• Title/Summary/Keyword: Large-scale experiments

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Estimatation of Mean Velocity from Surface Velocity (표면유속을 이용한 평균유속 추정방법의 개발)

  • Roh, Young-Sin;Yoon, Byung-Man;Yu, Kwon-Kyu
    • Journal of Korea Water Resources Association
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    • v.38 no.11
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    • pp.917-925
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    • 2005
  • LSIV (Large Scale Image Velcocimetry) Is one of the image-based velocity measurement techniques. Since it measures surface velocities, it gives simple and inexpensive way to measure velocity, compared to other methods. Because of these advantages, there have been many studies to apply LSIV to the river discharge measurement in the field. Measuring the discharge by using LSIV requires a method which converts a surface velocity to a mean velocity In the present study, experiments and analysis of vortical velocity profile of open-channel flow in various conditions were performed to develop methods which estimate a mean velocity from a surface velocity. The result of this experiment reveals that velocity-dip phenomena occur at free-surface layer in open channel flow and Froude number affects more than bed roughness does. Two methods for estimating the mean velocity were proposed. One is to correct the wake law's profiles by using the difference of surface velocity from the mean velocity, and the other is to use the ratio of mean and surface velocities. The result of applying these methods in an experiment shows that they are quite accurate having an error of approximately $6\%$ only.

Affinity Filtration Chromatography of Proteins by Chitosan and Chitin Membranes: 1. Preparation and Characterization of Porous Affinity Membranes (키토산 및 키틴 막에 의한 단백질의 친화 여과 크로마토그래피: 1. 다공성 친화 막의 제조와 특성 평가)

  • Youm Kyung-Ho;Yuk Yeong-Jae
    • Membrane Journal
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    • v.16 no.1
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    • pp.39-50
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    • 2006
  • Porous chitosan and chitin membranes were prepared by using silica particles as porogen. Membrane preparation was achieved via the following three steps: (1) chitosan film formation by casting an chitosan solution containing silica particles, (2) preparation of porous chitosan membrane by dissolving the silica particles by immersing the film into an alkaline solution and (3) preparation of porous chitin membrane by acetylation of chitosan membrane with acetic anhydride. The optimum preparation conditions which could provide a chitosan and chitin membranes with good mechanical strength and adequate pure water flux were determined. To allow protein affinity, a reactive dye (Cibacron Blue 3GA) was immobilized on porous chitosan membrane. Binding capacities of affinity chitosan and chitin membranes for protein and enzyme were determined by the batch adsorption experiments of BSA protein and lysozyme enzyme. The maximum binding capacity of affinity chitosan membrane for BSA protein is about 22 mg/mL, and that of affinity chitin membrane for lysozyme enzyme is about 26 mg/mL. Those binding capacities are about $several{\sim}several$ tens times larger than those of chitosan and chitin-based hydrogel beads. Those results suggest that the porous chitosan and chitin membranes are suitable in affinity filtration chromatography for large scale separation of proteins.

Case Study on the Improvement of Pollutant Removal Efficiency in Sihwa Constructed Wetland (시화호 인공습지의 수질정화기능 향상을 위한 사례연구)

  • Choi, Don-Hyeok;Kang, Ho;Choi, Kwang-Soon
    • Journal of Wetlands Research
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    • v.12 no.2
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    • pp.25-33
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    • 2010
  • Three plans(induction of water flow, supply of oxygen into water, control of fish causing resuspension of solids) proposed to improve the pollutant removal efficiency of Sihwa Constructed Wetland(CW) were estimated by considering the their efficiency and application to the wetland. After construction of facility for induction of water flow in lower part(W 122m${\times}$L 103m) of the wetland, the mean removal efficiencies of BOD, SS, TN and TP were in range of 12.8~37.4% and BOD was showing the highest efficiency. This result indicates that water flows is one of very important factors in the pollutant removal of wetland, especially near the outlet of a large scale wetland such as Sihwa CW. Dissolved oxygen(DO) concentrations after operation of two oxygen supply systems such as Air Bubble Diffuser and Surface Aeration System increased 15.5% and 27.2%, respectively. For maintaining effective DO concentration in Sihwa CW, the operation of oxygen supply system may be desirable during midnight to dawn in the location in which DO concentration is not enough, for instance less than 2 mg/L in CW. In experiments of the fish removal from Sihwa CW, the mean turbidity was lower in test site(6.2 NTU) than control site(10.6). The removal efficiency of thurbidity by th fish removal from the wetland was 41.5%. Therefore, a relevant fish management through a periodical monitoring of fish and turbidity is needed.

Trajectory Indexing for Efficient Processing of Range Queries (영역 질의의 효과적인 처리를 위한 궤적 인덱싱)

  • Cha, Chang-Il;Kim, Sang-Wook;Won, Jung-Im
    • The KIPS Transactions:PartD
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    • v.16D no.4
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    • pp.487-496
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    • 2009
  • This paper addresses an indexing scheme capable of efficiently processing range queries in a large-scale trajectory database. After discussing the drawbacks of previous indexing schemes, we propose a new scheme that divides the temporal dimension into multiple time intervals and then, by this interval, builds an index for the line segments. Additionally, a supplementary index is built for the line segments within each time interval. This scheme can make a dramatic improvement in the performance of insert and search operations using a main memory index, particularly for the time interval consisting of the segments taken by those objects which are currently moving or have just completed their movements, as contrast to the previous schemes that store the index totally on the disk. Each time interval index is built as follows: First, the extent of the spatial dimension is divided onto multiple spatial cells to which the line segments are assigned evenly. We use a 2D-tree to maintain information on those cells. Then, for each cell, an additional 3D $R^*$-tree is created on the spatio-temporal space (x, y, t). Such a multi-level indexing strategy can cure the shortcomings of the legacy schemes. Performance results obtained from intensive experiments show that our scheme enhances the performance of retrieve operations by 3$\sim$10 times, with much less storage space.

Design and Implementation of IP Video Wall System for Large-scale Video Monitoring in Smart City Environments (스마트 시티 환경에서 대규모 영상 모니터링을 위한 IP 비디오 월 시스템의 설계 및 구현)

  • Yang, Sun-Jin;Park, Jae-Pyo;Yang, Seung-Min
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.20 no.9
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    • pp.7-13
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    • 2019
  • Unlike a typical video wall system, video wall systems used for integrated monitoring in smart city environments should be able to display various videos, images, and texts simultaneously. In this paper, we propose an Internet Protocol (IP)-based video wall system that has no limit on the number of videos that can be monitored simultaneously, and that can arrange the monitor screen layout without restrictions. The proposed system is composed of multiple display servers, a wall controller, and video source providers, and they communicate with each other through an IP network. Since the display server receives and decodes the video stream directly from the video source devices, and displays it on the attached monitor screens, more videos can be simultaneously displayed on the entire video wall. When one video is displayed over several screens attached to multiple display servers, only one display server receives the video stream and transmits it to the other display servers by using IP multicast communications, thereby reducing the network load and synchronizing the video frames. Experiments show that as the number of videos increases, a system consisting of more display servers shows better decoding and rendering performance, and there is no performance degradation, even if the display server continues to be expanded.

Marine ecosystem risk assessment using a land-based marine closed mesocosm: Proposal of objective impact assessment tool (육상 기반 해양 폐쇄형 인공생태계를 활용한 해양생태계 위해성 평가: 객관적인 영향 평가 tool 제시)

  • Yoon, Sung-Jin
    • Korean Journal of Environmental Biology
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    • v.39 no.1
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    • pp.88-99
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    • 2021
  • In this study, a land-based marine closed mesocosm (LMCM) experiment was performed to objectively assess the initial stability of an artificial ecosystem experiment against biological and non-biological factors when evaluating ecosystem risk assessment. Changes in the CV (coefficient of value) amplitude were used as data to analyze the stability of the experimental system. The CV of the experimental variables in the LMCM groups (200, 400, 600, and 1,000 L) was maintained within the range of 20-30% for the abiotic variables in this study. However, the difference in CV amplitude in biological factors such as chlorophyll-a, phytoplankton, and zooplankton was high in the 600 L and 1,000 L LMCM groups. This result was interpreted as occurring due to the lack of control over biological variables at the beginning of the experiment. In addition, according to the ANOVA results, significant differences were found in biological contents such as COD (chemical oxygen demand), chlorophyll-a, phosphate, and zooplankton in the CV values between the LMCM groups(p<0.05). In this study, the stabilization of biological variables was necessary to to control and maintain the rate of changes in initial biological variables except for controllable water quality and nutrients. However, given the complexity of the eco-physiological activities of large-scale LMCMs and organisms in the experimental group, it was difficult to do. In conclusion, artificial ecosystem experiments as a scientific tool can distinguish biological and non-biological factors and compare and analyze clear endpoints. Therefore, it is deemed necessary to establish research objectives, select content that can maintain stability, and introduce standardized analysis techniques that can objectively interpret the experimental results.

A Study on Future Changes of Sea Surface Temperature and Ocean Currents in Northwest Pacific through CMIP6 Model Analysis (CMIP6 모형 결과 분석을 통한 북서태평양 해면수온과 해류의 미래변화에 대한 고찰)

  • JEONG, SUYEON;CHOI, SO HYEON;KIM, YOUNG HO
    • The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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    • v.26 no.4
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    • pp.291-306
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    • 2021
  • From the climate change scenario experiments of 21 models participating in Coupled Climate Model Inter-comparison Project Phase 6, future changes of sea surface temperature (SST) and Kuroshio in the Northwest Pacific were analyzed. The spatial feature of SST change was found to be related to the change of the current speed and spatial distribution of Kuroshio. To investigate the relationship between the change in latitude of the Kuroshio extension region, which flows along the boundary between the subtropical gyre and the subarctic gyre in the North Pacific, and the large-scale atmospheric circulation due to global warming, the zero-windstress curl line for each climate change experiment from 9 out of 21 models were compared. As the atmospheric radiative forcing increases due to the increase of greenhouse gases, it was confirmed that the zero-windstress curl line moves northward, which is consistent with the observation. These results indicate that as the Hadley Circulation expands to the north due to global warming, the warming of the mid-latitudes to which the Korean Peninsula belongs may be accelerated. The volume transport and temperature of the Tsushima Warm Current flowing into the East Sea through the Korea Strait also increased as the atmospheric radiative forcing increased.

Development of online drone control management information platform (온라인 드론방제 관리 정보 플랫폼 개발)

  • Lim, Jin-Taek;Lee, Sang-Beom
    • Journal of the Institute of Convergence Signal Processing
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    • v.22 no.4
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    • pp.193-198
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    • 2021
  • Recently, interests in the 4th industry have increased the level of demand for pest control by farmers in the field of rice farming, and the interests and use of agricultural pest control drones. Therefore, the diversification of agricultural control drones that spray high-concentration pesticides and the increase of agricultural exterminators due to the acquisition of national drone certifications are rapidly developing the agricultural sector in the drone industry. In addition, as detailed projects, an effective platform is required to construct large-scale big data due to pesticide management, exterminator management, precise spraying, pest control work volume classification, settlement, soil management, prediction and monitoring of damages by pests, etc. and to process the data. However, studies in South Korea and other countries on development of models and programs to integrate and process the big data such as data analysis algorithms, image analysis algorithms, growth management algorithms, AI algorithms, etc. are insufficient. This paper proposed an online drone pest control management information platform to meet the needs of managers and farmers in the agricultural field and to realize precise AI pest control based on the agricultural drone pest control processor using drones and presented foundation for development of a comprehensive management system through empirical experiments.

Prediction of Beach Profile Change Using Machine Learning Technique (머신러닝을 이용한 해빈단면 변화 예측)

  • Shim, Kyu Tae;Cho, Byung Sun;Kim, Kyu Han
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.42 no.5
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    • pp.639-650
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    • 2022
  • In areas where large-scale sediment transport occurs, it is important to apply appropriate countermeasure method because the phenomenon tends to accelerate by time duration. Among the various countermeasure methods applied so far, beach nourishment needs to be reviewed as an erosion prevention measure because the erosion pattern is mitigated and environmentally friendly depending on the particle size. In the case of beach nourishment. a detailed review is required to determine the size, range, etc., of an appropriate particle diameter. In this study, we investigated the characteristics of the related topographic change using the change in the particle size of nourishment materials, the application of partial area, and the condition under the coexistence of waves and wind as variables because those factors are hard to be analyzed and interpreted within results and limitation of that the existing numerical models are not able to calculate and result out so that it is required that phenomenon or efforts are reviewed at the same time through physical model experiments, field monitoring and etc. So we attempt to reproduce the tendency of beach erosion and deposition and predict possible phenomena in the future using machine learning techniques for phenomena that it is not able to be interpreted by numerical models. we used the hydraulic experiment results for the training data, and the accuracy of the prediction results according to the change in the training method was simultaneously analyzed. As a result of the study it was found that topographic changes using machine learning tended to be similar to those of previous studies in short-term predictions, but we also found differences in the formation of scour and sandbars.

A modified U-net for crack segmentation by Self-Attention-Self-Adaption neuron and random elastic deformation

  • Zhao, Jin;Hu, Fangqiao;Qiao, Weidong;Zhai, Weida;Xu, Yang;Bao, Yuequan;Li, Hui
    • Smart Structures and Systems
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    • v.29 no.1
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    • pp.1-16
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    • 2022
  • Despite recent breakthroughs in deep learning and computer vision fields, the pixel-wise identification of tiny objects in high-resolution images with complex disturbances remains challenging. This study proposes a modified U-net for tiny crack segmentation in real-world steel-box-girder bridges. The modified U-net adopts the common U-net framework and a novel Self-Attention-Self-Adaption (SASA) neuron as the fundamental computing element. The Self-Attention module applies softmax and gate operations to obtain the attention vector. It enables the neuron to focus on the most significant receptive fields when processing large-scale feature maps. The Self-Adaption module consists of a multiplayer perceptron subnet and achieves deeper feature extraction inside a single neuron. For data augmentation, a grid-based crack random elastic deformation (CRED) algorithm is designed to enrich the diversities and irregular shapes of distributed cracks. Grid-based uniform control nodes are first set on both input images and binary labels, random offsets are then employed on these control nodes, and bilinear interpolation is performed for the rest pixels. The proposed SASA neuron and CRED algorithm are simultaneously deployed to train the modified U-net. 200 raw images with a high resolution of 4928 × 3264 are collected, 160 for training and the rest 40 for the test. 512 × 512 patches are generated from the original images by a sliding window with an overlap of 256 as inputs. Results show that the average IoU between the recognized and ground-truth cracks reaches 0.409, which is 29.8% higher than the regular U-net. A five-fold cross-validation study is performed to verify that the proposed method is robust to different training and test images. Ablation experiments further demonstrate the effectiveness of the proposed SASA neuron and CRED algorithm. Promotions of the average IoU individually utilizing the SASA and CRED module add up to the final promotion of the full model, indicating that the SASA and CRED modules contribute to the different stages of model and data in the training process.