• Journal of Food Hygiene and Safety
• /
• v.36 no.6
• /
• pp.493-503
• /
• 2021

The study was designed to analyze raw and auxiliary materials of Korean traditional cookies such as Yugwa and Gangjeong, equipment and tools, personal hygiene of workers and microbial contamination of materials by each manufacturing process. In addition, it looked at washing method for reducing microorganisms at the site and reduction effect of microorganisms by frequency in the manufacturing processes of Yugwa. In the process of producing Korean traditional cookies, the level of total aerobic bacteria (TAB) in popped rice was 1.2 Log CFU/g and the level of TAB in finished products increased to 3.7 Log CFU/g. In the process of producing Yugwa, the level of TAB increased to a maximum of 6.5 Log CFU/g in the soaking process but decreased to 1.3 Log CFU/g in the frying process. However, the level of TAB increased again to 1.3 Log CFU/g in finished products that proves its recontamination. It is estimated that he manufacturing process causes cross-contamination that comes from the work tools, equipment or workers. In particular, the spatula, one of the work tools, was found to have 4.4 Log CFU/g of aerobic bacteria and 4.2 Log CFU/g of colon bacillus that show they are highly contaminated. In the soaking process of Yugwa that lasts seven days, the level of TAB was a maximum of 10 Log CFU/g and the level of total colon bacillus was 6.8 Log CFU/g. When compared with washing methods, using hands and tools or running water, it is confirmed that the level of both TAB and total colon bacillus decreased to 5.0 Log CFU/g and 2.8 Log CFU/g respectively when hands were washed with running water 10 times. The above result shows that it's required for workers to wash their hands as well as wash and disinfect work tools and equipment in the process of producing Korean traditional cookies at small-scale companies. In addition, to reduce the level of microbial contamination in finished products, workers are required to apply their reduction method at the site.

• Journal of the Korean Wood Science and Technology
• /
• v.32 no.2
• /
• pp.19-25
• /
• 2004

This study was carried out to investigate a radial distribution of moisture contents (MCs) within a log cross section (LC) during oven-drying of 3 mm-thick circumferential slices cut from several domestic softwoods LCs.For Korean red pine, drying rate of sapwood slices during oven-drying represented much higher values than that of heartwood slices, and so sapwood with higher green MC early reached below fiber saturation point (FSP) rather than heartwood did. However, this distribution of moistures did not last for long duration. For Japanese larch, green MC of sapwood was approximately three times higher than that of heartwood. This similar distribution in MC was lasted until about 20% average MC. The MC was around uniform throughout the sapwood of Ginkgo when green and during oven-drying, although it was somewhat fluctuated. For Japanese cedar, the heartwood with so low moistures around FSP would begin to shrink from the beginning stage of drying, but the sapwood above hygroscopic MC prevents the heartwood from shrinking, and consequently, the heartwood or the transition wood goes into tension stress. The results for Japanese cypress showed that the green MCs of the sapwoods were much lower than those for heartwoods, and then this trend was continued until about 20% in average MC. For Chinese thuja, the green MCs of sapwoods were about 2 times as high as those of heartwood, but this along the radial gradient in MC rapidly became gentle during oven-drying.

• Resources Recycling
• /
• v.31 no.5
• /
• pp.67-76
• /
• 2022

The furniture industry has a high possibility to create value-added and a high potential to create new occupations due to the characteristics of the industry, which mainly consists of small and medium-sized enterprises (SMEs). However, the used furniture, which has sufficient reuse value, is also crushed and used as solid refuse fuel (SRF) recently. Besides, the number of waste treatment companies continues to decrease, and it occurs congestion of wood waste. As a way to solve the issue, a business model development of remanufacturing used furniture can be suggested as an alternative due to its high circular economic efficiency. Remanufacturing business including furniture industry creates positive effects in various aspects such as economic, environmental and job creation. In other words, remanufacturing is an effective recycling way to reduce input resources and energy in the production process. The results of economic analysis show that the expected annual revenue from the single worker furniture remanufacturing site was 104 million won which is 3.11 times more than the average income of a single-worker household in Korea and its B/C ratio was estimated about 30 which means high business feasibility. Revenue through furniture remanufacturing also showed 320 times higher than that of SRF production from the perspective of weight. In addition, it is shown that the GHGs reduction from the furniture remanufacturing is 2.2 ton CO₂-eq. per year, which is similar to the amount of GHGs absorption effect of 937 pine trees or 622 Korean oak trees annually. Thus the results of this study demonstrate that it is important to adopt an appropriate recycling method considering the economic and environmental effects at the end-of-life stage.

• The Journal of Engineering Geology
• /
• v.33 no.3
• /
• pp.371-388
• /
• 2023

A stratum with a complex composition and a distributed low-permeability soil layer is difficult to remediate quickly because the soil remediation does not proceed easily. For efficient purification, the permeability should be improved and the soil remediation agent (H₂O₂) should be injected into the contaminated section to make sufficient contact with the TPH (Total petroleum hydrocarbons). This study analyzed a method for crack formation and effective delivery of the soil remediation agent based on pneumatic fracturing, plasma blasting, and vacuum suction (the PPV method) and compared its improvement effect relative to chemical oxidation. A demonstration test confirmed the effective delivery of the soil remediation agent to a site contaminated with TPH. The injection amount and injection time were monitored to calculate the delivery characteristics and the range of influence, and electrical resistivity surveying qualitatively confirmed changes in the underground environment. Permeability tests also evaluated and compared the permeability changes for each method. The amount of soil remediation agent injected was increased by about 4.74 to 7.48 times in the experimental group (PPV method) compared with the control group (chemical oxidation); the PPV method allowed injection rates per unit time (L/min) about 5.00 to 7.54 times quicker than the control method. Electrical resistivity measurements assessed that in the PPV method, the diffusion of H₂O₂2 and other fluids to the surface soil layer reduced the low resistivity change ratio: the horizontal change ratio between the injection well and the extraction well decreased the resistivity by about 1.12 to 2.38 times. Quantitative evaluation of hydraulic conductivity at the end of the test found that the control group had 21.1% of the original hydraulic conductivity and the experimental group retained 81.3% of the initial value, close to the initial permeability coefficient. Calculated radii of influence based on the survey results showed that the results of the PPV method were improved by 220% on average compared with those of the control group.

• Journal of Korea Water Resources Association
• /
• v.56 no.6
• /
• pp.403-417
• /
• 2023

In this research, a methodology was developed for constructing an appropriate rainfall image database for estimating rainfall intensity based on CCTV video. The database was constructed in the Large-Scale Climate Environment Chamber of the Korea Conformity Laboratories, which can control variables with high irregularity and variability in real environments. 1,728 scenarios were designed under five different experimental conditions. 36 scenarios and a total of 97,200 frames were selected. Rain streaks were extracted using the k-nearest neighbor algorithm by calculating the difference between each image and the background. To prevent overfitting, data with pixel values greater than set threshold, compared to the average pixel value for each image, were selected. The area with maximum pixel variability was determined by shifting with every 10 pixels and set as a representative area (180×180) for the original image. After re-transforming to 120×120 size as an input data for convolutional neural networks model, image augmentation was progressed under unified shooting conditions. 92% of the data showed within the 10% absolute range of PBIAS. It is clear that the final results in this study have the potential to enhance the accuracy and efficacy of existing real-world CCTV systems with transfer learning.

• The Journal of Engineering Geology
• /
• v.33 no.2
• /
• pp.275-291
• /
• 2023

Global warming has made the polar regions more accessible, leading to increased demand for the construction of new resource-development plants in oil-rich permafrost regions. The selection of locations of resource-development plants in permafrost regions should consider the surface displacement resulting from thawing and freezing of the active layer of permafrost. However, few studies have considered surface displacement in the selection of optimal locations of resource-development plants in permafrost region. In this study, Analytic Hierarchy Process (AHP) analysis using a range of geospatial information variables was performed to select optimal locations for the construction of oil-sands development plants in the permafrost region of southern Athabasca, Alberta, Canada, including consideration of surface displacement. The surface displacement velocity was estimated by applying the Small BAseline Subset Interferometric Synthetic Aperture Radar technique to time-series Advanced Land Observing Satellite Phased Array L-band Synthetic Aperture Radar images acquired from February 2007 to March 2011. ERA5 reanalysis data were used to generate geospatial data for air temperature, surface temperature, and soil temperature averaged for the period 2000~2010. Geospatial data for roads and railways provided by Statistics Canada and land cover maps distributed by the North American Commission for Environmental Cooperation were also used in the AHP analysis. The suitability of sites analyzed using land cover, surface displacement, and road accessibility as the three most important geospatial factors was validated using the locations of oil-sand plants built since 2010. The sensitivity of surface displacement to the determination of location suitability was found to be very high. We confirm that surface displacement should be considered in the selection of optimal locations for the construction of new resource-development plants in permafrost regions.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.25 no.2
• /
• pp.80-98
• /
• 2023

This study explores the effectiveness of various data preprocessing algorithms for improving subseasonal to seasonal (S2S) climate predictions from six climate forecast models and their Multi-Model Ensemble (MME) using a deep learning-based postprocessing model. A pipeline of data transformation algorithms was constructed to convert raw S2S prediction data into the training data processed with several statistical distribution. A dimensionality reduction algorithm for selecting features through rankings of correlation coefficients between the observed and the input data. The training model in the study was designed with TimeDistributed wrapper applied to all convolutional layers of U-Net: The TimeDistributed wrapper allows a U-Net convolutional layer to be directly applied to 5-dimensional time series data while maintaining the time axis of data, but every input should be at least 3D in U-Net. We found that Robust and Standard transformation algorithms are most suitable for improving S2S predictions. The dimensionality reduction based on feature selections did not significantly improve predictions of daily precipitation for six climate models and even worsened predictions of daily maximum and minimum temperatures. While deep learning-based postprocessing was also improved MME S2S precipitation predictions, it did not have a significant effect on temperature predictions, particularly for the lead time of weeks 1 and 2. Further research is needed to develop an optimal deep learning model for improving S2S temperature predictions by testing various models and parameters.

• Journal of Korea Water Resources Association
• /
• v.56 no.1
• /
• pp.53-62
• /
• 2023

Recently, due to the influence of climate change, the occurrence of damage to heavy rain is increasing around the world, and the frequency of heavy rain with a large amount of rain in a short period of time is also increasing. Heavy rains generate a large amount of outflow in a short time, causing flooding in the downstream part of the mountainous area before joining the small and medium-sized rivers. In order to reduce damage to downstream areas caused by flooding, it is very important to calculate the outflow of mountainous areas due to torrential rains. However, the sewage network flooding analysis, which is currently conducting the most analysis in Korea, uses the time and area method using the existing data rather than calculating the rainfall outflow in the mountainous area, which is difficult to determine that the soil characteristics of the region are accurately applied. Therefore, if the rainfall is analyzed for mountainous areas that can cause flooding in the downstream area in a short period of time due to large outflows, the accuracy of the analysis of flooding characteristics that can occur in the downstream area can be improved and used as data for evacuating residents and calculating the extent of damage. In order to calculate the rainfall outflow in the mountainous area, the rainfall outflow in the mountainous area was calculated using MIKE SHE among the MIKE series, and the flooding analysis in the downstream area was conducted through MIKE 21 FM (Flood model). Through this study, it was possible to confirm the amount of outflow and the time to reach downstream in the event of rainfall in the mountainous area, and the results of this analysis can be used to protect human and material resources through pre-evacuation in the downstream area in the future.

• The Journal of the Convergence on Culture Technology
• /
• v.8 no.3
• /
• pp.581-587
• /
• 2022

The water god, Venerable Bhadra, Indian Tammola (Tamla as the 'mol' and 'ju' characters were eliminated) came to Tamla with 900 Arahants(The highest Buddhist monks) around 563-483 BC. It is the propagation of Buddhism through the world's most sacred water (Heiligkeit). The traces of the three surnames of Goyangbu are the first samsunghyeol and the dwelling of the den of Jonjaam(cave of venerable Bhadra) in Yeongsil, giving a glimpse into the era of living in caves. The second is a link that is in line with 3, the basic number in the decomposition of 900 (=3^*3^*100) disciples of Bhadra, considering that 3 and 3 of the three surnames in Goyangbu are three times 9. At this time, 3 is the person of heaven and earth, religiously, marriage, hope, or complete number, and Jeju culture is resting everywhere. For example, 3 of the samsunghyeol, 3 of the 1, 2, 3 Dodong, 3 of the 3 Dado, 3 of the 3 Mudo, 3 of the 3 disasters, 3 of the Goyangbu 3-surnames, 3 of the house Olle Jeongnang and, among 900 (=3^*3^*100) disciples of Venerable Bhadra, the common factor is 3. It is the 'island of 3'. These papers consist of 1 and 2 parts. In Part 1, the name of Tamla came from Tammola, India, and 900 Indian Buddhist Arahants estimated that the three surnames in Goyangbu were the ancestors. Part 2 highlights how the basic principle of jeonganag derived from Indian customs has evolved and is being used in modern mobile communication and DNA gene life science.

• Journal of Korea Foundry Society
• /
• v.43 no.5
• /
• pp.230-240
• /
• 2023

The pitting corrosion behavior of 329LD cast lean duplex stainless steel and CF3M cast austenitic stainless steel was investigated in chloride environments. The pitting corrosion resistance of the 329LD alloy was superior to that of the CF3M alloy because the pitting potential, passive region, and critical pitting temperature of the low Ni-low Mo 329LD alloy were higher than those of the high Ni-medium Mo commercial CF3M alloy. There are two main reasons for the enhancement of the pitting corrosion resistance of high Cr-low Momedium N 329LD alloy compared to the low Cr-medium Mo CF3M alloy: First, the pitting resistance equivalent number (PREN_δ+γ) value of the 329LD alloy is higher than that of the CF3M alloy. Second, the passive region of the 329LD alloy is larger than that of the CF3M alloy. It indicates that the synergistic effect of the three elements by adding high Cr and low Mo-medium N to the 329LD alloy enhances the passivity of the passive film, thereby increasing the pitting corrosion resistance. It was verified that based on the PREN_γ of austenite (γ) and PREN_δ of ferrite (δ) values calculated using an N-factor of 16, the pitting corrosion of the 329LD alloy was selectively initiated at the γ-phases because PREN_γ value of austenite (γ) was smaller than that of ferrite (δ), and finally propagated from the γ-phase to the δ-phase.