Research on Interval Probability Prediction and Optimization of Vegetation Productivity in Hetao Irrigation District Based on Improved TCLA Model by Jie Ren, Delong Tian, Hexiang Zheng, Guoshuai Wang, Zekun Li

“…Traditional machine learning algorithms frequently experience overfitting when processing high-dimensional time-series data or substantial numbers of outliers, impeding the accurate prediction of various vegetation metrics. …”
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Machine-learning-based analytics for risk forecasting of anaphylaxis during general anesthesia by Shuang Liu, Yasuyuki Suzuki, Toshihiro Yorozuya, Masaki Mogi

“…To develop a personalized risk forecast platform for general anesthesia-related anaphylaxis, as a first step, we aimed to investigate the feasibility of machine-learning-based classification using clinical features of patients for risk prediction of anesthesia-related anaphylaxis. After data pre-processing, the performance of five classification methods: Logistic Regression Analysis, Support Vector Machine, Random Forest, Linear Discriminant Analysis, and Naïve Bayes), which were integrated with four feature selection methods (Recursive Feature Elimination, Chi-Squared Method, Correlation-based Feature Selection, and Information Gain Ratio), was evaluated using two-layer cross-validation. …”
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K-Gen PhishGuard: an Ensemble Approach for Phishing Detection with K-Means and Genetic Algorithm by Ali Al-Hafiz, Adnan Jabir, Shamala Subramaniam

“…In the second phase, the best set of features in each group is identified through the Genetic algorithm to enhance the classification process. Finally, a voting ensemble technique is applied, in which the Support Vector Machine (SVM), Random Forest (RF), Extreme Gradient Boosting (XGBoost) and Adaptive boosting (AdaBoost) models are combined. …”
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Investigating factors affecting the quality of water resources by multivariate analysis and soft computing approaches by Bing Cheng, Xinyu Liu, Keke Guo, Ahmad Rastegarnia

“…Therefore, Na+, Cl+, Na%, CO3 −, and SO4 2− were used as input variables (independent variables), and EC, TDS, and SAR were used as output variables (dependent variables). Support vector machine (SVM) with various kernel functions, multilayer perceptron artificial neural network (MLP-ANN) with various training algorithms, random forest algorithm (RFA), Gaussian process regression (GPR), and statistical analysis methods were used for modeling. …”
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Range Space and Similarity Transformation Using Symbolic Mathematics in Python by Chainarong Wisassakwichai, Prasert Phaochoo

“…It covers important theorems, including vector space basis, range space, null space, rank and nullity, eigenvalues, generalized eigenvectors, eigenspaces, and diagonal-Jordan canonical form transformations. …”
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Pedagogical conditions for ensuring continuity in the development of coherent speech in older preschool children and first graders by Olga V. Romanova

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EDB-Net: Efficient Dual-Branch Convolutional Transformer Network for Hyperspectral Image Classification by Hufeng Guo, Wenyi Liu

“…Hyperspectral image (HSI) classification, as a pivotal technology in remote sensing data processing, has garnered significant attention in recent years. …”
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LLM-Augmented Linear Transformer–CNN for Enhanced Stock Price Prediction by Lei Zhou, Yuqi Zhang, Jian Yu, Guiling Wang, Zhizhong Liu, Sira Yongchareon, Nancy Wang

“…The textual summaries are further transformed into vector representations using FinBERT, a pre-trained financial language model, to enhance the dataset with contextual insights. …”
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Evaluation of smartphone-based cough data in amyotrophic lateral sclerosis as a potential predictor of functional disability. by Pedro S Rocha, Nuno Bento, Duarte Folgado, André V Carreiro, Miguel Oliveira Santos, Mamede de Carvalho, Bruno Miranda

“…Support vector machines (SVM) were employed to estimate the accuracy of classifying between patients and controls and between patients with bulbar and respiratory impairment. …”
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CSpredR: A Multi-Site mRNA Subcellular Localization Prediction Method Based on Fusion Encoding and Hybrid Neural Networks by Xiao Wang, Wenshuai Suo, Rong Wang

“…They can encode the k-mer units in the sequence into word vectors, thus serving as the node feature vectors of the graph. …”
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A review on artificial intelligence thermal fluids and the integration of energy conservation with blockchain technology by Abdullah Ayub Khan, Asif Ali Laghari, Syed Azeem Inam, Sajid Ullah, Laila Nadeem

“…In order to model prediction and increase the effectiveness of thermal fluid application proposals, this review looks at the latest developments in the use of AI-enabled machine learning techniques, such as Artificial Neural Networks (ANNs), Support Vector Machines (SVM), and Deep Learning Hierarchy. …”
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Metals associated with Beach plastic litter at Woodbridge Island and Derdesteen in Table Bay, South Africa by Adetunji Awe, Ogheneochuko Oputu, Uyiosa Osagie Aigbe, Conrad Sparks

“…Of the plastic debris (≤ 200 mm) processed for metal content using an inductively coupled plasma mass spectrometer (ICP-MS), polystyrene plastics were found to contain a higher abundance of the analyzed metals. …”
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A Set of Proximal Regulatory Elements Contribute to the Transcriptional Activity of the Human Lipoprotein Lipase Promoter by Nasmah K. Bastaki, Taybha A. Albarjes, Afnan K. Mohamed, Noorhan H. Sabri, Suzanne A. Al-Bustan

“…Full and partial <i>LPL</i> promoter sequences, which contained and excluded the 12 regulatory elements, respectively, were cloned and inserted into a promoterless luciferase reporter vector. The functional activities of these constructs were tested in vitro using a dual-luciferase reporter assay. …”
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Multi-Domain Controversial Text Detection Based on a Machine Learning and Deep Learning Stacked Ensemble by Jiadi Liu, Zhuodong Liu, Qiaoqi Li, Weihao Kong, Xiangyu Li

“…Due to the rapid proliferation of social media and online reviews, the accurate identification and classification of controversial texts has emerged as a significant challenge in the field of natural language processing. However, traditional text-classification methodologies frequently encounter critical limitations, such as feature sensitivity and inadequate generalization capabilities. …”
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An Integrated Spatial-Spectral Denoising Framework for Robust Electrically Evoked Compound Action Potential Enhancement and Auditory Parameter Estimation by Fan-Jie Kung

“…In the second stage, the denoised matrix is vectorized and further processed using a log-spectral amplitude (LSA) Wiener filter for spectral domain denoising. …”
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Predictors of length of hospital stay in patients with acute COVID-19 by E. S. Pan’ko, S. V. Zhavoronok, A. M. Solovchuk, S. S. Pan’ko, S. V. Pan’ko

“…Conclusion: The proposed model for determining of the hypoxia vector by assessing the severity of ventilation-perfusion dissociation with indicators of oxygenation and ventilation showed that the MVV/MV ratio and SpO2/FiO2 ratio can be used alone and especially in combination, as effective outcome predictors of the acute phase of the infectious process caused by SARS-CoV-2.…”
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DYNAMICS OF PROTEINS OF THE ACUTE PHASE OF INFLAMMATION IN PARATONSILLAR ABSCESSES IN RESIDENTS OF THE INDUSTRIAL CITY by Виктор Дмитриевич Осипов, Вениамин Витальевич Павлов, Дмитрий Вячеславович Суржиков, Вера Викторовна Кислицына, Ирэна Юрьевна Мотуз, Дина Викторовна Пестерева, Варвара Адамовна Штайгер

“…The content of interleukin-6 in the blood serum was studied by the enzyme-linked immunosorbent assay using the test systems of the Vector-Best company. Statistical processing of the obtained data was carried out using the software packages «MS-EXCEL», «BIOSTAT». …”
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Speech emotion recognition algorithm of intelligent robot based on ACO-SVM by Xueliang Kang

“…Aiming at the shortcomings of existing algorithms in the accuracy and processing of complex emotion states, a novel emotion recognition model of intelligent robot speech based on ACO algorithm and multi-level support vector machine is proposed. …”
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Prognosis of air quality index and air pollution using machine learning techniques by Mostafa M. Abdelmalek, Hatem Mahmoud, Hassan Shokry

“…This study utilizes five machine learning (ML) models, which are Gaussian Process Regression (GPR), Ensemble Regression (ER), Support Vector Machine (SVM), Regression Tree (RT), and Kernel Approximation Regression (KAR), which are developed and compared to predict the Air Quality Index (AQI). …”
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PAR-3 knockdown enhances adhesion rate of PANC-1 cells via increased expression of integrinαv and E-cadherin. by Liora Segal, Liora S Katz, Hagit Shapira, Judith Sandbank, Elizabeth Geras-Raaka, Marvin C Gershengorn, Yoram Oron

“…PAR-3 KDs also exhibited slower in vitro wound closure than vector-control and PAR-1 KD cells. To study the molecular mechanism(s) of PAR-3 KD cells' enhanced rate of adhesion, we assayed the expression of the molecules that mediate cell-surface and cell-cell adhesion. …”
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