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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 Mar 19 2023
Journal Name
Journal Of Educational And Psychological Researches
Cognitive Absorption and E-learning Readiness in Learning Digitization among Preparatory Stage in Qatar
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Abstract

The study aims to examine the relationships between cognitive absorption and E-Learning readiness in the preparatory stage. The study sample consisted of (190) students who were chosen randomly. The Researcher has developed the cognitive absorption and E-Learning readiness scales. A correlational descriptive approach was adopted. The research revealed that there is a positive statistical relationship between cognitive absorption and eLearning readiness.

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Publication Date
Fri Dec 15 2023
Journal Name
Al-academy
Pedagogy and its applications in art education curricula
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               The research aims to (identify the applications of pedagogy in art education), the research community included, art education for the primary stage, so the community consisted of (8) main areas in art education, either the research sample was chosen, two main areas (objectives, and content), and included the research methodology (descriptive and analytical), the researcher built the research tool represented (the validity form of the tool) and presented to a group of experts to indicate its validity as well as to measure its stability,  To show the results, the researcher used the percentage, and the researcher recommended - modifying the curriculum every period of time, such as every four years, others

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Publication Date
Wed Jun 20 2018
Journal Name
Al-academy
Simulation and its applications in contemporary graphic design
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   The simulation is the oldest theory in art, since it appeared in the Greek aesthetic thought of the philosopher Plato, as we find in many of the thinkers and philosophers over a wide period of time to reach our world today. Our fascination with art in general and design art in particular is due to the creativity and innovations of the artist through the simulation, as well as the peculiarities in this simulation, which give objects signs and signals that may have an echo that sometimes does not exist in their physical reality.

   The real representation of life and design construction, descriptions of the expression of each of them in the form of intellectual construction and the ideas of producti

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Publication Date
Fri Jul 14 2023
Journal Name
International Journal Of Information Technology &amp; Decision Making
A Decision Modeling Approach for Data Acquisition Systems of the Vehicle Industry Based on Interval-Valued Linear Diophantine Fuzzy Set
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Modeling data acquisition systems (DASs) can support the vehicle industry in the development and design of sophisticated driver assistance systems. Modeling DASs on the basis of multiple criteria is considered as a multicriteria decision-making (MCDM) problem. Although literature reviews have provided models for DASs, the issue of imprecise, unclear, and ambiguous information remains unresolved. Compared with existing MCDM methods, the robustness of the fuzzy decision by opinion score method II (FDOSM II) and fuzzy weighted with zero inconsistency II (FWZIC II) is demonstrated for modeling the DASs. However, these methods are implemented in an intuitionistic fuzzy set environment that restricts the ability of experts to provide mem

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Publication Date
Thu Jul 01 2021
Journal Name
Journal Of Physical Education
The effect of e-learning on learning the skills of short Service and front-dimensional blow for badminton players under the age of 15 years.
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AO Dr. Ali Jihad, Journal of Physical Education, 2021

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Publication Date
Fri Feb 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
The role of monetary policy tools in stimulating local investments in Algeria
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Abstract

The various countries seek to encourage their local investments through the various policies they follow. The most important of these is the monetary policy, which is a means and procedures taken by the monetary authority to control the supply of money and maintain its stability of its financial impact on economic activity.
       The effect of monetary policy is to stimulate domestic investment through money supply that is inversely related to the interest rate and a direct relationship with domestic investment. When money supply increases, interest rates fall and local investment growth rates rise, but when the rise in money supply is high, Inflationary measure

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Publication Date
Sat May 01 2021
Journal Name
Chemical Engineering Research And Design
Ternary glycerol-based deep eutectic solvents: Physicochemical properties and enzymatic activity
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The present study investigates deep eutectic solvents (DESs) as potential media for enzymatic hydrolysis. A series of ternary ammonium and phosphonium-based DESs were prepared at different molar ratios by mixing with aqueous glycerol (85%). The physicochemical properties including surface tension, conductivity, density, and viscosity were measured at a temperature range of 298.15 K – 363.15 K. The eutectic points were highly influenced by the variation of temperature. The eutectic point of the choline chloride: glycerol: water (ratio of 1: 2.55: 2.28) and methyltriphenylphosphonium bromide:glycerol:water (ratio of 1: 4.25: 3.75) is 213.4 K and 255.8 K, respectively. The stability of the lipase enzyme isolated from porcine pancreas (PPL) a

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Publication Date
Tue Dec 01 2020
Journal Name
Journal Of Engineering Science And Technology
Survey and discharge measurements of the Iraqi border crossing rivers
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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
AlexNet-Based Feature Extraction for Cassava Classification: A Machine Learning Approach
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Cassava, a significant crop in Africa, Asia, and South America, is a staple food for millions. However, classifying cassava species using conventional color, texture, and shape features is inefficient, as cassava leaves exhibit similarities across different types, including toxic and non-toxic varieties. This research aims to overcome the limitations of traditional classification methods by employing deep learning techniques with pre-trained AlexNet as the feature extractor to accurately classify four types of cassava: Gajah, Manggu, Kapok, and Beracun. The dataset was collected from local farms in Lamongan Indonesia. To collect images with agricultural research experts, the dataset consists of 1,400 images, and each type of cassava has

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Publication Date
Sun Sep 03 2023
Journal Name
Iraqi Journal Of Computers, Communications, Control & Systems Engineering (ijccce)
Efficient Iris Image Recognition System Based on Machine Learning Approach
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HM Al-Dabbas, RA Azeez, AE Ali, IRAQI JOURNAL OF COMPUTERS, COMMUNICATIONS, CONTROL AND SYSTEMS ENGINEERING, 2023

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