Imitation learning is an effective method for training an autonomous agent to accomplish a task by imitating expert behaviors in their demonstrations. However, traditional imitation learning methods require a large number of expert demonstrations in order to learn a complex behavior. Such a disadvantage has limited the potential of imitation learning in complex tasks where the expert demonstrations are not sufficient. In order to address the problem, we propose a Generative Adversarial Network-based model which is designed to learn optimal policies using only a single demonstration. The proposed model is evaluated on two simulated tasks in comparison with other methods. The results show that our proposed model is capable of completing considered tasks despite the limitation in the number of expert demonstrations, which clearly indicate the potential of our model.
Estimating the semantic similarity between short texts plays an increasingly prominent role in many fields related to text mining and natural language processing applications, especially with the large increase in the volume of textual data that is produced daily. Traditional approaches for calculating the degree of similarity between two texts, based on the words they share, do not perform well with short texts because two similar texts may be written in different terms by employing synonyms. As a result, short texts should be semantically compared. In this paper, a semantic similarity measurement method between texts is presented which combines knowledge-based and corpus-based semantic information to build a semantic network that repre
... Show MoreWater is an essential aspect of life and important in evolution. Recently the potable water quality topic has received much attention. The study aims to determine drinking water quality in Al-Najaf City by collecting samples throughout Al-Najaf city and comparing the results with the Iraqi guidelines (IQS 417) and World Health Organization (WHO) guidelines, as well as to calculate the WQI. Samples were tested in the laboratory between December 2021 and June 2022. The results showed that multiple parameters exceeded the allowable limits during both testing periods; during winter months, the results of TDS and turbidity exceeded the upper limits in multiple locations. Total hardness values also
... Show MoreThe expenditures of the general budget, in its operational and investment divisions, are a basic factor in the economic and social growth of any country, and its impact on various economic activities such as income, employees , and the standard of living of members of society. This was based on a basic premise: Does increasing or decreasing investment expenditures have an effect on increasing or decreasing the tax proceeds, What is the level of relationship between them? and to achieve the goal of the research, an inductive and analytical method was chosen to measure the impact of the investment budget expenditures on the tax outcome quantitatively using the financial data obtained from The General Authority for Taxes, Ministry of Financ
... Show MoreAfter the fall of the Iraqi regime in the 9th of April 2003, and after the disintegration of the country, political and party political chaos that had never been witnessed before, has now taken over. In the past 2 years, the American military forces had a primary role in spreading this chaos and disorder by applying a set of wrong measures and policies. This chaos that is still affecting the iraqi people was completely ignored by the USA even 2 years after the occupation, no serious steps have been taken in order to bring back order and security, on the other hand, most of the government institutions and its forces were disintegrated, along with the decision made by Paul Bremer of dismissing all the iraqi journals and the workers of the
... Show MoreThe dynamic development of computer and software technology in recent years was accompanied by the expansion and widespread implementation of artificial intelligence (AI) based methods in many aspects of human life. A prominent field where rapid progress was observed are high‐throughput methods in biology that generate big amounts of data that need to be processed and analyzed. Therefore, AI methods are more and more applied in the biomedical field, among others for RNA‐protein binding sites prediction, DNA sequence function prediction, protein‐protein interaction prediction, or biomedical image classification. Stem cells are widely used in biomedical research, e.g., leukemia or other disease studies. Our proposed approach of
... Show MoreIn latest decades, genetic methods have developed into a potent tool in a number of life-attaching applications. In research looking at demographic genetic diversity, QTL detection, marker-assisted selection, and food traceability, DNA-based technologies like PCR are being employed more and more. These approaches call for extraction procedures that provide efficient nucleic acid extraction and the elimination of PCR inhibitors. The first and most important stage in molecular biology is the extraction of DNA from cells. For a molecular scientist, the high quality and integrity of the isolated DNA as well as the extraction method's ease of use and affordability are crucial factors. The present study was designed to establish a simple, fast
... Show MoreEmpirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F
... Show MoreAdvanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m
... Show MoreThe research talks about the most important challenges facing Muslim youth of their ideological, social and economic types, and the youth is facing several problems, the most important of which are the intellectual and social invasion to which the Islamic nation has been exposed and ways to address them from a Quranic perspective and find solutions to these problems and these challenges in accordance with Islamic Sharia and the texts of the Holy Quran. From three topics and several demands, during which the researcher tried to find solutions to each challenge through the verses of the Noble Qur’an.
Biodiesel can be prepared from various types of vegetable oils or animal fats with the aid of a catalyst.
Calcium oxide (CaO) is one of the prospective heterogeneous catalysts for biodiesel synthesis. Modification
of CaO by impregnation on silica (SiO2) can improve the performance of CaO as catalyst. Egg shells and rice
husks as biomass waste can be used as raw materials for the preparation of the silica modified CaO catalyst.
The present study was directed to synthesize and characterize CaO impregnated SiO2 catalyst from biomass
waste and apply it as catalyst in biodiesel synthesis. The catalyst was synthesized by wet impregnation
method and characterized by x-ray diffraction, x-ray fluorescence, nitr