Earticle

In order to see clearly the details inside the liver and enhance the users’ visual presence in the virtual surgery simulation system, the principles and methods of solid texture are used to render the photorealistic liver. Firstly, the sample sets are processed and multiple samples are used to synthesize the liver solid texture. Secondly, to improving the mapping efficiency of graphics hardware, the texture atlas is used to map the solid texture. In order to improve the fill rate of texture atlas, the height descending triangle bounding box method is used. The experimental result shows that the internal texture can be observed clearly. The study is of great significance to the photorealistic rendering of virtual liver surgery system, and provides a guideline for the solid texture synthesis and mapping of other human organs.

Reactive power procurement has been identified as an important ancillary service. The cost characteristics must be able to recover the lost opportunity cost component of generator reaching the field limits and causes the decrease in its active power when the reactive demand in the system increases. The Synchronous condensers supply reactive power to maintain the voltage and reduce the burden on the synchronous generators. In this paper, the cost characteristics of reactive power support by the generator are proposed based on its capability chart. A non-linear optimization problem formulation is proposed to compute both real and reactive power nodal prices for pool electricity market model with hydro condenser. The marginal prices at each node have been determined for both real and reactive power considering the minimization of fuel cost, reactive power cost, and cost of condenser. The cost characteristics of reactive power have been determined based on the existing methods and the proposed method. The comparison of the results obtained with existing method is also provided. The results have been determined for IEEE 24 bus test system.

Thought Extreme Learning Machine-Radial Basis Function(ELM-RBF) can be used easily and can complete learning phase at very fast speed and provide more compact network than classical Extreme Learning Machine(ELM), it still has some room to improvement. Micro-Genetic Algorithms(uGA) improved calculated speed while inherits the Genetic Algorithms advantage of good for optimization and overall search. Considered on these, the paper designed a optimization strategy for ELM-RBF neural network based on uGA. In particular, based on classical RBF-ELM, we use real-u GA algorithm to optimize ELM-RBF hidden layer neurons center and biases value. Experiments results show that ELM-RBF-uGA has better recognition and prediction performance than classical ELM-RBF.

In this paper, an adaptive Kalman Filtering method is presented for the state prediction of random systems. It is shown that the adaptive Kalman Filtering method in conjunction with equilibrium optimization solution can estimate the initial accelerations of targets effectively since the equilibrium optimization solution tunes the state prediction vector to diminish the error between measured value and prediction estimation value. We evaluate our model on special and random trajectories. Experimental evidence shows that the proposed method can robustly estimate an initial acceleration from a dynamic model and stably track a trajectory which is moving randomly.

Accurate segmentation of critical tissues in Magnetic Resonance (MR) Images is severely affected due to imperfections in the RF coil of the acquisition device. The problem becomes more prominent when there does not exist clear boundaries between various substructures. Hippocampus delineation from given MR image thus requires numerous preprocessing steps for correcting the intensity inhomogeneity resulting due to imperfections. Most of the time, extracted region will be partially containing the surrounded tissues. In this current work, an effective algorithm is developed aimed at segmenting the Hippocampus from the human brain MR image after performing the pre required bias correction. Before the given image is segmented, the image contrast is adjusted and then bias field is corrected. These steps are followed by clustering as well as region growing algorithms to finally yield effective results.

Oil spill accidents are likely to increase in three decades. An oil spill accident can lead to serious crisis to the marine environment. The wastewater and waste sludge all contains oil in the process of petroleum mining. The oil slick can move or transfer by spread, evaporate, dissolve, emulsifying, photolysis, and biodegradation and absorption which can pollute air, water and soil and is a disaster to the environment. The research analysis shows the oil slick flow with surface wave in wind and finds a few characteristics can help the design. A new collecting machine which can collect the oil slick efficient is designed by adjusting its position in the surface wave. The design includes three main parts of machine while the collecting plate is keeping under the wave but squeeze water surface. All the machine parts shall be controlled with a flexible smart system to adapt the changing surface wave in the ocean.

Based on the climate data and the social statistics of Guangzhou observatory from 1952 to 2014，this paper used Linear trend analysis, Morlet wavelet transform analysis, Mann-Kendall mutation test etc, to analyze the trend of climate change in Guangzhou nearly 65 years. The results showed that climatic conditions in Guangzhou in recent 65 years showed a warming and drying trend and this trend had become increasingly apparent since the 1990s. The average temperature increased at the rate of 0.153 ℃ / 10a , at the same time, the warming rate of average minimum temperature was higher than the average maximum temperature (0.15 ℃ / 10a> 0.14 ℃ / 10a). The annual precipitation had a slight increase at the rate of 37.77 mm / 10a. Under the effect of urban dry-island, the average relative humidity had a decreasing trend at the rate of 0.94% / 10a and the sunshine hours showed a decreasing trend with fluctuation.

In order to solve the problem about the brush and slip ring in drive motor of renewable energy vehicle, high frequency power magnetic field produced by a novel separable magnetic pot transformer could achieve contactless excitation energy transfer. For contactless energy transfer (CET) system, its research about energy and efficiency quality still remains a low level because application and research of CET are not integrated, especially how to improve transmission power and efficiency is still not enough. First of all in this paper, the topology of magnetic pot transformer is built to design resonant compensation circuit. Secondly, mutual inductance parameter is proposed by optimum efficiency analysis through calculation. Thirdly, circuit simulation model of Matlab and 3D simulation model of Ansoft Maxwell which can complete finite element transient analysis are built to verify the accuracy of optimum efficiency analysis. Lastly, the experiment platform about CET in synchronous generator prototype is performed. Although the output power had little increase, experiment and Matlab, Ansoft 3D simulation research proved that system efficiency had a quite increase based on optimum efficiency analysis.

For the increasingly serious global environmental pollution and rising awareness of environmental protection, a method for green design based on the environmental requirements is put forward. This paper lists the basic content based on the environmental requirements. On the grounds of knowledge reuse, the existing products’ conformity degree model is built on base of the fuzzy set theory. The fuzzy-analytic hierarchy process (F-AHP) and fuzzy set theory are used to determine the importance of the product's environmental requirements. In this paper we calculate the determination of the existing product with the each environmental requirement and the comprehensive conformity of the product. Then we can choose the best products to modify the design and achieve the purpose of green design. Finally we give the final green design method based on environmental requirements. In the product on the analysis of the conformity degree of the various environmental requirements, the method combines with the fuzzy analytic hierarchy process and fuzzy set method to effectively choose the best product that highly meets environment requirements to optimize and shorten the design cycle. Taking the design of the CNC machine tool as an example, we can get the validation that the method is an effective method of product green design.

In this research, Neuro-fuzzy fuzzy feedback linearization controller is recommended for sensitive three degrees of freedom dental actuator. To design stable high quality controller conventional feedback linearization controller is recommended. Conventional feedback linearization (FL) controller is a nonlinear, stable, and reliable controller. This controller is model-base and in uncertain situation, model-base is challenge. The nonlinear dynamic formulation problem in highly nonlinear system has been solved by fuzzy logic theorem. Fuzzy logic theory is used to estimate the system dynamics. This type of controller is free of mathematical dynamic parameters of plant. When system works in uncertainty, the nonlinearity term of system is not equal to equivalent term of FL controller. According to this technique, the number of rule base is reduced with respect to have PID like fuzzy logic controller. The simulation results show that the proposed controller works well in various situations. Based on result and discussion, proposed method can eliminate chattering in certain and uncertain condition. This controller reduces the level of energy due to the torque performance. This controller removed the fluctuation in presence of uncertainties.

With the fast advances of sensing technologies in the past decade, a significant amount of discrete point data has been obtained. Some of these points are of poor quality because of measurement uncertainty at the geometric discontinuity of mechanical parts. In this paper, a particle swarm algorithm is developed for optimally-constrained multiple-line fitting of discrete data points. It contains two important technical components: a) constrained least-squares fitting of multiple lines, b) particle swarm search for optimal corner/edge points. The algorithm is applied to two-dimensional and three-dimensional cases. Numerical experiments indicate the effectiveness and high accuracy of the proposed approach, compared to the conventional method. It can be used for the accurate determination of sharp edges or corners based on discrete data points measured in high-precision inspection and manufacturing.

Considering that the existing artificial bee colony (ABC) algorithm can not give simultaneously attention to evolution speed and solution quality, an improved ABC algorithm is proposed based on nelder-mead simplex method (NMSM) in this paper, and defined ad NMSM-ABC. In the process of iteration, the algorithm periodically passes the best individual vertex from NMSM operator into ABC, or migrates the optimal food source information from ABC to NMSM can get away from local minimum with aid of ABC. Hence, the proposed algorithm can realize cooperative co-evolution of the two so that the desired properties are obtained. In addition, the sensitivity analysis of the key parameter of NMSM-ABC is also conducted and the best value is suggested. Finally, Numerical experiments and comparisons on 6 benchmark functions are conducted with other ABC algorithms, and the results indicate that the proposed algorithm effectively overcomes the local minimum, and dramatically enhances the global searching ability and convergence speed, and is a good cooperative co-evolution algorithm.

To satisfy the requirements of smart power grids for online monitoring intelligent switchgear cabinets, this paper designed an online monitoring system for mechanical characteristics of circuit breaker with the multi-sensor fusion technology, realized the online monitoring of the characteristics including travel, over travel, speed at instant of contacts separating (touching), switch-off (on) time, bounce times, bouncing time and average speed; the results of field and remote tests showed that the developed monitoring device enabled real time and accurate monitoring of mechanical characteristics of circuit breakers.

To address the slow convergence and large residual error problems in the T/2 fractionally spaced equalization with constant modulus algorithm (T/2-FSE-CMA) for high-order QAM signal in wireless communication, we analyze the distribution characters of 16QAM signal constellations and propose an improved T/2 fractionally spaced blind equalization with coordinate transform and constant modulus algorithm (T/2-FSE-RCTCMA). In this algorithm, we equalize the real and imaginary parts of the input signal in the fractionally spaced equalizer separately. By using the coordinate transform the output signals are mapped into the same circle and the error function of constant modulus is achieved. Using the error function to adjust the weight vector of each sub-channel in the fractionally spaced equalizer, we may avoid the miss-detection caused by the T/2 FSE-CMA algorithm in multi-modulus high-order QAM signal equalization. The simulation results in wireless channel show that compared with T/2-FSE-CTCMA and T/2- FSE-CMA, the proposed algorithm has a faster convergence speed and a smaller residual error.

This paper proposes a new method of efficient image reconstruction based on the Modified Frame Reconstruction Iterative Thresholding Algorithm (MFR ITA) developed under the compressed sensing (CS) domain by using total variation algorithm. The new framework is consisted of three phases. Firstly, the input images are processed by the multilook processing with their sparse coefficients using the Discrete Wavelet Transform (DWT) method. Secondly, the measurements are obtained from sparse coefficient by using the proposed fusion method to achieve the balance resolution of the pixels. Finally, the fast CS method based on the MFR ITA is proposed to reconstruct the high resolution image. The proposed method achieved superior results on real images, and demonstrate qualitative improvements in terms of PSNR and SSIM values. Furthermore, achieved good reconstruction SNR in the presence of noise.

Currently, the scope of the traditional indicator system for performance evaluation of construction project is much broader. But the indicators are mostly involved only in quality, schedule, and environmental goals of the project. In other words, it only focuses on considering the level of performance that only a few large projects in progress goals, without taking into account of the impact on the overall performance level caused by the employees involved in the project and project management level of internal management of the project, which cannot meet the requirements for performance evaluation. Therefore, this article, from the view of the traditional project performance evaluation, through the introduction of financial indicators, indicators of internal, learning and development indicators, suggests a new comprehensive performance evaluation index system for construction projects. Based on the newly-built comprehensive performance evaluation index system of construction project, the collected project data by the author of this paper will be processed and analyzed. According to the characteristics of the index system and data rules, together with the introduction of a combination of indicators of empowerment evaluation method and TOPSIS method, the three construction project performance level is evaluated comprehensively in order to verify the rationality and practicality of the proposed construction project of comprehensive performance rating system. The results of this research show that the proposed project overall level of performance evaluation method is feasible, and it can be employed to do more comprehensive performance evaluation of the construction project, which provides new ideas and reference for the comprehensive evaluation of the level of performance of construction projects.

A semi-varying coefficient model, a type of semi-parametric model between the linear model and the varying coefficient model offers a good flexibility and has become an important tool for exploring the dynamic patterns in many areas of research, including economics, finance and biomedical research. This paper proposes a new estimation method for semi-varying coefficient models based on the roughness penalized spline approach. Asymptotic properties of their estimators are also obtained. The penalized spline estimation method is applied to an economic example using a semi-varying coefficient model.

In the modern age of information technology security of valuable asset become much important issue. Intrusion detection system plays a most important role in this area. It protects the system by attacks or threats by unauthorized access or person. The previous study has identified the need for more enhancements in the research of intrusion detection. This study gives the outline for intrusion detection and proposed a hybrid classification based method based on Decision Tree and K-Nearest Neighbor. This experiment perform on the bases of cross-10 fold validation techniques on the basis of decision tree and KNN classifiers and proposed hybrid classifier by using KDD cup dataset. Experimental result shows that the proposed idea gives good result as compared to individual base algorithms

In this paper we propose a novel differential evolution algorithm based on self-learning, in order to improve the environment adaptive ability of the population in dynamic optimization. The proposed algorithm can monitor the environment changes using re-evaluation of individuals. We direct the population evolution based on the current best individual and another two random individuals, so that the convergence speed is faster and the diversity of the population is maintained. In this way we may reduce the influence from the frequent environment changes. Testing on six dynamic functions, we study the influences caused by period and dimensions. We also compared the proposed algorithm with existing algorithms, the experimental results show that our algorithm has a better environment adaptive ability and achieves better optimization result.

In heterogeneous networks, the issue of interference between femtocells and macrocells should be carefully considered. Resource allocation schemes with cognitive technologies have been a key challenge to manage interference. In this paper, we investigate price-based power allocation strategies with the energy efficiency criterion for a spectrum-sharing heterogeneous cognitive network from the aspect of energy efficiency, and provide the utility function of macrocell and femtocells based on a non-cooperative Stackleberg game model. We build a combination of price vector and power allocation values by standard Lagrangian method and propose an improved iteration algorithm based on price updating to obtain the Stackleberg equilibrium solution. The simulation results verify the proposed method can improve energy efficiency and achieve better utility.

In this article, a unique and innovative design for addressing the speed synchronization problem in a multi-motor system using Brush less DC (BLDC), motors is presented by utilizing motor back emf equation and rotor position commonly called sensor less technique. In the proposed method, the system is modelled as a consensus problem of leader following multi-agent system (MAS), and a hybrid controller is designed by using Model Reference Adaptive Control (MRAC) along with Variable Structure (VS) control technique of Sliding Mode Control (SMC), herein called Variable Structure Model Reference Adaptive Control (VS-MRAC). The consensus algorithm of MAS (reformed w.r.t motor speed data), is fused with the hybrid controller to reach consensus on speed regulated by proposed hybrid controller. The stability of a system is endorse by designing a Lyapunov function. The efficiency of the proposed methodology is proven by simulations performed in MATLAB and the acquired results validate the success of proposed design methodology.

With the development trend of current economy and the rapid development of computer technology, intelligence is more and more widely applied in the construction industry. According to the actual situation of current society, this paper makes a brief introduction of building information model. Taking its application status at home and abroad and existing problems into consideration, as far as the development of the current field. The paper frames structure and simulates the interface with the help of computer-aided analyzing tools. Itapplies the computer intelligence factor analyzing method and gets the factors that influence the building information model are: the expected results, human intervention, promoting conditions, adoption intention, the ability to use technology and educational background variables. Then, through model testing, we got the direct link with strong degree between the expected results and adoption intention, human intervention and adoption intention, the expected results and the ability to use technology, promoting conditions and educational background variables. This paper analyzes the factors and the relations of building information model. Is has a certain economic value and practical significance. It can solve the existing problems in practical construction industry and lays a foundation for other related building software.

The continuous development of science technology promotes the great development of the information processing technology based on artificial intelligence. Such technology refers to the combination of various technologies such as the computer technology, communication technique, control technique and others, which is applied to the information collection and processing of information. This thesis, research the key artificial intelligence technology to process information, including the artificial neural network, fuzzy theory and others. Besides, the information processing technology based on artificial intelligence will be applied to the design of the intelligent transportation system in this research. The result shows that the application of the intelligent transportation system to which the information processing technology based on artificial intelligence could relieve the stress during the rush hours efficiently and improve the efficiency of information processing.

The online recruitment industry has developed rapidly under the Internet Plus environment, but the job hunters are rarely satisfied to the overall information service quality of recruitment websites. In order to improve the information service quality of recruitment websites, and maintain the competitive advantages of the industry, we conduct an empirical analysis of the factors influencing the information service quality of recruitment websites. Based on synthesizing the service quality evaluation indicators from both domestic and foreign studies,we propose the research model and hypotheses from the perspective of job hunters. We then conduct an online survey, and perform descriptive analysis, reliability analysis, factor analysis, variance analysis, correlation analysis and regression analysis on the sample data to test the research model and hypotheses with SPSS. The results show that the information content quality, reliability, ease of use, personalization and interactivity all have significantly positive correlation with the information service quality of recruitment websites.

In the existing literature, there is no consensus about the effect of the board capital on innovation performance. This study strive to find the reason by testing the testing the mediating effect of dynamic capability between the two variables. Data was collected from 385 Chinese listed manufacturing companies. The hierarchical regression analysis results confirmed the research hypotheses.

To solve the technical problems existing in air purification, a multileveled air purification device is presented. And the new device consists of catalytic purifying technology, low-temperature plasma, nanoscaled titania and dual-band ultraviolet. To deeply take a research on performance of the composite purification device, the device has been numerically simulated, with CFD simulation technology, through employing gas phase turbulence model, porous medium model and stochastic particle trajectory model. Comparative analyses on pressure distribution of internal flow field, velocity distribution, particle motion state and mass concentration distribution are made under different wind speed. The most appropriate wind speed can provide better centrifugal effect and less pressure loss. So some rules of velocity, pressure distribution and the particulate mass concentration distribution at all levels after filtering in internal device are acquired. In the meanwhile, a comparison among different research results has been made, and it helps to prove the reliability of this method.

To meet the demand of avionics control system's frequency response characteristic and the testing, a new avionics frequency response testing system is proposed. The design uses PXI series card of NI Corporation and the software programming is used in the design, to realize the function of the testing signal's generation, the collection of the response signal, the processing of the sampling data and the mapping of the system's frequency response characteristic curve, and so on. In this paper, the hardware composition, software design, testing steps, and the processing method of data sampling are mainly introduced. The results of application show that the proposed system is economical and reliable. It has a good stability and can meet the avionics system frequency response testing requirements. It not only achieves all the collection of the response signal, analysis and calculation, but also achieves the data storage and playback. The proposed system has the advantages of simple and quick, flexible configuration, portable, low cost, and so on.

This paper with spinach as the research object, to chlorpyrifos pesticide as detection object, using Raman spectroscopy technique surface pesticides in spinach residual detection method and rapid detection research. Starting from the detection method, study of the classic method and method for rapid detection of current situation of the development, Raman spectroscopy detection method as a means of detection, the selected object of study; master the Raman spectroscopy for rapid detection of the basic principles and originpro 9.0 software acquisition function using, lay the foundation for the subsequent detection of. After the actual test to determine Raman spectroscopy instrument laser wavelength to 473nm, acquisition time 2s spinach sample testing effect Best result. After no medicine Raman spectra to obtain the surface of spinach were denoising analysis results show that wavelet de noise method compared to the adjacent averaging, savitzky Golay method smoothing, median method effect better. On Spinach with different concentrations of chlorpyrifos Raman spectroscopy analysis that accorded with the residual linear relationship. The peak intensity method were selected to establish models were detected in spinach surface of pesticide chlorpyrifos. Raman spectroscopy detection method can of spinach surface of pesticide residues detection analysis. It solves the traditional measurement method for sample pretreatment is complex and long detection time, low efficiency of the measured defect

The energy consumption is one of the most important factors in the virtual machines deployment in the current data centres. Various studies proved that the energy aware management of the virtual machines can reduce the total energy consumption about tens of percents. We developed the new approach, based on the distributed algorithm, which is able to consolidate the virtual machines between various virtualization nodes without the central coordinator. The input data for this algorithm is collected online from the electronic wattmeters, which are placed before the energy input of each virtualization node.

On the basis of analyzing the working principle of ECT data acquisition system and wavelet Kalman algorithm, the realization method of a new ECT data acquisition filter is proposed about the acquisition accuracy and real-time requirement of electrical capacitance tomography ECT (Electrical Capacitance Tomography) data acquisition system. The method uses the principle of multiplexing and folding structure to make the multi wavelet decomposition and reconstruction combined, parallelize high-pass filter and low-pass filter to meet the requirement of real-time. The simulation experiment results show that the processing speed of the improved ECT data acquisition filter is improved, the acquisition speed and the accuracy of the data are better than the traditional ECT data acquisition system, it provides a new filter realization method for ECT data acquisition system.