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Multiple and Coherent Noise Removal from X-Profile 2D Seismic Data of Southern Iraq Using Normal Move Out-Frequency Wavenumber Technique
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Multiple eliminations (de-multiple) are one of seismic processing steps to remove their effects and delineate the correct primary refractors. Using normal move out to flatten primaries is the way to eliminate multiples through transforming these data to frequency-wavenumber domain. The flatten primaries are aligned with zero axis of the frequency-wavenumber domain and any other reflection types (multiples and random noise) are distributed elsewhere. Dip-filter is applied to pass the aligned data and reject others will separate primaries from multiple after transforming the data back from frequency-wavenumber domain to time-distance domain. For that, a suggested name for this technique as normal move out- frequency-wavenumber domain method for multiple eliminations. The method is tested on a fake reflection event to authorize their validity, and applied to a real field X-profile 2D seismic data from southern Iraq. The results ensure the possibility of internal multiple types existing in the deep reflection data in Iraq and have to remove. So that the interpretation for the true reflectors be valid. The final processed stacked seismic data using normal move out- frequency-wavenumber domain technique shows good, clear, and sharp reflectors in comparison with the conventional normal move out stack data. Open-source Madagascar reproducible package is used for processing all steps of this study and the package is very efficient, accurate, and easy to implement normal move out, frequency-wavenumber domain, Dip-filter programs. The aim of the current study is to separate internal multiples and noise from the real 2D seismic data.

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Publication Date
Thu Apr 27 2023
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Evaluation of the Effect of Type II Diabetes mellitus on Bone Mineral Density of Upper and Lower Limbs by Dual-Energy X-Ray Absorptiometry
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Background: Bone mineral density has been assessed using Dual-Energy X-Ray Absorptiometry. Bone mineral density is measured according to the results of the Dual-Energy X-Ray Absorptiometry examination of the vertebral column and pelvis. Although diabetes mellitus type II (DM) is known to affect bone mineral density, at the present time this particular relationship is not clear. Objective: The aim of current study was to evaluate the effects of type II diabetes mellitus on bone mineral density of the upper and lower limbs as well as gender differences. Patients and Methods: This study involved 165 patients complaining of bone pain (85 males and 80 females), 85 patients of who suffered from diabetes, involving both genders. In addition,

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Publication Date
Sun Jun 30 2024
Journal Name
International Journal Of Intelligent Engineering And Systems
Eco-friendly and Secure Data Center to Detection Compromised Devices Utilizing Swarm Approach
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Modern civilization increasingly relies on sustainable and eco-friendly data centers as the core hubs of intelligent computing. However, these data centers, while vital, also face heightened vulnerability to hacking due to their role as the convergence points of numerous network connection nodes. Recognizing and addressing this vulnerability, particularly within the confines of green data centers, is a pressing concern. This paper proposes a novel approach to mitigate this threat by leveraging swarm intelligence techniques to detect prospective and hidden compromised devices within the data center environment. The core objective is to ensure sustainable intelligent computing through a colony strategy. The research primarily focusses on the

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Publication Date
Fri Jan 01 2021
Journal Name
Journal Of Intelligent Systems
Void-hole aware and reliable data forwarding strategy for underwater wireless sensor networks
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Abstract<p>Reliable data transfer and energy efficiency are the essential considerations for network performance in resource-constrained underwater environments. One of the efficient approaches for data routing in underwater wireless sensor networks (UWSNs) is clustering, in which the data packets are transferred from sensor nodes to the cluster head (CH). Data packets are then forwarded to a sink node in a single or multiple hops manners, which can possibly increase energy depletion of the CH as compared to other nodes. While several mechanisms have been proposed for cluster formation and CH selection to ensure efficient delivery of data packets, less attention has been given to massive data co</p> ... Show More
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Publication Date
Mon Apr 11 2011
Journal Name
Icgst
Employing Neural Network and Naive Bayesian Classifier in Mining Data for Car Evaluation
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In data mining, classification is a form of data analysis that can be used to extract models describing important data classes. Two of the well known algorithms used in data mining classification are Backpropagation Neural Network (BNN) and Naïve Bayesian (NB). This paper investigates the performance of these two classification methods using the Car Evaluation dataset. Two models were built for both algorithms and the results were compared. Our experimental results indicated that the BNN classifier yield higher accuracy as compared to the NB classifier but it is less efficient because it is time-consuming and difficult to analyze due to its black-box implementation.

Publication Date
Mon Dec 05 2022
Journal Name
Baghdad Science Journal
A Security and Privacy Aware Computing Approach on Data Sharing in Cloud Environment
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Today, the role of cloud computing in our day-to-day lives is very prominent. The cloud computing paradigm makes it possible to provide demand-based resources. Cloud computing has changed the way that organizations manage resources due to their robustness, low cost, and pervasive nature. Data security is usually realized using different methods such as encryption. However, the privacy of data is another important challenge that should be considered when transporting, storing, and analyzing data in the public cloud. In this paper, a new method is proposed to track malicious users who use their private key to decrypt data in a system, share it with others and cause system information leakage. Security policies are also considered to be int

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Publication Date
Fri Sep 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
Semi parametric Estimators for Quantile Model via LASSO and SCAD with Missing Data
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In this study, we made a comparison between LASSO & SCAD methods, which are two special methods for dealing with models in partial quantile regression. (Nadaraya & Watson Kernel) was used to estimate the non-parametric part ;in addition, the rule of thumb method was used to estimate the smoothing bandwidth (h). Penalty methods proved to be efficient in estimating the regression coefficients, but the SCAD method according to the mean squared error criterion (MSE) was the best after estimating the missing data using the mean imputation method

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Publication Date
Mon Apr 17 2017
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
10.28936 STUDY OF THE KINETIC AND ADSORPTION ISOTHERM PARAMETERS FOR REMOVING COPPER AND IRON IONS FROM AQUEOUS SOLUTIONS BY USING AGRICALTURAL BY-PRODUCTS.: STUDY OF THE KINETIC AND ADSORPTION ISOTHERM PARAMETERS FOR REMOVING COPPER AND IRON IONS FROM AQUEOUS SOLUTIONS BY USING AGRICALTURAL BY-PRODUCTS.
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Wheat straw was modified with malonic acid in order to get low cost adsorbent have a good ability to remove copper and ferric ions from aqueous solutions, chemical modification temperature was 120°C and the time was 12 h. Parameters that affect the adsorption experiments were studied and found the optimum pH were 6 and 5 for copper and iron respectively and the time interval was 120 min and the adsorbent mass was 0.1 g. The values for adsorption isotherms parameters were determined according to Langmuir [qmax were 54.64 and 61.7 mg/g while b values were 0.234 and 0.22 mg/l] , Freundlich [Kf were 16.07 and 18.89 mg/g and n were 2.77 and 3.16], Temkin [B were 0.063 and 0.074 j/mol and At were 0.143 and 1.658 l/g] and for Dubinin-Radushkev

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Publication Date
Sat Dec 20 2025
Journal Name
Bulletin Of The Iraq Natural History Museum
MORPHOLOGICAL AND MOLECULAR DESCRIPTION FOR A NEW RECORD OF NEMATODE ACROBELOIDES VARIUS KIM, KIM &amp; PARK, 2017 (RHABDITIDA, CEPHALOBIDAE) FROM IRAQ
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This study aimed to identify and describe one of the bacterial feeder nematode Acrobeloides varius Kim, Kim and Park, 2017 (Rhabditida, Cephalobidae), which was isolated from soil samples that were collected from Baghdad, central of Iraq, and was classified using both morphological and molecular criteria. All specimens of A. varius were cultured, identified and described using morphometric criteria. Selected specimens (Zah. IRQ3 OR994579.1 isolate) of this species were characterized by having the body length of the male ranging from (184.94 – 221.72 μm), the body length of the female ranging (507.38 – 521.92 μm) and the body length of the juvenile ranging from (355.53 – 490.35 μm). Selected specimens of this species were m

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Publication Date
Fri Dec 01 2017
Journal Name
International Journal Of Science And Research (ijsr)
Histological Study of Some Isolation Fungi from Iraq / Baghdad Hospitals Apparatus that affected in Liver, Kidney and Testes in Albino Mice
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Publication Date
Tue Feb 01 2022
Journal Name
Baghdad Science Journal
Evaluation of Amygdalin (B17) and Cucurbita pepo (Pumpkin seed) Activity Against Blastocystis from Diarrheic Patients in Baghdad, Iraq: in Vitro Study
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Blastocystis is a ubiquitous human and animal protozoa that inhabit the gastrointestinal tract. Metronidazole is considered the standard drug for the treatment of Blastocystis infection; however, there is growing evidence of treatment failure, hazardous side effects, and appearance of strains resistant to metronidazole. In the last era, many studies have been implicated in the quest for new treatments for Blastocystis infection, especially natural products. Attention has been focused on the effect of Amygdalin (B17) and pumpkin seed on eradicating parasitic infections. The current work was built up to explore the in vitro efficacy of two natural compounds, Amygdalin (B17) and pumpkin seeds against

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