• Journal of Conservation Science
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• v.37 no.3
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• pp.232-244
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• 2021

This study examined the physical attributes and heat treatment characteristics of glass beads excavated from the Gimhae area, which is the location of Geumgwan Gaya. This enabled classification of surface characteristics of the beads based on the investigation of the color, size, and shape. The glass beads were classified into eight color systems, with purplish-blue beads as the representative color. Bead size was categorized into three types depending on the outer diameter and how it increased over time. Bead shapes were categorized as round, tubular, or doughnut-shaped based on the inner diameter and length, with round being the typical shape. According to the degree of heat treatment, there are three types of cross-section for glass beads that are manufactured by the drawing technique, most of which are the HT-III type. In addition, it is estimated that the heat treatment technology has more considerable effects than other methods. Through non-destructive analysis, the chemical composition was obtained and categorized as flux, stabilizer, and colorant. Analysis confirmed the presence of 63 and 9 pieces in the potash and soda glass groups, respectively. Overall findings from the study highlighted a correlation between the chemical composition and the external factors such as color, size, shape, and manufacturing technology of glass beads recovered from Geumgwan Gaya, revealing characteristics related to that time and region.

• Ecology and Resilient Infrastructure
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• v.8 no.1
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• pp.1-8
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• 2021

A surface image velocimeter (SIV) measures the velocity of a particle group by calculating the intensity distribution of the particle group in two consecutive images of the water surface using a cross-correlation method. Therefore, to increase the accuracy of the flow velocity calculated by a SIV, it is important to accurately calculate the displacement of the particle group in the images. In other words, the change in the physical distance of the particle group in the two images to be analyzed must be accurately calculated. In the image of an actual river taken using a camera, camera lens distortion inevitably occurs, which affects the displacement calculation in the image. In this study, we analyzed the effect of camera lens distortion on the displacement calculation using a dense and uniformly spaced grid board. The results showed that the camera lens distortion gradually increased in the radial direction from the center of the image. The displacement calculation error reached 8.10% at the outer edge of the image and was within 5% at the center of the image. In the future, camera lens distortion correction can be applied to improve the accuracy of river surface flow rate measurements.

• The Journal of Information Systems
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• v.30 no.1
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• pp.151-177
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• 2021

Purpose This paper aims to improve management performance by effectively responding to production needs and reducing inventory through synchronizing production planning and procurement in the aviation industry. In this study, the differences in production planning and execution were first analyzed in terms of demand, supply, inventory, and process using the big data collected from a domestic aircraft manufacturers. This paper analyzed the problems in procurement and inventory management using legacy big data from ERP system in the company. Based on the analysis, we performed a simulation to derive an efficient procurement and inventory management plan. Through analysis and simulation of operational data, we were able to discover procurement and inventory policies to effectively respond to production needs. Design/methodology/approach This is an empirical study to analyze the cause of decrease in inventory turnover and increase in inventory cost due to dis-synchronize between production requirements and procurement. The actual operation data, a total of 21,306,611 transaction data which are 18 months data from January 2019 to June 2020, were extracted from the ERP system. All them are such as basic information on materials, material consumption and movement history, inventory/receipt/shipment status, and production orders. To perform data analysis, it went through three steps. At first, we identified the current states and problems of production process to grasp the situation of what happened, and secondly, analyzed the data to identify expected problems through cross-link analysis between transactions, and finally, defined what to do. Many analysis techniques such as correlation analysis, moving average analysis, and linear regression analysis were applied to predict the status of inventory. A simulation was performed to analyze the appropriate inventory level according to the control of fluctuations in the production planing. In the simulation, we tested four alternatives how to coordinate the synchronization between the procurement plan and the production plan. All the alternatives give us more plausible results than actual operation in the past. Findings Based on the big data extracted from the ERP system, the relationship between the level of delivery and the distribution of fluctuations was analyzed in terms of demand, supply, inventory, and process. As a result of analyzing the inventory turnover rate, the root cause of the inventory increase were identified. In addition, based on the data on delivery and receipt performance, it was possible to accurately analyze how much gap occurs between supply and demand, and to figure out how much this affects the inventory level. Moreover, we were able to obtain the more predictable and insightful results through simulation that organizational performance such as inventory cost and lead time can be improved by synchronizing the production planning and purchase procurement with supply and demand information. The results of big data analysis and simulation gave us more insights in production planning, procurement, and inventory management for smart manufacturing and performance improvement.

• Journal of the Korea Convergence Society
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• v.13 no.4
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• pp.147-154
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• 2022

This paper evaluated visual function and stereoacuity function after surgery for intermittent exotropia. Subjects of this study were 18 patients (male: n = 10, female: n = 8) mean aged 12.06±5.43 years diagnosed with intermittent exotropia who underwent strabismus surgery. Of these subjects, 72.2% of the subjects underwent strabismus surgery once and 27.8% had it twice. Visual function and stereoacuity function were tested for these subjects. For data analysis, frequency analysis, cross analysis, and correlation analysis were used, and statistical significance was set at p<.05. Regarding the deviation state after strabismus surgery, exodeviation accounted for the most(72.2%), followed by diplopia(50.0%) and suppression(33.3%) for distance sensory fusion. Regarding near sensory fusion, fusion(50.0%) accounted for the most, followed by diplopia(44.4%). After strabismus surgery, subjects with distance stereoacuity blindness were the most at 61.1% and there were no subjects with a normal range of 40-60 arcsec. Near stereoacuity blindness subjects accounted for 33.3% and subjects with 40-60 arcsec accounted for 1.1%. Even after surgery for intermittent exotropia, there were some areas that did not improve in deviation state, stereoacuity, or sensory fusion. Therefore, it is necessary to manage and control strabismus through non-surgical methods before and after surgery for intermittent exotropia.

• Journal of Korean Neurosurgical Society
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• v.65 no.1
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• pp.74-83
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• 2022

Objective : Oblique lumbar interbody fusion (OLIF) is a surgical technique that utilizes a large interbody cage to indirectly decompress neural elements. The position of the cage relative to the vertebral body could affect the degree of foraminal decompression. Previous studies determined the position of the cage using plain radiographs, with conflicting results regarding the influence of the position of the cage to the degree of neural foramen decompression. Because of the cage obliquity, computed tomography (CT) has better accuracy than plain radiograph for the measurement of the obliquely inserted cage. The objective of this study is to find the correlation between the position of the OLIF cage with the degree of indirect decompression of foraminal stenosis using CT and magnetic resonance imaging (MRI). Methods : We review imaging of 46 patients who underwent OLIF from L2-L5 for 68 levels. Segmental lordosis (SL) was measured in a plain radiograph. The positions of the cage were measured in CT. Spinal canal cross-sectional area (SCSA), and foraminal crosssectional area (FSCA) measurements using MRI were taken into consideration. Results : Patients' mean age was 69.7 years. SL increases 3.0±5.1 degrees. Significant increases in SCSA (33.3%), FCSA (43.7% on the left and 45.0% on the right foramen) were found (p<0.001). Multiple linear regression analysis shows putting the cage in the more posterior position correlated with more increase of FSCA and decreases SL correction. The position of the cage does not affect the degree of the central spinal canal decompression. Obliquity of the cage does not result in different degrees of foraminal decompression between right and left side neural foramen. Conclusion : Cage position near the posterior part of the vertebral body increases the decompression effect of the neural foramen while putting the cage in the more anterior position correlated with increases SL.

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.571-585
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• 2022

As the threat of natural disasters such as droughts, floods, forest fires, and landslides increases due to climate change, social demand for high-resolution soil moisture retrieval, such as Synthetic Aperture Radar (SAR), is also increasing. However, the domestic environment has a high proportion of mountainous topography, making it challenging to retrieve soil moisture from SAR data. This study evaluated the usability of Sentinel-1 SAR, which is applied with the Artificial Neural Network (ANN) technique, to retrieve soil moisture. It was confirmed that the backscattering coefficient obtained from Sentinel-1 significantly correlated with soil moisture behavior, and the possibility of stand-alone use to correct vegetation effects without using auxiliary data observed from other satellites or observatories. However, there was a large difference in the characteristics of each site and topographic group. In particular, when the model learned on the mountain and at flat land cross-applied, the soil moisture could not be properly simulated. In addition, when the number of learning points was increased to solve this problem, the soil moisture retrieval model was smoothed. As a result, the overall correlation coefficient of all sites improved, but errors at individual sites gradually increased. Therefore, systematic research must be conducted in order to widely apply high-resolution SAR soil moisture data. It is expected that it can be effectively used in various fields if the scope of learning sites and application targets are specifically limited.

• Journal of Korea Water Resources Association
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• v.55 no.12
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• pp.1137-1147
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• 2022

River and groundwater stages are the main elements in the hydrologic cycle. They are spatially correlated and can be used to evaluate hydrological and agricultural drought. Stochastic simulation is often performed independently on hydrological variables that are spatiotemporally correlated. In this setting, interdependency across mutual variables may not be maintained. This study proposes the Bayesian vector autoregression model (VAR) to capture the interdependency between multiple variables over time. VAR models systematically consider the lagged stages of each variable and the lagged values of the other variables. Further, an autoregressive model (AR) was built and compared with the VAR model. It was confirmed that the VAR model was more effective in reproducing observed interdependency (or cross-correlation) between river and ground stages, while the AR generally underestimated that of the observed.

• Korean Journal of Environment and Ecology
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• v.36 no.5
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• pp.535-549
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• 2022

Damage to forests, such as broken or falling trees, has increased due to the increased intensity and frequency of abnormal climate events, such as strong winds and heavy rains. However, it is difficult to respond to them in advance based on prediction since structural defects such as cavities and bumps inside trees are difficult to identify with a visual inspection. Non-invasive sonic tomography (SoT) is a method of estimating internal defects while minimizing physical damage to trees. Although SoT is effective in diagnosing internal defects, its accuracy varies depending on the species. Therefore, it is necessary to analyze the reliability of its measurement results before applying it in the field. In this study, we measured internal defects in wood by cross-applying destructive resistance micro drilling on old Pinus densifloraSiebold & Zucc. and Ginkgo bilobaL., which are representative tree species in Korea, to verify the reliability of SoT and compared the evaluation results. The t-test for the mean values of the defect measurement between the two groups showed no statistically significant difference in pine trees and some difference in ginkgo trees. Linear regression analysis results showed a positive correlation with an increase in defects in SoT images when the defects in the drill resistance graph increased in both species.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1615-1615
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• 2001

During the past ten years, Near Infrared Spectroscopy has been successfully applied to the analysis of a great variety of agriculture products. Previous works (Morra et al., 1991; Salgo et al., 1998) have shown the potential of this technology for soil analysis, estimating different parameters just with one single scan. The main advantages of NIR applications in soils are the speed of response, allowing the increase of the number of samples analysed to define a particular soil, and the instantaneous elaboration of recommendations for fertilization and soil amendment. Another advantage is to avoid the use of chemical reagents at all, being an environmentally safe technique. In this paper, we have studied a set of 129 soil samples selected from representative glasshouse soils from Southern Spain. The samples were dried, milled, and sieved to pass a 2 mm sieve and then analysed for organic carbon, total nitrogen, inorganic nitrogen (nitrate ammonium), hygroscopic humidity, pH and electrical conductivity in the 1:1 extract. NIR spectra of all samples were obtained in reflectance mode using a Foss NIR Systems 6500 spectrophotometer equipped with a spinning module. Calibration equations were developed for seven analytical parameters (ph, Total nitrogen, organic nitrogen, organic carbon, C/N ratio and Electric Conductivity). Preliminary results show good correlation coefficients and standard errors of cross validation in equations obtained for Organic Carbon, Organic Nitrogen, Total Nitrogen and C/N ratio. Calibrations for nitrates and nitrites, ammonia and electric conductivity were not acceptable. Calibration obtained for pH had an acceptable SECV, but the determination coefficient was found very poor probably due to the reduced range in reference values. Since the estimation of Organic Carbon and C/N ratio are acceptable NIIRS could be used as a fast method to assess the necessity of organic amendments in soils from Mediterranean regions where the low level of organic matter in soils constitutes an important agronomic problem. Furthermore, the possibility of a single and fast estimation of Total Nitrogen (tedious determination by modifications of the Kjeldahl procedure) could provide and interesting data to use in the estimation of nitrogen fertilizer rates by means of nitrogen balances.

• Journal of Service Research and Studies
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• v.12 no.2
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• pp.80-93
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• 2022

This study is a study on a methodology that can extract various factors that affect purchase and use of products/services from the consumer's point of view through previous studies, and analyze the types and tendencies of consumers according to age and gender. To this end, we quantify factors in terms of general personal propensity, consumption influence, consumption decision, etc. to check the consistency of data, and based on these studies, we conduct research to suggest and prove data analysis methodologies of consumer types that are meaningful from the perspectives of startups and SMEs. did As a result, it was confirmed through cross-validation that there is a correlation between the three main factors assumed for data analysis from the consumer's point of view, the general tendency, the general consumption tendency, and the factors influencing the consumption decision. verified. This study presented a data analysis methodology and a framework for consumer data analysis from the consumer's point of view. In the current data analysis trend, where digital infrastructure develops exponentially and seeks ways to project individual preferences, this data analysis perspective can be a valid insight.