The first part of this paper contains an introduction to Bell inequalities and Tsirelson's theorem for the non-specialist. The next part gives an explicit optimum construction for the “hard” part of Tsirelson's theorem. In the final part we describe how upper bounds on the maximal quantum violation of Bell inequalities can be obtained by an extension of Tsirelson's theorem, and survey very recent results on how exact bounds may be obtained by solving an infinite series of semidefinite programs.

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Quantum random access coding (QRAC) is one of the basic tools in quantum computing. It uses a quantum state for encoding the sender's bit string so that the receiver can recover any single bit of the bit string with high probability. This article surveys recent developments of QRAC, with some concrete examples of QRAC using one quantum bit, and its applications, focusing on communication complexity and locally decodable codes.

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Quantum circuits for elementary arithmetic operations are important not only for implementing Shor's factoring algorithm on a quantum computer but also for understanding the computational power of small quantum circuits, such as linear-size or logarithmic-depth quantum circuits. This paper surveys some recent approaches to constructing efficient quantum circuits for elementary arithmetic operations and their applications to Shor's factoring algorithm. It covers addition, comparison, and the quantum Fourier transform used for addition.

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Quantum computations have so far proved to be more powerful than classical computations, but quantum computers still have not been put into practical use due to several technical issues. One of the most serious problems for realizing quantum computers is decoherence that occurs inevitably since our apparatus are surrounded with environment and open systems. In this paper, we give some surveys on a variety of effects of decoherence in quantum algorithms such as Grover's database search and quantum walks, and we show how quantum algorithms work under decoherence, how sensitive they are against decoherence, and how to implement a robust quantum circuit.

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To solve the problem of distributed multisensor fusion, the optimal linear methods can be used in Gaussian noise models. In practice, channel noise distributions are usually non-Gaussian, possibly heavy-tailed, making linear methods fail. By combining a classical tool of optimal linear fusion and a robust statistical method, the two-stage MAD robust fusion (MADRF) algorithm is proposed. It effectively performs both in symmetrically and asymmetrically contaminated Gaussian channel noise with contamination parameters varying over a wide range.

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An over current protection method suitable for Fixed ON-time PFM (Pulse Frequency Modulation) Control DC-DC converters is proposed. It is based on inductor bottom current limiting, realized by monitoring the synchronous rectifier current and extending the OFF-phase of the main switch until it decreases to a predetermined limit, and can properly limit the output current even in case of short circuit. A Fixed ON-time PFM DC-DC converter with the proposed over current protection was designed and fabricated in CMOS IC. Its current limiting operation was verified with simulations and measurements.

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This paper proposes a new chaos generator circuit with a current sampling scheme. This circuit generates an arbitrary nonlinear function corresponding to the time-domain current waveform supplied from an external source by using a pulse phase modulation approach. The measurement results of a fabricated chip with TSMC 0.25 µm process technology demonstrate that the proposed circuit can generate chaos signals even if D/A conversion is used for nonlinear waveform generation, because a current integral by sampling with a short pulse smooths the quantized nonlinear function.

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In this paper, we propose a simple nonlinear system which consists of a chaotic spiking oscillator and a controlling circuit to stabilize unknown periodic orbits. Our proposed system generates various stabilized unknown Unstable Periodic Orbits which are embedded on the chaotic attractor of the original chaotic spiking oscillator. The proposed system is simple and exhibits various bifurcation phenomena. The dynamics of the system is governed by 1-D piecewise linear return map. Therefore, the rigorous analysis can be performed. We provide conditions for stability and almost complete analysis for bifurcation and co-existence phenomena by using the 1-D return map. An implementation example of the controlled chaotic spiking oscillator is provided to confirm some theoretical results.

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Given a sparse linear system, A x = b, we can solve the equivalent system P A P^T y = P b, x = P^T y, where P is a permutation matrix. It has been known that, for example, when P is the RCMK (Reverse Cuthill-Mckee) ordering permutation, the convergence rate of the Krylov subspace method combined with the ILU-type preconditioner is often enhanced, especially if the matrix A is highly nonsymmetric. In this paper we offer a reordering heuristic for accelerating the solution of large sparse linear systems by the Krylov subspace methods with the ILUT preconditioner. It is the LRB (Line Red/Black) ordering based on the well-known 2-point Red-Black ordering. We show that for some model-like PDE (partial differential equation)s the LRB ordered FDM (Finite Difference Method)/FEM (Finite Element Method) discretization matrices require much less fill-ins in the ILUT factorizations than those of the Natural ordering and the RCMK ordering and hence, produces a more accurate preconditioner, if a high level of fill-in is used. It implies that the LRB ordering could outperform the other two orderings combined with the ILUT preconditioned Krylov subspace method if the level of fill-in is high enough. We compare the performance of our heuristic with that of the RCMK (Reverse Cuthill-McKee) ordering. Our test matrices are obtained from various standard discretizations of two-dimensional and three-dimensional model-like PDEs on structured grids by the FDM or the FEM. We claim that for the resulting matrices the performance of our reordering strategy for the Krylov subspace method combined with the ILUT preconditioner is superior to that of RCMK ordering, when the proper number of fill-in was used for the ILUT. Also, while the RCMK ordering is known to have little advantage over the Natural ordering in the case of symmetric matrices, the LRB ordering still can improve the convergence rate, even if the matrices are symmetric.

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This paper proposes a new method to numerically obtain Floquet multipliers which characterize stability of periodic orbits of ordinary differential equations. For sufficiently smooth periodic orbits, we can compute Floquet multipliers using some standard numerical methods with enough accuracy. However, it has been reported that these methods may produce incorrect results under some conditions. In this work, we propose a new iterative method to compute Floquet multipliers using eigenvectors of matrix solutions of the variational equations. Numerical examples show effectiveness of the proposed method.

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A novel adaptive reputation-based virtual organization formation is proposed. It restrains the bad performers effectively based on the consideration of the global experience of the evaluator and evaluates the direct trust relation between two grid nodes accurately by consulting the previous trust value rationally. It also consults and improves the reputation evaluation process in PathTrust model by taking account of the inter-organizational trust relationship and combines it with direct and recommended trust in a weighted way, which makes the algorithm more robust against collusion attacks. Additionally, the proposed algorithm considers the perspective of the VO creator and takes required VO services as one of the most important fine-grained evaluation criterion, which makes the algorithm more suitable for constructing VOs in grid environments that include autonomous organizations. Simulation results show that our algorithm restrains the bad performers and resists against fake transaction attacks and badmouth attacks effectively. It provides a clear advantage in the design of a VO infrastructure.

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Linear cryptanalysis using sieve methods is a technique proposed by Takeda et al. in 1998 as an attack capable of breaking ciphers with smaller amounts of data than linear cryptanalysis (LC) by using data that satisfies linear sieve conditions. This paper shows that when considering the amount of data required for cryptanalysis in Takeda et al.'s proposed sieved linear cryptanalysis (S-LC), it is necessary to take into account the independence of keys relating to the linear mask (Linear key) and keys relating to the linear sieve mask (Sieve key) in rounds that are affected by these keys. If p is the probability that the linear approximate expression holds and p^* is the probability after applying the linear sieve, then it has been shown that when the Linear keys are independent of the Sieve keys, then it is necessary to select the linear mask and linear sieve mask so that a larger value of p^* - p is obtained. It is also shown that the amount of data needed for S-LC cannot be reduced below the amount of data needed for LC when the Linear key and Sieve key are not independent. In fixed sieve linear cryptanalysis, it is shown that the amount of data needed for cryptanalysis cannot be reduced regardless of the independence of the Linear key and Sieve key.

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In direct communication, terminals that are close to each other can communicate directly without traffic going through centralized controller such as a base station (BS). This brings several advantages. We study direct communication with localized distribution, so that users tend to gather around some areas (clusters/hot-spots) within the cell such as buildings. Previous analysis about clustering has focused on one dimensional scenarios. Here we present theoretical analysis of direct communication with two dimensional clustering. Additional analysis is presented for direct communication with correlated clusters. With correlated clusters some pairs of source and destination clusters are more probable than other pairs. According to our best knowledge, this is the first time that theoretical analysis is presented about clustering and correlated clusters in two dimensional scenarios. Simulations confirm the validity of the analysis. In addition to the exact results, we also suggest using the point-based approximation to rapidly and easily obtain results. The numerical results show that the gains from direct communication, in terms of blocking probability and carried traffic, depend on the offered traffic. Additionally, correlation in cluster selection is shown to significantly improve performance. Point-based approximation is shown to be very useful when the number of clusters is large.

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In this letter, we propose new digital audio watermarking methods using interval wavelet decomposition. We develop not only non-blind type method, but also blind one. Experimental results demonstrate that the proposed methods give a watermarked audio clip of better quality and are robust against some attacks.

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Ant colony optimization (ACO) algorithms are a recently developed, population-based approach which has been successfully applied to optimization problems. However, in the ACO algorithms it is difficult to adjust the balance between intensification and diversification and thus the performance is not always very well. In this work, we propose an improved ACO algorithm in which some of ants can evolve by performing genetic operation, and the balance between intensification and diversification can be adjusted by numbers of ants which perform genetic operation. The proposed algorithm is tested by simulating the Traveling Salesman Problem (TSP). Experimental studies show that the proposed ACO algorithm with genetic operation has superior performance when compared to other existing ACO algorithms.

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Almost all the existing secret sharing schemes are based on a single dealer. Maybe in some situations, the secret needs to be maintained by multiple dealers. In this paper, we proposed a novel secret sharing scheme based on the multi-dealer by means of Shamir's threshold scheme and T. Okamoto and S. Uchiyama's public-key cryptosystem. Multiple dealers can commonly maintain the secret and the secret can be dynamically renewed by any dealer. Meanwhile, the reusable secret shadows just needs to be distributed only once. In the secret updated phase, the dealer just needs to publish a little public information instead of redistributing the new secret shadows. Its security is based on the security of Shamir's threshold scheme and the intractability of factoring problem and discrete logarithm problem.

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The Chikazawa-Yamagishi scheme is an ID-based key distribution scheme which is based on the RSA cryptosystem. There are several variant schemes to improve the efficiency and the security of the Chikazawa-Yamagishi scheme. Unfortunately, all of the proposed schemes have some weaknesses. First, all the proposed schemes require time synchronization of the communicating parties. Second, none of the proposed schemes provide both forward secrecy and security against session state reveal attacks. In this paper, we suggest an ID-based key distribution scheme which does not require time synchronization and provides both forward secrecy and security against session state reveal attacks.

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In order to improve the synchronization performance of the OFDM-based FM broadcasting system, this letter addresses the problem of delay selection when the system uses a cyclic delay diversity (CDD) scheme. By proper selection of the amount of cyclic delay, an improved fine carrier frequency offset estimator is derived. By computer simulation, the proposed estimator is shown to benefit from properly chosen delay parameter and perform robustly.

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In this letter, a new Inter lossless coding method based on a residual DPCM (Differential Pulse Code Modulation) is proposed to improve compression ratio in the H.264 standard. Since the spatial correlation in a residual block can be further exploited among the residual signals after motion estimation/compensation, horizontal or vertical DPCM in the residual signals can be applied to further reduce the magnitudes of the residual signals. The proposed method reduces the average bitrates of 3.5% compared with the Inter lossless coding of the H.264 standard.

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This paper proposes a novel RBF training algorithm based on immune operations for dynamic problem solving. The algorithm takes inspiration from the dynamic nature of natural immune system and locally-tuned structure of RBF neural network. Through immune operations of vaccination and immune response, the RBF network can dynamically adapt to environments according to changes in the training set. Simulation results demonstrate that RBF equalizer based on the proposed algorithm obtains good performance in nonlinear time-varying channels.

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