Novel thermopiles based on modulation doped AlGaAs/InGaAs, AlGaN/GaN, and ZnMgO/ZnO heterostructures are proposed and designed for the first time, for uncooled infrared image sensor application. These devices are expected to offer high performances due to both the superior Seebeck coefficient and the excellently high mobility of 2DEG and 2DHG due to high purity channel layers at the heterojunction interface. The AlGaAs/InGaAs thermopile has the figure-of-merit Z of as large as 1.110-2/K (ZT = 3.3 over unity at T = 300 K), and can be realized with a high responsivity R of 15,200 V/W and a high detectivity D* of 1.8109 cmHz1/2/W with uncooled low-cost potentiality. The AlGaN/GaN and the ZnMgO/ZnO thermopiles have the advantages of high sheet carrier concentration due to their large polarization charge effects (spontaneous and piezo polarization charges) as well as of a high Seebeck coefficient due to their strong phonon-drag effect. The high speed response time τ of 0.9 ms with AlGaN/GaN, and also the lower cost with ZnMgO/ZnO thermopiles can be realized. The modulation-doped heterostructure thermopiles presented here are expected to be used for uncooled infrared image sensor applications, and for monolithic integrations with other photon detectors such as InGaAs, GaN, and ZnO PiN photodiodes, as well as HEMT functional integrated circuit devices.

Polar Fourier Descriptor(PFD) and Spherical Fourier Descriptor(SFD) are rotation invariant feature descriptors for two dimensional(2D) and three dimensional(3D) image retrieval and pattern recognition tasks. They are demonstrated to show superiorities compared with other methods on describing rotation invariant features of 2D and 3D images. However in order to increase the computation speed, fast computation method is needed especially for machine vision applications like realtime systems, limited computing environments and large image databases. This paper presents fast computation method for PFD and SFD that are deduced based on mathematical properties of trigonometric functions and associated Legendre polynomials. Proposed fast PFD and SFD are 8 and 16 times faster than direct calculation that significantly boost computation process. Furthermore, the proposed methods are also compact for memory requirements for storing PFD and SFD basis in lookup tables. The experimental results on both synthetic and real data are given to illustrate the efficiency of the proposed method.

This letter presents the globally optimal data replication in the distributed networks. We propose a distributed approach based on the metropolis-hastings algorithm to achieve the globally optimal data replication without requiring any global information. Experimental results show that the proposed approach works well and the error can be held below 0.6% easily.

This paper presents a high-speed, low-complexity VLSI architecture based on the modified Euclidean (ME) algorithm for Reed-Solomon decoders. The low-complexity feature of the proposed architecture is obtained by reformulating the error locator and error evaluator polynomials to remove redundant information in the ME algorithm proposed by Truong. This increases the hardware utilization of the processing elements used to solve the key equation and reduces hardware by 30.4%. The proposed architecture retains the high-speed feature of Truong's ME algorithm with a reduced latency, achieved by changing the initial settings of the design. Analytical results show that the proposed architecture has the smallest critical path delay, latency, and area-time complexity in comparison with similar studies. An example RS(255,239) decoder design, implemented using the TSMC 0.18 µm process, can reach a throughput rate of 3 Gbps at an operating frequency of 375 MHz and with a total gate count of 27,271.

We develop a novel construction method for n-dimensional Hilbert space-filling curves. The construction method includes four steps: block allocation, Gray permutation, coordinate transformation and recursive construction. We use the tensor product theory to formulate the method. An n-dimensional Hilbert space-filling curve of 2r elements on each dimension is specified as a permutation which rearranges 2rn data elements stored in the row major order as in C language or the column major order as in FORTRAN language to the order of traversing an n-dimensional Hilbert space-filling curve. The tensor product formulation of n-dimensional Hilbert space-filling curves uses stride permutation, reverse permutation, and Gray permutation. We present both recursive and iterative tensor product formulas of n-dimensional Hilbert space-filling curves. The tensor product formulas are directly translated into computer programs which can be used in various applications. The process of program generation is explained in the paper.

This research addresses a high-speed computation method for the Kleene star of the weighted adjacency matrix in a max-plus algebraic system. We focus on systems whose precedence constraints are represented by a directed acyclic graph and implement it on a Cell Broadband EngineTM (CBE) processor. Since the resulting matrix gives the longest travel times between two adjacent nodes, it is often utilized in scheduling problem solvers for a class of discrete event systems. This research, in particular, attempts to achieve a speedup by using two approaches: parallelization and SIMDization (Single Instruction, Multiple Data), both of which can be accomplished by a CBE processor. The former refers to a parallel computation using multiple cores, while the latter is a method whereby multiple elements are computed by a single instruction. Using the implementation on a Sony PlayStation 3TM equipped with a CBE processor, we found that the SIMDization is effective regardless of the system's size and the number of processor cores used. We also found that the scalability of using multiple cores is remarkable especially for systems with a large number of nodes. In a numerical experiment where the number of nodes is 2000, we achieved a speedup of 20 times compared with the method without the above techniques.

In this paper, a novel CMA (constant modulus algorithm) algorithm employing fast convolution in the DFT (discrete Fourier transform) domain is proposed. We propose a non-linear adaptation algorithm that minimizes CMA cost function in the DFT domain. The proposed algorithm is completely new one as compared to the recently introduced similar DFT domain CMA algorithm in that, the original CMA cost function has not been changed to develop DFT domain algorithm, resulting improved convergence properties. Using the proposed approach, we can reduce the number of multiplications to O(Nlog2 N), whereas the conventional CMA has the computation order of O(N2). Simulation results show that the proposed algorithm provides a comparable performance to the conventional CMA.

This paper discusses the issues involved in the design of a complete information retrieval system for DataSpace based on user relevance probabilistic schemes. First, Information Hidden Model (IHM) is constructed taking into account the users' perception of similarity between documents. The system accumulates feedback from the users and employs it to construct user oriented clusters. IHM allows integrating uncertainty over multiple, interdependent classifications and collectively determines the most likely global assignment. Second, Three different learning strategies are proposed, namely query-related UHH, UHB and UHS (User Hidden Habit, User Hidden Background, and User Hidden keyword Semantics) to closely represent the user mind. Finally, the probability ranking principle shows that optimum retrieval quality can be achieved under certain assumptions. An optimization algorithm to improve the effectiveness of the probabilistic process is developed. We first predict the data sources where the query results could be found. Therefor, compared with existing approaches, our precision of retrieval is better and do not depend on the size and the DataSpace heterogeneity.

In this paper, we studied the use of common-mode noise reduction technique for in-vehicle electronic equipment in an actual instrument design. We have improved the circuit model of the common-mode noise that flows to the wire harness to add the effect of a bypass capacitor located near the LSI. We analyzed the improved circuit model using a circuit simulator and verified the effectiveness of the noise reduction condition derived from the circuit model. It was also confirmed that offsetting the impedance mismatch in the PCB section requires to make a circuit constant larger than that necessary for doing the impedance mismatch in the LSI section. An evaluation circuit board comprising an automotive microcomputer was prototyped to experiment on the common-mode noise reduction effect of the board. The experimental results showed the noise reduction effect of the board. The experimental results also revealed that the degree of impedance mismatch in the LSI section can be estimated by using a PCB having a known impedance. We further inquired into the optimization of impedance parameters, which is difficult for actual products at present. To satisfy the noise reduction condition composed of numerous parameters, we proposed a design method using an optimization algorithm and an electromagnetic field simulator, and confirmed its effectiveness.

In this paper, we propose an optimization system with parallel processing for reducing electromagnetic interference (EMI) on electronic control unit (ECU). We adopt simulated annealing (SA), genetic algorithm (GA) and taboo search (TS) to seek optimal solutions, and a Spice-like circuit simulator to analyze common-mode current. Therefore, the proposed system can determine the adequate combinations of the parasitic inductance and capacitance values on printed circuit board (PCB) efficiently and practically, to reduce EMI caused by the common-mode current. Finally, we apply the proposed system to an example circuit to verify the validity and efficiency of the system.

This paper presents a fast method capable of accelerating the Smith-Waterman algorithm for biological database search on a cluster of graphics processing units (GPUs). Our method is implemented using compute unified device architecture (CUDA), which is available on the nVIDIA GPU. As compared with previous methods, our method has four major contributions. (1) The method efficiently uses on-chip shared memory to reduce the data amount being transferred between off-chip video memory and processing elements in the GPU. (2) It also reduces the number of data fetches by applying a data reuse technique to query and database sequences. (3) A pipelined method is also implemented to overlap GPU execution with database access. (4) Finally, a master/worker paradigm is employed to accelerate hundreds of database searches on a cluster system. In experiments, the peak performance on a GeForce GTX 280 card reaches 8.32 giga cell updates per second (GCUPS). We also find that our method reduces the amount of data fetches to 1/140, achieving approximately three times higher performance than a previous CUDA-based method. Our 32-node cluster version is approximately 28 times faster than a single GPU version. Furthermore, the effective performance reaches 75.6 giga instructions per second (GIPS) using 32 GeForce 8800 GTX cards.

Previously, we have proposed an access point (AP) allocation algorithm in indoor environments for the Wireless Internet-access Mesh NETwork (WIMNET) using one gateway (GW) to the Internet. WIMNET consists of multiple APs that are connected wirelessly mainly by the Wireless Distribution System (WDS), to expand the coverage area inexpensively and flexibly. In this paper, we present two extensions of this algorithm to enhance the applicability to the large-scale WIMNET. One is the multiple GW extension of the algorithm to increase the communication bandwidth with multiple GWs, where all the rooms in the network field are first partitioned into a set of disjoint GW clusters and then, our previous allocation algorithm is applied to each GW cluster sequentially. The APs in a GW cluster share the same GW. The other is the dependability extension to assure the network function by maintaining the connectivity and the host coverage, even if one link/AP fault occurs, where redundant APs are added to the AP allocation by our previous algorithm. The effectiveness of our proposal in terms of the number of APs and the throughput is verified through simulations using the WIMNET simulator.

Social bookmarking services have recently made it possible for us to register and share our own bookmarks on the web and are attracting attention. The services let us get structured data: (URL, Username, Timestamp, Tag Set). And these data represent user interest in web pages. The number of bookmarks is a barometer of web page value. Some web pages have many bookmarks, but most of those bookmarks may have been posted far in the past. Therefore, even if a web page has many bookmarks, their value is not guaranteed. If most of the bookmarks are very old, the page may be obsolete. In this paper, by focusing on the timestamp sequence of social bookmarkings on web pages, we model their activation levels representing current values. Further, we improve our previously proposed ranking method for web search by introducing the activation level concept. Finally, through experiments, we show effectiveness of the proposed ranking method.

There is evidence in favor of a relationship between the presence of 1/f noise and computational universality in cellular automata. To confirm the relationship, we search for two-dimensional cellular automata with a 1/f power spectrum by means of genetic algorithms. The power spectrum is calculated from the evolution of the state of the cell, starting from a random initial configuration. The fitness is estimated by the power spectrum with consideration of the spectral similarity to the 1/f spectrum. The result shows that the rule with the highest fitness over the most runs exhibits a 1/f type spectrum and its transition function and behavior are quite similar to those of the Game of Life, which is known to be a computationally universal cellular automaton. These results support the relationship between the presence of 1/f noise and computational universality.

Deploying and managing content objects efficiently is critical for building a scalable and transparent content delivery system. This paper investigates the advanced incremental deploying problem of which the objects are delivered in a successive manner. Recently, the researchers show that the minimum-cost content deployment can be obtained by reducing the problem to the well-known network flow problem. In this paper, the maximum flow algorithm for a single graph is extended to the incremental growing graph. Based on this extension, an efficient incremental content deployment algorithm is developed in this work.

The linear Piece In Hand (PH, for short) matrix method with random variables was proposed in our former work. It is a general prescription which can be applicable to any type of multivariate public-key cryptosystems for the purpose of enhancing their security. Actually, we showed, in an experimental manner, that the linear PH matrix method with random variables can certainly enhance the security of HFE against the Grobner basis attack, where HFE is one of the major variants of multivariate public-key cryptosystems. In 1998 Patarin, Goubin, and Courtois introduced the plus method as a general prescription which aims to enhance the security of any given MPKC, just like the linear PH matrix method with random variables. In this paper we prove the equivalence between the plus method and the primitive linear PH matrix method, which is introduced by our previous work to explain the notion of the PH matrix method in general in an illustrative manner and not for a practical use to enhance the security of any given MPKC. Based on this equivalence, we show that the linear PH matrix method with random variables has the substantial advantage over the plus method with respect to the security enhancement. In the linear PH matrix method with random variables, the three matrices, including the PH matrix, play a central role in the secret-key and public-key. In this paper, we clarify how to generate these matrices and thus present two probabilistic polynomial-time algorithms to generate these matrices. In particular, the second one has a concise form, and is obtained as a byproduct of the proof of the equivalence between the plus method and the primitive linear PH matrix method.

A Peer-To-Peer (P2P) application uses an overlay network which is a virtual network constructed over the physical network. Traditional overlay construction methods do not take physical location of nodes into consideration, resulting in a large amount of redundant traffic. Some proximity-aware construction methods have been proposed to address this problem. These methods typically connect nearby nodes in the physical network. However, as the number of nodes increases, the path length of a route between two distant nodes rapidly increases. To alleviate this problem, we propose a technique which can be incorporated in existing overlay construction methods. The idea behind this technique is to employ long links to directly connect distant nodes. Through simulation experiments, we show that using our proposed technique, networks can achieve small path length and low communication cost while maintaining high resiliency to failures.

Skyline query is very important because it is the basis of many applications, e.g., decision making, user-preference queries. Given an N-dimensional dataset D, a point p is said to dominate another point q if p is better than q in at least one dimension and equal to or better than q in the remaining dimensions. In this paper, we study a generalized problem of skyline query that, users are more interested in the details of the dominant relationship in a dataset, i.e., a point p dominates how many other points and whom they are. We show that the existing framework proposed in can not efficiently solve this problem. We find the interrelated connection between the partial order and the dominant relationship. Based on this discovery, we propose a new data structure, ParCube, which concisely represents the dominant relationship. We propose some effective strategies to construct ParCube. Extensive experiments illustrate the efficiency of our methods.

In this paper, a Stochastic Collocation Algorithm combined with Sparse Grid technique (SSCA) is proposed to deal with the periodic steady-state analysis for nonlinear systems with process variations. Compared to the existing approaches, SSCA has several considerable merits. Firstly, compared with the moment-matching parameterized model order reduction (PMOR) which equally treats the circuit response on process variables and frequency parameter by Taylor approximation, SSCA employs Homogeneous Chaos to capture the impact of process variations with exponential convergence rate and adopts Fourier series or Wavelet Bases to model the steady-state behavior in time domain. Secondly, contrary to Stochastic Galerkin Algorithm (SGA), which is efficient for stochastic linear system analysis, the complexity of SSCA is much smaller than that of SGA for nonlinear case. Thirdly, different from Efficient Collocation Method, the heuristic approach which may result in "Rank deficient problem" and "Runge phenomenon," Sparse Grid technique is developed to select the collocation points needed in SSCA in order to reduce the complexity while guaranteing the approximation accuracy. Furthermore, though SSCA is proposed for the stochastic nonlinear steady-state analysis, it can be applied to any other kind of nonlinear system simulation with process variations, such as transient analysis, etc.

A new adaptive algorithm is proposed by introducing some modifications to the recursive least squares (RLS) algorithm. Except for the noise variance, the proposed algorithm does not require any statistics or knowledge of the desired signal, thus, it is suitable for adaptive filtering for channel estimation in code division multiple access (CDMA) systems in cases where the standard RLS approach cannot be used. A theoretical analysis demonstrates the convergence of the proposed algorithm, and simulation results for CDMA channel estimation show that the proposed algorithm outperforms existing channel estimation schemes.