Publications by authors named "Kyeongseok Kwon"

Article Synopsis
  • Importance of Vocalization Detection
  • : The study highlights the significance of monitoring pig vocalizations to manage pig welfare in modern farming, utilizing deep learning for detection and classification.
  • Deep Learning Model Development
  • : A new deep convolutional neural network (DCNN) architecture is proposed, employing a novel feature extraction method called Mixed-MMCT, which combines various audio features to enhance classification accuracy.
  • High Accuracy Results
  • : The model was evaluated on datasets from three pig farms, achieving impressive classification accuracies of 99.50%, 99.56%, and 99.67%, demonstrating its effectiveness in pig vocalization analysis.
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Quantifying emission factors of ammonia and particulate matter (PM) in livestock production systems is crucial for assessing and mitigating the environmental impact of animal production and for ensuring industry sustainability. This study aimed to determine emission factors of ammonia, total suspended particles (TSPs), PM, and PM for piglets and growing-finishing pigs at a commercial pig farm in Korea. It also sought to identify factors influencing these emission factors.

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Accurate ventilation control is crucial for maintaining a healthy and productive environment in research-specialized pig facilities. This study aimed to evaluate actual ventilation rates and ventilation efficiency by investigating different inlet and exhaust configurations. The research was conducted in two pig rooms, namely pig room A and pig room B, in the absence of animals and workers to focus solely on evaluating the ventilation system's performance.

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In this study, considering the difficulties for all farms to convert farm styles to animal welfare-based housing, an experiment was performed to observe the changes in the behavior and welfare of sows when the slat floor was changed to a collective breeding ground. Twenty-eight sows used in this study were between the second and fifth parities to minimize the influence of parity. Using a flats floor cover, the flattening rates were treated as 0%, 20%, 30%, 40%, and 50%.

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