Suggesting a Novel Hybrid Approach for Predicting Solar Irradiance in the Qinghai Province of China by Baran Yılmaz, Rachel Samra

“…This work aims to provide a hybrid model using machine learning to accurately predict solar Direct normal irradiance with the least amount of error. …”
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QeMFi: A Multifidelity Dataset of Quantum Chemical Properties of Diverse Molecules by Vivin Vinod, Peter Zaspel

“…Abstract Progress in both Machine Learning (ML) and Quantum Chemistry (QC) methods have resulted in high accuracy ML models for QC properties. …”
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Analisis Sentimen Pada Sosial Media Twitter Terhadap Kualitas Jaringan Internet Telkomsel Menggunakan Ensemble K-Nearest Neighbour -Support Vector Machine by Muchammad Farchan Fachrudin, Cucun Very Angkoso, Doni Abdul Fatah

“…Dalam penelitian analisis sentimen ini menggunakan model algoritma machine learning yaitu K-Nearest Neighbour, Support Vector Machine, dan Ensemble KNN-SVM yang berbasis majority vote dan berbasis average. …”
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Optimasi Algoritma Naive Bayes dengan Diskritisasi K-Means pada Diagnosis Penyakit Jantung by Nafa Fajriati, Budi Prasetiyo

“…Dataset yang digunakan yaitu Cleveland heart disease dataset dari UCI Machine Learning Repository. Untuk meningkatkan akurasi klasifikasi menggunakan algoritma Naive Bayes, atribut kontinu pada dataset diubah menjadi atribut diskrit dengan diskritisasi K-means. …”
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IL-23 tunes inflammatory functions of human mucosal-associated invariant T cells by Laetitia Camard, Tharshana Stephen, Hanane Yahia-Cherbal, Vincent Guillemot, Sébastien Mella, Victoire Baillet, Hélène Lopez-Maestre, Daniele Capocefalo, Laura Cantini, Claire Leloup, Julie Marsande, Katherine Garro, Juan Sienes Bailo, Ambre Dangien, Natalia Pietrosemoli, Milena Hasan, Huimeng Wang, Sidonia B.G. Eckle, Anne M. Fourie, Carrie Greving, Barbara Joyce-Shaikh, Raphaelle Parker, Daniel J. Cua, Elisabetta Bianchi, Lars Rogge

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Sistem Rekognisi Citra Digital Bahasa Isyarat Menggunakan Convolutional Neural Network dan Spatial Transformer by Mohammad Alfiano Rizky Mahardika, Novanto Yudistira, Achmad Ridok

“…Dengan menggunakan metode Convolutional Neural Network (CNN) yang merupakan bagian dari Deep Learning atau Machine Learning, sistem akan mengenali pose atau bentuk dari citra bahasa isyarat yang dimasukkan, dan memberikan luaran yang sesuai dengan maksud dari pose atau bentuk dari citra bahasa isyarat tersebut. …”
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Simulation of global sea surface temperature maps using Pix2Pix GAN by Deepayan Chakraborty, Adway Mitra

“…As an alternative approach, researchers are exploring if such simulated data can be generated by Generative Machine Learning models. In this work, we develop a model based on Pix2Pix conditional Generative Adversarial Network (cGAN), which can generate high-resolution spatial maps of global sea surface temperature (SST) using comparatively less computing power and time. …”
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Advancements in the Application of Convolutional Neural Networks in Ultrasound Imaging for Breast Cancer Diagnosis and Treatment by An Zichen, Li Fan

“…Deep learning (DL), as one of the most powerful machine learning techniques in the field of artificial intelligence (AI), has the ability to automatically select features from raw data, achieving remarkable advancements in breast US imaging. …”
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A multi-dimensional decision framework based on the XGBoost algorithm and the constrained parametric approach by Xinxin Wang, BingBing Zhang, Zeshui Xu, Ming Li, Marinko Skare

“…Under the framework, XGBoost algorithm, one of the machine learning methods, is conducted to capture the importance of attributes by using the historical data, and further calculate the attribute weights. …”
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The development trend of China’s marine economy: a predictive analysis based on industry level by Yu Chen, Huahan Zhang, Lingling Pei

“…First, the results from multi-step experiments demonstrate that the CFGM model significantly outperforms traditional statistical, machine learning models, and grey models in the context of the sectoral added value predictions, with an average accuracy improvement of 32.14%. …”
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Technology adoption and extreme stock risk: Evidence from digital tax reform in China by Kangqi Jiang, Xiaofeng Chen, Jiayun Li, Mengling Zhou

“…After performing parallel trend test, dealing with endogeneity concerns, and estimating the double machine learning model, we confirm baseline findings again. …”
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Enhancing urban air quality prediction using time-based-spatial forecasting framework by Shrikar Jayaraman, Nathezhtha T, Abirami S, Sakthivel G

“…The proposed Time-Based-Spatial (TBS) forecasting framework is integrated with spatial and temporal information using machine learning techniques on data collected from a wide range of cities. …”
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Prediction of individual patient outcomes to psychotherapy vs medication for major depression by Devon LoParo, Boadie W. Dunlop, Charles B. Nemeroff, Helen S. Mayberg, W. Edward Craighead

“…Individual response to treatment, however, is variable, implying individual differences that could allow for prospective differential prediction of treatment response and personalized treatment recommendation. We used machine learning to develop predictor variables that combined demographic and clinical items from a randomized clinical trial. …”
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Comparison of the Performance of the C.45 Algorithm with Naive Bayes in Analyzing Book Borrowing at the Library Pringsewu Muhammadiyah University by Dani Wilian, Sriyanto Sriyanto

“…This research underscores the potential of data mining techniques to optimize library management and proposes avenues for future investigation, such as exploring advanced machine learning algorithms and expanding datasets for use in broader library contexts.…”
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Double layer federated security learning architecture for artificial intelligence of things by ZHENG Chengbo, YAN Haonan, FU Caili, ZHANG Dong, LI Hui, WANG Bin

“…Federated learning, as a distributed machine learning architecture, can complete model co-training while protecting data privacy, and is widely used in Artificial Intelligence of Things. …”
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Prediction of hemolytic peptides and their hemolytic concentration by Anand Singh Rathore, Nishant Kumar, Shubham Choudhury, Naman Kumar Mehta, Gajendra P. S. Raghava

“…Among classification models, including machine learning (ML), quantum ML, and protein language models, a hybrid model combining random forest (RF) and a motif-based approach achieves the highest area under the receiver operating characteristic curve (AUROC) of 0.921. …”
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Recommended System Optimization in Social Networks Based on Cooperative Filter with Deep MVR Algorithm by Kim Hung Pho

“…In this research, we tried to provide a system of recommendations for introducing new users to previous users and vice versa based on the principles of machine learning. The proposed method is that the data is entered into the program and then the keywords are extracted from them. …”
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Accelerating charge estimation in molecular dynamics simulations using physics-informed neural networks: corrosion applications by Aditya Venkatraman, Mark A. Wilson, David Montes de Oca Zapiain

“…To address this, we develop reduced-order machine learning models that provide accurate and efficient predictions of charge density in corrosive environments. …”
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Comorbidity Networks From Population-Wide Health Data: Aggregated Data of 8.9M Hospital Patients (1997–2014) by Elma Dervić, Katharina Ledebur, Stefan Thurner, Peter Klimek

“…The dataset provides the possibility to researchers to create their own, tailor-made comorbidity networks from real patient data that can be used as a starting point in quantitative and machine learning methods. This data platform is intended to lead to deeper insights into a wide range of epidemiological, public health, and biomedical research questions.…”
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Leveraging multiplexed metasurfaces for multi-task learning with all-optical diffractive processors by Behroozinia Sahar, Gu Qing

“…Diffractive Neural Networks (DNNs) leverage the power of light to enhance computational performance in machine learning, offering a pathway to high-speed, low-energy, and large-scale neural information processing. …”
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