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Appl. Sci., Volume 6, Issue 6 (June 2016) – 25 articles

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Open AccessArticle
Maize Seed Variety Classification Using the Integration of Spectral and Image Features Combined with Feature Transformation Based on Hyperspectral Imaging
Appl. Sci. 2016, 6(6), 183; https://doi.org/10.3390/app6060183 - 21 Jun 2016
Cited by 21 | Viewed by 2806
Abstract
Hyperspectral imaging (HSI) technology has been extensively studied in the classification of seed variety. A novel procedure for the classification of maize seed varieties based on HSI was proposed in this study. The optimal wavelengths for the classification of maize seed varieties were [...] Read more.
Hyperspectral imaging (HSI) technology has been extensively studied in the classification of seed variety. A novel procedure for the classification of maize seed varieties based on HSI was proposed in this study. The optimal wavelengths for the classification of maize seed varieties were selected using the successive projections algorithm (SPA) to improve the acquiring and processing speed of HSI. Subsequently, spectral and imaging features were extracted from regions of interest of the hyperspectral images. Principle component analysis and multidimensional scaling were then introduced to transform/reduce the classification features for overcoming the risk of dimension disaster caused by the use of a large number of features. Finally, the integrating features were used to develop a least squares–support vector machines (LS–SVM) model. The LS–SVM model, using the integration of spectral and image features combined with feature transformation methods, achieved more than 90% of test accuracy, which was better than the 83.68% obtained by model using the original spectral and image features, and much higher than the 76.18% obtained by the model only using the spectral features. This procedure provides a possible way to apply the multispectral imaging system to classify seed varieties with high accuracy. Full article
(This article belongs to the Special Issue Applications of Hyperspectral Imaging for Food and Agriculture)
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Open AccessArticle
RBF-Based Monocular Vision Navigation for Small Vehicles in Narrow Space below Maize Canopy
Appl. Sci. 2016, 6(6), 182; https://doi.org/10.3390/app6060182 - 21 Jun 2016
Cited by 7 | Viewed by 2045
Abstract
Maize is one of the major food crops in China. Traditionally, field operations are done by manual labor, where the farmers are threatened by the harsh environment and pesticides. On the other hand, it is difficult for large machinery to maneuver in the [...] Read more.
Maize is one of the major food crops in China. Traditionally, field operations are done by manual labor, where the farmers are threatened by the harsh environment and pesticides. On the other hand, it is difficult for large machinery to maneuver in the field due to limited space, particularly in the middle and late growth stage of maize. Unmanned, compact agricultural machines, therefore, are ideal for such field work. This paper describes a method of monocular visual recognition to navigate small vehicles between narrow crop rows. Edge detection and noise elimination were used for image segmentation to extract the stalks in the image. The stalk coordinates define passable boundaries, and a simplified radial basis function (RBF)-based algorithm was adapted for path planning to improve the fault tolerance of stalk coordinate extraction. The average image processing time, including network latency, is 220 ms. The average time consumption for path planning is 30 ms. The fast processing ensures a top speed of 2 m/s for our prototype vehicle. When operating at the normal speed (0.7 m/s), the rate of collision with stalks is under 6.4%. Additional simulations and field tests further proved the feasibility and fault tolerance of our method. Full article
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Open AccessArticle
Output Properties of Transparent Submount Packaged FlipChip Light-Emitting Diode Modules
Appl. Sci. 2016, 6(6), 179; https://doi.org/10.3390/app6060179 - 20 Jun 2016
Cited by 2 | Viewed by 2314
Abstract
Flip chip technology has been widely adopted in modern power light-emitting diode (LED) fabrications and its output efficiency is closely related to the submount material properties. Here, we present the electrical, optical and thermal properties of flip chip light-emitting diodes mounted on transparent [...] Read more.
Flip chip technology has been widely adopted in modern power light-emitting diode (LED) fabrications and its output efficiency is closely related to the submount material properties. Here, we present the electrical, optical and thermal properties of flip chip light-emitting diodes mounted on transparent sapphire and borosilicate glass which have shown a higher output luminous flux when compared to the traditional non-transparent mounted LEDs. Exhibiting both better thermal conductivity and good optical transparency, flip chip LEDs with a sapphire submount showed superior performance when compared to the non-transparent silicon submount ones, and also showed better optical performance than the flip chip LEDs mounted on transparent but poor-thermal-conducting glass substrates. The correspondent analysis was carried out using ANSYS 14 to compare the experimental thermal imaging with the simulation results. TracePro software was also used to check the output luminous flux dependency on different LED mounting designs. Full article
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Open AccessArticle
Evaluation of Saponin Extract from Vitex doniana and Pentaclethra macrophylla for Antibacterial Activity
Appl. Sci. 2016, 6(6), 180; https://doi.org/10.3390/app6060180 - 17 Jun 2016
Viewed by 2167
Abstract
Saponins are pharmacologically active compounds that have been shown to ameliorate abnormal physiological processes and be aptly applied in folklore for the treatment of maladies occasioned by infectious agents. Consequently, saponins from Vitex doniana and Pentaclethra macrophylla were evaluated for antibacterial properties, as [...] Read more.
Saponins are pharmacologically active compounds that have been shown to ameliorate abnormal physiological processes and be aptly applied in folklore for the treatment of maladies occasioned by infectious agents. Consequently, saponins from Vitex doniana and Pentaclethra macrophylla were evaluated for antibacterial properties, as these herbs are used in folk medicine. Dried pulverized plant materials were defatted, and solvents with varying polarity were applied at varying ratios for the extraction of saponins. Phyto-chemistry was in accordance with standard methods, while an antibacterial assay was made through the agar well diffusion and micro broth dilution techniques. Phytochemical quantitation showed high concentrations of tannins, 231 ± 0.6 CE/g, and saponins, 58% from V. doniana. Similarly, P. macrophylla stem bark extract also showed high concentrations of tannins, 309 ± 2.42 CE/g, alkaloids, 71% ± 0.5%, and saponins, 87% ± 3.4%. The ethanol extracts of V. doniana inhibited the growth of Staphylococcus aureus (ATCC 11775) and a clinical strain with inhibition zone ranges of 15.5 ± 2.12 to 7.0 ± 0.0 (mm) against leaf extracts and 20.0 ± 1.41 to 7.0 ± 0.0 (mm) against stem bark extracts. Conversely, saponin extract from V. doniana showed a broad spectrum of activity, as it inhibited both Gram-negative and -positive test strains, E. coli clinical strain (20.0 ± 1.41 mm), P. aeruginosa clinical strain (18.5 ± 0.71 mm), E. coli ATCC 11775 (17.0 ± 0 mm), and S. aureus clinical strain (13.0 ± 1.41 mm). However, a broad spectrum was similarly achieved with P. macrophylla extracts, as all test bacteria genus was susceptible. Saponin fractions showed a high potency and broad spectrum antibacterial activity and thus a validation of the folklore applications and the potential for use as a drug or drug scaffold. Full article
(This article belongs to the Section Chemistry)
Open AccessArticle
The Feasibility of Modified Magnesia-Phosphate Cement as a Heat Resistant Adhesive for Strengthening Concrete with Carbon Sheets
Appl. Sci. 2016, 6(6), 178; https://doi.org/10.3390/app6060178 - 17 Jun 2016
Cited by 4 | Viewed by 2021
Abstract
External bonding of carbon fiber sheets has become a popular technique for strengthening concrete structures all over the world. Epoxy adhesive, which is used to bond the carbon fiber sheets and concrete, deteriorates rapidly when being exposed to high temperatures. This paper presents [...] Read more.
External bonding of carbon fiber sheets has become a popular technique for strengthening concrete structures all over the world. Epoxy adhesive, which is used to bond the carbon fiber sheets and concrete, deteriorates rapidly when being exposed to high temperatures. This paper presents a high-temperature-resistant modified magnesia-phosphate cement (MPC) with the compressive strength that does not decrease at the temperature of 600 °C. The bond properties of both the modified MPC and the epoxy adhesive between externally bonded carbon fiber sheets and concrete were evaluated by using a double-shear test method after exposure to elevating temperatures from 105 °C to 500 °C. The results showed that the bond strength of the modified MPC at room temperature (RT) is much higher than that of the epoxy resin. Full carbonation with almost 0 MPa was detected for the epoxy sample after the exposure to 300 °C, while only 40% reduction of bond strength was tested for the modified MPC sample. Although the modified MPC specimens failed through interlaminar slip of fiber strips instead of complete debonding, the MPC specimens performed higher bond strength than epoxy resin at ambient temperature, and retained much higher bond strength at elevated temperatures. It could be concluded that it is feasible to strengthen concrete structural members with externally bonded carbon fiber sheets using the modified MPC instead of epoxy adhesive. Furthermore, the use of the modified MPC as the binder between carbon fiber sheets and concrete can be less expensive and an ecologically friendly alternative. Full article
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Open AccessArticle
The Spotting Distribution of Wildfires
Appl. Sci. 2016, 6(6), 177; https://doi.org/10.3390/app6060177 - 17 Jun 2016
Cited by 15 | Viewed by 2756
Abstract
In wildfire science, spotting refers to non-local creation of new fires, due to downwind ignition of brands launched from a primary fire. Spotting is often mentioned as being one of the most difficult problems for wildfire management, because of its unpredictable nature. Since [...] Read more.
In wildfire science, spotting refers to non-local creation of new fires, due to downwind ignition of brands launched from a primary fire. Spotting is often mentioned as being one of the most difficult problems for wildfire management, because of its unpredictable nature. Since spotting is a stochastic process, it makes sense to talk about a probability distribution for spotting, which we call the spotting distribution. Given a location ahead of the fire front, we would like to know how likely is it to observe a spot fire at that location in the next few minutes. The aim of this paper is to introduce a detailed procedure to find the spotting distribution. Most prior modelling has focused on the maximum spotting distance, or on physical subprocesses. We will use mathematical modelling, which is based on detailed physical processes, to derive a spotting distribution. We discuss the use and measurement of this spotting distribution in fire spread, fire management and fire breaching. The appendix of this paper contains a comprehensive review of the relevant underlying physical sub-processes of fire plumes, launching fire brands, wind transport, falling and terminal velocity, combustion during transport, and ignition upon landing. Full article
(This article belongs to the Special Issue Dynamical Models of Biology and Medicine) Printed Edition available
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Open AccessArticle
Formal Security-Proved Mobile Anonymous Authentication Protocols with Credit-Based Chargeability and Controllable Privacy
Appl. Sci. 2016, 6(6), 176; https://doi.org/10.3390/app6060176 - 17 Jun 2016
Viewed by 2007
Abstract
Smart mobile phones are widely popularized and advanced mobile communication services are provided increasingly often, such that ubiquitous computing environments will soon be a reality. However, there are many security threats to mobile networks and their impact on security is more serious than [...] Read more.
Smart mobile phones are widely popularized and advanced mobile communication services are provided increasingly often, such that ubiquitous computing environments will soon be a reality. However, there are many security threats to mobile networks and their impact on security is more serious than that in wireline networks owing to the features of wireless transmissions and the ubiquity property. The secret information which mobile users carry may be stolen by malicious entities. To guarantee the quality of advanced services, security and privacy would be important issues when users roam within various mobile networks. In this manuscript, an anonymous authentication scheme will be proposed to protect the security of the network system and the privacy of users. Not only does the proposed scheme provide mutual authentication between each user and the system, but also each user’s identity is kept secret against anyone else, including the system. Although the system anonymously authenticates the users, it can still generate correct bills to charge these anonymous users via a credit-based solution instead of debit-based ones. Furthermore, our protocols also achieve fair privacy which allows the judge to revoke the anonymity and trace the illegal users when they have misused the anonymity property, for example, if they have committed crimes. Finally, in this paper, we also carry out complete theoretical proofs on each claimed security property. Full article
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Open AccessArticle
Network Modeling and Assessment of Ecosystem Health by a Multi-Population Swarm Optimized Neural Network Ensemble
Appl. Sci. 2016, 6(6), 175; https://doi.org/10.3390/app6060175 - 15 Jun 2016
Cited by 4 | Viewed by 2192
Abstract
Society is more and more interested in developing mathematical models to assess and forecast the environmental and biological health conditions of our planet. However, most existing models cannot determine the long-range impacts of potential policies without considering the complex global factors and their [...] Read more.
Society is more and more interested in developing mathematical models to assess and forecast the environmental and biological health conditions of our planet. However, most existing models cannot determine the long-range impacts of potential policies without considering the complex global factors and their cross effects in biological systems. In this paper, the Markov property and Neural Network Ensemble (NNE) are utilized to construct an estimated matrix that combines the interaction of the different local factors. With such an estimation matrix, we could obtain estimated variables that could reflect the global influence. The ensemble weights are trained by multiple population algorithms. Our prediction could fit the real trend of the two predicted measures, namely Morbidity Rate and Gross Domestic Product (GDP). It could be an effective method of reflecting the relationship between input factors and predicted measures of the health of ecosystems. The method can perform a sensitivity analysis, which could help determine the critical factors that could be adjusted to move the ecosystem in a sustainable direction. Full article
(This article belongs to the Special Issue Applied Artificial Neural Network) Printed Edition available
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Open AccessArticle
2D Gaze Estimation Based on Pupil-Glint Vector Using an Artificial Neural Network
Appl. Sci. 2016, 6(6), 174; https://doi.org/10.3390/app6060174 - 14 Jun 2016
Cited by 9 | Viewed by 3132
Abstract
Gaze estimation methods play an important role in a gaze tracking system. A novel 2D gaze estimation method based on the pupil-glint vector is proposed in this paper. First, the circular ring rays location (CRRL) method and Gaussian fitting are utilized for pupil [...] Read more.
Gaze estimation methods play an important role in a gaze tracking system. A novel 2D gaze estimation method based on the pupil-glint vector is proposed in this paper. First, the circular ring rays location (CRRL) method and Gaussian fitting are utilized for pupil and glint detection, respectively. Then the pupil-glint vector is calculated through subtraction of pupil and glint center fitting. Second, a mapping function is established according to the corresponding relationship between pupil-glint vectors and actual gaze calibration points. In order to solve the mapping function, an improved artificial neural network (DLSR-ANN) based on direct least squares regression is proposed. When the mapping function is determined, gaze estimation can be actualized through calculating gaze point coordinates. Finally, error compensation is implemented to further enhance accuracy of gaze estimation. The proposed method can achieve a corresponding accuracy of 1.29°, 0.89°, 0.52°, and 0.39° when a model with four, six, nine, or 16 calibration markers is utilized for calibration, respectively. Considering error compensation, gaze estimation accuracy can reach 0.36°. The experimental results show that gaze estimation accuracy of the proposed method in this paper is better than that of linear regression (direct least squares regression) and nonlinear regression (generic artificial neural network). The proposed method contributes to enhancing the total accuracy of a gaze tracking system. Full article
(This article belongs to the Special Issue Applied Artificial Neural Network) Printed Edition available
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Open AccessArticle
On Site Investigation and Health Monitoring of a Historic Tower in Mantua, Italy
Appl. Sci. 2016, 6(6), 173; https://doi.org/10.3390/app6060173 - 08 Jun 2016
Cited by 8 | Viewed by 1994
Abstract
The paper describes the strategy adopted to assess the structural condition of the tallest historic tower in Mantua (Italy) after the Italian seismic sequence of May–June 2012 and exemplifies the application of health monitoring using (automated) operational modal analysis. The post-earthquake survey (including [...] Read more.
The paper describes the strategy adopted to assess the structural condition of the tallest historic tower in Mantua (Italy) after the Italian seismic sequence of May–June 2012 and exemplifies the application of health monitoring using (automated) operational modal analysis. The post-earthquake survey (including extensive visual inspection, historic and documentary research, non-destructive (ND) material testing, and ambient vibration tests) highlighted the poor state of preservation of the upper part of the tower; subsequently, a dynamic monitoring system (consisting of a few accelerometers and one temperature sensor) was installed in the building to address the preservation of the historic structure, and automated modal identification was continuously performed. Despite the low levels of vibration that existed in operational conditions, the analysis of data collected over a period of about 15 months allowed to assess and model the effects of changing temperature on modal frequencies and to detect the occurrence of abnormal behavior and damage under the changing environment. The monitoring results demonstrate the potential key role of vibration-based structural health monitoring, implemented through low-cost hardware solutions and appropriate software tools, in the preventive conservation and the condition-based maintenance of historic towers. Full article
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Open AccessArticle
Surface Roughness Analysis in the Hard Milling of JIS SKD61 Alloy Steel
Appl. Sci. 2016, 6(6), 172; https://doi.org/10.3390/app6060172 - 08 Jun 2016
Cited by 19 | Viewed by 2557
Abstract
Hard machining is an efficient solution that can be used to replace the grinding operation in the mold and die manufacturing industry. In this study, an attempt is made to analyze the effect of process parameters on workpiece surface roughness (Ra) [...] Read more.
Hard machining is an efficient solution that can be used to replace the grinding operation in the mold and die manufacturing industry. In this study, an attempt is made to analyze the effect of process parameters on workpiece surface roughness (Ra) in the hard milling of JIS (Japanese Industrial Standard) SKD61 steel, based on a combination of the Taguchi method and response surface methodology (RSM). The cutting parameters are selected based on the structural dynamic analysis of the machine tool. A set of experiments is designed according to the Taguchi technique. The average Ra is measured by a Mitutoyo Surftest SJ-400, and then analysis of variance (ANOVA) is performed to determine the influences of cutting parameters on the given Ra. Quadratic mathematical modeling is introduced for prediction of the Ra during the hard milling process. The predicted values are in reasonable agreement with the observation of experiments. In an effort to obtain the minimizing Ra, a single objective optimization is employed based on the desirability function. The result shows that the percentage error between measured and predicted values of Ra is 3.2%, which is found to be insignificant. Eventually, the milled surface roughness under the optimized machining conditions is 0.122 µm. This finding shows that grinding may be replaced by finish hard milling in the mold and die manufacturing field. Full article
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Open AccessArticle
Optimizing Extraction of Cellulose and Synthesizing Pharmaceutical Grade Carboxymethyl Sago Cellulose from Malaysian Sago Pulp
Appl. Sci. 2016, 6(6), 170; https://doi.org/10.3390/app6060170 - 08 Jun 2016
Cited by 11 | Viewed by 2654
Abstract
Sago biomass is an agro-industrial waste produced in large quantities, mainly in the Asia-Pacific region and in particular South-East Asia. This work focuses on using sago biomass to obtain cellulose as the raw material, through chemical processing using acid hydrolysis, alkaline extraction, chlorination [...] Read more.
Sago biomass is an agro-industrial waste produced in large quantities, mainly in the Asia-Pacific region and in particular South-East Asia. This work focuses on using sago biomass to obtain cellulose as the raw material, through chemical processing using acid hydrolysis, alkaline extraction, chlorination and bleaching, finally converting the material to pharmaceutical grade carboxymethyl sago cellulose (CMSC) by carboxymethylation. The cellulose was evaluated using Thermogravimetric Analysis (TGA), Infrared Spectroscopy (FTIR), X-Ray Diffraction (XRD), Differential Scanning Calorimetry (DSC) and Field Emission Scanning Electronic Microscopy (FESEM). The extracted cellulose was analyzed for cellulose composition, and subsequently modified to CMSC with a degree of substitution (DS) 0.6 by typical carboxymethylation reactions. X-ray diffraction analysis indicated that the crystallinity of the sago cellulose was reduced after carboxymethylation. FTIR and NMR studies indicate that the hydroxyl groups of the cellulose fibers were etherified through carboxymethylation to produce CMSC. Further characterization of the cellulose and CMSC were performed using FESEM and DSC. The purity of CMSC was analyzed according to the American Society for Testing and Materials (ASTM) International standards. In this case, acid and alkaline treatments coupled with high-pressure defibrillation were found to be effective in depolymerization and defibrillation of the cellulose fibers. The synthesized CMSC also shows no toxicity in the cell line studies and could be exploited as a pharmaceutical excipient. Full article
(This article belongs to the Section Materials)
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Open AccessArticle
Health Condition Evaluation for a Shearer through the Integration of a Fuzzy Neural Network and Improved Particle Swarm Optimization Algorithm
Appl. Sci. 2016, 6(6), 171; https://doi.org/10.3390/app6060171 - 07 Jun 2016
Cited by 7 | Viewed by 2112
Abstract
In order to accurately evaluate the health condition of a shearer, a hybrid prediction method was proposed based on the integration of a fuzzy neural network (FNN) and improved particle swarm optimization (IPSO). The parameters of FNN were optimized by the use of [...] Read more.
In order to accurately evaluate the health condition of a shearer, a hybrid prediction method was proposed based on the integration of a fuzzy neural network (FNN) and improved particle swarm optimization (IPSO). The parameters of FNN were optimized by the use of PSO, which was coupled with a premature judgment and mutation mechanism to increase the convergence speed and enhance the generalization ability. The key technologies are elaborated and the flowchart of the proposed approach was designed. Furthermore, an experiment example was carried out and the comparison results indicated that the proposed approach was feasible and outperforms others. Finally, a field application example in coal mining face was demonstrated to specify the effect of the proposed system. Full article
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Open AccessArticle
Dual-Tree Complex Wavelet Transform and Twin Support Vector Machine for Pathological Brain Detection
Appl. Sci. 2016, 6(6), 169; https://doi.org/10.3390/app6060169 - 03 Jun 2016
Cited by 78 | Viewed by 3263
Abstract
(Aim) Classification of brain images as pathological or healthy case is a key pre-clinical step for potential patients. Manual classification is irreproducible and unreliable. In this study, we aim to develop an automatic classification system of brain images in magnetic resonance [...] Read more.
(Aim) Classification of brain images as pathological or healthy case is a key pre-clinical step for potential patients. Manual classification is irreproducible and unreliable. In this study, we aim to develop an automatic classification system of brain images in magnetic resonance imaging (MRI). (Method) Three datasets were downloaded from the Internet. Those images are of T2-weighted along axial plane with size of 256 × 256. We utilized an s-level decomposition on the basis of dual-tree complex wavelet transform (DTCWT), in order to obtain 12s “variance and entropy (VE)” features from each subband. Afterwards, we used support vector machine (SVM) and its two variants: the generalized eigenvalue proximal SVM (GEPSVM) and the twin SVM (TSVM), as the classifiers. In all, we proposed three novel approaches: DTCWT + VE + SVM, DTCWT + VE + GEPSVM, and DTCWT + VE + TSVM. (Results) The results showed that our “DTCWT + VE + TSVM” obtained an average accuracy of 99.57%, which was not only better than the two other proposed methods, but also superior to 12 state-of-the-art approaches. In addition, parameter estimation showed the classification accuracy achieved the largest when the decomposition level s was assigned with a value of 1. Further, we used 100 slices from real subjects, and we found our proposed method was superior to human reports from neuroradiologists. (Conclusions) This proposed system is effective and feasible. Full article
(This article belongs to the Special Issue Applied Artificial Neural Network) Printed Edition available
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Open AccessArticle
The Influence of Effective Microorganisms on Microbes and Nutrients in Kiwifruit Planting Soil
Appl. Sci. 2016, 6(6), 168; https://doi.org/10.3390/app6060168 - 02 Jun 2016
Cited by 3 | Viewed by 1723
Abstract
To understand the effects of effective microorganisms (EMs) containing multiple strains on microbes and nutrients in kiwifruit planting soil, EMs prepared with four different strains were added to kiwifruit planting soil monthly from April to August. The counts of bacteria, fungi, actinomycetes, and [...] Read more.
To understand the effects of effective microorganisms (EMs) containing multiple strains on microbes and nutrients in kiwifruit planting soil, EMs prepared with four different strains were added to kiwifruit planting soil monthly from April to August. The counts of bacteria, fungi, actinomycetes, and total microbes were determined. The pH, total nitrogen (TN), alkali-hydrolyzable nitrogen (A-N), organic matter (OM), available potassium (A-K), and available phosphorus (A-P) of the soil were measured. Results indicated that the counts of bacteria, fungi, actinomycetes, and total microbes reached 60.33 × 105, 4.00 × 105, 0.92 × 105, and 65.25 × 105 CFU/g, respectively, in August, all of which were higher than those of the control group (CK). The bacterial count of the experimental group (EG) was higher than that of the CK in August. The pH-values of the EG were always lower than those of the CK. In August, the TN content of the EG was 1.52 g/kg, which was higher than that of the CK (1.35 g/kg). A significant negative association between the actinomycetes count and TN (p < 0.05) was found. For A-N and OM, the content of the EG (A-N, 125.18 mg/kg; OM, 49.84 mg/kg) was roughly the same as that of the CK (A-N, 112.51 mg/kg; OM, 53.11 mg/kg) in August. However, the A-K and A-P contents of the EG (A-K, 145.25 mg/kg; A-P, 111.25 mg/kg) were lower than those of the CK (A-K, 182.52 mg/kg; A-P, 202.19 mg/kg) in August. Results show that application of EMs in kiwifruit planting soil can increase the counts of soil microbes and might promote the absorption of major nutrients for kiwifruit tree. Full article
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Open AccessArticle
Analytical Solution for Interference Fit for Multi-Layer Thick-Walled Cylinders and the Application in Crankshaft Bearing Design
Appl. Sci. 2016, 6(6), 167; https://doi.org/10.3390/app6060167 - 02 Jun 2016
Cited by 10 | Viewed by 3280
Abstract
Interference fit is an important contact mode used for torque transmission existing widely in engineering design. To prevent trackslip, a certain magnitude of interference has to be ensured; meanwhile, the interference needs to be controlled to avoid failure of the mechanical components caused [...] Read more.
Interference fit is an important contact mode used for torque transmission existing widely in engineering design. To prevent trackslip, a certain magnitude of interference has to be ensured; meanwhile, the interference needs to be controlled to avoid failure of the mechanical components caused by high assembly stress. The finite element method (FEM) can be used to analyze the stress, while the computational cost of FEM involving nonlinear contact algorithm is relatively high, and likely to come across low precision and convergence problems. Therefore, a rapid and accurate analytical method for estimation is of vital need, especially for the initial design stage when the parameters vary in a large range. In this study, an analytical method to calculate the contact pressure and stress between multi-layer thick-walled cylinders (MLTWC) with multi-contact pairs and temperature-raising effect is proposed, and evaluated by FEM. The analytical solution of the interference for tri-layer thick-walled cylinders is applied to the design of engine crankshaft bearing. The results indicate that the analytical method presented in this study can reduce complexity of MLTWC problems and improve the computational efficiency. It is well suited to be used for the calculation model of parameter optimization in early design. Full article
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Open AccessArticle
Determination of Optimal Initial Weights of an Artificial Neural Network by Using the Harmony Search Algorithm: Application to Breakwater Armor Stones
Appl. Sci. 2016, 6(6), 164; https://doi.org/10.3390/app6060164 - 31 May 2016
Cited by 27 | Viewed by 3175
Abstract
In this study, an artificial neural network (ANN) model is developed to predict the stability number of breakwater armor stones based on the experimental data reported by Van der Meer in 1988. The harmony search (HS) algorithm is used to determine the near-global [...] Read more.
In this study, an artificial neural network (ANN) model is developed to predict the stability number of breakwater armor stones based on the experimental data reported by Van der Meer in 1988. The harmony search (HS) algorithm is used to determine the near-global optimal initial weights in the training of the model. The stratified sampling is used to sample the training data. A total of 25 HS-ANN hybrid models are tested with different combinations of HS algorithm parameters. The HS-ANN models are compared with the conventional ANN model, which uses a Monte Carlo simulation to determine the initial weights. Each model is run 50 times and the statistical analyses are conducted for the model results. The present models using stratified sampling are shown to be more accurate than those of previous studies. The statistical analyses for the model results show that the HS-ANN model with proper values of HS algorithm parameters can give much better and more stable prediction than the conventional ANN model. Full article
(This article belongs to the Special Issue Applied Artificial Neural Network) Printed Edition available
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Open AccessReview
Review of the Remaining Useful Life Prognostics of Vehicle Lithium-Ion Batteries Using Data-Driven Methodologies
Appl. Sci. 2016, 6(6), 166; https://doi.org/10.3390/app6060166 - 27 May 2016
Cited by 47 | Viewed by 3364
Abstract
Lithium-ion batteries are the primary power source in electric vehicles, and the prognosis of their remaining useful life is vital for ensuring the safety, stability, and long lifetime of electric vehicles. Accurately establishing a mechanism model of a vehicle lithium-ion battery involves a [...] Read more.
Lithium-ion batteries are the primary power source in electric vehicles, and the prognosis of their remaining useful life is vital for ensuring the safety, stability, and long lifetime of electric vehicles. Accurately establishing a mechanism model of a vehicle lithium-ion battery involves a complex electrochemical process. Remaining useful life (RUL) prognostics based on data-driven methods has become a focus of research. Current research on data-driven methodologies is summarized in this paper. By analyzing the problems of vehicle lithium-ion batteries in practical applications, the problems that need to be solved in the future are identified. Full article
(This article belongs to the Special Issue Advancing Grid-Connected Renewable Generation Systems)
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Open AccessArticle
Building an Interoperability Test System for Electric Vehicle Chargers Based on ISO/IEC 15118 and IEC 61850 Standards
Appl. Sci. 2016, 6(6), 165; https://doi.org/10.3390/app6060165 - 26 May 2016
Cited by 4 | Viewed by 3387
Abstract
The electric vehicle market is rapidly growing due to its environmental friendliness and governmental support. As electric vehicles are powered by electricity, the interoperability between the vehicles and the chargers made by multiple vendors is crucial for the success of the technology. Relevant [...] Read more.
The electric vehicle market is rapidly growing due to its environmental friendliness and governmental support. As electric vehicles are powered by electricity, the interoperability between the vehicles and the chargers made by multiple vendors is crucial for the success of the technology. Relevant standards are being published, but the methods for conformance testing need to be developed. In this paper, we present our conformance test system for the electric vehicle charger in accordance with the standards ISO/IEC 15118, IEC 61851 and IEC 61850-90-8. Our test system leverages the TTCN-3 framework for its flexibility and productivity. We evaluate the test system by lab tests with two reference chargers that we built. We also present the test results in two international testival events for the ISO/IEC 15118 interoperability. We confirmed that our test system is robust, efficient and practical. Full article
(This article belongs to the Special Issue Smart Grid: Convergence and Interoperability)
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Open AccessArticle
Isolation, Identification, and Biotransformation of Teadenol A from Solid State Fermentation of Pu-erh Tea and In Vitro Antioxidant Activity
Appl. Sci. 2016, 6(6), 161; https://doi.org/10.3390/app6060161 - 26 May 2016
Cited by 6 | Viewed by 2246
Abstract
Post-fermented Pu-erh tea (PFPT) has several health benefits, however, little is known about the bioactive compounds. In this study, a PFPT compound was isolated by column chromatography and identified as Teadenol A by spectroscopic data analyses, including mass spectrometry and 1D and 2D [...] Read more.
Post-fermented Pu-erh tea (PFPT) has several health benefits, however, little is known about the bioactive compounds. In this study, a PFPT compound was isolated by column chromatography and identified as Teadenol A by spectroscopic data analyses, including mass spectrometry and 1D and 2D NMR spectroscopy. Teadenol A in tea leaves was biotransformed by Aspergillus niger and A. tamari at 28 °C for 14 d at concentrations ranging from 9.85 ± 1.17 to 12.93 ± 0.38 mg/g. Additionally, the compound was detected in 22 commercial PFPTs at concentrations ranging from 0.17 ± 0.1 to 8.15 ± 0.1 mg/g. Teadenol A promoted the secretion of adiponectin and inhibited the expression of protein tyrosine phosphatase-1B. Antioxidant assays (e.g., 1,1-diphenyl-2-picrylhydrazyl (DPPH) scavenging activity, total antioxidant capacity (T-AOC), hydrogen donating ability, and superoxide anion radical scavenging capacity) revealed that Teadenol A has antioxidant properties. Therefore, Teadenol A is an important bio-active component of PFPT. Full article
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Open AccessArticle
Opto-Acoustic Method for the Characterization of Thin-Film Adhesion
Appl. Sci. 2016, 6(6), 163; https://doi.org/10.3390/app6060163 - 25 May 2016
Cited by 1 | Viewed by 1683
Abstract
The elastic property of the film-substrate interface of thin-film systems is characterized with an opto-acoustic method. The thin-film specimens are oscillated with an acoustic transducer at audible frequencies, and the resultant harmonic response of the film surface is analyzed with optical interferometry. Polystyrene, [...] Read more.
The elastic property of the film-substrate interface of thin-film systems is characterized with an opto-acoustic method. The thin-film specimens are oscillated with an acoustic transducer at audible frequencies, and the resultant harmonic response of the film surface is analyzed with optical interferometry. Polystyrene, Ti, Ti-Au and Ti-Pt films coated on the same silicon substrate are tested. For each film material, a pair of specimens is prepared; one is coated on a silicon substrate after the surface is treated with plasma bombardment, and the other is coated on an identical silicon substrate without a treatment. Experiments indicate that both the surface-treated and untreated specimens of all film materials have resonance in the audible frequency range tested. The elastic constant of the interface corresponding to the observed resonance is found to be orders of magnitude lower than that of the film or substrate material. Observations of these resonance-like behaviors and the associated stiffness of the interface are discussed. Full article
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Open AccessArticle
Metrics for Polyphonic Sound Event Detection
Appl. Sci. 2016, 6(6), 162; https://doi.org/10.3390/app6060162 - 25 May 2016
Cited by 136 | Viewed by 4727
Abstract
This paper presents and discusses various metrics proposed for evaluation of polyphonic sound event detection systems used in realistic situations where there are typically multiple sound sources active simultaneously. The system output in this case contains overlapping events, marked as multiple sounds detected [...] Read more.
This paper presents and discusses various metrics proposed for evaluation of polyphonic sound event detection systems used in realistic situations where there are typically multiple sound sources active simultaneously. The system output in this case contains overlapping events, marked as multiple sounds detected as being active at the same time. The polyphonic system output requires a suitable procedure for evaluation against a reference. Metrics from neighboring fields such as speech recognition and speaker diarization can be used, but they need to be partially redefined to deal with the overlapping events. We present a review of the most common metrics in the field and the way they are adapted and interpreted in the polyphonic case. We discuss segment-based and event-based definitions of each metric and explain the consequences of instance-based and class-based averaging using a case study. In parallel, we provide a toolbox containing implementations of presented metrics. Full article
(This article belongs to the Special Issue Audio Signal Processing) Printed Edition available
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Open AccessArticle
Improving Multi-Instance Multi-Label Learning by Extreme Learning Machine
Appl. Sci. 2016, 6(6), 160; https://doi.org/10.3390/app6060160 - 24 May 2016
Cited by 4 | Viewed by 2026
Abstract
Multi-instance multi-label learning is a learning framework, where every object is represented by a bag of instances and associated with multiple labels simultaneously. The existing degeneration strategy-based methods often suffer from some common drawbacks: (1) the user-specific parameter for the number of clusters [...] Read more.
Multi-instance multi-label learning is a learning framework, where every object is represented by a bag of instances and associated with multiple labels simultaneously. The existing degeneration strategy-based methods often suffer from some common drawbacks: (1) the user-specific parameter for the number of clusters may incur the effective problem; (2) SVM may bring a high computational cost when utilized as the classifier builder. In this paper, we propose an algorithm, namely multi-instance multi-label (MIML)-extreme learning machine (ELM), to address the problems. To our best knowledge, we are the first to utilize ELM in the MIML problem and to conduct the comparison of ELM and SVM on MIML. Extensive experiments have been conducted on real datasets and synthetic datasets. The results show that MIMLELM tends to achieve better generalization performance at a higher learning speed. Full article
(This article belongs to the Special Issue Applied Artificial Neural Network) Printed Edition available
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Open AccessArticle
Styrene-Based Copolymer for Polymer Membrane Modifications
Appl. Sci. 2016, 6(6), 159; https://doi.org/10.3390/app6060159 - 24 May 2016
Cited by 3 | Viewed by 2651
Abstract
Poly(vinylidene fluoride) (PVDF) was modified with a styrene-based copolymer. The crystalline behavior, phase, thermal stability, and surface morphology of the modified membranes were analyzed. The membrane surface roughness showed a strong dependence on the styrene-acrylonitrile content and was reduced to 34% for a [...] Read more.
Poly(vinylidene fluoride) (PVDF) was modified with a styrene-based copolymer. The crystalline behavior, phase, thermal stability, and surface morphology of the modified membranes were analyzed. The membrane surface roughness showed a strong dependence on the styrene-acrylonitrile content and was reduced to 34% for a PVDF/styrene-acrylonitrile blend membrane with a 40/60 ratio. The thermal and crystalline behavior confirmed the blend miscibility of both polymers. It was observed in X-ray diffraction (XRD) experiments that the modified PVDF membranes show a drastic reduction in their crystallinity. The neat PVDF membrane has the highest degradation rate, which decreased with the addition of the styrene-based copolymer. Full article
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Open AccessArticle
A Fast Reactive Power Optimization in Distribution Network Based on Large Random Matrix Theory and Data Analysis
Appl. Sci. 2016, 6(6), 158; https://doi.org/10.3390/app6060158 - 24 May 2016
Cited by 4 | Viewed by 2469
Abstract
In this paper, a reactive power optimization method based on historical data is investigated to solve the dynamic reactive power optimization problem in distribution network. In order to reflect the variation of loads, network loads are represented in a form of random matrix. [...] Read more.
In this paper, a reactive power optimization method based on historical data is investigated to solve the dynamic reactive power optimization problem in distribution network. In order to reflect the variation of loads, network loads are represented in a form of random matrix. Load similarity (LS) is defined to measure the degree of similarity between the loads in different days and the calculation method of the load similarity of load random matrix (LRM) is presented. By calculating the load similarity between the forecasting random matrix and the random matrix of historical load, the historical reactive power optimization dispatching scheme that most matches the forecasting load can be found for reactive power control usage. The differences of daily load curves between working days and weekends in different seasons are considered in the proposed method. The proposed method is tested on a standard 14 nodes distribution network with three different types of load. The computational result demonstrates that the proposed method for reactive power optimization is fast, feasible and effective in distribution network. Full article
(This article belongs to the Special Issue Selected Papers from the 2015 International Conference on Inventions)
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