This masters thesis describes the development of signal processing and patternrecognition in monitoring Parkison’s disease. It involves the development of a signalprocess algorithm and passing it into a pattern recogniton algorithm also. Thesealgorithms are used to determine , predict and make a conclusion on the study ofparkison’s disease. We get to understand the nature of how the parkinson’s disease isin humans.

The aim of this thesis project is to develop the Traffic Sign Recognition algorithm for real time. Inreal time environment, vehicles move at high speed on roads. For the vehicle intelligent system itbecomes essential to detect, process and recognize the traffic sign which is coming in front ofvehicle with high relative velocity, at the right time, so that the driver would be able to pro-actsimultaneously on instructions given in the Traffic Sign. The system assists drivers about trafficsigns they did not recognize before passing them. With the Traffic Sign Recognition system, thevehicle becomes aware of the traffic environment and reacts according to the situation.The objective of the project is to develop a system which can recognize the traffic signs in real time.The three target parameters are the system’s response time in real-time video streaming, the trafficsign recognition speed in still images and the recognition accuracy. The system consists of threeprocesses; the traffic sign detection, the traffic sign recognition and the traffic sign tracking. Thedetection process uses physical properties of traffic signs based on a priori knowledge to detect roadsigns. It generates the road sign image as the input to the recognition process. The recognitionprocess is implemented using the Pattern Matching algorithm. The system was first tested onstationary images where it showed on average 97% accuracy with the average processing time of0.15 seconds for traffic sign recognition. This procedure was then applied to the real time videostreaming. Finally the tracking of traffic signs was developed using Blob tracking which showed theaverage recognition accuracy to 95% in real time and improved the system’s average response timeto 0.04 seconds. This project has been implemented in C-language using the Open Computer VisionLibrary.

Background: Organizations’ ability to recognize opportunities can provide competitive advantage for organizations in changing environment. In innovation-driven countries many en-trepreneurial people are working as employees in established companies and pursuing opportunities as corporate entrepreneurs. This is a group which researchers have dis-criminated by focusing only on CEO’s and entrepreneur’s opportunity identification capability. We would like to research the topic of employees’ opportunity recognition (OpR) and to find a link with their attitudes towards entrepreneurship, something that so far was not completely investigated in the literature. Purpose: The aim of the master thesis is to examine the relationship between the employee’s atti-tudes towards entrepreneurship and their implication on their ability to recognize opportu-nities – a step before developing innovation or uniqueness, resulting in creation of compet-itive advantage to the company, presumably leading to company growth. This paper in-tends to fill the gap in the literature regarding one of the dimensions of the factors leading to company growth and analyses a different business stakeholder group – namely employees in medium-sized companies. From business perspective, it might help company leaders understand the need of encouraging entrepreneurial initiatives and encourage them with some practical suggestions. The research question is: does employees’ attitude towards en-trepreneurship affect their opportunity recognition. Method: We have chosen deductive and explanatory approach for our research because we study causal relationship between attitudes towards entrepreneurship and OpR. The primary data was collected by a self-administered electronic questionnaire. The num-ber of received responses is 53, mainly from manufacturing and service industries. Conclusion: Employees’ positive attitude towards entrepreneurship increases their opportunity identification capability.

The purpose of this project is to test and improve people’s ability of face recognition. Although there are some tests on the internet with the same purpose, the problem is that people may feel bored and give up before finishing the tests. Consequently they may not benefit from testing nor from training. To solve this problem, face recognition and online game are put together in this project. The game is supposed to provide entertainment when people are playing, so that more people can take the test and improve their abilities of face recognition. In the game design, the game is assumed to take place in the face recognition lab, which is an imaginary lab. The player plays the main role in this game and asked to solve a number of problems. There are several scenarios waiting for the player, which mainly need face recognition skills from the player. At the end the player obtains the result of evaluation of her/his skills in face recognition.

This study examined the effectiveness of embedded picture mnemonic alphabet cards on the acquisition of letter name and letter sound knowledge with at-risk kindergarten students in a rural Texas public school. The study compared student achievement against a zero baseline when the student(s) are trained using a dissassociated picture mnemonic to an embedded picture mnemonic. A secondary area of investigation was the “Degree of Difficulty in Learning Letter Names” theory proposed by Treiman, Tincoff, Rodriguez, Mouzaki, & Francis. The theory states that consonant letter names can be divided into three categories based on phoneme characteristics: Easy to learn letters have a consonant-vowel pattern (the letter name for “D” is /d/ /e/); hard letters have a converse pattern of vowel-consonant (the letter name for “M” is /e/ /m/); and the other category has no phoneme pattern reflective to the letter name (the letter name “W” is “double” “you”). Students were randomly selected to either the treatment or the control group and after a ten-day (two week) training period, the students were given one week with no intervention then administered a posttest, followed by another week with no intervention followed by a post-posttest. The purpose for this assessment design was to determine if the training had an effect on long-term memory. Results revealed that children taught with the embedded picture mnemonics learned more letter name associations than did the control group. The embedded picture mnemonic had a positive effect on long term memory reflecting an increase from a moderate effect sizes for letter naming (d = .69) on the first week post test to a large effect size for letter naming (d =1.12) on the second week post test. The results also revealed inconclusive support for Treiman’s et al. (1998) degree of difficulty in learning letter names theory.

In state-of-the-art software library, such as Standard Template Library (STL) , they support a number of data models, for example, set, map, sequence, etc. Since graph data processing is widely used in combinatorial processing and optimization programs, in this research, we designed software implementation of a condition-based graph structure recognition method. This design consists of four kinds of condition functions specific to graph structures, control functions of structure recognition operation flow, and programming interface to facilitate programs writing various efficient graph structure recognition programs. We implemented a software library of this graph structure recognition method to support program design containing graph data and processing.

Terns usually will aggregate in the same reproduction area during breeding season. The color pattern of eggs may match the background, and it is important for breeding adults to distinguish their own eggs, especially in colonies with high density. This research was carried out at three islands, Huolung Shoal, Baisha and Jishan Islets of Penghu from May to August of 2007 and 2008. The experiment was divided into three parts, egg moving (EM) experiment, nest modification (NM) experiment and egg switching (ES) experiment. Terns spent more time for searching their own nests of each of the experiment situation. In the EM experiment 69.7% Black-naped Tern adults settled on original nests without eggs in 2007; 52.0% Roseate Tern in 2007 and 29.6 % in 2008 did the same. In the NM experiment, the behavior patterns of returning adults were significantly different between each operation and the control group. Adults were confused by the interference of the experimental conditions. In some occasions, adults settled on incorrect eggs quietly in ES experiment. In conclusion, terns have low ability of egg recognition but high ability of nest recognition. Terns presumably can recognize nests with the nearby environmental landmarks, but not be able to recognize eggs.

Thesis (Ph. D.)--University of Texas at Austin, 1999. / Vita. Includes bibliographical references (leaves 111-136). Available also in a digital version from Dissertation Abstracts.

Thesis (Ph. D.)--University of Texas at Austin, 2000. / Vita. Includes bibliographical references (leaves 138-150). Available also in a digital version from Dissertation Abstracts.

Thesis (Ph. D.)--State University of New York at Buffalo, 1995. / "August, 1995." Includes bibliographical references (p. 123-136). Also available in print.