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| 1 | Moisture profiles and shrinkage in early-age concrete pavements显示文摘 | Seungwook Lim Jin-Hoon Jeong Dan G. Zollinger | 2009 | International Journal of Pavement Engineering2009，，1： | 1 |
| 2 | Influence of stoichiometry and alkalinity on barium hexaferrite formation via the supercritical water crystallization method显示文摘 | Seungwook Rho Sangdo Park | 2002 | Korean Journal of Chemical Engineering2002，，1： | 1 |
| 3 | A classification of literature on determining the lot size under quantity discounts显示文摘 | Benton W C Park Seungwook | 1996 | European Journal of Operational Research1996，92，2： | 1 |
| 4 | Quality management practices and their relationship to buyer's supplier ratings: a study in the Korean automotive industry 显示文摘 | Seungwook Park Janet L Hartley Darryl Wilson | 2001 | Journal of Operations Management2001，19，： | 1 |
| 5 | 用于耐气候花岗岩填充土壤加固的复合土工合成材料的拉伸特性和排水作用显示文摘本项研究的最终目的是使加强土墙体系系统化 ,该体系在包含大量低渗透性细小颗粒的风化花岗岩回填土中使用复合土工合成材料。作为达到此目的的阶段性努力 ,进行了试验室的拉伸试验并建立了有限元模型 ,以便分析由抗拉强度较好的土工格栅和排水性能良好的土工布组成的复合土工合成材料的摩擦性能和相互作用。基于有限差分数字模型的分析 ,测试了放在土工格栅下面的土工布的排水性能。从目前的研究可以推断 ,风化花岗岩回填土中的复合土工合成材料或许可用于减少变形和增加抗拉强度 。 | Hongtaek Kim Seungwook Kim Hanyong Jeon Hankyu Yoo 陈霞 梁洪丽 | 2001 | 产业用纺织品2001，19，9： | 0 |
| 6 | Adaptive Electrospinning System Based on Reinforcement Learning for Uniform‑Thickness Nanofiber Air Filters显示文摘Electrospinning is a simple and versatile method to produce nanofiber filters.However,owing to bending instability that occurs during the electrospinning process,electrospinning has frequently produced a non-uniform-thickness nanofiber filter,which deteriorates its air filtration.Here,an adaptive electrospinning system based on reinforcement learning(E-RL)was developed to produce uniform-thickness nanofiber filters.The E-RL accomplished a real-time thickness measurement of an electrospun nanofiber filter by measuring the transmitted light through the nanofiber filter using a camera placed at the bottom of the collector and converting it into thickness using the Beer–Lambert law.Based on the measured thickness,the E-RL detected the non-uniformity of the nanofiber filter thickness and manipulated the movable collector to alleviate the non-uniformity of the thickness by a pre-trained reinforcement learning(RL)algorithm.For the training of the RL algo-rithm,the nanofiber production simulation software based on the empirical model of the deposition of the nanofiber filter was developed,and the training process of the RL algorithm was repeated until the optimal policy was achieved.After the training process with the simulation software,the trained model was transferred to the adaptive electrospinning system.By the movement of the collector under the optimal strategy of RL algorithm,the non-uniformity of such nanofiber filters was significantly reduced by approximately five times in standard deviation and error for both simulation and experiment.This finding has great potential in improving the reliability of electrospinning process and nanofiber filters used in research and industrial fields such as environment,energy,and biomedicine. | Seok Hyeon Hwang Jin Yeong Song Hyun Il Ryu Jae Hee Oh Seungwook Lee Donggeun Lee Dong Yong Park Sang Min Park | 2023 | Advanced Fiber Materials2023，5，2： | 0 |
| 7 | Correction to:Adaptive Electrospinning System Based on Reinforcement Learning for Uniform‑Thickness Nanofiber Air Filters显示文摘Correction to:Advanced Fiber Materials https://doi.org/10.1007/s42765-022-00247-3 In this article the author name Dong Yong Park was incorrectly written as Dong Young Park.The original article has been corrected.Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. | Seok Hyeon Hwang Jin Yeong Song Hyun Il Ryu Jae Hee Oh Seungwook Lee Donggeun Lee Dong Yong Park Sang Min Park | 2023 | Advanced Fiber Materials2023，5，2： | 0 |
| 8 | Use of Local Region Maps on Convolutional LSTM for Single-Image HDR Reconstruction显示文摘Low dynamic range(LDR)images captured by consumer cameras have a limited luminance range.As the conventional method for generating high dynamic range(HDR)images involves merging multiple-exposure LDR images of the same scene(assuming a stationary scene),we introduce a learning-based model for single-image HDR reconstruction.An input LDR image is sequentially segmented into the local region maps based on the cumulative histogram of the input brightness distribution.Using the local region maps,SParam-Net estimates the parameters of an inverse tone mapping function to generate a pseudo-HDR image.We process the segmented region maps as the input sequences on long short-term memory.Finally,a fast super-resolution convolutional neural network is used for HDR image reconstruction.The proposed method was trained and tested on datasets including HDR-Real,LDR-HDR-pair,and HDR-Eye.The experimental results revealed that HDR images can be generated more reliably than using contemporary end-to-end approaches. | Seungwook Oh GyeongIk Shin Hyunki Hong | 2022 | Computers, Materials & Continua2022，，6： | 0 |
| 9 | 摄食大豆蛋白降低猫血浆中牛磺酸显示文摘经大鼠实验,已知大豆蛋白可降低胆固醇和影响胆汁酸代谢,且猫食中蛋白质的数量和质量变化很大。基于这些原因,在本文中,将描述膳食大豆蛋白与酪蛋白、大豆纤维物质对猫的牛磺酸水平的影响。 | SEUNGWOOK W.KIM 张牧 | 1997 | 肉品卫生1997，，4： | 0 |
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