The detection of estrus continues to be a primary factor contributing to poor reproductive performance in modern dairy cattle. The objectives of this research were 1) to evaluate performance of automated detection of estrus using a reference standard of ovulation detection with temporal progesterone patterns 2) to evaluate the efficacy of parameters measured by automated detection of estrus systems 3) to evaluate the efficacy of alerts generated by several commercially available systems used for automated detection of estrus and 4) to determine the differences in these parameters among cows with or without poor health conditions at the time of estrus. Systems used for automated detection of estrus can perform better than the previous original reference standard, visual observation for standing behaviors. All systems used for automated detection of estrus tested were similar for estrus detection efficiency.

The recommended procedures for implementing COTMAN; a cotton management expert system; suggest frequent crop scouting at numerous locations for each field. Machine based height sensors coupled with the ability to spatially record height values make it possible to locate regions of a field that are height representative of the entire field. A machine based height measurement system called HMAP was used to assess plant height in various fields in the 2003 growing season while the same fields were monitored with COTMAN. The plant height data was used to determine an optimal COTMAN sampling scheme for each field consisting of significantly fewer sampling locations than recommended by COTMAN. It was possible to ascertain equivalent information from COTMAN using two sites selected from height data in place of six sites selected per COTMAN recommendations. The HMAP system was extended to monitor rate of growth in real time in addition to plant height by comparing historical plant height data recorded on previous field passes to current height values. The rate of growth capable HMAP system will make it possible to track cotton growth and development with an automated system.

Precision agriculture (PA) can be defined as a set of technologies that have helped propel agriculture into the computerized information-based world, and is designed to help farmers get greater control over the management of farm operations. Because of its potential to spatially reduce yield variability within the field through variable rate application of nutrients it is thought to be a production risk management instrument. Subsurface drip irrigation (SDI) is another production risk management technology that is generating interest from the farming community as a result of new technological improvements that facilitate equipment maintenance and reduces water consumption.In the first article the production risk management potential of these two technologies was investigated both for each technology and for a combination of the two. Simulated yield data for corn, wheat and soybeans were obtained using EPIC, a crop growth simulation model. Mathematical programming techniques were used in a standard E-V framework to reproduce the production environment of a Kentucky commercial grain farmer in Henderson County. Results show that for risk averse farmers, the lowest yield variability was obtained with the SDI technology. The highest profit level was obtained when the two technologies were combined.Investment in two sets of equipments (PA and SDI) to maximize profitability and reduce risk could however expose many farm operations to financial risk. In the second article, a discrete stochastic sequential programming (DSSP) model was used to analyze the impact of PA and/or SDI equipment investment on the farm's liquidity and debt to asset ratio.In the last article, the cotton sector in Benin, West Africa, was utilized to study the transferability of PA technology to a developing country. Properly introduced, precision agriculture (PA) technology could help farmers increase profitability, improve management practices, and reduce soil depletion. An improved production system could also help farmers better cope with the policy risk related to cotton production. Results from the two models show that PA is less profitable for the risk neutral farmer but more profitable for the risk averse one when compared to conventional production practices. The adoption of the new technology also has very little impact on the choice of crop rotation made by the farmer.

The harsh conditions of space, the stringent requirements for orbiting devices, and the increasing precision pointing requirements of many space applications demand an actuator that can provide necessary force while using less space and power than its predecessors. Ideally, this actuator would be able to isolate vibrations and never fail due to mechanical wear, while pointing with unprecedented accuracy. This actuator has many space applications from satellite optical communications and satellite appendage positioning to orbiting telescopes. This thesis presents the method of design of such an actuator a self-bearing motor. The actuator uses Lorentz forces to generate both torque and bearing forces. It has a slotless winding configuration with four sets of three-phase currents. A stand-alone software application, LFMD, was written to automatically optimize and configure such a motor according to a designers application requirements. The optimization is done on the bases of minimum powerloss, minimum motor outer diameter, minimum motor mass, and minimum length. Using that program, two sample space applications are analyzed and applicable motor configurations are presented.

This thesis examines the use of precision agriculture data, specifically yield maps, for makingsite-specific economic decisions for improved farm management. The adoption of precisionagriculture on farms has allowed producers to collect a greater quantity and more specificinformation about production than ever before. With such information, site-specific decisions canbe made. Incorporating economic data with yield map data, two primary decision examples aredeveloped: defining areas of production and nonproduction and managing temporal risk spatiallyacross a field. Included with the production/ nonproduction decision are the effects that landtenure arrangements and risk aversion levels have on the decision. The risk maps are developedusing break-even analysis, the coefficient of variation, and a mean-variance framework, all based ona twenty year average of temporal net returns, measured spatially. The risk maps are repeatedincorporating a crop insurance option, a commonly used risk management tool. Results show thatdeveloping these maps can be used by agricultural producers to help with their decision making. Byincorporating these maps into the decision-making process, decisions can be made to increase farmprofitability.

This thesis examines the use of two specific types of precision agriculture technologies: cost maps and lightbar. Cost maps visually depict spatial differences in production costs. The visual depictions of these costs are represented using ArcGIS in an attempt to aide farmers in further decision making. Results will show that cost maps have great possibilities in their addition to the set of tools that farmers use in decision making. This thesis will expand the understanding of lightbar from a partial budget study to a whole farm model incorporating competition across different enterprises for labor and capital. The results from the study of cost maps indicate that inaccuracy of machinery movement, whether in the application stage or the harvesting stage is very costly. As a result, the suggestion of lightbar as a guidance aide to improve farm profitability is recommended under the conditions analyzed and shows a net farm return increase in just over 6%.

The primary objective of this creative project was to fully explore and analyze the centuries old technique of lost wax casting.The secondary objective was to produce a body of work combining my creative inspirations from nature and my African culture.This body of work employed a variety of traditional metalsmithing techniques combining raised/constructed hollow ware, in a variety of metals, with cast metal forms. / Department of Art

This PhD thesis describes the design and development of a new resonator based tactile sensitive probe. This new sensor was proposed because of the increasing need for high-sensitivity, high-speed touch-sensitive probes in coordinate metrology due to the ever-growing demand for precision and reliability at sub-micron level accuracy. Extensive background research on the current development of touch trigger probes has shown that designs based on the resonator principle have potential for minimising lobing effects and the false triggering associated with most commercially available probes. Resonant based sensors have been investigated over many decades and used very successfully in a wide range of applications. However their commercial exploitation in the field of precision engineering has not been particularly successful. One reason for such slow progress is the complexity of the interaction between oscillatory probes and typical engineering surfaces in less than ideal environments. The main aim of this research was to design a high precision resonator based tactile sensitive probe and to investigate the causes of parametric changes on resonant touch sensors both before and during contact with a variety of engineering surfaces in order to achieve a better understanding of contact mechanisms. The four main objectives were: preliminary design and characterisation of a resonator based touch sensor; development of the mathematical model which predicts parametric changes on a resonant probe considering both near surface effects and mechanical contact; experimental verification of mathematical predictions; and an investigation into possible commercial exploitation of the new probe in precision applications. A novel resonator based tactile sensor that utilises the piezoelectric effect was designed and characterised. The design exploits the fact that when a stiff element (probe) oscillating near or at its resonance frequency comes into contact with the surface of another body (workpiece), the frequency of vibrational resonance of the probe changes depending on the properties of the workpiece. The phase-locked loop frequency detection technique was employed to track changes in frequency as well as in the phase of the resonant system. The initial characterisation of the touch sensor has shown a sensitivity to contact of less then 4 mN, a high triggering rate and good repeatability. The potential for application in measuring material properties was also demonstrated. As a result of the characterisation a comprehensive mathematical model was developed. This novel model was based on Hertzian contact mechanics, Rayleigh's approximate energy method and work carried out by Smith and Chetwynd on the analysis of elastic contact of a sphere on a flat. The model predicts that phase and frequency shift of a resonator based sensor can either increase or decrease depending on the dominant phenomena (added mass, stiffness and damping) in the contact region. Observation of dynamic characteristics at either side of the resonant frequency can be used to identify the predominant effect. In order to confirm the model experimentally, another prototype probe was developed. The new sensor was engaged in observations of contact mechanisms with engineering surfaces. The experimental results have showed favourable agreement with the developed mathematical model. This enabled a better understanding of contact phenomena uncovering possibilities for the application of resonant sensors in many other areas. The research has shown that the new probe has potential in contact measurements where it can be used for the quantitative assessment of the physical properties of different materials (modulus of elasticity, density and energy dissipation) and also in non-destructive hardness testing. It was shown that the device can be successfully used in coordinate metrology as a touch trigger probe and as a 3D vector probe. Finally, applications can also be found in surface topography as a surface characterisation instrument. It is intended that the research described in this thesis will make an important contribution in the area of resonator based probes, providing a better understanding of the causes of parametric changes on the oscillatory sensor during contact with the object being measured. Consequently, this will enable a more effective exploitation of resonant probes for a broad range of precision applications.

This work presents a static instruction allocation scheme for the precision timed architecture’s (PRET) scratchpad memory. Since PRET provides timing instructions to control the temporal execution of programs, the objective of the allocation scheme is to ensure that the explicitly specified temporal requirements are met. Furthermore, this allocation incorporates instructions from multiple hardware threads of the PRET architecture. We formulate the allocation as an integer-linear programming problem, and we implement a tool that takes binaries, constructs a control-flow graph, performs the allocation, rewrites the binary with the new allocation, and generates an output binary for the PRET architecture. We carry out experiments on a modified version of the Malardalen benchmarks to illustrate that commonly known ACET and WCET based approaches cannot be directly applied to meet explicit timing requirements. We also show the advantage of performing the allocation across multiple threads. We present a real time benchmark controlling an Unmanned Air Vehicle as the case study.

At no point in history have we demanded so much from our agricultural land whilst simultaneously leaving so little room for management error. Of the many possible environmental impacts from agriculture, soil and water salinisation has some of the most long-lived and deleterious effects. Despite its importance, however, land managers are often unable to make informed decisions of how to manage the risk of salinisation due to a lack of data. Furthermore, there remains no universally agreed method for salinity risk mapping. This thesis addresses these issues by investigating new methods for producing high-resolution predictions of soil salinity, soil physical properties and groundwater depth using a variety of traditional and emerging ancillary data sources. The results show that the methodologies produce accurate predictions yielding natural resource information at a scale and resolution not previously possible. Further to this, a new methodology using fuzzy logic is developed that exploits this information to produce high-resolution salinity risk maps designed to aid both agricultural and natural resource management decisions. The methodology developed represents a new and effective way of presenting salinity risk and has numerous advantages over conventional risk models. The incorporation of fuzzy logic provides a meaningful continuum of salinity risk and allows for the incorporation of uncertainty. The method also allows salinity risk to be calculated relative to any vegetation community and shows where the risk is coming from (root-zone or groundwater) allowing more appropriate management decisions to be made. The development of this methodology takes us a step closer to closing what some have called our greatest gap in agricultural knowledge. That is, our ability to manage the salinity risk at the subcatchment scale.