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Appl. Sci., Volume 11, Issue 16 (August-2 2021) – 594 articles

Cover Story (view full-size image): The study investigated the pre-touch reaction distance around touchable upper body parts, i.e., shoulders, elbows, and hands, based on human–human pre-touch interaction. The effects of gender, approach side, speed, and acclimation were analyzed for modeling a pre-touch reaction distance. It was found that distance around the hands is smaller than distance around the shoulders and elbows, and speed and acclimation affect the distance. On the other hand, gender and approach side do not significantly affect the pre-touch reaction distance. Finally, the results were implemented in a male-looking android, reacting to pre-touch based on the obtained model. View this paper
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Article
Deep Neural Fuzzy System Oriented toward High-Dimensional Data and Interpretable Artificial Intelligence
Appl. Sci. 2021, 11(16), 7766; https://doi.org/10.3390/app11167766 - 23 Aug 2021
Viewed by 543
Abstract
Fuzzy systems (FSs) are popular and interpretable machine learning methods, represented by the adaptive neuro-fuzzy inference system (ANFIS). However, they have difficulty dealing with high-dimensional data due to the curse of dimensionality. To effectively handle high-dimensional data and ensure optimal performance, this paper [...] Read more.
Fuzzy systems (FSs) are popular and interpretable machine learning methods, represented by the adaptive neuro-fuzzy inference system (ANFIS). However, they have difficulty dealing with high-dimensional data due to the curse of dimensionality. To effectively handle high-dimensional data and ensure optimal performance, this paper presents a deep neural fuzzy system (DNFS) based on the subtractive clustering-based ANFIS (SC-ANFIS). Inspired by deep learning, the SC-ANFIS is proposed and adopted as a submodule to construct the DNFS in a bottom-up way. Through the ensemble learning and hierarchical learning of submodules, DNFS can not only achieve faster convergence, but also complete the computation in a reasonable time with high accuracy and interpretability. By adjusting the deep structure and the parameters of the DNFS, the performance can be improved further. This paper also performed a profound study of the structure and the combination of the submodule inputs for the DNFS. Experimental results on five regression datasets with various dimensionality demonstrated that the proposed DNFS can not only solve the curse of dimensionality, but also achieve higher accuracy, less complexity, and better interpretability than previous FSs. The superiority of the DNFS is also validated over other recent algorithms especially when the dimensionality of the data is higher. Furthermore, the DNFS built with five inputs for each submodule and two inputs shared between adjacent submodules had the best performance. The performance of the DNFS can be improved by distributing the features with high correlation with the output to each submodule. Given the results of the current study, it is expected that the DNFS will be used to solve general high-dimensional regression problems efficiently with high accuracy and better interpretability. Full article
(This article belongs to the Section Computing and Artificial Intelligence)
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Article
Plastic Behavior of Laser-Deposited Inconel 718 Superalloy at High Strain Rate and Temperature
Appl. Sci. 2021, 11(16), 7765; https://doi.org/10.3390/app11167765 - 23 Aug 2021
Viewed by 482
Abstract
Nickel-based superalloys have several applications for components exposed to high temperatures and high strain rate loading conditions during services. The objective of this study was to investigate the tensile properties of Inconel 718 produced using the laser metal deposition technique. Specimens with different [...] Read more.
Nickel-based superalloys have several applications for components exposed to high temperatures and high strain rate loading conditions during services. The objective of this study was to investigate the tensile properties of Inconel 718 produced using the laser metal deposition technique. Specimens with different heat treatments were investigated. Experimental tests were performed at the DYNLab at Politecnico di Torino (Italy). The temperature sensitivity was investigated between 20 °C and 1000 °C on a Hopkinson bar setup at a nominal strain rate of 1500 s−1. The specimens heating was obtained by means of an induction heating system, and the temperature control was performed by thermocouples, an infrared pyrometer, and a high-speed infrared camera. The thermal images were analyzed to check the uniformity of the heating and to investigate the presence of adiabatic self-heating. The results showed that the materials strength exhibited a significant drop starting from 800 °C. The strain rate influence was investigated at room temperature, and limited sensitivity was found covering six orders of magnitude in the strain rate. A preliminary analysis of the fracture mode was performed. Finally, different solutions for the strength material modeling were proposed and discussed with the aim of identifying models to be used in finite element simulations. Full article
(This article belongs to the Special Issue Metal Plasticity at High Strain Rate)
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Article
Collision Risk Evaluation and Verification of GNSS-Based Train Integrity Detection
Appl. Sci. 2021, 11(16), 7764; https://doi.org/10.3390/app11167764 - 23 Aug 2021
Viewed by 468
Abstract
To meet the demand for middle and low-density railway lines, a Global Navigation Satellite System (GNSS) based on a train integrity monitoring system (TIMS) is used for train integrity detection. Each system has to be analyzed before it is applied in practice. To [...] Read more.
To meet the demand for middle and low-density railway lines, a Global Navigation Satellite System (GNSS) based on a train integrity monitoring system (TIMS) is used for train integrity detection. Each system has to be analyzed before it is applied in practice. To evaluate the safety of the train integrity detection, a collision risk evaluation method is proposed based on the positioning errors and protection level, in which the Probability of dangerous Failure per Hour (PFH) is computed to quantify the the criteria of Safety Integrity Level (SIL). Then, an experiment-based simulation procedure is presented for safety verification. Statistics results have been obtained from field test data, and simulations are carried out using CPN and MATLAB to verify the collision risk of GNSS-based train integrity detection. The result showed that the GNSS-based train integrity detection satisfies the safety requirements in the system design phase for railway applications. Full article
(This article belongs to the Section Transportation and Future Mobility)
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Article
WTA: A Static Taint Analysis Framework for PHP Webshell
Appl. Sci. 2021, 11(16), 7763; https://doi.org/10.3390/app11167763 - 23 Aug 2021
Viewed by 460
Abstract
Webshells are a malicious scripts that can remotely control a webserver to execute arbitrary commands, steal sensitive files, and further invade the internal network. Existing webshell detection methods, such as using pattern matching for webshell detection, can be easily bypassed by attackers using [...] Read more.
Webshells are a malicious scripts that can remotely control a webserver to execute arbitrary commands, steal sensitive files, and further invade the internal network. Existing webshell detection methods, such as using pattern matching for webshell detection, can be easily bypassed by attackers using the file include and user-defined functions. Furthermore, detecting unknown webshells has always been a problem in the field of webshell detection. In this paper, we propose a static webshell detection method based on taint analysis, which realizes accurate taint analysis based on ZendVM. We first converted the PHP code into Opline sequences, analyzed the Opline sequences in order, and marked the externally imported taint source. Then, the propagation of the taint variables was tracked, and the interprocedural analysis of the taint variables was performed. Finally, considering the dangerous functions’ call and the referencing of the taint variables at the point of the taint sink, we completed the webshell judgment. Based on this method, we constructed a taint analysis prototype system named WTA and evaluated it with a benchmark dataset by comparing its performance with popular webshell detection tools. The results showed that our method supports interprocedural analysis and has the ability to detect unknown webshells and that WTA’s performance surpasses well-known webshell detection tools such as D-shield, SHELLPUB, WebshellKiller, CloudWalker, ClamAV, LoKi, and findbot.pl. Full article
(This article belongs to the Section Electrical, Electronics and Communications Engineering)
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Article
Wear Behavior of Uncoated and Coated Tools in Milling Operations of AMPCO (Cu-Be) Alloy
Appl. Sci. 2021, 11(16), 7762; https://doi.org/10.3390/app11167762 - 23 Aug 2021
Viewed by 348
Abstract
Copper-Beryllium alloys have excellent wear resistance and high mechanical properties, they also possess good electrical and thermal conductivity, making these alloys very popular in a wide variety of industries, such as aerospace, in the fabrication of tools for hazardous environments and to produce [...] Read more.
Copper-Beryllium alloys have excellent wear resistance and high mechanical properties, they also possess good electrical and thermal conductivity, making these alloys very popular in a wide variety of industries, such as aerospace, in the fabrication of tools for hazardous environments and to produce injection molds and mold inserts. However, there are some problems in the processing of these alloys, particularly when these are subject to machining processes, causing tools to deteriorate quite rapidly, due to material adhesion to the tool’s surface, caused by the material’s ductile nature. An assessment of tool-wear after machining Cu-Be alloy AMPCOLOY 83 using coated and uncoated tools was performed, offering a comparison of the machining performance and wear behavior of solid-carbide uncoated and DLC/CrN multilayered coated end-mills with the same geometry. Multiple machining tests were conducted, varying the values for feed and cutting length. In the initial tests, cutting force values were registered. The material’s surface roughness was also evaluated and the cutting tools’ edges were subsequently analyzed, identifying the main wear mechanisms and how these developed during machining. The coated tools exhibited a better performance for shorter cutting lengths, producing a lower degree of roughness on the surface on the machined material. The wear registered for these tools was less intense than that of uncoated tools, which suffered more adhesive and abrasive damage. However, it was observed that, for greater cutting lengths, the uncoated tool performed better in terms of surface roughness and sustained wear. Full article
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Article
Sensorless Control for DC–DC Boost Converter via Generalized Parameter Estimation-Based Observer
Appl. Sci. 2021, 11(16), 7761; https://doi.org/10.3390/app11167761 - 23 Aug 2021
Viewed by 508
Abstract
The full-information state feedback controller is usually used for regulating the output voltage of converters. Sufficient sensors should be adopted to measure all of the states. However, the extensive use of current sensors not only increases the cost of the overall system, but [...] Read more.
The full-information state feedback controller is usually used for regulating the output voltage of converters. Sufficient sensors should be adopted to measure all of the states. However, the extensive use of current sensors not only increases the cost of the overall system, but also affects the reliability. In this paper, the sensorless control problem of DC–DC boost converters is addressed to avoid the need for the current sensor. First, a PI passivity-based control (PI-PBC) is proposed to stabilize this converter. The main feature of this design is that the exponential convergence of the system is guaranteed. Afterward, a generalized parameter estimation-based observer (GPEBO) is presented to estimate the inductor current with the finite-time convergence (FTC). By adding this estimate in the above PI-PBC, a sensorless controller is developed. Thanks to this FTC, the exponential convergence of an overall closed-loop system is ensured. Finally, the simulation and experimental results are given to assess the performance of the proposed controller. Full article
(This article belongs to the Special Issue Power Converters: Modeling, Control, and Applications)
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Article
Effects of Resonant Electromagnetic Fields on Biofilm Formation in Pseudomonas aeruginosa
Appl. Sci. 2021, 11(16), 7760; https://doi.org/10.3390/app11167760 - 23 Aug 2021
Viewed by 371
Abstract
The global rise of antimicrobial resistance (AMR) constitutes a future health threat and dictates a need to explore alternative and non-chemical approaches. The aim of this study was to explore the use of weak resonant electromagnetic fields as a method to disrupt biofilm [...] Read more.
The global rise of antimicrobial resistance (AMR) constitutes a future health threat and dictates a need to explore alternative and non-chemical approaches. The aim of this study was to explore the use of weak resonant electromagnetic fields as a method to disrupt biofilm formation of a pathogenic bacterium in cystic fibrosis patients. We developed a bioresonance laboratory setup able to distinguish between changes in planktonic growth and changes in biofilm formation and showed that certain resonant frequencies were able to affect biofilm formation without affecting planktonic growth. In addition, we show that the ambient day-to-day magnetic field affects biofilm formation in a non-consistent manner. Overall, we conclude that our assay is suitable for studying the potential of resonant magnetic fields as a treatment and prevention strategy to prevent biofilm infections, and that certain resonant frequencies may be used as future medical applications to combat antimicrobial resistance. Full article
(This article belongs to the Special Issue Electromagnetic Radiation in Biology and Health)
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Article
Robust Flow Field Signal Estimation Method for Flow Sensing by Underwater Robotics
Appl. Sci. 2021, 11(16), 7759; https://doi.org/10.3390/app11167759 - 23 Aug 2021
Viewed by 434
Abstract
The flow field is difficult to evaluate, and underwater robotics can only partly adapt to the submarine environment. However, fish can sense the complex underwater environment by their lateral line system. In order to reveal the fish flow sensing mechanism, a robust nonlinear [...] Read more.
The flow field is difficult to evaluate, and underwater robotics can only partly adapt to the submarine environment. However, fish can sense the complex underwater environment by their lateral line system. In order to reveal the fish flow sensing mechanism, a robust nonlinear signal estimation method based on the Volterra series model with the Kautz kernel function is provided, which is named KKF-VSM. The flow field signal around a square target is used as the original signal. The sinusoidal noise and the signal around a triangular obstacle are considered undesired signals, and the predicting performance of KKF-VSM is analyzed after introducing them locally in the original signals. Compared to the radial basis function neural network model (RBF-NNM), the advantages of KKF-VSM are not only its robustness but also its higher sensitivity to weak signals and its predicting accuracy. It is confirmed that even for strong nonlinear signals, such as pressure responses in the flow field, KKF-VSM is more efficient than the commonly used RBF-NNM. It can provide a reference for the application of the artificial lateral line system on underwater robotics, improving its adaptability in complex environments based on flow field information. Full article
(This article belongs to the Special Issue Advances in Aerial, Space, and Underwater Robotics)
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Article
k-Labelsets Method for Multi-Label ECG Signal Classification Based on SE-ResNet
Appl. Sci. 2021, 11(16), 7758; https://doi.org/10.3390/app11167758 - 23 Aug 2021
Viewed by 369
Abstract
Cardiovascular diseases are the leading cause of death globally. The ECG is the most commonly used tool for diagnosing cardiovascular diseases, and, recently, there are a number of attempts to use deep learning to analyze ECG. In this study, we propose a method [...] Read more.
Cardiovascular diseases are the leading cause of death globally. The ECG is the most commonly used tool for diagnosing cardiovascular diseases, and, recently, there are a number of attempts to use deep learning to analyze ECG. In this study, we propose a method for performing multi-label classification on standard ECG (12-lead with duration of 10 s) data. We used the ResNet model that can perform residual learning as a base model for classification in this work, and we tried to improve performance through SE-ResNet, which added squeeze and excitation blocks on the plain ResNet. As a result of the experiment, it was possible to induce overall performance improvement through squeeze and excitation blocks. In addition, the random k-labelsets (RAKEL) algorithm was applied to improve the performance in multi-label classification problems. As a result, the model that applied soft voting through the RAKEL algorithm to SE-ResNet-34 represented the best performance, and the average performances according to the number of label divisions k were achieved 0.99%, 88.49%, 92.43%, 90.54%, and 93.40% in exact match, accuracy, F1-score, precision, and recall, respectively. Full article
(This article belongs to the Topic Artificial Intelligence in Healthcare)
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Review
Cold Atmospheric Plasma Cancer Treatment, a Critical Review
Appl. Sci. 2021, 11(16), 7757; https://doi.org/10.3390/app11167757 - 23 Aug 2021
Viewed by 497
Abstract
Cold atmospheric plasma (CAP) is an ionized gas, the product of a non-equilibrium discharge at atmospheric conditions. Both chemical and physical factors in CAP have been demonstrated to have unique biological impacts in cancer treatment. From a chemical-based perspective, the anti-cancer efficacy is [...] Read more.
Cold atmospheric plasma (CAP) is an ionized gas, the product of a non-equilibrium discharge at atmospheric conditions. Both chemical and physical factors in CAP have been demonstrated to have unique biological impacts in cancer treatment. From a chemical-based perspective, the anti-cancer efficacy is determined by the cellular sensitivity to reactive species. CAP may also be used as a powerful anti-cancer modality based on its physical factors, mainly EM emission. Here, we delve into three CAP cancer treatment approaches, chemically based direct/indirect treatment and physical-based treatment by discussing their basic principles, features, advantages, and drawbacks. This review does not focus on the molecular mechanisms, which have been widely introduced in previous reviews. Based on these approaches and novel adaptive plasma concepts, we discuss the potential clinical application of CAP cancer treatment using a critical evaluation and forward-looking perspectives. Full article
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Article
Usefulness of Scissors with a Power-Support Mechanism to Assist Thumb Movement: An Observational Study
Appl. Sci. 2021, 11(16), 7756; https://doi.org/10.3390/app11167756 - 23 Aug 2021
Viewed by 619
Abstract
Long-term repetitive movements, such as opening and closing scissors, increase strain on muscles and joints. Amplitude probability distribution function (APDF) analysis of surface electromyogram (sEMG) data was used to quantify the burden of muscle activity. We aimed to test the hypothesis that scissors [...] Read more.
Long-term repetitive movements, such as opening and closing scissors, increase strain on muscles and joints. Amplitude probability distribution function (APDF) analysis of surface electromyogram (sEMG) data was used to quantify the burden of muscle activity. We aimed to test the hypothesis that scissors with a power-support device assist repetitive thumb movements to reduce potential myoelectric activity. Twenty female university students who met the eligibility criteria performed a cutting experiment, with and without power-support device scissors. The primary outcome was a change in muscle load due to sEMG data that were analyzed using APDF, and the secondary outcomes investigated the occurrence of muscle fatigue and pain. The adductor pollicis muscle showed a significant decrease in muscle activity with power assistance. In addition, it was also found that fatigue and pain of the thumb and on the radial side of the forearm were significantly lower under the power-assisted conditions. The results of this study suggest that the assistive action of scissors with a power-support device compensate for muscle load on the thenar eminence. This may be used as a reference value to prevent the occurrence of hand disorders for hairdressers. Full article
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Article
Antioxidant, α-Glucosidase Inhibitory, and Anti-Inflammatory Activities and Cell Toxicity of Waxy and Normal Wheat Sprouts at Various Germination Time
Appl. Sci. 2021, 11(16), 7755; https://doi.org/10.3390/app11167755 - 23 Aug 2021
Viewed by 423
Abstract
Germination is an effective process to improve the bioactivities including antioxidant and hypoglycemic activities of grains, but its effect on waxy wheat has not yet been actively studied. This study, therefore, examined the effect of germination time on the activities of Korean waxy [...] Read more.
Germination is an effective process to improve the bioactivities including antioxidant and hypoglycemic activities of grains, but its effect on waxy wheat has not yet been actively studied. This study, therefore, examined the effect of germination time on the activities of Korean waxy and normal wheat sprouts. The total phenolic and flavonoid contents, and antioxidant activities of the waxy and normal wheat sprouts increased with germination time. Flavonoid content and antioxidant activity were higher in waxy wheat sprouts than in normal ones, but the total phenolic content and α-glucosidase inhibitory activity were not significantly different. The NO production ratio of MEF cells was higher for waxy wheat sprout than for normal ones, thereby indicating lower anti-inflammatory activity of waxy wheat sprouts. The viabilities of Caco-2 cells treated with waxy wheat sprouts was higher than that of cells treated with normal ones for the water extract. These results imply that waxy wheat sprouts exhibit better antioxidant activity and less cell toxicity for water extract, and therefore, could be used as a health-promoting food. Full article
(This article belongs to the Topic Applied Sciences in Functional Foods)
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Article
Enhanced Tone Mapping Using Regional Fused GAN Training with a Gamma-Shift Dataset
Appl. Sci. 2021, 11(16), 7754; https://doi.org/10.3390/app11167754 - 23 Aug 2021
Viewed by 316
Abstract
High-dynamic-range (HDR) imaging is a digital image processing technique that enhances an image’s visibility by modifying its color and contrast ranges. Generative adversarial networks (GANs) have proven to be potent deep learning models for HDR imaging. However, obtaining a sufficient volume of training [...] Read more.
High-dynamic-range (HDR) imaging is a digital image processing technique that enhances an image’s visibility by modifying its color and contrast ranges. Generative adversarial networks (GANs) have proven to be potent deep learning models for HDR imaging. However, obtaining a sufficient volume of training image pairs is difficult. This problem has been solved using CycleGAN, but the result of the use of CycleGAN for converting a low-dynamic-range (LDR) image to an HDR image exhibits problematic color distortion, and the intensity of the output image only slightly changes. Therefore, we propose a GAN training optimization model for converting LDR images into HDR images. First, a gamma shift method is proposed for training the GAN model with an extended luminance range. Next, a weighted loss map trains the GAN model for tone compression in the local area of images. Then, a regional fusion training model is used to balance the training method with the regional weight map and the restoring speed of local tone training. Finally, because the generated module tends to show a good performance in bright images, mean gamma tuning is used to evaluate image luminance channels, which are then fed into modules. Tests are conducted on foggy, dark surrounding, bright surrounding, and high-contrast images. The proposed model outperforms conventional models in a comparison test. The proposed model complements the performance of an object detection model even in a real night environment. The model can be used in commercial closed-circuit television surveillance systems and the security industry. Full article
(This article belongs to the Topic Applied Computer Vision and Pattern Recognition)
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Article
Dropped Object Impact Analysis Considering Frequency and Consequence for LNG-FPSO Topside Module
Appl. Sci. 2021, 11(16), 7753; https://doi.org/10.3390/app11167753 - 23 Aug 2021
Viewed by 310
Abstract
Recently, quantitative risk assessment (QRA) has been widely used as a decision-making tool in the offshore industry. This study focused on analyzing dropped objects in the design of a modern offshore platform. A modified QRA procedure was developed for assessing production module protection [...] Read more.
Recently, quantitative risk assessment (QRA) has been widely used as a decision-making tool in the offshore industry. This study focused on analyzing dropped objects in the design of a modern offshore platform. A modified QRA procedure was developed for assessing production module protection against accidental external loads. Frequency and consequence analyses were performed using the developed QRA procedure. An exceedance curve was plotted, and a high-risk management item was derived through this process. In particular, simulations and experiments were used to verify the difference between the potential and impact energies according to drop orientation. When the object dropped in a specific orientation, the impact energy was confirmed to be up to 4.7 times greater than the potential energy. To reflect the QRA results in structural design, the proposed procedure should be used to calculate the maximum impact energy. The proposed procedure provides a step-by-step guide to assess the damage capacity of a production area as well as the damage frequency and consequences. Full article
(This article belongs to the Section Mechanical Engineering)
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Article
Optimal Control of a Virtual Power Plant by Maximizing Conditional Value-at-Risk
Appl. Sci. 2021, 11(16), 7752; https://doi.org/10.3390/app11167752 - 23 Aug 2021
Viewed by 338
Abstract
This research acquired data from the Central Weather Bureau Observation Data Inquiry System (CODIS) for historical weather information, such as observation time, temperature, humidity, wind speed, global radiation, etc., and constructed a historical weather database by using Excel software. Least square support vector [...] Read more.
This research acquired data from the Central Weather Bureau Observation Data Inquiry System (CODIS) for historical weather information, such as observation time, temperature, humidity, wind speed, global radiation, etc., and constructed a historical weather database by using Excel software. Least square support vector machine (LSSVM) was used to forecast wind speed and solar radiation; then, the power output of wind and solar was derived. Considering factors of the demand response and the load and electricity pricing, a maximized risk income model of the virtual power plant (VPP) is established based on conditional value-at-risk (CVAR). An enhanced bacterial foraging algorithm (EBFA) was proposed to solve the risk dispatch problem of a VPP in this paper. In an EBFA, the stochastic weight trade-off is embedded to improve the behavior pattern of individual bacteria to enhance their sorting efficiency and accuracy in a high-dimension solution space. Various moving patterns of EBFA were considered for improvement, which were demonstrated by using a VPP system on Penghu island, Taiwan. Many scenarios were created, including various seasons, power rebate pricings, and confidence levels, so the maximal risk and return of VPP could be simulated and analyzed. Simulation and tests show a positive result for a VPP to perform the power dispatch by maximizing risk income. This paper also provides a guideline for the VPP to handle the risk management. Full article
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Article
Machine Learning for the Identification of Hydration Mechanisms of Pharmaceutical-Grade Cellulose Polymers and Their Mixtures with Model Drugs
Appl. Sci. 2021, 11(16), 7751; https://doi.org/10.3390/app11167751 - 23 Aug 2021
Viewed by 345
Abstract
Differently bound water molecules confined in hydrated hydroxypropyl cellulose (HPC) type MF and their mixtures (1:1 w/w) with lowly soluble salicylic acid and highly soluble sodium salicylate were investigated by differential scanning calorimetry (DSC). The obtained ice-melting DSC curves of [...] Read more.
Differently bound water molecules confined in hydrated hydroxypropyl cellulose (HPC) type MF and their mixtures (1:1 w/w) with lowly soluble salicylic acid and highly soluble sodium salicylate were investigated by differential scanning calorimetry (DSC). The obtained ice-melting DSC curves of the HPC/H2O samples were deconvoluted into multiple components, using a specially developed curve decomposition tool. The ice-melting enthalpies of the individual deconvoluted components were used to estimate the amounts of water in three states in the HPC matrix: free water (FW), freezing bound water (FBW), and non-freezing water (NFW). A search for an optimal number of Gaussian functions was carried out among all available samples of data and was based on the analysis of the minimum fitting error vs. the number of Gaussians. Finally, three Gaussians accounting for three fractions of water were chosen for further analysis. The results of the calculations are discussed in detail and compared to previously obtained experimental DSC data. AI/ML tools assisted in theory elaboration and indirect validation of the hypothetical mechanism of the interaction of water with the HPC polymer. Full article
(This article belongs to the Special Issue Applications of Artificial Intelligence in Pharmaceutics)
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Article
Microstructural Characterization of a Single Crystal Copper Rod Using Monochromatic Neutron Radiography Scan and Tomography: A Test Experiment
Appl. Sci. 2021, 11(16), 7750; https://doi.org/10.3390/app11167750 - 23 Aug 2021
Viewed by 340
Abstract
This paper reports the analysis of a single crystal copper rod aiming to characterize the microstructural features related to the homogeneity of the single crystal growth and the presence, shape and extension of spatially distributed misaligned grains or areas. The analytical method used [...] Read more.
This paper reports the analysis of a single crystal copper rod aiming to characterize the microstructural features related to the homogeneity of the single crystal growth and the presence, shape and extension of spatially distributed misaligned grains or areas. The analytical method used for such analysis is wavelength scan neutron radiography and monochromatic neutron tomography. Such methods allow determination of the extent of differently oriented single crystal areas, identifying the most part of the rod volume as a single domain. It was also possible to characterize the spatial distribution and the degree of alignment of local point-like or extended defects. Full article
(This article belongs to the Special Issue Advances in Neutron Imaging)
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Article
Strategy for Exploring Feasible and Infeasible Solution Spaces to Solve a Multiple-Vehicle Bike Sharing System Routing Problem
Appl. Sci. 2021, 11(16), 7749; https://doi.org/10.3390/app11167749 - 23 Aug 2021
Viewed by 430
Abstract
In bicycle sharing systems, many vehicles restore bicycles to ports. To construct the shortest tour of these vehicles, in a previous work, we formulated the multiple-vehicle bike sharing system routing problem (mBSSRP) and demonstrated that an optimal solution can be obtained for small-sized [...] Read more.
In bicycle sharing systems, many vehicles restore bicycles to ports. To construct the shortest tour of these vehicles, in a previous work, we formulated the multiple-vehicle bike sharing system routing problem (mBSSRP) and demonstrated that an optimal solution can be obtained for small-sized instances through a general-purpose mixed-integer linear programming solver. However, for large-sized instances, the optimal solution could not be found in a reasonable time frame. Therefore, to find near-optimal solutions for the mBSSRPs in a short time, in this study, we develop a method with a searching strategy, which explores both the feasible and infeasible solution spaces. To investigate the performance of the proposed method, we solve benchmark problems of mBSSRP. In addition, we compare the proposed method with the method exploring only the feasible solution space, in terms of performance. The results of the numerical experiments demonstrate that the proposed method can reach optimal solutions for almost all small-sized mBSSRP instances and that searching both the feasible and infeasible solution spaces yields good feasible solutions both for small-sized and large-sized instances. Full article
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Article
Candida albicans Antimicrobial and Antibiofilm Activity of Novel Endodontic Solvents
Appl. Sci. 2021, 11(16), 7748; https://doi.org/10.3390/app11167748 - 23 Aug 2021
Viewed by 390
Abstract
Background: Candida albicans is the most prevalent fungi isolated in endodontic infections. In this study, the ability of C. albicans biofilm to tolerate the novel solvent mixtures methyl ethyl ketone (MEK)/tetrachloroethylene (TCE) and MEK/orange oil (OOil) sequentially to the standard irrigation of sodium [...] Read more.
Background: Candida albicans is the most prevalent fungi isolated in endodontic infections. In this study, the ability of C. albicans biofilm to tolerate the novel solvent mixtures methyl ethyl ketone (MEK)/tetrachloroethylene (TCE) and MEK/orange oil (OOil) sequentially to the standard irrigation of sodium hypochlorite (NaOCl) and ethylenediaminetetraacetic (EDTA) was evaluated. Methods: Biofilm cell cultures of C. albicans SC 5314 were treated sequentially with NaOCl and EDTA and exposed to MEK/TCE or MEK/OOil. The effect of the antimicrobial treatment was evaluated using the disk diffusion method for planktonic culture, and the enumeration of colony-forming units (CFUs) and scanning electron microscope (SEM) for biofilm cell culture. Results: C. albicans mature biofilm (24 h) was significantly reduced in biomass and cell viability after solvent mixtures’ exposure, compared with the previous NaOCl and EDTA treatments. MEK/OOil combination caused a total reduction of biofilm, while with MEK/TCE, there was a 3-log (CFU/cm2) reduction compared with the sequence NaOCl and EDTA, and a 4-log (CFU/cm2) reduction compared with the control. Conclusions: The additional exposure of a preformed 24 h C. albicans biofilm to novel solvent mixtures MEK/TCE and MEK/OOil caused a positive antibiofilm impact, overcoming the performance of the conventional endodontic irrigating protocol. Full article
(This article belongs to the Topic State-of-the-Art Dentistry and Oral Health)
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Article
Silver-Nanowire-Based Localized-Surface-Plasmon-Assisted Transparent Conducting Electrode for High-Efficiency Light-Emitting Diode
Appl. Sci. 2021, 11(16), 7747; https://doi.org/10.3390/app11167747 - 23 Aug 2021
Viewed by 409
Abstract
Silver nanowire (Ag NWs) networks with high transparency and low resistivity are widely used as promising candidates for the replacement of indium tin oxide (ITO)-based transparent conducting oxides (TCOs) in light-emitting diodes (LEDs). However, LEDs with Ag NW electrodes are less efficient than [...] Read more.
Silver nanowire (Ag NWs) networks with high transparency and low resistivity are widely used as promising candidates for the replacement of indium tin oxide (ITO)-based transparent conducting oxides (TCOs) in light-emitting diodes (LEDs). However, LEDs with Ag NW electrodes are less efficient than those with ITO electrodes because of their low electrical properties, such as high contact resistance and strong absorption in the visible region. In this work, we tried to improve the efficiency of LEDs with transparent conducting electrodes of Ag NWs networks via localized surface plasmons (LSPs) by adopting silver nanoparticles. We studied the effect of the thickness of the p-GaN layer on surface plasmon coupling. When a 45 nm thick p-GaN layer was used, the internal quantum efficiency was improved by LSP coupling between a dipole of QW and Ag NW/NP, and the light extraction was improved because the NPs afforded a leakage mode and acted as scattering centers. Full article
(This article belongs to the Special Issue Light Emitting Diode)
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Article
Pilot Studies of Vibrations Induced in Perambulators When Moving on Different Surfaces
Appl. Sci. 2021, 11(16), 7746; https://doi.org/10.3390/app11167746 - 23 Aug 2021
Viewed by 333
Abstract
The ergonomics of transport is a topic widely described in the literature. One of the fields of ergonomics that researchers are engaged in is vibrometry (both laser and accelerometry) of travel and its translation into NVH (Noise, Vibration and Harshness). However, so far, [...] Read more.
The ergonomics of transport is a topic widely described in the literature. One of the fields of ergonomics that researchers are engaged in is vibrometry (both laser and accelerometry) of travel and its translation into NVH (Noise, Vibration and Harshness). However, so far, the influence of baby carriage movement on the generated vibrations has not been described in more detail. The topic seems to be particularly important considering occurrence of vibrations with significant amplitudes, whose frequency range can have a direct bearing on the resonance frequencies of the child’s internal organs. The article presents the results of research consisting in the measurement of vibrations to which an infant, lying in two different types of prams, may be exposed when being transported on different surfaces. The author’s measurement system, based on accelerometry, was used for the research. The obtained weighted RMS acceleration values not only exceeded human comfort level in all cases (according to ISO standard) but several times were in the range of the highest discomfort (>2 m/s2). Furthermore, the observed vibration frequency range (≈0 ÷ 32 Hz) coincided with the frequencies of free vibration of organs and parts of the child’s body. Full article
(This article belongs to the Special Issue Sports Science, Medicine and Rehabilitation)
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Article
Wax Separated Effectively from Fischer-Tropsch Wax Residue by Solvent Desorption: Thermodynamic and Kinetic Analysis
Appl. Sci. 2021, 11(16), 7745; https://doi.org/10.3390/app11167745 - 23 Aug 2021
Viewed by 391
Abstract
The separation and recycling of effective resources in Fischer-Tropsch wax residue (FTWR) are urgent because of the environmental hazards and energy waste they bring. In this study, organic solvents are used to separate recyclable resources from FTWR efficiently, achieving the goals of “Energy [...] Read more.
The separation and recycling of effective resources in Fischer-Tropsch wax residue (FTWR) are urgent because of the environmental hazards and energy waste they bring. In this study, organic solvents are used to separate recyclable resources from FTWR efficiently, achieving the goals of “Energy Recycle” and “Fisher-Tropsch Wax Residue Treatment”. The response surface methodology (RSM) response surface analysis model accurately evaluates the relationship among temperature, residence time, liquid–solid ratio, and desorption rate and obtains the best process parameters. The results show that the product yield can reach 82.28% under the conditions of 80 °C, 4 h, and the liquid–solid ratio of 24.4 mL/g. Through the kinetic analysis of the desorption process of FTWR, the results show that the desorption process conforms to the pseudo second-order kinetic model and the internal diffusion model. The thermodynamic function results showed that there were not only van der Waals forces in the desorption process, but other strong interaction forces such as hydrogen bonds. In addition, Langmuir, Freundlich, and BET equations are used to describe the desorption equilibrium. Scanning electron microscopy (SEM) were used to analyze the pore structure of FTWR during desorption. X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FT-IR), and Gas chromatography-mass spectrometer (GC-MS) analysis confirmed that the desorption product’s main component was hydrocarbons (50.38 wt%). Furthermore, naphthenic (22.95 wt%), primary alcohol (11.62 wt%), esters (8.7 wt%), and aromatic hydrocarbons (6.35 wt%) compounds were found and can be further purified and applied to other industrial fields. This study shows that using petroleum ether to separate and recover clean resources from Fischer-Tropsch wax residue is feasible and efficient and has potential industrial application prospects. Full article
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Review
A Review of CO2 Laser-Mediated Therapy for Oral Mucosal Lesions
Appl. Sci. 2021, 11(16), 7744; https://doi.org/10.3390/app11167744 - 23 Aug 2021
Viewed by 300
Abstract
(1) Background: Several studies investigating the clinical outcomes of potentially premalignant oral epithelial lesions treated with CO2 lasers have been published over the last decades. (2) Methods: A systematic research review was performed for studies published between 2011 and 2021 in the [...] Read more.
(1) Background: Several studies investigating the clinical outcomes of potentially premalignant oral epithelial lesions treated with CO2 lasers have been published over the last decades. (2) Methods: A systematic research review was performed for studies published between 2011 and 2021 in the PubMed, Science Direct, and Google Scholar databases. (3) Results: Initially, the search identified 52 relevant articles. The primary analysis of the titles and abstracts eliminated 22 articles, leaving 30 articles whose full texts were examined. A total of 22 articles met the inclusion criteria. The studies were classified into 3 categories. (4) Conclusions: After evaluating the results of all the studies included in this review, an initial general statement can be made, namely that CO2 lasers are a treatment option worth taking into consideration when approaching oral mucosal lesions. When compared to other types of lasers used in dental practice, the CO2 laser stands out due to its many advantages. Full article
(This article belongs to the Section Applied Dentistry and Oral Sciences)
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Article
On the Impact of Additive Manufacturing Processes Complexity on Modelling
Appl. Sci. 2021, 11(16), 7743; https://doi.org/10.3390/app11167743 - 23 Aug 2021
Viewed by 362
Abstract
The interest in additive manufacturing (AM) processes is constantly increasing due to the many advantages they offer. To this end, a variety of modelling techniques for the plethora of the AM mechanisms has been proposed. However, the process modelling complexity, a term that [...] Read more.
The interest in additive manufacturing (AM) processes is constantly increasing due to the many advantages they offer. To this end, a variety of modelling techniques for the plethora of the AM mechanisms has been proposed. However, the process modelling complexity, a term that can be used in order to define the level of detail of the simulations, has not been clearly addressed so far. In particular, one important aspect that is common in all the AM processes is the movement of the head, which directly affects part quality and build time. The knowledge of the entire progression of the phenomenon is a key aspect for the optimization of the path as well as the speed evolution in time of the head. In this study, a metamodeling framework for AM is presented, aiming to increase the practicality of simulations that investigate the effect of the movement of the head on part quality. The existing AM process groups have been classified based on three parameters/axes: temperature of the process, complexity, and part size, where the complexity has been modelled using a dedicated heuristic metric, based on entropy. To achieve this, a discretized version of the processes implicated variables has been developed, introducing three types of variable: process parameters, key modeling variables and performance indicators. This can lead to an enhanced roadmap for the significance of the variables and the interpretation and use of the various models. The utilized spectrum of AM processes is discussed with respect to the modelling types, namely theoretical/computational and experimental/empirical. Full article
(This article belongs to the Topic Additive Manufacturing)
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Article
Parametric Simulations on Leakage and Performance of a Miniature Free-Piston Generator (MFPG)
Appl. Sci. 2021, 11(16), 7742; https://doi.org/10.3390/app11167742 - 23 Aug 2021
Viewed by 328
Abstract
The miniaturization of electrical equipment and popularization of portable devices is an appealing motivation for the development of small-scale heat engines. However, the in-cylinder charge leaks severely as the engine dimension shrinks. The free-piston engine on a small scale provides better sealing than [...] Read more.
The miniaturization of electrical equipment and popularization of portable devices is an appealing motivation for the development of small-scale heat engines. However, the in-cylinder charge leaks severely as the engine dimension shrinks. The free-piston engine on a small scale provides better sealing than other miniature heat engines. Therefore, a miniature free-piston generator (MFPG) with a single-piston internal combustion engine (ICE) and a voice coil motor (VCM) was proposed in this work. A dynamic model with special attention on the heat transfer and leakage was established accordingly, upon which parametric studies of leakage and its effects on the performance of the MFPG system were performed. Four key parameters, including scavenging pressure, ignition position, combustion duration and piston mass, were considered in the model. The results showed that the mass leakage during the compression decreases with the rise of the motoring current. The indicated thermal efficiency can be improved by boosting scavenging pressure and increase motoring current. The critical ignition position is 2 mm before the top dead center. When ignition occurs later than that, the MFPG system is incapable of outputting power. The chemical to electric energy conversion efficiency is about 5.13%, with an output power of 10~13 W and power density around 4.7~5.7 W/cc. Full article
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Article
Visual MAV Tracker with Adaptive Search Region
Appl. Sci. 2021, 11(16), 7741; https://doi.org/10.3390/app11167741 - 23 Aug 2021
Viewed by 304
Abstract
Tracking a micro aerial vehicle (MAV) is challenging because of its small size and swift motion. A new model was developed by combining compact and adaptive search region (SR). The model can accurately and robustly track MAVs with a fast computation speed. A [...] Read more.
Tracking a micro aerial vehicle (MAV) is challenging because of its small size and swift motion. A new model was developed by combining compact and adaptive search region (SR). The model can accurately and robustly track MAVs with a fast computation speed. A compact SR, which is slightly larger than a target MAV, is less likely to include a distracting background than a large SR; thus, it can accurately track the MAV. Moreover, the compact SR reduces the computation time because tracking can be conducted with a relatively shallow network. An optimal SR to MAV size ratio was obtained in this study. However, this optimal compact SR causes frequent tracking failures in the presence of the dynamic MAV motion. An adaptive SR is proposed to address this problem; it adaptively changes the location and size of the SR based on the size, location, and velocity of the MAV in the SR. The compact SR without adaptive strategy tracks the MAV with an accuracy of 0.613 and a robustness of 0.086, whereas the compact and adaptive SR has an accuracy of 0.811 and a robustness of 1.0. Moreover, online tracking is accomplished within approximately 400 frames per second, which is significantly faster than the real-time speed. Full article
(This article belongs to the Topic Applied Computer Vision and Pattern Recognition)
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Article
A Variable Ranking Method for Machine Learning Models with Correlated Features: In-Silico Validation and Application for Diabetes Prediction
Appl. Sci. 2021, 11(16), 7740; https://doi.org/10.3390/app11167740 - 23 Aug 2021
Viewed by 298
Abstract
When building a predictive model for predicting a clinical outcome using machine learning techniques, the model developers are often interested in ranking the features according to their predictive ability. A commonly used approach to obtain a robust variable ranking is to apply recursive [...] Read more.
When building a predictive model for predicting a clinical outcome using machine learning techniques, the model developers are often interested in ranking the features according to their predictive ability. A commonly used approach to obtain a robust variable ranking is to apply recursive feature elimination (RFE) on multiple resamplings of the training set and then to aggregate the ranking results using the Borda count method. However, the presence of highly correlated features in the training set can deteriorate the ranking performance. In this work, we propose a variant of the method based on RFE and Borda count that takes into account the correlation between variables during the ranking procedure in order to improve the ranking performance in the presence of highly correlated features. The proposed algorithm is tested on simulated datasets in which the true variable importance is known and compared to the standard RFE-Borda count method. According to the root mean square error between the estimated rank and the true (i.e., simulated) feature importance, the proposed algorithm overcomes the standard RFE-Borda count method. Finally, the proposed algorithm is applied to a case study related to the development of a predictive model of type 2 diabetes onset. Full article
(This article belongs to the Special Issue Data-Driven Biomedical Research and Applications)
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Article
The Impact of Geographical Location on the Chemical Compositions of Pimpinella lutea Desf. Growing in Tunisia
Appl. Sci. 2021, 11(16), 7739; https://doi.org/10.3390/app11167739 - 23 Aug 2021
Viewed by 555
Abstract
Essential oils are generally produced to confer the protection of medicinal plants against several natural enemies. Variations of chemical and physical environmental factors exert significant influences on plant development. They hence may affect the quality and quantity of volatile organic metabolites of interest [...] Read more.
Essential oils are generally produced to confer the protection of medicinal plants against several natural enemies. Variations of chemical and physical environmental factors exert significant influences on plant development. They hence may affect the quality and quantity of volatile organic metabolites of interest and, therefore, the economic applications of essential oils. This research focused on the effects of the harvest region on the production and analytes present in Tunisian Pimpinella lutea Desf. Apiaceae that were collected in three different growing environments (North and South Bizerta and Tabarka). Essential oils extracted from a variety of genotypes were analyzed, for the first time, using gas chromatography and mass spectrometry (GC/FID and GC/MS). The determination of the percentage of essential oil components allowed the recognition of three chemotypes: α-trans-Bergamotene quantified at a percentage of 18.1% in North Bizerta (NBEO), muurola-4,10(14)-dien-1-β-ol identified in South Bizerta (10.1%, SBEO) and acora-3,7(14)-dien present in a high level of 29.1% in Tabarka population (TEO). The richness of different populations in sesquiterpenes (60.2–78.1%) suggests that Pimpinella lutea Desf. may be used in different industrial segments. Full article
(This article belongs to the Special Issue Plants: From Farm to Food and Biomedical Applications)
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Article
Cyber-Attack Scoring Model Based on the Offensive Cybersecurity Framework
Appl. Sci. 2021, 11(16), 7738; https://doi.org/10.3390/app11167738 - 23 Aug 2021
Cited by 1 | Viewed by 918
Abstract
Cyber-attacks have become commonplace in the world of the Internet. The nature of cyber-attacks is gradually changing. Early cyber-attacks were usually conducted by curious personal hackers who used simple techniques to hack homepages and steal personal information. Lately, cyber attackers have started using [...] Read more.
Cyber-attacks have become commonplace in the world of the Internet. The nature of cyber-attacks is gradually changing. Early cyber-attacks were usually conducted by curious personal hackers who used simple techniques to hack homepages and steal personal information. Lately, cyber attackers have started using sophisticated cyber-attack techniques that enable them to retrieve national confidential information beyond the theft of personal information or defacing websites. These sophisticated and advanced cyber-attacks can disrupt the critical infrastructures of a nation. Much research regarding cyber-attacks has been conducted; however, there has been a lack of research related to measuring cyber-attacks from the perspective of offensive cybersecurity. This motivated us to propose a methodology for quantifying cyber-attacks such that they are measurable rather than abstract. For this purpose, we identified each element of offensive cybersecurity used in cyber-attacks. We also investigated the extent to which the detailed techniques identified in the offensive cyber-security framework were used, by analyzing cyber-attacks. Based on these investigations, the complexity and intensity of cyber-attacks can be measured and quantified. We evaluated advanced persistent threats (APT) and fileless cyber-attacks that occurred between 2010 and 2020 based on the methodology we developed. Based on our research methodology, we expect that researchers will be able to measure future cyber-attacks. Full article
(This article belongs to the Special Issue Cyber Security of Critical Infrastructures)
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Article
Nonlinear Loads Compensation Using a Shunt Active Power Filter Controlled by Feedforward Neural Networks
Appl. Sci. 2021, 11(16), 7737; https://doi.org/10.3390/app11167737 - 23 Aug 2021
Viewed by 343
Abstract
The shunt active power filter (SAPF) is a widely used tool for compensation of disturbances in three-phase electric power systems. A high number of control methods have been successfully developed, including strategies based on artificial neural networks. However, the typical feedforward neural network, [...] Read more.
The shunt active power filter (SAPF) is a widely used tool for compensation of disturbances in three-phase electric power systems. A high number of control methods have been successfully developed, including strategies based on artificial neural networks. However, the typical feedforward neural network, the multilayer perceptron, which has provided effective solutions to many nonlinear problems, has not yet been employed with satisfactory performance in the implementation of the SAPF control for obtaining the reference currents. In order to prove the capabilities of this simple neural topology, this work describes a suitable strategy of use, based on the accurate estimation of the Fourier coefficients corresponding to the fundamental harmonic of any distorted voltage or current. An effective training method has been developed, consisting of the use of many distorted patterns. The new generation procedure uses random combinations of multiple harmonics, including the possible nominal frequency deviations occurring in real power systems. The design of the generation of reference signals through computations based on the Fourier coefficients is presented. The objectives were the harmonic mitigation and power factor correction. Practical cases were tested through simulation and also by using an experimental platform, showing the feasibility of the proposal. Full article
(This article belongs to the Section Electrical, Electronics and Communications Engineering)
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