The N-value from the Standard Penetration Test (SPT), which is one of the representative in-situ test, is an important index that provides basic geological information and the depth of the bearing layer for the design of geotechnical structures. In the aspect of time and cost-effectiveness, there is a need to carry out a representative sampling test. However, the various variability and uncertainty are existing in the soil layer, so it is difficult to grasp the characteristics of the entire field from the limited test results. Thus the spatial interpolation techniques such as Kriging and IDW (inverse distance weighted) have been used for predicting unknown point from existing data. Recently, in order to increase the accuracy of interpolation results, studies that combine the geotechnics and deep learning method have been conducted. In this study, based on the SPT results of about 22,000 holes of ground survey, a comparative study was conducted to predict the depth of the bearing layer using deep learning methods and IDW. The average error among the prediction results of the bearing layer of each analysis model was 3.01 m for IDW, 3.22 m and 2.46 m for fully connected network and PointNet, respectively. The standard deviation was 3.99 for IDW, 3.95 and 3.54 for fully connected network and PointNet. As a result, the point net deep learing algorithm showed improved results compared to IDW and other deep learning method.
The Journal of The Korea Institute of Intelligent Transport Systems
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v.21
no.1
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pp.209-220
/
2022
With the worldwide spread of African swine fever, interest in livestock epidemics has increased. Livestock transport vehicles are the main cause of the spread of livestock epidemics, but there are no empirical quarantine procedures and standards related to the mobility of livestock transport vehicles in South Korea. This study extracted the trajectory of livestock-related vehicles using the facility-visit history data from the Korea Animal Health Integrated System and the DTG (Digital Tachograph) data from the Korea Transportation Safety Authority. The results are presented as exposure indices aggregating the link-time occupancy of each vehicle. As a result, 274,519 livestock-related vehicle trajectories were extracted, and the exposure values by link and zone were derived quantitatively. This study highlights the need for prior monitoring of livestock transport vehicles and the establishment of post-disaster prevention policies.
Kim, Yong Hwan;Yoon, Hyeong Seok;Lee, Jae Hee;Kang, Leen Seok
KSCE Journal of Civil and Environmental Engineering Research
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v.43
no.1
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pp.79-89
/
2023
The inventory of many materials requires a large storage space, and the longer the storage period, the higher the potential maintenance cost. When materials are stored on a construction site, there are also concerns about safety due to the reduction of room for movement and working. On the other hand, construction sites that do not store materials have insufficient inventory, making it difficult to respond to demands such as sudden design changes. Ordering materials is then subject to delays and extra costs. Although securing an appropriate amount of inventory is important, in many cases, material management on a construction site depends on the experience of the site manager, so a reasonable material inventory management plan that reflects the construction conditions of a site is required. This study proposes an economical material management method by reflecting variables such as the status of the preceding and following activities, site size, material delivery cost, timing of an order, and quantity of orders. To this end, we set the appropriate inventory amount while adjusting related activities in the activity network, using float time for each activity, the size of the yard, and the order quantity as the main variables, and applied a genetic algorithm to this process to suggest the optimal order timing and order quantity. The material delivery cost derived from the results is set as a fitness index and the efficiency of inventory management was verified through a case application.
KSCE Journal of Civil and Environmental Engineering Research
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v.28
no.1C
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pp.19-29
/
2008
As a part of study to develop LRFD (Load and Resistance Factor Design) codes for foundation structures in Korea, reliability analyses for driven steel pipe piles are performed and the target reliability indices are selected carefully. The 58 data sets of static load tests and soil property tests conducted in the whole domestic area were collected and analyzed to determine the representative bearing capacities of the piles. The static bearing capacity formula and the Meyerhof method using N values are applied to calculate the expected design bearing capacity of the piles. The resistance bias factors were evaluated for the two static design methods by comparing the representative bearing capacities with the design values. Reliability analysis was performed by two types of advanced methods: First Order Reliability Method (FORM), and Monte Carlo Simulation (MCS) method using resistance bias factor statistics. The static bearing capacity formula exhibited relatively small variation, whereas the Meyerhof method showed relatively high inherent conservatism in the resistance bias factors. Reliability indices for safety factors in the range of 3 to 5 were evaluated respectively as 1.50~2.89 and 1.61~2.72 for both of the static bearing capacity formula and the Meyerhof method. The target reliability indices are selected as 2.0 and 2.33 for group pile case and 2.5 for single pile case, based on the reliability level of the current design practice and considering redundancy of pile group, acceptable risk level, construction quality control, and significance of individual structure.
Journal of Korean Society of Occupational and Environmental Hygiene
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v.33
no.3
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pp.375-383
/
2023
Objectives: Coal-fired power plants feature diverse working conditions, including multi-layered employment structures and irregular work cycles due to outsourcing and non-standardized tasks. The current uniform occupational environment measurement systems have limitations in accurately assessing and evaluating these varied conditions. This study aims to propose alternative measurement and assessment strategies to supplement existing methods. Methods: Major domestic coal-fired power plants were selected as the study targets. To prepare for the study and establish strategies, work processes were identified and existing occupational environment measurement results were compared and analyzed. The study proceeded by employing three strategies: specific exposure groups (SEGs) measurement, continuous monitoring, and supplementary measurements, which were then compared and discussed. Results: Previous exposure index evaluations (5,268 cases) indicated that crystalline silica, a type of respirable particulate matter, had detection limits below the threshold (non-detectable) in 82.6% (4,349 cases) of instances. Exposures below 10% of the exposure limit were observed at a very low concentration of 96.1%. Similar exposure group measurements yielded results where detection limits were below the threshold in 38.2% of cases, and exposures below 10% of the limit were observed in 70.6%. Continuous monitoring indicated detection limits below the threshold in 12.6% of cases, and exposures below 10% of the limit were observed in 75.6%. Instances requiring active workplace management accounted for more than 30% of cases, with SEGs at 11.8% (four cases), showing a higher proportion compared to 3.0% (four cases) in continuous monitoring. For coal dust, exposures below 10% of the limit were highest in legal measurements at 90.2% (113 cases), followed by 74.0% (91 cases) in continuous monitoring, and 47.0% (16 cases) in SEGs. Instances exceeding 30% were most prevalent in SEGs at 14.7% (five cases), followed by legal measurements at 5.0% (eight cases), and continuous monitoring at 2.4% (three cases). When examining exposure levels through arithmetic means, crystalline silica was found to be 104.7% higher in SEGs at 0.0088 mg/m3 compared to 0.0043 mg/m3 in continuous monitoring. Coal dust measurements were highest in SEGs at 0.1247 mg/m3, followed by 0.1224 mg/m3 in legal measurements, and 0.0935 mg/m3 in continuous monitoring. Conclusions: Strategies involving SEGs measurement and continuous monitoring can enhance measurement reliability in environments with irregular work processes and frequent fluctuations in working conditions, as observed in coal-fired power plants. These strategies reduce the likelihood of omitting or underestimating processes and enhance measurement accuracy. In particular, a significant reduction in detection limits below the threshold for crystalline silica was observed. Supplementary measurements can identify worker exposure characteristics, uncover potential risks in blind spots of management, and provide a complementary method for legal measurements.
Agricultural drought is triggered by a depletion of moisture content in the soil, which hinders photosynthesis and thus increases carbon dioxide (CO2) concentrations in the atmosphere. The aim of this study is to analyze the relationship between soil moisture (SM) and vegetation activity toward quantifying CO2 concentration in the atmosphere. To this end, the MODerate resolution imaging spectroradiometer (MODIS), an optical multispectral sensor, was used to evaluate two regions in South Korea for validation. Vegetation activity was analyzed through MOD13A1 vegetation indices products, and MODIS gross primary productivity (GPP) product was used to calculate the CO2 flux based on its relationship with respiration. In the case of SM, it was calculated through the method of applying apparent thermal inertia (ATI) in combination with land surface temperature and albedo. To validate the SM and CO2 flux, flux tower data was used which are the observed measurement values for the extreme drought period of 2014 and 2015 in South Korea. These two variables were analyzed for temporal variation on flux tower data as daily time scale, and the relationship with vegetation index (VI) was synthesized and analyzed on a monthly scale. The highest correlation between SM and VI (correlation coefficient (r) = 0.82) was observed at a time lag of one month, and that between VI and CO2 (r = 0.81) at half month. This regional study suggests a potential capability of MODIS-based SM, VI, and CO2 flux, which can be applied to an assessment of the global view of the agricultural drought by using available satellite remote sensing products.
Seungju Lee;Wonhee Lee;Ji Hong Min;Deuk Jae Cho;Hyunwoo Park
Journal of Navigation and Port Research
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v.47
no.6
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pp.367-375
/
2023
This study developed a new distance metric for vessel trajectories, applicable to marine traffic control services in the Korean coastal waters. The proposed metric is designed through the weighted summation of the traditional Hausdorff distance, which measures the similarity between spatiotemporal data and incorporates the differences in the average Speed Over Ground (SOG) and the variance in Course Over Ground (COG) between two trajectories. To validate the effectiveness of this new metric, a comparative analysis was conducted using the actual Automatic Identification System (AIS) trajectory data, in conjunction with an agglomerative clustering algorithm. Data visualizations were used to confirm that the results of trajectory clustering, with the new metric, reflect geographical distances and the distribution of vessel behavioral characteristics more accurately, than conventional metrics such as the Hausdorff distance and Dynamic Time Warping distance. Quantitatively, based on the Davies-Bouldin index, the clustering results were found to be superior or comparable and demonstrated exceptional efficiency in computational distance calculation.
Hyeonjin Kim;Soohyun Jeong;Sung Wook Kim;Hyung-Jin Kim;Dae Yong Kim;Tae Han Yook;Gabsik Yang
Journal of Pharmacopuncture
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v.27
no.2
/
pp.59-69
/
2024
This study investigates the therapeutic potential of Indigo Naturalis (IN) in treating a Inflammatory Bowel Disease (IBD). The objective is to comprehensively examine the effects and pharmacological mechanisms of IN on IBD, assessing its potential as an novel treatment for IBD. Analysis of 11 selected papers is conducted to understand the effects of IN, focusing on compounds like indirubin, isatin, indigo, and tryptanthrin. This study evaluates their impact on Disease Activity Index (DAI) score, colon length, mucosal damage, and macrophage infiltration in Dextran Sulfate Sodium (DSS)-induced colitis mice. Additionally, It investigate into the anti-inflammatory mechanisms, including Aryl hydrocarbon Receptor (AhR) pathway activation, Nuclear Factor kappa B (NF-κB)/nod-like receptor family pyrin domain containing 3 (NLRP3)/Interleukin 1 beta (IL-1β) inhibition, and modulation of Toll-like receptor 4 (TLR4)/myeloid differentiation primary response 88 (MYD88)/NF-κB and Mitogen Activated Protein Kinase (MAPK) pathways. Immunomodulatory effects on T helper 17 (Th17)/regulatory T cell (Treg cell) balance and Glycogen synthase kinase-3 beta (GSK3-β) expression are also explored. Furthermore, the study addresses the role of IN in restoring intestinal microbiota diversity, reducing pathogenic bacteria, and increasing beneficial bacteria. The findings reveal that IN, particularly indirubin and indigo, demonstrates significant improvements in DAI score, colon length, mucosal damage, and macrophage infiltration in DSS-induced colitis mice. The anti-inflammatory effects are attributed to the activation of the AhR pathway, inhibition of inflammatory pathways, and modulation of immune responses. These results exhibit the potential of IN in IBD treatment. Notably, the restoration of intestinal microbiota diversity and balance further supports its efficacy. IN emerges as a promising and effective treatment for IBD, demonstrating anti-inflammatory effects and positive outcomes in preclinical studies. However, potential side effects necessitate further investigation for safe therapeutic development. The study underscores the need for future research to explore a broader range of active ingredients in IN to enhance therapeutic efficacy and safety.
Journal of the Computational Structural Engineering Institute of Korea
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v.37
no.3
/
pp.163-171
/
2024
Structural health monitoring for ships and offshore structures is important in various aspects. Ships and offshore structures are continuously exposed to various environmental conditions, such as waves, wind, and currents. In the event of an accident, immense economic losses, environmental pollution, and safety problems can occur, so it is necessary to detect structural damage or defects early. In this study, structural response data of multi-linked floating offshore structures under various wave load conditions was calculated by performing fluid-structure coupled analysis. Furthermore, the order reduction method with distortion base mode was applied to the structures for predicting the structural response by using the results of numerical analysis. The distortion base mode order reduction method can predict the structural response of a desired area with high accuracy, but prediction performance is affected by sensor arrangement. Optimization based on a genetic algorithm was performed to search for optimal sensor arrangement and improve the prediction performance of the distortion base mode-based reduced-order model. Consequently, a sensor arrangement that predicted the structural response with an error of about 84.0% less than the initial sensor arrangement was derived based on the root mean squared error, which is a prediction performance evaluation index. The computational cost was reduced by about 8 times compared to evaluating the prediction performance of reduced-order models for a total of 43,758 sensor arrangement combinations. and the expected performance was overturned to approximately 84.0% based on sensor placement, including the largest square root error.
The development of transportation methods has improved human transportation convenience and made it possible to expand the travel radius of people with disabilities who have difficulty moving. However, in the case of WAV (wheelchair Accessible Vehicle), the safety that may occur in a vehicle accident is still lower than that of regular passenger seats. In particular, in the case of a rear-end collision that may occur in a defenseless situation, it can cause fatal neck injuries to disabled passengers. Therefore, a more detailed design plan must be reflected in the headrest to be applied to WAV. In this study, a multi-cell headrest was proposed to implement local compression characteristic distribution of the headrest during rear-end collision of WAV. Afterwards, a correlation analysis was performed between the passenger's NIC (Neck Injury Criterion) and impact energy absorption using the data set construction through analysis and the clustering results using k-means clustering. As a result of clustering, it was confirmed that data clusters with similar characteristics were formed, and a correlation analysis between NIC and impact energy absorption through the characteristics of each cluster was performed. As a result of the analysis, it was confirmed that the softer the cell compression characteristics in Mid3 and Mid6, the more impact energy absorption increases, and the harder the cell compression characteristics in Front2, Mid3, and Mid6, the more effective it is in reducing NIC.
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