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Appl. Sci., Volume 13, Issue 5 (March-1 2023) – 623 articles

Cover Story (view full-size image): Eating is considered as one of the most important activities of daily living (ADL). However, with the aging population and the rapid spread of chronic diseases, many patients require assistance from family members or professional caregivers to eat. As a result, various types of meal assistance robots (MAR) have been developed and introduced to address this issue. In this study, we propose a MAR system suitable for an Asian diet, which includes dishes that are easy to handle with chopsticks and soup. The system comprises an eating utensil that can alternate chopsticks and spoons and a food acquisition point estimator that recognizes the food area from the plate image and calculates the best location to acquire each dish. Additionally, we have developed a contactless user interface based on facial recognition to accommodate users with physical limitations. View this paper
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15 pages, 4092 KiB  
Article
Rhodospirillum rubrum L-Asparaginase Conjugates with Polyamines of Improved Biocatalytic Properties as a New Promising Drug for the Treatment of Leukemia
Appl. Sci. 2023, 13(5), 3373; https://doi.org/10.3390/app13053373 - 06 Mar 2023
Cited by 1 | Viewed by 1606
Abstract
L-asparaginase Rhodospirillum rubrum (RrA) is an enzyme (amidohydrolases; EC 3.5.1.1) that catalyzes the L-asparagine hydrolysis reaction to form L-aspartic acid. Due to the shortcomings of existing L-asparaginases from Esherichia coli (EcA) and Erwinia chrysanthemi (ErA), RrA may turn out to be a new [...] Read more.
L-asparaginase Rhodospirillum rubrum (RrA) is an enzyme (amidohydrolases; EC 3.5.1.1) that catalyzes the L-asparagine hydrolysis reaction to form L-aspartic acid. Due to the shortcomings of existing L-asparaginases from Esherichia coli (EcA) and Erwinia chrysanthemi (ErA), RrA may turn out to be a new promising drug for the treatment of leukemia. RrA has a low homology with EcA and ErA, which makes the enzyme potentially less immunogenic. RrA has pronounced antitumor activity on a number of leukemia cells. However, there is a need to improve the biocatalytic properties of the enzyme. So, in this study, the RrA conjugates with polyamines with different molecular architectures were developed to regulate the catalytic properties of the enzyme. Linear polyethyleneimine (PEI), branched polyethyleneimine, modified with polyethylene glycol (PEI-PEG), and spermine (Spm) were used to obtain conjugates with RrA. It was discovered by gel permeation chromatography that Spm allows the most active tetrameric form of RrA to be obtained and stabilized. Molecular docking was used to study the binding of spermine to RrA subunits. The activity of the RrA conjugates with Spm and PEI-PEG was 23–30% higher than the native enzyme. The pH optimum of the conjugates shifted from 9.0 to 8.5. The conjugates had higher stability: Spm and PEI-PEG reduced the inactivation constant (kin) more than two-fold upon incubation at 53 °C. The conjugate RrA-PEI-PEG reduced the accessibility of trypsin to the protein surface and reduced kin by eight times. The modification of RrA with polyamines made it possible to obtain enzyme preparations with improved biocatalytic properties. These conjugates represent interest for further study as potential therapeutic agents. Full article
(This article belongs to the Special Issue Functional Polymers: Synthesis, Properties and Applications)
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13 pages, 40176 KiB  
Article
On Pseudorandomness and Deep Learning: A Case Study
Appl. Sci. 2023, 13(5), 3372; https://doi.org/10.3390/app13053372 - 06 Mar 2023
Viewed by 1212
Abstract
Pseudorandomness is a crucial property that the designers of cryptographic primitives aim to achieve. It is also a key requirement in the calls for proposals of new primitives, as in the case of block ciphers. Therefore, the assessment of the property is an [...] Read more.
Pseudorandomness is a crucial property that the designers of cryptographic primitives aim to achieve. It is also a key requirement in the calls for proposals of new primitives, as in the case of block ciphers. Therefore, the assessment of the property is an important issue to deal with. Currently, an interesting research line is the understanding of how powerful machine learning methods are in distinguishing pseudorandom objects from truly random objects. Moving along such a research line, in this paper a deep learning-based pseudorandom distinguisher is developed and trained for two well-known lightweight ciphers, Speck and Simon. Specifically, the distinguisher exploits a convolutional Siamese network for distinguishing the outputs of these ciphers from random sequences. Experiments with different instances of Speck and Simon show that the proposed distinguisher highly able to distinguish between the two types of sequences, with an average accuracy of 99.5% for Speck and 99.6% for Simon. Hence, the proposed method could significantly impact the security of these cryptographic primitives and of the applications in which they are used. Full article
(This article belongs to the Special Issue Women in Cryptography)
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16 pages, 2912 KiB  
Article
Effect of Protective Coatings on Wooden Elements Exposed to a Small Ignition Initiator
Appl. Sci. 2023, 13(5), 3371; https://doi.org/10.3390/app13053371 - 06 Mar 2023
Cited by 4 | Viewed by 1074
Abstract
This paper presents the results of monitoring the behaviour of selected wood species exposed to a small ignition initiator. We specifically aimed to investigate the effect of retardant coating on the combustion process of the wood species spruce (Picea abies), red [...] Read more.
This paper presents the results of monitoring the behaviour of selected wood species exposed to a small ignition initiator. We specifically aimed to investigate the effect of retardant coating on the combustion process of the wood species spruce (Picea abies), red spruce (Larix decidua), Scots pine (Pinus sylvestris), ash (Fraxinus excelsior L.), beech (Fagus sylvatica), and oak (Quercus robur) when exposed to a small initiator of ignition. At the same time, we studied the effect of different types of fungicidal agents (based on N-(3-aminopropyl)-N-dodecylpropane-1,3-diamine; alkyl (C12–16) dimethylbenzyl ammonium chloride or 3-iodo-prop-2-inylbutylcarbamate) on the effectiveness of a flame retardant (containing ferric phosphate) applied to the selected fungicide-treated wood samples. The experimentally obtained mass-loss and flame-spread results were statistically evaluated using the QtiPlot software program. A significant dependence of mass loss and surface flame spread on wood species was the primary focus. It was only confirmed for the surface-flame-spread variable. The dependence of the effect of fungicide treatment on the effectiveness of the selected retardant was confirmed. Fungicidal coatings with the active ingredient alkyl/benzyl (C12–16) dimethylbenzyl ammonium chloride indicated the lowest mass loss rate and flame spread for all wood samples. Full article
(This article belongs to the Special Issue Application of Wood Composites III)
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12 pages, 2287 KiB  
Article
Performance of Automated Oral Cancer Screening Algorithm in Tobacco Users vs. Non-Tobacco Users
Appl. Sci. 2023, 13(5), 3370; https://doi.org/10.3390/app13053370 - 06 Mar 2023
Cited by 1 | Viewed by 1863
Abstract
Oral non-neoplastic and neoplastic lesions have similar clinical manifestations, increasing the risk of inaccurate screening decisions that adversely affect oral cancer (OC) outcomes. Tobacco-use-related changes in the oral soft tissues may affect the accuracy of “smart” oral screening modalities. Because smoking is such [...] Read more.
Oral non-neoplastic and neoplastic lesions have similar clinical manifestations, increasing the risk of inaccurate screening decisions that adversely affect oral cancer (OC) outcomes. Tobacco-use-related changes in the oral soft tissues may affect the accuracy of “smart” oral screening modalities. Because smoking is such a strong predictor of OC risk, it may overwhelm the impact of other variables on algorithm performance. The objective was to evaluate the screening accuracy in tobacco users vs. non-users of a previously developed prototype smartphone and machine-learning algorithm-based oral health screening modality. 318 subjects with healthy mucosa or oral lesions were allocated into either a “tobacco smoker” group or a “tobacco non-smoker” group. Next, intraoral autofluorescence (AFI) and polarized white light images (pWLI), risk factors as well as clinical signs and symptoms were recorded using the prototype screening platform. OC risk status as determined by the algorithm was compared with OC risk evaluation by an oral medicine specialist (gold standard). The screening platform achieved 80.0% sensitivity, 87.5% specificity, 83.67% agreement with specialist screening outcome in tobacco smokers, and 62.1% sensitivity, 82.9% specificity, 73.1% agreement with specialist screening outcome in non-smokers. Tobacco use should be carefully weighted as a variable in the architecture of any imaging-based screening algorithm for OC risk. Full article
(This article belongs to the Special Issue Artificial Intelligence Applied to Dentistry)
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14 pages, 2079 KiB  
Article
Antibacterial Activity of Tanacetum vulgare L. Extracts against Clinical Isolates of Bovine Mastitis
Appl. Sci. 2023, 13(5), 3369; https://doi.org/10.3390/app13053369 - 06 Mar 2023
Cited by 4 | Viewed by 1624
Abstract
A bovine mastitis is an infectious disease, which is usually treated with antibiotics. Alternatively, herbal medicine has been proposed due to bacterial resistance. The aim of this study was to determine the antibacterial activity of the acetonic and ethanolic extracts of dried flowers [...] Read more.
A bovine mastitis is an infectious disease, which is usually treated with antibiotics. Alternatively, herbal medicine has been proposed due to bacterial resistance. The aim of this study was to determine the antibacterial activity of the acetonic and ethanolic extracts of dried flowers and leaves of Tanacetum vulgare L. against bovine mastitis-inducing clinical isolates such as Escherichia coli, Streptococcus agalactiae, Streptococcus uberis, Serratia liquefaciens, Staphylococcus aureus, and reference cultures of S. aureus and E. coli. The extracts of T. vulgare showed partial antibacterial activity against tested strains of S. aureus. The MIC and MBC values of a 70% ethanol extract of flowers (MIC = 3.4 mg/mL, MBC = 3.4–6.8 mg/mL) were lower than for the 70% ethanol extract of leaves (MIC = 15.7–31.4 mg/mL, MBC = 62.9–125.9 mg/mL). The flower extracts showed low activity against E. coli (MIC = 53.9 mg/mL, MBC = 53.9–107.8 mg/mL) and S. agalactiae (MIC, MBC = 53.9 mg/mL). T. vulgare leaf extracts had minimal antibacterial effects against Streptococcus strains (MIC = 31.4–62.9 mg/mL, MBC = 53.9–125.9 mg/mL) and Serratia liquefaciens (MIC, MBC = 125.9 mg/mL). However, flower extracts had a higher phenolic content that did not correlate with antibacterial effects. T. vulgare flower and leaf extracts could be combined to obtain broader antibacterial effects. Full article
(This article belongs to the Special Issue Antibacterial Activity of Plant Extracts)
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19 pages, 3929 KiB  
Article
Combining Statistical, Displacement and Damage Analyses to Study Slow-Moving Landslides Interacting with Roads: Two Case Studies in Southern Italy
Appl. Sci. 2023, 13(5), 3368; https://doi.org/10.3390/app13053368 - 06 Mar 2023
Cited by 2 | Viewed by 1202
Abstract
Slow-moving landslides are widespread natural hazards that can affect social and economic activities, causing damage to structures and infrastructures. This paper aims at proposing a procedure to analyze road damage induced by slow-moving landslides based on the joint use of landslide susceptibility maps, [...] Read more.
Slow-moving landslides are widespread natural hazards that can affect social and economic activities, causing damage to structures and infrastructures. This paper aims at proposing a procedure to analyze road damage induced by slow-moving landslides based on the joint use of landslide susceptibility maps, a road-damage database developed using Google Street View images and ground-displacement measurements derived from the interferometric processing of satellite SAR images. The procedure is applied to the municipalities of Vaglio Basilicata and Trivigno in the Basilicata region (southern Italy) following a matrix-based approach. First, a susceptibility analysis is carried out at the municipal scale, using data from landslide inventories and thematic information available over the entire municipalities. Then, the susceptibility index, the class of movement and the level of damage are calculated for the territorial units corresponding to the road corridors under investigation. Finally, the road networks are divided into stretches, each one characterized by a specific level of risk (or attention required) following the aggregation of the information provided by the performed analyses. The results highlight the importance of integrating all of these different approaches and data for obtaining quantitative information on the spatial and temporal behavior of slow-moving landslides affecting road networks. Full article
(This article belongs to the Special Issue New Frontiers in Natural Hazards and New Techniques)
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43 pages, 2308 KiB  
Review
A Survey of Handover Management in Mobile HetNets: Current Challenges and Future Directions
Appl. Sci. 2023, 13(5), 3367; https://doi.org/10.3390/app13053367 - 06 Mar 2023
Cited by 8 | Viewed by 3565
Abstract
With the rapid growth of data traffic and mobile devices, it is imperative to provide reliable and stable services during mobility. Heterogeneous Networks (HetNets) and dense networks have been identified as potential solutions to address the upcoming capacity crunch, but they also pose [...] Read more.
With the rapid growth of data traffic and mobile devices, it is imperative to provide reliable and stable services during mobility. Heterogeneous Networks (HetNets) and dense networks have been identified as potential solutions to address the upcoming capacity crunch, but they also pose significant challenges related to handover optimization. This paper presents a comprehensive review of recent handover decision algorithms in HetNets, categorizing them based on their decision techniques and summarizing their input parameters, techniques, and performance evaluations. Our study highlights the technical challenges and opportunities related to handovers in HetNets and dense cellular networks and provides key findings from recent studies. The significance of this survey is to provide a comprehensive overview of handover decision algorithms in HetNets and dense cellular networks, which can aid in the development of more advanced handover optimization approaches. Full article
(This article belongs to the Section Electrical, Electronics and Communications Engineering)
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14 pages, 1687 KiB  
Article
External Beam IBA Measurements for Cultural Heritage
Appl. Sci. 2023, 13(5), 3366; https://doi.org/10.3390/app13053366 - 06 Mar 2023
Cited by 1 | Viewed by 1063
Abstract
Ion beam analysis (IBA) methods refer to a set of analytical techniques based on the interactions of energetic ions, produced by a particle accelerator, with matter. The result of such interactions is the emission of characteristic radiation, X and gamma rays, and charged [...] Read more.
Ion beam analysis (IBA) methods refer to a set of analytical techniques based on the interactions of energetic ions, produced by a particle accelerator, with matter. The result of such interactions is the emission of characteristic radiation, X and gamma rays, and charged particles, which, upon detection, provide valuable information on the absolute concentration and depth distribution of the elements in the bombarded material. Moreover, IBA techniques can be performed while maintaining the object to be investigated at atmospheric pressure, without placing it in vacuum, in an analysis chamber, with the impinging ion beam extracted from the in-vacuum beamline of the accelerator, avoiding the need of invasive sampling and greatly easing the object positioning, thus allowing precious and big or large artefacts to be studied. This feature has opened the way for applications of IBA techniques for compositional analysis in cultural heritage studies, providing detailed and complete information about elemental compositions and depth distributions of analysed materials that are otherwise difficult or impossible for other analytical techniques. In this paper, the basic principles of the main IBA techniques applied to cultural heritage, namely, particle induced X-ray emission (PIXE), particle induced Gamma-ray emission (PIGE), and Rutherford or elastic backscattering spectrometry (RBS/EBS), will be recalled, and specific and practical details on how these techniques can be used for analysing cultural heritage objects with external beam set-ups will be provided. Full article
(This article belongs to the Special Issue Non-destructive Techniques for Cultural Heritage Characterization)
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24 pages, 5437 KiB  
Article
A Comprehensive Methodology for the Statistical Characterization of Solar Irradiation: Application to the Case of Morocco
Appl. Sci. 2023, 13(5), 3365; https://doi.org/10.3390/app13053365 - 06 Mar 2023
Cited by 1 | Viewed by 1304
Abstract
The prediction and characterization of solar irradiation relies mostly on either the use of complex models or on complicated mathematical techniques, such as artificial neural network (ANN)-based algorithms. This mathematical complexity might hamper their use by businesses and project developers when assessing the [...] Read more.
The prediction and characterization of solar irradiation relies mostly on either the use of complex models or on complicated mathematical techniques, such as artificial neural network (ANN)-based algorithms. This mathematical complexity might hamper their use by businesses and project developers when assessing the solar resource. In this study, a simple but comprehensive methodology for characterizing the solar resource for a project is presented. It is based on the determination of the best probability distribution function (PDF) of the solar irradiation for a specific location, assuming that the knowledge of statistical techniques may be more widely extended than other more complex mathematical methods. The presented methodology was tested on 23 cities across Morocco, given the high interest in solar investments in the country. As a result, a new database for solar irradiation values depending on historical data is provided for Morocco. The results show the great existing variety of PDFs for the solar irradiation data at the different months and cities, which demonstrates the need for undertaking a proper characterization of the irradiation when the assessment of solar energy projects is involved. When it is simply needed to embed the radiation uncertainty in the analysis, as is the case of the techno-economic valuation of solar energy assets, the presented methodology can reach this objective with much less complexity and less demanding input data. Moreover, its application is not limited to solar resource assessment, but can also be easily used in other fields, such as meteorology and climate change studies. Full article
(This article belongs to the Special Issue Solar Power Technology for Electricity Generation)
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20 pages, 4377 KiB  
Article
Active Disturbance Rejection Optimization Control for SOFCs in Offshore Wind Power
Appl. Sci. 2023, 13(5), 3364; https://doi.org/10.3390/app13053364 - 06 Mar 2023
Cited by 1 | Viewed by 1009
Abstract
With the development of offshore wind power (OWP)-based hydrogen production technology, hydrogen fuel cells play a critical role in buffering the mismatch between energy supply and demand in OWP systems. Benefitting from high efficiency, cleanliness, and nontoxicity, solid oxide fuel cells (SOFCs) have [...] Read more.
With the development of offshore wind power (OWP)-based hydrogen production technology, hydrogen fuel cells play a critical role in buffering the mismatch between energy supply and demand in OWP systems. Benefitting from high efficiency, cleanliness, and nontoxicity, solid oxide fuel cells (SOFCs) have been extensively investigated. However, OWP-based SOFC systems are characterized by strong nonlinearity and uncertainty and are vulnerable to disturbance, which leads to appreciable fluctuations and even instability to the system output voltage. Since conventional PID control schemes cannot achieve favorable performance, a more advanced control method is imperative. In response, this paper proposes a linear active disturbance rejection control (LADRC) method to reduce the influence of disturbance and ensure the stability of SOFC systems. In addition, an improved firefly algorithm (IFA) was adopted to optimize LADRC parameters. A step inertia weight was introduced, and a random generation mechanism was adopted to replace 30% of individuals with low luminous degrees. Using optimized LADRC parameters, a series of Monte Carlo experiments were carried out to verify the system’s robustness. The experimental results show that the overshoot of the LADRC method optimized by the IFA can be reduced by 5.7% compared with the traditional PID controller, i.e., the influence of the voltage disturbance can be well suppressed. Full article
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13 pages, 2355 KiB  
Article
Neural Image Analysis for the Determination of Total and Volatile Solids in a Composted Sewage Sludge and Maize Straw Mixture
Appl. Sci. 2023, 13(5), 3363; https://doi.org/10.3390/app13053363 - 06 Mar 2023
Cited by 1 | Viewed by 1119
Abstract
Waste management is one of most important challenges in environmental protection. Much effort is put into the development of waste treatment methods for further use. A serious problem is the treatment of municipal sewage sludge. One method that is useful for this substrate [...] Read more.
Waste management is one of most important challenges in environmental protection. Much effort is put into the development of waste treatment methods for further use. A serious problem is the treatment of municipal sewage sludge. One method that is useful for this substrate is composting. However, it is reasonable to compost a sewage sludge mixed with other substrates, such as maize straw. To carry out the composting process properly, it is necessary to control some parameters, including the total solids and volatile solids content in the composted mixture. In this paper, a method for the determination of the total solids and volatile solids content based on image analysis and neural networks was proposed. Image analysis was used for the determination of the colour and texture parameters. The three additional features describing the composted material were percentage of sewage sludge, type of maize straw, and stage of compost maturity. The neural models were developed based on various combinations of the input parameters. For both the total solids and volatile solids content, the most accurate models were obtained using all input parameters, including 30 parameters for image colour and texture and three features describing the composted material. The uncertainties of the developed models, expressed by the MAPE error, were 2.88% and 0.59%, respectively, for the prediction of the total solids and volatile solids content. Full article
(This article belongs to the Special Issue New Development in Smart Farming for Sustainable Agriculture)
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18 pages, 4753 KiB  
Article
Simplified Calculation of Shear Rotations for First-Order Shear Deformation Theory in Deep Bridge Beams
Appl. Sci. 2023, 13(5), 3362; https://doi.org/10.3390/app13053362 - 06 Mar 2023
Cited by 1 | Viewed by 1331
Abstract
Nodal rotations are produced by bending and shear effects and bending rotations can be easily calculated using Euler–Bernoulli’s stiffness matrix method. Nevertheless, shear rotations are traditionally neglected, as their effects are practically negligible in most structures. This assumption might lead to significant errors [...] Read more.
Nodal rotations are produced by bending and shear effects and bending rotations can be easily calculated using Euler–Bernoulli’s stiffness matrix method. Nevertheless, shear rotations are traditionally neglected, as their effects are practically negligible in most structures. This assumption might lead to significant errors in the simulation of the rotations in some structures, as well as the wrong identification of the mechanical properties in inverse analysis. Despite its important role, no other works studying the calculation of shear rotations in deep beams were found in the literature. To fill this gap, after illustrating the errors of commercial software regarding calculating the rotations in deep beams, this study proposed a simple and intuitive method to calculate shear rotations in both isostatic and statically redundant beams. The new method calculates the shear rotation for all segments separately and introduces the result to the total rotation of the structure. This method can be applied to find the shear rotation in a redundant structure as well. A parametric study was carried out to calculate slenderness ratios to determine in what structural systems the shear rotations can be neglected. In addition, the errors in the inverse analysis of deep beams were parametrically studied to determine the role of shear rotation in different structural systems. Finally, to validate the application of the method in actual structures, a construction stage of a composite bridge was analyzed. Full article
(This article belongs to the Special Issue Advanced Structural Health Monitoring: From Theory to Applications II)
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15 pages, 2020 KiB  
Article
Consistency of Water Vapour Pressure and Specific Heat Capacity Values for Modelling Clay-Based Engineered Barriers
Appl. Sci. 2023, 13(5), 3361; https://doi.org/10.3390/app13053361 - 06 Mar 2023
Viewed by 1091
Abstract
The aim of this study is to assess the consistency in the modelling of thermo-hydraulic problems in clay-based engineered barriers. This study focuses on two aspects: the modelling of vapour pressure as a function of temperature, and the specific heat capacities of liquid [...] Read more.
The aim of this study is to assess the consistency in the modelling of thermo-hydraulic problems in clay-based engineered barriers. This study focuses on two aspects: the modelling of vapour pressure as a function of temperature, and the specific heat capacities of liquid water and water vapour in relation to the enthalpy of vaporisation and the internal energy of liquid water and water vapour. Regarding the first aspect, several formulations of the saturated vapour pressure have been inspected, evaluating their accuracy and information provided in the temperature range from 0 to 150 °C. Regarding the second aspect, the enthalpy of vaporisation and the internal energy of water were used to assess the consistency of pairs of specific heat capacity values in the same temperature range. Values from the literature were also inspected. An accurate and simple enough expression for the saturated water vapour pressure with temperature has been identified as the optimal option for modelling. Recommendations on specific heat capacity constant values for liquid water and vapour are suggested to maximise consistency in the studied temperature range. However, the loss of accuracy in the enthalpy or internal energy of vaporisation associated with the inspected specific heat capacity pairs is limited. Full article
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12 pages, 1155 KiB  
Article
A Walkway from Crayfish to Oligochitosan
Appl. Sci. 2023, 13(5), 3360; https://doi.org/10.3390/app13053360 - 06 Mar 2023
Cited by 1 | Viewed by 1082
Abstract
Edible crayfish are an object of local fishing and artificial breeding in many countries. This industry is very promising in terms of production of healthy foods and byproducts, such as biologically active polyaminosaccharide—chitosan and its derivatives. However, crayfishing is far from being at [...] Read more.
Edible crayfish are an object of local fishing and artificial breeding in many countries. This industry is very promising in terms of production of healthy foods and byproducts, such as biologically active polyaminosaccharide—chitosan and its derivatives. However, crayfishing is far from being at the level at which it could be. This laboratory scale protocol describes a walkway from crayfish Actacus leptodactylus to chitin, chitosan, and oligochitosan hydrochloride, with the main emphasis on the way of getting rid of the impurities (residual heavy metals, proteins and other residues) commonly present in commercial chitosan and its derivatives, as well as the characterization of the products by means of inductively-coupled plasma mass spectrometry (ICP-MS), energy-dispersive X-ray spectroscopy (EDXS), protein and elemental analysis, proton magnetic resonance spectroscopy (1H NMR), and chromatography methods. The protocol includes the preparation of crude shell waste; the extraction of proteins from crude shell waste and preparation of deproteinated shell waste, demineralization and decolorization of the deproteinated crayfish shell waste, deacetylation of chitin, and depolymerization of chitosan. EDXS shows the presence of Al and Si residues in chitin is found when the deproteination of crayfish waste is carried out in an alumosilicate glass vessel. In contrast, these residues are absent when deproteination is carried out in the borosilicate glass flask. Analytical data show that the content of residues in chitosan and oligochitosan hydrochloride meets pharmaceutical requirements. The study demonstrates crayfish waste a promising for the purification of chitosan, for the preparation of pharmaceutical grade oligochitosan hydrochloride, and can improve commercialization of crayfishes. Full article
(This article belongs to the Special Issue Functional Polymers: Synthesis, Properties and Applications)
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21 pages, 7001 KiB  
Article
Voice Interaction Recognition Design in Real-Life Scenario Mobile Robot Applications
Appl. Sci. 2023, 13(5), 3359; https://doi.org/10.3390/app13053359 - 06 Mar 2023
Cited by 3 | Viewed by 2408
Abstract
This paper designed a voice interactive robot system that can conveniently execute assigned service tasks in real-life scenarios. It is equipped without a microphone where users can control the robot with spoken commands; the voice commands are then recognized by a well-trained deep [...] Read more.
This paper designed a voice interactive robot system that can conveniently execute assigned service tasks in real-life scenarios. It is equipped without a microphone where users can control the robot with spoken commands; the voice commands are then recognized by a well-trained deep neural network model of automatic speech recognition (ASR), which enables the robot to execute and complete the command based on the navigation of a real-time simultaneous localization and mapping (SLAM) algorithm. The voice interaction recognition model is divided into two parts: (1) speaker separation and (2) ASR. The speaker separation is applied by a deep-learning system consisting of eight convolution layers, one LSTM layer, and two fully connected (FC) layers to separate the speaker’s voice. This model recognizes the speaker’s voice as a referrer that separates and holds the required voiceprint and removes noises from other people’s voiceprints. Its automatic speech recognition uses the novel sandwich-type conformer model with a stack of three layers, and combines convolution and self-attention to capture short-term and long-term interactions. Specifically, it contains a multi-head self-attention module to directly convert the voice data into text for command realization. The RGB-D vision-based camera uses a real-time appearance-based mapping algorithm to create the environment map and replace the localization with a visional odometer to allow the robot to navigate itself. Finally, the proposed ASR model was tested to check if the desired results will be obtained. Performance analysis was applied to determine the robot’s environment isolation and voice recognition abilities. The results showed that the practical robot system successfully completed the interactive service tasks in a real environment. This experiment demonstrates the outstanding performance with other ASR methods and voice control mobile robot systems. It also verified that the designed voice interaction recognition system enables the mobile robot to execute tasks in real-time, showing that it is a convenient way to complete the assigned service applications. Full article
(This article belongs to the Special Issue Selected Papers from IMETI 2021)
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15 pages, 2803 KiB  
Article
Dehydrated Sauerkraut Juice in Bread and Meat Applications and Bioaccessibility of Total Phenol Compounds after In Vitro Gastrointestinal Digestion
Appl. Sci. 2023, 13(5), 3358; https://doi.org/10.3390/app13053358 - 06 Mar 2023
Viewed by 1161
Abstract
The aim of this study was to evaluate dehydrated sauerkraut juice (DSJ) in bread and meat applications and investigate bioaccessibility (BAC) of TPC in the analyzed products. In current research, sauerkraut juice, dehydrated sauerkraut juice, and bread and meat products prepared with dehydrated [...] Read more.
The aim of this study was to evaluate dehydrated sauerkraut juice (DSJ) in bread and meat applications and investigate bioaccessibility (BAC) of TPC in the analyzed products. In current research, sauerkraut juice, dehydrated sauerkraut juice, and bread and meat products prepared with dehydrated sauerkraut juice were analyzed. For all of the samples, total phenol content, antiradical activity by ABTS+, bioaccessibility, and volatile compound profile were determined. Additionally, sensory evaluation was performed to evaluate the degree of liking bread and meat with dehydrated sauerkraut juice. The addition of DSJ increased TPC in bread and meat samples. The bioaccessibility was higher for the control samples compared to DSJ samples. It exceeded 1 and is considered as good. DSJ did not promote bioaccessibility. Benzaldehyde was the highest peak area for the Bread DSJ and Meat DSJ samples, giving a roasted peanut and almond aroma. There were no significant differences in degree of liking for structure, taste, and aroma between the control bread and the Bread DSJ, while Meat DSJ was more preferable in sensory evaluation. DSJ could be used in food applications, but further research is necessary. Full article
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10 pages, 1138 KiB  
Article
Audio Feedback with the Use of a Smartphone in Sailing Training among Windsurfers
Appl. Sci. 2023, 13(5), 3357; https://doi.org/10.3390/app13053357 - 06 Mar 2023
Viewed by 1073
Abstract
The open-water training conditions in sailing sports limit the coach’s ability to provide instructions. Auditory feedback provided using a smartphone application in real-time seems to be a promising tool in the training process. The aim of the study was to assess the usefulness [...] Read more.
The open-water training conditions in sailing sports limit the coach’s ability to provide instructions. Auditory feedback provided using a smartphone application in real-time seems to be a promising tool in the training process. The aim of the study was to assess the usefulness of a smartphone application created to support tactical decisions via an auditory display. Thirteen successful windsurfers competing in RS:X class took part in the study. The results, collected with the use of a questionnaire, related to the technical and aesthetic aspects of the functions as well as decision-making assistance of the application during upwind sailing races. Most of the competitors positively evaluated application function (54–85%). Real-time information about the deviation from the set course and information about potential tack change due to a changed wind direction were statistically significantly more helpful for less experienced windsurfers (rho = −0.68 and rho = −0.78, respectively) and those with lower sports level (rho = −0.63 and rho = −0.65, respectively). It can be concluded that the use of sound feedback in the conditions of training on-water in sailing has potential, primarily for younger and less experienced competitors. Quantitative evaluations of the sailing performance should be considered in further research on the functionality of the application. Full article
(This article belongs to the Special Issue Wearables and Smartphone Applications in Sports)
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13 pages, 5024 KiB  
Article
Effectiveness of High-Damping Rubber (HDR) Damper and Tuned Mass—HDR Damper in Suppressing Stay-Cable Vibration
Appl. Sci. 2023, 13(5), 3356; https://doi.org/10.3390/app13053356 - 06 Mar 2023
Cited by 1 | Viewed by 1308
Abstract
High-damping rubber (HDR) dampers have the advantages of convenience for various shapes of pressure blocks, aesthetic installation, easy maintenance, temperature stability, etc.; thus, they present good application prospects in the vibration reduction of stay cables. Hence, a model of a taut cable equipped [...] Read more.
High-damping rubber (HDR) dampers have the advantages of convenience for various shapes of pressure blocks, aesthetic installation, easy maintenance, temperature stability, etc.; thus, they present good application prospects in the vibration reduction of stay cables. Hence, a model of a taut cable equipped with two types of HDR damper—i.e., HDR damper and tuned mass–high-damping rubber damper (TM-HDR-D)—is established herein. Then, based on this theoretical model, the effect of each damper acting alone and in combination on the cable’s additional modal damping is studied. Finally, an actual cable of a cable-stayed bridge is used to study the effectiveness of two dampers for practical engineering. The results show that, when the TM-HDR-D has a small mass, the total additional modal damping of the cable approximates the superposition of the respective effects of the two dampers. The damping effect of HDR mainly depends on its stiffness and installation position; meanwhile, the damping contribution of TM-HDR-D is mainly related to its tuning frequency and installation position. In practical engineering, the smaller installation mass of TM-HDR-D can make up for the lack of damping enhancement of the cable-end HDR damper. Full article
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17 pages, 19304 KiB  
Article
Structural Design of Aerostatic Bearing Based on Multi-Objective Particle Swarm Optimization Algorithm
Appl. Sci. 2023, 13(5), 3355; https://doi.org/10.3390/app13053355 - 06 Mar 2023
Cited by 1 | Viewed by 903
Abstract
Aerostatic bearings are considered crucial components that can improve the measurement accuracy of ground simulation tests of space equipment. A structural optimization design method is proposed to enhance the static performance of aerostatic bearings. A mathematical model which can quickly calculate the aerostatic [...] Read more.
Aerostatic bearings are considered crucial components that can improve the measurement accuracy of ground simulation tests of space equipment. A structural optimization design method is proposed to enhance the static performance of aerostatic bearings. A mathematical model which can quickly calculate the aerostatic bearing capacity and gas consumption is established, and the influence of structural parameters on bearing performance is analyzed using simulation software. By comparing the convergence time and convergence results of the algorithm using different initialization methods, the Latin hypercube initialization method is selected instead of the random initialization method. The multi-objective particle swarm optimization algorithm is used to obtain the optimal solution set distributed in the objective space. It is found that the optimized structural parameters meet the requirements of improving the capacity and reducing gas consumption, which verifies the method’s effectiveness in designing the structural parameters of aerostatic bearings. Full article
(This article belongs to the Special Issue Structural Optimization Methods and Applications)
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33 pages, 2975 KiB  
Review
Use of Phase Change Materials for Food Applications—State of the Art in 2022
Appl. Sci. 2023, 13(5), 3354; https://doi.org/10.3390/app13053354 - 06 Mar 2023
Cited by 9 | Viewed by 3041
Abstract
The availability of food to a growing world population is a matter of concern for decades. Despite that, post-harvest losses are large in many countries, due to insufficient food preservation. And recently rising prices for fossil energies additionally increase food cost, thus increase [...] Read more.
The availability of food to a growing world population is a matter of concern for decades. Despite that, post-harvest losses are large in many countries, due to insufficient food preservation. And recently rising prices for fossil energies additionally increase food cost, thus increase the demand for energy efficiency. Probably the first application of phase change materials (PCM) ever was the use of ice for food storage, for preservation. Related to that is the use of ice for transport, and for fast cool down in food processing. The result of a desktop study shows the range of food applications of PCM, the advantages using PCM, and the state-of-the-art, meaning past and ongoing R&D, also including existing commercial products. The overview covers food processing, e.g., industrial process cooling and heating, local pre-cooling of harvested food, solar drying and cooking, for storage and transport e.g., solar cold rooms, fridges, display coolers, trucks and containers, and for food production specifically greenhouses and water purification. PCM are used in many real applications as commercial products, and in many other applications their advantages are proven. Regarding future R&D, the overview also identifies potential for improvement, possibly even of commercial products. Full article
(This article belongs to the Special Issue The Application of Phase Change Materials in Heat Storage)
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27 pages, 4589 KiB  
Review
Bond Characterization in Cementitious Material Binders Using Fourier-Transform Infrared Spectroscopy
Appl. Sci. 2023, 13(5), 3353; https://doi.org/10.3390/app13053353 - 06 Mar 2023
Cited by 11 | Viewed by 4063
Abstract
Fourier-transform infrared (FTIR) spectroscopy is a fast and simple technique for functional group identification. This work provides a review and insight into the application and interpretation of FTIR spectroscopy for cementitious binders that comprise ordinary Portland cement, alkaline-activated binders, geopolymers, and material characterization [...] Read more.
Fourier-transform infrared (FTIR) spectroscopy is a fast and simple technique for functional group identification. This work provides a review and insight into the application and interpretation of FTIR spectroscopy for cementitious binders that comprise ordinary Portland cement, alkaline-activated binders, geopolymers, and material characterization for civil engineering material applications. This technique can be used to identify different compounds and a moiety of bond vibrations in inorganic molecules such as Si-O, -OH, H-O-H (water), C-O (carbonate or carbonation), aluminosilicate (Si-O-T, where T is Al or Si), and S-O (sulfate or gypsum) found in hydrated cement, alkaline binders, and geopolymers. The prominent bands include those representing carbonation (CO32− 1390–1475 cm−1), calcium carbonate (871, 1792–2516 cm−1), hydroxylation and water molecules (1607, 3400–3650 cm−1), strength skeletal framework compositions or Al-Si substitutions, silicate organization (C-A-S-H, N-A-S-H, or C-S-H (950–1055 cm−1), and sulfate (600–680, 1080–1100 cm−1). Some of the factors that could affect the spectra bands include elemental displacement due to changes in molar mass, activated temperature, pH, activator concentration, w/b ratio, Ca/Si ratio, Si/Al ratio, and the silica modulus (SiO2/Na2O) of the activators used in the binder synthesis. The method could be used for destructive and non-destructive testing on paste sample by using transmission and attenuated total reflectance methods, respectively. Full article
(This article belongs to the Special Issue Construction Materials: Characterization, Structure and Durability)
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11 pages, 599 KiB  
Article
Method for the Quantification of mHealth Related Physical Activity Intensity Using Consumer Mobile Sensors
Appl. Sci. 2023, 13(5), 3352; https://doi.org/10.3390/app13053352 - 06 Mar 2023
Viewed by 828
Abstract
Daily physical activity is one of the key factors to improve health and support the prevention of a variety of chronic diseases e.g., hypertension, depression or acute events such as strokes. Self-monitoring by the patients has shown to improve adherence to care and [...] Read more.
Daily physical activity is one of the key factors to improve health and support the prevention of a variety of chronic diseases e.g., hypertension, depression or acute events such as strokes. Self-monitoring by the patients has shown to improve adherence to care and thus leads to general improvement of health conditions. However, precise physical activity detection and quantification may involve heavy or expensive sensors and often-complex computations. Other types of bottlenecks, such as proprietary algorithms or machine learning methods, which often do not meet requirements of medical use cases due to a lack in transparency and requested levels of accuracy and robustness, motivated the work presented here. In this paper, we propose the adaptation of the Euclidean norm minus one method, which was already demonstrated as relevant for physical activity intensity discrimination. The main modification stands in the use of a gravity estimate to countervail imprecise sensors, which allows using the metric with low sampled wrist accelerometer data, collected with off-the-shelf smartwatches in daily live environments. As proof of concept, the proposed algorithm was evaluated on a reference data set acquired on healthy subjects. The method shows the ability to discriminate between low, moderate, and high intensity activities. Full article
(This article belongs to the Section Biomedical Engineering)
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16 pages, 5954 KiB  
Article
Interference Mitigation for Metro Train Location Based on Karhunen–Loeve Decomposition
Appl. Sci. 2023, 13(5), 3351; https://doi.org/10.3390/app13053351 - 06 Mar 2023
Viewed by 960
Abstract
We propose a communication positioning integrated signal (CPIS) to achieve sub-meter positioning of metro trains. However, the electromagnetic environment of metro trains is complex, and the interference of radio frequency signals will reduce the accuracy of train positioning and affect the safe operation [...] Read more.
We propose a communication positioning integrated signal (CPIS) to achieve sub-meter positioning of metro trains. However, the electromagnetic environment of metro trains is complex, and the interference of radio frequency signals will reduce the accuracy of train positioning and affect the safe operation of trains. In this paper, an interference mitigation method for metro train positioning based on Karhunen–Loeve decomposition is proposed. The signal is orthogonally expanded, and the eigenvalues of the interference signal are obtained according to the distribution characteristics of the eigenvalues. The reconstructed interference signal is then subtracted from the received signal to achieve interference suppression. The experimental results demonstrate the effectiveness of the method in interference scenarios. Full article
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15 pages, 8601 KiB  
Article
Design of Low-Power ECG Sampling and Compression Circuit
Appl. Sci. 2023, 13(5), 3350; https://doi.org/10.3390/app13053350 - 06 Mar 2023
Viewed by 946
Abstract
Compressed Sensing (CS) has been applied to electrocardiogram monitoring in wireless sensor networks, but existing sampling and compression circuits consume too much hardware. This paper proposes a low-power and small-area sampling and compression circuit with an Analog-to-Digital Converter (ADC) and a CS module. [...] Read more.
Compressed Sensing (CS) has been applied to electrocardiogram monitoring in wireless sensor networks, but existing sampling and compression circuits consume too much hardware. This paper proposes a low-power and small-area sampling and compression circuit with an Analog-to-Digital Converter (ADC) and a CS module. The ADC adopts split capacitors to reduce hardware consumption and uses a calibration technique to decrease offset voltage. The CS module uses an approximate addition calculation for compression and stores the compressed data in pulsed latches. The proposed addition completes the accurate calculation of the high part and the approximate calculation of the low part. In a 55 nm CMOS process, the ADC has an area of 0.011 mm2 and a power consumption of 0.214 μW at 10 kHz. Compared with traditional design, the area and power consumption of the proposed CS module are reduced by 19.5% and 31.7%, respectively. The sampling and compression circuit area is 0.325 mm2, and the power consumption is 2.951 μW at 1.2 V and 100 kHz. The compressed data are reconstructed with a percentage root mean square difference of less than 2%. The results indicate that the proposed circuit has performance advantages of hardware consumption and reconstruction quality. Full article
(This article belongs to the Section Electrical, Electronics and Communications Engineering)
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19 pages, 5423 KiB  
Article
Design and Implementation of an Active Vibration Control Algorithm Using Servo Actuator Control Installed in Series with a Spring-Damper
by , and
Appl. Sci. 2023, 13(5), 3349; https://doi.org/10.3390/app13053349 - 06 Mar 2023
Viewed by 3810
Abstract
The membrane-type air spring can be used to suppress lateral vibration of a vibration isolation table. However, compared to voice coil actuators, pneumatic actuators are difficult to use for precise vibration control, because servo valves have nonlinear dynamic characteristics. Therefore, actuators, such as [...] Read more.
The membrane-type air spring can be used to suppress lateral vibration of a vibration isolation table. However, compared to voice coil actuators, pneumatic actuators are difficult to use for precise vibration control, because servo valves have nonlinear dynamic characteristics. Therefore, actuators, such as voice coil actuators, can be placed in parallel with air springs, allowing force-type actuators to provide additional force to the system. These actuators generate force. In the case of a ball-screw mechanism device or a linear servomotor, it is an actuator that generates displacement. These actuators are represented as serial active systems. Serial active systems are structurally simpler than parallel active systems. However, there are very few studies on vibration isolation systems using serial active systems compared to parallel active systems. As the two are different types of systems, a new control algorithm suitable for the serial active system is needed. This study proposes a system in which an actuator capable of accurately controlling displacement is connected in series with a support spring-damper. A new active vibration control algorithm for the proposed control system is also developed, which is termed the position input and position output. The proposed control algorithm uses the displacement of the system as an input and outputs the desired displacement of the actuator installed in series with the damper and spring. The proposed control algorithm increases the damping at the target frequency and reduces the response of the system. Numerical studies and experiments were conducted on the single-degree-of-freedom and multi-degree-of-freedom systems. The results show the efficacy of the proposed control system and the novel control algorithm for the vibration suppression of the lateral vibration of a vibration isolation table. Full article
(This article belongs to the Special Issue Active Vibration and Noise Control)
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19 pages, 794 KiB  
Article
Temporal Extraction of Complex Medicine by Combining Probabilistic Soft Logic and Textual Feature Feedback
Appl. Sci. 2023, 13(5), 3348; https://doi.org/10.3390/app13053348 - 06 Mar 2023
Cited by 1 | Viewed by 1026
Abstract
In medical texts, temporal information describes events and changes in status, such as medical visits and discharges. According to the semantic features, it is classified into simple time and complex time. The current research on time recognition usually focuses on coarse-grained simple time [...] Read more.
In medical texts, temporal information describes events and changes in status, such as medical visits and discharges. According to the semantic features, it is classified into simple time and complex time. The current research on time recognition usually focuses on coarse-grained simple time recognition while ignoring fine-grained complex time. To address this problem, based on the semantic concept of complex time in Clinical Time Ontology, we define seven basic features and eleven extraction rules and propose a complex medical time-extraction method. It combines probabilistic soft logic and textual feature feedback. The framework consists of two parts: (a) text feature recognition based on probabilistic soft logic, which is based on probabilistic soft logic for negative feedback adjustment; (b) complex medical time entity recognition based on text feature feedback, which is based on the text feature recognition model in (a) for positive feedback adjustment. Finally, the effectiveness of our approach is verified in text feature recognition and complex temporal entity recognition experimentally. In the text feature recognition task, our method shows the best F1 improvement of 18.09% on the Irregular Instant Collection type corresponding to utterance l17. In the complex medical temporal entity recognition task, the F1 metric improves the most significantly, by 10.42%, on the Irregular Instant Collection type. Full article
(This article belongs to the Special Issue Natural Language Processing (NLP) and Applications)
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23 pages, 2315 KiB  
Article
A Flexible Session-Based Recommender System for e-Commerce
Appl. Sci. 2023, 13(5), 3347; https://doi.org/10.3390/app13053347 - 06 Mar 2023
Cited by 1 | Viewed by 2384
Abstract
Research into session-based recommendation systems (SBSR) has attracted a lot of attention, but each study focuses on a specific class of methods. This work examines and evaluates a large range of methods, from simpler statistical co-occurrence methods to embeddings and SotA deep learning [...] Read more.
Research into session-based recommendation systems (SBSR) has attracted a lot of attention, but each study focuses on a specific class of methods. This work examines and evaluates a large range of methods, from simpler statistical co-occurrence methods to embeddings and SotA deep learning methods. This paper analyzes theoretical and practical issues in developing and evaluating methods for SBSR in e-commerce applications, where user profiles and purchase data do not exist. The major tasks of SBRS are reviewed and studied, namely: prediction of next-item, next-basket and purchase intent. For physical retail shopping where no information about the current session exists, we treat the previous baskets purchased by the user as previous sessions drawn from a loyalty system. Mobile application scenarios such as push notifications and calling tune recommendations are also presented. Recommender models using graphs, embeddings and deep learning methods are studied and evaluated in all SBRS tasks using different datasets. Our work contributes a number of very interesting findings. Among all tested models, LSTMs consistently outperform other methods of SBRS in all tasks. They can be applied directly because they do not need significant fine-tuning. Additionally, they naturally model the dynamic browsing that happens in e-commerce web applications. On the other hand, another important finding of our work is that graph-based methods can be a good compromise between effectiveness and efficiency. Another important conclusion is that a “temporal locality principle” holds, implying that more recent behavior is better suited for prediction. In order to evaluate these systems further in realistic environments, several session-based recommender methods were integrated into an e-shop and an A/B testing method was applied. The results of this A/B testing are in line with the experimental results, which represents another important contribution of this paper. Finally, important parameters such as efficiency, application of business rules, re-ranking issues, and the utilization of hybrid methods are also considered and tested, providing comprehensive useful insights into SBRS and facilitating the transferability of this research work to other domains and recommendation scenarios. Full article
(This article belongs to the Special Issue Data Analysis and Mining)
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12 pages, 2759 KiB  
Communication
Multi-Objective Parametric Optimization Design for Mirrors Combined with Non-Dominated Sorting Genetic Algorithm
Appl. Sci. 2023, 13(5), 3346; https://doi.org/10.3390/app13053346 - 06 Mar 2023
Cited by 2 | Viewed by 1017
Abstract
The process of intelligent multi-objective parametric optimization design for mirrors is discussed in detail in this paper, with the error of the mirror surface shape and the total mass being examined as the optimization objectives. The establishment of complex objective functions for solving [...] Read more.
The process of intelligent multi-objective parametric optimization design for mirrors is discussed in detail in this paper, with the error of the mirror surface shape and the total mass being examined as the optimization objectives. The establishment of complex objective functions for solving the optimization problem of the mirror surface shape error was realized, and manual modification of the model was avoided. Moreover, combining this with a non-dominated sorting genetic algorithm (NSGA) helped the Pareto front move towards an ideal optimal set of solutions. To verify the effectiveness of the proposed method, an aluminum alloy mirror with an aperture of 140 mm was taken as an example. The Pareto optimal solution set of the mass and surface shape error under 1 g gravity was obtained for finding the required solution and satisfying the optimization goal. In addition, this method is applicable to other complex structural design problems. Full article
(This article belongs to the Special Issue Advanced Optoelectronic Devices and Systems)
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21 pages, 801 KiB  
Article
Does Context Matter? Effective Deep Learning Approaches to Curb Fake News Dissemination on Social Media
Appl. Sci. 2023, 13(5), 3345; https://doi.org/10.3390/app13053345 - 06 Mar 2023
Cited by 5 | Viewed by 1617
Abstract
The prevalence of fake news on social media has led to major sociopolitical issues. Thus, the need for automated fake news detection is more important than ever. In this work, we investigated the interplay between news content and users’ posting behavior clues in [...] Read more.
The prevalence of fake news on social media has led to major sociopolitical issues. Thus, the need for automated fake news detection is more important than ever. In this work, we investigated the interplay between news content and users’ posting behavior clues in detecting fake news by using state-of-the-art deep learning approaches, such as the convolutional neural network (CNN), which involves a series of filters of different sizes and shapes (combining the original sentence matrix to create further low-dimensional matrices), and the bidirectional gated recurrent unit (BiGRU), which is a type of bidirectional recurrent neural network with only the input and forget gates, coupled with a self-attention mechanism. The proposed architectures introduced a novel approach to learning rich, semantical, and contextual representations of a given news text using natural language understanding of transfer learning coupled with context-based features. Experiments were conducted on the FakeNewsNet dataset. The experimental results show that incorporating information about users’ posting behaviors (when available) improves the performance compared to models that rely solely on textual news data. Full article
(This article belongs to the Special Issue Text Mining, Machine Learning, and Natural Language Processing)
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17 pages, 2862 KiB  
Article
A Research on Fault Diagnosis of a USV Thruster Based on PCA and Entropy
Appl. Sci. 2023, 13(5), 3344; https://doi.org/10.3390/app13053344 - 06 Mar 2023
Cited by 2 | Viewed by 1248
Abstract
This study focuses on faults in the thrusters of unmanned surface vehicles, which are fatal to the integrity of their missions. As for the fault conditions, the breakage of the thruster blade and the entanglement of floating objects were selected, and a data-driven [...] Read more.
This study focuses on faults in the thrusters of unmanned surface vehicles, which are fatal to the integrity of their missions. As for the fault conditions, the breakage of the thruster blade and the entanglement of floating objects were selected, and a data-driven method was used to diagnose the faults. In the data-driven method, it is important to select the sensitive fault feature. In this study, vibration, current consumption, rotational speed and input voltage were selected as fault features. An experiment was conducted in an engineering water tank to obtain and analyze data on fault conditions to verify the validity of the selected features. In addition, a new fault diagnosis algorithm combining principal component analysis and Shannon entropy was applied for analyzing the correlations among fault features. This algorithm reduces the dimensionality of data while preserving their structure and characteristics, and diagnoses faults by quantifying entropy values. A fault is detected by comparing the entropy value and a predetermined threshold value, and is diagnosed by analyzing the entropy value and visualized 2D or 3D principal component results. Moreover, the fault diagnosis performance of the unmanned surface vehicle’s thruster was verified by analyzing the results for each fault condition. Full article
(This article belongs to the Special Issue Selected Papers from IMETI 2021)
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