Preferred Language
Articles
/
9hdcWZIBVTCNdQwC6azZ
Efficient Intrusion Detection Through the Fusion of AI Algorithms and Feature Selection Methods
...Show More Authors

With the proliferation of both Internet access and data traffic, recent breaches have brought into sharp focus the need for Network Intrusion Detection Systems (NIDS) to protect networks from more complex cyberattacks. To differentiate between normal network processes and possible attacks, Intrusion Detection Systems (IDS) often employ pattern recognition and data mining techniques. Network and host system intrusions, assaults, and policy violations can be automatically detected and classified by an Intrusion Detection System (IDS). Using Python Scikit-Learn the results of this study show that Machine Learning (ML) techniques like Decision Tree (DT), Naïve Bayes (NB), and K-Nearest Neighbor (KNN) can enhance the effectiveness of an Intrusion Detection System (IDS). Success is measured by a variety of metrics, including accuracy, precision, recall, F1-Score, and execution time. Applying feature selection approaches such as Analysis of Variance (ANOVA), Mutual Information (MI), and Chi-Square (Ch-2) reduced execution time, increased detection efficiency and accuracy, and boosted overall performance. All classifiers achieve the greatest performance with 99.99% accuracy and the shortest computation time of 0.0089 seconds while using ANOVA with 10% of features.

Crossref
View Publication Preview PDF
Quick Preview PDF
Publication Date
Wed Jan 01 2020
Journal Name
Solid State Technology
Image Fusion Using A Convolutional Neural Network
...Show More Authors

Image Fusion Using A Convolutional Neural Network

Publication Date
Fri Sep 22 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Food and feeding habits of the Indian catfish (Heteropneustes fossilis (Bloch)) from Tigris river at AI- Kadhimia region, north of Baghdad city
...Show More Authors

F0od  and  feeding habits  of  Hetropnezt.s!fes ]ossili/}:. (Bloch)  have been  investigated.  Monthly samples (twice a  m()nth}  were   taken during  the period  from  March  2000  to February  20.Ql , using small -

meshed cast net. A total of l9J  ftsh were used to examine the stomach

contents.

The analysis   of  stomach contents of H  fo.s-silis in  the- area  of study  revealed   that  fish  were  fed  on  the  bottom, mid ·surface  and surface  &

... Show More
View Publication Preview PDF
Publication Date
Tue Dec 26 2017
Journal Name
Al-khwarizmi Engineering Journal
Determination of Welding Velocity and Arc Energy for Fusion MAG Welding Joint
...Show More Authors

 Abstract

This paper is an experimental work to determinate the effect of welding velocity and formed arc energy for CO2-MAG fusion weld pool. The input parameters (arc voltage, wire feed speed and gas flow rate) were investigated to find their effects on the weld joint efficiency. Design of experiment with response surface methodology technique was used to build empirical mathematical models for welding velocity and arc energy in term of the input welding parameters. The predicted quadratic models were statistically checked for adequacy purpose by ANOVA analysis. Additionally, numerical optimization was conducted to obtain the optimum values for welding velocity and arc energy. A good agree

... Show More
View Publication Preview PDF
Publication Date
Fri Jun 24 2022
Journal Name
Iraqi Journal Of Science
Feature Extraction of Human Facail Expressions Using Haar Wavelet and Neural network
...Show More Authors

One of the challenging and active research topics in the recent years is Facial Expression. This paper presents the method to extract the features from the facial expressions from still images. Feature extraction is very important for classification and recognition process. This paper involve three stages which contain capture the images, pre-processing and feature extractions. This method is very efficient in feature extraction by applying haar wavelet and Karhunen-Loève Transform (KL-T). The database used in this research is from Cohen-Kanade which used six expressions of anger, sadness fear, happiness, disgust and surprise. Features that have been extracted from the image of facial expressions were used as inputs to the neural networ

... Show More
View Publication Preview PDF
Publication Date
Sun Jan 14 2018
Journal Name
Journal Of Engineering
Efficient Cost Management in the Housing Projects
...Show More Authors

The cost management of cost indicators in housing projects, on the level of planning and design, is the most important quality indicators, for adoption of strategies of planning and design efficient in managing these indicators. So this research points out the need to highlight the most effective and influential cost indicators in housing projects, and to determine strategies in the management of these indicators in order to raise the efficiency of housing projects quality, to seemly the income level target group, taking into consideration the quality of housing standards, to achieve the basic requirements of housing. This paper highlights the importance of the cost  management, the types of housing cost, the method

... Show More
View Publication Preview PDF
Publication Date
Tue Jun 22 2021
Journal Name
Expert Systems
Hybrid intelligent technology for plant health using the fusion of evolutionary optimization and deep neural networks
...Show More Authors

Scopus (2)
Crossref (1)
Scopus Clarivate Crossref
Publication Date
Mon Apr 26 2021
Journal Name
Journal Of Real-time Image Processing
Fast and efficient recursive algorithm of Meixner polynomials
...Show More Authors

View Publication
Scopus (31)
Crossref (27)
Scopus Clarivate Crossref
Publication Date
Fri Dec 29 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Panchromatic and Multispectral Image Fusion by Combining IHS Transform and Haar Wavelet
...Show More Authors

The technique of integrate complimentary details from two or more input images is known as image fusion.  The fusion image is more informational and will be complete more than any of the original input images. This paper Illustrates implementation and evaluation of fusion techniques used on the Satellite images a high-resolution Panchromatic (Pan) and Multispectral (MS). A new algorithm is proposed to fuse a  Pan  and MS  of the lowresolution images based on combining IHS and Haar wavelet transform.Firstly, this paper clarifies the classical fusion by using IHS transform and Haar wavelet transform individually. Secondly proposition new strategy of combining the two methods. Performance of the proposed method is evalua

... Show More
View Publication Preview PDF
Crossref (1)
Crossref
Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Research on Emotion Classification Based on Multi-modal Fusion
...Show More Authors

Nowadays, people's expression on the Internet is no longer limited to text, especially with the rise of the short video boom, leading to the emergence of a large number of modal data such as text, pictures, audio, and video. Compared to single mode data ,the multi-modal data always contains massive information. The mining process of multi-modal information can help computers to better understand human emotional characteristics. However, because the multi-modal data show obvious dynamic time series features, it is necessary to solve the dynamic correlation problem within a single mode and between different modes in the same application scene during the fusion process. To solve this problem, in this paper, a feature extraction framework of

... Show More
View Publication Preview PDF
Scopus (1)
Scopus Crossref
Publication Date
Mon Apr 23 2018
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Comparison of Features Extraction Algorithms Used in the Diagnosis of Plant Diseases
...Show More Authors

      The detection of diseases affecting plant is very important as it relates to the issue of food security, which is a very serious threat to human life. The system of diagnosis of diseases involves a series of steps starting with the acquisition of images through the pre-processing, segmentation and then features extraction that is our subject finally the process of classification. Features extraction is a very important process in any diagnostic system where we can compare this stage to the spine in this type of system. It is known that the reason behind this great importance of this stage is that the process of extracting features greatly affects the work and accuracy of classification. Proper selection of

... Show More
View Publication Preview PDF
Crossref (3)
Crossref