Comparison of Machine Learning and Statistical Approaches of Detecting Anomalies Using a Simulation Study by Klaudia Lenart

“…Originality/value: The two approaches to anomaly detection presented in the paper are not often compared, usually used by two separate groups of researchers – statisticians and machine learning or data science specialists.…”
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EEG analysis of speaking and quiet states during different emotional music stimuli by Xianwei Lin, Xinyue Wu, Zefeng Wang, Zhengting Cai, Zihan Zhang, Guangdong Xie, Lianxin Hu, Laurent Peyrodie

“…In terms of constructing the classification model, this study compares the classification performance of deep neural networks with other machine learning algorithms.ResultsThe differences in EEG signals between different emotions during speech are more pronounced compared to those in a quiet state. …”
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Comparison of tone mapping methods during images processing on liquid crystal displays by A. V. Sycev, A. A. Stepanov, A. G. Smirnov, K. .. Blankenbach

“…Image enhancement algorithms improve readability on liquid crystal displays under bright ambient light conditions and are the theme of many researchers and developers. …”
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A New Weighted Correlation Coefficient Method to Evaluate Reconstructed Brain Electrical Sources by Jong-Ho Choi, Min-Hyuk Kim, Luan Feng, Chany Lee, Hyun-Kyo Jung

“…To validate and compare the performances of inverse algorithms, many researchers have used artificially constructed EEG and MEG datasets. …”
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Evaluation of the Deep Q-Learning Models for Mobile Robot Path Planning Problem by Mehmet Gök

“…These drawbacks have led researchers to work on dynamic path planning algorithms. …”
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Predicting Olympic Medal Performance for 2028: Machine Learning Models and the Impact of Host and Coaching Effects by Zhenkai Zhang, Tengfei Ma, Yunpeng Yao, Ningjia Xu, Yujie Gao, Wanwan Xia

“…Four models (random forest, BP Neural Network, XGBoost, and SVM) are employed to predict medal outcomes, using historical data split into training and testing sets to compare their predictive performance. The research results show that XGBoost is the optimal medal predicted model, with the United States projected to win 57 gold medals and a total of 135 medals in 2028. …”
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Effect of tool angle in nanocutting of single crystal GaN using diamond cutter by Yongqiang WANG, Hao XIA, Zhihang HU, Shuaiyang ZHANG, Shaohui YIN

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Machine learning provides reconnaissance-type estimates of carbon dioxide storage resources in oil and gas reservoirs by Emil Attanasi, Philip Freeman, Timothy Coburn

“…We demonstrate the application of four different ML algorithms using data from onshore and offshore oil and gas reservoirs in Europe, and show they perform well when predictions are compared to engineering estimates. …”
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EEG-Based Emotion Recognition Datasets for Virtual Environments: A Survey by Hussein Ali Hamzah, Kasim K. Abdalla

“…Thus, many researchers interested in studying emotion recognition models choose to verify their concepts and compare them to related works using specific criteria. …”
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A Comprehensive Behavioral Dataset for the Abstraction and Reasoning Corpus by Solim LeGris, Wai Keen Vong, Brenden M. Lake, Todd M. Gureckis

“…Abstract The Abstraction and Reasoning Corpus (ARC) is a visual program synthesis benchmark designed to test out-of-distribution generalization in machines. Comparing AI algorithms to human performance is essential to measure progress on these problems. …”
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Excavation Safety Modeling Approach Using BIM and VPL by Numan Khan, Ahmad K. Ali, Miroslaw J. Skibniewski, Do Yeop Lee, Chansik Park

“…Academic researchers and industry professionals have currently devoted vital attention to acquire construction safety in preconstruction phase of the project. …”
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An Efficient and Fast Model Reduced Kernel KNN for Human Activity Recognition by Zongying Liu, Shaoxi Li, Jiangling Hao, Jingfeng Hu, Mingyang Pan

“…With accumulation of data and development of artificial intelligence, human activity recognition attracts lots of attention from researchers. Many classic machine learning algorithms, such as artificial neural network, feed forward neural network, K-nearest neighbors, and support vector machine, achieve good performance for detecting human activity. …”
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A Novel Approximation Method for Solving Ordinary Differential Equations Using the Representation of Ball Curves by Abdul Hadi Bhatti, Sharmila Karim, Ala Amourah, Ali Fareed Jameel, Feras Yousef, Nidal Anakira

“…To achieve minimal error and higher accuracy in approximate solutions, researchers have focused on developing algorithms using various numerical techniques. …”
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StopSpamX: A multi modal fusion approach for spam detection in social networking by Dasari Siva Krishna, Gorla Srinivas

“…In order to achieve a spam free environment, researchers have proposed numerous methods and algorithms for spam detection. …”
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Internal risk assessment of development and implementation of the state programs by A. I. Denisova

“…As part of the test case, the researcher showed the possibility of adapting the program’s action plan due to the influence of associated risks, assessing the magnitude of the program’s associated risks as indicators of the most problematic areas of implementation, and comparing the results of calculations with actual risks. …”
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CRISP: correlation-refined image segmentation process by Jennifer K. Briggs, Erli Jin, Matthew J. Merrins, Richard K. P. Benninger

“…To assess the activity of individual cells, researchers must segment images into the individual cells. …”
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Bitcoin Return Dynamics Volatility and Time Series Forecasting by Punit Anand, Anand Mohan Sharan

“…Bitcoin and other cryptocurrency returns show higher volatility than equity, bond, and other asset classes. Increasingly, researchers rely on machine learning techniques to forecast returns, where different machine learning algorithms reduce the forecasting errors in a high-volatility regime. …”
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Application of Artificial Intelligence Techniques for the Control of the Asynchronous Machine by F. Khammar, N. E. Debbache

“…The results of the different simulation tests highlight the properties of robustness of algorithms proposed and suggested to compare the different control strategies.…”
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Fine-art recognition using convolutional transformers by Yu Liu, Haozhe Bai, Jingchao Wang

“…Digital image processing is a constantly evolving field encompassing a wide range of techniques and applications. Researchers worldwide are continually developing various algorithms across multiple fields to achieve accurate image classification. …”
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Analysis of Generalization Ability for Different AdaBoost Variants Based on Classification and Regression Trees by Shuqiong Wu, Hiroshi Nagahashi

“…Then, a lot of comparison and review studies for AdaBoost variants have also been published. Some researchers compared different AdaBoost variants by experiments in their own fields, and others reviewed various AdaBoost variants by basically introducing these algorithms. …”
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