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.
Physicians are likely to expend significant labor and time while manually calculating blood smears. Automatic computer-based methods for classifying acute lymphoblastic leukemia have trouble correctly lighting stained white blood cell microscopy images and accurately separating cells that touch or overlap. Additionally, incorporating machine learning techniques into medical services is very hard because doctors can deal with rough guesses as long as the results aren't too bad, but they can't use these calculations for actual medical care. Enabling a A deep network having knowledge of the accuracy of its own predictions is a fascinating and crucial issue. Most instances segmentation frameworks weigh the mask quality during the instance
... Show MorePolyethersulfone (PES) ultrafiltration membrane blending NaX zeolite crystals as a hydrophilic additive was examined for zinc (II) and lead ions Pb (II) removal from aqueous solutions. The effect of NaX zeolite content on the permeation flux and removal efficiency was studied. The results showed that adding zeolite to the polymer matrix enhanced the permeation flux. The permeation flux of all the zeolite/PES matrix membranes was higher than the pristine membrane. No significant improvement was observed in the removal of Zn (II) ions using all prepared membranes as the removal percentage did not raise above 29.2%. However, the removal percentage of Pb (II) ions was enhanced to 97% using a membrane containing 0.9%wt. zeolite. Also, it was
... Show MoreLearn new methods of teaching mathematics contribute to raising the level of pupils to acquire mathematical concepts primary stage
Attempt advancement in the level of mathematics teaching for the better through the use of modern teaching strategies. The research aims at the progress in the acquisition of mathematical concepts schoolgirls after subjecting the fourth grade to teach in active learning strategies, the number of research sample (60) schoolgirl, by (30) schoolgirl experimental group and 30 pupils of the control group. Clear from the results shown the presence of a statistically significant difference between the acquisition of concepts of schoolgirls two groups (experimental and control) for the benefit of pupils of the exp
Objective: preparing educational units for the magnet poles strategy in learning the spiking skill in volleyball, and identifying the effect of the magnet poles strategy in learning the spiking skill in volleyball for female students.Research methodology: The experimental design with two equal experimental and control groups with tight control was also adopted in the pre- and post-tests. The boundaries of this research community are represented by fourth-grade middle school students at Basra Girls' Middle School (2024-2025), whose total number is (90) students, distributed by nature into 4 sections. Sections (A-B) were determined by lottery, so that Section (A) represents the experimental group and Section (B) represents the control
... Show MoreThis paper aimed at specifying the leading obstacles which faced by Iraqi EFL secondary school teachers in teaching English language. According to studies and observations, lack of adequate materials, overcrowding classrooms, lack of infrastructures, and low job satisfaction are the main barriers to English language teaching in Iraq. Data were collected from 130 EFL teachers from Iraqi schools through a standard questionnaire. The data were analyzed using a descriptive statistic to summarize and present it in a meaningful way. The findings supported previous studies regarding the classroom overcrowding, lack of teaching aids and materials, and dilapidated facilities. Furthermore, regarding job dissatisfaction and salary, interesting and eye
... Show MoreThe research aims to identify the effect of jigsaw strategy in learning achievement and engaging for the third grade intermediate students in chemistry. The research sample consisted of (61) students distributed in two experimental and control groups. The research tools consisted in the achievement test and the measure of engaging learning. The results showed that there are statistically significant differences at the level of (α = 0.05) between the experimental group and the control group in both the achievement test and the measure of learning involvement for the benefit of the experimental group. In this light, the researcher recommended the use of jigsaw strategy for teaching the subject matter. Lamia because of its impact in raising
... Show MoreThe research aims to identify the impact of the teaching methods Breathe test and imperative training method in learning some basic skills in Volleyball. The sample included 30 students of the first intermediate level from Al-Tawaia for boys / the public directorate of the education of Baghdad province – Al-Rasafa /2 ( The second). The samples are chosen randomly and divided into three groups : The systematic (Imperative method), first experimentary (training method), second experimentary (training method). Ten students are chosen for each group . The syllabus of the ministry of education is adopted on the systematic group while educational unites, which are prepared by the researcher, are used for the first and second experimenting group
... Show MoreWith the development of cloud computing during the latest years, data center networks have become a great topic in both industrial and academic societies. Nevertheless, traditional methods based on manual and hardware devices are burdensome, expensive, and cannot completely utilize the ability of physical network infrastructure. Thus, Software-Defined Networking (SDN) has been hyped as one of the best encouraging solutions for future Internet performance. SDN notable by two features; the separation of control plane from the data plane, and providing the network development by programmable capabilities instead of hardware solutions. Current paper introduces an SDN-based optimized Resch
Abstract. Hassan FM, Mahdi WM, Al-Haideri HH, Kamil DW. 2022. Identification of new species record of Cyanophyceae in Diyala River, Iraq based on 16S rRNA sequence data. Biodiversitas 23: 5239-5246. The biodiversity and water quality of the Diyala River require screening water in terms of biological contamination, because it is the only water source in Diyala City and is used for many purposes. This study aimed to identify a new species record of Cynaophyceae and emphasize the importance of using molecular methods beside classic morphological approaches, particularly in the water-shrinkage-aqua system. Five different sites along Diyala River were selected for Cyanophyceae identification. Morphological examination and 16S rRNA sequen
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