Scientific computations for diffusion equations and ANNs (Artificial Neural Networks) are data intensive tasks accompanied by heavy memory access; on the other hand, their computational complexities are relatively low. Thus, this type of tasks naturally maps onto SIMD (Single Instruction Multiple Data stream) parallel processing with distributed memory. This paper proposes a high performance acceleration processor of which architecture is optimized for scientific computing using diffusion equations and ANNs. The proposed architecture includes a customized instruction set and specific hardware resources which consist of a control unit (CU), 16 processing units (PUs), and a non-linear function unit (NFU) on chip. They are effectively connected with dedicated ring and global bus structure. Each PU is equipped with an address modifier (AM) and 16-bit 1.5 k-word local memory (LM). The proposed processor can be easily expanded by multi-chip expansion mode to accommodate to a large scale parallel computation. The prototype chip is implemented with FPGA. The total gate count is about 1 million with 530, 432-bit embedded memory cells and it operates at 15 MHz. The functionality and performance of the proposed processor is verified with simulation of oil reservoir problem using diffusion equations and character recognition application using ANNs. The execution times of two applications are compared with software realizations on 1.7 GHz Pentium IV personal computer. Though the proposed processor architecture and the instruction set are optimized for diffusion equations and ANNs, it provides flexibility to program for many other scientific computation algorithms.

Recently, broadband access is widely spreading, and many broadband network E-commerce services are planned and developed. This article proposes a broadband online shop where a videoconferencing system is used to enable direct, face-to-face communication. It is important for a broadband online shop to understand what preference their customers want in order to provide them with more appropriate information. By using customer preferences, a salesclerk can have a serviceable conversation with few questions to his online customers. So, we are developing a visual Customer Relationship Management system (v-CRM system) that offers customer preferences to broadband network service such as broadband online shop. In this paper, we classify customer preferences, and describe three visualization methods that enable customer preferences to be intuitively understood quickly. We outline the v-CRM evaluation system and describe an experiment where we evaluated how accurately customer preferences can be recognized using these methods. The results show that v-CRM system is effective for understanding customer preferences.

Ultrahigh-speed all-optical label processing method is proposed and experimentally demonstrated. This processing method dramatically increases the label processing capability. Optical packet switch (OPS) systems and networks based on OPS nodes are applications of optical processing technologies. For the experiment, we constructed the world's first 40 Gbit/s/port OPS prototype with an all-optical label processor, optical switch, optical buffer, and electronic scheduler. Three-hop optical packet routing using OPS nodes was experimentally demonstrated with it, verifying the feasibility of OPS networks.

In this paper, Message Passing Interface (MPI) techniques are used to implement high-order full 3-D Navier-Stokes equations in multi-domain applications. A two-domain interface with five-point overlapping used previously is expanded to a multi-domain computation. There are normally two approaches for this expansion. One is to break up the domain into two parts through domain decomposition (say, one overlapping), then using MPI directives to further break up each domain into n parts. Another is to break the domain up into 2n parts with (2n-1) overlappings. In our present effort, the latter approach is used and finite-size overlappings are employed to exchange data between adjacent multi-dimensional sub-domains. It is an alternative way to parallelize the high-order full 3-D Navier-Stokes equations into multi-domain applications without adding much complexity. Results with high-order boundary treatments show consistency among multi-domain calculations and single-domain results.

This paper proposes a new type of relationship between layers in layered architecture and shows how to concretize the relationship between layers into design constraints. The meaning of layer relationship is explained with examples from design patterns and Microsoft COM. In addition, a prototype tool to check conformance is implemented and the architecture document of an open-source software project is checked against the actual architecture extracted from source code developed by many international developers. As a result of checking, parts that do not conform to the architecture document are investigated and it is pointed out that their modifications should be controlled with caution.

This paper proposes an algorithm for detecting 3-way interactions. As far as the authors know, this is the first proposal ever made for a detection algorithm of 3-way interactions. In this paper, by analyzing examples, the mechanism of 3-way interactions is clarified and a detection algorithm of 3-way interactions is proposed. Namely the proposed detection algorithm is heuristic. To evaluate the algorithm, we implemented a detection system based on the proposed algorithm and applied it to 12 services, and 82 3-way interactions were detected. This shows the proposed algorithm is effective.

In this paper, two efficient VLSI architectures for biorthogonal wavelet transform are proposed. One is constructed by the filter bank implementation and another is constructed by the lifting scheme. In the filter bank implementation, due to the symmetric property of biorthogonal wavelet transform, the proposed architecture uses fewer multipliers than the orthogonal wavelet transform. Besides, the polyphase decomposition is adopted to speed up the processing by a factor of 2. In the lifting scheme implementation, the pipeline-scheduling technique is employed to optimize the architecture. Both two architectures are with advantages of lower implementation complexity and higher throughput rate. Moreover, they can also be applied to realize the inverse DWT efficiently. Based on the above properties, the two architectures can be applied to time-critical image compressions, such as JPEG2000. Finally, the architecture constructed by the lifting scheme is implemented into a single chip on 0.35 µm 1P4M CMOS technology, and its area and working performance are 5.005 5.005 mm2 and 50 MHz, respectively.

Evaluation of cyclic transitions in the discrete-time neural networks with antisymmetric and circular interconnection weights has been derived in an asymptotic mathematical form. The type and the number of limit cycles generated by circular networks, in which each neuron is connected only to its nearest neurons, have been investigated through analytical method. The results show that the estimated numbers of state vectors generating n- or 2n-periodic limit cycles are an exponential function of (1.6)n for a large number of neuron, n. The sufficient conditions for state vectors to generate limit cycles of period n or 2n are also given.

In this paper we give the necessary and sufficient conditions for 2-dimensional discrete-time systems described by the signum function to be stable.

The number of customers of a service for Internet access from cellular phones in Japan has been explosively increasing for some time. We analyze the relation between the number of customers and the volume of traffic, with a view to finding clues to the structure of human relations among the very large set of potential customers of the service. The traffic data reveals that this structure is a scale-free network, and we calculate the exponent that governs the distribution of node degree in this network. The data also indicates that people who have many friends tend to subscribe to the service at an earlier stage. These results are useful for investigating various fields, including marketing strategies, the propagation of rumors, the spread of computer viruses, and so on.

The rapid down-scaling of minimum feature size in CMOS technologies has boosted the RF performance, thereby opening up the RF application area to CMOS. The concurrent reduction of supply voltage pushes the MOSFETs used in circuit design more and more into the moderate-inversion regime of operation. As a consequence, compact MOS models are needed that are accurate in all operating regimes, including the moderate-inversion regime. Advanced analogue applications require accurate modelling of distortion, capacitances and noise. RF application of MOSFETs require the extension of this accurate modelling up to high frequencies and in addition accurate modelling of impedance levels and power gain. The implications for compact MOS models will be discussed, together with the state-of-the-art in compact MOS modelling. Special attention will be paid to some well-known circuit examples, and the compact model requirements needed for a correct description. Where relevant MOS Model 11 will be used to illustrate the discussion.

Compact encodings of the web graph are required in order to keep the graph on the main memory and to perform operations on the graph efficiently. In this paper, we propose a new compact encoding of the web graph. It is 10% more compact than Link2 used in the Connectivity Server of Altavista and 20% more compact than the encoding proposed by Guillaume et al. in 2002 and is comparable to it in terms of extraction time.

In this work, a novel Multiple Valued Exclusive-Or Sum Of Products (MVESOP) minimization formulation is analyzed and an algorithm is presented that detects minimum MVESOP expressions when the weight of the function is less than eight. A heuristic MVESOP algorithm based on a novel cube transformation operation is then presented. Experimental results on MCNC benchmarks and randomly generated functions indicate that the algorithm matches or outperforms the quality of the state of the art in ESOP minimizers.

This paper presents recursive algorithms for the least mean-squared error linear filtering and fixed-interval smoothing estimators, from uncertain observations for the case of white and white plus coloured observation noises. The estimators are obtained by an innovation approach and do not use the state-space model, but only covariance information about the signal and the observation noises, as well as the probability that the signal exists in the observed values. Therefore the algorithms are applicable not only to signal processes that can be estimated by the conventional formulation using the state-space model but also to those for which a realization of the state-space model is not available. It is assumed that both the signal and the coloured noise autocovariance functions are expressed in a semi-degenerate kernel form. Since the semi-degenerate kernel is suitable for expressing autocovariance functions of non-stationary or stationary signal processes, the proposed estimators provide estimates of general signal processes.

This paper considers the least-squares linear estimation problem of signals from randomly delayed observations when the additive white noise is correlated with the signal. The delay values are treated as unknown variables, modelled by a binary white noise with values zero or one; these values indicate that the measurements arrive in time or they are delayed by one sampling time. A recursive one-stage prediction and filtering algorithm is obtained by an innovation approach and do not use the state-space model of the signal. It is assumed that both, the autocovariance functions of the signal and the crosscovariance function between the signal and the observation noise are expressed in a semi-degenerate kernel form; using this information and the delay probabilities, the estimators are recursively obtained.

This paper considers Quasi-Reduced ordered Multi-valued Decision Diagrams with k bits (QRMDD(k)s) to represent binary logic functions. Experimental results show relations between the values of k and the numbers of nodes, the memory sizes, the numbers of memory accesses, and area-time complexity for QRMDD(k). For many benchmark functions, the numbers of nodes and memory accesses for QRMDD(k)s are nearly equal to of the corresponding Quasi-Reduced ordered Binary Decision Diagrams (QRBDDs), and the memory sizes and the area-time complexities for QRMDD(k)s are minimum when k = 2 and k = 3-6, respectively.

General closed-form expressions are derived and analyzed for the exact bit error rate (BER) performance of the arbitrary rectangular Gray coded QAM signal in conjunction with maximal-ratio combining (MRC) diversity on frequency non-selective slow m-distributed Nakagami fading channel. The analyses consider four channel models, independent and identical, independent and nonidentical, identical but correlated, and arbitrary correlated fading. Numerical results demonstrate error performance improvement with the use of MRC diversity reception. The new expressions presented here are suitable for evaluating various cases of practical interest on wireless communication channels.

In this paper, we propose a simple and accurate transfer function model of the power amplifiers for mobile communications. Detail analysis yields a generalized model for AM/AM characteristics in classes AB, B, and C. The analysis includes the effect of drain current variation with input level variation. This model introduces a loadline variation ratio to indicate the change of drain current and to represent the operation classes in a small signal region. Further discussion leads to simplified approximate equations for the AM/AM characteristics, and the estimation procedures for the simplified model parameters. Using the derived procedures, an efficient power amplifier employing pseudomorphic high electron mobility transistor (PHEMT) is fabricated for the 2 GHz band. Finally, the various characteristics given by the model, simulator and measurements are compared and found to agree well in the range of 20 dB below the saturated output level. The model is very effective for characterizing the power amplifiers that are used in linear compensation techniques such as predistortion methods, due to its severe nonlinearity of AM/AM and AM/PM characteristics.

Service differentiation has been a subject of research for the past few years in the IETF; and in the current Internet, IP flows are mostly treated in a best-effort approach. However, for next generation networks it is expected that users would like to obtain service differentiation based on their preferences or profiles as well as the different types of multimedia they opt to receive or send. In addition, current Quality of Service (QoS) provisioning architectures have been designed mostly for the fixed networks without taking into consideration the wireless or radio links special requirements, such as low bandwidth availability, error prone communications, etc. In this paper we propose a QoS provisioning architecture for next generation networks that uses a hybrid approach to deal with both the wireless and wired (fixed) part of the network. For administering the scarce resource of the radio environment, we have developed a resource allocation algorithm based on micro-economic principles that uses associated piecewise linear utility functions which describe the benefit a user receives from the allocation of various amounts of resource. For the wired part of the network we have also developed a Core-Stateless Utility based Rate allocation Framework (SURF) for performing traffic policing where the flow's requirements are expressed using utility functions. The core routers maintain no per-flow state and implement a simple packet level admission control algorithm that is based on a threshold utility value that is computed dynamically. To tie in these two mechanisms, we developed a signaling mechanism that collect network statistics when a user starts a call and a QoS administrator entity (or Broker) perform the computations for allocating resources based on the information of available resources in the fixed and the wireless sections of the network. A comparison between the hybrid approach and the SURF approach to show the performance of the proposed architecture is presented later in the paper.

We propose adaptive variable-rate constant-power scheme for ad hoc wireless networks, employing the modification of Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) protocol. Potential improvements in throughput and back-off probability are presented for different system parameters.