Vision-Based 6D Pose Analytics Solution for High-Precision Industrial Robot Pick-and-Place Applications by Balamurugan Balasubramanian, Kamil Cetin

“…It is experimentally verified that the proposed analytical solution outperforms the hybrid-based method (YOLO-v8 combined with PnP/RANSAC algorithms). Experimental results across four distinct picking scenarios demonstrate the proposed solution’s superior accuracy, with position errors under 2 mm, orientation errors below 1°, and a perfect success rate in pick-and-place tasks.…”
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A Methodology for Optimizing the Management of Spent Fuel of Nuclear Power Plants Using Dry Storage Casks by Ian B. Gomes, Pedro L. Cruz Saldanha, Antonio Carlos M. Alvim

“…The objective of this study is to propose a methodology that, using optimization algorithms, determines the ideal time for removal of the fuel assemblies from the spent fuel pool and to place them into dry casks for intermediate storage. …”
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Chaotic billiards optimized hybrid transformer and XGBoost model for robust and sustainable time series forecasting by Reham H. Mohammed, Asmaa Mohamed El-saieed

“…The use of CBO ensures efficient convergence with minimal parameter tuning, making the model suitable for large-scale datasets compared to conventional optimizers, including Adam, Particle Swarm Optimization (PSO) and Genetic Algorithms (GA). …”
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Inversion model of stress state reconstruction for geological hazard pipelines based on digital twin by Xue Luning, Tian Mingliang, Zhao Juncheng

“…The mechanical state of the physical pipeline is mapped in real time by the digital twin, the numerical simulation and multi-source monitoring data are integrated, and the parameters of the twin model are dynamically optimized by combining the optimization algorithms of Particle Swarm Optimization (PSO) and Support Vector Machine (SVM), so as to realize the real-time prediction of the pipeline stress state and the dynamic updating of the disaster scenario. …”
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Adaptive continuous-discrete variables optimization for active learning with extremely sparse data in optical material design by Serang Jung, Eungkyu Lee

“…In the adaptive scheme, we examine the performance of three machine learning (ML) models—Gaussian process regression, factorization machines (FM), and field-aware FM—for a surrogate function, and ML model-specific optimization algorithms such as discrete particle swarm optimization, artificial bee colony optimization, and simulated annealing. …”
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determination of dust using remote sensing techniques and numerical simulation by Razieh Pilehvaran, Zahra Rastgu, Sara Karami, Behrooz Moradpour

“…At the first step, in order to detect and observe the intensity of the dust concentration over the study area, the MODIS AOD product from the Deep blue and Dark target algorithms has been analyzed using the ENVI software, and the generated images have been displayed in the ArcGIS software. …”
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Advances in Multi-Source Navigation Data Fusion Processing Methods by Xiaping Ma, Peimin Zhou, Xiaoxing He

“…In recent years, the field of multi-source navigation data fusion has witnessed substantial advancements, propelled by the rapid development of multi-sensor technologies, Artificial Intelligence (AI) algorithms and enhanced computational capabilities. …”
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Porous Models for Enhanced Representation of Saturated Curly Hairs: Simulation and Learning by Jong-Hyun Kim, Jung Lee

“…Additionally, we propose to extend the learning representation solver through both numerical simulation algorithms and AI-based approaches.…”
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In the Refractory Hypertension “Labyrinth”. Focus on Primary Hyperaldosteronism by O. V. Tsygankova, T. I. Batluk, L. D. Latyntseva, E. V. Akhmerova, N. M. Akhmedzhanov

“…Primary hyperaldosteronism is an existence of a functional autonomous source with increased aldosterone production (full or partial) in relation to the renin-angiotensin system. …”
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Numerical Investigation of Large Wood Evolution Characteristics Transported by Flash Floods by SONG Siyuan, FEI Gaogao, WANG Xiekang

“…The two-way coupling algorithm can reflect the influence of large wood on water flow, thereby allowing the analysis of backwater rise problems caused by logjams. …”
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adm: An R package for constructing abundance‐based species distribution models by Admir Cesar deOliveira Junior, Santiago José Elías Velazco

“…To date, adm provides 35 functions in three categories, (i) modelling: to tune, fit and validate models with nine different algorithms, with a suite of possible model‐specific hyperparameters; (ii) post‐modelling: to predict abundance across space and construct partial dependence plots to explore the relationships between abundance and environmental predictors; and (iii) miscellaneous tools: to support the workflow in all steps, including data handling, transformations and hyperparameter selection. …”
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Near-Infrared Spectroscopy Combined With Support Vector Machine Model to Realize Quality Control of Ginkgolide Production by Lei Liu, Jun Wang, Haiyi Bian, Ahmed N. Abdalla

“…This study addresses this concern by leveraging chemometric models, specifically partial least squares (PLS), support vector machine (SVM), and random forest, in conjunction with near-infrared spectroscopy (NIRS) data. …”
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Unbiased machine learning-assisted approach for conditional discretization of human performances by Thepparit Banditwattanawong, Masawee Masdisornchote

“…Currently, the only statistical method available for norm-referenced performance discretization is Z score, which merely addresses partial conditions. To achieve a fully conditionally norm-referenced performance discretization, this article proposes four novel approaches enlisting a multi-modal technique that incorporates unsupervised machine-learning algorithms and a heuristic method as well as a novel decision function ensuring conditional unbiasedness. …”
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Surgical treatment of massive rotator cuff tears (literature review) by D. V. Menshova

“…Despite the large number of methods for the treatment of massive rotator cuff tears, there are no clear algorithms for managing patients and choosing one or another surgical tactics. …”
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Advanced Ai Tools for Predicting Mechanical Properties of Self-Compacting Concrete by AGRAWAL Achal, CHANDAK Narayan

“…Partial mutual information for selection and establishment of the degree of association of variables was used to aid in better attainment of results obtained through predictive models. …”
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Beyond purchase patterns: harnessing predictive analytics to anticipate unarticulated consumer needs by Khaled Alshaketheep, Hind Al-Ahmed, Ahmad Mansour

“…The results underscore the importance of integrating human-centered design with algorithmic precision to translate predictive insights into actionable business value.…”
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Secret sharing in a special linear group by V. I. Yanchevskiĭ, I. A. Havarushka, G. V. Matveev

“…A rigorous mathematical justification is given for the correctness of the algorithms for generating partial secrets and restoring the main secret in the special linear group over the ring of integers. …”
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Acute Appendicitis Remains a Great Mimicker – The Pitfalls in the Differential Diagnosis and Tactics - A Case Report by Georgi Popivanov, Marina Konaktchieva, Vladimir Vasilev, Kirien Kjossev, Marin Penkov, Dimitar Penchev

“…All emergency surgeons should also be familiar with the scenario of unexpected findings at laparotomy, especially with the management of CD and the algorithms for treatment of appendiceal malignancies. …”
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Simulation of plutonium-aerosol rise under chemical explosion conditions by Hongyi Yao, Yonggang Huo, Xingfu Cai, Sufen Li, Haowei Wang

“…Based on the Chapman model and Levenberg–Marquardt algorithm, the simulation results of the plutonium aerosol-cloud height were fitted to obtain it as a function of time. …”
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New sizes of complete (k, 4)-arcs in PG(2,17) by Zainab Shehab Hamed

“…               In this paper, the packing problem for complete (  4)-arcs in  is partially solved. The minimum and the maximum sizes of complete (  4)-arcs in  are obtained. …”
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