Study on Thermal Conductivity Prediction of Granites Using Data Augmentation and Machine Learning by Yongjie Ma, Lin Tian, Fuhang Hu, Jingyong Wang, Echuan Yan, Yanjun Zhang

“…To address the insufficient generalization ability of machine learning models caused by scarce measured data on granite thermal conductivity, this study focused on granites from the Gonghe Basin and Songliao Basin in Qinghai Province. …”
Get full text

Triple-effect correction for Cell Painting data with contrastive and domain-adversarial learning by Chengwei Yan, Yu Zhang, Jiuxin Feng, Heyang Hua, Zhihan Ruan, Zhen Li, Siyu Li, Chaoyang Yan, Pingjing Li, Jian Liu, Shengquan Chen

“…The interaction of various technical effects can obscure true biological signals and complicate the characterization of CP data, making correction essential for reliable analysis. …”
Get full text

Data mining methods application in reflexive adaptation realization in e-learning systems by A. S. Bozhday, Y. I. Evseeva, A. A. Gudkov

“…The purpose of this work is to develop the basics of the technology of self-optimization of software systems in the structure of e-learning. The proposed technology is based on the formulated and formalized principle of reflexive adaptation of software, applicable to a wide class of software systems and based on the discovery of new knowledge in the behavioral products of the system.To solve this problem, methods of data mining were applied. …”
Get full text

Adaptive machine learning framework: Predicting UHPC performance from data to modelling by Yinzhang He, Shaojie Gao, Yan Li, Yongsheng Guan, Jiupeng Zhang, Dongliang Hu

“…The framework has several key modules: data preprocessing, feature selection, outlier detection, model training, hyperparameter optimization, and model interpretation. …”
Get full text

Machine learning for battery quality classification and lifetime prediction using formation data by Jiayu Zou, Yingbo Gao, Moritz H. Frieges, Martin F. Börner, Achim Kampker, Weihan Li

“…Accurate classification of battery quality and prediction of battery lifetime before leaving the factory would bring economic and safety benefits. Here, we propose a data-driven approach with machine learning to classify the battery quality and predict the battery lifetime before usage only using formation data. …”
Get full text

Integration of multimodal imaging data with machine learning for improved diagnosis and prognosis in neuroimaging by Saurabh Bhattacharya, Sashikanta Prusty, Sanjay P. Pande, Monali Gulhane, Santosh H. Lavate, Nitin Rakesh, Saravanan Veerasamy

“…This work presents a novel mixed deep learning (DL) method combining data from many sources using CNN, GRU, and attention techniques. …”
Get full text

Time-Series Data-Driven PM_2.5 Forecasting: From Theoretical Framework to Empirical Analysis by Chunlai Wu, Ruiyang Wang, Siyu Lu, Jiawei Tian, Lirong Yin, Lei Wang, Wenfeng Zheng

“…Bibliometric analysis shows that research output is growing rapidly, with China and the United States playing a leading role, and recent research is increasingly focusing on data-driven methods such as deep learning. …”
Get full text

Stacked ensemble model for NBA game outcome prediction analysis by Guangsen He, Hyun Soo Choi

Get full text

Raw-Data Driven Functional Data Analysis with Multi-Adaptive Functional Neural Networks for Ergonomic Risk Classification Using Facial and Bio-Signal Time-Series Data by Suyeon Kim, Afrooz Shakeri, Seyed Shayan Darabi, Eunsik Kim, Kyongwon Kim

“…To overcome these challenges, this paper proposes a Multi-Adaptive Functional Neural Network (Multi-AdaFNN), a novel method that integrates functional data analysis with deep learning techniques. The proposed model introduces a novel adaptive basis layer composed of micro-networks tailored to each individual time-series feature, enabling end-to-end learning of discriminative temporal patterns directly from raw data. …”
Get full text

Cyberbullying Detection, Prevention, and Analysis on Social Media via Trustable LSTM-Autoencoder Networks over Synthetic Data: The TLA-NET Approach by Alfredo Cuzzocrea, Mst Shapna Akter, Hossain Shahriar, Pablo García Bringas

Get full text

Intelligence analysis and application for satellite imagery of big data by Jinfang ZHANG, Xiaohui HU, Hui ZHANG, Rui WANG, Haichang LI

“…Imaging capability has been greatly improved along with the development of remote sensing technology,the image information extraction based on deep learning raises to a new level,and cloud computing makes it possible of processing satellite imagery of big data.These three technologies activated the research on the expected potential commercial and military value,many research institutions joined the strength competition,and attracted a large number of venture capital.The potential value analysis and application based on satellite imagery of big data were summarized,and the next possible technological breakthroughs and the future direction of development were presented.…”
Get full text

Performance Evaluation of Support Vector Machine and Stacked Autoencoder for Hyperspectral Image Analysis by Brahim Jabir, Bendaoud Nadif, Isabel De la Torre Diez, Helena Garay, Irene Delgado Noya

“…Conversely, when abundant training data are available, SAE demonstrates impressive capabilities in learning complex patterns. …”
Get full text

Music Genre Classification Based on Functional Data Analysis by Jiahong Shen, Guangrun Xiao

“…This paper proposes a noval method for MGC using functional data analysis (FDA) to represent music signals as smooth functions, capturing their temporal and harmonic properties more naturally. …”
Get full text

Parenclitic Network Analysis of Methylation Data for Cancer Identification. by Alexander Karsakov, Thomas Bartlett, Artem Ryblov, Iosif Meyerov, Mikhail Ivanchenko, Alexey Zaikin

Get full text

How do they like it? Higher education teachers’ professional development preferences for blended learning and technology acceptance profiles by Anja Garone, Sarah K. Howard, Jie Yang, Jo Tondeur, Bram Pynoo, Bram Bruggeman, Katrien Struyven

Subjects: Get full text

Assessing dynamic brain activity during verbal associative learning using MEG/fMRI co-processing by Sangeeta Nair, Jerzy P. Szaflarski, Yingying Wang, Diana Pizarro, Jeffrey F. Killen, Jane B. Allendorfer

Subjects: Get full text

Machine Learning Based Method for Insurance Fraud Detection on Class Imbalance Datasets With Missing Values by Ahmed A. Khalil, Zaiming Liu, Ahmed Fathalla, Ahmed Ali, Ahmad Salah

“…We proposed addressing the missing data and the class imbalance problems with different methods. …”
Get full text

Statistical data analysis methods in Brillouin spectroscopy: Tutorial by Christopher G. Poulton, Hadi Mahmodi, Matthew D. Arnold, Luke McAlary, Lezanne Ooi, Irina Kabakova

“…In this tutorial, we discuss in detail the application of the two unsupervised machine learning methods, principal component analysis and vertex component analysis, which can be used to retrieve information from the Brillouin microscopy data of heterogeneous samples. …”
Get full text

Comparative analysis of machine learning techniques for enhanced vehicle tracking and analysis by Seema Rani, Sandeep Dalal

“…According to our data, these methods greatly enhance the accuracy of spotting, with YOLOv3 showing the best level of accuracy. …”
Get full text

A Method for Prediction and Analysis of Student Performance That Combines Multi-Dimensional Features of Time and Space by Zheng Luo, Jiahao Mai, Caihong Feng, Deyao Kong, Jingyu Liu, Yunhong Ding, Bo Qi, Zhanbo Zhu

Subjects: Get full text