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.
الخلفية: التهاب المفاصل الرَثَيَانِي أو الداء الرثياني أو الالتهاب المفصلي الروماتويدي هو مرض مزمن، من الأمراض الانضدادية التي تؤدي بالجهاز المناعي لمهاجمة المفاصل، مسببة التهابات وتدميرًا لها. ومن الممكن أيضًا أن يدمر جهاز المناعة أعضاء أخرى في الجسم مثل الرئتين والجلد. وفي بعض الحالات، يسبب المرض الإعاقة، مؤدية إلى فقدان القدرة على الحركة والإنتاجية. ويتم تشخيص المرض بواسطة تحاليل دم مخبرية مثل تحلي
... Show MoreABSTRACT Background: Polycystic ovary syndrome (PCOS) is one of the most common endocrine disorders affecting women in their reproductive age.It is characterized by anovulation or oligo-ovulation and hyperandrogensim.Androgen excess is the central defect in polycystic ovary syndrome. It is a complex disorder affects general health in addition to oral health.This study aimed to assess the gingival health status among a group of women with polycystic ovary syndrome as well as to estimate the levels of salivaryfree testosterone in unstimulated saliva in relation to gingival health condition. Materials and methods: Sixty two women with an age range 20-25 years old and with a body mass index range18.5-24.9 (normal weight) were included in this s
... Show MoreNeuron-derived neurotrophic factor [NENF], a human plasma neurotrophic factor, also increases neurotrophic activity in conjunction with Parkinson's disease-related proteins in Neudesin. Although Neudesin (neuron-derived neurotrophic secreted protein) is a member of the membrane-associated progesterone receptor (MAPR) protein subclass, it is not evolutionary related to the other members of the same family. The expression of Neudesin is found in both brain and spinal cord from embryonic stages to adulthood, as w Neudesin levels in Parkinson's patients with osteoporosis disease and Parkinson's patients without osteoporosis disease, as well as the relationship between Neudesin levels, Anthropometric and Clinical Features (Age, Gender, BMI) and
... Show MoreThe mathematical construction of an ecological model with a prey-predator relationship was done. It presumed that the prey consisted of a stage structure of juveniles and adults. While the adult prey species had the power to fight off the predator, the predator, and juvenile prey worked together to hunt them. Additionally, the effect of the harvest was considered on the prey. All the solution’s properties were discussed. All potential equilibrium points' local stability was tested. The prerequisites for persistence were established. Global stability was investigated using Lyapunov methods. It was found that the system underwent a saddle-node bifurcation near the coexistence equilibrium point while exhibiting a transcritical bifurcation
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The current research aims to examine the effectiveness of a training program for children with autism and their mothers based on the Picture Exchange Communication System to confront some basic disorders in a sample of children with autism. The study sample was (16) children with autism and their mothers in the different centers in Taif city and Tabuk city. The researcher used the quasi-experimental approach, in which two groups were employed: an experimental group and a control group. Children aged ranged from (6-9) years old. In addition, it was used the following tools: a list of estimation of basic disorders for a child with autism between (6-9) years, and a training program for children with autism
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Infertility is one of the types of diseases that occur in the reproductive system. Obesity is a state that can be occurred due to excessive fats, the progression in obesity stage results in a change in adipose tissue and the development of chronic inflammation, endocrine glands disorders and women’s reproductive system, and also increase the infection with covid-19. The study aimed to investigate the effect of the obesity, lipid-profile, and IL-6 on hormones-dysregulation in infertile-women with COVID-19 complications. The current study included 70 samples: 50 infertility-women-with-covid-19-infected, 20 healthy-women/control, the ages of both patients and healthy subjects were selected within the range 18-34 years. Levels of FBS, LH,
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