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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
Wed Aug 26 2020
Journal Name
Iraqi Journal Of Agricultural Sciences
COMPARISON THE ACCURACY OF COMPUTING POINT COORDINATS BETWEEN DIFFERENT INSTRUMENTS AND APPLICATIONS OF GPS
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The study was aimed to determine the coordinates of  the points were measured by different ways and different instruments, the most precise way using the differential global positioning system (DGPS) that will be the reference measurements in comparison, less precise way using navigator GPS. Google earth (pro.), and the other applications of GPS mobile ( Samsung and I-phone). In this research (8 points) were chosen that are occasional in location. The comparison of the different observations can give us an idea of ​​the extent to which the accuracy of the observations differs from the different devices used in the observing, as well as through the knowledge of the best device and the best way to measure coordinates accurately t

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Publication Date
Sat Jan 22 2022
Journal Name
Aip Conference Proceedings 2437, 020032
Study and preparation of optoelectronic properties of AgAl1-xInxSe2/Si heterojunction solar cell applications
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􀀤􀁅􀁖􀁗􀁕􀁄􀁆􀁗􀀑􀀃􀀬􀁑􀀃􀁗􀁋􀁌􀁖􀀃􀁕􀁈􀁖􀁈􀁄􀁕􀁆􀁋􀀏􀀃􀀤􀁊􀀤􀁏􀀔􀀐􀁛􀀬􀁑􀁛􀀶􀁈􀀕􀀃􀀋􀀤􀀤􀀬􀀶􀀌􀀃􀁆􀁒􀁐􀁓􀁒􀁘􀁑􀁇􀀃􀁄􀁏􀁏􀁒􀁜􀁖􀀃􀁓􀁕􀁈􀁓􀁄􀁕􀁈􀁇􀀃􀁉􀁒􀁕􀀃􀁇􀁌􀁉􀁉􀁈􀁕􀁈􀁑􀁗􀀃􀁛􀀃􀀋􀀓􀀑􀀖􀀏􀀃􀀓􀀑􀀙􀀃􀁄􀁑􀁇􀀃􀀓􀀑􀀜􀀌􀀃􀁅􀁜􀀃􀁐􀁈􀁏􀁗􀁌􀁑􀁊􀀃 􀁗􀁋􀁈􀁐􀀃 􀁌􀁑􀀃 􀁄􀁑􀀃 􀁈􀁙􀁄􀁆􀁘􀁄􀁗􀁈􀁇􀀃 􀁔􀁘􀁄􀁕􀁗􀁝􀀃 􀁗􀁘􀁅􀁈􀀃 􀀋􀀕􀀑􀀘􀀍􀀔􀀓􀀐􀀖􀀃 􀁗􀁒􀁕􀁕􀀌􀀑􀀃 􀀤􀀤􀀬􀀶􀀃 􀁚􀁌􀁗􀁋􀀃 􀁇􀁌􀁉􀁉

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Publication Date
Sat Jan 01 2022
Journal Name
Technologies And Materials For Renewable Energy, Environment And Sustainability: Tmrees21gr
Study and preparation of optoelectronic properties of AgAl1-xInxSe2/Si heterojunction solar cell applications
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Publication Date
Wed Nov 22 2023
Journal Name
Drug And Chemical Toxicology
Preparation, characterization, and toxicity evaluation of microemulsion formulation containing prunetin for potential oral applications
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Publication Date
Tue Apr 19 2022
Journal Name
Chemical Methodologies
Biosynthesis, Characterization, and Applications of Bismuth Oxide Nanoparticles Using Aqueous Extract of Beta Vulgaris
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Bismuth oxide nanoparticle Bi2O3NPs has a wide range of applications and less adverse effects than conventional radio sensitizers. In this work, Bi2O3NPs (D1, D2) were successfully synthesized by using the biosynthesis method with varying bismuth salts, bismuth sulfate Bi2(SO4)3 (D1) or bismuth nitrate. Penta hydrate Bi(NO3)3.5H2O (D2) with NaOH with beta-vulgaris extract. The Bi2O3NPs properties were characterized by different spectroscopic methods to determine Bi2O3NPs structure, nature of bonds, size of nanoparticle, element phase, presence, crystallinity and morphology. The existence of the Bi2O3 band was verified by the FT-IR. The Bi2O3 NPs revealed an absorption peak in the UV-visible spectrum, with energy gap Eg = 3.80eV. The X-ray p

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Publication Date
Tue Apr 18 2023
Journal Name
Al–bahith Al–a'alami
The uses of social networking applications and websites in promoting the gulf stock markets
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The study aims to identify the uses and the impact of social networking applications and websites on stock markets and their role in defining the details of dealing with stock movement and trading. The study also aims to highlight the role of these networks by increasing confidence in stock markets and companies as well as encouraging and inciting young people to invest in these markets, the study belongs to the descriptive analytical approach, the study population consisted of all current and potential investors in the stock and financial markets in the United Arab Emirates. The study used a questionnaire that was distributed to a number of followers of social networking pages and websites that deal with trading

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Publication Date
Wed Mar 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
Using Quadratic Form Ratio Multiple Test to Estimate Linear Regression Model Parameters in Big Data with Application: Child Labor in Iraq
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              The current paper proposes a new estimator for the linear regression model parameters under Big Data circumstances.  From the diversity of Big Data variables comes many challenges that  can be interesting to the  researchers who try their best to find new and novel methods to estimate the parameters of linear regression model. Data has been collected by Central Statistical Organization IRAQ, and the child labor in Iraq has been chosen as data. Child labor is the most vital phenomena that both society and education are suffering from and it affects the future of our next generation. Two methods have been selected to estimate the parameter

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Publication Date
Wed Jun 01 2022
Journal Name
World Neurosurgery
Letter to the Editor “Challenges of Meeting Cerebrovascular Surgery Demands in Low-and Middle-Income Countries: An Experience from Iraq”
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Publication Date
Thu Oct 01 2015
Journal Name
Journal Of Economics And Administrative Sciences
the challenges of accounting measurement of intangible assets of create additional value for the company and ways to address them
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   This research seeks to shed light on what you add intangible assets of benefit to the company and this antagonize pause for consideration because it makes the company in a good competitive position stimulates the rest of the companies to acquire those assets.

   That many companies have achieved competitive advantages in the market do not even achieved monopolies increased the value and reaped extraordinary profits as a result of those assets which requires the need to be measured to determine the extent to which contribution in the emergence of the value added to the value of the company on the one hand and to make the presentatio

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Publication Date
Wed Nov 14 2018
Journal Name
Journal Of Engineering And Applied Sciences
DEMONSTRATE OF MAGNETIC FIELD EFFECT ON THE CAPABILITY OF ADSORPTION PROCESS IN THE REMOVAL OF AZO DYE FROM THE AQUEOUS SOLUTIONS ON CALCINED IRAQI BENTONITE CLAY MINERAL VIA COLUM
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