• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.305-319
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• 2021

The overseas calibration sites such as Mongolia used for Korea Multi-purpose Satellite (KOMPSAT-5 or K5), have a disadvantage in that maintenance and repair costs are high and immediate response is difficult when an unexpected problem occurs. Accordingly, the necessity of establishing a domestic SAR calibration site was suggested, but the progress of related research is insignificant. In this paper, we investigated what conditions should be satisfied in terms of backscattering characteristics to construct a site for SAR satellite image quality evaluation and calibration. First of all, it was selected first by applying general indicators such as accessibility and availability among places recommended as satellite image calibration candidate sitesin Korea. Next, three places, site A (Goheung-gun, Jeollanam-do), site B (Jeonju-si, Jeollabuk-do), and site C (Daedeok Research Complex, Daejeon), were selected as the final candidates because they are relatively wide and easy to install AT or CR. Site A, located in Goheung-gun, Jeollanam-do, was best considered in terms of slope measurements, minimum site area to obtain ISLR, uniformity of DN values and backscatter coefficients, interference by strong reflectors, and backscatter clutter level.

• The Journal of the Korea Contents Association
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• v.19 no.6
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• pp.47-57
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• 2019

The purpose of this study is to explore how college students aware of the 4th industrial revolution and prepare to adjust it. The subjects of the study were 317 college students in Busan city and analyzed by gender, major and grades. Results are as follows. First, students who are male, higher grade and major in engineering area showed greater recognition compared to students who are female, lower grade and studying other areas for the new era. Also for big changes of the era most students agreed with convenience of life but decrease of job opportunities. Second, most students showed nothing special work yet but students in engineering area make an effort to foster their competence. Third, most students had lower, below average level of competence that are required in the new era. Fourth, the difficulties students encounter are lack of educational opportunities and financial problem. Male students responded lack of time and laboratory work and female students are lack of concerns. The study suggests that colleges should provide various method such as regular and irregular and extra curriculum to enhance students creativity and competence for the new era.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.141-160
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• 2019

Agile methodologies in software development, including the development of artificial intelligence software, have been widespread over the past several years. In spite of the popularity of agile methodologies in practice, there is a lack of empirical evidence to identify determinants of success of software projects in which agile methods are used. To understand the role of clients in software project where agile methods are used, we examine the effect of client-side factors, including lack of user involvement, unrealistic client expectations, and constant changes of requirements on project success from practitioners' perspective. Survey methods are used in this study. Data were collected by means of online survey to IT professionals who have experience with software development methodologies, and ordered logit regression is used to analyze the survey data. Results of our study imply the following managerial findings. First, user involvement is critical to project success to take advantage of agile methods. Second, it is interesting that, with an agile method, constant changes of client's requirements is not a negative factor but a positive factor of project success. Third, unrealistic client expectations do negatively affect project success even with agile methods.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.12
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• pp.653-659
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• 2018

The accurate prediction of construction cost is a key factor in a project's success. However, it is hard to predict the construction costs in the planning stages rapidly and precisely when drawings, specifications, construction cost calculation statements are incomplete, among other factors. Accurate construction-cost prediction in the planning stage of a project is also important for project feasibility studies and successful completion. Therefore, various techniques have been applied to accurately predict construction costs at an early stage when project information is limited. There are many factors that affect the construction cost prediction. This paper presents a construction-cost prediction method as multiple regression model with seven construction factors as independent variables. The method was used to predict the construction cost of a local housing union project, and the error rate was 4.87%. It is not possible to compare the cost of the project at the planning stage of the local housing union project, but it has high prediction accuracy compared to the unit price of an existing unit area. It is likely to be applied in construction-cost calculation work and to contribute to the establishment of the budget for the local housing union project.

• Korean Journal of Breeding Science
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• v.50 no.4
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• pp.529-533
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• 2018

Hyowon6, a mid-late maturing, good eating quality rice variety with multi-resistance, was developed by the rice breeding team of Pusan National University in 2013. This variety was derived from a cross between Hwayeong (as a multi-resistant parent) and Koshihikari (as a good eating quality parent). Selection by the pedigree breeding method was carried out until the $F_8$ generation. A promising line, JS14-12-36-8-5-3-1-1-1, was developed and designated as HY103 in 2013. This variety headed on August 22, which was 11 days later than that of Hwayeong. The culm length and panicle length of Hyowon6 was 85.7 cm and 21.1 cm, respectively. The number of panicles per hill was 14.5 and the number of grains per panicle was 101.7. The ratio of ripened grain was approximately 92% and the 1,000-grain weight was approximately 21.36 g for brown rice, which were similar to those of Hwayeong. Hyowon6 was moderately resistant to lodging and also to neck blast, leaf blight, and stripe virus. The glossiness value of Hyowon6 was 83, which was considerably higher than that of Hwayeong.

• Journal of Korea Water Resources Association
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• v.54 no.9
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• pp.681-692
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• 2021

Vegetation processes have a significant impact on rainfall runoff processes through evapotranspiration control, but are rarely considered in the conceptual lumped hydrological model. This study evaluated the model performance of the Hapcheon Dam watershed by integrating the ecological module expressing the leaf area index data sensed remotely from the satellite into the hydrological partition module. The proposed eco-hydrological model has three main features to better represent the eco-hydrological process in humid regions. 1) The growth rate of vegetation is constrained by water shortage stress in the watershed. 2) The maximum growth of vegetation is limited by the energy of the watershed climate. 3) The interaction of vegetation and aquifers is reflected. The proposed model simultaneously simulates hydrologic components and vegetation dynamics of watershed scale. The following findings were found from the validation results using the model parameters estimated by the SCEM algorithm. 1) Estimating the parameters of the eco-hydrological model using the leaf area index and streamflow data can predict the streamflow with similar accuracy and robustness to the hydrological model without the ecological module. 2) Using the remotely sensed leaf area index without filtering as input data is not helpful in estimating streamflow. 3) The integrated eco-hydrological model can provide an excellent estimate of the seasonal variability of the leaf area index.

• Korean Chemical Engineering Research
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• v.59 no.2
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• pp.191-199
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• 2021

A distillation column, which is a main facility of the chemical process, separates the desired product from a mixture by using the difference of boiling points. The distillation process requires the optimization and the prediction of operation because it consumes much energy. The target process of this study is difficult to operate efficiently because the composition of feed flow is not steady according to the supplier. To deal with this problem, we could develop a data-driven model to predict operating conditions. However, data preprocessing is essential to improve the predictive performance of the model because the raw data contains outlier and noise. In this study, after optimizing the predictive model based long-short term memory (LSTM) and Random forest (RF), we used a low-pass filter and one-class support vector machine for data preprocessing and compared predictive performance according to the method and range of the preprocessing. The performance of the predictive model and the effect of the preprocessing is compared by using R2 and RMSE. In the case of LSTM, R2 increased from 0.791 to 0.977 by 23.5%, and RMSE decreased from 0.132 to 0.029 by 78.0%. In the case of RF, R2 increased from 0.767 to 0.938 by 22.3%, and RMSE decreased from 0.140 to 0.050 by 64.3%.

• Journal of Korean Library and Information Science Society
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• v.51 no.4
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• pp.185-210
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• 2020

The library faced an unexpected crisis of COVID-19, and as a countermeasure strategy, non-face-to-face online service has been reinforced. Therefore, this study attempted to present a plan to overcome the challenges arising from rapidly changing external environment and current crisis. To this end, data search, electronic library, library service, cultural event and open space management status of 288 public libraries serviced as an integrated site were investigated. Based on this, the meaning of online services in the post-COVID-19 era and the implication of it were examined. As a result, first, the increase in the use rate of online data search services with the spread of non-face-to-face culture, second, the expansion of the services of the electronic library, third, the diversification of non-face-to-face, online services, fourth, expansion of online cultural event services, fifth, the diversification of open space services were proposed, sixth, Introduced an artificial intelligence system for unattended loan return based on access and the Seventh, expansion of experiential cultural support services and educational contents through VR, AR and MR. It is deemed necessary for the research on the future direction of the library's non-face-to-face services to be conducted by investigating the current status of online services in various types of libraries and the types and case studies of library services in the era of COVID-19.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.3
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• pp.133-139
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• 2021

Currently, the process of constructing a high-definition road map has a high proportion of manual labor, so there are limitations in construction time and cost. Research to automate map production with high-definition road maps using artificial intelligence is being actively conducted, but since the construction of training data for the map construction is also done manually, there is a need to automatically build training data. Therefore, in this study, after converting to images using point clouds acquired by a mobile mapping system, the road marking areas were extracted through image reclassification and overlap analysis using thresholds. Then, a methodology was proposed to automatically construct training data for deep learning data for the high-definition road map through the classification of the polygon types in the extracted regions. As a result of training 2,764 lane data constructed through the proposed methodology on a deep learning-based PointNet model, the training accuracy was 99.977%, and as a result of predicting the lanes of three color types using the trained model, the accuracy was 99.566%. Therefore, it was found that the methodology proposed in this study can efficiently produce training data for high-definition road maps, and it is believed that the map production process of road markings can also be automated.

• Journal of Convergence for Information Technology
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• v.12 no.4
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• pp.260-269
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• 2022

In this paper, We propose an anomaly detection model using deep neural network to automate the identification of outliers of the national air pollution measurement network data that is previously performed by experts. We generated training data by analyzing missing values and outliers of weather data provided by the Institute of Environmental Research and based on the BeatGAN model of the unsupervised learning method, we propose a new model by changing the kernel structure, adding the convolutional filter layer and the transposed convolutional filter layer to improve anomaly detection performance. In addition, by utilizing the generative features of the proposed model to implement and apply a retraining algorithm that generates new data and uses it for training, it was confirmed that the proposed model had the highest performance compared to the original BeatGAN models and other unsupervised learning model like Iforest and One Class SVM. Through this study, it was possible to suggest a method to improve the anomaly detection performance of proposed model while avoiding overfitting without additional cost in situations where training data are insufficient due to various factors such as sensor abnormalities and inspections in actual industrial sites.