Nerve‐Inspired Optical Waveguide Stretchable Sensor Fusing Wireless Transmission and AI Enabling Smart Tele‐Healthcare by Tianliang Li, Qian'ao Wang, Zichun Cao, Jianglin Zhu, Nian Wang, Run Li, Wei Meng, Quan Liu, Shifan Yu, Xinqin Liao, Aiguo Song, Yuegang Tan, Zude Zhou

“…A speech recognition and human‐machine interaction system, based on sensor signal acquisition, is constructed, and the convolutional neural network algorithm is integrated for disease assessment. …”
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A Software Tool for Optimal Sizing of PV Systems in Malaysia by Tamer Khatib, Azah Mohamed, K. Sopian

“…The software has the capabilities of predicting the metrological variables such as solar energy, ambient temperature and wind speed using artificial neural network (ANN), optimizes the PV module/ array tilt angle, optimizes the inverter size and calculate optimal capacities of PV array, battery, wind turbine and diesel generator in hybrid PV systems. …”
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Machine learning-driven power prediction in continuous extrusion of pure titanium for enhanced structural resilience under extreme loading by Ahmed Ghazi Abdulameer, Muhannad M. Mrah, Maryam Bazerkan, Luttfi A. Al-Haddad, Mustafa I. Al-Karkhi

“…Specifically, an Artificial Neural Network (ANN) model optimized using Stochastic Gradient Descent (SGD) was introduced to forecast power requirements with high precision. …”
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Exploring the Relationships between Subjective Evaluations and Objective Metrics of Vehicle Dynamic Performance by Jianyou Zhao, Jing Liu, Liping Yang, Ping He

“…Finally, an overall subjective evaluation model related to the three objective metrics was established based on the Probabilistic Neural Network (PNN). The analysis results demonstrated that the correlation coefficients of the three groups of data were greater than 0.5 and that each subjective evaluation was significantly correlated with its corresponding objective metric. …”
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Action Selection and Operant Conditioning: A Neurorobotic Implementation by André Cyr, Frédéric Thériault

“…We propose simulating an AS process by using a small spiking neural network (SNN) as the lower neural organisms, in order to control virtual and physical robots. …”
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Detecting Subtle Cyberattacks on Adaptive Cruise Control Vehicles: A Machine Learning Approach by Tianyi Li, Mingfeng Shang, Shian Wang, Raphael Stern

“…The proposed approach is observed to outperform contemporary neural network models in detecting irregular driving patterns of ACC vehicles.…”
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Distance Measurement and Error Compensation of High-Speed Coaxial Rotor Blades Based on Coded Ultrasonic Ranging by Yaohuan Lu, Shan Zhang, Wenchuan Hu, Zhen Qiu, Zurong Qiu, Yongqiang Qiu

“…The measurement error characteristics under different trigger phases and different rotational speeds are studied, and the error model is fitted by the back-propagation neural network method. After compensation, the vertical distance measurement errors are within ±2 mm in the range of 100–1000 mm under the condition that the rotational speed of the blade is up to 1020 RPM. …”
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Active Vibration Control of the Sting Used in Wind Tunnel: Comparison of Three Control Algorithms by Xing Shen, Yuke Dai, Mingxuan Chen, Lei Zhang, Li Yu

“…This paper details three algorithms, respectively, Classical PD Algorithm, Artificial Neural Network PID (NNPID), and Linear Quadratic Regulator (LQR) Optimal Control Algorithm, which can realize active vibration control of sting used in wind tunnel. …”
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YOLO-UNet Architecture for Detecting and Segmenting the Localized MRI Brain Tumor Image by Nur Iriawan, Anindya A. Pravitasari, Ulfa S. Nuraini, Nur I. Nirmalasari, Taufik Azmi, Muhammad Nasrudin, Adam F. Fandisyah, Kartika Fithriasari, Santi W. Purnami, null Irhamah, Widiana Ferriastuti

“…This paper employed deep learning to detect and segment brain tumor MRI images by combining the convolutional neural network (CNN) and fully convolutional network (FCN) methodology in serial. …”
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Effect of Caesalpinia decapetala on the Dry Sliding Wear Behavior of Epoxy Composites by Hailemariam Biratu, Mengistu Gelaw, Kiran Shahapurkar, Venkatesh Chenrayan, Manzoore Elahi M. Soudagar, Vineet Tirth, Ali Algahtani, Tawfiq Al-Mughanam

“…The grey relational analysis- (GRA-) coupled artificial neural network (ANN) hybrid technique was employed for the prediction and validation. …”
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DTI-MHAPR: optimized drug-target interaction prediction via PCA-enhanced features and heterogeneous graph attention networks by Guang Yang, Yinbo Liu, Sijian Wen, Wenxi Chen, Xiaolei Zhu, Yongmei Wang

“…Our approach initiates with the construction of a heterogeneous graph from various similarity metrics, which is then encoded via a graph neural network. We concatenate and integrate the resultant representation vectors to merge multi-level information. …”
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Fusion of MHSA and Boruta for key feature selection in power system transient angle stability by WANG Man, ZHOU Xiaoyu, CHEN Fan, LAI Yening, ZHU Ying

“…A transient power angle stability key feature selection method that seamlessly integrates multi-head self-attention (MHSA) and the Boruta algorithm. A deep neural network (DNN) with an MHSA model is initially constructed to execute transient stability assessments directly on the input grid features. …”
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Optimization of Jamming Type Selection for Countering Multifunction Radar Based on Generative Adversarial Imitation Learning by Tianjian Yang, You Chen, Siyi Cheng, Xing Wang, Xi Zhang

“…This difference is used as an internal reward to assist in updating the neural network parameters, effectively reducing the complexity of reward function design. …”
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Utilizing Machine Learning-based Classification Models for Tracking Air Pollution Sources: A Case Study in Korea by Yelim Choi, Bogyeong Kang, Daekeun Kim

“…Using 972 datasets consisting of five emission sources and 27 air pollutants, different classification models were implemented and subsequently compared: Random Forest (RF), Naïve Bayes Classifier (NBC), Support Vector Machine (SVM), Artificial Neural Network (ANN), and K-Nearest Neighbors (K-NN). …”
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Recent advances in journal bearings: wear fault diagnostics, condition monitoring and fault diagnosis methodologies by Nazik Jebur, Wafa Soud

“…Key findings indicate that ensemble models, such as the CNN and deep neural network (CNNEPDNN) model, significantly improve convergence speed, test accuracy, and F-Score in bearing fault diagnosis by 15-20% compared to individual models. …”
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A Novel Deep Learning-Based Data Analysis Model for Solar Photovoltaic Power Generation and Electrical Consumption Forecasting in the Smart Power Grid by Camille Franklin Mbey, Felix Ghislain Yem Souhe, Vinny Junior Foba Kakeu, Alexandre Teplaira Boum

“…The results obtained show the outperformance of the proposed optimized method based on deep learning in the both electrical consumption and PV power generation forecasting and its superiority compared to basic methods of deep learning such as support vector machine (SVM), MLP, recurrent neural network (RNN), and random forest algorithm (RFA).…”
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Attention-enhanced corn disease diagnosis using few-shot learning and VGG16 by Ruchi Rani, Jayakrushna Sahoo, Sivaiah Bellamkonda, Sumit Kumar

“…The proposed work uses a pre-trained convolution neural network, VGG16, as the backbone, fine-tuned on the corn disease dataset. …”
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NuFold: end-to-end approach for RNA tertiary structure prediction with flexible nucleobase center representation by Yuki Kagaya, Zicong Zhang, Nabil Ibtehaz, Xiao Wang, Tsukasa Nakamura, Pranav Deep Punuru, Daisuke Kihara

“…NuFold is a deep neural network trained end-to-end for the output structure from the input sequence. …”
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A Three‐Terminal Memristive Artificial Neuron with Tunable Firing Probability by Mila Lewerenz, Elias Passerini, Luca Weber, Markus Fischer, Nadia Jimenez Olalla, Raphael Gisler, Alexandros Emboras, Mathieu Luisier, Miklos Csontos, Ueli Koch, Juerg Leuthold

“…To date, the latter two key features are critically missing from the toolbox of artificial spiking neural network hardware, hindering the development of scalable and sustainable artificial intelligence (AI) platforms. …”
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Advanced Mineral Deposit Mapping via Deep Learning and SVM Integration With Remote Sensing Imaging Data by Nazir Jan, Nasru Minallah, Madiha Sher, Muhammad Wasim, Shahid Khan, Amal Al‐Rasheed, Hazrat Ali

“…Initially, we apply a deep convolutional neural network (CNN) to a specialized mineral dataset to map mineral deposits within the study area. …”
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