A mesh-connected processor array consists of many similar processing elements (PEs), which can be executed in both parallel and pipeline processing. For the implementation of an array of large numbers of processors, it is necessary to consider some fault tolerant issues to enhance the (fabrication-time) yield and the (run-time) reliability. In this paper, we introduce the 1(1/2)-track switch torus array by changing the connections in 1(1/2)-track switch mesh array, and we apply our approximate reconfiguration algorithm to the torus array. We describe the reconfiguration strategy for the 1(1/2)-track switch torus array and its realization using WSI, especially 3-dimensional realization. A hardware realization of the algorithm is proposed and simulation results about the array reliability are shown. These imply that a self-reconfigurable system with no host computer can be realized using our method, hence our method is effective in enhancing the run-time reliability as well as the fabrication-time yield of processor arrays.

We consider the problem of reconstructing architectural scenes from multiple photographs taken from arbitrary viewpoints. The original contribution is the use of a map as a source of geometric constraints to obtain in a fast and simple way a detailed model of a scene. We suppose that images are uncalibrated and have at least one planar structure as a faade for exploiting the planar homography induced between world plane and image to calculate a first estimation of the projection matrix. Estimations are improved by using correspondences between images and map. We show how these simple constraints can be used to calibrate the cameras and recover the projection matrices for each viewpoint. Finally, triangulation is used to recover 3D models of the scene and to visualise new viewpoints. Our approach needs minimal a priori information about the camera being used. A working system has been designed and implemented to allow the user to interactively build a model from uncalibrated images from arbitrary viewpoints and a simple map.

This paper proposes a linear algorithm for metric reconstruction from projective reconstruction. Metric reconstruction problem is equivalent to estimating the projective transformation matrix that converts projective reconstruction to Euclidean reconstruction. We build a quadratic form from dual absolute conic projection equation with respect to the elements of the transformation matrix. The matrix of quadratic form of rank 2 is then eigen-decomposed to produce a linear estimate. The algorithm is applied to three different sets of real data and the results show a feasibility of the algorithm. Additionally, our comparison of results of the linear algorithm to results of bundle adjustment, applied to sets of synthetic image data having Gaussian image noise, shows reasonable error ranges.

In this letter, we describe the conditions for measuring the nonlinear refractive index n2 when using the self-phase modulation-based cw dual-frequency method. We clarify the appropriate measurement conditions for dispersion-shifted and conventional single-mode fibers both numerically and experimentally. We also show experimentally that the evaluated n2 values for conventional single-mode fiber depend on the signal wavelength separation.

In this paper, a discrete-time convergence theorem for continuous-state Hopfield networks with self-interaction neurons is proposed. This theorem differs from the previous work by Wang in that the original updating rule is maintained while the network is still guaranteed to monotonically decrease to a stable state. The relationship between the parameters in a typical class of energy functions is also investigated, and consequently a "guided trial-and-error" technique is proposed to determine the parameter values. The third problem discussed in this paper is the post-processing of outputs, which turns out to be rather important even though it never attracts enough attention. The effectiveness of all the theorems and post-processing methods proposed in this paper is demonstrated by a large number of computer simulations on the assignment problem and the N-queen problem of different sizes.

This paper describes the adaptability of communication software through a biologically-inspired policy coordination. Many research efforts have developed adaptable systems that allow various users or applications to meet their specific requirements by configuring different design and optimization policies. Navigating through many policies manually, however, is tedious and error-prone. Developers face the significant manual and ad-hoc work of engineering an system. In contrast, we propose to provide autonomous adaptability in communication endsystem with OpenWebServer/iNexus, which is both a web server and an object-oriented framework to tailer various web services and applications. The OpenWebServer's modular architecture allows to abstract and maintain a wide range of aspects in a HTTP server, and reconfigure the system by adding, deleting, changing, or replacing their policies. iNexus is a tool for automated policy-based management of OpenWebServer. Its design is inspired by the natural immune system, particularly immune network, a truly autonomous decentralized system. iNexus inspects the current system condition of OpenWebServer periodically, measures the delivered quality of service, and selects suitable set of policies to reconfigure the system dynamically by relaxing constraints between them. The policy coordination process is performed through decentralized interactions among policies without a single point of control, as the natural immune system does. This paper discusses communication software can evolve continuously in the piecemeal way with biological concepts and mechanisms, adapting itself to ever-changing environment.

We have developed a novel self-alignment process using the surface tension of the liquid resin for assembly of electronic or optoelectronic devices. Though the liquid resins have a characteristics as low as one tenth of the surface tension of solder in general, restoring forces for self-alignment capability can be produced by making it constrained on the 3-dimensional pads on chip and substrate. In this paper, its principle and characteristics are described and the relationship between process parameters and joint geometry were examined. And the possibility of self-alignment process was verified by analytic numerical method and scaled-up experiment. A self-alignment accuracy was examined experimentally and show that it became less than 0.4 µm. It can provide a useful information on various parameters involved in joint geometry and optimal design guideline to generate the proper profiles.

This paper proposes an automatic dispersion equalization system using extracted clock power monitoring in order to facilitate the field installation of high-speed time-division multiplexed (TDM) systems over existing fiber cables. The proposed scheme adjusts the dispersion of a variable-dispersion equalizer so as to maximize the extracted clock power level. This scheme has a simple configuration, needs no communication channel between the transmitter and the receiver, and is sensitive to parameters such as initial chirping and fiber input power. The clock power dependence on the fiber dispersion is theoretically analyzed assuming that the return-to-zero (RZ) format is used and that pulse broadening is small compared to the bit duration. We show that the clock power is maximized when the dispersion-induced waveform distortion is minimized. Numerical simulations show that the proposed scheme is effective with the non-return-to-zero (NRZ) format and for the case that the optimum total dispersion deviates from zero due to initial and/or self-phase modulation (SPM)-induced chirping. The operation of the proposed automatic equalization system is experimentally confirmed in 20-Gbit/s transmission using both RZ and NRZ formats. Moreover, a 40-Gbit/s transmission experiment over 200 km of dispersion-shifted fiber (DSF) is successfully demonstrated using the proposed equalization scheme.

A signal suffers from nonlinear, linear, and additive distortion when transmitted through a channel. Linear equalizers are commonly used in receivers to compensate for linear channel distortion. As an alternative, novel equalizer structures utilizing neural computation have been developed for compensating for nonlinear channel distortion. In this paper, we propose a neural detector based on self-organizing map (SOM) in a 16 QAM system. The proposed scheme uses the SOM algorithm and symbol-by-symbol detector to form a neural detector, and it adapts well to the changing channel conditions, including nonlinear distortions because of the topology-preserving property of the SOM algorithm. According to the theoretical analysis and computer simulation results, the proposed scheme is shown to have better performance than traditional linear equalizer when facing with nonlinear distortion.

A self-similar behavior characterizes the traffic in many real-world communication networks. This traffic is traditionally modeled as an ON/OFF discrete-time second-order self-similar random process. The self-similar processes are identified by means of a polynomially decaying trend of the autocovariance function. In this work we concentrate on two criteria to build a chaotic system able to generate self-similar trajectories. The first criterion relates self-similarity with the polynomially decaying trend of the autocovariance function. The second one relates self-similarity with the heavy-tailedness of the distributions of the sojourn times in the ON and/or OFF states. A family of discrete-time chaotic systems is then devised among the countable piecewise affine Pseudo-Markov maps. These maps can be constructed so that the quantization of their trajectories emulates traffic processes with different Hurst parameters and average load. Some simulations are reported showing how, according to the theory, the map design is able to fit those specifications.

We study a class of nonlinear dynamical systems to develop efficient algorithms. As an efficient algorithm, interior point method based on Newton's method is well-known for solving convex programming problems which include linear, quadratic, semidefinite and lp-programming problems. On the other hand, the geodesic of information geometry is represented by a continuous Newton's method for minimizing a convex function called divergence. Thus, we discuss a relation between information geometry and convex programming in a related family of continuous Newton's method. In particular, we consider the α-projection problem from a given data onto an information geometric submanifold spanned with power-functions. In general, an information geometric structure can be induced from a standard convex programming problem. In contrast, the correspondence from information geometry to convex programming is slightly complicated. We first present there exists a same structure between the α-projection and semidefinite programming problems. The structure is based on the linearities or autoparallelisms in the function space and the space of matrices, respectively. However, the α-projection problem is not a form of convex programming. Thus, we reformulate it to a lp-programming and the related ones. For the reformulated problems, we derive self-concordant barrier functions according to the values of α. The existence of a polynomial time algorithm is theoretically confirmed for the problem. Furthermore, we present the coincidence with the gradient vectors for the divergence and a modified barrier function. These results connect a part of nonlinear and algorithm theories by the discreteness of variables.

A halftoning technique that uses a simple GA has proven to be very effective to generate high quality halftone images. Recently, the two major drawbacks of this conventional halftoning technique with GAs, i.e. it uses a substantial amount of computer memory and processing time, have been overcome by using an improved GA (GA-SRM) that applies genetic operators in parallel putting them in a cooperative-competitive stand with each other. The halftoning problem is a true multiobjective optimization problem. However, so far, the GA based halftoning techniques have treated the problem as a single objective optimization problem. In this work, the improved GA-SRM is extended to a multiobjective optimization GA to simultaneously generate halftone images with various combinations of gray level precision and spatial resolution. Simulation results verify that the proposed scheme can effectively generate several high quality images simultaneously in a single run reducing even further the overall processing time.

Detection of nonlinearly distorted signals is an essential problem in telecommunications. Recently, neural network combined conventional equalizer has been used to improve the performance especially in compensating for nonlinear distortions. In this paper, the self-organizing map (SOM) combined with the conventional symbol-by-symbol detector is used as an adaptive detector after the output of the decision feedback equalizer (DFE), which updates the decision levels to follow up the nonlinear distortions. In the proposed scheme, we use the box distance to define the neighborhood of the winning neuron of the SOM algorithm. The error performance has been investigated in both 16 QAM and 64 QAM systems with nonlinear distortions. Simulation results have shown that the system performance is remarkably improved by using SOM detector compared with the conventional DFE scheme.

It has been reported that IP packet traffic exhibits the self-similar nature and causes the degradation of network performance. Therefore it is crucial for the appropriate buffer design of routers and switches to predict the queueing behavior with self-similar input. It is well known that the fitting methods based on the second-order statistics of counts for the arrival process are not sufficient for predicting the performance of the queueing system with self-similar input. However recent studies have revealed that the loss probability of finite queuing system can be well approximated by the Markovian input models. This paper studies the time-scale impact on the loss probability of MMPP/D/1/K system where the MMPP is generated so as to match the variance of the self-similar process over specified time-scales. We investigate the loss probability in terms of system size, Hurst parameters and time-scales. We also compare the loss probability of resulting MMPP/D/1/K with simulation. Numerical results show that the loss probability of MMPP/D/1/K are not significantly affected by time-scale and that the loss probability is well approximated with resulting MMPP/D/1/K.

PID control schemes based on the classical control theory, have been widely used for various real control systems. However, in practice, since it is considerably difficult to determine the PID parameters suitably, lots of researches have been reported with respect to tuning schemes of PID parameters. Furthermore, several self-tuning and auto-tuning techniques in the PID control have been reported for systems with unknown or slowly time-varying parameters. On the other hand, so-called a generalized predictive control (GPC) scheme has been reported as a useful self-tuning control technique for unknown and/or time variant delay systems. In this paper, a new self-tuning predictive PID control algorithm based on a GPC criterion is proposed.

This paper proposes a λ-ring system that is a wavelength-based self-healing-ring application unlike ordinary fiber-based ones. To design survivable networks of interconnected such self-healing ring systems, a virtual mesh network scheme is used, in which wavelength assignment in virtual links can be considered according to the λ-ring-system or fiber-ring-system applications of the bidirectional wavelength-path switched architecture. Integer-programming-based design problems are then formulated that minimize the total fiber length in these self-healing-ring applications. Numerical examples show that the λ-ring-system application is always superior to 4-fiber and 2-fiber-ring-system applications and 1+1 end-to-end path protection.

This paper is concerned with a comparative study of the accepting powers of deterministic, Las Vegas, self-verifying nondeterminisic, and nondeterministic (simple) multihead finite automata. We show that (1) for each k 2, one-way deterministic k-head (resp., simple k-head) finite automata are less powerful than one-way Las Vegas k-head (resp., simple k-head) finite automata, (2) there is a language accepted by a one-way self-verifying nondeterministic simple 2-head finite automaton, but not accepted by any one-way deterministic simple multihead finite automaton, (3) there is a language accepted by a one-way nondeterministic 2-head (resp., simple 2-head) finite automaton, but not accepted by any one-way self-verifying nondeterministic multihead (resp., simple multihead) finite automaton, (4) for each k 1, two-way Las Vegas k-head (resp., simple k-head) finite automata have the same accepting powers as two-way self-verifying nondeterministic k-head (resp., simple k-head) finite automata, and (5) two-way Las Vegas simple 2-head finite automata are more powerful than two-way deterministic simple 2-head finite automata.

Recent studies on traffic measurement analysis in the various networks (LAN, MAN, WAN) have shown that packet traffic exhibits Self-Similarity. The packet traffic represents some behavior quite different from what it has been assumed. Some papers reported that Self-Similarity degrades the network performance, such as buffer overflow and network congestion. Thus, we need new network control scheme considering Self-Similar properties. The control scheme requires high-speed calculation method of Hurst Parameter. In this paper, we propose high-speed calculation method of Hurst Parameter based on the Variance-Time Plot method, and show its performance. Furthermore, we try to apply this method to the simple network control, in order to show effectiveness of the network control with Self-Similarity.

We propose middleware which works on widely-used commercial off-the-shelf platforms (UDP/IP, FastEthernet, and Windows NT or commercial real-time kernels) to realize real-time distributed services for plant monitoring and control systems. It is not suitable to use TCP/IP for the systems because of its unpredictable re-transmission, while, as well known, UDP/IP does not guarantee certain arrivals of packets and it is also not acceptable for the systems. With UDP/IP, packets are lost mainly because of collisions in a network and buffer overflows. To avoid these packet losses, the middleware controls scheduling of all the packets transmitted between the nodes in a distributed system and prevents excessive collisions and buffer overflows. The middleware provides a necessary set of functions for plant monitoring and control applications. The middleware on each node in a distributed system consists of library functions and run-time modules. An application program on the node is required to use these library functions according to the rules the middleware provides. In this way the middleware can manage all the traffic among the nodes in the system. Receiving requests from the application via library functions, the run-time module of the middleware schedules transmission of messages to other nodes, avoiding unexpected delivery delays or buffer overflows. The module also guarantees application-to-application quality of service (QoS), such as transmission period and delivery deadline, required by the applications. This is achieved by assigning the resources not shared by other services to each distributed service and scheduling these resources so as not to violate the assignment. Here, resources include maximum numbers of packets which a node can receive or send in a specific period (20 msec, for example). We show implementation of the middleware to make it clear how to guarantee application-to-application QoS with some application examples.

We have developed a signal processing method that is appropriate for detecting electromagnetic radiation due to earthquake activities. The radiation is usually accompanied by a background noise that is mainly caused by atmospheric discharges in the tropical regions. Data representing the seismic radiation is presented as sound via the concept of sonification. This is useful for immediately finding out anomalous seismic radiations, which are often followed by a disastrous earthquake, from the massive data collected from over forty observation stations. It is illustrated that the auditory display is valuable for future earthquake prediction systems.