Mathematical modeling of food intake and insulin infusion in a patient with type 1 Ddabetes in closed loop by J. Manrique-Córdoba, J. D. Romero-Ante, A. Vivas, J.M. Vicente, J. M. Sabater-Navarro

“…The model was integrated into a closed-loop insulin regulation algorithm, in order to evaluate the performance of the model and the eficiency of closed-loop treatments, compared to open-loop therapies. …”
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Bioinformatics Analysis of Oxidative Stress-Related Genes and Immune Infiltration Patterns in Vitiligo by Yang M, Wang H, Zhang R

“…Additionally, two machine learning algorithms were employed to identify hub genes, perform enrichment analyses, and evaluate their correlation with immune infiltration.Results: A total of 415 Oxidative Stress-DEGs were identified in vitiligo, including 317 up-regulated and 98 down-regulated genes. …”
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Rice Plant Disease Detection using Convolutional Neural Networks by A. Bala Ayyappan, T. Gobinath, M. Kumar, A. Sivaramakrishnan

“…The CNN model is trained on images of different plant diseases, and various models are evaluated to determine the most effective one for disease identification. …”
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Comprehensive Modeling in Predicting Liquid Density of the Refrigerant Systems Using Least-Squares Support Vector Machine Approach by Jinya Cai, Haiping Zhang, Xinping Yu, Amir Seraj

“…A robust machine learning algorithm known as the least-squares support vector machine (LSSVM) model was used to predict the liquid densities of 48 different refrigerant systems. …”
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SMART DShot: Secure Machine-Learning-Based Adaptive Real-Time Timing Correction by Hyunmin Kim, Zahid Basha Shaik Kadu, Kyusuk Han

“…Statistical validation using Analysis of Variance confirms significant performance differences (F(3,1996) = 30.30, <i>p</i> < 0.001) with large effect sizes (Cohen’s d up to 4.57), where 64.6% of algorithm comparisons showed large practical significance. …”
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Power Quality Disturbance Classification Method Based on Unscented Kalman Filter and Kernel Extreme Learning Machine by Yanjun Jiao, Haoyu Cao, Linke Wang, Jiahui Wei, Yansong Zhu, Hucheng He

“…Considering the limitations of the traditional time–frequency domain method and the complexity of the optimization algorithm in extracting features, a novel algorithm is proposed to classify the PQDs in this paper, which is based on the unscented Kalman filter (UKF) and the kernel extreme learning machine (KELM). …”
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Finding a suitable chest x-ray image size for the process of Machine learning to build a model for predicting Pneumonia by Kriengsak Yothapakdee, Yosawaj Pugtao, Sarawoot Charoenkhun, Tanunchai Boonnuk, Kreangsak Tamee

“…The neural network algorithm achieved an accuracy rate of 87.00% across different image sizes. …”
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Deep Learning Method for Wetland Segmentation in Unmanned Aerial Vehicle Multispectral Imagery by Pakezhamu Nuradili, Ji Zhou, Guiyun Zhou, Farid Melgani

“…Our approach, involving meticulous image preprocessing, customized network architecture, and iterative training procedures, aims to refine wetland boundary delineation. The algorithm demonstrates strong segmentation results, including a mean pixel accuracy (MPA) of 90.35% and a mean intersection over union (MIOU) of 73.87% across different classes, with a pixel accuracy (PA) of 95.42% and an intersection over union (IOU) of 90.46% for the wetland class. …”
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A Novel Method to Compute the Contact Surface Area Between an Organ and Cancer Tissue by Alessandra Bulanti, Alessandro Carfì, Paolo Traverso, Carlo Terrone, Fulvio Mastrogiovanni

“…Tested on synthetic data, the algorithm showed minimal error and was evaluated on data from 82 patients. …”
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Intelligent policy framework: Natural resource conservation, knowledge and big data analytics by Nina Xiao, Xianhe Qu

“…This approach integrates prior information and observational data to ensure the continuity and accuracy of predictions. The weighted SVM algorithm based on grey relational analysis improves the accuracy of the predictive model by identifying key factors within multi-dimensional data and assigning appropriate weights to different features to address the challenges posed by incomplete or noisy data. …”
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Prediction and Mapping of Soil Total Nitrogen Using GF-5 Image Based on Machine Learning Optimization Modeling by LIU Liqi, WEI Guangyuan, ZHOU Ping

“…Model performance was evaluated using three indicators: Coefficient of determination (R²), root mean square error (RMSE), and relative prediction deviation (RPD), to assess the prediction accuracy of different models.…”
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A Systematic Search of Distant Superclusters with the Subaru Hyper Suprime-Cam Survey by Tsung-Chi Chen, Yen-Ting Lin, Hsi-Yu Schive, Masamune Oguri, Kai-Feng Chen, Nobuhiro Okabe, Sadman Ali, Connor Bottrell, Roohi Dalal, Yusei Koyama, Rogério Monteiro-Oliveira, Rhythm Shimakawa, Tomotsugu Goto, Bau-Ching Hsieh, Tadayuki Kodama, Atsushi J. Nishizawa

“…The FoF algorithm is calibrated by evolving N -body simulations to the far future to ensure high purity. …”
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Identification of prognostic hub genes and functional role of BAIAP2L2 in prostate cancer progression: a transcriptomic and experimental study by Xiangyang Zhan, Xiangyang Zhan, Xiangyang Zhan, Xiangyang Zhan, Wenkai Wang, Jie Lian, Yichun Li, Jianyi Gu, Jianyi Gu, Jianyi Gu, Jianyi Gu, Dongdong Guo, Dongdong Guo, Dongdong Guo, Dongdong Guo, Dongliang Xu, Dongliang Xu, Dongliang Xu, Dongliang Xu, Guanqun Ju, Guanqun Ju, Guanqun Ju, Guanqun Ju

“…BackgroundProstate cancer (PCa) is a prevalent malignancy in men, and understanding its molecular mechanisms is crucial for identifying therapeutic targets.MethodsTranscriptomic data from prostate tumors and matched healthy tissues were obtained from The Cancer Genome Atlas (TCGA). Differential expression analysis using the DESeq2 algorithm identified differentially expressed genes (DEGs). …”
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Machine Learning-Based Prediction Performance Comparison of Marshall Stability and Flow in Asphalt Mixtures by Muhammad Farhan Zahoor, Arshad Hussain, Afaq Khattak

“…Their performances vary; therefore, evaluating different MLAs and comparing them is important. …”
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Development of a prognostic model for chemotherapy response and identification of TNFAIP2 as a target in colorectal cancer by Cheng Zhou, Chuan-Hai Xu, Min Xu, Xin-Kun Huang, Bin Zhu

“…The tumor microenvironment (TME) was assessed using the MCP-counter algorithm, and CRC cell experiments were performed to evaluate changes in drug sensitivity following oxaliplatin exposure. …”
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Data set for UWB Cooperative Navigation and Positioning of UAV Cluster by Cunle Zhang, Chengkai Tang, Haonan Wang, Baowang Lian, Lingling Zhang

“…The resulting data supports the development and validation of distance-based multi-target navigation algorithms, the evaluation of formation maintenance and collision avoidance algorithms for multiple UAVs, and also serves as a source for navigation evaluation and the development of multi-source fusion cluster positioning algorithms.…”
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Proof of concept of fully automated adaptive workflow for head and neck radiotherapy treatments with a conventional linear accelerator by Gaia Muti, Marco M. J. Felisi, Angelo F. Monti, Chiara Carsana, Roberto Pellegrini, Edoardo Salmeri, Mauro Palazzi, Paola E. Colombo

“…IntroductionThe objective of this study is to evaluate the performance of an automatic workflow for head-and-neck (H&amp;N) radiotherapy using a multi-atlas based auto-contouring software and an a-priori multicriteria plan optimization algorithm and implement an adaptive online approach with CBCT images. …”
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Cooperative Identification of Prolonged Motor Movement From EEG for BCI Without Feedback by Alicia Falcon-Caro, Joao Filipe Ferreira, Saeid Sanei

“…In such a formulation, orthogonal Bessel functions are utilized to represent different gestures and used as the target for the adaptation algorithm. …”
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Belief Propagation-Based Cognitive Routing in Maritime Ad Hoc Networks by Huma Ghafoor, Youngtae Noh, Insoo Koo

“…We apply both flood-based and geographical routing protocols to find a route between source and destination for different scenarios. We simulate our scheme for different ocean settings and evaluate path durations for different number of ships. …”
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Uncertainties Related to Scale and Sampling Window Size in Defining Macro Landforms by Neslihan Dal, Tolga Görüm

“…The differences in the definitions of different scales and analysis windows caused by the border uncertainties between mountainplateau and mountain-plain that are specific to Türkiye were discussed using the UNEP-WCMC 2000 classification algorithm. …”
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