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

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

Rehabilitation robots are widely recognized as vital for restoring motor function in patients with lower-limb impairments. A Modified Fractional-Order Proportional-Integral-Derivative (MFOPID) controller is proposed to improve trajectory tracking of a 2-DoF Lower Limb Rehabilitation Exoskeleton Robot (LLRER). The classical FOPID is augmented with a modified control formulation by which steady-state error is reduced and the transient response is sharpened. Controller gains and fractional orders were tuned offline using a hybrid metaheuristic Improved Elk Herd Optimization hybridized with Grey Wolf and Multi-Verse Optimization algorithms (IElk-GM) so that exploration and exploitation are balanced. Superiority over the classical FOPID

This research aims to know the reality of succession planning in the researched organization and how it occupies the important jobs in the organization and its readiness for sudden and urgent events that lead to the vacancy of these jobs, and the importance of this research is that it is one of the rare Arab and Iraqi studies and research in this field, as it is one of the first researches It deals with the reality of succession planning in light of the retirement law No. (26) of 2019, and the research problem was the absence of consecutive planning programs and the weak preparation of suitable candidates to face sudden and urgent conditions as replacements for current leaders who occupy the leading and key positions in the depar

Many pathophysiological processes can affect the pharmacokinetic properties of drugs in people with diabetes. The present study was deigned to evaluate the influence of diabetes mellitus (DM) on the pharmacokinetic parameters of metronidazole administered as single oral dose. Twelve healthy volunteers and twelve diabetic patients were enrolled in the present study. On day 1, a single oral dose of metronidazole 500 mg was administered orally to all participants at 9:00 am after a 10-hour fasting. Over the following 48 hours, blood samples were taken at frequent intervals and serum metronidazole concentrations were measured by a high-performance liquid chromatography method for assessment of pharmacokinetics of metronid

Many pathophysiological processes can affect the pharmacokinetic properties of drugs in people with diabetes. The present study was deigned to evaluate the influence of diabetes mellitus (DM) on the pharmacokinetic parameters of metronidazole administered as single oral dose. Twelve healthy volunteers and twelve diabetic patients were enrolled in the present study. On day 1, a single oral dose of metronidazole 500 mg was administered orally to all participants at 9:00 am after a 10-hour fasting. Over the following 48 hours, blood samples were taken at frequent intervals and serum metronidazole concentrations were measured by a high-performance liquid chromatography method for assessment of pharmacokinetics of metronidazole. The data