The distinctive household registration (hukou or huji) system of the People’s Republic of China (PRC) divides the population into two groups whose political rights and legal status are unequal. This thesis focuses on Shanghai to examine the establishment of the hukou system in the 1950s in the course of the rural and urban reforms led by the Chinese Communist Party (CCP). Although the system has been explained as a result of the CCP’s industrialization strategy, my investigation has led me to conclude that the hukou system was an indirect rather than direct consequence of industrialization. My examination also shows that “rural” and “urban” in the PRC are essentially neither residential nor occupational categories; rather they are closely connected with political privileges. The first part of this study focuses on the consequences of the CCP’s land reform and collectivization campaigns after 1949. During this period, a large number of people who had moved freely between urban and rural areas, playing active roles in both, were uprooted from the countryside. At the same time, the CCP carried out a series of expulsions from Shanghai and other cities. Hundreds of thousands of urban residents, particularly those lacking secure employment, were removed after being labeled as “undesirable.” Thus CCP policies turned the cities and the countryside into two separate worlds. Next the dissertation outlines how the PRC state evolved after 1949, focusing on those directly maintained on the government’s payroll in Shanghai. This group was small in the beginning but soon began to expand. During the 1950s, after taking over almost all public-service institutions, the state took steps to absorb private enterprises through the policy of “public-private joint operation.” A large cohort of workers was thus added to the state payroll. Following these changes, the cities had become home mainly to employees of the party-state, together with their dependents. The state provided various benefits to its insiders. At the same time, it reduced most of the rural population to a kind of serfdom, while putting in place a set of mechanisms to secure the boundary between insiders and outsiders. / Thesis (Ph.D, History) -- Queen's University, 2012-06-27 09:01:49.88

Quasi-articulated objects, such as human beings, are among the most commonly seen objects in our daily lives. Extensive research have been dedicated to 3D shape reconstruction and motion analysis for this type of objects for decades. A major motivation is their wide applications, such as in entertainment, surveillance and health care. Most of existing studies relied on one or more regular video cameras. In recent years, commodity depth sensors have become more and more widely available. The geometric measurements delivered by the depth sensors provide significantly valuable information for these tasks. In this dissertation, we propose three algorithms for monocular pose estimation and shape reconstruction of quasi-articulated objects using a single commodity depth sensor. These three algorithms achieve shape reconstruction with increasing levels of granularity and personalization. We then further develop a method for highly detailed shape reconstruction based on our pose estimation techniques. Our first algorithm takes advantage of a motion database acquired with an active marker-based motion capture system. This method combines pose detection through nearest neighbor search with pose refinement via non-rigid point cloud registration. It is capable of accommodating different body sizes and achieves more than twice higher accuracy compared to a previous state of the art on a publicly available dataset. The above algorithm performs frame by frame estimation and therefore is less prone to tracking failure. Nonetheless, it does not guarantee temporal consistent of the both the skeletal structure and the shape and could be problematic for some applications. To address this problem, we develop a real-time model-based approach for quasi-articulated pose and 3D shape estimation based on Iterative Closest Point (ICP) principal with several novel constraints that are critical for monocular scenario. In this algorithm, we further propose a novel method for automatic body size estimation that enables its capability to accommodate different subjects. Due to the local search nature, the ICP-based method could be trapped to local minima in the case of some complex and fast motions. To address this issue, we explore the potential of using statistical model for soft point correspondences association. Towards this end, we propose a unified framework based on Gaussian Mixture Model for joint pose and shape estimation of quasi-articulated objects. This method achieves state-of-the-art performance on various publicly available datasets. Based on our pose estimation techniques, we then develop a novel framework that achieves highly detailed shape reconstruction by only requiring the user to move naturally in front of a single depth sensor. Our experiments demonstrate reconstructed shapes with rich geometric details for various subjects with different apparels. Last but not the least, we explore the applicability of our method on two real-world applications. First of all, we combine our ICP-base method with cloth simulation techniques for Virtual Try-on. Our system delivers the first promising 3D-based virtual clothing system. Secondly, we explore the possibility to extend our pose estimation algorithms to assist physical therapist to identify their patients’ movement dysfunctions that are related to injuries. Our preliminary experiments have demonstrated promising results by comparison with the gold standard active marker-based commercial system. Throughout the dissertation, we develop various state-of-the-art algorithms for pose estimation and shape reconstruction of quasi-articulated objects by leveraging the geometric information from depth sensors. We also demonstrate their great potentials for different real-world applications.

Transnational Higher Education (TNHE) post-registration top-up nursing degree programmes are relatively new in Malaysia and their impact in clinical settings is unknown. This research interprets Malaysian nurses’ experiences of such programmes and their perspectives of the extent TNHE theoretical knowledge has been applied in clinical settings. The contextual framework was established by drawing on a range of relevant dominant discourses, i.e. TNHE, nurse education, continuous professional development, theory-practice link in nursing, and culture and its influences, including coping with and adjusting to new ways of learning. Hermeneutic phenomenology and the ethnographic principle of cultural interpretation were used to explore the views of eighteen Malaysian nurses from two UK and one Australian TNHE universities (determined by convenience and snowball sampling methods) to enable data saturation. Semi-structured interviews were conducted to enable the nurses’ voices to define, describe and evaluate their TNHE experiences that were focused on personal and professional development, implementation and reaction of others towards change. In addition to the interviews, three threads of my own personal, professional and researcher experiences were reflected upon, to provide the contextual lens to shape the research process and situate the work firmly in the practice context. Data was analysed using thematic analysis. Four pre-determined key areas drawn from the literature were investigated and eight new sub-themes emerged. Findings indicated nurses’ improved self-confidence, knowledge, questioning skills and professionalism. The extent to which TNHE theory was applied in clinical practice was unable to be determined due to conflicting perceptions, contradicting views and restricted number of nurse-led examples. The main contribution this thesis offers to practice is what the voices of nurses tell about their experiences in TNHE programmes and in applying the taught theory in clinical settings. This study indicates enhanced application of theoretical knowledge in practice for improved quality and culturally competent patient care is unlikely to occur under current TNHE arrangements. Nurses’ motives for enrolling were mainly to obtain the high status western degree and the extrinsic benefits of a financial incentive and promotion. However, drawing on their resilience, nurses developed self and professional perspective transformation. The research provides new insights to inform continuous professional education policy for nurses, employers and the Malaysian Nursing Board, and can assist TNHE provider institutions to improve their programme delivery.

Abstract available in pdf file.

Filtering is a key step in digital image processing and analysis. It is mainly used for amplification or attenuation of some frequencies depending on the nature of the application. Filtering can either be performed in the spatial domain or in a transformed domain. The selection of the filtering method, filtering domain, and the filter parameters are often driven by the properties of the underlying image. This thesis presents three different kinds of biomedical image filtering applications, where the filter parameters are automatically determined from the underlying images. Filtering can be used for image enhancement. We present a robust image dependent filtering method for intensity inhomogeneity correction of biomedical images. In the presented filtering method, the filter parameters are automatically determined from the grey-weighted distance transform of the magnitude spectrum. An evaluation shows that the filter provides an accurate estimate of intensity inhomogeneity. Filtering can also be used for analysis. The thesis presents a filtering method for heart localization and robust signal detection from video recordings of rat embryos. It presents a strategy to decouple motion artifacts produced by the non-rigid embryonic boundary from the heart. The method also filters out noise and the trend term with the help of empirical mode decomposition. Again, all the filter parameters are determined automatically based on the underlying signal. Transforming the geometry of one image to fit that of another one, so called image registration, can be seen as a filtering operation of the image geometry. To assess the progression of eye disorder, registration between temporal images is often required to determine the movement and development of the blood vessels in the eye. We present a robust method for retinal image registration. The method is based on particle swarm optimization, where the swarm searches for optimal registration parameters based on the direction of its cognitive and social components. An evaluation of the proposed method shows that the method is less susceptible to becoming trapped in local minima than previous methods. With these thesis contributions, we have augmented the filter toolbox for image analysis with methods that adjust to the data at hand.

Non-rigid shapes are generally known as objects whose three dimensional geometry may deform by internal and/or external forces. Deformable shapes are all around us, ranging from protein molecules, to natural objects such as the trees in the forest or the fruits in our gardens, and even human bodies. Two deformable shapes may be related by isometry, which means their intrinsic geometries are preserved, even though their extrinsic geometries are dissimilar. An important problem in the analysis of the deformable shapes is to identify the three-dimensional correspondence between two isometric shapes, given that the two shapes may be deviated from isometry by intrinsic distortions. A major challenge is that non-rigid shapes have large degrees of freedom on how to deform. Nevertheless, irrespective of how they are deformed, they may be aligned such that the geodesic distance between two arbitrary points on two shapes are nearly equal. Such alignment may be expressed by a permutation matrix (a matrix with binary entries) that corresponds to every paired geodesic distance in between the two shapes. The alignment involves searching the space over all possible mappings (that is all the permutations) to locate the one that minimizes the amount of deviation from isometry. A brute-force search to locate the correspondence is not computationally feasible. This thesis introduces a novel approach created to locate such correspondences, in spite of the large solution space that encompasses all possible mappings and the presence of intrinsic distortion. In order to find correspondences between two shapes, the first step is to create a suitable descriptor to accurately describe the deformable shapes. To this end, we developed deformation-invariant metric descriptors. A descriptor constitutes pair-wise geodesic distances among arbitrary number of discrete points that represent the topology of the non-rigid shape. Our descriptor provides isometric-invariant representation of the shape irrespective of its circumstantial deformation. Two isometric-invariant descriptors, representing two candidate deformable shapes, are the input parameters to our optimization algorithm. We then proceed to locate the permutation matrix that aligns the two descriptors, that minimizes the deviation from isometry. Once we have developed such a descriptor, we turn our attention to finding correspondences between non deformable shapes. In this study, we investigate the use of both classical and quantum particle swarm optimization (PSO) algorithms for this task. To explore the merits of variants of PSO, integer optimization involving test functions with large dimensions were performed, and the results and the analysis suggest that quantum PSO is more effective optimization method than its classical PSO counterpart. Further, a scheme is proposed to structure the solution space, composed of permutation matrices, in lexicographic ordering. The search in the solution space is accordingly simplified to integer optimization to find the integer rank of the targeted permutation matrix. Empirical results suggest that this scheme improves the scalability of quantum PSO across large solution spaces. Yet, quantum PSO's global search capability requires assistance in order to more effectively manoeuvre through the local extrema prevalent in the large solution spaces. A mutation based genetic algorithm (GA) is employed to augment the search diversity of quantum PSO when/if the swarm stagnates among the local extrema. The mutation based GA instantly disengages the optimization engine from the local extrema in order to reorient the optimization energy to the trajectories that steer to the global extrema, or the targeted permutation matrix. Our resultant optimization algorithm combines quantum Particle Swarm Optimization (PSO) and mutation based Genetic Algorithm (GA). Empirical results show that the optimization method presented is scalable and efficient on standard hardware across different solution space sizes. The performance of the optimization method, in simulations and on various near-isometric shapes, is discussed. In all cases investigated, the method could successfully identify the correspondence among the non-rigid deformable shapes that were related by isometry.

In this dissertation, the development and performance evaluation of new techniques for image registration and image geometric normalization, which are based on feature points extracted from images are investigated. A feature point extraction method based on scale-interaction of Mexican-hat wavelets is proposed. This feature point extractor can handle images of different scales by using a range of scaling factors for the Mexican-hat wavelet leading to feature points for different scaling factors. Experimental results show that the extracted feature points are invariant to image rotation and translation, and are robust to image degradations such as blurring, noise contamination, brightness change, etc. Further, the proposed feature extractor can handle images with scale change efficiently. A new algorithm is proposed for registration of geometrically distorted images, which may have partial overlap and may have undergone additional degradations. The global 2D affine transformations are considered in the registration process. Three main steps constitute the algorithm: extracting feature point using a feature point extractor based on scale-interaction of Mexican-hat wavelets, obtaining the correspondence between the feature points of the reference and the target images using Zernike moments of neighborhoods centered on the feature points, and estimating the transformation parameters between the first and the second images using an iterative weighted least squares algorithm. Experimental results show that the proposed algorithm leads to excellent registration accuracy using several types of images, even in cases with partial overlap between images. Further, it is robust against many image degradations and it can handle images of different scales effectively. A new technique for image geometric normalization is proposed. The locations of a set of feature points, extracted from the image, are used to obtain the normalization parameters needed to normalize the image. The geometric distortions considered in the proposed normalization technique include translation, rotation, and scaling. Experimental results show that the proposed technique yields good normalization accuracy and it is robust to many image degradations such as image compression, brightness change, noise contamination and image cropping. A blind watermarking technique for images is proposed, as an example of the possible applications of the presented geometric normalization technique. In order to enhance robustness of the watermarking technique to geometric distortions, the normalization technique is used to normalize the image, to be watermarked, during the embedding process. In the watermark detection stage, the normalization parameters for the possibly distorted watermarked image are obtained and used to transform the watermark into its normalized form. The transformed watermark is, then, correlated with the image to indicate whether the watermark is present in the image or not. Experimental results show that the proposed watermarking technique achieves good robustness to geometric distortions that include image translation, rotation, and scaling.

In 1982 the governments of Honduras and the United States signed a contract that established the Proyecto de Titulación de Tierras, or land titling project. This project was initiated primarily to provide titles to small coffee farmers on State-owned land. Among the expected consequences of the project were increased access to resources, especially credit, for small farmers and increased on-farm investment due to this access to credit and increased security. It was hoped that a greater use of credit and investment would increase farm production and therefore the income and well-being of the farmers involved. In this dissertation, the land titling project is placed within the context of the history of agrarian reform in Honduras. The titling project called for a baseline study and final evaluation. These were carried out in 1983 and 1988, respectively. The author was able to obtain these data and re-interview the same farmers in 1993. These farmers are from two regions, one of which was titled and another which was not. The interviews gathered data on production, credit, use of inputs, investments, income and general socio-economic indicators. These data are used to determine the extent to which the goals of the tiding project have been met. A stochastic frontier production function is used to estimate farm-level technical efficiency. Following this, these technical efficiency scores are regressed on various factors such as education, credit and technical assistance to estimate their possible effects on technical efficiency. Finally, simultaneous equations are used to estimate the relationships among these variables. In general, ten years after the start of the project, the original goals have not been achieved. This analysis found that titling does not affect technical efficiency, access to credit, or the use of inputs. Education and technical assistance are the two factors that are consistently the most significant in meeting the project's stated goals. This analysis suggests that basic education and technical assistance, rather than expensive land titling projects, should be promoted to enhance access to credit, the use of inputs and increased technical efficiency.

The term E-health - describes the use of information and IT, to satisfy needs of citizens, patients, and healthcare specialists, providers of healthcare services, managers and politics. Development of e-health structure and the use of patient healthcare services just in the beginning in Lithuania, so there is a need of work and solutions are made in this direction. The object of research – the spreading of e-health services, development and management solutions of healthcare institutions. The purpose is to investigate problems of management, describe the changes in e-healthcare development process. The second aim to investigate diffusion of e-health services in Lithuania and compare with situation in the world.

The study is about the foundation and registration procedures of legal entities. The author compares Lithuanian procedures with the proceduresof various different countries. Also the historical base of foundation procedures in Lithuania are described. The study is finished with detail analysis of different forms of legal entities in Lithuania.