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.
A total of 150 deep eutectic solvents (DESs) with varying salt, hydrogen bond donor, and molar ratios were studied to develop a screening tool for separating toluene-heptane mixtures. The activity coefficient at infinite dilution (γ∞) of each DES was predicted using COSMO-RS, and selectivity (S∞), capacity (C∞), and performance index (PI) were calculated. Key DES properties, including density, viscosity, melting/freezing point, surface tension, and conductivity, were compiled from the literature to create a DES property library. A comprehensive screening tool with four evaluation criteria was developed, which identified ethyl triphenylphosphonium bromide:ZnCl2 (1:4) as the optimal solvent for toluene-heptane separation. Tetrabutyl- b
... Show Morestudy aims to examine education and the challenges of globalization in light of Corona pandemic. The examination involves surveying a randomly selected sample from the University of Baghdad’s professors, particularly from the colleges of Education for Women, Arts, and Sciences. The purpose of this examination is to learn about the dimensions of globalization, its effects on the educational process, and the importance of distance education during the spread of Corona virus quarantine. To achieve this, the researcher followed a descriptive and analytical approach by applying a questionnaire to a sample of 70 teachers who were randomly selected electronically. Results have shown that 78.6% emphasized the contribution of globalization duri
... Show Morestudy the effect of radiation microwave (MW) in inhibition the growth of some types of bacteria in a minced meat and barker were exposed to MW for different times included (0, 10, 20, 30 and 40) sec.The results showed a high inhibition rate for 40 sec, reached to 100%. It is the other side studied the effect of microwave radiation against four types of bacteria included (Staphylococcus aureus, Escherichia coli, Proteus mirabilis and Klebsiella spp), when were exposed to for (0, 5, 10, 20, 30 and 40) sec the inhibition ratio reached to 100% in each of the Proteus mirabilis and Klebsiella spp at 30 sec and Staphylococcus aureus and Escherichia coli at 40sec. using MW in the sterilization media, such as Nutrient agar, Macconkey agar and Man
... 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
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 MoreThe agent-based modeling is currently utilized extensively to analyze complex systems. It supported such growth, because it was able to convey distinct levels of interaction in a complex detailed environment. Meanwhile, agent-based models incline to be progressively complex. Thus, powerful modeling and simulation techniques are needed to address this rise in complexity. In recent years, a number of platforms for developing agent-based models have been developed. Actually, in most of the agents, often discrete representation of the environment, and one level of interaction are presented, where two or three are regarded hardly in various agent-based models. The key issue is that modellers work in these areas is not assisted by simulation plat
... Show MoreA survey of fish species in the Iraqi marine waters was carried out for the period from November 2014 to March 2018. The list included 214 species representing 75 families.
The family Carangidae dominated the marine fishes in Iraq, which was represented by 24 species, followed by Haemulidae with 11 species, and then Serranidae and Sparidae with nine species for each, while 34 families contained a single species only.
The current study showed that the plants were collected from 23 geographical locations in Brenaj, Wasit, Iraq. The region was characterized by a great diversity of wild plants spread densely in this region. The results were as follows: 32 families, 149 species. Asteraceae was the most widespread with 29 species from the group of dicotyledons, followed by the Fabaceae family (19) species, but there are 13 plant families, with one plant species recorded for each plant family. in Brenaj, Wasit included: Aizoaceae, Capparaceae, Convolvulaceae, Frankeniaceae, Molluginaceae, Papaveraceae, Phyllanthaceae, Primulaceae, Rutaceae, Rubiaceae, Verbenaceae, Zygophyllaceae, Urticaceae, while the plant family Poaceae was most widespread in genera and spec
... Show MoreIn the last few years, the literature conferred a great interest in studying the feasibility of using memristive devices for computing. Memristive devices are important in structure, dynamics, as well as functionalities of artificial neural networks (ANNs) because of their resemblance to biological learning in synapses and neurons regarding switching characteristics of their resistance. Memristive architecture consists of a number of metastable switches (MSSs). Although the literature covered a variety of memristive applications for general purpose computations, the effect of low or high conductance of each MSS was unclear. This paper focuses on finding a potential criterion to calculate the conductance of each MMS rather t
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