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Nishi-Tokyo-shi, Japan

Tama University is a private university in Tama, Tokyo, Japan, established in 1989. Wikipedia.


Hadavandi E.,Amirkabir University of Technology | Shahrabi J.,Amirkabir University of Technology | Hayashi Y.,Tama University
Soft Computing | Year: 2015

In this paper, we focus on modeling multi-target regression problems with high-dimensional feature spaces and a small number of instances that are common in many real-life problems of predictive modeling. With the aim of designing an accurate prediction tool, we present a novel mixture of experts (MoE) model called subspace-projected MoE (SPMoE). Training the experts of the SPMoE is done using a boosting-like manner by a combination of ideas from subspace projection method and the negative correlation learning algorithm (NCL). Instead of using whole original input space for training the experts, we develop a new cluster-based subspace projection method to obtain projected subspaces focused on the difficult instances at each step of the boosting approach for training the diverse experts. The experts of the SPMoE are trained on the obtained subspaces using a new NCL algorithm called sequential NCL. The SPMoE is compared with the other ensemble models using three real cases of high-dimensional multi-target regression problems; the electrical discharge machining, energy efficiency and an important problem in the field of operations strategy called the practice–performance problem. The experimental results show that the prediction accuracy of the SPMoE is significantly better than the other ensemble and single models and can be considered to be a promising alternative for modeling the high-dimensional multi-target regression problems. © 2015 Springer-Verlag Berlin Heidelberg Source


Hayashi Y.,Tama University
International Journal of Computational Intelligence and Applications | Year: 2013

This paper presents theoretical and historical backgrounds related to neural network rule extraction. It also investigates approaches for neural network rule extraction by ensemble concepts. Bologna pointed out that although many authors had generated comprehensive models from individual networks, much less work had been done to explain ensembles of neural networks. This paper carefully surveyed the previous work on rule extraction from neural network ensembles since 1988. We are aware of three major research groups i.e., Bologna' group, Zhou' group and Hayashi' group. The reason of these situations is obvious. Since the structures of previous neural network ensembles were quite complicated, the research on the efficient rule extraction algorithm from neural network ensembles was few although their learning capability was extremely high. Thus, these issues make rule extraction algorithm for neural network ensemble difficult task. However, there is a practical need for new ideas for neural network ensembles in order to realize the extremely high-performance needs of various rule extraction problems in real life. This paper successively explain nature of artificial neural networks, origin of neural network rule extraction, incorporating fuzziness in neural network rule extraction, theoretical foundation of neural network rule extraction, computational complexity of neural network rule extraction, neuro-fuzzy hybridization, previous rule extraction from neural network ensembles and difficulties of previous neural network ensembles. Next, this paper address three principles of proposed neural network rule extraction: to increase recognition rates, to extract rules from neural network ensembles, and to minimize the use of computing resources. We also propose an ensemble-recursive-rule extraction (E-Re-RX) by two or three standard backpropagation to train multi-layer perceptrons (MLPs), which enabled extremely high recognition accuracy and the extraction of comprehensible rules. Furthermore, this enabled rule extraction that resulted in fewer rules than those in previously proposed methods. This paper summarizes experimental results of rule extraction using E-Re-RX by multiple standard backpropagation MLPs and provides deep discussions. The results make it possible for the output from a neural network ensemble to be in the form of rules, thus open the black box of trained neural networks ensembles. Finally, we provide valuable conclusions and as future work, three open questions on the E-Re-RX algorithm. © 2013 Imperial College Press. Source


Tomita M.,Tokyo Medical and Dental University | Kubota T.,Tama University | Ishioka F.,Okayama University
PLoS ONE | Year: 2015

Objective The number of suicides in Japan has remained high for many years. To effectively resolve this problem, firm understanding of the statistical data is required. Using a large quantity of wide-ranging data on Japanese citizens, the purpose of this study was to analyze the geographical clustering properties of suicides and how suicide rates have evolved over time, and to observe detailed patterns and trends in a variety of geographic regions. Methods Using adjacency data from 2008, the spatial and temporal/spatial clustering structure of geographic statistics on suicides were clarified. Echelon scans were performed to identify regions with the highest-likelihood ratio of suicide as the most likely suicide clusters. Results In contrast to results obtained using temporal/spatial analysis, the results of a period-byperiod breakdown of evolving suicide rates demonstrated that suicides among men increased particularly rapidly during 1988-1992, 1993-1997, and 1998-2002 in certain cluster regions located near major metropolitan areas. For women, results identified cluster regions near major metropolitan areas in 1993-1997, 1998-2002, and 2003-2007. Conclusions For both men and women, the cluster regions identified are located primarily near major metropolitan areas, such as greater Tokyo and Osaka. © 2015 Tomita et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Source


Murata-Soraci K.,Tama University
Psychology of Mindfulness | Year: 2014

In our daily attempt to make sense of life and the world, we come to realize that appropriation of life hinges upon our mindfulness. Being alert to how we dwell in the interior and exterior landscapes of our existence may yet turn around the present modes of living into a salutary condition and/or a better direction. And yet, in what sense(s) does "mindfulness" matter to us for genuinely experiencing our mortal time and for (re-)creation of the world? How successfully does "mindfulness" intervene the psycho-somatic experience of predicaments and enable us to better cope with times of distress and suffering? This book is an interdisciplinary collection of studies on mindfulness explored and discussed by the authors from different walks of life, disciplines and interests. It offers a rich set of interventions related to the practice of mindfulness meditations which effectively reduces human predicaments of menstrual-stress, neurosis, loneliness, anxiety, trauma, forgetfulness, and distress over cancer, fear of dying alone, mourning, etc., gathered by the authors through their research, teaching, and practice from the fields of philosophy, psychology, medicine, therapy, social work, education and fine arts. Most of the authors, even those of hard-nosed empirical scientists, share their concern and disquietude about the dualistic stance of the representational subject and the discriminatory thinking and language of substance and intentionality. They address, covertly or overtly, the difference between the Western mode of reflection and Eastern mode of meditation in the human subject's experience of life and try to integrate various forms of Christian, Hindu, Taoist and Zen meditations into their contexts. The authors in this volume are thus attuned to the menace of recognizable objectivism and objectification of intrinsically interconnected lives of things, and are seeking, through their studies, ways of overcoming a tyranny of the "I" under a zenith of its objectivism in our cultural climate. Accordingly, this volume includes also three informative essays on the Mahayana Buddhist traditions in India and China, Japanese Sôtô Zen practice of Dôgen, and a comparative study of meditation between the Western and the Eastern traditions of spirituality, so as to shed light on the historical and philosophical backgrounds of mindfulness meditation of the far East. This collection of essays closes with mindfulness as an issue of "interspecies, human-animal relations." In order to find a step beyond the epoch of anthropocentrism, this book will extend our alertness to nonhuman animals wherein the essential traits of mankind have been repeatedly drawn and appropriated in the history of man. In conclusion, the book will examine new possibilities in the mind of the reader for seeking a way of authentic co-belonging with other species and of building a new çthos beyond the age of objectivism and anthropocentrism. © 2014 by Nova Science Publishers, Inc. All rights reserved. Source


Okada A.,Tama University
Studies in Classification, Data Analysis, and Knowledge Organization | Year: 2012

Car switching or car trade-in data among car categories were analyzed by a procedure of asymmetric multidimensional scaling. The procedure, which deals with one-mode two-way asymmetric similarities, has originally been introduced to derive the centrality of the asymmetric social network. In the present procedure, the similarity from a car category to the other car category is represented not by the distance in a multidimensional space like the conventional multidimensional scaling, but is represented by the weighted sum of areas with the positive or negative sign along dimensions of a multidimensional space. The result of the analysis shows that attributes which already have been revealed in previous studies accounted for car switching among car categories by a different manner from previous studies, and can more easily be interpreted than the previous studies. © 2012 Springer-Verlag Berlin Heidelberg. Source

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