The effectiveness of media in Iraqi theatre performances, the play (The Pawns) as a model by Baha Amer Ashour Sabti, Mudhad Ajil Hassan

“…The research aims to identify the effectiveness of media in Iraqi theater performances (Al-Bayadiq as a Model). The first section deals with the concept of media and its effectiveness. …”
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Development and interpretation of machine learning-based prognostic models for predicting high-risk prognostic pathological components in pulmonary nodules: integrating clinical fe... by Dingxin Wang, Jianhao Qiu, Rongyang Li, Hui Tian

“…Lasso regression was utilized in order to identify key features, and a machine learning prediction model was constructed based on the screened key features. …”
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PEMFC RUL Prediction for Non-Stationary Time Series Based on Crossformer Model by Ning Zhou, He Zeng, Zefei Zheng, Ke Wang, Jianxin Zhou

“…Additionally, manual features are introduced through mathematical statistics to enhance the predictive performance of the model. …”
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Maize leaf disease multiclass classification and recognition for sustainable agriculture using multi preceptive deep learning model by Vinay Gautam, Aadam Quraishi, Azzah AlGhamdi, Gaganpreet Kaur, Faisal Alghayadh, Haewon Byeon, Mohammed Wasim Bhatt

“…It applied Multi-scaled Xception pre-trained models to extract deep features from images. The models were fine-tuned with varying weights for advancing the feature extraction so as to enhance the likelihood of correct visual classification. …”
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Enhancing Security of Proof-of-Learning Against Spoofing Attacks Using Feature-Based Model Watermarking by Ozgur Ural, Kenji Yoshigoe

“…This approach addresses critical challenges, including maintaining watermark robustness and balancing security with model performance. Through a comprehensive analysis, we identify vulnerabilities in existing PoL systems and demonstrate how feature-based watermarking can enhance security. …”
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Evapotranspiration estimation using deep learning models for robust sensor performance by Yassine Boukhali, Mohammed Nabil Kabbaj, Mohammed Benbrahim

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Performance Analysis of an Optimized ANN Model to Predict the Stability of Smart Grid by Ayushi Chahal, Preeti Gulia, Nasib Singh Gill, Jyotir Moy Chatterjee

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Optimizing SVM Performance through Combinatorial Hyperparameter Tuning and Model Selection by Hassan Tariq, Mehwish Majeed, Mueed Ahmad

“…Results demonstrate that the train-test-split model generally improves SVM performance, except for the heart disease dataset, on which the CV model performs well. …”
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Optimizing UAV performance with IoT and fuzzy linear fractional transportation models by Samaher Al-Janabi, Nawras G. Seyhood

“…This paper presents an innovative model integrating fully fuzzy linear fractional transportation programming (FTMP) with Internet of Things (IoT) technologies to enhance UAV performance. …”
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Performance Analysis of Artificial Intelligence Models for Classification of Transmission Line Losses by Abraham O. Amole, Oluwagbemiga E. Ajiboye, Stephen Oladipo, Ignatius K. Okakwu, Ibrahim A. Giwa, Olamide O. Olusanya

“…These models were implemented using the Python programming environment and evaluated using standard performance metrics, including accuracy, precision, recall, F1-score, support, and confusion matrices. …”
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Effects of Corrosion Depth on Wind-Induced Collapse Performance of an Angle Steel Transmission Tower by Zhibin Tu, Jianfeng Yao, Zhitong Liu, Xing Zhou, Ligang Zhang

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Automated Feature Extraction in Brain Tumor by Magnetic Resonance Imaging Using Gaussian Mixture Models by Ahmad Chaddad

“…This paper presents a novel method for Glioblastoma (GBM) feature extraction based on Gaussian mixture model (GMM) features using MRI. …”
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Causality-driven feature selection and domain adaptation for enhancing chemical foundation models in downstream tasks by Eduardo Soares, Victor Yukio Shirasuna, Emilio Vital Brazil, Karen Fiorella Aquino Gutierrez, Renato Cerqueira, Dmitry Zubarev, Kristin Schmidt, Daniel P Sanders

“…However, real-world scenarios often pose challenges due to domain shift, a phenomenon where the data distribution in downstream tasks differs from that of the pre-training phase, potentially degrading model performance. To address this, we present a novel causal-based framework for feature selection and domain adaptation to enhance the performance of chemical foundation models on downstream tasks. …”
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Structured-illumination reflectance imaging for the evaluation of microorganism contamination in pork: effects of spectral and imaging features on its prediction performance by Binjing Zhou, Xiaohua Liu, Yan Ge, Kang Tu, Jing Peng, Juan Francisco García-Martín, Jie Wu, Weijie Lan, Leiqing Pan

“…Besides, the prediction models based on the amplitude component or direct component image textural features and the data fusion models using spectrum and textural features from direct component and amplitude component images cannot significantly improve their prediction accuracy. …”
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A nomogram integrating mutation signatures and clinical features for prognostic stratification in bladder cancer by Lili Wang, Peng Chen, Huanhuan Liu, Jiayue Qin, Shanbo Cao, Hongzheng Li, Dingkun Hou, Kaibin Wang, Haitao Wang

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High-performance glass classification using advanced machine learning and deep learning algorithms with a comprehensive feature analysis by Mohammed Bouziane, Abdelghani Bouziane, Samia Larguech, Khatir Naima, Mohammad Salman Haque, Younes Menni

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Harnessing Multiple Level Features to Improve Segmentation Performance of Deep Neural Network: A Case Study in Magnetic Resonance Imaging of Nasopharyngeal Cancer by Rongzhi Mao, Liangxu Xie, Xiaohua Lu, Jialu Pei, Xiaojun Xu, Shan Chang

“…The existing general-purpose segmentation models have made significant progress, but their segmentation performance remains unsatisfactory in specific cancers. …”
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Prediction model for growth trends of subpleural subsolid nodules using CT radiomics and radiological features by Chengxiu Yuan, Hui Li, Jinliang Zhang, Congcong Gao, Zhe Wang, Minghui Sun, Yan Jiang, Hankang Wang

“…Model performance was evaluated via the area under the curve (AUC), calibration curves, and decision curve analysis (DCA). …”
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Survival analysis for sepsis patients: A machine learning approach to feature selection and predictive modeling by Kaida Cai, Xiaofang Yang, Zhengyan Wang, Wenzhi Fu, Hanwen Liu, Fatemeh Mahmoudi

“…Feature selection methods, including adaptive elastic net (AEN), smoothly clipped absolute deviation (SCAD), minimax concave penalty (MCP), and information gain (IG), were employed to refine model performance by identifying the most relevant clinical features. …”
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Prediction of Insulator ESDD Based on Meteorological Feature Mining and AdaBoost-MEA-ELM Model by Yaoping WANG, Te LI, Kaihua JIANG, Wenhui LI, Qiang WU, Yu WANG

“…Compared with other common models, the performance of the proposed model and the rationality of the combination of these three algorithms are verified. …”
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