• Title/Summary/Keyword: Multi-target estimation

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Genetic parameter analysis of reproductive traits in Large White pigs

  • Yu, Guanghui;Wang, Chuduan;Wang, Yuan
    • Animal Bioscience
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    • v.35 no.11
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    • pp.1649-1655
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    • 2022
  • Objective: The primary objective of this study was to determine the genetic parameters for reproductive traits among Large White pigs, including the following traits: total number born (TNB), number born alive (NBA), litter birth weight (LBW), average birth weight (ABW), gestation length (GL), age at first service (AFS) and age at first farrowing (AFF). Methods: The dataset consisted of 19,036 reproductive records from 4,986 sows, and a multi-trait animal model was used to estimate genetic variance components of seven reproductive traits. Results: The heritability estimates for these reproductive traits ranged from 0.09 to 0.26, with the highest heritability for GL and AFF, and the lowest heritability for NBA. The repeatabilities for TNB, NBA, LWB, ABW, and GL were ranged from 0.16 to 0.34. Genetic and phenotypic correlations ranged from -0.41 to 0.99, and -0.34 to 0.98, respectively. In particular, the correlations between TNB, NBA and LBW, between AFS and AFF, exhibited a strong positive correlation. Furthermore, for TNB, NBA, LBW, ABW, and GL, genetic correlations of the same trait between different parities were moderately to strongly correlated (0.32 to 0.97), and the correlations of adjacent parities were higher than those of nonadjacent parities. Conclusion: All the results in the present study can be used as a basis for the genetic assessment of the target population. In the formulation of dam line selection index, AFS or AFF can be considered to combine with TNB in a multiple trait swine breeding value estimation system. Moreover, breeders are encouraged to increase the proportion of sows at parity 3-5 and reinforce the management of sows at parity 1 and parity ≥8.

Estimation of Optimal Harvest Volume for the Long-term Forest Management Planning using Goal Programming (장기산림경영계획의 목표수확량 산출을 위한 목표계획법의 적용)

  • Won, Hyun-Kyu;Kim, Young-Hwan;Kwon, Soon-Duk
    • Journal of Korean Society of Forest Science
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    • v.98 no.1
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    • pp.125-131
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    • 2009
  • To facilitate the sustainable forest management, Forest Service in Korea has assigned 2.9 million hectare forests as 'intensive management forests' and encouraged local governments to develop a strategic management plan for their forests. One of problems for the sustainable forest management in Korea is the skewed distribution of forest age classes. Currently the majority of forestlands in Korea is occupied by age classes III and IV. In this study, we intended to find an optimum harvest volume, which enable one to make the intensive management forest in Youngdong-Gun evenly distributed for the age classes and allow an even harvest volume through a 50 year time horizon. To develop an optimization model, we applied the goal programming technique which is adequate for a multi-purpose management planning. The results indicated that it is necessary to harvest 1.2 million cubic meters in each decade to achieve the most stable distribution of age classes for the study site. The harvest volume target resulted from this study would be used in a management planning or an associated policy making process in the future.

A Study on Atmospheric Turbulence-Induced Errors in Vision Sensor based Structural Displacement Measurement (대기외란시 비전센서를 활용한 구조물 동적 변위 측정 성능에 관한 연구)

  • Junho Gong
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.28 no.3
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    • pp.1-9
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    • 2024
  • This study proposes a multi-scale template matching technique with image pyramids (TMI) to measure structural dynamic displacement using a vision sensor under atmospheric turbulence conditions and evaluates its displacement measurement performance. To evaluate displacement measurement performance according to distance, the three-story shear structure was designed, and an FHD camera was prepared to measure structural response. The initial measurement distance was set at 10m, and increased with an increment of 10m up to 40m. The atmospheric disturbance was generated using a heating plate under indoor illuminance condition, and the image was distorted by the optical turbulence. Through preliminary experiments, the feasibility of displacement measurement of the feature point-based displacement measurement method and the proposed method during atmospheric disturbances were compared and verified, and the verification results showed a low measurement error rate of the proposed method. As a result of evaluating displacement measurement performance in an atmospheric disturbance environment, there was no significant difference in displacement measurement performance for TMI using an artificial target depending on the presence or absence of atmospheric disturbance. However, when natural targets were used, RMSE increased significantly at shooting distances of 20 m or more, showing the operating limitations of the proposed technique. This indicates that the resolution of the natural target decreases as the shooting distance increases, and image distortion due to atmospheric disturbance causes errors in template image estimation, resulting in a high displacement measurement error.

Technology Development for Non-Contact Interface of Multi-Region Classifier based on Context-Aware (상황 인식 기반 다중 영역 분류기 비접촉 인터페이스기술 개발)

  • Jin, Songguo;Rhee, Phill-Kyu
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.20 no.6
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    • pp.175-182
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    • 2020
  • The non-contact eye tracking is a nonintrusive human-computer interface providing hands-free communications for people with severe disabilities. Recently. it is expected to do an important role in non-contact systems due to the recent coronavirus COVID-19, etc. This paper proposes a novel approach for an eye mouse using an eye tracking method based on a context-aware based AdaBoost multi-region classifier and ASSL algorithm. The conventional AdaBoost algorithm, however, cannot provide sufficiently reliable performance in face tracking for eye cursor pointing estimation, because it cannot take advantage of the spatial context relations among facial features. Therefore, we propose the eye-region context based AdaBoost multiple classifier for the efficient non-contact gaze tracking and mouse implementation. The proposed method detects, tracks, and aggregates various eye features to evaluate the gaze and adjusts active and semi-supervised learning based on the on-screen cursor. The proposed system has been successfully employed in eye location, and it can also be used to detect and track eye features. This system controls the computer cursor along the user's gaze and it was postprocessing by applying Gaussian modeling to prevent shaking during the real-time tracking using Kalman filter. In this system, target objects were randomly generated and the eye tracking performance was analyzed according to the Fits law in real time. It is expected that the utilization of non-contact interfaces.

Preliminary Estimation of Earthquake Losses Based on HAZUS in a Coastal Facility Area with Blocks Applying Site Classification (블록별 부지분류 적용 해안시설 영역에서의 HAZUS 기반 지진피해 추정)

  • Sun, Chang-Guk;Chun, Sung-Ho
    • Journal of the Korean Association of Geographic Information Studies
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    • v.17 no.4
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    • pp.10-27
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    • 2014
  • HAZUS-MH is a GIS-based computer program that estimates potential losses from multi-hazard phenomena: earthquakes, floods and hurricanes. With respect to seismic disaster, characteristics of a hypothetical or actual earthquake are entered into HAZUS. Then HAZUS estimates the intensity of ground shaking and calculates the correspondent losses. In this study, HAZUS was used as a part of the preparations of the future seismic events at a coastal plant facility area. To reliably characterize the target facility area, many geotechnical characteristics data were synthesized from the existing site investigation reports. And the buildings and facilities were sorted by analyzing their material and structural characteristics. In particular, the study area was divided into 17 blocks taking into account the situation of both land development and facility distribution. The ground conditions of blocks were categorized according to the site classification scheme for earthquake-resistant design. Moreover, seismic fragility curves of a main facilities were derived based on the numerical modeling and were incorporated into the database in HAZUS. The results estimated in the study area using HAZUS showed various seismic damage and loss potentials depending on site conditions and structural categories. This case study verified the usefulness of the HAZUS for estimating earthquake losses in coastal facility areas.

Estimation of Jaw and MLC Transmission Factor Obtained by the Auto-modeling Process in the Pinnacle3 Treatment Planning System (피나클치료계획시스템에서 자동모델화과정으로 얻은 Jaw와 다엽콜리메이터의 투과 계수 평가)

  • Hwang, Tae-Jin;Kang, Sei-Kwon;Cheong, Kwang-Ho;Park, So-Ah;Lee, Me-Yeon;Kim, Kyoung-Ju;Oh, Do-Hoon;Bae, Hoon-Sik;Suh, Tae-Suk
    • Progress in Medical Physics
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    • v.20 no.4
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    • pp.269-276
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    • 2009
  • Radiation treatment techniques using photon beam such as three-dimensional conformal radiation therapy (3D-CRT) as well as intensity modulated radiotherapy treatment (IMRT) demand accurate dose calculation in order to increase target coverage and spare healthy tissue. Both jaw collimator and multi-leaf collimators (MLCs) for photon beams have been used to achieve such goals. In the Pinnacle3 treatment planning system (TPS), which we are using in our clinics, a set of model parameters like jaw collimator transmission factor (JTF) and MLC transmission factor (MLCTF) are determined from the measured data because it is using a model-based photon dose algorithm. However, model parameters obtained by this auto-modeling process can be different from those by direct measurement, which can have a dosimetric effect on the dose distribution. In this paper we estimated JTF and MLCTF obtained by the auto-modeling process in the Pinnacle3 TPS. At first, we obtained JTF and MLCTF by direct measurement, which were the ratio of the output at the reference depth under the closed jaw collimator (MLCs for MLCTF) to that at the same depth with the field size $10{\times}10\;cm^2$ in the water phantom. And then JTF and MLCTF were also obtained by auto-modeling process. And we evaluated the dose difference through phantom and patient study in the 3D-CRT plan. For direct measurement, JTF was 0.001966 for 6 MV and 0.002971 for 10 MV, and MLCTF was 0.01657 for 6 MV and 0.01925 for 10 MV. On the other hand, for auto-modeling process, JTF was 0.001983 for 6 MV and 0.010431 for 10 MV, and MLCTF was 0.00188 for 6 MV and 0.00453 for 10 MV. JTF and MLCTF by direct measurement were very different from those by auto-modeling process and even more reasonable considering each beam quality of 6 MV and 10 MV. These different parameters affect the dose in the low-dose region. Since the wrong estimation of JTF and MLCTF can lead some dosimetric error, comparison of direct measurement and auto-modeling of JTF and MLCTF would be helpful during the beam commissioning.

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Estimation of sediment deposition rate in collapsed reservoirs(wetlands) using empirical formulas and multiple regression models (경험공식 및 다중회귀모형을 이용한 붕괴 저수지(습지) 비퇴사량 추정)

  • Kim, Donghyun;Lee, Haneul;Bae, Younghye;Joo, Hongjun;Kim, Deokhwan;Kim, Hung Soo
    • Journal of Wetlands Research
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    • v.23 no.4
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    • pp.287-295
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    • 2021
  • As facilities such as dam reservoir wetlands and agricultural irrigation reservoir wetlands are built, sedimentation occurs over time through erosion, sedimentation transport, and sediment deposition. Sedimentation issues are very important for the maintenance of reservoir wetlands because long-term sedimentation of sediments affects flood and drought control functions. However, research on resignation has been estimated mainly by empirical formulas due to the lack of available data. The purpose of this study was to calculate and compare the sediment deposition rate by developing a multiple regression model along with actual data and empirical formulas. In addition, it was attempted to identify potential causes of collapse by applying it to 64 reservoir wetlands that suffered flood damage due to the long rainy season in 2020 due to reservoir wetland sedimentation and aging. For the target reservoir, 10 locations including the GaGog reservoir located in Miryang city, Gyeongsangnam province in South Korea, where there is actual survey information, were selected. A multiple regression model was developed in consideration of physical and climatic characteristics, and a total of four empirical formulas and sediment deposition rate were calculated. Using this, the error of the sediment deposition rate was compared. As a result of calculating the sediment deposition rate using the multiple regression model, the error was the lowest from 0.21(m3km2/yr) to 2.13(m3km2/yr). Therefore, based on the sediment deposition rate estimated by the multi-regression model, the change in the available capacity of reservoir wetlands was analyzed, and the effective storage capacity was found to have decreased from 0.21(%) to 16.56(%). In addition, the sediment deposition rate of the reservoir where the overflow damage occurred was relatively higher than that of the reservoir where the piping damage occurred. In other words, accumulating sediment deposition rate at the bottom of the reservoir would result in a lack of acceptable effective water capacity and reduced reservoir flood and drought control capabilities, resulting in reservoir collapse damage.