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Ibaraki, Japan

Otemon Gakuin University is a private university at Ibaraki, Osaka, Japan, founded in 1966. Wikipedia.

Cui Y.,Otemon Gakuin University
Communications in Computer and Information Science | Year: 2015

With the establishment of highly advanced and sophisticated iSC, enterprises are able to improve their competitiveness, and meanwhile, effortlessly overcome the issues which cannot be resolved under the traditional supply chain operation. When we intensely show our concern to the construction of iSC, the fragility of supply chain caused by continuous pursue of high efficiency cannot be neglected. Resilience resembles to the immune system of supply chain, the more we pay attention to it, the more robust and stable the supply chain is. Henceforth, through the synergy effect of the acquired experience during the enhancement of resilience and the accumulation of information and network technology which progresses during the establishment of supply chain, operation of supply chain will turn out to be more simple and secure. Meanwhile, improvement of customer satisfaction degree will also benefit from it. In this paper, we propose a relationship model that is utilized to define the mechanism of improving Supply Chain Resilience with employment of IoT. © Springer-Verlag Berlin Heidelberg 2015.

Tochio Y.,Otemon Gakuin University
Journal of the Japan Research Association for Textile End-Uses | Year: 2012

In the main discourse, the problems are examined that an enterprise would like to employ new graduates rather than experienced persons. After reviewing general aspects of researches in labor economics, a new frame is presented about this problem.

Yoshimura S.,Otemon Gakuin University | Okamoto Y.,Hiroshima University | Yoshino A.,Hiroshima University | Kobayakawa M.,Hiroshima University | And 2 more authors.
PLoS ONE | Year: 2014

Reappraisal is a well-known emotion regulation strategy. Recent neuroimaging studies suggest that reappraisal recruits both medial and lateral prefrontal brain regions. However, few studies have investigated neural representation of reappraisals associated with anticipatory anxiety, and the specific nature of the brain activity underlying this process remains unclear. We used functional magnetic resonance imaging (fMRI) to investigate neural activity associated with reappraisals of transient anticipatory anxiety. Although transient anxiety activated mainly subcortical regions, reappraisals targeting the anxiety were associated with increased activity in the medial and lateral prefrontal regions (including the orbitofrontal and anterior cingulate cortices). Reappraisal decreased fear circuit activity (including the amygdala and thalamus). Correlational analysis demonstrated that reductions in subjective anxiety associated with reappraisal were correlated with orbitofrontal and anterior cingulate cortex activation. Reappraisal recruits medial and lateral prefrontal regions; particularly the orbitofrontal and anterior cingulate cortices are associated with successful use of this emotion regulation strategy. © 2014 Yoshimura et al.

Two new gnaphosid species of the genera Drassyllus and Hitobia are described from Amami- oshima Island, southwest Japan under the names of Drasyllus amamiensis and Hitobia makotoi. D. amamiensis'ss distinguished from D. biglobus Paik 1986 by the anterior epigynal magn shghtly swollen inward in antero-lateral parts. H makotoi is separated from H umfacigera (Bösenberg & Strand 1906) by the epigynum without posterior profusion. © Arachnological Society of Japan.

Nakano N.,Otemon Gakuin University
International Journal of Innovative Computing, Information and Control | Year: 2011

Recently, an agent-based problem has been attracting much attention in various fields, for instance marketing research as well as economic and social sciences. Though many researchers treat this problem, learning effects of agents cannot be disregarded because most agents (perwons,) often change their action rule according to circumstances. In this paper we deal with an agent-based problem including Q-learning algorithm, which is one of reinforcement learning methods. In this study, we employ two kinds of agents, followers and pioneerw, and design their characters by using Q values. Agents rJcirJ their ottiturJs by ones which nighhor ognts show, nm] thri Q ?Yn1?IFS nr updated. Simulation studies show that the results of agent-based simulations are affected by action rules of agents and the initial attitudes of agents. © 2011 ISSN.

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