Forest information in Japan is managed by using Geographic Information System (GIS). However, GIS has not been fully utilized because there are no human resources capable of operating it in forestry association. There is possibility of increasing the burden because the operation of the system is complicated. This paper describes the implementation of the forest GIS software specialized for required functions that can easily operate. We asked Ayabe City Forestry Association to cooperate, investigated the existing system and usage situation, and created forest GIS software which can easily operate with only necessary function.
{"title":"Development of Forest Information Management DB System Considering Ease of Use","authors":"K. Nozaki, T. Hochin, Hiroki Nomiya","doi":"10.1109/CSII.2018.00029","DOIUrl":"https://doi.org/10.1109/CSII.2018.00029","url":null,"abstract":"Forest information in Japan is managed by using Geographic Information System (GIS). However, GIS has not been fully utilized because there are no human resources capable of operating it in forestry association. There is possibility of increasing the burden because the operation of the system is complicated. This paper describes the implementation of the forest GIS software specialized for required functions that can easily operate. We asked Ayabe City Forestry Association to cooperate, investigated the existing system and usage situation, and created forest GIS software which can easily operate with only necessary function.","PeriodicalId":202365,"journal":{"name":"2018 5th International Conference on Computational Science/ Intelligence and Applied Informatics (CSII)","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130343168","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper proposes a clustering algorithm for updating clusters without reclustering when a point is inserted. We define the center and the radius of the cluster, and update clustering results of points using them. We introduce the concept of outliers and also consider the change in the number of clusters caused by data insertion. From comparative experiments with reclustering by the conventional method, it is shown that the proposed method can cluster points with short calculation time.
{"title":"Incremental Clustering for Hierarchical Clustering","authors":"K. Narita, T. Hochin, Hiroki Nomiya","doi":"10.1109/CSII.2018.00025","DOIUrl":"https://doi.org/10.1109/CSII.2018.00025","url":null,"abstract":"This paper proposes a clustering algorithm for updating clusters without reclustering when a point is inserted. We define the center and the radius of the cluster, and update clustering results of points using them. We introduce the concept of outliers and also consider the change in the number of clusters caused by data insertion. From comparative experiments with reclustering by the conventional method, it is shown that the proposed method can cluster points with short calculation time.","PeriodicalId":202365,"journal":{"name":"2018 5th International Conference on Computational Science/ Intelligence and Applied Informatics (CSII)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130298261","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The well-known NP-hard traveling salesman problem (TSP) primarily considers distance as its single objective. However, applications modeled from real world systems repeatedly involve more than one objective giving rise to multi-objective optimization. Fusing ideas of dimension reduction, decomposition approaches, and genetic algorithms, this paper presents a multiobjective minimum matrix search algorithm (MOMMS) for the heuristic resolution of the bi-objective TSP (bTSP). The MOMMS uses dimension reduction to obtain a reduce matrix network that is used to obtain or to approximate the set of efficient solutions. The reduce matrix network aids in the decomposition of a multiobjective combinatorial optimization (MOCO) problem into a single objective combinatorial optimization problem. Moreover, using the reduce matrix network MOMMS introduces a population generator that creates an initial population composed of an approximation to the extreme supported efficient solutions. The MOMMS does not use any numerical parameter. Also, MOMMS uses family competitive metamorphosis and short-term memory selection to maintain population diversity in MOCO problems. The proposed algorithm showed respectable results in testing on well-known benchmark problems of the bTSP. Comparisons are performed with the results of state-of-the-art algorithms from the literature. Moreover, the MOMMS is tested on largescale instances of the bTSP. The computational study shows that the proposed algorithm is able to solve large-scale instances in reasonable time. Therefore, the MOMMS is a competitive tool for solving the bTSP.
{"title":"A Multi-Objective Minimum Matrix Search Algorithm Applied to Large-Scale Bi-Objective TSP","authors":"M. M. Smith, Yun-Shiow Chen","doi":"10.1109/CSII.2018.00017","DOIUrl":"https://doi.org/10.1109/CSII.2018.00017","url":null,"abstract":"The well-known NP-hard traveling salesman problem (TSP) primarily considers distance as its single objective. However, applications modeled from real world systems repeatedly involve more than one objective giving rise to multi-objective optimization. Fusing ideas of dimension reduction, decomposition approaches, and genetic algorithms, this paper presents a multiobjective minimum matrix search algorithm (MOMMS) for the heuristic resolution of the bi-objective TSP (bTSP). The MOMMS uses dimension reduction to obtain a reduce matrix network that is used to obtain or to approximate the set of efficient solutions. The reduce matrix network aids in the decomposition of a multiobjective combinatorial optimization (MOCO) problem into a single objective combinatorial optimization problem. Moreover, using the reduce matrix network MOMMS introduces a population generator that creates an initial population composed of an approximation to the extreme supported efficient solutions. The MOMMS does not use any numerical parameter. Also, MOMMS uses family competitive metamorphosis and short-term memory selection to maintain population diversity in MOCO problems. The proposed algorithm showed respectable results in testing on well-known benchmark problems of the bTSP. Comparisons are performed with the results of state-of-the-art algorithms from the literature. Moreover, the MOMMS is tested on largescale instances of the bTSP. The computational study shows that the proposed algorithm is able to solve large-scale instances in reasonable time. Therefore, the MOMMS is a competitive tool for solving the bTSP.","PeriodicalId":202365,"journal":{"name":"2018 5th International Conference on Computational Science/ Intelligence and Applied Informatics (CSII)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123793880","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Md. Tahsin Tausif, S. A. Chowdhury, Md. Shiplu Hawlader, Mohammed Hasanuzzaman, Hasnain Heickal
Speech-To-Text conversion is the process of recognizing speech in audio and producing a text transcript for it. Due to speech being such an intuitive medium of communication, this technology can have far reaching effects in easing the interaction between humans and machine. This paper presents a complete speech-to-text conversion system for the Bangla language (also known as Bengali) using Deep Recurrent Neural Networks. Possible optimization such as Broken Language Format has been proposed which is based on properties of the Bangla Language for reducing the training time of the network. A simple deep recurrent neural network architecture has been used for speech recognition. It was trained with collected data and which yielded over 95% accuracy in case of training data and 50% accuracy in case of testing data.
{"title":"Deep Learning Based Bangla Speech-to-Text Conversion","authors":"Md. Tahsin Tausif, S. A. Chowdhury, Md. Shiplu Hawlader, Mohammed Hasanuzzaman, Hasnain Heickal","doi":"10.1109/CSII.2018.00016","DOIUrl":"https://doi.org/10.1109/CSII.2018.00016","url":null,"abstract":"Speech-To-Text conversion is the process of recognizing speech in audio and producing a text transcript for it. Due to speech being such an intuitive medium of communication, this technology can have far reaching effects in easing the interaction between humans and machine. This paper presents a complete speech-to-text conversion system for the Bangla language (also known as Bengali) using Deep Recurrent Neural Networks. Possible optimization such as Broken Language Format has been proposed which is based on properties of the Bangla Language for reducing the training time of the network. A simple deep recurrent neural network architecture has been used for speech recognition. It was trained with collected data and which yielded over 95% accuracy in case of training data and 50% accuracy in case of testing data.","PeriodicalId":202365,"journal":{"name":"2018 5th International Conference on Computational Science/ Intelligence and Applied Informatics (CSII)","volume":"01 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127371582","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Makoto Takamatsu, Tsuyoshi Tomioka, Eizaburo Iwata, M. Hasegawa
Social graph analysis using Bluetooth radio transmitters called "Beacon" is discussed in this paper. Each person carries the beacon and a smart phone; the smart phone is performed for a receiver. Someone's smart phone can recognize another person's beacon and the distance between the two persons. As the result, our social graph can be generated using those data. Graph pruning is necessary, and we discuss how to determine the two threshold parameters for the distance between two persons and the received signal reception frequency. We show one guideline to determine the two threshold. A system simulation is shown in our experiments.
{"title":"A Study on Social Graph Analysis Using Beacon Bluetooth Radio Transmitter","authors":"Makoto Takamatsu, Tsuyoshi Tomioka, Eizaburo Iwata, M. Hasegawa","doi":"10.1109/CSII.2018.00023","DOIUrl":"https://doi.org/10.1109/CSII.2018.00023","url":null,"abstract":"Social graph analysis using Bluetooth radio transmitters called \"Beacon\" is discussed in this paper. Each person carries the beacon and a smart phone; the smart phone is performed for a receiver. Someone's smart phone can recognize another person's beacon and the distance between the two persons. As the result, our social graph can be generated using those data. Graph pruning is necessary, and we discuss how to determine the two threshold parameters for the distance between two persons and the received signal reception frequency. We show one guideline to determine the two threshold. A system simulation is shown in our experiments.","PeriodicalId":202365,"journal":{"name":"2018 5th International Conference on Computational Science/ Intelligence and Applied Informatics (CSII)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125029617","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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