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Appl. Sci., Volume 12, Issue 22 (November-2 2022) – 567 articles

Cover Story (view full-size image): In recent years, gesture recognition and speech recognition, as important input methods in Human–Computer Interaction (HCI), have been widely used in the field of virtual reality. In particular, with the rapid development of deep learning, artificial intelligence, and other computer technologies, gesture recognition and speech recognition have achieved breakthrough research progress. The realization of gesture interaction and voice interaction in HCI is summarized, and the advantages brought by deep learning are selected for research. Then, the progress of gesture recognition and speech recognition interaction is analyzed. Finally, the current HCI in the direction of natural language processing is investigated. View this paper
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20 pages, 1537 KiB  
Article
Imaginary Speech Recognition Using a Convolutional Network with Long-Short Memory
Appl. Sci. 2022, 12(22), 11873; https://doi.org/10.3390/app122211873 - 21 Nov 2022
Cited by 2 | Viewed by 1835
Abstract
In recent years, a lot of researchers’ attentions were concentrating on imaginary speech understanding, decoding, and even recognition. Speech is a complex mechanism, which involves multiple brain areas in the process of production, planning, and precise control of a large number of muscles [...] Read more.
In recent years, a lot of researchers’ attentions were concentrating on imaginary speech understanding, decoding, and even recognition. Speech is a complex mechanism, which involves multiple brain areas in the process of production, planning, and precise control of a large number of muscles and articulation involved in the actual utterance. This paper proposes an intelligent imaginary speech recognition system of eleven different utterances, seven phonemes, and four words from the Kara One database. We showed, during our research, that the feature space of the cross-covariance in frequency domain offers a better perspective of the imaginary speech by computing LDA for 2D representation of the feature space, in comparison to cross-covariance in the time domain and the raw signals without any processing. In the classification stage, we used a CNNLSTM neural network and obtained a performance of 43% accuracy for all eleven different utterances. The developed system was meant to be a subject’s shared system. We also showed that, using the channels corresponding to the anatomical structures of the brain involved in speech production, i.e., Broca area, primary motor cortex, and secondary motor cortex, 93% of information is preserved, obtaining 40% accuracy by using 29 electrodes out of the initial 62. Full article
(This article belongs to the Special Issue Applied Artificial Intelligence (AI))
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16 pages, 3583 KiB  
Article
Laboratory Experimental Study on Polymer Flooding in High-Temperature and High-Salinity Heavy Oil Reservoir
Appl. Sci. 2022, 12(22), 11872; https://doi.org/10.3390/app122211872 - 21 Nov 2022
Cited by 4 | Viewed by 1889
Abstract
Polyacrylamide (HPAM) and other traditional polymers have poor temperature resistance and salinity tolerance and do not meet the needs of high-temperature and high-salinity reservoirs. In this study, a new temperature-resistant and salinity-tolerant polymer QJ75-39 was synthesized using acrylamide (AM) as a hydrophilic monomer, [...] Read more.
Polyacrylamide (HPAM) and other traditional polymers have poor temperature resistance and salinity tolerance and do not meet the needs of high-temperature and high-salinity reservoirs. In this study, a new temperature-resistant and salinity-tolerant polymer QJ75-39 was synthesized using acrylamide (AM) as a hydrophilic monomer, 1-acrylamide-2-methylpropanesulfonic acid (AMPS) and N-vinylpyrrolidone (NVP) as functional monomers and DS-16 as a hydrophobic monomer. Through laboratory experiments, the properties (temperature resistance, salinity tolerance and aging stability), polymer injection and core displacement effect of the polymer were studied. The experimental results showed that the new polymer could meet the needs of polymer flooding technology in high-temperature and high-salinity reservoirs. Experiments showed that the polymer had a temperature resistance of 95 °C and a salinity tolerance of 1.66 × 105 mg/L. When the temperature was 95 °C and the TDS was 55,376.8 mg/L, the viscosity of the polymer was 31.3 mPa s, and the viscosity remained above 30 mPa·s after aging for 60 days. The polymer had good injectivity between 300 and 600 mD, and the injection pressure could reach equilibrium quickly. The oil recovery effectively increased with the grsowth in the amount of injected polymer. When the injection amount was 0.5 PV, the enhanced oil recovery was 20.65%. This study is of great significance for the application and popularization of polymer flooding technology in high-temperature and high-salinity reservoirs. Full article
(This article belongs to the Section Applied Industrial Technologies)
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33 pages, 16646 KiB  
Article
Triple Phase Shift Control of Wireless Charging DAB LCC Resonant Converter for Unity Power Factor Operation with Optimized Rectifier AC Load Resistance
Appl. Sci. 2022, 12(22), 11871; https://doi.org/10.3390/app122211871 - 21 Nov 2022
Cited by 3 | Viewed by 1943
Abstract
This paper presents a new triple phase shift (TPS) closed-loop control scheme of a dual active bridge (DAB) LCC resonant DC/DC converter to improve wireless charging power transfer efficiency. The primary side inverter phase shift angle regulates the battery charging current/voltage. The secondary [...] Read more.
This paper presents a new triple phase shift (TPS) closed-loop control scheme of a dual active bridge (DAB) LCC resonant DC/DC converter to improve wireless charging power transfer efficiency. The primary side inverter phase shift angle regulates the battery charging current/voltage. The secondary side rectifier phase shift angle regulates the rectifier AC load resistance to match its optimized setting. The inverter-to-rectifier phase shift angle is set to achieve unity power factor operation of the DAB rectifier and inverter. The mathematical formulation of the TPS shift control is given for each phase shift angle. The analytical calculation, circuit simulation, and experimental test are carried out in a power scaled-down DAB LCC resonant wireless charging converter laboratory hardware setup to validate the proposed TPS close-loop control scheme. The PLECS circuit simulation shows that DAB LCC resonant SiC MOSFET operates at zero-voltage-switching (ZVS) with a unity power factor in emulated constant current (CC) mode battery charging. In constant voltage (CV) mode operation, one inverter/rectifier Leg does not operate at ZVS switching when Sic MOSFET is switched on near zero current. The experimental results show that the efficiency is greatly improved for CV mode charging with large DC load resistance connected if rectifier AC load resistance matching control is enabled. The measured efficiency matches well with the analytical calculation. The estimated efficiency improvement will be much more significant for EV applications in the kW power range with greater winding loss. The challenges and possible solutions to implement TPS PWM modulation in two separate inverter and rectifier control hardware are explained for future TPS control algorithm development in practical wireless charging products. Full article
(This article belongs to the Special Issue Electric Power Applications)
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20 pages, 752 KiB  
Article
Improving the Robustness and Quality of Biomedical CNN Models through Adaptive Hyperparameter Tuning
Appl. Sci. 2022, 12(22), 11870; https://doi.org/10.3390/app122211870 - 21 Nov 2022
Cited by 5 | Viewed by 2062
Abstract
Deep learning is an obvious method for the detection of disease, analyzing medical images and many researchers have looked into it. However, the performance of deep learning algorithms is frequently influenced by hyperparameter selection, the question of which combination of hyperparameters are best [...] Read more.
Deep learning is an obvious method for the detection of disease, analyzing medical images and many researchers have looked into it. However, the performance of deep learning algorithms is frequently influenced by hyperparameter selection, the question of which combination of hyperparameters are best emerges. To address this challenge, we proposed a novel algorithm for Adaptive Hyperparameter Tuning (AHT) that automates the selection of optimal hyperparameters for Convolutional Neural Network (CNN) training. All of the optimal hyperparameters for the CNN models were instantaneously selected and allocated using a novel proposed algorithm Adaptive Hyperparameter Tuning (AHT). Using AHT, enables CNN models to be highly autonomous to choose optimal hyperparameters for classifying medical images into various classifications. The CNN model (Deep-Hist) categorizes medical images into basic classes: malignant and benign, with an accuracy of 95.71%. The most dominant CNN models such as ResNet, DenseNet, and MobileNetV2 are all compared to the already proposed CNN model (Deep-Hist). Plausible classification results were obtained using large, publicly available clinical datasets such as BreakHis, BraTS, NIH-Xray and COVID-19 X-ray. Medical practitioners and clinicians can utilize the CNN model to corroborate their first malignant and benign classification assessment. The recommended Adaptive high F1 score and precision, as well as its excellent generalization and accuracy, imply that it might be used to build a pathologist’s aid tool. Full article
(This article belongs to the Section Computing and Artificial Intelligence)
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14 pages, 4708 KiB  
Article
Identification of Content-Adaptive Image Steganography Using Convolutional Neural Network Guided by High-Pass Kernel
Appl. Sci. 2022, 12(22), 11869; https://doi.org/10.3390/app122211869 - 21 Nov 2022
Cited by 1 | Viewed by 1428
Abstract
Digital images are very popular and commonly used for hiding crucial data. In a few instances, image steganography is misused for communicating with improper data. In this paper, a robust deep neural network is proposed for the identification of content-adaptive image steganography schemes. [...] Read more.
Digital images are very popular and commonly used for hiding crucial data. In a few instances, image steganography is misused for communicating with improper data. In this paper, a robust deep neural network is proposed for the identification of content-adaptive image steganography schemes. Multiple novel strategies are applied to improve detection performance. Two non-trainable convolutional layers is used to guide the proposed CNN with fixed kernels. Thirty-one kernels are used in both non-trainable layers, of which thirty are high-pass kernels and one is the neutral kernel. The layer-specific learning rate is applied for each layer. ReLU with customized thresholding is applied to achieve better performance. In the proposed method, image down-sampling is not performed; only the global average pooling layer is considered in the last part of the network. The experimental results are verified on BOWS2 and BOSSBase image sets. Content-adaptive steganography schemes, such as HILL, Mi-POD, S-UNIWARD, and WOW, are considered for generating the stego images with different payloads. In experimental analysis, the proposed scheme is compared with some of the latest schemes, where the proposed scheme outperforms other state-of-the-art techniques in the most cases. Full article
(This article belongs to the Special Issue Development of IoE Applications for Multimedia Security)
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14 pages, 5915 KiB  
Article
Study on Size Optimization of a Protective Coal Pillar under a Double-Key Stratum Structure
Appl. Sci. 2022, 12(22), 11868; https://doi.org/10.3390/app122211868 - 21 Nov 2022
Cited by 4 | Viewed by 905
Abstract
Because of the problem that the size of a coal pillar is difficult to determine and it is easy to waste coal resources, taking the Sangou Xindu coal industry as the engineering background, this paper examined the roof cutting and pressure relief technology [...] Read more.
Because of the problem that the size of a coal pillar is difficult to determine and it is easy to waste coal resources, taking the Sangou Xindu coal industry as the engineering background, this paper examined the roof cutting and pressure relief technology of small coal pillar gob-side entry driving by means of theoretical analysis, laboratory experiments, and numerical simulation. Through theoretical calculations, the coal pillar width should not be less than 7.15 m without cutting the top. According to the theory of key strata, there are two key strata in the overlying strata on the working face, namely the main key strata and the subkey strata. Through numerical simulation, the stress evolution characteristics of the coal at the side of the goaf under the double-key stratum roof cutting structure are studied. When the roof is not cut, the roof cutting height is 6 m and 12 m and the width of the lateral stress reduction zone in the goaf is 4 m, 8 m, and 10.5 m, respectively. Therefore, the cutting top height is determined to be 12 m and the hydraulic fracturing cutting plan is designed. After cutting the top of the main key stratum, the size of the coal pillar is optimized. Three schemes of coal pillar sizes of 6 m, 5 m, and 4 m are designed for simulation and the analysis shows that it is most reasonable to keep a 5 m wide coal pillar. After field application, the deformation of the surrounding rock in the roadway is within a controllable range and the roadway use is good. Full article
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20 pages, 5292 KiB  
Article
Experimental Study and Numerical Simulation of W/O Emulsion in Developing Heavy Oil Reservoirs
Appl. Sci. 2022, 12(22), 11867; https://doi.org/10.3390/app122211867 - 21 Nov 2022
Cited by 2 | Viewed by 1357
Abstract
In the process of waterflooding development of heavy oil, W/O emulsion has a strong ability to improve the mobility ratio and block the high-permeability layer, which can effectively improve the sweep coefficient and enhance oil recovery. In this paper, the stability and droplet [...] Read more.
In the process of waterflooding development of heavy oil, W/O emulsion has a strong ability to improve the mobility ratio and block the high-permeability layer, which can effectively improve the sweep coefficient and enhance oil recovery. In this paper, the stability and droplet size distribution of emulsions under different conditions were studied by taking heavy oil and formation water from Jimusar Oilfield in Xinjiang as samples. On this basis, double-pipe core flooding experiments were carried out to study the shut-off ability and oil displacement efficiency of W/O emulsion, and then a numerical simulation was carried out. The results show that oil and water can be completely emulsified when the stirring speed is higher than 4000 r/min. A stable emulsion can be formed when the experimental temperature is lower than 60 °C. A lower water cut results in a more stable emulsion. The emulsion is difficult to stabilize after the salinity exceeds 10,000 mg/L. When the pH value is about 7, the stability of the emulsion is the worst. With the increase in stirring speed, the increase in temperature, and the decrease in water content and salinity, the emulsion droplet size range is relatively concentrated, and the average particle size is smaller. In heterogeneous reservoirs, the permeability of different percolation channels is quite different, such that the displacement fluid only percolates along the high-permeability channel and cannot drive oil effectively. The results of displacement experiments show that the emulsion with a water cut of 60% has high viscosity and obvious sweep ability, but its stability is very poor; the effect is opposite when the water cut is less than 40%. The shut-off ability of W/O emulsion disappears gradually when the permeability contrast is more than 5.92. The research results are of great significance for improving oil recovery in heterogeneous heavy oil reservoirs. Full article
(This article belongs to the Section Applied Industrial Technologies)
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23 pages, 4010 KiB  
Article
Stability of MSW Landfill Slopes Reinforced with Geogrids
Appl. Sci. 2022, 12(22), 11866; https://doi.org/10.3390/app122211866 - 21 Nov 2022
Cited by 2 | Viewed by 1471
Abstract
Slope stability is one of the main problems encountered in MSW (municipality solid waste) landfill designs. Slope stability calculations become difficult due to the heterogeneous structure of MSW landfills and leachate, and therefore, slope geometries are formed by choosing low slope angles for [...] Read more.
Slope stability is one of the main problems encountered in MSW (municipality solid waste) landfill designs. Slope stability calculations become difficult due to the heterogeneous structure of MSW landfills and leachate, and therefore, slope geometries are formed by choosing low slope angles for safe designs. This causes less waste to be stored on site. This study presents slope stability analyses of MSW landfills. Numerical analyses were performed using finite element and limit equilibrium methods. The stability behavior of landfill slopes was analyzed for both unreinforced and geogrid-reinforced conditions in order to investigate the effects of shear strength parameters, the unit weight of soil waste, and material model parameters. It has been seen that the stability of landfill slopes can be increased significantly using geogrid materials. When the optimum geogrid parameters obtained from the numerical analysis results are used, it has been observed that the safety factor of the slope can be increased by up to approximately two times. Slopes in landfills reinforced with geogrid reinforcements can be formed steeper, allowing more solid waste to be stored. Considering the high initial investment cost of MSW landfills, it has been concluded that storing more solid waste with the use of geogrids will provide significant economic gains. Based on the results, the optimum values of geogrid parameters were determined and suggested for maximum reinforcing effects in MSW landfill slopes. Full article
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34 pages, 4328 KiB  
Review
Modern Techniques for Flavonoid Extraction—To Optimize or Not to Optimize?
Appl. Sci. 2022, 12(22), 11865; https://doi.org/10.3390/app122211865 - 21 Nov 2022
Cited by 7 | Viewed by 4357
Abstract
Flavonoids, specialized metabolites found in plants, have a number of beneficial properties and are important for maintaining good health. Efficient extraction methods are required to extract the most bioactive compounds from plant material. Modern techniques are replacing conventional methods of flavonoids extraction in [...] Read more.
Flavonoids, specialized metabolites found in plants, have a number of beneficial properties and are important for maintaining good health. Efficient extraction methods are required to extract the most bioactive compounds from plant material. Modern techniques are replacing conventional methods of flavonoids extraction in order to reduce energy and solvent consumption, increase extraction efficiency, and satisfy growing market demand as well as environmental legislation. The extraction of bioactive molecules compounds is affected by a number of variables. To determine the conditions that ensure the highest extraction yield, it is advisable to analyze the interactions between the above in parallel. In this work, an overview of the advantages and performance of modern methods (microwave-assisted extraction, ultrasound-assisted extraction, pressurized liquids-assisted extraction, and supercritical fluids extraction) for the extraction of flavonoids is presented. This work also presents the application of extraction process optimization and extraction kinetics for flavonoid extraction, using different types of experimental designs for different flavonoid sources and different extraction methods. The general conclusion of all the studies listed is that an experimental design combined with RSM modeling reduces the number of experiments that should be performed to achieve maximum extraction yield. Full article
(This article belongs to the Special Issue Knowledge-Based Biotechnology for Food, Agriculture and Fisheries)
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20 pages, 731 KiB  
Review
Trends and Application of Artificial Intelligence Technology in Orthodontic Diagnosis and Treatment Planning—A Review
Appl. Sci. 2022, 12(22), 11864; https://doi.org/10.3390/app122211864 - 21 Nov 2022
Cited by 9 | Viewed by 2718
Abstract
Artificial intelligence (AI) is a new breakthrough in technological advancements based on the concept of simulating human intelligence. These emerging technologies highly influence the diagnostic process in the field of medical sciences, with enhanced accuracy in diagnosis. This review article intends to report [...] Read more.
Artificial intelligence (AI) is a new breakthrough in technological advancements based on the concept of simulating human intelligence. These emerging technologies highly influence the diagnostic process in the field of medical sciences, with enhanced accuracy in diagnosis. This review article intends to report on the trends and application of AI models designed for diagnosis and treatment planning in orthodontics. A data search for the original research articles that were published over the last 22 years (from 1 January 2000 until 31 August 2022) was carried out in the most renowned electronic databases, which mainly included PubMed, Google Scholar, Web of Science, Scopus, and Saudi Digital Library. A total of 56 articles that met the eligibility criteria were included. The research trend shows a rapid increase in articles over the last two years. In total: 17 articles have reported on AI models designed for the automated identification of cephalometric landmarks; 12 articles on the estimation of bone age and maturity using cervical vertebra and hand-wrist radiographs; two articles on palatal shape analysis; seven articles for determining the need for orthodontic tooth extractions; two articles for automated skeletal classification; and 16 articles for the diagnosis and planning of orthognathic surgeries. AI is a significant development that has been successfully implemented in a wide range of image-based applications. These applications can facilitate clinicians in diagnosing, treatment planning, and decision-making. AI applications are beneficial as they are reliable, with enhanced speed, and have the potential to automatically complete the task with an efficiency equivalent to experienced clinicians. These models can prove as an excellent guide for less experienced orthodontists. Full article
(This article belongs to the Special Issue Applied and Innovative Computational Intelligence Systems)
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17 pages, 2479 KiB  
Article
Towards an Automatic Test Generation Method for Systems of Systems Based on Fault Injection and Model-Based Systems Engineering
Appl. Sci. 2022, 12(22), 11863; https://doi.org/10.3390/app122211863 - 21 Nov 2022
Viewed by 1064
Abstract
The emergence and development of systems of systems (SoSs) have expanded the complexity and adaptability of systems engineering. Due to the heterogeneity of its constituent systems, designing and analyzing an SoS faces enormous challenges. Therefore, the verification of an SoS is important in [...] Read more.
The emergence and development of systems of systems (SoSs) have expanded the complexity and adaptability of systems engineering. Due to the heterogeneity of its constituent systems, designing and analyzing an SoS faces enormous challenges. Therefore, the verification of an SoS is important in its design phase. However, related methods and techniques are still in the preliminary research state, mainly for requirements verification and system verification, and a lack of efforts in design verification for SoSs. Aiming to provide the ability to detect hazardous states at the design phase, we worked on a novel method for automatically generating test cases for model verification in SoSs. Considering the characteristics of SoSs, the method adopts fault injection and model-based system engineering as the foundations to extend the automated generation capability of test cases. This paper proposes an automatic test generation (ATG) method for an SoS based on fault injection and model-based systems engineering (MBSE). It is meant to generate test cases that can be used to check the effectiveness of fault detection or identification in SoSs and for the effective testing of their constituent systems (CSs). This paper discusses scenario generation and ATG in linear temporal logic and designs an algorithm to generate traces as test suites, taking into account the constraints of the models. By establishing a concept alignment example (CAE) as the experimental use case, three test scenarios are generated automatically, showing that the use of the proposed ATG method provides a reasonable hazardous detection capability for verification in SoS design. The main contributions of the paper are (1) the description of the proposed two-phase ATG approach with fault-centric modeling activities and generation-related activities; (2) the explanation of the designed ATG algorithm at both high and low levels; and (3) the discussion of the experiment in an emergency response CAE with three generated test scenarios. Full article
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10 pages, 2409 KiB  
Article
A Study on the Efficiency in the Energy Harvesting Device Using Resonance of Pendulum
Appl. Sci. 2022, 12(22), 11862; https://doi.org/10.3390/app122211862 - 21 Nov 2022
Cited by 1 | Viewed by 1087
Abstract
Recently, increased public interest in pollution caused by fossil fuels has prompted studies on various renewable energy sources. As it is important to ensure power generation efficiency in energy harvesting, research in this area continues. Therefore, this paper presents the results of a [...] Read more.
Recently, increased public interest in pollution caused by fossil fuels has prompted studies on various renewable energy sources. As it is important to ensure power generation efficiency in energy harvesting, research in this area continues. Therefore, this paper presents the results of a numerical analysis to calculate the efficiency of an energy harvesting generator that uses pendulum resonance. The Lagrange equation was used to derive the numerical model of the pendulum, which in turn was used to derive the angle of power generation and time required to reach this angle. The power generation efficiency was derived by calculating the input and output work using the power generation angle and time obtained from the numerical model. In addition, the effect of design variables, such as the mass of the pendulum, the length of the pendulum, and angle at which power generation starts, on the efficiency is considered by presenting an efficiency map. The efficiency map presented in this study is expected to be an important reference for designing highly efficient energy harvesting devices using pendulum resonance. Full article
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22 pages, 2248 KiB  
Article
Improving User Intent Detection in Urdu Web Queries with Capsule Net Architectures
Appl. Sci. 2022, 12(22), 11861; https://doi.org/10.3390/app122211861 - 21 Nov 2022
Cited by 2 | Viewed by 2641
Abstract
Detecting the communicative intent behind user queries is critically required by search engines to understand a user’s search goal and retrieve the desired results. Due to increased web searching in local languages, there is an emerging need to support the language understanding for [...] Read more.
Detecting the communicative intent behind user queries is critically required by search engines to understand a user’s search goal and retrieve the desired results. Due to increased web searching in local languages, there is an emerging need to support the language understanding for languages other than English. This article presents a distinctive, capsule neural network architecture for intent detection from search queries in Urdu, a widely spoken South Asian language. The proposed two-tiered capsule network utilizes LSTM cells and an iterative routing mechanism between the capsules to effectively discriminate diversely expressed search intents. Since no Urdu queries dataset is available, a benchmark intent-annotated dataset of 11,751 queries was developed, incorporating 11 query domains and annotated with Broder’s intent taxonomy (i.e., navigational, transactional and informational intents). Through rigorous experimentation, the proposed model attained the state of the art accuracy of 91.12%, significantly improving upon several alternate classification techniques and strong baselines. An error analysis revealed systematic error patterns owing to a class imbalance and large lexical variability in Urdu web queries. Full article
(This article belongs to the Special Issue Natural Language Processing (NLP) and Applications)
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22 pages, 5475 KiB  
Article
Improved Belgian AI Algorithm for Dynamic Management in Action Role-Playing Games
Appl. Sci. 2022, 12(22), 11860; https://doi.org/10.3390/app122211860 - 21 Nov 2022
Cited by 2 | Viewed by 1517
Abstract
Artificial intelligence in games is one of the most challenging tasks in academia and industry. In action role-playing games, how to manage combat effectively is a key issue related to game development and the player’s experience. The Belgian artificial intelligence (BAI) algorithm is [...] Read more.
Artificial intelligence in games is one of the most challenging tasks in academia and industry. In action role-playing games, how to manage combat effectively is a key issue related to game development and the player’s experience. The Belgian artificial intelligence (BAI) algorithm is a classic but limited method that is widely used for combat management between the player and enemies. To address the poor adaptability of BAI, this paper proposes an improved Belgian artificial intelligence (IBAI) algorithm with dynamic difficulty adjustment (DDA) and implements two systems separately based on BAI and IBAI in Unreal Engine 4. Advantages on 12 parameters—10.086 mean total score greater, and 0.079 standard deviation smaller—demonstrate that the system based on IBAI has higher adaptability and a better player experience by comparing the two systems in different situations and inviting players to participate in gameplay experiences and questionnaires. The robust dynamic management mechanism of IBAI can help game designers and developers achieve the combat system of action role-playing games more efficiently, thus, shortening the development cycle and improving the player retention rate. Full article
(This article belongs to the Special Issue Artificial Intelligence in Video Games)
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14 pages, 715 KiB  
Systematic Review
Effects of Surgically Assisted Rapid Palatal Expansion on Facial Soft Tissues: A Systematic Review
Appl. Sci. 2022, 12(22), 11859; https://doi.org/10.3390/app122211859 - 21 Nov 2022
Viewed by 1256
Abstract
Surgically assisted rapid palatal expansion (SARPE) is a successful method for treating transverse discrepancies in adult patients. The relocation of maxillary segments may induce changes at the surrounding soft tissues as well. The aim of this systematic review was to examine the possible [...] Read more.
Surgically assisted rapid palatal expansion (SARPE) is a successful method for treating transverse discrepancies in adult patients. The relocation of maxillary segments may induce changes at the surrounding soft tissues as well. The aim of this systematic review was to examine the possible effects that SARPE may have in the soft tissues of the face. Our search strategy included electronic databases (Pubmed, Scopus, ProQuest, Google Scholar, Cochrane Library) and a hand search of the reference list of found reviews. A priori definition of inclusion and exclusion criteria was made. Finally, 15 articles were included in qualitative synthesis. Risk of bias was generally high among the included studies. Study outcomes included nasal, labial, nasolabial and other facial soft tissue measurements. The evaluation of the changes was two-dimensional in six studies, and three-dimensional in nine studies. Meta-analysis was unfeasible due to lack of standardization, important methodological limitations, and shortcomings of the studies. A post-surgical increase in the dimensions of the alar width and the alar base width was commonly reported among the included studies. However, the above should be considered with caution due to the high risk of bias and the inability for quantitative synthesis. Full article
(This article belongs to the Special Issue Advances in Maxillofacial and Oral Surgery)
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25 pages, 8577 KiB  
Article
Multivehicle Point-to-Point Network Problem Formulation for UAM Operation Management Used with Dynamic Scheduling
Appl. Sci. 2022, 12(22), 11858; https://doi.org/10.3390/app122211858 - 21 Nov 2022
Cited by 1 | Viewed by 1968
Abstract
In this paper, we introduce a new formulation of the multivehicle point-to-point network problem to be utilised in urban air mobility (UAM) vertiport-to-vertiport network operations. Vehicle routing problems (VRPs) and their variants have previously been studied and applied in real-world situations, but these [...] Read more.
In this paper, we introduce a new formulation of the multivehicle point-to-point network problem to be utilised in urban air mobility (UAM) vertiport-to-vertiport network operations. Vehicle routing problems (VRPs) and their variants have previously been studied and applied in real-world situations, but these problems require additional depot locations, and not all the vehicles can travel to all the locations. In UAM operations, additional depot locations may not be required, and all vehicles can travel to all locations, meaning that existing routing problems are not suitable for application to the management of UAMs. Therefore, we propose a new formulation for UAM vertiport-to-vertiport operation by introducing new constraints. In addition, we integrate dynamic scheduling with the flight mission by controlling cruise speed and waiting in each UAM at each vertiport location to generate an arrival and departure schedule for different vertiports that can avoid collisions and increase the number of vehicles. A computational experiment is conducted using an MILP model, and the results show that although our formulation satisfies the problem definition, the computation time increases exponentially with an increase in the problem size. A case study is conducted in the Seoul area involving five vertiports, with 10- and 15-vehicle scenarios studied. This case study shows that the cruise speed variable is active only for the lower and upper bounds under dynamic scheduling, whereas the waiting time variable can be controlled between user-defined limits that can be applied to the management of vertiport-to-vertiport UAM operations. Full article
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19 pages, 1095 KiB  
Article
RIS-Assisted High-Speed Communications with Time-Varying Distance-Dependent Rician Channels
Appl. Sci. 2022, 12(22), 11857; https://doi.org/10.3390/app122211857 - 21 Nov 2022
Cited by 1 | Viewed by 1710
Abstract
Reconfigurable intelligent surface (RIS) has been envisioned as one of the promising solutions for enhancing signal transmissions in high-speed communications (HSC). In this paper, we present a time-varying channel model with distance-dependent Rician factors for the RIS-assisted HSC. Our model not only contains [...] Read more.
Reconfigurable intelligent surface (RIS) has been envisioned as one of the promising solutions for enhancing signal transmissions in high-speed communications (HSC). In this paper, we present a time-varying channel model with distance-dependent Rician factors for the RIS-assisted HSC. Our model not only contains Rayleigh components and Doppler shift (DS) terms but also distance-dependent Rician factors, for characterizing time-varying features. In particular, we show that when the vehicle is far from the base station and the RIS, the channel contains only Rayleigh fading. However, when they are close enough, the channel can be considered as a light-of-sight channel. Based on the proposed model, it is proven that using RIS phase shift optimization, the DS of the cascaded links can be aligned with the DS of the direct link; and if the direct link is blocked, the DS can be removed entirely. Furthermore, we derive the closed-form expressions for the ergodic spectral efficiency and the outage probability of the proposed system. Besides, it is observed that the deployment strategy also affects the system performance. Simulation results validate all analyses. Full article
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14 pages, 1907 KiB  
Article
Balance Stability and Cervical Spine Range of Motion While Wearing a Custom-Made Mandibular Splint with Special Consideration of the Sex
Appl. Sci. 2022, 12(22), 11856; https://doi.org/10.3390/app122211856 - 21 Nov 2022
Cited by 1 | Viewed by 1126
Abstract
Introduction: An altered dental occlusion can also affect balance stability or mobility. Thus, the aim of this study was to examine whether wearing a mandibular splint, which retains the occlusion close to the centric occlusion, can increase or decrease balance stability and the [...] Read more.
Introduction: An altered dental occlusion can also affect balance stability or mobility. Thus, the aim of this study was to examine whether wearing a mandibular splint, which retains the occlusion close to the centric occlusion, can increase or decrease balance stability and the range of motion (ROM) of the cervical spine as opposed to the habitual occlusion, and if there is a difference between men and women. Material and methods: In this study, 41 male (34.7 ± 11.4 years) and 50 female subjects (29.3 ± 12.7 years) participated. Cervical spine ROM was recorded using the Zebris CMS 70P system. For balance stability, a pressure measuring platform integrated into the treadmill system (FDM-T) of the company Zebris® Medical GmbH was used. Here, the area of the ellipse and the length of the Center of Pressure (CoP) was recorded whilst in the bipedal and unipedal stance. Results: The sex comparison showed significant differences for the area of the ellipse of the right leg and ROM extension in the habitual occlusion: females showed a better balance stability and a larger ROM extension. When wearing the splint, only the CoP of the left leg was significant with a better balance stability in female subjects. Within the male subjects, the ellipse area in the bipedal and unipedal (left/right) stance showed mostly significant reductions, while the rotation left and right as well as the lateral flexion (left/right) improved when wearing the splint. Female subjects, when wearing the splint, showed a significant decrease of the ellipse area and the CoP length when standing on either leg. Flexion, rotation to the right and lateral flexion to the left/right, all increased significantly. Conclusion: Wearing a splint that keeps the jaw close to the centric relation improved balance stability and increased the ROM of the cervical spine for both male and female subjects. Women may have marginally different basic balance stability strategies than men, with regard to bipedal and unipedal standing. Nevertheless, there are scarcely any differences between the two sexes in the adaptation when wearing a splint. Changing the jaw relation in healthy adults can possibly support the release of movement potentials that simplify the performance of everyday activities or sports movements. Full article
(This article belongs to the Special Issue Sports Medicine and Injury Prevention)
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19 pages, 41082 KiB  
Article
Pavement Distress Initiation Prediction by Time-Lag Analysis and Logistic Regression
Appl. Sci. 2022, 12(22), 11855; https://doi.org/10.3390/app122211855 - 21 Nov 2022
Cited by 3 | Viewed by 1283
Abstract
Pavement condition prediction plays a vital role in pavement maintenance. Many prediction models and analyses have been conducted based on long-term pavement condition data. However, the condition evaluation for road sections can hardly support daily routine maintenance. This paper uses high-frequency pavement distress [...] Read more.
Pavement condition prediction plays a vital role in pavement maintenance. Many prediction models and analyses have been conducted based on long-term pavement condition data. However, the condition evaluation for road sections can hardly support daily routine maintenance. This paper uses high-frequency pavement distress data to explore the relationship between distress initiation, weather, and geometric factors. Firstly, a framework is designed to extract the initial time of pavement distress. Weather and geometric data are integrated to establish a pavement distress initiation dataset. Then, the time-lag cross-correlation analysis methods were utilized to explore the relationship between distress initiation and environmental factors. In addition, the logistic regression model is used to establish the distress initiation prediction model. Finally, Akaike information criterion (AIC), Bayesian information criterions (BIC), and areas under receiver operating characteristic curves (AUC) of logistic regression models with or without time-lag variables are compared as performance measurements. The results show that pavement distress initiation is susceptible to weather factors and location relationships. Daily total precipitation, minimum temperature, and daily average temperature have a time delay effect on the initiation of the pavement distress. Distress initiation is negatively correlated with the distance from the nearby intersection and positively correlated with adjacent distresses. The weather factors, considering the time-lag effect, can improve the model performance of the distress initiation prediction model and provide support for emergency management after severe weather. Full article
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20 pages, 4545 KiB  
Article
Adaptive Feature Fusion for Small Object Detection
Appl. Sci. 2022, 12(22), 11854; https://doi.org/10.3390/app122211854 - 21 Nov 2022
Cited by 6 | Viewed by 2112
Abstract
In order to alleviate the situation that small objects are prone to missed detection and false detection in natural scenes, this paper proposed a small object detection algorithm for adaptive feature fusion, referred to as MMF-YOLO. First, aiming at the problem that small [...] Read more.
In order to alleviate the situation that small objects are prone to missed detection and false detection in natural scenes, this paper proposed a small object detection algorithm for adaptive feature fusion, referred to as MMF-YOLO. First, aiming at the problem that small object pixels are easy to lose, a multi-branch cross-scale feature fusion module with fusion factor was proposed, where each fusion path has an adaptive fusion factor, which can allow the network to independently adjust the importance of features according to the learned weights. Then, aiming at the problem that small objects are similar to background information and small objects overlap in complex scenes, the M-CBAM attention mechanism was proposed, which was added to the feature reinforcement extraction module to reduce feature redundancy. Finally, in light of the problem of small object size and large size span, the size of the object detection head was modified to adapt to the small object size. Experiments on the VisDrone2019 dataset showed that the mAP of the proposed algorithm could reach 42.23%, and the parameter quantity was only 29.33 MB, which is 9.13% ± 0.07% higher than the benchmark network mAP, and the network model was reduced by 5.22 MB. Full article
(This article belongs to the Special Issue Virtual Reality, Digital Twins and Metaverse)
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13 pages, 3008 KiB  
Article
A DDoS Detection and Prevention System for IoT Devices and Its Application to Smart Home Environment
Appl. Sci. 2022, 12(22), 11853; https://doi.org/10.3390/app122211853 - 21 Nov 2022
Cited by 3 | Viewed by 1797
Abstract
The Internet of Things (IoT) has become an integral part of our daily life as it is growing in many fields, such as engineering, e-health, smart homes, smart buildings, agriculture, weather forecasting, etc. However, the growing number of IoT devices and their weak [...] Read more.
The Internet of Things (IoT) has become an integral part of our daily life as it is growing in many fields, such as engineering, e-health, smart homes, smart buildings, agriculture, weather forecasting, etc. However, the growing number of IoT devices and their weak configuration raise many security challenges such as designing protocols to protect these devices from various types of attacks such as using them as bots for DDoS attacks on target servers. In order to protect IoT devices from enslavement as bots in a home environment, we develop a lightweight security model consisting of various security countermeasures. The working mechanism of the proposed security model is presented in a two-part experimental scenario. Firstly, we describe the working mechanism of how an attacker infects an IoT device and then spreads the infection to the entire network. Secondly, we propose a set of mechanisms consisting of filtration, detection of abnormal traffic generated from IoT devices, screening, and publishing the abnormal traffic patterns to the rest of the home routers on the network. We tested the proposed scheme by infecting an IoT device with malicious code. The infected device then infects the rest of the IoT devices in its network and launches a DDoS attack by receiving attack-triggering commands from the botmaster. Finally, the proposed detection mechanism is used to detect the abnormal traffic and block the connection of infected devices in the network. The results reveal that the proposed system blocks abnormal traffic if the packets from an IoT device exceeded a threshold of 50 packets. Similarly, the network packet statistics show that, in the event of an unwanted situation, the detection mechanism runs smoothly and avoids any possible delays in the network. Full article
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11 pages, 281 KiB  
Article
Conscious Inhalation Sedation with Nitrous Oxide and Oxygen in Children: A Retrospective Study
Appl. Sci. 2022, 12(22), 11852; https://doi.org/10.3390/app122211852 - 21 Nov 2022
Viewed by 2104
Abstract
Dental anxiety is a common problem in younger children, especially those who have had traumatic or perceived traumatic dental treatments. Nitrous oxide (N2O) and oxygen (O2) have been recommended by the American Academy of Pediatric Dentistry as the optimal [...] Read more.
Dental anxiety is a common problem in younger children, especially those who have had traumatic or perceived traumatic dental treatments. Nitrous oxide (N2O) and oxygen (O2) have been recommended by the American Academy of Pediatric Dentistry as the optimal approach for uncooperative or anxious patients. The study aimed to evaluate the cooperation of children treated on deciduous teeth without local anesthesia and with rubber dam. A retrospective study was conducted from January 2019 to December 2020 in a private dental practice on children aged 4–10 years who had previously reported cases of dental anxiety during dental procedures or refused to undergo them. After an initial cognitive examination, the children underwent conservative treatment lasting a maximum of 30 min. Initially, 100% O2 was administered, then N2O dose was gradually increased to 35%. At the end of the treatment, 100% pure O2 was administered for 5 min. Children’s cooperation was assessed by Venham score before treatment (T0), at the end of induction (T1), and during the treatment (T2). A total of 371 children (age: 6.3 ± 1.7 years) were included in the study. Cooperation increased significantly from baseline at T1 (p < 0.001) and T2 (p < 0.001). Younger children (4–6 years) showed lower levels of cooperation at baseline (p < 0.001) but achieved optimal levels of cooperation at T1 (p = 0.022). Only 2.7% of children reported side effects. N2O/O2 proved to be an effective and safe method in achieving a good level of cooperation in younger children. Full article
(This article belongs to the Special Issue Current Advances in Dentistry)
19 pages, 518 KiB  
Article
Clustering-Based Channel Allocation Method for Mitigating Inter-WBAN Interference
Appl. Sci. 2022, 12(22), 11851; https://doi.org/10.3390/app122211851 - 21 Nov 2022
Cited by 1 | Viewed by 1043
Abstract
In this paper, we propose a channel assignment method that can mitigate the inter-WBAN interference when the density of WBANs is high. To achieve the goal, we group the coexisting WBANs into a set of clusters by using the Louvain algorithm and allocate [...] Read more.
In this paper, we propose a channel assignment method that can mitigate the inter-WBAN interference when the density of WBANs is high. To achieve the goal, we group the coexisting WBANs into a set of clusters by using the Louvain algorithm and allocate different channels to the WBANs in the same cluster by using a graph coloring method. By increasing the distance between the WBANs using the same channel, our method reduces the inter-WBAN interference. As a result, compared with the conventional centralized channel allocation method, our method increases the average data rate of a WBAN more than twice even when the number of coexisting WBANs is larger than the number of available channels. Compared with a distributed method involving an iterative process, our method reduces the channel decision time by 94.6%. Furthermore, since our method self-configures the algorithm parameters dynamically according to the topology changes, it can be used without human intervention even when the topology changes. Full article
(This article belongs to the Section Electrical, Electronics and Communications Engineering)
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11 pages, 4768 KiB  
Article
Improving the Performance of an Ultrashort Soft X-ray Free-Electron Laser via Attosecond Afterburners
Appl. Sci. 2022, 12(22), 11850; https://doi.org/10.3390/app122211850 - 21 Nov 2022
Cited by 3 | Viewed by 1398
Abstract
In this study, we implement attosecond afterburners in an ultrashort soft X-ray free-electron laser (FEL) to improve the performance of generating attosecond pulses. In this scheme, the FEL pulse produced in the normal radiator section is dumped while the well bunched electron beam [...] Read more.
In this study, we implement attosecond afterburners in an ultrashort soft X-ray free-electron laser (FEL) to improve the performance of generating attosecond pulses. In this scheme, the FEL pulse produced in the normal radiator section is dumped while the well bunched electron beam is reserved and reused in downstream afterburners. Subsequently, radiation in the afterburners gains rapidly as the bunching factor in the current spike is large, making the radiation pulse much shorter and cleaner than that from a normal radiator. Multi-shot simulations are carried out to demonstrate the performance and stability of the proposed technique. Full article
(This article belongs to the Special Issue Recent Advances and Applications in X-ray Free-Electron Lasers)
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14 pages, 4216 KiB  
Article
Influence and Control of SARS-CoV-2 Transmission under Two Different Models
Appl. Sci. 2022, 12(22), 11849; https://doi.org/10.3390/app122211849 - 21 Nov 2022
Viewed by 910
Abstract
SARS-CoV-2 is transmitted by contacting; however, the virus is so active that it can attach to objects and be transmitted from objects to humans via such contacting. The virus, which spreads through some living or inanimate-mediated processes, is more dangerous. On the basis [...] Read more.
SARS-CoV-2 is transmitted by contacting; however, the virus is so active that it can attach to objects and be transmitted from objects to humans via such contacting. The virus, which spreads through some living or inanimate-mediated processes, is more dangerous. On the basis of the routine contact transmission of infectious diseases, this paper further discusses the scope and efficiency of infectious diseases with indirect transmission. Through the study of two different transmission routes, the dynamic models of infectious diseases were constructed. The propagation of these two processes is theoretically studied using a differential equation model and stability analysis theory, and some actual virus propagation processes are simulated by numerical solutions. The prevention and control methods of infectious diseases are given, which lay the theoretical foundation for the discussion of related problems in practical application. Full article
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18 pages, 5078 KiB  
Article
YOLO-T: Multitarget Intelligent Recognition Method for X-ray Images Based on the YOLO and Transformer Models
Appl. Sci. 2022, 12(22), 11848; https://doi.org/10.3390/app122211848 - 21 Nov 2022
Cited by 4 | Viewed by 2285
Abstract
X-ray security inspection processes have a low degree of automation, long detection times, and are subject to misjudgment due to occlusion. To address these problems, this paper proposes a multi-objective intelligent recognition method for X-ray images based on the YOLO deep learning network [...] Read more.
X-ray security inspection processes have a low degree of automation, long detection times, and are subject to misjudgment due to occlusion. To address these problems, this paper proposes a multi-objective intelligent recognition method for X-ray images based on the YOLO deep learning network and an optimized transformer structure (YOLO-T). We also construct the GDXray-Expanded X-ray detection dataset, which contains multiple types of dangerous goods. Using this dataset, we evaluated several versions of the YOLO deep learning network model and compared the results to those of the proposed YOLO-T model. The proposed YOLO-T method demonstrated higher accuracy for multitarget and hidden-target detection tasks. On the GDXray-Expanded dataset, the maximum mAP of the proposed YOLO-T model was 97.73%, which is 7.66%, 16.47%, and 7.11% higher than that obtained by the YOLO v2, YOLO v3, and YOLO v4 models, respectively. Thus, we believe that the proposed YOLO-T network has good application prospects in X-ray security inspection technologies. In all kinds of security detection scenarios using X-ray security detectors, the model proposed in this paper can quickly and accurately identify dangerous goods, which has broad application value. Full article
(This article belongs to the Section Computing and Artificial Intelligence)
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14 pages, 945 KiB  
Article
An Intelligent Healthcare System for Residential Aged Care during the COVID-19 Pandemic
Appl. Sci. 2022, 12(22), 11847; https://doi.org/10.3390/app122211847 - 21 Nov 2022
Cited by 2 | Viewed by 1206
Abstract
There are many healthcare possibilities for the elderly, such as hospitals, nursing homes, and home-based care. However, in times of COVID-19, most home-based elderly people did not have sufficient supplies or healthcare as usual. Fulfilling their desire for an independent lifestyle while protecting [...] Read more.
There are many healthcare possibilities for the elderly, such as hospitals, nursing homes, and home-based care. However, in times of COVID-19, most home-based elderly people did not have sufficient supplies or healthcare as usual. Fulfilling their desire for an independent lifestyle while protecting them from falls, sudden illness, or accidents is difficult. This study represents a smart system for coping with this problem in public healthcare. The existing methods for residential aged care (RAC), such as fall detection, focus on personal profiles and physical symptoms records or use a collaborative filtering method to notify caregivers or family members that the elderly person may be at a high level of risk. However, these methods have many limitations in times of COVID-19, including insufficient risk factors, problems gathering information from mobile sensors, and issues with handling human variability. This study proposes a new method for RAC in times of COVID-19 called the Intelligent Healthcare Agent System (IHAS), which, unlike the old system, incorporates context information, such as indoor and outdoor (IO), standing and lying (SL), and resting and moving (RM). IHAS integrates diverse mobile sensor data and utilizes artificial intelligence (AI) technologies into the research model and learning-oriented prototype system that can manage human variability. Ultimately, this study’s findings should contribute to the existing research and industrial applications of RAC, as well as offer new avenues of study in future research. Full article
(This article belongs to the Section Computing and Artificial Intelligence)
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16 pages, 4745 KiB  
Article
An Interactive System Based on the IASP91 Earth Model for Earthquake Data Processing
Appl. Sci. 2022, 12(22), 11846; https://doi.org/10.3390/app122211846 - 21 Nov 2022
Viewed by 1328
Abstract
System software for interactive human–computer data processing based on the IASP91 Earth model was designed. An interactive data processing system for visualizing earthquake data was designed and implemented via the Intel Fortran platform. The system reads and processes broadband seismic data acquired by [...] Read more.
System software for interactive human–computer data processing based on the IASP91 Earth model was designed. An interactive data processing system for visualizing earthquake data was designed and implemented via the Intel Fortran platform. The system reads and processes broadband seismic data acquired by field stations, mainly including the reading and import of raw data, pre-processing, identification of seismic phases and inter-correlation traveltimes picking. In the data processing step, shortcomings have been improved and functions have been gradually refined and enhanced, making it easier and faster to process data. It has already processed more than 1000 large seismic events received by the station from 2013 to 2018. The practical application shows that the human–computer interaction system is easy to operate, accurate, fast and flexible, and is an effective tool for processing seismic data. Full article
(This article belongs to the Special Issue Big Data in Seismology: Methods and Applications)
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17 pages, 12017 KiB  
Article
Configuration Design and Gait Planning of a Six-Bar Tensegrity Robot
Appl. Sci. 2022, 12(22), 11845; https://doi.org/10.3390/app122211845 - 21 Nov 2022
Cited by 3 | Viewed by 1589
Abstract
Due to their high kinematic characteristics, six-bar tensegrities have great potential application value in the field of robotics, especially in the field of deep space exploration robots. In this paper, an ultralight six-bar tensegrity robot is designed, and a gait planning method for [...] Read more.
Due to their high kinematic characteristics, six-bar tensegrities have great potential application value in the field of robotics, especially in the field of deep space exploration robots. In this paper, an ultralight six-bar tensegrity robot is designed, and a gait planning method for continuous motion is proposed. First, the equilibrium matrix of the tensegrity structure is constructed, and singular value decomposition (SVD) is performed to find the node coordinates and internal forces of the tensegrity structure. Two representative examples regarding tensegrity structures are presented to demonstrate the capability of the proposed method in the initial selfstress design that satisfies the stability of tensegrities. Furthermore, both the principal rolling analysis and gait planning are also addressed based on the offset of the center of gravity. A six-bar tensegrity robot prototype is developed, and the obstacle avoidance experiment is completed. Finally, the results show that the six-bar tensegrity robot has good kinematic performance. Moreover, this robot is expected to play a key role in future planetary exploration. Full article
(This article belongs to the Special Issue Advanced Motion Structures and Devices)
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15 pages, 3665 KiB  
Article
Dynamic Heat Transfer Calculation for Ground-Coupled Floor in Emergency Temporary Housing
Appl. Sci. 2022, 12(22), 11844; https://doi.org/10.3390/app122211844 - 21 Nov 2022
Cited by 3 | Viewed by 1194
Abstract
Generally, ground-coupled floor heat transfer is supposed as annual periodic, which is reasonable for conventional buildings. However, for emergency housing with a short life cycle, the influence of initial soil temperature needs to be considered. In a previous study, the Wiener–Hopf technique was [...] Read more.
Generally, ground-coupled floor heat transfer is supposed as annual periodic, which is reasonable for conventional buildings. However, for emergency housing with a short life cycle, the influence of initial soil temperature needs to be considered. In a previous study, the Wiener–Hopf technique was introduced to solve the two-dimensional transient heat transfer equation with mixed Dirichlet and Robin boundary conditions. Based on that, an analytical solution of the dynamic heat transfer equation with initial soil temperature conditions was obtained. Since the solution was in the form of a double integral, its numerical evaluation method was also analyzed to improve computational efficiency. The accuracy and efficiency of the solution were validated by the finite volume method. Then, the effects of initial soil temperatures in different seasons, soil heat conductivities, and floor insulation on ground-coupled heat transfer were discussed. Results showed significant temperature differences between the current solution and the annual periodic solutions (long-time solutions), especially in hot and cold climates. Moreover, the larger the thermal capacity of the soil, the bigger temperature differences occurred. Therefore, this study is expected to provide a theoretical foundation for the indoor environment prediction and optimization design of emergency temporary housing. Full article
(This article belongs to the Topic Advances in Building Simulation)
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