DNA Encoding and STR Extraction for Anomaly Intrusion Detection Systems

Omar Fitian Rashid; Zulaiha Ali Othman; Suhaila Zainudin; Noor Azah Samsudin

doi:10.1109/ACCESS.2021.3055431

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Publication Date

Fri Jan 01 2021

Journal Name

Ieee Access

Volume

9

DOI

10.1109/ACCESS.2021.3055431

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DNA Encoding and STR Extraction for Anomaly Intrusion Detection Systems

DNA

intrusion detection

Knuth-MorrisPratt

short tandem repeat

Teiresias algorithm.

Omar Fitian Rashid

Zulaiha Ali Othman

Suhaila Zainudin

Noor Azah Samsudin

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Publication Date

Tue Aug 10 2021

Journal Name

Design Engineering

Lossy Image Compression Using Hybrid Deep Learning Autoencoder Based On kmean Clusteri

Image compression

Convolutional Autoencoder (CAE)

k-mean algorithm

PSNR

Compression Rate (CR)

MSE

Clustering

CLIC

Kodak

deep learning

lossy

Mohammed S. H.

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Image compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eye

Publication Date

Thu Mar 30 2023

Journal Name

Journal Of Economics And Administrative Sciences

An Artificial Intelligence Algorithm to Optimize the Classification of the Hepatitis Type

Regression Tree Classification (CART)

Radial Basis Function (RBF)

Genetic Algorithm (GA)

شجرة الانحدار التصنيفية

شبكة دالة الاساس الشعاعي

الخوارزمية الجينية

Hiba

Sabah

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Hepatitis is one of the diseases that has become more developed in recent years in terms of the high number of infections. Hepatitis causes inflammation that destroys liver cells, and it occurs as a result of viruses, bacteria, blood transfusions, and others. There are five types of hepatitis viruses, which are (A, B, C, D, E) according to their severity. The disease varies by type. Accurate and early diagnosis is the best way to prevent disease, as it allows infected people to take preventive steps so that they do not transmit the difference to other people, and diagnosis using artificial intelligence gives an accurate and rapid diagnostic result. Where the analytical method of the data relied on the radial basis network to diagnose the

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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

Publication Date

Wed Dec 01 2021

Journal Name

Structures

The effect of ground motion characteristics on the fragility analysis of reinforced concrete frame buildings in Australia

The seismic performance of buildings can be assessed through fragility analysis as it yields the probability of the demand exceeding the capacity at a specified level of intensity. Although it's well-identified that earthquake uncertainties dominate the fragility characteristics

the influence of the characteristics of the earthquake on the fragility analysis is not well investigated. This study aims to compare the effect of earthquake characteristics on the fragility values of typical buildings in Australia. To achieve this

a typical reinforced concrete building is selected and modeled using a finite element approach. Various ground motion suites

such as near-fault

far-fault

and long-duration are selected

and the fragility analysis has been carried out for each ground motion suite. It is observed that the variation in the median values of the collapse fragilities can be as high as 48% between short-duration and long-duration ground motions

and about 40% between long-duration and pulse-like ground motions.

Aya

Sujith

Javad

Alaa

M.D. Morshed

Abbas A.

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