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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
Tue Feb 08 2022
Journal Name
Political Sciences Journal
The role of variables contact for non-state actors and opposite forces of civil social in ensuring the social peace
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Receipt date:6/3/2021  acceptance date:4/5/2021 Publication date:31/31/2021

Creative Commons License This work is licensed under a Creative Commons Attribution 4.0 International License.

The research in the role of variables contact for non-state actors have become more influential in the current of contemporary events, that related with the reality of seeking services and providing all of that in favor of maintaining the social peace, and ensuring its empowerment in order to make peace and stability outcomes as a real fa

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Mon Mar 08 2021
Journal Name
Baghdad Science Journal
The Study of properties structure and some optical properties forcopper Oxid (CuO) Thin film prepared by thermal evaporation in Vacume
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in this paper copper oxide (cuO thin films were prepared by the method of vacum thermal evaporation a pressure.

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Wed Aug 04 2021
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Membranes
Model Based Simulation and Genetic Algorithm Based Optimisation of Spiral Wound Membrane RO Process for Improved Dimethylphenol Rejection from Wastewater
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Reverse Osmosis (RO) has already proved its worth as an efficient treatment method in chemical and environmental engineering applications. Various successful RO attempts for the rejection of organic and highly toxic pollutants from wastewater can be found in the literature over the last decade. Dimethylphenol is classified as a high-toxic organic compound found ubiquitously in wastewater. It poses a real threat to humans and the environment even at low concentration. In this paper, a model based framework was developed for the simulation and optimisation of RO process for the removal of dimethylphenol from wastewater. We incorporated our earlier developed and validated process model into the Species Conserving Genetic Algorithm (SCG

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Fri Apr 01 2022
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International Journal Of Nanoscience
Study of the Interaction Between Reduced Graphene Oxide and NO<sub>2</sub>Gas Molecules via Density Functional Theory (DFT)
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Electronic properties such as density of state, energy gap, HOMO (the highest occupied molecular orbital) level, LUMO (the lowest unoccupied molecular orbital) level and density of bonds, as well as spectroscopic properties like infrared (IR), Raman scattering, force constant, and reduced masses for coronene C24, reduced graphene oxide (rGO) C24O5and interaction between C24O5and NO2gas molecules were investigated. Density functional theory (DFT) with the exchange hybrid function B3LYP with 6-311G** basis sets through the Gaussian 09 W software program was used to do these calculations. Gaussian view 05 was em

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Wed Jul 01 2020
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Chemical Engineering Research And Design
Simultaneous studies of emulsion stability and extraction capacity for the removal of tetracycline from aqueous solution by liquid surfactant membrane
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Plant Archives J.
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Publication Date
Thu Jan 06 2022
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Iraqi National Journal Of Nursing Specialties
Assessment of Nurse-Midwife's Knowledge and Performance Regarding Immediate Newborn Care in Delivery Rooms at Maternity Hospitals in Baghdad City
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Objectives: To assess nurses-midwives knowledge and performance regarding immediate newborn care in delivery rooms, and to identify the relationship between nurses-midwives knowledge and performance and their socio-demographic and professional variables regarding immediate newborn care.

 

 

 

Methodology: A descriptive study was conducted from 1st of October, 2019 to 20TH of October, 2020 at three maternity teaching hospitals in Baghdad city/Al-Russafa Health Directorate: Al-Elwiya Maternity Teaching Hospital, Fatema Al- Zahra Maternity and Pediatric Hospital, Al- Za'faraniyah General Hospital. Non-probability (purposive sample) include

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Publication Date
Sat Feb 18 2023
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Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Knowledge, Perception, and Reporting Practices of Healthcare Providers about Adverse Events Following the COVID-19 Vaccination in Iraq(Conference Paper )#
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  Routine vaccination activities, such as detection, reporting, and management of adverse events following immunization (AEFIs), are generally handled by healthcare providers (HCPs). Safe vaccines against severe acute respiratory syndrome coronavirus (SARS-CoV-2) were introduced to control the Coronavirus Disease-19 (COVID-19) pandemic. The study aimed to assess the knowledge, perceptions, and practice of HCPs in Iraq about reporting adverse events following COVID-19 vaccination, and their association with sociodemographic variables. The study was a cross-sectional study that was carried out between August and September 2021 at the COVID-19 vaccination centers in Iraq. This study used an online and paper-based questionnaire, which

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Publication Date
Sun Feb 10 2019
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Journal Of The College Of Education For Women
Spatial Aesthetics in the Novels (Shai Al-Aroos by Maysaloon Hadi) and (Qiyamat Baghdad by Alya Talib) Balance Technical Study
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This study aims to create spatial balance between two Iraqi writers' novels (Maysaloon
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different. Firstly, ingenuity description of the writers. Followed by the deep connection they
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to deep roots to homeland.
On the other hand, difference aspects, we see Maysaloon takes symbols and illusions
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Tue Jan 01 2019
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International Journal Of Agricultural And Statistical Sciences,
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