A study on the effects of education welfare action zone policy in Korea

This study was designed to analyze the effects of the support programs provided in education welfare action zones. Education welfare action zone policy came into effect by government from 2003 to guarantee actual educational opportunity to disadvantaged children in urban areas by providing educational, cultural, and welfare service. Education welfare action zones were selected in low-income group area in the metropolis. In this regard, both quantitative and qualitative analytical methods were used to ascertain the effects of the program. The qualitative analysis included a preliminary examination of conditions prior to the actual commencement of the program, which was then followed by an investigation of specific schools used, as case studies in order to identify the changes that had taken place during the program’s implementation process, and the program’s effect. Meanwhile, a quantitative analysis was employed to verify the actual changes that took place in several different aspects, changes that were revealed by the case studies.     

A cross-layer design approach on spectrum allocation and resource scheduling in cognitive PMP networks

We propose the spectrum allocation and resource scheduling algorithms in cognitive point to multipoint （PMP） networks with rapid changes of spectrum opportunities and present a media access control （MAC） protocol based on these algorithms. The objective of spectrum allocation is to make efficient use of the spectrum while maintaining the transceiver synchronization on frequency and time in the network. The objective of resource scheduling is to guarantee the quality of service （QoS） requirements of different kinds of connections and to minimize the total energy consumption in the network as well. By sensing only a small set of possible channels in each slot based on the state transition probability of each channel, our spectrum allocation algorithm achieves high spectrum efficiency in the network. The resource scheduling problem is divided into three sub problems and we derive optimal solutions to these problems by greedy algorithm and convex optimization. The simulation results show that our algorithm can make efficient use of the spectrum and the network resources at a cost of low computational complexity.     

Eccentricity and thermoviscous effects on ultrasonic scattering from a liquid-coated fluid cylinder

Calculation of the scattered field of the eccentric scatterers is an old problem with numerous applications. This study considers the interaction of a plane compressional sound wave with a liquid-encapsulated thermoviscous fluid cylinder submerged in an unbounded viscous thermally conducting medium. The translational addition theorem for cylindrical wave functions, the appropriate wave field expansions and the pertinent boundary conditions are employed to develop a closed-form solution in the form of infinite series. The analytical results are illustrated with a numerical example in which the compound cylinder is insonified by a plane sound wave at selected angles of incidence in a wide range of dimensionless frequencies. The backscattered far-field acoustic pressure amplitude and the spatial distribution of the total acoustic pressure in the vicinity of the cylinder are evaluated and discussed for representative values of the parameters characterizing the system. The effects of incident wave frequency, angle of incidence, fluid thermoviscosity, core eccentricity and size are thoroughly examined. Limiting case involving an ideal compressible liquid-coated cylinder is considered and fair agreement with a well-known solution is established.     

Bubble counter based on photoelectric technique for leakage detection of cryogenic valves

In order to overcome the inconvenience of manual bubble counting, a bubble counter based on photoelectric technique aiming for automatically detecting and measuring minute gas leakage of cryogenic valves is proposed. Experiments have been conducted on a self-built apparatus, testing the performance with different gas inlet strategies （bottom gas-inlet strategy and side gas-inlet strategy） and the influence of gas pipe length （0, 1, 2, 4, 6, 8, 10 m） and leakage rate （around 10, 20, 30, 40 bubbles/min） on first bubble time and bubble rate. A buffer of 110 cm^3 is inserted between leakage source and gas pipe to simulate the downstream cavum adjacent to the valve clack. Based on analyzing the experimental data, experiential parameters have also been summarized to guide leakage detection and measurement for engineering applications. A practical system has already been successfully applied in a cryogenic testing apparatus for cryogenic valves.     

Time-domain training sequences design for MIMO OFDM channel estimation

This paper describes a Least Squares （LS） channel estimation scheme for MIMO OFDM systems based on time-domain training sequence. We first compute the minimum mean square error （MSE） of the LS channel estimation, and then derive the optimal criteria of the training sequence with respect to the minimum MSE. It is shown that optimal time-domain training sequence should satisfy two criteria. First, the autocorrelation of the sequence transmitted from the same antenna is an impulse function in a region longer than the channel maximum delay. Second, the cross-correlation between sequences transmitted from different antennas is zero in this region. Simulation results show that the estimator using optimal time-domain training sequences has better performance than that using optimal frequency training sequence at low signal-to-noise ratio （SNR）. To reduce the training overhead, a suboptimal training sequence is also proposed. Comparing with optimal training sequence, it has low computation complexity and high transmission efficiency at the expense of little performance degradation.     

Reading Instruction for English Learners in the Middle Grades: a Meta-Analysis

This meta-analysis synthesizes the last two decades of experimental and quasi-experimental research on reading instruction across academic contexts (e.g., social studies, science, mathematics, English language arts) for English learners (ELs) in grades 4 through 8, to determine (a) the overall effectiveness of reading instruction for upper elementary and middle school students who are ELs and (b) how the magnitude of the effect varies based on student, instructional, and study characteristics. The analysis included a total of 11 studies with 46 individual effect sizes and yielded a mean effect size of g?=?0.35 across all (i.e., standardized and unstandardized) reading measures, g?=?0.01 across standardized reading measures, and g?=?0.43 across unstandardized reading measures. For all reading, unstandardized reading, all vocabulary, and unstandardized vocabulary measures, results suggest that higher quality studies tended to have smaller effects, and these effects were even more evident for unstandardized measures (i.e., one unit increase in study quality was associated with decreased effects: g?=?0.21, g?=?0.30, g?=?0.24, g?=?0.30, respectively). For all comprehension measures, effects were larger for instruction that included both vocabulary and comprehension (g?=?0.39) than for instruction that focused on vocabulary alone (g?=?0.08). Results suggest the benefit of developing and refining high-impact approaches to reading instruction for ELs that can be delivered across content areas and grades.     

Application of neural network in the study of combustion rate of natural gas/diesel dual fuel engine

In order to predict and improve the performance of natural gas/diesel dual fuel engine (DFE), a combustion rate model based on forward neural network was built to study the combustion process of the DFE. The effect of the operating parameters on combustion rate was also studied by means of this model. The study showed that the predicted results were good agreement with the experimental data. It was proved that the developed combustion rate model could be used to successfully predict and optimize the combustion process of dual fuel engine. Project supported by National Lab. for Automotive Engine and Safety, Tsinghua University, China     

Effects of 3D Printing Project-based Learning on Preservice Elementary Teachers’ Science Attitudes,Science Content Knowledge,and Anxiety About Teaching Science

3D printing technology is a powerful educational tool that can promote integrative STEM education by connecting engineering, technology, and applications of science concepts. Yet, research on the integration of 3D printing technology in formal educational contexts is extremely limited. This study engaged preservice elementary teachers (N?=?42) in a 3D Printing Science Project that modeled a science experiment in the elementary classroom on why things float or sink using 3D printed boats. The goal was to explore how collaborative 3D printing inquiry-based learning experiences affected preservice teachers’ science teaching self-efficacy beliefs, anxiety toward teaching science, interest in science, perceived competence in K-3 technology and engineering science standards, and science content knowledge. The 3D printing project intervention significantly decreased participants’ science teaching anxiety and improved their science teaching efficacy, science interest, and perceived competence in K-3 technological and engineering design science standards. Moreover, an analysis of students’ project reflections and boat designs provided an insight into their collaborative 3D modeling design experiences. The study makes a contribution to the scarce body of knowledge on how teacher preparation programs can utilize 3D printing technology as a means of preparing prospective teachers to implement the recently adopted engineering and technology standards in K-12 science education.