Imaging of the heart anatomy and function using magnetic resonance imaging (MRI) is an important diagnosis tool for heart diseases. Several techniques have been developed to increase the contrast-to-noise ratio (CNR) between myocardium and background. Recently, a technique that acquires cine cardiac images with black-blood contrast has been proposed. Although the technique produces cine sequence of high contrast, it suffers from elevated noise which limits the CNR. In this paper, we study the performance and efficiency of applying a Bayes classifier to remove background noise. Real MRI data is

Heart segmentation in Cardiac MRI images is a fundamental step to quantify myocardium global function. In this paper, we introduce a pipeline for heart localization and segmentation that is fast and robust even in the apical slices that have small myocardium. Also, we propose an enhancement to the popular U-Net architecture for segmentation. The proposed method utilizes the aggregation of different feature scales from the image by using the inception block along with the multi-gate block that propagates the multi-scale context of the supplied data where the heart is subject to changes in scale

This study attempted to investigate the removal of biological oxygen demand (BOD), chemical oxygen demand (COD), total suspended solids (TSS), ammonia-nitrogen (NH4-N), and total phosphorus (TP) from secondary treated domestic wastewater using algal photo-bioreactor. A semi-pilot plant was constructed and operated for 112 days under continuous flow conditions at Zenin wastewater treatment plant, Giza, Egypt (WWTP) which consists of an algal photo-bioreactor with an effective volume of 188 litters and a lamella settler. The removal of the studied parameters was studied at different hydraulic

Advanced oxidation processes (AOPs) using chemically prepared and green synthesized nano zero-valent iron (nZVI) has proved to be effective in removing organic contaminants. The green synthesized nano iron (GT-nZVI) was prepared by using extracted black tea reducing agent. The prepared nZVI particles were characterized using X-ray powder diffraction (XRD), scanning electron microscopy (SEM), and Energy Dispersive X-ray Analysis (EDAX) analysis. The main purpose of this study is to compare between chemically prepared nZVI and GT-nZVI in the biological oxygen demand (BOD) removal efficiency from

Condition assessment is an integral component in any infrastructure asset management system. Without condition information, asset managers lack the ability to make appropriate decisions regarding needed maintenance, rehabilitation, and replacement of infrastructure. Existing and emerging technologies for assessing the condition of water and sewer pipes provide a better picture of the state of these buried assets. Unfortunately, many of these technologies are costly and provide results that are not always highly reliable. This paper presents a methodology to assist asset managers in balancing

Due to the large usage of internet, our environment is transformed into digital society, in which everything is connected together and can be accessed from anywhere. This is the Internet of things (IoT), which refers to the usage of intelligently connected devices and systems. These devices usually collect their data from sensors and actuators in machines and other physical objects. This makes Wireless Sensor Network (WSN) a subset of an Internet of things (IoT) topology, and hence it acts like a bridge that connects the real world to the digital world. So it is important to find a flexible

Computer vision is shaping a new era with its constant development of SOTA algorithms. One heavily contested sub-field of computer vision is face detection, due to its versatile usage in many fields such as security, medical diagnosis, entertainment, and military applications. As the technology develops, it aims to run faster and more accurately on mobile devices and remote computers. In this paper, we aim to compare a number of the best face recognition algorithms and analyze the performance of each of them by deploying each algorithm on a Jetson Nano Developer Kit. Among the 6 algorithms

The issues of multitude of noisy, irrelevant, misleading features, and the capability to tackle inaccurate and inconsistent data in real world topics are the justification to turn into one of the most significant needs for feature selection. This paper proposes an intelligent hybrid approach using Rough Set Theory (RST), Chaos Theory and Binary Grey Wolf Optimization Algorithm (CBGWO) for feature selection problems. Ten different chaotic maps are used to estimate and tune GWO parameters. Experiments are applied on complex medical datasets with various uncertainty features and missing values

The degree to which innovators adopt Blockchain as a tool to create relevant and useful business solutions will determine how fast and far the platform moves into our daily lives. There are limitless opportunities for technology to define and shape future innovation. In a world dominated by digital technology, IoT plays a prominent role in our lives. It has created an ecosystem that links many systems to give smart performances in every task. The proliferation of the IoT has created a new evolution of cell phones, home and other embedded applications that are all connected to the internet

Conceptual cost estimates, are prepared at the very early stages of a project, and generally before the construction drawings and specifications are available. At this stage, cost estimates are needed by the owner, contractor, designer, or funding agencies for determination of the feasibility of a project, financial evaluation of a number of alternative projects, or establishment of an initial budget. Traditional approaches rely heavily on experienced engineers. This paper presents a method using fuzzy clustering technique for pump station projects cost estimation. The proposed conceptual cost