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Parametric Study on Unconnected Piled Raft Foundation Using Numerical Modelling
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Piled raft is commonly used as foundation for high rise buildings. The design concept of piled raft foundation is to minimize the number of piles, and to utilize the entire bearing capacity. High axial stresses are therefore, concentrated at the region of connection between the piles and raft. Recently, an alternative technique is proposed to disconnect the piles from the raft in a so called unconnected piled raft (UCPR) foundation, in which a compacted soil layer (cushion) beneath the raft, is usually introduced.  The piles of the new system are considered as reinforcement members for the subsoil rather than as structural members. In the current study, the behavior of unconnected piled rafts systems has been studied numerically by means of 3D Finite Element analysis via ABAQUS software. The numerical analysis was carried out to investigate the effect of thickness and stiffness of the cushion, pile length, stiffness of foundation soil, and stiffness of bearing soil on the performance of the unconnected piled raft. The results indicate that when unconnected piles are used, the axial stress along the pile is significantly reduced e.g. the axial stress at head of unconnected pile is decreased by 37.8% compared with that related to connected pile. It is also found that the stiffness and thickness of the cushion, and stiffness of foundation soil have considerable role on reduction the settlement.

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Publication Date
Mon May 20 2019
Journal Name
Journal Of Planner And Development
THE EVALUATION OF PUBLIC SERVICES IN BAQUBAH CITY BY USING REMOTE SENSING & GIS TECHNIQUES
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Baqubah city has grown extremely rapidly. The rate of growth exceeds the growth of services that must grow side by side with the growth of population. There are natural features that affect the growth of Baqubah city such as Dieyala river, Alssariya river, in addition to agricultural areas .All these natural features affect the growth of Baqubah city in the running form being seen . In this research the remote sensing and geographic information system (GIS) techniques are used for monitoring urban expansion and forecasting the probable axes to the growth of the city, and found that the probability of Baqubah growth to east is preferred due to Baqubah growth to the east would never interfere with natural features. Also in this res

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Publication Date
Sun Jun 12 2011
Journal Name
Baghdad Science Journal
Monitoring the Vegetation and Water Content of Al-Hammar Marsh Using Remote Sensing Techniques
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The object of the presented study was to monitor the changes that had happened in the main features (water, vegetation, and soil) of Al-Hammar Marsh region. To fulfill this goal, different satellite images had been used in different times, MSS 1973, TM 1990, ETM+ 2000, 2002, and MODIS 2009, 2010. A new technique of the unsupervised classification called (Color Extracting Technique) was used to classify the satellite images. MATLAP programming used the technique and separated Al-Hammar Marsh from other water features (rivers, irrigated lands, etc.) when calculated the changes in the water content of the study region. ArcGIS 9.3 (arcMAP, arcToolbox) were used to achieve this work and calculate area of each class.

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Publication Date
Sun Mar 05 2017
Journal Name
Baghdad Science Journal
Using Phragmites australis(Iraqi plant) to remove the Lead (II) Ions form Aqueous solution.
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Lead remediation was achieved using simple cost, effective and eco-friendly way from industrial wastewater. Phragmitesaustralis (P.a) (Iraqi plant), was used as anovel biomaterial to remove lead ions from synthesized waste water. Different parameters which affected on adsorption processes were investigated like adsorbent dose, pH, contact time, and adsorbent particle size, to reach the optimized conditions (maximum adsorption). The adsorption of Pb (?) on (P.a) involved fast and slow process as a mechanism steps according to obey two theoretical adsorption isotherms; Langmuir and Freundlich. The thermos dynamic adsorption parameters were evaluated also. The (?H) obtained positive value that meanes adsorption of lead ions was an endothermic

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Publication Date
Mon Jan 01 2018
Journal Name
Communications In Computer And Information Science
Automatically Recognizing Emotions in Text Using Prediction by Partial Matching (PPM) Text Compression Method
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In this paper, we investigate the automatic recognition of emotion in text. We perform experiments with a new method of classification based on the PPM character-based text compression scheme. These experiments involve both coarse-grained classification (whether a text is emotional or not) and also fine-grained classification such as recognising Ekman’s six basic emotions (Anger, Disgust, Fear, Happiness, Sadness, Surprise). Experimental results with three datasets show that the new method significantly outperforms the traditional word-based text classification methods. The results show that the PPM compression based classification method is able to distinguish between emotional and nonemotional text with high accuracy, between texts invo

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Publication Date
Sat Dec 01 2012
Journal Name
Journal Of Economics And Administrative Sciences
Eatimation Availability Function Through Determination The Optimal Imperfect Preventive Maintenance Period By using Simulation
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This paper deals with the modeling of a preventive maintenance strategy applied to a single-unit system subject to random failures.

According to this policy, the system is subjected to imperfect periodic preventive maintenance restoring it to ‘as good as new’ with probability

p and leaving it at state ‘as bad as old’ with probability q. Imperfect repairs are performed following failures occurring between consecutive

preventive maintenance actions, i.e the times between failures follow a decreasing quasi-renewal process with parameter a. Considering the

average durations of the preventive and corrective maintenance actions a

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Publication Date
Wed Mar 01 2023
Journal Name
Evergreen
Combustion Characteristics of a Free Piston Engine Linear Generator using Various Fuel Injection Durations
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Publication Date
Fri Sep 01 2017
Journal Name
International Journal Of Engineering Research And Advanced Technology
. Medical Image Compression using Hybrid Technique of Wavelet Transformation and Seed Selective Predictive Method
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Publication Date
Fri Sep 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
Distinguishing Shapes of Breast Cancer Masses in Ultrasound Images by Using Logistic Regression Model
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The last few years witnessed great and increasing use in the field of medical image analysis. These tools helped the Radiologists and Doctors to consult while making a particular diagnosis. In this study, we used the relationship between statistical measurements, computer vision, and medical images, along with a logistic regression model to extract breast cancer imaging features. These features were used to tell the difference between the shape of a mass (Fibroid vs. Fatty) by looking at the regions of interest (ROI) of the mass. The final fit of the logistic regression model showed that the most important variables that clearly affect breast cancer shape images are Skewness, Kurtosis, Center of mass, and Angle, with an AUCROC of

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Publication Date
Thu Mar 29 2018
Journal Name
Construction Research Congress 2018
Validation of Time-Safety Influence Curve Using Empirical Safety and Injury Data—Poisson Regression
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Publication Date
Sat Oct 04 2025
Journal Name
Mesopotamian Journal Of Computer Science
Enhanced IOT Cyber-Attack Detection Using Grey Wolf Optimized Feature Selection and Adaptive SMOTE
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The Internet of Things (IoT) has significantly transformed modern systems through extensive connectivity but has also concurrently introduced considerable cybersecurity risks. Traditional rule-based methods are becoming increasingly insufficient in the face of evolving cyber threats.  This study proposes an enhanced methodology utilizing a hybrid machine-learning framework for IoT cyber-attack detection. The framework integrates a Grey Wolf Optimizer (GWO) for optimal feature selection, a customized synthetic minority oversampling technique (SMOTE) for data balancing, and a systematic approach to hyperparameter tuning of ensemble algorithms: Random Forest (RF), XGBoost, and CatBoost. Evaluations on the RT-IoT2022 dataset demonstrat

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