Abstract: The aim of the present paper is to provide a unified integrated method for defining the concept of truth degree of propositions in diverse propositional logic systems, including but not limited to the logic systems of classic logic CL, Lukasiewicz logic, Gödel logic, product logic, and L*(or NM) logic, as well as the corresponding fuzzy logic systems. Based on the fundamental concept of truth degree of propositions, the concepts of similarity degree and pseudo-metric between propositions are also introduced under certain conditions. Finally, a kind of approximate reasoning is proposed.
Abstract: A novel wideband 5.8GHz CPW-fed antenna is presented for Radio frequency identification (RFID) tag. Four U-shaped and four L-shaped branches are used as additional resonators to achieve wideband operation. The proposed antenna was analyzed numerically using the Method of moment (MOM) and the Finite element method (FEM). With the antenna size limited to 30 × 30mm2, the -10dB bandwidth obtained by MOM is 3.235GHz (5.765～9GHz) and the -9.5dB bandwidth obtained by FEM is 2.74GHz (5.32～8.06GHz), corresponding to 55.7% and 47.2% of the center frequency 5.8GHz respectively. Moreover, the simulated results show that the proposed antenna has gain of more than 4.8dBi and the radiation pattern is nearly omnidirectional in the H-plane. The measured -10dB bandwidth is 2.68GHz (5.63GHz～8.31GHz), 46.2% of the 5.8GHz frequency. Furthermore, there are three measured resonant frequencies at 1.34GHz, 3.23GHz and 5.8GHz with lower than -10dB return loss respectively. The measurement result achieves a wideband RFID tag antenna performance and is in good agreement with the calculated results.
Abstract: Internet of Things (IoT) is attracting intensive attention. Currently, most existing IoT systems heavily rely on the identification (ID) number of each object/ thing, referred as ID-based IoTs. However, in many cases, the ID-based IoT becomes inapplicable due to noncooperative things that are not attached with any ID number or difficult to obtain an existing ID number. This paper proposes a new non-ID (nID) things concept for non-cooperative things, and nID-based IoT to make IoT suit more real situations. Then, a nID-based IoT solution is designed for the airport aviation risk management, and some key issues including sensing, coding and resolving are discussed. Additionally, an exemplary case study of birdstrike hazard management is presented to further explain how to apply the nID-based IoT for the scenario with noncooperative things. It is envisioned that nID-based IoT will support increasing number of applications where the things have no any available IDs.
Abstract: Very fast decision tree is one of the most successful and prominent algorithms specifically designed for stream data classification. In this paper, we develop a new decision tree induction model CFDT (Clustering feature decision tree model), which is an extension to VFDT (Very fast decision tree). CFDT applies a micro-clustering algorithm that scans the data only once to provide the statistical summaries of the data for incremental decision tree induction. Moreover, micro-clusters also serve as classifiers in tree leaves to improve classification accuracy and reinforce any-time property. Our experiments on synthetic and real-world datasets show that CFDT is highly scalable for data streams while also generating high classification accuracy with high speed.
Abstract: Hardware system has been expected to become increasingly vulnerable to faults due to continuously increasing function complexity and decreasing feature size. Using I/O-state-based dynamic value invariants, one of software visible symptoms, can probabilistically detect peripheral hardware faults. This paper explores a software solution that watches for anomalous dynamic value invariant behaviors to indicate the presence of peripheral hardware faults with low cost. The approach extracts I/Ostate- based dynamic value invariants of real commodity software, and detects faults by checking any data inconsistencies arising in an application’s behavior. We implemented the proof of concept in a full system simulator Bochs-P86. The experimentation with Windows XP shows that the approach is effective in detecting peripheral hardware faults. Four forms of dynamic value invariants all have over 46% coverage rate, detect more than 60% faults within 1000 instructions latency, and achieve less than 1.2% false positive rate.
Abstract: In this paper, a 780MHz low-power fully integrated receiver front-end fabricated in 0.18μm CMOS process is presented. A low noise amplifier utilizing current-reused configuration and single-balance passive mixer are proposed to achieve high conversion gain, low noise figure and low power consumption for wireless sensor network. As the measurement results show, the proposed front-end gets a conversion gain of 27dB, a noise figure of 5.7dB, an ⅡP3 of -20dBm and an ⅡP2 of 5dBm with only 1.71mA current from an 1.8V power supply.
Abstract: A fully integrated analog baseband circuitry for a China mobile multimedia broadcasting (CMMB) direct conversion tuner IC is proposed in this paper. It includes an 8th order Op-Amp-RC channel select filter with 1MHz or 4MHz bandwidth and 71dB stop-band rejection at 1.7f-3dB to meet the stringent Adjacent channel rejection (ACR) specifications and utilizes a novel gainbandwidth- product extension technique in designing the low power, high speed Operational amplifiers (Op-Amps) for the filter. A current steering type Variable gain amplifier (VGA) is adopted to provide 44dB variable gain range and an on-chip DC offset cancellation (DCOC) circuit is designed to prevent the baseband chain from saturation due to DC offsets. Fabricated in a 0.35μm SiGe BiCMOS process, the proposed chip consumes only 6mA from a 3V supply.
Abstract: It is a hot issue to detect and extract the infeasible paths in the test oriented the function calling relationship. In this paper, an algorithm is proposed to extract the infeasible function paths. By traversing the source codes and analyzing the conditional branch correlations, the proposed algorithm builds a mathematical model oriented the control flow, data flow and the correlations between the modules. The experimental results show that the algorithm can extract the infeasible function paths efficiently and accurately. The algorithm can save the testing cost effectively and improve the testing efficiency.
Abstract: With the advanced Internet technology, business applications across multiple enterprises based on Composition web services (CWS) paradigm are widely used. Since business processes among enterprises become complex, loosely coupled, long running and unpredictable, tasks collaborate in a peer-to-peer fashion without central control, in which task dependency is inevitable. And when a system crash occurs, some tasks of the transaction flow may be committed while others unscheduled, in this situation, it is important to accurately specify the dependency between tasks in Transactional composition service (TCS), contemporary technologies usually statically specify dependency point and avoid implicit interaction in parallel aggregation. In this paper, we propose a task dependency analysis method based on transaction execution logs. We present the formal description of atomicWeb service (WS) and discuss properties of the atomic WS such as pivot, compensability, retriability and vitalness, then analyze execution logs of transactions, specify data flow dependency and behavior dependency between tasks in TCS, behavior dependency and properties of aggregation patterns. The TCS based application of Trip reservation process (TRP) shows that it is feasible to ensure consistent execution of reliable TCS.
Abstract: With the increase of group communication applications in the Internet, how to provide a secure communication has become an important research issue for network security. In this paper, a distributed group key management approach is proposed, which integrates zeroknowledge set and hierarchy structure. In this newly proposed approach, re-key procedure is finished in sub-group so that members in other sub-groups cannot be affected and improve the efficiency. Zero-knowledge set which is used for the key generation and the commitment computation from leaf nodes to root of the key tree, can assure the anonymity of all communication entities. Hierarchy structure is good for addressing the scalability problem of group key management, and it can improve the efficiency and performance of re-key procedure and correspondence. It is demonstrated that the approach can achieve better efficiency in terms of communication, computation, storage cost, anonymity and security through comparing to the other schemes.
Abstract: Cloud computing will be a main information infrastructure in the future; it consists of many large datacenters which are usually geographically distributed and heterogeneous. How to design a secure data access for cloud computing platform is a big challenge. In this paper, we propose a secure data access scheme based on identity-based encryption and biometric authentication for cloud computing. Firstly, we describe the security concern of cloud computing and then propose an integrated data access scheme for cloud computing, the procedure of the proposed scheme include parameter setup, key distribution, feature template creation, cloud data processing and secure data access control. Finally, we compare the proposed scheme with other schemes through comprehensive analysis and simulation. The results show that the proposed data access scheme is feasible and secure for cloud computing.
Abstract: This paper is about to solve a multiexponential decay fitting, which is equivalent to an improper problem, called Fredholm integral equation of the first kind. The thought of Multi-resolution analysis of wavelet analysis has been applied here. In order to solve the specific problems, this paper managed to extract the feature of matrix essentially by ignoring the detail information of the large matrix. We solve the problem after dividing the matrix and vectors into blocks, and obtain a set of fuzzy solution for the original problem. Then we remove several weaker components and solve the problem using singular value decomposition. This method eventually greatly reduces the complexity and improves the solution accuracy and speeds up the solution.
Abstract: A kernel-based independent component analysis algorithm, which combines Kernel principal component analysis (KPCA) and Independent component analysis (ICA) is proposed for anomaly detection in hyperspectral imagery. Firstly, KPCA is performed on a feature space associated with the original hyperspectral data space via a certain nonlinear mapping function to whiten data and fully mine the nonlinear information between spectral bands. Then, ICA seeks the projection directions in the KPCA whitened space for making the distribution of the projected data mutually independent. Finally, RX detector is performed on the projected data to locate the anomaly targets. The kernel ICA algorithm saved the nonlinear information on dimension reduction in hyperspectral data and made the extracted features mutually independent, so improved the performance of RX detector in hyperspectral data. Numerical experiments are conducted on real hyperspectral images. Using receiver operating characteristic curves, the results show the improved performance and reduction in the false-alarm rate.
Abstract: Multi-path video streaming over networks emerges as an important application in multimedia communication. Since the efficiency of multi-path video streaming is closely tied to the packet scheduling strategies, in this paper, we develop a content-aware opportunistic packet scheduling scheme with dynamic routing algorithm, which aims to maximize the reconstructed video quality by considering the content diversity of each video packet. To handle the problem of increased reordering delay, a sliding-window-based policy is then developed to find a balance between the reconstructed video quality and the reordering delay, throughout and packet loss. Our extensive experimental results demonstrate that the proposed packet scheduling scheme significantly outperforms EDPF and achieves a good tradeoff between the reconstructed video quality and the reordering time at the receiver side.
Abstract: Based on quaternion algebra, this paper proposes two new smoothing models called colordependent diffusion equations. One model is designed to only smooth the components in the direction of a chosen color. The other model is designed to only smooth the components perpendicular to the direction of a chosen color. To improve the color selectivity, a weight factor W is proposed. For example, if we filter the parallel components of the image, greater weight is given to pixels with the color close to the chosen color. Finally, a color-dependent diffusion scheme is presented, which can detect a chosen color edge or low-pass filter a certain color efficiently. Experimental results demonstrate the effectiveness of this scheme applied to natural color images.
Abstract: A multi-case Chinese 3D face database Northwestern Polytechnical University 3D (NPU3D) has been built for automatic face recognition experiments and other possible face model applications. NPU3D contains 10500 3D facial surface data corresponding to 300 individuals, and there are 35 different scans per person. Currently, NPU3D database contain the largest cases in multi-scale systematic variations over the pose, facial expression, accessory and occlusion of each person in the world. In this paper, the database description, acquisition schema and the pre-processing methods are provided to help using the data and future extension. As an application, a multi-pose 3D face recognition algorithm is proposed. Experimental results show that the proposed algorithm has a good performance.
Abstract: A frequency estimator for a real single-tone is proposed, in which coarse frequency estimation is firstly got by using Pisarenko harmonic decomposer (PHD) with correlation lags 1 and 2. As the correlation of noise concentrates mainly on small lags, the frequency is re-estimated by PHD with correlation maximal lag k in the principal value interval of the arccosine function and with correlation lag 2k, which is determined by the coarse estimation, to decrease the influence of noise. The final frequency is obtained by adding to the re-estimated frequency a fine adjustment term, the closed-form of which is derived from Taylor’s series expansion of lag-limited correlation. Simulation experiments illustrate the performance improvement of the proposed estimator via comparison with several existing frequency estimators.
Abstract: In this paper, the problem of optimal Nonuniform sampling (NUS) is addressed for the purpose of sparsely sampled data system identification. Given a set of uniformly sampled data, its spectral information is available in the range limited by Nyquist rate, and results in alias out of the range. This cannot meet the “informative enough” condition, which is one indispensable prerequisite for system identifiability. Nevertheless, deliberate NUS pattern with certain random distributions can keep the alias-free feature of sampled signals and recover wider spectrum of the original signal, so that the identifiability is still guaranteed. In the case that no ideal alias-free signal is available, a criterion of alias suppression is founded and the optimal sampling is proposed to give an effective estimation of such systems with sparse samples. Simulation results shows the practicality and effectiveness of the proposed optimal sampling method, and how the identified model accuracy is affected by NUS.
Abstract: Based on a general architecture of erasure error correction under strict delay constraints for realtime wireless multicast, we contribute a simple method for analyzing quantitatively the effect of packet size on the throughput performance of Hybrid error correction (HEC) schemes. We then propose an adaptive HEC scheme for maximizing its throughput with Variable packet size (VPS). By analysis, it is found that the throughput performance of the adaptive HEC scheme with VPS is influenced deeply not only by the variation of packet size, but also by the change of the weight of overhead messages in packets. It indicates that the packet size and the weight of overhead messages should be designed jointly for achieving the optimum throughput performance. Finally, comparing with those schemes with fixed packet size, the analysis results show that the adaptive HEC scheme with VPS can improve the throughput by about 20% in some cases.
Abstract: In this paper, we propose two methods to choose the fidelity parameter in total variation based denoising model for Poisson noise. Firstly, we derive a scheme to choose the scalar parameter automatically. Secondly, we propose to use a local fidelity term with spatial-varying parameters which automatically controls the extent of denoising according to image contents. Experiments with simulated data demonstrate that the proposed algorithms are effective.
Abstract: In this paper, a novel evolutionary programming with self-adaptive Cauchy mutation ACEP is proposed to solve the numerical optimization problems. ACEP utilizes the self-adaptive parameter r of Cauchy mutation to alter the search step size in time, and it obtains the best solution with only half population size of Fast evolutionary programming (FEP). The empirical experiments on four benchmark functions are undertaken. In the typical unimodal functions, ACEP performs much better than FEP on the convergence rate and the best solutions. While in the multimodal functions with many local minima, the accuracy of the best value in ACEP improves at least 50 percent than FEP on average statistic.
Abstract: Long-distance IEEE 802.11 wireless mesh networks are expected to provide multimedia traffic service in addition to basic Internet access, as more and more such networks have been emerged in real life. However, few work has been done on QoS provisioning in this area. In this paper, we propose QoS routing and scheduling algorithms to guarantee the QoS of real-time traffic. MQDSR (MAR-based QoS dynamic source routing) integrates bandwidth reservation and admission control, according to MAR bandwidth constraints model. We also present a service index to describe the QoS requirements for different traffic classes. Based on the service index, the scheduling algorithm is proposed to allocate the bandwidth in fine granularity. Simulation results in NS2 show that the proposed QoS routing and scheduling algorithms can provide QoS support in terms of end-to-end delay and throughput for traffic with high and normal priority, while avoiding the starvation of the best-effort traffic.
Abstract: In this paper, a novel reduced-dimension approach to linearly constrained minimum variance beamforming is investigated. The proposed method is able to achieve a LCMV solution through a number of optimization cycles based on the partition matrices of small sizes instead of a full dimensional correlation matrix. The problem is formulated as a conditional optimization problem. The derivations and equations for the proposed method are shown. The proposed method achieves the optimal performance with a fast convergence and a stable performance characteristic. Simulation results illustrate the effectiveness of the proposed method.
Abstract: Current network for real-time service de- livery needs to maintain end-to-end service quality under various network uncertainties, e.g. traffic demand °uctua- tions or topological changes. This paper investigates coor- dinating AQM-RED and OSPF-TE for guaranteeing SLA under such network dynamics. The simulation experiments show that the proposed approach can significantly reduces the detrimental impact of link failures and traffic demand variation on end-to-end QoS provisioning without intro- ducing additional complexity or overheads to the current network paradigm.
Abstract: Energy efficiency is essential to a wireless sensor network with power concerned since the lifetime of the sensor network directly depends on its remaining power level. In this paper, a novel routing algorithm termed Neighboring propagation based on hierarchical routing scheme (NPHRS) is proposed, which is able to dramatically expend energy evenly among all of the sensor nodes and efficiently prolong network lifetime. In the NPHRS, affinity propagation clustering algorithm is used to divide a wireless sensor network into some clusters and select a cluster head for each cluster as relay node according to intra-cluster’s neighborhood information. Moreover, rational ant colony optimization algorithm is applied to establish the optimal multi-hop route with the minimum power consumption between cluster heads and sink node. The comparison of the extensive simulation results obtained with every routing protocol demonstrates that the network lifetime of NPHRS is longer than the existing typical algorithms such as LEACH.
Abstract: This work focuses on robust acoustic source localization in sensor networks with limited energy reserve, e.g. Wireless sensor networks (WSN). Real-world data revealed that the acoustic energy gathered at sensors exhibits a heavy-tail, non-Gaussian characteristic and should be fitted into a contaminated Gaussian model. This property causes conventional least square and maximum likelihood based localization methods ineffective. Hence an Energy-efficient robust acoustic source localization protocol (ERASLP) is proposed. With the ERASLP, each sensor receives observations from neighbors then examines its observation by a Local outlier rejection rule (LORR) such that detected outliers are not sent to the fusion center in order to reserve energy and reduce fusion risk. Further analysis show that the communication energy cost of ERASLP is related to the node density and outlier probability. Simulations show that LORR effectively surpasses outliers and that ERASLP has better tradeoff between robustness and energy consumption in most cases.
Abstract: In Impulse radio Ultra-Wideband (IRUWB) system, extremely high sampling rate is required for digital processing, it is difficult to meet this requirement under the current level of the hardware chips. Considering of the time-domain sparsity of IR-UWB communication signals, a novel signal recovery method is proposed to reduce the sampling rate based on Compressed sensing (CS) theory. The CS reconstruction model is developed, where the entries of quasi-Toeplitz measurement matrices satisfy with the logarithm normal distribution, and the feasibility of recovering the IR-UWB communication signals is proved by Restricted isometry property (RIP) analyzing. Simulation experiments are performed with Orthogonal matching pursuit (OMP) algorithm, and the results demonstrate that 1/10–1/20 of the Nyquist sampling rate will be sufficient to efficiently recover the IR-UWB communication signals.
Abstract: As is well known, the unified point addition formula is useful for resisting side channel attacks in elliptic curve cryptography. Furthermore, if the unified formula is complete, which means it is valid for any two points, then there are no exceptional cases to be described particularly. This feature is especially preferable for elegant codes of elliptic crypto-algorithms. Therefore, the unified and also complete point addition formula can provide the advantage for good security and convenient implementation. In this paper, we exploit sufficient and necessary condition for the existence of unified and complete point addition formula on several known elliptic curve models such asWeierstrass cubics, Jacobi quartics, Edwards curves, etc.. Moreover, we study another form of elliptic curves called Selmer curves. For practical application, we finally give some numerical examples of cryptographic secure Selmer curves.
Abstract: Wireless sensor networks (WSN) is uniquely characterized by its limited resources and often deployed in remote and harsh environments. It is highly dynamic, prone to faults and usually kept unattended. Therefore, proper management of WSN and its limited resources is highly desirable for an effective and efficient functioning of the network. By introducing state machines and publish/subscribe scheme, a light-weight and dynamically reconfigurable management architecture for WSN is proposed, which is called DRMA. By dynamically configuring the data collection mode and processing method, it supports application dynamics and new application additions, which in practice are very desirable to make applications better meet a big diversity of real needs. The result of simulation shows that DRMA can collection and process data timely and accurately.
Abstract: Auction is efficient for spectrum allocation in future dynamic spectrum access networks. Truthful or strategy-proof auction is favorable since every bidder only needs to bid his true valuation and the auctioneer assigns spectra to bidders who value them most. Existing truthful spectrum auction schemes however either generate very low revenue for the auctioneer or need extra prior distribution information on the true valuation of bidders. Low revenue generation could discourage the auctioneers from leasing their spectra and it is usually hard to get prior information on bidders’ true evaluations on the spectra. In this paper, we propose a class of truthful spectrum auction schemes which bring higher revenue for the spectrum owners and do not need any prior information at the same time. We present both theoretical and simulation results of our proposed auction schemes.
Abstract: FCC recently issued regulatory rules for the reuse of the underutilized TV white space spectrum without negative impact on digital television broadcasts. Cognitive Radio techniques are of great importance to acquire opportunistic access to the TV bands. Since primary user may experience out-of-band power leakage from the secondary signal, Cosine-Modulated Filter Banks are considered as interesting alternatives to traditional OFDMs for spectrum pooling, due to their small sideband power leakage and spectral efficiency. In this paper, we propose a Nearly Perfect Reconstruction CMFB system for CR. A new objective function is provided to control the tradeoff between the level of interference caused by secondary transmission to primary users and the spectral efficiency of secondary users. An adaptive linear search optimization technique is employed for the prototype filter design. Simulation results show a significant enhancement in terms of BER, sideband power rejection, sidelobe radiation and effective throughput compared to conventional OFDM.
Abstract: The detection of presence of decoy in terminal guidance is not only the prerequisite of countering against Towed radar active decoy (TRAD) jamming but also an important factor to decide the hit precision of missile. TRAD jamming makes the actual target and the spurious decoy unresolved within the radar beam of homing seeker, and in this case the detection and measure processing with conventional approach fails. This paper analyzes the distinction of echo fluctuation characteristic when the decoy is present or not, and the conditioned probability density functions of measured amplitude and observed Signal-to-noise-ratio (SNR) of echoes are abstracted and developed. Then the Generalized maximum likelihood detection (GMLD) algorithm based on these characteristics of radar echoes is proposed and a practical detection flow for TRAD in terminal guidance is developed. Simulation results with typical condition and dynamic jamming course illustrate the performance and application of the algorithm.
Abstract: With the recent launching of the 8th Compass navigation satellite, the Compass navigation satellite system has been completed. To augment the performance of this system for navigation on the Chinese mainland, it is necessary to optimize its current regional constellation. This paper analyzes the inadequacies of the current regional constellation and presents a method for optimizing the augmented regional constellation in which a new evolutionary algorithm and a Compass constellation optimization problem model are proposed. Three objective functions (the Weighted geometric dilution of precision (WGDOP), the number of visible satellites and constellation costs) are then introduced. Three optimal solutions were obtained through the optimization process. Based on a comparison of the performance of the three optimal solutions, this paper suggests that one GEO satellite and one IGSO satellite be added to complete the Compass augmented regional constellation.
Abstract: Phase noise is a topic of theoretical and practical interest in electronic circuits, as well as in other fields, such as optics. In this work, a cross-coupled topology of integrated CMOS VCO design is considered. Based on Hajimiri’s phase noise model, we present the analytical model of phase noise in LC VCO. The calculation results are agreed with the experiment results. The model we presented can reflect the relationship between phase noise and circuit parameters. There is some instruction to VCO designer.
Abstract: This paper presents a nonlinear dynamic bandwidth control algorithmfor Digitally controlled phaselocked loop (DCPLL). Because of nonlinear relationship between sensed phase error and feedback clock frequency, there are many erroneous bandwidth adjustment in the PLL with traditional dynamic bandwidth control algorithm. The proposed algorithm adjusts the DCPLL bandwidth when small phase error has been sensed several times by the phase detector, thus it avoids unnecessary bandwidth adjustment. To verify the feasibility of the proposed algorithm, we develop a behavioral model in Matlab. Simulation results show that the DCPLL locking time using the proposed algorithm is reduced to 28.6% to 85.7% compared with the DCPLL employing the traditional algorithm. Finally, a DCPLL is implemented by CSM 0.18μm 1P6M CMOS. The measured results show that the DCPLL without the proposed algorithm will spend extra 2.5μs when locking to 550MHz.