Optimized Machine Learning-Augmented Hybrid Empirical Models for AlGaN/GaN HEMTs: A Comprehensive Analysis by Ahmad Khusro, Saddam Husain, Mohammad Hashmi

“…Thereafter, six extensively optimized ML regression models, namely decision tree (DT), ensemble learning (EL), support vector regression (SVR), kernel approximation regression (KAR), Gaussian process regression (GPR), and neural networks (NN) are employed to simulate the intrinsic behavior of GaN HEMTs. …”
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Prediction of Key Quality Parameters in Hot Air-Dried Jujubes Based on Hyperspectral Imaging by Quancheng Liu, Chunzhan Yu, Yuxuan Ma, Hongwei Zhang, Lei Yan, Shuxiang Fan

“…This study provides important insights into the further application of HSI technology in the quality monitoring and optimization of the jujube drying process.…”
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STATIC OF ORTHODONTIC APPLIANCES WITH MOVABLE INCLINED PLANE FOR MESIAL BATE TREATMENT by P.S. Flis, A.I. Hryhorenko, N.M. Doroshenko, M.M. Tormakhov, V.V. Filonenko

“…Since the orthodontic force vector is in vestibular direction, the angle β is in the range from -30° to α. …”
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Integrating AI predictive analytics with naturopathic and yoga-based interventions in a data-driven preventive model to improve maternal mental health and pregnancy outcomes by Neha Irfan, Sherin Zafar, Kashish Ara Shakil, Mudasir Ahmad Wani, S. N. Kumar, A. Jaiganesh, K. M. Abubeker

“…Additionally, a custom loss function integrating Cross-Entropy Loss and an F1 Score Penalty was introduced to address class imbalance and enhance model performance. The training process, conducted over 10 epochs, demonstrated consistent loss reduction, with the lowest recorded loss at epoch 8 (2.4382), reflecting effective learning and parameter tuning. …”
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机器学习算法在食用植物油掺伪鉴别中应用的 研究进展Research progress on application of machine learning algorithms in adulteration identification of edible vegetable oils... by 吕壮，黄金，兰梓溶，代婷玉，许宙，陈茂龙，焦叶，文李，程云辉，丁利 LYU Zhuang, HUANG Jin, LAN Zirong, DAI Tingyu, XU Zhou, CHEN Maolong, JIAO Ye, WEN Li, CHENG Yunhui, DING Li

“…In order to provide a theoretical basis for the selection of algorithms in the adulteration identification of edible vegetable oils, the classification of machine learning algorithms and their application process in the adulteration identification of edible vegetable oils were briefly introduced. …”
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Predicting distant metastasis of bladder cancer using multiple machine learning models: a study based on the SEER database with external validation by Xin Chang Zou, Xue Peng Rao, Jian Biao Huang, Jie Zhou, Hai Chao Chao, Tao Zeng

“…After a rigorous screening process, a total of 4,108 patients were selected for further analysis, divided in a 7:3 ratio into a training cohort and an internal validation cohort. …”
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Identification and validation of endoplasmic reticulum autophagy-related potential biomarkers in periodontitis by Ruyue Wang, Jinyue Hu, Qing Sun, Shuixiang Guo, Gege Zhang, Ao Lu, Shuo Liu, Xue Yang, Lina Wang

“…Random forest, least absolute shrinkage and selection operator (LASSO) and support vector machine-recursive feature removal (SVM-RFE) algorithms were used to identify hub genes. …”
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Coupled intelligent prediction model for medium- to long-term runoff based on teleconnection factors selection and spatial-temporal analysis. by Jintao Li, Ping Ai, Chuansheng Xiong, Yanhong Song

“…However, runoff formation is a complex process influenced by various natural and anthropogenic factors, resulting in nonlinearity, nonstationarity, and long prediction periods, which complicate forecasting efforts. …”
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Regression Methods for Ophthalmic Glucose Sensing Using Metamaterials by Philipp Rapp, Martin Mesch, Harald Giessen, Cristina Tarín

“…In detail, we use the plasmonic analogue of electromagnetically induced transparency (EIT) as sensor and evaluate the acquired data with support vector machines. The metamaterial can be integrated into a contact lens. …”
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Robust STAP for MIMO Radar Based on Direct Data Domain Approach by Cheng Chen, Junjie He, Zeshi Yuan, Xiaohua Zhu, Hongtao Li

“…The detection performance of direct data domain (D3) space-time adaptive processing (STAP) will be extremely degraded when there are mismatches between the actual and the presumed signal steering vectors. …”
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VNA in MF, HF and VHF bands by Brian Maximiliano Gluzman, Ramiro Avalos Ribas, Alejandro José Uriz, Juan Alberto Etcheverry, Leonardo David Vazquez, Jorge Castiñeira Moreira

“…This paper proposes the design and implementation of a vector network analyzer for frequencies up to 300 MHz. …”
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Fatigue Detection of Air Traffic Controllers Through Their Eye Movements by Yi Hu, Haoran Shen, Hui Pan, Wenbin Wei

“…By observing eye movements among various individuals and environments, researchers have discovered correlations with multiple physiological metrics and cognitive processing abilities. This study involved human-in-the-loop simulations to collect eye movement and fatigue data from air traffic controllers and students. …”
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Machine learning‐guided plasticity model in refractory high‐entropy alloys by Shang Zhao, Jinshan Li, Weijie Liao, Ruihao Yuan

“…However, their limited plasticity at room temperature restricts their deformability, posing challenges for processing and industrial implementation. Traditional experimental methods for characterizing this property are time‐consuming and resource‐intensive, necessitating the development of efficient predictive models. …”
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A comparative study of wavelet families for schizophrenia detection by E. Sathiya, T. D. Rao, T. Sunil Kumar

“…The electroencephalogram (EEG) signals are processed using DWT, which decomposes them into multiple frequency bands, yielding approximation and detail coefficients at each level. …”
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A Machine Learning Approach to Credit Card Transaction Fraud Prediction by Liu Zixuan

“…By conducting data processing techniques such as feature scaling and dataset balancing, the model shows an effective identification of fraudulent transactions that rarely exist in a vast number of legitimate transactions. …”
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Providing Surround Sound with Loudspeakers: A Synopsis of Current Methods by Jens BLAUERT, Rudolf RABENSTEIN

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Ni-Doped Cu10%/YIG Nanoparticle-Based Metamaterials: Synthesis and Electromagnetic Property Investigation at Terahertz Frequencies by Ali Bahari, Fatemeh Delkhosh, Reza Gholipur

“…UV spectroscopy verified that the electronic structure and optical properties of the samples matched predicted characteristics Measurements of dielectric permittivity and magnetic permeability were conducted at room temperature using scattering parameters from a Vector Network Analyzer (VNA) and processed through MATLAB software. …”
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Predicting per capita expenditure using satellite imagery and transfer learning: A case study of east Java province, Indonesia by Heri Kuswanto, Wahidatul Wardah Al Maulidiyah, Widhianingsih Tintrim Dwi Ary, Yudistira Ashadi

“…The satellite images are processed using a transfer learning approach that employs a pretrained Convolutional Neural Network (CNN) model with VGG-16 architecture as a feature extractor. …”
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DDoS attack detection and defense based on hybrid deep learning model in SDN by Chuanhuang LI, Yan WU, Zhengzhe QIAN, Zhengjun SUN, Weiming WANG

“…Software defined network (SDN) is a new kind of network technology,and the security problems are the hot topics in SDN field,such as SDN control channel security,forged service deployment and external distributed denial of service (DDoS) attacks.Aiming at DDoS attack problem of security in SDN,a DDoS attack detection method called DCNN-DSAE based on deep learning hybrid model in SDN was proposed.In this method,when a deep learning model was constructed,the input feature included 21 different types of fields extracted from the data plane and 5 extra self-designed features of distinguishing flow types.The experimental results show that the method has high accuracy,it’s better than the traditional support vector machine (SVM) and deep neural network (DNN) and other machine learning methods.At the same time,the proposed method can also shorten the processing time of classification detection.The detection model is deployed in SDN controller,and the new security policy is sent to the OpenFlow switch to achieve the defense against specific DDoS attack.…”
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Effects of a Complex Feed Additive on Productivity and Blood Parameters of Laying Hens Using Stochastic Fractal-based Neural Network Model by Larisa Karpenko, Alesya Bakhta, Olga Babich, Stanislav Sukhikh, Nikolay Vorobyov, Ilya Nikonov, Solomonida Borisova, Darren Griffin, Michael Romanov

“…Further, EuclidNN computed the respective bioconsolidation indices of hens and, simultaneously, processed several profiles of OTUs for all experimental variants. …”
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