Journal of Electrical and Computer Engineering
 Journal metrics
See full report
Acceptance rate10%
Submission to final decision93 days
Acceptance to publication17 days
CiteScore3.400
Journal Citation Indicator0.480
Impact Factor2.4

Enhancing Analytical Precision in Company Earnings Reports through Neurofuzzy System Development: A Comprehensive Investigation

Read the full article

 Journal profile

Journal of Electrical and Computer Engineering publishes recent advances from the rapidly moving fields of both electrical engineering and computer engineering in the areas of circuits and systems, communications, power systems and signal processing.

 Editor spotlight

Journal of Electrical and Computer Engineering maintains an Editorial Board of practicing researchers from around the world, to ensure manuscripts are handled by editors who are experts in the field of study.

 Special Issues

We currently have a number of Special Issues open for submission. Special Issues highlight emerging areas of research within a field, or provide a venue for a deeper investigation into an existing research area.

Latest Articles

More articles
Research Article

Empirical Wavelet Transform Based ECG Signal Filtering Method

The electrocardiogram (ECG) is a diagnostic tool that provides insights into the heart’s electrical activity and overall health. However, internal and external noises complicate accurate heart issue diagnosis. Noise in the ECG signal distorts and introduces artifacts, making it difficult to detect subtle abnormalities. To ensure an accurate evaluation, noise-free ECG signals are crucial. This study introduces the empirical wavelet transform (EWT), a contemporary denoising method. EWT decomposes the signal into frequency components, allowing detailed analysis by constructing a customized wavelet basis. Researchers and practitioners can enhance signal analysis by separating the desired components from unwanted noise. The EWT approach effectively eliminates noise while maintaining signal information. The study applies DWT-ADTF, FST, Kalman, Liouville–Weyl fractional compound integral filter LW, Weiner, and EWT denoising methods to two ECG databases from MIT-BIH, which encompass a wide range of cardiac signals and noise levels. The comparative analysis highlights EWT’s strengths through improved signal quality and objective performance metrics. This adaptive transform proves promising for denoising ECG signals and facilitating accurate analysis in clinical and research settings.

Research Article

Pinched Hysteresis Loop with Nonlinear Electronic Components: From Memristor to Hysteristor Concepts

A memristor is an electrical two-terminal passive device that exhibits a pinched hysteresis loop that always passes through the origin in the voltage-current plane. We found a system that also exhibits pinched hysteresis loop, which, consequently following the trend in the literature, can be called memristors; however, their dynamics do not match the equation of memristor that is widely spread and used in the literature. For this reason, in this work, we proposed the name of hysteristor of order . It is a passive system with zero-crossing hysteresis loop in the V-I plane but not necessarily governed by the conventional equations of memristors. The system is proposed to provide a comprehensive circuit taxonomy. The concept of a hysteristor encapsulates and generalizes the idea of memristive systems. To validate the theory, we present theoretical analysis and representative simulations of a novel hysteristor of order 1.

Research Article

Design of PV, Battery, and Supercapacitor-Based Bidirectional DC-DC Converter Using Fuzzy Logic Controller for HESS in DC Microgrid

Renewable energy sources (RES) are becoming more popular globally as a reaction to critical energy concerns. Modern energy management technologies are used to maximize their efficiency while preserving the reliability of the grid. A hybrid energy storage system (HESS) connects to the DC microgrid through the bidirectional converter, allowing energy to be transferred among the battery and supercapacitor (SC). In this paper, a fuzzy logic control (FLC) technique is developed for PV-based DC microgrid systems that use both batteries and SCs. The proposed method uses the unbalanced energy from the battery pack to enhance the overall effectiveness of the HESS. The FLC approach is performed to validate under conditions of variable irradiance using MATLAB Simulink. When sudden changes in irradiance occur, the proposed FLC brings the voltage back to the desired level in terms of transient response like 33 ms settling times and 19% overshoot values. The results exhibit that the proposed method is more efficient in terms of time response, power output, increasing battery life, and ensuring a continuous supply of the PV system.

Research Article

The Formal Analysis on Negative Information Selections for Privacy Protection in Data Publishing

Negative information selection is an approach to protect the privacy by using negative information to replace original information. In this paper, we prove some bounds for negative information selection. Those bounds reveal the privacy protection strength of quantitative probability analysis. We also analyzed the reconstruction probability of original information from available negative information. The formal analysis can specify the bound on the strength of security and utility for negative information selection. Besides, we simulate brute force attacks under different data leakage ratios. Specifically, we calculate the attacker’s guess times before and after the data leakage. Experimental results indicate that the data leakage of over 30% can put the original information in a dangerous situation. Furthermore, we found that the leakage possibility has little relevance to the number of elements in the full set, but it is influenced by the ratio of the leaked information.

Research Article

A Novel Technique for High-Performance Grid Integrated with Restricted Placement of PV-DG considering Load Change

The distributed generation (DG) units’ penetrations in power systems are becoming more prevalent. The majority of recent studies are now focusing on how to best position and size PV-DG units to further improve grid performance. In actuality, and as a result of ideal design requirements, the size and position of the PV are chosen and executed, and no luxury for a change. In this work, the PV-DG unit sizing and location were determined and placed beforehand. Also, load change is a fact and is to be highly considered in the grid. Studying the grid performance and how to enhance it under these conditions is the main objective of this study. This examination was executed using an IEEE 15 bus system in a MATLAB environment. Distribution lines were proposed to connect the PV-DG from its restricted location to the required bus. The purpose of this study is therefore to evaluate the grid’s performance with various actual loads on each bus while connecting a PV-DG unit through a distribution line while taking the available transfer capacity (ATC) of the network into account to find the optimally connected bus. The results said that the optimally connected bus is changed by changing the load which is not doable on land. The results obtained indicate that breaking up PV-DG units into smaller units in the same location and connecting them to every bus was the best option for improving grid performance.

Research Article

Track Circuits Fault Diagnosis Method Based on the UNet-LSTM Network (ULN)

As a commonly used mode of transportation in people’s daily lives, the normal operation of railway transportation is crucial. The track circuit, as a key component of the railway transportation system, is prone to malfunctions due to environmental factors. However, the current method of inspecting track circuit faults still relies on the experience of on-site personnel. In order to improve the efficiency and accuracy of fault diagnosis, we propose to establish an intelligent fault diagnosis system. Considering that the fault data are a one-dimensional time series, this paper presents a fault diagnosis method based on the UNet-LSTM network (ULN). The LSTM network is established on the basis of fault data and used for ZPW-2000A track circuit fault diagnosis. However, the use of a single LSTM network has a high error rate in the common fault diagnosis of track circuits. Therefore, this paper proposes a feature extraction method based on the UNet network. This method is used to extract the features of the original data and then input them into the LSTM network for fault diagnosis. Through experiments with on-site fault data, it has been verified that this method can accurately classify seven common track circuit faults. Finally, the superiority of the method is verified by comparing it with other commonly used fault classification methods.

Journal of Electrical and Computer Engineering
 Journal metrics
See full report
Acceptance rate10%
Submission to final decision93 days
Acceptance to publication17 days
CiteScore3.400
Journal Citation Indicator0.480
Impact Factor2.4
 Submit Check your manuscript for errors before submitting

Article of the Year Award: Impactful research contributions of 2022, as selected by our Chief Editors. Discover the winning articles.