• Title/Summary/Keyword: 9-Block model

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A Performance Comparison of Block-Based Matching Cost Evaluation Models for FRUC Techniques

  • Kim, Jin-Soo;Kim, Jae-Gon
    • Journal of information and communication convergence engineering
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    • v.9 no.6
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    • pp.671-675
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    • 2011
  • DVC (Distributed Video Coding) and FRUC (Frame Rate Up Conversion) techniques need to have an efficient motion compensated frame interpolation algorithms. Conventional works of these applications have mainly focused on the performance improvement of overall system. But, in some applications, it is necessary to evaluate how well the MCI (Motion Compensated Interpolation) frame matches the original frame. For this aim, this paper deals with the modeling methods for evaluating the block-based matching cost. First, several matching criteria, which have already been dealt with the motion compensated frame interpolation, are introduced and then combined to make estimate models for the size of MSE (Mean Square Error) noise of the MCI frame to original one. Through computer simulations, it is shown that the block-based matching criteria are evaluated and the proposed model can be effectively used for estimating the MSE noise.

A Prediction Model of Piston Slap Induced Vibration Velocity of Engine Block Surface (피스톤 슬랩에 의해 발생되는 엔진 블록의 표면 진동 속도 예측 모델)

  • 안상태;조성호;김양한;이동수
    • Journal of KSNVE
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    • v.9 no.3
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    • pp.587-592
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    • 1999
  • Piston slap is one of the sources producing engine block surface vibration and mechanical noise. To analyze piston slap-induced vibration, a realistic but simple model is proposed and verified experimentally. A piston is modeled by 3 degree of freedom system and an impact point between piston skirt and cylinder wall by 2 degree of freedom system. Numerical simulation estimates impact forces of piston in cylinder, and the engine block surface vibration response is predicted by the convoluton of the impact forces with measured impulse responses. Experimental verification on the predicted response has been also performed by using a commercial 4-cylinder diesel engine. the predicted and experimental vibration responses confirm that the suggested model is practically useful.

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Nominal flexural strength of high-strength concrete beams

  • Al-Kamal, Mustafa Kamal
    • Advances in concrete construction
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    • v.7 no.1
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    • pp.1-9
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    • 2019
  • The conventional ACI rectangular stress block is developed on the basis of normal-strength concrete column tests and it is still being used for the design of high-strength concrete members. Many research papers found in the literature indicate that the nominal strength of high-strength concrete members appears to be over-predicted by the ACI rectangular stress block. This is especially true for HSC columns. The general shape of the stress-strain curve of high-strength concrete becomes more likely as a triangle. A triangular stress block is, therefore, introduced in this paper. The proposed stress block is verified using a database which consists of 52 tested singly reinforced high-strength concrete beams having concrete strength above 55 MPa (8,000 psi). In addition, the proposed model is compared with models of various design codes and proposals of researchers found in the literature. The nominal flexural strengths computed using the proposed stress block are in a good agreement with the tested data as well as with that obtained from design codes models and proposals of researchers.

A STUDY ON THERMAL MODEL REDUCTION ALGORITHM FOR SATELLITE PANEL (인공위성 패널 열해석모델 간소화 알고리즘 연구)

  • Kim, Jung-Hoon;Jun, Hyoung Yoll;Kim, Seung Jo
    • Journal of computational fluids engineering
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    • v.17 no.4
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    • pp.9-15
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    • 2012
  • Thermal model reduction algorithms and techniques are introduced to condense a huge satellite panel thermal model into the simplified model on the purpose of calculating the thermal responses of a satellite on orbit. Guyan condensation algorithm with the substitution matrix manipulation is developed and the mathematical procedure is depicted step by step. A block-form LU decomposition method is also invited to compare the developed algorithm. The constructed reduced thermal model induced from the detailed model based on a real satellite panel is satisfying the correlation criterion of ${\pm}2^{\circ}C$ for the validity accuracy. Guyan condensation algorithm is superior to the block-form LU decomposition method on computation time.

Fatigue reliability analysis of steel bridge welding member by fracture mechanics method

  • Park, Yeon-Soo;Han, Suk-Yeol;Suh, Byoung-Chul
    • Structural Engineering and Mechanics
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    • v.19 no.3
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    • pp.347-359
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    • 2005
  • This paper attempts to develop the analytical model of estimating the fatigue damage using a linear elastic fracture mechanics method. The stress history on a welding member, when a truck passed over a bridge, was defined as a block loading and the crack closure theory was used. These theories explain the influence of a load on a structure. This study undertook an analysis of the stress range frequency considering both dead load stress and crack opening stress. A probability method applied to stress range frequency distribution and the probability distribution parameters of it was obtained by Maximum likelihood Method and Determinant. Monte Carlo Simulation which generates a probability variants (stress range) output failure block loadings. The probability distribution of failure block loadings was acquired by Maximum likelihood Method and Determinant. This can calculate the fatigue reliability preventing the fatigue failure of a welding member. The failure block loading divided by the average daily truck traffic is a predictive remaining life by a day. Fatigue reliability analysis was carried out for the welding member of the bottom flange of a cross beam and the vertical stiffener of a steel box bridge by the proposed model. Results showed that the primary factor effecting failure time was crack opening stress. It was important to decide the crack opening stress for using the proposed model. Also according to the 50% reliability and 90%, 99.9% failure times were indicated.

The Model Test on Load Reduction Effect of Caps Foundation Method (캡스기초공법의 하중경감효과에 관한 모형시험)

  • Park, Jong-Man;Kang, Chi-Gwang;Kwak, Jung-Min;Han, Sang-Ho
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.20 no.11
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    • pp.479-486
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    • 2019
  • The caps foundation method can reduce the load of a building by using the arching effect, but verification of the method is still insufficient. In this paper, a model test was performed to quantitatively prove the load reduction effect by this method. The test was carried out using six conditions according to the size of caps foundation block and the area of the loading plate. The test results show that the earth pressure was the highest at the position closest to the loading point regardless of the size of caps foundation block and the area of the loading plate. At the highest earth pressure position, when the loading plate area was 30 cm × 30 cm, the earth pressure of a small block was reduced by 35.4% on average, and that of a big block was reduced by 39.7% compared to the pressure with no block. When the loading plate area was 60 cm × 60 cm, the earth pressure of the small block was reduced by 33.9% on average, and the earth pressure of the big block was reduced by 42.7%. Therefore, if the caps foundation method is applied, the load will be reduced by more than 33% for a small block and 39% for a big block.

Transaction Model Suggestion by using Two Enforcements with a Blockchain based on a Service Platform (서비스 플랫폼 기반 이중강화적용 블록체인 응용 거래모델 제안)

  • Lee, Kwan Mok;Kim, Yong Hwan;Bae, Ki Tae
    • Smart Media Journal
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    • v.9 no.4
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    • pp.91-96
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    • 2020
  • A blockchain is a technology in which all nodes participating in a distributed network manage each transaction's contents without a central server managing the transaction, which is a record of the transaction. The block containing the transaction record of a specific period is connected to the blockchain by referring to the hash value for the previous block, and the chain with the new block added is shared with all nodes again. Transactions using existing certificates will pass through FinTech, and in the near future, applications using blockchains are expected to emerge. In this study, we analyze the problems of the existing model, and propose a transaction model that applies the blockchain to come. Among various applications, this study develops a trading model targeting the energy sales market among the topics that will lead the fourth industrial revolution. As a result of analyzing the proposed model, it was possible to be sure of the possibility of a safer energy sales transaction than the existing method.

A White-box Implementation of SEED

  • Kim, Jinsu
    • Journal of Advanced Information Technology and Convergence
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    • v.9 no.2
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    • pp.115-123
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    • 2019
  • White-box cryptography is an implementation technique in order to protect secret keys of cryptographic algorithms in the white-box attack model, which is the setting that an adversary has full access to the implementation of the cryptographic algorithm and full control over their execution. This concept was introduced in 2002 by Chow et al., and since then, there have been many proposals for secure implementations. While there have been many approaches to construct a secure white-box implementation for the ciphers with SPN structures, there was no notable result about the white-box implementation for the block ciphers with Feistel structure after white-box DES implementation was broken. In this paper, we propose a secure white-box implementation for a block cipher SEED with Feistel structure, which can prevent the previous known attacks for white-box implementations. Our proposal is simple and practical: it is performed by only 3,376 table lookups during each execution and the total size of tables is 762.5 KB.

Graph Convolutional - Network Architecture Search : Network architecture search Using Graph Convolution Neural Networks (그래프 합성곱-신경망 구조 탐색 : 그래프 합성곱 신경망을 이용한 신경망 구조 탐색)

  • Su-Youn Choi;Jong-Youel Park
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.1
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    • pp.649-654
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    • 2023
  • This paper proposes the design of a neural network structure search model using graph convolutional neural networks. Deep learning has a problem of not being able to verify whether the designed model has a structure with optimized performance due to the nature of learning as a black box. The neural network structure search model is composed of a recurrent neural network that creates a model and a convolutional neural network that is the generated network. Conventional neural network structure search models use recurrent neural networks, but in this paper, we propose GC-NAS, which uses graph convolutional neural networks instead of recurrent neural networks to create convolutional neural network models. The proposed GC-NAS uses the Layer Extraction Block to explore depth, and the Hyper Parameter Prediction Block to explore spatial and temporal information (hyper parameters) based on depth information in parallel. Therefore, since the depth information is reflected, the search area is wider, and the purpose of the search area of the model is clear by conducting a parallel search with depth information, so it is judged to be superior in theoretical structure compared to GC-NAS. GC-NAS is expected to solve the problem of the high-dimensional time axis and the range of spatial search of recurrent neural networks in the existing neural network structure search model through the graph convolutional neural network block and graph generation algorithm. In addition, we hope that the GC-NAS proposed in this paper will serve as an opportunity for active research on the application of graph convolutional neural networks to neural network structure search.

Deep Learning Braille Block Recognition Method for Embedded Devices (임베디드 기기를 위한 딥러닝 점자블록 인식 방법)

  • Hee-jin Kim;Jae-hyuk Yoon;Soon-kak Kwon
    • Journal of Korea Society of Industrial Information Systems
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    • v.28 no.4
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    • pp.1-9
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    • 2023
  • In this paper, we propose a method to recognize the braille blocks for embedded devices in real time through deep learning. First, a deep learning model for braille block recognition is trained on a high-performance computer, and the learning model is applied to a lightweight tool to apply to an embedded device. To recognize the walking information of the braille block, an algorithm is used to determine the path using the distance from the braille block in the image. After detecting braille blocks, bollards, and crosswalks through the YOLOv8 model in the video captured by the embedded device, the walking information is recognized through the braille block path discrimination algorithm. We apply the model lightweight tool to YOLOv8 to detect braille blocks in real time. The precision of YOLOv8 model weights is lowered from the existing 32 bits to 8 bits, and the model is optimized by applying the TensorRT optimization engine. As the result of comparing the lightweight model through the proposed method with the existing model, the path recognition accuracy is 99.05%, which is almost the same as the existing model, but the recognition speed is reduced by 59% compared to the existing model, processing about 15 frames per second.