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"title": "Active Drag Reduction using Neural Networks",
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"abstract": "Abstract: This paper presents the application of a neural network controller to the problem of active drag reduction in a fully turbulent 3D fluid flow regime. The neural network learns a function nearly identical to an analytically derived control law. We then demonstrate the ability of a neural controller to maintain a drag-reduced flow in a fully turbulent fluid simulation. Finally we examine the amount of parameter variation that may be required for a physical implementation of such a neural controller.",
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"content": "Abstract: This paper presents the application of a neural network controller to the problem of active drag reduction in a fully turbulent 3D fluid flow regime. The neural network learns a function nearly identical to an analytically derived control law. We then demonstrate the ability of a neural controller to maintain a drag-reduced flow in a fully turbulent fluid simulation. Finally we examine the amount of parameter variation that may be required for a physical implementation of such a neural controller.",
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"affiliation": "California Institute of Technology, Pasadena, CA",
"fullName": "David Babcock",
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"affiliation": "California Institute of Technology, Pasadena, CA",
"fullName": "Rodney Goodman",
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"affiliation": "University of California Los Angeles, Los Angeles, CA",
"fullName": "Changhoon Lee",
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"affiliation": "University of California Los Angeles, Los Angeles, CA",
"fullName": "John Kim",
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"title": "Computational fluid mechanics and massively parallel processors",
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"abstract": "The author reports on work devising massively parallel implementations of vortex methods for computing turbulent flow in highly complex geometries. The challenges involved in fitting evolving compilers, hardware, and I/O to nontraditional fluid mechanics techniques, N-body solvers, and interactive real-time visualization environments are discussed. The results describe algorithms to compute two and three-dimensional inside chambers and around bluff bodies. Some issues involved in developing intuition about parallel implementation of complex codes are examined.",
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"content": "The author reports on work devising massively parallel implementations of vortex methods for computing turbulent flow in highly complex geometries. The challenges involved in fitting evolving compilers, hardware, and I/O to nontraditional fluid mechanics techniques, N-body solvers, and interactive real-time visualization environments are discussed. The results describe algorithms to compute two and three-dimensional inside chambers and around bluff bodies. Some issues involved in developing intuition about parallel implementation of complex codes are examined.",
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"proceeding": {
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"title": "2010 International Conference on Digital Manufacturing & Automation",
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"article": {
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"doi": "10.1109/ICDMA.2010.328",
"title": "Numerical Simulation and Analysis of Flow and Heat Transfer in the High-Pressure Vortex Tube",
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"abstract": "The high-pressure vortex tube is one of key equipment in the skid-mounted package liquefied CBM. The high pressure gas strong rotating flow in vortex tube is the key issues of energy separation. There are many problems that the current experimental methods for the strong high-pressure in three-dimensional rotating turbulent flow and heat transfer measurements. The flow field and temperature field structure characteristics in the high-pressure vortex tube are analyzed under different external pressure by numerical simulation model. The design of high-pressure vortex tube hot region should be focused on solving the problem of gas accumulation. This works provide guidance on the development of the high-pressure vortex tube of fluidified CBM.",
"abstracts": [
{
"abstractType": "Regular",
"content": "The high-pressure vortex tube is one of key equipment in the skid-mounted package liquefied CBM. The high pressure gas strong rotating flow in vortex tube is the key issues of energy separation. There are many problems that the current experimental methods for the strong high-pressure in three-dimensional rotating turbulent flow and heat transfer measurements. The flow field and temperature field structure characteristics in the high-pressure vortex tube are analyzed under different external pressure by numerical simulation model. The design of high-pressure vortex tube hot region should be focused on solving the problem of gas accumulation. This works provide guidance on the development of the high-pressure vortex tube of fluidified CBM.",
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"normalizedAbstract": "The high-pressure vortex tube is one of key equipment in the skid-mounted package liquefied CBM. The high pressure gas strong rotating flow in vortex tube is the key issues of energy separation. There are many problems that the current experimental methods for the strong high-pressure in three-dimensional rotating turbulent flow and heat transfer measurements. The flow field and temperature field structure characteristics in the high-pressure vortex tube are analyzed under different external pressure by numerical simulation model. The design of high-pressure vortex tube hot region should be focused on solving the problem of gas accumulation. This works provide guidance on the development of the high-pressure vortex tube of fluidified CBM.",
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"title": "2017 Data Compression Conference (DCC)",
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"article": {
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"doi": "10.1109/DCC.2017.23",
"title": "Dual Error Bounded Trajectory Simplification",
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"abstract": "Nowadays, various sensors are collecting, storing and transmitting tremendous trajectory data, and it is well-known that raw trajectory data seriously wastes the storage, network band and computing resource. Line simplification (LS) algorithms are effective approaches to attacking this issue by compressing data points in a trajectory to a set of continuous line segments, and are commonly used in practice. LS algorithms in general use the perpendicular Euclidean distance (PED) or synchronous Euclidean distance (SED) of a data point to a proposed generalized line as the condition to discard or retain that data point. In the observation that the PED approach performances well in terms of compression ratios but is not suitable for temporal-spatio queries, while the SED approach is on the contrary, this paper presents a dual distances checking approach that leverages the benefits of approaches PED and SED, and satisfies the varied distance checking requirements. We experimentally verify that our approach is flexible and effective, using two real-life trajectory datasets.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Nowadays, various sensors are collecting, storing and transmitting tremendous trajectory data, and it is well-known that raw trajectory data seriously wastes the storage, network band and computing resource. Line simplification (LS) algorithms are effective approaches to attacking this issue by compressing data points in a trajectory to a set of continuous line segments, and are commonly used in practice. LS algorithms in general use the perpendicular Euclidean distance (PED) or synchronous Euclidean distance (SED) of a data point to a proposed generalized line as the condition to discard or retain that data point. In the observation that the PED approach performances well in terms of compression ratios but is not suitable for temporal-spatio queries, while the SED approach is on the contrary, this paper presents a dual distances checking approach that leverages the benefits of approaches PED and SED, and satisfies the varied distance checking requirements. We experimentally verify that our approach is flexible and effective, using two real-life trajectory datasets.",
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"normalizedAbstract": "Nowadays, various sensors are collecting, storing and transmitting tremendous trajectory data, and it is well-known that raw trajectory data seriously wastes the storage, network band and computing resource. Line simplification (LS) algorithms are effective approaches to attacking this issue by compressing data points in a trajectory to a set of continuous line segments, and are commonly used in practice. LS algorithms in general use the perpendicular Euclidean distance (PED) or synchronous Euclidean distance (SED) of a data point to a proposed generalized line as the condition to discard or retain that data point. In the observation that the PED approach performances well in terms of compression ratios but is not suitable for temporal-spatio queries, while the SED approach is on the contrary, this paper presents a dual distances checking approach that leverages the benefits of approaches PED and SED, and satisfies the varied distance checking requirements. We experimentally verify that our approach is flexible and effective, using two real-life trajectory datasets.",
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"fullName": "Xuelian Lin",
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"affiliation": null,
"fullName": "Jiahao Jiang",
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"affiliation": null,
"fullName": "Yimeng Zuo",
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"abstract": "In the last decade, emotion modeling has taken an increasing place in research in virtual agents and synthetic actors. One challenge is to be able to design believable characters that show a coherent behavior with respect to a personality. Much work has been done for virtual affective characters but, more recently, research has shown the importance of social relation and its tight relation with emotions. Not only the social context influence the emotional behavior of virtual characters, but also emotions do affect the social relations. As a consequence, when designing virtual characters with a believable socio-emotional behavior, one need to take into account the social context, the emotions and the personality. These three elements together represent the socio-emotional context. In this article, we present the Open-Source Socio Emotional (OSSE) simulator. This software was first designed in the context of game industry. It allows game designers to describe characters and scenes, as a set of emotional events, so as to study the dynamics of emotions and social relation among characters. In the next section, we briefly present the theoretical model that undergoes our system and we show how the different elements can be settled in the OSSE simulator. Last section illustrates the functionning of the OSSE simulator with a concrete example.",
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"Public Domain Software",
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"Open Source Socio Emotional Simulator",
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"Layout",
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"Context Modeling",
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"affiliation": "Université Paris 6, LIP6",
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"affiliation": "National Institute of Informatics (NII), Tokyo, Japan",
"fullName": "Magalie Ochs",
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"abstract": "This paper is a part of an ongoing project designed to develop a multimodal mobile social robot for office and home environment. An event driven dialogue system architecture is proposed to integrate different components of spoken dialogue system as well as various agents for vision understanding, navigation and radio-frequency identification (RFID) through a number of events and messages. Speech recognition is powered by our in-house developed multilingual, speaker independent phonetic speech recognition engine. A template-based cum rule-based language generation paradigm is proposed to render the interaction so that the dialogue can be evolved based on the context and task domain. Three levels of error recovery strategy are employed to deal with different types of errors. The successful implementation of the proposed system on our experimental social mobile robot is a good showcase toward the integration of spoken language technology with other modalities.",
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{
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"affiliation": null,
"fullName": "Shaojie Yuan",
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{
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"title": "2014 IEEE 26th International Conference on Tools with Artificial Intelligence (ICTAI)",
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"doi": "10.1109/ICTAI.2014.114",
"title": "Mutual Information-Based Feature Selection from Set-Valued Data",
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"abstract": "In many machine learning and data mining applications, it may happen that the data acquired for classification analysis are set-valued, i.e., The feature values of an object set are set-valued, which can be used to characterize uncertain information in decision making tasks. Set-valued data are the generalized models of single-valued data. Some mutual information-based feature selection algorithms have been extensively studied, but less effort has been made to investigate the feature selection issue with the mutual information analysis in set-valued data. Just owing to these, mutual information is firstly introduced in the set-valued data in this paper. Unlike the traditional computations, the mutual information is estimated on the unmarked objects. Correspondingly, a feature selection algorithm based on mutual information is developed, which is implemented in a dwindling universe to quicken the feature selection process. Compared with the state-of-the-art methods, the experimental results on different data sets demonstrate the efficiency and effectiveness of the proposed algorithm in set-valued data.",
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"abstract": "Deep learning-based method for medical image fusion has become a hot topic in recent years. However, they ignore the expression of the most important features in image fusion and only extract the general features for medical image fusion, which will restrict the expression of unique information on the fusion image. To address this restriction, we propose a novel disentangled representation network for medical image fusion with mutual information estimation, which extract the disentangled features of medical image fusion, i.e., the shared and exclusive features between multi-model medical images. In our method, we use the cross mutual information method to obtain the shared features of each modality pair, which enforce the fusion network to achieve the maximum of mutual information estimation for multi-modal medical images. The exclusive features are extracted by the adversarial objective method and it constrains the fusion network with the optimization to the minimum of mutual information estimation between shared and exclusive features. These disentangled features effectively take the interpretative advantages and make the fusion image retaining more details from source images as well as improving the visual quality of fusion image. Our method has achieved better results than several state-of-the-art methods. Both qualitative and quantitative experiments have proved the superiority of our method.",
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"content": "Deep learning-based method for medical image fusion has become a hot topic in recent years. However, they ignore the expression of the most important features in image fusion and only extract the general features for medical image fusion, which will restrict the expression of unique information on the fusion image. To address this restriction, we propose a novel disentangled representation network for medical image fusion with mutual information estimation, which extract the disentangled features of medical image fusion, i.e., the shared and exclusive features between multi-model medical images. In our method, we use the cross mutual information method to obtain the shared features of each modality pair, which enforce the fusion network to achieve the maximum of mutual information estimation for multi-modal medical images. The exclusive features are extracted by the adversarial objective method and it constrains the fusion network with the optimization to the minimum of mutual information estimation between shared and exclusive features. These disentangled features effectively take the interpretative advantages and make the fusion image retaining more details from source images as well as improving the visual quality of fusion image. Our method has achieved better results than several state-of-the-art methods. Both qualitative and quantitative experiments have proved the superiority of our method.",
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"Feature Extraction",
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"affiliation": "University of Alberta Edmonton,Department of Computing Science,Alberta,Canada",
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"affiliation": "University of Alberta Edmonton,Servier Virtual Cardiac Centre Alberta Heart Institute Department of Radiology and Diagnostic Imaging,Alberta,Canada",
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"abstract": "This paper presents an integrated framework for surface reconstruction capable of handling large scale clouds of points. This framework is based on two proposed methods for implicit surface fitting and polygonization to convert a cloud of unorganized points into an optimized surface. The proposed fitting method employs the partition of unity (POU) method associated with the radial basis functions (RBF) over a distributed computing environment to facilitate and speedup fitting of large scale clouds without any data reduction to preserve all the surface details. Moreover, an innovative adaptive mesh refinement (AMR) based method is proposed for implicit surface polygonization. This method steers adaptive volume sampling via a series of optimization criteria to provide accurate and optimized surfaces with minimum number of polygons. The experimental results for the considered test models showed an average reduction of 60% in fitting time using 16 processing nodes and 90% in polygonization time on the master node only against other traditional methods with better performance.",
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"abstract": "Fit TC-Bezier surface with radial base function neural network, and build a radial base function network model which is suitable for surface reconstruction. A method is proposed in this paper, which suggests how to denoise and reconstructing free surface with radial base function neural network. This method simulates the internal relation between the points on surface using the study and training of scattered points made by neural cell. The result of simulation experiment shows that this model has strong capability of fitting surface, keeping the topological characteristic of the original points basically, and it also has function of smoothing noise. Besides, the speed of studying is fast and it can get surface of good fairness.",
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"abstract": "Neural network arithmetic was employed in incomplete points cloud data surface reconstruction, Radial basis function neural network and simulated annealing arithmetic was combined. The new arithmetic can approach any nonlinear function by arbitrary precision, and also keep the network from getting into local minimum. Global optimization feature of simulated annealing was employed to adjust the network weights. MATLAB program was compiled, experiments on incomplete points cloud data have been done employing this arithmetic, the result shows that this arithmetic can efficiently approach the surface with 10<sup>-4</sup> mm error precision, and also the learning speed is quick and the reconstruction surface is smooth. Different methods have been employed to do surface reconstruction in comparison, the results illustrate the error employed algorithmic proposed in the paper is little and converge speed is quick.",
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"abstract": "This paper presents a new approach for visually mining multivariate datasets and especially large ones. This unsupervised approach proposes to mix a SOM approach and a pixel-oriented visualization. The map is considered as a set of connected pixels, the space filling is driven by the SOM algorithm, and the color of each pixel is computed directly from data using an approach proposed by Blanchard et al. The method visually summarizes the data and helps in understanding its inner structure.",
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"fullName": "Cyril De Runz",
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"fullName": "Michel Herbin",
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"abstract": "Kohonen's self-organizing map is an unsupervised machine learning method designed to preserve the topology of its input space. Although this method has been used to efficiently summarize multidimensional data, the visualization of its constituent data has received less attention. We propose a method of addressing the visualization problem by augmenting a classical self-organizing map visualization to include an embedded histogram and evaluate its utility in depicting the self-organizing maps's constituents categorized by a discrete variable.",
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"affiliation": "Louisiana State University Shreveport,Dept. of Computer Science,Shreveport,LA,United States",
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{
"affiliation": "Louisiana State University Health Shreveport,Dept. of Pharmacology, Toxicolology, and Neuroscience,Shreveport,LA,United States",
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{
"proceeding": {
"id": "12OmNvRU0le",
"title": "Geometric Modeling and Processing",
"acronym": "gmp",
"groupId": "1000306",
"volume": "0",
"displayVolume": "0",
"year": "2000",
"__typename": "ProceedingType"
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"article": {
"id": "12OmNAXxXba",
"doi": "10.1109/GMAP.2000.838265",
"title": "Fast Conversion of Dynamic B-Spline Curves into a Set of Power Form Polynomial Curves",
"normalizedTitle": "Fast Conversion of Dynamic B-Spline Curves into a Set of Power Form Polynomial Curves",
"abstract": "Computation of the characteristic points such as inflection points or cusp on a curve is often necessary in CAGD applications. When a curve is represented in a B-spline form, such computations can be made easier once it is transformed in a set of polynomial curves in a power form. Once a curve is represented in a power form, a point evaluation can be also made faster due to Horner's rule even though some issues of stability remains. In addition, the implicitization process of a parametric curve using a resultant usually requires the geometry represented in a power form.Usual practice of the transformation of a B-spline curve into a set of piecewise polynomial curves in a power form is done by either a knot refinement followed by basis conversions, or applying a Taylor expansion on the B-spline curve for each knot span.Presented in this paper is a new algorithm, called Direct Expansion, for the problem. The algorithm first locates the coefficients of all the linear terms that make up the basis functions in a knot span, and then the algorithm directly obtains the power form representation of basis functions by expanding the summation of products of appropriate linear terms. Then, a polynomial segment of a knot span can be easily obtained by the summation of products of the basis functions within the knot span with corresponding control points. Repeating this operation for each knot span, all of the polynomials of the B-spline curve can be transformed into a power form.Experiment shows that the proposed algorithm outperforms the conventional approach when the degree of a given B-spline curve is relatively low. However, when one or more control points of a B-spline curve is continuously moving, the computational gain for the same problem turns out to be much more significant. Therefore, the presented algorithm can be very useful for the curve and surface implicitization as well as intersections when the curves or surfaces are dynamically changing.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Computation of the characteristic points such as inflection points or cusp on a curve is often necessary in CAGD applications. When a curve is represented in a B-spline form, such computations can be made easier once it is transformed in a set of polynomial curves in a power form. Once a curve is represented in a power form, a point evaluation can be also made faster due to Horner's rule even though some issues of stability remains. In addition, the implicitization process of a parametric curve using a resultant usually requires the geometry represented in a power form.Usual practice of the transformation of a B-spline curve into a set of piecewise polynomial curves in a power form is done by either a knot refinement followed by basis conversions, or applying a Taylor expansion on the B-spline curve for each knot span.Presented in this paper is a new algorithm, called Direct Expansion, for the problem. The algorithm first locates the coefficients of all the linear terms that make up the basis functions in a knot span, and then the algorithm directly obtains the power form representation of basis functions by expanding the summation of products of appropriate linear terms. Then, a polynomial segment of a knot span can be easily obtained by the summation of products of the basis functions within the knot span with corresponding control points. Repeating this operation for each knot span, all of the polynomials of the B-spline curve can be transformed into a power form.Experiment shows that the proposed algorithm outperforms the conventional approach when the degree of a given B-spline curve is relatively low. However, when one or more control points of a B-spline curve is continuously moving, the computational gain for the same problem turns out to be much more significant. Therefore, the presented algorithm can be very useful for the curve and surface implicitization as well as intersections when the curves or surfaces are dynamically changing.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Computation of the characteristic points such as inflection points or cusp on a curve is often necessary in CAGD applications. When a curve is represented in a B-spline form, such computations can be made easier once it is transformed in a set of polynomial curves in a power form. Once a curve is represented in a power form, a point evaluation can be also made faster due to Horner's rule even though some issues of stability remains. In addition, the implicitization process of a parametric curve using a resultant usually requires the geometry represented in a power form.Usual practice of the transformation of a B-spline curve into a set of piecewise polynomial curves in a power form is done by either a knot refinement followed by basis conversions, or applying a Taylor expansion on the B-spline curve for each knot span.Presented in this paper is a new algorithm, called Direct Expansion, for the problem. The algorithm first locates the coefficients of all the linear terms that make up the basis functions in a knot span, and then the algorithm directly obtains the power form representation of basis functions by expanding the summation of products of appropriate linear terms. Then, a polynomial segment of a knot span can be easily obtained by the summation of products of the basis functions within the knot span with corresponding control points. Repeating this operation for each knot span, all of the polynomials of the B-spline curve can be transformed into a power form.Experiment shows that the proposed algorithm outperforms the conventional approach when the degree of a given B-spline curve is relatively low. However, when one or more control points of a B-spline curve is continuously moving, the computational gain for the same problem turns out to be much more significant. Therefore, the presented algorithm can be very useful for the curve and surface implicitization as well as intersections when the curves or surfaces are dynamically changing.",
"fno": "05620337",
"keywords": [
"Power Form",
"Basis Conversion",
"Polynomial",
"B Spline",
"Dynamic Curve"
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"authors": [
{
"affiliation": "Hanyang University",
"fullName": "Deok-Soo Kim",
"givenName": "Deok-Soo",
"surname": "Kim",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Hanyang University",
"fullName": "Joonghyun Ryu",
"givenName": "Joonghyun",
"surname": "Ryu",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Hanyang University",
"fullName": "Taeboom Jang",
"givenName": "Taeboom",
"surname": "Jang",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Hongik University",
"fullName": "Hyunchan Lee",
"givenName": "Hyunchan",
"surname": "Lee",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Chrysler Corporation",
"fullName": "Hayong Shin",
"givenName": "Hayong",
"surname": "Shin",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Dongguk University",
"fullName": "Joonyoung Park",
"givenName": "Joonyoung",
"surname": "Park",
"__typename": "ArticleAuthorType"
}
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"pubDate": "2000-04-01T00:00:00",
"pubType": "proceedings",
"pages": "337",
"year": "2000",
"issn": null,
"isbn": "0-7695-0562-7",
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{
"proceeding": {
"id": "12OmNCbCrVP",
"title": "Environmental Science and Information Application Technology, International Conference on",
"acronym": "esiat",
"groupId": "1002836",
"volume": "1",
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"year": "2009",
"__typename": "ProceedingType"
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"article": {
"id": "12OmNBNM8XZ",
"doi": "10.1109/ESIAT.2009.22",
"title": "Two Kinds of Trigonometric Spline Curves with Shape Parameter",
"normalizedTitle": "Two Kinds of Trigonometric Spline Curves with Shape Parameter",
"abstract": "Two kinds of trigonometric spline curves with shape parameter are presented in this paper. The trigonometric spline curves are constructed with three consecutive control points for each curve segment. The given curves posses many properties of the quadratic B-spline curve. Meanwhile, they have many better properties than the quadratic B-spline curve. The first kind of curve is continuous with equidistant knot vector, and it is continuous with special shape parameter. The second kind of curve is continuous with equidistant knot vector. The shape parameter can adjust the given curves’ shape with the same control polygon. With the increase of the shape parameter, the trigonometric spline curves approximate to the control polygon. The given curves can be closer to the control polygon than the quadratic B-spline curve. In the last, the trigonometric spline surfaces with shape parameter are also constructed and they have most properties of the corresponding trigonometric spline curves.",
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"content": "One of the major problems in the generation of skinning B-spline surfaces is the incompatibility of the cross-sectional curves. This occurs when the cross sections are defined by control polygons having different number of control vertices. Traditionally, this incompatibility problem is overcome by knot insertion that makes all control polygons have equal number of vertices. The drawback of this solution is that it can very quickly lead to an explosion in the number of vertices of the control mesh defining the skinning surface. In this paper, we show that this problem can be rectified through the use of subdivision surfaces. We describe an approach to generate a skinning Catmull-Clark subdivision surface through incompatible cross-sections of cubic B-spline curves. The resulting surface has all the properties of subdivision surfaces while requiring a smaller number of control points than those obtained through the more conventional techniques.",
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"abstract": "This paper deals with the problem of matching and recognizing planar curves which are modeled as B-splines. The paper presents a fast algorithm for estimating the control points of the B-spline which is robust to nonuniform sampling and noise. Curve matching is achieved by using the similarity measure based on the knot points associated with the B-spline curves. This method, however, can not handle the affine transformation and/or occlusion between the curves. This paper presents solutions to these two problems through the use of a new class of weighted B-spline curve moments that results in (1) a closed-form solution for the affine transformation parameters; (2) the starting and ending points of the segment on the prototype curve that was affine transformed to yield the observed curve. The method is used for classifying affine transformed silhouette of aircrafts, and appears to perform well.<>",
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"title": "Optimization of Knots for the Multi Curve B-Spline Approximation",
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"abstract": "This article presents a method for multi curve approximation with B-spline. The approximation is formulated as a constrained optimization problem with the least squares error as the objective function and the knot vector as the variables. The method presented in this article is designed to eliminate the well-known lethargic behavior and to maintain the accuracy of control points. The method for fitting skeletal curves was tested on a single-section case and a multi-section case. The tests showed that the method reduces the objective function significantly. The proposed method has potential applications in the shape design of wings, turbine blades, and automotive body panels.",
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"affiliation": "University of Diponegoro",
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"affiliation": "University of Waterloo",
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"abstract": "The B-spline curve is one of the most famous curves in computer graphics, computational geometry and CAGD. Developing more convenient techniques for designing and modifying B-spline curves is an important problem, and is also an important research issue. In this study, the shape modification of B-spline curves by geometric constraints is presented. A new method based on changing the control points of the curves via constrained optimization is proposed. To satisfy the given constraints, the shape of the curves is optimally modified with adjusting control points of the original B-spline curves. Finally, numerical examples are also given.",
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"content": "The B-spline curve is one of the most famous curves in computer graphics, computational geometry and CAGD. Developing more convenient techniques for designing and modifying B-spline curves is an important problem, and is also an important research issue. In this study, the shape modification of B-spline curves by geometric constraints is presented. A new method based on changing the control points of the curves via constrained optimization is proposed. To satisfy the given constraints, the shape of the curves is optimally modified with adjusting control points of the original B-spline curves. Finally, numerical examples are also given.",
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"id": "proceedings/esiat/2009/3682/1/3682a553",
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"id": "proceedings/bife/2009/3705/0/3705a660",
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"article": {
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"doi": "10.1109/CGI.1997.601292",
"title": "An Interpolation Subspline Scheme Related to B-Spline Techniques",
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"abstract": "We construct (integral) interpolating subspline curves for given data points and the knot vector. The algorithm is very close to B spline approximation. The idea is to blend interpolating Lagrangian splines using B spline techniques. Everything is connected in an affinely invariant way with the control points and the knot vector. We are able to show that our scheme produces high quality subsplines, which include known procedures like Overhauser or quintic interpolation schemes. In addition we may sweep to B splines and return in a very lucid way. Examples show the power of the method. The given procedure allows generalisations to rational subsplines and to tensor product interpolating surfaces.",
"abstracts": [
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"content": "We construct (integral) interpolating subspline curves for given data points and the knot vector. The algorithm is very close to B spline approximation. The idea is to blend interpolating Lagrangian splines using B spline techniques. Everything is connected in an affinely invariant way with the control points and the knot vector. We are able to show that our scheme produces high quality subsplines, which include known procedures like Overhauser or quintic interpolation schemes. In addition we may sweep to B splines and return in a very lucid way. Examples show the power of the method. The given procedure allows generalisations to rational subsplines and to tensor product interpolating surfaces.",
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"normalizedAbstract": "We construct (integral) interpolating subspline curves for given data points and the knot vector. The algorithm is very close to B spline approximation. The idea is to blend interpolating Lagrangian splines using B spline techniques. Everything is connected in an affinely invariant way with the control points and the knot vector. We are able to show that our scheme produces high quality subsplines, which include known procedures like Overhauser or quintic interpolation schemes. In addition we may sweep to B splines and return in a very lucid way. Examples show the power of the method. The given procedure allows generalisations to rational subsplines and to tensor product interpolating surfaces.",
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"affiliation": "Inst. of Geometry, Tech. Univ. Graz, Austria",
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"doi": "10.1109/BIFE.2009.154",
"title": "Four Kinds of Trigonometric Spline Curves with Shape Parameter",
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"abstract": "Four kinds of trigonometric spline curves with shape parameter are presented in this paper. The trigonometric spline curves are constructed with three consecutive control points for each curve segment. The given curves posses many properties of the quadratic B-spline. Meanwhile, they have many better properties than the quadratic B-spline curve. The given curves have continuity with equidistant knot vector, and they have continuity when choosing special parameters. The shape parameter can adjust the given curves’ shape with the same control polygon. With the increase of the shape parameter, the trigonometric spline curves approximate to the control polygon. The given curves can be closer to the control polygon than the quadratic B-spline curve.",
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"title": "Towards Identification and Mitigation of Task-Based Challenges in Comparative Visualization Studies",
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"abstract": "The effectiveness of a visualization technique is dependent on how well it supports the tasks or goals of an end-user. To measure the effectiveness of a visualization technique, researchers often use a comparative study design. In a comparative study, two or more visualization techniques are compared over a set of tasks and commonly measure human performance in terms of task accuracy and completion time. Despite the critical role of tasks in comparative studies, the current lack of guidance in existing literature on best practices for task selection and communication of research results in evaluation studies is problematic. In this work, we systematically identify and curate the task-based challenges of comparative studies by reviewing existing visualization literature on the topic. Furthermore, for each of the presented challenges we discuss the potential threats to validity for a comparative study. The challenges discussed in this paper are further backed by evidence identified in a detailed survey of comparative tree visualization studies. Finally, we recommend best practices from personal experience and the surveyed tree visualization studies to provide guidelines for other researchers to mitigate the challenges. The survey data and a free copy of the paper is available at https://osf.io/g3btk/.",
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"authors": [
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"title": "Bring User Feedback into Keyword Search over Databases",
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"abstract": "Keyword Search Over Relational Databases (KSORD) enables casual users to use keyword queries (a set of keywords) to search relational databases just like searching the Web, without any knowledge of the database schema or any need of writing SQL queries. In KSORD, retrieval of user's initial query is often unsatisfying. User has to reformulate his query and execute the new query, which costs much time and effort. A method of automatically reformulating user queries by user feedback aimed at the results of KSORD is introduced in this paper, which is named UFBP (User Feedback Based on Probability). After the first time of retrieval, according to the users' feedback information, UFBP computes terms to be added into the expanded query based on probability and reformulates the new query using query expansion. After KSORD executing the new query automatically, more relevant results are presented to user. Experimental results verify its effectiveness.",
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"content": "Keyword Search Over Relational Databases (KSORD) enables casual users to use keyword queries (a set of keywords) to search relational databases just like searching the Web, without any knowledge of the database schema or any need of writing SQL queries. In KSORD, retrieval of user's initial query is often unsatisfying. User has to reformulate his query and execute the new query, which costs much time and effort. A method of automatically reformulating user queries by user feedback aimed at the results of KSORD is introduced in this paper, which is named UFBP (User Feedback Based on Probability). After the first time of retrieval, according to the users' feedback information, UFBP computes terms to be added into the expanded query based on probability and reformulates the new query using query expansion. After KSORD executing the new query automatically, more relevant results are presented to user. Experimental results verify its effectiveness.",
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"fullName": "Changliang Wang",
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"title": "The NETSPEAK WORDGRAPH: Visualizing keywords in context",
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"abstract": "NETSPEAK helps writers in choosing words while writing a text. It checks for the commonness of phrases and allows for the retrieval of alternatives by means of wildcard queries. To support such queries, we implement a scalable retrieval engine, which returns high-quality results within milliseconds using a probabilistic retrieval strategy. The results are displayed as WORDGRAPH visualization or as a textual list. The graphical interface provides an effective means for interactive exploration of search results using filter techniques, query expansion and navigation. Our observations indicate that, of three investigated retrieval tasks, the textual interface is sufficient for the phrase verification task, wherein both views support context-sensitive word choice, and the WORDGRAPH best supports the exploration of a phrase's context or the underlying corpus. The preferred view for context-sensitive word choice seems to depend on query complexity (i.e. the number of wildcards in a query).",
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"affiliation": "Virtual Reality Systems Group, Bauhaus-Universität Weimar, Germany",
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"title": "2006 IEEE International Conference on Multimedia and Expo",
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"title": "Combining Textual and Visual Ontologies to Solve Medical Multimodal Queries",
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"abstract": "In order to solve medical multimodal queries, we propose to split the queries in different dimensions using ontology. We extract both textual and visual terms depending on the ontology dimension they belong to. Based on these terms, we build different sub queries each corresponds to one query dimension. Then we use Boolean expressions on these sub queries to filter the entire document collection. The filtered document set is ranked using the techniques in vector space model. We also combine the ranked lists generated using both text and image indexes to further improve the retrieval performance. We have achieved the best overall performance for the medical image retrieval task in CLEF 2005. These experimental results show that while most queries are better handled by the text query processing as most semantic information are contained in the medical text cases, both textual and visual ontology dimensions are complementary in improving the results during media fusion",
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"affiliation": "Centre Universitaire d'Informatique, 24, rue Général-Dufour, CH-1211 Genève 4, Switzerland. Said.Radhouani@cui.unige.ch",
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"affiliation": "IPAL Lab, Institute for Infocomm Research, 21 Heng Mui Keng Terrace, Singapore 119613",
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"affiliation": "IPAL Lab, Institute for Infocomm Research, 21 Heng Mui Keng Terrace, Singapore 119613",
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"affiliation": "Centre Universitaire d'Informatique, 24, rue Général-Dufour, CH-1211 Genève 4, Switzerland",
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"abstract": "Is there an effect of Virtual Reality (VR) Head-Mounted Display (HMD) on the user's mental effort? In this paper, we compare the mental effort in VR versus in real environments. An experiment (N=27) was conducted to assess the effect of being immersed in a virtual environment (VE) using an HMD on the user's mental effort while performing a standardized cognitive task (the well-known N-back task, with three levels of difficulty, N ∈ {1,2,3}). In addition to test the effect of the environment (i.e., virtual versus real), we also explored the impact of performing a dual task (i.e., sitting versus walking) in both environments on mental effort. The mental effort was assessed through self-report, task performance, behavioural and physiological measures. In a nutshell, the analysis of all measurements revealed no significant effect of being immersed in the VE on the users' mental effort. In contrast, natural walking significantly increased the users' mental effort. Taken together, our results support the fact there is no specific additional mental effort related to the immersion in a VE using a VR HMD.",
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"abstract": "Cervical cancer is a leading severe malignancy throughout the world. Molecular processes and biomarkers leading to tumor progression in cervical cancer are either unknown or only partially understood. An increasing number of studies have shown that microRNAs play an important role in tumorigenesis so understanding the regulatory mechanism of miRNAs in gene-regulatory network will help elucidate the complex biological processes that occur during malignancy. Identification of microRNA-messengerRNA (miRNA-mRNA) regulatory modules will aid deciphering aberrant transcriptional regulatory network in cervical cancer but is computationally challenging. In this regard, an algorithm, termed as relevant and functionally consistent miRNA-mRNA modules (RFCM3), is proposed. It integrates miRNA and mRNA expression data of cervical cancer for identification of potential miRNA-mRNA modules. It selects a miRNA-mRNA module by maximizing relation of mRNAs with miRNA and functional similarity between selected mRNAs. Later using the knowledge of miRNA-miRNA synergistic network different modules are fused and finally a set of modules are generated containing several miRNAs as well as mRNAs. This type of module explains the underlying biological pathways containing multiple miRNAs and mRNAs. The effectiveness of the proposed approach over other existing methods has been demonstrated on a miRNA and mRNA expression data of cervical cancer with respect to enrichment analyses and other standard metrices. The proposed approach was found to generate more robust, integrated, and functionally enriched miRNA-mRNA modules in cervical cancer.",
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"content": "Cervical cancer is a leading severe malignancy throughout the world. Molecular processes and biomarkers leading to tumor progression in cervical cancer are either unknown or only partially understood. An increasing number of studies have shown that microRNAs play an important role in tumorigenesis so understanding the regulatory mechanism of miRNAs in gene-regulatory network will help elucidate the complex biological processes that occur during malignancy. Identification of microRNA-messengerRNA (miRNA-mRNA) regulatory modules will aid deciphering aberrant transcriptional regulatory network in cervical cancer but is computationally challenging. In this regard, an algorithm, termed as relevant and functionally consistent miRNA-mRNA modules (RFCM3), is proposed. It integrates miRNA and mRNA expression data of cervical cancer for identification of potential miRNA-mRNA modules. It selects a miRNA-mRNA module by maximizing relation of mRNAs with miRNA and functional similarity between selected mRNAs. Later using the knowledge of miRNA-miRNA synergistic network different modules are fused and finally a set of modules are generated containing several miRNAs as well as mRNAs. This type of module explains the underlying biological pathways containing multiple miRNAs and mRNAs. The effectiveness of the proposed approach over other existing methods has been demonstrated on a miRNA and mRNA expression data of cervical cancer with respect to enrichment analyses and other standard metrices. The proposed approach was found to generate more robust, integrated, and functionally enriched miRNA-mRNA modules in cervical cancer.",
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"title": "Quantifying Explainers of Graph Neural Networks in Computational Pathology",
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"abstract": "Explainability of deep learning methods is imperative to facilitate their clinical adoption in digital pathology. However, popular deep learning methods and explainability techniques (explainers) based on pixel-wise processing disregard biological entities’ notion, thus complicating comprehension by pathologists. In this work, we address this by adopting biological entity-based graph processing and graph explainers enabling explanations accessible to pathologists. In this context, a major challenge becomes to discern meaningful explainers, particularly in a standardized and quantifiable fashion. To this end, we propose herein a set of novel quantitative metrics based on statistics of class separability using pathologically measurable concepts to characterize graph explainers. We employ the proposed metrics to evaluate three types of graph explainers, namely the layer-wise relevance propagation, gradient-based saliency, and graph pruning approaches, to explain Cell-Graph representations for Breast Cancer Subtyping. The proposed metrics are also applicable in other domains by using domain-specific intuitive concepts. We validate the qualitative and quantitative findings on the BRACS dataset, a large cohort of breast cancer RoIs, by expert pathologists. The code, data, and models can be accessed here <sup>1</sup>.",
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"content": "Explainability of deep learning methods is imperative to facilitate their clinical adoption in digital pathology. However, popular deep learning methods and explainability techniques (explainers) based on pixel-wise processing disregard biological entities’ notion, thus complicating comprehension by pathologists. In this work, we address this by adopting biological entity-based graph processing and graph explainers enabling explanations accessible to pathologists. In this context, a major challenge becomes to discern meaningful explainers, particularly in a standardized and quantifiable fashion. To this end, we propose herein a set of novel quantitative metrics based on statistics of class separability using pathologically measurable concepts to characterize graph explainers. We employ the proposed metrics to evaluate three types of graph explainers, namely the layer-wise relevance propagation, gradient-based saliency, and graph pruning approaches, to explain Cell-Graph representations for Breast Cancer Subtyping. The proposed metrics are also applicable in other domains by using domain-specific intuitive concepts. We validate the qualitative and quantitative findings on the BRACS dataset, a large cohort of breast cancer RoIs, by expert pathologists. The code, data, and models can be accessed here <sup>1</sup>.",
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"abstract": "The depth images acquired by consumer depth sensors (e.g., Kinect and ToF) usually are of low resolution and insufficient quality. One natural solution is to incorporate with high resolution RGB camera for exploiting their statistical correlation. However, most existing methods are intuitive and limited in characterizing the complex and dynamic dependency between intensity and depth images. To address these limitations, we propose a weighted analysis representation model for guided depth image enhancement, which advances the conventional methods in two aspects: (i) task driven learning and (ii) dynamic guidance. First, we generalize the analysis representation model by including a guided weight function for dependency modeling. And the task-driven learning formulation is introduced to obtain the optimized guidance tailored to specific enhancement task. Second, the depth image is gradually enhanced along with the iterations, and thus the guidance should also be dynamically adjusted to account for the updating of depth image. To this end, stage-wise parameters are learned for dynamic guidance. Experiments on guided depth image upsampling and noisy depth image restoration validate the effectiveness of our method.",
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"content": "The depth images acquired by consumer depth sensors (e.g., Kinect and ToF) usually are of low resolution and insufficient quality. One natural solution is to incorporate with high resolution RGB camera for exploiting their statistical correlation. However, most existing methods are intuitive and limited in characterizing the complex and dynamic dependency between intensity and depth images. To address these limitations, we propose a weighted analysis representation model for guided depth image enhancement, which advances the conventional methods in two aspects: (i) task driven learning and (ii) dynamic guidance. First, we generalize the analysis representation model by including a guided weight function for dependency modeling. And the task-driven learning formulation is introduced to obtain the optimized guidance tailored to specific enhancement task. Second, the depth image is gradually enhanced along with the iterations, and thus the guidance should also be dynamically adjusted to account for the updating of depth image. To this end, stage-wise parameters are learned for dynamic guidance. Experiments on guided depth image upsampling and noisy depth image restoration validate the effectiveness of our method.",
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"content": "The guidance and control of net-recovery UAV based on airborne electro-optical vision guidance are proposed, because of disadvantages of the low precision, security and the dependence of data link in general recovery approaches. Optical visual guidance system is installed on the UAV, which can provide line of sight angle information for the net-recovery flight. In order to make UAV recover precisely along the expected glide path, guidance and control with line-of-sight angle of the net-recovery UAV was raised, designing strong anti-jamming control structure. Direct force control was adopted in the longitudinal control of the net-recovery UAV, increasing the agility of control. Dynamic parameter adjustment of control law based on the distance between the UAV and net was designed, which guaranteed the stability of whole recovery process. The aircraft recovery simulation of verified the guidance plan and the precision of small net-recovery UAV control.",
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"title": "TrajForesee: How limited detailed trajectories enhance large-scale sparse information to predict vehicle trajectories?",
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"abstract": "Foreseeing detailed vehicle future trajectories collectively enables a large scope of urban applications such as route planning and commercial advertising. Existing methods focused on predicting future trajectories of urban vehicles with their own fine-grained historical trajectories. Unfortunately, in real-world scenarios, fine-grained trajectories provided by GPS are limited to obtain due to privacy issues and business competitions. In this paper, our solution enables the ubiquitous but coarse-grained location-based surveillance information to predict the fine-grained trajectories of all vehicles with limited number of fine-grained trajectories. We first capture the vectorized semantic representation of trajectories by training the spatiotemporal embedding in large coarse trajectory set. Then, we propose a new measurement to calculate the trajectory similarity, which combines the vehicles' historical behavior similarity and short-term trajectory similarity. The obtained trajectory similarity is then seamlessly embedded into the dynamic graph convolution network in the manner of spatial attention. The dynamic graph convolution sequence-to-sequence module and the fully-connected layer are devised to generate final sequential trajectory predictions. The whole process is to train in a multi-task framework. Extensive experiments on real-world datasets show the excellent performance of our method.",
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"content": "With the development of satellite navigation, communication and positioning technology, more and more trajectory data are collected and stored. Exploring such trajectory data can help us understand human mobility. A typical task of group-level mobility modeling is trajectory clustering. However, trajectories usually vary in length and shape, also contain noises. These exert a negative influence on trajectory representation and thus hinder trajectory clustering. Therefore, this paper proposes a U-type robust sparse autoencoder model(uRSAA), which is robust against noise and form variety. Specifically, a sparsity penalty is applied to constrain the output to decrease the effect of noise. By introducing skip connections, our model can strengthen the data exchange and preserve the information. Experiments are conducted on both synthetic datasets and real datasets, and the results show that our model outperforms the existing models.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "With the development of satellite navigation, communication and positioning technology, more and more trajectory data are collected and stored. Exploring such trajectory data can help us understand human mobility. A typical task of group-level mobility modeling is trajectory clustering. However, trajectories usually vary in length and shape, also contain noises. These exert a negative influence on trajectory representation and thus hinder trajectory clustering. Therefore, this paper proposes a U-type robust sparse autoencoder model(uRSAA), which is robust against noise and form variety. Specifically, a sparsity penalty is applied to constrain the output to decrease the effect of noise. By introducing skip connections, our model can strengthen the data exchange and preserve the information. Experiments are conducted on both synthetic datasets and real datasets, and the results show that our model outperforms the existing models.",
"fno": "186500a260",
"keywords": [
"Data Analysis",
"Feature Extraction",
"Neural Nets",
"Pattern Clustering",
"Satellite Navigation",
"Positioning Technology",
"Trajectory Data",
"Group Level Mobility Modeling",
"Trajectory Clustering",
"U Type Robust Sparse Autoencoder Model",
"U RSAA",
"Satellites",
"Shape",
"Geology",
"Information Processing",
"Feature Extraction",
"Satellite Navigation Systems",
"Data Models",
"Mobility Modeling",
"Trajectory Clustering",
"Autoencoder"
],
"authors": [
{
"affiliation": "Wuhan University of Technology,Wuhan,China,430070",
"fullName": "Xiaofeng Wu",
"givenName": "Xiaofeng",
"surname": "Wu",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Wuhan University of Technology,Wuhan,China,430070",
"fullName": "Rui Zhang",
"givenName": "Rui",
"surname": "Zhang",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Wuhan University of Technology,Wuhan,China,430070",
"fullName": "Lin Li",
"givenName": "Lin",
"surname": "Li",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "mipr",
"isOpenAccess": false,
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"hasPdf": true,
"pubDate": "2021-09-01T00:00:00",
"pubType": "proceedings",
"pages": "260-266",
"year": "2021",
"issn": null,
"isbn": "978-1-6654-1865-2",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
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