Integrating bioinformatics and machine learning to discover sumoylation associated signatures in sepsis by Xue Teng, Qi Wang, Jinling Ma, Dongmei Li

Get full text

A comparative study of deep reinforcement learning for crop production management by Joseph Balderas, Dong Chen, Yanbo Huang, Li Wang, Ren-Cang Li

“…Recently, researchers have turned to machine learning to address these complexities. Specifically, reinforcement learning (RL), a cutting-edge approach designed to learn optimal decision-making strategies through trial and error in dynamic environments, has emerged as a promising tool for developing adaptive crop management policies. …”
Get full text

Deep ensemble learning with transformer models for enhanced Alzheimer’s disease detection by Shiza Latif, Naeem Ul Islam, Zaki Uddin, Khalid Mehmood Cheema, Syed Sohail Ahmed, Muhammad Farhan Khan

“…Finally, these branches are fused using the ensemble learning approach to give a more robust and accurate output. …”
Get full text

Deep Transfer Learning Approach in Smartwatch-Based Fall Detection Systems by Alessandro Leone, Andrea Manni, Gabriele Rescio, Pietro Siciliano, Andrea Caroppo

“…Due to the widespread use of these devices, the system as a whole is extremely accepted, easy to use, requires no tuning of any kind, and guarantees extended functioning for a long period. From a technical standpoint, falls are identified using AI techniques to analyze 3D raw data acquired by the smartwatch’s built-in accelerometer. …”
Get full text

Multitask and Transfer Learning Approach for Joint Classification and Severity Estimation of Dysphonia by Dosti Aziz, Sztaho David

“…Additionally, we conducted binary ‘healthy vs. dysphonia’ and multiclass ‘healthy vs. organic and functional dysphonia’ classification using multitask learning, with the speaker’s sex as an auxiliary task. …”
Get full text

Bridging Hydrological Ensemble Simulation and Learning Using Deep Neural Operators by Alexander Y. Sun, Peishi Jiang, Pin Shuai, Xingyuan Chen

“…To address this issue, we propose a deep neural operator learning approach. Neural operators are generic machine learning algorithms that can learn functional mappings between infinite‐dimensional spaces, providing a highly flexible tool for scientific machine learning. …”
Get full text

A review of deep learning models to detect malware in Android applications by Elliot Mbunge, Benhildah Muchemwa, John Batani, Nobuhle Mbuyisa

“…Smartphone applications use permissions to allow users to utilize different functionalities, making them susceptible to malicious software (malware). …”
Get full text

ODD-Net: a hybrid deep learning architecture for image dehazing by C. S. Asha, Abu Bakr Siddiq, Razeem Akthar, M. Ragesh Rajan, Shilpa Suresh

“…To overcome these challenges, we present ODD-Net, a hybrid deep learning architecture. Our research introduces a comprehensive data set and an innovative architecture called Atmospheric Light Net (A-Net) to estimate atmospheric light, using dilated convolution, batch normalisation, and ReLU activation functions. …”
Get full text

Neuro-VGNB: Transfer Learning-Based Approach for Detecting Brain Stroke by Muhammad Usama Tanveer, Kashif Munir, Bharati Rathore, Abdulatif Alabdulatif, Rutvij H. Jhaveri, Maham Fatima

“…A brain stroke occurs when blood flow to the brain is interrupted leading to potential brain damage and loss of functions controlled by the affected area. Timely diagnosis and intervention are critical for minimizing long-term disabilities and improving recovery outcomes.This study addresses the critical challenge of brain stroke detection by utilizing a combination of deep learning and machine learning techniques. …”
Get full text

Stimulating innovative learning practices with tech: artefacts influence learners’ actions by Shubashini Velu, Ishraat Saira Wahid, Kayalvily Tabianan

“…The literature indicates a lack of equilibrium between the functions of artefacts, actions, and pedagogy in the ever-changing technology-enhanced learning environment. …”
Get full text

DISTANCE LEARNING WITHIN THE FRAME OF MODERN EDUCATIONAL SYSTEMS: PSYCHOLOGICAL CONTEXT by Prakhova Svitlana A., Datsenko Oksana A, Semenov Kostiantyn A.

“…Taking into account the relevance and significance of the problem of distance learning, we consider it appropriate to analyze the content and features of the implementation of distance learning within the frame of modern educational systems at the level of foreign and domestic experience of higher education institutions. …”
Get full text

Deep Learning in Defect Detection of Wind Turbine Blades: A Review by Katleho Masita, Ali N. Hasan, Thokozani Shongwe, Hasan Abu Hilal

“…This review paper examines the state-of-the-art deep learning methodologies applied to defect detection in wind turbine blades. …”
Get full text

Phase diagram construction and prediction method based on machine learning algorithms by Shengkun Xi, Jiahui Li, Longke Bao, Rongpei Shi, Haijun Zhang, Xiaoyu Chong, Zhou Li, Cuiping Wang, Xingjun Liu

“…This methodology can efficiently predict the phase diagram of material system with higher number of components by training the phase diagram data of lower ones, thereby providing a new strategy to complement the CALPHAD with machine learning technique and extend the application of CALPHAD method to the advanced materials including high entropy alloys and functional materials.…”
Get full text

Clustering Electrophysiological Predisposition to Binge Drinking: An Unsupervised Machine Learning Analysis by Marcos Uceta, Alberto del Cerro‐León, Danylyna Shpakivska‐Bilán, Luis M. García‐Moreno, Fernando Maestú, Luis Fernando Antón‐Toro

“…We used hierarchical agglomerative UML techniques based on Ward's minimum variance criterion to clusterize relations between power spectrum and functional connectivity and alcohol consumption, based on similarity in their correlations, in frequency bands from theta to gamma. …”
Get full text

Implication of explicit knowledge and subjective evaluation in procedural perceptual-motor learning by Sarah Seiwert, Elodie Martin, Elodie Martin, Elodie Martin, Yannick Lagarrigue, David Amarantini, Lilian Fautrelle, Joseph Tisseyre, Jessica Tallet

Get full text

Optimizing the neural network and iterated function system parameters for fractal approximation using a modified evolutionary algorithm by Sana Abdulla, K. Mahipal Reddy

“…However, optimizing the parameters of Iterated Function System (IFS)-based fractal interpolants remains a challenging task, particularly for Rational Fractal Cubic (RFC) splines, which offer greater flexibility in shape control. …”
Get full text

Perineural invasion in pancreatic cancer: Current biological function in R status, prognosis, and pain by Federico Selvaggi, Elisa Bannone, Eugenia Melchiorre, Michele Diana, Roberto Cotellese, Gitana Maria Aceto

Get full text

Genetic identification of a network of factors that functionally interact with the nucleosome remodeling ATPase ISWI. by Giosalba Burgio, Gaspare La Rocca, Anna Sala, Walter Arancio, Dario Di Gesù, Marianna Collesano, Adam S Sperling, Jennifer A Armstrong, Simon J van Heeringen, Colin Logie, John W Tamkun, Davide F V Corona

“…Nucleosome remodeling and covalent modifications of histones play fundamental roles in chromatin structure and function. However, much remains to be learned about how the action of ATP-dependent chromatin remodeling factors and histone-modifying enzymes is coordinated to modulate chromatin organization and transcription. …”
Get full text

Clinical phenotype and functional influence of GRIN2A variants in epilepsy‐aphasia syndrome by Lu Zhang, Yiran Duan, Rui Ma, Jiaqi Han, Na Pan, Lehong Gao, Yuping Wang

“…Also, we reviewed previously published papers about GRIN2A variants in epilepsy to learn more about the correlations between their locations, functional changes, and clinical manifestations.…”
Get full text

Cationic substitution, dynamical stability, thermal stability, electronic and thermoelectric properties in 2D dialkali metal monoxides via DFT and ML approach by S. Chellaiya, Thomas Rueshwin, R. D. Eithiraj

Subjects: Get full text