A sanitizable signature scheme allows a semi-trusted party, designated by a signer, to modify pre-determined parts of a signed message without interacting with the original signer. To date, many sanitizable signature schemes have been proposed based on various cryptographic techniques. However, previous works are usually built upon the paradigm of dividing a message into submessages and applying a cryptographic primitive to each submessage. This methodology entails the computation time (and often signature length) in linear proportion to the number of sanitizable submessages. We present a new approach to constructing sanitizable signatures with constant overhead for signing and verification, irrespective of the number of submessages, both in computational cost and in signature size.

The Laplacian support vector machine (LSVM) is a semi-supervised framework that uses manifold regularization for learning from labeled and unlabeled data. However, the optimal kernel parameters of LSVM are difficult to obtain. In this paper, we propose a multi-kernel LSVM (MK-LSVM) method using multi-kernel learning formulations in combination with the LSVM. Our learning formulations assume that a set of base kernels are grouped, and employ l2 norm regularization for automatically seeking the optimal linear combination of base kernels. Experimental testing reveals that our method achieves better performance than the LSVM alone using synthetic data, the UCI Machine Learning Repository, and the Caltech database of Generic Object Classification.

Thin films of a divinyl derivative of tetraphenyldiaminobiphenyl DvTPD were prepared by vapor deposition followed by annealing. After annealing at 200°C for 1 h, the film became practically insoluble to organic solvents due to polymerization. Electrical characteristics of the films were measured by current-voltage measurement, time-of-flight measurement, and dielectric measurement. It was found that the hole mobility of DvTPD decreases when the film is polymerized. As a consequence of the decrease of hole mobility, carrier balance in the emissive layer of an organic light emitting diode (OLED) was improved, leading to a higher quantum efficiency and a pure emission spectrum. The dielectric measurement also confirmed the high thermal stability of the polymerized film.

Precise estimation of data distribution with a small number of sample patterns is an important and challenging problem in the field of statistical pattern recognition. In this paper, we propose a novel method for estimating multimodal data distribution based on the Gaussian mixture model. In the proposed method, multiple random vectors are generated after classifying the elements of the feature vector into subsets so that there is no correlation between any pair of subsets. The Gaussian mixture model for each subset is then constructed independently. As a result, the constructed model is represented as the product of the Gaussian mixture models of marginal distributions. To make the classification of the elements effective, a graph cut technique is used for rearranging the elements of the feature vectors to gather elements with a high correlation into the same subset. The proposed method is applied to a character recognition problem that requires high-dimensional feature vectors. Experiments with a public handwritten digit database show that the proposed method improves the accuracy of classification. In addition, the effect of classifying the elements of the feature vectors is shown by visualizing the distribution.

This paper presents a novel automated microwave filter tuning method based on successive optimization of phase and amplitude characteristics. We develop an optimization procedure to determine how much the adjusting screws of a filter should be rotated. The proposed filter tuning method consists of two stages; coarse and fine tuning stages. In the first stage, called coarse tuning, the phase response error of the target filter is minimized so that the filter roughly approximates almost ideal bandpass characteristics. Then in the second stage, called fine tuning, two different amplitude response errors are minimized in turn and then the resulting filter well approximate the ideal characteristics. Performance of the proposed tuning procedure is evaluated through some experiments of actual filter tuning.

Sequences with good correlation properties are of substantial interest in many applications. By interleaving a perfect array with shift sequences, a new method of constructing binary array set with zero correlation zone (ZCZ) is presented. The interleaving operation can be performed not only row-by-row but also column-by-column on the perfect array. The resultant ZCZ binary array set is optimal or almost optimal with respect to the theoretical bound. The new method provides a flexible choice for the rectangular ZCZ and the set size.

In this article, a simple structure of the Wilkinson power divider which can suppress the nth harmonics of the Wilkinson power divider is proposed. By replacing the quarter wavelength transmission lines of the conventional Wilkinson power divider with the equivalent P-type transmission lines, a compact power divider which can suppress the nth harmonic is achieved. Design equations of proposed P-type line are achieved by ABCD matrices. To verify the design approach, the proposed power divider is designed, simulated (by ADS, CST Studio, and Sonnet simulators), and fabricated at 1 GHz to suppress the fifth harmonic. The proposed structure is 46% of the conventional Wilkinson power divider, while maintaining the characteristics of the conventional Wilkinson power divider at the fundamental frequency. The insertion losses at the fifth harmonic are larger than 35 dB. Furthermore, the second to seventh harmonic are suppressed by least 10 dB. Here is an excellent agreement between simulated results and measured results.

In this letter, the compensation ability of nonlinear distortions for loudspeaker systems is demonstrated using dynamic distortion measurement. Two linearization methods using a Volterra filter and a Mirror filter are compared. The conventional evaluation utilizes swept multi-sinusoidal waves. However, it is unsatisfactory because wideband signals such as those of music and voices are usually applied to loudspeaker systems. Hence, the authours use dynamic distortion measurement employing a white noise. Experimental results show that the two linearization methods can effectively reduce nonlinear distortions for wideband signals.

Iris recognition is an important biometric method for personal identification. The accuracy of an iris recognition system highly depends on the success of an iris segmentation step. In this paper, a robust and accurate iris segmentation algorithm for closed-up NIR eye images is developed. The proposed method addressed problems of different characteristics of iris databases using local image properties. A precise pupil boundary is located with an adaptive thresholding combined with a gradient-based refinement approach. A new criteria, called a local signal-to-noise ratio (LSNR) of an edge map of an eye image is proposed for localization of the iris's outer boundary. The boundary is modeled with a weighted circular integral of LSNR optimization technique. The proposed method is experimented with multiple iris databases. The obtained results demonstrated that the proposed iris segmentation method is robust and desirable. The proposed method accurately segments iris region, excluding eyelids, eyelashes and light reflections against multiple iris databases without parameter tunings. The proposed iris segmentation method reduced false negative rate of the iris recognition system by half, compared to results obtained using Masek's method.

This paper proposes a probabilistic modeling learning algorithm for the local search approach to the Multiple-Valued Logic (MVL) networks. The learning model (PMLS) has two phases: a local search (LS) phase, and a probabilistic modeling (PM) phase. The LS performs searches by updating the parameters of the MVL network. It is equivalent to a gradient decrease of the error measures, and leads to a local minimum of error that represents a good solution to the problem. Once the LS is trapped in local minima, the PM phase attempts to generate a new starting point for LS for further search. It is expected that the further search is guided to a promising area by the probability model. Thus, the proposed algorithm can escape from local minima and further search better results. We test the algorithm on many randomly generated MVL networks. Simulation results show that the proposed algorithm is better than the other improved local search learning methods, such as stochastic dynamic local search (SDLS) and chaotic dynamic local search (CDLS).

This letter introduces a new fairness concept, namely proportional quasi-fairness and proves that the optimal end-to-end rate of a network utility maximization can be proportionally quasi-fair with a properly chosen network utility function for an arbitrary compact feasible set.

In this letter, we generalize the binary sequence introduced by Li et al. in [S. Q. Li et al., On the randomness generalized cyclotomic sequences of order two and length pq, IEICE Trans. Fund, vol. E90-A, no.9, pp.2037-2041, 2007] to sequence over arbitrary prime fields. Furthermore, the auto-correlation distribution and linear complexity of the proposed sequence are presented.

This letter studies application of the growing PSO to the design of DC-AC inverters. In this application, each particle corresponds to a set of circuit parameters and moves to solve a multi-objective problem of the total harmonic distortion and desired average power. The problem is described by the hybrid fitness consisting of analog objective function, criterion and digital logic. The PSO has growing structure and dynamic acceleration parameters. Performing basic numerical experiments, we have confirmed the algorithm efficiency.

We consider the problem of transmit power and bit rate allocation for OFDM based cognitive radio systems. An efficient allocation algorithm which mainly consists of two steps is proposed to maximize the sum rate of secondary users. In the first step of the algorithm, original nonlinear problem is converted to a convex problem which is solved by dual methods, and in the second step the final resource allocation results is obtained via iterative power rescale operation. Numerical results show the effectiveness of the proposed algorithm.

To reduce the inaccuracy caused by inappropriate time window, we propose two probabilistic fault localization schemes based on the idea of "extending time window." The global window extension algorithm (GWE) uses a window extension strategy for all candidate faults, while the on-demand window extension algorithm (OWE) uses the extended window only for a small set of faults when necessary. Both algorithms can increase the metric values of actual faults and thus improve the accuracy of fault localization. Simulation results show that both schemes perform better than existing algorithms. Furthermore, OWE performs better than GWE at the cost of a bit more computing time.

The scattering of a plane wave from the end-face of a three-dimensional waveguide system composed of a large number of cores is treated by the volume integral equation for the electric field and the first order term of a perturbation solution for TE and TM wave incidence is analytically derived. The far scattered field does not almost depend on the polarization of an incident wave and the angle dependence is described as the Fourier transform of the incident field in the cross section of cores. To clarify the dependence of the scattering pattern on the arrangement of cores some numerical examples are shown.

The turn of the century is witnessing radical changes in the way information services are spreading due to the progress of IT and the constantly increase in the number of users of the WWW. Therefore, the business market is changing its strategy for a modern online business environment. Autonomous Decentralized Database System (ADDS), based on autonomous coordinating subsystems, has been proposed as a system architecture in order to meet the innovative e-business requirements for consistency and high response among distributed database systems. Autonomy and decentralization of subsystems help achieving high response time in highly competitive situation and autonomous Mobile Agent based coordination has been proposed to achieve flexibility in a highly dynamic environment. In this paper, it is analyzed the case in which the system size increases; and a multi agent coordination, the same number of mobile agents and sites coexist in the system, is proposed for achieving the timeliness property. The response time in the system is conformed by those transactions that require coordination and those that can be satisfied immediately. In accordance, the distribution of the data in the system for coordination is a medullar issue for the improvement of the response time. A trade-off exits between these two kind of transactions depending on the coordination of the Mobile Agents, the capacity of allocating data among the sites, and as well as the distribution of the data and user requests in the system. In this sense, since the system requires high response time, a data allocation technology in which each mobile agent autonomously determine its own capacity for adjusting data among the sites is proposed. Thus, the system will adapt itself to the dynamic environment. The effectiveness of the proposed architecture and technologies are evaluated by simulation.

This paper discusses speaker verification (SV) using Gaussian mixture models (GMMs), where only utterances of enrolled speakers are required. Such an SV system can be realized using artificially generated cohorts instead of real cohorts from speaker databases. This paper presents a rational approach to set GMM parameters for artificial cohorts based on statistics of GMM parameters for real cohorts. Equal error rates for the proposed method are about 10% less than those for the previous method, where GMM parameters for artificial cohorts were set in an ad hoc manner.

A sanitizable signature scheme is a signature scheme which, after the signer generates a valid signature of a message, allows a specific entity (sanitizer) to modify the message for hiding several parts. Existing sanitizable signature schemes require the message to be divided into pre-defined blocks before signing so that each block can be sanitized independently. However, there are cases where the parts of the message which are needed to be sanitized can not be determined in the time of signing. Thus, it is difficult to decide the partition of the blocks in such cases. Since the length of the signature is usually proportional to the number of blocks, signing every bit independently will make the signature too long. In this paper, we propose a solution by introducing a new concept called sequential bitwise sanitizable signature schemes, where any sequence of bits of the signed document can be made sanitizable without pre-defining them, and without increasing the length of signature. We also show that a one-way permutation suffices to get a secure construction, which is theoretically interesting in its own right, since all the other existing schemes are constructed using stronger assumptions.

In this paper, we have derived a novel integral representation for the ground wave propagation over land-to-sea mixed-paths by applying the Helmholtz-Kirchhoff integral theorem. By using the method of stationary phase applicable uniformly as the stationary phase point approaches the endpoint of the integral, we have derived the asymptotic solution for the scattered fields consisting of the first-order and the second-order diffraction terms. We show that the asymptotic solution thus derived agrees with the asymptotic solution derived by applying the aperture field method (AFM) and the method of stationary phase. We have confirmed the validity and the utility of the novel integral representation and its asymptotic solution by comparing with the widely used mixed-path theorem and the experimental measurement performed in Kanto area and Tokyo bay.