The current study examined the psychological consequences of trait and state self objectification. This study had three main objectives: to examine the relation between trait self objectification and various eating pathologies; to examine the degree of state self objectification (induced by three different conditions) and the impact of condition on affect and sense of self; and finally, to examine the effect of condition on interactions with the opposite sex. The pilot study was used to select thin, thin sexually objectifying and average/plus size non-sexually objectifying images. Using a quasi-experimental research design with an elaborate cover story, the main study exposed one hundred seventy women to one of three conditions (thin non sexually objectifying, thin sexually objectifying or plus size non-sexually objectifying images) and measured negative affect and body image. Following viewing images, participants interacted with a male confederate for five minutes and their reported comfort level and flirting with the confederate were assessed. Results indicated that trait self objectification was associated with disordered eating symptomatology. However, the manipulation check revealed that the experimental condition did not produce varying degrees of sexual objectification. Nonetheless, results indicate an effect of condition on body dissatisfaction, in which individuals who viewed thin images reported more body dissatisfaction than participants in the above average/plus size group. In regards to the social interaction, individuals in the non-sexually objectified group reported more flirting than individuals in the sexually objectified group. Implications for clinical work and future research are discussed.

The current study examined affective reactivity to oneself in an upward socialcomparison manipulation using autonomic physiological responses. Study I was conducted to select images of thin and average size models used to elicit a social comparison process for Study II. For Study II, thirty-two female undergraduate students had their startle reflex and skin conductance responses recorded while viewing images of themselves presented adjacent to thin or average size models. Participants also viewed positive, negative, and neutral affect images to test our experimental manipulation of Peter Lang’s startle paradigm. Following the visual presentation, participants used the SAM scale to rate each image along the dimensions of valence, arousal, dominance, body satisfaction, and attractiveness. Analyses revealed that participants reacted to thin and average size models and self with similar levels of body image satisfaction, valence, and arousal, even though thin models were perceived as highly more attractive. Positive affect images were rated higher on valence and arousal among all the picture types. With regards to the psychophysiological data, there were differences in startle reactivity among the three model-to-self comparison images, with images of Thin-to-Self Comparison eliciting more of an inhibited startle response and Thin-to-Average Comparison images eliciting more of a potentiated startle response. In terms of arousal, positive affect images were perceived as more arousing among all the picture types. Contrary to what was expected, there were no significant differences in skin conductance responsiveness between the three model-to self comparison images. The results are discussed from a social-comparison perspective with regard to affective reactivity to body image. Future research directions are proposed.

Image generating system is usually considered as a noncausal system. The Kalman filter and the Wiener filter are two important linear filters for signal estimation. They are developed for the causal signal and noncausal signal respectively. However, the Kalman filter can also be applied to the noncausal system by rewriting the signal generating equation. In this thesis, we study the performance of the Wiener filter and the Kalman filter applied to image restoration. Our experiments have demonstrated that the rank of list for error performance is: the full order Winner filter, the Kalman filter, the reduced Kalman filter, the three-order Wiener filter. This performance is consisted with the amount of data used in the linear estimation. On the other hand the list for computation performance is as following: the reduced Kalman filter, the three-order Wiener filter, the Kalman filter, the full order Wiener filter. The efficiency of the reduced Kalman filter can be understood by the computation saving of huge updating procedures. It should be noted that the efficiency of applying the regular Kalman filter in this thesis is achieved by fully employed the special form of system matrix involved. In addition to the above noncausal image model, a causal image model can also be built if the central pixel is assumed to be affected only by the left and the upper pixels. The second model is not natural but is obviously advantageous in computation efficiency compared to the first model. However, the first model is much better than the second model error performance. Therefore, it is suggested that the natural image should be modeled as a noncausal model.

Numerous scholars pointed out that destination images are an important and successful factor for destination marketing. Travel destination with strong and positive images are a key factor that was usually chosen by tourists. Personal subject consciousness and customer¡¦ s behaviors will be influenced by destination images. Therefore, destination images are the most important role in the process of tourism decisions. This study is attempted to investigate what factors are influenced by the formation of destination images. And to know what Kaohsiung City¡¦s destination images are from the perspectives of foreign tourists. This research provided structure questionnaire to foreign tourists whose native languages are Chinese, Japanese, English and taking the Kaohsiung International Airport as an investigating place. According to SPSS analysis, the findings are as follows: (1) Kaohsiung City¡¦s destination overall images were considered as good in the perspective of foreign tourists. The hospitality and friendliness the local residents are truly agreed by foreign tourists. On the contrary, the traffic and amusement at night in Kaohsiung City are highly disagreed by foreign tourists. (2) Images would be influenced by cultural resources, quality of services and natural environment which were considered by foreign tourists. (3) The formation of destination image would be influenced by travel motivations. (4) The formation of destination images would be influenced by the number of times of the sightseeing, companion¡¦s relation, age and nationality. (5) The formation of destination images would be influenced by information sources, which included previous visiting experiences by oneself, introductions of relatives and friends, the TV programs, travel guides and films. According to these findings, this study suggests that native government should reinforce communications development. And to promote Kaohsiung City¡¦s uniqueness and advantage by using TV, travel guides and films, such as cultural resources, amusements at night etc. In the aspect of tourism market, they should strengthen marketing in Hong Kong.

The objective of the present work is to propose a novel method to extract a stable feature set representative of image content. Each image is represented by a linear combination of fractal orthonormal basis vectors. The mapping coefficients of an image projected onto each orthonormal basis constitute the feature vector. The set of orthonormal basis vectors are generated by utilizing fractal iterative function through target and domain blocks mapping. The distance measure remains consistent, i.e., isometric embedded, between any image pairs before and after the projection onto orthonormal axes. Not only similar images generate points close to each other in the feature space, but also dissimilar ones produce feature points far apart. The above statements are logically equivalent to that distant feature points are guaranteed to map to images with dissimilar contents, while close feature points correspond to similar images. Therefore, utilizing coefficients derived from the proposed linear combination of fractal orthonormal basis as key to search image database will retrieve similar images, while at the same time exclude dissimilar ones. The coefficients associated with each image can be later used to reconstruct the original. The content-based query is performed in the compressed domain. This approach is efficient for content-based query. Scaling, rotational, translation, mirroring and horizontal/vertical flipping variations of a query image are also supported. A symbolic image database system is a system in which a large amount of image data and their related information are represented by both symbolic images and physical images. How to perceive spatial relationships among the components in a symbolic image is an important criterion to find a match between the symbolic image of the scene object and the one being store as a modal in the symbolic image database. Spatial reasoning techniques have been applied to pictorial database, in particular those using 2D strings as an index representation have been successful. In most of the previous approaches for iconic indexing, for simplifying the concerns, they apply the MBR (Minimum bounding rectangle) of two objects to define the spatial relationship between them. Multiple instance learning algorithms provide ways for computer program to improve automatically with experience. Most images are inherently ambiguous disseminators of information. Unfortunately, interfaces to image databases normally involve the user giving the system ambiguous queries. By treating each query as a Multiple-Instance example, we make the ambiguity in each image explicit. In addition, by receiving several positive and negative examples, the system can learn what the user desires. Using the learned concept, the system returns images from the database that are close to that concept. In this project, we propose to apply the Multiple-Instance learning model by deriving the projection vector of fractal orthonormal bases for a small number of training images to learn what images from database are of interest to the user.

Abstract In recent years, the domestic market has suffered shrinking domestic demands resulting from the long term poor economy. In this year, this is particularly prominent that every segment of the retail industry has rather reserved or pessimistic expectations of the economic growth for the next few years. When the performance of business enterprises and channels can no longer grow with economic growth, only through the research and implementation of successful marketing activities and channel strategies can there be an opportunity for another performance peak. In addition to developing strong capabilities in marketing planning, information application, market development, market analysis and retail management, good channel relationship and research are the most important factors of success. This study investigates the relationships between the series of activities conducted by business enterprises and channel management, and their interrelationship. It aims to provide business enterprises some decision reference in marketing and management strategy. The results of the study indicate that brand image, product, promotion pricing and service strategy have significant and positive relationship with relation marketing of the channel.

With the advent of multimedia computer, the voice and images could be stored in database. How to retrieve the information user want is a heard question. To query the large numbers of digital images which human desired is not a simple task. The studies of traditional image database retrieval use color, shape, and content to analyze a digital image, and create the index file. But they cannot promise that use the similar index files will find the similar images, and the similar images can get the similar index files. In this thesis, we propose a new method to analyze a digital image by fractal code. Fractal coding is an effective method to compress digital image. In fractal code, the image is partitioned into a set of non-overlapping range blocks, and a set of overlapping domain blocks is chosen from the same image. For all range blocks, we need to find one domain block and one iteration function such that the mapping from the domain block is similar to the range block. Two similar images have similar iterated functions, and two similar iterated functions have similar attractors. In these two reasons, we use the iteration function to create index file. We have proved fractal code can be a good index file in chapter 3. In chapter 4, we implement the fractal-based image database. In this system, we used fractal code to create index file, and used Fisher discriminate function, color, complexity, and illumination to decide the output order.

The shape construction of three-dimensional objects has numerous applications in area that include manufacturing, virtual simulation, science, medicine, and consumer marketing. In this thesis, we consider a automatic system which captures and triangulates views of a real world 3D objects and finally registers and integrates them. There are four steps in our system, image acquisition, image processing, model construction and stereoscopic display. First step, image acquisition, we take 2D image pairs (by CCD camera movement) from different angles of the model with one CCD camera. Second step, image processing. In order to derive depth form two images captured by the CCD camera, we find registration points between two images by using image segmentation, feature extraction, image registration. Third step, 3D model construction, we divide it into three parts. First part, we generate partial depth surface by Delaunay triangle splitting , and for a selected set of viewing directions. Second part of this step, different surfaces have to be mapped into a uniform coordinate system for the given 3D object. Integration of registered surfaces defines the third part of the model construction. This finally, can lead to the generation of a complete 3D model of the given scene or of the given object. After generating a complete 3D model, we create a stereoscopic view in last step. We put on the LC-Shutter-Glasses and look through the lenses at high-resolution full color display while the lenses "shutter" on and off alternatively. The monitor displays only the left view while the right lens of the glasses shutters, and display the right view while the left lens of the glasses shutters.

This thesis proposes several hardware implementation approaches for the EBCOT (Embedded Block Coding with Optimized Truncation) algorithm, one of the key operations in the emerging JPEG 2000 standard. We also modify the EBCOT algorithm in order to reduce the memory requirement and to improve the speed performance. The modified EBCOT encoder saves 40% memory area with triple speed performance compared to the original design.

With the advent of multimedia computer, the voice and images could be stored in database. How to retrieve the information user want is a heard question. To query the large numbers of digital images which human desired is not a simple task. The studies of traditional image database retrieval use color, shape, and content to analyze a digital image, and create the index file. But they cannot promise that use the similar index files will find the similar images, and the similar images can get the similar index files. In this thesis, we propose a new method to analyze a digital image by fractal code. Fractal coding is an effective method to compress digital image. In fractal code, the image is partitioned into a set of non-overlapping range blocks, and a set of overlapping domain blocks is chosen from the same image. For all range blocks, we need to find one domain block and one iteration function such that the mapping from the domain block is similar to the range block. Two similar images have similar iterated functions, and two similar iterated functions have similar attractors. In these two reasons, we use the iteration function to create index file. We have proved fractal code can be a good index file in chapter 2. In chapter 3, we implement the fractal-based image database. In this system, we used fractal code to create index file, and used Fisher discriminate function, color, complexity, and illumination to decide the output order.