Design of an Efficient Deep Learning-Based Diagnostic Model for Wind Turbine Gearboxes Using SCADA Data by Xuan-Kien Mai, Jun-Yeop Lee, Jae-In Lee, Byeong-Soo Go, Seok-Ju Lee, Minh-Chau Dinh

Subjects: Get full text

Deep learning-based identification of precipitation clouds from all-sky camera data for observatory safety by Mohammad H. Zhoolideh Haghighi, Alireza Ghasrimanesh, Habib Khosroshahi

Subjects: Get full text

ENHANCING NETWORK INTRUSION DETECTION USING MACHINE LEARNING AND META-MODELLING FOR IMPROVED CYBER SECURITY PERFORMANCE by Sunita, Pankaj Verma, Nitika, Jaspreet Kaur, Vijay Rana

Subjects: Get full text

Sensor-Based Yield Prediction in Durum Wheat Under Semi-Arid Conditions Using Machine Learning Across Zadoks Growth Stages by Süreyya Betül Rufaioğlu, Ali Volkan Bilgili, Erdinç Savaşlı, İrfan Özberk, Salih Aydemir, Amjad Mohamed Ismael, Yunus Kaya, João P. Matos-Carvalho

Subjects: Get full text

Advances in Application of Federated Machine Learning for Oncology and Cancer Diagnosis by Mohammad Nasajpour, Seyedamin Pouriyeh, Reza M. Parizi, Meng Han, Fatemeh Mosaiyebzadeh, Yixin Xie, Liyuan Liu, Daniel Macêdo Batista

“…Machine learning has brought about a revolutionary transformation in healthcare. …”
Get full text

Survey of research on encrypted traffic classification based on machine learning by FU Yu, LIU Taotao, WANG Kun, YU Yihan

“…To this end, a systematic review of the latest advancements in machine learning-driven encrypted traffic classification was provided. …”
Get full text

Machine learning for post-diploma educational and career guidance: a scoping review in AI-driven decision support systems by Flavio Manganello, Elisa Rasca, Alberto Villa, Andrea Maddalena, Giannangelo Boccuzzi

Get full text

Improved Mixture Cure Model Using Machine Learning Approaches by Huina Wang, Tian Feng, Baosheng Liang

Get full text

A predictive analytics approach with Bayesian-optimized gentle boosting ensemble models for diabetes diagnosis by Behnaz Motamedi, Balázs Villányi

Get full text

Detection and Localization of False Data Injection Attacks in Smart Grids Applying an Interpretable Fuzzy Genetic Machine Learning/Data Mining Approach by Marian B. Gorzałczany, Filip Rudziński

“…In this paper, we consider the problem of accurate, transparent, and interpretable detection, as well as the localization of false data injection attacks (FDIAs) in smart grids. In order to address that problem, we employ our knowledge discovery machine learning/data mining (ML/DM) approach—implemented as a collection of fuzzy rule-based classifiers (FR-BCs)—characterized by a genetically optimized accuracy–interpretability trade-off. …”
Get full text

Retrospective analysis of COVID-19 clinical and laboratory data: Constructing a multivariable model across different comorbidities by Mahdieh Shokrollahi Barough, Mohammad Darzi, Masoud Yunesian, Danesh Amini Panah, Yekta Ghane, Sam Mottahedan, Sohrab Sakinehpour, Tahereh Kowsarirad, Zahra Hosseini-Farjam, Mohammad Reza Amirzargar, Samaneh Dehghani, Fahimeh Shahriyary, Mohammad Mahdi Kabiri, Marzieh Nojomi, Neda Saraygord-Afshari, Seyedeh Ghazal Mostofi, Zeynab Yassin, Nazanin Mojtabavi

Get full text

A machine learning approach to predict positive coronary artery calcium scores in individuals with diabetes: a cross-sectional analysis of ELSA-Brasil baseline data by J.L. Amorim, I.M. Bensenor, A.P. Alencar, A.C. Pereira, A.C. Goulart, P.A. Lotufo, I.S. Santos

“…This study aimed to identify features associated with positive coronary artery calcium scores (CACS) in individuals with diabetes using machine learning (ML) techniques. ELSA-Brasil is a cohort study with 15,105 participants aged 35 to 74 years in six Brazilian cities. …”
Get full text

Data Mining of 24-Hour Cumulative Precipitation Data in Iran Using Machine Learning: Multilayer Perceptron Neural Network and Decision Tree by mozaffar faraji, Majid Rezaii Banafsheh Daragh, Behroz sarisarraf, Ali Mohammad Khorshid Dust

“…Research Topic: This study examines 24-hour cumulative precipitation data in Iran and predicts rainfall amounts over various time periods using data mining and machine learning. …”
Get full text

Estimation of physico-chemical properties of soil using machine learning by Patience Chizoba Mba, Opegbemi Matthias Busoye, John Temitope Ajayi, Judith Nkechinyere Njoku, Cosmas Ifeanyi Nwakanma, Senorpe Asem-Hiablie, Rammohan Mallipeddi, Tusan Park, Daniel Dooyum Uyeh

“…The study integrated Machine Learning (ML) and Deep Learning (DL) techniques with soil image analysis, employing image feature extraction through Gray-Level Co-occurrence Matrix (GLCM) and Gabor filters to enhance the feature space across 1,388 samples (each consisting of 600 g of soil) and 16 properties. …”
Get full text

The role of statistics in advancing nitric oxide research in plant biology: from data analysis to mechanistic insights by Halah Fadhil Hussein AL-Hakeem, Murtaza Khan

“…New computational techniques, including machine learning, integrative omics approaches, and network-based systems biology, present commanding outlines for identifying NO-mediated regulatory mechanisms. …”
Get full text

Using Machine Learning to Propose a Qualitative Classification of Risk of Soil Erosion by Dione Pereira Cardoso, Paulo Cesar Ossani, Marcelo Angelo Cirillo, Marx Leandro Naves Silva, Junior Cesar Avanzi

“…Following this, machine learning techniques were applied to analyze the data. …”
Get full text

Application of Machine Learning for Predictive Analysis and Management of Mediterranean-Farmed Fish Mortalities: A Risk Management Case Study Using Apache Spark by Marios C. Gkikas, Dimitris C. Gkikas, Gerasimos Vonitsanos, John A. Theodorou, Spyros Sioutas

Get full text

Public Perception of Autonomous Mobility Using ML-Based Sentiment Analysis over Social Media Data by Nikolaos Bakalos, Nikolaos Papadakis, Antonios Litke

Get full text

Integrative analysis of miRNA expression data reveals a minimal signature for tumour cells classification by Sabrina Napoletano, David Dannhauser, Paolo Antonio Netti, Filippo Causa

Get full text

Multidimensional analysis of climate-induced streamflow variability using CMIP6 data and advanced modeling techniques by Phyo Thandar Hlaing, Usa Wannasingha Humphries, Muhammad Waqas

Get full text