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 Intrusi

Many approaches of different complexity already exist to edge detection in
color images. Nevertheless, the question remains of how different are the results
when employing computational costly techniques instead of simple ones. This
paper presents a comparative study on two approaches to color edge detection to
reduce noise in image. The approaches are based on the Sobel operator and the
Laplace operator. Furthermore, an efficient algorithm for implementing the two
operators is presented. The operators have been applied to real images. The results
are presented in this paper. It is shown that the quality of the results increases by
using second derivative operator (Laplace operator). And noise reduced in a good

Some of the main challenges in developing an effective network-based intrusion detection system (IDS) include analyzing large network traffic volumes and realizing the decision boundaries between normal and abnormal behaviors. Deploying feature selection together with efficient classifiers in the detection system can overcome these problems.  Feature selection finds the most relevant features, thus reduces the dimensionality and complexity to analyze the network traffic.  Moreover, using the most relevant features to build the predictive model, reduces the complexity of the developed model, thus reducing the building classifier model time and consequently improves the detection performance.  In this study, two different sets of select

Been Antkhav three isolates of soil classified as follows: Bacillus G3 consists of spores, G12, G27 led Pal NTG treatment to kill part of the cells of the three isolates varying degrees treatment also led to mutations urged resistance to streptomycin and rifampicin and double mutations

Alzheimer’s disease (AD) is an age-related progressive and neurodegenerative disorder, which is characterized by loss of memory and cognitive decline. It is the main cause of disability among older people. The rapid increase in the number of people living with AD and other forms of dementia due to the aging population represents a major challenge to health and social care systems worldwide. Degeneration of brain cells due to AD starts many years before the clinical manifestations become clear. Early diagnosis of AD will contribute to the development of effective treatments that could slow, stop, or prevent significant cognitive decline. Consequently, early diagnosis of AD may also be valuable in detecting patients with dementia who have n

The purpose of this study was to know the reality of motivational administrative methods for academic decision-makers in the faculties of physical education and sports sciences in Baghdad from the perspective of faculty members. To solve the nature of the current problem, the two researchers used the descriptive approach of the survey method. The two researchers determined their research community by limiting the sample to all faculty members in the faculties of physical education and sports sciences in Baghdad (Al-Mustansiriya University, Al-Jadriya Univeristy & Al-Waziriyah University). Their number reached 314 faculty members and the two researchers determined their research community by 90%, so the research sam

Cumhuriyet Üniversitesi Fen-Edebiyat Fakültesi Sosyal Bilimler Dergisi | Volume: 48 Issue: 2

Electrocoagulation process was employed for the treatment of river water flows in Iraq. In this study, a batch Electrocoagulation process was used to treat river water taken from Al - Qadisiyah water treatment plant. electrolysis time, voltage and inter-electrode spacing were the most important parameters to study . A statistical model was developed using the RSM model. The optimum condition after studying the parameter effect the process was 1 cm separating, 30 volts . The RSM model shows the ideal condition of removal for both the TSS and turbidity at 1 cm, 20 volts and 55 min.

Background: Strangles is a highly contagious equine respiratory disease caused by Streptococcus equi subsp. equi. It is a globally significant pathogen and one of the most common infectious agents in horses. In Iraq, no sequencing data on this pathogen are available, and only two molecular studies have been published to date. This study provides preliminary insights into strain diversity and provides a foundation for future large-scale investigations. Aim: This study aimed to investigate the molecular characteristics, identify SeM gene alleles, and perform a phylogenetic analysis of S. equi isolates from horses in Baghdad, Iraq. Methods: We analyzed 59 Streptococcus spp. isolates previously obtained from equine clinical sample