Configuring Transmission Thresholds in IIoT Alarm Scenarios for Energy-Efficient Event Reporting by David E. Ruiz-Guirola, Onel L. A. Lopez, Samuel Montejo-Sanchez

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Prediction of Electrotactile Stimulus Threshold in Real Time Using Voltage Waveforms Between Electrodes by Vibol Yem, Yasushi Ikei, Hiroyuki Kajimoto

Subjects: “…Threshold estimation…”
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Machine learning approach for identifying and forecasting streamflow droughts in data limited basins of South Korea using threshold levels by Young-Ho Seo, Jang Hyun Sung, Byung-Sik Kim, Junehyeong Park

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Exploring Nonlinear Threshold Effects and Interactions Between Built Environment and Urban Vitality at the Block Level Using Machine Learning by Cong Li, Yajuan Zhou, Manfei Wu, Jiayue Xu, Xin Fu

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EDGE DETECTION TECHNIQUE BASED ON BILATERAL FILTERING AND ITERATIVE THRESHOLD SELECTION ALGORITHM AND TRANSFER LEARNING FOR TRAFFIC SIGN RECOGNITION by Milind PARSE, Dhanya PRAMOD

“…The proposed edge detection algorithm and transfer learning is used to train the Convolutional Neural Network (CNN) models and recognize the traffic signs. …”
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Implementing the Self-Management Threshold Learning Outcome for Law: Some Intentional Design Strategies from the Current Curriculum Toolbox by Anna Huggins, Sally Kift, Rachel Field

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Empirical and machine learning-based approaches to identify rainfall thresholds for landslide prediction: a case study of Kerala, India by Varun Menon, Sreevalsa Kolathayar

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A Reliable Aggregation Method Based on Threshold Additive Secret Sharing in Federated Learning with Quality of Service (QoS) Support by Yu-Ting Ting, Po-Wen Chi, Chien-Ting Kuo

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Synchronized stepwise control of firing and learning thresholds in a spiking randomly connected neural network toward hardware implementation by Kumiko Nomura, Yoshifumi Nishi

“…We also define other thresholds for SP that synchronize with the firing threshold, which determine the direction of stepwise synaptic update that is executed on receiving a pre-synaptic spike. …”
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FldtMatch: Improving Unbalanced Data Classification via Deep Semi-Supervised Learning with Self-Adaptive Dynamic Threshold by Xin Wu, Jingjing Xu, Kuan Li, Jianping Yin, Jian Xiong

Subjects: “…deep semi-supervised learning…”
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Adaptive Autoencoder-Based Intrusion Detection System with Single Threshold for CAN Networks by Donghyeon Kim, Hyungchul Im, Seongsoo Lee

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An Enhanced Human Evolutionary Optimization Algorithm for Global Optimization and Multi-Threshold Image Segmentation by Liang Xiang, Xiajie Zhao, Jianfeng Wang, Bin Wang

“…In the CLNBHEOA, firstly, population diversity is enhanced using the Chebyshev–Tent chaotic mapping refraction opposites-based learning strategy. Secondly, an adaptive learning strategy is proposed which combines differential learning and adaptive factors to improve the ability of the algorithm to jump out of the locally optimum threshold. …”
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Effectiveness of Flipped Classroom Strategies on Learning Outcomes in Economics Threshold Concepts Across Arts, Commerce, and Science Disciplines in Secondary Schools by Abidat Mohammed, Akinola Jimoh, Samod Lawal-Arogundade

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Bare ground classification using a spectral index ensemble and machine learning models optimized across 12 international study sites by Sarah J. Becker, Megan C. Maloney, Andrew W. H. Griffin, Kristofer Lasko, Heather S. Sussman

“…This research investigates a global approach to map bare ground across diverse geographies with an ensemble of spectral indices using optimal thresholds identified in testing to train and evaluate machine learning models to extract bare ground pixels from Sentinel-2 imagery. …”
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Equitable hospital length of stay prediction for patients with learning disabilities and multiple long-term conditions using machine learning by Emeka Abakasanga, Rania Kousovista, Georgina Cosma, Ashley Akbari, Francesco Zaccardi, Navjot Kaur, Navjot Kaur, Danielle Fitt, Gyuchan Thomas Jun, Reza Kiani, Satheesh Gangadharan

Subjects: “…learning disabilities…”
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The Role of Wonder in Students’ Conception of and Learning About Evolution by Bodil Sundberg, Magdalena Andersson

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A Hybrid Ensemble Learning Framework for Predicting Lumbar Disc Herniation Recurrence: Integrating Supervised Models, Anomaly Detection, and Threshold Optimization by Mădălina Duceac (Covrig), Călin Gheorghe Buzea, Alina Pleșea-Condratovici, Lucian Eva, Letiția Doina Duceac, Marius Gabriel Dabija, Bogdan Costăchescu, Eva Maria Elkan, Cristian Guțu, Doina Carina Voinescu

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Machine learning-based identification of key factors and spatial heterogeneity analysis of urban flooding: a case study of the central urban area of Ordos by Yu Qin, Yingdong Yu, Jiahong Liu, Ruifen Liu

“…This study uses urban flood susceptibility (UFS) as an indicator, and comprehensively applies three machine learning models, XGBoost, CatBoost and LightGBM, in the Kangyi area of Ordos City. …”
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OperonSEQer: A set of machine-learning algorithms with threshold voting for detection of operon pairs using short-read RNA-sequencing data. by Raga Krishnakumar, Anne M Ruffing

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Detection of driving factors and critical thresholds for carbon sequestration capacity in urban agglomerations using a combined causal inference and machine learning approach by Yin Zhang, Weibo Ma, Nan Wang, Lijun Zhao, Qingwu Hu, Shaogang Lei, Haidong Li

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