Boruta-grid-search least square support vector machine for NO2 pollution prediction using big data analytics and IoT emission sensors by Habeeb Balogun, Hafiz Alaka, Christian Nnaemeka Egwim

Get full text

Damage Classification Approach for Concrete Structure Using Support Vector Machine Learning of Decomposed Electromechanical Admittance Signature via Discrete Wavelet Transform by Jingwen Yang, Demi Ai, Duluan Zhang

“…Then these indicators, incorporated with traditional ones including root mean square deviation (RMSD), baseline-changeable RMSD named RMSDk, correlation coefficient (CC), and mean absolute percentage deviation (MAPD), were processed by a support vector machine (SVM) model, and finally damage type could be automatically classified and identified. …”
Get full text

Synergizing remote sensing, support vector machine, and aeromagnetic data for precise lithological and mineral potential mapping: a case study from Egypt by Hatem M. El-Desoky, Ahmed M. Abdel-Rahman, Hamada El-Awny, Wael Fahmy, Reda Abdu Yousef El-Qassas, Kamal Abdelrahman, Hassan Alzahrani, Peter Andráš, Yahia Z. Amer, Ahmed M. Eldosouky

“…This goal involves extensive fieldwork, petrographical examinations, and image processing remote sensing techniques to accurately reveal the exposed lithologies distribution besides the potential relic areas. …”
Get full text

A New Two-Dimensional Electromagnetic Field Analysis and Loss Calculation Method for High-Frequency Applications Based on Vector Magnetic Circuit Theory by Chengbo Li, Ming Cheng, Wei Wang

“…The loss calculation of commercial finite element software is usually in the post-processing phase, making the loss calculation and electromagnetic field analysis irrelevant. …”
Get full text

A wireless sensor data-based coal mine gas monitoring algorithm with least squares support vector machines optimized by swarm intelligence techniques by Peng Chen, Yonghong Xie, Pei Jin, Dezheng Zhang

“…In order to assess the risks arisen from gas explosion or gas poisoning, wireless sensor data should be processed and classified efficiently. Due to the fact that the “negative samples” of coal mine safety data are scarce, least squares support vector machine is introduced to deal with this problem. …”
Get full text

Enhancing gender equity in resume job matching via debiasing-assisted deep generative model and gender-weighted sampling by Swati Tyagi, Anuj, Wei Qian, Jiaheng Xie, Rick Andrews

“…This study scrutinizes how biased representations in job assignments, influenced by a variety of factors such as skills and resume descriptors within diverse semantic frameworks, affect the classification process. The investigation extends to the nuanced language of resumes and the presence of subtle gender biases, including the employment of gender-associated terms, and examines how these terms’ vector representations can skew fairness, leading to a disproportionate mapping of resumes to job categories based on gender.Our findings reveal a significant correlation between gender discrepancies in classification true positive rate and gender imbalances across professions that potentially deepen these disparities. …”
Get full text

Discovering action insights from large-scale assessment log data using machine learning by Minyoung Yun, Minjeong Jeon, Heyoung Yang

“…Abstract This study introduces a novel machine learning algorithm that combines natural language processing techniques, such as Word2Vec and Doc2Vec, with neural networks to identify and validate significant actions within human action sequences. …”
Get full text

Fine-tuned PhoBERT for sentiment analysis of Vietnamese phone reviews by Tan Minh Ngo, Ba Hung Ngo, Stuchilin Vladimir Valerievich

Get full text

Fine-tuned PhoBERT for sentiment analysis of Vietnamese phone reviews by Tan Minh Ngo, Ba Hung Ngo, Stuchilin Vladimir Valerievich

Get full text

CHANGE OF MAINTENANCE OF DRY SUBSTANCES AND STARCH IN TUBERS OF POTATO IN DEPENDENCE ON TERMS OF TILL by V. K. Serderov, T. G. Chanbabaev, D. V. Serderova

“…One of the quality indexes of the use of potato varieties for their processing is high level of dry matter and starch. As a result of the research, the following varieties were identified: high-yielding are Impala, Irbit, Zhukovsky Ranniy, Manifesto, Matushka, Nevsky, Primabella, Rosara, Silvana, Spiridon and Udacha; high dry matter content are Alena, Vektor, Dzhokonda, Desiree, Matushka, Nart, Primabella and Rossi; high in starch: Desiree - 23%, Vector and Primabella - 22.2% each. …”
Get full text

A High-Precision Method for Warehouse Material Level Monitoring Using Millimeter-Wave Radar and 3D Surface Reconstruction by Wenxin Zhang, Yi Gu

“…The proposed method employs Chirp-Z Transform (CZT) super-resolution processing to enhance spectral resolution and measurement accuracy. …”
Get full text

The short video platform recommendation mechanism based on the improved neural network algorithm to the mainstream media by Mengruo Qi

“…This method combines natural language processing and image analysis in deep learning to construct accurate user and video models, deeply explore user interests, and improve the accuracy and effectiveness of recommendation systems for user preferences. …”
Get full text

AIoT-Driven Human Activity Recognition for Versatile Framework on Multipurpose Applications by Nanik Triwahyuni, Eni Wardihani, Aminuddin Rizal, Samuel Beta, Ricky Sambora, Rindang Oktaviani

“…The framework integrates sensor data from wearable IoT devices, which is then processed by AI algorithms to classify and predict human activities in real-time. …”
Get full text

Cyberbullying detection of resource constrained language from social media using transformer-based approach by Syed Sihab-Us-Sakib, Md. Rashadur Rahman, Md. Shafiul Alam Forhad, Md. Atiq Aziz

Get full text

A crop sequence dataset of the German federal state of North Rhine-Westphalia from 2019–2024Zenodo by Christoph Pahmeyer, Till Kuhn, Hugo Storm

Get full text

Categorizing Mental Stress: A Consistency-Focused Benchmarking of ML and DL Models for Multi-Label, Multi-Class Classification via Taxonomy-Driven NLP Techniques by Juswin Sajan John, Boppuru Rudra Prathap, Gyanesh Gupta, Jaivanth Melanaturu

“…This study introduces a novel approach to effectively characterize mental stress through a multi-label, multi-class classification framework through natural language processing techniques. Building on existing literature, discussions with psychologists and other mental health practitioners, we developed a taxonomy of 27 distinctive markers spread across 4 label categories; aiming to create a preliminary screening tool leveraging textual data.The core objective is to identify the most suitable model for this complex task, encompassing comprehensive evaluation of various machine learning and deep learning algorithms. we experimented with support vector machines (SVM), random forest (RF) and long short-term memory (LSTM) algorithms incorporating various feature combinations involving Term Frequency-Inverse Document Frequency (TF-IDF) and Latent Dirichlet Allocation (LDA). …”
Get full text

A Fuzzy Logic Framework for Text-Based Incident Prioritization: Mathematical Modeling and Case Study Evaluation by Arturo Peralta, José A. Olivas, Pedro Navarro-Illana

“…This paper proposes a fuzzy logic-based framework for incident categorization and prioritization, integrating natural language processing (NLP) with a formal system of fuzzy inference. …”
Get full text

Highway subgrade stability prediction model based on depth separation convolutional fusion network by Yubian Wang

“…The research results of this paper further improve the efficiency of the neural network model and maintain the accuracy of data, which not only meets the needs of highway subgrade detection but also promotes the application of large-scale image processing technology. Therefore, it has great market application value.…”
Get full text

Supervised Machine Learning Thyroid Carcinoma Diagnosis Using Wide-Field SHG Microscopy by Yaraslau Padrez, Radu Hristu, Igor Timoshchenko, Lucian G. Eftimie, Danielis Rutkauskas, Lena Golubewa

Get full text

Specific Features of Estimating Labour Productivity in Railway Transport by A. O. Batsokin

“…Based on aspects of using vector methods the  article  shows  the  necessity  to  design  a  unique  approach  to  estimating  labour  productivity  of  operating contingent within the frames of testing processes on railway transport. …”
Get full text