Survey of node localization scheme in underwater wireless sensor network by YANG Qiuling, ZHU Rongxin, TANG Zhichao, LI Wenjie, HUANG Xiangdang

“…Representative methods were divided into three categories, namely traditional algorithms, deep learning models, and reinforcement learning strategies, and they were summarized and compared in terms of their fundamental principles, performance characteristics, and applicable scenarios. …”
Get full text

Performance for rotor system of hybrid electromagnetic bearing and elastic foil gas bearing with dynamic characteristics analysis under deep learning. by Xiangxi Du, Yanhua Sun

Get full text

Optimal Control Based on Reinforcement Learning for Flexible High-Rise Buildings with Time-Varying Actuator Failures and Asymmetric State Constraints by Min Li, Rui Xie

“…By introducing a time-varying asymmetric Lyapunov function, system state constraints are ensured, safeguarding system stability and security. …”
Get full text

Alleviating Local Optima in Bridge Bidding via Diverse PPO Ensembling by Yi Zhang, Fengyi Song, Chaohui Zhang, Tao Zhang, Weiguo Deng

“…These improvements are further integrated through ensemble learning to create a robust and efficient strategic framework. …”
Get full text

Road Damage Detection Using Yolov9-Based Imagery by Febrian Akbar Azhari, Tatang Rohana, Kiki Ahmad Baihaqi, Ahmad Fauzi

“…A consistent decline in loss functions during training also signifies effective learning by the model. …”
Get full text

TLEABLCNN: Brain and Alzheimer’s Disease Detection Using Attention-Based Explainable Deep Learning and SMOTE Using Imbalanced Brain MRI by Erol Kina

“…It degenerates the brain and reduces the activity of individuals by disrupting their memory and physiological functions. A comprehensive examination of specific brain tissue is required in order to accurately diagnose a brain condition using magnetic resonance imaging. …”
Get full text

Potential impacts of artificial intelligence for management accounting in the perception of professionals in the field by Marcela Chagas de Souza Schwindt, Simone Alves da Costa

“…Results: The results show that some AI functions could potentially interfere with the business and converge with previous investigations, namely: process mining and machine learning. …”
Get full text

Toward Specialized Wireless Networks Using an ML-Driven Radio Interface by Kamil Szczech, Maksymilian Wojnar, Katarzyna Kosek-Szott, Krzysztof Rusek, Szymon Szott, Dileepa Marasinghe, Nandana Rajatheva, Richard Combes, Francesc Wilhelmi, Anders Jonsson, Boris Bellalta

“…An enabler of SpecNets are the recent advances in artificial intelligence and machine learning (AI/ML), which allow to continuously learn and react to changing requirements and scenarios. …”
Get full text

The multiple uses of artificial intelligence in exercise programs: a narrative review by Alberto Canzone, Alberto Canzone, Giacomo Belmonte, Antonino Patti, Domenico Savio Salvatore Vicari, Domenico Savio Salvatore Vicari, Fabio Rapisarda, Valerio Giustino, Patrik Drid, Antonino Bianco

Get full text

Incorporating Traffic Flow Model into A Deep Learning Method for Traffic State Estimation: A Hybrid Stepwise Modeling Framework by Yuyan Annie Pan, Jifu Guo, Yanyan Chen, Siyang Li, Wenhao Li

“…We build a hybrid cost function to adjust the weights of model-driven and data-driven proportions. …”
Get full text

Optimizing learning outcomes in physical education: A comprehensive systematic review of hybrid pedagogical models integrated with the Sport Education Model. by Junlong Zhang, Kim Geok Soh, Xiaorong Bai, Mohd Ashraff Mohd Anuar, Wensheng Xiao

“…What learning outcomes are optimized through the hybrid models that combine SEM with other PMs?…”
Get full text

Alpha helices are more evolutionarily robust to environmental perturbations than beta sheets: Bayesian learning and statistical mechanics for protein evolution by Tomoei Takahashi, George Chikenji, Kei Tokita, Yoshiyuki Kabashima

“…This evolutionary stability is defined as a decreasing function of a quantity analogous to the susceptibility in the statistical mechanics of magnetic bodies specific to the amino acid sequence of a protein. …”
Get full text

Fault-tolerant Q-learning for discrete-time linear systems with actuator and sensor faults using input-output measured data by Mohammadrasoul Kankashvar, Sajad Rafiee, Hossein Bolandi

“…We develop a unique expression of the Fault-Tolerant Q-function (FTQF) in the input-output format and derive a model-free optimal output feedback fault-tolerant control (FTC) policy. …”
Get full text

Innovative diagnostic framework for shoulder instability: a narrative review on machine learning-enhanced scapular dyskinesis assessment in sports injuries by Yahui Fu, Shuai Ma, Benxu Ma, Meng Han, Dongxue Zhao, Ziteng Li

“…The aetiology of scapular dyskinesia (SD) adversely affects shoulder stability and function, including postural abnormalities, musculoskeletal problems, and neurological conditions. …”
Get full text

Enhanced Semi-Supervised Medical Image Classification Based on Dynamic Sample Reweighting and Pseudo-Label Guided Contrastive Learning (DSRPGC) by Kun Liu, Ji Liu, Sidong Liu

“…Finally, we introduce a pseudo-label guided contrastive learning (PGC) loss function that improves intra-class compactness and inter-class separability of the model’s feature representations. …”
Get full text

Adaptive distributed stochastic deep reinforcement learning control for voltage and frequency restoration in islanded AC microgrids with communication noise and delay by Nima Mahdian Dehkordi, Vahab Nekoukar

“…Abstract This paper proposes an adaptive secondary control strategy for islanded AC microgrids (MGs) using Distributed Stochastic Deep Reinforcement Learning (DSDRL), targeting reliable frequency and voltage restoration alongside proportional power sharing. …”
Get full text

Novel 3D UAV Path Planning for IoT Services Based on Interactive Cylindrical Vector Teaching–Learning Optimization Algorithm by Xinghe Jiang, Xuanyu Wu, Zhifeng Zhang, Zhaoxi Hong, Xi Xiao, Yixiong Feng

“…The ICVTLBO is compared with other classical and novel algorithms on the CEC2022 benchmark function suite, demonstrating its effectiveness and reliability in solving complex optimization problems. …”
Get full text

MUF-Net: A Novel Self-Attention Based Dual-Task Learning Approach for Automatic Left Ventricle Segmentation in Echocardiography by Juan Lyu, Jinpeng Meng, Yu Zhang, Sai Ho Ling

“…Left ventricular ejection fraction (LVEF) is a critical indicator for assessing cardiac function and diagnosing heart disease. LVEF can be derived by estimating the left ventricular volume from end-systolic and end-diastolic frames through echocardiography segmentation. …”
Get full text

GeoMM-SSL: Integrating Geospatial Object Relations in Multimodal Self-Supervised Learning for Semantic Segmentation of Remote Sensing Images by Yang Liu, Tong Zhang, Yanru Huang

“…The proposed framework includes a teacher-student framework with residual gated guidable attention units as the backbone, a multihead graph attention network that encodes prior knowledge of geospatial object relations, a multimodal representation fusion module that facilitates mutual learning between visual features of remote sensing images and topological features of geospatial object relations, and a multilevel loss function that performs multiple levels of evaluation, enabling the model to learn the data representation at the pixel, object, and global levels. …”
Get full text

Image-based soft drink type classification and dietary assessment system using deep convolutional neural network with transfer learning by Rubaiya Hafiz, Mohammad Reduanul Haque, Aniruddha Rakshit, Mohammad Shorif Uddin

“…To develop consciousness among people, the present work describes an image-based tool to self-monitor the nutritional information of soft drinks by using a deep convolutional neural network (CNN) along with transfer learning. At first, a pre-processing function is done through noise reduction and contrast enhancement. …”
Get full text