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Appl. Sci., Volume 12, Issue 6 (March-2 2022) – 451 articles

Cover Story (view full-size image): Criminals often conceal corrosive solutions in inconspicuous plastic bottles in order to incapacitate a victim while committing a robbery or to cause physical harm. There is currently no method available to law enforcement for the safe identification of these corrosive substances without being exposed to them. In this work, the feasibility of a near infrared (NIR) handheld spectrometer for the screening of corrosive inorganic solutions through plastic bottles is investigated. The models designed identified the corrosive substances in scenarios of concentrated solutions, showcasing the potential capability of this technique for the pre-screening of corrosive substances. View this paper
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Article
Binding of Arsenic by Common Functional Groups: An Experimental and Quantum-Mechanical Study
Appl. Sci. 2022, 12(6), 3210; https://doi.org/10.3390/app12063210 - 21 Mar 2022
Viewed by 522
Abstract
Arsenic is a well-known contaminant present in different environmental compartments and in human organs and tissues. Inorganic As(III) represents one of the most dangerous arsenic forms. Its toxicity is attributed to its great affinity with the thiol groups of proteins. Considering the simultaneous [...] Read more.
Arsenic is a well-known contaminant present in different environmental compartments and in human organs and tissues. Inorganic As(III) represents one of the most dangerous arsenic forms. Its toxicity is attributed to its great affinity with the thiol groups of proteins. Considering the simultaneous presence in all environmental compartments of other common functional groups, we here present a study aimed at evaluating their contribution to the As(III) complexation. As(III) interactions with four (from di- to hexa-) carboxylic acids, five (from mono- to penta-) amines, and four amino acids were evaluated via experimental methods and, in simplified systems, also by quantum-mechanical calculations. Data were analyzed also with respect to those previously reported for mixed thiol-carboxylic ligands to evaluate the contribution of each functional group (-SH, -COOH, and -NH2) toward the As(III) complexation. Formation constants of As(III) complex species were experimentally determined, and data were analyzed for each class of ligand. An empirical relationship was reported, taking into account the contribution of each functional group to the complexation process and allowing for a rough estimate of the stability of species in systems where As(III) and thiol, carboxylic, or amino groups are involved. Quantum-mechanical calculations allowed for the evaluation and the characterization of the main chelation reactions of As(III). The potential competitive effects of the investigated groups were evaluated using cysteine, a prototypical species possessing all the functional groups under investigation. Results confirm the higher binding capabilities of the thiol group under different circumstances, but also indicate the concrete possibility of the simultaneous binding of As(III) by the thiol and the carboxylic groups. Full article
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Article
Using Feature Selection with Machine Learning for Generation of Insurance Insights
Appl. Sci. 2022, 12(6), 3209; https://doi.org/10.3390/app12063209 - 21 Mar 2022
Viewed by 782
Abstract
Insurance is a data-rich sector, hosting large volumes of customer data that is analysed to evaluate risk. Machine learning techniques are increasingly used in the effective management of insurance risk. Insurance datasets by their nature, however, are often of poor quality with noisy [...] Read more.
Insurance is a data-rich sector, hosting large volumes of customer data that is analysed to evaluate risk. Machine learning techniques are increasingly used in the effective management of insurance risk. Insurance datasets by their nature, however, are often of poor quality with noisy subsets of data (or features). Choosing the right features of data is a significant pre-processing step in the creation of machine learning models. The inclusion of irrelevant and redundant features has been demonstrated to affect the performance of learning models. In this article, we propose a framework for improving predictive machine learning techniques in the insurance sector via the selection of relevant features. The experimental results, based on five publicly available real insurance datasets, show the importance of applying feature selection for the removal of noisy features before performing machine learning techniques, to allow the algorithm to focus on influential features. An additional business benefit is the revelation of the most and least important features in the datasets. These insights can prove useful for decision making and strategy development in areas/business problems that are not limited to the direct target of the downstream algorithms. In our experiments, machine learning techniques based on a set of selected features suggested by feature selection algorithms outperformed the full feature set for a set of real insurance datasets. Specifically, 20% and 50% of features in our five datasets had improved downstream clustering and classification performance when compared to whole datasets. This indicates the potential for feature selection in the insurance sector to both improve model performance and to highlight influential features for business insights. Full article
(This article belongs to the Topic Machine and Deep Learning)
Article
Biological Effect of Gamma Rays According to Exposure Time on Germination and Plant Growth in Wheat
Appl. Sci. 2022, 12(6), 3208; https://doi.org/10.3390/app12063208 - 21 Mar 2022
Cited by 1 | Viewed by 480
Abstract
Gamma rays as a type of ionizing radiation constitute a physical mutagen that induces mutations and could be effectively used in plant breeding. To compare the effects of gamma and ionizing irradiation according to exposure time in common wheat (Keumgang, IT 213100), seeds [...] Read more.
Gamma rays as a type of ionizing radiation constitute a physical mutagen that induces mutations and could be effectively used in plant breeding. To compare the effects of gamma and ionizing irradiation according to exposure time in common wheat (Keumgang, IT 213100), seeds were exposed to 60Co gamma rays at different dose rates. To evaluate the amount of free radical content, we used electron spin resonance spectroscopy. Significantly more free radicals were generated in the case of long-term compared with short-term gamma-ray exposure at the same dose of radiation. Under short-term exposure, shoot and root lengths were slightly reduced compared with those of the controls, whereas long-term exposure caused severe growth inhibition. The expression of antioxidant-related and DNA-repair-related genes was significantly decreased under long-term gamma-ray exposure. Long-term exposure caused higher radiosensitivity than short-term exposure. The results of this study could help plant breeders select an effective mutagenic induction dose rate in wheat. Full article
(This article belongs to the Special Issue Plant Biotechnology in Agriculture)
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Article
Technology Prediction for Acquiring a Must-Have Mobile Device for Military Communication Infrastructure
Appl. Sci. 2022, 12(6), 3207; https://doi.org/10.3390/app12063207 - 21 Mar 2022
Viewed by 567
Abstract
The smartphone is a must-have mobile device for the military forces to accomplish critical missions and protect critical infrastructures. This paper explores the applicability of a technology prediction methodology to manage technological obsolescence while pursuing the acquisition of advanced commercial technology for military [...] Read more.
The smartphone is a must-have mobile device for the military forces to accomplish critical missions and protect critical infrastructures. This paper explores the applicability of a technology prediction methodology to manage technological obsolescence while pursuing the acquisition of advanced commercial technology for military use. It reviews the Technology Forecasting using Data Envelopment Analysis (TFDEA) methodology and applies an author-written Stata program for smartphone technology forecasting using TFDEA. We analyzed smartphone launch data from 2005 to 2020 to predict the adoption of smartphone technology and discuss the pace of technological change. The study identifies that the market is undergoing reorganization as new smartphone models expand the market and increase their technical performance. The average rate of technological change, the efficiency change, and the technology change were 1.079, 1.004, and 1.011 each, respectively, which means that the technology progressed over the period. When dividing before and after 2017, technological change and efficiency change generally regressed except for Huawei, Xiaomi, and Oppo. This means that Chinese smartphones are expanding the global market in all directions and the technology is reaching maturity and market competition is accelerating. Full article
(This article belongs to the Special Issue Innovative Protection Facility and CBRNE Effects)
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Article
Effects of Nonlinear Damping on Vibrations of Microbeam
Appl. Sci. 2022, 12(6), 3206; https://doi.org/10.3390/app12063206 - 21 Mar 2022
Cited by 1 | Viewed by 386
Abstract
The present paper develops a new Bernoulli–Euler theory of microbeams for the consideration of small-scale effects and nonlinear terms, which are induced by the axial elongation of the beam and Kelvin–Voigt damping. The non-resonance and primary resonance of microbeams are researched through the [...] Read more.
The present paper develops a new Bernoulli–Euler theory of microbeams for the consideration of small-scale effects and nonlinear terms, which are induced by the axial elongation of the beam and Kelvin–Voigt damping. The non-resonance and primary resonance of microbeams are researched through the application of Galerkin and multiple scale methods to the new model. The results suggest the following: (1) Nonlinear damping slightly affects the vibration amplitudes under the non-resonance condition; (2) nonlinear damping can significantly change the bifurcation points that induce a jump in the vibration amplitudes under the primary resonance condition. The current researches indicate that nonlinear damping is necessary for an accurate description of microbeam vibrations. Full article
(This article belongs to the Section Acoustics and Vibrations)
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Article
Assessment of Two Commonly used Dermal Regeneration Templates in a Swine Model without Skin Grafting
Appl. Sci. 2022, 12(6), 3205; https://doi.org/10.3390/app12063205 - 21 Mar 2022
Cited by 1 | Viewed by 403
Abstract
In the medical care of partial and full-thickness wounds, autologous skin grafting is still the gold standard of dermal replacement. In contrast to spontaneous reepithelializing of superficial wounds, deep dermal wounds often lead to disturbing scarring, with cosmetically or functionally unsatisfactory results. However, [...] Read more.
In the medical care of partial and full-thickness wounds, autologous skin grafting is still the gold standard of dermal replacement. In contrast to spontaneous reepithelializing of superficial wounds, deep dermal wounds often lead to disturbing scarring, with cosmetically or functionally unsatisfactory results. However, modern wound dressings offer promising approaches to surface reconstruction. Against the background of our future aim to develop an innovative skin substitute, we investigated the behavior of two established dermal substitutes, a crosslinked and a non-crosslinked collagen biomatrix. The products were applied topically on a total of 18 full-thickness skin defects paravertebrally on the back of female Göttingen Minipigs—six control wounds remained untreated. The evaluation was carried out planimetrically (wound closure time) and histologically (neoepidermal cell number and epidermis thickness). Both treatment groups demonstrated significantly faster reepithelialization than the controls. The histologic examination verified the highest epidermal thickness in the crosslinked biomatrix-treated wounds, whereas the non-crosslinked biomatrix-treated wounds showed a higher cell density. Our data presented a positive influence on epidermal regeneration with the chosen dermis substitutes even without additional skin transplantation and, thus, without additional donor site morbidity. Therefore, it can be stated that the single biomatrix application might be used in a clinical routine with small wounds, which needs to be investigated further in a clinical setting to determine the size and depths of a suitable wound bed. Nevertheless, currently available products cannot solely achieve wound healing that is equal to or superior to autologous tissue. Thus, the overarching aim still is the development of an innovative skin substitute to manage surface reconstruction without additional skin grafting. Full article
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Article
A WSN Framework for Privacy Aware Indoor Location
Appl. Sci. 2022, 12(6), 3204; https://doi.org/10.3390/app12063204 - 21 Mar 2022
Viewed by 509
Abstract
In the past two decades, technological advancements in smart devices, IoT, and smart sensors have paved the way towards numerous implementations of indoor location systems. Indoor location has many important applications in numerous fields, including structural engineering, behavioral studies, health monitoring, etc. However, [...] Read more.
In the past two decades, technological advancements in smart devices, IoT, and smart sensors have paved the way towards numerous implementations of indoor location systems. Indoor location has many important applications in numerous fields, including structural engineering, behavioral studies, health monitoring, etc. However, with the recent COVID-19 pandemic, indoor location systems have gained considerable attention for detecting violations in physical distancing requirements and monitoring restrictions on occupant capacity. However, existing systems that rely on wearable devices, cameras, or sound signal analysis are intrusive and often violate privacy. In this research, we propose a new framework for indoor location. We present an innovative, non-intrusive implementation of indoor location based on wireless sensor networks. Further, we introduce a new protocol for querying and performing computations in wireless sensor networks (WSNs) that preserves sensor network anonymity and obfuscates computation by using onion routing. We also consider the single point of failure (SPOF) of sink nodes in WSNs and substitute them with a blockchain-based application through smart contracts. Our set of smart contracts is able to build the onion data structure and store the results of computation. Finally, a role-based access control contract is used to secure access to the system. Full article
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Article
Citation Context Analysis Using Combined Feature Embedding and Deep Convolutional Neural Network Model
Appl. Sci. 2022, 12(6), 3203; https://doi.org/10.3390/app12063203 - 21 Mar 2022
Viewed by 576
Abstract
Citation creates a link between citing and the cited author, and the frequency of citation has been regarded as the basic element to measure the impact of research and knowledge-based achievements. Citation frequency has been widely used to calculate the impact factor, H [...] Read more.
Citation creates a link between citing and the cited author, and the frequency of citation has been regarded as the basic element to measure the impact of research and knowledge-based achievements. Citation frequency has been widely used to calculate the impact factor, H index, i10 index, etc., of authors and journals. However, for a fair evaluation, the qualitative aspect should be considered along with the quantitative measures. The sentiments expressed in citation play an important role in evaluating the quality of the research because the citation may be used to indicate appreciation, criticism, or a basis for carrying on research. In-text citation analysis is a challenging task, despite the use of machine learning models and automatic sentiment annotation. Additionally, the use of deep learning models and word embedding is not studied very well. This study performs several experiments with machine learning and deep learning models using fastText, fastText subword, global vectors, and their blending for word representation to perform in-text sentiment analysis. A dimensionality reduction technique called principal component analysis (PCA) is utilized to reduce the feature vectors before passing them to the classifier. Additionally, a customized convolutional neural network (CNN) is presented to obtain higher classification accuracy. Results suggest that the deep learning CNN coupled with fastText word embedding produces the best results in terms of accuracy, precision, recall, and F1 measure. Full article
(This article belongs to the Special Issue Application of Machine Learning in Text Mining)
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Article
An Approach for Modelling Harnesses in the Extreme near Field for Low Frequencies
Appl. Sci. 2022, 12(6), 3202; https://doi.org/10.3390/app12063202 - 21 Mar 2022
Viewed by 447
Abstract
A key part of every space science mission, in the system-level approach, is the detailed study and modeling of the emissions from transmission lines. Harnesses usually emit electromagnetic fields due to the currents (of common and/or differential modes) that flow on their shields. [...] Read more.
A key part of every space science mission, in the system-level approach, is the detailed study and modeling of the emissions from transmission lines. Harnesses usually emit electromagnetic fields due to the currents (of common and/or differential modes) that flow on their shields. These fields can be identified via conducted emissions measurements. Relying on the operating frequency, any cable can be considered as a dipole or a traveling-wave antenna. Limited work can be found in the literature regarding modeling methodologies for cable topologies, especially in the low frequency (ELF, SLF, VLF, LF) domain. This work intends to provide perceptions for the precise estimation of harness radiated emissions, consider a mission-specific measurement point (where the sensors are placed), and follow ESA’s recent science mission studies for electromagnetic cleanliness applications. For the low frequencies considered herein, any linear cable path is considered as a point source (infinitesimal dipole) and we evaluate its effect on the calculated electric field extremely close to the source. For such distances, it is shown that the dipole representation is not accurate. To remedy this phenomenon, this article proposes a methodology, which can be easily expanded to complex cable geometry cases. Full article
(This article belongs to the Collection Electromagnetic Antennas for HF, VHF, and UHF Band Applications)
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Review
Further Advances in Atrial Fibrillation Research: A Metabolomic Perspective
Appl. Sci. 2022, 12(6), 3201; https://doi.org/10.3390/app12063201 - 21 Mar 2022
Viewed by 510
Abstract
Atrial fibrillation involves an important type of heart arrhythmia caused by a lack of control in the electrical signals that arrive in the heart, produce an irregular auricular contraction, and induce blood clotting, which finally can lead to stroke. Atrial fibrillation presents some [...] Read more.
Atrial fibrillation involves an important type of heart arrhythmia caused by a lack of control in the electrical signals that arrive in the heart, produce an irregular auricular contraction, and induce blood clotting, which finally can lead to stroke. Atrial fibrillation presents some specific characteristics, but it has been treated and prevented using conventional methods similar to those applied to other cardiovascular diseases. However, due to the influence of this pathology on the mortality caused by cerebrovascular accidents, further studies on the molecular mechanism of atrial fibrillation are required. Our aim here is provide a compressive review of the use of metabolomics on this condition, from the study of the metabolic profile of plasma to the development of animal models. In summary, most of the reported studies highlighted alterations in the energetic pathways related to the development of the condition. Full article
(This article belongs to the Special Issue Metabolomic Analysis in Human Diseases: Latest Advances and Prospects)
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Review
Application of Nanofluids in CO2 Absorption: A Review
Appl. Sci. 2022, 12(6), 3200; https://doi.org/10.3390/app12063200 - 21 Mar 2022
Cited by 6 | Viewed by 604
Abstract
The continuous release of CO2 into the atmosphere as a major cause of increasing global warming has become a growing concern for the environment. Accordingly, CO2 absorption through an approach with maximum absorption efficiency and minimum energy consumption is of paramount [...] Read more.
The continuous release of CO2 into the atmosphere as a major cause of increasing global warming has become a growing concern for the environment. Accordingly, CO2 absorption through an approach with maximum absorption efficiency and minimum energy consumption is of paramount importance. Thanks to the emergence of nanotechnology and its unique advantages in various fields, a new approach was introduced using suspended particles in a base liquid (suspension) to increase CO2 absorption. This review article addresses the performance of nanofluids, preparation methods, and their stability, which is one of the essential factors preventing sedimentation of nanofluids. This article aims to comprehensibly study the factors contributing to CO2 absorption through nanofluids, which mainly addresses the role of the base liquids and the reason behind their selection. Full article
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Article
Dog Behavior Recognition Based on Multimodal Data from a Camera and Wearable Device
Appl. Sci. 2022, 12(6), 3199; https://doi.org/10.3390/app12063199 - 21 Mar 2022
Cited by 2 | Viewed by 549
Abstract
Although various studies on monitoring dog behavior have been conducted, methods that can minimize or compensate data noise are required. This paper proposes multimodal data-based dog behavior recognition that fuses video and sensor data using a camera and a wearable device. The video [...] Read more.
Although various studies on monitoring dog behavior have been conducted, methods that can minimize or compensate data noise are required. This paper proposes multimodal data-based dog behavior recognition that fuses video and sensor data using a camera and a wearable device. The video data represent the moving area of dogs to detect the dogs. The sensor data represent the movement of the dogs and extract features that affect dog behavior recognition. Seven types of behavior recognition were conducted, and the results of the two data types were used to recognize the dog’s behavior through a fusion model based on deep learning. Experimentation determined that, among FasterRCNN, YOLOv3, and YOLOv4, the object detection rate and behavior recognition accuracy were the highest when YOLOv4 was used. In addition, the sensor data showed the best performance when all statistical features were selected. Finally, it was confirmed that the performance of multimodal data-based fusion models was improved over that of single data-based models and that the CNN-LSTM-based model had the best performance. The method presented in this study can be applied for dog treatment or health monitoring, and it is expected to provide a simple way to estimate the amount of activity. Full article
(This article belongs to the Special Issue Intelligent Computing for Big Data)
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Article
Materials Separation via the Matrix Method Employing Energy-Discriminating X-ray Detection
Appl. Sci. 2022, 12(6), 3198; https://doi.org/10.3390/app12063198 - 21 Mar 2022
Viewed by 402
Abstract
The majority of lab-based X-ray sources are polychromatic and are not easily tunable, which can make the 3D quantitative analysis of multi-component samples challenging. The lack of effective materials separation when using conventional X-ray tube sources has motivated the development of a number [...] Read more.
The majority of lab-based X-ray sources are polychromatic and are not easily tunable, which can make the 3D quantitative analysis of multi-component samples challenging. The lack of effective materials separation when using conventional X-ray tube sources has motivated the development of a number of potential solutions including the application of dual-energy X-ray computed tomography (CT) as well as the use of X-ray filters. Here, we demonstrate the simultaneous decomposition of two low-density materials via inversion of the linear attenuation matrices using data from the energy-discriminating PiXirad detector. A key application for this method is soft-tissue differentiation which is widely used in biological and medical imaging. We assess the effectiveness of this approach using both simulation and experiment noting that none of the materials investigated here incorporate any contrast enhancing agents. By exploiting the energy discriminating properties of the detector, narrow energy bands are created resulting in multiple quasi-monochromatic images being formed using a broadband polychromatic source. Optimization of the key parameters for materials separation is first demonstrated in simulation followed by experimental validation using a phantom test sample in 2D and a small-animal model in 3D. Full article
(This article belongs to the Special Issue X-ray Medical and Biological Imaging)
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Article
Acute Effects of Different Intensities during Bench Press Exercise on the Mechanical Properties of Triceps Brachii Long Head
Appl. Sci. 2022, 12(6), 3197; https://doi.org/10.3390/app12063197 - 21 Mar 2022
Cited by 1 | Viewed by 436
Abstract
This study aimed to analyze acute changes in the muscle mechanical properties of the triceps brachii long head after bench press exercise performed at different external loads and with different intensities of effort along with power performance. Ten resistance-trained males (age: 27.7 ± [...] Read more.
This study aimed to analyze acute changes in the muscle mechanical properties of the triceps brachii long head after bench press exercise performed at different external loads and with different intensities of effort along with power performance. Ten resistance-trained males (age: 27.7 ± 3.7 yr, body mass: 90.1 ± 17.1 kg, height: 184 ± 4 cm; experience in resistance training: 5.8 ± 2.6 yr, relative one-repetition maximum (1RM) in the bench press: 1.23 ± 0.22 kg/body mass) performed two different testing conditions in a randomized order. During the experimental session, participants performed four successive sets of two repetitions of the bench press exercise at: 50, 70, and 90% 1RM, respectively, followed by a set at 70% 1RM performed until failure, with a 4 min rest interval between each set. Immediately before and after each set, muscle mechanical properties of the dominant limb triceps brachii long head were assessed via a Myoton device. To determine fatigue, peak and average barbell velocity were measured at 70% 1RM and at 70% 1RM until failure (only first and second repetition). In the control condition, only muscle mechanical properties at the same time points after the warm-up were assessed. The intraclass correlation coefficients indicated “poor” to “excellent” reliability for decrement, relaxation time, and creep. Therefore, these variables were excluded from further analysis. Three-way ANOVAs (2 groups × 2 times × 4 loads) indicated a statistically significant group × time interaction for muscle tone (p = 0.008). Post hoc tests revealed a statistically significant increase in muscle tone after 70% 1RM (p = 0.034; ES = 0.32) and 90% 1RM (p = 0.011; ES = 0.56). No significant changes were found for stiffness. The t-tests indicated a significant decrease in peak (p = 0.001; ES = 1.02) and average barbell velocity (p = 0.008; ES = 0.8) during the first two repetitions of a set at 70% 1RM until failure in comparison to the set at 70% 1RM. The results indicate that low-volume, high-load resistance exercise immediately increases muscle tone but not stiffness. Despite no significant changes in the mechanical properties of the muscle being registered simultaneously with a decrease in barbell velocity, there was a trend of increased muscle tone. Therefore, further studies with larger samples are required to verify whether muscle tone could be a sensitive marker to detect acute muscle fatigue. Full article
(This article belongs to the Special Issue Epigenetic and Transcriptional Regulation in Muscle Cells)
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Article
Stochastic Models and Control of Anchoring Mechanisms for Grasping in Microgravity
Appl. Sci. 2022, 12(6), 3196; https://doi.org/10.3390/app12063196 - 21 Mar 2022
Cited by 1 | Viewed by 374
Abstract
Robots equipped with anchoring mechanisms have attractive applications in asteroid exploration. However, complex application scenarios bring great challenges to the modeling and control of anchoring mechanisms. This paper presents a grasping model and control method for an anchoring mechanism for asteroid exploration. First, [...] Read more.
Robots equipped with anchoring mechanisms have attractive applications in asteroid exploration. However, complex application scenarios bring great challenges to the modeling and control of anchoring mechanisms. This paper presents a grasping model and control method for an anchoring mechanism for asteroid exploration. First, the structure of the anchoring mechanism is demonstrated. Second, stochastic grasping models based on surface properties are established. The effectiveness of the grasping model is verified by experiments. A stiffness-modeling method of the microspine is proposed. On this basis, the stochastic grasping model of the anchoring mechanism is established, and the grasping cloud diagram of the anchoring mechanism is drawn. Third, in order to reduce the collision force between the anchor mechanism and the asteroid surface, a control method for the anchoring mechanism in the movement process is proposed based on the motion mode of the asteroid-exploration robot. Finally, a prototype is developed, and the experimental results validate the motion ability of the robot and the control method. Full article
(This article belongs to the Special Issue Mechanisms and Robotics in Astronautic and Deep Space Exploration)
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Article
Aerodynamic Optimization and Analysis of Low Reynolds Number Propeller with Gurney Flap for Ultra-High-Altitude Unmanned Aerial Vehicle
Appl. Sci. 2022, 12(6), 3195; https://doi.org/10.3390/app12063195 - 21 Mar 2022
Viewed by 420
Abstract
Ultra-high-altitude unmanned aerial vehicles have created a high demand for the performance of propellers under low Reynolds numbers, while the efficiency of such propellers by the existing design framework has reached a bottleneck. This paper explores the possibility of extending the Gurney flap [...] Read more.
Ultra-high-altitude unmanned aerial vehicles have created a high demand for the performance of propellers under low Reynolds numbers, while the efficiency of such propellers by the existing design framework has reached a bottleneck. This paper explores the possibility of extending the Gurney flap on low Reynolds number propellers to achieve efficiency breakthrough. An iterative optimization strategy for propellers with Gurney flaps is established, in which cross-sectional airfoils can be continuously optimized under updated Reynolds numbers and lift coefficients. A computational fluid dynamics (CFD) simulation based on the γ-Reθ model was used as an aerodynamic analysis method. Propellers with and without Gurney flaps were optimized successively. Optimal results were analyzed using the CFD method. Results showed that an optimal propeller with a Gurney flap can achieve an efficiency of 82.0% in cruising conditions, which is 1.8% higher than an optimal propeller without a Gurney flap. Compared with the latter, the consumed power of the optimal propeller with a Gurney flap can be reduced by 2.2% with the same advance speed. Furthermore, the variation of the improvement by the Gurney flap propeller, along with its Reynolds number, was studied. A wind tunnel test indicates that the performance of the propellers obtained by the CFD method are in good agreement with the test results. Full article
(This article belongs to the Section Aerospace Science and Engineering)
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Article
Thermal–Structural Coupling Analysis of Subsea Connector Sealing Contact
Appl. Sci. 2022, 12(6), 3194; https://doi.org/10.3390/app12063194 - 21 Mar 2022
Viewed by 463
Abstract
Taking a subsea collet connector as an example, the contact characteristics of the sealing structure of the subsea connector under thermal–structural coupling were studied. Considering the heat transfer problem of the subsea connector in deep water, the heat transfer model of seawater layer [...] Read more.
Taking a subsea collet connector as an example, the contact characteristics of the sealing structure of the subsea connector under thermal–structural coupling were studied. Considering the heat transfer problem of the subsea connector in deep water, the heat transfer model of seawater layer between sealing structures was established, and the relationship between equivalent thermal conductivity, composite heat transfer coefficient, and temperature was determined. The steady-state temperature field distribution of the connector under the action of the internal high-temperature oil and gas and external low-temperature seawater was obtained. Considering the stress and deformation of the subsea connector under the thermal load, the thermal–structural coupling analysis model of the steady-state temperature field was established, and the thermal stress theoretical analysis and numerical simulation of the key sealing structures of the connector were compared and verified. Analysis of coupled stress calculation, for example, under a steady-state temperature field, was carried out on the sealing structure of the subsea connector. At the same time, the pressure shock mode under a steady temperature field was analyzed, which showed that the lenticular sealing gasket is sensitive to high pressure under high-temperature conditions. Full article
(This article belongs to the Special Issue Structural Design and Computational Methods)
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Article
Inkjet-Printed Flexible Strain-Gauge Sensor on Polymer Substrate: Topographical Analysis of Sensitivity
Appl. Sci. 2022, 12(6), 3193; https://doi.org/10.3390/app12063193 - 21 Mar 2022
Viewed by 416
Abstract
Inkjet-printed strain gauges on flexible substrates have recently been investigated for biomedical motion detection as well as the monitoring of structural deformation. This study performed a topographical analysis of an inkjet-printed strain gauge constructed using silver conductive ink on a PET (polyethylene terephthalate) [...] Read more.
Inkjet-printed strain gauges on flexible substrates have recently been investigated for biomedical motion detection as well as the monitoring of structural deformation. This study performed a topographical analysis of an inkjet-printed strain gauge constructed using silver conductive ink on a PET (polyethylene terephthalate) substrate. Serpentine strain-gauge sensors of various thicknesses and widths were fabricated using inkjet printing and oven sintering. The fabricated gauge sensors were attached to curved surfaces, and gauge factors ranging from 2.047 to 3.098 were recorded. We found that the cross-sectional area of the printed strain gauge was proportional to the gauge factor. The correlation was mathematically modelled as y = 0.4167ln(x) + 1.3837, for which the coefficient of determination (R2) was 0.8383. Full article
(This article belongs to the Special Issue The Latest Developments and Applications of Printed Electronics)
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Review
Poly(lactic acid)-Based Electrospun Fibrous Structures for Biomedical Applications
Appl. Sci. 2022, 12(6), 3192; https://doi.org/10.3390/app12063192 - 21 Mar 2022
Cited by 5 | Viewed by 722
Abstract
Poly(lactic acid)(PLA) is an aliphatic polyester that can be derived from natural and renewable resources. Owing to favorable features, such as biocompatibility, biodegradability, good thermal and mechanical performance, and processability, PLA has been considered as one of the most promising biopolymers for biomedical [...] Read more.
Poly(lactic acid)(PLA) is an aliphatic polyester that can be derived from natural and renewable resources. Owing to favorable features, such as biocompatibility, biodegradability, good thermal and mechanical performance, and processability, PLA has been considered as one of the most promising biopolymers for biomedical applications. Particularly, electrospun PLA nanofibers with distinguishing characteristics, such as similarity to the extracellular matrix, large specific surface area and high porosity with small pore size and tunable mechanical properties for diverse applications, have recently given rise to advanced spillovers in the medical area. A variety of PLA-based nanofibrous structures have been explored for biomedical purposes, such as wound dressing, drug delivery systems, and tissue engineering scaffolds. This review highlights the recent advances in electrospinning of PLA-based structures for biomedical applications. It also gives a comprehensive discussion about the promising approaches suggested for optimizing the electrospun PLA nanofibrous structures towards the design of specific medical devices with appropriate physical, mechanical and biological functions. Full article
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Article
An Efficient Method for Biomedical Entity Linking Based on Inter- and Intra-Entity Attention
Appl. Sci. 2022, 12(6), 3191; https://doi.org/10.3390/app12063191 - 21 Mar 2022
Viewed by 404
Abstract
Biomedical entity linking is an important research problem for many downstream tasks, such as biomedical intelligent question answering, information retrieval, and information extraction. Biomedical entity linking is the task of mapping mentions in medical texts to standard entities in a given knowledge base. [...] Read more.
Biomedical entity linking is an important research problem for many downstream tasks, such as biomedical intelligent question answering, information retrieval, and information extraction. Biomedical entity linking is the task of mapping mentions in medical texts to standard entities in a given knowledge base. Recently, BERT-based models have achieved state-of-the-art results on the biomedical entity linking task. Although this type of method is effective, it brings challenges for fine-tuning and online services in practical industries due to a large number of model parameters and long inference time. In addition, due to the numerous surface variants of biomedical mentions, it is difficult for a single matching module to achieve good results. To address the challenge, we propose an efficient biomedical entity linking method that integrates inter- and intra-entity attention to better capture the information between medical entity mentions and candidate entities themselves and each other, and the model in this paper is more lightweight. Experimental results show that our method achieves competitive performance on two biomedical benchmark datasets, NCBI and ADR, with an accuracy rate of 91.28% and 93.13%, respectively. Moreover, it also achieves comparable or even better results compared to the BERT-based entity linking method while having far fewer model parameters and very high inference speed. Full article
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Article
A Deep Learning Ensemble Method to Visual Acuity Measurement Using Fundus Images
Appl. Sci. 2022, 12(6), 3190; https://doi.org/10.3390/app12063190 - 21 Mar 2022
Cited by 1 | Viewed by 462
Abstract
Visual acuity (VA) is a measure of the ability to distinguish shapes and details of objects at a given distance and is a measure of the spatial resolution of the visual system. Vision is one of the basic health indicators closely related to [...] Read more.
Visual acuity (VA) is a measure of the ability to distinguish shapes and details of objects at a given distance and is a measure of the spatial resolution of the visual system. Vision is one of the basic health indicators closely related to a person’s quality of life. It is one of the first basic tests done when an eye disease develops. VA is usually measured by using a Snellen chart or E-chart from a specific distance. However, in some cases, such as the unconsciousness of patients or diseases, i.e., dementia, it can be impossible to measure the VA using such traditional chart-based methodologies. This paper provides a machine learning-based VA measurement methodology that determines VA only based on fundus images. In particular, the levels of VA, conventionally divided into 11 levels, are grouped into four classes and three machine learning algorithms, one SVM model and two CNN models, are combined into an ensemble method in order to predict the corresponding VA level from a fundus image. Based on a performance evaluation conducted using randomly selected 4000 fundus images, we confirm that our ensemble method can estimate with 82.4% of the average accuracy for four classes of VA levels, in which each class of Class 1 to Class 4 identifies the level of VA with 88.5%, 58.8%, 88%, and 94.3%, respectively. To the best of our knowledge, this is the first paper on VA measurements based on fundus images using deep machine learning. Full article
(This article belongs to the Special Issue Applications of Artificial Intelligence in Medicine Practice)
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Article
Iterative Dynamic Critical Path Scheduling: An Efficient Technique for Offloading Task Graphs in Mobile Edge Computing
Appl. Sci. 2022, 12(6), 3189; https://doi.org/10.3390/app12063189 - 21 Mar 2022
Viewed by 351
Abstract
Recent years have witnessed a paradigm shift from centralized cloud computing to decentralized edge computing. As a key enabler technique in edge computing, computation offloading migrates computation-intensive tasks from resource-limited devices to nearby devices, optimizing service latency and energy consumption. In this paper, [...] Read more.
Recent years have witnessed a paradigm shift from centralized cloud computing to decentralized edge computing. As a key enabler technique in edge computing, computation offloading migrates computation-intensive tasks from resource-limited devices to nearby devices, optimizing service latency and energy consumption. In this paper, we investigate the problem of offloading task graphs in edge computing scenarios. Previous work based on list-scheduling heuristics is likely to suffer from severe processor time wastage due to intricate task dependencies and data transfer requirements. To this end, we propose a novel offloading algorithm, referred to as Iterative Dynamic Critical Path Scheduling (IDCP). IDCP minimizes the makespan by iteratively migrating tasks to keep shortening the dynamic critical path. Through IDCP, what is managed are essentially the sequences among tasks, including task dependencies and scheduled sequences on processors. Since we only schedule sequences here, the actual start time of each task is not fixed during the scheduling process, which effectively helps to avoid unfavorable schedules. Such flexibilities also offer us much space for continuous scheduling optimizations. Our experimental results show that our algorithm significantly outperforms existing list-scheduling heuristics in various scenarios, which demonstrates the effectiveness and competitiveness of our algorithm. Full article
(This article belongs to the Collection Energy-efficient Internet of Things (IoT))
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Article
Content Curation in E-Learning: A Case of Study with Spanish Engineering Students
Appl. Sci. 2022, 12(6), 3188; https://doi.org/10.3390/app12063188 - 21 Mar 2022
Viewed by 626
Abstract
Over the last decade, e-learning and the use of digital tools have received a great boost in higher education. This paper presents a content curation methodology to assess the acquisition of specific content and soft skills during the attainment of a Degree in [...] Read more.
Over the last decade, e-learning and the use of digital tools have received a great boost in higher education. This paper presents a content curation methodology to assess the acquisition of specific content and soft skills during the attainment of a Degree in Industrial Electronic Engineering at the University of Jaén. In this teaching–learning experience, 101 engineering students were involved in activities with digital tools related to content curation, and four steps were proposed: search, select, sense making, and share. As evaluation tools, a rubric and a questionnaire of the digital tools were proposed. Moreover, a curation index was defined in order to assess the degree of achievement of the content curation. The academic results after using the rubric were better than previous years. The average content curation index obtained was 53.53. Of the four evaluated steps, search and sense making had the lowest scores and, therefore, these steps should be further developed in the future. In addition, the Kaiser–Meyer–Olkin test and Pearson’s correlation were used for analyzing the results of the questionnaires. It was concluded that the experience had a great impact on the skills related to collaborative work, digital information management, and lifelong learning, which are transversal skills at the university level. Thus, the results highlight the great educational potential of content curation. Full article
(This article belongs to the Special Issue Application of Technologies in E-learning Assessment)
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Article
Benchmarking Various Pseudo-Measurement Data Generation Techniques in a Low-Voltage State Estimation Pilot Environment
Appl. Sci. 2022, 12(6), 3187; https://doi.org/10.3390/app12063187 - 21 Mar 2022
Viewed by 380
Abstract
Distribution system state estimation (DSSE) is a valuable step for DSOs toward tackling the challenges of transitioning to a more sustainable energy system and the evolution and proliferation of electric cars and power electronic devices. However, on the LV level, implementation has only [...] Read more.
Distribution system state estimation (DSSE) is a valuable step for DSOs toward tackling the challenges of transitioning to a more sustainable energy system and the evolution and proliferation of electric cars and power electronic devices. However, on the LV level, implementation has only taken place in a few pilot projects. In this paper, an LV DSSE method is presented and implemented in four real Hungarian LV supply areas, according to well-defined scenarios. Pseudo-measurement datasets are generated from AACs and SLPs, which have been used in different combinations on networks built with different accuracies in terms of load placement. The paper focuses on the critical aspects of finding accurate and coherent information on network topology with automated management of information systems, real LV network implementation for power flow calculation and managing portions of the network characterized by uncertain or inconsistent line lengths. A refining algorithm is implemented for the integrated network information system (INIS) models. The published method estimates node voltages with a relative error of less than 1% when using AACs, and a meter-placement method to reduce the maximum value of relative errors in future scenarios is also presented. It is shown that the observation of node voltages can be improved with the usage of AACs and SLPs, and with optimal meter placement. Full article
(This article belongs to the Special Issue Data Science Applications in Medium/Low Voltage Smart Grids)
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Article
Low-Cost Sensors Accuracy Study and Enhancement Strategy
Appl. Sci. 2022, 12(6), 3186; https://doi.org/10.3390/app12063186 - 21 Mar 2022
Cited by 4 | Viewed by 416
Abstract
Today, low-cost sensors in various civil engineering sectors are gaining the attention of researchers due to their reduced production cost and their applicability to multiple nodes. Low-cost sensors also have the advantage of easily connecting to low-cost microcontrollers such as Arduino. A low-cost, [...] Read more.
Today, low-cost sensors in various civil engineering sectors are gaining the attention of researchers due to their reduced production cost and their applicability to multiple nodes. Low-cost sensors also have the advantage of easily connecting to low-cost microcontrollers such as Arduino. A low-cost, reliable acquisition system based on Arduino technology can further reduce the price of data acquisition and monitoring, which can make long-term monitoring possible. This paper introduces a wireless Internet-based low-cost data acquisition system consisting of Raspberry Pi and several Arduinos as signal conditioners. This study investigates the beneficial impact of similar sensor combinations, aiming to improve the overall accuracy of several sensors with an unknown accuracy range. The paper then describes an experiment that gives valuable information about the standard deviation, distribution functions, and error level of various individual low-cost sensors under different environmental circumstances. Unfortunately, these data are usually missing and sometimes assumed in numerical studies targeting the development of structural system identification methods. A measuring device consisting of a total of 75 contactless ranging sensors connected to two microcontrollers (Arduinos) was designed to study the similar sensor combination theory and present the standard deviation and distribution functions. The 75 sensors include: 25 units of HC-SR04 (analog), 25 units of VL53L0X, and 25 units of VL53L1X (digital). Full article
(This article belongs to the Special Issue Artificial Intelligence Technologies for Structural Health Monitoring)
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Article
Experimental Analysis on the Impact of Current on the Strength and Lifespan of a Ni-Ti Element
Appl. Sci. 2022, 12(6), 3185; https://doi.org/10.3390/app12063185 - 21 Mar 2022
Viewed by 321
Abstract
Intelligent materials, especially materials with shape memory, are an important discovery, with technical applications in the medical and aerospace field, among others, which led to the development of systems and applications with multiple advantages and disadvantages due to ignorance about their functionality. This [...] Read more.
Intelligent materials, especially materials with shape memory, are an important discovery, with technical applications in the medical and aerospace field, among others, which led to the development of systems and applications with multiple advantages and disadvantages due to ignorance about their functionality. This paper presents an application developed in the research laboratory for determining and monitoring the behavior of a material element with Ni-Ti shape memory, and its lifespan. The application allows the stress level of the Ni-Ti element subjected to numerous repeated cycles of deformation to be determined by supplying it to a constant electric current. Thus, the results show the variation of the Ni-Ti element force, in the form of a spring, at the ambient temperature variations as well as force variations at different numbers of attempts. The Ni-Ti alloy has both shape retention and superelasticity properties, being the most common in the fields of applicability. Due to its unique properties, it can be used in the most demanding applications in the medical field, usually involving difficult conditions of resistance to fatigue. Full article
(This article belongs to the Special Issue New Materials and Advanced Procedures of Obtaining and Processing II)
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Article
Study on Mechanical Properties of Modified Polyurethane Concrete at Different Temperatures
Appl. Sci. 2022, 12(6), 3184; https://doi.org/10.3390/app12063184 - 21 Mar 2022
Viewed by 388
Abstract
The objective of the present research was to study the effect of temperature on the mechanical properties, failure mode and uniaxial compression constitutive relationship of a modified polyurethane concrete. A total of 24 cube and 27 prism specimens were fabricated, and the uniformity [...] Read more.
The objective of the present research was to study the effect of temperature on the mechanical properties, failure mode and uniaxial compression constitutive relationship of a modified polyurethane concrete. A total of 24 cube and 27 prism specimens were fabricated, and the uniformity of the polyurethane concrete was checked. The compressive test, splitting tensile test and static uniaxial compression test were carried out at 0, 15, 40 and 60 °C. The failure mode, cube compressive strength, splitting tensile strength, axial compressive strength, elastic modulus and the compressive stress–strain curves of the modified polyurethane concrete were obtained. Based on the experimental results, a uniaxial compression constitutive model of the modified polyurethane concrete considering temperature characteristics was proposed. The results show that the elastic modulus, cubic compressive strength, splitting tensile strength and axial compressive strength of the modified polyurethane concrete decrease with the increase of temperature, and the peak strain and ultimate strain increase significantly. When the temperature rises from 0 to 60 °C, the cubic compressive strength, splitting tensile strength and axial compressive strength are decreased by 67.1%, 66.4% and 73.3%, respectively. The calculation results of the proposed constitutive model are in good agreement with the test results. The results are expected to guide the application of the modified polyurethane concrete in bridge deck pavement. Full article
(This article belongs to the Special Issue Road Materials and Sustainable Pavement Design)
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Review
Effect of Magnetic and Electrical Fields on Yield, Shelf Life and Quality of Fruits
Appl. Sci. 2022, 12(6), 3183; https://doi.org/10.3390/app12063183 - 21 Mar 2022
Cited by 1 | Viewed by 506
Abstract
The presented article is a review of the literature reports on the influence of magnetic and electric fields on the growth, yield, ripening, and durability of fruits and their quality. The article shows the potential application of MF and EF in agricultural production. [...] Read more.
The presented article is a review of the literature reports on the influence of magnetic and electric fields on the growth, yield, ripening, and durability of fruits and their quality. The article shows the potential application of MF and EF in agricultural production. Magnetic and electrical fields increase the shelf life of the fruit and improve its quality. Alternating magnetic fields (AMF) with a value of 0.1–200 mT and a power frequency of 50 Hz or 60 Hz improve plant growth parameters. MF cause an increase in firmness, the rate of maturation, the content of beta-carotene, lycopene, and fructose, sugar concentration, and a reduction in acidity and respiration. The most common is a high-voltage electric field (HVEF) of 2–3.61 kV/cm. These fields extend the shelf life and improve the quality of fruit by decreasing respiration rate and ethylene production. The presented methods seem to be a promising way to increase the quantity and quality of crops in agricultural and fruit production. They are suitable for extending the shelf life of fruit and vegetables during their storage. Further research is needed to develop an accessible and uncomplicated way of applying MF and AEF in agricultural and fruit production. Full article
(This article belongs to the Special Issue Engineering of Smart Agriculture)
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Article
Enhanced Adsorption of Methyl Orange by Mongolian Montmorillonite after Aluminum Pillaring
Appl. Sci. 2022, 12(6), 3182; https://doi.org/10.3390/app12063182 - 21 Mar 2022
Cited by 1 | Viewed by 461
Abstract
This article studies the enhancement of methyl orange (MO) adsorption by Mongolian montmorillonite (MMt) modified by the intercalation of the Keggin Al13 complex, followed by calcination during the pillaring process. The properties of MMt, Al-intercalated MMt (P-MMt), and Al-pillared MMt (P-MMt-C) were [...] Read more.
This article studies the enhancement of methyl orange (MO) adsorption by Mongolian montmorillonite (MMt) modified by the intercalation of the Keggin Al13 complex, followed by calcination during the pillaring process. The properties of MMt, Al-intercalated MMt (P-MMt), and Al-pillared MMt (P-MMt-C) were determined using X-ray diffraction (XRD), thermogravimetric analysis (TGA), surface-area analysis, and a field emission scanning electron microscope (FE-SEM). The MO adsorption by modified MMt was subsequently evaluated. The XRD basal distance (d001) and the specific surface area (SSA) increased after the modification of MMt. The TGA results revealed that P-MMt and P-MMt-C had better thermal stability than MMt. The Al-pillared MMt obtained after calcination (e.g., P-MMt-C400) showed a larger basal distance and surface area than that without pillaring. The MO adsorption process of P-MMt-C400 was supposed to be dominated by chemisorption and heterogeneous multilayer adsorption, according to the kinetic and isotherm studies. The maximum adsorption capacity of P-MMt-C400 is 6.23 mg/g. The MO adsorption ability of Al-pillared MMt was contributed by the Keggin Al13 complex attracting MO and the increase in the surface area of macro-, meso- and micro-pores (>1.2 nm). The Al-pillared MMt in this study could be applied as an adsorbent in a water purification system to remove MO or other dye elements. Full article
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Article
Deep Deterministic Policy Gradient with Reward Function Based on Fuzzy Logic for Robotic Peg-in-Hole Assembly Tasks
Appl. Sci. 2022, 12(6), 3181; https://doi.org/10.3390/app12063181 - 21 Mar 2022
Viewed by 445
Abstract
Robot automatic assembly of weak stiffness parts is difficult due to potential deformation during assembly. The robot manipulation cannot adapt to the dynamic contact changes during the assembly process. A robot assembly skill learning system is designed by combining the compliance control and [...] Read more.
Robot automatic assembly of weak stiffness parts is difficult due to potential deformation during assembly. The robot manipulation cannot adapt to the dynamic contact changes during the assembly process. A robot assembly skill learning system is designed by combining the compliance control and deep reinforcement, which could acquire a better robot assembly strategy. In this paper, a robot assembly strategy learning method based on variable impedance control is proposed to solve the robot assembly contact tasks. During the assembly process, the quality evaluation is designed based on fuzzy logic, and the impedance parameters in the assembly process are studied with a deep deterministic policy gradient. Finally, the effectiveness of the method is verified using the KUKA iiwa robot in the weak stiffness peg-in-hole assembly. Experimental results show that the robot obtains the robot assembly strategy with variable compliant in the process of weak stiffness peg-in-hole assembly. Compared with the previous methods, the assembly success rate of the proposed method reaches 100%. Full article
(This article belongs to the Topic Industrial Robotics)
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