Exploration of Machine Learning Models for Prediction of Gene Electrotransfer Treatment Outcomes by Alex Otten, Michael Francis, Anna Bulysheva

“…Tissue heterogeneity complicates the delivery process, requiring the extensive optimization of pulsing protocols currently empirically optimized. …”
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Analyzing the influence of manufactured sand and fly ash on concrete strength through experimental and machine learning methods by S Sathvik, Solomon Oyebisi, Rakesh Kumar, Pshtiwan Shakor, Olutosin Adejonwo, Adithya Tantri, V Suma

“…Furthermore, machine learning (ML) techniques were engaged to predict the compressive strength of the concrete samples using Extreme Gradient Boosting (XGBoost), Long Short-Term Memory (LSTM), Support Vector Machine (SVM), and Gaussian Process Regression (GPR). …”
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Research on the characteristics of the Maerkang MS6.0 earthquake based on the joint analysis of annual changes in gravity and magnetic fields by Dong Liu, Yufei Zhao, Yong Zhang, Jiangpei Huang, Yuqin Wu

“…The annual variation of the lithospheric magnetic field revealed that the horizontal vector of the magnetic field weakened overall before the earthquake, with the epicentral region continuing to weaken and the periphery converging, followed by a reverse weakening. …”
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An Assist-as-Needed Control Strategy Based on a Subjective Intention Decline Model by Hao Yan, Fangcao Zhang, Xingao Li, Chenchen Zhang, Yunjia Zhang, Yongfei Feng

“…In the rehabilitation training process for stroke patients, the level of excitement in the patient’s physiological state has a positive impact on the efficacy of the training. …”
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Analysis of Surface Roughness and Machine Learning-Based Modeling in Dry Turning of Super Duplex Stainless Steel Using Textured Tools by Shailendra Pawanr, Kapil Gupta

“…Two models, Least-Squares Support Vector Machine (LSSVM) and Multi-Gene Genetic Programming (MGGP), were trained and evaluated on various statistical metrics. …”
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Prmt1-mediated histone H4R3me2a methylation regulates the proliferation, migration and invasion of laryngeal cancer cells by affecting the expression level of NCOA5 by Linlu Li, Jiao Cui, Xiaoyu Li, Yuting Zhu, Hongfei Wu, Lanzhu Zhou

“…The present study aimed to investigate how PRMT1-mediated H4R3me2a methylation affects the proliferation, migration and invasion of laryngeal cancer cells and to verify the role of NCOA5 in this process.MethodsThe expression of PRMT1 and NCOA5 was inhibited by siRNA mediated gene knockdown in laryngeal cancer cells. …”
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Ferritin1-mediated ferroptosis participates in granular acini degeneration of Haemaphysalis longicornis salivary glands by Dongqi Yuan, Songqin Chen, Yongzhi Zhou, Jie Cao, Houshuang Zhang, Yanan Wang, Jinlin Zhou

“…Our findings are important for developing novel preventive measures against H. longicornis as a disease vector.…”
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Research on Reservoir Identification of Gas Hydrates with Well Logging Data Based on Machine Learning in Marine Areas: A Case Study from IODP Expedition 311 by Xudong Hu, Wangfeng Leng, Kun Xiao, Guo Song, Yiming Wei, Changchun Zou

“…This article selects six ML methods, including Gaussian process classification (GPC), support vector machine (SVM), multilayer perceptron (MLP), random forest (RF), extreme gradient boosting (XGBoost), and logistic regression (LR). …”
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Copy-Move Forgery Detection Technique Using Graph Convolutional Networks Feature Extraction by Varun Shinde, Vineet Dhanawat, Ahmad Almogren, Anjanava Biswas, Muhammad Bilal, Rizwan Ali Naqvi, Ateeq Ur Rehman

“…The aim to use GCN is due to its ability to improve the feature extraction process by utilizing the spatial and structural affiliation between elements in the digital images. …”
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A comparative performance analysis of machine learning models for compressive strength prediction in fly ash-based geopolymers concrete using reference data by Muhammad Kashif Anwar, Muhammad Ahmed Qurashi, Xingyi Zhu, Syyed Adnan Raheel Shah, Muhammad Usman Siddiq

“…This study will have made attempt to address the complexities involves in the concrete mix designs process with the aim of achieving the desired 28-day compressive strength for FAGP. …”
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Land-cover classification in Addo Elephant National Park: Analyzing the impact of variables, classifiers, and object-based approach by Mohammad Safaei, Jane Southworth, Cerian Gibbes, Hannah V. Herrero, Mashoukur Rahaman, Bewuket B. Tefera, Jason K. Blackburn

“…Two machine learning (ML) techniques, Random Forest (RF) and Support Vector Machines (SVM), were compared with a deep learning (DL) technique, UNet++. …”
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Stomatal State Identification and Classification in Quinoa Microscopic Imprints through Deep Learning by Abdul Razzaq, Sharaiz Shahid, Muhammad Akram, Muhammad Ashraf, Shahid Iqbal, Aamir Hussain, M. Azam Zia, Sulman Qadri, Najia Saher, Faisal Shahzad, Ali Nawaz Shah, Aziz-ur Rehman, Sven-Erik Jacobsen

“…Stomata are the main medium of plants for the trade of water, regulate the gas exchange, and are responsible for the process of photosynthesis and transpiration. The stomata are surrounded by guard cells, which help to control the rate of transpiration by opening and closing the stomata. …”
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Enhancing Healthcare With WBAN and Digital Twins: A Machine Learning Approach for Predictive Health Monitoring by Rishit Mahapatra, Deepak Sethi, Kaushik Mishra

“…The collected data undergoes processing and is then sent to a remote medical server over the Internet. …”
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Emotion Recognition in a Closed-Cabin Environment: An Exploratory Study Using Millimeter-Wave Radar and Respiration Signals by Hanyu Wang, Dengkai Chen, Sen Gu, Yao Zhou, Jianghao Xiao, Yiwei Sun, Jianhua Sun, Yuexin Huang, Xian Zhang, Hao Fan

“…An automatic sparse encoder was used to extract features from respiration signals, and two support vector machines were employed for emotion classification. …”
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A Comparative Study of Machine Learning Models for Accurate E-Waste Prediction by Mohammed Algafri, Mohammed Sayad, Mohammad A.M. Abdel-Aal, Ahmed M. Attia

“…This study evaluates six Machine Learning (ML) models, Linear Regression, Regression Tree, Support Vector Regression, Ensemble Regression, Gaussian Process Regression (GPR), and Artificial Neural Networks, for e-waste forecasting. …”
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Evaluation of the cold island effect of the urban parks in the main urban area of Wuhan from the perspective of supply and demand by Jufang Song, Yongxuan Qiao, Yihan Liu

“…Among these, the urban heat island effect has emerged as one of the most pronounced environmental concerns, presenting formidable challenges for urban planning in terms of sustainable development and environmental livability. In this process, the construction of urban parks is particularly susceptible to discrepancies between supply and demand.MethodsIn this study, urban parks with an area of more than 3hm2 in the main urban area of Wuhan were selected as research objects. …”
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A Hybrid Three-Staged, Short-Term Wind-Power Prediction Method Based on SDAE-SVR Deep Learning and BA Optimization by Ruiqin Duan, Xiaosheng Peng, Cong Li, Zimin Yang, Yan Jiang, Xiufeng Li, Shuangquan Liu

“…In order to improve the prediction accuracy of WPP, in this paper we propose a three-step model named SDAE-SVR-BA to be applied in short-term WPP based on stacked-denoising-autoencoder (SDAE) feature processing, bat algorithm (BA) optimization and support vector regression (SVR). …”
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An efficient retrieval method on Google Earth Engine and comparison with hybrid methods: a case study of leaf area index retrieval by Sijia Li, Zhiguang Tang, Kaisen Ma, Zhenyi Wang, Wenjuan Li

“…The performances of LUT and hybrid methods, including random forest (RF), gradient boosting regression tree (GBRT), classification and regression tree (CART), support vector regression (SVR), and Gaussian process regression (GPR), were evaluated on GEE by simulation experiments. …”
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Comparative analysis of visible and near-infrared (Vis-NIR) spectroscopy and prediction of moisture ratio using machine learning algorithms for jujube dried under different conditi... by Seda Günaydın, Necati Çetin, Cevdet Sağlam, Kamil Sacilik, Ahmad Jahanbakhshi

“…Also, the MR was predicted by the MC, and the drying rate (DR), drying times, and final thickness were predicted using the multi-layer perceptron (MLP), gaussian process (GP), k-nearest neighbors (KNN), random forest (RF), and support vector regression (SVR) algorithms. …”
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Design and Linearization of a Doherty Power Amplifier in 45 nm CMOS Technology for 5G Applications by Alexandre Zem de Morais, André Augusto Mariano, Eduardo Gonçalves de Lima, Luis Schuartz, Bernardo Rego Barros de Almeida Leite

“…DPD is applied to comply with error vector magnitude (EVM) standards for a 5G NR modulated signal. …”
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