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Anaerobic Digestion and Codigestion of Chlorella Vulgaris Microalgae Biomass with Wastewater Sludge and Dairy Manure for Biogas Production
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Abstract

 

Anaerobic digestion process of organic materials is biochemical decomposition process done by two types of digestion bacteria in the absence of oxygen resulting in the biogas production, which is produced as a waste product of digestion. The first type of bacteria is known as acidogenic which converts organic waste to fatty acids. The second type of bacteria is called methane creators or methanogenic which transforms the fatty acids to biogas (CH4 and CO2). The considerable amounts of biodegradable constitutes such as carbohydrates, lipids and proteins present in the microalgae biomass make it a suitable substrate for the anaerobic digestion or even co-digested with other organic wastes. The present work investigated methane biogas production by anaerobic codigestion of microalgae, Chlorella vulgaris biomass with organic waste from several sources such as wastewater sludge and dairy manure waste in different proportions as an additional carbon supply to enhance anaerobic digestion and therefore biogas production. Six bottles, employed as batch biodigesters each of 1 liter capacity, were used for that purpose at moderate conditions (35±2 oC). The produced biogas volume was monitored daily along 35 days and the results showed that the daily and cumulative biogas production was increased 4.5 times and 3 times for the bottles with 66.67% microalgae compared with the bottles with wastewater sludge or dairy manure waste only, respectively.

 Keywords: Anaerobic codigestion, biogas; dairy manure, microalgae Chlorella Vulgaris, wastewater sludge.

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Publication Date
Sun May 01 2022
Journal Name
Journal Of Engineering
Performance Analysis of different Machine Learning Models for Intrusion Detection Systems
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In recent years, the world witnessed a rapid growth in attacks on the internet which resulted in deficiencies in networks performances. The growth was in both quantity and versatility of the attacks. To cope with this, new detection techniques are required especially the ones that use Artificial Intelligence techniques such as machine learning based intrusion detection and prevention systems. Many machine learning models are used to deal with intrusion detection and each has its own pros and cons and this is where this paper falls in, performance analysis of different Machine Learning Models for Intrusion Detection Systems based on supervised machine learning algorithms. Using Python Scikit-Learn library KNN, Support Ve

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Publication Date
Sun Sep 01 2019
Journal Name
2019 11th Computer Science And Electronic Engineering (ceec)
ANN based Measurement for No-Reference Video Quality of Experience Metric
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Publication Date
Thu May 18 2023
Journal Name
Journal Of Engineering
Development of Pavement Maintenance Management System for Baghdad Urban Roadway Network
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The road transportation system is considered as major component of the infrastructure in any country, it affects the developments in economy and social activities. The Asphalt Concrete which is considered as the major pavement material for the road transportation system in Baghdad is subjected to continuous deterioration with time due to traffic loading and environmental conditions, it was felt that implementing a comprehensive pavement maintenance management system (PMMS), which should be capable for preserving the functional and structural conditions of pavement layers, is essential. This work presents the development of PMMS with Visual inspection technique for evaluating the Asphalt Concrete pavement surface condition; common types o

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Publication Date
Mon Feb 27 2023
Journal Name
Applied Sciences
Comparison of ML/DL Approaches for Detecting DDoS Attacks in SDN
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Software-defined networking (SDN) presents novel security and privacy risks, including distributed denial-of-service (DDoS) attacks. In response to these threats, machine learning (ML) and deep learning (DL) have emerged as effective approaches for quickly identifying and mitigating anomalies. To this end, this research employs various classification methods, including support vector machines (SVMs), K-nearest neighbors (KNNs), decision trees (DTs), multiple layer perceptron (MLP), and convolutional neural networks (CNNs), and compares their performance. CNN exhibits the highest train accuracy at 97.808%, yet the lowest prediction accuracy at 90.08%. In contrast, SVM demonstrates the highest prediction accuracy of 95.5%. As such, an

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Publication Date
Wed Oct 12 2022
Journal Name
Axioms
Razy: A String Matching Algorithm for Automatic Analysis of Pathological Reports
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Pathology reports are necessary for specialists to make an appropriate diagnosis of diseases in general and blood diseases in particular. Therefore, specialists check blood cells and other blood details. Thus, to diagnose a disease, specialists must analyze the factors of the patient’s blood and medical history. Generally, doctors have tended to use intelligent agents to help them with CBC analysis. However, these agents need analytical tools to extract the parameters (CBC parameters) employed in the prediction of the development of life-threatening bacteremia and offer prognostic data. Therefore, this paper proposes an enhancement to the Rabin–Karp algorithm and then mixes it with the fuzzy ratio to make this algorithm suitable

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Publication Date
Fri May 03 2024
Journal Name
Journal Of Optics
Transmission Of 10 Gb/s For Underwater Optical Wireless Communication System
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Publication Date
Mon Jan 01 2024
Journal Name
Recent Research On Geotechnical Engineering, Remote Sensing, Geophysics And Earthquake Seismology
Evaluating the Accuracy of iPhone Lidar Sensor for Building Façades Conservation
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Publication Date
Mon Jan 28 2019
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Economic analysis of the investment of human capital and the policy of privatization
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The research problem is dedicated to investigate reservoirs irrational economic behavior adopted by the ruling elites in developing countries about the investment methodology of human capital and operating policies is based on the terms of reference of economic theory and standards governing the market, which led to a chronic structural imbalance in the workforce structure and lack of consistency with different production structure, in turn, which had a reported effects in the emergence of the phenomenon of unemployment and that they involved a certain privacy, as has become the issues of unemployment and employment in the various countries of the world are issues more important due to the presence of large numbers of the workforce in th

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Publication Date
Mon Jan 01 2018
Journal Name
Iraqi Journal Of Embryos & Infertility Researches
Analysis of Amino Acids of the Brain in Embryo and Adult of Quail.
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Amino acids have the role in the process of proteins synthesis. They are an essential source of nitrogen atoms that have a role in the pathways of synthetic reaction pathways. The carbon skeletons of the amino acids are the source of energy in addition to their role as precursors in the paths of interactions. The amino acids analysis for the brain of the quail bird in different stage of development (10-16 days of incubation) in addition to the hatching stage (17th day) and the adult. Materials and Methods: Amino Acids Analysis The amino acids were separated from the embryos and adult brains of the quail bird Coturnix coturnix and were diagnosed based on standard amino acids, using high performance liquid chromatographic device (H.P.L.C.). R

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Publication Date
Thu Jan 01 2015
Journal Name
International Journal Of Astronomy And Astrophysics
Determination of Velocity and Radius of Supernova Remnant after 1000 yrs of Explosion
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Supernova explosions are described as very violent events which transfer a significant amount of energy to interstellar media and are responsible for a large variety of physical processes. This study does not discuss the actual explosion mechanisms but follows the behavior of the dynamical evolution of some selected type I and type II supernova remnant and particularly after a thousand years from their explosion and shows how the density of the medium affects the evolution and the lifetime of each remnant. By studying such behaviors, a simplified model has been proposed here for the velocity and radius of the remnant after thousand years of explosion that depends only on the density of the medium and age of the remnant. It has been found th

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