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.
Introduction: Cardiovascular diseases are the main cause of death among type 2 diabetic patients. Higher levels of plasminogen activator urokinase receptor have been found to predict morbidity and mortality across acute and chronic diseases in the common populace. This study aims to explore the role of serum plasminogen activator urokinase receptor levels as a cardiometabolic risk factor among type 2 diabetic Iraqi patients. Methods: Seventy type 2 diabetic patients (40 male and 30 female) (mean age: 46.20±7.56 years) participated in this study; 35 patients were with cardiovascular disease and 35 were without cardiovascular disease; their ages range was 40-55 years. In addition, 30 individuals who apparently healthy were selected a
... Show MoreAnkylosing spondylitis (AS) represents one kind of advanced arthritis formed via inflammatory stimuli long-term in the spin‘s joints. Interleukin (IL)-29 (interferon- lambda1(IFN- λ1)), interleukin (IL)-28A (interferon- lambda 2 (IFN- λ2)) and interleukin (IL)-28B (interferon- lambda 3(IFN-λ3)) are three interferon lambda (IFN- λs) molecules that have recently been identified as new members of the IFN family. IL-28B expression in ankylosing spondylitis (AS) is not well understood. 150 male healthy controls ((HC) and 160 males with AS as patients group participated in this study. Serum level and gene polymorphism were assessed using an enzyme-linked immunosorbent assay and Sanger sequencing for IL-28B, respectively. The results showed
... Show MoreThis is the first record of a new species of cyanobacteria Westiellopsis akinetica in the Iraqi environment, Samples were collected on June 2013 and the existence of it was not documented before. We isolated and purified this species ten years ago in Iraq, but we couldn't identify accurately based on all taxonomic handbooks. This is due to the species features being different from the other documented species in the available taxonomic lectures. It resembled many species by morphological characteristics such as Fischerella muscicola, Fischerella thermalis, Westiellopsis biateralis SA16. Westiellopsis interrupta, Westiellopsis persica SA33, Westiellopsis prolifica and Symphyonema bifilamentata. Describing a new species of the Westiellops
... Show MoreThe aim of this study was to assess the effectiveness of listening to music or Quran in reducing cancer patients’ anxiety before chemotherapy administration. Reducing anxiety in people with cancer, prior to chemotherapy administration, is a crucial goal in nursing care.
An experimental comparative study was conducted.
A simple randomization sampling method was applied. Two hundred thirty‐eight people with cancer who underwent chemotherapy were participated. They are assigned as Quran, music and control groups.
Breast cancer is the most common cancer among women over the world. To reducing reoccurrence and mortality rates, adjuvant hormonal therapy (AHT) is used for a long period. The major barrier to the effectiveness of the treatment is adherence. Adherence to medicines among patients is challenging. Patient beliefs in medications can be positively or negatively correlated to adherence. Objectives: To investigate the extent of adherence and factors affecting adherence, as well as to investigate the association between beliefs and adherence in women with breast cancer taking AHT. Method: A cross-sectional study included 124 Iraqi women with breast cancer recruited from Middle Euphrates
... Show MoreThis study was aimed to evaluate the effect of spraying nano chitosan loaded with NPK fertilizer and nettle leaf and green tea extracts on the growth and productivity of potato for the spring and fall seasons of 2021.It was conducted at private farm in Wasit Governorate, Iraq, as a factorial experiment (5 × 5) within randomized complete block design using three replicates. The first factor included spraying with four concentrations of chitosan nanoparticles loaded with NPK fertilizer 0, 10. 15 and 20% in addition to chemical fertilization treatment, the second factor was spraying nettle leaf extract 25 and 35 gL-1 and green tea extract with 2 and 4 g.L-1, in addition to the control treatment, spraying with distilled water only. The
... Show MoreThe use of data envelopment analysis method helps to improve the performance of organizations in order to exploit their resources efficiently in order to improve the service quality. represented study a problem in need of the Iraqi Middle East Investment Bank to assess the performance of bank branches, according to the service quality provided, Thus, the importance of the study is to contribute using a scientific and systematic method by applying the data envelopment analysis method in assessing the service quality provided by the bank branches, The study focused on achieving the goal of determining the efficiency of the services quality provided by the bank branches manner which reflect the extent of utilization of a
... Show MoreShear wave velocity is an important feature in the seismic exploration that could be utilized in reservoir development strategy and characterization. Its vital applications in petrophysics, seismic, and geomechanics to predict rock elastic and inelastic properties are essential elements of good stability and fracturing orientation, identification of matrix mineral and gas-bearing formations. However, the shear wave velocity that is usually obtained from core analysis which is an expensive and time-consuming process and dipole sonic imager tool is not commonly available in all wells. In this study, a statistical method is presented to predict shear wave velocity from wireline log data. The model concentrated to predict shear wave velocity fr
... Show MoreEvaporation is one of the major components of the hydrological cycle in the nature, thus its accurate estimation is so important in the planning and management of the irrigation practices and to assess water availability and requirements. The aim of this study is to investigate the ability of fuzzy inference system for estimating monthly pan evaporation form meteorological data. The study has been carried out depending on 261 monthly measurements of each of temperature (T), relative humidity (RH), and wind speed (W) which have been available in Emara meteorological station, southern Iraq. Three different fuzzy models comprising various combinations of monthly climatic variables (temperature, wind speed, and relative humidity) were developed
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