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Appl. Sci., Volume 8, Issue 8 (August 2018)

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Open AccessArticle Cartilage Differentiation of Bone Marrow-Derived Mesenchymal Stem Cells in Three-Dimensional Silica Nonwoven Fabrics
Appl. Sci. 2018, 8(8), 1398; https://doi.org/10.3390/app8081398 (registering DOI)
Received: 24 June 2018 / Revised: 9 August 2018 / Accepted: 16 August 2018 / Published: 18 August 2018
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Abstract
In cartilage tissue engineering, three-dimensional (3D) scaffolds provide native extracellular matrix (ECM) environments that induce tissue ingrowth and ECM deposition for in vitro and in vivo tissue regeneration. In this report, we investigated 3D silica nonwoven fabrics (Cellbed®) as a scaffold
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In cartilage tissue engineering, three-dimensional (3D) scaffolds provide native extracellular matrix (ECM) environments that induce tissue ingrowth and ECM deposition for in vitro and in vivo tissue regeneration. In this report, we investigated 3D silica nonwoven fabrics (Cellbed®) as a scaffold for mesenchymal stem cells (MSCs) in cartilage tissue engineering applications. The unique, highly porous microstructure of 3D silica fabrics allows for immediate cell infiltration for tissue repair and orientation of cell–cell interaction. It is expected that the morphological similarity of silica fibers to that of fibrillar ECM contributes to the functionalization of cells. Human bone marrow-derived MSCs were cultured in 3D silica fabrics, and chondrogenic differentiation was induced by culture in chondrogenic differentiation medium. The characteristics of chondrogenic differentiation including cellular growth, ECM deposition of glycosaminoglycan and collagen, and gene expression were evaluated. Because of the highly interconnected network structure, stiffness, and permeability of the 3D silica fabrics, the level of chondrogenesis observed in MSCs seeded within was comparable to that observed in MSCs maintained on atelocollagen gels, which are widely used to study the chondrogenesis of MSCs in vitro and in vivo. These results indicated that 3D silica nonwoven fabrics are a promising scaffold for the regeneration of articular cartilage defects using MSCs, showing the particular importance of high elasticity. Full article
(This article belongs to the Special Issue Biocompatible Materials)
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Open AccessArticle Deep Learning for Audio Event Detection and Tagging on Low-Resource Datasets
Appl. Sci. 2018, 8(8), 1397; https://doi.org/10.3390/app8081397 (registering DOI)
Received: 15 June 2018 / Revised: 11 August 2018 / Accepted: 14 August 2018 / Published: 18 August 2018
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Abstract
In training a deep learning system to perform audio transcription, two practical problems may arise. Firstly, most datasets are weakly labelled, having only a list of events present in each recording without any temporal information for training. Secondly, deep neural networks need a
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In training a deep learning system to perform audio transcription, two practical problems may arise. Firstly, most datasets are weakly labelled, having only a list of events present in each recording without any temporal information for training. Secondly, deep neural networks need a very large amount of labelled training data to achieve good quality performance, yet in practice it is difficult to collect enough samples for most classes of interest. In this paper, we propose factorising the final task of audio transcription into multiple intermediate tasks in order to improve the training performance when dealing with this kind of low-resource datasets. We evaluate three data-efficient approaches of training a stacked convolutional and recurrent neural network for the intermediate tasks. Our results show that different methods of training have different advantages and disadvantages. Full article
(This article belongs to the Special Issue Computational Acoustic Scene Analysis)
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Open AccessArticle Comparative Life Cycle Assessment of End-of-Life Silicon Solar Photovoltaic Modules
Appl. Sci. 2018, 8(8), 1396; https://doi.org/10.3390/app8081396 (registering DOI)
Received: 26 July 2018 / Revised: 14 August 2018 / Accepted: 14 August 2018 / Published: 18 August 2018
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Abstract
The cumulative global photovoltaic (PV) waste reached 250,000 metric tonnes by the end of 2016 and is expected to increase considerably in the future. Hence, adequate end-of-life (EoL) management for PV modules must be developed. Today, most of the EoL modules go to
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The cumulative global photovoltaic (PV) waste reached 250,000 metric tonnes by the end of 2016 and is expected to increase considerably in the future. Hence, adequate end-of-life (EoL) management for PV modules must be developed. Today, most of the EoL modules go to landfill, mainly because recycling processes for PV modules are not yet economically feasible and regulation in most countries is not yet well established. Nevertheless, several methods for recycling PV modules are under development. Life cycle assessment (LCA) is a methodology that quantifies the environmental impacts of a process or a product. An attributional LCA was undertaken to compare landfill, incineration, reuse and recycling (mechanical, thermal and chemical routes) of EoL crystalline silicon (c-Si) solar modules, based on a combination of real process data and assumptions. The results show that recovery of materials from solar modules results in lower environmental impacts compared to other EoL scenarios, considering our assumptions. The impacts could be even lower with the adoption of more complex processes that can reclaim more materials. Although recycling processes can achieve good recycling rates and recover almost all materials from solar modules, attention must be paid to the use of toxic substances during the chemical routes of recycling and to the distance to recycling centres due to the impacts of transportation. Full article
(This article belongs to the Special Issue Next Generation Photovoltaic Solar Cells)
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Open AccessArticle Evaluation of the Undrained Shear Strength of Organic Soils from a Dilatometer Test Using Artificial Neural Networks
Appl. Sci. 2018, 8(8), 1395; https://doi.org/10.3390/app8081395 (registering DOI)
Received: 23 July 2018 / Revised: 10 August 2018 / Accepted: 13 August 2018 / Published: 17 August 2018
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Abstract
The undrained shear strength of organic soils can be evaluated based on measurements obtained from the dilatometer test using single- and multi-factor empirical correlations presented in the literature. However, the empirical methods may sometimes show relatively high values of maximum relative error. Therefore,
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The undrained shear strength of organic soils can be evaluated based on measurements obtained from the dilatometer test using single- and multi-factor empirical correlations presented in the literature. However, the empirical methods may sometimes show relatively high values of maximum relative error. Therefore, a method for evaluating the undrained shear strength of organic soils using artificial neural networks based on data obtained from a dilatometer test and organic soil properties is presented in this study. The presented neural network, with an architecture of 5-4-1, predicts the normalized undrained shear strength based on five independent variables: the normalized net value of a corrected first pressure reading (pouo)/σ′v, the normalized net value of a corrected second pressure reading (p1uo)/σ′v, the organic content Iom, the void ratio e, and the stress history indictor (oc or nc). The neural model presented in this study provided a more reliable prediction of the undrained shear strength in comparison to the empirical methods, with a maximum relative error of ±10%. Full article
(This article belongs to the Section Materials)
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Open AccessArticle A New Method for Active Cancellation of Engine Order Noise in a Passenger Car
Appl. Sci. 2018, 8(8), 1394; https://doi.org/10.3390/app8081394 (registering DOI)
Received: 8 June 2018 / Revised: 3 August 2018 / Accepted: 14 August 2018 / Published: 17 August 2018
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Abstract
This paper presents a novel active noise cancellation (ANC) method to reduce the engine noise inside the cabin of a car. During the last three decades, many methods have been developed for the active control of a quasi-stationary narrowband sinusoidal signal. However, since
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This paper presents a novel active noise cancellation (ANC) method to reduce the engine noise inside the cabin of a car. During the last three decades, many methods have been developed for the active control of a quasi-stationary narrowband sinusoidal signal. However, since the interior noise signal is non-stationary with a fast frequency variation when the car accelerates rapidly, these methods cannot stably reduce the interior noise. The proposed method can reduce the interior noise stably even if the speed of the car is changed quickly. The method uses an adaptive filter with an optimal weight vector for the active control of such an engine noise. The method of determining the optimal weight vector of an adaptive filter is demonstrated. In order to validate the advantages of the proposed method, a conventional method and the proposed method are simulated with three synthesized signals. Finally, the proposed method is applied to the cancellation of booming noise in a sport utility vehicle. We demonstrate that the performance of the ANC system with the proposed algorithm is excellent for the attenuation of engine noise inside the cabin of a car. Full article
(This article belongs to the Special Issue Active and Passive Noise Control)
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Open AccessArticle The Accuracy of Predicted Acoustical Parameters in Ancient Open-Air Theatres: A Case Study in Syracusae
Appl. Sci. 2018, 8(8), 1393; https://doi.org/10.3390/app8081393 (registering DOI)
Received: 20 June 2018 / Revised: 9 August 2018 / Accepted: 10 August 2018 / Published: 17 August 2018
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Abstract
Nowadays, ancient open-air theatres are often re-adapted as performance spaces for the additional historical value they can offer to the spectators’ experience. Therefore, there has been an increasing interest in the modelling and simulation of the acoustics of such spaces. These open-air performance
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Nowadays, ancient open-air theatres are often re-adapted as performance spaces for the additional historical value they can offer to the spectators’ experience. Therefore, there has been an increasing interest in the modelling and simulation of the acoustics of such spaces. These open-air performance facilities pose several methodological challenges to researchers and practitioners when it comes to precisely measure and predict acoustical parameters. Therefore this work investigates the accuracy of predicted acoustical parameters, that is, the Reverberation Time (T20), Clarity (C80) and Sound Strength (G), taking the ancient Syracusae open-air theatre in Italy as a case study. These parameters were derived from both measured and simulated Impulse Responses (IR). The accuracy of the acoustic parameters predicted with two different types of acoustic software, due to the input variability of the absorption and scattering coefficients, was assessed. All simulated and measured parameters were in good agreement, within the range of one “just noticeable difference” (JND), for the tested coefficient combinations. Full article
(This article belongs to the Special Issue Modelling, Simulation and Data Analysis in Acoustical Problems)
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Open AccessArticle Vibration-Based Bearing Fault Detection and Diagnosis via Image Recognition Technique Under Constant and Variable Speed Conditions
Appl. Sci. 2018, 8(8), 1392; https://doi.org/10.3390/app8081392 (registering DOI)
Received: 16 July 2018 / Revised: 11 August 2018 / Accepted: 13 August 2018 / Published: 17 August 2018
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Abstract
This paper addresses the application of an image recognition technique for the detection and diagnosis of ball bearing faults in rotating electrical machines (REMs). The conventional bearing fault detection and diagnosis (BFDD) methods rely on extracting different features from either waveforms or spectra
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This paper addresses the application of an image recognition technique for the detection and diagnosis of ball bearing faults in rotating electrical machines (REMs). The conventional bearing fault detection and diagnosis (BFDD) methods rely on extracting different features from either waveforms or spectra of vibration signals to detect and diagnose bearing faults. In this paper, a novel vibration-based BFDD via a probability plot (ProbPlot) image recognition technique under constant and variable speed conditions is proposed. The proposed technique is based on the absolute value principal component analysis (AVPCA), namely, ProbPlot via image recognition using the AVPCA (ProbPlot via IR-AVPCA) technique. A comparison of the features (images) obtained: (1) directly in the time domain from the original raw data of the vibration signals; (2) by capturing the Fast Fourier Transformation (FFT) of the vibration signals; or (3) by generating the probability plot (ProbPlot) of the vibration signals as proposed in this paper, is considered. A set of realistic bearing faults (i.e., outer-race fault, inner-race fault, and balls fault) are experimentally considered to evaluate the performance and effectiveness of the proposed ProbPlot via the IR-AVPCA method. Full article
(This article belongs to the Special Issue Fault Detection and Diagnosis in Mechatronics Systems)
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Open AccessArticle Low-Field NMR and MRI to Analyze the Effect of Edible Coating Incorporated with MAP on Qualities of Half-Smooth Tongue Sole (Cynoglossus Semilaevis Günther) Fillets during Refrigerated Storage
Appl. Sci. 2018, 8(8), 1391; https://doi.org/10.3390/app8081391 (registering DOI)
Received: 30 July 2018 / Revised: 10 August 2018 / Accepted: 15 August 2018 / Published: 17 August 2018
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Abstract
Nondestructive and fast measurement and characterization of fish is highly desired during various processing treatments. This research investigated the effectiveness of low field LF-NMR and MRI as fast monitoring techniques to estimate the qualities of half-smooth tongue sole fillets treated with edible coating
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Nondestructive and fast measurement and characterization of fish is highly desired during various processing treatments. This research investigated the effectiveness of low field LF-NMR and MRI as fast monitoring techniques to estimate the qualities of half-smooth tongue sole fillets treated with edible coating combined with modified atmosphere packaging during refrigeration. T2 relaxation spectra showed three peaks representing bound water (T21), immobile water (T22), and free water (T23), respectively. pT22 accounted for the largest proportion of three types of water, followed by pT23. The weighted MRI provided the internal structure information associated with different samples, indicting the combination of edible coating and MAP (70% CO2 + 30% N2) is the best performance in the maintenance of qualities and freshness of HTS fillets. All results demonstrated that the combination of LF-NMR and MRI as fast and nondestructive methods have great potential to monitor qualities deterioration and predict shelf life in of HTS fillets during refrigerated storage. Full article
(This article belongs to the Special Issue Applications of Low Field Magnetic Resonance)
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Open AccessArticle A Solar–Thermal-Assisted Adiabatic Compressed Air Energy Storage System and Its Efficiency Analysis
Appl. Sci. 2018, 8(8), 1390; https://doi.org/10.3390/app8081390 (registering DOI)
Received: 14 June 2018 / Revised: 10 August 2018 / Accepted: 14 August 2018 / Published: 17 August 2018
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Abstract
Adiabatic compressed air energy storage (A-CAES) is an effective balancing technique for the integration of renewables and peak-shaving due to the large capacity, high efficiency, and low carbon use. Increasing the inlet air temperature of turbine and reducing the compressor power consumption are
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Adiabatic compressed air energy storage (A-CAES) is an effective balancing technique for the integration of renewables and peak-shaving due to the large capacity, high efficiency, and low carbon use. Increasing the inlet air temperature of turbine and reducing the compressor power consumption are essential to improving the efficiency of A-CAES. This paper proposes a novel solar–thermal-assisted A-CAES system (ST-CAES), which features a higher inhale temperature of the turbine to improve the system efficiency. Solar–thermal energy, as an external thermal source, can alleviate the inadequate temperature of the thermal energy storage (TES), which is constrained by the temperature of the exhaust air of the compressor. Energy and exergy analyses were performed to identify ST-CAES performance, and the influence of key parameters on efficiency were studied. Furthermore, exergy efficiency and the destruction ratio of each component of ST-CAES were investigated. The results demonstrate that electricity storage efficiency, round-trip efficiency, and exergy efficiency can reach 70.2%, 61%, and 50%, respectively. Therefore, the proposed system has promising prospects in cities with abundant solar resources owing to its high efficiency and the ability to jointly supply multiple energy needs. Full article
(This article belongs to the Special Issue Smart Grid and Smart Cities Activities)
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Open AccessArticle Polyadic Cantor Fractal Ultrasonic Lenses: Design and Characterization
Appl. Sci. 2018, 8(8), 1389; https://doi.org/10.3390/app8081389 (registering DOI)
Received: 5 July 2018 / Revised: 9 August 2018 / Accepted: 15 August 2018 / Published: 17 August 2018
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Abstract
Traditional acoustic lenses modulate the ultrasonic beam due to their curved surfaces and the refractive material of which they are made. In this work, a different type of acoustic lens, based on Polyadic Cantor Fractals (PCF), is presented and thoroughly analyzed. These new
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Traditional acoustic lenses modulate the ultrasonic beam due to their curved surfaces and the refractive material of which they are made. In this work, a different type of acoustic lens, based on Polyadic Cantor Fractals (PCF), is presented and thoroughly analyzed. These new Polyadic Cantor Fractal Lenses (PCFLs) are completely flat and easy to build, and they present interesting modulation capabilities over the acoustic profile. The dependence of the focusing profile on the PCFL design parameters is fully characterized, and it is shown that certain design parameters provide a dynamic control, which is critical in many medical applications such as thermal ablation of tumors. Full article
(This article belongs to the Section Acoustics)
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Open AccessFeature PaperReview Photoelectrochemical Device Designs toward Practical Solar Water Splitting: A Review on the Recent Progress of BiVO4 and BiFeO3 Photoanodes
Appl. Sci. 2018, 8(8), 1388; https://doi.org/10.3390/app8081388 (registering DOI)
Received: 26 July 2018 / Revised: 11 August 2018 / Accepted: 13 August 2018 / Published: 17 August 2018
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Abstract
Solar-driven water splitting technology is considered to be a promising solution for the global energy challenge as it is capable of generating clean chemical fuel from solar energy. Various strategies and catalytic materials have been explored in order to improve the efficiency of
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Solar-driven water splitting technology is considered to be a promising solution for the global energy challenge as it is capable of generating clean chemical fuel from solar energy. Various strategies and catalytic materials have been explored in order to improve the efficiency of the water splitting reaction. Although significant progress has been made, there are many intriguing fundamental phenomena that need to be understood. Herein, we review recent experimental efforts to demonstrate enhancement strategies for efficient solar water splitting, especially for the light absorption, charge carrier separation, and water oxidation kinetics. We also focus on the state of the art of photoelectrochemical (PEC) device designs such as application of facet engineering and the development of a ferroelectric-coupled PEC device. Based on these experimental achievements, future challenges, and directions in solar water splitting technology will be discussed. Full article
(This article belongs to the Special Issue Nanomaterials for Solar Water Splitting)
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Open AccessArticle A Study on Stability Control of Grid Connected DC Distribution System Based on Second Order Generalized Integrator-Frequency Locked Loop (SOGI-FLL)
Appl. Sci. 2018, 8(8), 1387; https://doi.org/10.3390/app8081387
Received: 21 July 2018 / Revised: 13 August 2018 / Accepted: 13 August 2018 / Published: 16 August 2018
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Abstract
This paper studies a second order generalized integrator-frequency locked loop (SOGI-FLL) control scheme applicable for 3-phase alternating current/direct current (AC/DC) pulse width modulation (PWM) converters used in DC distribution systems. The 3-phase AC/DC PWM converter is the most important power conversion system of
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This paper studies a second order generalized integrator-frequency locked loop (SOGI-FLL) control scheme applicable for 3-phase alternating current/direct current (AC/DC) pulse width modulation (PWM) converters used in DC distribution systems. The 3-phase AC/DC PWM converter is the most important power conversion system of DC distribution, since it can boost 380 Vrms 3-phase line-to-line AC voltage to 700 Vdc DC output with various DC load devices and grid voltages. The direct-quadrature (d-q) transformation, positive sequence voltage extraction, proportional integral (PI) voltage/current control, and phase locked loop (PLL) are necessary to control the 3-phase AC/DC PWM converter. Besides, a digital filter, such as low pass filter and all pass filter, are essential in the conventional synchronous reference frame-phase locked loop (SRF-PLL) method to eliminate the low order harmonics of input. However, they limit the bandwidth of the controller, which directly affects the output voltage and load of 3-phase AC/DC PWM converter when sever voltage fluctuation, such as sag, swell, etc. occurred in the grid. On the other hand, the proposed control method using SOGI-FLL is able to do phase angle detection, positive sequence voltage extraction, and harmonic filtering without additional digital filters, so that more stable and fast transient control is achieved in the DC distribution system. To verify the improvement of the characteristics in the unbalanced voltage and frequency fluctuation of the grid, a simulation and experiment are implemented with 50 kW 3-phase AC/DC PWM converter used in DC distribution. Full article
(This article belongs to the Special Issue HVDC for Grid Services in Electric Power Systems)
Open AccessArticle Influence of Graphene Nanoplatelet and Silver Nanoparticle on the Rheological Properties of Water-Based Mud
Appl. Sci. 2018, 8(8), 1386; https://doi.org/10.3390/app8081386
Received: 20 July 2018 / Revised: 10 August 2018 / Accepted: 13 August 2018 / Published: 16 August 2018
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Abstract
Water-based mud is known as an environmental-friendly drilling fluid system. The formulation of water-based mud is designed to have specific rheological properties under specific oil field conditions. In this study, graphene nanoplatelet and silver nanoparticle (nanosilver) were added to a water-based mud formulation
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Water-based mud is known as an environmental-friendly drilling fluid system. The formulation of water-based mud is designed to have specific rheological properties under specific oil field conditions. In this study, graphene nanoplatelet and silver nanoparticle (nanosilver) were added to a water-based mud formulation in which they act as drilling mud additives. Rheological properties measurements and filtration tests were conducted for evaluating the influence of the added nanoparticles. The results showed that the graphene nanoplatelet and the nanosilver increased the plastic viscosity (PV) by up to 89.2% and 64.2%, respectively. Meanwhile, both the yield point (YP) and the fluid loss values were reduced. In addition, we believe this is the first result ever report where nanosilver is utilized for enhancing-enhanced water-based mud’s performance. Full article
(This article belongs to the Special Issue Nanotech for Oil and Gas)
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Open AccessArticle Highly Reliable and Efficient Three-Layer Cloud Dispatching Architecture in the Heterogeneous Cloud Computing Environment
Appl. Sci. 2018, 8(8), 1385; https://doi.org/10.3390/app8081385
Received: 21 July 2018 / Revised: 7 August 2018 / Accepted: 13 August 2018 / Published: 16 August 2018
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Abstract
Due to the rapid development and popularity of the Internet, cloud computing has become an indispensable application service. However, how to assign various tasks to the appropriate service nodes is an important issue. Based on the reason above, an efficient scheduling algorithm is
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Due to the rapid development and popularity of the Internet, cloud computing has become an indispensable application service. However, how to assign various tasks to the appropriate service nodes is an important issue. Based on the reason above, an efficient scheduling algorithm is necessary to enhance the performance of the system. Therefore, a Three-Layer Cloud Dispatching (TLCD) architecture is proposed to enhance the performance of task scheduling. In the first layer, the tasks need to be distinguished into different types by their characters. Subsequently, the Cluster Selection Algorithm is proposed to dispatch the tasks to appropriate service clusters in the second layer. Besides this, a new scheduling algorithm is proposed in the third layer to dispatch the task to a suitable server in a server cluster to enhance the scheduling efficiency. Basically, the best task completion time can be obtained in our TLCD architecture. Furthermore, load balancing and reliability can be achieved under a cloud computing network environment. Full article
(This article belongs to the Special Issue Selected Papers from IEEE ICASI 2018)
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Open AccessReview Electricity Generation in LCA of Electric Vehicles: A Review
Appl. Sci. 2018, 8(8), 1384; https://doi.org/10.3390/app8081384 (registering DOI)
Received: 25 July 2018 / Revised: 10 August 2018 / Accepted: 13 August 2018 / Published: 16 August 2018
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Abstract
Life Cycle assessments (LCAs) on electric mobility are providing a plethora of diverging results. 44 articles, published from 2008 to 2018 have been investigated in this review, in order to find the extent and the reason behind this deviation. The first hurdle can
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Life Cycle assessments (LCAs) on electric mobility are providing a plethora of diverging results. 44 articles, published from 2008 to 2018 have been investigated in this review, in order to find the extent and the reason behind this deviation. The first hurdle can be found in the goal definition, followed by the modelling choice, as both are generally incomplete and inconsistent. These gaps influence the choices made in the Life Cycle Inventory (LCI) stage, particularly in regards to the selection of the electricity mix. A statistical regression is made with results available in the literature. It emerges that, despite the wide-ranging scopes and the numerous variables present in the assessments, the electricity mix’s carbon intensity can explain 70% of the variability of the results. This encourages a shared framework to drive practitioners in the execution of the assessment and policy makers in the interpretation of the results. Full article
(This article belongs to the Special Issue Plug-in Hybrid Electric Vehicle (PHEV))
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Open AccessArticle A Robust Cover Song Identification System with Two-Level Similarity Fusion and Post-Processing
Appl. Sci. 2018, 8(8), 1383; https://doi.org/10.3390/app8081383 (registering DOI)
Received: 23 July 2018 / Revised: 13 August 2018 / Accepted: 14 August 2018 / Published: 16 August 2018
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Abstract
Similarity measurement plays an important role in various information retrieval tasks. In this paper, a music information retrieval scheme based on two-level similarity fusion and post-processing is proposed. At the similarity fusion level, to take full advantage of the common and complementary properties
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Similarity measurement plays an important role in various information retrieval tasks. In this paper, a music information retrieval scheme based on two-level similarity fusion and post-processing is proposed. At the similarity fusion level, to take full advantage of the common and complementary properties among different descriptors and different similarity functions, first, the track-by-track similarity graphs generated from the same descriptor but different similarity functions are fused with the similarity network fusion (SNF) technique. Then, the obtained first-level fused similarities based on different descriptors are further fused with the mixture Markov model (MMM) technique. At the post-processing level, diffusion is first performed on the two-level fused similarity graph to utilize the underlying track manifold contained within it. Then, a mutual proximity (MP) algorithm is adopted to refine the diffused similarity scores, which helps to reduce the bad influence caused by the “hubness” phenomenon contained in the scores. The performance of the proposed scheme is tested in the cover song identification (CSI) task on three cover song datasets (Covers80, Covers40, and Second Hand Songs (SHS)). The experimental results demonstrate that the proposed scheme outperforms state-of-the-art CSI schemes based on single similarity or similarity fusion. Full article
(This article belongs to the Special Issue Digital Audio and Image Processing with Focus on Music Research)
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Open AccessArticle Effectiveness of Distributed vs. Concentrated Volt/Var Local Control Strategies in Low-Voltage Grids
Appl. Sci. 2018, 8(8), 1382; https://doi.org/10.3390/app8081382
Received: 28 June 2018 / Revised: 10 August 2018 / Accepted: 13 August 2018 / Published: 16 August 2018
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Abstract
This paper introduces a novel local Volt/var control strategy in a low-voltage smart grid. Nowadays, various Volt/var local control strategies built on customer photovoltaic inverters, e.g., cosφ(P) and Q(U), are introduced to mitigate the upper voltage limit
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This paper introduces a novel local Volt/var control strategy in a low-voltage smart grid. Nowadays, various Volt/var local control strategies built on customer photovoltaic inverters, e.g., cosφ(P) and Q(U), are introduced to mitigate the upper voltage limit violations in feeders with high prosumer share. Nevertheless, although these strategies are further refined by including more local variables, their use is still very limited. In this study, the effects of a new concentrated Volt/var local control strategy in low-voltage grids are investigated. Concentrated var-sinks, e.g., coils-L(U), are set at the end of each violated feeder. The concentrated local control strategy L(U) is compared with the distributed cosφ(P) and Q(U) strategies. Initially, both control strategies are theoretically investigated, followed by simulations in a test feeder. Finally, the expected practical significance of the findings is verified through simulations in a real typical urban and rural grid. Additionally, the impact of the different local control strategies used in low-voltage grids on the behavior of the medium-voltage grid is analyzed. The results show that the concentrated Volt/var control strategy eliminates the violation of upper voltage limit even in longer feeders, where both distributed local strategies fail. In addition, the concentrated L(U) local control causes less reactive power exchange on the distribution transformer level than the distributed cosφ(P) and Q(U) strategies. Therefore, the reactive power exchange with the medium-voltage grid and thus the distribution transformer loading are smaller in the case of concentrated local control strategy. Full article
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Open AccessArticle Influence of a New Form of Bolted Connection on the Mechanical Behaviors of a PC Shear Wall
Appl. Sci. 2018, 8(8), 1381; https://doi.org/10.3390/app8081381
Received: 5 July 2018 / Revised: 2 August 2018 / Accepted: 13 August 2018 / Published: 16 August 2018
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Abstract
A variety of forms of connection in precast reinforced concrete (PC) have been proposed, but the impact of the connection forms on the shear wall remains to be studied. In this paper, through quasi-static experiments and numerical simulations, the influences of a new
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A variety of forms of connection in precast reinforced concrete (PC) have been proposed, but the impact of the connection forms on the shear wall remains to be studied. In this paper, through quasi-static experiments and numerical simulations, the influences of a new form of bolted connection on the mechanical behaviors of the PC shear wall are investigated. The results show that the strain of the connector is less than the yield strain and the failure does not occur in the connector; the mechanical behaviors of this connection form of the PC shear wall are equivalent to those of the cast-in-place reinforced concrete (RC) shear wall. Meanwhile, reasonable suggestions are put forward for the design of the connector from the pretightening force, bolt number, and axial compression ratio. This implies that this form of bolted connection has little influence on the mechanical behaviors of the PC shear wall and design suggestions can be used in practical projects. Full article
(This article belongs to the Special Issue Emerging Construction Materials and Sustainable Infrastructure)
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Open AccessArticle Gait Energy Response Functions for Gait Recognition against Various Clothing and Carrying Status
Appl. Sci. 2018, 8(8), 1380; https://doi.org/10.3390/app8081380
Received: 24 July 2018 / Revised: 4 August 2018 / Accepted: 13 August 2018 / Published: 16 August 2018
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Abstract
Silhouette-based gait representations are widely used in the current gait recognition community due to their effectiveness and efficiency, but they are subject to changes in covariate conditions such as clothing and carrying status. Therefore, we propose a gait energy response function (GERF) that
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Silhouette-based gait representations are widely used in the current gait recognition community due to their effectiveness and efficiency, but they are subject to changes in covariate conditions such as clothing and carrying status. Therefore, we propose a gait energy response function (GERF) that transforms a gait energy (i.e., an intensity value) of a silhouette-based gait feature into a value more suitable for handling these covariate conditions. Additionally, since the discrimination capability of gait energies, as well as the degree to which they are affected by the covariate conditions, differs among body parts, we extend the GERF framework to spatially dependent GERF (SD-GERF) which accounts for spatial dependence. Moreover, the proposed GERFs are represented as a vector in the transformation lookup table and are optimized through an efficient generalized eigenvalue problem in a closed form. Finally, two post-processing techniques, Gabor filtering and spatial metric learning, are employed for the transformed gait features to boost the accuracy. Experimental results with three publicly available datasets including clothing and carrying status variations show the state-of-the-art performance of the proposed method compared with other state-of-the-art methods. Full article
(This article belongs to the Section Computer Science and Electrical Engineering)
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Open AccessArticle A Review of Ghost Imaging via Sparsity Constraints
Appl. Sci. 2018, 8(8), 1379; https://doi.org/10.3390/app8081379
Received: 20 June 2018 / Revised: 23 July 2018 / Accepted: 27 July 2018 / Published: 16 August 2018
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Abstract
Different from conventional imaging methods, which are based on the first-order field correlation, ghost imaging (GI) obtains the image information through high-order mutual-correlation of light fields from two paths with an object appearing in only one path. As a new optical imaging technology,
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Different from conventional imaging methods, which are based on the first-order field correlation, ghost imaging (GI) obtains the image information through high-order mutual-correlation of light fields from two paths with an object appearing in only one path. As a new optical imaging technology, GI not only provides us new capabilities beyond the conventional imaging methods, but also gives out a new viewpoint of imaging physical mechanism. It may be applied to many potential applications, such as remote sensing, snap-shot spectral imaging, thermal X-ray diffraction imaging and imaging through scattering media. In this paper, we reviewed mainly our research work of ghost imaging via sparsity constraints (GISC) and discussed the application and theory prospect of GISC concisely. Full article
(This article belongs to the Special Issue Ghost Imaging)
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Open AccessArticle Magneto-Optical Kerr Effect Driven by Spin Accumulation on Cu, Au, and Pt
Appl. Sci. 2018, 8(8), 1378; https://doi.org/10.3390/app8081378
Received: 18 July 2018 / Revised: 9 August 2018 / Accepted: 13 August 2018 / Published: 15 August 2018
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Abstract
The magneto-optical Kerr effect (MOKE) has recently been achieved on non-ferromagnetic metals by injecting spin currents. To use the magneto-optical Kerr effect as a quantitative tool, it is crucial to study the relationship between the Kerr rotation angle and the spin accumulation on
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The magneto-optical Kerr effect (MOKE) has recently been achieved on non-ferromagnetic metals by injecting spin currents. To use the magneto-optical Kerr effect as a quantitative tool, it is crucial to study the relationship between the Kerr rotation angle and the spin accumulation on non-ferromagnets. In this work, I measure a transient magneto-optical Kerr rotation on non-ferromagnetic metals of Cu, Au, and Pt driven by an ultrafast spin current from an adjacent ferromagnetic metal. Through comparing the measured Kerr rotation and the calculated spin accumulation, I determine the conversion ratio between the Kerr rotation and the spin accumulation to be: −4 × 10−9 (real part), −2.5 × 10−8 (real part), and −3 × 10−9 (imaginary part) rad m A−1 for Cu, Au, and Pt, respectively, at a wavelength of 784 nm. Full article
(This article belongs to the Special Issue Optics in Spintronic Materials)
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Open AccessArticle Engineering Properties of Controlled Low-Strength Materials Containing Bottom Ash of Municipal Solid Waste Incinerator and Water Filter Silt
Appl. Sci. 2018, 8(8), 1377; https://doi.org/10.3390/app8081377
Received: 26 July 2018 / Revised: 8 August 2018 / Accepted: 13 August 2018 / Published: 15 August 2018
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Abstract
The bottom ash of a municipal solid waste incinerator (MSWI) and water filter silt (WFS) were applied to a controlled low-strength material (CLSM) in the present study. The CLSM of the control group was composed of cement, water, and fine aggregates. WFS was
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The bottom ash of a municipal solid waste incinerator (MSWI) and water filter silt (WFS) were applied to a controlled low-strength material (CLSM) in the present study. The CLSM of the control group was composed of cement, water, and fine aggregates. WFS was first used as a fill material to replace 10% of the volume of natural fine aggregates in the CLSM. MSWI bottom ash was used to replace 0%, 25%, 50%, 75%, and 100% of the volume of the remaining natural fine aggregates with a water-cement ratio of 1.6. The engineering properties of freshness, hardening, and durability were examined. The results revealed that the slump flows of all of the mixture proportions ranged between 50 and 70 cm. The tube flow ranged between 20 and 30 cm, conforming to ASTM D6103 and construction regulations regarding CLSMs stipulated by the Water Resources Agency of the Ministry of Economic Affairs in Taiwan. Increases in the replacement amount of MSWI bottom ash prolonged the time required to achieve a resistance to penetration of 2.74 MPa. The diameter of the drop test ball was less than 7.6 cm, indicating that the mixture proportions had sufficient bearing capacity for successive construction. At an age of 28 d, the compressive strength did not exceed the 8.4 MPa prescribed in ASTM D4832. The ultrasonic pulse velocity and water absorption exhibited identical growth tendencies. In summary, using MSWI bottom ash to create CLSMs is feasible on the condition that the appropriate amount of WFS should be added. Full article
(This article belongs to the Section Materials)
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Open AccessReview Interface Engineering Strategies for Fabricating Nanocrystal-Based Organic–Inorganic Nanocomposites
Appl. Sci. 2018, 8(8), 1376; https://doi.org/10.3390/app8081376
Received: 9 July 2018 / Revised: 7 August 2018 / Accepted: 13 August 2018 / Published: 15 August 2018
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Abstract
Hybrid organic–inorganic nanocomposites have attracted considerable attention because they have the advantages of both conjugated polymers (CPs) and nanocrystals (NCs). Recent developments in the interfacial engineering of CP–NC organic–inorganic nanocomposites enabled the formation of an intimate contact between NCs and CPs, facilitating electronic
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Hybrid organic–inorganic nanocomposites have attracted considerable attention because they have the advantages of both conjugated polymers (CPs) and nanocrystals (NCs). Recent developments in the interfacial engineering of CP–NC organic–inorganic nanocomposites enabled the formation of an intimate contact between NCs and CPs, facilitating electronic interactions between these two constituents. To design CP–NC nanocomposites, several approaches have been introduced, including ligand refluxing, direct grafting methods, direct growth of NCs in proximity to CPs, and template-guided strategies. In this review, the general reactions of ligand exchange processes, purification methods, and characterization techniques have been briefly introduced. This is followed by a highlight of recent advances in the synthesis of hybrid CP–NC nanocomposites and newly developed inorganic surface treatments, as well as their applications. An outlook for future directions in this area is also presented. Full article
(This article belongs to the Section Nanotechnology and Applied Nanosciences)
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Open AccessReview Mg-Based Hydrogen Absorbing Materials for Thermal Energy Storage—A Review
Appl. Sci. 2018, 8(8), 1375; https://doi.org/10.3390/app8081375
Received: 24 July 2018 / Revised: 8 August 2018 / Accepted: 9 August 2018 / Published: 15 August 2018
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Abstract
Utilization of renewable energy such as solar, wind, and geothermal power, appears to be the most promising solution for the development of sustainable energy systems without using fossil fuels. Energy storage, especially to store the energy from fluctuating power is quite vital for
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Utilization of renewable energy such as solar, wind, and geothermal power, appears to be the most promising solution for the development of sustainable energy systems without using fossil fuels. Energy storage, especially to store the energy from fluctuating power is quite vital for smoothing out energy demands with peak/off-peak hour fluctuations. Thermal energy is a potential candidate to serve as an energy reserve. However, currently the development of thermal energy storage (TES) by traditional physical means is restricted by the relatively low energy density, high temperature demand, and the great thermal energy loss during long-period storage. Chemical heat storage is one of the most promising alternatives for TES due to its high energy density, low energy loss, flexible temperature range, and excellent storage duration. A comprehensive review on the development of different types of Mg-based materials for chemical heat storage is presented here and the classic and state-of-the-art technologies are summarized. Some related chemical principles, as well as heat storage properties, are discussed in the context. Finally, some dominant factors of chemical heat storage materials are concluded and the perspective is proposed for the development of next-generation chemical heat storage technologies. Full article
(This article belongs to the Special Issue Materials for Thermal Energy Storage)
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Open AccessArticle Experimental Analysis of Pore and Permeability Characteristics of Coal by Low-Field NMR
Appl. Sci. 2018, 8(8), 1374; https://doi.org/10.3390/app8081374
Received: 21 July 2018 / Revised: 8 August 2018 / Accepted: 10 August 2018 / Published: 15 August 2018
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Abstract
On the basis of the complexity of the pore structure characteristics of a coal reservoir, coal samples with different ranks were selected to study the difference in pore structures and permeability using nuclear magnetic resonance (NMR), scanning electron microscopy (SEM), mercury intrusion porosimetry
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On the basis of the complexity of the pore structure characteristics of a coal reservoir, coal samples with different ranks were selected to study the difference in pore structures and permeability using nuclear magnetic resonance (NMR), scanning electron microscopy (SEM), mercury intrusion porosimetry (MIP), and permeability measurement. Porosity and pore size distribution (PSD) above 20 nm can be analyzed by the improved NMR equation, and the results were basically consistent with that of SEM and MIP. The NMR spectra of the coal samples from the same location were close, but the difference between the coal samples from different locations was quite large, which indicated that the heterogeneity of a coal reservoir was strong. An empirical equation of movable fluid porosity was proposed, which can be used to evaluate the fluid migration characteristics of the coal reservoir, and the porosity of movable fluid mainly came from the contribution of fissures and micro-fissures. The average movable fluid porosity of the coal samples from the Chengzhuang (CZ) coal mine, Wuyang (WY) coal mine, and Yujialiang (YJL) coal mine was 1.37%, 0.67%, and 4.26%, respectively. Although the permeability is related to the NMR porosity and movable fluid porosity, it was difficult to establish a widely used mathematical equation correlating permeability and porosity based on the experimental data. Full article
(This article belongs to the Special Issue Nanotech for Oil and Gas)
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Open AccessArticle Research on Residual Life Prediction for Electrical Connectors Based on Intermittent Failure and Hidden Semi-Markov Model
Appl. Sci. 2018, 8(8), 1373; https://doi.org/10.3390/app8081373
Received: 15 July 2018 / Revised: 11 August 2018 / Accepted: 13 August 2018 / Published: 15 August 2018
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Abstract
Based on the dynamic properties of electrical connector intermittent failure, the model and methods for residual life prediction for electrical connectors are studied in this paper. Firstly, the mechanism of electrical connector intermittent failure is analyzed, and the area enclosed by the contact
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Based on the dynamic properties of electrical connector intermittent failure, the model and methods for residual life prediction for electrical connectors are studied in this paper. Firstly, the mechanism of electrical connector intermittent failure is analyzed, and the area enclosed by the contact resistance curve and the fault threshold is defined as the generalized severity of intermittent failure to describe how severe the electrical connector’s intermittent failure is. Then, the Hidden Semi-Markov Model (HSMM) is introduced to build the residual life prediction model of the electrical connector. Further, the evaluation method of using the state and prediction method for residual life are studied. Finally, by carrying out the residual life prediction test, the effectiveness of the residual life prediction method for electrical connectors based on intermittent failure and HSMM is verified. Full article
(This article belongs to the Section Mechanical Engineering)
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Open AccessArticle Feature Selection and Transfer Learning for Alzheimer’s Disease Clinical Diagnosis
Appl. Sci. 2018, 8(8), 1372; https://doi.org/10.3390/app8081372
Received: 25 July 2018 / Revised: 10 August 2018 / Accepted: 11 August 2018 / Published: 15 August 2018
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Abstract
Background and Purpose: A majority studies on diagnosis of Alzheimer’s Disease (AD) are based on an assumption: the training and testing data are drawn from the same distribution. However, in the diagnosis of AD and mild cognitive impairment (MCI), this identical-distribution assumption may
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Background and Purpose: A majority studies on diagnosis of Alzheimer’s Disease (AD) are based on an assumption: the training and testing data are drawn from the same distribution. However, in the diagnosis of AD and mild cognitive impairment (MCI), this identical-distribution assumption may not hold. To solve this problem, we utilize the transfer learning method into the diagnosis of AD. Methods: The MR (Magnetic Resonance) images were segmented using spm-Dartel toolbox and registrated with Automatic Anatomical Labeling (AAL) atlas, then the gray matter (GM) tissue volume of the anatomical region were computed as characteristic parameter. The information gain was introduced for feature selection. The TrAdaboost algorithm was used to classify AD, MCI, and normal controls (NC) data from Alzheimer’s Disease Neuroimaging Initiative (ADNI) database, meanwhile, the “knowledge” learned from ADNI was transferred to AD samples from local hospital. The classification accuracy, sensitivity and specificity were calculated and compared with four classical algorithms. Results: In the experiment of transfer task: AD to MCI, 177 AD and 40NC subjects were grouped as training data; 245 MCI and 45 remaining NC subjects were combined as testing data, the highest accuracy achieved 85.4%, higher than the other four classical algorithms. Meanwhile, feature selection that is based on information gain reduced the features from 90 to 7, controlled the redundancy efficiently. In the experiment of transfer task: ADNI to local hospital data, the highest accuracy achieved 93.7%, and the specificity achieved 100%. Conclusions: The experimental results showed that our algorithm has a clear advantage over classic classification methods with higher accuracy and less fluctuation. Full article
(This article belongs to the Section Applied Biosciences and Bioengineering)
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Open AccessEditorial Special Issue on Socio-Cognitive and Affective Computing
Appl. Sci. 2018, 8(8), 1371; https://doi.org/10.3390/app8081371
Received: 2 August 2018 / Accepted: 14 August 2018 / Published: 15 August 2018
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Abstract
Social cognition focuses on how people process, store, and apply information about other people and social situations. [...] Full article
(This article belongs to the Special Issue Socio-Cognitive and Affective Computing)
Open AccessArticle A Stackelberg Game Approach for Price Response Coordination of Thermostatically Controlled Loads
Appl. Sci. 2018, 8(8), 1370; https://doi.org/10.3390/app8081370
Received: 27 May 2018 / Revised: 26 July 2018 / Accepted: 1 August 2018 / Published: 15 August 2018
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Abstract
In this paper, we study the demand response of the thermostatically controlled loads (TCLs) to control their set-point temperatures by considering the tradeoff between the electricity payment and TCL user’s comfort preference. Based upon the dynamics of the TCLs, we set up the
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In this paper, we study the demand response of the thermostatically controlled loads (TCLs) to control their set-point temperatures by considering the tradeoff between the electricity payment and TCL user’s comfort preference. Based upon the dynamics of the TCLs, we set up the relationship between the set-point temperature and the energy demand. Then, we define a discomfort function with respect to the associated energy demand which represents the discomfort level of the set-point temperature. More specifically, the system is equipped with a coordinator named electric energy control center (EECC) which can buy energy resources from the electricity market and sell them to TCL users. Due to the interaction between EECC and TCL users, we formulate the specific energy trading process as a one-leader multiple-follower Stackelberg game. As the main contributions of this work, we show the existence and uniqueness of the equilibrium for the underlying Stackelberg games, and develop a DR algorithm based on the so-called Backward Induction to achieve the equilibrium. Several numerical simulations are presented to verify the developed results in this work. Full article
(This article belongs to the Special Issue Smart Home and Energy Management Systems)
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Open AccessArticle Spatial Modelling of Gully Erosion Using GIS and R Programing: A Comparison among Three Data Mining Algorithms
Appl. Sci. 2018, 8(8), 1369; https://doi.org/10.3390/app8081369
Received: 13 July 2018 / Revised: 10 August 2018 / Accepted: 10 August 2018 / Published: 14 August 2018
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Abstract
Gully erosion triggers land degradation and restricts the use of land. This study assesses the spatial relationship between gully erosion (GE) and geo-environmental variables (GEVs) using Weights-of-Evidence (WoE) Bayes theory, and then applies three data mining methods—Random Forest (RF), boosted regression tree (BRT),
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Gully erosion triggers land degradation and restricts the use of land. This study assesses the spatial relationship between gully erosion (GE) and geo-environmental variables (GEVs) using Weights-of-Evidence (WoE) Bayes theory, and then applies three data mining methods—Random Forest (RF), boosted regression tree (BRT), and multivariate adaptive regression spline (MARS)—for gully erosion susceptibility mapping (GESM) in the Shahroud watershed, Iran. Gully locations were identified by extensive field surveys, and a total of 172 GE locations were mapped. Twelve gully-related GEVs: Elevation, slope degree, slope aspect, plan curvature, convergence index, topographic wetness index (TWI), lithology, land use/land cover (LU/LC), distance from rivers, distance from roads, drainage density, and NDVI were selected to model GE. The results of variables importance by RF and BRT models indicated that distance from road, elevation, and lithology had the highest effect on GE occurrence. The area under the curve (AUC) and seed cell area index (SCAI) methods were used to validate the three GE maps. The results showed that AUC for the three models varies from 0.911 to 0.927, whereas the RF model had a prediction accuracy of 0.927 as per SCAI values, when compared to the other models. The findings will be of help for planning and developing the studied region. Full article
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