Electronics

Open AccessCommunication

Supervised Learning Spectrum Sensing Method via Geometric Power Feature

by

Qian Hu

,

Zhongqiang Luo

and

Wenshi Xiao

Electronics 2023, 12(7), 1616; https://doi.org/10.3390/electronics12071616 (registering DOI) - 29 Mar 2023

Abstract

In order to improve the spectrum sensing (SS) performance under a low Signal Noise Ratio (SNR), this paper proposes a supervised learning spectrum sensing method based on Geometric Power (GP) feature. The GP is used as the feature vector in the supervised learning [...] Read more.

In order to improve the spectrum sensing (SS) performance under a low Signal Noise Ratio (SNR), this paper proposes a supervised learning spectrum sensing method based on Geometric Power (GP) feature. The GP is used as the feature vector in the supervised learning spectrum sensing method for training and testing based on the actual captured data set. Experimental results show that the detection performance of the GP-based supervised learning spectrum sensing method is better than that of the Energy Statistics (ES) and Differential Entropy (DE)-based supervised learning spectrum sensing methods. Full article

(This article belongs to the Special Issue Machine Learning and Deep Learning Based Pattern Recognition)

Open AccessArticle

No-Reference Image Quality Assessment Using the Statistics of Global and Local Image Features

by

Domonkos Varga

Electronics 2023, 12(7), 1615; https://doi.org/10.3390/electronics12071615 (registering DOI) - 29 Mar 2023

Abstract

Methods of image quality assessment are widely used for ranking computer vision algorithms or controlling the perceptual quality of video and streaming applications. The ever-increasing number of digital images has encouraged the research in this field at an accelerated pace in recent decades. [...] Read more.

Methods of image quality assessment are widely used for ranking computer vision algorithms or controlling the perceptual quality of video and streaming applications. The ever-increasing number of digital images has encouraged the research in this field at an accelerated pace in recent decades. After the appearance of convolutional neural networks, many researchers have paid attention to different deep architectures to devise no-reference image quality assessment algorithms. However, many systems still rely on handcrafted features to ensure interpretability and restrict the consumption of resources. In this study, our efforts are focused on creating a quality-aware feature vector containing information about both global and local image features. Specifically, the research results of visual physiology indicate that the human visual system first quickly and automatically creates a global perception before gradually focusing on certain local areas to judge the quality of an image. Specifically, a broad spectrum of statistics extracted from global and local image features is utilized to represent the quality-aware aspects of a digital image from various points of view. The experimental results demonstrate that our method’s predicted quality ratings relate strongly with the subjective quality ratings. In particular, the introduced algorithm was compared with 16 other well-known advanced methods and outperformed them by a large margin on 9 accepted benchmark datasets in the literature: CLIVE, KonIQ-10k, SPAQ, BIQ2021, TID2008, TID2013, MDID, KADID-10k, and GFIQA-20k, which are considered de facto standards and generally accepted in image quality assessment. Full article

(This article belongs to the Special Issue Machine and Computer Vision Methods for Natural Images in Electronics and Interdisciplinary Applications)

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Open AccessArticle

Range Deception Jamming Performance Evaluation for Moving Targets in a Ground-Based Radar Network

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Electronics 2023, 12(7), 1614; https://doi.org/10.3390/electronics12071614 (registering DOI) - 29 Mar 2023

Abstract

With the rapid development of electronic information technology, the forms and technologies of electronic warfare have become more complicated, and electronic countermeasures (ECMs) and electronic counter-countermeasures (ECCMs) have become fierce in recent years. Networked radars have become an important means of ECMs due [...] Read more.

With the rapid development of electronic information technology, the forms and technologies of electronic warfare have become more complicated, and electronic countermeasures (ECMs) and electronic counter-countermeasures (ECCMs) have become fierce in recent years. Networked radars have become an important means of ECMs due to their “four anti-resistance performance” against electronic jamming, anti-stealth, anti-radiation missiles, and low-altitude penetration. Based on this, this paper evaluates the performance of range deception jamming on an air-based jammer in a ground-based radar network. In this paper, the ground-based radar coordinate system conversion relationship is first established. Then, the statistical variance data fusion criterion for the radar network is constructed. Hence, based on the data fusion criterion, the jamming range delay boundary and the radar position information are recorded. Finally, the jamming performance evaluation can be achieved by analyzing the relationship between the jamming range delay and the radar position. The results of the simulated experiments reveal that when the jamming range delay is sufficiently small, the radar network system can be interfered with successfully by the range false target. Full article

(This article belongs to the Special Issue Advancements in Radar Signal Processing)

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Open AccessArticle

Dynamic Load Balancing in Stream Processing Pipelines Containing Stream-Static Joins

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Electronics 2023, 12(7), 1613; https://doi.org/10.3390/electronics12071613 (registering DOI) - 29 Mar 2023

Abstract

Data stream processing systems are used to continuously run mission-critical applications for real-time monitoring and alerting. These systems require high throughput and low latency to process incoming data streams in real time. However, changes in the distribution of incoming data streams over time [...] Read more.

Data stream processing systems are used to continuously run mission-critical applications for real-time monitoring and alerting. These systems require high throughput and low latency to process incoming data streams in real time. However, changes in the distribution of incoming data streams over time can cause partition skew, which is defined as an unequal distribution of data partitions among workers, resulting in sub-optimal processing due to an unbalanced load. This paper presents the first solution designed specifically to address partition skew in the context of joining streaming and static data. Our solution uses state-of-the-art principles to monitor processing load, detect load imbalance, and dynamically redistribute partitions, to achieve optimal load balance. To accomplish this, our solution leverages the collocation of streaming and static data, while considering the processing load of the join and the subsequent stream processing operations. Finally, we present the results of an experimental evaluation, in which we compared the throughput and latency of four stream processing pipelines containing such a join. The results show that our solution achieved significantly higher throughput and lower latency than the competing approaches. Full article

(This article belongs to the Special Issue Parallel and Distributed Cloud, Edge and Fog Computing: Latest Advances and Prospects)

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Open AccessArticle

The Impact of Digitalization on Macroeconomic Indicators in the New Industrial Age

by

Alina Ștefania Chenic

,

Adrian Burlacu

,

Răzvan Cătălin Dobrea

,

Laurenţiu Tescan

,

Alin Ioan Creţu

,

Mihaela Roberta Stanef-Puica

,

Teodor Narcis Godeanu

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Alina Magdalena Manole

,

Daniela Virjan

and

Nicolae Moroianu

Electronics 2023, 12(7), 1612; https://doi.org/10.3390/electronics12071612 (registering DOI) - 29 Mar 2023

Abstract

Digitalization has become a watchword in all areas of economic and social activity, and its integration has become a necessity for every state worldwide. If a few years ago we were talking about technological innovation and cutting-edge technologies we are now talking about [...] Read more.

Digitalization has become a watchword in all areas of economic and social activity, and its integration has become a necessity for every state worldwide. If a few years ago we were talking about technological innovation and cutting-edge technologies we are now talking about digital technologies, robotics, big data, and artificial intelligence, and future industrial production will develop in symbiosis with modern information and communication technology. The paper aims to show the impact of digitalization on macroeconomic indicators, including labor productivity, value-added, and value of exports of goods and services, and in this regard, we have built an econometric model to see how digitalization and the evolution of macroeconomic indicators work, and how they will influence the degree of growth and economic development. The research results verify the hypotheses we started from, namely that there is a positive and strong correlation between digitalization and productivity, as well as between digitalization and value-added, and that there is a positive, yet weaker correlation between digitization and exports. The impact of digitalization on macroeconomic indicators extends beyond the theoretical and practical implications, as they influence both the decision-making process of the companies’ management and national and European economic policies. Full article

(This article belongs to the Special Issue Recent Applications of Emerging Digital Technologies in Economy and Society)

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Open AccessArticle

Design and Implementation of CNFET SRAM Cells by Using Multi-Threshold Technique

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Electronics 2023, 12(7), 1611; https://doi.org/10.3390/electronics12071611 (registering DOI) - 29 Mar 2023

Abstract

This paper presents a CNFET (Carbon Nano-tube FET) based MT (Multi-Threshold)-SRAM (Static Random Access Memory) design based on the leakage reduction mechanism. A multi-threshold logic is employed for reducing the leakage current during read/write operations. Here, the multi-threshold technique is used to insert [...] Read more.

This paper presents a CNFET (Carbon Nano-tube FET) based MT (Multi-Threshold)-SRAM (Static Random Access Memory) design based on the leakage reduction mechanism. A multi-threshold logic is employed for reducing the leakage current during read/write operations. Here, the multi-threshold technique is used to insert the high threshold sleep control to the low threshold circuit. The insertion is performed in a serial manner. The high threshold transistors are very useful for deriving the low sub-threshold current. Meanwhile, the low threshold transistors are promising for improving the circuit performance. The high-low threshold transistor pairs are used to change the channel length by modifying the oxide thickness of the transistors. The overall implementation of the Multi-threshold-based SRAM cells are implemented with the help of CNFET in-order to avoid the short channel effect, mobility degradation which is occurred while considering the channel length below 32 nm in CMOS (Complementary Metal Oxide Semiconductor) devices. The paper clearly represents the performance improvement of the proposed SRAM cells with above-mentioned technologies. Full article

(This article belongs to the Special Issue State-of-the-Art and New Trends of Power Electronics Technologies and Applications)

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Open AccessArticle

A Wide-Range Four-Phase All-Digital DLL with De-Skew Circuit

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Electronics 2023, 12(7), 1610; https://doi.org/10.3390/electronics12071610 (registering DOI) - 29 Mar 2023

Abstract

A four-phase all-digital delay-locked loop (ADDLL) with a de-skew circuit for NAND Flash high-speed interfaces is proposed. The proposed de-skew circuit adopts a fall-edge-judgment phase adjuster and a three-stage digitally controlled delay line to align the system input clock and 0

^{\circ}

output [...] Read more.

A four-phase all-digital delay-locked loop (ADDLL) with a de-skew circuit for NAND Flash high-speed interfaces is proposed. The proposed de-skew circuit adopts a fall-edge-judgment phase adjuster and a three-stage digitally controlled delay line to align the system input clock and 0

^{\circ}

output clock of the four-phase DLL over a wide frequency range, thus solving the four-phase offset caused by clock skew. A parallel-cascade configuration is proposed to solve the variable phase alignment problem caused by mode switching, thus effectively improving the phase-locked accuracy. The proposed circuit is fabricated in the 0.13

μ

m CMOS process with a 0.072 mm

^{2}

core area. The chip testing results show an operating frequency range from 26 MHz to 1.55 GHz and a typical alignment error of approximately 17 ps. Full article

(This article belongs to the Special Issue Advance in RF, Analog, and Mixed Signal Circuits)

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Open AccessArticle

Digital Image Identification and Verification Using Maximum and Preliminary Score Approach with Watermarking for Security and Validation Enhancement

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A. S. M. Sanwar Hosen

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In-Ho Ra

,

Maninder Kaur

and

Satnam Singh

Electronics 2023, 12(7), 1609; https://doi.org/10.3390/electronics12071609 (registering DOI) - 29 Mar 2023

Abstract

Digital face approaches possess currently received awesome attention because of their huge wide variety of digital audio, and visual programs. Digitized snapshots are progressively more communicated using an un-relaxed medium together with cyberspace. Consequently, defence, clinical, medical, and exceptional supervised photographs are essentially [...] Read more.

Digital face approaches possess currently received awesome attention because of their huge wide variety of digital audio, and visual programs. Digitized snapshots are progressively more communicated using an un-relaxed medium together with cyberspace. Consequently, defence, clinical, medical, and exceptional supervised photographs are essentially blanketed towards trying to employ it; such controls ought to damage such choices constructed totally based on those pictures. So, to shield the originality of digital audio/visual snapshots, several approaches proposed. Such techniques incorporate traditional encoding, breakable and nominal breakable watermarking with virtual impressions which are based upon the material of image content. Over the last few decades, various holistic approaches are proposed for improving image identification and verification. In this paper, a combination of both the feature level and score level of different techniques were used. Image is one of the identities of a person which reflects its emotions, feeling, age etc. which also helps to gather an information about a person without knowing their name, caste, and age and this could be not of much importance when it is used for domestic or framing applications. To secure the originality of digital audio/visual impressions many methods come into pictures and are proposed which include digital signatures, watermarking, cryptography, and fragile depend upon face contents. The objective of this research article is to identify & verify real-time video images using feature and score levels using watermarking that will help to judge the authenticity of any images at the initial stage by extracting the features which are evaluated by following an algorithm known as Viterbi and where input data is changed initially into an embedded treat or state then the matrix is evaluated of achieved transformation and on this basis preliminary score estimation will be generated after many iterations for each image that will help in validation. Finally, the tested image will be verified using several approaches to protect and provide security to the original image being verified. This approach may be useful for different surveillance applications for real-time image identification and verification. Also, measurement of accuracy was done by reconfiguring the HMM to identify the constant segmentation and feature removal of the image was settled by initializing parameters and teaching the image feature using the algorithm “Viterbi”. Full article

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Open AccessArticle

Operation Method of PV–Battery Hybrid Systems for Peak Shaving and Estimation of PV Generation

by

Kun-Yik Jo

and

Seok-Il Go

Electronics 2023, 12(7), 1608; https://doi.org/10.3390/electronics12071608 (registering DOI) - 29 Mar 2023

Abstract

Photovoltaic (PV)–battery hybrid systems, which are composed of PV arrays, batteries, and bidirectional inverters, can level the loads of traditional utility grids. Their objective is to supply predetermined active and reactive power to the power grid. This paper presents an operation method for [...] Read more.

Photovoltaic (PV)–battery hybrid systems, which are composed of PV arrays, batteries, and bidirectional inverters, can level the loads of traditional utility grids. Their objective is to supply predetermined active and reactive power to the power grid. This paper presents an operation method for PV–battery hybrid systems by estimating PV generation. Using the PV installation information, the maximum PV generation on a clear day was predicted and compared with historical data. The PV generation was estimated using historical data from 2007 to 2010. The method aims to reduce the peak load of the power system using the estimated load and PV generation of the next day. With the given weather information and load pattern for the next day, the charge and discharge set points of the battery can be determined by considering the initial SoC (State of Charge) and capacity of the battery. To compensate for the estimation error of the load and PV output, an operational margin was considered. This method can maximize system operation efficiency by fully utilizing the battery. The effectiveness of the operation method was validated through simulation studies. It was confirmed that the peak load could be reduced by 30% using the proposed algorithm. Full article

(This article belongs to the Special Issue Advanced Modeling, Control and Emerging Application of Energy Storage Systems)

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Open AccessArticle

Attention-Enhanced Lightweight One-Stage Detection Algorithm for Small Objects

by

Nan Jia

,

Zongkang Wei

and

Bangyu Li

Electronics 2023, 12(7), 1607; https://doi.org/10.3390/electronics12071607 (registering DOI) - 29 Mar 2023

Abstract

The majority of object detection algorithms based on convolutional neural network are focused on larger objects. In order to improve the accuracy and efficiency of small object detection, a novel lightweight object detection algorithm with attention enhancement is proposed in this paper. The [...] Read more.

The majority of object detection algorithms based on convolutional neural network are focused on larger objects. In order to improve the accuracy and efficiency of small object detection, a novel lightweight object detection algorithm with attention enhancement is proposed in this paper. The network part of the proposed algorithm is based on a single-stage framework and takes MobileNetV3-Large as a backbone. The representation of shallower scale features in the scale fusion module is enhanced by introducing an additional injection path from the backbone and a detection head specially responsible for detecting small objects is added. Instead of pooling operators, dilated convolution with hierarchical aggregation is used to reduce the effect of background pixels on the accuracy of small object locations. To improve the efficacy of merging, the spatial and channel weights of scale features are modified adaptively. Last but not least, to improve the representation of small objects in the training datasets, the Consistent Mixed Cropping method is also proposed. The small labels of standard datasets are expanded with the self-collected samples for the training of the algorithm network. According to the test results and visualization on the 64-Bit Extended (X86-64) platform and embedded Advanced RISC Machine (ARM) platform, we find that the average accuracy (mAP) of the proposed algorithm is 4.6% higher than YOLOv4 algorithm, which achieves better small object detection performance than YOLOv4 algorithm, and the computational complexity is only 12% of YOLOv4 algorithm. Full article

(This article belongs to the Collection Deep Learning for Computer Vision: Algorithms, Theory and Application)

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Open AccessArticle

ECG Signal Denoising Method Based on Disentangled Autoencoder

by

Haicai Lin

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Ruixia Liu

and

Zhaoyang Liu

Electronics 2023, 12(7), 1606; https://doi.org/10.3390/electronics12071606 (registering DOI) - 29 Mar 2023

Abstract

The electrocardiogram (ECG) is widely used in medicine because it can provide basic information about different types of heart disease. However, ECG data are usually disturbed by various types of noise, which can lead to errors in diagnosis by doctors. To address this [...] Read more.

The electrocardiogram (ECG) is widely used in medicine because it can provide basic information about different types of heart disease. However, ECG data are usually disturbed by various types of noise, which can lead to errors in diagnosis by doctors. To address this problem, this study proposes a method for denoising ECG based on disentangled autoencoders. A disentangled autoencoder is an improved autoencoder suitable for denoising ECG data. In our proposed method, we use a disentangled autoencoder model based on a fully convolutional neural network to effectively separate the clean ECG data from the noise. Unlike conventional autoencoders, we disentangle the features of the coding hidden layer to separate the signal-coding features from the noise-coding features. We performed simulation experiments on the MIT-BIH Arrhythmia Database and found that the algorithm had better noise reduction results when dealing with four different types of noise. In particular, using our method, the average improved signal-to-noise ratios for the three noises in the MIT-BIH Noise Stress Test Database were 27.45 db for baseline wander, 25.72 db for muscle artefacts, and 29.91 db for electrode motion artefacts. Compared to a denoising autoencoder based on a fully convolutional neural network (FCN), the signal-to-noise ratio was improved by an average of 12.57%. We can conclude that the model has scientific validity. At the same time, our noise reduction method can effectively remove noise while preserving the important information conveyed by the original signal. Full article

(This article belongs to the Special Issue Advanced Technologies of Artificial Intelligence in Signal Processing)

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Open AccessArticle

Bidirectional CLLLC Resonant Converter Based on Frequency-Conversion and Phase-Shift Hybrid Control

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Electronics 2023, 12(7), 1605; https://doi.org/10.3390/electronics12071605 (registering DOI) - 29 Mar 2023

Abstract

Due to the symmetrical structure, consistent working characteristics in the forward and reverse operations, and good soft-switching characteristics, bidirectional CLLLC resonant converters are widely used in electric vehicles and other fields. To meet the requirements of the on-board charger, this paper uses a [...] Read more.

Due to the symmetrical structure, consistent working characteristics in the forward and reverse operations, and good soft-switching characteristics, bidirectional CLLLC resonant converters are widely used in electric vehicles and other fields. To meet the requirements of the on-board charger, this paper uses a bidirectional CLLLC resonant converter as the rear-stage of the on-board charger. The converter uses a constant voltage and constant current control in the forward operation and voltage and current double-closed-loop control in the reverse operation. Aiming at the problem whereby the voltage gain range of the bidirectional CLLLC resonant converter is relatively narrow under frequency-conversion control, the paper proposed a hybrid control method of frequency conversion and phase shift. Frequency-conversion control is used when the voltage gain is high, and phase-shift control is used when the voltage gain is low. The output voltage range of the converter is effectively broadened, and zero voltage switching and zero current switching can be realized in the full load range to improve operating efficiency. A 3.3 kW bidirectional CLLLC resonant converter simulation system is built in the simulation software. The simulation results verify the correctness and feasibility of the designed circuit and control method. Full article

(This article belongs to the Special Issue Energy Storage, Analysis and Battery Usage)

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Open AccessArticle

Chiplet Multi-Objective Optimization Algorithm Based on Communication Consumption and Temperature

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Electronics 2023, 12(7), 1604; https://doi.org/10.3390/electronics12071604 (registering DOI) - 29 Mar 2023

Abstract

A chiplet multi-objective optimization algorithm for 2.5-D integrated circuit (IC) based on a passive interposer is discussed in this article. Inspired by the network-on-chip mapping problem, we propose a novel algorithm, called chiplet multi-objective optimization, which minimizes the average temperature and the communication [...] Read more.

A chiplet multi-objective optimization algorithm for 2.5-D integrated circuit (IC) based on a passive interposer is discussed in this article. Inspired by the network-on-chip mapping problem, we propose a novel algorithm, called chiplet multi-objective optimization, which minimizes the average temperature and the communication consumption between chiplets at the same time. The algorithm considers the specificities of 2.5-D IC chiplets, such as the spacing and different sizes of chiplets. In addition to the weight factor, α is also introduced to make a balance between temperature and the communication consumption. The designer can change the weight factor according to their own requirement. The multi-window display system is used as an example in this article to demonstrate the algorithm’s efficiency and the accuracy. According to our algorithm, the system temperature of the most ideal solution can be reduced by 8.34 K and the communication consumption reduced by 232.13 μJ. Full article

(This article belongs to the Section Circuit and Signal Processing)

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Open AccessArticle

Thermal Runaway Characteristics and Gas Composition Analysis of Lithium-Ion Batteries with Different LFP and NCM Cathode Materials under Inert Atmosphere

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Electronics 2023, 12(7), 1603; https://doi.org/10.3390/electronics12071603 (registering DOI) - 29 Mar 2023

Abstract

During thermal runaway (TR), lithium-ion batteries (LIBs) produce a large amount of gas, which can cause unimaginable disasters in electric vehicles and electrochemical energy storage systems when the batteries fail and subsequently combust or explode. Therefore, to systematically analyze the post-thermal runaway characteristics [...] Read more.

During thermal runaway (TR), lithium-ion batteries (LIBs) produce a large amount of gas, which can cause unimaginable disasters in electric vehicles and electrochemical energy storage systems when the batteries fail and subsequently combust or explode. Therefore, to systematically analyze the post-thermal runaway characteristics of commonly used LIBs with

{LiFePO}_{4}

(LFP) and

{LiNi}_{x} {C o}_{y} {M n}_{z} O_{2}

(NCM) cathode materials and to maximize the in situ gas generation during battery thermal runaway, we designed experiments using an adiabatic explosion chamber (AEC) under an inert atmosphere to test LIBs. Additionally, we conducted in situ analysis of the gas components produced during thermal runaway. Our research findings indicate that after thermal runaway, NCM batteries produce more gas than LFP batteries. Based on battery gas production, the degree of harm caused by TR can be ranked as follows: NCM9 0.5 0.5 > NCM811 > NCM622 > NCM523 > LFP. The primary gas components during thermal runaway for both NCM and LFP batteries include

H_{2}, C O, {C O}_{2}, C_{2} H_{4}

, and

{C H}_{4}

. The gas produced by LFP batteries contains a high proportion of

H_{2}

. The high concentration of

H_{2}

results in a lower flammability limit (LFL) for the gas generated by LFP batteries during TR compared to the mixed gas produced by NCM batteries. Therefore, in terms of battery TR gas composition, the order of hazard level is LFP > NCM811 > NCM622 > NCM523 > NCM9 0.5 0.5 0.5. Although experimental results show that LFP batteries have superior thermal stability and lower gas production during large-scale battery thermal runaway events, considering gas generation composition and thermal runaway products, the thermal runaway risk of LFP batteries may be higher than that of NCM batteries. Although LFP batteries are considered very safe, our research results have once again drawn researchers’ attention to LFP batteries. These gases can also serve as detection signals for battery thermal runaway warnings, providing a cautionary note for the future development of electrochemical energy storage and the renewable energy sector. Full article

(This article belongs to the Special Issue Energy Storage, Analysis and Battery Usage)

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Open AccessArticle

Multi-Physics Coupling Simulation Technique for Phase Stable Cables

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Electronics 2023, 12(7), 1602; https://doi.org/10.3390/electronics12071602 - 29 Mar 2023

Abstract

This paper is concerned with calculating the phase stability of a phase stable cable with multi-physics coupling simulations. A three-dimensional electromagnetic-thermal-flow-mechanics multi-physics coupling model is established to simulate the phase stable cable operating in air. The simulation results demonstrate that the electric field [...] Read more.

This paper is concerned with calculating the phase stability of a phase stable cable with multi-physics coupling simulations. A three-dimensional electromagnetic-thermal-flow-mechanics multi-physics coupling model is established to simulate the phase stable cable operating in air. The simulation results demonstrate that the electric field distribution of the corrugated cable shows differences from that of a normal coaxial cable around the outer conductor, i.e., the electric field is stronger around the sharp points of the outer conductor than the blunt points, which elevates the voltage endurance requirement of the cable and the risk of breakdown during the transmission of high power. Regarding the thermal deformation, simulations reveal that the corrugated outer conductor restrains the insulation from expanding along both the cross-section direction and the axial direction, and the thermal expansion might be manipulated through the proper design of the outer conductor parameters. Finally, the consistency between the simulated and measured results of phase stability witnesses the validity of the multi-physics coupling model, and its accuracy might be refined with more precise material properties. Full article

(This article belongs to the Section Industrial Electronics)

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Open AccessArticle

Nonparametric Generation of Synthetic Data Using Copulas

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Electronics 2023, 12(7), 1601; https://doi.org/10.3390/electronics12071601 - 29 Mar 2023

Abstract

This article presents a novel nonparametric approach to generate synthetic data using copulas, which are functions that explain the dependency structure of the real data. The proposed method addresses several challenges faced by existing synthetic data generation techniques, such as the preservation of [...] Read more.

This article presents a novel nonparametric approach to generate synthetic data using copulas, which are functions that explain the dependency structure of the real data. The proposed method addresses several challenges faced by existing synthetic data generation techniques, such as the preservation of complex multivariate structures presented in real data. By using all the information from real data and verifying that the generated synthetic data follows the same behavior as the real data under homogeneity tests, our method is a significant improvement over existing techniques. Our method is easy to implement and interpret, making it a valuable tool for solving class imbalance problems in machine learning models, improving the generalization capabilities of deep learning models, and anonymizing information in finance and healthcare domains, among other applications. Full article

(This article belongs to the Special Issue Recent Advances in Synthetic Data Generation)

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Open AccessArticle

A Comprehensive Model of Android Software Aging and Rejuvenation Considering Battery Saving

by

Vitaliy Yakovyna

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Bohdan Uhrynovskyi

and

Natalya Shakhovska

Electronics 2023, 12(7), 1600; https://doi.org/10.3390/electronics12071600 - 29 Mar 2023

Abstract

The more complex the software system, the greater the number of possible combinations of defects that can cause errors, resulting in software defects that are difficult to isolate and expensive to correct in the development stage. An essential feature of such defects is [...] Read more.

The more complex the software system, the greater the number of possible combinations of defects that can cause errors, resulting in software defects that are difficult to isolate and expensive to correct in the development stage. An essential feature of such defects is a gradual deterioration in software performance finishing with software failure—software aging. Mobile devices are particularly vulnerable to software aging. Thus, there is a constant need for methods and tools to eliminate the effects of aging in mobile systems based on modeling the aging process, including the study of metrics and aging factors and the development of more reliable and adequate aging and rejuvenation models. This paper summarizes the previously developed Android software aging and rejuvenation models and presents a comprehensive model of aging and rejuvenation for the Android operating system. The comprehensive model is based on continuous-time Markov Chains and considers different aging levels, mobile device activity, and battery status. The aging and rejuvenation model can be used to assess the software quality, allows obtaining expressions for indicators of software rejuvenation efficiency, and can be used to design and select parameters of the software rejuvenation method considering battery saving. Full article

(This article belongs to the Special Issue Machine Learning (ML) and Software Engineering)

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Open AccessArticle

A Preliminary Empirical Study of the Power Efficiency of Matrix Multiplication

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Electronics 2023, 12(7), 1599; https://doi.org/10.3390/electronics12071599 - 29 Mar 2023

Abstract

Matrix multiplication is ubiquitous in high-performance applications. It will be a significant part of exascale workloads where power is a big concern. This work experimentally studied the power efficiency of three matrix multiplication algorithms: the definition-based, Strassen’s divide-and-conquer, and an optimized divide-and-conquer. The [...] Read more.

Matrix multiplication is ubiquitous in high-performance applications. It will be a significant part of exascale workloads where power is a big concern. This work experimentally studied the power efficiency of three matrix multiplication algorithms: the definition-based, Strassen’s divide-and-conquer, and an optimized divide-and-conquer. The study used reliable on-chip integrated voltage regulators for measuring the power. Interactions with memory, mainly cache misses, were thoroughly investigated. The main result was that the optimized divide-and-conquer algorithm, which is the most time-efficient, was also the most power-efficient, but only for cases that fit in the cache. It consumed drastically less overall energy than the other two methods, regardless of placement in memory. For matrix sizes that caused a spill to the main memory, the definition-based algorithm consumes less power than the divide-and-conquer ones at a high total energy cost. The findings from this study may be of interest when cutting power usage is more vital than running for the shortest possible time or least amount of energy. Full article

(This article belongs to the Section Computer Science & Engineering)

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Open AccessArticle

An Optimal Active Defensive Security Framework for the Container-Based Cloud with Deep Reinforcement Learning

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Electronics 2023, 12(7), 1598; https://doi.org/10.3390/electronics12071598 - 29 Mar 2023

Abstract

Due to the complexity of attack scenarios in the container-based cloud environment and the continuous changes in the state of microservices, the effectiveness of active defense strategies decreases with the cloud environment and microservice change. To tackle it, the main focus is how [...] Read more.

Due to the complexity of attack scenarios in the container-based cloud environment and the continuous changes in the state of microservices, the effectiveness of active defense strategies decreases with the cloud environment and microservice change. To tackle it, the main focus is how to establish a comprehensive threat model and adaptive active defense deployment strategy. In this study, we present an optimal active defensive security framework (OADSF) for a container-based cloud with deep reinforcement learning. Firstly, based on the characteristics of container clouds and microservices, the security threats and attack paths of attackers are analyzed from the application layer and container layer. Then, we propose a Holistic System Attack Graph to quantitatively analyze the security gain, quality of service (QOS) and defense efficiency in the container-based cloud scenarios. Finally, the optimization of a moving target defense (MTD) strategy is modeled as a Markov decision process. Deep reinforcement learning is proposed to handle the state space explosion under large-scale cloud applications, thus solving the optimal defense configuration strategy for the orchestration platform. We use Kubernetes to build container-based clusters. The algorithm is implemented in Python 3.7 based on Tensorflow 1.14. Simulation results show that the proposed method can quickly converge under large-scale cloud applications and increase defensive efficiency. Compared with DSEOM and SmartSCR, the defense efficiency is increased by 35.19% and 12.09%, respectively. Full article

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