• Imaging Science in Dentistry
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• v.49 no.2
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• pp.159-169
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• 2019

Purpose: Cone-beam computed tomography (CBCT) is widely used for 3-dimensional assessments of cranio-maxillo-facial relationships, especially in patients undergoing orthognathic surgery. We have introduced, for reference in CBCT cephalometry, an anatomical mid-sagittal plane (MSP) identified by the nasion, the midpoint between the posterior clinoid processes of the sella turcica, and the basion. The MSP is an updated version of the median plane previously used at our institution for 2D posterior-anterior cephalometry. This study was conducted to test the accuracy of the CBCT measures compared to those obtained using standard posterior-anterior cephalometry. Materials and Methods: Two operators measured the inter-zygomatic distance on 15 CBCT scans using the MSP as a reference plane, and the CBCT measurements were compared with measurements made on patients' posterior-anterior cephalograms. The statistical analysis evaluated the absolute and percentage differences between the 3D and 2D measurements. Results: As demonstrated by the absolute mean difference (roughly 1 mm) and the percentage difference (less than 3%), the MSP showed good accuracy on CBCT compared to the 2D plane, especially for measurements of the left side. However, the CBCT measurements showed a high standard deviation, indicating major variability and low precision. Conclusion: The anatomical MSP can be used as a reliable reference plane for transverse measurements in 3D cephalometry in cases of symmetrical or asymmetrical malocclusion. In patients who suffer from distortions of the skull base, the identification of landmarks might be difficult and the MSP could be unreliable. Becoming familiar with the relevant software could reduce errors and improve reliability.

• International Area Studies Review
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• v.16 no.1
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• pp.243-274
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• 2012

This research analyzes the determinants of Korea's trade using the Gravity model, Chow test and panel data anaysis. According to the pooled panel OLS analysis using the gravity model and Chow-test, Korea's trade patterns before and after the 2008 financial crisis are heterogeneous. Variables of basic gravity model, GDP per capita, distance, and population, identically showed positive and significant correlation with trade volume before and after financial crisis, but also equally showed the decrease in absolute value of coefficient. On the other hands, Overseas Direct Investments(ODI) variable showed the increase in absolute value of coefficient. But TCI was no longer significant. This research is significant in that it is able to show the strategy for the long term growth in Korea's volume of international trade through econometric analysis based on data of 55 trading partner of Korea.

• Tunnel and Underground Space
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• v.31 no.6
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• pp.508-519
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• 2021

In this study, a model was developed to predict the peak particle velocity (PPV) that affects people and the surrounding environment during blasting. Four machine learning models using the k-nearest neighbors (kNN), classification and regression tree (CART), support vector regression (SVR), and particle swarm optimization (PSO)-SVR algorithms were developed and compared with each other to predict the PPV. Mt. Yogmang located in Changwon-si, Gyeongsangnam-do was selected as a study area, and 1048 blasting data were acquired to train the machine learning models. The blasting data consisted of hole length, burden, spacing, maximum charge per delay, powder factor, number of holes, ratio of emulsion, monitoring distance and PPV. To evaluate the performance of the trained models, the mean absolute error (MAE), mean square error (MSE), and root mean square error (RMSE) were used. The PSO-SVR model showed superior performance with MAE, MSE and RMSE of 0.0348, 0.0021 and 0.0458, respectively. Finally, a method was proposed to predict the degree of influence on the surrounding environment using the developed machine learning models.

• Journal of the Korean Applied Science and Technology
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• v.40 no.5
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• pp.977-987
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• 2023

The purpose of this study was to investigate the effect of visual information on the dynamic balance on Y-balance Test(YBT). The subjects of the study were 18 male and female adults in their 20s and 30s (age: 23.17±1.72 years, height: 172.46±9.84 cm, weight: 73.39±11.44 kg, leg length: 88.89±5.69 cm) who participated in the study. To measure dynamic balance between binocular and monocular use, absolute reach distance, composite score, and COP variables were measured on left and right feet through YBT and results were derived. As a result of the study, monocular block(left and right eye block) showed higher absolute reach and composite scores than binocular use in posterolateral, posteromedial, and composite scores during YBT. As a result of COP, there was no difference in anterior and posteromedial reach. When reaching posterolateral, AP COP velocity of left foot in monocular block appeared slower than that in binocular vision, and in COP velocity, COP velocity of left foot in monocular block appeared slower than binocular vision.

• Journal of the Korean association of regional geographers
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• v.16 no.1
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• pp.59-75
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• 2010

This study analyzed on the recognition characteristics of high school students in Seoul about the factors influencing the land value. The results are as follows; First, when the factors influencing the land value was divided into 'the factors related with the publicly assessed land value' and 'the unrelated factors.' Students recognized that the former had more influence on the land value than the latter. Second, students recognized that 'the relative factors of land' had more influence on the land value than 'the absolute factors of land'. Third, as a result of checking how much five evaluation criterions influence on the recognition characteristics about the factors influencing the land value, the distance to major facilities had the most influence on the recognition, while the situation of land use had the weakest one. Among 13 factors, the distance from the convenience facilities was most influential and the shape of the land was least influential. Fourth, there was a gap between recognition of choosing the highest land value areas and the lowest land value areas and recognition of degree that the factor influencing the land value had an effect on the land value. Lastly, when the result of recognition about factors influencing the land value and the land value ranking was compared with the result of the co-relation between the land value and factors influencing the land value of the real region, either similar or different results were shown.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.5
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• pp.548-553
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• 2014

In order to evaluate the performance of arrow that manufactures through production process, it is used that personal experiences such as hunters who have been using bow and arrow for a long time, technicians who produces leisure and sports equipment, and experts related with this industries. Also, the intensity of arrow's impact point which obtains from repeated shooting experiments is an important indicator for evaluating the performance of arrow. There are some ongoing researches for evaluating performance of arrow using intensity of the arrow's impact point and the arrow's flying image that obtained from high-speed camera. However, the research that deals with mutual relation between distribution of the arrow's impact point and characteristics of the arrow (length, weight, spine, overlap, straightness) is not enough. Therefore, this paper suggests both the system that could describes the distribution of the arrow's impact point into numerical representation and the correlation model between characteristics of arrow and impact points. The inputs of the model are characteristics of arrow (spine, straightness). And the output is MAD (mean absolute distance) of triangular shaped coordinates that could be obtained from 3 times repeated shooting by changing knock degree 120. The input-output data is collected for learning the correlation model, and ANN (artificial neural network) is used for implementing the model.

• Korean Journal of Heritage: History & Science
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• v.50 no.3
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• pp.30-43
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• 2017

The purpose of this study is to improve the usefulness of photogrammetry in the field of cultural heritage recording concentrated on laser scanning. Two measurement methods(laser scanning, photogrammetry) were compared in terms of accuracy and reality for the Rock-carved Standing Buddha in Singyeong-ri, Hongseong. With regard to accuracy, the distances of major points by both shape information and between the two shape information were compared. Only a deviation of about 1mm was found in the distance measurement of the major points by both shape information. In particular, the average distance between two shape information identified through aligning was only about 0.01mm. Also, the absolute deviation within about 2mm accounted for 70% of the total, and the absolute deviation within about 3.5mm was found to be 95.4% of the total. These values showed very high similarity between laser scanning and photogrammetry-based shape information. In respect of reality, the carved depth, texture, and patterns were compared. As a result of comparing four cross-sectional shapes, only slight differences were found in the shape information of both measurement techniques and similar shapes were identified. The overall texture of both shape information was also similar. However, the detailed shape based on the photogrammetry with decimation is realized with a smoother texture than the original and laser scanning. In particular, Photogrammetry also realistically expressed the various ornaments carved in the Rock-carved Buddha and the patterns with shallow depths were comparatively detailed.

• Geomechanics and Engineering
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• v.35 no.2
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• pp.121-133
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• 2023

The demand for cement and limestone crushed materials has increased many folds due to the tremendous increase in construction activities in Pakistan during the past few decades. The number of cement production industries has increased correspondingly, and so the rock-blasting operations at the limestone quarry sites. However, the safety procedures warranted at these sites for the blast-induced ground vibrations (BIGV) have not been adequately developed and/or implemented. Proper prediction and monitoring of BIGV are necessary to ensure the safety of structures in the vicinity of these quarry sites. In this paper, an attempt has been made to predict BIGV using artificial neural network (ANN) at three selected limestone quarries of Pakistan. The ANN has been developed in Python using Keras with sequential model and dense layers. The hyper parameters and neurons in each of the activation layers has been optimized using randomized and grid search method. The input parameters for the model include distance, a maximum charge per delay (MCPD), depth of hole, burden, spacing, and number of blast holes, whereas, peak particle velocity (PPV) is taken as the only output parameter. A total of 110 blast vibrations datasets were recorded from three different limestone quarries. The dataset has been divided into 85% for neural network training, and 15% for testing of the network. A five-layer ANN is trained with Rectified Linear Unit (ReLU) activation function, Adam optimization algorithm with a learning rate of 0.001, and batch size of 32 with the topology of 6-32-32-256-1. The blast datasets were utilized to compare the performance of ANN, multivariate regression analysis (MVRA), and empirical predictors. The performance was evaluated using the coefficient of determination (R²), mean absolute error (MAE), mean squared error (MSE), mean absolute percentage error (MAPE), and root mean squared error (RMSE)for predicted and measured PPV. To determine the relative influence of each parameter on the PPV, sensitivity analyses were performed for all input parameters. The analyses reveal that ANN performs superior than MVRA and other empirical predictors, andthat83% PPV is affected by distance and MCPD while hole depth, number of blast holes, burden and spacing contribute for the remaining 17%. This research provides valuable insights into improving safety measures and ensuring the structural integrity of buildings near limestone quarry sites.

• Journal of radiological science and technology
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• v.31 no.1
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• pp.83-87
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• 2008

The purpose of this study is to get the correction factor to correct the measured values of the absolute absorbed dose proportional to the water equivalent depth. The measurement conditions in white polystyrene and water phantoms for 10MV X-ray beam are that the distance of source to center of ionization chamber is fixed at SAD 100 cm, the field sizes are $10{\times}10\;cm^2$, $20{\times}20\;cm^2$ and the depths are 2.3 cm, 5 cm, 10 cm, and 15 cm, respectively. The mean value of ionization was obtained by three times measurements in each field size and depths after delivering 100 MU from linear accelerator with output of 400 MU per min to the two phantoms. The correction factor and the percentage deviation in TPR were obtained below 0.97% and 0.53%, respectively. Therefore, we can get high accuracy by using the correction factor and the percentage deviation in TPR in measuring the absolute absorbed dose with the solid water equivalent phantom.

• Tunnel and Underground Space
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• v.25 no.1
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• pp.56-67
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• 2015

In this study, a source locating technique applicable to transversely isotropic media was developed. Wave velocity anisotropy was considered based on the partition approximation method, which simply enabled AE source locating. Sets of P wave arrival time were decided by the two-step AIC algorithm and they were later used to locate the AE sources when having the least error compared with the partitioned elements. In order to validate the technique, pencil lead break test on artificial transversely isotropic mortar specimen was carried out. Defining the absolute error as the distance between the pencil lead break point and the located point, 1.60 mm ~ 14.46 mm of range and 8.57 mm of average were estimated therefore it was regarded as thought to be 'acceptable' considering the size of the specimen and the AE sensors. Comparing each absolute error under different threshold levels, results showed small discrepancies therefore this technique was hardly affected by background noise. Absolute error could be decomposed into each coordinate axis error and through it, effect of AE sensor position could be understood so if optimum sensor position was able to be decided, one could get more precise outcome.