Functional Signal plus Noise (FSN) models are proposed for analysing the dynamics of a large cross-section of yields or asset prices in which contemporaneous observations are functionally related. The FSN models are used to forecast high dimensional yield curves for US Treasury bonds at the one month ahead horizon. The models achieve large reductions in mean square forecast errors relative to a...

Potato (Solanum tuberosum L.) is one of the most important food crops worldwide. Current potato varieties are highly susceptible to drought stress. In view of global climate change, selection of cultivars with improved drought tolerance and high yield potential is of paramount importance. Drought tolerance breeding of potato is currently based on direct selection according to yield and phenotyp...

In New Zealand (NZ) herd testing is done for milk, fat, protein and somatic cell count (SCC). Currently, routine genetic evaluation is done for milk, fat and protein yields but not for SCC. A new system has been developed to calculate SCC breeding values (BVs) for the dairy industry. The current evaluation of milk, fat and protein involves combining herd test results to predict a 270-day yield ...

We investigate diffusive propagation of light and consequent random lasing in an amplifying medium comprising resonant spherical scatterers. A Monte-Carlo calculation based on photon propagation via three-dimensional random walks is employed to obtain the dwell-times of light in the system. We compare the inter-scatterer and intra-scatterer dwell-times for representative resonant and non-resona...

This paper proposes an equation-based multi-scenario iterative robust optimization methodology for analog/mixed-signal circuits. We show that due to local circuit performance monotonicity in random variations constraint maximization can be used to efficiently find critical constraints and worst-case scenarios of random process variations and populate them into a multi-scenario optimization. Thi...

We consider the asymptotic behavior of a probability density function for the sum of any two lognormally distributed random variables that are nontrivially correlated. We show that both the left and right tails can be approximated by some simple functions. Furthermore, the same techniques are applied to determine the tail probability density function for a ratio statistic, and for a sum with mo...

Our project attempted to use machine learning to recreate or redefine features of an image using an arrangement of transparent overlapping polygons. From genetic algorithm[1] and hill climbing[2], we came up an implementation that starts by generating a random sequence of polygons then iteratively mutating the sequence (slightly modifying a random attribute of a random polygon), incrementally b...

Random selection of spanning trees on graphs has been treated extensively in technical literature. Popular randomized algorithms have time complexity varying from to , where is the order of a graph, namely, the number of vertices. In this work, we introduce effective and efficient procedures to select spanning trees using random walks with the purpose to balance the diameter of the selected tre...

Drought is the most important factor limiting rice yield in most rainfed areas of Asia and Africa. Four large BC2F2 populations consisted of 3,200 individuals, which were derived from crosses between an elite Geng variety, Jigeng88, and four donors from three different countries, were screened and progeny tested under severe drought stress, resulting in the development of 72 introgression lines...

In the present work, covariance components for milk yield and disease liability were estimated with bivariate random regression test-day sire models using a Bayesian approach and implemented via the Gibbs sampler. The data consist of 8075 first-parity Danish Holstein (DH) cows, from 1259 sires, performing in 57 herds from 1992 to 1997. Treatments associated with five different type of diseases ...