Commentary on Krishnaswamy et al. - Quantifying and mapping biodiversity and ecosystem services: Utility of a multi-season NDVI based Mahalanobis distance surrogate

Remote sensing is a powerful tool for characterizing, estimating or modelling species diversity. Differences in environmental properties of different habitats should lead to differences of spectral responses, which can be detected by satellite imagery. Hence, spectral distance may be related to species diversity. Based on previous studies, Krishnaswamy et al. [Krishnaswamy, J., Bawa, K. S., Ganeshaiah, K. N., & Kiran, M. C. (2009). Quantifying and mapping biodiversity and ecosystem services: Utility of a multi-season NDVI based Mahalanobis distance surrogate. Remote Sensing of Environment.] used spectral distance to estimate species diversity. Since a noisy scatterplot of species versus spectral diversity is expected, the commonly used Ordinary Least Square regression may fail to detect trends which occur across other quantiles than the mean.Krishnaswamy et al. [Krishnaswamy, J., Bawa, K. S., Ganeshaiah, K. N., & Kiran, M. C. (2009). Quantifying and mapping biodiversity and ecosystem services: Utility of a multi-season NDVI based Mahalanobis distance surrogate. Remote Sensing of Environment.] proposed a quantile-quantile plot method as an alternative to conventional regression based approaches which are inappropriate for dependent pair-wise dissimilarity or similarity data. By this commentary I demonstrate the utility of a quantile regression technique to complement the Krishnaswamy et al. [Krishnaswamy, J., Bawa, K. S., Ganeshaiah, K. N., & Kiran, M. C. (2009). Quantifying and mapping biodiversity and ecosystem services: Utility of a multi-season NDVI based Mahalanobis distance surrogate. Remote Sensing of Environment.] graphical approach in terms of a predictive model.     

Comparison of multiple linear regression and artificial neural network in developing the objective functions of the orthopaedic screws

Optimizing the orthopaedic screws can greatly improve their biomechanical performances. However, a methodical design optimization approach requires a long time to search the best design. Thus, the surrogate objective functions of the orthopaedic screws should be accurately developed. To our knowledge, there is no study to evaluate the strengths and limitations of the surrogate methods in developing the objective functions of the orthopaedic screws. Three-dimensional finite element models for both the tibial locking screws and the spinal pedicle screws were constructed and analyzed. Then, the learning data were prepared according to the arrangement of the Taguchi orthogonal array, and the verification data were selected with use of a randomized selection. Finally, the surrogate objective functions were developed by using either the multiple linear regression or the artificial neural network. The applicability and accuracy of those surrogate methods were evaluated and discussed. The multiple linear regression method could successfully construct the objective function of the tibial locking screws, but it failed to develop the objective function of the spinal pedicle screws. The artificial neural network method showed a greater capacity of prediction in developing the objective functions for the tibial locking screws and the spinal pedicle screws than the multiple linear regression method. The artificial neural network method may be a useful option for developing the objective functions of the orthopaedic screws with a greater structural complexity. The surrogate objective functions of the orthopaedic screws could effectively decrease the time and effort required for the design optimization process.     

Conservative and aggressive rough SVR modeling

Support vector regression provides an alternative to the neural networks in modeling non-linear real-world patterns. Rough values, with a lower and upper bound, are needed whenever the variables under consideration cannot be represented by a single value. This paper describes two approaches for the modeling of rough values with support vector regression (SVR). One approach, by attempting to ensure that the predicted high value is not greater than the upper bound and that the predicted low value is not less than the lower bound, is conservative in nature. On the contrary, we also propose an aggressive approach seeking a predicted high which is not less than the upper bound and a predicted low which is not greater than the lower bound. The proposal is shown to use ?-insensitivity to provide a more flexible version of lower and upper possibilistic regression models. The usefulness of our work is realized by modeling the rough pattern of a stock market index, and can be taken advantage of by conservative and aggressive traders.     

传感器输出特性的线性化回归程序设计

介绍了用面向对象程序设计方法编制的线性回归数据处理程序 ,该程序用于传感器实验数据的回归处理和特性曲线的绘制     

Disambiguation of partial cognates

Partial cognates are pairs of words in two languages that have the same meaning in some, but not all contexts. Detecting the actual meaning of a partial cognate in context can be useful for Machine Translation tools and for Computer-Assisted Language Learning tools. We propose a supervised and a semi-supervised method to disambiguate partial cognates between two languages: French and English. The methods use only automatically-labeled data; therefore they can be applied to other pairs of languages as well. The aim of our work is to automatically detect the meaning of a French partial cognate word in a specific context.

微博转发预测算法评测系统的建立及性能比较

为解决微博转发行为预测问题,提出了一个基本的预测算法评测系统框架.该系统解决了原始微博数据的抓取和预处理,以及用户微博的转发和忽略行为的判定,微博和用户的特征提取等问题,为解决微博转发行为预测问题提供了技术基础.详细分析了现有文献和工作中的微博转发行为预测算法,阐述了它们的基本原理.通过定量实验分析了不同微博转发行为预测算法的在局部预测问题和全局预测问题方面的性能,并且从算法的原理等方面出发给出了定性的分析.     

The "hidden observer" phenomenon in hypnosis: Some additional findings.

23 highly hypnotizable undergraduates (Harvard Group Scale of Hypnotic Susceptibility) underwent 2 specially constructed 7-item hypnotic inductions. Over the 14 items, the main finding was of a relationship between E. R. Hilgard's (1973, 1977, 1979) "hidden observer" effect and 2 aspects of hypnotic age regression. Ss reporting a hidden observer experienced duality during regression to age 5, in which they were aware of being both adult and child. When asked to write a complex sentence, most did so, usually without spelling errors. The Ss not reporting this effect experienced quasi-lateral age regression in which they had the exclusive feeling of being 5 yrs old, with no sense of an adult identity. Most of these Ss were unable to write the same complex sentence when requested to during age regression. The study replicated Hilgard's finding of the hidden observer phenomenon in terms of its incidence and obtained similar verbal reports from Ss experiencing it. At the same time, the results suggest that a neodissociation account of hypnosis may need some modifications to accommodate these additional findings. (27 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

一种16QAM调制实现技术的研究

讨论了16QAM调制时应用不同类型和参数的滤波器对系统性能的影响．针对16QAM的特点，采用了存储波形累加求和法来代替一般的滤波成形，提高了调制速度．并利用其相位对称的特点将波形存储表压缩为原容量的1／4，有效地节约了存储空间．     

Meshless local Petrov-Galerkin method for continuously nonhomogeneous linear viscoelastic solids

A meshless method based on the local Petrov-Galerkin approach is proposed for the solution of quasi-static and transient dynamic problems in two-dimensional (2-D) nonhomogeneous linear viscoelastic media. A unit step function is used as the test functions in the local weak form. It is leading to local boundary integral equations (LBIEs) involving only a domain-integral in the case of transient dynamic problems. The correspondence principle is applied to such nonhomogeneous linear viscoelastic solids where relaxation moduli are separable in space and time variables. Then, the LBIEs are formulated for the Laplace-transformed viscoelastic problem. The analyzed domain is covered by small subdomains with a simple geometry such as circles in 2-D problems. The moving least squares (MLS) method is used for approximation of physical quantities in LBIEs.     

Adaptive equality prediction of batch processes based on PLS model

There are usually no on-line product quality measurements in batch and semi-batch processes, which make the process control task very difficult. In this paper, a model for predicting the end-product quality from the available on-line process variables at the early stage of a batch is developed using partial least squares (PLS) method. Furthermore, some available mid-course quality measurements are used to rectify the final prediction results. To deal with the problem that the process may change with time, recursive PLS (RPLS) algorithm is used to update the model based on the new batch data and the old model parameters after each batch. An application to a simulated batch MMA polymerization process demonstrates the effectiveness of the proposed method. __________ Translated from Jorunal of Tsinghua Science and Technology(Natural Science Edition), 2004, 44(10): 1360–1363 (in Chinese)