• Journal of the Korean Wood Science and Technology
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• v.25 no.3
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• pp.50-57
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• 1997

The presence of slime in paper mills is practically universal. Many researches have been performed for many years to resolve the problem caused by the slime in pulp and paper mill. Many papers have been published to show the bacteria is a major cause of paper mill slime. Now that the recycling of the water has been increased and the regulations of a toxic chemical dosage have become more strengthen, the importance of the control of slime in pulp and paper mill recently has been more recognized. Therefore, to produce quality products at the lowest economic and environmental costs, a through study of the microbial ecology and the indentification of troublesome slime-forming bacteria is a quite necessary. The purpose of this paper is to indentify slime~forming bacteria isolated from the papermaking process. The samples were taken from four parts of making fine paper : machine chest, head box, wire part, white water tank. Machine chest showed the most numbers of bacteria, numbering $2.55{\times}10^7$. The different colony types were taken from the 105 dilution plate. Nine bacteria were identified u sing the Biolog system and the vitek system: 6 gram-negative bacteria, 3 gram-positive bacteria. They are Pseudomonas paucimobilis B., Staphylococcus sp., Acinetobacter calcoaceticus., Pseudomonas cepacia, Actinobaci1lus capsulatus, Acidovorax sp., Flavobacterium sp., and Staphylococcus auricularis in addition to one unidentified sp., Among them. Pseudomonas paucimobillis was found in all places where the samples were taken. And, each parts had the different predominant bacteria in it : Pseudomonas paucimobilis B. in machine chest, Acinetobactor calcoaceticus. in Wire Part and Staphylococcus sp. in head box.

• Archives of Plastic Surgery
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• v.51 no.1
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• pp.139-145
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• 2024

Background Applying into plastic surgery (PS) is competitive. Lacking a home residency program (HRP) is another barrier. Our goal is to characterize challenges faced by PS applicants without HRPs and identify solutions. Methods Surveys were designed for current integrated PS residents and applicants in the 2022 Match without HRPs. Surveys were distributed electronically. Only U.S. allopathic graduate responses were included. Results Of 182 individuals surveyed, 74 responded (39%, 33 residents, 41 applicants). Sixty-six percent reported feeling disadvantaged due to lack of an HRP. Seventy-six percent of applicants successfully matched. Of these, 48% felt they required academic time off (research year) versus 10% of unmatched applicants. Ninety-seven percent of matched applicants identified a mentor versus 40% of unmatched applicants (p < 0.05). Matched applicants identified mentors through research (29%) and cold calling/emailing (25%). Matched versus unmatched applicants utilized the following resources: senior students (74 vs. 10%, p < 0.05) and social media (52 vs. 10%, p < 0.05). Among residents, 16 had PS divisions (48%). Thirty-six percent with divisions felt they had opportunities to explore PS, compared with 12% without divisions. Residents without divisions felt disadvantaged in finding research (94 vs. 65%, p < 0.05), delayed in deciding on PS (50 vs. 28%), and obtaining mentors (44 vs. 35%) and letters of recommendation (31 vs. 24%). Conclusion PS residents and applicants without HRPs reported feeling disadvantaged when matching. The data suggest that access to departments or divisions assists in matching. We identified that external outreach and research were successful strategies to obtain mentorship. To increase awareness for unaffiliated applicants, we should increase networking opportunities during local, regional, and national meetings.

• Journal of the Semiconductor & Display Technology
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• v.23 no.1
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• pp.12-18
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• 2024

The accelerated pace of climate crisis due to continuous industrialization and greenhouse gas emissions necessitates sustainable solutions that simultaneously address mitigation and adaptation to climate change. Naturebased Solutions (NbS) have gained prominence as viable approaches, with Green Infrastructure being a representative NbS. Green Infrastructure involves securing green spaces within urban areas, providing diverse climate adaptation functions such as removal of various air pollutants, carbon sequestration, and isolation. The proliferation of Green Infrastructure is influenced by the quantification of improvement effects related to various projects. To support decision-making by assessing the climate vulnerability of Green Infrastructure, the U.S. Department of Agriculture (USDA) has developed i-Tree Tools. This study proposes a comprehensive evaluation approach for climate change adaptation types by quantifying the climate adaptation performance of urban Green Infrastructure. Using i-Tree Canopy, the analysis focuses on five urban green spaces covering more than 30 hectares, considering the tree ratio relative to the total area. The evaluation encompasses aspects of thermal environment, aquatic environment, and atmospheric environment to assess the overall eco-friendliness in terms of climate change adaptation. The results indicate that an increase in the tree ratio correlates with improved eco-friendliness in terms of thermal, aquatic, and atmospheric environments. In particular, it is necessary to prioritize consideration of the water environment sector in order to realize climate change adaptive green infrastructure, such as increasing green space in urban areas, as it has been confirmed that four out of five target sites are specialized in improving the water environment.

• Journal of the Korea Safety Management & Science
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• v.26 no.3
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• pp.51-57
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• 2024

The purpose of this study is to compare and analyze the impact range of explosion damage due to gas leaks at LPG filling stations, focusing on propane and butane, which are components of vehicle LPG. The scenarios were designed based on the explosion incident at an LPG filling station in Gangwon-do, where an actual gas leak accident occurred, resulting in Scenario I and Scenario II. The ALOHA program, developed by the U.S. National Oceanic and Atmospheric Administration (NOAA), was used as the tool to analyze the impact range of the explosion damage for both substances. The results of the study indicated that, under identical conditions, propane had a wider impact range of damage than butane. This is presumed to be due to the greater explosion energy of propane, attributable to its physicochemical properties. Therefore, when preparing for LPG leak accidents, measures for propane need to be prioritized. As safety measures for propane, two suggestions were made to minimize human casualties. First, from a preventive perspective, it is suggested to educate workers about propane. Second, from the perspective of response measures and damage minimization, it is suggested to thoroughly prepare emergency evacuation and rescue plans, evacuation routes, designated shelters, and emergency response teams. This study compares and analyzes the impact range of radiative heat damage based on LPG components. However, hazardous accidents are critically influenced by the type of leaking substance, the form of the leak, and meteorological factors affecting the diffusion pattern of the substance. Therefore, for future research, it is proposed to model various leakage scenarios for the same substance to conduct a comprehensive risk assessment.

• Journal of Korean Society of Forest Science
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• v.45 no.1
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• pp.1-10
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• 1979

This study was conducted to widen the range of characteristics of the hybrids, P.alba ${\times}$ P.glandulosa, i.e. aiming for gene population expansion P.glandulosa seemed to have the similar characteristics as the one segregated from the natural hybrids between P.alba and P.davidiana. Thus the main objectives of this study were to make many crosses among poplars and then to identify leaf characteristics of the crosses similar to P.glandulosa, the results obtained can be summerized as follows; 1. Leaf characteristics such as leaf margin, presence of glands at leaf base and pubescence density, of crosses made from P.alba.davidiana ${\times}$ P.datidiana, and P.davidiana.alba ${\times}$ P.davidina showed 44% and 90%, respectively, of similarity to P.glandulosa. 2. The ratio of leaf size, including leaf length, leaf width, length from leaf base to width line, and petiole length, of the above crosses was similar to P.glandulosa. 3. Pubescence density of the dorsal leaf surface in hybrids between P.alba and P.davidiana showed generally intermediate of the parental appearance. Frequency of pubescence appearance differed from depending upon the use of P.alba, either as a female or a male parent. The use of P.alba as a male parent increased frequency of Pubescence appearance. 4. The presence of glands at the leaf base in P.glandulosa may be inherited from P.davidiana which possesses gland although gland is not present in all P.davidiana rather from P.alba which has no gland.

• Microbiology and Biotechnology Letters
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• v.39 no.4
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• pp.317-323
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• 2011

Strain A-3, an amylase-producing bacteria, was isolated from coastal seawater near Daecheon in the Republic of Korea. It was seen to possess a single polar flagella and grow well, on ASW-YP agar plates, at temperatures of between $20-37^{\circ}C$. However, it grew more slowly at the temperatures of $15^{\circ}C$ and $40^{\circ}C$. Similarly, it was observed to grow abundantly, in an Artificial Sea Water-Yeast extract-Peptone (ASW-YP) liquid medium, in a pH range of 6-9, but not grow at pHs of 4-5 and a pH of 10. Strain A-3 was noted as being close to Pseudoalteromonas phenolica O-$BC30^T$, Pseudoalteromonas luteoviolacea $NCIMB1893^T$, Pseudoalteromonas rubra $ATCC29570^T$, and Pseudoalteromonas byunsanensis $FR1199^T$, with 98.30%, 97.86%, 97.78%, and 97.25% similarities respectively, in its 16S rRNA sequence. A phylogenetic tree revealed that strain A-3 and P. phenolica O-$BC30^T$ belong to a clade. However, strain A-3 differed from P. phenolica O-$BC30^T$ in relation to a number of physiological characteristics. Strain A-3 exhibited no growth above 5% NaCl concentrations, no utilization of D-glucose, D-mannose, D-maltose, or D-melibose, and no lipase (C-14) activity. All of these properties strongly indicate that strain A-3 is distant from P. phenolica O-$BC30^T$ and thus led us to name it Pseudoalteromonas sp. A-3. Pseudoalteromonas sp. A-3 produces ${\alpha}$-amylase throughout growth. Maximal amylase activities of 144.48 U/mL and 149.20 U/mL were seen at pH 7.0 and $37^{\circ}C$, respectively. Pseudoalteromonas sp. A-3's high, stable production of ${\alpha}$-amylase in addition to its biochemical features, such as alkalitolerance, suggest that it is a good candidate for industrial applications.

• Korean Journal of Agricultural and Forest Meteorology
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• v.6 no.1
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• pp.38-48
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• 2004

Tropospheric ozone data in Korea for 1998-2002 were analyzed to assess the impact on vegetation. SUM06(sum of hourly concentrations at or above 0.06 ppm) and AOT40(accumulated exposure over a threshold of 40 ppb), widely used as ozone indices in the U.S. and Europe, were calculated based on hourly ozone concentration in 612 areas during 1998-2002 in Korea. SUM06 of the highest 30 areas were 5-12 ppm/hr which were almost the same levels of the U.S. average, and a crop loss of 5% would be expected. Ozone pollution in Seoul during 1998-2002 had decreased compared to that for 1990-97 except in the Northern area; however, ozone pollution in Kyunggi during 1998-2002 had been increased twice compare to the previous 5 years. Korea was divided into four regions: Seoul Metropolitan area, Jungbu, Honam, and Youngnam. Ozone pollution in the Seoul Metropolitan area was much higher during 1998-2000 than the other areas, but ozone pollution during 2001-2002 was almost the same in all four regions. Chunnam-Kwangyang na Kyungbuk-Gumi, famous industrial complexes in southern Korea, were significant ozone pollution areas. However, other industrial complexes, such as Incheon, Ulsan, and Kyunggi-Sihwa, were not polluted compared to their neighbors. Comparing all ozone indices, SUM06(yr), SUM06(3mon), AOT40(yr), AOT40(3mon), number of hours exceeding 100 ppb, 95 percentile, 99 percentile, and maximum concentration, it was determined reasonable to use SUM06(3mon), AOT40(3mon) and number of hours exceeding 100 ppb for evaluation of the chronic impact of ozone on vegetation.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.121-142
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• 2023

As the number and weight of imported food are steadily increasing, safety management of imported food to prevent food safety accidents is becoming more important. The Ministry of Food and Drug Safety conducts on-site inspections of foreign food facilities before customs clearance as well as import inspection at the customs clearance stage. However, a data-based safety management plan for imported food is needed due to time, cost, and limited resources. In this study, we tried to increase the efficiency of the on-site inspection by preparing a machine learning prediction model that pre-selects the companies that are expected to fail before the on-site inspection. Basic information of 303,272 foreign food facilities and processing businesses collected in the Integrated Food Safety Information Network and 1,689 cases of on-site inspection information data collected from 2019 to April 2022 were collected. After preprocessing the data of foreign food facilities, only the data subject to on-site inspection were extracted using the foreign food facility_code. As a result, it consisted of a total of 1,689 data and 103 variables. For 103 variables, variables that were '0' were removed based on the Theil-U index, and after reducing by applying Multiple Correspondence Analysis, 49 characteristic variables were finally derived. We build eight different models and perform hyperparameter tuning through 5-fold cross validation. Then, the performance of the generated models are evaluated. The research purpose of selecting companies subject to on-site inspection is to maximize the recall, which is the probability of judging nonconforming companies as nonconforming. As a result of applying various algorithms of machine learning, the Random Forest model with the highest Recall_macro, AUROC, Average PR, F1-score, and Balanced Accuracy was evaluated as the best model. Finally, we apply Kernal SHAP (SHapley Additive exPlanations) to present the selection reason for nonconforming facilities of individual instances, and discuss applicability to the on-site inspection facility selection system. Based on the results of this study, it is expected that it will contribute to the efficient operation of limited resources such as manpower and budget by establishing an imported food management system through a data-based scientific risk management model.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.979-995
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• 2023

As wildfires are difficult to predict, real-time monitoring is crucial for a timely response. Geostationary satellite images are very useful for active fire detection because they can monitor a vast area with high temporal resolution (e.g., 2 min). Existing satellite-based active fire detection algorithms detect thermal outliers using threshold values based on the statistical analysis of brightness temperature. However, the difficulty in establishing suitable thresholds for such threshold-based methods hinders their ability to detect fires with low intensity and achieve generalized performance. In light of these challenges, machine learning has emerged as a potential-solution. Until now, relatively simple techniques such as random forest, Vanilla convolutional neural network (CNN), and U-net have been applied for active fire detection. Therefore, this study proposed an active fire detection algorithm using state-of-the-art (SOTA) deep learning techniques using data from the Advanced Himawari Imager and evaluated it over East Asia and Australia. The SOTA model was developed by applying EfficientNet and lion optimizer, and the results were compared with the model using the Vanilla CNN structure. EfficientNet outperformed CNN with F1-scores of 0.88 and 0.83 in East Asia and Australia, respectively. The performance was better after using weighted loss, equal sampling, and image augmentation techniques to fix data imbalance issues compared to before the techniques were used, resulting in F1-scores of 0.92 in East Asia and 0.84 in Australia. It is anticipated that timely responses facilitated by the SOTA deep learning-based approach for active fire detection will effectively mitigate the damage caused by wildfires.

• Journal of Korean Society of Forest Science
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• v.86 no.2
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• pp.177-185
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• 1997

The influences of fertilizer treatment and clones of five willows and one hybrid poplar on above ground and soil carbon (C) accumulations in a willow bioenergy plantation were studied. The aboveground and soil samples were collected in the winter of 1992 and 1993 from the previously established willow plantation at Tully, New York, U.S.A. in 1987. Half of the plots were fertilized annually with 336kg/ha N, 112kg/ha P, and 224kg/ha K. All trees were harvested annually. The most productive clone, willow clone SV1 with fertilization, accumulated 5.4 and 6.8 t/ha/yr aboveground C contents during the sixth(1992) and seventh(1993) growing seasons, respectively. The average percentage of C in bolewood, bolebark, and branches for the five willow clones and one hybrid poplar clone ranged from 51.1 to 57.5, from 54.0 to 55.4, and from 55.6 to 56.5, respectively, among all treatment combinations. Only tyro of the six clones(SA22 and SA2) responded significantly to the addition of fertilizer by increasing the amount of aboveground C accumulated for the 1992 sampling period(clone-by-fertilizer interaction). No fertilization effect, on aboveground C content, was noted for the 1993 sampling period. No significant fertilization effect on soil C accumulation for all soil sampling depths(0-10, 10-20, and 20-40cm) was found in 1992 and 1993 sampling years. Little clone effect on soil C content was found in 1992 and 1993 sampling years, except at 0-10cm soil depth in 1992. The significant clonal effect on soil C content at 0-10cm soil depth could be because of stone content variation rather than clonal effect. The significant clone-by-fertilizer treatment interaction observed requires that evaluation of response to fertilization by willows be made for each clone individually.