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.
In this paper, a procedure to establish the different performance measures in terms of crisp value is proposed for two classes of arrivals and multiple channel queueing models, where both arrival and service rate are fuzzy numbers. The main idea is to convert the arrival rates and service rates under fuzzy queues into crisp queues by using graded mean integration approach, which can be represented as median rule number. Hence, we apply the crisp values obtained to establish the performance measure of conventional multiple queueing models. This procedure has shown its effectiveness when incorporated with many types of membership functions in solving queuing problems. Two numerical illustrations are presented to determine the validity of the
... Show MoreRestoration of degraded lands by adoption of recommended conservation management practices can rehabilitate watersheds and lead to improving soil and water quality. The objective was to evaluate the effects of grass buffers (GBs), biomass crops (BCs), grass waterways (GWWs), agroforestry buffers (ABs), landscape positions, and distance from tree base for AB treatment on soil quality compared with row crop (RC) (corn [
Is to obtain competitive advantage legitimate objective pursued by all organizations to achieve, because they live today in environments of rapid change and dynamic in order to meet the demands of the customer changing as well as intense competition between the organizations, which requires them to get the location of competitive markets in order to do this will remain to do the building and strengthening competitive advantage to be able to achieve, but that this feature is not easy and is not only through the identification and use of a successful strategy for a competitive standard and then manage it successfully. Hence the research problem of determining the sources of differentiation strategy and its impact on the dimensions of compe
... Show More230 stool samples were collected from 2 state homes for (males and females) to investigate
the infection of different intestinal parasites (pathogenic and non-pathogenic).
The infection rate was higher among males 15.7% than females 6%, these rates were
increased when concentration method was employed up to 54.8% for males and 8.7% for
females significantly.
Most infected orphans were found to harbor single parasite followed by double, triple
parasites.
The highest rate of infection was found among young age group (1-5) years old, while
the older age groups got lowest rates.
Of helminthes, the commonest parasite was Hymenolepis nana 5.7% and of protozoa, the
commonest intestinal parasite was Giardia lamblia
Background : It had been indentified by histological, histochemical and morphometrical studies that peganum harmala is a mammogenic herb and borage officinalis is a lactogenic one . To complete our investigation about these two herbs , we performed electron microscopical study . Materials and methods : Rats were grouped according to their physiological status into three groups . Each group was subdivided in to three subgroups : one control and two experimental . The two experimental group were treated daily; the 1st one with an aqueous extract of peganum harmala seeds and the 2nd with an aqueous extract of borage officinalis flowers . After two weeks of treatment , mammary glands were employed for electron microscopical study . Resu
... Show MoreThis paper deals with modelling and control of Euler-Bernoulli smart beam interacting with a fluid medium. Several distributed piezo-patches (actuators and/or sensors) are bonded on the surface of the target beam. To model the vibrating beam properly, the effect of the piezo-patches and the hydrodynamic loads should be taken into account carefully. The partial differential equation PDE for the target oscillating beam is derived considering the piezo-actuators as input controls. Fluid forces are decomposed into two components: 1) hydrodynamic forces due to the beam oscillations, and 2) external (disturbance) hydrodynamic loads independent of beam motion. Then the PDE is discretized usi
Many consumers of electric power have excesses in their electric power consumptions that exceed the permissible limit by the electrical power distribution stations, and then we proposed a validation approach that works intelligently by applying machine learning (ML) technology to teach electrical consumers how to properly consume without wasting energy expended. The validation approach is one of a large combination of intelligent processes related to energy consumption which is called the efficient energy consumption management (EECM) approaches, and it connected with the internet of things (IoT) technology to be linked to Google Firebase Cloud where a utility center used to check whether the consumption of the efficient energy is s
... Show MoreActive learning is a teaching method that involves students actively participating in activities, exercises, and projects within a rich and diverse educational environment. The teacher plays a role in encouraging students to take responsibility for their own education under their scientific and pedagogical supervision and motivates them to achieve ambitious educational goals that focus on developing an integrated personality for today’s students and tomorrow’s leaders. It is important to understand the impact of two proposed strategies based on active learning on the academic performance of first-class intermediate students in computer subjects and their social intelligence. The research sample was intentionally selected, consis
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