• The Journal of Society for e-Business Studies
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• v.26 no.4
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• pp.81-93
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• 2021

Through processors, wholesale markets, intermediate sellers, and retailers, agricultural products have been distributed in a multi-level customary manner for a long time as they are easy to deteriorate and no not have a standardized system of size and quality. However, with the advancement of Internet networks and logistic services during the 2000s that facilitated the development of offline markets, and the rise of the non-contact purchase preference in direct response to COVID-19, previous offline consumers flowed into the online market to purchase agricultural goods. In other words, the volume of online agricultural transactions exploded since the pandemic. Against this social backdrop, this study focused on the difference in distribution costs as a result of converting from conventional offline distribution channels to online channels, and analyzed the reduced distribution costs through a case study of garlic sales on the online platform "H" shopping mall. The analysis found that considerable economic effects occurred, some of the effects being an approximate 39% decrease in distribution cost when comparing direct online transactions of the online shopping mall with other more traditional means, a reduced distribution cost rate of approximately 28%p, and increased profit for farmers.

• Journal of the Society of Disaster Information
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• v.18 no.1
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• pp.146-153
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• 2022

Purpose: In the case of domestic port facilities, port structures that have been in use for a long time have many problems in terms of safety performance and functionality due to the enlargement of ships, increased frequency of use, and the effects of natural disasters due to climate change. A big data analysis method was studied to develop an approximate model that can predict the aging pattern of a port facility based on the maintenance history data of the port facility. Method: In this study, member-level maintenance history data for caisson-type quay walls were collected, defined as big data, and based on the data, a predictive approximation model was derived to estimate the aging pattern and deterioration of the facility at the project level. A state-based aging pattern prediction model generated through Gaussian process (GP) and linear interpolation (SLPT) techniques was proposed, and models suitable for big data utilization were compared and proposed through validation. Result: As a result of examining the suitability of the proposed method, the SLPT method has RMSE of 0.9215 and 0.0648, and the predictive model applied with the SLPT method is considered suitable. Conclusion: Through this study, it is expected that the study of predicting performance degradation of big data-based facilities will become an important system in decision-making regarding maintenance.

• Journal of Navigation and Port Research
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• v.46 no.6
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• pp.471-482
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• 2022

This study aims to investigate the characteristics of wave generation in a deep ocean engineering basin and to develop a meta-model of the transfer function of the wavemaker that reflects the geometric characteristics of the deep ocean engineering basin. To this end, the two-dimensional frequency domain boundary element method was applied to achieve an efficient analysis that reflects the geometric characteristics of the deep ocean engineering basin. The developed numerical method was validated through comparison with the analytical solution. Numerical analyses were conducted for the boundary value problem of the wavemaker according to various periods and the positions of the movable bottom. The numerical results were used to investigate the effect of the geometric characteristics of the deep ocean engineering basin on the transfer function of the wavemaker, and the effect of depth on wave generation was checked by changing the position of the movable bottom. To efficiently utilize the various results of the boundary element method, a meta-model, an approximate model of the transfer function of the wave maker, was developed using a thin plate spline interpolation model. The validity of the developed meta-model was confirmed through a comparison of the results of the model tests.

• The Korea Journal of Herbology
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• v.28 no.3
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• pp.17-24
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• 2013

Objectives : This study was to evaluate the single dose toxicity of Persicae Semen (PS) in ICR mice. Methods : Aqueous extracts of PS (Yield = 18.60%) were administered as an oral dose of 2,000, 1,000 and 500 mg/kg (body weight) according to the recommendation of Korea Food and Drug Administration (KFDA) guidelines (2009-116, 2009). Animals were monitored for the mortality and changes in body weight, clinical signs and gross observation during 14 days after dosing, upon necropsy; organ weight and histopathology of 12 principle organs were examined. Results : Amygdalin contents in PS aqueous extracts were detected as $32.50{\pm}5.96{\mu}g/ml$. We could not find any PS extracts treatment related mortalities, clinical signs, changes on the body and organ weights, gross and histopathological observations up to 2,000 mg/kg in both female and male mice, except for transient and slight loss of locomotion detected in female and male mice treated with 2,000 mg/kg. In addition, pharmacological immunomodulatory effects related findings were also demonstrated in 2,000mg/kg treated female and male mice as hypertrophy and hyperplasia of lymphoid cells in the submandibular lymph nodes. Conclusions : Based on the results of this experiment, the approximate lethal dose (ALD) of PS extracts after single oral treatment in female and male mice were considered above 2,000 mg/kg, respectively. It should be carefully used in clinics because the possibilities of respiratory or neurological disorders were observed when administered over 2,000 mg/kg of PS extract related to amygdalin.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.2
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• pp.244-253
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• 2022

Recently, installation projects of structures such as offshore wind farms have been increasing, and the installation of such marine obstacles could affect ships that pass nearby. Therefore, the purpose of this study was to quantitatively evaluate the risk posed to passing ships due to obstacles in their passage. Hence, parameters that affected the risk were selected, and scenarios were set based on the parameters. The scenarios were evaluated through the ES model, which is a risk assessment model, and we confirmed that the risk ratio increased as the size of the obstacle increased, the safe distance from the obstacle increased, the speed of ship decreased, and the traffic volume increased. Additionally, we found that when the traffic flow direction was designated, the risk ratio was lower than that of general traffic flow. In this study, we proposed a generalization model based on the results of the performed scenarios, applied it to the Dadaepo offshore wind farm, and demonstrated that the estimation of the approximate risk ratio was possible through the generalization model. Finally, we judged that the generalization model proposed in this study could be used as a preliminary reference for the installation of marine obstacles.

• Korean journal of applied entomology
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• v.61 no.4
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• pp.549-554
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• 2022

Life table-related studies in insect ecology have been an interesting topic for insect researchers. Two calculation methods are commonly applied to estimate the intrinsic rate of natural increase (r_m) in the life table statistics. The first method is to estimate an approximate r_m by dividing the natural logarithm of the net reproductive rate (R₀) by mean generation time (T) (namely mean generation time-based method). Another approach is to apply the Lotka-Euler equation derived from the population growth equation of Lotka-Volterra to estimate accurate r_m using the maximum likelihood method (Lotka-Euler equation-based method). In the latter case, there is a difference in the estimated r_m value when the initial age class of the target cohort was set to "0" or "1", which confused the application. In this short review, a brief history of the calculation process of the life table was reviewed. It was again confirmed in the Lotka-Euler equation-based method that the form of $\sum\limits_{x=1}^{w}e^{-rx}l_xm_x=1$ should be applied to estimate r_m when the first age class was set to zero, while the form of $\sum\limits_{x=0}^{w}e^{-r(x+1)}l_xm_x=1$ when set to one.

• Journal of Service Research and Studies
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• v.13 no.3
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• pp.105-126
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• 2023

The domestic used car market continues to grow along with the used car online platform service. The used car online platform service discloses vehicle specifications, accident history, inspection history, and detailed options to service consumers. Most of the preceding studies were predictions of used car prices using vehicle specifications and some options for vehicles. As a result of the study, it was confirmed that there was a nonlinear relationship between used car prices and some specification variables. Accordingly, the researchers tried to solve the nonlinear problem by executing a Machine Learning model. In common, the Regression based Machine Learning model had the advantage of knowing the actual influence and direction of variables, but there was a disadvantage of low Cost Function figures compared to the Decision Tree based Machine Learning model. This study attempted to predict used car prices of six domestic brands by utilizing both vehicle specifications and vehicle options. Through this, we tried to collect the advantages of the two types of Machine Learning models. To this end, we sequentially conducted a regression based Machine Learning model and a decision tree based Machine Learning model. As a result of the analysis, the practical influence and direction of each brand variable, and the best tree based Machine Learning model were selected. The implications of this study are as follows. It will help buyers and sellers who use used car online platform services to predict approximate used car prices. And it is hoped that it will help solve the problem caused by information inequality among users of the used car online platform service.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.30-31
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• 2009

Early detection of schedule delay in field construction activities is vital to project management. It provides the opportunity to initiate remedial actions and increases the chance of controlling such overruns or minimizing their impacts. This entails project managers to design, implement, and maintain a systematic approach for progress monitoring to promptly identify, process and communicate discrepancies between actual and as-planned performances as early as possible. Despite importance, systematic implementation of progress monitoring is challenging: (1) Current progress monitoring is time-consuming as it needs extensive as-planned and as-built data collection; (2) The excessive amount of work required to be performed may cause human-errors and reduce the quality of manually collected data and since only an approximate visual inspection is usually performed, makes the collected data subjective; (3) Existing methods of progress monitoring are also non-systematic and may also create a time-lag between the time progress is reported and the time progress is actually accomplished; (4) Progress reports are visually complex, and do not reflect spatial aspects of construction; and (5) Current reporting methods increase the time required to describe and explain progress in coordination meetings and in turn could delay the decision making process. In summary, with current methods, it may be not be easy to understand the progress situation clearly and quickly. To overcome such inefficiencies, this research focuses on exploring application of unsorted daily progress photograph logs - available on any construction site - as well as IFC-based 4D models for progress monitoring. Our approach is based on computing, from the images themselves, the photographer's locations and orientations, along with a sparse 3D geometric representation of the as-built scene using daily progress photographs and superimposition of the reconstructed scene over the as-planned 4D model. Within such an environment, progress photographs are registered in the virtual as-planned environment, allowing a large unstructured collection of daily construction images to be interactively explored. In addition, sparse reconstructed scenes superimposed over 4D models allow site images to be geo-registered with the as-planned components and consequently, a location-based image processing technique to be implemented and progress data to be extracted automatically. The result of progress comparison study between as-planned and as-built performances can subsequently be visualized in the D4AR - 4D Augmented Reality - environment using a traffic light metaphor. In such an environment, project participants would be able to: 1) use the 4D as-planned model as a baseline for progress monitoring, compare it to daily construction photographs and study workspace logistics; 2) interactively and remotely explore registered construction photographs in a 3D environment; 3) analyze registered images and quantify as-built progress; 4) measure discrepancies between as-planned and as-built performances; and 5) visually represent progress discrepancies through superimposition of 4D as-planned models over progress photographs, make control decisions and effectively communicate those with project participants. We present our preliminary results on two ongoing construction projects and discuss implementation, perceived benefits and future potential enhancement of this new technology in construction, in all fronts of automatic data collection, processing and communication.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.869-875
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• 2009

Safety is a big issue in the construction sites. For safe and secure management, tracking locations of construction resources such as labors, materials, machineries, vehicles and so on is important. The materials, machineries and vehicles could be controlled by computer, whereas the movement of labors does not have fixed pattern. So, the location and movement of labors need to be monitored continuously for safety. In general, Global Positioning System(GPS) is an opt solution to obtain the location information in outside environments. But it cannot be used for indoor locations as it requires a clear Line-Of-Sight(LOS) to satellites Therefore, indoor location monitoring system could be a convenient alternative for environments such as tunnel and indoor building construction sites. This paper presents a case study to investigate feasibility of Wi-Fi based indoor location monitoring system in construction site. The system is developed by using fingerprint map of gathering Received Signal Strength Indication(RSSI) from each Access Point(AP). The signal information is gathered by Radio Frequency Identification (RFID) tags, which are attached on a helmet of labors to track their locations, and is sent to server computer. Experiments were conducted in a shield tunnel construction site at Guangzhou, China. This study consists of three phases as follows: First, we have a tracking test in entrance area of tunnel construction site. This experiment was performed to find the effective geometry of APs installation. The geometry of APs installation was changed for finding effective locations, and the experiment was performed using one and more tags. Second, APs were separated into two groups, and they were connected with LAN cable in tunnel construction site. The purpose of this experiment was to check the validity of group separating strategy. One group was installed around the entrance and the other one was installed inside the tunnel. Finally, we installed the system inner area of tunnel, boring machine area, and checked the performance with varying conditions (the presence of obstacles such as train, worker, and so on). Accuracy of this study was calculated from the data, which was collected at some known points. Experimental results showed that WiFi-based indoor location system has a level of accuracy of a few meters in tunnel construction site. From the results, it is inferred that the location tracking system can track the approximate location of labors in the construction site. It is able to alert the labors when they are closer to dangerous zones like poisonous region or cave-in..

• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.1
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• pp.56-68
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• 2023

A system that extracts seabed topographic information by simultaneously and continuously observing the horizontal position and water depth in the sea by combining a single beam echosounder and GNSS was constructed. By applying the developed system to actual measurements of small-scale sea areas, the effectiveness of bathymetry and sea-floor topographic data acquisition using GNSS and echosounder was examined. By using the developed outdoor program DS-NAV and indoor program DS-CAD and applying the tide level data at the time of actual measurement of the target sea area, it was possible to derive bathymetry results based on the datum level i.e. approximate lowest low water level(A.L.L.W). By using the developed outdoor program DS-NAV and indoor program DS-CAD and applying the tide level data at the time of actual measurement of the target sea area, it was possible to derive the results of bathymetric survey based on the datum level. From database built through the actual measurement. it was possible to create 3D model of the sea-floor topography and extract cross-sections. The results of this study are expected to be economically useful for extracting seabed topographical information from small sea areas or in dredging sites for offshore construction.