Abstract: This paper, aiming at trustworthiness of domain software, proposed a trustworthiness evaluation method based on actual evidence, analyzed and expanded the attributes model for trustworthiness requirements of domain software, elaborated methods of classification, collection and demonstration of trustworthy actual evidences, built trustworthiness level model based on actual evidence, and finally generated the assessment results for software trustworthiness including trustworthiness level, bottleneck analysis and attributive analysis. Practical application proved that the above-mentioned evaluating method was provided with sound operability and practical applicability.
Abstract: Recently, Yu Yong et al. proposed the first multi-proxy signature scheme that can be proven secure in the standard model. However, there are two drawbacks in their scheme. Firstly, it needs a relatively large number of public parameters and secondly, it is not strongly unforgeable since an adversary can easily convert a multi-proxy signature on a message into another valid multi-proxy signature on the same message. In this paper, sharing Boneh and Boyen’s technique and Waters’ technique, we propose a novel construction to overcome the weaknesses of Yu et al.’s scheme. The new scheme achieves the property of strong unforgeability in the standard model whose security can be reduced to the CDH assumption in bilinear groups. The new scheme has three advantages over Yu et al.’s scheme, stronger security, shorter system parameters and higher efficiency.
Abstract: In an e-learning environment, learning community is an effective solution to conquer feelings of loneliness and to share experiences and resources with one another quickly and efficiently for learners. How to cluster learners who share the same interest is a very active area of research. This paper draws knowledge point evaluation matrix from routine learning process; factorize this knowledge point evaluation matrix by Non-negative matrix factorization (NMF); use the result of factorization to build learning communities and the relation between learners and learning communities. As a result, learners with similar interests are automatically grouped into the same community; and each learner is associated with several communities according to his or her multiple interests. The algorithms were evaluated in an online college involving 1200 students. The evaluation showed the effectiveness and efficiency of the algorithms.
Abstract: The paper proposes the wolf colony algorithm that simulates the intelligent predatory behaviors of the wolf colony to solve the optimization problem. The solution in the searching space is the artificial wolf in the algorithm. A few artificial wolves are assigned to searching in the activity range of the quarry. When the searching artificial wolves discover the quarry, they notify the position of the quarry to the other artificial wolves by howl. The other artificial wolves get close to the quarry and besiege it. The wolf colony is updated according to the assignment rule of the wolf colony. The performance of wolf colony algorithm is discussed according to the function optimization problem. To prove the good generalization, the wolf colony algorithm is used to plan the optimal path for the mobile robot. The results prove that the path planning method based on the wolf colony algorithm is viable and efficient.
Abstract: Many of large-scale systems have embraced a number of highly nonlinear dynamic behaviours and thus pose an operational challenge for fault diagnosis schemes based on a linear perturbation model. In this paper, we proposed a novel Fault detection and identification (FDI) scheme for a class of nonlinear systems. The scheme seeks to design an on-line approximator with an adjustable parameter, which is the so-called Fault tracking approximator (FTA). Motivated by the success of predictive control and iterative learning control theory, a stable iterative algorithm is also exploited to update the adjustable parameter in the FTA. The main progress made in this work is that the proposed approach has enabled a leading-edge feature of detecting and identifying the fault shape and fault magnitude simultaneously. The proposed approach is illustrated to be very robust and effective in numerical simulation experiment of this paper.
Abstract: Multi-robots cooperative online FastSLAM algorithm is proposed to solve the problem of particles surviving in the resamping processes, for paying no attention to the measurement in FastSLAM 1.0. The leader robot is defined and measured as a Robot landmark (RL) by the follower robot. At each step, the RL’s posteriori estimation is used as the leader robot’s priori estimation for its next pose prediction. Then the leader robot’s pose posterior estimation is used as the RL’s following priori estimation to be put into landmarks prediction. Through this implementation, the leader robot can enjoy the measurements by the follower robot’s help and avoid the complexity of EKF updating of FastSLAM 2.0. The simulation results show that the errors of the leader robot in localization and mapping are both reduced, more effective particles can survive, and the most important encouragement is that this method is easy in implementation.
Abstract: In this paper, a novel Chinese text feature selection algorithmbased on Probability latent semantic analysis (PLSA) was presented for text classification. The algorithm first employs the Expectation-maximization method (EM) to calculate the correlations between words and the latent topics for every category documents. It then selects feature words for each latent topics and merge those words to describe the corresponding category documents. At last, it merges all feature words of every category into classification feature words. An empirical comparison with other four effective feature selection methods on a benchmark data is presented in this paper. The results show that this method could get the best classification performance.
Abstract: Generation of test data using genetic algorithms has attracted many researchers’ interests in recent years, the efficiency of previous methods, however, needs to be further improved. A method of generating test data based on genetic algorithms to cover multiple target paths in one run is presented in this study. First, the problem of generating test data is formulated as a multi-objective optimization problem in which the number of objectives decreases along with generation of test data. Then, test data are generated using genetic algorithms incorporating with domain knowledge. Finally, our method is applied to two typical benchmark programs, and compared with Ahmed’s method and the single path method. The experimental results confirm that our method has advantage in terms of the number of generations and the time consumption.
Abstract: Most works on privacy preserving data publishing have focused on anonymizing relational data. Only a few works were on transaction data, all of which are heuristic based and do not provide any guarantee on the optimality of data utility. This paper presents an optimal algorithm, which first mines the most general privacy threats in transaction data, and then finds an optimal generalization solution to eliminate all threats. Several novel techniques are proposed, including an inverse lexicographic tree with strong pruning techniques for mining privacy threats, and a cut enumeration tree with a cost based pruning technique for searching the optimal solution. Experiments show that our algorithm outperforms prior algorithms in terms of data utility and efficiency on real world databases.
Abstract: In this paper, a robust high density 7T subthreshold SRAM bitcell is proposed for ultra low voltage (200 mV) applications. Dual-ended write and single-ended read operation ensures high read static noise margin of SRAM bitcell without the expense of writability. Combined with partial dynamic threshold MOSFET technique, 7T SRAM exhibits both robust and density efficiency, making the design less vulnerable to process variation with less area penalty. Compared to the referenced 6T and 8T SRAM bitcell, the proposed bitcell has four aspects of improvement: (1) 5.13% and 7.27% larger hold margin, (2) 80.60% and 51.92% of hold margin standard deviation, (3) 28.58% and 46.28% reduction of bitcell area, and (4) 16X and 8X number of bitcells per bitline (at 200 mV).
Abstract: Small changes to software are sometimes likely to cause unpredicted and negative effects on other parts of the software, especially for object-oriented Java programs due to the complicated relations between their components. Software Change impact analysis (CIA) is a key technique for identifying these potential effects. Most existing CIA techniques focus on method level without considering various changes at different granularity levels. In this article, we propose a new CIA technique, HSMImpact, which is performed in three steps: firstly, hierarchical change sets are defined at different granularity levels; then a CIA process is promoted based on the Hierarchical slicing model (HSM) technology; finally Hierarchical impact sets (HIS) are computed from package-level to statementlevel, which show that precision can be improved at finer granularity level. Preliminary case studies demonstrate the effectiveness of our technique.
Abstract: This paper theoretically advances a new method to establish population inversion between energy levels of pure 87Rb atom without buffer gas driven by appropriate laser fields. With the help of density matrix equation and numerical computation tool, the lasing dynamical behavior of 87Rb atom with population inversion in a cavity is demonstrated. The detailed properties of this lasing dynamic behavior and the atom-cavity coupling with photon are also discussed. This method can be extended to other alkali atoms.
Abstract: In order to deal with the ambiguities in the processes of signal acquisition and fault feature extraction, each Fault template (FT) in fault mode database is modeled as a set of Gaussian membership functions by statistically analyzing typical fault data. Every real-time Fault feature (FF) is modeled as a single membership function extracted from the on-line monitoring data. The matching degree between a FF and every FT can be obtained based on random sets model of fuzzy information. An Interval basic probability assignment (IBPA) can be calculated from this matching degree by the Modified Latin Hypercube Sampling Monte Carlo (MLHSMC) technique. Several IBPAs can be fused by interval evidence combination rule. A diagnosis decision-making can be done according to the fusion results. Finally, the diagnosis examples of machine rotor show that the proposed method can enhance accuracy and reliability of fusion-based diagnosis system.
Abstract: In this work, we develop a multi-hop packet delay bound violation model using Support vector machines (SVM) to predict the packet loss probability and end-to-end distortion for video streaming over multi-hop networks. Based on this model, we formulate the resource allocation into a non-convex optimization problem which aims to minimize the overall video distortion while maintaining fairness between sessions. We solve this optimization problem using Lagrangian duality methods. Extensive experimental results demonstrate that, with this widely-used offline-training-online-estimation mechanism, the proposed model is potentially applicable to almost all network conditions and can provide fairly accurate estimation results as compared with other models with a given sample data set. The proposed optimization algorithm achieves more efficient resource allocation than existing schemes.
Abstract: This paper applies the sparse and redundant representation techniques to the problem of speech enhancement. More specifically, the K-SVD algorithm was used to train a data-driven overcomplete dictionary that describes the sparsity of speech. Orthogonal matching pursuit was employed to reconstruct the clean speech as a direct sparse decomposition technique over redundant dictionaries. Furthermore, the principle of iteration was introduced to the denoising process. When training was done on the noisy speech directly, the overall trainingreconstructing algorithm became fused into one iterative procedure. Simulation shows that our proposed approach outperforms the conventional methods in terms of spectrogram analysis, objective and subjective measures.
Abstract: In this paper, a novel joint source channel safety and virtual user identification method for DSCDMA ad hoc networks is proposed. Previous algorithms for DS-CDMA ad hoc networks mainly concentrated on how to solve packet collision and save the power of the nodes. However, they didn’t involve how to improve the safety of the channels, which is critical for many applications. In our method, the header of the packet is protected and encrypted at the sender by embedding a random, safe and identifiable header, which is related to the source information at the beginning of every packet as base-band digital modulation. It has been shown that our proposed method improves the active user estimation precision and reduces the probability of missing detection for virtual user identification. In addition, it can obtain advanced channel safety.
Abstract: Robust speaker identification is presented for speech recorded by distant microphones. Three compensation approaches are investigated to improve the robustness of speaker identification in such environments. The first approach applies spectral subtraction before feature extraction to reduce the late-reverberation effect. The second approach makes use of feature warping as feature compensation in distant speaker identification under mismatched training-testing conditions. The third approach employs a novel method of initializing Gaussian mixture model parameters: combined division and k-means clustering. The experiment results show that, relative to the baseline system based on CMN, the channel-average recognition rates for the compensated system were 11.4%, 15.4%, 17.0%, and 17.8% higher for the TIMIT database and 6.8%, 6.4%, 9.3%, and 14.0% higher for the JNAS database for four different environments. In addition, the results show that the combination of the three approaches has better performance than the use of a single compensation method.
Abstract: Random linear network coding is a feasible encoding tool for network coding, specially for the non-coherent network, and its performance is important in theory and application. In this paper, we study the performance of random linear network coding for the well-known butterfly network by analyzing some failure probabilities. We determine the exact values of the failure probabilities for the butterfly network with or without channel failure probability p.
Abstract: This paper is focused on the theoretical analysis of the efficiency of Independent component analysis (ICA) based non-Gaussian signal representations corrupted by different types of noises. We first present a mathematical derivation demonstrating that ICA-based signal representations, in which the ICA transformation matrix was derived on clean non-Gaussian signals (denoted by ICAc) are efficient representations than DCT for signals when being both clean and corrupted by Gaussian noise, while it may not have better performance for the non-Gaussian noises corrupted signals. The analysis also demonstrates that to obtain efficient representations of non-Gaussian corrupted signals, the ICA transformation matrix should be obtained from noise corrupted signal (denoted by ICAn). The ICAn-based features can provide significant recognition accuracy improvements to non- Gaussian corrupted signals over both the ICAc-based features and MFCC features. Our findings are experimentally demonstrated by employing the ICA for speech feature extraction; specifically, the ICA is used to transform the logarithm filter-bank-energies (instead of the DCT which provides MFCC features). The evaluation is presented for a GMM-based speaker identification task on the TIMIT database for clean speech and speech corrupted by Gaussian noises and non- Gaussian noises.
Abstract: This paper presents a novel method to design the microphone array post-filter. The key issue of post-filter is to accurately estimate the noise power spectrum, thus a subspace based noise estimation method is proposed. Furthermore, the Gamma probability density function is used to describe the signal power spectrum distribution and the signal-plus-noise subspace dimension is determined by maximizing the probability density signal to noise ratio. The noise power spectrum can be computed either with the speech or without the speech, using the eigenvalues corresponding to the noise subspace. With the same Gamma distribution assumption, a post-filter estimation method is proposed. Experiments show that the proposed noise estimation performs better than the conventional VAD based method. The post-filter can obtain a significant gain over the comparing methods in terms of quality measures of the enhanced speech.
Abstract: Based on software radio technique, a novel improved design structure of digital Costas loop for spread spectrum communication is put forward in the paper. Main practical works includes: (1) For carrier recovery in the traditional Costas central, it improves a way applicable to the spread spectrum communication and gives a detailed mathematical deduction; (2) As for traditional QPSK modem methods, it joins the encoding, interleaving, deinterlacing, decoding, balanced module in the QPSK modulation and demodulation process in spread spectrum communications to reduce the system Bit error rate (BER); (3) a PN code magna-scope demodulator and two low power filers are added in order to get sensitive weighing signal. Simulation contrast results show that the improvement is feasible.
Abstract: Employing the symmetry group direct method and symbolic computation, both the Lie point groups and the non-Lie symmetry groups of the nonisospectral KP-B and BKK are obtained. Then some exact solutions of the two equations are derived from two simple traveling wave solutions by the finite symmetry transformation groups.
Abstract: New properties and methods about the linear complexity and the k-error linear complexity of binary 2n-periodic sequences are provided. Using Games-Chan algorithm and new method, we give some new results about k-error linear complexity, and the method to count the number of critical error sequences is also provided.
Abstract: The Expanded time-frequency (ETF-) OFDM system uses the two-level spreading technology for data transmissions. This system has shown to be robust against the narrowband jamming in flat fading channels. However, in multipath fading channels, the orthogonality of its spreading codes can be destroyed. To mitigate the adverse effects of multipath fading, narrowband jamming, and white noise in ETF-OFDM systems, we propose a transmission approach that finds a proper spreading code assignment at the transmitter and adopts the zero-forcing equalizer at the receiver. Simulation results show that the proposed scheme enables the ETF-OFDM system to suppress the interference under multipath fading channels.
Abstract: Identity based signcryption Key encapsulation mechanism (KEM) is used to encapsulate a symmetric key during the construction of hybrid signcryption in the identity based setting. We introduce the notion of Identity based signcryption KEM to multiple recipients (mIDSC-KEM), and define security models for this new primitive. We illustrate by proposing an efficient mIDSCKEM scheme. Our scheme is proved secure in the random oracle model under the Gap bilinear Diffie-Hellman (Gap-BDH) and the Computational Diffie-Hellman (CDH) assumption.
Abstract: In this paper, we firstly propose an Identity-based threshold decryption (IBTD) scheme based on truncated decisional Augmented bilinear Diffie-Hellman exponent (ABDHE) assumption, and prove that it is chosen ciphertext secure in the adaptive identity (adaptive- ID) model without random oracles. To the best of our knowledge, it is the first in the literature to achieve such a high security level, tight security reduction and computationally efficiency at the same time. It also enjoys desirable property of non-reconstruction of the private key. In addition, we extend the proposed IBTD scheme into a new mediated identity-based encryption (mIBE) scheme.
Abstract: An Energy-efficient and reliability-ensured multipath routing (ERMR) algorithm is proposed for Wireless multimedia sensor networks (WMSNs). By considering the residual energy of nodes, the local link reliability and the distance between nodes, multiple node-disjoint routing paths are constructed from the source node to the sink node. And then several routing paths with high reliability are selected for transmitting multiple copies of a packet. As a result, the end-to-end reliability constraint of packet transmission is ensured. Simulation results show that the ERMR algorithm can effectively balance the energy consumption of nodes, and prolong the network lifetime while satisfying the end-to-end reliability constraint of packet transmission.
Abstract: We propose a new efficient aggregate signature scheme with specified verifier from bilinear pairings. The characteristic, only the designated verifier can verify the correctness of the signature, prevents the disclosure of the signer’s any relevant information. Compared to the previous scheme with this characteristic, we use a new method and the new scheme requires less one pairing operation. Presumed the difficulty of Computational Diffie-Hellman Problem, the proposed aggregate signature scheme is secure against existential forgery in the random oracle model.
Abstract: In the flat Rayleigh channels, two remote antennas are assumed at the base station for receiving the signal transmitted from the mobile station with a single antenna. By utilizing the coverage range of each remote antenna, a constraint is exploited to associate the timedelays from the mobile station to the two remote antennas. With this constraint, a maximum likelihood-based cooperative timing acquisition method is proposed to improve the probability of correct acquisition for each remote antenna. Moreover, a lower bound of the probability of correct acquisition is derived to evaluate the performance of the proposed method. By the analysis and simulations, it is shown that the probability of correct acquisition for each remote antenna can be improved by the cooperation between the two remote antennas.
Abstract: A three-frequency simultaneously matching transformer for complex impedances with three-section is proposed. In this paper, based on a lossless transmissionline model, the design equations and corresponding solutions processes for the transformer is derived. The results of the numerical examples show that two complex impedances can be matched at three different frequencies simultaneously. This proposed transformer can be regarded as the extension of a dual-frequency transformer for complex impedances with two unequal sections, as well as the extension of a three-frequency transformer with threesection for two resistances.
Abstract: Global data center capacity is growing rapidly, consuming more financial resources and emitting more greenhouse gases. A significant portion of typical data centers energy consumption can be apportioned to the cooling infrastructure. In this paper, we proposed a Thermal camera network (TCN) to improve utilization of the cooling infrastructure. It can cool the hotspots intelligently instead of the whole data center. A TCN is composed of multiple thermal cameras and actors, which can wirelessly communicate with each other. Actors will cool the region where hotspots appear as soon as thermal cameras locate the hotspots. In that way, the TCN can save substantial energy in some meaning. In addition, this paper addresses the method of cooperatively detection and formulates the coordinates of the hotspot located by multiple thermal cameras.
Abstract: To maximize the network coverage and prolong the lifetime of the network, an optimization for the Wireless sensor network (WSN) coverage is proposed, which is combined the principle of Cellular automata (CA) with Genetic algorithm (GA) in this paper. Through the evolutionary mechanism of cellular and the redistribution of pheromones, the searching of solution space is effectively improved and the phenomenon of “premature” is avoided. The artificial result reveals that, to a target area having complex boundary, WSN can achieve an optimal cover from a random initial cover by self-organized shift and power control. Moreover, the simulation results also show the Cellular genetic algorithm (CGA) is better than GA and Efficient cover set selection (ECSS) approaches in coverage optimization.
Abstract: In this paper we introduced a method to exchange the private key by adopting steganography in RTCP packet for the covert communication based on VoIP. We presented a model of covert communication based on VoIP, and pointed out the significance of key exchanging to the covert communication. Then, we turned to suggest a steganography algorithm to hide the private key in RTCP packet, and analyzed the performance of the algorithm. To overcome the packet loss, a scheme of key pairs was suggested in case the previous key was lost in transmission. Finally, we analyzed the performance of this scheme, and find that the steganographic key exchanging could be finished in about 1 second even when the packet loss rate is as high as 5% in VoIP using G.711 codec.
Abstract: One challenge of adapting network coding for video transmission over an erasure network is the insufficient rank in the Global coefficient matrix (GCM) at the decoder. To reduce the impact of above problem on video transmission, a special design for the global coding matrix of Random linear network coding (RLNC) is proposed to realize reliable video multicast. Rate allocation is also presented to minimize the quality degradation of the video. Simulation results show the method can provide higher reconstructed quality of video compared with traditional store and forward method and conventional RLNC design for video transmission. The method can be applied to video multicast over different type of network such as P2P networks.
Abstract: K2 is a secure and high-performance clock controlled stream cipher developed by the Information Security Laboratory of the KDDI R&D Laboratories Inc., Japan. Its initial key length is 128-bit or 256-bit. In this paper, a related-key chosen IV attack on K2 is presented. The computational complexity of our attack is 2128, requiring 297 chosens IV s, 2101 keystream words and 2100 words of memory. The result shows that when the initial key length is 256-bit, our attack needs much less computational effort than an exhaustive key search to break K2. Thus, K2 does not have 256-bit security claimed by its designers.
Abstract: This paper proposes a mathematical model and computation method for determining the attitude misalignment parameters of a geostationary meteorological satellite. The mathematical model is built based on the observation geometry. Mathematical modeling of the attitude misalignment parameters for landmark navigation and star navigation are both considered. The analytic solution for the model is also given. Theoretical analysis shows that there is no effective solution if there is only one observation. This paper has provided an important theoretical foundation for the image navigation system of a geostationary meteorological satellite.
Abstract: This paper addresses the problem of the signal detection and tracking of targets with low signalto- noise ratio, a new track-before-detect method based on extended H∞ particle filter is proposed. The proposed method overcomes the degeneracy problem of particle filter, because the system’s latest observations are considered by the importance density function of the extended H∞ particle filter. Therefore, the acquired particles are more convergent to the true samples. The simulation results exhibit the robustness of the proposed method which shows much better performance than track-before-detect based on traditional particle filter.
Abstract: Due to the high system Degrees of freedom (DOF) by utilizing the multiple transmitting elements and receiving elements, MIMO-SAR can improve the performance of static scene imaging and Ground moving target indication (GMTI), simultaneously. To realize the above multifunctional design, the optimal linear array configuration is given for MIMO-SAR in this paper at first. Furthermore, the DOF tradeoff schemes are proposed for static scene imaging and GMTI. Meanwhile, it is shown that the tradeoff between azimuth high-resolution and wide-swath can be solved by MIMO-SAR more effectively than the existing Multiple phase centers SAR (MPC-SAR). The proposed four propositions and numerical experimental results are provided to demonstrate the effectiveness of MIMOSAR.
Abstract: The general formulas of field intensity and mutual impedance of probes located in an elliptic waveguide are given by means of Ddyadic Green’s function (DGF), field transformation, and reaction concept. The waveguide is semi-infinite. The reflection coefficient at terminal plane is Γ. The lengths, feed points, and orientations of two probes in the waveguide are all arbitrary.