Low-threshold dual-polarization electro-optic nonlinear activation functions by Tao Jin, Jian Lin, Pengjun Wang, Qiang Fu, Yuhan Sun, Yi Zou, Shixun Dai, Weiwei Chen, Jun Li, Tingge Dai, Jianyi Yang

“…If the above-mentioned two nonlinear activation functions are introduced into the convolutional neural network to perform the modified National Institute of Standards and Technology handwritten digit classification task, validation accuracies of 97.3% and 96.85% will be achieved.…”
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Deep learning based gasket fault detection: a CNN approach by S. Arumai Shiney, R. Seetharaman, V. J. Sharmila, S. Prathiba

“…Deep learning algorithms are specific for feature extraction and classification together with a convolutional neural network (CNN) module that allows for seamless connection. …”
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A BEARING DEEP LEARNING TRANSFER DIAGNOSIS METHOD BASED ON OPTIMIZATION OF SYMMETRIC POLAR COORDINATES by WU DingHai, WANG HuaiGuang, SONG Bin, ZHANG YunQiang

“…Aiming at the problem of graphical feature representation of one-dimensional mechanical vibration signals, a bearing fault diagnosis method based on symmetric polar coordinates and residual network migration learning is proposed, which combines the powerful image classification and recognition ability of convolution neural network. Therefore, a bearing fault diagnosis method based on symmetric polar coordinates and residual network transfer learning is proposed in this paper. …”
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Software Integration of Power System Measurement Devices with AI Capabilities by Victoria Arenas-Ramos, Federico Cuesta, Victor Pallares-Lopez, Isabel Santiago

“…Moreover, real-time Artificial Intelligence capabilities have been validated by implementing three Machine Learning classifiers (Neural Network, Decision Tree, and Random Forest) to distinguish between three different loads in real time.…”
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Finite volume modeling of neural communication: Exploring electrical signaling in biological systems by Muzammal Saleem, Muhammad Saqib, Badar Saad Alshammari, Shahid Hasnain, Amjad Ayesha

“…The model has been widely applied to study phenomena such as neural network behavior and the impact of drugs on neuronal function. …”
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Energy-Efficient Robust Control for Direct Drive and Energy Recuperation Hydraulic Servo System by Weiping Wang, Jiyun Zhao

“…To compensate for the uncertainties, both in the variable supply pressure control circuit and the robust controller, the RBF neural network is employed to approximate the unknown function. …”
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Bearing fault diagnosis method based on SAVMD and CNN by SONG ChunSheng, LIANG YaRu, LU NiFang, DU Gang, JIA Bo

“…The intrinsic mode function (IMF) components were reconstructed by weighted kurtosis evaluation index, put them into convolutional neural network (CNN) model for fault classification. Finally, the proposed method was verified by numerical simulations with the open bearing data of Case Western Reserve University. …”
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Deep Neural Learning Adaptive Sequential Monte Carlo for Automatic Image and Speech Recognition by Patcharin Kamsing, Peerapong Torteeka, Wuttichai Boonpook, Chunxiang Cao

“…Using a pretrained model helps reduce the computational time to deploy an image classification model and uses a simple deep convolutional neural network for speech recognition. The applied method results in a higher speech recognition accuracy score—89.693% for the test dataset—than the conventional method, which reaches 89.325%. …”
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Wireless Mobile Power Communication System Based on Artificial Intelligence Algorithm by Juan Du, Mingqi Guo

“…First, the research status of risk assessment of wireless mobile communication system at home and abroad is analyzed, and the risk assessment index system of wireless mobile communication system is established; then, the learning samples are collected according to the risk assessment index system of wireless mobile communication system, and artificial intelligence algorithm is used to optimize the neural network. Build the wireless mobile communication system risk assessment model; finally, carry out the wireless mobile communication system risk assessment simulation comparison test. …”
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Factors Affecting Digital Financial Service Adoption in Bangladesh: Evidence from SEM-ANN Approaches by Nafis Sadik, Md. Mominur Rahman

“…This study investigates the key drivers affecting the adoption of DFS in Bangladesh by employing Structural Equation Modeling (SEM) and Artificial Neural Network (ANN) approaches. Using survey data collected from 340 DFS users, the SEM analysis validates the proposed relationships, identifying financial literacy, trust, access to capital, digital payment usage, and digital financial inclusion as significant factors driving DFS adoption. …”
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Zero-shot intelligent fault diagnosis via semantic fusion embedding by Honghua Xu, Zijian Hu, Ziqiang Xu, Qilong Qian

“…On the other hand, a neural network-based metric module is designed to replace traditional distance measurements, enhancing the transferring capability between domains. …”
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FTNet-HiLa: An adaptive multimodal histopathological image categorization network by Shuo Yin, Dong Zhang, YongKang Zhang, Xing Zhao, XuYing Zhao

“…The integration of artificial intelligence in medical imaging has witnessed a surge in neural network applications for pathological image classification, with Vision Transformers (ViTs) emerging as highly accurate models in general visual recognition tasks. …”
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Estimating the Ultimate Bearing Capacity for Strip Footing Near and within Slopes Using AI (GP, ANN, and EPR) Techniques by Ahmed M. Ebid, Kennedy C. Onyelowe, Emmanuel E. Arinze

“…The genetic programming (GP), evolutionary polynomial regression (EPR), and artificial neural network (ANN) intelligent techniques were employed to predict the ultimate bearing capacity of footing on or adjacent to a slope. …”
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Use of the Human Walking Gait Cycle for Assistive Torque Generation for the Hip Joint Exoskeleton by Riska Analia, Jan Hong, Joshua Mangkey, null Susanto, Daniel Pamungkas, Hendawan Soebhakti, Abdullah Sani

“…In this work, we classify the human gait cycle based on data from an inertial moment unit sensor and information on the angle of the hip joint and use the results as initial signals to produce a suitable assistive torque for a lower limb exoskeleton. A neural network module is used as a prediction module to identify the intention to walk based on the gait cycle. …”
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Adaptive Fuzzy Sliding Mode Guidance Law considering Available Acceleration and Autopilot Dynamics by Yulin Wang, Shengjing Tang, Wei Shang, Jie Guo

“…Then, a fuzzy system is utilized to approximate and replace the variable structure term, which can handle the unknown target acceleration. And an adaptive neural network system is adopted to compensate the effects caused by the designed overlarge acceleration of interceptor such that the interceptor with small available acceleration can intercept the high maneuvering target. …”
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Classification and Analysis of <em>Agaricus bisporus</em> Diseases with Pre-Trained Deep Learning Models by Umit Albayrak, Adem Golcuk, Sinan Aktas, Ugur Coruh, Sakir Tasdemir, Omer Kaan Baykan

“…This research evaluates 20 advanced convolutional neural network (CNN) architectures for classifying mushroom diseases in <i>Agaricus bisporus</i>, utilizing a custom dataset of 3195 images (2464 infected and 731 healthy mushrooms) captured under uniform white-light conditions. …”
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Sensorimotor environment but not task rule reconfigures population dynamics in rhesus monkey posterior parietal cortex by Hao Guo, Shenbing Kuang, Alexander Gail

“…While neural dynamics in monkey posterior parietal cortex show shifted initial states and non-aligned low-dimensional neural subspaces in the SE task, remapping is achieved in overlapping subspaces in the TR task. A recurrent neural network model demonstrates how output constraints mimicking SE and TR tasks are sufficient to generate the two fundamentally different neural computational dynamics. …”
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Application of deep learning for technological parameter optimization of laser shock peening of Ti-6Al-4V alloy by Mikhail Verezhak, Aleksei Vshivkov, Elena Gachegova, Maria Bartolomei, Alexander Mayer, Sathya Swaroop

“…The results of research on determination of the optimal configuration of the deep learning model showed that when using sinusoidal activation function of the neural network with 4 hidden layers and the number of neurons 10, the best level of accuracy in solving the problem is achieved. …”
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Breast Cancer Prediction Using the Affinity Propagation Clustering with Regard to the Weights of Variables by Sina Dami, Zeinab Hatamchuri

“…In addition, the Wilcoxon assumption test confirmed the superiority of the combined neural network compared to other methods.…”
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Application of Machine Learning in Multi-Directional Model to Follow Solar Energy Using Photo Sensor Matrix by P. Dhanalakshmi, V. Venkatesh, P. S. Ranjit, N. Hemalatha, S. Divyapriya, R. Sandhiya, Sumit Kushwaha, Asmita Marathe, Mekete Asmare Huluka

“…In this paper, we introduce a deep neural network (DNN) for forecasting the intra-day solar irradiance, photovoltaic PV plants, regardless of whether or not they have energy storage, can benefit from the work being done here. …”
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