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University of Yamanashi, Japan

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24 Papers

Development of Flow Rate Feedback Control in Tilting-ladle-type Pouring Robot with Direct Manipulation of Pouring Flow Rate

Topics: Human-Robots Interfaces; Mechatronics Systems; Engineering Applications on Robotics and Automation

Authors: Yuta Sueki and Yoshiyuki Noda

Affiliation: Department of Mechanical Engineering, University of Yamanashi, 4-3-11, Takeda, Kofu, 400-8511 and Japan

Digital Object Identifier: 10.5220/0007951004600467

Proceedings of ICINCO 2019, ISBN: 978-989-758-380-3

Quick Abstract

This paper describes the advanced control technology for the tilting-ladle-type pouring robots in the casting industry. In the pouring process in which the molten metal is poured into the pouring basin of the mold by tilting the ladle, it is difficult to pour the molten metal as desired pouring flow rate by the operator. Because the pouring flow rate is manipulated indirectly by manipulating the ladle’s angle. In order to solve this problem, in previous studies, we developed the direct manipulation system of the pouring flow rate in the pouring robots. However, the error between the desired and the actual pouring flow rate can be caused by the disturbances in the pouring condition. Therefore, in this study, we develop the pouring flow rate feedback control for improving the tracking performance. In this approach, the pouring flow rate can be estimated by using the extended Kalman filter, and the feedback controller can be constructed by the gain-scheduled PID control based on the estimated flow rate. The developed system is applied to the laboratory-type pouring robot. According to the experiments, the operator can manipulate the pouring flow rate as desired, even in the pouring condition with the disturbance.

Related Ontology Subjects/Areas/Topics (4)

Human-Robots Interfaces		Mechatronics Systems		Robotics and Automation
Informatics in Control, Automation and Robotics

Integrating Internet Directories by Estimating Category Correspondences

Topic: Integration and Interoperability

Authors: Yoshimi Suzuki and Fumiyo Fukumoto

Affiliation: Graduate Faculty of Interdisciplinary Research, University of Yamanashi and Japan

Digital Object Identifier: 10.5220/0008354104270434

Proceedings of KEOD 2019, ISBN: 978-989-758-382-7

Quick Abstract

This paper focuses on two existing category hierarchies and proposes a method for integrating these hierarchies into one. Integration of hierarchies is proceeded based on semantically related categories which are extracted by using text categorization. We extract semantically related category pairs by estimating category correspondences. Some categories within hierarchies are merged based on the extracted category pairs. We assign the remaining categories to a newly constructed hierarchy. To evaluate the method, we applied the results of new hierarchy to text categorization task. The results showed that the method was effective for categorization.

Is (President,大統領) a Correct Sense Pair? - Linking and Creating Bilingual Sense Correspondences

Topics: Natural Language Processing; Knowledge Acquisition

Authors: Fumiyo Fukumoto , Yoshimi Suzuki and Attaporn Wangpoonsarp

Affiliation: University of Yamanashi, Japan

Digital Object Identifier: 10.5220/0006489900390048

Proceedings of KEOD 2017, ISBN: 978-989-758-272-1

Quick Abstract

This paper presents a method of linking and creating bilingual sense correspondences between English and Japanese noun word dictionaries. Locally, we extracted bilingual noun words using sentence-based similarity. Globally, for each monolingual dictionary, we identified domain-specific senses using a textual corpus with category information. We incorporated these, i.e., we assigned a sense to each noun word of the extracted bilingual words keeping domain (category) consistency. Evaluation on the WordNet 3.0 and EDR Japanese dictionaries using Reuters andMainichi Japanese newspaper corpora showed 23.1% improvement of bilingual noun word extraction over the baseline with local data view only. Moreover, we found that the extracted bilingual noun senses can be used as a lexical resource for the machine translation.

Related Ontology Subjects/Areas/Topics (8)

Applications	Knowledge Engineering and Ontology Development	Pattern Recognition
Artificial Intelligence	Knowledge-Based Systems	Symbolic Systems
Knowledge Acquisition	Natural Language Processing

Prediction of Company's Trend based on Publication Statistics and Sentiment Analysis

Topics: Business Intelligence Applications; User Profiling and Recommender Systems

Authors: Fumiyo Fukumoto ¹ , Yoshimi Suzuki ¹ , Akihiro Nonaka ¹ and Karman Chan ²

Affiliations: ¹ Univ. of Yamanashi, Japan , ² IIJ Innovation Institute Inc., Japan

Digital Object Identifier: 10.5220/0006048602830290

Proceedings of KDIR 2016/IC3K, ISBN: 978-989-758-203-5

Quick Abstract

This paper presents a method for predicting company’s trend on research and development(R&D) in business area. We used three types of data collections, i.e, scientific papers, open patents, and newspaper articles to estimate temporal changes of trends on company’s business area. We used frequency counts on scientific papers and open patents to be published in time series. For news articles, we applied sentiment analysis to extract positive news reports related to the company’s business areas, and count their frequencies. For each company, we then created temporal changes based on these frequency statistics. For each business area, we clustered these temporal changes. Finally, we estimated prediction models for each cluster. The results show that the the model obtained by combining three data is effective to predict company’s future trends, especially the results show that SP clustering contributes overall performance.

Related Ontology Subjects/Areas/Topics (6)

Artificial Intelligence		Knowledge Discovery and Information Retrieval		Symbolic Systems
Business Intelligence Applications		Knowledge-Based Systems		User Profiling and Recommender Systems

Opinion Extraction from Editorial Articles based on Context Information

Topics: Natural Language Processing; Knowledge Acquisition

Authors: Yoshimi Suzuki and Fumiyo Fukumoto

Affiliation: University of Yamanashi, Japan

Digital Object Identifier: 10.5220/0005633503750380

Proceedings of KEOD 2015/IC3K, ISBN: 978-989-758-158-8

Quick Abstract

Opinion extraction supports various tasks such as sentiment analysis in user reviews for recommendations and editorial summarization. In this paper, we address the problem of opinion extraction from newspaper editorials. To extract author’s opinion, we used context information addition to the features within a single sentence only. Context information are a location of the target sentence, and its preceding, and succeeding sentences. We defined the opinion extraction task as a sequence labeling problem, using conditional random fields (CRF). We used Japanese newspaper editorials in the experiments, and used multiple combination of features of CRF to reveal which features are effective for opinion extraction. The experimental results show the effectiveness of the method, especially, predicate expression, location and previous sentence are effective for opinion extraction.

Related Ontology Subjects/Areas/Topics (8)

Applications	Knowledge Engineering and Ontology Development	Pattern Recognition
Artificial Intelligence	Knowledge-Based Systems	Symbolic Systems
Knowledge Acquisition	Natural Language Processing

Temporal-based Feature Selection and Transfer Learning for Text Categorization

Topics: Clustering and Classification Methods; Information Extraction

Authors: Fumiyo Fukumoto and Yoshimi Suzuki

Affiliation: University of Yamanashi, Japan

Digital Object Identifier: 10.5220/0005593100170026

Proceedings of KDIR 2015/IC3K, ISBN: 978-989-758-158-8

Quick Abstract

This paper addresses text categorization problem that training data may derive from a different time period from the test data. We present a method for text categorization that minimizes the impact of temporal effects. Like much previous work on text categorization, we used feature selection. We selected two types of informative terms according to corpus statistics. One is temporal independent terms that are salient across full temporal range of training documents. Another is temporal dependent terms which are important for a specific time period. For the training documents represented by independent/dependent terms, we applied boosting based transfer learning to learn accurate model for timeline adaptation. The results using Japanese data showed that the method was comparable to the current state-of-the-art biased-SVM method, as the macro-averaged F-score obtained by our method was 0.688 and that of biased-SVM was 0.671. Moreover, we found that the method is effective, especially when the creation time period of the test data differs greatly from that of the training data.

Related Ontology Subjects/Areas/Topics (6)

Artificial Intelligence		Information Extraction		Knowledge-Based Systems
Clustering and Classification Methods		Knowledge Discovery and Information Retrieval		Symbolic Systems

2-D Load Transfer Control Considering Obstacle Avoidance and Vibration Suppression

Topics: Supply Chain and Logistics Engineering; Industrial Automation and Robotics; Intelligent Design and Manufacturing; Manufacturing Systems Engineering

Authors: Junichi Nakajima and Yoshiyuki Noda

Affiliation: University of Yamanashi, Japan

Digital Object Identifier: 10.5220/0005030806530660

Proceedings of ICINCO 2014, ISBN: 978-989-758-040-6

Quick Abstract

This paper is concerned with an advanced transfer control for load transfer machines such as a crane. In the load transfer machine, it is required to carry the load efficiently and safety. In order to satisfy this requirement, fast transfer of load, obstacle avoidance and vibration suppression have to be accomplished in the load transfer system. Therefore in this study, the load transfer control system which the transfer trajectory on a plane is optimized in consideration of the vibration suppression, obstacles avoidance and fast transfer is proposed. Moreover, in order to optimize the trajectory in a short time, the fast solution approach is also proposed in this study. The effectiveness of the proposed transfer control system is verified by the experiments using the laboratory type overhead traveling crane system.

Related Ontology Subjects/Areas/Topics (6)

Industrial Automation and Robotics		Informatics in Control, Automation and Robotics		Manufacturing Systems Engineering
Industrial Engineering		Intelligent Design and Manufacturing		Supply Chain and Logistics Engineering

Incorporating Guest Preferences into Collaborative Filtering for Hotel Recommendation

Topics: User Profiling and Recommender Systems; Collaborative Filtering

Authors: Fumiyo Fukumoto , Hiroki Sugiyama , Yoshimi Suzuki and Suguru Matsuyoshi

Affiliation: Univ. of Yamanashi, Japan

Digital Object Identifier: 10.5220/0005034000220030

Proceedings of KDIR 2014/IC3K, ISBN: 978-989-758-048-2

Quick Abstract

Collaborative filtering (CF) has been widely used as a filtering technique because it is not necessary to apply more complicated content analysis. However, it is difficult to take users’ preferences/criteria related to the aspects of a product/hotel into account. This paper presents a method of hotel recommendation that incorporates different aspects of a product/hotel to improve quality of the score. We used the results of aspect-based sentiment analysis for guest preferences. The empirical evaluation using Rakuten Japanese travel data showed that aspect-based sentiment analysis improves overall performance. Moreover, we found that it is effective for finding hotels that have never been stayed at but share the same neighborhoods.

Related Ontology Subjects/Areas/Topics (6)

Artificial Intelligence		Knowledge Discovery and Information Retrieval		Symbolic Systems
Collaborative Filtering		Knowledge-Based Systems		User Profiling and Recommender Systems

Operational Assistance System using 3-DOF Joystick with Reaction Force Display to Load Transfer Machine in a Plane

Topics: Human-Robots Interfaces; Intelligent Transportation Technologies and Systems; Human-Machine Interfaces; Mechatronics Systems; Engineering Applications

Authors: Tomoya Kuneguchi ¹ , Yoshiyuki Noda ¹ , Yukinori Sago ² and Kiyoaki Kakihara ³

Affiliations: ¹ University of Yamanashi, Japan , ² Toyohashi University of Technology, Japan , ³ KER Co. and Ltd, Japan

Digital Object Identifier: 10.5220/0005026303460352

Proceedings of ICINCO 2014, ISBN: 978-989-758-040-6

Quick Abstract

This paper is concerned with an operational assistance system to a load transfer machine in a plane such as a manually guided vehicle and a crane without vertical transfer. In the transfer machine, collisions with obstacles are often occurred by the incorrect operations. Therefore, in order to avoid the obstacles to the transfer machine, the operational assistance system using 3-DOF(3 Degree of Freedom) joystick with reaction force display is proposed in this study. The 3-DOF joystick enables operator to manipulate the transfer machine with back-and-forth, left-and-right, and rotation motions. And, it has motors for presenting the reaction force on each axis. In this system, the joystick displays the reaction force which consists of the virtual elastic force and viscosity resistance, which are controlled by PD control gains. By associating the gains in the PD control with the distance between the obstacles and the transfer object, the joystick operation is constrained for avoiding the obstacles. The effectiveness of the proposed operational assistance system is verified by the experiments using the simulator of the transfer machine manipulated by the 3-DOF joystick.

Related Ontology Subjects/Areas/Topics (9)

Engineering Applications	Informatics in Control, Automation and Robotics	Mechatronics Systems
Human-Machine Interfaces	Intelligent Control Systems and Optimization	Robotics and Automation
Human-Robots Interfaces	Intelligent Transportation Technologies and Systems	Signal Processing, Sensors, Systems Modeling and Control

Support for Motor Learning by Visualizing the Similarity of Sports Form - Examining Effective Image Features in Back Hip Circle Videos of Children

Topics: Multimedia and Information Technology; Motor Learning; Training and Testing; Coaching; Computer Supported Training and Decision Support Systems

Authors: Ayumi Matsumoto ¹ , Dan Mikami ¹ , Harumi Kawamura ¹ , Akifumi Kijima ² and Akira Kojima ¹

Affiliations: ¹ Nippon Telegraph and Telephone Corporation, Japan , ² University of Yamanashi, Japan

Quick Abstract

The goal of our study is to propose systems that can support motor learning and coaching for users (or teachers) without requiring any detailed knowledge of sports. We propose a system that can visualize similarities in “ form ” as the term applies to sports (e.g., batting form, hurdling form) and an instruction method that will automatically be suitable for the person using it. As a step toward this goal, in this paper we propose a framework for the similarity visualization that is based on similarities in form and optimal image features for classifying similarities in target forms in sports actions that require different lengths of time to perform. We performed form classification experiments with the aim of determining appropriate image features in order to visualize form similarities. The highest classification precision was obtained with BoVW by applying a sliding window to back hip circle videos.

Related Ontology Subjects/Areas/Topics (9)

Coaching	Health, Sports Performance and Support Technology	Signal Processing and Motor Behavior
Computer Supported Training	Motor Learning	Sport Science Research and Technology
Computer Systems in Sports	Multimedia and Information Technology	Training and Testing

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