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.
The Log-Logistic distribution is one of the important statistical distributions as it can be applied in many fields and biological experiments and other experiments, and its importance comes from the importance of determining the survival function of those experiments. The research will be summarized in making a comparison between the method of maximum likelihood and the method of least squares and the method of weighted least squares to estimate the parameters and survival function of the log-logistic distribution using the comparison criteria MSE, MAPE, IMSE, and this research was applied to real data for breast cancer patients. The results showed that the method of Maximum likelihood best in the case of estimating the paramete
... Show MorePurpose: To contribute to the development of an appropriate program for the management of medical waste based on clear-cut principles in order to reach the overall goal of improving the public health and environment of the population in our country.
Design / Approach / Introduction: The research is based on the analytical descriptive approach as a method of study in the field of data collection using a check list and analysis of the data through the use of some statistical treatments.
Results: The need is to establish a medical waste management in hospitals and follow international standards in all stages of waste management from sorting, collection, transportation and treat
... Show MoreThis research aims at identifying the commitment of satellite news channels in Arabic to the set of important standards that reflect their credibility in dealing with the media material, and considering that these channels give special importance to events in Iraq, as well as the Arab region and the world, decide to choose them and study them with a problem The research was a question about the level of credibility of Iraqi media. This research is descriptive research, which used the survey method on an objective sample of 245 items, while the questionnaire was used as a data collection tool. Seven channels were selected in Arabic for the study. The three most watched channels were chosen. These channels included the channels of Russia t
... Show Moreالخلاصة: الحكة اليوريمية لدى مرضى غسيل الكلى يؤثر على أكثر من 40٪ من المرضى. وربما ترتبط الحكة المستمرة بمستويات عالية من الإنترلوكين 31. الاهداف: النظر إلى مستويات مصل إنترلوكين 31 لدى مرضى غسيل الكلى المصابين بمرض الكلى في المرحلة النهائية، سواء مع أو بدون حكة يوريمية. النتائج: لم يكن مستوى المصل [الوسيط (] لـ IL-31 في المرضى الذين يعانون من الحكة اليوريميةأو بدون حكة في عينة مصل ما قبل غسيل الكلى مختلفًا بشكل م
... Show MoreSoftware-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne
... Show More<span lang="EN-US">In the last years, the self-balancing platform has become one of the most common candidates to use in many applications such as flight, biomedical fields, and industry. In this paper, the physical prototype of a proposed self-balancing platform that described the self-balancing attitude in the (X-axis, Y-axis, or biaxial) under the influence of road disturbance has been introduced. In the physical prototype, the inertial measurement unit (IMU) sensor will sense the disturbance in (X-axis, Y-axis, and biaxial). With the determined error, the corresponding electronic circuit, DC servo motors, and the Arduino software, the platform overcame the tilt angle(disturbance). Optimization of the proportional-integral-
... Show MoreIn this work ,pure and doped(CdO)thin films with different concentration of V2O5x (0.0, 0.05, 0.1 ) wt.% have been prepared on glass substrate at room temperature using Pulse Laser Deposition technique(PLD).The focused Nd:YAG laser beam at 800 mJ with a frequency second radiation at 1064 nm (pulse width 9 ns) repetition frequency (6 Hz), for 500 laser pulses incident on the target surface At first ,The pellets of (CdO)1-x(V2O5)x at different V2O5 contents were sintered to a temperature of 773K for one hours.Then films of (CdO)1-x(V2O5)x have been prepared.The structure of the thin films was examined by using (XRD) analysis..Hall effect has been measured in orded to know the type of conductivity, Finally the solar cell and the effici
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