A Short-Term Risk Prediction Method Based on In-Vehicle Perception Data by Xinpeng Yao, Nengchao Lyu, Mengfei Liu

“…The method incorporates Monte Carlo simulation for threshold calibration, Boruta-based feature selection, and multiple machine learning models, including the light gradient-boosting machine (LGBM), with performance interpretation via SHAP analysis. …”
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Physiological and Morphological Characterization of Organotypic Cocultures of the Chick Forebrain Area MNH and its Main Input Area DMA/DMP by Heike Endepols, Julia Jungnickel, Katharina Braun

“…Cocultures of the learning-relevant forebrain region mediorostrai neostriatum and hyperstriatum ventrale (MNH) and its main glutamatergic input area nucleus dorsomedialis anterior thalami/posterior thalami were morphologically and physiologically characterized. …”
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Synthetic ECG signal generation using generative neural networks. by Edmond Adib, Fatemeh Afghah, John J Prevost

“…Therefore, there is always a need for more ECG data, especially for the training of automatic diagnosis machine learning models, which perform better when trained on a balanced dataset. …”
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Traffic travel pattern recognition based on sparse Global Positioning System trajectory data by Juan Chen, Kepei Qi, Shiyu Zhu

“…Finally, the three machine learning models of support-vector machine, decision tree, and convolutional neural network are used for comparison experiments. …”
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Electronic Information Signal Recognition Based on a Stochastic Neural Network Algorithm by Jiaye Wang

“…TSVD-SCN performs SVD decomposition on the hidden layer output of the network and sets a threshold to remove the smaller singular values, so as to reduce the number of conditions of the hidden layer output matrix and improve the network recognition rate. …”
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Theory and practice of family education in Germany by Kateřina Neubauerová

“…Family education is characterised by a coordinated, structured and continuous provision of free, low-threshold educational opportunities for families. …”
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Good practice for assignment of breeds and populations—a review by H. Wilmot, H. Wilmot, N. Gengler

“…In the case selection of SNPs is necessary, we advise the use of one stage methodologies and to define a threshold for this selection. Then, machine learning can be used to develop the model per se, based on the selected or available markers. …”
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CityCenter, Las Vegas: 'De-Theming' in the Neoliberal City by Kurt Kraler

“…The sprawling resort campus signalled a departure from all-encompassing themes of kitsch that had long defined the Las Vegas Strip, obfuscating the threshold between public and private. It is indicative of the broader push for deregulation and monopolization that are characteristic of neoliberal processes. …”
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Conformal Segmentation in Industrial Surface Defect Detection with Statistical Guarantees by Cheng Shen, Yuewei Liu

“…With the threshold, defective pixels with high probability in test images are extracted to construct prediction sets. …”
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Energy-Efficient Fall-Detection System Using LoRa and Hybrid Algorithms by Manny Villa, Eduardo Casilari

“…This study introduces a hybrid system that integrates a threshold-based model for preliminary detection with a deep learning-based approach that combines a CNN (Convolutional Neural Network) for spatial feature extraction with a LSTM (Long Short-Term Memory) model for temporal pattern recognition, aimed at improving classification accuracy. …”
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A Method of Printing Defect Detection Based on DCGAN by WANG Hai-tao, GAO Yu-dong, HOU Jian-xin, HE Yong-jun, CHEN De-yun

“…In recent years, deep learning has been widely used in defect detection. …”
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Abnormal Electricity Consumption Behaviors Detection Based on Improved Deep Auto-Encoder by Nvgui LIN, Lanxiu HONG, Daoshan HUANG, Yang YI, Zhixuan LIU, Qifeng XU

“…Firstly, the data of normal electricity users are employed as training samples, and the effective features of the data are automatically extracted by AE; and then the data is reconstructed to calculate the detection threshold. Because the effective data characteristics are destroyed by the abnormal behaviors, the abnormal behaviors can be detected through comparing the difference between the reconstruction error and the detection threshold. …”
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A model of occupational stress to assess impact of COVID-19 on critical care and redeployed nurses: a mixed-methods study by Janice Rattray, Jordan Miller, Beth Pollard, Louise McCallum, Alastair Hull, Pam Ramsay, Lisa Salisbury, Teresa Scott, Stephen Cole, Diane Dixon

“…Findings Three-quarters of nurses reached threshold for psychological distress, approximately 50% reached threshold for burnout emotional exhaustion and a third clinically concerning post-traumatic stress symptoms. …”
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The value of a combined model based on ultra-radiomics and multi-modal ultrasound in the benign-malignant differentiation of C-TIRADS 4A thyroid nodules: a prospective multicenter... by Shuai Cui, Qifan Liu, Hailong Wang, Husha Li, Wei Li, Chenlong Li, Leilei Bi, Yang Mu, Wenjing Guo, Jundong Yao, Zhoulong Zhang

“…Based on 17 ultrasound radiomics features, a radiomics model was constructed using the RF machine learning algorithm. The combined model was developed by combining the two aforementioned models. …”
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Lameness Recognition of Dairy Cows Based on Compensation Behaviour Analysis by Swing and Posture Features from Top View Depth Image by Ruihong Zhang, Kaixuan Zhao, Jiangtao Ji, Jinjin Wang

“…Lameness classification models were constructed using machine learning and threshold discrimination methods, achieving classification accuracies of 81.6% and 83.05%, respectively. …”
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Predicting Suicide or Self-Harm Crises Based on Decision Tree Analysis of Life Events and Coping Style: A Population-Based Study in China by Shumeng Ma, Ping Li, Liwen Ren, Ning Jia

“…Among male students, only interpersonal relationships exceeded the 10% threshold in importance, whereas a wider range of events surpassed this threshold for female students. …”
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Intelligent Trust Evaluation Method for Underwater Sensor Networks Based on Fuzzy Clustering and Dynamic Weight Allocation by Zhaohui WANG, Guangjie HAN, Jiaxin DU, Chuan LIN, Lei WANG

“…Then, the unsupervised machine learning algorithm, namely fuzzy C-means clustering, was employed to enable adaptive node trust decision-making. …”
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Development of a Wireless Sensor Network and IoT-based Smart Irrigation System by Juliana Ngozi Ndunagu, Kingsley Eghonghon Ukhurebor, Moses Akaaza, Robert Birundu Onyancha

“…The data collected are then analyzed at the edge server and updated every 15 minutes. Based on the threshold value, the system starts pumping water or stops the irrigation process depending on the irrigation schedule. …”
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Galaxy morphology classification: are stellar circularities enough? by Baucalo Katarina, Mitrašinović Ana

“…We also discuss the potential for this classification to support machine learning efforts as a baseline or training set for future morphological studies.…”
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Triplet Spatial Reconstruction Attention-Based Lightweight Ship Component Detection for Intelligent Manufacturing by Bocheng Feng, Zhenqiu Yao, Chuanpu Feng

“…Future research directions include developing adaptive threshold learning mechanisms for varying industrial conditions and integration with surface defect detection capabilities to enhance comprehensive quality control in intelligent manufacturing systems.…”
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