An Automatic Irrigation System Based on Hourly Cumulative Evapotranspiration for Reducing Agricultural Water Usage by Yongjae Lee, Seung-un Ha, Xin Wang, Seungyong Hahm, Kwangya Lee, Jongseok Park

“…This study investigates the development and application of an automatic irrigation system based on hourly cumulative evapotranspiration (ET) to optimize cabbage growth while reducing agricultural water usage. …”
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Research Progress of Dangerous Driving Behavior Recognition Methods Based on Deep Learning by Junjian Hou, Bingyu Zhang, Yudong Zhong, Wenbin He

“…In this paper, the research progress in the recognition methods of dangerous driving behavior based on deep learning is analyzed. Firstly, the data collection methods are categorized into four types, evaluating their respective advantages, disadvantages, and applicability. …”
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Machine vision model using nail images for non-invasive detection of iron deficiency anemia in university students by Jorge Raul Navarro-Cabrera, Miguel Angel Valles-Coral, María Elena Farro-Roque, Nelly Reátegui-Lozano, Lolita Arévalo-Fasanando

“…The images were pre-processed using segmentation and data augmentation techniques to standardize the dataset. …”
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Feature-Based Normality Models for Anomaly Detection by Hui Yie Teh, Kevin I-Kai Wang, Andreas W. Kempa-Liehr

“…To improve sensor data quality while addressing the challenges of anomaly detection in Internet of Things applications, we present an anomaly detection framework that learns a normality model of sensor data. …”
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Enhanced Adaptive Sine Multi-Taper Power Spectral Density Estimation for System Performance Evaluation in Low-Frequency Gravitational Wave Detection by Caiyun Liu, Yang Li, Changkang Fu, Hongming Zhang, Qiang Wang, Dong He, Yongmei Huang

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Development of a Cost-effective Adsorption Dryer for High-quality Aerosol Sampling by Simonas Kecorius, Leizel Madueño, Susanne Sues, Josef Cyrys, Mario Lovrić, Mira Pöhlker, Kristina Plauškaitė, Lina Davulienė, Agnė Minderytė, Steigvilė Byčenkienė

“…The presented DD is easily scalable, thus, can be adapted for multiple applications at a low cost without compromising the data quality.…”
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Real-Time Object Detection Using Low-Resolution Thermal Camera for Smart Ventilation Systems by Jun-Hee Lee, Eung-Tea Kim

“…To address the scarcity of thermal data, we developed the TOI (Thermal Object Insertion) data augmentation technique, which generates new training data while preserving thermal pattern characteristics. …”
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Accelerating adverse pregnancy outcomes research amidst rising medication use: parallel retrospective cohort analyses for signal prioritization by Yeon Mi Hwang, Samantha N. Piekos, Alison G. Paquette, Qi Wei, Nathan D. Price, Leroy Hood, Jennifer J. Hadlock

“…We narrowed down from 1329 to 58 medications that showed statistically significant association with the risk of preterm birth even after addressing numerous covariates through propensity score matching. This data-driven approach demonstrated that multiple testable hypotheses in pregnancy pharmacology can be prioritized at scale and lays the foundation for application in other pregnancy outcomes.…”
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Estimating groundwater recharge across Africa during 2003–2023 using GRACE-derived groundwater storage changes by Vagner G. Ferreira, Hao Yang, Christopher Ndehedehe, Hongyan Wang, Ying Ge, Jia Xu, Min Xia, Ikechukwu Kalu, Miao Jing, Nathan Agutu

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Evaluating the Potential of Improving In-Season Potato Nitrogen Status Diagnosis Using Leaf Fluorescence Sensor as Compared with SPAD Meter by Seiya Wakahara, Yuxin Miao, Dan Li, Jizong Zhang, Sanjay K. Gupta, Carl Rosen

“…Further research is needed to develop an easy-to-use application and corresponding in-season N recommendation strategy to facilitate practical on-farm applications.…”
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Novel Hemorrhagic Risk Score in Elderly Patients with Coronary Artery Disease and Gastrointestinal Malignant Tumor Comorbidity: A 10-year Clinical Inpatient Data Analysis from 2 Me... by Nandi Bao, Wanling Wang, Huitao Wu, Yabin Wang, Hebin Che, Wenwen Meng, Jiaxin Miao, Dong Han, Fan Yin, Tianyu Xu, Xiaoxia Fu.

“…To allow for convenient clinical application, a smartphone application was developed for easy access and calculation (http://fir.master-wx.com/sghr). …”
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Computing ecosystem risk hotspots: A mediterranean case study by Gianpaolo Coro, Laura Pavirani, Anton Ellenbroek

“…Traditional approaches evaluate single stressors, whereas complex models assess cumulative impacts of frequently interacting stressors and offer better accuracy at the expense of low cross-area re-applicability and long implementation times.We introduce a versatile, re-useable, and semi-automated workflow designed for big data-driven ecosystem risk assessment, utilising spatiotemporal data from open repositories. …”
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Improved Detection and Location of Small Crop Organs by Fusing UAV Orthophoto Maps and Raw Images by Huaiyang Liu, Huibin Li, Haozhou Wang, Chuanghai Liu, Jianping Qian, Zhanbiao Wang, Changxing Geng

“…Extracting the quantity and geolocation data of small objects at the organ level via large-scale aerial drone monitoring is both essential and challenging for precision agriculture. …”
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Anatomy-Informed Multimodal Learning for Myocardial Infarction Prediction by Ivan-Daniel Sievering, Ortal Senouf, Thabo Mahendiran, David Nanchen, Stephane Fournier, Olivier Muller, Pascal Frossard, Emmanuel Abbe, Dorina Thanou

“…In this work, we propose a novel anatomy-informed multimodal deep learning framework to predict future MI from clinical data and Invasive Coronary Angiography (ICA) images. …”
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Two-to-One Trigger Mechanism for Event-Based Environmental Sensing by Nursultan Daupayev, Christian Engel, Sören Hirsch

“…However, these systems typically have high energy consumption, data overload, and large equipment sizes, which makes them difficult to install in constrained spaces. …”
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Deployable Deep Learning for Cross-Domain Plant Leaf Disease Detection via Ensemble Learning, Knowledge Distillation, and Quantization by Mohammad Junayed Hasan, Suvodeep Mazumdar, Sifat Momen

“…Finally, field deployment via a multilingual and multi-platform Flutter application validates real-world feasibility, establishing the first scalable framework bridging research and practical agricultural deployment. …”
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Enhancing wheat flour origin traceability by using laser-induced breakdown spectroscopy and Raman spectroscopy by Minghui Gu, Chao Liu, Hansong Huang, Xin Zhang, Jiguo Li, Qingbin Jiao, Liang Xu, Mingyu Yang, Xin Tan

“…Finally, to enhance the practical applicability of the model, model parameter transfer techniques were introduced, with a small amount of wheat flour spectral data from five other provinces used as the training set to fine-tune the established 2D CNN model. …”
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Co-creation and application of a framework for the de-prioritization of urban communities during insecticide-treated bed net mass campaigns for malaria prevention and control in Kw... by Ifeoma D. Ozodiegwu, Laurette Mhlanga, Eniola A. Bamgboye, Adeniyi F. Fagbamigbe, Cyril Ademu, Chukwu Okoronkwo, Joshua O. Akinyemi, Akintayo O. Ogunwale, IkeOluwapo O. Ajayi, Beatriz Galatas

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Developing a generalized nonlinear mixed-effects biomass model at stand-level under different age conditions for Chinese fir based on LiDAR and ground survey data in southern China by Xinsheng Zhu, Tianbao Huang, Ziyang Liu, Lang Bai, Yongfeng Yang, Jinsheng Ye, Qiulai Wang, Ram P. Sharma, Liyong Fu

“…Validation with independent test samples confirmed the robustness and reliability of the nonlinear mixed-effects model.DiscussionThis study highlights the effectiveness of airborne LiDAR data in providing efficient and precise estimates of stand biomass. …”
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Temporal scalability analysis of spectral remote sensing and Machine Learning-Based models for forest mapping in the tropical region of Nigeria by K. Pawłuszek-Filipiak, D. Włodarczyk, K. Stuchły, F.E. Ikuemonisan

“…The integration of machine learning (ML) algorithms with remote sensing (RS) data offers significant potential for enhancing dynamic forest characterization and change detection through high temporal density mapping. …”
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