DistB-Condo: Distributed Blockchain-Based IoT-SDN Model for Smart Condominium by Anichur Rahman, Md. Jahidul Islam, Ziaur Rahman, Md. Mahfuz Reza, Adnan Anwar, M. A. Parvez Mahmud, Mostofa Kamal Nasir, Rafidah Md. Noor

“…Eventually, this article evaluates the performance of the proposed architecture using different parameters (e.g., throughput, packet arrival rate, and response time). …”
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Machine learning techniques for predicting the peak response of reinforced concrete beam subjected to impact loading by Ali Husnain, Munir Iqbal, Hafiz Ahmed Waqas, Mohammed El-Meligy, Muhammad Faisal Javed, Rizwan Ullah

“…A set of 145 experimental data points from 12 different sources is used to train and evaluate these machine learning models. …”
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Capabilities of BIOMASS Three-Baseline PolInSAR Mode for the Characterization of Tropical Forests by Yanzhou Xie, Laurent Ferro-Famil, Yue Huang, Thuy Le Toan, Jianjun Zhu, Haiqiang Fu, Peng Shen

“…In this study, the capabilities of three-baseline PolInSAR in BIOMASS configuration and the spaceborne system-induced impacts are systematically evaluated. First, the BIOMASS data were simulated using the airborne P-band SAR acquisitions collected over two different tropical forests in Paracou, French Guiana, and Mondah, Gabon. …”
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Development of a Hyperspectral Imaging Protocol for Painting Applications at the University of Seville by Giovanna Vasco, Hélène Aureli, Isabel Fernández-Lizaranzu, Javier Moreno-Soto, Anabelle Križnar, Rubén Parrilla-Giraldez, Emilio Gómez-González, Miguel Angel Respaldiza Galisteo

“…However, a considerable limitation was given by redundant and time-consuming features, with the necessary application of statistical algorithms and image-processing tools to extract relevant information. …”
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Deep Learning for Ultrasonographic Assessment of Temporomandibular Joint Morphology by Julia Lasek, Karolina Nurzynska, Adam Piórkowski, Michał Strzelecki, Rafał Obuchowicz

“…The TMJ space width measurement algorithm demonstrated minimal bias, with a mean difference of 0.08 mm and a mean absolute error of 0.18 mm compared to reference measurements. …”
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Machine learning model for prediction of palliative care phases in patients with advanced cancer: a retrospective study by Junchen Guo, Yunyun Dai, Sishan Jiang, Junqingzhao Liu, Xianghua Xu, Yongyi Chen

“…The Gradient Boosting Decision Tree in the machine learning algorithm to establish a palliative care phase prediction model and evaluated the prediction performance of this model. …”
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Addressing Spatial Variability in Estimating Cover Management Factor of Soil Erosion Models using Geoinformatics: A Case Study of Netravati Catchment, Karnataka, India by Waleed Makhdumi, Shwetha H. R., G. S. Dwarakish, Jagadeesha B. Pai

“…This study aims to improve the accuracy of C factor estimates for the Netravati catchment present in the Western Ghats and Coastal Plains of India by using the Random Forest Algorithm and Sentinel 2 satellite data. The research examined five commonly used Normalized Difference Vegetation Index (NDVI) based C factor estimating equations and found that they inadequately represented local vegetation dynamics in the study area. …”
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A Shared Control Method of Multiobjective Motion Fusion for Surgical Robot by Xilin Xiao, Xiaojian Li, Hangjie Mo, Yudong Shi, Jing Fang, Ling Li, Bo Ouyang, Shanlin Yang

“…In addition, a state feedback mechanism with prediction and evaluation model is developed to balance the control inputs of different control objectives. …”
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Is human-like decision making explainable? Towards an explainable artificial intelligence for autonomous vehicles by Jiming Xie, Yan Zhang, Yaqin Qin, Bijun Wang, Shuai Dong, Ke Li, Yulan Xia

“…These findings have the potential to inform ongoing research on brain-like neural learning and could function as a catalyst for developing swifter and more potent algorithmic solutions in the realm of intelligent transportation.…”
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Digital and online symptom checkers and health assessment/triage services for urgent health problems: systematic review by Andrew Booth, Duncan Chambers, Anna J Cantrell, Maxine Johnson, Louise Preston, Susan K Baxter, Janette Turner

“…Diagnostic accuracy varied between different systems but was generally low. Algorithm-based triage tended to be more risk averse than that of health professionals. …”
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Data-driven cluster analysis on the association of aging, obesity and insulin resistance with new-onset diabetes in Chinese adults: a multicenter retrospective cohort study by Yazhi Wang, Mingkang Zhang, Peng Wang

“…After clustering, multivariate Cox proportional hazards regression analysis was used to evaluate and compare the risk of diabetes incidence among different clusters.ResultsThe study population comprising 12,607 subjects was clustered into four distinct groups: Cluster 1 (metabolic health cluster), Cluster 2 (low HDL-C cluster), Cluster 3 (old age and mild metabolic disorder cluster), and Cluster 4 (severe obesity and insulin resistance cluster). …”
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Modeling Worldwide Tree Biodiversity Using Canopy Structure Metrics from Global Ecosystem Dynamics Investigation Data by Jin Xu, Kjirsten Coleman, Volker C. Radeloff, Melissa Songer, Qiongyu Huang

“…Using Forest Global Earth Observatory (ForestGEO) data, we developed three models using the random forest algorithm to predict global tree species richness across climate zones, including a dynamic habitat index (DHI)-only model, a GEDI-only model, and a combined GEDI-DHI model. …”
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A model of indoor thermal condition based on traditional acehnese houses using artificial neural network by Muslimsyah, Abdul Munir, Yuwaldi Away, Abdullah, Teuku Yuliar Arif, Andri Novandri

“…The study employs an ANN (Artificial Neural Network) algorithm to predict thermal condition parameters including indoor: temperature, humidity, and wind speed. …”
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Multi-scenario analysis of green water resource efficiency under carbon emission constraints in the Chengdu-Chongqing urban agglomeration, China: A system dynamics approach by Keyao Yu, Zhigang Li

“…These scenarios are used to simulate and predict different development paths and evaluate the impact of various key indicators on GWRE. …”
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Towards an automated protocol for wildlife density estimation using camera‐traps by Andrea Zampetti, Davide Mirante, Pablo Palencia, Luca Santini

“…Here, we assessed the capability of two camera‐trap based models to provide robust density estimates when image classification is carried out by machine learning algorithms. We simulated density estimation with Camera‐Trap Distance Sampling (CT‐DS) and Random Encounter Model (REM) under different scenarios of automated image classification. …”
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Profile of the HIV epidemic in Cape Verde: molecular epidemiology and drug resistance mutations among HIV-1 and HIV-2 infected patients from distinct islands of the archipelago. by Isabel Inês M de Pina-Araujo, Monick L Guimarães, Gonzalo Bello, Ana Carolina P Vicente, Mariza G Morgado

“…Algorithm Homepage, respectively. Among the 221 patients (169 [76.5%] HIV-1, 43 [19.5%] HIV-2 and 9 [4.1%] HIV-1/HIV-2 co-infections), 67% were female. …”
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Enhancing Drought Forecast Accuracy Through Informer Model Optimization by Jieru Wei, Wensheng Tang, Pakorn Ditthakit, Jiandong Shang, Hengliang Guo, Bei Zhao, Gang Wu, Yang Guo

“…The performance of these models was evaluated using the root mean square error (RMSE), Nash–Sutcliffe efficiency coefficient (NSE), and Mean Absolute Error (MAE). …”
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An Enhanced Framework for Assessing Pluvial Flooding Risk with Integrated Dynamic Population Vulnerability at Urban Scale by Xinyi Shu, Chenlei Ye, Zongxue Xu, Ruting Liao, Pengyue Song, Silong Zhang

“…This study uses Jinan, a typical foothill plain city in Shandong Province, as a case study to compare the performance of differential evolution (DE), genetic algorithm (GA), and particle swarm optimization (PSO) in calibrating the SWMM. …”
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Predicting breeding values in Murrah buffaloes using random regression models by ANAND JAIN, ASHISH RANJAN, I D GUPTA, H K SINGH

“…Various random regression models with different order of Legendre polynomials for permanent environmental and genetic effects were constructed to evaluate Murrah buffaloes under field condition. …”
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Enhancing weld quality of novel robotic-arm arc welding: Vision-based monitoring, real-time control seam tracking by Aman Sharma, Rishabh Chaturvedi, Kamal Sharma, Saad Abrahim Binhowimal, Jayant Giri, T. Sathish

“…New software is used for welding seam monitoring to examine different features of robotic arm arc welding. The software system comprises several components: welding voltage regulation, analytical parameters, image capture or analysis using enhanced algorithms, weld experts’ database, robot coordination, and trajectory operations management. …”
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