Software-defined networking (SDN) is an innovative network paradigm, offering substantial control of network operation through a network’s architecture. SDN is an ideal platform for implementing projects involving distributed applications, security solutions, and decentralized network administration in a multitenant data center environment due to its programmability. As its usage rapidly expands, network security threats are becoming more frequent, leading SDN security to be of significant concern. Machine-learning (ML) techniques for intrusion detection of DDoS attacks in SDN networks utilize standard datasets and fail to cover all classification aspects, resulting in under-coverage of attack diversity. This paper proposes a hybr

     Community detection is an important and interesting topic for better understanding and analyzing complex network structures. Detecting hidden partitions in complex networks is proven to be an NP-hard problem that may not be accurately resolved using traditional methods. So it is solved using evolutionary computation methods and modeled in the literature as an optimization problem.  In recent years, many researchers have directed their research efforts toward addressing the problem of community structure detection by developing different algorithms and making use of single-objective optimization methods. In this study, we have continued that research line by improving the Particle Swarm Optimization (PSO) algorithm using a

Heart sound is an electric signal affected by some factors during the signal's recording process, which adds unwanted information to the signal. Recently, many studies have been interested in noise removal and signal recovery problems. The first step in signal processing is noise removal; many filters are used and proposed for treating this problem. Here, the Hankel matrix is implemented from a given signal and tries to clean the signal by overcoming unwanted information from the Hankel matrix. The first step is detecting unwanted information by defining a binary operator. This operator is defined under some threshold. The unwanted information replaces by zero, and the wanted information keeping in the estimated matrix. The resulting matrix

This study aims to determine the prevalence of Entamoeba histolytica, Entamoeba dispar and
Entamoeba moshkovskii by three methods of diagnosis (microscopic examination, cultivation and PCR) that
were compared to obtain an accurate diagnosis of Entamoeba spp. during amoebiasis. Total (n=150) stool
samples related to patients were (n = 100) and healthy controls (n= 50). Clinically diagnosed stool samples
(n=100) were collected from patients attending the consultant clinics of different hospitals in Basrah during
the period from January 2018 to January 2019. The results showed that 60% of collected samples were
positive in a direct microscopic examination. All samples were cultivated on different media; the Bra

Out of a total of fifty samples, thirty-five isolates were identified as Serratia marcescens. Thesediverse clinical samples were collected over a three-month period, from October 2023 to December 2023, fromseveral hospitals in Baghdad, including Fatima Al-Zahraa Hospital, Al-Sader Hospital, Ibn Al-Balady Hospital,and Al-Imam Ali Hospital. The clinical samples primarily included urine from patients with urinary tractinfections (UTIs). All isolates were cultured on nutrient agar, MacConkey agar, and blood agar, and theiridentities were confirmed through biochemical testing and the Vitek 2 compact system. Based on phenotypicvirulence factors, the S. marcescens isolates showed varying positive patterns: 32 out of 35 (91.42%) forprotease

After the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings

Rationing is a commonly used solution for shortages of resources and goods that are vital for the citizens of a country. This paper identifies some common approaches and policies used in rationing as well asrisks that associated to suggesta system for rationing fuelwhichcan work efficiently. Subsequently, addressing all possible security risks and their solutions. The system should theoretically be applicable in emergency situations, requiring less than three months to implement at a low cost and minimal changes to infrastructure.

The organization and coordination of any communication is based on the system of turn-taking which refers to the process by which a participant in a conversation takes the role of speaker. The progression of any conversation is achieved by the change of roles between speaker and hearer which, in its turn, represents the heart of the turn-taking system. The turn-taking system is not a random process but it is a highly organized process governed by a set of rules. Thus, this system has certain features and rules which exist in any English communicative process. These rules, if applied by speakers, help to achieve successful exchange of turns in any conversation. This paper attempts to present full exposition of the concepts of conversation

  This study investigated the effect of applying an external magnetic field on the characteristics of laser-induced plasma, such as its parameters plasma, magnetization properties, emission line intensities, and plasma coefficients, for plasma induced from zinc oxide: aluminum composite (ZO:AL) at an atomic ratio of 0.3 %. Plasma properties include magnetization and emission line intensities. The excitation was done by a pulsed laser of Nd:YAG with 400 mJ energy at atmospheric pressure. Both the electron temperature and number density were determined with the help of the Stark effect principle and the Boltzmann-Plot method. There was a rise in the amount of (n_e) and (T_e) that was produced