• Journal of the Architectural Institute of Korea Planning & Design
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• v.35 no.5
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• pp.21-30
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• 2019

The purpose of this study is to present the direction of the new space plan by reflecting the opinions of the user (student) in the existing standardized elementary school space planning. The purpose of this study is to investigate the activities of elementary school students by using socio - spatial network analysis method and to propose the direction of new elementary school space planning through the results. We analyzed the results of each centrality by using the analysis of closeness analysis, betweeness analysis, girvan-newman clustering, and concor analysis. The results of this study are as follows. First, it should be planned to use the classroom and the special room as one area by utilizing the corridor. Second, it should be planned that the outdoor space and the indoor space are closely related to each other by utilizing the hall, the lobby and the classroom. Third, the school should create a small space where physical activity is possible in an indoor space of the school. In order to improve the standardized elementary school space, this study proposes a method to reflect the opinions of the users in the school planning stage.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.120-120
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• 2020

Spatial precipitation data is one of the essential components in modeling hydrological problems. The estimation of these data has achieved significant achievements own to the recent advances in remote sensing technology. However, there are still gaps between the satellite-derived rainfall data and observed data due to the significant dependence of rainfall on spatial and temporal characteristics. An effective approach based on the Convolutional Neural Network (CNN) model to correct the satellite-derived rainfall data is proposed in this study. The Mekong River basin, one of the largest river system in the world, was selected as a case study. The two gridded precipitation data sets with a spatial resolution of 0.25 degrees used in the CNN model are APHRODITE (Asian Precipitation - Highly-Resolved Observational Data Integration Towards Evaluation) and PERSIANN-CDR (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks). In particular, PERSIANN-CDR data is exploited as satellite-based precipitation data and APHRODITE data is considered as observed rainfall data. In addition to developing a CNN model to correct the satellite-based rain data, another statistical method based on standard deviations for precipitation bias correction was also mentioned in this study. Estimated results indicate that the CNN model illustrates better performance both in spatial and temporal correlation when compared to the standard deviation method. The finding of this study indicated that the CNN model could produce reliable estimates for the gridded precipitation bias correction problem.

• Journal of Information Processing Systems
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• v.17 no.2
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• pp.337-351
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• 2021

Automatically recognizing facial expressions in video sequences is a challenging task because there is little direct correlation between facial features and subjective emotions in video. To overcome the problem, a video facial expression recognition method using spatiotemporal recurrent neural network and feature fusion is proposed. Firstly, the video is preprocessed. Then, the double-layer cascade structure is used to detect a face in a video image. In addition, two deep convolutional neural networks are used to extract the time-domain and airspace facial features in the video. The spatial convolutional neural network is used to extract the spatial information features from each frame of the static expression images in the video. The temporal convolutional neural network is used to extract the dynamic information features from the optical flow information from multiple frames of expression images in the video. A multiplication fusion is performed with the spatiotemporal features learned by the two deep convolutional neural networks. Finally, the fused features are input to the support vector machine to realize the facial expression classification task. The experimental results on cNTERFACE, RML, and AFEW6.0 datasets show that the recognition rates obtained by the proposed method are as high as 88.67%, 70.32%, and 63.84%, respectively. Comparative experiments show that the proposed method obtains higher recognition accuracy than other recently reported methods.

• Structural Monitoring and Maintenance
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• v.11 no.3
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• pp.203-217
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• 2024

Electro-mechanical impedance (EMI) technique is a low-cost structural damage detection method. It reflects structural damage through the change in admittance signal which contains the structural mechanical impedance information. The ambient temperature greatly affects the admittance signal, which hides the changes caused by structural damage and reduces the accuracy of damage identification. This study introduces a convolutional neural network to compensate for the temperature effect. The proposed method uses a framework that consists of a feature extraction network and a decoding network, and the original admittance signal with temperature information is used as the input. The output admittance signal is eliminated from the temperature effect, improving damage identification robustness. The admittance data simulated by the finite element model of the spatial grid structure is used to verify the effectiveness of the proposed method. The results show that the proposed method has advantages in identification accuracy compared with the damage index minimization method and the principal component analysis method.

• Journal of Biomedical Engineering Research
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• v.16 no.1
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• pp.33-42
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• 1995

A new neural network architecture for the recognition of patterns from images is proposed, which is partially based on the results of physiological studies. The proposed network is composed of multi-layers and the nerve cells in each layer are connected by spatial filters which approximate receptive fields in optic nerve fields. In the proposed method, patterns recognition for complicated images is carried out using global features as well as local features such as lines and end-points. A new generating method of matched filters representing global features is proposed in this network.

• Journal of the Korean Geographical Society
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• v.43 no.4
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• pp.526-543
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• 2008

Based on the social network analysis(SNA), this study examines the structural and spatial characteristics of the actor networks of the manufacturing industries for the elderly. In the field of economic geography, former researches on network have mainly focused on the network governance. However, this study focused on the social network analysis. Centrality indexes are used to analyze the topological structure of actor networks of firms and organizations. In order to investigate the spatial structure of actor networks, not only the regional distribution of actors but also the correlation between centrality index and distance are analyzed. Network matrixes among actors are transformed to network matrixes among regions using block modeling method to reveal the spatial characteristics of the actor networks. In spite of the importance of the Capital Region, networks in the non-Capital Region like Chungnam and Pusan were showed high network density. This suggested that some kinds of policy project operating in the non-Capital Region had the influence on this network in the initial stage of industry.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.2
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• pp.185-194
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• 2016

The purpose of this study is to present a method to provide environment information based on spatial information document. At present, a lot of spatial information, including environment information, is being produced, but separate software or system is required for the user to acquire the information. In particular, in the case of environment information, various types of information are being produced, such as ecology, vegetation and measurement network data. Therefore, it is necessary to present the form and the making method of spatial information document that allows using environment information as spatial information without separate software or system. To provide spatial information document-based environment information, types and forms of environment information, data format and offering methods produced by the government, in particular, the Ministry of Environment and the local governments, are analyzed. 12 fields are classified and the form of produced data is GIS DB, measurement network data, text data and so on. With decrease of paper maps, spatial information document that offers display by layer, coordinate data, attribute data, distance and area measurement, location search by coordinates, GPS location linkage and location display on the map is presented to increase utilization of geo-environment information maps. Finally, the standard document specification based on spatial information document is presented in consideration of usability and readability in order to provide a variety of environment information without separate software or system.

• Journal of Korea Spatial Information System Society
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• v.1 no.1 s.1
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• pp.29-37
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• 1999

Recently, brisk up the construction of the spatial information, many people highly concern to tile information circulation of GIS. Each system like GIS has a structure of the information circulation to itself. In this paper, we study on the performance evaluation method of tile structure which to circulate tile spatial information based on the internet. To do this, we hypothesize values of content and scale of the geo-spatial information on each internet network and volumes of the information to circulate between internet networks. Then we suggest a method to evaluate the performance of the structure to aid the circulation of spatial information based on queueing model. Henceforth, with the volumes of data stored and circulated information of each GIS, this method can help to design the structure to circulate the GIS information more efficiently.

• Journal of Internet of Things and Convergence
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• v.8 no.2
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• pp.79-84
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• 2022

This paper presents an enhancement method of document restoration capability which is robust for security, loss, and contamination, It is based on two methods, that is, encryption and DnCNN(DeNoise Convolution Neural Network). In order to implement this encryption method, a mathematical model is applied as a spatial frequency transfer function used in optics of 2D image information. Then a method is proposed with optical interference patterns as encryption using spatial frequency transfer functions and using mathematical variables of spatial frequency transfer functions as ciphers. In addition, by applying the DnCNN method which is bsed on deep learning technique, the restoration capability is enhanced by removing noise. With an experimental evaluation, with 65% information loss, by applying Pre-Training DnCNN Deep Learning, the peak signal-to-noise ratio (PSNR) shows 11% or more superior in compared to that of the spatial frequency transfer function only. In addition, it is confirmed that the characteristic of CC(Correlation Coefficient) is enhanced by 16% or more.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.4
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• pp.115-123
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• 2016

The road name address system has been in effect in Korea since 2012. However, the existing address system is still being used in many fields because of the difference between the spatial awareness of people and the road name address system. For the spatial awareness based on the road name address system, various spatial datasets in daily life should be referenced by the road names. The goal of this paper is to link the road name address system with the wayfinding process, which is closely related to the spatial awareness. To achieve our goal, we designed and implemented a geometric matching method for spatial data sets. This method generates network neighborhoods from road objects in the 'road name address map' and the 'pedestrian network data'. Then it computes the geometric similarities between the neighborhoods to identify corresponding road name for each object in the network data. The performance by F0.5 was assessed at 0.936 and it was improved to 0.978 by the manual check for 10% of the test data selected by the similarity. By help of our method, the road name address system can be utilized in the wayfinding services, and further in the spatial awareness of people.