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Subjects / keywords: Programming languages (Electronic computers); R (Computer program language); Social sciences; Data processing; Electronic books

Subjects / keywords: Ecology; Data processing; Environmental sciences; R (Computer program language)

Subjects / keywords: SPSS (Computer file); Handbooks, manuals, etc; Social sciences; Statistical methods; Computer programs; Electronic books

Subjects / keywords: Multiagent systems; NetLogo (Computer program language); Social sciences; Statistical methods

Subjects / keywords: SPSS for Windows; Social sciences; Statistical methods; Computer programs; Electronic books

Subjects / keywords: SPSS for Windows; R (Computer program language); Social sciences; Statistical methods; Computer programs

In this research, we address a critical problem for strawberry growers in Lima: the management of phytosanitary diseases. Traditionally, these farmers relied on time-consuming, imprecise, and error-prone visual observati...

Abstract Physical sciences are essential to the predictive modeling of complex environmental systems, particularly environmental monitoring and sustainability applications, as they provide the deterministic foundation re...

Convolutional Neural Network Twin Arm Robot for Automated Packing of Electronic Components is an intellectual robotic system that is developed as a COCA (Collaborative Operation Control Agent) operational handler of the ...

Quantum coherence properties are attractive for making a quantum computer, but they are easily destroyed by environmental disorder. This contribution examines a way of achieving a perfect electric wire of gallium arsenid...

Understanding neural responses to varying physical loads is essential for developing ergonomic designs. Conventional methods for analyzing peripheral muscle activity, such as electromyography (EMG) and kinematic analysis...

Abstract Purpose This study introduces a new Convolutional Neural Network (CNN) architecture, EyeDiagNet, for the classification of fundus images into four classes: normal, cataract, diabetic retinopathy (DR), and glauco...

This research paper explores a robotic arm that is operated by hand movements so that individuals can work with machines effortlessly. The implementation is composed of computer vision, machine learning and small hardwar...

This paper will offer a unified strategy to the optimization of the chassis of a Formula SAE Supra car and predict structural failures using machine learning and Finite Element Analysis (FEA). The work demonstrates that ...

Event-based image processing represents an emerging research field within computer vision and is gaining increasing relevance in modern imaging technologies. In contrast to conventional frame-based approaches, neuromorph...

Virtual reality (VR) is one of the most common technologies nowadays, which make a virtual environment exactly similar to the real environment. The purpose behind this is to test several issues (designing or manufacturin...

Mathematics and computer science play a pivotal role in modern biology. Dynamical models based on differential equations are particularly adapted to describe dynamic behaviors of many biological processes. However, tradi...

Abstract Precise extraction of medical phenotypes and entities from electronic health record (EHR) text is vital for numerous clinical research tasks, including cohort classification, tracking temporal patterns in diseas...

Abstract Early small fires in coal mines are of critical importance for mine safety, as most incidents begin as small fire sources. These fires essentially constitute a task of small-object detection. Detecting such targ...

Abstract Cloud computing is quite popular because of its scalability and flexibility merits. However, faces significant security risks from malware, which exploits infrastructure weaknesses to cause unauthorized access, ...

Abstract Recently, numerous lightweight image super-resolution methods with low computational complexity have been proposed, achieving a promising trade-off between reconstruction quality and efficiency. However, most ex...

Abstract While multi-access edge computing (MEC) enables flexible task offloading, the inherent dynamism and complexity of real-world environments, accompanied by various uncertainties, exacerbate the challenges in offlo...

Abstract Accurate differentiation of pulmonary emphysema from chest X-rays remains challenging due to imbalanced data, image noise, and the limitations of traditional deep networks in managing diagnostic uncertainty. In ...

Abstract The rapid development of China’s financial markets, particularly the expansion of the ETF ecosystem, has made dynamic sector rotation strategies increasingly feasible and cost-effective for investors. At the s...