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.
Enhancing fatigue resistance in asphalt binders and mixtures is crucial for prolonging pavement lifespan and improving road performance. Recent advancements in nanotechnology have introduced various nanomaterials such as alumina (NA), carbon nanotubes (CNTs), and silica (NS) as potential asphalt modifiers. These materials possess unique properties that address challenges related to asphalt fatigue. However, their effectiveness depends on proper dispersion and mixing techniques. This review examines the mixing methods used for each nanomaterial to ensure uniform distribution within the asphalt matrix and maximize performance benefits. Recent research findings are synthesized to elucidate how these nanomaterials and their mixing proce
... Show MoreThe tunnel’s stability during construction is a very important matter. Some methods have been proposed for stability evaluation, but the hazard warning levels (HWLs) are more applicable among these methods. Despite monitoring and applying HWLs, several collapses in Shibli twin tunnels in Iran have cast doubts on the accuracy of this criterion in the presence of water. In this study, the critical strains under different water contents were measured through uniaxial compressive strength tests on 11 different shale and marl samples. A comparison of laboratory tests and numerical results shows that the influence of the moisture content on the critical strain is negligible. In addition, the results show that there is no dir
... Show MoreBackground: the primary objective for many researches carried out in dental implantology was to reduce the period needed for functional implant loading, simvastatin (cholesterol lowering medication) had many pleiotropic effects, one of which was increasing bone density around titanium implants (1) and subsequently establishing faster osseointegrated dental implants (2,3). This study aims to reduce the period of time needed to establish secondary stability of dental implant measured in ISQ (Implant Stability Quotient) by investigating the effect of orally administered simvastatin on bone. Materials and methods: simvastatin tablets (40mg/day for three months) were administered orally for 11 healthy women aged (40-51) years old who received 1
... Show MoreIntrusion detection system is an imperative role in increasing security and decreasing the harm of the computer security system and information system when using of network. It observes different events in a network or system to decide occurring an intrusion or not and it is used to make strategic decision, security purposes and analyzing directions. This paper describes host based intrusion detection system architecture for DDoS attack, which intelligently detects the intrusion periodically and dynamically by evaluating the intruder group respective to the present node with its neighbors. We analyze a dependable dataset named CICIDS 2017 that contains benign and DDoS attack network flows, which meets certifiable criteria and is ope
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This paper proposes a new approach, of Clustering Ultrasound images using the Hybrid Filter (CUHF) to determine the gender of the fetus in the early stages. The possible advantage of CUHF, a better result can be achieved when fuzzy c-mean FCM returns incorrect clusters. The proposed approach is conducted in two steps. Firstly, a preprocessing step to decrease the noise presented in ultrasound images by applying the filters: Local Binary Pattern (LBP), median, median and discrete wavelet (DWT),(median, DWT & LBP) and (median & Laplacian) ML. Secondly, implementing Fuzzy C-Mean (FCM) for clustering the resulted images from the first step. Amongst those filters, Median & Laplace has recorded a better accuracy. Our experimental evaluation on re
... Show MoreAn experimental model is used to simulate the loss of soil lateral confinement due to excavation nearby an individual axially loaded pile. The effects of various parameters, such as the horizontal distance of excavation, depth of excavation and pile slenderness ratios are investigated. The experimental analysis results showed the effect of excavation is more remarkable as the horizontal distance of excavation becomes closer to the pile than half pile length. The effect of excavation diminishes gradually as the horizontal distance increases beyond that distance for all the investigated pile slenderness ratios and depths of excavation. The pile head deflection, settlement and bending moments along pile increase with decreasing horizontal d
... Show MoreSoil is considered one of the main factors of subsidence phenomena which
became continually happen in Baghdad (Ghazalia, Ameria, and Hay al-Amyl)
causing bad effects as shortage of drinking water, traffic jam and formation
swamps.
This thesis depends on soil study to a depth 15 meters, due to its
importance in subsidence. This done through specifying its chemical physical
properties.
Soil within Iraq climate, in case of water stopping for any reason it contract
and shrink away especially when it exposed to high pressure these factors
finally caused subsidence. In case of leakage underground water or that of
damaged water pipes this will contribute to chemical reactions which damage soil
structure and incr
The aim of this paper is to present a new methodology to find the private key of RSA. A new initial value which is generated from a new equation is selected to speed up the process. In fact, after this value is found, brute force attack is chosen to discover the private key. In addition, for a proposed equation, the multiplier of Euler totient function to find both of the public key and the private key is assigned as 1. Then, it implies that an equation that estimates a new initial value is suitable for the small multiplier. The experimental results show that if all prime factors of the modulus are assigned larger than 3 and the multiplier is 1, the distance between an initial value and the private key
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