This research proposes the application of the dragonfly and fruit fly algorithms to enhance estimates generated by the Fama-MacBeth model and compares their performance in this context for the first time. To specifically improve the dragonfly algorithm's effectiveness, three parameter tuning approaches are investigated: manual parameter tuning (MPT), adaptive tuning by methodology (ATY), and a novel technique called adaptive tuning by performance (APT). Additionally, the study evaluates the estimation performance using kernel weighted regression (KWR) and explores how the dragonfly and fruit fly algorithms can be employed to enhance KWR. All methods are tested using data from the Iraq Stock Exchange, based on the Fama-French three-f

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

Malicious software (malware) performs a malicious function that compromising a computer system’s security. Many methods have been developed to improve the security of the computer system resources, among them the use of firewall, encryption, and Intrusion Detection System (IDS). IDS can detect newly unrecognized attack attempt and raising an early alarm to inform the system about this suspicious intrusion attempt. This paper proposed a hybrid IDS for detection intrusion, especially malware, with considering network packet and host features. The hybrid IDS designed using Data Mining (DM) classification methods that for its ability to detect new, previously unseen intrusions accurately and automatically. It uses both anomaly and misuse dete

Software Defined Network (SDN) is a new technology that separate the ‎control plane from the data plane. SDN provides a choice in automation and ‎programmability faster than traditional network. It supports the ‎Quality of Service (QoS) for video surveillance application. One of most ‎significant issues in video surveillance is how to find the best path for routing the packets ‎between the source (IP cameras) and destination (monitoring center). The ‎video surveillance system requires fast transmission and reliable delivery ‎and high QoS. To improve the QoS and to achieve the optimal path, the ‎SDN architecture is used in this paper. In addition, different routing algorithms are ‎used with different steps. First, we eva

This study relates to  the estimation of  a simultaneous equations system for the Tobit model where the dependent variables  ( )  are limited, and this will affect the method to choose the good estimator. So, we will use new estimations methods  different from the classical methods, which if used in such a case, will produce biased and inconsistent estimators which is (Nelson-Olson) method  and  Two- Stage limited dependent variables(2SLDV) method  to get of estimators that hold characteristics the good estimator .

That is , parameters will be estim

HBV and HCV are the major causes of chronic liver diseases throughout the world, and constitute a major global health risk. There is accumulated evidence that the imbalance of proinflammatory and anti-inflammatory cytokine production may play an important role in the pathogenesis of viral hepatic infections and may influence the clinical outcome and disease progression. This study was undertaken to analyze the circulating levels of Tumor Necrotic Factor (TNF-α) and Th2 cytokine IL-10 in patients infected with Hepatitis B and C virus. The study population consisted of 30 patients with chronic HBV, in addition to other 30 patients with chronic HCV infection were recruited on their first examination at the Al-Kindy General Hospital in Baghdad

Hepatitis B infection is a prominent infectious disease caused by hepatitis B virus (HBV), which infect liver and is considered as the main cause of liver cirrhosis, fibrosis and liver cancer worldwide. A pro-inflammatory cytokine Interleukin32 is believed to have a role in chronic HBV infections. Since its role in CHB infections is remain unclear, this study was done to detect IL-32 gene expression in CHB patients in order to identify its exact role. A total number of 110 blood samples were collected from Gastroenterology and Hepatology Teaching Hospital in Baghdad Medical City from CHB patients for both males and females with different age groups according to the research ethics form then sent to Central Public Health Laboratory (CPHL),