Takumi Ichimura

Tohoku University

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Shin Kamada

Hiroshima City University

Akira Hara

Kyoto University

Kazuya Mera

Hiroshima City University

Tetsuyuki Takahama

Hiroshima City University

Muneo Hori

Japan Agency for Marine-Earth Science and Technology

Toshiyuki Yamashita

Tokyo Metropolitan University

Shinichi Oeda

National Institute of Technology, Kisarazu College

Katsumi Yoshida

Tokyo Institute of Technology

Yoshiaki Kurosawa

Hiroshima City University

Kenneth J. Mackin

Tokyo University of Information Sciences

Cooperative Institutions

The University of Tokyo

Tohoku University

Hiroshima City University

University of Tsukuba

Osaka University

Kyoto University

Prefectural University of Hiroshima

Spintronics Research Network of Japan

SPring-8

Kyushu University

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A video prediction method by using long short-term memory-based adaptive structural learning of deep belief network and its investigation of input sequence length for data structure

International Journal of Computational Intelligence Studies (2021)

Shin Kamada Takumi Ichimura

In our research, the adaptive structural learning method using RBM and DBN has been developed as a deep learning model, which can find a suitable size of network structure for given input space during its training. The adaptive RBM and DBN were extended to the time-series prediction using the idea of long short-term memory (LSTM). Our previous research tackled the problems for supervised learning, in this paper, we challenge to reveal the power of our proposed method in the video recognition using Moving MNIST, which is a benchmark dataset for video recognition. Adaptive LSTM-DBN trained the time-series movement from the video data and it showed higher future prediction performance than the existing LSTM models (more than 90% for test data). Moreover, the detailed prediction results were investigated by training adaptive LSTM-DBN with various length of input sequence in the experiment results.

Sequence (biology)

Deep belief network

10.1504/ijcistudies.2021.10038082

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Immune Multi Agent Neural Network and Its Application to the Coronary Heart Disease Database

Lecture notes in computer science (2004)

Shinichi Oeda Takumi Ichimura Katsumi Yoshida

Training set

10.1007/978-3-540-30133-2_146

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Citations (7)

Using Mitate-shi Related to the CONTAINER Schema for Detecting the Container-for-Contents Metonymy

Lecture notes in computer science (2004)

Yoshiaki Kurosawa Takumi Ichimura Teruaki Aizawa

Schema (genetic algorithms)

10.1007/978-3-540-30133-2_21

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A Proposal of recommendation application for Tourism Resource Based Participatory Sensing Data analysis

IEICE Technical Report; IEICE Tech. Rep. (2016)

Takumi Ichimura Kamada Shin

Source

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Web intelligence for tourism using railway data by a simplified fuzzy reasoning method

Journal of Intelligent & Fuzzy Systems (2013)

Takashi Hasuike Takumi Ichimura

This paper proposes an approach to analyze the tourism information and data derived from the Web, particularly seat availability data of bullet trains in Japan, and to discover some useful knowledge for the tourism. For the fast development of inform

10.3233/ifs-2012-0551

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Citations (6)

Emergence of altruism behavior in army ant-based social evolutionary system

SpringerPlus (2014)

Takumi Ichimura Takuya Uemoto Akira Hara Kenneth J. Mackin

Army ants perform the altruism behavior that an ant sacrifices its own well-being for the benefit of another ants. They build bridges using their own bodies along the path from a food to the nest. We developed the army ant inspired social evolutionary system by using Swarm library. The system has 2 kinds of ant agents, ‘Major ant’ and ‘Minor ant’. They communicate with each other via pheromones. Army ant can recognize them as the signals from the other ants. The pheromones evaporate with the certain ratio and diffused into the space of neighbors stochastically. If the optimal bridge is found, the path through the bridge is the shortest route from the food to the nest. We define the probability for an ant to leave a bridge as to the number of neighboring ants. The constructing method of the optimal route has been proposed. In this paper, the behaviors of ant under the environment with two or more feeding spots were observed. Some experimental results show the behaviors of great interest with respect to altruism of ants. The knowledge discovery of social evolutionary process from some computer simulation results is described in this paper.

Ant colony

Altruism

Bridge (graph theory)

Eusociality

10.1186/2193-1801-3-712

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A classification method for spam e-mail by Self-Organizing Map and automatically defined groups

Takumi Ichimura Akira Hara Yoshiaki Kurosawa Takumi Ichimura Akira Hara

We have some difficulties in E-mails as a communication tool, because the number of E-mails infected with virus and/or recognized as Spam increases. Some E-mail filter softwares removes such problematic ones. However, we may mett the misjudgements for the filtering the Spam E-mail, even if the E-mail is important and then we cannot receive it. In this paper, we propose a classification method for Spam E-mail based on the results of SpamAssassin, which is the open source software to identify spam signatures. This method can learn patterns of Spam E-mails and Ham ones and correctly recognize them. First, the method divides Emails into some categories by Self-Organizing Map(SOM) and extracts the correct judgement rules by Automatically Defined Groups(ADGs), even if the results by SpamAssassin are wrong. In order to verify the effectiveness of our proposed method, we examined approximately 3,000 E-mails.

Electronic mail

Judgement

10.1109/icsmc.2007.4413626

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Citations (12)

A Classification Capability of Reflective Neural Networks in Medical Databases

Takumi Ichimura Shinichi Oeda Machi Suka Kunihiro Yoshida

Medical database recorded diagnostic information based on a patient’s medical card. However, each card does not fulfill all the required information for learning algorithm. Reflective Neural Network has an outstanding classification capability, even if such records with shortage exist in a set of training cases. Reflective Neural Network is based on the network module concept. There are two kinds of network modules; an allocation module to distribute a training case and some classification modules to classify a subset of training cases. Each classification module consists of a monitor neural network and a worker neural network. The monitor neural network estimates how conformable the worker neural network is to a given training case. Moreover, the training case is distributed over different classification modules. These classification modules compete with each other in the classification task. In this paper, we report the classification capability in a medical database on the patients in ICUs.

Economic shortage

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Mobile Healthcare System for Preventive of Metabolic Syndrome

Hiroshi Inoue Takumi Ichimura

Recently, metabolic syndrome affects a great number of people in Japan. Glycemic control can delay the onset and slow the progression of vascular complications. Lifestyle modification including weight reduction can contribute significantly to glycemic control. This paper describes the mobile application of the healthcare support system for metabolic patients.

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Altruistic behaviours-based recommendation system of tourist information from smartphone application to SNS community

International Journal of Computational Intelligence Studies (2017)

Takumi Ichimura Takuya Uemoto Shin Kamada

We have already developed the recommendation system of sightseeing information on SNS by using smartphone based user participatory sensing system. Our smartphone application can collect tourist subjective data which includes jpeg files with GPS, geographic location name, the evaluation, and comments written in natural language at sightseeing spot. The system can post the attractive information for tourists to the specified Facebook page directly by our developed smartphone application. Moreover, the system can recommend the sightseeing spot and the local food corresponded to the user's feeling which can be estimated at the sightseeing spot by emotion generating calculations (EGC). The users in Facebook, who are interested in sightseeing, can come to crowd the posted articles at the cyber space. However, the current activities in the SNS community are only supported by the specified people called a hub. We proposed the method of vitalisation of tourist behaviors to give a stimulus to the Facebook users. We developed the simulation system for multi-agent system with altruistic behaviors inspired by the army ants. The army ant takes feeding action with altruistic behaviours to suppress selfish behaviour to a common object. In this paper, we introduced the altruism behaviour determined by some simulation to vitalise the SNS community. The efficiency of the revitalisation process of the community was investigated by some experimental simulation results.

Participatory Sensing

10.1504/ijcistudies.2017.10010609

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Citations (1)