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A survey on deep learning tools dealing with data scarcity: definitions, challenges, solutions, tips, and applications
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Abstract<p>Data scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications have small or inadequate data to train DL frameworks. Usually, manual labeling is needed to provide labeled data, which typically involves human annotators with a vast background of knowledge. This annotation process is costly, time-consuming, and error-prone. Usually, every DL framework is fed by a significant amount of labeled data to automatically learn representations. Ultimately, a larger amount of data would generate a better DL model and its performance is also application dependent. This issue is the main barrier for many applications dismissing the use of DL. Having sufficient data is the first step toward any successful and trustworthy DL application. This paper presents a holistic survey on state-of-the-art techniques to deal with training DL models to overcome three challenges including small, imbalanced datasets, and lack of generalization. This survey starts by listing the learning techniques. Next, the types of DL architectures are introduced. After that, state-of-the-art solutions to address the issue of lack of training data are listed, such as Transfer Learning (TL), Self-Supervised Learning (SSL), Generative Adversarial Networks (GANs), Model Architecture (MA), Physics-Informed Neural Network (PINN), and Deep Synthetic Minority Oversampling Technique (DeepSMOTE). Then, these solutions were followed by some related tips about data acquisition needed prior to training purposes, as well as recommendations for ensuring the trustworthiness of the training dataset. The survey ends with a list of applications that suffer from data scarcity, several alternatives are proposed in order to generate more data in each application including Electromagnetic Imaging (EMI), Civil Structural Health Monitoring, Medical imaging, Meteorology, Wireless Communications, Fluid Mechanics, Microelectromechanical system, and Cybersecurity. To the best of the authors’ knowledge, this is the first review that offers a comprehensive overview on strategies to tackle data scarcity in DL.</p>
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Publication Date
Fri Nov 29 2024
Journal Name
The Iraqi Geological Journal
Data Driven Approach for Predicting Pore Pressure of Oil and Gas Wells, Case Study of Iraq Southern Oilfields
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Precise forecasting of pore pressures is crucial for efficiently planning and drilling oil and gas wells. It reduces expenses and saves time while preventing drilling complications. Since direct measurement of pore pressure in wellbores is costly and time-intensive, the ability to estimate it using empirical or machine learning models is beneficial. The present study aims to predict pore pressure using artificial neural network. The building and testing of artificial neural network are based on the data from five oil fields and several formations. The artificial neural network model is built using a measured dataset consisting of 77 data points of Pore pressure obtained from the modular formation dynamics tester. The input variables

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Publication Date
Tue Oct 01 2019
Journal Name
Journal Of Engineering
Evaluation of the Performance of Online GPS/GNSS Data Processing Services for Monitoring the Land Deformations and Movements
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In recent years, the Global Navigation Satellite Services (GNSS) technology has been frequently employed for monitoring the Earth crust deformation and movement. Such applications necessitate high positional accuracy that can be achieved through processing GPS/GNSS data with scientific software such as BERENSE, GAMIT, and GIPSY-OSIS. Nevertheless, these scientific softwares are sophisticated and have not been published as free open source software. Therefore, this study has been conducted to evaluate an alternative solution, GNSS online processing services, which may obtain this privilege freely. In this study, eight years of GNSS raw data for TEHN station, which located in Iran, have been downloaded from UNAVCO website

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Publication Date
Wed Jan 31 2024
Journal Name
Iraqi Geological Journal
Estimation of Rock Mechanical Properties of the Hartha Formation and their Relationship to Porosity Using Well-Log Data
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The physical and elastic characteristics of rocks determine rock strengths in general. Rock strength is frequently assessed using porosity well logs such as neutron and sonic logs. The essential criteria for estimating rock mechanic parameters in petroleum engineering research are uniaxial compressive strength and elastic modulus. Indirect estimation using well-log data is necessary to measure these variables. This study attempts to create a single regression model that can accurately forecast rock mechanic characteristics for the Harth Carbonate Formation in the Fauqi oil field. According to the findings of this study, petrophysical parameters are reliable indexes for determining rock mechanical properties having good performance p

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Publication Date
Fri May 10 2019
Journal Name
Research Journal Of Chemistry And Environment
Solid Phase Extraction of Theophylline in Aqueous Solutions by Modified Magnetic Iron Oxide Nanoparticles as an Extractor Material and Spectrophotometry Technique for the Determination
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new, simple and fast solid-phase extraction method for separation and preconcentration of trace theophylline in aqueous solutions was developed using magnetite nanoparticles (MIONPs) coated with aluminium oxide (AMIONPs) and modified with palmitate (P) as an extractor (P@AMIONPs). It has shown that the developed method has a fast absorbent rate of the theophylline at room temperature. The parameters that affect the absorbent of theophylline in the aqueous solutions have been investigated such as the amount of magnetite nanoparticle, pH, standing time and the volume, concentration of desorption solution. The linear range, limit of quantification (LOQ) and limit of detection (LOD) for the determination of theophylline were 0.05-2.450 μg mL-

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Publication Date
Fri Aug 23 2024
Journal Name
Cureus
The Effect of Pan-Retinal Photocoagulation on Central Macular Thickness in a Sample of Iraqi Patients With Proliferative Diabetic Retinopathy
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Publication Date
Tue Oct 01 2019
Journal Name
Biochemical And Cellular Archives
THE EFFECT OF TWIST EXPRESSION ON THE DEVELOPMENT OF CERVICAL CARCINOMA IN A GROUP OF IRAQI WOMEN INFECTED WITH HPV
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Cervical carcinoma represent the second predominant cancer in female and there is a strong correlation between cervical cancer and the infection with high-risk types of HPV and expression the viral oncogenes. EMT is viewed as a vital advance in carcinoma development and ensuing metastasis. To evaluate correlation between the expression of Twist and HPV16 infection in a group of Iraqi patients with cervical carcinoma. A total of forty paraffin blocks included in this study which were divided into 30 sample of cervical cancer infected with HPV16and 10 sample of normal cervical tissues. The samples were subjected to immunohistochemical technique using Anti-Twist2 polyclonal antibody. The obtained data from this study indicate that majority of

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Publication Date
Wed Mar 29 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
A Comparative Biochemical Study of Proteins Profile in Iraqi Children and Adolescent with ?-Thalassemia
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The aim of the present research is to study different protein fractions in sera of children and adolescent with  β –thalassemia major and minor and to compare the results with that of healthy control.One hundred fifty children and adolescents were enrolled in this study,including 50 patients with β- thalassemia major , 50 patients with  β- thalassemia minor as pathological control group and another apparently 50 healthy individuals as a control group. The age of all studied  groups ranged from (4-18)years.Total protein, albumin and immunoglobulins were estimated in sera of all subjects.  A Significant  decrease  was  found  in  the  total  protein and  albumin&nb

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Publication Date
Tue Dec 01 2020
Journal Name
Baghdad Science Journal
A Competitive Study Using UV and Ozone with H2O2 in Treatment of Oily Wastewater
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          In this study, ultraviolet (UV), ozone techniques with hydrogen peroxide oxidant were used to treat the wastewater which is produced from South Baghdad Power Station using lab-scale system. From UV-H2O2 experiments, it was shown that the optimum exposure time was 80 min. At this time, the highest removal percentages of oil, COD, and TOC were 84.69 %, 56.33 % and 50 % respectively. Effect of pH on the contaminants removing was studied in the range of (2-12). The best oil, COD, and TOC removal percentages (69.38 %, 70 % and 52 %) using H2O2/UV were at pH=12. H2O2/ozone experiments exhibited better performance compared to

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Publication Date
Thu Jul 01 1999
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
Some leaf hopper and a plant hopper with their populations in Abu-Ghraib, Iraq
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Seven leafhoppers (Cicadeilidae). and one plantboppei (Delpbacidae), Homoptera were identified from a one year operated light trap at the College of Agiculture farm in Abu¬Ghraib. The leafhoppers were: Balclutha hortensis Lind.; B. rufaofasciata Merine.; psammctettix alien us Dahlbem.; P. striatus L.; Extianus capicola.; Neoaliturus haematoceps H. R.; and Orozius albicnctus Dist. The planthopper was Sogatella vibix Haupt. one year records of their populations, indicated that B. rufofasciata occured during the fall from October 10 until December 18; E. capicola from October 24 until November 21 and again in the summer from March to October. The others occured only during the summer, from the end of March and early April until Mid-Septemb

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Publication Date
Wed Jan 08 2020
Journal Name
Nursing &amp; Health Sciences
Medication adherence and predictive factors in patients with cardiovascular disease: A cross‐sectional study
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Abstract<p>Adherence to cardiac medications makes a significant contribution to avoidance of morbidity and premature mortality in patients with cardiovascular disease. This quantitative study used cross‐sectional survey design to evaluate medication adherence and contributing factors among patients with cardiovascular disease, comparing patients who were admitted to a cardiac ward (<italic>n</italic> = 89) and those attending outpatient cardiac rehabilitation (<italic>n</italic> = 31) in Australia. Data collection was completed between October 2016 and December 2017. Descriptive and regression analyses were conducted to identify medication adherence and determine factors independently pred</p> ... Show More
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