A comprehensive review of metasurface-assisted direction-of-arrival estimation by Huang Min, Li Ruichen, Zou Yijun, Zheng Bin, Qian Chao, Jin Hui, Chen Hongsheng

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Big Data Analysis Using Apache Spark MLlib and Hadoop HDFS with Scala and Java by Hoger Khayrolla Omar, Alaa Khalil Jumaa

Subjects: “…Keywords: Big data, Data analysis, Apache Spark, Hadoop HDFS, Machine learning, Spark MLlib, Resilient Distributed Datasets(RDD).…”
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Predicting Iran Cooperative Development Bank's Profit/Loss: Two-stage Collective Learning by Seyed Bagher Fattahi, Seyed Mozafar Mirbargkar, Ebrahim Chirani, Mohammadreza Vatanparast

Subjects: “…two-stage collective machine learning…”
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Defect Detection in Concrete Structures Based on Characteristics of Hammer Reaction Force and Apparent Stiffness of Concrete by Koki Shoda, Jun Younes Louhi Kasahara, Qi An, Atsushi Yamashita

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PREDICTING THE LEARNING PATH TO LEARNER’S OPTIMUM COMPREHENSION by Ifeanyi Isaiah Achi, Chukwuemeka Odi Agwu, Christopher Chizoba Nnamene, Sylvester C. Aniobi, Ifebude Barnabas C., Kelechi Christian Oketa, Godson Kenechukwu Ezeh, John Otozi Ugah

Subjects: “…Machine Learning…”
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Harnessing artificial intelligence for predicting breast cancer recurrence: a systematic review of clinical and imaging data by Jaqueline Alvarenga Silveira, Alexandre Ray da Silva, Mariana Zuliani Theodoro de Lima

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Meta Learning Strategies for Comparative and Efficient Adaptation to Financial Datasets by Kubra Noor, Ubaida Fatima

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AI-enhanced 3D-QSAR screening of fragment-based novel designed molecules targeting Phalaris minor ACCase by Bikash Kumar Rajak, Priyanka Rani, Durg Vijay Singh, Nitesh Singh

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Prediction of Soil Organic Carbon Content in <italic>Spartina alterniflora</italic> by Using UAV Multispectral and LiDAR Data by Jiannan He, Yongbin Zhang, Mingyue Liu, Lin Chen, Weidong Man, Hua Fang, Xiang Li, Xuan Yin, Jianping Liang, Wenke Bai, Fuping Li

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Closed-form interpretation of neural network classifiers with symbolic gradients by Sebastian J Wetzel

“…Machine Learning: Science and Technology…”
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Efficient Monte Carlo simulation of streamer discharges with deep-learning denoising models by F M Bayo-Muñoz, A Malagón-Romero, A Luque

“…Machine Learning: Science and Technology…”
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Randomized radial basis function neural network for solving multiscale elliptic equations by Yuhang Wu, Ziyuan Liu, Wenjun Sun, Xu Qian

“…Machine Learning: Science and Technology…”
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Inception networks, data augmentation and transfer learning in EEG-based photosensitivity diagnosis by Fernando Moncada Martins, Víctor M González, José R Villar, Beatriz García López, Ana Isabel Gómez-Menéndez

“…Machine Learning: Science and Technology…”
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Quantitative assessment of PINN inference on experimental data for gravity currents flows by Mickaël Delcey, Yoann Cheny, Jean Schneider, Simon Becker, Sébastien Kiesgen De Richter

“…Machine Learning: Science and Technology…”
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Into the latent space of capacitive sensors: interpolation and synthetic data generation using variational autoencoders by Miguel Monteagudo Honrubia, Francisco Javier Herraiz-Martínez, Javier Matanza Domingo

“…Machine Learning: Science and Technology…”
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Deep(er) reconstruction of imaging Cherenkov detectors with swin transformers and normalizing flow models by C Fanelli, J Giroux, J Stevens

“…Machine Learning: Science and Technology…”
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Evaluasi Kinerja MLLIB APACHE SPARK pada Klasifikasi Berita Palsu dalam Bahasa Indonesia by Antonius Angga Kurniawan, Metty Mustikasari

“… Machine learning digunakan untuk menganalisis, mengklasifikasikan, atau memprediksi data. …”
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Analisis Kinerja Intrusion Detection System Berbasis Algoritma Random Forest Menggunakan Dataset Unbalanced Honeynet BSSN by Kuni Inayah, Kalamullah Ramli

“…Hasil analisis menunjukkan bahwa pemodelan IDS based on machine learning memiliki rata-rata nilai akurasi lebih dari 90%, nilai presisi 91%, nilai recall 90%, dan F1-score 90%. …”
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Joint Distribution pada Weighted Majority Vote (WMV) untuk Peningkatan Kinerja Sentiment Analysis Tersupervisi pada Dataset Twitter by Bagus Setya Rintyarna

“…Ada dua pendekatan yang umum digunakan dalam teknik sentiment analysis yaitu pendekatan berbasis machine learning (ML) dan pendekatan berbasis sentiment lexicon (SL). …”
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Exploring small-scale optimization coupling learning approaches for enterprises’ financial health forecasts by Lin Zhu, Zhihua Zhang, M. James C. Crabbe

“…Most data-driven financial health forecasts are based on the direct use of small-scale machine learning. In this study, we proposed the idea of optimization coupling learning to improve these machine learning models in financial health forecasting. …”
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