Copper Nodule Defect Detection in Industrial Processes Using Deep Learning by Zhicong Zhang, Xiaodong Huang, Dandan Wei, Qiqi Chang, Jinping Liu, Qingxiu Jing

Get full text

Research on rock strength prediction model based on machine learning algorithm by Xiang Ding, Mengyun Dong, Wanqing Shen

“…It is noteworthy that AdaBoost was found to be the best model for predicting rock compressive strength. This study presents a significant advancement in the field by demonstrating the effectiveness of machine learning algorithms in this context, which have not been extensively applied to rock compressive strength predictions. …”
Get full text

Deep learning model for detecting high-grade dysplasia in colorectal adenomas by Eric Steimetz, Zeliha Celen Simsek, Asmita Saha, Rong Xia, Raavi Gupta

“…In this study, we trained a deep learning model to distinguish between colorectal adenomas with LGD and HGD. …”
Get full text

Adaptive deep feature representation learning for cross-subject EEG decoding by Shuang Liang, Linzhe Li, Wei Zu, Wei Feng, Wenlong Hang

“…Specifically, we first minimize the distribution discrepancy between the source and target domains by employing maximum mean discrepancy (MMD) regularization, which aids in learning the shared feature representations. We then utilize the instance-based discriminative feature learning (IDFL) regularization to make the learned feature representations more discriminative. …”
Get full text

Facilitating cross-cultural competence of students in an interactive VR learning environment by Rustam Shadiev, Xuan Chen, Wayan Sintawati, Fahriye Altinay, Yan Li, Nurassyl Kerimbayev, Ahmed Tlili

“…Therefore, we aimed to address this issue in the present study by developing an interactive VR learning environment with such elements as (a) 360-degree video camera for creating cultural content, (b) 360-degree video viewing tool for viewing the created content, and (c) online video conference platform, enabling students to watch each other’s VR content and communicate about it simultaneously. …”
Get full text

Real-time classification of EEG signals using Machine Learning deployment by Swati CHOWDHURI, Satadip SAHA, Samadrita KARMAKAR, Ankur CHANDA

“…However, the realtime impact of machine learning models necessitates a careful consideration as their deployment is concerned. …”
Get full text

An Analysis of Layer-Freezing Strategies for Enhanced Transfer Learning in YOLO Architectures by Andrzej D. Dobrzycki, Ana M. Bernardos, José R. Casar

“…This research addresses this gap by presenting a detailed analysis of layer-freezing strategies. …”
Get full text

Fault Detection in Photovoltaic Systems Using a Machine Learning Approach by Jossias Zwirtes, Fausto Bastos Libano, Luis Alvaro de Lima Silva, and Edison Pignaton de Freitas

“…Crucial information, including voltage, current, ambient temperature, and irradiance, was recorded to assess and classify these kinds of faults. This study presents three main contributions: the implementation and comparison of multiple machine learning models for fault detection, an investigation into the feasibility of identifying these faults using only electrical and environmental data, and an analysis of model performance in a photovoltaic system different from the one used for training. …”
Get full text

Multilingual sentiment analysis in restaurant reviews using aspect focused learning by Arifur Rahman, Md. Azam Khan, Kanchon Kumar Bishnu, Uland Rozario, Adit Ishraq, M. F. Mridha, Zeyar Aung

Get full text

Optimized Machine Learning for the Early Detection of Polycystic Ovary Syndrome in Women by Bharti Panjwani, Jyoti Yadav, Vijay Mohan, Neha Agarwal, Saurabh Agarwal

“…An ensemble learning (EL) model, with seven base classifiers, and a deep learning (DL) model, as the meta-level classifier, are proposed. …”
Get full text

Learning about social suffering through illness narrative: possibilities and challenges by Young-Gyung Paik, Jidong Sung

“…Methods This study presents a qualitative analysis of short essays submitted by forty second-year medical students at a single medical school after a class based on narrative medicine principle. …”
Get full text

Leveraging machine learning for data-driven building energy rate prediction by Nasim Eslamirad, Mehdi Golamnia, Payam Sajadi, Francesco Pilla

“…This paper presents a novel, data-driven approach for predicting Building Energy Ratings (BER) in urban environments, using advanced Machine Learning (ML) algorithms. …”
Get full text

Benchmarking In-Sensor Machine Learning Computing: An Extension to the MLCommons-Tiny Suite by Fabrizio Maria Aymone, Danilo Pietro Pau

“…This paper proposes a new benchmark specifically designed for in-sensor digital machine learning computing to meet an ultra-low embedded memory requirement. …”
Get full text

Single Transit Detection in Kepler with Machine Learning and Onboard Spacecraft Diagnostics by Matthew T. Hansen, Jason A. Dittmann

Get full text

The Content-Validated Geometry Lessons in Islam Observed Brain-based Learning by Sherma O. Sappari, Florante P. Ibarra, Amirul Mukminin, Kasinyo Harto, Lenny Marzulina, Herri Mulyono, Asmendri Asmendri

“… This study examined the process of learning geometry in content-validated lessons with the integration of Islamic values as perceived to have observed brain-based learning principles. …”
Get full text

Enhancing Incentive Schemes in Edge Computing through Hierarchical Reinforcement Learning by Gowtham R, Vatsala Anand, Yadati Vijaya Suresh, Kasetty Lakshmi Narasimha, R. Anil Kumar, V. Saraswathi

“…This work contributes to the advancement of edge learning by presenting a reliable and efficient solution for real-world applications. …”
Get full text

Bridging the Gap: A Review of Machine Learning in Water Quality Control by Herlina Abdul Rahim, Nur Athirah Syafiqah Noramli, Indrabayu

“…This review critically examines the integration of machine learning (ML) with conventional water quality monitoring and treatment methods, presenting a systematic comparison of their capabilities, limitations, and synergies. …”
Get full text

Enhanced slope stability prediction using ensemble machine learning techniques by Devendra Kumar Yadav, Swarup Chattopadhyay, Debi Prasad Tripathy, Pragyan Mishra, Pritiranjan Singh

“…Abstract The accurate prediction of slope stability is a challenging research endeavor, particularly in real-world environments. This study presents a machine learning (ML) model for evaluating slope stability that meets high precision and speed criteria in slope engineering. …”
Get full text

Preserved learning of implicit regularities with predictive social cues in older adults by Claudia Salera, Ala Yankouskaya, Maria Daniela Gazzaneo, Alessia Bonavita, Alessia Bonavita, Mariella Pazzaglia, Cecilia Guariglia, Cecilia Guariglia, Anna Pecchinenda

“…This learning biases attention as it enhances the gaze cueing effect even when the regularities are not present. …”
Get full text

Transformation of Geospatial Modelling of Soil Erosion Susceptibility Using Machine Learning by Muhammad Ramdhan Olii, Sartan Nento, Nurhayati Doda, Rizky Selly Nazarina Olii, Haris Djafar, Ririn Pakaya

“… Soil erosion presents substantial environmental and economic challenges, especially in areas prone to land degradation. …”
Get full text