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

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

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

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

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)

Atrial fibrillation is associates with elevated risk of stroke. The simplest stroke risk assessment schemes are CHADS₂ and CHA₂DS₂-VASc score. Aspirin and oral anticoagulants are recommended for stroke prevention in such patients.

The aim of this study was to  assess status of CHADS₂ and CHA₂DS₂-VASc scores in Iraqi atrial fibrillation patients and to report current status of stroke prevention in these patients with either warfarin or aspirin in relation to these scores.

This prospective cross-sectional study was carried out at Tikrit, Samarra, Sharqat, Baquba, and AL-Numaan hospitals from July 2017 to October 2017. CHADS₂

The aim of the research is to know the characteristics of both variables in order to be able the to construct the integrated framework of its paragraphs through the available information on both inspirational leadership and organizational health. as fundamental variables of research,  as well as the extent of the influence of the inspirational variable as an independent variable in the  organizational health variable as a variable in its three  physical, mental and social dimensions. The research is important to stimulate the behavior side of the staff. Which is one of the top concerns of senior management in the ministry, because of its great importance in increasing the effectiveness of the  performance of e

The aim of this research was to indicate the opinion of the Iraqi consumer about the quality and safety of local food products, the questionnaire was included 19 questions for product quality, price, distribution and promotion as a tool to survey the opinions of 128 consumers in Baghdad, the data was analyzed by using percentage, weighted mean, and weight percent, the results obtained showed that the Iraqi consumer prefer local food products for their high quality and appropriate price, however they need attention to packaging, promotion and distribution.