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"abstract": "In this paper we present an adaptive dandelion model for reconstructing spherical terrain-like visual hull (VH) surfaces. The dandelion model represents a solid by a pencil of organized line segments emitted from a common point. The directions and the topology of the line segments are derived from the triangle facets of a geodesic sphere, which are recursively subdivided until the desired precision is achieved. The initial lines are cut by silhouettes in 2D and then lifted back to 3D to determine the ending points of the line segments defining sampling points on the spherical terrain-like VH surface. A mesh model can be easily constructed from the dandelion model. Our algorithm has the advantages of controllable precision, adaptive resolution, simplicity and speediness. We validate our algorithm by theories and experiments.",
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"abstract": "We propose a flexible raster image districting framework based on generalized Voronoi diagrams through Euclidean distance transforms. We introduce a three-scan algorithm that segments raster images in O(N) time when N is the number of pixels. The algorithm is capable of handling generators of complex types (point, line and area), Minkowski metrics and different weights. This paper also provides applications of the proposed method in various geoinformation datasets. Illustrated examples demonstrate the usefulness and robustness of our proposed method.",
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"abstract": "HSTCP (High Speed TCP congestion control) is a well- suited congestion control mechanism for high bandwidth flows. In this paper, we first present a fluid flow model for the feedback control system of HSTCP and AQM (active queue management) by using Stochastic Differential equation. Based on this model, we analyses the stability of the system, and obtain one method of configuring of control parameters of RED. NS2 simulation shows the method is effective.",
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"abstract": "In this paper we consider the Hamiltonian formulation of the equations of incompressible ideal fluid flow from the point of view of optimal control theory. The equations are compared to the finite symmetric rigid body equations analyzed earlier by the authors. We discuss various aspects of the Hamiltonian structure of the Euler equations and show in particular that the optimal control approach leads to a standard formulation of the Euler equations-the so-called impulse equations in their Lagrangian form. We discuss various other aspects of the Euler equations from a pedagogical point of view. We show that the Hamiltonian in the maximum principle is given by the pairing of the Eulerian impulse density with the velocity. We provide a comparative discussion of the flow equations in their Eulerian and Lagrangian form and describe how these forms occur naturally in the context of optimal control. We demonstrate that the extremal equations corresponding to the optimal control problem for the flow have a natural canonical symplectic structure.",
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"abstract": "An improved technique for 3D head tracking under varying illumination conditions is proposed. The head is modeled as a texture mapped cylinder. Tracking is formulated as an image registration problem in the cylinder's texture map image. To solve the registration problem in the presence of lighting variation and head motion, the residual error of registration is modeled as a linear combination of texture warping templates and orthogonal illumination templates. Fast and stable on-line tracking is then achieved via regularized, weighted least squares minimization of the registration error. The regularization term tends to limit potential ambiguities that arise in the warping and illumination templates. Tracking does not require a precise initial fit of the model; the system is initialized automatically using a simple 2D face detector. The only assumption is that the target is facing the camera in the first frame of the sequence. Experiments in tracking are reported.",
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"affiliation": "Departments of Radiology, Neurology, and Ophthalmology, Johns Hopkins University School of Medicine, Baltimore, MD, USA",
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"abstract": "One of the most promising avenues for compiling anatomical brain connectivity data arises from diffusion magnetic resonance imaging (dMRI). dMRI provides a rather novel family of medical imaging techniques with broad application in clinical as well as basic neu-roscience as it offers an estimate of the brain's fiber structure completely non-invasively and in vivo. A convenient way to reconstruct neuronal fiber pathways and to characterize anatomical connectivity from this data is the computation of diffusion tractograms. In this paper, we present a novel and effective method for visualizing probabilistic tractograms within their anatomical context. Our illustrative rendering technique, called fiber stippling, is inspired by visualization standards as found in anatomical textbooks. These illustrations typically show slice-based projections of fiber pathways and are typically hand-drawn. Applying the automatized technique to diffusion tractography, we demonstrate its expressiveness and intuitive usability as well as a more objective way to present white-matter structure in the human brain.",
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"content": "One of the most promising avenues for compiling anatomical brain connectivity data arises from diffusion magnetic resonance imaging (dMRI). dMRI provides a rather novel family of medical imaging techniques with broad application in clinical as well as basic neu-roscience as it offers an estimate of the brain's fiber structure completely non-invasively and in vivo. A convenient way to reconstruct neuronal fiber pathways and to characterize anatomical connectivity from this data is the computation of diffusion tractograms. In this paper, we present a novel and effective method for visualizing probabilistic tractograms within their anatomical context. Our illustrative rendering technique, called fiber stippling, is inspired by visualization standards as found in anatomical textbooks. These illustrations typically show slice-based projections of fiber pathways and are typically hand-drawn. Applying the automatized technique to diffusion tractography, we demonstrate its expressiveness and intuitive usability as well as a more objective way to present white-matter structure in the human brain.",
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"abstract": "We address three crucial issues encountered in DT-MRI (Diffusion Tensor Magnetic Resonance Imaging) : diffusion tensor Estimation, Regularization and fiber bundle Visualization. We first review related algorithms existing in the literature and propose then alternative variational formalisms that lead to new and improved schemes, thanks to the preservation of important tensor constraints (positivity, symmetry). We illustrate how our complete DT-MRI processing pipeline can be successfully used to construct and draw fiber bundles in the white matter of the brain, from a set of noisy raw MRI images.",
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"abstract": "Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) uses radioactive contrast agents as a tracer to provide tumor morphology and contrast kinetics information of tumor regions, which are crucial in breast cancer diagnosis and treatment. The effectiveness of the imaging modality relies on its capacity to acquire dynamic data at a sufficient sampling rate to gain the desired temporal resolution. This can be achieved by sparsely sampling the k-space data and applying advanced image reconstruction method that exploits compressed sensing, such as the recently proposed GenSeT (Generalized Series with Temporal constraint) method. Due to the highly nonlinear nature of compressed-sensing-based approach, computational complexity of the reconstruction algorithm is a practical challenge, especially for large breast DCE-MRI datasets. In this study, the GenSeT algorithm was implemented in GPU using CUDA platform to significantly reduce reconstruction time, yielding a much more practical solution. Experimental results showed that for a breast DCE-MRI data, the proposed GPU-based GenSeT implementation achieved approximately 48 times faster in the reconstruction time as compared to the CPU approach, without sacrificing the image quality. Although this work focuses on accelerating image reconstruction for sparsely-sampled breast DCE-MRI, the proposed GPU-based algorithm can be easily applied for sparsely sampled DCE-MRI of other organs.",
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"content": "Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) uses radioactive contrast agents as a tracer to provide tumor morphology and contrast kinetics information of tumor regions, which are crucial in breast cancer diagnosis and treatment. The effectiveness of the imaging modality relies on its capacity to acquire dynamic data at a sufficient sampling rate to gain the desired temporal resolution. This can be achieved by sparsely sampling the k-space data and applying advanced image reconstruction method that exploits compressed sensing, such as the recently proposed GenSeT (Generalized Series with Temporal constraint) method. Due to the highly nonlinear nature of compressed-sensing-based approach, computational complexity of the reconstruction algorithm is a practical challenge, especially for large breast DCE-MRI datasets. In this study, the GenSeT algorithm was implemented in GPU using CUDA platform to significantly reduce reconstruction time, yielding a much more practical solution. Experimental results showed that for a breast DCE-MRI data, the proposed GPU-based GenSeT implementation achieved approximately 48 times faster in the reconstruction time as compared to the CPU approach, without sacrificing the image quality. Although this work focuses on accelerating image reconstruction for sparsely-sampled breast DCE-MRI, the proposed GPU-based algorithm can be easily applied for sparsely sampled DCE-MRI of other organs.",
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"abstract": "Sarcopenia is defined as a muscle disease rooted in the continuous loss of muscle mass, strength and function. In terms of human health, sarcopenia leads to mobility disorders, increases the risk of falls and fractures and contributes to a lowered quality of life. Therefore, an early detection is essential for those suffering from sarcopenia. The rectus femoris muscle (RF) is suspected to be an early biomarker of sarcopenia in older adults. In this work the possibility of using MeVisLab as a muscle-specific diffusion tensor-magnetic resonance imaging (DT-MRI) software tool is analyzed. It turned out that MeVisLab is a powerful tool to perform muscle-specific processing and fiber tracking. The plausibility of the results is going to be discussed for further application in studies.",
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"abstract": "We have developed an energy based approach for identifying the binding site residues in protein-protein complexes. The binding site residues have been analyzed with sequence and structure based parameters such as neighboring residues in the vicinity of binding sites and conformational switching. We observed specific preferences of dipeptides and tripeptides for binding, which is unique to protein-protein complexes. Our analysis showed that 7% of residues changed their conformations upon protein-protein complex formation and it is 9.2% and 6.6% in the binding and non-binding sites, respectively. Specifically, the residues Glu, Lys, Leu and Ser changed their conformation from coil to helix/strand and from helix to coil/strand. Leu, Ser, Thr and Val prefer to change their conformation from strand to coil/helix. The results obtained in this study will be helpful for understanding and predicting the binding sites in protein-protein complexes.",
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"content": "We have developed an energy based approach for identifying the binding site residues in protein-protein complexes. The binding site residues have been analyzed with sequence and structure based parameters such as neighboring residues in the vicinity of binding sites and conformational switching. We observed specific preferences of dipeptides and tripeptides for binding, which is unique to protein-protein complexes. Our analysis showed that 7% of residues changed their conformations upon protein-protein complex formation and it is 9.2% and 6.6% in the binding and non-binding sites, respectively. Specifically, the residues Glu, Lys, Leu and Ser changed their conformation from coil to helix/strand and from helix to coil/strand. Leu, Ser, Thr and Val prefer to change their conformation from strand to coil/helix. The results obtained in this study will be helpful for understanding and predicting the binding sites in protein-protein complexes.",
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"normalizedAbstract": "We have developed an energy based approach for identifying the binding site residues in protein-protein complexes. The binding site residues have been analyzed with sequence and structure based parameters such as neighboring residues in the vicinity of binding sites and conformational switching. We observed specific preferences of dipeptides and tripeptides for binding, which is unique to protein-protein complexes. Our analysis showed that 7% of residues changed their conformations upon protein-protein complex formation and it is 9.2% and 6.6% in the binding and non-binding sites, respectively. Specifically, the residues Glu, Lys, Leu and Ser changed their conformation from coil to helix/strand and from helix to coil/strand. Leu, Ser, Thr and Val prefer to change their conformation from strand to coil/helix. The results obtained in this study will be helpful for understanding and predicting the binding sites in protein-protein complexes.",
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"affiliation": "Computational Biology Research Center (CBRC), National Institute of Advanced Industrial, Science and Technology (AIST), 2-4-7 Aomi, Koto-ku, Tokyo 135-0064, Japan",
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"affiliation": "Department of Bioinformatics, Bharathidasan University, Tiruchirapalli 620024, Tamilnadu, India",
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"affiliation": "Department of Bioinformatics, Bharathidasan University, Tiruchirapalli 620024, Tamilnadu, India",
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"abstract": "Proteins play a crucial role in every organism, which perform a vast amount of functions. The hot regions in protein-protein interactions consist of hot spot residues in protein-protein binding sites which are called interfaces, can help proteins to perform their biological function. Residue based computational prediction of hot regions might be useful to understand the molecular mechanism and is crucial in drug design and protein design. However, it is very challenging to identify the hot regions in protein-proteins. In this paper, we have proposed a support vector machine based on ensemble learning system for predicting hot spot residues, and predicted hot regions in protein-protein interactions. The efficiency of our method is analyzed in identifying hot spots and hot regions in protein-protein interactions and the results obtained are compared with the existing techniques. The results demonstrate that the proposed method is superior to identify the hot spots and hot regions in the protein interfaces.",
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"content": "Proteins play a crucial role in every organism, which perform a vast amount of functions. The hot regions in protein-protein interactions consist of hot spot residues in protein-protein binding sites which are called interfaces, can help proteins to perform their biological function. Residue based computational prediction of hot regions might be useful to understand the molecular mechanism and is crucial in drug design and protein design. However, it is very challenging to identify the hot regions in protein-proteins. In this paper, we have proposed a support vector machine based on ensemble learning system for predicting hot spot residues, and predicted hot regions in protein-protein interactions. The efficiency of our method is analyzed in identifying hot spots and hot regions in protein-protein interactions and the results obtained are compared with the existing techniques. The results demonstrate that the proposed method is superior to identify the hot spots and hot regions in the protein interfaces.",
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"abstract": "Protein is the major component of the organism. A concave (pocket) on a protein surface is known to be thebest target for a drug to react. We previously presented astudy on distance analysis between pockets and amino acidresidue. We firstly identified pockets on the protein surfaceand then calculated distances between atoms of an amino acidresidue and the deepest points or the outer loops of the pockets. We extracted proteins which at least one of the pockets areclose to arbitrary pairs of amino acid residues, calculated theratios of druggable proteins, and visualized the distributionof the ratios as a colored matrix. We suggested from thevisualization results that particular pairs of amino acid residuesmay affect the druggability of the proteins in our previousstudy. This paper presents an extension of our study to explorethe relevance between druggability of proteins and distancesbetween a set of amino acid residues and protein surfacepockets. Our technique treats the pockets as 20-dimensionalvectors consisting of distances to each of amino acid residues, and applies GeodesicSOM with the set of the vectors. Sphericalmaps generated by GeodesicSOM are used to visualizationof distribution of the pockets in the 20-dimensional vectorspace, and estimation of druggability of proteins with the 20-dimensional vectors of the pockets.",
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"content": "Protein is the major component of the organism. A concave (pocket) on a protein surface is known to be thebest target for a drug to react. We previously presented astudy on distance analysis between pockets and amino acidresidue. We firstly identified pockets on the protein surfaceand then calculated distances between atoms of an amino acidresidue and the deepest points or the outer loops of the pockets. We extracted proteins which at least one of the pockets areclose to arbitrary pairs of amino acid residues, calculated theratios of druggable proteins, and visualized the distributionof the ratios as a colored matrix. We suggested from thevisualization results that particular pairs of amino acid residuesmay affect the druggability of the proteins in our previousstudy. This paper presents an extension of our study to explorethe relevance between druggability of proteins and distancesbetween a set of amino acid residues and protein surfacepockets. Our technique treats the pockets as 20-dimensionalvectors consisting of distances to each of amino acid residues, and applies GeodesicSOM with the set of the vectors. Sphericalmaps generated by GeodesicSOM are used to visualizationof distribution of the pockets in the 20-dimensional vectorspace, and estimation of druggability of proteins with the 20-dimensional vectors of the pockets.",
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"normalizedAbstract": "Protein is the major component of the organism. A concave (pocket) on a protein surface is known to be thebest target for a drug to react. We previously presented astudy on distance analysis between pockets and amino acidresidue. We firstly identified pockets on the protein surfaceand then calculated distances between atoms of an amino acidresidue and the deepest points or the outer loops of the pockets. We extracted proteins which at least one of the pockets areclose to arbitrary pairs of amino acid residues, calculated theratios of druggable proteins, and visualized the distributionof the ratios as a colored matrix. We suggested from thevisualization results that particular pairs of amino acid residuesmay affect the druggability of the proteins in our previousstudy. This paper presents an extension of our study to explorethe relevance between druggability of proteins and distancesbetween a set of amino acid residues and protein surfacepockets. Our technique treats the pockets as 20-dimensionalvectors consisting of distances to each of amino acid residues, and applies GeodesicSOM with the set of the vectors. Sphericalmaps generated by GeodesicSOM are used to visualizationof distribution of the pockets in the 20-dimensional vectorspace, and estimation of druggability of proteins with the 20-dimensional vectors of the pockets.",
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"abstract": "The placement of knot vector and the determination of control points are two fundamental issues in B-spline surface reconstruction. This paper presents a variational approach to construct B-spline surfaces from a set of data points. The approach finds the optimal placement of knots and control points simultaneously while most previous methods determine the knots heuristically or in a separate step. Moreover, different from most previous methods using least squares metric, our approach adapts L_1-norm with total variation (TV) as regularization in the fitting procedure, which enables the approach to handle both Gaussian noise and outliers in the same manner and is able to automatically optimize the placement of knot vector to faithfully reconstruct the sharp features. A numerical solver based on the augmented Lagrangian method is also proposed in the paper to efficiently solve the TV-L_1 optimization. Experimental results demonstrate the effectiveness and efficiency of the proposed variational B-spline surface reconstruction.",
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"content": "Due to carriers Band-To-Band-Tunneling (BTBT) through channel-source/drain contacts, Conventional MOS-like Carbon Nanotube Field Effect Transistors (C-CNFETs) suffer from ambipolar conductance, which deteriorates the device performance greatly. In order to reduce such ambipolar behavior, a novel device design based on dual gate material is proposed. The simulation results show that, with proper choice of tuning gate material, this device design can not only reduce the ambipolar conductance and increase the available ON-OFF current ratio but also decrease the average sub-threshold swing, which are all very desirable in circuit design to reduce the system power and improve the working frequency as well. Further study reveals the fact that the performance of the proposed design depends highly on the choice of tuning gate material which should be paid with much attention in application.",
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"abstract": "In order to investigate dangerous goods detection function of the dual-energy X-ray security machine, the paper starting point is testing theory of dual-energy security machine and dual-energy projection technology. By analyze on the detection method, that is, using atomic number R and material density to judge the material type, the determining approach of two parameters (R and ) is presented in detail. And the mathematical model of the superposing phenomenon in detecting process is further constructed , in order to achieve the ultimate aim of finding dangerous goods.",
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"content": "In order to investigate dangerous goods detection function of the dual-energy X-ray security machine, the paper starting point is testing theory of dual-energy security machine and dual-energy projection technology. By analyze on the detection method, that is, using atomic number R and material density to judge the material type, the determining approach of two parameters (R and ) is presented in detail. And the mathematical model of the superposing phenomenon in detecting process is further constructed , in order to achieve the ultimate aim of finding dangerous goods.",
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"affiliation": null,
"fullName": "Tong Gang",
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"content": "Dual-Energy Computed Tomography (DECT) is a new modality of CT where two images are acquired simultaneously at two energy levels, and then decomposed into two material density images. It is also possible to further decompose these images into volume fraction images that approximate the percentage of a given material at each pixel. Here, we describe a novel parallel version of the multilateral decomposition algorithm proposed by Mendonça et al., which is used to obtain volume fraction images. Our parallel version accelerates decomposition by 200x. We also discuss some of the algorithm limitations.",
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"affiliation": "Department of Computer Science, University of Calgary, Calgary, Canada",
"fullName": "Rafael Simon Maia",
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"affiliation": "Department of Computer Science, University of Calgary, Calgary, Canada",
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"affiliation": "Department of Radiology, The Mayo Clinic, Scottsdale, AZ, USA",
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"affiliation": "Department of Radiology, The Mayo Clinic, Scottsdale, AZ, USA",
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"affiliation": "Department of Radiology, The Mayo Clinic, Scottsdale, AZ, USA",
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"abstract": "The assessment of bone mineral density (BMD) in vertebrae is critical for the diagnosis of osteoporosis. Recent developments in dual-source CT allow for the simultaneous acquisition of two image data sets with different X-ray tube energies - dual-energy CT (DECT). We present a comprehensive approach for assessing the density of the trabecular bone in vertebrae of the spine based on DECT image data. For this, we apply and combine methods from different areas: the deformation of a template mesh for delineating the structures of interest, a biophysical model of the trabecular bone for the computation of BMD values, and different visualization approaches for the display of the results. In addition, we investigate the correlation between the computed BMD values with concurrently measured pull-out forces for pedicle screws. We show that there is a linear correlation between both measures and thus, DECT provides correct BMD values for the trabecular bone. We conclude that our approach enables the radiologist to diagnose osteoporosis based on DECT image data which has the potential to replace the current gold standard dual-energy X-ray absorptiometry.",
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"content": "The assessment of bone mineral density (BMD) in vertebrae is critical for the diagnosis of osteoporosis. Recent developments in dual-source CT allow for the simultaneous acquisition of two image data sets with different X-ray tube energies - dual-energy CT (DECT). We present a comprehensive approach for assessing the density of the trabecular bone in vertebrae of the spine based on DECT image data. For this, we apply and combine methods from different areas: the deformation of a template mesh for delineating the structures of interest, a biophysical model of the trabecular bone for the computation of BMD values, and different visualization approaches for the display of the results. In addition, we investigate the correlation between the computed BMD values with concurrently measured pull-out forces for pedicle screws. We show that there is a linear correlation between both measures and thus, DECT provides correct BMD values for the trabecular bone. We conclude that our approach enables the radiologist to diagnose osteoporosis based on DECT image data which has the potential to replace the current gold standard dual-energy X-ray absorptiometry.",
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"normalizedAbstract": "The assessment of bone mineral density (BMD) in vertebrae is critical for the diagnosis of osteoporosis. Recent developments in dual-source CT allow for the simultaneous acquisition of two image data sets with different X-ray tube energies - dual-energy CT (DECT). We present a comprehensive approach for assessing the density of the trabecular bone in vertebrae of the spine based on DECT image data. For this, we apply and combine methods from different areas: the deformation of a template mesh for delineating the structures of interest, a biophysical model of the trabecular bone for the computation of BMD values, and different visualization approaches for the display of the results. In addition, we investigate the correlation between the computed BMD values with concurrently measured pull-out forces for pedicle screws. We show that there is a linear correlation between both measures and thus, DECT provides correct BMD values for the trabecular bone. We conclude that our approach enables the radiologist to diagnose osteoporosis based on DECT image data which has the potential to replace the current gold standard dual-energy X-ray absorptiometry.",
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"affiliation": "Interactive Graphics Syst. Group (GRIS), Tech. Univ. Darmstadt, Darmstadt, Germany",
"fullName": "S. Wesarg",
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"abstract": "Dual-energy X-ray scanners are used for aviation security screening given their capability to discriminate materials inside passenger baggage. To facilitate manual operator inspection, a pseudo-colouring is assigned to the effective composition of the material. Recently, paired image to image translation models based on conditional Generative Adversarial Networks (cGAN) have shown to be effective for image colourisation. In this work, we investigate the use of such a model to translate from the raw X-ray energy responses (high, low, effective-Z) to the pseudo-coloured images and vice versa. Specifically, given N X-ray modalities, we train a cGAN conditioned in N − m domains to generate the remaining m representation. Our method achieves a mean squared error (MSE) of 16.5 and a structural similarity index (SSIM) of 0.9815 when using the raw modalities to generate the pseudo-colour representation. Additionally, raw X-ray high energy, low energy and effective-Z projections were generated given the pseudo-colour image with minimum MSE of 2.57, 5.63 and 1.43, and maximum SSIM of 0.9953, 0.9901 and 0.9921. Furthermore, we assess the quality of our synthesised pseudo-colour reconstructions by measuring the performance of two object detection models originally trained on real X-ray pseudo-colour images over our generated pseudo-colour images. Interestingly, our generated pseudo-colour images obtain marginally improved detection performance than the corresponding real X-ray pseudo-colour images, showing that meaningful representations are synthesized and that these reconstructions are applicable for differing aviation security tasks.",
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"abstract": "Material spectroscopy (MS) is used to identify elemental composition of micro particles. Energy dispersive X-Ray spectroscopy (EDX or EDS) is one such method. EDX analysis of defects found during wafer inspection aids in performing their root cause analysis (RCA). However, due to large processing time of EDX, it is applied very judiciously on a few chosen defects only. A wafer can typically contain ~100s of defects. The defect coverage of EDX is ~1% [1] thereby resulting in considerable gap in proper diagnosis and RCA. To overcome this issue, we demonstrate a soft method to perform MS of defects. The method predicts accurate elemental compositions of defect and background (~80%F1) when compared with EDX predictions on the same defect. The method is fast and could increase defect coverage for MS to ~100%. This can significantly improve RCA and thus help in Yield Enhancement (YE). Computing exact YE is complex as it involves many hidden and un-trackable factors. We perform theoretical high level modelling of more tangible factors i.e. profitability per month of Fab which is directly proportional to YE and theoretically show 14.6% improvement using our soft MS method.",
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"content": "Material spectroscopy (MS) is used to identify elemental composition of micro particles. Energy dispersive X-Ray spectroscopy (EDX or EDS) is one such method. EDX analysis of defects found during wafer inspection aids in performing their root cause analysis (RCA). However, due to large processing time of EDX, it is applied very judiciously on a few chosen defects only. A wafer can typically contain ~100s of defects. The defect coverage of EDX is ~1% [1] thereby resulting in considerable gap in proper diagnosis and RCA. To overcome this issue, we demonstrate a soft method to perform MS of defects. The method predicts accurate elemental compositions of defect and background (~80%F1) when compared with EDX predictions on the same defect. The method is fast and could increase defect coverage for MS to ~100%. This can significantly improve RCA and thus help in Yield Enhancement (YE). Computing exact YE is complex as it involves many hidden and un-trackable factors. We perform theoretical high level modelling of more tangible factors i.e. profitability per month of Fab which is directly proportional to YE and theoretically show 14.6% improvement using our soft MS method.",
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"normalizedAbstract": "Material spectroscopy (MS) is used to identify elemental composition of micro particles. Energy dispersive X-Ray spectroscopy (EDX or EDS) is one such method. EDX analysis of defects found during wafer inspection aids in performing their root cause analysis (RCA). However, due to large processing time of EDX, it is applied very judiciously on a few chosen defects only. A wafer can typically contain ~100s of defects. The defect coverage of EDX is ~1% [1] thereby resulting in considerable gap in proper diagnosis and RCA. To overcome this issue, we demonstrate a soft method to perform MS of defects. The method predicts accurate elemental compositions of defect and background (~80%F1) when compared with EDX predictions on the same defect. The method is fast and could increase defect coverage for MS to ~100%. This can significantly improve RCA and thus help in Yield Enhancement (YE). Computing exact YE is complex as it involves many hidden and un-trackable factors. We perform theoretical high level modelling of more tangible factors i.e. profitability per month of Fab which is directly proportional to YE and theoretically show 14.6% improvement using our soft MS method.",
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"abstract": "Piecewise smooth surfaces reconstruction algorithm for finite element mixed meshes is proposed in this paper. Meshes are supposed to have been segmented and T shaped nodes among segments are permitted, i.e. a boundary in one segment can be split into at least two boundaries of other segments. A frame of B-spline curves is constructed first, which interpolates boundary nodes of all segments. All the B-spline curves should satisfy the condition that opposite curves in quad segments, i.e. segments with rectangle topology, have the same knots vector. Two situations need to be considered for all the segments. For a quad segment, the initial B-spline surface is constructed by skinning its four boundary curves. For a segment with non-rectangle topology or a segment with holes inside, a trimmed B-spline surface is developed. There are also two cases when an initial trimmed base surface is to be constructed. If two appropriate neighbor curves in the outer boundaries loop of the segment are found, the base surface can be obtained by sweeping and extending. Otherwise, the initial base surface is built by skinning the boundary curves of the bounding box for projected points of all nodes on a least squares fitting plane. Nodes in each segment are parameterized by projection on the corresponding base surface. All base surfaces are recalculated with geometry and additional shape preservation constraints. Examples indicate efficiency of our algorithm.",
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"content": "Piecewise smooth surfaces reconstruction algorithm for finite element mixed meshes is proposed in this paper. Meshes are supposed to have been segmented and T shaped nodes among segments are permitted, i.e. a boundary in one segment can be split into at least two boundaries of other segments. A frame of B-spline curves is constructed first, which interpolates boundary nodes of all segments. All the B-spline curves should satisfy the condition that opposite curves in quad segments, i.e. segments with rectangle topology, have the same knots vector. Two situations need to be considered for all the segments. For a quad segment, the initial B-spline surface is constructed by skinning its four boundary curves. For a segment with non-rectangle topology or a segment with holes inside, a trimmed B-spline surface is developed. There are also two cases when an initial trimmed base surface is to be constructed. If two appropriate neighbor curves in the outer boundaries loop of the segment are found, the base surface can be obtained by sweeping and extending. Otherwise, the initial base surface is built by skinning the boundary curves of the bounding box for projected points of all nodes on a least squares fitting plane. Nodes in each segment are parameterized by projection on the corresponding base surface. All base surfaces are recalculated with geometry and additional shape preservation constraints. Examples indicate efficiency of our algorithm.",
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"title": "Segmenting film sequences using active surfaces",
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"abstract": "Special effects in motion pictures largely employ image compositing to seamlessly join picture elements together from separate sequences. The extraction of objects such as actors from real backgrounds rather than blue screens requires manual tracking of the object boundary by skilled operators: an inaccurate and error-prone task which inevitably generates a bubbling artifact. An active surface model defined over the three dimensional spatio-temporal space is recovered whose intersection with each image plane represents the required object boundary. Such active surfaces are a generalisation of snake contours common in many image processing applications. Initial crude boundaries are drawn in end frames and key intermediate frames to construct an initial surface. A energy minimisation process is used to iteratively refine the location of boundaries in all frames simultaneously. User selected edge data may also be employed to guide the crudely specified initial contours to their correct location.",
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"abstract": "We consider the problem of designing space efficient solutions for representing the connectivity information of manifold triangle meshes. Most mesh data structures are quite redundant, storing a large amount of information in order to efficiently support mesh traversal operators. Several compact data structures have been proposed to reduce storage cost while supporting constant-time mesh traversal. Some recent solutions are based on a global re-ordering approach, which allows to implicitly encode a map between vertices and faces. Unfortunately, these compact representations do not support efficient updates, because local connectivity changes (such as edge-contractions, edge-flips or vertex insertions) require reordering the entire mesh. Our main contribution is to propose a new way of designing compact data structures which can be dynamically maintained. In our solution, we push further the limits of the re-ordering approaches: the main novelty is to allow to re-order vertex data (such as vertex coordinates), and to exploit this vertex permutation to easily maintain the connectivity under local changes. We describe a new class of data structures, called Editable SQuad (ESQ), offering the same navigational and storage performance as previous works, while supporting local editing in amortized constant time. As far as we know, our solution provides the most compact dynamic data structure for triangle meshes. We propose a linear-time and linear-space construction algorithm, and provide worst-case bounds for storage and time cost.",
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"abstract": "As the use of 3D information presentation becomes more prevalent, the need for effective viewing tools grows accordingly. Much work has been done in developing tools for 2D spaces which allow for detail in context views. We examine the extension of such 2D methods to 3D and explore the limitations encountered in accessing internal regions of the data with these methods. We then describe a novel solution to this problem of internal access with the introduction of a distortion function which creates a clear line of sight to the focus revealing sections previously obscured. The distortion is symmetric about the line of sight and is smoothly integrated back into the original 3D layout.",
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"title": "Recovering 3D facial shape via coupled 2D/3D space learning",
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"abstract": "This paper presents a method for recovering 3D facial shape from single image via learning the relationship between the 2D intensity images and the 3D facial shapes. With a coupled training set, the intensity images and their corresponding facial shapes make up two vector spaces respectively. But only the correlated components in both spaces are useful for inference, so there must be embedded hidden subspaces in each space which preserve the inter-space correlation information. Thus by learning the projection onto hidden subspaces based on maximum correlation criteria and optimizing the linear transform between the hidden spaces, 3D facial shape is inferred from the intensity image. The effectiveness of the method is demonstrated on both synthesized and real world data.",
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"content": "This paper presents a method for recovering 3D facial shape from single image via learning the relationship between the 2D intensity images and the 3D facial shapes. With a coupled training set, the intensity images and their corresponding facial shapes make up two vector spaces respectively. But only the correlated components in both spaces are useful for inference, so there must be embedded hidden subspaces in each space which preserve the inter-space correlation information. Thus by learning the projection onto hidden subspaces based on maximum correlation criteria and optimizing the linear transform between the hidden spaces, 3D facial shape is inferred from the intensity image. The effectiveness of the method is demonstrated on both synthesized and real world data.",
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"Computer Vision",
"Correlation Methods",
"Face Recognition",
"Image Reconstruction",
"Learning Artificial Intelligence",
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"Singular Value Decomposition",
"3 D Facial Shape Recovery",
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"Face",
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"Light Sources",
"Statistics",
"Deformable Models",
"Image Reconstruction",
"Active Shape Model",
"Space Technology"
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{
"affiliation": "Key Lab of Intelligent Information Processing of CAS, Institute of Computing Technology, Beijing 100190, China",
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{
"affiliation": "Key Lab of Intelligent Information Processing of CAS, Institute of Computing Technology, Beijing 100190, China",
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{
"affiliation": "System Research Center, NOKIA Research Center, Beijing, 100176, China",
"fullName": "Xiujuan Chai",
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{
"affiliation": "Institute of Digital Media, Peking University, Beijing, 100871, China",
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