Bottomland hardwood forests are highly productive ecosystems which perform many important ecological services. Unfortunately, many bottomland hardwood forests have been degraded or lost. Accurate land cover mapping is crucial for management decisions affecting these disappearing systems. SPOT-5 imagery from 2005 was combined with Light Detection and Ranging (LiDAR) data from 2006 and several ancillary datasets to map a portion of the bottomland hardwood system found in the Sulphur River Basin of Northeast Texas. Pixel-based classification techniques, rulebased classification techniques, and object-based classification techniques were used to distinguish nine land cover types in the area. The rule-based classification (84.41% overall accuracy) outperformed the other classification methods because it more effectively incorporated the LiDAR and ancillary datasets when needed. This output was compared to previous classifications from 1974, 1984, 1991, and 1997 to determine abundance trends in the area’s bottomland hardwood forests. The classifications from 1974-1991 were conducted using identical class definitions and input imagery (Landsat MSS 60m), and the direct comparison demonstrates an overall declining trend in bottomland hardwood abundance. The trend levels off in 1997 when medium resolution imagery was first utilized (Landsat TM 30m) and the 2005 classification also shows an increase in bottomland hardwood from 1997 to 2005, when SPOT-5 10m imagery was used. However, when the classifications are re-sampled to the same resolution (60m), the percent area of bottomland hardwood consistently decreases from 1974-2005. Additional investigation of object-oriented classification proved useful. A major shortcoming of object-based classification is limited justification regarding the selection of segmentation parameters. Often, segmentation parameters are arbitrarily defined using general guidelines or are determined through a large number of parameter combinations. This research justifies the selection of segmentation parameters through a process that utilizes landscape metrics and statistical techniques to determine ideal segmentation parameters. The classification resulting from these parameters outperforms the classification resulting from arbitrary parameters by approximately three to six percent in terms of overall accuracy, demonstrating that landscape metrics can be successfully linked to segmentation parameters in order to create image objects that more closely resemble real-world objects and result in a more accurate final classification.

Vibroarthrograpyhy (VAG) is an innovative, objective and non-invasive technique to obtain diagnostic information concerning the articular cartilage of knee joints. Knee VAG signals can be detected by putting a contact sensor on the surface of the knee joints during the movement such as flexion and extension. Before this research, there are many VAG group studies that contribute in signal processing and database building. The adaptive segmentation method and autoregressive modeling are developed to segment the nonstationary VAG signals. This thesis tries to investigate the accuracy of some database containing root mean square (RMS) value and intraclass distance (ID) feature parameters of physiological patellofemoral crepitus (PPC) signals. This research is first setting up two diagnosis standards for RMS and ID. According to the two standards, all signals are divided into three types: normal, unknown and injured, and those appear both in normal type of RMS and ID parameters are picked out. The same does the injured type. In conclusion, by checking the anamneses of these signals, we can be aware of the numbers of real normal and real injured in normal type and injured type; therefore the accuracy of the database can be derived. Consequently the accuracy of database in this thesis is quite certifiable.

Generation Xers are latchkey kids. They are used to eat microwave food, and grow up with TV ¡V games. As the leading edge of the baby boomer creeps inexorably toward retirement and tighter spending habits, every company with something to sell is starting to focus on younger demographics Gen X'ers in their mid-20s to 40. The purpose of the study is to study Generation X life styles in the purchasing of sedans. More particularly, the purpose is to study the relationship of life style and decision making process, EKB model, of Generation X in the purchasing of sedans. The study aims to examine and identify applicable life styles segments of Generation X, and identify their differences between decision making process in the purchasing of sedans. This study method is questionnaire and 600 questionnaires are released, and the retrieved valid questionnaires are 404 copies. This study utilizes using SPSS for Windows as the tool to conduct statistical analysis, including descriptive analysis, reliability test, factor analysis, cluster analysis, Pearson¡¦s Chi ¡V Square and ANOVA test. Four types of life styles are generalized. There are ACTIVE life style, INFORMATION ¡V ORIENTATION life style, STABLE life style, and INDEPENDENT life style. The finding results as follow. 1. In the purchasing of sedans, there are partial significant differences on demographics with respect of Generation X life styles. 2. In the purchasing of sedans, there are no significant differences on problem recognition with respect of Generation X life styles. 3. In the purchasing of sedans, there are no significant differences on information search with respect of Generation X life styles. 4. In the purchasing of sedans, there are partial significant differences on elevation of alternatives with respect of Generation X life styles. 5. In the purchasing of sedans, there are partial significant differences on purchase with respect of Generation X life styles. In the end of the study, some suggestions for further research are made. Given the study results, the marketer and policymakers of manufacturer sedan brands can find the needs of Generation X life styles in the purchasing of sedans. The study results for marketers and policymakers may provide strategy for sedans with Generation X life styles different of degree of demographics, problem recognition, information search, elevation of alternatives, and purchase.

The innovation of information techniques has changed many aspects of our life. In health care field, we can obtain, manage and communicate high-quality large volumetric image data by computer integrated devices, to support medical care. In this dissertation I propose several promising methods that could assist physicians in processing, observing and communicating the image data. They are included in my three research aspects: telemedicine integration, medical image visualization and image segmentation. And these methods are also demonstrated by the demo software that I developed. One of my research point focuses on medical information storage standard in telemedicine, for example DICOM, which is the predominant standard for the storage and communication of medical images. I propose a novel 3D image data storage method, which was lacking in current DICOM standard. I also created a mechanism to make use of the non-standard or private DICOM files. In this thesis I present several rendering techniques on medical image visualization to offer different display manners, both 2D and 3D, for example, cut through data volume in arbitrary degree, rendering the surface shell of the data, and rendering the semi-transparent volume of the data. A hybrid segmentation approach, designed for semi-automated segmentation of radiological image, such as CT, MRI, etc, is proposed in this thesis to get the organ or interested area from the image. This approach takes advantage of the region-based method and boundary-based methods. Three steps compose the hybrid approach: the first step gets coarse segmentation by fuzzy affinity and generates homogeneity operator; the second step divides the image by Voronoi Diagram and reclassifies the regions by the operator to refine segmentation from the previous step; the third step handles vague boundary by level set model. Topics for future research are mentioned in the end, including new supplement for DICOM standard for segmentation information storage, visualization of multimodal image information, and improvement of the segmentation approach to higher dimension. / Innovative Informationstechnologien haben viele Bereiche unseres Lebens verändert. Im Gesundheitsbereich ist es mittels Computer möglich, qualitativ hochwertige und große volumetrische Bilddaten zu verwalten, zu verarbeiten und dadurch die medizinische Betreuung zu unterstützen. In dieser Dissertation stelle ich verschiedene Methoden vor, die Mediziner beim Prozess der Beobachtung, Verarbeitung und Nutzung von Bilddaten verstärkt unterstützten können. Meine Forschungsarbeit befasst sich mit drei Schwerpunktthemen: Telemedizinintegration, Visualisierung von medizinischen Bildern und Bildsegmentierung. Zur Demonstration der Machbarkeit der vorgeschlagenen Methoden implementierte ich zudem eine Anwendungssoftware. Das entwickelte System kann in punkto Telemedizinintegration nicht nur Dateien im DICOM Format lesen und schreiben, sondern auch nicht-standardisierte Dateien reparieren. In meiner Arbeit gebe ich außerdem einen Vorschlag für eine Erweiterung des DICOM Standards für die Speicherung von 3D Bildinformationen. Zur Darstellung der Bilddaten wurden in dem entwickelten System drei verschiedene Ansichten implementiert: Volumen Ansicht, Oberflächen Ansicht sowie Querschnitt Ansicht. Ein Großteil meiner Arbeit ist der Vorschlag eines neuen hybriden Bildsegmentierungsansatzes. Durch das neu vorgeschlagene Verfahren können komplexe neurale MRI Daten effizient und präzise segmentiert werden. Zusätzlich wird der manuelle Arbeitsaufwand der Experten drastisch verringert.

In stochastic representation an image is a sample function of an array of random variables which is called a random field. For characterizing an ensemble of images, we choose an autoregressive model as our image model. An image model often applies to image processing such as image data compression and image restoration. Therefore the validity of the image model affect it¡¦s performance of image processing. The output of the AR model depends on its parameters ¡V system transition matrix and generating noise. Hence the validity of this model is related to these two parameters. How to seek the standard of the validity of the image model is a problem. We exploit performance of image model¡¦s application ¡V image restoration - to find a method of determining the validity of the image model. In our paper we find a relation between image restoration performance and image model¡¦s parameters by the Kalman filtering equations. An image model with lower generating noise power and system transition matrix is better for image restoration and is considered a good image model. In the analysis of the parameters of the image model, we can meet the requirements of the parameters by image segmentation method, residual image method and normalized image method. In addition it also helps us understand the Kalman filter much more and know how to find the solution of similar problems.

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Abstract The origin of Human Resource is education. In terms of marketing, the purpose of this study is to understand the main sources of information and influence as well as the priority of factors on the future intentions and determinations of junior high school students in the target market. Besides, Discussed and understood by way of Market Segmentation Analysis Technology, various sorts of students¡¦ characteristics affect on the recruitment on senior high and vocational high school students. Followed by the above analyses, there are some suggestions are concluded to the options of goals, the main focus of strategies and the plan of related activities on student recruitment, ought to think how to develop their own characteristics. Through the analyses of Market Segmentation, the priority of school types, the sources of information and influence, the outcomes are concluded to suggest the goals to recruit senior high school students will be focused on students which are Cluster 3 (ideal-approached), Cluster 1 (career-approached), living in the neighborhood of business areas, and whose the educational levels of parents are ranged above college; moreover, the grades of students are ranged within top 10 will have the priorities. As to the deliveries of information, family or relatives will be the first and best choice. Then, by way of the DM of senior high and vocational high schools, teachers and classmates will be in junior high school. Except for students themselves, those who are influential will be mother, and then father will comes after mother. Meanwhile, it is important to emphasize consultancy on future career, the distance from school, the peer quality, the ranges of Joint Entrance Exams for years and the faculty. The goals to recruit vocational high school students will be as follows: students who belong to Cluster 1, Cluster 3, who live in industrial or port areas, whose parents only received education below junior high school with mid-low payment and the students will be ranged after 21 in their class. As to the deliveries of information, family or relatives will be the first and best choice. Then, by way of the DM of senior high/vocational high schools, teachers and classmates in junior high school. Except for students themselves, those who are influential will be mother, father and then classmates. Meanwhile, it is important to emphasize consultancy on future career (consultancy on further study), the distance from school, the convenience of living, the ranges of Joint Entrance Exams for years and the percentages of further study to gradated students. The goals to recruit complex type of senior high school students will be as follows: students who live in industrial or port areas, whose parents finished senior/vocational high school education with mid-low payment and the students will be ranged within 11 to 20 in their class. As to the deliveries of information, family or relatives will be the first and best choice. Then, by way of the DM of senior high/vocational high schools, teachers from senior/vocational high schools, their own junior high school teachers. Except for students themselves, those who are influential will be mother, and then father will comes after mother. Meanwhile, it is important to emphasize consultancy on future career, the distance from school, the peer quality, the ranges of Joint Entrance Exams for years.

Texture boundary detection (or segmentation) is an important capability of the human visual system. Usually, texture segmentation is viewed as a 2D problem, as the definition of the problem itself assumes a 2D substrate. However, an interesting hypothesis emerges when we ask a question regarding the nature of textures: What are textures, and why did the ability to discriminate texture evolve or develop? A possible answer to this question is that textures naturally define physically distinct surfaces or objects, thus, we can hypothesize that 2D texture segmentation may be an outgrowth of the ability to discriminate surfaces in 3D. In this thesis, I investigated the relative difficulty of learning to segment textures in 2D vs. 3D configurations. It turns out that learning is faster and more accurate in 3D, very much in line with what was expected. Furthermore, I have shown that the learned ability to segment texture in 3D transfers well into 2D texture segmentation, but not the other way around, bolstering the initial hypothesis, and providing an alternative approach to the texture segmentation problem.

The past decade has seen a steady increase in wine consumption in Taiwan. With the increase comes the need to understand how consumers choose wine. Market segmentation is the principal concept in this study, and the aim is to find consumer behaviors of wine in different segments. A range of behavioral and demographic information was collected by the survey of questionnaire. In particular, participants were asked to indicate on average how many bottles of wine they purchased and how many hours they spent to acquire wine information per month. The above information forms the basis of segmenting, together with other behavioral information, combines to form profiles of consumers with high and low involvement of wine. In the process, cluster analysis was performed to divide the respondents into two groups, cross analysis and chi-square test were used to evaluate the significant differences on behavioral variables, and factor analysis and one-way ANOVA were applied to find which wine characteristics were important toward each segment. The result showed that significant differences were found between two groups on the choices of wine types and wine outlets, the way of acquiring wine information, the factors effecting to choose wines, and the characteristics of wine they emphasized.