Journal Description
Applied Sciences
Applied Sciences
is an international, peer-reviewed, open access journal on all aspects of applied natural sciences published semimonthly online by MDPI.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, SCIE (Web of Science), Inspec, CAPlus / SciFinder, and other databases.
- Journal Rank: JCR - Q2 (Engineering, Multidisciplinary) / CiteScore - Q1 (General Engineering)
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 16.9 days after submission; acceptance to publication is undertaken in 2.6 days (median values for papers published in this journal in the second half of 2023).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
- Testimonials: See what our authors say about Applied Sciences.
- Companion journals for Applied Sciences include: Applied Nano, AppliedChem, Applied Biosciences, Virtual Worlds, Spectroscopy Journal and JETA.
Impact Factor:
2.7 (2022);
5-Year Impact Factor:
2.9 (2022)
Latest Articles
Investigating the Effects of Virtual Reality-Based Training on Balance Ability and Balance Confidence in Older Individuals
Appl. Sci. 2024, 14(11), 4581; https://doi.org/10.3390/app14114581 (registering DOI) - 27 May 2024
Abstract
Each year, over 25% of adults aged sixty-five years old or older suffer a fall, and three million are treated for fall-related injuries due to lack of balance. Here, we aimed to investigate how virtual reality (VR)-based training affects balance performance and confidence
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Each year, over 25% of adults aged sixty-five years old or older suffer a fall, and three million are treated for fall-related injuries due to lack of balance. Here, we aimed to investigate how virtual reality (VR)-based training affects balance performance and confidence in older adults. To accomplish this goal, we studied 21 healthy, older individuals between 60 and 85 years old, both pre- and post-training (6 weeks of training, twice per week (or 12 sessions)). The VR group donned an Oculus VR headset and consisted of nine participants (aged 75.9 3.7 years old), while the control group (aged 75.1 6.7 years old) performed training without a headset and consisted of eight participants that completed our study. To assess balance ability, we utilized the Balance Error Scoring System (BESS) and the Timed Up and Go (TUG) test. To assess balance confidence, we implemented the Activities-Specific Balance Confidence (ABC) Scale and, to assess fear of falling, the Tinetti Falls Efficacy Scale (FES). Further, we assessed depression (via the Geriatric Depression Scale (GDS)) and cognitive ability (via the Mini-Mental State Examination (MMSE)). The post-training results showed improvements in balance ability for both the VR and control groups, as well as changes in the relationship between balance confidence and balance ability for the VR group only. Further, improvements in cognitive ability were seen in the control group. This study is an indication that older individuals’ balance ability may benefit from several weeks of targeted training.
Full article
(This article belongs to the Special Issue The Use of Virtual Reality (VR) in Medical Rehabilitation: Assessment Tools, Application Methods, VR Technology and Clinical Applications)
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Open AccessArticle
Evaluating Acceptance of Novel Vehicle-Mounted Perfume Automatic Dispersal Device for Fatigued Drivers
by
Yanqun Yang, Xinli Wu, Linwei Wang, Said M. Easa and Xinyi Zheng
Appl. Sci. 2024, 14(11), 4580; https://doi.org/10.3390/app14114580 (registering DOI) - 27 May 2024
Abstract
This paper evaluates the influence of different variables on drivers’ willingness to accept and use a vehicle-mounted perfume automatic dispersal device (VP-ADD) connected to the vehicle’s electronic map. Based on the technical acceptance model, we clarify and condense the explanation of the model
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This paper evaluates the influence of different variables on drivers’ willingness to accept and use a vehicle-mounted perfume automatic dispersal device (VP-ADD) connected to the vehicle’s electronic map. Based on the technical acceptance model, we clarify and condense the explanation of the model used to evaluate the impact of user behavior attitudes and device characteristics on six factors, perceived usefulness, perceived ease of use, attitude towards use, intention to use, perceived playfulness, and perceived risk, proposing eight hypotheses. Then, we assessed the responses of 562 drivers in China using SPSS for reliability and validity and AMOS for structural equation modeling to test our hypotheses. The findings reveal that the perceived usefulness, ease of use, playfulness, and risk significantly affected the willingness to accept and use the VP-ADD. Furthermore, the perceived risk has a negative influence, while the perceived usefulness, perceived ease of use, perceived playfulness, and attitude towards use have a positive influence. This research is significant for further development and application of the VP-ADD. It is essential to alleviate driver fatigue, ensure traffic safety, and provide theoretical and empirical support for designing more popular driving assistance devices. Furthermore, it offers valuable insights for developing fatigue driving warning policies, in-vehicle device guidelines, and traffic safety regulations.
Full article
(This article belongs to the Special Issue Ergonomics and Human Factors in Transportation Systems)
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Ransomware Detection Model Based on Adaptive Graph Neural Network Learning
by
Jun Li, Gengyu Yang and Yanhua Shao
Appl. Sci. 2024, 14(11), 4579; https://doi.org/10.3390/app14114579 (registering DOI) - 27 May 2024
Abstract
Ransomware is a type of malicious software that encrypts or locks user files and demands a high ransom. It has become a major threat to cyberspace security, especially as it continues to be developed and updated at exponential rates. Ransomware detection technology has
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Ransomware is a type of malicious software that encrypts or locks user files and demands a high ransom. It has become a major threat to cyberspace security, especially as it continues to be developed and updated at exponential rates. Ransomware detection technology has become a focus of research on information security risk detection methods. However, current ransomware detection techniques have high false positive and false negative rates, and traditional methods ignore global word co-occurrence and correlation information between key node steps in the entire process. This poses a significant challenge for accurately identifying and detecting ransomware. We propose a ransomware detection model based on co-occurrence information adaptive diffusion learning using a Text Graph Convolutional Network (ADC-TextGCN). Specifically, ADC-TextGCN first assign self-weights to word nodes based on sensitive API call functions and preserve co-occurrence information using Point Mutual Information Theory (COIR-PMI); then our model automatically learn the optimal neighborhood through an Adaptive Diffusion Convolution (ADC) strategy, thereby improving the ability to aggregate long-distance node information across layers and enhancing the network’s ability to represent ransomware behavior. Experimental results show that our method achieves an accuracy of over 96.6% in ransomware detection, proving its effectiveness and superiority compared to traditional methods based on CNN and RNN in ransomware detection.
Full article
(This article belongs to the Special Issue Advances and Challenges in the Next-Generation Internet of Things (IoT))
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Automated Assessment Tool for 3D Computer-Aided Design Models
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Ameni Eltaief, Sabrine Ben Amor, Borhen Louhichi, Nashmi H. Alrasheedi and Abdennour Seibi
Appl. Sci. 2024, 14(11), 4578; https://doi.org/10.3390/app14114578 (registering DOI) - 27 May 2024
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Computer-aided design (CAD) has become an integral part of engineering education, particularly for those studying mechanical engineering. By providing practical skills that are highly valued in the engineering industry, proficiency in CAD systems enhances students’ employability. Generally, CAD systems provide students with the
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Computer-aided design (CAD) has become an integral part of engineering education, particularly for those studying mechanical engineering. By providing practical skills that are highly valued in the engineering industry, proficiency in CAD systems enhances students’ employability. Generally, CAD systems provide students with the tools and knowledge necessary to excel in their engineering education and future careers. In order to help teachers to give the best training to their students and to make the right evaluations, an automatized tool is needed to support the evaluation of CAD models during training sessions. After an extensive bibliographical search, this paper proposes a CAD Model Automatized Assessment (MAA) Tool for mechanical courses called the CAD MAA Tool. This tool is mainly based on a developed model that takes into account different aspects of modeling, such as geometric, feature-based, and parametric modeling. To correctly evaluate a given part compared to a reference one, the proposed model uses different coefficients fixed by the teacher according to their teaching strategies or course objectives.
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Automatic Optimization System for Heat Source Layout of Multi-Chip Components Based on Multi-Software Integration
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Xingxing Huang, Jiangcheng Hu, Yan Ge, Liang Guo, Kang Han and Jiahong Zhang
Appl. Sci. 2024, 14(11), 4577; https://doi.org/10.3390/app14114577 (registering DOI) - 27 May 2024
Abstract
This paper presents an automatic optimization system for the heat source layout of multi-chip modules, referred to as IOS. The system aims to optimize the heat source layout of multi-chip modules through the integration of multiple software tools. The IOS utilizes an optimization
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This paper presents an automatic optimization system for the heat source layout of multi-chip modules, referred to as IOS. The system aims to optimize the heat source layout of multi-chip modules through the integration of multiple software tools. The IOS utilizes an optimization algorithm, WINDOW DOS, and other methods to achieve this goal. Initially, two optimization strategies are introduced which are utilized in conjunction with the Non-dominated Sorting Genetic Algorithm-II(NSGA-II). Subsequently, a simplified thermal model of the multi-chip module is applied to the IOS. The automatic optimization module is then used to optimize the heat source layout. In the end, we simulated and analyzed the application results. The simulation analysis reveals that when the temperature extreme value index is optimized, the PCB board’s transient temperature range falls within [343.14 K, 344.09 K]. Similarly, when the temperature homogeneity index is optimized, the PCB board’s transient temperature range falls within [343.39 K, 344.21 K]. Comparing these results with the experience layout, the temperature difference is reduced by 76.36% and 79.60%, respectively. The optimization results demonstrate that the IOS has a significant impact, offering remarkable optimization effects, low cost, high efficiency, and a more uniform temperature distribution. These findings indicate that the IOS holds promising potential for applications and provides value in optimizing the heat source layout of multi-chip modules.
Full article
(This article belongs to the Section Applied Thermal Engineering)
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Study on the Meso-Failure Mechanism of Granite under Real-Time High Temperature by Numerical Simulation
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Kangwen Li and Fan Zhang
Appl. Sci. 2024, 14(11), 4575; https://doi.org/10.3390/app14114575 (registering DOI) - 27 May 2024
Abstract
In the development of geothermal resources in hot dry rocks, deep underground rock masses are typically subjected to real-time high-temperature environments. High temperatures alter the physical and mechanical properties of the rocks, directly affecting the safe and efficient utilization of hot dry rock
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In the development of geothermal resources in hot dry rocks, deep underground rock masses are typically subjected to real-time high-temperature environments. High temperatures alter the physical and mechanical properties of the rocks, directly affecting the safe and efficient utilization of hot dry rock resources. Therefore, a grain-based model (GBM) of particle flow code (PFC) was constructed based on uniaxial compression tests, and the model was verified according to macroscopic mechanical parameters and damage modes, in order to carry out the simulation study of the uniaxial compression of granite and explore the meso-failure mechanism of granite under real-time high temperature. The relationships between stress–strain curves and crack derivation, the evolution of microcracks, and the characteristics of acoustic emission activity and energy changes at different temperatures were investigated in conjunction with the results of laboratory tests. The results show that crack development, acoustic emission activity, and energy evolution during uniaxial compression include four main stages: initial compression, elasticity, plastic strengthening, and post-peak damage. The failure of granite is primarily controlled by mica and feldspar. During loading, intergranular tensile cracks first emerge within the granite, followed by intragranular tensile cracks, with shear cracks appearing last. As the temperature increases, the total number of microcracks continuously rises, the frequency of acoustic emission events increases, and both dissipated energy and boundary energy gradually decrease, showing an upward trend in the energy dissipation ratio, indicating an increase in thermal damage due to high temperatures. At 400 °C, the rate of microcrack formation increases significantly, with intergranular and intragranular cracks starting to coalesce into macroscopic cracks that extend outward. In the post-peak stage, the phenomenon of multiple peaks in acoustic emission events begins to appear. At 600 °C, the rate of microcrack formation reaches its maximum, with cracks extending throughout the sample to form a network of fractures, resulting in the granite exhibiting ductile failure characteristics.
Full article
(This article belongs to the Special Issue Advances and Challenges in Rock Mechanics and Rock Engineering)
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Re-Evaluating the Long-Term Efficacy of Semi-Rigid Fixation Using a Nitinol Spring Rod in Lumbar Surgery: A Retrospective Study on an Effective Alternative for Reducing Adjacent Segment Disease
by
Hyun-Jun Jang, Bong-Ju Moon and Dong-Kyu Chin
Appl. Sci. 2024, 14(11), 4574; https://doi.org/10.3390/app14114574 (registering DOI) - 27 May 2024
Abstract
Adjacent segment disease (ASD) is a prevalent complication following lumbar fusion surgery, representing a significant challenge in spinal surgery. This study aimed to assess the long-term outcomes of Nitinol spring rod semi-rigid fixation, a potential alternative to traditional rigid fixation, in reducing the
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Adjacent segment disease (ASD) is a prevalent complication following lumbar fusion surgery, representing a significant challenge in spinal surgery. This study aimed to assess the long-term outcomes of Nitinol spring rod semi-rigid fixation, a potential alternative to traditional rigid fixation, in reducing the incidence of ASD. This retrospective case study evaluated 89 patients who underwent lumbar or lumbosacral surgeries using a combination of Bioflex® (a Nitinol spring rod dynamic stabilization system) and an interbody cage over 10 years of follow-up. The fusion status, adjacent segment disc height, mechanical complications, and re-operation rates were analyzed. The cohort had a median follow-up duration of 13.0 years. All patients achieved solid fusion at the final follow-up visit. One patient underwent revision surgery for clinical ASD (1.1%), and no patients required revision surgery due to mechanical problems. Radiological evidence of ASD was observed in 16.9% of the patients. This study’s findings suggest that semi-rigid fixation using Bioflex with an interbody cage is a possibly effective treatment strategy to prevent ASD. The technique potentially reduces the risk of ASD by allowing a degree of movement at the surgical site.
Full article
(This article belongs to the Special Issue Advances in Orthopedic Diseases Treatment)
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Exploring the Effectiveness of the Phase Features on Double Compressed AMR Speech Detection
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Aykut Büker and Cemal Hanilçi
Appl. Sci. 2024, 14(11), 4573; https://doi.org/10.3390/app14114573 (registering DOI) - 26 May 2024
Abstract
Determining whether an audio signal is single compressed (SC) or double compressed (DC) is a crucial task in audio forensics, as it is closely linked to the integrity of the recording. In this paper, we propose the utilization of phase spectrum-based features for
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Determining whether an audio signal is single compressed (SC) or double compressed (DC) is a crucial task in audio forensics, as it is closely linked to the integrity of the recording. In this paper, we propose the utilization of phase spectrum-based features for detecting DC narrowband and wideband adaptive multi-rate (AMR-NB and AMR-WB) speech. To the best of our knowledge, phase spectrum features have not been previously explored for DC audio detection. In addition to introducing phase spectrum features, we propose a novel parallel LSTM system that simultaneously learns the most representative features from both the magnitude and phase spectrum of the speech signal and integrates both sets of information to further enhance its performance. Analyses demonstrate significant differences between the phase spectra of SC and DC speech signals, suggesting their potential as representative features for DC AMR speech detection. The proposed phase spectrum features are found to perform as well as magnitude spectrum features for the AMR-NB codec, while outperforming the magnitude spectrum in detecting AMR-WB speech. The proposed phase spectrum features yield 8% performance improvement in terms of true positive rate over the magnitude spectrogram features. The proposed parallel LSTM system further improves DC AMR-WB speech detection.
Full article
(This article belongs to the Section Computing and Artificial Intelligence)
Open AccessArticle
Synthesis of Non-Linguistic Utterances for Sound Design Support Using a Genetic Algorithm
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Ahmed Khota, Eric W. Cooper and Yu Yan
Appl. Sci. 2024, 14(11), 4572; https://doi.org/10.3390/app14114572 (registering DOI) - 26 May 2024
Abstract
As social robots become more prevalent, they often employ non-speech sounds, in addition to other modes of communication, to communicate emotion and intention in an increasingly complex visual and audio environment. These non-speech sounds are usually tailor-made, and research into the generation of
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As social robots become more prevalent, they often employ non-speech sounds, in addition to other modes of communication, to communicate emotion and intention in an increasingly complex visual and audio environment. These non-speech sounds are usually tailor-made, and research into the generation of non-speech sounds that can convey emotions has been limited. To enable social robots to use a large amount of non-speech sounds in a natural and dynamic way, while expressing a wide range of emotions effectively, this work proposes an automatic method of sound generation using a genetic algorithm, coupled with a random forest model trained on representative non-speech sounds to validate each produced sound’s ability to express emotion. The sounds were tested in an experiment wherein subjects rated the perceived valence and arousal. Statistically significant clusters of sounds in the valence arousal space corresponded to different emotions, showing that the proposed method generates sounds that can readily be used in social robots.
Full article
(This article belongs to the Special Issue Intelligent Robotics: Design and Applications)
Open AccessArticle
Influence of Non-Ionic Surfactant and Silver on the Photocatalytic Activity of TiO2 Films for Degradation of Dyes in Distilled and Tap Water
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Dobrina Ivanova, Elisaveta Mladenova and Nina Kaneva
Appl. Sci. 2024, 14(11), 4571; https://doi.org/10.3390/app14114571 (registering DOI) - 26 May 2024
Abstract
This study describes the impact of surfactant molecular weights (PEG 2000 and PEG 4000) on the photocatalytic activity of TiO2 films, deposited via dip-coating from a PEG-stabilized suspension and silver-functionalized photo-fixation of Ag+ under UV illumination. The photocatalytic activity of pure
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This study describes the impact of surfactant molecular weights (PEG 2000 and PEG 4000) on the photocatalytic activity of TiO2 films, deposited via dip-coating from a PEG-stabilized suspension and silver-functionalized photo-fixation of Ag+ under UV illumination. The photocatalytic activity of pure and Ag/TiO2 films is assessed in the aqueous-phase degradation of Malachite green and Methylene blue in distilled and tap water under UV and visible illumination. The results indicate a positive effect of both the higher-molecular-weight non-ionic surfactant and Ag-functionalization yield higher photocatalytic efficiency. Notably, films photo-fixed with 10−2 M Ag+ show the highest degradation percentages in all experimental conditions. A direct correlation between the concentration of Ag+ ions and the enhancement of the photocatalytic activity is revealed: pure TiO2 < Ag, 10−4/TiO2 < Ag, 10−3/TiO2 < Ag, 10−2/TiO2. Flame atomic absorption spectrometry is used to study the Ag+ leeching from the Ag/TiO2 films. The structural properties of the nanostructures are investigated through scanning electron microscopy, Brunauer–Emmett–Teller analysis, energy-dispersive X-ray spectroscopy, and X-ray diffraction. Additionally, after three cycles of operation, Ag, 10−2/TiO2 (PEG 4000) films can maintain their photocatalytic activity, suggesting a potential application in the treatment of dye wastewater.
Full article
(This article belongs to the Special Issue Environmental Catalysis and Green Chemistry)
Open AccessArticle
Implementation of a Generative AI Algorithm for Virtually Increasing the Sample Size of Clinical Studies
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Anastasios Nikolopoulos and Vangelis D. Karalis
Appl. Sci. 2024, 14(11), 4570; https://doi.org/10.3390/app14114570 (registering DOI) - 26 May 2024
Abstract
Determining the appropriate sample size is crucial in clinical studies due to the potential limitations of small sample sizes in detecting true effects. This work introduces the use of Wasserstein Generative Adversarial Networks (WGANs) to create virtual subjects and reduce the need for
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Determining the appropriate sample size is crucial in clinical studies due to the potential limitations of small sample sizes in detecting true effects. This work introduces the use of Wasserstein Generative Adversarial Networks (WGANs) to create virtual subjects and reduce the need for recruiting actual human volunteers. The proposed idea suggests that only a small subset (“sample”) of the true population can be used along with WGANs to create a virtual population (“generated” dataset). To demonstrate the suitability of the WGAN-based approach, a new methodological procedure was also required to be established and applied. Monte Carlo simulations of clinical studies were performed to compare the performance of the WGAN-synthesized virtual subjects (i.e., the “generated” dataset) against both the entire population (the so-called “original” dataset) and a subset of it, the “sample”. After training and tuning the WGAN, various scenarios were explored, and the comparative performance of the three datasets was evaluated, as well as the similarity in the results against the population data. Across all scenarios tested, integrating WGANs and their corresponding generated populations consistently exhibited superior performance compared with those from samples alone. The generated datasets also exhibited quite similar performance compared with the “original” (i.e., population) data. By introducing virtual patients, WGANs effectively augment sample size, reducing the risk of type II errors. The proposed WGAN approach has the potential to decrease costs, time, and ethical concerns associated with human participation in clinical trials.
Full article
(This article belongs to the Special Issue Applications of Artificial Intelligence in Biomedical Data Analysis)
Open AccessArticle
Research on the Construction of a Blockchain-Based Industrial Product Full Life Cycle Information Traceability System
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Leifeng Xiao, Wenlei Sun, Saike Chang, Cheng Lu and Renben Jiang
Appl. Sci. 2024, 14(11), 4569; https://doi.org/10.3390/app14114569 (registering DOI) - 26 May 2024
Abstract
The application of blockchain technology in industrial product quality traceability is analyzed to construct a new model of product quality traceability that is mainly based on blockchain technology and supplemented by an identity system. The blockchain-enabled overall technical architecture of an industrial product
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The application of blockchain technology in industrial product quality traceability is analyzed to construct a new model of product quality traceability that is mainly based on blockchain technology and supplemented by an identity system. The blockchain-enabled overall technical architecture of an industrial product quality traceability system is explored, and a blockchain-based industrial product full life cycle information traceability system is constructed. First, the weights of the information indicators of different links of the industrial equipment information traceability system were calculated using the EAHP hierarchical analysis method. The manufacturing link had the largest weight, with a value of 18.8%. Second, the system’s functional module design is based on the weights. We designed and developed the industrial product information traceability platform based on the hybrid blockchain chain structure of private chain + alliance chain. Finally, a manufacturing enterprise in the Xinjiang region is taken as the research object, query validation is carried out for the products produced by the enterprise, and the average query time of the system is measured to be 65.376 ms. It can meet the traceability needs of consumers and enterprise users. The research can provide theoretical support and reference for the whole life cycle information traceability of industrial products.
Full article
Open AccessArticle
Removal of Color-Document Image Show-Through Based on Self-Supervised Learning
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Mengying Ni, Zongbao Liang and Jindong Xu
Appl. Sci. 2024, 14(11), 4568; https://doi.org/10.3390/app14114568 (registering DOI) - 26 May 2024
Abstract
Show-through phenomena have always been a challenging issue in color-document image processing, which is widely used in various fields such as finance, education, and administration. Existing methods for processing color-document images face challenges, including dealing with double-sided documents with show-through effects, accurately distinguishing
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Show-through phenomena have always been a challenging issue in color-document image processing, which is widely used in various fields such as finance, education, and administration. Existing methods for processing color-document images face challenges, including dealing with double-sided documents with show-through effects, accurately distinguishing between foreground and show-through parts, and addressing the issue of insufficient real image data for supervised training. To overcome these challenges, this paper proposes a self-supervised-learning-based method for removing show-through effects in color-document images. The proposed method utilizes a two-stage-structured show-through-removal network that incorporates a double-cycle consistency loss and a pseudo-similarity loss to effectively constrain the process of show-through removal. Moreover, we constructed two datasets consisting of different show-through mixing ratios and conducted extensive experiments to verify the effectiveness of the proposed method. Experimental results demonstrate that the proposed method achieves competitive performance compared to state-of-the-art methods and can effectively perform show-through removal without the need for paired datasets. Specifically, the proposed method achieves an average PSNR of 33.85 dB on our datasets, outperforming comparable methods by a margin of 0.89 dB.
Full article
(This article belongs to the Special Issue AI-Based Image Processing: 2nd Edition)
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A Quantitative and Qualitative Analysis of the Lubricity of Used Lubricating Oil Diluted with Diesel Oil
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Leszek Chybowski, Marcin Szczepanek, Robert Sztangierski and Piotr Brożek
Appl. Sci. 2024, 14(11), 4567; https://doi.org/10.3390/app14114567 (registering DOI) - 26 May 2024
Abstract
Experience shows that dilution of lubricating oil with diesel oil is unfavorable to the engine, causing issues including deterioration of engine performance, shortening of oil life, and reduction in engine reliability and safety. This paper presents the verification of the hypothesis that the
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Experience shows that dilution of lubricating oil with diesel oil is unfavorable to the engine, causing issues including deterioration of engine performance, shortening of oil life, and reduction in engine reliability and safety. This paper presents the verification of the hypothesis that the changes in lubricity, friction coefficient, and decreasing oil film thickness (using a relative approach, given as a percentage) are similar for lubricating oil and diesel mixtures prepared from fresh lubricating oil and used lubricating oil. To validate this hypothesis, an experiment is conducted using a high-frequency reciprocating rig (HFFR), in which the lubricity is determined by the corrected average wear scar WS1.4, the coefficient of friction μ, and the percentage relative decrease in oil film thickness r. A qualitative visual assessment of the wear scars on the test specimens is also performed after the HFFR tests. The testing covers mixtures of SAE 30 grade Marinol CB-30 RG1230 lubricating oil with Orlen Efecta Diesel Biodiesel. The used lubricating oil is extracted from the circulating lubrication system of a supercharged, trunk-piston, four-stroke ZUT Zgoda Sulzer 5 BAH 22 engine installed in the laboratory of ship power plants of the Maritime University of Szczecin. Mixtures for the experiment are prepared for fresh lubricating oil with diesel oil and used lubricating oil with diesel oil. Mixtures of these lubricating oils with diesel oil are examined for diesel oil concentrations in the mixture equal to 1, 2, 5, 10, 15, and 20% m/m. The results of the experiment confirm the hypothesis, proving that, for up to 20% m/m diesel oil concentration in lubricating oil, the changes in the lubricity of used lubricating oil diluted with diesel oil can be evaluated based on reference data prepared for mixtures of diesel oil with fresh lubricating oil. The linear approximation of μ and r trends is made with a certain margin of error we estimated. The experiment also confirms the results of previous studies which state that oil aging products in small quantities contribute to improved lubricity.
Full article
(This article belongs to the Special Issue Digital and Computational Tribology)
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Open AccessArticle
Small-Cell Combs Offer as Favorable Conditions of Rearing Worker Bees as Standard-Cell Combs in the Temperate Climate in Spring
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Piotr Dziechciarz, Aneta Strachecka, Grzegorz Borsuk and Krzysztof Olszewski
Appl. Sci. 2024, 14(11), 4566; https://doi.org/10.3390/app14114566 (registering DOI) - 26 May 2024
Abstract
During the spring development of bee colonies, small-cell combs were found to create equally favorable conditions for worker bee rearing as standard-cell combs, since the workers reared in the small-cell combs did not differ significantly in the majority of morphometric traits, including the
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During the spring development of bee colonies, small-cell combs were found to create equally favorable conditions for worker bee rearing as standard-cell combs, since the workers reared in the small-cell combs did not differ significantly in the majority of morphometric traits, including the length of wings and the sum of the widths of the third and fourth tergites, from those reared in standard-cell combs. Moreover, they had a significantly longer and wider thorax. It can be assumed that the workers reared in small-cell combs collect nectar as effectively as those reared in standard-cell combs, as both groups did not differ in the proboscis length. It was confirmed that the body size of workers is relatively constant and is less influenced by the width of comb cells than was assumed previously, as the values of their morphometric parameters did not increase proportionally with the increasing cell width. The colony kept on small-cell combs provided worse rearing conditions for workers reared in standard-cell combs than the colony kept on standard-cell combs, which may have been related to the less abundant feeding of larvae by workers reared in small-cell combs.
Full article
(This article belongs to the Special Issue Apiculture: Challenges and Opportunities)
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Open AccessArticle
The Effect of the Initial Phase of a Tightly Focused Laser Pulse on the Emission Characteristics of High-Energy Electrons
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Yiwei Zhou, Erhan Li and Youwei Tian
Appl. Sci. 2024, 14(11), 4565; https://doi.org/10.3390/app14114565 (registering DOI) - 26 May 2024
Abstract
Abstract: Based on the classical theory of nonlinear Thomson scattering and the single electron model, we performed extensive numerical simulations in MATLAB R2022b to comprehensively investigate how the initial phase of a tightly focused, circularly polarized laser pulse affects the radiation characteristics of
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Abstract: Based on the classical theory of nonlinear Thomson scattering and the single electron model, we performed extensive numerical simulations in MATLAB R2022b to comprehensively investigate how the initial phase of a tightly focused, circularly polarized laser pulse affects the radiation characteristics of high-energy electrons at different energy levels. Our findings indicate that the polar angle corresponding to the maximum radiation energy remains constant as the initial phase of the laser changes from 0 to 2π, while the azimuth angle correspondingly moves from 0 to 2π. Moreover, as the initial phase changes, the pulse width of the electron radiation peak displays a quasi-periodic oscillation with a period of π. Notably, an increase in the initial energy of the electrons results in a significant enhancement in both the peak radiation value and the collimation of the radiation. These results demonstrate that manipulating the initial phase of the driving laser pulse enables effective control over the spatial distribution of radiation light.
Full article
(This article belongs to the Section Optics and Lasers)
Open AccessArticle
Impact of Augmented Reality on Assistance and Training in Industry 4.0: Qualitative Evaluation and Meta-Analysis
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Ginés Morales Méndez and Francisco del Cerro Velázquez
Appl. Sci. 2024, 14(11), 4564; https://doi.org/10.3390/app14114564 (registering DOI) - 26 May 2024
Abstract
In the context of Industry 4.0, industrial environments are at a crossroads, facing the challenge of greater flexibility and significant technical skills gaps. In this situs, Augmented Reality (AR) emerges as a transformative tool, enhancing the synergy between technical staff and emerging technologies.
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In the context of Industry 4.0, industrial environments are at a crossroads, facing the challenge of greater flexibility and significant technical skills gaps. In this situs, Augmented Reality (AR) emerges as a transformative tool, enhancing the synergy between technical staff and emerging technologies. This article focuses on exploring the integration of AR in Industry 4.0, with a particular emphasis on its role in improving technical assistance and training. The research addresses the ways in which AR not only facilitates more efficient processes but also acts as an essential bridge for training and skills development in constantly changing technological environments. It investigates the significant impact of AR on both optimising work processes and training workers to meet the emerging challenges of Industry 4.0. Through a qualitative analysis, the studies are categorised according to their application domains, grouping them into specific thematic areas. Subsequently, a meta-analysis is conducted to determine the actual impact of AR in the sector. The findings reveal a positive and significant correlation between the implementation of AR and its effectiveness in assistance and training in the framework of Industry 4.0. Finally, the article delves into an analysis of current limitations and challenges, providing insights into possible developments and trends in the use of AR for assistance and training in Industry 4.0.
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(This article belongs to the Special Issue Virtual/Augmented Reality and Its Applications)
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Open AccessArticle
Machine Learning-Based Fatigue Level Prediction for Exoskeleton-Assisted Trunk Flexion Tasks Using Wearable Sensors
by
Pranav Madhav Kuber, Abhineet Rajendra Kulkarni and Ehsan Rashedi
Appl. Sci. 2024, 14(11), 4563; https://doi.org/10.3390/app14114563 (registering DOI) - 26 May 2024
Abstract
Monitoring physical demands during task execution with exoskeletons can be instrumental in understanding their suitability for industrial tasks. This study aimed at developing a fatigue level prediction model for Back-Support Industrial Exoskeletons (BSIEs) using wearable sensors. Fourteen participants performed a set of intermittent
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Monitoring physical demands during task execution with exoskeletons can be instrumental in understanding their suitability for industrial tasks. This study aimed at developing a fatigue level prediction model for Back-Support Industrial Exoskeletons (BSIEs) using wearable sensors. Fourteen participants performed a set of intermittent trunk-flexion task cycles consisting of static, sustained, and dynamic activities, until they reached medium-high fatigue levels, while wearing BSIEs. Three classification algorithms, Support Vector Machine (SVM), Random Forest (RF), and XGBoost (XGB), were implemented to predict perceived fatigue level in the back and leg regions using features from four wearable wireless Electromyography (EMG) sensors with integrated Inertial Measurement Units (IMUs). We examined the best grouping and sensor combinations by comparing prediction performance. The findings showed best performance in binary classification of leg and back fatigue with 95% (2 EMG + IMU sensors) and 82% (single IMU sensor) accuracy, respectively. Tertiary classification for back and leg fatigue level prediction required four sensor setups with both EMG and IMU measures to perform at 79% and 67% accuracy, respectively. The efforts presented in our article demonstrate the feasibility of an accessible fatigue level detection system, which can be beneficial for objective fatigue assessment, design selection, and implementation of BSIEs in real-world scenarios.
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(This article belongs to the Special Issue Advances in Digital Technology Assisted Industrial Design)
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Open AccessArticle
Harnessing Heritage BIM for Enhanced Architectural Documentation of Ad Deir in Petra
by
Ahmad Baik and Yahya Alshawabkeh
Appl. Sci. 2024, 14(11), 4562; https://doi.org/10.3390/app14114562 (registering DOI) - 26 May 2024
Abstract
This paper investigates the utilisation of heritage building information modelling (BIM) in order to improve the architectural heritage documentation process at Ad Deir, a significant historical building within the UNESCO World Heritage site of Petra, Jordan. Ad Deir, also known as ‘The Monastery’,
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This paper investigates the utilisation of heritage building information modelling (BIM) in order to improve the architectural heritage documentation process at Ad Deir, a significant historical building within the UNESCO World Heritage site of Petra, Jordan. Ad Deir, also known as ‘The Monastery’, requires accurate and complete documentation for its preservation and effective management. Traditional documentation methods, such as manual surveys and 2D drawings, frequently fail to obtain the intricate details and complexity of heritage structures. This study proposes the use of heritage BIM, which involves creating a digital representation of Ad Deir by combining various data types such as geometric, material, and historical information. Laser scanning technology is used to capture the site in three dimensions, providing a precise representation of its current state. The point clouds are exported to the BIM workflow once they have been processed. The longitudinal and cross-sections of the point clouds revealed the dimensions of regular and irregular elements, which were then traced and modelled accurately. This digital model serves as a platform for future data integration, which may include historical documentation, architectural plans, and construction details. Creating accurate heritage BIM, which involves various levels of knowledge, improves quality control during conservation work and aids in informed decision-making.
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(This article belongs to the Special Issue Advances in BIM-Based Architecture and Civil Infrastructure Systems)
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The Impact of Pulsed Electric Field Treatment and Shelf Temperature on Quality of Freeze-Dried Pumpkin
by
Oleksii Rastorhuiev, Aleksandra Matys, Artur Wiktor, Katarzyna Rybak, Alica Lammerskitten, Stefan Toepfl, Wolfram Schnäckel, Ewa Gondek and Oleksii Parniakov
Appl. Sci. 2024, 14(11), 4561; https://doi.org/10.3390/app14114561 (registering DOI) - 26 May 2024
Abstract
Pulsed electric field (PEF) treatment is known as a method that can intensify heat- and mass-transfer-based processes such as osmotic dehydration, drying, or freeze-drying. However, the literature about its impact on quality of freeze-dried products is limited to a few raw materials. The
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Pulsed electric field (PEF) treatment is known as a method that can intensify heat- and mass-transfer-based processes such as osmotic dehydration, drying, or freeze-drying. However, the literature about its impact on quality of freeze-dried products is limited to a few raw materials. The aim of this study was to analyze the effect of PEF on the cell disintegration index, selected bioactive compounds, and physical quality parameters of freeze-dried pumpkin. The final quality of the freeze-dried product was evaluated by residual moisture content, color analysis, total phenolic content, total carotenoid content, sugars content, and hygroscopic properties. The application of PEF treatment induced the disintegration of pumpkin cells even at low energy input (0.11 kJ/kg), and the saturation level of electroporation was reached after 4 kJ/kg. PEF treatment at 2 kJ/kg allowed 40% more total carotenoids to be retained in comparison to the untreated sample. Furthermore, all PEF-treated freeze-dried pumpkin samples exhibited lower sucrose content but had higher glucose and fructose contents in comparison to the reference samples. However, this effect was more pronounced when the shelf temperature was equal to 40 °C.
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(This article belongs to the Special Issue Characterization of Bioactive Compounds and Antioxidants in Natural Products)
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