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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 Oct 01 2024
Journal Name
Renewable And Sustainable Energy Reviews
A critical review on the efficient cooling strategy of batteries of electric vehicles: Advances, challenges, future perspectives
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Publication Date
Mon May 18 2026
Journal Name
Al–bahith Al–a'alami
The agenda of the French news agency AFP in dealing with the press image of the peaceful resistance The Great Return Marches as a model "an analytical study" “A analytical study”
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The study aimed to identify the treatment of the press image of the Great Return Marches in the French international news agency AFP by knowing the most important issues, their direction and the degree of interest in them. The study belongs to the descriptive research, and used the survey method, within the context of the content analysis method, and the researcher relied on the content analysis form tool and the interview tool to collect data. The study population is represented in the photos published by the French News Agency about the Great Return Marches during the period (end of March / 2018 until the end of November / 2019. The researcher chose an intentional sample using the Complete Census method. The study material represented

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Publication Date
Sat Dec 01 2012
Journal Name
Journal Of Economics And Administrative Sciences
Relationship and impact of the Analysis and evaluation jobs with employees performance : Survey study
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        The aim the research that definition on the impact a lot of Analysis and evaluation jobs impact in support the employees performance the property that are Analysis and evaluation jobs is one of the jobs however of the human resource management on organization and the impact footpace big on the chractericties and performance of the people and the impact that success of the organization , And here problem stool of the research in the omission the role for the Analysis and evaluation jobs impact in support the employees performance from the upward management in the organization , Polls were adopted as tools for obtaining data and the Depart

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Publication Date
Sat Mar 01 2025
Journal Name
Coed
Engaging High School Teachers with Artificial Intelligence Concepts, Applications, and Developments
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This work analyzes the effectiveness of an artificial intelligence (AI) community- building workshop designed for high school teachers and it focuses on contemporary issues related to AI concepts and applications. A group of high school teachers from local education districts attended a one-day AI hands-on workshop at our university. The workshop included several AI-related topics and hands-on examples and exercises aiming to introduce AI concepts and tools relevant to pre-college education. The participating teachers were expected to become a part of a collaborative network created to design, develop, and implement novel AI learning modules for high school students. Initial and a post-training surveys have been used to measure the

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Publication Date
Wed May 31 2023
Journal Name
Iraqi Geological Journal
A Survey of Infill Well Location Optimization Techniques
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The maximization of the net present value of the investment in oil field improvements is greatly aided by the optimization of well location, which plays a significant role in the production of oil. However, using of optimization methods in well placement developments is exceedingly difficult since the well placement optimization scenario involves a large number of choice variables, objective functions, and restrictions. In addition, a wide variety of computational approaches, both traditional and unconventional, have been applied in order to maximize the efficiency of well installation operations. This research demonstrates how optimization approaches used in well placement have progressed since the last time they were examined. Fol

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Publication Date
Fri Jan 01 2016
Journal Name
Bio-inspired Computing – Theories And Applications
Image Segmentation Using Membrane Computing: A Literature Survey
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Publication Date
Fri Aug 01 2014
Journal Name
Int. J. Mod. Eng. Res
Exact solutions for MHD flow of a viscoelastic fluid with the fractional Burgers’ model in an annular pipe
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This paper presents an analytical study for the magnetohydrodynamic (MHD) flow of a generalized Burgers’ fluid in an annular pipe. Closed from solutions for velocity is obtained by using finite Hankel transform and discrete Laplace transform of the sequential fractional derivatives. Finally, the figures are plotted to show the effects of different parameters on the velocity profile.

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Publication Date
Sat Sep 01 2018
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The role of risk management programs in Dealing With risks at international airports: An Applied research at Baghdad International Airport
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The objective of the research is to identify the efficiency of risk management in various names at Baghdad International Airport in the face of various risks (financial - technical - human - natural ..) facing the sample of the search of the General Establishment of Civil Aviation and the Iraqi Airways Company where the researcher identified the hypothesis that summarizes There is a significant significant correlation between risk management, risk management and risk review and assessment. The researcher used the means of research from observation and interviews with the relevant officials in this field, as well as used the questionnaire and distributed a sample of 170 employees in the field of risk management (SMS Department) in Iraqi A

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Publication Date
Wed Aug 30 2023
Journal Name
Baghdad Science Journal
Deep Learning-based Predictive Model of mRNA Vaccine Deterioration: An Analysis of the Stanford COVID-19 mRNA Vaccine Dataset
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The emergence of SARS-CoV-2, the virus responsible for the COVID-19 pandemic, has resulted in a global health crisis leading to widespread illness, death, and daily life disruptions. Having a vaccine for COVID-19 is crucial to controlling the spread of the virus which will help to end the pandemic and restore normalcy to society. Messenger RNA (mRNA) molecules vaccine has led the way as the swift vaccine candidate for COVID-19, but it faces key probable restrictions including spontaneous deterioration. To address mRNA degradation issues, Stanford University academics and the Eterna community sponsored a Kaggle competition.This study aims to build a deep learning (DL) model which will predict deterioration rates at each base of the mRNA

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Publication Date
Fri Dec 01 2023
Journal Name
Applied Energy
Deep clustering of Lagrangian trajectory for multi-task learning to energy saving in intelligent buildings using cooperative multi-agent
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The intelligent buildings provided various incentives to get highly inefficient energy-saving caused by the non-stationary building environments. In the presence of such dynamic excitation with higher levels of nonlinearity and coupling effect of temperature and humidity, the HVAC system transitions from underdamped to overdamped indoor conditions. This led to the promotion of highly inefficient energy use and fluctuating indoor thermal comfort. To address these concerns, this study develops a novel framework based on deep clustering of lagrangian trajectories for multi-task learning (DCLTML) and adding a pre-cooling coil in the air handling unit (AHU) to alleviate a coupling issue. The proposed DCLTML exhibits great overall control and is

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