No description available.

Purpose/aim The aim is to examine the distribution of hotel ownerships and star-rated levels in different regions. This thesis depends on the analysis of the examination to find out if the change of investment behaviors can decrease or avoid the adverse effects of bureaucracy in the Chinese hotel industry. Design/methodology/approach Data has been collected through the third-party electronic distribution channel. The analysis includes a description of the samples and statistical tests. Findings The analysis showed that there is a connection between hotel ownerships, star-rated levels, and different regions. The adverse effects of bureaucracy in the second-tier cities and third-tier cities are stronger than that in the first-tier cities and tourist cities. The state-owned hotels also can do the enterprise transformation in the tourist cities to avoid or decrease the adverse effects of the bureaucracy. Originality/value The original idea is using the hotel ownerships distribution in different regions to find out the different levels of adverse effects of the bureaucracy in different regions. This thesis should be a meaningful contribution to knowledge development.

En aquesta tesi s'estudien els mètodes de codificació d'imatges i seqüències de vídeo des del punt de vista de la forma en què el sistema visual humà percep i entén la informació visual. La rellevància d'aquest estudi ve donada pel paper tan important que tenen els senyals d'imatge en la civilització actual i pel gran volum de dades que representen les fonts d'informació visual pels sistemes que les han de processar. S'han estudiat tres aproximacions per a la codificació de textures en un esquema avançat de compressió fonamentat en aspectes de percepció visual. La primera aproximació es basa en les transicions de la imatge i estudia la interpolació d'àrees suaus a partir de les esmentades transicions. La segona contempla l'extracció, selecció i codificació de detalls significatius per al sistema visual humà. Finalment, la tercera aproximació estudia la representació eficient de les textures fines i homogènies, que donen una aparença natural a les imatges sintetitzades aconseguint elevades tasses de compressió. Per a l'aplicació d'aquestes tècniques a la codificació d'imatge i vídeo, es proposa un model d'imatge de tres components adaptat a les característiques perceptuals de la visió humana.Les aproximacions de codificació objecte de l'estudi han portat al disseny de tècniques noves d'anàlisi i codificació d'imatge. A partir d'eines no lineals de tractament obtingudes de l'entorn de la Morfologia Matemàtica, s'han desenvolupat tres tècniques de codificació de textures. En concret,- Un mètode d'interpolació "morfològica" orientat a la resolució del problema d'interpolació de senyals bidimensionals a partir de conjunts arbitraris de punts dispersos.- S'ha introduït de manera experimental un criteri subjectiu empíric per a la ordenació i selecció de detalls en les imatges, segons un criteri perceptual.- Finalment, s'ha investigat l'aplicació d'una tècnica clàssica, la codificació "subbanda", a l'interior de regions de forma arbitrària, resultant en un nou mètode de codificació de textures anomenat "Region-based subband coding".Aquestes tècniques han estat innovadores en el camp de codificació d'imatge entre les anomenades tècniques orientades a objectes o de Segona Generació. Tanmateix, el model d'imatge estudiat, es troba en la línia de les últimes propostes en l'entorn de l'MPEG4, el futur estàndard per a comunicació d'imatge a baixa velocitat, que contempla la possibilitat de la manipulació de continguts. / This thesis studies image and video sequence coding methods from the point of view of the way the human visual system perceives and understands visual information. The relevance of such study is due, on the one hand, to the important role that visual signals have in our civilization and, on the other hand, to the problem of representing the large amount of data that image and video processing systems have to deal with.Three different approaches have been investigated for the coding of image textures in an advanced compression scheme relying in aspects of visual perception. The first approach is based on image transitions and the interpolation of smooth areas from such transitions. The second one, considers the extraction, selection and coding of meaningful image details.Finally, the third approach studies the efficient representation of homogeneous fine textures that give a natural appearance to the reconstructed images at high compression levels. In order to apply these techniques for still image and video coding, a three component model of the image, that matches the perceptual properties of the human vision, is put forward.The coding approaches subject of research have leaded to the design of three new image analysis and coding techniques. Using non-linear tools from the framework of Mathematical Morphology, three texture coding techniques are developed. In particular,- A "morphological" image interpolation method aimed at the problem of scattered data interpolation.- An empirical subjective criterion for the ranking and selection of image details according to visual perception.- The application of a conventional image coding technique, subband coding, to the coding of arbitrarily shaped image regions (region-based subband coding).These are new texture coding techniques in the field of object-oriented and Second Generation image and video coding schemes. Furthermore, the model of the image that has been investigated follows the line of the last proposals in the framework of MPEG4, the forthcoming coding standard for low bit-rate visual communications, which considers the possibility of content-based manipulation and coding of visual information.

The early detection of prostate cancer plays a significant role in the success of treatment and outcome. To detect prostate cancer, imaging modalities such as TransRectal UltraSound (TRUS) and Magnetic Resonance Imaging (MRI) are relied on. MRI images are more comprehensible than TRUS images which are corrupted by noise such as speckles and shadowing. However, MRI screening is costly, often unavailable in many community hospitals, time consuming, and requires more patient preparation time. Therefore, TRUS is more popular for screening and biopsy guidance for prostate cancer. For these reasons, TRUS images are chosen in this research. Radiologists first segment the prostate image from ultrasound image and then identify the hypoechoic regions which are more likely to exhibit cancer and should be considered for biopsy. In this thesis, the focus is on prostate segmentation and on Regions of Interest (ROI)segmentation. First, the extraneous tissues surrounding the prostate gland are eliminated. Consequently, the process of detecting the cancerous regions is focused on the prostate gland only. Thus, the diagnosing process is significantly shortened. Also, segmentation techniques such as thresholding, region growing, classification, clustering, Markov random field models, artificial neural networks (ANNs), atlas-guided, and deformable models are investigated. In this dissertation, the deformable model technique is selected because it is capable of segmenting difficult images such as ultrasound images. Deformable models are classified as either parametric or geometric deformable models. For the prostate segmentation, one of the parametric deformable models, Gradient Vector Flow (GVF) deformable contour, is adopted because it is capable of segmenting the prostate gland, even if the initial contour is not close to the prostate boundary. The manual segmentation of ultrasound images not only consumes much time and effort, but also leads to operator-dependent results. Therefore, a fully automatic prostate segmentation algorithm is proposed based on knowledge-based rules. The new algorithm results are evaluated with respect to their manual outlining by using distance-based and area-based metrics. Also, the novel technique is compared with two well-known semi-automatic algorithms to illustrate its superiority. With hypothesis testing, the proposed algorithm is statistically superior to the other two algorithms. The newly developed algorithm is operator-independent and capable of accurately segmenting a prostate gland with any shape and orientation from the ultrasound image. The focus of the second part of the research is to locate the regions which are more prone to cancer. Although the parametric dynamic contour technique can readily segment a single region, it is not conducive for segmenting multiple regions, as required in the regions of interest (ROI) segmentation part. Since the number of regions is not known beforehand, the problem is stated as 3D one by using level set approach to handle the topology changes such as splitting and merging the contours. For the proposed ROI segmentation algorithm, one of the geometric deformable models, active contours without edges, is used. This technique is capable of segmenting the regions with either weak edges, or even, no edges at all. The results of the proposed ROI segmentation algorithm are compared with those of the two experts' manual marking. The results are also compared with the common regions manually marked by both experts and with the total regions marked by either expert. The proposed ROI segmentation algorithm is also evaluated by using region-based and pixel-based strategies. The evaluation results indicate that the proposed algorithm produces similar results to those of the experts' manual markings, but with the added advantages of being fast and reliable. This novel algorithm also detects some regions that have been missed by one expert but confirmed by the other. In conclusion, the two newly devised algorithms can assist experts in segmenting the prostate image and detecting the suspicious abnormal regions that should be considered for biopsy. This leads to the reduction the number of biopsies, early detection of the diseased regions, proper management, and possible reduction of death related to prostate cancer.

The early detection of prostate cancer plays a significant role in the success of treatment and outcome. To detect prostate cancer, imaging modalities such as TransRectal UltraSound (TRUS) and Magnetic Resonance Imaging (MRI) are relied on. MRI images are more comprehensible than TRUS images which are corrupted by noise such as speckles and shadowing. However, MRI screening is costly, often unavailable in many community hospitals, time consuming, and requires more patient preparation time. Therefore, TRUS is more popular for screening and biopsy guidance for prostate cancer. For these reasons, TRUS images are chosen in this research. Radiologists first segment the prostate image from ultrasound image and then identify the hypoechoic regions which are more likely to exhibit cancer and should be considered for biopsy. In this thesis, the focus is on prostate segmentation and on Regions of Interest (ROI)segmentation. First, the extraneous tissues surrounding the prostate gland are eliminated. Consequently, the process of detecting the cancerous regions is focused on the prostate gland only. Thus, the diagnosing process is significantly shortened. Also, segmentation techniques such as thresholding, region growing, classification, clustering, Markov random field models, artificial neural networks (ANNs), atlas-guided, and deformable models are investigated. In this dissertation, the deformable model technique is selected because it is capable of segmenting difficult images such as ultrasound images. Deformable models are classified as either parametric or geometric deformable models. For the prostate segmentation, one of the parametric deformable models, Gradient Vector Flow (GVF) deformable contour, is adopted because it is capable of segmenting the prostate gland, even if the initial contour is not close to the prostate boundary. The manual segmentation of ultrasound images not only consumes much time and effort, but also leads to operator-dependent results. Therefore, a fully automatic prostate segmentation algorithm is proposed based on knowledge-based rules. The new algorithm results are evaluated with respect to their manual outlining by using distance-based and area-based metrics. Also, the novel technique is compared with two well-known semi-automatic algorithms to illustrate its superiority. With hypothesis testing, the proposed algorithm is statistically superior to the other two algorithms. The newly developed algorithm is operator-independent and capable of accurately segmenting a prostate gland with any shape and orientation from the ultrasound image. The focus of the second part of the research is to locate the regions which are more prone to cancer. Although the parametric dynamic contour technique can readily segment a single region, it is not conducive for segmenting multiple regions, as required in the regions of interest (ROI) segmentation part. Since the number of regions is not known beforehand, the problem is stated as 3D one by using level set approach to handle the topology changes such as splitting and merging the contours. For the proposed ROI segmentation algorithm, one of the geometric deformable models, active contours without edges, is used. This technique is capable of segmenting the regions with either weak edges, or even, no edges at all. The results of the proposed ROI segmentation algorithm are compared with those of the two experts' manual marking. The results are also compared with the common regions manually marked by both experts and with the total regions marked by either expert. The proposed ROI segmentation algorithm is also evaluated by using region-based and pixel-based strategies. The evaluation results indicate that the proposed algorithm produces similar results to those of the experts' manual markings, but with the added advantages of being fast and reliable. This novel algorithm also detects some regions that have been missed by one expert but confirmed by the other. In conclusion, the two newly devised algorithms can assist experts in segmenting the prostate image and detecting the suspicious abnormal regions that should be considered for biopsy. This leads to the reduction the number of biopsies, early detection of the diseased regions, proper management, and possible reduction of death related to prostate cancer.

In 1944, the Government of Saskatchewan created the Northern Administrative District (NAD), which established Northern Saskatchewan as a spatial entity within the provincial milieu. Attention was focused on modernizing the region, and public health nursing became one of the first state-sponsored institutions to be introduced by the provincial government. By examining the day-to-day activities of nurses who worked at remote nursing outposts in Northern Saskatchewan between 1944 and 1957 and beyond, this research examines the complex internal factors involved in region-making. Nurses lived and worked amongst their patients in small remote communities, thus making them effective vehicles for promoting modernization principles through preventative and educations programs. Despite the governments intention to modernize Northern Saskatchewan, a colonial relationship emerged between the region and the rest of the province. This situation left nurses in a confusing and often difficult position, because the institution behind initiatives to modernize the region was also their employer to whom they had certain obligations. Furthermore, the colonial attitude towards the region also extended to the nursing stations and the nurses, which often frustrated their attempts to provide medical care. As such, the small cadre of nurses played an ambiguous role, both as agents of modernization, but also opponents of its egregious effects.<p> The research examines the role of nursing in region-making through two types of geography: A geography of region-making where the literature focuses on the formal process of institutionalization, and a geography of social life, where the emerging literature on the geography of nursing provides an entry point. This two-part approach provides an opportunity to use different lenses to view the processes involved in shaping Northern Saskatchewan as it emerged as a distinct northern place within Canada.

The report is aimed to stress the support of start-up businesses that exists in the environment of cluster regions. The author will introduce the reader to the conceptions of cluster regions and different shapes of social capital. The empirical study is based on two specific networks operating in two cluster areas – contributing with a broader aspect of the conception of integration. The districts are the region of Gnosjö in southern Sweden and Silicon Valley in southern San Francisco, USA. The author explore relationships between actors within the two networks and highlight two different approaches the networks use dealing with different perspectives as supporting start-up businesses. She emphasizes the importance of nurturing relations in the regional environment, with stand in natural routines and informal meetings. This will be illustrated through examples of intimate interaction in Gnosjöandan and Silicon Valley, through a perspective of regional advantage, facing global markets. The analysis is based on theoretical support with foundation in several themes of conditions for a start-up business to establish on the market. With basis in theoretical frameworks and empirical facts the report has generated an interesting argumentation of critical conditions for establishment of start-up businesses. The discussion is based on different perspectives due to the dissimilar cases used in the study. Consequently, start-up conditions, generated in cluster atmospheres, are highlighted through three interesting aspects.

The history of Taiwan has formed the developed structure of Taiwan cities, policies of industry development caused the main markets focusing in north Taiwan, generating the problem of uneven development between regions. This article adopts ¡§New Economic Geography¡¨ proposed by Krugman to discuss the differences between north region and south region in Taiwan. Moreover, this article extends the issue to real estate market and researches the influence of industrial clusters, transportation construction, labor market and migration of employed population. The empirical results indicate that money supply, industrial cluster and the construction of transportation will affect the development of regional house prices.

Effects of globalization transform the forms of relations between settlements and it also changed the relations between capital and labor. In this global era performances of individual settlements became crucial in the absence of old hierarchic boundaries. But individual performances of settlements are not enough to integrate the global system. A New type of spatial organization appeared which is called networking to enhance complementary and cooperative relations crucial for synergy. The spatial reflexions of this transformation process are city regions. This study aims to determine the factors affecting economic performance and networking patterns of settlements in Antalya Region with the use of quantitative research methods.

In this thesis, an LMI-based pole-clustering characterization for descriptor systems is investigated. A necessary and sufficient condition for checking simultaneously the regularity, impulse immunity, and finite eigenvalues locating in the generalized LMI regions is derived. Since uncertainty exists inevitably in control systems, we propose two sufficient conditions to guarantee the robust pole clustering in the generalized LMI regions for uncertain descriptor systems with two types of uncertainties, i.e. the norm bounded uncertainty and the convex polytopic uncertainty. The LMI-based state feedback controller design methods are developed as well. Finally, the validity and the feasibility of our theoretical results are verified by the numerical simulation results of several examples.