Applied Sciences

15 pages, 1183 KiB

Open AccessArticle

Effects of the Addition of Pecan Nuts on the Nutritional Properties and Final Quality of Merino Lamb Burgers

by María Jesús Martín-Mateos, Lucía León, Alberto Ortiz, David Tejerina, Carmen Barraso, María Montaña López-Parra, Palmira Curbelo and Susana García-Torres

Appl. Sci. 2023, 13(11), 6860; https://doi.org/10.3390/app13116860 - 5 Jun 2023

Viewed by 2083

Abstract

This paper attempts to analyse lamb burgers from meat cuts of lower commercial value to which various amounts of freeze-dried pecan nuts (5%, 10% and 15%) were added to study the influence of the addition of pecans on the quality of the burger. [...] Read more.

This paper attempts to analyse lamb burgers from meat cuts of lower commercial value to which various amounts of freeze-dried pecan nuts (5%, 10% and 15%) were added to study the influence of the addition of pecans on the quality of the burger. One hundred eight burgers were evaluated by means of physicochemical, sensory and microbiological analyses. The addition of pecan nuts mainly affected the meat’s fatty acid profile. Fat content was higher as the amount of pecan nuts was increased, and the monounsaturated fatty acid (MUFA) and polyunsaturated fatty acid (PUFA) levels also increased (p < 0.001), whereas the saturated fatty acid content decreased (p < 0.001). Pecan nuts also proved able to increase the antioxidant capacity of the product, significantly reducing the oxidation values of lipids (p < 0.001) and proteins (p < 0.05). In general, no significant differences were identified in the sensory attributes under study. In conclusion, we found that the use of pecan nuts improves the nutritional content of the hamburgers without negatively affecting the technological or sensory properties. Full article

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7 pages, 586 KiB

Open AccessCommunication

Actinidia arguta (Baby Kiwi) Waste: Preliminary Considerations on Seed Recovery

by Nicole Roberta Giuggioli, Cristiana Peano and Luca Brondino

Appl. Sci. 2023, 13(11), 6859; https://doi.org/10.3390/app13116859 - 5 Jun 2023

Viewed by 1573

Abstract

Fruit seed oils are of new interest due to their significant properties and can be a good opportunity to recover fruit waste. Actinidia arguta (baby kiwi) fruits are a novelty in the market and berries can be consumed with the peels. Due to [...] Read more.

Fruit seed oils are of new interest due to their significant properties and can be a good opportunity to recover fruit waste. Actinidia arguta (baby kiwi) fruits are a novelty in the market and berries can be consumed with the peels. Due to their limited shelf life, fruits are very perishable and the waste management techniques used post-harvest are an important issue. Berry waste can be reused, for biological flows focused on food losses and waste reduction. Therefore, baby kiwi fruit samples were collected from the Ortofruititalia company orchards in Cuneo, Italy, and then processed and analysed for seed oil constituents using standard analytical methods. The results of this study indicate that unsaturated fatty acids were the most dominant fatty acids (92.6 g/100 g) in comparison with saturated (7.4 g/100 g). In addition, α-linoleic acid (82.7 g/100 g) was the most dominant unsaturated fatty acid. Additionally, γ-Tocopherol (0.023 g/100 g) was the most dominant tocopherol in this study. Extraction of seed oil from these berries could be proposed as an option for obtaining high-added-value oils for pharmaceutical cosmetics, among other uses. Full article

(This article belongs to the Special Issue Trends in Fruit and Vegetable Chemistry, Nutrition and Post-harvest Technology)

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15 pages, 2995 KiB

Open AccessArticle

Highly Active under VIS Light M/TiO₂ Photocatalysts Prepared by Single-Step Synthesis

by Olga Thoda, Anastasia M. Moschovi, Konstantinos Miltiadis Sakkas, Ekaterini Polyzou and Iakovos Yakoumis

Appl. Sci. 2023, 13(11), 6858; https://doi.org/10.3390/app13116858 - 5 Jun 2023

Viewed by 1469

Abstract

A single-step impregnation approach is investigated as a synthetic route for photocatalyst synthesis active under visible light. The as-derived photocatalysts exhibited very high degradation rates towards methylene blue (MB) decolorization under visible light despite the high concentration of the initial MB solution concentration. [...] Read more.

A single-step impregnation approach is investigated as a synthetic route for photocatalyst synthesis active under visible light. The as-derived photocatalysts exhibited very high degradation rates towards methylene blue (MB) decolorization under visible light despite the high concentration of the initial MB solution concentration. The TiO₂-based photocatalysts were prepared using nitrate precursor compounds for copper and silver; thus, Ag/TiO₂ and Cu/TiO₂ photocatalysts were prepared. The photocatalyst’s physicochemical properties were determined by XRF, BET, and XRD analysis. The metal nature of the titania substrate, the titania matrix effect, and the metal concentration parameters were studied, while the catalyst concentration in the MB initial solution was optimized. Full article

(This article belongs to the Special Issue Practical Application of Functionalized Carbon-Based Nanomaterials - Volume Ⅱ)

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17 pages, 4514 KiB

Open AccessArticle

Influence of Waste Filler on the Mechanical Properties and Microstructure of Epoxy Mortar

by Masood Ur Rahman and Jing Li

Appl. Sci. 2023, 13(11), 6857; https://doi.org/10.3390/app13116857 - 5 Jun 2023

Cited by 4 | Viewed by 2022

Abstract

This paper presents experimental investigations on epoxy mortar produced using industrial wastes. In some recent studies, coal bottom ash and polyethylene terephthalate (PET) waste have been chosen as a filler to replace sand, and fly ash and silica fume have been chosen as [...] Read more.

This paper presents experimental investigations on epoxy mortar produced using industrial wastes. In some recent studies, coal bottom ash and polyethylene terephthalate (PET) waste have been chosen as a filler to replace sand, and fly ash and silica fume have been chosen as micro fillers for epoxy mortar production; enhanced results in terms of compressive and tensile strengths and durability have been achieved. However, these approaches failed to boost the strength and durability compared to the epoxy steel slag, epoxy sand, epoxy marble dust, and epoxy polyvinyl chloride (PVC) waste. This present research work has investigated the influence of waste filler on the mechanical properties and microstructure of epoxy mortar, produced by using sand and industrial wastes, i.e., steel slag, marble dust, and polyvinyl chloride waste. Based on the composition ratio, the prepared samples of epoxy resin mortar containing 25% epoxy binder (epoxy resin plus epoxy hardener) and 75% filler (1:3) were compared to the cement mortar. However, each specimen of epoxy resin mortar was prepared by mixing with different fillers. The properties such as compressive strength, tensile strength, and microstructural changes were measured using different characterization techniques including X-ray diffraction (XRD), scanning electron microscopy (SEM), Fourier transform infrared radiation spectroscopy (FTIR), and scanning electron microscopy and energy dispersive X-ray spectroscopy (SEM-EDX). From the obtained results, it was found that the strength of the specimens increases when blended with steel slag and marble dust, which is attributed to their peak densities and enhanced particle interactions. The XRD, SEM, FTIR, and SEM-EDX analyses showed the formation of calcium, magnesium, and other phases in the microstructure of epoxy resin-based mortars. This resulted in lower water absorption and porosity, as well as improvements in both compressive and tensile strengths. This research can help in understanding the important role of different industrial wastes as feasible fillers in epoxy resin-based composites. Full article

(This article belongs to the Section Materials Science and Engineering)

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11 pages, 1893 KiB

Open AccessArticle

Video-Based Recognition of Human Activity Using Novel Feature Extraction Techniques

by Obada Issa and Tamer Shanableh

Appl. Sci. 2023, 13(11), 6856; https://doi.org/10.3390/app13116856 - 5 Jun 2023

Cited by 7 | Viewed by 1799

Abstract

This paper proposes a novel approach to activity recognition where videos are compressed using video coding to generate feature vectors based on compression variables. We propose to eliminate the temporal domain of feature vectors by computing the mean and standard deviation of each [...] Read more.

This paper proposes a novel approach to activity recognition where videos are compressed using video coding to generate feature vectors based on compression variables. We propose to eliminate the temporal domain of feature vectors by computing the mean and standard deviation of each variable across all video frames. Thus, each video is represented by a single feature vector of 67 variables. As for the motion vectors, we eliminated their temporal domain by projecting their phases using PCA, thus representing each video by a single feature vector with a length equal to the number of frames in a video. Consequently, complex classifiers such as LSTM can be avoided and classical machine learning techniques can be used instead. Experimental results on the JHMDB dataset resulted in average classification accuracies of 68.8% and 74.2% when using the projected phases of motion vectors and video coding feature variables, respectively. The advantage of the proposed solution is the use of FVs with low dimensionality and simple machine learning techniques. Full article

(This article belongs to the Special Issue Computational Intelligence in Image and Video Analysis)

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15 pages, 3135 KiB

Open AccessArticle

Non-Surgical Lower-Limb Rehabilitation Enhances Quadriceps Strength in Inpatients with Hip Fracture: A Study on Force Capacity and Fatigue

by Alessandro Scano, Rebecca Re, Alessandro Tomba, Oriana Amata, Ileana Pirovano, Cristina Brambilla, Davide Contini, Lorenzo Spinelli, Caterina Amendola, Antonello Valerio Caserta, Rinaldo Cubeddu, Lorenzo Panella and Alessandro Torricelli

Appl. Sci. 2023, 13(11), 6855; https://doi.org/10.3390/app13116855 - 5 Jun 2023

Cited by 2 | Viewed by 1730

Abstract

Measuring muscle fatigue and resistance to fatigue is a topical theme in many clinical research studies. Multi-domain approaches, including electromyography (EMG), are employed to measure fatigue in rehabilitation contexts. In particular, spectral features, such as the reduction in the median frequency, are accepted [...] Read more.

Measuring muscle fatigue and resistance to fatigue is a topical theme in many clinical research studies. Multi-domain approaches, including electromyography (EMG), are employed to measure fatigue in rehabilitation contexts. In particular, spectral features, such as the reduction in the median frequency, are accepted biomarkers to detect muscle fatigue conditions. However, applications of fatigue detection in clinical scenarios are still limited and with margin for improvement. One of the potential applications of such methodology in clinics concerns the evaluation of the rehabilitation after hip fracture. In this work, 20 inpatients, in the acute phase after hip fracture surgery and with lower limb weakness, performed isometric contractions with their healthy lower limb (quadriceps muscle) and their resistance to fatigue before and after 2 weeks of rehabilitation program was measured. Multi-channel EMG and Maximum Voluntary Contractions (MVC, force) were recorded on five muscle heads. We found that, after performing the same number of repetitions (repetitions pre-treatment: 19.7 ± 1.34; repetitions post-treatment: 19.9 ± 0.36; p = 0.223), MVC improved (MVC pre-treatment: 278 ± 112 N; MVC post-treatment: 322 ± 88 N; p = 0.015) after rehabilitation for most of the patients and fatigue did not change. These results suggest that higher force exertion was performed after rehabilitation, with the same level of fatigue (fatigued muscles pre-treatment: 1.40 ± 1.70; fatigued muscles post-treatment: 1.15 ± 1.59; p = 0.175) after. Results are discussed addressing the potential of multifactorial instrumental assessments for describing patients’ status and provide data for clinical decision making. Full article

(This article belongs to the Section Biomedical Engineering)

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29 pages, 2265 KiB

Open AccessOpinion

Towards a New Paradigm for Digital Health Training and Education in Australia: Exploring the Implication of the Fifth Industrial Revolution

by Toh Yen Pang, Tsz-Kwan Lee and Manzur Murshed

Appl. Sci. 2023, 13(11), 6854; https://doi.org/10.3390/app13116854 - 5 Jun 2023

Cited by 11 | Viewed by 4698

Abstract

Digital transformation, characterised by advanced digitalisation, blockchain, the Internet of Things, artificial intelligence, machine learning technologies, and robotics, has played a key role in revolutionising various industries, especially the healthcare sector. The adoption of and transition (from traditional) to new technology will bring [...] Read more.

Digital transformation, characterised by advanced digitalisation, blockchain, the Internet of Things, artificial intelligence, machine learning technologies, and robotics, has played a key role in revolutionising various industries, especially the healthcare sector. The adoption of and transition (from traditional) to new technology will bring challenges, opportunities, and disruptions to existing healthcare systems. According to the European Union, we must pursue both digital and green transitions to achieve sustainable, human-centric, and resilient industries to achieve a world of prosperity for all. The study aims to present a novel approach to education and training in the digital health field that is inspired by the fifth industrial revolution paradigm. The paper highlights the role of training and education interventions that are required to support digital health in the future so that students can develop the capacity to recognise and exploit the potential of new technologies. This article will briefly discuss the challenges and opportunities related to healthcare systems in the era of digital transformation and beyond. Then, we look at the enabling technologies from an Industry 5.0 perspective that supports digital health. Finally, we present a new teaching and learning paradigm and strategies that embed Industry 5.0 technologies in academic curricula so that students can develop their capacities to embrace a digital future and minimise the disruption that will inevitably accompany it. By incorporating Industry 5.0 principles into digital health education, we believe students can gain a deeper understanding of the industry and develop skills that will enable them to deliver a more efficient, effective, and sustainable healthcare system. Full article

(This article belongs to the Special Issue Challenges and Opportunities in Digital Health)

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19 pages, 10497 KiB

Open AccessArticle

Towards Intricate Stand Structure: A Novel Individual Tree Segmentation Method for ALS Point Cloud Based on Extreme Offset Deep Learning

by Yizhuo Zhang, Hantao Liu, Xingyu Liu and Huiling Yu

Appl. Sci. 2023, 13(11), 6853; https://doi.org/10.3390/app13116853 - 5 Jun 2023

Cited by 5 | Viewed by 1693

Abstract

Due to the complex structure of high-canopy-density forests, the traditional individual tree segmentation (ITS) algorithms based on ALS point cloud, which set segmentation threshold manually, is difficult to adequately cover a variety of complex situations, so the ITS accuracy is unsatisfactory. In this [...] Read more.

Due to the complex structure of high-canopy-density forests, the traditional individual tree segmentation (ITS) algorithms based on ALS point cloud, which set segmentation threshold manually, is difficult to adequately cover a variety of complex situations, so the ITS accuracy is unsatisfactory. In this paper, a top-down segmentation strategy is adopted to propose an adaptive segmentation method based on extreme offset deep learning, and the ITS set aggregation strategy based on gradient change criterion is designed for the over-segmentation generated by random offset, and the precise ITS is realized. Firstly, the segmentation sub-plot is set as 25 m × 25 m, the regional point cloud and its treetop are marked, and the offset network is trained. Secondly, the extreme offset network is designed to carry out spatial transformation of the original point cloud, and each point is offset to the position near the treetop to obtain the offset point cloud with a high density at the treetop, which enhances the discrimination among individual trees. Thirdly, the self-adaptive mean shift algorithm based on average neighboring distance is designed to divide and mark the offset point cloud. Fourthly, the offset point cloud, after clustering, is mapped back to the original space to complete the preliminary segmentation. Finally, according to the gradient change among different canopies, the ITS aggregation method is designed to aggregate adjacent canopies with a gentle gradient change. In order to investigate the universality of the proposed method on different stand structures, two coniferous forest plots (U1, U2) in the Blue Ridge area of Washington, USA, and two mixed forest plots (G1, G2) in Bretten, Germany, are selected in the experiment. The learning rate of the deep network is set as 0.001, the sampled point number of the sub-plot is 900, the transformer dimension is 512 × 512, the neighboring search number of points is 16, and the number of up-sampling blocks is 3. Experimental results show that in mixed forests (G1, G2) with complex structures, the F-score of the proposed method reaches 0.89, which is about 4% and 7% higher than the classical SHDR and improved DK, respectively. In high-canopy-density areas (U2, G2), the F-score of the proposed method reaches 0.89, which is about 3% and 4% higher than the SHDR and improved DK, respectively. The results show that the proposed method has high universality and accuracy, even in a complex stand environment with high canopy density. Full article

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21 pages, 12662 KiB

Open AccessArticle

Design of N-Way Wilkinson Power Dividers with New Input/Output Arrangements for Power-Halving Operations

by Ceyhun Karpuz, Mehmet Cakir, Ali Kursad Gorur and Adnan Gorur

Appl. Sci. 2023, 13(11), 6852; https://doi.org/10.3390/app13116852 - 5 Jun 2023

Cited by 1 | Viewed by 3038

Abstract

In this paper, new single/double-layer N-way Wilkinson power dividers (WPDs) were designed by using slow-wave structures such as narrow-slit-loaded and meandered transmission lines. For size reduction, the slit-loaded and meandered lines were used instead of the quarter-wavelength transmission lines of a conventional WPD. [...] Read more.

In this paper, new single/double-layer N-way Wilkinson power dividers (WPDs) were designed by using slow-wave structures such as narrow-slit-loaded and meandered transmission lines. For size reduction, the slit-loaded and meandered lines were used instead of the quarter-wavelength transmission lines of a conventional WPD. Based on the proposed approaches, two-, four-, and eight-way power dividers were designed, simulated, and fabricated. The fabricated 2-, 4-, and 8-way circuits were measured at the center frequencies of 2.03, 1.77, and 1.73 GHz, which are in excellent agreement with the predicted ones. The meandered transmission lines were also used to design WPD types with novel input/output port arrangements. For this purpose, two three-way WPDs were located on both sides of the same board to have different power-splitting ratios at different inputs and outputs in order to provide alternative solutions for antenna arrays. Furthermore, a five-way dual-layer WPD was introduced by locating the meandered transmission lines into two layers. The most important advantage of the proposed 3- and 5-way WPDs is that they allowed the input power at the next output port to be halved, in the order of P/2, P/4, P/8, P/16, and P/16. All the designed power-halving WPDs were simulated, fabricated, and successfully tested. Full article

(This article belongs to the Special Issue Trends and Prospects in Applied Electromagnetics)

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17 pages, 2087 KiB

Open AccessArticle

SFCA: A Scalable Formal Concepts Driven Architecture for Multi-Field Knowledge Graph Completion

by Xiaochun Sun, Chenmou Wu and Shuqun Yang

Appl. Sci. 2023, 13(11), 6851; https://doi.org/10.3390/app13116851 - 5 Jun 2023

Viewed by 1531

Abstract

With the proliferation of Knowledge Graphs (KGs), knowledge graph completion (KGC) has attracted much attention. Previous KGC methods focus on extracting shallow structural information from KGs or in combination with external knowledge, especially in commonsense concepts (generally, commonsense concepts refer to the basic [...] Read more.

With the proliferation of Knowledge Graphs (KGs), knowledge graph completion (KGC) has attracted much attention. Previous KGC methods focus on extracting shallow structural information from KGs or in combination with external knowledge, especially in commonsense concepts (generally, commonsense concepts refer to the basic concepts in related fields that are required for various tasks and academic research, for example, in the general domain, “Country” can be considered as a commonsense concept owned by “China”), to predict missing links. However, the technology of extracting commonsense concepts from the limited database is immature, and the scarce commonsense database is also bound to specific verticals (commonsense concepts vary greatly across verticals, verticals refer to a small field subdivided vertically under a large field). Furthermore, most existing KGC models refine performance on public KGs, leading to inapplicability to actual KGs. To address these limitations, we proposed a novel Scalable Formal Concept-driven Architecture (SFCA) to automatically encode factual triples into formal concepts as a superior structural feature, to support rich information to KGE. Specifically, we generate dense formal concepts first, then yield a handful of entity-related formal concepts by sampling and delimiting the appropriate candidate entity range via the filtered formal concepts to improve the inference of KGC. Compared with commonsense concepts, KGC benefits from more valuable information from the formal concepts, and our self-supervision extraction method can be applied to any KGs. Comprehensive experiments on five public datasets demonstrate the effectiveness and scalability of SFCA. Besides, the proposed architecture also achieves the SOTA performance on the industry dataset. This method provides a new idea in the promotion and application of knowledge graphs in AI downstream tasks in general and industrial fields. Full article

(This article belongs to the Topic Data Science and Knowledge Discovery)

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17 pages, 3182 KiB

Open AccessArticle

An Integrated Data-Driven Predictive Resilience Framework for Disaster Evacuation Traffic Management

by Tanzina Afrin, Lucy G. Aragon, Zhibin Lin and Nita Yodo

Appl. Sci. 2023, 13(11), 6850; https://doi.org/10.3390/app13116850 - 5 Jun 2023

Cited by 1 | Viewed by 1590

Abstract

Maintaining smooth traffic during disaster evacuation is a lifesaving step. Traffic resilience is often used to define the ability of a roadway during disaster evacuation to withstand and recover its functionality from disturbances in terms of traffic flow caused by a disaster. However, [...] Read more.

Maintaining smooth traffic during disaster evacuation is a lifesaving step. Traffic resilience is often used to define the ability of a roadway during disaster evacuation to withstand and recover its functionality from disturbances in terms of traffic flow caused by a disaster. However, a high level of variances due to system complexity and inherent uncertainty associated with disaster and evacuation risks poses great challenges in predicting traffic resilience during evacuation. To fill this gap, this study aimed to propose a new integrated data-driven predictive resilience framework that enables incorporating traffic uncertainty factors in determining road traffic conditions and predicting traffic performance using machine learning approaches and various space and time (spatiotemporal) data sources. This study employed an augmented Long Short-Term Memory (LSTM)-based approach with correlated spatiotemporal traffic data to predict traffic conditions, then to map those conditions to traffic resilience levels: daily traffic, segment traffic, and overall route traffic. A case study of Hurricane Irma’s evacuation traffic was used to demonstrate the effectiveness of the proposed framework. The results indicated that the proposed method could effectively predict traffic conditions and thus help to determine traffic resilience. The data also confirmed that the traffic infrastructures along the US I-75 route remained resilient despite the disturbances during the disaster evacuation activities. The findings of this study suggest that the proposed framework is applicable to other disaster management scenarios to obtain more robust decisions for the emergency response during disaster evacuation. Full article

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18 pages, 3804 KiB

Open AccessArticle

Effects of Short-Term Sodium Nitrate versus Sodium Chloride Supplementation on Energy and Lipid Metabolism during High-Intensity Intermittent Exercise in Athletes

by Larissa Sarah Blau, Jan Gerber, Armin Finkel, Moritz Lützow, Norbert Maassen, Magdalena Aleksandra Röhrich, Erik Hanff, Dimitrios Tsikas, Vladimir Shushakov and Mirja Jantz

Appl. Sci. 2023, 13(11), 6849; https://doi.org/10.3390/app13116849 - 5 Jun 2023

Viewed by 1457

Abstract

The aim of this study was to investigate the possible effects of chronic nitrate supplementation on the metabolites of energy metabolism during high-intensity, high-volume intermittent training (HIHVT). In this placebo-controlled double-blind study, 17 participants exercised 3 times a week on a cycle ergometer. [...] Read more.

The aim of this study was to investigate the possible effects of chronic nitrate supplementation on the metabolites of energy metabolism during high-intensity, high-volume intermittent training (HIHVT). In this placebo-controlled double-blind study, 17 participants exercised 3 times a week on a cycle ergometer. Sodium nitrate or sodium chloride as the placebo was supplemented daily at 8.5 mg/kg body weight for 10 days. The training exercise consisted of a warm-up, a 45-min interval period, and a post-exercise period. Oxygen uptake, respiratory exchange ratio, and various parameters were measured in the venous blood and plasma. During training, the oxygen uptake and respiratory exchange ratio did not differ between the nitrate and the placebo group. Venous plasma concentrations of nitrate and nitrite were significantly increased in the nitrate group (p < 0.001 and p = 0.007, respectively). Triglyceride concentrations were significantly lower in the nitrate group than in the placebo group (p = 0.010). The concentration of free fatty acids in the plasma did not change upon nitrate supplementation and no significant differences were observed in the contribution of fat to energy metabolism during exercise. An increase in plasma ammonia concentration was observed in the nitrate group during and after exercise (p = 0.048). Metabolites of energy-rich phosphates did not differ between the nitrate and chloride groups, suggesting no improvement in efficiency through the supplemented nitrate. It was concluded that nitrate supplementation did not reduce oxygen uptake and adenosine triphosphate resynthesis by hydrolysis or through creatine kinase activity during high-intensity, high-volume intermittent exercise. Although, lipid metabolism as well as amino acid metabolism might be affected by nitrate supplementation during HIHVT. Full article

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12 pages, 30676 KiB

Open AccessArticle

3D Reconstruction of Celadon from a 2D Image: Application to Path Tracing and VR

by Seongil Kim and Youngjin Park

Appl. Sci. 2023, 13(11), 6848; https://doi.org/10.3390/app13116848 - 5 Jun 2023

Cited by 1 | Viewed by 1638

Abstract

We present a straightforward approach for reconstructing 3D celadon models from a single 2D image. The celadon is a historical example of the surface of revolution. Our approach uses a surface of revolution technique to generate the basic shape of the celadon and [...] Read more.

We present a straightforward approach for reconstructing 3D celadon models from a single 2D image. The celadon is a historical example of the surface of revolution. Our approach uses a surface of revolution technique to generate the basic shape of the celadon and then applies texture mapping to create a realistic appearance. The process involves detecting the contour and corners of the celadon image, determining an axis of revolution, generating a profile curve, and finally constructing a 3D celadon model. Additionally, we create models as triangular meshes at multiple resolutions, employing a B-spline curve as the profile curve. It enhances the adaptability of the models for various purposes. We render various scenes using a path tracer to assess the suitability of the generated 3D celadon models and generate a VR celadon museum with the models. Overall, our approach offers a simple and efficient solution for reconstructing a 3D celadon model, generating VR content, and demonstrating extensive applicability across numerous disciplines. Full article

(This article belongs to the Special Issue 3D Information Technologies for Tangible and Intangible Cultural Heritage)

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20 pages, 1761 KiB

Open AccessArticle

Path following for Autonomous Ground Vehicle Using DDPG Algorithm: A Reinforcement Learning Approach

by Yu Cao, Kan Ni, Xiongwen Jiang, Taiga Kuroiwa, Haohao Zhang, Takahiro Kawaguchi, Seiji Hashimoto and Wei Jiang

Appl. Sci. 2023, 13(11), 6847; https://doi.org/10.3390/app13116847 - 5 Jun 2023

Cited by 2 | Viewed by 3276

Abstract

The potential of autonomous driving technology to revolutionize the transportation industry has attracted significant attention. Path following, a fundamental task in autonomous driving, involves accurately and safely guiding a vehicle along a specified path. Conventional path-following methods often rely on rule-based or parameter-tuning [...] Read more.

The potential of autonomous driving technology to revolutionize the transportation industry has attracted significant attention. Path following, a fundamental task in autonomous driving, involves accurately and safely guiding a vehicle along a specified path. Conventional path-following methods often rely on rule-based or parameter-tuning aspects, which may not be adaptable to complex and dynamic scenarios. Reinforcement learning (RL) has emerged as a promising approach that can learn effective control policies from experience without prior knowledge of system dynamics. This paper investigates the effectiveness of the Deep Deterministic Policy Gradient (DDPG) algorithm for steering control in ground vehicle path following. The algorithm quickly converges and the trained agent achieves stable and fast path following, outperforming three baseline methods. Additionally, the agent achieves smooth control without excessive actions. These results validate the proposed approach’s effectiveness, which could contribute to the development of autonomous driving technology. Full article

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13 pages, 1550 KiB

Open AccessArticle

Biochar Effects on Ce Leaching and Plant Uptake in Lepidium sativum L. Grown on a Ceria Nanoparticle Spiked Soil

by Guido Fellet, Pellegrino Conte and Luca Marchiol

Appl. Sci. 2023, 13(11), 6846; https://doi.org/10.3390/app13116846 - 5 Jun 2023

Cited by 3 | Viewed by 1528

Abstract

The increasing use of nanoparticles is causing a threat to the environment and humans. The aim of this work was to evaluate the effects of the quenching procedure of biochar production on the biochar capacity to retain the CeO₂ nanoparticle (CeO₂ [...] Read more.

The increasing use of nanoparticles is causing a threat to the environment and humans. The aim of this work was to evaluate the effects of the quenching procedure of biochar production on the biochar capacity to retain the CeO₂ nanoparticle (CeO₂NP) in soil. The effects on Lepidium sativum L. (watercress) were considered. Two biochars were produced from fir wood pellets under the same pyrolysis conditions but with different quenching procedures: dry quenching and wet quenching. The two biochars (BCdryQ and BCwetQ) were separately added to a CeO₂NP-spiked soil (1000 mg kg⁻¹) at the dose 5%_DW and placed in 12 lysimeters under controlled conditions. Lepidium sativum L. seeds were sowed on each lysimeter. The lysimeters were irrigated once a week for 7 weeks, and the leachates were collected. At the end of the experiment, the aboveground biomass was harvested; the total number of plants and the number of plants at the flowering stage were counted, and the height of the tallest plant and the total dry biomass were measured. The data showed that the quenching procedure influences the CeO₂NP retention in soil, and BCdryQ can reduce the leaching of the nanoparticles. Biochar significantly increased the flowering in plants, and BCwetQ reduced the biomass production. This work highlights the importance of the biochar production process for soil applications. The production settings are crucial in determining the efficacy of the product for its ultimate use. Full article

(This article belongs to the Special Issue Potentially Toxic Trace Elements in Contaminated Sites: Fate, Risk and Remediation)

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27 pages, 6162 KiB

Open AccessArticle

Two-Stage Short-Term Power Load Forecasting Based on SSA–VMD and Feature Selection

by Weijian Huang, Qi Song and Yuan Huang

Appl. Sci. 2023, 13(11), 6845; https://doi.org/10.3390/app13116845 - 5 Jun 2023

Cited by 6 | Viewed by 1590

Abstract

Short-term power load forecasting is of great significance for the reliable and safe operation of power systems. In order to improve the accuracy of short-term load forecasting, for the problems of random fluctuation in load and the complexity of load-influencing factors, this paper [...] Read more.

Short-term power load forecasting is of great significance for the reliable and safe operation of power systems. In order to improve the accuracy of short-term load forecasting, for the problems of random fluctuation in load and the complexity of load-influencing factors, this paper proposes a two-stage short-term load forecasting method, SSA–VMD-LSTM-MLR-FE (SVLM–FE) based on sparrow search algorithm (SSA), to optimize variational mode decomposition (VMD) and feature engineering (FE). Firstly, an evaluation criterion on the loss of VMD decomposition is proposed, and SSA is used to find the optimal combination of parameters for VMD under this criterion. Secondly, the first stage of forecasting is carried out, and the different components obtained from SSA–VMD are predicted separately, with the high-frequency components input to a long short-term memory network (LSTM) for forecasting and the low-frequency components input to a multiple linear regression model (MLR) for forecasting. Finally, the forecasting values of the components obtained in the first stage are input to the second stage for error correction; factors with a high degree of influence on the load are selected using the Pearson correlation coefficient (PCC) and maximal information coefficient (MIC), and the load value at the moment that has a great influence on the load value at the time to be predicted is selected using autocorrelation function (ACF). The forecasting values of the components are fused with the selected feature values to construct a vector, which is fed into the fully connected layer for forecasting. In this paper, the performance of SVLM–FE is evaluated experimentally on two datasets from two places in China. In Place 1, the RMSE, MAE, and MAPE are 128.169 MW, 102.525 MW, and 1.562%, respectively; in Place 2, the RMSE, MAE, and MAPE are 111.636 MW, 92.291 MW, and 1.426%, respectively. The experimental results show that SVLM–FE has high accuracy and stability. Full article

(This article belongs to the Special Issue Advances in AI-Based (AI+) Energy and Resource Research)

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26 pages, 9007 KiB

Open AccessReview

Light–Matter Complex Interactions in Stereolithographies

by Thomas Doualle, Laurent Gallais and Jean-Claude André

Appl. Sci. 2023, 13(11), 6844; https://doi.org/10.3390/app13116844 - 5 Jun 2023

Cited by 1 | Viewed by 1453

Abstract

Since its inception in 1984, 3D printing has revolutionized manufacturing by leveraging the additivity principle and simple material–energy coupling. Stereolithography, as the pioneering technology, introduced the concept of photopolymerization with a single photon. This groundbreaking approach not only established the essential criteria for [...] Read more.

Since its inception in 1984, 3D printing has revolutionized manufacturing by leveraging the additivity principle and simple material–energy coupling. Stereolithography, as the pioneering technology, introduced the concept of photopolymerization with a single photon. This groundbreaking approach not only established the essential criteria for additive processes employing diverse localized energies and materials, including solid, pasty, powdery, organic, and mineral substances, but also underscored the significance of light–matter interactions in the spatial and temporal domains, impacting various critical aspects of stereolithography’s performance. This review article primarily focuses on exploring the intricate relationship between light and matter in stereolithography, aiming to elucidate operational control strategies for fabrication processes, encompassing voxel size manipulation. Furthermore, advancements in light excitation modes, transitioning from one-photon to two-photon mechanisms, have unlocked new material and creative possibilities. Notable advantages include the elimination of layering (true 3D printing) and the ability to fabricate objects using silica glass. Although these volumetric 3D printing methods deviate from conventional additive manufacturing concepts and possess narrower application scopes, they offer reduced manufacturing and design timeframes along with enhanced spatial resolution in select cases. These complex light–matter interactions form the cornerstone of this comprehensive review, shedding light on operational control strategies and considerations in stereolithography. By comprehensively analyzing the impact of light–matter interactions, including the novel two-photon excitation, this review highlights the transformative potential of stereolithography for rapid and precise fabrication. While these techniques may occupy a smaller niche within the broader spectrum of 3D printing technologies, they serve as valuable additions to the array of 3D devices available in the market. Full article

(This article belongs to the Section Additive Manufacturing Technologies)

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11 pages, 3301 KiB

Open AccessArticle

Analysis of Sealing Characteristics of Lip Seal Rings for Deep-Sea Separable Pressure Vessels

by Xuepeng Liu, Shiping He and Jianhua Zheng

Appl. Sci. 2023, 13(11), 6843; https://doi.org/10.3390/app13116843 - 5 Jun 2023

Cited by 1 | Viewed by 2372

Abstract

Deep-sea pressure vessels are specialized pressure vessels designed for automatic deployment from underwater to the surface. These vessels find extensive applications in underwater life-saving and transportation. Their interiors are furnished with a pair of sealing rings, one of which is lip-shaped, and the [...] Read more.

Deep-sea pressure vessels are specialized pressure vessels designed for automatic deployment from underwater to the surface. These vessels find extensive applications in underwater life-saving and transportation. Their interiors are furnished with a pair of sealing rings, one of which is lip-shaped, and the other is a convex shape, to ensure a dependable seal. With increasing water depth, the sealing rings experience augmented pressure, resulting in a gradual pressing of the rings into the sealing groove. Using ANSYS workbench finite element software, a two-dimensional axisymmetric lip seal finite element model using forces for overall constraint was established, the complete process of progressive pressing into the sealing groove was simulated, and the deformation, contact stress, maximum shear stress, and von Mises stress distribution was also simulated. We also conducted a comparative analysis of lip seals under low and high-water pressure sealing conditions. The findings of the study indicate that when subjected to a combined effect of the installation pre-tightening force and the working water pressure, the lip seal experiences complete compression into the sealing groove at a specific water depth. When subjected to the simultaneous influence of water pressure on the sealing ring material and friction force on the contact surface, two extremes of contact stress manifest in the primary sealing zone of the lip seal. These extremes have the capacity to elevate the contact stress and the effective sealing width, ultimately leading to an improvement in the sealing performance. Concurrently, as the water pressure gradually increases, the inner concave circle of the sealing ring experiences stretching, leading to a reduction in stress concentration, equivalent stress, and shear stress to a considerable extent. This mechanism ensures that the lip-shaped sealing ring retains sufficient strength. This study offers a viable solution for conducting sealing studies on deep-sea separable pressure vessels. Full article

(This article belongs to the Special Issue Advances in Failure Mechanism and Numerical Methods for Geomaterials)

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16 pages, 9511 KiB

Open AccessEditor’s ChoiceArticle

Materials and Technique: The First Look at Saturnino Gatti

by Letizia Bonizzoni, Simone Caglio, Anna Galli, Luca Lanteri and Claudia Pelosi

Appl. Sci. 2023, 13(11), 6842; https://doi.org/10.3390/app13116842 - 5 Jun 2023

Cited by 11 | Viewed by 2246

Abstract

As part of the study project of the pictorial cycle, attributed to Saturnino Gatti, in the church of San Panfilo at Villagrande di Tornimparte (AQ), image analyses were performed in order to document the general conservation conditions of the surfaces, and to map [...] Read more.

As part of the study project of the pictorial cycle, attributed to Saturnino Gatti, in the church of San Panfilo at Villagrande di Tornimparte (AQ), image analyses were performed in order to document the general conservation conditions of the surfaces, and to map the different painting materials to be subsequently examined using spectroscopic techniques. To acquire the images, radiation sources, ranging from ultraviolet to near infrared, were used; analyses of ultraviolet fluorescence (UVF), infrared reflectography (IRR), infrared false colors (IRFC), and optical microscopy in visible light (OM) were carried out on all the panels of the mural painting of the apsidal conch. The Hypercolorimetric Multispectral Imaging (HMI) technique was also applied in selected areas of two panels. Due to the accurate calibration system, this technique is able to obtain high-precision colorimetric and reflectance measurements, which can be repeated for proper surface monitoring. The integrated analysis of the different wavelengths’ images—in particular, the ones processed in false colors—made it possible to distinguish the portions affected by retouching or repainting and to recover the legibility of some figures that showed chromatic alterations of the original pictorial layers. The IR reflectography, in addition to highlighting the portions that lost materials and were subject to non-original interventions, emphasized the presence of the underdrawing, which was detected using the spolvero technique. UVF photography led to a preliminary mapping of the organic and inorganic materials that exhibited characteristic induced fluorescence, such as a binder in correspondence with the original azurite painting or the wide use of white zinc in the retouched areas. The collected data made it possible to form a better iconographic interpretation. Moreover, it also enabled us to accurately select the areas to be investigated using spectroscopic analyses, both in situ and on micro-samples, in order to deepen our knowledge of the techniques used by the artist to create the original painting, and to detect subsequent interventions. Full article

(This article belongs to the Special Issue Results of the II National Research Project of AIAr: Archaeometric Study of the Frescoes by Saturnino Gatti and Workshop at the Church of San Panfilo in Tornimparte (AQ, Italy))

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14 pages, 3811 KiB

Open AccessArticle

Short Words for Writer Identification Using Neural Networks

by Georgia Koukiou

Appl. Sci. 2023, 13(11), 6841; https://doi.org/10.3390/app13116841 - 5 Jun 2023

Cited by 1 | Viewed by 1402

Abstract

In biometrics, it is desirable to distinguish a person using only a short sample of his handwriting. This problem is treated in the present work using only a short word with three letters. It is shown that short words can contribute to high-performance [...] Read more.

In biometrics, it is desirable to distinguish a person using only a short sample of his handwriting. This problem is treated in the present work using only a short word with three letters. It is shown that short words can contribute to high-performance writer identification if line characteristics are extracted using morphological directional transformations. Thus, directional morphological structuring elements are used as a tool for extracting this kind of information with the morphological opening operation. The line characteristics are organized based on Markov chains so that the elements of the transition matrix are used as feature vectors for identification. The Markov chains describe the alternation in the directional line features along the word. The analysis of the feature space is carried out using the Fisher linear discriminant method. The identification performance is assessed using neural networks, where the simplest neural structures are sought. The capabilities of these simple neural structures are investigated theoretically concerning the achieved separability into the feature space. The identification capabilities of the neural networks are further assessed using the leave-one-out method. It is proved that the neural methods achieve identification performance that approaches 100%. The significance of the proposed method is that it is the only one in the literature that presents high identification performance using only one short word. Furthermore, the features used as well as the classifiers are simple and robust. The method is independent of the language used regardless of the direction of writing. The NIST database is used for extracting short-length words having only three letters each. Full article

(This article belongs to the Special Issue Advances in Natural Computing: Methods and Application)

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3 pages, 195 KiB

Open AccessEditorial

Special Issue on Applications of Speech and Language Technologies in Healthcare

by Inma Hernáez-Rioja, Jose A. Gonzalez-Lopez and Heidi Christensen

Appl. Sci. 2023, 13(11), 6840; https://doi.org/10.3390/app13116840 - 5 Jun 2023

Viewed by 1130

Abstract

In recent years, the exploration and uptake of digital health technologies have advanced rapidly with a real potential impact to revolutionise healthcare delivery and associated industries [...] Full article

(This article belongs to the Special Issue Applications of Speech and Language Technologies in Healthcare)

22 pages, 7226 KiB

Open AccessArticle

A Malware Detection and Extraction Method for the Related Information Using the ViT Attention Mechanism on Android Operating System

by Jeonggeun Jo, Jaeik Cho and Jongsub Moon

Appl. Sci. 2023, 13(11), 6839; https://doi.org/10.3390/app13116839 - 5 Jun 2023

Cited by 10 | Viewed by 2196

Abstract

Artificial intelligence (AI) is increasingly being utilized in cybersecurity, particularly for detecting malicious applications. However, the black-box nature of AI models presents a significant challenge. This lack of transparency makes it difficult to understand and trust the results. In order to address this, [...] Read more.

Artificial intelligence (AI) is increasingly being utilized in cybersecurity, particularly for detecting malicious applications. However, the black-box nature of AI models presents a significant challenge. This lack of transparency makes it difficult to understand and trust the results. In order to address this, it is necessary to incorporate explainability into the detection model. There is insufficient research to provide reasons why applications are detected as malicious or explain their behavior. In this paper, we propose a method of a Vision Transformer(ViT)-based malware detection model and malicious behavior extraction using an attention map to achieve high detection accuracy and high interpretability. Malware detection uses a ViT-based model, which takes an image as input. ViT offers a significant advantage for image detection tasks by leveraging attention mechanisms, enabling robust interpretation and understanding of the intricate patterns within the images. The image is converted from an application. An attention map is generated with attention values generated during the detection process. The attention map is used to identify factors that the model deems important. Class and method names are extracted and provided based on the identified factors. The performance of the detection was validated using real-world datasets. The malware detection accuracy was 80.27%, which is a high level of accuracy compared to other models used for image-based malware detection. The interpretability was measured in the same way as the F1-score, resulting in an interpretability score of 0.70. This score is superior to existing interpretable machine learning (ML)-based methods, such as Drebin, LIME, and XMal. By analyzing malicious applications, we also confirmed that the extracted classes and methods are related to malicious behavior. With the proposed method, security experts can understand the reason behind the model’s detection and the behavior of malicious applications. Given the growing importance of explainable artificial intelligence in cybersecurity, this method is expected to make a significant contribution to this field. Full article

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17 pages, 8897 KiB

Open AccessArticle

A DEM Study on Bearing Behavior of Floating Geosynthetic-Encased Stone Column in Deep Soft Clays

by Feng Liu, Panpan Guo, Xunjian Hu, Baojian Li, Haibo Hu and Xiaonan Gong

Appl. Sci. 2023, 13(11), 6838; https://doi.org/10.3390/app13116838 - 5 Jun 2023

Viewed by 1224

Abstract

The use of geosynthetic-encased stone columns has been proven to be an economical and effective method for soft soil foundation treatment. This method is widely used in civil engineering projects at home and abroad. When the geosynthetic-encased stone columns are applied to deep [...] Read more.

The use of geosynthetic-encased stone columns has been proven to be an economical and effective method for soft soil foundation treatment. This method is widely used in civil engineering projects at home and abroad. When the geosynthetic-encased stone columns are applied to deep soft clays, they are in a floating state. The load-bearing deformation mechanism of geosynthetic-encased stone columns has changed. The interaction between the aggregates, geogrid, and soil is worth studying, especially at the bottom of the column. In this paper, the discrete element method is used to simulate a floating geosynthetic-encased stone column with a 280 mm encasement depth in deep soft clays. The load-bearing deformation characteristics and mesoscopic mechanism of the floating geosynthetic-encased stone column are studied. The results show that there are large vertical and radial stresses in the top region. Moreover, the porosity and sliding fraction of aggregates in this region increase with settlement, and the coordination number decreases with settlement. The vertical and radial stresses of the soil near the column body are not affected much by the column body. When the encasement depth exceeds 280 mm, the bearing capacity of the FGESC does not increase much. The encasement depth controls the failure mode of the floating geosynthetic-encased stone column. As the encasement depth increases, the failure mode of the floating geosynthetic-encased stone column gradually transitions from swelling deformation to penetration failure. Full article

(This article belongs to the Topic New Trends in Rock Materials Mechanics and Engineering Geology)

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23 pages, 19345 KiB

Open AccessArticle

Mechanisms for the Formation of an Exceptionally Gently Inclined Basal Shear Zone of a Landslide in Glacial Sediments—The Ludoialm Case Study

by Xiaoru Dai, Barbara Schneider-Muntau, Julia Krenn, Christian Zangerl and Wolfgang Fellin

Appl. Sci. 2023, 13(11), 6837; https://doi.org/10.3390/app13116837 - 5 Jun 2023

Cited by 5 | Viewed by 1561

Abstract

The Ludoialm landslide, which is located in the municipality of Münster in Tyrol, Austria, represents a large-scale translational landslide in glacial soil sediments characterised by an exceptionally low inclined basal shear zone of only 12

^{°}

. Although a temporal coincidence between meteorological [...] Read more.

The Ludoialm landslide, which is located in the municipality of Münster in Tyrol, Austria, represents a large-scale translational landslide in glacial soil sediments characterised by an exceptionally low inclined basal shear zone of only 12

^{°}

. Although a temporal coincidence between meteorological events and slope displacement is obvious, the hydromechanical coupled processes responsible for the initial landslide formation and the ongoing movement characteristics have not yet been identified. This article provides a comprehensive analysis of the predisposition factors and the initial failure mechanism of this landslide from geological and geotechnical perspectives. We use a prefailure geometry of the cross section to simulate the initial slope failure process by a limit equilibrium analysis (LEA), a strength-reduction finite element method (SRFEM), and a finite element limit analysis (FELA). The shape and location of the computationally obtained basal sliding zone compare well with the geologically assumed one. Based on the computational study, it turns out that a high groundwater table probably caused by snow melting in combination with different permeabilities for the different layers is needed for the formation of the exceptionally low inclined basal shear zone. This paper presents the failure mechanism of the Ludoialm landslide and discusses the role of the shear band propagation in the process of slope destabilization. Full article

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14 pages, 2376 KiB

Open AccessArticle

Study on Stress and Displacement of Axisymmetric Circular Loess Tunnel Surrounding Rock Based on Joint Strength

by Rongjin Li, Weishi Bai, Rongjian Li and Jinshuo Jiang

Appl. Sci. 2023, 13(11), 6836; https://doi.org/10.3390/app13116836 - 5 Jun 2023

Cited by 1 | Viewed by 1259

Abstract

The development of an effective evaluation method suitable for loess-tunnel excavation is necessary to avoid the collapse accidents caused by tunnel excavation and any secondary disasters. Although the Fenner formulas and the modified Fenner formulas are widely used in tunnel engineering, a defect [...] Read more.

The development of an effective evaluation method suitable for loess-tunnel excavation is necessary to avoid the collapse accidents caused by tunnel excavation and any secondary disasters. Although the Fenner formulas and the modified Fenner formulas are widely used in tunnel engineering, a defect still exists in these formulas because the Mohr–Coulomb (M–C) criterion exaggerates the tensile strength of the surrounding rock of the loess tunnel. A newly modified Fenner formula was derived based on joint strength to overcome this deficiency. First, the expressions of stress and the radius of the plastic zone of the surrounding rock of the loess tunnel and the expressions of radial displacement were derived based on the stress-equilibrium equation of the axisymmetric plane and the joint strength. Then, the difference in the modified Fenner formulas based on the two kinds of strength criteria for the loess tunnel were compared. The results showed that the radius of the plastic zone and the radial displacement of the loess tunnel determined by the modified Fenner formula based on joint strength were larger than those determined by the modified Fenner formula based on M–C strength. However, the plastic stress of the plastic zone determined by the modified Fenner formula based on joint strength was smaller. The comparative analysis reveals that the modified Fenner formula based on joint strength can evaluate the stress and plastic-displacement field of the surrounding rock of a loess tunnel more reasonably. Full article

(This article belongs to the Special Issue Advanced Research on Tunnel Slope Stability and Land Subsidence)

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14 pages, 6806 KiB

Open AccessArticle

Characterizing Crustal Deformation of the Weihe Fault, Weihe Basin (Central China), Using InSAR and GNSS Observations

by Qin-Hu Tian, Wen-Ting Zhang and Wu Zhu

Appl. Sci. 2023, 13(11), 6835; https://doi.org/10.3390/app13116835 - 5 Jun 2023

Cited by 3 | Viewed by 1538

Abstract

The Weihe Fault is an important basement fault that is buried deep and controls the formation, evolution, and seismicity of the Weihe Basin. It has been quiescent for more than 300 years with only a few moderate and small earthquakes distributed unevenly. Therefore, [...] Read more.

The Weihe Fault is an important basement fault that is buried deep and controls the formation, evolution, and seismicity of the Weihe Basin. It has been quiescent for more than 300 years with only a few moderate and small earthquakes distributed unevenly. Therefore, it is necessary to investigate the current tectonic deformation pattern in order to assess regional seismic risk. In this context, the tectonic deformation velocities of the Weihe Fault were analyzed using an interferometric synthetic aperture radar (InSAR), a global navigation satellite system (GNSS) and leveling observations. The line of slight (LOS) deformation rates spanning from 2015 to 2019 were estimated from stacking-InSAR technology. Subsequently, the three-dimensional deformation rates in the north–south, east–west, and vertical directions were separated through the integration of GNSS-derived horizontal deformation and InSAR-derived LOS deformation. After that, the long-wavelength tectonic deformation was decomposed from the separated vertical deformation based on the spherical wavelet multiscale approach. Finally, the slip rate and locking depth were inverted for the assessment of the seismic hazard and tectonic activity of the Weihe Fault. The results show that the separated vertical deformation is consistent with the leveling observations, where the standard deviation between them is 1.69 mm/yr and the mean value is 0.6 mm/yr, demonstrating the reliability of the proposed method. The decomposed long-wavelength tectonic deformation exhibits uplift in the north and subsidence in the south, as well as the obvious vertical velocity gradient. The inversion result shows that the slip rate of the Weihe Fault gradually decreases from the west to the east, and the dip gradually increases from the west to the east, indicating a segmented activity and the geometric characteristics of the fault. The locking depth of the Weihe Fault gradually increases from the west (~5 km) to the east (~14 km), implying a higher stress accumulation and seismic risk on the eastern section of the fault. Taking into account the higher locking depth and frequent historical earthquakes on the eastern section of the Weihe Fault, further attention should be paid to the earthquake risk of the eastern section of the Weihe Fault. Full article

(This article belongs to the Special Issue Remote Sensing Technology in Landslide and Land Subsidence)

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12 pages, 5104 KiB

Open AccessArticle

Parallel-Coupled-Line Bandpass Filter with Notch for Ultra-Wideband (UWB) Applications

by Faris H. Almansour, Geamel H. Alyami and Hussein N. Shaman

Appl. Sci. 2023, 13(11), 6834; https://doi.org/10.3390/app13116834 - 5 Jun 2023

Cited by 5 | Viewed by 1984

Abstract

A compact parallel-coupled-line microstrip bandpass filter with a very wideband passband and a narrow notched band is demonstrated in this paper. The presented bandpass filter was constructed from one section of three parallel-coupled-lines which has a length of a quarter wavelength at a [...] Read more.

A compact parallel-coupled-line microstrip bandpass filter with a very wideband passband and a narrow notched band is demonstrated in this paper. The presented bandpass filter was constructed from one section of three parallel-coupled-lines which has a length of a quarter wavelength at a midband frequency of 6.9 GHz. For the purpose of increasing the filter selectivity, the middle line is extended by a length of a quarter-wavelength and connected at one end to the ground plane. Therefore, a transmission zero was generated at each side of the passband which effectively improved the filter performance. In addition, a narrow notched band at a precise frequency inside the proposed passband was exhibited by placing a stepped-impedance resonator near the parallel-coupled-line for blocking the unwanted radio signal. The proposed filter was designed, simulated, fabricated, and measured. The fabricated filter has a very compact circuit size and its measured response shows an excellent agreement with the simulated results. Full article

(This article belongs to the Section Electrical, Electronics and Communications Engineering)

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12 pages, 940 KiB

Open AccessArticle

Feature Extracted Deep Neural Collaborative Filtering for E-Book Service Recommendations

by Ji-Yoon Kim and Chae-Kwan Lim

Appl. Sci. 2023, 13(11), 6833; https://doi.org/10.3390/app13116833 - 5 Jun 2023

Cited by 3 | Viewed by 1440

Abstract

The electronic publication market is growing along with the electronic commerce market. Electronic publishing companies use recommendation systems to increase sales to recommend various services to consumers. However, due to data sparsity, the recommendation systems have low accuracy. Also, previous deep neural collaborative [...] Read more.

The electronic publication market is growing along with the electronic commerce market. Electronic publishing companies use recommendation systems to increase sales to recommend various services to consumers. However, due to data sparsity, the recommendation systems have low accuracy. Also, previous deep neural collaborative filtering models utilize various variables of datasets such as user information, author information, and book information, and these models have the disadvantage of requiring significant computing resources and training time for their training. To address this issue, we propose a deep neural collaborative filtering model with feature extraction that uses minimal data such as user number, book number, and rating information. The proposed model comprises an input layer for inputting and embedding the product and user data, a feature extraction layer for extracting the features through data correlation analysis between the embedded user and product data, a multilayer perceptron, and an output layer. To improve the performance of the proposed model, Bayesian optimization was used to determine hyperparameters. To evaluate the deep neural collaborative filtering model with feature extraction, a comparative analysis experiment was conducted with currently used collaborative filtering models. The goodbooks-10k public dataset was used, and the results of the experiment show that the low accuracy caused by data sparsity was considerably improved. Full article

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16 pages, 8140 KiB

Open AccessArticle

Research on Cutting Temperature of GH4169 Turning with Micro-Textured Tools

by Xinmin Feng, Xiwen Fan, Jingshu Hu and Jiaxuan Wei

Appl. Sci. 2023, 13(11), 6832; https://doi.org/10.3390/app13116832 - 5 Jun 2023

Cited by 4 | Viewed by 1392

Abstract

The GH4169 superalloy has the characteristics of high strength, strong thermal stability, large specific heat capacity, small thermal conductivity, etc., but it is also a typical hard-to-cut material. When cutting this material with ordinary cutting tools, the cutting force is large, and the [...] Read more.

The GH4169 superalloy has the characteristics of high strength, strong thermal stability, large specific heat capacity, small thermal conductivity, etc., but it is also a typical hard-to-cut material. When cutting this material with ordinary cutting tools, the cutting force is large, and the cutting temperature is high, which leads to severe tool wear and short service life. In order to improve the performance of tools when cutting GH4169, reduce the cutting temperature, and extend the service life of the tool, micro-textured tools were used to cut GH4169 in spray cooling. The effects of micro-texture morphology and dimensional parameters on cutting temperature were analyzed. Firstly, tools with micro-textures of five different morphologies were designed near the nose on the rake face of the cemented carbide tools. The three-dimensional cutting models of the micro-textured tools with different morphologies were established by using ABAQUS, and a simulation analysis was carried out. Compared with the non-textured tools, the micro-texture morphology with the lowest cutting temperature was selected according to the simulation results of the cutting temperature. Secondly, based on the optimized morphology, tools with micro-textures of different size parameters were designed. When cutting GH4169, the cutting temperature of the tools was simulated and analyzed, and the size parameters of the micro-textured tools with the lowest cutting temperature were selected as well. Finally, the designed micro-textured tools were processed and applied in cutting experiments. The simulation model was verified in the experiments, and the influence of size parameters of micro-textures on the cutting temperature was analyzed. This paper provides a theoretical reference and basis for cutting GH4169 and the design and application of micro-textured tools. Full article

(This article belongs to the Special Issue Advanced Manufacturing and Precision Machining)

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14 pages, 544 KiB

Open AccessArticle

A Blockchain-Based Cooperative Authentication Mechanism for Smart Grid

by Yunfa Li, Di Zhang, Zetian Wang and Guanxu Liu

Appl. Sci. 2023, 13(11), 6831; https://doi.org/10.3390/app13116831 - 5 Jun 2023

Cited by 4 | Viewed by 1367

Abstract

With the advancement of smart devices, the operation and communication of smart grids have become increasingly efficient. Many smart devices such as smart meters, smart transformers, and smart grid controllers are already widely used in smart grids. Thus, a series of complex architectures [...] Read more.

With the advancement of smart devices, the operation and communication of smart grids have become increasingly efficient. Many smart devices such as smart meters, smart transformers, and smart grid controllers are already widely used in smart grids. Thus, a series of complex architectures and a series of communication modes have been formed. However, these smart devices will be exposed to various cyber attacks such as distributed denial of service (DDoS) attack and replay attack. This is because they are open and dynamic. Therefore, there are serious security problems in the complex architectures and the communication modes. In this paper, we propose a multi-domain authentication mechanism based on blockchain cooperation to maintain the security of smart devices. In this mechanism, we propose a series of methods and algorithms, which include initialization method based on blockchain cooperative authentication, dynamic change method of intelligent devices and information, cross-domain authentication algorithm, and cross-domain key cooperative algorithm. To demonstrate the security and effectiveness of our proposed mechanism, we analysed its security and conducted a series of simulation experiments. The analysis and simulation experiments show that our proposed approach is secure and effective. Full article

(This article belongs to the Special Issue Research Progress on Cyber-Physical Distribution System)

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