calculations support the observed phenomena. Moreover, using C60-graphene heterostructures, we fabricate vertical graphene transistors incorporating n-type organic semiconducting materials with an on/off ratio above 3 × 10(3). Our work demonstrates that graphene can serve as an excellent substrate for assembly of molecules, and attained organic/graphene heterostructures have great potential for electronics applications.

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.

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.

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.

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.