Balancing complexity and accuracy for defect detection on filters with an improved RT-DETR by Maoyuan Zhang, Xiaojuan Wei, Guojun Liu, Mengxu Chen, Chunxia Zhao, Yingxiao Liu, Zhikang Bao, Yunfeng Guo, Run An, Pengcheng Zhao

“…However, existing defect detection algorithms often struggle to balance between detection accuracy and the computational efficiency required for industrial deployment. …”
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A Holistic Solution for Supporting the Diagnosis of Historic Constructions from 3D Point Clouds by Luis Javier Sánchez-Aparicio, Rubén Santamaría-Maestro, Pablo Sanz-Honrado, Paula Villanueva-Llauradó, Jose Ramón Aira-Zunzunegui, Diego González-Aguilera

“…This tool incorporates state-of-the-art algorithms for the segmentation and analysis of construction systems and damage. …”
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Optimal reception of multiple phase shift keying and quadrature amplitude modulation signals with non-coherent processing of harmonic interference by G. V. Kulikov, T. T. Do, A. A. Lelyukh, V. D. Nguyen

“…Therefore, the development of algorithms for compensating the influence of such forms of interference is an urgent task. …”
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Instance Assignment Coverage Feature for Operation Control of SAT Solver by Zhihui Li, Shuwei Chen, Guanfeng Wu, Yang Xu

“…The CoverT metric provided unique insight into the characteristics of the instance structure, allowing dynamic adaptation of branching heuristics in our proposed Deep Restart-Enhanced Conflict-Driven Clause Learning algorithm framework (DR-CDCL). Experimental validation in 2021–2023 SAT Competition benchmarks demonstrated statistically significant improvements: 14 additional solved instances for satisfiable cases (352 $$\rightarrow $$ → 366, $$p<0.05$$ p < 0.05 via McNemar’s test). 7.3% reduction in average runtime for SAT instances under the 5000 s timeout threshold. …”
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GIS-based framework for assessing priority locations for blue-green infrastructure implementation in urban areas by Ewelina Pochodyła-Ducka, Paweł Burandt, Katarzyna Glińska-Lewczuk

“…The analysis highlighted a reduction in surface permeability driven by urban expansion from 2006 to 2018. …”
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Sleep stages classification based on feature extraction from music of brain by Hamidreza Jalali, Majid Pouladian, Ali Motie Nasrabadi, Azin Movahed

“…A total of 19 features are extracted from the sequence of notes and fed into feature reduction algorithms; the selected features are applied to a two-stage classification structure: 1) the classification of 5 classes (merging S1 and REM-S2-S3-S4-W) is made with an accuracy of 89.5 % (Cap sleep database), 85.9 % (Sleep-EDF database), 86.5 % (Sleep-EDF expanded database), and 2) the classification of 2 classes (S1 vs. …”
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A Comparison of Effective doses for the 16, 64, and 128-slice Computed Tomography Scanners: A First Health Cluster Study in Riyadh by Mansour Al Moudi, Sultan Al Dosari, Abdullah Ibrahim Al Hussain, Mazen Abounassif

“…When performing routine CT scans with low-end CT scanner systems, dose-reduction strategies should be considered.…”
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Semantic SLAM using laser-vision data fusion: Enhancing autonomous navigation in unstructured environments by Ning Chen, Dong Wei, Dongsheng Lin, Linhan Lin

“…For the fusion of visual and laser information, NN-SLAM demonstrated a reduction in filter processing time by 0.2440 ms and 3.6497 ms on the KITTI 0011 and 0093 datasets, respectively, when compared to the Visual-Lidar Odometry and Mapping (ALOAM) algorithm. …”
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Characterization and Stability Analysis of Rock Mass Discontinuities in Layered Slopes: A Case Study from Fushun West Open-Pit Mine by Ming Li, Zhanguo Xiu, Jianhua Han, Fanzhen Meng, Feili Wang, Hongguang Ji

“…., 3D point cloud data) in this study. After the noise reduction processing of the generated rock slope model, the orientation and dominant grouping of the rock mass discontinuities were calculated by the KNN (K-nearest neighbor) search and the PCA (principal component analysis) algorithms, and the calculated results are calibrated with manual measurements in the local slope area. …”
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Hybrid Adaptive Sheep Flock Optimization and Gradient Descent Optimization for Energy Management in a Grid-Connected Microgrid by Sri Harish Nandigam, Krishna Mohan Reddy Pothireddy, K. Nageswara Rao, Surender Reddy Salkuti

“…Results demonstrate the efficiency of the proposed hybrid algorithm, achieving substantial improvements in energy efficiency and cost reduction compared to traditional methods like interior point optimization, gradient descent, branch and bound, and a population-based algorithm named Golden Jackal optimization. …”
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HouseGanDi: A Hybrid Approach to Strike a Balance of Sampling Time and Diversity in Floorplan Generation by Azmeraw Bekele Yenew, Beakal Gizachew Assefa, Elefelious Getachew Belay

“…To address these issues, various techniques such as regualrization techniques, architectural modifications, and optimization algorithms, have been employed. However, existing techniques still struggle to balance both sampling time and diversity simultaneously. …”
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A Learning Emotion Recognition Model Based on Feature Fusion of Photoplethysmography and Video Signal by Xiaoliang Zhu, Zili He, Chuanyong Wang, Zhicheng Dai, Liang Zhao

“…Secondly, video-based emotion recognition algorithms may witness a reduction in accuracy within spontaneous scenes due to variations, occlusions, and uneven lighting conditions, etc. …”
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Automating the Design of Scalable and Efficient IoT Architectures Using Generative Adversarial Networks and Model-Based Engineering for Industry 4.0 by William Villegas-Ch, Jaime Govea, Diego Buenano-Fernandez, Aracely Mera-Navarrete

“…Traditional approaches, such as heuristic and genetic algorithms, have proven insufficient in automating and optimizing large-scale IoT configurations, resulting in a high design and validation time cost. …”
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Personalizing mHealth Interventions for Occupational Stress: Protocol for a Randomized Pilot Study by Beatrix Kunas, Oliver Jung, Christoph Schranz, Mathias Schmoigl-Tonis, Manuela Ploessnig, Anton-Rupert Laireiter

“…The app offered interventions based on algorithms, which altered the probability of their selection after learning from the data, thereby personalizing the user experience. …”
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Autonomous detection of nail disorders using a hybrid capsule CNN: a novel deep learning approach for early diagnosis by Gunjan Shandilya, Sheifali Gupta, Salil Bharany, Ateeq Ur Rehman, Upinder Kaur, Hafizan Mat Som, Seada Hussen

“…Based on this, we build an initial baseline CNN model, which is then further advanced by the introduction of the Hybrid Capsule CNN model by the reduction of space hierarchy deficiencies of the classic CNN model. …”
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Parvovirus B19 Infection due to over Immunosuppression in Kidney Transplant Recipients: Case Reports and Literature Review by Abdulrahman Altheaby, Malak Alotaibi, Nuha Alajlan, Ala Alshareef, Mohammed Alruwaymi, Ghaleb Aboalsamh, Mohammed F. Shaheen, Mohammed Alzunitan, Ziad Arabi

“…The limited data available regarding consensus on screening algorithms and indications in donors and recipients prior to kidney transplantation makes diagnosis and management challenging. …”
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Adaptive AI-enhanced computation offloading with machine learning for QoE optimization and energy-efficient mobile edge systems by Dinesh Kumar Nishad, Vandna Rani Verma, Pushkar Rajput, Sandeep Gupta, Anurag Dwivedi, Dharti Raj Shah

“…The AAEO framework achieves up to a 35% improvement in QoE and a 40% reduction in energy consumption, while maintaining stable task completion times with only a 12% increase under maximum user load. …”
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Comprehensive analysis of total knee arthroplasty kinematics and functional recovery: Exploring full-body gait deviations in patients with knee osteoarthritis. by Xavier Gasparutto, Alice Bonnefoy-Mazure, Michael Attias, Katia Turcot, Stéphane Armand, Hermès H Miozzari

“…Patients were clustered by applying K-means algorithms on full-body kinematic features of gait before surgery. …”
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Results of clinical developments of early triple negative breast cancer drug treatment: ASCO-2022 by D. A. Andreev, A. A. Zavyalov

“…In Russia, state tasks have been set within the framework of the Federal project “Fight against cancer”, which provide for a significant reduction in mortality from neoplasms, including by improving the quality and effectiveness of drug treatment.Materials and methods. …”
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Multiobjective Optimization-Based Hyperspectral Unsupervised Band Selection for Anomaly Detection by Shihui Liu, Bing Xue, Meiping Song, Haimo Bao, Mengjie Zhang

“…Band selection (BS) is a critical topic in hyperspectral image dimensionality reduction, focusing on identifying representative bands that can convey the essential information of the full bands without significant loss. …”
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