We propose an effective technique for estimation of targets by ground penetrating radar (GPR) using model-based compressive sensing (CS). We demonstrate the technique's performance by applying it to detection of buried landmines. The conventional CS algorithm enables the reconstruction of sparse subsurface images using much reduced measurement by exploiting its sparsity. However, for landmine detection purposes, CS faces some challenges because the landmine is not exactly a point target and also faces high level clutter from the propagation in the medium. By exploiting the physical characteristics of the landmine using model-based CS, the probability of landmine detection can be increased. Using a small pixel size, the landmine reflection in the image is represented by several pixels grouped in a three dimensional plane. This block structure can be used in the model based CS processing for imaging the buried landmine. The evaluation using laboratory data and datasets obtained from an actual mine field in Cambodia shows that the model-based CS gives better reconstruction of landmine images than conventional CS.

The ordered successive interference cancellation (OSIC) detector based on the minimum mean square error (MMSE) criterion has been proved to be a low-complexity detector with efficient bit error rate (BER) performance. As the well-known MMSE-Based OSIC detector, the MMSE-Based vertical Bell Laboratories Layered Space-Time (VBLAST) detector, whose computational complexity is cubic, can not attain the minimum BER performance. Some approaches to reducing the BER of the MMSE-Based VBLAST detector have been contributed, however these improvements have large computational complexity. In this paper, a low complexity MMSE-Based OSIC detector called MMSE-OBEP (ordering based on error probability) is proposed to improve the BER performance of the previous MMSE-Based OSIC detectors, and it has cubic complexity. The proposed detector derives the near-exact error probability of the symbols in the MMSE-Based OSIC detector, thus giving priority to detect the symbol with the smallest error probability can minimize the error propagation in the MMSE-Based OSIC detector and enhance the BER performance. We show that, although the computational complexity of the proposed detector is cubic, it can provide better BER performance than the previous MMSE-Based OSIC detector.

This paper deals with the security of chaos-based “true” random number generators (RNG)s. An attack method is proposed to analyze the security weaknesses of chaos-based RNGs and its convergence is proved using a master slave synchronization scheme. Attack on a RNG based on a double-scroll attractor is also presented as an example. All secret parameters of the RNG are revealed where the only information available is the structure of the RNG and a scalar time series observed from the double-scroll attractor. Simulation and numerical results of the proposed attack method are given such that the RNG doesn't fulfill NIST-800-22 statistical test suite, not only the next bit but also the same output bit stream of the RNG can be reproduced.

The increasing demand for navigation and automation has led to the development of a number of accurate and precise navigation applications that make use of the Global Navigation Satellite System (GNSS) and additional sensors. One of the precise navigation techniques in GNSS, the real-time kinematic (RTK) technique, is well known. In this method, once the correct integer ambiguities are found in the carrier phase observation data, position can be determined to within 10cm. In particular, the advent of QZSS and BeiDou satellites can increase the availability of RTK-GNSS (relative to RTK using only GPS). It is understood that the increasing availability of RTK-GNSS will improve the performance of the integration of GNSS with additional sensors because the errors due to the inertial measurement unit (IMU) accumulate as time goes on. On the other hand, GNSS tends to suffer from multipath errors, especially in urban environments. To overcome this problem, a method was developed for improving RTK-GNSS using a low-cost IMU and conventional vehicle speed sensors. In this study, the quality of the complete observation data was assessed based on the carrier-to-noise ratio and satellite elevation angle, and the least-squares ambiguity decorrelation adjustment method and the ratio test were used to obtain fixed positions. We used speed information obtained from Doppler measurements as an alternative source of information; information from the IMU and vehicle speed sensor (integrated with the RTK-GNSS via a Kalman Filter) was used when there were no visible satellites. We also used the IMU and vehicle speed sensors to detect wrong fixes in the RTK-GNSS. A position and orientation system for land vehicles (Applanix) was used to estimate the reference positions. During GNSS outages, it is important to accurately determine the last heading of the car for precise navigation. In this study, it was found that GNSS Doppler-based direction data are required to obtain better direction information. The results of the experiment demonstrate that our proposed method is, to some extent, beneficial as an alternative to the conventional RTK-GPS in an urban environment.

This paper describes a hierarchical and cooperative transport system with demand responsive buses to improve service quality of public transport system in city area and its suburbs. To provide the demand responsive buses generally requires planning route and schedule called dial-a-ride problem. However, the problem complexity increases with the increasing of the number of requests. Therefore, we propose the hierarchical and cooperative transport system. Framework of the system can reduce scale of the problem by grouping customers. We have evaluated the proposed system on a static simulation and a dynamic microscopic simulation. The simulation result has shown the system could improve service quality by reducing customer's load. Moreover, the result of the dynamic simulation have provided the detailed features of the system.

This letter proposes a situation-adaptive detection algorithm for the improved efficiency of the detection performance and complexity in the MIMO-OFDM system. The proposed algorithm adaptively uses the QRD-M, DFE, and iterative detection scheme in according to the detection environment. Especially, the proposed algorithm effectively reduces the occurrence probability of error in the successive interference cancellation procedure by the unit of the spatial stream. The simulations demonstrate that the adaptive detection method using the proposed algorithm provides a better trade-off between detection performance and complexity in the MIMO-OFDM system.

In this paper, we present a weighted-polarization wearable multiple-input multiple-output (MIMO) antenna that is based on radio-frequency (RF) signal processing to realize ultra-high-speed and high-capacity mobile communications. The proposed antenna is comprised of three orthogonal dipoles, two of which can be selected according to a weight function in different usage scenarios. The weight function is determined by considering the variation in the cross-polarization power ratio (XPR) and the antenna inclination angle which depend on the radio-propagation environment and human motion. To confirm the suitability of the proposed antenna, we perform preliminary experiments to evaluate the channel capacity of a weighted-polarization wearable MIMO antenna with an arm-swinging dynamic phantom. The measured and analytical results are in good agreement, which verifies the effectiveness of the proposed antenna. We demonstrate that the proposed antenna is suitable for realizing gigabit mobile communications in future wearable MIMO applications.

The key factors in overcoming for weak global navigation satellite systems (GNSS) signal acquisition are sensitivity and dwell time. In the conventional MAX/TC criteria, a preset threshold value is used to determine whether the signal exists. Thus the threshold is calculated carefully to balance the sensitivity and the dwell time. Affected by various environment noise and interference, the acquisition circuit will enter verifying mode frequently to eliminate false alarms, which will extend the mean acquisition time (MAT). Based on the periodicity of spread spectrum code in GNSS, this paper presents an improved double-dwell scheme that uses no threshold in detecting weak GNSS signals. By adopting this method, the acquisition performance of weak signal is significantly improved. Theoretical analysis and numerical simulation are presented detailed. Compared with the conventional MAX/TC criteria, the proposed method achieves improved performance in terms of detection probability and false alarm rate. Furthermore, the MAT decreases 15s when C/N0 is above 20dB-Hz. This can enhance the receiver sensitivity and shorten the time to first fix (TTFF).

There is a strong push towards the ultra-realistic presentation of multimedia contents made possible by the latest advances in computational and signal processing technologies. Three-dimensional sound presentation is necessary to convey a natural and rich multimedia experience. Promising ways to achieve this include the sound field reproduction technique known as high-order Ambisonics (HOA). While these advanced methods are now within the capabilities of consumer-level processing systems, their adoption is hindered by the lack of contents. Production and coding of the audio components in multimedia focus on traditional formats such as stereophonic sound. Mainstream audio codecs and media such as CDs or DVDs do not support advanced, rich contents such as HOA encodings. To ameliorate this problem and speed up the adoption of spatial sound technologies, this paper proposes a novel way to downmix HOA contents into a stereo signal. The resulting data can be distributed using conventional methods such as audio CDs or as the audio component of an internet video stream. The results can be listened to using legacy stereo reproduction systems. However, they include spatial information encoded as the inter-channel level and phase differences. The proposed method consists of a downmixing filterbank which independently modulate inter-channel differences at each frequency bin. The proposal is evaluated using simple test signals and found to outperform conventional methods such as matrix-encoded surround and the Ambisonics UHJ format in terms of spatial resolution. The proposal can be coupled with a previously presented method to recover HOA signals from stereo recordings. The resulting system allows for the preservation of full-surround spatial information in ultra-realistic contents when they are transferred using a stereo stream. Simulation results show that a compatible decoder can accurately recover up to five HOA channels from a stereo signal (2nd order HOA data in the horizontal plane).

In PQCrypto 2013, Yasuda, Takagi and Sakurai proposed a new signature scheme as one of multivariate public key cryptosystems (MPKCs). This scheme (called YTS) is based on the fact that there are two isometry classes of non-degenerate quadratic forms on a vector space with a prescribed dimension. The advantage of YTS is its efficiency. In fact, its signature generation is eight or nine times faster than Rainbow of similar size. For the security, it is known that the direct attack, the IP attack and the min-rank attack are applicable on YTS, and the running times are exponential time for the first and the second attacks and sub-exponential time for the third attack. In the present paper, we give a new attack on YTS whose approach is to use the diagonalization of matrices. Our attack works in polynomial time and it actually recovers equivalent secret keys of YTS having 140-bits security against min-rank attack in around fifteen seconds.

In many movies, social conditions and awareness of the issues of the times are depicted in any form. Even if fantasy and science fiction are works far from reality, the character relationship does mirror the real world. Therefore, we try to understand social conditions of the real world by analyzing the movie. As a way to analyze the movies, we propose a method of estimating interpersonal relationships of the characters, using a machine learning technique called Markov Logic Network (MLN) from movie script databases on the Web. The MLN is a probabilistic logic network that can describe the relationships between characters, which are not necessarily satisfied on every line. In experiments, we confirmed that our proposed method can estimate favors between the characters in a movie with F-measure of 58.7%. Finally, by comparing the relationships with social indicators, we discussed the relevance of the movies to the real world.

This letter proposes a novel post-processing method for self-similarity based super-resolution (SR). Existing back-projection (BP) methods enhance SR images by refining the reconstructed coarse high-frequency (HF) information. However, it causes artifacts due to interpolation and excessively smoothes small HF signals, particularly in texture regions. Motivated by these observations, we propose a novel post-processing method referred to as middle-frequency (MF) based refinement. The proposed method refines the reconstructed HF information in the MF domain rather than in the spatial domain, as in BP. In addition, it does not require an internal interpolation process, so it is free from the side-effects of interpolation. Experimental results show that the proposed algorithm provides superior performance in terms of both the quantity of reproduced HF information and the visual quality.

In this paper, a method for designing of Incremental Granular Model (IGM) based on integration of Linear Regression (LR) and Linguistic Model (LM) with the aid of fuzzy granulation is proposed. Here, IGM is designed by the use of information granulation realized via Context-based Interval Type-2 Fuzzy C-Means (CIT2FCM) clustering. This clustering approach are used not only to estimate the cluster centers by preserving the homogeneity between the clustered patterns from linguistic contexts produced in the output space, but also deal with the uncertainty associated with fuzzification factor. Furthermore, IGM is developed by construction of a LR as a global model, refine it through the local fuzzy if-then rules that capture more localized nonlinearities of the system by LM. The experimental results on two examples reveal that the proposed method shows a good performance in comparison with the previous works.

In this letter, an effective acoustic feedback cancellation algorithm is proposed based on the normalized sub-band adaptive filter (NSAF). To improve the confliction between fast convergence rate and low misalignment in the NSAF algorithm, a variable step size is designed to automatically vary according to the update state of the filter. The update state of the filter is adaptively detected via the normalized distance between the long term average and the short term average of the tap-weight vector. Simulation results demonstrate that the proposed algorithm has superior performance in terms of convergence rate and misalignment.

Recent work on joint word segmentation, POS (Part Of Speech) tagging, and dependency parsing in Chinese has two key problems: the first is that word segmentation based on character and dependency parsing based on word were not combined well in the transition-based framework, and the second is that the joint model suffers from the insufficiency of annotated corpus. In order to resolve the first problem, we propose to transform the traditional word-based dependency tree into character-based dependency tree by using the internal structure of words and then propose a novel character-level joint model for the three tasks. In order to resolve the second problem, we propose a novel semi-supervised joint model for exploiting n-gram feature and dependency subtree feature from partially-annotated corpus. Experimental results on the Chinese Treebank show that our joint model achieved 98.31%, 94.84% and 81.71% for Chinese word segmentation, POS tagging, and dependency parsing, respectively. Our model outperforms the pipeline model of the three tasks by 0.92%, 1.77% and 3.95%, respectively. Particularly, the F1 value of word segmentation and POS tagging achieved the best result compared with those reported until now.

This paper presents a new methodology of the over-the-air (OTA) assessment for vertically arranged multiple-input multiple-output (MIMO) array antennas. Particular emphasis is placed on how well handset MIMO antennas with a vertically arranged structure are characterized using the limited number of scatterers implemented in a fading emulator. First we studied the mechanism of the arrangement of scatterers on the variation of channel responses using a proposed three-dimensional analytical model. It is shown that the condition of a 3D-OTA with the prescribed parameters allows the correlation to be reduced, which permits the channel capacity to increase in the same manner that sufficient scatterers are distributed over the entire solid angle. Then the appropriate scatterers arrangement for a 3D-OTA instrument considering the number of DUT antenna elements and multipath characteristics is investigated. The analytical results show that a suitable scatterers arrangement can be determined for various conditions of multipath environments and numbers of array elements, and that the arrangement can be employed for designing an actual 3D-OTA apparatus.

Linear cryptanalysis proposed by Matsui is one of the most effective attacks on block ciphers. Some attempts to improve linear cryptanalysis have been made since Matsui introduced. We focus on how to optimize linear cryptanalysis with such techniques, and we apply the optimized linear cryptanalysis on FEAL-8X. First, we evaluate two existing implementation methods so as to optimize the computation time of linear cryptanalysis. Method 1 removes redundant round function computations and optimizes the other computation of linear cryptanalysis by transforming it into bitwise operations. Method 2 transforms the computation of linear cryptanalysis into a matrix multiplication and reduces the time complexity of the multiplication using the fast Fourier transform (FFT). We implement both methods optimized for modern microprocessors and compare their computation time to clarify the appropriate method for practical cryptanalysis. From the result, we show that the superior implementation depends on the number of given known plaintexts (KPs) and that of guessed key bits. Furthermore, we show that these results enable us to select the superior method to implement linear cryptanalysis without another comparative experiment. By using the superior method, we implement the multiple linear cryptanalysis (MLC) on FEAL-8X. Our implementation can recover the secret key of FEAL-8X with 210KPs in practical computation time with non-negligible probability, and it is the best attack on FEAL-8X in data complexity.

The conventional bilateral motion estimation (BME) for motion-compensated frame rate up-conversion (MC-FRUC) can avoid the problem of overlapped areas and holes but usually results in lots of inaccurate motion vectors (MVs) since 1) the MV of an object between the previous and following frames is more likely to have no temporal symmetry with respect to the target block of the interpolated frame and 2) the repetitive patterns existing in video frame lead to the problem of mismatch due to the lack of the interpolated block. In this paper, a new BME algorithm with a low computational complexity is proposed to resolve the above problems. The proposed algorithm incorporates multi-resolution search into BME, since it can easily utilize the MV consistency between two adjacent pyramid levels and spatial neighboring MVs to correct the inaccurate MVs resulting from no temporal symmetry while guaranteeing low computational cost. Besides, the multi-resolution search uses the fast wavelet transform to construct the wavelet pyramid, which not only can guarantee low computational complexity but also can reserve the high-frequency components of image at each level while sub-sampling. The high-frequency components are used to regularize the traditional block matching criterion for reducing the probability of mismatch in BME. Experiments show that the proposed algorithm can significantly improve both the objective and subjective quality of the interpolated frame with low computational complexity, and provide the better performance than the existing BME algorithms.

This letter describes a speech enhancement algorithm for stereo signals corrupted by diffuse noise. It estimates the noise signal and also a beamformed target signal based on blind target signal cancelation derived from sparsity minimization. Enhanced target speech is obtained by Wiener filtering using both the signals. Experimental results demonstrate the effectiveness of the proposed method.

Facial paralysis is a popular clinical condition occurring in 30 to 40 patients per 100,000 people per year. A quantitative tool to support medical diagnostics is necessary. This paper proposes a simple, visual and robust method that can objectively measure the degree of the facial paralysis by the use of spatiotemporal features. The main contribution of this paper is the proposal of an effective spatiotemporal feature extraction method based on a tracking of landmarks. Our method overcomes the drawbacks of the other techniques such as the influence of irrelevant regions, noise, illumination change and time-consuming process. In addition, the method is simple and visual. The simplification helps to reduce the time-consuming process. Also, the movements of landmarks, which relate to muscle movement ability, are visual. Therefore, the visualization helps reveal regions of serious facial paralysis. For recognition rate, experimental results show that our proposed method outperformed the other techniques tested on a dynamic facial expression image database.