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 set of ten drug compounds containing an amino group in the structure were determined theoretically. The parameters were entered into a model to forecast the optimal values of practical (log P) medicinal molecules. The drugs were evaluated theoretically using different types of calculations which are AM1, PM3, and Hartree Fock at the basis set (HF/STO-3G). The Physico-chemical data like (entropy, total energy, Gibbs Free Energy,…etc were computed and played an important role in the predictions of the practical lipophilicity values. Besides, Eigenvalues named HOMO and LUMO were determined. Linearity was shown when correlated between the experimental data with the evaluated physical properties. The statistical analysis was used to analy
... Show MoreAbstract A descriptive (retrospective) (a case-control) study was carried out at Al-Karama Teaching Hospital, Baghdad Teaching Hospital and Surgical Specialties Hospital, and Gastro-Intestinal Tract and Liver (GIT) Hospital for the period of December 1st, 2001 To March 15th 2002. To identify aspects of life-style that may contribute to the occurrence of peptic ulcer (P.U)as risk factors. And to find out the relationship between the demographic characteristic of the group. Non-probability (Purposive) sample of (100) cases who were admitted to the endoscopy department who were later on diagnosed as having
Teen-Computer Interaction (TeenCI) stands in an infant phase and emerging in positive path. Compared to Human-Computer Interaction (generally dedicated to adult) and Child-Computer Interaction, TeenCI gets less interest in terms of research efforts and publications. This has revealed extensive prospects for researchers to explore and contribute in the region of computer design and evaluation for teen, in specific. As a subclass of HCI and a complementary for CCI, TeenCI that tolerates teen group, should be taken significant concern in the sense of its context, nature, development, characteristics and architecture. This paper tends to discover teen’s emotion contribution as the first attempt towards building a conceptual model for TeenC
... Show MoreThe aim of this study was to critically appraise and synthesize the best available evidence on the effectiveness of interventions suitable for delivery by nurses, designed to enhance cardiac patients' adherence to their prescribed medications.
Cardiac medications have statistically significant health benefits for patients with heart disease, but patients' adherence to prescribed medications remains suboptimal.
A systematic quantitative review of intervention effects.
Leigh's syndrome, or sub acute necrotizing encephalomyelopathy, is a rare inherited neurometabolic disease of infancy and early childhood with variable course and prognosis. Rarely, it occurs in juveniles and adults. The diagnosis is difficult and still remains to challenge the clinicians on the basis of history; hence the role of imaging is very essential. It is the neuroimaging, chiefly the Magnetic Resonance Imaging showing characteristic symmetrical necrotic lesions in the basal ganglia and/or brain stem that leads to the diagnosis. Late-onset varieties are rare and only few cases were reported all over the world. Here, I report a case of late onset (juvenile) Leigh syndrome presenting with an acute polyneuropathy. Neuroimaging confi
... Show MoreWe present the notion of bipolar fuzzy k-ideals with thresholds (
Hyperprolactinemia is a common endocrine abnormality caused by physiological factors like pregnancy and lactation, drug-induced factors like antipsychotics, pituitary adenomas that secrete prolactin, or stalk compression or section that reduces dopamine inhibition. Dopamine agonists cure most prolactinomas.
To assess response to treatment in micro versus macroprolactinoma.
The adsorption of Malonic acid, Succinic acid, Adipic acid, and Azelaic acid from their aqueous solutions on zinc oxide surface were investigated. The adsorption efficiency was investigated using various factors such as adsorbent amount, contact time, initial concentration, and temperature. Optimum conditions for acids removal from its aqueous solutions were found to be adsorbent dose (0.2 g), equilibrium contact time (40 minutes), initial acids concentration (0.005 M). Variation of temperature as a function of adsorption efficiency showed that increasing the temperature would result in decreasing the adsorption ability. Kinetic modeling by applying the pseudo-second order model can provide a better fit of the data with a greater correla
... Show MoreGiven the paucity and toxicity of available drugs for leishmaniasis, coupled with the advent of drug resistance, the discovery of new therapies for this neglected tropical disease is recognised as being of the utmost urgency. As such antimicrobial peptides (AMPs) have been proposed as promising compounds against the causative Leishmania species, insect vector-borne protozoan parasites. Here the AMP temporins A, B and 1Sa have been synthesised and screened for activity against Leishmania mexicana insect stage promastigotes and mammalian stage amastigotes, a significant cause of human cutaneous disease. In contrast to previous studies with other species the activity of these AMPs against L. mexicana amastigotes was low. This suggests that ama
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