Abstract: Expressional face recognition is a challenge in computer vision for complex expressions. Facial data field is proposed to recognize expression. Fundamentals are presented in the methodology of face recognition upon data field and subsequently, technical algorithms including normalizing faces, generating facial data field, extracting feature points in partitions, assigning weights and recognizing faces. A case is studied with JAFFE database for its verification. Result indicates that the proposed method is suitable and effective in expressional face recognition considering the whole average recognition rate is up to 94.3%. In conclusion, data field is considered as a valuable alternative to pattern recognition.
Abstract: In this paper, we present a conversion algorithm to translate a Linear temporal logic (LTL) formula to a Büchi automaton (BA) directly. Acceptance degree (AD) is presented to record acceptance conditions satisfied in each state and transition of the BA. According to AD, on-the-fly de-generalization algorithm, which is different from the standard de-generalization algorithm, is conceived and implemented. On-the-fly de-generalization algorithm is performed in the case of the given LTL formula containing U-subformulae or F-subformulae, that is, it is performed as required during the expansion of the given LTL formula. We compare the conversion algorithm presented in this paper to previous works, and show that it is more efficient for a series of LTL formulae in common use.
Abstract: Deterministic tree-based algorithms are mostly used to guarantee that all the tags in the reader field are successfully identified, and to achieve the best performance. Through an analysis of the deficiencies of existing tree-based algorithms, a Q-ary search algorithm was proposed. The Q-ary search (QAS) algorithm introduced a bit encoding mechanism of tag ID by which the multi-bit collision arbitration was implemented. According to the encoding mechanism, the collision cycle was reduced. The theoretical analysis and simulation results showed that the proposed MS algorithm overcame the shortcoming of existing tree-based algorithms and exhibited good performance during identification.
Abstract: GPGPUs adopt SIMT execution model in which each logical thread in a warp corresponds to a SIMD lane while can still follow an independent control flow. When a branch divergence appears and threads within a warp take different execution paths, GPGPUs have to execute each path serially through SIMD lane masking, which potentially decreases the SIMD utilization and performance. We propose an efficient thread compaction mechanism to handle branch divergence with a novel register file structure. We also develop a new thread scheduling policy cooperating with our compaction mechanism. The simulation results show that our approach improves the SIMD utilization up to 74.4% and achieves a maximum 11.1% performance speedup with small hardware overhead.
Abstract: Noise exists in the actual communication environment. It is necessary and significant to analyze the security of "SAGR04" protocol in the noise environment. An excellent model of collective rotation noise analysis is introduced and the discussing of the security of "SAGR04" protocol is based on the method of information theory. The eavesdropping can be detected for the increment of the qubit error rate and eavesdropper can maximally get about 50% of the keys. It can be concluded that the "SAGR04" protocol, used as quantum key distribution, is secure.
Abstract: To improve the performance of K-means clustering algorithm, this paper presents a new hybrid approach of Enhanced artificial bee colony algorithm and K-means (EABCK). In EABCK, the original artificial bee colony algorithm (called ABC) is enhanced by a new mutation operation and guided by the global best solution (called EABC). Then, the best solution is updated by K-means in each iteration for data clustering. In the experiments, a set of benchmark functions was used to evaluate the performance of EABC with other comparative ABC variants. To evaluate the performance of EABCK on data clustering, eleven benchmark datasets were utilized. The experimental results show that EABC and EABCK outperform other comparative ABC variants and data clustering algorithms, respectively.
Abstract: A phase difference detection method used for reading the resonant frequency through mutual coupling is designed to meet the pressure measurement in harsh environments, and a testing device of integrated modular by developing the hardware circuits is proposed. Description and discussion of the novel theoretical model in the phase readout system is presented, and a pressure test platform based on the phase difference detection is also established, which is to measure the frequency of a LC resonant sensor on the basis of 96% alumina ceramic substrate. The experimental results show that the proposed phase difference readout system presents sweep-frequency detection in the range of 1-100MHz bandwidth, and a high frequency resolution of 0.006MHz. Sensitivity of the sensor is approximately 0.225 MHz/bar from 1 bar to 2 bar. The accuracy and functionality of the phase readout system have emphasized a wider engineering application range, so that we can make it possible that the wireless passive LC resonant sensor revolves well in practical engineering occasions outside the laboratory environment.
Abstract: In view of the issue concerns multiple Directedacyclic graphs (DAGs) scheduling in multi-tenantcloud computing environment, a scheduling strategy thatintegrate security and availability is proposed to satisfythe tenants' requirements for resource security and availability,as thus it can not only protect the users' privacyand data security but also advance the success rate. Theproposal assesses resource reputation to ensure jobs canbe scheduled onto relatively security nodes; during taskscheduling, it classifies the DAGs to achieve fairness; inthe process of resources allocation, the objective functionwould maximize the user's security satisfaction and minimizethe deviation of availability; meanwhile, it takes advantageof "time chips" flexibly to promote resource utilizationrate; afterwards, we present a Greedy algorithmintegrating with security and availability (GISA) to implementthe strategy. The experimental results show thecorrectness and superior of the novel strategy.
Abstract: Skyline query has been applied widely in sensor networks. We propose a connected key node set-based skyline Efficient skyline query processing (EffiSky) algorithm to minimize communication traffic for resources-limited sensor networks. In the EffiSky algorithm, we discover a Connected key node set (CKNS) used to transmit and collect queries and results among the sensor nodes, which can reduce the average communication cost of the networks significantly. We set up a two-level filtering scheme that prunes many useless dominated tuples. Both the theoretical analysis and experiment results demonstrate that EffiSky excels the existing work in terms of network traffic, scalability in network expansion, node density, and dimension change.
Abstract: Wireless sensor networks (WSNs) have been employed as an ideal solution in many applications for data gathering in harsh environment. Energy consumption is a key issue in wireless sensor networks since nodes are often battery operated. Medium access control (MAC) protocol plays an important role in energy efficiency in wireless sensor networks because nodes' access to the shared medium is coordinated by the MAC layer. An energy efficient MAC protocol is designed for data gathering in linear wireless sensor networks. In order to enhance the performance, when a source node transmits data to the sink, proper relay nodes are selected for forwarding data according to the energy consumption factor and residual energy balance factor. Some simulation experiments are conducted and the results show that, the proposed protocol provides better energy efficiency and long lifetime than the existing DMAC protocol.
Abstract: A Hybrid compression framework of trajectory data (HCFT) is proposed for effective compression of trajectory data with road network limited. It's different from the present researches which mainly focus on compression of single trajectory, and further takes data redundancy raised by the similarity of movement pattern of moving objects into consideration. HCFT divides the redundancy of trajectory data into Single trajectory redundancy (STR) and Multiple trajectories redundancy (MTR) and compresses them in a hybrid way (i.e. synchronous compression for STR at first and then asynchronous compression for MTR). We propose an asynchronous extraction algorithm for MTR based on frequent Road track subsequence (RTS), which replaces similar movement route by RTS, with the complexity of calculation significantly reduced. HCFT can not only gain higher compression ratio, but also ensure effectiveness of compressed trajectory. We also verify effectiveness and superiority of the new method according to the experiments of real trajectory dataset.
Abstract: Previous approaches using active membrane systems to solve the N-queens problem defined many membranes with just one rule inside them. This resulted in many communication rules utilised to communicate between membranes, which made communications between the cores and the threads a very time-consuming process. The proposed approach reduces unnecessary membranes and communication rules by defining two membranes with many objects and rules inside each membrane. With this structure, objects and rules can evolve concurrently in parallel, which makes the model suitable for implementation on a Graphics processing unit (GPU). The speedup using a GPU with global memory for N=10 is 10.6 times, but using tiling and shared memory, it is 33 times.
Abstract: The satisfiability problem (SAT) is a well known NP-complete problem. Obtaining All of the truth assignments of SAT is called All-SAT and it has numerous applications in artificial intelligence and computer theories. Many algorithms about SAT have been built, but how to solve All-SAT is still difficult. P system is a new distributed and parallel computation model. We use membrane division, which is frequently investigated to obtain an exponential working space in a linear time, to design a family of P systems to solve All-SAT in polynomial time. Our work provides a new and effective solution to All-SAT in a distributed and parallel manner.
Abstract: This paper presents a large-range, high-precision and continuously variable delay reconstruction method for wideband and arbitrary bandlimited signal, which combines dynamic index technique with complex-coefficient Lagrange interpolation technique. The method samples time-continuous bandlimited signal and stores samples in sequence. It manages to obtain the high-precision delay parameters of every sampling period from desired delay to compute the so-called index position variable and interpolator parameters. It dynamically indexes and chooses a set of samples to implement piecewise complex-coefficient Lagrange interpolation for reconstructing the delayed sequences. The time-continuous delay reconstruction signal can be simply accomplished through digital-to-analog conversion. The mathematical model of the method and its transformed form is given, and the arithmetic of dynamic index and complex-coefficient Lagrange interpolation is derived. Simulation and test results show the validity and performance of the method.
Abstract: Motivated by the importance of Human visual system (HVS) in image processing, we propose a novel Image signature based mean square error (ISMSE) metric for full reference Image quality assessment (IQA). Efficient image signature based describer is used to predict visual saliency map of the reference image. The saliency map is incorporated into luminance difference between the reference and distorted images to obtain image quality score. The effect of luminance difference on visual quality with larger saliency value which is usually corresponding to foreground objects is highlighted. Experimental results on LIVE database release 2 show that by integrating the effects of image signature based saliency on luminance difference, the proposed ISMSE metric outperforms several state-of-the-art HVS-based IQA metrics but with lower complexity.
Abstract: Multiple visual sensor fusion provides an effective way to improve the robustness and accuracy of video surveillance system. Traditional video fusion methods fuse the source videos using static image fusion methods frame-by-frame without considering the information in temporal dimension. The temporal information can't be fully utilized in fusion procedure. Aiming at this problem, a visible and infrared video fusion method based on Uniform discrete curvelet transform (UDCT) and spatial-temporal information is proposed. The source videos are decomposed by using UDCT, and a set of local spatial-temporal energy based fusion rules are designed for decomposition coefficients. In these rules, we consider the current frame's coefficients and the coefficients on temporal dimension which are the coefficients of adjacent frames. Experimental results demonstrated that the proposed method works well and outperforms comparison methods in terms of temporal stability and consistency as well as spatial-temporal information extraction.
Abstract: X-ray imaging is an effective technique to obtain the continuous motions of the vocal tract during speech, and Active appearance model (AAM) is a useful tool to analyze the X-ray images. However, for the task of tongue tracking in X-ray images, the accuracy of AAM fitting is insufficient. AAM aims to minimize the residual error between the model appearance and the input image. It often fails to accurately converge to the true landmarks. To improve the tracking accuracy, we propose a fitting method by combining Constrained local model (CLM) into AAM. In our method, we first combine the objective functions of AAM and CLM into a single objective function. Then, we project out the texture variation and derive a gradient based method to optimize the objective function. Our method effectively incorporates not only the shape prior and global texture, but also local texture around each landmark. Experiments demonstrate that the proposed method significantly reduces the fitting error. We also show that realistic 3D tongue animation can be created by using tongue tracking results of the X-ray images.
Abstract: The biorthogonal wavelets families are used widely because they have compact support, complete symmetry and linear phase. According to Bézout's theorem, the biorthogonal wavelets available now are only some particular examples of total solutions. The quantity of solutions is decided jointly by the scaling function vanishing moment N and dual vanishing moment Ñ. The relationship of N, Ñ and solutions' quantity is discussed in detail. According to the constraint conditions which the compact biorthogonal wavelets satisfy, a number of biorthogonal wavelets are constructed in which the global convergent homotopy method is used for different N and Ñ. The filter coefficients and plots of scaling function, dual scaling function, wavelet function and dual wavelet function are given.
Abstract: Certificate-based cryptography is a new kind of public key algorithm, which combines the merits of traditional Public key infrastructure (PKI) and identity-based cryptography. It removes the inherent key escrow problem in the identity-based cryptography and eliminates the certificate revocation problem and third-party queries in the traditional PKI. In this paper, we propose an efficient certificate-based signature scheme based on bilinear pairings. Under the strong security model of certificate-based signature scheme, we prove that our scheme is existentially unforgeable against adaptive chosen message and identity attacks in the random oracle. In our scheme, only two pairing operations are needed in the signing and verification processes. Compared with some certificate-based signature schemes from bilinear pairings, our scheme enjoys more advantage in computational cost and communicational cost.
Abstract: This paper presents a novel construction method of irregular Low-density parity-check (LDPC) codes based on Quasi-cyclic (QC) structure and zigzag pattern. By using the proposed method, a class of irregular and highly structured LDPC codes can be designed with the advantages of low storage requirement and linear time encoding complexity. The constructed codes are called Irregular repeat-accumulate like (IRA-like) codes since their parity-check matrices are similar with those of IRA codes, which all contain a sparse zigzag pattern submatrix. The left part of the parity-check matrix of IRA-like codes is a kind of circulant permutation matrix. A best-effort analyzing method for optimizing the cycle structure of IRA-like codes is presented. We further details the proper constraints for avoiding short cycles and low-weight codewords. Simulation results show that the proposed IRA-like codes have low encoding complexity, good iterative decoding performance and flexible choice of code parameters.
Abstract: Along with the explosive growth of images, automatic image annotation has attracted great interest of various research communities. However, despite the great progress achieved in the past two decades, automatic annotation is still an important open problem in computer vision, and can hardly achieve satisfactory performance in real-world environment. In this paper, we address the problem of annotation when noise is interfering with the dataset. A semantic neighborhood learning model on noisy media collection is proposed. Missing labels are replenished, and semantic balanced neighborhood is construct. The model allows the integration of multiple label metric learning and local nonnegative sparse coding. We construct semantic consistent neighborhood for each sample, thus corresponding neighbors have higher global similarity, partial correlation, conceptual similarity along with semantic balance. Meanwhile, an iterative denoising method is also proposed. The method proposed makes a marked improvement as compared to the current state-of-the-art.
Abstract: To localize inspection robot in an in-service substation costs much. How to discriminate its location among highly similar scenes is the main problem of localizing robot in the substation using vision. A novel approach for visual localization using image retrieval and multi-view geometry is proposed. It is applicable for autonomous inspection of in-service substation without additional modifications of the environment. The experimental results demonstrate the efficiency and reliability of our approach. They have been further discussed by means of parameters for image description, number of neighbouring images for coordinates estimation, training dataset selection and performance evaluation. They verified that our approach is a cost-effective solution to robot localization in in-service substation.
Abstract: This study proposes an innovative M-L (Multiple-channel local binary fitting) model for medical image segmentation. Designed to improve upon existing image segmentation models, the M-L model introduces a regional limit function to the multi-band active contour model to enable multilayer image segmentation. The Gaussian kernel function is used to improve the previous model's robustness, necessitating the use of a new initialization curve which enhances the accuracy of segmentation results. Compared to existing image segmentation methods, the proposed M-L model improves numerical stability and efficiency through the introduction of a new penalty term and an increased step length. This simulation experiment verifies the advantages of the new M-L model for improved medical image segmentation, including increased efficiency and usability of the model.
Abstract: A four-moded Census transform stereo matching algorithm using bidirectional constraint dynamic programming and relative confidence plane fitting is proposed to solve the problems of matching quality. Using the four-moded Census transform which adds a restrictive condition replaces traditional Census transform to improve matching accuracy and mean value of all pixels intensity replaces the center pixel intensity in the Census window to solve the problem of the center pixel distortion effectively, a refined initial local matching cost can be obtained. During the disparity optimization, the difficulty of disparity computation in textureless areas is overcome by the estimated condition and defined relative confident pixels. Experiment results show that a better dense matching map can be obtained by the proposed algorithm.
Abstract: Variable selection is one of the most important problems in pattern recognition. In linear regression model, there are many methods can solve this problem, such as Least absolute shrinkage and selection operator (LASSO) and many improved LASSO methods, but there are few variable selection methods in generalized linear models. We study the variable selection problem in logistic regression model. We propose a new variable selection method-the logistic elastic net, prove that it has grouping effect which means that the strongly correlated predictors tend to be in or out of the model together. The logistic elastic net is particularly useful when the number of predictors (p) is much bigger than the number of observations (n). By contrast, the LASSO is not a very satisfactory variable selection method in the case when p is more larger than n. The advantage and effectiveness of this method are demonstrated by real leukemia data and a simulation study.
Abstract: Optimal set of the frequency hopping sequences can be derived from some irreducible cyclic codes. This paper determines the linear span of the frequency hopping sequences in the optimal set. The linear span is much less than the length of the frequency hopping sequences. In order to improve the linear span, we use two types of permutation polynomials, power permutation and binomial permutation, to transform the optimal set of the frequency hopping sequences. The transformed frequency hopping sequences have optimal Hamming correlation and larger linear span than the original frequency hopping sequences. Compared with the original frequency hopping sequences, the transformed optimal frequency hopping sequences have higher security to resist the cryptanalytic method.
Abstract: Femtocells have been considered as a cost-effective solution to unload traffic from already overburdened macrocell networks in 4G cellular networks. The severe interference in spectrum-sharing macro and femto networks may cause User-equipment (UE) to experience outage. We derive an utmost isotropic Spatial Poisson point process (SPPP) density for Femtocell access points (FAPs) under the UEs' outage constraints. Based on the derived isotropic SPPP density, we propose a distributed transmit probability self-regulation scheme for an FAP to adapt its transmit probability per Transmission time interval (TTI). The scheme adjusts the homogeneous distributed FAPs in practice deployment to the proposed isotropic one. Simulation results show that the derived density can fulfill the outage probability constraints of UEs while accommodating the maximum femtocells. The self-regulation scheme can adapt the femtocell transmit probabilities to provide reliable downlink service, for even a large number of femtocells per cell site.
Abstract: This paper discussed the characteristics of addressing from the perspective of Internet addressing mechanism. An Internet of things (IOT) resource addressing iteration model was defined. In the model, a direct addressing mode for active nodes and an indirect addressing mode for passive codes were proposed, which meet the requirement for multiple encoding mode. A unified IOT resource lightweight addressing scheme based on IPv6 has been proposed to implement the two addressing modes. The scheme utilized the virtual domain to solve the problem of the heterogeneous encoding. The paper implemented the addressing process from the Internet host to the sensor node based on IPv6 over low-power wireless personal area networks (6LoWPAN) protocol. The experiment results show that the scheme is performed to realize communication between wireless sensor networks and IPv6 networks.
Abstract: The time-varying characteristic of wireless channel under the high-speed mobile environments in tunnels causes the Doppler spread to the transmitted signals, which affects the performance of wireless communication systems. The real-time Doppler effect simulation methodology directly based on Radio frequency (RF) circuits is proposed to simulate different Doppler spread effects in real environments. Mixers and a Digital-to-analog (DA) converter circuit are utilized to spread the spectrum of RF signals. A PC platform with the interface written in C# is configured to control the spectrum spread parameters. This radio channel emulator with the proposed methodology can replace the expensive fading simulating instruments with only 25.1ns system delay. Such an emulator has been applied to test the Multi-carrier wireless information local loop (McWiLL) wireless vehicle communication system in the laboratory to meet the requirement of metro Communication based train control (CBTC) system.
Abstract: In order to meet different delay requirements of various communication services in Cognitive radio (CR) networks, Secondary users (SUs) are divided into two classes according to the priority of accessing to spectrum in this paper. Based on the proactive spectrum handoff scheme, the Preemptive resume priority (PRP) M/G/1 queueing is used to characterize multiple spectrum handoffs under two different spectrum handoff strategies. The traffic-adaptive spectrum handoff strategy is proposed for graded SUs so as to minimize the average cumulative handoff delay. Simulation results not only verify that our theoretical analysis is valid, but also show that the strategy we proposed can reduce the average cumulative handoff delay evidently. The effect of service rate on the proposed spectrum switching point and the admissible access region are provided.
Abstract: The Magnetically-coupled resonant (MCR) technology is exploited in this paper to realize Synchronous wireless information and power transfer (SWIPT) function, which means that the power carriers also transmit information. The circuit structure of SWIPT system is analyzed and the existence of two optimal frequencies in power efficiency under small resistance circumstance is proved. The physical parameters having influences on the two optimal frequencies are discussed, such as the distance between coils, impedance characteristics of coils and loads. These results provide a way to increase the bandwidth of MCR technology, while maintaining high power efficiency to realize SWIPT function. Simulations and experimental results are presented to verify the feasibility of the proposed system and obtained theoretical expressions.
Abstract: Partial transmit sequence (PTS) is one of effective technique to reduce high Peak-to-average power ratio (PAPR) in Orthogonal frequency division multiplexing (OFDM) system. However, the complexity of Original PTS (O-PTS) increases exponentially with the number of sub-blocks. To reduce the computational complexity while still offering a lower PAPR, a new PTS method is proposed to search for suboptimal rotating vectors in this paper. In the proposed method, the candidate rotation vectors are generated based on greedy and genetic algorithm. We also combine the proposed method and the superimposed training sequence method to get a further PAPR reduction. The theory and simulations results show that the proposed method can achieve better PAPR reduction and significantly reduce the computational complexity.
Abstract: Ciphertext-policy attribute-based encryption (CP-ABE) is becoming a promising solution to guarantee data security in cloud computing. In this paper, we present an attribute-based secure data sharing scheme with Efficient revocation (EABDS) in cloud computing. Our scheme first encrypts data with Data encryption key (DEK) using symmetric encryption and then encrypts DEK based on CP-ABE, which guarantees the data confidentiality and achieves fine-grained access control. In order to solve the key escrow problem in current attribute based data sharing schemes, our scheme adopts additively homomorphic encryption to generate attribute secret keys of users by attribute authority in cooperation with key server, which prevents attribute authority from accessing the data by generating attribute secret keys alone. Our scheme presents an immediate attribute revocation method that achieves both forward and backward security. The computation overhead of user is also reduced by delegating most of the decryption operations to the key server. The security and performance analysis results show that our scheme is more secure and efficient.
Abstract: A new high-gain cylindrical Dielectric resonator antenna (DRA) with a large bandwidth is proposed. A cylindrical Dielectric resonator (DR), a double-annular patch and a metallic cylinder are used to obtain a large bandwidth and a high gain. The mode TM12 excited in the patch is used to enhance the gain of the DRA, and the cavity formed by the metallic cylinder provides a further higher gain and a larger bandwidth. The measured results demonstrate that the proposed DRA achieves a large bandwidth of 23% from 5.3 to 6.8GHz with VSWR less than two and a high gain around 11 dBi.
Abstract: A two-section Folded rectangular groove waveguide (FRGWG) Slow wave structure (SWS) Traveling wave tube (TWT) with large dimension of beam tunnel is studied. Compared with the Folded waveguide (FWG) under the same size parameters conditions, the interaction impedance and center frequency of the FRGWG are higher. The advantage is that a beam tunnel with large dimension can be applied to the FRGWG without the influence caused by signal decrease, reflection and oscillation. The microwave amplification capability based on beam-wave interaction is obtained through the particle-in-cell method. This circuit structure can produce an output power of over 100W ranging from 136 to 142GHz when the operation voltage and beam current are set as 18.4kV and 150mA, respectively, for a 95mm long circuit.
Abstract: The Adaptive integral method (AIM) in conjunction with the best uniform approximation technique is applied to analyze the electromagnetic problems of surface-wire junction geometries over a wide frequency band. To improve the computation efficiency, the best uniform approximation method is utilized. The AIM can reduce memory requirements and accelerate the matrix-vector multiplications in iterative process. Some numerical examples are shown to demonstrate the efficiency and accuracy of the proposed method. Compared with the direct solution method and Asymptotic waveform evaluation (AWE) technique, the proposed technique is found to be efficient in a broadband with the lower Central processing unit (CPU) time required and without loss of accuracy.
Abstract: In this work, the thermal conduction property of thermoelectric microwave power sensors is researched. The fabrication of the thermoelectric microwave power sensor consists of a front side and a back side processing using GaAs Monolithic microwave integrated circuit (MMIC) process and MEMS technology. An isolation structure on the front side is designed to prevent the thermal conduction from the resistor to the Coplanar waveguide (CPW). A thin-membrane on the back side is designed to prevent the thermal conduction from the resistor to the substrate. For the microwave power sensor without an isolation structure, the sensitivity is about 0.138, 0.136, 0.132, 0.115 and 0.111mV/mW at 8, 9, 10, 11 and 12GHz, respectively. For the microwave power sensor with an isolation structure, the sensitivity is about 0.142, 0.139, 0.135, 0.117 and 0.115mV/mW at 8, 9, 10, 11 and 12GHz, respectively. As a result, the higher thermal conduction efficiency and the higher sensitivity are obtained for the optimized thermoelectric microwave power sensors.