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.
The aim of the research to highlight the calendar of the most important tools used by the Central Bank of Iraq, in the implementation of the function of supervisory oversight, to verify the stability of the banking system, and protect the funds of shareholders, and depositors in general and the absence of any raises the risks of default and financial failure in particular, for commercial banks. The most important flaws and weaknesses in these tools, in the early detection of the risks of continuity in a timely manner, The study concluded a set of conclusions, including the weakness of the tools used in the performance of the function of supervisory oversight in detecting cases of default and financial failure in the early time as well as
... Show MoreThis 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 MoreDiscriminant analysis is a technique used to distinguish and classification an individual to a group among a number of groups based on a linear combination of a set of relevant variables know discriminant function. In this research discriminant analysis used to analysis data from repeated measurements design. We will deal with the problem of discrimination and classification in the case of two groups by assuming the Compound Symmetry covariance structure under the assumption of normality for univariate repeated measures data.
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Re-use of the byproduct wastes resulting from different municipal and industrial activities in the reclamation of contaminated water is real application for green projects and sustainability concepts. In this direction, the synthesis of composite sorbent from the mixing of waterworks and sewage sludge coated with new nanoparticles named “siderite” (WSSS) is the novelty of this study. These particles can be precipitated from the iron(II) nitrate using waterworks sludge as alkaline agent and source of carbonate. Characterization tests using X-ray diffraction (XRD), scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS) mapping revealed that the coating process was c
Takbiratul Ehram "The First Takbeer to Start Prayer" means: the words that the worshiper says to start his prayers, and refrain from anything invalidates it. the findings revealed that the four school jurists agreed that the prayer is not valid without Takbiratul Ehram "The First Takbeer to Start Prayer", and they disagreed on its description, so the majority of jurists said that it is a pillar, and some of them called it an obligatory, but Hanafi made it a condition. Likewise, the four jurists agreed that the one who articulates Takbiratul Ehram "The First Takbeer to Start Prayer" with the word: “Allahu Akbar,”; his Takbeer is correct, and they disagreed about the one who adds a word, or replaced it with another, where the m
... Show MoreThe research aimed to identify “The impact of an instructional-learning design based on the brain- compatible model in systemic thinking among first intermediate grade female students in Mathematics”, in the day schools of the second Karkh Educational directorate.In order to achieve the research objective, the following null hypothesis was formulated:There is no statistically significant difference at the significance level (0.05) among the average scores of the experimental group students who will be taught by applying an (instructional- learning) design based to on the brain–compatible model and the average scores of the control group students who will be taught through the traditional method in the systemic thinking test.The resear
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This research aim to measure the critical success factors for total quality management applications, in order to know the key and important role played by these factors at applying the total quality management through a comparative study conducted in a number of a private colleges.
The research problem posed a set of questions, the most important ones are: Are the colleges (sample of research) aware of the critical success factors at applying the total quality management? What is the availability of the critical success factors at the work of the colleges (sample of research)?
What are the critical success factors in the work of the researc
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