Next Issue
Previous Issue

Table of Contents

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

  • Issues are regarded as officially published after their release is announced to the table of contents alert mailing list.
  • You may sign up for e-mail alerts to receive table of contents of newly released issues.
  • PDF is the official format for papers published in both, html and pdf forms. To view the papers in pdf format, click on the "PDF Full-text" link, and use the free Adobe Readerexternal link to open them.
Cover Story (view full-size image) The bottom portion of the figure displays the colour change during the synthesis of silver [...] Read more.
View options order results:
result details:
Displaying articles 1-188
Export citation of selected articles as:
Open AccessArticle Neural Prediction of Tunnels’ Support Pressure in Elasto-Plastic, Strain-Softening Rock Mass
Appl. Sci. 2018, 8(5), 841; https://doi.org/10.3390/app8050841
Received: 13 May 2018 / Revised: 16 May 2018 / Accepted: 17 May 2018 / Published: 22 May 2018
PDF Full-text (9979 KB) | HTML Full-text | XML Full-text
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)
Figures

Figure 1

Open AccessArticle Characteristics of Moduli Decay for the Asphalt Mixture under Different Loading Conditions
Appl. Sci. 2018, 8(5), 840; https://doi.org/10.3390/app8050840
Received: 4 May 2018 / Revised: 17 May 2018 / Accepted: 19 May 2018 / Published: 22 May 2018
Cited by 1 | PDF Full-text (5436 KB) | HTML Full-text | XML Full-text
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
Figures

Figure 1

Open AccessArticle Detection of Impact Damage on PVA-ECC Beam Using Infrared Thermography
Appl. Sci. 2018, 8(5), 839; https://doi.org/10.3390/app8050839
Received: 16 April 2018 / Revised: 16 May 2018 / Accepted: 17 May 2018 / Published: 22 May 2018
PDF Full-text (3451 KB) | HTML Full-text | XML Full-text
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)
Figures

Figure 1

Open AccessArticle An Intelligent Condition Monitoring Approach for Spent Nuclear Fuel Shearing Machines Based on Noise Signals
Appl. Sci. 2018, 8(5), 838; https://doi.org/10.3390/app8050838
Received: 15 April 2018 / Revised: 11 May 2018 / Accepted: 18 May 2018 / Published: 22 May 2018
PDF Full-text (3309 KB) | HTML Full-text | XML Full-text
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)
Figures

Figure 1

Open AccessArticle An Improved Image Semantic Segmentation Method Based on Superpixels and Conditional Random Fields
Appl. Sci. 2018, 8(5), 837; https://doi.org/10.3390/app8050837
Received: 11 April 2018 / Revised: 11 May 2018 / Accepted: 17 May 2018 / Published: 22 May 2018
PDF Full-text (7324 KB) | HTML Full-text | XML Full-text
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 Section Computer Science and Electrical Engineering)
Figures

Figure 1

Open AccessArticle Piezoelectric Poly(vinylidene fluoride) (PVDF) Polymer-Based Sensor for Wrist Motion Signal Detection
Appl. Sci. 2018, 8(5), 836; https://doi.org/10.3390/app8050836
Received: 10 April 2018 / Revised: 10 May 2018 / Accepted: 18 May 2018 / Published: 22 May 2018
PDF Full-text (9581 KB) | HTML Full-text | XML Full-text
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)
Figures

Figure 1

Open AccessArticle On the Robustness of No-Feedback Interdependent Networks
Appl. Sci. 2018, 8(5), 835; https://doi.org/10.3390/app8050835
Received: 16 April 2018 / Revised: 18 May 2018 / Accepted: 18 May 2018 / Published: 21 May 2018
PDF Full-text (2254 KB) | HTML Full-text | XML Full-text | Supplementary Files
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)
Figures

Figure 1

Open AccessArticle Static and Dynamic Response of FG-CNT-Reinforced Rhombic Laminates
Appl. Sci. 2018, 8(5), 834; https://doi.org/10.3390/app8050834
Received: 30 March 2018 / Revised: 30 April 2018 / Accepted: 30 April 2018 / Published: 21 May 2018
PDF Full-text (4516 KB) | HTML Full-text | XML Full-text
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)
Figures

Figure 1

Open AccessArticle YAG Ceramic Nanocrystals Implementation into MCVD Technology of Active Optical Fibers
Appl. Sci. 2018, 8(5), 833; https://doi.org/10.3390/app8050833
Received: 29 April 2018 / Revised: 15 May 2018 / Accepted: 15 May 2018 / Published: 21 May 2018
PDF Full-text (3968 KB) | HTML Full-text | XML Full-text
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)
Figures

Figure 1

Open AccessArticle An Automated Segmentation Method for Lung Parenchyma Image Sequences Based on Fractal Geometry and Convex Hull Algorithm
Appl. Sci. 2018, 8(5), 832; https://doi.org/10.3390/app8050832
Received: 26 March 2018 / Revised: 17 May 2018 / Accepted: 18 May 2018 / Published: 21 May 2018
PDF Full-text (4088 KB) | HTML Full-text | XML Full-text
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)
Figures

Figure 1

Open AccessArticle Electrospun Porous PDLLA Fiber Membrane Coated with nHA
Appl. Sci. 2018, 8(5), 831; https://doi.org/10.3390/app8050831
Received: 25 April 2018 / Revised: 17 May 2018 / Accepted: 18 May 2018 / Published: 21 May 2018
PDF Full-text (6021 KB) | HTML Full-text | XML Full-text
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
Figures

Graphical abstract

Open AccessArticle Fast Extended Depth-of-Field Reconstruction for Complex Holograms Using Block Partitioned Entropy Minimization
Appl. Sci. 2018, 8(5), 830; https://doi.org/10.3390/app8050830
Received: 3 May 2018 / Revised: 17 May 2018 / Accepted: 18 May 2018 / Published: 21 May 2018
PDF Full-text (27663 KB) | HTML Full-text | XML Full-text
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)
Figures

Figure 1

Open AccessArticle Water Resistant Composite Membranes for Carbon Dioxide Separation from Methane
Appl. Sci. 2018, 8(5), 829; https://doi.org/10.3390/app8050829
Received: 17 April 2018 / Revised: 17 May 2018 / Accepted: 17 May 2018 / Published: 21 May 2018
PDF Full-text (721 KB) | HTML Full-text | XML Full-text
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))
Figures

Figure 1

Open AccessEditorial Optics and Spectroscopy for Fluid Characterization
Appl. Sci. 2018, 8(5), 828; https://doi.org/10.3390/app8050828
Received: 15 May 2018 / Revised: 16 May 2018 / Accepted: 16 May 2018 / Published: 21 May 2018
PDF Full-text (161 KB) | HTML Full-text | XML Full-text
Abstract
This Editorial provides an introduction to and an overview of the special issue “Optics and Spectroscopy for Fluid Characterization”. Full article
Open AccessArticle An Efficient Multiscale Scheme Using Local Zernike Moments for Face Recognition
Appl. Sci. 2018, 8(5), 827; https://doi.org/10.3390/app8050827
Received: 3 April 2018 / Revised: 13 May 2018 / Accepted: 17 May 2018 / Published: 21 May 2018
PDF Full-text (3482 KB) | HTML Full-text | XML Full-text
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 Section Computer Science and Electrical Engineering)
Figures

Figure 1

Back to Top