A new improved algorithm of histogram equalization was discussed and actualized by analyzing the traditional algorithm. This improved algorithm has better effect than the traditional one, especially it is used to proc...A new improved algorithm of histogram equalization was discussed and actualized by analyzing the traditional algorithm. This improved algorithm has better effect than the traditional one, especially it is used to process poor quality images.展开更多
Ultrasonic treatment and hydrothermal method were applied in the traditional homogeneous precipitation for nano-TiO_2 preparation, which was used as carrier material for the production of honeycomb selective catalytic...Ultrasonic treatment and hydrothermal method were applied in the traditional homogeneous precipitation for nano-TiO_2 preparation, which was used as carrier material for the production of honeycomb selective catalytic reduction(SCR) catalyst. The influence rules of the two improved methods on characterization of TiO_2 samples, denitration activity and mechanical strength of honeycomb SCR catalyst samples were mainly focused on. The results indicate that the specific surface area, particle size and uniformity of TiO_2 samples are significantly improved by both of the ultrasonic and hydrothermal treatments compared with the traditional homogeneous precipitation. Also, the denitration activities of catalyst samples are enhanced by the two improved methods(the NO_x reduction ratio increases from 88.89% to 95.45% by ultrasonic homogeneous precipitation process, and to 94.12% by hydrothermal homogeneous precipitation process). On the other hand, because of good spherical shape and high particle distribution of TiO_2 sample from hydrothermal homogeneous precipitation process, the corresponding honeycomb catalyst samples get the best mechanical strength, which is even higher than that of the reference sample from commercial nano-TiO_2. So, it is concluded that the hydrothermal homogeneous precipitation can be a feasible and effective preparation method of TiO_2 carrier for the honeycomb SCR catalyst production.展开更多
Because of cloud computing's high degree of polymerization calculation mode, it can't give full play to the resources of the edge device such as computing, storage, etc. Fog computing can improve the resource ...Because of cloud computing's high degree of polymerization calculation mode, it can't give full play to the resources of the edge device such as computing, storage, etc. Fog computing can improve the resource utilization efficiency of the edge device, and solve the problem about service computing of the delay-sensitive applications. This paper researches on the framework of the fog computing, and adopts Cloud Atomization Technology to turn physical nodes in different levels into virtual machine nodes. On this basis, this paper uses the graph partitioning theory to build the fog computing's load balancing algorithm based on dynamic graph partitioning. The simulation results show that the framework of the fog computing after Cloud Atomization can build the system network flexibly, and dynamic load balancing mechanism can effectively configure system resources as well as reducing the consumption of node migration brought by system changes.展开更多
Comparing with the homogeneous slope, the nonhomogeneous slope has more significance in practice. The main purpose of the present study is to provide a preliminary idea that how the nonhomogeneity influences the stabi...Comparing with the homogeneous slope, the nonhomogeneous slope has more significance in practice. The main purpose of the present study is to provide a preliminary idea that how the nonhomogeneity influences the stability of slopes under four different water drawdown regimes. Two typical categories of nonhomogeneity, identified as layered profile and strength increasing with depth profile, are included in the paper, and a nonhomogeneity coefficient is defined to quantify the degree of soil properties nonhomogeneity. With a modified discretization technique, the safety factors of nonhomogeneous slopes are calculated. On this basis, the variation of safety factor with the nonhomogeneity coefficient of friction angle and the water table level are investigated. In the present example, safety factor correlates linearly with friction angle nonhomogeneity coefficient from a whole view and the influences of the water table level on safety factor is basically similar with that in homogeneous condition.展开更多
Hybrid modeling approaches have recently been investigated as an attractive alternative to model fermentation processes. Normally, these approaches require estimation data to train the empirical model part of a hybrid...Hybrid modeling approaches have recently been investigated as an attractive alternative to model fermentation processes. Normally, these approaches require estimation data to train the empirical model part of a hybrid model. This may result in decreasing the generalization ability of the derived hybrid model. Therefore, a simultaneous hybrid modeling approach is presented in this paper. It transforms the training of the empirical model part into a dynamic system parameter identification problem, and thus allows training the empirical model part with only measured data. An adaptive escaping particle swarm optimization(AEPSO) algorithm with escaping and adaptive inertia weight adjustment strategies is constructed to solve the resulting parameter identification problem, and thereby accomplish the training of the empirical model part. The uniform design method is used to determine the empirical model structure. The proposed simultaneous hybrid modeling approach has been used in a lab-scale nosiheptide batch fermentation process. The results show that it is effective and leads to a more consistent model with better generalization ability when compared to existing ones. The performance of AEPSO is also demonstrated.展开更多
The mechanical behavior of geomaterials is studied using an XFEM (extended finite element method). Usually, the modeling of such heterogeneous material is performed either through an analytical homogenization approa...The mechanical behavior of geomaterials is studied using an XFEM (extended finite element method). Usually, the modeling of such heterogeneous material is performed either through an analytical homogenization approach, or numerically, especially for complex microstructures. For comparison, the effective properties are obtained using a classical finite element analysis (through the so-called unit cell method) and an analytical homogenization approach. The use of XFEM proposed here retains the accuracy oftbe classical finite element approach, allowing one to use meshes that do not necessarily match the physical boundaries of the material constituents. Thanks to such methods, it is then possible to study materials with complex microstructures that have non-simplified assumptions commonly used by other methods, as well as quantify the impact of such simplification. The versatility of XFEM in dealing with complex microstructures, including polycrystalline-like microstructures, is also shown through the role of shape inclusions on the overall effective properties o fan argillite rock. Voronoi representation is used to describe the complex microstructure of argillite.展开更多
Condition assessment is one of the most significant techniques of the equipment’s health management.Also,in PHM methodology cycle,which is a developed form of CBM,condition assessment is the most important step of th...Condition assessment is one of the most significant techniques of the equipment’s health management.Also,in PHM methodology cycle,which is a developed form of CBM,condition assessment is the most important step of this cycle.In this paper,the remaining useful life of the equipment is calculated using the combination of sensor information,determination of degradation state and forecasting the proposed health index.The combination of sensor information has been carried out using a new approach to determining the probabilities in the Dempster-Shafer combination rules and fuzzy c-means clustering method.Using the simulation and forecasting of extracted vibration-based health index by autoregressive Markov regime switching(ARMRS)method,final health state is determined and the remaining useful life(RUL)is estimated.In order to evaluate the model,sensor data provided by FEMTO-ST Institute have been used.展开更多
(2-acrylamido) ethyl tetradecyl dimethylammonium bromide (AMC14AB) was polymerized in aqueous solu- tion to form the homopolymer P(AMC14AB). The physicochemical properties of P(AMC14AB) in aqueous solution wer...(2-acrylamido) ethyl tetradecyl dimethylammonium bromide (AMC14AB) was polymerized in aqueous solu- tion to form the homopolymer P(AMC14AB). The physicochemical properties of P(AMC14AB) in aqueous solution were mainly studied with fluorescent probe method, surface tension measurement and conductom- etry. The experimental results show that the aggregation morphology of P(AMC14AB) in aqueous solution is unimolecular micelle as expected. Being different from conventional multimolecular micelle systems, the unimolecular micelle system of P(AMC14AB) not only shows critical micellar concentration (CMC=0), (i.e. once added to pure water, the surface tension decreases immediately in spite how small the density is), but also the surface tension stays almost the same with the concentration increasing. That is to say, there is no mutational point on the relationship curve between surface tension and concentration. Furthermore, the unimolecular micelle system of P(AMC14AB) has no Krafft temperature, i.e. at any temperature, so long as it is dissolved in water, the unimolecular micelles will form. Besides this, for the solubilization of hydrophobic organic substances, the unimolecular micelle system of P(AMC14AB) is obviously different from the common multimolecular micelle system, having no turning point on the relationship curve between toluene solubi- lizaion amount and P(AMC14AB) concentration, and the solubilizing ability of the unimolecular-micelle system of P(AMC14AB) for hydrophobic organic substances is much higher than that of the conventional multimolecular micelle solutions of common surfactants, such as centyl trimethyl ammonium bromide.展开更多
This paper proposes an algorithm that extracts features of back side of the vehicle and detects the front vehicle in real-time by local feature tracking of vehicle in the continuous images.The features in back side of...This paper proposes an algorithm that extracts features of back side of the vehicle and detects the front vehicle in real-time by local feature tracking of vehicle in the continuous images.The features in back side of the vehicle are vertical and horizontal edges,shadow and symmetry.By comparing local features using the fixed window size,the features in the continuous images are tracked.A robust and fast Haarlike mask is used for detecting vertical and horizontal edges,and shadow is extracted by histogram equalization,and the sliding window method is used to compare both side templates of the detected candidates for extracting symmetry.The features for tracking are vertical edges,and histogram is used to compare location of the peak and magnitude of the edges.The method using local feature tracking in the continuous images is more robust for detecting vehicle than the method using single image,and the proposed algorithm is evaluated by continuous images obtained on the expressway and downtown.And it can be performed on real-time through applying it to the embedded system.展开更多
Quantized kernel least mean square(QKLMS) algorithm is an effective nonlinear adaptive online learning algorithm with good performance in constraining the growth of network size through the use of quantization for inp...Quantized kernel least mean square(QKLMS) algorithm is an effective nonlinear adaptive online learning algorithm with good performance in constraining the growth of network size through the use of quantization for input space. It can serve as a powerful tool to perform complex computing for network service and application. With the purpose of compressing the input to further improve learning performance, this article proposes a novel QKLMS with entropy-guided learning, called EQ-KLMS. Under the consecutive square entropy learning framework, the basic idea of entropy-guided learning technique is to measure the uncertainty of the input vectors used for QKLMS, and delete those data with larger uncertainty, which are insignificant or easy to cause learning errors. Then, the dataset is compressed. Consequently, by using square entropy, the learning performance of proposed EQ-KLMS is improved with high precision and low computational cost. The proposed EQ-KLMS is validated using a weather-related dataset, and the results demonstrate the desirable performance of our scheme.展开更多
We study the quantum phase transition of ultracold atoms in the honeycomb optical lattice. The Hamiltonian of ultracold bosonic atoms in the honeycomb optical lattice is derived. We take the mean-field approximation a...We study the quantum phase transition of ultracold atoms in the honeycomb optical lattice. The Hamiltonian of ultracold bosonic atoms in the honeycomb optical lattice is derived. We take the mean-field approximation and further solve the Hamiltonian with the numerical diagonalization method. We obtain the phase diagram and find that the Mort-insulator (MI), density wave (DW) and modulated superfluid (MS) phases appear. Furthermore, the phase diagram is analyzed according to the order parameter and the average number of particles.展开更多
文摘A new improved algorithm of histogram equalization was discussed and actualized by analyzing the traditional algorithm. This improved algorithm has better effect than the traditional one, especially it is used to process poor quality images.
基金Project(201031)supported by the Environmental Protection Scientific Research of Jiangsu Province,ChinaProject(BE2010184)supported by the Technology Support Program of Jiangsu Province-Industrial Parts,China
文摘Ultrasonic treatment and hydrothermal method were applied in the traditional homogeneous precipitation for nano-TiO_2 preparation, which was used as carrier material for the production of honeycomb selective catalytic reduction(SCR) catalyst. The influence rules of the two improved methods on characterization of TiO_2 samples, denitration activity and mechanical strength of honeycomb SCR catalyst samples were mainly focused on. The results indicate that the specific surface area, particle size and uniformity of TiO_2 samples are significantly improved by both of the ultrasonic and hydrothermal treatments compared with the traditional homogeneous precipitation. Also, the denitration activities of catalyst samples are enhanced by the two improved methods(the NO_x reduction ratio increases from 88.89% to 95.45% by ultrasonic homogeneous precipitation process, and to 94.12% by hydrothermal homogeneous precipitation process). On the other hand, because of good spherical shape and high particle distribution of TiO_2 sample from hydrothermal homogeneous precipitation process, the corresponding honeycomb catalyst samples get the best mechanical strength, which is even higher than that of the reference sample from commercial nano-TiO_2. So, it is concluded that the hydrothermal homogeneous precipitation can be a feasible and effective preparation method of TiO_2 carrier for the honeycomb SCR catalyst production.
基金supported in part by the National Science and technology support program of P.R.China(No.2014BAH29F05)
文摘Because of cloud computing's high degree of polymerization calculation mode, it can't give full play to the resources of the edge device such as computing, storage, etc. Fog computing can improve the resource utilization efficiency of the edge device, and solve the problem about service computing of the delay-sensitive applications. This paper researches on the framework of the fog computing, and adopts Cloud Atomization Technology to turn physical nodes in different levels into virtual machine nodes. On this basis, this paper uses the graph partitioning theory to build the fog computing's load balancing algorithm based on dynamic graph partitioning. The simulation results show that the framework of the fog computing after Cloud Atomization can build the system network flexibly, and dynamic load balancing mechanism can effectively configure system resources as well as reducing the consumption of node migration brought by system changes.
基金Project(51408180)supported by the National Natural Science Foundation of China
文摘Comparing with the homogeneous slope, the nonhomogeneous slope has more significance in practice. The main purpose of the present study is to provide a preliminary idea that how the nonhomogeneity influences the stability of slopes under four different water drawdown regimes. Two typical categories of nonhomogeneity, identified as layered profile and strength increasing with depth profile, are included in the paper, and a nonhomogeneity coefficient is defined to quantify the degree of soil properties nonhomogeneity. With a modified discretization technique, the safety factors of nonhomogeneous slopes are calculated. On this basis, the variation of safety factor with the nonhomogeneity coefficient of friction angle and the water table level are investigated. In the present example, safety factor correlates linearly with friction angle nonhomogeneity coefficient from a whole view and the influences of the water table level on safety factor is basically similar with that in homogeneous condition.
基金Supported by the Specialized Research Fund for the Doctoral Program of Higher Education(No.20120042120014)
文摘Hybrid modeling approaches have recently been investigated as an attractive alternative to model fermentation processes. Normally, these approaches require estimation data to train the empirical model part of a hybrid model. This may result in decreasing the generalization ability of the derived hybrid model. Therefore, a simultaneous hybrid modeling approach is presented in this paper. It transforms the training of the empirical model part into a dynamic system parameter identification problem, and thus allows training the empirical model part with only measured data. An adaptive escaping particle swarm optimization(AEPSO) algorithm with escaping and adaptive inertia weight adjustment strategies is constructed to solve the resulting parameter identification problem, and thereby accomplish the training of the empirical model part. The uniform design method is used to determine the empirical model structure. The proposed simultaneous hybrid modeling approach has been used in a lab-scale nosiheptide batch fermentation process. The results show that it is effective and leads to a more consistent model with better generalization ability when compared to existing ones. The performance of AEPSO is also demonstrated.
文摘The mechanical behavior of geomaterials is studied using an XFEM (extended finite element method). Usually, the modeling of such heterogeneous material is performed either through an analytical homogenization approach, or numerically, especially for complex microstructures. For comparison, the effective properties are obtained using a classical finite element analysis (through the so-called unit cell method) and an analytical homogenization approach. The use of XFEM proposed here retains the accuracy oftbe classical finite element approach, allowing one to use meshes that do not necessarily match the physical boundaries of the material constituents. Thanks to such methods, it is then possible to study materials with complex microstructures that have non-simplified assumptions commonly used by other methods, as well as quantify the impact of such simplification. The versatility of XFEM in dealing with complex microstructures, including polycrystalline-like microstructures, is also shown through the role of shape inclusions on the overall effective properties o fan argillite rock. Voronoi representation is used to describe the complex microstructure of argillite.
文摘Condition assessment is one of the most significant techniques of the equipment’s health management.Also,in PHM methodology cycle,which is a developed form of CBM,condition assessment is the most important step of this cycle.In this paper,the remaining useful life of the equipment is calculated using the combination of sensor information,determination of degradation state and forecasting the proposed health index.The combination of sensor information has been carried out using a new approach to determining the probabilities in the Dempster-Shafer combination rules and fuzzy c-means clustering method.Using the simulation and forecasting of extracted vibration-based health index by autoregressive Markov regime switching(ARMRS)method,final health state is determined and the remaining useful life(RUL)is estimated.In order to evaluate the model,sensor data provided by FEMTO-ST Institute have been used.
文摘(2-acrylamido) ethyl tetradecyl dimethylammonium bromide (AMC14AB) was polymerized in aqueous solu- tion to form the homopolymer P(AMC14AB). The physicochemical properties of P(AMC14AB) in aqueous solution were mainly studied with fluorescent probe method, surface tension measurement and conductom- etry. The experimental results show that the aggregation morphology of P(AMC14AB) in aqueous solution is unimolecular micelle as expected. Being different from conventional multimolecular micelle systems, the unimolecular micelle system of P(AMC14AB) not only shows critical micellar concentration (CMC=0), (i.e. once added to pure water, the surface tension decreases immediately in spite how small the density is), but also the surface tension stays almost the same with the concentration increasing. That is to say, there is no mutational point on the relationship curve between surface tension and concentration. Furthermore, the unimolecular micelle system of P(AMC14AB) has no Krafft temperature, i.e. at any temperature, so long as it is dissolved in water, the unimolecular micelles will form. Besides this, for the solubilization of hydrophobic organic substances, the unimolecular micelle system of P(AMC14AB) is obviously different from the common multimolecular micelle system, having no turning point on the relationship curve between toluene solubi- lizaion amount and P(AMC14AB) concentration, and the solubilizing ability of the unimolecular-micelle system of P(AMC14AB) for hydrophobic organic substances is much higher than that of the conventional multimolecular micelle solutions of common surfactants, such as centyl trimethyl ammonium bromide.
基金supported by the Brain Korea 21 Project in 2011 and MKE(The Ministry of Knowledge Economy),Korea,under the ITRC(Infor mation Technology Research Center)support program supervised by the NIPA(National IT Industry Promotion Agency)(NIPA-2011-C1090-1121-0010)
文摘This paper proposes an algorithm that extracts features of back side of the vehicle and detects the front vehicle in real-time by local feature tracking of vehicle in the continuous images.The features in back side of the vehicle are vertical and horizontal edges,shadow and symmetry.By comparing local features using the fixed window size,the features in the continuous images are tracked.A robust and fast Haarlike mask is used for detecting vertical and horizontal edges,and shadow is extracted by histogram equalization,and the sliding window method is used to compare both side templates of the detected candidates for extracting symmetry.The features for tracking are vertical edges,and histogram is used to compare location of the peak and magnitude of the edges.The method using local feature tracking in the continuous images is more robust for detecting vehicle than the method using single image,and the proposed algorithm is evaluated by continuous images obtained on the expressway and downtown.And it can be performed on real-time through applying it to the embedded system.
基金supported by the National Key Technologies R&D Program of China under Grant No. 2015BAK38B01the National Natural Science Foundation of China under Grant Nos. 61174103 and 61603032+4 种基金the National Key Research and Development Program of China under Grant Nos. 2016YFB0700502, 2016YFB1001404, and 2017YFB0702300the China Postdoctoral Science Foundation under Grant No. 2016M590048the Fundamental Research Funds for the Central Universities under Grant No. 06500025the University of Science and Technology Beijing - Taipei University of Technology Joint Research Program under Grant No. TW201610the Foundation from the Taipei University of Technology of Taiwan under Grant No. NTUT-USTB-105-4
文摘Quantized kernel least mean square(QKLMS) algorithm is an effective nonlinear adaptive online learning algorithm with good performance in constraining the growth of network size through the use of quantization for input space. It can serve as a powerful tool to perform complex computing for network service and application. With the purpose of compressing the input to further improve learning performance, this article proposes a novel QKLMS with entropy-guided learning, called EQ-KLMS. Under the consecutive square entropy learning framework, the basic idea of entropy-guided learning technique is to measure the uncertainty of the input vectors used for QKLMS, and delete those data with larger uncertainty, which are insignificant or easy to cause learning errors. Then, the dataset is compressed. Consequently, by using square entropy, the learning performance of proposed EQ-KLMS is improved with high precision and low computational cost. The proposed EQ-KLMS is validated using a weather-related dataset, and the results demonstrate the desirable performance of our scheme.
基金Supported by the Teaching and Research Foundation for the Outstanding Young Faculty of Southeast University
文摘We study the quantum phase transition of ultracold atoms in the honeycomb optical lattice. The Hamiltonian of ultracold bosonic atoms in the honeycomb optical lattice is derived. We take the mean-field approximation and further solve the Hamiltonian with the numerical diagonalization method. We obtain the phase diagram and find that the Mort-insulator (MI), density wave (DW) and modulated superfluid (MS) phases appear. Furthermore, the phase diagram is analyzed according to the order parameter and the average number of particles.