Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne

       Synthesis and preliminary biological evaluation of imidazo (2, 1-b) Thiazole derivatives is reported. Under Mannich conditions, a series of new imidazo (2, 1-b) Thiazole derivatives were synthesized. Starting from the reaction of 2- amino thiazole with 4- bromo phenyl bromide to produce 5-(4-bromo phenyl) imidazo (2, 1-b) thiazoles, following by introduce the substituted aminomethyl at position 6-by reacting with different aromatic amines under Mannich conditions to afford 6-secondary amine-5-(4-bromo phenyl) imidazo (2,1-b) thiazole in high yields.

FT-IR, 1H NMR, and 13C NMR techniques were used to characterize the synthesized derivatives. In addition, all compounds were tested for their antioxidant activity, and thr

     This study included partial purification of the lipase enzyme from the karnel of the pecan nut. After applying ion exchange chromatography technique using CM-Cellulose, two lipase isoenzymes were observed with specific activity values of 2.66 and 1.7 units/mg protein. The highest activity of both isoenzymes appeared at the optimum pH values of 8 and 6 and at temperatures of 40 and 50 °C, respectively. A pure single band was obtained by using electrophoresis technique and it was found that the approximate molecular weight was 42 kDa for the two isoenzymes. The study dealt with the preparation of the diester compound 1,4-diacetoxybenzene, which was diagnosed by GC-MS and ¹H NMR spectrometry. When studying the inhibitio

In the present paper, chitosan Schiff base has been synthesized from chitosan’s reaction with the salicyldehyde. The AuNPs was manufacture by extract of onion peels as a reducing agent. The Au NPs that have been prepared were characterized through the UV-vis spectroscopy, XRD analyses and SEM microscopy. The polymer blends of the chitosan Schiff base / PVP has been prepared through using the approach of solution casting. Chitosan Schiff base / PVP Au nano-composites was prepared. Nano composites and polymer blends have been characterized by FTIR which confirm the formation of Schiff base by revealing a new band of absorption at 1651cm^-1 as a result of the (C=N) imine group. SEM, DSC and TGA confirms the thermal stability of

Introduction: Inadequate pain assessment and management is a problem in hospitalized patients that impairs their wellbeing. Intensive care unit nurses’ pain practices are affected by several barriers and enablers. Objectives: The objectives of this study were to determine the level of nurses’ practices and perceived barriers related to pain assessment in critically ill patients. Methodology: A cross-sectional design study was used. Purposive sampling technique was employed, including 100 nurses recruited from 8 intensive care units in Baghdad city, Iraq. The study was conducted from September 1st to October 20th, 2022. The pain assessment and management for critically ill patients survey was used to collect data. Descriptive sta

The intelligent buildings provided various incentives to get highly inefficient energy-saving caused by the non-stationary building environments. In the presence of such dynamic excitation with higher levels of nonlinearity and coupling effect of temperature and humidity, the HVAC system transitions from underdamped to overdamped indoor conditions. This led to the promotion of highly inefficient energy use and fluctuating indoor thermal comfort. To address these concerns, this study develops a novel framework based on deep clustering of lagrangian trajectories for multi-task learning (DCLTML) and adding a pre-cooling coil in the air handling unit (AHU) to alleviate a coupling issue. The proposed DCLTML exhibits great overall control and is