Showing papers by "National University of Defense Technology published in 2007"
02 Jul 2007
TL;DR: The experimental results demonstrate that the proposed approach can not only decrease computational complexity, but also localize the duplicated regions accurately even when the image was highly compressed or edge processed.
Abstract: The presence of duplicated regions in the image can be considered as a tell-tale sign for image forgery, which belongs to the research field of digital image forensics. In this paper, a blind forensics approach based on DWT (discrete wavelet transform) and SVD (singular value decomposition) is proposed to detect the specific artifact. Firstly, DWT is applied to the image, and SVD is used on fixed-size blocks of low-frequency component in wavelet sub-band to yield a reduced dimension representation. Then the SV vectors are then lexicographically sorted and duplicated image blocks will be close in the sorted list, and therefore will be compared during the detection steps. The experimental results demonstrate that the proposed approach can not only decrease computational complexity, but also localize the duplicated regions accurately even when the image was highly compressed or edge processed.
330 citations
TL;DR: The KLSPI algorithm provides a general RL method with generalization performance and convergence guarantee for large-scale Markov decision problems (MDPs) and can be applied to online learning control by incorporating an initial controller to ensure online performance.
Abstract: In this paper, we present a kernel-based least squares policy iteration (KLSPI) algorithm for reinforcement learning (RL) in large or continuous state spaces, which can be used to realize adaptive feedback control of uncertain dynamic systems. By using KLSPI, near-optimal control policies can be obtained without much a priori knowledge on dynamic models of control plants. In KLSPI, Mercer kernels are used in the policy evaluation of a policy iteration process, where a new kernel-based least squares temporal-difference algorithm called KLSTD-Q is proposed for efficient policy evaluation. To keep the sparsity and improve the generalization ability of KLSTD-Q solutions, a kernel sparsification procedure based on approximate linear dependency (ALD) is performed. Compared to the previous works on approximate RL methods, KLSPI makes two progresses to eliminate the main difficulties of existing results. One is the better convergence and (near) optimality guarantee by using the KLSTD-Q algorithm for policy evaluation with high precision. The other is the automatic feature selection using the ALD-based kernel sparsification. Therefore, the KLSPI algorithm provides a general RL method with generalization performance and convergence guarantee for large-scale Markov decision problems (MDPs). Experimental results on a typical RL task for a stochastic chain problem demonstrate that KLSPI can consistently achieve better learning efficiency and policy quality than the previous least squares policy iteration (LSPI) algorithm. Furthermore, the KLSPI method was also evaluated on two nonlinear feedback control problems, including a ship heading control problem and the swing up control of a double-link underactuated pendulum called acrobot. Simulation results illustrate that the proposed method can optimize controller performance using little a priori information of uncertain dynamic systems. It is also demonstrated that KLSPI can be applied to online learning control by incorporating an initial controller to ensure online performance.
279 citations
TL;DR: A novel algorithm for image feature extraction, namely, the two-dimensional locality preserving projections (2DLPP), which directly extracts the proper features from image matrices based on locality preserving criterion is proposed.
276 citations
TL;DR: In this article, the iterated unscented Kalman filter (IUKF) is proposed based on the analysis and comparison of conventional nonlinear tracking problem, which can obtain more accurate state and covariance estimation.
Abstract: It is of great importance to develop a robust and fast tracking algorithm in passive localization and tracking system because of its inherent disadvantages such as weak observability and large initial errors. In this correspondence, a new algorithm referred to as the iterated unscented Kalman filter (IUKF) is proposed based on the analysis and comparison of conventional nonlinear tracking problem. The algorithm is developed from UKF but it can obtain more accurate state and covariance estimation. Compared with the traditional approaches (e.g., extended Kalman filter (EKF) and UKF) used in passive localization, the proposed method has potential advantages in robustness, convergence speed, and tracking accuracy. The correctness as well as validity of the algorithm is demonstrated through numerical simulation and experiment results.
204 citations
10 Dec 2007
TL;DR: This paper proposes to design a right-angled triangular checkerboard and to employ the invisible intersection points of the laser range finder's slice plane with the edges of theCheckerboard to set up the constraints equations.
Abstract: This paper presents an effective algorithm for calibrating the extrinsic parameters between a camera and a laser range finder whose trace is invisible. On the basis of an analysis of three possible features, we propose to design a right-angled triangular checkerboard and to employ the invisible intersection points of the laser range finder's slice plane with the edges of the checkerboard to set up the constraints equations. The extrinsic parameters are then calibrated by minimizing the algebraic errors between the measured intersections points and their corresponding projections on the image plane of the camera. We compared our algorithm with the existing methods by both simulations and the real data of a stereo measurement system. The simulation and experimental results confirmed that the proposed algorithm can yield more accurate results.
121 citations
TL;DR: In this paper, the effects of rare-earth elements substitution on microstructural and electromagnetic properties were analyzed and the matching thickness and the reflection loss (RL) of one-layer ferrite absorber were calculated.
119 citations
TL;DR: In this article, the absorbing properties of FSS absorber with cross-shaped resistive patches were studied by finite element method and the calculated results indicate that lattice type, element spacing, cross dipole size, patch sheet resistance and thickness of dielectric substrate all can affect the absorbing performance of the FSS absorbing material.
115 citations
TL;DR: It is shown that the attack information has an important effect on the vulnerability of scale-free networks and that hiding a fraction of the nodes information is a cost-efficient strategy for enhancing the robustness of complex networks.
Abstract: We study the vulnerability of complex networks under intentional attack with incomplete information, which means that one can only preferentially attack the most important nodes among a local region of a network. The known random failure and the intentional attack are two extreme cases of our study. Using the generating function method, we derive the exact value of the critical removal fraction fc of nodes for the disintegration of networks and the size of the giant component. To validate our model and method, we perform simulations of intentional attack with incomplete information in scale-free networks. We show that the attack information has an important effect on the vulnerability of scale-free networks. We also demonstrate that hiding a fraction of the nodes information is a cost-efficient strategy for enhancing the robustness of complex networks.
106 citations
TL;DR: A new controller for controlling a number of feature points on a robot manipulator to trace desired trajectories specified on the image plane of a fixed camera is presented and asymptotic convergence of the image errors to zero is proved by the Lyapunov theory based on the nonlinear robot dynamics.
Abstract: This paper presents a new controller for controlling a number of feature points on a robot manipulator to trace desired trajectories specified on the image plane of a fixed camera. It is assumed that the intrinsic and extrinsic parameters of the camera are not calibrated. A new adaptive algorithm is developed to estimate the unknown parameters online, based on three original ideas. First, we use the pseudoinverse of the depth-independent interaction matrix to map the image errors onto the joint space of the manipulator. By eliminating the depths in the interaction matrix, we can linearly parameterize the closed-loop dynamics of the manipulator. Second, to guarantee the existence of the pseudoinverse, the adaptive algorithm introduces a potential force to drive the estimated parameters away from the values that result in a singular Jacobian matrix. Third, to ensure that the estimated parameters are convergent to their true values up to a scale, we combine the Slotine-Li method with an online algorithm for minimizing the error between the estimated projections and real image coordinates of the feature points. We have proved asymptotic convergence of the image errors to zero by the Lyapunov theory based on the nonlinear robot dynamics. Experiments have been carried out to verify the performance of the proposed controller.
106 citations
TL;DR: A novel center-based nearest neighbor (CNN) classifier is proposed to deal with the pattern classification problems, which is based on the nearest distance from an unknown sample point to a certain CL for classification.
106 citations
TL;DR: In this paper, the complex band structures and attenuation spectra of flexural waves in slender beams with periodically mounted local resonators were investigated with transfer matrix method, and it was observed that the frequency range and attenuant gap become larger in complex band structure if larger resonators are used.
TL;DR: In this paper, a multi-objective optimization of linearized impulsive rendezvous is investigated and this optimization includes the minimum characteristic velocity, the minimum time of flight, and the maximum safety performance index, of which the trajectory safety index is defined as the minimum relative distance between a chaser and a target in the chaser's free-flying path.
Abstract: The multi-objective optimization of linearized impulsive rendezvous is investigated in this paper and this optimization includes the minimum characteristic velocity, the minimum time of flight, and the maximum safety performance index, of which the trajectory safety performance index is defined as the minimum relative distance between a chaser and a target in the chaser's free-flying path. A theoretical model for calculating this safety performance index is provided. The three-objective optimization model is proposed based on the Clohessy-Wiltshire system, wherein a generalized inverse matrix solution for linear equations is applied to avoid handling the terminal equality constraints. The multi-objective nondominated sorting genetic algorithm is employed to obtain the Pareto solution set. The proposed approach is evaluated using the -V-bar homing and +V-bar homing rendezvous missions. It is shown that tradeoffs between time of flight, fuel cost, and passive trajectory safety for rendezvous trajectory is quickly demonstrated by the approach. By identifying multiple solutions, the approach can produce a variety of missions to meet different needs.
25 Jun 2007
TL;DR: This paper proposes a new architecture for the MAF unit that supports multiple IEEE precisions multiply-add operation (AtimesB+C) with Single Instruction Multiple Data (SIMD) feature and shows that it is suitable for processors with floatingpoint unit (FPU).
Abstract: The floating-point multiply-add fused (MAF) unit sets a new trend in the processor design to speed up floatingpoint performance in scientific and multimedia applications. This paper proposes a new architecture for the MAF unit that supports multiple IEEE precisions multiply-add operation (AtimesB+C) with Single Instruction Multiple Data (SIMD) feature. The proposed MAF unit can perform either one double-precision or two parallel single-precision operations using about 18% more hardware than a conventional double-precision MAF unit and with 9% increase in delay. To accommodate the simultaneous computation of two single-precision MAF operations, several basic modules of double-precision MAF unit are redesigned. They are either segmented by precision mode dependent multiplexers or attached by the duplicated hardware. The proposed MAF unit can be fully pipelined and the experimental results show that it is suitable for processors with floatingpoint unit (FPU).
TL;DR: In this paper, the E-characteristic polynomial of an even order supersymmetric tensor is established by using the classical Macaulay formula of resultants, and an upper bound for the degree of that E characterisation is given.
TL;DR: In this article, the authors demonstrate an experiment for remote preparation of arbitrary photon polarization states using spontaneous parametric down-conversion (SPDC) as an entanglement source.
Abstract: We demonstrate an experiment for remote preparation of arbitrary photon polarization states. With local operations, polarization measurement, and one way classical communication, any states lying on and inside the Poincar\'e sphere can be remotely prepared. For arbitrary pure states, the efficiency is 100% with a communication cost of one entanglement bit and two classical bits. For mixed states, polarization insensitive measurement is introduced and the classical communication cost is one bit. Spontaneous parametric down-conversion (SPDC) is employed as an entanglement source. The remotely prepared qubits are estimated via quantum tomography process and fidelity between the experimentally prepared state and the expected state is considered to test the data. We achieve remote preparation of 13 states with fidelities all above 0.994.
TL;DR: The theoretical analysis and experiments prove that the proposed filter can greatly remove decorrelation noise while preserving the fringe phase well, even for those fringes with strong curvatures for InSAR processing.
Abstract: An adaptive contoured window filter is proposed to filter off the noise from phase images of interferometric synthetic aperture radar (InSAR) in this letter. The contoured windows can best satisfy the requirement that constrains the phase signal constant inside windows on which low-pass filtering can remove the noise well while the fringe phases are well preserved. The contoured windows are determined by tracing along the local fringe orientation. An algorithm for determining window sizes adaptive to the fringe density is also proposed. The theoretical analysis and experiments prove that the proposed filter can greatly remove decorrelation noise while preserving the fringe phase well, even for those fringes with strong curvatures for InSAR processing
TL;DR: This paper investigates the impact of transmission opportunity (TXOP) and wireless channel errors on the performance of Enhanced distributed coordination function (EDCF), and proposes a new CAC algorithm that provides the desired throughput and access delay performance.
Abstract: The draft IEEE 802.11e standard aims at providing quality of service (QoS) support in 802.11 wireless local area networks (WLANs). Enhanced distributed coordination function (EDCF), being the fundamental medium access control mechanism in IEEE 802.11e, can only provide service differentiation but offers no QoS guarantees. While service differentiation does not perform well under high traffic load conditions, call admission control (CAC) becomes necessary in order to provide and support the QoS of existing calls. In this paper, we first analyze the saturation throughput and mean access delay performance of differentiated service provided by EDCF. Specifically, we investigate the impact of transmission opportunity (TXOP) and wireless channel errors on the performance of the EDCF. Based on the results from this analysis, we propose a new CAC algorithm that provides the desired throughput and access delay performance. Simulated performance results demonstrate the effectiveness of the proposed CAC algorithm
TL;DR: A novel repeater jamming based on interrupted sampling technique is presented, and the efficiency of thejamming is described and stated as expressions of key parameters which are also beneficial to the jamming design for other coherent radars.
Abstract: Coherent jamming is one of the important trends in modern radar electronic war-fare. High-speed sampling of wideband radio frequency (RF) signals and high iso-lation of two receive-transmit antennas are key technologies for the realization of coherent jamming. However, these technologies present significant challenges to engineering application. In this paper, a novel repeater jamming based on inter-rupted sampling technique is presented. For a jammer with a receive-transmit time-sharing antenna, a radar signal is sampled with a low rate by the jammer. Then, a train of false targets will be achieved after the jamming signal feed the matched filter of a pulse compression radar. For the case of the linear frequency modulated (LFM) pulse compression radars, mathematic principles of the interrupted-sam- pling repeater jamming is developed, and then the efficiency of the jamming is de-scribed and stated as expressions of key parameters which are also beneficial to the jamming design for other coherent radars.
TL;DR: AFCNN has distinct advantages over FCNN in both boundary integrity and recall accuracy, and the performance index Binary_rate is generally much higher for AFCNN than for FCNN when applied to CT liver images.
19 Jun 2007
TL;DR: A mechanism named as DOW (defense and offense wall), which defends against layer-7 attacks using combination of detection technology and currency technology, and an encouragement model that uses client's session rate as currency to defend against session-flooding attacks.
Abstract: Application layer DDoS attacks, which are legitimate in packets and protocols, gradually become a pressing problem for commerce, politics and military. We build an attack model and characterize layer-7 attacks into three classes: session flooding attacks, request flooding attacks and asymmetric attacks. We proposed a mechanism named as DOW (defense and offense wall), which defends against layer-7 attacks using combination of detection technology and currency technology. An anomaly dete-ction method based on K-means clustering is introduced to detect and filter request flooding attacks and asymmetric attacks. To defend against session-flooding attacks, we propose an encouragement model that uses client's session rate as currency. Detection model drops suspicious sessions, while currency model encourages more legitimate sessions. By collaboration of these two models, normal clients could gain higher service rate and lower delay of response time.
11 Jul 2007
TL;DR: This paper explores solutions based on multiple classifiers fusion and not strictly dependent on certain malicious code using the standard signature-based technique for detecting viruses and shows improvement compared to the classification results produced by the individual classifiers.
Abstract: As malicious codes become more complex and sophisticated, the scanning detection method is no longer able to detect various forms of viruses effectively. In this paper, we explore solutions based on multiple classifiers fusion and not strictly dependent on certain malicious code. Motivated by the standard signature-based technique for detecting viruses, we explore the idea of automatically detecting malicious code using the n-gram analysis. After selecting features based on information gain, the probabilistic neural network is used in the process of building and testing the proposed multi-classifiers system. Each one of the individual classifiers is used to produce classification evidences. Then these evidences are combined by the Dempster-Shafer combination rules to form the final classification results for new malicious code. Experimental results produced by the proposed detection engine shows improvement compared to the classification results produced by the individual classifiers.
TL;DR: In this article, the effects of infiltration processes on the microstructure and mechanical properties of 3D-C f /SiC composites were investigated, and the results showed that increasing temperature could reduce the viscosity of the PCS/DVB solution, which was propitious to the infiltration processes.
10 Sep 2007
TL;DR: This paper proves the maximum directional area coverage (MDAC) to be NP-complete and proposes one distributed scheduling algorithm for the MDAC to maximize covered area by scheduling the working directions of the sensors in the network.
Abstract: Unlike traditional omni-directional sensors that always have an omni-angle of sensing range, directional sensors may be able to switch to several directions and each direction has a limited angle of sensing range. Area coverage is still an essential issue in a directional sensor network which consists of a number of directional sensors. In this paper, we study a novel "area coverage by directional sensors" problem. We propose the maximum directional area coverage (MDAC) problem to maximize covered area by scheduling the working directions of the sensors in the network. We prove the MDAC to be NP-complete and propose one distributed scheduling algorithm for the MDAC. Simulation results are also presented to demonstrate the performance of the proposed algorithm.
TL;DR: This review summarizes some new and important advances in the understanding of functional laterality of the cerebellum in primary motor and higher cognitive functions, and proposes that multi-scale connectivity analyses and careful studies of high-level cerebellar functional asymmetry would make an important contribution to theUnderstanding of the human Cerebellum and cerebral neural networks.
Abstract: Recent discoveries on the way in which the cerebellum carries out higher non-motor functions, have stimulated a proliferation of researches into functional integration and neural mechanisms in the cerebellum. Cerebellar functional asymmetry is a special characteristic of cerebellar functional organization and the cerebro-cerebellar circuitry that underlies task performance. Multi-level neuroimaging studies demonstrate that cerebellar functional asymmetry has a rather complex pattern, and may be correlated with practice or certain disorders. In this review, we summarize some new and important advances in the understanding of functional laterality of the cerebellum in primary motor and higher cognitive functions, and highlight the differences in the patterns of cerebellar functional asymmetry in the various functional domains. We propose that cerebellar functional asymmetry may be associated with the pattern of connectivity between a large number of widely distributed brain areas and between special cerebellar functional regions. It is suggested that cerebro-cerebellar circuits in particular play an important role in cerebellar functional asymmetry. Finally, we propose that multi-scale connectivity analyses and careful studies of high-level cerebellar functional asymmetry would make an important contribution to the understanding of the human cerebellum and cerebral neural networks.
09 Jun 2007
TL;DR: The design and implementation of a 64-bit stream processor, FT64 (Fei Teng 64), for scientific computing and a novel stream programming language, SF95 (Stream FORTRAN95), and its compiler,SF95Compiler, are developed to facilitate the development of scientific applications.
Abstract: Stream architecture is a novel microprocessor architecture with wide application potential. But as for whether it can be used efficiently in scientific computing, many issues await further study. This paper first gives the design and implementation of a 64-bit stream processor, FT64 (Fei Teng 64), for scientific computing. The carrying out of 64-bit extension design and scientific computing oriented optimization are described in such aspects as instruction set architecture, stream controller, micro controller, ALU cluster, memory hierarchy and interconnection interface here. Second, two kinds of communications as message passing and stream communications are put forward. An interconnection based on the communications is designed for FT64-based high performance computers. Third, a novel stream programming language, SF95 (Stream FORTRAN95), and its compiler, SF95Compiler (Stream FORTRAN95 Compiler), are developed to facilitate the development of scientific applications. Finally, nine typical scientific application kernels are tested and the results show the efficiency of stream architecture for scientific computing.
TL;DR: It is proved that for each odd positive integer n there are exactly two n-variable symmetric Boolean functions with maximum algebraic immunity.
Abstract: In this note, it is proved that for each odd positive integer n there are exactly two n-variable symmetric Boolean functions with maximum algebraic immunity.
TL;DR: In this paper, the authors investigated the absorption properties induced by localized resonance in phononic crystal and showed that the longitudinal to transverse mode conversion nearby the locally resonant region is an effective way to enhance the anechoic performance.
05 Sep 2007
TL;DR: A video semantic content analysis framework based on ontology is presented and a reasoning algorithm is proposed for events detection and shows promising results.
Abstract: The rapid increase in the available amount of video data is creating a growing demand for efficient methods for understanding and managing it at the semantic level. New multimedia standards, such as MPEG-4 and MPEG-7, provide the basic functionalities in order to manipulate and transmit objects and metadata. But importantly, most of the content of video data at a semantic level is out of the scope of the standards. In this paper, a video semantic content analysis framework based on ontology is presented. Domain ontology is used to define high level semantic concepts and their relations in the context of the examined domain. And low-level features (e.g. visual and aural) and video content analysis algorithms are integrated into the ontology to enrich video semantic analysis. OWL is used for the ontology description. Rules in Description Logic are defined to describe how features and algorithms for video analysis should be applied according to different perception content and low-level features. Temporal Description Logic is used to describe the semantic events, and a reasoning algorithm is proposed for events detection. The proposed framework is demonstrated in a soccer video domain and shows promising results.
TL;DR: In this paper, a non-local viscoelastic foundation model is proposed and used to analyse the dynamics of beams with different boundary conditions using the finite element method, where the reaction of the nonlocal model is obtained as a weighted average of state variables over a spatial domain via convolution integrals with spatial kernel functions that depend on a distance measure.
Abstract: In this paper, a non-local viscoelastic foundation model is proposed and used to analyse the dynamics of beams with different boundary conditions using the finite element method. Unlike local foundation models the reaction of the non-local model is obtained as a weighted average of state variables over a spatial domain via convolution integrals with spatial kernel functions that depend on a distance measure. In the finite element analysis, the interpolating shape functions of the element displacement field are identical to those of standard two-node beam elements. However, for non-local elasticity or damping, nodes remote from the element do have an effect on the energy expressions, and hence the damping and stiffness matrices. The expressions of these direct and cross-matrices for stiffness and damping may be obtained explicitly for some common spatial kernel functions. Alternatively numerical integration may be applied to obtain solutions. Numerical results for eigenvalues and associated eigenmodes of Euler–Bernoulli beams are presented and compared (where possible) with results in literature using exact solutions and Galerkin approximations. The examples demonstrate that the finite element technique is efficient for the dynamic analysis of beams with non-local viscoelastic foundations. Copyright © 2007 John Wiley & Sons, Ltd.
TL;DR: In this paper, a hybrid optimization approach is proposed for the design of a rendezvous-phasing strategy with combined maneuvers, which is normally considered as a complex multiple-impulse, multiple-revolution, nonlinear rendezvous problem.
Abstract: A new hybrid optimization approach is proposed for the design of a rendezvous-phasing strategy with combined maneuvers, which is normally considered as a complex multiple-impulse, multiple-revolution, nonlinear rendezvous problem. In this approach, a feasible iteration optimization model is first formulated using a multiple-revolution Lambert algorithm, and a parallel simulated annealing algorithm is employed to locate the unperturbed solution. Subsequently, an infeasible iteration optimization model accounting for trajectory perturbations is formulated, and a sequential quadratic programming algorithm is used to obtain the perturbed solution, with the unperturbed solution as an initial reference solution. The global convergence ability of the proposed approach is verified by solving a classical same-circle rendezvous problem. Two different solutions satisfying Lawden's necessary optimality conditions are located and one solution outperforms an optimal solution previously reported. The proposed approach is further evaluated in a practical two-day rendezvous-phasing mission with different initial conditions. It is shown that this approach is effective and efficient and the combined maneuvers can save propellant at a range of 4-35% when compared with the special-point maneuvers.