Research on Fire Detection of Cotton Picker Based on Improved Algorithm by Zhai Shi, Fangwei Wu, Changjie Han, Dongdong Song

“…The improved fusion algorithm is used as a learning algorithm to optimize the BP neural network, and the optimized network is used to process and predict the data collected from temperature and gas sensors, which effectively improves the accuracy of fire prediction. …”
Get full text

QPSO-Based Adaptive DNA Computing Algorithm by Mehmet Karakose, Ugur Cigdem

“…Some contributions provided by the proposed QPSO based on adaptive DNA computing algorithm are as follows: (1) parameters of population size, crossover rate, maximum number of operations, enzyme and virus mutation rate, and fitness function of DNA computing algorithm are simultaneously tuned for adaptive process, (2) adaptive algorithm is performed using QPSO algorithm for goal-driven progress, faster operation, and flexibility in data, and (3) numerical realization of DNA computing algorithm with proposed approach is implemented in system identification. …”
Get full text

A three-dimensional mathematical model for drug delivery from drug-eluting stents by P. Darvishi, S. M. Salehi

“…The obtained results showed that the binding process is more limited by convection and diffusion, where convection is the rate-controlling step. …”
Get full text

Comparative Analysis of Gradient Descent Learning Algorithms in Artificial Neural Networks for Forecasting Indonesian Rice Prices by Rica Ramadana, Agus Perdana Windarto, Dedi Suhendro

“…Artificial Neural Networks (ANN) are a field of computer science that mimics the way the human brain processes data. ANNs can be used to classify, estimate, predict, or simulate new data from similar sources. …”
Get full text

When Multimodal Large Language Models Meet Computer Vision: Progressive GPT Fine-Tuning and Stress Testing by Konstantinos I. Roumeliotis, Nikolaos D. Tselikas, Dimitrios K. Nasiopoulos

“…The rapid evolution of Multimodal Large Language Models (LLMs) has redefined the landscape of artificial intelligence, with OpenAI’s GPT-4o representing a transformative leap in multimodal learning and processing. This study pioneers the fine-tuning of GPT-4o on image data, addressing a critical gap in evaluating its performance beyond zero-shot capabilities. …”
Get full text

An interrupted time series study of the leprosy case detection in Brazil after the COVID-19 pandemic by George Jó Bezerra Sousa, Daniele dos Santos Lages, Patrícia Pereira Lima Barbosa, Margarida Cristiana Napoleão Rocha, Sebastião Alves de Sena Neto, Jurema Guerrieri Brandão, Francisco Carlos Félix Lana, Carlos Henrique Alencar, Maria Lúcia Duarte Pereira, Alda Maria da Cruz, Ciro Martins Gomes

“…Abstract COVID-19 pandemics affected several health systems processes, including leprosy care. This study aimed to estimate the impact of the COVID-19 pandemic on the leprosy case detection rate in Brazil from 2017 to 2022. …”
Get full text

Conceptualization of Policies, Strategies and Programs for Poverty Alleviation in Iran: A Qualitative Study by Hassan Danaeefard, Morteza Nabavi, Faramarz Nasri, Seyed Mohammad Javad Sajjadi Nezhad

“…(Kaviani et al., 2023) The Ministry of Labor, Cooperative and Social Welfare has announced in a report that with the sharp growth of the poverty line, the poverty rate has reached 31% in 2020 from 19% in 2017, that is, in 2021, 30% of the total. …”
Get full text

Compressive Sensing in Power Engineering: A Comprehensive Survey of Theory and Applications, and a Case Study by Lekshmi R. Chandran, Ilango Karuppasamy, Manjula G. Nair, Hongjian Sun, Parvathy Krishnan Krishnakumari

“…Compressive Sensing (CS) is a transformative signal processing framework that enables sparse signal acquisition at rates below the Nyquist limit, offering substantial advantages in data efficiency and reconstruction accuracy. …”
Get full text

Collocating Recommendation Method for E-Commerce Based on Fuzzy C-Means Clustering Algorithm by LiJia Wang, Yanyan Jiang

“…In order to reduce the time for customers to select commodities they are interested in, improve the purchase efficiency, improve the success rate of sales of merchants, and create greater economic benefits for enterprises and merchants, this project collects information and data of e-commerce users, using neural network model to analyze and mine data characteristics and shopping records of e-commerce users. …”
Get full text

Large language models to facilitate pregnancy prediction after in vitro fertilization by Ping Cao, Ganesh Acharya, Andres Salumets, Masoud Zamani Esteki

“…The results suggest that LLMs can facilitate data processing, optimize machine learning models in predicting IVF success rates, and provide data interpretation methods. …”
Get full text

Soil Erosion Prediction Using Morgan-Morgan-Finney Model in a GIS Environment in Northern Ethiopia Catchment by Gebreyesus Brhane Tesfahunegn, Lulseged Tamene, Paul L. G. Vlek

“…Even though scientific information on spatial distribution of hydrophysical parameters is critical for understanding erosion processes and designing suitable technologies, little is known in Geographical Information System (GIS) application in developing spatial hydrophysical data inputs and their application in Morgan-Morgan-Finney (MMF) erosion model. …”
Get full text

Towards energy-efficient joint relay selection and resource allocation for D2D communication using hybrid heuristic-based deep learning by C. H. Ramesh Babu, S. Nandakumar

“…In relay-assisted D2D communication, relays are employed to minimize data rate degradation when D2D users are distant from one another. …”
Get full text

Credit card default prediction using ML and DL techniques by Fazal Wahab, Imran Khan, Sneha Sabada

“…Subsequently, various techniques are employed to preprocess the unprocessed data and visually present the outcomes through the use of exploratory data analysis (EDA). …”
Get full text

Exploring the Digitalization of Hospitals Upon the EMRAM Model: The Case of Türkiye by Oğuz Işık, Burak Tekerek

“…The methodology of the research relies on the updated EMRAM criteria by HIMSS. We collected the data face-to-face from the authorized staff in the hospitals (e.g., information processing managers). …”
Get full text

Systematic Literature Review of Machine Learning Models for Detecting DDoS Attacks in IoT Networks by Marcos Luengo Viñuela, Jesús-Ángel Román Gallego

“…It highlights that incorporating deep learning significantly enhances DDoS attack detection precision and efficiency, achieving detection rates between 94 % and 99 %. Despite progress, challenges persist, such as limited training data and IoT device processing constraints with large data volumes. …”
Get full text

Methodology сomparative statistical analysis of Russian industry based on cluster analysis by Sergey S. Shishulin

“…The article is devoted to researching of the possibilities of applying multidimensional statistical analysis in the study of industrial production on the basis of comparing its growth rates and structure with other developed and developing countries of the world. …”
Get full text

Inflammation and Arterial Stiffness as Drivers of Cardiovascular Risk in Kidney Disease by Lorenzo Lo Cicero, Paolo Lentini, Concetto Sessa, Niccolò Castellino, Ambra D'Anca, Irene Torrisi, Carmelita Marcantoni, Pietro Castellino, Domenico Santoro, Luca Zanoli

“…The lower the glomerular filtration rate, the higher the CV risk. Summary: Current data suggest that several uremic toxins lead to vascular inflammation and oxidative stress that, in turn, lead to endothelial dysfunction, changes in smooth muscle cells’ phenotype, and increased degradation of elastin and collagen fibers. …”
Get full text

Predicting mortality in intensive care unit patients with acute pancreatitis using an interpretable machine learning model by Li Zhuangli, Li Zhuangli, Zhang Xingcheng, Zhang Xiaoli, Lu Zhonghua, Sun Yun

“…This study aimed to develop an interpretable machine learning model for predicting in-hospital mortality in ICU patients with AP and to identify key contributing factors.MethodsA retrospective analysis was performed on 306 ICU patients diagnosed with AP. After data preprocessing and feature selection via the Least Absolute Shrinkage and Selection Operator (LASSO), seven machine learning models were developed: decision tree, random forest, XGBoost, support vector machine (SVM), multilayer perceptron, k-nearest neighbors (KNN), and logistic regression. …”
Get full text

Predictors of failure to transition from pediatric to adult nephrology care by Laura Nishi, Jay Kang, Cybele Ghossein

“…This care transition occurs at a highly vulnerable time in life, and rates of unsuccessful transition are high. Evidence-based transition protocols can greatly facilitate the process. …”
Get full text

Mechanistic Modelling and Bayesian Inference Elucidates the Variable Dynamics of Double-Strand Break Repair. by Mae L Woods, Chris P Barnes

“…Our results show that when multiple data sets are combined, the rate for intermediate repair is variable amongst genetic knockouts. …”
Get full text