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joe-1600
Evaluation of ANFIS and Regression Techniques in Estimating Soil Compression Index for Cohesive soils
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Generally, direct measurement of soil compression index (Cc) is expensive and time-consuming. To save time and effort, indirect methods to obtain Cc may be an inexpensive option. Usually, the indirect methods are based on a correlation between some easier measuring descriptive variables such as liquid limit, soil density, and natural water content. This study used the ANFIS and regression methods to obtain Cc indirectly. To achieve the aim of this investigation, 177 undisturbed samples were collected from the cohesive soil in Sulaymaniyah Governorate in Iraq. Results of this study indicated that ANFIS models over-performed the Regression method in estimating Cc with R2 of 0.66 and 0.48 for both ANFIS and Regression models, respectively. This work is an effort to practice the advantages of machine learning techniques to build a robust and cost-effective model for Cc estimation by designers, decision makers, and stakeholders.

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Publication Date
Tue Apr 30 2024
Journal Name
International Journal On Technical And Physical Problems Of Engineering
Deep Learning Techniques For Skull Stripping of Brain MR Images
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Deep Learning Techniques For Skull Stripping of Brain MR Images

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Publication Date
Mon Jan 01 2024
Journal Name
Aip Conference Proceedings
Comparative analysis of deep learning techniques for lung cancer identification
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One of the diseases on a global scale that causes the main reasons of death is lung cancer. It is considered one of the most lethal diseases in life. Early detection and diagnosis are essential for lung cancer and will provide effective therapy and achieve better outcomes for patients; in recent years, algorithms of Deep Learning have demonstrated crucial promise for their use in medical imaging analysis, especially in lung cancer identification. This paper includes a comparison between a number of different Deep Learning techniques-based models using Computed Tomograph image datasets with traditional Convolution Neural Networks and SequeezeNet models using X-ray data for the automated diagnosis of lung cancer. Although the simple details p

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Publication Date
Sat Nov 12 2016
Journal Name
International Journal Of Mechanical Engineering And Technology (ijmet)
PERFORMANCE OF TWO-WAY NESTING TECHNIQUES FOR SHALLOW WATER MODELS
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A new two-way nesting technique is presented for a multiple nested-grid ocean modelling system. The new technique uses explicit center finite difference and leapfrog schemes to exchange information between the different subcomponents of the nested-grid system. The performance of the different nesting techniques is compared, using two independent nested-grid modelling systems. In this paper, a new nesting algorithm is described and some preliminary results are demonstrated. The validity of the nesting method is shown in some problems for the depth averaged of 2D linear shallow water equation.

Publication Date
Sun Jul 31 2022
Journal Name
Iraqi Geological Journal
A Review of Historical Studies for Water Saturation Determination Techniques
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Water saturation is the most significant characteristic for reservoir characterization in order to assess oil reserves; this paper reviewed the concepts and applications of both classic and new approaches to determine water saturation. so, this work guides the reader to realize and distinguish between various strategies to obtain an appropriate water saturation value from electrical logging in both resistivity and dielectric has been studied, and the most well-known models in clean and shaly formation have been demonstrated. The Nuclear Magnetic Resonance in conventional and nonconventional reservoirs has been reviewed and understood as the major feature of this approach to estimate Water Saturation based on T2 distribution. Artific

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Publication Date
Sat Jan 01 2022
Journal Name
International Journal Of Agricultural And Statistical Sciences
ON ERROR DISTRIBUTION WITH SINGLE INDEX MODEL
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In this paper, the error distribution function is estimated for the single index model by the empirical distribution function and the kernel distribution function. Refined minimum average variance estimation (RMAVE) method is used for estimating single index model. We use simulation experiments to compare the two estimation methods for error distribution function with different sample sizes, the results show that the kernel distribution function is better than the empirical distribution function.

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Publication Date
Sat Apr 01 2023
Journal Name
Iop Conference Series: Earth And Environmental Science
Using PCR and Gel Electrophoresis Techniques to Molecular Confirm and Detection for Flowering Gene Presence in Maize Hybrids
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Abstract<p>The laboratory experiment was conducted in the laboratories of the Musayyib Bridge Company for Molecular Analyzes in the year 2021-2022 to study the molecular analysis of the inbreed lines and their hybrids F1 to estimate the genetic variation at the level of DNA shown by the selected pure inbreed lines and the resulting hybrids F1 of the flowering gene. Five pure inbreed lines of maize were selected (ZA17WR) Late, ZM74, Late, ZM19, Early ZM49WZ (Zi17WZ, Late, ZM49W3E) and their resulting hybrids, according to the study objective, from fifteen different inbreed lines with flowering time. The five inbreed lines were planted for four seasons (spring and fall 2019) and (spring and fall 2</p> ... Show More
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Publication Date
Fri Mar 14 2014
Journal Name
Arabian Journal Of Geosciences
Wetting and drying collapse behaviour of collapsible gypseous soils treated by grouting
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Publication Date
Sat May 01 2021
Journal Name
Iop Conference Series: Earth And Environmental Science
Isolation and Identification of Alkaline Protease Producing Aspergills niger from Iraqi Soils
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Abstract<p>Twenty purified isolates were obtained by using different soil sources, only twelve isolates belonging to Aspergillus genera depending on cultural and morphological characterization. The isolates were used as alkaline protease producer. The highest proteolytic, enzymatic activity (95.83U/ml) was obtained from <italic>Aspergillus</italic> sp. ZE isolate. This isolate was identified by 5.8 rRNA gene sequencing as <italic>Aspergills niger</italic> (accuracy of 99%), which was matched with the sequence of <italic>Aspergills niger</italic> strain GM775228 recorded in Gene bank under the ID: GM 775228.1.</p>
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Publication Date
Sun Dec 28 2025
Journal Name
Journal Of Baghdad College Of Dentistry
Evaluation of the push-out bond strength of root canal obturation materials filled by four different obturation techniques
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Background: The aim of this study was to comparatively evaluate the push out bond strength (PBS) of root canal fillings using four different obturation techniques (single cone (SC), cold lateral compaction (CLC), continuous wave (CW), and carrier based gutta percha (CBG)). Materials and Methods: Forty mandibular premolar decoronated and instrumented with rotary ProTaper to F3 then teeth were divided randomly into 4 groups of 10 teeth for each as follow: group (I) single- cone obturation with matched-taper gutta-percha, group (II) cold lateral compaction technique, group (III) continuous wave of obturation technique, and group( IV) carrier based gutta-percha technique. Zinc oxide eugenol (ZOE) sealer was used as a root canal sealer for the

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Publication Date
Mon Jun 01 2020
Journal Name
Journal Of Engineering
GIS as A Tool for Expansive Soil Detection at Sulaymaniyah City
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Geotechnical engineering like any other engineering field has to develop and cope with new technologies. This article intends to investigate the spatial relationships between soil’s liquid limit (LL), plasticity index (PI) and Liquidity index (LI) for particular zones of Sulaymaniyah City. The main objective is to study the ability to produce digital soil maps for the study area and determine regions of high expansive soil. Inverse Distance Weighting (IDW) interpolation tool within the GIS (Geographic Information System) program was used to produce the maps. Data from 592 boreholes for LL and PI and 245 boreholes for LI were used for this study. Layers were allocated into three depth ranges (1 to 2, 2 to 4 and 4 to 6)

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