Analysis and Verilog-A Modeling of Floating-Gate Transistors by Sayma Nowshin Chowdhury, Matthew Chen, Sahil Shah

“…Floating-gate transistors provide non-volatile analog storage in standard CMOS processes and are crucial in the development of reconfigurable Systems on Chips (SoCs), programmable analog structures, analog neural networks, and mixed-signal neuromorphic circuits. …”
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Image Quality Assessments by Leveraging Diverse Visual Tasks by Joonhee Lee, Dongwon Park, Se Young Chun

“…While recent advances in deep neural networks (DNNs) have sparked much research on IQA, with the hope for IQA to mimic humans effectively, there has been a lack of systematic and analytical research on understanding what factors humans prioritize during IQA. …”
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Directed Energy Deposition via Artificial Intelligence-Enabled Approaches by Utkarsh Chadha, Senthil Kumaran Selvaraj, Aakrit Sharma Lamsal, Yashwanth Maddini, Abhishek Krishna Ravinuthala, Bhawana Choudhary, Anirudh Mishra, Deepesh Padala, Shashank M, Vedang Lahoti, Addisalem Adefris, Dhanalakshmi S

“…Various AI techniques like neural networks, gradient boosted decision trees, support vector machines, and Gaussian process techniques can achieve the desired aim. …”
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Quality Control of Olive Oils Using Machine Learning and Electronic Nose by Emre Ordukaya, Bekir Karlik

“…Different machine learning classifiers such as Naïve Bayesian, K-Nearest Neighbors (k-NN), Linear Discriminate Analysis (LDA), Decision Tree, Artificial Neural Networks (ANN), and Support Vector Machine (SVM) were used. …”
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Prediction of Causative Genes in Inherited Retinal Disorders from Spectral-Domain Optical Coherence Tomography Utilizing Deep Learning Techniques by Yu Fujinami-Yokokawa, Nikolas Pontikos, Lizhu Yang, Kazushige Tsunoda, Kazutoshi Yoshitake, Takeshi Iwata, Hiroaki Miyata, Kaoru Fujinami, on behalf of Japan Eye Genetics Consortium

“…It is anticipated that deep neural networks will be integrated into general screening to support clinical/genetic diagnosis, as well as enrich the clinical education.…”
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Analysis and Recommendation of Outdoor Activities for Smart City Users Based on Real-Time Contextual Data by S. R. Mani Sekhar, D. M. Mushtaq Ahmed, G. M. Siddesh

“…Deep learning models, such as recurrent neural networks (RNNs) and convolutional neural networks (CNNs), are employed to analyze this data and predict real-time contextual information, including weather conditions, traffic patterns, and social events. …”
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Mapping knowledge landscapes and emerging trends in artificial intelligence for antimicrobial resistance: bibliometric and visualization analysis by Zhongli Wang, Zhongli Wang, Gaopei Zhu, Shixue Li, Shixue Li

“…Keyword analysis identified six enduring research clusters from 2014 to 2024: sepsis, artificial neural networks, antimicrobial resistance, antimicrobial peptides, drug repurposing, and molecular docking, demonstrating the sustained integration of AI in antimicrobial therapy development. …”
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Prescribed Performance Tracking Control for the Hypersonic Vehicle with Actuator Faults by Zhenghui Yang, Wentao He, Yushan He, Yaen Xie, Jun Li, Shuo Song

“…Simultaneously, radial basis function neural networks (RBFNNs) are adopted for approximating the unavailable dynamics, in which the minimum learning parameter (MLP) algorithm brilliantly alleviates the excessive occupation of the computational resource. …”
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Slot Parameter Optimization for Multiband Antenna Performance Improvement Using Intelligent Systems by Erdem Demircioglu, Ahmet Fazil Yagli, Senol Gulgonul, Haydar Ankishan, Emre Oner Tartan, Murat H. Sazli, Taha Imeci

“…The slot parameters on MMPA are modeled using soft computing technique of artificial neural networks (ANN). To achieve the best ANN performance, Particle Swarm Optimization (PSO) and Differential Evolution (DE) are applied with ANN’s conventional training algorithm in optimization of the modeling performance. …”
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Enhancing classification efficiency in capsule networks through windowed routing: tackling gradient vanishing, dynamic routing, and computational complexity challenges by Gangqi Chen, Zhaoyong Mao, Junge Shen, Dongdong Hou

“…Abstract Capsule networks overcome the two drawbacks of convolutional neural networks: weak rotated object recognition and poor spatial discrimination. …”
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The Recognition of Holy Qur’an Reciters Using the MFCCs’ Technique and Deep Learning by Ghassan Samara, Essam Al-Daoud, Nael Swerki, Dalia Alzu’bi

“…In this study, we propose a deep learning model using convolutional neural networks (CNNs) and a dataset consisting of seven well-known reciters. …”
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Utilization of Artificial Intelligence for the automated recognition of fine arts. by Ruhua Chen, Mohammad Reza Ghavidel Aghdam, Mohammad Khishe

“…This article introduces a novel AI-based approach for fine art recognition, utilizing Convolutional Neural Networks (CNNs) and advanced feature extraction techniques. …”
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Deep Blue Cannot Play Checkers: The Need for Generalized Intelligence for Mobile Robots by Troy D. Kelley, Lyle N. Long

“…This approach will require a system of systems approach that uses many AI techniques: neural networks, fuzzy logic, and cognitive architectures.…”
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Study of the Permanent Deformation of Soil Used in Flexible Pavement Design by Wendel S. Cabral, Suelly H. A. Barroso, Samuel A. Torquato

“…This is a study of the permanent deformation (PD) of soil used in pavement layers, obtaining prediction models through the technique of artificial neural networks, in addition to the design of pavement structures using mechanistic-empirical and empirical methods. …”
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Approximation-Based Fixed-Time Adaptive Tracking Control for a Class of Uncertain Nonlinear Pure-Feedback Systems by Cheng He, Jian Wu, Jiyang Dai, Zhe Zhang, Libin Xu, Pinwei Li

“…Radial basis function neural networks are introduced to approximate unknown functions for solving the fixed-time control problem of unknown nonlinear pure-feedback systems, and the mean value theorem is used to solve the problem of nonaffine structure in nonlinear pure-feedback systems. …”
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Graph attention, learning 2-opt algorithm for the traveling salesman problem by Jia Luo, Herui Heng, Geng Wu

“…Abstract In recent years, deep graph neural networks (GNNs) have been used as solvers or helper functions for the traveling salesman problem (TSP), but they are usually used as encoders to generate static node representations for downstream tasks and are incapable of obtaining the dynamic permutational information in completely updating solutions. …”
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Comparison of Machine Learning Algorithms for the Prediction of Mechanical Stress in Three-Phase Power Transformer Winding Conductors by Fausto Valencia, Hugo Arcos, Franklin Quilumba

“…This research compares four machine learning techniques: linear regression, support vector regression, random forests, and artificial neural networks, with regard to the determination of mechanical stress in power transformer winding conductors due to three-phase electrical faults. …”
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Deep and Reinforcement Learning Technologies on Internet of Vehicle (IoV) Applications: Current Issues and Future Trends by Lina Elmoiz Alatabani, Elmustafa Sayed Ali, Rania A. Mokhtar, Rashid A. Saeed, Hesham Alhumyani, Mohammad Kamrul Hasan

“…In this paper, some concepts related to deep learning networks will be discussed as one of the uses of machine learning in IoV systems, in addition to studying the effect of neural networks (NNs) and their types, as well as deep learning mechanisms that help in processing large amounts of unclassified data. …”
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Model pruning techniques in the Internet of things: state of the art, methods and perspectives by ZHAO Junhui, LI Huaicheng, WANG Dongming, LI Jiamin, ZHOU Yiqing, SHU Feng

“…Model pruning technology could effectively reduce computation and storage requirements by reducing redundant parameters in neural networks without impairing the performance of AI models. …”
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Optimization of VGG-16 Accuracy for Fingerprint Pattern Imager Classification by Agus Andreansyah, Julian Supardi

“…The dataset used in this study is FVC2000. Convolutional Neural Networks (CNN) were applied for fingerprint image enhancement and classification, focusing on patterns such as whorl, arch, radial loop, ulnar loop, and twinted loop. …”
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