This paper proposes a novel service configuration approach that can realize dynamic critical Quality of Service (QoS) adaptation to ever-changing and resource-limited ubiquitous computing environments. In the approach, service configuration is reduced to a Fuzzy Control System (FCS) which aims to achieve critical QoS variations on minimal level with less power cost. Two configuration strategies, service chain reconfiguration and QoS parameters adjustment, along with a configuration algorithm, are implemented to handle different types of QoS variations. A self-optimizing algorithm is designed to enhance the adaptation of the FCS. Simulation results validate the proposed approach.

This paper presents an FPGA implementation of highly modular universal discrete transforms. The implementation relies upon the unified discrete Fourier Hartley transform (UDFHT), based on which essential sinusoidal transforms including discrete Fourier transform (DFT), discrete Hartley transform (DHT), discrete cosine transform (DCT) and discrete sine transform (DST) can be realized. It employs a reconfigurable, scalable and modular architecture that consists of a memory-based FFT processor equipped with pre- and post-processing units. Besides, a pipelining technique is exploited to seamlessly harmonize the operation between each sub-module. Experimental results based on Xilinx Virtex-II Pro are given to examine the performance of the proposed UDFHT implementation. Two practical applications are also shown to demonstrate the flexibility and modularity of the proposed work.

Halo doping profile is used in nanoscale surrounding-gate MOSFETs to suppress short channel effect and improve current driving capability. Analytical surface potential and threshold voltage models are derived based on the analytical solution of Poisson's equation for the fully depleted symmetric and asymmetric halo-doped MOSFETs. The validity of the analytical models is verified using 3D numerical simulation. The performance of the halo-doped MOSFETs are studied and compared with the uniformly doped surrounding-gate MOSFETs. It is shown that the halo-doped channel can suppress threshold voltage roll-off and drain-induced barrier lowering, and improve carrier transport efficiency. The asymmetric halo structure is better in suppressing hot carrier effect than the symmetric halo structure.

In this letter, we propose a novel signal detection method, reduced complexity QRM-MLD, which achieves almost identical error performance to that of the conventional QRM-MLD while significantly reducing the computational complexity.

With the growth of wireless computing and the popularity of eXtensible Markup Language (XML), wireless XML data management is emerging as an important research area. In this paper, cache invalidation methodology with XML update is addressed in wireless computing environments. A family of XML cache invalidation strategies, called S-XIR, D-XIR and E-XIR, is suggested. Using S-XIR and D-XIR, the unchanged part of XML data, only its structure changes, can be effectively reused in client caching. E-XIR, which uses prefetching, can further improve access time. Simulations are carried out to evaluate the proposed methodology; they show that the proposed strategies improve both tuning time and access time significantly. In particular, the proposed strategies are on average about 4 to 12 times better than the previous approach in terms of tuning time.

For recent and future nanometer-technology VLSIs, static and dynamic delay variations become a serious problem. In many cases, the hold constraint, as well as the setup constraint, becomes critical for latching a correct signal under delay variations. This paper treats the hold constraint in a datapath circuit, and discusses a register assignment in high level synthesis considering delay variations. Our approach to ensure the hold constraint under delay variations is to enlarge the minimum-path delay between registers, which is called minimum-path delay compensation (MDC) in this paper. MDC can be done by inserting delay elements mainly in non-critical paths of a functional unit (FU). One of our contributions is to show that the minimization of the number of minimum-path delay compensated FUs is NP-hard in general, and it is in the class P if the number of FUs is a constant. A polynomial time algorithm for the latter is also shown in this paper. In addition, an integer linear programming (ILP) formulation is also presented. The proposed method generates a datapath having (1) robustness against delay variations, which is ensured partly by MDC technique and partly by SRV-based register assignment, and (2) the minimum possible numbers of MDCs and registers.

Complex bandpass ΔΣAD modulators can provide superior performance to a pair of real bandpass ΔΣAD modulators of the same order. They process just input I and Q signals, not image signals, and AD conversion can be realized with low power dissipation, so that they are desirable for such low-IF receiver applications. This paper proposes a new architecture for complex bandpass Δ ΣAD modulators with cross-noise-coupled topology, which effectively raises the order of the complex modulator and achieves higher SQNDR (Signal to Quantization Noise and Distortion Ratio) with low power dissipation. By providing the cross-coupled quantization noise injection to internal I and Q paths, noise coupling between two quantizers can be realized in complex form, which enhances the order of noise shaping in complex domain, and provides a higher-order NTF using a lower-order loop filter in the complex ΔΣAD modulator. Proposed higher-order modulator can be realized just by adding some passive capacitors and switches, the additional integrator circuit composed of an operational amplifier is not necessary, and the performance of the complex modulator can be effectively raised without more power dissipation. We have performed simulation with MATLAB to verify the effectiveness of the proposed architecture. The simulation results show that the proposed architecture can achieve the realization of higher-order enhancement, and improve SQNDR of the complex bandpass ΔΣAD modulator.

Recently, the appearance frequency of computer virus variants has increased. Updates to virus information using the normal pattern matching method are increasingly unable to keep up with the speed at which viruses occur, since it takes time to extract the characteristic patterns for each virus. Therefore, a rapid, automatic virus detection algorithm using static code analysis is necessary. However, recent computer viruses are almost always compressed and obfuscated. It is difficult to determine the characteristics of the binary code from the obfuscated computer viruses. Therefore, this paper proposes a method that unpacks compressed computer viruses automatically independent of the compression format. The proposed method unpacks the common compression formats accurately 80% of the time, while unknown compression formats can also be unpacked. The proposed method is effective against unknown viruses by combining it with the existing known virus detection system like Paul Graham's Bayesian Virus Filter etc.

A CMOS current-mode companding divider is presented. Currents of both dividend and divisor are compressed into log-domain. Then the logarithm current of divisor is subtracted from the logarithm current of dividend. After expanding the subtraction result, the division function could be achieved. The simulation results indicate that the proposed divider has with good performance at only 1.8 V supply voltage.

As a flexible, cost effective solution for a large-scale access network to the Internet, we have studied the design optimization of the Wireless Internet-access Mesh NETwork (WIMNET). WIMNET consists of multiple access points (APs) that have wireless links between them mainly on the wireless distribution system (WDS). In WIMNET, the links around the Internet gateway can be bottlenecks because every packet passes through it after multihop link activations. Besides, the link quality may be degraded by obstacles in indoor environments. Thus, the proper allocation of APs is essential in WIMNET, so that the communication quality should be ensured while the installation and management cost be minimized. In this paper, we formulate this AP allocation problem for indoor environments in WIMNET with the proof of the NP-completeness of its decision version. Then, we present its two-stage heuristic algorithm composed of the initial greedy allocation and the iterative improvement. The effectiveness of our proposal is verified through extensive simulations in three indoor environments.

In this letter, a low-cost weighted interpolation scheme (WIS) for deinterlacing within a single frame is discussed. Three useful weights measurements are introduced within the operation window to reduce false decisions on the basis of the LCID algorithm. The WIS algorithm has a simple weight-evaluating structure with low complexity, which therefore makes it easy to implement in hardware. Experimental results demonstrated that the WIS algorithm performs better than previous techniques.

It is a very important and intriguing problem in digital image-processing to decompose an input image into intuitively convincible image-components such as a structure component and a texture component, which is an inherently nonlinear problem. Recently, several numerical schemes to solve the nonlinear image-decomposition problem have been proposed. The use of the nonlinear image-decomposition as a pre-process of several image-processing tasks will possibly pave the way to solve difficult problems posed by the classic approach of digital image-processing. Since the new image-processing approach via the nonlinear image-decomposition treats each separated component with a processing method suitable to it, the approach will successfully attain target items seemingly contrary to each other, for instance invisibility of ringing artifacts and sharpness of edges and textures, which have not attained simultaneously by the classic image-processing approach. This paper reviews quite recently developed state-of-the-art schemes of the nonlinear image-decomposition, and introduces some examples of the decomposition-and-processing approach.

Nonnegative matrix factorization (NMF) and its extensions such as Nonnegative Tensor Factorization (NTF) have become prominent techniques for blind sources separation (BSS), analysis of image databases, data mining and other information retrieval and clustering applications. In this paper we propose a family of efficient algorithms for NMF/NTF, as well as sparse nonnegative coding and representation, that has many potential applications in computational neuroscience, multi-sensory processing, compressed sensing and multidimensional data analysis. We have developed a class of optimized local algorithms which are referred to as Hierarchical Alternating Least Squares (HALS) algorithms. For these purposes, we have performed sequential constrained minimization on a set of squared Euclidean distances. We then extend this approach to robust cost functions using the alpha and beta divergences and derive flexible update rules. Our algorithms are locally stable and work well for NMF-based blind source separation (BSS) not only for the over-determined case but also for an under-determined (over-complete) case (i.e., for a system which has less sensors than sources) if data are sufficiently sparse. The NMF learning rules are extended and generalized for N-th order nonnegative tensor factorization (NTF). Moreover, these algorithms can be tuned to different noise statistics by adjusting a single parameter. Extensive experimental results confirm the accuracy and computational performance of the developed algorithms, especially, with usage of multi-layer hierarchical NMF approach [3].

Optical burst switching (OBS) is a promising approach for the realization of future flexible high-speed optical networks. In particular, a multicast forwarding method for optical bursts is important if an efficient high-speed grid computing network is to be realized. In OBS networks, the number of burst replicas generated at each node is strongly restricted due to optical power impairment of multicast bursts. Moreover, unrestricted replication of multicast bursts at each OBS node may not be advantageous because an increase in the number of multicast bursts within the network causes more frequent deflection forwarding of both multicast and unicast bursts. This paper proposes an efficient hop-by-hop multicast forwarding method for optical bursts, where idle output ports are selected based on scores simply calculated using a routing table that each OBS node holds. This method can mitigate increases in loss rate and transfer delay of multicast bursts, even if the number of burst replicas generated at each OBS node is strongly restricted. Moreover, this method can efficiently mitigate an increase in the number of multicast bursts within the network by avoiding unnecessary replication of multicast bursts at each OBS node. Simulation results show that the proposed method can actually mitigate degradation of the loss rate and transfer delay for multicast bursts under the restricted number of burst replicas at each OBS node. Moreover, when the arrival rate of multicast bursts is large relative to that of unicast bursts, the proposed method is able to improve the loss rates of both multicast and unicast bursts by switching the forwarding method for the multicast bursts to the simple unicast forwarding method without burst replication.

A sound field reproduction method is proposed that uses blind source separation and a head-related transfer function. In the proposed system, multichannel acoustic signals captured at distant microphones are decomposed to a set of location/signal pairs of virtual sound sources based on frequency-domain independent component analysis. After estimating the locations and the signals of the virtual sources by convolving the controlled acoustic transfer functions with each signal, the spatial sound is constructed at the selected point. In experiments, a sound field made by six sound sources is captured using 48 distant microphones and decomposed into sets of virtual sound sources. Since subjective evaluation shows no significant difference between natural and reconstructed sound when six virtual sources and are used, the effectiveness of the decomposing algorithm as well as the virtual source representation are confirmed.

This paper shows that there is a fruitful world behind sampling theorems. For this purpose, the sampling problem is reformulated from a functional analytic standpoint, and is consequently revealed that the sampling problem is a kind of inverse problem. The sampling problem covers, for example, signal and image restoration including super resolution, image reconstruction from projections such as CT scanners in hospitals, and supervised learning such as learning in artificial neural networks. An optimal reconstruction operator is also given, providing the best approximation to an individual original signal without our knowing the original signal.

A desired property of large distributed systems is self adaptability against the faults that occur more frequently as the size of the distributed system grows. Self-stabilizing protocols provide autonomous recovery from finite number of transient faults. Fault-containing self-stabilizing protocols promise not only self-stabilization but also containment of faults (quick recovery and small effect) against small number of faults. However, existing composition techniques for self-stabilizing protocols (e.g. fair composition) cannot preserve the fault-containment property when composing fault-containing self-stabilizing protocols. In this paper, we present Recovery Waiting Fault-containing Composition (RWFC) framework that provides a composition of multiple fault-containing self-stabilizing protocols while preserving the fault-containment property of the source protocols.

An algorithm for blind signal separation (BSS) of convolutive mixtures is presented. In this algorithm, the BSS problem is treated as multidimensional independent component analysis (ICA) by introducing an extended signal vector which is composed of current and previous samples of signals. It is empirically known that a number of conventional ICA algorithms solve the multidimensional ICA problem up to permutation and scaling of signals. In this paper, we give theoretical justification for using any conventional ICA algorithm. Then, we discuss the remaining problems, i.e., permutation and scaling of signals. To solve the permutation problem, we propose a simple algorithm which classifies the signals obtained by a conventional ICA algorithm into mutually independent subsets by utilizing temporal structure of the signals. For the scaling problem, we prove that the method proposed by Koldovský and Tichavský is theoretically proper in respect of estimating filtered versions of source signals which are observed at sensors.

We identify a broadband equivalent circuit of an on-chip self-complementary antenna integrated with a µm-sized semiconductor mesa structure whose circuit elements can be interpreted by using closed-form analysis. Prior to the equivalent circuit analysis, an electromagnetic simulation is done to investigate frequency independency of the input impedance for the integrated self-complementary antenna in terahertz range.

In equational theorem proving, convergent term rewriting systems play a crucial role. In order to compute convergent term rewriting systems, the standard completion procedure (KB) was proposed by Knuth and Bendix and has been improved in various ways. The multi-completion system MKB developed by Kurihara and Kondo accepts as input a set of reduction orders in addition to equations and efficiently simulates parallel processes each of which executes the KB procedure with one of the given orderings. Wehrman and Stump also developed a new variant of completion procedure, constraint-based completion, in which reduction orders need not be given by using automated modern termination checkers. As a result, the constraint-based procedures simulate the execution of parallel KB processes in a sequential way, but naive search algorithms sometimes cause serious inefficiency when the number of the potential reduction orders is large. In this paper, we present a new procedure, called a constraint-based multi-completion procedure MKBcs, by augmenting the constraint-based completion with the framework of the multi-completion for suppressing the combinatorial explosion by sharing inferences among the processes. The existing constraint-based system SLOTHROP, which basically employs the best-first search, is more efficient when its built-in heuristics for process selection are appropriate, but when they are not, our system is more efficient. Therefore, both systems have their role to play.