Microwave imaging techniques, in particular synthetic aperture radar (SAR), are able to obtain useful images even in adverse weather or darkness, which makes them suitable for target position or feature estimation. However, typical SAR imagery is not informative for the operator, because it is synthesized using complex radio signals with greater than 1.0 m wavelength. To deal with the target identification issue for imaging radar, various automatic target recognition (ATR) techniques have been developed. One of the most promising ATR approaches is based on neural network classification. However, in the case of SAR images heavily contaminated by random or speckle noises, the classification accuracy is severely degraded because it only compares the outputs of neurons in the final layer. To overcome this problem, this paper proposes a self organized map (SOM) based ATR method, where the binary SAR image is classified using the unified distance matrix (U-matrix) metric given by the SOM. Our numerical analyses and experiments on 5 types of civilian airplanes, demonstrate that the proposed method remarkably enhances the classification accuracy, particular in lower S/N situations, and holds a significant robustness to the angular variations of the observation.

In camera-based object recognition and classification, surface color is one of the most important characteristics. However, apparent object color may differ significantly according to the illumination and surface conditions. Such a variation can be an obstacle in utilizing color features. Geusebroek et al.'s color invariants can be a powerful tool for characterizing the object color regardless of illumination and surface conditions. In this work, we analyze the estimation process of the color invariants from RGB images, and propose a novel invariant feature of color based on the elementary invariants to meet the circular continuity residing in the mapping between colors and their invariants. Experiments show that the use of the proposed invariant in combination with luminance, contributes to improve the retrieval performances of partial object image matching under varying illumination conditions.

This paper presents a compact metal plate lens antenna for evaluating a wave absorber placed on ceiling of the ETC gate. The focal distance of the lens was derived to be 129 cm by the geometrical optics procedure. By arranging the lens in front of a horn antenna, the gain and beamwidth characteristics were improved from 18 dBi to 26 dBi and from 22 degrees to 7 degrees, respectively. Then the antenna characteristics were evaluated when the distance between the antenna and the lens was changed in order to miniaturize the lens antenna. As the result, the changes in beamwidth were held to within 1 dB when the lens came close to the horn antenna. Scattering, phase and electric field intensity of electromagnetic wave were evaluated to clarify the foundation of the given characteristics. It was found that the field intensity for the miniaturized lens antenna is stronger than that for GO designed one though the phase uniformity is worse. The distance between the horn antenna and lens can be reduced to 80 cm. The absorption characteristics for the arranged absorbers which have different absorptions were measured, and it was shown that the proposed method was suitable for specifying the deteriorated absorber in the ETC system.

In this letter, we focus on detecting a random primary user (PU) network for cognitive radio systems in a cooperative manner by using maximum likelihood (ML) detection. Different from traditional PU network models, the random PU network model in this letter considers the randomness in the PU network topology, and so is better suited for describing the infrastructure-less PU network such as an ad hoc network. Since the joint pdf required for the ML detection is hard to obtain in a closed form, we derive approximate ones from the Gaussian approximation. The performance of the proposed algorithm is comparable to the optimal one.

The non-homogeneous Poisson process (NHPP) has been applied successfully to model nonstationary counting phenomena for a large class of problems. In software reliability engineering, the NHPP-based software reliability models (SRMs) are of a very important class. Since NHPP is characterized by its rate (intensity) function, which is known as the software failure rate of NHPP-based SRM, it is of great interest to estimate accurately the rate function from observed software failure data. In the existing work the same authors introduced a Haar-wavelet-based technique for this problem and found that the Haar wavelet transform provided a very powerful performance in estimating software failure rate. In this paper, we consider the application potentiality of a Daubechies wavelet estimator in the estimation of software failure rate, given the software failure time data. We give practical solutions by overcoming technical difficulties in applying the Daubechies wavelet estimator to the real software failure time data.

The present paper proposes a new method for constructing polyphase asymmetric zero-correlation zone (A-ZCZ) sequence sets. The proposed method can generate A-ZCZ sequence sets that cannot be obtained from methods proposed by other researchers and is a generalized version of our previously proposed method. An A-ZCZ sequence set can be regarded as a ZCZ sequence set. The newly obtained A-ZCZ sequence sets include quasi-optimal ZCZ sequence sets of which the zero-cross-correlation zone (ZCCZ) length between different sequence subsets is larger than the mathematical upper bound of conventional ZCZ sequence sets. A new method for extending the A-ZCZ sequence sets is also presented in the present paper.

In this paper, we propose a successive signal-to-leakage-plus-noise ratio (SLNR) based precoding with geometric mean decomposition (GMD) for the downlink multi-user multiple-input multiple-output (MU-MIMO) systems. The known leakages are canceled at the transmit side, and SLNR is calculated with the unknown leakages. GMD is applied to cancel the known leakages, so the subchannels for each receiver have equal gain. We further improve the proposed precoding scheme by ordering users. Simulation results show that the proposed schemes have a considerable bit error rate (BER) improvement over the original SLNR scheme.

In this letter, we propose a dissimilarity metric (DM) to measure the deviation of a cognitive radio from the network in terms of local sensing reports. Utilizing the probability mass function of the DM, we present a dissimilarity-based attacker detection algorithm to distinguish Byzantine attackers from honest users. The proposed algorithm is able to identify the attackers without a priori information of the attacking styles and is robust against both independent and dependent attacks.

This study proposes an efficient identity-based secure routing protocol based on Weil pairing, that considers symmetric and asymmetric links for Wireless Mesh Networks (WMNs). A wireless mesh network is a group of wireless mesh routers and several types of wireless devices (or nodes). Individual nodes cooperate by forwarding packets to each other, allowing nodes to communicate beyond the symmetric or asymmetric links. Asymmetric communication is a special feature of WMNs because of the wireless transmission ranges of different wireless devices may be different. The asymmetric link enhances WMN coverage. Ensuring security in WMNs has become an important issue over the last few years. Existing research on this topic tends to focus on providing security for routing and data content in the symmetric link. However, most studies overlook the asymmetric link in WMNs. This study proposes a novel distributed routing protocol that considers symmetric and asymmetric links. The proposed protocol guarantees the security and high reliability of the established route in a hostile environment, such as WMNs, by avoiding the use of unreliable intermediate nodes. The routes generated by the proposed protocol are shorter than those in prior studies. The major objective of the proposed protocol is to allow trustworthy intermediate nodes to participate in the path construction protocol. Using the proposed protocol, mesh clients out of mesh router wireless transmission range may discover a secure route to securely connect to the mesh router for Internet access. The proposed protocol enhances wireless mesh network coverage and assures security.

Code clones are duplicated or similar code fragments, and they have been known as major entities affecting the software maintainability. Sometimes there are “co-changes” in pair of code clones: when a code fragment is changed, the clone of the fragment is also changed. Such a co-change is one of key event to discuss the successful management of code clone. This paper analyzes the trends of co-changed code clones by using the length and the content of code clones. The empirical results show that: (1) there would be a specific length of clone to be mostly co-changed (around 60-100 tokens), and (2) code clones without any “control flow keywords” have a higher possibility to be co-changed than the others.

An exponential regression-based model with stochastic intensity is developed to describe the software reliability growth phenomena, where the software testing metrics depend on the intensity process. For such a generalized modeling framework, the common maximum likelihood method cannot be applied any more to the parameter estimation. In this paper, we propose to use the pseudo maximum likelihood method for the parameter estimation and to seek not only the model parameters but also the software reliability measures approximately. It is shown in numerical experiments with real software fault data that the resulting software reliability models based on four parametric approximations provide the better goodness-of-fit performance than the common non-homogeneous Poisson process models without testing metric information.

This paper presents the basic characteristics of a beam tilting slot antenna element whose forced resonance is realized by reactance loading; its structure complements that of a dipole antenna element. The radiation pattern is tilted using a properly determined driving point position; a single loading reactance is used to obtain the forced resonance without great changes in the tilt angle. Numerical results show that the reactance element needs to be loaded near the driving point in order to obtain the forced resonance of the antenna and the minimum changes in the beam tilt angle at the same time. When the proposed forced resonant beam tilting slot antenna with a 0.8 λ length is driven at -0.2 λ from the center, the main beam tilt angle of 57.7 degrees and the highest power gain of 3.8 dB are obtained. This slot element has a broad bandwidth, unlike the complementary dipole element.

In this paper, we propose a novel method of measuring the perceived picture quality of H.264 coded video based on parametric analysis of the coded bitstream. The parametric analysis means that the proposed method utilizes only bitstream parameters to evaluate video quality, while it does not have any access to the baseband signal (pixel level information) of the decoded video. The proposed method extracts quantiser-scale, macro block type and transform coefficients from each macroblock. These parameters are used to calculate spatiotemporal image features to reflect the perception of coding artifacts which have a strong relation to the subjective quality. A computer simulation shows that the proposed method can estimate the subjective quality at a correlation coefficient of 0.923 whereas the PSNR metric, which is referred to as a benchmark, correlates the subjective quality at a correlation coefficient of 0.793.

This paper presents a new hybrid speed function needed to perform image segmentation within the level-set framework. The proposed speed function uses both the boundary and region information of objects to achieve robust and accurate segmentation results. This speed function provides a general form that incorporates the robust alignment term as a part of the driving force for the proper edge direction of an active contour, an active region term derived from the region partition scheme, and the smoothing term for regularization. First, we use an external force for active contours as the Gradient Vector Flow field. This is computed as the diffusion of gradient vectors of a gray level edge map derived from an image. Second, we partition the image domain by progressively fitting statistical models to the intensity of each region. Here we adopt two Gaussian distributions to model the intensity distribution of the inside and outside of the evolving curve partitioning the image domain. Third, we use the active contour model that has the computation of geodesics or minimal distance curves, which allows stable boundary detection when the model's gradients suffer from large variations including gaps or noise. Finally, we test the accuracy and robustness of the proposed method for various medical images. Experimental results show that our method can properly segment low contrast, complex images.

This letter proposes an efficient local descriptor for wide-baseline dense matching. It improves the existing Daisy descriptor by combining intensity-based Haar wavelet response with a new color-based ratio model. The color ratio model is invariant to changes of viewing direction, object geometry, and the direction, intensity and spectral power distribution of the illumination. The experiments show that our descriptor has high discriminative power and robustness.

Recently, a flexible loss recovery scheme, called Active Caching (AC) has been proposed to accomplish a Desired Communication Reliability (DCR) about the whole data packets at a source depending on the various applications. However, since AC does not consider the packet delivery rate of each wireless link on multi-hop forwarding paths, it increases the number of totally transmitted packets to achieve a DCR and thus grows the energy consumption of sensor nodes. Thus, this letter proposes a novel recovery scheme which can minimize the number of totally transmitted packets while satisfying a DCR. By geometric programming, the proposed scheme allocates an optimized one-hop packet transmission rate of each wireless link on the multi-hop forwarding path.

It is well known that Boolean functions used in stream and block ciphers should have high algebraic immunity to resist algebraic attacks. Up to now, there have been many constructions of Boolean functions achieving the maximum algebraic immunity. In this paper, we present several constructions of rotation symmetric Boolean functions with maximum algebraic immunity on an odd number of variables which are not symmetric, via a study of invertible cyclic matrices over the binary field. In particular, we generalize the existing results and introduce a new method to construct all the rotation symmetric Boolean functions that differ from the majority function on two orbits. Moreover, we prove that their nonlinearities are upper bounded by .

In this paper, we present a new biometric verification system. The proposed system employs a novel biometric hashing scheme that uses our proposed quantization method. The proposed quantization method is based on error-correcting output codes which are used for classification problems in the literature. We improve the performance of the random projection based biometric hashing scheme proposed by Ngo et al. in the literature [5]. We evaluate the performance of the novel biometric hashing scheme with two use case scenarios including the case where an attacker steals the secret key of a legitimate user. Simulation results demonstrate the superior performance of the proposed scheme.

A simple DFT-based noise variance estimator for orthogonal frequency division multiplexing access (OFDMA) systems is proposed. The conventional DFT-based estimator differentiates the channel impulse response and noise in the time domain. However, for partial frequency response, its time domain signal will leak to all taps due to the windowing effect. The noise and channel leakage power become mixed. In order to accurately derive the noise power, we propose a novel symmetric extension method to reduce the channel leakage power. This method is based on the improved signal continuity at the boundaries introduced by symmetric extension. Numerical results show that the normalized mean square error (NMSE) of our proposed method is significantly lower than that of the conventional DFT method.

Face image hashing is an emerging method used in biometric verification systems. In this paper, we propose a novel face image hashing method based on a new technique called discriminative projection selection. We apply the Fisher criterion for selecting the rows of a random projection matrix in a user-dependent fashion. Moreover, another contribution of this paper is to employ a bimodal Gaussian mixture model at the quantization step. Our simulation results on three different databases demonstrate that the proposed method has superior performance in comparison to previously proposed random projection based methods.