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Analyzing the behavior of different classification algorithms in diabetes prediction
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<span lang="EN-US">Diabetes is one of the deadliest diseases in the world that can lead to stroke, blindness, organ failure, and amputation of lower limbs. Researches state that diabetes can be controlled if it is detected at an early stage. Scientists are becoming more interested in classification algorithms in diagnosing diseases. In this study, we have analyzed the performance of five classification algorithms namely naïve Bayes, support vector machine, multi layer perceptron artificial neural network, decision tree, and random forest using diabetes dataset that contains the information of 2000 female patients. Various metrics were applied in evaluating the performance of the classifiers such as precision, area under the curve (AUC), accuracy, receiver operating characteristic (ROC) curve, f-measure, and recall. Experimental results show that random forest is better than any other classifier in predicting diabetes with a 90.75% accuracy rate.</span>

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Publication Date
Tue Aug 03 2021
Journal Name
Key Engineering Materials
Study the Behavior of Castellated Steel Column Encasing by Different Reactive Powder Concrete Thickness with Laced Reinforcement
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Castellated columns are structural members that are created by breaking a rolled column along the center-line by flame after that rejoining the equivalent halves by welding such that for better structural strength against axial loading, the total column depth is increased by around 50 percent. The implementation of these institutional members will also contribute to significant economies of material value. The main objectives of this study are to study the enhancement of the load-carrying capacity of castellated columns with encasement of the columns by Reactive Powder Concrete (RPC) and lacing reinforcement, and serviceability of the confined castellated columns. The Castellated columns with RPC and Lacing Reinforcement improve com

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Publication Date
Sat Oct 01 2022
Journal Name
Civil Engineering Journal
Using CRF Tool for Analyzing the Resilience of Cities
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The new sustainable development goals set by the UN include a goal of making cities inclusive, safe, sustainable, and resilient. Cities are growing at huge rates, and conditions of deteriorating QOL̛s are increasing in the form of poor access to services, and slums are remarkable, especially in the cities of the Middle East; hence, the research problem can arise from a lack of knowledge regarding the in determination of a way to assess the resilience of cities to develop mechanisms that will improve the quality of urban life. In this study, a tool called CRF has been applied for the assessment of the city's resilience principles of health and quality of life, economics and social, infrastructure and environmental systems, and the principle

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Publication Date
Thu Sep 01 2011
Journal Name
Journal Of Economics And Administrative Sciences
Analyzing the relationship between stock market volatility and economic activity in the USA
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This study examines the dynamic relationship between stock market and economic activity in the United States to verify the possibility of using financial indicators to monitor the turning points in the expected path of future economic activity. Has been used methodology (Johansen - Juselius) for the Co-integration and causal (Granger) to test the relationship between the (S & P 500 , DJ) index  and gross domestic product (GDP) in the United States for the period
(1960-2009). The results of the analysis revealed the existence of a causal relationship duplex (two-way) between the variables mentioned. which means the possibility of the use stock market indicators to pre

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Publication Date
Mon Jun 01 2020
Journal Name
Journal Of Engineering
Artificial Neural Network (ANN) for Prediction of Viscosity Reduction of Heavy Crude Oil using Different Organic Solvents
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The increase globally fossil fuel consumption as it represents the main source of energy around the world, and the sources of heavy oil more than light, different techniques were used to reduce the viscosity and increase mobility of heavy crude oil. this study focusing on the experimental tests  and modeling with Back Feed Forward Artificial Neural Network (BFF-ANN) of the dilution technique to reduce a  heavy oil viscosity that was collected from the south- Iraq oil fields using organic solvents, organic diluents with different weight percentage  (5, 10 and  20 wt.% )  of  (n-heptane, toluene, and a mixture of  different ratio

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Publication Date
Tue Apr 20 2021
Journal Name
Journal Of Optical Communications
Analyzing of UVLC system considering the effect of water depth
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Abstract<p>This paper presents a new approach to discover the effect of depth water for underwater visible light communications (UVLC). The quality of the optical link was investigated with varying water depth under coastal water types. The performance of the UVLC with multiple input–multiple output (MIMO) techniques was examined in terms of bit error rate (BER) and data rate. The theoretical result explains that there is a good performance for UVLC system under coastal water.</p>
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Publication Date
Mon Jan 01 2018
Journal Name
Lecture Notes Of The Institute For Computer Sciences, Social Informatics And Telecommunications Engineering
Sensor Data Classification for the Indication of Lameness in Sheep
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Publication Date
Sat Jun 03 2023
Journal Name
Al-rafidain Journal Of Medical Sciences ( Issn: 2789-3219 )
Analyzing the Potential Antioxidative Effects of Omega-369 in Preventing Acetaminophen-Induced Liver Damage
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Background: As acetaminophen (APAP) toxicity has become more common in many countries, related cases of poisoning, whether deliberate or unintentional, have been identified as a key contributor to acute liver failure. Aime: To discover if omega-369 fatty acids could protect the liver of male mice from the effects of acetamiophen. Methods: Thirty-five albino male mice were allocated to one of five groups at random. Group 1 served as the "negative control" and received a single intraperitoneal injection (10 ml/kg) of normal saline on the eleventh day of the test following ten days of receiving liquid paraffin orally at a dose of 10 ml/kg. The liquid paraffin was given to group 2 "positive control". Group 3 received Omega 369 (50 mg/kg

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Publication Date
Sat Jun 29 2013
Journal Name
Journal Of Statistics Applications & Probability
Analyzing Skewed Data with the Epsilon Skew Gamma distribution
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A new distribution, the Epsilon Skew Gamma (ESΓ ) distribution, which was first introduced by Abdulah [1], is used on a near Gamma data. We first redefine the ESΓ distribution, its properties, and characteristics, and then we estimate its parameters using the maximum likelihood and moment estimators. We finally use these estimators to fit the data with the ESΓ distribution

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Publication Date
Wed May 24 2023
Journal Name
College Of Islamic Sciences
Analyzing the likeness of fundamentalists and examples of its jurisprudential applications
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The new events in every era are endless, and it is not required of the legal texts to pursue each event by itself and attach to it its ruling.
At the same time, every event or action must have a Shari’a ruling according to the wise Lawgiver, and our scholars have noted this in every event presented to them. ...etc.
It is well known that reaching the legal ruling on a matter, by examining the detailed evidence, is subject to following the path of the rules and regulations specific to the overall evidence, which we organize on the basis of the principles of jurisprudence.
Therefore, any disagreement about the manner or content of these rules will have an impact on the difference of jurists in partial issues, when examining the d

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Publication Date
Sun Jan 22 2023
Journal Name
Mesopotamian Journal Of Big Data
Parallel Machine Learning Algorithms
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 To expedite the learning process, a group of algorithms known as parallel machine learning algorithmscan be executed simultaneously on several computers or processors. As data grows in both size andcomplexity, and as businesses seek efficient ways to mine that data for insights, algorithms like thesewill become increasingly crucial. Data parallelism, model parallelism, and hybrid techniques are justsome of the methods described in this article for speeding up machine learning algorithms. We alsocover the benefits and threats associated with parallel machine learning, such as data splitting,communication, and scalability. We compare how well various methods perform on a variety ofmachine learning tasks and datasets, and we talk abo

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