Many deterministic small-world network models have been proposed so far, and they have been proven useful in describing some real-life networks which have fixed interconnections. Search efficiency is an important property to characterize small-world networks. This paper tries to clarify how the search procedure behaves when random walks are performed on small-world networks, including the classic WS small-world network and three deterministic small-world network models: the deterministic small-world network created by edge iterations, the tree-structured deterministic small-world network, and the small-world network derived from the deterministic uniform recursive tree. Detailed experiments are carried out to test the search efficiency of various small-world networks with regard to three different types of random walks. From the results, we conclude that the stochastic model outperforms the deterministic ones in terms of average search steps.

The noise in digital images acquired by image sensors has complex characteristics due to the variety of noise sources. However, most noise reduction methods assume that an image has additive white Gaussian noise (AWGN) with a constant standard deviation, and thus such methods are not effective for use with image signal processors (ISPs). To efficiently reduce the noise in an ISP, we estimate a unified noise model for an image sensor that can handle shot noise, dark-current noise, and fixed-pattern noise (FPN) together, and then we adaptively reduce the image noise using an adaptive Smallest Univalue Segment Assimilating Nucleus ( SUSAN ) filter based on the unified noise model. Since our noise model is affected only by image sensor gain, the parameters for our noise model do not need to be re-configured depending on the contents of image. Therefore, the proposed noise model is suitable for use in an ISP. Our experimental results indicate that the proposed method reduces image sensor noise efficiently.

A highly parallel turbo decoder for 3GPP LTE/LTE-Advanced systems is presented. It consists of 32 radix-4 soft-in/soft-out (SISO) decoders. Each SISO decoder is based on the proposed full-parallel sliding window (SW) schedule. Implemented in a 0.13 µm CMOS technology, the proposed design occupies 12.96 mm2 and achieves 1.5 Gb/s while decoding size-6144 blocks with 5.5 iterations. Compared with conventional SW schedule, the throughput is improved by 30–76% with 19.2% area overhead and negligible energy overhead.

A gate-all-around tunneling field-effect transistor (GAA TFET) with local high-k gate-dielectric and tunneling-boost n-layer based on silicon is demonstrated by two dimensional (2D) device simulation. Application of local high-k gate-dielectric and n-layer leads to reduce the tunneling barrier width between source and intrinsic channel regions. Thus, it can boost the on-current (Ion) characteristics of TFETs. For optimal design of the proposed device, a tendency of device characteristics has been analyzed in terms of the high-k dielectric length (Lhigh-k) for the fixed n-layer length (Ln-layer). The simulation results have been analyzed in terms of on- and off-current (Ion and Ioff), subthreshold swing (SS), and RF performances.

A predictive spatio-temporal interval join finds all pairs of moving objects satisfying a join condition on future time interval and space. In this paper, we propose a method called PTJoin. PTJoin partitions the inner index into small sub-trees and performs the join process for each sub-tree to reduce the number of disk page accesses for each window search. Furthermore, to reduce the number of pages accessed by consecutive window searches, we partition the index so that overlapping index pages do not belong to the same partition. Our experiments show that PTJoin reduces the number of page accesses by up to an order of magnitude compared to Interval_STJoin [9], which is the state-of-the-art solution, when the buffer size is small.

Training one-class support vector machines (one-class SVMs) involves solving a quadratic programming (QP) problem. By increasing the number of training samples, solving this QP problem becomes intractable. In this paper, we describe a modified Pegasos algorithm for fast training of one-class SVMs. We show that this algorithm is much faster than the standard one-class SVM without loss of performance in the case of linear kernel.

This work proposes an exponential computation with low-computational complexity and applies this technique to the expectation-maximization (EM) algorithm for Gaussian mixture model (GMM). For certain machine-learning techniques, such as the EM algorithm for the GMM, fast and low-cost implementations are preferred over high precision ones. Since the exponential function is frequently used in machine-learning algorithms, this work proposes reducing computational complexity by transforming the function into powers of two and introducing a look-up table. Moreover, to improve efficiency the look-up table is scaled. To verify the validity of the proposed technique, this work obtains simulation results for the EM algorithm used for parameter estimation and evaluates the performances of the results in terms of the mean absolute error and computational time. This work compares our proposed method against the Taylor expansion and the exp( ) function in a standard C library, and shows that the computational time of the EM algorithm is reduced while maintaining comparable precision in the estimation results.

In summary, we successfully fabricated the nonvolatile hybrid polymer 4F2 memory-cell. It was based on bistable state, which was observed in PS layer that is containing a Ni nanocrystals capped with NiO tunneling barrier sandwiched by Al electrodes. The current conduction mechanism for polymer memory-cell was demonstrated by fitting the I-V curves. The electrons were charged and discharged on Ni nanocrystals by tunneling through the NiO tunneling barrier. In addition, the memory-cell showed a good and reproducible nonvolatile memory-cell characteristic. Its memory margin is about 1.410. The retention-time is more than 105 seconds and the endurance cycles of program-and-erase is more than 250 cycles. Furthermore, Thefore, polymer memory-cell would be good candidates for nonvolatile 4F2 cross-bar memory-cell.

We propose a novel threshold-free salient object detection approach which integrates both saliency density and edge response. The salient object with a well-defined boundary can be automatically detected by our approach. Saliency density and edge response maximization is used as the quality function to direct the salient object discovery. The global optimal window containing a salient object is efficiently located through the proposed saliency density and edge response based branch-and-bound search. To extract the salient object with a well-defined boundary, the GrabCut method is applied, initialized by the located window. Experimental results show that our approach outperforms the methods only using saliency or edge response and achieves a comparable performance with the best state-of-the-art method, while being without any threshold or multiple iterations of GrabCut.

In this letter, we first introduce a new generalized cyclotomic sequence of order two of length pq, then we calculate its linear complexity and minimal polynomial. Our results show that this sequence possesses both high linear complexity and optimal balance on 1 s and 0 s, which may be attractive for use in stream cipher cryptosystems.

In this paper, several spiral inductors with various ground clearance structures and turns were investigated to achieve noise suppression up to the fourth harmonic (3.2 GHz) regime of DDR3-1600. Their performances were characterized in terms of their capability to effectively suppress simultaneous switching noise (SSN) in the frequency region of interest. For a wider noise suppression bandwidth, a spiral inductor with large ground clearance, which provides a high self resonance frequency (SRF) as well as high inductances, was implemented. The proposed spiral inductor exhibited good noise suppression characteristics in the frequency domain and achieved 50% voltage fluctuation reduction in the time domain, compared to the identical 4-turn spiral without pattern ground structure.

A modified modeling of residue effect on nano-electro-mechanical nonvolatile memory (NEMory) is presented for considering wet etching process. The effect of a residue under the cantilever is investigated for the optimization. The feasibility of the proposed model is investigated by finite element analysis simulations.

In this paper, we study the problem of joint resource allocation in the two-way relay system, where a pair of multi-antenna users wish to exchange information via multi-antenna amplify-and-forward relay under orthogonal frequency-division multiplexing (OFDM) modulation. We formulate a sum-rate maximization problem subject to a limited power constraint for each user and relay. Our resource allocation strategy aims at finding the best pairing scheme and optimal power allocation over subchannels in frequency and space domains. This turns out to be a mixed integer programming problem. We then derive an asymptotically optimal solution though the Lagrange dual decomposition approach. Finally, simulation results are provided to demonstrate the performance gain of the proposed algorithms.

We have investigated the impact of O2 annealing after SiOx deposition on the switching behavior to gain a better understanding of the resistance switching mechanism, especially the role of oxygen deficiency in the SiOx network. Although resistive random access memories (ReRAMs) with SiOx after 300 annealing sandwiched with Pt electrodes showed uni-polar type resistance switching characteristics, the switching behaviors were barely detectable for the samples after annealing at temperatures over 500. Taking into account of the average oxygen content in the SiOx films evaluated by XPS measurements, oxygen vacancies in SiOx play an important role in resistance switching. Also, the results of conductive AFM measurements suggest that the formation and disruption of a conducting filament path are mainly responsible for the resistance switching behavior of SiOx.

In this letter, we present a joint blind adaptive scheme to suppress inter-block interference and estimate a carrier frequency offset (CFO) in downlink OFDMA systems. The proposed scheme is a combination of a channel shortening method and a CFO estimator, both based on the carrier nulling criterion. Simulation results demonstrate the effectiveness of the proposed scheme.

Ultra-wideband (UWB) pulse radar has high range resolution and permeability in a dielectric medium, and has great potential for the non-destructive inspection or early-stage detection of breast cancer. As an accurate and high-resolution imaging method for targets embedded in a dielectric medium, extended range points migration (RPM) has been developed. Although this method offers an accurate internal target image in a homogeneous media, it assumes the permittivity of the dielectric medium is given, which is not practical for general applications. Although there are various permittivity estimation methods, they have essential problems that are not suitable for clear, dielectric boundaries like walls, or is not applicable to an unknown and arbitrary shape of dielectric medium. To overcome the above drawbacks, we newly propose a permittivity estimation method suitable for various shapes of dielectric media with a clear boundary, where the dielectric boundary points and their normal vectors are accurately determined by the original RPM method. In addition, our method iteratively compensates for the scattered waveform deformation using a finite-difference time domain (FDTD) method to enhance the accuracy of the permittivity estimation. Results from a numerical simulation demonstrate that our method achieves accurate permittivity estimation even for a dielectric medium of wavelength size.

With the rapid expansion of vector data model application to digital content such as drawings and digital maps, the security and retrieval for vector data models have become an issue. In this paper, we present a vector data-hashing algorithm for the authentication, copy protection, and indexing of vector data models that are composed of a number of layers in CAD family formats. The proposed hashing algorithm groups polylines in a vector data model and generates group coefficients by the curvatures of the first and second type of polylines. Subsequently, we calculate the feature coefficients by projecting the group coefficients onto a random pattern, and finally generate the binary hash from binarization of the feature coefficients. Based on experimental results using a number of drawings and digital maps, we verified the robustness of the proposed hashing algorithm against various attacks and the uniqueness and security of the random key.

First, this paper derives the prefix sum-of-products expression (PreSOP) and the number of products in a PreSOP for an interval function. Second, it derives Ψ(n,τp), the number of n-variable interval functions that can be represented with τp products. Finally, it shows that more than 99.9% of the n-variable interval functions can be represented with ⌈ n - 1 ⌉ products, when n is sufficiently large. These results are useful for a fast PreSOP generator and for estimating the size of ternary content addressable memories (TCAMs) for packet classification.

We investigated the effects of chemical treatments for removing native oxide layers on InAlN surfaces by X-ray photoelectron spectroscopy (XPS). The untreated surface of the air exposed InAlN layer was covered with the native oxide layer mainly composed of hydroxides. Hydrochloric acid treatment and ammonium hydroxide treatment were not efficient for removing the native oxide layer even after immersion for 15 min, while hydrofluoric acid (HF) treatment led to a removal in a short treatment time of 1 min. After the HF treatment, the surface was prevented from reoxidation in air for 1 h. We also found that the 5-min buffered HF treatment had almost the same effect as the 1-min HF treatment. Finally, an attempt was made to apply the HF-based treatment to the metal-InAlN contact to confirm the XPS results.

In this paper, a high performance current latch sense amplifier (CLSA) with vertical MOSFET is proposed, and its performances are investigated. The proposed CLSA with the vertical MOSFET realizes a 11% faster sensing time with about 3% smaller current consumption relative to the conventional CLSA with the planar MOSFET. Moreover, the proposed CLSA with the vertical MOSFET achieves an 1.11 dB increased voltage gain G(f) relative to the conventional CLSA with the planar MOSFET. Furthermore, the proposed CLSA realizes up to about 1.7% larger yield than the conventional CLSA, and its circuit area is 42% smaller than the conventional CLSA.