著者

山田 悟史 吉川 優矢 大山 智基 大内 宏友 及川 清昭

出版者

日本建築学会

雑誌

日本建築学会計画系論文集 (ISSN:13404210)

巻号頁・発行日

vol.78, no.692, pp.2163-2172, 2013-10-30 (Released:2014-07-10)

参考文献数

19

被引用文献数

6 5

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This study aims to construct a visualization method for understanding the effects of a helicopter emergency medical service. The effects will be calculated for the time that elapses before medical action is initiated. To calculate the elapsed time, the distance between each points will be measured using a geographic information system while considering geographical factors. The effects will also be investigated from visual and quantitative perspectives while considering the population of the study area. The proposed method will be examined from the viewpoints of the rendezvous point and emergency hospital acting as helicopter bases.

著者

上野 聡 本同 宏成 山田 悟史

出版者

一般社団法人 日本物理学会

雑誌

日本物理学会誌 (ISSN:00290181)

巻号頁・発行日

vol.71, no.11, pp.767-770, 2016-11-15 (Released:2017-08-03)

参考文献数

8

被引用文献数

2

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話題―身近な現象の物理―チョコレートのおいしい物理学

著者

藤井 健史 山田 悟史

出版者

日本建築学会

雑誌

日本建築学会計画系論文集 (ISSN:13404210)

巻号頁・発行日

vol.88, no.811, pp.2636-2642, 2023-09-01 (Released:2023-09-01)

参考文献数

13

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In this study, a total of 28,800 random tree placement models were generated from combinations of 12 tree shapes and 8 stages of green coverage, assuming a site of 50m square. Then, using the generated model, a Monte Carlo simulation of green visibility calculation was performed to obtain an expected value of green visibility rate for each condition. In addition, the calculation results were expressed in figures and estimation formulas so that they can be easily referred to actual tree placement plans. These achievements have made it possible to plan tree placement based on the scientific index of green visibility.

著者

山田 悟史 大野 耕太郎

出版者

日本建築学会

雑誌

日本建築学会計画系論文集 (ISSN:13404210)

巻号頁・発行日

vol.84, no.759, pp.1323-1331, 2019 (Released:2019-05-30)

参考文献数

23

被引用文献数

7 7

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This research is a basic study on utilizing artificial intelligence (AI) by applying deep learning to the fields of architecture and urban design.  In recent years, the use of budding technologies, such as deep learning, has increased in the field of architecture and urban design. While this technology has potential in various fields, this study focuses on learning and deduction of sensibility evaluation and impression of design. Needless to say, the relationship of design with sensibility and impression is important, and the design heightens sensibility and impressions. However, the causal relationship of quantitative representation (feature value) and feature value of design with impression is complex and is characteristically difficult to deduce. Such a characteristic is a property similar to fields where deep learning has been successfully used. It is, therefore, thought that AI using deep learning could be applicable. As mentioned, this research examines the budding properties of AI that deduce “street names and desire to visit” based on city landscapes. Specifically, the “desire/no-desire to visit (classification)” and “degree of desire to visit” are deduced, and as constituents of image consciousness, street names are also classified (21 classes).  The object of the study and the city landscapes were prepared from 21 streets selected from a large city and sightseeing information. The images for city landscapes were obtained from street view on Google Earth to ensure that these images were not of any one building, ground, or sky. A total of 2,100 images, 100 for each street, were considered.  Deduction AI with high precision was first successfully developed to deduce “classification of street names (21 classes)”. Its precision was approximately 86% for the F-value with a K-coefficient of 0.8508 (p-value = 1.6e-15). Next, for the classification, deduction AI with high conformity with desire/no-desire to visit criteria of test subjects was successfully prepared. Its precision had a K-coefficient of 0.8920 (p-value = 2.2e-15). Further, for deducing degree of desire, there was little difference in the degree of desire to visit between test subjects, and AI permitting deduction with high correlation was successfully developed. For its precision, the effect size of Wilcoxon’s signed rank test (test of paired nonparametric data) was 0.18, and Spearman’s rank correlation was 0.7564 (p-value = 0.0005742). Finally, to generalize the methodology of AI using deep learning, the 95% confidence interval that considered 100 kinds of AI developed using this method was confirmed to be small. Specifically, the effect size did not exceed 0.2 (a threshold value indicating small effect size) and did not fall below 0.6 (a threshold value indicating high correlation). Under the experimental conditions of this study, the AI developed using deep learning can be described as a method that presents generality in the degree of precision.  From the perspective of the experimental conditions of the study and usage, a successful impression deduction AI for city landscapes with good precision is developed. This provides the first step in systematically organizing and investigating the hitherto unstudied budding potential of deep learning in the fields of architecture and urban design.

著者

藤井 健史 山田 悟史

出版者

一般社団法人 日本建築学会

雑誌

日本建築学会技術報告集 (ISSN:13419463)

巻号頁・発行日

vol.26, no.63, pp.802-807, 2020-06-20 (Released:2020-06-20)

参考文献数

18

被引用文献数

1

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Using GPGPU, we developed a method to calculate the solid angle of landscape elements with an omnidirectional field of vision, via intersection detection. We confirmed that the processing speed was approximately 500 times faster than the processing speed achieved using a single CPU. Furthermore, the developed method was applied for the calculation of the omnidirectional green visibility of models with randomly arranged trees. Thus, the relationship between the shape and number of trees and the omnidirectional green visibility was analyzed statistically. These results can be considered as an index of the green visibility rate when planning the arrangement of trees.

著者

山田 悟史 大野 耕太郎

出版者

日本建築学会

雑誌

日本建築学会計画系論文集 (ISSN:13404210)

巻号頁・発行日

vol.85, no.770, pp.987-995, 2020 (Released:2020-04-30)

参考文献数

27

被引用文献数

1

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In recent years, there has been a growing interest in the application of Deep Learning to architecture and urbanism. This research is focused on content generation AI using Deep Learning. Despite claims that replacing creativity-related work with machines is difficult, the use of generative adversarial networks (GANs) is becoming more popular in various fields. The objective of this research is to develop an AI-supported design or a co-creation between humans and AI through the application of GANs. The primary goal of this work could be interpreted as repurposing existing concepts to create new designs through the combination of multiple design sources. Therefore, the purpose of this research is the creation of AI that emulate and support the design process.  This research examines two types of AI through a two-stage process; the first is an AI that reproduces design, and the second is an AI that generates design. The first type of AI reproduces designs from different sources and includes an analysis of whether the design can be expressed mathematically. This analysis is a prerequisite for the creation of the second type of AI that generates new designs by combining information from multiple sources. In other words, the second type of AI views designs mathematically, and the possibility of expressing designs mathematically (using the first type of AI) is examined to ensure that such a function is feasible and in line with user intention. Here, a mathematical expression refers to a 100-dimensional vector and an already-learned deep neural network.  The AI that reproduces design was applied to famous cityscapes (Kyoto and Edinburgh) and the façades of famous buildings (three works by Le Corbusier). The designs were reproduced as images and used for subject experiments to confirm that the intended impressions (oriental and occidental) and the designs of each type were successfully reproduced.  For the AI that generates design, a new design was generated from calculations of different combinations (three pairs and one trio) of the façades of three works by Le Corbusier (church of Saint-Pierre, Notre Dame du Haut, and Villa Savoye). This design was subsequently used for text mining Bayesian-estimation-based subject experiments to confirm that the characteristics of the design sources were successfully inherited.  To the best of our knowledge, these are new types of AI. Further, we believe that these achievements may facilitate better dissemination of design through fast generation of a large number of images (design patterns) that constitute new types of designs. This achievement may also help expand the concept of human design thinking by suggesting designs that can be permuted using AI but otherwise inconceivable for human designers. Ultimately, this can help in the creation of a new design environment, namely “co-creation between humans and AI,” wherein the designers choose the sources and the AI generates a number of design choices for the final design.

著者

大野 耕太郎 山田 悟史 宗本 晋作

出版者

日本建築学会

雑誌

日本建築学会計画系論文集 (ISSN:13404210)

巻号頁・発行日

vol.87, no.798, pp.1602-1611, 2022-08-01 (Released:2022-08-01)

参考文献数

17

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This study aimed to estimate human willingness to visit cityscape images via artificial intelligence (AI) using multimodal deep learning. In this study, gaze information was acquired through subject experiments using a measurement device. We added gaze information when humans felt motivated to visit the cityscape image, and confirmed whether the estimation accuracy of AI would improve. We also created an AI model that generated gaze-view images, and used it for multimodal deep learning. We used pix2pix to generate the images. Finally, we verified the accuracy of the proposed multimodal deep learning approach, when the generated pseudo-gaze image was attached.

著者

山田 悟史

出版者

立命館大学

雑誌

若手研究(B)

巻号頁・発行日

2014-04-01

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本研究はドクターヘリ及びドクターカーの運用効果を算出し,基地病院とランデブーポイントの配置計画を検討したものである。運用効果の指標は,医師による医療行為開始時間,救命率,人口をもとにした4指標である。対象は関西広域連合とし,場外離着陸場のランデブーポイント化,三次救急病院を候補とした基地病院の追加の運用効果をGISと既往研究から算出した。これに基づき,場外離着陸場のランデブーポイント化,及び基地病院の追加の効果上昇が平坦化する施設数,効果が大きい適正配置を提示した。具合的な方法,数値や施設名称・位置については研究成果報告・発表済み原稿を参照して頂きたい。

著者

北本 英里子 山田 悟史 神長 伸幸

出版者

一般社団法人 日本建築学会

雑誌

日本建築学会技術報告集 (ISSN:13419463)

巻号頁・発行日

vol.27, no.66, pp.1104-1109, 2021-06-20 (Released:2021-06-20)

参考文献数

12

被引用文献数

2

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The impression of space and perception of distance may be different in real space, 3D space on the flat display (DP space), and 3D space on the immersive head-mounted display (HMD space). In this study, the mean value and standard deviation were calculated and verified based on the data obtained from the experiment. The difference between DP space and HMD space for the real space is described. The results showed differences of the perceived distance and, in psychological evaluations, differences of the openness and the presence of the object.

著者

山田 悟史 北本 英里子 神長 伸幸 及川 清昭

出版者

一般社団法人 日本建築学会

雑誌

日本建築学会技術報告集 (ISSN:13419463)

巻号頁・発行日

vol.24, no.58, pp.1303-1307, 2018-10-20 (Released:2018-10-20)

参考文献数

13

被引用文献数

3

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In real space, 3D space seen on the display (DP space), and space seen on the immersive head head-mounted display (HMD space), the impressions of space and perceptions of distance are different. In this study, the t-test was carried out based on data obtained from experiments to clarify the difference of DP space and HMD space from real space. The results show that there is a significant difference between the DP space and the HMD space, and it became clear that the DP space gives a perception close to the real space.

著者

小島 尚之 山田 悟史

出版者

立命館大学歴史都市防災研究所

雑誌

歴史都市防災論文集 (ISSN:18821766)

巻号頁・発行日

vol.15, pp.247-252, 2021-07

著者

山田 悟史 藤井 健史 宗本 晋作

出版者

日本建築学会

雑誌

日本建築学会計画系論文集 (ISSN:13404210)

巻号頁・発行日

vol.81, no.727, pp.2083-2093, 2016 (Released:2016-09-30)

参考文献数

29

被引用文献数

5 6

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In recent years, there have been a number of social initiatives related to improving the environment in city landscapes. Green space is becoming a tool to enhance the comfort of city space. "The Basic Plan for Green of Kyoto City" is one such example, where the ratio of visible green space is being used as a tool to improve the city environment. Many studies are being carried out to support this initiative and this study is one of them. The purpose of this study was to: 1) present a method to measure the location/angle specific ratio of green spaces in the omnidirectional visibility rate using a three-dimensional model of the target location, 2) create a perception deduction model based on Self-organizing Maps and 72 variables of visible green space in omnidirectional visibility rate, and 3) statistical verification of the accuracy of the perception deduction model. There are 72 categories of green space in the omnidirectional visibility rate. These categories are based on the location- and angle specific ratio of these spaces. Six of these categories were used for the location specific measurement, namely, "tall trees", "medium trees", "shrubs", " implantable ", "ground cover", and "others". Twelve angle specific measurements for every fifteen degrees were used and eight perception estimation parameters were selected. The perception estimation parameters included: “many or less", "satisfied or not satisfied", "pleasant", "serene", "covered (wrapped)", "close by or far", " surrounded by", "refreshing” and “widely spread". In this paper, we present results from the "ratio of visible green space in the omnidirectional visibility rate map”, the “self-organizing map" and the "perception estimation value map”. During the verification of the perception estimation model (the primary objective of this study), we compared the estimated perception values with the survey based observed values associated with a location of green space that was not included in the model creation. When we compared them statistically, we confirmed a significant correlation (n=32, p<0.05) between the estimated values and observed values (Pearson's correlation). We noted that the strength of the correlation was moderate but significant (correlation coefficient values around 0.6), with when we used the lower significance level (p<0.001). Taking into account effect size from psychological statistics, the average difference between the estimated and observed values of perception can be considered small for the parameters "many or less" "satisfied or not satisfied", "pleasant", "serene", "covered (wrapped)", "close by or far" and" surrounded by". However, the average difference was moderate for “Refreshing” and “Widely spread” and a significant difference between observed and estimated perception values was noted for these parameters in a paired t-test. Consequently, this perception deduction model is able to predict low and high values of “Refreshing” and “Widely spread", however, we need to be aware of the one degree difference, which happens to be the width of the confidence interval and may affect the estimated values.

著者

北本 英里子 山田 悟史

出版者

一般社団法人日本建築学会

雑誌

学術講演梗概集. F-1, 都市計画, 建築経済・住宅問題 (ISSN:13414534)

巻号頁・発行日

vol.2010, pp.793-794, 2010-07-20