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.

In this letter, the k-out-of-n rule for cooperative sensing is considered. For a given n, we derive the optimal value of k that minimizes the total sensing error probability subject to the sensing accuracy, considering both the effective of sensing errors and the primary activities. According to the optimal k, we analyze the performance and compare with other schemes, which illustrate the effectiveness of the proposed scheme.

In this work, a gate-all-around (GAA) tunneling field-effect transistor (TFET) with InGaAs/Si heterojunction for high-performance and low-standby power operations is studied. Gallium (Ga) compositon ($x)$ in In$_{1-x}$Ga$_{x}$As source substantially affects the physical properties related with device performances including lattice constant, bandgap energy, effective tunneling mass, channel mobility, and others. Thus, it is worthy investigating the effect of Ga fraction on performances of the proposed heterojunction TFET. For this goal, the device design and its performance evaluation are carried out by technology computer-aided design (TCAD). Direct-current (DC) performances are investigated in terms of on-state current ($I_{ m{on}})$, off-state current ($I_{ m{off}})$, current ratio ($I_{ m{on}}$/$I_{ m{off}})$, and subthreshold swing ($S$). Furthermore, it is shown that the device with an n-type Si insertion layer between source and channel demonstrates the enhanced DC characteristics.

We consider some attacks on multi-prime RSA (MPRSA) with a modulus N = p1p2 . . . pr (r ≥ 3). It is believed that the small private exponent attack on the MPRSA is less effective than that on RSA (see Hinek et al.'s work at SAC 2003), which means smaller private exponents can be used in the MPRSA to speed up the decryption process. Our work shows that even if a private exponent is significantly beyond Hinek et al.'s bound, it still may be insecure if the prime difference Δ (Δ = pr - p1 = Nγ, supposing p1 < p2 < … < pr) is small, i.e. 0 < γ < 1/r. Specifically, by taking full advantage of prime properties, our small private exponent attack reveals that the MPRSA is insecure when $delta<1-sqrt{1+2gamma-3/r}$ (if $gammagerac{3}{2r}-rac{1+delta}{4}$) or $deltale rac{3}{r}-rac{1}{4}-2gamma$ (if $gamma < rac{3}{2r}-rac{1+delta}{4}$), where δ is the exponential of the private exponent d with base N, i.e., d = Nδ. In addition, we present a Fermat-like factoring attack which factors N efficiently when Δ < N1/r2. These proposed attacks surpass previous works (e.g. Bahig et al.'s at ICICS 2012), and are proved effective in practice.

In this paper, the function expansion based topology optimization is employed to the automatic optimization of the waveguide dispersion property, and the optimum design of low-dispersion slow-light photonic crystal waveguides is demonstrated. In order to realize low-dispersion and large group index, an objective function to be optimized is expressed by the weighted sum of the objective functions for the desired group index and the low-dispersion property, and weighting coefficients are updated through the optimization process.

An optoelectronic 32-bit serial-to-parallel converter with a novel conversion scheme and shared-trigger configuration has been developed for the label processing of 100-Gbps (25-Gbps $ imes 4 lambda)$ optical packets. No external optical trigger source is required to operate the converter, as the optical packet itself is used to perform self-triggering. Compared to prior optoelectronic label converters, the new device has a much higher gain even while converting labels at higher data rates, and exhibits tolerance to the voltage swing of received packets. The device response is presented together with the experimental demonstration of serial-to-parallel conversion for 4 different labels at 25 Gbps.

Blur distortion is a common artifact in image communication and affects the perceived sharpness of a digital image. In this paper, we capitalize on the mathematical knowledge of Gaussian convolution and propose a strategy to minimally reblur test images. From the reblur algorithm, synthetic reblur images are created. We propose a new blind blur metric which makes use of the reblur images to produce blur scores. Compared to other no-reference blur assessments, the proposed method has the advantages of fast computation and training-free operation. Experiment results also show that the proposed method can produce blur scores which are highly correlated with human perception of blurriness.

We address the problem of estimating the difference between two probability densities. A naive approach is a two-step procedure that first estimates two densities separately and then computes their difference. However, such a two-step procedure does not necessarily work well because the first step is performed without regard to the second step and thus a small error in the first stage can cause a big error in the second stage. Recently, a single-shot method called the least-squares density-difference (LSDD) estimator has been proposed. LSDD directly estimates the density difference without separately estimating two densities, and it was demonstrated to outperform the two-step approach. In this paper, we propose a variation of LSDD called the constrained least-squares density-difference (CLSDD) estimator, and theoretically prove that CLSDD improves the accuracy of density difference estimation for correctly specified parametric models. The usefulness of the proposed method is also demonstrated experimentally.

In recent years, computation offloading, through which applications on a mobile device can offload their computations onto more resource-rich clouds, has emerged as a promising technique to reduce battery consumption as well as augment the devices' limited computation and memory capabilities. In order for computation offloading to be energy-efficient, an accurate estimate of battery consumption is required to decide between local processing and computation offloading. In this paper, we propose a novel technique for estimating battery consumption without requiring detailed information about the mobile application's internal structure or its execution behavior. In our approach, the relationship is derived between variables that affect battery consumption (i.e., the input to the application, the transmitted data, and resource status) and the actual consumed energy from the application's past run history. We evaluated the performance of the proposed technique using two different types of mobile applications over different wireless network environments such as 3G, Wi-Fi, and LTE. The experimental results show that our technique can provide tolerable estimation accuracy and thus make correct decisions between local processing and computation offloading.

With the advances in wireless Internet and mobile positioning technology, location-based services (LBSs) have become popular. In LBSs, users must send their exact locations in order to use the services, but they may be subject to several privacy threats. To solve this problem, query processing algorithms based on a cloaking method have been proposed. The algorithms use spatial cloaking methods to blur the user's exact location in a region satisfying the required privacy threshold (k). With the cloaked region, an LBS server can execute a spatial query processing algorithm preserving their privacy. However, the existing algorithms cannot provide good query processing performance. To resolve this problem, we, in this paper, propose a k-NN query processing algorithm based on network Voronoi diagram for spatial networks. Therefore, our algorithm can reduce network expansion overhead and share the information of the expanded road network. In order to demonstrate the efficiency of our algorithms, we have conducted extensive performance evaluations. The results show that our algorithm achieves better performance on retrieval time than the existing algorithms, such as PSNN and kRNN. This is because our k-NN query processing algorithm can greatly reduce a network expansion cost for retrieving k POIs.

We propose a power-saving mechanism (PSM) specific to request-and-response-based applications, which simply changes the order of the operating procedure of the legacy PSM by considering the attributes of the request-and-response delay. We numerically analyze the PSM with respect to the energy consumption and buffering delay and characterize this performance by employing a simple energy-delay trade-off (EDT) curve that is determined by the operating parameters. The resulting EDT curve clearly shows that the proposed PSM outperforms the legacy PSM.

In LTE (Long Term Evolution)-Advanced system, a transparent MU-MIMO (Multi-User Multiple-Input Multiple Output) scheduling is basically considered, so the performance degradation in channel estimation may occur due to the unpredictable interference from co-scheduled layers. In order to detect and mitigate the interference, traditional binary hypothesis testing based interference detection method and iterative channel estimation method can be applied. However, there are two major problems. First, the binary hypothesis testing based interference detection is not suitable solution for LTE-Advanced system which has four dynamically changing interference hypotheses. Second, the conventional iterative operation does not guarantee sufficient performance gain with limited iteration time due to the estimation error in initial estimation stage. To overcome these problems, we introduce an enhanced iterative channel estimation method which considers simple matrix operation-based partial interference estimation. Based on the outcomes of the partial interference estimation, we can not only detect interference layers individually, but also partially eliminate the interference in initial channel estimation stage. Consequently, the proposed method can effectively mitigate the interference adaptively to the dynamically changing interference condition.

Graphene is attracting attention in electrical and optical research fields recently. We measured the optical absorption characteristics and polarization dependence of single-layer graphene (SLG) on sub-micrometer Si waveguide. The results for graphene lengths ranging from 2.5 to 200 $mu$ m reveal that the optical absorption by graphene is 0.09 dB/$mu$ m with the TE mode and 0.05 dB/$mu$ m with the TM mode. The absorption in the TE mode is 1.8 times higher than that in the TM mode. An optical spectrum, theoretical analysis and Raman spectrum indicate that surface-plasmon polaritons in graphene support TM mode light propagation.

Acoustic feedback is a major complaint of hearing aid users. Adaptive filters are a common method for suppressing acoustic feedback in digital hearing aids. In this letter, we propose a new variable step-size algorithm for normalized least mean square and an affine projection algorithm to combine with a variable step-size affine projection algorithm and global speech absence probability in an adaptive filter. The computer simulation used to test the proposed algorithm results in a lower misalignment error than the comparison algorithm at a similar convergence rate. Therefore, the proposed algorithm suggests an effective solution for the feedback suppression system of digital hearing aids.

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.

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.

Currently, a correspondent host will have difficulties in establishing a direct session path to a mobile host because of the partial deployment of MIPv6-aware mobile hosts. Even MIPv6-aware hosts will spend up to several seconds to obtain the new location of the mobile host during Layer 3 (L3) handover. This paper proposes an application-level mobility management scheme that can solve the problems related to the increase of Internet traffic end-to-end delay under the current situation that most of the mobile devices are MIPv6-non-aware. The proposed Secure Mobility Management Application (SMMA) enables the updates of care-of address to be faster and more reliable even when L3 handovers occur frequently. SMMA uses a cross-layer approach for session mobility management with the support of Binding Updates to the home agent via IPSec tunnels. The main feature of SMMA is to handle the session-related mobility management for which operation starts just after the completion of name resolution as a pre-call mobility management, which operates in conjunction with the DNS. Our session-related mobility management introduces three new signaling messages: SS-Create for session state creation, SS-Refresh for session state extension and SS-Renewal for updating new care-of address at the mid-session. Finally, this paper analyzes the work load imposed on a mobile host to create a session state and the security strength of the SS-Renewal message, which depends on the key size used.

In this invited paper, software defined network (SDN)-based approaches for future cost-effective optical mobile backhaul (MBH) networks are discussed, focusing on key principles, throughput optimization and dynamic service provisioning as its use cases. We propose a novel physical-layer aware throughput optimization algorithm that confirms > 100Mb/s end-to-end per-cell throughputs with ≥2.5Gb/s optical links deployed at legacy cell sites. We also demonstrate the first optical line terminal (OLT)-side optical Nyquist filtering of legacy 10G on-off-keying (OOK) signals, enabling dynamic >10Gb/s Orthogonal Frequency Domain Multiple Access (OFDMA) λ-overlays for MBH over passive optical network (PON) with 40-km transmission distances and 1:128 splitting ratios, without any ONU-side equipment upgrades. The software defined flexible optical access network architecture described in this paper is thus highly promising for future MBH networks.

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.

This paper presents a new information-theoretical evaluation method, for the resistance of cryptographic implementation against side-channel attacks. In conventional methods, the results of actual attacks have been often used empirically. However, these experimental methods have some problems. In the proposed method, a side-channel attack is regarded as a communication channel model. Then, a new evaluation index “the amount of leakage information” can be defined. The upper-bound of this index is estimated as the channel capacity. The proposed evaluation using this index can avoid the problems of conventional methods. Consequently, the proposed method provides some benefits: (1) It provides rationale for evaluation; (2) It enables execution of numerical evaluation and mutual evaluation among several kinds of countermeasures. This research achieves a unification of evaluation indexes for resistance against side-channel attack. This paper applies the proposed method to correlation power analysis against implementations of stream cipher Enocoro-128 v2. As a result, we confirmed its effectiveness.