KSCE Journal of Civil and Environmental Engineering Research
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v.30
no.3A
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pp.297-307
/
2010
Recently, maintenance engineering and technology for civil and building structures have begun to draw big attention and actually the number of structures that need to be evaluate on structural safety due to deterioration and performance degradation of structures are rapidly increasing. When stiffness is decreased because of deterioration of structures and member cracks, dynamic characteristics of structures would be changed. And it is important that the damaged areas and extent of the damage are correctly evaluated by analyzing dynamic characteristics from the actual behavior of a structure. In general, typical measurement instruments used for structure monitoring are dynamic instruments. Existing dynamic instruments are not easy to obtain reliable data when the cable connecting measurement sensors and device is long, and have uneconomical for 1 to 1 connection process between each sensor and instrument. Therefore, a method without attaching sensors to measure vibration at a long range is required. The representative applicable non-contact methods to measure the vibration of structures are laser doppler effect, a method using GPS, and image processing technique. The method using laser doppler effect shows relatively high accuracy but uneconomical while the method using GPS requires expensive equipment, and has its signal's own error and limited speed of sampling rate. But the method using image signal is simple and economical, and is proper to get vibration of inaccessible structures and dynamic characteristics. Image signals of camera instead of sensors had been recently used by many researchers. But the existing method, which records a point of a target attached on a structure and then measures vibration using image processing technique, could have relatively the limited objects of measurement. Therefore, this study conducted shaking table test and field load test to verify the validity of the method that can measure multi-point displacement responses of structures using image processing technique.
Ye Seong Kang;Ki Su Park;Eun Li Kim;Jong Chan Jeong;Chan Seok Ryu;Jung Gun Cho
Korean Journal of Remote Sensing
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v.39
no.5_1
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pp.669-681
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2023
Studies have tried to apply remote sensing technology, a non-destructive survey method, instead of the existing destructive survey, which requires relatively large labor input and a long time to estimate chlorophyll content, which is an important indicator for evaluating the growth of fruit trees. This study was conducted to non-destructively evaluate the chlorophyll content of pear tree leaves using unmanned aerial vehicle-based hyperspectral imagery for two years(2021, 2022). The reflectance of the single bands of the pear tree canopy extracted through image processing was band rationed to minimize unstable radiation effects depending on time changes. The estimation (calibration and validation) models were developed using machine learning algorithms of elastic-net, k-nearest neighbors(KNN), and support vector machine with band ratios as input variables. By comparing the performance of estimation models based on full band ratios, key band ratios that are advantageous for reducing computational costs and improving reproducibility were selected. As a result, for all machine learning models, when calibration of coefficient of determination (R2)≥0.67, root mean squared error (RMSE)≤1.22 ㎍/cm2, relative error (RE)≤17.9% and validation of R2≥0.56, RMSE≤1.41 ㎍/cm2, RE≤20.7% using full band ratios were compared, four key band ratios were selected. There was relatively no significant difference in validation performance between machine learning models. Therefore, the KNN model with the highest calibration performance was used as the standard, and its key band ratios were 710/714, 718/722, 754/758, and 758/762 nm. The performance of calibration showed R2=0.80, RMSE=0.94 ㎍/cm2, RE=13.9%, and validation showed R2=0.57, RMSE=1.40 ㎍/cm2, RE=20.5%. Although the performance results based on validation were not sufficient to estimate the chlorophyll content of pear tree leaves, it is meaningful that key band ratios were selected as a standard for future research. To improve estimation performance, it is necessary to continuously secure additional datasets and improve the estimation model by reproducing it in actual orchards. In future research, it is necessary to continuously secure additional datasets to improve estimation performance, verify the reliability of the selected key band ratios, and upgrade the estimation model to be reproducible in actual orchards.
Yu Jeong Roh;Ji Eun Kim;You Jeong Jin;Ayun Seol;Hee Jin Song;Tae Ryeol Kim;Kyeong Seon Min;Eun Seo Park;Ki Ho Park;Dae Youn Hwang
Journal of Life Science
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v.33
no.11
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pp.887-896
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2023
The inflammatory response have been considered as one of important targets for cancer treatment because they play a key role during all steps of tumor development including initiation, promotion, malignant conversion and progression. To investigate the anti-inflammatory response during anti-tumor activity of an aqueous extracts of Ecklonia cava (AEC), alterations on the distribution of mast cells and the expression of inducible nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2), nuclear factor (NF)-κB, inflammasome compositional protein and inflammatory cytokines were examined in CT26 colon tumor-bearing BALB/cKorl syngeneic mice after administrating AEC for five weeks. After treatment of AEC, total weight of tumor and necrotic region of tumor section were significantly decreased compared to vehicle treated group. The number of infiltered mast cells was higher in AEC treated group than vehicle treated group, while the expression levels of COX-2 and iNOS were decreased in AEC treated group. Also, similar decrease pattern were detected in the expression levels of NF-κB, NLR family pyrin domain containing 3 (NLRP3), apoptosis-associated speck-like protein containing a caspase recruitment domain (ASC) and caspase-1 (Cas-1) after AEC treatment although the decrease rate was varied. Furthermore, the mRNA expressions of three inflammatory cytokines including tumor necrosis factor-α (TNF-α), interleukin-1α (IL-1α) and interleukin-6 (IL-6) were remarkably decreased in AEC treated group compared to vehicle treated group. These results suggest that inhibition of inflammatory response may be tightly associated with anti-tumor activity of AEC in CT26 colon tumor-bearing BALB/cKorl syngeneic mice.
Won-Woo Seo;Hongki Kang;Wansang Yoon;Pyung-Chae Lim;Sooahm Rhee;Taejung Kim
Korean Journal of Remote Sensing
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v.39
no.6_1
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pp.1211-1224
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2023
Clouds cause many difficult problems in observing land surface phenomena using optical satellites, such as national land observation, disaster response, and change detection. In addition, the presence of clouds affects not only the image processing stage but also the final data quality, so it is necessary to identify and remove them. Therefore, in this study, we developed a new cloud detection technique that automatically performs a series of processes to search and extract the pixels closest to the spectral pattern of clouds in satellite images, select the optimal threshold, and produce a cloud mask based on the threshold. The cloud detection technique largely consists of three steps. In the first step, the process of converting the Digital Number (DN) unit image into top-of-atmosphere reflectance units was performed. In the second step, preprocessing such as Hue-Value-Saturation (HSV) transformation, triangle thresholding, and maximum likelihood classification was applied using the top of the atmosphere reflectance image, and the threshold for generating the initial cloud mask was determined for each image. In the third post-processing step, the noise included in the initial cloud mask created was removed and the cloud boundaries and interior were improved. As experimental data for cloud detection, CAS500-1 L2G images acquired in the Korean Peninsula from April to November, which show the diversity of spatial and seasonal distribution of clouds, were used. To verify the performance of the proposed method, the results generated by a simple thresholding method were compared. As a result of the experiment, compared to the existing method, the proposed method was able to detect clouds more accurately by considering the radiometric characteristics of each image through the preprocessing process. In addition, the results showed that the influence of bright objects (panel roofs, concrete roads, sand, etc.) other than cloud objects was minimized. The proposed method showed more than 30% improved results(F1-score) compared to the existing method but showed limitations in certain images containing snow.
Sea ice currently covers approximately 7% of the world's ocean area, primarily concentrated in polar and high-altitude regions, subject to seasonal and annual variations. It is very important to analyze the area and type classification of sea ice through time series monitoring because sea ice is formed in various types on a large spatial scale, and oil and gas exploration and other marine activities are rapidly increasing. Currently, research on the type and area of sea ice is being conducted based on high-resolution satellite images and field measurement data, but there is a limit to sea ice monitoring by acquiring field measurement data. High-resolution optical satellite images can visually detect and identify types of sea ice in a wide range and can compensate for gaps in sea ice monitoring using Geostationary Ocean Color Imager-II (GOCI-II), an ocean satellite with short time resolution. This study tried to find out the possibility of utilizing sea ice monitoring by training a rule-based machine learning model based on learning data produced using high-resolution optical satellite images and performing detection on GOCI-II images. Learning materials were extracted from Liaodong Bay in the Bohai Sea from 2021 to 2022, and a Random Forest (RF) model using GOCI-II was constructed to compare qualitative and quantitative with sea ice areas obtained from existing normalized difference snow index (NDSI) based and high-resolution satellite images. Unlike NDSI index-based results, which underestimated the sea ice area, this study detected relatively detailed sea ice areas and confirmed that sea ice can be classified by type, enabling sea ice monitoring. If the accuracy of the detection model is improved through the construction of continuous learning materials and influencing factors on sea ice formation in the future, it is expected that it can be used in the field of sea ice monitoring in high-altitude ocean areas.
So Hyun Park;Hyeon Hwa Oh;Do Youn Jeong;Young-Soo Kim
Food Science and Preservation
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v.30
no.4
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pp.703-715
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2023
This study was conducted to investigate the fermentation characteristics and anti-obesity effects of acetic acid fermentation products of coffee wine. The live cell counts, soluble solids, pH and total acidity of the acetic acid unfermented coffee wine (AUFCW; day 0, before fermentation) were 6.35 log CFU/mL, 8.10 °Brix, 3.88, and 1.29%, respectively, while the acetic acid fermented coffee wine (AFCW; day 15, after fermentation) were 4.40 log CFU/mL, 8.57 °Brix, 3.07, and 7.45%, respectively. Pancreatic lipase inhibitory activity tended to increase as the acetic acid fermentation period increased. The anti-obesity effects of AFCW on 3T3-L1 cells, which was induced by MDI, were evaluated based on the lipid accumulation rate, leptin expression, and fat production-related gene expression (PPAR-γ and SREBP-1c) at the mRNA level. In the case of AFCW, the lipid accumulation rate and leptin expression were decreased to 69.37% and 50.20% at a concentration of 200 ㎍/mL, respectively, and the expression levels of PPAR-γ and SREBP-1c at the mRNA level were decreased to 79.89% and 48.81%, respectively. These results indicate that anti-obesity effect of acetic acid fermentation products could be increased by acetic acid fermentation of coffee wine.
Original scripts of e-learning lectures for the CEOs of corporation S were analyzed using topic analysis, which is a text mining method. Twenty-two topics were extracted based on the keywords chosen from five-year records that ranged from 2011 to 2015. Research analysis was then conducted on various issues. Promising topics were selected through evaluation and element analysis of the members of each topic. In management and economics, members demonstrated high satisfaction and interest toward topics in marketing strategy, human resource management, and communication. Philosophy, history of war, and history demonstrated high interest and satisfaction in the field of humanities, whereas mind health showed high interest and satisfaction in the field of in lifestyle. Studies were also conducted to identify topics on the proportion of content, but these studies failed to increase member satisfaction. In the field of IT, educational content responds sensitively to change of the times, but it may not increase the interest and satisfaction of members. The present study found that content production for CEOs should draw out deep implications for value innovation through technology application instead of simply ending the technical aspect of information delivery. Previous studies classified contents superficially based on the name of content program when analyzing the status of content operation. However, text mining can derive deep content and subject classification based on the contents of unstructured data script. This approach can examine current shortages and necessary fields if the service contents of the themes are displayed by year. This study was based on data obtained from influential e-learning companies in Korea. Obtaining practical results was difficult because data were not acquired from portal sites or social networking service. The content of e-learning trends of CEOs were analyzed. Data analysis was also conducted on the intellectual interests of CEOs in each field.
Thanks to the growth of computing power and the recent development of data analytics, researchers have started to work on the data produced by users through the Internet or social media. This study is in line with these recent research trends and attempts to adopt data analytical techniques. We focus on the impact of "internal marketing" factors on firm performance, which is typically studied through survey methodologies. We looked into the job review platform Jobplanet (www.jobplanet.co.kr), which is a website where employees and former employees anonymously review companies and their management. With web crawling processes, we collected over 40K data points and performed morphological analysis to classify employees' reviews for internal marketing data. We then implemented econometric analysis to see the relationship between internal marketing and market capitalization. Contrary to the findings of extant survey studies, internal marketing is positively related to a firm's market capitalization only within a limited area. In most of the areas, the relationships are negative. Particularly, female-friendly environment and human resource development (HRD) are the areas exhibiting positive relations with market capitalization in the manufacturing industry. In the service industry, most of the areas, such as employ welfare and work-life balance, are negatively related with market capitalization. When firm size is small (or the history is short), female-friendly environment positively affect firm performance. On the contrary, when firm size is big (or the history is long), most of the internal marketing factors are either negative or insignificant. We explain the theoretical contributions and managerial implications with these results.
Hye Ran Kim;Seol Hwa Park;Jisoo Wi;Seongshin Lee;Sung Dae Lee;Hwan Ku Kang;Chaehwa Ryu
Korean Journal of Poultry Science
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v.51
no.2
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pp.57-63
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2024
As global warming worsens, it is feared that higher ambient temperatures and relative humidity might result in a more intense heat stress for livestock animals, especially broilers, which lack sweat glands for thermoregulation and have been selectively bred for rapid growth. Therefore, strategic livestock management is needed to mitigate the adverse effects of heat stress on broilers. In Korea's poultry farming systems, tunnel-ventilated broiler houses and pad cooling systems are commonly installed to lower indoor temperatures during the summer. However, caution is advised with pad cooling systems as they can increase the humidity inside the houses, potentially causing further harm. This study aimed to evaluate the effectiveness of pad cooling systems in tunnel-ventilated broiler house by assessing the reduction in indoor temperature using the Temperature-Humidity Index (THI), which accounts for the impact of relative humidity. Temperature and humidity data were collected during the summer (Jun to Sep) from eight farms with tunnel-ventilated broiler house located in different regions of Korea. The farms were divided into two groups based on the use of pad cooling systems is used, and temperature and humidity data, along with THI values, were analyzed two weeks before the birds were marketed. Meta-analysis results showed that at the hottest time of the day, 14:00, farms with pad cooling systems had significantly lower indoor temperatures compared to the control group, but observed an increase in indoor temperatures by 16:00 (p<0.05). There is no significant difference in relative humidity (p>0.05). The THI values decreased in the treatment group with cooling pads compared to the control group starting from 15:00, suggesting a diminished effect (p<0.05). This study indicates the potential for developing optimal operational guidelines for cooling pads to reduce heat stress in broilers during the summer season.
Jung Hee Byon;Gong Yong Jin;Young Min Han;Eun Jung Choi;Kum Ju Chae;Eun Hae Park
Journal of the Korean Society of Radiology
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v.84
no.4
/
pp.900-910
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2023
Purpose To assess normal CT scans with quantitative CT (QCT) analysis based on smoking habits and chronic obstructive pulmonary disease (COPD). Materials and Methods From January 2013 to December 2014, 90 male patients with normal chest CT and quantification analysis results were enrolled in our study [non-COPD never-smokers (n = 38) and smokers (n = 45), COPD smokers (n = 7)]. In addition, an age-matched cohort study was performed for seven smokers with COPD. The square root of the wall area of a hypothetical bronchus of internal perimeter 10 mm (Pi10), skewness, kurtosis, mean lung attenuation (MLA), and percentage of low attenuation area (%LAA) were evaluated. Results Among patients without COPD, the Pi10 of smokers (4.176 ± 0.282) was about 0.1 mm thicker than that of never-smokers (4.070 ± 0.191, p = 0.047), and skewness and kurtosis of smokers (2.628 ± 0.484 and 6.448 ± 3.427) were lower than never-smokers (2.884 ± 0.624, p = 0.038 and 8.594 ± 4.944, p = 0.02). The Pi10 of COPD smokers (4.429 ± 0.435, n = 7) was about 0.4 mm thicker than never-smokers without COPD (3.996 ± 0.115, n = 14, p = 0.005). There were no significant differences in MLA and %LAA between groups (p > 0.05). Conclusion Even on normal CT scans, QCT showed that the airway walls of smokers are thicker than never-smokers regardless of COPD and it preceded lung parenchymal changes.
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