• Korean Journal of Ecology and Environment
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• v.47 no.3
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• pp.167-175
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• 2014

This study was conducted to quantify a carbon budget of major vegetation types established in the campus of the National Institute of Ecology (NIE). Carbon budget was measured for Pinus thunbergii and Castanea crenata stands as the existing vegetation. Net Primary Productivity (NPP) was determined by applying allometric method and soil respiration was measured by EGM-4. Heterotrophic respiration was calculated as 55% of total respiration based on the existing results. Net Ecosystem Production (NEP) was determined by the difference between NPP and heterotrophic respiration (HR). NPPs of P. thunbergii and C. crenata stands were shown in $4.9ton\;C\;ha^{-1}yr^{-1}$ and $5.3ton\;C\;ha^{-1}yr^{-1}$, respectively. Heterotrophic respirations of P. thunbergii and C. crenata stands were shown in $2.4ton\;C\;ha^{-1}yr^{-1}$ and $3.5ton\;C\;ha^{-1}yr^{-1}$, respectively. NEPs of P. thunbergii and C. crenata stands were shown in $2.5ton\;C\;ha^{-1}yr^{-1}$ and $1.8ton\;C\;ha^{-1}yr^{-1}$, respectively. Carbon absorption capacity for the whole set of vegetation types established in the NIE was estimated by applying NEP indices obtained from current study and extrapolating NEP indices from existing studies. The value was shown in $147.6ton\;C\;ha^{-1}yr^{-1}$ and it was calculated as $541.2ton\;CO_2ha^{-1}yr^{-1}$ converted into $CO_2$. This function corresponds to 62% of carbon emission from energy that NIE uses for operation of various facilities including the glass domes known in Ecorium. This carbon offset capacity corresponds to about five times of them of the whole national territory of Korea and the representative rural area, Seocheongun. Considered the fact that ongoing climate change was originated from imbalance of carbon budget at the global level, it is expected that evaluation on carbon budget in the spatial dimension reflected land use pattern could provide us baseline information being required to solve fundamentally climate change problem.

• The Journal of Korean Academy of Prosthodontics
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• v.46 no.2
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• pp.105-115
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• 2008

Statement of problem: Proper finishing and polishing enhance both the esthetics and the longevity of restored teeth. Blade finishing technique would be suited for smoothing and finishing. Evaluation of this technique are necessary. Purpose: The purpose of this study was to evaluate the blade finishing and polishing procedures on the surface profile and roughness of ormocer-based composite resin and nanohybrid composite resin. Material and methods: The material included a ormocer-based composite resin ($Admira^{(R)}$ & $Admira^{(R)}$ Flow); a nanohybrid composite resin ($Grandio^{(R)}$ & $Grandio^{(R)}$ Flow). One hundred forty specimens of each group were prepared using a mylar strip and randomly divied into blade finishing and rubber polishing groups (n=10). The average surface roughness (Ra) in micrometers was measured and the surface profile was examined by scanning electron microscopy (SEM) (Magnification ${\times}$ 200). The data were analyzed by Mann-Whitney Test at 0.05 significance level. Conclusion: The results of this study indicated that the mylar strip produced the smoothest surface on all materials and among the finishing-polishing methods was not significanct difference (P>0.05). Ormocer-based flowable composite resin performedthe lowest variability in initial surface roughness among the tested materials.

• Journal of Intelligence and Information Systems
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• v.27 no.2
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• pp.1-15
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• 2021

If it is difficult for us to make decisions, we ask for advice from friends or people around us. When we decide to buy products online, we read anonymous reviews and buy them. With the advent of the Data-driven era, IT technology's development is spilling out many data from individuals to objects. Companies or individuals have accumulated, processed, and analyzed such a large amount of data that they can now make decisions or execute directly using data that used to depend on experts. Nowadays, the recommender system plays a vital role in determining the user's preferences to purchase goods and uses a recommender system to induce clicks on web services (Facebook, Amazon, Netflix, Youtube). For example, Youtube's recommender system, which is used by 1 billion people worldwide every month, includes videos that users like, "like" and videos they watched. Recommended system research is deeply linked to practical business. Therefore, many researchers are interested in building better solutions. Recommender systems use the information obtained from their users to generate recommendations because the development of the provided recommender systems requires information on items that are likely to be preferred by the user. We began to trust patterns and rules derived from data rather than empirical intuition through the recommender systems. The capacity and development of data have led machine learning to develop deep learning. However, such recommender systems are not all solutions. Proceeding with the recommender systems, there should be no scarcity in all data and a sufficient amount. Also, it requires detailed information about the individual. The recommender systems work correctly when these conditions operate. The recommender systems become a complex problem for both consumers and sellers when the interaction log is insufficient. Because the seller's perspective needs to make recommendations at a personal level to the consumer and receive appropriate recommendations with reliable data from the consumer's perspective. In this paper, to improve the accuracy problem for "appropriate recommendation" to consumers, the recommender systems are proposed in combination with context-based deep learning. This research is to combine user-based data to create hybrid Recommender Systems. The hybrid approach developed is not a collaborative type of Recommender Systems, but a collaborative extension that integrates user data with deep learning. Customer review data were used for the data set. Consumers buy products in online shopping malls and then evaluate product reviews. Rating reviews are based on reviews from buyers who have already purchased, giving users confidence before purchasing the product. However, the recommendation system mainly uses scores or ratings rather than reviews to suggest items purchased by many users. In fact, consumer reviews include product opinions and user sentiment that will be spent on evaluation. By incorporating these parts into the study, this paper aims to improve the recommendation system. This study is an algorithm used when individuals have difficulty in selecting an item. Consumer reviews and record patterns made it possible to rely on recommendations appropriately. The algorithm implements a recommendation system through collaborative filtering. This study's predictive accuracy is measured by Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE). Netflix is strategically using the referral system in its programs through competitions that reduce RMSE every year, making fair use of predictive accuracy. Research on hybrid recommender systems combining the NLP approach for personalization recommender systems, deep learning base, etc. has been increasing. Among NLP studies, sentiment analysis began to take shape in the mid-2000s as user review data increased. Sentiment analysis is a text classification task based on machine learning. The machine learning-based sentiment analysis has a disadvantage in that it is difficult to identify the review's information expression because it is challenging to consider the text's characteristics. In this study, we propose a deep learning recommender system that utilizes BERT's sentiment analysis by minimizing the disadvantages of machine learning. This study offers a deep learning recommender system that uses BERT's sentiment analysis by reducing the disadvantages of machine learning. The comparison model was performed through a recommender system based on Naive-CF(collaborative filtering), SVD(singular value decomposition)-CF, MF(matrix factorization)-CF, BPR-MF(Bayesian personalized ranking matrix factorization)-CF, LSTM, CNN-LSTM, GRU(Gated Recurrent Units). As a result of the experiment, the recommender system based on BERT was the best.

• Journal of Korea Water Resources Association
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• v.56 no.4
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• pp.235-243
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• 2023

Due to the revision of the River Act and the enactment of the Act on the Investigation, Planning, and Management of Water Resources, a regular bed change survey has become mandatory and a system is being prepared such that local governments can manage water resources in a planned manner. Since the topography of a bed cannot be measured directly, it is indirectly measured via contact-type depth measurements such as level survey or using an echo sounder, which features a low spatial resolution and does not allow continuous surveying owing to constraints in data acquisition. Therefore, a depth measurement method using remote sensing-LiDAR or hyperspectral imaging-has recently been developed, which allows a wider area survey than the contact-type method as it acquires hyperspectral images from a lightweight hyperspectral sensor mounted on a frequently operating drone and by applying the optimal bandwidth ratio search algorithm to estimate the depth. In the existing hyperspectral remote sensing technique, specific physical quantities are analyzed after matching the hyperspectral image acquired by the drone's path to the image of a surface unit. Previous studies focus primarily on the application of this technology to measure the bathymetry of sandy rivers, whereas bed materials are rarely evaluated. In this study, the existing hyperspectral image-based water depth estimation technique is applied to rivers with vegetation, whereas spatio-temporal hyperspectral imaging and cross-sectional hyperspectral imaging are performed for two cases in the same area before and after vegetation is removed. The result shows that the water depth estimation in the absence of vegetation is more accurate, and in the presence of vegetation, the water depth is estimated by recognizing the height of vegetation as the bottom. In addition, highly accurate water depth estimation is achieved not only in conventional cross-sectional hyperspectral imaging, but also in spatio-temporal hyperspectral imaging. As such, the possibility of monitoring bed fluctuations (water depth fluctuation) using spatio-temporal hyperspectral imaging is confirmed.

• Journal of Bio-Environment Control
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• v.32 no.3
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• pp.249-255
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• 2023

Korean melon (Cucumis melo L.) is grown mostly in Northeast Asia area, and as a fruit mainly produced in Korea, the yield per unit area continues to improve, but the cultivation method is limited to soil cultivation, so it is necessary to develop hydroponic cultivation technology for scale and labor-saving is needed. As the ratio of NO₃^- increased, the plant height, the leaf length, the leaf width, and the internode length became longer and larger. On the other hand, the SPAD value decreased. The lower the ratio of NO₃^-, the faster the female flower bloom, and there was no difference in fruit maturity between treatments. There was no difference in the shape of fruit according to the ratio of NO₃^-, and the hardness was higher as the ratio of NO₃^- was lower. The total yield from March to July was KM3 5,650 kg/10a and KM1 4,439 kg/10a, 27% higher in KM3 and, in particular, 36% higher in quantity from March to May, when Korean melon prices were high season. Therefore, it was judged that it would be appropriate to supply NO₃^- suitable for hydroponic cultivation of Korean melon, which was formalized in December and produced from spring, at the level of 6.5 to 10 me·L^-1.

• Analytical Science and Technology
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• v.20 no.5
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• pp.434-441
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• 2007

The aim of this paper is to investigate composition of fatty acids in sweat on purpose of latent fingerprint detectant developing and crime evidence searching. Fingerprint from 5 male donors (aged 29-50 years) were collected. We identified fatty acid components on sweat using methylester mixture (37species) as standard fatty acid and analyzed them by GC-FID. As donor was aged, the level of total fat was found to decrease markedly (aged 20-30 years: 56.4-72.0 %, aged 50 years : 32.4-45.4 %). We identifided 28 species fatty acid, primarilly C16:0(palmitic acid), C16:1 (palmitoleic acid), C18:1n9c(oleic acid), C18:0 (stearic acid), C14:0 (tetradecanoic acid) and all sweats were found to contain C12:0 (lauric acid), C15:0 (pentadecanoic acid), C18:2n6c (linoleic acid), C18:2n6t (linolelaidic acid), C20:0 (arachidic acid), C24:0/C20:5n3 (lignoceric acid/eicosapentaenoic acid), but with differing frequencies and at varying levels. C14:1 (myristoleic acid), C15:1 (pentadecenoic acid), C21:0 (heneicosanoic acid), C22:1n9 (erucic acid) were often observed in sample. Ratio of saturated and unsaturated fatty acid was from 0.94:1 to 2.6:1. And decrease of total fatty acids components caused by loss of saturated fatty acid and monounsaturated fatty acid. In case of sweat amino acids, we detected serine ($0-31.9{\mu}L/mL$), threonine ($0-26.2{\mu}L/mL$), glycine ($0-18.9{\mu}L/mL$) and 20-30 years old, highly protein intake ratio individuals increased (10 times) than 50 years old. We observed greatly individual characterization of amino acid compounds in sweat.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.19-19
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• 2022

Hulled and naked oat is a perspective crop for the low input production systems due to its low requirements for soil quality and nutrition. Oats have good competitive ability against weeds and can provide appropriate yield in organic farming in comparison with other cereal species such as wheat or barley. It is a perspective crop from the point of view of use in the food industry too. The aim of our study was to compare the production and quality parameters of naked and hulled oat grown in both organic (OF) and conventional fields (CF). Small plot trials were conducted in two locations in the Czech Republic (České Budějovice, Prague) for four years (2018-2021) in two production systems (OF, and CF). We used four varieties of hulled oat (Korok, Kertag, Raven, Seldon) and one variety of naked oat (Patrik). During the vegetation, agronomically important data were recorded. After harvest samples were processed in the laboratory and analyzed selected quality parameters of grain dry matter (the protein content was determined by the Kjeldahl method, starch content in grain according to Ewers, fat content in grain dry matter by the modified method according to Soxhlet, and ash content in grain dry matter). The data were evaluated using the program STATISTICA version 13.2, StatSoft, Inc., California, USA. It is clear from the results that the number of panicles before the harvest was influenced by the location, cultivation system, year, and, to a lesser extent, the influence of the variety. The number of panicles in OF averaged 340 per square meter, which was 90% of the value of CF. For thousand grain weight (TGW), a significantly predominant effect of year was found. The independent effect of location on TGW was statistically not significant. Grain yield was predominantly influenced by cultivation system and location. In OF, it reached an average of 3.97 t.ha^-1, which was 75% of the yield of CF. As part of the evaluation of the basic grain quality indicators, the content of protein, starch, fat, and ash in the dry matter of the grain was evaluated. The content of protein in the dry matter of the grain was predominantly influenced by year, followed by the influence of the variety and a fairly comparable influence of the cultivation system and locality. On average, it achieved 16.05% in OF and 17.01% in CF. The starch content was then related to the protein content, where as a result of the lower protein content in the grain of OF oats, the content of starch and fat was on the contrary increased. The year turned out to be the most significant factor, affecting both the starch content in the dry matter of the grain and the fat content. This was followed again by a fairly comparable influence on the cultivation system and locality. The influence of the cultivation system and location was not statistically significantly applied in the case of ash content in dry matter. Based on our results we can propose both types of oat (hulled and naked) as perspective crops for OF. An organic farmer can expect to achieve stable yields which, in less favorable conditions for the production of cereals in the OF, may be close to the level of conventional yields. In the future, it will be important to change agrotechnology in OF and increase oat yield because this crop has a good potential to grow in areas with low nitrogen input or less fertile soil.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.3
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• pp.147-163
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• 2022

The relocation policy of public Institutions throughout provincial areas that implemented for the purpose of "balanced national development" finished in 2019 with the last relocation of the Korea Institute of Science & Technology Evaluation and Planning, which moved to Chungbuk Innovation City. Electric power public corporations also completed relocation program over eight regions across the nation. This study was conducted empirically to identify the structural relationship between the public service motivation and job attitude. In this, the relationship of organizational change, particularly occurred by the regional relocation, with the psychological state of these organization members (experienced direct changes and got substantial impacts in various aspects such as psychological, economic and living environment, etc.,) was studied. This study aims to seek early organizational stabilization ideas for electric power public corporations after relocation, and to present some implications that can contribute to the secondary relocation of public institutions to local areas. This study shows the statistically significant relationship between the psychological state occurred by relocation and organizational commitment. The result shows that the higher the expectation levels, the higher the degree of organizational commitment, while anxious psychological state has no relation with that. Additionally, expectation level has no significant functional relation with turnover intention. Followings are the major conclusions revealed in this study; The stronger the anxious psychological state, the higher the turnover inducement goes up. The higher the expectation levels, the higher the public service motivation grows, and the higher the anxiety psychological state, the public service motivation lowers. The organizational commitment grows according to the public service motivation proportionally, but the turnover inducement intention is weak. The moderating effect of public service motivation between the expectation of organizational change and turnover intention was not significant, but it was analyzed that the moderating effect of public service motivation formed a significant relationship with other anxiety psychology. The expectation levels of employees of electric power public corporations has grown up after moving to provincial areas. Relationship between the expectation mind and the turnover inducement has decreased after local relocation.

• Korean Journal of Remote Sensing
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• v.40 no.2
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• pp.229-241
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• 2024

With the advancement of big data processing technology using cloud platforms, access, processing, and analysis of large-volume data such as satellite imagery have recently been significantly improved. In this study, the Change Detection Method, a relatively simple technique for retrieving soil moisture, was applied to the backscattering coefficient values of pre-processed Sentinel-1 synthetic aperture radar (SAR) satellite imagery product based on Google Earth Engine (GEE), one of those platforms, to estimate the surface soil moisture for six observatories within the Yongdam Dam watershed in South Korea for the period of 2015 to 2023, as well as the watershed average. Subsequently, a correlation analysis was conducted between the estimated values and actual measurements, along with an examination of the applicability of GEE. The results revealed that the surface soil moisture estimated for small areas within the soil moisture observatories of the watershed exhibited low correlations ranging from 0.1 to 0.3 for both VH and VV polarizations, likely due to the inherent measurement accuracy of the SAR satellite imagery and variations in data characteristics. However, the surface soil moisture average, which was derived by extracting the average SAR backscattering coefficient values for the entire watershed area and applying moving averages to mitigate data uncertainties and variability, exhibited significantly improved results at the level of 0.5. The results obtained from estimating soil moisture using GEE demonstrate its utility despite limitations in directly conducting desired analyses due to preprocessed SAR data. However, the efficient processing of extensive satellite imagery data allows for the estimation and evaluation of soil moisture over broad ranges, such as long-term watershed averages. This highlights the effectiveness of GEE in handling vast satellite imagery datasets to assess soil moisture. Based on this, it is anticipated that GEE can be effectively utilized to assess long-term variations of soil moisture average in major dam watersheds, in conjunction with soil moisture observation data from various locations across the country in the future.

• Journal of the Korean Society of Radiology
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• v.18 no.4
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• pp.327-334
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• 2024

The purpose of this study is to develop a customized foot disease analysis and management system for diabetic patients to prevent foot ulcers in diabetic foot disease patients. This system utilizes image analysis technology to measure not only foot pressure, but also ankle deformation, body balance, and foot wounds. Through various data, it is possible to accurately analyze the state of foot deformation, and based on this, the exact state of deformation of the foot of a patient with diabetic foot disease was identified and a customized insole was produced. This study was conducted to examine the satisfaction level of using an application that checks the status of diabetic foot disease wounds and to identify the degenerative status of diabetic foot disease patients and foot disease patients by wearing customized insoles and to survey the satisfaction of wearing insoles. As a result of the study, the knee angle measured for plantar pressure was -0.8 ± 1.3 degrees and ranged from a minimum of -2.4 degrees to a maximum of 1.1 degrees, and there was no significant difference in valgus knee between both lower extremities (p = 0.534). There was a significant difference in tibial angle between both lower extremities (p < 0.001). Ankle angle on the left side was 2.6 ± 2.0 degrees, ranging from a minimum of 0 degrees to a maximum of 6.3 degrees, and on the right, it was 4.5 ± 2.1 degrees, with a distribution of minimum 1.5 degrees to a maximum of 9.1 degrees. There was a significant difference in ankle angle between both lower extremities (p = 0.011). They responded that they felt an average of 4.3 points of satisfaction with the plantar pressure measurement application. Respondents responded that they felt an average of 3.9 points of satisfaction with the use of customized insoles.