Yutaka Takahashi

University of Hyogo, Akō, Hyogo-ken, Japan

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Publications (18)0 Total impact

  • M. Nii, Kazuki Nakai, Yutaka Takahashi, K. Maenaka, K. Higuchi
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    ABSTRACT: In order to maintain our healthcare, daily monitoring our physical condition is very important. A multiple microelectromechanical system (MEMS) based monitoring system has been developed. The MEMS based monitoring system is developed for aiming noninvasive and unconstrained monitoring to our physical condition. From a viewpoint of the hardware, the smaller size of such monitoring system is better for us. Additionally, the smaller size is better for power consumption. Therefore, we need to design and develop a very small size of monitoring software. Two-step abstraction method for estimating human behavior had been proposed. In this paper, we propose an extended method of the two-step abstraction for ultra-small hardwares.
    World Automation Congress (WAC), 2012; 01/2012
  • M. Nii, Yutaka Takahashi, A. Uchinuno, R. Sakashita
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    ABSTRACT: In order to improve the nursing-care quality, freestyle Japanese texts which are called “nursing-care texts” are collected through the Internet in Japan. The nursing-care experts can evaluate actual nursing-care and recommend some improvements to nurses by reading the collected nursing-care texts carefully. Since the number of nursing-care experts who can evaluate the nursing-care texts is a few, it is hard to do the above mentioned evaluation process for a large number of nurses. To assist nursing-care experts in evaluating the nursing-care texts, a computer aided nursing-care text classification system has been developed. In this paper, we propose a method to improve the classification performance of the computer aided nursing-care text classification system. Conceptual fuzzy sets are constructed from the collected nursing-care texts and used to make feature vectors in our proposed method.
    World Automation Congress (WAC), 2012; 01/2012
  • [show abstract] [hide abstract]
    ABSTRACT: A monitoring system based on multiple microelectromechanical systems (MEMS) has been developed to maintain human healthcare. Using such a MEMS based monitoring system, several kinds of numerical data from several types of sensors can be measured. Our goal is to develop a intelligent monitoring system with small size. In order to microminiaturize the monitoring system, we need to minimize the power consumption. Therefore, we have to keep our intelligent system simple. We propose a behavior estimation method which consists of a SVM and a fuzzy rule based system to estimate the subject's behavior. Our proposed method consists of two steps of abstraction. First, action primitives are defined. A SVM based classification system is trained using sample numerical data of action primitives. Then, the SVM based system classifies a part of numerical data into one of action primitives. Therefore, whole numerical data are expressed by a sequence of action primitives. Next, a fuzzy rule which maps a sequence of actions onto a behavior is defined for each behavior. In the second-step abstraction, each action sequence is expressed as a behavior by using the defined fuzzy rules. From the results of the abstraction, we can estimate the subject's state.
    Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, Anchorage, Alaska, USA, October 9-12, 2011; 01/2011
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    ABSTRACT: When we use a MEMS based monitoring system for monitoring human behavior, several kinds of numerical data can be measured. In order to develop an intelligent monitoring system with small size, we need to minimize the power consumption. Therefore, we need to develop a simple intelligent system. We have proposed a behavior estimation method which consists of a fuzzy rule based system to estimate the subject $B!G (Bs behavior. In the proposed method, two steps of abstraction for numerical data extract some human behaviors from numerical data. The proposed method can estimate only human behavior such as $B!H (Bwalking $B!I (B or $B!H (Bsitting $B!I (B etc. In this paper, we propose an estimation method that can estimate both human state and behavior. Our proposed method can estimate human state using both heart rate from ECG and human behavior obtained from acceleration sensors. From the results of our proposed method, we show the effectiveness of our proposed method.
    01/2011;
  • Manabu Nii, Kazuki Nakai, Yutaka Takahashi
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    ABSTRACT: To record daily activity for well-maintained human health care, a monitoring system based on multiple microelectromechanical systems (MEMS) has been developed. Several kinds of numerical data of subject's activity can be stored using the MEMS based monitoring system. When we use subject's activity on a single day, a huge volume of data is obtained and recorded. In order to estimate the subject's behavior from such a huge volume data, we propose a behavior estimation method which consists of a SVM and a fuzzy rule based system. Our proposed method consists of two steps of abstraction. First, action primitives are defined and a SVM based classification system is generated from sample numerical data of action primitives or human knowledge. Then, the SVM classifies a part of numerical data into each action primitive. Therefore, numerical data are expressed by a sequence of action primitives. Next, a fuzzy rule which maps a sequence of actions onto a behavior is defined by human user for each behavior. In the second-step abstraction, each action sequence is expressed as a behavior by using the defined fuzzy rules. From the results of the abstraction, we can estimate the subject's state.
    01/2011;
  • [show abstract] [hide abstract]
    ABSTRACT: In this paper, for improving performance of the nursing-care text classification, we introduce a mechanism of retrieving terms from Web. Every year, the nursing-care texts are collected by using Web application to improve nursing-care quality in Japan. The collected nursing-care texts are decomposed into morphemes (i.e., terms), and then terms are stored as a term list. Each text is represented as a feature vector by using the term list and classified using a SVM based classification system. The training data sets for constructing SVM based classification system are different from the evaluation data sets. That is, there are differences between the term lists of the nursing-care texts because the nursing-care texts are collected and evaluated every year. To cover this difference, we introduce a mechanism of retrieving terms from Web. A new term which appeared in the evaluation data sets is used as a query of a search engine. The terms in the term list are also used as queries. Terms are represented by the search results, and then are compared with each other. We use the most similar term in the term list as an alternative of the new term. From experimental results, we show effectiveness of our proposed method.
    FUZZ-IEEE 2011, IEEE International Conference on Fuzzy Systems, Taipei, Taiwan, 27-30 June, 2011, Proceedings; 01/2011
  • JACIII. 01/2010; 14:142-149.
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    ABSTRACT: We define the peculiarity of text as a metric of information credibility. Higher peculiarity means lower credibility. We extract the theme word and the characteristic words from text and check whether there is a subject-description relation between them. The peculiarity is defined using the ratio of the subject-description relation between a theme word and characteristic words. We evaluate the extent to which peculiarity can be used to judge by classifying text from Wikipedia and Uncyclopedia in terms of the peculiarity.
    The Role of Digital Libraries in a Time of Global Change, 12th International Conference on Asia-Pacific Digital Libraries, ICADL 2010, Gold Coast, Australia, June 21-25, 2010. Proceedings; 01/2010
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    ABSTRACT: In this paper, an automatic planning system is developed. By our proposed technique, the vehicle routing planning is optimized using the evolutionary computation. A mutation which sa-tisfies all constraints is designed. Simulation results using real world data show the effectiveness of our developed system. Furthermore, in order to improve in the computational speed by paralleliza-tion, using GPGPU is considered. By parallel implementation of our developed system, computational time is short enough in actual planning of the vehicle routing problems.
    01/2010;
  • [show abstract] [hide abstract]
    ABSTRACT: In order to maintain human health care, it is important to record daily activity. For recording daily human activity, monitoring system which consists of multiple micro electromechanical systems (MEMS) has been developed. Using the MEMS based monitoring system, numerical data of subject's activity can be stored into a database. For example, when subject's activity on a single day is recorded, a huge volume of data is saved. To estimate the subject's activity condition from such a huge volume data, a fuzzy rule based approach is used in our study. Our proposed method consists of two steps of abstraction. First, action primitives are defined. In the first-step abstraction, sensor data is expressed as a sequence of actions by using the defined action primitives. Next, a fuzzy rule which maps a sequence of actions to a behavior is defined for each behavior. In the second-step abstraction, each sequence of actions is expressed as a behavior. From the results of abstraction, we can estimate the subject's state.
    Emerging Trends in Engineering & Technology, International Conference on. 01/2010;
  • Yuko Koba, Takayuki Yumoto, Manabu Nii, Yutaka Takahashi
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    ABSTRACT: People often want to know the names of the objects that they can explain but don't know the names. It is, however, difficult to find such object names using conventional Web search engines. So, we propose a new method for finding the object name from the descriptions given by a user. This method consists of two phases, the extraction phase and the validation phase. In the extraction phase, candidate words are extracted by conducting a Web search using a combination of the queries generated from the user's descriptions. In the validation phrase, each candidate word is validated through a Web search using the candidate word. We rank the candidate words based on the user's description. We evaluated our algorithm by performing several tasks to find the object names from questions in Q&A sites. We also compared it with the methods using queries consisting of all the words in the description and queries consisting of user-selected and user-generated words. The precision by our algorithm was higher than the precision by the other methods.
    01/2010;
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    ABSTRACT: We propose a method for searching for comprehensible how-to information on the Web. In our how-to information search, we use lightweight analysis of Web pages to extract how-to information from Web pages obtained by conventional Web search engines and rank them according to their easily-viewable-degree. In the extraction process, we focus on expressions in Web page text blocks that describe procedures. In the ranking process, we focus on images, the effect of letter string and the length of the how-to information.
    Proceedings of the 3rd International Universal Communication Symposium, IUCS 2009, Tokyo, Japan, 3-4 December 2009; 01/2009
  • Shinya Aoki, Takayuki Yumoto, Manabu Nii, Yutaka Takahashi
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    ABSTRACT: Recently, we have been able to often compare two objects using search engines. However, we often browse high ranked Web pages by search engines, which may give biased information. We propose a method for searching Web pages where two objects are compared using a search engine, extracting comparison points from those Web pages, and showing these points to users. Comparison points are keywords for comparing objects. The proposed method can be used to extract points for efficient comparison by using comparison expressions such as "Liquid Crystal TVs are better ..." and "... than Plasma TVs.", etc.
    Proceedings of the 3rd International Universal Communication Symposium, IUCS 2009, Tokyo, Japan, 3-4 December 2009; 01/2009
  • [show abstract] [hide abstract]
    ABSTRACT: The nursing care quality improvement is very important for our life. Currently, nursing-care freestyle texts (nursing-care data) are collected from many hospitals in Japan by using Web applications. The collected nursing-care data are stored into the database. To evaluate nursing-care data, we have already proposed a fuzzy classification system, a neural network based system, a support vector machine (SVM) based classification system. Then, in order to improve the classification performance, we have proposed a genetic algorithm (GA) based feature selection method for generating numerical data from collected nursing-care texts.In this paper, we propose a fuzzy rule extraction method from the nursing-care text data. First, features of nursing-care texts are selected by a genetic algorithm based feature selection method. Next, numerical training data are generated by using selected features. Then we train neural networks using generated training data. Finally, fuzzy if-then rules are extracted from the trained neural networks by the parallelized rule extraction method.From computer simulation results, we show the effectiveness of our proposed method.
    ISMVL 2009, 39th International Symposium on Multiple-Valued Logic, 21-23 May 2009, Naha, Okinawaw, Japan; 01/2009
  • Journal of Japan Society for Fuzzy Theory and Intelligent Informatics 01/2008; 20(1):9-18.
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    ABSTRACT: The nursing care quality improvement is very important in the medical field. Currently, nursing-care freestyle texts (nursing-care data) are collected from many hospitals in Japan by using Web applications. Some nursing-care ex- perts evaluate the collected data to improve nursing care quality. For evaluating the nursing-care data, experts need to read all freestyle texts carefully. However, it is a hard task for an expert to evaluate the data because of huge number of nursing-care data in the database. In order to reduce work- loads evaluating nursing-care data, we propose a support vector machine(SVM) based classification system.
    Granular Computing, 2007. GRC 2007. IEEE International Conference on; 12/2007
  • Proceedings of the 3rd International Symposium on Autonomous Minirobots for Research and Edutainment (AMiRE 2005), Awara-Spa, Fukui, Japan, September 20-22, 2005; 01/2005
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    ABSTRACT: When one application needs results calculated by another application simulating different phenomena to simulate some phenomena, users must write communication codes to exchange data between two applications. Because users require to program codes as simple as possible in general, writing communication codes should be more easier. It is, however, complicated for users to implement these codes using the existing method. In this paper, we have proposed the Distributed Computing Collaboration Protocol as a simple user interface for communication between application programs.
    Parallel and Distributed Computing: Applications and Technologies, 5th International Conference, PDCAT 2004, Singapore, December 8-10, 2004, Proceedings; 01/2004