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Optical imaging and single-molecule imaging, in particular, utilize fluorescent tags in order to differentiate observed species by color. The degree of color multiplexing is dependent on the available spectral detection ...

In response to issues in regional landslide risk evaluation (LRE), such as the over-reliance on administrative unit statistics for vulnerability characterization and the difficulty in capturing the fine-scale spatial het...

Identification of defects in crystalline structures is of vital importance when describing the plastic behavior of metals. Despite the increasing number of tools available in the literature, additional techniques are sti...

This review provides a comprehensive introduction to the current state of optimization through quantum computing, as well as its main methods and highlights. It begins with an overview of the history and principles of qu...

Electromagnetic (EM) sensing is uniquely positioned among nondestructive examination options, which enables us to see clearly targets, even when they visually invisible, and thus has found many valuable applications in s...

With the rapid growth of Internet of Vehicles (IoV) technology, the attack surface has expanded significantly in recent years. Traditional intrusion detection systems, such as signature-based and rule-based approaches, a...

ABSTRACT Background and Aims Artificial Intelligence (AI), particularly Machine Learning (ML) and Deep Learning (DL), is transforming healthcare by enabling improved diagnosis, prognosis, and personalized treatments. How...

Disease Diagnosis in crops is a very expensive and lengthy process, as it often involves the need for few experts to make observations, leading to delayed diagnosis, viral spread of diseases, and thus, massive economic l...

Mobile Legends: Bang Bang (MLBB) has become a significant phenomenon within the global e-sports landscape, attracting millions of active players and fans. This study presents a comprehensive sentiment analysis and topic ...

The adoption of artificial intelligence (AI) in cardiovascular disease prediction has significantly improved risk stratification, offering new avenues for early diagnosis and preventive care. With the growing availabilit...

Abstract Deep learning-based image semantic segmentation techniques have made great strides in recent years. However, they still need large amounts of finely annotated image data, and generalizing the model from known cl...

Mining activities in the Kenyan Marble Quarries (KMQ) are a potential source of atmospheric pollution, raising health concerns for the local population. This study aims to examine the extent to which marble mining contri...

Abstract This research proposes an innovative Arabic financial forecasting model that integrates linguistic relation extraction with advanced deep learning and machine learning techniques. The framework combines Arabic O...

Abstract In many real-world applications, binary and multi-class classification problems involving imbalanced data and overlapping boundaries present a significant challenge for traditional machine learning algorithms. I...

Over the past decade, mobile devices have become an integral part of our daily routines, offering a broad spectrum of applications that enhance everyday tasks. As more people adopt smartphones, developers are increasingl...

Airport planning depends to a large extent on the levels of activity that are anticipated. To plan the facilities and infrastructures of an airport system and to be able to satisfy future needs, it is essential to predic...

Artificial intelligence (AI), including machine learning, deep learning, reinforcement learning, and generative AI, has the potential to advance critical care nephrology (CCN) by enhancing prediction accuracy, improving ...

Abstract The rapid adoption of AI is transforming industrial wastewater treatment by enabling real-time monitoring, predictive control, and operational optimization. Publications on the subject accelerated sharply betwee...

Machine learning has evolved into a potent tool for analysing patterns and making predictions from complex data. In this machine learning era, we employed neural network techniques to estimate the parameters of statistic...

The field of artificial intelligence (AI), machine learning and intelligent automation has become pervasive in our modern digital world. It extends from business and public services to environmental management and even i...

Maritime transport is the backbone of international trade and globalization. Maritime transport research can be roughly divided into two categories, namely the shipping side and the port side. Most of the classic approac...

Abstract The growing importance of machine learning in geological data computing, as well as in the broader geoscience and energy sectors, makes it essential to evaluate the impact of data augmentation on model performan...

This research aims to implement web scraping techniques to collect testimonial data from the CeriaMultimedia website and perform sentiment analysis to evaluate service quality. The collected data consists of a limited nu...

The shift from conventional irrigation methods to sprinkler systems is intended to improve accuracy and efficiency; however, it requires thorough validation of the uniformity of water distribution. This research focuses ...