Objective; swine flu is known to be caused by influenza A subtypes H1N1,H1N2, H2N3, H3N1, and H3N2, was first proposed to be a disease related to human flu during the 1918 flu pandemic, Iraq face the epidemic of 2009, many patients admitted to the medical word of alkindy teaching hospital, the clinical features were observed and managed according to WHO protocols.
The aim of the study; is to asses some features of morbidity and mortality of swine flu epidemic admitted patients in 2009 in alkindy teaching hospital.
Methods; A total 131 patients with suspected influenza
admitted to Alkindy Teaching Hospital all complain of
fever more than 38c, sore throat with or without cough.
The admitted patients are of two main
groups

BACKGROUND: Cough-variant asthma (CVA) is a type of asthma in which the main symptom is a dry, non-productive cough. OBJECTIVE: The objective of the study was to evaluate the therapeutic effect of Montelukast in CVA and to investigate the prevalence of Montelukast in CVA. METHODS: A cross-sectional study was conducted on 30 patients with chronic cough at least 8 weeks using Montelukast at Al-Kindy Hospital over the period of January 2018‒March 2018. An interview using questionnaire was used to collect the data that were specifically prepared to meet the objective of study including age, sex, associated disease, exacerbation factors, and classical therapy. RESULTS: There was a reduction of the symptoms associated

Objective; swine flu is known to be caused by influenza A subtypes H1N1,H1N2, H2N3, H3N1, and H3N2, was first proposed to be a disease related to human flu during the 1918 flu pandemic, Iraq face the epidemic of 2009, many patients admitted to the medical word of alkindy teaching hospital, the clinical features were observed and managed according to WHO protocols.
The aim of the study; is to asses some features of morbidity and mortality of swine flu epidemic admitted patients in 2009 in alkindy teaching hospital.
Methods; A total 131 patients with suspected influenza
admitted to Alkindy Teaching Hospital all complain of
fever more than 38c, sore throat with or without cough.
The admitted patients are of two main
groups

Aim: The study aimed to investigate the presence of the specific B1 gene T gondii in blood and milk samples from natural infected cattle and pregnant women (16-30 weeks) whose examination performed by the officers at the women's and children's Educational hospital in Al-Diwaniyah, Iraq. Materials and methods: A total of 150 serum samplings were collected analysed and scanned for Anti-T gondi antibodies (75 naturally-infected goats and 75 pregnant women with Toxoplasma). Polymerase chain reaction (PCR) was used to detect of B1(399pb) gene in 26 goat's blood samples and 7 samples from pregnant women. Results: A quick-test anti-cassette gondii results showed 26 positive samples of goats in a percentage of 34,666 percent, while a higher percent

Most recent studies have focused on using modern intelligent techniques spatially, such as those
developed in the Intruder Detection Module (IDS). Such techniques have been built based on modern
artificial intelligence-based modules. Those modules act like a human brain. Thus, they should have had the
ability to learn and recognize what they had learned. The importance of developing such systems came after
the requests of customers and establishments to preserve their properties and avoid intruders’ damage. This
would be provided by an intelligent module that ensures the correct alarm. Thus, an interior visual intruder
detection module depending on Multi-Connect Architecture Associative Memory (MCA)

Until recently, researchers have utilized and applied various techniques for intrusion detection system (IDS), including DNA encoding and clustering that are widely used for this purpose. In addition to the other two major techniques for detection are anomaly and misuse detection, where anomaly detection is done based on user behavior, while misuse detection is done based on known attacks signatures. However, both techniques have some drawbacks, such as a high false alarm rate. Therefore, hybrid IDS takes advantage of combining the strength of both techniques to overcome their limitations. In this paper, a hybrid IDS is proposed based on the DNA encoding and clustering method. The proposed DNA encoding is done based on the UNSW-NB15

In this paper, RBF-based multistage auto-encoders are used to detect IDS attacks. RBF has numerous applications in various actual life settings. The planned technique involves a two-part multistage auto-encoder and RBF. The multistage auto-encoder is applied to select top and sensitive features from input data. The selected features from the multistage auto-encoder is wired as input to the RBF and the RBF is trained to categorize the input data into two labels: attack or no attack. The experiment was realized using MATLAB2018 on a dataset comprising 175,341 case, each of which involves 42 features and is authenticated using 82,332 case. The developed approach here has been applied for the first time, to the knowledge of the authors, to dete

Cybersecurity refers to the actions that are used by people and companies to protect themselves and their information from cyber threats. Different security methods have been proposed for detecting network abnormal behavior, but some effective attacks are still a major concern in the computer community. Many security gaps, like Denial of Service, spam, phishing, and other types of attacks, are reported daily, and the attack numbers are growing. Intrusion detection is a security protection method that is used to detect and report any abnormal traffic automatically that may affect network security, such as internal attacks, external attacks, and maloperations. This paper proposed an anomaly intrusion detection system method based on a

Cybersecurity refers to the actions that are used by people and companies to protect themselves and their information from cyber threats. Different security methods have been proposed for detecting network abnormal behavior, but some effective attacks are still a major concern in the computer community. Many security gaps, like Denial of Service, spam, phishing, and other types of attacks, are reported daily, and the attack numbers are growing. Intrusion detection is a security protection method that is used to detect and report any abnormal traffic automatically that may affect network security, such as internal attacks, external attacks, and maloperations. This paper proposed an anomaly intrusion detection system method based on a

Modern civilization increasingly relies on sustainable and eco-friendly data centers as the core hubs of intelligent computing. However, these data centers, while vital, also face heightened vulnerability to hacking due to their role as the convergence points of numerous network connection nodes. Recognizing and addressing this vulnerability, particularly within the confines of green data centers, is a pressing concern. This paper proposes a novel approach to mitigate this threat by leveraging swarm intelligence techniques to detect prospective and hidden compromised devices within the data center environment. The core objective is to ensure sustainable intelligent computing through a colony strategy. The research primarily focusses on the