Application of Artificial Intelligence Techniques for the Control of the Asynchronous Machine by F. Khammar, N. E. Debbache

“…While the criteria for response time, overtaking, and static error can be assured by the techniques of conventional control, the criterion of robustness remains a challenge for researchers. …”
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Methods to quantify soft-tissue based facial growth and treatment outcomes in children: a systematic review. by Sander Brons, Machteld E van Beusichem, Ewald M Bronkhorst, Jos Draaisma, Stefaan J Bergé, Thomas J Maal, Anne Marie Kuijpers-Jagtman

“…<h4>Context</h4>Technological advancements have led craniofacial researchers and clinicians into the era of three-dimensional digital imaging for quantitative evaluation of craniofacial growth and treatment outcomes.…”
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Water-responsive shape memory hybrid: Design concept and demonstration

“…Even for professionals, like materials researchers, it could involve tedious trial and error procedures. …”
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Three-dimensional positioning system using Bluetooth low-energy beacons by Hyunwook Park, Jaewon Noh, Sunghyun Cho

“…It allows devices to receive information over a short distance. Thus, many researchers are actively investigating positioning methods that use beacons. …”
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BER Performance for Downlink NOMA by Tabarek Hussein, Ismael Sharhan Haburi

“…As a result, academic and industry researchers have recently looked into the error performance and capacity of NOMA schemes. …”
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Approximate Time-Fractional Differential Equations by Saber Tavan, Mohammad Jahangiri Rad, Ali Salimi Shamloo, Yaghoub Mahmoudi

“…The convergence analysis and the error estimate of the proposed method are also provided. …”
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INDONESIAN EFL STUDENTS’ WRITING CHALLENGES: A QUALITATIVE META-ANALYSIS by Muhammad Hasan Hamdani, Nuskhan Abid

“…The results of keyword searches found articles totalling (n=6.791). Then, the researcher was identified based on the title and abstract, and screening through inclusion and exclusion criteria was conducted by the researchers. …”
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CRISP: correlation-refined image segmentation process by Jennifer K. Briggs, Erli Jin, Matthew J. Merrins, Richard K. P. Benninger

“…To assess the activity of individual cells, researchers must segment images into the individual cells. …”
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Understanding forest insect outbreak dynamics: a comparative analysis of machine learning techniques by Roberto Molowny-Horas, Saeed Harati-Asl, Liliana Perez

“…By employing advanced modeling techniques, researchers and managers can anticipate the evolving dynamics of forest ecosystems, thereby facilitating timely interventions and sustainable management practices. …”
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Hybrid Grey–Fuzzy Approach for Optimizing Circular Quality Responses in Plasma Jet Manufacturing of Aluminum Alloy by Ivan Peko, Boris Crnokić, Jelena Čulić-Viskota, Tomislav Matić

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Comparative Study of Machine Learning Techniques for Predicting UCS Values Using Basic Soil Index Parameters in Pavement Construction by Mudhaffer Alqudah, Haitham Saleh, Hakan Yasarer, Ahmed Al-Ostaz, Yacoub Najjar

“…The results indicate that the ANN-based model provided the most accurate predictions for UCS, achieving an R² of 0.83, a root-mean-squared error (RMSE) of 1.11, and a mean absolute relative error (MARE) of 0.42. …”
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Neural network decoding of the block Markov superposition transmission by Qianfan WANG, Sheng BI, Zengzhe CHEN, Li CHEN, Xiao MA

“…A neural network (NN)-based decoding algorithm of block Markov superposition transmission (BMST) was researched.The decoders of the basic code with different network structures and representations of training data were implemented using NN.Integrating the NN-based decoder of the basic code in an iterative manner,a sliding window decoding algorithm was presented.To analyze the bit error rate (BER) performance,the genie-aided (GA) lower bounds were presented.The NN-based decoding algorithm of the BMST provides a possible way to apply NN to decode long codes.That means the part of the conventional decoder could be replaced by the NN.Numerical results show that the NN-based decoder of basic code can achieve the BER performance of the maximum likelihood (ML) decoder.For the BMST codes,BER performance of the NN-based decoding algorithm matches well with the GA lower bound and exhibits an extra coding gain.…”
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An enhanced deep learning-based feature extraction framework for moving object detection by Upasana Panigrahi, Prabodh Kumar Sahoo, Manoj Kumar Panda, Aswini Kumar Samantaray, Ganapati Panda

“…Various methods across the globe are developed by the researcher for change detection. However, most current methods require improvement in the challenging datasets. …”
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Practical Introduction to Benchmarking and Characterization of Quantum Computers by Akel Hashim, Long B. Nguyen, Noah Goss, Brian Marinelli, Ravi K. Naik, Trevor Chistolini, Jordan Hines, J.P. Marceaux, Yosep Kim, Pranav Gokhale, Teague Tomesh, Senrui Chen, Liang Jiang, Samuele Ferracin, Kenneth Rudinger, Timothy Proctor, Kevin C. Young, Irfan Siddiqi, Robin Blume-Kohout

“…Breakthroughs in quantum algorithms, quantum simulations, and quantum error correction are bringing useful quantum computation closer to fruition. …”
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Field Deviation in Radiated Emission Measurement in Anechoic Chamber for Frequencies up to 60 GHz and Deep Learning-Based Correction by Feng Shi, Liping Yan, Xuping Yang, Xiang Zhao, Richard Xian-Ke Gao

“…The results indicate that the correction is reliable, with an average error of 6.35% for a 3 m distance in a semianechoic chamber and less than 4.83% for other test scenarios. …”
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A Modified Grey Wolf Algorithm with Applications to Engineering by Vahid Mahboub

“…But the problem that can be mentioned about it is that the decreasing factor used in it is linear and in some non-linear problems, it may cause more error or late convergence to the original solution. …”
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Results for Chaos Synchronization with New Multi-Fractional Order of Neural Networks by Multi-Time Delay by Fatin Nabila Abd Latiff, Wan Ainun Mior Othman

“…In comparison, the fractional-order Lyapunov direct method (FLDM) is proposed and is implemented to SMC to maintain the systems’ sturdiness and assure the global convergence of the error dynamics. An extensive literature survey has been conducted, and we found that many researchers focus only on fractional order of neural networks (FNNs) without delay in different systems. …”
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Validation of a portable three-dimensional imaging system for volumetric measurement in the periorbital region by Xuan Zhang, Ji Shao, Ningxin Dai, Huimin Li, Yongwei Guo, Juan Ye, Lixia Lou

“…Intra-device, intra-rater and inter-rater reliabilities and accuracy of the volumetric measurement were evaluated by intraclass correlation coefficient (ICC), mean absolute difference (MAD), technical error of measurement (TEM), relative error measurement (REM), and relative TEM (rTEM).ResultsThe intra-device reliability of the 3D imaging system for volumetric measurement in the periorbital region was excellent (ICC = 0.922, MAD = 0.11 mm3, TEM = 0.09 mm3, REM = 0.19%, rTEM = 0.15%). …”
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A Novel Electrical Load Forecasting Model for Extreme Weather Events Based on Improved Gated Spiking Neural P Systems and Frequency Enhanced Channel Attention Mechanism by Yuanshuo Guo, Jun Wang, Yan Zhong, Tao Wang, Zeyuan Sui

“…This paper proposes a basic framework for future load forecasting researches of sustainable energy systems under extreme weather events and provides new direction for membrane computing model in terms of load forecasting. …”
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The ubiquity of selective attention in the processing of feedback during category learning. by Katerina Dolguikh, Tyrus Tracey, Mark R Blair

“…We discuss the implications of our findings for modelling efforts in category learning from the perspective of researchers trying to capture the full dynamic interaction of selective attention and learning, as well as for researchers focused on other issues, such as category representation, whose work only requires simplifications that do a reasonable job of capturing learning.…”
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