Data-Driven Approach for Modeling the Nonlane-Based Mixed Traffic Conditions by Narayana Raju, Shriniwas S. Arkatkar, Said Easa, Gaurang Joshi

“…The data were used to extract the parameters required for modeling the vehicles’ positions using machine learning algorithms. Three established supervised machine learning algorithms (k-NN, random forest, and regression tree) and deep learning are selected to model mixed traffic conditions. …”
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Predicting appropriateness of antibiotic treatment among ICU patients with hospital-acquired infection by Ella Goldschmidt, Ella Rannon, Daniel Bernstein, Asaf Wasserman, Michael Roimi, Anat Shrot, Dan Coster, Ron Shamir

“…Our study demonstrates the potential of machine learning models to predict inappropriate empiric antibiotic treatment.…”
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Refining the prediction of user satisfaction on chat-based AI applications with unsupervised filtering of rating text inconsistencies by Hae Sun Jung, Jang Hyun Kim, Haein Lee

“…Subsequently, the authors conduct supervised sentiment analysis using various machine learning and deep learning algorithms. The experimental results confirm the effectiveness of the proposed approach showing improvement in prediction accuracy with cost efficiency. …”
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Online energy consumption forecast for battery electric buses using a learning-free algebraic method by Zejiang Wang, Guanhao Xu, Ruixiao Sun, Anye Zhou, Adian Cook, Yuche Chen

“…In contrast to the mainstream machine-learning-based methods, the proposed method does not require access to the historical energy consumption data. …”
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GKRR: A gravitational-based kernel ridge regression for software development effort estimation by Mohammad Bagher Dowlatshahi, Mohammad Ali Zare-Chahooki, Saba Beiranvand, Amin Hashemi

“…To increase the estimation accuracy, the researchers tried to provide various machine learning regressors for SDEE. Kernel Ridge Regression (KRR) has demonstrated good potentials to solve regression problems as a powerful machine learning technique. …”
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Emerging Technologies Driving Zero Trust Maturity Across Industries by Hrishikesh Joshi

“…The research investigates how artificial intelligence, machine learning, blockchain, quantum computing, and cloud/edge technologies are reshaping the implementation and efficacy of Zero Trust architectures. …”
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Presenting a Novel Hybrid Approach of Text Mining Sentiment Analysis in Twitter Using CART Decision Tree by Nasir Tayarani, Mehrdad Jalali

“…In this paper, a new hybrid approach of machine learning and vocabulary-based method to text-mining sentiment analysis on Twitter. …”
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A simulation work for generating a novel dataset to detect distributed denial of service attacks on Vehicular Ad hoc NETwork systems by Fahd A Alhaidari, Alia Mohammed Alrehan

“…It has garnered much interest from researchers studying the mitigation of attacks including distributed denial of service attacks. Machine learning techniques, which mainly rely on the quality of the datasets used, play a role in detecting many attacks with a high level of accuracy. …”
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Lentil plant disease and quality assessment: A detailed dataset of high-resolution images for deep learning researchMendeley Data by Eram Mahamud, Md Assaduzzaman, Shayla Sharmin

“…The dataset aims to support the development of machine-learning models for precise disease detection and quality assessment in lentil cultivation. …”
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Improved ML-Based Technique for Credit Card Scoring in Internet Financial Risk Control by Shuangshuang Fan, Yanbo Shen, Shengnan Peng

“…In order to overcome the limitations of the credit card scoring model and evaluate credit risk better, this paper proposes a credit evaluation model based on extreme gradient boosting tree (XGBoost) machine learning (ML) algorithm to construct a credit risk assessment model for Internet financial institutions. …”
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Modeling Evapotranspiration Response to Climatic Forcings Using Data-Driven Techniques in Grassland Ecosystems by Xianming Dou, Yongguo Yang

“…This is attributed partly to the considerable development of machine learning techniques that allow the scientific community to use these advanced tools for approximating the nonlinear processes affecting the variation of water vapor in terrestrial ecosystems. …”
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An End-to-End Rumor Detection Model Based on Feature Aggregation by Aoshuang Ye, Lina Wang, Run Wang, Wenqi Wang, Jianpeng Ke, Danlei Wang

“…It is crucial to identify rumors automatically. Machine learning technology is widely implemented in the identification and detection of misinformation on social networks. …”
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Assessing Land Cover Changes Using the LUCAS Database and Sentinel Imagery: A Comparative Analysis of Accuracy Metrics by Beata Hejmanowska, Piotr Kramarczyk

“…Classification of remote sensing images using machine learning models requires a large amount of training data. …”
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Review of communication optimization methods in federated learning by YANG Zhikai, LIU Yaping, ZHANG Shuo, SUN Zhe, YAN Dingyu

“…Federated learning, as a distributed machine learning paradigm with privacy protection capabilities, exchanges model parameters through frequent communication between clients and parameter servers, training a joint model without the raw data leaving the local area. …”
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A data-consistent model of the last glaciation in the Alps achieved with physics-driven AI by Tancrède P. M. Leger, Guillaume Jouvet, Sarah Kamleitner, Jürgen Mey, Frédéric Herman, Brandon D. Finley, Susan Ivy-Ochs, Andreas Vieli, Andreas Henz, Samuel U. Nussbaumer

“…We tackle this issue by applying the Instructed Glacier Model, a three-dimensional model enhanced with physics-informed machine learning. This approach allows us to produce 100 Alps-wide and 17 thousand-year-long simulations at 300 m resolution. …”
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Enhancing Orthopedic Surgery and Treatment Using Artificial Intelligence and Its Application in Health and Dietary Welfare by D. Rubidha Devi, S. K. UmaMaheswaran, Sandhya Tarar, Abu Sarwar Zamani, Durgaprasad Gangodkar, A. Prabhu Chakkaravarthy, IssahAbubakari Samori

“…The current decade has seen an increased usage of high-end digital technologies like machine learning in the field of health care services which enable in supporting and performing different functions with less or no human interventions. …”
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Shallow Foundation Settlement Quantification: Application of Hybridized Adaptive Neuro-Fuzzy Inference System Model by Mariamme Mohammed, Ahmad Sharafati, Nadhir Al-Ansari, Zaher Mundher Yaseen

“…Overall, ANFIS-PSO model showed a robust machine learning for settlement prediction.…”
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Metallicity and α-abundance for 48 Million Stars in Low-extinction Regions in the Milky Way by Kohei Hattori

“…We further investigate how our machine learning models extract information on ([M/H], [ α /M]). …”
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Enhancement of Heat Transfer Using Water/Graphene Nanofluid and the Impact of Passive Techniques—Experimental, Numerical, and ML Approaches by Javed Syed

“…The experimental outcomes for the convergent nozzle insert are employed to validate the supervised machine learning model. Subsequently, a numerical analysis of the convergent–divergent nozzle insert is conducted using approximately 220 samples for training and testing purposes. …”
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Comparison of Feature Selection and Feature Extraction Role in Dimensionality Reduction of Big Data by Haidar Khalid Malik, Nashaat Jasim Al-Anber, Fuad AbdoEsmail Al- Mekhlafi

“…The importance of Dimensionality Reduction technology lies in several fields, including “data processing, patterns recognition, machine learning, and data mining”. This paper compares two essential methods of dimensionality reduction, Feature Extraction and Feature Selection Which Machine Learning models frequently employ. …”
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