This paper presents a low-latency, low-cost architecture for computing square and cube roots in the fixed-point format. The proposed architecture is designed based on a non-iterative root calculation scheme to achieve fast computations. While previous non-iterative root calculators are restricted to a square-root operation due to the limitation of their mathematical property, the root computation is generalized in this paper to apply an approximation method to the non-iterative scheme. On top of that, a recurrent method is proposed to select parameters, which enables us to reduce the table size while keeping the maximum relative error value low. Consequently, the proposed root calculator can support both square and cube roots at the expense of small delay and low area overheads. This extension can be generalized to compute the nth roots, where n is a positive integer.

We have studied the formation of Ti-nanodots (NDs) by remote H2 plasma (H2-RP) exposure and investigated how the embedding of Ti-NDs affects the resistive switching properties of Si-rich oxides (SiOx) because it is expected that NDs will trigger the formation of the conductive filament path in SiOx. Ti-NDs with an areal density as high as 1011 cm-2 were fabricated by exposing a Ge/Ti stacked layer to the H2-RP without external heating, and changes in the chemical structure of Ge/Ti stacked layer with the Ti-NDs formation were evaluated by using hard x-ray photoemission spectroscopy (HAXPES) and x-ray photoelectron spectroscopy (XPS). Resistive switching behaviors of SiOx with Ti-NDs were measured from current-voltage curves and compared to the results obtained from samples of SiOx with a Ti thin layer.

Personal Wi-Fi Hotspot, the Wi-Fi tethering function, is widely deployed on mobile devices to allow other wireless clients to share Internet access via a broadband connection. Its advantages include no connection fee and support of non-3G/LTE devices. However, utilizing this function can rapidly deplete the battery power of the tethering device because both interface connections (3G/LTE and Wi-Fi) are always on. To address this problem, this paper proposes the Energy Management Mechanism for Wi-Fi Tethering Mode on Mobile Devices (EMWT). The mechanism is designed to effectively manage both interfaces by adjusting certain sleep durations according to the incoming traffic. Short, Long, and Deep sleep durations are introduced for saving energy. EMWT can also guarantee the packet delay bound by limiting the maximum sleep period. Five traffic rates, composed of very low, low, medium, high, and very high, are evaluated. NS-3 simulation results reveal that energy savings of up to 52.52% can be achieved with only a slight impact on system performance, in terms of end-to-end delay, throughput, and packet loss.

In this study, our recent research activities on nanophotonic devices with semiconductor quantum nanostructures are reviewed. We have developed a technique for nanofabricating of high-quality and high-density semiconductor quantum dots (QDs). On the basis of this core technology, we have studied next-generation nanophotonic devices fabricated using high-quality QDs, including (1) a high-performance QD laser for long-wavelength optical communications, (2) high-efficiency compound-type solar cell structures, and (3) single-QD devices for future applications related to quantum information. These devices are expected to be used in high-speed optical communication systems, high-performance renewable energy systems, and future high-security quantum computation and communication systems.

We developed an electrically driven near-infrared broadband light source based on self-assembled InAs quantum dots (QDs). By combining emissions from four InAs QD ensembles with controlled emission center wavelengths, electro-luminescence (EL) with a Gaussian-like spectral shape and approximately 85-nm bandwidth was obtained. The peak wavelength of the EL was blue-shifted from approximately 1230 to 1200 nm with increased injection current density (J). This was due to the state-filling effect: sequential filling of the discrete QD electron/hole states by supplied carriers from lower (ground state; GS) to higher (excited state; ES) energy states. The EL intensities of the ES and GS emissions exhibited different J dependence, also because of the state-filling effect. The point-spread function (PSF) deduced from the Fourier-transformed EL spectrum exhibited a peak without apparent side lobes. The half width at half maximum of the PSF was 6.5 µm, which corresponds to the estimated axial resolution of the optical coherence tomography (OCT) image obtained with this light source. These results demonstrate the effectiveness of the QD-based device for realizing noise-reduced high-resolution OCT.

Bag of Visual Words (BoVW) is an effective framework for image retrieval. Query expansion (QE) further boosts retrieval performance by refining a query with relevant visual words found from the geometric consistency check between the query image and highly ranked retrieved images obtained from the first round of retrieval. Since QE checks the pairwise consistency between query and highly ranked images, its performance may deteriorate when there are slight degradations in the query image. We propose Query Bootstrapping as a variant of QE to circumvent this problem by using the consistency of highly ranked images instead of pairwise consistency. In so doing, we regard frequently co-occurring visual words in highly ranked images as relevant visual words. Frequent itemset mining (FIM) is used to find such visual words efficiently. However, the FIM-based approach requires sensitive parameters to be fine-tuned, namely, support (min/max-support) and the number of top ranked images (top-k). Here, we propose an adaptive support algorithm that adaptively determines both the minimum support and maximum support by referring to the first round's retrieval list. Selecting relevant images by using a geometric consistency check further boosts retrieval performance by reducing outlier images from a mining process. An important parameter for the LO-RANSAC algorithm that is used for the geometric consistency check, namely, inlier threshold, is automatically determined by our algorithm. We further introduce tf-fi-idf on top of tf-idf in order to take into account the frequency of inliers (fi) in the retrieved images. We evaluated the performance of QB in terms of mean average precision (mAP) on three benchmark datasets and found that it gave significant performance boosts of 5.37%, 9.65%, and 8.52% over that of state-of-the-art QE on Oxford 5k, Oxford 105k, and Paris 6k, respectively.

We construct the first fully homomorphic encryption (FHE) scheme that encrypts matrices and supports homomorphic matrix addition and multiplication. This is a natural extension of packed FHE and thus supports more complicated homomorphic operations. We optimize the bootstrapping procedure of Alperin-Sheriff and Peikert (CRYPTO 2014) by applying our scheme. Our optimization decreases the lattice approximation factor from Õ(n3) to Õ(n2.5). By taking a lattice dimension as a larger polynomial in a security parameter, we can also obtain the same approximation factor as the best known one of standard lattice-based public-key encryption without successive dimension-modulus reduction, which was essential for achieving the best factor in prior works on bootstrapping of standard lattice-based FHE.

This letter proposes an image fusion method which adopts a union of multiple directional lapped orthogonal transforms (DirLOTs). DirLOTs are used to generate symmetric orthogonal discrete wavelet transforms and then to construct a union of unitary transforms as a redundant dictionary with a multiple directional property. The multiple DirLOTs can overcome a disadvantage of separable wavelets to represent images which contain slant textures and edges. We analyse the characteristic of local luminance contrast, and propose a fusion rule based on interscale relation of wavelet coefficients. Relying on the above, a novel image fusion method is proposed. Some experimental results show that the proposed method is able to significantly improve the fusion performance from those with the conventional discrete wavelet transforms.

This paper proposes a Poisson denoising method with a union of directional lapped orthogonal transforms (DirLOTs). DirLOTs are 2-D non-separable lapped orthogonal transforms with directional characteristics under the fixed-critically-subsampling, overlapping, orthonormal, symmetric, real-valued and compact-support property. In this work, DirLOTs are used to generate symmetric orthogonal discrete wavelet transforms and then a redundant dictionary as a union of unitary transforms. The multiple directional property is suitable for representing natural images which contain diagonal textures and edges. Multiple DirLOTs can overcome a disadvantage of separable wavelets in representing diagonal components. In addition to this feature, multiple DirLOTs make transform-based denoising performance better through the redundant representation. Experimental results show that the combination of the variance stabilizing transformation (VST), Stein's unbiased risk estimator-linear expansion of threshold (SURE-LET) approach and multiple DirLOTs is able to significantly improve the denoising performance.

A miniaturized patch hybrid coupler with arbitrary power ratio and impedance transformation is proposed and designed by loading a pair of asymmetric cross slots on a squared patch resonator. To obtain the arbitrary power ratio and impedance transformation, the rectangular size of stepped slot ends should be well designed to be asymmetry and thus to obtain the different inductive loadings along two current paths. Theoretically, the equivalent transmission line model is first developed to understand the physical relationship between the patch and traditional branch-line hybrids. The matching/isolation and power ratio conditions are then derived at center frequency. By following a detailed design guideline, a prototype of the hybrid with 1:2 power ratio and 1:1.3 impedance transformation is designed and fabricated at 4.2 GHz. The measured results show a good agreement with simulated results, where the measured -10 dB impedance bandwidth achieves 18% and the bandwidth of 90°±6° phase difference is about 35% in a frequency range from 3.5 GHz to 5 GHz.

Ni nanodots (NDs) used as nano-scale top electrodes were formed on a 10-nm-thick Si-rich oxide (SiO$_{mathrm{x}}$)/Ni bottom electrode by exposing a 2-nm-thick Ni layer to remote H$_{2}$-plasma (H$_{2}$-RP) without external heating, and the resistance-switching behaviors of SiO$_{mathrm{x}}$ were investigated from current-voltage ( extit{I--V}) curves. Atomic force microscope (AFM) analyses confirmed the formation of electrically isolated Ni NDs as a result of surface migration and agglomeration of Ni atoms promoted by the surface recombination of H radicals. From local extit{I--V} measurements performed by contacting a single Ni ND as a top electrode with a Rh coated Si cantilever, a distinct uni-polar type resistance switching behavior was observed repeatedly despite an average contact area between the Ni ND and the SiO$_{mathrm{x}}$ as small as $sim$ 1.9 $ imes$ 10$^{-12}$cm$^{2}$. This local extit{I--V} measurement technique is quite a simple method to evaluate the size scalability of switching properties.

It is significant to develop better search methods to handle the rapidly increasing volume of multimedia data. For NN (Nearest Neighbor) search in metric spaces, the TLAESA (Tree Linear Approximating and Eliminating Search Algorithm) is a state of art fast search method. In this paper a method is proposed to improve the TLAESA by revising the tree structure with an optimal number of selected global pivots in the higher levels as representatives and employing the best-first search strategy. Based on an improved version of the TLAESA that succeeds in using the best-first search strategy to greatly reduce the distance calculations, this method improves the drawback that calculating less at the price of the lower pruning rate of branches. The lower pruning rate further can lead to lower search efficiency, because the priority queue used in the adopted best-first search strategy stores the information of the visited but unpruned nodes, and need be frequently accessed and sorted. In order to enhance the pruning rate of branches, the improved method tries to make more selected global pivots locate in the higher levels of the search tree as representatives. As more real distances instead of lower bound estimations of the node-representatives are used for approximating the closet node and for “branch and bound”, not only which nodes are close to the query object can be evaluated more effectively, but also the pruning rate of branches can be enhanced. Experiments show that for k-NN queries in Euclidean space, in a proper pivot selection strategy the proposed method can reach the same fewest distance calculations as the LAESA (Linear Approximating and Eliminating Search Algorithm) which saves more calculations than the TLAESA, and can achieve a higher search efficiency than the TLAESA.

The MR image segmentation is always a challenging problem because of the intensity inhomogeneity. Many existing methods don't reach their expected segmentations; besides their implementations are usually complicated. Therefore, we originally interleave the extended Otsu segmentation with bias field estimation in an energy minimization. Via our proposed method, the optimal segmentation and bias field estimation are achieved simultaneously throughout the reciprocal iteration. The results of our method not only satisfy the required classification via its applications in the synthetic and the real images, but also demonstrate that our method is superior to the baseline methods in accordance with the performance analysis of JS metrics.

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.

A number of well-known learning-based face detectors can achieve extraordinary performance in controlled environments. But face detection under varying illumination is still challenging. Possible solutions to this illumination problem could be creating illumination invariant features or utilizing skin color information. However, the features and skin colors are not sufficiently reliable under difficult lighting conditions. Another possible solution is to do illumination normalization (e.g., Histogram Equalization (HE)) prior to executing face detectors. However, applications of normalization to face detection have not been widely studied in the literature. This paper applies and evaluates various existing normalization methods under the framework of combining the illumination normalization and two learning-based face detectors (Haar-like face detector and LBP face detector). These methods were initially proposed for different purposes (face recognition or image quality enhancement), but some of them significantly improve the original face detectors and lead to better performance than HE according to the results of the comparative experiments on two databases. Meanwhile, we propose a new normalization method called segmentation-based half histogram stretching and truncation (SH) for face detection under varying illumination. It first employs Otsu method to segment the histogram (intensities) of the input image into several spans and then does the redistribution on the segmented spans. In this way, the non-uniform illumination can be efficiently compensated and local facial structures can be appropriately enhanced. Our method obtains good performance according to the experiments.

In this paper we report on experiences gained and lessons learned by the use of the Timed OTS/CafeOBJ method in the formal verification of TESLA source authentication protocol. These experiences can be a useful guide for the users of the OTS/CafeOBJ, especially when dealing with such complex systems and protocols.

We have succeeded in highly selective growth and positioning of Si- and SiGe-quantum-dots (QDs) on SiO2 patterns by controlling the reactive area, whose surface is terminated with OH bonds for Si nucleation in low-pressure chemical vapor deposition (LPCVD). The selective growth of QDs on thermally grown SiO2 line-patterns was demonstrated in LPCVD of SiH4 and GeH4 just after Si nucleation by controlling the early stages of Si2H6-LPCVD, which indicates effectively enhanced initial nucleation on OH-terminated SiO2 surface and suppression of the nucleation and growth of dots on as-grown SiO2 surface during Si2H6-LPCVD prior to SiH4-LPCVD.

Recently, the wavelet-based estimation method has gradually been becoming popular as a new tool for software reliability assessment. The wavelet transform possesses both spatial and temporal resolution which makes the wavelet-based estimation method powerful in extracting necessary information from observed software fault data, in global and local points of view at the same time. This enables us to estimate the software reliability measures in higher accuracy. However, in the existing works, only the point estimation of the wavelet-based approach was focused, where the underlying stochastic process to describe the software-fault detection phenomena was modeled by a non-homogeneous Poisson process. In this paper, we propose an interval estimation method for the wavelet-based approach, aiming at taking account of uncertainty which was left out of consideration in point estimation. More specifically, we employ the simulation-based bootstrap method, and derive the confidence intervals of software reliability measures such as the software intensity function and the expected cumulative number of software faults. To this end, we extend the well-known thinning algorithm for the purpose of generating multiple sample data from one set of software-fault count data. The results of numerical analysis with real software fault data make it clear that, our proposal is a decision support method which enables the practitioners to do flexible decision making in software development project management.

In P2P applications, networks are formed by devices belonging to independent users. Therefore, routing hotspots or routing congestions are typically created by an unanticipated new event that triggers an unanticipated surge of users to request streaming service from some particular nodes; and a challenging problem is how to provide incentive mechanisms to allocation bandwidth more fairly in order to avoid congestion and other short backs for P2P QoS. In this paper, we study P2P bandwidth game — the bandwidth allocation in P2P networks. Unlike previous works which focus either on routing or on forwarding, this paper investigates the game theoretic mechanism to incentivize node's real bandwidth demands and propose novel method that avoid congestion proactively, that is, prior to a congestion event. More specifically, we define an incentive-compatible pricing vector explicitly and give theoretical proofs to demonstrate that our mechanism can provide incentives for nodes to tell the true bandwidth demand. In order to apply this mechanism to the P2P distribution applications, we evaluate our mechanism by NS-2 simulations. The simulation results show that the incentive pricing mechanism can distribute the bandwidth fairly and effectively and can also avoid the routing hotspot and congestion effectively.

This paper, presents a high-speed full swing driver for a heavy-load flat-panel scan-line circuit. The high driving capability is achieved using the proposed Complementary Dual-Bootstrap (CDUB) technique. The scan-line CDUB driver was fabricated in a 0.35-µm CMOS technology. The measured results, under the flat-panel scan-line load model, indicate that the delay time is within 2.8µs and the average power is 0.74mW for a 5V supply voltage.