Static calculation of the dynamic deflection elements for separation devices by Pavlenko I. V., Liaposhchenko O. O., Demianenko M. M., Starynskyi O. Ye.

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Stochastic differential equation modeling approach for grading astrocytomas on brain MRI images by Mahsa Raisi-Nafchi, Mahnoosh Tajmirriahi, Hossein Rabbani, Zahra Amini

“…This paper presents a new preoperative classification method for astrocytomas, addressing the issue of data scarcity in medical imaging. This work leverages an advanced statistical modeling approach based on stochastic differential equations to analyze post-contrast T1-weighted brain MRI images that require minimal data and offer rapid processing times. …”
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Assessing the impact of pozzolanic materials on the mechanical characteristics of UHPC: analysis, and modeling study by Diar Fatah Abdulrahman Askari, Sardam Salam Shkur Shkur, Azad Abdwlqader Mohammed, Hersh F. Mahmood, Brwa Hamah Saeed Hamah Ali, Soran Abdrahman Ahmad

“…This article reviews previous experimental work on the use of various pozzolanic materials, including Silica Fume (SF), Fly Ash (FA), Ground Granulated Blast Furnace Slag (GGBS), Quartz Powder (QP), Rice Husk Ash (RHA), and Metakaolin (MT), in the production of Ultra-High Performance Concrete (UHPC).In addition to gathering previous experimental data on the use of various pozzolanic materials to predict the compressive strength of UHPC, the collected data are modeled using several statistical techniques, including Support Vector Machine (SVM), Ensemble Boosting Tree (EBT), and Artificial Neural Networks (ANN). …”
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Research on Fault Diagnosis of Traction Power Supply System Based on PSO-LSSVM by Lei ZHANG

“…A fault diagnosis model based on PSO optimized least squares support vector machine was established, and PCA algorithm was used to extract data characteristics as input of fault diagnosis model, and reduce input dimension. …”
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Breast Cancer Image Classification Using Phase Features and Deep Ensemble Models by Edgar Omar Molina Molina, Victor H. Diaz-Ramirez

“…Next, a three-channel image is created using the local phase, amplitude, and orientation features of the ROI. A feature vector is constructed for the processed mammogram using the developed CNN model. …”
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Application of Fuzzy-RBF-CNN Ensemble Model for Short-Term Load Forecasting by Mohini Yadav, Majid Jamil, Mohammad Rizwan, Richa Kapoor

“…In this article, the design of a hybrid short-term load forecasting model (STLF) is proposed. This work combines the features of an artificial neural network (ANN), ensemble forecasting, and a deep learning network. …”
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Development of machine learning models for the prediction of the skin sensitization potential of cosmetic compounds by Wu Qiao, Tong Xie, Jing Lu, Tinghan Jia

“…RNA-Seq was subsequently employed to analyze THP-1 cells, followed by differential expression gene (DEG) analysis and weighted gene co-expression net-work analysis (WGCNA). Using two data preprocessing methods and three feature extraction techniques, we constructed and validated models with eight machine learning algorithms. …”
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A Comparative Study of Machine Learning Models for Short-Term Load Forecasting by Etna Vianita, Henri Tantyoko

“…This study presented a comparative analysis of five machine learning models namely XGBoost, Random Forest, Multi-Layer Perceptron (MLP), Support Vector Regression (SVR), and LightGBM using real-world electricity demand data collected over a four-month period. …”
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Ion channel classification through machine learning and protein language model embeddings by Ghazikhani Hamed, Butler Gregory

“…This study extends our previous work on protein language models for ion channel prediction, significantly advancing the methodology and performance. …”
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Modeling energy consumption indexes of an industrial cement ball mill for sustainable production by Saeed Chehreh Chelgani, Rasoul Fatahi, Ali Pournazari, Hamid Nasiri

“…Such a CL model for a cement mill can be used for training operators, controlling the process, saving time and energy, reducing laboratory work, and scaling issues, and finally enhancing sustainability.…”
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A mathematical model of the gravitational potential of the planet taking into account tidal deformations by А. V. Shatina, A. S. Borets

“…In this work, the viscoelastic ball model is used to take into account tidal effects. …”
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Optimized machine learning model for Alzheimer and epilepsy detection from EEG signals by P. Jasphin Jeni Sharmila, T. S. Shiny Angel

“…The attained accuracy of 94% is much better than existing Gaussian Mixture Model (GMM), Relevance Vector Machine (RVM), Support Vector Machine (SVM), and Artificial Neural Network (ANN) methods.…”
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AUV path planning method based on improved sparrow search algorithm by Lijun TANG, Yunxia FAN, Xingyu ZHOU, Qian SUN

“…By modeling the uncertain ocean currents as intervals, the algorithm can accurately calculate the energy consumption and navigation times for different paths. …”
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Broken Bags: Disrupting Service Through the Contamination of Large Language Models With Misinformation by Yonghua Mo, Maoyang Tang, Ruohan Lin, Bohao Zhou, Xiaojian Li

“…For instance, when the RAG system engages with publicly available knowledge bases, adversaries can take advantage of the accessibility of these RAG knowledge bases to introduce malicious texts into the retrieval database, so as to intentionally alter the model’s behavior. This work employs the linguistic similarity between toxic content and the geographical vector characteristics of the “query question” to influence the information returned by RAG, hence preventing the LLM from generating responses to the target questions. …”
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Developing a Transparent Anaemia Prediction Model Empowered With Explainable Artificial Intelligence by Muhammad Sajid Farooq, Muhammad Hassan Ghulam Muhammad, Oualid Ali, Zahid Zeeshan, Muhammad Saleem, Munir Ahmad, Sagheer Abbas, Muhammad Adnan Khan, Taher M. Ghazal

“…In this research work, a transparent anaemia prediction model (white box) empowered by explainable AI techniques is proposed to address the limitations of black boxes in terms of transparency. …”
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Sex-Specific Ensemble Models for Type 2 Diabetes Classification in the Mexican Population by Mendoza-Mendoza MM, Acosta-Jiménez S, Galván-Tejada CE, Maeda-Gutiérrez V, Celaya-Padilla JM, Galván-Tejada JI, Cruz M

“…Data are split by sex, and feature selection is performed using GALGO, a genetic algorithm-based tool. Classification models including Random Forest, K-Nearest Neighbor, Support Vector Machine, and Logistic Regression are trained and evaluated. …”
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Application Analysis of Credit Scoring of Financial Institutions Based on Machine Learning Model by Yi Wu, Yuwen Pan

“…On this basis, WOE coding was carried out on the dataset, which was applied to random forest, support vector machine, and logistic regression models, and the performance was compared. …”
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ECG‐based epileptic seizure prediction: Challenges of current data‐driven models by Sotirios Kalousios, Jens Müller, Hongliu Yang, Matthias Eberlein, Ortrud Uckermann, Gabriele Schackert, Witold H. Polanski, Georg Leonhardt

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Triphasic CT Radiomics Model for Preoperative Prediction of Hepatocellular Carcinoma Pathological Grading by Huang H, Pan X, Zhang Y, Yang J, Chen L, Zhao Q, Huang L, Lu W, Deng Y, Huang Y, Ding K

“…Logistic regression and support vector machine (SVM) classifiers were employed to develop individual phase-specific models and a triphasic fusion model. …”
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A New Grey Box Approach for Friction Modelling of Machine Tool Drives by Adrian Karl Rüppel, Markus Meurer, Thomas Bergs

“…The results show the model to have errors between 7 % and 12 % over the full working range of the x- and y-axes, respectively, outperforming the benchmark models significantly.…”
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