Measurement-Based Neural Network Technique for Modeling the Low-Frequency Electric Field Radiated Behavior of Satellite Units by Anna N. Lampou, Anargyros T. Baklezos, Konstantinos K. Spyridakis, Dimitrios A. Rigas-Papakonstantinou, Ioannis O. Vardiambasis, Christos D. Nikolopoulos

“…The network uses the electric field vector, measured at 14 discrete locations, as input and reports the position and moment of the electric dipole that best matches the measured fields. …”
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Automatic Synthesis of Recurrent Neurons for Imitation Learning From CNC Machine Operators by Hoa Thi Nguyen, Roland Olsson, Oystein Haugen

“…AutoML approaches aim to automate this process, reducing human bias and improving accuracy and cost-effectiveness. …”
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MSJosSAR Configuration Optimization and Scattering Mechanism Classification Based on Multi-Dimensional Features of Attribute Scattering Centers by Shuo Liu, Fubo Zhang, Longyong Chen, Minan Shi, Tao Jiang, Yuhui Lei

“…The approach transforms the configuration optimization problem into a vector separability problem commonly addressed in machine learning. …”
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CPS-LSTM: Privacy-Sensitive Entity Adaptive Recognition Model for Power Systems by Hao Zhang, Jing Wang, Xuanyuan Wang, Xuhui Lü, Zhenzhi Guan, Zhenghua Cai, Hua Zhang

“…We then introduce CPS-LSTM (Character-level Privacy-sensitive Entity Adaptive Recognition Model), which enhances the recognition capability of privacy-sensitive entities in mixed Chinese and English text through character-level embedding and word vector fusion. The model features a streamlined architecture, accelerating convergence and enabling parallel sentence processing. …”
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Mobile Accelerometer Applications in Core Muscle Rehabilitation and Pre-Operative Assessment by Aleš Procházka, Daniel Martynek, Marie Vitujová, Daniela Janáková, Hana Charvátová, Oldřich Vyšata

“…The study employs a range of machine learning methods, including support vector machines, Bayesian analysis, and neural networks, to evaluate the balance of various physical activities. …”
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A Fast Power Market Clearing Method Based on Active Constraints Identification by Deep Learning by Yunliang WU, Jianxin ZHANG, Bao LI, Peng LI, Zhiyong LI, Xin ZHOU, Yan YANG, Xiaowen LAI

“…Secondly, a deep learning strategy is proposed for identification of active constraint sets, which can provide technical support for deep neural networks to effectively identify the active constraints of SCED from two aspects: feature vector design and efficient processing of the results of deep neural network. …”
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Continuous prediction of human knee joint angle using a sparrow search algorithm optimized random forest model based on sEMG signals by Liuyi Ling, Zhu Lin, Bin Feng, Liyu Wei, Li Jin, Yiwen Wang

“…The performance of the proposed model was compared with those of traditional backpropagation neural network, support vector machine regression, and random forest models. …”
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A Novel Adaptive Cuboid Regional Growth Algorithm for Trunk–Branch Segmentation of Point Clouds from Two Fruit Tree Species by Yuheng Cao, Ning Wang, Bin Wu, Xin Zhang, Yaxiong Wang, Shuting Xu, Man Zhang, Yanlong Miao, Feng Kang

“…This method integrates a growth vector that is adaptively adjusted based on the growth trend of branches and a growth cuboid that is dynamically regulated according to branch diameters. …”
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Soil Organic Carbon Prediction and Mapping in Morocco Using PRISMA Hyperspectral Imagery and Meta-Learner Model by Yassine Bouslihim, Abdelkrim Bouasria, Budiman Minasny, Fabio Castaldi, Andree Mentho Nenkam, Ali El Battay, Abdelghani Chehbouni

“…The first layer consists of Random Forest (RF), Support Vector Regression (SVR), and Partial Least Squares Regression (PLSR). …”
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An Iterative Pixel-Based Dimensional Voting Model for High Spatial-Resolution Image Classification by Muhamad Asyraf Mohd Pouzi, Haza Nuzly Abdull Hamed, Muhammad Razib Othman, Hishammuddin Asmuni, Mohd Adham Isa, Husni Ruslai

“…Pixel-DMV outperformed conventional methods, including Support Vector Machine (SVM), Random Forest (RF), and Maximum Likelihood (ML) classifications. …”
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An Integrated Learning Approach for Municipal Solid Waste Classification by Hieu M. Sondao, Tuan M. Le, Hung V. Pham, Minh T. Vu, Son Vu Truong Dao

“…These selected features are then fed into machine learning classifiers—Support Vector Machine (SVM), Random Forest (RF), Logistic Regression (LR), and K-Nearest Neighbor (KNN)—for final predictions. …”
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A CGAN-based adversarial attack method for data-driven state estimation by Qi Wang, Jing Zhang, Jianxiong Hu, Shutan Wu, Shiyi Hou, Yi Tang

“…Therefore, to reveal the security threats of adversarial attacks, a conditional generative adversarial network (CGAN) is innovatively adapted to the attack vector generation scenario of the power system in this paper. …”
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Viral and Viroid Communities in Peach Cultivars Grown in Bulgaria by Mariyana Gozmanova, Vesselin Baev, Rumyana Valkova, Elena Apostolova-Kuzova, Stoyanka Jurac, Galina Yahubyan, Lilyana Nacheva, Snezhana Milusheva

“…Climate change may alter vector populations and lead to shifts in agricultural practices, influencing the spread of these viruses and viroids. …”
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High expression of long non-coding RNA ZEB1-AS1 promotes colorectal cancer cell proliferation partially by suppressing p15 expression by Huangbo Gong, Hao Wen, Xuhui Zhu, Yifan Lian, Xiaojun Yang, Zhuyin Qian, Jin Zhu

“…Subsequently, small interfering RNA or lentivirus vector–mediated lncRNA ZEB1-AS1 was transfected into colorectal cancer cell lines. …”
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IoT-MFaceNet: Internet-of-Things-Based Face Recognition Using MobileNetV2 and FaceNet Deep-Learning Implementations on a Raspberry Pi-400 by Ahmad Saeed Mohammad, Thoalfeqar G. Jarullah, Musab T. S. Al-Kaltakchi, Jabir Alshehabi Al-Ani, Somdip Dey

“…Additionally, an in-house database is compiled, capturing data from 50 individuals via a web camera and 10 subjects through a smartphone camera. Pre-processing of the in-house database involves face detection using OpenCV’s Haar Cascade, Dlib’s CNN Face Detector, and Mediapipe’s Face. …”
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Active learning based surrogate ensemble assisted multi-objective optimization framework for reservoir water-flooding optimization by Lian Wang, Liang Zhang, Rui Deng, Jianhua Qu, Hehua Wang, Liehui Zhang, Xing Zhao, Bing Xu, Xindong Lv, Caspar Daniel Adenutsi

“…In this proposed ALSA-MOPO method, three frequently-used surrogate models, the radial basis function network, Gaussian process regression, and support vector regression are adopted to construct the surrogate ensemble. …”
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Advanced long-term actual evapotranspiration estimation in humid climates for 1958–2021 based on machine learning models enhanced by the RReliefF algorithm by Ahmed Elbeltagi, Salim Heddam, Okan Mert Katipoğlu, Abdullah A. Alsumaiei, Mustafa Al-Mukhtar

“…AET was estimated using support vector machine (SVM), ensemble bagged and boosted trees, robust linear regression (RLR), and Matern 5/2 Gaussian process regression (M-GPR) models. …”
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Evaluation of machine learning-based regression techniques for prediction of diabetes levels fluctuations by Badriah Alkalifah, Muhammad Tariq Shaheen, Johrah Alotibi, Tahani Alsubait, Hosam Alhakami

“…To support this an Artificial Neural Network (ANN), Binary Decision Tree (BDT), Linear Regression (LR), Boosting Regression Tree Ensemble (BSTE), Linear Regression with Stochastic Gradient Descent (LRSGD), Stepwise (SW), Support Vector Machine (SVM), and Gaussian process regression (GPR) were investigated. …”
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Butterfly magnetoreception based neighbour awareness strategy protocol for autonomous aerial vehicles by Janjhyam Venkata Naga Ramesh, C. Dastagiraiah, Suraya Mubeen, W. Deva Priya, M. Kameswara Rao, B. H. K. Bhagat Kumar

“…Key navigation parameters, including orientation angle (θ), heading angle (α), and velocity vector (V), are used to achieve precise and adaptive control. …”
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Axial Capacity Estimation of FRP-strengthened Corroded Concrete Columns by Chandan Gupta, Harish Arora, Aman Kumar, Prashant Kumar, Nishant Raj Kapoor, Madhu Sharma

“…Considering the scarcity of reliable design guidelines for estimating the axial strength of RC columns considering corrosion effects, artificial neural network (ANN), Gaussian process regression (GPR), and support vector machine (SVM) techniques were employed. …”
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