• International Journal of Advanced Culture Technology
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• v.11 no.4
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• pp.464-469
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• 2023

As modern society develops, the number of diseases caused by bad smells is increasing. As it can harm people's health, it is important to predict in advance the extent to which bad smells may occur, inform the public about this, and take preventive measures. In this paper, we propose a hybrid neural network structure of CNN and LSTM that can be used to detect or predict the occurrence of odors, which are most required in manufacturing or real life, using odor complex sensors. In addition, the proposed learning model uses a complex odor sensor to receive four types of data, including hydrogen sulfide, ammonia, benzene, and toluene, in real time, and applies this data to the inference model to detect and predict the odor state. The proposed model evaluated the prediction accuracy of the training model through performance indicators based on accuracy, and the evaluation results showed an average performance of more than 94%.

• Journal of Korea Port Economic Association
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• v.34 no.3
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• pp.17-52
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• 2018

The purpose of this paper is to measure the clustering change and analyze empirical results. Additionally, by using k-means, hierarchical, and mixed models on Asian container ports over the period 2006-2015, the study aims to form a cluster comprising Busan, Incheon, and Gwangyang ports. The models consider the number of cranes, depth, birth length, and total area as inputs and container twenty-foot equivalent units(TEU) as output. Following are the main empirical results. First, ranking order according to the increasing ratio during the 10 years analysis shows that the value for average linkage(AL), mixed ward, rule of thumb(RT)& elbow, ward, and mixed AL are 42.04% up, 35.01% up, 30.47%up, and 23.65% up, respectively. Second, according to the RT and elbow models, the three Korean ports can be clustered with Asian ports in the following manner: Busan Port(Hong Kong, Guangzhou, Qingdao, and Singapore), Incheon Port(Tokyo, Nagoya, Osaka, Manila, and Bangkok), and Gwangyang Port(Gungzhou, Ningbo, Qingdao, and Kasiung). Third, optimal clustering numbers are as follows: AL(6), Mixed Ward(5), RT&elbow(4), Ward(5), and Mixed AL(6). Fourth, empirical clustering results match with those of questionnaire-Busan Port(80%), Incheon Port(17%), and Gwangyang Port(50%). The policy implication is that related parties of Korean seaports should introduce port improvement plans like the benchmarking of clustered seaports.

• Journal of Astronomy and Space Sciences
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• v.36 no.4
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• pp.283-292
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• 2019

The purpose of this study was to develop a period analysis algorithm for detecting new variable stars in the time-series data observed by charge coupled device (CCD). We used the data from a variable star monitoring program of the CBNUO. The R filter data of some magnetic cataclysmic variables observed for more than 20 days were chosen to achieve good statistical results. World Coordinate System (WCS) Tools was used to correct the rotation of the observed images and assign the same IDs to the stars included in the analyzed areas. The developed algorithm was applied to the data of DO Dra, TT Ari, RXSJ1803, and MU Cam. In these fields, we found 13 variable stars, five of which were new variable stars not previously reported. Our period analysis algorithm were tested in the case of observation data mixed with various fields of view because the observations were carried with 2K CCD as well as 4K CCD at the CBNUO. Our results show that variable stars can be detected using our algorithm even with observational data for which the field of view has changed. Our algorithm is useful to detect new variable stars and analyze them based on existing time-series data. The developed algorithm can play an important role as a recycling technique for used data

• Korean Journal of Remote Sensing
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• v.23 no.5
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• pp.483-491
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• 2007

One of the major obstacles to classify and validate Land Cover maps is the high cost of acquiring reference data. In case of inaccessible areas such as North Korea, the high resolution satellite imagery may be used for reference data. The objective of this paper is to investigate the possibility of utilizing QuickBird high resolution imagery of North Korea that can be obtained from Google Earth data via internet for reference data of land cover classification. Monthly MODIS NDVI data of nine months from the summer of 2004 were classified into L=54 cluster using ISODATA algorithm, and these L clusters were assigned to 7 classes - coniferous forest, deciduous forest, mixed forest, paddy field, dry field, water, and built-up areas - by careful use of reference data obtained through visual interpretation of the high resolution imagery. The overall accuracy and Kappa index were 85.98% and 0.82, respectively, which represents about 10% point increase of classification accuracy than our previous study based on GCP point data around North Korea. Thus we can conclude that Google Earth may be used to substitute the traditional reference data collection on the site where the accessibility is severely limited.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.23 no.3
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• pp.1-22
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• 2020

This study was conducted as a basic data for preparing future management alternatives by analyzing the status and characteristics of invasive alien plants by land-use type based on the formation of a new town in Goyang Siksa district. As a result, the invasive alien plants in the Goyang Siksa district were 20 families 46 genera 57 taxa; according to the land-use type, the residential area(Wi City apartment complex) is 7 families 10 genera 12 taxa, the public facilities area(Dongguk University campus) is 17 families 40 genera 47 taxa, the mixed forest is 5 families 10 genera 10 taxa, the rice paddy is 5 families 6 genera 7 taxa, river(Mt. Gyeondal creek) is 7 families 13 genera 15 taxa were appeared. The life-form of invasive alien plants in Goyang Siksa district is annuals, the origin is America, the introduction time is third period(1962~the present), and the diffusion grade is wide spread(5 grade) species. It was higher than other types. The naturalization index by location was 31.9% in river(Mt. Gyeondal creek), 21.2% in rice paddy, 16.7% in mixed forest, 15.5% in public facilities area(Dongguk University campus), and 8.5% in residential area(Wi City apartment complex). As a result of comparing the naturalization index by regions with the previous studies, it is judged that there are differences due to the environment such as urbanization progress, size, area, population inflow and location conditions. Although many new towns have been established to date, there is a lack of research on flora (including invasive alien plants) as a basic data for preparing management alternatives. Therefore, Through this study, basic data on the management of exotic plants by land use unit in urban areas can be provided.

• Environmental Engineering Research
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• v.16 no.3
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• pp.121-129
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• 2011

The completely mixed flow and plug flow (CAP) water quality model was developed for streams with discontinuous flows, a condition that often occurs in low base flow streams with in-stream hydraulic structures, especially during dry seasons. To consider the distinct physical properties of each reach effectively, the CAP model stream network can include both plug flow (PF) segments and completely mixed flow (CMF) segments. Many existing water quality models are capable of simulating various constituents and their interactions in surface water bodies. More complicated models do not necessarily produce more accurate results because of problems in data availability and uncertainties. Due to the complicated and even random nature of environmental forcing functions, it is not possible to construct an ideal model for every situation. Therefore, at present, many governmental level water quality standards and decisions are still based on lumped constituents, such as the carbonaceous biochemical oxygen demand (CBOD), the total nitrogen (TN) or the total phosphorus (TP). In these cases, a model dedicated to predicting the target concentration based on available data may provide as equally accurate results as a general purpose model. The CAP model assumes that its water quality constituents are independent of each other and thus can be applied for any constituent in waters that follow first order reaction kinetics. The CAP model was applied to the Geum River in Korea and tested for CBOD, TN, and TP concentrations. A trial and error method was used for parameter calibration using the field data. The results agreed well with QUAL2EU model predictions.

• Journal of Environmental Impact Assessment
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• v.11 no.4
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• pp.247-258
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• 2002

This study aimed at verifying the grain-sized distribution of surface deposits in a tidal flat using multi-spectral Landsat TM. In this study, we employed the grain-sized analysis, PCA and unsupervised classification techniques for analyzing the distribution of deposits. As a result in this study, the unsupervised classification method using PCA image was found to be most useful in classifying tidal flat deposits using satellite data. This method is considerably effective in analyzing not only the aspects of distribution in terms of accumulated deposits and erosion, but also the changes in seaside topography and shoreline. The grain-sized distribution analysis indicates that the mud flat inside the Cheonsu-bay tidal flat is distributed, the mixed flat located in the middle, and the sand flat distributed near the sea. The sand flat is dominant around the southern part of Seomot isle and its beach. On the other hand, the mud and mixed flat is dominant on the western part. Likewise, the western coast of Seomot isle and its beach is significantly affected by waves facing the offshore. However, the eastern side of the bay could be a site for the evolution of tidal flat made of fine materials where it is less affected by ocean waves. These results show that multi-spectral satellite data are effective for the classification of distribution materials and environmental impact assessment and continuous monitoring. In particular, the research on environmental deposits can provide important decision-supporting information for decision-making on seaside development, by analyzing the progress of deposits and environmental changes.

• Atmosphere
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• v.24 no.2
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• pp.151-158
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• 2014

This study investigated a method for the discrimination of precipitation type using thickness of geopotential height at 1000~850 hPa and improved Matsuo's scheme over South Korea using 7 upper-level observations data during winter time from 2003 to 2008. With this research, it was suggested that thickness between snow and rain should range from 1281 to 1297 gpm at 1000~850 hPa. This threshold was suitable for determining precipitation type such as snow, sleet and rain and it was verified by investigation at 7 upper-level observation and 10 surface observation data for 3 years (2009~2011). In addition, precipitation types were separated properly by Matsuo's scheme and its improved one, which is a fuction of surface air temperature and relative humidity, when they lie in mixed sectors. Precipitation types in the mixed sector were subdivided into 5 sectors (rain, rain and snow, snow and rain, snow, and snow cover). We also present the decision table for monitoring and predicting precipitation types using model output of Korea Local Analysis and Prediction System (KLAPS) and observation data.

• Journal of Preventive Medicine and Public Health
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• v.56 no.1
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• pp.21-30
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• 2023

Objectives: To prevent the spread of coronavirus disease 2019 (COVID-19), behaviors such as mask-wearing, social distancing, decreasing mobility, and avoiding crowds have been suggested, especially in high-risk countries such as Indonesia. Unfortunately, the level of compliance with those practices has been low. This study was conducted to determine the predisposing, enabling, and reinforcing factors of COVID-19 prevention behavior in Indonesia. Methods: This cross-sectional study used a mixed-methods approach. The participants were 264 adults from 21 provinces in Indonesia recruited through convenience sampling. Data were collected using a Google Form and in-depth interviews. Statistical analysis included univariate, bivariate, and multivariate logistic regression. Furthermore, qualitative data analysis was done through content analysis and qualitative data management using Atlas.ti software. Results: Overall, 44.32% of respondents were non-compliant with recommended COVID-19 prevention behaviors. In multivariate logistic regression analysis, low-to-medium education level, poor attitude, insufficient involvement of leaders, and insufficient regulation were also associated with decreased community compliance. Based on in-depth interviews with informants, the negligence of the Indonesian government in the initial stages of the COVID-19 pandemic may have contributed to the unpreparedness of the community to face the pandemic, as people were not aware of the importance of preventive practices. Conclusions: Education level is not the only factor influencing community compliance with recommended COVID-19 prevention behaviors. Changing attitudes through health promotion to increase public awareness and encouraging voluntary community participation through active risk communication are necessary. Regulations and role leaders are also required to improve COVID-19 prevention behavior.

• The Journal of Korean Academic Society of Nursing Education
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• v.30 no.3
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• pp.290-300
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• 2024

Purpose: Nursing clinical practice education is transforming with the advent of mobile education and the unique experiences it offers in caring for virtual patients. For this innovative approach, this study aims to evaluate the efficacy of mobile-based virtual women's breast cancer nursing simulation training content on nursing students' confidence, satisfaction, and learning flow. It also examines the nursing students' virtual patient care experiences. Methods: A mixed methods approach using a convergent design was employed to examine students' cancer care confidence and satisfaction, learning flow, and learning experiences. Quantitative data through online questionnaires and qualitative data through focus group interviews were collected, merged, and analyzed. Results: This study developed a virtual nursing training module aimed at caring for women with breast cancer, a novel approach to facilitate mobile-based simulation training for nursing students. Data were analyzed using descriptive analysis, a chi-squared test, Fisher's exact test, t-test for participant homogeneity (experimental: 20, control: 20), independent t-test, and paired t-test. Satisfaction (t=3.53, p=.001) and confidence (t=4.07, p=.001), as well as flow (t=3.78, p=.001), significantly improved in the experimental group compared to the control group. Two core themes and five sub-themes were derived from the experimental group's experiences acquired by caring for women with breast cancer virtually, including that the students "Virtually cared for breast cancer patients, learning as if real." Conclusion: The mobile-based virtual nursing simulation training content allowed nursing students to upgrade their comprehensive nursing care skills by experiencing a fun and practical environment made possible by a new learning method.