• Title/Summary/Keyword: interest development

Search Result 4,440, Processing Time 0.027 seconds

The Perception Analysis of Autonomous Vehicles using Network Graph (네트워크 그래프를 활용한 자율주행차에 대한 인식 분석)

  • Hyo-gyeong Park;Yeon-hwi You;Sung-jung Yong;Seo-young Lee;Il-young Moon
    • Journal of Practical Engineering Education
    • /
    • v.15 no.1
    • /
    • pp.97-105
    • /
    • 2023
  • Recently, with the development of artificial intelligence technology, many technologies for user convenience are being developed. Among them, interest in autonomous vehicles is increasing day by day. Currently, many automobile companies are aiming to commercialize autonomous vehicles. In order to lay the foundation for the government's new and reasonable policy establishment to support commercialization, we tried to analyze changes and perceptions of public opinion through news article data. Therefore, in this paper, 35,891 news article data mentioning terms similar to 'autonomous vehicles' over the past three years were collected and network analyzed. As a result of the analysis, major keywords such as 'autonomous driving', 'AI', 'future', 'Hyundai Motor', 'autonomous driving vehicle', 'automobile', 'industrial', and 'electric vehicle' were derived. In addition, the autonomous vehicle industry is developing into a faster and more diverse platform and service industry by converging with various industries such as semiconductor companies and big tech companies as well as automobile companies and is paying attention to the convergence of industries. To continuously confirm changes and perceptions in public opinion, it is necessary to analyze perceptions through continuous analysis of SNS data or technology trends.

Development and Application of Statistical Programs Based on Data and Artificial Intelligence Prediction Model to Improve Statistical Literacy of Elementary School Students (초등학생의 통계적 소양 신장을 위한 데이터와 인공지능 예측모델 기반의 통계프로그램 개발 및 적용)

  • Kim, Yunha;Chang, Hyewon
    • Communications of Mathematical Education
    • /
    • v.37 no.4
    • /
    • pp.717-736
    • /
    • 2023
  • The purpose of this study is to develop a statistical program using data and artificial intelligence prediction models and apply it to one class in the sixth grade of elementary school to see if it is effective in improving students' statistical literacy. Based on the analysis of problems in today's elementary school statistical education, a total of 15 sessions of the program was developed to encourage elementary students to experience the entire process of statistical problem solving and to make correct predictions by incorporating data, the core in the era of the Fourth Industrial Revolution into AI education. The biggest features of this program are the recognition of the importance of data, which are the key elements of artificial intelligence education, and the collection and analysis activities that take into account context using real-life data provided by public data platforms. In addition, since it consists of activities to predict the future based on data by using engineering tools such as entry and easy statistics, and creating an artificial intelligence prediction model, it is composed of a program focused on the ability to develop communication skills, information processing capabilities, and critical thinking skills. As a result of applying this program, not only did the program positively affect the statistical literacy of elementary school students, but we also observed students' interest, critical inquiry, and mathematical communication in the entire process of statistical problem solving.

A Study on the Relationship between Motivation and Community Satisfaction of Audience for Non-profit Performing Arts (지역사회 비영리 공연 관람객의 관람동기와 지역사회만족도 간의 관계)

  • Jongeun Jwa;Seolwoo Park
    • Journal of Service Research and Studies
    • /
    • v.13 no.4
    • /
    • pp.47-69
    • /
    • 2023
  • The main purpose of this study is to examine the mediating effects of performance satisfaction and audience loyalty through the motivation and community satisfaction of non-profit performance attendees in the local community. Motivations were examined by distinguishing between intrinsic and extrinsic factors to understand the profound desires of the audience. A survey was conducted targeting attendees who had experienced non-profit performances in the Jeju area over the past year to gather data. Ultimately, the survey responses from 363 participants were used as the basis for analysis. The results of the analysis indicated that higher levels of intrinsic and extrinsic motivations generally led to greater satisfaction and loyalty towards performances (H1, H2, H3). However, extrinsic motivation did not directly influence loyalty (H4). Nevertheless, both types of motivations were found to positively influence loyalty through performance satisfaction (H5, H8). While satisfaction with performances did not have a direct impact on community satisfaction (H6), audience loyalty was found to have a positive influence on community satisfaction (H7). Regarding motivations, performance satisfaction did not mediate the relationship between motivations and community satisfaction (H9). In the case of audience loyalty, intrinsic motivation showed mediating effects, while extrinsic motivation did not (H10). The process of motivation-satisfaction-loyalty-community satisfaction demonstrated a sequential pathway (H11). In conclusion, if local residents show interest and participate in non-profit performances, they develop a positive perception of the respective community. Therefore, performances provided at the local level should be recognized as crucial elements for the development of the community.

An Experiment for Surface Soil Moisture Mapping Using Sentinel-1 and Sentinel-2 Image on Google Earth Engine (Google Earth Engine 제공 Sentinel-1과 Sentinel-2 영상을 이용한 지표 토양수분도 제작 실험)

  • Jihyun Lee ;Kwangseob Kim;Kiwon Lee
    • Korean Journal of Remote Sensing
    • /
    • v.39 no.5_1
    • /
    • pp.599-608
    • /
    • 2023
  • The increasing interest in soil moisture data using satellite data for applications of hydrology, meteorology, and agriculture has led to the development of methods for generating soil moisture maps of variable resolution. This study demonstrated the capability of generating soil moisture maps using Sentinel-1 and Sentinel-2 data provided by Google Earth Engine (GEE). The soil moisture map was derived using synthetic aperture radar (SAR) image and optical image. SAR data provided by the Sentinel-1 analysis ready data in GEE was applied with normalized difference vegetation index (NDVI) based on Sentinel-2 and Environmental Systems Research Institute (ESRI)-based Land Cover map. This study produced a soil moisture map in the research area of Victoria, Australia and compared it with field measurements obtained from a previous study. As for the validation of the applied method's result accuracy, the comparative experimental results showed a meaningful range of consistency as 4-10%p between the values obtained using the algorithm applied in this study and the field-based ones, and they also showed very high consistency with satellite-based soil moisture data as 0.5-2%p. Therefore, public open data provided by GEE and the algorithm applied in this study can be used for high-resolution soil moisture mapping to represent regional land surface characteristics.

Soil Moisture Estimation Using KOMPSAT-3 and KOMPSAT-5 SAR Images and Its Validation: A Case Study of Western Area in Jeju Island (KOMPSAT-3와 KOMPSAT-5 SAR 영상을 이용한 토양수분 산정과 결과 검증: 제주 서부지역 사례 연구)

  • Jihyun Lee;Hayoung Lee;Kwangseob Kim;Kiwon Lee
    • Korean Journal of Remote Sensing
    • /
    • v.39 no.6_1
    • /
    • pp.1185-1193
    • /
    • 2023
  • The increasing interest in soil moisture data from satellite imagery for applications in hydrology, meteorology, and agriculture has led to the development of methods to produce variable-resolution soil moisture maps. Research on accurate soil moisture estimation using satellite imagery is essential for remote sensing applications. The purpose of this study is to generate a soil moisture estimation map for a test area using KOMPSAT-3/3A and KOMPSAT-5 SAR imagery and to quantitatively compare the results with soil moisture data from the Soil Moisture Active Passive (SMAP) mission provided by NASA, with a focus on accuracy validation. In addition, the Korean Environmental Geographic Information Service (EGIS) land cover map was used to determine soil moisture, especially in agricultural and forested regions. The selected test area for this study is the western part of Jeju, South Korea, where input data were available for the soil moisture estimation algorithm based on the Water Cloud Model (WCM). Synthetic Aperture Radar (SAR) imagery from KOMPSAT-5 HV and Sentinel-1 VV were used for soil moisture estimation, while vegetation indices were calculated from the surface reflectance of KOMPSAT-3 imagery. Comparison of the derived soil moisture results with SMAP (L-3) and SMAP (L-4) data by differencing showed a mean difference of 4.13±3.60 p% and 14.24±2.10 p%, respectively, indicating a level of agreement. This research suggests the potential for producing highly accurate and precise soil moisture maps using future South Korean satellite imagery and publicly available data sources, as demonstrated in this study.

An Accelerated Approach to Dose Distribution Calculation in Inverse Treatment Planning for Brachytherapy (근접 치료에서 역방향 치료 계획의 선량분포 계산 가속화 방법)

  • Byungdu Jo
    • Journal of the Korean Society of Radiology
    • /
    • v.17 no.5
    • /
    • pp.633-640
    • /
    • 2023
  • With the recent development of static and dynamic modulated brachytherapy methods in brachytherapy, which use radiation shielding to modulate the dose distribution to deliver the dose, the amount of parameters and data required for dose calculation in inverse treatment planning and treatment plan optimization algorithms suitable for new directional beam intensity modulated brachytherapy is increasing. Although intensity-modulated brachytherapy enables accurate dose delivery of radiation, the increased amount of parameters and data increases the elapsed time required for dose calculation. In this study, a GPU-based CUDA-accelerated dose calculation algorithm was constructed to reduce the increase in dose calculation elapsed time. The acceleration of the calculation process was achieved by parallelizing the calculation of the system matrix of the volume of interest and the dose calculation. The developed algorithms were all performed in the same computing environment with an Intel (3.7 GHz, 6-core) CPU and a single NVIDIA GTX 1080ti graphics card, and the dose calculation time was evaluated by measuring only the dose calculation time, excluding the additional time required for loading data from disk and preprocessing operations. The results showed that the accelerated algorithm reduced the dose calculation time by about 30 times compared to the CPU-only calculation. The accelerated dose calculation algorithm can be expected to speed up treatment planning when new treatment plans need to be created to account for daily variations in applicator movement, such as in adaptive radiotherapy, or when dose calculation needs to account for changing parameters, such as in dynamically modulated brachytherapy.

Scale Development of Family Strength for Dual-Earner Families with Children (자녀가 있는 맞벌이가정의 건강성 척도 개발 연구)

  • Song, Hyerim;Koh, Sun-Kang;Kang, Eunju
    • Journal of Family Resource Management and Policy Review
    • /
    • v.27 no.3
    • /
    • pp.1-19
    • /
    • 2023
  • This study aims to develop a family strength scale for dual-earner families with young children. Based on existing theories of family strength and a review of related literature, we draw on 80 items to measure the strength of dual-earner families. Using a sample of 747 people, all members of dual-earner families with young children, we examined the items' factor structures. Using the statistical method, we checked the validity and reliability of these items. The final scale consisted of four domains with a total of 49 items : basic foundation (basic structure, economic life, and resource management), parenting, social interest and participation (citizenship, volunteer, leisure, network), work-life balance (balance between work and family, sharing the family role, equal division of role). The developed scale can be used in the field, such as in the Healthy Family Support Center or Family Center, in the context of education, counseling, or consulting for dual-earner families. In order to enhance the usefulness and efficiency of the scale, the adequate education system for the professionals who handle this scale in the field and updated data are required.

A Conjoint Analysis on the Preference Analysis of the Han River Skyline Focus on the Apgujeong Apartment District in the Han River Embankments, Seoul (컨조인트 분석(Conjoint analysis)을 이용한 한강 변 스카이라인 형태 선호도 분석 연구 - 한강 변 압구정 아파트지구를 중심으로 -)

  • Kang, Song-Hee;Jang, Chang-Hee;Lee, Jae-Seung
    • Journal of Cadastre & Land InformatiX
    • /
    • v.53 no.2
    • /
    • pp.79-92
    • /
    • 2023
  • With a growing interest in the Han River Skyline, which greatly influences Seoul's image, careful consideration of the skyline form has become crucial in the redevelopment plans for apartment complexes along the Han River. The Seoul Metropolitan City government has lifted the height limitations for apartments along the Hang River to cultivate a vibrant skyline. However, traditional skyline analysis often overlooks specific attributes, limiting the provision of precise guidelines for Seoul's unique skyline plans. Despite advancements in Digital Twin technology, only some tools effectively manage urban skylines with preferred shapes. Hence, this study aims to make a substantial contribution to the advancement of a Digital Twin 3D modeling program capable of effectively managing urban skylines. This is achieved through the utilisation of Conjoint Analysis, which assesses the importance of each attribute in determining the preferred skyline shape. Focusing on Apgujeong apartment complexes along the Han River currently undergoing redevelopment or planned for redevelopment, the study analyses the preferred skyline shape to propose standards for the Digital Twin 3D modeling program development. It also suggests that Conjoint Analysis can be beneficial in this process.

Analysis of major issues in the field of Maritime Autonomous Surface Ships using text mining: focusing on S.Korea news data (텍스트 마이닝을 활용한 자율운항선박 분야 주요 이슈 분석 : 국내 뉴스 데이터를 중심으로)

  • Hyeyeong Lee;Jin Sick Kim;Byung Soo Gu;Moon Ju Nam;Kook Jin Jang;Sung Won Han;Joo Yeoun Lee;Myoung Sug Chung
    • Journal of the Korean Society of Systems Engineering
    • /
    • v.20 no.spc1
    • /
    • pp.12-29
    • /
    • 2024
  • The purpose of this study is to identify the social issues discussed in Korea regarding Maritime Autonomous Surface Ships (MASS), the most advanced ICT field in the shipbuilding industry, and to suggest policy implications. In recent years, it has become important to reflect social issues of public interest in the policymaking process. For this reason, an increasing number of studies use media data and social media to identify public opinion. In this study, we collected 2,843 domestic media articles related to MASS from 2017 to 2022, when MASS was officially discussed at the International Maritime Organization, and analyzed them using text mining techniques. Through term frequency-inverse document frequency (TF-IDF) analysis, major keywords such as 'shipbuilding,' 'shipping,' 'US,' and 'HD Hyundai' were derived. For LDA topic modeling, we selected eight topics with the highest coherence score (-2.2) and analyzed the main news for each topic. According to the combined analysis of five years, the topics '1. Technology integration of the shipbuilding industry' and '3. Shipping industry in the post-COVID-19 era' received the most media attention, each accounting for 16%. Conversely, the topic '5. MASS pilotage areas' received the least media attention, accounting for 8 percent. Based on the results of the study, the implications for policy, society, and international security are as follows. First, from a policy perspective, the government should consider the current situation of each industry sector and introduce MASS in stages and carefully, as they will affect the shipbuilding, port, and shipping industries, and a radical introduction may cause various adverse effects. Second, from a social perspective, while the positive aspects of MASS are often reported, there are also negative issues such as cybersecurity issues and the loss of seafarer jobs, which require institutional development and strategic commercialization timing. Third, from a security perspective, MASS are expected to change the paradigm of future maritime warfare, and South Korea is promoting the construction of a maritime unmanned system-based power, but it emphasizes the need for a clear plan and military leadership to secure and develop the technology. This study has academic and policy implications by shedding light on the multidimensional political and social issues of MASS through news data analysis, and suggesting implications from national, regional, strategic, and security perspectives beyond legal and institutional discussions.

An Investigation Into the Effects of AI-Based Chemistry I Class Using Classification Models (분류 모델을 활용한 AI 기반 화학 I 수업의 효과에 대한 연구)

  • Heesun Yang;Seonghyeok Ahn;Seung-Hyun Kim;Seong-Joo Kang
    • Journal of the Korean Chemical Society
    • /
    • v.68 no.3
    • /
    • pp.160-175
    • /
    • 2024
  • The purpose of this study is to examine the effects of a Chemistry I class based on an artificial intelligence (AI) classification model. To achieve this, the research investigated the development and application of a class utilizing an AI classification model in Chemistry I classes conducted at D High School in Gyeongbuk during the first semester of 2023. After selecting the curriculum content and AI tools, and determining the curriculum-AI integration education model as well as AI hardware and software, we developed detailed activities for the program and applied them in actual classes. Following the implementation of the classes, it was confirmed that students' self-efficacy improved in three aspects: chemistry concept formation, AI value perception, and AI-based maker competency. Specifically, the chemistry classes based on text and image classification models had a positive impact on students' self-efficacy for chemistry concept formation, enhanced students' perception of AI value and interest, and contributed to improving students' AI and physical computing abilities. These results demonstrate the positive impact of the Chemistry I class based on an AI classification model on students, providing evidence of its utility in educational settings.