At Eurocrypt'03, Boneh, Gentry, Lynn and Shacham proposed a pairing based verifiably encrypted signature scheme (the BGLS-VES scheme). In 2004, Hess mounted an efficient rogue-key attack on the BGLS-VES scheme in the plain public-key model. In this letter, we show that the BGLS-VES scheme is not secure in the proof of possession (POP) model.

Given a simple connected graph G with n vertices, the spanning tree problem involves finding a tree that connects all the vertices of G. Solutions to this problem have applications in electrical power provision, computer network design, circuit analysis, among others. It is known that highly efficient sequential or parallel algorithms can be developed by restricting classes of graphs. Circular trapezoid graphs are proper superclasses of trapezoid graphs. In this paper, we propose an O(n) time algorithm for the spanning tree problem on a circular trapezoid graph. Moreover, this algorithm can be implemented in O(log n) time with O(n/log n) processors on EREW PRAM computation model.

We study a static analysis problem on k-secrecy, which is a metric for the security against inference attacks on XML databases. Intuitively, k-secrecy means that the number of candidates of sensitive data of a given database instance or the result of unauthorized query cannot be narrowed down to k-1 by using available information such as authorized queries and their results. In this paper, we investigate the decidability of the schema k-secrecy problem defined as follows: for a given XML database schema, an authorized query and an unauthorized query, decide whether every database instance conforming to the given schema is k-secret. We first show that the schema k-secrecy problem is undecidable for any finite k>1 even when queries are represented by a simple subclass of linear deterministic top-down tree transducers (LDTT). We next show that the schema ∞-secrecy problem is decidable for queries represented by LDTT. We give an algorithm for deciding the schema ∞-secrecy problem and analyze its time complexity. We show the schema ∞-secrecy problem is EXPTIME-complete for LDTT. Moreover, we show similar results LDTT with regular look-ahead.

In this article, we propose a method to reduce the impact of primary traffic on spectrum sensing performance. In practice, the sensing performance is degraded by noise-only sample in the spectrum sensing time. Therefore, we employ a time of primary user (PU) signal arrival detector in order to remove the noise-only portion. Then, we employ equal-weight-based energy detection (EWED) to provide the detection decision. The analysis and simulation results show that there exists an optimal early time of arrival (ToA) false alarm which provides better performance compared to the use of a single EWED scheme.

In Long-Term Evolution (LTE)-Advanced, heterogeneous networks are important to further improve the system throughput per unit area. In heterogeneous network deployment, low power nodes such as picocells are overlaid onto macrocells. In the downlink, the combined usage of inter-cell interference coordination (ICIC), which is a technique that reduces the severe interference from macrocells by reducing the transmission power or stopping the transmission from the macrocells, and cell range expansion (CRE), which is a technique that expands the cell radius of picocells by biasing the received signal power, is very effective in improving the system and cell-edge user throughput. In this paper, we consider two types of ICIC. The first one reduces the transmission power from the macrocells (referred to as reduced power ICIC) and the second one stops the transmission from the macrocells (referred to as zero power ICIC). This paper investigates the impact of the reduction in the transmission power when using reduced power ICIC and the restriction on the modulation scheme caused by the reduction in the transmission power when using reduced power ICIC on the user throughput performance with the CRE offset value as a parameter. In addition, the throughput performance when applying reduced power ICIC is compared to that when applying zero power ICIC. Simulation results show that the user throughput with reduced power ICIC is not sensitive to the protected subframe ratio compared to that with zero power ICIC even if the modulation scheme is restricted to only QPSK in the protected subframes. This indicates that reduced power ICIC is more robust than zero power ICIC for non-optimum protected subframe ratios.

This paper deals with delay faults on clock lines assuming the launch-on-capture test. In this realistic fault model, the amount of delay at the FF driven by the faulty clock line is such that the scan shift operation can perform correctly even in the presence of a fault, but during the system clock operation, capturing functional value(s) at faulty FF(s), i.e. FF(s) driven by the clock with delay, is delayed and correct value(s) may not be captured. We developed a fault simulator that can handle such faults and using this simulator we investigate the relation between the duration of the delay and the difficulty of detecting clock delay faults in the launch-on-capture test. Next, we propose test generation methods for detecting clock delay faults that affect a single or two FFs. Experimental results for benchmark circuits are given in order to establish the effectiveness of the proposed methods.

Due to the growing popularity of High Dynamic Range (HDR) images and HDR displays, a large amount of existing Low Dynamic Range (LDR) images are required to be converted to HDR format to benefit HDR advantages, which give rise to some LDR to HDR algorithms. Most of these algorithms especially tackle overexposed areas during expanding, which is the potential to make the image quality worse than that before processing and introduces artifacts. To dispel these problems, we present a new LDR to HDR approach, unlike the existing techniques, it focuses on avoiding sophisticated treatment to overexposed areas in dynamic range expansion step. Based on a separating principle, firstly, according to the familiar types of overexposure, the overexposed areas are classified into two categories which are removed and corrected respectively by two kinds of techniques. Secondly, for maintaining color consistency, color recovery is carried out to the preprocessed images. Finally, the LDR image is expanded to HDR. Experiments show that the proposed approach performs well and produced images become more favorable and suitable for applications. The image quality metric also illustrates that we can reveal more details without causing artifacts introduced by other algorithms.

The string analysis is a static analysis of dynamically generated strings in a target program, which is applied to check well-formed string construction in web applications. The string analysis constructs a finite state automaton that approximates a set of possible strings generated for a particular string variable at a program location at runtime. A drawback in the string analysis is imprecision in the analysis result, leading to false positives in the well-formedness checkers. To address the imprecision, this paper proposes an improvement technique of the string analysis to make it perform more precise analysis with respect to input validation in web applications. This paper presents the improvement by annotations representing screening of a set of possible strings, and empirical evaluation with experiments of the improved analyzer on real-world web applications.

Substrate coupling of radio frequency (RF) components is represented by equivalent circuits unifying a resistive mesh network with lumped capacitors in connection with the backside of device models. Two-port S-parameter test structures are used to characterize the strength of substrate coupling of resistors, capacitors, inductors, and MOSFETs in a 65 nm CMOS technology with different geometries and dimensions. The consistency is finely demonstrated between simulation with the equivalent circuits and measurements of the test structures, with the deviation of typically less than 3 dB for passive and 6 dB for active components, in the transmission properties for the frequency range of interest up to 8 GHz.

Scale-Invariant Feature Transform (SIFT) has lately attracted attention in computer vision as a robust keypoint detection algorithm which is invariant for scale, rotation and illumination changes. However, its computational complexity is too high to apply in practical real-time applications. This paper proposes a low complexity keypoint extraction algorithm based on SIFT descriptor and utilization of the database, and its real-time hardware implementation for Full-HD resolution video. The proposed algorithm computes SIFT descriptor on the keypoint obtained by corner detection and selects a scale from the database. It is possible to parallelize the keypoint detection and descriptor computation modules in the hardware. These modules do not depend on each other in the proposed algorithm in contrast with SIFT that computes a scale. The processing time of descriptor computation in this hardware is independent of the number of keypoints because its descriptor generation is pipelining structure of pixel. Evaluation results show that the proposed algorithm on software is 12 times faster than SIFT. Moreover, the proposed hardware on FPGA is 427 times faster than SIFT and 61 times faster than the proposed algorithm on software. The proposed hardware performs keypoint extraction and matching at 60 fps for Full-HD video.

In this paper we propose a method to use features of an individual object to locate and recognize this object concurrently in a static image with Multi-feature fusion based on multiple objects sample library. This method is proposed based on the observation that lots of previous works focuses on category recognition and takes advantage of common characters of special category to detect the existence of it. However, these algorithms cease to be effective if we search existence of individual objects instead of categories in complex background. To solve this problem, we abandon the concept of category and propose an effective way to use directly features of an individual object as clues to detection and recognition. In our system, we import multi-feature fusion method based on colour histogram and prominent SIFT (p-SIFT) feature to improve detection and recognition accuracy rate. p-SIFT feature is an improved SIFT feature acquired by further feature extraction of correlation information based on Feature Matrix aiming at low computation complexity with good matching rate that is proposed by ourselves. In process of detecting object, we abandon conventional methods and instead take full use of multi-feature to start with a simple but effective way-using colour feature to reduce amounts of patches of interest (POI). Our method is evaluated on several publicly available datasets including Pascal VOC 2005 dataset, Objects101 and datasets provided by Achanta et al.

This paper describes algorithms for generating low intermodulation-distortion (IMD) two-tone sinewaves, for such as communication application ADC testing, using an arbitrary waveform generator (AWG) or a multi-bit ΣΔ DAC inside an SoC. The nonlinearity of the DAC generates distortion components, and we propose here eight methods to precompensate for the IMD using DSP algorithms and produce low-IMD two-tone signals. Theoretical analysis, simulation, and experimental results all demonstrate the effectiveness of our approach.

This paper provides a novel normalized sign least-mean square (NSLMS) algorithm which updates only a part of the filter coefficients and simultaneously performs sparse updates with the goal of reducing computational complexity. A combination of the partial-update scheme and the set-membership framework is incorporated into the context of L∞-norm adaptive filtering, thus yielding computational efficiency. For the stabilized convergence, we formulate a robust update recursion by imposing an upper bound of a step size. Furthermore, we analyzed a mean-square stability of the proposed algorithm for white input signals. Experimental results show that the proposed low-complexity NSLMS algorithm has similar convergence performance with greatly reduced computational complexity compared to the partial-update NSLMS, and is comparable to the set-membership partial-update NLMS.

Event extraction is vital to social media monitoring and social event prediction. In this paper, we propose a method for social event extraction from web documents by identifying binary relations between named entities. There have been many studies on relation extraction, but their aims were mostly academic. For practical application, we try to identify 130 relation types that comprise 31 predefined event types, which address business and public issues. We use structured Support Vector Machine, the state of the art classifier to capture relations. We apply our method on news, blogs and tweets collected from the Internet and discuss the results.

In this paper, 1) it is shown that amplitude-only images (AOIs) have quite wide intensity ranges (IRs), and 2) an IR reduction method for AOIs is proposed. An AOI is the inversely transformed amplitude spectra of an image, and it is used in the privacy- and copyright-protected image trading system because of its invisibility. Since an AOI is the coherent summation of cosine waves with the same phase, the IR of the AOI is too large to be stored and/or transmitted. In the proposed method, random signs are applied to discrete Fourier transformed amplitude coefficients to obtained AOIs with significantly lower IRs without distortion while keeping the invisibility of images. With reasonable processing time, high correct watermark extracting rates, inversely quantized AOIs with low mean squared errors, and reconstructed images with high peak signal-to-noise ratios are obtained by a linear quantizer in the proposed method.

The paper proposes the PMD method to design an introductory programming practice course plan that is inclusive for all learners and stable throughout a course. To achieve the course plan, the method utilizes personas, each of which represents learners having similar motivation to study programming. The learning of the personas is directed to the course goal with an enforcement resulting from the discipline, which is an integration of effective learning strategies with affective components of the persoans. Under the enforcement, services to facilitate and promote the learning of each persona can be decided, based on motivation components of each persona, motivational effects of the services, and the cycle of self-efficacy. The application of the method on about 500 freshmen in C programming practice course has shown this is a successful approach for designing courses.

This paper proposes a reduced-complexity multiband multiple-input multiple-output (MIMO) receiver that can be used in cognitive radios. The proposed receiver uses heterodyne reception implemented with a wide-passband band-pass filter in the radio frequency (RF) stage. When an RF Hilbert transformer is utilized in the receiver, image-band interference occurs because of the transformer's imperfections. Thus, the imperfection of the Hilbert transformer is corrected in the intermediate frequency (IF) stage to reduce the hardware complexity. First, the proposed receiver estimates the channel impulse response in the presence of the strong image-band interference signals. Next, the coefficients are calculated for the correction of the imperfection at the IF stage, and are fed back to the IF stage through a feedback loop. However, the imperfection caused by the digital-to-analog (D/A) converter and the baseband amplifier in the feedback loop corrupts the coefficients on the way back to the IF stage. Therefore, the proposed receiver corrects the imperfection of the analog devices in the feedback loop. The performance of the proposed receiver is verified by using computer simulations. The proposed receiver can maintain its performance even in the presence of strong image-band interference signals and imperfection of the analog devices in the feedback loop. In addition, this paper also reveals the condition for rapid convergence.

This paper analyzes the conventional unequal erasure protection (UXP) scheme for scalable video transmission, and proposes a dynamic hybrid UXP/ARQ transmission framework to improve the performance of the conventional UXP method for bandwidth-constrained scalable video transmission. This framework applies automatic retransmission request (ARQ) to the conventional UXP scheme for scalable video transmission, and dynamically adjusts the transmission time budget of each group of picture (GOP) according to the feedback about the transmission results of the current and previous GOPs from the receiver. Moreover, the parameter of target video quality is introduced and optimized to adapt to the channel condition in pursuit of more efficient dynamic time allocation. In addition, considering the play-out deadline constraint, the time schedule for the proposed scalable video transmission system is presented. Simulation results show that compared with the conventional UXP scheme and its enhanced method, the average peak signal to noise ratio (PSNR) of the reconstructed video can be improved significantly over a wide range of packet loss rates. Besides, the visual quality fluctuation among the GOPs can be reduced for the video which has much movement change.

Dynamic spectrum leasing (DSL) is regarded as a promising dynamic spectrum sharing (DSS) scheme both to improve the spectrum revenue of primary users (PUs) and to guarantee the QoS of secondary users (SUs). A pricing-based DSL termed PBDSL is formulated as a Stackelberg DSL game model, where PUs as players entering the interacting game with multiple SUs. The strategic design contains both optimal spectrum pricing schemes (including unit spectrum/interference price and interference sensitivity distributed adjustments) of PUs for the specific shared/leased spectrum and optimal transmission strategies (e.g., transmit power and bandwidth) of SUs. To capture two types of competition relationships among multiple SUs and between SUs and PUs, we investigate two intra-game models of multiple PUs and SUs, respectively, which interact with each other to constitute the final Stackelberg DSL game. The existence and uniqueness of Stackelberg equilibrium solution (SES) are analyzed and proved for presented games, based on which a joint multi-stage PBDSL algorithm is presented to approximate the optimal equilibrium strategies. Numerical results demonstrate the convergence property of the interactive decision-making process, and verify the effectiveness of the proposed algorithm, in a comparison with the Nash equilibrium solution (NES)-based approach.

This paper proposes a simple decentralized cell association method for heterogeneous networks, where low transmission-power pico or femto base stations (BSs) overlay onto a high transmission-power macro BS. The focus of this investigation is on the downlink and the purpose of cell association is to achieve better user fairness, in other words, to increase the minimum average user throughput (worst user throughput). In the proposed method, an appropriate cell association for all users within a cell is achieved in an iterative manner based on the feedback information of each individual user assisted by a small amount of broadcast information from the respective BSs. The proposed method does not require cooperation between BSs. Furthermore, the proposed method is applicable to cases of inter-cell interference coordination (ICIC) between macro and pico/femto BSs through the use of protected radio resources exclusively used by the pico/femto BSs. Based on numerical results, we show that the proposed method adaptively achieves better cell association for all users according to the user location distributions compared to the conventional cell range expansion (CRE) method. The advantage of the proposed method over CRE is further enhanced in an ICIC scenario.