Image denoising is regarded as an ill-posed problem in computer vision 92-95 civic k-swap mounts tasks that removes additive noise from imaging sensors.Recently, several convolution neural network-based image-denoising methods have achieved remarkable advances.However, it is difficult for a simple denoising network to recover aesthetically pleasing
Improving documentation of prescriptions for as-required medications in hospital inpatients
It is estimated that 1 in 10 hospital inpatients in Scotland have experienced a medication error.In our unit, an audit in 2019 identified documentation of as-required prescriptions on drug Kardexes as an important target dosatron d40mz2 for improvement.This project aimed to reduce the percentage of these errors to <5% in the ward in 6 months.Wee
Study on the post-partum disorders and their relationship with the reproductive performance in Iraqi cow-buffaloes
This study was conducted to evaluate the influence of various postpartum disorders on subsequent reproductive performance in Iraqi cow buffaloes.The data were collected from 172 buffaloes within private dairy buffaloes herd.In this study, the diagnosis and treatment of the affected cases with postpartum disorders (Retained placenta, puerperal metri
SISTEM MONETER ISLAM: MENUJU KESEJAHTERAAN HAKIKI
The Studies in this article aims to look at how the efforts of the Islamic monetary system in creating the true welfare.Welfare in the conventional economic system (capitalist and socialist) contain of different meanings, when in the conventional economic system, welfare is defined only in terms of materials (material fulfillment), but in the Islam
Landslide Susceptibility Prediction Modeling Based on Remote Sensing and a Novel Deep Learning Algorithm of a Cascade-Parallel Recurrent Neural Network
Landslide susceptibility prediction (LSP) modeling is an important and challenging problem.Landslide features are generally uncorrelated or nonlinearly correlated, resulting in limited LSP performance when leveraging conventional machine learning models.In this study, a deep-learning-based model using the long short-term memory (LSTM) recurrent neu