Effects of organic gases (1, 4-butanediol, n-hexane, phenol, and benzene) on the contact resistance (the electrical life and the mechanical life) and the sticking were evaluated. These effects were evaluated by using telecommunication relays from which the cases were removed. Contact materials were Au90Ag10(clad)/Ag40Pd60 (base). Test conditions were as follows: In the cases of the electrical life test and the mechanical life test: Load conditions: DC28 V, 100 mA and 0 V, 0 mA. Temperature: 85. Frequency: 5 Hz. Number of operations: 2,500,000 times. In the case of the sticking test: Load condition: DC96 V, 140 mA. Temperature: 50. Frequency: 5 Hz. Number of operations: 2,000,000 times. It was found that the electrical life was more than 2,500,000 times, the mechanical life was more than 2,500,000 times, and the sticking didnt occur in the case of 1, 4-butanediol. The electrical life was improved by adding 1, 4-butanediol to phenol and benzene, respectively.

As expert system technology gains wider acceptance in digital system design, the need to build and maintain a large scale knowledge base will assume greater importance. However, how to build a correct and efficient rule base is even a hard part in the knowledge-based system development. In this paper, we develop FARHDL (Frame-And-Rule-based Hardware Description Language) to form a knowledge base. The FARHDL is simple but powerful to specify the hardware requirements and can be directly simulated by PROLOG. Through the knowledge base transformed from FARHDL, a formal method can be developed to design, implement, and validate the digital hardware systems. Furthermore, behavioral properties, anomaly properties, structural properties, and timing properties are applied to analyze the requirements specification. The purposes of those properties are used to detect explicit/implicit incorrect specification clauses and to capture some desired requirements, such as completeness and consistency. Finally, the analysis results can be a useful tool for finding obscure problems in tricky digital system designs and can also aid in the development of formal specifications.

We discuss the uniqueness of 3-D shape reconstruction of a polyhedron from a single shading image. First, we analytically show that multiple convex (and concave) shape solutions usually exist for a simple polyhedron if interreflections are not considered. Then we propose a new approach to uniquely determine the concave shape solution using interreflections as a constraint. An example, in which two convex and two concave shapes were obtained from a single shaded image for a trihedral corner, has been given by Horn. However, how many solutions exist for a general polyhedron wasn't described. We analytically show that multiple convex (and concave) shape solutions usually exist for a pyramid using a reflectance map, if interreflection distribution is not considered. However, if interreflection distribution is used as a constraint that limits the shape solution for a concave polyhedron, the polyhedral shape can be uniquely determined. Interreflections, which were considered to be deleterious in conventional approaches, are used as a constraint to determine the shape solution in our approach.

The tape deformation due to such particles as wear debris and dust in the head/tape contact region is one of the main causes of the signal quality deterioration in magnetic tape devices. Thus it is significant to make clear the tape deformation due to a particle for realizing higher recording densities. This paper investigates the tape deformation profile generated by a particle through an interferometric experiment and a simulation using a point loaded tape model. A rather good agreement between them is obtained, thereby the simulation is verified appropriate to estimate the tape deformation due to a particle. This paper also describes the relationship between the spacing loss and the particle height, considering the tape deformation profile obtained from the simulation. In addition, the influence of the particle height on the width of the tape deformed area is estimated, which can make a basis of the design of error correction code.

We introduce a subclass of context-free languages, called pure context-free (PCF) languages, which is generated by context-free grammars with only one type of symbol (i. e. , terminals and nonterminals are not distinguished), and consider the problem of identifying paralleled even monogenic pure context-free (pem-PCF) languages, PCF languages with restricted and enhanced features, from positive data only. In this paper we show that the ploblem of identifying the class of pem-PCF languages is reduced to the ploblem of identifying the class of monogenic PCF (mono-PCF), by decomposing each string of pem-PCF languages. Then, with its result, we show that the class of pem-PCF languages is polynomial time identifiable in the limit from positive data. Further, we refer to properties of its identification algorithm.

Geometric region method is one of the techniques to handle real-time systems which have potentially infinite state spaces. However, the original geometric region method gives incorrect results for the CTL model checking of time Petri nets. In this paper, we discuss the sufficient condition for the geometric region graphs to be correct with respect to the CTL model checking of time Petri nets, and then propose a technique to partition given geometric regions so that the graphs satisfy the sufficient condition. Finally, we implement the proposed algorithm, and compare it with the other methods by using small examples.

An acoustic diagnosis technique for the blower by wavelet transform and neural networks is described. It is important for this diagnosis to detect surging phenomena, which lead to the destruction of the blower. Dyadic wavelet transform is used as the pre-processing method. A multi-layered neural network is used as the discrimination method. Experiment is performed for a blower. The results show that the neural network with wavelet transform can detect surging sound well.

The electromagnetic interference (EMI) induced by steady arc has been demonstrated to be dependent on arc voltage fluctuation when the arc transfers from the metallic phase to the gaseous phase. In order to give the physical understanding of this arc voltage fluctuation and EMI, several typical materials, such as Ag, Cu and Zr, were tested and their arc behavior was determined and compared. The experimental results indicated that the arc behavior, in particular the arc voltage fluctuation in the moment that metallic phase transfers to the gaseous phase was different for different materials. Based on the test results and former investigations, a plausible mechanism is proposed for understanding these phenomena.

One of the ways to execute a processing algorithm in high speed is parallel processing on multiple computing resources such as processors and functional units. To identify the minimum number of computing resources, the most important is the scheduling to determine when each operation in the processing algorithm is executed. Among feasible schedules satisfying all the data dependencies in the processing algorithm, an overlapped schedule can achieve the fastest execution speed for an iterative processing algorithm. In the case of processing algorithms with operations which are executed on some conditions, computing resources can be shared by those conditional operations. In this paper, we propose a scheduling method which derives an overlapped schedule where the required number of computing resources is minimized by considering the sharing by conditional operations.

Conventional fast block-matching algorithms, such as TSS and DSWA/IS, are widely used for motion estimation in the low-bit-rate video coding. These algorithms are based on the assumption that when searching in the previous frame for the block that best matches a block in the current frame, the difference between them increases monotonically when a matching block moves away from the optimal solution. Unfortunately, this assumption of global monotonicity is often not valid, which can lead to a high possibility for the matching block to be trapped to local minima. On the other hand, monotonicity does exist in localized areas. In this paper, we proposed a new algorithm called Peano-Hilbert scanning search algorithm (PHSSA). With the Peano-Hilbert image representation, the assumption of global monotonicity is not necessary, while local monotonicity can be effectively explored with binary search. PHSSA selects multiple winners at each search stage, minimizing the possibility of the result being trapped to local minima. The algorithm allows selection of three parameters to meet different search accuracy and process speed: (1) the number of initial candidate intervals, (2) a threshold to remove the unpromising candidate intervals at each stage, and (3) a threshold to control when interval subdivision stops. With proper parameters, the multiple-candidate PHSSA converges to the optimal result faster and with better accuracy than the conventional block matching algorithms.

A simulation model for natural convection was developed for determining the surface temperature distribution in base plates with rectangular vertical fins in communication equipment. An estimated velocity derived from the buoyancy and pressure drop equations in a duct was used for laminar forced convection cooling simulations in parallel plates. Temperature distributions in finned plates were calculated by numerical integration of the heat conduction equation. An experimental study was also performed, to check these simulation results, by changing the height of fins, the pitch of fins, and the heat generation conditions. Experimental results and analytical results were found to agree well. Also, this simulation method was extended to analyze natural convection cooling in vertical base plates with inclined parallel fins. We placed alternately on the plates the sections without fins and the sections with fins on the plates. Using the inclined fins, air flow rate between fins was large and fresh air flew into the fins from the side of the plates. The natural convective heat-transfer rate for inclined fins was found to be 14% higher than that for vertical fins.

A new learning method is proposed to enhance the performances of the fuzzy ARTMAP neural network in the noisy environment. It combines the average learning and slow learning for the weight vectors in the fuzzy ARTMAP. It effectively reduces a category proliferation problem and enhances recognition performance for noisy input patterns.

In this paper, we propose a transformation technique for the multiplications of one variable with multiple constants, which are frequently seen in the various applications of signal processing, image processing, and so forth. The method is based on the exploration of common subexpressions among constants and reduces the number of shifts, additions, and subtractions to implement linear computations with hardware. Our method searches for regularity among elements of a linear transform using matrix decomposition and generates a reduced data-flow graph which preserves the full regularity. We show experimental results obtained using Discrete Cosine Transform (DCT) and Fast Fourier Transform (FFT) and illustrate the effectiveness of the method.

This paper describes the fiber unit blowing length of an optical fiber distribution system for business buildings which employs pipe cable, fiber units and the fiber unit blowing technique. The relationship between the applied force and the length of a fiber unit blown into a straight pipe is investigated theoretically and experimentally and the fiber unit blowing length is estimated. Moreover, the pipe bending radius which has a small bending resistance force is clarified. Cables, fiber units and unit blowing equipment are manufactured based on the results and their transmission and mechanical characteristics are confirmed to be stable.

An adaptive array has been proposed as a canceller for both inter-symbol interference (ISI) and co-channel interference (CCI). However, it has no path-diversity gain since it selects just one signal correlated to the reference signal. In this paper, a novel interference canceller having sufficient path-diversity gain is proposed. The canceller is characterized by the combined configuration of an adaptive array and an equalizer. In the proposed system, a pre-selecting adaptive array is installed first. By employing a specific training sequence and sampling timing at the receiver during the training period, the perfect correlation between the "desired signal" and "short delayed" is achieved. Therefore, the pre-selecting adaptive array can extract the desired and ISI signals simultaneously, and the cascaded adaptive equalizer can provide the path-diversity gain without degradation by interference. The proposed system achieves a simple configuration and robustness against both ISI and CCI with a sufficient path diversity gain. In computer simulations, average BER characteristics of the proposed system were evaluated in a quasi-static Rayleigh fading channel. The simulation results showed that the system can reduce both long-delayed ISI and CCI efficiently, and that the expected path diversity gain is obtained even with strong CCI. They also showed that the degradation is not so serious when the number of antenna elements is less than that of incoming signals.

In this letter, we propose new methods for estimating frequency and phase of a complex sinusoid in complex white Gaussian noise. These new estimators use the cyclostationarity of the sinusoid which is a cyclostationary signal type. Only one component corresponding to a lag of zero of cyclic autocorrelations is used to reduce the computational load. The performances of our proposed estimators are compared to those of Kay estimator, Cramer-Rao bound (CRB) and maxim-likelihood estimator (MLE). Simulation results show that our proposed methods can estimate the frequency and phase correctly even in low signal-to-noise ratio (SNR).

A training data selection method is proposed for multilayer neural networks (MLNNs). This method selects a small number of the training data, which guarantee both generalization and fast training of the MLNNs applied to pattern classification. The generalization will be satisfied using the data locate close to the boundary of the pattern classes. However, if these data are only used in the training, convergence is slow. This phenomenon is analyzed in this paper. Therefore, in the proposed method, the MLNN is first trained using some number of the data, which are randomly selected (Step 1). The data, for which the output error is relatively large, are selected. Furthermore, they are paired with the nearest data belong to the different class. The newly selected data are further paired with the nearest data. Finally, pairs of the data, which locate close to the boundary, can be found. Using these pairs of the data, the MLNNs are further trained (Step 2). Since, there are some variations to combine Steps 1 and 2, the proposed method can be applied to both off-line and on-line training. The proposed method can reduce the number of the training data, at the same time, can hasten the training. Usefulness is confirmed through computer simulation.

In the multipath mobile channel, the received signal suffers from both the fluctuation in the received field intensity caused by fading and waveform distortion caused by the echo. Diversity reception using multiple spaced antennas is an effective method to compensate for fading, while echo cancellation with an adaptive array is good at compensating for waveform distortion. In this paper, an adaptive switching echo cancellation/diversity reception method to compensate for both waveform distortion and fading is proposed. The proposed switching reception monitors the impacts of channel conditions on received signal and then one of an echo canceller and a diversity receiver is selected accordingly to compensate the channel. The compensation performance of the proposed switching reception in terms of both average DUR (Desired to Undesired signal Ratio) and the probability of DUR below a threshold value is investigated with computer simulation. The results show that the adaptive switching echo cancellation/diversity reception has realized the advantages of both adaptive echo cancellation and diversity reception.

In this paper, we propose an interference canceller for asynchronous DS-CDMA. The principle is based on parallel cancellation using soft decision(PCSD), however, we propose to add an operation to suppress the strength of interfering signals replica on PCSD. We show here that this operation plays a very important theoretical role in PCSD, and that the performance of our proposed scheme approaches that of a perfect decorrelating detector under certain conditions. With this theoretical background in mind, we named this scheme the "Near-Decorrelating Multistage Detector"(NDMD). To demonstrate NDMD performance, we performed two kinds of computer simulations. In the first kind of simulation, simple conditions are assumed in order to evaluate basic cancelling performance. In the other kind of simulation, essential techniques for CDMA cellular systems such as FEC, transmission power control(TPC), and base band filtering were implemented while taking into account NDMD as applied to such systems. These simulations numerically demonstrate that NDMD is very efficient in cancelling out interference and that it improves asynchronous DS-CDMA performance.

The location of stations on the buses can not be ignored in the analysis of the DQDB protocol, especially when traffic load is heavy. In this paper, we propose a new method to model the DQDB (Distributed Queue Dual Bus) protocol by assuming that the request arrival process depends on both the value of the request counter and the location of a station on the buses. By taking these dependences, we can catch the real behavior of the DQDB stations, which is locationally dependent and unfair under heavy load traffic. Based on this model, we analyze the DQDB system with finite buffer by considering the request counter states and buffer states separately and obtain the throughput, mean packet delay and packet reject probability of individual stations. The throughput in individual stations matches that of simulation very well within the range of traffic up to the channel capacity. Also the delay and packet reject rate performance is good up to moderate traffic load. These numerical results reveal the properties of the location dependence and the unfairness of DQDB system under heavy load condition. The analytic results under heavy load traffic for a general DQDB system has not been reported till now. Therefore we conclude that our model and analysis are valid and effective.