Trajectory Planning for Robotic Manipulators in Automated Palletizing: A Comprehensive Review by Samuel Romero, Jorge Valero, Andrea Valentina García, Carlos F. Rodríguez, Ana Maria Montes, Cesar Marín, Ruben Bolaños, David Álvarez-Martínez

“…By reviewing and synthesizing the most recent research, this article sheds light on the state-of-the-art manipulator planning algorithms for pick-and-place tasks in palletizing applications.…”
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Artificial Intelligence-Based Prediction of Bloodstream Infections Using Standard Hematological and Biochemical Markers by Ferhat DEMİRCİ, Murat AKŞİT, Aylin DEMİRCİ

“…The model’s strong performance and interpretability suggest its potential application in clinical decision support systems to improve diagnostic stewardship, reduce unnecessary cultures, and optimize resource use in suspected BSI cases.…”
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Exploration and Construction of Personalized Customization Mode in Modern Fashion Design by Sun Huaiqun

“…By analyzing the advantages of this model in meeting personalized consumer needs, improving production efficiency, and promoting green design and sustainable development, this article further proposes specific suggestions for technology optimization, process simplification, and user experience improvement. …”
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Hyperspectral imaging combined with residual-attention-net for spectral-spatial feature fusion in liver disease diagnosis by Yunze Li, Jingjing Wang, Miaoqing Zhao, Jinlin Deng, Chongxuan Tian, Qize Lv, Yifei Liu, Kun Ru, Wei Li

“…We incorporated band selection techniques, including the Norris derivative and the Successive Projections Algorithm (SPA), and optimized the data processing workflow. …”
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Research of Regenerative Braking Strategy for Electric Vehicles by Van Nghia Le, Hoang Phuc Dam, Trong Hoan Nguyen, S. V. Kharitonchik, V. A. Kusyak

“…The carried out investigations confirm the available significant potential for improving the efficiency of the electric vehicles usage by developing the control strategy and algorithms of the braking energy regeneration.…”
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synax: A Differentiable and GPU-accelerated Synchrotron Simulation Package by Kangning Diao, Zack Li, Richard D. P. Grumitt, Yi Mao

“…This facilitates powerful inference algorithms, such as Hamiltonian Monte Carlo (HMC) and gradient-based optimization, which enables inference over models that would otherwise be computationally prohibitive. …”
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Errors in the diagnosis of types of diabetes mellitus: causes and prevention strategies (literature review and own research results) by K.I. Gerush, N.V. Pashkovska, O.Z. Ukrainets

“…This is due to the increasing heterogeneity of DM, blurring of the boundaries between its types, atypical disease course, the decreased diagnostic value of the essential criteria for DM types (age, presence of metabolic syndrome signs, ketosis, dependency on insulin therapy), presence of comorbid conditions, and limited availability of diagnostic tests to specify the type of diabetes. To optimize diagnosis and prevent diagnostic errors, we have developed a Telegram bot DiaType based on a multilevel algorithm for the differential diagnosis of various types of DM. …”
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Minding the gap. Drug-related problems among breastfeeding women by Karolina Morze, Edyta Szałek, Magdalena Waszyk-Nowaczyk

“…Future research should focus on developing evidence-based guidelines for medication use during lactation and improving healthcare provider education to optimize maternal and infant health.…”
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Early Warning of Axillary Lymph Node Metastasis in Breast Cancer Patients Using Multi-Omics Signature: A Machine Learning-Based Retrospective Study by Ke Z, Shen L, Shao J

“…The AUC of GLRM was 0.818 (95% CI: 0.757~0.879), significantly lower than that of RFM’s AUC 0.893 (95% CI: 0.836~0.950).Conclusion: The prediction models based on machine learning (ML) algorithms and multiomics have shown good performance in predicting ALN metastasis, and RFM shows greater advantages compared to traditional GLRM. …”
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A Multifrequency Seamless Dual-Link Handover Scheme Based on Beamforming for High-Speed Railway by Suoping Li, Ke Wang, Jaafar Gaber, Sa Yang, Wenwu Liang

“…We also establish a probabilistic model and corresponding handover algorithm for the proposed scheme to complete the handover operations and theoretically analyze a series of indexes including handover trigger probability (HTP), HFP, communication interruption probability (CIP), and HSP. …”
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Machine Learning and Neural Networks for IT-Diagnostics of Neurological Diseases by U. A. Vishniakou, Y. W. Xia, Ch. Y. Yu

“…Among them are the GridSearchCV algorithm for optimizing the hyperparameters of the random forest classifier for recognizing Alzheimer’s disease (recognition accuracy is 87.6 %) and the KNN algorithm for training and testing on publicly available datasets of speech change features in patients with Parkinson’s disease. …”
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Reduction of Multiplicative Noise in Radar Images by A. A. Tuzova, V. A. Pavlov, A. A. Belov

“…The proposed algorithm allowed optimal parameters for several speckle noise filters to be determined. …”
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Impact of imbalanced features on large datasets by Waleed Albattah, Rehan Ullah Khan

“…Distributed Gaussian (D-GA) and Distributed Poisson (D-PO) are found to be the most effective techniques, especially in improving Random Forest (RF) and SVM models. …”
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A Precise Detection Method for Tomato Fruit Ripeness and Picking Points in Complex Environments by Xinfa Wang, Xuan Wen, Yi Li, Chenfan Du, Duokuo Zhang, Chengxiu Sun, Bihua Chen

“…Aiming at the problems faced in practical applications, such as low accuracy of tomato ripeness and picking points detection in complex greenhouse environments, which leads to wrong picking, missed picking, and fruit damage by robots, this study proposes the YOLO-TMPPD (Tomato Maturity and Picking Point Detection) model. YOLO-TMPPD is structurally improved and algorithmically optimized based on the YOLOv8 baseline architecture. …”
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Named Entity Recognition in Aviation Products Domain Based on BERT by Mingye Yang, Bernadin Namoano, Maryam Farsi, John Ahmet Erkoyuncu

“…Through experiments on the constructed aviation product dataset, the model achieved a Precision value of 91.74%, a Recall value of 92.46%, and an F1 score of 92.1%, Compared with other baseline models, the F1-score is improved by 0.9% to 1.5%. …”
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A Rapid Identification Method for Cottonseed Varieties Based on Near-Infrared Spectral and Generative Adversarial Networks by Qingxu Li, Hao Li, Renhao Liu, Xiaofeng Dong, Hongzhou Zhang, Wanhuai Zhou

“…Data augmentation using GAN-CNIRD-generated cottonseed data improved the accuracy of the three optimal models by 6%, 5%, and 6%, respectively. …”
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Advancing road maintenance with EfficientDet-based pothole monitoring by Jenefa Archpaul, Taurshia Antony, Kuriakose Bessy Mani, Kumar Edward Naveen Vijaya, Lincy Archpaul

“…Our experimental evaluations demonstrate that the EfficientDet-based model achieves an impressive average precision of 0.90 and a robust recall of 0.92, highlighting its capacity for accurate and swift pothole detection-an essential component for improving road maintenance. …”
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Development of an Intelligent System for Processing Semistructured Data: Industry Structuring and Advanced Analysis of Information Extracted from Comments to Video Clips in Social... by A. A. Poguda, H. Tape

“…The development of an intelligent system for processing semistructured data has improved the analysis of comments on videos in social networks through a combination of various machine learning models and algorithms. …”
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Exploring the Relationship between Spatiotemporal Distribution of Urban Vibrancy and Neighborhood Attributes by Coupling Multi-Source Data: A Case of Nanshan District in Shenzhen by Liu Feng, Tang Zhong, Zhang Liang, Yu Lingmin, Liu Ke

“…Systematically incorporating a multidimensional set of neighborhood factors, including human vision, functionality, morphology, location, and street configuration, and utilizing spatial regression models in resonance with advanced algorithms facilitates a more profound comprehension of the spatiotemporal differentiation of urban vibrancy within urban spaces and the driving or inhibiting factors involved. …”
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Artificial Intelligence in the Diagnostic Use of Transcranial Doppler and Sonography: A Scoping Review of Current Applications and Future Directions by Giuseppe Miceli, Maria Grazia Basso, Elena Cocciola, Antonino Tuttolomondo

“…AI, particularly machine learning and deep learning algorithms, has emerged as a transformative tool to address these challenges by automating image acquisition, optimizing signal quality, and enhancing diagnostic accuracy. …”
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