Botnet Detection Using Support Vector Machines with Artificial Fish Swarm Algorithm by Kuan-Cheng Lin, Sih-Yang Chen, Jason C. Hung

“…The proposed method was used to identify the critical features that determine the pattern of botnet. The experimental results indicated that the method can be used for identifying the essential botnet features and that the performance of the proposed method was superior to that of genetic algorithms.…”
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Decoding the brain-machine interaction for upper limb assistive technologies: advances and challenges by Sutirtha Ghosh, Rohit Kumar Yadav, Sunaina Soni, Shivangi Giri, Shivangi Giri, Suriya Prakash Muthukrishnan, Lalan Kumar, Lalan Kumar, Shubhendu Bhasin, Sitikantha Roy

“…This review aims to provide a comprehensive overview of recent progress in deciphering neural activity patterns associated with both physiological and assisted upper limb movements, highlighting avenues for future exploration in neurorehabilitation and brain-machine interface development.…”
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Machine learning approach for Studying the multifunctionality of soil against global climate changes by Xiangng Hu, Yingying Xie, Qixing Zhou, Li Mu

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Environmental Data Analytics for Smart Cities: A Machine Learning and Statistical Approach by Ali Suliman AlSalehy, Mike Bailey

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Connecting metal-organic framework synthesis to applications using multimodal machine learning by Sartaaj Takrim Khan, Seyed Mohamad Moosavi

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Navigating Data Corruption in Machine Learning: Balancing Quality, Quantity, and Imputation Strategies by Qi Liu, Wanjing Ma

“…The results indicate that performance degradation follows a diminishing-return pattern, well modeled by an exponential function. …”
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Detecting expert’s eye using a multiple-kernel Relevance Vector Machine by Giuseppe Boccignone, Mario Ferraro, Sofia Crespi, Carlo Robino, Claudio de’Sperati

“…Decoding mental states from the pattern of neural activity or overt behavior is an intensely pursued goal. …”
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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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Estimation Algorithm of Machine Operational Intention by Bayes Filtering with Self-Organizing Map by Satoshi Suzuki, Fumio Harashima

“…Specifically, an investigation of intentions pattern discriminated by eight analysts showed that the estimator could not identify the same modes that human analysts could not discriminate. …”
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What drives the profitability of banking sectors in the European Union? The machine learning approach by Bernardelli Michał, Korzeb Zbigniew, Niedziółka Paweł

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Comparative Investigation of Machine Learning and Deep Learning Approaches for Air Quality Prediction by Zhang Borui

“…Deep learning captures nonlinear patterns more effectively but lacks interpretability and requires more data. …”
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Neutrosophic Set and Machine Learning Model for Identifying Botnet Attacks on IoT Effectively by Wasal S AL-Bash AL-Azzawi, Hassan W. Hilou, Nawfal H. warush, Hasan Meslmani, Ahmed A El-Douh, Ahmed Abdelhafeez

“…These algorithms are examined, contrasted, and demonstrated to be very successful in identifying intricate patterns suggestive of botnet activity, leading to a notable enhancement in IoT security. …”
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Machine learning and spatio-temporal analysis of meteorological factors on waterborne diseases in Bangladesh. by Arman Hossain Chowdhury, Md Siddikur Rahman

“…Therefore, this study aimed to fill this gap by investigating the spatio-temporal pattern and identifying the best tree-based ML models for determining the meteorological factors associated with waterborne diseases in Bangladesh.…”
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Efficiency Monitoring of a Cooling Water Pump based on Machine Learning Techniques by Marta Casero, Miguel A. Sanz-Bobi, F. Javier Bellido-López, Antonio Muñoz, Daniel Gonzalez-Calvo, Tomas Alvarez-Tejedor

“…The method is based on monitoring the performance of the pumps over time using machine learning techniques that try to discover patterns in the data observed from the pumps. …”
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A new benchmark for machine learning applied to powder X-ray diffraction by Sergio Rincón, Gabriel González, Mario A. Macías, Pablo Arbeláez

“…This new benchmark includes 467,861 crystal structures from the Crystallography Open Database (COD) and their powder X-ray diffraction patterns. SIMPOD presents simulated one-dimensional powder X-ray diffractograms and derived two-dimensional radial images to facilitate the adoption of computer vision models for this task. …”
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APPLICATION OF A MACHINE LEARNING MODEL FOR FORECASTING FREIGHT RATE IN ROAD TRANSPORT by Artur, Maria

“…The analysis allowed to conclude that machine learning models can be effective in forecasting freight prices in the context of sustainable transport due to their ability to capture complex patterns and relationships in large datasets. …”
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The Implementation of Machine Learning in Lithofacies Classification using Multi Well Logs Data by Sudarmaji Saroji*, Ekrar Winata, Putra Pratama Wahyu Hidayat, Suryo Prakoso, Firman Herdiansyah

“…The classified lithofacies then can be used as the input for describing lateral and vertical rock distribution patterns.…”
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Efficient Human Activity Recognition Using Machine Learning and Wearable Sensor Data by Ziwei Zhong, Bin Liu

“…Human activity recognition and monitoring systems offer a powerful means of identifying daily movement patterns, which helps in understanding human behaviors and provides valuable insights for life management. …”
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Identification of key proteins and pathways in myocardial infarction using machine learning approaches by Chang Liu, Xing Zhang, Qian Xie, Binbin Fang, Fen Liu, Junyi Luo, Gulandanmu Aihemaiti, Wei Ji, Yining Yang, Xiaomei Li

“…This study combines proteomics, transcriptomics and machine learning (ML) to identify key proteins and pathways associated with AMI. …”
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Spatial Clusters of Gambling Outlet: A Machine Learning Tree-Based Algorithm by Salvador Martínez-Cava, Fernando A. López, MLuz Maté Sánchez-del-Val

“…The results reveal different spatial patterns regarding the locations of these two types of gambling establishments. …”
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