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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 Jan 01 2023
Journal Name
The Egyptian Journal Of Hospital Medicine
The Effect of a Program Using Auxiliary Tools to Improve The Long Passing Skill of Football Juniors
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Publication Date
Wed Mar 25 2020
Journal Name
International Journal Of Drug Delivery Technology
Study of Molecular Interaction for Antibiotic Drug with Sugar Solutions at Different Temperature
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The interactions of drug amoxicillin with maltose or galactose solutions with a variation of temperature have been discussed by taking in the volumetric and viscometric procedures. Physical properties [densities (ρ) and viscosities (η)] of amoxicillin (AMOX) aqueous solutions and aqueous solutions of two type saccharides (maltose and galactose 0.05m) have been measured at T = (298.15, 303.15 and 308.15) K under atmospheric pressure. The apparent molar volume (ϕv cm3mole-1) has been evaluated from density data and fitted to a Redlich-Mayer equation. The empirical parameters of the Mayer-Redlich equation and apparent molar volume at infinite dilution ذv were explicated in terms of interactions from type solute-solvent and solute

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Publication Date
Wed Jan 01 2020
Journal Name
International Journal Of Advance Science And Technology
MR Images Classification of Alzheimer's Disease Based on Deep Belief Network Method
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Background/Objectives: The purpose of this study was to classify Alzheimer’s disease (AD) patients from Normal Control (NC) patients using Magnetic Resonance Imaging (MRI). Methods/Statistical analysis: The performance evolution is carried out for 346 MR images from Alzheimer's Neuroimaging Initiative (ADNI) dataset. The classifier Deep Belief Network (DBN) is used for the function of classification. The network is trained using a sample training set, and the weights produced are then used to check the system's recognition capability. Findings: As a result, this paper presented a novel method of automated classification system for AD determination. The suggested method offers good performance of the experiments carried out show that the

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Publication Date
Tue Jun 30 2015
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Single Well Coning Problem and Applicable Solutions
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One of the most important and common problems in petroleum engineering; reservoir, and production engineering is coning; either water or gas coning. Almost 75% of the drilled wells worldwide contains this problem, and in Iraq water coning problem is much wider than the gas coning problem thus in this paper we try to clarify most of the reasons causing water coning and some of applicable solutions to avoid it using the simulation program (CMG Builder) to build a single well model considering an Iraqi well in north of Iraq black oil field with a bottom water drive, Coning was decreased by 57% by dividing into sub-layers (8) layers rather than (4) layers, also it was decreased (Coning) by 45% when perforation numbers and positions was chang

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Publication Date
Sun Apr 01 2018
Journal Name
Journal Of Educational And Psychological Researches
Discipline in the classroom (problems and solutions)
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Research Summary

First: the problem of research and its importance

      The teacher's success in facilitating the students' learning and growth according to the educational and educational goals set out, he must identify the problems of discipline of students in the classroom in terms of sources and reasons and types and methods of prevention and treatment and the teacher to remember that success in his teaching and instruction is not completed more fully once he has the information And knowledge of the subject of the lesson, but must understand the dynamics of the group (class group) and master the skills of classroom management, su

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Publication Date
Fri Mar 01 2019
Journal Name
Iraqi Journal Of Physics
Synthesized pure cobalt oxide nanostructure and doped with yttrium by hydrothermal method for photodetector applications
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In this study, pure Co3O4 nano structure and doping with 4 %, and
6 % of Yttrium is successfully synthesized by hydrothermal method.
The XRD examination, optical, electrical and photo sensing
properties have been studied for pure and doped Co3O4 thin films.
The X-ray diffraction (XRD) analysis shows that all films are
polycrystalline in nature, having cubic structure.
The optical properties indication that the optical energy gap follows
allowed direct electronic transition calculated using Tauc equation
and it increases for doped Co3O4. The photo sensing properties of
thin films are studied as a function of time at different wavelengths to
find the sensitivity for these lights.
High photo sensitivity dope

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Publication Date
Mon Mar 23 2020
Journal Name
Baghdad Science Journal
Compact MIMO Slots Antenna Design with Different Bands and High Isolation for 5G Smartphone Applications
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 In this paper, two elements of the multi-input multi-output (MIMO) antenna had been used to study the five (3.1-3.55GHz and 3.7-4.2GHz), (3.4-4.7 GHz), (3.4-3.8GHz) and (3.6-4.2GHz) 5G bands of smartphone applications that is to be introduced to the respective US, Korea, (Europe and China) and Japan markets. With a proposed dimension of 26 × 46 × 0.8 mm3, the medium-structured and small-sized MIMO antenna was not only found to have demonstrated a high degree of isolation and efficiency, it had also exhibited a lower level of envelope correlation coefficient and return loss, which are well-suited for the 5G bands application. From the fabrication of an inexpensive FR4 substrate with a 0.8 mm thickness level, a loss tang

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Publication Date
Tue Jun 20 2023
Journal Name
Bulletin Of The Iraq Natural History Museum
SURVEY WITH REVISED CHECKLIST OF COMPOSITAE IN THE HERBARIUM OF IRAQ NATURAL HISTORY RESEARCH CENTER AND MUSEUM
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A survey and revised checklist of the species belonging to the family of Compositae for the specimens which are collected and deposited previously at the herbarium of the Iraq Natural History Research Center and Museum, in addition to the current specimens collected for the period 2016-2021. A total of 85 species belonging to 49 genera and 16 tribes are revised with their synonyms, locality, and distributions, flowering and fruiting period.

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Publication Date
Tue Oct 08 2002
Journal Name
Iraqi Journal Of Laser
Design Considerations of Laser Source in a Ring Network Based on Fiber Distributed Data Interface (FDDI)
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This work presents the use of laser diode in the fiber distributed data interface FDDI networks. FDDI uses optical fiber as a transmission media. This solves the problems resulted from the EMI, and noise. In addition it increases the security of transmission. A network with a ring topology consists of three computers was designed and implemented. The timed token protocol was used to achieve and control the process of communication over the ring. Nonreturn to zero inversion (NRZI) modulation was carried out as a part of the physical (PHY) sublayer. The optical system consists of a laser diode with wavelength of 820 nm and 2.5 mW maximum output power as a source, optical fiber as a channel, and positive intrinsic negative (PIN) photodiode

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Publication Date
Fri Aug 05 2016
Journal Name
Wireless Communications And Mobile Computing
A comparison study on node clustering techniques used in target tracking WSNs for efficient data aggregation
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Wireless sensor applications are susceptible to energy constraints. Most of the energy is consumed in communication between wireless nodes. Clustering and data aggregation are the two widely used strategies for reducing energy usage and increasing the lifetime of wireless sensor networks. In target tracking applications, large amount of redundant data is produced regularly. Hence, deployment of effective data aggregation schemes is vital to eliminate data redundancy. This work aims to conduct a comparative study of various research approaches that employ clustering techniques for efficiently aggregating data in target tracking applications as selection of an appropriate clustering algorithm may reflect positive results in the data aggregati

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