The endosperm, a result of double fertilization in flowering plants, is a triploid tissue whose genetic composition is more complex than diploid tissue. We present a new maximum-likelihood-based statistical method for mapping quantitative trait loci (QTL) underlying endosperm traits in an autogamous plant. Genetic mapping of quantitative endosperm traits is qualitatively different from traits f...

The paper introduces a reinforcement learning-based methodology for performance improvement of Intelligent Controllers. The translation interfaces of a 3-level Hierarchical Goal-Directed Intelligent Machine (HGDIM) are modeled by a 2-stage Hierarchical Learning Stochas-tic Automaton (HLSA). The decision probabilities at the two stages are recursively updated from the success and failure signals...

We consider two-stage scattered data fitting with truncated hierarchical B-splines (THB-splines) for the adaptive reconstruction of industrial models. The first stage scheme is devoted to computation local least squares variational spline approximations, exploiting a simple fairness functional handle distributions locally varying density points. Hierarchical quasi-interpolation based on THB-spl...

When multiple geo-spatial datasets are integrated, the process should be done in several stages. In each stage two datasets are fused to one. Since different sequences may lead to different results, it is important to select a sequence that would lead to the required results. Two approaches, namely the sequential and hierarchical, for selecting the sequence are presented, and their results are ...

introduction breast cancer is the second cause of mortality among women. early detection of it can enhance the chance of survival. screening systems such as mammography cannot perfectly differentiate between patients and healthy individuals. computer-aided diagnosis can help physicians make a more accurate diagnosis. materials and methods regarding the importance of separating normal and abnorm...

Agglomerative hierarchical clustering becomes infeasible when applied to large datasets due to its O(N2) storage requirements. We present a multi-stage agglomerative hierarchical clustering (MAHC) approach aimed at large datasets of speech segments. The algorithm is based on an iterative divide-and-conquer strategy. The data is first split into independent subsets, each of which is clustered se...

Although it is common practice to fit a complex Bayesian model using Markov chain Monte Carlo (MCMC) methods, we provide an alternative sampling-based method to fit a two-stage hierarchical model in which there is conjugacy conditional on the parameters in the second stage. Using the sampling/importance resampling (SIR) algorithm, our method subsamples independent samples from an approximate jo...

There are multiple scenarios where at-speed coverage over core boundaries is difficult. The idea is to resolve this problem using two stage wrapper. Generally single stage wrapper is used in the present design techniques, and is used in industries. Here two stage wrapper is used in which test coverage has been increased. Additional scan compression architecture is introduced to reduce the patte...

This paper presents a robust semantic model for one-stage interpretation of natural speech. Our semantic analysis uses no explicit syntactic and morphologic knowledge, which seems sufficient for narrow application domains. In contrast to previous approaches, our semantic model is embedded in a uniform, hierarchical, stochastic modeling framework together with acoustic-phonetic and lexical knowl...

We analyze in this paper finite horizon hierarchical signaling games between informed senders and decision maker receivers in a dynamic environment. The underlying information evolves in time while sender and receiver interact repeatedly. Different from the classical communication models, however, the sender and the receiver have different objectives and there is a hierarchy between the players...