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Appl. Sci., Volume 8, Issue 5 (May 2018) – 188 articles

Cover Story (view full-size image): The bottom portion of the figure displays the colour change during the synthesis of silver nanowires as the reaction temperature increases, while the top portion shows the transition from AgNO3 to silver nanocrystal, nanorods and nanowires respectively. Thus, a simple colourmetric assessment can be made that correlates with the species of nanoparticle present. View this paper.
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15 pages, 9979 KiB  
Article
Neural Prediction of Tunnels’ Support Pressure in Elasto-Plastic, Strain-Softening Rock Mass
by Ali Ghorbani, Hadi Hasanzadehshooiili and Łukasz Sadowski
Appl. Sci. 2018, 8(5), 841; https://doi.org/10.3390/app8050841 - 22 May 2018
Cited by 13 | Viewed by 4599
Abstract
The prediction of the support pressure (Pi) and the development of the ground reaction curve (GRC) are crucial elements of the convergence–confinement procedure used to design underground structures. In this paper, two different types of artificial neural networks (ANNs) are [...] Read more.
The prediction of the support pressure (Pi) and the development of the ground reaction curve (GRC) are crucial elements of the convergence–confinement procedure used to design underground structures. In this paper, two different types of artificial neural networks (ANNs) are used to predict the Pi of circular tunnels in elasto-plastic, strain-softening rock mass. The developed ANNs consider the stress state, the radial displacement of tunnel and the material softening behavior. Among these parameters, strain softening is the parameter of the deterioration of the material’s strength in the plastic zone. The analysis also presents separate solutions for the Mohr–Coulomb and Hoek–Brown strength criteria. In this regard, multi-layer perceptron (MLP) and radial basis function (RBF) ANNs were successfully applied. MLP with the architectures of 15-5-10-1 for the Mohr–Coulomb criteria and 17-5-15-1 for the Hoek–Brown criteria appeared optimum for the prediction of the Pi. On the other hand, the RBF networks with the architectures of 15-5-1 for the Mohr–Coulomb criterion and 17-3-12-1 for the Hoek–Brown criterion were found to be the optimum for the prediction of the Pi. Full article
(This article belongs to the Special Issue Soft Computing Techniques in Structural Engineering and Materials)
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16 pages, 5436 KiB  
Article
Characteristics of Moduli Decay for the Asphalt Mixture under Different Loading Conditions
by Songtao Lv, Xiyan Fan, Chengdong Xia, Jianlong Zheng, Dong Chen and Lingyun You
Appl. Sci. 2018, 8(5), 840; https://doi.org/10.3390/app8050840 - 22 May 2018
Cited by 18 | Viewed by 3756
Abstract
In order to explore the moduli decay patterns of asphalt mixtures under different loading conditions, the nonlinear fatigue damage model was implemented in order to simulate the moduli decay patterns. Then, the direct tensile, indirect tensile, and uniaxial compression fatigue tests were employed [...] Read more.
In order to explore the moduli decay patterns of asphalt mixtures under different loading conditions, the nonlinear fatigue damage model was implemented in order to simulate the moduli decay patterns. Then, the direct tensile, indirect tensile, and uniaxial compression fatigue tests were employed under four kinds of stress levels with four parallel tests. The specimens of AC-13C Styrene-butadiene-styrene (SBS) modified mixtures were manufactured. Based on the test results, the decay patterns of the moduli during fatigue tests under different stress states were revealed, and the parameters of the damage model under different test conditions were obtained. By changing the values of the model parameters under a certain loading condition, fatigue curves were obtained. Then, the fatigue properties of asphalt mixtures under different stress states could be compared and analyzed directly. The result indicated that the evolution curves of fatigue damage for the direct tensile test, the indirect tensile test, and the uniaxial compression test all experienced three stages, which indicates that the fatigue damage characteristic of asphalt mixtures is non-linear. The decay patterns of the direct tensile moduli and the tensile moduli measured by the indirect tensile test are similar. The decay patterns of the uniaxial compression and the compression moduli measured by indirect tensile test are similar. The decay patterns of tensile and compressive moduli are obviously different. At the same cycle ratio state, the position of the decay curve for the compression moduli is higher than that of the tensile moduli. It indicates that the tensile failure is the main reason of the fatigue damage for asphalt mixture. The new analysis method of fatigue damage was proposed, which provides a possibility to compare the fatigue results that were obtained from different loading conditions and different specimen sizes. Full article
(This article belongs to the Special Issue Achievements and Prospects of Advanced Pavement Materials Technologies)
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13 pages, 3451 KiB  
Article
Detection of Impact Damage on PVA-ECC Beam Using Infrared Thermography
by Jianchao Wu, Changhang Xu, Baoxin Qi and Francisco C. Robles Hernandez
Appl. Sci. 2018, 8(5), 839; https://doi.org/10.3390/app8050839 - 22 May 2018
Cited by 11 | Viewed by 3797
Abstract
The main purpose of the current research is to pilot study the impact damage detection in a beam structure using infrared thermography. In this study, a beam structure, made of polyvinyl alcohol fiber reinforced engineering cementitious composite (PVA-ECC) was subjected to multiple low-velocity [...] Read more.
The main purpose of the current research is to pilot study the impact damage detection in a beam structure using infrared thermography. In this study, a beam structure, made of polyvinyl alcohol fiber reinforced engineering cementitious composite (PVA-ECC) was subjected to multiple low-velocity impacts at a constant energy level. After each impact, the structure was heated by means of halogen lamp, and acquisition of thermal images was conducted simultaneously. Sequences of thermal images were acquired with starting and ending time sets so as to include the entire evolution of thermal phenomenon, during both heating to cooling processes. Based on the relationship between the damage and the temperature variation under the thermal excitation, different damages in the impacted structures were analyzed in the thermographs. Through experimental investigation, the results demonstrated that different degrees of damage correspond to different infrared thermal characteristics. The generation and evolution of thermal signatures revealed the initiation and propagation of impact damages. It further illustrated that the proposed method is an innovative and effective approach to detect impact damage. Full article
(This article belongs to the Special Issue Structural Damage Detection and Health Monitoring)
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19 pages, 3309 KiB  
Article
An Intelligent Condition Monitoring Approach for Spent Nuclear Fuel Shearing Machines Based on Noise Signals
by Jia-Hua Chen and Shu-Liang Zou
Appl. Sci. 2018, 8(5), 838; https://doi.org/10.3390/app8050838 - 22 May 2018
Cited by 5 | Viewed by 3425
Abstract
Shearing machines are the key pieces of equipment for spent–fuel reprocessing in commercial reactors. Once a failure happens and is not detected in time, serious consequences will arise. It is very important to monitor the shearing machine and to diagnose the faults immediately [...] Read more.
Shearing machines are the key pieces of equipment for spent–fuel reprocessing in commercial reactors. Once a failure happens and is not detected in time, serious consequences will arise. It is very important to monitor the shearing machine and to diagnose the faults immediately for spent–fuel reprocessing. In this study, an intelligent condition monitoring approach for spent nuclear fuel shearing machines based on noise signals was proposed. The approach consists of a feature extraction based on wavelet packet transform (WPT) and a hybrid fault diagnosis model, the latter combines the advantage on dynamic–modeling of hidden Markov model (HMM) and pattern recognition of artificial neural network (ANN). The verification results showed that the approach is more effective and accurate than that of the isolated HMM or ANN. Full article
(This article belongs to the Section Acoustics and Vibrations)
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17 pages, 7324 KiB  
Article
An Improved Image Semantic Segmentation Method Based on Superpixels and Conditional Random Fields
by Wei Zhao, Yi Fu, Xiaosong Wei and Hai Wang
Appl. Sci. 2018, 8(5), 837; https://doi.org/10.3390/app8050837 - 22 May 2018
Cited by 39 | Viewed by 6381
Abstract
This paper proposed an improved image semantic segmentation method based on superpixels and conditional random fields (CRFs). The proposed method can take full advantage of the superpixel edge information and the constraint relationship among different pixels. First, we employ fully convolutional networks (FCN) [...] Read more.
This paper proposed an improved image semantic segmentation method based on superpixels and conditional random fields (CRFs). The proposed method can take full advantage of the superpixel edge information and the constraint relationship among different pixels. First, we employ fully convolutional networks (FCN) to obtain pixel-level semantic features and utilize simple linear iterative clustering (SLIC) to generate superpixel-level region information, respectively. Then, the segmentation results of image boundaries are optimized by the fusion of the obtained pixel-level and superpixel-level results. Finally, we make full use of the color and position information of pixels to further improve the semantic segmentation accuracy using the pixel-level prediction capability of CRFs. In summary, this improved method has advantages both in terms of excellent feature extraction capability and good boundary adherence. Experimental results on both the PASCAL VOC 2012 dataset and the Cityscapes dataset show that the proposed method can achieve significant improvement of segmentation accuracy in comparison with the traditional FCN model. Full article
(This article belongs to the Special Issue Advanced Intelligent Imaging Technology)
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12 pages, 9581 KiB  
Article
Piezoelectric Poly(vinylidene fluoride) (PVDF) Polymer-Based Sensor for Wrist Motion Signal Detection
by Yaohui Hu, Wuwei Kang, Yong Fang, Lingrui Xie, Longzhen Qiu and Tao Jin
Appl. Sci. 2018, 8(5), 836; https://doi.org/10.3390/app8050836 - 22 May 2018
Cited by 42 | Viewed by 7172
Abstract
In this paper, a sensor based on polyvinylidene fluoride (PVDF) piezoelectric thin film was designed and fabricated to detect wrist motion signals. A series of dynamic experiments have been carried out, including the contrast experiments of different materials and force-charge signal characterization. The [...] Read more.
In this paper, a sensor based on polyvinylidene fluoride (PVDF) piezoelectric thin film was designed and fabricated to detect wrist motion signals. A series of dynamic experiments have been carried out, including the contrast experiments of different materials and force-charge signal characterization. The experimental results show that when the excitation signal exceeds 15 Hz, the sensitivity of the sensor is always stable at 3.10 pC/N. The signal acquisition experiment of the wrist motion has been carried out by using this sensor. The experiment results show that, with the advantages of small size, good flexibility, and high sensitivity, this wrist PVDF sensor can be used to detect the wrist motion signals with weak amplitude, low frequency, strong interference, and randomness. Full article
(This article belongs to the Special Issue Piezoelectric Actuators)
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13 pages, 2254 KiB  
Article
On the Robustness of No-Feedback Interdependent Networks
by Junde Wang, Songyang Lao, Shengjun Huang, Liang Bai and Lvlin Hou
Appl. Sci. 2018, 8(5), 835; https://doi.org/10.3390/app8050835 - 21 May 2018
Viewed by 3402
Abstract
The continuous operation of modern society is dominated by interdependent networks, such as energy networks, communication networks, and traffic networks. As a result, the robustness of interdependent networks has become increasingly important in recent years. On the basis of past research, a no-feedback [...] Read more.
The continuous operation of modern society is dominated by interdependent networks, such as energy networks, communication networks, and traffic networks. As a result, the robustness of interdependent networks has become increasingly important in recent years. On the basis of past research, a no-feedback interdependent networks model is introduced. Compared with previous work, this model is more consistent with the characteristics of real interdependent systems. In addition, two types of failure modes, unilateral failure and bilateral failure, are defined. For each failure mode, the influence of coupling strength and dependency strength on the robustness of no-feedback interdependent networks was analyzed and discussed in relation to various giant component sizes. The simulation results indicated that the robustness of the no-feedback interdependent networks was inversely proportional to coupling strength and dependency strength, and the effect of coupling strength and dependency strength on the robustness was equivalent. These conclusions are beneficial for helping researchers and engineers to build more robust interdependent systems. Full article
(This article belongs to the Special Issue Security and Privacy for Cyber Physical Systems)
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28 pages, 4516 KiB  
Article
Static and Dynamic Response of FG-CNT-Reinforced Rhombic Laminates
by Md Irfan Ansari, Ajay Kumar, Danuta Barnat-Hunek, Zbigniew Suchorab, Wojciech Andrzejuk and Dariusz Majerek
Appl. Sci. 2018, 8(5), 834; https://doi.org/10.3390/app8050834 - 21 May 2018
Cited by 14 | Viewed by 3898
Abstract
The present study focuses on the static and dynamic response of functionally graded carbon nanotube (FG-CNT)-reinforced rhombic laminates. The cubic variation of thickness coordinate in the displacement field is considered in terms of Taylor’s series expansion, which represents the higher-order transverse cross-sectional deformation [...] Read more.
The present study focuses on the static and dynamic response of functionally graded carbon nanotube (FG-CNT)-reinforced rhombic laminates. The cubic variation of thickness coordinate in the displacement field is considered in terms of Taylor’s series expansion, which represents the higher-order transverse cross-sectional deformation modes. The condition of zero-transverse shear strain at upper and lower surface of FG-CNT-reinforced rhombic laminates is imposed in the present formulation. The present two-dimensional model is formulated in a finite element, with the C0 element consisting of seven nodal unknowns per node. The final material properties of FG-CNT-reinforced rhombic laminates are estimated using the rule of mixture. The obtained numerical are compared with the results available in the literature to verify the reliability of the present model. The present study investigates the effect of CNT distribution, loading pattern, volume fraction, and various combinations of boundary constraints by developing a finite element code in FORTRAN. Full article
(This article belongs to the Section Mechanical Engineering)
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12 pages, 3968 KiB  
Article
YAG Ceramic Nanocrystals Implementation into MCVD Technology of Active Optical Fibers
by Jan Mrázek, Ivan Kašík, Lenka Procházková, Václav Čuba, Vladimír Girman, Viktor Puchý, Wilfried Blanc, Pavel Peterka, Jan Aubrecht, Jakub Cajzl and Ondřej Podrazký
Appl. Sci. 2018, 8(5), 833; https://doi.org/10.3390/app8050833 - 21 May 2018
Cited by 23 | Viewed by 5249
Abstract
Nanoparticle doping is an alternative approach the conventional solution doping method allowing the preparation of active optical fibers with improved optical and structural properties. The combination of the nanoparticle doping with MCVD process has brought new technological challenges. We present the preparation of [...] Read more.
Nanoparticle doping is an alternative approach the conventional solution doping method allowing the preparation of active optical fibers with improved optical and structural properties. The combination of the nanoparticle doping with MCVD process has brought new technological challenges. We present the preparation of fiber lasers doped with Er-doped yttrium aluminum garnet (Er:YAG) nanocrystals. These nanocrystals, prepared by a hydrothermal reaction, were analyzed by several structural methods to determine the mean nanocrystal size and an effective hydrodynamic radius. The nanocrystals were incorporated into silica frits with various porosity made by the conventional MCVD process. The Er:YAG-doped silica frits were processed into preforms, which were drawn into optical fibers. We studied the effect of the nanocrystal size and frit’s porosity on the final structural and optical properties of prepared preforms and optical fibers. Selected optical fibers were tested as an active medium in a fiber ring laser setup and the characteristics of the laser were determined. Optimal laser properties were achieved for the fiber length of 7 m. The slope efficiency of the fiber laser was about 42%. Presented method can be simply extended to the deposition of other ceramic nanomaterials. Full article
(This article belongs to the Special Issue Rare-Earth Doping for Optical Applications)
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16 pages, 4088 KiB  
Article
An Automated Segmentation Method for Lung Parenchyma Image Sequences Based on Fractal Geometry and Convex Hull Algorithm
by Xiaojiao Xiao, Juanjuan Zhao, Yan Qiang, Hua Wang, Yingze Xiao, Xiaolong Zhang and Yudong Zhang
Appl. Sci. 2018, 8(5), 832; https://doi.org/10.3390/app8050832 - 21 May 2018
Cited by 18 | Viewed by 4732
Abstract
Statistically solitary pulmonary nodules are about 6% to 17% of juxtapleural nodules. The accurate segmentation of lung parenchyma sequences of juxtapleural nodules is the basis of subsequent pulmonary nodule segmentation and detection. In order to solve the problem of incomplete segmentation of the [...] Read more.
Statistically solitary pulmonary nodules are about 6% to 17% of juxtapleural nodules. The accurate segmentation of lung parenchyma sequences of juxtapleural nodules is the basis of subsequent pulmonary nodule segmentation and detection. In order to solve the problem of incomplete segmentation of the juxtapleural nodules and segmentation inefficiency, this paper proposes an automated framework to combine the threshold iteration method to segment the lung parenchyma images and the fractal geometry method to detect the depression boundary. The framework includes an improved convex hull repair to complete the accurate segmentation of the lung parenchyma. The evaluation results confirm that the proposed method can segment juxtapleural lung parenchymal images accurately and efficiently. Full article
(This article belongs to the Special Issue Fractal Based Information Processing and Recognition)
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13 pages, 6021 KiB  
Article
Electrospun Porous PDLLA Fiber Membrane Coated with nHA
by Linhui Qiang, Cong Zhang, Feng Qu, Xiaonan Wu and Hongyan Wang
Appl. Sci. 2018, 8(5), 831; https://doi.org/10.3390/app8050831 - 21 May 2018
Cited by 6 | Viewed by 4102
Abstract
Porous poly- D, L-lactic acid (PDLLA) electrospinning fiber membrane was prepared, and nano-hydroxyapatite (nHA) was adsorbed and wrapped into it during the unique shrinking process of the PDLLA fiber membrane to fabricate the PDLLA/nHA composite membrane scaffold for tissue engineering. Compare with the [...] Read more.
Porous poly- D, L-lactic acid (PDLLA) electrospinning fiber membrane was prepared, and nano-hydroxyapatite (nHA) was adsorbed and wrapped into it during the unique shrinking process of the PDLLA fiber membrane to fabricate the PDLLA/nHA composite membrane scaffold for tissue engineering. Compare with the composite fibers prepared by blend electrospinning, most of nHA particles are observed to distribute on the surface of new type composite fibers, which could significantly improve the water wettability and induce the cellular adherence. FTIR analysis indicated that the PDLLA/nHA composite fibrous membrane was formed by physical adsorption. The combination was probed by scanning electron microscope, thermo-gravimetric, water contact angle and mechanical property analysis. It was proved that the nHA particles’ content and distribution, surface wettability, modulus and tensile strength of PDLLA/nHA composite fibrous membrane were influenced by the concentration of nHA dispersion and pores on the PDLLA fiber surface. The 10.6 wt % PDLLA/nHA composite fibrous membrane exhibits a more balanced tensile strength (3.28 MPa) and surface wettability (with a water contact angle of 0°) of the composite mats. Scanning electron microscope and confocal laser scanning microscopy images of chondrocyte proliferation further showed that the composite scaffold is non-toxic. The adherence and proliferation of chondrocytes on the 10.6 wt % PDLLA/nHA fibrous membrane was significantly improved, compared with PDLLA mat. The 10.6 wt % PDLLA/nHA composite fibrous membrane has potential application value as scaffold material in tissue engineering. Full article
(This article belongs to the Special Issue Biomaterials and Scaffolds in Tissue Engineering Applications and Cancer Therapies 2018)
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14 pages, 27663 KiB  
Article
Fast Extended Depth-of-Field Reconstruction for Complex Holograms Using Block Partitioned Entropy Minimization
by Peter Wai Ming Tsang, Ting-Chung Poon and Jung-Ping Liu
Appl. Sci. 2018, 8(5), 830; https://doi.org/10.3390/app8050830 - 21 May 2018
Cited by 6 | Viewed by 3968
Abstract
Optical scanning holography (OSH) is a powerful and effective method for capturing the complex hologram of a three-dimensional (3-D) scene. Such captured complex hologram is called optical scanned hologram. However, reconstructing a focused image from an optical scanned hologram is a difficult issue, [...] Read more.
Optical scanning holography (OSH) is a powerful and effective method for capturing the complex hologram of a three-dimensional (3-D) scene. Such captured complex hologram is called optical scanned hologram. However, reconstructing a focused image from an optical scanned hologram is a difficult issue, as OSH technique can be applied to acquire holograms of wide-view and complicated object scenes. Solutions developed to date are mostly computationally intensive, and in so far only reconstruction of simple object scenes have been demonstrated. In this paper we report a low complexity method for reconstructing a focused image from an optical scanned hologram that is representing a 3-D object scene. Briefly, a complex hologram is back-propagated onto regular spaced images along the axial direction, and from which a crude, blocky depth map of the object scene is computed according to non-overlapping block partitioned entropy minimization. Subsequently, the depth map is low-pass filtered to decrease the blocky distribution, and employed to reconstruct a single focused image of the object scene for extended depth of field. The method proposed here can be applied to any complex holograms such as those obtained from standard phase-shifting holography. Full article
(This article belongs to the Special Issue Holography, 3D Imaging and 3D Display)
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12 pages, 721 KiB  
Article
Water Resistant Composite Membranes for Carbon Dioxide Separation from Methane
by Colin A. Scholes
Appl. Sci. 2018, 8(5), 829; https://doi.org/10.3390/app8050829 - 21 May 2018
Cited by 8 | Viewed by 4405
Abstract
Membranes that are resistant to water vapor permeation have potential in natural gas sweetening by reducing the need for pretreatment. The perfluorinated polymer Teflon AF1600 has proven resistance to water vapor, which is adapted here in the form of composite membranes consisting of [...] Read more.
Membranes that are resistant to water vapor permeation have potential in natural gas sweetening by reducing the need for pretreatment. The perfluorinated polymer Teflon AF1600 has proven resistance to water vapor, which is adapted here in the form of composite membranes consisting of a Teflon AF1600 protective layer on membranes of the polyimide 4,4′-(hexafluoroisopropylidene) diphthalic anhydride 2,3,5,6-tetramethyl-1,4-phenylenediamine (6FDA-TMPDA) as well as Polymer of Intrinsic Micro-porosity (PIM-1). The permeability of CO2 and CH4 through the composite membranes was shown to be a function of the respective permeabilities of the individual polymer layers, with the Teflon AF1600 layer providing the majority of the resistance to mass transfer. Upon exposure to water, the composite membranes had reduced water permeation of 7–13% compared to pure membranes of 6FDA-TMPDA and PIM-1, because of the water resistance of the Teflon AF1600 layer. It was observed that water permeated as clusters through the composite structure. Under CO2-CH4 mixed gas conditions, 6FDA-TMPDA layer permselectivity performance was reduced and became comparable to Teflon AF1600, while the PIM-1 layer retained much of its high permselectivity performance. Importantly, at water activities below 0.2 the PIM-1 composite membrane achieved higher permeability for CO2 compared to water. Full article
(This article belongs to the Special Issue Carbon Capture Utilization and Sequestration (CCUS))
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3 pages, 161 KiB  
Editorial
Optics and Spectroscopy for Fluid Characterization
by Johannes Kiefer
Appl. Sci. 2018, 8(5), 828; https://doi.org/10.3390/app8050828 - 21 May 2018
Cited by 2 | Viewed by 2987
Abstract
This Editorial provides an introduction to and an overview of the special issue “Optics and Spectroscopy for Fluid Characterization”. Full article
(This article belongs to the Special Issue Optics and Spectroscopy for Fluid Characterization)
22 pages, 3482 KiB  
Article
An Efficient Multiscale Scheme Using Local Zernike Moments for Face Recognition
by Emrah Basaran, Muhittin Gökmen and Mustafa E. Kamasak
Appl. Sci. 2018, 8(5), 827; https://doi.org/10.3390/app8050827 - 21 May 2018
Cited by 11 | Viewed by 6769
Abstract
In this study, we propose a face recognition scheme using local Zernike moments (LZM), which can be used for both identification and verification. In this scheme, local patches around the landmarks are extracted from the complex components obtained by LZM transformation. Then, phase [...] Read more.
In this study, we propose a face recognition scheme using local Zernike moments (LZM), which can be used for both identification and verification. In this scheme, local patches around the landmarks are extracted from the complex components obtained by LZM transformation. Then, phase magnitude histograms are constructed within these patches to create descriptors for face images. An image pyramid is utilized to extract features at multiple scales, and the descriptors are constructed for each image in this pyramid. We used three different public datasets to examine the performance of the proposed method:Face Recognition Technology (FERET), Labeled Faces in the Wild (LFW), and Surveillance Cameras Face (SCface). The results revealed that the proposed method is robust against variations such as illumination, facial expression, and pose. Aside from this, it can be used for low-resolution face images acquired in uncontrolled environments or in the infrared spectrum. Experimental results show that our method outperforms state-of-the-art methods on FERET and SCface datasets. Full article
(This article belongs to the Special Issue Advanced Intelligent Imaging Technology)
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7 pages, 976 KiB  
Article
Refractive Index Variation of Magnetron-Sputtered a-Si1−xGex by “One-Sample Concept” Combinatory
by Tivadar Lohner, Benjamin Kalas, Peter Petrik, Zsolt Zolnai, Miklós Serényi and György Sáfrán
Appl. Sci. 2018, 8(5), 826; https://doi.org/10.3390/app8050826 - 21 May 2018
Cited by 7 | Viewed by 3771
Abstract
Gradient a-Si1−xGex layers have been deposited by ”one-sample concept” combinatorial direct current (DC) magnetron sputtering onto one-inch-long Si slabs. Characterizations by electron microscopy, ion beam analysis and ellipsometry show that the layers are amorphous with a uniform thickness, small [...] Read more.
Gradient a-Si1−xGex layers have been deposited by ”one-sample concept” combinatorial direct current (DC) magnetron sputtering onto one-inch-long Si slabs. Characterizations by electron microscopy, ion beam analysis and ellipsometry show that the layers are amorphous with a uniform thickness, small roughness and compositions from x = 0 to x = 1 changing linearly with the lateral position. By focused-beam mapping ellipsometry, we show that the optical constants also vary linearly with the lateral position, implying that the optical constants are linear functions of the composition. Both the refractive index and the extinction coefficient can be varied in a broad range for a large spectral region. The precise control and the knowledge of layer properties as a function of composition is of primary importance in many applications from solar cells to sensors. Full article
(This article belongs to the Special Issue Photonic Metamaterials)
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14 pages, 29177 KiB  
Article
The Impact of Diesel/LPG Dual Fuel on Performance and Emissions in a Single Cylinder Diesel Generator
by Mustafa Aydin, Ahmet Irgin and M. Bahattin Çelik
Appl. Sci. 2018, 8(5), 825; https://doi.org/10.3390/app8050825 - 20 May 2018
Cited by 25 | Viewed by 21553
Abstract
Compared to other engines of the same size, diesel engines are more economical in addition to their ability to generate high power. For this reason, they are widely used in many fields such as industry, agriculture, transportation, electricity generation. The increasing environmental concerns [...] Read more.
Compared to other engines of the same size, diesel engines are more economical in addition to their ability to generate high power. For this reason, they are widely used in many fields such as industry, agriculture, transportation, electricity generation. The increasing environmental concerns and diminishing oil resources led researchers to improve fuel consumption and emissions. In this context, the usage of Liquefied Petroleum Gas (LPG) fuel in diesel engines is one of the important research subjects that has been keeping up to date. This paper investigates the effects of LPG direct injection towards the end of air inlet period on engine emissions and performance characteristics. A four-stroke, air cooled, single cylinder diesel engine was modified to direct injection of LPG for diesel/LPG dual fuel operation. An Electronic Control Unit (ECU) was designed and used to adjust LPG injection timing and duration. LPG injection rates were selected as 30%, 50% and 70% on a mass base. The test engine was operated at 3000 rpm constant engine speed under varying load conditions. Throughout the experiments, it was observed that smoke density significantly reduced on the dual-fuel operation, compared to the pure diesel operation. Carbon Monoxide (CO) and Hydrocarbon (HC) emissions decreased by 30% and 20%, respectively. Brake Specific Fuel Consumption (BSFC) decreased by 8%. Nitrogen Oxide (NOx) emissions increased by 6% while effective efficiency increased up to 1.25%. Full article
(This article belongs to the Special Issue Direct Injection Reciprocating Internal Combustion Engines)
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18 pages, 8007 KiB  
Article
Detection and Quantification of Damage in Metallic Structures by Laser-Generated Ultrasonics
by Yongqiang Liu, Shixi Yang and Xuekun Liu
Appl. Sci. 2018, 8(5), 824; https://doi.org/10.3390/app8050824 - 20 May 2018
Cited by 15 | Viewed by 3653
Abstract
The appearance of damage on metallic structures is inevitable due to complex working environments. Non-destructive testing (NDT) of these structures is critical to the safe operation of the equipment. This paper presents a non-destructive damage detection, visualization, and quantification technique based on laser-generated [...] Read more.
The appearance of damage on metallic structures is inevitable due to complex working environments. Non-destructive testing (NDT) of these structures is critical to the safe operation of the equipment. This paper presents a non-destructive damage detection, visualization, and quantification technique based on laser-generated ultrasonics. The undamaged and damaged metallic structures are irradiated with laser pulses to produce broadband input ultrasonic waves. Damage to the structures plays the role of a nonlinear radiation source of new frequencies. Usually these new frequencies are too weak to be detected directly. Here, the state space predictive model is proposed to address the problem. Based on the recorded responses in the time domain, the state space attractors are reconstructed. Damage to the structures is shown to change the properties of the attractors. A nonlinear damage detection feature called normalized nonlinear prediction error (NNPE) is extracted from the state space to identify the changes in the attractors—and hence the damage. Furthermore, the damage is visualized and quantified using the NNPE values extracted from the entire area by using a laser scanning technique. Experimental results validate that the proposed technique is capable of detecting, visualizing and quantifying artificial damage to aluminum alloy plates and actual fatigue cracks to a twin-screw compressor body. Full article
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15 pages, 2968 KiB  
Article
Reliability-Based View Synthesis for Free Viewpoint Video
by Zengming Deng and Mingjiang Wang
Appl. Sci. 2018, 8(5), 823; https://doi.org/10.3390/app8050823 - 20 May 2018
Cited by 8 | Viewed by 3496
Abstract
View synthesis is a crucial technique for free viewpoint video and multi-view video coding because of its capability to render an unlimited number of virtual viewpoints from adjacent captured texture images and corresponding depth maps. The accuracy of depth maps is very important [...] Read more.
View synthesis is a crucial technique for free viewpoint video and multi-view video coding because of its capability to render an unlimited number of virtual viewpoints from adjacent captured texture images and corresponding depth maps. The accuracy of depth maps is very important to the rendering quality, since depth image–based rendering (DIBR) is the most widely used technology among synthesis algorithms. There are some issues due to the fact that stereo depth estimation is error-prone. In addition, filling occlusions is another challenge in producing desirable synthesized images. In this paper, we propose a reliability-based view synthesis framework. A depth refinement method is used to check the reliability of depth values and refine some of the unreliable pixels, and an adaptive background modeling algorithm is utilized to construct a background image aiming to fill the remaining empty regions after a proposed weighted blending process. Finally, the proposed approach is implemented and tested on test video sequences, and experimental results indicate objective and subjective improvements compared to previous view synthesis methods. Full article
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16 pages, 2196 KiB  
Article
Model Predictive Stabilization Control of High-Speed Autonomous Ground Vehicles Considering the Effect of Road Topography
by Kai Liu, Jianwei Gong, Shuping Chen, Yu Zhang and Huiyan Chen
Appl. Sci. 2018, 8(5), 822; https://doi.org/10.3390/app8050822 - 19 May 2018
Cited by 37 | Viewed by 5236
Abstract
This paper presents a model predictive control (MPC) scheme for the stabilization of high-speed autonomous ground vehicles (AGVs) considering the effect of road topography. Accounting for the road curvature and bank angle, a single-track dynamic model with roll dynamics is derived. Variable time [...] Read more.
This paper presents a model predictive control (MPC) scheme for the stabilization of high-speed autonomous ground vehicles (AGVs) considering the effect of road topography. Accounting for the road curvature and bank angle, a single-track dynamic model with roll dynamics is derived. Variable time steps are utilized for vehicle model discretization, enabling collision avoidance in the long-term without compromising the prediction accuracy in the near-term. Accordingly, safe driving constraints including the sideslip envelope, zero-moment-point and lateral safety corridor are developed to handle stability and obstacle avoidance. Taking these constraints into account, an MPC problem is formulated and solved at each step to determine the optimal steering control commands. Moreover, feedback corrections are integrated into the MPC to compensate the unmodeled dynamics and parameter uncertainties. Comparative simulations validate the capability and real-time ability of the proposed control scheme. Full article
(This article belongs to the Special Issue Multi-Actuated Ground Vehicles: Recent Advances and Future Challenges)
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14 pages, 2040 KiB  
Article
State-of-Health Identification of Lithium-Ion Batteries Based on Nonlinear Frequency Response Analysis: First Steps with Machine Learning
by Nina Harting, René Schenkendorf, Nicolas Wolff and Ulrike Krewer
Appl. Sci. 2018, 8(5), 821; https://doi.org/10.3390/app8050821 - 19 May 2018
Cited by 35 | Viewed by 10664
Abstract
In this study, we show an effective data-driven identification of the State-of-Health of Lithium-ion batteries by Nonlinear Frequency Response Analysis. A degradation model based on support vector regression is derived from highly informative Nonlinear Frequency Response Analysis data sets. First, an ageing test [...] Read more.
In this study, we show an effective data-driven identification of the State-of-Health of Lithium-ion batteries by Nonlinear Frequency Response Analysis. A degradation model based on support vector regression is derived from highly informative Nonlinear Frequency Response Analysis data sets. First, an ageing test of a Lithium-ion battery at 25 °C is presented and the impact of relevant ageing mechanisms on the nonlinear dynamics of the cells is analysed. A correlation measure is used to identify the most sensitive frequency range for ageing tests. Here, the mid-frequency range from 1 Hz to 100 Hz shows the strongest correlation to Lithium-ion battery degradation. The focus on the mid-frequency range leads to a dramatic reduction in measurement time of up to 92% compared to standard measurement protocols. Next, informative features are extracted and used to parametrise the support vector regression model for the State of Health degradation. The performance of the degradation model is validated with additional cells and validation data sets, respectively. We show that the degradation model accurately predicts the State of Health values. Validation data demonstrate the usefulness of the Nonlinear Frequency Response Analysis as an effective and fast State of Health identification method and as a versatile tool in the diagnosis of ageing of Lithium-ion batteries in general. Full article
(This article belongs to the Special Issue Battery Management and State Estimation)
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10 pages, 2980 KiB  
Article
Heat Transfer Designed for Bionic Surfaces with Rib Turbulators Inspired by Alopias Branchial Arch in a Simplified Gas Turbine Transition Piece
by Haotian Guo, Xiao Liang, Zhenglei Yu, Tao Xu, Tianyi Zhang, Huan Liu and Long Ma
Appl. Sci. 2018, 8(5), 820; https://doi.org/10.3390/app8050820 - 19 May 2018
Cited by 8 | Viewed by 3574
Abstract
The energy needed for highly efficient heat transfer has shown a continuous growth, as the energy reduction. For highly efficient power convection, gas turbine is an important device at present. But, the design of highly efficient gas turbine is limited by the temperature [...] Read more.
The energy needed for highly efficient heat transfer has shown a continuous growth, as the energy reduction. For highly efficient power convection, gas turbine is an important device at present. But, the design of highly efficient gas turbine is limited by the temperature and the material’s temperature resistance around the inlet. One part of the inlet need to be protected from burning out is transition piece. A bionic thermal surface with rib turbulators is designed according to the turbulence function of alopias’ branchial arches and is evaluated for thermo-protection enhancement in a simplified gas turbine transition piece using computational fluid dynamics (CFD) simulation. With the given diameter (Φ = 10.26 mm) of the impinging hole, three different horizontal distances (S) from impinging holes to the front of first-row rib were solved, which were S1 = 20 mm, S2 = 40 mm, and S3 = 60 mm, respectively, in case 1. But, the results revealed that S is not a significant influence factor on heat transfer efficiency. The cooling coefficient increases from 0.194 to 0.198 when the distance varies from S1 to S3. In case 2, rib turbulator width (W) and height (H) have been studied in ranges from 0.5 × Φ to 1.5 × Φ. All of the numerical results indicated that the best size of the rib turbulators could improve the heat transfer efficiency to 32.5%, when comparing with the smooth surface. All of the comparisons will benefit the structural design of heat transfer, which could be used for solving more severe problems in thermo-protection. Full article
(This article belongs to the Section Mechanical Engineering)
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18 pages, 824 KiB  
Article
Parallel Improvements of the Jaya Optimization Algorithm
by Héctor Migallón, Antonio Jimeno-Morenilla and Jose-Luis Sanchez-Romero
Appl. Sci. 2018, 8(5), 819; https://doi.org/10.3390/app8050819 - 18 May 2018
Cited by 9 | Viewed by 4515
Abstract
A wide range of applications use optimization algorithms to find an optimal value, often a minimum one, for a given function. Depending on the application, both the optimization algorithm’s behavior, and its computational time, can prove to be critical issues. In this paper, [...] Read more.
A wide range of applications use optimization algorithms to find an optimal value, often a minimum one, for a given function. Depending on the application, both the optimization algorithm’s behavior, and its computational time, can prove to be critical issues. In this paper, we present our efficient parallel proposals of the Jaya algorithm, a recent optimization algorithm that enables one to solve constrained and unconstrained optimization problems. We tested parallel Jaya algorithms for shared, distributed, and heterogeneous memory platforms, obtaining good parallel performance while leaving Jaya algorithm behavior unchanged. Parallel performance was analyzed using 30 unconstrained functions reaching a speed-up of up to 57.6 x using 60 processors. For all tested functions, the parallel distributed memory algorithm obtained parallel efficiencies that were nearly ideal, and combining it with the shared memory algorithm allowed us to obtain good parallel performance. The experimental results show a good parallel performance regardless of the nature of the function to be optimized. Full article
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15 pages, 1377 KiB  
Article
Effect of Carrier Localization on Recombination Processes and Efficiency of InGaN-Based LEDs Operating in the “Green Gap”
by Sergey Yu. Karpov
Appl. Sci. 2018, 8(5), 818; https://doi.org/10.3390/app8050818 - 18 May 2018
Cited by 25 | Viewed by 5117
Abstract
A semi-empirical model of carrier recombination accounting for hole localization by composition fluctuations in InGaN alloys is extended to polar and nonpolar quantum-well structures. The model provides quantitative agreement with available data on wavelength-dependent radiative and Auger recombination coefficients in polar LEDs. Comparison [...] Read more.
A semi-empirical model of carrier recombination accounting for hole localization by composition fluctuations in InGaN alloys is extended to polar and nonpolar quantum-well structures. The model provides quantitative agreement with available data on wavelength-dependent radiative and Auger recombination coefficients in polar LEDs. Comparison of calculated internal quantum efficiencies of polar and nonpolar LEDs enables an assessment of the roles of carrier localization, quantum-confined Stark effect, and native material properties for the efficiency decline in the “green gap”. Full article
(This article belongs to the Special Issue Highly Efficient UV and Visible Light Sources)
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7 pages, 185 KiB  
Editorial
Special Feature on Bio-Inspired Robotics
by Toshio Fukuda, Fei Chen and Qing Shi
Appl. Sci. 2018, 8(5), 817; https://doi.org/10.3390/app8050817 - 18 May 2018
Cited by 6 | Viewed by 3736
Abstract
n/a Full article
(This article belongs to the Special Issue Bio-Inspired Robotics)
38 pages, 6291 KiB  
Article
Agreement Technologies for Coordination in Smart Cities
by Holger Billhardt, Alberto Fernández, Marin Lujak and Sascha Ossowski
Appl. Sci. 2018, 8(5), 816; https://doi.org/10.3390/app8050816 - 18 May 2018
Cited by 12 | Viewed by 5128
Abstract
Many challenges in today’s society can be tackled by distributed open systems. This is particularly true for domains that are commonly perceived under the umbrella of smart cities, such as intelligent transportation, smart energy grids, or participative governance. When designing computer applications for [...] Read more.
Many challenges in today’s society can be tackled by distributed open systems. This is particularly true for domains that are commonly perceived under the umbrella of smart cities, such as intelligent transportation, smart energy grids, or participative governance. When designing computer applications for these domains, it is necessary to account for the fact that the elements of such systems, often called software agents, are usually made by different designers and act on behalf of particular stakeholders. Furthermore, it is unknown at design time when such agents will enter or leave the system, and what interests new agents will represent. To instil coordination in such systems is particularly demanding, as usually only part of them can be directly controlled at runtime. Agreement technologies refer to a sandbox of tools and mechanisms for the development of such open multiagent systems, which are based on the notion of agreement. In this paper, we argue that agreement technologies are a suitable means for achieving coordination in smart city domains, and back our claim through examples of several real-world applications. Full article
(This article belongs to the Special Issue Multi-Agent Systems)
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28 pages, 5284 KiB  
Article
Class Imbalance Ensemble Learning Based on the Margin Theory
by Wei Feng, Wenjiang Huang and Jinchang Ren
Appl. Sci. 2018, 8(5), 815; https://doi.org/10.3390/app8050815 - 18 May 2018
Cited by 129 | Viewed by 8058
Abstract
The proportion of instances belonging to each class in a data-set plays an important role in machine learning. However, the real world data often suffer from class imbalance. Dealing with multi-class tasks with different misclassification costs of classes is harder than dealing with [...] Read more.
The proportion of instances belonging to each class in a data-set plays an important role in machine learning. However, the real world data often suffer from class imbalance. Dealing with multi-class tasks with different misclassification costs of classes is harder than dealing with two-class ones. Undersampling and oversampling are two of the most popular data preprocessing techniques dealing with imbalanced data-sets. Ensemble classifiers have been shown to be more effective than data sampling techniques to enhance the classification performance of imbalanced data. Moreover, the combination of ensemble learning with sampling methods to tackle the class imbalance problem has led to several proposals in the literature, with positive results. The ensemble margin is a fundamental concept in ensemble learning. Several studies have shown that the generalization performance of an ensemble classifier is related to the distribution of its margins on the training examples. In this paper, we propose a novel ensemble margin based algorithm, which handles imbalanced classification by employing more low margin examples which are more informative than high margin samples. This algorithm combines ensemble learning with undersampling, but instead of balancing classes randomly such as UnderBagging, our method pays attention to constructing higher quality balanced sets for each base classifier. In order to demonstrate the effectiveness of the proposed method in handling class imbalanced data, UnderBagging and SMOTEBagging are used in a comparative analysis. In addition, we also compare the performances of different ensemble margin definitions, including both supervised and unsupervised margins, in class imbalance learning. Full article
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19 pages, 4379 KiB  
Article
Study on Path Planning Method for Imitating the Lane-Changing Operation of Excellent Drivers
by Guoqing Geng, Zhen Wu, Haobin Jiang, Liqin Sun and Chen Duan
Appl. Sci. 2018, 8(5), 814; https://doi.org/10.3390/app8050814 - 18 May 2018
Cited by 16 | Viewed by 4344
Abstract
Lane-changing is an important operation of an autonomous vehicle driving on the road. Safety and comfort are fully considered by excellent drivers in lane-changing operation. However, only the kinematic and dynamic constraints are taken into account in the traditional path planning methods, and [...] Read more.
Lane-changing is an important operation of an autonomous vehicle driving on the road. Safety and comfort are fully considered by excellent drivers in lane-changing operation. However, only the kinematic and dynamic constraints are taken into account in the traditional path planning methods, and the path generated by the traditional methods is very different from the actual trajectory of the vehicle driven by the excellent driver. In this paper, a path planning method for imitating the lane-changing operation of excellent drivers is proposed. Five experienced drivers are invited to do the lane-changing test, and the lane-changing trajectories data under different conditions are recorded. The excellent driver lane-changing model is established based on the genetic algorithm (GA) and back propagation (BP) neural network trained by the data of the lane-changing tests. The proposed approach can plan out an optimized lane change path according to the vehicle condition by learning the excellent drivers’ driving routes. The results of simulations verify that the path generated by the proposed algorithm is basically same as the track selected by the excellent drivers under same conditions, which can reflect the characteristics of the operations of the excellent driver. While applying safe lane-changing to autonomous vehicle, it can improve the ride comfort of the vehicle and therefore reduce the probability of motion sickness of the passengers caused by improper operation during lane change. Full article
(This article belongs to the Special Issue Advanced Mobile Robotics)
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11 pages, 1346 KiB  
Letter
Small Object Detection in Optical Remote Sensing Images via Modified Faster R-CNN
by Yun Ren, Changren Zhu and Shunping Xiao
Appl. Sci. 2018, 8(5), 813; https://doi.org/10.3390/app8050813 - 18 May 2018
Cited by 226 | Viewed by 14405
Abstract
The PASCAL VOC Challenge performance has been significantly boosted by the prevalently CNN-based pipelines like Faster R-CNN. However, directly applying the Faster R-CNN to the small remote sensing objects usually renders poor performance. To address this issue, this paper investigates on how to [...] Read more.
The PASCAL VOC Challenge performance has been significantly boosted by the prevalently CNN-based pipelines like Faster R-CNN. However, directly applying the Faster R-CNN to the small remote sensing objects usually renders poor performance. To address this issue, this paper investigates on how to modify Faster R-CNN for the task of small object detection in optical remote sensing images. First of all, we not only modify the RPN stage of Faster R-CNN by setting appropriate anchors but also leverage a single high-level feature map of a fine resolution by designing a similar architecture adopting top-down and skip connections. In addition, we incorporate context information to further boost small remote sensing object detection performance while we apply a simple sampling strategy to solve the issue about the imbalanced numbers of images between different classes. At last, we introduce a simple yet effective data augmentation method named ‘random rotation’ during training. Experimental results show that our modified Faster R-CNN algorithm improves the mean average precision by a large margin on detecting small remote sensing objects. Full article
(This article belongs to the Special Issue Complex Networks and Machine Learning: From Molecular to Social Sciences)
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10 pages, 1543 KiB  
Article
Blue Electrofluorescence Properties of Furan–Silole Ladder Pi-Conjugated Systems
by Hui Chen, Mathieu Denis, Pierre-Antoine Bouit, Yinlong Zhang, Xinda Wei, Denis Tondelier, Bernard Geffroy, Zheng Duan and Muriel Hissler
Appl. Sci. 2018, 8(5), 812; https://doi.org/10.3390/app8050812 - 18 May 2018
Cited by 6 | Viewed by 4043
Abstract
A synthetic route to novel benzofuran fused silole derivatives is described and the new compounds were fully characterized. These compounds showed optical and electrochemical properties that differ from their benzothiophene analog. Preliminary results show that these derivatives can be used as blue emitters [...] Read more.
A synthetic route to novel benzofuran fused silole derivatives is described and the new compounds were fully characterized. These compounds showed optical and electrochemical properties that differ from their benzothiophene analog. Preliminary results show that these derivatives can be used as blue emitters in organic light emitting devices (OLEDs) illustrating the potential of these new compounds for opto-electronic applications. Full article
(This article belongs to the Special Issue Fluorescence and Phosphorescence in Organic Materials: from Fundamental to OLED Devices)
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