Modeling the latent impacts of extreme floods on indoor mold spores in residential buildings: Application of machine learning algorithms by M. Pakdehi, E. Ahmadisharaf, P. Azimi, Z. Yan, Z. Keshavarz, C. Caballero, J.G. Allen

“…These impacts can be direct and indirect. Past research has focused more on the former impacts. Of the indirect impacts, those on mold growth in indoor environments that affect human respiratory health (e.g. asthma) have received limited attention. …”
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IMPLEMENTATION OF THE DBSCAN ALGORITHM FOR CLUSTERING STUNTING PREVALENCE TYPOLOGY IN WEST JAVA, CENTRAL JAVA, AND EAST JAVA REGIONS by Bagus Sumargo, Kadir Kadir, Dena Safariza, Munawar Asikin, Dania Siregar, Nilam Novita Sari, Danu Umbara, Rizky Hilmianto, Robert Kurniawan, Irman Firmansyah

“…This study aims to group districts/cities in these provinces based on factors that influence stunting using the DBSCAN method (there has been no previous research using this method for this case), so the typology of stunting prevalence is implied. …”
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The Impact of Image Spatial Resolution and Machine Learning Algorithm on Urban Vegetation Classification: Focus on Data Loss and Misclassification by Alexander Takele Muleta, Julius Bamah, Shirley Bushner, Oz Kira

“…High-resolution remote sensing imagery is widely used for urban vegetation classification, but the influence of spatial resolution on mapping accuracy remains underexplored. This research investigates the classification efficiency of various satellite resolutions and machine learning algorithms, assessing the impact of spatial resolution on urban vegetation classification using WorldView-2 imagery resampled from 0.5 to 5 and 10 m. …”
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Ethnic Architectural Heritage Identification Using Low-Altitude UAV Remote Sensing and Improved Deep Learning Algorithms by Ting Luo, Xiaoqiong Sun, Weiquan Zhao, Wei Li, Linjiang Yin, Dongdong Xie

“…Taking Buyi architecture in China as an example, this paper proposes a minority architectural heritage identification method that combines low-altitude unmanned aerial vehicle (UAV) remote sensing technology and an improved deep learning algorithm. First, UAV images are used as the data source to provide high-resolution images for research on ethnic architecture recognition and to solve the problems associated with the high costs, time consumption, and destructiveness of traditional methods for ethnic architecture recognition. …”
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Optimizing energy constrained target localization and tracking with radial bias and seeker optimization algorithms in wireless sensor networks by S. Yazhinian, S. Famila, P. Jose, Mahendar A, Sofia R

“…It is seen that the proposed RadB_SOA achieves 12.4 % of transmission error, 14.6 % of ranging error, 96.3 % of localization coverage, 98.65 % of PDR, and 21.56 % of energy consumption. • The Radial Bias-Seeker Optimization Algorithm (RadB_SOA) suggested enhances the precision in target localization and optimizes energy usage in wireless sensor networks. • Simulation outcomes reveal improved tracking accuracy, minimized transmission and ranging errors, as well as increased localization coverage over current techniques. • The research presents an extensive evaluation of particle count fluctuations in RBSO, demonstrating enhanced positioning speed and precision with network efficiency.…”
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Multiple-to-single maximum power point tracking for empowering conventional MPPT algorithms under partial shading conditions by Njimboh Henry Alombah, Ambe Harrison, Wulfran Fendzi Mbasso, Hamid Belghiti, Hilaire Bertrand Fotsin, Pradeep Jangir, Saad F. Al-Gahtani, Z. M. S. Elbarbary

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Analysis of phenotypic manifestations of connective tissue dysplasia in adult patients with osteogenesis imperfecta and development of a diagnostic algorithm by D. I. Valeeva, R. I. Khusainova, L. N. Khusainova, M. M. Khafizov, A. V. Tyurin

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Research on Nonlinear Error Compensation and Intelligent Optimization Method for UAV Target Positioning by Yinglei Li, Qingping Hu, Shiyan Sun, Wenjian Ying, Xiaojia Yan

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Research on High-Reliability Energy-Aware Scheduling Strategy for Heterogeneous Distributed Systems by Ziyu Chen, Jing Wu, Lin Cheng, Tao Tao

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Application of Machine Learning Algorithms for Predicting the Dynamic Stiffness of Rail Pads Based on Static Stiffness and Operating Conditions by Isaac Rivas, Jose A. Sainz-Aja, Diego Ferreño, Víctor Calzada, Isidro Carrascal, Jose Casado, Soraya Diego

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Evaluation and Improvement of Ocean Color Algorithms for Chlorophyll-<i>a</i> and Diffuse Attenuation Coefficients in the Arctic Shelf by Yubin Yao, Tao Li, Qing Xu, Xiaogang Xing, Xingyuan Zhu, Yubao Qiu

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Long and short term fault prediction using the VToMe-BiGRU algorithm for electric drive systems by Lihui Zheng, Xu Fan, Zongshan Kang, Xinjun Jin, Wenchao Zheng, Xiaofen Fang

“…In order to prevent serious faults in the short-term leading to potential accidents, this paper proposes an innovative approach for embedding the Token Merging (ToMe) algorithm into the Vision Transformer (ViT), called the VToMe algorithm and combining it with the Bidirectional Gated Recurrent Unit (BiGRU) network to form the VToMe-BiGRU architecture for electric drive system fault prediction. …”
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A Bayesian-Optimized Surrogate Model Integrating Deep Learning Algorithms for Correcting PurpleAir Sensor Measurements by Masrur Ahmed, Jing Kong, Ningbo Jiang, Hiep Nguyen Duc, Praveen Puppala, Merched Azzi, Matthew Riley, Xavier Barthelemy

“…This study introduces BaySurcls, a Bayesianoptimised surrogate model integrating deep learning (DL) algorithms to improve the PurpleAir sensor PM2.5 (PAS2.5) measurement accuracy. …”
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An algorithm for infectious screening of corneal donors in eye tissue bank of the Fyodorov Eye Microsurgery Federal State Institution by S.A. Borzenok, M.Yu. Gerasimov, Yu.A. Komakh, M.Kh. Khubetsova, H.D. Tonaeva, L.M. Malikova, P.I. Plaksa

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Gradient-Enhanced Kriging-Based Parallel Efficient Global Optimization Algorithm and Its Application in Aerodynamic Shape Optimization by Hang Fu, Qingyu Wang, Takuji Nakashima, Asahi Kawasaki, Chenguang Lai, Keigo Shimizu, Rahul Bale, Makoto Tsubokura

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Cervical Cancer Prediction Based on Imbalanced Data Using Machine Learning Algorithms with a Variety of Sampling Methods by Mădălina Maria Muraru, Zsuzsa Simó, László Barna Iantovics

“…Cervical cancer affects a large portion of the female population, making the prediction of this disease using Machine Learning (ML) of utmost importance. ML algorithms can be integrated into complex, intelligent, agent-based systems that can offer decision support to resident medical doctors or even experienced medical doctors. …”
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Effect of the exposure to brominated flame retardants on hyperuricemia using interpretable machine learning algorithms based on the SHAP methodology. by Yu Cai, Xi-Ru Huang, Sheng-Jia Wang, Ying-Chao Liang, De-Liang Liu, Shu-Fang Chu, Hui-Lin Li

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Research and Ground Verification of the Force Compliance Control Method for Space Station Manipulator by Bingshan Hu, Huanlong Chen, Liangliang Han, Hongliu Yu

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A pulmonary hypertension targeted algorithm to improve referral to right heart catheterization: A machine learning approach by Paola Argiento, Anna D'Agostino, Rossana Castaldo, Monica Franzese, Matteo Mazzola, Ekkehard Grünig, Lavinia Saldamarco, Valeria Valente, Alessandra Schiavo, Erica Maffei, Davide Lepre, Antonio Cittadini, Eduardo Bossone, Michele D'Alto, Luna Gargani, Alberto Maria Marra

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A novel TID + IDN controller tuned with coatis optimization algorithm under deregulated hybrid power system by Geetanjali Dei, Deepak Kumar Gupta, Binod Kumar Sahu, Mohit Bajaj, Vojtech Blazek, Lukas Prokop

“…The controller’s parameters are optimized using an advanced Coatis Optimization Algorithm (COA). High effective efficiency and absence of control parameters are the key advantages of Coatis Optimization Algorithm. …”
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