We propose a digital image watermarking method satisfying information hiding criteria (IHC) for robustness against JPEG compression, cropping, scaling, and rotation. When a stego-image is cropped, the marking positions of watermarks are unclear. To detect the position in a cropped stego-image, a marker or synchronization code is embedded with the watermarks in a lattice pattern. Attacks by JPEG compression, scaling, and rotation cause errors in extracted watermarks. Against such errors, the same watermarks are repeatedly embedded in several areas. The number of errors in the extracted watermarks can be reduced by using a weighted majority voting (WMV) algorithm. To correct residual errors in output of the WMV algorithm, we use a high-performance error-correcting code: a low-density parity-check (LDPC) code constructed by progressive edge-growth (PEG). In computer simulations using the IHC ver. 4 the proposed method could a bit error rate of 0, the average PSNR was 41.136 dB, and the computational time for synchronization recovery was less than 10 seconds. The proposed method can thus provide high image quality and fast synchronization recovery.

An efficient balanced truncation for RC and RLC networks is presented in this paper. To accelerate the balanced truncation, sparse structures of original networks are considered. As a result, Lyapunov equations, the solutions of which are necessary for making the transformation matrices, are efficiently solved, and the reduced order models are efficiently obtained. It is proven that reciprocity of original networks is preserved while applying the proposed method. Passivity of the reduced RC networks is also guaranteed. In the illustrative examples, we will show that the proposed method is compatible with PRIMA in efficiency and is more accurate than PRIMA.

We introduce two cheater identifiable secret sharing (CISS) schemes with efficient reconstruction, tolerating t

Speaker verification is the task of determining whether two utterances represent the same person. After representing the utterances in the i-vector space, the crucial problem is only how to compute the similarity of two i-vectors. Metric learning has provided a viable solution to this problem. Until now, many metric learning algorithms have been proposed, but they are usually limited to learning a linear transformation. In this paper, we propose a nonlinear metric learning method, which learns an explicit mapping from the original space to an optimal subspace using deep Restricted Boltzmann Machine network. The proposed method is evaluated on the NIST SRE 2008 dataset. Since the proposed method has a deep learning architecture, the evaluation results show superior performance than some state-of-the-art methods.

We propose an appearance-based proficiency evaluation methodology based on fine-motion analysis. We consider the effects of individual habit in evaluating proficiency and analyze the fine motion of guitar-picking. We first extract multiple features on a large number of dense trajectories of fine motion. To facilitate analysis, we then generate a histogram of motion features using a bag-of-words model and change the number of visual words as appropriate. To remove the effects of individual habit, we extract the common principal histogram elements corresponding to experts or beginners according to discrimination's contribution rates using random forests. We finally calculate the similarity of the histograms to evaluate the proficiency of a guitar-picking motion. By optimizing the number of visual words for proficiency evaluation, we demonstrate that our method distinguishes experts from beginners with an accuracy of about 86%. Moreover, we verify experimentally that our proposed methodology can evaluate proficiency while removing the effects of individual habit.

We previously proposed an unsupervised model using the inclusion-exclusion principle to compute sentence information content. Though it can achieve desirable experimental results in sentence semantic similarity, the computational complexity is more than O(2n). In this paper, we propose an efficient method to calculate sentence information content, which employs the thinking of the difference set in hierarchical network. Impressively, experimental results show that the computational complexity decreases to O(n). We prove the algorithm in the form of theorems. Performance analysis and experiments are also provided.

We propose a new direction-of-arrival (DOA) estimation method of wideband signals. In several decades, many approaches to estimate DOA of wideband signal sources have been proposed. Test of orthogonality of projected subspaces (TOPS) and Squared TOPS are the estimation algorithms to realize high resolution performance of closely spaced signal sources. These methods, however, are not suitable for DOA estimation of multiple signal sources, because the spatial spectrum calculated by Squared TOPS has some false peaks. Therefore, the authors have proposed the weighted squared TOPS (WS-TOPS) to suppress these false peaks by modifying the orthogonality evaluation matrix, WS-TOPS also achieves better DOA estimation accuracy than that of Squared TOPS. On the other hand, WS-TOPS has a drawback, it requires high computational complexity. Our new method can realize good DOA estimation performance, which is better than that of Squared TOPS, with low computational complexity by reducing the size of orthogonality evaluation matrix and the number of subspaces to be used. Simulation results show that the new method can provide high resolution performance and high DOA estimation accuracy with low computational complexity.

Many hemodialysis patients undergo plasitc surgery to form the arterio-venous fistula (AVF) in their forearm to improve the vascular access by shunting blood flows. The issue of AVF is the stenosis caused by the disturbance of blood flows; therefore the auscultation system to assist the stenosis diagnosis has been developed. Although the system is intended to be used as a steady monitoring for stenosis assessment, its efficiency was not always high because it cannot estimate where the stenosis locates. In this study, for extracting and estimating the stenosis signal, the shunt murmurs captured by many microphones were decomposed by the principal component analysis (PCA). Furthermore, applying the hierarchical categorization of the recursive subdivision self-organizing map (rs-SOM), the modelling of the stenosis signal was proposed to realise the effective stenosis assessment. The false-positive rate of the stenosis assessment was significantly reduced by using the improved auscultation system.

Orthogonal arrays and orthogonal partitions have great significance in communications and coding theory. In this letter, by using a generalized orthogonal partition, Latin squares and orthogonal Latin squares, we present an iterative construction method of orthogonal arrays of strength t and orthogonal partitions. As an application of the method, more orthogonal arrays of strength t and orthogonal partitions than the existing methods can be constructed.

Non-orthogonal multiple access (NOMA) enables multiple mobile devices to share the same frequency band. In a conventional NOMA scheme, the receiver of a far user detects its desired signal without canceling the signal for a near user. However, the signal for the near user acts as interference and degrades the accuracy of likelihood values for the far user. In this paper, a joint maximum likelihood detection scheme for the far user of the NOMA downlink is proposed. The proposed scheme takes the interference signal into account in calculating the likelihood values. Numerical results obtained through computer simulation show that the proposed scheme improves the performance by from 0.2dB to 3.1dB for power allocation coefficients of 0.2 to 0.4 at a bit error rate (BER) of 10-2 relative to the conventional scheme.

In many multimedia applications, image encryption has to be conducted prior to image compression. This letter proposes an Encryption-then-Compression system using JPEG XR/JPEG-LS friendly perceptual encryption method, which enables to be conducted prior to the JPEG XR/JPEG-LS standard used as an international standard lossless compression method. The proposed encryption scheme can provides approximately the same compression performance as that of the lossless compression without any encryption. It is also shown that the proposed system consists of four block-based encryption steps, and provides a reasonably high level of security. Existing conventional encryption methods have not been designed for international lossless compression standards, but for the first time this letter focuses on applying the standards.

One of major ideas to design a multivariate public key cryptosystem (MPKC) is to generate its quadratic forms by a polynomial map over an extension field. In fact, Matsumoto-Imai's scheme (1988), HFE (Patarin, 1996), MFE (Wang et al., 2006) and multi-HFE (Chen et al., 2008) are constructed in this way and Sflash (Akkar et al., 2003), Quartz (Patarin et al., 2001), Gui (Petzoldt et al, 2015) are variants of these schemes. An advantage of such extension field type MPKCs is to reduce the numbers of variables and equations to be solved in the decryption process. In the present paper, we study the security of MPKCs whose quadratic forms are derived from a “quadratic” map over an extension field and propose a new attack on such MPKCs. Our attack recovers partial information of the secret affine maps in polynomial time when the field is of odd characteristic. Once such partial information is recovered, the attacker can find the plain-text for a given cipher-text by solving a system of quadratic equations over the extension field whose numbers of variables and equations are same to those of the system of quadratic equations used in the decryption process.

The integer least-squares (ILS) problem frequently arises in wireless communication systems. Sphere decoding (SD) is a systematic search scheme for solving ILS problem. The enumeration of candidates is a key part of SD for selecting a lattice point, which will be searched by the algorithm. Herein, the authors present a computationally efficient Schnorr-Euchner enumeration (SEE) algorithm to solve the constrained ILS problems, where the solution is limited into the finite integer lattice. To trace only valid lattice points within the underlying finite lattice, the authors devise an adaptive computation of the enumeration step and counting the valid points enumerated. In contrast to previous SEE methods based on a zig-zag manner, the proposed method completely avoids enumerating invalid points outside the finite lattice, and it further reduces real arithmetic and logical operations.

Card-based protocols enable us to easily perform cryptographic tasks such as secure multiparty computation using a deck of physical cards. Since the first card-based protocol appeared in 1989, many protocols have been designed. A protocol is usually described with a series of somewhat intuitive and verbal descriptions, such as “turn over this card,” “shuffle these two cards,” “apply a random cut to these five cards,” and so on. On the other hand, a formal computational model of card-based protocols via abstract machine was constructed in 2014. By virtue of the formalization, card-based protocols can be treated more rigorously; for example, it enables one to discuss the lower bounds on the number of cards required for secure computations. In this paper, an overview of the computational model with its applications to designing protocols and a survey of the recent progress in card-based protocols are presented.

We propose a home base-aware store-carry-forward routing scheme using location-dependent utilities of nodes, which adopts different message forwarding strategies depending on location where nodes encounter. Our routing scheme first attempts to deliver messages to its home base, the area with the highest potential for the presence of the destination node in the near future. Once a message copy reaches its home base, message dissemination is limited within the home base, and nodes with message copies wait for encountering the destination node. To realize our routing scheme, we use two different utilities of nodes depending on location: Outside the home base of a message, nodes approaching to the home base have high utility values, while within the home base, nodes staying the home base have high utility values. By using these utilities properly, nodes with message copies will catch the destination node “by ambush” in the home base of the destination node. Through simulation experiments, we demonstrate the effectiveness of our routing scheme.

Single-instruction multiple-data (SIMD) extension provides an energy-efficient platform to scale the performance of media and scientific applications while still retaining post-programmability. However, the major challenge is to translate the parallel resources of the SIMD hardware into real application performance. Currently, all the slots in the vector register are used when compilers exploit SIMD parallelism of programs, which can be called sufficient vectorization. Sufficient vectorization means all the data in the vector register is valid. Because all the slots which vector register provides must be used, the chances of vectorizing programs with low SIMD parallelism are abandoned by sufficient vectorization method. In addition, the speedup obtained by full use of vector register sometimes is not as great as that obtained by partial use. Specifically, the length of vector register provided by SIMD extension becomes longer, sufficient vectorization method cannot exploit the SIMD parallelism of programs completely. Therefore, insufficient vectorization method is proposed, which refer to partial use of vector register. First, the adaptation scene of insufficient vectorization is analyzed. Second, the methods of computing inter-iteration and intra-iteration SIMD parallelism for loops are put forward. Furthermore, according to the relationship between the parallelism and vector factor a method is established to make the choice of vectorization method, in order to vectorize programs as well as possible. Finally, code generation strategy for insufficient vectorization is presented. Benchmark test results show that insufficient vectorization method vectorized more programs than sufficient vectorization method by 107.5% and the performance achieved by insufficient vectorization method is 12.1% higher than that achieved by sufficient vectorization method.

The overdrive technique is widely used to eliminate motion blur in liquid-crystal displays (LCDs). However, this technique requires a large frame memory to store the previous frame. A reduction in the frame memory requires an image compression algorithm suitable for real-time data processing. In this paper, we present an algorithm based on multimode-color-conversion block truncation coding (MCC-BTC) to obtain a constant output bit rate and high overdrive performance. The MCC-BTC algorithm uses four compression methods, one of which is selected. The four compression modes either use the single-bitmap-generation method or the subsampling method for chrominance. As shown in the simulation results, the proposed algorithm improves the performance of both coding (up to 2.73dB) and overdrive (up to 2.61dB), and the visual quality is improved in comparison to other competing algorithms in literature.

A Reed-Solomon (RS) decoder is designed based on the pipelined recursive Euclidean algorithm in the key equation solution. While the Euclidean algorithm uses less Galois multipliers than the modified Euclidean (ME) and reformulated inversionless Berlekamp-Massey (RiBM) algorithms, division between two elements in Galois field is required. By implementing the division with a multi-cycle Galois inverter and a serial Galois multiplier, the proposed key equation solver architecture achieves lower complexity than the conventional ME and RiBM based architectures. The proposed RS (255,239) decoder reduces the hardware complexity by 25.9% with 6.5% increase in decoding latency.

In this letter, we show the new signal power estimation method base on the subspace projection. This work mainly contributes to the SINR estimation problem because, in this research, the signal power estimation is implicitly or explicitly performed. The difference between our method and the conventional method related to this topic is the exploitation of the subspace character of the signals constructing the observed signal. As tools to perform subspace operation, we apply orthogonal projection and oblique projection which can extracts desired parameters. In the proposed scheme, the statistics of the projected observed signal by these projection are used to estimate the parameters.

Non-volatile memories are paid attention to as a promising alternative to memory design. Data stored in them still may be destructed due to crosstalk and radiation. We can restore the data by using error-correcting codes which require extra bits to correct bit errors. Further, non-volatile memories consume ten to hundred times more energy than normal memories in bit-writing. When we configure them using error-correcting codes, it is quite necessary to reduce writing bits. In this paper, we propose a method to generate a bit-write-reducing code with error-correcting ability. We first pick up an error-correcting code which can correct t-bit errors. We cluster its codeswords and generate a cluster graph satisfying the S-bit flip conditions. We assign a data to be written to each cluster. In other words, we generate one-to-many mapping from each data to the codewords in the cluster. We prove that, if the cluster graph is a complete graph, every data in a memory cell can be re-written into another data by flipping at most S bits keeping error-correcting ability to t bits. We further propose an efficient method to cluster error-correcting codewords. Experimental results show that the bit-write-reducing and error-correcting codes generated by our proposed method efficiently reduce energy consumption. This paper proposes the world-first theoretically near-optimal bit-write-reducing code with error-correcting ability based on the efficient coding theories.