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Special issue with selection of extended papers from 6th International Conference on Logistic, Informatics and Service Science LISS’2016

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Heft Title: Special Heft on Application of Advanced Computing and Simulation in Information Systems

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The publishing of the present issue (Volumen 13, No 4, 2013) of the journal “Cybernetics and Information Technologies” is financially supported by FP7 project “Advanced Computing for Innovation” (ACOMIN), grant agreement 316087 of Call FP7 REGPOT-2012-2013-1.

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Volumen 12 (2012): Heft 1 (March 2012)

Zeitschriftendaten
Format
Zeitschrift
eISSN
1314-4081
Erstveröffentlichung
13 Mar 2012
Erscheinungsweise
4 Hefte pro Jahr
Sprachen
Englisch

Suche

Volumen 16 (2016): Heft 5 (October 2016)
Heft Title: Special Heft on Application of Advanced Computing and Simulation in Information Systems

Zeitschriftendaten
Format
Zeitschrift
eISSN
1314-4081
Erstveröffentlichung
13 Mar 2012
Erscheinungsweise
4 Hefte pro Jahr
Sprachen
Englisch

Suche

17 Artikel
Uneingeschränkter Zugang

Preface

Online veröffentlicht: 20 Oct 2016
Seitenbereich: 3 - 4

Zusammenfassung

Uneingeschränkter Zugang

New Mixed Kernel Functions of SVM Used in Pattern Recognition

Online veröffentlicht: 20 Oct 2016
Seitenbereich: 5 - 14

Zusammenfassung

Abstract

The pattern analysis technology based on kernel methods is a new technology, which combines good performance and strict theory. With support vector machine, pattern analysis is easy and fast. But the existing kernel function fits the requirement. In the paper, we explore the new mixed kernel functions which are mixed with Gaussian and Wavelet function, Gaussian and Polynomial kernel function. With the new mixed kernel functions, we check different parameters. The results shows that the new mixed kernel functions have good time efficiency and accuracy. In image recognition we used SVM with two mixed kernel functions, the mixed kernel function of Gaussian and Wavelet function are suitable for more states.

Schlüsselwörter

  • Support vector machine
  • kernel functions
  • pattern recognition
  • Wavelet function
Uneingeschränkter Zugang

PID Controller Design Based on Radial Basis Function Neural Networks for the Steam Generator Level Control

Online veröffentlicht: 20 Oct 2016
Seitenbereich: 15 - 26

Zusammenfassung

Abstract

Steam generator level control system is a vital control system for the Pressurized Water Reactor (PWR). However, the steam generator level process is a highly nonlinear and non-minimum phase system, the conventional Proportional- Integral-Derivative (PID) control scheme with fixed parameters was difficult to obtain satisfactory control performance. The Radial Basis Function (RBF) Neural Networks based PID control strategy (RBFNN-PID) is proposed for the steam generator level control. This method can identify the mathematical model of the steam generator via the RBF neural networks, and then the PID parameters can be optimized automatically to accommodate the characteristic variation of the process. The optimal number of the hidden layer neurons is also discussed in this paper. The simulation results shows that the PID controller designed based on the RBF neural networks has good control performance on the steam generator level control.

Schlüsselwörter

  • PID controller
  • radial basis function
  • neural networks
  • steam generator
  • water level control
Uneingeschränkter Zugang

Triangulation Reconstruction for 3D Surface Based on Information Model

Online veröffentlicht: 20 Oct 2016
Seitenbereich: 27 - 33

Zusammenfassung

Abstract

The aim of this paper is to address the surface reconstruction from point cloud in reverser engineering. The data was acquired through a 3D scan device and was processed as point cloud data. The points in cloud were connected to build 3D surface. The points cloud was processed in four steps to get 3D information surface. First, the subtraction scheme was used to get cover boxes ended with the set of convex was found under the convergence rule. Secondly, the points in the box were projected to the directions which were close to the normal direction method. Thirdly the overlap was avoided by using convergence rule and inner subdivision rule. Finally the information model was used to reconstruction. The method was used in landslide monitoring of Three Gorges area for 3D surface reconstruction and monitoring. The reconstruction method obtains high precision and low complexity. It is effective for large scale monitoring.

Schlüsselwörter

  • Triangulation reconstruction
  • 3D elastic model
  • vector projection
  • point cloud
  • landslide monitoring
Uneingeschränkter Zugang

ICA-ASIFT-Based Multi-Temporal Matching of High-Resolution Remote Sensing Urban Images

Online veröffentlicht: 20 Oct 2016
Seitenbereich: 34 - 49

Zusammenfassung

Abstract

While SIFT (Scale Invariant Feature Transform) features are used to match High-Resolution (HR) remote sensing urban images captured at different phases with large scale and view variations, feature points are few and the matching accuracy is low. Although replacing SIFT with fully affine invariant features ASIFT (Affine-SIFT) can increase the number of feature points, it results in matching inefficiency and a non-uniform distribution of matched feature point pairs. To address these problems, this paper proposes the novel matching method ICA-ASIFT, which matches HR remote sensing urban images captured at different phases by using an Independent Component Analysis algorithm (ICA) and ASIFT features jointly. First, all possible affine deformations are modeled for the image transform, extracting ASIFT features of remote sensing images captured at different times. The ICA algorithm reduces the dimensionality of ASIFT features and improves matching efficiency of subsequent ASIFT feature point pairs. Next, coarse matching is performed on ASIFT feature point pairs through the algorithms of Nearest Vector Angle Ratio (NVAR), Direction Difference Analysis (DDA) and RANdom SAmple Consensus (RANSAC), eliminating apparent mismatches. Then, fine matching is performed on rough matched point pairs using a Neighborhoodbased Feature Graph Matching algorithm (NFGM) to obtain final ASIFT matching point pairs of remote sensing images. Finally, final matching point pairs are used to compute the affine transform matrix. Matching HR remote sensing images captured at different phases is achieved through affine transform. Experiments are used to compare the performance of ICA-ASFIT and three other algorithms (i.e., Harris- SIFT, PCA-SIFT, TD-ASIFT) on HR remote sensing images captured at different times in different regions. Experimental results show that the proposed ICA-ASFIT algorithm effectively matches HR remote sensing urban images and outperforms other algorithms in terms of matching accuracy and efficiency.

Schlüsselwörter

  • Remote sensing image matching
  • Independent component analysis
  • SIFT
  • Affine transform
Uneingeschränkter Zugang

Research on QPM and Its Cascaded Structure Applied in FOPA

Online veröffentlicht: 20 Oct 2016
Seitenbereich: 50 - 58

Zusammenfassung

Abstract

In the research of optical communication, Optical Parametric Amplification (OPA) has been an important point. As a Four Wave Mixing (FWM) effect based nonlinear process, OPA also requires Phase Matching (PM). Rigorous PM in practical research requires extremely harsh conditions. Quasi Phase Matching (QPM) and its cascaded structure can solve that problem, which would construct an overall phase matching. In the first part of this thesis, a QPM mechanism of segmented High NonLinear Fibre (HNLF) and inserted phase shifter for pumps, was proposed in application of FOPA. The phase shifters would “correct” the phase mismatching after every amplified signal by HNLF section. In this structure the phase matching was always kept in the vicinity of the initial matching value. The signal gain was flatter, and 6.4-9.5 dB higher than that of the non-QPM structure. In second part, a cascaded FWM+OPA structure was used to realize the copier-FOPA according to the cascaded QPM scheme. In the copier part, the information of signal wave was copied into the generated idler wave, before the signal light was amplified. Not only the copy, a 160 nm (Phase Insensitive, PI)/170 nm (Phase Sensitive, PS) gain bandwidth was obtained, which improved greatly comparing to that of the conventional. In FOPA part, the signal flatter gain decreases by approximately 14 dB (PI)/15 dB (PS), with fluctuation down to <0.1 dB (PI) / <0.2 dB (PS). The gain bandwidth decreases to 135 nm (PI) / 150 nm (PS), which is tens of nanometers wider than conventional FOPA.

Schlüsselwörter

  • FOPA
  • QPM
  • WC
  • cascaded structure
  • gain
Uneingeschränkter Zugang

Using Fitness Value for Monitoring Kiwifruit’s Variant Seedling in Tissue Culture

Online veröffentlicht: 20 Oct 2016
Seitenbereich: 59 - 68

Zusammenfassung

Abstract

Based on Genetic Algorithm, a pattern recognition approach using fitness to dynamically monitor the sub cultured seeding of kiwifruit is proposed in order to decrease the loss of variant seedlings in tissue culture. By coding, selection, mutation and cross-overing the selected primer pairs of the sub cultured seeding, we simulate the process of optimizing the kiwifruit’s genomic DNA polymorphism. The corresponding fitness values of the primer pairs are evaluated with fitness function for monitor the variation of kiwi’s DNA. The result shows that kiwi’s plantlets can better maintain their genes’ genetic stability for the first to the ninth generation. But from the tenth generation, the fitness values become variation. The results are based on experimentation, which uses optimized AFLP system for analyzing genetic diversity of 75 samples of seventh to eleventh 5 generations of kiwi.

Schlüsselwörter

  • Kiwifruit
  • Variant Seedling
  • monitoring
  • Genetic Algorithm
  • Fitness Function
Uneingeschränkter Zugang

Noval Stream Data Mining Framework under the Background of Big Data

Online veröffentlicht: 20 Oct 2016
Seitenbereich: 69 - 77

Zusammenfassung

Abstract

Stream data mining has been a hot topic for research in the data mining research area in recent years, as it has an extensive application prospect in big data ages. Research on stream data mining mainly focuses on frequent item sets mining, clustering and classification. However, traditional steam data mining methods are not effective enough for handling high dimensional data set because these methods are not fit for the characteristics of stream data. So, these traditional stream data mining methods need to be enhanced for big data applications. To resolve this issue, a hybrid framework is proposed for big steam data mining. In this framework, online and offline model are organized for different tasks, the interior of each model is rationally organized according to different mining tasks. This framework provides a new research idea and macro perspective for stream data mining under the background of big data.

Schlüsselwörter

  • Stream data
  • data mining
  • clustering
  • classification
  • framework
Uneingeschränkter Zugang

Research on the Distribution System Simulation of Large Company’s Logistics under Internet of Things Based on Traveling Salesman Problem Solution

Online veröffentlicht: 20 Oct 2016
Seitenbereich: 78 - 87

Zusammenfassung

Abstract

This paper is research on the distribution system’s simulation of large company’s logistics under Internet of Things (IoT) based on traveling salesman problem solution. The authors claim that the real-time traffic synergy is better than traditional distribution strategy in general, verifying and comparing the simulation results in different situations of goals and starting time distribution. The simulation method used in this paper makes the result more scientific and reliable. The simulation truly reflects the degree of influence of information synergy to improve the efficiency of logistics system. The information synergy had an obvious enhancing effect on system operation efficiency. Taking full advantage of the value of information and improving the information synergy to the best level have irreplaceable effect on system operation efficiency.

Schlüsselwörter

  • Main simulation method
  • Distribution system
  • Large Company’s Logistics
  • Internet of Things (IoT)
  • Traveling salesman problem solution
Uneingeschränkter Zugang

Synchronous Rendezvous Based on Cluster in Low-Duty-Cycle Wireless Sensor Network

Online veröffentlicht: 20 Oct 2016
Seitenbereich: 88 - 96

Zusammenfassung

Abstract

This paper presents SRBC, a new design for synchronous rendezvous in low-duty-cycle Wireless Sensor Network (WSN).The main idea of SRBC is utilizing the cluster, which includes a part of the sensor nodes in the WSN. Each node in a cluster alters its clock drift as well as its skew towards the central node of the cluster through exchange of their clock information with normal communication. Then it reduces the overhead of the process usual for the traditional time-stamp exchange. In different clusters, the border nodes exchange the relative clock drift as well as the skew to improve the performance during the synchronous rendezvous. Results show that the design of SRBC is practical and effective.

Schlüsselwörter

  • Wireless sensor network
  • synchronous rendezvous
  • low-duty-cycle
  • clock drift
  • clock skew
Uneingeschränkter Zugang

Research on the Novel Method of Edge Detection Based on the Isotropic Diffusion Model and Total Variation Model

Online veröffentlicht: 20 Oct 2016
Seitenbereich: 97 - 108

Zusammenfassung

Abstract

A novel model of image segmentation based on watershed method is proposed in this work. To prevent the over segmentation of traditional watershed, our proposed algorithm has five stages. Firstly, the morphological reconstruction is applied to smooth the flat area and preserve the edge of the image. Secondly, multiscale morphological gradient is used to avoid the thickening and merging of the edges. Thirdly, for contrast enhancement the top/bottom hat transformation is used. Fourthly, the morphological gradient of an image is modified by imposing regional minima at the location of both the internal and the external markers. Finally, a weighted function is used to combine the top/bottom hat transformation algorithm and the markers algorithm to get the algorithm. The experimental results show the superiority of the new algorithm in terms of suppression over segmentation.

Schlüsselwörter

  • Novel method
  • Edge detection
  • The isotropic diffusion model
  • Total variation model
Uneingeschränkter Zugang

Research on the Image Denoising Method Based on Partial Differential Equations

Online veröffentlicht: 20 Oct 2016
Seitenbereich: 109 - 118

Zusammenfassung

Abstract

In this paper we propose a new approach for image denoising based on the combination of PM model, isotropic diffusion model, and TV model. To emphasize the superiority of the proposed model, we have used the Structural Similarity Index Measure (SSIM) and Peak Signal to Noise Ratio (PSNR) as the subjective criterion. Numerical experiments with different images show that our algorithm has the highest PSNR and SS1M, as well as the best visual quality among the six algorithms. Experimental results confirm the high performance of the proposed model compared with some well-known algorithms. In a word, the new model outperforms the mentioned three well known algorithms in reducing the Gibbs-type artifacts, edges blurring, and the block effect, simultaneously.

Schlüsselwörter

  • Image denoising method
  • Partial differential equations
  • The blending algorithm
Uneingeschränkter Zugang

Analysis of an Optimal Measurement Index Based on the Complex Network

Online veröffentlicht: 20 Oct 2016
Seitenbereich: 119 - 126

Zusammenfassung

Abstract

In this paper, the discussion on the scientific cooperation network structure, the use of complex network analysis and social network analysis and the network analysis result from a scientific cooperation in both dynamic and static perspective. This paper extracts articles from 1995 to 2015 in conference proceedings, as experimental data sets with the corresponding network are called data mining cooperative network. The classic center-based index analysis was proposed by an improved node center metrics (c-index), weighted measure of the power of collaborative network node cooperation.

Schlüsselwörter

  • Complex network
  • node centrality metrics (c-index)
  • weighted cooperative network
Uneingeschränkter Zugang

A New Localization Algorithm Based on Taylor Series Expansion for NLOS Environment

Online veröffentlicht: 20 Oct 2016
Seitenbereich: 127 - 136

Zusammenfassung

Abstract

In Non-Line-Of-Sight (NLOS) environment, location accuracy of Taylorseries expansion location algorithm degrades greatly. A new Taylor-series expansion location algorithm based on self-adaptive Radial-Basis-Function (RBF) neural network is proposed in this paper, which can reduce the impact on the positioning accuracy of NLOS effectively on the basis of the measurement error correction. RBF neural network has a faster learning characteristic and the ability of approximate arbitrary nonlinear mapping. In the process of studying, RBF neural network adjusts to the quantity of the nodes according to corresponding additive strategy and removing strategy. The newly-formed network has a simple structure with high accuracy and better adaptive ability. After correcting the error, reuse Taylor series expansion location algorithm for positioning. The simulation results indicate that the proposed algorithm has high location accuracy, the performance is better than RBF-Taylor algorithm, LS-Taylor algorithm, Chan algorithm and LS algorithm in NLOS environment.

Schlüsselwörter

  • Position location
  • NLOS propagation
  • Adaptive processing
  • RBF neural network
Uneingeschränkter Zugang

Compound Controller for DC Motor Servo System Based on Inner-Loop Extended State Observer

Online veröffentlicht: 20 Oct 2016
Seitenbereich: 137 - 145

Zusammenfassung

Abstract

As DC motor servo systems are more and more widely applied in the manufacturing industry and aerospace domain, the requirements on control performance are increased by the complicated various working environments. With regard to the uncertainties including modeling error, parameter variations and external disturbances in DC motor servo system, one Nonlinear Extended Disturbance Observer (NESO) is constructed, and its output will be used as the design reference of disturbance compensation term in control system. Based on the as-built NESO in inner loop, one outer-loop compound controller by means of state-space design method is proposed in order to realize the high-precision position tracking ability of the servo system. Computer simulation results show that compared with conventional control schemes, the proposed control scheme can guarantee fewer tracking errors of DC motor servo system. Moreover, it possesses stronger robustness against system uncertainties including modeling error, parameter variations and friction moment disturbance.

Schlüsselwörter

  • Motor servo system
  • Extended State Observer (ESO)
  • Active Disturbance Rejection Control (ADRC)
  • compound control
  • robust control
Uneingeschränkter Zugang

Capacity of Right-Turn Lane at Signalized Intersection under Pedestrian-Bicycle Effect

Online veröffentlicht: 20 Oct 2016
Seitenbereich: 146 - 155

Zusammenfassung

Abstract

The effect of pedestrian and bicycle infrastructure is used to analyze the capacity for right-turn lane at signalized intersection. Each cycle at the signalized intersection was divided into several periods. The effect of pedestrian and bicycle at each period was analyzed. The number of right-turn cars going through signalized intersection was calculated by using probability theory and mathematical statistics. The capacity under the effect of pedestrian and bicycle for right-turn lane at signalized Intersection was deduced. The calculated results were deduced by using the survey data of two signalized intersections at Jinan city. The mean difference values are 8% and 10.1%, compared with VISSIM simulation results. The comparisons show that this model can fully describe the effect of pedestrian and bicycle to signalized intersection.

Schlüsselwörter

  • Traffic engineering
  • Capacity
  • Pedestrian-bicycle
  • Signalized intersection
  • Right-turn lane
Uneingeschränkter Zugang

Nighttime Pedestrian Ranging Algorithm Based on Monocular Vision

Online veröffentlicht: 20 Oct 2016
Seitenbereich: 156 - 167

Zusammenfassung

Abstract

Since the traditional computer vision ranging algorithm is imperfect in pertinence and precision, night time monocular vision pedestrian ranging method is proposed for vehicular infrared night vision goggles. Firstly, the method calibrated the internal and external parameters of infrared night-vision goggles, then, it corrected distortion of collected Vehicular Infrared Night Vision Image, and finally it ranged objective pedestrians by using night time monocular vision pedestrian ranging algorithm. The experimental results show that this method has the characteristics of pertinence, high precision and good real-time, and has good practicability.

Keyword

  • Ranging algorithm
  • infrared night vision goggles
  • monocular vision
  • distortion correction
17 Artikel
Uneingeschränkter Zugang

Preface

Online veröffentlicht: 20 Oct 2016
Seitenbereich: 3 - 4

Zusammenfassung

Uneingeschränkter Zugang

New Mixed Kernel Functions of SVM Used in Pattern Recognition

Online veröffentlicht: 20 Oct 2016
Seitenbereich: 5 - 14

Zusammenfassung

Abstract

The pattern analysis technology based on kernel methods is a new technology, which combines good performance and strict theory. With support vector machine, pattern analysis is easy and fast. But the existing kernel function fits the requirement. In the paper, we explore the new mixed kernel functions which are mixed with Gaussian and Wavelet function, Gaussian and Polynomial kernel function. With the new mixed kernel functions, we check different parameters. The results shows that the new mixed kernel functions have good time efficiency and accuracy. In image recognition we used SVM with two mixed kernel functions, the mixed kernel function of Gaussian and Wavelet function are suitable for more states.

Schlüsselwörter

  • Support vector machine
  • kernel functions
  • pattern recognition
  • Wavelet function
Uneingeschränkter Zugang

PID Controller Design Based on Radial Basis Function Neural Networks for the Steam Generator Level Control

Online veröffentlicht: 20 Oct 2016
Seitenbereich: 15 - 26

Zusammenfassung

Abstract

Steam generator level control system is a vital control system for the Pressurized Water Reactor (PWR). However, the steam generator level process is a highly nonlinear and non-minimum phase system, the conventional Proportional- Integral-Derivative (PID) control scheme with fixed parameters was difficult to obtain satisfactory control performance. The Radial Basis Function (RBF) Neural Networks based PID control strategy (RBFNN-PID) is proposed for the steam generator level control. This method can identify the mathematical model of the steam generator via the RBF neural networks, and then the PID parameters can be optimized automatically to accommodate the characteristic variation of the process. The optimal number of the hidden layer neurons is also discussed in this paper. The simulation results shows that the PID controller designed based on the RBF neural networks has good control performance on the steam generator level control.

Schlüsselwörter

  • PID controller
  • radial basis function
  • neural networks
  • steam generator
  • water level control
Uneingeschränkter Zugang

Triangulation Reconstruction for 3D Surface Based on Information Model

Online veröffentlicht: 20 Oct 2016
Seitenbereich: 27 - 33

Zusammenfassung

Abstract

The aim of this paper is to address the surface reconstruction from point cloud in reverser engineering. The data was acquired through a 3D scan device and was processed as point cloud data. The points in cloud were connected to build 3D surface. The points cloud was processed in four steps to get 3D information surface. First, the subtraction scheme was used to get cover boxes ended with the set of convex was found under the convergence rule. Secondly, the points in the box were projected to the directions which were close to the normal direction method. Thirdly the overlap was avoided by using convergence rule and inner subdivision rule. Finally the information model was used to reconstruction. The method was used in landslide monitoring of Three Gorges area for 3D surface reconstruction and monitoring. The reconstruction method obtains high precision and low complexity. It is effective for large scale monitoring.

Schlüsselwörter

  • Triangulation reconstruction
  • 3D elastic model
  • vector projection
  • point cloud
  • landslide monitoring
Uneingeschränkter Zugang

ICA-ASIFT-Based Multi-Temporal Matching of High-Resolution Remote Sensing Urban Images

Online veröffentlicht: 20 Oct 2016
Seitenbereich: 34 - 49

Zusammenfassung

Abstract

While SIFT (Scale Invariant Feature Transform) features are used to match High-Resolution (HR) remote sensing urban images captured at different phases with large scale and view variations, feature points are few and the matching accuracy is low. Although replacing SIFT with fully affine invariant features ASIFT (Affine-SIFT) can increase the number of feature points, it results in matching inefficiency and a non-uniform distribution of matched feature point pairs. To address these problems, this paper proposes the novel matching method ICA-ASIFT, which matches HR remote sensing urban images captured at different phases by using an Independent Component Analysis algorithm (ICA) and ASIFT features jointly. First, all possible affine deformations are modeled for the image transform, extracting ASIFT features of remote sensing images captured at different times. The ICA algorithm reduces the dimensionality of ASIFT features and improves matching efficiency of subsequent ASIFT feature point pairs. Next, coarse matching is performed on ASIFT feature point pairs through the algorithms of Nearest Vector Angle Ratio (NVAR), Direction Difference Analysis (DDA) and RANdom SAmple Consensus (RANSAC), eliminating apparent mismatches. Then, fine matching is performed on rough matched point pairs using a Neighborhoodbased Feature Graph Matching algorithm (NFGM) to obtain final ASIFT matching point pairs of remote sensing images. Finally, final matching point pairs are used to compute the affine transform matrix. Matching HR remote sensing images captured at different phases is achieved through affine transform. Experiments are used to compare the performance of ICA-ASFIT and three other algorithms (i.e., Harris- SIFT, PCA-SIFT, TD-ASIFT) on HR remote sensing images captured at different times in different regions. Experimental results show that the proposed ICA-ASFIT algorithm effectively matches HR remote sensing urban images and outperforms other algorithms in terms of matching accuracy and efficiency.

Schlüsselwörter

  • Remote sensing image matching
  • Independent component analysis
  • SIFT
  • Affine transform
Uneingeschränkter Zugang

Research on QPM and Its Cascaded Structure Applied in FOPA

Online veröffentlicht: 20 Oct 2016
Seitenbereich: 50 - 58

Zusammenfassung

Abstract

In the research of optical communication, Optical Parametric Amplification (OPA) has been an important point. As a Four Wave Mixing (FWM) effect based nonlinear process, OPA also requires Phase Matching (PM). Rigorous PM in practical research requires extremely harsh conditions. Quasi Phase Matching (QPM) and its cascaded structure can solve that problem, which would construct an overall phase matching. In the first part of this thesis, a QPM mechanism of segmented High NonLinear Fibre (HNLF) and inserted phase shifter for pumps, was proposed in application of FOPA. The phase shifters would “correct” the phase mismatching after every amplified signal by HNLF section. In this structure the phase matching was always kept in the vicinity of the initial matching value. The signal gain was flatter, and 6.4-9.5 dB higher than that of the non-QPM structure. In second part, a cascaded FWM+OPA structure was used to realize the copier-FOPA according to the cascaded QPM scheme. In the copier part, the information of signal wave was copied into the generated idler wave, before the signal light was amplified. Not only the copy, a 160 nm (Phase Insensitive, PI)/170 nm (Phase Sensitive, PS) gain bandwidth was obtained, which improved greatly comparing to that of the conventional. In FOPA part, the signal flatter gain decreases by approximately 14 dB (PI)/15 dB (PS), with fluctuation down to <0.1 dB (PI) / <0.2 dB (PS). The gain bandwidth decreases to 135 nm (PI) / 150 nm (PS), which is tens of nanometers wider than conventional FOPA.

Schlüsselwörter

  • FOPA
  • QPM
  • WC
  • cascaded structure
  • gain
Uneingeschränkter Zugang

Using Fitness Value for Monitoring Kiwifruit’s Variant Seedling in Tissue Culture

Online veröffentlicht: 20 Oct 2016
Seitenbereich: 59 - 68

Zusammenfassung

Abstract

Based on Genetic Algorithm, a pattern recognition approach using fitness to dynamically monitor the sub cultured seeding of kiwifruit is proposed in order to decrease the loss of variant seedlings in tissue culture. By coding, selection, mutation and cross-overing the selected primer pairs of the sub cultured seeding, we simulate the process of optimizing the kiwifruit’s genomic DNA polymorphism. The corresponding fitness values of the primer pairs are evaluated with fitness function for monitor the variation of kiwi’s DNA. The result shows that kiwi’s plantlets can better maintain their genes’ genetic stability for the first to the ninth generation. But from the tenth generation, the fitness values become variation. The results are based on experimentation, which uses optimized AFLP system for analyzing genetic diversity of 75 samples of seventh to eleventh 5 generations of kiwi.

Schlüsselwörter

  • Kiwifruit
  • Variant Seedling
  • monitoring
  • Genetic Algorithm
  • Fitness Function
Uneingeschränkter Zugang

Noval Stream Data Mining Framework under the Background of Big Data

Online veröffentlicht: 20 Oct 2016
Seitenbereich: 69 - 77

Zusammenfassung

Abstract

Stream data mining has been a hot topic for research in the data mining research area in recent years, as it has an extensive application prospect in big data ages. Research on stream data mining mainly focuses on frequent item sets mining, clustering and classification. However, traditional steam data mining methods are not effective enough for handling high dimensional data set because these methods are not fit for the characteristics of stream data. So, these traditional stream data mining methods need to be enhanced for big data applications. To resolve this issue, a hybrid framework is proposed for big steam data mining. In this framework, online and offline model are organized for different tasks, the interior of each model is rationally organized according to different mining tasks. This framework provides a new research idea and macro perspective for stream data mining under the background of big data.

Schlüsselwörter

  • Stream data
  • data mining
  • clustering
  • classification
  • framework
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Research on the Distribution System Simulation of Large Company’s Logistics under Internet of Things Based on Traveling Salesman Problem Solution

Online veröffentlicht: 20 Oct 2016
Seitenbereich: 78 - 87

Zusammenfassung

Abstract

This paper is research on the distribution system’s simulation of large company’s logistics under Internet of Things (IoT) based on traveling salesman problem solution. The authors claim that the real-time traffic synergy is better than traditional distribution strategy in general, verifying and comparing the simulation results in different situations of goals and starting time distribution. The simulation method used in this paper makes the result more scientific and reliable. The simulation truly reflects the degree of influence of information synergy to improve the efficiency of logistics system. The information synergy had an obvious enhancing effect on system operation efficiency. Taking full advantage of the value of information and improving the information synergy to the best level have irreplaceable effect on system operation efficiency.

Schlüsselwörter

  • Main simulation method
  • Distribution system
  • Large Company’s Logistics
  • Internet of Things (IoT)
  • Traveling salesman problem solution
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Synchronous Rendezvous Based on Cluster in Low-Duty-Cycle Wireless Sensor Network

Online veröffentlicht: 20 Oct 2016
Seitenbereich: 88 - 96

Zusammenfassung

Abstract

This paper presents SRBC, a new design for synchronous rendezvous in low-duty-cycle Wireless Sensor Network (WSN).The main idea of SRBC is utilizing the cluster, which includes a part of the sensor nodes in the WSN. Each node in a cluster alters its clock drift as well as its skew towards the central node of the cluster through exchange of their clock information with normal communication. Then it reduces the overhead of the process usual for the traditional time-stamp exchange. In different clusters, the border nodes exchange the relative clock drift as well as the skew to improve the performance during the synchronous rendezvous. Results show that the design of SRBC is practical and effective.

Schlüsselwörter

  • Wireless sensor network
  • synchronous rendezvous
  • low-duty-cycle
  • clock drift
  • clock skew
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Research on the Novel Method of Edge Detection Based on the Isotropic Diffusion Model and Total Variation Model

Online veröffentlicht: 20 Oct 2016
Seitenbereich: 97 - 108

Zusammenfassung

Abstract

A novel model of image segmentation based on watershed method is proposed in this work. To prevent the over segmentation of traditional watershed, our proposed algorithm has five stages. Firstly, the morphological reconstruction is applied to smooth the flat area and preserve the edge of the image. Secondly, multiscale morphological gradient is used to avoid the thickening and merging of the edges. Thirdly, for contrast enhancement the top/bottom hat transformation is used. Fourthly, the morphological gradient of an image is modified by imposing regional minima at the location of both the internal and the external markers. Finally, a weighted function is used to combine the top/bottom hat transformation algorithm and the markers algorithm to get the algorithm. The experimental results show the superiority of the new algorithm in terms of suppression over segmentation.

Schlüsselwörter

  • Novel method
  • Edge detection
  • The isotropic diffusion model
  • Total variation model
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Research on the Image Denoising Method Based on Partial Differential Equations

Online veröffentlicht: 20 Oct 2016
Seitenbereich: 109 - 118

Zusammenfassung

Abstract

In this paper we propose a new approach for image denoising based on the combination of PM model, isotropic diffusion model, and TV model. To emphasize the superiority of the proposed model, we have used the Structural Similarity Index Measure (SSIM) and Peak Signal to Noise Ratio (PSNR) as the subjective criterion. Numerical experiments with different images show that our algorithm has the highest PSNR and SS1M, as well as the best visual quality among the six algorithms. Experimental results confirm the high performance of the proposed model compared with some well-known algorithms. In a word, the new model outperforms the mentioned three well known algorithms in reducing the Gibbs-type artifacts, edges blurring, and the block effect, simultaneously.

Schlüsselwörter

  • Image denoising method
  • Partial differential equations
  • The blending algorithm
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Analysis of an Optimal Measurement Index Based on the Complex Network

Online veröffentlicht: 20 Oct 2016
Seitenbereich: 119 - 126

Zusammenfassung

Abstract

In this paper, the discussion on the scientific cooperation network structure, the use of complex network analysis and social network analysis and the network analysis result from a scientific cooperation in both dynamic and static perspective. This paper extracts articles from 1995 to 2015 in conference proceedings, as experimental data sets with the corresponding network are called data mining cooperative network. The classic center-based index analysis was proposed by an improved node center metrics (c-index), weighted measure of the power of collaborative network node cooperation.

Schlüsselwörter

  • Complex network
  • node centrality metrics (c-index)
  • weighted cooperative network
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A New Localization Algorithm Based on Taylor Series Expansion for NLOS Environment

Online veröffentlicht: 20 Oct 2016
Seitenbereich: 127 - 136

Zusammenfassung

Abstract

In Non-Line-Of-Sight (NLOS) environment, location accuracy of Taylorseries expansion location algorithm degrades greatly. A new Taylor-series expansion location algorithm based on self-adaptive Radial-Basis-Function (RBF) neural network is proposed in this paper, which can reduce the impact on the positioning accuracy of NLOS effectively on the basis of the measurement error correction. RBF neural network has a faster learning characteristic and the ability of approximate arbitrary nonlinear mapping. In the process of studying, RBF neural network adjusts to the quantity of the nodes according to corresponding additive strategy and removing strategy. The newly-formed network has a simple structure with high accuracy and better adaptive ability. After correcting the error, reuse Taylor series expansion location algorithm for positioning. The simulation results indicate that the proposed algorithm has high location accuracy, the performance is better than RBF-Taylor algorithm, LS-Taylor algorithm, Chan algorithm and LS algorithm in NLOS environment.

Schlüsselwörter

  • Position location
  • NLOS propagation
  • Adaptive processing
  • RBF neural network
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Compound Controller for DC Motor Servo System Based on Inner-Loop Extended State Observer

Online veröffentlicht: 20 Oct 2016
Seitenbereich: 137 - 145

Zusammenfassung

Abstract

As DC motor servo systems are more and more widely applied in the manufacturing industry and aerospace domain, the requirements on control performance are increased by the complicated various working environments. With regard to the uncertainties including modeling error, parameter variations and external disturbances in DC motor servo system, one Nonlinear Extended Disturbance Observer (NESO) is constructed, and its output will be used as the design reference of disturbance compensation term in control system. Based on the as-built NESO in inner loop, one outer-loop compound controller by means of state-space design method is proposed in order to realize the high-precision position tracking ability of the servo system. Computer simulation results show that compared with conventional control schemes, the proposed control scheme can guarantee fewer tracking errors of DC motor servo system. Moreover, it possesses stronger robustness against system uncertainties including modeling error, parameter variations and friction moment disturbance.

Schlüsselwörter

  • Motor servo system
  • Extended State Observer (ESO)
  • Active Disturbance Rejection Control (ADRC)
  • compound control
  • robust control
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Capacity of Right-Turn Lane at Signalized Intersection under Pedestrian-Bicycle Effect

Online veröffentlicht: 20 Oct 2016
Seitenbereich: 146 - 155

Zusammenfassung

Abstract

The effect of pedestrian and bicycle infrastructure is used to analyze the capacity for right-turn lane at signalized intersection. Each cycle at the signalized intersection was divided into several periods. The effect of pedestrian and bicycle at each period was analyzed. The number of right-turn cars going through signalized intersection was calculated by using probability theory and mathematical statistics. The capacity under the effect of pedestrian and bicycle for right-turn lane at signalized Intersection was deduced. The calculated results were deduced by using the survey data of two signalized intersections at Jinan city. The mean difference values are 8% and 10.1%, compared with VISSIM simulation results. The comparisons show that this model can fully describe the effect of pedestrian and bicycle to signalized intersection.

Schlüsselwörter

  • Traffic engineering
  • Capacity
  • Pedestrian-bicycle
  • Signalized intersection
  • Right-turn lane
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Nighttime Pedestrian Ranging Algorithm Based on Monocular Vision

Online veröffentlicht: 20 Oct 2016
Seitenbereich: 156 - 167

Zusammenfassung

Abstract

Since the traditional computer vision ranging algorithm is imperfect in pertinence and precision, night time monocular vision pedestrian ranging method is proposed for vehicular infrared night vision goggles. Firstly, the method calibrated the internal and external parameters of infrared night-vision goggles, then, it corrected distortion of collected Vehicular Infrared Night Vision Image, and finally it ranged objective pedestrians by using night time monocular vision pedestrian ranging algorithm. The experimental results show that this method has the characteristics of pertinence, high precision and good real-time, and has good practicability.

Keyword

  • Ranging algorithm
  • infrared night vision goggles
  • monocular vision
  • distortion correction

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