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 research discusses the obstacles that faced the Iraqi strategic performance in achieving sustainable development after the election of the first Iraqi government in 2005 and the most important strategies to overcome these obstacles.
The aim of the research is to provide an analytical study to promote financial inclusion in Iraq by clarifying the opportunities and challenges of the economic and demographic situation in Iraq, studying the structure of the financial system and introducing non-bank financial institutions operating in Iraq, and using the descriptive approach. Analytical in the study of the phenomenon of research, the research reached a number of conclusions, the most prominent of which were:
- Iraqi society is a young society.
- The majority of the population is 70 percent. They live almost in urban areas.
- The coverage of bank branch networks is concentrated in only four provinces, leaving other provinces outside financial
سعي المجتمع العراقي منذ أكثر من نصف قرن مضى لإعادة استثمار عشرات المليارات من الدولارات من الإيرادات النفطية في القطاع الزراعي وهياكله وبنياته التحية، كإنشاء السدود والخزانات المائية واستصلاح الأراضي والمشاريع الإنتاجية الحيوانية والنباتية وبطاقات كادت تقترب او تتجاوز حاجز طلب السكان من الأغذية والمنتوجات الزراعية التي تغذي الصناعة الا ان الزيادة السكانية وتحسن مستوى الدخل النفطي شكلا انتقالا جدي
... Show MoreIn this paper we estimate the coefficients and scale parameter in linear regression model depending on the residuals are of type 1 of extreme value distribution for the largest values . This can be regard as an improvement for the studies with the smallest values . We study two estimation methods ( OLS & MLE ) where we resort to Newton – Raphson (NR) and Fisher Scoring methods to get MLE estimate because the difficulty of using the usual approach with MLE . The relative efficiency criterion is considered beside to the statistical inference procedures for the extreme value regression model of type 1 for largest values . Confidence interval , hypothesis testing for both scale parameter and regression coefficients
... Show MoreAO Dr. Ali Jihad, Journal of Physical Education, 2021
Radiation measuring devices need to process calibration which
lose their sensitivity and the extent of the response and the amount of
stability under a changing conditions from time to time and this
period depends on the nature and use of field in which used devices.
A comparison study was done to a (451P) (ionization chamber
survey meter) and this showed the variation of calibration factor in
five different years. This study also displayed the concept of
radiation instrument calibration and necessity of every year
calibration of them.
In this project we used the five years calibration data for ionization
chamber survey meter model Inspector (451P) to get that the values
of Calibration Factor (CF) and Res
This is a survey study that presents recent researches concerning factional controllers. It presents several types of fractional order controllers, which are extensions to their integer order counterparts. The fractional order PID controller has a dominant importance, so thirty-one paper are presented for this controller. The remaining types of controllers are presented according to the number of papers that handle them; they are fractional order sliding mode controller (nine papers), fuzzy fractional order sliding mode controller (five papers), fractional order lag-lead compensator (three papers), fractional order state feedback controller (three papers), fractional order fuzzy logic controller (three papers). Finally,
... Show MoreThis is a survey study that presents recent researches concerning factional controllers. It presents several types of fractional order controllers, which are extensions to their integer order counterparts. The fractional order PID controller has a dominant importance, so thirty-one paper are presented for this controller. The remaining types of controllers are presented according to the number of papers that handle them; they are fractional order sliding mode controller (nine papers), fuzzy fractional order sliding mode controller (five papers), fractional order lag-lead compensator (three papers), fractional order state feedback controller (three papers), fractional order fuzzy logic controller (three papers). Finally, several conclusions
... Show More