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bsj-1301
An Embedded Data Using Slantlet Transform
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Data hiding is the process of encoding extra information in an image by making small modification to its pixels. To be practical, the hidden data must be perceptually invisible yet robust to common signal processing operations. This paper introduces a scheme for hiding a signature image that could be as much as 25% of the host image data and hence could be used both in digital watermarking as well as image/data hiding. The proposed algorithm uses orthogonal discrete wavelet transforms with two zero moments and with improved time localization called discrete slantlet transform for both host and signature image. A scaling factor ? in frequency domain control the quality of the watermarked images. Experimental results of signature image recovery after applying JPEG coding to the watermarking image are included.

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Publication Date
Wed Aug 31 2022
Journal Name
Iraqi Journal Of Science
Data Mining Methods for Extracting Rumors Using Social Analysis Tools
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       Rumors are typically described as remarks whose true value is unknown. A rumor on social media has the potential to spread erroneous information to a large group of individuals. Those false facts will influence decision-making in a variety of societies. In online social media, where enormous amounts of information are simply distributed over a large network of sources with unverified authority, detecting rumors is critical. This research proposes that rumor detection be done using Natural Language Processing (NLP) tools as well as six distinct Machine Learning (ML) methods (Nave Bayes (NB), random forest (RF), K-nearest neighbor (KNN), Logistic Regression (LR), Stochastic Gradient Descent (SGD) and Decision Tree (

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Publication Date
Wed Aug 25 2021
Journal Name
2021 7th International Conference On Contemporary Information Technology And Mathematics (iccitm)
Anomaly Detection in Flight Data Using the Naïve Bayes Classifier
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Publication Date
Thu Nov 01 2012
Journal Name
2012 International Conference On Advanced Computer Science Applications And Technologies (acsat)
Data Missing Solution Using Rough Set theory and Swarm Intelligence
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This paper presents a hybrid approach for solving null values problem; it hybridizes rough set theory with intelligent swarm algorithm. The proposed approach is a supervised learning model. A large set of complete data called learning data is used to find the decision rule sets that then have been used in solving the incomplete data problem. The intelligent swarm algorithm is used for feature selection which represents bees algorithm as heuristic search algorithm combined with rough set theory as evaluation function. Also another feature selection algorithm called ID3 is presented, it works as statistical algorithm instead of intelligent algorithm. A comparison between those two approaches is made in their performance for null values estima

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Publication Date
Fri Feb 04 2022
Journal Name
Iraqi Journal Of Science
Geomatics correction model for GPS data using RTK-DGPS survey
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Determination of the sites of geographical coordinates with high accuracy and in short time is very important in many applications, including: air and sea navigation, and in the uses geodetic surveys. Today, the Global Positioning System (GPS) plays an important role in performing this task. The datum used for GPS positioning is called World Geodetic System 1984 (WGS84). It consists of a three-dimensional Cartesian coordinate system and an associated ellipsoid so that WGS84 positions describe coordinates as latitude, longitude and ellipsoid height (h) coordinates, with respect to the center of mass of the Earth This study develops a mathematical model for geomantic measurement correction for ellipsoidal heights (h) between two different

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Publication Date
Tue Dec 01 2020
Journal Name
Baghdad Science Journal
Combining Several Substitution Cipher Algorithms using Circular Queue Data Structure
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With the revolutionized expansion of the Internet, worldwide information increases the application of communication technology, and the rapid growth of significant data volume boosts the requirement to accomplish secure, robust, and confident techniques using various effective algorithms. Lots of algorithms and techniques are available for data security.  This paper presents a cryptosystem that combines several Substitution Cipher Algorithms along with the Circular queue data structure. The two different substitution techniques are; Homophonic Substitution Cipher and Polyalphabetic Substitution Cipher in which they merged in a single circular queue with four different keys for each of them, which produces eight different outputs for

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Publication Date
Sun Apr 30 2023
Journal Name
Iraqi Journal Of Science
Numerical and Analytical Solutions of Space-Time Fractional Partial Differential Equations by Using a New Double Integral Transform Method
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  This work discusses the beginning of fractional calculus and how the Sumudu and Elzaki transforms are applied to fractional derivatives. This approach combines a double Sumudu-Elzaki transform strategy to discover analytic solutions to space-time fractional partial differential equations in Mittag-Leffler functions subject to initial and boundary conditions. Where this method gets closer and closer to the correct answer, and the technique's efficacy is demonstrated using numerical examples performed with Matlab R2015a.

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Publication Date
Tue Jan 18 2022
Journal Name
Iraqi Journal Of Science
Proposed Approach for Analysing General Hygiene Information Using Various Data Mining Algorithms
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General medical fields and computer science usually conjugate together to produce impressive results in both fields using applications, programs and algorithms provided by Data mining field. The present research's title contains the term hygiene which may be described as the principle of maintaining cleanliness of the external body. Whilst the environmental hygienic hazards can present themselves in various media shapes e.g. air, water, soil…etc. The influence they can exert on our health is very complex and may be modulated by our genetic makeup, psychological factors and by our perceptions of the risks that they present. Our main concern in this research is not to improve general health, rather than to propose a data mining approach

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Publication Date
Tue Dec 01 2015
Journal Name
Journal Of Engineering
Data Aggregation in Wireless Sensor Networks Using Modified Voronoi Fuzzy Clustering Algorithm
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Data centric techniques, like data aggregation via modified algorithm based on fuzzy clustering algorithm with voronoi diagram which is called modified Voronoi Fuzzy Clustering Algorithm (VFCA) is presented in this paper. In the modified algorithm, the sensed area divided into number of voronoi cells by applying voronoi diagram, these cells are clustered by a fuzzy C-means method (FCM) to reduce the transmission distance. Then an appropriate cluster head (CH) for each cluster is elected. Three parameters are used for this election process, the energy, distance between CH and its neighbor sensors and packet loss values. Furthermore, data aggregation is employed in each CH to reduce the amount of data transmission which le

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Publication Date
Mon Sep 23 2019
Journal Name
Baghdad Science Journal
Hazard Rate Estimation Using Varying Kernel Function for Censored Data Type I
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     In this research, several estimators concerning the estimation are introduced. These estimators are closely related to the hazard function by using one of the nonparametric methods namely the kernel function for censored data type with varying bandwidth and kernel boundary. Two types of bandwidth are used:  local bandwidth and global bandwidth. Moreover, four types of boundary kernel are used namely: Rectangle, Epanechnikov, Biquadratic and Triquadratic and the proposed function was employed with all kernel functions. Two different simulation techniques are also used for two experiments to compare these estimators. In most of the cases, the results have proved that the local bandwidth is the best for all the

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Publication Date
Sun Jul 02 2023
Journal Name
Iraqi Journal Of Science
Estimation of Gypsum- Calcite Percentages Using a Fourier Transform Infrared Spectrophotometer (FTIR), in Alexandria Gypsiferous Soil -Iraq
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In this study the Fourier Transform Infrared Spectrophotometry (FTIR) provides a quick, efficient and relatively inexpensive method for identifying and quantifying gypsum concentrations in the samples taken from different sites from different localities from Alexandria district southwest Baghdad. A comprehensive spectroscopic study of gypsum-calcite system was reported to give good results for the first time by using IR for analytical grades of gypsum (CaSO4.2H2O) and calcite (CaCO3) pure crystals. The spectral results were used to create a calibration curve relates the two minerals concentrations to the intensity (peaks) of FTIR absorbance and applies this calibration to specify gypsum and calcite concentrations in Iraqi gypsiferous soi

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