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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 Aug 02 2022
Journal Name
Journal Of Population Therapeutics & Clinical Pharmacology
A systematic review of Antimicrobial peptides and their current applications
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In present days, drug resistance is a major emerging problem in the healthcare sector. Novel antibiotics are in considerable need because present effective treatments have repeatedly failed. Antimicrobial peptides are the biologically active secondary metabolites produced by a variety of microorganisms like bacteria, fungi, and algae, which possess surface activity reduction activity along with this they are having antimicrobial, antifungal, and antioxidant antibiofilm activity. Antimicrobial peptides include a wide variety of bioactive compounds such as Bacteriocins, glycolipids, lipopeptides, polysaccharide-protein complexes, phospholipids, fatty acids, and neutral lipids. Bioactive peptides derived from various natural sources like bacte

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Publication Date
Fri Mar 01 2019
Journal Name
Al-khwarizmi Engineering Journal
Design and Implementation of a Telemetry System for Environmental Applications
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The Environmental Data Acquisition Telemetry System is a versatile, flexible and economical means to accumulate data from multiple sensors at remote locations over an extended period of time; the data is normally transferred to the final destination and saved for further analysis.

This paper introduces the design and implementation of a simplified, economical and practical telemetry system to collect and transfer the environmental parameters (humidity, temperature, pressure etc.) from a remote location (Rural Area) to the processing and displaying unit.

To get a flexible and practical system, three data transfer methods (three systems) were proposed (including the design and implementation) for rural area services, the fi

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Publication Date
Wed Jan 01 2025
Journal Name
Special Topics &amp; Reviews In Porous Media: An International Journal
EXPERIMENTAL AND NUMERICAL INVESTIGATION OF A DOUBLE PASS SOLAR AIR HEATER PROVIDED WITH POROUS ABSORBER PLATE FOR DRYING APPLICATIONS
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This investigation integrates experimental and numerical approaches to study a novel solar air heater aimed at achieving an efficient design for a solar collector suitable for drying applications under the meteorological conditions of Iraq. The importance of this investigation stems from the lack of optimal exploitation of solar energy reaching the solar collector, primarily attributable to elevated thermal losses despite numerous designs employed in such solar systems. Consequently, enhancing the thermal performance of solar collectors, particularly those employed in crop drying applications, stands as a crucial focal point for researchers within this domain. Two identical double-pass solar air heaters were designed and constructed for

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Publication Date
Mon Jan 01 2018
Journal Name
Proceedings Of The 10th International Joint Conference On Computational Intelligence
Deep Classifier Structures with Autoencoder for Higher-level Feature Extraction
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Publication Date
Tue Jun 01 2021
Journal Name
2021 Ieee/cvf Conference On Computer Vision And Pattern Recognition Workshops (cvprw)
Alps: Adaptive Quantization of Deep Neural Networks with GeneraLized PositS
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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
Tue Jan 31 2023
Journal Name
International Journal Of Nonlinear Analysis And Applications
Survey on intrusion detection system based on analysis concept drift: Status and future directions
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Nowadays, internet security is a critical concern; the One of the most difficult study issues in network security is "intrusion detection". Fight against external threats. Intrusion detection is a novel method of securing computers and data networks that are already in use. To boost the efficacy of intrusion detection systems, machine learning and deep learning are widely deployed. While work on intrusion detection systems is already underway, based on data mining and machine learning is effective, it requires to detect intrusions by training static batch classifiers regardless considering the time-varying features of a regular data stream. Real-world problems, on the other hand, rarely fit into models that have such constraints. Furthermor

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Publication Date
Fri Dec 11 2020
Journal Name
2020 Ieee 8th Conference On Systems, Process And Control (icspc)
A Survey of Different DC Faults in a Solar Power System
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Publication Date
Sun Jun 30 2024
Journal Name
Journal Of Language Studies
Translation Challenges in Children's Literature: A Comparative Study of Story Narratives
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This paper presents the intricate issues and strategies related to the translation of children's books, and it particularly focuses on the comparative analysis of "The Tale of Peter Rabbit" by Beatrix Potter and "Le Petit Prince" (The Little Prince) by Antoine de Saint-Exupéry. The study finds that the typical problems in translation are, idiomatic expressions, cultural reference, and the voice preservation, along side-sheet-specific challenges which each of the text faces. The translator of Potter's work should have skills of transposing all culturally oriented peculiarities of the UK land to the international audience to keep it accessible. On the contrary, "Le Petit Prince" translation will be the process of capturing the abstra

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