“拒绝”与“回绝”语义对比分析

以现代汉语同义词“拒绝”与“回绝”为研究对象,运用语义特征分析法和三个平面语法理论,从动作行为、行为主体对象、行为连带对象三个方面,对二者进行全面系统的语义对比分析,揭示其中的同与异。为今后的对外汉语教学提供有益的参考,帮助留学生掌握其基本用法,减少使用偏误。

Quasi-Static Energy Recovery Logic with Single Power-Clock Supply

This paper presents a new quasi-static single-phase energy recovery logic （QSSERL）, which unlike any other existing adiabatic logic family,uses a single sinusoidal supply-clock without additional timing control volta- ges. This not only ensures lower energy dissipation, but also simplifies the clock design, which would be otherwise more complicated due to the signal synchronization requirement. It is demonstrated that QSSERL circuits operate as fast as conventional two-phase energy recovery logic counterparts. Simulation with an 8bit logarithmic look- ahead adder （LLA） using static CMOS,clocked CMOS adiabatic logic （CAL,an existing typical single-phase ener- gy recovery logic）,and QSSERL,under 128 randomly generated input vectors,shows that the power consumption of the QSSERL adder is only 45% of that of the conventional static CMOS counterpart at 10MHz, and the QS- SERL adder achieves better energy efficiency than CAL when the input frequency finput is larger than 2MHz.

Characterizing pressure fluctuation into single-loop oscillating heat pipe

The pressure characteristics inside single loop oscillating heat pipe （OHP） having 4.5 mm inner diameter copper tube with the loop height of 440 mm were addressed. Distilled water was used as working fluid inside the OHP with different filling ratios of 40%, 60% and 80% of total inside volume. Experimental results show that the thermal characteristics are significantly inter-related with pressure fluctuations as well as pressure frequency. And the pressure frequency also depends upon the evaporator temperature that is maintained in the range of 60-96 ℃. Piezoresistive absolute pressure sensor （Model-Kistler 4045A5） was used to take data. The investigation shows that the filling ratio of 60% gives the highest inside pressure magnitude at maximum number of pressure frequency at any of set evaporator temperature and the lowest heat flow resistance is achieved at 60% filling ratio.

A Quantitative Structure Property Relationship for Prediction of Flash Point of Alkanes Using Molecular Connectivity Indices

Many structure-property/activity studies use graph theoretical indices, which are based on the topological properties of a molecule viewed as a graph. Since topological indices can be derived directly from the molecular structure without any experimental effort, they provide a simple and straightforward method for property prediction. In this work the flash point of alkanes was modeled by a set of molecular connectivity indices （Х）, modified molecular connectivity indices （ ^mХ^v ） and valance molecular connectivity indices （ ^mХ^v ）, with ^mХ^v calculated using the hydrogen perturbation. A stepwise Multiple Linear Regression （MLR） method was used to select the best indices. The predicted flash points are in good agreement with the experimental data, with the average absolute deviation 4.3 K.

Short Term Wind Power Prediction Using Wavelet Transform and ARIMA

A sustainable production of electricity is essential for low carbon green growth in South Korea. Although wind energy is unlimited in potential, both intermittency and volatility should be tackled for smart grid integration in future. To cope with this, many works have been done for wind speed and power forecasting. It is shown that statistical techniques are useful for short-term forecasting of wind power. This paper presents a statistical wind speed forecasting. The wavelet decomposition is employed as a de-noising technique. An illustration will be given by real-world dataset. According to the result, the MAD （mean absolute deviation） is improved as much as 10%.

A new group contribution-based method for estimation of flash point temperature of alkanes

Flash point is a primary property used to determine the fire and explosion hazards of a liquid. New group contribution-based models were presented for estimation of the flash point of alkanes by the use of multiple linear regression(MLR)and artificial neural network(ANN). This simple linear model shows a low average relative deviation(AARD) of 2.8% for a data set including 50(40 for training set and 10 for validation set) flash points. Furthermore, the predictive ability of the model was evaluated using LOO cross validation. The results demonstrate ANN model is clearly superior both in fitness and in prediction performance.ANN model has only the average absolute deviation of 2.9 K and the average relative deviation of 0.72%.

RANDOM WEIGHTING METHOD FOR CENSORED REGRESSION MODEL

Rao and Zhao (1992) used random weighting method to derive the approximate distribution of the M-estimator in linear regression model.In this paper we extend the result to the censored regression model (or censored “Tobit” model).

Retracts, fixed point property and existence of periodic points

Let X be a metric space, f∈ C0(X), and V X. The set-trajectory ( V, f( V),…,fn(V)) is investigated and some conditions for f to have periodic points with given periods are obtained.

Nonadiabatic acceleration of plasma sheet ions related to ion cyclotron waves

The nonadiabatic acceleration of plasma sheet ions is important to the understanding of substorm energetic injections and the formation of ring current. Previous studies show that nonadiabatic acceleration of protons by magnetic field dipolarization is hard to occur at X>–10 RE because the time-scale of dipolarization(several minutes) is much larger than the gyroperiod of protons there(several seconds). In this paper, we present a case of nonadiabatic acceleration of plasma sheet ions observed by Cluster on October 30, 2006 at(XGSM, YGSM)=(-7.7, 4.7) RE. The nonadiabatic acceleration of ions is caused not by previously reported magnetospheric dipolarization but by the ultra low frequency(ULF) waves during magnetospheric dipolarization. The nonadiabatic acceleration of ions generates a new energy flux structure of ions, which is characterized by the usual energy flux increase of ions(28–80 ke V) and a concurrent energy flux decrease of ions in a lower energy range(10 e V–20 ke V). These new observations constitute a complete physical picture: The lower energy ions absorb the wave energy, and thus get accelerated to higher energy. We use a nonadiabatic model to interpret the ion energy flux variations. Both analytic and simulation results are in good agreement with the observations. This indicates that the nonadiabatic acceleration associated with ULF waves superposed on dipolarized magnetic field is an effective mechanism for ion energization in the near-Earth plasma sheet. The presented energy flux structures can be used as a proxy to identify the similar dynamic process.

Prediction of thermal conductivity of polymer-based composites by using support vector regression

Support vector regression (SVR) combined with particle swarm optimization (PSO) for its parameter optimization, was proposed to establish a model to predict the thermal conductivity of polymer-based composites under different mass fractions of fillers (mass fraction of polyethylene (PE) and mass fraction of polystyrene (PS)). The prediction performance of SVR was compared with those of other two theoretical models of spherical packing and flake packing. The result demonstrated that the estimated errors by leave-one-out cross validation (LOOCV) test of SVR models, such as mean absolute error (MAE) and mean absolute percentage error (MAPE), all are smaller than those achieved by the two theoretical models via applying identical samples. It is revealed that the generalization ability of SVR model is superior to those of the two theoretical models. This study suggests that SVR can be used as a powerful approach to foresee the thermal property of polymer-based composites under different mass fractions of polyethylene and polystyrene fillers.