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Appl. Sci., Volume 12, Issue 20 (October-2 2022) – 501 articles

Cover Story (view full-size image): Explainable artificial intelligence (XAI) has shown benefits in clinical decision support systems (CDSSs). However, it is still unclear to CDSS developers how to select an XAI method which optimizes the advice-taking of healthcare practitioners. We performed a user study of healthcare practitioners to explore and compare two XAI methods from a machine-learning-based CDSS: explanation by feature contribution and explanation by example. This study demonstrates the impact that a CDSS explained by these XAI methods has on healthcare practitioners’ decision making as well as their preferences for explanations, providing guidelines for future CDSS developers. View this paper
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19 pages, 5387 KiB  
Article
Cosine-Based Embedding for Completing Lightweight Schematic Knowledge in DL-Litecore
by Weizhuo Li, Xianda Zheng, Huan Gao, Qiu Ji and Guilin Qi
Appl. Sci. 2022, 12(20), 10690; https://doi.org/10.3390/app122010690 - 21 Oct 2022
Viewed by 1509
Abstract
Schematic knowledge, an important component of knowledge graphs (KGs), defines a rich set of logical axioms based on concepts and relations to support knowledge integration, reasoning, and heterogeneity elimination over KGs. Although several KGs consist of lots of factual knowledge, their schematic knowledge [...] Read more.
Schematic knowledge, an important component of knowledge graphs (KGs), defines a rich set of logical axioms based on concepts and relations to support knowledge integration, reasoning, and heterogeneity elimination over KGs. Although several KGs consist of lots of factual knowledge, their schematic knowledge (e.g., subclassOf axioms, disjointWith axioms) is far from complete. Currently, existing KG embedding methods for completing schematic knowledge still suffer from two limitations. Firstly, existing embedding methods designed to encode factual knowledge pay little attention to the completion of schematic knowledge (e.g., axioms). Secondly, several methods try to preserve logical properties of relations for completing schematic knowledge, but they cannot simultaneously preserve the transitivity (e.g., subclassOf) and symmetry (e.g., disjointWith) of axioms well. To solve these issues, we propose a cosine-based embedding method named CosE tailored for completing lightweight schematic knowledge in DL-Litecore. Precisely, the concepts in axioms will be encoded into two semantic spaces defined in CosE. One is called angle-based semantic space, which is employed to preserve the transitivity or symmetry of relations in axioms. The other one is defined as translation-based semantic space that is used to measure the confidence of each axiom. We design two types of score functions for these two semantic spaces, so as to sufficiently learn the vector representations of concepts. Moreover, we propose a novel negative sampling strategy based on the mutual exclusion between subclassOf and disjointWith. In this way, concepts can obtain better vector representations for schematic knowledge completion. We implement our method and verify it on four standard datasets generated by real ontologies. Experiments show that CosE can obtain better results than existing models and keep the logical properties of relations for transitivity and symmetry simultaneously. Full article
(This article belongs to the Special Issue Natural Language Processing (NLP) and Applications)
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15 pages, 3016 KiB  
Article
Hybrid Genetic Algorithm−Based BP Neural Network Models Optimize Estimation Performance of Reference Crop Evapotranspiration in China
by Anzhen Qin, Zhilong Fan and Liuzeng Zhang
Appl. Sci. 2022, 12(20), 10689; https://doi.org/10.3390/app122010689 - 21 Oct 2022
Cited by 4 | Viewed by 1379
Abstract
Precise estimation of reference evapotranspiration (ET0) is of significant importance in hydrologic processes. In this study, a genetic algorithm (GA) optimized back propagation (BP) neural network model was developed to estimate ET0 using different combinations of meteorological data across various [...] Read more.
Precise estimation of reference evapotranspiration (ET0) is of significant importance in hydrologic processes. In this study, a genetic algorithm (GA) optimized back propagation (BP) neural network model was developed to estimate ET0 using different combinations of meteorological data across various climatic zones and seasons in China. Fourteen climatic locations were selected to represent five major climates. Meteorological datasets in 2018–2020, including maximum, minimum and mean air temperature (Tmax, Tmin, Tmean, °C) and diurnal temperature range (∆T, °C), solar radiation (Ra, MJ m−2 d−1), sunshine duration (S, h), relative humidity (RH, %) and wind speed (U2, m s−1), were first subjected to correlation analysis to determine which variables were suitable as input parameters. Datasets in 2018 and 2019 were utilized for training the models, while datasets in 2020 were for testing. Coefficients of determination (r2) of 0.50 and 0.70 were adopted as threshold values for selection of correlated variables to run the models. Results showed that U2 had the least r2 with ET0, followed by ∆T. Tmax had the greatest r2 with ET0, followed by Tmean, Ra and Tmin. GA significantly improved the performance of BP models across different climatic zones, with the accuracy of GABP models significantly higher than that of BP models. GABP0.5 model (input variables based on r2 > 0.50) had the best ET0 estimation performance for different seasons and significantly reduced estimation errors, especially for autumn and winter seasons whose errors were larger with other BP and GABP models. GABP0.5 model using radiation/temperature data is highly recommended as a promising tool for modelling and predicting ET0 in various climatic locations. Full article
(This article belongs to the Special Issue Advanced Plant Biotechnology in Sustainable Agriculture)
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9 pages, 4284 KiB  
Communication
Wideband E00-E10 Silicon Mode Converter Based on 180 nm CMOS Technology
by Yan Xu, Yang Gao, Songyue Liu, Tingyu Liu, Xiaoqiang Sun, Bo Tang, Peng Zhang and Daming Zhang
Appl. Sci. 2022, 12(20), 10688; https://doi.org/10.3390/app122010688 - 21 Oct 2022
Cited by 2 | Viewed by 1288
Abstract
Mode division multiplexing (MDM) is a promising technology for the capacity enlargement of the optical transmission network. As a key element in the MDM system, the mode converter plays an important role in signal processing. In this work, a wideband E00-E [...] Read more.
Mode division multiplexing (MDM) is a promising technology for the capacity enlargement of the optical transmission network. As a key element in the MDM system, the mode converter plays an important role in signal processing. In this work, a wideband E00-E10 silicon mode converter constructed by Y-branch and cascaded multimode interference coupler is demonstrated. The theoretical mode crosstalk is less than –29.2 dB within the wavelength range from 1540 nm to 1600 nm. By 180 nm standard CMOS fabrication, the tested mode conversion efficiency of 91.5% and the crosstalk of −10.3 dB can be obtained at 1575.9 nm. The 3 dB bandwidth is over 60 nm. The proposed E00-E10 silicon mode converter is applicable in mode multiplexing. Full article
(This article belongs to the Special Issue Laser and Silicon Photonics: Technology, Preparation and Application)
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14 pages, 7946 KiB  
Article
Analysis of Freeze–Thaw Response and Pore Characteristics of Artificially Frozen Soft Soil under Combined Formation Seepage
by Jie Zhou, Zhongqiu Guo, Chuanhe Wang, Zeyao Li, Huade Zhou and Wansheng Pei
Appl. Sci. 2022, 12(20), 10687; https://doi.org/10.3390/app122010687 - 21 Oct 2022
Cited by 2 | Viewed by 1254
Abstract
Artificial ground freezing (AGF) is a widely used method in coastal tunnel construction and reinforcement. With more and more underground construction in coastal areas, clay–sand combined formation, which is common in coastal areas, brings more challenges to AGF. In this paper, the frost–thaw [...] Read more.
Artificial ground freezing (AGF) is a widely used method in coastal tunnel construction and reinforcement. With more and more underground construction in coastal areas, clay–sand combined formation, which is common in coastal areas, brings more challenges to AGF. In this paper, the frost–thaw characteristics of soft clay during AFG under the construction of combined formation seepage were studied by model test. It was found that the shape of the freezing curtain changed under the condition of seepage, and the water content of the upper soft soil layer decreased markedly after settlement. Subsequently the micro characteristics of melted soil by CT were also conducted for further mechanism analysis, and it was indicated that the distribution of CT number had obvious segmentation characteristics along the height. Finally, the 3D structure of melted clay was reconstructed, and a method was proposed to calculate freeze–thaw settlement through CT numbers. Full article
(This article belongs to the Special Issue Artificial Ground Freezing Technology)
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32 pages, 7632 KiB  
Article
Automated Design of Salient Object Detection Algorithms with Brain Programming
by Gustavo Olague, Jose Armando Menendez-Clavijo, Matthieu Olague, Arturo Ocampo, Gerardo Ibarra-Vazquez, Rocio Ochoa and Roberto Pineda
Appl. Sci. 2022, 12(20), 10686; https://doi.org/10.3390/app122010686 - 21 Oct 2022
Cited by 2 | Viewed by 1788
Abstract
Despite recent improvements in computer vision, artificial visual systems’ design is still daunting since an explanation of visual computing algorithms remains elusive. Salient object detection is one problem that is still open due to the difficulty of understanding the brain’s inner workings. Progress [...] Read more.
Despite recent improvements in computer vision, artificial visual systems’ design is still daunting since an explanation of visual computing algorithms remains elusive. Salient object detection is one problem that is still open due to the difficulty of understanding the brain’s inner workings. Progress in this research area follows the traditional path of hand-made designs using neuroscience knowledge or, more recently, deep learning, a particular branch of machine learning. Recently, a different approach based on genetic programming appeared to enhance handcrafted techniques following two different strategies. The first method follows the idea of combining previous hand-made methods through genetic programming and fuzzy logic. The second approach improves the inner computational structures of basic hand-made models through artificial evolution. This research proposes expanding the artificial dorsal stream using a recent proposal based on symbolic learning to solve salient object detection problems following the second technique. This approach applies the fusion of visual saliency and image segmentation algorithms as a template. The proposed methodology discovers several critical structures in the template through artificial evolution. We present results on a benchmark designed by experts with outstanding results in an extensive comparison with the state of the art, including classical methods and deep learning approaches to highlight the importance of symbolic learning in visual saliency. Full article
(This article belongs to the Collection Computer Vision and Machine Learning: Theory, Methods and Applications)
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13 pages, 3238 KiB  
Article
Inhibitory Effect of Coumarins and Isocoumarins Isolated from the Stems and Branches of Acer mono Maxim. against Escherichia coli β-Glucuronidase
by Nguyen Viet Phong, Byung Sun Min, Seo Young Yang and Jeong Ah Kim
Appl. Sci. 2022, 12(20), 10685; https://doi.org/10.3390/app122010685 - 21 Oct 2022
Cited by 5 | Viewed by 1414
Abstract
We isolated eight known secondary metabolites, including two isocoumarins and six coumarins, from the stems and branches of Acer mono Maxim. Their structures were confirmed using nuclear magnetic resonance spectroscopy and by comparing the data to published reports. The inhibitory effects of all [...] Read more.
We isolated eight known secondary metabolites, including two isocoumarins and six coumarins, from the stems and branches of Acer mono Maxim. Their structures were confirmed using nuclear magnetic resonance spectroscopy and by comparing the data to published reports. The inhibitory effects of all compounds (1−8) on Escherichia coli β-glucuronidase were evaluated for the first time using in vitro assays. 3-(3,4-Dihydroxyphenyl)-8-hydroxyisocoumarin (1) displayed an inhibitory effect against β-glucuronidase (IC50 = 58.83 ± 1.36 μM). According to the findings of kinetic studies, compound 1 could function as a non-competitive inhibitor. Molecular docking indicated that compound 1 binds to the allosteric binding site of β-glucuronidase, and the results corroborated those from kinetic studies. Furthermore, molecular dynamics simulations of compound 1 were performed to identify the behavioral and dynamic properties of the protein–ligand complex. Our results reveal that compound 1 could be a lead metabolite for designing new β-glucuronidase inhibitors. Full article
(This article belongs to the Special Issue Potential Health Benefits of Fruits and Vegetables II)
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19 pages, 3398 KiB  
Review
Imputation Methods for scRNA Sequencing Data
by Mengyuan Wang, Jiatao Gan, Changfeng Han, Yanbing Guo, Kaihao Chen, Ya-zhou Shi and Ben-gong Zhang
Appl. Sci. 2022, 12(20), 10684; https://doi.org/10.3390/app122010684 - 21 Oct 2022
Cited by 5 | Viewed by 2406
Abstract
More and more researchers use single-cell RNA sequencing (scRNA-seq) technology to characterize the transcriptional map at the single-cell level. They use it to study the heterogeneity of complex tissues, transcriptome dynamics, and the diversity of unknown organisms. However, there are generally lots of [...] Read more.
More and more researchers use single-cell RNA sequencing (scRNA-seq) technology to characterize the transcriptional map at the single-cell level. They use it to study the heterogeneity of complex tissues, transcriptome dynamics, and the diversity of unknown organisms. However, there are generally lots of technical and biological noises in the scRNA-seq data since the randomness of gene expression patterns. These data are often characterized by high-dimension, sparsity, large number of “dropout” values, and affected by batch effects. A large number of “dropout” values in scRNA-seq data seriously conceal the important relationship between genes and hinder the downstream analysis. Therefore, the imputation of dropout values of scRNA-seq data is particularly important. We classify, analyze and compare the current advanced scRNA-seq data imputation methods from different angles. Through the comparison and analysis of the principle, advantages and disadvantages of the algorithm, it can provide suggestions for the selection of imputation methods for specific problems and diverse data, and have basic research significance for the downstream function analysis of data. Full article
(This article belongs to the Special Issue Recent Advances in Big Data Analytics)
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14 pages, 7100 KiB  
Article
Test Stand for a Motor Vehicle Powered by Different Fuels
by Dawid Tatarynow, Rafał Longwic, Przemysław Sander, Łukasz Zieliński, Michał Trojgo, Wincenty Lotko and Paweł Lonkwic
Appl. Sci. 2022, 12(20), 10683; https://doi.org/10.3390/app122010683 - 21 Oct 2022
Viewed by 1631
Abstract
This article discusses current testing methods for motor vehicle engines. Traction engines have so far been tested, for example, according to WLTP (Worldwide Harmonized Light Vehicle Test Procedure) driving tests, but due to the “VW—gate” incident, these are now to be supplemented by [...] Read more.
This article discusses current testing methods for motor vehicle engines. Traction engines have so far been tested, for example, according to WLTP (Worldwide Harmonized Light Vehicle Test Procedure) driving tests, but due to the “VW—gate” incident, these are now to be supplemented by RDE (Real Driving Emissions) tests, conducted under real road conditions. The analyses of the state of knowledge and the directions of research to date unequivocally indicate the need for the construction of a stand that allows: testing of a complete vehicle admitted to traffic; testing of a motor vehicle with the possibility of simulating real operating conditions; load setting with the possibility of its regulation; feeding the engine with various fuels; modification of the software of controllers having a direct impact on the control strategies of the engine; transmission and traction control system; reading, recording and analysis of the parameters of the operation of control systems in real time; detailed recording and analysis of the combustion process occurring directly in the combustion chamber; and the measurement of emitted toxic substances. On a bench with the above features, tests were carried out on a diesel motor vehicle, which were based on recording changes in the parameters of the combustion and injection process. The tests were conducted under static and dynamic conditions. Tests under static conditions were conducted on a chassis dynamometer. They consisted of indicating the engine for different fuel dose control maps. The vehicle equipped with the test engine was driven at a constant speed on the chassis dynamometer and loaded with a drag force of 130 Nm. Tests under dynamic conditions were conducted under real traffic conditions. They were limited to the presentation of results under static conditions. The main results of the tests are given in the conclusion and include a general summary. In particular, the presented results of the diesel tests demonstrate an attempt to adapt the engine to co-power with hydrogen. Full article
(This article belongs to the Section Mechanical Engineering)
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17 pages, 2063 KiB  
Article
Free Vibration Analysis of Thick Annular Functionally Graded Plate Integrated with Piezo-Magneto-Electro-Elastic Layers in a Hygrothermal Environment
by Faraz Kiarasi, Masoud Babaei, Kamran Asemi, Rossana Dimitri and Francesco Tornabene
Appl. Sci. 2022, 12(20), 10682; https://doi.org/10.3390/app122010682 - 21 Oct 2022
Cited by 12 | Viewed by 1615
Abstract
The present work aims at investigating the hygrothermal effect on the natural frequencies of functionally graded (FG) annular plates integrated with piezo-magneto-electro-elastic layers resting on a Pasternak elastic foundation. The formulation is based on a layer-wise (LW) theory, where the Hamiltonian principle is [...] Read more.
The present work aims at investigating the hygrothermal effect on the natural frequencies of functionally graded (FG) annular plates integrated with piezo-magneto-electro-elastic layers resting on a Pasternak elastic foundation. The formulation is based on a layer-wise (LW) theory, where the Hamiltonian principle is used to obtain the governing equation of the problem involving temperature- and moisture-dependent material properties. The differential quadrature method (DQM) is applied here as a numerical strategy to solve the governing equations for different boundary conditions. The material properties of FG annular plates are varied along the thickness based on a power law function. The accuracy of the proposed method is, first, validated for a limit-case example. A sensitivity study of the free vibration response is, thus, performed for different input parameters, such as temperature and moisture variations, elastic foundation, boundary conditions, electric and magnetic potential of piezo-magneto-electro-elastic layers and geometrical ratios, with useful insights from a design standpoint. Full article
(This article belongs to the Special Issue Latest Advances and Prospects of Functionally Graded Material)
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17 pages, 6727 KiB  
Article
Experimental Investigation on Compressive Strength, Ultrasonic Characteristic and Cracks Distribution of Granite Rock Irradiated by a Moving Laser Beam
by Lianfei Kuang, Lipeng Sun, Dongxu Yu, Yijiang Wang, Zhaoxiang Chu and Jo Darkwa
Appl. Sci. 2022, 12(20), 10681; https://doi.org/10.3390/app122010681 - 21 Oct 2022
Cited by 5 | Viewed by 2458
Abstract
Efficient fracturing is the key issue for the exploitation of geothermal energy in a Hot Dry Rock reservoir. By using the laser irradiation cracking method, this study investigates the changes in uniaxial compressive strength, ultrasonic characteristics and crack distributions of granite specimens by [...] Read more.
Efficient fracturing is the key issue for the exploitation of geothermal energy in a Hot Dry Rock reservoir. By using the laser irradiation cracking method, this study investigates the changes in uniaxial compressive strength, ultrasonic characteristics and crack distributions of granite specimens by applying a laser beam under various irradiation conditions, including different powers, diameters and moving speeds of the laser beam. The results indicate that the uniaxial compressive strength is considerably dependent on the power, diameter and moving speed of the laser beam. The ultrasonic-wave velocity and amplitude of the first wave both increase with a decreased laser power, increased diameter or moving speed of the laser beam. The wave form of irradiated graphite is flattened by laser irradiation comparing with that of the original specimen without laser irradiation. The crack angle and the ratio of the cracked area at both ends are also related to the irradiation parameters. The interior cracks are observed to be well-developed around the bottom of the grooving kerf generated by the laser beam. The results indicate that laser irradiation is a new economical and practical method that can efficiently fracture graphite. Full article
(This article belongs to the Special Issue Mechanical Properties of Rocks under Complex Stress Conditions)
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12 pages, 4248 KiB  
Article
A Study on the Field Applicability of Intermittent Irrigation in Protected Cultivation Using an Automatic Irrigation System
by Sang-Hyeon Kang, Youngjin Kim, Sangbong Lee, Heetae Kim and Minyoung Kim
Appl. Sci. 2022, 12(20), 10680; https://doi.org/10.3390/app122010680 - 21 Oct 2022
Cited by 1 | Viewed by 1616
Abstract
The demand for efficient water use and automatic systems has been increasing due to the frequent drought damage to crops as a result of climate change, the shortage of water resources in rural areas, and the aging of farmers. The existing automatic irrigation [...] Read more.
The demand for efficient water use and automatic systems has been increasing due to the frequent drought damage to crops as a result of climate change, the shortage of water resources in rural areas, and the aging of farmers. The existing automatic irrigation systems reduce the amount of labor required for irrigation and maintain soil moisture. However, the irrigation threshold criteria are user-determined as opposed to being automated according to input objectives such as improving crop productivity and saving water. In this study, an algorithm that could automatically determine suitable soil moisture according to a database and an automatic irrigation system with intermittent irrigation for efficient water use were developed. An experiment was then conducted on the productivity of crops for protected cultivation according to the application of the system. As the frequency domain reflectometry (FDR) sensor used in this system measured the volumetric water content of the soil, the soil moisture tension corresponding with the set value was converted into the volumetric water content using a regression equation. The process of intermittent irrigation was defined by using the moisture movement modeling of Hydrus 2D to reduce water loss on the soil surface and allow moisture to penetrate the soil unobstructed. An experimental field of a tomato farm was divided into empirical manual and controlled automatic irrigation plots. A total of 97.3% of the soil moisture values in the −33 kPa-controlled automatic irrigation plot and 96.6% of the soil moisture values in the −25 kPa-controlled automatic irrigation plot were within each set range during the first cropping season. During the second cropping season, a total of 94.8% of the soil moisture values in the −33 kPa-controlled automatic irrigation plot was within the set range. Compared with the empirical manual irrigation plot, the water productivity in the first cropping season was 113.9% in the −33 kPa-controlled automatic irrigation plot and 106.3% in the −25 kPa-controlled automatic irrigation plot. In the second cropping season, the water productivity was 117.3% in the −33 kPa-controlled automatic irrigation plot. Therefore, an automatic irrigation system applied with intermittent irrigation could be critical to increasing agricultural production and improving water-use efficiency. Full article
(This article belongs to the Special Issue Water and Wastewater Management in Agriculture)
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23 pages, 3489 KiB  
Article
Concept and Architecture for Applying Continuous Machine Learning in Multi-Access Routing at Underground Mining Vehicles
by Pekka Pääkkönen, Jere Backman, Daniel Pakkala, Jori Paananen, Kari Seppänen and Kimmo Ahola
Appl. Sci. 2022, 12(20), 10679; https://doi.org/10.3390/app122010679 - 21 Oct 2022
Cited by 1 | Viewed by 1318
Abstract
Autonomous moving vehicles facilitate mining of ore in underground mines. The vehicles are usually equipped with many sensor-based devices (e.g., Lidar, video camera, proximity sensor, etc.), which enable environmental monitoring, and remote control of the vehicles at the control center. Transfer of sensor-based [...] Read more.
Autonomous moving vehicles facilitate mining of ore in underground mines. The vehicles are usually equipped with many sensor-based devices (e.g., Lidar, video camera, proximity sensor, etc.), which enable environmental monitoring, and remote control of the vehicles at the control center. Transfer of sensor-based data from the vehicles towards the control center is challenging due to limited connectivity enabled by the multi-access technologies of the communication infrastructure (e.g., 5G, Wi-Fi) within the underground mine, and the mobility of the vehicles. This paper presents design, development, and evaluation of a concept and architecture enabling continuous machine learning (ML) for optimizing route selection of real-time streaming data in a real and emulated underground mining environment. Continuous ML refers to training and inference based on the most recently available data. Experiments in the emulator indicated that utilization of a ML-based model (based on the RandomForestRegressor) in decision making achieved ~5–13% lower one-way delay in streaming data transfers, when compared to a simpler heuristic model. Full article
(This article belongs to the Section Computing and Artificial Intelligence)
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21 pages, 2516 KiB  
Review
Recent Developments and Emerging Trends in Paint Industry Wastewater Treatment Methods
by Nicolette Viktoryová, Agneša Szarka and Svetlana Hrouzková
Appl. Sci. 2022, 12(20), 10678; https://doi.org/10.3390/app122010678 - 21 Oct 2022
Cited by 6 | Viewed by 5898
Abstract
High amounts of industrial wastewater are generated by the ever-growing demand and production of paint and coating materials. These effluents have negative effects on human health and the environment. The source of industrial effluents highly influences the properties, composition, and content of pollutants. [...] Read more.
High amounts of industrial wastewater are generated by the ever-growing demand and production of paint and coating materials. These effluents have negative effects on human health and the environment. The source of industrial effluents highly influences the properties, composition, and content of pollutants. The manufacturing of paint and coatings uses huge volumes of water and chemical reagents, consequently producing huge volumes of heavily polluted wastewater. This review is focused on summarizing various methods of industrial wastewater treatment from the paint manufacturing industry. Current trends in paint industry wastewater treatment processes have resulted in high efficiency of the reduction of chemical oxygen demand. Factors affecting the treatment processes are discussed and future trends are outlined. The effectiveness of the recently used methods is compared and the limitations of advanced treatment systems are highlighted. The review of recent developments in paint industry wastewater treatments points to the need for paying great attention to advanced analytical methods allowing the identification of individual contaminants to guarantee safe disposal limits. Full article
(This article belongs to the Special Issue Perspectives in Water Recycling)
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14 pages, 1713 KiB  
Article
Simplified Polydispersion Analysis of Small-Angle Scattering Data
by Flavio Carsughi
Appl. Sci. 2022, 12(20), 10677; https://doi.org/10.3390/app122010677 - 21 Oct 2022
Viewed by 1027
Abstract
With polydisperse inhomogeneities, the analysis of small-angle scattering (SAS) data is possible by fitting the experimental data to theoretical models. Despite scientific software being available for this task, many scientists in different fields prefer other techniques for their investigations. With the simplified polydispersion [...] Read more.
With polydisperse inhomogeneities, the analysis of small-angle scattering (SAS) data is possible by fitting the experimental data to theoretical models. Despite scientific software being available for this task, many scientists in different fields prefer other techniques for their investigations. With the simplified polydispersion analysis (SPA) presented here, it is possible to analyse the SAS data in a much simpler way. A straightforward interpolation of SAS data using any commercial software, requiring no advanced computational skills, allows the determination of the size distribution function (SDF) of the polydisperse inhomogeneities. Here, this innovative approach was tested against simulated SAS data of spherical inhomogeneities, as well as experimental data with excellent results. The results reported here offer new opportunities for many scientists to use the SAS technique to investigate polydisperse systems. Full article
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10 pages, 4092 KiB  
Article
A VHF Band Small CRLH Antenna Using Double-Sided Meander Lines
by Soyeong Lee and Yong Bae Park
Appl. Sci. 2022, 12(20), 10676; https://doi.org/10.3390/app122010676 - 21 Oct 2022
Viewed by 1258
Abstract
In this paper, a miniaturized very-high frequency (VHF) band antenna using both top and bottom meander lines is proposed. To design a compact size antenna in the VHF band, a Composite Right/Left-Handed (CRLH) transmission line is applied to antenna structure; additionally, both top [...] Read more.
In this paper, a miniaturized very-high frequency (VHF) band antenna using both top and bottom meander lines is proposed. To design a compact size antenna in the VHF band, a Composite Right/Left-Handed (CRLH) transmission line is applied to antenna structure; additionally, both top and bottom meander lines were used to achieve a greater inductance. The CRLH transmission line unit cell operates at 88 MHz, and the fabricated antenna is designed by arranging 7-unit cells. The overall size of the proposed antenna is 0.087λ × 0.02λ × 0.0003λ at the lowest operating frequency, and the antenna operates at 84 MHz. The VSWR 3.5:1 reference operating bandwidth of the antenna is 2%. The received power of the proposed CRLH antenna was measured to verify the antenna performance. Full article
(This article belongs to the Collection Electromagnetic Antennas for HF, VHF, and UHF Band Applications)
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17 pages, 3676 KiB  
Article
Pre-Inpainting Convolutional Skip Triple Attention Segmentation Network for AGV Lane Detection in Overexposure Environment
by Zongxin Yang, Xu Yang, Long Wu, Jiemin Hu, Bo Zou, Yong Zhang and Jianlong Zhang
Appl. Sci. 2022, 12(20), 10675; https://doi.org/10.3390/app122010675 - 21 Oct 2022
Cited by 1 | Viewed by 1219
Abstract
Visual navigation is an important guidance method for industrial automated guided vehicles (AGVs). In the actual guidance, the overexposure environment may be encountered by the AGV lane image, which seriously reduces the accuracy of lane detection. Although the image segmentation method based on [...] Read more.
Visual navigation is an important guidance method for industrial automated guided vehicles (AGVs). In the actual guidance, the overexposure environment may be encountered by the AGV lane image, which seriously reduces the accuracy of lane detection. Although the image segmentation method based on deep learning is widely used in lane detection, it cannot solve the problem of overexposure of lane images. At the same time, the requirements of segmentation accuracy and inference speed cannot be met simultaneously by existing segmentation networks. Aiming at the problem of incomplete lane segmentation in an overexposure environment, a lane detection method combining image inpainting and image segmentation is proposed. In this method, the overexposed lane image is repaired and reconstructed by the MAE network, and then the image is input into the image segmentation network for lane segmentation. In addition, a convolutional skip triple attention (CSTA) image segmentation network is proposed. CSTA improves the inference speed of the model under the premise of ensuring high segmentation accuracy. Finally, the lane segmentation performance of the proposed method is evaluated in three image segmentation evaluation metrics (IoU, F1-score, and PA) and inference time. Experimental results show that the proposed CSTA network has higher segmentation accuracy and faster inference speed. Full article
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13 pages, 280 KiB  
Article
Can Voice Reviews Enhance Trust in Voice Shopping? The Effects of Voice Reviews on Trust and Purchase Intention in Voice Shopping
by Jaeun Seo, Daeho Lee and Inyoung Park
Appl. Sci. 2022, 12(20), 10674; https://doi.org/10.3390/app122010674 - 21 Oct 2022
Cited by 2 | Viewed by 1494
Abstract
Despite the high expectations of the voice shopping market, the impact of reviews and product types on voice commerce has yet to be explored. The purpose of this study is to investigate the effect of reviews and product types on users’ trust and [...] Read more.
Despite the high expectations of the voice shopping market, the impact of reviews and product types on voice commerce has yet to be explored. The purpose of this study is to investigate the effect of reviews and product types on users’ trust and purchase intentions in voice shopping. We explore users’ trust for voice shopping, trust in the vendor and purchase intention in three different types of reviews (i.e., no review, review by rating, and review by feature) and product types (i.e., search goods, experience goods, and convenience goods). We found that review conditions had a significant effect on purchase intentions and trust in voice shopping, whereas product types did not. Even within the review conditions, only the review by rating condition showed a significant difference from the no review condition. This study contributes to consumers and marketers by demonstrating the importance of providing rating reviews which requires a low cognitive load in the audio-centric environment. Full article
(This article belongs to the Special Issue Current Trends in Human-Computer Interaction(HCI))
11 pages, 3870 KiB  
Article
Series-Parallel Generative Adversarial Network Architecture for Translating from Fundus Structure Image to Fluorescence Angiography
by Yiwei Chen, Yi He, Wanyue Li, Jing Wang, Ping Li, Lina Xing, Xin Zhang and Guohua Shi
Appl. Sci. 2022, 12(20), 10673; https://doi.org/10.3390/app122010673 - 21 Oct 2022
Cited by 2 | Viewed by 1168
Abstract
Although fundus fluorescein angiography (FFA) is a very effective retinal imaging tool for ophthalmic diagnosis, the requirement of intravenous injection of harmful fluorescein dye limits its application. As a screening diagnostic method that reduces the frequency of intravenous injection, a series-parallel generative adversarial [...] Read more.
Although fundus fluorescein angiography (FFA) is a very effective retinal imaging tool for ophthalmic diagnosis, the requirement of intravenous injection of harmful fluorescein dye limits its application. As a screening diagnostic method that reduces the frequency of intravenous injection, a series-parallel generative adversarial network (GAN) architecture for translating fundus structure image to FFA images is proposed herein, using deep learning-based software that only needs an intravenous injection for the training process. Firstly, the fundus structure image and the corresponding FFA images of three phases are collected. Secondly, our series-parallel GAN is trained to translate FFA images from fundus structure image with the supervision of FFA images. Thirdly, the trained series-parallel GAN model is used to translate FFA images by only using fundus structure image. By comparing the FFA images translated by our algorithm, Sequence GAN, pix2pix, and cycleGAN, we show the advancement of our algorithm. To further confirm the advancements of our algorithm, we evaluate the peak signal-to-noise ratio (PSNR), structural similarity (SSIM) index, and mean-squared error (MSE) of our algorithm, Sequence GAN, pix2pix, and cycleGAN. To demonstrate the performance of our method, we show some typical FFA images translated by our algorithm. Full article
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7 pages, 1367 KiB  
Communication
Design and Modelling a Graduated Dispenser for Metabolic Diseases—Phenylketonuria
by Corina Adriana Dobocan, Emanuela Pop, Monica Bogdan and Catalin Grec
Appl. Sci. 2022, 12(20), 10672; https://doi.org/10.3390/app122010672 - 21 Oct 2022
Viewed by 979
Abstract
In metabolic diseases such as phenylketonuria (a rare disease), a very important way to keep the patient healthy is the administration of amino acid substitutes. This dispenser was designed because in other places (except home) for patients, it is very difficult to take [...] Read more.
In metabolic diseases such as phenylketonuria (a rare disease), a very important way to keep the patient healthy is the administration of amino acid substitutes. This dispenser was designed because in other places (except home) for patients, it is very difficult to take the substitute powder due to the custom weight, which depends on the body weight. We designed and made on a 3D printer a graduated dosing device (12 g) which can be used very easily and has all the elements to be transported. In this way, the necessary dose of amino acid substitutes can be administered to patients with phenylketonuria, including infants aged 6 months–1 year, at the kindergarten or any other places with the absence of a food scale. This dispenser is very easy to carry and very useful to patients. Full article
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18 pages, 4167 KiB  
Article
Control–Flight Conflict Interdependent Network Based Controllers’ Workload Prediction Evaluation Study
by Yuming Heng, Minggong Wu, Xiangxi Wen and Fugen Lin
Appl. Sci. 2022, 12(20), 10671; https://doi.org/10.3390/app122010671 - 21 Oct 2022
Viewed by 1084
Abstract
As the core link of the air traffic control system, the evaluation and management of controllers’ workload are of great significance for the rapid development of China’s civil aviation industry and aviation safety. To address the problems of strong subjectivity and lag in [...] Read more.
As the core link of the air traffic control system, the evaluation and management of controllers’ workload are of great significance for the rapid development of China’s civil aviation industry and aviation safety. To address the problems of strong subjectivity and lag in the current controller evaluation methods, we propose to construct a flight conflict network and control network based on inter-aircraft flight conflict, controller control relationship and control transfer relationship by using the interdependent network theory. Based on the urgency of inter-aircraft conflict and the control difficulty of controllers, we set the side rights and construct an interdependent network model. Based on the constructed network model, the controller workload is evaluated by selecting the interdependent network index characteristics. Finally, the experimental analysis is carried out by program simulation and control data of Takasaki Airport. The results demonstrate that the method is able to evaluate the controller’s workload. At the same time, it can quickly and accurately identify the key control nodes and provide assistance for controllers to allocate their efforts reasonably. Our proposed controller workload evaluation method enables quantitative analysis and predicts the future workload of controllers based on the potential conflict relationships between air posture and aircraft. The method has strong timeliness and objectivity. At the same time, the constructed interdependent network model can realize the identification of key aircraft in the control area and reflect the impact of key aircraft on the whole network, which can help controllers to perform better control work. Full article
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13 pages, 11521 KiB  
Article
The Geomorphological and Geological Structure of the Samaria Gorge, Crete, Greece—Geological Models Comprehensive Review and the Link with the Geomorphological Evolution
by Emmanouil Manoutsoglou, Ilias Lazos, Emmanouil Steiakakis and Antonios Vafeidis
Appl. Sci. 2022, 12(20), 10670; https://doi.org/10.3390/app122010670 - 21 Oct 2022
Cited by 12 | Viewed by 2434
Abstract
The Samaria Gorge is a dominant geomorphological and geological structure on Crete Island and it is one of the national parks established in Greece. Due to the complex tectonics and the stratigraphic ambiguities imprinted in the geological formations of the area, a comprehensive [...] Read more.
The Samaria Gorge is a dominant geomorphological and geological structure on Crete Island and it is one of the national parks established in Greece. Due to the complex tectonics and the stratigraphic ambiguities imprinted in the geological formations of the area, a comprehensive review of the geological models referring to the geological evolution of the area is essential in order to clarify its geomorphological evolution. In particular, the study area is geologically structured by the Gigilos formation, the Plattenkalk series and the Trypali unit. Regarding lithology, the Gigilos formation predominantly includes phyllites and slates, while the Plattenkalk series and the Trypali unit are mainly structured by metacarbonate rocks; the Plattenkalk series metacarbonate rocks include cherts, while the corresponding ones of the Trypali unit do not. Furthermore, the wider region was subjected to compressional tectonics, resulting in folding occurrences and intense faulting, accompanied by high dip angles of the formations, causing similar differentiations in the relief. Significant lithological differentiations are documented among them, which are further analyzed in relation to stratigraphy, the tectonics, and the erosion rate that changes, due to differentiations of the lithological composition. In addition, the existing hydrological conditions are decisive for further geomorphological evolution. Full article
(This article belongs to the Special Issue Geomorphology in the Digital Era)
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32 pages, 1651 KiB  
Review
Bricks Using Clay Mixed with Powder and Ashes from Lignocellulosic Biomass: A Review
by Ines Labaied, Omar Douzane, Marzouk Lajili and Geoffrey Promis
Appl. Sci. 2022, 12(20), 10669; https://doi.org/10.3390/app122010669 - 21 Oct 2022
Cited by 6 | Viewed by 3451
Abstract
The production of fired or stabilized bricks from lignocellulosic biomass ash is thoroughly examined in this article. Bricks are typically made through the high-temperature firing process or by stabilizing the mixture with binders such as lime and cement. These bricks have a large [...] Read more.
The production of fired or stabilized bricks from lignocellulosic biomass ash is thoroughly examined in this article. Bricks are typically made through the high-temperature firing process or by stabilizing the mixture with binders such as lime and cement. These bricks have a large carbon footprint and high levels of grey energy. In many parts of the world, the excessive use of clay as a natural raw material for the production of conventional bricks will lead to its scarcity. The mixing of clay with lignocellulosic ash during brick manufacturing leads to a better and more reliable solution that conserves scarce natural resources and reduces the impact of environmental pollution. This study aims to review the state of the art in the production of bricks based on lignocellulosic ashes and their physical, thermal, and mechanical properties. The most recent data in the literature related to the manufacture of lignocellulosic ash-based bricks either by firing, cementing or geopolymerization, the design of mixtures, as well as the identification of the main factors influencing the performance and durability of these bricks are presented and discussed. Despite extensive research, there is still very little commercial use of waste bricks in general and lignocellulosic biomass ash in particular. Various toxicity issues of lignocellulosic ash used in brick production limit their use on an industrial scale due to a lack of appropriate standards. In order to achieve practical production of bricks from lignocellulosic ash, research is still needed on standardizing and sustaining biomass ash recycling. Full article
(This article belongs to the Special Issue Application of Municipal/Industrial Solid and Liquid Waste in Energy Area)
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18 pages, 2552 KiB  
Article
An Assessment of Two Types of Industrially Produced Municipal Green Waste Compost by Quality Control Indices
by Daniela V. Borisova, Gergana S. Kostadinova, Georgi S. Petkov, Diyana M. Dermendzhieva and Georgi G. Beev
Appl. Sci. 2022, 12(20), 10668; https://doi.org/10.3390/app122010668 - 21 Oct 2022
Cited by 2 | Viewed by 1315
Abstract
Municipal green waste (MGW) has significantly increased with the development of urban green areas, and its utilization by composting is a good alternative to solve the problem. This paper presents the results from the quality assessment of two industrial composts (from the composting [...] Read more.
Municipal green waste (MGW) has significantly increased with the development of urban green areas, and its utilization by composting is a good alternative to solve the problem. This paper presents the results from the quality assessment of two industrial composts (from the composting facility of a regional nonhazardous waste landfill) based on their physicochemical properties, hygienic safety (microbiological parameters), fertilizing potential (by fertilizing index, FI) and heavy metal polluting potential (by clean index, CI). Compost 1 (C1) was made from MGW (100%) and Compost 2 (C2) was made from MGW (75%) and discarded green peppers (25%). The evaluation of physicochemical parameters was conducted according to Bulgarian Standards (BDS) methods and microbiological analysis using selective, chromogenic detection systems. It was found that the EC, P, K, Mg, Cu, Cr and Ni were lower for C1 (p < 0.05–0.001). On the other hand, Pb concentration was higher compared to C2 (p < 0.001); the concentrations of Cd, Hg and the E. coli were very low for both composts; presence of Salmonella was not detected. The estimated quality indexes (FI and CI) classified C1 as Class B compost (very-good-quality compost with medium fertilizing potential) and C2 as Class A compost (best-quality compost with high soil fertility potential and low heavy metal content). The C1 and C2 composts meet the requirements of EU and Bulgarian legislation and can be used as soil fertilizers. Full article
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22 pages, 6399 KiB  
Article
Electromagnetic Assessment of UHF-RFID Devices in Healthcare Environment
by Victoria Ramos, Oscar J. Suárez, Samuel Suárez, Víctor M. Febles, Erik Aguirre, Patryk Zradziński, Luis E. Rabassa, Mikel Celaya-Echarri, Pablo Marina, Jolanta Karpowicz, Francisco Falcone and José A. Hernández
Appl. Sci. 2022, 12(20), 10667; https://doi.org/10.3390/app122010667 - 21 Oct 2022
Cited by 3 | Viewed by 3271
Abstract
In this work, the evaluation of electromagnetic effect of Ultra High Frequency Radio Frequency Identification (UHF-RFID) passive tags used in the healthcare environment is presented. In order to evaluate exposure levels caused by EM field (865–868 MHz) of UHF-RFID readers, EM measurements in [...] Read more.
In this work, the evaluation of electromagnetic effect of Ultra High Frequency Radio Frequency Identification (UHF-RFID) passive tags used in the healthcare environment is presented. In order to evaluate exposure levels caused by EM field (865–868 MHz) of UHF-RFID readers, EM measurements in an anechoic chamber and in a real medical environment (Hospital Universitario de Canarias), as well as simulations by 3D Ray Launching algorithm, and of biophysical exposure effects in human models are presented. The results obtained show that the EM exposure is localized, in close vicinity of RFID reader and inversely proportional to its reading range. The EM exposure levels detected are sufficient to cause EM immunity effects in electronic devices (malfunctions in medical equipment or implants). Moreover, more than negligible direct effects in humans (exceeding relevant SAR values) were found only next to the reader, up to approximately 30% of the reading range. As a consequence, the EM risk could be firstly evaluated based on RFID parameters, but should include an in situ exposure assessment. It requires attention and additional studies, as increased applications of monitoring systems are observed in the healthcare sector—specifically when any system is located close to the workplace that is permanently occupied. Full article
(This article belongs to the Special Issue RFID(Radio Frequency Identification) Localization and Application)
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14 pages, 14461 KiB  
Article
Research on Electrochemical Controllable Machining Technology of Small-Sized Inner Intersecting Hole Rounding
by Guibing Pang, Zhaobin Yan, Xiaofei Zhu and Shuangjiao Fan
Appl. Sci. 2022, 12(20), 10666; https://doi.org/10.3390/app122010666 - 21 Oct 2022
Viewed by 1303
Abstract
Small-sized inner intersecting holes are a common structure for large engine nozzles, hydraulic valves, and other parts. In order to ensure the uniform and stable fluid state in the intersecting hole, it is necessary to process the fillet at the intersecting line and [...] Read more.
Small-sized inner intersecting holes are a common structure for large engine nozzles, hydraulic valves, and other parts. In order to ensure the uniform and stable fluid state in the intersecting hole, it is necessary to process the fillet at the intersecting line and accurately control the fillet radius. Limited by the structure and size, the rounding of the small-sized inner intersecting hole is a technical problem, and the traditional machining methods have problems, in terms of efficiency and accuracy. In order to solve this problem, electrochemical machining technology was applied to the rounding of small-sized inner intersecting holes. According to the structure of inner intersecting holes, an electrochemical rounding processing scheme with built-in fixed cathode was designed. The electric field distribution of different cathode shapes was analyzed using finite element method software. The influence of processing voltage and processing time on the current density distribution was studied for different cathode shapes, to determine the most reasonable cathode shape. Taking the inner intersecting hole with a diameter of 2 mm as the research object, and according to the analysis of the influence of processing voltage on the processing effect, a suitable control factor for controlling the rounding was processing time, and the optimal processing voltage was obtained. The formulas of fillet radius and processing time were obtained by regression analysis and verified using machining examples. The results provide a feasible method for the accurate and controllable machining of small-sized inner intersecting hole rounding. Full article
(This article belongs to the Special Issue Precision Manufacturing and Intelligent Machine Tools)
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16 pages, 3378 KiB  
Article
Centrifugal Test Replicated Numerical Model Updating for 3D Strutted Deep Excavation with the Response-Surface Method
by Md Mehidi Hassan, Jong Seok Yun, Md Motiur Rahman, Yun Wook Choo, Jin-tae Han and Dookie Kim
Appl. Sci. 2022, 12(20), 10665; https://doi.org/10.3390/app122010665 - 21 Oct 2022
Cited by 2 | Viewed by 1736
Abstract
Centrifugal tests provide an efficacious experimental process to predict the behavior of deep excavations, and numerical models are indispensable for demonstrating the test results and analyzing the engineering demand parameters. Uncertainty in material properties can cause simulations to differ from tests; therefore, updating [...] Read more.
Centrifugal tests provide an efficacious experimental process to predict the behavior of deep excavations, and numerical models are indispensable for demonstrating the test results and analyzing the engineering demand parameters. Uncertainty in material properties can cause simulations to differ from tests; therefore, updating the model becomes inevitable. This study presents a response-surface-based model updating technique for the nonlinear three-dimensional simulation of the centrifugal testing model of strutted deep excavation in sand. An overview of the fundamentals of the response-surface model is provided, including selecting uncertain parameters as input factors, creating a design order for training the model, building a second-order polynomial surface, and updating the input factors through targeted centrifugal results. The bending strains of diaphragm wall panels at multiple points along the depth are used to form the multiobjective function. Response-surface model predictions were well-matched with actual numerical responses, with less than a 0.5% difference. Parametric analyses could be conducted utilizing this updated strutted deep excavation model. Full article
(This article belongs to the Special Issue Advanced Technologies in Deep Excavation)
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22 pages, 565 KiB  
Article
Designing a Deep Q-Learning Model with Edge-Level Training for Multi-Level Task Offloading in Edge Computing Networks
by Ahmad Zendebudi and Salimur Choudhury
Appl. Sci. 2022, 12(20), 10664; https://doi.org/10.3390/app122010664 - 21 Oct 2022
Viewed by 1235
Abstract
Even though small portable devices are becoming increasingly more powerful in terms of processing power and power efficiency, there are still workloads that require more computational capacity than these devices offer. Examples of such workloads are real-time sensory input processing, video game streaming, [...] Read more.
Even though small portable devices are becoming increasingly more powerful in terms of processing power and power efficiency, there are still workloads that require more computational capacity than these devices offer. Examples of such workloads are real-time sensory input processing, video game streaming, and workloads relating to IoT devices. Some of these workloads such as virtual reality, however, require very small latency; hence, the workload cannot be offloaded to a cloud service. To tackle this issue, edge devices, which are closer to the user, are used instead of cloud servers. In this study, we explore the problem of assigning tasks from mobile devices to edge devices in order to minimize the task response latency and the power consumption of mobile devices, as they have limited power capacity. A deep Q-learning model is used to handle the task offloading decision process in mobile and edge devices. This study has two main contributions. Firstly, training a deep Q-learning model in mobile devices is a computational burden for a mobile device; hence, a solution is proposed to move the computation to the connected edge devices. Secondly, a routing protocol is proposed to deliver task results to mobile devices when a mobile device connects to a new edge device and therefore is no longer connected to the edge device to which previous tasks were offloaded. Full article
(This article belongs to the Special Issue Edge Computing Communications)
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23 pages, 5294 KiB  
Systematic Review
Response Surface Methodology Using Observational Data: A Systematic Literature Review
by Mochammad Arbi Hadiyat, Bertha Maya Sopha and Budhi Sholeh Wibowo
Appl. Sci. 2022, 12(20), 10663; https://doi.org/10.3390/app122010663 - 21 Oct 2022
Cited by 9 | Viewed by 3313
Abstract
In the response surface methodology (RSM), the designed experiment helps create interfactor orthogonality and interpretable response models for the purpose of process and design optimization. However, along with the development of data-recording technology, observational data have emerged as an alternative to experimental data, [...] Read more.
In the response surface methodology (RSM), the designed experiment helps create interfactor orthogonality and interpretable response models for the purpose of process and design optimization. However, along with the development of data-recording technology, observational data have emerged as an alternative to experimental data, and they contain potential information on design/process parameters (as factors) and product characteristics that are useful for RSM analysis. Recent studies in various fields have proposed modifications to the standard RSM procedures to adopt observational data and attain considerable results despite some limitations. This paper aims to explore various methods to incorporate observational data in the RSM through a systematic literature review. More than 400 papers were retrieved from the Scopus database, and 83 were selected and carefully reviewed. To adopt observational data, modifications to the procedures of RSM analysis include the design of the experiment (DoE), response modeling, and design/process optimization. The proposed approaches were then mapped to capture the sequence of the modified RSM analysis. The findings highlight the novelty of observational-data-based RSM (RSM-OD) for generating reproducible results involving the discussion of the treatments for observational data as an alternative to the DoE, the refinement of the RSM model to fit the data, and the adaptation of the optimization technique. Future potential research, such as the improvement of factor orthogonality and RSM model modifications, is also discussed. Full article
(This article belongs to the Topic Numerical and Experimental Advances in Innovative Manufacturing Processes)
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14 pages, 3154 KiB  
Article
Analysis of the Driving Force of Spatial and Temporal Differentiation of Carbon Storage in Taihang Mountains Based on InVEST Model
by Chengwu Wang, Junjie Luo, Feng Qing, Yong Tang and Yunfei Wang
Appl. Sci. 2022, 12(20), 10662; https://doi.org/10.3390/app122010662 - 21 Oct 2022
Cited by 9 | Viewed by 1683
Abstract
The Taihang Mountains are an important ecological barrier in China, and their ecosystems have good carbon sink capacity. Studying the spatial-temporal variation characteristics and driving factors of carbon storage in the Taihang Mountains ecosystem provides decision-making for the construction of “dual carbon” projects [...] Read more.
The Taihang Mountains are an important ecological barrier in China, and their ecosystems have good carbon sink capacity. Studying the spatial-temporal variation characteristics and driving factors of carbon storage in the Taihang Mountains ecosystem provides decision-making for the construction of “dual carbon” projects and the improvement of ecological environment quality in this region. This paper takes the area in the Taihang Mountains as the research area, based on the land use and carbon density data of 2005, 2010, 2015, and 2019 of the Taihang Mountains, calculates the carbon storage in the region with the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model, explores the main factors affecting the spatial differentiation of carbon storage in this region, and analyzes their driving mechanisms by Geodetector. The results show that: (1) From 2005 to 2019, the land use of the Taihang Mountains changed somewhat. The area of forest and construction land increased slightly, while the area of farmland and grassland decreased. (2) The current carbon storage in the Taihang Mountains ranges from 1472.91 × 106 t to 1478.17 × 106 t (t is the abbreviation of ton), and shows a decreasing trend, which is due to the decrease in forest and the increase in construction land. (3) Slope and Normalized Difference Vegetation Index (NDVI) are the main driving factors affecting the spatial variation of carbon storage in the Taihang Mountains ecosystem. Temperature, precipitation, and population density are the secondary factors affecting the spatial variation of carbon storage. (4) The synergy between the driving factors is more potent than the individual factor, which is the most evident between NDVI and slope. This means some areas may have more abundant carbon storage under the combined effect of slope and NDVI. Full article
(This article belongs to the Special Issue Applications and Challenges in Carbon Capture, Utilization and Storage)
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9 pages, 2285 KiB  
Brief Report
Contact Lens-Based Microchannel Rings for Detecting Ocular Hypertension
by Yousef Alqurashi, Mohamed Elsherif, Rosalia Moreddu, Magdalena Cieslak, Hemeth Dhaliwal, Khamis Essa and Haider Butt
Appl. Sci. 2022, 12(20), 10661; https://doi.org/10.3390/app122010661 - 21 Oct 2022
Viewed by 1382
Abstract
Glaucoma is a major cause of irreversible blindness worldwide. The most acknowledged biomarker to diagnose and monitor glaucoma progression is intraocular pressure (IOP). Gold standard techniques for IOP monitoring are invasive, uncomfortable, and require visiting a clinic. In addition, most methods only provide [...] Read more.
Glaucoma is a major cause of irreversible blindness worldwide. The most acknowledged biomarker to diagnose and monitor glaucoma progression is intraocular pressure (IOP). Gold standard techniques for IOP monitoring are invasive, uncomfortable, and require visiting a clinic. In addition, most methods only provide a single snapshot on widely varying parameters. On the other hand, contact lenses have attracted particular interest to be used as continuous monitoring platforms to incorporate sensors, drugs, and more. Here, commercial contact lenses were laser-processed to be capable of detecting IOP variations in the physiological range. Three ring-couples with interspaces of 1.0, 1.5, and 2.0 mm were engraved on three soft contact lenses separately by using a carbon dioxide laser. The IOP/pressure variations induced repeatable changes in the ring-couple interspace which acted as a smartphone-readable pressure sensor. The processed contact lenses may be a potential candidate toward IOP monitoring at point-of-care settings. Full article
(This article belongs to the Special Issue Recent Advances in Pathogenesis and Management of Eye Diseases)
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