• Title/Summary/Keyword: 모바일 AI

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A Study on Analysis and Improvement of Contents of Domestic Disaster & Safety Education (국내 재난안전교육 컨텐츠 분석 및 개선방안 연구)

  • Chung, Hee-Soo;Song, Chang-Geun
    • Journal of Convergence for Information Technology
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    • v.12 no.1
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    • pp.76-82
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    • 2022
  • Recently, natural and social disasters in Korea are increasing, and new disasters such as COVID 19 and sinkholes, and large-scale disasters that combine natural and social disasters are occurring frequently. In order to reduce damage caused by disasters and effectively respond to disasters, the importance of disaster safety education is emerging because it is necessary to understand the awareness of disaster situations and the functional response process. Ministry of Public Interior and Security is providing disaster safety education for emergency managers through 54 specialized disaster safety education institutions. There is also a lack of experience facilities. This has a problem in that it makes it difficult for disaster safety personnel to effectively respond to disasters due to lack of experience in actual disaster sites. Also, unlike other education fields, the connection between disaster safety education contents and new technologies such as AI is still lacking. In this study, focusing on natural disaster, the current status and problems of domestic disaster safety education institutions and their contents are investigated and analyzed, and based on this, this study suggested improvement plans for domestic disaster safety education contents such as establishment of a unified disaster safety standard curriculum, production and distribution of disaster safety education experience contents using virtual reality technology and infotainment technology, and development of mobile AI tutoring service.

Construction Status and Proposal for Information Communication Facility of Childcare Center -After COVID19, focusing on IT Technology Utilization- (어린이집 정보통신설비 구축현황 및 제안 -COVID19 이후 IT기술활용 중심으로-)

  • Lee, Jae-Yong;Shin, Seung-Jung
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.20 no.4
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    • pp.43-50
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    • 2020
  • The purpose of this study is to examine the case of constructing information and communication facilities in daycare centers and to propose an educational environment that can foster young talents who can lead the era of the fourth industrial revolution. In particular, after COVID19, a method was proposed to create an information and communication environment suitable for children to receive personalized education, and to create an environment for experiential education if possible, and at the same time to enable averaging of customized learning. Since there has been no research on information and communication facilities in daycare centers, we intend to place significance on starting, and in the future, to foster creative and contextual children, we will reduce the movement of teachers through smart speakers and mobile devices, and tailor the educational environment through AI data. I think that the design of the daycare center should be changed in the direction of making the product. To this end, the CM role of information and communication supervision is needed, and it is hoped that it will become a design standard for daycare centers after COVID19 by developing research on daycare centers.

T-commerce Trends and Development Model Proposal -Focusing on Broadcasting Screens and Customer Data Utilization- (T커머스 동향 및 발전모델 제안 -방송화면 및 고객데이터 활용중심-)

  • Lee, Jae-Yong;Shin, Seung-Jung
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.21 no.2
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    • pp.49-54
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    • 2021
  • The purpose of this study is to identify trends in T commerce and further propose ways to improve customer data-based services and development models for changes in broadcasting screens with the expansion of IPTV subscribers. Implementing a customized shopping model like mobile through TV media and improving customer satisfaction will reduce customer departures and provide a more convenient shopping environment through large screens. We would like to learn about the current status and problems of T commerce broadcasting and explain some technically validated models (channel-in-channel, AI speaker) and talk about improvement of legal (broadcasting and Internet multimedia business law) constraints.

Technical Suggestions for Smart Airport Realization - Viewpoint of Passenger Convenience (스마트공항 실현을 위한 기술적 제언 - 여객 편의성 관점)

  • Hong, Jin Woo;Oh, Jeong Hoon;Lee, Han Kyu;Kim, Moon Ku;Song, Ho Young
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2018.10a
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    • pp.268-271
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    • 2018
  • Smart Airport which applies the new ICT technologies to the airport is a future airport to provide convenient and safe services for passengers who are airport users, and promote the efficient management of the airport system in point of airport operator's view. The ranges of smart airport include the overall area of the airport like land side, terminal, and air side. In this paper, we propose a technical solution for airport process of terminal providing passenger convenience in various ranges for smart airport realization. Self-service such as web or mobile check-in, self check-in/tagging/back drop/boarding etc. should be strengthened to smartize the airport process and technologies such as automatic immigration, smart security search and automatic AI-based baggage search should be applied. In this paper, we explain the concept of smart airport and smart process, and then propose technical considerations.

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A Study on Malware Identification System Using Static Analysis Based Machine Learning Technique (정적 분석 기반 기계학습 기법을 활용한 악성코드 식별 시스템 연구)

  • Kim, Su-jeong;Ha, Ji-hee;Oh, Soo-hyun;Lee, Tae-jin
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.29 no.4
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    • pp.775-784
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    • 2019
  • Malware infringement attacks are continuously increasing in various environments such as mobile, IOT, windows and mac due to the emergence of new and variant malware, and signature-based countermeasures have limitations in detection of malware. In addition, analytical performance is deteriorating due to obfuscation, packing, and anti-VM technique. In this paper, we propose a system that can detect malware based on machine learning by using similarity hashing-based pattern detection technique and static analysis after file classification according to packing. This enables more efficient detection because it utilizes both pattern-based detection, which is well-known malware detection, and machine learning-based detection technology, which is advantageous for detecting new and variant malware. The results of this study were obtained by detecting accuracy of 95.79% or more for benign sample files and malware sample files provided by the AI-based malware detection track of the Information Security R&D Data Challenge 2018 competition. In the future, it is expected that it will be possible to build a system that improves detection performance by applying a feature vector and a detection method to the characteristics of a packed file.

A System for Determining the Growth Stage of Fruit Tree Using a Deep Learning-Based Object Detection Model (딥러닝 기반의 객체 탐지 모델을 활용한 과수 생육 단계 판별 시스템)

  • Bang, Ji-Hyeon;Park, Jun;Park, Sung-Wook;Kim, Jun-Yung;Jung, Se-Hoon;Sim, Chun-Bo
    • Smart Media Journal
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    • v.11 no.4
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    • pp.9-18
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    • 2022
  • Recently, research and system using AI is rapidly increasing in various fields. Smart farm using artificial intelligence and information communication technology is also being studied in agriculture. In addition, data-based precision agriculture is being commercialized by convergence various advanced technology such as autonomous driving, satellites, and big data. In Korea, the number of commercialization cases of facility agriculture among smart agriculture is increasing. However, research and investment are being biased in the field of facility agriculture. The gap between research and investment in facility agriculture and open-air agriculture continues to increase. The fields of fruit trees and plant factories have low research and investment. There is a problem that the big data collection and utilization system is insufficient. In this paper, we are proposed the system for determining the fruit tree growth stage using a deep learning-based object detection model. The system was proposed as a hybrid app for use in agricultural sites. In addition, we are implemented an object detection function for the fruit tree growth stage determine.

Radar rainfall forecasting evaluation using consecutive advection characteristics of rainfall fields (강우장의 연속 이류특성을 활용한 레이더 강수량 예측성 평가)

  • Kim, Tae-Jeong;Kim, Jang-Gyeong;Kwon, Hyun-Han
    • Proceedings of the Korea Water Resources Association Conference
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    • 2021.06a
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    • pp.39-39
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    • 2021
  • 기상재해를 극소화하기 위해서는 그 원인이 되는 기상현상의 규모와 거동을 명확히 감시하고 분석하여 신뢰성 있는 예측정보가 제공되어야 한다. 최근 위험기상 발생빈도가 증가하여 초단기 및 위험기상 예보의 정확도 향상을 위한 고품질 레이더 정보 활용 연구가 활발하게 진행되고 있다. 레이더는 전자파를 이용하여 강우의 양과 분포, 이동특성을 관측하는 장비로써 우리나라는 초단기적 위험기상 대응능력 향상을 추진하기 위한 목적으로 첨단 성능의 이중편파레이더 관측망을 구축하고 있다. 국내 기상관측용 레이더는 기상예보(기상청), 홍수예보(환경부), 군 작전 기상지원(국방부) 등으로 각 기관이 개별적으로 설치운영 하고 있다. 본 연구에서는 관계부처에서 운영하고 있는 레이더의 합성장을 이용하여 강수장의 상관성을 기반으로 이류(advection) 특성을 도출하였다. 정확도 있는 이류특성을 도출하기 위하여 시간해상도는 10분을 적용하였으며 가우시안 필터링 기법을 적용하여 강수장 상관분석을 수행하였다. 호우와 태풍을 대상으로 강수장의 이류패턴을 추출하여 강수장의 이동방향 및 속도를 고려한 강수량 예측기법의 적용성을 평가하였다. 본 연구 결과는 격자형 강수예측정보를 제공하여 AI 홍수예보 및 수치예보 모델의 초기조건 입력 등에 활용되어 기후변동성에 따른 대국민 안전 실현을 확보하는데 기후변화 대응전략의 핵심기술로 활용될 수 있을 것으로 판단된다. 덧붙어, 4차 산업혁명에 따른 수문기상 빅 데이터(big data) 통합 플랫폼을 구축하여 고해상도 홍수대응 기술 및 GIS 및 모바일 시스템을 연계한 실시간 기후재해 예·경보가 가능할 것으로 사료된다.

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Proposal of a Learning Model for Mobile App Malicious Code Analysis (모바일 앱 악성코드 분석을 위한 학습모델 제안)

  • Bae, Se-jin;Choi, Young-ryul;Rhee, Jung-soo;Baik, Nam-kyun
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.10a
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    • pp.455-457
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    • 2021
  • App is used on mobile devices such as smartphones and also has malicious code, which can be divided into normal and malicious depending on the presence or absence of hacking codes. Because there are many kind of malware, it is difficult to detect directly, we propose a method to detect malicious app using AI. Most of the existing methods are to detect malicious app by extracting features from malicious app. However, the number of types have increased exponentially, making it impossible to detect malicious code. Therefore, we would like to propose two more methods besides detecting malicious app by extracting features from most existing malicious app. The first method is to learn normal app to extract normal's features, as opposed to the existing method of learning malicious app and find abnormalities (malicious app). The second one is an 'ensemble technique' that combines the existing method with the first proposal. These two methods need to be studied so that they can be used in future mobile environment.

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Analysis on the Current Status of the Fourth Industrial Revolution-Oriented Curriculum of the Computer and Software-Related Majors Based on the Standard Classification (표준분류에 기준한 컴퓨터 및 소프트웨어 관련 전공의 제4차 산업혁명중심 교육과정 운영 현황 분석)

  • Choi, Jin-Il;Choi, Chul-Jae
    • The Journal of the Korea institute of electronic communication sciences
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    • v.15 no.3
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    • pp.587-592
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    • 2020
  • This paper analyzed the curriculum of computer and software-related majors educating the core IT-related skills needed for the 4th Industrial Revolution. The analysis was conducted on 158 majors classified as applied software, computer science and computer engineering according to the standard classification of university education units by the Standard Classification Committee of the Korean Council of University Education. The current status of introduction of curricular divided into the fields of Internet of Things(IoT) & mobile, cloud & big data, artificial intelligence(AI), and information security was analyzed among the contents of education in the relevant departments. According to the analysis, an average of 81.6% of the majors for each group of curricular organized related subjects into the curriculum. The Curriculum Response Index for the 4th industrial revolution(CRI4th) by major, calculated by weighting track operations by education sector, averaged 27.5 point out of 100 point. And the IoT & mobile sector had the highest score of 42.3 points.

Performance comparison of wake-up-word detection on mobile devices using various convolutional neural networks (다양한 합성곱 신경망 방식을 이용한 모바일 기기를 위한 시작 단어 검출의 성능 비교)

  • Kim, Sanghong;Lee, Bowon
    • The Journal of the Acoustical Society of Korea
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    • v.39 no.5
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    • pp.454-460
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    • 2020
  • Artificial intelligence assistants that provide speech recognition operate through cloud-based voice recognition with high accuracy. In cloud-based speech recognition, Wake-Up-Word (WUW) detection plays an important role in activating devices on standby. In this paper, we compare the performance of Convolutional Neural Network (CNN)-based WUW detection models for mobile devices by using Google's speech commands dataset, using the spectrogram and mel-frequency cepstral coefficient features as inputs. The CNN models used in this paper are multi-layer perceptron, general convolutional neural network, VGG16, VGG19, ResNet50, ResNet101, ResNet152, MobileNet. We also propose network that reduces the model size to 1/25 while maintaining the performance of MobileNet is also proposed.