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Appl. Sci., Volume 11, Issue 6 (March-2 2021) – 440 articles

Cover Story (view full-size image): The butterfly flaps its wings and simultaneously moves its main body to achieve different flying motions. Its wings and body are coupled in various flight states. Through the analysis of aerodynamic simulation of a multi-rigid butterfly model, an optimal kinematic model can be obtained, and the formation and development of vortex structures are presented. The results reveal that wing flapping and abdominal swinging play a key role in reorienting the “clap and peel” mechanism and that longitudinal flight performance is mainly related to the kinematic parameters of the wing and body, which are instructive for the design of butterfly-inspired aircraft. View this paper
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Article
Spondias mombin Seed Oil Compounds Identification by Raman Spectroscopy and NMR
Appl. Sci. 2021, 11(6), 2886; https://doi.org/10.3390/app11062886 - 23 Mar 2021
Viewed by 498
Abstract
Spondias mombin L. has been used in traditional medicine to treat some cases such as infections and inflammations. Some researchers have reported that its biological components, such as carotenoids, carotenes, and phenols, have been characterized primarily by HPLC analysis. Here, we report on [...] Read more.
Spondias mombin L. has been used in traditional medicine to treat some cases such as infections and inflammations. Some researchers have reported that its biological components, such as carotenoids, carotenes, and phenols, have been characterized primarily by HPLC analysis. Here, we report on the characterization of Spondias mombin L. seed oil by Raman spectroscopy, and the profile identification of fatty acids by 1H-NMR and 13C-NMR spectroscopy. The oil was extracted from different weight volumes of seeds using organic solvent, and each batch was characterized. The analysis of the fatty acid profile by NMR indicated that the seed oil is highly unsaturated (monounsaturated: 29.4% and polyunsaturated: 43.5%). Molecular Raman vibrations at 1006, 1158 and 1523 cm−1 showed the presence of carotenoids, which in turn performed an antioxidant activity. This was demonstrated by a 2,2′-Azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) diammonium salt (ABTS) method. The cell viability in colon cancer cells was promoted in the presence of the oil. The compounds identified in this study from seed oil could be an interesting proposal for food or pharmaceutical applications. Full article
(This article belongs to the Special Issue Biological and Medical Applications of Vibrational Spectroscopy)
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Article
Development of Autonomous Robot Osteotomy for Mandibular Ramal Bone Harvest and Evaluation of Its Accuracy: A Phantom Mandible-Based Trial
Appl. Sci. 2021, 11(6), 2885; https://doi.org/10.3390/app11062885 - 23 Mar 2021
Viewed by 367
Abstract
An autonomous robot osteotomy using direct coordinate determination for registering was developed, and the accuracy of the designed osteotomy along the preprogrammed plan was evaluated. Furthermore, the accuracy of the robotic and manual osteotomy was compared in regard to cut position, length, angle [...] Read more.
An autonomous robot osteotomy using direct coordinate determination for registering was developed, and the accuracy of the designed osteotomy along the preprogrammed plan was evaluated. Furthermore, the accuracy of the robotic and manual osteotomy was compared in regard to cut position, length, angle and depth. A light-weight robot was used in this study, with an electric gripper. Twenty stone models were used to evaluate accuracy of osteotomy and sixteen mandible phantoms were used to simulate the ramal bone harvest osteotomy for comparison between robotic and manual surgery. In the stone model experiment, the absolute mean values for osteotomy errors for position, length, angle, and depth were 0.93 ± 0.45 mm, 0.81 ± 0.34 mm, 1.26 ± 1.35°, and 1.19 ± 0.73 mm, respectively. In the mandible phantom model experiment, the robotic surgery showed lower errors for position, length and angle (0.70 ± 0.34 mm, 0.35 ± 0.19 mm and 1.32 ± 0.96°) and somewhat higher errors for depth (0.59 ± 0.46 mm) than manual surgery (1.83 ± 0.65 mm, 0.62 ± 0.37 mm, 5.96 ± 3.47° and 0.40 ± 0.31 mm). This study may provide a basis for developing clinical application of an autonomous robot osteotomy. Full article
(This article belongs to the Section Applied Dentistry)
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Article
COVID-19 Diagnosis in Chest X-rays Using Deep Learning and Majority Voting
Appl. Sci. 2021, 11(6), 2884; https://doi.org/10.3390/app11062884 - 23 Mar 2021
Viewed by 607
Abstract
The COVID-19 disease has spread all over the world, representing an intriguing challenge for humanity as a whole. The efficient diagnosis of humans infected by COVID-19 still remains an increasing need worldwide. The chest X-ray imagery represents, among others, one attractive means to [...] Read more.
The COVID-19 disease has spread all over the world, representing an intriguing challenge for humanity as a whole. The efficient diagnosis of humans infected by COVID-19 still remains an increasing need worldwide. The chest X-ray imagery represents, among others, one attractive means to detect COVID-19 cases efficiently. Many studies have reported the efficiency of using deep learning classifiers in diagnosing COVID-19 from chest X-ray images. They conducted several comparisons among a subset of classifiers to identify the most accurate. In this paper, we investigate the potential of the combination of state-of-the-art classifiers in achieving the highest possible accuracy for the detection of COVID-19 from X-ray. For this purpose, we conducted a comprehensive comparison study among 16 state-of-the-art classifiers. To the best of our knowledge, this is the first study considering this number of classifiers. This paper’s innovation lies in the methodology that we followed to develop the inference system that allows us to detect COVID-19 with high accuracy. The methodology consists of three steps: (1) comprehensive comparative study between 16 state-of-the-art classifiers; (2) comparison between different ensemble classification techniques, including hard/soft majority, weighted voting, Support Vector Machine, and Random Forest; and (3) finding the combination of deep learning models and ensemble classification techniques that lead to the highest classification confidence on three classes. We found that using the Majority Voting approach is an adequate strategy to adopt in general cases for this task and may achieve an average accuracy up to 99.314%. Full article
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Article
Variable Stiffness Mechanism for the Reduction of Cutting Forces in Robotic Deburring
Appl. Sci. 2021, 11(6), 2883; https://doi.org/10.3390/app11062883 - 23 Mar 2021
Viewed by 489
Abstract
One of the main issues related to robotic deburring is that the tool can get damaged or stopped when the burr thickness exceeds a certain threshold. The aim of this work is to devise a mechanism that can reduce cutting forces automatically, in [...] Read more.
One of the main issues related to robotic deburring is that the tool can get damaged or stopped when the burr thickness exceeds a certain threshold. The aim of this work is to devise a mechanism that can reduce cutting forces automatically, in the event that the burr is too high, and is able to return to the baseline configuration when the burr thickness is acceptable again. On the one hand, in normal cutting conditions, the mechanism should have high stiffness to ensure high cutting precision. On the other hand, when the burr is too high the mechanism should exploit its compliance to reduce the cutting forces and, as a consequence, a second cutting cycle will be necessary to completely remove the burr. After the conceptual design of the mechanism and the specification of the desired stiffness curve, the main design parameters of the system are derived thanks to an optimization method. The effectiveness of the proposed mechanism is verified by means of dynamic simulations using selected test cases. A reduction up to 60% of the cutting forces is obtained, considering a steel burr up to 6 mm high. Full article
(This article belongs to the Special Issue Innovative Robot Designs and Approaches)
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Article
Fault Current and Voltage Estimation for Pole-to-Pole Faults in Modular Multilevel Converter Based DC Grids Considering AC Active Power
Appl. Sci. 2021, 11(6), 2882; https://doi.org/10.3390/app11062882 - 23 Mar 2021
Viewed by 359
Abstract
DC short-circuit faults are one of the challenges for modular multilevel converter (MMC) based DC grid. It is vital for proper design of protection system to estimate the fault currents and voltages. The existing calculation methods based on RLC equivalent model of MMC [...] Read more.
DC short-circuit faults are one of the challenges for modular multilevel converter (MMC) based DC grid. It is vital for proper design of protection system to estimate the fault currents and voltages. The existing calculation methods based on RLC equivalent model of MMC have enough accuracy in estimating the branch currents but suffer from poor accuracy in estimating the node voltages. To better reflect the dynamics of MMC control during the fault, MMC is equivalent to a RLC series circuit in parallel with a variable controlled current source. This model not only considers the discharge of sub-module capacitors but also the AC active power and MMC control. Then, based on the discrete adjoint model of the equivalent MMC model and the RL series equivalent model of DC lines, the fault voltages and currents for the pre-fault and faulted DC grids could be easily obtained. From the aspect of power balance, the importance of AC active power on estimating the fault currents and voltages is discussed then. At last, based on the Zhangbei bipolar DC grid, comparisons are conducted between the simulations on PSCAD, the numerical calculation under the proposed method and the existing methods. The results show that the proposed method and the existing methods are both able to accurately estimate the fault currents within a relative error of 1%. However, compared with the error of the existing methods in calculating the fault voltages, the relative error for the proposed method is limited to less than 5% for the whole DC gird. Full article
(This article belongs to the Special Issue Power Electronics in Power Networks)
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Review
The Effect of Removable Orthodontic Appliances on Oral Microbiota: A Systematic Review
Appl. Sci. 2021, 11(6), 2881; https://doi.org/10.3390/app11062881 - 23 Mar 2021
Cited by 1 | Viewed by 464
Abstract
Background (1): Removable orthodontic appliances may favor plaque accumulation and oral microbe colonization. This might be associated with intraoral adverse effects on enamel or periodontal tissues. The proposed systematic review was carried out to evaluate qualitatively and quantitatively the microbiological changes occurring during [...] Read more.
Background (1): Removable orthodontic appliances may favor plaque accumulation and oral microbe colonization. This might be associated with intraoral adverse effects on enamel or periodontal tissues. The proposed systematic review was carried out to evaluate qualitatively and quantitatively the microbiological changes occurring during orthodontic therapy with removable orthodontic appliances. Methods (2): PubMed, Cochrane Library, Embase, Web of Science, Scopus, Ovid Medline, and Dentistry and Oral Sciences Source were searched. The research included every article published up to January 2020. The Preferred Reporting Items for Reporting Systematic reviews and Meta Analyses (PRISMA) protocol and the “Swedish Council on Technology Assessment in Health Care Criteria for Grading Assessed Studies” (SBU) method were adopted to conduct this systematic review. Results (3): The current study has a moderate evidence, demonstrating that removable appliances do influence the oral microbiota. Significant alterations occur just 15 days after the beginning of therapy, independently from the type of appliance. Furthermore, the levels of oral pathogens decrease significantly or even returned to pre-treatment levels several months later the therapy end. Conclusions (4): This review suggests that orthodontic treatment with removable appliances induces changes to oral microflora, but these alterations might not be permanent. Full article
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Review
Applicability of Clinical Decision Support in Management among Patients Undergoing Cardiac Surgery in Intensive Care Unit: A Systematic Review
Appl. Sci. 2021, 11(6), 2880; https://doi.org/10.3390/app11062880 - 23 Mar 2021
Viewed by 424
Abstract
The advances achieved in recent decades regarding cardiac surgery have led to a new risk that goes beyond surgeons’ dexterity; postoperative hours are crucial for cardiac surgery patients and are usually spent in intensive care units (ICUs), where the patients need to be [...] Read more.
The advances achieved in recent decades regarding cardiac surgery have led to a new risk that goes beyond surgeons’ dexterity; postoperative hours are crucial for cardiac surgery patients and are usually spent in intensive care units (ICUs), where the patients need to be continuously monitored to adjust their treatment. Clinical decision support systems (CDSSs) have been developed to take this real-time information and provide clinical suggestions to physicians in order to reduce medical errors and to improve patient recovery. In this review, an initial total of 499 papers were considered after identification using PubMed, Web of Science, and CINAHL. Twenty-two studies were included after filtering, which included the deletion of duplications and the exclusion of titles or abstracts that were not of real interest. A review of these papers concluded the applicability and advances that CDSSs offer for both doctors and patients. Better prognosis and recovery rates are achieved by using this technology, which has also received high acceptance among most physicians. However, despite the evidence that well-designed CDSSs are effective, they still need to be refined to offer the best assistance possible, which may still take time, despite the promising models that have already been applied in real ICUs. Full article
(This article belongs to the Special Issue Advances in Information and Communication Technologies (ICT))
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Review
The Application of Virtual Reality in Engineering Education
Appl. Sci. 2021, 11(6), 2879; https://doi.org/10.3390/app11062879 - 23 Mar 2021
Viewed by 624
Abstract
The advancement of VR technology through the increase in its processing power and decrease in its cost and form factor induced the research and market interest away from the gaming industry and towards education and training. In this paper, we argue and present [...] Read more.
The advancement of VR technology through the increase in its processing power and decrease in its cost and form factor induced the research and market interest away from the gaming industry and towards education and training. In this paper, we argue and present evidence from vast research that VR is an excellent tool in engineering education. Through our review, we deduced that VR has positive cognitive and pedagogical benefits in engineering education, which ultimately improves the students’ understanding of the subjects, performance and grades, and education experience. In addition, the benefits extend to the university/institution in terms of reduced liability, infrastructure, and cost through the use of VR as a replacement to physical laboratories. There are added benefits of equal educational experience for the students with special needs as well as distance learning students who have no access to physical labs. Furthermore, recent reviews identified that VR applications for education currently lack learning theories and objectives integration in their design. Hence, we have selected the constructivist and variation learning theories as they are currently successfully implemented in engineering education, and strong evidence shows suitability of implementation in VR for education. Full article
(This article belongs to the Special Issue Applications of Virtual, Augmented, and Mixed Reality)
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Article
Dynamic Energy Efficient Control of Induction Machines Using Anticipative Flux Templates
Appl. Sci. 2021, 11(6), 2878; https://doi.org/10.3390/app11062878 - 23 Mar 2021
Viewed by 475
Abstract
Energy efficiency optimization techniques for steady state operation of induction machines are the state-of-the-art, and many methods have already been developed. However, many real-world industrial and electric vehicle applications cannot be considered to be in steady state operation. The focus of this contribution [...] Read more.
Energy efficiency optimization techniques for steady state operation of induction machines are the state-of-the-art, and many methods have already been developed. However, many real-world industrial and electric vehicle applications cannot be considered to be in steady state operation. The focus of this contribution is on the efficiency optimization of induction machines in dynamic operation. Online dynamic operation is challenging due to the computational complexity and the required low sample times in an inverter. An offline optimization is therefore conducted to gain knowledge. Based on this offline optimal solution, a simple and easy to implement template based solution is developed. This approach aims at replicating the solution found by the offline optimization by resembling the shape and anticipative characteristics of the optimal flux trajectory. The energy efficiency improvement of the template based solution is verified by simulations and measurements on a test bench and using a real-world drive cycle scenario. For comparison, a model predictive numerical online optimization is investigated too. Full article
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Article
Process Simulation of Steam Gasification of Torrefied Woodchips in a Bubbling Fluidized Bed Reactor Using Aspen Plus
Appl. Sci. 2021, 11(6), 2877; https://doi.org/10.3390/app11062877 - 23 Mar 2021
Viewed by 382
Abstract
A comprehensive process model is proposed to simulate the steam gasification of biomass in a bubbling fluidized bed reactor using the Aspen Plus simulator. The reactor models are implemented using external FORTRAN codes for hydrodynamic and reaction kinetic calculations. Governing hydrodynamic equations and [...] Read more.
A comprehensive process model is proposed to simulate the steam gasification of biomass in a bubbling fluidized bed reactor using the Aspen Plus simulator. The reactor models are implemented using external FORTRAN codes for hydrodynamic and reaction kinetic calculations. Governing hydrodynamic equations and kinetic reaction rates for char gasification and water-gas shift reactions are obtained from experimental investigations and the literature. Experimental results at different operating conditions from steam gasification of torrefied biomass in a pilot-scale gasifier are used to validate the process model. Gasification temperature and steam-to-biomass ratio promote hydrogen production and improve process efficiencies. The steam-to-biomass ratio is directly proportional to an increase in the content of hydrogen and carbon monoxide, while gas yield and carbon conversion efficiency enhance significantly with increasing temperature. The model predictions are in good agreement with experimental data. The mean error of CO2 shows the highest value of 0.329 for the steam-to-biomass ratio and the lowest deviation is at 0.033 of carbon conversion efficiency, respectively. The validated model is capable of simulating biomass gasification under various operating conditions. Full article
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Article
Investigation of the Structural Response of the MRE-Based MDOF Isolated Structure under Historic Near- and Far-Fault Earthquake Loadings
Appl. Sci. 2021, 11(6), 2876; https://doi.org/10.3390/app11062876 - 23 Mar 2021
Viewed by 448
Abstract
Fixed base structures subjected to earthquake forces are prone to various issues, such as the attraction of greater forces to structure, amplified accelerations to non-structural components, expensive design for better seismic performance, and so forth. Base isolation applied at the foundation of vulnerable [...] Read more.
Fixed base structures subjected to earthquake forces are prone to various issues, such as the attraction of greater forces to structure, amplified accelerations to non-structural components, expensive design for better seismic performance, and so forth. Base isolation applied at the foundation of vulnerable structures is a radical bypass from the conventional approaches utilized by structural engineers. However, the practical implementation of passive base isolation is constrained by factors such as large displacements at isolation level, uplifting forces at isolators, and vulnerability to unpredictable and versatile earthquakes. This study is focused on the evaluation of the smart base isolation system under various harmonic and earthquake loadings. The proposed system employs a magnetorheological elastomer (MRE)—a class of smart materials, based on an adaptive isolation layer under the building structure for its vibration control. The building is idealized as a five-degree-of-freedom (DOF) structure with the mass lumped at each storey. The stiffness of the MRE isolation layer is adjusted using the linear quadratic regulator (LQR) optimal feedback control algorithm. A total of 18 simulations have been performed for the fixed base, passively isolated, and MRE-based isolated structures under a series of earthquake loadings of both a near-fault and far-fault nature for analyzing a total of 306 responses of the structures. The simulation results indicate that MRE-based isolation has significantly reduced all the responses compared to the passively isolated structure for both the near-fault and far-fault earthquake loadings. For harmonic loading, however, the passively isolated structure outperformed the MRE isolated structure in terms of storey drift and acceleration responses. Full article
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Article
Biogeochemical Modelling of Uranium Immobilization and Aquifer Remediation Strategies Near NCCP Sludge Storage Facilities
Appl. Sci. 2021, 11(6), 2875; https://doi.org/10.3390/app11062875 - 23 Mar 2021
Viewed by 381
Abstract
Nitrate is a substance which influences the prevailing redox conditions in groundwater, and in turn the behaviour of U. The study of groundwater in an area with low-level radioactive sludge storage facilities has shown their contamination with sulphate and nitrate anions, uranium, and [...] Read more.
Nitrate is a substance which influences the prevailing redox conditions in groundwater, and in turn the behaviour of U. The study of groundwater in an area with low-level radioactive sludge storage facilities has shown their contamination with sulphate and nitrate anions, uranium, and some associated metals. The uranyl ion content in the most contaminated NO3–Cl–SO4–Na borehole is 2000 times higher (1.58 mg/L) than that in the background water. At the same time, assessment of the main physiological groups of microorganisms showed a maximum number of denitrifying and sulphate-reducing bacteria (e.g., Sulfurimonas) in the water from the same borehole. Biogenic factors of radionuclide immobilization on sandy rocks of upper aquifers have been experimentally investigated. Different reduction rates of NO3, SO42−, Fe(III) and U(VI) with stimulated microbial activity were dependent on the pollution degree. Moreover, 16S rRNA gene analysis of the microbial community after whey addition revealed a significant decrease in microbial diversity and the activation of nonspecific nitrate-reducing bacteria (genera Rhodococcus and Rhodobacter). The second influential factor can be identified as the formation of microbial biofilms on the sandy loam samples, which has a positive effect on U sorption (an increase in Kd value is up to 35%). As PHREEQC physicochemical modelling numerically confirmed, the third most influential factor that drives U mobility is the biogenic-mediated formation of a sulphide redox buffer. This study brings important information, which helps to assess the long-term stability of U in the environment of radioactive sludge storage facilities. Full article
(This article belongs to the Special Issue Sustainable Strategies for Remediation of Contaminated Water and Soil)
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Article
Comparative Tissue Responses of Marine Mollusks on Seasonal Changes in the Northern Adriatic Sea
Appl. Sci. 2021, 11(6), 2874; https://doi.org/10.3390/app11062874 - 23 Mar 2021
Viewed by 362
Abstract
In the shallow Northern Adriatic, marine mollusks are affected by bottom trawling and seafood disturbance. Seasonal oscillations of oceanographic factors additionally influence their physiology, stress responses and survival. Tissue responses to seasonal variations in green ormer (Haliotis tuberculata L.) and Mediterranean scallop [...] Read more.
In the shallow Northern Adriatic, marine mollusks are affected by bottom trawling and seafood disturbance. Seasonal oscillations of oceanographic factors additionally influence their physiology, stress responses and survival. Tissue responses to seasonal variations in green ormer (Haliotis tuberculata L.) and Mediterranean scallop (Pecten jacobaeus L.) in the Northern Adriatic have not been reported. Hence, their biochemical and antioxidant defense properties over seasons were studied and the microanatomical structure of their tissue was correlated with function. Histological analysis of gonads revealed two peaks of gonadal maturation and spawning during the spring/summer period and winter season for scallops, and one peak during the fall for ormers. The gonadal maturation of both species was correlated with their seasonal variations of metabolic demands and antioxidant capacity. The lipid vacuoles of tubuloacinar terminations in the digestive gland differed between the two species; in scallop they are several-fold larger in size and number. Low temperatures in winter contributed to a decline in enzymatic antioxidant defense in scallop tissues, having lower superoxide dismutase (SOD) and glutathione peroxidase (GPx) activity, and higher concentrations of thiobarbituric acid reactive substances (TBARS) and total antioxidant status (TAS). In ormers, winter induced lower TAS, TBARS, SOD and GPx concentrations. The significant difference of winter TAS and TBARS levels between ormers and scallops was correlated with variations in their reproductive cycles, as well as in antioxidant defense systems. The most important factor for stress-related parameters for both species in this work was found to be the season-induced temperature change. Full article
(This article belongs to the Special Issue Aquatic Animal Health in Vulnerable Environments)
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Article
Frequency-Based Haze and Rain Removal Network (FHRR-Net) with Deep Convolutional Encoder-Decoder
Appl. Sci. 2021, 11(6), 2873; https://doi.org/10.3390/app11062873 - 23 Mar 2021
Viewed by 333
Abstract
Removing haze or rain is one of the difficult problems in computer vision applications. On real-world road images, haze and rain often occur together, but traditional methods cannot solve this imaging problem. To address rain and haze problems simultaneously, we present a robust [...] Read more.
Removing haze or rain is one of the difficult problems in computer vision applications. On real-world road images, haze and rain often occur together, but traditional methods cannot solve this imaging problem. To address rain and haze problems simultaneously, we present a robust network-based framework consisting of three steps: image decomposition using guided filters, a frequency-based haze and rain removal network (FHRR-Net), and image restoration based on an atmospheric scattering model using predicted transmission maps and predicted rain-removed images. We demonstrate FHRR-Net’s capabilities with synthesized and real-world road images. Experimental results show that our trained framework has superior performance on synthesized and real-world road test images compared with state-of-the-art methods. We use PSNR (peak signal-to-noise) and SSIM (structural similarity index) indicators to evaluate our model quantitatively, showing that our methods have the highest PSNR and SSIM values. Furthermore, we demonstrate through experiments that our method is useful in real-world vision applications. Full article
(This article belongs to the Special Issue Advances in Deep Learning Ⅱ)
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Article
Development of Robot Patient Lower Limbs to Reproduce the Sit-to-Stand Movement with Correct and Incorrect Applications of Transfer Skills by Nurses
Appl. Sci. 2021, 11(6), 2872; https://doi.org/10.3390/app11062872 - 23 Mar 2021
Viewed by 444
Abstract
Recently, human patient simulators have been widely developed as substitutes for real patients with the objective of applying them as training tools in nursing education. Such simulated training is perceived as beneficial for imparting the required practical skills to students. Considering the aging [...] Read more.
Recently, human patient simulators have been widely developed as substitutes for real patients with the objective of applying them as training tools in nursing education. Such simulated training is perceived as beneficial for imparting the required practical skills to students. Considering the aging world population, this study aimed to develop a robot patient for training nursing students in the sit-to-stand (STS) transfer skill, which is indispensable in caring for elderly people. To assess a student’s skill, the robot patient should be able to access the skill correctness and behave according to whether the skill is correctly or incorrectly implemented. Accordingly, an STS control method was proposed to reproduce the different STS movements during correct and incorrect applications of the skill by the nurses. The lower limbs of a prototype robot were redesigned to provide an active joint with a compliant unit, which enables the measurement of external torque and flexibility of the human joint to be reproduced. An experiment was conducted with four nurse teachers, each of whom was asked to demonstrate both correct and incorrect STS transfer skills. The results of the external torque and joint torque measured in robot’s lower limbs revealed that a significant difference (p < 0.05) between correct and incorrect skills. It also indicates the introduction of the proposed control method for the robot can satisfy the requirement of the assessment of STS skill. Among the various measurements conducted, the external torque of the hip joint exhibited the most significant difference and therefore represented the most robust measure for assessing whether the STS transfer skill was correctly applied. Full article
(This article belongs to the Section Robotics and Automation)
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Article
A UWB-Driven Self-Actuated Projector Platform for Interactive Augmented Reality Applications
Appl. Sci. 2021, 11(6), 2871; https://doi.org/10.3390/app11062871 - 23 Mar 2021
Viewed by 408
Abstract
With the rapid development of interactive technology, creating systems that allow users to define their interactive envelope freely and provide multi-interactive modalities is important to build up an intuitive interactive space. We present an indoor interactive system where a human can customize and [...] Read more.
With the rapid development of interactive technology, creating systems that allow users to define their interactive envelope freely and provide multi-interactive modalities is important to build up an intuitive interactive space. We present an indoor interactive system where a human can customize and interact through a projected screen utilizing the surrounding surfaces. An ultra-wideband (UWB) wireless sensor network was used to assist human-centered interaction design and navigate the self-actuated projector platform. We developed a UWB-based calibration algorithm to facilitate the interaction with the customized projected screens, where a hand-held input device was designed to perform mid-air interactive functions. Sixteen participants were recruited to evaluate the system performance. A prototype level implementation was tested inside a simulated museum environment, where a self-actuated projector provides interactive explanatory content for the on-display artifacts under the user’s command. Our results depict the applicability to designate the interactive screen efficiently indoors and interact with the augmented content with reasonable accuracy and relatively low workload. Our findings also provide valuable user experience information regarding the design of mobile and projection-based augmented reality systems, with the ability to overcome the limitations of other conventional techniques. Full article
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Article
Turbine Blade Temperature Field Prediction Using the Numerical Methods
Appl. Sci. 2021, 11(6), 2870; https://doi.org/10.3390/app11062870 - 23 Mar 2021
Viewed by 422
Abstract
Nowadays, material science and stress characteristics are crucial in the field of jet engines. There are methods for fatigue life, stress, and temperature prediction; however, the conventional methods are ineffective and time-consuming. The article is devoted to the research in the field of [...] Read more.
Nowadays, material science and stress characteristics are crucial in the field of jet engines. There are methods for fatigue life, stress, and temperature prediction; however, the conventional methods are ineffective and time-consuming. The article is devoted to the research in the field of application of the numerical methods in order to develop an innovative methodology for the temperature fields prediction based on the integration of the finite element methods and artificial neural networks, which leads to the creation of the novel methodology for the temperature field prediction. The proposed methodology was applied to the temperature field prediction on the surface blades of the experimental iSTC-21v jet engine turbine. The results confirmed the correctness of the new methodology, which is able to predict temperatures at the specific points on the surface of a turbine blade immediately. Moreover, the proposed methodology is able to predict temperatures at specific points on the turbine blade during the engine runs, even for the multiple operational regimes of the jet engine. Thanks to this new unique methodology, it is possible to increase the reliability and lifetime of turbines and hot parts of any jet engine and to reduce not only the maintenance but also the research and development costs due to the significantly lower time demands. The main advantage is to predict temperature fields much faster in comparison to the methods available today (computational fluid dynamics (CFD), etc.), and the major aim of the proposed article is to predict temperatures using a neural network. Apart from the above-mentioned advantages, the article’s main purpose is devoted to the artificial neural networks, which have been until now used for many applications, but in our case, the neural network was for the first time applied for the temperature field prediction on the turbine blade. Full article
(This article belongs to the Section Mechanical Engineering)
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Article
Abrasive Surface Finishing on SLM 316L Parts Fabricated with Recycled Powder
Appl. Sci. 2021, 11(6), 2869; https://doi.org/10.3390/app11062869 - 23 Mar 2021
Viewed by 470
Abstract
Improving the surface roughness quality of 3D printed components, especially metallic ones, which are fabricated from the selective laser melting (SLM) method, has drawn enormous attention from the research community. It should be noted that various studies on this topic have reported that [...] Read more.
Improving the surface roughness quality of 3D printed components, especially metallic ones, which are fabricated from the selective laser melting (SLM) method, has drawn enormous attention from the research community. It should be noted that various studies on this topic have reported that precise surface roughness results can be obtained with various techniques that are indeed not cost-effective. Differing itself from these studies, this manuscript investigates an economical solution for fabricating and surface treating SLM components. Specifically, the inspected specimens were printed with recycled 316L stainless steel powder and treated solely with two abrasive surface finishing methods. In the manuscript, two scanning strategies namely meander and stripes, and three types of surfaces were investigated. Subsequently, their 2D and 3D surface roughness results were elaborated. After the proposed herein abrasive treatment, 3D surface roughness arithmetical mean height of a surface (Sa) value of 0.9 µm can be achieved. Full article
(This article belongs to the Section Mechanical Engineering)
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Article
Structural Crack Detection and Recognition Based on Deep Learning
Appl. Sci. 2021, 11(6), 2868; https://doi.org/10.3390/app11062868 - 23 Mar 2021
Cited by 1 | Viewed by 358
Abstract
The detection and recognition of surface cracks are of great significance for structural safety. This paper is based on a deep-learning methodology to detect and recognize structural cracks. First, a training dataset of the model is built. Then, three neural networks, AlexNet, VGGNet13, [...] Read more.
The detection and recognition of surface cracks are of great significance for structural safety. This paper is based on a deep-learning methodology to detect and recognize structural cracks. First, a training dataset of the model is built. Then, three neural networks, AlexNet, VGGNet13, and ResNet18, are employed to recognize and classify crack images. The tests indicate that the ResNet18 model generates the most satisfactory results. It is also found that the trained YOLOv3 model detects the crack area with satisfactory accuracy. This study also confirms that the proposed deep learning as a novel technology has the potential to be an efficient and robust tool for crack detection and recognition to replace traditional methods. Full article
(This article belongs to the Section Civil Engineering)
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Article
The Triad Hsp60-miRNAs-Extracellular Vesicles in Brain Tumors: Assessing Its Components for Understanding Tumorigenesis and Monitoring Patients
Appl. Sci. 2021, 11(6), 2867; https://doi.org/10.3390/app11062867 - 23 Mar 2021
Cited by 1 | Viewed by 346
Abstract
Brain tumors have a poor prognosis and progress must be made for developing efficacious treatments, but for this to occur their biology and interaction with the host must be elucidated beyond current knowledge. What has been learned from other tumors may be applied [...] Read more.
Brain tumors have a poor prognosis and progress must be made for developing efficacious treatments, but for this to occur their biology and interaction with the host must be elucidated beyond current knowledge. What has been learned from other tumors may be applied to study brain tumors, for example, the role of Hsp60, miRNAs, and extracellular vesicles (EVs) in the mechanisms of cell proliferation and dissemination, and resistance to immune attack and anticancer drugs. It has been established that Hsp60 increases in cancer cells, in which it occurs not only in the mitochondria but also in the cytosol and plasma-cell membrane and it is released in EVs into the extracellular space and in circulation. There is evidence suggesting that these EVs interact with cells near and far from their original cell and that this interaction has an impact on the functions of the target cell. It is assumed that this crosstalk between cancer and host cells favors carcinogenesis in various ways. We, therefore, propose to study the triad Hsp60-related miRNAs-EVs in brain tumors and have standardized methods for the purpose. These revealed that EVs with Hsp60 and related miRNAs increase in patients’ blood in a manner that reflects disease status. The means are now available to monitor brain tumor patients by measuring the triad and to dissect its effects on target cells in vitro, and in experimental models in vivo. Full article
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Article
Phonetic Variation Modeling and a Language Model Adaptation for Korean English Code-Switching Speech Recognition
Appl. Sci. 2021, 11(6), 2866; https://doi.org/10.3390/app11062866 - 23 Mar 2021
Viewed by 357
Abstract
In this paper, we propose a new method for code-switching (CS) automatic speech recognition (ASR) in Korean. First, the phonetic variations in English pronunciation spoken by Korean speakers should be considered. Thus, we tried to find a unified pronunciation model based on phonetic [...] Read more.
In this paper, we propose a new method for code-switching (CS) automatic speech recognition (ASR) in Korean. First, the phonetic variations in English pronunciation spoken by Korean speakers should be considered. Thus, we tried to find a unified pronunciation model based on phonetic knowledge and deep learning. Second, we extracted the CS sentences semantically similar to the target domain and then applied the language model (LM) adaptation to solve the biased modeling toward Korean due to the imbalanced training data. In this experiment, training data were AI Hub (1033 h) in Korean and Librispeech (960 h) in English. As a result, when compared to the baseline, the proposed method improved the error reduction rate (ERR) by up to 11.6% with phonetic variant modeling and by 17.3% when semantically similar sentences were applied to the LM adaptation. If we considered only English words, the word correction rate improved up to 24.2% compared to that of the baseline. The proposed method seems to be very effective in CS speech recognition. Full article
(This article belongs to the Section Computing and Artificial Intelligence)
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Article
Marine Gas Hydrate Geohazard Assessment on the European Continental Margins. The Impact of Critical Knowledge Gaps
Appl. Sci. 2021, 11(6), 2865; https://doi.org/10.3390/app11062865 - 23 Mar 2021
Viewed by 411
Abstract
This paper presents a geohazard assessment along the European continental margins and adjacent areas. This assessment is understood in the framework of the seafloor’s susceptibility to (i.e., likelihood of) being affected by the presence of hydrate deposits and the subsequent hazardous dissociation processes [...] Read more.
This paper presents a geohazard assessment along the European continental margins and adjacent areas. This assessment is understood in the framework of the seafloor’s susceptibility to (i.e., likelihood of) being affected by the presence of hydrate deposits and the subsequent hazardous dissociation processes (liquefaction, explosion, collapse, crater-like depressions or submarine landslides). Geological and geophysical evidence and indicators of marine gas hydrates in the theoretical gas hydrate stability zone (GHSZ) were taken into account as the main factors controlling the susceptibility calculation. Svalbald, the Barents Sea, the mid-Norwegian margin-northwest British Islands, the Gulf of Cádiz, the eastern Mediterranean and the Black Sea have the highest susceptibility. Seafloor areas outside the theoretical GHSZ were excluded from this geohazard assessment. The uncertainty analysis of the susceptibility inference shows extensive seafloor areas with no data and a very low density of data that are defined as critical knowledge gaps. Full article
(This article belongs to the Special Issue Geohazards: Risk Assessment, Mitigation and Prevention)
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Article
In Vitro Cytotoxic Evaluation and Apoptotic Effects of Datura innoxia Grown in Saudi Arabia and Phytochemical Analysis
Appl. Sci. 2021, 11(6), 2864; https://doi.org/10.3390/app11062864 - 23 Mar 2021
Viewed by 353
Abstract
Datura innoxia is an important species of Solanaceae family with several purposes in folk medicine. This study intends to explore the cytotoxic effect of D. innoxia on various cancer cell proliferation. D. innoxia ethanolic extract’s effect on the progression of the cell cycle [...] Read more.
Datura innoxia is an important species of Solanaceae family with several purposes in folk medicine. This study intends to explore the cytotoxic effect of D. innoxia on various cancer cell proliferation. D. innoxia ethanolic extract’s effect on the progression of the cell cycle and the induction of apoptosis were investigated by flow cytometry. Further, real-time PCR was employed to confirm apoptosis initiation. In addition, active phytochemicals of D. innoxia was identified by gas chromatography–mass spectroscopy (GC-MS). The cell viability study revealed that the ethanolic extract of D. innoxia demonstrated potent cytotoxicity, with an IC50 value of 10 μg/mL against LoVo colon cancer cells. Cell cycle staining with propidium iodide revealed that D. innoxia treatment leads to cell accumulation in the sub-G1 phase. Using the Annexin V-FITC/PI assay, the ethanolic extract was found to cause a dose-dependent increase in early and late apoptosis when compared to control cells. Apoptosis as the mode of cell death was also confirmed by the increased expression of p53, bax and caspase-8, -9, and -3 along with downregulation of Bcl-2. GC-MS analysis displayed that 3,5-Dihydroxybenzoic acid (16.53%), heneicosyl formate (14.14%), 2,3-dimethyl-3-pentanol (12.89%), 2-hydroxy-4-methyl pentanoic acid (5.19%) were the main phytoconstituents. These findings conclude that D. innoxia causes cell death through apoptosis, suggesting more attention should be paid to further exploration of the active components from D. innoxia responsible for the observed activities. Full article
(This article belongs to the Special Issue Application of Plant Natural Compounds)
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Article
Current Ripple Reduction of Predictive Torque-Controlled Induction Motor Drive Using Delta-Star Switchover
Appl. Sci. 2021, 11(6), 2863; https://doi.org/10.3390/app11062863 - 23 Mar 2021
Viewed by 339
Abstract
The current and torque ripple of inverter-fed induction motor drives is an inherent problem of control strategies working with switching frequencies in the range of multiple kilohertz, such as direct torque and, more recently, predictive torque control. If the drive operates in a [...] Read more.
The current and torque ripple of inverter-fed induction motor drives is an inherent problem of control strategies working with switching frequencies in the range of multiple kilohertz, such as direct torque and, more recently, predictive torque control. If the drive operates in a wide-speed and wide-torque range and is equipped with a machine with an accessible terminal block whose winding is nominally connected in delta, then the current and torque ripple can be reduced by utilizing the delta-star winding changeover technique. When the winding configuration is switched from delta to star, the instantaneous motor phase voltage peak is lowered, and its total harmonic distortion is reduced. However, the control strategy must be adjusted according to the actual winding topology, mainly due to the difference in the coordinate transformations of the measured currents and the difference between the phase voltage vectors obtained from the inverter. This paper proposes a predictive torque control of an induction motor drive with a switchable delta-star winding configuration. The paper is supported by theoretical background, and the key idea is verified by simulations in MATLAB/Simulink and experiments conducted on a dSPACE-controlled 5.5-kW laboratory drive. The simulations validated the presented equations and show the effects of not respecting the actual winding topology. The experiments mainly focused on analyzing the total harmonic distortion of the currents and consumed electrical power in multiple operating points. Full article
(This article belongs to the Section Electrical, Electronics and Communications Engineering)
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Article
Foot Contact Dynamics and Fall Risk among Children Diagnosed with Idiopathic Toe Walking
Appl. Sci. 2021, 11(6), 2862; https://doi.org/10.3390/app11062862 - 23 Mar 2021
Viewed by 346
Abstract
Children that are diagnosed with Idiopathic Toe walking (cITW) are characterized by persistent toe-to-toe contacts. The objective of this study was to explore whether typical foot contact dynamics during walking predisposes cITW to a higher risk of falling. Twenty cITW and age-matched controls [...] Read more.
Children that are diagnosed with Idiopathic Toe walking (cITW) are characterized by persistent toe-to-toe contacts. The objective of this study was to explore whether typical foot contact dynamics during walking predisposes cITW to a higher risk of falling. Twenty cITW and age-matched controls performed typical and toe walking trials. The gait parameters related to foot contact dynamics, vertical force impulses during stance, slip, and trip risk were compared for both groups. We found that cITW manifest less stable gait and produced significantly higher force impulses during push-off. Additionally, we found that cITW had a higher slip-initiation risk that was associated with higher foot contact horizontal and vertical velocities in addition to lower transitional acceleration of center of mass. We found that cITW exhibited a higher trip risk with toe clearance being significantly lower when compared to healthy counterparts. This study allowed for a quantitative description of foot contact dynamics and delineated typical from toe walking among cITW. Overall, the results indicate that cITW are less stable during typical walking and are prone to a higher risk of slip and trip-like falls. Full article
(This article belongs to the Special Issue New Trends in Neuromechanics and Motor Rehabilitation)
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Article
Comparison of Endurance Time Prediction of Biceps Brachii Using Logarithmic Parameters of a Surface Electromyogram during Low-Moderate Level Isotonic Contractions
Appl. Sci. 2021, 11(6), 2861; https://doi.org/10.3390/app11062861 - 23 Mar 2021
Viewed by 302
Abstract
At relatively low effort level tasks, surface electromyogram (sEMG) spectral parameters have demonstrated an inconsistent ability to monitor localized muscle fatigue and predict endurance capacity. The main purpose of this study was to assess the potential of the endurance time (Tend) [...] Read more.
At relatively low effort level tasks, surface electromyogram (sEMG) spectral parameters have demonstrated an inconsistent ability to monitor localized muscle fatigue and predict endurance capacity. The main purpose of this study was to assess the potential of the endurance time (Tend) prediction using logarithmic parameters compared to raw data. Ten healthy subjects performed five sets of voluntary isotonic contractions until their exhaustion at 20% of their maximum voluntary contraction (MVC) level. We extracted five sEMG spectral parameters namely the power in the low frequency band (LFB), the mean power frequency (MPF), the high-to-low ratio between two frequency bands (H/L-FB), the Dimitrov spectral index (DSI), and the high-to-low ratio between two spectral moments (H/L-SM), and then converted them to logarithms. Changes in these ten parameters were monitored using area ratio and linear regressive slope as statistical predictors and estimating from onset at every 10% of Tend. Significant correlations (r > 0.5) were found between log(Tend) and the linear regressive slopes in the logarithmic H/L-SM at every 10% of Tend. In conclusion, logarithmic parameters can be used to describe changes in the fatigue content of sEMG and can be employed as a better predictor of Tend in comparison to the raw parameters. Full article
(This article belongs to the Special Issue Biotechnology and Sports Engineering)
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Article
Efficiency of Machine Sanding of Wood
Appl. Sci. 2021, 11(6), 2860; https://doi.org/10.3390/app11062860 - 23 Mar 2021
Cited by 2 | Viewed by 361
Abstract
We hypothesized that the type of wood, in combination with the grit size of sandpapers, would affect sanding efficiency. Fixed factors were used in the experiment (a belt sander with pressure p = 3828 Pa, and a belt speed of vs = [...] Read more.
We hypothesized that the type of wood, in combination with the grit size of sandpapers, would affect sanding efficiency. Fixed factors were used in the experiment (a belt sander with pressure p = 3828 Pa, and a belt speed of vs = 14.5 m/s) as well as variable factors (three sand belts (P60, P120, P180), six hardwood species (beech, oak, ash, hornbeam, alder, walnut) and three softwood species (pine, spruce, larch)). The masses of the test samples were measured until they were completely sanded. The sanding efficiency of hardwood species is less variable than for softwood species. Maximum sanding efficiency for the softwood ranged from 1 to 2 min, while for the hardwood species, it ranged from 2 to 4.5 min at the start of sanding and then decreased. The average time for complete sanding of the softwood samples was: 87 s (P60), 150 s (P120), and 188 s (P180). For hardwood, these times were 2.4, 1.5, and 1.8 times longer. The results indicate that the factors determining sanding efficiency are the type of wood, and, secondly, the grit size of sanding belts. In the first phase of blunting with the sanding belts, the sanding processes of hardwood and softwood are significantly different. In the second phase of blunting, sanding belts with higher grit numbers (P120 and P180) behaved similarly while sanding hardwood and softwood. Full article
(This article belongs to the Special Issue Application of Wood Composites)
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Article
A Symmetric Three-Layer Plate with Two Coaxial Cracks under Pure Bending
Appl. Sci. 2021, 11(6), 2859; https://doi.org/10.3390/app11062859 - 23 Mar 2021
Cited by 1 | Viewed by 274
Abstract
The purpose of this research was to investigate the effect of mechanical features and geometrical parameters on the stress–strain state of a cracked layered plate under pure bending (bending moments are uniformly distributed at infinity). The sixth-order bending problem of an infinite, symmetric, [...] Read more.
The purpose of this research was to investigate the effect of mechanical features and geometrical parameters on the stress–strain state of a cracked layered plate under pure bending (bending moments are uniformly distributed at infinity). The sixth-order bending problem of an infinite, symmetric, three-layer plate with two coaxial through cracks is considered under the assumption of no crack closure. By using complex potentials and methods of the theory of functions of a complex variable, the solution to the problem was obtained in the form of a singular integral equation. It is reduced to the system of linear algebraic equations and solved in a numerical manner by the mechanical quadrature method. The distributions of stresses and bending moments near the crack tips are shown. Numerical results are presented as graphical dependences of the reduced moment intensity factor on various problem parameters. In this particular case, the optimum ratio of layer thicknesses is determined. Full article
(This article belongs to the Section Mechanical Engineering)
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Review
Design of a Computed Tomography Automation Architecture
Appl. Sci. 2021, 11(6), 2858; https://doi.org/10.3390/app11062858 - 23 Mar 2021
Viewed by 350
Abstract
This paper presents a literature review on techniques related to the computed tomography procedure that incorporate automation elements in their research investigations or industrial applications. Computed tomography (CT) is a non-destructive testing (NDT) technique in that the imaging and inspection are performed without [...] Read more.
This paper presents a literature review on techniques related to the computed tomography procedure that incorporate automation elements in their research investigations or industrial applications. Computed tomography (CT) is a non-destructive testing (NDT) technique in that the imaging and inspection are performed without damaging the sample, allowing for additional or repeated analysis if necessary. The reviewed literature is organized based on the steps associated with a general NDT task in order to define an end-to-end computed tomography automation architecture. The process steps include activities prior to image collection, during the scan, and after the data are collected. It further reviews efforts related to repeating this process based on a previous scan result. By analyzing the multiple existing but disparate efforts found in the literature, we present a framework for fully automating NDT procedures and discuss the remaining technical gaps in the developed framework. Full article
(This article belongs to the Special Issue Nondestructive Testing (NDT): Volume II)
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Article
Uncovering Hidden Community Structure in Multi-Layer Networks
Appl. Sci. 2021, 11(6), 2857; https://doi.org/10.3390/app11062857 - 23 Mar 2021
Viewed by 386
Abstract
Community detection, also known as graph clustering, in multi-layer networks has been extensively studied in the literature. The goal of community detection is to partition vertices in a network into densely connected components so called communities. Networks contain a set of strong, dominant [...] Read more.
Community detection, also known as graph clustering, in multi-layer networks has been extensively studied in the literature. The goal of community detection is to partition vertices in a network into densely connected components so called communities. Networks contain a set of strong, dominant communities, which may interfere with the detection of weak, natural community structure. When most of the members of the weak communities also belong to stronger communities, they are extremely hard to be uncovered. We call the weak communities the hidden or disguised community structure. In this paper, we present a method to uncover weak communities in a network by weakening the strength of the dominant structure. With the aim to detect the weak communities, through experiments, we observe real-world networks to answer the question of whether real-world networks have hidden community structure or not. Results of the hidden community detection (HCD) method showed the great variation in the number of communities detected in multiple layers when compared with the results of other community detection methods. Full article
(This article belongs to the Section Computing and Artificial Intelligence)
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