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A Comparative Study Using DCT, Delta Modulation, and Double Shift Coding for Compressing Electroencephalogram Data
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      Storing, transferring, and processing high-dimensional electroencephalogram (EGG) signals is a critical challenge. The goal of EEG compression is to remove redundant data in EEG signals. Medical signals like EEG must be of high quality for medical diagnosis. This paper uses a compression system with near-zero Mean Squared Error (MSE) based on Discrete Cosine Transform (DCT) and double shift coding for fast and efficient EEG data compression. This paper investigates and compares the use or non-use of delta modulation, which is applied to the transformed and quantized input signal. Double shift coding is applied after mapping the output to positive as a final step. The system performance is tested using EEG data files from the CHB-MIT Scalp EEG Database. Compression Ratio (CR) is used to evaluate the compression system performance. The results are encouraging when compared with previous works on the same data samples.

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Publication Date
Fri Jul 01 2016
Journal Name
Journal Of Engineering
Data Base for Dynamic Soil Properties of Seismic Active Zones in Iraq
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Iraq is located near the northern tip of the Arabian plate, which is advancing northwards relative to the Eurasian plate, and is predictably, a tectonically active country. Seismic activity in Iraq increased significantly during the last decade. So structural and geotechnical engineers have been giving increasing attention to the design of buildings for earthquake resistance. Dynamic properties play a vital role in the design of structures subjected to seismic load. The main objective of this study is to prepare a data base for the dynamic properties of different soils in seismic active zones in Iraq using the results of cross hole and down hole tests. From the data base collected it has been observed that the average ve

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Publication Date
Mon May 22 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Evaluation of The Nuclear Data on(α,n)Reaction for Natural Molybdenum
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The cross section evaluation for (α,n) reaction was calculated according to the available International Atomic Energy Agency (IAEA) and other experimental published data . These cross section are the most recent data , while the well known international libraries like ENDF , JENDL , JEFF , etc.   We considered an energy range from threshold to 25 MeV in interval (1 MeV).   The average weighted cross sections for all available experimental and theoretical(JENDL) data and for all the considered isotopes was calculated . The cross section of the element is then calculated according to the cross sections of the isotopes of that element taking into account their abundance . A mathematical representative equation for eac

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Publication Date
Mon Feb 21 2022
Journal Name
Iraqi Journal For Computer Science And Mathematics
Fuzzy C means Based Evaluation Algorithms For Cancer Gene Expression Data Clustering
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The influx of data in bioinformatics is primarily in the form of DNA, RNA, and protein sequences. This condition places a significant burden on scientists and computers. Some genomics studies depend on clustering techniques to group similarly expressed genes into one cluster. Clustering is a type of unsupervised learning that can be used to divide unknown cluster data into clusters. The k-means and fuzzy c-means (FCM) algorithms are examples of algorithms that can be used for clustering. Consequently, clustering is a common approach that divides an input space into several homogeneous zones; it can be achieved using a variety of algorithms. This study used three models to cluster a brain tumor dataset. The first model uses FCM, whic

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Publication Date
Fri Jan 01 2010
Journal Name
Ibn Al- Haitham J. Fo R Pure & Appl. Sci
Evaluation of The Nuclear Data on(α,n)Reaction for Natural Molybdenum
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The cross section evaluation for (α,n) reaction was calculated according to the available International Atomic Energy Agency (IAEA) and other experimental published data . These cross section are the most recent data , while the well known international libraries like ENDF , JENDL , JEFF , etc. We considered an energy range from threshold to 25 M eV in interval (1 MeV). The average weighted cross sections for all available experimental and theoretical(JENDL) data and for all the considered isotopes was calculated . The cross section of the element is then calculated according to the cross sections of the isotopes of that element taking into account their abundance . A mathematical representative equation for each of the element

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Publication Date
Fri Jan 01 2021
Journal Name
Ieee Access
Proposition of New Ensemble Data-Intelligence Models for Surface Water Quality Prediction
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Publication Date
Mon May 28 2018
Journal Name
Iraqi Journal Of Science
Hide Secret Messages in Raster Images for Transmission to Satellites using a 2-D Wavelet Packet
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     The hiding of information has become of great importance in recent times. With dissemination through the internet, and communication through satellites, information needs to be secure. Therefore, a new algorithm is proposed that enables secret messages to be embedded inside satellite images, wherein images of any size or format can be hidden, using a system’s image compression techniques. This operation is executed in three main steps: first phase – the original image is converted into a raster image; second phase– steganography, in which a binary secret message is hidden inside a raster image, using a 4×4 array as the secret key; and third phase– compre

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Publication Date
Wed Dec 30 2020
Journal Name
Iraqi Journal Of Science
A Comparison of Different Estimation Methods to Handle Missing Data in Explanatory Variables
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Missing data is one of the problems that may occur in regression models. This problem is usually handled by deletion mechanism available in statistical software. This method reduces statistical inference values because deletion affects sample size. In this paper, Expectation Maximization algorithm (EM), Multicycle-Expectation-Conditional Maximization algorithm (MC-ECM), Expectation-Conditional Maximization Either (ECME), and Recurrent Neural Networks (RNN) are used to estimate multiple regression models when explanatory variables have some missing values. Experimental dataset were generated using Visual Basic programming language with missing values of explanatory variables according to a missing mechanism at random general pattern and s

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Publication Date
Mon Feb 14 2022
Journal Name
Journal Of Educational And Psychological Researches
Comparison between Rush Model Parameters to Completed and Lost Data by Different Methods of Processing Missing Data
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The current study aims to compare between the assessments of the Rush model’s parameters to the missing and completed data in various ways of processing the missing data. To achieve the aim of the present study, the researcher followed the following steps: preparing Philip Carter test for the spatial capacity which consists of (20) items on a group of (250) sixth scientific stage students in the directorates of Baghdad Education at Al–Rusafa (1st, 2nd and 3rd) for the academic year (2018-2019). Then, the researcher relied on a single-parameter model to analyze the data. The researcher used Bilog-mg3 model to check the hypotheses, data and match them with the model. In addition

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Publication Date
Thu Dec 01 2022
Journal Name
Al-khwarizmi Engineering Journal
Comparative Transfer Learning Models for End-to-End Self-Driving Car
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Self-driving automobiles are prominent in science and technology, which affect social and economic development. Deep learning (DL) is the most common area of study in artificial intelligence (AI). In recent years, deep learning-based solutions have been presented in the field of self-driving cars and have achieved outstanding results. Different studies investigated a variety of significant technologies for autonomous vehicles, including car navigation systems, path planning, environmental perception, as well as car control. End-to-end learning control directly converts sensory data into control commands in autonomous driving. This research aims to identify the most accurate pre-trained Deep Neural Network (DNN) for predicting the steerin

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Publication Date
Sat Sep 23 2023
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Effect of pharmacist interventions on pulmonary function parameters of Iraqi asthmatic patients: A comparative study: Effect of pharmacist interventions on pulmonary functions tests
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Background: Despite the fact that asthma is a long-term disease that may be treated, many people are unable to control their symptoms due to a lack of knowledge about their condition. The study's purpose was to find out if a pharmacist intervention improved asthma management because of this.

Objective: this study designed to assess the effect of pharmaceutical care on pulmonary functions test.

Method: The study was completed in three months. The patients who were enrolled were divided into two groups: Group 1 consists of 23 asthma patients who were randomly assigned to receive conventional therapy for chronic bronchial asthma based on disease stage and se

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