The Limit of Finite Sample Breakdown Point of Tukey’s Halfspace Median for General Data

Under special conditions on data set and underlying distribution, the limit of finite sample breakdown point of Tukey＇s halfspace median （1） has been obtained in the literature. In this paper, we establish the result under weaker assumptions imposed on underlying distribution （weak smoothness） and on data set （not necessary in general position）. The refined representation of Tukey＇s sample depth regions for data set not necessary in general position is also obtained, as a by-product of our derivation.

Numerical analysis of the effects of downhole dynamic conditions on formation testing while drilling

Formation testing while drilling is an innovative technique that is replacing conventional pressure testing in which the fluid sampling is conducted in a relatively short time following the drilling. At this time, mud invasion has just started, mudcake has not formed entirely and the formation pressure is not stable. Therefore, it is important to study the influence of the downhole dynamic environment on pressure testing and fluid sampling. This paper applies an oil-water two phase finite element model to study the influence of mudcake quality and mud filtrate invasion on supercharge pressure, pretest and sampling in the reservoirs of different permeability. However, the study is only for the cases with water based mud in the wellbore. The results illustrate that the mudcake quality has a significant influence on the supercharge pressure and fluid sampling, while the level of mud filtrate invasion has a strong impact on pressure testing and sampling. In addition, in-situ formation pressure testing is more difficult in low permeability reservoirs as the mud filtrate invasion is deeper and therefore degrades the quality of fluid sampling. Finally, a field example from an oil field on the Alaskan North Slope is presented to validate the numerical studies of the effects of downhole dynamic conditions on formation testing while drilling.

An Artificial Neural Network-Based Response Surface Method for Reliability Analyses of c-φ Slopes with Spatially Variable Soil

This paper presents an artificial neural network（ANN）-based response surface method that can be used to predict the failure probability of c-φslopes with spatially variable soil.In this method,the Latin hypercube sampling technique is adopted to generate input datasets for establishing an ANN model;the random finite element method is then utilized to calculate the corresponding output datasets considering the spatial variability of soil properties;and finally,an ANN model is trained to construct the response surface of failure probability and obtain an approximate function that incorporates the relevant variables.The results of the illustrated example indicate that the proposed method provides credible and accurate estimations of failure probability.As a result,the obtained approximate function can be used as an alternative to the specific analysis process in c-φslope reliability analyses.

Design of the sample cell in near-field surface-enhanced Raman scattering by finite difference time domain method

The rational design of the sample cell may improve the sensitivity of surface-enhanced Raman scattering （SERS） detection in a high degree. Finite difference time domain （FDTD） simulations of the configuration of Ag film-Ag particles illuminated by plane wave and evanescent wave are performed to provide physical insight for design of the sample cell. Numerical solutions indicate that the sample cell can provide more ＂hot spots＂ and the massive field intensity enhancement occurs in these ＂hot spots＂. More information on the nanometer character of the sample can be got because of gradient-field Raman （GFR） of evanescent wave. OCIS codes： 290.5860, 240.0310, 240.6680, 999.9999 （surface-enhanced Raman scattering）.

Robust linear receivers for STBC systems with unknown co-channel interference

Focusing on space-time block code （STBC） systems with unknown co-channel interference, an oblique projection-based robust linear receiver is proposed in this paper.Based on the oblique projection, the desired signal subspace and interference-plus-noise subspace are first identified from the received signal.Then the matched filter receiver is used to decode the STBC encoded signals in the desired signal subspace.Simulation results show that the proposed linear receiver obtains significant performance improvement over conventional Capon-type receivers under finite sample-size situations and in the presence of channel estimation errors.

Estimation of Censored Regression Model： A Simulation Study

We investigate the finite sample performance of several estimators proposed for the panel data Tobit regression model with individual effects, including Honor6 estimator, Hansen＇s best two-step GMM estimator, the continuously updating GMM estimator, and the empirical likelihood estimator （ELE）. The latter three estimators are based on more conditional moment restrictions than the Honor6 estimator, and consequently are more efficient in large samples. Although the latter three estimators are asymptotically equivalent, the last two have better finite sample performance. However, our simulation reveals that the continuously updating GMM estimator performs no better, and in most cases is worse than Honor6 estimator in small samples. The reason for this finding is that the latter three estimators are based on more moment restrictions that require discarding observations. In our designs, about seventy percent of observations are discarded. The insufficiently few number of observations leads to an imprecise weighted matrix estimate, which in turn leads to unreliable estimates. This study calls for an alternative estimation method that does not rely on trimming for finite sample panel data censored regression model.

On the Sum-Rate Capacity of Poisson Multiple Access Channel with Non-Perfect Photon-Counting Receiver

We investigate two-user sum-rate capacity for Poisson channel considering practical photon-counting receiver,including finite sampling rate and dead time.The sum-rate capacity reduction due to photon-counting loss is characterized and compared with that of continuous Poisson channel.We show that the sum-rate capacity with non-perfect receiver approaches the capacity of continuous time Poisson channel as the sampling time and dead time both approach zero.For optimal transmission strategy,we demonstrate three possible transmission strategies,including only one active user and two active users.In addition,we study the special case of identical peak power constraint for each user.We adopt majorization method to demonstrate that the optimal duty cycle for the two users must be the same and unique.Furthermore,we analyze the sum-rate capacity for multiple input single output(MISO)multiple-access channel(MAC).We propose a sufficient condition on dead time where the sum-rate capacity of the Poisson MISO-MAC is equivalent to that of single input single output,and the equivalence would not hold for sufficient large peak power or dead time.The theoretical capacity results are validated by numerical results.