The use of virtual crowds in visual eects has grown tremendously since the warring armies of virtual orcs and elves were seen in The Lord of the Rings. These crowds are generated by agent-based simulations, where each agent has the ability to reason and act for itself. This autonomy is eective at automatically producing realistic, complex group behaviour but leads to problems in controlling the crowds. Due to interaction between crowd members, the link between the behaviour of the individual and that of the whole crowd is not obvious. The control of a crowd's behaviour is, therefore, time consuming and frustrating, as manually editing the behaviour of individuals is often the only control approach available. This problem of control has not been widely addressed in crowd simulation research. We propose, implement and test a system in which a user may control the behaviour of a crowd by means of general constraints. This Constraint Satisfaction system automatically alters the behaviour of the individuals in the crowd such that the group behaviour meets the provided constraints. We test this system on a number of scenarios involving dierent types of agents and compare the effectiveness of this automatic system to an expert user manually changing the crowd. We find our method of control, in most cases, to be at least as effective as the expert user.

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This item was digitized as part of the Million Books Project led by Carnegie Mellon University and supported by grants from the National Science Foundation (NSF). Cornell University coordinated the participation of land-grant and agricultural libraries in providing historical agricultural information for the digitization project; the University of Arizona Libraries, the College of Agriculture and Life Sciences, and the Office of Arid Lands Studies collaborated in the selection and provision of material for the digitization project. / 1. Cotton Electronic Accounting (News Release) 2. 4th Annual Arizona Cotton Tour 3. 1964 Cotton Center Field Day, A Big Success 4. Wellton-Mohawk Herbicide School - Yuma County 5. County Cotton Meetings Prove Valuable 6. Two Counties Participate in Seed Program 7. County Cotton Tour Acquaints Growers with New Varieties 8. It Was a Great Little Idea 9. Increased Accuracy and Capacity Coming in the Cultivation Operation

With over 1.3 million applications on the Android marketplace, there is increasing competition between mobile applications for customer sales. As usability is a significant factor in an application’s success, many mobile developers refer to the Android design guidelines when designing the user interface (UI). These principles help to provide consistency of navigation and aesthetics, with the rest of the Android platform. However, misinterpretation of the abstract guidelines may mean that patterns and elements selected to organise content of an application do not improve the usability. Therefore, usability tests would be beneficial to ensure that an application meets objectives efficiently and improve on user experience. Usability testing is an important and crucial step in the mobile development process Many freelance developers, however, have limited resources for usability testing, even though the advantages of usability feedback during initial development stages are clear and can save time and money in the long-run. In this thesis, we investigate which method of usability testing is most useful for resource constrained mobile developers. To test the efficacy of Android guidelines, three alternate designs of a unique Android tablet application, Glycano, are developed. High-fidelity paper prototypes were presented to end-users for usability testing and to usability experts for heuristic evaluations. Both usability and heuristic tests demonstrated that following the Android guidelines aids in user familiarity and learnability. Regardless of the different UI designs of the three mockups, Android guidelines provided an initial level of usability by providing familiarity to proficient users and an intuitiveness of certain patterns to new users. However, efficiency in building Glycano schematics was an issue that arose consistently. Testing with end-users and experts, revealed several navigational problems. Usability experts uncovered more general UI problems than the end-user group, who focused more on the content of the application. More refinements and suggestions of additional features to enhance usability and user experience were provided by the experts. Use of usability experts would therefore be most advantageous in initial design stages of an application. Feedback from usability testing is, however, also beneficial and is more valuable than not performing any test at all.

The Video Game industry is maturing. Success in the video game industry relies on many things, including marketing, sound business practises, and top notch technical implementation. Games Engines are software systems that facilitate game production. The growth of the game industry has increased the demand for programmers trained in game development technologies. A simplified game engine, designed specifically for the game development courses which service the supply of graduates for the industry, could have many advantages. This dissertation analysed the requirements of such a system. We found that such a game engine would need to be extensible, reusable, modular, be easy to learn, and be open source. It would also need to at least include graphics, audio, networking and pathfinding components. Our analysis found that no game engine currently exists that fulfills all these requirements. We designed and implemented a game engine to fulll all these requirements. Our game engine is built around a module framework, where each task of the game engine is handled by a module. This modular design allows us to easily change functionality by adding, removing or updating modules. All source code of the engine is available, thus any part of the engine can be changed if needed. Open source also means the engine is free for all to use. Game engines also need to be reusable so that in the industry the development costs of creating an engine can be amortised multiple projects, but also in a university context it means that time students can continue to use the system across multiple projects. The system was tested by having students complete game development tasks using our game engine, ModEngine, and another comparable game engine. We used lines of code as a measure of code complexity and completion time as a measure of performance. We found that there is a statistically significant reduction in both the lines of code and the completion time of student's ModEngine assignments versus the comparison. Our p value (the probability that the data was due to chance alone) for lines of code is 9.662776 X 10^(-5) and for completion time is 0.018. Students were also given questionnaires to complete where they were asked about their experience using both engines. ModEngine was found to be easier to learn and was simpler to use; students can more easily explore game development concepts with ModEngine and can get started working with it much more easily.

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Time-delay feed-forward Artificial Neural Networks are examined for gasoline engine cylinder pressure reconstruction using both measured crank kinematics obtained from a shaft encoder, and measured engine cylinder block vibrations obtained from a production knock sensor. Initially, the study focuses on the information content associated with measured data, which is considered to be of equal importance to the particular network architecture and the training methodology. Several hypotheses are constructed, which when tested, reveal the influence of the data information content on the reconstruction potential and limitations. These hypotheses are tested on real data from a 3-cylinder (DISI) engine. Three distinct ideas emerge through this testing process, which are combined to produce a single pressure reconstruction methodology. Reconstruction results obtained via this methodology, applied to crank kinematics associated with steady-state engine operation, show a marked improvement over previously published reconstruction accuracy. Moreover, in steady-state engine operation, the application of this methodology to acceleration measurements of cylinder block vibration, obtained from a knock sensor, show very significant improvements over previous attempts. But the direct application of this same reconstruction methodology to transient engine operation, proves to be problematic. However, a novel generalisation of the approach in the form of a time-dependent feed-forward neural network is proposed and the required adaptation made to the use of the Levenberg-Marquardt training algorithm. This time-dependent approach has been tested under limited transient conditions and shown in the thesis to give good results, therefore offering considerable potential for use with real engine operation. Overall, the thesis shows that by careful processing of measured engine data, standard neural network architectures and standard training algorithms can be used to reconstruct engine cylinder pressure.

The main driving force behind this research was the need for cleaner and more efficient engines to meet the ever-increasing demands on the modern automobile's emissions. In recent years different studies have been carried out to analyze the combined effects of high-pressure injection, boost pressure, multiple injections, included spray angle and combustion chamber geometry. Though considerable research has shown these technologies can meet the low emission regulations, the careful optimization of the engine operating conditions is still required in order to get the full benefit of the different strategies. With these issues as motivation, the first important objective of this study was to gain a detailed understanding of the mechanisms through which fuel injection interacts with other engine parameters and influences diesel combustion and emissions, and hence to attempt to generalize the adoption of multiple injection strategies with regards to improving diesel engine performance. For this purpose, a modified parameter called “Homogeneity Factor of in-cylinder charge” (HF) was introduced and proposed as a new measure in combustion theory to analyze the combustion characteristics and air-fuel mixing process of diesel engines in more detail. The second part of this research builds upon a detail investigation on the included spray cone angle concept and explores further their use in conjunction with multiple-injection strategies in diesel engines. In addition, an investigation was performed in third phase of this research to analyze the effects of piston geometry on combustion, performance and exhaust emission characteristics. The results showed that employing a post-injection combined with a pilot injection results in reduced soot formation from diffusion combustion and enhances the soot oxidation process during the expansion stroke, resulting in decreased soot emissions, while the NOx concentration is maintained in low levels. It was also found that spray targeting is very effective for controlling the in-cylinder mixture distributions especially when it accompanied with advanced injection strategies. Moreover, the results confirmed that a narrower width of piston bowl has a higher unburned fuel air mixture region and hence results in higher soot emissions but with slightly larger piston surface area the optimum operating point could be obtained.

Due to the inherent nonlinearity of the diesel engine, real-time control of the variable geometry turbocharger (VGT) and exhaust gas recirculation (EGR) valve still remains a challenging task. A controller has to be capable of coping with the transient operating condition of the engine, the interactions between the VGT and EGR, and also the trade-off effect in this control problem. In this work, novel real-time fuzzy logic controllers (RFLC) were developed and tested. Firstly, the proposed controllers were calibrated and validated in a transient diesel engine model which was developed and validated against the Caterpillar 3126B engine test bed located at the University of Sussex. The controllers were then further tested on the engine test bed. Compared to conventional controllers, the proposed controllers can effectively reduce engine emissions as well as fuel consumption. Experimental results show that compared to the baseline engine running on the Nonroad Transient Cycle (NRTC), mean values of the exhaust gas opacity and the nitrogen oxides (NOx) emission production were reduced by 36.8% and 33%, respectively. Instant specific fuel consumption of the RFLC engine was also reduced by up to 50% compared to the baseline engine during the test. Moreover, the proposed fuzzy logic controllers can also reduce development time and cost by avoiding extensive engine mapping of inlet air pressure and flow. When on-line emission measurements were not available, on-board emission predictors were developed and tested to supply the proposed fuzzy logic controller with predictions of soot and NOx production. Alternatively, adaptive neuro fuzzy inference system (ANFIS) controllers, which can learn from fuzzy logic controllers, were developed and tested. In the end, the proposed fuzzy logic controllers were compared with PI controllers using the transient engine model.