The all-atom protein backbone reconstruction problem (PBRP) is to reconstruct the 3D coordinates of all atoms, including N, C, and O atoms on the backbone, for a protein whose primary sequence and £\-carbon coordinates are given. A variety of methods for solving PBRP have been proposed, such as Adcock¡¦s method, SABBAC, BBQ, Chang¡¦s and Yen¡¦s methods. In a recent work, Yen et al. found that the results of Chang¡¦s method are not always better than SABBAC. So they apply a tool preference classification to determine which tool is more suitable for predicting the structure of the given protein. In this thesis, we involve BBQ (Backbone Building from Quadrilaterals) and Chang¡¦s method as our candidate prediction tools. In addition, the tool preferences of different atoms (N, C, O) are determined separately. We call the preference classification as an atom classifier, which is built by support vector machine (SVM). According to the preference classification of each atom classifier, a proper prediction tool, either BBQ or Chang¡¦s method, is used to construct the atom of the target protein. Thus, the combination of all atom results, the backbone structure of a protein is reconstructed. The datasets of our experiments are extracted from CASP7, CASP8, and CASP9, which consists of 30, 24, and 55 proteins, respectively. The proteins of the datasets contain only standard amino acids. We improve the average RMSDs of Yen¡¦s results from 0.4019 to 0.3682 in CASP7, from 0.4543 to 0.4202 in CASP8, and from 0.4155 to 0.3601 in CASP9.

Abstract This thesis describes position-sensitive devices (PSDs) and optical sensor systems suitable for industrial tracking and displacement sensing applications. The main application areas of the proposed sensors include automatic pointing of a rangefinder beam and measuring the lateral displacement of an object. A conventional tracking sensor is composed of a laser illuminator, a misfocused quadrant detector (QD) receiver and a corner cube retroreflector (CCR) attached to the target. The angular displacement of a target from the receiver optical axis is detected by illuminating the target and determining the direction of the reflection using the QD receiver. The main contribution of the thesis is related to the modifications proposed for this conventional construction in order to make its performance sufficient for industrial applications that require a few millimetre to submillimetre accuracy. The work includes sensor optical construction modifications and the designing of new types of PSDs. The conventional QD-based sensor, although electrically very sensitive, is not considered optimal for industrial applications since its precision is severely hampered by atmospheric turbulence due to the misfocusing needed for its operation. Replacing the CCR with a sheet reflector is found to improve the precision of the conventional sensor construction in outdoor beam pointing applications, and is estimated to allow subcentimetre precision over distances of up to 100 m under most operating conditions. Submillimetre accuracy is achievable in close-range beam pointing applications using a small piece of sheet reflector, coaxial illumination and a focused QD receiver. Polarisation filtering is found to be effective in eliminating the main error contributor in close-range applications, which is low reflector background contrast, especially in cases when a sheet reflector has a specularly reflecting background. The tracking sensor construction is also proposed for measuring the aiming trajectory of a firearm in an outdoor environment. This time an order of magnitude improvement in precision is achieved by replacing the QD with a focused lateral effect photodiode (LEP). Use of this construction in cases of intermediate atmospheric turbulence allows a precision better than 1 cm to be achieved up to a distance of 300 m. A method based on averaging the positions of multiple reflectors is also proposed in order to improve the precision in turbulence-limited cases. Finally, various types of custom-designed PSDs utilising a photodetector array structure are presented for long-range displacement sensing applications. The goal was to be able to replace the noisy LEP with a low-noise PSD without compromising the low turbulence sensitivity achievable with the LEP. An order of magnitude improvement in incremental sensitivity is achievable with the proposed array PSDs.

Much research effort has been devoted to producing algorithms that contribute directly or indirectly to the extraction of 3D information from a wide variety of types of scenes and conditions of image capture. The research work presented in this thesis is aimed at three distinct applications in this area: interactively extracting 3D points from a pair of uncalibrated images in a flexible way; finding corresponding points automatically in high resolution images, particularly those of archaeological scenes captured from a freely moving light aircraft; and improving a correlation approach to dense disparity mapping leading to 3D surface reconstructions. The fundamental concepts required to describe the principles of stereo vision, the camera models, and the epipolar geometry described by the fundamental matrix are introduced, followed by a detailed literature review of existing methods. An interactive system for viewing a scene via a monochrome or colour anaglyph is presented which allows the user to choose the level of compromise between amount of colour and ghosting perceived by controlling colour saturation, and to choose the depth plane of interest. An improved method of extracting 3D coordinates from disparity values when there is significant error is presented. Interactive methods, while very flexible, require significant effort from the user finding and fusing corresponding points and the thesis continues by presenting several variants of existing scale invariant feature transform methods to automatically find correspondences in uncalibrated high resolution aerial images with improved speed and memory requirements. In addition, a contribution to estimating lens distortion correction by a Levenberg Marquard based method is presented; generating data strings for straight lines which are essential input for estimating lens distortion correction. The remainder of the thesis presents correlation based methods for generating dense disparity maps based on single and multiple image rectifications using sets of automatically found correspondences and demonstrates improvements obtained using the latter method. Some example views of point clouds for 3D surfaces produced from pairs of uncalibrated images using the methods presented in the thesis are included.

Much research effort has been devoted to producing algorithms that contribute directly or indirectly to the extraction of 3D information from a wide variety of types of scenes and conditions of image capture. The research work presented in this thesis is aimed at three distinct applications in this area: interactively extracting 3D points from a pair of uncalibrated images in a flexible way; finding corresponding points automatically in high resolution images, particularly those of archaeological scenes captured from a freely moving light aircraft; and improving a correlation approach to dense disparity mapping leading to 3D surface reconstructions. The fundamental concepts required to describe the principles of stereo vision, the camera models, and the epipolar geometry described by the fundamental matrix are introduced, followed by a detailed literature review of existing methods. An interactive system for viewing a scene via a monochrome or colour anaglyph is presented which allows the user to choose the level of compromise between amount of colour and ghosting perceived by controlling colour saturation, and to choose the depth plane of interest. An improved method of extracting 3D coordinates from disparity values when there is significant error is presented. Interactive methods, while very flexible, require significant effort from the user finding and fusing corresponding points and the thesis continues by presenting several variants of existing scale invariant feature transform methods to automatically find correspondences in uncalibrated high resolution aerial images with improved speed and memory requirements. In addition, a contribution to estimating lens distortion correction by a Levenberg Marquard based method is presented; generating data strings for straight lines which are essential input for estimating lens distortion correction. The remainder of the thesis presents correlation based methods for generating dense disparity maps based on single and multiple image rectifications using sets of automatically found correspondences and demonstrates improvements obtained using the latter method. Some example views of point clouds for 3D surfaces produced from pairs of uncalibrated images using the methods presented in the thesis are included. / Al-Baath University / The appendices files and images are not available online.

This thesis deals with a more work-efficient and time-efficient method of calibration of standard glass scales, with practical use in the Czech Metrology Institute Regional Inspectorate in Brno. The desired streamlining of calibration were achieved in the use of a 3D coordinate measuring machine Micro-Vu Excel 4520. In the service software InSpec, six measuring programs were designed in the use of a standard glass scale brand SIP. The measurement uncertainties of this calibration were presented and calculated. This thesis draws up a draft proposal of the calibration procedure and drafts a formalized document of the calibration.