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bsj-4906
Measuring Positive and Negative Association of Apriori Algorithm with Cosine Correlation Analysis
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This work aims to see the positive association rules and negative association rules in the Apriori algorithm by using cosine correlation analysis. The default and the modified Association Rule Mining algorithm are implemented against the mushroom database to find out the difference of the results. The experimental results showed that the modified Association Rule Mining algorithm could generate negative association rules. The addition of cosine correlation analysis returns a smaller amount of association rules than the amounts of the default Association Rule Mining algorithm. From the top ten association rules, it can be seen that there are different rules between the default and the modified Apriori algorithm. The difference of the obtained rules from positive association rules and negative association rules strengthens to each other with a pretty good confidence score.

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Publication Date
Tue Oct 01 2019
Journal Name
Journal Of Engineering
Mechanisms of Plant-Correlation Phytoremediation of Al-Daura Iraqi Refinery Wastewater Using Wetland Plant from Tigris River
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In developing countries, conventional physico-chemical methods are commonly used for removing contaminants. These methods are not efficient and very costly. However, new in site strategy with high treatment efficiency and low operation cost named constructed wetland (CW) has been set. In this study, Phragmites australis was used with free surface batch system to estimate its ability to remediate total
petroleum hydrocarbons (TPH) and chemical oxygen demand (COD) from Al-Daura refinery wastewater. The system operated in semi-batch, thus, new wastewater was weekly added to the plant for 42 days. The results showed high removal percentages (98%) of TPH and (62.3%) for COD. Additionally, Phragmites australis biomass increased significant

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Publication Date
Thu Jan 01 2015
Journal Name
Journal Of Al-mansoor College
An Improvement to Face Detection Algorithm for Non-Frontal Faces
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Publication Date
Fri Feb 08 2019
Journal Name
Journal Of The College Of Education For Women
Online Sumarians Cuneiform Detection Based on Symbol Structural Vector Algorithm
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The cuneiform images need many processes in order to know their contents
and by using image enhancement to clarify the objects (symbols) founded in the
image. The Vector used for classifying the symbol called symbol structural vector
(SSV) it which is build from the information wedges in the symbol.
The experimental tests show insome numbersand various relevancy including
various drawings in online method. The results are high accuracy in this research,
and methods and algorithms programmed using a visual basic 6.0. In this research
more than one method was applied to extract information from the digital images
of cuneiform tablets, in order to identify most of signs of Sumerian cuneiform.

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Publication Date
Thu Feb 01 2024
Journal Name
Baghdad Science Journal
A Novel Gravity ‎Optimization Algorithm for Extractive Arabic Text Summarization
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An automatic text summarization system mimics how humans summarize by picking the most ‎significant sentences in a source text. However, the complexities of the Arabic language have become ‎challenging to obtain information quickly and effectively. The main disadvantage of the ‎traditional approaches is that they are strictly constrained (especially for the Arabic language) by the ‎accuracy of sentence feature ‎functions, weighting schemes, ‎and similarity calculations. On the other hand, the meta-heuristic search approaches have a feature tha

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Publication Date
Fri Feb 08 2019
Journal Name
Journal Of The College Of Education For Women
Minimum Spanning Tree Algorithm for Skin Cancer Image Object Detection
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This paper proposes a new method Object Detection in Skin Cancer Image, the minimum
spanning tree Detection descriptor (MST). This ObjectDetection descriptor builds on the
structure of the minimum spanning tree constructed on the targettraining set of Skin Cancer
Images only. The Skin Cancer Image Detection of test objects relies on their distances to the
closest edge of thattree. Our experimentsshow that the Minimum Spanning Tree (MST) performs
especially well in case of Fogginessimage problems and in highNoisespaces for Skin Cancer
Image.
The proposed method of Object Detection Skin Cancer Image wasimplemented and tested on
different Skin Cancer Images. We obtained very good results . The experiment showed that

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Publication Date
Thu May 01 2008
Journal Name
2008 International Conference On Computer And Communication Engineering
A binary Particle Swarm Optimization for attacking knapsacks Cipher Algorithm
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Publication Date
Mon May 01 2017
Journal Name
Australian Journal Of Basic And Applied Sciences
Sprite Region Allocation Using Fast Static Sprite Area Detection Algorithm
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Background: Sprite coding is a very effective technique for clarifying the background video object. The sprite generation is an open issue because of the foreground objects which prevent the precision of camera motion estimation and blurs the created sprite. Objective: In this paper, a quick and basic static method for sprite area detection in video data is presented. Two statistical methods are applied; the mean and standard deviation of every pixel (over all group of video frame) to determine whether the pixel is a piece of the selected static sprite range or not. A binary map array is built for demonstrating the allocated sprite (as 1) while the non-sprite (as 0) pixels valued. Likewise, holes and gaps filling strategy was utilized to re

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Publication Date
Thu May 05 2022
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Classification SINGLE-LEAD ECG by using conventional neural network algorithm
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Publication Date
Wed Dec 01 2021
Journal Name
Journal Of Physics: Conference Series
Art Image Compression Based on Lossless LZW Hashing Ciphering Algorithm
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Abstract<p>Color image compression is a good way to encode digital images by decreasing the number of bits wanted to supply the image. The main objective is to reduce storage space, reduce transportation costs and maintain good quality. In current research work, a simple effective methodology is proposed for the purpose of compressing color art digital images and obtaining a low bit rate by compressing the matrix resulting from the scalar quantization process (reducing the number of bits from 24 to 8 bits) using displacement coding and then compressing the remainder using the Mabel ZF algorithm Welch LZW. The proposed methodology maintains the quality of the reconstructed image. Macroscopic and </p> ... Show More
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Publication Date
Sun Apr 01 2018
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Information Hiding using LSB Technique based on Developed PSO Algorithm
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<p>Generally, The sending process of secret information via the transmission channel or any carrier medium is not secured. For this reason, the techniques of information hiding are needed. Therefore, steganography must take place before transmission. To embed a secret message at optimal positions of the cover image under spatial domain, using the developed particle swarm optimization algorithm (Dev.-PSO) to do that purpose in this paper based on Least Significant Bits (LSB) using LSB substitution. The main aim of (Dev. -PSO) algorithm is determining an optimal paths to reach a required goals in the specified search space based on disposal of them, using (Dev.-PSO) algorithm produces the paths of a required goals with most effi

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