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"abstract": "With the rapid growth of the computer applications, multitudinous procedures were developed for the prediction of the strength and fractures of various materials in engineering applications. A finite element simulation of composite woven reinforcement forming requires the knowledge of the fabric mechanical behavior. In the presented microscopic approach, the plain weaved glass fabric/epoxy laminates were investigated, the tensile mechanical behavior of the Represent Volume Elementary (RVE, in the microscopic level) are used in a finite element made of woven meshes. The meshed elements were established parametrically according to the microscopic geometry of the yarns. By means of finite element software ANSYS, the components of the RVE were meshed into 8 node-solid elements. The Modules and strength of the RVE were predicted by numerical analysis. The results show that simulated modulus coincides well with the equivalent stiffness method and test results; the predicted strength conforms to the tensile test results.",
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"abstract": "A mathematical model for contaminant species passing through fractured porous media is presented. In the numerical model, we combine two locally conservative methods, i.e. mixed finite element (MFE) and the finite volume (FV) methods. Adaptive triangle mesh is used for effective treatment of the fractures. A hybrid MFE method is employed to provide an accurate approximation of velocities field for both the fractures and matrix which are crucial to the convection part of the transport equation. The FV method and the standard MFE method are used to approximate the convection and dispersion terms respectively. Numerical examples in a medium containing fracture network illustrate the robustness and efficiency of the proposed numerical model.",
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"content": "A mathematical model for contaminant species passing through fractured porous media is presented. In the numerical model, we combine two locally conservative methods, i.e. mixed finite element (MFE) and the finite volume (FV) methods. Adaptive triangle mesh is used for effective treatment of the fractures. A hybrid MFE method is employed to provide an accurate approximation of velocities field for both the fractures and matrix which are crucial to the convection part of the transport equation. The FV method and the standard MFE method are used to approximate the convection and dispersion terms respectively. Numerical examples in a medium containing fracture network illustrate the robustness and efficiency of the proposed numerical model.",
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"title": "On the Impact Fracture Simulations of Automotive Laminated Glass",
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"abstract": "In this work, we review three kinds of numerical algorithms, namely the discrete element method (DEM), the coupling discrete element and finite element method (DEM/FEM) and the cohesive zone model (CZM), for the impact fracture simulations of automotive laminated glass. Based on the non-continuum theory, the DEM is capable of modeling the impact fracture phenomenon. However, this method is very time-consuming. To remedy this shortcoming, we have been devoted to combining the discrete element method and the finite element method. Another notable work is to simulate the impact fracture behaviors by using the CZM. Some future works concerning this research aspect are also presented.",
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"content": "In this work, we review three kinds of numerical algorithms, namely the discrete element method (DEM), the coupling discrete element and finite element method (DEM/FEM) and the cohesive zone model (CZM), for the impact fracture simulations of automotive laminated glass. Based on the non-continuum theory, the DEM is capable of modeling the impact fracture phenomenon. However, this method is very time-consuming. To remedy this shortcoming, we have been devoted to combining the discrete element method and the finite element method. Another notable work is to simulate the impact fracture behaviors by using the CZM. Some future works concerning this research aspect are also presented.",
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"title": "Customized anatomically adjusted plate for fixation of mandible internal fractures",
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"abstract": "Mandible internal fractures are a common injury because of the mandible's lack of structural support. For the treatment of such injuries various fixation elements are used. In order to improve quality of the orthodontists interventions anatomically correct and geometrically accurate customized implants are necessary. In this paper an example of accurate geometrical model of the customized plate implant for the fixation of mandible fracture is presented. For the creation of such model new method has been developed. This method is based on reverse engineering techniques applied on the CT scan of the specific patient mandible. With the application of this method it is possible to create geometrical model of the customized plate implant which geometry and topology conforms to the shape of the mandible of the specific patient. The side of the implant, which is in contact with a periosteum outer layer of the mandible, is fully aligned with the shape of the mandible outer surface near the fracture. The obtained model(s) can be used for production of plate implants, and/or for simulation of orthodontist interventions.",
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"content": "Mandible internal fractures are a common injury because of the mandible's lack of structural support. For the treatment of such injuries various fixation elements are used. In order to improve quality of the orthodontists interventions anatomically correct and geometrically accurate customized implants are necessary. In this paper an example of accurate geometrical model of the customized plate implant for the fixation of mandible fracture is presented. For the creation of such model new method has been developed. This method is based on reverse engineering techniques applied on the CT scan of the specific patient mandible. With the application of this method it is possible to create geometrical model of the customized plate implant which geometry and topology conforms to the shape of the mandible of the specific patient. The side of the implant, which is in contact with a periosteum outer layer of the mandible, is fully aligned with the shape of the mandible outer surface near the fracture. The obtained model(s) can be used for production of plate implants, and/or for simulation of orthodontist interventions.",
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"title": "Tracking Fractures of Deformable Objects in Real-Time with an RGB-D Sensor",
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"abstract": "This paper introduces a method able to track in real-time a 3D elastic deformable objects which undergo fractures, using the point cloud data provided by an RGB-D sensor. Our framework relies on a prior visual segmentation of the object in the image. The segmented point cloud is registered by non-rigidly fitting the mesh, based on the Finite Element Method to physically model elasticity, and on geometrical point-to-point correspondences to compute external forces exerted on the mesh. Fractures are handled by processing the stress tensors computed on the mesh of the FEM model, in order to detect fracturable nodes. Local remeshing around fracturable nodes is then performed to propagate the fracture. The real-time performance of the system is demonstrated on real data involving various deformations and fractures.",
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"content": "This paper introduces a method able to track in real-time a 3D elastic deformable objects which undergo fractures, using the point cloud data provided by an RGB-D sensor. Our framework relies on a prior visual segmentation of the object in the image. The segmented point cloud is registered by non-rigidly fitting the mesh, based on the Finite Element Method to physically model elasticity, and on geometrical point-to-point correspondences to compute external forces exerted on the mesh. Fractures are handled by processing the stress tensors computed on the mesh of the FEM model, in order to detect fracturable nodes. Local remeshing around fracturable nodes is then performed to propagate the fracture. The real-time performance of the system is demonstrated on real data involving various deformations and fractures.",
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"fullName": "Bruno Siciliano",
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"title": "Tibial Plateau Fracture: Mathematical Model to Correlate Agent Force Trauma",
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"abstract": "The present paper, based on a bio-engineering application, intends to apply the mathematical model in the treatment and diagnosis of tibial plateau fractures. Therefore, we focused on the method of finite elements (MFE), which is the general method of solving differential equations with partial derivates that describe physical phenomena. The thus carried out mathematical simulation has revealed the different types of fracture as well as the durability of given mountings, outlining both their advantages and disadvantages.",
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"abstract": "Due to its unobservability, randomness and staggered complexity, we cannot well understand the real form and distribution of the natural fracture of the rock in the deep strata, leading to a series of construction problems in the exploration and development of oil. At present, the geometry of fractures is displayed by the form of two-dimensional graph or data table, which cannot be performed more visually. In light of this finding, through the data analysis of fractures collected from the engineering practice, using the Monte Carlo method and a variety of programming languages, this paper has performed three-dimensional visualization of macroscopic fractures around wellbore underground. The data collected from Keshen block in Tarim oil field is simulatedand its results show that the simulation of the three-dimensional geometry of the fractures has achieved a good visual effect and provided a visualization of platform for further research such as wellbore stability about fractureformation.",
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"content": "Due to its unobservability, randomness and staggered complexity, we cannot well understand the real form and distribution of the natural fracture of the rock in the deep strata, leading to a series of construction problems in the exploration and development of oil. At present, the geometry of fractures is displayed by the form of two-dimensional graph or data table, which cannot be performed more visually. In light of this finding, through the data analysis of fractures collected from the engineering practice, using the Monte Carlo method and a variety of programming languages, this paper has performed three-dimensional visualization of macroscopic fractures around wellbore underground. The data collected from Keshen block in Tarim oil field is simulatedand its results show that the simulation of the three-dimensional geometry of the fractures has achieved a good visual effect and provided a visualization of platform for further research such as wellbore stability about fractureformation.",
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"title": "2021 5th International Conference on Vision, Image and Signal Processing (ICVISP)",
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"title": "Numerical Simulation of Fracture Propagation in Bedded Shale Based on Cohesive Zone Model",
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"abstract": "based on the global embedded cohesive zone model, the finite element model of complex hydraulic fracture (HF) propagation in layered shale is established in this paper. Considering the effects of fluid flow/geological stress coupling, pore elastic deformation and back stress, the effects of stratification approach angle, horizontal stress difference, displacement and fracturing fluid viscosity on the morphology of complex HF were studied based on the model. The results show that when the bedding approach angle is greater than 45°, it is more likely to form complex fractures through the bedding, and when the bedding approach angle is less than 45°, it is more likely to form simple fractures along the bedding direction. When the approach angle is 45°, HF tend to form simple fractures captured by bedding under low stress difference, and simple fractures that extend along bedding after passing through partial bedding under high stress difference. In the case of moderate stress difference, it is more likely to form complex cracks that extend through and along the bedding. The increase in the flow rate and the viscosity of the fracturing fluid can lead to the formation of more fractures across the bedding, higher fracture complexity and greater maximum fracture opening.",
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"content": "based on the global embedded cohesive zone model, the finite element model of complex hydraulic fracture (HF) propagation in layered shale is established in this paper. Considering the effects of fluid flow/geological stress coupling, pore elastic deformation and back stress, the effects of stratification approach angle, horizontal stress difference, displacement and fracturing fluid viscosity on the morphology of complex HF were studied based on the model. The results show that when the bedding approach angle is greater than 45°, it is more likely to form complex fractures through the bedding, and when the bedding approach angle is less than 45°, it is more likely to form simple fractures along the bedding direction. When the approach angle is 45°, HF tend to form simple fractures captured by bedding under low stress difference, and simple fractures that extend along bedding after passing through partial bedding under high stress difference. In the case of moderate stress difference, it is more likely to form complex cracks that extend through and along the bedding. The increase in the flow rate and the viscosity of the fracturing fluid can lead to the formation of more fractures across the bedding, higher fracture complexity and greater maximum fracture opening.",
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"keywords": [
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"affiliation": "Southwest Petroleum University,State Key Laboratory of Oil-Gas Reservoir Geology & Exploitation,Chengdu,China",
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"affiliation": "Shengli Oilfield Dongsheng Jinggong Petroleum Development Group Co., Ltd.,Dongying,China",
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"affiliation": "Shengli Oilfield Dongsheng Jinggong Petroleum Development Group Co., Ltd.,Dongying,China",
"fullName": "Shouxing Kang",
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"affiliation": "Shengli Oilfield Dongsheng Jinggong Petroleum Development Group Co., Ltd.,Dongying,China",
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"affiliation": "Shengli Oilfield Dongsheng Jinggong Petroleum Development Group Co., Ltd.,Dongying,China",
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"title": "2008 IEEE International Test Conference",
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"doi": "10.1109/TEST.2008.4700634",
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"abstract": "The self-assembly of nanoelectronic devices provides an opportunity to achieve unprecedented density and manufacturing scale in the post-Moore's Law era. Bottom-up DNA self-assembly has emerged as a promising technique towards achieving this vision and it has been used to demonstrate precise patterning and functionalization at resolutions below 20 nm. However, a lack of understanding of fabrication defects and their impact on circuit behavior are major obstacles to the eventual application of these substrates to circuit design. We present a classification of defects observed in our experimental work on self-assembled nanostructures. Atomic force microscope (AFM) images are used to study these defects and determine their relative frequencies. We connect these defects to fault models and predict their likely impact on the behavior of logic gates. This work will be useful in predicting the potential success of defect-tolerance techniques for DNA self-assembled nanoelectronic substrates.",
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"content": "The self-assembly of nanoelectronic devices provides an opportunity to achieve unprecedented density and manufacturing scale in the post-Moore's Law era. Bottom-up DNA self-assembly has emerged as a promising technique towards achieving this vision and it has been used to demonstrate precise patterning and functionalization at resolutions below 20 nm. However, a lack of understanding of fabrication defects and their impact on circuit behavior are major obstacles to the eventual application of these substrates to circuit design. We present a classification of defects observed in our experimental work on self-assembled nanostructures. Atomic force microscope (AFM) images are used to study these defects and determine their relative frequencies. We connect these defects to fault models and predict their likely impact on the behavior of logic gates. This work will be useful in predicting the potential success of defect-tolerance techniques for DNA self-assembled nanoelectronic substrates.",
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"abstract": "We propose an extension of van Lamsweerde's goal-oriented requirements engineering to the domain of programmable DNA nanotechnology. This is a domain in which individual devices (agents) are at most a few dozen nanometers in diameter. These devices are programmed to assemble themselves from molecular components and perform their assigned tasks. The devices carry out their tasks in the probabilistic world of chemical kinetics, so they are individually error-prone. However, the number of devices deployed is roughly on the order of a nanomole (a 6 followed by fourteen 0s), and some goals are achieved when enough of these agents achieve their assigned subgoals. We show that it is useful in this setting to augment the AND/OR goal diagrams to allow goal refinements that are mediated by threshold functions, rather than ANDs or ORs. We illustrate this method by engineering requirements for a system of molecular detectors (DNA origami “pliers” that capture target molecules) invented by Kuzuya, Sakai, Yamazaki, Xu, and Komiyama (2011). We model this system in the Prism probabilistic symbolic model checker, and we use Prism to verify that requirements are satisfied, provided that the ratio of target molecules to detectors is neither too high nor too low. This gives prima facie evidence that software engineering methods can be used to make DNA nanotechnology more productive, predictable and safe.",
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"affiliation": "Department of Computer Science, Iowa State University, Ames, IA 50011 USA",
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"affiliation": "Department of Genetics, Development, and Cell Biology, Iowa State University, Ames, IA 50011 USA",
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"affiliation": "Department of Genetics, Development, and Cell Biology, Iowa State University, Ames, IA 50011 USA",
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"affiliation": "Department of Computer Science, Iowa State University, Ames, IA 50011 USA",
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"abstract": "As development of high-throughput and low-cost sequencing technologies is leading to massive volumes of genomic data, new solutions for handling data-intensive applications on parallel platforms are urgently required. Particularly, the nature of processing leads to both load balancing and I/O contention challenges. In this paper, we have developed a novel middleware system, RE-PAGE, which allows parallelization of applications that process genomic data with a simple, high-level API. To address load balancing and I/O contention, the features of the middleware include: 1) use of domain-specific information in the formation of data chunks (which can be of non-uniform sizes), 2) replication and placement of each chunk on a small number of nodes, performed in an intelligent way, and 3) scheduling schemes for achieving load balance, when data movement costs out-weigh processing costs and the chunks are of non-uniform sizes. We have evaluated our framework using three genomic applications, which are VarScan, Unified Genotyper, and Coverage Analyzer. We show that our approach leads to better performance than conventional MapReduce scheduling approaches and systems that access data from a centralized store. We also compare against popular frameworks, Hadoop and GATK, and show that our middleware outperforms both, achieving high parallel efficiency and scalability.",
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"abstract": "Digital competences, such as advanced scientific computing and data mining tools, are often anchored in domain specific research areas. There is a substantial overlap of data types generated from the different fields of science, and hence there is a possibility for sharing knowledge and tools across disciplines. Mapping of software programming tools and identification of use cases that includes High Performance Computing (HPC) may serve as inspiration in order to bring new value of domain specific data in an interdisciplinary way. This poster share the experience from Denmark based on software mapping in 290 publications that included use of HPC.",
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"abstract": "Facial animation has contributed to many fields such as movies, computer games, education and e-commerce. Facial animation is obtained in two ways: pre-calculated animation and real-time animation. Pre-calculated animation often produces very realistic results with very powerful computer systems and is often used for animated movies. Real-time animation often produces lower quality results due to the real-time requirements and is often used for interactive applications. We propose in this paper a real-time animation method which operates on a 2D image of face. We simulate the effect of facial muscles with image warping techniques. Our method can produce realistic facial expressions and can be easily deployed on not very strong environments such as web pages, mobile phones and PDAs.",
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"abstract": "In this paper we introduce a Facial Animation system using real three-dimensional models of people, acquired by a 3D scanner. We consider a dataset composed by models displaying different facial expressions and a linear interpolation technique is used to produce a smooth transition between them. One-to-one correspondences between the meshes of each facial expression are required in order to apply the interpolation process. Instead of focusing in the computation of dense correspondence, some points are selected and a triangulation is defined, being refined by consecutive subdivisions, that compute the matchings of intermediate points. We are able to animate any model of the dataset, given its texture information for the neutral face and the geometry information for all the expressions along with the neutral face. This is made by computing matrices with the variations of every vertex when changing from the neutral face to the other expressions. The knowledge of the matrices obtained in this process makes it possible to animate other models given only the texture and geometry information of the neutral face. Furthermore, the system uses 3D reconstructed models, being capable of generating a three-dimensional facial animation from a single 2D image of a person. Also, as an extension of the system, we use artificial models that contain expressions of visemes, that are not part of the expressions of the dataset, and their displacements are applied to the real models. This allows these models to be given as input to a speech synthesis application in which the face is able to speak phrases typed by the user. Finally, we generate an average face and increase the displacements between a subject from the dataset and the average face, creating, automatically, a caricature of the subject.",
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"content": "In this paper we introduce a Facial Animation system using real three-dimensional models of people, acquired by a 3D scanner. We consider a dataset composed by models displaying different facial expressions and a linear interpolation technique is used to produce a smooth transition between them. One-to-one correspondences between the meshes of each facial expression are required in order to apply the interpolation process. Instead of focusing in the computation of dense correspondence, some points are selected and a triangulation is defined, being refined by consecutive subdivisions, that compute the matchings of intermediate points. We are able to animate any model of the dataset, given its texture information for the neutral face and the geometry information for all the expressions along with the neutral face. This is made by computing matrices with the variations of every vertex when changing from the neutral face to the other expressions. The knowledge of the matrices obtained in this process makes it possible to animate other models given only the texture and geometry information of the neutral face. Furthermore, the system uses 3D reconstructed models, being capable of generating a three-dimensional facial animation from a single 2D image of a person. Also, as an extension of the system, we use artificial models that contain expressions of visemes, that are not part of the expressions of the dataset, and their displacements are applied to the real models. This allows these models to be given as input to a speech synthesis application in which the face is able to speak phrases typed by the user. Finally, we generate an average face and increase the displacements between a subject from the dataset and the average face, creating, automatically, a caricature of the subject.",
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"abstract": "Research on the full Steiner tree problem in the Euclidean plane R2 has important theoretic significance, and it also has broad applications in material construction, VLSI design, WDM optical networks and wireless communications. In this paper, combining with the material construction and the actual cost, we introduce two new variants of the full Steiner tree problem in the Euclidean plane R2: the minimumlength full Steiner tree problem (MLFST, for short) and the minimum-number of Steiner points in the full Steiner tree problem (MNPFST, for short). These problems are both NP-hard, and we design one approximation algorithm for each of them which have important applications in real life. To enhance the convenience of application, a subdivision procedure method and a minimum disk cover of points method are adopted in some designed algorithms.",
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"content": "Research on the full Steiner tree problem in the Euclidean plane R2 has important theoretic significance, and it also has broad applications in material construction, VLSI design, WDM optical networks and wireless communications. In this paper, combining with the material construction and the actual cost, we introduce two new variants of the full Steiner tree problem in the Euclidean plane R2: the minimumlength full Steiner tree problem (MLFST, for short) and the minimum-number of Steiner points in the full Steiner tree problem (MNPFST, for short). These problems are both NP-hard, and we design one approximation algorithm for each of them which have important applications in real life. To enhance the convenience of application, a subdivision procedure method and a minimum disk cover of points method are adopted in some designed algorithms.",
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"abstract": "This paper proposes Steiner-based algorithms to extend already deployed tenant slices or Virtualized Network Functions Forwarding Graphs (or Service Function Chains) as demand grows or additional services are appended to prior service functions and chains. The tenant slices are hosted by Network Function Virtualization Infrastructure (NVFI) providers that can make use of the proposed algorithms to extend tenant slices on demand for growing traffic loads and service extensions including protection and security services(such as extending a slice with a dedicated security slice). The paper proposes a Steiner-based ILP as an exact solution for small graphs and Steiner based approximation algorithms to improve scalability for larger problems.",
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"content": "This paper proposes Steiner-based algorithms to extend already deployed tenant slices or Virtualized Network Functions Forwarding Graphs (or Service Function Chains) as demand grows or additional services are appended to prior service functions and chains. The tenant slices are hosted by Network Function Virtualization Infrastructure (NVFI) providers that can make use of the proposed algorithms to extend tenant slices on demand for growing traffic loads and service extensions including protection and security services(such as extending a slice with a dedicated security slice). The paper proposes a Steiner-based ILP as an exact solution for small graphs and Steiner based approximation algorithms to improve scalability for larger problems.",
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"abstract": "This paper studies a variant of the Steiner tree problem in the Euclidean plane ℝ<sup>2</sup>: the minimum-number of a specific material for the full Steiner tree problem (MNFST, for short). This question is an extension of the Steiner tree problem and the full Steiner tree problem. It has a wide range of applications in real life. The MNFST has been shown to be NP-hard. In this paper, we propose two asymptotic polynomial-time approximation algorithms for this problem. These two algorithms satisfy OUT ≤ 2.428OPT + 1 and Z_$OUT \\leq 2.123sOPT + \\frac{3}{2}$_Z, respectively.",
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"abstract": "Genetic algorithms, owning to their characteristics of intrinsic parallel mechanism and full optimization, can be used to search for solutions for objective programming. In this study, empirical study method was combined with the multi-objective optimization to develop a multi-objective forest harvest adjustment model by introducing Pareto multi-objective genetic algorithm into optimization model. This methodology was applied to Fengshu Mountain tree farm, Jiangxi province and the obtained results showed that integrating of the genetic algorithm with the multi-objective programming of the forest harvest adjustment led to non-inferior solution set which provided much greater choice space for decision-making. Moreover, this method overcame the shortcomings that exist in the original harvest adjustment procedure in which different objective weight values are needed. In addition, the genetic algorithm successfully achieved the adjustment of Masson Pine age-class area and balancing rate as well as increased volume and volume yield per unit area.",
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"content": "Genetic algorithms, owning to their characteristics of intrinsic parallel mechanism and full optimization, can be used to search for solutions for objective programming. In this study, empirical study method was combined with the multi-objective optimization to develop a multi-objective forest harvest adjustment model by introducing Pareto multi-objective genetic algorithm into optimization model. This methodology was applied to Fengshu Mountain tree farm, Jiangxi province and the obtained results showed that integrating of the genetic algorithm with the multi-objective programming of the forest harvest adjustment led to non-inferior solution set which provided much greater choice space for decision-making. Moreover, this method overcame the shortcomings that exist in the original harvest adjustment procedure in which different objective weight values are needed. In addition, the genetic algorithm successfully achieved the adjustment of Masson Pine age-class area and balancing rate as well as increased volume and volume yield per unit area.",
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"normalizedAbstract": "Genetic algorithms, owning to their characteristics of intrinsic parallel mechanism and full optimization, can be used to search for solutions for objective programming. In this study, empirical study method was combined with the multi-objective optimization to develop a multi-objective forest harvest adjustment model by introducing Pareto multi-objective genetic algorithm into optimization model. This methodology was applied to Fengshu Mountain tree farm, Jiangxi province and the obtained results showed that integrating of the genetic algorithm with the multi-objective programming of the forest harvest adjustment led to non-inferior solution set which provided much greater choice space for decision-making. Moreover, this method overcame the shortcomings that exist in the original harvest adjustment procedure in which different objective weight values are needed. In addition, the genetic algorithm successfully achieved the adjustment of Masson Pine age-class area and balancing rate as well as increased volume and volume yield per unit area.",
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"affiliation": "Res. Center of Spatial Inf. & Digital Eng., Wuhan Univ., Wuhan, China",
"fullName": "Daisheng Tang",
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"affiliation": "Coll. of forestry, Central South Univ. of Forestry & Technol., Changsha, China",
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"title": "Investigating the influence of thunderstorms on atmospheric electric field potential gradient variations",
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"abstract": "In this paper, we simultaneously investigate daily variations of the atmospheric electric field during thunderstorms and lightning parameters within the zone of representative operation of electric field mills, to allow for detailed spatial-temporal analysis of electric field variations. For this purpose, we develop a firmware complex for processing of experimental data of the lightning sensor and electric field mill networks, and software implementations for data mining, transferring and processing of the relevant data. Experimental results of atmospheric electric fields during lightning of different polarities are discussed.",
"abstracts": [
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"content": "In this paper, we simultaneously investigate daily variations of the atmospheric electric field during thunderstorms and lightning parameters within the zone of representative operation of electric field mills, to allow for detailed spatial-temporal analysis of electric field variations. For this purpose, we develop a firmware complex for processing of experimental data of the lightning sensor and electric field mill networks, and software implementations for data mining, transferring and processing of the relevant data. Experimental results of atmospheric electric fields during lightning of different polarities are discussed.",
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"fno": "07760183",
"keywords": [
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"Discharges Electric",
"Atmospheric Measurements",
"Clouds",
"Geophysical Measurements",
"Monitoring"
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"fullName": "Anatoly Adzhiev",
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"fullName": "Iakov Korovin",
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{
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"abstract": "Spot detection is an important step in 2D-GE image analysis. The results of Spot detection may substantially influence subsequent stages of gel image analysis. However, in current suggested methods, the detection of spot in complex regions are far from satisfactory. This paper provides an effective method to raise the accuracy of spot detection in complex regions where many protein spots are overlapped. The proposed method firstly employs the Euclidean distance transform to estimate the spot centroids in complex regions and locates new centroids using the geodesic distance measure, then split the spot regions based on geodesic distances according the estimated spot centroids. compared with the existing method, experiments indicated the suggested method has good and efficient performance in the gel detection task.",
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"affiliation": "Institute for Information and System Science, Xi'an Jiaotong University, Xi'an, Shaan'xi, P. R. China, dymeng@mail.xjtu.edu.cn",
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"abstract": "Both prominent feature points and geodesic distance are key factors for mesh segmentation. With these two factors, this paper proposes a graph cut based mesh segmentation method. The mesh is first preprocessed by Laplacian smoothing. According to the Gaussian curvature, candidate feature points are then selected by a predefined threshold. With DBSCAN (Density-Based Spatial Clustering of Application with Noise), the selected candidate points are separated into some clusters, and the points with the maximum curvature in every cluster are regarded as the final feature points. We label these feature points, and regard the faces in the mesh as nodes for graph cut. Our energy function is constructed by utilizing the ratio between the geodesic distance and the Euclidean distance of vertex pairs of the mesh. The final segmentation result is obtained by minimizing the energy function using graph cut. The proposed algorithm is pose-invariant and can robustly segment the mesh into different parts in line with the selected feature points.",
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"content": "Both prominent feature points and geodesic distance are key factors for mesh segmentation. With these two factors, this paper proposes a graph cut based mesh segmentation method. The mesh is first preprocessed by Laplacian smoothing. According to the Gaussian curvature, candidate feature points are then selected by a predefined threshold. With DBSCAN (Density-Based Spatial Clustering of Application with Noise), the selected candidate points are separated into some clusters, and the points with the maximum curvature in every cluster are regarded as the final feature points. We label these feature points, and regard the faces in the mesh as nodes for graph cut. Our energy function is constructed by utilizing the ratio between the geodesic distance and the Euclidean distance of vertex pairs of the mesh. The final segmentation result is obtained by minimizing the energy function using graph cut. The proposed algorithm is pose-invariant and can robustly segment the mesh into different parts in line with the selected feature points.",
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"fullName": "Lei Liu",
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"abstract": "Semi-supervised learning based on manifolds has been the focus of extensive research in recent years. Convenient neighbourhood graph construction is a key component of a successful semi-supervised classification method. Previous graph construction methods fail when there are pairs of data points that have small Euclidean distance, but are far apart over the manifold. To overcome this problem, we start with an arbitrary neighbourhood graph and iteratively update the edge weights by using the estimates of the geodesic distances between points. Moreover, we provide theoretical bounds on the values of estimated geodesic distances. Experimental results on real-world data show significant improvement compared to the previous graph construction methods.",
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"abstractType": "Regular",
"content": "Semi-supervised learning based on manifolds has been the focus of extensive research in recent years. Convenient neighbourhood graph construction is a key component of a successful semi-supervised classification method. Previous graph construction methods fail when there are pairs of data points that have small Euclidean distance, but are far apart over the manifold. To overcome this problem, we start with an arbitrary neighbourhood graph and iteratively update the edge weights by using the estimates of the geodesic distances between points. Moreover, we provide theoretical bounds on the values of estimated geodesic distances. Experimental results on real-world data show significant improvement compared to the previous graph construction methods.",
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"abstract": "With the popularity of 3D sensors in self-driving and other robotics applications, extensive research has focused on designing novel neural network architectures for accurate 3D point cloud completion. However, unlike point cloud classification and reconstruction, the role of adversarial samples in 3D point cloud completion has seldom been explored. In this work, we demonstrate that adversarial samples can benefit neural networks on 3D point cloud completion tasks. We propose a novel approach to craft adversarial samples that improve the performance of models on both clean and adversarial inputs. In contrast to the Projected Gradient Descent (PGD) attack, our method generates adversarial samples that keep the geometric features in clean samples and contain few outliers. In particular, we use minimum absolute curvature directions to constrain the adversarial perturbations for each input point. The gradient components in the minimum absolute curvature directions are taken as adversarial perturbations. In addition, we adopt attack strength accumulation and auxiliary Batch Normalization layers to speed up the training process and alleviate the distribution mismatch between clean and adversarial samples. Experimental results demonstrate that training with the adversarial samples crafted by our method under the geometric-aware constraint effectively enhances the performance of the Point Completion Network (PCN) on the ShapeNet dataset.",
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"content": "With the popularity of 3D sensors in self-driving and other robotics applications, extensive research has focused on designing novel neural network architectures for accurate 3D point cloud completion. However, unlike point cloud classification and reconstruction, the role of adversarial samples in 3D point cloud completion has seldom been explored. In this work, we demonstrate that adversarial samples can benefit neural networks on 3D point cloud completion tasks. We propose a novel approach to craft adversarial samples that improve the performance of models on both clean and adversarial inputs. In contrast to the Projected Gradient Descent (PGD) attack, our method generates adversarial samples that keep the geometric features in clean samples and contain few outliers. In particular, we use minimum absolute curvature directions to constrain the adversarial perturbations for each input point. The gradient components in the minimum absolute curvature directions are taken as adversarial perturbations. In addition, we adopt attack strength accumulation and auxiliary Batch Normalization layers to speed up the training process and alleviate the distribution mismatch between clean and adversarial samples. Experimental results demonstrate that training with the adversarial samples crafted by our method under the geometric-aware constraint effectively enhances the performance of the Point Completion Network (PCN) on the ShapeNet dataset.",
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"doi": "10.1109/ICISFall51598.2021.9627361",
"title": "Research on Chinese Short Text Segmentation for New Media Comments",
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"abstract": "With the development of new media industry, comments based user interaction is now fairly routine in live broadcasting. User comments usually appear in the form of short text with freestyle and cyber new words. The general word segmentation methods could not adapt to Chinese short text in new media comments. This paper proposes a novel method of Chinese short text segmentation to solve the problem of word segmentation granularity self-adaption. A New Media Comment Short Text Dataset(NMCD) is built for our researches, a word vector text containing cyber new words and entity words as well. Our optimized bidirectional Long Short Term Memory(LSTM) model based on attention mechanism and transfer learning could make number and its unit together after the word segmentation. The experiment results show that the Fl-score is improved by 21.43%. The word segmentation method in this paper could be efficiently applied to the new media comments analysis system later.",
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"abstract": "With the rapid growth of product review forums, discussion groups, and Blogs, it is almost impossible for a customer to make an informed purchase decision. Different and possibly contradictory opinions written by different reviewers can even make customers more confused. In the last few years, mining customer reviews (opinion mining) has emerged as an interesting new research direction to address this need. One of the interesting problem in opinion mining is Opinion Question Answering (Opinion QA). While traditional QA can only answer factual questions, opinion QA aims to find the authors' sentimental opinions on a specific target. Current opinion QA systems suffers from several weaknesses. The main cause of these weaknesses is that these methods can only answer a question if they find a content similar to the given question in the given documents. As a result, they cannot answer majority questions like \"What is the best digital camera?\" nor comparative questions, e.g. \"Does SamsungY work better than CanonX?\". In this paper we address the problem of opinion question answering to answer opinion questions about products by using reviewers' opinions. Our proposed method, called Aspect-based Opinion Question Answering (AQA), support answering of opinion-based questions while improving the weaknesses of current techniques. AQA contains five phases: question analysis, question expansion, high quality review retrieval, subjective sentence extraction, and answer grouping. AQA adopts an opinion mining technique in the preprocessing phase to identify target aspects and estimate their quality. Target aspects are attributes or components of the target product that have been commented on in the review, e.g. 'zoom' and 'battery life' for a digital camera. We conduct experiments on a real life dataset, Epinions.com, demonstrating the improved effectiveness of the AQA in terms of the accuracy of the retrieved answers.",
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"content": "With the rapid growth of product review forums, discussion groups, and Blogs, it is almost impossible for a customer to make an informed purchase decision. Different and possibly contradictory opinions written by different reviewers can even make customers more confused. In the last few years, mining customer reviews (opinion mining) has emerged as an interesting new research direction to address this need. One of the interesting problem in opinion mining is Opinion Question Answering (Opinion QA). While traditional QA can only answer factual questions, opinion QA aims to find the authors' sentimental opinions on a specific target. Current opinion QA systems suffers from several weaknesses. The main cause of these weaknesses is that these methods can only answer a question if they find a content similar to the given question in the given documents. As a result, they cannot answer majority questions like \"What is the best digital camera?\" nor comparative questions, e.g. \"Does SamsungY work better than CanonX?\". In this paper we address the problem of opinion question answering to answer opinion questions about products by using reviewers' opinions. Our proposed method, called Aspect-based Opinion Question Answering (AQA), support answering of opinion-based questions while improving the weaknesses of current techniques. AQA contains five phases: question analysis, question expansion, high quality review retrieval, subjective sentence extraction, and answer grouping. AQA adopts an opinion mining technique in the preprocessing phase to identify target aspects and estimate their quality. Target aspects are attributes or components of the target product that have been commented on in the review, e.g. 'zoom' and 'battery life' for a digital camera. We conduct experiments on a real life dataset, Epinions.com, demonstrating the improved effectiveness of the AQA in terms of the accuracy of the retrieved answers.",
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"abstract": "Passage retrieval of Question Answering (QA) systems aims to find the text segments or sentences that may contain the exact answers for the given question. Previous studies on passage retrieval are mostly utilized a single function to calculate the relevance scores of passages. However, some research has proved that the relations between passages can be utilized to improve the accuracy of relevance evaluation. Hence, a passage retrieval method based on passage-passage graph model is proposed. A KNN-based question expansion method is proposed and then the candidate answer passages are retrieved based on the expanded question model. The passage graph is constructed based on the similarities between the candidate answer passages. Finally, a graph-based ranking model is utilized to re-calculate the relevance scores of the answer passages and the ranking parameter is trained using the learning method. Experiment results show that our method can significantly increase the MRR and TRDR performances compared to the baseline methods.",
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"content": "Passage retrieval of Question Answering (QA) systems aims to find the text segments or sentences that may contain the exact answers for the given question. Previous studies on passage retrieval are mostly utilized a single function to calculate the relevance scores of passages. However, some research has proved that the relations between passages can be utilized to improve the accuracy of relevance evaluation. Hence, a passage retrieval method based on passage-passage graph model is proposed. A KNN-based question expansion method is proposed and then the candidate answer passages are retrieved based on the expanded question model. The passage graph is constructed based on the similarities between the candidate answer passages. Finally, a graph-based ranking model is utilized to re-calculate the relevance scores of the answer passages and the ranking parameter is trained using the learning method. Experiment results show that our method can significantly increase the MRR and TRDR performances compared to the baseline methods.",
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"abstract": "Against steganography to hide secret messages into an innocent-like cover, steganalysis was studied to detect the presence of hidden messages, and steganography flaws were determined by human intervention. In this paper, we present a steganalysis method using deep learning for spatial domain steganography which does not require human intervention. The deep learning-based steganalysis model is designed to have 1 high pass filter, 2 convolutional layers and 2 full connected layers. After being trained with cover images and LSB stego-images, unknown images are tested to determine if secret messages have been embedded. Experiments are performed using BOSS and SIPI database and the presented model shows 98% and 90% accuracy for LSB stego-images with the same key and different keys.",
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"abstract": "While Cryptography is the science of secure communication, Steganography is the art of covert communication. Steganography has a long history, but modern steganography uses digital carriers such as electronic text, disk space, network packets, digital audio and images to hide secrets. Steganalysis, the countermeasure to steganography, is designed to detect and analyse the hidden data disseminated using steganography. This paper reviews and compares three steganalysis techniques: the Histogram Characteristic Function (HCF) technique, the Regular-Singular analysis (RS) technique, and Raw Quick Pair (RQP) technique. The paper analyses the performance, characteristics, and limitations of these three techniques, supported by empirical evidence.",
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"abstract": "In this paper, an effective steganalysis method based on Markov transition matrix is proposed to attacking the advanced JPEG steganographic schemes. As the horizontal and vertical scan modes failed to detect F5 steganography with low imbedding-rate, zigzag scanning pattern is developed to arrange both DCT (Discrete Cosine Transform) blocks and coefficients in each block. Difference computation was applied on the arranged JPEG 2-D array, which enhanced the variation caused by data embedding. Threshold and truncation techniques are utilized to make the computational complexity of the proposed method manageable. Bidirectional Markov matrix is exploited to capture the correlations between the adjacent coefficients in both intra-block and inter-block senses, which have been changed during data embedding. Features for steganalysis are derived from intra-block and inter-block Markov transition matrixes. The experiment works have demonstrated the effectiveness of the proposed scheme, which greatly improves the capability of steganalysis, the detection accuracy for each steganography at embedding-rate 0.05 exceeds 95%.",
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"content": "In this paper, an effective steganalysis method based on Markov transition matrix is proposed to attacking the advanced JPEG steganographic schemes. As the horizontal and vertical scan modes failed to detect F5 steganography with low imbedding-rate, zigzag scanning pattern is developed to arrange both DCT (Discrete Cosine Transform) blocks and coefficients in each block. Difference computation was applied on the arranged JPEG 2-D array, which enhanced the variation caused by data embedding. Threshold and truncation techniques are utilized to make the computational complexity of the proposed method manageable. Bidirectional Markov matrix is exploited to capture the correlations between the adjacent coefficients in both intra-block and inter-block senses, which have been changed during data embedding. Features for steganalysis are derived from intra-block and inter-block Markov transition matrixes. The experiment works have demonstrated the effectiveness of the proposed scheme, which greatly improves the capability of steganalysis, the detection accuracy for each steganography at embedding-rate 0.05 exceeds 95%.",
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"abstract": "Text steganography aims to embed hidden messages in text information while the goal of text steganalysis is to identify the existence of hidden information or further uncover the embedded message from the text. Steganalysis has received significant attention recently for the security and privacy purpose. In this paper, we develop unsupervised learning approaches for text steganalysis. In particular, two detection models based on deep learning have been proposed to detect hidden information that may be embedded in text from a global and a local perspective. Extensive studies have been carried out on the Chinese poetry text steganography datasets. It is seen that the proposed models show strong empirical performance in steganographic text detection.",
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"content": "Text steganography aims to embed hidden messages in text information while the goal of text steganalysis is to identify the existence of hidden information or further uncover the embedded message from the text. Steganalysis has received significant attention recently for the security and privacy purpose. In this paper, we develop unsupervised learning approaches for text steganalysis. In particular, two detection models based on deep learning have been proposed to detect hidden information that may be embedded in text from a global and a local perspective. Extensive studies have been carried out on the Chinese poetry text steganography datasets. It is seen that the proposed models show strong empirical performance in steganographic text detection.",
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