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Crude Oil Price Forecasts Using Support Vector Regression and Technical Indicators
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Oil price forecasting has captured the attention of both researchers and academics because of the unique characteristics of crude oil prices and how they have a big impact on a lot of different parts of the economic value of the product. As a result, most academics use a lot of different ways to predict the future. On the other hand, researchers have a hard time because crude oil prices are very unpredictable and can be affected by many different things. This study uses support vector regression (SVR) with technical indicators as a feature to improve the prediction of the monthly West Texas Intermediate (WTI) price of crude oil. The root mean square error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE) measure how well the model is working. The RMSE was 1.5456, the MAE was 1.3219, and the MAPE was 1.9173 in the experiment. The results show that WTI crude oil prices are affected by technical indicators and get good performance that outperforms most other models that can be found.

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Publication Date
Tue Sep 01 2015
Journal Name
Journal Of Engineering
Cost of Optimum Design of Trunk Mains Network Using Geographical Information System and Support Programs
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Sewer network is one of the important utilities in modern cities which discharge the sewage from all facilities. The increase of population numbers consequently leads to the increase in water consumption; hence waste water generation. Sewer networks work is very expensive and need to be designed accurately. Thus construction effective sewer network system with minimum cost is very necessary to handle waste water generation.

 In this study trunk mains networks design was applied which connect the pump stations together by underground pipes for too long distances. They usually have large diameters with varying depths which consequently need excavations and gathering from pump stations and transport the sewage

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Publication Date
Sun Jan 01 2023
Journal Name
Aip Conference Proceedings
Mining categorical Covid-19 data using chi-square and logistic regression algorithms
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Publication Date
Sat Dec 31 2022
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Estimation of nonparametric regression function using shrinkage wavelet and different mother functions
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Publication Date
Sun Oct 30 2022
Journal Name
Iraqi Journal Of Science
An Internet of Things Botnet Detection Model Using Regression Analysis and Linear Discrimination Analysis
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The Internet of Things (IoT) has become a hot area of research in recent years due to the significant advancements in the semiconductor industry, wireless communication technologies, and the realization of its ability in numerous applications such as smart homes, health care, control systems, and military. Furthermore, IoT devices inefficient security has led to an increase cybersecurity risks such as IoT botnets, which have become a serious threat. To counter this threat there is a need to develop a model for detecting IoT botnets.

This paper's contribution is to formulate the IoT botnet detection problem and introduce multiple linear regression (MLR) for modelling IoT botnet features with discriminating capability and alleviatin

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Publication Date
Thu Dec 30 2021
Journal Name
Iraqi Journal Of Science
Protective influence of Costus afer Aqueous Extract In Rats Fed With Crude Oil Contaminated Diet as Measured by Employing Biochemical Indices
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The use of medicinal plants in the treatment of harmful impacts of xenobiotics in animals is attracting an increasing attention in recent times. The aim of the current study is to assess the preventive potential of Costus afer aqueous leaves extract (CAAE) in treating metabolic aberrations imposed by crude oil contaminated diet in
Wistar albino rats. Six groups of rats were treated as follows: A = Normal diet; B=Normal diet + 100 mg/kg body weight of CAAE; C =Normal diet + 200 mg/kg body weight of CAAE; D= Crude oil contaminated diet; E= crude oil contaminated diet + 100 mg/kg body weight of CAAE, F = crude oil contaminated diet + 200 mg/kg body weight of CAAE. After thirty days of exposure to the diet and administration of the corres

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Publication Date
Sun Jan 27 2019
Journal Name
Civil Engineering Journal
Prediction of Sediment Accumulation Model for Trunk Sewer Using Multiple Linear Regression and Neural Network Techniques
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Sewer sediment deposition is an important aspect as it relates to several operational and environmental problems. It concerns municipalities as it affects the sewer system and contributes to sewer failure which has a catastrophic effect if happened in trunks or interceptors. Sewer rehabilitation is a costly process and complex in terms of choosing the method of rehabilitation and individual sewers to be rehabilitated.  For such a complex process, inspection techniques assist in the decision-making process; though, it may add to the total expenditure of the project as it requires special tools and trained personnel. For developing countries, Inspection could prohibit the rehabilitation proceeds. In this study, the researchers propos

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Publication Date
Mon Jan 01 2007
Journal Name
2007 Ieee International Conference On Signal Processing And Communications
Fast Multi-level Image Vector Quantization
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Publication Date
Sun Apr 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Estimate Kernel Ridge Regression Function in Multiple Regression
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             In general, researchers and statisticians in particular have been usually used non-parametric regression models when the parametric methods failed to fulfillment their aim to analyze the models  precisely. In this case the parametic methods are useless so they turn to non-parametric methods for its easiness in programming. Non-parametric methods can also used to assume the parametric regression model for subsequent use. Moreover, as an advantage of using non-parametric methods is to solve the problem of Multi-Colinearity between explanatory variables combined with nonlinear data. This problem can be solved by using kernel ridge regression which depend o

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Publication Date
Tue Jan 11 2022
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Permeability Enhancement of Methotrexate Transdermal Gel using Eucalyptus oil, Peppermint Oil and Olive Oil(Conference Paper )#
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Abstract

Objective: the idea of this study to improve transdermal permeability of Methotrexate using eucalyptus oil, olive oil and peppermint oil as enhancers.
Method: eucalyptus oil (2% and 4%), peppermint oil (2% and 4%) and olive oil (2% and 4%) all used as natural enhancers to develop transdermal permeability of Methotrexate via gel formulation. The gel was subjected to many physiochemical properties tests. In-vitro release and permeability studies for the drug were done by Franz cell diffusion across synthetic membrane, kinetic model was studied via korsmeyer- peppas equation.
Result: the results demonstrate that safe, nonirritant or cause necrosis to rats' skin and stable till 60 days gel was successfully formulated.<

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Publication Date
Mon Aug 07 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
The Impact of Ascending Levels of Crude Oil Pollution on Growth of Olive ( Olea europaea Linn) Seedlings
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A study on the impact of ascending levels of crude oil on the growth of transplanted seedlings ( March2005 ) of Olive (Olea europaea Linn) was carried out at the experimental area of Iraq Natural History Museum and Research centre / Baghdad University (Bab-Al-Madham –Baghdad)  grown under field condition  and continued till April 2008.The experiment was laid out in complete randomized design ( CRD ) with five levels of pollution (0.0 , 0.5 , 1.0 , 2.0 and 3.0 liter / seedling ) poured at the soil surface , each seedling represented one replicate and was replicated four times . Data collected from the experiment were visual symptoms , percents of seedlings death, plant height and total  dry weight  of harvested

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