• The Journal of Industrial Distribution & Business
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• v.9 no.6
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• pp.77-85
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• 2018

Purpose - The purpose of this study is to subdivide trade transaction-centered structure in a logistics/distribution industry system to apply blockchain, to establish and resolve with which types of technology, and to provide policy direction of government institution and technology to apply blockchain in this kind of industry. Research design, data, and methodology - This study was conducted with previous researches centered on cases applied in various industry sectors on the basis of blockchain technology. Results - General fields of blockchain application include digital contents distribution, IoT platform, e-Commerce, real-estate transaction, decentralized app. development(storage), certification service, smart contract, P2P network infrastructure, publication/storage of public documents, smart voting, money exchange, payment/settlement, banking security platform, actual asset storage, stock transaction and crowd funding. Blockchain is being applied in various fields home and abroad and its application cases can be explained in the banking industry, public sector, e-Commerce, medical industry, distribution and supply chain management, copyright protection. As examined in the blockchain application cases, it is expected to establish blockchain that can secure safety through distributed ledger in trade transaction because blockchain is established and applied in various sectors of industries home and abroad. Parties concerned of trade transaction can secure visibility even in interrupted specific section when they provide it as a base for distributed ledger application in trade and establish trade transaction model by applying blockchain. In case of interrupted specific section by using distributed ledger, blockchain model of trade transaction needs to be formed to make it possible for parties concerned involved in trade transaction to secure visibility and real-time tracking. Additionally, management should be possible from the time of contract until payment, freight transfer to buyers through land, air and maritime transportation. Conclusions - In order to boost blockchain-based logistics/distribution industry, the government, institutionally, needs to back up adding legal plan of shipping, logistics and distribution, reviewing standardization of electronic switching system and coming up with blockchain-based industrial road maps. In addition, the government, technologically, has to support R&D for integration with other high technology, standardization of distribution industry's blockchain technology and manpower training to expand technology development.

• Tunnel and Underground Space
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• v.25 no.2
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• pp.186-198
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• 2015

This paper aims for the ultimate goal to optimize the work place environment through assuring the optimal required ventilation rate based on the analysis of the airflow. The working environment is deteriorated due to a rise in temperature of a coal mine caused by increase of its depth and carriage tunnels. To improve the environment, the ventilation evaluation on J coal mine is carried out and the effect of a length of the tunnel on the temperature to enhance the ventilation efficiency in the subsurface is numerically analyzed. The analysis shows that J coal mine needs $17,831m^3/min$ for in-flow ventilation rate but the total input air flowrate is $16,474m^3/min$, $1,357m^3/min$ of in-flow ventilation rate shortage. The temperatures were predicted on the two developed models of J mine, and VnetPC that is a numerical program for the flowrate prediction. The result of the simulation notices the temperature in the case of developing all 4 areas of -425ML as a first model is predicted 29.30 at the main gangway 9X of C section and in the case of developing 3 areas of -425ML excepting A area as a second model, it is predicted 27.45 Celsius degrees.

• Korean Journal of Agricultural and Forest Meteorology
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• v.6 no.3
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• pp.170-176
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• 2004

This study was carried out to establish a spatial decision support system for evaluating climatic aspects of a given geographic location in complex terrains with respect to the quality apple production. Monthly climate data from S6 synoptic stations across South Korea were collected for 1971-2000. A digital elevation model (DEM) with a 10-m cell spacing was used to spatially interpolate daily maximum and minimum temperatures based on relevant topoclimatological models applied to Jangsoo county in Korea. For daily minimum temperature, a spatial interpolation scheme accommodating the potential influences of cold air accumulation and the temperature inversion was used. For daily maximum temperature estimation, a spatial interpolation model loaded with the overheating index was used. Freezing risk in January was estimated under the recurrence intervals of 30 years. Frost risk at bud-burst and blossom was also estimated. Fruit quality was evaluated for soluble solids, anthocyanin content, Hunter L and A values, and LID ratio, which were expressed as empirical functions of temperature based on long-term field observations. AU themes were prepared as ArcGlS Grids with a 10-m cell spacing. Analysis showed that 11 percent of the whole land area of Jangsoo county might be suitable for quality 'Fuji' apple production. A computer program (MAPLE) was written to help utilize the results in decision-making for site-selection of new orchards in this region.

• Journal of Environmental Science International
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• v.28 no.3
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• pp.341-356
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• 2019

In this study, the impacts of local meteorology caused by tidal changes in the West Sea on ozone distributions in the Seoul Metropolitan Area (SMA) were analyzed using a meteorological model (WRF) and an air quality (CMAQ) model. This study was carried out during the day (1200-1800 LST) between August 3 and 9, 2016. The total area of tidal flats along with the tidal changes was calculated to be approximately $912km^2$, based on data provided by the Environmental Geographic Information Service (EGIS) and the Ministry of Oceans and Fisheries (MOF). Modeling was carried out based on three experiments, and the land cover of the tidal flats for each experiment was designed using the coastal wetlands, water bodies (i.e., high tide), and the barren or sparsely vegetated areas (i.e., low tide). The land cover parameters of the coastal wetlands used in this study were improved in the herbaceous wetland of the WRF using updated albedo, roughness length, and soil heat capacity. The results showed that the land cover variation during high tide caused a decrease in temperature (maximum $4.5^{\circ}C$) and planetary boundary layer (PBL) height (maximum 1200 m), and an increase in humidity (maximum 25%) and wind speed (maximum $1.5ms^{-1}$). These meteorological changes increased the ozone concentration (about 5.0 ppb) in the coastal areas including the tidal flats. The increase in the ozone concentration during high tide may be caused by a weak diffusion to the upper layer due to a decrease in the PBL height. The changes in the meteorological variables and ozone concentration during low tide were lesser than those occurring during high tide. This study suggests that the meteorological variations caused by tidal changes have a meaningful effect on the ozone concentration in the SMA.

• Journal of Cadastre & Land InformatiX
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• v.52 no.1
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• pp.105-118
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• 2022

The demand for information related to 3D spatial objects model in metaverse, smart cities, digital twins, autonomous vehicles, urban air mobility will be increased. 3D model construction for spatial objects is possible with various equipments such as satellite-, aerial-, ground platforms and technologies such as modeling, artificial intelligence, image matching. However, it is not easy to quickly detect and convert spatial objects that need updating. In this study, based on spatial information (features) and attributes, using matching elements such as address code, number of floors, building name, and area, the converged building DB and the detected building DB are constructed. Both to support above and to verify the suitability of object selection that needs to be updated, one system prototype was developed. When constructing the converged building DB, the convergence of spatial information and attributes was impossible or failed in some buildings, and the matching rate was low at about 80%. It is believed that this is due to omitting of attributes about many building objects, especially in the pilot test area. This system prototype will support the establishment of an efficient drone shooting plan for the rapid update of 3D spatial objects, thereby preventing duplication and unnecessary construction of spatial objects, thereby greatly contributing to object improvement and cost reduction.

• Journal of the Ergonomics Society of Korea
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• v.36 no.3
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• pp.183-196
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• 2017

Objective: The purpose of this research was to assess the agreement between job physical risk factor analysis by ergonomists using ergonomic methods and physical examinations made by occupational physicians on the presence of musculoskeletal disorders of the upper extremities. Background: Ergonomics is the systematic application of principles concerned with the design of devices and working conditions for enhancing human capabilities and optimizing working and living conditions. Proper ergonomic design is necessary to prevent injuries and physical and emotional stress. The major types of ergonomic injuries and incidents are cumulative trauma disorders (CTDs), acute strains, sprains, and system failures. Minimization of use of excessive force and awkward postures can help to prevent such injuries Method: Initial data were collected as part of a larger study by the University of Utah Ergonomics and Safety program field data collection teams and medical data collection teams from the Rocky Mountain Center for Occupational and Environmental Health (RMCOEH). Subjects included 173 male and female workers, 83 at Beehive Clothing (a clothing plant), 74 at Autoliv (a plant making air bags for vehicles), and 16 at Deseret Meat (a meat-processing plant). Posture and effort levels were analyzed using a software program developed at the University of Utah (Utah Ergonomic Analysis Tool). The Ergonomic Epicondylitis Model (EEM) was developed to assess the risk of epicondylitis from observable job physical factors. The model considers five job risk factors: (1) intensity of exertion, (2) forearm rotation, (3) wrist posture, (4) elbow compression, and (5) speed of work. Qualitative ratings of these physical factors were determined during video analysis. Personal variables were also investigated to study their relationship with epicondylitis. Logistic regression models were used to determine the association between risk factors and symptoms of epicondyle pain. Results: Results of this study indicate that gender, smoking status, and BMI do have an effect on the risk of epicondylitis but there is not a statistically significant relationship between EEM and epicondylitis. Conclusion: This research studied the relationship between an Ergonomic Epicondylitis Model (EEM) and the occurrence of epicondylitis. The model was not predictive for epicondylitis. However, it is clear that epicondylitis was associated with some individual risk factors such as smoking status, gender, and BMI. Based on the results, future research may discover risk factors that seem to increase the risk of epicondylitis. Application: Although this research used a combination of questionnaire, ergonomic job analysis, and medical job analysis to specifically verify risk factors related to epicondylitis, there are limitations. This research did not have a very large sample size because only 173 subjects were available for this study. Also, it was conducted in only 3 facilities, a plant making air bags for vehicles, a meat-processing plant, and a clothing plant in Utah. If working conditions in other kinds of facilities are considered, results may improve. Therefore, future research should perform analysis with additional subjects in different kinds of facilities. Repetition and duration of a task were not considered as risk factors in this research. These two factors could be associated with epicondylitis so it could be important to include these factors in future research. Psychosocial data and workplace conditions (e.g., low temperature) were also noted during data collection, and could be used to further study the prevalence of epicondylitis. Univariate analysis methods could be used for each variable of EEM. This research was performed using multivariate analysis. Therefore, it was difficult to recognize the different effect of each variable. Basically, the difference between univariate and multivariate analysis is that univariate analysis deals with one predictor variable at a time, whereas multivariate analysis deals with multiple predictor variables combined in a predetermined manner. The univariate analysis could show how each variable is associated with epicondyle pain. This may allow more appropriate weighting factors to be determined and therefore improve the performance of the EEM.

• Journal of Bio-Environment Control
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• v.18 no.1
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• pp.29-39
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• 2009

The influence of windbreak to minimize the ventilation velocity near the plant canopy of a greenhouse strawberry was thoroughly investigated using computational fluid dynamics (CFD) technology. Windbreaks were constructed surrounding the plant canopy to control ventilation and maintain the concentration of the supplied $CO_2$ from the soil surface close to the strawberry plants. The influence of no windbreak, 0.15 m and 0.30 m height windbreaks with varied air velocity of 0.5, 1.0 and 1.5 m/s were simulated in the study. The concentrations of supplied $CO_2$ within the plant canopy of were measured. To simplify the model, plants were not included in the final model. Considering 1.0m/s wind velocity which is the normal wind velocity of greenhouses, the concentrations of $CO_2$ were approximately 420, 580 and 653 ppm ($1{\times}10^{-9}kg/m^3$) for no windbreak, 0.15 and 0.30 m windbreak height, respectively. Considering that the maximum concentration of $CO_2$ for the strawberry plants was around 600-800 ppm, the 0.30 m windbreak height is highly recommended. This study revealed that the windbreak was very effective in preserving $CO_2$ gas within the plant canopy. More so, the study also proved that the CFD technique can be used to determine the concentration of $CO_2$ within the plant canopy for the plants consumption at any designed condition. For an in-depth application of this study, the plants as well as the different conditions for $CO_2$ utilization, etc. should be considered.

• Korean Journal of Remote Sensing
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• v.36 no.6_3
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• pp.1653-1667
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• 2020

In this study, we coupled a computation fluid dynamics (CFD) model to the local data assimilation and prediction system (LDAPS), a current operational numerical weather prediction model of the Korea Meteorological Administration. We investigated the characteristics of fine particulate matter (PM2.5) distributions in a building-congested district. To analyze the effects of road emission on the PM2.5 concentrations, we calculated road emissions based on the monthly, daily, and hourly emission factors and the total amount of PM2.5 emissions established from the Clean Air Policy Support System (CAPSS) of the Ministry of Environment. We validated the simulated PM2.5 concentrations against those measured at the PKNU-AQ Sensor stations. In the cases of no road emission, the LDAPS-CFD model underestimated the PM2.5 concentrations measured at the PKNU-AQ Sensor stations. The LDAPS-CFD model improved the PM2.5 concentration predictions by considering road emission. At 07 and 19 LST on 22 June 2020, the southerly wind was dominant at the target area. The PM2.5 distribution at 07 LST were similar to that at 19 LST. The simulated PM2.5 concentrations were significantly affected by the road emissions at the roadside but not significantly at the building roof. In the road-emission case, the PM2.5 concentration was high at the north (wind speeds were weak) and west roads (a long street canyon). The PM2.5 concentration was low in the east road where the building density was relatively low.

• Korean Journal of Agricultural and Forest Meteorology
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• v.9 no.3
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• pp.209-215
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• 2007

To improve the accuracy of frost warning system for pear orchard in a complex terrain in Naju area, the daily minimum temperature forecasted by Korea Meteorological Administration (KMA) was interpolated using a regional climate model based on topoclimatic estimation and optimum scale interpolation from 2004 to 2005. Based on the validation experiments done for three pear orchards in the spring of 2004, the results showed a good agreement between the observed and predicted values, resulting in improved predictability compared to the forecast from Korea Meteorological Administration. The differences between the observed and the predicted temperatures were $-2.1{\sim}2.7^{\circ}C$ (on average $-0.4^{\circ}C$) in the valley, $-1.6{\sim}2.7^{\circ}C$ (on average $-0.4^{\circ}C$) in the riverside and $-1.1{\sim}3.5^{\circ}C$ (on average $0.6^{\circ}C$) in the hills. Notably, the errors have been reduced significantly for the valley and riverside areas that are more affected by the cold air drainage and more susceptible to frost damage than hills.

• Korean Journal Plant Pathology
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• v.3 no.3
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• pp.210-216
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• 1987

A computer program written to predict blast occurrence based on micro climatic events was developed and tested as an on-site microcomputer in field plots in 1984 and 1985. A microcomputer unit operating on alkaline batteries; continuously monitored air temperature, leaf wetness, and relative humidity; interpreted the microclimate information in relation to rice blast development and displayed daily values (0-8) of blast units of severity (BUS). Cumulative daily BUS values (CBUS) were highly correlated with blast development on the two susceptible cultivars, M-201 and Brazos grown in field plots. When CBUS values were used to predict the logit of disease proportions, the average coefficients of determination $(R^2)$ between these two factors were 71 to $91\%$, depending on cultivar and year. This was a significant improvement when compared to 61 to $79\%$ when days were used as a predictor of logit disease severity. The ability of CBUS to predict logit disease severity was slightly less with Brazos than M-201. This is significant inasmuch as Brazos showed field resistance at mid-sea­son. The results in this study indicate that the model has the potential for future use and that the model could be improved by incorporating other variables associated with host plants and pathogen races in addition to the key environmental variables.