Enhancing Text Classification Through Grammar-Based Feature Engineering and Learning Models by Alaa Mohasseb, Andreas Kanavos, Eslam Amer

“…This study proposes a hybrid approach that integrates grammar-based feature engineering with deep learning and transformer models to enhance classification performance. …”
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Prediction Model of Material Properties Based on Feature Fusion and Convolutional Neural Network by SHI Jingchen, LIU Feining, WANG Wenjie, ZHAO Rui

“…Aiming at the problem that most machine learning models need a lot of prior knowledge and manual selection of feature vectors in the prediction of material properties, a convolutional neural network model OPCNN (Orbital of Electron and Periodic table CNN) is established by feature fusion based on two descriptors, electronic orbit matrix and periodic table method. …”
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A small underwater object detection model with enhanced feature extraction and fusion by Tao Li, Yijin Gang, Sumin Li, Yizi Shang

“…To tackle these challenges, this paper presents an efficient deep convolutional network model. First, a CSP for small object and lightweight (CSPSL) module is introduced to enhance feature retention and preserve essential details. …”
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Predictive modeling of visible-light azo-photoswitches’ properties using structural features by Said Byadi, P. K. Hashim, Pavel Sidorov

“…We compile a comprehensive data set from literature sources and perform a rigorous benchmark to select the best feature type and modeling approach. …”
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Effects of data transformation and model selection on feature importance in microbiome classification data by Zuzanna Karwowska, Oliver Aasmets, Estonian Biobank research team, Tomasz Kosciolek, Elin Org

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EEG Depression Recognition Based on Multi-domain Features Combined with CBAM Model by CHEN Yu, HU Xiuxiu, WANG Sheng

“…At present, the electroencephalogram (EEG) identification method for depression mainly uses a single feature extraction method, which cannot cover multi-domain feature information, resulting in poor classification performance of the existing model. …”
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Medical image retrieval using ROI extraction and hybrid bag-of-features model by Sneha Kugunavar, C. J. Prabhakar

“…This paper proposes a novel CBMIR framework based on a hybrid bag-of-features model designed for improved scalability, interpretability, and retrieval performance. …”
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Energy Consumption Prediction Model for Electric Buses Considering Actual Quantifiable Features by Guowei Zhu, Miao Shi, Jia He

“…Secondly, the energy consumption influencing factors were used to extract trip energy consumption features, including departure moment features, vehicle performance features, and driver attribute features. …”
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Hybrid Intelligence Model Based on Image Features for the Prediction of Flotation Concentrate Grade by YaLin Wang, XiaoFang Chen, XiaoLing Zhou, WeiHua Gui, Louis Caccetta, Honglei Xu

“…The data-driven models based on froth image features provide accurate prediction within well-sampled space but rely heavily on sample data with less generalization capability. …”
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Extracting Optimal Number of Features for Machine Learning Models in Multilayer IoT Attacks by Badeea Al Sukhni, Soumya K. Manna, Jugal M. Dave, Leishi Zhang

“…The proposed framework managed to extract an optimal set of 13 significant features out of 64 in the Edge-IIoT dataset, which is crucial for the efficient detection and classification of multilayer attacks, and also outperforms the performance of the KNN model compared to other classifiers in binary classification. …”
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Boosting adversarial transferability in vision-language models via multimodal feature heterogeneity by Long Chen, Yuling Chen, Zhi Ouyang, Hui Dou, Yangwen Zhang, Haiwei Sang

“…Extensive experiments demonstrate MFHA’s significant advantage in transferable attack capability, with an average improvement of 16.05%, and outstanding attack performance on multimodal large language models like MiniGPT4 and LLaVA. …”
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Altered auditory feature discrimination in a rat model of Fragile X Syndrome. by D Walker Gauthier, Noelle James, Benjamin D Auerbach

“…Using an experimentally informed population model, we show that these cortical physiological differences can recapitulate the observed behavior discrimination deficits, with decoder performance being tightly linked to differences in cortical tuning width and signal-to-noise ratios. …”
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Harvester Maintenance Prediction Tool: Machine Learning Model Based on Mechanical Features by Rodrigo Oliveira Almeida, Richardson Barbosa Gomes da Silva, Danilo Simões

“…Although the combination models performed well, the Random Forest model performed better in the default mode with an accuracy of 0.933. …”
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Study on Photovoltaic Plant Site Selection Models Based on Geographic and Environmental Features by RAO Zhi, YANG Zaimin, YANG Xiongping, LI Jiaming, YANG Ping, WEI Zhichu

“…A high-precision prediction framework driven by multiple features was constructed by incorporating environmental and geographical parameters into the model input to enhance the overall performance. …”
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Clinical features and predictive model for invasive pulmonary fungal infections in hematologic disorders by Jun Wang, Xuefeng He, Feng Chen, Xiao Ma, Daxiong Zeng, Junhong Jiang

“…Objective: This study was to investigate the clinical features of hematological disorders complicated by invasive pulmonary fungal infections and identify factors affecting treatment outcomes, with the aim of developing a predictive model. …”
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Numerical Study of the Hydrodynamic Performance of Rim-Driven Propulsion Featuring a Modified 19A Duct by Masoumpour Meysam, Ghassemi Hassan, Hossein Mousavizadegan S., He Guanghua

“…In this study, the Reynolds-averaged Navier-Stokes (RANS) equations are employed together with the moving reference frame method and steady-state numerical simulations to address challenges related to applicability. The SST turbulence model is also incorporated. Initially, a Ka-Series+19A ducted propeller (DP) is considered, and the numerical results for its hydrodynamic performance are found to show a close correlation with experimental data. …”
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Assessing CO2 separation performances of IL/ZIF-8 composites using molecular features of ILs by Hasan Can Gulbalkan, Alper Uzun, Seda Keskin

“…We simulated CO2, CH4, and N2 adsorption properties of these composites and used this high-quality molecular simulation data to develop ML models that can predict gas uptakes of any IL/ZIF-8 composite when chemical and structural features of the IL are given. …”
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A Unified Framework for Fault and Performance Prediction Using Spatio-Temporal Geometric Features Based on STSFE by Dong-Hyun Kang, A-Youn Yang, Jong-Min Lee, Jong-Gu Lee

“…This paper proposes a unified deep-learning framework for fault and performance prediction in communication equipment by utilizing spatiotemporal geometric features. …”
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The Impact of PDDL+ Language Features on Planning Performance: An Empirical Analysis on a Real-world Case Study by Anas El Kouaiti, Francesco Percassi, Alessandro Saetti, Mauro Vallati

“…It includes a number of features designed to improve the readability and conciseness of the resulting knowledge models, but that are commonly doubted to have detrimental impact on the performance of domain-independent searches and heuristics. …”
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Performance Analysis and Improvement of Machine Learning with Various Feature Selection Methods for EEG-Based Emotion Classification by Sherzod Abdumalikov, Jingeun Kim, Yourim Yoon

“…For both datasets, the experimented three feature selection methods consistently improved the accuracy of the models. …”
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