• Smart Media Journal
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• v.12 no.7
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• pp.43-51
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• 2023

As online transactions increase, the image of clothing has a great influence on consumer purchasing decisions. The importance of image information for clothing materials has been emphasized, and it is important for the fashion industry to analyze clothing images and grasp the materials used. Textile materials used for clothing are difficult to identify with the naked eye, and much time and cost are consumed in sorting. This study aims to classify the materials of textiles from clothing images based on deep learning algorithms. Classifying materials can help reduce clothing production costs, increase the efficiency of the manufacturing process, and contribute to the service of recommending products of specific materials to consumers. We used machine vision-based deep learning algorithms ResNet and Vision Transformer to classify clothing images. A total of 760,949 images were collected and preprocessed to detect abnormal images. Finally, a total of 167,299 clothing images, 19 textile labels and 20 fabric labels were used. We used ResNet and Vision Transformer to classify clothing materials and compared the performance of the algorithms with the Top-k Accuracy Score metric. As a result of comparing the performance, the Vision Transformer algorithm outperforms ResNet.

• Journal of Animal Science and Technology
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• v.65 no.1
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• pp.69-95
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• 2023

In order to evaluate the effects of ARG sources (arginine [ARG] and Guanidinoacetic acid [GAA]) and phenylalanine (PHE) supplementation on performance, susceptibility to ascites, intestinal morphology, and nutrient digestibility in the cold-stressed broilers fed a canola meal (CM)-based diet, a 2×2 factorial experiment with four treatments was conducted. The dietary treatments included CM-based diet + 2.57 g/kg ARG, CM-based diet + 2.57 g/kg ARG + 1.5 g/kg PHE, CM-based diet + 1.8 g/kg GAA and CM-based diet + 1.8 g/kg GAA + 1.5 g/kg PHE. The corn-CM diet without supplementation was used as a negative control (NC) group in the fifth treatment that excluded the factorial arrangement. The results showed that adding ARG to diets without PHE supplement increased (p < 0.05) feed intake. Also, birds fed diets containing ARG had higher (p < 0.05) body weight gain (BWG) compared to those fed GAA added diets. Supplementation of PHE improved (p < 0.05) the FCR compared to groups fed diets without added PHE. Further, ARG addition increased (p < 0.05) plasma nitric oxide (NO) concentration, carcass, breast and leg yields, duodenal, jejunal, and ileal villus height (VH) to crypt depth (CD, and dry matter digestibility, while decreasing (p < 0.05) ascites mortality and right ventricle (RV) to total ventricle (TV) ratio compared to GAA added groups. Supplementation of PHE also declined susceptibility to ascites by reducing (p < 0.01) RV to TV ratio while increasing (p < 0.05) plasma NO level. The digestibility of ether extract also increased (p < 0.05) in broilers fed GAA supplemented diets versus those fed ARG added diets. The findings suggested that ARG may improve BWG and lower ascites incidence in broilers fed a diet based on CM under cold stress because of its antihypertensive effects. Moreover, the findings of this study demonstrated the importance of including PHE formulation in ARG-deficient diets to attenuate the adverse effects of cold stress on broilers. It was also concluded that GAA could be efficaciously used in cold-stressed broilers fed an ARG-deficient diet.

• Journal of Korean Society of Forest Science
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• v.112 no.2
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• pp.145-156
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• 2023

In this study, Fourier-transform near-infrared (FT-NIR) spectra of Korean red pine seeds stored at -18℃ and 4℃ for 18 years were analyzed. To develop seed-germination prediction models, the performance of seven machine learning methods, namely XGBoost, Boosted Tree, Bootstrap Forest, Neural Networks, Decision Tree, Support Vector Machine, PLS-DA, were compared. The predictive performance, assessed by accuracy, misclassification, and area under the curve (0.9722, 0.0278, and 0.9735 for XGBoost, and 0.9653, 0.0347, and 0.9647 for Boosted Tree), was better for the XGBoost and decision tree models when compared with other models. The 54 wave-number variables of the two models were of high relative importance in seed-germination prediction and were grouped into six spectral ranges (811~1,088 nm, 1,137~1,273 nm, 1,336~1,453 nm, 1,666~1,671 nm, 1,879~2,045 nm, and 2,058~2,409 nm) for aromatic amino acids, cellulose, lignin, starch, fatty acids, and moisture, respectively. Use of the NIR spectral data and two machine learning models developed in this study gave >96% accuracy for the prediction of pine-seed germination after long-term storage, indicating this approach could be useful for non-destructive viability testing of stored seed genetic resources.

• Journal of the Korea Society of Computer and Information
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• v.14 no.3
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• pp.41-49
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• 2009

Flash memory has become increasingly requestion for the importance and the demand as a storage due to its low power consumption, cheap prices and large capacity medium. This research is to design a high performance flash memory structure for the substitution of a hard-disk by dynamic prefetching of aggressive spatial locality from the spatial smart buffer system. The proposed buffer system in a NAND flash memory consists of three parts, i.e., a fully associative victim buffer for temporal locality, a fully associative spatial buffer for spatial locality, and a dynamic fetching unit. We proposed new dynamic prefetching algorithm for aggressive spatial locality. That is to use the flash memory instead of the hard disk, the proposed flash system can achieve better performance gain by overcoming many drawbacks of the flash memory by the new structure and the new algorithm. According to the simulation results, compared with the smart buffer system, the average miss ratio is reduced about 26% for Mediabench applications. The average memory access times are improved about 35% for Mediabench applications, over 30% for Spec2000 applications.

• Journal of Life Science
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• v.33 no.6
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• pp.490-497
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• 2023

Pregnant women may need to take medications to treat preexisting diseases or diseases that develop during pregnancy. However, some drugs may be fetotoxic and lead to, for example, teratogenicity and growth retardation. Predicting the fetotoxicity of drugs is thus important for the health of the mother and fetus. The fetotoxicity of many drugs has not been established because various challenges hinder the ability of researchers to determine their fetotoxicity. The need exists for in silico-based fetotoxicity assessment models, as they can modernize the testing paradigm, improve predictability, and reduce the use of animals and the costs of fetotoxicity testing. In this study, we collected data on the fetotoxicity of drugs and constructed fetotoxicity prediction models based on various machine learning algorithms. We optimized the models for more precise predictions by tuning the hyperparameters. We then performed quantitative performance evaluations. The results indicated that the constructed machine learning-based models had high performance (AUROC >0.85, AUPR >0.9) in fetotoxicity prediction. We also analyzed the feature importance of our model's predictions, which could be leveraged to identify the specific features of drugs that are strongly associated with fetotoxicity. The proposed model can be used to prescreen drugs and drug candidates at a lower cost and in less time. It provides a predictive score for fetotoxicity risk, which may be beneficial in the design of studies on fetotoxicity in human pregnancy.

• 한국체육학회지인문사회과학편
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• v.55 no.2
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• pp.35-46
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• 2016

This study aims to observe the operation aspect of physical education during before class and further, to search for the utmost improvement direction using IPA (Importance-Performance Analysis). 500 middle & high school students have chosen through a purposeful sampling method, and 430 was used for analysis. The results were as follows. The quadrant I is "the keep up the good work" part. And the quadrant I includes "de-stress", "the pleasure of school life", "improvement in performance", "peer relationship", "help for P.E.", "health promotion", "sport facility surroundings", "rules", "teacher leadership", "passionate coaching", "fair coaching", "improvement in exercise ability", "understanding P.E." The quadrant II is "the concentrate here" part. And the quadrant II includes "develop talent", "excercise time", "safety management for exercise facility", "new sports event", "consider needs and interests", "consider level" "consider gender". The quadrant III is "the low priority" part. And the quadrant III includes "change of personality", "ability to do various sports event", "develope thinking ability". "communication with peer" "an intelligible explanation" In order to improve the quality of before classes, first, "safety connected program" second, "emotional and intellectual development program", third, "divided classes per level and gender", and the last, "professional manpower for developing the quality of class" are needed.

• Journal of Korea Water Resources Association
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• v.56 no.2
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• pp.91-101
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• 2023

In this study, we estimated the concentration of chlorophyll-a (Chl-a) using hyperspectral water surface reflectance in an inland weir (Baekjae weir) and estuarine reservoir (Namyang Reservoir) for monitoring the occurrence of algae in freshwater in South Korea. The hyperspectral reflectance was measured by aircraft in Baekjae Weir (BJW) from 2016 to 2017, and a drone in Namyang Reservoir (NYR) from 2020 to 2021. The 30 reflectance bands (BJW: 400-530, 620-680, 710-730, 760-790 nm, NYR: 400-430, 655-680, 740-800 nm) that were highly related to Chl-a concentration were selected using permutation importance. Artificial neural network based Chl-a estimation model was developed using the selected reflectance in both water bodies. And the performance of the model was evaluated with the coefficient of determination (R²), the root mean square error (RMSE), and the mean absolute error (MAE). The performance evaluation results of the Chl-a estimation model for each watershed was R²: 0.63, 0.82, RMSE: 9.67, 6.99, and MAE: 11.25, 8.48, respectively. The developed Chl-a model of this study may be used as foundation tool for the optimal management of freshwater algal blooms in the future.

• (The) Research of the performance art and culture
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• no.22
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• pp.157-183
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• 2011

This study is to find out the legitimacy and features of Honam Choreography via Lee Mae-bang and Han Jin-ok, two of the masters, and to seek better and more creative ways to pass it down in view of regional particularities. The study looks into the traditional choreography's multi-conceptuality that is derived from various forms of art and lends it its identity with the original notion rooted in Buddhist dancing. Despite the local cultural traits of the Honam area, the fact that Lee Mae-bang is more feminine and Han Jin-ok more masculine shows the two's worlds of dancing have been created from different perspectives, though they are quite common in their roots and locales. The particularities of passing down traditional choreography are given a thought in this study with the distinction and identity taken into account. Also, it will give an opportunity to discuss the importance of localism as aesthetic consciousness and communica tion channel. In any case, there is no doubt that local difference and communica tion make a very important source of culture when we look into the originality of the choreography.

• The Journal of the Acoustical Society of Korea
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• v.42 no.6
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• pp.544-551
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• 2023

Speech enhancement used to improve the perceptual quality and intelligibility of noise speech has been studied as a method using a complex-valued spectrum that can improve both magnitude and phase in a method using a magnitude spectrum. In this paper, a study was conducted on how to apply attention mechanism to complex-valued spectrum-based speech enhancement systems to further improve the intelligibility and quality of noise speech. The attention is performed based on additive attention and allows the attention weight to be calculated in consideration of the complex-valued spectrum. In addition, the global average pooling was used to consider the importance of the feature map. Complex-valued spectrum-based speech enhancement was performed based on the Deep Complex U-Net (DCUNET) model, and additive attention was conducted based on the proposed method in the Attention U-Net model. The results of the experiments on noise speech in a living room environment showed that the proposed method is improved performance over the baseline model according to evaluation metrics such as Source to Distortion Ratio (SDR), Perceptual Evaluation of Speech Quality (PESQ), and Short Time Object Intelligence (STOI), and consistently improved performance across various background noise environments and low Signal-to-Noise Ratio (SNR) conditions. Through this, the proposed speech enhancement system demonstrated its effectiveness in improving the intelligibility and quality of noisy speech.

• Journal of Venture Innovation
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• v.5 no.1
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• pp.145-154
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• 2022

This study briefly compares the first-cycle certification of nursing hospitals with the second-cycle certification, reviews the changes and achievements of the second-cycle certification and the third-cycle certification, and examples of challenges and solutions in the process of preparing the third-cycle certification. In this study, it is suggested as follows. First, in order to see the practical effect of certification intended by the government, the exhibition is prepared in a short period of time before certification. Second, after the implementation of the nursing hospital certification system, research on the hospital performance of the medical institution certification system is insufficient in terms of quality and quantity. Therefore, in order to see the effect on the certification system, various research support is also required so that research on this can be actively conducted. Third, design certification standard guidelines from a long-term perspective so that the standard guidelines for certification do not change significantly, and certify not only the guidelines but also individual standards and forms that can be used by medical institutions. Fourth, in the four-cycle certification, accurate and realistic guidelines for infection control and quarantine ward operation support should be developed. The importance of managing infectious diseases will be highlighted in the future due to COVID-19. Fifth, medical institutions can improve the quality of medical care in nursing hospitals and have competitiveness if their daily activities, not short-term certification preparation, are carried out in accordance with certification standards, which affects performance. Sixth, when preparing for certification, nursing hospital officials have problems in organizing documents or processing administratively in the short term as in the past. This is also based on the certification criteria for the usual business process.