The proliferation of Internet of Things (IoT) systems has led to the generation of vast amounts
of data, increasing the need for effective anomaly detection mechanisms to ensure system …

One of the most groundbreaking approaches to the processing and analysis of large
datasets has been created as a result of the combination of MapReduce techniques and …

Due to the quantization noise created by analog-to-digital converters (ADCs) with just one
bit of resolution, signal identification in Multiple-Input Multiple-Output (MIMO) systems is a …

Energy consumption forecasting is crucial in smart buildings so as to effectively manage
energy usage and minimize the expenses. The conventional methods of machine learning …

The exponential growth of data in recent years has necessitated the development of more
efficient and scalable machine learning algorithms to handle large-scale data analysis …

The U-Net architecture is a convolutional neural network model that is well-known for its
skills in biomedical image segmentation. This study investigates the revolutionary potential …

In order to understand the soil's health, fertility, and crop appropriateness, soil quality
assessments are an important part of sustainable agricultural techniques. Using their …

This work provides a novel computer vision technique for high-resolution biospherical
imaging based on cutting-edge machine learning and optical coherence technology. Our …

Career and professional development is a long process of personal growth along an
individual's life span. Despite their efforts to develop skills and knowledge, there are …

Safe water and sanitation are fundamental for health, preventing disease, child
development, and economic prosperity. The objectives of this study were to assess the …