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Appl. Sci., Volume 13, Issue 1 (January-1 2023) – 675 articles

Cover Story (view full-size image): A digital twin describes the virtual presentation of a real process. Designing suitable digital twins for the path planning of autonomous robots or drones is often challenging due to a large number of different dynamic environments and multi-task and agent systems. In this work, homotopic shrinking is used to generate the digital twin, which can be used to extract all possible path proposals. Such a deterministic path algorithm can flexibly respond to changing environmental conditions and consider multiple tasks simultaneously for path generation. The method is tested on 2D and 3D maps with different tasks, obstacles, and multiple robots. Finally, it was shown that the environment for the digital twin can be reduced to reasonable paths by constrained shrinking, both for real 2D maps and for complex virtual 2D and 3D maps. View this paper
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23 pages, 1653 KiB  
Review
Control System Design and Methods for Collaborative Robots: Review
by Ayesha Hameed, Andrzej Ordys, Jakub Możaryn and Anna Sibilska-Mroziewicz
Appl. Sci. 2023, 13(1), 675; https://doi.org/10.3390/app13010675 - 3 Jan 2023
Cited by 12 | Viewed by 7596
Abstract
Collaborative robots cooperate with humans to assist them in undertaking simple-to-complex tasks in several fields, including industry, education, agriculture, healthcare services, security, and space exploration. These robots play a vital role in the revolution of Industry 4.0, which defines new standards of manufacturing [...] Read more.
Collaborative robots cooperate with humans to assist them in undertaking simple-to-complex tasks in several fields, including industry, education, agriculture, healthcare services, security, and space exploration. These robots play a vital role in the revolution of Industry 4.0, which defines new standards of manufacturing and the organization of products in the industry. Incorporating collaborative robots in the workspace improves efficiency, but it also introduces several safety risks. Effective safety measures then become indispensable to ensure safe and robust interaction. This paper presents the review of low-level control methodologies of a collaborative robot to assess the current status of human–robot collaboration over the last decade. First, we discuss the classification of human–robot collaboration, architectures of systems and the complex requirements on control strategies. The most commonly used control approaches were presented and discussed. Several methods of control, reported in industrial applications, are elaborated upon with a prime focus on HR-collaborative assembly operations. Since the physical HRC is a critical control problem for the co-manipulation task, this article identifies key control challenges such as the prediction of human intentions, safety, and human-caused disturbances in motion synchronization; the proposed solutions were analyzed afterwards. The discussion at the end of the paper summarizes the features of the control systems that should be incorporated within the systematic framework to allow the execution of a robotic task from global task planning to low-level control implementation for safe and robust interactions. Full article
(This article belongs to the Section Computing and Artificial Intelligence)
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13 pages, 5140 KiB  
Article
Deep Image Clustering Based on Label Similarity and Maximizing Mutual Information across Views
by Feng Peng and Kai Li
Appl. Sci. 2023, 13(1), 674; https://doi.org/10.3390/app13010674 - 3 Jan 2023
Viewed by 3368
Abstract
Most existing deep image clustering methods use only class-level representations for clustering. However, the class-level representation alone is not sufficient to describe the differences between images belonging to the same cluster. This may lead to high intra-class representation differences, which will harm the [...] Read more.
Most existing deep image clustering methods use only class-level representations for clustering. However, the class-level representation alone is not sufficient to describe the differences between images belonging to the same cluster. This may lead to high intra-class representation differences, which will harm the clustering performance. To address this problem, this paper proposes a clustering model named Deep Image Clustering based on Label Similarity and Maximizing Mutual Information Across Views (DCSM). DCSM consists of a backbone network, class-level and instance-level mapping block. The class-level mapping block learns discriminative class-level features by selecting similar (dissimilar) pairs of samples. The proposed extended mutual information is to maximize the mutual information between features extracted from views that were obtained by using data augmentation on the same image and as a constraint on the instance-level mapping block. This forces the instance-level mapping block to capture high-level features that affect multiple views of the same image, thus reducing intra-class differences. Four representative datasets are selected for our experiments, and the results show that the proposed model is superior to the current advanced image clustering models. Full article
(This article belongs to the Special Issue Algorithms and Applications of Multi-View Information Clustering)
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14 pages, 1937 KiB  
Article
Research on Efficient Construction Paths for Intelligent Coal Mines in China from the Configuration Perspective
by Xiaofang Yuan, Yutong Wu, Linhui Sun and Xinping Wang
Appl. Sci. 2023, 13(1), 673; https://doi.org/10.3390/app13010673 - 3 Jan 2023
Cited by 21 | Viewed by 3295
Abstract
The intelligent transformation of coal mines is an inevitable choice to promote the green transformation of energy and to achieve safety and efficiency in the industry. Exploring the path of its efficient construction is the key to realizing the construction of intelligent coal [...] Read more.
The intelligent transformation of coal mines is an inevitable choice to promote the green transformation of energy and to achieve safety and efficiency in the industry. Exploring the path of its efficient construction is the key to realizing the construction of intelligent coal mines in China. To analyze the configuration paths for the efficient construction of intelligent coal mines, 17 typical coal-producing provinces in China were used as the research object of a fuzzy set qualitative comparative analysis (fsQCA), and five conditional variables, namely research funds, technical talent, government importance degree, national demonstration, and basic resource support, were selected from four levels (technology, organization, environment, and resources) based on relevant national data from 2019–2021, and multiple configurations as well as multiple driving paths for the construction of intelligent coal mines were discussed. We found that there are three configuration paths that will enable the construction of intelligent coal mines: a technology-driven path under the government’s supervision, a path jointly driven by three-prongs, and a policy-driven path under the resource priority. The critical importance of the government is the common factor among the three driving modes. These research results can provide useful construction ideas for the construction of intelligent coal mines in different regions and enable provincial governments to carry out strategic combination actions according to local conditions to contribute to the efficient construction of intelligent coal mines and the green transformation of energy across the country. Full article
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22 pages, 7200 KiB  
Article
AC Electric Powertrain without Power Electronics for Future Hybrid Electric Aircrafts: Architecture, Design and Stability Analysis
by Alexandre Richard, Xavier Roboam, Florent Rougier, Nicolas Roux and Hubert Piquet
Appl. Sci. 2023, 13(1), 672; https://doi.org/10.3390/app13010672 - 3 Jan 2023
Cited by 2 | Viewed by 1601
Abstract
This paper proposes an electric powertrain architecture for future hybrid electric aircrafts which structure is only composed of permanent magnet synchronous machines for both generators (PMSG) and motors (PMSM). The direct connection through an AC bus of a PMSG with one or several [...] Read more.
This paper proposes an electric powertrain architecture for future hybrid electric aircrafts which structure is only composed of permanent magnet synchronous machines for both generators (PMSG) and motors (PMSM). The direct connection through an AC bus of a PMSG with one or several PMSMs involves the suppression of power electronics usually embedded in electric or hybrid electric powertrains. The idea is clearly to simplify the architecture and to significantly reduce the weight of propulsive device, “weight being the prime enemy in aeronautics”. However, the connection between power generation and propulsion devices through power electronics converters offers degrees of freedom allowing to control and stabilize the whole system. Contrarily, the direct connection between synchronous machines (PMSG-PMSM) sets a rigid link with non-linear behavior between both devices, causing complex stability issues that are analyzed. For that purpose, after having discussed the advantages and drawbacks of this powertrain by comparison with classical architectures, including power electronics, a set of models (analytic and simulation) and analysis tools (root locus, transient time simulation) is proposed. They are used in a theoretical approach to emphasize the stability issue and to assess parameter sensitivity. A reduced power scale test bench with a single-motor AC powertrain is presented: together with circuit simulation models, it is used to compare and validate the theoretical analysis results. Full article
(This article belongs to the Special Issue Aerospace Vehicle Design under Uncertainties)
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14 pages, 4521 KiB  
Article
Three-Dimensional Numerical Modeling of Artificially Freezing Ground in Metro Station Construction
by Bo Wang, Jun Hu, Xiaoqi Lin and Hui Zeng
Appl. Sci. 2023, 13(1), 671; https://doi.org/10.3390/app13010671 - 3 Jan 2023
Viewed by 1768
Abstract
In this study, the engineering background of No. 2 complex connecting passage of Binhu Road Station/Jinhu Square Station of Nanning Metro Line 3 is investigated, where the artificial ground freezing technique is adopted. A three-dimensional finite element model is established to investigate the [...] Read more.
In this study, the engineering background of No. 2 complex connecting passage of Binhu Road Station/Jinhu Square Station of Nanning Metro Line 3 is investigated, where the artificial ground freezing technique is adopted. A three-dimensional finite element model is established to investigate the temperature development of the frozen soil curtain, with a simulation of the dynamic evolution of the frosted soil curtain. The finite element model is validated by comparing the overall trend of the measured temperature value and the resulting temperature value, which are roughly the same. According to the design scheme, the weakest part of the whole frozen soil curtain is the top of the bell mouth where the downhole tunnel intersects the connecting passage. It is recommended to make a row of smaller freezing holes to enhance the freezing effect in this area. The thickness of the frozen soil curtain reached 1.75 m or more, indicating that the whole frozen soil curtain meets the design requirements and shows the right features for excavation construction. After freezing for 40 days, the average thickness of the frozen soil curtain is 2.4 m, indicating that the freezing effect meets the design requirements. The project can be successfully carried out, which suggests that the underneath passage construction is feasible. As a result, the results of the numerical model are applicable for comparable projects using artificially freezing ground in metro station construction. Full article
(This article belongs to the Special Issue State-of-the-Art Earth Sciences and Geography in China)
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21 pages, 6138 KiB  
Article
ReconTraj4Drones: A Framework for the Reconstruction and Semantic Modeling of UAVs’ Trajectories on MovingPandas
by Konstantinos Kotis and Andreas Soularidis
Appl. Sci. 2023, 13(1), 670; https://doi.org/10.3390/app13010670 - 3 Jan 2023
Cited by 1 | Viewed by 2465
Abstract
Unmanned aerial vehicles (UAVs), also known as drones, are important for several application domains, such as the military, agriculture, cultural heritage documentation, surveillance, and the delivery of goods/products/services. A drone’s trajectory can be enriched with external and heterogeneous data beyond latitude, longitude, and [...] Read more.
Unmanned aerial vehicles (UAVs), also known as drones, are important for several application domains, such as the military, agriculture, cultural heritage documentation, surveillance, and the delivery of goods/products/services. A drone’s trajectory can be enriched with external and heterogeneous data beyond latitude, longitude, and timestamp to create its semantic trajectory, providing meaningful and contextual information on its movement data, enabling decision makers to acquire meaningful and enriched contextual information about the current situation in the field of its operation and eventually supporting simulations and predictions of high-level critical events. In this paper, we present an ontology-based, tool-supported framework for the reconstruction, modeling, and enrichment of drones’ semantic trajectories. This framework extends MovingPandas, a widely used and open-source trajectory analytics and visualization tool. The presented research extends our preliminary work on drones’ semantic trajectories by contributing (a) an updated methodology for the reconstruction of drones’ trajectories from geo-tagged photos taken by drones during their flights in cases in which flight plans and/or real-time movement data have been lost or corrupted; (b) an enrichment of the reconstructed trajectories with external data; (c) the semantic annotation of the enriched trajectories based on a related ontology; and (d) the use of SPARQL queries to analyze and retrieve knowledge related to the flight of a drone and the field of operations (context). An evaluation of the presented framework, namely, ReconTraj4Drones, was conducted against several criteria, using real and open datasets. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicles (UAVs) and Their Applications)
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17 pages, 10044 KiB  
Article
Preliminary Study for Smoke Color Classification of Combustibles Using the Distribution of Light Scattering by Smoke Particles
by Hyo-Yeon Jang and Cheol-Hong Hwang
Appl. Sci. 2023, 13(1), 669; https://doi.org/10.3390/app13010669 - 3 Jan 2023
Cited by 4 | Viewed by 2148
Abstract
Photoelectric smoke detectors are used for early detection of building fires, and sensitivity adjustment is generally performed using white smoke generated by the burning of filter paper. Therefore, when black smoke of the same concentration is introduced, the detector is often not activated. [...] Read more.
Photoelectric smoke detectors are used for early detection of building fires, and sensitivity adjustment is generally performed using white smoke generated by the burning of filter paper. Therefore, when black smoke of the same concentration is introduced, the detector is often not activated. To address this problem, differences in the distribution of light scattered by smoke of various colors were analyzed. A light-scattering chamber with a light-receiving unit for various scattering angles was constructed to measure the scattered light generated inside the chamber of the smoke detector. The light scattering distribution was measured for smoke generated from three combustibles—filter paper (white smoke), kerosene (black smoke), and polyurethane (gray-black smoke)—and three analysis criteria were applied. By identifying a section where the measured values were concentrated for a specific analysis criterion and scattering angle, it was confirmed that some combustibles can be distinguished. Specifically, criterion III, a probabilistic section, was presented to determine which combustible smoke particles were close by applying the proposed section in a complex manner. A preliminary study was conducted to evaluate a methodology for the color classification of smoke particles flowing into a smoke detector chamber; this can be utilized as a foundation for determining optical properties. Full article
(This article belongs to the Special Issue Advanced Analysis and Technology in Fire Science and Engineering)
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18 pages, 4429 KiB  
Article
A Two-Stage Rolling Bearing Weak Fault Feature Extraction Method Combining Adaptive Morphological Filter with Frequency Band Selection Strategy
by Jun Li, Hongchao Wang, Simin Li, Liang Chen and Qiqian Dang
Appl. Sci. 2023, 13(1), 668; https://doi.org/10.3390/app13010668 - 3 Jan 2023
Viewed by 1556
Abstract
To extract the weak fault features hidden in strong background interference in the event of the early failure of rolling bearings, a two-stage based method is proposed. The broadband noise elimination ability of an adaptive morphological filter (AMF) and the superior capability of [...] Read more.
To extract the weak fault features hidden in strong background interference in the event of the early failure of rolling bearings, a two-stage based method is proposed. The broadband noise elimination ability of an adaptive morphological filter (AMF) and the superior capability of a frequency band selection (FBS) strategy for fault transient location identification are comprehensively utilized by the proposed method. Firstly, the AMF with a simple theory and high calculation efficiency is used as a preprocessing program to enhance the fault transient features. Then, the proposed FBS strategy based on the sparsity index (SI) is utilized to further handle the filtered signal processed by the AMF. Finally, the constructed optimum bandpass filter based on the analysis result of the FBS is used to further filter the handled signal processed by AMF and envelope spectral analysis is applied on the last filtered signal to realize the ideal fault feature extraction effect. Compared with the other traditional FBS methods based on kurtosis or the other index, the proposed FBS strategy based on SI has strong robustness to noise. One experimental signal and one engineering vibration signal are used, respectively, to verify the feasibility of the proposed method. Full article
(This article belongs to the Special Issue Active Vibration and Noise Control)
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11 pages, 261 KiB  
Article
Reliability of the Polygraphic Home Sleep Test for OSA Determined by the Severity and Pattern Changes of Two Consecutive Examinations
by Renáta Rozgonyi, József Janszky, Norbert Kovács and Béla Faludi
Appl. Sci. 2023, 13(1), 667; https://doi.org/10.3390/app13010667 - 3 Jan 2023
Viewed by 1216
Abstract
Diagnosis and effective treatment of obstructive sleep apnea syndrome (OSA) in adults is an important health priority. Home respiratory polygraphy is a cost-effective alternative to polysomnography in OSA. The aim of this study was to investigate the variability of two consecutive home respiratory [...] Read more.
Diagnosis and effective treatment of obstructive sleep apnea syndrome (OSA) in adults is an important health priority. Home respiratory polygraphy is a cost-effective alternative to polysomnography in OSA. The aim of this study was to investigate the variability of two consecutive home respiratory polygraphic examinations by comparing the severity characteristics and pattern (supine dominant, continuous, etc.) variability. We examined 100 patients with clinically suspected OSA on two consecutive nights by home respiratory polygraphy. The correlation of time in bed (TIB), apnea-hypopnea index (AHI), oxygen desaturation index (ODI), and T90 of the two examinations were compared by the Pearson test. The severity ranks and nocturnal apnea patterns of the two periods were compared using Spearman and Wilcoxon tests. Pearson’s correlations represented a strong correlation of the AHI, ODI, and T90, but only moderate for TIB. The severity-specific correlation was the highest for AHI in the severe group. Out of 100 pairs of polygraphic examinations, 25 cases showed change in the severity ranking (decreased in 11, increased in 14); 15 cases showed a change in the polygraphic pattern (supine, non-supine, etc.), with severity change in 6 cases. Therapy change based on the second examination was initiated in 6 cases. Our results revealed a good intra-individual correlation between the severity grades of the two nights, with the highest value in the severe cases. In some cases, the nightly variation in the polygraphic pattern may explain the change in the severity. From a therapeutic point of view, the low number of severity changes between moderate and severe groups revealed good reliability. Full article
(This article belongs to the Special Issue Obstructive Sleep Apnoea Syndrome and Its Management)
8 pages, 2818 KiB  
Communication
Biomechanical Rationale for a Novel Implant Design Reducing Stress on Buccal Bone
by Annika Schulz, Virgilia Klär, Tanja Grobecker-Karl and Matthias Karl
Appl. Sci. 2023, 13(1), 666; https://doi.org/10.3390/app13010666 - 3 Jan 2023
Cited by 3 | Viewed by 1391
Abstract
Modern implant designs should allow for adequate primary stability but limit mechanical stress on buccal bone in order to prevent initial marginal bone loss. A dental implant characterized by a shift in core diameter and thread geometry was evaluated. Polyurethane foam was used [...] Read more.
Modern implant designs should allow for adequate primary stability but limit mechanical stress on buccal bone in order to prevent initial marginal bone loss. A dental implant characterized by a shift in core diameter and thread geometry was evaluated. Polyurethane foam was used as bone surrogate material and implant placement was performed measuring insertion torque and strain development on buccal bone using strain gauges as well as primary stability by using damping capacity assessments. An existing tapered bone-level implant was used as a control while the novel experimental implant described above (n = 10) was used in the test group. Statistical analysis was based on t-tests (α = 0.05). Both the maximum insertion torque (p = 0.0016) and maximum strain development in buccal bone (p = 0.1069) were greater in control implants as compared to the novel implant design. Moreover, in the control group, these were reached at a significantly later timepoint of the insertion process, i.e., when the implant was almost fully seated (maximum insertion torque p = 0.0001, maximum strain development p < 0.00001). The final insertion torque (p < 0.00001) and final strain development (p = 0.0137) were significantly lower in the novel implant design while the primary stability of both implant types did not differ significantly (p = 0.219). The novel implant design allowed for a greater undersizing of osteotomies while not mechanically overstressing buccal bone. Comparable primary stability was obtained from trabecular bone instead of compressing cortical bone as occurs in conventional, existing tapered implant designs. Full article
(This article belongs to the Section Applied Dentistry and Oral Sciences)
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14 pages, 4052 KiB  
Article
Comparison of Measurement Possibilities by Non-Invasive Reflectometric Sensors and Invasive Probes
by Magdalena Paśnikowska-Łukaszuk, Magda Wlazło-Ćwiklińska, Jarosław Zubrzycki and Zbigniew Suchorab
Appl. Sci. 2023, 13(1), 665; https://doi.org/10.3390/app13010665 - 3 Jan 2023
Cited by 3 | Viewed by 1454
Abstract
The measurement of the moisture content of building materials is of key importance both in the process of building structures and in their subsequent operation. In engineering practice, indirect techniques of moisture measurement, mainly, resistance and capacitive, are the most popular. The main [...] Read more.
The measurement of the moisture content of building materials is of key importance both in the process of building structures and in their subsequent operation. In engineering practice, indirect techniques of moisture measurement, mainly, resistance and capacitive, are the most popular. The main objective of this research work was to compare the classic TDR measurement technique to the non-invasive, surface TDR sensors. Moisture measurements were carried out on samples made of cellular concrete with density class of 400 and 600. These samples were moist to various degrees, from 0 to 69% (400 c.c.) and from 0 to 55 (600 c.c.). For each sample, five measurements were carried out. Both the RMSE and the expanded uncertainty values were more favorable for the TDR FP/mts probe and were consistent with the literature data. Compared to them, the measurement result for the 400 c.c. samples with the S1 probe was 154.6%, and that with the S2 probe was 87.03% of the values obtained with the invasive probe. When measuring the 600 c.c. samples, we found values of 122.16% for S1 and of 120.1% for S2 of those obtained with the invasive probe. The use of surface TDR sensors provided an easy and quick measurement without damaging the surface and structure of the tested material, as there was no need to introduce the probe actuators inside the tested material. Full article
(This article belongs to the Topic Advances in Non-Destructive Testing Methods)
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13 pages, 6379 KiB  
Article
Pavement Structure Characteristics and Behaviour Analysis with Digital Image Correlation
by Ivana Barišić, Tihomir Dokšanović and Matija Zvonarić
Appl. Sci. 2023, 13(1), 664; https://doi.org/10.3390/app13010664 - 3 Jan 2023
Cited by 4 | Viewed by 1460
Abstract
Digital image correlation (DIC) is a method of point displacement measurement by an optical system. If two cameras are used for capturing the same point displacement, three-dimensional data are obtained using the 3D-DIC method. The areas of application of this method in pavement [...] Read more.
Digital image correlation (DIC) is a method of point displacement measurement by an optical system. If two cameras are used for capturing the same point displacement, three-dimensional data are obtained using the 3D-DIC method. The areas of application of this method in pavement construction are diverse, but it is mainly used for displacement monitoring during standard tests of the failure of specimens due to load application. Furthermore, DIC technology was used only for testing particular material characteristics and assuming their influence on the overall pavement system. Within this research, DIC was applied in two areas: defining material mechanical characteristics and analyses of pavement structure behaviour under cyclic loading. The scope of this research was to gain more insights into DIC’s potential application within pavement behaviour analyses, specifically on cement-bound granular material (CBGM) characterisation. Results from this study confirm the suitability of 3D-DIC technology for pavement material characterisation. Furthermore, it is shown that certain trends of material behaviour defined on the simple material level of each independent pavement layer will significantly differ when it is placed in the system, and this kind of complex analysis is possible by using 3D-DIC technology. Full article
(This article belongs to the Special Issue New Trends in Sustainable Geotechnics—Volume II)
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14 pages, 19559 KiB  
Review
Evaluation of the Efficacy of Probiotics Domiciliary Protocols for the Management of Periodontal Disease, in Adjunction of Non-Surgical Periodontal Therapy (NSPT): A Systematic Literature Review
by Andrea Butera, Elisa Folini, Saverio Cosola, Gianluca Russo, Andrea Scribante, Simone Gallo, Giulia Stablum, Giovanni Battista Menchini Fabris, Ugo Covani and Annamaria Genovesi
Appl. Sci. 2023, 13(1), 663; https://doi.org/10.3390/app13010663 - 3 Jan 2023
Cited by 9 | Viewed by 2250
Abstract
Introduction: Periodontitis is a multifactorial chronic inflammatory disease induced by a dysbiosis between the host and oral microbiota, which can compromise the host’s immune defenses and lead to the destruction of periodontal tissues. Despite the efficacy of non-surgical periodontal therapy (NSPT) as the [...] Read more.
Introduction: Periodontitis is a multifactorial chronic inflammatory disease induced by a dysbiosis between the host and oral microbiota, which can compromise the host’s immune defenses and lead to the destruction of periodontal tissues. Despite the efficacy of non-surgical periodontal therapy (NSPT) as the gold standard of periodontal treatment, its application can produce lower results due to anatomical and microbiological limitations. This systematic literature review was performed to assess the long-term efficacy of the effects of probiotics as an adjunct to NSPT compared to the control groups with follow-up of clinical, microbiological and immunological outcomes. Materials and methods: A literature review was conducted, considering manuscripts published from November 2016 to February 2022. The research question was formulated following the population, intervention, comparison and outcome strategies. Randomized controlled trials (RCT), systematic review and meta-analysis investigating the periodontal efficacy of domiciliary probiotic therapy in an adjunct to the mechanical therapy were included. Results: Regarding clinical outcomes, there is a reduction in periodontal probing depth (PPD), clinical attachments level (CAL), bleeding on probing (BoP) and plaque index (PI) for the test groups compared to the control groups in a short-term period. No differences were generally observed in the following indices over a period of more than 3 months for most studies considered. Conclusions: Weak evidence suggests that the use of probiotics as an adjunct to non-surgical periodontal therapy treatment may be able to show improvements in periodontal clinical parameters for up to 3 months. However, a significant and large heterogeneity of studies, along with the absence of long-term microbiological and immunological data, preclude any definitive conclusions. Full article
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9 pages, 2148 KiB  
Article
DFA-UNet: Efficient Railroad Image Segmentation
by Yan Zhang, Kefeng Li, Guangyuan Zhang, Zhenfang Zhu and Peng Wang
Appl. Sci. 2023, 13(1), 662; https://doi.org/10.3390/app13010662 - 3 Jan 2023
Cited by 8 | Viewed by 3470
Abstract
In computer vision technology, image segmentation is a significant technological advancement for the current problems of high-speed railroad image scene changes, low segmentation accuracy, and serious information loss. We propose a segmentation algorithm, DFA-UNet, based on an improved U-Net network architecture. The model [...] Read more.
In computer vision technology, image segmentation is a significant technological advancement for the current problems of high-speed railroad image scene changes, low segmentation accuracy, and serious information loss. We propose a segmentation algorithm, DFA-UNet, based on an improved U-Net network architecture. The model uses the same encoder–decoder structure as U-Net. To be able to extract image features efficiently and further integrate the weights of each channel feature, we propose to embed the DFA attention module in the encoder part of the model for the adaptive adjustment of feature map weights. We evaluated the performance of the model on the RailSem19 dataset. The results showed that our model showed improvements of 2.48%, 0.22%, 3.31%, 0.97%, and 2.2% in mIoU, F1-score, Accuracy, Precision, and Recall, respectively, compared with U-Net. The model can effectively achieve the segmentation of railroad images. Full article
(This article belongs to the Special Issue Applications of Video, Digital Image Processing and Deep Learning)
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12 pages, 23752 KiB  
Brief Report
Long-Term Clinical and Radiographic Analysis of Platform Matching and Platform Switching Implants in the Esthetic Zone: A Retrospective Cohort Study
by Andrea Raco, Bianca Di Murro, Pier Carmine Passarelli, Antonio D’Addona, Andrea Pilloni, Lorenzo Marini and Piero Papi
Appl. Sci. 2023, 13(1), 661; https://doi.org/10.3390/app13010661 - 3 Jan 2023
Cited by 1 | Viewed by 3311
Abstract
Background: The aims of this study are to retrospectively compare the clinical, radiographic and esthetic outcomes of platform switching (PS) and platform matching (PM) dental implants in the anterior maxilla after ≥ 10 years of functional loading. Methods: Marginal bone loss (MBL) levels [...] Read more.
Background: The aims of this study are to retrospectively compare the clinical, radiographic and esthetic outcomes of platform switching (PS) and platform matching (PM) dental implants in the anterior maxilla after ≥ 10 years of functional loading. Methods: Marginal bone loss (MBL) levels were recorded; furthermore, peri-implant clinical parameters (PPD, BOP, PI) were collected and the Pink and White Esthetic scores (PES/WES) were used to evaluate the esthetic outcomes. Wilcoxon signed rank tests were performed to compare collected parameters among the two groups, with a p-value < 0.05. Results: A final sample of 58 patients was enrolled in this study (PM implants = 29; PS implants = 29). PS implants showed lower MBL levels (1.02 ± 0.81 mm vs. 1.67 ± 0.99 mm, p = 0.028) and PPD values (3.69 ± 1.1 vs. 5.16 ± 1.09 mm, p < 0.001) compared to PM implants. Mean PES values were higher in the PS group compared to the PM group (8.46 ± 0.69 vs. 7.89 ± 0.78, p < 0.005), while there were no differences for WES values (7.82 ± 1.09 vs. 7.71 ± 0.85, p > 0.05) and peri-implant diseases’ prevalence (p > 0.05). Conclusions: After 10 years, PS implants showed statistically significant lower MBL and PPD values and higher PES values compared to PM implants. Full article
(This article belongs to the Special Issue Novel Biomaterial and Implant in Dentistry)
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6 pages, 3020 KiB  
Communication
Broadband DOA Estimation by Exploiting DFT Extrapolation
by Euiho Shin, Young-seek Chung, Seonkyo Kim, Cheolsun Park and Jungsuek Oh
Appl. Sci. 2023, 13(1), 660; https://doi.org/10.3390/app13010660 - 3 Jan 2023
Viewed by 1370
Abstract
This study proposes broadband direction (DOA) estimation through discrete Fourier transform (DFT) extrapolation. We used DFT extrapolation in the lower band and extended the sampled data to reduce the beam width in the spectral domain and improved the accuracy of the estimated DOA. [...] Read more.
This study proposes broadband direction (DOA) estimation through discrete Fourier transform (DFT) extrapolation. We used DFT extrapolation in the lower band and extended the sampled data to reduce the beam width in the spectral domain and improved the accuracy of the estimated DOA. The sampled data with a length of 12 were extrapolated to 36 by the addition of 12-element virtual arrays to 12 real arrays on both sides. The average RMSEs of the estimated DOAs were measured throughout the wide frequency band. To verify the validity of the proposed algorithm, we demonstrated that the RMSE obtained from the broadband DOA estimation for multiple signals of interest (SOIs) was reduced in the extrapolated array. It was demonstrated that the proposed algorithm can broaden the frequency band at which a fixed number of array can estimate the DOA accurately. Full article
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13 pages, 1910 KiB  
Article
3D Facial Plastic Surgery Simulation: Based on the Structured Light
by Zhi Rao, Shuo Sun, Mingye Li, Xiaoqiang Ji and Jipeng Huang
Appl. Sci. 2023, 13(1), 659; https://doi.org/10.3390/app13010659 - 3 Jan 2023
Cited by 1 | Viewed by 2794
Abstract
The 3D quantitative analysis of facial morphology is of importance in plastic surgery (PS), which could help surgeons design appropriate procedures before conducting the surgery. We propose a system to simulate and guide the shaping effect analysis, which could produce a similar but [...] Read more.
The 3D quantitative analysis of facial morphology is of importance in plastic surgery (PS), which could help surgeons design appropriate procedures before conducting the surgery. We propose a system to simulate and guide the shaping effect analysis, which could produce a similar but more harmonious face simulation. To this end, first, the depth camera based on structured light coding is employed for facial 3D data acquisition, from which the point cloud data of multiple facial perspectives could be obtained. Next, the cascade regression tree algorithm is used to extract the esthetic key points of the face model and to calculate the facial features composed of the key points, such as the nose, chin, and eyes. Quantitative facial esthetic indexes are offered to doctors to simulate PS. Afterward, we exploit a face mesh metamorphosis based on finite elements. We design several morphing operators, including augmentation, cutting, and lacerating. Finally, the regional deformation is detected, and the operation effect is quantitatively evaluated by registering the 3D scanning model before and after the operation. The test of our proposed system and the simulation of PS operations find that the measurement error of facial geometric features is 0.458 mm, and the area is 0.65 mm2. The ratings of the simulation outcomes provided by panels of PS prove that the system is effective. The manipulated 3D faces are deemed more beautiful compared to the original faces respecting the beauty canons such as facial symmetry and the golden ratio. The proposed algorithm could generate realistic visual effects of PS simulation. It could thus assist the preoperative planning of facial PS. Full article
(This article belongs to the Special Issue Advanced Optoelectronic Devices and Systems)
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18 pages, 5706 KiB  
Article
Fast Real-Time Data Process Analysis Based on NoSQL for IoT Pavement Quality Management Platform
by Sung-Sam Hong, Jaekang Lee, Suwan Chung and Byungkon Kim
Appl. Sci. 2023, 13(1), 658; https://doi.org/10.3390/app13010658 - 3 Jan 2023
Cited by 3 | Viewed by 1644
Abstract
The quality of road pavements is highly impacted by environmental variables, such as temperature, humidity, and weather; and construction-related variables, such as material quality and time. In this paper, an advanced data collection and analysis system based on big data/cloud was proposed for [...] Read more.
The quality of road pavements is highly impacted by environmental variables, such as temperature, humidity, and weather; and construction-related variables, such as material quality and time. In this paper, an advanced data collection and analysis system based on big data/cloud was proposed for the use of IoT location-based smart platforms for pavement quality big data at road pavement sites. For the big data platform, a relational database management system (RDBMS) for a general alphanumeric data-based infrastructure for IoT-based systems was designed based on distributed/parallel processing to enable rapid and big data collection and analysis. The structure was established based on a NoSQL-based database to enable real-time high-speed collection and analysis, and the big data platform was developed as a data collection and visualization infrastructure. When the big data system was studied using data analysis methods, the proposed system demonstrated improvements in data collection performance and analysis speed, indicating that analysis results could be derived in real time. Specifically, the data collection processing (create) speed of the NoSQL-based system (0.405 ms) was significantly higher than that of the compared existing system (21.146 ms). Real-time processing capacity was also verified based on quality big data generated on actual road pavements, and the proposed system was proven suitable for the real-time monitoring (the data collection processing) of road pavement quality big data. Full article
(This article belongs to the Special Issue Advances in the IoT and Smart Cities)
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12 pages, 1140 KiB  
Article
Force of Intermaxillary Latex Elastics from Different Suppliers: A Comparative In Vitro Study
by Ivana Dubovská, Barbora Ličková, Iva Voborná, Wanda Urbanová and Magdalena Koťová
Appl. Sci. 2023, 13(1), 657; https://doi.org/10.3390/app13010657 - 3 Jan 2023
Viewed by 1717
Abstract
The main characteristic of orthodontic intermaxillary elastics is the generated force. Therefore, it is necessary to know the exact properties of elastics for clinical use and their force degradation over time. Methods: A total of 500 latex elastics of the type 3/16” Medium [...] Read more.
The main characteristic of orthodontic intermaxillary elastics is the generated force. Therefore, it is necessary to know the exact properties of elastics for clinical use and their force degradation over time. Methods: A total of 500 latex elastics of the type 3/16” Medium from the manufacturers Dentaurum, American Orthodontics, 3M, Ortho Organizers, and G&H Orthodontics were tested; 100 elastics from each. The force was measured with a force meter at time 0 and at 2, 8, 24, and 48 h. Elastics were stored being stretched three times on a 3D-printed board in an incubator at 37 °C and under controlled humidity. Shapiro–Wilk normality tests, ANOVA tests, and Bonferroni post hoc tests were used. Results: The mean initial force among the manufacturers ranged from 1.109 N to 1.550 N, with Dentaurum elastics being the closest to the declared force of 1.255 newton. The greatest force degradation occurred during the first two hours; the decrease in force within 24 h ranged from 20% to 33% among the manufacturers. The maximum decrease was observed for American Orthodontics elastics. The smallest decrease occurred between 2 and 8 h for 3M, and between 24 and 48 h for Ortho Organizers. Conclusion: Intermaxillary 3/16” Medium elastics measured in vitro differ in initial force and force degradation among individual manufacturers. The attending clinician must be aware of the basic parameters of the elastics when recommending them to patients, and measuring the initial force directly in the patient’s mouth with a force meter might be helpful. Full article
(This article belongs to the Special Issue Clinical Applications in Orthodontic)
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18 pages, 1346 KiB  
Article
Isolation and Characterization of Biohydrogen-Producing Bacteria for Biohydrogen Fermentation Using Oil Palm Biomass-Based Carbon Source
by Abdullah Amru Indera Luthfi, Peer Mohamed Abdul, Jamaliah Md Jahim, Nurul Sakinah Engliman, Nur Syakina Jamali, Jian Ping Tan, Shareena Fairuz Abdul Manaf, Mohd Shaiful Sajab and Nurul Adela Bukhari
Appl. Sci. 2023, 13(1), 656; https://doi.org/10.3390/app13010656 - 3 Jan 2023
Cited by 5 | Viewed by 2275
Abstract
The effectiveness of biohydrogen conversion from biomass sources is governed by the selection of ideal biohydrogen-producing bacteria to achieve high and consistent production performance. The aim of this research was to isolate and identify a biohydrogen producer in local soil samples, as well [...] Read more.
The effectiveness of biohydrogen conversion from biomass sources is governed by the selection of ideal biohydrogen-producing bacteria to achieve high and consistent production performance. The aim of this research was to isolate and identify a biohydrogen producer in local soil samples, as well as to evaluate its fermentability in biohydrogen production from oil palm empty fruit bunches (OPEFB). To this end, preliminary identification was performed using morphological, phenotype, biological, and 16s rRNA analyses. The fermentability of the isolate was further evaluated in a serum bottle and then in a 1.5 L anaerobic column bioreactor (ACBR) to investigate the potential for biohydrogen production using two OPEFB-based carbon sources: hydrolysate of ammonia fiber expansion (AFEX)-pretreated OPEFB and molasses from dilute acetic acid (DAA)-pretreated OPEFB. The isolated strain, Enterobacter sp. KBH 6958, was found to be capable of producing biohydrogen from various carbon sources via the pyruvate:ferredoxin oxidoreductase (PFOR) pathway. The cumulative conversion of AFEX OPEFB hydrolysate was 45% higher than that observed in DAA OPEFB molasses fermentation in the production of biohydrogen. The biohydrogen yield after fermenting AFEX OPEFB hydrolysate with Enterobacter sp. KBH 6958 was 1.55 mol H2/mol sugar, with a maximum productivity of 98.1 mL H2/h (4.01 mmol H2/L/h), whereas butyrate (10.6 mM), acetate (11.8 mM), and ethanol (4.56 mM) were found to be the major soluble metabolites. This study successfully demonstrated the biotechnological conversion of OPEFB into biohydrogen using a locally isolated strain, which not only solves environmental issues associated with the industry but may also offer a solution to the world’s energy insecurity. Full article
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15 pages, 5356 KiB  
Article
Seismic Data Denoising Based on Wavelet Transform and the Residual Neural Network
by Tianwei Lan, Zhaofa Zeng, Liguo Han and Jingwen Zeng
Appl. Sci. 2023, 13(1), 655; https://doi.org/10.3390/app13010655 - 3 Jan 2023
Cited by 4 | Viewed by 2158
Abstract
The neural network denoising technique has achieved impressive results by being able to automatically learn the effective signal from the data without any assumptions. However, it has been found experimentally that the performance of the method using neural networks gradually decreases with increasing [...] Read more.
The neural network denoising technique has achieved impressive results by being able to automatically learn the effective signal from the data without any assumptions. However, it has been found experimentally that the performance of the method using neural networks gradually decreases with increasing pollution levels when processing contaminated seismic data, and how to improve the performance will become the direction of further development of the method. As a traditional method widely used for tainted seismic data, the wavelet transform can effectively separate the signal from the noise. Thus, we propose a method combining wavelet transform and a residual neural network that achieves good results in suppressing random noise data. Full article
(This article belongs to the Special Issue Active Vibration and Noise Control)
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22 pages, 4317 KiB  
Article
TKIFRPM: A Novel Approach for Topmost-K Identical Frequent Regular Patterns Mining from Incremental Datasets
by Saif Ur Rehman, Muhammad Altaf Khan, Habib Un Nabi, Shaukat Ali, Noha Alnazzawi and Shafiullah Khan
Appl. Sci. 2023, 13(1), 654; https://doi.org/10.3390/app13010654 - 3 Jan 2023
Viewed by 1336
Abstract
The regular frequent pattern mining (RFPM) approaches are aimed to discover the itemsets with significant frequency and regular occurrence behavior in a dataset. However, these approaches mainly suffer from the following two issues: (1) setting the frequency threshold parameter for the discovery of [...] Read more.
The regular frequent pattern mining (RFPM) approaches are aimed to discover the itemsets with significant frequency and regular occurrence behavior in a dataset. However, these approaches mainly suffer from the following two issues: (1) setting the frequency threshold parameter for the discovery of regular frequent patterns technique is not an easy task because of its dependency on the characteristics of a dataset, and (2) RFPM approaches are designed to mine patterns from the static datasets and are not able to mine dynamic datasets. This paper aims to solve these two issues by proposing a novel top-K identical frequent regular patterns mining (TKIFRPM) approach to function on online datasets. The TKIFRPM maintains a novel synopsis data structure with item support index tables (ISI-tables) to keep summarized information about online committed transactions and dataset updates. The mining operation can discover top-K regular frequent patterns from online data stored in the ISI-tables. The TKIFRPM explores the search space in recursive depth-first order and applies a novel progressive node’s sub-tree pruning strategy to rapidly eliminate a complete infrequent sub-tree from the search space. The TKIFRPM is compared with the MTKPP approach, and it found that it outperforms its counterpart in terms of runtime and memory usage to produce designated topmost-K frequent regular pattern mining on the datasets following incremental updates. Full article
(This article belongs to the Special Issue Scientific Data Processing and Analysis)
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14 pages, 472 KiB  
Article
Development and Chemico-Physical Characterization of Ovine Milk-Based Ingredients for Infant Formulae
by Giacomo Lai, Pierluigi Caboni, Cristina Piras, Massimo Pes, Maria Sitzia, Margherita Addis, Antonio Pirisi and Paola Scano
Appl. Sci. 2023, 13(1), 653; https://doi.org/10.3390/app13010653 - 3 Jan 2023
Cited by 3 | Viewed by 1708
Abstract
The great majority of infant formula (FM) for neonate’s nutrition are produced using ingredients from cow milk. Recently, some countries, such as China and New Zealand, are turning their attention to the use of ovine milk ingredients for FM production. In this study, [...] Read more.
The great majority of infant formula (FM) for neonate’s nutrition are produced using ingredients from cow milk. Recently, some countries, such as China and New Zealand, are turning their attention to the use of ovine milk ingredients for FM production. In this study, a pilot plant process has been set up to produce infant formula ingredients from Sarda sheep milk. To meet the nutritional needs of neonates (0–6 and 6–12 months of age) two different liquid milk-derived formulations (IF1 and IF2, respectively) obtained mixing whole milk, skimmed milk, and whey milk ultrafiltration concentrate (retentate) were produced. Compositional analysis of milk, retentate, and the final IFs showed that the two formulations contain elements of nutritional interest, such as well-balanced content of high biological value proteins (casein:whey proteins ratio of 30:70 and 60:40 for IF1 and IF2, respectively), vitamin A, E and B5, cholesterol, minerals, nucleotides, free amino acids and essential fatty acids (n–6:n–3 ~1), compatible with the growth and development needs of neonates. Therefore, the obtained IF1 and IF2 can be proposed as valuable ovine dairy ingredients for FM manufacturing. Further studies will be necessary to verify the adaptability of the developed process from laboratory to industrial scale application. Full article
(This article belongs to the Special Issue Advance in Processing and Quality Control of Dairy Products)
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15 pages, 3447 KiB  
Article
Calculation and Characterization of Air Void in Mortar of the Hot Mix Asphalt (HMA) Based on CT Scanning and Image Analysis Methods
by Li-Heng Shu, Fu-Jian Ni, Ji-Wang Jiang, Zi-Li Zhao and Zhao-Yuan Guo
Appl. Sci. 2023, 13(1), 652; https://doi.org/10.3390/app13010652 - 3 Jan 2023
Cited by 3 | Viewed by 1992
Abstract
The air void content is one of the most important volumetric properties of asphalt matrixes, such as asphalt mixtures or mortars, because it can greatly affect the performance of the matrix. At the mixture level, there are standardized methods for measuring the air [...] Read more.
The air void content is one of the most important volumetric properties of asphalt matrixes, such as asphalt mixtures or mortars, because it can greatly affect the performance of the matrix. At the mixture level, there are standardized methods for measuring the air void content, which is an important design parameter of a mixture. However, at the mortar scale, no unified method has been proposed to determine the air void content corresponding to the asphalt mixture. Therefore, this research aims to, first, characterize the air void distribution within the mortar of an asphalt mixture and then develop an updated theoretical method for calculating the air void content of asphalt mortar. The internal structures of air voids from three commonly used asphalt mixtures with different gradations were captured using an industrial CT scanning technique and then morphologically characterized using the image analysis method. Three-dimensional models of the air voids were reconstructed, and the air void content calculated from the CT images was also verified by density tests. The scanning results show that the air void content and air void size fit the cumulative Weibull curve. The results show that the nominal maximum particle size (NMPS) of mortar and the mixture air void content were the main parameters that affected the mortar’s air voids. The mortar air void content had linear relationships with both the mixture air void content and the mixture asphalt aggregate ratio. The mortar air void content was more sensitive to the NMPS of the asphalt mixture compared with the air void content or asphalt aggregate ratio of the mixture. This research provides a quantitative method to calculate the air void content of asphalt mortar within a mixture, which may help in the matrix design of mortar. Full article
(This article belongs to the Special Issue Advanced Technologies in Asphalt Materials)
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21 pages, 8028 KiB  
Article
Research on Fault Activation and Its Influencing Factors on the Barrier Effect of Rock Mass Movement Induced by Mining
by Yanhui Guo, Luo Luo and Chuangye Wang
Appl. Sci. 2023, 13(1), 651; https://doi.org/10.3390/app13010651 - 3 Jan 2023
Cited by 14 | Viewed by 2260
Abstract
For the study of the driving forces behind fault activation and its influencing factors on the barrier effect of rock mass movement under the influence of mining, the discrete element numerical simulation software 3DEC was used for the analysis of the impact on [...] Read more.
For the study of the driving forces behind fault activation and its influencing factors on the barrier effect of rock mass movement under the influence of mining, the discrete element numerical simulation software 3DEC was used for the analysis of the impact on the distance to mining area from fault, the buried depth of the upper boundary of the fault, the dip angle of fault, the size of the mining area and the thickness of the fault zone respectively. The results show that the mining areas are closer to the fault as distances decrease, the burial depth of the upper boundary of the fault increases, and the size of the mining area increases, the fault is easier to activate, and fault activation has a stronger barrier impact on displacement field and stress field propagation. When the fault is cut into the goaf, the difference of rock displacement in both directions of the fault increases when the dip of the fault increases, and the fault is more susceptible to instability and activation. The barrier strength grows with the increase of the thickness of the fault fracture zone. The results of this study have important implications for the guard against and control of deep mining-related fault activation disasters. Full article
(This article belongs to the Special Issue Fracture and Failure of Jointed Rock Mass)
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18 pages, 10868 KiB  
Article
Resolution Enhancement Method of L(0,2) Ultrasonic Guided Wave Signal Based on Variational Mode Decomposition, Wavelet Transform and Improved Split Spectrum Processing
by Binghui Tang, Yuemin Wang, Ang Chen, Ruqing Gong and Yunwei Zhao
Appl. Sci. 2023, 13(1), 650; https://doi.org/10.3390/app13010650 - 3 Jan 2023
Cited by 1 | Viewed by 1336
Abstract
Pipeline systems are prone to defects due to the harsh service conditions, which may induce catastrophic failure if found not in time. Ultrasonic guided wave (UGW) testing provides a convenient option for pipeline detection, showing high-efficiency, non-contact, long-distance and large-scale capabilities. To address [...] Read more.
Pipeline systems are prone to defects due to the harsh service conditions, which may induce catastrophic failure if found not in time. Ultrasonic guided wave (UGW) testing provides a convenient option for pipeline detection, showing high-efficiency, non-contact, long-distance and large-scale capabilities. To address the problem that UGW signals suffer from poor signal resolution that is mainly related to the coherent noise caused by the dispersion, multi-mode and mode conversion, an advanced signal processing method called VWISSP, based on variational mode decomposition (VMD), wavelet transform (WT), and improved split spectrum processing (ISSP) was proposed, of which SSP was improved by replacing the Gaussian filter bank with cosine filters of constant frequency-to-bandwidth and frequency-to-filter spacing ratios. Compared with ISSP, VWISSP shows better higher accuracy and resolution processing effects to noisy multi-defect UGW signals, which is manifested through the improvement of both the signal-to-noise ratio gain and the defect-to-noise gain. Only feature signals (defects and pipe end) are retained, whereas noise signals are eliminated completely. Full article
(This article belongs to the Section Acoustics and Vibrations)
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27 pages, 5421 KiB  
Article
KCFS-YOLOv5: A High-Precision Detection Method for Object Detection in Aerial Remote Sensing Images
by Ziwei Tian, Jie Huang, Yang Yang and Weiying Nie
Appl. Sci. 2023, 13(1), 649; https://doi.org/10.3390/app13010649 - 3 Jan 2023
Cited by 14 | Viewed by 4432
Abstract
Aerial remote sensing image object detection, based on deep learning, is of great significance in geological resource exploration, urban traffic management, and military strategic information. To improve intractable problems in aerial remote sensing image, we propose a high-precision object detection method based on [...] Read more.
Aerial remote sensing image object detection, based on deep learning, is of great significance in geological resource exploration, urban traffic management, and military strategic information. To improve intractable problems in aerial remote sensing image, we propose a high-precision object detection method based on YOLOv5 for aerial remote sensing image. The object detection method is called KCFS-YOLOv5. To obtain the appropriate anchor box, we used the K-means++ algorithm to optimize the initial clustering points. To further enhance the feature extraction and fusion ability of the backbone network, we embedded the Coordinate Attention (CA) in the backbone network of YOLOv5 and introduced the Bidirectional Feature Pyramid Network (BiFPN) in the neck network of conventional YOLOv5. To improve the detection precision of tiny objects, we added a new tiny object detection head based on the conventional YOLOv5. To reduce the deviation between the predicted box and the ground truth box, we used the SIoU Loss function. Finally, we fused and adjusted the above improvement points and obtained high-precision detection method: KCFS-YOLOv5. This detection method was evaluated on three datasets (NWPU VHR-10, RSOD, and UCAS-AOD-CAR). The comparative experiment results demonstrate that our KCFS-YOLOv5 has the highest accuracy for the object detection in aerial remote sensing image. Full article
(This article belongs to the Special Issue Deep Learning in Object Detection and Tracking)
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17 pages, 4996 KiB  
Article
Settlement Analysis of Fractional-Order Generalised Kelvin Viscoelastic Foundation under Distributed Loads
by Bingcheng Huang, Aizhong Lu and Ning Zhang
Appl. Sci. 2023, 13(1), 648; https://doi.org/10.3390/app13010648 - 3 Jan 2023
Cited by 3 | Viewed by 1274
Abstract
A solution is proposed for ground surface settlement induced in fractional-generalised Kelvin semi-infinite space by distributed loads, based on the fractional differential theory. The effects of four main parameters—the differential order, the two shear moduli and the coefficient of viscosity—on the settlements are [...] Read more.
A solution is proposed for ground surface settlement induced in fractional-generalised Kelvin semi-infinite space by distributed loads, based on the fractional differential theory. The effects of four main parameters—the differential order, the two shear moduli and the coefficient of viscosity—on the settlements are analysed using a numerical example, and a parametric-sensitivity analysis is conducted. The results show that the fractional-order generalised Kelvin model is more flexible than the conventional integer-order generalised Kelvin model since it can account for the rate of the deceleration creep phase; therefore, a wider range of mechanical properties of viscoelastic materials can be described with fewer parameters, and the differential order has a higher sensitivity than the other three parameters. Finally, the model is used to identify and fit the parameters to the data of the field-bearing plate rheological tests. The fit results of the fractional-order generalised Kelvin model, unlike those of the integer-order generalised Kelvin model, are closer to the measured results and can more accurately describe the rock’s rheological behaviour at the test location. Full article
(This article belongs to the Section Civil Engineering)
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21 pages, 3073 KiB  
Article
Improving the Safety and Security of Software Systems by Mediating SAP Verification
by Maram Fahaad Almufareh and Mamoona Humayun
Appl. Sci. 2023, 13(1), 647; https://doi.org/10.3390/app13010647 - 3 Jan 2023
Cited by 3 | Viewed by 1687
Abstract
Security and performance (SAP) are two critical NFRs that affect the successful completion of software projects. Organizations need to follow the practices that are vital to SAP verification. These practices must be incorporated into the software development process to identify SAP-related defects and [...] Read more.
Security and performance (SAP) are two critical NFRs that affect the successful completion of software projects. Organizations need to follow the practices that are vital to SAP verification. These practices must be incorporated into the software development process to identify SAP-related defects and avoid failures after deployment. This can only be achieved if organizations are fully aware of SAP verification activities and appropriately include them in the software development process. However, there is a lack of awareness of the factors that influence SAP verification, which makes it difficult for businesses to improve their verification efforts and ensure that the released software meets these requirements. To fill this gap, this research study aimed to identify the mediating factors (MFs) influencing SAP verification and the actions to promote them. Ten MFs and their corresponding actions were identified after thoroughly reviewing the existing literature. The mapping of MFs and their corresponding actions were initially evaluated with the help of a pilot study. Mathematical modeling was utilized to model these MFs and examine each MF’s unique effect on software SAP verification. In addition, two case studies with a small- and a medium-sized organization were used to better understand the function these MFs play in the process of SAP verification. The research findings suggested that MFs assist software development organizations in their efforts to integrate SAP verification procedures into their standard software systems. Further investigation is required to support the understanding of these MFs when building modern software systems. Full article
(This article belongs to the Special Issue Reliability and Safety of Software Systems)
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26 pages, 7013 KiB  
Article
Topology Optimization for Minimum Compliance with Material Volume and Buckling Constraints under Design-Dependent Loads
by Yuanteng Jiang, Ke Zhan, Jie Xia and Min Zhao
Appl. Sci. 2023, 13(1), 646; https://doi.org/10.3390/app13010646 - 3 Jan 2023
Cited by 3 | Viewed by 3378
Abstract
Stability is a critical factor in structural design. Although buckling-constrained topology optimization has been investigated in previous work, the problem has not been considered under design-dependent loads. In this study, a model of buckling constraints in topology optimization problems under design-dependent loads was [...] Read more.
Stability is a critical factor in structural design. Although buckling-constrained topology optimization has been investigated in previous work, the problem has not been considered under design-dependent loads. In this study, a model of buckling constraints in topology optimization problems under design-dependent loads was proposed to solve the above problem. First, the Kreisselmeier–Steinhauser aggregation function was employed to reduce multiple constraints to a single constraint. Then, the problem was sequentially approximated using the optimality criteria method tailored to update the variables. After that, a gradient-based optimization algorithm was established based on finite element and sensitivity analyses for the topology optimization problem with design-dependent loads. Finally, four numerical examples with design-dependent loads were comparatively analyzed, with and without bucking-constrained solutions. The calculation results proved the effectiveness and reliability of the optimization algorithm. Therefore, in this study, it was suggested that the developed optimization algorithm gained improved applicability. Full article
(This article belongs to the Special Issue Structural Optimization Methods and Applications)
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