Volunteer Support Network for Elderly Foreigners : A New Movement of Korean Residents in Kyoto

departmental bulletin pape

Observation of B+ → χc0K+

journal articl

Joseph Alois Schumpeter経済学の基礎

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Robust-control using model-error-feedback CDOB and DOB under variable-time-delay

This paper presents the robustness improvement of the Communication-Disturbance-OBserver (CDOB) based on Lyapunov-Krasovskii functional(LKF), and proposes the Network-based-Control-System (NCS) using the LKF based CDOB and a local-side DOB. The CDOB is a compensation method for a output signal includes a communication delay. By using LKF, a steady-state output-estimation-error of the CDOB under variable time-delay and parameter-perturbations is suppressed. However, the latest studies have not shown the robustness to the disturbance-input. In this paper, the frequency- weight of CDOB to the disturbance is introduced to the design of the LKF based CDOB, to suppress the error. From a calculated error-characteristic and a numerical simulation, the account of the weight is validated. Additionally, implementing a disturbance observer in the local (controlled object) side, the robustness of the NCS is improved much in the numerical simulation.journal articl

Correlation between food intake and body weight gain for all animals except those in the two recovery groups

<p><b>Copyright information:</b></p><p>Taken from "Effect of an herbal extract Number Ten (NT) on body weight in rats"</p><p>http://www.cmjournal.org/content/2/1/10</p><p>Chinese Medicine 2007;2():10-10.</p><p>Published online 14 Sep 2007</p><p>PMCID:PMC2034566.</p><p></p

Proposal and Evaluation of Surrogate-Assisted Self-Adaptive MBEANN

This paper proposes an extension for Mutation-Based Evolving Artificial Neural Networks (MBEANN) algorithm. The proposed method consists of two parts: a surrogate model and a self-adaptive mutation. Firstly, the surrogate-assisted mechanism is introduced to MBEANN for reducing the cost of fitness evaluations. This mechanism employs approximated fitness values predicted by a surrogate model instead of true fitness functions. Secondly, the self-adaptive mutation is applied to MBEANN for adjusting the exploring area in parameter space. The performance of the proposed method is compared with the normal MBEANN and NEAT algorithms by using the three benchmarks of OpenAI Gym. The experimental results showed that the proposed method outperformed other algorithms in all benchmarks.journal articl