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"abstract": "We propose a novel method, based on the two-pass z-buffer algorithm, to calculate shadows with sufficient precision and efficiency for rendering a daytime landscape with solar penumbrae.The feature of the proposed method is that the precision of the shadows can be preserved to be superior than that of any visible surface by using the appropriate number of plural shadow buffers; it gives a fairly satisfactory trade-off between computation time and quality of shadows.By using the shadow buffers, before calculating solar illuminance we can divide visible surfaces into three types of fragments, that is, bright regions, umbra regions, and the remaining penumbra regions.Thus, we can efficiently render a daytime landscape with sufficient precision of penumbrae because the algorithm can set the calculation points of solar illuminance variably, with their number depending on the type of region they belong to.",
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"abstract": "Object detection is a critical step in automating the monitoring and surveillance tasks. To maximize its reliability, robust algorithms are needed to separate real objects from moving shadows. In this paper we propose a framework for detecting moving shadows caused by moving objects in video, which first learns autonomously and on-line the characteristic features of typical shadow pixels at various parts of the observed scene. The collected knowledge is then used to calibrate itself for the given scene, and to identify shadow pixels in subsequent frames. Experiments show that our system has a good performance, while being more adaptable and using only brightness information.",
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"content": "Object detection is a critical step in automating the monitoring and surveillance tasks. To maximize its reliability, robust algorithms are needed to separate real objects from moving shadows. In this paper we propose a framework for detecting moving shadows caused by moving objects in video, which first learns autonomously and on-line the characteristic features of typical shadow pixels at various parts of the observed scene. The collected knowledge is then used to calibrate itself for the given scene, and to identify shadow pixels in subsequent frames. Experiments show that our system has a good performance, while being more adaptable and using only brightness information.",
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"content": "Abstract: Anti-aliasing in form factor computation and precise determination of shadow boundaries are important issues for Radiosity method. A-Buffer is a technique introduced by Carpenter for anti-aliasing in hidden surface removal. In this paper, we propose a method based on the A-Buffer to replace the Z-buffer in the computation of form factors using the Hemicube for anti-aliasing. The method directly computes shadow boundaries in contrast to the adaptive re-meshing approach. Though the processing of shadow boundaries is not fast, only one discontinuity meshing (no iteration) is required. We implement the method in an infrastructure building design system.",
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"affiliation": "National University of Singapore",
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{
"affiliation": "National University of Singapore",
"fullName": "C. H. Lim",
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{
"affiliation": "National University of Singapore",
"fullName": "H. C. Teh",
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{
"affiliation": "National University of Singapore",
"fullName": "Z. Huang",
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"abstract": "Underwater acoustic sensor networks (UASNs) have been put significant attention recently from both academia and industry for undersea resources exploring and of scientific data gathering in underwater environments. The important characteristic of an underwater acoustic sensor network is that, most underwater acoustic sensor nodes have a certain beam width and a three-dimensional direction, is ignored by the existing underwater routing protocols. This characteristic will reduce the network connectivity and cause a large number of asymmetric links, so it will lead to the sharp decline of the existing protocol performance. We develop a Beam width and Direction Concerned Routing protocol (BDCR) to tackle this problem in UASNs. A key advantage of our protocol is that it can achieve relatively high packet delivery rate and ensure reasonable energy consumption when take into account the impact of the beam width and three-dimensional direction. The proposed protocol is compared with a representative routing protocol for UASNs. The simulation results verify the effectiveness and feasibility of the proposed work.",
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"title": "A Test Based on Beam Angle of Ultrasonic Transducer Array",
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"abstract": "Ultrasonic transducer array is the crucial parts of the audio directional transmission weapon system. Beam angle is also an important performance index. In order to make a change on the disordered actuality of audio signal beam angle test methods, improve the testing efficiency and accuracy, and shorten the testing time, directivity model of ultrasonic transducer array is analyzed in this paper. By a digital simulation, the ranges of the angle and intensity are obtained, and angle step in test was put forward. Through parametric array theoretical calculation and experimental verification, the test distance is acquired. Finally, a new beam angle test method has been proposed. It can be the reference and basis for the beam angle testing of the audio directional transmission weapon system based on ultrasonic transducer array.",
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"content": "Ultrasonic transducer array is the crucial parts of the audio directional transmission weapon system. Beam angle is also an important performance index. In order to make a change on the disordered actuality of audio signal beam angle test methods, improve the testing efficiency and accuracy, and shorten the testing time, directivity model of ultrasonic transducer array is analyzed in this paper. By a digital simulation, the ranges of the angle and intensity are obtained, and angle step in test was put forward. Through parametric array theoretical calculation and experimental verification, the test distance is acquired. Finally, a new beam angle test method has been proposed. It can be the reference and basis for the beam angle testing of the audio directional transmission weapon system based on ultrasonic transducer array.",
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"fno": "9961a255",
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"Acoustic Beams",
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"fullName": "Jia-Xiao Wang",
"givenName": "Jia-Xiao",
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{
"affiliation": null,
"fullName": "Peng Rao",
"givenName": "Peng",
"surname": "Rao",
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{
"affiliation": null,
"fullName": "Guang-Qi Luan",
"givenName": "Guang-Qi",
"surname": "Luan",
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"fullName": "Ming-Zhao Sun",
"givenName": "Ming-Zhao",
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"title": "2017 IEEE 14th International Conference on Mobile Ad Hoc and Sensor Systems (MASS)",
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"abstract": "Transmitting large amounts of data such as videos underwater is an important yet challenging problem in the harsh underwater environment in which radio-frequency waves are absorbed for distances above a few tens of meters, optical waves require narrow laser beams and suffer from scattering and ocean wave motion, and acoustic waves-while being able to propagate up to several tens of kilometers-lead to a communication channel that is very dynamic, prone to fading, spectrum limited with passband bandwidths of only a few tens of kHz, and affected by non-Gaussian noise. Notwithstanding these challenges, a hybrid solution that is capable of transmitting at high data rates underwater via acoustic waves at short/medium distances is proposed. The solution introduces a novel signaling method, called Signal-Space-Frequency Beamforming (SSFB), for a multiple antenna where each antenna consists of Uniform Circular Array (UCA) hydrophones mounted on an underwater vehicle to steer the beam in both azimuth and elevation planes; then, an array of Acoustic Vector Sensors (AVS)-hydrophones that are able to capture the acoustic particle velocity/direction of arrival in addition to measuring regular scalar pressure-are mounted on the surface buoy. Detection is performed based on the beam spatial separation and direction of arrival angles' estimation. Simulation results confirm that this solution outperforms stateof-the-art underwater acoustic transmission techniques, whose data rates are limited only to few tens of kbps.",
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"title": "Towards An Indoor Navigation System Using Monocular Visual SLAM",
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"abstract": "The trackball metaphor is exploited in many applications where volumetric data needs to be explored. Although it provides an intuitive way to inspect the overall structure of objects of interest, an in-detail inspection can be tedious - or when cavities occur even impossible. Therefore we propose a context-aware navigation technique for the exploration of volumetric data. While navigation techniques for polygonal data require information about the rendered geometry, this strategy is not sufficient in the area of volume rendering. Since rendering parameters, e.g., the transfer function, have a strong influence on the visualized structures, they also affect the features to be explored. To compensate for this effect we propose a novel image-based navigation approach for volumetric data. While being intuitive to use, the proposed technique allows the user to perform complex navigation tasks, in particular to get an overview as well as to perform an in-detail inspection without any navigation mode switches. The technique can be easily integrated into raycasting based volume renderers, needs no extra data structures and is independent of the data set as well as the rendering parameters. We will discuss the underlying concepts, explain how to enable the navigation at interactive frame rates using OpenCL, and evaluate its usability as well as its performance.",
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"abstract": "Shuffled Frog Leaping Algorithm(SFLA) is a very popular population-based meta-heuristic algorithm, created by Eusuff and Lansey in 2006. Because of its limited variables and easiness in implementation, it is used in memetics and particle swarm optimization to give several use cases. We believe one unexplored application of this algorithm is in video games, primarily in the genre of action based video games. They involve optimizations in path planning and navigation where SFLA can be utilized. We also believe these games can serve as simulations for real-life scenarios of navigation, thereby giving a virtual environment to enhance this algorithm further. Finally, we compare this method with popular nature based ones such as BFA and SPPSO algorithms and conclude on their optimization efficiency for action maze video games like Pac-Man.",
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"title": "2020 IEEE Symposium on Computers and Communications (ISCC)",
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"title": "Defense Against Advanced Persistent Threats: Optimal Network Security Hardening Using Multi-stage Maze Network Game",
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"abstract": "Advanced Persistent Threat (APT) is a stealthy, continuous and sophisticated method of network attacks, which can cause serious privacy leakage and millions of dollars losses. In this paper, we introduce a new game-theoretic framework of the interaction between a defender who uses limited Security Resources(SRs) to harden network and an attacker who adopts a multi-stage plan to attack the network. The game model is derived from Stackelberg games called a Multi-stage Maze Network Game (M<sup>2</sup>NG) in which the characteristics of APT are fully considered. The possible plans of the attacker are compactly represented using attack graphs(AGs), but the compact representation of the attacker’s strategies presents a computational challenge and reaching the Nash Equilibrium(NE) is NP-hard. We present a method that first translates AGs into Markov Decision Process(MDP) and then achieves the optimal SRs allocation using the policy hill-climbing(PHC) algorithm. Finally, we present an empirical evaluation of the model and analyze the scalability and sensitivity of the algorithm. Simulation results exhibit that our proposed reinforcement learning-based SRs allocation is feasible and efficient.",
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"content": "Advanced Persistent Threat (APT) is a stealthy, continuous and sophisticated method of network attacks, which can cause serious privacy leakage and millions of dollars losses. In this paper, we introduce a new game-theoretic framework of the interaction between a defender who uses limited Security Resources(SRs) to harden network and an attacker who adopts a multi-stage plan to attack the network. The game model is derived from Stackelberg games called a Multi-stage Maze Network Game (M<sup>2</sup>NG) in which the characteristics of APT are fully considered. The possible plans of the attacker are compactly represented using attack graphs(AGs), but the compact representation of the attacker’s strategies presents a computational challenge and reaching the Nash Equilibrium(NE) is NP-hard. We present a method that first translates AGs into Markov Decision Process(MDP) and then achieves the optimal SRs allocation using the policy hill-climbing(PHC) algorithm. Finally, we present an empirical evaluation of the model and analyze the scalability and sensitivity of the algorithm. Simulation results exhibit that our proposed reinforcement learning-based SRs allocation is feasible and efficient.",
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"keywords": [
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"Learning Artificial Intelligence",
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"affiliation": "Chinese Academy of Sciences,Institute of Information Engineering,Beijing,China,100093",
"fullName": "Hangsheng Zhang",
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"affiliation": "Chinese Academy of Sciences,Institute of Information Engineering,Beijing,China,100093",
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"affiliation": "Chinese Academy of Sciences,Institute of Information Engineering,Beijing,China,100093",
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"affiliation": "Chinese Academy of Sciences,Institute of Information Engineering,Beijing,China,100093",
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"abstract": "Presents a method for analysis of nonrigid motion in time sequences of volume images (4D data). In this method, nonrigid motion of the deforming object's contour is dynamically approximated by a deformable surface. In order to reduce the number of parameters describing the deformation, we make use of modal analysis, which provides a spatial smoothing of the surface, and Fourier analysis of the time signals of the main deformation spectrum components, which provides a temporal smoothing. Thus, a complex nonrigid deformation displayed in 4D data is described by very few parameters: the main excited spatial modes and the main Fourier harmonics. Therefore, 4D data can be analyzed and reduced in a very efficient way. The power of the approach is illustrated by results on 4D heart-scan data.<>",
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"abstract": "This paper presents a method for triangulation of 3D points given their projections in two images. Recent results show that the triangulation mapping can be represented as a linear operator K applied to the outer product of corresponding homogeneous image coordinates, leading to a triangulation of very low computational complexity. K can be determined from the camera matrices, together with a so-called blind plane, but we show here that it can be further refined by a process similar to gold standard methods for camera matrix estimation. In particular, it is demonstrated that K can be adjusted to minimize the Euclidean L1 residual 3D error, bringing it down to the same level as the optimal triangulation by Hartley and Sturm. The resulting K optimally fits a set of 2D+2D+3D data where the error is measured in the 3D space. Assuming that this calibration set is representative for a particular application, where later only the 2D points are known, this K can be used for triangulation of 3D points in an optimal way, which in addition is very efficient since the optimization need only be made once for the point set. The refinement of K is made by iteratively reducing errors in the 3D and 2D domains, respectively. Experiments on real data suggests that very few iterations are needed to accomplish useful results.",
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"abstract": "Terrorist attacks do great harm to the economic and social development. Structural perspective provides an explanatory framework for the activities of terrorist organizations which are social network structure. Network centrality are used to to identify key nodes in terrorist organizations. Existing researches often neglect the optimization of centrality indicators by structural holes. By considering structural holes that local factors impact on the overall network. We propose an k-shell based on structural hole method to find key nodes. We conducted experiments on three open source data sets of terrorist organization networks. Compare with the traditional centrality index to prove the effectiveness and accuracy of the algorithm proposed in this paper. The results show that, with the proximity of the center algorithm of the center compared to the number of dielectric, eigenvector centrality, hollow structure and algorithms k-shell value algorithm, the better the improvement in recognition accuracy and discrimination results. The algorithm can be used to identify key nodes in terrorist organizations and provide feasible methods for analyzing and combating terrorist organizations.",
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"abstract": "In order to analyze the network structure of the “East Turkistan” organization and identify members with higher individual threats, so as to conduct a better attack on the “East Turkistan” organization. We use Gephi, a network analysis software, and collect open source information on three batches of 25 terrorists announced by the Ministry of Public Security and use networkX, a Python package to study the structure of complex networks, to conduct social network analysis(SNA) of the “East Turkistan” organization personnel. The “East Turkistan” organization presents a combination of scale-free network and hierarchical network in the topological structure. To manifest the analysis of social network methods' importance in combating terrorism, we simulate the effect of removing the core members of the “East Turkistan” organization. The construction of SNA requires a large deal of open source information. How to obtain intelligence is an important factor that restricts precision strikes. In addition, how to combine social network analysis with computer deep learning knowledge is also a new hot spot and direction in the field of anti-terrorism.",
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"content": "In order to analyze the network structure of the “East Turkistan” organization and identify members with higher individual threats, so as to conduct a better attack on the “East Turkistan” organization. We use Gephi, a network analysis software, and collect open source information on three batches of 25 terrorists announced by the Ministry of Public Security and use networkX, a Python package to study the structure of complex networks, to conduct social network analysis(SNA) of the “East Turkistan” organization personnel. The “East Turkistan” organization presents a combination of scale-free network and hierarchical network in the topological structure. To manifest the analysis of social network methods' importance in combating terrorism, we simulate the effect of removing the core members of the “East Turkistan” organization. The construction of SNA requires a large deal of open source information. How to obtain intelligence is an important factor that restricts precision strikes. In addition, how to combine social network analysis with computer deep learning knowledge is also a new hot spot and direction in the field of anti-terrorism.",
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"abstract": "Large numbers of dimensions not only cause clutter in multi-dimensional visualizations, but also make it difficult for users to navigate the data space. Effective dimension management, such as dimension ordering, spacing and filtering, is critical for visual exploration of such datasets. Dimension ordering and spacing explicitly reveal dimension relationships in arrangement-sensitive multi-dimensional visualization techniques, such as Parallel Coordinates, Star Glyphs, and Pixel-Oriented techniques. They facilitate the visual discovery of patterns within the data. Dimension filtering hides some of the dimensions to reduce clutter while preserving the major information of the dataset. In this paper, we propose an interactive hierarchical dimension ordering, spacing and filtering approach, called DOSFA. DOSFA is based on dimension hierarchies derived from similarities among dimensions. It is a scalable multi-resolution approach making dimensional management a tractable task. On the one hand, it automatically generates default settings for dimension ordering, spacing and filtering. On the other hand, it allows users to efficiently control all aspects of this dimension management process via visual interaction tools for dimension hierarchy manipulation. A case study visualizing a dataset containing over 200 dimensions reveals how our proposed approach greatly improves the effectiveness of high dimensional visualization techniques.",
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"abstract": "Clustering gene expression data is an important task in bioinformatics research and biomedical applications. In this paper, we present an effective clustering algorithm for gene expression data. The clustering algorithm is based on the analysis of data's density distribution. We propose an intersecting partition of gene expression data into the supports of data points. Density clusters are maximally connected regions at certain density levels, and thus, can be organized in a hierarchical structure. For interactive visual exploration, we use a 2D radial layout of the hierarchical density cluster tree with linked as well as embedded views of parallel coordinates and heat maps. Our system supports the understanding of the distribution of density clusters and the patterns of the density clusters. Experimental results for common gene expression data sets shows the effectiveness and scalability of the algorithm.",
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"abstract": "Extensive spread of malicious code on the Internet and also within intranets has risen the user's concern about what kind of data is transferred between her or his computer and other hosts on the network. Visual analysis of this kind of information is a challenging task, due to the complexity and volume of the data type considered, and requires special design of appropriate visualization techniques. In this paper, we present a scalable visualization toolkit for analyzing network activity of computer hosts on a network. The visualization combines network packet volume and type distribution information with geographic information, enabling the analyst to use geographic distortion techniques such as the HistoMap technique to become aware of the traffic components in the course of the analysis. The presented analysis tool is especially useful to compare important network load characteristics in a geographically aware display, to relate communication partners, and to identify the type of network traffic occurring. The results of the analysis are helpful in understanding typical network communication activities, and in anticipating potential performance bottlenecks or problems. It is suited for both off-line analysis of historic data, and via animation for on-line monitoring of packet-based network traffic in real time",
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