System of polarization autofluorescence diagnostics of biological layers with fuzzy logic of decision support by N.I. Zabolotna, V.V. Sholota

“…Further statistical processing of the measured distributions, which is carried out in an improved system of laser polarization autofluorescence diagnostics, allows you to form a vector of informative features from estimates of their averages, dispersion, asymmetry and kurtosis, formed at each of the three specified wavelengths. …”
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Spatiotemporal variable and parameter selection using sparse hybrid genetic algorithm for traffic flow forecasting by Xiaobo Chen, Zhongjie Wei, Xiang Liu, Yingfeng Cai, Zuoyong Li, Feng Zhao

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Fast Backpropagation Neural Network for VQ-Image Compression by Basil Mahmood, Omaima AL-Allaf

“…Artificial neural networks are becoming very attractive in image processing where high computational performance and parallel architectures are required.…”
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Optimization of Noise Transfer Path Based on the Composite Panel Acoustic and Modal Contribution Analysis by Qiang Liu, Xuanyi Zhou, Jianxin Zhu, Xiaoping Gong

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Dynamic overmodulation strategy based on torque and flux optimal tracking for DTC‐SVM of surface‐mounted PMSM drives by Peihe Li, Anwen Shen, Qipeng Tang, Xin Luo, Jinbang Xu

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An alternative approach to detect Trypanosoma in Glossina (Diptera, Glossinidae) without dissection by Filipa Ferreira, Jorge Cano, Andreia Furtado, Nicolas Ndong-Mabale, Pedro Ndong-Asumu, Agustin Benito, João Pinto, Maria Odete Afonso, Jorge Seixas, Jorge Atouguia, Sónia Centeno-Lima

“…The method allows an effective processing of a large number of field captured tsetse in a central laboratory.…”
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Convolutional Neural Networks for Automatic Identification of Individuals at Terrestrial Terminals by Darwin Yarango-Farro, Alex Mondragon-Fernandez, Heber I. Mejia-Cabrera, Juan Arcila-Diaz

“…In FAISS, the embeddings were stored in vector format to facilitate fast and efficient querying. …”
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Modeling and prediction of tribological properties of copper/aluminum-graphite self-lubricating composites using machine learning algorithms by Huifeng Ning, Faqiang Chen, Yunfeng Su, Hongbin Li, Hengzhong Fan, Junjie Song, Yongsheng Zhang, Litian Hu

“…Correlation of friction coefficients and wear rates of copper/aluminum-graphite (Cu/Al-graphite) self-lubricating composites with their inherent material properties (composition, lubricant content, particle size, processing process, and interfacial bonding strength) and the variables related to the testing method (normal load, sliding speed, and sliding distance) were analyzed using traditional approaches, followed by modeling and prediction of tribological properties through five different ML algorithms, namely support vector machine (SVM), K-Nearest neighbor (KNN), random forest (RF), eXtreme gradient boosting (XGBoost), and least-squares boosting (LSBoost), based on the tribology experimental data. …”
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On the Use of Azimuth Cutoff for Sea Surface Wind Speed Retrieval From SAR by Yuting Zhu, Giuseppe Grieco, Jiarong Lin, Marcos Portabella, Xiaoqing Wang

“…The methodology probabilistically combines SAR data with ancillary meteorological information and optimizes the retrieval process through a cost function that leverages the sensitivity of the azimuth cutoff to changes in wind vector fields. …”
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Machine learning aided UV absorbance spectroscopy for microbial contamination in cell therapy products by Shruthi Pandi Chelvam, Alice Jie Ying Ng, Jiayi Huang, Elizabeth Lee, Maciej Baranski, Derrick Yong, Rohan B. H. Williams, Stacy L. Springs, Rajeev J. Ram

“…Abstract We demonstrate the feasibility of machine-learning aided UV absorbance spectroscopy for in-process microbial contamination detection during cell therapy product (CTP) manufacturing. …”
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Optimal design of high‐performance rare‐earth‐free wrought magnesium alloys using machine learning by Shaojie Li, Zaixing Dong, Jianfeng Jin, Hucheng Pan, Zongqing Hu, Rui Hou, Gaowu Qin

“…The ML algorithms, including support vector machine regression (SVR), artificial neural network, and other three methods, are employed, and the SVR has the best performance in predicting mechanical properties based on the components, and process parameters, with the mean absolute percentage error of YS, UTS, and EL being 6.34%, 4.19%, and 13.64% in the test set, respectively. …”
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Grape vine (Vitis vinifera) yield prediction using optimized weighted ensemble machine learning approach by Nobin Chandra Paul, Pratapsingh S. Khapte, Navyasree Ponnaganti, Sushil S. Changan, Sangram B. Chavan, K. Ravi Kumar, Dhananjay D. Nangare, K. Sammi Reddy

“…A diverse set of machine learning (ML) models, including Random Forest (RF), Artificial Neural Network (ANN), Extreme Gradient Boosting (XgBoost), Support Vector Regression (SVR), Gaussian Process Regression (GPR), Cubist and Multivariate Adaptive Regression Splines (MARS), were employed to model the grapevine yield. …”
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Vulnerability-Based Economic Loss Rate Assessment of a Frame Structure Under Stochastic Sequence Ground Motions by Zheng Zhang, Yunmu Jiang, Zixin Liu

“…A coherence function model is further developed from real seismic records, treating the mainshock–aftershock pair as a vector-valued stochastic process and thus enabling a more accurate representation of their spectral dependence. …”
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Enhanced Performance by Time-Frequency-Phase Feature for EEG-Based BCI Systems by Baolei Xu, Yunfa Fu, Gang Shi, Xuxian Yin, Zhidong Wang, Hongyi Li, Changhao Jiang

“…Support vector machines (SVMs) and extreme learning machines (ELMs) are compared for classification between clench speed and clench force motor imagery using the optimized feature. …”
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MANAGEMENT OF INNOVATIVE DEVELOPMENT OF ENTERPRISES IN THE CONTEXT OF A CHOICE OF ENERGY SECURITY STRATEGY by Oksana Mykoliuk, Nataliia Prylepa

“…Tasks: to determine the choice of alternative strategic perspectives of energy security; to analyze the main approaches to formation of energy security strategy in the conditions of innovative development; to develop scientific and methodological recommendations for neutralization of threats of the energy strategy of enterprise in internal and external environment, revealed in innovation development process. The following results were obtained: defined the main selection criteria of energy security strategy of enterprise; the author’s interpretation of the concept "energy security strategy of enterprise" is proposed, which is based on the vector of innovative development of enterprise in the field of energy security, which is aimed at rational and efficient use of energy and natural energy resources for achievement of strategic innovation aimed goals of energy policy; a structure for the energy security monitoring of enterprise has been formed and the main tasks of the enterprise’s energy security subdivision have been defined. …”
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Live Weight Prediction in Norduz Sheep Using Machine Learning Algorithms by Cihan Çakmakçı

“…The MANN algorithm, on the other hand, required a longer runtime to process the same dataset.…”
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A Meta-Learning-Based Ensemble Model for Explainable Alzheimer’s Disease Diagnosis by Fatima Hasan Al-bakri, Wan Mohd Yaakob Wan Bejuri, Mohamed Nasser Al-Andoli, Raja Rina Raja Ikram, Hui Min Khor, Zulkifli Tahir, The Alzheimer’s Disease Neuroimaging Initiative

“…The methodology involves training an ensemble model that integrates Random Forest, Support Vector Machine, XGBoost, and Gradient Boosting classifiers, with meta-logistic regression used for the final decision. …”
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A Deep Learning Approach for Extracting Cyanobacterial Blooms in Eutrophic Lakes From Satellite Imagery by Nan Wang, Zhenyu Tan, Chen Yang, Jinge Ma, Hongtao Duan

“…Moreover, a novel labeling technique using remote sensing indices simplified the labeling process. Experiments showed that MBAUNet achieved over 90% precision and recall, with an F1 score of 94.01%, outperforming vanilla UNet, DeepLabV3+, random forest, and support vector machine, while halving the number of parameters and training time compared to UNet. …”
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Optimizing Outdoor Micro-Space Design for Prolonged Activity Duration: A Study Integrating Rough Set Theory and the PSO-SVR Algorithm by Jingwen Tian, Zimo Chen, Lingling Yuan, Hongtao Zhou

“…This study proposes an optimization method based on Rough Set Theory (RST) and Particle Swarm Optimization–Support Vector Regression (PSO-SVR), aimed at enhancing the emotional dimension of outdoor micro-space (OMS) design, thereby improving users’ outdoor activity duration preferences and emotional experiences. …”
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Detection of Psychomotor Retardation in Youth Depression: A Machine Learning Approach to Kinematic Analysis of Handwriting by Vladimir Džepina, Nikola Ivančević, Sunčica Rosić, Blažo Nikolić, Dejan Stevanović, Jasna Jančić, Milica M. Janković

“…The feature selection process revealed that velocity-related features were most effective in distinguishing patients with depression from controls, expectedly reflecting a slowdown in psychomotor functioning among the patients. …”
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