• Title/Summary/Keyword: 인공지능서비스

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Generation of Stage Tour Contents with Deep Learning Style Transfer (딥러닝 스타일 전이 기반의 무대 탐방 콘텐츠 생성 기법)

  • Kim, Dong-Min;Kim, Hyeon-Sik;Bong, Dae-Hyeon;Choi, Jong-Yun;Jeong, Jin-Woo
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.24 no.11
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    • pp.1403-1410
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    • 2020
  • Recently, as interest in non-face-to-face experiences and services increases, the demand for web video contents that can be easily consumed using mobile devices such as smartphones or tablets is rapidly increasing. To cope with these requirements, in this paper we propose a technique to efficiently produce video contents that can provide experience of visiting famous places (i.e., stage tour) in animation or movies. To this end, an image dataset was established by collecting images of stage areas using Google Maps and Google Street View APIs. Afterwards, a deep learning-based style transfer method to apply the unique style of animation videos to the collected street view images and generate the video contents from the style-transferred images was presented. Finally, we showed that the proposed method could produce more interesting stage-tour video contents through various experiments.

AI Advisor for Response of Disaster Safety in Risk Society (위험사회 재난 안전 분야 대응을 위한 AI 조력자)

  • Lee, Yong-Hak;Kang, Yunhee;Lee, Min-Ho;Park, Seong-Ho;Kang, Myung-Ju
    • Journal of Platform Technology
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    • v.8 no.3
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    • pp.22-29
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    • 2020
  • The 4th industrial revolution is progressing by country as a mega trend that leads various technological convergence directions in the social and economic fields from the initial simple manufacturing innovation. The epidemic of infectious diseases such as COVID-19 is shifting digital-centered non-face-to-face business from economic operation, and the use of AI and big data technology for personalized services is essential to spread online. In this paper, we analyze cases focusing on the application of artificial intelligence technology, which is a key technology for the effective implementation of the digital new deal promoted by the government, as well as the major technological characteristics of the 4th industrial revolution and describe the use cases in the field of disaster response. As a disaster response use case, AI assistants suggest appropriate countermeasures according to the status of the reporter in an emergency call. To this end, AI assistants provide speech recognition data-based analysis and disaster classification of converted text for adaptive response.

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Considerations for Applying SDN to Embedded Device Security (임베디드 디바이스 보안을 위한 SDN 적용 시 고려사항)

  • Koo, GeumSeo;Sim, Gabsig
    • The Journal of the Korea Contents Association
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    • v.21 no.6
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    • pp.51-61
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    • 2021
  • In the era of the 4th industrial revolution symbolized by the Internet of Things, big data and artificial intelligence, various embedded devices are increasing exponentially. These devices have communication functions despite their low specifications, so the possibility of personal information leakage is increasing, and security threats are also increasing. Embedded devices can have security issues at most levels, from hardware to services over the network. In addition, it is difficult to apply general security techniques because it has characteristics of resource constraints such as low specifications and low power, and the related technology has not been standardized. In this study, we present vulnerabilities and possible problems and considerations in applying SDN to embedded devices in consideration of structural characteristics and real-world discovered cases. This study presents vulnerabilities and possible problems and considerations when applying SDN to embedded devices. From a hardware perspective, we consider the problems of Wi-Fi chips and Bluetooth, the problems of open flow implementation, SDN controllers, and examples of structural properties. SDN separates the data plane and the control plane, and provides a standardized interface between the two, enabling efficient communication control. It can respond to the security limitations of existing network technologies that are difficult to respond to rapid changes.

The Influence of Learning Commitment and Interest by Repetitive Education Activities of Adult Learners on Satisfaction in Online Learning Using Flip Learning Pedagogy (플립러닝을 활용한 온라인 학습에서 중·장년층 학습자의 반복학습에 따른 학습몰입과 흥미가 학습만족도에 미치는 영향)

  • Kang, Tae-Gu;Lim, Gu-Won
    • Journal of Industrial Convergence
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    • v.19 no.3
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    • pp.27-34
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    • 2021
  • In the era of the 4th industrial revolution, the age of artificial intelligence, the development of ICT technology is having various effects on the online and offline educational environment. The universal access of online education changes the educational paradigm and converts it to a learner-centered service. At the time when a new educational environment is required to change, interest in flip learning is increasing. Even adult learner's online learning needs is also shown very high. The purpose of this study was to investigate how repetitive learning activities through flip learning for middle-aged online learners of K-Cyber University has a relationship and structural relationship between the effects of learning immersion and learning interest on learning satisfaction. Through this study, there is significance in research to suggest direction for learning satisfaction based on flip learning. For further studies, if a model of analysis of various factors that can be measured is specified and applied, it can be used as a research background that can maximize learning satisfaction based on flip learning.

A Decentralized Face Mask Distribution System Based on the Decentralized Identity Management (블록체인 분산신원증명에 기반한 탈중앙화된 마스크 중복구매 확인 시스템)

  • Noh, Siwan;Jang, Seolah;Rhee, Kyung-Hyune
    • KIPS Transactions on Computer and Communication Systems
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    • v.9 no.12
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    • pp.315-320
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    • 2020
  • Identity authentication is an important technology that has long been used in society to identify individuals and provide appropriate services. With the development of the Internet infrastructure, many areas have expanded into online areas, and identity authentication technologies have also expanded online. However, there is still a limit to identity authentication technology that relies entirely on trusted third parties like the government. A centralized identity management system makes the identification process between agencies with different identity management systems very complex, resulting in a waste of money and time for users. In particular, the limits of the centralized identity management system were clearly revealed in the face mask shortage in the 2020 COVID-19 crisis. A Decentralized Identity (DID) is a way for users to manage their identity on their own, and recently, a number of DID platform based on blockchain technology have been proposed. In this paper, we analyze the limitations of the existing centralized identity management system and propose a DID system that can be utilized in future national emergency situations such as COVID-19.

Detection The Behavior of Smartphone Users using Time-division Feature Fusion Convolutional Neural Network (시분할 특징 융합 합성곱 신경망을 이용한 스마트폰 사용자의 행동 검출)

  • Shin, Hyun-Jun;Kwak, Nae-Jung;Song, Teuk-Seob
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.24 no.9
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    • pp.1224-1230
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    • 2020
  • Since the spread of smart phones, interest in wearable devices has increased and diversified, and is closely related to the lives of users, and has been used as a method for providing personalized services. In this paper, we propose a method to detect the user's behavior by applying information from a 3-axis acceleration sensor and a 3-axis gyro sensor embedded in a smartphone to a convolutional neural network. Human behavior differs according to the size and range of motion, starting and ending time, including the duration of the signal data constituting the motion. Therefore, there is a performance problem for accuracy when applied to a convolutional neural network as it is. Therefore, we proposed a Time-Division Feature Fusion Convolutional Neural Network (TDFFCNN) that learns the characteristics of the sensor data segmented over time. The proposed method outperformed other classifiers such as SVM, IBk, convolutional neural network, and long-term memory circulatory neural network.

Text Mining of Online News, Social Media, and Consumer Review on Artificial Intelligence Service (인공지능 서비스에 대한 온라인뉴스, 소셜미디어, 소비자리뷰 텍스트마이닝)

  • Li, Xu;Lim, Hyewon;Yeo, Harim;Hwang, Hyesun
    • Human Ecology Research
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    • v.59 no.1
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    • pp.23-43
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    • 2021
  • This study looked through the text mining analysis to check the status of the virtual assistant service, and explore the needs of consumers, and present consumer-oriented directions. Trendup 4.0 was used to analyze the keywords of AI services in Online News and social media from 2016 to 2020. The R program was used to collect consumer comment data and implement Topic Modeling analysis. According to the analysis, the number of mentions of AI services in mass media and social media has steadily increased. The Sentimental Analysis showed consumers were feeling positive about AI services in terms of useful and convenient functional and emotional aspects such as pleasure and interest. However, consumers were also experiencing complexity and difficulty with AI services and had concerns and fears about the use of AI services in the early stages of their introduction. The results of the consumer review analysis showed that there were topics(Technical Requirements) related to technology and the access process for the AI services to be provided, and topics (Consumer Request) expressed negative feelings about AI services, and topics(Consumer Life Support Area) about specific functions in the use of AI services. Text mining analysis enable this study to confirm consumer expectations or concerns about AI service, and to examine areas of service support that consumers experienced. The review data on each platform also revealed that the potential needs of consumers could be met by expanding the scope of support services and applying platform-specific strengths to provide differentiated services.

Analysis of the Ripple Effect of the US Federal Reserve System's Quantitative Easing Policy on Stock Price Fluctuations (미국연방준비제도의 양적완화 정책이 주가 변동에 미치는 영향 분석)

  • Hong, Sunghyuck
    • Journal of Digital Convergence
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    • v.19 no.3
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    • pp.161-166
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    • 2021
  • The macroeconomic concept represents the movement of a country's economy, and it affects the overall economic activities of business, government, and households. In the macroeconomy, by looking at changes in national income, inflation, unemployment, currency, interest rates, and raw materials, it is possible to understand the effects of economic actors' actions and interactions on the prices of products and services. The US Federal Reserve System (FED) is leading the world economy by offering various stimulus measures to overcome the corona economic recession. Although the stock price continued to decline on March 20, 2020 due to the current economic recession caused by the corona, the US S&P 500 index began rebounding after March 23 and to 3,694.62 as of December 15 due to quantitative easing, a powerful stimulus for the FED. Therefore, the FED's economic stimulus measures based on macroeconomic indicators are more influencing, rather than judging the stock price forecast from the corporate financial statements. Therefore, this study was conducted to reduce losses in stock investment and establish sound investment by analyzing the FED's economic stimulus measures and its effect on stock prices.

A Study on Analysis of Pilates-related Patent Information (필라테스 분야 특허 정보 분석에 관한 연구)

  • Chi, Dong-Cheol;Kim, Jong-Hyuck
    • Journal of the Korea Convergence Society
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    • v.13 no.4
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    • pp.513-519
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    • 2022
  • The 4th industrial revolution has made our life convenient, and the development of new technologies has brought affluent life. Considering that the 4th industrial revolution is a next-generation industrial revolution led by robot technology, life science, and artificial intelligence, the need for convergence research in sports field stimulated the continuous efforts for the academic foundation of sports. Recently, as interest in home training has increased due to the COVID-19 pandemic, the Pilates has also attracted much attentions demand for related supplies has increased. This is an demonstration that COVID-19 has had an impact on the sports industry ecosystem. The purpose of this study was, accordingly, to identify current trends through accurate patent information related to Pilates and to provide basic data for future studies on sports convergence industry and sports intellectual property. For the purpose, based on the data from Jan. 1 to Dec. 31, 2021 provided by KIPRIS (www.kipris.or.kr), the patent information search service provided by the Korean Intellectual Property Office, patent status analysis, international patent classification (IPC) patent analysis, and detailed patent analysis by classification were performed.

Design and Implementation of a Food Price Information Analysis System Based on Public Big Data (공공 빅데이터 기반의 식품 가격 정보 분석 시스템의 설계 및 구현)

  • Lim, Jongtae;Lee, Hyeonbyeong;Bok, Kyoungsoo;Yoo, Jaesoo
    • The Journal of the Korea Contents Association
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    • v.22 no.7
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    • pp.10-17
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    • 2022
  • Recently, with the issue of the 4th Industrial Revolution, many services using big data have been developed. Accordingly, studies have been conducting to utilize public data, which is considered as the most valuable data among big data. In this paper, we design and implement a food price information analysis system based on public big data. The proposed system analyzes the collected food price-related data in various forms from various sources and classifies them according to characteristics. In addition, the proposed system analyzes the factors affecting the price of food through big data analysis techniques and uses them as data to predict the price of food in the near future. Finally, the proposed system provides the user with the analyzed results through data visualization.