There is no adequate methodology to evaluate the effectiveness of a company information system. Many companies are not sure how to invest money to the information systems. Recently, the information systems is recognized so importantly that it is often discussed in relation to the business management strategy. Information systems investment should be evaluated as one of the relevant measures to gain the competitive edge against its competitors. Effectiveness of the information systems fully depends on the ability for its users to utilize it. The information systems department should create a tough organaiztion to improve the whole business operation through the usage of the state-of-the-arts Information Technology.
We investigated the possibility of high speed data transmission using earth returning circuit on low voltage distribution line. It is expected that high quality and high speed acquisition of distribution facilities and customers data will be indispensable near future because of Demand Side Management etc. However at present, the data transmission rate on distribution line is about 100 bps by narrow band FSK or PSK. We use spread spectrum communication which is thought to be suitable for relatively low S/N. In this paper, we measured the transmission characteristics of earth returning circuit to make a model of transmission characteristics. We also measured the BER-Eb/N0 characteristics both on outdoor model distribution line and on indoor simulator to confirm the transmission rate of 9600bps with the reach of 100m by direct spread spectrum modem. However, if we make use of this modem on actual distribution facilities, emission regulation and leakage voltage into customers' facilities must be taken into account.
Dependencies of ventricular and arterial pressures on the dynamical properties of afterload and viscous resistance of ventricular muscle have been analyzed by a theoretical model. The ventricular contractile element was expressed by a time varying capacitor and arterial system was described by 2 compartments, each of which was composed of resistances and capacitors. With time dependent decreases in arterial resistance and time dependent increase in ventricular viscous resistance, pressures in ventricle and artery have been reduced. With reduction of aortic compliance, those pressures have been elevated while peripheral compliance did not contribute to them. Time dependent decrease in aortic valvular resistance reduced ventricular pressure while it elevated arterial pressure.
This paper presents a novel method for evaluating optical disk media, for instance, magneto-optical or phase-change disk media. In this method, a three-axis objective lens actuator was installed for scanning in the tangential direction on a nonmoving disk during servo-engaging in the focus and tracking directions. In preparing the disk media, deposition or sputtering, took place in 5-mm diameters to film on a pre-grooved substrate, spot by spot. Signals were recorded on a rotating disk, and reproduction signals from the spot media were analyzed using isolated waveforms during disk rotation using a Fast Fourie Transform (FFT) spectrum analyzer and a three-axis actuator. The effectiveness of this novel evaluating method was confirmed by comparing the carrier-to-noise ratio (CNR) measured between analogue and FFT spectrum analyzers.
This paper presents the effect of objective lens tilt on bit error rate (BER) characteristics in magneto-optical disk recorder which is used for non-compressed digital recording at high density and high bit rates. The author studied the relation between coma aberration and optical moment for the Airy ring of the focused spot image. The lens tilt margin was determined by a BER level of 3_??_10-5 for a bit length of 0.33 μm/bit under the conditions of NA=0.55 and a laser wavelength was of 680nm. The lens tilt margins for a triplet lens and an aspherical lens was within ±0.1 and ±0.2 degrees of angle, respectively.
The size of a hierarchical neural network is desirable to be compact according to each application problem, because the network size is closely related to not only the computer memory but also the generalization ability. If the network is too large, it will be over-fitting the training data and bad generalization will occur. In an opposite situation, training for its own sake will fail due to under-fitting. This paper deals with a method to reduce the network size and to obtain a compact network equivalent to the original one. Principal Component Analysis (PCA) performs a central role in a size reduction. The reduction can be implemented in the follwing way: (a) At first, train a largish network in order to avoid under-fitting. (b) after training, the output matrix of hidden units is changed into the component score matrix by PCA. (c) determine n components corresponding to the n largest eigenvalues according to PCA so that the cumulative proportion may be almost 100%. Then the number of hidden units can be reduced up to n. (d) determine weights and thresholds by solving simple linear equations so that the reduced network may be equivalent to the original one. The proposed method is applied to a simple pattern recognition problem and the result shows the effectiveness of the proposed method.
This paper describes a control law for multiple actuation servo systems. Multiple actuation systems have an ability to solve some difficult engineering problems: backlash, Coulomb friction and disturbance. The proposed control strategy remarkably improves the performance comparing with conventional single actuation systems. The experimental system demonstrates high precision and high robustness against disturbances in spite of heavy gear backlash, Coulomb friction, and sensor dead-zone.
The energy consumption in transportation sector is still increasing nevertheless of the oil crises. Since transportation sector strongly depends upon fossil fuels, it is expected to be effective for energy conservation to reduce CO2 emission to cope with global warming. In this study the authors investigate the relationship between transportation activities and land use structure in urban areas from the viewpoint of minimizing total trip length to reduce energy consumption in transportation sector Two models are developed based on congestion-free city concept which means the supply of road is adjusted to satisfy the traffic. One is the model in which people move depending on the population at their destination while the other depending on the trip length. The latter model describes the preference of shorter commuting. In the former model the optimal land use to minimize total trip length is attained. The result shows that offices are allocated around the center while residential area is relatively on the suburbs, which indicates similar pattern of land use compared with actual cities. On the other hand, results of the latter model show that there exists the optimal preference of commuting length which causes minimization of the automobiles' trip length per capita. Result concerning road area is also discussed and compared with the empirical data of Tokyo.
An autonomous robot must have a real-time path plan satisfying environmental changes and unknown situations. The obstacle avoidance is one of the problem in the path plan. This research has addresses the realization of real-time generating the path of large area obstacle avoidance in the already-known environment based on consept of the neural network and the graph processing. This reports propose the technique for generating the shortest path based on a parallel algorithm. This path planning simulation with EWS (hp 9000/715) required less than 1 seconds. Supposing that each of elements independently renews the parameter, the present technique is the useful one for path plan of an autonomous robot.
This paper deals with a flexible link hammer which can continuously hit an object with an unknown coefficient of rebound. This hammer system makes use of only the first mode of vibration of the link for a desired hitting. The relative deflection of the flexible link hammer is expressed as a function of an angular acceleration which is used as the input of the link driver. When the hammer hits an object, the hammer has to avoid the ‘twice collision’ in one hitting cycle and flap an object with a desired hitting velocity. The expression of the relative deflection can easily derive two sets of non-linear simultaneous equations satisfying the hitting conditions. The input of the link driver are determined from the numerical solutions of the simultaneous equations. Since the equations are the function of the initial velocity, the coefficient of rebound has to be identified by using the strain of the flexible link. However, it is difficult for this numerical method to find out the optimal input pattern by on-line processing. Therefore, the multi-layered neural networks are applied for the generation of the optimal input pattern. The neural networks acquire the relationship between the initial velocity of the hammer head and the parameters of the input pattern of the hammer driver. The trained neural networks can generate the input pattern of the link driver for a measured initial velocity and are effective for the on-line processing.