• Fashion & Textile Research Journal
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• 제25권5호
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• pp.560-567
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• 2023

This study aims to rediscover the industrial value of a borderless service in the hyper-connected era by producing fashion content at the forefront of the cultural industry as XR content and contributing to developing fashion content for edutech. The research method employed design aesthetic theory, while the empirical proposal utilized scientific knowledge information to build a framework for 3D convergence content. The characteristics of fashion content exhibitions that apply the neumorphism technique are as follows: The first is a virtual space that produces clothing culture by type. Africa, where dyeing and crafts are developed, selects a product-oriented exhibition type; Asia, where weaving and textiles are excellent, selects a random movement type; and Europe, where the evolution of clothing design over time is evident, selects a guided movement type to create a three-dimensional fashion edutech. The goal was to produce content. The second is creative reproducibility, which combines a new fashion design that embraces the aura of the original with a trendy sense. The realistic folk costume style of the original allowed for its implementation in the AR exhibition space using historical traditional style techniques such as weaving and textiles. The third is building organic, modular content. By designing and then saving/editing/arranging the basic VP zone for each style, learners and instructors can freely edit the content for each fashion class topic and create various presentations to ensure that it functions as non-face-to-face edutech content around the world.

• Journal of the Korean Society of Radiology
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• 제18권1호
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• pp.21-26
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• 2024

The one of the famous deep learning models for object detection task is you only look once version 5 (YOLOv5) framework based on the one stage architecture. In addition, YOLOv5 model indicated high performance for accurate lesion detection using the bottleneck CSP layer and skip connection function. The purpose of this study was to evaluate the performance of YOLOv5 framework according to various hyperparameters in position emission tomogrpahy (PET) phantom images. The dataset was obtained from QIN PET segmentation challenge in 500 slices. We set the bounding box to generate ground truth dataset using labelImg software. The hyperparameters for network train were applied by changing optimization function (SDG, Adam, and AdamW), activation function (SiLU, LeakyRelu, Mish, and Hardwish), and YOLOv5 model size (nano, small, large, and xlarge). The intersection over union (IOU) method was used for performance evaluation. As a results, the condition of outstanding performance is to apply AdamW, Hardwish, and nano size for optimization function, activation function and model version, respectively. In conclusion, we confirmed the usefulness of YOLOv5 network for object detection performance in nuclear medicine images.

• Korean Journal of Remote Sensing
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• 제34권2_1호
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• pp.191-201
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• 2018

In this present study, we, for the first time, retrieved total column of ozone ($O_3$) and tropospheric ozone vertical profile using the Optimal Estimation (OE) method based on the MAX-DOAS measurement at the Yonsei University in Seoul, Korea. The optical density fitting is carried out using the OE method to calculate ozone columns. The optical density between the MAX-DOAS data obtained by dividing the measured intensities for each viewing elevated angle by those at the zenith angle. The retrieved total columns of the ozone are 375.4 and 412.6 DU in the morning (08:13) and afternoon (17:55) on 23 May, 2017, respectively. In addition, under 10 km altitude, the $O_3$ vertical profile was retrieved with about 5% of retrieval uncertainty. However, above 10 km altitude, the $O_3$ vertical profile retrieval uncertainty was increased (>10%). The spectral fitting errors are 16.8% and 19.1% in the morning and afternoon, respectively. The method suggested in this present study can be useful to measure the total ozone column using the ground-based hyper-spectral UV sensors.

• Journal of the Institute of Electronics Engineers of Korea SD
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• 제49권7호
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• pp.39-49
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• 2012

Demand for high resolution video services leads to active studies on high speed video processing. Especially, widespread deployment of multi-core systems accelerates researches on high resolution video processing based on parallelization of multimedia software. Previously proposed parallelization approach could improve the decoding performance. However, some parallelization methods did not consider the entropy decoding and others considered only a partial decoding parallelization. Therefore, we consider parallel entropy decoding integrated with other parallel video decoding process on a multi-core system. We propose a novel parallel decoding method called Integrated Parallelization. We propose a method on how to optimize the parallelization of video decoding when we have a multi-core system with many cores. We parallelized the KTA 2.7 decoder with the proposed technique on an Intel i7 Quad-Core platform with Intel Hyper-Threading technology and multi-threads scheduling. We achieved up to 70% performance improvement using IP method.

• KSCE Journal of Civil and Environmental Engineering Research
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• 제30권5D호
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• pp.453-459
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• 2010

In the study of traffic safety, it is utmost important to obtain more reliable estimates of the expected crashes for a site (or a segment). The observed crashes have been mainly used as the estimate of the expected crashes in Korea, while the empirical Bayes (EB) estimates based on the Poisson-gamma mixture model have been used in the USA and several European countries. Although numerous studies have used the EB method for estimating the expected crashes and/or the effectiveness of the safety countermeasures, no past studies examine the difference in the estimation errors between the two estimates. Thus, this study compares the estimation errors of the two estimates using a Monte Carlo simulation study. By analyzing the crash dataset at 3,000,000 simulated sites, this study reveals that the estimation errors of the EB estimates are always less than those of the observed crashes. Hence, it is imperative to incorporate the EB method into the traffic safety research guideline in Korea. However, the results show that the differences in the estimation errors between the two estimates decrease as the uncertainty of the prior distribution increases. Consequently, it is recommended that the EB method be used with reliable hyper-parameter estimates after conducting a comprehensive examination on the estimated negative binomial model.

• Journal of Chest Surgery
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• 제37권6호
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• pp.530-535
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• 2004

Background: Thoracoscopic R3 (above the third rib)sympathicotomy has been performed as an effective method in treating palmar hyperhidrosis because it is effective in eliminating the symptoms of hyperhidrosis and has lower degree of compensatory hyperhidrosis than that of sympathectomy. Most of the results published were based on the short-term follow up. So we evaluated the intermediate term follow up results of the R3 sympathicotomy. Material and Method: From April 1999 to August 2001, ninety-four patients with palmar hyperhidrosis had been treated by R3 sympathicotomy at the Inha University Hospital. Follow-up study was completed for 76 patients (male 38, female 38) and average follow-up period were 25$\pm$9.1 (15∼50) months. The sympathetic trunk passing above the upper border of third rib was divided by electric cautery. The patient's satisfaction after surgery was estimated using the analogue scale from score 0 to 100 (100 means perfect satisfaction). Result. The scale of patient's satisfaction immediately after operation was 92.36$\pm$9.93. After 15 months, the scale of satisfaction was decreased to average 71.80$\pm$20.24 and it is statiscally significant. The cause of dissatisfaction were compensatory hyper-hidrosis and recurrence of symptom. The degree of sweating immediately after operation was mean 0 and after 15 months it increased to mean 1.5. The degree of the compensatory hyperhidrosis immediately after operation was mean 1 and it increased to mean 5 after 15 months. Conclusion: R3 sympathicotomy has excellent therapeutic results immediately after operation but therapeutic effectiveness is becoming to decrease 15 months after operation. The common causes of dissatisfaction are compensatory hyperhidrosis and recurrence of hyperhidrosis.

• Journal of Chest Surgery
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• 제32권8호
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• pp.745-748
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• 1999

Background: A definitive cure for an essential hyperhidrosis can be obtained by an upper thoracic sympathectomy. However, this is offset by the occurrence of a compensatory hyper hidrosis as a side effect and it is irreversible. We performed a thoracoscopic sympathetic chain block using an endoscopic clip in order to avoid the compensatory hyperhidrosis. Material and Method: From Aug. 1998 to Nov. 1998, 42 cases of thoracoscopic clipping of the T2 sympathetic chain were performed. The sympathetic chain was clipped using an endoscopic clip instead of cutting. Result: Bilateral procedure took less than 40 minutes and occasionally necessitated one night in the hospital. There were no mortality nor life- threatening complications. Horners syndrome occurred in two cases. At the end of postoperative follow-up(median 3 months), 95.0% of the patients were satisfied with the results. Compensatory sweating occurred in 31 cases(77.5%) where nine of those cases were classified as either embarrassing(6 cases-15.0%) or disabling(3 cases-7.5%). Conclusion: Endoscopic thoracic T2 sympathetic chain block using endoscopic clipping is an efficient, safe and minimally invasive surgical method for the treatment of palmar and craniofacial hyperhidrosis and the results were similar to those underwent T2 sympathicotomy. We recommend that patients receive endoscopic sympathetic chain block in summer.

• Horticultural Science & Technology
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• 제33권5호
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• pp.737-750
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• 2015

This study was carried out to construct a DNA profile database for 102 watermelon cultivars through the comparison of polymorphism level and genetic relatedness using genomic microsatellite (gMS) and expressed sequence tag (EST)-microsatellite (eMS) markers. Sixteen gMS and 10 eMS primers showed hyper-variability and were able to represent the genetic variation within 102 watermelon cultivars. With gMS markers, an average of 3.63 alleles per marker were detected with a polymorphism information content (PIC) value of 0.479, whereas with eMS markers, the average number of alleles per marker was 2.50 and the PIC value was 0.425, indicating that eMS detects a lower polymorphism level compared to gMS. Cluster analysis and Jaccard's genetic distance coefficients using the unweighted pair group method with arithmetic average (UPGMA) based on the gMS, eMS, and combined data sets showed that 102 commercial watermelon cultivars could be categorized into 6 to 8 major groups corresponding to phenotypic traits. Moreover, this method was sufficient to identify 78 out of 102 cultivars. Correlation analysis with Mantel tests for those clusters using 3 data sets showed high correlation ($r{\geq}0.80$). Therefore, the microsatellite markers used in this study may serve as a useful tool for germplasm evaluation, genetic purity assessment, and fingerprinting of watermelon cultivars.

• Journal of the Korea Institute of Information and Communication Engineering
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• 제26권10호
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• pp.1517-1524
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• 2022

In this paper, we consider a heterogeneous network (HetNet) consisting of one macro base station and multiple small base stations, and assume the coordinated multi-point transmission between the base stations. In addition, we assume that the channel between the base station and the user consists of path loss and Rayleigh fading. Under these assumptions, we present the energy efficiency (EE) achievable by the user for a given base station and we formulate an optimization problem of dynamic cell selection and transmit power allocation to maximize the total EE of the HetNet. In this paper, we propose an unsupervised deep learning method to solve the optimization problem. The proposed deep learning-based scheme can provide high EE while having low complexity compared to the conventional iterative convergence methods. Through the simulation, we show that the proposed dynamic cell selection scheme provides higher EE performance than the maximum signal-to-interference-plus-noise ratio scheme and the Lagrangian dual decomposition scheme, and the proposed transmit power allocation scheme provides the similar performance to the trust region interior point method which can achieve the maximum EE.

• Geomechanics and Engineering
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• 제35권2호
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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.