• 제목/요약/키워드: AI characteristics

검색결과 740건 처리시간 0.026초

Stochastic Channel Modeling for Railway Tunnel Scenarios at 25 GHz

  • He, Danping;Ai, Bo;Guan, Ke;Zhong, Zhangdui;Hui, Bing;Kim, Junhyeong;Chung, Heesang;Kim, Ilgyu
    • ETRI Journal
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    • 제40권1호
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    • pp.39-50
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    • 2018
  • More people prefer using rail traffic for travel or for commuting owing to its convenience and flexibility. The railway scenario has become an important communication scenario in the fifth generation era. The communication system should be designed to support high-data-rate demands with seamless connectivity at a high mobility. In this paper, the channel characteristics are studied and modeled for the railway tunnel scenario with straight and curved route shapes. On the basis of measurements using the "Mobile Hotspot Network" system, a three-dimensional ray tracer (RT) is calibrated and validated for the target scenarios. More channel characteristics are explored via RT simulations at 25.25 GHz with a 500-MHz bandwidth. The key channel parameters are extracted, provided, and incorporated into a 3rd-Generation-Partnership-Project-like stochastic channel generator. The necessary channel information can be practically realized, which can support the link-level and system-level design of the communication system in similar scenarios.

영화 배경으로서의 도시 공간의 특징과 의미 해석 - 1960년 이후의 한국영화를 중심으로 - (Interpreting the Characteristics and the Meanings of Urban Spaces as the Background of Films - Focusing on Korean Films from 1960's -)

  • 서영애;조경진
    • 한국조경학회지
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    • 제34권1호
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    • pp.69-80
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    • 2006
  • The purposes of this study are to analyze the meanings of urban spaces which are the background of the Korean films, and to capture the interactions of ordinary culture and urban spaces. By reading urban spaces through films, it is possible to understand the variety of experiences that are hardly captured with direct eyes, specific and vivid urban images, and various events formed by the interactions of spaces and people. The scope of the study is the urban spaces revealed in Korean films portraying cities after the 1960's as their settings, and the total of 18 films was selected with every $4{\sim}5$ films for each time stage. With the selected films, analytical meanings were developed with considering three aspects; 1) phylogenetic meaning that simply reflects social-cultural and historical background, 2) the outer strum meaning that concerns the situation of special background and film scene, and 3) metaphorical and metanymic meaning on films. According to the appearance frequency, spatial backgrounds of film scenes are mainly alleys, main streets, railroad, loft, and riverside. And then the connection between spaces and meaning clusters was grasped, and reflected meanings were derived for every spaces. And the meaning of urban space in films was analyzed based on the meaning of developments and outer stratum. The fundamental characteristics and feelings of people in media such as films are more emphasized than in real world. Urban space is not considered as a simple visible shell, but is recognized as 'a real situation' created by people. The intension of this study was to open the possibility of the various views of urban spaces. The construction of the urban space should be approached from a perspective of creating new places at where the space and human beings interact with considerations of stories of various human lives. I hope new vistas can be opened up for the research subjects and methodologies about the hereafter study of urban spaces through the mutual communications with various adjacent regions including films.

국내외 기능성 침구 개발 현황에 관한 연구 -IoT(Internet of Things) 기술기반 스마트 침구를 중심으로- (A Study for Development Status of Functional Bedding -Focusing on Smart Bedding Based on Internet of Things-)

  • 윤수빈;김성달
    • 패션비즈니스
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    • 제23권1호
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    • pp.14-24
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    • 2019
  • Various types of functional bedding for inducing and maintaining sleep, are developed and launched with the importance of improving health through sleep emphasized currently. The purpose of this study is to examine development status and direction of functional bedding in the $4^{th}$ Industrial Revolution era, through systematic classification of elements of IoT-based smart bedding cases actively developed as functional bedding at home and abroad. Through previous research, literature and Internet data, characteristics and functional extension of smart bedding and the background of smart bed development was analyzed. And it was analyzed that smart bedding pursues recent functionalism and convergence of physical and digital concept such as IoT or AI, and also mental value to improve sleep quality. As bedroom where smart bedding place in has the private and limited characteristics and users are in sleep-conscious, that hard to ensure power and discomfort in carrying are moderated and the aesthetic elements are not very important, and that the smart bedding performance while sleeping were affected on developmental background. Based on CES case study and analysis on how smart beds are functionally expanded from conventional bedding, smart beds have gained information through digital sensing, and common properties that can be controlled anytime, anywhere, using a smart phone. Some set up the right environment and pose, while others stimulate nerves directly as active intervention. It is expected that smart bedding will be developed to cure user's body and mind, through active intervention when sleeping.

History and Trends of Data Education in Korea - KISTI Data Education Based on 2001-2019 Statistics

  • Min, Jaehong;Han, Sunggeun;Ahn, Bu-young
    • 인터넷정보학회논문지
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    • 제21권6호
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    • pp.133-139
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    • 2020
  • Big data, artificial intelligence (AI), and machine learning are keywords that represent the Fourth industrial Revolution. In addition, as the development of science and technology, the Korean government, public institutions and industries want professionals who can collect, analyze, utilize and predict data. This means that data analysis and utilization education become more important. Education on data analysis and utilization is increasing with trends in other academy. However, it is true that not many academy run long-term and systematic education. Korea Institute of Science and Technology Information (KISTI) is a data ecosystem hub and one of its performance missions has been providing data utilization and analysis education to meet the needs of industries, institutions and governments since 1966. In this study, KISTI's data education was analyzed using the number of curriculum trainees per year from 2001 to 2019. With this data, the change of interest in education in information and data field was analyzed by reflecting social and historical situations. And we identified the characteristics of KISTI and trainees. It means that the identity, characteristics, infrastructure, and resources of the institution have a greater impact on the trainees' interest of data-use education.In particular, KISTI, as a research institute, conducts research in various fields, including bio, weather, traffic, disaster and so on. And it has various research data in science and technology field. The purpose of this study can provide direction forthe establishment of new curriculum using data that can represent KISTI's strengths and identity. One of the conclusions of this paper would be KISTI's greatest advantages if it could be used in education to analyze and visualize many research data. Finally, through this study, it can expect that KISTI will be able to present a new direction for designing data curricula with quality education that can fulfill its role and responsibilities and highlight its strengths.

럭셔리 패션 브랜드의 디지털 마케팅 전략 분석 (Analysis of digital marketing strategies of luxury fashion brands)

  • 박지수;이영주
    • 한국의상디자인학회지
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    • 제23권1호
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    • pp.87-102
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    • 2021
  • The purpose of this study is to consider effective digital marketing strategies through analysis of luxury fashion brands. This study conducted both quantitative analysis and case studies of the brands Louis Vuitton, Gucci, Burberry, and Chanel. To measure the brand image of the luxury fashion brands, the survey was distributed to Millennials, and total of 277 responses were used for the final analysis by using SPSS 25.0 statistical program. Other than survey, this paper analyzed digital marketing strategies of luxury fashion brands through brand-related papers, website and social media of each brand, Samsung Designnet's database, and news posted on search engines. The results of this study are as follows: First, according to the result of examining brand image of luxury fashion brands, there was no significant difference between brands, except Gucci. Second, this study analyzed each luxury fashion brand to understand the characteristics of digital marketing, and common characteristics were identified. Third, by analyzing the brand image and digital marketing strategies of luxury fashion brands, it was confirmed that Gucci's brand image and digital marketing strategies were consistent, while there was a difference between Burberry's brand image and digital marketing strategy. Therefore, this article proposes the following digital marketing strategies that are suitable for luxury fashion brands. First, is the connection of on/offline channels. Second, is the use of AI technology. Third, is a blockchain-based platform.

유사 이미지 분류를 위한 딥 러닝 성능 향상 기법 연구 (Research on Deep Learning Performance Improvement for Similar Image Classification)

  • 임동진;김태홍
    • 한국콘텐츠학회논문지
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    • 제21권8호
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    • pp.1-9
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    • 2021
  • 딥 러닝을 활용한 컴퓨터 비전 연구는 여전히 대규모의 학습 데이터와 컴퓨팅 파워가 필수적이며, 최적의 네트워크 구조를 도출하기 위해 많은 시행착오가 수반된다. 본 연구에서는 네트워크 최적화나 데이터를 보강하는 것과 무관하게 데이터 자체의 특성만을 고려한 CR(Confusion Rate)기반의 유사 이미지 분류 성능 향상 기법을 제안한다. 제안 방법은 유사한 이미지 데이터를 정확히 분류하기 위해 CR을 산출하고 이를 손실 함수의 가중치에 반영함으로서 딥 러닝 모델의 성능을 향상시키는 기법을 제안한다. 제안 방법은 네트워크 최적화 결과와 독립적으로 이미지 분류 성능의 향상을 가져올 수 있으며, 클래스 간의 유사성을 고려해 유사도가 높은 이미지 식별에 적합하다. 제안 방법의 평가결과 HanDB에서는 0.22%, Animal-10N에서는 3.38%의 성능향상을 보였다. 제안한 방법은 다양한 Noisy Labeled 데이터를 활용한 인공지능 연구에 기반이 될 것을 기대한다.

A Detailed Review on Recognition of Plant Disease Using Intelligent Image Retrieval Techniques

  • Gulbir Singh;Kuldeep Kumar Yogi
    • International Journal of Computer Science & Network Security
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    • 제23권9호
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    • pp.77-90
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    • 2023
  • Today, crops face many characteristics/diseases. Insect damage is one of the main characteristics/diseases. Insecticides are not always effective because they can be toxic to some birds. It will also disrupt the natural food chain for animals. A common practice of plant scientists is to visually assess plant damage (leaves, stems) due to disease based on the percentage of disease. Plants suffer from various diseases at any stage of their development. For farmers and agricultural professionals, disease management is a critical issue that requires immediate attention. It requires urgent diagnosis and preventive measures to maintain quality and minimize losses. Many researchers have provided plant disease detection techniques to support rapid disease diagnosis. In this review paper, we mainly focus on artificial intelligence (AI) technology, image processing technology (IP), deep learning technology (DL), vector machine (SVM) technology, the network Convergent neuronal (CNN) content Detailed description of the identification of different types of diseases in tomato and potato plants based on image retrieval technology (CBIR). It also includes the various types of diseases that typically exist in tomato and potato. Content-based Image Retrieval (CBIR) technologies should be used as a supplementary tool to enhance search accuracy by encouraging you to access collections of extra knowledge so that it can be useful. CBIR systems mainly use colour, form, and texture as core features, such that they work on the first level of the lowest level. This is the most sophisticated methods used to diagnose diseases of tomato plants.

신경망 회로 제어기를 이용한 선박 엔진 발전기의 여자기 제어 성능 개선에 관한 연구 (Study on the Performance Improvement of Marine Engine Generator Exciter Control using Neural Network Controller)

  • 김희문;김종수;김성완;전현민
    • 해양환경안전학회지
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    • 제29권6호
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    • pp.659-665
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    • 2023
  • 선박 발전기의 여자기는 출력 단자 전압을 일정하게 유지하기 위하여 여자전류 제어를 통해 자속을 조정한다. 여자기 내부에 있는 전압제어기는 통상적으로 비례 적분 제어방식이 사용되는데 게인과 시정수에 의해 결정되는 응답 특성은 적절치 못한 설정값에 의해 원하지 않는 출력을 내며 이로 인해 선내 전력의 품질과 안정성을 떨어뜨릴 수 있다. 본 논문에서는 IEEE에서 제공하는 AC4A 타입의 여자기 모델을 통해 얻을 수 있는 안정적인 입출력 데이터를 활용하여 신경망 회로를 학습시킨 후 기존의 비례 적분 제어방식의 전압제어기를 학습된 신경망 회로 제어기로 대체하여 시뮬레이션을 수행하였다. 그 결과 기존 대비 최대 9.63%까지 오버슈팅이 개선되었으며, 안정적인 응답 특성에 대한 우수성을 확인하였다.

인간의 습관적 특성을 고려한 악성 도메인 탐지 모델 구축 사례: LSTM 기반 Deep Learning 모델 중심 (Case Study of Building a Malicious Domain Detection Model Considering Human Habitual Characteristics: Focusing on LSTM-based Deep Learning Model)

  • 정주원
    • 융합보안논문지
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    • 제23권5호
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    • pp.65-72
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    • 2023
  • 본 논문에서는 LSTM(Long Short-Term Memory)을 기반으로 하는 Deep Learning 모델을 구축하여 인간의 습관적 특성을 고려한 악성 도메인 탐지 방법을 제시한다. DGA(Domain Generation Algorithm) 악성 도메인은 인간의 습관적인 실수를 악용하여 심각한 보안 위협을 초래한다. 타이포스쿼팅을 통한 악성 도메인의 변화와 은폐 기술에 신속히 대응하고, 정확하게 탐지하여 보안 위협을 최소화하는 것이 목표이다. LSTM 기반 Deep Learning 모델은 악성코드별 특징을 분석하고 학습하여, 생성된 도메인을 악성 또는 양성으로 자동 분류한다. ROC 곡선과 AUC 정확도를 기준으로 모델의 성능 평가 결과, 99.21% 이상 뛰어난 탐지 정확도를 나타냈다. 이 모델을 활용하여 악성 도메인을 실시간 탐지할 수 있을 뿐만 아니라 다양한 사이버 보안 분야에 응용할 수 있다. 본 논문은 사용자 보호와 사이버 공격으로부터 안전한 사이버 환경 조성을 위한 새로운 접근 방식을 제안하고 탐구한다.

Forecasting the Business Performance of Restaurants on Social Commerce

  • Supamit BOONTA;Kanjana HINTHAW
    • 유통과학연구
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    • 제22권4호
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    • pp.11-22
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    • 2024
  • Purpose: This research delves into the various factors that influence the performance of restaurant businesses on social commerce platforms in Bangkok, Thailand. The study considers both internal and external factors, including but not limited to business characteristics and location. Moreover, this research also analyzes the effects of employing multiple social commerce platforms on business efficiency and explores the underlying reasons for such effects. Research design, data, and methodology: Restaurants can be classified into different price ranges: low, medium, and high. To further investigate, we employed natural language processing AI to analyze online reviews and evaluate algorithm performance using machine learning techniques. We aimed to develop a model to gauge customer satisfaction with restaurants across different price categories effectively. Results: According to the research findings, several factors significantly impact restaurant groups in the low and mid-price ranges. Among these factors are population density and the number of seats at the restaurant. On the other hand, in the mid-and high-price ranges, the price levels of the food and drinks offered by the restaurant play a crucial role in determining customer satisfaction. Furthermore, the correlation between different social commerce platforms can significantly affect the business performance of high-price range restaurant groups. Finally, the level of online review sentiment has been found to influence customer decision-making across all restaurant types significantly. Conclusions: The study emphasizes that restaurants' characteristics based on their price level differ significantly, and social commerce platforms have the potential to affect one another. It is worth noting that the sentiment expressed in online reviews has a more significant impact on customer decision-making than any other factor, regardless of the type of restaurant in question.