Earticle

In order to enhance or produce stochastic resonance (SR), to obtain the required output response with specific properties, two bistable systems based on fractional over-damped Langevin equation are coupled into one multi-steady-state system via nonlinear method, one fractional bistable system where inherent parameters can be controlled is fed into the other system, the kinetic characteristics of the new coupled system is found much richer than each single fractional system. Theoretical analysis and numerical simulation results show that the SR can be enhanced or produced by adjusting parameters as coupling coefficient, fractional system inherent parameters as well as the external periodical signal amplitude while another fractional system’s parameters fixed. The coupled system has high practical value, which provides a reliable theoretical basis for the control and its applications of artificially generated stochastic resonance.

A variable message signs is an electronic traffic sign often used on roadways to give travelers information about special events. However, a variable message signs has the different sizes and a specific type according to the city scene and it has to be displayed by different message on the display panels in real-time. And the variable message signs providers must produce the different products each order. In addition that, they should test and check the correct operation to each variable message signs product using different message frame. That is very time and workers consuming and automatic variable message frame generator system for variable message signs is necessary. In this paper, we design and implement an emulator system for variable message signs. The exact message size is decided when the message is generated. And the variable message generator can decide the exact message size using the difference between a given data size and a field of the data size. The system can be set several parameters easily on a window dialog which are necessary parameters for generating the variable message frame.

For dynamic mathematical model of permanent magnet synchronous motor (PMSM) applied in electric vehicles, to reduce the ripple of the speed of electric vehicles in the driving process and to improve anti-interference and fast tracking ability, control strategy based on fuzzy and auto-disturbances-rejection was proposed. The fuzzy part of the system instead of hysteresis comparator and selector switching table of the traditional DTC control, reduces the flux and torque ripple and earns superior performance. The active-disturbance-rejection (ADR) technology was applied to the speed controller to compensate system perturbation on real-time. The simulation results show that the controller based on fuzzy and active-disturbance-rejection have the advantages that flux linkage and torque ripples are small, the speed tracking is faster and steady precision is higher.

This paper developed the set-top box-typed hardware terminal which process data collected from heterogeneous sensors and RFID readers. The developed terminal can reduce expenses because it can process tag data of heterogeneous sensors and RFID readers as the integrated terminal which collect and process data and be provided with users by the method which support several client applications with requirements of various tag data. This study developed the hardware terminal that support of common data formats which are necessary for sophistication of data processing modules of various sensors, stabilization of communication modules, and status management was improved. It extracted the core function of the middleware which are commonly necessary for various typed USN application services.

The aim of this study is to extract water body using the integrated features of Landsat ETM+ and ALOS PALSAR data. Water body extracted from Landsat ETM+ tends to lose smaller water bodies like small rivers and ponds. Besides, water area with plant (lotus) is difficult to recognize. ALOS PALSAR data have a much higher resolution, capable of extracting almost all the water bodies without confusion with other surface features, but leave some holes in water bodies due to its speckles. As a consequence, there is a significant interest in the development of fusion methods that are able to take advantage of the complementary nature of Landsat ETM+ and ALOS PALSAR data. A new combination method of integrating band 3, band 7 of Landsat ETM+ with a modified HH polarization of ALOS PALSAR is proposed, which well combine the complementary water information from each source compared to the standard image fusion methods. Experimental outcomes of the proposed combination B37ModHH shows great enhancement in water classification accuracy compared to Landsat ETM+ and ALOS PALSAR alone.

This paper recognizes life environment risks which variously exist to guarantee safety of users from all kinds of risk factors that do in resident environment and suggests a plan to infer degree of risk. The artificial neural network theory which makes a great contribution to the artificial intelligence and data-mining fields detects risk factors through mechanical learning even in the environment that cannot in advance recognize them and provides clues of good methods to be able to evaluate the degree of risk of real-life situations. The risk factors which exist in each residential environment are not uniform and there are many cases that don't have single factors. It's the plan which can suppose high level of each risk factor and risk environment by handling these various and multiple risk factors. This paper includes the pre-clustering to the risk calculation using the artificial neural network. It was confirmed that the risk calculation using the artificial neural network could be improved through a pre-clustering of the input data.

Aiming at the refitted HAFEI hybrid electric vehicle (HEV), fuzzy logic energy management strategy is constructed based on genetic algorithm optimization. The difference value D between the total require torque Tr of path and the target required torque Te of engine, the intelligence quotient value with Tr is selected as the first input variable of fuzzy controller, the SOC of battery as the second input variable; torque control coefficient C is selected as output variable, meanwhile two input variable membership function is improved on genetic algorithm. To further evaluate the control strategy, dynamic programming control strategy is used as standard; the simulation experiments show that every kind of gas emission is obviously reduced by 12% to 47% in fuzzy control strategy B based on genetic algorithm optimization compared to strategy A based on determinacy rules. Compared to dynamic programming, fuel economy in strategy A is only 45.09% of standard value which is not ideal, the utilization of fuel is low and the gas emission is serious, while in strategy B fuel economy is 78.89% of standard value and effect is improved obviously.

Ubiquitous healthcare (uHealthcare) technology is emerging as a solution to increasing chronic disease patients with the advent of aging of society. uHealthcare improves accessibility to medical services but it increases probability of privacy violation of personal medical information. Recently, Huang et al. proposed an identity authentication and context privacy preservation in wireless health monitoring system. However, Lee et al. showed that their scheme has lack of data privacy consideration and not enough security system for physician. Thereby, this paper proposes an enhanced identity authentication and context privacy preservation to solve the problems mentioned in Lee et al. The proposed scheme uses smartcard for the additional authentication and easiness to keep secret values and encryption algorithms for the contextual privacy. Analysis demonstrates the security of the proposed scheme.

New voltage-based on-line fault detection and faulty switch identification algorithms under multiple open-switches in a grid-connected wind power converter are proposed in this paper. The proposed algorithms are based on the three-phase voltages which are calculated by using the DC link voltage and switching times determined from the space vector PWM scheme. From the calculated three-phase voltages, the absolute of average phase voltage and normalized three-phase RMS voltages are obtained to be used for the fault detection and faulty switch identification algorithms in three-phase AC/DC PWM converter. To determine faulty switches, three-phase voltages and RMS currents are taken as faulty switch localization variables. The complete diagnosis is carried out by a simple method during operation, which does not require any additional sensors. Therefore, the proposed methods are cost-effective and easy to use. To verify the validity and performance of the proposed algorithms, the simulation is carried out using the PSIM software for twenty-one cases of faults including multiple open-switches. As a result, the proposed scheme can effectively detect the occurrence of fault as well as faulty switches for these conditions independent of operating conditions.