ENERGY EFFICIENCY IN FOOD PROCESSING IN THE SOUTHERN REGION

Agribusiness,

Communication System For Firefighters

Currently firefighters use two-way radios to communicate on the job, and they are forced to write reports based on their memory because there is not an easy way to record the communications between two-way radios. Firefighters need a system to automatically document what happened while they were responding to a call. To save them a significant amount of time when creating reports, our solution is to implement an application that allows firefighters to take pictures, record video and communicate in real time with their team of on-site responders. The proposed system will use a Wireless Local Area Network (WLAN) hosted on the fire truck itself to act as an access point (AP) to which the firefighters can connect. This AP will also save communication between firefighters to a local storage location. Upon return to the fire station, the AP will route all of the information stored locally to a larger database. For now, Wi-Fi will be our communication medium, with a prediction that our technology can eventually be extended to include radio signal

A cross-sectional pilot study of the Scottish early development instrument : a tool for addressing inequality

Early childhood is recognised as a key developmental phase with implications for social, academic, health and wellbeing outcomes in later childhood and indeed throughout the adult lifespan. Community level data on inequalities in early child development are therefore required to establish the impact of government early years' policies and programmes on children's strengths and vulnerabilities at local and national level. This would allow local leaders to target tailored interventions according to community needs to improve children's readiness for the transition to school. The challenge is collecting valid data on sufficient samples of children entering school to derive robust inferences about each local birth cohort's developmental status. This information needs to be presented in a way that allows community stakeholders to understand the results, expediting the improvement of preschool programming to improve future cohorts' development in the early years. The aim of the study was to carry out a pilot to test the feasibility and ease of use in Scotland of the 104-item teacher-administered Early Development Instrument, an internationally validated measure of children's global development at school entry developed in Canada. Phase 1 was piloted in an education district with 14 Primary 1 teachers assessing a cohort of 154 children, following which the instrument was adapted for the Scottish context (Scottish Early Development Instrument: SEDI). Phase 2 was then carried out using the SEDI. Data were analysed from a larger sample of 1090 participants, comprising all Primary 1 children within this school district, evaluated by 68 teachers. The SEDI displayed adequate psychometric and discriminatory properties and is appropriate for use across Scotland without any further modifications. Children in the lowest socioeconomic status quintiles were 2-3 times more likely than children in the most affluent quintile to score low in at least one developmental domain. Even in the most affluent quintile though, 17% of children were 'developmentally vulnerable', suggesting that those in need cannot be identified by socioeconomic status alone. The SEDI offers a feasible means of providing communities with a holistic overview of school readiness for targeting early years' interventions

Application of reinforcement learning methods to computer game dynamics

The dynamics of the game world present both challenges and opportunities for AI to make a useful difference. Learning smart behaviours for game assets is a first step towards realistic conflict or cooperation. The scope this thesis is the application of Reinforcement Learning to moving assets in the game world. Game sessions a generate stream data on asset's performance which must be processed on the fly. The lead objective is to produce fast, lightweight and flexible learning algorithms for run-time embedding. The motivation from current work is to shorten the time to achieve a workable policy solution by investigating the exploration / exploitation balance, overcome the curse of dimensionality of complex systems, and avoid the use of extra endogenous parameters which require multiple data passes and use a simple state aggregation rather than functional approximation. How action selection (AS) contributes to efficient learning is a key issue in RL since is determines the balance between exploiting and confirming the current policy or exploring an early less likely policy which may prove better in the long run. The methodology deploys the simulation of several AS using 10-armed bandit problem averaged over 10000 epochs. The results show a considerable variation in performance in terms of latency and asymptotic direction. The Upper Confidence Bound comes out leader over most of the episode range, especially at about 100. Using insight from action selection order statistics are applied to determine a criterion for the convergence of policy evaluation. The probability that the action of maximum sample mean is indeed the action of maximum population mean (PMSMMPM) is calculated using the 3 armed bandit problem. PMSMMPM reaches 0.988 by play 26 which provides evidence for it as a convergence criterion. An iteration stopping rule is defined using PMSMMPM and it shows plausible properties as the population parameters are varied. A mathematical analysis of the approximation (P21) of just taking the top two actions yields a minimum sampling size for any level of P21. Using the gradient of P21 a selection rule is derived and when combined with UCB a new complete exploratory policy is demonstrated for 3-arm bandit that requires just over half the sample size when compared with pure UCB. The results provide evidence that the augmented UCB selection rule will contribute to faster learning. TD sarsa(0) learning algorithm has been applied to learn a steering policy for the untried caravan reversing problem and for the kerb avoiding steering problem of racing car both using negative rewards on failure and a simple aggregation. The output policy for the caravan is validated as non jack-knifing for a high proportion of start states. The racing car policy has a similar validation outcome for two exploratory polies which are compared and contrasted

Demonstration of adaptive overcurrent protection using IEC 61850 communications

This paper contains a description of an adaptive protection scheme that has been implemented and demonstrated in a hardware in the loop simulation environment using commercially available protection hardware and IEC 61850 communications.The implementation is based on an actual 11kV system which includes distributed generation and network automation. IEC 61850 communications offers several benefits for the implementation of adaptive protection, but also presents some limitations which are discussed in the paper. An alternative approach to overcome a number of the limitations is also presented