Currently, genomic evaluations use multiple-step procedures, which are prone to biases and errors. A single-step procedure may be applicable when genomic predictions can be obtained by modifying the numerator relationship matrix A to H = A + A(Delta), where A(Delta) includes deviations from expected relationships. However, the traditional mixed model equations require H(-1), which is usually di...

Objectives and Approach of the Working Panel The importance of public policies in education and training, particularly in the open and distance learning market A tentative classification of public actions

assigning a set of objects to groups such that objects in one group or cluster are more similar to each other than the other clusters’ objects is the main task of clustering analysis. sspco optimization algorithm is anew optimization algorithm that is inspired by the behavior of a type of bird called see-see partridge. one of the things that smart algorithms are applied to solve is the problem ...

Abstract. In this paper we present the distributed event localization and tracking algorithm DELTA that solely depends on light measurements. Based on this information and the positions of the sensors, DELTA is able to track a moving person equipped with a flashlight by dynamically building groups and electing well located nodes as group leaders. Moreover, DELTA supports object localization. Th...

nowadays, outsourcing is viewed as a trade strategy and organizations tend to adopt new strategies to achieve competitive advantages in the current world of business. focusing on main copmpetencies, and transferring most of activities to outside resources of organization( outsourcing) is one such strategy is. in this paper, we aim to decide on decision maker agent of transportation system, by a...

Learning useful information across long time lags is a critical and difficult problem for temporal neural models in tasks such as language modeling. Existing architectures that address the issue are often complex and costly to train. The differential state framework (DSF) is a simple and high-performing design that unifies previously introduced gated neural models. DSF models maintain longer-te...

This work evaluates the effectiveness of a new hybrid algorithm in the training of modular neural networks with multilayers specialists. The algorithm is applied on the classification of electric disturbances previously characterized and pre-processed, making possible the comparison between its performance with multilayers perceptrons networks. It presents the algorithm’s development and inclus...

Learning and long-term memory are thought to involve temporally defined changes in gene expression that lead to the strengthening of synaptic connections in selected brain regions. We used cDNA microarrays to study hippocampal gene expression in animals trained in a spatial discrimination-learning paradigm. Our analysis identified 19 genes that showed statistically significant changes in expres...

The present study evaluated the effects of the principal active component of marijuana (delta 9 THC) on motor abilities and motor learning in mice with cerebellar dysfunction. For this purpose, spontaneous locomotor activity, equilibrium abilities, muscular tone, motor coordination and motor learning were investigated in Lurcher mutant and non-mutant B6/CBA mice 20 min after i.p. administration...

We developed a system called DELTA that supports the students’ use of backward chaining (BC) to prove the congruence of two triangles. DELTA is designed as an interactive learning environment and supports the use of BC by providing hints and a function to automatically check the proofs inputted by the students. DELTA also has coloring, marking, and highlighting functions to support students’ at...