This paper analyzes the correlation between various acoustic features and perceptual voice quality similarity, and proposes a perceptually similar speaker selection technique based on distance metric learning. To analyze the relationship between acoustic features and voice quality similarity, we first conduct a large-scale subjective experiment using the voices of 62 female speakers and perceptual voice quality similarity scores between all pairs of speakers are acquired. Next, multiple linear regression analysis is carried out; it shows that four acoustic features are highly correlated to voice quality similarity. The proposed speaker selection technique first trains a transform matrix based on distance metric learning using the perceptual voice quality similarity acquired in the subjective experiment. Given an input speech, acoustic features of the input speech are transformed using the trained transform matrix, after which speaker selection is performed based on the Euclidean distance on the transformed acoustic feature space. We perform speaker selection experiments and evaluate the performance of the proposed technique by comparing it to speaker selection without feature space transformation. The results indicate that transformation based on distance metric learning reduces the error rate by 53.9%.

This letter deals with the signal declipping algorithm based on the matrix rank minimization approach, which can be applied to the signal restoration in linear systems. We focus on the null space of a low-rank matrix and provide a block adaptive algorithm of the matrix rank minimization approach to signal declipping based on the null space alternating optimization (NSAO) algorithm. Numerical examples show that the proposed algorithm is faster and has better performance than other algorithms.

The concept of dual pairing vector spaces (DPVS) was introduced by Okamoto and Takashima in 2009, and it has been employed in various applications, functional encryption (FE) including attribute-based encryption (ABE) and inner-product encryption (IPE) as well as attribute-based signatures (ABS), generic conversion from composite-order group based schemes to prime-order group based ones and public-key watermarking. In this paper, we show the concept of DPVS, the major applications to FE and the key techniques employed in these applications. This paper presents them with placing more emphasis on plain and intuitive descriptions than formal preciseness.

In this letter, we consider the localization problem using received signal strength in wireless sensor networks. Working with a simple non-cooperative scenario in an outdoor localization, we transform the received signal strength measurement model to an alternative optimization problem which is much easier to solve and less complex compared to finding the optimum solutions from the maximum likelihood estimator. Then, we can solve a sequence of nonconvex problems as a range constrainted optimization problem, while the estimated solution also guarantees a monotonic convergence to the original solution. Simulation results confirm the effectiveness of our proposed approach.

Primitive linear recurring sequences over rings are important in modern communication technology, and character sums of such sequences are used to analyze their statistical properties. We obtain a new upper bound for the character sum of primitive sequences of order n over the residue ring modulo a square-free odd integer m, and thereby improve previously known bound mn/2.

For digital forensic investigations, the proposed scheme verifies the integrity of video contents in legacy surveillance camera systems with no built-in integrity protection. The scheme exploits video frames remaining in slack space of storage media, instead of timestamp information vulnerable to tampering. The scheme is applied to integrity verification of video contents formatted with AVI or MP4 files in automobile blackboxes.

Speeded up robust features (SURF) can detect/describe scale- and rotation-invariant features at high speed by relying on integral images for image convolutions. However, the time taken for matching SURF descriptors is still long, and this has been an obstacle for use in real-time applications. In addition, the matching time further increases in proportion to the number of features and the dimensionality of the descriptor. Therefore, we propose a fast matching method that rearranges the elements of SURF descriptors based on their entropies, divides SURF descriptors into sub-descriptors, and sequentially and analytically matches them to each other. Our results show that the matching time could be reduced by about 75% at the expense of a small drop in accuracy.

Our society has been getting more privacy-sensitive. Diverse information is given by users to information and communications technology (ICT) systems such as IC cards benefiting them. The information is stored as so-called big data, and there is concern over privacy violation. Visual information such as images and videos is also considered privacy-sensitive. The growing deployment of surveillance cameras and social network services has caused a privacy problem of information given from various sensors. To protect privacy of subjects presented in visual information, their face or figure is processed by means of pixelization or blurring. As image analysis technologies have made considerable progress, many attempts to automatically process flexible privacy protection have been made since 2000, and utilization of privacy information under some restrictions has been taken into account in recent years. This paper addresses the recent progress of privacy protection for visual information, showing our research projects: PriSurv, Digital Diorama (DD), and Mobile Privacy Protection (MPP). Furthermore, we discuss Harmonized Information Field (HIFI) for appropriate utilization of protected privacy information in a specific area.

A design strategy (the required ECC strength and the judgment method of the dominant error mode) of error-prediction low-density parity-check (EP-LDPC) error-correcting code (ECC) and error-recovery schemes for scaled NAND flash memories is discussed in this paper. The reliability characteristics of NAND flash memories are investigated with 1X, 2X and 3Xnm NAND flash memories. Moreover, the system-level reliability of SSDs is analyzed from the acceptable data-retention time of the SSD. The reliability of the NAND flash memory is continuously degrading as the design rule shrinks due to various problems. As a result, future SSDs will not be able to maintain system-level reliability unless advanced ECCs with signal processing are adopted. Therefore, EP-LDPC and error-recovery (ER) schemes are previously proposed to improve the reliability. The reliability characteristics such as the bit-error rate (BER) versus the data-retention time and the effect of the cell-to-cell interference on the BER are measured. These reliability characteristics obtained in this paper are stored in an SSD as a reliability table, which plays a principal role in EP-LDPC scheme. The effectiveness of the EP-LDPC scheme with the scaling of the NAND flash memory is also discussed by analyzing the cell-to-cell interference. An interference factor $alpha$ is proposed to discuss the impact of the cell-to-cell coupling. As a result, the EP-LDPC scheme is assumed to be effective down to 1Xnm NAND flash memory. On the other hand, the ER scheme applies different voltage pulses to memory cells, according to the dominant error mode: program-disturb or data-retention error dominant mode. This paper examines when the error mode changes, corresponding to which pulse should be applied. Additionally, the estimation methods of the dominant error mode by ER scheme are also discussed. Finally, as a result of the system-level reliability analysis, it is concluded that the use of the EP-LDPC scheme can maintain the reliability of the NAND flash memory in 1Xnm technology node.

An optimal design method of linear processors intended for a multi-input multi-output (MIMO) full-duplex (FD) amplify-and-forward (AF) relay network is presented under the condition of spatial-domain self-interference nulling. This method is designed to suit the availability of channel state information (CSI). If full CSI of source station (SS)-relay station (RS), RS-RS (self-interference channel), and RS-destination station (DS) links are available, the instantaneous end-to-end capacity is maximized. Otherwise, if CSI of the RS-DS link is either partially available (only covariance is known), or not available, while CSI of the other links is known, then the ergodic end-to-end capacity is maximized. Performance of the proposed FD-AF relay system is demonstrated through computer simulations, especially under various correlation conditions of the RS-DS link.

For estimating user's location, Global Navigation Satellite System (GNSS) is very useful. Especially, Global Positioning System (GPS) by USA is very popular. A GPS receiver needs multiple satellites (usually 4 and more satellites). Propagation to the satellites needs line-of-sight. However, in urban area, there are many buildings. Received signals tend to become bad quality. Such signals are often called as non-line-of-sight (NLOS) or multipath signals. The problem is that the receiver cannot get line-of-sight signals from adequate number of the satellites coinstantaneously. This case leads to degradation of estimation quality or impossibility of estimation. In this paper, we will introduce a novel estimation algorithm, which can estimate own position with as low number of satellites as possible. The proposal achieves the estimation by only two satellites. The proposal also uses a traveling distance sensor which is often equipped on vehicles. By recorded satellite data, we will confirm our effectiveness.

Given an edge-weighted tree with n vertices and a positive integer L, the length-constrained maximum-density path problem is to find a path of length at least L with maximum density in the tree. The density of a path is the sum of the weights of the edges in the path divided by the number of edges in the path. We present an O(n) time algorithm for the problem. The previously known algorithms run in O(nL) or O(n log n) time.

Pedestrian dead reckoning (PDR) is an effective positioning means that can be used in urban-canyon environments where the accuracy of GPS is significantly degraded. Magnetic disturbances caused by artificial objects affect the accuracy of positioning if the PDR system uses a magnetometer to estimate the heading direction. Conventional PDR systems consider magnetic disturbances as unpredictable error sources, but the error becomes predictable and removable if the amount of the deviation in the magnetic field can be calculated at any position. In this study, we propose a method to correct the heading direction by referring to a map of magnetic deviation. The experimental results show that our method reduced the error in the heading direction caused by magnetic disturbances. Our approach removed the error components that differ depending on the position, and consequently, the resultant trajectory represented better the shape of the true trajectory.

Resonant scattering of flexural waves in acoustic waveguide is analysed by using the recursive transfer method (RTM). Because flexural waves are governed by a fourth-order differential equation, a localized wave tends to be induced around the scattering region and dampening wave tails from the localized wave may reach the ends of a simulation domain. A notable feature of RTM is its ability to extract the localized wave even if the dampening tail reaches the end of the simulation domain. Using RTM, the enhanced reflection caused by a localized wave is predicted and the shape of the localized wave is explored at its resonance with the incident wave.

This paper presents an efficient method for differential fault analysis (DFA) on substitution-permutation network (SPN)-based block ciphers. A combination of a permutation cancellation and an algebraic key filtering technique makes it possible to reduce the computational cost of key filtering significantly and therefore perform DFAs with new fault models injected at an earlier round, which defeats conventional countermeasures duplicating or recalculating the rounds of interest. In this paper, we apply the proposed DFA to the LED block cipher. Whereas existing DFAs employ fault models injected at the 30th round, the proposed DFA first employs a fault model injected at the 29th round. We demonstrate that the proposed DFA can obtain the key candidates with only one pair of correct and faulty ciphertexts in about 2.1h even from the 29th round fault model and the resulting key space is reduced to 24.04

This letter studies the problem of cooperative spectrum sensing in wideband cognitive radio networks. Based on the basis expansion model (BEM), the problem of estimation of power spectral density (PSD) is transformed to estimation of BEM coefficients. The sparsity both in frequency domain and space domain is used to construct a sparse estimation structure. The theory of L1/2 regularization is used to solve the compressed sensing problem. Simulation results demonstrate the effectiveness of the proposed method.

A new technology for video frame rate up-conversion (FRUC) is presented by combining a median filter and motion estimation (ME) with an occlusion detection (OD) method. First, ME is performed to obtain a motion vector. Then, the OD method is used to refine the MV in the occlusion region. When occlusion occurs, median filtering is applied. Otherwise, bidirectional motion compensated interpolation (BDMC) is applied to create the interpolated frames. The experimental results show that the proposed algorithm provides better performance than the conventional approach. The average gain in the PSNR (Peak Signal to Noise Ratio) is always better than the other methods in the Full HD test sequences.

Password-protected secret sharing (PPSS, for short) schemes were proposed by Bagherzandi, Jarecki, Saxena and Lu. In this paper, we consider another attack for PPSS schemes which is based on public parameters and documents. We show that the protocol proposed by Bagherzandi et al. is broken with the attack. We then propose an enhanced protocol which is secure against the attack.

A multi-port device is characterized using measurement results of a two-port Vector Network Analyzer (VNA) with four different structures. The loads used as terminations are open-, or short-circuited transmission lines (TLs), which are characterized along with Ground-Signal-Ground pads based on L-2L de-embedding method. A new characterization method for a four-port device is introduced along with its theory. The method is validated using simulation and measurement results. The characterized four-port device is a Crossing Transmission Line (CTL), mainly used for over-pass or under-pass of RF signals. Four measurement results are used to characterize the CTL. The S-parameter response of the CTL is found. To compare the results, reconstructed responses compared with the measurements. Results show good agreement between the measured and modeled results from 1 GHz to 110 GHz.

We proposed and evaluated a speech intelligibility estimation method that does not require a clean speech reference signal. The propose method uses the features defined in the ITU-T standard P.563, which estimates the overall quality of speech without the reference signal. We selected two sets of features from the P.563 features; the basic 9-feature set, which includes basic features that characterize both speech and background noise, e.g., cepstrum skewness and LPC kurtosis, and the extended 31-feature set with 22 additional features for a more accurate description of the degraded speech and noise, e.g., SNR, average pitch, and spectral clarity among others. Four hundred noise samples were added to speech, and about 70% of these samples were used to train a support vector regression (SVR) model. The trained models were used to estimate the intelligibility of speech degraded by added noise. The proposed method showed a root mean square error (RMSE) value of about 10% and correlation with subjective intelligibility of about 0.93 for speech distorted with known noise type, and RMSE of about 16% and a correlation of about 0.84 for speech distorted with unknown noise type, both with either the 9 or the 31-dimension feature set. These results were higher than the estimation using frequency-weighed SNR calculated in critical frequency bands, which requires the clean reference signal for its calculation. We believe this level of accuracy proves the proposed method to be applicable to real-time speech quality monitoring in the field.