Abstract: Ciphertext-policy attribute-based encryption (CP-ABE) allows a user with some attributes to decrypt the ciphertexts associated with these attributes. Though several CP-ABE schemes with the constant size ciphertext were proposed to reduce the communication cost, their master public and secret keys still have the size linear in the total number of attributes. These schemes are unpractical for the attribute-scalable and many-attributes scenario. A new CP-ABE scheme is proposed. Each attribute is mapped to a mathematical value by a combination method. The master public and secret keys of the proposed CP-ABE scheme have the size linear in the binary size of a hash function's range. It has the comparable performance with existing schemes in the aspects like the time costs of encryption and decryption, the expressiveness of access policy and the provable security.
Abstract: A new feature selection method is proposed for high-dimensional data clustering on the basis of data field. With the potential entropy to evaluate the importance of feature subsets, features are filtered by removing unimportant features or noises from the original datasets. Experiments show that the proposed method can sharply reduce the number of dimensions and effectively improve the clustering performance on WDBC dataset.
Abstract: Laser soldering process was introduced in Universal serial bus (USB) 2.0 electric connector to improve the mechanical and electrical bonding reliability. While, the effects of laser soldering technology on electric connector solder joints need to be estimated completely, especially on power consumption. The combined method based on numerical simulation and the Accelerated temperature experiment (ATE) was developed to analyze the power consumption of USB 2.0 electric connector in this paper. The ATE contains thermal cycle and thermal shock tests, and the four-electrode method is used to obtain the conductivity of solder joints. Numerical modeling and analysis was used to quantify the power consumption and optimize the geometry of solder joints, because the electric experimental measurements of power consumption during ATE are time-costing and often intractable. Accurate knowledge of the power consumption is a prerequisite for the reliability of the electric connector.
Abstract: In order to improve the general detection accuracy of eye state, this paper puts forward an innovative method for judging human eye state based on PERCLOS. After pretreatment of the eye image, Hough transformation is used for ellipse detection and pupil position. The gray projection variance threshold analysis is then used to help make the final detection. Freeman chain and the Snake model algorithm are used for the corner detection and precise calculation of the height of an open eye. Thus the PERCLOS value and the eye state can be figured out. The performance of our eye state recognition algorithm is validated by more than 1000 images within product database. The statistics result shows that the fatigue detection accuracy rate can meet the need of usage in complex environment.
Abstract: We present an improved gate charge model for High electron mobility transistors (HEMTs) that is direct formulated from the branch charges. Different charge modeling procedures based on the charge conservation principle have been discussed and the proposed model is more accurate, easier to be implemented into commercial simulators. An improved modeling method on channel length modulation parameter to account for the drain-current kink effect of HEMTs has also been introduced. The nonlinear model is verified by comparing the measurements and simulations using 0.25-μm gate-length GaAs HEMT devices.
Abstract: A novel Power-on-reset (POR) circuit is proposed with ultra-low steady-state current consumption. A band-gap voltage comparator is used to generate a stable pull-up voltage. To eliminate the large current consumptions of the analog part, a power switch is adopted to cut the supply of band-gap voltage comparator, which gained ultra-low current consumption in steady-state after the POR rest process completed. The state of POR circuit is maintained through a state latch circuit. The whole circuit was designed and implemented in 65nm CMOS technology with an active area of 120μm*160μm. Experimental results show that it has a steady pull-up voltage of 0.69V and a brown-out voltage of 0.49V under a 1.2V supply voltage rising from 0V, plus its steady-state current is only 9nA. The proposed circuit is suitable to be integrated in system on chip to provide a reliable POR signal.
Abstract: Various multi-layered bus architectures are now being used in the SoC industry. Reckless use of bus layers may result in low utilization of communication resource and waste silicon area. This paper introduces a quantitative analysis at the initial stage of SoC design. The time complexity is examined and it is found that their scale is the order of n to the power of n, or combinatorial, and thus the problem is NP-complete. The paper proposes some heuristic methods through in-depth investigation and applies them to each step of the exploration to reduce the time complexity. The exploration processes and the proposed methods are implemented as a software program and several experiments are performed. From the results, the performance of SNP turns out to be significantly enhanced and achieves 25% enhancement in comparison with a de-facto standard bus, AXI. For time complexity, the reduction ratio goes down to 3.7×10-6.
Abstract: Energy management is emerging as an important issue for High performance computing (HPC) owning to high operational cost and low reliability. Compared with low-power architectural approach, energy-aware scheduling based on Dynamic voltage scaling (DVS) and Dynamic power management (DPM) is regarded as a promising way since it is practical and low-cost. At present, most studies focus on pure DVS or non-DVS environment, while most high performance computing systems are hybrid non-DVS/DVS platforms. We propose an energy-aware scheduling algorithm for parallel application to consider both DVS and non-DVS characteristics of hybrid system. We present the rule of task assignment, make analysis on DVS and DPM technique and give their mathematical formulation, which maintains makespan optimization and energy conservation. The clustering and merging algorithm, and priority computation method consider the situation of resource constraints. The extensive simulations demonstrate that the proposed algorithm has stronger ability of energy saving and time optimization than Heterogeneous earliest finish time (HEFT), Energy-efficient task duplication scheduling (EETDS) and Heterogeneous energy-aware duplication scheduling (HEADUS) algorithm no matter for synthetic workload or realistic workload.
Abstract: Microblog has emerged as a popular medium for providing new sources of information and rapid communications, particularly during burst topics. Burst keywords detection from real-time microblog streams is important for burst topics detection. The exiting algorithms may detect fake burst keywords without taking into account the trustworthiness of the users and human's daily timetable. Our work is the first to combine the trustworthiness of the users with burst keywords detection. We propose a novel approach to detect burst keywords based on social trust and dynamics model. We adapt basic notions of dynamics from physics and model keywords bursts as momentum change of the keywords. On the analogy of physical dynamics model, this approach defines mass as the trustworthiness of user and position as the frequency of keywords. We compute each keyword's burst value by using Moving average convergence/divergence (MACD) and determine whether it is a burst keyword in a given time window. The experimental results on large-scale Sina microblog dataset show that the proposed approach can avoid detecting fake burst keywords.
Abstract: Current parallel programs are often composed of lots of processes that communicate through message passing. The mapping of the program processes onto the underlying processor. By analyzing the MPI library, we find that the communication protocols have great influence upon the communication characteristics. The profiling information used by the existing process placement methods does not include the communication protocols. We propose and implement a method called Protocol-aware process placement (PaPP) to incorporate the influences of communication protocols into the mapping problem. We demonstrate the validations of PaPP by the experiments using NPB3.3-MPI benchmarks. The experimental results show that compared to basic process placement, the average execution time when using PaPP scheme is reduced by 9.5%.
Abstract: A metaheuristic chain based memetic algorithm namely MCMA is proposed for the classification of metabolomics data. MCMA regards both global evolution and local search as equivalent elemental metaheuristics, and searches with a chain of metaheuristics performed alternatively on the target problem. A hidden Markov model based scheduling mechanism is employed in MCMA for the selection of metaheuristics. By using MCMA for optimizing the linkage weight vector, a feature weighting algorithm for metabolomics data is formed to identify relevant metabolite features and reveal their exact relationships with the given physiological states. An extreme learning machine based classifier is utilized in predicting the physiological states according to the weighted metabolite features. Experimental results on real metabolomics data of clinical liver transplantation demonstrate that the proposed feature weighting and classification method obtains better performance than the other compared algorithms.
Abstract: Collaborative filtering can be classified into user-based or item-based methods according to different assumptions. Our experiment results show that both user-based and item-based methods can reach a certain degree of accuracy, but the recommendation coverage of these two methods is significantly different. This paper qualitatively analyzes the advantages and disadvantages of such two methods, and found that user-based methods advantage in recommending popular items while item-based methods perform better at suggesting long tail items. Based on this analysis, we proposes a novel machine learning framework to systematically combine both. We train a model for each user-item pair for discovering the local preference of the user or item over both methods, and effectively combine user-based and item-based predictions using the preference information. Experiment results show that our approach can significantly improve the recommendation quality, and to a certain extend, alleviate the data sparsity problem.
Abstract: In order to realize automatic region matching between source and target images, a multi-source local color transfer algorithm based on texture similarity is proposed.The source and target images are segmented into a set of regions using an image segmentation algorithm. It computes the texture features of each region through the gray level co-occurrence matrix and then constructs corresponding texture feature vectors. The authors measure the relevance between the target and source regions by computing the Euclidean distance between corresponding texture feature vectors. The source region having the largest relevance with the target region is selected as the transfer source. Complete the color transfer by performing color space transformation and linear conversion on color values. Experimental results concerning on multi-source local color transfer and gray image colorization verify the validity of the proposed algorithm.
Abstract: Various modulation methods for the Current Source Rectifier (CSR) controlling scheme have been investigated in recent years. The traditional modulation methods have the disadvantages such as the great computing cost, sensitivity to load and system parameter variation. In this study, an Artificial neural network (ANN) based algorithm is adopted to tackle the problem. This algorithm features parallel computation and self-tuning. The Random weight change (RWC) algorithm is employed for on-line parameter tuning to achieve better performance. The principle of the trilogic Space vector modulation (SVM) for CSR is introduced as the theoretical foundation. The proposed method is introduced in two parts, the constructing of the neural network and the designing of an on-line parameter tuning algorithm. The simulation results based on SABER software show that the new algorithm has a good performance, especially under a non-rated system load.
Abstract: In this paper, a new method for multidimensional frequency estimation of multiple sinusoids that combines the HOSVD (Higher-order singular value decomposition) subspace and projection separation approaches is presented. Frequency parameters in the first dimension are obtained by using the signal subspace of the first dimension which is extracted by the HOSVD decomposition. Subsequently, a set of projection separation matrices is constructed to project the measure tensor and separate the components of the received tensor into single ones. And then, the signal subspace of each dimension of separated measure tensor are estimated by the HOSVD decomposition and the desired multidimensional frequency pairing are automatically obtained. Simulation results are included to demonstrate the advantage of the proposed method over two existing methods in terms of performance as well computational load.
Abstract: The patch matching of the traditional Nonlocal means (NLM) filter mainly depends on structure similarity and cannot adapt to the patch rotation or mirroring transformation. Therefore, designing a measure with rotationally invariant similarity is of significant importance for improving the effectiveness of patch comparison of NLM. This paper proposes to apply a no-reference image content metric with the rotation-invariance to NLM for denoising Magnetic resonance (MR) images. The metric measures quantitatively the content of a patch in an image, including sharpness, contrast, and geometric features such as textures and edges. The metric values for every patch are computed and added into the Gaussian matching kernel of NLM so as to effectively perform patch matching. The main advantage of the proposed method is that it does not need to rotate patches in different orientations during patch matching. Experimental results show that the proposed method is superior to the traditional NLM, the state-of-the-art method Block-matching and 3-D (BM3D) filtering and the Unbiased NLM (UNLM) for MRI denoising.
Abstract: The integrality of moving objects is the basis for video-based object tracking and action analysis. But it often becomes unreliable as a result of shadow elimination when the object has similar properties with real shadow. The proposed methods manage to improve the integrality of detected moving objects as much as possible, by image matting operated on candidate shadow regions. Existing approaches for image matting require manual labeling of foreground and background. Considering the moving feature points in shadow may cause classification errors, we propose automatic scribbling methods based on Scale invariant feature transform (SIFT) and Speeded-up robust feature (SURF) respectively. Experiments demonstrate that our methods eliminate real shadow effectively and improve object segmentation in the case of object parts and shadows presenting similar characteristics.
Abstract: Compressed sensing based Magnetic resonance (MR) image reconstruction can be done by minimizing the sum of least square data fitting item, the Total variation (TV) and l1 norm regularizations. In this paper, inspired by the conventional constrained reconstruction model, we propose a hybrid weighted l1-TV minimization method to reconstruct MR image. We introduce the iterative mechanism to update the weights for l1 and TV norms adaptively. The weights vary at each element of the image matrix according to the presented weights selection strategy. Experiments on Shepp-Logan phantom and practical MR images demonstrate the proposed method can preserve image details and obtain improved reconstruction quality compared to the traditional CS-MRI method and other weighted methods.
Abstract: This paper presents the dynamic method for fault diagnosis based on the updating of Interval-valued belief structures (IBSs). The classical Jeffrey's updating rule and the linear updating rule are extended to the framework of IBSs. Both of them are recursively used to generate global diagnosis evidence with the form of Interval basic belief assignment (IBBA) by updating the previous evidence with the incoming evidence. The diagnosis decision can be made by global diagnosis evidence. In the process of evidence updating, the similarity factors of evidence are used to determine switching between the extended Jeffrey's and linear updating rules, and to calculate the linear combination weights. The diagnosis examples of machine rotor show that the proposed method can provide more reliable and accurate results than the diagnosis methods based on Dempster-Shafer evidence theory.
Abstract: Classic Perona-Malik (PM) model is usually used to smooth noise for the degraded image. However, to our knowledge, a well-known defect of the PM model is prone to cause ‘staircase’ effect and blur image fine feature because of the lack of correct diffusion strength in diffusion process. To tackle the problem, we will improve the PM model by developing a new structure descriptor to adjust anisotropic diffusion strength for smoothing noise and preserving image feature adaptively. The new structure descriptor is based on image local geometry-Hessian matrix, called difference eigenvalue, which can adaptively track edge feature and high degree of homogeneity in an image, even when the observed image is blurred. Experiments on both nature and medical images show that the improved PM method can achieve a superior performance than the traditional methods in terms of visual inspection and quantitative measurements.
Abstract: Let n=me and p be an odd prime. Let Fp be a finite field and Fpn be its nth field extension. By some polynomial GCD computations, this paper characterize the bentness and semi-bentness of two classes of p-ary quadratic functions from Fpn to Fp with coefficients in Fpe. Moreover, the enumeration formulas of constructed bent functions are obtained for some special cases of m. The results generalize some previous related work.
Abstract: This paper is devoted to the study of constacyclic codes over a non-chain ring R. The generator polynomials of all constacyclic codes over R are characterized and their dual codes are also determined. We also introduce a Gray map. It is proved that the image of a v-constacyclic code of length n over R under the Gray map is a cyclic code of length 2n over a field with p elements, where p is odd prime. Moreover, we obtain a substantial number of optimal p-ary linear (cyclic) codes, in terms of their parameters, via the Gray map.
Abstract: Attribute-based encryption (ABE) has been an active research area in cryptography due to its attractive applications. But almost all attribute-based encryption schemes are based on bilinear maps, which leave them vulnerable to quantum cryptanalysis. The lattice-based ABE schemes from the Learning with errors (LWE) have appeared, but they are not efficient enough for practical applications. Thus we propose an efficient attribute-based encryption based on the Learning with errors over Rings (R-LWE), which is called ABER-LWE. The security analysis shows that ABER-LWE scheme is secure in the selective-set model under the R-LWE assumption, whose security can reduce to the hardness of the shortest vector problem in the worst case on ideal lattices. The efficiency analysis indicates that ABER-LWE is more efficient than previous ABE cryptosystems on lattices.
Abstract: Per-flow queuing is believed to be able to guarantee advanced Quality of service (QoS) for each flow at high speed routers. With the dramatic increase for both link speed and number of traffic flows, per-flow queuing confronts a great challenge, since millions of queues need to be maintained for implementation in a traditional sense. In this paper, setting only a small number of physical queues, we propose a Dynamic per-flow queuing (DPFQ) mechanism that achievesthe same performance as per-flow queuing at a cost of an additional Binary content addressable memory (BCAM). The proposed mechanism works due to the fact that the number of simultaneous active flows at a mini-time scale in the router buffer is much smaller than that of in-progress flows. In DPFQ, a physical queue is created on demand when a new flow comes, and released when the flow temporarily pauses or finishes. A small BCAM is occupied to map flows to queues, so as to guarantee that only the packets from the same flow are buffered in any assigned queue. Through analysis and simulation we show that using a small number of physical queues, DPFQ achieves both low operation delay and power consumption.
Abstract: An authentication code can be constructed with a family of ε-Almost strong universal (ε-ASU) hash functions, with the index of hash functions as the authentication key. This paper considers the performance of authentication codes from ε-ASU, when the authentication key is only partially secret. We show how to apply the result to privacy amplification against active attacks in the scenario of two independent partially secret strings shared between a sender and a receiver.
Abstract: It has been proposed to deploy relay nodes for the sake of prolonging Wireless sensor networks (WSN) lifetime, such that sensors transmit the sensed data to them which in turn delivers the data to base stations. For survivability requirements, relay placements which considers fault tolerant ability have been noticed and studied. While related works are limited or most existing works don't take factors such as fault tolerance, or base stations into account comprehensively in two tired WSN. We focus on fault tolerant relay node placement in two-tiered heterogeneous WSN with base stations. As far as we know, fault tolerance contains two fundamental aspects, for one is multi-coverage and the second is multi-path. It is a NP-hard problem and figure out an approximation, whose approximation ratio is enhanced to be (18+ε). While a sub-problem approximation is also described as supplementary. Experimental results verify that the number of relay nodes deployed by our algorithm is somewhat superior to existed relay node placement solutions.
Abstract: In this paper, we partly determine the cycle structure of two types of Nonlinear feedback shift registers (NFSRs). Based on these results, the cycle structure of a class of NFSRs with symmetric feedback functions can be completely characterized. Furthermore, an alternative proof of Kjeldsen's results is presented. Compared with the original proof based on abstract algebra theory, ours is straightforward and easy to understand.
Abstract: This paper proposes an intra-PAN mobility management scheme for IPv6 over Low-power wireless personal area networks (6LoWPAN) on the basis of network-based idea. We developed a tree-like network architecture which includes coordinate nodes for packet routing. All of the control messages are designed to transmit in link layer, and the sensor nodes are free to consider care-of address and the mobile nodes are unnecessary to deal with any mobility handoff messages. The simulation results show that this scheme efficiently cuts down the signaling cost and reduces the energy consumed by fixed nodes which can extend the life time of the whole Personal area networks (PAN).
Abstract: Mobile wireless sensor networks (MWSNs) may be under attack due to their large-scale characteristics. One of the main threats is to inject malware into some nodes. To prevent malware from spreading in a largescale MWSN, an effective measure is to immunize susceptible nodes by disseminating and installing security patches. This work suggests a novel modeling framework and some mathematical models based on the pulse differential equation and the epidemic theory, in which the immunization operations are implemented on susceptible nodes in a pulse way. The maximum immunization period of time is derived to minimine the number of immunization operations while ensuring malware extinct over time in the MWSN. The theoretical results are confirmed by extensive simulations.
Abstract: Construction and count of 1-resilient Rotation symmetric Boolean functions (RSBFs) on pr variables are demonstrated. It is proved that constructions of 1-resilient RSBFs on pr variables are equivalent to solving an equation system. An accurate enumeration formula of all 1-resilient RSBFs on pr variables is also proposed. Some examples are given, and the exact numbers of 1-resilient RSBFs on 8 and 9 variables are obtained respectively.
Abstract: The performance of multiuser Continuous phase modulation(CPM) over the additive white Gaussian noise channel with coherent maximum likelihood detection is considered. Algorithms are developed to calculate the Euclidean distance spectra employing tree-search and A-star algorithm. The complexity of proposed algorithms are further reduced using trellis minimization. The distance spectrum is then used to evaluate the performance of multiuser CPM systems, which reveals that the performance of multiuser CPM can be significantly improved by using optimized parameters. Both equally-powered and non-equally powered systems are considered. Numerical and simulated results confirm that the proposed algorithms can generate the distance spectra of all systems with lower complexity relative to previous methods and are particularly suited for multi user CPM systems.
Abstract: A Group key agreement (GKA) protocol enables a group of communicating parties to negotiate a common secret key over an open, untrusted network. The design goal of GKA is to achieve secure group communication, which is an important research issue for mobile communication. The conventional (symmetric) GKA protocol allows a group of members to establish a common secret key for imbalanced mobile networks. However, only the group members can broadcast secret message to the group. To overcome this limitation, this paper proposes an authenticated asymmetric GKA protocol. Instead of a common secret key, each group member negotiates a common group public key and holds a different decryption key. The paper proposed protocol supports the dynamic nodes update of mobile networks, which has forward secrecy and backward secrecy of group key. This protocol is proven secure under the Bilinear Computational Diffie-Hellman problem assumption and the performance analysis shows that the proposed scheme is highly efficient.
Abstract: Hash function has been widely used in cryptographic field. This paper proposes a Hash function based on complexly Coupled chaotic map latices (CCML). It is equipped with new features of parallel and flexible processing. Parallelism indicates that the algorithm can reach high level of efficiency and speed. Flexibility means the length of Hash function and message block processed each time can be easily changed to adapt to practical demand. Experimental results show that the Hash function is one-way, with high plaintext sensitivity, as well as its strong capability for confusion and diffusion, and collision resistance. In comparison with MD5 and another Hash function based on chaos, the proposed Hash function shows good performance.
Abstract: We propose a new construction of identity-based encryption without key escrow over the tradition RSA cryptosystems. The security of our scheme follows from the decisional Diffie-Hellman assumption and the difficulty of Modular inversion hidden number problem with error (MIHNPwE), which can be seen as a generalization of the modular inversion hidden number problem. We give an analysis on the hardness of MIHNPwE by lattice techniques. In our construction, we generate each user's partial private key in the form of an MIHNPwE instance. The hardness of MIHNPwE provides our scheme with resistance against key-collusion attacks from any number of traitors. Our prototype implementation of the proposed scheme shows that it can be more computation efficient and easy-to-implementation than the influential pairing-friendly elliptic-curve based IBE scheme.
Abstract: Traditional refined track initiation methods for group targets have mistakes or loss of tracks when tracking irregular motions, for the reason that they rely on a stable relative position of group members. To solve the problem, a group dynamic model was introduced for proposing a new initiation algorithm and its whole framework. We made a self-adaptive improvement of the group separation on various group radii. After the pre-association of these groups, a state equation derived from the model was used for predictions of group members. Then a relational matrix was defined for refined data associations. Finally tracks were validated by logic-based method. Particular scenarios and Monte Carlo simulations showed that, compared with algorithms based on relative position, this algorithm has better performance on the adaptability to changes of a group structure and the correctness of initiation.
Abstract: In the space environment, Viterbi decoder implemented on SRAM-based FPGA is sensitive to Single event upsets (SEUs), which may lead to functional failure of the decoder. Conventional SEU mitigation techniques like modular redundancy could not exploit the characters of Viterbi decoders, therefore could not provide optimized SEU tolerance when the device resource utilization cost is a constraint. Leveraging the properties of the decoding algorithm, three effective mitigation techniques are adopted, including structure optimization, Error detection and correction (EDAC) for Block RAM (BRAM) protection, and Partial triple-modular redundancy (PTMR), which are applied to the modules of the decoder in accordance with their characteristics. Analysis of effectiveness shows that compared with unmitigated design, the SEU induced failure rate in the proposed SEU tolerant decoder can be reduced to 1/4 at the cost of 61.1% extra resource utilization.
Abstract: A new type of Substrate integrated waveguide end slot antenna (SIWESA) radiating from the waveguide end of a Substrate integrated waveguide(SIW) at X-band is investigated with simulation and experiment in this paper. A novel SIW transmission line and a SIWTL end matching network are developed to transfer the energy from the coaxial line to the SIW end radiating slot. This whole antenna is fabricated on a microwave substrate with standard PCB process. The simulated results of a single SIWESA are in good agreement with the experiment ones. Furthermore, a 4-element array are fabricated and measured. The good tested results and the low-cost PCB process fabrication technology demonstrate that SIWESA is a new candidate for the phased arrays.
Abstract: The conventional Wavenumber domain algorithm (WDA) employs Fast Fourier transform (FFT) to implement matched filter. It is characterized by its high precision SAR imaging. Compared with FFT, Fractional Fourier transform (FrFT) can provide lower and narrower sidelobes when it is applied to compress chirp signals at the optimal transform. This paper proposed a novel SAR imaging algorithm, termed FrWDA which replaces FFT in WDA with FrFT. The FrWDA was derived and its implementation was presented. How to choose the optimal transformation order was given subsequently. The FrWDA preserves high precision focusing, and has better performance on sidelobe suppression. The FrWDA is more suitable for the high precision SAR imaging, especially in target detection and recognition. Simulation results demonstrate that FrWDA provides better performance on focusing and sidelobe suppression compared with the classical FFT-based WDA.