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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
Sun Mar 01 2009
Journal Name
Journal Of Economics And Administrative Sciences
THE REALITY OF THE AGRICULTURL SECTOR IN IRAQ AND CHALLENGES FACING THE FUTURE
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سعي المجتمع العراقي منذ أكثر من نصف قرن مضى لإعادة استثمار عشرات المليارات من الدولارات من الإيرادات النفطية في القطاع الزراعي وهياكله وبنياته التحية، كإنشاء السدود والخزانات المائية واستصلاح الأراضي والمشاريع الإنتاجية الحيوانية والنباتية وبطاقات كادت تقترب او تتجاوز حاجز طلب السكان من الأغذية والمنتوجات الزراعية التي تغذي الصناعة الا ان الزيادة السكانية وتحسن مستوى الدخل النفطي شكلا انتقالا جدي

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Publication Date
Sun Mar 19 2023
Journal Name
Journal Of Educational And Psychological Researches
Cognitive Absorption and E-learning Readiness in Learning Digitization among Preparatory Stage in Qatar
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Abstract

The study aims to examine the relationships between cognitive absorption and E-Learning readiness in the preparatory stage. The study sample consisted of (190) students who were chosen randomly. The Researcher has developed the cognitive absorption and E-Learning readiness scales. A correlational descriptive approach was adopted. The research revealed that there is a positive statistical relationship between cognitive absorption and eLearning readiness.

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Publication Date
Sun Feb 03 2019
Journal Name
Iraqi Journal Of Physics
Calibration of ionization chamber survey meter
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Radiation measuring devices need to process calibration which
lose their sensitivity and the extent of the response and the amount of
stability under a changing conditions from time to time and this
period depends on the nature and use of field in which used devices.
A comparison study was done to a (451P) (ionization chamber
survey meter) and this showed the variation of calibration factor in
five different years. This study also displayed the concept of
radiation instrument calibration and necessity of every year
calibration of them.
In this project we used the five years calibration data for ionization
chamber survey meter model Inspector (451P) to get that the values
of Calibration Factor (CF) and Res

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Publication Date
Mon Mar 23 2020
Journal Name
Journal Of Engineering
Survey Study of Factional Order Controllers
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This is a survey study that presents recent researches concerning factional controllers. It presents several types of fractional order controllers, which are extensions to their integer order counterparts. The fractional order PID controller has a dominant importance, so thirty-one paper are presented for this controller. The remaining types of controllers are presented according to the number of papers that handle them; they are fractional order sliding mode controller (nine papers), fuzzy fractional order sliding mode controller (five papers), fractional order lag-lead compensator (three papers), fractional order state feedback controller (three papers), fractional order fuzzy logic controller (three papers). Finally,

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Publication Date
Mon Mar 23 2020
Journal Name
Journal Of Engineering
Survey Study of Factional Order Controllers
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This is a survey study that presents recent researches concerning factional controllers. It presents several types of fractional order controllers, which are extensions to their integer order counterparts. The fractional order PID controller has a dominant importance, so thirty-one paper are presented for this controller. The remaining types of controllers are presented according to the number of papers that handle them; they are fractional order sliding mode controller (nine papers), fuzzy fractional order sliding mode controller (five papers), fractional order lag-lead compensator (three papers), fractional order state feedback controller (three papers), fractional order fuzzy logic controller (three papers). Finally, several conclusions

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Publication Date
Sun Sep 03 2023
Journal Name
Iraqi Journal Of Computers, Communications, Control & Systems Engineering (ijccce)
Efficient Iris Image Recognition System Based on Machine Learning Approach
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HM Al-Dabbas, RA Azeez, AE Ali, IRAQI JOURNAL OF COMPUTERS, COMMUNICATIONS, CONTROL AND SYSTEMS ENGINEERING, 2023

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Publication Date
Fri Apr 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Product development For Use Some Of The Lean Production Tools A Practical Research in the General Company for the automotive industry
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Abstract 

     This research aims to analyze the reality of the production process in an assembly line Cars (RUNNA) in the public company for the automotive industry / Alexandria through the use of some Lean production tools, and data were collected through permanence in the company to identify the problems of the line in order to find appropriate to adopt some Lean production tools solutions, and results showed the presence of Lead time in some stations, which is reflected on the customer's waiting time to get the car, as well as some of the problems existing in the car produced such as high temperature of the car, as the company does not take into account customer preferences,

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Publication Date
Sun Mar 03 2013
Journal Name
Baghdad Science Journal
Survey study of intestinal parasites on Fresh vegetables collected from some Baghdad Sales and its role in human infection
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Fresh vegetables are an important part of a healthy diet. The consumption of raw vegetables without cooking or good washing can be a major rout of transmission to the parasitic infection. The goal of this study was to determine the intestinal parasitic contamination of fresh vegetables from vegetables sales markets in Baghdad province during the different above months of the year. A total of 303 samples of different vegetables were randomly selected from three wholesale markets distributed through different regions in Baghdad (East, West and South) and then were examined by a floatation method. The present study showed that the collected vegetables were contaminated with 12 species of intestinal parasites, and the total percentage of contam

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Publication Date
Sat Mar 01 2008
Journal Name
Iraqi Journal Of Physics
Comparison between Different Data Image Compression Techniques Applied on SAR Images
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In this paper, image compression technique is presented based on the Zonal transform method. The DCT, Walsh, and Hadamard transform techniques are also implements. These different transforms are applied on SAR images using Different block size. The effects of implementing these different transforms are investigated. The main shortcoming associated with this radar imagery system is the presence of the speckle noise, which affected the compression results.

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Publication Date
Sun Jan 01 2023
Journal Name
International Journal Of Nonlinear Analysis And Applications
Rock facies classification and its effect on the estimation of original oil in place based on petrophysical properties data
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The most significant function in oil exploration is determining the reservoir facies, which are based mostly on the primary features of rocks. Porosity, water saturation, and shale volume as well as sonic log and Bulk density are the types of input data utilized in Interactive Petrophysics software to compute rock facies. These data are used to create 15 clusters and four groups of rock facies. Furthermore, the accurate matching between core and well-log data is established by the neural network technique. In the current study, to evaluate the applicability of the cluster analysis approach, the result of rock facies from 29 wells derived from cluster analysis were utilized to redistribute the petrophysical properties for six units of Mishri

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