• Title/Summary/Keyword: 블록효과

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Deep Learning-based SISR (Single Image Super Resolution) Method using RDB (Residual Dense Block) and Wavelet Prediction Network (RDB 및 웨이블릿 예측 네트워크 기반 단일 영상을 위한 심층 학습기반 초해상도 기법)

  • NGUYEN, HUU DUNG;Kim, Eung-Tae
    • Journal of Broadcast Engineering
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    • v.24 no.5
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    • pp.703-712
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    • 2019
  • Single image Super-Resolution (SISR) aims to generate a visually pleasing high-resolution image from its degraded low-resolution measurement. In recent years, deep learning - based super - resolution methods have been actively researched and have shown more reliable and high performance. A typical method is WaveletSRNet, which restores high-resolution images through wavelet coefficient learning based on feature maps of images. However, there are two disadvantages in WaveletSRNet. One is a big processing time due to the complexity of the algorithm. The other is not to utilize feature maps efficiently when extracting input image's features. To improve this problems, we propose an efficient single image super resolution method, named RDB-WaveletSRNet. The proposed method uses the residual dense block to effectively extract low-resolution feature maps to improve single image super-resolution performance. We also adjust appropriated growth rates to solve complex computational problems. In addition, wavelet packet decomposition is used to obtain the wavelet coefficients according to the possibility of large scale ratio. In the experimental result on various images, we have proven that the proposed method has faster processing time and better image quality than the conventional methods. Experimental results have shown that the proposed method has better image quality by increasing 0.1813dB of PSNR and 1.17 times faster than the conventional method.

Operational Properties and Microbial Inactivation Performance of Dielectric Barrier Discharge Plasma Treatment System (유전체장벽방전 플라즈마 장치의 조작특성과 살균력)

  • Mok, Chulkyoon;Lee, Taehoon
    • Food Engineering Progress
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    • v.15 no.4
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    • pp.398-403
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    • 2011
  • A dielectric barrier discharge plasma (DBDP) treatment system was fabricated and the optimum operating conditions for the plasma generation were determined in order to explore the potential of cold plasma as a non-thermal proessing technology. The microbial inactivation performance of the system was also evaluated against Staphyloocus aureus. The system consisted of power supply, transformer, electrode assembly and sample treatment plate. The input power was 220 V single phase AC and amplified to 10.0-50.0 kV on a transformer. A pulsed sine wave of frequency 10.0-50.0 kHz was introduced to the electrode embedded in ceramic as a dielectric barrier material in order to generate plasma at atmospheric pressure. Higher currents and consequently greater power were required for the plasma generation as the frequencies increased. A homogeneous and stable plasma was generated at currents of 1.0-2.0, and frequencies of 32.0-35.3 kHz. The optimum electrode-gaps for the plasma generation were 1.85 mm without loaded samples. More power was consumed as the electrode-gaps increased. The practically optimum electrode- gap was, however, 2.65 mm when samples were treated on slide-glasses for microbial inactivation. The maximum temperature increase after 10 min treatment was less than 20$^{\circ}C$, indicating no microbial inactivation effect by heat and thereby insuring a non-thermal method. The DBDP inactivation effect against Staphyloocus aureus increased linearly with treatment time up to 5 min, but plateaued afterward. More than 5 log reduction was achieved by 10 min treatment at 1.25 A.

A Study on the Connective Validity of Technology Maturity and Industry for Core Technologies based on 4th Industrial Revolution (4차 산업혁명 기반 핵심기술에 대한 기술성숙도와 산업과 연계 타당성 연구)

  • Cho, Han-Jin;Jeong, Kyuman
    • Journal of the Korea Convergence Society
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    • v.10 no.3
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    • pp.49-57
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    • 2019
  • The core technology development of the Fourth Industrial Revolution is linked to the development of other core technologies, which will change the industrial structure in the future and create a new smart business model. In this paper, tried to analyze the technology maturity level and analyze the technology maturity. To do this, used technology trend information to investigate and integrate the market, policy, etc. Of core technology of the 4th Industrial Revolution to achieve a comprehensive maturity level. Because technology maturity measures are scored by technology developers, prejudices may be acted upon according to a person's tendency, which may be a subjective evaluation. It is also a measure of the maturity of individual technologies, and thus is not suitable for evaluating the overall system integration perspective. However, it is possible to evaluate the maturity before integrating the core element technologies constituting the whole system and to use it as a means to compare the effect of the whole system and its feasibility and play an important role in the planning of technology development.

Power-efficiency Analysis of the MIMO-VLC System considering Dimming Control (조광제어를 고려한 MIMO-VLC 시스템의 전력 효율 분석)

  • Kim, Yong-Won;Lee, Byung-Jin;Lee, Byung-Hoon;Lee, Min-Jung;Kim, Kyung-Seok
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.18 no.6
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    • pp.169-180
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    • 2018
  • White light-emitting diodes (LEDs) are more economical than fluorescent lights, and provide high brightness, a high lifetime expectancy, and greater durability. As LEDs are closely connected with people's daily lives, dimming control of LED is an important component in providing energy savings and improving quality of life. In visible light communications systems using these LEDs, multiple input multiple output (MIMO) technology has attracted a lot of attention, in that it can attain the channel capacity in proportion to the number of antennas. This paper analyzes the power performance of three kinds of modulation in visible light communications (VLC) systems applied space-time block code (STBC) techniques. The modulation schemes are return-to-zero on-off keying (RZ-OOK), variable pulse position modulation (VPPM), and overlapping pulse position modulation (OPPM), and dimming control was applied. The power requirements and power consumption were used as metrics to compare the power efficiency in $2{\times}2$ STBC-VLC environments under the three kinds of modulation. We confirm that dimming control affects the communications performance of each modulation scheme. VPPM showed greater consumption among the three modulations, and OPPM showed energy savings comparable to VPPM.

Real-time Segmentation of Black Ice Region in Infrared Road Images

  • Li, Yu-Jie;Kang, Sun-Kyoung;Jung, Sung-Tae
    • Journal of the Korea Society of Computer and Information
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    • v.27 no.2
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    • pp.33-42
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    • 2022
  • In this paper, we proposed a deep learning model based on multi-scale dilated convolution feature fusion for the segmentation of black ice region in road image to send black ice warning to drivers in real time. In the proposed multi-scale dilated convolution feature fusion network, different dilated ratio convolutions are connected in parallel in the encoder blocks, and different dilated ratios are used in different resolution feature maps, and multi-layer feature information are fused together. The multi-scale dilated convolution feature fusion improves the performance by diversifying and expending the receptive field of the network and by preserving detailed space information and enhancing the effectiveness of diated convolutions. The performance of the proposed network model was gradually improved with the increase of the number of dilated convolution branch. The mIoU value of the proposed method is 96.46%, which was higher than the existing networks such as U-Net, FCN, PSPNet, ENet, LinkNet. The parameter was 1,858K, which was 6 times smaller than the existing LinkNet model. From the experimental results of Jetson Nano, the FPS of the proposed method was 3.63, which can realize segmentation of black ice field in real time.

Characteristics of Science Education Apps Developed by Preservice Elementary Teachers and Elementary Teachers' Thoughts about Education Developing Apps (초등 예비교사가 제작한 과학교육용 앱의 특징과 앱 제작 교육에 대한 초등교사의 생각)

  • Na, Jiyeon
    • Journal of Korean Elementary Science Education
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    • v.42 no.1
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    • pp.17-33
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    • 2023
  • This study examined inservice elementary teachers' thoughts on the development of educational apps by preservice elementary teachers and implications for TPACK education for preservice elementary teachers. A case study was conducted in which preservice elementary teachers developed a science education app, and the three teachers were surveyed for their thoughts regarding this. The results regarding the characteristics of the developed app by preservice teachers were as follows. First, "inquiry" had the highest value among educational goals intended by the preservice teachers. In addition, the scores for tool-type apps and apps in which interaction between learners and instructors occurs were relatively high. Second, most of the preservice teachers developed apps to meet curriculum goals, but their apps showed low-level characteristics in terms of the constructive and cooperative dimensions. The results of the analysis of the thinking of elementary school teachers regarding the education development apps are as follows. First, elementary school teachers assigned the lowest scores to the effectiveness of the apps, and to this problem, the achievement standard with respect to the curriculum and the evaluation and modification activities fir the apps were proposed. Second, the teachers indicated that it would be appropriate to provide the experience of making apps to directly improve the TPACK of preservice teachers. Third, the respondents thought that preservice teachers should develop block coding literacy to create apps using App Inventor. Fourth, the teachers considered it necessary to emphasize simulated instructions, as well as the experience of collecting and handling data through apps to improve preservice teachers' TPACK app development for educational use.

A Modified Method for the Radial Consolidation with the Time Dependent Well Resistance (시간 의존적 배수저항을 고려한 방사방향 압밀곡선 예측법)

  • Kim, Rae-Hyun;Hong, Sung-Jin;Jung, Doo-Suk;Lee, Woo-Jin
    • Journal of the Korean Geotechnical Society
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    • v.24 no.6
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    • pp.77-84
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    • 2008
  • The existing equations for radial consolidation cannot account for the changes of well resistance with time and cannot predict the appropriate in-situ consolidation curve. In this study, small cylinder cell tests are performed to evaluate the discharge capacity of PVD. Also, a block sample of 1.2 m in diameter and 2.0 m in height was consolidated to observe the change in the drainage capacity with time for three types of PVD. From the test results on a block sample, the drainage curves normalized with initial drainage of each PVD are similar, regardless of the PVD type and the consolidation curve, which is predicted using solutions of radial consolidation based on the discharge capacity measured in a small cylinder cell tests, significantly overestimates the degree of consolidation. The term of well resistance in the radial consolidation solution was back-calculated to fit the consolidation curve of a large block sample and it is defined as the time dependent well resistance factor, L(t). The L(t) was found to be linearly proportional to the dimensionless time factor, Th. It was also shown that the consolidation curve evaluated by using L(t) provides more accurate prediction than the existing solution.

Bearing Reinforcing Effect of Concrete Block with a Round End according to the Application of Aluminum Stiffener (알루미늄 보강재 적용에 따른 원형 단부 콘크리트 블록의 지압 보강 효과)

  • Seok Hyeon Jeon;Tae-Yun Kwon;Jin-Hee Ahn
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.27 no.3
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    • pp.38-46
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    • 2023
  • In this study, a bearing test was performed and analytically evaluated to evaluate the bearing performance according to the application of the aluminum stiffener in round-end concrete. In the bearing strength test, the change in bearing performance due to the aluminum stiffener using the aluminum form for manufacturing concrete with round-end, and the steel anchor bolts for member movement and assembly was confirmed. The FE analysis model was identically configured to the experimental conditions, and the result was compared with the experiment. Also, the crack patterns and stress behavior were confirmed. In addition, the effect of strength change of the aluminum stiffener on the round-end concrete was also evaluated analytically. The bearing strength of the round-end concrete increased by about 20% due to the aluminum stiffener, and it was confirmed that the steel anchor bolt did not affect the bearing strength. The maximum load and crack patterns shown as a result of FE analysis were similar to those of the experiment. As a result of FE analysis according to the strength change of the aluminum stiffener, the maximum load change according to the increase and decrease of the strength of the aluminum stiffener by 10% and 20% was evaluated to have no significant effect at a maximum of about 4% compared to before the strength change.

Multi-View 3D Human Pose Estimation Based on Transformer (트랜스포머 기반의 다중 시점 3차원 인체자세추정)

  • Seoung Wook Choi;Jin Young Lee;Gye Young Kim
    • Smart Media Journal
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    • v.12 no.11
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    • pp.48-56
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    • 2023
  • The technology of Three-dimensional human posture estimation is used in sports, motion recognition, and special effects of video media. Among various methods for this, multi-view 3D human pose estimation is essential for precise estimation even in complex real-world environments. But Existing models for multi-view 3D human posture estimation have the disadvantage of high order of time complexity as they use 3D feature maps. This paper proposes a method to extend an existing monocular viewpoint multi-frame model based on Transformer with lower time complexity to 3D human posture estimation for multi-viewpoints. To expand to multi-viewpoints our proposed method first generates an 8-dimensional joint coordinate that connects 2-dimensional joint coordinates for 17 joints at 4-vieiwpoints acquired using the 2-dimensional human posture detector, CPN(Cascaded Pyramid Network). This paper then converts them into 17×32 data with patch embedding, and enters the data into a transformer model, finally. Consequently, the MLP(Multi-Layer Perceptron) block that outputs the 3D-human posture simultaneously updates the 3D human posture estimation for 4-viewpoints at every iteration. Compared to Zheng[5]'s method the number of model parameters of the proposed method was 48.9%, MPJPE(Mean Per Joint Position Error) was reduced by 20.6 mm (43.8%) and the average learning time per epoch was more than 20 times faster.

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A Big Data Analysis Methodology for Examining Emerging Trend Zones Identified by SNS Users: Focusing on the Spatial Analysis Using Instagram Data (SNS 사용자에 의해 형성된 트렌드 중심지 도출을 위한 빅 데이터 분석 방법론 연구: 인스타그램 데이터 활용 공간분석을 중심으로)

  • Il Sup Lee;Kyung Kyu Kim;Ae Ri Lee
    • Information Systems Review
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    • v.20 no.2
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    • pp.63-85
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    • 2018
  • Emerging hotspot and trendy areas are formed into alleys and blocks with the help of viral effects among social network services (SNS) users called "Golmogleo." These users search for every corner of the alleys to share and promote their own favorite places through SNS. An analysis of hot places is limited if it is only based on macroeconomic indicators such as commercial area data published by national organizations, large-scale visiting facilities, and commuter figures. Careful analyses based on consumers' actual activities are needed. This study develops a "social big data analysis methodology" using Instagram data, which is one of the most popular SNSs suitable to identify recent consumer trends. We build a spatial analysis model using Local Moran's I. Results show that our model identifies new trend zones on the basis of posting data in Instagram, which are not included in the commercial information prepared by national organizations. The proposed analysis methodology enables better identification of the latest trend areas formulated by SNS user activities. It also provides practical information for start-ups, small business owners, and alley merchants for marketing purposes. This analytical methodology can be applied to future studies on social big data analysis.