Applied Sciences

15 pages, 2146 KiB

Open AccessArticle

Optical Flow-Based Fast Motion Parameters Estimation for Affine Motion Compensation

by Antoine Chauvet, Yoshihiro Sugaya, Tomo Miyazaki and Shinichiro Omachi

Appl. Sci. 2020, 10(2), 729; https://doi.org/10.3390/app10020729 - 20 Jan 2020

Cited by 3 | Viewed by 3698

This study proposes a lightweight solution to estimate affine parameters in affine motion compensation. Most of the current approaches start with an initial approximation based on the standard motion estimation, which only estimates the translation parameters. From there, iterative methods are used to [...] Read more.

This study proposes a lightweight solution to estimate affine parameters in affine motion compensation. Most of the current approaches start with an initial approximation based on the standard motion estimation, which only estimates the translation parameters. From there, iterative methods are used to find the best parameters, but they require a significant amount of time. The proposed method aims to speed up the process in two ways, first, skip evaluating affine prediction when it is likely to bring no encoding efficiency benefit, and second, by estimating better initial values for the iteration process. We use the optical flow between the reference picture and the current picture to estimate quickly the best encoding mode and get a better initial estimation. We achieve a reduction in encoding time over the reference of half when compared to the state of the art, with a loss in efficiency below 1%. Full article

(This article belongs to the Special Issue Advances in Image Processing, Analysis and Recognition Technology)

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Graphical abstract

13 pages, 6330 KiB

Open AccessArticle

Properties of Curved Parts Laser Cladding Based on Controlling Spot Size

by Haibo Huang, Wenlei Sun, Yong Huang and Jiangtong Yu

Appl. Sci. 2020, 10(2), 728; https://doi.org/10.3390/app10020728 - 20 Jan 2020

Cited by 1 | Viewed by 3169

Abstract

In this study, a method based on controlling the laser spot size was proposed in the process of curved parts laser cladding, and the coatings obtained by this method were analysed through investigation of the microstructure, microhardness, adhesion property and wear resistance properties. [...] Read more.

In this study, a method based on controlling the laser spot size was proposed in the process of curved parts laser cladding, and the coatings obtained by this method were analysed through investigation of the microstructure, microhardness, adhesion property and wear resistance properties. The nonuniform rational B-spline surface (NURBS) reconstruction method was used to obtain the workpiece geometrical characteristics of laser cladding, and through the establishment of a mathematical model, the process of the laser beam working on the curved surface was simplified as the intersection of the cylinder and curvature sphere. Then, the spot size was transformed into the area of a cylinder intersecting with a sphere, and by adjusting the laser head, the size of the laser spot was controlled in the threshold and interpolation points were obtained. The laser cladding trajectory was ensured by these interpolation points, and the experiment was carried out to study the properties of the coating. The results showed that the average coating thickness was about 1.07 mm, and the fluctuation of coating thickness did not exceed 0.05 mm; also, there were no cracks or pores in the layer after penetrant flaw detection. The SEM showed that the grains passed through the transition of plane crystal, cellular crystal, dendrite and equiaxed crystal from the bottom to the top of the layer. After 30 cycles of thermal shock tests, the cladding layer was still well bonded with the substrate and the microhardness and wear resistance were 2 times and 1.4 times higher than that of substrate, respectively. Full article

(This article belongs to the Section Optics and Lasers)

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17 pages, 968 KiB

Open AccessArticle

Secure Secondary Authentication Framework for Efficient Mutual Authentication on a 5G Data Network

by Seonghyeon Gong, Abir EL Azzaoui, Jeonghun Cha and Jong Hyuk Park

Appl. Sci. 2020, 10(2), 727; https://doi.org/10.3390/app10020727 - 20 Jan 2020

Cited by 10 | Viewed by 5168

Abstract

The service-based architecture of the Fifth Generation(5G) had combined the services and security architectures and enhanced the authentication process of services to expand the coverage of the network, including heterogeneous devices. This architecture uses the secondary authentication for mutual authentication between the User [...] Read more.

The service-based architecture of the Fifth Generation(5G) had combined the services and security architectures and enhanced the authentication process of services to expand the coverage of the network, including heterogeneous devices. This architecture uses the secondary authentication for mutual authentication between the User Equipment (UE) and the Data Network (DN) to authenticate devices and services. However, this authentication mechanism can cause a signaling storm in the Non-Access Stratum (NAS) because the end node needs to communicate with the authentication server of the NAS area. This problem could affect the availability of the network when the network is extended. This research proposes a mutual authentication framework that can efficiently perform a mutual authentication process through secondary authentication between UE and DN. The proposed framework uses newly devised network functions: Secondary Authentication Function (SAF) and the Authentication Data Management Function (ADMF). This framework proposes a methodology at the protocol level for efficient mutual authentication using the mobile edge computing architecture. We analyzed the proposed framework in the point of security considerations, and we evaluated the effect of the framework on the traffic of the NAS layer and user experience. Our simulation results show that the proposed framework can reduce the NAS traffic by 39% and total traffic of the overall network by 10%. Full article

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

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14 pages, 4637 KiB

Open AccessArticle

Consensus Design for Heterogeneous Battery Energy Storage Systems with Droop Control Considering Geographical Factor

by Yalin Zhang, Yunzhong Song and Shumin Fei

Appl. Sci. 2020, 10(2), 726; https://doi.org/10.3390/app10020726 - 20 Jan 2020

Cited by 2 | Viewed by 2634

Abstract

This paper proposes a hierarchical control strategy to coordinate battery energy storage devices based on a multi-agent system. The heterogeneous nature of the battery volume is paid much more attention in designing the proportional protocol of the consensus controller. Besides that, a cluster [...] Read more.

This paper proposes a hierarchical control strategy to coordinate battery energy storage devices based on a multi-agent system. The heterogeneous nature of the battery volume is paid much more attention in designing the proportional protocol of the consensus controller. Besides that, a cluster algorithm based on Minimum Spanning Tree (MST) is suggested to represent geographical factor, and on account of that, each Battery Energy Storage System (BESS) is classified into its specific cluster zone. Further, an active leader is assigned to be in charge of information from the external side in every cluster. The consensus algorithm reconciles all clusters in a step-by-step way. Energy level, voltage, frequency and active/reactive power sharing of every BESS can reach consensus by an information exchange within and among clusters respectively. Further, a virtual leader is taken into the active leader role in directing frequency and voltage to the reference values. To verify the consensus algorithm, a modified IEEE 57-bus is employed for time-domain simulations in an islanded mode and all BESSs are working in a discharge model. Full article

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176 pages, 1383 KiB

Open AccessEditorial

Acknowledgement to Reviewers of Applied Sciences in 2019

by Applied Sciences Editorial Office

Appl. Sci. 2020, 10(2), 725; https://doi.org/10.3390/app10020725 - 20 Jan 2020

Viewed by 15794

Abstract

The editorial team greatly appreciates the reviewers who have dedicated their considerable time and expertise to the journal’s rigorous editorial process over the past 12 months, regardless of whether the papers are finally published or not [...] Full article

20 pages, 12601 KiB

Open AccessArticle

Improving Incident Response in Big Data Ecosystems by Using Blockchain Technologies

by Julio Moreno, Manuel A. Serrano, Eduardo B. Fernandez and Eduardo Fernández-Medina

Appl. Sci. 2020, 10(2), 724; https://doi.org/10.3390/app10020724 - 20 Jan 2020

Cited by 13 | Viewed by 5217

Abstract

Big data ecosystems are increasingly important for the daily activities of any type of company. They are decisive elements in the organization, so any malfunction of this environment can have a great impact on the normal functioning of the company; security is therefore [...] Read more.

Big data ecosystems are increasingly important for the daily activities of any type of company. They are decisive elements in the organization, so any malfunction of this environment can have a great impact on the normal functioning of the company; security is therefore a crucial aspect of this type of ecosystem. When approaching security in big data as an issue, it must be considered not only during the creation and implementation of the big data ecosystem, but also throughout its entire lifecycle, including operation, and especially when managing and responding to incidents that occur. To this end, this paper proposes an incident response process supported by a private blockchain network that allows the recording of the different events and incidents that occur in the big data ecosystem. The use of blockchain enables the security of the stored data to be improved, increasing its immutability and traceability. In addition, the stored records can help manage incidents and anticipate them, thereby minimizing the costs of investigating their causes; that facilitates forensic readiness. This proposal integrates with previous research work, seeking to improve the security of big data by creating a process of secure analysis, design, and implementation, supported by a security reference architecture that serves as a guide in defining the different elements of this type of ecosystem. Moreover, this paper presents a case study in which the proposal is being implemented by using big data and blockchain technologies, such as Apache Spark or Hyperledger Fabric. Full article

(This article belongs to the Special Issue Machine Learning for Cybersecurity Threats, Challenges, and Opportunities)

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11 pages, 5762 KiB

Open AccessArticle

Micro-Mechanism Research into Molecular Chains Orientation Synergistically Induced by Carbon Nanotube and Shear Flow in Injection Molding

by Meili Zhang and Yong Xin

Appl. Sci. 2020, 10(2), 723; https://doi.org/10.3390/app10020723 - 20 Jan 2020

Cited by 2 | Viewed by 2531

Abstract

For the degree of orderly arrangement of the molecular chains at the interface of nanocomposites, the static and sheared polyethylene (PE)/carbon nanotube (CNT) models and the sheared pure PE model were constructed, and molecular simulation experiments were carried out in comparison. The micro-mechanism [...] Read more.

For the degree of orderly arrangement of the molecular chains at the interface of nanocomposites, the static and sheared polyethylene (PE)/carbon nanotube (CNT) models and the sheared pure PE model were constructed, and molecular simulation experiments were carried out in comparison. The micro-mechanism of molecular chains orientation, synergistically induced by the carbon nanotube and shear flow in injection molding, was discussed by analyzing the radius of gyration, molecular chain motion, conformation evolution of molecular chains, bond orientation parameter, interface binding energy and atom distribution. The results show that, for the static composite system, the conformation adjustment of PE molecular chains induced by CNT is limited due to the hindrance from the surrounding chains. Thus, the orientation and radius of gyration of molecular chains increase slightly. For the sheared pure PE system, the orientation induced by shear flow is unstable. After the cessation of shear, the molecular chains undergo intense thermal movement and relax quickly. The disorientation is obvious, and the radius of gyration decreases considerably. It is worth noting that for the sheared composite system, shear flow and the CNT have a synergistic effect on the orientation of the molecular chains, which is due to the adsorption effect of the CNT on shear-induced oriented chains and the inhibition effect of CNT on the relaxation of shear-induced oriented chains. Thus, the orientation stability of PE chains is greatly improved, and interface crystallization is promoted. Moreover, because of the more regular arrangement of molecular chains in the sheared composite system, more H atoms and C atoms are close to the surface of the CNT, which increases the van der Waals force, and correspondingly increases the interface binding energy. Full article

(This article belongs to the Section Chemical and Molecular Sciences)

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15 pages, 2646 KiB

Open AccessArticle

Real-Time Hand Gesture Spotting and Recognition Using RGB-D Camera and 3D Convolutional Neural Network

by Dinh-Son Tran, Ngoc-Huynh Ho, Hyung-Jeong Yang, Eu-Tteum Baek, Soo-Hyung Kim and Gueesang Lee

Appl. Sci. 2020, 10(2), 722; https://doi.org/10.3390/app10020722 - 20 Jan 2020

Cited by 66 | Viewed by 13694

Abstract

Using hand gestures is a natural method of interaction between humans and computers. We use gestures to express meaning and thoughts in our everyday conversations. Gesture-based interfaces are used in many applications in a variety of fields, such as smartphones, televisions (TVs), video [...] Read more.

Using hand gestures is a natural method of interaction between humans and computers. We use gestures to express meaning and thoughts in our everyday conversations. Gesture-based interfaces are used in many applications in a variety of fields, such as smartphones, televisions (TVs), video gaming, and so on. With advancements in technology, hand gesture recognition is becoming an increasingly promising and attractive technique in human–computer interaction. In this paper, we propose a novel method for fingertip detection and hand gesture recognition in real-time using an RGB-D camera and a 3D convolution neural network (3DCNN). This system can accurately and robustly extract fingertip locations and recognize gestures in real-time. We demonstrate the accurateness and robustness of the interface by evaluating hand gesture recognition across a variety of gestures. In addition, we develop a tool to manipulate computer programs to show the possibility of using hand gesture recognition. The experimental results showed that our system has a high level of accuracy of hand gesture recognition. This is thus considered to be a good approach to a gesture-based interface for human–computer interaction by hand in the future. Full article

(This article belongs to the Special Issue Big Data Analysis and Visualization)

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15 pages, 9511 KiB

Open AccessArticle

High-Velocity Impact Performance of Aluminum and B₄C/UHMW-PE Composite Plate for Multi-Wall Shielding

by Yangyu Lu, Qingming Zhang, Yijiang Xue, Wenjin Liu and Renrong Long

Appl. Sci. 2020, 10(2), 721; https://doi.org/10.3390/app10020721 - 20 Jan 2020

Cited by 9 | Viewed by 3774

Abstract

Three types of multi-wall shielding were experimentally investigated for their performances under the high-velocity impact of a cm-size cylindrical projectile by using a two-stage light-gas gun. The three shields contained the same two aluminum bumpers but different rear walls, which were 7075-T651 aluminum [...] Read more.

Three types of multi-wall shielding were experimentally investigated for their performances under the high-velocity impact of a cm-size cylindrical projectile by using a two-stage light-gas gun. The three shields contained the same two aluminum bumpers but different rear walls, which were 7075-T651 aluminum (Al) plate, boron carbide (B₄C)/Al 7075-T651/Kevlar composite plate and B₄C/ultra-high molecular weight polyethylene (UHMW-PE) composite plate. The impact test was carried out using a cylindrical shape of 6 g mass 7075-T651 Al projectile in a speed range (1.6 to 1.9 km/s) to achieve an effective shield configuration. A numerical simulation was undertaken by using ANSYS Autodyn-3D and the results of this were in good agreement with the experimental results. Meanwhile, both the experimental and the numerical simulation results indicated that B₄C/UHMW-PE composite plates performed a better interception of the high-velocity projectiles within the specific speed range and could be considered as a good configuration for intercepting large fragments in shielding design. Full article

(This article belongs to the Special Issue Armour and Protection Systems)

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Graphical abstract

16 pages, 2249 KiB

Open AccessArticle

Energy Performance Forecasting of Residential Buildings Using Fuzzy Approaches

by Àngela Nebot and Francisco Mugica

Appl. Sci. 2020, 10(2), 720; https://doi.org/10.3390/app10020720 - 20 Jan 2020

Cited by 30 | Viewed by 3130

Abstract

The energy consumption used for domestic purposes in Europe is, to a considerable extent, due to heating and cooling. This energy is produced mostly by burning fossil fuels, which has a high negative environmental impact. The characteristics of a building are an important [...] Read more.

The energy consumption used for domestic purposes in Europe is, to a considerable extent, due to heating and cooling. This energy is produced mostly by burning fossil fuels, which has a high negative environmental impact. The characteristics of a building are an important factor to determine the necessities of heating and cooling loads. Therefore, the study of the relevant characteristics of the buildings, regarding the heating and cooling needed to maintain comfortable indoor air conditions, could be very useful in order to design and construct energy-efficient buildings. In previous studies, different machine-learning approaches have been used to predict heating and cooling loads from the set of variables: relative compactness, surface area, wall area, roof area, overall height, orientation, glazing area and glazing area distribution. However, none of these methods are based on fuzzy logic. In this research, we study two fuzzy logic approaches, i.e., fuzzy inductive reasoning (FIR) and adaptive neuro fuzzy inference system (ANFIS), to deal with the same problem. Fuzzy approaches obtain very good results, outperforming all the methods described in previous studies except one. In this work, we also study the feature selection process of FIR methodology as a pre-processing tool to select the more relevant variables before the use of any predictive modelling methodology. It is proven that FIR feature selection provides interesting insights into the main building variables causally related to heating and cooling loads. This allows better decision making and design strategies, since accurate cooling and heating load estimations and correct identification of parameters that affect building energy demands are of high importance to optimize building designs and equipment specifications. Full article

(This article belongs to the Special Issue Machine Learning for Energy Forecasting)

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21 pages, 13700 KiB

Open AccessArticle

Characteristics of Crack Growth in Rock-Like Materials under Monotonic and Cyclic Loading Conditions

by Tae Young Ko and Sean Seungwon Lee

Appl. Sci. 2020, 10(2), 719; https://doi.org/10.3390/app10020719 - 20 Jan 2020

Cited by 12 | Viewed by 3438

Abstract

Experiments with gypsum as a model rock material were conducted to investigate the characteristics of crack growth under monotonic and cyclic loading. The specimens had two pre-existing flaws that were placed at different inclination angle, spacing and continuity. Tensile or wing cracks and [...] Read more.

Experiments with gypsum as a model rock material were conducted to investigate the characteristics of crack growth under monotonic and cyclic loading. The specimens had two pre-existing flaws that were placed at different inclination angle, spacing and continuity. Tensile or wing cracks and secondary or shear cracks were observed in both the monotonic and cyclic tests. Wing cracks or tensile cracks initiated at (or near) the tips of flaws and grew parallel to the loading direction. Secondary or shear cracks occurred after initiation of the wing crack and culminated in a final failure. Secondary cracks started at the tips of flaws and propagated in the colinear direction of flaws or perpendicular to loading. Six types of coalescence were observed. Both the monotonic and cyclic tests showed almost identical coalescence types. Coalescence occurred due to the internal shear cracks in specimens containing colinear flaws, while it occurred through combinations of internal shear cracks, internal wing cracks and tension cracks in specimens with non-colinear flaws. Fatigue cracks occurred in tests under cyclic loads. Finally, the subcritical crack growth parameters under monotonic and cyclic loading were determined. Although there were variations in the parameters, the parameter “n” showed similar values. Full article

(This article belongs to the Special Issue Structural Performances of Concrete Composite Members: Experimental, Theoretical, Numerical Approaches)

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22 pages, 10152 KiB

Open AccessArticle

A New Integrated Approach Based on the Iterative Super-Resolution Algorithm and Expectation Maximization for Face Hallucination

by K. Lakshminarayanan, R. Santhana Krishnan, E. Golden Julie, Y. Harold Robinson, Raghvendra Kumar, Le Hoang Son, Trinh Xuan Hung, Pijush Samui, Phuong Thao Thi Ngo and Dieu Tien Bui

Appl. Sci. 2020, 10(2), 718; https://doi.org/10.3390/app10020718 - 20 Jan 2020

Cited by 6 | Viewed by 3153

Abstract

This paper proposed and verified a new integrated approach based on the iterative super-resolution algorithm and expectation-maximization for face hallucination, which is a process of converting a low-resolution face image to a high-resolution image. The current sparse representation for super resolving generic image [...] Read more.

This paper proposed and verified a new integrated approach based on the iterative super-resolution algorithm and expectation-maximization for face hallucination, which is a process of converting a low-resolution face image to a high-resolution image. The current sparse representation for super resolving generic image patches is not suitable for global face images due to its lower accuracy and time-consumption. To solve this, in the new method, training global face sparse representation was used to reconstruct images with misalignment variations after the local geometric co-occurrence matrix. In the testing phase, we proposed a hybrid method, which is a combination of the sparse global representation and the local linear regression using the Expectation Maximization (EM) algorithm. Therefore, this work recovered the high-resolution image of a corresponding low-resolution image. Experimental validation suggested improvement of the overall accuracy of the proposed method with fast identification of high-resolution face images without misalignment. Full article

(This article belongs to the Section Applied Biosciences and Bioengineering)

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29 pages, 8580 KiB

Open AccessArticle

Application of Non-Symmetric Bending Principles on Modelling Fatigue Crack Behaviour and Vibration of a Cracked Rotor

by Joseph Spagnol, Helen Wu and Chunhui Yang

Appl. Sci. 2020, 10(2), 717; https://doi.org/10.3390/app10020717 - 20 Jan 2020

Cited by 17 | Viewed by 3191

Abstract

Many studies on cracked rotors developed crack breathing models that assume that the neutral axis of bending always remains horizontal for simplification. These models may generate significant discrepancies and thus there is a need to develop more sophisticated models to look into the [...] Read more.

Many studies on cracked rotors developed crack breathing models that assume that the neutral axis of bending always remains horizontal for simplification. These models may generate significant discrepancies and thus there is a need to develop more sophisticated models to look into the shifting of the neutral axis for a cracked rotor. Herein, a case study on the shifting of the neutral axis for a cracked rotor is firstly performed by using a three-dimensional finite element model to confirm that the neutral axis becomes inclined as the cracked rotor rotates. In response to this finding, non-symmetric bending principles are used to develop a new crack breathing model which has the advantage of being able to numerically calculate the inclination angle of the neutral axis. When compared to an existing crack model in the literature that assumes that the neutral axis remains horizontal (HNA model), the proposed model is relatively less stiff in bending as a result of an overall lower area moment of inertia. Using the harmonic balance method, a two-dimensional finite element vibration model of a cracked rotor was devised by employing the proposed crack breathing model and the HNA model for validation. It can be found that the vibration amplitudes of the first three frequency components are similar between the two models for shallow cracks and significantly differed for deep cracks. This result highlights the potential of the proposed model for modelling and detecting mid-to-late-stage cracks in rotors. Full article

(This article belongs to the Special Issue Advances in Rotordynamics)

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10 pages, 4015 KiB

Open AccessArticle

Development of a Structural Monitoring System for Cable Bridges by Using Seismic Accelerometers

by Seong-Hoon Jeong, Won-Seok Jang, Jin-Won Nam, Hohyun An and Dae-Jin Kim

Appl. Sci. 2020, 10(2), 716; https://doi.org/10.3390/app10020716 - 20 Jan 2020

Cited by 6 | Viewed by 3266

Abstract

In this study, a structural health monitoring system for cable-stayed bridges is developed. In the system, condition assessment of the structure is performed based on measured records from seismic accelerometers. Response indices are defined to monitor structural safety and serviceability and derived from [...] Read more.

In this study, a structural health monitoring system for cable-stayed bridges is developed. In the system, condition assessment of the structure is performed based on measured records from seismic accelerometers. Response indices are defined to monitor structural safety and serviceability and derived from the measured acceleration data. The derivation process of the indices is structured to follow the transformation from the raw data to the final outcome. The process includes, noise filtering, baseline correction, numerical integration, and calculation of relative differences. The system is packed as a condition assessment program, which consists of four major process of the structural health evaluation: (i) format conversion of the raw data, (ii) noise filtering, (iii) generation of response indices, and (iv) condition evaluation. An example set of limit states is presented to evaluate the structural condition of the test-bed cable-stayed bridge. Full article

(This article belongs to the Special Issue Selected Papers from IMETI 2018)

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18 pages, 2351 KiB

Open AccessArticle

Optical Wave Guiding and Spectral Properties of Micro/Nanofibers Used for Quantum Sensing and Quantum Light Generation

by Yong Sup Ihn, Zaeill Kim and Su-Yong Lee

Appl. Sci. 2020, 10(2), 715; https://doi.org/10.3390/app10020715 - 20 Jan 2020

Viewed by 3085

Abstract

Subwavelength optical micro/nanofibers have been widely used as basic building blocks in the field of quantum sensing and quantum light source by virtue of their properties which include pronounced evanescent field, large surface area, and small optical mode area. This paper presents theoretical [...] Read more.

Subwavelength optical micro/nanofibers have been widely used as basic building blocks in the field of quantum sensing and quantum light source by virtue of their properties which include pronounced evanescent field, large surface area, and small optical mode area. This paper presents theoretical studies on the propagation properties of the guided optical wave and the spectral properties of entangled photons from spontaneous four-wave mixing in micro/nanofibers. We first analyze numerically single-mode propagation, field distribution, fraction of power, and group-velocity-dispersions by solving Maxwell’s equations with boundary conditions in cylindrical coordinates. Then, optical wave guiding properties of micro/nanofibers are applied to estimate the spectral properties such as central wavelengths and bandwidths of the created photons via spontaneous four-wave mixing that can be tailored by controlling diameter and length of micro/nanofibers. This theoretical work provides useful guidelines to design micro/nanofiber-based quantum sensing and quantum light sources for quantum technologies. Full article

(This article belongs to the Special Issue Recent Development of Quantum Sensing and Metrology)

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23 pages, 3746 KiB

Open AccessArticle

Managing a Smart City Integrated Model through Smart Program Management

by Vita Santa Barletta, Danilo Caivano, Giovanni Dimauro, Antonella Nannavecchia and Michele Scalera

Appl. Sci. 2020, 10(2), 714; https://doi.org/10.3390/app10020714 - 20 Jan 2020

Cited by 37 | Viewed by 6477

Abstract

Context. A Smart city is intended as a city able to offer advanced integrated services, based on information and communication technology (ICT) technologies and intelligent (smart) use of urban infrastructures for improving the quality of life of its citizens. This goal is [...] Read more.

Context. A Smart city is intended as a city able to offer advanced integrated services, based on information and communication technology (ICT) technologies and intelligent (smart) use of urban infrastructures for improving the quality of life of its citizens. This goal is pursued by numerous cities worldwide, through smart projects that should contribute to the realization of an integrated vision capable of harmonizing the technologies used and the services developed in various application domains on which a Smart city operates. However, the current scenario is quite different. The projects carried out are independent of each other, often redundant in the services provided, unable to fully exploit the available technologies and reuse the results already obtained in previous projects. Each project is more like a silo than a brick that contributes to the creation of an integrated vision. Therefore, reference models and managerial practices are needed to bring together the efforts in progress towards a shared, integrated, and intelligent vision of a Smart city. Objective. Given these premises, the goal of this research work is to propose a Smart City Integrated Model together with a Smart Program Management approach for managing the interdependencies between project, strategy, and execution, and investigate the potential benefits that derive from using them. Method. Starting from a Smart city worldwide analysis, the Italian scenario was selected, and we carried out a retrospective analysis on a set of 378 projects belonging to nine different Italian Smart cities. Each project was evaluated according to three different perspectives: application domain transversality, technological depth, and interdependences. Results. The results obtained show that the current scenario is far from being considered “smart” and motivates the adoption of a Smart integrated model and Smart program management in the context of a Smart city. Conclusions. The development of a Smart city requires the use of Smart program management, which may significantly improve the level of integration between the application domain transversality and technological depth. Full article

(This article belongs to the Special Issue Artificial Intelligence Applications to Smart City and Smart Enterprise)

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13 pages, 4385 KiB

Open AccessFeature PaperArticle

Fast and Robust Object Tracking Using Tracking Failure Detection in Kernelized Correlation Filter

by Jungsup Shin, Heegwang Kim, Dohun Kim and Joonki Paik

Appl. Sci. 2020, 10(2), 713; https://doi.org/10.3390/app10020713 - 20 Jan 2020

Cited by 32 | Viewed by 4579

Abstract

Object tracking has long been an active research topic in image processing and computer vision fields with various application areas. For practical applications, the object tracking technique should be not only accurate but also fast in a real-time streaming condition. Recently, deep feature-based [...] Read more.

Object tracking has long been an active research topic in image processing and computer vision fields with various application areas. For practical applications, the object tracking technique should be not only accurate but also fast in a real-time streaming condition. Recently, deep feature-based trackers have been proposed to achieve a higher accuracy, but those are not suitable for real-time tracking because of an extremely slow processing speed. The slow speed is a major factor to degrade tracking accuracy under a real-time streaming condition since the processing delay forces skipping frames. To increase the tracking accuracy with preserving the processing speed, this paper presents an improved kernelized correlation filter (KCF)-based tracking method that integrates three functional modules: (i) tracking failure detection, (ii) re-tracking using multiple search windows, and (iii) motion vector analysis to decide a preferred search window. Under a real-time streaming condition, the proposed method yields better results than the original KCF in the sense of tracking accuracy, and when a target has a very large movement, the proposed method outperforms a deep learning-based tracker, such as multi-domain convolutional neural network (MDNet). Full article

(This article belongs to the Special Issue Advanced Intelligent Imaging Technology Ⅱ)

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10 pages, 1605 KiB

Open AccessArticle

Variable Curvature Displays: Optical Designs and Applications for VR/AR/MR Headsets

by Eduard Muslimov, Thibault Behaghel, Emmanuel Hugot, Kelly Joaquina and Ilya Guskov

Appl. Sci. 2020, 10(2), 712; https://doi.org/10.3390/app10020712 - 20 Jan 2020

Cited by 1 | Viewed by 3228

Abstract

In the present paper, we discuss the design of a projection system with curved display and its enhancement by variably adjusting the curvature. We demonstrate that the focal surface curvature varies significantly with a change of the object position and that it can [...] Read more.

In the present paper, we discuss the design of a projection system with curved display and its enhancement by variably adjusting the curvature. We demonstrate that the focal surface curvature varies significantly with a change of the object position and that it can easily be computed with the Seidel aberration theory. Using this analytically derived curvature value as the starting point, we optimise a refocusable projection system with

90^{°}

field of view and

F / # = 6.2

. It is demonstrated that such a system can provide stable image quality and illumination when refocusing from infinity to 1.5 m. The gain in spatial resolution is as high as 1.54 times with respect to a flat focal surface. Furthermore, we prove that a silicon die can be curved to the required shape with a safety factor of 4.3 in terms of the mechanical stress. Finally, it is shown that the developed system can be used in a virtual reality headset providing high resolution, low distortion and a flexible focusing mode. Full article

(This article belongs to the Section Optics and Lasers)

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14 pages, 2267 KiB

Open AccessArticle

Use of Smart Technology to Improve Management of Utility Tunnels

by Isam Shahrour, Hanbing Bian, Xiongyao Xie and Zixin Zhang

Appl. Sci. 2020, 10(2), 711; https://doi.org/10.3390/app10020711 - 20 Jan 2020

Cited by 18 | Viewed by 4487

Abstract

This paper presents a smart solution for the utility tunnel, which allows hosting a wide range of water and energy utilities in an accessible underground space. It is well known that utility tunnels offer major advantages such as the possibility to inspect, maintain, [...] Read more.

This paper presents a smart solution for the utility tunnel, which allows hosting a wide range of water and energy utilities in an accessible underground space. It is well known that utility tunnels offer major advantages such as the possibility to inspect, maintain, and easily extend urban utilities without excavation, thereby eliminating disturbances related to urban excavation such as traffic jams, noise, pollution, and pavement degradation. However, despite these advantages, the effective development of this facility remains below expectations, because of serious challenges related to the security and governance of this “shared space”. The solution presented in this paper is based on discussions with experts and companies involved in the design, construction, and management of utility tunnels, as well as on the authors’ experiences in the design and implementation of smart solutions for urban utilities. The paper firstly presents the major challenges of utility tunnels and then discusses how theb smart technology could help in coping with these challenges. The paper presents the architecture of this solution, as well as the main layers of monitoring, information system data analysis, and system control. It also presents the methodology to be followed for the implementation of this smart solution. Finally, the paper discusses two major issues for utility tunnels: fire risk and risk assessment. The paper shows that the use of smart technology allows developing a comprehensive digital solution, which uses advanced monitoring system to collect real-time data about the tunnel environment and functioning. These data can be easily shared by authorized staffs. Analysis of these data allows improving the utility tunnel security and performances. Full article

(This article belongs to the Section Civil Engineering)

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14 pages, 5489 KiB

Open AccessArticle

An Experimental Strain-Based Study on the Working State of Husk Mortar Wallboards with Openings

by Xuesong Cai, Shijun Sun and Guangchun Zhou

Appl. Sci. 2020, 10(2), 710; https://doi.org/10.3390/app10020710 - 19 Jan 2020

Cited by 3 | Viewed by 2173

Abstract

Rice husks as common agricultural remnants with low density and good thermal conductivity properties have been used in infill walls in the northern area of China. Accordingly, many tests and numerical simulations were conducted to address a difficult issue, the inaccurate estimation on [...] Read more.

Rice husks as common agricultural remnants with low density and good thermal conductivity properties have been used in infill walls in the northern area of China. Accordingly, many tests and numerical simulations were conducted to address a difficult issue, the inaccurate estimation on the lateral load-bearing capacity of different types of husk mortar energy-saving (HMES) wallboards. The difficulty has not been overcome so far, implying that the novel methods are anticipated to achieve the accurate estimation. This paper tests the full-scale HMES wallboards with different openings and obtains the strains at the points distributed on the wallboard sides. The experimental strains are modeled as the approximate strain energy values to produce the characteristic parameter of the HMES wallboard’s stressing state. Furthermore, the inherent working state characteristic points of HMES wallboards are revealed from the evolution of the characteristic parameter called as the normalized approximate strain energy sum, leading to the redefinition of the failure loads for the HMES wallboards. Finally, it investigates the stressing state mode evolution of the HMES wallboard around the failure loads. The achieved results provide the reference to the accurate estimation of the bearing capacity of the HMES wallboards. Full article

(This article belongs to the Special Issue Green Concrete for a Better Sustainable Environment)

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13 pages, 4081 KiB

Open AccessArticle

Active Disturbance Compensation Based Robust Control for Speed Regulation System of Permanent Magnet Synchronous Motor

by Yuxiang Ma and Yunhua Li

Appl. Sci. 2020, 10(2), 709; https://doi.org/10.3390/app10020709 - 19 Jan 2020

Cited by 16 | Viewed by 4134

Abstract

This paper deals with the robust control method for permanent magnet synchronous motor (PMSM) speed-regulation system based on active disturbance compensation. Different from the classical PMSM disturbance compensation scheme, a novel disturbance feed-forward compensation based on extended state observer (ESO) is designed for [...] Read more.

This paper deals with the robust control method for permanent magnet synchronous motor (PMSM) speed-regulation system based on active disturbance compensation. Different from the classical PMSM disturbance compensation scheme, a novel disturbance feed-forward compensation based on extended state observer (ESO) is designed for speed loop and q-axis current loop of PMSM. The disturbances of current loop include unmodeled dynamics of back electromotive force and parameters variations of stator are considered as lumped disturbance to compensate actively. In this way, the dynamic response of q-axis current loop can be improved to guarantee the anti-disturbance ability. A composite controller using sliding mode control and ESO is designed as speed loop controller, and an ESO-based proportional-integral controller is designed for q-axis current loop. Moreover, a transition process of reference signal is introduced to replace the step reference signal, which reduces the initial error and increases the range of feedback gain to improve system robustness. Finally, simulations and experiments are given to demonstrate the effectiveness of the proposed strategy. Full article

(This article belongs to the Section Applied Industrial Technologies)

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21 pages, 600 KiB

Open AccessArticle

Numerical Study for the Effects of Temperature Dependent Viscosity Flow of Non-Newtonian Fluid with Double Stratification

by Hafiz Abdul Wahab, Hussan Zeb, Saira Bhatti, Muhammad Gulistan, Seifedine Kadry and Yunyoung Nam

Appl. Sci. 2020, 10(2), 708; https://doi.org/10.3390/app10020708 - 19 Jan 2020

Cited by 26 | Viewed by 4635

Abstract

The main aim of the current study is to determine the effects of the temperature dependent viscosity and thermal conductivity on magnetohydrodynamics (MHD) flow of a non-Newtonian fluid over a nonlinear stretching sheet. The viscosity of the fluid depends on stratifications. Moreover, Powell–Eyring [...] Read more.

The main aim of the current study is to determine the effects of the temperature dependent viscosity and thermal conductivity on magnetohydrodynamics (MHD) flow of a non-Newtonian fluid over a nonlinear stretching sheet. The viscosity of the fluid depends on stratifications. Moreover, Powell–Eyring fluid is electrically conducted subject to a non-uniform applied magnetic field. Assume a small magnetic reynolds number and boundary layer approximation are applied in the mathematical formulation. Zero nano-particles mass flux condition to the sheet is considered. The governing model is transformed into the system of nonlinear Ordinary Differential Equation (ODE) system by using suitable transformations so-called similarity transformation. In order to calculate the solution of the problem, we use the higher order convergence method, so-called shooting method followed by Runge-Kutta Fehlberg (RK45) method. The impacts of different physical parameters on velocity, temperature and concentration profiles are analyzed and discussed. The parameters of engineering interest, i.e., skin fraction, Nusselt and Sherwood numbers are studied numerically as well. We concluded that the velocity profile decreases by increasing the values of

S t, H

and M. Also, we have analyzed the variation of temperature and concentration profiles for different physical parameters. Full article

(This article belongs to the Special Issue Heat and Mass Transfer: Fundamentals and Applications in Thermal Energy)

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14 pages, 267 KiB

Open AccessArticle

A Quantum-Like Model of Information Processing in the Brain

by Andrei Khrennikov and Masanari Asano

Appl. Sci. 2020, 10(2), 707; https://doi.org/10.3390/app10020707 - 19 Jan 2020

Cited by 18 | Viewed by 5622

Abstract

We present the quantum-like model of information processing by the brain’s neural networks. The model does not refer to genuine quantum processes in the brain. In this model, uncertainty generated by the action potential of a neuron is represented as quantum-like superposition of [...] Read more.

We present the quantum-like model of information processing by the brain’s neural networks. The model does not refer to genuine quantum processes in the brain. In this model, uncertainty generated by the action potential of a neuron is represented as quantum-like superposition of the basic mental states corresponding to a neural code. Neuron’s state space is described as complex Hilbert space (quantum information representation). The brain’s psychological functions perform self-measurements by extracting concrete answers to questions (solutions of problems) from quantum information states. This extraction is modeled in the framework of open quantum systems theory. In this way, it is possible to proceed without appealing to the state’s collapse. Dynamics of the state of psychological function F is described by the quantum master equation. Its stationary states represent classical statistical mixtures of possible outputs of F (decisions). This model can be used for justification of quantum-like modeling cognition and decision-making. The latter is supported by plenty of statistical data collected in cognitive psychology. Full article

(This article belongs to the Special Issue Quantum Cooperativity in Neural Signaling)

19 pages, 4787 KiB

Open AccessArticle

Evaluation of Condition of Concrete Structures Using Ultrasonic Pulse Velocity Method

by Seonguk Hong, Sangki Yoon, Jonghyun Kim, Changjong Lee, Seunghun Kim and Yongtaeg Lee

Appl. Sci. 2020, 10(2), 706; https://doi.org/10.3390/app10020706 - 19 Jan 2020

Cited by 48 | Viewed by 5726

Abstract

The purpose of this study is to estimate the compressive strength according to the age of the concrete structure using ultrasonic pulse velocity method. If the correlation between the ultrasonic pulse velocity and the compressive strength according to the age is derived, the [...] Read more.

The purpose of this study is to estimate the compressive strength according to the age of the concrete structure using ultrasonic pulse velocity method. If the correlation between the ultrasonic pulse velocity and the compressive strength according to the age is derived, the compressive strength of the early age of the concrete structure can be estimated at the new construction site and the compressive strength of the existing structure can be estimated at the remodeling construction site. Concrete structural specimens were constructed with 123 specimens by setting 9 parameters based on the design compressive strength of 24, 30, 40 MPa at 16, 20, 24, 48, 72, 120, 168, 360, 672 h. For the calculation of the average ultrasonic velocity according to the age of concrete, it is carried out according to KS F 2731, ASTM C597 and ACI 228-2R, and the concrete compressive strength is carried out according to KS F 2405. From correlation between ultrasonic pulse velocity and compressive strength, this experiment suggests compressive strength estimation equation. The proposed estimation equation confirmed that it is possible to estimate the compressive strength of concrete according to its age using nondestructive test methods. Full article

(This article belongs to the Special Issue Selected Papers from IMETI 2018)

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18 pages, 6559 KiB

Open AccessArticle

A Deep Neural Network Based Glottal Flow Model for Predicting Fluid-Structure Interactions during Voice Production

by Yang Zhang, Xudong Zheng and Qian Xue

Appl. Sci. 2020, 10(2), 705; https://doi.org/10.3390/app10020705 - 19 Jan 2020

Cited by 13 | Viewed by 3723

Abstract

This paper proposes a machine-learning based reduced-order model that can provide fast and accurate prediction of the glottal flow during voice production. The model is based on the Bernoulli equation with a viscous loss term predicted by a deep neural network (DNN) model. [...] Read more.

This paper proposes a machine-learning based reduced-order model that can provide fast and accurate prediction of the glottal flow during voice production. The model is based on the Bernoulli equation with a viscous loss term predicted by a deep neural network (DNN) model. The training data of the DNN model is a Navier-Stokes (N-S) equation-based three-dimensional simulation of glottal flows in various glottal shapes generated by a synthetic shape function, which can be obtained by superimposing the instantaneous modal displacements during vibration on the prephonatory geometry of the glottal shape. The input parameters of the DNN model are the geometric and flow parameters extracted from discretized cross sections of the glottal shapes and the output target is the corresponding flow resistance coefficient. With this trained DNN-Bernoulli model, the flow resistance coefficient as well as the flow rate and pressure distribution in any given glottal shape generated by the synthetic shape function can be predicted. The model is further coupled with a finite-element method based solid dynamics solver for simulating fluid-structure interactions (FSI). The prediction performance of the model for both static shape and FSI simulations is evaluated by comparing the solutions to those obtained by the Bernoulli and N-S model. The model shows a good prediction performance in accuracy and efficiency, suggesting a promise for future clinical use. Full article

(This article belongs to the Special Issue Selected Papers from The 13th International Conference on Advances in Quantitative Laryngology, Voice and Speech Research)

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24 pages, 7909 KiB

Open AccessArticle

Performance Degradation Analysis and Optimization of the Stepless Capacity Regulation System for Reciprocating Compressors

by Wenhua Liu, Zhinong Jiang, Yao Wang, Chao Zhou, Xu Sun and Jinjie Zhang

Appl. Sci. 2020, 10(2), 704; https://doi.org/10.3390/app10020704 - 19 Jan 2020

Cited by 10 | Viewed by 3280

Abstract

The regulating performance degradation of the stepless capacity regulation system for reciprocating compressors occurs frequently in long-term operations. It affects the safe and stable operation of the compressor seriously. The degradation mechanisms in a stepless capacity regulation system are mainly caused by valve [...] Read more.

The regulating performance degradation of the stepless capacity regulation system for reciprocating compressors occurs frequently in long-term operations. It affects the safe and stable operation of the compressor seriously. The degradation mechanisms in a stepless capacity regulation system are mainly caused by valve leakage, degeneration of the reset spring of the unloader, and (or) deviation of the solenoid valve’s characteristic parameters. In this study, to research the system performance degradation mechanisms and the influence of control parameters on system behavior, a multi-subsystem mathematics model which integrates compressor, gas pipeline, buffer tank, and actuator was built. In order to calculate the rate of degradation, a load prediction model based on a modified back-propagation neural network was established. The rate of degradation can be calculated using the predicted results. In order to optimize system regulation performance, a degradation-based optimization framework was developed which determines optimum control parameter compensation to achieve a minimum degradation rate. In addition, in order to avoid over-compensation, an adaptive control parameter compensation optimization method was adopted. According to the deviation between the given load and the prediction load, the control parameter compensations are obtained adaptively. Finally, two optimization experiments are carried out to show the effectiveness of the developed framework. The optimization results illustrate the degradation rate of the system gradually returning to normal during 60s without any over-compensation. Full article

(This article belongs to the Section Mechanical Engineering)

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15 pages, 7087 KiB

Open AccessArticle

Accurate Output Forecasting Method for Various Photovoltaic Modules Considering Incident Angle and Spectral Change Owing to Atmospheric Parameters and Cloud Conditions

by Hiroki Tawa, Hiromu Saiki, Yasuyuki Ota, Kenji Araki, Tatsuya Takamoto and Kensuke Nishioka

Appl. Sci. 2020, 10(2), 703; https://doi.org/10.3390/app10020703 - 19 Jan 2020

Cited by 22 | Viewed by 5420

Abstract

Because semiconductors absorb wavelengths dependent on the light absorption coefficient, photovoltaic (PV) energy output is affected by the solar spectrum. Therefore, it is necessary to consider the solar spectrum for highly accurate PV output estimation. Bird’s model has been used as a general [...] Read more.

Because semiconductors absorb wavelengths dependent on the light absorption coefficient, photovoltaic (PV) energy output is affected by the solar spectrum. Therefore, it is necessary to consider the solar spectrum for highly accurate PV output estimation. Bird’s model has been used as a general spectral model. However, atmospheric parameters such as aerosol optical depth and precipitable water have a constant value in the model that only applies to clear days. In this study, atmospheric parameters were extracted using the Bird’s spectrum model from the measured global spectrum and the seasonal fluctuation of atmospheric parameters was examined. We propose an overcast spectrum model and calculate the all-weather solar spectrum from clear to overcast sky through linear combination. Three types of PV modules (fixed Si, two-axis tracking Si, and fixed InGaP/GaAs/InGaAs triple-junction solar cells) were installed at the University of Miyazaki. The estimated performance ratio (PR), which takes into account incident angle and spectral variations, was consistent with the measured PR. Finally, the energy yield of various PVs installed across Japan was successfully estimated. Full article

(This article belongs to the Special Issue Solar Radiation: Measurements and Modelling, Effects and Applications)

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8 pages, 2875 KiB

Open AccessArticle

Plasma Electrolysis Spraying Al₂O₃ Coating onto Quartz Fiber Fabric for Enhanced Thermal Conductivity and Stability

by Aiming Bu, Yongfu Zhang, Yan Xiang, Yunjie Yang, Weiwei Chen, Huanwu Cheng and Lu Wang

Appl. Sci. 2020, 10(2), 702; https://doi.org/10.3390/app10020702 - 19 Jan 2020

Cited by 6 | Viewed by 2971

Abstract

This manuscript reported the synthesis of Al₂O₃ coating onto quartz fiber fabric by plasma electrolysis spray for enhanced thermal conductivity and stability. The nano- and micro-sized clusters were partially observed on the coating, while most coating was relatively smooth. It [...] Read more.

This manuscript reported the synthesis of Al₂O₃ coating onto quartz fiber fabric by plasma electrolysis spray for enhanced thermal conductivity and stability. The nano- and micro-sized clusters were partially observed on the coating, while most coating was relatively smooth. It was suggested that the formation of a ceramic coating was followed as the nucleation-growth raw, that is, the formation of the coating clusters was dependent on the fast grow-up partially, implying the inhomogeneous energy distribution in the electrolysis plasma. The deposition of the Al₂O₃ coating increased the tensile strength from 19.2 to 58.1 MPa. The thermal conductivity of the coated quartz fiber was measured to be 1.17 W m⁻¹ K⁻¹, increased by ~45% compared to the bare fiber. The formation mechanism of the Al₂O₃ coating was preliminarily discussed. The thermally conductive quartz fiber with high thermal stability by plasma electrolysis spray will be widely used in flexible thermal shielding and insulation materials. Full article

(This article belongs to the Special Issue The Applications of Plasma Techniques)

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22 pages, 7479 KiB

Open AccessArticle

Coupling Control Strategy and Experiments for Motion Mode Switching of a Novel Electric Chassis

by Jiwei Qu, Kangquan Guo, Zhenya Zhang, Shujie Song and Yining Li

Appl. Sci. 2020, 10(2), 701; https://doi.org/10.3390/app10020701 - 19 Jan 2020

Cited by 5 | Viewed by 2960

Abstract

A flexible chassis (FC) is a type of electric vehicle driven by in-wheel motors that can be used in narrow conditions in agricultural facilities. The FC is composed primarily of four off-center steering mechanisms (OSMs) that can be controlled independently. Various FC operation [...] Read more.

A flexible chassis (FC) is a type of electric vehicle driven by in-wheel motors that can be used in narrow conditions in agricultural facilities. The FC is composed primarily of four off-center steering mechanisms (OSMs) that can be controlled independently. Various FC operation modes can be achieved including cross motion (CM), in-place rotation (IR), diagonal motion (DM), and steering motion (SM). However, it is difficult to achieve satisfactory motion mode switching (MMS) results under traditional distribution control methodologies due to a lack of linkage relationships between the four OSMs. The goal of this study was to provide a coupling control method that can cope with this problem. First, dynamic MMS models were derived. Then, an MMS coupling error (CE) model was derived based on coupling control and Lyapunov stability theory. Second, a fuzzy proportional integral derivative (PID) controller with self-tuning parameters was designed to reduce the CE during MMS. A fuzzy PI controller was also employed to improve response times and decrease OSM tracking motion steady-state error. Finally, MATLAB/Simulink simulations were performed and experimentally validated on hard pavement. The results showed that the proposed methodology could effectively reduce CE and guarantee MMS control stability while substantially shortening response times. The proposed methodology is effective and feasible for FC MMS. Full article

(This article belongs to the Section Mechanical Engineering)

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19 pages, 7452 KiB

Open AccessFeature PaperArticle

Global MPPT Based on Machine-Learning for PV Arrays Operating under Partial Shading Conditions

by Christos Kalogerakis, Eftichis Koutroulis and Michail G. Lagoudakis

Appl. Sci. 2020, 10(2), 700; https://doi.org/10.3390/app10020700 - 19 Jan 2020

Cited by 34 | Viewed by 5411

Abstract

A global maximum power point tracking (GMPPT) process must be applied for detecting the position of the GMPP operating point in the minimum possible search time in order to maximize the energy production of a photovoltaic (PV) system when its PV array operates [...] Read more.

A global maximum power point tracking (GMPPT) process must be applied for detecting the position of the GMPP operating point in the minimum possible search time in order to maximize the energy production of a photovoltaic (PV) system when its PV array operates under partial shading conditions. This paper presents a novel GMPPT method which is based on the application of a machine-learning algorithm. Compared to the existing GMPPT techniques, the proposed method has the advantage that it does not require knowledge of the operational characteristics of the PV modules comprising the PV system, or the PV array structure. Additionally, due to its inherent learning capability, it is capable of detecting the GMPP in significantly fewer search steps and, therefore, it is suitable for employment in PV applications, where the shading pattern may change quickly (e.g., wearable PV systems, building-integrated PV systems etc.). The numerical results presented in the paper demonstrate that the time required for detecting the global MPP, when unknown partial shading patterns are applied, is reduced by 80.5%–98.3% by executing the proposed Q-learning-based GMPPT algorithm, compared to the convergence time required by a GMPPT process based on the particle swarm optimization (PSO) algorithm. Full article

(This article belongs to the Special Issue Advancing Grid-Connected Renewable Generation Systems 2019)

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