doi:10.29304/jqcm.2023.15.1.1195

Details

Publication Date

Fri Mar 31 2023

Journal Name

Journal Of Al-qadisiyah For Computer Science And Mathematics

Volume

15

Issue Number

1

DOI

10.29304/jqcm.2023.15.1.1195

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A Cryptosystem for Database Security Based on RC4 Algorithm

Cryptosystem

Database

Security

RC4 algorithm

Encryption

Decryption

Saad Abdulkareem

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Because of vulnerable threats and attacks against database during transmission from sender to receiver, which is one of the most global security concerns of network users, a lightweight cryptosystem using Rivest Cipher 4 (RC4) algorithm is proposed. This cryptosystem maintains data privacy by performing encryption of data in cipher form and transfers it over the network and again performing decryption to original data. Hens, ciphers represent encapsulating system for database tables

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Publication Date

Thu Nov 29 2018

Journal Name

Iraqi Journal Of Science

Improving Extractive Multi-Document Text Summarization Through Multi-Objective Optimization

Multi-objective optimization

multi-objective multi-document text summarization problem

MOO

multi-objective evolutionary algorithm

non-dominated solution

EP

Nasreen J.

Hilal H.

Bara’a

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Multi-document summarization is an optimization problem demanding optimization of more than one objective function simultaneously. The proposed work regards balancing of the two significant objectives: content coverage and diversity when generating summaries from a collection of text documents.

Any automatic text summarization system has the challenge of producing high quality summary. Despite the existing efforts on designing and evaluating the performance of many text summarization techniques, their formulations lack the introduction of any model that can give an explicit representation of – coverage and diversity – the two contradictory semantics of any summary. In this work, the design of

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Publication Date

Sat Jan 01 2022

Journal Name

Turkish Journal Of Physiotherapy And Rehabilitation

classification coco dataset using machine learning algorithms

learning Machine

classification

MCOCO dataset

K Nearest Neighbor's

Stochastic Gradient Descent learning (SGD)

Logistic Regression Algorithm(LR)

and Multi-Layer Perceptron (MLP).

Rasool

Bushra

Raaid

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In this paper, we used four classification methods to classify objects and compareamong these methods, these are K Nearest Neighbor's (KNN), Stochastic Gradient Descentlearning (SGD), Logistic Regression Algorithm(LR), and Multi-Layer Perceptron (MLP). Weused MCOCO dataset for classification and detection the objects, these dataset image wererandomly divided into training and testing datasets at a ratio of 7:3, respectively. In randomlyselect training and testing dataset images, converted the color images to the gray level, thenenhancement these gray images using the histogram equalization method, resize (20 x 20) fordataset image. Principal component analysis (PCA) was used for feature extraction, andfinally apply four classification metho

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