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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 28 2023
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Bitcoin Prediction with a hybrid model
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. In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction a

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Publication Date
Sun Oct 01 2023
Journal Name
Baghdad Science Journal
Gaussian Integer Solutions of the Diophantine Equation x^4+y^4=z^3 for x≠ y
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The investigation of determining solutions for the Diophantine equation  over the Gaussian integer ring for the specific case of  is discussed. The discussion includes various preliminary results later used to build the resolvent theory of the Diophantine equation studied. Our findings show the existence of infinitely many solutions. Since the analytical method used here is based on simple algebraic properties, it can be easily generalized to study the behavior and the conditions for the existence of solutions to other Diophantine equations, allowing a deeper understanding, even when no general solution is known.

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Publication Date
Fri Sep 30 2016
Journal Name
Al-khwarizmi Engineering Journal
Modeling the removal of Cadmium Ions from Aqueous Solutions onto Olive Pips Using Neural Network Technique
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The uptake of Cd(II) ions from simulated wastewater onto olive pips was modeled using artificial neural network (ANN) which consisted of three layers. Based on 112 batch experiments, the effect of contact time (10-240 min), initial pH (2-6), initial concentration (25-250 mg/l), biosorbent dosage (0.05-2 g/100 ml), agitation speed (0-250 rpm) and temperature (20-60ºC) were studied. The maximum uptake (=92 %) of Cd(II) was achieved at optimum parameters of 60 min, 6, 50 mg/l, 1 g/100 ml, 250 rpm and 25ºC respectively.

Tangent sigmoid and linear transfer functions of ANN for hidden and output layers respectively with 7 neurons were sufficient to present good predictions for cadmium removal efficiency with coefficient of correlatio

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Publication Date
Fri May 01 2015
Journal Name
Journal Of Engineering
Use of non-Conventional Material to Remove Cu+2 ions from Aqueous Solutions using Chemical Coagulation
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Coagulation - flocculation are basic chemical engineering method in the treatment of metal-bearing industrial wastewater because it removes colloidal particles, some soluble compounds and very fine solid suspensions initially present in the wastewater by destabilization and formation of flocs. This research was conducted to study the feasibility of using natural coagulant such as okra and mallow and chemical coagulant such as alum for removing Cu and increase the removal efficiency and reduce the turbidity of treated water. Fourier transform Infrared (FTIR) was carried out for okra and mallow before and after coagulant to determine their type of functional groups. Carbonyl and hydroxyl functional groups on the surface of

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Publication Date
Wed Dec 01 2021
Journal Name
Baghdad Science Journal
Studying the Photodegradation of Congo Red Dye from Aqueous Solutions Using Bimetallic Au–Pd/TiO2 Photocatalyst
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In this study, the photodegradation of Congo red dye (CR) in aqueous solution was investigated using Au-Pd/TiO2 as photocatalyst. The concentration of dye, dosage of photocatalyst, amount of H2O2, pH of the medium and temperature were examined to find the optimum values of these parameters. It has been found that 28 ppm was the best dye concentration. The optimum amount of photocatalyst was 0.09 g/75 mL of dye solution when the degradation percent was ~ 96 % after irradiation time of 12 hours, while the best amount of hydrogen peroxide was 7μl/75 mL of dye solution at degradation percent ~97 % after irradiation time of 10 hours, whereas pH 5 was the best value to carry out the reaction at the highest degradation percent. In additio

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Publication Date
Sun Dec 06 2015
Journal Name
Baghdad Science Journal
Bounded Solutions of the Second Order Differential Equation x ?+f(x) x ?+g(x)=u(t)
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In this paper we prove the boundedness of the solutions and their derivatives of the second order ordinary differential equation x ?+f(x) x ?+g(x)=u(t), under certain conditions on f,g and u. Our results are generalization of those given in [1].

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Publication Date
Wed Dec 01 2021
Journal Name
Baghdad Science Journal
Studying the Photodegradation of Congo Red Dye from Aqueous Solutions Using Bimetallic Au–Pd/TiO2 Photocatalyst
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In this study, the photodegradation of Congo red dye (CR) in aqueous solution was investigated using Au-Pd/TiO2 as photocatalyst. The concentration of dye, dosage of photocatalyst, amount of H2O2, pH of the medium and temperature were examined to find the optimum values of these parameters. It has been found that 28 ppm was the best dye concentration. The optimum amount of photocatalyst was 0.09 g/75 mL of dye solution when the degradation percent was ~ 96 % after irradiation time of 12 hours, while the best amount of hydrogen peroxide was 7μl/75 mL of dye solution at degradation percent ~97 % after irradiation time of 10 hours, whereas pH 5 was the best value to carry out the reaction at the highest degradation percent. In additio

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Scopus (19)
Crossref (13)
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Publication Date
Wed Dec 01 2021
Journal Name
Baghdad Science Journal
Studying the Photodegradation of Congo Red Dye from Aqueous Solutions Using Bimetallic Au–Pd/TiO2 Photocatalyst
...Show More Authors

In this study, the photodegradation of Congo red dye (CR) in aqueous solution was investigated using Au-Pd/TiO2 as photocatalyst. The concentration of dye, dosage of photocatalyst, amount of H2O2, pH of the medium and temperature were examined to find the optimum values of these parameters. It has been found that 28 ppm was the best dye concentration. The optimum amount of photocatalyst was 0.09 g/75 mL of dye solution when the degradation percent was ~ 96 % after irradiation time of 12 hours, while the best amount of hydrogen peroxide was 7μl/75 mL of dye solution at degradation percent ~97 % after irradiation time of 10 hours, whereas pH 5 was the best value to carry out the reaction at the highest deg

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Crossref (13)
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Publication Date
Sun Jun 30 2024
Journal Name
Iraqi Geological Journal
Electrical Resistivity Synthetic Modeling and Field Survey for Subsurface Features Investigation of the Borsippa Archaeological Site, Babylon Governorate, Middle Iraq
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The selection of proper field survey parameters of electrical resistivity can significantly provide efficient results within a reasonable time and cost. Four electrode arrays of 2D Electric Resistivity Imaging (ERI) surveys were applied to characterize and detect subsurface archaeological bodies and to determine the appropriate array type that should be applied in the field survey. This research is to identify the subsurface features of the Borsippa archaeological site, Babylon Governorate, Middle Iraq. Synthetic modeling studies were conducted to determine the proper array and parameters for imaging the shallow subsurface features or targets. The efficiency of many array types has been tested for the detection the buried archaeolog

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Publication Date
Sun Jan 01 2017
Journal Name
البحوث التربوية والنفسية
the effect of an educational -learning programe according to the concepts of renewable energy and nanotechnology on technological enlightenment among students of the che chemistry department
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