Total Organic Carbon Content Prediction in Lacustrine Shale Using Extreme Gradient Boosting Machine Learning Based on Bayesian Optimization by Xingzhou Liu, Zhi Tian, Chang Chen

“…Based on the degree of correlation, six logging curves reflecting TOC content were selected to construct training dataset for machine learning. Then, the performance of the XGBoost model was tested using K-fold cross-validation, and the hyperparameters of the model were determined using a Bayesian optimization method to improve the search efficiency and reduce the uncertainty caused by the rule of thumb. …”
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Circle chaotic map tuna swarm optimization (CCMTSO) based feature selection and deep learning approach for air quality prediction by Aradhyamatada Swamy, Rohitha U.M.

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Penerapan Blok SE-NET Pada Deep Learning Inceptionv3 untuk Meningkatkan Deteksi Penyakit Mpox pada Manusia by M. Bakhara Alief Rachman, Aliyah Kurniasih, Andika Sundawijaya, Ahlijati Nuraminah

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Enhanced thyroid disease prediction using ensemble machine learning: a high-accuracy approach with feature selection and class balancing by Md. Rezaul Islam, Aniruddha Islam Chowdhury, Sharmin Shama, Md. Masudul Hasan Lamyea

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Predicting hydropower generation: A comparative analysis of Machine learning models and optimization algorithms for enhanced forecasting accuracy and operational efficiency by Chunyang Wang, Chao Li, Yudong Feng, Shoufeng Wang

“…Optimizing hydropower generation is crucial for addressing economic and environmental concerns, though it requires comprehensive monitoring and understanding of energy conversion processes. Machine Learning techniques such as integrated Gradient Boosting and Categorical Gradient Boosting, optimized with Hunger Games search, Chaos game optimization, and Archimedes Optimization Algorithm algorithms, are used to forecast and optimize hydropower generation. …”
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Wheel/Rail Adhesion State Identification of Heavy-Haul Locomotive Based on Particle Swarm Optimization and Kernel Extreme Learning Machine by Jianhua Liu, Linfan Liu, Jing He, Changfan Zhang, Kaihui Zhao

“…A wheel/rail adhesion state identification method based on particle swarm optimization (PSO) and kernel extreme learning machine (KELM) is proposed. To this end, a wheel/rail state identification model is constructed using KELM, and then the regularization coefficient and kernel parameter of KELM are optimized by using PSO to improve its accuracy. …”
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The application of naive bayes method for final project topic selection within the project-based learning framework in the data mining course by Denny Kurniadi

Subjects: “…naive bayes method, final project topic, project-based learning, data mining, students…”
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A Novel Model to Detect and Classify Fresh and Damaged Fruits to Reduce Food Waste Using a Deep Learning Technique by T. Bharath Kumar, Deepak Prashar, Gayatri Vaidya, Vipin Kumar, S. Deva Kumar, F. Sammy

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Deep Learning Approaches for 3D Model Generation from 2D Artworks to Aid Blind People with Tactile Exploration by Rocco Furferi

“…The findings suggest that, while deep learning models demonstrate that they are effective for 3D retrieval from paintings, they also call for post-processing and user interaction to improve the accuracy of the 3D models.…”
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Comparative assessment of empirical and hybrid machine learning models for estimating daily reference evapotranspiration in sub-humid and semi-arid climates by Siham Acharki, Ali Raza, Dinesh Kumar Vishwakarma, Mina Amharref, Abdes Samed Bernoussi, Sudhir Kumar Singh, Nadhir Al-Ansari, Ahmed Z. Dewidar, Ahmed A. Al-Othman, Mohamed A. Mattar

“…This study evaluates the performance of eight empirical models and four machine learning (ML) models, along with their hybrid counterparts, in estimating daily RET within the Gharb and Loukkos irrigated perimeters in Morocco. …”
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Colorimetric aptasensor coupled with a deep-learning-powered smartphone app for programmed death ligand-1 expressing extracellular vesicles by Adeel Khan, Adeel Khan, Haroon Khan, Nongyue He, Zhiyang Li, Heba Khalil Alyahya, Yousef A. Bin Jardan

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Analyzing the relationship between gene expression and phenotype in space-flown mice using a causal inference machine learning ensemble by James A. Casaletto, Ryan T. Scott, Makenna Myrick, Graham Mackintosh, Hamed Chok, Amanda Saravia-Butler, Adrienne Hoarfrost, Jonathan M. Galazka, Lauren M. Sanders, Sylvain V. Costes

“…In this work, we use a machine learning ensemble of causal inference methods called the Causal Research and Inference Search Platform (CRISP) which was developed to predict causal features of a binary response variable from high-dimensional input. …”
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Machine learning algorithm for predict the in-hospital mortality in critically ill patients with congestive heart failure combined with chronic kidney disease by Xunliang Li, Zhijuan Wang, Wenman Zhao, Rui Shi, Yuyu Zhu, Haifeng Pan, Deguang Wang

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Estimating the Pile Settlement Using a Machine Learning Technique Optimized by Henry's Gas Solubility Optimization and Particle Swarm Optimization by Saravana Kumar, Savarimuthu Robinson

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Study of staffing conditions to identify the adaptability of Russian higher education institutions to develop international cooperation using digital learning technologies by M. A. Tanina, V. V. Bondarenko, V. A. Yudina, D. P. Penzina

“…The study is analysed the staffing effectiveness of the Russian universities for compliance with the current requirements of the digital and distance learning technologies market, and readiness for the use of mechanisms for the development of international cooperation in the context of global digitalisation of the educational space according to statistical data was carried out. …”
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Clinical utility of receptor status prediction in breast cancer and misdiagnosis identification using deep learning on hematoxylin and eosin-stained slides by Gil Shamai, Ran Schley, Alexandra Cretu, Tal Neoran, Edmond Sabo, Yoav Binenbaum, Shachar Cohen, Tal Goldman, António Polónia, Keren Drumea, Karin Stoliar, Ron Kimmel

“…Here we explore the clinical utility of predicting receptor status from digitized hematoxylin and eosin-stained (H&E) slides using machine learning trained and evaluated on a multi-institutional dataset. …”
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PENERAPAN ASESMEN REPRESENTASI MELALUI PENDEKATAN STUDENT CENTERED LEARNING (SCL) UNTUK MENINGKATKAN PENGUASAAN KONSEP DAN KEMAMPUAN PSIKOMOTOR by Rosane Medriati, Eko Risdianto

“…keywords: representation assessment , student centered learning, concept mastering, psychomotor skills …”
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Digital twin-centered hybrid data-driven multi-stage deep learning framework for enhanced nuclear reactor power prediction by James Daniell, Kazuma Kobayashi, Ayodeji Alajo, Syed Bahauddin Alam

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Identification of standing dead trees in Robinia pseudoacacia plantations across China’s Loess Plateau using multiple deep learning models by Li Zhang, Xiaodong Gao, Shuyi Zhou, Zhibo Zhang, Tianjie Zhao, Yaohui Cai, Xining Zhao

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Rare Abdominal Wall Metastasis following Curative Resection of Gastric Cancer: What Can Be Learned from the Use of Percutaneous Catheters? by Arthur A. Parsee, Kerry L. Thomas, Masoumeh Ghayouri, Rutika Mehta, Kujtim Latifi, Jennifer Sweeney, Daniel Jeong, Abraham Ahmed

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