Earticle

A bottle up hyperbox granular computing (HBGrC) is developed based on distance measure. Firstly, hyperbox granule is represented by the beginning point and the end point. Secondly, the distance measure between two hyperbox granules is defined by the beginning points and the end points. Thirdly, operations between two hyperbox granules are designed to the transformation between two hyperbox granule spaces with different granularities, HBGrC is developed by the join operator and the user-defined granularity threshold  on the basis of bottle up scheme. Experimental results shown that HBGrC achieved the better testing accuracies over the machine learning benchmark datasets.

Image segmentation has received extensive attention due to the use of high-level descriptions of image content. This paper proposes a fault diagnosis model using a Gabor filter on segmented two-dimensional (2D) gray-level images. The proposed approach first converts time domain AE signals into 2D gray-level images to exploit texture information from the converted images. 2D discrete wavelet transform (DWT) is then applied to select appropriate (vertical) texture information and reconstructed it into an image. The reconstructed image is segmented into a number of sub-images depending on the segment size and a Gabor filter is applied on each sub-image. Finally, feature vectors are extracted from the Gabor-filtered sub-images and utilized as inputs in a one-against-all multiclass support vector (OAA-MCSVM) to identify each fault in an induction motor. In this study, multiple bearing defects under various segment sizes are utilized to validate the effectiveness of the proposed method. Experimental results indicate that the proposed model outperforms conventional Gabor-filter-based 2D fault diagnosis algorithms in classification accuracy, exhibiting a 97 % average classification accuracy for 64×64 segmented images.

Tracking and stabilization are two typical problems of chaotic system control. A unit error model is built for the above both two problems and a kind of adaptive control is designed to solve a special kind of system uncertainty. The uncertain nonlinear function. Is not required to be bounded compared with a known smooth positive function. Also a kind of approximation method is proposed for nonlinear functions based on Fourier series method. At last, a four dimension chaotic system is taken as an example to do the numerical simulation to testify the rightness of the proposed method.

Maintaining phosphoric slurry within the optimal temperature range is of great significance in improving the quality of the phosphoric acid product. Due to the lack of integral parts and the limited number of expert rules, general fuzzy controllers are commonly incapable of achieving accurate output. This paper proposed a novel fuzzy controller based on variable universes of discourse (VUD) to improve the accuracy of the temperature of phosphoric slurry. By tuning the motorized motor in the vacuum pump, the controller can obtain an appropriate vacuum degree in flash evaporators. With the online operation of contraction-expansion factors, fuzzy rules can be reproduced online, which is equivalent to the densification of fuzzy sets on universes of discourse. Thus, the output accuracy of VUD fuzzy controllers can be enhanced significantly. The experimental results show that VUD fuzzy controllers can tune the temperature of phosphoric slurry to within the optimal range and have a much better effect than general fuzzy controllers.

Recently, there is a growing IoT(Internet of Things) service using sensors for environmental monitoring and actuators for reacting to environmental changes. Sensor networks have provided us with facilities to collect information and track certain phenomena in the physical environment based on the region of interest. Sensor networks consist of a collection of sensor nodes and a sink node for many applications in different areas, including environmental surveillance, intelligent building, health monitoring, intelligent transportations, etc. In this paper, we present a sensor service provider for integration of heterogeneous large-scale sensor networks. This paper focuses on the design and implementation of the open sensor service provider for the integrated multiple sensor middleware in heterogeneous sensor networks. This provider has various heterogeneous sensor middleware, and each sensor middleware has a sensor networks. We design the sensor service provider using sequence diagram and state diagram, and implement it based on .Net framework. The sensor service provider has the service interface, the sensor content service manager, the sensor service manager, the sensing service manager, and the service controller, etc. The provider supports comprehensive to carry out the context acquisition and provisioning functionality.

A family of independent-regulation multiple-output (IRMO) dc-dc flyback converters was researched in this paper, and its control in discontinuous conduction mode (DCM) was achieved by using pulse-train (PT) control method. To avoid cross-regulation between each output of multiple output flyback converters, time-multiplexing scheme is used to determine which output is controlled in the time interval of time-multiplexing signal. Error amplifier and corresponding compensators as required by conventional pulse width modulation (PWM) technique were not used in PT control. The multiple output flyback converters with PT control proposed in this paper is simple and enjoys fast dynamic response. It can achieve constant voltage output, and can also achieve constant current output, which provides an effective solution for multiple constant current output application, especially in LED backlight application.

In this work an adaptive sliding mode controller in the presence of uncertainty, as well as the external disturbance is considered. A concise introduction and investigation of the dynamic behavior of a novel class of chaotic systems with fractional order derivatives for synchronization is presented. It is supposed that the high bounds of uncertainty and external disturbance are unknown. The proposed controller is designed based on error dynamics and acceptable adaptive laws. The sliding mode dynamic stability and the condition to start sliding are proved by Lyapunov stability theory. With this new proposed approach, Chen and Lorenz system with fractional order derivatives are synchronized. Finally, simulation results with MATLAB software showed that the designed comparative sliding mode controller was able to synchronize chaotic systems with fractional order derivatives in the presence of the mentioned adverse factors. The main characteristic of the proposed method compared to other methods is providing acceptable adaptive laws for satisfactory functioning against uncertainty and external disturbance and eliminate the chattering phenomenon for synchronization of non-identical chaotic systems with fractional order derivatives.

This paper addresses the trajectory tracking problem of underactuated autonomous underwater vehicles (AUVs) in the presence of ocean currents on the horizontal plane. The tracking control problem is reduced the problem of stabilizing the nonlinear tracking error system to two separate problems. The backstepping technique is applied to design tracking controller, and the conditions of control gains are derived such that the AUV can track a reference AUV. Simulations results show the effectiveness of the proposed trajectory tracking controller.

The developing trend of Automotive Lightweight has brought about the application of High-Strength Steel sheet in the automotive body, but High-Strength Steel sheet has poor formability with cold stamping process, and the existing cold stamping process cannot fully meet the needs of high strength steel forming. The hot stamping technology of High-Strength Steel sheet is the effective method to solve the above-described problem. It can greatly shorten the tryout time of die, and can effectively solve some problems like discarding of die, unreasonable process, and poor forming quality etc. In this paper, mainly for the Thermo-Mechanical Coupling process of sheet metal, introduce the thermal field analysis of High-Strength Steel sheet, the interaction of deformation and temperature field, and the main steps of Thermo-Mechanical Coupling. And for the U Shaped part, built the Finite element model and set process parameters with software ‘Dynaform’. Simulated its forming process of Thermo-Mechanical Coupling with solver ‘LS-DYNA’. The changing temperature field, thickness, and thickness reduction rate were calculated. The results show that, Thermo-Mechanical Coupled Stamping Simulation is an effective method to forecast high temperature formability of High-Strength Steel Sheet.

Low-Emissivity Insulation has enclosed reflective air spaces between aluminum foils that have very low emissivity. The reflective air spaces are composed of optimum-sized air cells, which are enclosed by polyethylene foam. The critical difference between Low-Emissivity Insulation and conventional reflective insulation is the presence of a honey-comb structure formed from polyethylene that serves as the core material. Low-Emissivity Insulation has a foil surface emissivity of 0.04 with enclosed air cells between foils. Its core material is polyethylene foam with 35 times expansion, which is expanded to make air cells. The enclosed air cells with foil reduce convective and radiative heat transfer. To verify the high efficiency of Low-Emissivity Insulation, it was tested by an accredited laboratory designated by the Korean government. Comprehensive thermal transmittance tests were conducted for the Low-Emissivity Insulation of specimens of various thicknesses. The thicknesses of the specimens were 10, 20, 30, 40, 50, 60, 80, and 100mm. Based on the test results, its insulation-affecting factors were investigated using a trial-and-error method.

With the popularity of the Internet and improvement of information technology, digital information sharing increasingly becomes the trend. More and more universities pay attention to the digital campus, and the construction of digital library has become the focus of digital campus. A set of manageable, authenticated and secure solutions are needed for remote access to make the campus network be a transit point for the outside users. The VPN (Virtual Private Network) remote access solution of university library digital resources was proposed, two main ways to achieve the VPN were introduced, the realization of remote access to digital library resources based on SSL (Secure Sockets Layer) VPN system was elaborated. These measures can provide remote access to outside users, and can greatly improve the utilization of digital library resources.

Aiming at the problem of time delay in the networked control system, by using the nonlinear approximation of the fuzzy control algorithm，and Smith forecast compensation. A kind of controller based on fuzzy adaptive PID with new Smith predictor is presented. This controller is easy to be implemented. Then using Matlab/simulink simulation software, the simulation research on a DC motor is done, and the simulation result shows, compared with the traditional PID control and PID control with Smith predictor, the control algorithm based on the fuzzy adaptive PID with new Smith predictor can effectively improve the robustness and adaptability of the system.

The effect of maintenance activities on the component of a system could either be perfect or imperfect. A perfect maintenance implies that the condition of the component is as good as new while imperfect implies that its condition has improved to a certain degree. Real engineering system problems in this domain usually consist of components with varying maintenance policies; perfect and imperfect. It is usually easier to optimise or analyse a system when subjected to homogeneous preventive maintenance (PM) policy; either solely perfect or imperfect. This paper investigates the optimisation of a heterogeneous (both perfect and imperfect) PM policy by using respective evaluation models and establishing a variant of the non-dominated sorting genetic algorithm (NSGA) II for the problem.

Image segmentation is a fundamental and challenging problem in image processing and often a vital step for high level analysis. Being CV based models have the unsatisfactory segmentation results and inefficient curve evolution against weak boundary and intensity heterogeneous images because of the inappropriate initial contour and unbalanced using the local and global information of the image. Based on the study of the edges and local/global contrast of the image, in this paper, we proposed a stable active contour model of image segmentation. Firstly, a new automatic initial contour choosing algorithm has been proposed which may improve the evolution efficient to a large extent compare to the human chosen initial contour. Besides, this algorithm may also improve the accuracy of the segmentation regions. Secondly, based on the study of the local binary fitting (LBF) model, local/global information fitting (LGIF) model and edge-flow based active contour model, we proposed a gray and contrast guided active contour model. In this model, we use gray and contrast information of the image as a decision standard to balance the local and global information. Finally, based on the above two algorithms, we construct a new image segmentation framework. The experiments show that our algorithm is less dependent on the parameters compare to the other models. On the other hand, this algorithm may also improve efficient of curve evolution to a large extent. Extensive experiments on synthetic and real images are provided to evaluate our method, showing the segmentation of the blurry boundary and intensity heterogeneous images may achieve more accuracy results.

In this paper, we propose that when a random network graph model that prefers to close two-hop chains and transform them to triangles as part of link formation. We hypothesize that such a model would generate random network graphs with high clustering coefficients and a larger variation in node degree, compared to that of the well-known Erdos-Renyi (ER) model. We refer to the proposed model as two-hop neighbor preference (THNP)-model that prefers to pair a node with any of its two-hop neighbors rather than to an arbitrary node. The probability of link formation is still governed by the formulation used to generate links in the ER model. We observe the THNP-model to generate random network graphs wherein the clustering coefficient of a node decreases with increase in node degree (resembling closely to several of the real-world network graphs), and the graphs still exhibit a Poisson-style distribution for the node degree and path length.

This paper focuses on the controller parameterization method of H∞ control for switched dissipative Hamiltonian systems (SDHSs) via multiple Lyapunov functions (MLFs) and proposes an algorithm for solving parameters of the controller with symbolic computation. An important merit of the proposed parameterization method is that it is based on the explicit construction of Lyapunov functions, which avoids solving the Hamilton-Jacobi (HJ) equations (or inequalities), sufficient conditions for the solvability of the robust H∞ control problem are presented. A numerical example shows that the controller is effective to SDHSs and the proposed method is feasibility.

With the rapid development of computer and information technology, people are focusing on how to find valuable information from the vast contents quickly and efficiently. As a result, the search engine system is a solution to this problem. However, there are few relatively work done in access control for search engine system when security is a critical requirement for broader applications of the technology not only in the current but also in the future. In this paper, an architecture for enterprise security search engine based on role-based access control is presented, and based on this architecture the search engine system can not only crawl the documents from the controlled resource sites but also can return different searching results from the index database according to the user’s different identities and permissions for the same keywords. We believe that the proposed architecture is realistic and secure.

We consider a local stabilization problem of an uncertain equilibrium point existed in a nonlinear continuous-time system by a state-derivative feedback controller. In previous researches, it is investigated that the uncertainty of the equilibrium point results in nonzero steady-state control input so that a different equilibrium point is stabilized. Then, a feedback controllers with steady-state blocking zeros eliminate the dependence on the steady-state. In this paper, we focus on the class of state-derivative feedback control, and develop a design method for a dynamic state-derivative feedback controller with steady-state blocking zeros. The proposed controller can reject the dependence on the uncertainty of equilibrium points. Moreover, we illustrate the effectiveness of the proposed control method by the numerical example which is the stabilization problem of the uncertain equilibrium point. In addition, we show that the poles of the closed-loop system with the proposed dynamic controller can be assigned at the desired locations.

In this article, we present an improved resampling algorithm for particle filtering, which is based on partial resampling and residual resampling. This algorithm provides an approach to selectively carry out hierarchical resampling operations on three sets of particles divided by large, medium and small weights, and especially to do skip resampling for partial small particles with an adaptive interval M. Simulation results verify that the proposed algorithm could reduce the depletion problem, maintain a good diversity of particles and improve the accuracy of PF performance.

It is an undeniable fact that renewable energy is nearly infinite and pollution-free, and that the demand for it is increasing. What is important here is the conversion of this energy into a usable energy form. Among new renewable energy, ocean wave energy is highly efficient, with various routes to harvest this energy. A lot of research is still in process on wave energy. Also, as the wave surges in the ocean far away from the land, applications in fish farms or drill ships that are distant from land is also made possible. The purpose of this paper is to utilize Wells Turbine with enhanced efficiency. We examined the variation of produced electric power with Wells turbine’s different tip to hub ratio like 3:1 and 2:1. There was a noticeable distinction between 3:1 turbine and 2:1 turbine. We have examined the elements that influenced this outcome and how it affected the operation of the sensor node. The result of this research may be adopted in real marine environments, utilized in fish farms, and referred in research for reinforcing the structure of independent power plants.

Aiming at the compensation problem of random time-delay in networked control system, a new network time-delay compensation method based on improved fast implicit generalized predictive control (GPC) is proposed. The buffer is established respectively including the forward output, feedback input of controller and the input of actuator, the network induced time-delay is compensated, and it will avoid the control data transmission. Then an improved fast implicit generalized predictive control with differential effect is used for time-delay compensation. Simulation results demonstrate that the proposed method reduces the system regulation time and restrain the overshoot, has good compensation effect.

In order to improve the servo accuracy of hydraulic quadruped robot electro-hydraulic servo actuators during operation, the load characteristic of equivalent model of electro-hydraulic servo actuators with swing phase and support phase was analyzed, respectively, the compound control strategy including flow compensator, velocity compensator, internal model controller, and improved internal model controller was proposed, the dynamic performance of system was guaranteed by internal model controller, the accuracy was further improvement by improved internal model controller. The composite control strategy was verified by robot single leg test platform, the experiment results show that the deviation and phase lag of response curve with flow compensation, velocity compensation and internal model controller was less than ±5% and 18°, respectively, the value of phase lag can be further reduced to 7°by the improved internal model controller, and the efficiency of the proposed control strategy was verified.

This paper is based on a previous study on the temperature characteristics of thermal moxibustion for clinical trials. Moxa is one of Korea's traditional medical therapies, using thermal and chemical stimulations to cure and prevent diseases. Moxibustion is used by burning a pellet-like moxa cone put on the meridian and affected regions of the body, and the heat and products generated by burning triggers stimulations for treatment. As the previous study was about the quantification of traditional moxa cautery, this study developed a moxibustion apparatus for application to the experimental animal. The developed moxibustion apparatus enabled constant uniform heating by passing the temperature data of heater read through the K-type sensor to MCU by using RS485 communication. As a result, it was found that the temperature of the heater used in a moxibustion apparatus is 120℃; the uniform heat is passed in treatment temperature. It was also found that adjusting the duty rate can help pass the heat of various patterns.

In order to solve differential bome problem of traditional backstepping control method, this paper studies four different differential algorithms. An adaptive backstepping control method is designed for an uncertain second order system, then four kinds of different differential algorithms are integrated with the adaptive backstepping control strategy. Through comparing the control effect of four different differential algorithms, a conclusion can be made that the comprehensive effect of one order filtering differential algorithm is the best one among above four kinds of differential algorithms.

This paper addresses the problem that the inherently hierarchical nature of resource allocation is usually ignored in the research on multiple design projects. We propose a bi-level programming mathematical model to solve this problem and seek its approximately satisfactory solution with simulated annealing algorithm. A simple numerical example is presented to demonstrate the method. We wrote the article to propose a reasonable possible research direction and attract more interests in our engineering design community for the resource allocation in multiple design projects.

In order to solve the path planning problem about UAV attack multiple moving targets under dynamic environment, analytical method is proposed in this paper. Firstly, the Voronoi diagram method is used to create threat field, and the total planning cost is established. Then, the artificial potential field method and the dijkstra algorithm is improved and optimized respectively. For the track point outside the Voronoi diagram, the artificial potential field method is used to generate the local track. For the track point inside the Voronoi diagram, the dijkstra algorithm is used to track the moving target tracking along the side of Voronoi diagram, and the analytical method that UAV path planning method of moving target under dynamic environment is put forward. Finally, the simulation experiment is conducted, the result of simulation shows that the Voronoi diagram method can become complex airspace into division problems, the search space is reduced effectively, the time of planning is shorten, and the UAV real-time tracking and precision strikes against multiple moving targets can be resolved efficiently.

Today, Knowledge based systems are used for complex problem solving and are having number of successful applications. Fault diagnosis methodology is based on failure behavior and hardware of the unit under test. This methodology is considered for the present work. Fault diagnosis in a microprocessor based electronic circuit boards needs lot of empirical knowledge and expertise and is a true artificial intelligence problem. Present research work relates to artificial intelligence systems and more particularly to a fault diagnostic knowledge based system that infers a cause of failure in electronics circuit board. The basic components of systems are knowledge base, inference engine and user interface. The knowledge is represented using object-rule structures and inference mechanism is implemented using classes. Performance of object oriented approach and rule based approach is compared and diagnosed faults were validated by industrial experts.

Using ambient excited data under PMU measurements to identify the low frequency oscillation mode and oscillation modes parameter information corresponding, has good prospects in power system analysis and control. This article discusses the applicability by using the natural excitation technique (NExT) in conjunction with the eigensystem realization algorithm for low frequency oscillation modes identification, then introduced fuzzy C-means clustering algorithm to picked up the authenticity of the identified modal results automatically and improving the recognition accuracy. On the IEEE-11 and IEEE-68 bus test system numerical example shows that the proposed method has higher modal recognition ability and efficiency, and can meet the needs of online applications.

By taking full use of the temporal information of alarm message for quick and accurate diagnosis is very important. This paper presents an effective method for fault diagnosis, based on the time constraint fuzzy directed graph (TCFDG), in order to solve the cases of incomplete alarm information. An improved recognition algorithm is proposed which can effectively recognize misreports, missing messages and timing inconsistencies etc. And false alarms are filtered to overcome the deficiencies of incomplete alarm information, and to provide protection for the precise positioning of faults. Then, a reasoning method based on TCFDG is proposed, and use min operator and multiplication operator to determine the fault source, and use incidence matrix reduction method, reducing the dimension of the matrix, improved operational efficiency. Finally, a typical power system compared with some other typical methods was shown for demonstrating the feasibility and efficiency of the proposed method.

A flight simulator is usually developed to verify the operations of aircraft and train the pilot through it. For this goal, it is necessary to include a variety of functions that work in real-time way. However, due to a huge volume of terrain data, graphic rendering speed becomes slow whenever additional computing processing is demanded. To address this problem, in this paper, we propose two techniques to speed up rendering speed for new flight simulator under our software architecture and module. Both hybrid cloud effect and adaptive culling scheme are proposed and implemented by OpenSceneGraph(OSG) library on Windows. Through diverse experimental results to verify their suitability, we demonstrate that acceptable rendering speed is maintained or enhanced without regard to additional computing overhead.