Browse Items (26 total)

This paper presents an innovative edge device architecture that significantly enhances
solar energy management systems. By integrating advanced functionalities
such as generation prediction, maintenance alerts, and solar anomaly detection,
this…

Big data analytics (BDA) has increasingly become popular both in theory and practice in recent years. Globally, larger businesses have used BDA to collect, study, and evaluate vast volumes of data to identify market trends and insights that lead to…

Customer segmentation is important for e-commerce companies to understand and target different customers. The primary focus of this work is the application and comparison of K-means clustering and hierarchical clustering, unsupervised machine…

This study investigates the use of visible light communication (VLC) for rapid environmental monitoring by leveraging thin film solar cells as signal receivers. VLC, which employs visible light for data transmission, presents an energy-efficient and…

This study presents a comprehensive internet of things (IoT) solution for improving home automation and fire safety. It describes the design and construction of an all-inclusive house fire extinguishing system using an ESP8266 microcontroller to…

In the domain of gallium nitride based high electron mobility transistors (GaN HEMT), this work refines a class A low noise amplifier (LNA) tailored for fifth generation (5G) wireless applications within the sub-6 GHz band. Employing a common-source…

In an era marked by the proliferation of devices and operating systems, delivering native-feeling applications across platforms has become indispensable. This paper scrutinizes native development through the lens of cross-platform frameworks,…

The conventional method for assessing the working memory performance of children is time-consuming and potentially inaccurate, especially when dealing with many samples. Therefore, an automated system that can produce swift and accurate results is…

The popularity of deep learning in time series prediction has significantly increased compared to the past. In this article, we utilize deep learning methods, which encompass long short term memory (LSTM) networks, simple recurrent neural network…