Applied Sciences

14 pages, 7199 KiB

Open AccessArticle

Internet of Things Meets Computer Vision to Make an Intelligent Pest Monitoring Network

by Bruno Cardoso, Catarina Silva, Joana Costa and Bernardete Ribeiro

Appl. Sci. 2022, 12(18), 9397; https://doi.org/10.3390/app12189397 - 19 Sep 2022

Cited by 8 | Viewed by 4688

With the increase of smart farming in the agricultural sector, farmers have better control over the entire production cycle, notably in terms of pest monitoring. In fact, pest monitoring has gained significant importance, since the excessive use of pesticides can lead to great [...] Read more.

With the increase of smart farming in the agricultural sector, farmers have better control over the entire production cycle, notably in terms of pest monitoring. In fact, pest monitoring has gained significant importance, since the excessive use of pesticides can lead to great damage to crops, substantial environmental impact, and unnecessary costs both in material and manpower. Despite the potential of new technologies, pest monitoring is still done in a traditional way, leading to excessive costs, lack of precision, and excessive use of human labour. In this paper, we present an Internet of Things (IoT) network combined with intelligent Computer Vision (CV) techniques to improve pest monitoring. First, we propose to use low-cost cameras at the edge that capture images of pest traps and send them to the cloud. Second, we use deep neural models, notably R-CNN and YOLO models, to detect the Whitefly (WF) pest in yellow sticky traps. Finally, the predicted number of WF is analysed over time and results are accessible to farmers through a mobile app that allows them to visualise the pest in each specific field. The contribution is to make pest monitoring autonomous, cheaper, data-driven, and precise. Results demonstrate that, by combining IoT, CV technology, and deep models, it is possible to enhance pest monitoring. Full article

(This article belongs to the Special Issue Advanced IoT Technologies in Agriculture)

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18 pages, 19543 KiB

Open AccessArticle

Space Node Topology Optimization Design Considering Anisotropy of Additive Manufacturing

by Xianjie Wang, Fan Zhang, Zhenjiang Weng, Xinyu Jiang, Rushuang Wang, Hao Ren and Feiyun Zheng

Appl. Sci. 2022, 12(18), 9396; https://doi.org/10.3390/app12189396 - 19 Sep 2022

Cited by 2 | Viewed by 2144

Abstract

At present, a large number of scholars have conducted related research on topology optimization for additive manufacturing (AM). However, there are few relevant research reports on the impact of different directions of additive manufacturing on the optimal design and manufacturing results. In this [...] Read more.

At present, a large number of scholars have conducted related research on topology optimization for additive manufacturing (AM). However, there are few relevant research reports on the impact of different directions of additive manufacturing on the optimal design and manufacturing results. In this paper, using the bidirectional evolutionary optimization (BESO) method, anisotropic optimization analysis was carried out on space nodes that are currently popular in the field of additive manufacturing and topology optimization. The elastic constants in different directions were used as anisotropic material properties for optimization research in this paper through tensile testing, which was carried out on 316L stainless-steel specimens fabricated using Selective Laser Melting (SLM) technology. In addition, SEM analyses were performed to explore the microscopic appearance of the material. The study found that additive manufacturing is affected by the printing direction in terms of both macroscopic mechanical properties and microscopic material structure; the deformation obtained by anisotropic optimization was about 1.1–2.3% smaller than that obtained by isotropic optimization. Full article

(This article belongs to the Special Issue Porous Materials and Structures)

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18 pages, 991 KiB

Open AccessArticle

Anonymous Identity Based Broadcast Encryption against Continual Side Channel Attacks in the State Partition Model

by Qihong Yu, Jiguo Li and Sai Ji

Appl. Sci. 2022, 12(18), 9395; https://doi.org/10.3390/app12189395 - 19 Sep 2022

Cited by 2 | Viewed by 1633

Abstract

In the past 10 years, many side-channel attacks have been discovered and exploited one after another by attackers, which have greatly damaged the security of cryptographic systems. Since no existing anonymous broadcast encryption scheme can resist the side-channel attack, the paper presents an [...] Read more.

In the past 10 years, many side-channel attacks have been discovered and exploited one after another by attackers, which have greatly damaged the security of cryptographic systems. Since no existing anonymous broadcast encryption scheme can resist the side-channel attack, the paper presents an anonymous identity-based broadcast encryption against continual side-channel attacks in the state partition model (CLR-SS-AIBBE). Based on split-state technology, the proposed scheme divides the private key into two states, and the decryption operations are correspondingly divided into two steps. Based on the three static hypotheses for a bilinear group with composite order, the proposed scheme can be proved to be fully secure by the dual system encryption technology in the standard model. The leakage ratio about the private key can reach 1/3. Full article

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14 pages, 3590 KiB

Open AccessArticle

Earthquake Risk Probability Evaluation for Najin Lhasa in Southern Tibet

by Jianlong Zhang, Ye Zhu, Yingfeng Ji, Weiling Zhu, Rui Qu, Zhuoma Gongqiu and Chaodi Xie

Appl. Sci. 2022, 12(18), 9394; https://doi.org/10.3390/app12189394 - 19 Sep 2022

Viewed by 1701

Abstract

The probabilistic seismic hazard analysis (PSHA) method is effectively used in an earthquake risk probability evaluation in seismogenic regions with active faults. In this study, by focusing on the potential seismic source area in Najin Lhasa, southern Tibet, and by incorporating the PSHA [...] Read more.

The probabilistic seismic hazard analysis (PSHA) method is effectively used in an earthquake risk probability evaluation in seismogenic regions with active faults. In this study, by focusing on the potential seismic source area in Najin Lhasa, southern Tibet, and by incorporating the PSHA method, we determined the seismic activity parameters and discussed the relationship of ground motion attenuation, the seismic hazard probability, and the horizontal bedrock ground motion acceleration peak value under different transcendence probabilities in this area. The calculation results show that the PSHA method divides the potential source area via specific tectonic scales and detailed tectonic markers, which reduces the scale of the potential source area and better reflects the uneven spatial distribution of seismic activity in the vicinity of Najin. The corrected attenuation relationship is also in line with the actual work requirements and is suitable for earthquake risk analysis. In addition, the major influences on the peak acceleration of ground motion in the study area are mainly in the potential source areas of Qushui (M7.5), Dangxiong (M8.5), and Kangma (M7.5). The peak horizontal ground motion acceleration (PGA) with a transcendence probability of 10% in 50 years is 185.9 cm/s², and that with a transcendence probability of 2% in 50 years is 265.9 cm/s². Full article

(This article belongs to the Section Earth Sciences)

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12 pages, 3535 KiB

Open AccessArticle

Design and Implementation of an Additively Manufactured Reactor Concept for the Catalytic Methanation

by Alexander Hauser, Michael Neubert, Alexander Feldner, Alexander Horn, Fabian Grimm and Jürgen Karl

Appl. Sci. 2022, 12(18), 9393; https://doi.org/10.3390/app12189393 - 19 Sep 2022

Cited by 6 | Viewed by 1695

Abstract

The methanation process is discussed as one way to chemically store renewable energy in a future energy system. An important criterion for its application is the availability of compact, low-cost reactor concepts with high conversion rates for decentralized use where the renewable energy [...] Read more.

The methanation process is discussed as one way to chemically store renewable energy in a future energy system. An important criterion for its application is the availability of compact, low-cost reactor concepts with high conversion rates for decentralized use where the renewable energy is produced. Current research focuses on the maximization of the methane yield through improved temperature control of the exothermic reaction, which attempts to avoid both kinetic and thermodynamic limitations. In this context, traditional manufacturing methods limit the design options of the reactor and thus the temperature control possibilities. The use of additive manufacturing methods removes this restriction and creates new freedom in the design process. This paper formulates the requirements for a novel methanation reactor and presents their implementation to a highly innovative reactor concept called ‘ADDmeth’. By using a conical reaction channel expanding from Ø 8 to 32 mm, three twisted, expanding heat pipes (Ø 8 mm in evaporation zone, Ø 12 mm in condenser zone) and a lattice structure for feed gas preheating and mechanical stabilization of the reactor, the design explicitly exploits the advantages of additive manufacturing. The reactor is very compact with a specific mass of 0.36 kg/kW and has a high share of functional volume of 52%. The reactor development was accompanied by tensile tests of additively manufactured samples with the used material 1.4404 (316 L), strength calculations for stability verification and feasibility studies on the printability of fine structures. Ultimate tensile strengths of up to 750 N/mm² (at room temperature) and sufficiently high safety factors of the pressure-loaded structures against yielding were determined. Finally, the paper presents the manufactured bench-scale reactor ADDmeth1 and its implementation. Full article

(This article belongs to the Special Issue Applications of 3D Printing in Different Industries)

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28 pages, 6720 KiB

Open AccessArticle

Understanding and Predicting the Usage of Shared Electric Scooter Services on University Campuses

by Seyed Mohammad Hossein Moosavi, Zhenliang Ma, Danial Jahed Armaghani, Mahdi Aghaabbasi, Mogana Darshini Ganggayah, Yuen Choon Wah and Dmitrii Vladimirovich Ulrikh

Appl. Sci. 2022, 12(18), 9392; https://doi.org/10.3390/app12189392 - 19 Sep 2022

Cited by 9 | Viewed by 4625

Abstract

Electric vehicles (EVs) have been progressing rapidly in urban transport systems given their potential in reducing emissions and energy consumptions. The Shared Free-Floating Electric Scooter (SFFES) is an emerging EV publicized to address the first-/last-mile problem in travel. It also offers alternatives for [...] Read more.

Electric vehicles (EVs) have been progressing rapidly in urban transport systems given their potential in reducing emissions and energy consumptions. The Shared Free-Floating Electric Scooter (SFFES) is an emerging EV publicized to address the first-/last-mile problem in travel. It also offers alternatives for short-distance journeys using cars or ride-hailing services. However, very few SFFES studies have been carried out in developing countries and for university populations. Currently, many universities are facing an increased number of short-distance private car travels on campus. The study is designed to explore the attitudes and perceptions of students and staff towards SFFES usage on campus and the corresponding influencing factors. Three machine learning models were used to predict SFFES usage. Eleven important factors for using SFFESs on campus were identified via the supervised and unsupervised feature selection techniques, with the top three factors being daily travel mode, road features (e.g., green spaces) and age. The random forest model showed the highest accuracy in predicting the usage frequency of SFFESs (93.5%) using the selected 11 variables. A simulation-based optimization analysis was further conducted to discover the characterization of SFFES users, barriers/benefits of using SFFESs and safety concerns. Full article

(This article belongs to the Special Issue Novel Hybrid Intelligence Techniques in Engineering)

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28 pages, 19023 KiB

Open AccessArticle

Geodetic Upper Crust Deformation Based on Primary GNSS and INSAR Data in the Strymon Basin, Northern Greece—Correlation with Active Faults

by Ilias Lazos, Ioannis Papanikolaou, Sotirios Sboras, Michael Foumelis and Christos Pikridas

Appl. Sci. 2022, 12(18), 9391; https://doi.org/10.3390/app12189391 - 19 Sep 2022

Cited by 17 | Viewed by 3117

Abstract

The Strymon basin (Northern Greece) belongs to the geodynamically active regime of the Aegean and, as expected, it hosts active faults. Nevertheless, the study area exhibits a low instrumentally and historically recorded seismicity. In order to comprehend the crustal deformation, we implemented GNSS- [...] Read more.

The Strymon basin (Northern Greece) belongs to the geodynamically active regime of the Aegean and, as expected, it hosts active faults. Nevertheless, the study area exhibits a low instrumentally and historically recorded seismicity. In order to comprehend the crustal deformation, we implemented GNSS- and InSAR-based techniques. Global Navigation Satellite System (GNSS) primary geodetic data recorded by 32 permanent stations over 7 years were analyzed and input in the triangulation methodology so as to calculate a series of deformational parameters. Moreover, a geostatistical methodology indicated the spatial distribution of each parameter, showing strain delimited up to 2750 × 10⁻⁹. These results are in broad agreement with palaeoseismological surveys and active fault mapping. Moreover, InSAR analysis, based on a 6-year data recording, concluded that no horizontal rates have been traced in the E–W direction; if they do exist, they would be below resolution (less than 2 mm/yr). Peak vertical subsidence values of a few mm/yr are traced towards the hanging wall of the Serres fault zone within the Quaternary sediments at the eastern margin of Strymon basin but are attributed mainly to groundwater extraction. However, it is noteworthy that geodetic strain analysis implies: (a) that a couple of areas need further study to trace potentially active faults by palaeoseismological means; (b) the fault trace of the Serres fault zone might be further prolonged 8–10 km eastwards, where Quaternary sediments cover the fault. Full article

(This article belongs to the Special Issue The Contribution of Geology and Geomatics to Seismic Hazard and Earthquake Engineering)

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11 pages, 4607 KiB

Open AccessArticle

Design and Synthesis of 3D-Graphene@C/Co@N-C Composites with Broadband Microwave Absorption Performance

by Songyan Li, Xiaoxia Tian, Jiafu Wang and Shaobo Qu

Appl. Sci. 2022, 12(18), 9390; https://doi.org/10.3390/app12189390 - 19 Sep 2022

Cited by 1 | Viewed by 1661

Abstract

Improving the microwave absorption performance of Co-MOF-derived Co@N-C composite by constructing the morphology and spatial structure is a known challenge. In this work, under the action of the binder polyvinylpyrrolidone, 3D-graphene particles can be well decorated on the surface of the Co@N-C composite [...] Read more.

Improving the microwave absorption performance of Co-MOF-derived Co@N-C composite by constructing the morphology and spatial structure is a known challenge. In this work, under the action of the binder polyvinylpyrrolidone, 3D-graphene particles can be well decorated on the surface of the Co@N-C composite after high-temperature pyrolysis. In addition, due to the structural characteristics of MOFs, Co particles can be well covered by a carbon layer, which effectively solves the problem that magnetic metal particles are prone to corrosion and oxidation. The microwave absorption performances of the composite can be well adjusted by changing the average dotted density of the 3D-graphene on the Co@N-C composite. It is worth noting that the maximum reflection loss can reach −58.72 dB at the thickness of 1.64 mm, and the maximum effective absorption bandwidth can achieve 5.74 GHz at the 1.79 mm thickness, which almost covers the whole Ku band. Importantly, these results demonstrate that 3D-graphene@C/Co@N-C composites have great potential as high-efficiency microwave absorption materials. Full article

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16 pages, 2491 KiB

Open AccessArticle

AdaCB: An Adaptive Gradient Method with Convergence Range Bound of Learning Rate

by Xuanzhi Liao, Shahnorbanun Sahran, Azizi Abdullah and Syaimak Abdul Shukor

Appl. Sci. 2022, 12(18), 9389; https://doi.org/10.3390/app12189389 - 19 Sep 2022

Viewed by 2294

Abstract

Adaptive gradient descent methods such as Adam, RMSprop, and AdaGrad achieve great success in training deep learning models. These methods adaptively change the learning rates, resulting in a faster convergence speed. Recent studies have shown their problems include extreme learning rates, non-convergence issues, [...] Read more.

Adaptive gradient descent methods such as Adam, RMSprop, and AdaGrad achieve great success in training deep learning models. These methods adaptively change the learning rates, resulting in a faster convergence speed. Recent studies have shown their problems include extreme learning rates, non-convergence issues, as well as poor generalization. Some enhanced variants have been proposed, such as AMSGrad, and AdaBound. However, the performances of these alternatives are controversial and some drawbacks still occur. In this work, we proposed an optimizer called AdaCB, which limits the learning rates of Adam in a convergence range bound. The bound range is determined by the LR test, and then two bound functions are designed to constrain Adam, and two bound functions tend to a constant value. To evaluate our method, we carry out experiments on the image classification task, three models including Smallnet, Network IN Network, and Resnet are trained on CIFAR10 and CIFAR100 datasets. Experimental results show that our method outperforms other optimizers on CIFAR10 and CIFAR100 datasets with accuracies of (82.76%, 53.29%), (86.24%, 60.19%), and (83.24%, 55.04%) on Smallnet, Network IN Network and Resnet, respectively. The results also indicate that our method maintains a faster learning speed, like adaptive gradient methods, in the early stage and achieves considerable accuracy, like SGD (M), at the end. Full article

(This article belongs to the Special Issue AI-Based Image Processing)

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17 pages, 3224 KiB

Open AccessArticle

Evading Logits-Based Detections to Audio Adversarial Examples by Logits-Traction Attack

by Songshen Han, Kaiyong Xu, Songhui Guo, Miao Yu and Bo Yang

Appl. Sci. 2022, 12(18), 9388; https://doi.org/10.3390/app12189388 - 19 Sep 2022

Cited by 2 | Viewed by 1578

Abstract

Automatic Speech Recognition (ASR) provides a new way of human-computer interaction. However, it is vulnerable to adversarial examples, which are obtained by deliberately adding perturbations to the original audios. Thorough studies on the universal feature of adversarial examples are essential to prevent potential [...] Read more.

Automatic Speech Recognition (ASR) provides a new way of human-computer interaction. However, it is vulnerable to adversarial examples, which are obtained by deliberately adding perturbations to the original audios. Thorough studies on the universal feature of adversarial examples are essential to prevent potential attacks. Previous research has shown classic adversarial examples have different logits distribution compared to normal speech. This paper proposes a logit-traction attack to eliminate this difference at the statistical level. Experiments on the LibriSpeech dataset show that the proposed attack reduces the accuracy of the LOGITS NOISE detection to 52.1%. To further verify the effectiveness of this approach in attacking detection based on logits, three different features quantifying the dispersion of logits are constructed in this paper. Furthermore, a richer target sentence is adopted for experiments. The results indicate that these features can detect baseline adversarial examples with an accuracy of about 90% but cannot effectively detect Logits-Traction adversarial examples, proving that Logits-Traction attack can evade the logits-based detection method. Full article

(This article belongs to the Special Issue AI, Machine Learning and Deep Learning in Signal Processing)

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18 pages, 5583 KiB

Open AccessArticle

Study on Spray Characteristics and Breakup Mechanism of an SCR Injector

by Chuanxin Bai, Kai Liu, Tong Zhao and Jinjin Liu

Appl. Sci. 2022, 12(18), 9387; https://doi.org/10.3390/app12189387 - 19 Sep 2022

Cited by 5 | Viewed by 1860

Abstract

Selective catalytic reduction (SCR) is currently one of the most efficient denitration technologies to reduce nitrogen oxide (NO_x) emissions of diesel engines. AdBlue (urea water solution, UWS) is the carrier of the reducing agent of SCR, and the spray process of [...] Read more.

Selective catalytic reduction (SCR) is currently one of the most efficient denitration technologies to reduce nitrogen oxide (NO_x) emissions of diesel engines. AdBlue (urea water solution, UWS) is the carrier of the reducing agent of SCR, and the spray process of UWS is one of the critical factors affecting denitration efficiency. In this paper, a non-air-assisted pressure-driven full process spray (NPFPS) model is proposed to illustrate the breakup mechanism and the spray distribution properties of UWS through computational fluid dynamics (CFD). In the NPFPS model, the mechanism of the primary breakup is described by the volume of fluid (VOF) approach, which realizes the quantitative study of the critical parameters determining spray characteristics such as the breakup length, inclination angle, droplet size of the primary breakup, and primary velocity. The distribution of the spray after the primary breakup is depicted by the discrete phase model (DPM) coupled with the Taylor analogy breakup (TAB) model, through which the degree of secondary breakup can be obtained including quantitative studies of the droplet size distribution and velocity distribution in the different cross-sections. To verify the accuracy and feasibility of the NPFPS model, the experimental data are employed to compare with the simulation data. The results are in good agreement, which indicate the practical value of the model. Full article

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20 pages, 11008 KiB

Open AccessArticle

Investigating the Energy-Efficient Structures Using Building Energy Performance Simulations: A Case Study

by Safeer Abbas, Omer Saleem, Mujasim Ali Rizvi, Syed Minhaj Saleem Kazmi, Muhammad Junaid Munir and Shahid Ali

Appl. Sci. 2022, 12(18), 9386; https://doi.org/10.3390/app12189386 - 19 Sep 2022

Cited by 6 | Viewed by 3134

Abstract

The use of energy efficient structures in the local construction industry assists in promoting green building concepts, leading to economical and eco-friendly solutions for self-sustained structures. The main aim of this study was to examine and compare the energy performance of various local [...] Read more.

The use of energy efficient structures in the local construction industry assists in promoting green building concepts, leading to economical and eco-friendly solutions for self-sustained structures. The main aim of this study was to examine and compare the energy performance of various local buildings. Detailed 3D building models (house, office, and warehouse buildings) were constructed and investigated for their cost and energy savings using building energy simulation tools (green building studio and insight). Moreover, the effects of various building materials for walls, window panels, and roof construction were explored, and a life-cycle cost analysis was performed. It was observed that the effect of the window-to-wall ratio was less severe in term of energy use in office buildings compared to normal houses due to the larger amount of space available for air circulation. Furthermore, the most efficient location for windows was found to be at the middle of the wall in comparison with the top and bottom positions. The effect of the orientation mainly depended on the symmetry of the building. More symmetric buildings, i.e., tested warehouse buildings (rectangular structure), showed an energy use difference of around 7 MJ/m²/year for a 360° orientation change. Tested house buildings exhibited an energy use difference of up to 25 MJ/m²/year. Three-pane glass windows also showed major improvements, and the total energy consumption for houses was reduced to 14%. Furthermore, wood walls showed comparable energy performance with brick walls without the use of insulation. According to US-LEED guidelines, the tested house, office, and warehouse buildings achieved 79, 89, and 88 points, respectively. The cost recovery period for house, office, and warehouse buildings was estimated to 54, 13, and 14 years, respectively, including running and maintenance costs. It can be argued that the Insight and Green Building Studio packages can assist construction stakeholders to determine the energy efficiency of the modeled building as well as to help in the selection of materials for optimized and improved design. Full article

(This article belongs to the Section Civil Engineering)

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13 pages, 2236 KiB

Open AccessArticle

Three-Dimensional Change of Lip after Two-Jaw Surgery in Facial Asymmetry Using Facial Scanner

by Young-Jae Kim, Sung-Hwan Choi, Yoon Jeong Choi, Kee-Joon Lee, Sang-Hwy Lee and Hyung-Seog Yu

Appl. Sci. 2022, 12(18), 9385; https://doi.org/10.3390/app12189385 - 19 Sep 2022

Viewed by 2372

Abstract

A facial scanner and three-dimensional computed tomography (CT) were used to evaluate the three-dimensional change in lip asymmetry before and after two-jaw surgery for 22 patients with facial asymmetry (menton deviation > 3 mm). We used the labrale superius (Ls), deviated/non-deviated-side cheilions (Ch-D/Ch-ND), [...] Read more.

A facial scanner and three-dimensional computed tomography (CT) were used to evaluate the three-dimensional change in lip asymmetry before and after two-jaw surgery for 22 patients with facial asymmetry (menton deviation > 3 mm). We used the labrale superius (Ls), deviated/non-deviated-side cheilions (Ch-D/Ch-ND), and labrale inferius (Li) to construct the upper and lower lip planes to evaluate the lip asymmetry. A correlation analysis was performed to determine the factors related to the vertical change in the cheilions (ΔChZ-D/ND). In the transverse axis, Ch-D and Li moved to improve the asymmetry after surgery. All landmarks, except the Ls, moved backward in the anteroposterior axis. In the vertical axis, significant upward movement was observed in all hard tissue landmarks; however, there were no significant changes in the soft tissue. In the lip plane, the difference in the height of Ch-D and Ch-ND was significantly reduced (1.38 mm vs. 0.72 mm). In the anteroposterior axis, the ΔChZ-D/ND showed significant correlations with the mandibular setback. In the vertical axis, the ΔCh-ND showed significant correlations with the maxillary impaction of the non-deviated side. The improvement in lip asymmetry post-surgery was mainly achieved by the movement of the lower lip and Ch-D rather than the upper lip and Ch-ND. Full article

(This article belongs to the Special Issue Clinical Applications of Orthodontic TSADs (Temporary Skeletal Anchorage Devices))

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15 pages, 2054 KiB

Open AccessArticle

Applications of Metaheuristics Inspired by Nature in a Specific Optimisation Problem of a Postal Distribution Sector

by Michał Berliński, Eryk Warchulski and Stanisław Kozdrowski

Appl. Sci. 2022, 12(18), 9384; https://doi.org/10.3390/app12189384 - 19 Sep 2022

Cited by 3 | Viewed by 1504

Abstract

This paper presents a logistics problem, related to the transport of goods, which can be applied in practice, for example, in postal or courier services. Two mathematical models are presented as problems occurring in a logistics network. The main objective of the optimisation [...] Read more.

This paper presents a logistics problem, related to the transport of goods, which can be applied in practice, for example, in postal or courier services. Two mathematical models are presented as problems occurring in a logistics network. The main objective of the optimisation problem presented is to minimise capital resources (Capex), such as cars or containers. Three methods are proposed to solve this problem. The first is a method based on mixed integer programming (MIP) and available through the CPLEX solver. This method is the reference method for us because, as an exact method, it is guaranteed to find the optimal solution as long as the problem is not too large. However, the logistic problem under consideration belongs to the class of NP-complete problems and therefore, for larger problems, i.e., for networks of large size, the MIP method does not find any integer solution in a reasonable computational time. Therefore, two nature-inspired heuristic methods have been proposed. The first is the evolutionary algorithm and the second is the artificial bee colony algorithm. Results indicate that the heuristics methods solve instances of large size, giving suboptimal solutions and therefore, enabling their application to real-life scenarios. Full article

(This article belongs to the Special Issue Metaheuristics for Real-World Optimization Problems)

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15 pages, 2859 KiB

Open AccessArticle

A Partial Multiplicative Dimensional Reduction-Based Reliability Estimation Method for Probabilistic and Non-Probabilistic Hybrid Structural Systems

by Xuyong Chen, Yuanlin Peng, Zhifeng Xu and Qiaoyun Wu

Appl. Sci. 2022, 12(18), 9383; https://doi.org/10.3390/app12189383 - 19 Sep 2022

Viewed by 1568

Abstract

A new reliability estimation method based on partial multiplicative dimensional reduction is proposed for probabilistic and non-probabilistic hybrid structural systems. The proposed method is characterized by decorrelating interval input variables from random input variables using the partial multiplicative dimensional reduction method in conjunction [...] Read more.

A new reliability estimation method based on partial multiplicative dimensional reduction is proposed for probabilistic and non-probabilistic hybrid structural systems. The proposed method is characterized by decorrelating interval input variables from random input variables using the partial multiplicative dimensional reduction method in conjunction with the weakest-link theory. In this method, the failure statistics of the original performance function are equivalent to a statical chain of two elements, in which one of the two elements represents the failures due to random input variables and the other represents the failures due to interval variables. Rather than yielding an estimated interval of failure probability, the proposed method produces a single value for failure probability, which is more meaningful for engineering. In addition, the accuracy, validity, and superiority of the proposed method are demonstrated, and the error-related properties of the proposed method are investigated. Full article

(This article belongs to the Special Issue Soft Computing Application to Engineering Design)

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19 pages, 6236 KiB

Open AccessArticle

Influence of FK209 Cobalt Doped Electron Transport Layer in Cesium Based Perovskite Solar Cells

by Ahmed Hayali, Roger J. Reeves and Maan M. Alkaisi

Appl. Sci. 2022, 12(18), 9382; https://doi.org/10.3390/app12189382 - 19 Sep 2022

Viewed by 1992

Abstract

The efficiency and stability of perovskite solar cells (PSCs) depend not only on the perovskite film quality, but they are also influenced by the charge carriers of both the electron and hole transport layers (ETL and HTL). Doping of the carrier transport layers [...] Read more.

The efficiency and stability of perovskite solar cells (PSCs) depend not only on the perovskite film quality, but they are also influenced by the charge carriers of both the electron and hole transport layers (ETL and HTL). Doping of the carrier transport layers is considered one of effective technique applied to enhance the efficiency and performance of the PSCs. FK209 cobalt TFSI and lithium TFSI salt were investigated as dopants for mesoporous TiO₂ (M-TiO₂) in the ETL. Herein, FK209 cobalt doping offers improved conductivity, reproducibility and stability compared to other doping or undoped M-TiO₂ control device. It has been found that an optimum concentration of 2.5 mg FK209 cobalt in the M-TiO₂ has resulted in an efficiency of 15.6% on 0.36 cm² active device area, whereas, the undoped M-TiO₂ yielded an average efficiency of 10.8%. The enhanced efficiency is due to the improved conductivity of the ETL while maintaining high transparency and low surface roughness with FK209 doping. The M-TiO₂ doped with FK209 has a transparency of the 90% over the visible range and its measured energy gap was 3.59 eV. Perovskite films deposited on the M-TiO₂ doped with FK209 has also a lower PL intensity indicating faster charge extraction. The measured lifetime of the perovskite films deposited on the optimised M-TiO₂ film was 115.8 ns. Full article

(This article belongs to the Special Issue Selected Papers from ICAET 2022)

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27 pages, 9180 KiB

Open AccessArticle

Design and Implementation of Cloud-Based Collaborative Manufacturing Execution System in the Korean Fashion Industry

by Minjae Ko, Changho Lee and Yongju Cho

Appl. Sci. 2022, 12(18), 9381; https://doi.org/10.3390/app12189381 - 19 Sep 2022

Cited by 6 | Viewed by 4202

Abstract

Recently, manufacturing companies have been improving quality and productivity, reducing costs, and producing customized products according to Industry 4.0. The global value chain (GVC) is also being reorganized and manufacturing companies are recovering the connectivity of value chains based on, e.g., the regional [...] Read more.

Recently, manufacturing companies have been improving quality and productivity, reducing costs, and producing customized products according to Industry 4.0. The global value chain (GVC) is also being reorganized and manufacturing companies are recovering the connectivity of value chains based on, e.g., the regional value chain (RVC) and reshoring. With the advent of Industry 4.0, many manufacturing companies are introducing smart factories. A new type of manufacturing execution system (MES), a core system of smart factories, is necessary, owing to the new technologies and the increase in collaboration between companies. Here, we present the framework, development, and application processes of a “cloud-based collaborative MES System” to support the value chain of “order-design-production-delivery” for the manufacture of personalized sportswear products in the fashion industry in Korea. To this end, first, nine future MES deployment directions and frameworks are presented. Second, we present the UML modeling, conceptual framework, and functional framework for MES system development, considering six future MES establishment directions such as cloud and collaboration. Third, the application and effect of the designed and developed cloud-based collaborative MES system are analyzed for design, fabric, printing, and sewing companies that play a role in each stage of the sportswear value chain. Full article

(This article belongs to the Special Issue Smart Manufacturing Systems in Industry 4.0)

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3 pages, 185 KiB

Open AccessEditorial

Special Issue on Development and Application of Particle Detectors

by Andrea Giachero and Luca Gironi

Appl. Sci. 2022, 12(18), 9380; https://doi.org/10.3390/app12189380 - 19 Sep 2022

Cited by 1 | Viewed by 1261

Abstract

Particle detection has been increasingly applied over a wide range of disciplines, including high-energy physics, astroparticles, space science and astronomy, biological sciences, medical imaging, remote sensing, environmental monitoring, cultural heritage, and homeland security [...] Full article

(This article belongs to the Special Issue Development and Application of Particle Detectors)

16 pages, 6346 KiB

Open AccessArticle

Design and Kinematic Analysis of Cable-Driven Target Spray Robot for Citrus Orchards

by Xiulan Bao, Yuxin Niu, Yishu Li, Jincheng Mao, Shanjun Li, Xiaojie Ma, Qilin Yin and Biyu Chen

Appl. Sci. 2022, 12(18), 9379; https://doi.org/10.3390/app12189379 - 19 Sep 2022

Cited by 6 | Viewed by 2023

Abstract

In Southeast Asia, many varieties of citrus are grown in hilly areas. Compared with plain orchards, it is difficult for large spraying equipment to move in hilly orchards. Small spraying equipment can enter hilly orchards, but their spraying power cannot make droplets penetrate [...] Read more.

In Southeast Asia, many varieties of citrus are grown in hilly areas. Compared with plain orchards, it is difficult for large spraying equipment to move in hilly orchards. Small spraying equipment can enter hilly orchards, but their spraying power cannot make droplets penetrate into the canopy, resulting in low deposition rates within the canopy. As a kind of unstructured narrow space, the branches within the canopy are interlaced, thus a flexible manipulator that can move within the canopy is required. In this paper, a novel remote-controlled, cable-driven target spray robot (CDTSR) was designed to achieve a precise spray within the canopy. It consisted of a small tracked vehicle, a cable-driven flexible manipulator (CDFM), and a spray system. The CDFM had six degrees of freedom driven by a cable tendon. The forward and inverse kinematics model of the CDFM were established and then the semispherical workspace was calculated. Furthermore, while considering precise control requirements, the dynamics equations were derived. The experimental results demonstrated that the CFDM could move dexterously within the canopy with interlacing branches to reach pests and diseases areas in the canopy. The entire operation took 3.5 s. This study solved the problem of a low spray deposition rate within a canopy and has potential applications in agricultural plant protection. Full article

(This article belongs to the Special Issue Advances in Robotics and Mechatronics for Agriculture)

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17 pages, 12061 KiB

Open AccessArticle

Applying Evolutionary Multitasking for Process Parameter Optimization in Polymerization Process of Carbon Fiber Production

by Liang Jin, Zude Zhou, Kunlun Li, Guoliang Zhang, Quan Liu, Bitao Yao and Yilin Fang

Appl. Sci. 2022, 12(18), 9378; https://doi.org/10.3390/app12189378 - 19 Sep 2022

Cited by 4 | Viewed by 1859

Abstract

Carbon fiber is becoming a key material for engineering applications due to its excellent comprehensive properties. The process parameter optimization is an important step in the polymerization process of carbon fiber production. At present, most of the research on process parameter optimization is [...] Read more.

Carbon fiber is becoming a key material for engineering applications due to its excellent comprehensive properties. The process parameter optimization is an important step in the polymerization process of carbon fiber production. At present, most of the research on process parameter optimization is usually carried out on a single production line, without considering the correlation between optimization problems. In this paper, a multiobjective mechanism model for the co-optimization of the polymerization process of carbon fiber production is established. Each of these submodels is a multiobjective process parameter optimization task, corresponding to the polymerization process of a production line. In order to solve the model effectively, we also designed an evolutionary multitasking algorithm based on transfer learning, which reuses the past experiences of one task to generate a population pool for the next iteration of another task, enabling explicit genetic transfer between different tasks and accelerating the population convergence speed. The proposed multitasking framework for operation optimization has been conducted on 10 different production conditions of the polymerization process. Experimental results show that compared with other implicit and explicit genetic algorithms, this algorithm is very competitive in generating effective solutions. This research provides important support for process parameter optimization and manufacturing of carbon fiber production, which will help engineers and technicians to make informed decisions. Full article

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18 pages, 4288 KiB

Open AccessArticle

Improving IoT Data Security and Integrity Using Lightweight Blockchain Dynamic Table

by Saleem S. Hameedi and Oguz Bayat

Appl. Sci. 2022, 12(18), 9377; https://doi.org/10.3390/app12189377 - 19 Sep 2022

Cited by 10 | Viewed by 2922

Abstract

Over the past few years, the Internet of Things (IoT) is one of the most significant technologies ever used, as everything is connected to the Internet. Integrating IoT technologies with the cloud improves the performance, activity, and innovation of such a system. However, [...] Read more.

Over the past few years, the Internet of Things (IoT) is one of the most significant technologies ever used, as everything is connected to the Internet. Integrating IoT technologies with the cloud improves the performance, activity, and innovation of such a system. However, one of the major problems which cannot be ignored in such integration is the security of the data that are transferred between the client (IoT) and the server (cloud). Solving that problem leads to the use the of IoT technologies in more critical applications and fields. This paper proposes a new security framework by combining blockchain technology with the AES algorithm. Blockchain technology is used and modified to protect data integrity and generate unique device identification within minimal power consumption and best performance. The AES algorithm is used to improve the data confidentiality when being transmitted to the server. The outcomes demonstrated that the proposed solution improves the security system of the IoT healthcare data and proved its efficiency and power consumption compared to other methods. Full article

(This article belongs to the Special Issue Advances in Blockchain-enabled Internet of Things (IoT))

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18 pages, 470 KiB

Open AccessArticle

Target-Oriented Teaching Path Planning with Deep Reinforcement Learning for Cloud Computing-Assisted Instructions

by Tengjie Yang, Lin Zuo, Xinduoji Yang and Nianbo Liu

Appl. Sci. 2022, 12(18), 9376; https://doi.org/10.3390/app12189376 - 19 Sep 2022

Cited by 1 | Viewed by 1954

Abstract

In recent years, individual learning path planning has become prevalent in online learning systems, while few studies have focused on teaching path planning for traditional classroom teaching. This paper proposes a target-oriented teaching path optimization scheme for cloud computing-assisted instructions, in which a [...] Read more.

In recent years, individual learning path planning has become prevalent in online learning systems, while few studies have focused on teaching path planning for traditional classroom teaching. This paper proposes a target-oriented teaching path optimization scheme for cloud computing-assisted instructions, in which a sequence of learning contents is arranged to ensure the maximum benefit for a given group of students. First, to evaluate the teaching performance, we investigate various student models and define some teaching objectives, including the pass rate, the excellence rate, the average score, and related constraints. Second, a new Deep Reinforcement Learning (DRL)-based teaching path planning method is proposed to tackle the learning path by maximizing a multi-objective target while satisfying all teaching constraints. It adopts a Proximal Policy Optimization (PPO) framework to find a model-free solution for achieving fast convergence and better optimality. Finally, extensive simulations with a variety of commonly used teaching methods show that our scheme provides nice performance and versatility over commonly used student models. Full article

(This article belongs to the Special Issue New Engineering in Cloud Computing and Cloud Data)

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17 pages, 1977 KiB

Open AccessArticle

Particulate Matter Concentrations and Fungal Aerosol in Horse Stables as Potential Causal Agents in Recurrent Airway Disease in Horses and Human Asthma and Allergies

by Anna Lenart-Boroń, Anna Bajor, Marek Tischner, Klaudia Kulik and Julia Kabacińska

Appl. Sci. 2022, 12(18), 9375; https://doi.org/10.3390/app12189375 - 19 Sep 2022

Cited by 3 | Viewed by 1942

Abstract

Exposure to bioaerosols associated with horse stable indoor environment and their health effects on people and horses has recently become of particular interest. Moreover, increasing frequency of recurrent airway disease (RAO) among horses made it necessary to search for the most probable causal [...] Read more.

Exposure to bioaerosols associated with horse stable indoor environment and their health effects on people and horses has recently become of particular interest. Moreover, increasing frequency of recurrent airway disease (RAO) among horses made it necessary to search for the most probable causal agents of this disease and methods of their eradication. The study was conducted in two horse stables in southern Poland (Kraków and Tarnów). Particulate matter (PM_2.5, PM₄, and PM₁₀) concentrations were determined photometrically, the concentration of fungal aerosol was determined by a six-stage impactor, and next generation sequencing (NGS) was used to determine fungal community composition in one of these stables. The highest PM concentrations were observed in Tarnów, but fungal aerosol levels were higher in the Kraków stable. Based on the NGS results, the three most prevalent fungal species were Wallemia sebi, Aspergillus penicillioides, and Epicoccum nigrum, all highly allergenic and potentially involved in the occurrence of RAO in horses. Spores of the detected fungi can penetrate deeply into the respiratory system. Therefore, this study suggests that examinations of particulate matter and fungal aerosol concentrations, along with species composition assessment, should be regularly conducted in horse stables. Full article

(This article belongs to the Special Issue Fungi Associated with Indoor Environments and Materials)

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12 pages, 5402 KiB

Open AccessArticle

Novel Method for Monitoring Mining Subsidence Featuring Co-Registration of UAV LiDAR Data and Photogrammetry

by Jibo Liu, Xiaoyu Liu, Xieyu Lv, Bo Wang and Xugang Lian

Appl. Sci. 2022, 12(18), 9374; https://doi.org/10.3390/app12189374 - 19 Sep 2022

Cited by 9 | Viewed by 2401

Abstract

Addressing the problem that traditional methods cannot reliably monitor surface subsidence in coal mining, a novel method has been developed for monitoring subsidence in mining areas using time series unmanned aerial vehicle (UAV) photogrammetry in combination with LiDAR. A dynamic subsidence basin based [...] Read more.

Addressing the problem that traditional methods cannot reliably monitor surface subsidence in coal mining, a novel method has been developed for monitoring subsidence in mining areas using time series unmanned aerial vehicle (UAV) photogrammetry in combination with LiDAR. A dynamic subsidence basin based on the differential digital elevation model (DEM) was constructed and accuracy of the proposed method was verified, with the uncertainty of the DEM of difference (DoD) being quantified via co-registration of a dense matching point cloud of the time series UAV data. The root mean square error calculated for the monitoring points on the subsidence DEM was typically between 0.2 m and 0.3 m with a minimum of 0.17 m. The relative error between the maximum subsidence value of the extracted profile line on the main section after fitting and the measured maximum subsidence value was not more than 20%, and the minimum value was 0.7%. The accuracy of the UAV based method was at the decimeter level, and high accuracy in monitoring the maximum subsidence value was attained, confirming that an innovative strategy for monitoring mining subsidence was realized. Full article

(This article belongs to the Special Issue Advances, Challenges and Applications in Unmanned Aerial Vehicle Remote Sensing Techniques)

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24 pages, 7443 KiB

Open AccessArticle

Proposed New Analytical Method of Tower Load in Large-Span Arch Bridge Cable Lifting Construction

by Qian Huang, Xiaoguang Wu, Yunfei Zhang and Min Ma

Appl. Sci. 2022, 12(18), 9373; https://doi.org/10.3390/app12189373 - 19 Sep 2022

Cited by 8 | Viewed by 2459

Abstract

The cable lifting construction method is the most widely used construction method for large-span arch bridges. The correct calculation and analysis of cable lifting construction is essential to ensure the safety and linearity in the construction of arch bridges. The existing research mainly [...] Read more.

The cable lifting construction method is the most widely used construction method for large-span arch bridges. The correct calculation and analysis of cable lifting construction is essential to ensure the safety and linearity in the construction of arch bridges. The existing research mainly focuses on the construction scheme and finite element analysis of cable lifting for large-span arch bridges. There is relatively little research on calculation theory, and there is no analytical method for cable lifting construction of arch bridges. To calculate and analyze cable lifting construction more quickly and accurately, based on the deformation coordination principle and suspension cable theory, a practical calculation method is proposed to calculate the load of the tower acting by a cable system in the cable lifting construction of arch bridges. A large-span arch bridge under construction was used as a case study, and the correctness of the calculation method was verified by measuring the displacements of the tower top. A brief description of the structure, verification method, and verification process is presented. The displacement results are calculated by the numerical calculation software SAP2000, the actual measured displacement data are discussed and comparatively analyzed, and the correctness and calculation accuracy of the proposed calculation method are also evaluated. The results show that the calculation method has sufficient accuracy. The tower load calculation is mainly undertaken to prepare for the analysis of the tower mechanical properties; therefore, the calculation method is applied to towers of the case engineering, and the stability, load carrying capacity, and deformation of the tower are analyzed to verify whether its mechanical properties meet the engineering requirements. The results show that steel pipe columns of the buckle tower are prone to twisting instability. The normal stress of the tower’s part of the pressurized rod or pressurized bending rod is larger. Wind cable load calculation models and tower design-related recommendations are presented in this tower analysis. The tower load calculation method and tower mechanics analysis method in this study can provide guidance for the calculation and analysis of the cable lifting construction of large-span arch bridges. Full article

(This article belongs to the Special Issue Advanced Technologies for Bridge Design and Construction)

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18 pages, 1741 KiB

Open AccessArticle

Comparison of Methods to Identify and Monitor Mold Damages in Buildings

by Pedro Maria Martin-Sanchez, Maria Nunez, Eva Lena Fjeld Estensmo, Inger Skrede and Håvard Kauserud

Appl. Sci. 2022, 12(18), 9372; https://doi.org/10.3390/app12189372 - 19 Sep 2022

Cited by 4 | Viewed by 4786

Abstract

Molds thrive in indoor environments, challenging the stability of building materials and occupants’ health. Diverse sampling and analytical techniques can be applied in the microbiology of buildings, with specific benefits and drawbacks. We evaluated the use of two methods, the microscopy of visible [...] Read more.

Molds thrive in indoor environments, challenging the stability of building materials and occupants’ health. Diverse sampling and analytical techniques can be applied in the microbiology of buildings, with specific benefits and drawbacks. We evaluated the use of two methods, the microscopy of visible mold growth (hereinafter “mold” samples) (tape lifts) and the DNA metabarcoding of mold and dust samples (swabs), for mapping mold-damage indicator fungi in residential buildings in Oslo. Overall, both methods provided consistent results for the mold samples, where nearly 80% of the microscopy-identified taxa were confirmed by DNA analyses. Aspergillus was the most abundant genus colonizing all materials, while some taxa were associated with certain substrates: Acremonium with gypsum board, Chaetomium with chipboard, Stachybotrys with gypsum board and wood, and Trichoderma with wood. Based on the DNA data, the community composition was clearly different between the mold and the dust, with a much higher alpha diversity in the dust. Most genera identified in the mold were also detected with a low abundance in the dust from the same apartments. Their spatial distribution indicated some local spread from the mold growth to other areas, but there was no clear correlation between the relative abundances and the distance to the damages. To study mold damages, different microbiological analyses (microscopy, cultivation, DNA, and chemistry) should be combined with a thorough inspection of buildings. The interpretation of such datasets requires the collaboration of skilled mycologists and building consultants. Full article

(This article belongs to the Special Issue Fungi Associated with Indoor Environments and Materials)

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17 pages, 5304 KiB

Open AccessArticle

Supervised Learning-Based Image Classification for the Detection of Late Blight in Potato Crops

by Marco Javier Suarez Baron, Angie Lizeth Gomez and Jorge Enrique Espindola Diaz

Appl. Sci. 2022, 12(18), 9371; https://doi.org/10.3390/app12189371 - 19 Sep 2022

Cited by 16 | Viewed by 2248

Abstract

This article presents the application of supervised learning and image classification for the early detection of late blight disease in potato using convolutional neural network and support vector machine SVM. The study was realized in the Boyacá department, Colombia. An initial dataset is [...] Read more.

This article presents the application of supervised learning and image classification for the early detection of late blight disease in potato using convolutional neural network and support vector machine SVM. The study was realized in the Boyacá department, Colombia. An initial dataset is created with the acquisition of a large number of images directly from the crops. These images are pre-processed in order to extract the main characteristics of the late blight disease. A classification model is developed to identify the potato plants as healthy or infected. Several performance, efficiency, and quality metrics were applied in the learning and classification tasks to determine the best machine learning algorithms. Then, an additional data set was used for validation, image classification, and detection of late blight disease in potato crops in the department of Boyacá, Colombia. The results obtained in the AUC curve show that the CNN trained with the data set obtained an AUC equal to 0.97; and the analysis through SVM obtained an AUC equal to 0.87. Future work requires the development of a mobile application with advanced features as a technological tool for precision agriculture that supports farmers with increased agricultural productivity. Full article

(This article belongs to the Special Issue Computer Vision and Pattern Recognition Based on Deep Learning)

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14 pages, 4293 KiB

Open AccessArticle

Intelligent Timber Damage Monitoring Using PZT-Enabled Active Sensing and Intrinsic Multiscale Entropy Analysis

by Shuai Guo, Tong Shen, Li Li, Huangxing Hu, Jicheng Zhang and Zhiwen Lu

Appl. Sci. 2022, 12(18), 9370; https://doi.org/10.3390/app12189370 - 19 Sep 2022

Cited by 1 | Viewed by 1401

Abstract

Timber has been commonly used in the field of civil engineering, and the health condition of timber is of great significance for the whole structure in practical scenarios. However, due to mechanical load and environmental impact, timber-based constructions are vulnerable to termite attack, [...] Read more.

Timber has been commonly used in the field of civil engineering, and the health condition of timber is of great significance for the whole structure in practical scenarios. However, due to mechanical load and environmental impact, timber-based constructions are vulnerable to termite attack, microbial corrosion and fractures within their service lives. Thus, the damage monitoring of timber structures is very challenging under real situations. This paper presents an intelligent timber damage monitoring approach using Lead Zirconate Titanate (PZT)-enabled active sensing and intrinsic multiscale entropy analysis. The proposed approach adopts PZT-enabled active sensing to collect the signals depicting dynamic characteristics of the timber structure. The proposed intrinsic multiscale entropy analysis utilizes variational mode decomposition (VMD) to deal with the collected response signals. Decomposition of the response signals into a set of band-limited intrinsic mode functions (BLIMFs) denoting nonlinear and nonstationary characteristics. Then multiscale sample entropy (MSE) is employed to extract quantitative features, which are adopted as health condition indicators of timber structures. Finally, the convolutional neural network (CNN) fulfills the intelligent timber damage monitoring by using the quantitative features as the effective input. The research findings reveal the efficacy and superiority of the proposed method. Full article

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2 pages, 156 KiB

Open AccessEditorial

Special Issue “Spine and Spinal Cord Biomechanics and Rehabilitation”

by Norihiro Nishida

Appl. Sci. 2022, 12(18), 9369; https://doi.org/10.3390/app12189369 - 19 Sep 2022

Viewed by 1364

Abstract

Spinal cord injuries are directly related to quality of life [...] Full article

21 pages, 1429 KiB

Open AccessArticle

Application of Extension Engineering in Safety Evaluation of Chemical Enterprises

by Qilong Han, Peng Liu and Zhiqiang Ma

Appl. Sci. 2022, 12(18), 9368; https://doi.org/10.3390/app12189368 - 19 Sep 2022

Cited by 1 | Viewed by 1785

Abstract

To effectively analyze the safety risk of chemical enterprises and ensure the safety of production and management of enterprises, the contradiction problems in the process of index selection and risk early warning model in practical application are addressed. In this paper, extension engineering [...] Read more.

To effectively analyze the safety risk of chemical enterprises and ensure the safety of production and management of enterprises, the contradiction problems in the process of index selection and risk early warning model in practical application are addressed. In this paper, extension engineering is introduced into the safety-security field of chemical enterprises to extract hidden useful information from the production environment and outdoor environment data and provide decision support for the managers of chemical enterprises. First, based on data preprocessing and extension analysis, the safety-security data of chemical enterprises that meet the quality requirements and can be efficiently mined are searched. Then, the outdoor environment is combined in the paper to conduct the mining of these data in two aspects: (1) comprehensive analysis and evaluation of data quality; (2) key factors affecting factory safety mining, realizing the safety-security evaluation of intelligent factories in chemical enterprises. Based on the proposed chemical factory safety extension prerisk model, the risk assessment of the safety status of a chemical enterprise in Hebei Province is carried out. The research results of this paper provide a theoretical basis for the safety production analysis of such chemical enterprises and put forward practical suggestions for preventing possible accidents in the production process. Full article

(This article belongs to the Special Issue Recent Analysis and Applications of Algorithms, Programs and Data Based on Artificial Intelligence)

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Appl. Sci., Volume 12, Issue 18 (September-2 2022) – 473 articles

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