Review of Control Techniques for Dual Three-phase PMSM Drives with Low Carrier Ratios by Minrui Gu, Zheng Wang, Ming Cheng, Weifeng Su, Linyue Shang, Po Liu

“…Specifically, three categories of methods, i.e., the space vector modulation based control, the model predictive control (MPC), and the optimized pulse pattern (OPP) based control are reviewed with principles and performance. …”
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Detecting small seamounts in multibeam data using convolutional neural networks by Tobias Ziolkowski, Colin W. Devey, Agnes Koschmider

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Innovations in animal health: artificial intelligence-enhanced hematocrit analysis for rapid anemia detection in small ruminants by Aftab Siddique, Sudhanshu S. Panda, Sophia Khan, Seymone T. Dargan, Savana Lewis, India Carter, Jan A. Van Wyk, Ajit K. Mahapatra, Eric R. Morgan, Thomas H. Terrill

“…Four separate machine learning models (ML) supported models, namely support vector machine (SVM), K-nearest neighbors (KNN), backpropagation neural network (BPNN), and image classification-based Keras model, were created and assessed using the image dataset. …”
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Effect of Foreign Direct Investment on Affordable Housing in Kenya: The Role of Inflation as a Moderating Variable by Chamwoma Katu Aggrey, Ngala Consolata, Umulkher Ali

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Fast Prediction for Roll Motion of a Damaged Ship Based on SVR by LIU Han, SU Yan, ZHANG Guoqiang

“…ANSYS-AQWA is applied to analyze the rolling motion response of the damaged ship DTMB5415 under various working conditions. The results are compared with those in exiting literature to validate the practicality of the hydrodynamic model. …”
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Enhancing public transportation through user feedback: the case of Braamfontein, Johannesburg by Retsepile Kalaoane, Trynos Gumbo

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Local Binary and Multiclass SVMs Trained on a Quantum Annealer by Enrico Zardini, Amer Delilbasic, Enrico Blanzieri, Gabriele Cavallaro, Davide Pastorello

“…Support vector machines (SVMs) are widely used machine learning models, with formulations for both classification and regression tasks. …”
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Study on Exposure Time Difference Compensation Method for DMD-Based Dual-Path Multi-Target Imaging Spectrometer by Yingming Zhao, Jianing Yang, Chunyu Liu, Chen Wang, Guoxiu Zhang, Yi Ding

“…To address this issue, we propose a dual-path exposure time difference compensation method based on a velocity vector field model, enabling dynamic and precise matching of the dual paths. …”
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On bifurcations of a periodic orbit tangent to switching lines at two points by V.Sh. Roitenberg

“…Dynamic systems defined by discontinuous piecewise smooth vector fields on a plane are natural mathematical models of relay systems in automatic control theory. …”

Enhancing RAG Performance by Representing Hierarchical Nodes in Headers for Tabular Data by Minchae Song

“…This study introduced hierarchical node-based header representation models designed to enhance the processing and integration of external table data, addressing the key limitations of existing RAG techniques when working with structured table sources. …”
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MILLING FORCE MODELING BASED ON EQUIVALENT TURNING FORCE AND OBLIQUE CUTTING FORCE MODEL (MT) by WU MingZhou, ZHANG GuangPeng, LIU MoHan, GOU JianFeng, ZHANG Peng

“…The accuracy of traditional milling force prediction model is low, and it is difficult to provide effective support for the reasonable selection of process parameters in practical production, by synthetically considering the equivalent turning force model of working angle, cutting edge arc and radius of tool tip arc, in this model, the actual turning tool is equivalent to the ideal turning tool model to identify the material constant, the chip flow angle and the average friction angle in the material constitutive equation, according to the oblique cutting model, the shear stress on the main shear plane and the F₀ vector of the unit cutting force at different cutting speeds are calculated, thus the instantaneous cutting force on the front face of the end mill can be calculated, the three-dimensional cutting force of end mill in X-Y-Z coordinate system is obtained by coordinate transformation. …”
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Evaluating the Effects of Mitigating Urban Heat Islands of Green Infrastructure on Increasing the Productivity of Light and Heavy Work (Case Study: Tabriz Metropolitan) by Mahdi Herischian, Hassan Mahmoudzadeh, Rasoul Ghorbani

“…The ecosystem service value of mitigating heat islands in the green infrastructure of Tabriz was calculated based on lost productivity in light and heavy work sectors. The primary inputs for the model included a land use/land cover raster map, a reference evapotranspiration (ET0) raster map, a biophysical table containing details about each land use/land cover class, a vector map of city buildings, and an energy consumption rate table categorized by building type and air temperature. …”
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An Innovative Approach to Estimate Chloride Diffusion Coefficient in Submerged Concrete Structures Using Soft Computing by Seyyed Ali Habibi, Ali Hemmati, Hosein Naderpour

“…Among all kinds of structures, corrosion of submerged structures is of great importance and prevalence due to the impossibility of direct visibility, high reconstruction cost and special environmental conditions. The work done in the field of corrosion of these structures has mainly dealt with modeling the problem in the form of mathematical formulation or using soft computing methods. …”
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A k-nearest text similarity-BiGRU approach for duration prediction of traffic accidents on expressways by Jiaona Chen, Jin Zhang, Peng Wang, Yinli Jin

“…This study proposes a k-nearest text similarity-BiGRU(Bidirectional Gated Recurrent Unit) approach to predict the duration of traffic accidents using textual records. Firstly, text vectors are extracted through a TF-IDF (Term Frequency-Inverse Document Frequency) model to vectorize textual descriptions. …”
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Computational hybrid analysis of drug diffusion in three-dimensional domain with the aid of mass transfer and machine learning techniques by Mohammed Alqarni, Ali Alqarni

“…We employ three tree-based ensemble models: Kernel Ridge Regression (KRR), $$\:{\upnu\:}$$ -Support Vector Regression ( $$\:{\upnu\:}$$ -SVR), and Multi Linear Regression (MLR) for modeling the relationship between spatial coordinates and the concentration. …”
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Colorectal cancer detection with enhanced precision using a hybrid supervised and unsupervised learning approach by Akella S. Narasimha Raju, K. Venkatesh, Ranjith Kumar Gatla, Eswara Prasad Konakalla, Marwa M. Eid, Nataliia Titova, Sherif S. M. Ghoneim, Ramy N. R. Ghaly

“…The hybrid schema of this work treats the deficiencies of the previous approaches, such as incorporating CNN-based effective feature extraction, Transformer networks for developing attention mechanisms, and finally the fine decision boundary of the support vector machine. …”
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On adaptive identification of systems having multiple nonlinearities by N. N. Karabutov

“…Therefore, the present work sets out to develop an approach to the identification of nonlinear dynamical systems under conditions of uncertainty. …”
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Persian SMS Spam Detection using Machine Learning and Deep Learning Techniques by Roya Khorashadizade, Somayyeh Jafarali Jassbi, Alireza Yari

“…A huge body of research and experiments has revealed that techniques based on deep and combined learning are superior at identifying unpleasant text messages. This work sought to develop an effective strategy for identifying SMS spam through utilizing combining machine learning classification algorithms together with deep learning models. …”
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Symbolic Framework for Evaluation of NOMA Modulation Impairments Based on Irregular Constellation Diagrams by Nenad Stefanovic, Vladimir Mladenovic, Borisa Jovanovic, Ron Dabora, Asutosh Kar

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Bearing Response Prediction in Hydrothermal Aged Carbon Fiber Reinforced Epoxy Composite Joints Using Machine Learning Techniques by Mohit Kumar, Govind Vashishtha, Babita Dhiman, Sumika Chauhan

“…Conversely, under the same conditions, MWCNTs added composite bolted joints exhibit only a 9.2% reduction. The predictive models find the value of 0.0081 RSME and 0.8 R2 respectively through support vector regression confirming that the predicted values lie in between the upper and lower bond.…”
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