Thresholding rules for recovering a sparse signal from microarray experiments

We consider array experiments that compare expression levels of a high number of genes in two cell lines with few repetitions and with no subject effect. We develop a statistical model that illustrates under which assumptions thresholding is optimal in the analysis of such microarray data. The results of our model explain the success of the empirical rule of two-fold change. We illustrate a thresholding procedure that is adaptive to the noise level of the experiment, the amount of genes analyzed, and the amount of genes that truly change expression level. This procedure, in a world of perfect knowledge on noise distribution, would allow reconstruction of a sparse signal, minimizing the false discovery rate. Given the amount of information actually available, the thresholding rule described provides a reasonable estimator for the change in expression of any gene in two compared cell lines.     

Wavelet threshold based ECG compression using USZZQ and Huffman coding of DSM

In this paper, a new Wavelet threshold based ECG signal compression technique using uniform scalar zero zone quantizer (USZZQ) and Huffman coding on differencing significance map (DSM) is proposed. Wavelet coefficients are selected based on the energy packing efficiency of each sub-band. Significant Wavelet coefficients are quantized with uniform scalar zero zone quantizer. Significance map is created to store the indices of the significant coefficients. This map is encoded efficiently with less number of bits by applying Huffman coding on the differences between indices in the significance map. ECG records from the MIT-BIH arrhythmia database are selected as test data. For the record 117, the proposed technique achieves a compression ratio of 18.7:1 with lower percentage root mean square difference (PRD) compared to other threshold based methods. The proposed technique is tested for MIT-BIH arrhythmia record 119 and a compression ratio of 21.81:1 is achieved with a PRD value of 3.716% which is much lower compared to the reported PRD value of 5.0 and 5.5% of set partitioning in hierarchical tress (SPIHT) and analysis by synthesis ECG compressor (ASEC), respectively. The noise eliminating capability of the proposed technique is also demonstrated in this work. The proposed technique achieves the required compression ratio with less reconstruction error for GSM-based cellular telemedicine system.     

Thermo-Mechanical Analysis of Restored Molar Tooth using Finite Element Analysis

The aim of the study is to find most optimum combination of crown material and adhesive to avoid loosening and thereby failure of restored tooth. This study describes the Thermo-Mechanical analysis of restored molar tooth crown for determination of the stress levels due to thermal and mechanical loads on restored molar tooth. The potential use of the 3-D model was demonstrated and analyzed using different materials for crown. Thermal strain, stress and deformation were measured at hot and cold conditions in ANSYS and correlated with analytical calculation and existing experimental data for model validation and optimization. It is concluded that amongst various material porcelain crown with composite resin adhesive cement closely simulates the behavior of natural crown and should ideally result into long lasting restoration.     

三江源大型食草动物数量无人机自动监测方法

应用无人机进行动物调查的研究越来越多,但是缺乏有效的自动处理图像方法,使得目视解释的工作量较大。为研究快速与准确估算三江源区域大型食草动物数量的方法,本文使用两种无人机进行7个站点的遥感影像采集。首先对无人机影像进行灰度化,使矩阵维数下降但梯度信息仍然保留,使运算速度大幅度提高;其次对影像开展高斯滤波,高斯滤波将数据进行能量转化,排除掉属于低能量部分的噪声;第三开展阈值处理得到二值化图像;采用样本中动物形态学特征开展形态运算,先用开运算消除小物体尽可能排除干扰,同时不误删牲畜,再用闭运算排除小型黑洞将同一对象连通不重复计数;最后从二值图像中检索轮廓,并返回检测到的轮廓的个数;从而自动获得主要大型食草动物物种数量与空间分布。精度检验方法为手工计数与自动计数结果比较,相对误差3.1%~6.5%,大多数情况均可达到此水平。采用计算机自动处理图像后,每张图像处理和计数的平均时间小于3 s。无人机影像的自动处理方法可为今后大规模进行藏羊、牦牛、西藏野驴和藏原羚等动物调查提供一种有效、可靠的技术途径。