Non-invasive ML methods for diagnosis of congenital heart disease associated with pulmonary arterial hypertension by Yuyang Gao, Pengyue Ma, Jiahua Pan, Hongbo Yang, Tao Guo, Weilian Wang

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Optimizing Tumor Detection in Brain MRI with One-Class SVM and Convolutional Neural Network-Based Feature Extraction by Azeddine Mjahad, Alfredo Rosado-Muñoz

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Metasurface-enabled multifunctional single-frequency sensors without external power by Masaya Tashiro, Kosuke Ide, Kosei Asano, Satoshi Ishii, Yuta Sugiura, Akira Uchiyama, Hiroki Wakatsuchi

“…Moreover, we provide a method for predicting physical parameters via the machine learning-based approach of random forest regression. …”
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A Method of the Vibration Information Detection for Rotating Machinery Based on the Rolling-Shutter CMOS and Digital Image Processing by Yonggong Yuan, Ji Zhang, Nanwangdi Li, Haifeng Wang, Yuxin Hu, Yilong Wang, Ning Mei, Han Yuan

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Forecasting Eruptions at Steamboat Geyser: Time Scales, Differentiability, and Detectability of Seismic Precursors Through Data‐Driven Methods by Alberto Ardid, Anna Barth, David Dempsey, Michael Manga, Shane J. Cronin

“…Seismic features with the most predictive power include autocorrelations, longest strike above the mean, and change quantiles, particularly within the 4.5–16 Hz frequency range. We applied isotonic regression, a method that converts raw model outputs into calibrated probabilities, to improve the interpretability of eruption forecasting outputs. …”
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A Lightweight Kernel Density Estimation and Adaptive Synthetic Sampling Method for Fault Diagnosis of Rotating Machinery with Imbalanced Data by Wenhao Lu, Wei Wang, Xuefei Qin, Zhiqiang Cai

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Hilbert-Huang Transform and machine learning based electromechanical analysis of induction machine under power quality disturbances by V. Indragandhi, R. Senthil Kumar, R. Saranya

“…Monitoring and predicting Power Quality (PQ) is crucial for quickly minimizing risk, protecting induction machines (IMs), and increasing productivity. This paper proposes an electromechanical analytical framework for IM working with various PQ disturbances based on machine learning (ML). …”
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Characterizing privacy in quantum machine learning by Jamie Heredge, Niraj Kumar, Dylan Herman, Shouvanik Chakrabarti, Romina Yalovetzky, Shree Hari Sureshbabu, Changhao Li, Marco Pistoia

“…We further investigate conditions for a strong privacy breach, where original input data can be recovered from snapshots by classical or quantum-assisted methods. We establish properties of the encoding map, such as classical simulatability, overlap with DLA basis, and its Fourier frequency characteristics that enable such a privacy breach of VQC models. …”
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Optimization of welding strength in the tungsten inert gas welding process for aluminium alloys by Amit Gupta, Rajeev Ranjan, Robert Cep, Ajay Kumar, Ajay Kumar, Sanjay Kumar Jha, Faisal Altarazi, Ashish Kumar, Namrata Dogra

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Dependency of the pulse dynamic electrochemical machining characteristics of Allvac 718 plus in NaNO3 solution on the machining paraments by Moqi Shen, Shuanglu Duan, Zhengrui Zhou, Zhichun Zhang, Jia Liu, Di Zhu

“…Subsequently, PDECM experiments were conducted on ATI718 Plus under different duty cycles, vibration frequencies, and applied voltages. The relationships between these processing parameters and the machining quality of ATI718 Plus were explored by examining the post-processing microstructure, surface roughness, material dissolution rate, and machining precision. …”
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Investigating the effects of Gaussian noise on epileptic seizure detection: The role of spectral flatness, bandwidth, and entropy by Nuri Ikizler, Gunes Ekim

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Enhanced Channel Estimation for RIS-Assisted OTFS Systems by Introducing ELM Network by Mintao Zhang, Zhiying Liu, Li Wang, Wenquan Hu, Chaojin Qing

“…In high-mobility communication scenarios, leveraging reconfigurable intelligent surfaces (RISs) to assist orthogonal time frequency space (OTFS) systems proves advantageous. …”
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A Multilevel and Hierarchical Approach for Multilabel Classification Model in SDGs Research by Berliana Sugiarti Putri, Lya Hulliyyatus Suadaa, Efri Diah Utami

“…This study aimed to implement and evaluate problem transformation methods and machine learning classification algorithms with a multilevel and hierarchical approach to categorize research publications into SDG levels. …”
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Machine Learning-Based Damage Diagnosis in Floating Wind Turbines Using Vibration Signals: A Lab-Scale Study Under Different Wind Speeds and Directions by John S. Korolis, Dimitrios M. Bourdalos, John S. Sakellariou

“…Remote and automated diagnosis, including the stages of detection, identification, and severity characterization of early stage damages in FWTs through advanced vibration-based structural health monitoring (SHM) methods of the machine learning (ML) type, is evidently critical for timely repairs, extending their operational lifecycle, reducing maintenance costs, and enhancing safety. …”
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Comparison of Lithuanian and Polish Consonant Phonemes Based on Acoustic Analysis – Preliminary Results by Gražina KORVEL, Olga KURASOVA, Bożena KOSTEK

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Reaction Pathway Differentiation Enabled Fingerprinting Signal for Single Nucleotide Variant Detection by Huixiao Yang, Linghao Zhang, Xinmiao Kang, Yunpei Si, Ping Song, Xin Su

“…Through the application of machine learning to fluorescence kinetic data analysis, the classification of SNV and WT signals is automated with an accuracy of 99.6%, significantly exceeding the 80.7% accuracy of conventional methods. …”
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Music Performers Classification by Using Multifractal Features: A Case Study by Natasa RELJIN, David POKRAJAC

“…The results of proposed method were compared with those obtained using mel-frequency cepstral coefficients (MFCCs) as descriptors. …”
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Towards an annual urban settlement map in France at 10 m spatial resolution using a method for massive streams of Sentinel-2 data by Romain Wenger, David Michéa, Anne Puissant

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Numerical analyses of the influences of rock properties and joints on rock fragmentation in shaft sinking by drilling method by Pingping Xu, Jiuqun Zou, Xin Huang, Jihuan Han

“…This research is crucial for controlling the stability of drilling machine during shaft sinking by drilling method.…”
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Fusion of Deep and Time–Frequency Local Features for Melanoma Skin Cancer Detection by Hamidreza Eghtesaddoust, Morteza Valizadeh, Mehdi Chehel Amirani

“…Detecting MEL in the early stage can hugely increase the chance of a cure. There are several methods based on machine learning to detect MEL from dermoscopic images. …”
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