This paper proposed a novel model for short term load forecast (STLF) in the electricity market. The prior electricity demand data are treated as time series. The model is composed of several neural networks whose data are processed using a wavelet technique. The model is created in the form of a simulation program written with MATLAB. The load data are treated as time series data. They are dec...

Aim: This study assessed the prevalence of non-nutritive sucking habits and its association with breastfeeding duration and sociodemographic characteristics in 140 children (1 to 3 years of age) attending health and treatment centers in the city of Yazd, Iran. Methods: The sample divided into 2 groups of having NNS (non nutritive sucking) habit and not having NNS habit. The data were collected ...

Objectives: To determine whether non-nutritive sucking (NNS) has an effect on circadian rhythm of circadian genes in peripheral blood mononuclear cells (PBMC) in preterm neonates. Methods: Ten premature neonates, gestational age from 30 to 31 weeks, were recruited. Infants with birth asphyxia, respiratory distress syndrome, apnoea, malformation, infection or haemolytic diseases were excluded. A...

SUMMARY A method is proposed to solve the inverse kinematics and control problems of robot control systems using a cerebellar model articulation controller neural network combined with a genetic algorithm. Computer simulations and experiments with a 7-DOF redundant modular manipulator have demonstrated the effectiveness of the proposed method. 1. INTRODUCTION The design of a redundant manipulat...

Borna disease virus (BDV) causes central nervous system (CNS) disease that is frequently manifested by behavioral abnormalities. Recent evidence indicates that the natural host range and geographic distribution of BDV is wider than originally thought BDV has been molecularly characterized as a non-segmented, negative single-stranded (NNS) RNA virus. Its genome (ca 8.9 kb), the smallest among kn...

In this brief, we present a data-driven framework for real-time estimation of reachable sets control systems where the plant is modeled using neural networks (NNs). We utilize running example quadrotor model that learned trajectory data via NNs. The NN offline can be excited online to obtain linear approximations reachability analysis. use dynamic mode decomposition (DMD)-based approach lifting...

Obesity has become an epidemic, not just in the United States, but also across the globe. Obesity is a result of many factors including poor dietary habits, inadequate physical activity, hormonal issues, and sedentary lifestyle, as well as many psychological issues. Direct and indirect costs associated with obesity-related morbidity and mortality have been estimated to be in the billions of dol...

BACKGROUND Globally, case detection of tuberculosis (TB) has stabilized in recent years. Active case finding (ACF) has regained an increased attention as a complementary strategy to fill the case detection gap. In the Philippines, the DetecTB project implemented an innovative ACF strategy that offered a one-stop diagnostic service with a mobile unit equipped with enhanced diagnostic tools inclu...

The theme of this study is to present the impacts and importance fractional order derivatives susceptible, infected quarantine (SIQ) model based on coronavirus with lockdown effects. purpose these investigations achieve more accuracy use in SIQ model. integer, nonlinear mathematical system effects also provided study. are categorized into dynamics infective quarantine, generally known as system...

We investigate classification performance of neural networks (NNs) based on topological insight in an attempt to guarantee stability their inference. NNs which can accurately classify a dataset map it into hidden space while disentangling intertwined data. sometimes acquire forcible mapping disentangle the data, and this generates outliers. The around outliers is unstable because outputs change...