A Novel Approach to Optimize Key Limitations of Azure Kinect DK for Efficient and Precise Leaf Area Measurement by Ziang Niu, Ting Huang, Chengjia Xu, Xinyue Sun, Mohamed Farag Taha, Yong He, Zhengjun Qiu

“…An efficient pixel filter-based depth inpainting algorithm was then designed to inpaint void and flying pixels and restore consistent, high-confidence depth values within semantic regions. …”
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Analysis and 3D modelling of percolated conductive networks in nanoparticle-based thin films by Stanislav Haviar, Benedikt Prifling, Tomáš Kozák, Kalyani Shaji, Tereza Košutová, Šimon Kos, Volker Schmidt, Jiří Čapek

“…Using the experimental data, virtual films were generated through a data-driven stochastic 3D microstructure model that is based on a sphere packing algorithm, where the particle size distribution, porosity and vertical density profile are taken into account. …”
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A multi-stage weakly supervised design for spheroid segmentation to explore mesenchymal stem cell differentiation dynamics by Arash Shahbazpoor Shahbazi, Farzin Irandoost, Reza Mahdavian, Seyedehsamaneh Shojaeilangari, Abdollah Allahvardi, Hossein Naderi-Manesh

“…To quantitatively evaluate our algorithm, extensive experiments were conducted using available annotated data, confirming the reliability and robustness of our method. …”
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A Lightweight Network for Ship Detection in SAR Images Based on Edge Feature Aware and Fusion by Yuming Li, Jin Liu, Xingye Li, Xiliang Zhang, Zhongdai Wu, Bing Han

“…Finally, we propose a selective quantization algorithm based on a bit-width selection mechanism to reduce model memory usage without compromising performance. …”
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Identifying and prioritizing appropriate strategies for customer loyalty in a mass environment (case study: clothing house) by Zahra Joorbonyan, Ali Sorourkhah, Seyyed Ahmad Edalatpanah

“…The present study aims to provide a combined approach for prioritizing customer loyalty strategies.Methodology: This research uses a matrix-based approach to robustness analysis, which can deal with complexity and uncertainty. The proposed algorithm combines it with strategic planning tools (strategies derived from strategic objectives and SWOT analysis) for prioritizing and selecting strategies. …”
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Classifying Sunn Pest Damaged and Healthy Wheat Grains Across Different Species with YOLOV8 and Vision Transformers by Melike Çolak, Özgü Özkan, Ali Berkol, Nergis Pervan Akman, Murat Ardıç, Okan Sezer, Nazife Gözde Ayter Arpacıoğlu, Zekiye Budak Başçiftçi, Murat Olgun

“…Over time, the number of researchers focusing on this problem by using various machine learning algorithms and image processing techniques has increased. …”
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Joint Effect of CFH and ARMS2/HTRA1 Polymorphisms on Neovascular Age-Related Macular Degeneration in Chinese Population by Kai Fang, Pei Gao, Jun Tian, Xueying Qin, Wenzhen Yu, Juan Li, Qing Chen, Lvzhen Huang, Dafang Chen, Yonghua Hu, Xiaoxin Li

“…We explored the potential interactions among gene variants using generalized multifactor dimensionality reduction (GMDR) algorithm and the method to measure the departure from the additivity model. …”
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Draft genome dataset of Streptomyces griseoincarnatus strain R-35 isolated from tidal pool sedimentsMendeley DataNCBI by Danielle Dana Mitchell, Jo-Marie Vreulink, Alaric Prins, Marilize Le Roes-Hill

“…The phylogenomic positioning of S. griseoincarnatus strain R-35 was determined using the Type Strain Genome Server (TYGS) and was found to be related to S. griseoincarnatus JCM 4381T, with a digital DNA-DNA hybridisation (dDDH) value of 84.1%, and an OrthoANIu value of 98.22%. The CARD RGI algorithm on Proksee predicted the presence of 6,107 antimicrobial resistance (AMR) features, 27 biosynthetic gene clusters (BGCs) were predicted using antiSMASH, while 189 carbohydrate-active enzymes (CAZymes) were predicted using dbCAN3. …”
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Prediction of Multiple Organ Failure Complicated by Moderately Severe or Severe Acute Pancreatitis Based on Machine Learning: A Multicenter Cohort Study by Fumin Xu, Xiao Chen, Chenwenya Li, Jing Liu, Qiu Qiu, Mi He, Jingjing Xiao, Zhihui Liu, Bingjun Ji, Dongfeng Chen, Kaijun Liu

“…The adaptive boosting algorithm (AdaBoost) showed the best predictive performance with the highest AUC value (0.826; 95% confidence interval: 0.740 to 0.888). …”
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Machine learning-driven identification of critical gene programs and key transcription factors in migraine by Lei Zhang, Yujie Li, Yunhao Xu, Wei Wang, Guangyu Guo

“…The cell-type-specific expression (CELLEX) algorithm was employed to calculate specific expression profiles for each region, while non-negative matrix factorization (NMF) was applied to decompose gene programs within the single-cell data from these regions. …”
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A Study of the Star Clusters’ Population in the Giant Molecular Cloud G174+2.5 by Tatyana A. Permyakova, Giovanni Carraro, Anton F. Seleznev, Andrej M. Sobolev, Dmitry A. Ladeyschikov, Maria S. Kirsanova

“…To evaluate the reddening, we use both the NICEST algorithm and the Q -method. Both methods produce consistent extinction maps in the regions of the four studied clusters. …”
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Development of clinical decision support for patients older than 65 years with fall-related TBI using artificial intelligence modeling. by Biche Osong, Eric Sribnick, Jonathan Groner, Rachel Stanley, Lauren Schulz, Bo Lu, Lawrence Cook, Henry Xiang

“…We employed a conditional inference tree algorithm with bootstrap (B = 100) and grid search options to grow the decision tree and measure discrimination ability using the area under the curve (AUC) and calibration plots.…”
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Investigating LiDAR Metrics for Old-Growth Beech- and Spruce-Dominated Forest Identification in Central Europe by Devara P. Adiningrat, Andrew Skidmore, Michael Schlund, Tiejun Wang, Haidi Abdullah, Marco Heurich

“…To determine the important LiDAR standard and structural metrics in identifying old-growth forests, multicollinearity analysis using the variance inflation factor (VIF) approach was applied to identify and remove metrics with high collinearity, followed by the random forest algorithm to rank which LiDAR standard and structural metrics are important in old-growth forest classification. …”
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Career Development Center Berbasis Social Media Menggunakan Algoritma Gale-Shapley dan Framework Codeigniter by Rifky Syaripudin, Oman Komarudin, Intan Purnamasari

“…The modeling design uses UML (Unified Modeling Language) which is implemented using the Gale-Shapley Algorithm and Codeigniter Framework with Netbeans 7.4 IDE tools. …”
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Predictive model for determining the indications for automated 3D ultrasound for screening patients at low risk of developing breast tumors by A. E. Garanina, A. V. Kholin

“…The developed algorithms will help optimize screening and referral for additional examinations, which is of practical importance for improving diagnostics and optimizing healthcare resources.…”
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Using machine learning to predict outcomes following transcarotid artery revascularization by Ben Li, Naomi Eisenberg, Derek Beaton, Douglas S. Lee, Leen Al-Omran, Duminda N. Wijeysundera, Mohamad A. Hussain, Ori D. Rotstein, Charles de Mestral, Muhammad Mamdani, Graham Roche-Nagle, Mohammed Al-Omran

“…We developed machine learning (ML) algorithms that predict 1-year outcomes following TCAR. …”
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Measurement and Analysis of Gait Pattern during Stair Walk for Improvement of Robotic Locomotion Rehabilitation System by Sang-Eun Park, Ye-Ji Ho, Min Ho Chun, Jaesoon Choi, Youngjin Moon

“…The measured marker data were converted into joint kinematic data by using an algorithm that included resampling and normalization. …”
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A Parallel Image Denoising Network Based on Nonparametric Attention and Multiscale Feature Fusion by Jing Mao, Lianming Sun, Jie Chen, Shunyuan Yu

“…The experimental results showed that this paper’s algorithm had better objective indexes on all test sets and outperformed the comparison algorithms. …”
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Host-symbiont-gene phylogenetic reconciliation by Menet, Hugo, Trung, Alexia Nguyen, Daubin, Vincent, Tannier, Eric

“…Given three phylogenetic trees, we devise a Monte Carlo algorithm which samples evolutionary scenarios of symbionts and genes according to an approximation of their likelihood in the model. …”
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Understanding uncertainties in the satellite altimeter measurement of coastal sea level: insights from a round-robin analysis by F. Birol, F. Bignalet-Cazalet, M. Cancet, M. Cancet, J.-A. Daguze, W. Fkaier, E. Fouchet, E. Fouchet, F. Léger, C. Maraldi, F. Niño, M.-I. Pujol, N. Tran

“…Here, we take advantage of the recent availability of many new algorithms developed for altimetry sea level computation to quantify and analyze the uncertainties associated with the choice of algorithms when approaching the coast. …”
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