• 한국축산시설환경학회지
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• 제5권2호
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• pp.93-100
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• 1999

Pig's original image data was transformed to a binary image, an image excluding head and tail portion from the whole binary image, and a projected image associated with pig's height. Then the length of body, width of shoulder, and area of pig were calculated and the relationships among the above characteristics and pig's weight were analyzed. The results obtained from this study were as follows: 1. Whole binary image data was considered to be improper to determine the pig's weight because the movement of pig's head and tail portion affected the image data. 2. Binary image data excluding head and tail portion from the whole binary image showed a better estimation of the pig's weight than the whole binary image. 3. Pig's should width was analyzed to be improper factor to determine the pig's weight. 4. The projected image associated with pig's height showed the highest correlation between the pig's area of the image and pig's weight(R2=0.9965). From this research the projected image associated with pig's height, which is excluding head and tail portion from the whole body of pig's image, was considered to be the prime factor to measure the pig's weight by the noncontact measurement.

• 디지털융복합연구
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• 제19권10호
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• pp.105-110
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• 2021

양돈 ICT 자동 급이기는 설정된 조건에 맞춰 사료 등을 자동 급이가 가능하다. 그러나, 설정 조건 자체는 사용자의 경험에 의존해야 하는 단점이 있다. 그렇기 때문에, 시행착오를 유발하고, 효율성이 떨어지는 문제가 발생하고 있다. 따라서, 데이터에 기반한 최적의 급이 설정 조건을 제시해 양돈 생산성을 향상시킬 수 있는 시스템 개발 및 서비스 모델 구현이 필요하다. 따라서, 본 논문에서는 기존의 급이 데이터, 사양관리 데이터 및 양돈 생산 관리 시스템 등의 성적분석 프로그램을 활용한 양돈 급이 관리 서비스 모델을 개발하였다. 이를 통해, 양돈 데이터 분석으로 효율적으로 활용할 수 있는 수요자 중심의 급이 관리 서비스 모델을 개발하였다. 또한, 지능화된 자동 급이 관리 서비스로 농가의 폐사율 감소 및 MSY 증가에 일조함으로써 양돈 농가의 생산성 향상과 이로 인해 양돈 농가의 소득 증대에 기여하는 서비스를 제공할 수 있다.

• 한국HCI학회:학술대회논문집
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• 한국HCI학회 2006년도 학술대회 1부
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• pp.1107-1112
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• 2006

Geometry PIG (Pipeline Inspection Gauge)는 배관 내에 삽입되어 내부를 흐르는 매체에 의해서 추진되는 장치로서 배관의 기하학적 형상을 파악하기 위해 사용된다. Geometry PIG는 여러 종류의 센서를 지니고 배관 내부를 주행 하면서 탑재된 저장장치에 빠른 샘플링 속도로 데이터를 저장하기 때문에 획득된 많은 양의 데이터를 분석하기 위한 가시화 기법이 필요하다. 본 논문에서는 데이터의 특성을 고려하여 다양한 가시화 기법들의 스키마를 정의하고, 이러한 가시화 기법들을 이용해 geometry PIG 데이터 분석을 위한 통합된 가시화 기법을 제안한다. 통합된 가시화 기법은 각 가시화 기법들을 사용자가 원하는 형태로 배치하며 사용자가 원하는 시점에서 데이터를 파악할 수 있도록 가시화 기법에 따른 동기화와 사용자 인터페이스를 지원한다.

• 한국정보통신학회논문지
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• 제24권1호
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• pp.130-133
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• 2020

Smart pig farm which is based on IoT has been widely adopted by many pig farmers. In order to achieve optimal control of smart pig farm, the relation between environmental conditions and performance metric should be characterized. In this study, the relation between multiple environmental conditions including temperature, humidity and various performance metrics, which are daily gain, feed intake, and MSY, is analyzed based on data obtained from 55 real pig farm. Especially, based on preprocessing of data, various regression based machine learning algorithms are considered. Through performance evaluation, we show that the performance can be predicted with high precision, which can improve the efficiency of management.

• 한국농공학회논문집
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• 제62권1호
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• pp.71-81
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• 2020

Enclosed pig house are creating an environment with high concentrations of gas and dust. Poor conditions in pig farms reduce pig weight and increase disease and accidents for livestock workers. In the pig house, the high concentration of harmful gas may cause asphyxiation accidents to workers and chronic respiratory disease by long-term exposure. As pig farm workers have been aging and feminized, the damage to the health of the harsh environment is getting serious, and real-time monitoring is needed to prevent the damage. However, most of the measuring devices related to humidity, harmful gas, and fine dust except temperature sensors are exposed to high concentrations of gas and dust inside pig house and are difficult to withstand for a long time. The purpose of this study is to develop an wearable based device to monitor the hazardous environment exposed to workers working in pig farms. Based on the field monitoring and previous researches, the measurement range and basic specifications of the equipment were selected, and wearable based device was designed in terms of utilization, economic efficiency, size and communication performance. Selected H₂S and NH₃ sensors showed the average error of 5.3% comparing to standard gas concentrations. The measured data can be used to manage the working environment according to the worker's location and to obtain basic data for work safety warning.

• 한국멀티미디어학회논문지
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• 제25권4호
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• pp.583-599
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• 2022

Although the object detection accuracy with a single image has been significantly improved with the advance of deep learning techniques, the detection accuracy for pig monitoring is challenged by occlusion problems due to a complex structure of a pig room such as food facility. These detection difficulties with a single image can be mitigated by using a video data. In this research, we propose a method in pig detection for video monitoring environment with a static camera. That is, by using both image processing and deep learning techniques, we can recognize a complex structure of a pig room and this information of the pig room can be utilized for improving the detection accuracy of pigs in the monitored pig room. Furthermore, we reduce the execution time overhead by applying a pruning technique for real-time video monitoring on an embedded board. Based on the experiment results with a video data set obtained from a commercial pig farm, we confirmed that the pigs could be detected more accurately in real-time, even on an embedded board.

• 한국멀티미디어학회논문지
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• 제24권7호
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• pp.890-902
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• 2021

Although the object detection accuracy with still images has been significantly improved with the advance of deep learning techniques, the object detection problem with video data remains as a challenging problem due to the real-time requirement and accuracy drop with occlusion. In this research, we propose a method in pig detection for video monitoring environment. First, we determine a motion, from a video data obtained from a tilted-down-view camera, based on the average size of each pig at each location with the training data, and extract key frames based on the motion information. For each key frame, we then apply YOLO, which is known to have a superior trade-off between accuracy and execution speed among many deep learning-based object detectors, in order to get pig's bounding boxes. Finally, we merge the bounding boxes between consecutive key frames in order to reduce false positive and negative cases. Based on the experiment results with a video data set obtained from a pig farm, we confirmed that the pigs could be detected with an accuracy of 97% at a processing speed of 37fps.

• Animal Bioscience
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• 제34권8호
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• pp.1350-1364
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• 2021

Objective: Adequate vitamin and trace mineral intake for pigs are important to achieve satisfactory growth performance. There are no data available on the vitamin and trace mineral intake across pig producers in China. The purpose of this study was to investigate and describe the amount of vitamin and trace minerals used in Chinese pig diets. Methods: A 1-year survey of supplemented vitamin and trace minerals in pig diets was organized in China. A total of 69 producers were invited for the survey, which represents approximately 90% of the pig herd in China. Data were compiled by bodyweight stages to determine descriptive statistics. Nutrients were evaluated for vitamin A, vitamin D, vitamin E, vitamin K, thiamine, riboflavin, vitamin B₆, vitamin B₁₂, pantothenic acid, niacin, folic acid, biotin, choline, copper, iron, manganese, zinc, selenium, and iodine. Data were statistically analyzed by functions in Excel. Results: The results indicated variation for supplemented vitamin (vitamin A, vitamin D, vitamin E, vitamin K, vitamin B₁₂, pantothenic acid, niacin, and choline) and trace minerals (copper, manganese, zinc, and iodine) in pig diets, but most vitamins and trace minerals were included at concentrations far above the total dietary requirement estimates reported by the National Research Council and the China's Feeding Standard of Swine. Conclusion: The levels of vitamin and trace mineral used in China's pig industry vary widely. Adding a high concentration for vitamin and trace mineral appears to be common practice in pig diets. This investigation provides a reference for supplementation rates of the vitamins and trace minerals in the China's pig industry.

• 한국임상수의학회지
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• 제32권1호
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• pp.78-84
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• 2015

Although researches have highlighted the important role of enhanced farm biosecurity to reduce the severity and prevalence of diseases in livestock, to date there has been little study in Korea on farmers' adoption of biosecurity measures to control porcine reproductive and respiratory syndrome virus (PRRSV) infection. To mitigate the risk of PRRSV infection in pigs, the risk factors by which PRRSV is introduced in pig farms must be determined. The primary aim of this study was to investigate pig producers' perceptions about on-farm biosecurity practices. We also analyzed data obtained from a cross-sectional study on 196 farrow-to-finish farms conducted between March 2013 and February 2014 to identify risk factors for PRRSV infection at farm level. Standardized questionnaires with information about basic demographical data and management practices were collected in each farm by on-site visit of trained veterinarians. Farms were classified as negative or positive through the use of infection profiles that combined data on PCR positive pigs and serological testing including antibody titer, sero-conversion pattern at each age category, and vaccination status. Data on biosecurity practices, farm management and environmental characteristics were analyzed using multivariate ordinal logistic regression. Generally, the biosecurity level in the pig farms included in this study were insufficient to reduce/prevent the risk of PRRSV infection given the high pig density areas and the considerable extent of vehicle movement. Factors associated with PRRSV infection were those where owners used on-farm vaccination programs had a lower risk of infection (OR = 0.19, 95% CI 0.06-0.61). The results from the analysis may guide to tailor biosecurity measures in the reduction or prevention of PRRS to the specific circumstances of pig farms in different localities of the world. To the best knowledge of the authors, this is the first study to report information on the biosecurity practices currently implemented on Korean pig farms.

• 한국정보통신학회논문지
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• 제21권8호
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• pp.1560-1566
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• 2017

최근 사물 인터넷 센서가 설치된 스마트 돈사의 보급을 통해 돈사 관련 빅데이터 축적이 가능해졌고, 다양한 기계 학습방안들이 수집된 데이터에 적용되어 축산농가의 생산성을 향상시키고 있다. 본 연구에서는 다양한 기계학습 방안을 이용하여 돈사관리에서 가장 중요한 요소 중 하나인 급수량을 예측하였다. 구체적으로 실제 돈사에서 수집된 데이터에 회귀 방안인 선형회귀, 회귀트리 및 아다부스트 회귀 방안과 분류 방안인 로지스틱 분류, 결정트리 및 서포트 벡터 머신 (SVM) 분류방안을 적용하여 돈사의 온도와 습도를 기반으로 급수량을 예측하였다. 성능 분석을 통해서 제안한 방안이 높은 정확도로 급수량을 예측하는 것을 확인할 수 있었다. 제안한 방안은 돈사의 급수시설 이상을 조기에 파악하는데 활용되어 가축을 폐사를 막고 돈사 생산성을 높이는데 활용될 수 있다.