• Title/Summary/Keyword: Fusion Model

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Mathematical Modeling of Scheduling Problems for the Fusion Fuel Cycle (핵융합 공정주기에서의 생산 계획 최적화)

  • Lee, Suh-Young;Ha, Jin-Kuk;Lee, In-Beum;Lee, Euy Soo
    • Korean Chemical Engineering Research
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    • v.58 no.4
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    • pp.596-603
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    • 2020
  • In this study, a mathematical model for optimal operation of the fusion fuel cycle is developed based on scheduling approach. The fusion fuel cycle consists of a system for storing and supplying deuterium and tritium, and receiving and separating process after the fusion reaction. Except that tritium is a radioactive material, most of these processes consist of catalytic reactions and separation process. For these reasons, it is possible to apply scheduling approach which is also widely utilized to chemical plants to derive the optimal operating scenarios. The developed model determined the optimal regeneration cycle to minimize the amount of tritium inside the vacuum pumps. Based on the characteristics of various device in the fusion reactor, the optimal tritium plant operation scenario is evaluated. The formulated model was applied to the actual tokamak scenario and utilized to analyze the fuel flow and balance of ITER fuel cycle.

Effective Multi-Modal Feature Fusion for 3D Semantic Segmentation with Multi-View Images (멀티-뷰 영상들을 활용하는 3차원 의미적 분할을 위한 효과적인 멀티-모달 특징 융합)

  • Hye-Lim Bae;Incheol Kim
    • KIPS Transactions on Software and Data Engineering
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    • v.12 no.12
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    • pp.505-518
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    • 2023
  • 3D point cloud semantic segmentation is a computer vision task that involves dividing the point cloud into different objects and regions by predicting the class label of each point. Existing 3D semantic segmentation models have some limitations in performing sufficient fusion of multi-modal features while ensuring both characteristics of 2D visual features extracted from RGB images and 3D geometric features extracted from point cloud. Therefore, in this paper, we propose MMCA-Net, a novel 3D semantic segmentation model using 2D-3D multi-modal features. The proposed model effectively fuses two heterogeneous 2D visual features and 3D geometric features by using an intermediate fusion strategy and a multi-modal cross attention-based fusion operation. Also, the proposed model extracts context-rich 3D geometric features from input point cloud consisting of irregularly distributed points by adopting PTv2 as 3D geometric encoder. In this paper, we conducted both quantitative and qualitative experiments with the benchmark dataset, ScanNetv2 in order to analyze the performance of the proposed model. In terms of the metric mIoU, the proposed model showed a 9.2% performance improvement over the PTv2 model using only 3D geometric features, and a 12.12% performance improvement over the MVPNet model using 2D-3D multi-modal features. As a result, we proved the effectiveness and usefulness of the proposed model.

Visual Attention Model Based on Particle Filter

  • Liu, Long;Wei, Wei;Li, Xianli;Pan, Yafeng;Song, Houbing
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.8
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    • pp.3791-3805
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    • 2016
  • The visual attention mechanism includes 2 attention models, the bottom-up (B-U) and the top-down (T-D), the physiology of which have not yet been accurately described. In this paper, the visual attention mechanism is regarded as a Bayesian fusion process, and a visual attention model based on particle filter is proposed. Under certain particular assumed conditions, a calculation formula of Bayesian posterior probability is deduced. The visual attention fusion process based on the particle filter is realized through importance sampling, particle weight updating, and resampling, and visual attention is finally determined by the particle distribution state. The test results of multigroup images show that the calculation result of this model has better subjective and objective effects than that of other models.

A Numerical Investigation of Hydrogen Absorption Reaction Based on ZrCo for Tritium Storage (I) (삼중수소 저장을 위한 ZrCo 저장재에서의 수소 흡장에 대한 수치해석적 연구 (I))

  • Yoo, Haneul;Yun, Seihun;Chang, Minho;Kang, Hyungoo;Ju, Hyunchul
    • Transactions of the Korean hydrogen and new energy society
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    • v.23 no.5
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    • pp.448-454
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    • 2012
  • In this paper, a three-dimensional hydrogen absorption model is applied to a thin double-layered annulus ZrCo hydride bed and validated against the temperature evolution data measured by Kang et al. The present model reasonably captures the bed temperature evolution behavior and the 99% hydrogen charging time. The equilibrium pressure expression for hydrogen absorption on ZrCo is derived as a function of temperature and the H/M atomic ratio based on the pressure-composition isotherm data given by Konishi et al. In addition, this present model provides multi-dimensional contours such as temperature and H/M atomic ratio in the thin doublelayered annulus metal hydride region. This numerical study provides fundamental understanding during hydrogen absorption process and indicates that efficient design of the metal hydride bed is critical to achieve rapid hydrogen charging performance. The present three-dimensional hydrogen absorption model is a useful tool for the optimization of bed design and operating conditions.

Simulation of Mobile Robot Navigation based on Multi-Sensor Data Fusion by Probabilistic Model

  • Jin, Tae-seok
    • Journal of the Korean Society of Industry Convergence
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    • v.21 no.4
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    • pp.167-174
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    • 2018
  • Presently, the exploration of an unknown environment is an important task for the development of mobile robots and mobile robots are navigated by means of a number of methods, using navigating systems such as the sonar-sensing system or the visual-sensing system. To fully utilize the strengths of both the sonar and visual sensing systems, In mobile robotics, multi-sensor data fusion(MSDF) became useful method for navigation and collision avoiding. Moreover, their applicability for map building and navigation has exploited in recent years. In this paper, as the preliminary step for developing a multi-purpose autonomous carrier mobile robot to transport trolleys or heavy goods and serve as robotic nursing assistant in hospital wards. The aim of this paper is to present the use of multi-sensor data fusion such as ultrasonic sensor, IR sensor for mobile robot to navigate, and presents an experimental mobile robot designed to operate autonomously within indoor environments. Simulation results with a mobile robot will demonstrate the effectiveness of the discussed methods.

Numerical Investigation of RF Pulsing Effect on Ion Energy Distributions at RF-biased Electrodes

  • Kwon, Deuk-Chul;Song, Mi-Young;Yoon, Jung-Sik
    • Applied Science and Convergence Technology
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    • v.23 no.5
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    • pp.265-272
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    • 2014
  • The ion energy distributions (IEDs) arriving at a substrate strongly affect the etching rates in plasma etching processes. In order to determine the IEDs accurately, it is important to obtain the characteristics of radio frequency (rf) sheath at pulsed rf substrates. However, very few studies have been conducted to investigate pulsing effect on IEDs at multiple rf driven electrodes. Therefore, in this work, we extended previous one-dimensional dynamics model for pulsed-bias electrodes. We obtained the IEDs using the developed rf sheath model and observed that numerically solved IEDs are in a good agreement with the experimental results.

A Study on the Introduction of Livestock U-healthcare (가축 U-Healthcare 도입방안 연구)

  • Koo, Jee-Hee;Jung, Tae-Woong;Ahn, Ji-Yeon;Lee, Sang-Rak
    • Journal of Animal Environmental Science
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    • v.18 no.2
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    • pp.85-90
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    • 2012
  • In Korea, livestock has grown into the most value-added business in the agricultural and forest industry. But due to the recent outbreak of deadly infectious diseases such as foot-and-mount disease and avian influenza (AI), the demand for IT-enabled cutting-edge management system is getting stronger. As for humans, pilot projects and researches concerning U-healthcare have been carried out since early 2000. So this study explored the current progress of U-healthcare introduction, and suggested the strategies to develop technologies of collecting, processing, and utilizing information; to apply elements for a service model development and prioritization; to provide policy and institutional support. Therefore it is expected to vitalize the livestock U-healthcare in the future through continuous study based on these results.

Text Classification by Deep Learning Fusion (딥러닝 융합에 의한 텍스트 분류)

  • Shin, Kwang-Seong;Ham, Seo-Hyun;Shin, Seong-Yoon
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2019.07a
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    • pp.385-386
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    • 2019
  • This paper proposes a fusion model based on Long-Short Term Memory networks (LSTM) and CNN deep learning methods, and applied to multi-category news datasets, and achieved good results. Experiments show that the fusion model based on deep learning has greatly improved the precision and accuracy of text sentiment classification.

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Suboptimal Decision Fusion in Wireless Sensor Networks under Non-Gaussian Noise Channels (비가우시안 잡음 채널을 갖는 무선 센서 네트워크의 준 최적화 결정 융합에 관한 연구)

  • Park, Jin-Tae;Koo, In-Soo;Kim, Ki-Seon
    • Journal of Internet Computing and Services
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    • v.8 no.4
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    • pp.1-9
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    • 2007
  • Decision fusion in wireless sensor networks under non-Gaussian noise channels is studied. To consider the tail behavior noise distributions, we use a exponentially-tailed distribution as a wide class of noise distributions. Based on a canonical parallel fusion model with fading and noise channels, the likelihood ratio(LR) based fusion rule is considered as an optimal fusion rule under Neyman-Pearson criterion. With both high and low signal-to-noise ratio (SNR) approximation to the optimal rule, we obtain several suboptimal fusion rules. and we propose a simple fusion rule that provides robust detection performance with a minimum prior information, Performance evaluation for several fusion rules is peformed through simulation. Simulation results show the robustness of the Proposed simple fusion rule.

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Study on INS/GPS Sensor Fusion for Agricultural Vehicle Navigation System (농업기계 내비게이션을 위한 INS/GPS 통합 연구)

  • Noh, Kwang-Mo;Park, Jun-Gul;Chang, Young-Chang
    • Journal of Biosystems Engineering
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    • v.33 no.6
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    • pp.423-429
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    • 2008
  • This study was performed to investigate the effects of inertial navigation system (INS) / global positioning system (GPS) sensor fusion for agricultural vehicle navigation. An extended Kalman filter algorithm was adopted for INS/GPS sensor fusion in an integrated mode, and the vehicle dynamic model was used instead of the navigation state error model. The INS/GPS system was consisted of a low-cost gyroscope, an odometer and a GPS receiver, and its performance was tested through computer simulations. When measurement noises of GPS receiver were 10, 1.0, 0.5, and 0.2 m ($1{\sigma}$), RMS position and heading errors of INS/GPS system at 5 m/s straight path were remarkably reduced with 10%, 35%, 40%, and 60% of those obtained from the GPS receiver, respectively. The decrease of position and heading errors by using INS/GPS rather than stand-alone GPS can provide more stable steering of agricultural equipments. Therefore, the low-cost INS/GPS system using the extended Kalman filter algorithm may enable the self-autonomous navigation to meet required performance like stable steering or more less position errors even in slow-speed operation.