With the dominance of service industry and the membership of WTO for Taiwan, the farming and fishing industries are facing fierce competition from globalization. Traditional agricultural society has thus largely perished, its population aged and young people moving to cities, productivity being low. Farming and fishing industries are no longer able to support livelihood of local communities. It is highly trumpeted for these industries to be transformed to leisure-purposed farming and fishing. Tourism is now almost seen as a panacea for the future. However, there are many problems. The current study uses a ¡¥mediocre¡¦ case of Shi-Tsao area of Tainan as an example, to study the normal pattern of development of traditional communities into tourism destinations. The research focuses on the issues that this area has faced, the ecological functions and environmental attributes of its coastal area, including the carrying capacity; an environmental analysis of the community is also executed. Adopting a qualitative approach, the research is based on in-depth interviews, literature evidence, and a case study of Tao-Mi Community. The purpose is to study the issues that Shi-Tsao faces during its transit to a new industry. SWOT analysis is used, and cross-analyses of the Strength, Weakness, Opportunity and Threat are executed to find out the priorities of the related issues. Suggestions are given as how to make the transition more smooth and plausible. The ultimate purpose is to help understand the whole situation that Taiwanese rural area faces nowadays. The conclusions include issues in ecology, land use, investment and professional planning from outside and legal problems; it is also found that social and political issues such as resource distributions and partisan are detrimental to development.

This thesis studies the operating characteristics of lead acid batteries with the intermittent discharging current. Rest time is added periodically on purpose during the battery discharging to observe its impact on the releasable capacity. From the experimental results that take the frequency and the duty-ratio as two variables, batteries with the intermittent discharging at high frequencies or low duty ratios can release more capacity. The results also indicate that the depth of discharge (DOD) affects the intermittent discharging. More capacity is released while approaching the end of the discharging, whereas no clear difference is found in the beginning. Last but not least, the average current is proved experimentally to play a significant role in current discharging. With the same average current, the maximum capacity obtained from the intermittent current discharging is close to that from the constant current discharging.

The studies of tidal current and sea level variation in the Taiwan Strait are popular topics in recent years. The sea level data, to be applied to data analysis or model forcing and validation, are mostly observed in the near shore region. It is relative not easier to obtain real tidal data in the offshore area. This study intended to obtain sea level data within Taiwan Strait, using in-situ water depth measurements collected by EK500 of research vessels OR1, OR2 and OR3 during 1989-2003. The basic assumption of this work is that the changes of sea level and topographical depth equal to observed water depth. By using a large set of field measurements, it is possible to get bottom topography such that tidal data can be extracted by harmonic analysis of long-term discrete time series of water depth data. A total of 1513 cruises of water depth data were collected, which account for nearly 6 million samples. These data were screened through a series of criteria for quality control. Firstly, data were plotted cruise by cruise ( longitude vs latitude , longitude vs depth , time vs depth), then reasonable range of time, depth and region were choosed manually. Second, outliers, defined as values greater than 3 standard deviations on 5 point moving mean along the cruise track (or time), were replaced by linear interpolation values. Finally, a 2-minute moving average was applied to the along track time series water depth data. This step was trying to remove the effect of surface waves. The original huge records were reduced to about 550,000 valuable samples for the 1513 cruises data. According to the density distribution of water depth samples in Taiwan Strait, 32 sub-region were selected for topography and harmonic analyses. In each sub-region, the bottom topography was mapped by an optimal interpolation method through a Gaussian weighting function. The radius of Gaussian weighting function applied is 3 time of the distance of grid. Water depth samples subtracted topographical depth of nearby grid to form a set of sea level data ready for harmonic analysis. The phase and amplitude of semi-diurnal tides (M2) and diurnal tides (K1¡BO1) in each sub-region were computed for the 32 regions in Taiwan Strait. The water depth measurements derived sea level variations were compatible with that of a global tidal model (OSU) and a set of moored long-term pressure records in the middle of the strait. Especially, the tidal phase among these results were quite close. However, the tidal amplitudes of water depth data derived were smaller. Sensitivity analysis showed that the errors, differences between OSU model and depth derived sea levels, were small with regions of high density of water depth measurements. Both harmonic derived sea level variations and OSU model predictions indicated a southward propagating tidal wave, which matched with the scenario of Kevin wave propagation in Taiwan Strait. Our analysis also showed that the sea level variations in the northern part of the strait were dominated by M2 and K1 components while the southern part of the strait were dominated by M2 and O1 components.

The Cheng Ching Lake is a reservoir. It functions not only as a water supplier, but also as a scenic spot. It used to be one of the top three scenic spots in Taiwan. However, it has gradually lost its competitiveness with environmental change. And its tourists has also decreased with year, which has resulted in deficits of earning and prosperity. This study probes into the competitive advantage of the Cheng Ching Lake scenic spot according to the Resource-Based Theory. The unique competitiveness of general enterprises comes from two complementary sources-- the resources and the competencies in the enterprises. Since it is easier for an enterprise to control and manage its resources and competencies, the two factors are more suitable being as references and indicators for a company to decide on its tactics of development. Therefore, an enterprise should make good use of its resources in advantage and even its core resources in order to make profits and maintain its substainable competitive advantage. This thesis adopted qualitative methods and conducted in-depth interviews with the administrator of the Cheng Ching Lake scenic spot, superiors in authorities concerned, scholars, and experts. After discussing with them the effects that tangible assets, intangible assets, human resources and capabilities have on competitive advantage, the results¡GThe core resource of the Cheng Ching Lake scenic spot is ¡§its water resource and ecology¡¨ that is unique, specific, and imperfectly imitable, which shape the Cheng Ching Lake¡¦s competitiveness. As for the core competence, the management ability, age, quality, professional training, adjustment ability of its employees lack in competitiveness, the Cheng Ching Lake scenic spot does not have core competence . Based on the above findings, this study gets some suggest to development strategies for the Cheng Ching Lake senic spot as follows: 1.Using the differentiation to separate the market. 2.Selecting a specific theme for further development. 3.Modifying after a whole plan, and to run the business with each section separated for different usage. 4.Adopting alliance strategy to promote its competitiveness. 5.Collecting cleaning fees from people doing morning exercise to compensate for the loss in profits.

A method using a phase mask to extend the depth of field for an incoherent lens system is presented. This phase mask is designed to generate a point spread function in which the intensity distribution is invariant to misfocus. Thus, image could be retrieved by de-convoluting the misfocused one. Its application to 3D profile sensing using point white light illumination is presented as well. A fringe pattern is projected onto the inspected surface using the point white light source. Fringe distribution is then observed by a CCD camera through the presented phase mask at a different viewpoint. Phase can be extracted by the Fourier transform method or the phase-shifting technique. With triangulation methods or proper calibration approaches, depth information can be identified from the phase of the fringes. The phase mask enlarges the depth of field of the image acquisition system, while the point white light illumination increases the depth of focus of the fringe projection system. Thus, a highly accurate, non-scanning projected fringe profilometer with large depth measuring range can be realized.

Thesis (Ph. D.)--University of Washington, 2001. / Vita. Includes bibliographical references (leaves 242-249).

The objective of this Thesis research is to develop algorithms for temporally consistent semantic segmentation in videos. Though many different forms of semantic segmentations exist, this research is focused on the problem of temporally-consistent holistic scene understanding in outdoor videos. Holistic scene understanding requires an understanding of many individual aspects of the scene including 3D layout, objects present, occlusion boundaries, and depth. Such a description of a dynamic scene would be useful for many robotic applications including object reasoning, 3D perception, video analysis, video coding, segmentation, navigation and activity recognition. Scene understanding has been studied with great success for still images. However, scene understanding in videos requires additional approaches to account for the temporal variation, dynamic information, and exploiting causality. As a first step, image-based scene understanding methods can be directly applied to individual video frames to generate a description of the scene. However, these methods do not exploit temporal information across neighboring frames. Further, lacking temporal consistency, image-based methods can result in temporally-inconsistent labels across frames. This inconsistency can impact performance, as scene labels suddenly change between frames. The objective of our this study is to develop temporally consistent scene descriptive algorithms by processing videos efficiently, exploiting causality and data-redundancy, and cater for scene dynamics. Specifically, we achieve our research objectives by (1) extracting geometric context from videos to give broad 3D structure of the scene with all objects present, (2) Detecting occlusion boundaries in videos due to depth discontinuity, (3) Estimating depth in videos by combining monocular and motion features with semantic features and occlusion boundaries.

Traditional computer vision algorithms depend on information taken by visible-light cameras. But there are inherent limitations of this data source, e.g. they are sensitive to illumination changes, occlusions and background clutter. Range sensors give us 3D structural information of the scene and it’s robust to the change of color and illumination. In this thesis, we present a series of approaches which are developed using the depth information by Kinect to address the issues regarding human detection and action recognition. Taking the depth information, the basic problem we consider is to detect humans in the scene. We propose a model based approach, which is comprised of a 2D head contour detector and a 3D head surface detector. We propose a segmentation scheme to segment the human from the surroundings based on the detection point and extract the whole body of the subject. We also explore the tracking algorithm based on our detection result. The methods are tested on a dataset we collected and present superior results over the existing algorithms. With the detection result, we further studied on recognizing their actions. We present a novel approach for human action recognition with histograms of 3D joint locations (HOJ3D) as a compact representation of postures. We extract the 3D skeletal joint locations from Kinect depth maps using Shotton et al.’s method. The HOJ3D computed from the action depth sequences are reprojected using LDA and then clustered into k posture visual words, which represent the prototypical poses of actions. The temporal evolutions of those visual words are modeled by discrete hidden Markov models (HMMs). In addition, due to the design of our spherical coordinate system and the robust 3D skeleton estimation from Kinect, our method demonstrates significant view invariance on our 3D action dataset. Our dataset is composed of 200 3D sequences of 10 indoor activities performed by 10 individuals in varied views. Our method is real-time and achieves superior results on the challenging 3D action dataset. We also tested our algorithm on the MSR Action3D dataset and our algorithm outperforms existing algorithm on most of the cases. / text

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Vacuum arc remelting is a secondary melting process used to produce a variety of segregation sensitive and reactive metal alloys. The present day VAR practice for superalloys involves, typically, melting electrodes of 17'' into ingots of 20'' in diameter. Even larger diameter forging stock is desirable. However, beyond 20'' ingots of superalloys are increasingly prone to segregation defects if solidification is not adequately controlled. In the past years a new generation of model-based controllers was developed to prevent segregation in VAR by controlling melt rate, or the total amount of power flowing into the liquid pool. These controllers were seen as significant improvements in the industry of remelting processes, but these controllers were still focusing on the melting sub-process and ignoring ingot solidification. Accurate control of the liquid pool profile is expected to result in segregation-free ingots, but unfortunately a controller capable of stabilizing the solidification front in VAR is currently not available. The goal of the proposed research is to develop a cyber-enabled controller for VAR pool depth control that will enhance the capabilities of current technologies. More specifically, the objectives of this research are threefold. Firstly, a control-friendly model is proposed based on a high-fidelity ingot solidification model and is coupled to a thermal model of electrode melting. Secondly, sequential Monte Carlo estimators are proposed to replace the traditional Kalman filter, used in the previous VAR controllers. And finally, a model predictive controller (MPC) is designed based on the proposed reduced-order model. The time-critical characteristics of these methods are studied, and the feasibility of their real-time implementation is reported. / text