Producing Landslide Susceptibility Maps Using Statistics and Machine Learning Techniques: The Rize-Taşlıdere Basin Example by Arif Çağdaş Aydınoğlu, Gehver Altürk

“…Using the landslide inventory and input parameters, a parameter analysis was performed for the landslide susceptibility map in five classes by employing the frequency ratio (FR), logistic regression (LR), and artificial neural network (ANN) methods. …”
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Phenolic content discrimination in Thai holy basil using hyperspectral data analysis and machine learning techniques. by Apichat Suratanee, Panita Chutimanukul, Tanapon Saelao, Supachitra Chadchawan, Teerapong Buaboocha, Kitiporn Plaimas

“…In this study, we employed hyperspectral imaging combined with machine learning techniques to determine the levels of total phenolic contents in Thai holy basil. …”
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Comparative Analysis of Machine Learning Approaches for Fetal Movement Detection with Linear Acceleration and Angular Rate Signals by Lucy Spicher, Carrie Bell, Kathleen H. Sienko, Xun Huan

“…Reduced fetal movement (RFM) can indicate that a fetus is at risk, but current monitoring methods provide only a “snapshot in time” of fetal health and require trained clinicians in clinical settings. …”
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Clinical obstacles to machine-learning POCUS adoption and system-wide AI implementation (The COMPASS-AI survey) by Adrian Wong, Nurul Liana Roslan, Rory McDonald, Julina Noor, Sam Hutchings, Pradeep D’Costa, Gabriele Via, Francesco Corradi

“…The integration of artificial intelligence (AI) and machine learning (ML) holds significant promise to enhance POCUS capabilities further. …”
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Innovative Machine Learning Approach for Distinguishing Rheumatoid Arthritis and Osteoarthritis: Integrating Shapely Additive Explanations and Dendrograms by Alexander A. Huang, Samuel Y. Huang

“…Cluster 1 of the heatmap and dendrogram also included Income to Poverty Ratio, Direct HDL Cholesterol (mmol/L), BMXHIP–Hip Circumference, Folate DFE, and Globulin indicating they were most similar in having high aggregate gain, cover, and frequency metrics. Conclusion: Machine learning models that incorporate dendrograms and heat maps can offer additional summaries of model statistics that assist in differentiating factors between osteoarthritis and rheumatoid arthritis. …”
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Magnitude and Impact of Hallucinations in Tabular Synthetic Health Data on Prognostic Machine Learning Models: Validation Study by Lisa Pilgram, Samer El Kababji, Dan Liu, Khaled El Emam

“…ObjectiveThis study aims to investigate the magnitude of hallucinations in tabular synthetic data, whether their frequency increases with training data complexity, and the extent to which they impact the utility of synthetic data for downstream prognostic machine learning (ML) modeling tasks. …”
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Audio-Based Engine Fault Diagnosis with Wavelet, Markov Blanket, ROCKET, and Optimized Machine Learning Classifiers by Bernardo Luis Tuleski, Cristina Keiko Yamaguchi, Stefano Frizzo Stefenon, Leandro dos Santos Coelho, Viviana Cocco Mariani

“…The audio data are broken down into sub-time series with various frequencies and resolutions using the WPT. These data are subsequently utilized as input for obtaining an informative feature subset using a Markov blanket-based selection method. …”
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Construction and Validation of a Machine Learning-Based Risk Prediction Model for Sleep Quality in Patients with OSA by Tong Y, Wen K, Li E, Ai F, Tang P, Wen H, Guo B

“…The SHapley Additive exPlanation (SHAP) analysis was used to interpret the model and identify key predictors of sleep quality.Results: The LightGBM model demonstrated the best predictive performance, with an AUC of 0.910 in the validation set, outperforming support vector machine and random forest. SHAP analysis identified six key predictors of sleep quality: depressive symptoms, OSA duration, oxygen desaturation index (ODI), anxiety symptoms, exercise frequency, and coffee consumption. …”
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Identifying presence or absence of grizzly and polar bear cubs from the movements of adult females with machine learning by Erik M. Andersen, Justin G. Clapp, Milan A. Vinks, Todd C. Atwood, Daniel D. Bjornlie, Cecily M. Costello, David D. Gustine, Mark A. Haroldson, Lori L. Roberts, Karyn D. Rode, Frank T. van Manen, Ryan R. Wilson

“…Reproduction could be documented remotely, however, from post-denning movement data if discernable differences exist between females with and without cubs. Methods We trained support vector machines (SVMs) with eight variables derived from telemetry data of female grizzly (2000–2022) and polar bears (1985–2016) with or without cubs during seven periods with lengths ranging from 5 to 60 days starting at den departure. …”
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A predictive machine-learning model for clinical decision-making in washed microbiota transplantation on ulcerative colitis by Sheng Zhang, Gaochen Lu, Weihong Wang, Qianqian Li, Rui Wang, Zulun Zhang, Xia Wu, Chenchen Liang, Yujie Liu, Pan Li, Quan Wen, Bota Cui, Faming Zhang

“…This study aimed to build a machine learning model on washed microbiota transplantation (WMT) for ulcerative colitis (UC), providing patients and clinicians with a new evaluation system to optimize clinical decision-making.MethodsPatients with UC who underwent WMT via mid-gut or colonic delivery route at an affiliated hospital of Nanjing Medical University from April 2013 to June 2022 were recruited. …”
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Synthesis of Vibration Environment Spectra and Fatigue Assessment for Underfloor Equipment in High-Speed EMU Trains by Can Chen, Lirong Guo, Guoshun Li, Yongheng Li, Yichao Zhang, Hongwei Zhang, Dao Gong

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DESIGN OF BED SADDLE OF HIGH-SPEED PRECISION CNC LATHE BASED ON TOPOLOGY OPTIMIZATION by DUAN MingDe, LI Yan, GU JiaJia, ZHANG ZhuangYa

“…In order to meet the condition of high precision,efficiency and speed of modern NC machine tools and to improve the static,dynamic performance as well as lightweight design of their basic components,the design of bed saddle which is the key components of ADGM numerical control machine tool was optimized based on topology optimization method. …”
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Machine learning guided thermal management of Open Computing Language applications on CPU‐GPU based embedded platforms by Rakesh Kumar, Bibhas Ghoshal

“…Our experiments with OpenCL applications on the state of the art ODROID XU4 embedded platform show that the CPU cores of the experimental board if operated at a frequency proposed by our Machine Learning‐based predictive method brings about 12.5°C reduction in processor temperature at 1.06% degradation in performance compared to the baseline frequency (default performance frequency governor of the embedded platform).…”
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High-Resolution Rotor Fault Diagnosis of Wound Rotor Induction Machine Based on Stator Current Signature Analyses by Reza Ghadirinezhd, Mohammad Hoseintabar-Marzebali

“…In recent years, stator current signature analysis due to simplicity, cost-effectiveness, and availability has been considered for fault detection process in comparison with previous conventional methods such as acoustic and vibration. In this paper, a high-resolution technique based on the chirp-Z transform is used for rotor asymmetry fault (RAF) detection in induction machines through stator current signature analysis. …”
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Moving Towards the Reliability-oriented Design of Hairpin Winding for EV Traction Machines Driven by SiC Inverter by Xiaowei Ju, Yue Zhang, Zhiwei Xue, Yuan Cheng, Shumei Cui

“…With the development of high-frequency and high-voltage traction machines (TM) incorporating hairpin windings (HW) and SiC inverters for electric vehicles (EV), both the interturn voltage stress and temperature within HW are rising, increasing the risk of partial discharge (PD), and presenting significant challenges to insulation safety. …”
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Investigation on the Relationship Between the Vibratory Peening Process Parameters and Almen Intensity by Maxime Paques, Miao Hong Yan, Changeux Benoit, Turenne Sylvain, Badreddine Jawad, Martin Etienne

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Fine-Tuned Machine Learning Classifiers for Diagnosing Parkinson’s Disease Using Vocal Characteristics: A Comparative Analysis by Mehmet Meral, Ferdi Ozbilgin, Fatih Durmus

“…<b>Methods</b>: This study used a publicly available dataset of vocal samples from 188 people with PD and 64 controls. …”
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Enhanced Fault Diagnosis in Milling Machines Using CWT Image Augmentation and Ant Colony Optimized AlexNet by Niamat Ullah, Muhammad Umar, Jae-Young Kim, Jong-Myon Kim

“…A method is proposed for fault classification in milling machines using advanced image processing and machine learning. …”
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A new framework for landslide susceptibility mapping in contiguous impoverished areas using machine learning and catastrophe theory by Wei Zhou, Yingzhi Zhou, Shuneng Liang, Chengnian Zhang, Hongzhou Dai, Xiaofei Sun

“…First, we selected 12 factors representing both internal environmental and external triggering conditions to assess landslide susceptibility. The frequency ratio method was used to assess the correlation between historical landslides and these factors. …”
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Development and Validation of an Interpretable Machine Learning Model for Predicting Tic Disorders and Severity in Children Based on Electroencephalogram Data by Wanting Xiang, Gang Zhu, Yichong Hou, Zhandong Mei, Lin Wan, Li Zhang, Guang Yang, Jian Zu

“…A two-stage progressive diagnosis framework based on EEG data and machine learning methods was developed. To achieve individualized prediction and reduce the feature dimension, we proposed a novel individual-based feature-weighted integration method in machine learning, as well as a new SHAP-driven feature selection and weighting (SFSW) strategy to improve the prediction accuracy. …”
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