The important factors for dependability are safety and reliability. When dependability is evaluated, in view of safety along with the probability of an accident occurring, both the degree of accident damage and the capability of installed-safety devices should be included as items to be evaluated. To establish a barometer to quantitatively determine the dependability of a system, a study to standardize and rationalize the safety index is currently under way. However, to standardize the Tree Analysis for Safety (TAS) which is used to determine the safety index of a system, TAS has been unable to deal with the degree of damage occurring in accidents and has not been able to cope with a wide range of accidents in a consistent manner. For a TAS standard that can be applied to accidents, we propose that a mechanism, to select safety devices applicable in accordance with protection capabilities, be built into TAS by identifying the upper limit of the protection capability of safety devices by considering the potential amounts of hazard potential factors which greatly affect the degree of accident damage. We have applied this system to accidents during normal hours and to maintenance in Factory Automation systems, and have confirmed that this system could be used as an evaluation method.
Market price systems constitute a well-understood class of mechanisms that provide effective decentralisation of decision making with minimal communication overhead. In a market-oriented programming approach to distributed problem solving, the resource allocations for a set of computational agents are derived by computing competitive equilibrium of an artificial economy in static conditions. In this paper we newly propose a dynamic market-oriented programming. Each agent has transitional dynamic utilities and tries to find equilibrium point by evaluating the tradeoffs of acquiring different resources in dynamic environment. Careful constructions of the dynamic decision process according to economic principles can lead to efficient distributed resource allocation, and the behaviour of the system can be analysed in economic terms.
In this study, a new heuristic method is proposed involving a non-recursive algorithm and priority rules to integrate the operation sequencing and tool selection phase in a CAM system. The object of the algorithm is to automatically define the operation sequence and tool to be used for each operation while minimizing the number of tool changes and the total number of tools. As an effective method for reducing tool preparatory task, resident tool practice is accommodated by comparing accumulated frequency record of the past use of candidate tools. A numerical example has been provided in this study. Also, the proposed algorithm is compared with other known algorithms and its advantages examined.
Hathaway and Bezdek's Fuzzy c-Regression Models (FCRM) is regarded as a simultaneous analysis of clustering and multiple regression. In high dimensional setting, the regression techniques do not perform well for reasonable sample sizes because of the inherent sparsity of samples in the cluster. This paper proposes a simultaneous approach to the clustering, principal component analysis and multiple regression analysis. Aiming at knowledge discovery from POS data that are recorded automatically into the cash register transactions, we analyze the relationship between meteorological information and sales of perishables.
This paper describes newly developed ultrasound ring array probes. In one probe, eight transducers were aligned circularly and turned toward the central axis of the probe. The other one has an ultrasound transducer with convex surface at the center of the probe and eight transducers was set to surround the transmitter and used as receivers. Using these probes, we performed experiments to reconstruct a 3D image of a measurement object. The experimental results indicated these probes has the availability for high resolution imaging.
In this paper, two time shortning methods are proposed in path planning calculation of the autonomous robot vehicle using the neural network. The first method is to automatically set the relay point in order to avoid the local minimum in the generation of optimum route, and the second method is to give initial value of motion command input into the cascaded neural networks from the look-up table learned. These methods used jointly are examined for the effectiveness by applying to the path planning in various environments. As the results, the effectiveness of the system which used two methods jointly at the start and immediately excluded the restraint of the relay point passage afterwards was clarified.