• Title/Summary/Keyword: media components

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The Effects of ETC-based Group Art Therapy : Focusing on the Parental Anxiety of Elementary School Students' Mothers (ETC 기반 집단미술치료의 효과성 연구: 초등학생 어머니의 양육불안 감소를 중심으로)

  • Park, Sang-Soon;Rim, Sung-Ryun
    • The Journal of the Korea Contents Association
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    • v.21 no.4
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    • pp.303-316
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    • 2021
  • This study is aimed at verifying the effects of an ETC(Expressive Therapies Continuum)-based group art therapy program on reducing parental anxiety in first-grade elementary school students' mothers. An ETC program was composed based on the therapeutic factors of the ETC components. Seven mothers of first-grade students located in city A of Gyeonggi-do were selected as the subjects of the study. These mothers underwent 11 sessions of ETC-based group art therapy from April 18 to May 24, 2019, 1 to 2 times a week for 70 to 90 minutes. In order to verify the effectiveness of this research program, scores from pre- and post-parental anxiety scales were analyzed using SPSS 24.0 program. Results demonstrated that first, mothers' parental anxiety was significantly reduced after the ETC program participation. Second, changes in ETC component use throughout the program positively influenced reductions in parental anxiety. In conclusion, each participant experienced the opportunity to self-explore and self-understand at all levels of ETC with their preferred art medium, thereby lowering parenting anxiety. It is meaningful that through the ETC-based art therapy program, the client can be self-aware of his or her problem, and the client can decide the direction that is beneficial to them through voluntary media selection. In addition, it is meaningful that the ETC group art therapy is able to perform activities tailored to each individual.

Change Attention-based Vehicle Scratch Detection System (변화 주목 기반 차량 흠집 탐지 시스템)

  • Lee, EunSeong;Lee, DongJun;Park, GunHee;Lee, Woo-Ju;Sim, Donggyu;Oh, Seoung-Jun
    • Journal of Broadcast Engineering
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    • v.27 no.2
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    • pp.228-239
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    • 2022
  • In this paper, we propose an unmanned vehicle scratch detection deep learning model for car sharing services. Conventional scratch detection models consist of two steps: 1) a deep learning module for scratch detection of images before and after rental, 2) a manual matching process for finding newly generated scratches. In order to build a fully automatic scratch detection model, we propose a one-step unmanned scratch detection deep learning model. The proposed model is implemented by applying transfer learning and fine-tuning to the deep learning model that detects changes in satellite images. In the proposed car sharing service, specular reflection greatly affects the scratch detection performance since the brightness of the gloss-treated automobile surface is anisotropic and a non-expert user takes a picture with a general camera. In order to reduce detection errors caused by specular reflected light, we propose a preprocessing process for removing specular reflection components. For data taken by mobile phone cameras, the proposed system can provide high matching performance subjectively and objectively. The scores for change detection metrics such as precision, recall, F1, and kappa are 67.90%, 74.56%, 71.08%, and 70.18%, respectively.

Lightweight Super-Resolution Network Based on Deep Learning using Information Distillation and Recursive Methods (정보 증류 및 재귀적인 방식을 이용한 심층 학습법 기반 경량화된 초해상도 네트워크)

  • Woo, Hee-Jo;Sim, Ji-Woo;Kim, Eung-Tae
    • Journal of Broadcast Engineering
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    • v.27 no.3
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    • pp.378-390
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    • 2022
  • With the recent development of deep composite multiplication neural network learning, deep learning techniques applied to single-image super-resolution have shown good results, and the strong expression ability of deep networks has enabled complex nonlinear mapping between low-resolution and high-resolution images. However, there are limitations in applying it to real-time or low-power devices with increasing parameters and computational amounts due to excessive use of composite multiplication neural networks. This paper uses blocks that extract hierarchical characteristics little by little using information distillation and suggests the Recursive Distillation Super Resolution Network (RDSRN), a lightweight network that improves performance by making more accurate high frequency components through high frequency residual purification blocks. It was confirmed that the proposed network restores images of similar quality compared to RDN, restores images 3.5 times faster with about 32 times fewer parameters and about 10 times less computation, and produces 0.16 dB better performance with about 2.2 times less parameters and 1.8 times faster processing time than the existing lightweight network CARN.

A Study on Non-Contact Vocal Instruction (비대면 가창 수업 방법 고찰)

  • Lim, Ji-Hyun;Min, Kyung-Won
    • Journal of Korea Entertainment Industry Association
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    • v.15 no.1
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    • pp.27-38
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    • 2021
  • Non-Contact society has arrived due to social distinctions by COVID 19 pandemic. The arrival of the era of non-contact is having a profound impact on educational activities as well as on our social and economic lives. In response to the pandemic situation universities and all other educational institutions have implemented non-contact online classes. In particular arts physical educations and other practical classes are experiencing many difficulties due to the limited environment caused by social distancing from COVID 19 pandemic. Vocal classes are undergoing a transition mainly from 1:1 individual face-to-face lessons or group teaching methods to the non-contact era of online teaching or lesson methods. It is necessary to look at the direction of non-face-to-face practical classes in preparation for accelerated educational innovation. Edu-tech, which innovates technology in the wake of the age of non-contact after COVID 19 pandemic is expected to begin in earnest at school sites in Korea which have remained in the traditional way of education. The purpose of this study is to effectively non-contact vocal instructional methods by cogitating the current state of higher practical education and vocal classes in Korea. In addition, This study conducted two components of satisfied instructions such as 'Priorlearning of monitoring of recorded singing', and 'Immediate analyzing of various vocal contents and supplementary lessons of music theory' with a research on the peos and cons of non-face-to-face vocal class. Over a period of time, The effective non-contact of vocal instructional methods is in need to supplement non-face-to-face vocal class problems and further research and system construction with non-face-to-face vocal class's pros and cons to construct high-quality lecture contents is warranted.

The Play World Structure of EBS Character "Pengsu" (EBS 캐릭터 '펭수'의 놀이세계 구조)

  • Kim, Jeong-Seob
    • Journal of Korea Entertainment Industry Association
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    • v.14 no.3
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    • pp.267-275
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    • 2020
  • Even ordinary-looking plays can have a profound meaning. Based on this assumption, Eugene Pink (1960) has established an analytical model of play with five elements, namely "delight", "meaning", "community", "rules" and "tools." It was an effort to reflect on the true meaning of play beyond the cortical entertaining nature of play. In this study, it was carried out that all the texts containing images and performance from the EBS character "Pengsu" were selected, since he emerged as a new star in 2019. And also his play structure was analyzed by applying the Pink's model. As a result, Pengsu's play structure was confirmed to be systematic and complete as a play prototype because it was well-organized with five elements of play. It was regarded as a successful character that skillfully attracts participants to the play world. Among the components of the play, "fun" was found to be his funny appearance, sudden and unconventional behavior, "meaning" was the elimination of authoritarianism, self-esteeming and energizing, "community" was a multi-platform media user who crossed off-on-line, analog-digital-line, "rules" was to set his concept fixed as a young stranger with an ego to unreveal his identity, and "tools" was shown as his character itself and continual discourse. It shows that until now, Pengsu has a social net function of quite spreading the positive meaning of encouragement and comfort, advice and guide, consideration and forgiveness, introspection and nirvana to all members of our society, including the youth who are struggling with uncertainty and anxiety by showing rather exaggerated and stimulating performance that precisely combines these play elements.

Latent Shifting and Compensation for Learned Video Compression (신경망 기반 비디오 압축을 위한 레이턴트 정보의 방향 이동 및 보상)

  • Kim, Yeongwoong;Kim, Donghyun;Jeong, Se Yoon;Choi, Jin Soo;Kim, Hui Yong
    • Journal of Broadcast Engineering
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    • v.27 no.1
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    • pp.31-43
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    • 2022
  • Traditional video compression has developed so far based on hybrid compression methods through motion prediction, residual coding, and quantization. With the rapid development of technology through artificial neural networks in recent years, research on image compression and video compression based on artificial neural networks is also progressing rapidly, showing competitiveness compared to the performance of traditional video compression codecs. In this paper, a new method capable of improving the performance of such an artificial neural network-based video compression model is presented. Basically, we take the rate-distortion optimization method using the auto-encoder and entropy model adopted by the existing learned video compression model and shifts some components of the latent information that are difficult for entropy model to estimate when transmitting compressed latent representation to the decoder side from the encoder side, and finally compensates the distortion of lost information. In this way, the existing neural network based video compression framework, MFVC (Motion Free Video Compression) is improved and the BDBR (Bjøntegaard Delta-Rate) calculated based on H.264 is nearly twice the amount of bits (-27%) of MFVC (-14%). The proposed method has the advantage of being widely applicable to neural network based image or video compression technologies, not only to MFVC, but also to models using latent information and entropy model.

Rubidium Market Trends, Recovery Technologies, and the Relevant Future Countermeasures (루비듐 시장 및 회수 동향에 따른 향후 관련 대응방안)

  • Sang-hun Lee
    • Resources Recycling
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    • v.32 no.3
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    • pp.3-8
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    • 2023
  • This study discussed production, demand, and future prospects of rubidium, which is an alkali group metal that is highly reactive to various media and requires carefulness in handling, but no significant environmental hazard of rubidium has been reported yet. Rubidium is used in various fields such as optoelectronic equipment, biomedical, and chemical industries. Because of difficulty in production as well as limited demand, the transaction price of rubidium is relatively high, but its detail information such as market status and potential growth is uncertain. However, if the mass production of versatile ultra-high-performance equipment such as quantum computers and the necessity of rubidium use in the equipment are confirmed, there is a possibility that the rubidium market will expand in the future. Rubidium is often found together with lithium, beryllium, and cesium, and may be present in granite containing minerals such as lepidolite and pollucite, as well as in seawater and industrial waste. Several technologies such as acid leaching, roasting, solvent extraction, and adsorption are used to recover rubidium. The maximum recovery efficiency of the rubidium from the sources and the processing above is generally high, but, in many practices, rubidium is not the main recovery target, and therefore the actual recovery effects should depend on presence of other valuable components or impurities, together with recovery costs, energy consumption, environmental issues, etc. In conclusion, although the current production and consumption of rubidium are limited, with consideration of the possible market fluctuations according to the emergence of large-scale demand sources, etc., further investigations by related institutions should be necessary.

Mass Cultivation of Rhodococcus sp. 3-2, a Carbendazim-Degrading Microorganism, and Development of Microbial Agents (카벤다짐 분해 미생물인 Rhodococcus sp. 3-2의 대량 배양 및 미생물 제제 개발)

  • Jun-Kyung Park;Seonghun Im;Jeong Won Kim;Jung-Hwan Ji;Kong-Min Kim;Haeseong Park;Yeong-Seok Yoon;Hang-Yeon Weon;Gui Hwan Han
    • Korean Journal of Environmental Agriculture
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    • v.42 no.4
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    • pp.259-268
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    • 2023
  • Rhodococcus sp. 3-2 strain has been reported to degrade benzimidazole-based pesticides, such as benomyl and carbendazim. Therefore, this study aimed to optimize culture medium composition and culture conditions to achieve cost-effective and efficient large-scale production of the Rhodococcus sp. 3-2 strain. The study identified that the optimal media composition for mass culture comprised 0.5% glucose, 0.5% yeast extract, 0.15% NaCl, 0.5% K2HPO4, 0.5% sodium succinate, and 0.1% MgSO4. Additionally, a microbial agent was developed using a 1.5-ton fermenter, with skim milk (20%), monosodium glutamate (15%), and vitamin C (2%) as key components. The storage stability of the microbial agent has been confirmed, with advantages of low temperature conservation, which helps to sustain efficacy for at least six months. We also assessed the benomyl degradation activity of the microbial agent within field soil. The results revealed an over 90% degradation rate when the concentration of viable cells exceeded 2.65 × 106 CFU/g after a minimum of five weeks had elapsed. Based on these findings, Rhodococcus sp. 3-2 strain can be considered a cost-effective microbial agent with diverse agricultural applications.

Digital Library Interface Research Based on EEG, Eye-Tracking, and Artificial Intelligence Technologies: Focusing on the Utilization of Implicit Relevance Feedback (뇌파, 시선추적 및 인공지능 기술에 기반한 디지털 도서관 인터페이스 연구: 암묵적 적합성 피드백 활용을 중심으로)

  • Hyun-Hee Kim;Yong-Ho Kim
    • Journal of the Korean Society for information Management
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    • v.41 no.1
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    • pp.261-282
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    • 2024
  • This study proposed and evaluated electroencephalography (EEG)-based and eye-tracking-based methods to determine relevance by utilizing users' implicit relevance feedback while navigating content in a digital library. For this, EEG/eye-tracking experiments were conducted on 32 participants using video, image, and text data. To assess the usefulness of the proposed methods, deep learning-based artificial intelligence (AI) techniques were used as a competitive benchmark. The evaluation results showed that EEG component-based methods (av_P600 and f_P3b components) demonstrated high classification accuracy in selecting relevant videos and images (faces/emotions). In contrast, AI-based methods, specifically object recognition and natural language processing, showed high classification accuracy for selecting images (objects) and texts (newspaper articles). Finally, guidelines for implementing a digital library interface based on EEG, eye-tracking, and artificial intelligence technologies have been proposed. Specifically, a system model based on implicit relevance feedback has been presented. Moreover, to enhance classification accuracy, methods suitable for each media type have been suggested, including EEG-based, eye-tracking-based, and AI-based approaches.

Analysis of E-Waste Disposal Trends in a Security Perspective (보안관점의 전자폐기물 처리동향 분석 연구)

  • Juno Lee;Yuna Han;Yeji Choi;Yurim Choi;Hangbae Chang
    • Journal of Platform Technology
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    • v.11 no.6
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    • pp.56-67
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    • 2023
  • The increased demand for electronic components, spurred by the Fourth Industrial Revolution and the COVID-19 pandemic, has facilitated human life but also escalated the production of e-waste. Discussions on the impact of e-waste have primarily revolved around environmental, health, and social issues, with global legislations focusing on addressing these concerns. However, e-waste poses unique security risks, such as potential technological and personal information leaks, unlike conventional waste. Current discourse on e-waste security is notably insufficient. This study aims to empirically analyze the relatively overlooked trends in e-waste security, employing three methodologies. Firstly, it assesses the general trend in discussions on e-waste by analyzing year-wise documents and media reports. Secondly, it identifies key trends in e-waste security by examining documents on the subject. Thirdly, the study reviews national security guidelines related to e-waste disposal to assess the necessity of designing security strategies for e-waste management. This research is significant as it is one of the first in korea to address e-waste from a security perspective and offers a multi-dimensional analysis of e-waste security trends. The findings are expected to enhance domestic awareness of e-waste and its security issues, providing an opportunity for proactive response to these security risks.

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