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Prediction Unconfined Compressive Strength for Different Lithology Using Various Wireline Type and Core Data for Southern Iraqi Field
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Unconfined Compressive Strength is considered the most important parameter of rock strength properties affecting the rock failure criteria.  Various research have developed rock strength for specific lithology to estimate high-accuracy value without a core.  Previous analyses did not account for the formation's numerous lithologies and interbedded layers. The main aim of the present study is to select the suitable correlation to predict the UCS for hole depth of formation without separating the lithology. Furthermore, the second aim is to detect an adequate input parameter among set wireline to determine the UCS by using data of three wells along ten formations (Tanuma, Khasib, Mishrif, Rumaila, Ahmady, Maudud, Nahr Umr, Shuaiba and Zubair). After calibration with core test, the results revealed that Young’s Modulus correlations are the best to predict UCS with RMSE (53.23 psi).

Furthermore, the result showed that using the static Young Modulus as an input parameter in predicting UCS gives a closer result to the laboratory test than using a sonic log. This study found that many previous equations were developed for only one type of rock and tended to generalize poorly to the broader database. This study also provided more accurate rock strength estimation, leading to better prognosis in operational strategies and hydraulic fracturing location planning in oil well development when geomechanical analysis needs to be addressed where no core is available. Finally, the expected continuous rock mechanical profile indicates the formation's strength and stability around the wellbore.

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Publication Date
Mon Mar 09 2020
Journal Name
Agrosystems, Geosciences & Environment
In-season potato yield prediction with active optical sensors
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Crop yield prediction is a critical measurement, especially in the time when parts of the world are suffering from farming issues. Yield forecasting gives an alert regarding economic trading, food production monitoring, and global food security. This research was conducted to investigate whether active optical sensors could be utilized for potato (Solanum tuberosum L.) yield prediction at the mid.le of the growing season. Three potato cultivars (Russet Burbank, Superior, and Shepody) were planted and six rates of N (0, 56, 112, 168, 224, and 280 kg ha−1), ammonium sulfate, which was replaced by ammonium nitrate in the 2nd year, were applied on 11 sites in a randomized complete block design, with four replications. Normalized difference ve

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Publication Date
Mon Sep 30 2024
Journal Name
Iraqi Journal Of Science
Attention-Deficit Hyperactivity Disorder Prediction by Artificial Intelligence Techniques
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Attention-Deficit Hyperactivity Disorder (ADHD), a neurodevelopmental disorder affecting millions of people globally, is defined by symptoms of hyperactivity, impulsivity, and inattention that can significantly affect an individual's daily life. The diagnostic process for ADHD is complex, requiring a combination of clinical assessments and subjective evaluations. However, recent advances in artificial intelligence (AI) techniques have shown promise in predicting ADHD and providing an early diagnosis. In this study, we will explore the application of two AI techniques, K-Nearest Neighbors (KNN) and Adaptive Boosting (AdaBoost), in predicting ADHD using the Python programming language. The classification accuracies obtained w

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Publication Date
Thu Apr 04 2024
Journal Name
Journal Of Electrical Systems
AI-Driven Prediction of Average Per Capita GDP: Exploring Linear and Nonlinear Statistical Techniques
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Average per capita GDP income is an important economic indicator. Economists use this term to determine the amount of progress or decline in the country's economy. It is also used to determine the order of countries and compare them with each other. Average per capita GDP income was first studied using the Time Series (Box Jenkins method), and the second is linear and non-linear regression; these methods are the most important and most commonly used statistical methods for forecasting because they are flexible and accurate in practice. The comparison is made to determine the best method between the two methods mentioned above using specific statistical criteria. The research found that the best approach is to build a model for predi

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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
An Observation and Analysis the role of Convolutional Neural Network towards Lung Cancer Prediction
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Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c

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Publication Date
Mon May 01 2017
Journal Name
Journal Of Stored Products Research
Detection and prediction of Sitophilus oryzae infestations in triticale via visible and near-infrared spectral signatures
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Triticale is a hybrid of wheat and rye grown for use as animal feed. In Florida, due to its soft coat, triticale is highly vulnerable to Sitophilus oryzae L. (rice weevil) and there is interest in development of methods to detect early-instar larvae so that infestations can be targeted before they become economically damaging. The objective of this study was to develop prediction models of the infestation degree for triticale seed infested with rice weevils of different growth stages. Spectral signatures were tested as a method to detect rice weevils in triticale seed. Groups of seeds at 11 different levels (degrees) of infestation, 0–62%, were obtained by combining different ratios of infested and uninfested seeds. A spectrophotometer wa

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Publication Date
Thu Oct 31 2019
Journal Name
Asian Journal Of Pharmaceutical And Clinical Research
DESIGN, SYNTHESIS, DOCKING, ANTITUMOR SCREENING, AND ABSORPTION, DISTRIBUTION, METABOLISM, AND EXCRETION PREDICTION OF NEW HESPERDIN DERIVATIVE
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Objective: Hesperidin (HSP) is a pharmacologically active organic compound found in citrus fruits and peppermint. We synthesized a new HSP derivative by reacting it with 5-Amino-1,3,4-thiadiazole-2-thiol in acetic acid. Methods: This compound was characterized by Fourier-transform infrared, proton nuclear magnetic resonance, and electron impact mass spectra. A molecular docking study explores the predicted binding of the compound and its possible mode of action. Bioavailability, site of absorption, drug mimic, and topological polar surface was predicted using absorption, distribution, metabolism, and excretion (ADME) studies. Results: The docking study predicts that the new compound binds to the active sites of Aurora-B

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Publication Date
Sat Mar 26 2022
Journal Name
Indian Journal Of Ecology
Assessment of Antimicrobial Resistance to Klebsiella pneumonia Isolated from Various Clinical Samples in Baghdad
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Klebsiella pneumoniae is a severe opportunistic strain of enteric bacteria that is a major cause of urinary tract infection and pneumonia. This study was conducted in Baghdad City during September 2020-November 2020 on 50 clinical samples of urine, vaginal, sputum, wound swabs, ear swabs, and burn swabs. strains were identified using the VITEK-2 compact system and tested in K. pneumoniae terms of susceptibility to various antimicrobial drugs by Kirby-Bauer test. The isolates were more predominant in the females (56%) compared to males (44%). The antibiotic resistance rate of varied among different isolated clinical sample sources. K. pneumoniae K. pneumoniae isolated from different clinical specimens differed with respect

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Publication Date
Wed Jun 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
The role of the green human resources management practices in a achieving requirements of environmental citizenship- Field research at the General Company for Vegetable Oils.
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The research aims to determine the role of the practices of green human resources management in achieving requirements of environmental citizenship in the workplace, the General Company for Vegetable Oils was chosen for the application of field-side of research which represent one of the important industrial companies in Iraq, which suffers from poor Green human resources management applications, which reflected negatively on the development Environmental citizenship among Employees. The questionnaire use as a tool to collect data and information as well as field presence of the researcher, The research sample included (30) managers of departments and Division ,and through using statistical program (SPSS) the data has been analys

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Publication Date
Sun Jun 06 2010
Journal Name
Baghdad Science Journal
Preparation of Media for Growth and Isolation of Lactic Acid Bacteria by Using the Starch-Industry by- Products
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By- products of corn starch industry were used to prepare media for propagation the lactic acid bacteria as a natural auxotroph. The by- products used were the corn steep water (S) and gluten extract (G) after a proper treatment to get them ready for media preparation. The results showed that it was possible to replace the peptone and meat extract by gluten extract in MRS medium. The growth was approximately similar to that obtained in standard MRS media. Corn steep water (S) was used as well and the growth enhanced by including Tween – 80 at 1% level. The later media named MZ, which was superior for growing standard and local strains and starters. The MZ medium modified by adding acetate and glacial acetic acid similarly to

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Publication Date
Wed Jul 01 2020
Journal Name
Journal Of Engineering
Securing Physical Layer for FHSS Communication System Using Code andPhase Hopping Techniques in CDMA, System Design and Implementation
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The Frequency-hopping Spread Spectrum (FHSS) systems and techniques are using in military and civilianradar recently and in the communication system for securing the information on wireless communications link channels, for example in the Wi-Fi 8.02.X IEEE using multiple number bandwidth and frequencies in the wireless channel in order to hopping on them for increasing the security level during the broadcast, but nowadays FHSS problem, which is, any Smart Software Defined Radio (S-SDR) can easily detect a wireless signal at the transmitter and the receiver for the hopping sequence in both of these, then duplicate this sequence in order to hack the signal on both transmitter and receiver messages using the order of the se

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