多元线性回归分析在内蒙古查干布拉根矿区矿石体重计算中的应用

位于内蒙古的查干布拉根矿床是一处受构造控制的脉状铅锌银矿床,本文通过多元线性回归分析法对其小体重计算得出的数据进行了校正,并且通过F统计量对回归方程的显著性进行检验,通过t-stat(t检验值)与P-value(P值)两个统计量对于每个回归系数显著性进行了检验。

基于激光雷达的猪只体重测量系统开发与研究

随着养殖业规模化的不断发展,自动化养猪已成为目前猪只养殖业的一种趋势;针对传统猪只体重测量过程中出现一系列应激性行为问题,文章利用二维激光雷达对猪只进行无害、非接触式扫描,设计开发猪只体重测量系统构建猪只三维模型,计算并显示猪只体重;该系统通过以激光雷达为核心的硬件设备与软件系统相结合,实现了猪只二维模型建立;在此基础上采用QT3D框架构建视窗,并对视窗进行水平垂直布局并构建猪只三维模型视窗;采用Delaunay三角划分的方式对猪只三维模型中相邻点云采用互不相交、互不共面连线的方法分割成若干个三棱柱,通过对三棱柱体积计算并叠加得到整头猪只的体积;利用系统采集到的体积数据与猪只真实体重构建体积与体重数学模型,拟合精度R^(2)为0.925 25。对该模型验证分析得知体重误差在±8%范围内;该系统扫描速度快、建模效果良好、体重计算精确,为猪只非接触式测重和相关领域的点云数据三维建模应用提供了新的技术研究方法。

ZResponse to selection,heritability and genetic correlations between body weight and body size in Pacific white shrimp,Litopenaeus vannamei

To quantify the response to selection, heritability and genetic correlations between weight and size ofLitopenaeus vannamei, the body weight （BW）, total length （TL）, body length （BL）, first abdominal segment depth （FASD）, third abdominal segment depth （TASD）, first abdominal segment width （FASW）, and partial carapace length （PCL） of 5-month-old parents and of offspring were measured by calculating seven body measurings of offspring produced by a nested mating design. Seventeen half-sib families and 42 full-sib families ofL. vannamei were produced using artificial fertilization from 2-4 dams by each sire, and measured at around five months post-metamorphosis. The results show that heritabilities among various traits were high： 0.515±0.030 for body weight and 0.394±0.030 for total length. After one generation of selection, the selection response was 10.70% for offspring growth. In the 5th month, the realized heritability for weight was 0.296 for the offspring generation. Genetic correlations between body weight and body size were highly variable. The results indicate that external morphological parameters can be applied during breeder selection for enhancing the growth without sacrificing animals for determining the body size and breed ability; and selective breeding can be improved significantly, simultaneously with increased production.

Evaluation of body weight of sea cucumber Apostichopus japonicus by computer vision

Apostichopus japonicus(Holothuroidea,Echinodermata) is an ecological and economic species in East Asia.Conventional biometric monitoring method includes diving for samples and weighing above water,with highly variable in weight measurement due to variation in the quantity of water in the respiratory tree and intestinal content of this species.Recently,video survey method has been applied widely in biometric detection on underwater benthos.However,because of the high flexibility of A.japonicus body,video survey method of monitoring is less used in sea cucumber.In this study,we designed a model to evaluate the wet weight of A.japonicus,using machine vision technology combined with a support vector machine(SVM) that can be used infield surveys on the A.japonicus population.Continuous dorsal images of free-moving A.japonicus individuals in seawater were captured,which also allows for the development of images of the core body edge as well as thorn segmentation.Parameters that include body length,body breadth,perimeter and area,were extracted from the core body edge images and used in SVM regression,to predict the weight of A.japonicus and for comparison with a power model.Results indicate that the use of SVM for predicting the weight of 33 A.japonicus individuals is accurate(R^2=0.99) and compatible with the power model(R^2=0.96).The image-based analysis and size-weight regression models in this study may be useful in body weight evaluation of A.japonicus in lab and field study.

PRCA： A highly efficient computing architecture

Applications can only reach 8 %~15 % of utilization on modern computer systems. There are many obstacles to improving system efficiency. The key root is the conflict between the fixed general computer architecture and the variable requirements of applications. Proactive reconfigurable computing architecture(PRCA) is proposed to improve computing efficiency. PRCA dynamically constructs an efficient computing architecture for a specific application via reconfigurable technology by perceiving requirements,workload and utilization of computing resources. Proactive decision support system(PDSS),hybrid reconfigurable computing array(HRCA) and reconfigurable interconnect(RIC) are intensively researched as the key technologies. The principles of PRCA have been verified with four applications on a test bed. It is shown that PRCA is feasible and highly efficient.

Architecture design for reliable and reconfigurable FPGA-based GNC computer for deep space exploration

SRAM(static random access memory)-based FPGA(field programmable gate array), owing to its large capacity, high performance, and dynamical reconfiguration, has become an attractive platform for So PC(system on programmable chip) development. However, as the configuration memory and logic memory of the SRAM-based FPGA are highly susceptible to SEUs(single-event upsets) in deep space, it is a challenge to design and implement a highly reliable FPGA-based system for spacecraft, and no practical architecture has been proposed. In this paper, a new architecture for a reliable and reconfigurable FPGAbased computer in a highly critical GNC(guidance navigation and control) system is proposed. To mitigate the effect of an SEU on the system, multi-layer reconfiguration and multi-layer TMR(triple module redundancy) techniques are proposed, with a reliable reconfigurable real-time operating system(Space OS) managing the system level fault tolerance of the computer in the architecture. The proposed architecture for the reconfigurable FPGA-based computer has been implemented with COTS(commercial off the shelf) FPGA and has firstly been applied to the GNC system of a circumlunar return and reentry flight vehicle. The in-orbit results show that the proposed architecture is capable of meeting the requirements of high reliability and high availability, and can provide the expressive varying functionality and runtime flexibility for an FPGA-based GNC computer in deep space.

A study of a three-dimensional self-propelled flying bird with flapping wings

In this paper, a study of a three-dimensional(3D) self-propelled bionic flying bird in a viscous flow is carried out. This bionic bird is propelled and lifted through flapping and rotating wings, and better flying can be achieved by adjusting the flapping and rotation motion of wings. In this study, we found that the bird can fly faster forward and upward with appropriate center of rotation and oscillation without more energy consumption and have perfect flight performance at a certain angle of attack by adjusting the center of oscillation. The study utilizes a 3D computational fluid dynamics package which constitutes combined immersed boundary method and the volume of fluid method. In addition, it includes adaptive multigrid finite volume method and control strategy of swimming and flying.