• Korean Journal of Remote Sensing
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• v.24 no.2
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• pp.205-211
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• 2008

The river management in Korea had been focused on line based 2D spatial data for the developing river management application system. In this study, the polygon based 3D spatial data such as aerial photos and satellite images were selected and used through comparing their resolution levels for the river environment management. In addition, 1m detailed DEM (Digital Elevation Model) was constructed to implement the real topography information around river so that the damage area scale could be extracted for flood disaster. Also, the social environment thematic maps such as a cadastral map or land cover map could be used to verify the real damage area scale by overlay analysis on aerial photos or satellite images. The construction of these spatial data makes possible to present the real surface information and extract quantitative analysis to support the scientific decision making for establishing the river management policy. For the further study, the lidar surveying data will be considered as the very useful data by offering the real height information of riverbed as the depth of river so that flood simulation can give more reality.

• Journal of The Korean Astronomical Society
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• v.54 no.6
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• pp.171-182
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• 2021

The lack of short baselines, referred to as the short-spacing problem (SSP), is a well-known limitation of the performance of radio interferometers, causing a reduction of the flux detected from source structure on large angular scales. The very large number of antennas operated in the Atacama Large Millimeter/sub-millimeter Array (ALMA) generates situations for which the impact of the SSP takes a complex form, not simply measurable by a single number, such as the maximal recoverable scale. In particular, extended antenna configurations, complemented by a small group of closeby antennas at the centre of the array, may result in a double-humped baseline distribution with a significant gap between the two groups. In such cases one should adopt as the effective maximal recoverable scale the one associated with the extended array and use only the central array to recover missing flux, as one would do with single dish or ACA (Atacama Compact Array) observations. The impact of the missing baselines can be very important and may easily be underestimated, or even overlooked. The present study uses ALMA archival data of the ²⁹SiO(8-7) line emission of the AGB star W Hydrae for a demonstration. A critical discussion of the reliability of the observations away from the star is presented together with comments of a broader scope. Properties of the circumstellar envelope of W Hya within ~15 au from the star, many of which are not mentioned in the published literature, are briefly described and compared with R Doradus, an AGB star having properties very similar to W Hya.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.5
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• pp.209-213
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• 2021

For the human body shape information, body measurement techniques using a tape measure or image analysis are used. However, there is a demand for a method with high measurement accuracy and reproducibility while being simple. In this paper, domestic and foreign patent research related to body size measurement technology was conducted to identify the development trend of the related technology. WISDOMAIN DB was used to search for patents published in Korea, the United States, Japan, and Europe, and valid patents were derived by defining the technical scope of major and medium classifications and sub-categories. For the derived patents, patent trends by year, major applicants by country, and the status of technological fields were analyzed. In the field of body size measurement technology, the proportion of patent applications filed in Korea is high, indicating that Korea is leading the patent application in this field. Although the number of patent applications in the field of sensor-type measurement technology was not large, it has an advantage in measurement simplicity, so the development of related technology is expected to contribute to the improvement of measurement accuracy related to body composition analysis.

• Fashion & Textile Research Journal
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• v.20 no.6
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• pp.656-668
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• 2018

The main object of this study was to understand the body image and body management behavior associated with desiring a thinner and more muscular body. The present study examined whether the drives for thinness and muscularity occur concurrently for both male and female college students, and whether there are gender differences. Moreover, the effects of objectified body consciousness on drive for thinness and drive for muscularity were investigated. A self-administered survey was conducted and a total of 390 data were used for data analysis. Participants included 197 male college students and 193 female students. Results indicated that male students reported significantly lower drive for thinness and higher drive for muscularity than female students. However, the drives for thinness and muscularity were significantly correlated for both male and female college students, and they reported discrepancies between their BMI and self-perceived weight and muscle mass. Findings supported the significant effects of objected body consciousness on the drives for thinness and muscularity for both male and females. Sub-dimensions of objectified body consciousness had differential effects on drive for thinness and muscularity. Specifically, body surveillance and body shame significantly influenced male and female students' drive for thinness, while their control belief did not have significant effects on their drive for thinness. Additionally, body shame emerged as significant unique predictor of drive for muscularity. In terms of gender comparisons, while the effect of body shame was the strongest for the males, the effect of surveillance was as strong as that of body shame for the females.

• Journal of Digital Convergence
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• v.17 no.7
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• pp.317-329
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• 2019

Instagram, a photo and image centered social networking service, has received increasing attention these days, from scholars and practitioners. However, little is known about the social and psychological factors that lead consumers to use this service. To provide a baseline understanding on Instagram users, the current study was conducted to discover perfectionistic self-presentation tendency expressed by the Instagram users and explore the relationships between identified perfectionistic self-presentation and intention to use Instagram variables with 250 participants. In addition, this study tried to determine the moderator effect of self-efficacy and self-construal. A comprehensive survey was directed and a total of 380 participants were recruited to verify anticipated hypotheses and research questions. The research results suggest that perfectionistic self-presentation has five sub factors: others conscious self-presentation, subjective self-presentation, environmental adaptation self-presentation, self-expansion self-presentation, and social self-presentation. The implications of this research findings are discussed.

• Journal of Korean Elementary Science Education
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• v.38 no.3
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• pp.406-425
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• 2019

The purpose of this study is to analyze The Effect of Teacher Participation-oriented Education Program (TPEP) centered on Multi-Faceted Analysis of Elementary Science Classes on the Class Expertise of novice teacher. First, in order to develop the TPEP, lectures and exploratory science classes were analyzed using imaging and eye-tracking techniques. In this study, the TPEP was developed in five stages: image analysis, eye analysis, teaching language analysis, gesture analysis, and class development. Participants directly analyzed the classes of experienced and novice teachers at each stage. The TPEP developed in this study is different from the existing teacher education program in that it reflected the human performance technology aspects. The participants analyzed actual elementary science classes in a multi-faceted way and developed better classes based on them. The results of this study are as follows. First, at the teacher training institutions and the school sites, pre-service teachers and novice teachers should be provided with various experiences in class analysis and multi-faceted analysis of their own classes. Second, through this study, we were able to identify the limitations of existing class observations and video analysis. Third, the TPEP should be developed to improve the novice teachers' class expertise. Finally, we hope that the results of this study are used as basic data in developing programs to improve teachers' class expertise in teacher training institutions and education policy institutions.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.5
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• pp.205-212
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• 2019

Scene graph is a kind of knowledge graph that represents both objects and their relationships found in a image. This paper proposes a 3D scene graph generation model for three-dimensional indoor environments. An 3D scene graph includes not only object types, their positions and attributes, but also three-dimensional spatial relationships between them, An 3D scene graph can be viewed as a prior knowledge base describing the given environment within that the agent will be deployed later. Therefore, 3D scene graphs can be used in many useful applications, such as visual question answering (VQA) and service robots. This proposed 3D scene graph generation model consists of four sub-networks: object detection network (ObjNet), attribute prediction network (AttNet), transfer network (TransNet), relationship prediction network (RelNet). Conducting several experiments with 3D simulated indoor environments provided by AI2-THOR, we confirmed that the proposed model shows high performance.

• Investigative Magnetic Resonance Imaging
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• v.25 no.2
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• pp.118-128
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• 2021

Purpose: To investigate the value of MR textural analysis, including use of diffusion-weighted imaging (DWI) to differentiate malignant from benign soft-tissue tumors on 3T MRI. Materials and Methods: We enrolled 69 patients (25 men, 44 women, ages 18 to 84 years) with pathologically confirmed soft-tissue tumors (29 benign, 40 malignant) who underwent pre-treatment 3T-MRI. We calculated MR texture, including mean, standard deviation (SD), skewness, kurtosis, mean of positive pixels (MPP), and entropy, according to different spatial-scale factors (SSF, 0, 2, 4, 6) on axial T1- and T2-weighted images (T1WI, T2WI), contrast-enhanced T1WI (CE-T1WI), high b-value DWI (800 sec/mm²), and apparent diffusion coefficient (ADC) map. We used the Mann-Whitney U test, logistic regression, and area under the receiver operating characteristic curve (AUC) for statistical analysis. Results: Malignant soft-tissue tumors had significantly lower mean values of DWI, ADC, T2WI and CE-T1WI, MPP of ADC, and CE-T1WI, but significantly higher kurtosis of DWI, T1WI, and CE-T1WI, and entropy of DWI, ADC, and T2WI than did benign tumors (P < 0.050). In multivariate logistic regression, the mean ADC value (SSF, 6) and kurtosis of CE-T1WI (SSF, 4) were independently associated with malignancy (P ≤ 0.009). A multivariate model of MR features worked well for diagnosis of malignant soft-tissue tumors (AUC, 0.909). Conclusion: Accurate diagnosis could be obtained using MR textural analysis with DWI and CE-T1WI in differentiating benign from malignant soft-tissue tumors.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.4
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• pp.93-106
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• 2020

This research explores how imported automobile companies can develop their strategies to improve the outcome of their recalls. For this, the researchers analyzed patterns of recall demand, classified recall types based on the demand patterns and examined response strategies, considering plans on how to procure parts and induce customers to visit workshops, recall execution capacity and costs. As a result, recalls are classified into four types: U-type, reverse U-type, L- type and reverse L-type. Also, as determinants of the types, the following factors are further categorized into four types and 12 sub-types of recalls: the height of maximum demand, which indicates the volatility of recall demand; the number of peaks, which are the patterns of demand variations; and the tail length of the demand curve, which indicates the speed of recalls. The classification resulted in the following: L-type, or customer-driven recall, is the most common type of recalls, taking up 25 out of the total 36 cases, followed by five U-type, four reverse L-type, and two reverse U-type cases. Prior studies show that the types of recalls are determined by factors influencing recall execution rates: severity, the number of cars to be recalled, recall execution rate, government policies, time since model launch, and recall costs, etc. As a component demand forecast model for automobile recalls, this study estimated the ARIMA model. ARIMA models were shown in three models: ARIMA (1,0,0), ARIMA (0,0,1) and ARIMA (0,0,0). These all three ARIMA models appear to be significant for all recall patterns, indicating that the ARIMA model is very valid as a predictive model for car recall patterns. Based on the classification of recall types, we drew some strategic implications for recall response according to types of recalls. The conclusion section of this research suggests the implications for several aspects: how to improve the recall outcome (execution rate), customer satisfaction, brand image, recall costs, and response to the regulatory authority.

• Nuclear Engineering and Technology
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• v.54 no.8
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• pp.3006-3016
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• 2022

In this study, the images of specific prompt gamma (PG)-rays of 719 keV emitted from proton-boron reactions were analyzed using single-photon emission computed tomography (SPECT). Quantitative evaluation of the images verified the detection of anatomical changes in tumors, one of the important factors in daily adaptive proton therapy (DAPT) and verified the possibility of application of the PG-ray images to DAPT. Six scenarios were considered based on various sizes and locations compared to the reference virtual tumor to observe the anatomical alterations in the virtual tumor. Subsequently, PG-rays SPECT images were acquired using the modified ordered subset expectation-maximization algorithm, and these were evaluated using quantitative analysis methods. The results confirmed that the pixel range and location of the highest value of the normalized pixel in the PG-rays SPECT image profile changed according to the size and location of the virtual tumor. Moreover, the alterations in the virtual tumor size and location in the PG-rays SPECT images were similar to the true size and location alterations set in the phantom. Based on the above results, the tumor anatomical alterations in DAPT could be adequately detected and verified through SPECT imaging using the 719 keV PG-rays acquired during treatment.