Earticle

This paper analyzes the advantages of double breaks under series connection for 126kV HV vacuum circuit breaker. It makes efforts in the break designing to avoid hidden danger brought by voltage-sharing capacitor. Voltage is evenly distributed in the shape of ▽ at the basic break that asks for no voltage-sharing capacitors. Permanent magnetic actuator is used to ensure the synchronization of opening and closing of double breaks. Based on this layout, this paper designs a new actuator and motion system for vacuum circuit breaker optimized by virtual prototype software ADAMS and genetic algorithm. Laboratory tests have proved that the opening and closing speed of the breaker meets the speed standard and that the 126kV HV vacuum circuit breaker is feasible.

We propose quantum secret sharing scheme that emphasizes on the cooperation (twice) of communicating parties to avoid untrustworthy members and improves the strength of the key. The proposed scheme is a new approach in quantum secret sharing in which cooperation of the parties is emphasized at the same time the key is strengthened by performing a shift operation on the received partial keys. In this method, we have managed to achieve the following: security of the key is significantly enhanced; cooperation between parties is also increased (to two) and improved. This method shows that it is difficult for an eavesdropper to obtain the key easily. It is also hard for the communicating parties to cheat since key verification is done twice and if any member cheats, it can easily be identified and communication can be aborted immediately.

In reality, flame is a common fluid scene. In this paper, we simulated flame by using improved particle system and detail the properties and changes of particles in the model. We realized a realistic color change and dynamic flickering flame characteristics. We used texture mapping method to render the flame and used the hierarchical programming structure to provide a simple and practical interactive flame simulation. We also designed and implemented demonstration system of flame simulation. Experiments show that using the flame image generated in this paper can not only satisfy the visual effect but also meet the real-time requirements.

Recently, some unexpected disasters have been occurring and there are much more damages from unexpected disasters than expected. The reason is that there is no way to make an accurate estimate about damages from unexpected disaster. So, it is efficient way to make a plan to do a restoration work promptly. For this purpose, we have been doing research to develop a restoration manual and data-base system prepared for emergency situations. However, the study is not finished yet. There remain some related research processes to make the results more in-depth.

This thesis designs a new type of driving recorder, utilizing intelligent terminal as the client, driving recorder as a serve. In data processing, information display and data storage. Utilizing intelligent terminal such as a smartphone or tablet itself processor, a display and a memory card to replace the traditional corresponding feature of driving recorder. In the aspect of data transmission, utilize WIFI for information interaction between driving recorder and intelligent terminal, realizing wireless communications. Through the intelligent terminal to realize the data preview and playback function, driving recorder become more portable．

Integrated separate layer water injection technology is an effective approach to reduce the workload of injection oilfield. The primary equipment which consists of flowmeter, motor and control value is placed underground for a long time. Injection rate allocation fault diagnosis is a problem with character of multiformity. The fault symptoms and reasons are random, and it is hard to differentiate them. Weighted fuzzy C-means clustering algorithm combining symptoms signals and fuzzy mathematics approach is used on the technology. The algorithm is based on fuzzy C-means clustering algorithm, and increase weight to each fault sample to reduce the impact of samples on fault classifications. Simulation and analysis illustrates that the algorithm is able to reflect the real structure of the sample data. And it improves the accuracy of fault classification.

This study seeks to explore the effects of smart-based flipped learning activities on learners’ study achievement, self-directed learning, collaborative learning and information use ability. To achieve this study purpose, 112 6th-grade students in the elementary school P in Gympo-si, Gyeonggi-do South Korea were selected as this research experiment group (Flipped classroom based on smart-learning, and normal flipped learning) as well as the control group (traditional ICT-based class learning). They were examined for 11 weeks from the 2nd week of March to 2nd week of May, 2014. In the Flipped classroom based on smart-learning, the participants studied at home in advance with materials made by their teachers. Then, in class, they searched data instantly by using smart pads, used applications for learning or as a tool, and conducted online evaluation, etc. The normal flipped learning-based education group studied at home in advance with videos made by their teachers and, in class, they were instructed to focus on knowledge sharing among themselves and discussions. As a result, an effect on study achievement was found between the flipped learning and traditional ICT-based learning methods. And the smart-based flipped learning was found to have improved self-directed learning ability more than the general flipped learning and traditional ICT-based method. Collaborative learning ability and information use ability were found to be more improved with statistical significance in the smart-based flipped learning group than the other groups.

FAT (Fault tree analysis) of drying processing was performed to investigate the causes for faults in equipments management. The causes were deductively identified as the events causing every possible hazard by constructing a fault tree. The fault tree was constructed in a hierarchical structure with a single top event fault, four intermediate event faults, and eight basic event faults connected by a Boolean AND gate, or an OR gate. Qualitative analysis of the fault tree yielded minimal cut sets, structural importance, and common cause vulnerability. Quantitative analysis of the fault tree yielded simulation of final top event fault, cut set importance, item importance, and sensitivity. Basically, these factors were a measure to represent the priority order of the basic events causing the top event. The priority order of these basic events was consistent between qualitative and quantitative analysis. Therefore, the FTA, with qualitative and quantitative analysis, was a good alternative approach to fault analysis in spray dryer, and it also could be further used to the analysis of critical control points..

It is high time that state, local government, public institution, company and people should establish a new paradigm in order to overcome water shortage due to global population growth, urbanization and climate change etc. This means that we should establish strategies for water management in a dimension of securing state competitiveness of a dynamic force for new growth as well as prevention of disaster through integrated smart water management, turning away from passive defense strategy to water crisis. Smart Water Management that refers to implement intelligent water information systems by IT convergence is considered a new paradigm. Smart Water Grid (hereinafter “SWG”) is the core of this water management policy. In this paper, we try to study the Smart Water policy, especially SWG, and legislation development trends in major advanced countries such as U.S.A., EU, Singapore, Australia and Japan etc. In the conclusion, we suggest a proposal for structuring a legal framework of SWG in an era of climate change.

In this paper, the problem of power control for cognitive systems is studied via game theory. The objective is to maximize the sum utility of secondary users (SUs) subject to the primary users (PUs) interference constraints, the transmission power constraints of SUs, and the signal-to-interference-plus-noise ratio (SINR) constraint of each SU. In our earlier work, the problem was formulated as a non-cooperative game under the assumption of perfect channel state information (CSI). Nash equilibrium (NE) is considered as the solution of this game. A distributed algorithm is proposed which can converge to the NE. Due to the limited cooperation between the secondary base station (SBS) and the PU, imperfect CSI between the SBS and the PU is further considered in this work. The problem is formulated as a robust game. As it is difficult to solve the optimization problem in this case, existence of the NE cannot be analyzed. Therefore, convergence property of the sum utility of SUs will be illustrated numerically. Simulation results show that under imperfect CSI the proposed approach can converge to a locally optimal transmission power level, while the sum utility of SUs converges with the increase of the transmission power constraint of SUs.

The alongside replenishment scheduling problem with time constraint determining the partition of the ships, the order of replenishment and the allocation of time to the ships at the same time is analyzed. It is equivalent to a multi-stage flow shop scheduling problem with the object of maximizing the effectiveness value of ship fleet. The problem solving process is divided into three steps, and based on the analysis of the three steps, a heuristic algorithm is proposed. The algorithm firstly considers the time allocated to each ship, and then sequences the ships by heuristic rule combining greed with insertion, finally determines the ships partitioning to the port and standard side. Emulating example with different problems’ scale and time constraints shows that the proposed heuristic algorithm is superior to some other algorithms.

Now a days, each and everything in our life demands the characteristic of being real time. Traffic control is a challenging issue in our daily life and it always requires to be modified to cope with real time demand. Ongoing systems have limitation because these have fixed time interval for providing signal as well as non-systematic way of signal time manipulation which does not provide the flexibility to readjust the system according to the changing situation. More over choice of an appropriate algorithm is not suitable always to control the system with variety of time. Considering these facts we have proposed a traffic management system with a modified process scheduling algorithm. For the betterment of traffic management, we actually proposed a modified round-robin algorithm in this paper. To verify it’s appropriateness virtually, a simulation environment is developed in JAVA. We considered variety of input and calculated average waiting time, variance and standard deviation of waiting time as performance metric for selecting the most suitable scheduling algorithm. The performance of existing process scheduling algorithms and modified round-robin are evaluated and compared. Finally, the simulation results show that the proposed modified round-robin algorithm is better adaptable to design an intelligent traffic control system.

Guidance of unmanned aerial vehicle (UAV) in three-dimensional space was studied in this paper. We designed a three-dimensional fuzzy neural network guidance law with the fuzzy rules of Takagi-Sugeno that based on proportional guidance principle and put the characteristics of the fuzzy neural network control into use. We decomposed the 3-D tracking trajectory into two two-dimensional planes and guided respectively, and took the influence of target mobility for guidance trajectory into consider. The design of guidance law was using the principle of proportional guidance, based on the Takagi-Sugeno type fuzzy inference, we took horizontal line of approaching velocity of missile-to-target, vertical line of sight angle velocity and sight angle velocity as inputs of fuzzy neural network, and yaw and pitch acceleration commands of UAV are the outputs, then we simulated the seeker tracking process against the target doing uniform motion in a straight line, curve movement and uniform circular motion respectively for UAV. Verified by simulation in this paper, the effect of the design of guidance law is ideal, and the proposed law is superior to the others and has good effect in response to the maneuvering target, and guidance trajectory is smoother.

The ability to detect taxis, pedestrian walk symbols, zebra crossings, and straight line tactile guide paths and junctions is essential for blind people in any city. This work applies a novel method that detects automatically these five targets via their colors, geometric elements and structural features. To reduce processing time, this method is tailored to low-resolution images that are roughly 80 x 60 pixels. Additionally, another novel method based on the Hough Transform can recognize straight lines, an important geometric element, in low-resolution images. The effectiveness and efficiency of the proposed method are validated experimentally.

Based on a set of reaction-diffusion equations of oxygen, glucose and growth inhibitory factor which were built to describe the tumor growth environment, a cell cycle control factor was proposed for the simulation of the avascular tumor growth. In order to fix the model parameters, a two-level heuristic searching was given for the parameter selection. Finally, a total finite element energy equation was present to combine the chemical simulation and the physical simulation for the avascular tumor growth. Experimental results showed that the presented approach outperformed the baseline approach in the simulation of the mouse mammary tumor cells EMT6/Ro.

To improve the reliability of hydraulic systems, a fault diagnosis approach based on radial basis function (RBF) networks was proposed in this paper. According to the target fault features extracted from a fuzzy auto-regressive with extra outputs (FARX) model, RBF networks serve as a fault classifier and the output of the RBF networks is the result of fault diagnosis. Several typical faults of hydraulic systems were used to test the fault diagnosis approach. Experiment results showed that the fault diagnosis approach is feasible and effective for improving the reliability of hydraulic systems.

Generally speaking, Vehicular Ad hoc Networks comprise vehicles and roadside stations as the common types of nodes. These nodes are mainly providing each other with relevant information. A wide range of applications are supported by Vehicular Ad hoc Networks such as file downloading, or access to the Internet with lack of resource controlling. These challenging resource managements degrade the network performance and create competitive environments. Through this paper, we introduce a novel algorithm for bandwidth sharing enhancement in both vehicle-to-vehicle and vehicle-to-roadside communications. We aim to improve the bandwidth usage based on coalition formation game in order to reduce the cost paid by vehicles for bandwidth reservation at roadsides. Mainly, we intend the enhancement of both individual vehicles’ payoff along with the whole network gain. Simulation results have proven that the proposed algorithm succeed to analyze this conflicting situation efficiently. In addition, satisfaction rates up to 75% have been achieved with an incredibly increase in the network throughput.

In order to solve dynamic path planning problem of multi-robot systems in unknown dynamic environment, a kind of method based on fuzzy and behavior control idea was proposed in this paper. This method designs two fuzzy controllers, which are danger degree fuzzy controller and velocity fuzzy controller. They took fully into account the position and the velocity of the obstacle and the azimuth of the target. Fuzzy rules were designed based on behavior control idea and which reflected move-to-goal behavior, avoid-obstacle behavior and follow-obstacle behavior. The experimental results show that the proposed method is feasible and valid and is suitable for the dynamic and complicated environment in particularly.

The artificial intelligence techniques are widely applied to many works of engineering. This paper presents the application of the artificial intelligence techniques to identify the AC-DC power system parameters. The DC-link filters are normally included in such power systems. For some applications, accurate DC-link filter parameters are very important for the system analysis and design. According to the measurement errors and a large variation in a capacitor value, the parameter identification is needed to provide the accurate parameters. Therefore, the paper presents the identification of DC-link filter parameters using the adaptive tabu search technique and the genetic algorithm. The experimental results from the testing rig and the averaging model of the system are used in the searching process. The identification results show that the accurate DC-link filter parameters including line parameters on the AC side can be easily obtained via the proposed method. Moreover, the resulting parameters are very useful for a stability analysis of the power electronic systems due to a constant power load.

Based on the structural features of electric vehicle (EV) driven by in-wheel motors and the characteristics of low speed as well as high torque for in-wheel motors, regenerative braking method for in-wheel motors has been presented. All braking torque for vehicle deceleration is output by in-wheel motors under Medium-intensity braking condition for the sake of recovering the maximum braking energy. The vehicle dynamics model that includes the hydraulic braking system and in-wheel motors driving system has been built by AMESim software. Simulation has been carried out for vehicle driving conditions by NEDC cycle and FTP75 cycle. The result shows that the recovery rate of braking energy is increased dramatically by in-wheel motor braking method. The energy efficiency of electric vehicle has been improved more than 30%. It is significant for electric vehicles to increase driving range and reduce costs.

This paper presents an analysis method aiming at UAV cooperative detection problem. The UAV detect the target and establish the state information respectively, and send the message to the adjacent friendly aircraft. The friendly aircraft judge if there are repetition between their own information and the message they have received after they receive the message, and re-order the target till the state information of all UAV are same and complete the mission of multi-UAV distributed cooperative detection. The simulation shows that the algorithm presented in this paper could accomplish the cooperative detection mission effective and reasonable.

RFID authentication on large numbers of tags or tag groups has attracted many researchers’ attention as an extension of initial one-or-two-tags scenarios. Due to demands of RFID application in supply chain, various proofs are proposed in the purpose of solving existing problems of grouping tags identification. However, it is proved that verifiers in these proofs are not aware of abnormal relating devices instantly, which may cause both security and technical risks and lie heavy upon identification of the problematic tags and readers. In this paper, we propose an enhanced grouping proof for multiple RFID readers and tag groups, according to which the verifier is able to cope with multiple readers and tag groups simultaneously and know the detailed status of the problematic tags. In addition, privacy protection is provided by offering mutual authentication between the readers and tags. Moreover, it is hard for the malicious tags to pass the verification in the proposed proof.

In this paper, we propose an algorithm to solve handover problems in heterogeneous wireless networks. Many previous studies concentrated on the lower level layer to solve handover problems. In this paper, we concentrate on high level handover problems such as network and transport layers. We solve handover problems of the transport layer in a heterogeneous wireless networks and propose a Freeze DeadLine (FDL) algorithm for better performance. The proposed method is analyzed from a theoretical perspective and is verified using the Network Simulator– 2.

Aiming at short endurance mileage for electric vehicle, effected vehicle life because of battery excessive charging and discharging, the control method is put forward making use of super-capacitor to recovery regenerative braking energy, Hafei-Saibao electric vehicle is as example，seven kinds of topology with composite energy-single load are researched on power consumption, and the force condition of front and rear wheels is analyzed for front driving vehicle，the required energy of front wheel is detected to develop control strategy. On the basis of experimental data, co-simulation is achieved in the vehicle special simulation software, the experimental results show endurance mileage of improved car has increased by 34%, endurance mileage after being charged is 243 kilometer, the per hundred kilometers consumption has been decreased to 7.5 kW.h from 12 kW.h, the electrical consumption has been decreased by 37.5%, and the full load characteristics is optimized.

Location estimation (LE) is important in Ubiquitous Computing Environments (UCE). For positioning application, Global Positioning System (GPS) and Received Signal Strength (RSS) from Access Pointer (AP) using LE is increasingly popular choice especially after pervasive adoption of IEEE 802.11 Wireless Sensor Networks (WSN). Fundamental requirement of such LE is to estimate location from RSS at a particular location. Multi-Path Fading Effects (MPFE) make RSS to fluctuate in unpredictable manner, introducing uncertainty in LE. Moreover, in practical situations, RSS values RF Signal (RFS) from AP are not available at some locations all the time making the problem more difficult. To deal with this problem, machine learning techniques have been applied so that the carried along devices can learn and make decision where they are in the building, especially. Recent machine learning techniques remain many unsolved problem such as high cost of computation, high complexity of model structures and scalability. In this paper, we will introduce a few methods which give high accuracy and overcome other methods’ disadvantages, such as Support Vector Machine (SVM), Push Pull Estimation (PPE), and Modular Multi-Layer Perceptron (MMLP) with Neural Networks (NN) using RFS from AP.

The archwire bending is one of processes the most frequently used in the orthodontic treatment. Furthermore, the springback of sheet metal, which is defined as elastic recovery of the part during unloading, should be taken into consideration so as to produce formed archwire within acceptable tolerance limits. In this paper, the springback angle of different alloy archwires (including NiTi alloy wire, Beta-Ti alloy wires, Chinese stainless steel wires, and Australian stainless steel wires) were performed by the theoretical calculation based on large deformation theory and the finite element analysis. A series of numerical simulations has been conducted for the bending test, which physically simulates the actual bending of alloy archwire with a robotic apparatus. The finite element analysis of springback is shown to be very consistent with the theoretical calculation results.

Design of complex mechanical equipment and scheme of manufacturing need a comprehensive consideration of constraints, and it embodies multiple layers, complexity, multiple types and uncertainty. This paper analyzes the question of scheme optimization for complex mechanical equipment and proposes a method of manufacturing scheme optimization for complex mechanical equipment based on multi -attribute fuzzy information measurement model. This method functions to build an indicator system of optimization scheme for manufacturing complex mechanical equipment. Three models are designed to evaluate all optimization indicators the system, namely model for computation of fuzzy interval indicator’s information quantity, model for computation of qualitative indicator information quantity and model for computation of fuzzy indicator’s information quantity with degree of membership. Weights are given to information quantity optimization indicators in different layers get total complex mechanical equipment scheme choose optimal strategy based on design manufacture.

With the advances of IT technology, the interest in smartwork is increasing by using various mobile devices through Internet services at anytime and anywhere. The introduction of smartwork to a company provides business efficiency, improves productivity and reduces costs, but security researches are required to solve a variety of security issues in it. For the secure user authentication, Won proposed a user authentication method using NFC in smartwork environment. However, this paper shows that Won’s method has some security problems, including weak against stolen verifier attack and replay attack and lack of message integrity, and proposes a new NFC based user authentication mechanism to solve the problems. The proposed mechanism could be used as a security building block in various smartwork environments including telework, mobile office, and so on.

A method of object recognition for objects with special topological structure is developed based on top-hat transformation for service robot. The objects with four legs are easily detected and recognized by service robot with laser ranger array by this method. First, the top-hat transformation in one dimension is reviewed, then the recognition strategy of self-adapting threshold for objects with special topological structure is proposed, and the general data process for object recognition and position is proposed and analyzed. Experimental results show that the process of object recognition based on top-hat transformation proposed in this article is an effective and accurate application.

The multi degrees of freedom actuator is an important joint, which has attracted worldwide developing interests for its medical, industry and aerospace applications. This paper addresses the problem of trajectory tracking of three dimensions joint in the presence of model uncertainties and external disturbances. An adaptive fuzzy sliding mode controller (AFLSMC) is proposed to steer a three dimension joint along a desired trajectory precisely. First, the dynamics model of a three dimension joint is formulated and the trajectory tracking problem is described. Second, a sliding mode controller (SMC) is designed to track a time-varying trajectory. The fuzzy logic system (FLS) is employed to approximate the uncertain model of the three dimension joint, with the tracking error and its derivatives and the commanded trajectory and its derivatives as FLS inputs and the approximation of the uncertain model as FLS output. And a fuzzy logic system is also adopted to attenuate the chattering results from the SMC. The control gains are tuned synchronously with the sliding surface according to fuzzy rules, with switching sliding surface as fuzzy logic inputs and control gains as fuzzy logic outputs. The stability and convergence of the closed-loop controller is proven using the Lyapunov stability theorem. Finally, the effectiveness and robustness of the proposed controller are demonstrated via simulation results. Contrasting simulation results indicate that the AFLSMC attenuates the chattering effectively and has better performance against the SMC.