Browsing by Author "Fuangfar Pensiri"

Now showing 1 - 6 of 6
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    Clustering tourist using DBSCAN algorithm
    (American Institute of Physics Inc., 2022) Fuangfar Pensiri; Porawat Visutsak; Orawan Chaowalit; O. Chaowalit; King Mongkut's University of Technology North Bangkok University, Bangkok, 1518 Pracharat 1 Road Wongsawang Bangsue, 10800, Thailand; email: orawan@su.ac.th
    The tourist clustering refer the aggregating of prospective tourist into different groups with common observance by using statistical data analysis technique. In this paper, we apply the Density-based spatial clustering of applications with noise (DBSCAN) to find the factors that can segment the tourist associated with using digital technology equipment as a tourism facility based on the data of tourist behaviour and activity. We describe the methodology, firstly analyse the algorithm. Secondly, compare execution of the different parameter values (Eps): the maximum radius of the neighbourhood from core point and the minimum number of points required to form a dense region (MinPts). Finally, examine the outcome of the application, Tourist's career and tourism style are two factors from eleven factors can cluster the tourists into eight groups with Eps and MinPts parameters 0.5 and 10 respectively. © 2022 Author(s).
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    Development of Digital Media using Augmented Reality for HM King Prajadhipok's Interests in Arts and Culture
    (Institute of Electrical and Electronics Engineers Inc., 2018) Porawat Visutsak; Fuangfar Pensiri
    For Thai people, the kingship is just not the institution; Thai people respect the King like the father of the land. The good evidence to show that the kingship is revered by Thai people and admired throughout the world is the statement given by the president of the 71st session of the UN general assembly plenary meeting to pay tribute to HM King Bhumibol Adulyadej (King Rama IX), who passed away on 13 October 2016. In the past few years, to study the history of Thailand according to each reign of the dynasty, Thai people need to study the documents, the media and films from the various data sources. With the current trends of the augmented reality and digital technologies, people can study the multimodal media interactively at hands. This study aims to gather evidences and archives of HM King Prajadhipok, the 7th King of the House of Chakri (King Rama VII). The current study of HM King Prajadhipok is mostly focusing on the political conflicts and social changes during the Revolution of 1932. Documents and media about HM King Prajadhipok's interests in arts, music, paintings and films have not been yet gathered and archived successfully. The main contribution of this work has been installed in the archival King Prajadhipok study room, the office of documentation and information, Sukhothai Thammathirat Open University (STOU), Bangkok, Thailand. The virtual contents consist of photographs, documents and films concerning the HM King Prajadhipok's life during his reign and after the abdication. The archival of this work mainly focuses on the architectures, the royal's song writing, films making and paintings to promote his interests in arts and culture. � 2018 IEEE.
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    Durian cultivar recognition using discriminant function
    (Institute of Electrical and Electronics Engineers Inc., 2017) Fuangfar Pensiri; Porawat Visutsak
    The distinction of the Durian Cultivar is its physical characteristics such as smell, thorn's color, the resonant sound when knocking the husk. This research study which characteristics can classify the two popular Durian Cultivar; 'Chanee' and 'Monthong'. The array of thorns in vertical, horizontal and diagonal and the geometric lines at the thorn's bases; rectangular, pentagon, hexagon and heptagon were the features used in this study. The process starts with Durian image edge detection to obtain the outline for identifying the position of thorn's peaks and the geometric outlines. The attributes are analyzed by the Linear Discriminant Analysis Method. The experimental results show that Durian Cultivar can be classified according to the thorn's array in vertical and horizontal. The results provide the efficient performance of classifier. The accuracy of the discriminative model is 94.44%. � 2017 IEEE.
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    Image Analysis of Mushroom Types Classification by Convolution Neural Networks
    (Association for Computing Machinery, 2019) Jitdumrong Preechasuk; Orawan Chaowalit; Fuangfar Pensiri; Porawat Visutsak
    Mushrooms are fungi. The edible mushrooms include nutritional content and health benefits. However, some mushroom species is toxic and contains poisonous substances that could cause illness and lead to death. Mushroom poisoning accounts for approximately 70% of natural poisoning and often causes death. However, there are only 30-50 poisonous species among the thousands of species found on earth, and of these, no more than 10 are fatally poisonous [1]. The main reason of eating poisonous mushrooms is the lack of knowledge and skill to classify the edible and poisonous mushrooms. Besides, the physical characteristics of mushrooms are similar. Therefore, this work focuses on the classification of 45 types of mushrooms. This work aims to reduce the number of illness persons whom are risk of exposure to toxic mushrooms. This work proposes a new model of classifying 45 types of mushrooms including edible and poisonous mushrooms by using a technique of Convolution Neural Networks. The proposed model was tested on both types of mushroom. It was trained to construct the CNN models and used the trained models to classify all types of mushroom. The proposed model gives the results of 0.78, 0.73 and 0.74 of precision, recall and F1 score, respectively. It concluded that the proposed model can classify types of mushroom image with efficiently and effectively. � 2019 ACM.
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    Smooth voxel surface for medical volumetric rendering
    (SPIE, 2019) Porawat Visutsak; Fuangfar Pensiri; Orawan Chaowalit
    This paper aims to implement the trilinear interpolation algorithm with the marching cubes method for generating the smooth voxel surface from 2D digital images. The trilinear interpolation is a straight extension of the bilinear interpolation technique. It can be seen as the linear interpolation of two bilinear interpolations. The novel method is a fast and easy to implement and it also produces a smooth results (compared to the marching cubes technique). Therefore, for volume rendering such as the 3D medical models and terrains where a very large numbers of lookups in 3D grids are performed, this method is a very good choice for generating the high resolution of 3D surfaces. � 2019 SPIE.
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    The image recognition system for terrestrial reconnaissance
    (Springer Verlag, 2017) Fuangfar Pensiri; Chayute Phupittayathanakorn; Porawat Visutsak; P. Visutsak; Faculty of Applied Science, King Mongkut�s University of Technology North Bangkok, Bangkok, Thailand; email: porawat.v@sci.kmutnb.ac.th
    Terrestrial reconnaissance in the border provinces in Thailand is very risky and dangerous mission for troops and government officers. Many of troops were killed and injured by the incendiary bombs buried in the roads. In order to preventing the loss of life and property damages, many inventions of bomb detector have been commercially used such as GPR (Ground Penetration Radar) and REST (Remote Explosive Scent Tracing). Unfortunately, these technologies are expensive and inappropriate in some situations. This paper presents the forthcoming technology of the real-time image recognition for terrestrial reconnaissance. By using the road texture analysis in image analytic, the data set of normal surfaces of the road (e.g. asphalt road and gravel road) will be trained as the prior-knowledge. The system can compare the buried surface with the normal surface of the road and warning the troops beforehand. � Springer Nature Singapore Pte Ltd. 2017.