Evaluating the generalisability of region-naïve machine learning algorithms for the identification of epilepsy in low-resource settings. by Ioana Duta, Symon M Kariuki, Anthony K Ngugi, Angelina Kakooza Mwesige, Honorati Masanja, Daniel M Mwanga, Seth Owusu-Agyei, Ryan Wagner, J Helen Cross, Josemir W Sander, Charles R Newton, Arjune Sen, Gabriel Davis Jones

“…Model performances and parameters were then compared across every permutation of sites. …”
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Interpretable machine learning approaches to assess the compressive strength of metakaolin blended sustainable cement mortar by Naseer Muhammad Khan, Liqiang Ma, Waleed Bin Inqiad, Muhammad Saud Khan, Imtiaz Iqbal, Muhammad Zaka Emad, Saad S. Alarifi

“…A comprehensive dataset compiled from published literature having five input parameters including water-to-binder ratio, mortar age, and maximum aggregate diameter etc. was used for this purpose. …”
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Balancing Complexity and Performance of Machine Learning Models for Avian Pests Sound Detection in Agricultural Environments by Micheline Kazeneza, Anna Sergeevna Bosman, Destiny Kwabla Amenyedzi, Damien Hanyurwimfura, Emmanuel Ndashimye, Anthony Vodacek

“…This necessitates optimized machine learning (ML) solutions for low-power edge devices. …”
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Characterizing low femoral neck BMD in Qatar Biobank participants using machine learning models by Nedhal Al-Husaini, Rozaimi Razali, Amal Al-Haidose, Mohammed Al-Hamdani, Atiyeh M. Abdallah

“…Abstract Background Identifying determinants of low bone mineral density (BMD) is crucial for understanding the underlying pathobiology and developing effective prevention and management strategies. Here we applied machine learning (ML) algorithms to predict low femoral neck BMD using standard demographic and laboratory parameters. …”
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Gait-based Parkinson’s disease diagnosis and severity classification using force sensors and machine learning by Navita, Pooja Mittal, Yogesh Kumar Sharma, Anjani Kumar Rai, Sarita Simaiya, Umesh Kumar Lilhore, Vimal Kumar

“…Abstract A dual-stage model for classifying Parkinson’s disease severity, through a detailed analysis of Gait signals using force sensors and machine learning approaches, is proposed in this study. …”
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Leveraging Machine Learning and Remote Sensing for Water Quality Analysis in Lake Ranco, Southern Chile by Lien Rodríguez-López, Lisandra Bravo Alvarez, Iongel Duran-Llacer, David E. Ruíz-Guirola, Samuel Montejo-Sánchez, Rebeca Martínez-Retureta, Ernesto López-Morales, Luc Bourrel, Frédéric Frappart, Roberto Urrutia

“…This study examines the dynamics of limnological parameters of a South American lake located in southern Chile with the objective of predicting chlorophyll-a levels, which are a key indicator of algal biomass and water quality, by integrating combined remote sensing and machine learning techniques. …”
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Energy‐Efficient Hardware Implementation of Spiking‐Restricted Boltzmann Machines Using Pseudo‐Synaptic Sampling by Hyunwoo Kim, Suyeon Jang, Uicheol Shin, Masatoshi Ishii, Atsuya Okazaki, Megumi Ito, Akiyo Nomura, Kohji Hosokawa, Sungmin Lee, Matthew BrightSky, Sangbum Kim

“…Stochastic sampling is performed to reduce hardware energy consumption and prevent overfitting by reducing parameters, because not all data are required for learning. …”
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Integrating Dimensional Analysis and Machine Learning for Predictive Maintenance of Francis Turbines in Sediment-Laden Flow by Álvaro Ospina, Ever Herrera Ríos, Jaime Jaramillo, Camilo A. Franco, Esteban A. Taborda, Farid B. Cortes

“…This understanding, in turn, informs the selection and interpretation of features for machine learning (ML) models aimed at the predictive maintenance of the target variable and important features for the next stage. …”
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Emergency Department Blood Pressure Management in Type B Aortic Dissection: An Analysis with Machine Learning by Nelson Chen, Jessica V. Downing, Jacob Epstein, Samira Mudd, Angie Chan, Sneha Kuppireddy, Roya Tehrani, Isha Vashee, Emily Hart, Emily Esposito, Rose Chasm, Quincy K. Tran

“…Conclusion: Many patients with type B AAD did not achieve hemodynamic parameters in line with 2010 or 2022 AHA guidelines while being in the ED prior to transferring to a quaternary care center for further evaluation and management. …”
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Objective assessment of gait and posture symptoms in Parkinson’s disease using wearable sensors and machine learning by Lingyan Ma, Lingyan Ma, Shinuan Lin, Shinuan Lin, Jianing Jin, Jianing Jin, Zhan Wang, Zhan Wang, Xuemei Wang, Xuemei Wang, Zhonglue Chen, Zhonglue Chen, Yun Ling, Yun Ling, Fei Zhang, Fei Zhang, Kang Ren, Kang Ren, Tao Feng, Tao Feng, Tao Feng

“…The dataset was randomly split into a training set (80%) and an independent test set (20%) with balanced age, sex, and PD duration. Two machine learning models—extreme gradient boosting (XGBoost) and support vector machine (SVM)—were trained to predict scores for five gait and posture items (#3.9–3.13) from the MDS-UPDRS III.ResultsXGBoost was chosen as the final model due to its better performance than SVM. …”
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Optimization of Gray Level Co-occurrence Matrix (GLCM) Texture Feature Parameters in Determining Rice Seed Quality by Aji Setiawan, Adam Arif Budiman

“…The results indicate that certain parameter configurations significantly affect the discriminative power of the extracted features, with the Support Vector Machine (SVM) classifier achieving the highest performance at a pixel distance of 1, with an accuracy of 0.73, precision of 0.79, recall of 0.73, and F1-score of 0.72. …”
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Perspective contact imprint parameters of road roller working body with bearing surface when compacting road materials by S. V. Saveliev, R. E. Litovchenko, A. A. Yurchenko

“…Introduction. The most efficient machine for compacting road building materials in the construction of transport facilities, a road roller with a promising pneumatic tire roller that can effectively use vibration, is considered.Materials and methods. …”
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Multi-Parameter Water Quality Inversion in Heterogeneous Inland Waters Using UAV-Based Hyperspectral Data and Deep Learning Methods by Hongran Li, Nuo Wang, Zixuan Du, Deyu Huang, Mengjie Shi, Zhaoman Zhong, Dongqing Yuan

“…The experimental results demonstrate that TL-Net markedly outperforms conventional machine learning approaches, delivering consistently high predictive accuracy across all evaluated water quality parameters. …”
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Predicted sewing thread consumption using neural network method based on the physical and structural parameters of knitted fabrics by Khedher Faouzi, Hamdi Thouraya, Jaouachi Boubaker, Jmali Mohamed

“…This work allows for examining the effects of the sewing machine foot pressure height, surface mass, fabric thickness, and number of layers sewn on thread consumption. …”
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DETECTION OF Β THALASSEMIA CARRIERS BY RED CELL PARAMETERS OBTAINED FROM AUTOMATIC COUNTERS USING MATHEMATICAL FORMULAS by Idit Lachover Roth, Boaz Lachover, Guy Koren, Carina Levin, Luci Zalman, Ariel Koren

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Investigating the Effect of Climatic Parameters Predicting the Mortality Rate Due to Cardiovascular and Respiratory Disease with Soft Computing Methods by Hamidreza Ghazvinian, Hojat Karami

“…This study was conducted with the aim of comparing the performance of multilayer perceptron (MLP) neural network, radial basis function (RBF) and regression support vector machine (SVR) methods in modeling and predicting the time series of mortality caused by cardiovascular and respiratory diseases based on climatic parameters and pollutants. …”
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Optimizing the neural network and iterated function system parameters for fractal approximation using a modified evolutionary algorithm by Sana Abdulla, K. Mahipal Reddy

“…However, optimizing the parameters of Iterated Function System (IFS)-based fractal interpolants remains a challenging task, particularly for Rational Fractal Cubic (RFC) splines, which offer greater flexibility in shape control. …”
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The intensity of geomagnetic storms associated with the interplanetary magnetic field and solar wind parameters during Solar Cycle 24 by Anwar Santoso, Sismanto Sismanto, Rhorom Priyatikanto, Eddy Hartantyo, Dyah R. Martiningrum

“…In this article, we present an analysis of the interplanetary magnetic field (IMF) and solar wind parameters relevant to 100 geomagnetic storms in Solar Cycle 24. …”
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Effect of contour process parameters on the surface roughness of laser powder bed fusion manufactured 304 stainless steel by Mashayamombe Tafadzwa, Madyibi Xola, Matope Stephen

“…In this study, the authors investigated the effect of contour process parameters on the surface roughness of vertical surfaces and sloped surfaces associated with up and down surfaces fabricated by LPBF using 304 stainless steel (304 SS) powder feedstock. …”
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DETERMINATION OF OSCILLATOR CIRCUIT PARAMETERS OF A MATHEMATICAL MODEL OF THE DYNAMICS OF THE CUTTING PROCESS WITH A METAL CUTTING TOOL by M. R. Akhmedova, R. V. Guseynov

“…The calculated dependences allow the parameters of  the Machine-Device-Tool-Part (MDTP) system to be set with an  acceptable accuracy when analysing metal processing dynamics  using metal cutting tools. …”
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