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.
This dissertation studies the application of equivalence theory developed by Mona Baker in translating Persian to Arabic. Among various translation methodologies, Mona Baker’s bottom-up equivalency approach is unique in several ways. Baker’s translation approach is a multistep process. It starts with studying the smallest linguistic unit, “the word”, and then evolves above the level of words leading to the translation of the entire text. Equivalence at the word level, i.e., word for word method, is the core point of Baker’s approach.
This study evaluates the use of Baker’s approach in translation from Persian to Arabic, mainly because finding the correct equivalence is a major challenge in this translation. Additionall
... Show MoreThis study was designed to compare the effect of two types of viral hepatitis A and E (HAV
and HEV) on liver functions in Iraqi individuals by the measurement of biochemical changes
associated with hepatitis.
The study performed on 58 HEV and 66 HAV infected patients compared with 28 healthy
subjects. The measured biochemical tests include total serum bilirubin, serum transminases (ALT
and AST) alkaline phosphatase (ALP) and gamma glutamyl transferase (GGT).
The study showed that adolescent and young adults (17-29) years, were mostly affected by
HEV while children (5-12) years were frequently affected by HAV. The severity of liver damage in
HEV patients was higher than HAV patients as a result of high serum transa
Churning of employees from organizations is a serious problem. Turnover or churn of employees within an organization needs to be solved since it has negative impact on the organization. Manual detection of employee churn is quite difficult, so machine learning (ML) algorithms have been frequently used for employee churn detection as well as employee categorization according to turnover. Using Machine learning, only one study looks into the categorization of employees up to date. A novel multi-criterion decision-making approach (MCDM) coupled with DE-PARETO principle has been proposed to categorize employees. This is referred to as SNEC scheme. An AHP-TOPSIS DE-PARETO PRINCIPLE model (AHPTOPDE) has been designed that uses 2-stage MCDM s
... Show MorePatients with renal failure in the final stages undergo the treatment by hemodialysis. Hemodialysis is used to reinstate the intracellular and extracellular fluid environment, by propagation of molecules in solution through a semipermeable membrane along an electrochemical concentration gradient. Blood catching in the dialysis machine and the recurrent phlebotomy may lead to losing about 1-3 g of iron per year. Prohepcidin hormone is an acute phase protein (type II) that plays a major role in the systemic iron irregularities as it is a mediator of anemia in inflammation and regulator of iron metabolism. This study aims to evaluate the effect of hemodialysis on iron hemostasis and its relationship with prohepcidin as an inflammatory mark
... Show MoreThe cheif aim of the present investigation is to develop Leslie Gower type three species food chain model with prey refuge. The intra-specific competition among the predators is considered in the proposed model. Besides the logistic growth rate for the prey species, Sokol Howell functional response for predation is chosen for our model formulation. The behaviour of the model system thoroughly analyses near the biologically significant equilibria. The linear stability analysis of the equilibria is carried out in order to examine the response of the system. The present model system experiences Hopf bifurcation depending on the choice of suitable model parameters. Extensive numerical simulation reveals the validity of the proposed model.
Many researchers tried to prevent or reduce moisture damage and its sensitivity to temperature to improving the performance of hot mix asphalt because it is decreasing the functional and structural life of fixable pavement due to the moisture damage had exposed to it.
The main objective of this study is to inspect the effect of (fly ash “3%, 6%, 12%”, hydrated lime”5%, 10%, 20%” and silica fumes”1%, 2%, 4%) referring to previous research by the net weight asphalt cement as a modified material on the moisture and temperature sensitivity of hot mix asphalt. This was done using asphalt from AL-Nasiria refinery with penetration grade 40-50, nominal maximum size (12.5) mm (surface course) of aggregate and on
... Show MoreThe direct electron transfer behavior of hemoglobin that is immobilized onto screen-printed carbon electrode (SPCE) modified with silver nanoparticles (AgNPs) and chitosan (CS) was studied in this work. Cyclic voltametry and spectrophotometry were used to characterize the hemoglobin (Hb) bioconjunction with AgNPs and CS. Results of the modified electrode showed quasi-reversible redox peaks with a formal potential of (-0.245 V) versus Ag/AgCl in 0.1 M phosphate buffer solution (PBS), pH7, at a scan rate of 0.1 Vs-1. The charge transfer coefficient (α) was 0.48 and the apparent electron transfer rate constant (Ks) was 0.47 s-1. The electrode was used as a hydrogen peroxide biosensor with a linear response over 3 to 240 µM and a detection li
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