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Generative Adversarial Network for Imitation Learning from Single Demonstration
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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.

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Publication Date
Wed Feb 27 2019
Journal Name
Journal Of Nano Research
A Specific NH<sub>3</sub> Gas Sensor of a Thick MWCNTs-OH Network for Detection at Room Temperature
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NH3 gas sensor was fabricated based on deposited of Functionalized Multi-Walled Carbon Nanotubes (MWCNTs-OH) suspension on filter paper substrates using suspension filtration method. The structural, morphological and optical properties of the MWCNTs film were characterized by XRD, AFM and FTIR techniques. XRD measurement confirmed that the structure of MWCNTs is not affected by the preparation method. The AFM images reflected highly ordered network in the form of a mat. The functional groups and types of bonding have appeared in the FTIR spectra. The fingerprint (C-C stretch) of MWCNTs appears in 1365 cm-1, and the backbone of CNTs observed at 1645 cm-1. A homemade sensi

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Publication Date
Fri May 16 2025
Journal Name
Asean Journal Of Science And Engineering
Enhancing Predictive Maintenance in Energy Systems Using a Hybrid Kolmogorov-Arnold Network (KAN) with Short-Time Fourier Transform (STFT) Framework for Rotating Machinery
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This study proposes a hybrid predictive maintenance framework that integrates the Kolmogorov-Arnold Network (KAN) with Short-Time Fourier Transform (STFT) for intelligent fault diagnosis in industrial rotating machinery. The method is designed to address challenges posed by non-linear and non-stationary vibration signals under varying operational conditions. Experimental validation using the FALEX multispecimen test bench demonstrated a high classification accuracy of 97.5%, outperforming traditional models such as SVM, Random Forest, and XGBoost. The approach maintained robust performance across dynamic load scenarios and noisy environments, with precision and recall exceeding 95%. Key contributions include a hardware-accelerated K

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Publication Date
Sat Feb 24 2024
Journal Name
Journal Of Studies And Researches Of Sport Education
The effect of the use of the Colb model according to the two forms (adaptive, ascending) in learning some of the technical skills of women
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The objective of the study was to identify the effect of the use of the Colb model for the students of the third stage in the College of Physical Education and Sports Sciences, University of Baghdad,As well as to identify the differences between the research groups in the remote tests in learning skills using the model Colb.The researcher used the experimental method and included the sample of the research on the students of the third stage in the College of Physical Education and Sports Science / University of Baghdad by drawing lots, the third division (j) was chosen to represent the experimental group,And the third division (c) to represent the control groupafter the distribution of the sample splitting measure according to the Colb mode

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Publication Date
Thu Dec 28 2017
Journal Name
Al-khwarizmi Engineering Journal
Simulation Study of Mass Transfer Coefficient in Slurry Bubble Column Reactor Using Neural Network
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The objective of this study was to develop neural network algorithm, (Multilayer Perceptron), based correlations for the prediction overall volumetric mass-transfer coefficient (kLa), in slurry bubble column for gas-liquid-solid systems. The Multilayer Perceptron is a novel technique based on the feature generation approach using back propagation neural network. Measurements of overall volumetric mass transfer coefficient were made with the air - Water, air - Glycerin and air - Alcohol systems as the liquid phase in bubble column of 0.15 m diameter. For operation with gas velocity in the range 0-20 cm/sec, the overall volumetric mass transfer coefficient was found to decrease w

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Publication Date
Tue Sep 01 2020
Journal Name
Baghdad Science Journal
Developing Arabic License Plate Recognition System Using Artificial Neural Network and Canny Edge Detection
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            In recent years, there has been expanding development in the vehicular part and the number of vehicles moving on the roads in all the sections of the country. Arabic vehicle number plate identification based on image processing is a dynamic area of this work; this technique is used for security purposes such as tracking of stolen cars and access control to restricted areas. The License Plate Recognition System (LPRS) exploits a digital camera to capture vehicle plate numbers is used as input to the proposed recognition system. Basically, the proposed system consists of three phases, vehicle license plate localization, character segmentation, and character recognition, the

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Publication Date
Sat Dec 15 2018
Journal Name
Journal Of The College Of Education For Women
The Reasons for the Behavior of Bullying school Students in the first grade average from the point of view of teachers and teachers and methods of modification
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 هدف البحث التعرف الى اسباب سلوك التنمر لدى طلاب الصف الاول المتوسط من وجهة نظر المدرسين والمدرسات واساليب تعديله، واستعمل الباحثان المنهج الوصفي واختيار عينة عشوائية من المدرسين والمدرسات في متوسطة أرض الرافدين ومتوسطة الرحمن للبنين وكان عددهم (46) مدرساً ومدرسة بواقع (32) مدرساً و(14) مدرسة، واعتمد الباحثان الاستبانة أداة للتعرف الى اسباب سلوك التنمر واساليب تعديله، واشارت نتائج البحث الى تنوع اسباب التن

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Publication Date
Fri Jan 23 2026
Journal Name
Al–bahith Al–a'alami
The extent of Concern of the University Press in Students’ Issues (Journal of the University of Technology as a Model) for the Period from 2009 to 2012
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The university press is an essential pillar in building an academic community to achieve its objectives in the service of society. Since the university press is a means of university media, which is issued by the departments or units of media in Iraqi universities as academic governmental-institutions, so it highlights the activities of the university and link them to its internal society in the first place as the university press is a mirror of the university and its voice is sincerely expressed. This research comes to know the extent of interest of the university press in various student issues.

In order to identify the problem of the research, the method of content analysis was adopted within the survey method

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Publication Date
Sat Oct 01 2022
Journal Name
Al–bahith Al–a'alami
Employing Statistical Analysis in Public Relations Researches: (An Analytical Study of the Theses and Dissertations of Public Relations for the Period from 2005 to 2012)
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Public relations are amongst the social sciences that rely on scientific methods in achieving new knowledge or resolving existing problems by means of its scientific researches that are often applied and require a classification in terms of their results’ analysis. It also requires subtle statistical processes whether in constructing their material or in analyzing and interpreting their results.

This research seeks to identify the relation between public relations and statistics, and the significance a researcher or practitioner in the domain of public relations should assign to statistics being one of the important criteria in identifying the accuracy and object

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Publication Date
Fri Jun 01 2018
Journal Name
International Journal Of Civil Engineering And Technology (ijciet)
Performance assessment of biological treatment of sequencing batch reactor using artificial neural network technique.
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Artificial Neural Network (ANN) model's application is widely increased for wastewater treatment plant (WWTP) variables prediction and forecasting which can enable the operators to take appropriate action and maintaining the norms. It is much easier modeling tool for dealing with complex nature WWTP modeling comparing with other traditional mathematical models. ANN technique significance has been considered at present study for the prediction of sequencing batch reactor (SBR) performance based on effluent's (BOD5/COD) ratio after collecting the required historical daily SBR data for two years operation (2015-2016) from Baghdad Mayoralty and Al-Rustamiya WWTP office, Iraq. The prediction was gotten by the application of a feed-forwa

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Publication Date
Mon Mar 11 2019
Journal Name
Baghdad Science Journal
Determination of Nicotine Extracted from Eggplant and Green Pepper by HPLC
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Nicotine was separated from eggplant and green pepper seeds (Solanaceous) by High Performance Liquid Chromatography (HPLC).The concentration of nicotine in the eggplant extract (0.871-0.877 μg/ml) was determined by injecting standard material with 0.5 and 1.5 μg/ml, while the concentrations of nicotine in green pepper extract (0.613-0.618 μg/ml) was determined when the standard material was injected with 0.5 and 1.5 μg/ml. The qualitative chemical data was calculated from derivations of the standard material. Nicotine concentration was measured qualitatively in both extracts through the calibration curve and method of the standard addition. This technique has high accuracy and compatibility, bringing the proportion of relati

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