• Journal of the Korean Society of Radiology
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• v.10 no.2
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• pp.73-79
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• 2016

The purpose of this analysis is to compare 2D T1 FEE and 3D T1 THRIVE for demonstration of the pancreas. A total of 85(45 men, 40 women; 58 years) PACS network datum were analysis clinically indicated pancreas MRI at 1.5 T. The SNRs and CNRs of 3D T1 THRIVE(SNR: $46.42{\pm}0.67$, CNR: $28.16{\pm}0.50$) showed significantly higher values than those from 2D T1 FEE(SNR: $53.84{\pm}1.20$, CNR: $35.48{\pm}0.70$), p<0.05, The image quality of the 3D T1 THRIVE($2.63 {\pm}0.14$) was significantly superior to that with the 2D T1 FEE($2.2{\pm}0.05$), but 3D T1 THRIVE revealed several artifacts resulting in poor quality. In conclusion, The 3D T1 THRIVE technique with a 1.5 T resulting in improved SNRs, CNRs and image quality was demonstrated.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.07a
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• pp.573-576
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• 2022

본 논문에서는 삼각형 구조로 구성된 3차원 메쉬(Mesh)에서 합성곱 신경망(Convolutional Neural Network, CNN)의 정확도를 개선시킬 수 있는 새로운 학습 표현 기법을 제시한다. 우리는 메쉬를 구성하고 있는 삼각형의 넓이와 그 로컬 특징을 기반으로 학습을 진행한다. 일반적으로 딥러닝은 인공신경망을 수많은 계층 형태로 연결한 기법을 말하며, 주요 처리 대상은 오디오 파일과 이미지이었다. 인공지능에 대한 연구가 지속되면서 3차원 딥러닝이 도입되었지만, 기존의 학습과는 달리 3차원 학습은 데이터의 확보가 쉽지 않다. 혼합현실과 메타버스 시장으로 인해 3차원 모델링 시장이 증가가 하면서 기술의 발전으로 데이터를 획득할 수 있는 방법이 생겼지만, 3차원 데이터를 직접적으로 학습 표현하는 방식으로 적용하는 것은 쉽지 않다. 그렇기 때문에 본 논문에서는 산업 현장에서 사용되는 데이터인 삼각형 메쉬 구조를 바탕으로 기존 방법보다 정확도가 높은 학습 기법을 제안한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.01a
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• pp.369-372
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• 2023

본 논문에서는 삼각형 구조로 구성된 3차원 메쉬(Mesh)에서 합성곱 신경망(Convolution Neural Network, CNN)을 응용하여 정확도가 높은 새로운 학습 표현 기법을 제시한다. 우리는 메쉬를 구성하고 있는 폴리곤의 edge와 face의 로컬 특징을 기반으로 학습을 진행한다. 일반적으로 딥러닝은 인공신경망을 수많은 계층 형태로 연결한 기법을 말하며, 주요 처리 대상은 1, 2차원 데이터 형태인 오디오 파일과 이미지였다. 인공지능에 대한 연구가 지속되면서 3차원 딥러닝이 도입되었지만, 기존의 학습과는 달리 3차원 딥러닝은 데이터의 확보가 쉽지 않다. 혼합현실과 메타버스 시장의 확대로 인해 3차원 모델링 시장이 증가하고, 기술의 발전으로 데이터를 획득할 수 있는 방법이 생겼지만, 3차원 데이터를 직접적으로 학습에 이용하는 방식으로 적용하는 것은 쉽지 않다. 그렇게 때문에 본 논문에서는 산업 현장에서 이용되는 데이터인 메쉬 구조를 폴리곤의 최소 단위인 삼각형 형태로 구성하여 학습 데이터를 구성해 기존의 방법보다 정확도가 높은 학습 기법을 제안한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.11
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• pp.5276-5298
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• 2019

Internet of Things (IoT) based sensor networks have gained unprecedented popularity in recent years. With the exponential explosion of the objects (sensors and mobiles), the bandwidth and the speed of data transmission are dwarfed by the anticipated emergence of IoT. In this paper, we propose a novel heterogeneous IoT model integrated the power line communication (PLC) and WiFi network to increase the network capacity and cope with the rapid growth of the objects. We firstly propose the mean transmission delay calculation algorithm based the 3D Markov chain according to the multi-priority of the objects. Then, the attractor selection algorithm, which is based on the adaptive behavior of the biological system, is exploited. The combined the 3D Markov chain and the attractor selection model, named MASM, can select the optimal path adaptively in the heterogeneous IoT according to the environment. Furthermore, we verify that the MASM improves the transmission efficiency and reduce the transmission delay effectively. The simulation results show that the MASM is stable to changes in the environment and more applicable for the heterogeneous IoT, compared with the other algorithms.

• Journal of information and communication convergence engineering
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• v.5 no.2
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• pp.83-87
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• 2007

This research studies real time interaction and dynamic data shared through 3D scenes in virtual network environments. In a distributed virtual environment of client-server structure, consistency is maintained by the static information exchange; as jerks occur by packet delay when updating messages of dynamic data exchanges are broadcasted disorderly, the network bottleneck is reduced by predicting the movement path by using the Dead-reckoning algorithm. In Dead-reckoning path prediction, the error between the estimated and the actual static values which is over the threshold based on the shared object location requires interpolation and multicasting of the previous location by the ESPDU of DIS. The shared dynamic data of the 3D virtual environment is implementation using the VRML.

• Transactions of Materials Processing
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• v.8 no.4
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• pp.331-339
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• 1999

In this study, to analyze the shaped drawing process from round bar, the practical conical die with considering die radius and bearing was defined by a mathematical expression, and also a simple technique for initial mesh generation to the shaped drawing process was proposed. The drawing of rectangular section from round bar, one of the shaped drawing process, has been simulated by using non-steady state 3D rigid plastic finite element method in order to evaluate the influence of semi-die angle and reduction in area to corner filling. Other process variables such as friction constant, rectangular ratio, die radius and bearing length were fixed during the simulation. An artificial neural network has been introduced to obtain the optimal process conditions which gave rise to a fast simulation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.2
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• pp.1118-1133
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• 2017

Computer vision-based human activity recognition (HAR) has become very famous these days due to its applications in various fields such as smart home healthcare for elderly people. A video-based activity recognition system basically has many goals such as to react based on people's behavior that allows the systems to proactively assist them with their tasks. A novel approach is proposed in this work for depth video based human activity recognition using joint-based motion features of depth body shapes and Deep Belief Network (DBN). From depth video, different body parts of human activities are segmented first by means of a trained random forest. The motion features representing the magnitude and direction of each joint in next frame are extracted. Finally, the features are applied for training a DBN to be used for recognition later. The proposed HAR approach showed superior performance over conventional approaches on private and public datasets, indicating a prominent approach for practical applications in smartly controlled environments.

• Electronics and Telecommunications Trends
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• v.35 no.2
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• pp.89-103
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• 2020

Knowledge of the technology, characteristics, and market trends of the latest CPUs used in smartphones, computers, and supercomputers and the research trends of leading US university experts gives an edge to policy-makers, business executives, large investors, etc. To this end, we describe three topics in detail at a level that can help educate the non-majors to the extent possible. Topic 1 comprises the design and manufacture of a CPU and the technology and trends of the smartphone SoC. Topic 2 comprises the technology and trends of the x86 CPU and supercomputer, and Topic 3 involves an optical network chip that has the potential to emerge as a major semiconductor chip. We also describe three techniques and experiments that can be used to implement the optical network chip.

• Electronics and Telecommunications Trends
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• v.35 no.2
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• pp.120-136
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• 2020

Knowledge of the technology, characteristics, and market trends of the latest CPUs used in smartphones, computers, and supercomputers and the research trends of leading US university experts gives an edge to policy-makers, business executives, large investors, etc. To this end, we describe three topics in detail at a level that can help educate the non-majors to the extent possible. Topic 1 comprises the design and manufacture of a CPU and the technology and trends of the smartphone SoC. Topic 2 comprises the technology and trends of the x86 CPU and supercomputer, and Topic 3 involves an optical network chip that has the potential to emerge as a major semiconductor chip. We also describe three techniques and experiments that can be used to implement the optical network chip.

• Electronics and Telecommunications Trends
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• v.35 no.2
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• pp.104-119
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• 2020

Knowledge of the technology, characteristics, and market trends of the latest CPUs used in smartphones, computers, and supercomputers and the research trends of leading US university experts gives an edge to policy-makers, business executives, large investors, etc. To this end, we describe three topics in detail at a level that can help educate the non-majors to the extent possible. Topic 1 comprises the design and manufacture of a CPU and the technology and trends of the smartphone SoC. Topic 2 comprises the technology and trends of the x86 CPU and supercomputer, and Topic 3 involves an optical network chip that has the potential to emerge as a major semiconductor chip. We also describe three techniques and experiments that can be used to implement the optical network chip.