This paper proposes secure regenerating codes that are composed of non-secure regenerating codes and a new all-or-nothing transform. Unlike the previous analysis of secure regenerating codes, the security of the proposed codes is analyzed in the sense of the indistinguishability. The advantage of the proposed codes is that the overhead caused by the security against eavesdropping is much less than that of previous secure regenerating codes. The security of the proposed codes against eavesdropping mainly depends on the new all-or-nothing transform.

An 8-issue superscalar core generally requires a 24-port RAM for the register file. The area and energy consumption of a multiported RAM increase in proportional to the square of the number of ports. A register cache can reduce the area and energy consumption of the register file. However, earlier register cache systems suffer from lower IPC caused by register cache misses. Thus, we proposed the Non-Latency-Oriented Register Cache System (NORCS) to solve the IPC problem with a modified pipeline. We evaluated NORCS mainly from the viewpoint of microarchitecture in the original article, and showed that NORCS maintains almost the same IPC as conventional register files. Researchers in NVIDIA adopted the same idea for their GPUs. However, the evaluation was not sufficient from the viewpoint of LSI design. In the original article, we used CACTI to evaluate the area and energy consumption. CACTI is a design space exploration tool for cache design, and adopts some rough approximations. Therefore, this paper shows design of NORCS with FreePDK45, an open source process design kit for 45nm technology. We performed manual layout of the memory cells and arrays of NORCS, and executed SPICE simulation with RC parasitics extracted from the layout. The results show that, from a full-port register file, an 8-entry NORCS achieves a 75.2% and 48.2% reduction in area and energy consumption, respectively. The results also include the latency which we did not present in our original article. The latencies of critical path is 307ps and 318ps for an 8-entry NORCS and a conventional multiported register file, respectively, when the same two cycles are allocated to register file read.

This work reports a novel power-rail electrostatic discharge (ESD) clamp circuit with parasitic bipolar-junction-transistor (BJT) and channel parallel shunt paths. The parallel shunt paths are formed by delivering a tiny ratio of drain voltage to the gate terminal of the clamp device in ESD events. Under such a mechanism, the proposed circuit achieves enhanced robustness over those of both gate-grounded NMOS (ggNMOS) and the referenced gate-coupled NMOS (gcNMOS). Besides, the proposed circuit also achieves improved fast power-up immunity over that of the referenced gcNMOS. All investigated designs are fabricated in a 65-nm CMOS process. Transmission-line-pulsing (TLP) and human-body-model (HBM) test results have both confirmed the performance enhancements of the proposed circuit. Finally, the validity of the achieved performance enhancements on other trigger circuits is essentially revealed in this work.

An equivalent-circuit model is an effective tool for the analysis and design of metamaterials. This paper describes a systematic and theoretical method for the circuit modeling of meta-atoms. We focus on the structures of wired metallic spheres and propose a method for deriving a sophisticated equivalent circuit that has the same topology as the wires using the partial element equivalent circuit (PEEC) method. Our model contains the effect of external electromagnetic coupling: excitation by an external field modeled by voltage sources and radiation modeled by the radiation resistances for each mode. The equivalent-circuit model provides the characteristics of meta-atoms such as the resonant frequencies and the resonant modes induced by the current distribution in the wires by an external excitation. Although the model is obtained by a very coarse discretization, it provides a good agreement with an electromagnetic simulation.

In this paper, we present two classes of zero difference balanced (ZDB) functions, which are derived by difference balanced functions, and a class of perfect ternary sequences respectively. The proposed functions have parameters not covered in the literature, and can be used to design optimal constant composition codes, and perfect difference systems of sets.

Superconducting Transition edge sensor (TES) coupled with a heavy metal absorber is a promising microcalorimeter for Gamma-ray (γ-ray) spectroscopy with ultra-high energy resolution and high detection efficiency. It is very useful for the non-destructed inspection of the nuclide materials. High resolving power of γ-ray peaks can precisely identify multiple nuclides such as Plutonium (Pu) and Actinides with high efficiency and safety. For this purpose, we have developed the TES coupled with a tin absorber. We suggest the new device structure using the gold bump post which connects a tin absorber to the thermometer of the superconducting Ir/Au bilayer. High thermal conductivity of the gold bump post realized strong thermal coupling between the thermometer and the γ-ray absorber, and it brought the benefit of large pulse height and fast decay time. Our TES achieved the good energy resolution of 84 eV FWHM at 59.5 keV. Using this TES device, we also succeeded to demonstrate the nuclear material measurements. In the measurement of a Pu sample, we detected the sharp γ-ray peaks from 239Pu and 240Pu, and of a Fission Products (FP) sample, we observed fluorescence X-ray peaks emitted by the elements contained in FP. The TES could resolve the fine structures of each fluorescence X-ray line like Kα1 and Kα2. In addition to that, we developed the TES coupled with tantalum absorber, which is expected to have higher absorption efficiency for γ-rays. This device reported the best energy resolution of 465 eV at 662 keV.

The solution of the standard 2-norm-based multiple kernel regression problem and the theoretical limit of the considered model space are discussed in this paper. We prove that 1) The solution of the 2-norm-based multiple kernel regressor constructed by a given training data set does not generally attain the theoretical limit of the considered model space in terms of the generalization errors, even if the training data set is noise-free, 2) The solution of the 2-norm-based multiple kernel regressor is identical to the solution of the single kernel regressor under a noise free setting, in which the adopted single kernel is the sum of the same kernels used in the multiple kernel regressor; and it is also true for a noisy setting with the 2-norm-based regularizer. The first result motivates us to develop a novel framework for the multiple kernel regression problems which yields a better solution close to the theoretical limit, and the second result implies that it is enough to use the single kernel regressors with the sum of given multiple kernels instead of the multiple kernel regressors as long as the 2-norm based criterion is used.

We proposed to apply compressed sensing to realize information sharing of link quality for wireless mesh networks (WMNs) with grid topology. In this paper, we extend the link quality sharing method to be applied for WMNs with arbitrary topology. For arbitrary topology WMNs, we introduce a link quality matrix and a matrix formula for compressed sensing. By employing a diffusion wavelets basis, the link quality matrix is converted to its sparse equivalent. Based on the sparse matrix, information sharing is achieved by compressed sensing. In addition, we propose compressed transmission for arbitrary topology WMNs, in which only the compressed link quality information is transmitted. Experiments and simulations clarify that the proposed methods can reduce the amount of data transmitted for information sharing and maintain the quality of the shared information.

An efficient means of learning tree-structural features from tree-structured data would enable us to construct effective mining methods for tree-structured data. Here, a pattern representing rich tree-structural features common to tree-structured data and a polynomial time algorithm for learning important tree patterns are necessary for mining knowledge from tree-structured data. As such a tree pattern, we introduce a term tree pattern t such that any edge label of t belongs to a finite alphabet Λ, any internal vertex of t has ordered children and t has a new kind of structured variable, called a height-constrained variable. A height-constrained variable has a pair of integers (i, j) as constraints, and it can be replaced with a tree whose trunk length is at least i and whose height is at most j. This replacement is called height-constrained replacement. A sequence of consecutive height-constrained variables is called a variable-chain. In this paper, we present polynomial time algorithms for solving the membership problem and the minimal language (MINL) problem for term tree patternshaving no variable-chain. The membership problem for term tree patternsis to decide whether or not a given tree can be obtained from a given term tree pattern by applying height-constrained replacements to all height-constrained variables in the term tree pattern. The MINL problem for term tree patternsis to find a term tree pattern t such that the language generated by t is minimal among languages, generated by term tree patterns, which contain all given tree-structured data. Finally, we show that the class, i.e., the set of all term tree patternshaving no variable-chain, is polynomial time inductively inferable from positive data if |Λ| ≥ 2.

Characteristics of the bis-styrylbenzene derivatives with trifluoromethyl or methyl moieties were evaluated in each as-vapor-deposited film, thermally-treated film, and the crystal from the solution. Thermal treatment dramatically changed morphologies and photo-physical properties of the vapor-deposited film.

In this letter, we propose a novel method for face hallucination by learning a new distance metric in the low-resolution (LR) patch space (source space). Local patch-based face hallucination methods usually assume that the two manifolds formed by LR and high-resolution (HR) image patches have similar local geometry. However, this assumption does not hold well in practice. Motivated by metric learning in machine learning, we propose to learn a new distance metric in the source space, under the supervision of the true local geometry in the target space (HR patch space). The learned new metric gives more freedom to the presentation of local geometry in the source space, and thus the local geometries of source and target space turn to be more consistent. Experiments conducted on two datasets demonstrate that the proposed method is superior to the state-of-the-art face hallucination and image super-resolution (SR) methods.

It is well known that spatially coupled (SC) codes with erasure-BP decoding have powerful error correcting capability over memoryless erasure channels. However, the decoding performance of SC-codes significantly degrades when they are used over burst erasure channels. In this paper, we propose band splitting permutations (BSP) suitable for (l,r,L) SC-codes. The BSP splits a diagonal band in a base matrix into multiple bands in order to enhance the span of the stopping sets in the base matrix. As theoretical performance guarantees, lower and upper bounds on the maximal burst correctable length of the permuted (l,r,L) SC-codes are presented. Those bounds indicate that the maximal correctable burst ratio of the permuted SC-codes is given by λmax≃1/k where k=r/l. This implies the asymptotic optimality of the permuted SC-codes in terms of burst erasure correction.

In this paper, a printed elliptical monopole antenna for wideband circular polarization is proposed. The antenna's structure is asymmetric with regard to the microstrip line. The section of the ground plane that overlaps the elliptical patch is removed. With simulations, the relationship between the antenna's geometrical parameters and the antenna's axial ratio of circularly polarized wave is clarified. The operational principle for wideband circular polarization is explained by the simulated electric current distributions. The simulated and measured bandwidths of the 3dB-axial ratio with a 2-VSWR is approximately 88.4% (2.12GHz-5.47GHz) and 83.6% (2.20GHz-5.36GHz), respectively.

Network coding (NC) is considered a new paradigm for distributed networks. However, NC has an all-or-nothing property. In this paper, we propose a sparse recovery approach using sparse sensing matrix to solve the NC all-or-nothing problem over a finite field. The effectiveness of the proposed approach is evaluated based on a sensor network.

Much attention has recently been paid to sparsity-aware space-time adaptive processing (STAP) algorithms. The idea of sparsity-aware technology is commonly based on the convex l1-norm penalty. However, some works investigate the lq (0 < q < 1) penalty which induces more sparsity owing to its lack of convexity. We herein consider the design of an lq penalized STAP processor with a generalized sidelobe canceler (GSC) architecture. The lq cyclic descent (CD) algorithm is utilized with the least squares (LS) design criterion. It is validated through simulations that the lq penalized STAP processor outperforms the existing l1-based counterparts in both convergence speed and steady-state performance.

Carrier transport characteristics of TIPS-pentacene single crystalline film were controlled by changing the deposition condition of the blade-coating method. Anisotropic carrier transport in the single crystalline grain was visualized by means of the time-resolved microscopic optical second harmonic generation (TRM-SHG) measurement. Slow deposition yields the film with high mobility and large transport anisotropy. For molecular crystals, intermolecular interaction can be modified easily by changing the process condition.

In this paper, we propose a method to find similar sentences based on language resources for building a parallel corpus between English and Korean from Wikipedia. We use a Wiki-dictionary consisted of document titles from the Wikipedia and bilingual example sentence pairs from Web dictionary instead of traditional machine readable dictionary. In this way, we perform similarity calculation between sentences using sequential matching of the language resources, and evaluate the extracted parallel sentences. In the experiments, the proposed parallel sentences extraction method finally shows 65.4% of F1-score.

The paper studies controllability of an aggregate demand response system, i.e., the amount of the change of the total electric consumption in response to the change of the electric price, for real-time pricing (RTP). In order to quantify the controllability, this paper defines the controllability index as the lowest occurrence probability of the total electric consumption when the best possible the electric price is chosen. Then the paper formulates the problem which finds the consumer group maximizing the controllability index. The controllability problem becomes hard to solve as the number of consumers increases. To give a solution of the controllability problem, the article approximates the controllability index by the generalized central limit theorem. Using the approximated controllability index, the controllability problem can be reduced to a problem for solving nonlinear equations. Since the number of variables of the equations is independent of the number of consumers, an approximate solution of the controllability problem is obtained by numerically solving the equations.

Event-triggered control is a control method that the measured signal is sent to the controller only when a certain triggering condition on the measured signal is satisfied. In this paper, we propose a linear quadratic regulator (LQR) with decentralized triggering conditions. First, a suboptimal solution to the design problem of LQRs with decentralized triggering conditions is derived. A state-feedback gain can be obtained by solving a convex optimization problem with LMI (linear matrix inequality) constraints. Next, the relation between centralized and decentralized triggering conditions is discussed. It is shown that control performance of an LQR with decentralized event-triggering is better than that with centralized event-triggering. Finally, a numerical example is illustrated.

Purchase behavior prediction is one of the most important issues to promote both e-commerce companies' sales and the consumers' satisfaction. The prediction usually uses features based on the statistics of items. This kind of features can lead to the loss of detailed information of items. While all items are included, a large number of features has the negative impact on the efficiency of learning the predictive model. In this study, we propose to use the most popular items for improving the prediction. Experiments on the real-world dataset have demonstrated the effectiveness and the efficiency of our proposed method. We also analyze the reason for the performance of the most popular items. In addition, our work also reveals if interactions among most popular items are taken into account, the further significant improvement can be achieved. One possible explanation is that online retailers usually use a variety of sales promotion methods and the interactions can help to predict the purchase behavior.