A Comparative Evaluation of Machine Learning Methods for Predicting Student Outcomes in Coding Courses by Zakaria Soufiane Hafdi, Said El Kafhali

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Classification and risk assessment of ovarian-adnexal lesions using parametric and radiomic analysis of co-registered ultrasound-photoacoustic tomographic images by Yixiao Lin, Quing Zhu

“…A machine learning model (US-PAT KNN model) was developed based on an optimized subset of eight US and PAT imaging features to classify a lesion as either cancer, one of four subtypes of benign lesions, or a normal ovary. …”
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Pathway-based cancer transcriptome deciphers a high-resolution intrinsic heterogeneity within bladder cancer classification by Zhan Wang, Zhaokai Zhou, Shuai Yang, Zhengrui Li, Run Shi, Ruizhi Wang, Kui Liu, Xiaojuan Tang, Qi Li

“…Notably, MA subtype exhibited the most favorable response to immunotherapy, potentially attributable to its distinctive tumor immune microenvironment. …”
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Research Progress and Applications of Artificial Intelligence in Agricultural Equipment by Yong Zhu, Shida Zhang, Shengnan Tang, Qiang Gao

“…The findings reveal a deep integration of AI models with multimodal perception technologies, significantly improving the operational efficiency, resource utilization, and environmental adaptability of agricultural equipment. …”
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An End-to-End Solution for Large-Scale Multi-UAV Mission Path Planning by Jiazhan Gao, Liruizhi Jia, Minchi Kuang, Heng Shi, Jihong Zhu

“…The MHA module effectively models global spatial-task dependencies among nodes, enhancing solution quality. …”
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A Machine Learning Implementation to Predictive Maintenance and Monitoring of Industrial Compressors by Ahmad Aminzadeh, Sasan Sattarpanah Karganroudi, Soheil Majidi, Colin Dabompre, Khalil Azaiez, Christopher Mitride, Eric Sénéchal

“…Then, a Linear Regression model was fitted to the training data, and the optimized model was stored for real-time inference. …”
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Challenges of the Biopharmaceutical Industry in the Application of Prescriptive Maintenance in the Industry 4.0 Context: A Comprehensive Literature Review by Johnderson Nogueira de Carvalho, Felipe Rodrigues da Silva, Erick Giovani Sperandio Nascimento

“…The limitations presented in the literature include a reduced number of models, the lack of a clearer understanding of its construction, lack of applications directly linked to the biopharmaceutical industry, and lack of measurement of costs and implementation time of these models. …”
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Speech Signal Enhancement Techniques by Chouki Zegar, Abdelhakim Dahimene

“…The comparison study results based on subjective and objective tests showed that the Optimally Modified Log-Spectral Amplitude Estimator (OM-LSA) method outperforms all the implemented DFTbased single-channel speech enhancement algorithms …”
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Advances and challenges in neoantigen prediction for cancer immunotherapy by Yi Zhang, Ting-Ting Chen, Xiong Li, Ai-Lin Lan, Peng-Fei Ji, Ya-Juan Zhu, Xue-Yao Ma

“…Future advancements will focus on dynamic tumor microenvironment monitoring, multi-omics integration, improved computational models and algorithms to refine neoantigen prediction, and developing optimized personalized vaccines.…”
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Short-term prediction of trimaran load based on data driven technology by Haoyun Tang, Rui Zhu, Qian Wan, Deyuan Ren

“…The impact analysis on the factors such as input length, neuron number, artificial neural network (ANN) optimizer, and output scope, are taken. To highlight the trimaran high-frequency load fluctuation and improve the prediction accuracy, the LSTM neural network combines with different signal decomposition algorithms, such as Empirical Mode Decomposition (EMD), Ensemble Empirical Mode Decomposition (EEMD), Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), and Variational Mode Decomposition (VMD). …”
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SEPDNet: simple and effective PCB surface defect detection method by Du Lang, Zhenzhen Lv

“…Current PCB defect detection methods are typically optimized using existing models such as YOLO and Faster R-CNN to enhance detection accuracy. …”
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Intelligent Malfunction Identification Method in Mechanical Manufacturing Process Based on Multisensor Data by Meng Wang

“…The mechanical data of keyboard chords are acquired by sound-sensitive sensors, and the data features are extracted by wavelet packet decomposition. Based on the optimized BP, a mechanical malfunction judgment model is constructed, and various parameters in the model are calculated. …”
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Empowering Education: Leveraging Clustering and Recommendations for Enhanced Student Insights by Kheira Ouassif, Benameur Ziani, Jorge Herrera-Tapia, Chaker Abdelaziz Kerrache

“…The overarching goal was to refine adaptive learning models that cater to the diverse needs of students, improving their academic success and participation.…”
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Advancing Agricultural Machinery Maintenance: Deep Learning-Enabled Motor Fault Diagnosis by Xusong Bai, Qian Chen, Xiangjin Song, Weihang Hong

“…This article further discusses future research directions, such as optimizing DL models for real-time processing, improving robustness under varying agricultural conditions, and developing user-friendly interfaces for farmers and technicians. …”
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Integrating Proximal and Remote Sensing with Machine Learning for Pasture Biomass Estimation by Bernardo Cândido, Ushasree Mindala, Hamid Ebrahimy, Zhou Zhang, Robert Kallenbach

“…We applied the Boruta algorithm for feature selection to identify influential biophysical predictors and evaluated four machine learning models—Linear Regression, Decision Tree, Random Forest, and XGBoost—for biomass prediction. …”
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BucketAugment: Reinforced Domain Generalisation in Abdominal CT Segmentation by David Jozef Hresko, Peter Drotar

“…<italic>Methods:</italic> BucketAugment leverages principles from the Q-learning algorithm and employs validation loss to search for an optimal policy within a search space comprised of distributed stacks of 3D volumetric augmentations, termed &#x2018;buckets.…”
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Parallelizing Quantum Simulation With Decision Diagrams by Shaowen Li, Yusuke Kimura, Hiroyuki Sato, Masahiro Fujita

“…The target is to find the optimal parallelization strategies and improve the performance of DD-based quantum simulation. …”
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Research on Mobile Agent Path Planning Based on Deep Reinforcement Learning by Shengwei Jin, Xizheng Zhang, Ying Hu, Ruoyuan Liu, Qing Wang, Haihua He, Junyu Liao, Lijing Zeng

“…A sensor-driven three-dimensional simulation environment featuring static obstacles was constructed using the ROS and Gazebo platforms, where LiDAR-equipped mobile agent models were trained for real-time environmental perception and strategy optimization prior to deployment on experimental vehicles. …”
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Research Status and Progress of Acoustic Fire Extinguishing Technology by Xinyue Shi, Zhaojun Tian, Yi Lu, Qing Ye

“…Future advancements require breakthroughs in acoustic metamaterials, the integration of intelligent algorithms, and the collaborative optimization of multi-technology systems to facilitate the transition of acoustic wave-based fire suppression from laboratory settings to real-world industrial firefighting applications. …”
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An in-depth exploration of supervised and semi-supervised learning on face recognition by Purnawansyah, Wibawa Aji Prasetya, Widiyaningtyas Triyanna, Haviluddin, Darwis Herdianti, Azis Huzain

“…Although there are some instances of sub-optimal performance in certain algorithms like CNN on specific datasets, this research provides comprehensive insights into the effectiveness of various models in contexts of limited-label learning. …”
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