• Title/Summary/Keyword: Video Data

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AI Art Creation Case Study for AI Film & Video Content (AI 영화영상콘텐츠를 위한 AI 예술창작 사례연구)

  • Jeon, Byoungwon
    • The Journal of the Convergence on Culture Technology
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    • v.7 no.2
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    • pp.85-95
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    • 2021
  • Currently, we stand between computers as creative tools and computers as creators. A new genre of movies, which can be called a post-cinema situation, is emerging. This paper aims to diagnose the possibility of the emergence of AI cinema. To confirm the possibility of AI cinema, it was examined through a case study whether the creation of a story, narrative, image, and sound, which are necessary conditions for film creation, is possible by artificial intelligence. First, we checked the visual creation of AI painting algorithms Obvious, GAN, and CAN. Second, AI music has already entered the distribution stage in the market in cooperation with humans. Third, AI can already complete drama scripts, and automatic scenario creation programs using big data are also gaining popularity. That said, we confirmed that the filmmaking requirements could be met with AI algorithms. From the perspective of Manovich's 'AI Genre Convention', web documentaries and desktop documentaries, typical trends post-cinema, can be said to be representative genres that can be expected as AI cinemas. The conditions for AI, web documentaries and desktop documentaries to exist are the same. This article suggests a new path for the media of the 4th Industrial Revolution era through research on AI as a creator of post-cinema.

A Study on System of Feasibility Study and Issues of Economic Analysis in Cultural Facility Construction: Focused on the National Museum of Contemporary Art(MMCA), Seoul (문화시설 건립 타당성조사의 체계와 경제성 분석에서의 쟁점 - 국립현대미술관 서울관 건립사업을 중심으로 -)

  • Jung, Sang-chul
    • Korean Association of Arts Management
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    • no.53
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    • pp.101-125
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    • 2020
  • This paper presents the problems and improvement methods in estimating demand and benefit, which have been controversial in the feasibility study of building cultural facilities. Although there are justifications for supplying cultural facilities by expanding leisure time and increasing income, the economic burden from the insolvent operation after construction is high. Feasibility studies can prevent these problems in advance. In order to estimate the demand for cultural facilities, similar facilities were selected and the gravity model was used to estimate the demand. In the future, it is necessary to prepare the criteria for setting the reference facility to increase the accuracy of the demand estimation. In addition, in the case of cultural facilities constructed through feasibility study, it is necessary to induce and enforce the disclosure of operational data and information, and to establish a database so that it can be used as a reference facility for demand estimation in future feasibility study on cultural facility. Accurate benefit estimation requires multiple CVM surveys. In addition to the current CVM survey, this paper suggest that supplementary online non-face-to-face surveys is considered. Furthermore, this research suggests that the use of video media for explanation of alternative materials for cultural facilities to be constructed because the WTP may be excessive due to lack of alternatives for survey respondents in the current CVM survey.

A Study on Deep Learning based Aerial Vehicle Classification for Armament Selection (무장 선택을 위한 딥러닝 기반의 비행체 식별 기법 연구)

  • Eunyoung, Cha;Jeongchang, Kim
    • Journal of Broadcast Engineering
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    • v.27 no.6
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    • pp.936-939
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    • 2022
  • As air combat system technologies developed in recent years, the development of air defense systems is required. In the operating concept of the anti-aircraft defense system, selecting an appropriate armament for the target is one of the system's capabilities in efficiently responding to threats using limited anti-aircraft power. Much of the flying threat identification relies on the operator's visual identification. However, there are many limitations in visually discriminating a flying object maneuvering high speed from a distance. In addition, as the demand for unmanned and intelligent weapon systems on the modern battlefield increases, it is essential to develop a technology that automatically identifies and classifies the aircraft instead of the operator's visual identification. Although some examples of weapon system identification with deep learning-based models by collecting video data for tanks and warships have been presented, aerial vehicle identification is still lacking. Therefore, in this paper, we present a model for classifying fighters, helicopters, and drones using a convolutional neural network model and analyze the performance of the presented model.

Efficient Searching for Shipwreck Using an Integrated Geophysical Survey Techniques in the East Sea of Korea (동해에서 지구 물리 이종방법간의 결합시스템을 활용한 침선 수색의 효용성 연구)

  • Lee-Sun, Yoo;Nam Do, Jang;Seom-Kyu, Jung;Seunghun, Lee;Cheolku, Lee;Sunhyo, Kim;Jin Hyung, Cho
    • Ocean and Polar Research
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    • v.44 no.4
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    • pp.355-364
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    • 2022
  • When the 60-ton-class patrol boat '72' of the Korea Coast Guard (KCG) was on duty and she accidentally collided with another patrol boat ('207', 200-ton-class) and sank. A month-long search found a small amount of lost items, but neither the crew nor the ship was found. For the first time in 39 years since the accident, the Korea Institute of Ocean Science and Technology (KIOST) searched the boat 72 using the latest integrated geophysical techniques. A number of sonar images presumed to be of a sunken ship was acquired using a combined system of side scan sonar and marine magnetometer, operated at an altitude of approximately 30 m from the seabed. At the same time, a strong magnetic anomaly (100 nT) was detected in one place, indicating the presence of an iron ship. A video survey using a remotely operated underwater vehicle (ROV) confirmed the presence of a shielding part of a personal firearm at the stern of the sunken vessel. Based on these comprehensive data, the sunken vessel discovered in this exploration was assumed to be '72'. This result is meaningful in terms of future ocean exploration and underwater archaeology, as the integrated system of various geophysical methods is an efficient means of identifying objects present in the water.

Use of Digital Educational Resources in the Training of Future Specialists in the EU Countries

  • Plakhotnik, Olga;Zlatnikov, Valentyn;Matviienko, Olena;Bezliudnyi, Oleksandr;Havrylenko, Anna;Yashchuk, Olena;Andrusyk, Pavlo
    • International Journal of Computer Science & Network Security
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    • v.22 no.10
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    • pp.17-24
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    • 2022
  • The article proves that the main goal of informatization of higher education institutions in the EU countries is to improve the quality of education of future specialists by introducing digital educational resources into the education process. The main tasks of informatization of education are defined. Digital educational resources are interpreted as a set of data in digital form that is applicable for use in the learning process; it is an information source containing graphic, text, digital, speech, music, video, photo and other information aimed at implementing the goals and objectives of modern education; educational resources on the Internet, electronic textbooks, educational programs, electronic libraries, etc. The creation of digital educational resources is defined as one of the main directions of informatization of all forms and levels of Education. Types of digital educational resources by educational functions are considered. The factors that determine the effectiveness of using digital educational resources in the educational process are identified. The use of digital educational resources in the training of future specialists in the EU countries is considered in detail. European countries note that digital educational resources in professional use allow you to implement a fundamentally new approach to teaching and education, which is based on broad communication, free exchange of opinions, ideas, information of participants in a joint project, on a completely natural desire to learn new things, expand their horizons; is based on real research methods (scientific or creative laboratories), allowing you to learn the laws of nature, the basics of techniques, technology, social phenomena in their dynamics, in the process of solving vital problems, features of various types of creativity in the process of joint activities of a group of participants; promotes the acquisition by teachers of various related skills that can be very useful in their professional activities, including the skills of using computer equipment and various digital technologies.

Effect of alternative farrowing pens with temporary crating on the performance of lactating sows and their litters

  • Si Nae, Cheon;So Hee, Jeong;Guem Zoo, Yoo;Se Jin, Lim;Chan Ho, Kim;Gul Won, Jang;Jung Hwan, Jeon
    • Journal of Animal Science and Technology
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    • v.64 no.3
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    • pp.574-587
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    • 2022
  • This study was performed to development the alternative farrowing pen (AFP) and to investigate performance and behavior of lactating sows and their litter. A total of 64 multiparous sows were randomly divided into two groups and were allocated to farrowing crates (FCs) and AFPs. The AFPs contained a crate and support bars that could be folded to provide the sows with extra space on day 5 postpartum. Behavior was recorded by charge-coupled device cameras and digital video recorders, and the data were scanned every 2 min to obtain an instantaneous behavioral sample. Farrowing systems did not affect feed intake, back-fat thickness, litter size and piglet weight at birth and weaning (p > 0.05). In addition, there were no differences in the number of crushed piglets between the two farrowing systems (p > 0.05). However, the weaning-to-estrus interval was shorter in the sows of the AFPs than in thous of the FCs (p < 0.05). The sows spent most of their time lying down during the lactating period, at about 80% lateral recumbency and 10%-15% ventral recumbency. The only significant differences were in the feeding and drinking behavior between sows in the two farrowing systems (p < 0.05). The FC sows displayed more feeding and drinking behavior than the AFP sows, especially in the late lactating period (p < 0.05). Piglets in the FCs tended to spend more time walking than piglets in the AFPs (p < 0.05), whereas there were no differences in suckling and lying behavior between piglets in the two farrowing systems (p > 0.05). It is concluded that the AFPs with temporary crating until day 4 postpartum did not negatively affect performance and crushed piglet compared with the FCs. It also may improve animal welfare by allowing sows to move and turn around during the lactating period. Further research is needed to find suitable housing designs to enhance productivity and animal welfare.

Deep Learning-based Object Detection of Panels Door Open in Underground Utility Tunnel (딥러닝 기반 지하공동구 제어반 문열림 인식)

  • Gyunghwan Kim;Jieun Kim;Woosug Jung
    • Journal of the Society of Disaster Information
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    • v.19 no.3
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    • pp.665-672
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    • 2023
  • Purpose: Underground utility tunnel is facility that is jointly house infrastructure such as electricity, water and gas in city, causing condensation problems due to lack of airflow. This paper aims to prevent electricity leakage fires caused by condensation by detecting whether the control panel door in the underground utility tunnel is open using a deep learning model. Method: YOLO, a deep learning object recognition model, is trained to recognize the opening and closing of the control panel door using video data taken by a robot patrolling the underground utility tunnel. To improve the recognition rate, image augmentation is used. Result: Among the image enhancement techniques, we compared the performance of the YOLO model trained using mosaic with that of the YOLO model without mosaic, and found that the mosaic technique performed better. The mAP for all classes were 0.994, which is high evaluation result. Conclusion: It was able to detect the control panel even when there were lights off or other objects in the underground cavity. This allows you to effectively manage the underground utility tunnel and prevent disasters.

Hate Speech Detection Using Modified Principal Component Analysis and Enhanced Convolution Neural Network on Twitter Dataset

  • Majed, Alowaidi
    • International Journal of Computer Science & Network Security
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    • v.23 no.1
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    • pp.112-119
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    • 2023
  • Traditionally used for networking computers and communications, the Internet has been evolving from the beginning. Internet is the backbone for many things on the web including social media. The concept of social networking which started in the early 1990s has also been growing with the internet. Social Networking Sites (SNSs) sprung and stayed back to an important element of internet usage mainly due to the services or provisions they allow on the web. Twitter and Facebook have become the primary means by which most individuals keep in touch with others and carry on substantive conversations. These sites allow the posting of photos, videos and support audio and video storage on the sites which can be shared amongst users. Although an attractive option, these provisions have also culminated in issues for these sites like posting offensive material. Though not always, users of SNSs have their share in promoting hate by their words or speeches which is difficult to be curtailed after being uploaded in the media. Hence, this article outlines a process for extracting user reviews from the Twitter corpus in order to identify instances of hate speech. Through the use of MPCA (Modified Principal Component Analysis) and ECNN, we are able to identify instances of hate speech in the text (Enhanced Convolutional Neural Network). With the use of NLP, a fully autonomous system for assessing syntax and meaning can be established (NLP). There is a strong emphasis on pre-processing, feature extraction, and classification. Cleansing the text by removing extra spaces, punctuation, and stop words is what normalization is all about. In the process of extracting features, these features that have already been processed are used. During the feature extraction process, the MPCA algorithm is used. It takes a set of related features and pulls out the ones that tell us the most about the dataset we give itThe proposed categorization method is then put forth as a means of detecting instances of hate speech or abusive language. It is argued that ECNN is superior to other methods for identifying hateful content online. It can take in massive amounts of data and quickly return accurate results, especially for larger datasets. As a result, the proposed MPCA+ECNN algorithm improves not only the F-measure values, but also the accuracy, precision, and recall.

The Self-Perception and Science Teaching Implementation of Elementary School Teacher Aiming for Student-centered Inquiry Classes -Focusing on RTOP Analysis of the Elementary School 'Temperature and Heat' Unit- (학생 중심 탐구수업을 지향하는 초등교사의 과학수업에 대한 자기인식과 실행 -초등학교 '온도와 열' 단원에 대한 RTOP 분석을 중심으로-)

  • Chaeyeon Shin;Hyojoon Kim
    • Journal of Science Education
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    • v.47 no.1
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    • pp.88-106
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    • 2023
  • This study aims to investigate the disparity between the teacher's perception of student-centered inquiry classes and the actual implementation of such practices. Specifically, we compared an elementary science teacher's self-perception of her science lessons with the observers' evaluation using the Reformed Teaching Observation Protocol (RTOP) of the "Temperature and Heat" unit. Research data were collected through classroom teaching survey, interview, and science lessons video which were analyzed using the RTOP. As a result of the study, the teacher recognized that she was practicing inquiry-oriented/student-centered classes, but the results judged by the RTOP score were found to be transitional/student-affected classes by a slight difference. Teacher H planned and practiced classes based on a high understanding and content knowledge of the curriculum and created a science classroom culture that promotes active interaction among students as well as students and teachers. However, teacher-led aspects were still emphasized in teaching design and implementation, and the project theme and content were inappropriate to improve the quality of students' science inquiry experience. In the end, the slight difference between teacher's perception of inquiry-oriented/student-centered classes and actual implementation is related to how student-centered "lesson design" is and how to plan and implement classes supported by "procedural knowledge" for students' experience in the science inquiry process. These results indicate that the teacher's self-evaluation alone is not enough to determine whether the teacher's intentions and efforts are actually being implemented, and that it is necessary to conduct objective analysis, evaluation, and discuss the results of science classes by the external observers.

An Analysis Study on the Current Status and Integration Methods of the Domestic Early Warning System (국내 재난 예경보 시스템 현황 및 통합 방안에 대한 분석 연구)

  • Hwang, Woosuk;Pyo, Kyungsoo
    • Journal of Broadcast Engineering
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    • v.27 no.1
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    • pp.80-90
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    • 2022
  • Currently, the domestic early warning system is issued differently for each disaster, and is operated independently by relevant organizations from central government to local governments. Representative domestic disaster warning systems include disaster broadcasting using CBS(Cell Broadcasting Service) and DMB(Digital Multimedia Broadcasting) Automatic Emergency Alert Service, DITS(Disaster Information Transform System) transmitted and displayed on TV screens, automatic response system, automated rainfall warning system, and disaster message board. However, due to the difference in the method of issuing each emergency alert at the site of an emergency disaster, the alerts are issued at different times for each media, and the delivered content is also not integrated. If these systems are integrated, it is expected that damage to people's property and lives will be minimized by sharing and integrated management of disaster information such as voice, video, and data to comprehensively judge and make decisions about disaster situations. Therefore, in this study, we present a plan for the integration of the disaster warning system along with the analysis of the operation status of the domestic early warning system.