This paper presents a novel test data compression scheme for SoCs based on block merging and compatibility. The technique exploits the properties of compatibility and inverse compatibility between consecutive blocks, consecutive merged blocks, and two halves of the encoding merged block itself to encode the pre-computed test data. The decompression circuit is simple to be implemented and has advantage of test-independent. In addition, the proposed scheme is applicable for IP cores in SoCs since it compresses the test data without requiring any structural information of the circuit under test. Experimental results demonstrate that the proposed technique can achieve an average compression ratio up to 68.02% with significant low test application time.

Gaussian mixture model (GMM) has recently been applied for image registration given its robustness and efficiency. However, in previous GMM methods, all the feature points are treated identically. By incorporating local class features, this letter proposes a multiple Gaussian mixture models (M-GMM) method for image registration. The proposed method can achieve higher accuracy results with less registration time. Experiments on real image pairs further proved the superiority of the proposed method.

Fault tolerant methods using dynamically reconfigurable devices have been studied to overcome wear-out failures. However, quantitative comparisons have not been sufficiently assessed on device lifetime enhancement with these methods, whereas they have mainly been evaluated individually from various viewpoints such as additional hardware overheads, performance, and downtime for fault recovery. This paper presents quantitative lifetime evaluations performed by simulating the fault-avoidance procedures of five representative methods under the same conditions in wear-out scenarios, applications, and device architecture. The simulation results indicated that improvements of up to 70% mean-time-to-failure (MTTF) in comparison with ideal fault avoidance could be achieved by using methods of fault avoidance with ‘row direction shift’ and ‘dynamic partial reconfiguration’. ‘Column shift’, on the other hand, attained a high degree of stability with moderate improvements in MTTF. The experimental results also revealed that spare basic elements (BEs) should be prevented from aging so that improvements in MTTF would not be adversely affected. Moreover, we found that the selection of initial mappings guided by wire utilization could increase the lifetimes of partial reconfiguration based fault avoidance.

For next generation planar lightwave circuit (PLC) devices, high function and high-density integration are required as well as downsizing and cost reduction. To realize these needs, high refractive index difference between a core and a clad $(Delta)$ is required. To use PLC for practical applications, silica-based PLC is one of the most attractive candidate. However, degradation of the optical properties and productivity occur when $Delta$ of the core becomes high. Thus, $Delta$ of most of the conventional PLC with GeO$_2$-SiO$_2$ core is designed less than 2.5%. In this paper, we report a silica-based ultra-high $Delta $ PLC with ZrO$_2$-SiO$_2$ core. 5.5%-$Delta$ ZrO$_2$-SiO$_2$ PLC has been realized with low propagation loss and basic characteristics has been confirmed. Potential of chip size reduction of the ZrO$_2$-SiO$_2$ PLC is shown.

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.

In this paper, a novel hybrid technique for analyzing complex antennas around the coated object is proposed, which is termed as “iterative vector fields with Physical Optics (PO)”. A closed box is used to enclose the antennas and the complex field vectors on the box' surfaces can then be obtained using Huygens principle. The equivalent electromagnetic currents on Huygens surfaces are computed by Higher-order Method of Moments (HOB-MoM) and the fields scattered from the coated object are calculated by PO method. In addition, the parallel technique based on Message Passing Interface (MPI) and Scalable Linear Algebra Package (ScaLAPACK) is employed so as to accelerate the computation. Numerical examples are presented to validate and to show the effectiveness of the proposed method on solving the practical engineering problem.

Nonlinearity compensation algorithm and soft-decision forward error correction (FEC) are considered as key technologies for future high-capacity and long-haul optical transmission system. In this report, we experimentally demonstrate the following three benefits brought by low complexity perturbation back-propagation nonlinear compensation algorithm in 224Gb/s DP-16QAM transmission over large-Aeff pure silica core fiber; (1) improvement of pre-FEC bit error ratio, (2) reshaping noise distribution to more Gaussian, and (3) reduction of cycle slip probability.

This paper presents a fundamental locally one-dimensional (FLOD) method for 3-D thermal simulation. We first propose a locally one-dimensional (LOD) method for heat transfer equation within general inhomogeneous media. The proposed LOD method is then cast into compact form and formulated into the FLOD method with operator-free right-hand-side (RHS), which leads to computationally efficient update equations. Memory storage requirements and boundary conditions for both FLOD and LOD methods are detailed and compared. Stability analysis by means of analyzing the eigenvalues of amplification matrix substantiates the stability of the FLOD method. Additionally, the potential instability of the Douglas Gunn (DG) alternating-direction-implicit (ADI) method for inhomogeneous media is demonstrated. Numerical experiments justify the gain achieved in the overall efficiency for FLOD over LOD, DG-ADI and explicit methods. Furthermore, the relative maximum error of the FLOD method illustrates good trade-off between accuracy and efficiency.

The research reported in this paper is an attempt to elucidate the predictors of pause duration in read-aloud discourse. Through simple linear regression analysis and stepwise multiple linear regression, we examined how different factors (namely, syntactic structure, discourse hierarchy, topic structure, preboundary length, and postboundary length) influenced pause duration both separately and jointly. Results from simple regression analysis showed that discourse hierarchy, syntactic structure, topic structure, and postboundary length had significant impacts on boundary pause duration. However, when these factors were tested in a stepwise regression analysis, only discourse hierarchy, syntactic structure, and postboundary length were found to have significant impacts on boundary pause duration. The regression model that best predicted boundary pause duration in discourse context was the one that first included syntactic structure, and then included discourse hierarchy and postboundary length. This model could account for about 80% of the variance of pause duration. Tests of mediation models showed that the effects of topic structure and discourse hierarchy were significantly mediated by syntactic structure, which was most closely correlated with pause duration. These results support an integrated model combining the influence of several factors and can be applied to text-to-speech systems.

This paper studies the design of cooperative beamforming (CB) and cooperative jamming (CJ) for the physical layer security of an amplify-and-forward (AF) relay network in the presence of multiple multi-antenna eavesdroppers. The secrecy rate maximization (SRM) problem of such a network is to maximize the difference of two concave functions, a problem which is non-convex and has no efficient solution. Based on the inner convex approximation (ICA) and semidefinite relaxation (SDR) techniques, we propose two novel low-complexity schemes to design CB and CJ for SRM in the AF network. In the first strategy, relay nodes adopt the CB only to secure transmission. Based on ICA, this design guarantees convergence to a Karush-Kuhn-Tucker (KKT) solution of the SDR of the original problem. In the second strategy, the optimal joint CB and CJ design is studied and the proposed joint design can guarantee convergence to a KKT solution of the original problem. Moreover, in the second strategy, we prove that SDR always has a rank-1 solution for the SRM problem. Simulation results show the superiority of the proposed schemes.

Honeycomb structures are widely used in aerospace industry because of the lightweight and durable properties they provide. Here we propose to use a honeycomb core as the wave guiding structure in Radial Line Slot Antennas (RLSAs). This paper quantifies the propagation characteristics, especially the loss due to the honeycomb. At 32GHz, by choosing the proper cell size, both good isotropy and reasonably low effective dielectric constants are realized with the honeycomb as a spacer in a radial line waveguide. To estimate the material loss factor, several methods are compared and a factor of about 0.014∼0.018dB/mm is predicted and measured. A fabricated 90cm diameter honeycomb RLSA suffers about a 3.5∼5dB loss, which coincides with the estimates using the predicted loss factor.

Four calculation techniques for the Q-factor determination of resonant structures are compared on the basis of the influence of the VNA measurement uncertainty. The influence is evaluated using Monte Carlo calculations. On the basis of the deviation, the dispersion, and the effect of nearby resonances, the circle fitting method is the most appropriate technique. Although the 3dB method is the most popular technique, the Q-factors calculated by this method exhibit deviations, and the sign and amount of the deviation depend on the measurement setup. Comparisons using measurement data demonstrate that the uncertainty of the dielectric loss tangent calculated by the circle fitting method is less than a third of those calculated by the other three techniques.

A ladder lottery, known as the “Amidakuji” in Japan, is a network with n vertical lines and many horizontal lines each of which connects two consecutive vertical lines. Each ladder lottery corresponds to a permutation. Ladder lotteries are frequently used as natural models in many areas. Given a permutation π, an algorithm to enumerate all ladder lotteries of π with the minimum number of horizontal lines is known. In this paper, given a permutation π and an integer k, we design an algorithm to enumerate all ladder lotteries of π with exactly k horizontal lines.

There have been steady demands for a speech segmentation method to handle various speech applications. Conventional segmentation algorithms show reliable performance but they require a sufficient training database. This letter proposes a manner class segmentation method based on the acoustic event and landmark detection used in the knowledge-based speech recognition system. Measurements of sub-band abruptness and additional parameters are used to detect the acoustic events. Candidates of manner classes are segmented from the acoustic events and determined based on the knowledge of acoustic phonetics and acoustic parameters. Manners of vowel/glide, nasal, fricative, stop burst, stop closure, and silence are segmented in this system. In total, 71% of manner classes are correctly segmented with 20-ms error boundaries.

Recent studies have focused on developing security systems using micro-Doppler radars to detect human bodies. However, the resolution of these conventional methods is unsuitable for identifying bodies and moreover, most of these conventional methods were designed for a solitary or sufficiently well-spaced targets. This paper proposes a solution to these problems with an image separation method for two closely spaced pedestrian targets. The proposed method first develops an image of the targets using ultra-wide-band (UWB) Doppler imaging radar. Next, the targets in the image are separated using a supervised learning-based separation method trained on a data set extracted using a range profile. We experimentally evaluated the performance of the image separation using some representative supervised separation methods and selected the most appropriate method. Finally, we reject false points caused by target interference based on the separation result. The experiment, assuming two pedestrians with a body separation of 0.44m, shows that our method accurately separates their images using a UWB Doppler radar with a nominal down-range resolution of 0.3m. We describe applications using various target positions, establish the performance, and derive optimal settings for our method.

We consider the problem of optimizing the quantizer design for distributed estimation systems where all nodes located at different sites collect measurements and transmit quantized data to a fusion node, which then produces an estimate of the parameter of interest. For this problem, the goal is to minimize the amount of information that the nodes have to transmit in order to attain a certain application accuracy. We propose an iterative quantizer design algorithm that seeks to find a non-regular mapping between quantization partitions and their codewords so as to minimize global distortion such as the estimation error. We apply the proposed algorithm to a system where an acoustic amplitude sensor model is employed at each node for source localization. Our experiments demonstrate that a significant performance gain can be achieved by our technique as compared with standard typical designs and even with distributed novel designs recently published.

This paper presents a 120-GHz-band amplifier module with a hermetic sealing structure for a broadband wireless system. The sealing structure for F-band waveguides is a laminate composed of two sealing plates and a spacer. Each sealing plate has a fused glass window and separates inside air from the ambient atmosphere. The design process of the sealing structure is simple and has good simulation fidelity. The hermetic sealing structure designed for an amplifier in a 120-GHz-band wireless link has an insertion loss of less than 1dB and a return loss of more than 15dB in the operating band. We made three kinds of sealed modules to evaluate the sealing function. The modules sealed with this technique meet the hermetic-seal standard in MIL-STD-883F. We then verified that the sealing structure on the sealed modules has a small enough effect for the transmittance of the intrinsic characteristics. In addition, we performed 10-Gbit/s data transmission using a sealed amplifier module with the bit error rate of less than 10-10.

At CaLC 2001, Howgrave-Graham proposed the polynomial time algorithm for solving univariate linear equations modulo an unknown divisor of a known composite integer, the so-called partially approximate common divisor problem. So far, two forms of multivariate generalizations of the problem have been considered in the context of cryptanalysis. The first is simultaneous modular univariate linear equations, whose polynomial time algorithm was proposed at ANTS 2012 by Cohn and Heninger. The second is modular multivariate linear equations, whose polynomial time algorithm was proposed at Asiacrypt 2008 by Herrmann and May. Both algorithms cover Howgrave-Graham's algorithm for univariate cases. On the other hand, both multivariate problems also become identical to Howgrave-Graham's problem in the asymptotic cases of root bounds. However, former algorithms do not cover Howgrave-Graham's algorithm in such cases. In this paper, we introduce the strategy for natural algorithm constructions that take into account the sizes of the root bounds. We work out the selection of polynomials in constructing lattices. Our algorithms are superior to all known attacks that solve the multivariate equations and can generalize to the case of arbitrary number of variables. Our algorithms achieve better cryptanalytic bounds for some applications that relate to RSA cryptosystems.

In this paper, we show a connection between #P and computing the (real) value of the high order derivative at the origin. Consider, as a problem instance, an integer b and a sufficiently often differentiable function F(x) that is given as a string. Then we consider computing the value F(b)(0) of the b-th derivative of F(x) at the origin. By showing a polynomial as an example, we show that we have FP = #P if we can compute log 2F(b)(0) up to certain precision. The previous statement holds even if F(x) is limited to a function that is analytic at any x ∈ R. It implies the hardness of computing the b-th value of a number sequence from the closed form of its generating function.

We propose an architecture for offloading processes in applications to support low-performance devices. Almost all applications based on standardized web technologies are compatible with our architecture. We discuss how interfaces should be used properly to offload processes in JavaScript and argue that an interface for offloading should only be used for defining complex processes. We also propose a method for applying our architecture to web applications that use web workers. Our method automatically offloads some worker processes to the cloud. We also compare the processing times achieved with and without our method. Our architecture exhibits good efficacy with regards to the N-Queen problem, although it is influenced by network latency between a device and the cloud.