Self-Learning Prediciton System for Optimisation of Workload Managememt in a Mainframe Operating System

We present a framework for extraction and prediction of online workload data from a workload manager of a mainframe operating system. To boost overall system performance, the prediction will be corporated into the workload manager to take preventive action before a bottleneck develops. Model and feature selection automatically create a prediction model based on given training data, thereby keeping the system flexible. We tailor data extraction, preprocessing and training to this specific task, keeping in mind the nonstationarity of business processes. Using error measures suited to our task, we show that our approach is promising. To conclude, we discuss our first results and give an outlook on future work

Smart home technology for aging

The majority of the growing population, in the US and the rest of the world requires some degree of formal and or informal care either due to the loss of function or failing health as a result of aging and most of them suffer from chronic disorders. The cost and burden of caring for elders is steadily increasing. This thesis focuses on providing the analysis of the technologies with which a Smart Home is built to improve the quality of life of the elderly. A great deal of emphasis is given to the sensor technologies that are the back bone of these Smart Homes. In addition to the Analysis of these technologies a survey of commercial sensor products and products in research that are concerned with monitoring the health of the occupants of the Smart Home is presented. A brief analysis on the communication technologies which form the communication infrastructure for the Smart Home is also illustrated. Finally, System Architecture for the Smart Home is proposed describing the functionality and users of the system. The feasibility of the system is also discussed. A scenario measuring the blood glucose level of the occupant in a Smart Home is presented as to support the system architecture presented

Intelligent autoreclosing for systems of high penetration of wind generation with real time modelling, development and deployment

COPYRIGHT Attention is drawn to the fact that copyright of this thesis rests with its author. A copy of this thesis has been supplied on condition that anyone who consults it is understood to recognise that its copyright rests with the author and they must not copy it or use material from it except as permitted by law or with the consent of the author. This thesis may be made available for consultation within the University Library and may be photocopied or lent to other libraries for the purposes of consultation. ii This thesis presents investigations into the effect of modern wind farms on grid side short circuits using extensive real time digital simulation. Particular reference is made to adaptive autoreclosing algorithms using artificial neural networks. A section of 132kV transmission grid in Scotland, including DFIG wind farms, is modelled on a real time digital simulator. An algorithm is then developed and tested using this model to show that this autoreclosing technique is feasible in systems with high penetration of wind generation. Although based on an existing technique, an important innovation is the use of two neural networks for the separate tasks of arc presence and extinction. The thesis also describes a low-cost, real time, relay development platform. Executive summary of key achievements- The effect of wind turbines on transmission line short circuit transients, with a comparison of the other significant parameters- Treatment of unbalanced faults and realistic arc modelling in this context- Feasibility studies on RTDS development of AdTAR using primary arcing and inter-circuit coupling- Development of robust AdSPAR autoreclosing algorithm using twin neural networks- A critical discussion of the use of AI in power system protection- A low cost, IEC 61850 compliant, real time relay development platfor

Constructivist neural network models of cognitive development

In this thesis I investigate the modelling of cognitive development with constructivist neural networks. I argue that the constructivist nature of development, that is, the building of a cognitive system through active interactions with its environment, is an essential property of human development and should be considered in models of cognitive development. I evaluate this claim on the basis of evidence from cortical development, cognitive development, and learning theory. In an empirical evaluation of this claim, I then present a constructivist neural network model of the acquisition of the English past tense and of impaired inflectional processing in German agrammatic aphasics. The model displays a realistic course of acquisition, closely modelling the U-shaped learning curve and more detailed effects such as frequency and family effects. Further, the model develops double dissociations between regular and irregular verbs. I argue that the ability of the model to account for the hu..

Advances in Computer Recognition, Image Processing and Communications, Selected Papers from CORES 2021 and IP&C 2021

As almost all human activities have been moved online due to the pandemic, novel robust and efficient approaches and further research have been in higher demand in the field of computer science and telecommunication. Therefore, this (reprint) book contains 13 high-quality papers presenting advancements in theoretical and practical aspects of computer recognition, pattern recognition, image processing and machine learning (shallow and deep), including, in particular, novel implementations of these techniques in the areas of modern telecommunications and cybersecurity

ReSCon '12, Research Student Conference: Book of Abstracts

The fifth SED Research Student Conference (ReSCon2012) was hosted over three days, 18-20 June 2012, in the Hamilton Centre at Brunel University. The conference consisted of 130 oral and 70 poster presentations, based on the high quality and diverse research being conducted within the School of Engineering and Design by postgraduate research students. The conference is held annually, and ReSCon plays a key role in contributing to research and innovations within the School

Utility Applications of Smart Online Energy Systems: A case for Investing in Online Power Electronics

The backbone of any power grid, the transmission and sub-transmission networks, should be flexible, robust, resilient and self-healing to cope with wide types of network adverse conditions and operations. Power electronic applications are making a major impact on the present and future state of power systems generation, transmission and distribution. These applications include FACTS (Flexible Alternating Current Transmission), HVDC (High Voltage Direct Current) in transmission and Custom Power devices in distribution. FACTS devices are some of the advanced assets that network planners can use to make the transmission grid become more flexible and robust. Many established research ideas to advance operations of these devices have been published in the open literature over the last ten years. The most recent publications in this field are reviewed in this thesis. A critical analysis of literature and existing conditions reveals a range of potentials that are ideal for development in Qatar’s increasingly strained electricity network. As a result of demand surge in Qatar in recent years and the forecast to grow in the same rate, the need for improvement in Qatar Power Transmission System (QPTS) is great and significant. Conventional planning and operational solutions such as conductor up-rating, and fixed series capacitors (FSC) are considered. However there are growing challenges on getting new rights of ways for new overhead lines and even corridors for new cables. Advanced FACTS devices are considered for dynamic control of power flows and voltages, such as TCSC (Thyristor Controlled Series Capacitor) and GUPFC (Generalized, Unified Power Flow Controller). The research in this thesis examines the potential for QPTS to improve and develop, with emphasis on increased output through integrated online energy systems, online FACTS and HVDC controllers based on synchrophasor measurements. The devices are modelled in Siemens PTI’s PSS®E software, through steady-state mode case study to investigate power flow control and voltage support. Comparison between similar FACTS technologies, such as SVC and STATCOM, is also presented. The improvement in power flow imbalance between transmission lines with different ratings and lengths is studied. The FACTS devices are tested for voltage support to enhance the network voltage profile and hence increase security and reliability to important industrial customers. Optimization techniques of the FACTS devices allocation and rating are generally discussed considering the voltage improvement and optimal power flow control. The results achieved showing the network improvement with using the FACTS are presented in the case studies. In a separate case study, applying medium voltage custom power devices to convert DC battery storage and photovoltaic energy into AC energy using a power conversion system is discussed. The dynamic mode of the STATCOM is modelled in QPTS in the succeeding case study using the same software and compared with the capacitor banks. This is followed by another case of HVDC analysis modelled with and without STATCOM present. The thesis discussed the real time operation and control of power system physical parameters in QPTS using capacitors, FACTS and HVDC. The key contribution of this thesis is the application and resting of all sorts of FACTS and HVDC in QPTS. The system wide area, coordinated control of FACTS (Online Power Electronics-OPE) is a new concept. Another major contribution is being able to look at a system wide approach for a transmission smart grid application. The results of thesis are presented in international conferences in USA, Hong Kong, France, Portugal, and locally in the Arabian Gulf (Dubai, Oman and Qatar). The thesis’s papers are listed in the ‘References’ section and in Appendix-F