Motivational profiles of learning multiple foreign languages

Second language motivation has been well-researched in SLA and has a consistent positive correlation with learning achievement, which is empirically supported by many studies in different contexts with different second languages (Masgoret & Gardner, 2003). However, except for a few recent studies (Dörnyei & Chan, 2013; Henry & Cliffordson, 2013), little is known about how motivation differs when learners attempt to study more than one foreign language simultaneously. This paper reports on how university students in Vietnam are motivated to learn both English and Mandarin. Conceptualizing motivation via the L2 Motivational Self System, proposed and validated by Dörnyei and other scholars, 154 Vietnamese university students were given a motivation questionnaire. Using both quantitative and qualitative profile analyses, the results generally indicated that students have different motivations for learning English and Mandarin

Stochastic control for optimal power flow in islanded microgrid

The problem of optimal power flow (OPF) in an islanded mircrogrid (MG) for hybrid power system is described. Clearly, it deals with a formulation of an analytical control model for OPF. The MG consists of wind turbine generator, photovoltaic generator, and diesel engine generator (DEG), and is in stochastic environment such as load change, wind power fluctuation, and sun irradiation power disturbance. In fact, the DEG fails and is repaired at random times so that the MG can significantly influence the power flow, and the power flow control faces the main difficulty that how to maintain the balance of power flow? The solution is that a DEG needs to be scheduled. The objective of the control problem is to find the DEG output power by minimizing the total cost of energy. Adopting the Rishel’s famework and using the Bellman principle, the optimality conditions obtained satisfy the Hamilton-Jacobi-Bellman equation. Finally, numerical examples and sensitivity analyses are included to illustrate the importance and effectiveness of the proposed model

Effects of BaSO4 nano-particles on the enhancement of the optical performance of white LEDs

The usage of BaSO4 nanoparticles on WLEDs luminous flux and color uniformity improvements have been analyzed and demonstrated in this manuscript. The mixture of BaSO4 and silicone placed on the yellow phosphor layer benefits the internal light scattering and thus enhances the angular correlated color temperature (CCT) homogeneity. Specifically, the blue-light intensity at large angles tend to increase and results in light intensity discrepancy, which can be corrected with added BaSO4. In addition to this, the BaSO4-silicone composite modifies the refractive index of the air-phosphor layer interface to an appropriate value, and thus, the luminous efficiency increases. The results show that the CCT deviations is reduced by 580 K, from 1000 K to 420 K, within the angle range from -700 to +700 with BaSO4 in the phosphor structure. The increase in luminous flux is also recorded by 2.25%, in comparison with that of the non-BaSO4 traditional structure, at the 120-mA driving current. Hence, integrating BaSO4 nanoparticles into the remote phosphor structure can contributes to the enhancement of both lumen output and CCT uniformity

A hybrid artificial neural network - genetic algorithm for load shedding

This paper proposes the method of applying Artificial Neural Network (ANN) with Back Propagation (BP) algorithm in combination or hybrid with Genetic Algorithm (GA) to propose load shedding strategies in the power system. The Genetic Algorithm is used to support the training of Back Propagation Neural Networks (BPNN) to improve regression ability, minimize errors and reduce the training time. Besides, the Relief algorithm is used to reduce the number of input variables of the neural network. The minimum load shedding with consideration of the primary and secondary control is calculated to restore the frequency of the electrical system. The distribution of power load shedding at each load bus of the system based on the phase electrical distance between the outage generator and the load buses. The simulation results have been verified through using MATLAB and PowerWorld software systems. The results show that the Hybrid Gen-Bayesian algorithm (GA-Trainbr) has a remarkable superiority in accuracy as well as training time. The effectiveness of the proposed method is tested on the IEEE 37 bus 9 generators standard system diagram showing the effectiveness of the proposed method

Minimize the load reduction considering the activities control of the generators and phase distance

This study shows how to calculate the minimum load that needs to be reduced to restore the frequency to the specified threshold. To implement this problem, the actual operation of the electricity system in the event of a generator outage is considered. The main idea of this method is to use the power balance equation between the generation and the load with different frequency levels. In all cases of operating the electrical system before and after the generator outage, the reserve capacity of other generators is considered in each generator outage situation. The reduced load capacity is calculated based on the reciprocal phase angle sensitivity or phase distance. This makes the voltage phase angle and voltage value quality of recovery nodes better. The standard IEEE 9-generator 37-bus test scheme was simulated to show the result of the proposed technique