• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.34 no.5
• /
• pp.525-534
• /
• 2016

In South Korea, paddy rice has been consumed over the entire region and it is the main source of income for farmers, thus mathematical model for the estimation of rice yield is required for such decision-making processes in agriculture. The objectives of our study are to: (1) develop rice yield estimation model using Convolutional Neural Networks(CNN), (2) choose hyper-parameters for the model which show the best performance and (3) investigate whether CNN model can effectively predict the rice yield by the comparison with the model using Artificial Neural Networks(ANN). Weather and MODIS(The MOderate Resolution Imaging Spectroradiometer) products from April to September in year 2000~2013 were used for the rice yield estimation models and cross-validation was implemented for the accuracy assessment. The CNN and ANN models showed Root Mean Square Error(RMSE) of 36.10kg/10a, 48.61kg/10a based on rice points, respectively and 31.30kg/10a, 39.31kg/10a based on 'Si-Gun-Gu' districts, respectively. The CNN models outperformed ANN models and its possibility of application for the field of rice yield estimation in South Korea was proved.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.9 no.3
• /
• pp.664-673
• /
• 2008

Recently, the ubiquitous is handled by maximum topic. New knowledge information and ubiquitous computing evolution have promoted new paradigm transfer and grand change. Also, need technology as powerful engineering approached fairly system and educational guidance side examination necessarily to overcome u-Learning base situation and studying obstacle situations. This treatise embodied handiness examination about attention shortage and excess obstacle (Attention Deficit Hyperactivity Disorder, low ADHD) who must solve so as to be square and level being increase trend in primary school using USB (Universal Serial Bus) terminal system that allow fetters to OSGi (Open Service Gateway Initiative). That OSGi base USB terminal system is easy preservation of information, safety of network, cost-cutting and maintenance by various ubiquitous system that server that load many USB terminals and OSGi uses an USB bus of high speed and construct network, there is advantage of concentration elevation and so on of week and ADHD handled in this treatise because early diagnosis and treatment are serious. The confirmed system application that can supplement paper and pens examination's shortcoming and could solve examination's problem which use computer, and help in student guidance through ADHD simpleexamination who utilize OSGi base USB terminal system. Is available by game system that system for human nature examination or intelligence test and general exam explaining and level studying, order style question investigation program, studying system for disabled person, majority that enforce in public in school this study finding does together.

• Korean Journal of Remote Sensing
• /
• v.37 no.5_2
• /
• pp.1307-1315
• /
• 2021

The Changjiang Diluted Water (CDW) spreads over the East China Sea every summer and significantly affects the sea surface salinity changes in the seas around Jeju Island and the southern coast of Korea peninsula. Sometimes its effect extends to the eastern coast of Korea peninsula through the Korea Strait. Specifically, the CDW has a significant impact on marine physics and ecology and causes damage to fisheries and aquaculture. However, due to the limited field surveys, continuous observation of the CDW in the East China Sea is practically difficult. Many studies have been conducted using satellite measurements to monitor CDW distribution in near-real time. In this study, an algorithm for estimating Sea Surface Salinity (SSS) in the East China Sea was developed using the Geostationary Ocean Color Imager (GOCI). The Multilayer Perceptron Neural Network (MPNN) method was employed for developing an algorithm, and Soil Moisture Active Passive (SMAP) SSS data was selected for the output. In the previous study, an algorithm for estimating SSS using GOCI was trained by 2016 observation data. By comparison, the train data period was extended from 2015 to 2020 to improve the algorithm performance. The validation results with the National Institute of Fisheries Science (NIFS) serial oceanographic observation data from 2011 to 2019 show 0.61 of coefficient of determination (R²) and 1.08 psu of Root Mean Square Errors (RMSE). This study was carried out to develop an algorithm for monitoring the surface salinity of the East China Sea using GOCI and is expected to contribute to the development of the algorithm for estimating SSS by using GOCI-II.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.4
• /
• pp.2060-2077
• /
• 2019

Recently, mobile healthcare services have attracted significant attention because of the emerging development and supply of diverse wearable devices. Smartwatches and health bands are the most common type of mobile-based wearable devices and their market size is increasing considerably. However, simple value comparisons based on accumulated data have revealed certain problems, such as the standardized nature of health management and the lack of personalized health management service models. The convergence of information technology (IT) and biotechnology (BT) has shifted the medical paradigm from continuous health management and disease prevention to the development of a system that can be used to provide ground-based medical services regardless of the user's location. Moreover, the IT-BT convergence has necessitated the development of lifestyle improvement models and services that utilize big data analysis and machine learning to provide mobile healthcare-based personal health management and disease prevention information. Users' health data, which are specific as they change over time, are collected by different means according to the users' lifestyle and surrounding circumstances. In this paper, we propose a prediction model of user physical activity that uses data characteristics-based long short-term memory (DC-LSTM) recurrent neural networks (RNNs). To provide personalized services, the characteristics and surrounding circumstances of data collectable from mobile host devices were considered in the selection of variables for the model. The data characteristics considered were ease of collection, which represents whether or not variables are collectable, and frequency of occurrence, which represents whether or not changes made to input values constitute significant variables in terms of activity. The variables selected for providing personalized services were activity, weather, temperature, mean daily temperature, humidity, UV, fine dust, asthma and lung disease probability index, skin disease probability index, cadence, travel distance, mean heart rate, and sleep hours. The selected variables were classified according to the data characteristics. To predict activity, an LSTM RNN was built that uses the classified variables as input data and learns the dynamic characteristics of time series data. LSTM RNNs resolve the vanishing gradient problem that occurs in existing RNNs. They are classified into three different types according to data characteristics and constructed through connections among the LSTMs. The constructed neural network learns training data and predicts user activity. To evaluate the proposed model, the root mean square error (RMSE) was used in the performance evaluation of the user physical activity prediction method for which an autoregressive integrated moving average (ARIMA) model, a convolutional neural network (CNN), and an RNN were used. The results show that the proposed DC-LSTM RNN method yields an excellent mean RMSE value of 0.616. The proposed method is used for predicting significant activity considering the surrounding circumstances and user status utilizing the existing standardized activity prediction services. It can also be used to predict user physical activity and provide personalized healthcare based on the data collectable from mobile host devices.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.40 no.3
• /
• pp.207-215
• /
• 2022

This research has been focused on accessing precision and accuracy of UAV (Unmanned Aerial Vehicle)-derived 3-D surveying coordinates. To this end, a highly precise and accurate testing control network had been established by GNSS (Global Navigation Satellite Systems) campaign and its network adjustment. The coordinates of the ground control points and the check points were estimated within 1cm accuracy for 95% of the confidence level. FC330 camera mounted on DJI Phantom 4 repeatedly took aerial photos of an experimental area seven times, and then processed them by two widely used software packages. To evaluate the precision and accuracy of the aerial surveys, 3-D coordinates of the ten check points which automatically extracted by software were compared with GNSS solutions. For the 95% confidence level, the standard deviation of two software's result is within 1cm, 2cm, and 4cm for the north-south, east-west, and height direction, and RMSE (Root Mean Square Error) is within 9cm and 8cm for the horizontal, vertical component, respectively. The interest is that the standard deviation is much smaller than RMSE. The F-ratio test was performed to confirm the statistical difference between the two software processing results. For the standard deviation and RMSE of most positional components, exception of RMSE of the height, the null hypothesis of the one-tailed tests was rejected. It indicates that the result of UAV photogrammetry can be different statistically based on the processing software.

• The Journal of the Korea Contents Association
• /
• v.21 no.12
• /
• pp.791-802
• /
• 2021

In Korea, the cities continue to deteriorate, while the vacant houses in the small local towns emerge as a serious social problem. Despite the vacant houses emerge as a serious social problem in the small local towns as well as in the large cities, the basic researches into them are yet to be conducted on a full scale. Thus, in order to know about the spatial distribution of the vacant houses, this study conducted the square analysis and the kernel density analysis. As a result, it was confirmed that the vacant houses in Okcheon-gun had certain crowding forms and characteristics at the level of statistical significance. Next, in order to examine the distribution of the vacant houses in terms of the accessibility to the living SOC facilities, the GIS network analysis was performed, focusing on the major facilities and road networks. As a result, it was found that the better the accessibility to the living SOC facilities such as medical and well-being was, the ratio of the vacant houses was lower. In contrast, it was found that the accessibility to the obligatory facilities such as public administration and educational facilities did not have any important effects on the distribution of the vacant houses. All in all, through this study, the spatial distribution of the vacant houses in the small local town and their accessibility to the major SOC facilities could be analyzed.

• Korean Journal of Radiology
• /
• v.24 no.11
• /
• pp.1151-1163
• /
• 2023

Objective: To develop a deep-learning-based bone age prediction model optimized for Korean children and adolescents and evaluate its feasibility by comparing it with a Greulich-Pyle-based deep-learning model. Materials and Methods: A convolutional neural network was trained to predict age according to the bone development shown on a hand radiograph (bone age) using 21036 hand radiographs of Korean children and adolescents without known bone development-affecting diseases/conditions obtained between 1998 and 2019 (median age [interquartile range {IQR}], 9 [7-12] years; male:female, 11794:9242) and their chronological ages as labels (Korean model). We constructed 2 separate external datasets consisting of Korean children and adolescents with healthy bone development (Institution 1: n = 343; median age [IQR], 10 [4-15] years; male: female, 183:160; Institution 2: n = 321; median age [IQR], 9 [5-14] years; male: female, 164:157) to test the model performance. The mean absolute error (MAE), root mean square error (RMSE), and proportions of bone age predictions within 6, 12, 18, and 24 months of the reference age (chronological age) were compared between the Korean model and a commercial model (VUNO Med-BoneAge version 1.1; VUNO) trained with Greulich-Pyle-based age as the label (GP-based model). Results: Compared with the GP-based model, the Korean model showed a lower RMSE (11.2 vs. 13.8 months; P = 0.004) and MAE (8.2 vs. 10.5 months; P = 0.002), a higher proportion of bone age predictions within 18 months of chronological age (88.3% vs. 82.2%; P = 0.031) for Institution 1, and a lower MAE (9.5 vs. 11.0 months; P = 0.022) and higher proportion of bone age predictions within 6 months (44.5% vs. 36.4%; P = 0.044) for Institution 2. Conclusion: The Korean model trained using the chronological ages of Korean children and adolescents without known bone development-affecting diseases/conditions as labels performed better in bone age assessment than the GP-based model in the Korean pediatric population. Further validation is required to confirm its accuracy.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.20 no.8
• /
• pp.392-402
• /
• 2019

The purpose of this study is to determine the factors that predict happiness among aged males and females who live alone, and we focused on their satisfaction with their socio-physical environment, their social network, regular participation in social activities, their subjective health status and if they suffer from depression. A total of 2,76 people were the subjects of this study, their average age was 65 years old, they lived alone and all of them were selected from the '2017 Community Health Survey' data. The data was analyzed utilizing the Chi-square test, the Mann-Whitney test and multivariate logistic regression analysis. The subjects were 605 males (21.86%) and 2,163 females (78.14%). For the result of this study, the significant predictive factors of happiness for aged males living alone were monthly income (OR=2.363, 95% CI=1.473-3.791), basic livelihood rights (OR=1.903, 95% CI=1.144-3.167), trusting their neighbors (OR=2.018, 95% CI=1.263-3.225), religious activities (OR=2.098, 95% CI=1.314-3.349), subjective health (OR=2.753, 95% CI=1.217-6.228), and depression (OR=0.852, 95% CI=0.803-0.905). The significant predictive factors of happiness for aged females living alone were income (OR=2.407 95% CI=1.362-4.253), basic livelihood rights (OR=1.350, 95% CI=1.019-1.788), contact with friends (OR=1.879, 95% CI=1.323-2.669), religious activities (OR=1.372, 95% CI=1.124-1.676), recreation/leisure activities (OR=1.608, 95% CI=1.161-2.228), subjective health (OR=5.327, 95% CI=1.347-21.070), and depression (OR=0.864, 95% CI=0.840-0.890). In conclusion, programs to enhance happiness should be developed with considering the characteristics affecting the happiness of aged Korean males and females who live alone.

• Journal of the Korean Institute of Landscape Architecture
• /
• v.38 no.4
• /
• pp.64-74
• /
• 2010

The study is based on an urban park design that is designed in consideration of the characteristics of Uijeongbu City, applied with adequate functions for the environment and showcasing the unique scenery in relation to the relocation of the US Air Force Camp Falling Water. The bases of the design are: the reasonable convergence of the square and park in consideration of the site characteristics; the application of an urban context as the park is located near a station; and the realization of an eco-friendly space. This study is based on foundation research regarding a review of urban square patterns, particular items in planning in relation to modern urban parks and the adaptability of the park in the future. Regarding space usage, the design is applied with notable ideas that allow the space to make its own characteristics through voluntary user activity in conjunction with the environment that will allow the park to cope with changes in the future, as opposed to a space that users experience through pre-determined programs. Below are the focal points of the design. First, the park is designed as an empty space which may accommodate the urban structural context of and usage patterns for being a field of the city ecology that changes and develops, beyond a passively-created square pattern. Such open spaces have a continuity which allows it to adapt to the development of the city. In addition, the design facilitates spontaneous processes through changes in usage pattern and time. Second, the design includes the message that the park and the city, natural things and artificial things, must communicate and network with each other. Hence the park shall not be an isolated green island within the city, but is an open space accommodating the demands for open area from nearby commercial, public and residential facilities; the park shall include a field that can accommodate a variety of programs. Third, the park is designed to encourage the effect of direct and indirect practical education by reflecting a physical plan as well as interesting experience design methods to lower carbon emissions and to create and maintain an eco-friendly space, the basis of a zero-emissions city.

• Korean Journal of Environment and Ecology
• /
• v.37 no.4
• /
• pp.289-301
• /
• 2023

Forests within watersheds are essential in maintaining ecosystems and are the central infrastructure for constructing an ecological network system. However, due to indiscriminate development projects carried out over past decades, forest fragmentation and land use changes have accelerated, and their original functions have been lost. Since a forest's structural pattern directly impacts ecological processes and functions in understanding forest ecosystems, identifying and analyzing change patterns is essential. Therefore, this study analyzed structural changes in the forest landscape according to the time-series land cover changes using the FRAGSTATS model for the dam watershed of the Geum River upstream. Land cover changes in the dam watershed of the Geum River upstream through land cover change detection showed an increase of 33.12 square kilometers (0.62%) of forests and 67.26 square kilometers (1.26%) of urbanized dry areas and a decrease of 148.25 square kilometers (2.79%) in agricultural areas from the 1980s to the 2010s. The results of no-sampling forest landscape analysis within the watershed indicated landscape percentage (PLAND), area-weighted proximity index (CONTIG_AM), average central area (CORE_MN), and adjacency index (PLADJ) increased, and the number of patches (NP), landscape shape index (LSI), and cohesion index (COHESION) decreased. Identification of structural change patterns through a moving window analysis showed the forest landscape in Sangju City, Gyeongsangbuk Province, Boeun County in Chungcheongbuk Province, and Jinan Province in Jeollabuk Province was relatively well preserved, but fragmentation was ongoing at the border between Okcheon County in Chungcheongbuk Province, Yeongdong and Geumsan Counties in Chungcheongnam Province, and the forest landscape in areas adjacent to Muju and Jangsu Counties in Jeollabuk Province. The results indicate that it is necessary to establish afforestation projects for fragmented areas when preparing a future regional forest management strategy. This study derived areas where fragmentation of forest landscapes is expected and the results may be used as basic data for assessing the health of watershed forests and establishing management plans.