• Title/Summary/Keyword: Information Platform

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Analysis of Effects of Convergence Education Program about State Classification of the Matters using Machine Learning for Pre-service Teachers (예비교사를 위한 머신러닝 활용 물질의 상태 분류에 대한 융합교육 프로그램의 효과 분석)

  • Yi, Soyul;Lee, YoungJun;Paik, Sung-Hey
    • Journal of Convergence for Information Technology
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    • v.12 no.5
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    • pp.139-149
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    • 2022
  • The purpose of this study is to develop and analyze the effects of an educational program that can cultivate artificial intelligence(AI) convergence education competency for future education and enhance students' understanding of pre-service teachers. For this end, an AI convergence education program using Machine Learning for Kids and Scratch 3 was developed for 15 weeks under the theme of classifying the state of matter. The developed program were treated by K University pre-service teachers who participated voluntarily. As a result, pre-service teachers were able to metaphorically understand the learning process of students through understanding of machine learning training process. In addition, the pre-post t-test result of AI teaching efficacy showed a statistically significant improvement with t=-7.137 (p<.000). Therefore, it is suggested that the AI convergence education program developed in this study can help to increase the understanding of the pre-service teacher's students in an indirect way other than practice teaching, and can contribute to foster AI education competency.

Card Transaction Data-based Deep Tourism Recommendation Study (카드 데이터 기반 심층 관광 추천 연구)

  • Hong, Minsung;Kim, Taekyung;Chung, Namho
    • Knowledge Management Research
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    • v.23 no.2
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    • pp.277-299
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    • 2022
  • The massive card transaction data generated in the tourism industry has become an important resource that implies tourist consumption behaviors and patterns. Based on the transaction data, developing a smart service system becomes one of major goals in both tourism businesses and knowledge management system developer communities. However, the lack of rating scores, which is the basis of traditional recommendation techniques, makes it hard for system designers to evaluate a learning process. In addition, other auxiliary factors such as temporal, spatial, and demographic information are needed to increase the performance of a recommendation system; but, gathering those are not easy in the card transaction context. In this paper, we introduce CTDDTR, a novel approach using card transaction data to recommend tourism services. It consists of two main components: i) Temporal preference Embedding (TE) represents tourist groups and services into vectors through Doc2Vec. And ii) Deep tourism Recommendation (DR) integrates the vectors and the auxiliary factors from a tourism RDF (resource description framework) through MLP (multi-layer perceptron) to provide services to tourist groups. In addition, we adopt RFM analysis from the field of knowledge management to generate explicit feedback (i.e., rating scores) used in the DR part. To evaluate CTDDTR, the card transactions data that happened over eight years on Jeju island is used. Experimental results demonstrate that the proposed method is more positive in effectiveness and efficacies.

A Comparative Study on the Social Awareness of Metaverse in Korea and China: Using Big Data Analysis (한국과 중국의 메타버스에 관한 사회적 인식의 비교연구: 빅데이터 분석의 활용 )

  • Ki-youn Kim
    • Journal of Internet Computing and Services
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    • v.24 no.1
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    • pp.71-86
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    • 2023
  • The purpose of this exploratory study is to compare the differences in public perceptual characteristics of Korean and Chinese societies regarding the metaverse using big data analysis. Due to the environmental impact of the COVID-19 pandemic, technological progress, and the expansion of new consumer bases such as generation Z and Alpha, the world's interest in the metaverse is drawing attention, and related academic studies have been also in full swing from 2021. In particular, Korea and China have emerged as major leading countries in the metaverse industry. It is a timely research question to discover the difference in social awareness using big data accumulated in both countries at a time when the amount of mentions on the metaverse has skyrocketed. The analysis technique identifies the importance of key words by analyzing word frequency, N-gram, and TF-IDF of clean data through text mining analysis, and analyzes the density and centrality of semantic networks to determine the strength of connection between words and their semantic relevance. Python 3.9 Anaconda data science platform 3 and Textom 6 versions were used, and UCINET 6.759 analysis and visualization were performed for semantic network analysis and structural CONCOR analysis. As a result, four blocks, each of which are similar word groups, were driven. These blocks represent different perspectives that reflect the types of social perceptions of the metaverse in both countries. Studies on the metaverse are increasing, but studies on comparative research approaches between countries from a cross-cultural aspect have not yet been conducted. At this point, as a preceding study, this study will be able to provide theoretical grounds and meaningful insights to future studies.

Threat Situation Determination System Through AWS-Based Behavior and Object Recognition (AWS 기반 행위와 객체 인식을 통한 위협 상황 판단 시스템)

  • Ye-Young Kim;Su-Hyun Jeong;So-Hyun Park;Young-Ho Park
    • KIPS Transactions on Software and Data Engineering
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    • v.12 no.4
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    • pp.189-198
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    • 2023
  • As crimes frequently occur on the street, the spread of CCTV is increasing. However, due to the shortcomings of passively operated CCTV, the need for intelligent CCTV is attracting attention. Due to the heavy system of such intelligent CCTV, high-performance devices are required, which has a problem in that it is expensive to replace the general CCTV. To solve this problem, an intelligent CCTV system that recognizes low-quality images and operates even on devices with low performance is required. Therefore, this paper proposes a Saying CCTV system that can detect threats in real time by using the AWS cloud platform to lighten the system and convert images into text. Based on the data extracted using YOLO v4 and OpenPose, it is implemented to determine the risk object, threat behavior, and threat situation, and calculate the risk using machine learning. Through this, the system can be operated anytime and anywhere as long as the network is connected, and the system can be used even with devices with minimal performance for video shooting and image upload. Furthermore, it is possible to quickly prevent crime by automating meaningful statistics on crime by analyzing the video and using the data stored as text.

The Effects of Hotel Visitors' Cultural Characteristics on Hotel Selection Attributes: Focusing on the Hofstede Cultural Dimension (호텔 방문객들의 문화적 특성이 호텔 선택속성에 끼치는 영향: Hofstede 문화차원을 중심으로)

  • Jaewon Jang;Byunghyun Lee;Jaekyeong Kim
    • Knowledge Management Research
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    • v.24 no.1
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    • pp.99-126
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    • 2023
  • As cultural background contributes members of society to recognize and behave in a specific direction, customers with different cultural backgrounds show various reactions even when they are provided with the same service. Previous studies have used the Hofstede cultural dimension to understand how hotel visitors' satisfaction varies with the provided service as per their cultural background. However existing research only considered the cultural background of the guests, and there are not many studies focused on the types of travel. Therefore, in this study, the travel types of hotel visitors are classified into business travel visitors and leisure tourism visitors, and analyzed the effect of Hofstede's cultural dimension on hotel selection attributes according to the styles of travel. In this study, we collected information on six cultural dimensions of Hofstede, and from TripAdvisor, a representative tourism platform, 204,261 optional attribute ratings for hotels in New York to investigate the satisfaction of hotel selection attributes. In conclusion, it is expected that this study will be able to identify which service attributes the customers of various cultures who visit hotels put emphasis in advance, and therefore provide suitable service accordingly.

A Study on Strategic Approaches Plans for Industrial Revitalization and Overseas Export of Smart City Technology (스마트도시 기술의 산업 활성화와 해외수출을 위한 전략적 접근 방안에 관한 연구)

  • Kim, Dae Ill;Kim, Jeong Hyeon;Yeom, Chun Ho
    • Smart Media Journal
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    • v.11 no.1
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    • pp.67-80
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    • 2022
  • Smart City Technology, which is significant in the era of the 4th industrial revolution, greatly increases the efficiency and productivity of cities nowadays. The purpose of this study is to present a strategic approach for industrial revitalization and overseas export by analyzing the current status of smart city-related companies and discovering high-priority smart city technologies. To this end, the smart city theory and ASEAN smart city were reviewed through prior research, and a survey of companies with domestic smart city technology was conducted. As a result of the survey, it is revealed that companies with smart city technology in Korea are highly willing to export to ASEAN countries. There is a strong desire to export the following technologies: construction, traffic, green·energy, etc. And there was a high willingness to export the following services: IoT, platform, AI, etc. The following solutions have been proposed as solutions to Strategic Plans to Promote the Export: 1) Deregulation and incentives, 2) Global human resource development, 3) Information provision and strengthening of local networks, 4) Financial and public relations support.

Experience Design Guideline for Smart Car Interface (스마트카의 인터페이스를 위한 경험 디자인 가이드라인)

  • Yoo, Hoon Sik;Ju, Da Young
    • Design Convergence Study
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    • v.15 no.1
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    • pp.135-150
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    • 2016
  • Due to the development of communication technology and expansion of Intelligent Transport System (ITS), the car is changing from a simple mechanical device to second living space which has comprehensive convenience function and is evolved into the platform which is playing as an interface for this role. As the interface area to provide various information to the passenger is being expanded, the research importance about smart car based user experience is rising. This study has a research objective to propose the guidelines regarding the smart car user experience elements. In order to conduct this study, smart car user experience elements were defined as function, interaction, and surface and through the discussions of UX/UI experts, 8 representative techniques, 14 representative techniques, and 8 locations of the glass windows were specified for each element. Following, the smart car users' priorities of the experience elements, which were defined through targeting 100 drivers, were analyzed in the form of questionnaire survey. The analysis showed that the users' priorities in applying the main techniques were in the order of safety, distance, and sensibility. The priorities of the production method were in the order of voice recognition, touch, gesture, physical button, and eye tracking. Furthermore, regarding the glass window locations, users prioritized the front of the driver's seat to the back. According to the demographic analysis on gender, there were no significant differences except for two functions. Therefore this showed that the guidelines of male and female can be commonly applied. Through user requirement analysis about individual elements, this study provides the guides about the requirement in each element to be applied to commercialized product with priority.

Oil Spill Monitoring in Norilsk, Russia Using Google Earth Engine and Sentinel-2 Data (Google Earth Engine과 Sentinel-2 위성자료를 이용한 러시아 노릴스크 지역의 기름 유출 모니터링)

  • Minju Kim;Chang-Uk Hyun
    • Korean Journal of Remote Sensing
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    • v.39 no.3
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    • pp.311-323
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    • 2023
  • Oil spill accidents can cause various environmental issues, so it is important to quickly assess the extent and changes in the area and location of the spilled oil. In the case of oil spill detection using satellite imagery, it is possible to detect a wide range of oil spill areas by utilizing the information collected from various sensors equipped on the satellite. Previous studies have analyzed the reflectance of oil at specific wavelengths and have developed an oil spill index using bands within the specific wavelength ranges. When analyzing multiple images before and after an oil spill for monitoring purposes, a significant amount of time and computing resources are consumed due to the large volume of data. By utilizing Google Earth Engine, which allows for the analysis of large volumes of satellite imagery through a web browser, it is possible to efficiently detect oil spills. In this study, we evaluated the applicability of four types of oil spill indices in the area of various land cover using Sentinel-2 MultiSpectral Instrument data and the cloud-based Google Earth Engine platform. We assessed the separability of oil spill areas by comparing the index values for different land covers. The results of this study demonstrated the efficient utilization of Google Earth Engine in oil spill detection research and indicated that the use of oil spill index B ((B3+B4)/B2) and oil spill index C (R: B3/B2, G: (B3+B4)/B2, B: (B6+B7)/B5) can contribute to effective oil spill monitoring in other regions with complex land covers.

Development of Task Planning System for Intelligent Excavating System Applying Heuristics (휴리스틱스(Heuristics)를 활용한 지능형 굴삭 시스템의 Task Planning System 개발)

  • Lee, Seung-Soo;Kim, Jeong-Hwan;Kang, Sang-Hyeok;Seo, Jong-Won
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.28 no.6D
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    • pp.859-869
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    • 2008
  • These days, almost every industry's production line has become automatic and this phenomenon brought a lot of benefits such as increase in productivity and economical effect, assurance in industrial safety, better quality and compatibility. However, unlike industrial production line, in construction industry, automation has number of barriers like uncertainty incidents and intellectual judgment to make ability to make solution out of it. Therefore construction industry is still demanding use of construction machine through labor. Due to this matter operational labor in construction industry is aging and fading. To solve these problem, in developed nations like Europe, US or Japan are keep researching for the automation in construction and road pavement, strengthening and some other simple operations have been worked through automation but in civil engineering site, automation research is still low despite of its importance in constructional site. For automating civil engineering operation, effective operational plan have to be set by analyzing ground information acquainted. If skillful worker apply heuristics, trial & error can be reduced with increased safety and the effective work plan can be established. Hence, this research will introduce Intellectual Task Planning System for Intelligent Excavating System's effective work plan and heuristics applied in each steps.

Effect of Social Network Service (SNS) Users' Object Relations Factors on User Satisfaction through Pleasure and Self-efficacy (소셜네트워크서비스(SNS) 이용자의 대상관계 요인이 즐거움과 자기효능감을 통해 이용자 만족에 미치는 영향)

  • Chae, Su-in;Choi, Hyo-geun;Kwon, Do-Soon;Park, Dong-cheol
    • Journal of Convergence for Information Technology
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    • v.12 no.2
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    • pp.1-16
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    • 2022
  • Social network service (SNS) using mobile or web is growing rapidly, and the emergence of various platform services is causing innovative changes in social network service (SNS). This study is to identify the target relation factors of social network users and to empirically study the causal relationship of how much these factors affect user satisfaction through pleasure and self-efficacy. To present an effective and efficient development plan in. In order to empirically verify the research model of this study, a survey was conducted with the general public who had experience using social network services (SNS). Path analysis was performed. As a result, it was possible to verify the correlation of the object relational factors on user satisfaction through pleasure and self-efficacy.First, non-excluded had a significant effect on pleasure, but did not significantly affect self-efficacy. Second, stability attachment did not significantly affect both enjoyment and self-efficacy. Third, social ability did not significantly affect both enjoyment and self-efficacy. Fourth, self-centeredness did not have a significant effect on both enjoyment and self-efficacy. Fifth, pleasure had a significant effect on both self-efficacy and user satisfaction. Sixth, self-efficacy had a significant effect on user satisfaction.