Spatiotemporal Mapping of Grazing Livestock Behaviours Using Machine Learning Algorithms by Guo Ye, Rui Yu

“…This study investigated the spatiotemporal patterns of livestock behaviours under different grazing management systems and grazing-intensity gradients (GIGs) in Wenchang, China, using high-resolution GPS tracking data and machine learning classification. the K-Nearest Neighbours (KNN) model combined with SMOTE-ENN resampling achieved the highest accuracy, with F1-scores of 0.960 and 0.956 for continuous and rotational grazing datasets. …”
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A Machine Learning Approach for User Behavior Analysis in Developing Websites by Aeesha Shaheen

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AI Narrative Modeling: How Machines’ Intelligence Reproduces Archetypal Storytelling by Igor Kabashkin, Olga Zervina, Boriss Misnevs

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Four Machine Learning Algorithms for Biometrics Fusion: A Comparative Study by I. G. Damousis, S. Argyropoulos

“…Supervised learning was carried out using a number of patterns from a well-known benchmark biometrics database, and the validation/testing took place with patterns from the same database which were not included in the training dataset. …”
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Reliability process methodology of the centrifugal rotary machining in the medium of steel balls by Denis Vladimirovich Kazakov

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Tooth Contact Analysis of Straight Bevel Gears Machined with Concave Cutters by Wang Zhiyong, Zhang Zhu, Duan Zhihong, Zhang Yu

“…The tooth contact analysis program is compiled, and the contact pattern and transmission error curve of the gear pair are calculated. …”
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Can machine learning distinguish between elite and non-elite rowers? by Orten Kristine Fjellkårstad, Helgesen Sander Elias Magnussen, Chen Bihui, Baselizadeh Adel, Torresen Jim, Herrebrøden Henrik

“…A major challenge for sports coaches and analysts is to identify critical elements of athletes’ movement patterns. A potentially relevant tool is machine learning, useful because of its ability to extract patterns from data. …”
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Machine Learning-Based Network Anomaly Detection: Design, Implementation, and Evaluation by Pilar Schummer, Alberto del Rio, Javier Serrano, David Jimenez, Guillermo Sánchez, Álvaro Llorente

“…<b>Background:</b> In the last decade, numerous methods have been proposed to define and detect outliers, particularly in complex environments like networks, where anomalies significantly deviate from normal patterns. Although defining a clear standard is challenging, anomaly detection systems have become essential for network administrators to efficiently identify and resolve irregularities. …”
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Machine learning-based characteristic identification of MSG content in gravy foods by Rosyady Phisca Aditya, Habibah Nurina Umy, Masita, Yudhana Anton

“…Sensor value readings based on different light sources have the same pattern, but different values. The difference in sensor value is caused by the effect of LED color on specimen color. …”
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Automating the amino acid identification in elliptical dichroism spectrometer with Machine Learning. by Ridhanya Sree Balamurugan, Yusuf Asad, Tommy Gao, Dharmakeerthi Nawarathna, Umamaheswara Rao Tida, Dali Sun

“…Advanced data preprocessing techniques and ML algorithms to learn patterns from the absorption profiles that distinguish different amino acids were investigated to prove the feasibility of this approach. …”
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Machine learning applications in the analysis of sedentary behavior and associated health risks by Ayat S Hammad, Ayat S Hammad, Ali Tajammul, Ismail Dergaa, Ismail Dergaa, Ismail Dergaa, Maha Al-Asmakh, Maha Al-Asmakh

“…As prolonged inactivity becomes a growing public health concern, researchers are increasingly utilizing machine learning (ML) techniques to examine and understand these patterns. …”
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Assessment of Machine Learning Models for Predicting Aboveground Biomass in the Indian Subcontinent by S. Mamgain, B. Ghale, H. C. Karnatak, A. Roy

“…This study highlights the importance of using robust machine learning models like RF to accurately capture spatial patterns of biomass distribution, which is crucial for forest management, carbon accounting, &amp; biodiversity conservation in the Indian subcontinent.…”
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Machine Learning Techniques to Model and Predict Airflow Requirements in Underground Mining by Maria Karagianni, Andreas Benardos

“…More particularly, ML techniques are utilized to capture patterns or prevailing conditions and to be able to generalize/predict future conditions managed via the ventilation system. …”
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PREDICTION OF TELECOM SERVICES CONSUMERS CHURN BY USING MACHINE LEARNING ALGORITHMS by Edin Osmanbegović, Anel Džinić, Mirza Suljić

“…The name "machine learning" refers to the automated detection of meaningful patterns in large data sets.  …”
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PREDICTION OF TELECOM SERVICES CONSUMERS CHURN BY USING MACHINE LEARNING ALGORITHMS by Edin Osmanbegović, Anel Džinić, Mirza Suljić

“…The name "machine learning" refers to the automated detection of meaningful patterns in large data sets.  …”
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A Novel Nonparallel Hyperplane Based Extreme Learning Machine for Classification by Arvind Kumar, Sanyam Shukla, Manasi Gyanchandani

“…Recently, researchers have developed nonparallel variants of both extreme learning machine (ELM) and support vector machine (SVM) classifiers to improve learning speed and generalization. …”
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Stock Price Prediction in the Financial Market Using Machine Learning Models by Diogo M. Teixeira, Ramiro S. Barbosa

“…The complexity of advanced models such as XGBoost and GRU is reflected in their overall performance, suggesting that they can be particularly effective at capturing patterns and making accurate predictions in more complex time series, such as stock prices.…”
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Predicting Students’ Performance Using a Hybrid Machine Learning Approach by Ropafadzo Duwati, Tawanda Mudawarima

“…The Linear Support Vector Classifier (SVC) captured linear patterns within the data, and Logistic Regression was employed as a meta-learner to make the final predictions. …”
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Machine learning technology in the classification of glaucoma severity using fundus photographs by Sukhumal Thanapaisal, Passawut Uttakit, Worapon Ittharat, Pukkapol Suvannachart, Pawasoot Supasai, Pattarawit Polpinit, Prapassara Sirikarn, Panawit Hanpinitsak

“…Glaucoma severity grading was based on the Hodapp-Parrish-Anderson (HPA) criteria incorporating the mean deviation value, defective points in the pattern deviation probability map, and defect proximity to the fixation point. …”
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An Assessment of Land Use Land Cover Using Machine Learning Technique by V. Pushpalatha, H. N. Mahendra, A. M. Prasad, N. Sharmila, D. Mahesh Kumar, N. M. Basavaraju, G. S. Pavithra and S. Mallikarjunaswamy

“…The study aims to analyze the spatiotemporal patterns of urban expansion, land-use dynamics, and associated factors influencing the city’s built environment. …”
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