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
Effect of Sodium Laureth Sulfate on Contact Angles of High-Impact Polystyrene and Acrylonitrile–Butadiene–Styrene from Recycled Refrigeration Equipment
Appl. Sci. 2024, 14(11), 4407; https://doi.org/10.3390/app14114407 (registering DOI) - 22 May 2024
Abstract
This paper investigates the effects of sodium laureth sulfate (SLES) on the wettability of the surface of the two most common recycled plastics in refrigeration equipment: HIPS (high-impact polystyrene) and ABS (acrylonitrile–butadiene–styrene). These plastics, in the form of flakes, were identified on the
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This paper investigates the effects of sodium laureth sulfate (SLES) on the wettability of the surface of the two most common recycled plastics in refrigeration equipment: HIPS (high-impact polystyrene) and ABS (acrylonitrile–butadiene–styrene). These plastics, in the form of flakes, were identified on the basis of their FTIR spectra, and then, they were subjected to a study of contact angles using the sessile droplet method. The solutions for the angle analysis included tap water with the addition of SLES. The results of this study showed that at SLES concentrations of 0.1 g/L and 0.2 g/L, the differences in the contact angles for HIPS and ABS were 10.76° and 10.10°, respectively. This research confirmed the potential of using SLES as a support for the flotation separation of plastics with similar densities and surface characteristics, such as HIPS and ABS.
Full article
(This article belongs to the Section Applied Industrial Technologies)
Open AccessArticle
Investigation of the Degree of Monomer Conversion in Dental Composites through Various Methods: An In Vitro Study
by
Musa Kazim Ucuncu, Ozge Celiksoz, Emine Sen, Yasemin Yucel Yucel and Bircan Dinc
Appl. Sci. 2024, 14(11), 4406; https://doi.org/10.3390/app14114406 (registering DOI) - 22 May 2024
Abstract
The degree of monomer conversion (DC) values of three different dental composites were examined using three different methods: surface microhardness (ratio of bottom/top), Fourier-transform infrared (FT-IR), and differential scanning calorimetry (DSC). Two of the dental composites included in the study were nanohybrid (Dentsply
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The degree of monomer conversion (DC) values of three different dental composites were examined using three different methods: surface microhardness (ratio of bottom/top), Fourier-transform infrared (FT-IR), and differential scanning calorimetry (DSC). Two of the dental composites included in the study were nanohybrid (Dentsply Neo Spectra ST HV and Omnichroma), and one was a microhybrid-labeled newly marketed composite containing nanoparticles (Dentac Myra). Composite discs were prepared according to the methodology for all methods and analyzed (2 mm thickness × 5 mm diameter). Surface microhardness values were measured in Vickers Hardness Number (VHN), while FT-IR and DSC values were obtained in percentage (%). Significant differences were observed in both bottom/top surface microhardness values and DC values obtained from FT-IR. However, there was no statistical difference in the ratio of bottom/top microhardness values. Neo Spectra ST HV exhibited superior performance in both microhardness and monomer conversion compared to the other two composites. Newly marketed Myra showed values close to Omnichroma. It was found that the values obtained by the DSC method were parallel to those obtained by FT-IR. In conclusion, the structure of dental composites leads to different mechanical properties. Additionally, DSC measurements and FTIR spectra were found to be complementary techniques for characterizing monomer conversion values.
Full article
(This article belongs to the Section Applied Dentistry and Oral Sciences)
Open AccessArticle
A Learnable Viewpoint Evolution Method for Accurate Pose Estimation of Complex Assembled Product
by
Delong Zhao, Feifei Kong and Fuzhou Du
Appl. Sci. 2024, 14(11), 4405; https://doi.org/10.3390/app14114405 (registering DOI) - 22 May 2024
Abstract
Balancing adaptability, reliability, and accuracy in vision technology has always been a major bottleneck limiting its application in appearance assurance for complex objects in high-end equipment production. Data-driven deep learning shows robustness to feature diversity but is limited by interpretability and accuracy. The
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Balancing adaptability, reliability, and accuracy in vision technology has always been a major bottleneck limiting its application in appearance assurance for complex objects in high-end equipment production. Data-driven deep learning shows robustness to feature diversity but is limited by interpretability and accuracy. The traditional vision scheme is reliable and can achieve high accuracy, but its adaptability is insufficient. The deeper reason is the lack of appropriate architecture and integration strategies between the learning paradigm and empirical design. To this end, a learnable viewpoint evolution algorithm for high-accuracy pose estimation of complex assembled products under free view is proposed. To alleviate the balance problem of exploration and optimization in estimation, shape-constrained virtual–real matching, evolvable feasible region, and specialized population migration and reproduction strategies are designed. Furthermore, a learnable evolution control mechanism is proposed, which integrates a guided model based on experience and is cyclic-trained with automatically generated effective trajectories to improve the evolution process. Compared to the m of the state-of-the-art data-driven method and the m of the classic strategy combination, the pose estimation error of complex assembled product in this study is m, which proves the effectiveness of the proposed method. Meanwhile, through in-depth exploration, the robustness, parameter sensitivity, and adaptability to the virtual–real appearance variations are sequentially verified.
Full article
(This article belongs to the Topic Applied Computer Vision and Pattern Recognition: 2nd Volume)
Open AccessReview
Design and Application of Bionic Camouflage Materials Simulating Spectral Reflection Characteristics of Plants: A Review
by
Yanping Lin, Luquan Ren, Xiaodong Yang and Hengyi Yuan
Appl. Sci. 2024, 14(11), 4404; https://doi.org/10.3390/app14114404 (registering DOI) - 22 May 2024
Abstract
Hyperspectral remote sensing (RS) has rapidly developed in recent years and has been widely used in the military field. This technology not only brings huge opportunities for military reconnaissance but also poses unprecedented challenges to military camouflage, severely complicating the development of plant
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Hyperspectral remote sensing (RS) has rapidly developed in recent years and has been widely used in the military field. This technology not only brings huge opportunities for military reconnaissance but also poses unprecedented challenges to military camouflage, severely complicating the development of plant hyperspectral camouflage materials and technology. In this review, the spectral reflectance characteristics of plants and the application of hyperspectral RS in plant RS and military operations are reviewed. The development status of bionic camouflage materials that simulate the spectral reflection characteristics of plants is analyzed. With the existing hyperspectral camouflage materials and technology, bionic camouflage technology is limited by the inability of bionic materials to accurately imitate the characteristic absorption peaks of green vegetation, low stability and durability, and the large overall material thickness, which complicate actual large-scale application. On this basis, a future development direction and a trend of plant hyperspectral bionic camouflage materials and technology are proposed.
Full article
(This article belongs to the Section Materials Science and Engineering)
Open AccessArticle
All-in-Focus Three-Dimensional Reconstruction Based on Edge Matching for Artificial Compound Eye
by
Sidong Wu, Liuquan Ren and Qingqing Yang
Appl. Sci. 2024, 14(11), 4403; https://doi.org/10.3390/app14114403 (registering DOI) - 22 May 2024
Abstract
An artificial compound eye consists of multiple apertures that allow for a large field of view (FOV) while maintaining a small size. Each aperture captures a sub-image, and multiple sub-images are needed to reconstruct the full FOV. The reconstruction process is depth-related due
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An artificial compound eye consists of multiple apertures that allow for a large field of view (FOV) while maintaining a small size. Each aperture captures a sub-image, and multiple sub-images are needed to reconstruct the full FOV. The reconstruction process is depth-related due to the parallax between adjacent apertures. This paper presents an all-in-focus 3D reconstruction method for a specific type of artificial compound eye called the electronic cluster eye (eCley). The proposed method uses edge matching to address the edge blur and large textureless areas existing in the sub-images. First, edges are extracted from each sub-image, and then a matching operator is applied to match the edges based on their shape context and intensity. This produces a sparse matching result that is then propagated to the whole image. Next, a depth consistency check and refinement method is performed to refine the depth of all sub-images. Finally, the sub-images and depth maps are merged to produce the final all-in-focus image and depth map. The experimental results and comparative analysis demonstrate the effectiveness of the proposed method.
Full article
(This article belongs to the Special Issue Advanced Pattern Recognition & Computer Vision)
Open AccessArticle
Study on Classification of Fishing Vessel Operation Types Based on Dilated CNN-IndRNN
by
Jiachen Yu, Shunlong Fu and Xiongguan Bao
Appl. Sci. 2024, 14(11), 4402; https://doi.org/10.3390/app14114402 - 22 May 2024
Abstract
At present, fishery resources are becoming increasingly depleted, and a reliable assessment of fishing activity is a key step in protecting marine resources. Correctly identifying the type of fishing operation can help identify illegal fishing vessels, strengthen fishing regulations, and prevent overfishing. Aiming
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At present, fishery resources are becoming increasingly depleted, and a reliable assessment of fishing activity is a key step in protecting marine resources. Correctly identifying the type of fishing operation can help identify illegal fishing vessels, strengthen fishing regulations, and prevent overfishing. Aiming to address these problems, this study first collects and preprocesses fishing vessel AIS data. Improvements are proposed on the basis of the convolutional neural network (CNN), long short-term memory (LSTM), and other models, changing the CNN to dilated CNN and LSTM to independently recurrent neural network (IndRNN). The results of the experiment show that the accuracy, precision, recall, and F-1 score of the model are finally obtained as 93.12%, 93.10%, 93.14%, and 93.10%, respectively. Overall, the new model proposed in this study offers a significant improvement in performance compared to the models of other scholars in the past.
Full article
(This article belongs to the Section Marine Science and Engineering)
Open AccessArticle
OBU for Accurate Navigation through Sensor Fusion in the Framework of the EMERGE Project
by
Angel Luis Zuriarrain Sosa, Valeria Ioannucci, Marco Pratesi , Roberto Alesii , Carlo Albanese , Francesco Valentini , Elena Cinque , Alessio Martinelli and Michele Brizzi
Appl. Sci. 2024, 14(11), 4401; https://doi.org/10.3390/app14114401 - 22 May 2024
Abstract
With the development of advanced driver assistance systems (ADAS) and autonomous vehicles (AV), recent years have seen an increasing evolution of onboard sensors and communication interfaces capable of interacting with available infrastructures, including satellite constellations, road structures, modern and heterogeneous network systems (e.g.,
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With the development of advanced driver assistance systems (ADAS) and autonomous vehicles (AV), recent years have seen an increasing evolution of onboard sensors and communication interfaces capable of interacting with available infrastructures, including satellite constellations, road structures, modern and heterogeneous network systems (e.g., 5G and beyond) and even adjacent vehicles. Consequently, it is essential to develop architectures that cover data fusion (multi–sensor approach), communication, power management, and system monitoring to ensure accurate and reliable perception in several navigation scenarios. Motivated by the EMERGE project, this paper describes the definition and implementation of an On Board Unit (OBU) dedicated to the navigation process. The OBU is equipped with the Xsens MTi–630 AHRS inertial sensor, a multi–constellation/multi–frequency Global Navigation Satellite System (GNSS) receiver with the u–blox ZED–F9P module and communication interfaces that afford access to the PointPerfect augmentation service. Experimental results show that GNSS, with corrections provided by augmentation, affords centimetre accuracy, with a Time To First Fix (TTFF) of about 30 s. During the on–road tests, we also collect: the output of fusion with inertial sensor data, monitoring information that assess correct operation of the module, and the OBU power consumption, that remains under 5 W even in high–power operating mode.
Full article
(This article belongs to the Special Issue Advanced Technologies in Automated Driving)
Open AccessReview
Personalized Video Summarization: A Comprehensive Survey of Methods and Datasets
by
Michail Peronikolis and Costas Panagiotakis
Appl. Sci. 2024, 14(11), 4400; https://doi.org/10.3390/app14114400 - 22 May 2024
Abstract
In recent years, the scientific and technological developments have led to an explosion of available videos on the web, increasing the necessity of fast and effective video analysis and summarization. Video summarization methods aim to generate a synopsis by selecting the most informative
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In recent years, the scientific and technological developments have led to an explosion of available videos on the web, increasing the necessity of fast and effective video analysis and summarization. Video summarization methods aim to generate a synopsis by selecting the most informative parts of the video content. The user’s personal preferences, often involved in the expected results, should be taken into account in the video summaries. In this paper, we provide the first comprehensive survey on personalized video summarization relevant to the techniques and datasets used. In this context, we classify and review personalized video summary techniques based on the type of personalized summary, on the criteria, on the video domain, on the source of information, on the time of summarization, and on the machine learning technique. Depending on the type of methodology used by the personalized video summarization techniques for the summary production process, we classify the techniques into five major categories, which are feature-based video summarization, keyframe selection, shot selection-based approach, video summarization using trajectory analysis, and personalized video summarization using clustering. We also compare personalized video summarization methods and present 37 datasets used to evaluate personalized video summarization methods. Finally, we analyze opportunities and challenges in the field and suggest innovative research lines.
Full article
(This article belongs to the Special Issue Novel Research on Image and Video Processing Technology)
Open AccessArticle
Modification of Insulating Properties of Surfaces of Dielectric High-Voltage Devices Using Plasma
by
Roman Pernica, Miloš Klíma, Pavel Londák and Pavel Fiala
Appl. Sci. 2024, 14(11), 4399; https://doi.org/10.3390/app14114399 - 22 May 2024
Abstract
Plasma discharges under atmospheric pressure are applicable for modifying the electrical properties of dielectric surfaces. The aim of the plasma discharge treatment of such surfaces is to design a procedure so that its characteristic parameters improve the resulting levels of the breakdown electrical
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Plasma discharges under atmospheric pressure are applicable for modifying the electrical properties of dielectric surfaces. The aim of the plasma discharge treatment of such surfaces is to design a procedure so that its characteristic parameters improve the resulting levels of the breakdown electrical strength Eb when tested under pulsed or alternating electrical voltages. In this research, a set of functional experiments performed by using plasma in samples of two types of materials (thermoset, thermoplastic) were processed and evaluated, and the resulting effect of the magnitude of the breakdown electrical voltage, electrical intensity, and electrical conductivity of the surface were compared. A slit plasma chamber, previously described and parameterized, was employed to treat the surface of the dielectric samples. The surface structure was modified via plasma discharge without precursors, and methodologies were developed to evaluate these modifications with respect to the change in the electrical strength parameters of the insulator surface. Subsequently, the surface strength of the affected and unaffected samples was measured and evaluated as a function of exposure time, and the stability of the modification was assessed. The first methodical test showed that plasma discharge without precursors improved the long-term surface electrical strength of the dielectric surface. The test and its parameters were carried out with respect to feasibility in an industrial environment.
Full article
(This article belongs to the Special Issue Advances in Surface Characterisation and Surface Modification of the Materials)
Open AccessArticle
Study on the Seismic Response of a Water-Conveyance Tunnel Considering Non-Uniform Longitudinal Subsurface Geometry and Obliquely Incident SV-Waves
by
Erlei Yao, Yu Rao, Meishan Liu, Zhifang Liu and Ang Cao
Appl. Sci. 2024, 14(11), 4398; https://doi.org/10.3390/app14114398 - 22 May 2024
Abstract
The longitudinal seismic response characteristics of a shallow-buried water-conveyance tunnel under non-uniform longitudinal subsurface geometry and obliquely incident SV-waves was studied using the numerical method, where the effect of the non-uniform longitudinal subsurface geometry due to the existence of a local one-sided rock
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The longitudinal seismic response characteristics of a shallow-buried water-conveyance tunnel under non-uniform longitudinal subsurface geometry and obliquely incident SV-waves was studied using the numerical method, where the effect of the non-uniform longitudinal subsurface geometry due to the existence of a local one-sided rock mountain on the seismic response of the tunnel was focused on. Correspondingly, a large-scale three-dimensional (3D) finite-element model was established, where different incidence angles and incidence directions of the SV-wave were taken into consideration. Also, the non-linearity of soil and rock and the damage plastic of the concrete lining were incorporated. In addition, the wave field of the site and the acceleration response as well as damage of the tunnel were observed. The results revealed the following: (i) a local inclined subsurface geometry may focus an obliquely incident wave due to refraction or total reflection; (ii) a tunnel in a site adjacent to a rock mountain may exhibit a higher acceleration response than a tunnel in a homogeneous plain site; and (iii) damage in the tunnel in the site adjacent to a rock mountain may appear in multiple positions, and the effect of the incidence angle on the mode of compressive deformation and damage of the lining is of significance.
Full article
(This article belongs to the Special Issue Earthquake Engineering and Seismic Risk)
Open AccessArticle
Optimization of Composite Material Repair Patch Shape Based on Strength Analysis
by
Ruishan Xing, Fan Wang, Yang Yang and Gang Li
Appl. Sci. 2024, 14(11), 4397; https://doi.org/10.3390/app14114397 - 22 May 2024
Abstract
With the increasing use of composite materials in aircraft structures and the extension of their service life, the selection of repair patch shapes for composite material damage repair has become a significant engineering concern. The ultimate strength of the repaired structure is among
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With the increasing use of composite materials in aircraft structures and the extension of their service life, the selection of repair patch shapes for composite material damage repair has become a significant engineering concern. The ultimate strength of the repaired structure is among the main evaluation criteria for selecting optimal patch shapes. In this study, strength analysis is conducted along with the use of the Digital Image Correlation (DIC) method to assess the quality of the repaired components, making the evaluation method more rational. Early studies often focused on simplified models, which diverged significantly from the practicalities of maintenance engineering in civil aviation. Therefore, it is essential to research full-scale composite material repair patches, as this will provide a more reliable basis for the optimal selection of patch shapes in composite material maintenance engineering for civil aircraft.
Full article
Open AccessArticle
Birthplace and Birthdate Effect during Talent Process in Professional Soccer Academy Players
by
Lander Hernandez-Simal, Julio Calleja-González, Alberto Lorenzo Calvo and Maite Aurrekoetxea-Casaus
Appl. Sci. 2024, 14(11), 4396; https://doi.org/10.3390/app14114396 - 22 May 2024
Abstract
The main objective of this study was to detect, from among a set of innate, acquired, and contextual factors, those variables that are ascribed to players ultimately promoted to the professional team of a Spanish league club during the earlier selection and development
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The main objective of this study was to detect, from among a set of innate, acquired, and contextual factors, those variables that are ascribed to players ultimately promoted to the professional team of a Spanish league club during the earlier selection and development phases. The data were presented in frequencies and correlations and by means of a classificatory cluster model. The variables used for the analyses included date of birth, birthplace density, player position, laterality, academy entry stage, international participation, and debutant status. These variables were related to the talent selection and promotion phases (i.e., academy entry stage and player debut). A dataset of information on 1411 players from the last 30 seasons of the Athletic Club de Bilbao (1993–2021) was used. Regarding the results, first, there was an over-representation of players with respect to their Q1 birth date and K5 density quintile in the selection phase; however, once players joined the academy, their chances of promotion (debut) fell for players in the Q4 birth date and K3 density quintiles. Second, there was a significant correlation between players’ debut and the stage of incorporation (p < 0.01; V = 0.46) and internationalisation (p < 0.01; V = 0.5). Finally, the birthplace density and laterality variables converged as classificatory features of the players.
Full article
(This article belongs to the Section Applied Biosciences and Bioengineering)
Open AccessArticle
Denoising Multiscale Back-Projection Feature Fusion for Underwater Image Enhancement
by
Wen Qu, Yuming Song and Jiahui Chen
Appl. Sci. 2024, 14(11), 4395; https://doi.org/10.3390/app14114395 - 22 May 2024
Abstract
In recent decades, enhancing underwater images has become a crucial challenge when obtaining high-quality visual information in underwater environment detection, attracting increasing attention. Original underwater images are affected by a variety of underwater environmental factors and exhibit complex degradation phenomena such as low
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In recent decades, enhancing underwater images has become a crucial challenge when obtaining high-quality visual information in underwater environment detection, attracting increasing attention. Original underwater images are affected by a variety of underwater environmental factors and exhibit complex degradation phenomena such as low contrast, blurred details, and color distortion. However, most encoder-decoder-based methods fail to restore the details of underwater images due to information loss during downsampling. The noise in images also influences the recovery of underwater images with complex degradation. In order to address these challenges, this paper introduces a simple but effective denoising multiscale back-projection feature fusion network, which represents a novel approach to restoring underwater images with complex degradation. The proposed method incorporates a multiscale back-projection feature fusion mechanism and a denoising block to restore underwater images. Furthermore, we designed a multiple degradation knowledge distillation strategy to extend our method to enhance various types of degraded images, such as snowy images and hazy images. Extensive experiments on the standard datasets demonstrate the superior performance of the proposed method. Qualitative and quantitative analyses validate the effectiveness of the model compared to several state-of-the-art models. The proposed method outperforms previous deep learning models in recovering both the blur and color bias of underwater images.
Full article
Open AccessArticle
Ecosystem of Aviation Maintenance: Transition from Aircraft Health Monitoring to Health Management Based on IoT and AI Synergy
by
Igor Kabashkin and Vladimir Perekrestov
Appl. Sci. 2024, 14(11), 4394; https://doi.org/10.3390/app14114394 - 22 May 2024
Abstract
This paper presents an in-depth exploration of the transformative impact of integrating the Internet of Things (IoT), cloud computing, and artificial intelligence (AI) within the domain of aviation maintenance. It articulates the transition from conventional health monitoring practices to a more advanced, comprehensive
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This paper presents an in-depth exploration of the transformative impact of integrating the Internet of Things (IoT), cloud computing, and artificial intelligence (AI) within the domain of aviation maintenance. It articulates the transition from conventional health monitoring practices to a more advanced, comprehensive health management approach, leveraging these modern technologies. This paper emphasizes the pivotal shift from reactive maintenance strategies to proactive and predictive maintenance paradigms, facilitated by the real-time data collection capabilities of IoT devices and the analytical prowess of AI. This transition not only enhances the safety and reliability of flight operations but also optimizes maintenance procedures, thereby reducing operational costs and improving efficiency. This paper meticulously outlines the implementation challenges, including technological integration, regulatory compliance, and security concerns, while proposing a future research agenda to address these issues and further harness the potential of these technologies in revolutionizing aviation maintenance.
Full article
Open AccessArticle
Routing Algorithm for Sensor Network Monitoring the Condition of Mining Equipment
by
Jerzy Jagoda, Krzysztof Stankiewicz, Sławomir Bartoszek, Joanna Rogala-Rojek, Mariusz Hetmańczyk and Andrzej Dymarek
Appl. Sci. 2024, 14(11), 4393; https://doi.org/10.3390/app14114393 - 22 May 2024
Abstract
This paper presents a concept of a routing algorithm for a network of sensors monitoring the condition of machinery and equipment operating in areas at risk of methane and/or coal dust explosion. It was assumed that the proposed algorithm would find application in
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This paper presents a concept of a routing algorithm for a network of sensors monitoring the condition of machinery and equipment operating in areas at risk of methane and/or coal dust explosion. It was assumed that the proposed algorithm would find application in sensor networks monitoring, among other things, oil pressure in powered roof supports and the position of powered roof support elements. The results of a literature analysis were presented, which included the simulation of sensor network routing algorithms, including, among others, reactive algorithms, proactive algorithms and algorithms based on so-called swarm intelligence (SI). As a result of the analyses, several algorithms were selected and implemented in a prototype sensor network. The characteristics of each of these algorithms are described. The article includes a description of the commissioning work of the network, which consisted of between 3 and 30 nodes. An analysis of the collected measurement data obtained for each criterion of the performance evaluation of the routing algorithms is presented.
Full article
(This article belongs to the Special Issue Trends in Modern Mining Technology)
Open AccessArticle
A Rapid Nondestructive Detection Method for Liquor Quality Analysis Using NIR Spectroscopy and Pattern Recognition
by
Guiyu Zhang, Xianguo Tuo, Yingjie Peng, Xiaoping Li and Tingting Pang
Appl. Sci. 2024, 14(11), 4392; https://doi.org/10.3390/app14114392 - 22 May 2024
Abstract
Liquor has a complex system with high dimensional components. The trace components in liquor are varied and have low content and complex coordination relationships. This study aimed to solve the problem of reliance on smell and taste. Based on the characteristics of near-infrared
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Liquor has a complex system with high dimensional components. The trace components in liquor are varied and have low content and complex coordination relationships. This study aimed to solve the problem of reliance on smell and taste. Based on the characteristics of near-infrared spectrum response to hydrogen-containing groups, qualitative analysis was carried out in combination with machine learning technology. Firstly, an iterative adaptive weighted penalized least squares algorithm with spectral peak discrimination was used for baseline correction to effectively retain useful information in the feature absorption peaks. Then, the convolution smoothing algorithm was used to filter the noise, and the spectral curve smoothness was adjusted using the convolution window width. The near-infrared spectrum has a high dimension. Monte Carlo random sampling combined with an improved competitive adaptive reweighting method was used to evaluate the importance of spectral sampling points. According to the importance coefficient, the dimension of the spectral data set was optimized by using an exponential attenuation function through an iterative operation, and the data set with the smallest root-mean-square error was taken as the characteristic spectrum. The nonlinear separability of characteristic spectra was further improved by kernel principal component analysis. Finally, a liquor quality recognition model based on principal component analysis was established by using the hierarchical multiclass support vector machine method. Our key findings revealed that the prediction accuracy of the model reached 96.87% when the number of principal components was 5–12, with more than 95% of the characteristic information retained. These results demonstrated that this rapid nondestructive testing method resolved the challenge posed by relying on subjective sensory evaluation for liquor analysis. The findings provide a reliable analytical approach for studying substances with high-dimensional component characteristics.
Full article
(This article belongs to the Section Food Science and Technology)
Open AccessArticle
Multitask Learning-Based Affective Prediction for Videos of Films and TV Scenes
by
Zhibin Su, Shige Lin, Luyue Zhang, Yiming Feng and Wei Jiang
Appl. Sci. 2024, 14(11), 4391; https://doi.org/10.3390/app14114391 - 22 May 2024
Abstract
Film and TV video scenes contain rich art and design elements such as light and shadow, color, composition, and complex affects. To recognize the fine-grained affects of the art carrier, this paper proposes a multitask affective value prediction model based on an attention
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Film and TV video scenes contain rich art and design elements such as light and shadow, color, composition, and complex affects. To recognize the fine-grained affects of the art carrier, this paper proposes a multitask affective value prediction model based on an attention mechanism. After comparing the characteristics of different models, a multitask prediction framework based on the improved progressive layered extraction (PLE) architecture (multi-headed attention and factor correlation-based PLE), incorporating a multi-headed self-attention mechanism and correlation analysis of affective factors, is constructed. Both the dynamic and static features of a video are chosen as fusion input, while the regression of fine-grained affects and classification of whether a character exists in a video are designed as different training tasks. Considering the correlation between different affects, we propose a loss function based on association constraints, which effectively solves the problem of training balance within tasks. Experimental results on a self-built video dataset show that the algorithm can give full play to the complementary advantages of different features and improve the accuracy of prediction, which is more suitable for fine-grained affect mining of film and TV scenes.
Full article
(This article belongs to the Special Issue Application of Artificial Intelligence in Visual Processing)
Open AccessArticle
Combining the Fuzzy Analytic Hierarchy Process Method with the Weighted Aggregated Sum Product Assessment Method to Address Internet Platform Selection Problems in an Environment with Incomplete Information
by
Kuei-Hu Chang, Hsin-Hung Lai and Bo-Jiun Hung
Appl. Sci. 2024, 14(11), 4390; https://doi.org/10.3390/app14114390 - 22 May 2024
Abstract
With the advancement of information technology, the Internet is pivotal in today’s society, serving as a global connectivity platform. Leveraging Internet technology within an enterprise can improve operational efficiency and curtail costs. However, traditional Internet platform selection methods cannot simultaneously handle quantitative and
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With the advancement of information technology, the Internet is pivotal in today’s society, serving as a global connectivity platform. Leveraging Internet technology within an enterprise can improve operational efficiency and curtail costs. However, traditional Internet platform selection methods cannot simultaneously handle quantitative and qualitative information, fuzzy semantics, and incomplete expert-provided information. To address these limitations, this study integrated the fuzzy analytic hierarchy process (FAHP) and the weighted aggregated sum product assessment (WASPAS) approaches to tackle Internet platform selection problems within an incomplete information environment. To demonstrate the validity of this research approach, this study utilized a construction industry Internet platform selection case to confirm the efficacy of the proposed novel fuzzy analytic hierarchy process-based method. Comparative analysis against the weighted sum model (WSM), weighted product model (WPM), FAHP, and typical WASPAS approaches was conducted with numerical verification, revealing that the proposed method in this study effectively manages comprehensive information and yields more rational outcomes for construction industry Internet platforms.
Full article
(This article belongs to the Special Issue Applications of Fuzzy Systems and Fuzzy Decision Making)
Open AccessArticle
Comparative Analysis of Energy Efficiency between Battery Electric Buses and Modular Autonomous Vehicles
by
Ioan-Tudor Oargă, Gabriel Prunean, Bogdan Ovidiu Varga, Dan Moldovanu and Dan Doru Micu
Appl. Sci. 2024, 14(11), 4389; https://doi.org/10.3390/app14114389 (registering DOI) - 22 May 2024
Abstract
This paper presents the initial steps taken in analysing the benefits of connected autonomous vehicles (CAVs), especially Modular Autonomous Vehicles (MAVs), in search of sustainable solutions for reducing energy consumption per passenger in air transport. For this particular case, a Mobility-as-a-Service (MaaS) solution
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This paper presents the initial steps taken in analysing the benefits of connected autonomous vehicles (CAVs), especially Modular Autonomous Vehicles (MAVs), in search of sustainable solutions for reducing energy consumption per passenger in air transport. For this particular case, a Mobility-as-a-Service (MaaS) solution is proposed, correlating airside transport with landside transport, as an urban mobility alternative. To better understand the benefits of the proposal, this paper studies the impact on energy consumption conceptual differences between a conventional public transport fleet using Battery Electric Buses (BEBs) and an MAV fleet. Simulations for simple public transport tasks are performed to highlight the advantages of the modular vehicle concept, in which routes are assigned dynamically based on the requested passenger carrying capacity and travel distance, aiming to optimize the efficiency of the entire system. With a proven reduction in energy consumption due to better use of available passenger capacity and reduced travel times in which the vehicle is driving with a number of passengers less than half of its capacity, the concept can be addressed further in developing a predictive system that processes public transport data and delivers an optimized schedule for the entire fleet. The main goal being to improve overall operational efficiency and total cost of ownership, the second part of the paper studies the impact of weight distribution on efficiency parameters such as energy consumption, range, and overall performance of an electric bus. The impact on dynamic elements such as acceleration, braking, and cornering performance is analyzed, to assess the viability and safety of all types of electric bus operations.
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(This article belongs to the Special Issue Virtual Models for Autonomous Driving Systems)
Open AccessArticle
Study on Rock Interface Stability in the Heat Exchange Channel of the Horizontal Section of U-Shaped Wells in Hot Dry Rock
by
Yafei Xue, Bo Xiong, Shejiao Wang, Chaohe Fang, Shaoyuan Mo, Fudong Xin and Yuxi Xian
Appl. Sci. 2024, 14(11), 4388; https://doi.org/10.3390/app14114388 - 22 May 2024
Abstract
Enhanced Geothermal Systems (EGS) represent a promising direction for sustainable energy development, yet their efficiency and feasibility often suffer due to suboptimal heat extraction methods and interface instability in U-shaped wells. This study introduces an innovative volume encapsulation technology that aims to address
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Enhanced Geothermal Systems (EGS) represent a promising direction for sustainable energy development, yet their efficiency and feasibility often suffer due to suboptimal heat extraction methods and interface instability in U-shaped wells. This study introduces an innovative volume encapsulation technology that aims to address these challenges. The proposed technology employs a combination of hydraulic fracturing and acidification to prepare the rock interface, followed by encapsulation using high-temperature liquid metal. Low-melting-point alloys are utilized as a heat exchange medium between the horizontal sections of the wells. This study meticulously analyzes the impact of formation stress, thermal shock stress, and liquid metal properties on rock interface stability. Advanced simulation tools and experimental setups were used to test the encapsulation process under various conditions. The application of liquid metal encapsulation demonstrated significant improvements in energy conversion efficiency and rock interface stability. In conditions simulating a dry and hot rock reservoir at depths up to 3000 m and temperature gradients reaching 2200 °C/m, the adjusted depth of horizontal sections and increased pumping pressure contributed to maintaining interface stability. The established failure criteria provide a robust theoretical foundation for the encapsulation process. Volume encapsulation technology using liquid metal not only enhances the operational efficiency of EGS but also stabilizes the rock interface, thereby increasing the feasibility of continuous geothermal energy extraction. This study offers valuable theoretical insights and practical guidance for future research and applications in geothermal energy technologies, creating new pathways for the efficient exploitation of geothermal resources.
Full article
(This article belongs to the Section Applied Thermal Engineering)
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