A Synergy Between Machine Learning and Formal Concept Analysis for Crowd Detection by Anas M. Al-Oraiqat, Oleksandr Drieiev, Sattam Almatarneh, Mohammadnoor Injadat, Karim A. Al-Oraiqat, Hanna Drieieva, Yassin M. Y. Hasan

“…Recent systems take advantage of the synergy between machine learning, data mining, and image processing to extract/analyze features from crowded zones and recognize patterns and anomalies from the crowd behavior. …”
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Prediction of Sonic Log Values Using a Gradient Boosting Algorithm in the 'AB' Field by Rasif Nahari, Utama Widya, Ardhya Garini Sherly, Fitri Indriani Rista, Pratama Novian Putra Dhea

“…To address missing data, machine learning algorithms, like gradient boosting, provide an effective solution. …”
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Hypertension Detection Using Passive-Aggressive Algorithm With The PA-I And PA-II Methods by M. Hafidz Ariansyah, Sri Winarno

“…Researchers get detection results using a branch of AI technology, namely machine learning to find new knowledge from data and find patterns to make diagnoses. …”
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Feature Extraction using Histogram of Oriented Gradients and Moments with Random Forest Classification for Batik Pattern Detection by Wafiq Azizah, Soffiana Agustin

“…These findings underscore the efficacy of integrating HOG and Texture Moments with the Random Forest algorithm for automated batik pattern recognition.…”
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The Synergy of Minds and Machines: Rethinking the AI-HI Relationship through Dialectical Reconstruction by Ridwan Ishola MOGAJI, Adewale Oluwaseun MOTADEGBE

“…Artificial intelligence on the other hand is the simulation of human cognitive functions by machines, especially in tasks such as problem-solving, pattern recognition, and decision-making, which often operates based on algorithms and data, both of which are unique and important in themselves. …”
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Application of Machine Learning Models in Optimizing Wastewater Treatment Processes: A Review by Florin-Stefan Zamfir, Madalina Carbureanu, Sanda Florentina Mihalache

“…Thus, this paper identifies gaps in the current research, discusses ML and DL algorithms in the context of optimizing wastewater treatment processes, and identifies future directions for optimizing these processes through data-driven methods. …”
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Machine learning and discriminant analysis model for predicting benign and malignant pulmonary nodules by Zhi Li, Wenjing Zhang, Jinyi Huang, Ling Lu, Dongming Xie, Jinrong Zhang, Jiamin Liang, Yuepeng Sui, Linyuan Liu, Jianjun Zou, Ao Lin, Lei Yang, Fuman Qiu, Zhaoting Hu, Mei Wu, Yibin Deng, Xin Zhang, Jiachun Lu

“…Three widely applicable machine learning algorithms (Random Forests, Gradient Boosting Machine, and XGBoost) were used to screen the metrics, and then the corresponding predictive models were constructed using discriminative analysis, and the best performing model was selected as the target model. …”
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Monitoring and Modeling Urban Temperature Patterns in the State of Iowa, USA, Utilizing Mobile Sensors and Geospatial Data by Clemir Abbeg Coproski, Bingqing Liang, James T. Dietrich, John DeGroote

“…Using the random forest machine-learning algorithm and estimated urban morphological variables at varying neighborhood distances derived from 1 m² aerial imagery and derived products from LiDAR data, we created 24 predicted surface temperature models that demonstrated R² coefficients ranging from 0.879 to 0.997 with the majority exceeding an R² of 0.95, all with <i>p</i>-values < 0.001. …”
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Prophetic Energy Assessment with Smart Implements in Hydroelectricity Entities Using Artificial Intelligence Algorithm by Abdullah Saleh Alqahtani, Pravin R. Kshirsagar, Hariprasath Manoharan, Praveen Kumar Balachandran, C. K. Yogesh, Shitharth Selvarajan

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Modeling Stock Price Changes Based on Microstructural Market Data by N. A.  Bilev

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Development of a Mobile-Based Application for Classifying Caladium Plants Using the CNN Algorithm by Rudy Chandra, Tegar Arifin Prasetyo, Heni Ernita Lumbangaol, Veny Siahaan, Johan Immanuel Sianipar

“…To overcome this problem, research will use machine learning with the Convolutional Neural Network (CNN) algorithm to build a mobile application that can accurately classify four types of Caladiums. …”
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An improved Red-billed blue magpie feature selection algorithm for medical data processing. by Chenyi Zhu, Zhiyi Wang, Yinan Peng, Wenjun Xiao

“…Feature selection is a crucial preprocessing step in the fields of machine learning, data mining and pattern recognition. …”
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BiAF: research on dynamic goat herd detection and tracking based on machine vision by Yun Hou, Mingjuan Han, Wei Fan, Xinyu Jia, Zhuo Gong, Ding Han

“…Traditional methods, such as manual tracking and wearable monitoring, often disrupt the natural movement and feeding behaviors of grazing livestock, posing significant challenges for in-depth studies of grazing patterns. In this paper, we propose a machine vision-based grazing goat herd detection algorithm that enhances the streamlined ELAN module in YOLOv7-tiny, incorporates an optimized CBAM attention mechanism, refines the SPPCSPC module to reduce the parameter count, and improves the anchor boxes in YOLOv7-tiny to enhance target detection accuracy. …”
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Commonalities and differences in gene expression patterns in major depressive disorder and chronic spontaneous urticaria: implications for comorbidity by Yibo Jiang, Wen Li, Lihao Zheng, Nan Ba

“…Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were used to characterize putative pathophysiological mechanisms. Subsequently, machine learning algorithms were implemented via 10-fold cross-validation to build transcriptomic classifiers for MDD in a sex-stratified manner. …”
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Clustering and Interpretability of Residential Electricity Demand Profiles by Sarra Kallel, Manar Amayri, Nizar Bouguila

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Detecting Fraudulent Transaction in Banking Sector Using Rule-Based Model and Machine Learning by Cut Dinda Rizki Amirillah

“…This research aims to develop an effective fraud detection model in banking transactions using the rule-based model (RBM) approach and the isolation forest (IF) machine learning algorithm. Based on data from the Ministry of Communication and Information Technology, there were more than 405,000 online fraud cases during the 2019–2022 period, indicating the need for a reliable fraud detection system to protect customers. …”
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Planning and layout of tourism and leisure facilities based on POI big data and machine learning. by Shifeng Wu, Jiangyun Wang, Yinuo Jia, Jintian Yang, Jixiu Li

“…Key findings include: Firstly, compared with the existing tourism and leisure facilities, the fitting degree tested by the machine learning algorithm is 83.5%, suggests that the proposed method is highly feasible. …”
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Analysis of 19.9 million publications from the PubMed/MEDLINE database using artificial intelligence methods: approaches to the generalizations of accumulated data and the phenomen... by I. Yu. Torshin, O. A. Gromova, L. V. Stakhovskaya, N. P. Vanchakova, A. N. Galustyan, Zh. D. Kobalava, T. R. Grishina, A. N. Gromov, I. A. Ilovaiskaya, V. M. Kodentsova, A. G. Kalacheva, O. A. Limanova, V. A. Maksimov, S. I. Malyavskaya, E. V. Mozgovaya, N. I. Tapilskaya, K. V. Rudakov, V. A. Semenov

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Modeling Flood Susceptibility Utilizing Advanced Ensemble Machine Learning Techniques in the Marand Plain by Ali Asghar Rostami, Mohammad Taghi Sattari, Halit Apaydin, Adam Milewski

“…In this case study, flood susceptibility patterns in the Marand Plain, located in the East Azerbaijan Province in northwest Iran, were analyzed using five machine learning (ML) algorithms: M5P model tree, Random SubSpace (RSS), Random Forest (RF), Bagging, and Locally Weighted Linear (LWL). …”
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Effectiveness of machine learning methods in detecting grooming: a systematic meta-analytic review by Marcelo Leiva-Bianchi, Nicolas Castillo, César A. Astudillo, Francisco Ahumada-Méndez

“…The results highlight the efficacy of certain algorithms and contribute to the identification of online predators. …”
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