• Title/Summary/Keyword: 망 분리

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Machine Parts(O-Ring) Defect Detection Using Adaptive Binarization and Convex Hull Method Based on Deep Learning (적응형 이진화와 컨벡스 헐 기법을 적용한 심층학습 기반 기계부품(오링) 불량 판별)

  • Kim, Hyun-Tae;Seong, Eun-San
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.25 no.12
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    • pp.1853-1858
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    • 2021
  • O-rings fill the gaps between mechanical parts. Until now, the sorting of defective products has been performed visually and manually, so classification errors often occur. Therefore, a camera-based defect classification system without human intervention is required. However, a binarization process is required to separate the required region from the background in the camera input image. In this paper, an adaptive binarization technique that considers the surrounding pixel values is applied to solve the problem that single-threshold binarization is difficult to apply due to factors such as changes in ambient lighting or reflections. In addition, the convex hull technique is also applied to compensate for the missing pixel part. And the learning model to be applied to the separated region applies the residual error-based deep learning neural network model, which is advantageous when the defective characteristic is non-linear. It is suggested that the proposed system through experiments can be applied to the automation of O-ring defect detection.

Analysis of Reduction Efficiency of Storm water and Pollutant in Filter Type and Clearance Type Permeable Blocks (침투형 및 틈새형 투수블럭에서의 빗물유출 및 오염물질 저감효율 분석)

  • Gil, Kyungik;Lee, Dawon
    • Proceedings of the Korea Water Resources Association Conference
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    • 2020.06a
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    • pp.210-210
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    • 2020
  • LID (Low Impact Development, 저영향개발)는 산업화 및 도시화 진행 지역에서 비점오염원으로부터 배출되는 오염물질을 제어해 개발지역 내 자연순화 기능을 최대한 유지하고, 물순환 기능증대를 통해 강우 유출수를 지역 내에서 관리하는 것을 목표로 한다. 비점오염원 저감 LID 시설에는 자연형과 장치형 시설이 있다. 자연형 시설에는 저류형, 침투, 식생형 시설 등이 있다. 특히, 침투시설에는 대표적으로 투수블럭이 있으며, 이는 투수성 포장재를 통해 강우 유출수를 지하로 침투시켜 여과나 흡착 등으로 비점오염물질을 제어하는 시설이다. 장치형 시설로는 여과재나 망을 이용해 비점오염물질을 분리하는 여과형 및 스크린형 시설, 응집과 침전을 통해 비점오염물질을 분리하는 응집·침전 시설 등이 있다. 이에 본 연구는 2016년부터 2018년 3년간 전주 서곡지구 지역 내 설치된 필터형 투수블럭, 틈새형 투수블럭에서 진행했다. 각각의 투수블럭에서 총 19회, 20회의 강우 모니터링을 실시했고, 오염물질 유입 및 유출 EMC 등의 분석을 통해 유출 및 오염물질 저감효과를 분석했다. 연구 대상 각 투수블럭의 주요 제원은 시설 용량 14.4㎥, 시설 면적은 14.4㎡이다. 모니터링 결과값을 분석한 결과 필터형 투수블럭의 경우 유출 저감율은 17.4 ~ 100%, 틈새형 투수블럭은 29.6 ~ 100%이었다. 필터형 투수블럭과 틈새형 투수블럭의 단위면적당 유량 저감량은 각각 0.014 ~ 0.583㎥/㎡, 0.035 ~ 0.588㎥/㎡이었다. 오염물질 저감효율을 분석한 결과 유기물 항목(BOD, TOC)의 경우 틈새형 투수블럭에서의 저감효율(BOD 93.59%, TOC 90.39%)이 필터형 투수블럭에서의 저감효율(BOD 89.99%, TOC 86.94%) 보다 다소 높게 나타났다. 영양염류 항목(T-N, T-P)의 경우 필터형, 틈새형 모두 비슷한 저감효율(필터형 T-N 89.02%, 필터형 T-P 98.12%, 틈새형 T-N 90.41%, 틈새형 T-P 98.04%)을 보였다.

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An investigation of effect of density difference on mixing at confluence channel in the Nakdong River (낙동강 합류부에서 밀도차가 수체 혼합에 미치는 영향 분석)

  • Lee, Minjae;Park, Yong Sung
    • Proceedings of the Korea Water Resources Association Conference
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    • 2022.05a
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    • pp.94-94
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    • 2022
  • 본류와 지류가 만나는 하천 합류부에서 발생하는 복잡한 흐름 구조는 하상변동에 영향을 주며, 본류와 다른 특성을 보이는 지류의 유입은 수질과 수생태계에도 영향을 준다. 합류부는 하천 변화의 다양성을 보이기 때문에 하천 관리 측면에서 중요한 구간으로, 흐름 및 혼합 특성 이해가 중요하다. 합류부에서의 흐름 및 혼합은 본류와 지류의 유량비, 밀도차, 단차, 합류각, 하도형상 등의 영향으로 그 양상이 달라지며, 흐름장 및 두 수체에 의한 이송물질의 혼합이 이루어졌다고 간주하는 혼합거리는 지류가 본류에 미치는 영향 범위 분석을 위한 중요한 매개변수이다. 본 연구에서는 합류부 흐름에 미치는 주요 인자 중 유량비와 밀도차가 합류부 흐름 및 혼합에 미치는 영향을 수치해석을 통해 분석하고, 조건의 변화에 따른 혼합거리를 예측해 보고자 한다. 본 연구의 대상 지역인 낙동강-황강 합류부는 다기능보와 댐의 운영에 따라 유입 유량 및 유량비가 조절되며, 여름철에는 황강의 수온이 낙동강보다 평균 4℃ 이상 낮으며, 9℃(지류 20℃; 본류 29℃) 이상의 수온차가 발생하기도 한다. 이 경우 밀도비는 0.998로 밀도류가 발생할 수 있는데, 밀도류가 발생할 경우 수표면과 저층이 분리되어 흐르기 때문에 동일 유량 조건에서도 혼합 양상은 달라진다. 밀도류가 발생하기 위해서는 수표면과 저층이 분리되는 성층이 발달해야 하는데, 이는 유속 또는 유량의 범위에 따라 성층의 발달 여부가 달라질 수 있다. 이러한 현장 조건을 반영한 수치해석을 통해 다양한 유량 조건(유량비)에서 밀도의 차이(수온차)가 합류부의 흐름 및 혼합에 미치는 영향을 분석해 보고자 하며, 합류부에서 밀도차에 의한 흐름의 변화 조건을 무차원수(Richardson number, Densimetric Froude number 등)를 통해 정량화해보고자 한다. 이는 지류가 본류에 미치는 영향의 정도와 범위를 파악함으로써 하천 관리를 위한 관측망 및 현장 조사의 범위 선정의 기초자료 마련뿐 아니라 본류의 수온 변화가 발생할 수 있는 범위의 파악을 통해 수생태계에 미치는 영향 파악을 위한 기초자료로 활용될 수 있을 것으로 기대된다.

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Evaluation of the Fiber Separation Method and Differences in the Storage Root Fiber Content among Sweetpotato (Ipomoea batatas L.) Varieties (고구마 괴근의 섬유질 분리 조건 탐색 및 품종별 섬유질 함량 차이)

  • Won Park;Im been Lee;Mi Nam Chung;Hyeong-Un Lee;Tae Hwa Kim;Kyo Hwui Lee;Sang Sik Nam
    • KOREAN JOURNAL OF CROP SCIENCE
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    • v.68 no.1
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    • pp.20-26
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    • 2023
  • Fiber content in the storage roots of sweetpotato varies between different varieties. For examples, the high fiber content of certain types has a poor texture when steamed or roasted. This study was conducted to evaluate the optimal sieve mesh size for separating fibers, the chemical composition of fibers and differences in fiber content among different varieties. We found that the separated fiber content (dry weight) of mashed and steamed sweetpotato was higher after washing three times (143.3 mg/100 g) compared with that washed five times (128.4 mg/100 g). The Hogammi variety remained 85.9% of total fiber content at 10 mesh (2,000 ㎛) and 9.6% of total fiber content at 30 mesh (600 ㎛), and Jinyulmi remained 74.9 and 16.7% of total fiber content , respectively. Therefore, a 30 mesh sieve was considered the most suitable for fiber separation. Among the 10 studied cultivars, Jinhongmi showed the lowest amount of fiber (24.8 mg/100 g) and Hogammi had the highest amount (111.4 mg/100 g), which was 4.5 times larger than that of Jinhongmi. Cellulose, hemicellulose and lignin content of separated fibers showed no difference between the viscous-type Hogammi and powdery-type Jinyulmi varieties, with averages of 32.5, 22.3 and 29.6%, respectively. Correlation results using the Image J program showed a significant correlation between the distribution of the stained area and the fiber content (R = 0.74, p < 0.05). Staining distribution differed among varieties, suggesting that a simple fiber content test could be performed using the staining method on raw sweetpotato. These results provide useful information to help inform farmers on the fiber content of different sweetpotato varieties.

Limited Indirect Acknowledgement for TCP Performance Enhancement over Wireless Networks (무선 망에서의 TCP 성능 향상을 위한 제한적인 Indirect-ACK)

  • 김윤주;이미정;안재영
    • Journal of KIISE:Information Networking
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    • v.30 no.2
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    • pp.233-243
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    • 2003
  • With the original Transmission Control Protocol(TCP) design, which is particularly targeted at the wired networks, a packet loss is assumed to be caused by the network congestion. In the wireless environment where the chances to lose packets due to transmission bit errors are not negligible, though, this assumption may result in unnecessary TCP performance degradation. In this paper, we propose three schemes that improve the ability to conceal the packet losses in the wireless network while limiting the degree of violating TCP end-to-end semantics to a temporary incidents. If there happens a packet loss at the wireless link and there is a chance that the loss is noticed by the sending TCP, the proposed schemes send an indirect acknowledgement. Each of the proposed schemes uses different criteria to decide whether there is a chance that the packet loss occurred in the wireless part is noticed by the sender. In order to limit the buffer overhead in the base, the indirect acknowledgements are issued only when the length of buffer is less than a certain threshold. We use simulation to compare the overhead and the performance of the proposed schemes, and to show that the proposed schemes improve the TCP performance compared to Snoop with a limited amount of buffer at the base station.

Development a Downscaling Method of Remotely-Sensed Soil Moisture Data Using Neural Networks and Ancillary Data (신경망기법과 보조 자료를 사용한 원격측정 토양수분자료의 Downscaling기법 개발)

  • Kim, Gwang-Seob;Lee, Eul-Rae
    • Journal of Korea Water Resources Association
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    • v.37 no.1
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    • pp.21-29
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    • 2004
  • The growth of water resources engineering associated with stable supply, management, development is essential to overcome the coming water deficit of our country. Large scale remote sensing and the analysis of sub-pixel variability of soil moisture fields are necessary in order to understand water cycle and to develop appropriate hydrologic model. The target resolution of coming Global monitoring of soil moisture field is about 10km which is not appropriate for the regional scale hydrologic model. Therefore, we need a downscaling scheme to generate hydrologic variables which are suitable for the regional hydrologic model. The results of the analysis of sub-pixel soil moisture variability show that the relationship between ancillary data and soil moisture fields shows there is very weak linear relationship. A downscaling scheme was developed using physically-based classification scheme and Neural Networks which are able to link the nonlinear relationship between ancillary data and soil moisture fields. The model is demonstrated by downscaling soil moisture fields from 4km to 0.2km resolution using remotely-sensed data from the Washita'92 experiment.

A Prepaid System Promotion Policy for the 3G MVNO - Carrier Selection, Interconnection, Number Portability, Prepay, Wholesale Provision - (3G MVNO를 통한 선불요금제 활성화 정책 - 선불요금, 상호접속, 사업자선택, 도매제공 및 번호이동 -)

  • Kim, Byung-Woon
    • Informatization Policy
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    • v.18 no.3
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    • pp.88-107
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    • 2011
  • This paper proposes a prepaid system promotion policy for the 3G(WCDMA) MVNO with regard to the newly included paragraphs 3, 4 and 5 of Article 32 (User Protection) and Article 38 (Provision of Wholesale Telecommunications Services) of the Telecommunication Business Act, which was revised on March 22, 2010. As of June 2011, there are only a few prepaid system subscribers to the mobile communications service due to various limitations, including prepay, interconnection, carrier selection, the MVNO policy, and number portability. However, overseas communications service regulatory agencies and service providers are increasingly presenting policies and strategies for mobile prepaid plans, in order to accommodate the various customer demands that are increasing the use of smart phones and data. This paper advances various proposals concerning promotion of the prepaid system by the 3G MVNO under the current Telecommunication Business Act, including separation of the prepaid data system and the mobile network; introduction of a monthly fixed-rate hybrid prepaid system, a top-up system and USIM system; introduction of mobile network carrier selection; differentiated retail discounts between prepaid and post-paid prices; revision of the retail discount policy for wholesale provision; increase in the number of mandatory service providers; and in-depth consideration of the introduction of a number portability policy for the prepaid and post-paid systems.

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A Non-annotated Recurrent Neural Network Ensemble-based Model for Near-real Time Detection of Erroneous Sea Level Anomaly in Coastal Tide Gauge Observation (비주석 재귀신경망 앙상블 모델을 기반으로 한 조위관측소 해수위의 준실시간 이상값 탐지)

  • LEE, EUN-JOO;KIM, YOUNG-TAEG;KIM, SONG-HAK;JU, HO-JEONG;PARK, JAE-HUN
    • The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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    • v.26 no.4
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    • pp.307-326
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    • 2021
  • Real-time sea level observations from tide gauges include missing and erroneous values. Classification as abnormal values can be done for the latter by the quality control procedure. Although the 3𝜎 (three standard deviations) rule has been applied in general to eliminate them, it is difficult to apply it to the sea-level data where extreme values can exist due to weather events, etc., or where erroneous values can exist even within the 3𝜎 range. An artificial intelligence model set designed in this study consists of non-annotated recurrent neural networks and ensemble techniques that do not require pre-labeling of the abnormal values. The developed model can identify an erroneous value less than 20 minutes of tide gauge recording an abnormal sea level. The validated model well separates normal and abnormal values during normal times and weather events. It was also confirmed that abnormal values can be detected even in the period of years when the sea level data have not been used for training. The artificial neural network algorithm utilized in this study is not limited to the coastal sea level, and hence it can be extended to the detection model of erroneous values in various oceanic and atmospheric data.

Development of Data Analysis and Interpretation Methods for a Hybrid-type Unmanned Aircraft Electromagnetic System (하이브리드형 무인 항공 전자탐사시스템 자료의 분석 및 해석기술 개발)

  • Kim, Young Su;Kang, Hyeonwoo;Bang, Minkyu;Seol, Soon Jee;Kim, Bona
    • Geophysics and Geophysical Exploration
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    • v.25 no.1
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    • pp.26-37
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    • 2022
  • Recently, multiple methods using small aircraft for geophysical exploration have been suggested as a result of the development of information and communication technology. In this study, we introduce the hybrid unmanned aircraft electromagnetic system of the Korea Institute of Geosciences and Mineral resources, which is under development. Additionally, data processing and interpretation methods are suggested via the analysis of datasets obtained using the system under development to verify the system. Because the system uses a three-component receiver hanging from a drone, the effects of rotation on the obtained data are significant and were therefore corrected using a rotation matrix. During the survey, the heights of the source and the receiver and their offsets vary in real time and the measured data are contaminated with noise. The noise makes it difficult to interpret the data using the conventional method. Therefore, we developed a recurrent neural network (RNN) model to enable rapid predictions of the apparent resistivity using magnetic field data. Field data noise is included in the training datasets of the RNN model to improve its performance on noise-contaminated field data. Compared with the results of the electrical resistivity survey, the trained RNN model predicted similar apparent resistivities for the test field dataset.

A Comparative Research on End-to-End Clinical Entity and Relation Extraction using Deep Neural Networks: Pipeline vs. Joint Models (심층 신경망을 활용한 진료 기록 문헌에서의 종단형 개체명 및 관계 추출 비교 연구 - 파이프라인 모델과 결합 모델을 중심으로 -)

  • Sung-Pil Choi
    • Journal of the Korean Society for Library and Information Science
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    • v.57 no.1
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    • pp.93-114
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    • 2023
  • Information extraction can facilitate the intensive analysis of documents by providing semantic triples which consist of named entities and their relations recognized in the texts. However, most of the research so far has been carried out separately for named entity recognition and relation extraction as individual studies, and as a result, the effective performance evaluation of the entire information extraction systems was not performed properly. This paper introduces two models of end-to-end information extraction that can extract various entity names in clinical records and their relationships in the form of semantic triples, namely pipeline and joint models and compares their performances in depth. The pipeline model consists of an entity recognition sub-system based on bidirectional GRU-CRFs and a relation extraction module using multiple encoding scheme, whereas the joint model was implemented with a single bidirectional GRU-CRFs equipped with multi-head labeling method. In the experiments using i2b2/VA 2010, the performance of the pipeline model was 5.5% (F-measure) higher. In addition, through a comparative experiment with existing state-of-the-art systems using large-scale neural language models and manually constructed features, the objective performance level of the end-to-end models implemented in this paper could be identified properly.