Enhancing precision in multiple sclerosis lesion segmentation: A U-net based machine learning approach with data augmentation by Oezdemir Cetin, Berkay Canel, Gamze Dogali, Unal Sakoglu

“…This study proposes a robust machine learning algorithm designed to identify MS lesions using both single-modal and multi-modal MRI data. …”
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Tracking and climbing behavior recognition of heavy-duty trucks on roadways by Lei Tang, Jingchi Jia, Zongtao Duan, Jingyu Ma, Xin Wang, Weiwei Kong

“…A heavy-duty truck mobility (HVMove) model is constructed based on the map information to apply the roadway geometry to the tracking and behavior recognition algorithm. We develop an extended Metropolis–Hastings algorithm to tune the parameters of the HVMove model. …”
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European sovereign debt control through reinforcement learning by Tato Khundadze, Willi Semmler, Willi Semmler, Willi Semmler

“…We demonstrate that the Soft Actor-Critic algorithm provides comparable or, in some cases, better solutions to multi-objective macroeconomic optimization problems, in comparison to Nonlinear Model Predictive Control (NMPC) algorithm.…”
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Mining patterns of comorbidity evolution in patients with multiple chronic conditions using unsupervised multi-level temporal Bayesian network. by Syed Hasib Akhter Faruqui, Adel Alaeddini, Carlos A Jaramillo, Jennifer S Potter, Mary Jo Pugh

“…We also use a longest path algorithm to identify the most likely sequence of comorbidities emerging from and/or leading to specific chronic conditions. …”
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Applying interpretable machine learning to assess intraspecific trait divergence under landscape‐scale population differentiation by Sambadi Majumder, Chase M. Mason

“…Methods Recursive feature elimination was applied to functional trait data from the HeliantHOME database, followed by the application of the Boruta algorithm to detect the traits that are most predictive of ecoregion. …”
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Traffic congestion forecasting using machine learning methods by Ramil R. Zagidullin, Almaz N. Khaybullin

“…To identify patterns in the data, additive time series decomposition, spectral analysis based on the fast Fourier transform, and autocorrelation analysis were applied. The predictive model was implemented using a two-stage approach: the classical ARIMA algorithm was used for baseline forecasting, while an LSTM architecture with two recurrent layers and regularization was trained on 24-hour sequences. …”
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Lithium-ion battery state of health estimation using intelligent methods by Hemavathi S

“…This study proposes an intelligent SOH estimation algorithm utilizing Feed-forward and Recurrent Neural Networks, trained with the Levenberg-Marquardt function, to predict battery SOH under various aging conditions. …”
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Real-time urban regional route planning model for connected vehicles based on V2X communication by Pangwei Wang, Hui Deng, Juan Zhang, Mingfang Zhang

“…Second, according to the topology structure of the current regional road network, all predicted routes are listed based on the Dijkstra algorithm. …”
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Confidence-Aware Ship Classification Using Contour Features in SAR Images by Al Adil Al Hinai, Raffaella Guida

“…Additionally, the information entropy is presented as a valuable metric for quantifying the confidence (or uncertainty) associated with classification predictions. Two segmentation methods for the contour extraction were investigated: a classical approach using the watershed algorithm and a U-Net architecture. …”
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Enhancing Hazard Detection and Risk Severity Assessment in Construction through Multinomial Naive Bayes and Regression by Akaninyene Michael Akwaisua, Anietie Ekong, Godwin Ansa

“…Using the Linear Regression algorithm, the model predicts the severity of risks based on textual descriptions of a hazard.  …”
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CHARACTERISTICS OF THE NOISE STABILITY OF RADIO COMMUNICATION SYSTEMS WITH FREQUENSY HOPING by I. I. Skib, A. V. Martsinovich, E. L. Kreidik, V. A. Cherdyntsev

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Cheby-KANs: Advanced Kolmogorov–Arnold Networks for Applying Geometric Deep Learning in Quantum Chemistry Applications by Amgad Abdallah Mahmoud, Andreas Pester, Maha M. Muttardi, Frederic Andres, Shihori Tanabe, Nicolas Greneche, Hesham H. Ali

“…In this work, we present an enhanced version of the Kolmogorov–Arnold network (KAN) algorithm, called Cheby-KAN, that offers a more efficient, more reliable, and faster alternative to conventional KANs. …”
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Smart Odour Sensing for Automated Monitoring of Bread Products by Carmen Bax, Bianca di Diodoro, Alessandro Ticozzi, Nicolò Dellarosa, Flavio Corazza, Giacomo Langfelder, Laura Capelli

“…This work proposes an electronic nose (e-nose) system based on resistive gas sensors to predict the cooking evolution of different types of bread. …”
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Optimal by criterion of minimum of average risk adaptive device for decision meaning considering correlation properties of the reflected signal by S. A. Gabets, S. U. Sedushev, R. A. Hutsau

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Protection of confidentiality of medical data PATIENTS by A. A. Givojno, V. N. Rostovtsev

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Identification of Perceptual Phonetic Training Gains in a Second Language Through Deep Learning by Georgios P. Georgiou

“…This study addresses this gap by developing a deep learning algorithm designed to identify perceptual gains resulting from second language (L2) phonetic training. …”
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An ensemble learning strategy for multi‐source hydrogen embrittlement data by introducing missing information by Xujie Gong, Ruichao Lei, Ruize Sun, Xue Jiang, Yanjing Su, Yu Yan

“…Abstract Accurately and quickly predicting hydrogen embrittlement performance is critical for the service of metal materials. …”
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A new model of dry firn-densification constrained by continuous strain measurements near South Pole by C. Max Stevens, David A. Lilien, Howard Conway, T. J. Fudge, Michelle R. Koutnik, Edwin D. Waddington

“…We use the data to derive a new firn-densification algorithm framed as a constitutive relationship. We also compare our measurements to compaction rates predicted by several existing firn-densification models. …”
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Exploring machine learning classification for community based health insurance enrollment in Ethiopia by Seyifemickael Amare Yilema, Seyifemickael Amare Yilema, Yegnanew A. Shiferaw, Yikeber Abebaw Moyehodie, Setegn Muche Fenta, Denekew Bitew Belay, Denekew Bitew Belay, Haile Mekonnen Fenta, Haile Mekonnen Fenta, Teshager Zerihun Nigussie, Ding-Geng Chen, Ding-Geng Chen

“…Therefore, this study aimed to identify the ML algorithm with the best predictive accuracy for CBHI enrollment and to determine the most influential predictors among the dataset.MethodsThe 2019 Ethiopian Mini Demographic and Health Survey (EMDHS) data were used. …”
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Estimation of gas hydrate and free gas saturation using the rock physics model based on constrained least squares and trust region method in the Shenhu Area, South China Sea by Dajiang Meng, Dajiang Meng, Ruwei Zhang, Ruwei Zhang, Yuan Gu, Yuan Gu, Baojin Zhang, Baojin Zhang, Yunqian Lu, Yunqian Lu, Jiangnan Lin, Jiangnan Lin, Lijie Wang, Lijie Wang

“…Additionally, the application results indicate that the trust region algorithm demonstrates favorable global convergence.…”
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