Electronics, Volume 11, Issue 22

The Internet of Things (IoT) grew in popularity in recent years, becoming a crucial component of industrial, residential, and telecommunication applications, among others. This innovative idea promotes communication between physical components, such...

The coronavirus epidemic (COVID-19) is growing quickly around the globe. The first acute atypical respiratory illness was reported in December 2019, in Wuhan, China. This quickly spread from Wuhan city to other locations. Deep learning (DL) algorithm...

Protection against a growing number of increasingly sophisticated and complex cyberattacks requires the real-time acquisition of up-to-date information on identified threats and their potential impact on an enterprise’s operation. However, the...

Accurate short-term load forecasting can ensure the safe and stable operation of power grids, but the nonlinear load increases the complexity of forecasting. In order to solve the problem of modal aliasing in historical data, and fully explore the re...

In the past two years, various graph convolution neural networks (GCNs) accelerators have emerged, each with their own characteristics, but their common disadvantage is that the hardware architecture is not programmable and it is optimized for a spec...

Focusing on the fine-grained access control challenge of multi-user searchable encryption, we propose a hierarchical searchable encryption scheme using blockchain-based indexing (HSE-BI). First, we propose a hierarchical search index structure based...

Artificial Neural Network (ANN) models, specifically Convolutional Neural Networks (CNN), were applied to extract emotions based on spectrograms and mel-spectrograms. This study uses spectrograms and mel-spectrograms to investigate which feature extr...

The intelligent vehicle infrastructure system (IVIS) requires systematic testing before being put into large-scale applications. IVIS testing under closed conditions includes stress tests for typical scenarios and extreme scenario strength testing. T...

This work aims to evaluate the possibility of fabricating conductive paths for printed circuit boards from low-temperature melting metal alloys on low-temperature 3D printed substrates and mounting through-hole electronic components using the fused d...

Border patrol object detection is an important basis for obtaining information about the border patrol area and for analyzing and determining the mission situation. Border Patrol Staffing is now equipped with medium to close range UAVs and portable r...

The hybrid AC-DC microgrid (MG) has gained popularity recently as it offers the benefits of AC and DC systems. Interconnecting AC-DC converters are necessary since the MG has both DC and AC sub-grids. Adding an extra harmonic adjustment mechanism to...

Managing software development processes is still a serious challenge and offers the possibility of introducing improvements that will reduce the resources needed to successfully complete projects. The article presents the original concept of classifi...

In optimization algorithms, there are some challenges, including lack of optimal solution, slow convergence, lack of scalability, partial search space, and high computational demand. Inspired by the process of gold exploration and exploitation, we pr...

The current research investigates a new and unique Multi-Objective Generalized Normal Distribution Optimization (MOGNDO) algorithm for solving large-scale Optimal Power Flow (OPF) problems of complex power systems, including renewable energy sources...

A novel design method of simultaneous beam forming and focusing using a checkerboard anisotropic surface is proposed and verified in this paper. The proposed multibeam control regardless of far and near regions can easily be achieved through a rearra...

To address the technical shortcomings of conventional histogram equalization (HE), such as over-enhancement and artifacts, we propose a histogram-constrained and contrast-tunable HE technique for digital image enhancement. Firstly, the input image hi...

The azimuth multi-channel synthetic aperture radar (MC-SAR) systems can simultaneously realize high-resolution and wide-swath (HRWS) earth observations. However, channel phase bias inevitably exists in the practical work of the azimuth MC-SAR system,...

A trade-off between the memory window and the endurance exists for transition-metal-oxide RRAM. In this work, we demonstrated that HfO_x/Ge-based metal-insulator-semiconductor RRAM devices possess both a larger memory window and longer endurance compa...

A main barrier for autonomous and general learning systems is their inability to understand and adapt to new environments—that is, to apply previously learned abstract solutions to new problems. Supervised learning system functions such as clas...

The growing interest in developing autonomous underwater vehicles (AUVs) and creating underwater sensor networks (USNs) has led to a need for communication tools in underwater environments. For obvious reasons, wireless means of communication are the...

The exploitation of internet networks through denial of services (DoS) attacks has experienced a continuous surge over the past few years. Despite the development of advanced intrusion detection and protection systems, network security remains a chal...

Federated learning is a hot area of concern in the field of privacy protection. There are local model parameters that are difficult to integrate, poor model timeliness, and local model training security issues. This paper proposes a blockchain-based...

Digitalization becomes a key strategy for the success of businesses, which in today’s critical times, are under remarkable pressures and diffused uncertainty. The rapid pace of digitization is forcing deep changes in the modus operandi of organ...

Scene text image super-resolution aims to improve readability by recovering text shapes from low-resolution degraded text images. Although recent developments in deep learning have greatly improved super-resolution (SR) techniques, recovering text im...

Knowledge distillation, in which the parameter values learned in a large teacher network are transferred to a smaller student network, is a popular and effective network compression method. Recently, researchers have proposed methods to improve the p...

Sustainability accounting and reporting is an emerging area of accounting that is receiving increasing attention as a result of sustainability requirements. In this paper, we examine the effects of implementing digital technology on sustainability ac...

Currently, social networks have become one of the most used channels by society to share their ideas, their status, generate trends, etc. By applying artificial intelligence techniques and sentiment analysis to the large volume of data found in socia...

The deterioration of numerous eye diseases is highly related to the fundus retinal structures, so the automatic retinal vessel segmentation serves as an essential stage for efficient detection of eye-related lesions in clinical practice. Segmentation...

With continued dimension scaling of the semiconductor devices, the parasitic parameters become increasingly obvious and it affects the device performance directly. The harmonic distortion is one of the key factors to limit the RF system bandwidth res...

The introduction of convolutional neural networks (CNNs) into single-image super-resolution (SISR) has resulted in remarkable performance in the last decade. There is a contradiction in SISR between indiscriminate processing and the different process...

Signal detection is a serious challenge for uplink massive multiple-input multiple-output (MIMO) systems. The traditional linear minimum-mean-squared error (MMSE) achieves good detection performance for such systems, but involves matrix inversion, wh...

This paper presents an integrated circuit for time-based electrical impedance spectroscopy (EIS) of sensors. The circuit exploits maximum-length sequences (MLS) in order to perform a broadband excitation of the sensors under test. Therefore, the meas...

In multi-tasking scenarios with dynamically changing loads, the parallel computing of convolutional neural networks (CNNs) causes high energy and resource consumption in the system. Another critical problem is that previous neural network hardware ac...

Three-dimensional electromagnetic imaging can be used to monitor grain within metallic grain bins. Data acquisition requires multiple antennas surrounding the imaging space, which are used to transmit and receive the electromagnetic energy inside the...

This paper proposes a dual-polarization dipole antenna for a cylindrical phased array working in Ku-band. The dipole antenna is double-layer structured and is composed of two orthogonal butterfly shaped dipole radiators, two ground co-planar waveguid...

In this article, the development of a compact 10–14.5 GHz quadrature hybrid with digitally reconfigurable I/Q phase in 130 nm SiGe BiCMOS process is presented. Thanks to the switched capacitance loaded on I/Q path of the quadrature hybrid, the...

The current real-time detection of sowing depth has the problems of low detection accuracy and poor reliability. After analyzing the movement mechanism of the sowing monomer parallel four-bar linkage, an improved adaptive Kalman filtering method for...

A multigranulation rough set (MGRS) model is an expansion of the Pawlak rough set, in which the uncertain concept is characterized by optimistic and pessimistic upper/lower approximate boundaries, respectively. However, there is a lack of approximate...

Multimodal research is an emerging field of artificial intelligence, and the analysis of dangerous driving behavior is one of the main application scenarios in the field of multimodal fusion. Aiming at the problem of data heterogeneity in the process...

The performance of the activation function in convolutional neural networks is directly related to the model’s image classification accuracy. The rectified linear unit (ReLU) activation function has been extensively used in image classification...

Developing countries have had numerous obstacles in diagnosing the COVID-19 worldwide pandemic since its emergence. One of the most important ways to control the spread of this disease begins with early detection, which allows that isolation and trea...

This study proposes a 3D attitude estimation algorithm using the RMPE algorithm coupled with a deep neural network that combines human pose estimation and action recognition, which provides a new idea for basketball auxiliary training. Compared with...

The aim of this systematic literature review (SLR) is to identify and critically evaluate current research advancements with respect to small data and the use of data augmentation methods to increase the amount of data available for deep learning cla...

Photovoltaic (PV) power production is characterized by high variability due to short-term meteorological effects such as cloud movements. These effects have a significant impact on the incident solar irradiance in PV parks. In order to control PV par...

Accurate prediction of cellular traffic will contribute to efficient operations and management of mobile network. With deep learning, many studies have achieved exact cellular traffic prediction. However, the reality is that quite a few subnets in th...

Along with rising traffic jams, accurate counting of vehicles in surveillance images is becoming increasingly difficult. Current counting methods based on density maps have achieved tremendous improvement due to the prosperity of convolution neural n...

Purpose: Identification of individual cow breeds may offer various farming opportunities for disease detection, disease prevention and treatment, fertility and feeding, and welfare monitoring. However, due to the large population of cows with hundred...

This paper introduces the DLR Thermofluid Stream Library: a free open-source library for the robust modeling of complex thermofluid architectures. Designed to be easy to use, easy to adapt, and enriched by a number of examples, this library contains...

FasterAI is a PyTorch-based library, aiming to facilitate the use of deep neural network compression techniques, such as sparsification, pruning, knowledge distillation, or regularization. The library is built with the purpose of enabling quick imple...

Water crises due to climate change, high population growth and increasing demands from industry and agriculture claim for increasing efficiency and universalizing water resources management strategies and techniques. Water monitoring helps providing...