Estimation of Some Genetic Parameters, Correlation and Heritability in Various Maize Traits

The study was carried out using ten maize hybrids in spring 2015 and 2016 were planted at the field of Agriculture College, University of Duhok. All treatments arranged in Randomized Complete Block Design (RCBD) with three replications to determine the heritability, genetic advance, correlation and genetic parameters govering the inheritance of grain yield and related agronomic traits. The result showed significant difference among hybrids for studied traits in spring 2015 and 2016 and also the results revealed that hybrids and seasons interaction had a significant difference for all traits. The season’s spring 2015 was superior than spring 2016 in leaf area, days to 75% tasseling and silking, yield and its components. The hybrid (OH40 xIK8) was superior in No. of rows ear-1, No. of kernels row-1,300 kernel weight and kernel yield plant1. All studied traits recorded higher value of heritability, high genetic advance coupled with heritability was observed in leaf area and kernel yield plant-1, thus selection based on these traits will be effective in maize breeding program. Grain yield was positively correlated with leaf area and 300 kernel weight, also No. of row ear-1 exhibited positive correlation coefficient with leaf area, 300-kernell weight and kernel yield plant-1

Learning from Outside the Viability Kernel: Why we Should Build Robots that can Fall with Grace

Despite impressive results using reinforcement learning to solve complex problems from scratch, in robotics this has still been largely limited to model-based learning with very informative reward functions. One of the major challenges is that the reward landscape often has large patches with no gradient, making it difficult to sample gradients effectively. We show here that the robot state-initialization can have a more important effect on the reward landscape than is generally expected. In particular, we show the counter-intuitive benefit of including initializations that are unviable, in other words initializing in states that are doomed to fail.Comment: Proceedings of the 2018 IEEE International Conference on SImulation, Modeling and Programming for Autonomous Robots (SIMPAR), Brisbane, Australia, 16-19 201

Statistical inferences for functional data

With modern technology development, functional data are being observed frequently in many scientific fields. A popular method for analyzing such functional data is ``smoothing first, then estimation.'' That is, statistical inference such as estimation and hypothesis testing about functional data is conducted based on the substitution of the underlying individual functions by their reconstructions obtained by one smoothing technique or another. However, little is known about this substitution effect on functional data analysis. In this paper this problem is investigated when the local polynomial kernel (LPK) smoothing technique is used for individual function reconstructions. We find that under some mild conditions, the substitution effect can be ignored asymptotically. Based on this, we construct LPK reconstruction-based estimators for the mean, covariance and noise variance functions of a functional data set and derive their asymptotics. We also propose a GCV rule for selecting good bandwidths for the LPK reconstructions. When the mean function also depends on some time-independent covariates, we consider a functional linear model where the mean function is linearly related to the covariates but the covariate effects are functions of time. The LPK reconstruction-based estimators for the covariate effects and the covariance function are also constructed and their asymptotics are derived. Moreover, we propose a $L^2$-norm-based global test statistic for a general hypothesis testing problem about the covariate effects and derive its asymptotic random expression. The effect of the bandwidths selected by the proposed GCV rule on the accuracy of the LPK reconstructions and the mean function estimator is investigated via a simulation study. The proposed methodologies are illustrated via an application to a real functional data set collected in climatology.Comment: Published at http://dx.doi.org/10.1214/009053606000001505 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

Communications for Next Generation single chip computers

It is the thesis of this report that much of what is presently thought to require specialized VLSI functions might instead be achieved by combinations of fast general purpose single chip computers with upgraded communication facilities. To this end, the characteristics of applications of this nature are first surveyed briefly and some working principles established. In the light of these, three different chip philosophies are explored in some detail. This study shows that some upgrading of typical single chip I/O will definitely be necessary, but that this upgrading does not have to be complex and that true multiprocessor-multibus operation could be achieved without excessive cost

A Low Cost Two-Tier Architecture Model For High Availability Clusters Application Load Balancing

This article proposes a design and implementation of a low cost two-tier architecture model for high availability cluster combined with load-balancing and shared storage technology to achieve desired scale of three-tier architecture for application load balancing e.g. web servers. The research work proposes a design that physically omits Network File System (NFS) server nodes and implements NFS server functionalities within the cluster nodes, through Red Hat Cluster Suite (RHCS) with High Availability (HA) proxy load balancing technologies. In order to achieve a low-cost implementation in terms of investment in hardware and computing solutions, the proposed architecture will be beneficial. This system intends to provide steady service despite any system components fails due to uncertainly such as network system, storage and applications.Comment: Load balancing, high availability cluster, web server cluster