Development of Competent Mathematical Speech of Students at Technical University by A. V. Muzhikova, M. N. Gabova

“…The prepared organizational and methodological support of teaching, the systemic educational work allow students to improve their speech skills and skills of active use of mathematical language as a universal language of science, to develop logical, algorithmic and mathematical thinking, the ability to apply methods of mathematical analysis and modeling, theoretical and experimental research in solving professional problems.…”
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Can the number of confirmed COVID-19 cases be predicted more accurately by including lifestyle data? An exploratory study for data-driven prediction of COVID-19 cases in metropolit... by Sungwook Jung

“…Finally, a ‘lifestyle addition’ set was constructed that added lifestyle data to the number of past confirmed cases and search term frequency data. The deep learning algorithms used in the analysis are deep neural networks (DNNs) and recurrent neural networks (RNNs). …”
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Random Forest–Based Coal Mine Roof Displacement Prediction and Application by Hongxia Li, Rong Wu, Jianan Gao

“…Based on Random Forest (RF), XGBoost, and Gradient Boosting Decision Tree (GBDT) algorithms, three kinds of roof displacement prediction models are established respectively. …”
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High-Quality Text-to-Image Generation Using High-Detail Feature-Preserving Network by Wei-Yen Hsu, Jing-Wen Lin

“…Multistage text-to-image generation algorithms have shown remarkable success. However, the images produced often lack detail and suffer from feature loss. …”
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Multi-Scale Feature Fusion and Context-Enhanced Spatial Sparse Convolution Single-Shot Detector for Unmanned Aerial Vehicle Image Object Detection by Guimei Qi, Zhihong Yu, Jian Song

“…., VisDrone and ARH2000; the latter dataset was created by the researchers) demonstrate that the MFFCESSC-SSD remarkably outperforms the performance of the SSD and numerous conventional object detection algorithms in terms of accuracy and efficiency.…”
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A data-driven methodology for the classification of different liquids in artificial taste recognition applications with a pulse voltammetric electronic tongue by Jersson X Leon-Medina, Leydi J Cardenas-Flechas, Diego A Tibaduiza

“…However, one of the problems in the use of this kind of device is associated with the development of reliable pattern recognition algorithms and robust data analysis. In this sense, this work introduces a taste recognition methodology, which is composed of several steps including unfolding data, data normalization, principal component analysis for compressing the data, and classification through different machine learning models. …”
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ExAIRFC-GSDC: An Advanced Machine Learning-Based Interpretable Framework for Accurate Gas Leakage Detection and Classification by B. Lalithadevi, S. Krishnaveni

“…The proposed ExAIRFC-GSDC model integrates machine learning algorithms, particularly a Random Forest Classifier, with explainable artificial intelligence (XAI) techniques to enhance interpretability. …”
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Intelligent On/Off Dynamic Link Management for On-Chip Networks by Andreas G. Savva, Theocharis Theocharides, Vassos Soteriou

“…Most of these proposed algorithms focus on a pessimistic and simple static threshold mechanism which determines whether or not a link should be turned on/off. …”
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Knee Joint Biomechanical Gait Data Classification for Knee Pathology Assessment: A Literature Review by Mariem Abid, Neila Mezghani, Amar Mitiche

“…We recorded the relevant information pertaining to the investigated knee joint pathologies, the participants’ attributes, data acquisition, feature extraction, and selection used to represent the data, as well as the classification algorithms and validation of the results. Results. Thirty-one studies met the inclusion criteria for review. …”
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Sulfasalzine in the management of pure axial spondyloarthritis: Need to have a relook! by Subramanian Shankar, Arun Hegde

“…We also explore the role of other innovative strategies in the management of axial SpA and suggest alternate algorithms catering to the Indian scenario.…”
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Dynamic Foraging in Swarm Robotics: A Hybrid Approach with Modular Design and Deep Reinforcement Learning Intelligence by Ali Hammoud, Alaa Iskandar, Béla Kovács

“…This paper proposes a hybrid approach that combines intelligent algorithms and modular design to solve a foraging problem within the context of swarm robotics. …”
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A Comparative Study of Three Resolving Parameters of Graphs by Hafiz Muhammad Ikhlaq, Hafiz Muhammad Afzal Siddiqui, Muhammad Imran

“…It is used to monitor the movement of robots on a network, to debug computer networks, to develop algorithms, and to analyze the structural properties of chemical structures, among other things. …”
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Unlocking autism’s complexity: the Move Initiative’s path to comprehensive motor function analysis by Ashley Priscilla Good, Elizabeth Horn

“…Despite advances in sensors, wearables, algorithms, machine learning, and agentic AI, autism research remains siloed, with many tools inaccessible to affected families and care teams. …”
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Data-Driven versus Köppen–Geiger Systems of Climate Classification by Vajira Lasantha, Taikan Oki, Daisuke Tokuda

“…We applied three clustering algorithms—k-means, ISODATA, and unsupervised random forest classification—to a dataset comprising 10 climatic variables and elevation; we then compared the obtained results with those from the Köppen–Geiger classification system. …”
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Performance Evaluation of Two ANFIS Models for Predicting Water Quality Index of River Satluj (India) by Sharad Tiwari, Richa Babbar, Gagandeep Kaur

“…Recently, artificial intelligence algorithms that are appropriate for nonlinear forecasting and also dealing with uncertainties have been applied to various domains of water quality forecasting. …”
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Attribute Selection Impact on Linear and Nonlinear Regression Models for Crop Yield Prediction by Alberto Gonzalez-Sanchez, Juan Frausto-Solis, Waldo Ojeda-Bustamante

“…However, attributes are usually selected based on expertise assessment or in dimensionality reduction algorithms. A fairer comparison should include the best subset of features for each regression technique; an evaluation including several crops is preferred. …”
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Enhancing surface detection: A comprehensive analysis of various YOLO models by G. Deepti Raj, B. Prabadevi

“…However, implementing accurate and automated object detection algorithms mitigates these challenges, allowing errors or defects to be detected before processing. …”
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Learning From High-Cardinality Categorical Features in Deep Neural Networks by Mustafa Murat Arat

“…Some machine learning algorithms expect the input variables and the output variables to be numeric. …”
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Deep learning‐based unmanned aerial vehicle detection in the low altitude clutter background by Zeyang Wu, Yuexing Peng, Wenbo Wang

“…Sufficient experiments are carried out on both real and simulated data sets, and the comparative results verify that the proposed model outperforms the mainstream algorithms and improves the detection accuracy by more than 5% under severe ground clutter interference.…”
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