Three-Dimensional (3-D) imaging is vital in computer-assisted surgical planning including minimal invasive surgery, targeted drug delivery, and tumor resection. Selective Internal Radiation Therapy (SIRT) is a liver directed radiation therapy for the treatment of liver cancer. Accurate calculation of anatomical liver and tumor volumes are essential for the determination of the tumor to normal liver ratio and for the calculation of the dose of Y-90 microspheres that will result in high concentration of the radiation in the tumor region as compared to nearby healthy tissue. Present manual techniques for segmentation of the liver from Computed Tomography (CT) tend to be tedious and greatly dependent on the skill of the technician/doctor performing the task. This dissertation presents the development and implementation of a fully integrated algorithm for 3-D liver and tumor segmentation from tri-phase CT that yield highly accurate estimations of the respective volumes of the liver and tumor(s). The algorithm as designed requires minimal human intervention without compromising the accuracy of the segmentation results. Embedded within this algorithm is an effective method for extracting blood vessels that feed the tumor(s) in order to plan effectively the appropriate treatment. Segmentation of the liver led to an accuracy in excess of 95% in estimating liver volumes in 20 datasets in comparison to the manual gold standard volumes. In a similar comparison, tumor segmentation exhibited an accuracy of 86% in estimating tumor(s) volume(s). Qualitative results of the blood vessel segmentation algorithm demonstrated the effectiveness of the algorithm in extracting and rendering the vasculature structure of the liver. Results of the parallel computing process, using a single workstation, showed a 78% gain. Also, statistical analysis carried out to determine if the manual initialization has any impact on the accuracy showed user initialization independence in the results. The dissertation thus provides a complete 3-D solution towards liver cancer treatment planning with the opportunity to extract, visualize and quantify the needed statistics for liver cancer treatment. Since SIRT requires highly accurate calculation of the liver and tumor volumes, this new method provides an effective and computationally efficient process required of such challenging clinical requirements.

This thesis investigates the possibility of detecting weak vital signs, such as heartbeat and respiration rate, through the implementation of quadrature demodulation and frequency spectrum algorithms on a high performance digital signal processor. This thesis has been part of an ongoing research project at Linkoping University, with the aim to develop a sensor platform for wireless measurements of these vital signs. This sensor platform has been expected to consist of two major physical devices, a RF-radar front-end including a quadrature multi-port and a processing back-end which holds the implementation of the algorithms to detect the vital signs. The back-end consists of a data acquisition- and a processing-part which together forms the digital signal processor. The results show that the implemented algorithms works in terms of being able to find artificial vital signs from quadrature signals. This result also confirms that the hardware solution proposed during this thesis, has been considered as viable for the aim of the project.

Speech is intuitive, fast and easy to generate, but it is hard to index and easy to forget. What is more, listening to speech is slow. Text is easier to store, process and consume, both for computers and for humans, but writing text is slow and requires some intention. In this thesis, we study speech recognition which allows converting speech into text, making it easier both to create and to use information. Our tool of study is Hidden Markov Models which is one of the most important machine learning models in speech and language processing. The aim of this thesis is to do a rst study in Hidden Markov Models and understand their importance, particularly in speech recognition. We will go through three fundamental problems that come up naturally with Hidden Markov Models: to compute a likelihood of an observation sequence, to nd an optimal state sequence given an observation sequence and the model, and to adjust the model parameters. A solution to each problem will be given together with an example and the corresponding simulations using MatLab. The main importance lies in the last example, in which a rst approach to speech recognition will be done.

This thesis explores the impacts and behavior of 3-phase distribution transformers when subject to ungrounded single phase open circuit faults. A simple 3-phase system is modeled using MATLAB Simulink and operation under fault conditions are simulated and studied. Simulation results are confirmed via lab experimentation. Finally, a robust detection and protection method using neutral current injection (as proposed in industry literature) is built and demonstrated. Electric utility operating experience has demonstrated that all too often, loads on 3-phase distribution transformers are not adequately protected against an ungrounded single phase open circuit fault (commonly called “single phasing”). This type of fault is amongst the least understood and hence the least protected against. This is especially true at end of transmission system radial feeds where 3-phase transformers can re-create the opened phase voltage due to a variety of effects including magnetic coupling, voltage loops and loading effects. Operating experience in the nuclear power industry has shown that the results can be catastrophic especially considering the impacts to motor loads. Impacts can result in unavailability of emergency loads, tripping of motor protection circuits or even motor damage and failure.

A Stewart Platform robot was designed, constructed, and programmed for use in Cal Poly’s ME 423 Robotics: Fundamentals and Applications laboratory section. A Stewart Platform is a parallel manipulator robot with six prismatic joints that has six degrees of freedom, able to be defined in both position and orientation. Its purpose is to supplement parallel robot material covered in lecture. Learning objectives include applying and verifying the Stewart Platform inverse kinematics and investigating the Stewart Platform’s operation, range of motion, and limitations. The Stewart Platform geometry and inverse kinematics were modeled and animated using MATLAB. The platform was then built using linear actuators, magnetic spherical bearings, and acrylic plates. Control of the Stewart Platform is achieved using an Arduino Due and a custom HexaMoto shield. Users interact with the system using a GUI created with MATLAB’s App Designer.

This master's thesis focuses on the design and creation of a decision support tool for the investment property plan. The evaluation of real estate is based on fuzzy logic. The design and debugging of fuzzy models are done by using MATLAB, but the application is developed in Java.

This diploma thesis is focused on the evaluation of suppliers the selection of the best one for company Fast & Healthy food services, s.r.o. This work describes methods and the process of model creation using fuzzy logic. The aim is to establish two decision models, a model created in MS Excel and a model created in MATLAB which simplify the selection of the supplier.

The vibration analysis of a production machine is a key factor of its functionality, service life and occupational safety. This work deals with mathematical dynamic modelling and its contribution to the improvement of a mechanical design and mechanism failure prevention. The whole process is presented on the example of a drum cam rotary indexing table and on the example of actuators of multi spindle automatic lathes. The analysis consisted of complex nonlinear models based on basic linear models. It was computed using Matlab, Simulink and MSC ADAMS. Models of these mechanisms were validated with experimental measurements. The results were used for mechanical design improvement and for speed control optimization.

Creating a decision-making system for evaluating cooperation between companies based on the fuzzy model in MS Excel and MATLAB programming environment. Subsequent evaluation of possible risks for the selected company.

Master’s thesis deals with designing decision making system based on fuzzy logic principles which evaluates suppliers offers. In this Master’s thesis there were created two decision making systems based on the demands of the company. First decision making system was designed within the environment of MS Excel, the second one was designed in MATLAB software. In addition of creating the decision making system the thesis puts emphasis on the analysis of the current decision making model in the company and this section will serve as a springboard to designing a decision making system based on fuzzy logic. At the beginning of the work there are included all the necessary theoretical framework on which I based the writing of this thesis.