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

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

Ground-based active optical sensors (GBAOS) have been successfully used in agriculture to predict crop yield potential (YP) early in the season and to improvise N rates for optimal crop yield. However, the models were found weak or inconsistent due to environmental variation especially rainfall. The objectives of the study were to evaluate if GBAOS could predict YP across multiple locations, soil types, cultivation systems, and rainfall differences. This study was carried from 2011 to 2013 on corn (Zea mays L.) in North Dakota, and in 2017 in potatoes in Maine. Six N rates were used on 50 sites in North Dakota and 12 N rates on two sites, one dryland and one irrigated, in Maine. Two active GBAOS used for this study were GreenSeeker and Holl

The operation of production planning is a difficult operation and it's required High effect and large time especially it is dynamic activity which it's basic variables change in continuous with the time, for this reason it needs using one of the operation research manner (Dynamic programming) which has a force in the decision making process in the planning and control on the production and its direct affect on the cost of production operation and control on the inventory.

The importance of this research comes from the possibility of achieving positive interaction between accounting and tax through the interest in setting accounting standards and adapting them to local tax legislation, as the adoption of the application of the international standard (IAS 12) for income taxes helps to measure and determine the base for income tax and may lead to an increase in the tax outcome. Through the reliance of enterprises on many accounting bases, and that the tax administration in Iraq depends on the element of personal judgment in determining the tax base, which leads to lack of objectivity in determining the tax outcome, as the impact of the accounting standard (IAS 12) on the tax base and tax outcome is one of th

<span>Dust is a common cause of health risks and also a cause of climate change, one of the most threatening problems to humans. In the recent decade, climate change in Iraq, typified by increased droughts and deserts, has generated numerous environmental issues. This study forecasts dust in five central Iraqi districts using machine learning and five regression algorithm supervised learning system framework. It was assessed using an Iraqi meteorological organization and seismology (IMOS) dataset. Simulation results show that the gradient boosting regressor (GBR) has a mean square error of 8.345 and a total accuracy ratio of 91.65%. Moreover, the results show that the decision tree (DT), where the mean square error is 8.965, c

This study examined the effect of transformational leadership four main dimensions (ideal influence, inspirational motivation, intellectual stimulation, individual considerations) as the independent variable on the dimensions of empowerment (knowledge and skill, communication, trust, incentives).

The study sought to achieve a set of goals and most important: the study of the reality of the organization surveyed to identify strategies or policies with employees by transformational leadership, moreover see how much support such a leadership strategy for empowerment and describe the dimensions of empowerment of (knowledge and skill, communication, and trust , and incentives) and the extent of its contributio

The objective of this research is to know the extent to which Iraqi and Arab companies apply the criteria of accounting for sustainability and disclosure, as well as to analyze the content of the annual financial reports of the companies listed in the financial market to determine their compliance with the Sustainability Accounting Standards Board )SASB(. Annual Report The commitment of telecommunications companies to implement sustainability issues related to the standard of telecommunications services reached a general average of (54%) for the sample of the research sample. This means that there is a degree of admissibility in applying the standard. As well as the highest level of reporting to the criterion of the (Jordan Telec

Construction projects have become a changing dramatically in recent decades and that the goal of the beneficiaries of the implementation of structural project is to complete the work with less time and within the cost of the specific and the best possible quality may sometimes happen that highlights the importance of time on the rest of the items at the implementation of projects for various reasons, including the need to use the project as soon as possible possible change rapidly to customer's requests, but the high cost of the project represents the biggest obstacle for entrepreneurs with its effects on the quality and the time workers, and is a measure of those elements in monetary terms is the key to integration between them, so the

The prevalence of using the applications for the internet of things (IoT) in many human life fields such as economy, social life, and healthcare made IoT devices targets for many cyber-attacks. Besides, the resource limitation of IoT devices such as tiny battery power, small storage capacity, and low calculation speed made its security a big challenge for the researchers. Therefore, in this study, a new technique is proposed called intrusion detection system based on spike neural network and decision tree (IDS-SNNDT). In this method, the DT is used to select the optimal samples that will be hired as input to the SNN, while SNN utilized the non-leaky integrate neurons fire (NLIF) model in order to reduce latency and minimize devices