It is known that Boolean functions used in stream ciphers should have good cryptographic properties to resist fast algebraic attacks. In this paper, we study a new class of Boolean functions with good cryptographic properties: balancedness, optimum algebraic degree, optimum algebraic immunity and a high nonlinearity.

The ratio of two probability densities is called the importance and its estimation has gathered a great deal of attention these days since the importance can be used for various data processing purposes. In this paper, we propose a new importance estimation method using Gaussian mixture models (GMMs). Our method is an extention of the Kullback-Leibler importance estimation procedure (KLIEP), an importance estimation method using linear or kernel models. An advantage of GMMs is that covariance matrices can also be learned through an expectation-maximization procedure, so the proposed method--which we call the Gaussian mixture KLIEP (GM-KLIEP)--is expected to work well when the true importance function has high correlation. Through experiments, we show the validity of the proposed approach.

Compiler is the most important supporting tool to facilitate the use of reconfigurable computing architecture (RCA). In this paper, a template-based compiler framework is proposed. This compiler can synthesize the executables for RCA from native high-level programming language source code directly. It supports to generate run-time dynamic configuration context. And it is capable to generate both full configuration context and partial configuration context. Experimental results show that the executables generated by the proposed compiler can achieve better execution performance and smaller configuration context size than previous compilers. Moreover, this compiler does not require the programmer to have any extra knowledge about the hardware architecture of RCA.

In the modern day, MPEG-4 image compression technique have been commonly applied in various indoor wireless communication systems. The efficient system design mostly relies on the joint source channel coding algorithms, which aim to reduce the complexity of channel coding process, while maintaining the quality of the receiving images. In this paper, we design the MAP source-controlled channel decoders with both random and semirandom interleavers for Rician slow flat block-fading channels. The MAP-Viterbi decoder employs the residual redundancy from zerotree symbol sequences of MPEG-4 HFS packets. The interleaving processes are done after the overall channel coding process to combat the block-fading effects. The computer simulations summarize the system performance in terms of average WER and PSNR (dB). With the interleavers, the significant improvement in PSNR of about 15-17 dB is obtained for both ML and MAP decoding. Also in many cases, we obtain more improvement of about 0.2-0.4 dB for using MAP decoding with the interleavers.

Networking technologies have recently been evolving and network applications are now expected to support flexible composition of upper-layer network services, such as security, QoS, or personal firewall. We propose a multi-platform framework called FreeNA* that extends existing applications by incorporating the services based on user definitions. This extension does not require users to modify their systems at all. Therefore, FreeNA is valuable for experimental system usage. We implemented FreeNA on both Linux and Microsoft Windows operating systems, and evaluated their functionality and performance. In this paper, we describe the design and implementation of FreeNA including details on how to insert network services into existing applications and how to create services in a multi-platform environment. We also give an example implementation of a service with SSL, a functionality comparison with relevant systems, and our performance evaluation results. The results show that FreeNA offers finer configurability, composability, and usability than other similar systems. We also show that the throughput degradation of transparent service insertion is 2% at most compared with a method of directly inserting such services into applications.

When we design a robust vector quantizer (VQ) for noisy channels, an appropriate index assignment function should be contrived to minimize the channel-error effect. For relatively high rates, the complexity for finding an optimal index assignment function is too high to be implemented. To overcome such a problem, we use a structurally constrained VQ, which is called the sample-adaptive product quantizer (SAPQ) [12], for low complexities of quantization and index assignment. The product quantizer (PQ) and its variation SAPQ [13], which are based on the scalar quantizer (SQ) and thus belong to a class of the binary lattice VQ [16], have inherent error resilience even though the conventional affine index assignment functions, such as the natural binary code, are employed. The error resilience of SAPQ is observed in a weak sense through worst-case bounds. Using SAPQ for noisy channels is useful especially for high rates, e.g., > 1 bit/sample, and it is numerically shown that the channel-limit performance of SAPQ is comparable to that of the best codebook permutation of binary switching algorithm (BSA) [23]. Further, the PQ or SAPQ codebook with an affine index assignment function is used for the initial guess of the conventional clustering algorithm, and it is shown that the performance of the best BSA can be easily achieved.

In this letter we show that the dynamic optimal PCID allocation problem in LTE systems is NP-complete. Subsequently we provide a near-optimal solution using SON which models the problem using new merge operations and explores the search space using a suitable randomized algorithmic approach. Two feasible options for dynamic auto-configuration of the system are also discussed. Simulation results point out that the approach provides near-optimal auto-configuration of PCIDs in computationally feasible time.

In this paper, the vibration characteristics of stapes, driven by the implanted differential floating mass transducer (DFMT) in the human middle ear, are analyzed by using an electrical model. The electrical model has been simulated by using the PSpice, in which the simulated results are compared with the experimental results by using the fabricated DFMT and the human temporal bones.

This letter presents the optimal routing by the intermediate model; a construction that lies between the pipe and hose models. We show that it is a practical way of realizing optimal routing. A formulation extended from the pipe model to the intermediate model can not be solved as a regular linear programming (LP) problem. Our solution, the introduction of a duality theorem, successfully turns our problem into an LP formulation that can be easily solved. Numerical results show that the intermediate model has better routing performance than the hose model.

This paper clarifies the adequacy of the linear channel coding approach for Slepian-Wolf coding of individual sequences. A sufficient condition for ensembles of linear codes from which a universal Slepian-Wolf code can be constructed is given. Our result reveals that an ensemble of LDPC codes gives a universal code for Slepian-Wolf coding of individual sequences.

In this paper, an image restoration method using the Wiener filter is proposed. In order to bring the theory of the Wiener filter consistent with images that have spatially varying statistics, the proposed method adopts the locally adaptive Wiener filter (AWF) based on the universal Gaussian mixture distribution model (UNI-GMM) previously proposed for denoising. Applying the UNI-GMM-AWF for deconvolution problem, the proposed method employs the stationary Wiener filter (SWF) as a pre-filter. The SWF in the discrete cosine transform domain shrinks the blur point spread function and facilitates the modeling and filtering at the proceeding AWF. The SWF and UNI-GMM are learned using a generic training image set and the proposed method is tuned toward the image set. Simulation results are presented to demonstrate the effectiveness of the proposed method.

Decision diagrams (DDs) are data structures commonly used for representation of discrete functions with large number of variables. Binary DDs (BDDs) are used for representation and manipulation with Boolean functions. Complexity of a BDD is usually measured by its size, that is defined as the number of non-terminal nodes in the BDD. Minimization of the sizes of DDs is a problem greatly considered in literature and many related algorithms (exact and heuristic) have been proposed. However, there are many functions for which BDDs when minimized are still large and can have even an exponential size in the number of variables. An approach to derive compact decision diagram representations for such functions is transformation of BDDs into Multi-valued DDs (MDDs) and Heterogeneous MDDs (HMDDs). Complexity of MDDs and HMDDs is measured by the cost which is a generalization of the notion of the size by taking into account complexity of nodes in MDDs and HMDDs. This paper presents a method for transformation of BDD into HMDD with minimal cost. The proposed method reduces the time for determination of the type of nodes in HMDDs by introducing a matrix expressing dependency (interconnections) among nodes at different levels. Comparing to other methods for conversion of BDDs into HMDDs, the method reduces the number of traverses of a BDD necessary for collecting enough information to construct an equivalent HMDD. For an experimental verification of its efficiency, the method is applied to construction of HMDDs for some benchmark functions and their arithmetic and Walsh spectra.

In a Direct-Sequence/Spread-Spectrum (DS/SS) system, a RAKE receiver is used to improve a bit error rate (BER) performance. The RAKE receiver can collect more signal energy through independent paths and achieve path diversity. The RAKE receiver obtains further diversity gain through fractional sampling. However, the power consumption of the RAKE receiver increases in proportion to a sampling rate and does not always maximize the signal-to-noise ratio (SNR). Therefore, sampling rate selection schemes have been proposed to reduce the average sampling rate without degrading the BER. These schemes select the tap positions and the sampling rate depending on channel conditions and the power consumption can be reduced. In this paper, sampling rate selection schemes for the DS/SS system are investigated through an experiment since there have been no numerical results through an experiment. Numerical results show that the power consumption can be reduced even through the experiment without the degradation of the BER.

Boundary-based corner detection has been widely applied in spline curve fitting, automated optical inspection, image segmentation, object recognition, etc. In order to obtain good results, users usually need to adjust the length of region of support to resist zigzags due to quantization and random noise on digital boundaries. To automatically determine the length of region of support for corner detection, Teh-Chin and Guru-Dinesh presented adaptive approaches based on some local properties of boundary points. However, these local-property based approaches are sensitive to noise. In this paper, we propose a new approach to find the optimum length of region of support for corner detection based on a statistic discriminant criterion. Since our approach is based on the global perspective of all boundary points, rather than the local properties of some points, the experiments show that the determined length of region of support increases as the noise intensity strengthens. In addition, the detected corners based on the optimum length of region of support are consistent with human experts' judgment, even for noisy boundaries.

To enable fine-grained delegations for proxy re-encryption systems, in AsiaCCS'09, Weng et al.'s introduced the concept of conditional proxy re-encryption (C-PRE), in which the proxy can convert a ciphertext only if a specified condition is satisfied. Weng et al. also proposed a C-PRE scheme, and claimed that their scheme is secure against chosen-ciphertext attack (CCA). In this paper, we show that their scheme is not CCA-secure under their defined security model.

How to minimize the number of mirroring resources under a QoS constraint (resource minimization problem) is an important issue in content delivery networks. This paper proposes a novel approach that takes advantage of the parallelism of dynamically reconfigurable processors (DRPs) to solve the resource minimization problem, which is NP-hard. Our proposal obtains the optimal solution by running an exhaustive search algorithm suitable for DRP. Greedy algorithms, which have been widely studied for tackling the resource minimization problem, cannot always obtain the optimal solution. The proposed method is implemented on an actual DRP and in experiments reduces the execution time by a factor of 40 compared to the conventional exhaustive search algorithm on a Pentium 4 (2.8 GHz).

A method was developed for deriving the control input for a multi-dimensional discrete-time nonlinear system so that a performance index is approximately minimized. First, a moment vector equation (MVE) is derived; it is a multi-dimensional linear equation that approximates a nonlinear system in the whole domain of the system state and control input. Next, the performance index is approximated by using a quadratic form with respect to the moment vector. On the basis of the MVE and the quadratic form, an approximate optimal controller is derived by solving the linear quadratic optimal control problem. A bilinear optimal control problem and a mountain-car problem were solved using this method, and the solutions were nearly optimal.

Let us introduce n ( ≥ 2) mappings fi (i=1,,n ≡ 0) defined on reflexive real Banach spaces Xi-1 and let fi:Xi-1 → Yi be completely continuous on bounded convex closed subsets Xi-1(0) ⊂ Xi-1. Moreover, let us introduce n set-valued mappings Fi : Xi-1 Yi → Fc(Xi) (the family of all non-empty compact subsets of Xi), (i=1,,n ≡ 0). Here, we have a fixed point theorem in weak topology on the successively recurrent system of set-valued mapping equations:xi ∈ Fi(xi-1, fi(xi-1)), (i=1,,n ≡ 0). This theorem can be applied immediately to analysis of the availability of system of circular networks of channels undergone by uncertain fluctuations and to evaluation of the tolerability of behaviors of those systems.

The multiobjective route selection problem (m-RSP) is a key research topic in the car navigation system (CNS) for ITS (Intelligent Transportation System). In this paper, we propose an interactive multistage weight-based Dijkstra genetic algorithm (mwD-GA) to solve it. The purpose of the proposed approach is to create enough Pareto-optimal routes with good distribution for the car driver depending on his/her preference. At the same time, the routes can be recalculated according to the driver's preferences by the multistage framework proposed. In the solution approach proposed, the accurate route searching ability of the Dijkstra algorithm and the exploration ability of the Genetic algorithm (GA) are effectively combined together for solving the m-RSP problems. Solutions provided by the proposed approach are compared with the current research to show the effectiveness and practicability of the solution approach proposed.

Localization is an important problem for Wireless Sensor Networks (WSN). The localization method can be categorized as range-free or range-based schemes. Since sensor nodes are usually cheap and small, the range-based schemes that require range measurement unit are unsuitable in WSN. The DV-hop algorithm is one of the range-free localization algorithms in which average hop-distance and hop counts are used for range estimation. But it requires heavy communication cost if the number of nodes increases in the network. Therefore, we propose a simple algorithm to reduce the communication cost and its performance is verified via computer simulations.