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Appl. Sci., Volume 8, Issue 11 (November 2018)

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Open AccessArticle Quadrotor Formation Strategies Based on Distributed Consensus and Model Predictive Controls
Appl. Sci. 2018, 8(11), 2246; https://doi.org/10.3390/app8112246 (registering DOI)
Received: 18 October 2018 / Revised: 9 November 2018 / Accepted: 12 November 2018 / Published: 14 November 2018
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Abstract
In this study, the distributed consensus control and model predictive control (MPC)-based formation strategies for quadrotors are proposed. First, the formation-control problem is decoupled into horizontal and vertical motions. The distributed consensus control and MPC-based formation strategy are implemented in the follower’s horizontal
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In this study, the distributed consensus control and model predictive control (MPC)-based formation strategies for quadrotors are proposed. First, the formation-control problem is decoupled into horizontal and vertical motions. The distributed consensus control and MPC-based formation strategy are implemented in the follower’s horizontal formation control. In the horizontal motion, the leader tracks the given waypoints by simply using the MPC, and generates the desired formation trajectory for each follower based on its flight information, predicted trajectory, and the given formation pattern. On the other hand, the followers carry out the formation flight based on the proposed horizontal formation strategy and the desired formation trajectories generated by the leader. In the vertical motion, formation control is carried out using only the MPC for both the leader and the follower. Likewise, the leader tracks the desired altitude/climb rate and generates the desired formation trajectories for the followers, and the followers track the desired formation trajectories generated by the leader using the MPC. The optimization problem considered in the MPC differs for the horizontal and vertical motions. The problem is formulated as a quadratic programming (QP) problem for the horizontal motion, and as a linear quadratic tracker (LQT) for the vertical motion. Simulation of a comprehensive maneuver was carried out under a Matlab/Simulink environment to examine the performance of the proposed formation strategies. Full article
(This article belongs to the Section Mechanical Engineering)
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Open AccessArticle An Enhanced Mobility and Temperature Aware Routing Protocol through Multi-Criteria Decision Making Method in Wireless Body Area Networks
Appl. Sci. 2018, 8(11), 2245; https://doi.org/10.3390/app8112245 (registering DOI)
Received: 13 September 2018 / Revised: 2 November 2018 / Accepted: 10 November 2018 / Published: 14 November 2018
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Abstract
In wireless body area networks, temperature-aware routing plays an important role in preventing damage of surrounding body tissues caused by the temperature rise of the nodes. However, existing temperature-aware routing protocols tend to choose the next hop according to the temperature metric without
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In wireless body area networks, temperature-aware routing plays an important role in preventing damage of surrounding body tissues caused by the temperature rise of the nodes. However, existing temperature-aware routing protocols tend to choose the next hop according to the temperature metric without considering transmission delay and data loss caused by human posture. To address this problem, multiple research efforts exploit different metrics such as temperature, hop count and link quality. Because their approaches are fundamentally based on simple computation through weighted factor for each metric, it is rarely feasible to obtain reasonable weight value through experiments. To solve this problem, we propose an enhanced mobility and temperature-aware routing protocol based on the multi-criteria decision making method. The proposed protocol adopts the analytical hierarchy process and simple additive weighting method to assign suitable weight factors and choose the next hop while considering multiple routing criteria. Simulation results are presented to demonstrate that the proposed protocol can efficiently improve transmission delay and data loss better than existing protocols by preventing the temperature rise on the node. Full article
(This article belongs to the Special Issue Body Area Networks)
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Open AccessArticle Three-Dimensional Nanofluid Flow with Heat and Mass Transfer Analysis over a Linear Stretching Surface with Convective Boundary Conditions
Appl. Sci. 2018, 8(11), 2244; https://doi.org/10.3390/app8112244 (registering DOI)
Received: 23 October 2018 / Revised: 7 November 2018 / Accepted: 10 November 2018 / Published: 14 November 2018
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Abstract
In this study, we analyzed the three-dimensional flow of Williamson (pseudoplastic) fluids upon a linear porous stretching sheet. The thermal radiation impact was taken into account. The transformed non-linear equations were solved by the homotopy analysis method (HAM). The influence of the embedded
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In this study, we analyzed the three-dimensional flow of Williamson (pseudoplastic) fluids upon a linear porous stretching sheet. The thermal radiation impact was taken into account. The transformed non-linear equations were solved by the homotopy analysis method (HAM). The influence of the embedded parameters tretching parameter, Williamson parameter, porosity parameter, thermal radiation parameter, thermophoresis parameter, Brownian motion parameter, Prandtl number and Biot number are presented on velocity, temperature and concentration functions in the graphs and explained in detail. The velocity function along the x-direction reduces with the impact of the stretching, porosity and Williamson parameters. Velocity along the y-direction increases with the stretching parameter, while it reduces with the porosity and Williamson parameters. The effect of Skin friction, heat transfer and mass transfer are shown numerically. The numerical values of surface drag force and the impact of different parameters are calculated and it is observed that increasing the stretching parameter and the porosity parameter reduces the surface drag force, while increasing the Williamson parameter augments the surface drag force. Higher values of the stretching parameter, the Prandtl number and the radiation parameter enhance the heat transfer rate, while the augmented value of the thermophoresis and Brownian motion parameters reduces the heat transfer rate, where higher values of the stretching parameter, thermophoresis and Brownian motion parameters enhance the mass transfer rate. Full article
(This article belongs to the Section Nanotechnology and Applied Nanosciences)
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Open AccessArticle Aircraft Air Compressor Bearing Diagnosis Using Discriminant Analysis and Cooperative Genetic Algorithm and Neural Network Approaches
Appl. Sci. 2018, 8(11), 2243; https://doi.org/10.3390/app8112243 (registering DOI)
Received: 28 September 2018 / Revised: 24 October 2018 / Accepted: 7 November 2018 / Published: 14 November 2018
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Abstract
Monitoring and diagnosis of rotating machines has become an effective and indispensable tool for the efficient and timely detection of defects, avoiding then incidents that can have serious economic and human consequences. Bearings are the most sensitive parts of these machines; this is
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Monitoring and diagnosis of rotating machines has become an effective and indispensable tool for the efficient and timely detection of defects, avoiding then incidents that can have serious economic and human consequences. Bearings are the most sensitive parts of these machines; this is why special attention must be paid to its monitoring. This paper presents a methodology for diagnosing an aircraft air compressor bearing using neural networks that have been optimized by genetic algorithms. We used in our study a database of vibratory signals that were recorded on a test bench from bearings with different defects. The faults features are extracted from these noisy signals using the estimate of the spectral density. The diagnostic capacity of obtained model has been demonstrated by a comparative study with two other automatic classifiers, which are discriminant analysis and neural networks whose training has been done with the Back-Propagation algorithm. This approach has the advantage of simultaneously ensuring the optimal structure of the neural network and accomplishing its learning. The importance of this study is the construction of a diagnostic tool that is characterized by efficiency, speed of decision making and ease of implementation not only on the computers on the ground, but also on the mounted calculators on aircraft. Full article
(This article belongs to the Special Issue Fault Detection and Diagnosis in Mechatronics Systems)
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Open AccessArticle A Novel Discriminating and Relative Global Spatial Image Representation with Applications in CBIR
Appl. Sci. 2018, 8(11), 2242; https://doi.org/10.3390/app8112242 (registering DOI)
Received: 18 October 2018 / Revised: 7 November 2018 / Accepted: 12 November 2018 / Published: 14 November 2018
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Abstract
The requirement for effective image search, which motivates the use of Content-Based Image Retrieval (CBIR) and the search of similar multimedia contents on the basis of user query, remains an open research problem for computer vision applications. The application domains for Bag of
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The requirement for effective image search, which motivates the use of Content-Based Image Retrieval (CBIR) and the search of similar multimedia contents on the basis of user query, remains an open research problem for computer vision applications. The application domains for Bag of Visual Words (BoVW) based image representations are object recognition, image classification and content-based image analysis. Interest point detectors are quantized in the feature space and the final histogram or image signature do not retain any detail about co-occurrences of features in the 2D image space. This spatial information is crucial, as it adversely affects the performance of an image classification-based model. The most notable contribution in this context is Spatial Pyramid Matching (SPM), which captures the absolute spatial distribution of visual words. However, SPM is sensitive to image transformations such as rotation, flipping and translation. When images are not well-aligned, SPM may lose its discriminative power. This paper introduces a novel approach to encoding the relative spatial information for histogram-based representation of the BoVW model. This is established by computing the global geometric relationship between pairs of identical visual words with respect to the centroid of an image. The proposed research is evaluated by using five different datasets. Comprehensive experiments demonstrate the robustness of the proposed image representation as compared to the state-of-the-art methods in terms of precision and recall values. Full article
(This article belongs to the Special Issue Intelligent Imaging and Analysis)
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Open AccessArticle Effect of a Healing Agent on the Curing Reaction Kinetics and Its Mechanism in a Self-Healing System
Appl. Sci. 2018, 8(11), 2241; https://doi.org/10.3390/app8112241 (registering DOI)
Received: 7 October 2018 / Revised: 28 October 2018 / Accepted: 7 November 2018 / Published: 14 November 2018
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Abstract
Self-healing cementitious composites have been developed by using microcapsules. In this study, the effect of the healing agent on the crosslinking and curing reaction kinetics was analyzed. The effect of the diluent n-butyl glycidyl ether (BGE) on the reaction was investigated for five
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Self-healing cementitious composites have been developed by using microcapsules. In this study, the effect of the healing agent on the crosslinking and curing reaction kinetics was analyzed. The effect of the diluent n-butyl glycidyl ether (BGE) on the reaction was investigated for five fractions, namely 10.0%, 12.5%, 15.0%, 17.5%, and 20.0% mass fractions to epoxy resin. The Kissinger and Crane equations were used to obtain the activation energy and reaction order with different mass fractions of diluent, as well as the kinetic parameters of the curing reaction. The optimal fraction of BGE was determined as 17.5%. Likewise, the effect of the curing agent MC120D on the reaction kinetics was investigated for 10%, 20%, 30%, 40%, and 50% mass fractions to the diluted epoxy resin. The optimal fraction was determined as 20%. The mechanism of the curing reaction with the healing agent was investigated. The infrared spectra of the cured products of 20% MC120D with BGE/E51 (0.0%, 12.5%, 15.0%, 20.0%, 100%) were analyzed. It is shown that not only the epoxy resin E-51 was cured, but also that the BGE was involved in the cross-linking reaction of the epoxy resin E-51 with MC120D. Full article
(This article belongs to the Special Issue Synthesis and Application of Microcapsules)
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Open AccessArticle Nonlinear Ultrasonic Detection Method for Delamination Damage of Lined Anti-Corrosion Pipes Using PZT Transducers
Appl. Sci. 2018, 8(11), 2240; https://doi.org/10.3390/app8112240 (registering DOI)
Received: 20 October 2018 / Revised: 4 November 2018 / Accepted: 8 November 2018 / Published: 14 November 2018
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Abstract
Lined anti-corrosion pipes are widely used in oil and gas, petrochemical, pharmaceutical industries. However, defects, especially delamination, may occur in the production and service of pipes which result in safety accidents. Based on nonlinear ultrasonic theory, this paper studied the delamination detection method
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Lined anti-corrosion pipes are widely used in oil and gas, petrochemical, pharmaceutical industries. However, defects, especially delamination, may occur in the production and service of pipes which result in safety accidents. Based on nonlinear ultrasonic theory, this paper studied the delamination detection method using the nonlinear harmonics for lined anti-corrosion pipes. The response characteristics of the anti-corrosion pipe were obtained through a sweep sine response experiment and the preferred excitation frequency was determined. The Wavelet Packet transform and Hilbert–Huang transform is applied for signal process and feature extraction. Then, a series of experiments were carried out and the results were analyzed and discussed. The results showed that a second-order and third-order nonlinear coefficient increased with the delamination damage. The amplitude of second-harmonic is much stronger than the third-order one. The mean squared error of the nonlinear coefficient, which was processed by Wavelet Packet transform and Hilbert–Huang transform, is smaller than wavelet packet transform and Discrete Fourier transform or processed only Hilbert–Huang transform. The higher harmonics can describe the change of delamination damage, which means that the nonlinear ultrasonic detection method could use for damage detection of anti-corrosion pipe. The nonlinear higher-harmonic is sensitive to delamination damage. The nonlinear ultrasonic method has the potential for damage detection for lined anti-corrosion pipes. Full article
(This article belongs to the Special Issue Structural Damage Detection and Health Monitoring)
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Open AccessArticle Design and Implementation of a Smart IoT Based Building and Town Disaster Management System in Smart City Infrastructure
Appl. Sci. 2018, 8(11), 2239; https://doi.org/10.3390/app8112239 (registering DOI)
Received: 30 September 2018 / Revised: 27 October 2018 / Accepted: 8 November 2018 / Published: 13 November 2018
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Abstract
Recently, fire accidents in buildings have become bigger around the world, and it has become necessary to build an efficient building disaster management system suitable for fires in a Smart City. As building fires increase the number of casualties and property damage, it
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Recently, fire accidents in buildings have become bigger around the world, and it has become necessary to build an efficient building disaster management system suitable for fires in a Smart City. As building fires increase the number of casualties and property damage, it is necessary to take appropriate action accordingly. There has been an increasing effort to develop such disaster management systems worldwide by applying information communication technology (ICT), and many studies have been conducted in practice. In this paper, an augmented reality (AR)-based Smart Building and Town Disaster Management System is suggested in order to acquire visibility and to grasp occupants in case of fire disasters in buildings. This system provides visualization information and optimal guide for quick initial response by utilizing smart element AR-based disaster management service through linkage of physical virtual domain in the building. Additionally, we show a scenario flow chart of the fire extinguishment process according to the time from the ignition stage to the extinguishment stage in the building. Finally, we introduce the related sensors, the actuators, and a small test-bed for AR-based disaster management service. This test-bed was designed for interlocking and interoperability test of the system between the sensors and the actuators. It is expected that the proposed system can provide a quick and safe rescue guideline to the occupants and rescuers in the building where fire is generated and in regions of poor visibility. Full article
(This article belongs to the Special Issue Advanced Internet of Things for Smart Infrastructure System)
Open AccessArticle Postbuckling and Free Vibration of Multilayer Imperfect Nanobeams under a Pre-Stress Load
Appl. Sci. 2018, 8(11), 2238; https://doi.org/10.3390/app8112238 (registering DOI)
Received: 10 October 2018 / Revised: 5 November 2018 / Accepted: 5 November 2018 / Published: 13 November 2018
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Abstract
This paper investigates the postbuckling and free vibration response of geometrically imperfect multilayer nanobeams. The beam is assumed to be subjected to a pre-stress compressive load due to the manufacturing and its ends are kept at a fixed distance in space. The small-size
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This paper investigates the postbuckling and free vibration response of geometrically imperfect multilayer nanobeams. The beam is assumed to be subjected to a pre-stress compressive load due to the manufacturing and its ends are kept at a fixed distance in space. The small-size effect is modeled according to the nonlocal elasticity differential model of Eringen within the nonlinear Bernoulli-Euler beam theory. The constitutive equations relating the stress resultants to the cross-section stiffness constants for a nonlocal multilayer beam are developed. The governing nonlinear equation of motion is derived and then manipulated to be given in terms of only the lateral displacement. The static problem is solved for the buckling load and the postbuckling deflection in terms of three parameters: Imperfection amplitude, size, and lamination. A closed-form solution for the buckling load in terms of all of the beam parameters is developed. With the presence of imperfection and size effects, it has been shown that the buckling load can be either less or greater than the Euler buckling load. Moreover, the free vibration in the pre and postbuckling domains are investigated for the first five modes. Numerical results show that the effects of imperfection, the nonlocal parameter, and layup on buckling loads and natural frequencies of the nanobeams are significant. Full article
(This article belongs to the Special Issue Recent Advances in Non-Local Modelling of Nano-Structures)
Open AccessArticle Experimental Study on the Static Behavior of Reinforced Warren Circular Hollow Section (CHS) Tubular Trusses
Appl. Sci. 2018, 8(11), 2237; https://doi.org/10.3390/app8112237 (registering DOI)
Received: 18 October 2018 / Revised: 9 November 2018 / Accepted: 9 November 2018 / Published: 13 November 2018
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Abstract
For truss structures, the question of whether to weld hidden welds or not has been controversial. In the actual construction process of truss structures, the members are usually spot welded in place on the assembly platform, and then welded as a whole, while
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For truss structures, the question of whether to weld hidden welds or not has been controversial. In the actual construction process of truss structures, the members are usually spot welded in place on the assembly platform, and then welded as a whole, while the hidden welds of the truss are not welded, especially for small pipe diameter trusses. Furthermore, in this study, under hidden weld unwelded conditions, two kinds of reinforcing method (adding a half outer sleeve on each joint and filling concrete into the chord members) are adopted to achieve the purpose of strengthening the truss. Therefore, this paper presents an experimental study on the static behavior of four types of Warren tubular trusses made of CHS members. These four types are (1) T-HW: The truss with hidden welds welded; (2) T-HN: The truss with hidden welds unwelded; (3) TS-AS: The truss strengthened on the basis of T-HN by adding a half outer sleeve on each joint; (4) TS-FC: The truss strengthened on the basis of T-HN by filling concrete into the top and bottom chord members. The mechanical behavior, failure mode, bearing capacity, and load-displacement of all specimens were investigated. The surface plasticity of the bottom chord member, the weld fracture around tubular joints at the bottom chord member, and the bending deformation of the bottom chord member were observed in the tests. Compared with the T-HW specimen, the load carrying capacity of the T-HN specimen decreased by 18%. On the other hand, the T-HN specimen has better deformability than the T-HW specimen. The reinforcing method of adding a half outer sleeve on each joint and filling concrete into the chord members can effectively improve the load carrying capacity and stiffness of the truss, thus reducing the overall deformation of the truss, but the reinforcing method of filling concrete into the chord members is more efficient. Full article
(This article belongs to the Special Issue Emerging Construction Materials and Sustainable Infrastructure)
Open AccessArticle A Unified Approach to Design Robust Controllers for Nonlinear Uncertain Engineering Systems
Appl. Sci. 2018, 8(11), 2236; https://doi.org/10.3390/app8112236 (registering DOI)
Received: 25 September 2018 / Revised: 24 October 2018 / Accepted: 5 November 2018 / Published: 13 November 2018
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Abstract
This paper presents new theorems, which allow to design in a unified way robust proportional-derivative (PD)-type control laws without chattering for a broad class of uncertain nonlinear multi-input multi-output (MIMO) systems, subject to bounded disturbances and noises, of great theoretical and engineering relevance.
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This paper presents new theorems, which allow to design in a unified way robust proportional-derivative (PD)-type control laws without chattering for a broad class of uncertain nonlinear multi-input multi-output (MIMO) systems, subject to bounded disturbances and noises, of great theoretical and engineering relevance. These controllers are used to track a reference signal with bounded second derivative with the tracking error norm smaller than a prescribed value. The proposed control laws are simple to design and implement, above all for robotic systems, both in the case of a trajectory assigned in the joint space and in the workspace. The obtained theoretical results can have numerous applications. In this paper four significant applications are provided. The first one concerns the solution of a nonlinear equations system or the determination of an equilibrium point of a nonlinear system. The second case study deals with the inversion of a nonlinear vectorial function or the kinematic inversion of a robot. The third application concerns: (A) the tracking control of a robot with parametric uncertainties, with and without measurement noise on velocity, both in the joint space and the workspace; (B) the impedance control of a robot interacting with a human operator. The fourth case study addresses the tracking control of an uncertain nonlinear system that does not belong to the class of mechanical systems. Finally, an appendix is included, providing six easy examples, which show how the results proposed in the paper can eliminate and/or reduce serious disadvantages existing in the robust control literature for significant classes of linear and nonlinear uncertain systems. Full article
Open AccessArticle Adaptive Threshold Generation for Fault Detection with High Dependability for Cyber-Physical Systems
Appl. Sci. 2018, 8(11), 2235; https://doi.org/10.3390/app8112235 (registering DOI)
Received: 26 October 2018 / Revised: 9 November 2018 / Accepted: 10 November 2018 / Published: 13 November 2018
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Abstract
Cyber-physical systems (CPS) applied to safety-critical or mission-critical domains require high dependability including safety, security, and reliability. However, the safety of CPS can be significantly threatened by increased security vulnerabilities and the lack of flexibility in accepting various normal environments or conditions. To
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Cyber-physical systems (CPS) applied to safety-critical or mission-critical domains require high dependability including safety, security, and reliability. However, the safety of CPS can be significantly threatened by increased security vulnerabilities and the lack of flexibility in accepting various normal environments or conditions. To enhance safety and security in CPS, a common and cost-effective strategy is to employ the model-based detection technique; however, detecting faults in practice is challenging due to model and environment uncertainties. In this paper, we present a novel generation method of the adaptive threshold required for providing dependability for the model-based fault detection system. In particular, we focus on statistical and information theoretic analysis to consider the model and environment uncertainties, and non-linear programming to determine an adaptive threshold as an equilibrium point in terms of adaptability and sensitivity. To do this, we assess the normality of the data obtained from real sensors, define performance measures representing the system requirements, and formulate the optimal threshold problem. In addition, in order to efficiently exploit the adaptive thresholds, we design the storage so that it is added to the basic structure of the model-based detection system. By executing the performance evaluation with various fault scenarios by varying intensities, duration and types of faults injected, we prove that the proposed method is well designed to cope with uncertainties. In particular, against noise faults, the proposed method shows nearly 100% accuracy, recall, and precision at each of the operation, regardless of the intensity and duration of faults. Under the constant faults, it achieves the accuracy from 85.4% to 100%, the recall of 100% from the lowest 54.2%, and the precision of 100%. It also gives the accuracy of 100% from the lowest 83.2%, the recall of 100% from the lowest 43.8%, and the precision of 100% against random faults. These results indicate that the proposed method achieves a significantly better performance than existing dynamic threshold methods. Consequently, an extensive performance evaluation demonstrates that the proposed method is able to accurately and reliably detect the faults and achieve high levels of adaptability and sensitivity, compared with other dynamic thresholds. Full article
(This article belongs to the Special Issue Fault Detection and Diagnosis in Mechatronics Systems)
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Open AccessArticle A Graph Representation Composed of Geometrical Components for Household Furniture Detection by Autonomous Mobile Robots
Appl. Sci. 2018, 8(11), 2234; https://doi.org/10.3390/app8112234 (registering DOI)
Received: 30 September 2018 / Revised: 2 November 2018 / Accepted: 8 November 2018 / Published: 13 November 2018
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Abstract
This study proposes a framework to detect and recognize household furniture using autonomous mobile robots. The proposed methodology is based on the analysis and integration of geometric features extracted over 3D point clouds. A relational graph is constructed using those features to model
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This study proposes a framework to detect and recognize household furniture using autonomous mobile robots. The proposed methodology is based on the analysis and integration of geometric features extracted over 3D point clouds. A relational graph is constructed using those features to model and recognize each piece of furniture. A set of sub-graphs corresponding to different partial views allows matching the robot’s perception with partial furniture models. A reduced set of geometric features is employed: horizontal and vertical planes and the legs of the furniture. These features are characterized through their properties, such as: height, planarity and area. A fast and linear method for the detection of some geometric features is proposed, which is based on histograms of 3D points acquired from an RGB-D camera onboard the robot. Similarity measures for geometric features and graphs are proposed, as well. Our proposal has been validated in home-like environments with two different mobile robotic platforms; and partially on some 3D samples of a database. Full article
(This article belongs to the Special Issue Advanced Mobile Robotics)
Open AccessArticle Minimum Barrier Distance-Based Object Descriptor for Visual Tracking
Appl. Sci. 2018, 8(11), 2233; https://doi.org/10.3390/app8112233 (registering DOI)
Received: 10 September 2018 / Revised: 24 October 2018 / Accepted: 30 October 2018 / Published: 13 November 2018
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Abstract
In most visual tracking tasks, the target is tracked by a bounding box given in the first frame. The complexity and redundancy of background information in the bounding box inevitably exist and affect tracking performance. To alleviate the influence of background, we propose
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In most visual tracking tasks, the target is tracked by a bounding box given in the first frame. The complexity and redundancy of background information in the bounding box inevitably exist and affect tracking performance. To alleviate the influence of background, we propose a robust object descriptor for visual tracking in this paper. First, we decompose the bounding box into non-overlapping patches and extract the color and gradient histograms features for each patch. Second, we adopt the minimum barrier distance (MBD) to calculate patch weights. Specifically, we consider the boundary patches as the background seeds and calculate the MBD from each patch to the seed set as the weight of each patch since the weight calculated by MBD can represent the difference between each patch and the background more effectively. Finally, we impose the weight on the extracted feature to get the descriptor of each patch and then incorporate our MBD-based descriptor into the structured support vector machine algorithm for tracking. Experiments on two benchmark datasets demonstrate the effectiveness of the proposed approach. Full article
(This article belongs to the Special Issue Advanced Intelligent Imaging Technology)
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Open AccessArticle Simultaneous Measurement Method and Error Analysis of the Six Degrees-of-Freedom Motion Errors of a Rotary Axis
Appl. Sci. 2018, 8(11), 2232; https://doi.org/10.3390/app8112232 (registering DOI)
Received: 28 September 2018 / Revised: 31 October 2018 / Accepted: 7 November 2018 / Published: 13 November 2018
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Abstract
Error measurement of a rotary axis is the key to error compensation and to improving motion accuracy. However, only a few instruments can measure all the motion errors of a rotary axis. In this paper, a device based on laser collimation and laser
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Error measurement of a rotary axis is the key to error compensation and to improving motion accuracy. However, only a few instruments can measure all the motion errors of a rotary axis. In this paper, a device based on laser collimation and laser interferometry was introduced for simultaneous measurement of all six degrees-of-freedom motion errors of a rotary axis. Synchronous rotation of the target and reference rotary axes was achieved by developing a proportional–integral–derivative algorithm. An error model for the measuring device was established using a homogeneous transformation matrix. The influences of installation errors, manufacturing errors, and error crosstalk were studied in detail, and compensation methods for them were proposed. After compensation, the repeatability of axial and radial motion errors was significantly improved. The repeatability values of angular positioning error and of tilt motion error around the y axis and x axis were 28.0″, 2.8″, and 3.9″. The repeatability values of translational motion errors were less than 2.8 μm. The comparison experiments show that the comparison errors of angular positioning error and tilt motion error around the y axis were 2.3″ and 2.9″, respectively. These results demonstrate the effectiveness of our method and the error compensation model. Full article
(This article belongs to the Special Issue Precision Dimensional Measurements)
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Open AccessArticle The Effect of Ageing on Chemical and Mechanical Properties of Asphalt Mortar
Appl. Sci. 2018, 8(11), 2231; https://doi.org/10.3390/app8112231 (registering DOI)
Received: 8 October 2018 / Revised: 8 November 2018 / Accepted: 9 November 2018 / Published: 13 November 2018
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Abstract
Asphalt mortar is a mixture of bitumen, filler, and sand. Mortar plays an important role in asphalt mixtures as it serves as the adhesive between the coarser aggregates. Due to the effect of bitumen ageing, the chemical and mechanical properties of asphalt mortar
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Asphalt mortar is a mixture of bitumen, filler, and sand. Mortar plays an important role in asphalt mixtures as it serves as the adhesive between the coarser aggregates. Due to the effect of bitumen ageing, the chemical and mechanical properties of asphalt mortar evolve with time. The mortar becomes more brittle and prone to cracking, thus leading to inferior pavement performance. In this study, Fourier transform infrared (FTIR) spectrometry was used to quantify changes in the chemical functional groups related to ageing and to calculate the carbonyl and sulfoxide indices. In addition, frequency sweep tests and uniaxial tension tests were performed by means of dynamic shear rheometer (DSR) tests to determine evolution of the stiffness and strength due to ageing. Two different oven ageing protocols were used to evaluate the effect of fine mineral particles on bitumen ageing. The protocols differed with respect to the order of ageing and mixing of the constituents. The results showed that both the chemical and mechanical properties of mortars significantly changed with ageing. Specifically, the carbonyl index, stiffness, and strength of the mortar increased. Under the same ageing conditions, a higher ageing level was observed for mortars produced by first mixing and then ageing compared to the mortars produced by mixing aged bitumen with filler and sand. This could be due to the presence of sand and filler particles, which resulted in an increased length of diffusion paths and consequently a slower ageing process. Full article
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Open AccessArticle LDS Realization of High-Q SIW Millimeter Wave Filters with Cyclo-Olefin Polymers
Appl. Sci. 2018, 8(11), 2230; https://doi.org/10.3390/app8112230 (registering DOI)
Received: 11 October 2018 / Revised: 5 November 2018 / Accepted: 6 November 2018 / Published: 13 November 2018
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Abstract
In this paper, we present narrow-band substrate integrated waveguide (SIW) millimeter wave band-pass filters, designed using cyclo-olefin polymers (COP). The structures were molded, drilled, and metalized with a laser direct structuring (LDS) process. COP are a type of thermoplastic with low dielectric losses
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In this paper, we present narrow-band substrate integrated waveguide (SIW) millimeter wave band-pass filters, designed using cyclo-olefin polymers (COP). The structures were molded, drilled, and metalized with a laser direct structuring (LDS) process. COP are a type of thermoplastic with low dielectric losses in the millimeter waveband, typically 7.5 × 10−4 at 40 GHz for the COP RS420-LDS from Zeon®. The body of the filter was realized using a molding process that facilitates the combination of thin 50 Ω microstrip access lines with high thickness microwave cavities through 3D transitions, thus making high quality factors attainable. The simulations and experimental results are presented and discussed. Full article
(This article belongs to the Special Issue Substrate Integrated Waveguide (SIW) and its Applications)
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Open AccessArticle A Novel Approach for a Inverse Kinematics Solution of a Redundant Manipulator
Appl. Sci. 2018, 8(11), 2229; https://doi.org/10.3390/app8112229 (registering DOI)
Received: 18 September 2018 / Revised: 6 November 2018 / Accepted: 8 November 2018 / Published: 12 November 2018
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Abstract
Kinematically-redundant manipulators present considerable difficulties, especially from the view of control. A high number of degrees of freedom are used to control so-called secondary tasks in order to optimize manipulator motion. This paper introduces a new algorithm for the control of kinematically-redundant manipulator
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Kinematically-redundant manipulators present considerable difficulties, especially from the view of control. A high number of degrees of freedom are used to control so-called secondary tasks in order to optimize manipulator motion. This paper introduces a new algorithm for the control of kinematically-redundant manipulator considering three secondary tasks, namely a joint limit avoidance task, a kinematic singularities avoidance task, and an obstacle avoidance task. For path planning of end-effector from start to goal point, the potential field method is used. The final inverse kinematic model is designed by a Jacobian-based method considering weight matrices in order to prioritize particular tasks. Our approach is based on the flexible behavior of priority value due to the acceleration of numerical simulation. The results of the simulations show the advantage of our approach, which results in a significant decrease of computing time. Full article
(This article belongs to the Special Issue Advanced Mobile Robotics)
Open AccessArticle A High-Resolution Texture Mapping Technique for 3D Textured Model
Appl. Sci. 2018, 8(11), 2228; https://doi.org/10.3390/app8112228 (registering DOI)
Received: 1 October 2018 / Revised: 1 November 2018 / Accepted: 8 November 2018 / Published: 12 November 2018
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Abstract
We proposed a texture mapping technique that comprises mesh partitioning, mesh parameterization and packing, texture transferring, and texture correction and optimization for generating a high-quality texture map of a three-dimensional (3D) model for applications in e-commerce presentations. The main problems in texture mapping
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We proposed a texture mapping technique that comprises mesh partitioning, mesh parameterization and packing, texture transferring, and texture correction and optimization for generating a high-quality texture map of a three-dimensional (3D) model for applications in e-commerce presentations. The main problems in texture mapping are that the texture resolution is generally worse than in the original images and considerable photo inconsistency exists at the transition of different image sources. To improve the texture resolution, we employed an oriented boundary box method for placing mesh islands on the parametric (UV) map. We also provided a texture size that can keep the texture resolution of the 3D textured model similar to that of the object images. To improve the photo inconsistency problem, we employed a method to detect and overcome the missing color that might exist on a texture map. We also proposed a blending process to minimize the transition error caused by different image sources. Thus, a high-quality 3D textured model can be obtained by applying this series of processes for presentations in e-commerce. Full article
(This article belongs to the Special Issue Intelligent Imaging and Analysis)
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Open AccessArticle A Practical Approach for Data Gathering for Polymer Cure Simulations
Appl. Sci. 2018, 8(11), 2227; https://doi.org/10.3390/app8112227 (registering DOI)
Received: 16 October 2018 / Revised: 31 October 2018 / Accepted: 31 October 2018 / Published: 12 November 2018
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Abstract
Producing precision parts requires good control of the production parameters. When casting thermoset polymers an understanding of the curing process, with its heat release and associated temperature changes, is important. This paper describes how the cure of a polymer of unknown detailed chemical
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Producing precision parts requires good control of the production parameters. When casting thermoset polymers an understanding of the curing process, with its heat release and associated temperature changes, is important. This paper describes how the cure of a polymer of unknown detailed chemical composition in a large part can be predicted and how the necessary material properties required for the predictions can be obtained. The approach given is a relatively simple method that a part manufacturer can perform. It will not characterize chemical reactions in detail, but it gives sufficient accuracy to describe the process. The procedures will be explained for an example of casting a large block of a filled two-component thermoset polyurethane. The prediction of the degree of cure, the associated heat and temperature increase during the curing of a polymer was successfully done using a standard finite element program with the input parameters reaction energy, the Arrhenius pre-factor and the kinetic function, which describes the chemical reaction. The three parameters could be obtained with standard Differential Scanning Calorimetry (DSC) equipment. The data were analyzed with the model-free isoconversional method combined with the compensation effect. The same set of parameters allowed the prediction of experimental cure behavior over two orders of magnitude of time and at a curing temperature range from room temperature up to 420 K. Full article
(This article belongs to the Section Materials)
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Open AccessLetter Band-Pass Sampling in High-Order BOC Signal Acquisition
Appl. Sci. 2018, 8(11), 2226; https://doi.org/10.3390/app8112226 (registering DOI)
Received: 26 September 2018 / Revised: 2 November 2018 / Accepted: 5 November 2018 / Published: 12 November 2018
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Abstract
The binary offset carrier (BOC) modulation, which has been adopted in modern global navigation satellite systems (GNSS), provides a higher spectral compatibility with BPSK signals, and better tracking performance. However, the autocorrelation function (ACF) of BOC signals has multiple peaks. This feature complicates
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The binary offset carrier (BOC) modulation, which has been adopted in modern global navigation satellite systems (GNSS), provides a higher spectral compatibility with BPSK signals, and better tracking performance. However, the autocorrelation function (ACF) of BOC signals has multiple peaks. This feature complicates the acquisition process, since a smaller time searching step is required, which results in longer searching time or greater amounts of hardware resources. Another problem is the high Nyquist frequency, which leads to high computational complexity and power consumption. In this paper, to overcome these drawbacks, the band-pass sampling technique for multiple signals is introduced to BOC signals. The sampling frequency can be reduced significantly. Furthermore, the ACF of the sampled signal has only two secondary peaks, so that the code phase can be searched with a larger searching step. An acquisition structure base on dual-loop is proposed, to completely eliminate the ambiguity and compensate the subcarrier Doppler. The acquisition performance and the computational complexity are also analysed. Full article
(This article belongs to the Special Issue Signal Processing for Satellite Positioning Systems)
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Open AccessArticle Impact of a Pilot-Scale Plasma-Assisted Washing Process on the Culturable Microbial Community Dynamics Related to Fresh-Cut Endive Lettuce
Appl. Sci. 2018, 8(11), 2225; https://doi.org/10.3390/app8112225 (registering DOI)
Received: 30 September 2018 / Revised: 30 October 2018 / Accepted: 1 November 2018 / Published: 12 November 2018
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Abstract
Cold plasma is described as a promising technique for the treatment of fresh food. In particular, the application of plasma-treated water gained interest in fresh-cut produce processing. This study aimed to evaluate the effectiveness of plasma-treated water (PTW) to decontaminate lettuce during washing
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Cold plasma is described as a promising technique for the treatment of fresh food. In particular, the application of plasma-treated water gained interest in fresh-cut produce processing. This study aimed to evaluate the effectiveness of plasma-treated water (PTW) to decontaminate lettuce during washing on a pilot-scale level with special interest in the dynamics of the culturable microbial community in a first approach. PTW was used in pilot-scale washing at different processing steps, and the total viable count (TVC) of endive lettuce was determined after treatment and after storage (seven days, 2 °C). Microflora representatives were identified using MALDI-ToF MS. The highest reduction of TVC (1.8 log units) was achieved using PTW for washing whole lettuce before cutting. The microbial community structure showed high variations in the composition along the processing chain and during storage with a decrease in diversity after washing with PTW. PTW reduced the microbial load of endive lettuce; however, this was not clearly detectable at the end of storage, similar to other sanitizers used in comparable studies. To assure the safety of fresh products, detailed knowledge about the microbial load and the composition of the microbial community close to the end of shelf life is of high interest for optimized process design. Full article
(This article belongs to the Special Issue Cold Plasma Treatment for Food Safety and Quality)
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Open AccessArticle Adaptive Solar Power Forecasting based on Machine Learning Methods
Appl. Sci. 2018, 8(11), 2224; https://doi.org/10.3390/app8112224 (registering DOI)
Received: 19 September 2018 / Revised: 20 October 2018 / Accepted: 7 November 2018 / Published: 12 November 2018
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Abstract
Due to the existence of predicting errors in the power systems, such as solar power, wind power and load demand, the economic performance of power systems can be weakened accordingly. In this paper, we propose an adaptive solar power forecasting (ASPF) method for
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Due to the existence of predicting errors in the power systems, such as solar power, wind power and load demand, the economic performance of power systems can be weakened accordingly. In this paper, we propose an adaptive solar power forecasting (ASPF) method for precise solar power forecasting, which captures the characteristics of forecasting errors and revises the predictions accordingly by combining data clustering, variable selection, and neural network. The proposed ASPF is thus quite general, and does not require any specific original forecasting method. We first propose the framework of ASPF, featuring the data identification and data updating. We then present the applied improved k-means clustering, the least angular regression algorithm, and BPNN, followed by the realization of ASPF, which is shown to improve as more data collected. Simulation results show the effectiveness of the proposed ASPF based on the trace-driven data. Full article
(This article belongs to the Special Issue Applications of Artificial Neural Networks for Energy Systems)
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Open AccessArticle Numerical Analysis for Thermal Performance of a Photovoltaic Thermal Solar Collector with SiO2-Water Nanofluid
Appl. Sci. 2018, 8(11), 2223; https://doi.org/10.3390/app8112223 (registering DOI)
Received: 17 October 2018 / Revised: 2 November 2018 / Accepted: 5 November 2018 / Published: 11 November 2018
Viewed by 209 | PDF Full-text (841 KB)
Abstract
Numerical analysis of a photovoltaic-thermal (PV/T) unit with SiO2-water nanofluid was performed. The coupled heat conduction equations within the layers and convective heat transfer equations within the channel of the module were solved by using the finite volume method. Effects of
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Numerical analysis of a photovoltaic-thermal (PV/T) unit with SiO 2 -water nanofluid was performed. The coupled heat conduction equations within the layers and convective heat transfer equations within the channel of the module were solved by using the finite volume method. Effects of various particle shapes, solid volume fractions, water inlet temperature, solar irradiation and wind speed on the thermal and PV efficiency of the unit were analyzed. Correlation for the efficiencies were obtained by using radial basis function neural networks. Cylindrical shape particles were found to give best performance in terms of efficiency enhancements. Total efficiency enhances by about 7.39% at the highest volume fraction with cylindrical shape particles. Cylindrical shape particle gives 3.95% more enhancement as compared to spherical ones for the highest value of solid particle volume fraction. Thermal and total efficiency enhance for higher values of solid particle volume fraction, solar irradiation and lower values of convective heat transfer coefficient and inlet temperature. The performance characteristics of solar PV-thermal unit with radial basis function artificial neural network are found to be in excellent agreement with the results obtained from computational fluid dynamics modeling. Full article
Open AccessArticle An Improved Neural Network Cascade for Face Detection in Large Scene Surveillance
Appl. Sci. 2018, 8(11), 2222; https://doi.org/10.3390/app8112222 (registering DOI)
Received: 30 September 2018 / Revised: 8 November 2018 / Accepted: 8 November 2018 / Published: 11 November 2018
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Abstract
Face detection for security cameras monitoring large and crowded areas is very important for public safety. However, it is much more difficult than traditional face detection tasks. One reason is, in large areas like squares, stations and stadiums, faces captured by cameras are
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Face detection for security cameras monitoring large and crowded areas is very important for public safety. However, it is much more difficult than traditional face detection tasks. One reason is, in large areas like squares, stations and stadiums, faces captured by cameras are usually at a low resolution and thus miss many facial details. In this paper, we improve popular cascade algorithms by proposing a novel multi-resolution framework that utilizes parallel convolutional neural network cascades for detecting faces in large scene. This framework utilizes the face and head-with-shoulder information together to deal with the large area surveillance images. Comparing with popular cascade algorithms, our method outperforms them by a large margin. Full article
(This article belongs to the Special Issue Advanced Intelligent Imaging Technology)
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Open AccessArticle Sorption of Ag+ and Cu2+ by Vermiculite in a Fixed-Bed Column: Design, Process Optimization and Dynamics Investigations
Appl. Sci. 2018, 8(11), 2221; https://doi.org/10.3390/app8112221 (registering DOI)
Received: 15 October 2018 / Revised: 4 November 2018 / Accepted: 9 November 2018 / Published: 11 November 2018
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Abstract
Vermiculite has been used for the removal of Cu2+ and Ag+ from aqueous solutions in a fixed-bed column system. The effects of initial silver and copper ion concentrations, flow rate, and bed height of the adsorbent in a fixed-bed column
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Vermiculite has been used for the removal of Cu 2 + and Ag + from aqueous solutions in a fixed-bed column system. The effects of initial silver and copper ion concentrations, flow rate, and bed height of the adsorbent in a fixed-bed column system were investigated. Statistical analysis confirmed that breakthrough curves depended on all three factors. The highest inlet metal cation concentration (5000 mg/dm3), the lowest bed height (3 cm) and the lowest flow rate (2 and 3 cm3/min for Ag + and Cu 2 + , respectively) were optimal for the adsorption process. The maximum total percentage of metal ions removed was 60.4% and 68.7% for Ag+ and Cu2+, respectively. Adsorption data were fitted with four fixed-bed adsorption models, namely Clark, Bohart–Adams, Yoon–Nelson and Thomas models, to predict breakthrough curves and to determine the characteristic column parameters. The adsorbent was characterized by SEM, FTIR, EDS and BET techniques. The results showed that vermiculite could be applied as a cost-effective sorbent for the removal of Cu 2 + and Ag + from wastewater in a continuous process. Full article
(This article belongs to the Special Issue The Adsorption of Emerging Contaminants in Aqueous Environment)
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Open AccessCommunication Moving towards Smart Cities: A Selection of Middleware for Fog-to-Cloud Services
Appl. Sci. 2018, 8(11), 2220; https://doi.org/10.3390/app8112220 (registering DOI)
Received: 1 October 2018 / Revised: 3 November 2018 / Accepted: 8 November 2018 / Published: 11 November 2018
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Abstract
Smart cities aim at integrating various IoT (Internet of Things) technologies by providing many opportunities for the development, governance, and management of user services. One of the ways to support this idea is to use cloud and edge computing techniques to reduce costs,
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Smart cities aim at integrating various IoT (Internet of Things) technologies by providing many opportunities for the development, governance, and management of user services. One of the ways to support this idea is to use cloud and edge computing techniques to reduce costs, manage resource consumption, enhance performance, and connect the IoT devices more effectively. However, the selection of services remains a significant research question since there are currently different strategies towards cloud computing, including services for central remote computing (traditional cloud model) as well as distributed local computing (edge computing). In this paper, we offer an integrated view of these two directions and the selection among the edge technologies based on MCDA (Multiple Criteria Decision Analysis) algorithms. To this end, we propose a foglet as a middleware that aims at achieving satisfactory levels of customer services by using fuzzy similarity and TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) to facilitate the rating and selection of services in the fog-to-cloud environment. Then, we describe the selection process with a numerical example, and conclude our work with an outline of future perspectives. Full article
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Open AccessArticle Real-Time HIFU Treatment Monitoring Using Pulse Inversion Ultrasonic Imaging
Appl. Sci. 2018, 8(11), 2219; https://doi.org/10.3390/app8112219 (registering DOI)
Received: 3 October 2018 / Revised: 30 October 2018 / Accepted: 8 November 2018 / Published: 11 November 2018
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Abstract
Real-time monitoring of high-intensity focused ultrasound (HIFU) surgery is essential for safe and accurate treatment. However, ultrasound imaging is difficult to use for treatment monitoring during HIFU surgery because of the high intensity of the HIFU echoes that are received by an imaging
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Real-time monitoring of high-intensity focused ultrasound (HIFU) surgery is essential for safe and accurate treatment. However, ultrasound imaging is difficult to use for treatment monitoring during HIFU surgery because of the high intensity of the HIFU echoes that are received by an imaging transducer. Here, we propose a real-time HIFU treatment monitoring method based on pulse inversion of imaging ultrasound; an imaging transducer fires ultrasound twice in 0° and 180° phases for one scanline while HIFUs of the same phase are transmitted in synchronization with the ultrasound transmission for imaging. By doing so, HIFU interferences can be eliminated after subtracting the two sets of the signals received by the imaging transducer. This function was implemented in a commercial research ultrasound scanner, and its performance was evaluated using the excised bovine liver. The experimental results demonstrated that the proposed method allowed ultrasound images to clearly show the echogenicity change induced by HIFU in the excised bovine liver. Additionally, it was confirmed that the moving velocity of the organs in the abdomen due to respiration does not affect the performance of the proposed method. Based on the experimental results, we believe that the proposed method can be used for real-time HIFU surgery monitoring that is a pivotal function for maximized treatment efficacy. Full article
(This article belongs to the Section Acoustics and Vibrations)
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Open AccessArticle A Novel Ultrasonic Cavitation Peening Approach Assisted by Water Jet
Appl. Sci. 2018, 8(11), 2218; https://doi.org/10.3390/app8112218 (registering DOI)
Received: 28 September 2018 / Revised: 26 October 2018 / Accepted: 9 November 2018 / Published: 11 November 2018
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Abstract
Ultrasonic cavitation peening is an environmentally friendly technology to improve surface properties. In the traditional ultrasonic cavitation peening process, specimens have to be immersed in a liquid and temperature control is required, which limits the wide usage of this technology due to the
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Ultrasonic cavitation peening is an environmentally friendly technology to improve surface properties. In the traditional ultrasonic cavitation peening process, specimens have to be immersed in a liquid and temperature control is required, which limits the wide usage of this technology due to the geometry and complicated setup. In order to improve this process, water is slowly jetted (75 mL/min) into the gap between the sonotrode tip and specimen surface. The water jet makes the gap full of water. Thus, cavitation bubbles can be generated in the gap as the traditional ultrasonic cavitation peening process. In this case, the water container and temperature control are no longer necessary. The goal of this contribution is to evaluate the treatment effectiveness of this novel approach by the impact loads, the volume loss, the surface roughness, the microhardness and the microstructure of the specimen surface. The results indicate that a higher input power is beneficial and there would be an optimal gap width for this novel ultrasonic cavitation peening process. Full article
(This article belongs to the Section Mechanical Engineering)
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Open AccessArticle Scandium Doping Effect on a Layered Perovskite Cathode for Low-Temperature Solid Oxide Fuel Cells (LT-SOFCs)
Appl. Sci. 2018, 8(11), 2217; https://doi.org/10.3390/app8112217 (registering DOI)
Received: 22 October 2018 / Revised: 6 November 2018 / Accepted: 8 November 2018 / Published: 11 November 2018
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Abstract
Layered perovskite oxides are considered as promising cathode materials for the solid oxide fuel cell (SOFC) due to their high electronic/ionic conductivity and fast oxygen kinetics at low temperature. Many researchers have focused on further improving the electrochemical performance of the layered perovskite
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Layered perovskite oxides are considered as promising cathode materials for the solid oxide fuel cell (SOFC) due to their high electronic/ionic conductivity and fast oxygen kinetics at low temperature. Many researchers have focused on further improving the electrochemical performance of the layered perovskite material by doping various metal ions into the B-site. Herein, we report that Sc3+ doping into the layered perovskite material, PrBaCo2O5+δ (PBCO), shows a positive effect of increasing electrochemical performances. We confirmed that Sc3+ doping could provide a favorable crystalline structure of layered perovskite for oxygen ion transfer in the lattice with improved Goldschmidt tolerance factor and specific free volume. Consequently, the Sc3+ doped PBCO exhibits a maximum power density of 0.73 W cm−2 at 500 °C, 1.3 times higher than that of PBCO. These results indicate that Sc3+ doping could effectively improve the electrochemical properties of the layered perovskite material, PBCO. Full article
(This article belongs to the Special Issue New Materials for Solid Oxide Fuel Cells/Electrolysers)
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