Deep Learning-Based Hookworm Detection in Wireless Capsule Endoscopic Image Using AdaBoost Classifier

Hookworm is an illness caused by an internal sponger called a roundworm. Inferable from deprived cleanliness in the developing nations, hookworm infection is a primary source of concern for both motherly and baby grimness. The current framework for hookworm detection is composed of hybrid convolutional neural networks; explicitly an edge extraction framework alongside a hookworm classification framework is developed. To consolidate the cylindrical zones obtained from the edge extraction framework and the trait map acquired into the hookworm scientific categorization framework, pooling layers are proposed. The hookworms display different profiles, widths, and bend directions. These challenges make it difficult for customized hookworm detection. In the proposed method, a contourlet change was used with the development of the Hookworm detection. In this study, standard deviation, skewness, entropy, mean, and vitality were used for separating the highlights of the each form. These estimations were found to be accurate. AdaBoost classifier was utilized to characterize the hookworm pictures. In this paper, the exactness and the territory under bend examination in identifying the hookworm demonstrate its scientific relevance.     

潮流不对称与推移质泥沙长期净输运

由统计学中的“偏度”概念出发,对潮流不对称的量化进行了探讨,进而将潮流不对称与推移质泥沙的长期净输运联系起来.在此基础上,对潮流不对称对推移质泥沙输运的作用机制进行了研究,并推导了利用潮流调和常数估算推移质泥沙长期净输运的方法.研究认为,产生潮流不对称的原因包括满足一定条件的分潮间的相互作用以及余流与分潮的相互作用,不同分潮组合对潮流不对称的贡献既与分潮间的相对振幅有关,又与分潮间的相对相位有关;对推移质泥沙输运而言,既包括同方向的分潮之间、分潮与余流之间的相互作用,又包括不同方向的分潮之间、分潮与余流之间的相互作用.由偏度结合推移质泥沙输沙公式导出的潮流不对称与推移质输沙之间的关系提供了一个由潮流调和常数估算河口推移质输沙的简便方法,经对比,该方法与直接采用推移质输沙率公式结果是一致的.     

基于暂态零序电流的含光伏电源配电网单相故障定位方法

针对分布式光伏电源接入配电网使得传统配电网继电保护存在可靠性、灵敏性降低的问题,提出了一种考虑母线多分支情况下应用偏度系数来衡量暂态零序电流极性的分布式故障定位方法。分析了分布式电源接入的配电网发生单相接地故障时零序电流的分布特征,发现故障时刻故障区段两端暂态零序电流极性相同,非故障区段两端暂态零序电流极性相反,引入偏度系数来衡量暂态零序电流的极性,实现分布式故障定位。仿真结果表明,该方法能够适用于含分布式光伏电源配电网的故障定位,且在不同的故障条件下具有较强的适用性。     

空间区域中对象流动模式构建方法研究

随着时空数据获取设备的普及应用,产生了大量反映移动对象活动的位置数据,数据的海量性及分析的复杂性决定了该类数据为典型的大数据。位置数据中的到达和离开可以反映移动对象的流动规律,可以表示为区域的流动模式,本文研究空间区域中移动对象流动模式的构建方法,将区域的流动规律以时间序列进行定量表示,模式可用于指导交通、安全等方面的可预测调度。由于对象流动的随机性,使得构建高预测精度的模式成为一个挑战。提出一种基于层次聚类的流动模式构建模型,模型中通过数据的离散化、序列化、模式训练等步骤实现模式构建;提出偏斜度层次聚类树及异常序列去除方法,可以有效去除局部异常序列及自动聚簇选取,提高了模式的预测精度。利用真实数据集对所提出的模式训练方法进行了充分的实验,验证了所构建的空间区域中的流动模式可以用于表达区域中对象的流动规律,所提出的模式训练方法与现有的训练方法相比具有较高的预测精度。     

ICESat/GLAS水面回波波形分析及判定

正确识别水面上的观测值,对于利用ICESat/GLAS卫星激光测高数据监测内陆水系和确定海冰覆盖区的海面高的研究具有重要意义。通过对ICESat/GLAS在水面的回波波形特性的分析,并考虑波形饱和与大气前向散射对波形的影响,提出了根据GLA14数据中提供的回波波形参数识别ICESat/GLAS水面测高数据的方法。测试结果表明,该方法的正确率可达90%以上,可以为内陆水体监测提供有效的支持和帮助。     

基于下偏度的作战风险控制兵力组合优化模型研究

为降低作战中因作战体系兵力配置不当引发重大损失的概率,依据历史兵力单元作战训练数据,以下偏度衡量作战要素组合中的可能风险,建立了以下偏度最小化为目标函数的优化模型。模型体现了预期作战效能产生波动风险的本质,以历史作战效能关联系数反映联合作战中多个作战单元、作战要素间的相互关系,提高模型的实用性和解析能力;最后用VaR控制兵力组合的预期作战风险,计算偏度控制兵力组合可能发生重大损失的概率,实现了体系对抗中对兵力组合风险的双重控制,并实例验证了模型的可行性和实用性。     

Extended Rama Distribution: Properties and Applications

In this paper, the Rama distribution (RD) is considered, and a new model called extended Rama distribution (ERD) is suggested. The new model involves the sum of two independent Rama distributed random variables. The probability density function (pdf) and cumulative distribution function (cdf) are obtained and analyzed. It is found that the new model is skewed to the right. Several mathematical and statistical properties are derived and proved. The properties studied include moments, coefficient of variation, coefficient of skewness, coefficient of kurtosis and moment generating function. Some simulations are undertaken to illustrate the behavior of these properties. In addition, the reliability analysis of the distribution is investigated through the hazard rate function, reversed hazard rate function and odds function. The parameter of the distribution is estimated based on the maximum likelihood method. The distributions of order statistics for ERD are also presented. The performance of the suggested model is compared with several other lifetime distributions based on some goodness of fit tests on a real dataset. It turns out that the suggested model is more flexible than its competitors considered in this study, for modeling real lifetime data.     

Synchronous estimation of DTM and fractional vegetation cover in forested area from airborne LIDAR height and intensity data

We proposed a method to separate ground points and vegetation points from discrete return,small footprint airborne laser scanner data,called skewness change algorithm.The method,which makes use of intensity of laser scanner data,is especially applicable in steep,and forested areas.It does not take slope of forested area into account,while other algorithms consider the change of slope in steep forested area.The ground points and vegetation points can be used to estimate digital terrain model(DTM) and fractio...     

薄膜成核过程的分子动力学模拟

用分子动力学的方法,在计算机上模拟了在具有不同偏斜度Sk的衬底上薄膜的成核过程,从理论上证明了偏斜度Sk取值在-1～-3时,薄膜的成核率高,从而有利于薄膜的生长。     

基于峰度偏度和WD-LDA的飞机目标分类方法

目前,多数的喷气发动机调制特征提取方法都是基于调制波的周期或调制线谱的谱间间隔,但该类谱估计方法往往受信噪比、脉冲重复频率及观测时间影响很难获得很好的分类性能。文中对三类飞机目标回波进行统计分析发现,其归一化幅度分布存在明显差异,据此创造性地提取出峰度偏度特征,并结合小波分解-线性判别分析处理,对目标进行分类。该特征具有很强的抗噪声能力,对脉冲重复频率和观测时间要求不高,且可通过其中一个参数去弥补另一个参数。仿真实验证明了所提方法具有很好的分类性能。