Abstract. Traffic flow models with cellular automata have been applied to analysis of traffic phenomena to understand traffic jams and to construct urban traffic simulators. Estimating vehicular characteristics from the traffic flow is expected to realize the high performance and reproducible simulation. In this paper, we propose an estimation method of the parameter of a multi-species ZRP based on the variational Bayes method, and detect the OV function, which shows the optimal speed with respect to the distance between cars, from the spatio-temporal diagram.

Abstract. Hsiao code is a SEC-DED code which is used for the error correction of main memories of computers. Since the error rate in the main memory is relatively low compared to the data transmission channel, generally, the coded rate can be estimated higher. Thus, it is an important problem to construct Hsiao codes which have high coded rate with small number of Hamming weight 4 code-words. This paper shows an effective algorithm for the computer search of such codes.

Abstract. We consider the allocation of a running time supplement to a railway timetable. Previously, Vekas et al. developed a stochastic programming model. In this paper, their optimization model is improved by adding bound constraints on the supplements. It is shown that the probability of delays decreases when using the proposed model. In addition, an effective L-shaped algorithm is presented.

Abstract. In this paper, we develop the Shifted Block BiCGSTAB(ℓ) method for solving linear systems with multiple right hand sides and multiple shifts. This method is based on the Block BiCGSTAB(ℓ) method and the Shifted BiCGSTAB(ℓ) method. We also discuss the accuracy of the Shifted Block BiCGSTAB(ℓ) method and propose more accurate method. In numerical experiments, the Shifted Block BiCGSTAB(ℓ) method is faster than the Shifted BiCGSTAB(ℓ) method for each right hand side, although it’s accuracy is a little lower than the other in some cases.

Abstract. In this paper, we present the new computational method for estimating a noise covariance matrix directly from noisy multichannel data. Our proposal outperforms the conventional time shift difference (TSD) method with an increase of sharpness (focalization) for estimated brain source locations, which are calculated by using the noise covariance incorporated multiple signal classification (MUSIC) algorithm proposed by Sekihara et al. 1997. This conclusion is validated through numerical simulations of a realistic magnetoencephalography (MEG) system.