Multimodal ultrasound radiomics model combined with clinical model for differentiating follicular thyroid adenoma from carcinoma by Qianqian Zhao, Shiyan Guo, Yan Zhang, Jinguang Zhou, Ping Zhou

“…Methods We retrospectively included 201 patients with histopathologically confirmed FTC (n = 133) or FTA (n = 68). Radiomics features were extracted from B-US and CEUS images, followed by feature selection and machine-learning model development. …”
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Performance analysis of a novel design of an engine piston for a single cylinder by Mnati Hayder M., Hammami Maroua, Haeeb Laith Jaafer, Ksentini Olfa, Feki Nabih, Abbes Mohamed Slim, Haddar Mohamed, Hanon Muammel M.

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Effect of Surface Error Distribution and Aberration on Electromagnetic Performance of a Reflector Antenna by Binbin Xiang, Congsi Wang, Peiyuan Lian

“…Based on these, the error profile of the primary influence and the approximate feature of EMP can be determined, and the antenna performance can be predicted in a simple manner.…”
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Design and Investigation of a High-Performance Quartz-Based SAW Temperature Sensor by Jianfei Jiang

“…Employing the Coupling-of-Modes (COM) model, a detailed analysis was conducted on the effects of the number of interdigital transducers (IDTs), the number of reflectors, and their spacing on the performance of the SAW device. …”
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Short term prediction of photovoltaic power with time embedding temporal convolutional networks by Jingxin Wang, Guohan Li, Jin Gu, Zhengyi Xu, Xinrong Chen, Jianming Wei

“…To address these limitations, this study introduces the Time-Embedding Temporal Convolutional Network (ETCN), providing an innovative solution. The ETCN model follows three key steps: First, a heatmap-based feature selection method identifies and prioritizes the most influential features, enhancing performance and reducing computational complexity. …”
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AI-Driven Signal Processing for SF6 Circuit Breaker Performance Optimization by Philippe A. V. D. Liz, Giovani B. Vitor, Ricardo T. Lima, Aurélio L. M. Coelho, Eben P. Silveira

“…As a result, the models evaluated obtained good performance in the identification of operation points above 93%, considering precision and accuracy. …”
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Performance evaluation of enhanced deep learning classifiers for person identification and gender classification by Vasu Krishna Suravarapu, Hemprasad Yashwant Patil

“…Further, an adaptive coati optimization algorithm is used to adjust the hyperparameters of the classification models. The efficacy of the model is assessed concerning different outcome indicators. …”
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Experimental Study on the System Performance of Adjacent Precast Concrete Box Beam Bridges by Yanling Leng, Jinquan Zhang, Ruinian Jiang, Yangjian Xiao

“…To understand the system performance of the bridges, the redundancy and robustness of a bridge model with a scale of 1 ∶ 2, based on the prototype design drawings for 10-meter adjacent box beam bridges in China, were assessed through a system safety evaluation procedure. …”
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Realistic synthetic dataset generation for cyber-physical systems: a performance evaluation by Yaa Acquaah, Kaushik Roy

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Regression-based leaf nitrogen concentration estimation of young Cephalotaxus hainanensis in small and imbalanced samples by Mengmeng Shi, Tian Wang, Ling Lin, Qingxue Li, Zhulin Chen, Xingjing Chen, Peng Wang, Xuefeng Wang

“…Logarithmic transformation enhanced the correlation between LNC and image-derived features. The ADASYNR-SVR model also significantly improved predictive performance compared to other models in rare cases, with the highest F1-score, recall, and precision in both the training set and test set. …”
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Improvement in low-homology template-based modeling by employing a model evaluation method with focus on topology. by Wentao Dai, Tingrui Song, Xuan Wang, Xiaoyang Jin, Lizong Deng, Aiping Wu, Taijiao Jiang

“…To improve the performance of TBM methods for such targets, a novel model evaluation method was developed here, and named MEFTop. …”
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Performance Analysis of Carbon Fiber Reinforced Epoxy Composites in Particle‐Assisted EDM by Abhijit Bhowmik, Raman Kumar, Ramdevsinh Jhala, Nagaraj Patil, Abinash Mahapatro, Manoj Kumar Ojha, Parveen Kumar, Deepak Gupta, A. Johnson Santhosh

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Direction and velocity kinematic features of point-light displays grasping actions are differentially coded within the action observation network by Settimio Ziccarelli, Antonino Errante, Leonardo Fogassi

“…The current findings could have implications for observational-based rehabilitation treatments of patients with motor disorders and artificial intelligence-based hand action recognition models.…”
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Tribological performance of graphene oxide reinforced PEEK nanocomposites with machine learning approach by Yagnik Patel, Unnati Joshi, Prince Jain, Anand Joshi, Sanketsinh Thakor, Swapnil Parikh

“…Additionally, the predictive performance of Extra Tree and XGBoost regression models in estimating wear and friction force was investigated using performance metrics such as MAE and R-squared, incorporating confidence intervals to quantify prediction uncertainty. …”
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A Novel Method for PolISAR Interpretation of Space Target Structure Based on Component Decomposition and Coherent Feature Extraction by Zhuo Chen, Zhiming Xu, Xiaofeng Ai, Qihua Wu, Xiaobin Liu, Jianghua Cheng

“…This paper proposes a space target structure polarization interpretation method based on component decomposition and PolISAR feature extraction. The proposed method divides the target into components at the stage of modeling. …”
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YOLO-OD: Obstacle Detection for Visually Impaired Navigation Assistance by Wei Wang, Bin Jing, Xiaoru Yu, Yan Sun, Liping Yang, Chunliang Wang

“…The proposed YOLO-OD achieves an average precision of 30.02% on a public dataset, making it a worth studying approach for blind and visually impaired navigation aids.Our study effectively addresses the navigation challenges faced by visually impaired individuals by improving model performance, thereby enhancing its practical values. …”
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Machine learning based radiomics approach for outcome prediction of meningioma – a systematic review [version 1; peer review: 2 approved] by Saikiran Pendem, Divya B, Girish R Menon, Saroh S, Shailesh Nayak S, Prakashini K, Priyanka -

“…A support vector machine (SVM) model reached an area under curve (AUC) of 0.80 with radiomic features, improving to 0.88 with ADC integration. …”
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Research on soybean leaf disease recognition in natural environment based on improved Yolov8 by Chen Chen, Chen Chen, Xiaolei Lu, Lei He, Lei He, Ruoxue Xu, Ruoxue Xu, Yi Yang, Yi Yang, Jing Qiu, Jing Qiu

“…A lightweight detection head (LSCD) is further introduced to facilitate multiscale feature interactions while reducing the overall model parameter count. …”
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Traffic flow prediction based on spatial-temporal multi factor fusion graph convolutional networks by Ying-Ting Chen, An Liu, Cheng Li, Shuang Li, Xiao Yang

“…Experimental results on four public real-world datasets prove the superiority of our model in terms of prediction performance and capturing the dynamic spatial-temporal correlation.…”
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A Fusion XGBoost Approach for Large-Scale Monitoring of Soil Heavy Metal in Farmland Using Hyperspectral Imagery by Xuqing Li, Huitao Gu, Ruiyin Tang, Bin Zou, Xiangnan Liu, Huiping Ou, Xuying Chen, Yubin Song, Wei Luo, Bin Wen

“…The XGB-Boruta-PCC algorithm was used for precise feature selection to obtain the final modeled spectral response features. …”
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