International Natural Uranium Price Prediction Based on TF-CNN-BiLSTM Model by YANG Jingzhe, XUE Xiaogang

“…Its ability to integrate global dependencies, local patterns, and temporal context makes it a promising approach for financial time series forecasting in the energy sector. However, the model’s performance could be further enhanced by incorporating additional relevant features such as geopolitical indicators, economic indices, and policy variables. …”

Combining diffusion and transformer models for enhanced promoter synthesis and strength prediction in deep learning by Xin Lei, Xing Wang, Guanlin Chen, Ce Liang, Quhuan Li, Huaiguang Jiang, Wei Xiong

“…This model proficiently assimilates and utilizes inherent biological features from natural promoter sequences to engineer synthetic variants. …”
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ILN-YOLOv8: A Lightweight Image Recognition Model for Crimped Wire Connectors by Xiaojian Zhou, Jicheng Kan, Nur Fatin Liyana Mohd Rosely, Xu Duan, Jiajing Cai, Zihan Zhou

“…Taking the original YOLOv8 model as a baseline, the new model enhances the ability to extract shallow features from small targets by increasing the P2 detection layer and improving the Feature Pyramid Network(FPN) and Path Aggregation Network(PAN) structures. …”
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Evaluating YOLO Models for Efficient Crack Detection in Concrete Structures Using Transfer Learning by Muhammad Sohaib, Muzamal Arif, Jong-Myon Kim

“…The YOLO models are initially trained on a dataset containing both images with and without cracks, producing a generalized model capable of extracting abstract features beneficial for crack detection. …”
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The Adoption of Runosong Techniques in Estonian Antiphonal Psalmody: Toward a Circular Model of Chanting by Jõks Eerik

“…Drawing on selected features of runosong, such as the circular musical phrase, anticipatory entry (leegajus), and ingressive phonation (inward speaking), the study culminates in the formulation of a circular model of antiphonal psalmody offering a new approach to communal ecclesiastical chanting.…”
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The Speaker Identification Model for Air-Ground Communication Based on a Parallel Branch Architecture by Weijun Pan, Shenhao Chen, Yidi Wang, Sheng Chen, Xuan Wang

“…The model also demonstrates strong performance on four cross-domain datasets, highlighting its broad potential for real-time applications.…”
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Enhancing 3D Reconstructions in Underwater Environments: The Impact of Image Enhancement on Model Quality by A. Vrochidis, A. Vrochidis, D. Tzovaras, S. Krinidis

“…Three real-world underwater datasets were analyzed to assess the effectiveness of these methods in improving the accuracy and completeness of reconstructed 3D models. Notably, the RGB-CLAHE combination achieved the most substantial improvements, increasing reconstructed points by 7.60%, detected features by 7.56%, and reconstructed features by 12.94% on average across the datasets. …”
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DSR-YOLO: A lightweight and efficient YOLOv8 model for enhanced pedestrian detection by Mustapha Oussouaddi, Omar Bouazizi, Aimad El mourabit, Zine el Abidine Alaoui Ismaili, Yassine Attaoui, Mohamed Chentouf

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YOLOv11-GSF: an optimized deep learning model for strawberry ripeness detection in agriculture by Haoran Ma, Qian Zhao, Runqing Zhang, Chunxu Hao, Wenhui Dong, Xiaoying Zhang, Fuzhong Li, Xiaoqin Xue, Gongqing Sun

“…To overcome these limitations, this paper introduces YOLOv11-GSF, a real-time strawberry ripeness detection algorithm based on YOLOv11, which incorporates several innovative features: a Ghost Convolution (GhostConv) convolution method for generating rich feature maps through lightweight linear transformations, thereby reducing computational overhead and enhancing resource utilization; a C3K2-SG module that combines self-moving point convolution (SMPConv) and convolutional gated linear units (CGLU) to better capture the local features of strawberry ripeness; and a F-PIoUv2 loss function inspired by Focaler IoU and PIoUv2, utilizing adaptive penalty factors and interval mapping to expedite model convergence and optimize ripeness classification. …”
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Latent space improved masked reconstruction model for human skeleton-based action recognition by Enqing Chen, Xueting Wang, Xin Guo, Ying Zhu, Dong Li

“…However, in visual classification tasks such as action recognition, the limited ability of the encoder to learn features in the autoencoder structure results in poor classification performance. …”
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A Predictive Approach for Enhancing Accuracy in Remote Robotic Surgery Using Informer Model by Muhammad Hanif Lashari, Shakil Ahmed, Wafa Batayneh, Ashfaq Khokhar

“…The method is evaluated using the JIGSAWS dataset, achieving a prediction accuracy of over 90% under various network scenarios. A comparison with models such as TCN, RNN, and LSTM demonstrates the Informer framework’s superior performance in handling position prediction and meeting real-time requirements, making it suitable for Tactile Internet-enabled robotic surgery.…”
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Development and validation of radiomics model for MRI-based identification of anterior talofibular ligament injuries by Tian-Xin Chen, Jun-Ying Wu, Tong-Jie Yang, Gang Chen, Yan Li, Lei Zhang

“…A dataset of 467 arthroscopically confirmed cases (276 partial tears, 191 complete tears) was analyzed, and 28 key features were selected for model construction using machine learning classifiers. …”
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Cobb angle prediction for adolescent idiopathic scoliosis via an explainable machine learning model by Yu Ding, Bin Li, Xiaoyong Guo

“…The output of the TreeExplainer provides us a richer understanding that demonstrates how a feature’s value impacts the model’s prediction for every instance. …”
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A Novel Dataset for Polyp Segmentation and Detection Using a Vision-Language Model by Mahdiyeh Alilou, Javad Mozaffari, Abdollah Amirkhani, Shahriar B. Shokouhi, Alireza Khafaf

“…Results indicate that the proposed model performs better than state-of-the-art studies by 2.7% and 2.5%, respectively, in mDice and mIoU. …”
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A small object detection model in aerial images based on CPDD-YOLOv8 by Jingyang Wang, Jiayao Gao, Bo Zhang

“…The CPDD-YOLOv8 is proposed to improve the performance of small object detection. Firstly, we propose the C2fGAM structure, which integrates the Global Attention Mechanism (GAM) into the C2f structure of the backbone so that the model can better understand the overall semantics of the images. …”
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Construction of a predictive model for cervical lymph node metastasis in papillary thyroid carcinoma by YanHong Hao, Yuan Su, Yanan Li, Qiaohong Pan, Liping Liu

“…Comprehensive clinical information, serological indices, and ultrasonography features were obtained for every participant. LASSO (Least Absolute Shrinkage and Selection Operator) and BSR (Best Subset Regression) to select features for model construction. …”
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Providing a model of purchase intention and customer experience on customer behavior in virtual networks by Kazem Tolooee, Hossein budaghi Khajeh Noubar, Hossein Gharehbiglo, Mojtaba Ramazani

“…In addition, relatively little work has been done to determine customer perceptions of a digital marketing approach using virtual interior design and its interactive features. Therefore, a theoretical model for interactive virtual interior design features for digital marketing is proposed.Research methodologyThe current research is applicable in terms of purpose and descriptive-survey in terms of nature and method. …”
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A hybrid power load forecasting model using BiStacking and TCN-GRU. by Jun Ma, Jishen Peng, Haotong Han, Liye Song, Hao Liu

“…The model first applies the Pearson correlation coefficient (PCC) to select features highly correlated with the power load. …”
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How gamification influences e-commerce behavior in hardcore vs. casual gamers? by Junialdi Dwijaputra, Diana Purwitasari, Ellya Zulaikha

“…Using data collected from 302 e-commerce users in Indonesia, this study employs structural equation modeling (SEM) to analyze the relationships between gamification design, user behavior, and business performance. …”
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Comprehensive Evaluation of Bankruptcy Prediction in Taiwanese Firms Using Multiple Machine Learning Models by Hung V. Pham, Tuan Chu, Tuan M. Le, Hieu M. Tran, Huong T.K. Tran, Khanh N. Yen, Son V. T. Dao

“…Additionally, a wrapper-based feature selection (FS) utilizing Binary Particle Swarm Optimization (BPSO) was utilized to find an optimal feature subset and boost the model’s predictive performance. …”
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