Reinforcement learning controllers for automatic generation control in power systems having re-heat units with GRC and dead-band

A new automatic generation controller (AGC) design approach, adopting reinforcement learning (RL) techniques, was recently pro- posed [1]. In this paper we demonstrate the design and performance of controllers based on this RL approach for automatic generation control of systems consisting of units having complex dynamics—the reheat type of thermal units. For such systems, we also assess the capabilities of RL approach in handling realistic system features such as network changes, parameter variations, generation rate constraint (GRC), and governor deadband.

Hybrid Working Set Algorithm for SVM Learning With a Kernel Coprocessor on FPGA

Support vector machines (SVM) are a popular class of supervised models in machine learning. The associated compute intensive learning algorithm limits their use in real-time applications. This paper presents a fully scalable architecture of a coprocessor, which can compute multiple rows of the kernel matrix in parallel. Further, we propose an extended variant of the popular decomposition technique, sequential minimal optimization, which we call hybrid working set (HWS) algorithm, to effectively utilize the benefits of cached kernel columns and the parallel computational power of the coprocessor. The coprocessor is implemented on Xilinx Virtex 7 field-programmable gate array-based VC707 board and achieves a speedup of upto 25x for kernel computation over single threaded computation on Intel Core i5. An application speedup of upto 15x over software implementation of LIBSVM and speedup of upto 23x over SVMLight is achieved using the HWS algorithm in unison with the coprocessor. The reduction in the number of iterations and sensitivity of the optimization time to variation in cache size using the HWS algorithm are also shown.

A Bacterial Foraging Optimization and Learning Automata Based Feature Selection for Motor Imagery EEG Classification

Selection of relevant features is an open problem in Brain-computer interfacing (BCI) research. Sometimes, features extracted from brain signals are high dimensional which in turn affects the accuracy of the classifier. Selection of the most relevant features improves the performance of the classifier and reduces the computational cost of the system. In this study, we have used a combination of Bacterial Foraging Optimization and Learning Automata to determine the best subset of features from a given motor imagery electroencephalography (EEG) based BCI dataset. Here, we have employed Discrete Wavelet Transform to obtain a high dimensional feature set and classified it by Distance Likelihood Ratio Test. Our proposed feature selector produced an accuracy of 80.291% in 216 seconds.

FIVDL: Fingerprint Image Verification using Dictionary Learning

Fingerprints are used for identification in forensics and are classified into Manual and Automatic. Automatic fingerprint identification system is classified into Latent and Exemplar. A novel Exemplar technique of Fingerprint Image Verification using Dictionary Learning (FIVDL) is proposed to improve the performance of low quality fingerprints, where Dictionary learning method reduces the time complexity by using block processing instead of pixel processing. The dynamic range of an image is adjusted by using Successive Mean Quantization Transform (SMQT) technique and the frequency domain noise is reduced using spectral frequency Histogram Equalization. Then, an adaptive nonlinear dynamic range adjustment technique is utilized to determine the local spectral features on corresponding fingerprint ridge frequency and orientation. The dictionary is constructed using spatial fundamental frequency that is determined from the spectral features. These dictionaries help in removing the spurious noise present in fingerprints and reduce the time complexity by using block processing instead of pixel processing. Further, dictionaries are used to reconstruct the image for matching. The proposed FIVDL is verified on FVC database sets and Experimental result shows an improvement over the state-of-the-art techniques. (C) 2015 The Authors. Published by Elsevier B.V.

Obtaining teaching expertise from F2F learning interactions

Learning environments are commonly used nowadays, but they exclude face-to-face interaction among teachers and students what is a successful basis of traditional education. On the other hand, in many cases teachers are imposed to use technology, what they do in an intuitive way. That is, teachers “learn by doing” and do not fully exploit its potential benefits. Consequently, some questions arise: How do teachers use F2F interaction to guide learning session? How can technology help teachers and students in their day by day? Moreover, are teachers and students really opened to be helped by technology? In this paper we present the formal process carried out to obtain information about teachers’ expertise and necessities regarding the direct interactions with students. We expose the possibilities to cover those necessities and the willingness that teachers show to be helped.

Hopwood Hall College: Touchscreen technology overtakes interactive whiteboards as interactive teaching tool of choice

Hopwood Hall is adopting the use of touch screen technology and gradually replacing its interactive whiteboards to improve access to interactive learning. The touch screen monitors connected to LCD TV’s provide a cheaper classroom build with technology that’s more user-friendly and better suited to classroom delivery. Until now, interactive boards had been the mainstay of classrooms but they created teaching barriers for staff including the additional software to learn and master. They are also expensive and often have usability issues with 'pens' not working or having a delay when used as the mouse tool.

Priestley College: How do you successfully develop your new learning space? ...ask your students, of course!

When Priestley College began to plan the redevelopment of its learning resource centre, it continued the culture of student involvement that exists within the College by asking students to help plan and create the new development. This case study describes how the Jisc infoKit on 'Planning and Designing Technology-Rich Learning Spaces' was used as the starting point for ideas and planning, and how the finished development was the recognisable result of students' ideas and plans.

People and Business Development (PBD): Learning to deliver learning effectively

In October 2010, PBD introduced its eQual Learning VLE (virtual learning environment) to provide an online knowledge resource for its students. During the project, the company learnt many lessons about how to deliver learning effectively. In the course of a year researching VLE platforms, looking for material, and remapping NVQ courses for new QCF qualifications, the company realised that it was more important to deliver engaging and relevant content, rather than boasting the most innovative technology.

How do you change the learning landscape?

Analysis of the Changing the Learning Landscape strategic conversations with senior managers, staff and students in 58 institutions was undertaken in order to identify trends and direction of change in relation to technology-enhanced learning (TEL) and the student experience.

12 steps towards embedding inclusive use of technology

This briefing for senior managers is based upon research conducted by Jisc via interviews with a range of pro-vice chancellors for Learning and Teaching (or equivalent). The briefing describes 12 steps that senior managers can take to lead and embed a culture of inclusive practice right across the institution, building on any pockets of excellence that already exist. TDL

An Open and Social Spaced Repetition System for Language Learning

In the last decades big improvements have been done in the field of computer aided learning, based on improvements done in computer science and computer systems. Although the field has been always a bit lagged, without using the latest solutions, it has constantly gone forward taking profit of the innovations as they show up. As long as the train of the computer science does not stop (and it won’t at least in the near future) the systems that take profit of those improvements will not either, because we humans will always need to study; Sometimes for pleasure and some other many times out of need. Not all the attempts in the field of computer aided learning have been in the same direction. Most of them address one or some few of the problems that show while studying and don’t take into account solutions proposed for some other problems. The reasons for this can be varied. Sometimes the solutions simply are not compatible. Some other times, because the project is an investigation it’s interesting to isolate the problem. And, in commercial products, licenses and patents often prevent the new projects to use previous work. The world moved forward and this is an attempt to use some of the options offered by technology, mixing some old ideas with new ones.

Emerging Practice in a Digital Age: A guide to technology-enhanced institutional innovation

Since the launch of the JISC guide Innovative Practice with e-Learning (JISC, 2005), so much has changed. At that time, early adopters were exploring the potential of mobile and wireless learning. Since then, the increased availability of public and institutional wireless networks, the emergence of new and more powerful technologies and an increase in personal ownership of these technologies are changing the way we connect, communicate and collaborate. Emerging Practice in a Digital Age, one of a series of Effective Practice guides, draws on recent JISC reports and case studies and looks at how colleges and universities are continuing to embrace innovation and respond to changes in economic, social and technological circumstances in a fastchanging world.

Learning in a Digital Age: Extending higher education opportunities for lifelong learning

Learning in a Digital Age is one in a series of Effective Practice guides. It demonstrates, through a range of case studies, how institutions are using technology to attract and retain diverse groups of learners, offer professional development opportunities for their staff, and enhance engagement and collaboration with employers and other organisations with a stake in effective lifelong learning.