Root-finding algorithms have been studied for ages for their various applications. Newton's Method is just one of these root-finding algorithms. This report discusses Newton's Method and aims to describe the procedures behind the method and to determine its capabilities in finding the zeros for various functions. The possible outcomes when using this method are also explained; whether the Newton function will converge to a root, diverge from the root, or enter a cycle. Modifications of the method and its applications are also described, showing the flexibility of the method for different situations. / text

To get the distribution network to operate at its optimum performance in an automated distribution system reconfiguration was been proposed and researched. Considering, however, that optimum performance implies minimum loss, no overloading of transformers and cables, correct voltage profile, and absence of phase voltage and current imbalances, network reconfiguration alone is insufficient. It has to be complemented with techniques for phase rearrangement between the distribution transformer banks and the specific primary feeder with a radial structure and dynamic phase and load balancing along a feeder with a radial structure. This paper contributes such a technique at the low-voltage and medium-voltage levels of a distribution network simultaneously with reconfiguration at both levels. While the neural network is adopted for the network reconfiguration problem, this paper introduces a heuristic method for the phase balancing/loss minimization problem. A comparison of the heuristic algorithm with that of the neural network shows the former to be more robust. The approach proposed here, therefore for the combined problem, uses the neural network in conjunction with a heuristic method which enables different reconfiguration switches to be turned on/off and connected consumers to be switched between different phases to keep the phases balanced. An application example of the proposed method using real data is presented.

Sound source localization with microphone arrays has received considerable attention as a means for the automated tracking of individuals in an enclosed space and as a necessary component of any general-purpose speech capture and automated camera pointing system. A novel computationally efficient method compared to traditional source localization techniques is proposed and is both theoretically and experimentally investigated in this research. This thesis first reviews the previous work in this area. The evolution of a new localization algorithm accompanied by an array structure for audio signal localization in three dimensional space is then presented. This method, which has similarities to the structure of the eye, consists of a novel hemispherical microphone array with microphones on the shell and one microphone in the center of the sphere. The hemispherical array provides such benefits as 3D coverage, simple signal processing and low computational complexity. The signal processing scheme utilizes parallel computation of a special and novel closeness function for each microphone direction on the shell. The closeness functions have output values that are linearly proportional to the spatial angular difference between the sound source direction and each of the shell microphone directions. Finally by choosing directions corresponding to the highest closeness function values and implementing linear weighted spatial averaging in those directions we estimate the sound source direction. The experimental tests validate the method with less than 3.10 of error in a small office room. Contrary to traditional algorithmic sound source localization techniques, the proposed method is based on parallel mathematical calculations in the time domain. Consequently, it can be easily implemented on a custom designed integrated circuit.

Vision-based grasp planning can be approached as an optimization problem, where a hand configuration that indicates a stable grasp needs to be located in a large search space. In this thesis, we proposed applying genetic algorithm (GA) to grasp planning of 3D object in arbitrary shapes and any robot hand. Details are given on the selection of operators and parameters of GA. GraspIt! simulator [2] is used for implementing the proposed algorithm and as the test environment. A quantitative analysis including the comparison with simple random algorithm and simulated annealing (SA) method is carried out to evaluate the performance of the GA based planner. Both GA and SA grasp planner are tested on different sets of hand-object. And two different quality metrics are used in the planning. Given the same amount of time, GA is shown to be capable of finding a force-closure grasp with higher stability than SA.

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A number of technologies exist that captures data from biological systems. In addition, several computational tools, which aim to organize the data resulting from these technologies, have been created. The ability of these tools to organize the information into biologically meaningful results, however, needs to be stringently tested. The research contained herein focuses on data produced by technology that records short Expressed Sequence Tags (EST's).

Hemodialysis catheter occlusion compromises hemodialysis adequacy and increases the cost of care. Repeated administration of alteplase in hemodialysis catheters typically produces only short-term benefits. The purpose of this study was to design, implement and evaluate the efficacy of a step-by-step algorithm to optimize the management of hemodialysis catheter occlusion. The study had a prospective quasi-experimental design in two parts. Baseline data on the use of alteplase and catheter exchange were collected during Part I; while, Part II consisted of algorithm implementation. Rates of alteplase use and catheter exchange per 1000 catheter days were main outcomes of the study. One-hundred and seventy-two catheters in 131 patients were followed up during the course of the study. The vast majority of the study population were on clopidogrel or aspirin (75%); whereas, approximately 11% were on warfarin. The adjusted rate of alteplase use was not significantly different after algorithm implementation (Part I vs. Part II relative risk: 1.10; 95% CI: 0.73 – 1.65, p > 0.05). Similarly, catheter exchange rates were not significantly different in both parts of the study (1.12 vs. 1.03 per 1000 catheter-days, p > 0.05). Regression analysis showed that the rate of alteplase use was inversely related to the catheter age (p < 0.05). In a secondary analysis on a subgroup of patients with occlusion-related catheter exchanges (n = 28), the number of alteplase administrations significantly increased with longer waiting time for catheter exchange (p < 0.05). In conclusion the hemodialysis catheter management algorithm was not effective in decreasing the rate of alteplase use.

This research aims to improve the performance of the service of a Chemotherapy Treatment Unit by reducing the waiting time of patients within the unit. In order to fulfill the objective, initially, the chemotherapy treatment unit is deduced as an identical parallel machines scheduling problem with unequal release time and single resource. A mathematical model is developed to generate the optimum schedule. Afterwards, a Tabu search (TS) algorithm is developed. The performance of the TS algorithm is evaluated by comparing results with the mathematical model and the best results of benchmark problems reported in the literature. Later on, an additional resource is considered which converted the problem into a dual resources scheduling problem. Three approaches are proposed to solve this problem; namely, heuristics, a Tabu search algorithm with heuristic (TSHu), and Tabu search algorithm for dual resources (TSD).

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