The facilities of residential areas are necessary for economical and social activities. During the planning on development projects for new facilities, the effective uses of them are examined. However, these development projects have negative impacts as well as positive impacts on the inhabitants around the facilities. While the economic effects are regarded as positive, the environmental disruptions are regarded as negative. Therefore, it is important to measure comfort degrees quantitatively and evaluate the facilities synthetically. In this paper, we propose a model of comfort degrees and distances, and construct an evaluating system for residential environment with comfort degrees. We consider evaluating results of this system.
When we evaluate a key technology for a global environmental issue, we must draw a conclusion considering all the impacts on the environment throughout whole product lifecycle. However, an aggregation of conventional product-oriented lifecycle analyses for individual products, which are interactively produced, is not sufficient for objective evaluation. In this paper, we propose a new method for the evaluation of technologies using systems approach. The method consists of two steps; total effect indexes are first calculated, then the system is evaluated from the viewpoint in which an investigator is interested. With this method, we could avoid allocating the effect of the technology to several products, thus the technology is evaluated focusing on the effect in the whole system. As a case study, several recycle systems of PET bottle were analyzed. Quantitative analysis from the viewpoints of CO2 emission and crude oil consumption showed the effectiveness of those recycle systems as well as the availability of the proposed method.
It is becoming increasingly important to decompose chlorofluorocarbon (CFC) which destruct ozone layer. The purpose of this study is to investigate CFC decomposition activities of catalyst and a decomposition system. CFC decomposition activities with H2O by KI-100 catalyst which we have developed a TiO2-based catalyst was investigated. KI-100 catalyst showed high activity for CFC11, CFC12 and CFC113 decomposition. However, the conversion rate for CFC113 was decreased with time and was 70% after 1000h. In order to clear the reason, the KI-100 catalyst was analyzed. From the results of quantitative analyses, it was found that a weight of TiO2 in the catalyst was decreased from 11.42g to 1.09g (-90.5wt%) and TiO2 changed to TiOF2. To prevent the formation of TiOF2, the other component, which was less reactive with CFC than TiO2, was coated over the catalyst surface. The improved catalyst, KI-1000, showed long durability for CFC12 decomposition and the conversion rate was above 99.99% over 2000h. Based on these results, we commercialized “Catalytic Decomposition Equipment of CFC”.
The present paper shows that oil from waste plastics can be used as fuel for diesel electric generator. The experimental results indicated that 80wt% of waste plastic could be recovered as oil by using a laboratory scale facility with plastic feed rate of 30kg/h. When reflex converter is operated under the optimum condition, an oil substance which has both high ignitability and fluidity is recovered. Under the combustion performance test with the recovered oil, a 70kilowatt diesel engine could be operated stably. The properties of exhaust gas cleared all regulatory standards, although the level of nitrogen oxides (NOx) was higher than that of kerosene. The concentration of NOx could be reduced by optimization of fuel injection timing.
This article deals with Life-Cycle Assessment (LCA) of electric power and Town-gas (gas through mains) system. LCA is an objective process to evaluate the environmental burdens associated with a product, process, or activity by identifying and quantifying energy and materials used and wastes released to the environment, to assess the impact of them, and to evaluate and implement opportunities to affect environmental improvements. The assessment includes the entire life cycle of the product, process, or activity, encompassing extraction and processing of raw materials, manufacturing, transportation and distribution, use/re-use/maintenance, recycling, and final disposal. For this purpose, we first developed a novel mathematical model called Process-relational Model. Utilizing this model, we can dissolve the difficulties of LCA in retracing complicated repercussions among production systems and in allocating environmental emissions among multiple products. Then we investigated electric power and town gas system, and developed data-base of energy and material balance concerning them, and calculated primary energy consumption and CO2 emission per respective units. Applying the results, we simulated the replacement from conventional system utilizing electricity-gas to co-generation system utilizing Town-gas, and we evaluated the variation of resource requirements and emissions.
In this paper, the nonlinear phenomena in driven RLC circuit systems including a nonlinear inductor composed of the GIC electronic circuit are studied. By both simulation experiments and real circuit experiments, it is shown that for given nonlinear system, bifurcation and chaos occur in some range of driven frequency.
Newly developed press packed reverse conducting IGBT (RCIGBT): ST1000EX21, having 2500V-1000A rating, has realized the use in high reliability required application area. Multiple chips press packed RCIGBT structure, containing IGBT chips and fast recovery diode (FRD) chips, has been achieved founded on the basic experimental results and the stress analysis using finite element structure analysis program ABAQUS. Excellent electrical characteristics, especially tough turn-off capability, such as Ic=5000A, Vcp=2800V at Tj=125°C, have been obtained. And high reliability, withstanding the thermal cycling (fatigue) test more than 50, 000 cycles and the high temperature voltage blocking test for 2, 000 hours, has been confirmed. The device is now available and successfully used for transportation systems and the other applications, which require high reliability and long term stability. Voltage and current ratings in IGBTs and IEGTs are now going to be expanded to higher grade.
In this paper, we evaluate source derivation method for visualization of localized brain activity. To realize more accurate analisys of brain activity by Electroencephalograph (EEG), it is necessary to reduce background EEG which give bad influence as a noise from other regions of the brain, when we record EEGs. Source derivation (SD) method can realize such function based on electromagnetism theory. At first, we evaluate SD method by simulation to know its characteristics of localization and noise reduction. Then, we apply it to analysis of auditory evoked potential and EEG recorded during music listening. It becomes clear that SD method can easily extract the buried features of localized brain activity which are difficult to visualize by usual technique.
Interface traps and bulk traps induced by heavy metal impurities in Si-MOS structure have been characterized, using Isothermal Capacitance Transient Spectroscopy (ICTS). In addition, the use of MOS inversion time is proposed for the detection of a very low density of heavy metal impurities in the ICTS measurements. As a result, it has been made clear that heavy metal impurities enhanced interface trap densities as well as induced bulk traps. The degree of the enhancement is varied by the species of heavy metal impurities. It is discussed that interface traps may be enhanced by the substitutional heavy metal impurities. Moreover, it has been ascertained that a very low level of contamination by heavy metals is able to be detected by using MOS inversion time. This has been experimentally shown by the use of copper impurities. Furthermore, it has been clarified from the change of MOS inversion time that interface traps are also detrimental to carrier generation lifetime.
In recent years, an automated mobile vehicle without direct control by a human has been researched and developed at the companies and universities. We have proposed the tracking control system of the autonomous mobile robot with multiple sensors in which supersonic distance sensors and infrared direction sensors are configured. In discussion on the controllability of the vehicle, it must be indispensable for us to track the trajectory of moving vehicle precisely without human manipulation. In the paper, we have proposed a new locus measuring system for cruising object using the neural network and genetic algorithm. Especially in the present neural network algorithm, the learning process with noises is introduced to enhance the percentage of the recognition of the objects in case of damaged or un-focal images with noises and being out of focus. The paradigm based on the genetic algorithm (GA) is introduced to enhance the speed of the rough detection of the target object because the scanning target could not be conducted randomly in the neural network approach.
An optimization method is proposed for unconstrained optimization problems, including neural network training. To avoid falling into local optima, the method is based on stochastic search and performs diversified and intensified searches alternatingly. Besides, for more efficient search of the solution space, it utilizes its history of searching which is stored in long, medium and short term memories and controls the diversification and intensification of the search. The method includes minimum number of adjustable parameters aiming at a generic method that does not need much parameter tuning. An example shows that the method can find the global optimum irrespective to the initial solutions.
An imaging method to take high-speed moving objects with wide dynamic range image has been developed. In order to expand dynamic range of the image, the method combines two images taken under different exposure conditions at the same time. To obtain the two different exposure condition images, incident light is divided to different light intensity by optical beam splitter, and then these divided light are converted to images by CCD devices. Using this method we product a high-speed wide dynamic range camera. With this camera and newly developed algorithms, we have constructed a printed character recognition system for moving electronic parts. Using this system, a recognition accuracy of 98.1% (2895 parts, moving speed is 50cm/sec and lighting condition is 1500lux-10000lux) is obtained, which indicates sufficient performance for practice application.
A teleoperation system based on virtual environment (VE) is an emergent technology for operating a robot in remote or hazardous environment. We have developed a VE-based teleoperation system for robot-arm manipulation in a simplified real world. The VE for manipulating the robot arm is constructed by measuring the 3D positions of the objects around the robot arm by motion-stereo method. The 3D position is estimated by using two-(calibration) planes method based on images captured by the CCD camera on the robot-arm, since the two-planes method does not need pin-hole-model assumption to the camera system. The precision of this 3D-measurement is evaluated through experiments and then derived is the theoretical model to the error in the measurement. This measurement system is applied to VE-based teleoperation experiment for Peg-in-hole practice by the robot arm.
We describe a real-time system to estimate the pose of an object manipulated by a multi-fingered hand in a realistic environment. The system uses least-squares technique to estimate the pose, on the assumption that the initial pose and the geometric shape of the object and each fingertip are known. The 3D data of object's surface is obtained by visual tracking with stereo camera using a template matching method. The primary features used for tracking are distinguisable texture patterns on object's surface. In complex environments, visual tracking can be failed due to the various occlusion. The system solves the occlusion problem by detecting occlusion and using contact information of fingertips with the 3D visual information. Actual implemetation of the system applied to the task of a multi-fingered hand is explained together with results of experiments about the stability of tracking, the accuracy of estimation, and the processing time of the system.
Correlation structure of wavelet packets will be derived first. Then it will be proved that for fractional Brownian motion (fBm) processes, correlation coefficients will decrease exponentially across the wavelet packets scales-in other words almost KL-expansion. Based on the derived theorem, it is possible to estimate the parameters of fBm processes. Flexibility of the wavelet packet structure permits us to choose the bases accordingly. Simulation results show that utilizing wavelet packets it is possible to get better estimate with fewer computation than wavelet based estimation counterpart. Further application on extraction of voice signal embedded in 1/f noise will also be given.
It is recognized that elucidation of chemical structure at molecular level is important to develop new application of coal. As a result of various experiments, it has been clarified that the coal molecular consists of the following three components, the aromatic class cluster, the bridge connecting the aromatic class cluster, and the end permutation radical. Chemists have to construct theses components by hand, utilizing their empirical knowledge. It is desired to support this time consuming work with computers. The molecular structure of coal is not specified with an unique structure. In addition, the constructed structure is evaluated from various viewpoints, such as density and potential energy. Therefore, the deterministic approach is inappropriate to the estimation of the molecular structure. In this paper, we propose a method of constructing the molecular structure using the genetic algorithm (GA). In this method, the chromosomes are expressed in the form of graphs. At the crossover operation, partial graph of one parent is kept and the nodes in the rest graph inherit connectivity of nodes from the other parent. The evaluation function is determined based on the heuristics of chemists as ‘the density of the coal molecular is uniform averagely’. As a result of some experiments with structures constructed from real coal data, the following properties of our method were clarified: (1) improvement of the evaluation value was observed with the progress of the generation, (2) the coal models constructed by GA had good value of potential energy in comparison with the structure constructed by coal chemists.
This paper presents a method of discrete-time multivariable model reference adaptive control with disturbances. It is assumed that the disturbances are described by a polynomial function of time with known degree and unknown coefficients. The proposed scheme uses only input and output data and the existence of bounds for all signals is proved, which assures the output error convergence to zero. Finally, the results of computer simulation are presented to show the effectiveness of the proposed method.
For realization of a fuzzy inference, it is necessary to give appropriate fuzzy rules. Some methods which get these fuzzy rules are proposed. A fuzzy inductive learning algorithm is one of it and gets fuzzy rules from a training example set, where a training example consists of some attributes and a discrete class. However, this algorithm can't directly deal with a continuous class. If the fuzzy rules want to deal with a continuous class, it is necessary to give a relation with a continuous class and a discrete class. In this paper, I propose the method which deals with the continuous class and a revised inductive learning algorithm composed with the method. This algorithm automatically transforms a example with a continuous class into a example with a discrete class, learns fuzzy rules which deal with the discrete class, and transforms the rules which deal with the continuous class. Also, I examine the efficiency of the algorithm by two numerical experiments.
On-line measurement of ship's attitude is important from the viewpoints of search of sea-bed pattern with sonars and intelligent attitude control. From this point, the author has developed on-line accurate measurement systems which measure the heaving, rolling and pitching of ships using servo-type accelerometers and inclinometer. However, especially for the heaving, the measurement accuracy was not so good as the others because of the sensing mechanism such that the information on the heaving displacement was obtained only through the acceleration. The paper introduces a spring system which suppresses the effect of the short periodic waves on the accelerometer and improves the measurement accuracy.
This paper deals with a new design method of optimal deadbeat servo-system having L samples controlling delay. An actual deadbeat controller is composed of the series compensator with integral-action, the pre-compensator having L samples controlling delay and state feedback compensation. The optimal deadbeat control signal which can minimize the quadratic performance index for the manipulated variable and deviation can be easily obtained from the matrix computation using sampled data of the step response of the system. Then, the deadbeat controller can be designed by using the sequence of the control signal. Illustrative numerical examples are presented and the design method proposed here is very simple comparing with other methods, and it seems to be useful for the practical use.