Context Comprehending code is crucial in all areas of software development, with many existing supporting tools and techniques for various languages. However, for R, a widely used programming language, especially in the field of statistical computing, ...

• The ability of two spectra to detect wheat powdery mildew (WPM) was compared.
• The performance of multi-feature detection WPM was compared.
• A three-band texture index could detect WPM in advance compared to other features.
• WPM ...

Remote sensing based on unmanned aerial vehicle (UAV) is a non-destructive way for wheat powdery mildew (WPM) detection in the field management and crop protection. However, WPM causes complex symptoms and impacts on wheat plants, such as ...

Artificial intelligence (AI), particularly deep learning (DL) and machine learning (ML) have revolutionized disease diagnosis using complex medical images such as X-rays and CT scans, significantly improving accuracy in identifying various ...

• Developed a highly accurate COVID-19 diagnosis model using transfer learning from DenseNet-121, which achieved an impressive accuracy of 95.85 % for normal and COVID-19 classes.
• Uncovered and demonstrated the vulnerability of deep ...

This article introduces a novel mathematical model analyzing the dynamics of Dengue in the recent past, specifically focusing on the 2023 outbreak of this disease. The model explores the patterns and behaviors of dengue fever in Bangladesh. ...

• We proposed a time-varying contact rate model to analyze the dynamics of Dengue.
• Introduce a sinusoidal function to explore patterns and behaviors of Dengue.
• Besides ARIMA and LSTM models, the Prophet model can predict future ...

This paper presents a novel approach to designing and optimizing a Solar-Wind Hybrid Energy System (SWHS) for an Electric Vehicle Charging Station (EVCS) and a university shopping complex in India. Objectives include addressing sustainable energy ...

Analyzing large volumes of categorical data presents a recurring challenge in the social, behavioral, and biological sciences. Therefore, there is a necessity to reduce these data while maintaining minimal loss of information. CATPCA serves as an ...

The open-source HYPEtools R package aims to address current challenges in hydrological modeling and data analysis by providing a suite of tools for data management, visualization, interpretation, and exploration. Originally developed as a ...

• HYPEtools is an R package for analysis and visualization of hydrological data.
• HYPEtools supports development & calibration of hydrological models such as HYPE.
• The package includes interactive features for mapping, plotting, & ...

• A unified formulation of artificial compressibility and local low Mach number preconditioning methods is presented.
• The formulation enables a single solver can be used to analyze problems from incompressible fluid flows to compressible ...

This paper presents a unified approach to artificial compressibility and local low Mach number preconditioning methods. The numerical formulation is presented, which provides a seamless transition between incompressible and compressible systems. ...

Latest studies confirmed that abnormal function of histone deacetylase (HDAC) plays a pivotal role in formation of tumors and is a potential therapeutic target for treating breast cancer. In this research, in-silico drug discovery approaches via ...

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• QSAR model was generated with good statistical results based on indazole derivatives as potential HDAC inhibitors.
• Compounds C32, C26 and C31 from model 3 had relatively higher inhibitory activity with pIC50 of 9.30103, 9.1549 and ...

Solar photovoltaic system is a significant source of power generation and its production are impacted by changing weather and other environmental conditions. A possible option for achieving high power even under changeable situations is the ...

Pre-trained Code Language Models (Code-PLMs) have shown many advancements and achieved state-of-the-art results for many software engineering tasks in the past few years. These models are mainly targeted at popular programming languages such as Java and ...

In this work, we introduce the R package fabisearch, available on the Comprehensive R Archive Network (CRAN), which implements an original change point detection method for multivariate high-dimensional time series data and a new interactive, 3-...

Artificial neural network (ANN) has acquired noticeable interest from the research community to handle complex problems in Construction and Building engineering (CB). This interest has led to an enormous amount of scientific publications in ...

• Performing scientometric review for ANN Applications in Construction and Building Engineering publications.
• Visualizing publications collaboration networks for key contributors.
• Visualizing publications direct citation networks for ...

• A real-time online fault diagnosis framework for simultaneous diagnosis of normal resistance alterations and resistance-alteration-based faults is proposed.
• Based on the observability of resistance, the layout method of the node wind ...

Resistance-alteration-based multiple-fault diagnosis of mine ventilation systems is essential to ensuring the safety of mine production. The basic assumptions, definitions, framework, theory, algorithms and experiments regarding the resistance-...

This study aims to examine geometric models of the corneal surface that can be used to reduce in reasonable time the dimensionality of datasets of normal anterior corneas. Polynomial models (P) like Zernike polynomials (ZP) and spherical harmonic ...

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• Geometric models of corneas can substantially reduce corneal data dimensionality.
• Spherical harmonic (SH) vs. Zernike (Z), polynomials (P) vs. rational functions (R).
• Results - Accuracy: SHR > SHP > ZR > ZP ⇒ SH > Z & R > P.
• ...

• A lightweight approach for stock trend forecast using DenseNet-41 and autoencoder.
• A custom DenseNet-41 model with STI’s for reliable features to improve the prediction accuracy.
• Our framework can predict the buy/sell/hold signal ...

Reliable estimation of future cost prices of stocks are a significant and exciting task in both educational and economic research. Current progressions in machine learning (ML), and explicitly, in the area of deep learning (DL) have permitted the ...

With the exponential growth of data, the demand for effective data analysis tools has increased significantly. R language, known for its statistical modeling and data analysis capabilities, has become one of the most popular programming languages among ...

For a few decades, parallelization in statistical computing has been an increasing trend, and researchers have put significant effort into converting or adjusting known statistical methods and algorithms in parallel. The main reasons for the ...

This paper presents the ARDL package for the statistical language R, demonstrating its main functionalities in a step by step guide. Some of its main advantages over other related R packages are the intuitive API, and the fact that includes many ...

• Combination of vegetation indices, morphological characteristics and ecological factors improves the accuracy of leaf area index estimation.
• Texture information and ecological factors exhibit a close relationship with vegetation ...

Leaf area index (LAI) is an important phenotypic trait closely related to photosynthesis, respiration, and water utilization. In recent years, unmanned aerial vehicles (UAVs) multispectral capabilities enable the acquisition of spectral ...