Abstract: This paper has proposed a route optimization algorithm to reduce the routing burden and to increase the routes’ life time in VANET (Vehicular ad-hoc network) environment. Then it has been combined into the LAR (Location-aided routing) and AODV (Ad hoc on-demand distance vector routing) protocols to see the performance. After the simulation which has been done by the Qualnet simulator, the result shows much obvious improvement in data transmission.
Abstract: Through the analysis and research on existing trusted software evaluation technology, an evidencedriven framework for trustworthiness evaluation of software based on rules is put forward, rules are used as expression method of trustworthiness evaluation logic, and evidence is used to drive the operation of trustworthiness evaluation process, trustworthiness evidence collection and processing logic as well as mapping method of trustworthiness levels have been encapsulated in rules, and the selection, instantiation, collection, format definition and measurement of trustworthiness evidence are carried out under the guidance of the rules, and the mapping of trustworthiness levels and the analysis of trustworthiness bottleneck are done based on the measured evidence instances, this framework has provided an application implementation scheme for software trustworthiness evaluation.
Abstract: For High performance Digital signal process (HP-DSP) system with low-volume market, performance/ watt, flexibility and cost of design are becoming goals pursued by architects. This paper presents a template-based reconfigurable platformTISA-II, where application-specific stream computing system can be constructed fast, efficiently and conveniently. This paper describes the platform in terms of architecture, programming model, a hardware/software co-design flow, and our implementation. Finally, the paper evaluates TISA-II by a real applications HD H.264 encoding. The results are encouraging, TISA-II with 4 computing node achieves 50～100x speedup over embedded programmable processors (C64 DSP, MIPS) and 3x over dedicated stream processor (Storm), while consequently performance per watt that is also greater.
Abstract: As the transportation system usage grows, there remains of some challenges. On the one hand, the emergence of intelligent transportation system becomes increasingly attractive; on the other hand, researchers are hardly to access real-time and dynamic information about traffics. In this paper, a new solved approach is designed. At first, real-time data on incomplete public traffics are collected via Internet. Then to achieve reliable extracting bus trajectory, the algorithms are proposed that consists of two aspects: trajectory fragments are generated based strong correlation of original data and trajectory fragments are connected with minimum connection distance. To the best of our knowledge, there are the first results for solving these problems, which will lay on data basis for subsequent traffic forecast. At the same time, the proposed algorithm on eliminating abnormal data and tackle with mass data effectively will provide new knowledge and experience for similar research areas.
Abstract: This paper studies the controllability of multi-agent systems with multiple leaders and switching topologies. In this case, we introduce the concept of union graph and reveal that the multi-agent system with switching topologies is controllable if the corresponding system with union graph is controllable. Moreover, we obtain a necessary and sufficient condition for structural controllability of multi-agent systems with multiple leaders and switching topologies. With these conclusions respect to the union graph, some sufficient conditions for controllability of the switching multi-agent systems are shown based on the properties of controllability of multi-agent systems with fixed topology. Three computational tests and an application example are given to demonstrate the effectiveness and the practicability of the results.
Abstract: Recommender systems form an essential part of e-business systems. Collaborative filtering (CF), a widely used technique by recommender systems, performs poorly for cold start users and is vulnerable to shilling attacks. Therefore, a novel CF using kernel methods for prediction is proposed. The method is called Iterative kernelbased CF (IKCF), for it is an iterative process. First, mode or mean is used to smooth the unknown ratings; second, discrete or continuous kernel estimators are used to generate predicted ratings iteratively and to export the predicted ratings in the end. The experimental results on three real-world datasets show that, with IKCF as a booster, the prediction accuracy of recommenders can be significantly improved especially for sparse datasets. IKCF can also achieve high prediction accuracy with a small number of iteration.
Abstract: Parallel test task scheduling is one of the key technologies used in parallel test. A hybrid Particle swarm optimization and Taboo search algorithm (PSO-TS) is proposed to solve parallel test task scheduling with constraints. The scheduling process is divided into two subproblems: task scheduling sequence with constraints and resource optimization. Under the view, the test resource scheduling problem can be solved after the task scheduling with constraints. This can improve the optimization rate of PSO-TS. What is more, a new inertia weight is proposed to enhance exploitation and exploration ability and a new constraint-handling mechanism is used to code during the particle updating for the test task scheduling problem. Simulation results show the suitability of the proposed algorithm in terms of feasibility and effectiveness.
Abstract: By analyzing the characteristics of many E-mail viruses in reality, we address an SHIS (Susceptiblehidden- infected-susceptible) model in this paper. In our model, on the one hand, the state H is introduced, which denotes user receives some E-mails with virus but s/he doesn’t activate them and they aren’t infectious. On the other hand, the topology of E-mail network is considered. The model not only describes better the practical condition of E-mail virus propagation than existing models, but also makes it possible to analyze the users’ behavior. By analyzing the rate equation of the model, we study the epidemic threshold and the equilibrium point. We also present the relationship between the infected density and two important parameters: the percentage of activating Email with virus and the frequency, in which users check the Email box. Finally, some numerical simulations are also presented to show the correctness of theoretical analysis. Our model would help to understand and control E-mail virus spreading.
Abstract: A convex active contour model based on local image statistics is proposed in this paper. By assuming that the intensity distribution of the image pixels in a window is described by a Gaussian distribution, our model is able to segment images with intensity inhomogeneity. Due to the convexity of the proposed model, we introduce a dual formulation to solve the minimization problem and obtain a much efficient method. Experiments show that the segmentation results of the proposed method are similar to that of the non-convex method based on local statistics, but our method is much more efficient.
Abstract: A novel Boosted charge transfer (BCT) circuit is proposed for Bucket-brigade devices (BBDs) based charge-domain (CD) pipelined Analog-to-digital converter (ADC). It can significantly lower the sensitivity on Process, voltage and temperature (PVT) variations of traditional BCT circuit, which can eliminate the Common mode (CM) charge control circuit in the existing CD pipelined ADC. With the proposed BCT circuit, a prototype ADC is realized in a 0.18μm CMOS process without using any common mode charge control techniques, with only 27mW power consumption at 1.8 V supply. It achieves Spurious free dynamic range (SFDR) of 67.7 dB, Signal-to-noiseand- distortion ratio (SNDR) of 55.8 dB and Effective number of bits (ENOB) of 9.0 for a 3.79 MHz input at full sampling rate. The Differential nonlinearity (DNL) is +0.5/?0.3 LSB, and the Integral nonlinearity (INL) is +0.7/?0.55 LSB.
Abstract: Frequent episode mining helps to set up episode rules and predict future events. In frequent episode mining, 2-episode mining plays an important role. The mining methods for 2-episodes determine the global strategies of frequent episode mining. The paper focuses on minimal occurrence based frequent 2-episode mining. For the problems existing in the current methods, a novel frequent 2-episode mining method is proposed with high efficiency based on episode matrix and the lock strategy. It does not need to generate candidate episodes and only scans data once. A series of experiments on real data sets show the advantages of the proposed method at time and space cost.
Abstract: Modeling and simulating group behaviours have been an active research topic in the field of computer animation and game. This paper presents some novel approaches for supporting entity modeling and path generation in crowd simulation. It analyses related work about crowd simulation first. Then, an entity modeling approach based on CGA (Cellular genetic algorithm) and NURBS (Non uniform relational B splines) technologies is presented. Next, following the analysis to PSO (Particle swarm optimization) and ABC (Artificial bee colony) algorithms, a crowd path generative approach based on ABCPSO is put forward. After that, a simulating example of crowd cohesion and performance comparison are exhibited for showing the efficiency of the algorithms. Finally, the current work is summarized and an outlook for the future work is given.
Abstract: EEPROM is an important part for interface circuit of sensor. It saves the calibration data and parameter setting data by non-volatile storage. A new lowpower Erasable and electrically programmable read only memory (EEPROM) circuit for sensor interface circuit is introduced in this paper. The data stored in EEPROM can be reloaded automatically by the power-on-reset technique when the power is on. The module consumes power only during power-on-reset and data changing by status optimization and low-power design. This EEPROM circuit has been used in a MEMS accelerometer readout circuit verified by 0.35μm CMOS EEPROM process. The results are satisfying in that the module can write and store 25bit data and automatically reloads data within 0.1μs after power-on and then turns to low power mode.
Abstract: We propose a principle called orthogonality for Auxiliary problems (APs) selection in Alternating structure optimization (ASO) algorithm. Both theoretical analyses and experimental results indicate the following conclusions. If the weight matrices of different types of APs are orthogonal or approximately orthogonal, their multi-combinations perform better than or equal to any components. Moreover, as long as the ratios of their components are appropriate, even if the total amounts of APs are fixed, the multi-combinations still perform better than or equal to any components. In short, the principle of orthogonality holds.
Abstract: In this paper, we propose a variational image denoising model by exploiting an adaptive featurepreserving strategy which is derived from the Non-local means (NL-means) denoising approach. The commonly used NL-means filter is not optimal for noisy images containing small features of interest since image noise always makes it difficult to estimate the correct coefficients for averaging, leading to over-smoothing and other artifacts. We address this problem by a non-local detail preserving constraint, which is performed by adding two terms in the Total variation (TV) model. One is a non local patch based regularization term that controls the amount of denoising to preserve textures, small details, or global information, the other is a new data fidelity term, which forces the gradients of desired image being close to the smoothed normal. The Euler-Lagrange equation is used to solve the problem. Experimental results show that the proposed method can alleviate the over-smoothing effect and other artifacts, while preserving the fine details.
Abstract: Mining coexpression clusters across multiple datasets is a major approach for identifying transcription modules in systems biology. The main difficulty of this problem lies in the fact that these subgraphs are buried among huge irrelevant connections. In this paper, we address this problem using a noise reduction strategy. It consists of three processes: (1) Coarse filtering; (2) Clustering potential subsets of graphs; (3) Refined filtering on those subsets. Using yeast as a model system, we demonstrate that most of the gene clusters derived from our method are enrichment clusters. That is they are likely to be functional homogenous entities or potential transcription modules.
Abstract: A fusion scheme is proposed for incomplete fingerprint to extract the Region of interest (ROI) centered at the reference point. Firstly, the orientation entropy is computed. Secondly, it is necessary for ROI extraction to segment foreground and background efficiently. So, the feature vector, based on orientation and gray, is defined for segmentation with SVM. Then, the fingerprint segmentation of the incomplete area is re-computed and measured with correlation and competition of texture, which is based on Local binary pattern (LBP). Finally, the proposed method is based on mutual information of fingerprint orientation and Poincare Index to detect the reference point of fingerprints, and then extract ROI. The performance of the new method is evaluated on FVC2004 database. And the performance is shown in the experiments and proves that it could locate the position of reference point of all type fingerprints more effectively and precisely.
Abstract: P systems are distributed parallel computing models in the area of membrane computing, which are inspired by the structure and the functioning of living cells, as well as the organization of cells in tissues, organs, and other higher order structures. P systems with proteins on membranes are a class of P systems, which have proved to be very efficient computing devices. Specifically, it was known that the Quantified satisfiability problem (QSAT) of a Boolean formula can be solved by a semi-uniform family of P systems with proteins on membranes and with membrane division. However, it remains open whether a uniform families of P systems with proteins on membranes can solve in polynomial time exactly the class of problems PSPACE. In this work, we present a uniform solution to QSAT problem by P systems with proteins on membranes in a linear time with respect to both the number n of Boolean variables and the number m of clauses of the instance, which answers the above open problem.
Abstract: A new Missing value (MV) estimation method for gene expression profile data is proposed by considering both the internal and external conditions of gene expression profiles. The internal condition emphasizes the time-series characteristic of gene expression profile data. Therefore, we can use the cubic spline fitting method to construct a gene expression curve so as to estimate MVs. The main idea of MV estimation based on the external condition is to reconstruct MVs according to the expression values of candidate genes. Firstly, an initial subset of candidate genes is determined by defining a trace matrix. Then a final subset of candidate genes is constructed by selecting genes from the initial subset according to an improved Pearson correlation coefficient. At last, we select K genes that are most correlated with the target gene from the final subset to compute the weighted sum of the K expression values. Thus, the weighted sum is the estimated value of the target gene based on the external condition. Experimental results indicate that, compared with commonly used MV estimation methods, KNNimpute, SKNNimpute and IKNNimpute, the proposed method has higher estimation accuracy and is robust to the magnitude of K.
Abstract: Rate control plays an important role in video coding and transmission. In this paper, a novel rate-distortion model has first been proposed to characterize the coding characteristics of stereoscopic video coding, where the weighted average of the left and right viewpoint measured with the Video quality metric (VQM) is adopted as the stereoscopic video coding distortion metric, instead of Mean square error (MSE). Then a frame layer rate control method for stereoscopic video coding has been presented based on the proposed R-D model. Experimental results demonstrate that, the proposed R-D model can accurately characterize the relationship among coding distortion, coding rate and quantization parameter and the proposed rate control method can efficiently control the output bit rate consistent with the target bit rate while the R-D coding performance is superior to that of JMVC 4.0.
Abstract: The traditional eigentransformation method for face hallucination is a linear subspace approach, which represents an image as a linear combination of training samples. Consequently, those novel facial appearances not included in the training samples cannot be superresolved properly. In this paper, a KPLS (Kernel partial least squares) regression is introduced into the eigentransformation method to reconstruct the High resolution (HR) image from a Low resolution (LR) facial image. We have evaluated our proposed method using different zooming factors and compared these performances with the current Super resolution (SR) algorithms. Experimental results show that our algorithm can produce better HR face images than the compared eigentransformation based method and the KPLS method in terms of both visual quality and numerical errors.
Abstract: In this paper, we extend Haber and Pinkas’ notion of combined (cryptographic) scheme to the twoparty setting, which is shown to be a useful tool in some real-world application which we name the “2-boss problem”. In a two-party combined scheme, a single public key associated with two independent private keys and one escrow decryption key is provided. Any ciphertext encrypted under the public key can be simultaneously decrypted by the three keys. Meanwhile, the two private keys can also be used as signing keys to achieve non-repudiation service. We provide formal security definitions for two-party combined schemes, and present a simple and efficient scheme. Our construction is derived from bilinear pairings, and the security is based on the Bilinear Diffie-Hellman (BDH) assumption.
Abstract: As the reality that human beings usually pay more attention to areas of interest, visual attention model is a feasible method to find Regions of interest (ROIs) and measure the interest of a region. However, it is required to decompress image data completely. A visual attention model based ROIs detection in compressed domain is proposed in this paper, which can compute visual attention model with partially decompression. This method includes: (1) Visual saliency map computation; (2) Focus of attention (FOA) selection and shift; (3) ROIs detection. The experimental results show the proposed method performs well on the speed/accuracy of ROIs detection and interest measurement.
Abstract: Homomorphic signatures can authenticate vector subspaces of a given ambient space. Aggregate signatures can compress multiple signatures into a compact signature. In order to study the security issues in multisource network coding and sensor data aggregation, the homomorphic aggregate signature scheme is introduced, which can aggregate signatures with message operated from different users. Compared to the classical cryptography, the lattice cryptography is more secure, simple and flexible, so it is applied to the signature scheme design. Bonsai tree characteristics of lattice cryptography can generate multiple bases of a lattice, which means multiple users have the same public key and different private keys. Further, the homomorphic aggregate signature scheme is proposed. Our scheme is secure under the lattice-based inhomogeneous smallest integer solution assumption. Compared to the ordinary lattice-based signature schemes, the communication and verification efficiency are improved.
Abstract: All end-to-end traffic in a network constructs Traffic matrix (TM) which reveals all traffic traversing the whole networks. In this paper, we investigate TM estimation problem in large-scale backbone networks. We propose an accurate approach to estimate it, based on the Recurrent multilayer perceptron (RMLP) which has a powerful ability of modeling. According to constraint relations between link loads and TM, we introduce their temporal and spatial correlation to modify the traditional RMLP and establish our models. And the outputs of our models take into account the constraints that TM itself is satisfied with. Trained with input-output data pairs, our models can learn and grasp all kinds of characteristics of TM and all weight parameters are determined. Finally, we use the real data to validate our method. Simulation results show that our method can perform the accurate and fast estimation of TM very well.
Abstract: In FSE 2003, Johan Wall′en proposed efficient log-time algorithms for computing linear approximations of addition modulo 2n. They posed that his algorithms can be generalized to more complex functions such as Pseudo-Hadamard Transform, but didn’t to the readers. In this paper, we present a formula for computing linear correlation of Pseudo-Hadamard Transform.
Abstract: Existing commercial Digital rights management (DRM) schemes are not suitable for personal content protection because of centralized architecture and rigid constraints. To enable secure and flexible sharing of sensitive personal content, a new DRM scheme is proposed in this paper. Social trust between content sharers is modeled as computable concepts with DRM related contexts; based on the trust model, decentralized DRM architecture and scalable content sharing protocols are presented. Using the proposed DRM scheme, personal content owners can perform authentication and authorization without the intervention of Trusted authority (TA); by performing content sharing recommendations, authorized content users can conditionally have content shared with friends. Prototype implementation and simulation experiments indicate that the proposed scheme achieves satisfactory security and usability.
Abstract: To evaluate the Quality of experience (QoE) of video steaming services in real time continues to be a desirable yet challenging work. In this paper, we present a novel no-reference model for the QoE assessment of the video streaming service in wireless networks. This model evaluates the QoE of video streaming as a comprehensive function of all the parameters about the encoding/ decoding, transmission, and video content. Through the comprehensive function, our model not only renders a general and accurate tool for the QoE assessment, but also provides several useful guidelines for cross-layer optimizations: such as how to balance the image quality and the playback quality to maximize the video quality and how to protect different types of packets to minimize the transmission distortions.
Abstract: The existing IEEE802.11 a/b/g/n provides robust and relatively low cost wireless services but there only provide best effort services. IEEE802.11e provides Quality of service (QoS) to the real time applications but the bandwidth distribution is controlled by the IEEE802.11e and network administrator has no controls over the QoS mechanisms. We propose a non-disruptive and yet low-cost QoS and Fairness provisioning solution over existing best-effort WLAN networks with an Adaptive layer-3 buffer management (AL3BM) Scheme for small domestic wireless network. The existing WLAN networks or hotspots can continue their operation without any major disruption or costly upgrade. AL3BM is implemented in a network router that sits between the wired and wireless network to control the heavy downlink traffic. The network administrator can partially controls the bandwidth allocation through the AL3BM. Simulations have been carried out to examine the proposed scheme in providing services differentiation, and fairness. The simulation results show that AL3BM improves the performance of the wireless end users. Hardware testbed is configured and the experimental results show that AL3BM provides QoS to the WLAN.
Abstract: In order to improve the eavesdropping detection efficiency in two-step quantum direct communication protocol, an improved eavesdropping detection strategy using extended three-particle GHZ state is proposed, in which extended three-particle GHZ state is used to detect eavesdroppers. During the security analysis, the method of the entropy theory is introduced, and two detection strategies are compared quantitatively by using the constraint between the information which eavesdropper can obtain and the interference introduced. If the eavesdroppers intend to obtain all information, the eavesdropping detection rate of the original two-step quantum direct communication protocol by using EPR pair block as detection particles is 50%; while the proposed strategy’s detection rate is 59%. In the end, the security of the proposed protocol is discussed. The analysis results show that the eavesdropping detection strategy presented is more secure.
Abstract: Strong scatterer, such as sign point, exists in Interferometric synthetic aperture radar (InSAR) image. This paper focuses on the interferometric phase statistics of the strong scatterer in InSAR. Based on the InSAR echo model, the phase Probability density function (PDF) of strong scatterer is deduced. Then it is presented that interferometric phase PDF of strong scatterer is determined not only by correlation coefficient, but also by the characteristic parameter of strong scatterer, and the PDF becomes more centralized with the increasing of dominative scatterer intensity. According to interferometric phase PDF of strong scatterer deduced in this paper, the phase Cramer-Rao lower bound (CRLB) of strong scatterer is presented. The higher the intensity of dominative scatterer is, the better estimation accuracy can be obtained. It reveals that the accuracy of Interferometric phase estimation (IPE) assessed with strong scatterer is better than that in actual case. Therefore, Concomitant sign point (CSP) is presented to assess the accuracy of IPE. Simulation results illustrate the validity of the theory proposed in this paper.
Abstract: In order to realize a simple topology, high efficiency, high frequency, low voltage stress, easily controlled soft switching converter, a novel soft switching converter with active auxiliary resonant commutation is presented in this paper. Soft switching of main power switch and auxiliary power switch can be achieved by using active auxiliary resonant network. It is very attractive for high power application where IGBT (Insulated gate bipolar transistor) is predominantly used as the power switch. Its operation principle is analyzed through its application to the boost converter. The novel soft switching cell can be also used in other basic DC-DC converter. A 3kW, 16kHz prototype which uses IGBT was made. The effectiveness of the proposed converter is confirmed by the experimental results.
Abstract: In the third-generation Low-light-level (LLL) image tube, a super thinner Ion barrier film (IBF) is often coved on the input surface of Microchannel plate (MCP) to protect the photocathode and prolong the operation life of the image tube. In order to further investigate on the properties of IBFs, a physical model for the interaction of low-energy electrons with solid was described. A Monte-Carlo simulation on the noise characteristics of the Al2O3 IBF was conducted. Trajectory and spatial distribution of the transmission electrons were simulated with Matlab software. Besides, influence factors for transmittance characteristic of electrons in the Al2O3 IBF were studied. Finally, noise factor of IBFs was calculated and discussed, based on a method of Time domain division. This work provided a theory support for fabricating high performance LLL device.
Abstract: Novel and accurate Computer-aided design (CAD) models based on Artificial neural networks (ANNs) are proposed for the synthesis of Asymmetric coplanar waveguides (ACPWs) with finite dielectric thickness. First, the ACPWs are analyzed by using the Conformal mapping technique (CMT) to obtain the training data sets. Then, six training algorithms are used to train the ANNs for finding proper training algorithm. Highprecision models are obtained by using the Levenberg- Marquardt (LM) training algorithm. The models also can be used for symmetric coplanar waveguides. At last, the models are validated by the comparison with the CMT analysis, HFSS electromagnetic simulation, and experimental results available in the literature. The proposed CAD models are extremely useful to microwave engineers for accurately calculating the physical dimensions of ACPWs with finite dielectric thickness.
Abstract: The Two-step algorithm (TSA) is widely used for trajectory deviation compensation of airborne Synthetic aperture radar (SAR), by which most of the motion errors are compensated before Range curve migration compensation (RCMC) and the residual after the RCMC. We found that the RCMC in the presence of the residual motion errors results in additional range shift errors hard to be compensated for. Based on theoretical investigations, this shortage of TSA is reported and a new compensation scheme which greatly alleviates the RCMC induced errors is proposed. Besides, range resampling considering the residual motion errors is very convinent, which, however, is boresome in TSA. The new method is effective to compensate the high resolution SAR systems for large trajectory deviations, which is hard to be achieved by TSA because of the uncompensated errors. Results on the simulated data are provided to demonstrate the effectiveness of the new method.
Abstract: It is widely accepted that modern computational capabilities have made the application of Multiple hypothesis tracking (MHT) feasible for a wide variety of applications. However, even in typical expected scenarios, periods of unusually high target or clutter density may occur that stress the ability of MHT to operate in real-time and under the constraints of limited computer memory. The most computing burden in MHT is the best global hypothesis formation. This paper establishes a solution tree and introduces the branch and bound strategy for the best global hypothesis formation. Then, a novel MHT algorithm which can be applied in practical radar implementations is proposed. The algorithm is illustrated with examples of simulated missile defense scenarios and a target tracking scenario with real radar data. The experiment results indicate that the algorithm is valid.