• Journal of the Society of Cosmetic Scientists of Korea
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• v.45 no.3
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• pp.217-224
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• 2019

Phthalates, endocrine disrupting chemicals, are similar in structure to sex hormones and mainly show reproductive toxicity and developmental toxicity. In this study, we analyzed 11 phthalates, including 3 kinds of phthalates prohibited in cosmetic use and 8 kinds of phthalates regulated in 'Common standards for children's products safety' and EU cosmetic regulation (EC No. 1223/2009). The phthalate analysis was optimized using GC-MS/MS. In analytical method validation, this method was satisfied in specificity, linearity, recovery rate, accuracy and MQL. Therefore, we used this method to analyze 82 products of Nail cosmetics & polish. Although six phthalates such as DBP, BBP, DEHP, DPP, DIBP and DIDP were detected at concentrations of $1.0{\sim}59.8{\mu}g/g$g, they were suitable to Korean cosmetic standards. DIBP and DBP were detected at concentration of $1.1{\sim}2.6{\mu}g/g$ in artificial nail, DBP and DEHP were $1.4{\sim}2.5{\mu}g/g$ in glue for nails, and DIBP, DBP, and DEHP were $2.5{\sim}33.3{\mu}g/g$ in nail stickers. Although substances such as DBP and DEHP in artificial nail, Glue for nails, and nail stickers were detected, they were suitable to 'Common safety standards for children's products. DIBP is not a regulated substance in Korea but showed the third highest detection rate following DBP (84.6%) and DEHP (63.4%). The concentration of phthalates detected in nail products is considered to be safe in current standards but continuous monitoring and research about non-regulated substances are also needed to be considered.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.3
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• pp.82-98
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• 2019

The importance of spatial information is rapidly rising. In particular, 3D spatial information construction and modeling for Real World Objects, such as smart cities and digital twins, has become an important core technology. The constructed 3D spatial information is used in various fields such as land management, landscape analysis, environment and welfare service. Three-dimensional modeling with image has the hig visibility and reality of objects by generating texturing. However, some texturing might have occlusion area inevitably generated due to physical deposits such as roadside trees, adjacent objects, vehicles, banners, etc. at the time of acquiring image Such occlusion area is a major cause of the deterioration of reality and accuracy of the constructed 3D modeling. Various studies have been conducted to solve the occlusion area. Recently the researches of deep learning algorithm have been conducted for detecting and resolving the occlusion area. For deep learning algorithm, sufficient training data is required, and the collected training data quality directly affects the performance and the result of the deep learning. Therefore, this study analyzed the ability of detecting the occlusion area of the image using various image quality to verify the performance and the result of deep learning according to the quality of the learning data. An image containing an object that causes occlusion is generated for each artificial and quantified image quality and applied to the implemented deep learning algorithm. The study found that the image quality for adjusting brightness was lower at 0.56 detection ratio for brighter images and that the image quality for pixel size and artificial noise control decreased rapidly from images adjusted from the main image to the middle level. In the F-measure performance evaluation method, the change in noise-controlled image resolution was the highest at 0.53 points. The ability to detect occlusion zones by image quality will be used as a valuable criterion for actual application of deep learning in the future. In the acquiring image, it is expected to contribute a lot to the practical application of deep learning by providing a certain level of image acquisition.

• The Korean Journal of Nuclear Medicine Technology
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• v.23 no.2
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• pp.29-37
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• 2019

Purpose DMIDR(Discovery Molecular Imaging Digital Ready, General Electric Healthcare, USA) is a PET/CT scanner designed to allow application of PSF(Point Spread Function), TOF(Time of Flight) and Q.Clear algorithm. Especially, Q.Clear is a reconstruction algorithm which can overcome the limitation of OSEM(Ordered Subset Expectation Maximization) and reduce the image noise based on voxel unit. The aim of this paper is to evaluate the performance of reconstruction algorithms and optimize the algorithm combination to improve the accurate SUV(Standardized Uptake Value) measurement and lesion detectability. Materials and Methods PET phantom was filled with $^{18}F-FDG$ radioactivity concentration ratio of hot to background was in a ratio of 2:1, 4:1 and 8:1. Scan was performed using the NEMA protocols. Scan data was reconstructed using combination of (1)VPFX(VUE point FX(TOF)), (2)VPHD-S(VUE Point HD+PSF), (3)VPFX-S (TOF+PSF), (4)QCHD-S-400((VUE Point HD+Q.Clear(${\beta}-strength$ 400)+PSF), (5)QCFX-S-400(TOF +Q.Clear(${\beta}-strength$ 400)+PSF), (6)QCHD-S-50(VUE Point HD+Q.Clear(${\beta}-strength$ 50)+PSF) and (7)QCFX-S-50(TOF+Q.Clear(${\beta}-strength$ 50)+PSF). CR(Contrast Recovery) and BV(Background Variability) were compared. Also, SNR(Signal to Noise Ratio) and RC(Recovery Coefficient) of counts and SUV were compared respectively. Results VPFX-S showed the highest CR value in sphere size of 10 and 13 mm, and QCFX-S-50 showed the highest value in spheres greater than 17 mm. In comparison of BV and SNR, QCFX-S-400 and QCHD-S-400 showed good results. The results of SUV measurement were proportional to the H/B ratio. RC for SUV is in inverse proportion to the H/B ratio and QCFX-S-50 showed highest value. In addition, reconstruction algorithm of Q.Clear using 400 of ${\beta}-strength$ showed lower value. Conclusion When higher ${\beta}-strength$ was applied Q.Clear showed better image quality by reducing the noise. On the contrary, lower ${\beta}-strength$ was applied Q.Clear showed that sharpness increase and PVE(Partial Volume Effect) decrease, so it is possible to measure SUV based on high RC comparing to conventional reconstruction conditions. An appropriate choice of these reconstruction algorithm can improve the accuracy and lesion detectability. In this reason, it is necessary to optimize the algorithm parameter according to the purpose.

• The Journal of Korean Academy of Prosthodontics
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• v.57 no.3
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• pp.203-210
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• 2019

Purpose: The purpose of this study was to verify the effect of the abutment superimposition process on the final virtual model in the scanning process of single and 3-units bridge model using a dental model scanner. Materials and methods: A gypsum model for single and 3-unit bridges was manufactured for evaluating. And working casts with removable dies were made using Pindex system. A dental model scanner (3Shape E1 scanner) was used to obtain CAD reference model (CRM) and CAD test model (CTM). The CRM was scanned without removing after dividing the abutments in the working cast. Then, CTM was scanned with separated from the divided abutments and superimposed on the CRM (n=20). Finally, three-dimensional analysis software (Geomagic control X) was used to analyze the root mean square (RMS) and Mann-Whitney U test was used for statistical analysis (${\alpha}=.05$). Results: The RMS mean abutment for single full crown preparation was $10.93{\mu}m$ and the RMS average abutment for 3 unit bridge preparation was $6.9{\mu}m$. The RMS mean of the two groups showed statistically significant differences (P<.001). In addition, errors of positive and negative of two groups averaged $9.83{\mu}m$, $-6.79{\mu}m$ and 3-units bridge abutment $6.22{\mu}m$, $-3.3{\mu}m$, respectively. The mean values of the errors of positive and negative of two groups were all statistically significantly lower in 3-unit bridge abutments (P<.001). Conclusion: Although the number of abutments increased during the scan process of the working cast with removable dies, the error due to the superimposition of abutments did not increase. There was also a significantly higher error in single abutments, but within the range of clinically acceptable scan accuracy.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.43-61
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• 2019

Development of technologies in artificial intelligence has been rapidly increasing with the Fourth Industrial Revolution, and researches related to AI have been actively conducted in a variety of fields such as autonomous vehicles, natural language processing, and robotics. These researches have been focused on solving cognitive problems such as learning and problem solving related to human intelligence from the 1950s. The field of artificial intelligence has achieved more technological advance than ever, due to recent interest in technology and research on various algorithms. The knowledge-based system is a sub-domain of artificial intelligence, and it aims to enable artificial intelligence agents to make decisions by using machine-readable and processible knowledge constructed from complex and informal human knowledge and rules in various fields. A knowledge base is used to optimize information collection, organization, and retrieval, and recently it is used with statistical artificial intelligence such as machine learning. Recently, the purpose of the knowledge base is to express, publish, and share knowledge on the web by describing and connecting web resources such as pages and data. These knowledge bases are used for intelligent processing in various fields of artificial intelligence such as question answering system of the smart speaker. However, building a useful knowledge base is a time-consuming task and still requires a lot of effort of the experts. In recent years, many kinds of research and technologies of knowledge based artificial intelligence use DBpedia that is one of the biggest knowledge base aiming to extract structured content from the various information of Wikipedia. DBpedia contains various information extracted from Wikipedia such as a title, categories, and links, but the most useful knowledge is from infobox of Wikipedia that presents a summary of some unifying aspect created by users. These knowledge are created by the mapping rule between infobox structures and DBpedia ontology schema defined in DBpedia Extraction Framework. In this way, DBpedia can expect high reliability in terms of accuracy of knowledge by using the method of generating knowledge from semi-structured infobox data created by users. However, since only about 50% of all wiki pages contain infobox in Korean Wikipedia, DBpedia has limitations in term of knowledge scalability. This paper proposes a method to extract knowledge from text documents according to the ontology schema using machine learning. In order to demonstrate the appropriateness of this method, we explain a knowledge extraction model according to the DBpedia ontology schema by learning Wikipedia infoboxes. Our knowledge extraction model consists of three steps, document classification as ontology classes, proper sentence classification to extract triples, and value selection and transformation into RDF triple structure. The structure of Wikipedia infobox are defined as infobox templates that provide standardized information across related articles, and DBpedia ontology schema can be mapped these infobox templates. Based on these mapping relations, we classify the input document according to infobox categories which means ontology classes. After determining the classification of the input document, we classify the appropriate sentence according to attributes belonging to the classification. Finally, we extract knowledge from sentences that are classified as appropriate, and we convert knowledge into a form of triples. In order to train models, we generated training data set from Wikipedia dump using a method to add BIO tags to sentences, so we trained about 200 classes and about 2,500 relations for extracting knowledge. Furthermore, we evaluated comparative experiments of CRF and Bi-LSTM-CRF for the knowledge extraction process. Through this proposed process, it is possible to utilize structured knowledge by extracting knowledge according to the ontology schema from text documents. In addition, this methodology can significantly reduce the effort of the experts to construct instances according to the ontology schema.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.45 no.1
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• pp.69-75
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• 2019

Preservatives of cosmetics is managed by positive list in Korea. Positive list requires a proper quantitative analysis method, but the analysis method is still insufficient. In this study, gas chromatography with flame ionization detector was used to simultaneously analyze 14 preservatives in cosmetics. As a result of method validation, the specificity was confirmed by the calibration curves of 14 preservatives showing good linearity correlation coefficient of above 0.9997 except dehydroacetic acid (0.9891). The limits of detection (LOD) and quantification (LOQ) of 14 preservatives were 0.0001 mg/mL ~ 0.0039 mg/mL and 0.0003 mg/mL ~ 0.0118 mg/mL, respectively, but they were 0.0204 mg/mL, 0.0617 mg/mL for dehydroacetic acid, respectively. The precision (Repeatability) of the values was less than 1.0%, but 7.1% for dehydroacetic acid. The Accuracy (% recovery) of 14 preservatives in cosmetics showed 96.9% ~ 109.2%. Finally, this method was applied to 50 cosmetics available in market. Results showed that the commonly used preservatives were chlorophene, phenoxyethanol, benzyl alcohol and parabens. However, the amount of the detected preservatives was within maximum allowed limits established by KFDA.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.36 no.4
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• pp.94-104
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• 2018

This study examined photogrammetric reconstruction techniques that can measure the original form of a cultural property utilizing photographs taken in the past. During the research process, photographs taken in the past as well as photograph on the internet of Soswaewon Garden in Damyang(scenic site 40) were collected and utilized. The landscaping structures of Maedae, Aiyangdan, Ogokmun Wall, and Yakjak and natural scenery Gwangseok, of which photographs can be taken from any 360 degree direction from a close distance or a far distance without any barriers in the way, were selected and tested for the possibility of reproducing three-dimensional shapes. The photography method of 151 landscape photographs (58.6%) from internet portal sites for the aforementioned five landscape subjects containing information on the date the photograph was taken, focal length, and exposure were analyzed. As a result of the analysis, it was revealed that the majority of the photographs tend to focus on important parts of each subject. In addition, we discovered that there are two or three photography methods that internet users preferred in regards to each landscape subject. For the purposes of the experiment, photographs in which a single scene consistently appears for each landscape subject and it was determined that there was a high level of preference related to the photography method were analyzed, and three-dimensional mesh shape model was produced with a photoscan program to analyze the reproducibility of three-dimensional shapes. Based on the results of the reproduction, it was relatively possible to reproduce three-dimensional shapes for artifacts such as Ogukmun wall, Maedae, and Aeyangdan, but it was impossible to reproduce three-dimensional images for natural scenery or an object that has similar texture such as Yakjak and Gwangseok. As a result of experimentation related to the reconstruction of three-dimensional shapes with the photographs taken on site using a photography method similar to that of the photographs selected as previously mentioned, there was success related to reproducing the three-dimensional shapes of Yakjak and Gwangseok, of which it was not possible to do so through the photographs that had been collected previously. In addition, through comparison of past and present images, it was possible to measure the exact sizes as well as discover any changes that have taken place. If past photographs taken by tourists or landscape architects of cultural properties can be obtained, the three-dimensional shapes from a particular period of time can be reproduced. If this technology becomes widespread, it will increase the level of accuracy and reliability in regards to measuring the past shapes of cultural landscape properties and examining any changes to the properties.

• Korean Journal of Remote Sensing
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• v.35 no.3
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• pp.415-431
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• 2019

The satellite-viewed cloudiness, a ratio of cloudy pixels to total pixels ($C_{sat,\;prev}$), inevitably differs from the "ground-viewed" cloudiness ($C_{grd}$) due to different viewpoints. Here we develop an algorithm to retrieve the satellite-viewed, but adjusted cloudiness to $C_{grd} (C_{sat,\;adj})$. The key process of the algorithm is to convert the cloudiness projected on the plane surface into the cloudiness on the celestial hemisphere from the observer. For this conversion, the supplementary satellite retrievals such as cloud detection and cloud top pressure are used as they provide locations of cloudy pixels and cloud base height information, respectively. The algorithm is tested for Himawari-8 level 1B data. The $C_{sat,\;adj}$ and $C_{sat,\;prev}$ are retrieved and validated with $C_{grd}$ of SYNOP station over Korea (22 stations) and China (724 stations) during only daytime for the first seven days of every month from July 2016 to June 2017. As results, the mean error of $C_{sat,\;adj}$ (0.61) is less that than that of $C_{sat,\;prev}$ (1.01). The percent of detection for 'Cloudy' scenario of $C_{sat,\;adj}$ (73%) is higher than that of $C_{sat,\;prev}$ (60%) The percent of correction, the accuracy, of $C_{sat,\;adj}$ is 61%, while that of $C_{sat,\;prev}$ is 55% for all seasons. For the December-January-February period when cloudy pixels are readily overestimated, the proportion of correction of $C_{sat,\;adj$ is 60%, while that of $C_{sat,\;prev}$ is 56%. Therefore, we conclude that the present algorithm can effectively get the satellite cloudiness near to the ground-viewed cloudiness.

• Journal of Wetlands Research
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• v.21 no.2
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• pp.163-172
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• 2019

The USLE P factor is a factor that varies depending on how croplands are managed and cultivated. Previous studies tend to overestimate the amount of soil loss because the factor was estimated from the slope of the watershed rather than the estimate of each cultivated land. In addition, the accuracy of estimating the soil loss is decreasing due to the fact that the factor is calculated without considering various conditions of cultivated land defined by Wishmeier and Smith. In order to overcome these problems, the Ministry of Environment (MOE) has proposed to establish the topsoil notification and calculate the P factor according to the cultivation methods (e.g., tillage system, support practice). However, it is required to apply the conditions proposed in the United States to domestic circumstances as it is causing uncertainties. Thus, this study selected the watersheds where soil loss was serious (Haean, Jaun, Banbyeoncheon), measured the actual slopes and slope lengths, and examined the crop, tillage systems, and support practice for each cultivated land. The P factors were recalculated considering the actual conditions of cultivated land and compared to the factors proposed by the previous studies (MOE). As the result of the study, the P factors calculated based on the previous studies were 0.8 ~ 1.0 in three watersheds. On the other hand, it is confirmed that there is a significant difference between the factors notified by MOE and estimated by reflecting the topography and cultivation methods in this study. Therefore, it is considered that the research for developing the cultivation conditions to calculate the P factor suitable for the domestic environment should be continuously carried out.

• Korean Journal of Clinical Laboratory Science
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• v.51 no.2
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• pp.191-197
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• 2019

Although auto-adjusting positive airway pressure (APAP) titration at home has several advantages over a CPAP titration in terms of convenience and time saving, there are still concerns as to whether it will show corresponding accuracy when compared to laboratory-based polysomnography (PSG) and CPAP titration. To obtain more evidence supporting home-based auto-titration, APAP titration was performed at home for patients who were presented with OSA on laboratory-based diagnostic PSG followed by CPAP titration. A total of 79 patients were included in the study. They all underwent split-night PSG with CPAP titration, and APAP titration for more than 7 days. The patients with successful titration at both situations were selected. The optimal pressure and apnea-hypopnea index (AHI) of CPAP and APAP titration were compared. The optimal pressure for CPAP and APAP titration were $7.0{\pm}1.8cmH_2O$ and $7.6{\pm}1.6cmH_2O$ (P<0.001), whereas the corresponding AHI were $1.3{\pm}1.5/h$ and $3.0{\pm}1.7/h$ (P<0.001). As a result, the achievement rates of optimal pressure for CPAP and APAP titration were 96.2% and 94.9% (r=-0.045, P=0.688), respectively. The results of this study did not differ with regard to the optimal pressure between CPAP and APAP titration. Overall, CPAP and APAP titrations should be chosen depending on a required situation.