• Title/Summary/Keyword: 학과 분류

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The Study on the Class Difficulty of Elementary Pre-service Teachers' Seasonal Change Unit (초등예비교사의 계절변화 단원에 대한 수업곤란도 연구)

  • Soon-shik Kim
    • Journal of the Korean Society of Earth Science Education
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    • v.16 no.3
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    • pp.340-350
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    • 2023
  • This study analyzed the difficulty level of class on the seasonal change unit for 84 students at a university of education. The conclusions of this study are as follows. First, if we first present the four topics that make up the seasonal changes in elementary science, the subjects that have the greatest difficulty in teaching for prospective elementary school teachers are 'Why do seasonal changes occur?' (Teaching difficulty level 4.05), 'The sun changes depending on the season' What is the difference between the southern altitude and the length of day and night?' (difficulty level of class, 3.12), 'What is the relationship between the altitude of the sun, length of shadow, and temperature during the day?' (difficulty level of class, 2.85), 'How does the temperature change depending on the season?' (class difficulty level 2.80). As a result, in the elementary science season change unit, the class on the four topics 'Why do seasons change?', which is classified as a class topic that requires the concept of spatial perception, showed a higher level of class difficulty than other units. Second, in the seasonal change unit, various factors of class difficulty appeared depending on the class topic. When pre-service elementary school teachers look at the factors that make class difficult when teaching a lesson on seasonal changes in order of frequency, 42 (50%) said 'Experimental instruction for comparing the altitude of solar masculine according to the tilt of the axis of rotation', followed by 'Solar masculine'. 38 people (45%) answered 'Difficulty in explaining mid-high altitude and the length of day and night', 27 people (32%) answered 'Difficulty in explaining the concept of mid-high altitude', and 24 people (32%) answered 'Difficulty in explaining seasonal changes in the sun's position.' 29%), 20 people (24%) said 'Explain the reasonable reason why the height of the light should be adjusted when measuring the solar altitude', and 16 people (19%) said 'It is difficult to explain the reason for the discrepancy between the solar altitude and the maximum temperature'. ), 'difficulties in measuring sand (ground) temperature' were mentioned by 12 people (14%). Third, when analyzing the factors of class difficulty, there were more curriculum factors than teacher factors. In this context, the exploratory activities on 'Why do seasonal changes occur?', the fourth topic of the seasonal change unit in which elementary school pre-service teachers showed the greatest difficulty in teaching, need improvement in terms of the curriculum.

Predicting the Effects of Rooftop Greening and Evaluating CO2 Sequestration in Urban Heat Island Areas Using Satellite Imagery and Machine Learning (위성영상과 머신러닝 활용 도시열섬 지역 옥상녹화 효과 예측과 이산화탄소 흡수량 평가)

  • Minju Kim;Jeong U Park;Juhyeon Park;Jisoo Park;Chang-Uk Hyun
    • Korean Journal of Remote Sensing
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    • v.39 no.5_1
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    • pp.481-493
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    • 2023
  • In high-density urban areas, the urban heat island effect increases urban temperatures, leading to negative impacts such as worsened air pollution, increased cooling energy consumption, and increased greenhouse gas emissions. In urban environments where it is difficult to secure additional green spaces, rooftop greening is an efficient greenhouse gas reduction strategy. In this study, we not only analyzed the current status of the urban heat island effect but also utilized high-resolution satellite data and spatial information to estimate the available rooftop greening area within the study area. We evaluated the mitigation effect of the urban heat island phenomenon and carbon sequestration capacity through temperature predictions resulting from rooftop greening. To achieve this, we utilized WorldView-2 satellite data to classify land cover in the urban heat island areas of Busan city. We developed a prediction model for temperature changes before and after rooftop greening using machine learning techniques. To assess the degree of urban heat island mitigation due to changes in rooftop greening areas, we constructed a temperature change prediction model with temperature as the dependent variable using the random forest technique. In this process, we built a multiple regression model to derive high-resolution land surface temperatures for training data using Google Earth Engine, combining Landsat-8 and Sentinel-2 satellite data. Additionally, we evaluated carbon sequestration based on rooftop greening areas using a carbon absorption capacity per plant. The results of this study suggest that the developed satellite-based urban heat island assessment and temperature change prediction technology using Random Forest models can be applied to urban heat island-vulnerable areas with potential for expansion.

Performance Evaluation of Monitoring System for Sargassum horneri Using GOCI-II: Focusing on the Results of Removing False Detection in the Yellow Sea and East China Sea (GOCI-II 기반 괭생이모자반 모니터링 시스템 성능 평가: 황해 및 동중국해 해역 오탐지 제거 결과를 중심으로)

  • Han-bit Lee;Ju-Eun Kim;Moon-Seon Kim;Dong-Su Kim;Seung-Hwan Min;Tae-Ho Kim
    • Korean Journal of Remote Sensing
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    • v.39 no.6_2
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    • pp.1615-1633
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    • 2023
  • Sargassum horneri is one of the floating algae in the sea, which breeds in large quantities in the Yellow Sea and East China Sea and then flows into the coast of Republic of Korea, causing various problems such as destroying the environment and damaging fish farms. In order to effectively prevent damage and preserve the coastal environment, the development of Sargassum horneri detection algorithms using satellite-based remote sensing technology has been actively developed. However, incorrect detection information causes an increase in the moving distance of ships collecting Sargassum horneri and confusion in the response of related local governments or institutions,so it is very important to minimize false detections when producing Sargassum horneri spatial information. This study applied technology to automatically remove false detection results using the GOCI-II-based Sargassum horneri detection algorithm of the National Ocean Satellite Center (NOSC) of the Korea Hydrographic and Oceanography Agency (KHOA). Based on the results of analyzing the causes of major false detection results, it includes a process of removing linear and sporadic false detections and green algae that occurs in large quantities along the coast of China in spring and summer by considering them as false detections. The technology to automatically remove false detection was applied to the dates when Sargassum horneri occurred from February 24 to June 25, 2022. Visual assessment results were generated using mid-resolution satellite images, qualitative and quantitative evaluations were performed. Linear false detection results were completely removed, and most of the sporadic and green algae false detection results that affected the distribution were removed. Even after the automatic false detection removal process, it was possible to confirm the distribution area of Sargassum horneri compared to the visual assessment results, and the accuracy and precision calculated using the binary classification model averaged 97.73% and 95.4%, respectively. Recall value was very low at 29.03%, which is presumed to be due to the effect of Sargassum horneri movement due to the observation time discrepancy between GOCI-II and mid-resolution satellite images, differences in spatial resolution, location deviation by orthocorrection, and cloud masking. The results of this study's removal of false detections of Sargassum horneri can determine the spatial distribution status in near real-time, but there are limitations in accurately estimating biomass. Therefore, continuous research on upgrading the Sargassum horneri monitoring system must be conducted to use it as data for establishing future Sargassum horneri response plans.

Customer Value Factors Influencing the Continuous Use Intention of Department Store Mobile Apps : Focusing on the Customer of Sinsegae Department Store (백화점 모바일 앱 지속 이용 의도에 영향을 미치는 고객 가치 요인 : 신세계 백화점 이용 고객을 중심으로 )

  • Kim, So-hyun;Choi, Chang-bum
    • Journal of Venture Innovation
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    • v.6 no.4
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    • pp.23-40
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    • 2023
  • This study examines the customer value factors affecting the intention to continue using the mobile app of department stores, which are traditional offline retailers, in the retail industry that is rapidly digitalizing and becoming mobile. This study clarifies multidimensional customer value in three dimensions; functional, convenience, and social. Functional value refers to the integrated channel, and consistent customer experience provided between channels in the omnichannel retail environment, while convenience value is the convenience of saving time and effort save while customers use a mobile app. Social value refers to the improvement of social approval or social self-concept occurring due to the use of products or services related to green marketing within the mobile app of the department store. The influence of each on the dependent variable, the mobile app's continuous use intention, was analyzed by using the three dimensions of customer value as independent variables. Data was collected from customers who have a history of using the mobile app of Shinsegae Department Store in Korea, and a confirmatory analysis was conducted using Smart PLS 4.0. The analysis results showed that all three dimensions of customer value; functional value, convenience value, and social value, had a positive (+) influence on customers' intention to continue using the mobile app, and the influence of functional value had the greatest impact. As functional value appears to be the most important influencing factor due to the omnichannel retail trend by advancement of technology, it suggests that it is important for department stores, and offline retailers, to provide integrated channels. This provides insights into the direction of customer-centered strategy formulation for activating department store mobile apps and suggests basic analytical data for customized services and marketing activities that department stores can effectively meet the changing expectations and demands of customers through new mobile channels rather than existing offline channels.

Building Change Detection Methodology in Urban Area from Single Satellite Image (단일위성영상 기반 도심지 건물변화탐지 방안)

  • Seunghee Kim;Taejung Kim
    • Korean Journal of Remote Sensing
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    • v.39 no.5_4
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    • pp.1097-1109
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    • 2023
  • Urban is an area where small-scale changes to individual buildings occur frequently. An existing urban building database requires periodic updating to increase its usability. However, there are limitations in data collection for building changes over a wide urban. In this study, we check the possibility of detecting building changes and updating a building database by using satellite images that can capture a wide urban region by a single image. For this purpose, building areas in a satellite image are first extracted by projecting 3D coordinates of building corners available in a building database onto the image. Building areas are then divided into roof and facade areas. By comparing textures of the roof areas projected, building changes such as height change or building removal can be detected. New height values are estimated by adjusting building heights until projected roofs align to actual roofs observed in the image. If the projected image appeared in the image while no building is observed, it corresponds to a demolished building. By checking buildings in the original image whose roofs and facades areas are not projected, new buildings are identified. Based on these results, the building database is updated by the three categories of height update, building deletion, or new building creation. This method was tested with a KOMPSAT-3A image over Incheon Metropolitan City and Incheon building database available in public. Building change detection and building database update was carried out. Updated building corners were then projected to another KOMPSAT-3 image. It was confirmed that building areas projected by updated building information agreed with actual buildings in the image very well. Through this study, the possibility of semi-automatic building change detection and building database update based on single satellite image was confirmed. In the future, follow-up research is needed on technology to enhance computational automation of the proposed method.

Genetic Characterization of Antigenic Variant Infectious Bursal Disease Virus (IBDV) in Chickens in Korea

  • Jong-Yeol Park;Ki-Woong Kim;Ke Shang;Sang-Won Kim;Yu-Ri Choi;Cheng-Dong Yu;Ji-Eun Son;Gyeong-Jun Kim;Won-Bin Jeon;In-Hwan Kim;Bai Wei;Min Kang;Hyung-Kwan Jang;Se-Yeoun Cha
    • Korean Journal of Poultry Science
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    • v.50 no.4
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    • pp.231-240
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    • 2023
  • Infectious bursal disease (IBD) is an acute, highly contagious, and immunosuppressive disease in young chickens, and causes considerable economic losses to the poultry industry. More than 30 years ago, an antigenic variant IBDV (avIBDV) was reported in chicken farms in the United States. Recently, a novel avIBDV exhibited clear differences in molecular characteristics compared with previous variant strains. This study investigated the molecular characteristics of recently isolated avIBDV strains in Korea. Strains of avIBDV were confirmed by reverse transcription PCR (RT-PCR) and were propagated in 10-day-old specific-pathogen-free (SPF) embryonated chicken eggs through chorioallantoic membrane (CAM) inoculation. Multiple sequence alignment and phylogenetic analyses of hypervariable regions VP2 gene revealed that the strains originated from two different avIBDV lineages (G2a and G2d). In our results, we confirmed the co-existence and prevalence of avIBDV genogroup G2a and G2d in chicken farms. It is necessary to study the protective efficacy of current vaccines against avIBDVs.

A case study of elementary school mathematics-integrated classes based on AI Big Ideas for fostering AI thinking (인공지능 사고 함양을 위한 인공지능 빅 아이디어 기반 초등학교 수학 융합 수업 사례연구)

  • Chohee Kim;Hyewon Chang
    • The Mathematical Education
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    • v.63 no.2
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    • pp.255-272
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    • 2024
  • This study aims to design mathematics-integrated classes that cultivate artificial intelligence (AI) thinking and to analyze students' AI thinking within these classes. To do this, four classes were designed through the integration of the AI4K12 Initiative's AI Big Ideas with the 2015 revised elementary mathematics curriculum. Implementation of three classes took place with 5th and 6th grade elementary school students. Leveraging the computational thinking taxonomy and the AI thinking components, a comprehensive framework for analyzing of AI thinking was established. Using this framework, analysis of students' AI thinking during these classes was conducted based on classroom discourse and supplementary worksheets. The results of the analysis were peer-reviewed by two researchers. The research findings affirm the potential of mathematics-integrated classes in nurturing students' AI thinking and underscore the viability of AI education for elementary school students. The classes, based on AI Big Ideas, facilitated elementary students' understanding of AI concepts and principles, enhanced their grasp of mathematical content elements, and reinforced mathematical process aspects. Furthermore, through activities that maintain structural consistency with previous problem-solving methods while applying them to new problems, the potential for the transfer of AI thinking was evidenced.

Analysis of Micro-Sedimentary Structure Characteristics Using Ultra-High Resolution UAV Imagery: Hwangdo Tidal Flat, South Korea (초고해상도 무인항공기 영상을 이용한 한국 황도 갯벌의 미세 퇴적 구조 특성 분석)

  • Minju Kim;Won-Kyung Baek;Hoi Soo Jung;Joo-Hyung Ryu
    • Korean Journal of Remote Sensing
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    • v.40 no.3
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    • pp.295-305
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    • 2024
  • This study aims to analyze the micro-sedimentary structures of the Hwangdo tidal flats using ultra-high resolution unmanned aerial vehicle (UAV) data. Tidal flats, located in the transitional area between land and sea, constantly change due to tidal activities and provide a unique environment important for understanding sedimentary processes and environmental conditions. Traditional field observation methods are limited in spatial and temporal coverage, and existing satellite imagery does not provide sufficient resolution to study micro-sedimentary structures. To overcome these limitations, high-resolution images of the Hwangdo tidal flats in Chungcheongnam-do were acquired using UAVs. This area has experienced significant changes in its sedimentary environment due to coastal development projects such as sea wall construction. From May 17 to 18, 2022, sediment samples were collected from 91 points during field surveys and 25 in-situ points were intensively analyzed. UAV data with a spatial resolution of approximately 0.9 mm allowed identifying and extracting parameters related to micro-sedimentary structures. For mud cracks, the length of the major axis of the polygons was extracted, and the wavelength and ripple symmetry index were extracted for ripple marks. The results of the study showed that in areas with mud content above 80%, mud cracks formed at an average major axis length of 37.3 cm. In regions with sand content above 60%, ripples with an average wavelength of 8 cm and a ripple symmetry index of 2.0 were formed. This study demonstrated that micro-sedimentary structures of tidal flats can be effectively analyzed using ultra-high resolution UAV data without field surveys. This highlights the potential of UAV technology as an important tool in environmental monitoring and coastal management and shows its usefulness in the study of sedimentary structures. In addition, the results of this study are expected to serve as baseline data for more accurate sedimentary facies classification.

Usefulness of 18F-FDG PET/CT and Multiphase CT in the Differential Diagnosis of Hepatocellular Carcinoma and Combined Hepatocellular Carcinoma-Cholangiocarcinoma (간세포암종과 혼합성 간세포암종-담관암종에서 다위상 전산단층촬영술 소견과 18F-FDG PET/CT에서 섭취율 차이에 대한 분석 )

  • Jae Chun Park; Jung Gu Park;Gyoo-Sik Jung;Hee Kang;Sungmin Jun
    • Journal of the Korean Society of Radiology
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    • v.81 no.6
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    • pp.1424-1435
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    • 2020
  • Purpose The purpose of this study was to evaluate the usefulness of multiphasic CT and 18F-fluorodeoxyglucose (FDG) PET/CT for the differentiation of combined hepatocellular carcinoma-cholangiocarcinoma (cHCC-CCA) from hepatocellular carcinoma (HCC). Materials and Methods From January 2007 to April 2016, 93 patients with pathologically confirmed HCC (n = 84) or cHCC-CCA (n = 9) underwent CT and PET/CT imaging. Contrast enhancement patterns were divided into three types based on the attenuation of the surrounding liver parenchyma: type I (early arterial enhancement with delayed washout), type II (early arterial enhancement without delayed washout), and type III (early hypovascular, infiltrative appearance, or peripheral rim enhancement). Results cHCC-CCAs (89%) had a higher PET/CT positive rate than did HCCs (61%), but the PET/CT positive rate did not differ significantly (p = 0.095). Among the 19 cases of the type II enhancement pattern, 3 (21%) of 14 HCCs and 4 (80%) of 5 cHCC-CCAs were PET/CT positive. cHCC-CCAs had a significantly higher PET/CT positive rate (p = 0.020) in the type II enhancement pattern. Conclusion The PET/CT positive rate of cHCC-CCA was significantly higher than that of HCC in lesions with a type II enhancement pattern. The 18F-FDG PET/CT can be useful for the differentiation of cHCC-CCA from HCC in lesions with a type II enhancement pattern on multiphasic CT.

A Study of the Influencing Factors for Decision Making on Construction Contract Types : Focused on DoD Construction Acquisitions with Firm Fixed Price and Cost Reimbursable in FAR (건설공사 대가지급방식의 의사결정 영향요인에 관한 연구 - 미국 연방조달규정에 따른 미국 국방성의 정액계약과 실비정산계약을 중심으로 -)

  • Son, Young-Hoon;Kim, Kyung-Rai
    • Korean Journal of Construction Engineering and Management
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    • v.25 no.2
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    • pp.23-35
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    • 2024
  • This study analyzed the correlation between each of the 12 influencing factors in FAR 16.04 and the decision-making process for construction contract types, using data from a total of 2,406 DoD Construction Acquisitions spanning from 2008 to 2022. The study considered 12 independent variables, grouped into 4 Characteristics with 3 factors each. Meanwhile, all other contract types were categorized into two types: Firm-Fixed-Price (FFP) and Cost-Reimbursement Contract (CRC), which served as the dependent variables. The findings revealed that FFP contracts significantly dominated in terms of acquisition volume. In line with prevailing beliefs, logistic data analysis and Analytical Hierarchy Process (AHP) analysis of Relative Weights from Experts' Survey demonstrated that independent variables like Uncertainty of the Scope of Work and Complexity found out to be increasing the likelihood of selecting CRC. The number of contractors in the market does indeed influence the possibilities of contract decision-making between CRC and FFP. Meanwhile, the p-values of the top 3 influencing factors on CRC from the AHP analysis-namely, Appropriateness of CAS, Project Urgency, and Cost Analysis-exceeded 0.05 in the binominal regression results, rendering it inconclusive whether they significantly influenced the construction contract type decision, particularly with respect to payment methods. This outcome partly results from the fact that a majority of respondents possessed specific experiences related to the USFK relocation project. Furthermore, influencing factors in construction projects behave differently than common beliefs suggest. As a result, it is imperative to consider the 12 influencing factors categorized into 4 Characteristics areas before establishing acquisition strategies for targeted construction projects.