VecTor© is a suite of computer programs developed for nonlinear finite element analysis of reinforced concrete. A graphics-based pre-processor (FormWorks) was developed for 2D concrete membrane structures, greatly contributing to the software’s utility and success. However, modeling other types of structures is a time consuming process, requiring manual definition of the finite element mesh, loads and analysis parameters in standard text files. A user-friendly pre-processor is required for the entire suite of programs if they are to be of greater use to design engineers. The purpose of this study is to develop an updated version of FormWorks, FormWorks 3.5, which is more user-friendly and compatible with the improvements made in VecTor2 over the past ten years. In addition, an extended version of FormWorks, FormWorks-Plus, will be created for the remaining VecTor programs with a wide range of viewing features, and facilities for specification of node coordinates, elements, loads and material properties.

This study considers the dynamic pedestrian detection system and the static pedestrian detection system with a single camera. In the static detection system, this study reconstructs the static database. As to feature extraction, HOG combining with SVM classifier is used in this study. Experimental results show the database can detect people by this algorithm in several scenes. In the dynamic detection system, because the population of older persons and disabled persons increases gradually nowadays, cross the intersection is a challenge for older persons and disabled persons, so this study researches in dynamic pedestrian detection system by a single camera for assisting autonomous transport robots, and this system detects people at the intersection for assisting older persons and disabled persons when they cross the intersection. As to the algorithm this study uses the foot detection algorithm to detect dynamic pedestrians. According to the experimental results, the light and clothes effect on the experimental results both in the dynamic pedestrian system and the static pedestrian system. The dynamic pedestrian system still shows real-time performance not only in the longitudinal direction but also in the lateral direction.

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Thesis (Ph. D.)--University of Chicago, 1921. / Published also without thesis note.

Thesis (M. Sc. (Mathematics))--Rhodes University, 2002.

No description available.

Many computer vision problems involve building automatic systems by extracting complex high-level information from visual data. Such problems can often be modeled using structural models, which relate raw input variables to structural high-level output variables. Structural support vector machine is a discriminative method for learning structural models. It allows a flexible feature construction with good robustness against overfitting, and thus provides state-of-the-art prediction accuracies for structural prediction tasks in computer vision. This thesis first studies the application of structural SVMs in interactive image segmentation. A novel interactive image segmentation technique that automatically learns segmentation parameters tailored for each and every image is proposed. Unlike existing work, the proposed method does not require any offline parameter tuning or training stage, and is capable of determining image-specific parameters according to some simple user interactions with the target image. The segmentation problem is modeled as an inference of a conditional random field (CRF) over a segmentation mask and the target image. This CRF is parametrized by the weights for different terms (e.g., color, texture and smoothing). These weight parameters are learned via a one-slack structural SVM, which is solved using a constraint approximation scheme and the cutting plane algorithm. Experimental results show that the proposed method, by learning image-specific parameters automatically, outperforms other state-of-the-art interactive image segmentation techniques. This thesis then uses structural SVMs to speed up large scale relatively-paired space analysis. A new multi-modality analysis technique based on relatively-paired observations from multiple modalities is proposed. Relative-pairing information is encoded using relative proximities of observations in a latent common space. By building a discriminative model and maximizing a distance margin, a projection function that maps observations into the latent common space is learned for each modality. However, training based on large scale relatively-paired observations could be extremely time consuming. To this end, the training is reformulated as learning a structural model, which can be optimized by the cutting plane algorithm where only a few training samples are involved in each iteration. Experimental results validate the effectiveness and efficiency of the proposed technique. / published_or_final_version / Computer Science / Doctoral / Doctor of Philosophy

No description available.

Malaria, a preventable disease caused by a mosquito-transmitted parasitic infection, continues to be a prominent public health problem today. Progress has been made in the last decade demonstrated by malaria mortality reductions primarily attributed to current vector control strategies. However, the continuing threat of resistance, both resistance of mosquitoes to insecticides and parasites to antimalarial medicines, requires the development of new and improved strategies to supplement those already in place. Housing improvements such as screening doors and windows, closing eaves, patching cracks in walls, and installing ceilings are one such intervention that help stop contact between malaria vectors and humans, and therefore, help stop malaria transmission. Historically considered successful in helping fight malaria, housing improvements are being looked to again today.

Simulation is a powerful tool for developing electric drive systems. Simulations allow the designer to experiment with control algorithms and hardware systems in a safe environment. To this end simulation is becoming increasingly popular. On'-line simulation does have its limitations in that the controller developed during the simulation period has eventually to be transferred to the target processor which will operate in the actual drive system. If, however, a real-time simulation environment could be realised, then the actual controller running in the actual target processor could be included in the simulation. Therefore no translation of code would be required once the controller had been developed and tested within the simulation. This would obviously lead to a reduction in development time and eliminate any possibility of introducing errors due to the translation between the simulated and actual controllers. This thesis describes the development of such a system using a multiple digital signal processing environment. The real-time simulated drive is operated in parallel with an experimental drive to allow a direct comparison between the two. The ability of the multiple processing system to operate in real-time has allowed the whole concept of simulation to be taken a stage further by the development of a real-time power level simulator. This simulator is capable of emulating a machine and load in real-time with real level of voltage and current. It is designed to replace a real machine during the development and testing stages of drive manufacture. This Virtual Machine is a controllable source/sink which is driven by the real-time simulation, and because of this the Virtual Machine takes on the characteristics of any choice of model within the real-time simulation. Moreover, because of its ability to handle bi-directional power flow, the Virtual machine can be programmed to emulate motors or generators. The Virtual Machine also includes the emulation of loads, thus making it extremely flexible and of interest to applications such as machine tools, electric vehicles, and wind generators, to name but a few.