Recently, a novel approach to color image compression based on colorization has been presented. The conventional method for colorization-based image coding tends to lose the local oscillation of chrominance components that the original images had. A large number of color assignments is required to restore these oscillations. On the other hand, previous studies suggest that an oscillation of a chrominance component correlates with the oscillation of a corresponding luminance component. In this paper, we propose a new colorization-based image coding method that utilizes the local correlation between texture components of luminance and chrominance. These texture components are obtained by a total variation regularized energy minimization method. The local correlation relationships are approximated by linear functions, and their coefficients are extracted by an optimization method. This key idea enables us to represent the oscillations of chrominance components by using only a few pieces of information. Experimental results showed that our method can restore the local oscillation and code images more efficiently than the conventional method, JPEG, or JPEG2000 at a high compression rate.

Recently, social network services are rapidly growing and this trend is expected to continue in the future. Social network data can be published for various purposes such as statistical analysis and population studies. When social network data are published, however, the privacy of some people may be disclosed. The most straightforward manner to preserve privacy in social network data is to remove the identifiers of persons from the social network data. However, an adversary can infer the identity of a person in the social network by using his/her background knowledge, which consists of content information such as the age, sex, or address of the person and structural information such as the number of persons having a relationship with the person. In this paper, we propose a privacy protection method for social network data. The proposed method anonymizes social network data to prevent privacy attacks that use both content and structural information, while minimizing the information loss or distortion of the anonymized social network data. Through extensive experiments, we verify the effectiveness and applicability of the proposed method.

Using a single-site lightning location technique, a new portable lightning location system is developed. We incorporate an attitude detection technique using inertial sensors to detect an accurate electromagnetic field vector of sferics by palm-sized electromagnetic sensors which can have arbitrary attitude. The present paper describes the concept and the performance of the developed prototype of the portable system.

We study joint rate control and resource allocation with a packet collision constraint that maximizes the total utility of secondary users in cognitive radio networks. We formulate and decouple the original optimization problem into separable subproblems and then develop an algorithm that converges to optimal rate control and resource allocation. The proposed algorithm can operate on different time-scales to reduce the amortized time complexity.

This paper considers the normalization of Miller functions for computing “point-evaluation” pairings on an elliptic curve E over a finite field Fq, where the characteristic of Fq is neither 2 nor 3. It is shown that the normalized Miller functions for computing point-evaluation pairings on G2G1 when (i) the embedding degree k is even, or (ii) 3|k and E/Fq(q ≡ (1 mod 3)) is a curve of the form Y2=X3+b. Thus, there is no need to consider the normalization for computing pairings on many pairing-friendly elliptic curves.

One of the most challenging issues in wireless sensor networks is extension of the overall network lifetime. Data aggregation is one promising solution because it reduces the amount of network traffic by eliminating redundant data. In order to aggregate data, each sensor node must temporarily store received data, which requires a specific amount of memory. Most sensor nodes use static random access memory (SRAM) or flash memory for storage. SRAM can be implemented in a one-chip sensor node at low cost; however, SRAM requires standby energy, which consumes a lot of power, especially because the sensor node spends most of its time sleeping, i.e. its radio circuits are quiescent. This study proposes two types of divided SRAM: equal-size divided SRAM and equal-ratio divided SRAM. Simulations show that both proposed SRAM types offer reduced power consumption in various situations.

In this paper, we apply an improved method for the guiding problem of dielectric waveguide with arbitrary inhomogeneous media along the middle layer introduced the defect layers, and analyzed the propagation characteristics of dielectric waveguide composed of dielectric circular cylinders and the arbitrary inhomogeneous media in the middle layer by using a combination of the improved Fourier series expansion method and multilayer method. Numerical results are given for the propagation constants in the first stop band regions, and the distribution of energy flow for both TE0 and TM0 modes. The influence of permittivity and the shape variation of arbitrary inhomogeneous media are discussed in the first stop band regions.

This paper deals with reflection and transmission of a TE plane wave from a two-dimensional random slab with slanted fluctuation by means of the stochastic functional approach. Such slanted fluctuation of the random slab is written by a homogeneous random field having a power spectrum with a rotation angle. By starting with the previous paper [IEICE Trans. Electron., Vol. E92-C, no.1, pp.77–84, January 2009], any statistical quantities are immediately obtained even for slanted fluctuation cases. The first-order incoherent scattering cross section is numerically calculated and illustrated in figures. It is then newly found that shift and separation phenomena of the leading or enhanced peaks at four characteristic scattering angles take place in the transmission and reflection sides, respectively.

CLEFIA is a 128-bit block cipher proposed by Shirai et al. in 2007. On its saturation attack, Tsunoo et al. reported peculiar saturation characteristics in 2010. They formulated some hypotheses on the existence of the characteristics with no proof. In this paper we have theoretically proved their hypotheses. In their attack scenario, we show that the mod-2 distribution is a code word of Extended Hamming code, and then proof is given by using the property of Hadamard transform.

A new frequency estimator for a single real-valued sinusoid signal in white noise is proposed. The new estimator uses the Pisarenko Harmonic Decomposer (PHD) estimator to get a coarse frequency estimate and then makes use of multiple correlation lags to obtain an adjustment term. For the limited-length single sinusoid, its correlation has the same frequency as itself but with a non-zero phase. We propose to use Taylor series to expand the correlation at the PHD coarse estimated frequency with amplitude and phase of the correlation into consideration. Simulation results show that this new method improves the estimation performance of the PHD estimator. Moreover, when compared with other existing estimator, the mean square frequency error of the proposed method is closer to the Cramer-Rao Lower Bound (CRLB) for certain SNR range.

We propose a novel channel model of satellite-to-ground optical transmission to achieve a global-scale high-capacity communication network. In addition, we compose an effective channel coding scheme based on low-density generator matrix (LDGM) code suitable for that channel. Because the first successful optical satellite communication demonstrations are quite recent, no practical channel model has been introduced. We analyze the results of optical transmission experiments between ground station and the Optical Inter-orbit Communications Engineering Test Satellite (OICETS) performed by NICT and JAXA in 2008 and propose a new Markov-based practical channel model. Furthermore, using this model we design an effective long erasure code (LEC) based on LDGM to achieve high-quality wireless optical transmissions.

This paper presents the design and performance evaluation of a delay attack-resilient clock synchronization scheme (abbreviated to DARCS) for wireless sensor networks. In order to provide both synchronization accuracy and robustness, we propose a novel three-way handshake-based protocol, which completely excludes non-deterministic factors such as random backoff durations and unexpected hardware interrupts in a software manner and, in this way, the node can accurately estimate the relative clock offset and the end-to-end delay between a pair of nodes. Consequently, DARCS makes it possible to correct time synchronization errors as well as to detect delay attacks precisely. The simulation results show that DARCS achieves a higher synchronization accuracy and is more resilient to delay attacks than the other popular time synchronization schemes.

Since wireless sensor networks (WSNs) are resources-constrained, it is very essential to gather data efficiently from the WSNs so that their life can be prolonged. Data aggregation can conserve a significant amount of energy by minimizing transmission cost in terms of the number of data packets. Many applications require privacy and integrity protection of the sampled data while they travel from the source sensor nodes to a data collecting device, say a query server. However, the existing schemes suffer from high communication cost, high computation cost and data propagation delay. To resolve the problems, in this paper, we propose a new and efficient integrity protecting sensitive data aggregation scheme for WSNs. Our scheme makes use of the additive property of complex numbers to achieve sensitive data aggregation with protecting data integrity. With simulation results, we show that our scheme is much more efficient in terms of both communication and computation overheads, integrity checking and data propagation delay than the existing schemes for protecting integrity and privacy preserving data aggregation in WSNs.

Permutation polynomial based interleavers over integer rings have recently received attention for their excellent channel coding performance, elegant algebraic properties and simplicity of implementation. In this letter, it is shown that permutation polynomial based interleavers of practical interest is decomposed into linear permutation polynomials. Based on this observation, it is shown that permutation polynomial based interleavers as well as their inverses can be efficiently implemented.

This paper proposes a novel approach to traffic state estimation using mobile phones. In this work, a real-time traffic data collection policy based on the so-called “3R” philosophy, a unique vehicle classification method, and a reasonable traffic state quantification model are proposed. The “3R” philosophy, in which the Right data are collected by the Right mobile devices at the Right time, helps to improve not only the effectiveness but also the scalability of the traffic state estimation model. The vehicle classification method using the simple data collected by mobile phones makes the traffic state estimation more accurate. The traffic state quantification model integrates both the mean speed capacity and the density of a traffic flow to improve the comprehensibility of the traffic condition. The experimental results reveal the effectiveness as well as the robustness of the proposed solutions.

This paper proposes a high-accuracy sub-pixel registration framework based on phase correlation for noisy images. First we introduce a denoising module, where the edge-preserving filter is adopted. This strategy not only filters off the noise but also preserves most of the original image signal. A confidence-weighted optimization module is then proposed to fit the linear phase plane discriminately and to achieve sub-pixel shifts. Experiments demonstrate the effectiveness of the combination of our modules and improvements of the accuracy and robustness against noise compared to other sub-pixel phase correlation methods in the Fourier domain.

Petri net is a powerful modeling tool for concurrent systems. Subclasses of Petri net are suggested to model certain realistic applications with less computational cost. Structurally weakly persistent net (SWPN) is one of such subclasses where liveness is verified in deterministic polynomial time. This paper studies the computational complexity to verify whether a give net is SWPN. 3UNSAT problem is reduced to the problem to verify whether a net is not SWPN. This implies co-NP completeness of verification problem of SWPN.

Beyond deep sub-micron era, Power Gating (PG) is one of the most effective techniques to reduce leakage power of circuits. The most important issue of PG circuit design is how to decide the width of sleep transistor. Smaller total sleep transistor width provides smaller leakage power in standby mode, however, insufficient sleep transistor insertion suffers from significant performance degradation. In this paper, we present an accurate and fast gate-level delay estimation method for PG circuits and a novel sleep transistor sizing method utilizing our delay estimation for module-based PG circuits. This method achieves high accuracy within acceptable computation time utilizing accurate discharge current estimation based on delayed logic simulations with limited input vector patterns and by realizing precise current characteristics for logic gates and sleep transistors. Experimental results show that our delay estimation successfully achieves high accuracy and avoids overestimation and underestimation seen in conventional method. Also, our sleep transistor sizing method on average successfully reduces the width of sleep transistors by 40% when compared to conventional methods within an acceptable computation time.

The statistical static timing analysis has been studied intensively in the last decade so as to deal with the process variability, and various techniques to represent distributions of timing information, such as a gate delay, a signal arrival time, and a slack, have been proposed. Among them, the Gaussian mixture model is distinguished from the others in that it can handle various correlations, non-Gaussian distributions, and slew distributions easily. However, the previous algorithm of computing the statistical maximum for Gaussian mixture models, which is one of key operations in the statistical static timing analysis, has a defect such that it produces a distribution similar to Gaussian in a certain case, although the correct distribution is far from Gaussian. In this paper, we propose a new algorithm for statistical maximum (minimum) operation for Gaussian mixture models. It takes the cumulative distribution function curve into consideration so as to compute accurate criticalities (probabilities of timing violation), which is important for detecting delay faults and circuit optimization with the use of statistical approaches. We also show some experimental results to evaluate the performance of the proposed method.

Device-parameter estimation sensors inside a chip are gaining its importance as the post-fabrication tuning is becoming of a practical use. In estimation of variational parameters using on-chip sensors, it is often assumed that the outputs of variation sensors are not affected by random variations. However, random variations can deteriorate the accuracy of the estimation result. In this paper, we propose a device-parameter estimation method with on-chip variation sensors explicitly considering random variability. The proposed method derives the global variation parameters and the standard deviation of the random variability using the maximum likelihood estimation. We experimentally verified that the proposed method improves the accuracy of device-parameter estimation by 11.1 to 73.4% compared to the conventional method that neglects random variations.