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Data Classification using Quantum Neural Network
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In this paper, integrated quantum neural network (QNN), which is a class of feedforward

neural networks (FFNN’s), is performed through emerging quantum computing (QC) with artificial neural network(ANN) classifier. It is used in data classification technique, and here iris flower data is used as a classification signals. For this purpose independent component analysis (ICA) is used as a feature extraction technique after normalization of these signals, the architecture of (QNN’s) has inherently built in fuzzy, hidden units of these networks (QNN’s) to develop quantized representations of sample information provided by the training data set in various graded levels of certainty. Experimental results presented here show that (QNN’s) are capable of recognizing structures in data, a property that conventional (FFNN’s) with sigmoidal hidden units lack. In addition, (QNN) gave a kind of fast and realistic results compared with the (FFNN). Simulation results indicate that QNN is superior (with total accuracy of 97.778%) than ANN (with total accuracy of 93.334%).

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Publication Date
Thu Jun 01 2023
Journal Name
Journal Of Engineering
Proposing a General Formula for Evaluating the Parametric Cost Using MLR Method
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This research takes up address the practical side by taking case studies for construction projects that include the various Iraqi governorates, as it includes conducting a field survey to identify the impact of parametric costs on construction projects and compare them with what was reached during the analysis and the extent of their validity and accuracy, as well as adopting the approach of personal interviews to know the reality of the state of construction projects. The results showed, after comparing field data and its measurement in construction projects for the sectors (public and private), the correlation between the expected and actual cost change was (97.8%), and this means that the data can be adopted in the re

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Publication Date
Tue May 01 2018
Journal Name
Journal Of Engineering
Prediction of the Effect of Using Stone Column in Clayey Soil on the Behavior of Circular Footing by ANN Model
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Shallow foundations are usually used for structures with light to moderate loads where the soil underneath can carry them. In some cases, soil strength and/or other properties are not adequate and require improvement using one of the ground improvement techniques. Stone column is one of the common improvement techniques in which a column of stone is installed vertically in clayey soils. Stone columns are usually used to increase soil strength and to accelerate soil consolidation by acting as vertical drains. Many researches have been done to estimate the behavior of the improved soil. However, none of them considered the effect of stone column geometry on the behavior of the circular footing. In this research, finite ele

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Publication Date
Thu Feb 28 2019
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The Use Of Artificial Neural Networks In Developing The Role Of Auditor In Discovering Fundamental Errors: An Applied Research In General Company for Electrical Industries and Nasr General Company for Mechanical Industries
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Artificial neural networks usage, as a developed technique, increased in many fields such as Auditing business. Contemporary auditor should cope with the challenges of the technology evolution in the business environment by using computerized techniques such as Artificial neural networks, This research is the first work made in the field of modern techniques of the artificial neural networks in the field of auditing; it is made by using thesample of neural networks as a sample of the artificial multi-layer Back Propagation neural networks in the field of detecting fundamental mistakes of the financial statements when making auditing. The research objectives at offering a methodology for the application of theartificial neural networks wi

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Publication Date
Mon Jan 01 2018
Journal Name
International Journal Of Data Mining, Modelling And Management
Association rules mining using cuckoo search algorithm
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Association rules mining (ARM) is a fundamental and widely used data mining technique to achieve useful information about data. The traditional ARM algorithms are degrading computation efficiency by mining too many association rules which are not appropriate for a given user. Recent research in (ARM) is investigating the use of metaheuristic algorithms which are looking for only a subset of high-quality rules. In this paper, a modified discrete cuckoo search algorithm for association rules mining DCS-ARM is proposed for this purpose. The effectiveness of our algorithm is tested against a set of well-known transactional databases. Results indicate that the proposed algorithm outperforms the existing metaheuristic methods.

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Publication Date
Mon Jan 01 2018
Journal Name
Communications In Computer And Information Science
Automatically Recognizing Emotions in Text Using Prediction by Partial Matching (PPM) Text Compression Method
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In this paper, we investigate the automatic recognition of emotion in text. We perform experiments with a new method of classification based on the PPM character-based text compression scheme. These experiments involve both coarse-grained classification (whether a text is emotional or not) and also fine-grained classification such as recognising Ekman’s six basic emotions (Anger, Disgust, Fear, Happiness, Sadness, Surprise). Experimental results with three datasets show that the new method significantly outperforms the traditional word-based text classification methods. The results show that the PPM compression based classification method is able to distinguish between emotional and nonemotional text with high accuracy, between texts invo

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Publication Date
Sun Sep 01 2019
Journal Name
Baghdad Science Journal
PWRR Algorithm for Video Streaming Process Using Fog Computing
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       The most popular medium that being used by people on the internet nowadays is video streaming.  Nevertheless, streaming a video consumes much of the internet traffics. The massive quantity of internet usage goes for video streaming that disburses nearly 70% of the internet. Some constraints of interactive media might be detached; such as augmented bandwidth usage and lateness. The need for real-time transmission of video streaming while live leads to employing of Fog computing technologies which is an intermediary layer between the cloud and end user. The latter technology has been introduced to alleviate those problems by providing high real-time response and computational resources near to the

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Publication Date
Thu Jul 01 2021
Journal Name
International Journal Of Nonlinear Analysis And Application
Forecasting enhancement using a hodrick-prescott filter
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: Sound forecasts are essential elements of planning, especially for dealing with seasonality, sudden changes in demand levels, strikes, large fluctuations in the economy, and price-cutting manoeuvres for competition. Forecasting can help decision maker to manage these problems by identifying which technologies are appropriate for their needs. The proposal forecasting model is utilized to extract the trend and cyclical component individually through developing the Hodrick–Prescott filter technique. Then, the fit models of these two real components are estimated to predict the future behaviour of electricity peak load. Accordingly, the optimal model obtained to fit the periodic component is estimated using spectrum analysis and Fourier mod

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Publication Date
Fri Sep 01 2023
Journal Name
Journal Of Engineering
Iraqi Sentiment and Emotion Analysis Using Deep Learning
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Analyzing sentiment and emotions in Arabic texts on social networking sites has gained wide interest from researchers. It has been an active research topic in recent years due to its importance in analyzing reviewers' opinions. The Iraqi dialect is one of the Arabic dialects used in social networking sites, characterized by its complexity and, therefore, the difficulty of analyzing sentiment. This work presents a hybrid deep learning model consisting of a Convolution Neural Network (CNN) and the Gated Recurrent Units (GRU) to analyze sentiment and emotions in Iraqi texts. Three Iraqi datasets (Iraqi Arab Emotions Data Set (IAEDS), Annotated Corpus of Mesopotamian-Iraqi Dialect (ACMID), and Iraqi Arabic Dataset (IAD)) col

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Publication Date
Wed Jun 30 2021
Journal Name
Modern Sport
The impact of the question network strategy in accordance with mental capacity in the strength of cognitive control in the subject of teaching methods of sports education for undergraduate students
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The study aimed at identifying the mental capacity of the research sample and classifying them for the purposes of the study, preparing the scale of cognitive control of the subject of teaching methods of sports education, preparing educational units by establishing the question network for the subject of the teaching methods of sports education, and adopting the experimental method by experimental design workers (2×2) for the two groups The limits of the research community are represented by third-stage students of the Department of Physical Education and Sports Science in the morning study of the College of Knowledge, the Community University, which continues in the regular working hours of the year (2019-2020) adult Their number

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Publication Date
Wed Jan 01 2020
Journal Name
Modern Sport
Special exercises according to the Dynafoot data and its effect on the force index and the performance of the front straight air flip skill on the ground movements mat device
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