Showing papers in "International Journal of Intelligent Systems and Applications in 2011"

A Stroke Shape and Structure Based Approach for Off-line Chinese Handwriting Identification

Abstract: Handwriting identification is a technique of automatic person identification based on the personal handwriting. It is a hot research topic in the field of pattern recognition due to its indispensible role in the biometric individual identification. Although many approaches have emerged, recent research has shown that off-line Chinese handwriting identification remains a challenge problem. In this paper, we propose a novel method for off-line Chinese handwriting identification based on stroke shapes and structures. To extract the features embedded in Chinese handwriting characters, two special structures have been explored according to the trait of Chinese handwriting characters. These two structures are the bounding rectangle and the TBLR quadrilateral. Sixteen features are extracted from the two structures, which are used to compute the unadjusted similarity, and the other four commonly used features are also computed to adjust the similarity adaptively. The final identification is performed on the similarity. Experimental results on the SYSU and HanjaDB1 databases have validated the effectiveness of the proposed method.

Research on Adaptive Fuzzy PID Synchronous Control Strategy of Double-Motor

Abstract: The double-motor synchronous control system is widely used in industrial field. Its performance plays an important role in production. Traditional PID controller parameters are difficult to tune when used in control system, as well as the control effect can not satisfy the requirement of producing process when the controller plant is complex non-linear system. In this paper, adaptive fuzzy PID which can tune the parameters on-line is introduced to apply in the double-motor synchronous control system. In MATLAB / SMULINK simulation environment, the speed of master motor is perfectly followed by slave motor, and high robustness and precision are obtained. The simulation results show that fuzzy logic PID control strategy has better performances than traditional controller.

Theoretical Design and Computational Fluid Dynamic Analysis of Projectile Intake

Abstract: With the development of the science and technology, the more requirements such as cost effective, high specific impulse in wide operation rang, becomes stricter and multiplicity. However, the existing supersonic inlet can no longer adjust to all the new projectiles. In this paper, based on the basic characteristic of inlet and considering the design requirements, the two-dimensional supersonic projectile inlet was designed and verified by numerical simulation under different operating conditions such as attack angle, altitude, and so on. The results are shown that: 1) The design process is successful, but the working conditions should be limited to the small angle of attack; 2) The total pressure recovery coefficient is increasing as the Ma number increases, and then is gradually decreased after the point of Mach number is equal to 0.5; 3) The existence of attack angle reduces values of total pressure recovery. And moreover, the shock wave which occurs at the anterior point is gradually deviating from projectile body direction with the increase of attack angle; 4). The variance ratio in the outlet has the acute changed with increasing of altitudes clearly, but its corresponding values degrade sharply in the entrance. Index Terms—supersonic air inlet, two-dimension, ramjet projectile, numerical simulation, influence factors

Study on The Novel Transient Bus Protection Based on Morphological Top-bottom-operator

Abstract: A novel transient component bus protection based on mathematical morphology is presented in this paper, which takes the morphological max top-bottom- operator of current traveling wave to fast distinguish the bus internal fault from the external fault. The method is based on the principle that the high frequency component of transient traveling wave caused by bus external fault will be attenuated by the bus capacitance but the traveling wave caused by bus internal fault changes slightly. Simulation is carried out with the electromagnetic transient simulation software PSCAD/EMTDC, the result verifies the bus protection is reliable and accurate. The novel bus protection also can treat lightning failure or lightning disturbance happened on transmission lines as bus external fault, without malfunction.

Predication and Optimization of Maintenance Resources for Weapon System

Abstract: Maintenance resources are important part of the maintenance support system. The whole efficiency of weapon system is directly affected by the allocation of maintenance resources. Joint support for weapon system of multi-kinds of equipments is the main fashion of maintenance support in the future. However, there is a lack of the efficiency tools and methods for predication and optimization of weapon system maintenance resources presently. For the prediction requirement of maintenance resources of weapon system, the primary infection factors for the requirement of maintenance resources were analyzed. According to the different characteristics of maintenance resources and the analysis for the traditional classification methods, a kind of classification for weapon system's maintenance resources was given. A prediction flow for the maintenance resources requirement was designed. Four kinds of models for predicting the maintenance resources requirement in a weapon system were designed and described in detail. In this paper, approaches of the optimal selection from the simulation schemes and reverse simulation for the resources allocation optimization were analyzed; some optimization models for maintenance resources such as spare parts and personnel were constructed. Further more, an optimization and decision-making system was not only designed but also developed. At last, an example was presented, which proved the prediction and optimization methods were applicability and feasibility, the decision-making system for the optimization of maintenance resources was a supportable and efficient tool.

Cloud Theory and Fractal Application in Virtual Plants

Abstract: Plants is an important component of natural scene. Unfortunately, due to high level complexity of the structure of plant, simulating plant becomes extremely a difficult task. When the fractal theory is imported, it provides a broader development space for the plant modeling. With the development of the fractal research, virtual plant has become a hot and interesting research topic in computer graphics area. The virtual plants technology is very important in guiding the crop production, implementing the agriculture informationization and constructing the virtual environment. At present a single virtual plant modeling technology is quite mature, the method to generate a body of plants often uses the even algorithm or the normal algorithm, but a body of plants in the real world is not even, and is not normal also, the cloud model relaxes the precise determination membership function to expectation function with normal distributed membership degree, combines ambiguity and randomness organically to fit the real world objectively. So it has general applicability, producing a body of plants based on the cloud model can simulate plant's condition and the distribution well.

A High Performance Image Authentication Algorithm on GPU with CUDA

Abstract: There has been large amounts of research on image authentication method. Many of the schemes perform well in verification results; however, most of them are time- consuming in traditional serial manners. And improving the efficiency of authentication process has become one of the challenges in image authentication field today. In the future, it's a trend that authentication system with the properties of high performance, real-time, flexible and ease for development. In this paper, we present a CUDA-based implementation of an image authentication algorithm with NVIDIA's Tesla C1060 GPU devices. Comparing with the original implementation on CPU, our CUDA-based implementation works 20x-50x faster with single GPU device. And experiment shows that, by using two GPUs, the performance gains can be further improved around 1.2 times in contras to single GPU.

Study on The Earthquake Disaster Reduction Information Management System and Its Application

Abstract: It is significant to scientifically carry out the urban earthquake disaster reduction. According to the features of China urban earthquake disaster reduction, this paper designed the urban earthquake disaster reduction information management system, which proposed a system design idea, system composition and function structure. The system adopted the object-oriented language VB6.0 and the component set ArcGIS Engine provided by ESRI for development. We applied a variety of information techniques (GIS and database) for spatial information acquisition, analysis and computing, and drew up function modules corresponding to inquiry, spatial analysis, risk analysis and data management. By using this system we can achieve scientific management about the earthquake disaster information in storage and transportation engineering, draw up kinds of earthquake emergency decisions intellectually and make them visual, which improved the efficiency and velocity of earthquake emergency evidently, and assisted the decision-making system effectively for the earthquake emergency work .

An improved PSO algorithm and its application in seismic wavelet extraction

Abstract: The seismic wavelet estimation is finally a multi- dimension, multi-extreme and multi-parameter optimization problem. PSO is easy to fall into local optimum, which has simple concepts and fast convergence. This paper proposes an improved PSO with adaptive parameters and boundary constraints, in ensuring accuracy of the algorithm optimization and fast convergence. Simulation results show that the methods have good applicability and stability for seismic wavelet extraction.

Numerical Oscillations of Runge-Kutta Methods for Differential Equations with Piecewise Constant Arguments of Alternately Advanced and Retarded Type

Abstract: The purpose of this paper is to study the numerical oscillations of Runge-Kutta methods for the solution of alternately advanced and retarded differential equations with piecewise constant arguments. The conditions of oscillations for the Runge-Kutta methods are obtained. It is proven that the Runge-Kutta methods preserve the oscillations of the analytic solution. In addition, the relationship between stability and oscillations are shown. Some numerical examples are given to confirm the theoretical results.

The Application of Sparse Antenna Array Synthesis Based on Improved Mind Evolutionary Algorithm

Abstract: Mind Evolutionary Algorithm (MEA) imitates the human mind evolution by using similartaxis and dissimilation operations, which overcomes the prematurity and improves searching efficiency. But the generation of the initial population is blind and the addition of naturally washed out temporary subpopulations is random. This paper improved MEA by introducing chaos and difference into it, which brought adequate diversity to the initial population and saved the excellent genes in the evolution. Then the improved MEA is used in the synthesis of sparse antenna arrays. The excellent results of computer simulation show the advantage of array antenna patterns synthesis using the improved MEA.

New Trending Events Detection based on the Multi-Representation Index Tree Clustering

Abstract: Traditional Clustering is a powerful technique for revealing the hot topics among Web information. However, it failed to discover the trending events coming out gradually. In this paper, we propose a novel method to address this problem which is modeled as detecting the new cluster from time-streaming documents. Our approach concludes three parts: the cluster definition based on Multi- Representation Index Tree (MI-Tree), the new cluster detecting process and the metrics for measuring a new cluster. Compared with the traditional method, we process the newly coming data first and merge the old clustering tree into the new one. Our algorithm can avoid that the documents owning high similarity were assigned to different clusters. We designed and implemented a system for practical application, the experimental results on a variety of domains demonstrate that our algorithm can recognize new valuable cluster during the iteration process, and produce quality clusters.

Towards More Sustainability: A Dynamic Recycling Framework of Discarded Products Based on SD Theory

Abstract: The mechanism of a recycling system about discarded products is running with a few critical roles and processes. To identify the relationship and collaborate the activities involved in this recycling circle are the very significant work in practice. For the sake the paper explores and identifies the critical drivers underlying the system, based on which a framework is established to explore the relationship among relevant activities consisted of collection, remanufacturing and resale, as well as companies and customers' behaviours. A dynamic quantitative model is designed to simulate this vigorous relation, which demonstrates and verifies the rule of this relationship with details about the recycling activities. The information will benefit practitioners a lot in terms of the recycling operation planning under different situation.

Application of Neural Network on Burr Expert System in Micro-machining

Abstract: The demands placed by designers on workpiece performance and functionality are increasing rapidly Important aspects of manufacturing's contribution to the fulfillment of these demands are the conditions at the work piece edges However, Burrs are often created on the workpiece edges in micro-machining In many cases, time consuming and expensive deburring processes have to be applied in order to ensure the desired part functionality Burrs make troubles on production lines in terms of deburring cost, quality of products and cutting tool wear To prevent problems caused by burrs in micro-machining, prediction and control of burr size is desirable Experimental studies show that burr formation in micro- milling is a highly complex process depending on a number of parameters such as material properties, tool geometry and cutting parameters It is very difficult to establish the relationship between burr sizes and cutting conditions A web-based micro-machining burr expert system for burr sizes prediction and control was developed using ASPNET platform Burrs types and sizes prediction and cutting conditions optimization for burr controlling which based on the reasoning method of BP neural networks are realized Operation results show that the system is reliable It provides a new technology for burrs modelling and controlling Index Terms—burr expert system, neural network, micro- machining, burr prediction, edge quality

An Initialization Method for Subspace clustering Algorithm

Abstract: Soft subspace clustering is an important part and research hotspot in clustering research. Clustering in high dimensional space is especially difficult due to the sparse distribution of the data and the curse of dimensionality. By analyzing limitations of the existing algorithms, the concept of subspace difference and an improved initialization method are proposed. Based on these, a new objective function is given by taking into account the compactness of the subspace clusters and subspace difference of the clusters. And a subspace clustering algorithm based on k-means is presented. Theoretical analysis and experimental results demonstrate that the proposed algorithm significantly improves the accuracy.

A New Joint Possibility Data Association Algorithm Avoiding Track Coalescence

Abstract: For the problem of tracking multiple targets, the Joint Probabilistic Data Association approach has shown to be very effective in handling clutter and missed detections However, it tends to coalesce neighboring tracks and ignores the coupling between those tracks To avoid track coalescence,a K Nearest Neighbor Joint Probabilistic Data Association algorithm is proposed in this paper Like the Joint Probabilistic Data Association algorithm, the association possibilities of target with every measurement will be computed in the new algorithm, but only the first K measurements whose association probabilities with the target are larger than others' are used to estimate target's state Finally, through Monte Carlo simulations, it is shown that the new algorithm is able to avoid track coalescence and keeps good tracking performance in heavy clutter and missed detections

Genetic Algorithm Combination of Boolean Constraint Programming for Solving Course of Action Optimization in Influence Nets

Abstract: A military decision maker is typically confronted by the task of determining optimal course of action under some constraints in complex uncertain situation. Thus, a new class of Combinational Constraint Optimization Problem (CCOP) is formalized, that is utilized to solve this complex Operation Optimization Problem. The object function of CCOP is modeled by Influence net, and the constraints of CCOP relate to resource and collaboration. These constraints are expressed by Pseudo-Boolean and Boolean constraints. Thus CCOP holds a complex mathematical configuration, which is expressed as a 0 1 integer optimization problem with compositional constraints and unobvious optimal object function. A novel method of Genetic Algorithm (GA) combination of Boolean Constraint Programming (BCP) is proposed to solve CCOP. The constraints of CCOP can be easily reduced and transformed into Disjunctive Normal Form (DNF) by BCP. The DNF representation then can be used to drive GA so as to solve CCOP. Finally, a numerical experiment is given to demonstrate the effectiveness of above method.

CRPCG—Clustering Routing Protocol based on Connected Graph

Abstract: In order to balance the load between cluster head, save the energy consumption of the inter-cluster routing, enhance reliability and flexibility of data transmission, the paper proposes a new clustering routing protocol based on connected graph (CRPCG). The protocol optimizes and innovates in three aspects: cluster head election, clusters formation and clusters routing. Eventually, a connected graph is constituted by the based station and all cluster heads, using the excellent algorithm of the graph theory, to guarantee the network connectivity and reliability, improve the link quality, balance node energy and prolong the network life cycle. The results of simulation show that, the protocol significantly prolong the network life cycle, balance the energy of network nodes, especially in the phase of intercluster data transmission, improving the reliability and efficiency of data transmission.

A Dynamic Self-Adjusted Buffering Mechanism for Peer-to-Peer Real-Time Streaming

Abstract: Multimedia live stream multicasting and on-line real-time applications are popular recently. Real-time multicast system can use peer-to-peer technology to keep stability and scalability without any additional support from the underneath network or a server. Our proposed scheme focuses on the mesh architecture of peer-to-peer live streaming system and experiments with the buffering mechanisms. We design the dynamic buffer to substitute the traditional fixed buffer. According to the existing measurements and our simulation results, using the traditional static buffer in a dynamic peer-to-peer environment has a limit of improving quality of service. In our proposed method, the buffering mechanism can adjust buffer to avoid the frozen or reboot of streaming based on the input data rate. A self-adjusted buffer control can be suitable for the violently dynamic peer-to-peer environment. Without any support of infrastructure and modification of peer-to-peer protocols, our proposed scheme can be workable in any chunk-based peer-to-peer streaming delivery. Hence, our proposed dynamic buffering mechanism varies the existing peer-to- peer live streaming system less to improve quality of experience more.

A Growing Evolutionary Algorithm and Its Application for Data Mining

Abstract: an unsuitable representation will make the task of mining classification rules very hard for a traditional evolutionary algorithm (EA). But for a given dataset, it is difficult to decide which one is the best representation used in the mining progress. In this paper, we analyses the effects of different representations for a traditional EA and proposed a growing evolutionary algorithm which was robust for mining classification rules in different datasets. Experiments showed that the proposed algorithm is effective in dealing with problems of deception, linkage, epistasis and multimodality in the mining task.

The Identification of Internal and External Faults for±800kV UHVDC Transmission Line Using Wavelet based Multi-Resolution Analysis

Abstract: There is a smoothing reactor and DC filter between the inverter and the direct current line to form a boundary in the HVDC transmission system. Since this boundary presents the stop-band characteristic to the high frequency transient voltage signals, the high-frequency transient voltage signal caused by external faults through boundary will be attenuated and the signals caused by internal faults will be unchanged. The wavelet analysis can be used as a tool to extract the feature of the fault to classify the internal fault and the external fault in HVDC transmission system. This paper explores the new method of wavelet based Multi-Resolution Analysis for signal decomposition to classify the difference types fault.

Inverse Operation of Four-dimensional Vector Matrix

Abstract: This is a new series of study to define and prove multidimensional vector matrix mathematics, which includes four-dimensional vector matrix determinant, four- dimensional vector matrix inverse and related properties. There are innovative concepts of multi-dimensional vector matrix mathematics created by authors with numerous applications in engineering, math, video conferencing, 3D TV, and other fields.

Classification of Forest Land Information Using Environment Satellite (HJ-1) Data

Abstract: For researching properties of HJ-1A CCD camera multi- spectral data in performance on extraction of land features information, this paper selected the east area of NiLeke forest farm in the western Tianshan mountain as the study area, and analyzed different accuracies for HJ-1A CCD data in identifying forest land categories using various classification methods. Firstly, maximum- likelihood classifier, Mahalanobis distance classifier, minimum distance classifier and K-means classifier were used to category land use types with two different scales on HJ-1A CCD1 and Landsat5 TM images, and analyzed separately with confusion matrix. Secondly, forest land types were distinguished by texture information and the smallest polygon size using K-NN method based on clustering algorithm. The comparing results show: at first, different classification system have different accuracy. In the first land use classification system, the accuracy of HJ-1A CCD1 images are lower than TM images, but higher in the second land use classification system. Secondly, accuracy result of maximum- likelihood classification is the best method to classify land use types. In the first land use classification system, TM total accuracy is up to 85.1% and Kappa coefficient is 0.8. In the second land use classification system, the result is up to 85.4% and kappa coefficient is 0.74.Thirdly, judgment both from the view of visual interpretation and quantitative accuracy testes, non-supervised method with K- means classifier has low qualities where many land features have characters of scattered distribution and small different spectrum information. Finally, the experiment proved that there were good vector results on HJ-1A remote sensing image in the view of visual judgment, and extracted deferent forest land by the overall accuracy 87% with the supports by those variables' distribution knowledge, such as conifer, mixed forest, broadleaf, shrubby. Index Terms—HJ-1A CCD1 data, image classification, different scale, land use features extraction

Application of SQL RAT Translation a Statement of RQP/RMP with an Object-oriented Solution

Abstract: Since we have already designed a flexible form of representing the Relational Algebra Tree (RAT) translated by the SQL parser, the application of this kind of object- oriented representation should be explored. In this paper, we will show you how to apply this technique to complicated scenarios. The application of Reverse Query Processing and Reverse Manipulate Processing related to this issue will be discussed.

Numerical Simulation of Transient Gauss pulse Coupling through Small Apertures

Abstract: Transient electromagnetic pulse (EMP) can easily couple into equipments through small apertures in its shells. To study the coupling effects of transient Gauss pulse to a cubic cavity with openings, coupling course is simulated using sub-gridding finite difference in time domain (FDTD) algorithm in this paper. A new grid partition approach is provided to simulate each kind of apertures with complex shapes. With this approach, the whole calculation space is modeled, and six kinds of aperture with different shapes are simulated. Coupling course is simulate in the whole time domain using sub-gridding FDTD approach. Selecting apertures with dimension of several millimeters to research, coupled electric field waveform, power density and coupling coefficient are calculated. The affect on coupling effects by varied incident angle and varied pulse width are also analyzed. The main conclusion includes interior resonance phenomenon, increase effect around rectangle aperture and several distributing rules of coupled electric field in the cavity. The correctness of these results is validated by comparing with other scholars' results. These numerical results can help us to understand coupling mechanism of the transient Gauss pulse.

Research on temperature field and temperature stress of prestressed concrete girders

Abstract: This paper introduces the establishment and simplification of the temperature field and the general calculation method of temperature stress of the prestressed concrete box girders. Three kinds of sunshine temperature gradient models were loaded to a real bridge respectively, and got stress and displacement curves. Research data of several prestressed concrete box girders were selected from different regions of China to compare the relative error of the calculated and measured value. We indicate that the study of temperature field and thermal stress of prestressed concrete box girders is necessary, and will help engineers to solve the problem in structure design.

Speed up linear scan in high-dimensions by sorting one-dimensional projections

Abstract: High-dimensional indexing is a pervasive challenge faced in multimedia retrieval. Existing indexing methods applying linear scan strategy, such as VA-file and its variations, are still efficient when the dimensionality is high. In this paper, we propose a new access idea implemented on linear scan based methods to speed up the nearest-neighbor queries. The idea is to map high- dimensional points into two kinds of one-dimensional values using projection and distance computation. The projection values on the line determined by the first Principal Component are sorted and indexed using a B + -tree, and the distances of each point to a reference point are also embedded into leaf node of the B + -tree. When performing nearest neighbor search, the Partial Distortion Searching and triangular inequality are employed to prune search space. In the new search algorithm, only a small portion of data points need to be linearly accessed by computing the bounded distance on the one-dimensional line, which can reduce the I/O and processor time dramatically. Experiment results on large image databases show that the new access method provides a faster search speed than existing high-dimensional index methods.

Sensitive Data Protection Based on Intrusion Tolerance in Cloud Computing

Abstract: Service integration and supply on-demand coming from cloud computing can significantly improve the utilization of computing resources and reduce power consumption of per service, and effectively avoid the error of computing resources. However, cloud computing is still facing the problem of intrusion tolerance of the cloud computing platform and sensitive data of new enterprise data center. In order to address the problem of intrusion tolerance of cloud computing platform and sensitive data in new enterprise data center, this paper constructs a virtualization intrusion tolerance system based on cloud computing by researching on the existing virtualization technology, and then presents a method of intrusion tolerance to protect sensitive data in cloud data center based on virtual adversary structure by utilizing secret sharing. This system adopts the method of hybrid fault model, active and passive replicas, state update and transfer, proactive recovery and diversity, and initially implements to tolerate F faulty replicas in N=2F+1 replicas and ensure that only F+1 active replicas to execute during the intrusion-free stage. The remaining replicas are all put into passive mode, which significantly reduces the resource consuming in cloud platform. At last we prove the reconstruction and confidentiality property of sensitive data by utilizing secret sharing.

Simulation of Airflow Distribution of Parallel-Type Electrostatic Fabric Filter in Coal-fired Power Plant

Abstract: This paper introduces the status of parallel-type Electrostatic Fabric Filter was researched, and the factors influencing collection efficiency were analyzed in this paper. Using software Gambit, which also meshed the calculating region, a three-dimensional structure model of the precipitator was established. And then the numerical simulation of the air distribution characteristic was carried on with the software of fluent 6.2, which sets the boundary conditions, standard k-a 2-equation model and SIMPLE algorithm; Then draw the path line and contour chart of the cross-section, obtained the mean square deviation value, analyzed the airflow distribution situation and the reasons for why its uneven. By setting an appropriate opening rate for the airflow distribution plates and collection plates to improve the air distribution. The results show that the airflow distribution can be uniformed by improving the opening rate of the collection plates. The numerical simulation result is more reasonable and can be used as the reference of optimizing the structural design of Electrostatic Fabric Filter.

The Study of Joint Acoustic Holography Algorithms based on Continuous Scanning

Abstract: To effectively solve the problem of rapid measurement and recognition about large underwater sound source, continuous scanning is applied to measure the large underwater sound source. The theory of sound source recognition based on mobile framework technology (FAH)nd Helmholtz equation least squares method (HELS)s investigated. Combination of acoustic holography method based on MFAH and HELS is created and verified through simulation and basin test. The study shows that combination algorithm can accurately identify all kinds of underwater source and obtain a high positioning accuracy of the noise source, and can be used for a wide frequency range; when there are multiple coherent sound sources in the complex sound field, noise source identification and location only requires that an array holographic measurement surface is 1.3 times for the reconstruction surface. Using a small measuring surface to quickly identify large underwater sound source is achieved. The shortcomings of workload and time-consuming in the traditional measurement are resolved. And it provides convenience for engineering applications.