In this paper, optimal control of multi-vehicle systems is studied. In the case where collision avoidance between vehicles and obstacle avoidance are imposed, state discretization is effective as one of the simplified approaches. Furthermore, using state discretization, cooperative actions such as rendezvous can be easily specified by linear temporal logic (LTL) formulas. However, it is not necessary to discretize all states, and partial states (e.g., the position of vehicles) should be discretized. From this viewpoint, a new control method for multi-vehicle systems is proposed in this paper. First, the system in which partial states are discretized is formulated. Next, the optimal control problem with constraints described by LTL formulas is formulated, and its solution method is proposed. Finally, numerical simulations are presented. The proposed method provides us a useful method in control of multi-vehicle systems.

Most recent work on cooperative spectrum sensing using cognitive radios has focused on issues involving the sensing channels and seemed to ignore those involving the reporting channels. Furthermore, no research has treated the effect of correlated composite Rayleigh-lognormal fading, also known as Suzuki fading, in cognitive radio. This paper proposes a technique for reuse of shadowed CRs, discarded during the sensing phase, as amplified-and-forward (AF) diversity relays for other surviving CRs to mitigate the effects of such fading in reporting channels. A thorough analysis of and a closed-form expression for the outage probability of the resulting cooperative AF diversity network in correlated composite Rayleigh-lognormal fading channels are presented in this paper. In particular, an efficient solution to the “PDF of sum-of-powers” of correlated Suzuki-distributed random variables using moment generating function (MGF) is proposed.

This letter presents a new blind audio watermarking scheme using eigenvalue decomposition (EVD). Initially, the original audio is divided into frames and the samples of each frame are arranged into a square matrix. EVD is applied to each of these matrices. Watermark data is embedded into the largest eigenvalue of each diagonal matrix by quantization. Data embedding rate of the proposed scheme is 172.39bps. Simulation results confirm the imperceptibility of the proposed scheme and its higher robustness against various attacks compared to the state-of-the-art watermarking methods available in the literature.

The maximization of non-Gaussianity is an effective approach to achieve the complex independent component analysis (ICA) problem. However, the traditional complex maximization of non-Gaussianity (CMN) algorithm does not consider the influence of noise. In this letter, a modification of the fixed-point algorithm is proposed for more practical occasions of the complex noisy ICA model. Simulations show that the proposed method demonstrates significantly improved performance over the traditional CMN algorithm in the noisy ICA model when the sample size is sufficient.

Chronic liver disease is a major worldwide health problem. Diagnosis and staging of chronic liver diseases is an important issue. In this paper, we propose a quantitative method of analyzing local morphological changes for accurate and practical computer-aided diagnosis of cirrhosis. Our method is based on sparse and low-rank matrix decomposition, since the matrix of the liver shapes can be decomposed into two parts: a low-rank matrix, which can be considered similar to that of a normal liver, and a sparse error term that represents the local deformation. Compared with the previous global morphological analysis strategy based on the statistical shape model (SSM), our proposed method improves the accuracy of both normal and abnormal classifications. We also propose using the norm of the sparse error term as a simple measure for classification as normal or abnormal. The experimental results of the proposed method are better than those of the state-of-the-art SSM-based methods.

This paper proposes an efficient two-scan labeling algorithm for binary hexagonal images. Unlike conventional labeling algorithms, which process pixels one by one in the first scan, our algorithm processes pixels two by two. We show that using our algorithm, we can check a smaller number of pixels. Experimental results demonstrated that our method is more efficient than the algorithm extended straightly from the corresponding labeling algorithm for rectangle binary images.

This paper shows a method to find a linear transformation that reduces the number of variables to represent a given incompletely specified index generation function. It first generates the difference matrix, and then finds a minimal set of variables using a covering table. Linear transformations are used to modify the covering table to produce a smaller solution. Reduction of the difference matrix is also considered.

In developing an automatic system of a single tooth length measurement on x-ray image, since a tooth shape is assumed to be straight and curve, an algorithm which can accurately deal with straight and curve is required. This paper proposes an automatic algorithm for measuring the length of single straight and curve teeth. In the algorithm consisting of control point determination, curve fitting, and length measurement, PCA is employed to find the first and second principle axes as vertical and horizontal ones of the tooth, and two terminal points of vertical axis and the junction of those axes are determined as three first-order control points. Signature is then used to find a peak representing tooth root apex as the forth control point. Bezier curve, Euclidean distance, and perspective transform are finally applied with determined four control points in curve fitting and tooth length measurement. In the experiment, comparing with the conventional PCA-based method, the average mean square error (MSE) of the line points plotted by the expert is reduced from 7.548 pixels to 4.714 pixels for tooth image type-I, whereas the average MSE value is reduced from 7.713 pixels and 7.877 pixels to 4.809 pixels and 5.253 pixels for left side and right side of tooth image type-H, respectively.

Boneh et al. proposed the new idea of pairing-based cryptography by using the composite order group instead of prime order group. Recently, many cryptographic schemes using pairings of composite order group were proposed. Miller's algorithm is used to compute pairings, and the time of computing the pairings depends on the cost of calculating the Miller loop. As a method of speeding up calculations of the pairings of prime order, the number of iterations of the Miller loop can be reduced by choosing a prime order of low Hamming weight. However, it is difficult to choose a particular composite order that can speed up the pairings of composite order. Kobayashi et al. proposed an efficient algorithm for computing Miller's algorithm by using a window method, called Window Miller's algorithm. We can compute scalar multiplication of points on elliptic curves by using a window hybrid binary-ternary form (w-HBTF). In this paper, we propose a Miller's algorithm that uses w-HBTF to compute Tate pairing efficiently. This algorithm needs a precomputation both of the points on an elliptic curve and rational functions. The proposed algorithm was implemented in Java on a PC and compared with Window Miller's Algorithm in terms of the time and memory needed to make their precomputed tables. We used the supersingular elliptic curve y2=x3+x with embedding degree 2 and a composite order of size of 2048-bit. We denote w as window width. The proposed algorithm with w=6=2·3 was about 12.9% faster than Window Miller's Algorithm with w=2 although the memory size of these algorithms is the same. Moreover, the proposed algorithm with w=162=2·34 was about 12.2% faster than Window Miller's algorithm with w=7.

Information-centric networking (ICN) is a promising architecture and has attracted much attention in the area of future Internet architectures. As one of the key technologies in ICN, in-network caching can enhance content retrieval at a global scale without requiring any special infrastructure. In this paper, we propose a workload-aware caching policy, LRU-GT, which allows cache nodes to protect newly cached contents for a period of time (guard time) during which contents are protected from being replaced. LRU-GT can utilize the temporal locality and distinguish contents of different popularity, which are both the characteristics of the workload. Cache replacement is modeled as a semi-Markov process under the Independent Reference Model (IRM) assumption and a theoretical analysis proves that popular contents have longer sojourn time in the cache compared with unpopular ones in LRU-GT and the value of guard time can affect the cache hit ratio. We also propose a dynamic guard time adjustment algorithm to optimize the performance. Simulation results show that LRU-GT can reduce the average hops to get contents and improve cache hit ratio.

In this paper, we consider a parallel ring-line rat-race circuit realized by replacing some parts of the ring-lines with composite right-/left-handed transmission lines (CRLH-TLs). For a conventional rat-race circuit, the minimum coupling factor is limited by the highest impedance of the ring-lines that can be manufactured by general printed circuit board (PCB) technologies. However, the coupling factor of the parallel ring-line type rat-race circuit proposed in this paper is determined by the difference between the admittances of the parallel ring-lines. As a result of designing parallel ring-line rat-race circuits having coupling factors of $-20$ and $-30$,dB for an operation frequency of 4,GHz, the proposed rat-race circuit realizes broadband characteristics of about 35.5% according to the numerical results for the $-20$,dB circuit. Furthermore, broadband characteristics including reflection, isolation, and couplings can be maintained for the fabricated $-20$,dB rat-race circuit up to an input power of 40,dBm.

Energy harvesting technology was introduced into wireless sensor networks (WSNs) to solve the problem of the short lifetimes of sensor nodes. The technology gives sensor nodes the ability to convert environmental energy into electricity. Sufficient electrical energy can lengthen the lifetime and improve the quality of service of a WSN. This paper proposes a novel use of mutual information to evaluate data transmission behavior in the energy harvesting WSNs. Data at a sink for a node deteriorates over time until the next periodic transmission from the node is received. In this paper, we suggest an optimized intermittent transmission method for WSNs that harvest energy. Our method overcomes the problem of information deterioration without increasing energy cost. We show that by using spatial correlation between different sensor nodes, our proposed method can mitigate information deterioration significantly at the sink.

This paper presents a novel filter to keep from over-smoothing the edges and corners and rectify the outliers in the flow field after each incremental computation step, which plays a key role during the process of estimating flow field. This filter works according to the spatial-temporal derivatives distance of the input image and velocity field distance, whose principle is more reasonable in filtering mechanism for optical flow than other existing nonlinear filters. Moreover, we regard the spatial-temporal derivatives as new powerful descriptions of different motion layers or regions and give a detailed explanation. Experimental results show that our proposed method achieves better performance.

A new real-time sound field transmission system is presented. To construct this system, a large listening area needs to be reproduced at not less than a constant height. Additionally, the driving signals of the loudspeakers should be obtained only from received signals of microphones. Wave field reconstruction (WFR) filtering for linear arrays of microphones and loudspeakers is considered to be suitable for this kind of system. An experimental system was developed to show the feasibility of real-time sound field transmission using the WFR filter. Experiments to measure the reproduced sound field and a subjective listening test of sound localization were conducted to evaluate the proposed system. Although the reproduced sound field included several artifacts such as spatial aliasing and faster amplitude decay, the experimental results indicated that the proposed system was able to provide sound localization accuracy for virtual sound sources comparable to that for real sound sources in a large listening area.

We propose a speaker adaptation method based on the probabilistic principal component analysis (PPCA) of acoustic models. We define a training matrix which is represented in a two-way array and decompose the training models by PPCA to construct bases. In the two-way array representation, each training model is represented as a matrix and the columns of each training matrix are treated as training vectors. We formulate the adaptation equation in the maximum a posteriori (MAP) framework using the bases and the prior.

A new stock index trend analysis approach is proposed in this paper, which is based on a newly developed signal decomposition approach - adaptive Fourier decomposition (AFD). AFD can effectively extract the signal's primary trend, which specifically suits the Dow Theory based technique analysis. The proposed approach integrates two different kinds of forecasting approaches, including the Dow theory the RBF neural network. Effectiveness of the proposed approach is assessed through comparison with the direct RBF neural network approach. The result is proved to be promising.

This paper proposes a so called quasi-linear support vector machine (SVM), which is an SVM with a composite quasi-linear kernel. In the quasi-linear SVM model, the nonlinear separation hyperplane is approximated by multiple local linear models with interpolation. Instead of building multiple local SVM models separately, the quasi-linear SVM realizes the multi local linear model approach in the kernel level. That is, it is built exactly in the same way as a single SVM model, by composing a quasi-linear kernel. A guided partitioning method is proposed to obtain the local partitions for the composition of quasi-linear kernel function. Experiment results on artificial data and benchmark datasets show that the proposed method is effective and improves classification performances.

The present study aims to investigate the effect of voluntary movements on human temporal perception in multisensory integration. We therefore performed temporal order judgment (TOJ) tasks in audio-tactile integration under three conditions: no movement, involuntary movement, and voluntary movement. It is known that the point of subjective simultaneity (PSS) under the no movement condition, that is, normal TOJ tasks, appears when a tactile stimulus is presented before an auditory stimulus. Our experiment showed that involuntary and voluntary movements shift the PSS to a value that reduces the interval between the presentations of auditory and tactile stimuli. Here, the shift of the PSS under the voluntary movement condition was greater than that under the involuntary movement condition. Remarkably, the PSS under the voluntary movement condition appears when an auditory stimulus slightly precedes a tactile stimulus. In addition, a just noticeable difference (JND) under the voluntary movement condition was smaller than those under the other two conditions. These results reveal that voluntary movements alternate the temporal integration of audio-tactile stimuli. In particular, our results suggest that voluntary movements reverse the temporal perception order of auditory and tactile stimuli and improve the temporal resolution of temporal perception. We discuss the functional mechanism of shifting the PSS under the no movement condition with voluntary movements in audio-tactile integration.

One of the most important problems in web services application is the integration of different existing services into a new composite service. Existing work has the following disadvantages: (i) developers are often required to provide a composite service model first and perform formal verifications to check whether the model is correct. This makes the synthesis process of composite services semi-automatic, complex and inefficient; (ii) there is no assurance that composite services synthesized by using the fully-automatic approaches are correct; (iii) some approaches only handle simple composition problems where existing services are atomic. To address these problems, we propose a correct assurance approach for automatically synthesizing composite services based on finite state machine model. The syntax and semantics of the requirement model specifying composition requirements is also proposed. Given a set of abstract BPEL descriptions of existing services, and a composition requirement, our approach automatically generate the BPEL implementation of the composite service. Compared with existing approaches, the composite service generated by utilizing our proposed approach is guaranteed to be correct and does not require any formal verification. The correctness of our approach is proved. Moreover, the case analysis indicates that our approach is feasible and effective.

We consider the method of evaluating the detection performance of a single pulse monostatic radar for a fluctuating target in compound-Gaussian clutter plus noise background. The system uses a coded pulse compression waveform as its transmitting signal and the linear minimum mean square error (LMMSE) based reiterated filtering, also known as the adaptive pulse compression (APC). We study the theoretical statistical characteristics of the amplitude of the APC estimation for infinite iterations in this scenario. Based on this theory, we derive both the theoretical probability of false alarm and the probability of detection for the ‘ideal constant false alarm rate (CFAR)’ detector that uses amplitude of the APC estimation as the test statistics. Finaly, we verify the validity of the theoretical detection performance calculations with Monte Carlo simulations. The simulations include three different compound-Gaussian clutter models and all theoretical results well fit the simulated ones.