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Akademický článek

An IMU-based machine learning approach for daily behavior pattern recognition in dairy cows

Autor: Hua-Ta Liang, Shu-Wen Hsu, Jih-Tay Hsu, Chia-Jui Tu, Yi-Chu Chang, Chua Teck Jian, Ta-Te Lin

Publikováno v: Smart Agricultural Technology, Vol 9, Iss , Pp 100539- (2024)

Technological advancements have revolutionized livestock farming, notably in health monitoring. Traditional methods, which have been criticized for subjectivity and treatment delays, can be replaced with efficient health monitoring systems, thereby r

Externí odkaz: https://doaj.org/article/8b50e000f4a74ef0893655450f74195a

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Akademický článek

Brain white matter correlates of learning ankle tracking using a wearable device: importance of the superior longitudinal fasciculus II

Autor: Chishan Shiao, Pei-Fang Tang, Yu-Chen Wei, Wen-Yih Isaac Tseng, Ta-Te Lin

Publikováno v: Journal of NeuroEngineering and Rehabilitation, Vol 19, Iss 1, Pp 1-15 (2022)

Abstract Background Wearable devices have been found effective in training ankle control in patients with neurological diseases. However, the neural mechanisms associated with using wearable devices for ankle training remain largely unexplored. This

Externí odkaz: https://doaj.org/article/cd5f8b7ebcf24bfcb84cf657ab5ace51

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Akademický článek

Honey Bee Colony Population Daily Loss Rate Forecasting and an Early Warning Method Using Temporal Convolutional Networks

Autor: Thi-Nha Ngo, Dan Jeric Arcega Rustia, En-Cheng Yang, Ta-Te Lin

Publikováno v: Sensors, Vol 21, Iss 11, p 3900 (2021)

The population loss rate of a honey bee colony is a critical index to verify its health condition. Forecasting models for the population loss rate of a honey bee colony can be an essential tool in honey bee health management and pave a way to early w

Externí odkaz: https://doaj.org/article/41ea400fa5f64be787001dcf3333c1ec

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Akademický článek

Exoskeletons for Elderly Activity of Daily Living Assistance: A Review of Upper Limb Exoskeletons and Assessments.

Autor: Abdul Jalal, Muhammad Fairuz, Harith, Hazreen Haizi, Wan Hasan, Wan Zuha, Salim, Mazatulfazura S. F., Ta-Te Lin

Publikováno v: International Journal of Integrated Engineering (IJIE); 2024, Vol. 16 Issue 1, p87-105, 19p

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Automated Imaging System for Continuous Monitoring of Insect Pests in a Remote Outdoor Mango Orchard

Autor: Dan Jeric Arcega Rustia, Wei-Che Lee, Chen-Yi Lu, Ya-Fang Wu, Pei-Yu Shih, Sheng-Kuan Chen, Jui-Yung Chung, Ju-Chun Hsu, Ta-Te Lin

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::d55ddfee2b681e300f4959abeecf8531
https://doi.org/10.2139/ssrn.4355544

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Intelligent Insect Monitoring Systems

Autor: Dan Jeric Arcega Rustia, Ta-Te Lin

Publikováno v: Encyclopedia of Smart Agriculture Technologies. Springer
Encyclopedia of Smart Agriculture Technologies
Encyclopedia of Smart Agriculture Technologies ISBN: 9783030891237

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ac1ce10eafdfbf582a2e04f63f343d0b
https://research.wur.nl/en/publications/intelligent-insect-monitoring-systems

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Online semi-supervised learning applied to an automated insect pest monitoring system

Autor: Jui-Yung Chung, Ju-Chun Hsu, Dan Jeric Arcega Rustia, Ta-Te Lin, Ya-Fang Wu, Jun-Jee Chao, Chen-Yi Lu

Publikováno v: Biosystems Engineering. 208:28-44

The unavailability and variability of training samples are the two essential concerns in the training of deep neural network models for image classification. For automated image monitoring systems, these problems are difficult when training a model t

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::58c544b0ac2e0c47ba25729a6682d83d
https://doi.org/10.1016/j.biosystemseng.2021.05.006

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Towards intelligent and integrated pest management through an AIoT-based monitoring system

Autor: Dan Jeric Arcega Rustia, Lin‐Ya Chiu, Chen‐Yi Lu, Ya‐Fang Wu, Sheng‐Kuan Chen, Jui‐Yung Chung, Ju‐Chun Hsu, Ta‐Te Lin

Publikováno v: Pest management scienceREFERENCES. 78(10)

Main bottleneck in facilitating integrated pest management (IPM) is the unavailability of reliable and immediate crop damage data. Without sufficient insect pest and plant disease information, farm managers are unable to make proper decisions to prev

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::20e7363b5edb4f5421773087ba83e4c7
https://pubmed.ncbi.nlm.nih.gov/35716088

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Automatic greenhouse insect pest detection and recognition based on a cascaded deep learning classification method

Autor: Lin-Ya Chiu, Ju-Chun Hsu, Dan Jeric Arcega Rustia, Jui-Yung Chung, Ta-Te Lin, Ya-Fang Wu, Jun-Jee Chao

Publikováno v: Journal of Applied Entomology. 145:206-222

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::4132c022c1a78424d57676351faa118a
https://doi.org/10.1111/jen.12834

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Assessment of dairy cow heat stress by monitoring drinking behaviour using an embedded imaging system

Autor: Dan Jeric Arcega Rustia, Shih-Torng Ding, Ta-Te Lin, Hsu Jih-Tay, Tsai Yu-Chi

Publikováno v: Biosystems Engineering. 199:97-108

To counteract heat stress in dairy cows, a more reliable and efficient method for monitoring the activity of dairy cows and ambient environmental conditions should be developed. This research presents a cost-effective embedded imaging system that is

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::e43d417711e2856052b2df8f35954735
https://doi.org/10.1016/j.biosystemseng.2020.03.013

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