The recent advances in technology, the increased dependence on electrical energy and the emergence of the fourth industrial revolution (Industry 4.0) were all factors in the increased need for smart, efficient and reliable energy systems. This introduced the concept of the Smart Grid (SG). A SG is a potential replacement for older power grids, capable of adapting and distributing energy based on demand. SG systems are complex. They combine various components and have high requirements for real time reliable operation. This paper attempts to provide an overview of SG systems, by outlining SG architecture and various components. It also introduces communication technologies, integration and network management tools that are involved in SG sys

Within the framework of big data, energy issues are highly significant. Despite the significance of energy, theoretical studies focusing primarily on the issue of energy within big data analytics in relation to computational intelligent algorithms are scarce. The purpose of this study is to explore the theoretical aspects of energy issues in big data analytics in relation to computational intelligent algorithms since this is critical in exploring the emperica aspects of big data. In this chapter, we present a theoretical study of energy issues related to applications of computational intelligent algorithms in big data analytics. This work highlights that big data analytics using computational intelligent algorithms generates a very high amo

<p><span>A Botnet is one of many attacks that can execute malicious tasks and develop continuously. Therefore, current research introduces a comparison framework, called BotDetectorFW, with classification and complexity improvements for the detection of Botnet attack using CICIDS2017 dataset. It is a free online dataset consist of several attacks with high-dimensions features. The process of feature selection is a significant step to obtain the least features by eliminating irrelated features and consequently reduces the detection time. This process implemented inside BotDetectorFW using two steps; data clustering and five distance measure formulas (cosine, dice, driver &amp; kroeber, overlap, and pearson correlation

Grass trimming operation is widely done in Malaysia for the purpose of maintaining highways. Large number of operators engaged in this work encounters high level of noise generated by back pack type grass trimmer used for this purpose. High level of noise exposure gives different kinds of ill effect on human operators. Exact nature of deteriorated work performance is not known. For predicting the work efficiency deterioration, fuzzy tool has been used in present research. It has been established that a fuzzy computing system will help in identification and analysis of fuzzy models fuzzy system offers a convenient way of representing the relationships between the inputs and outputs of a system in the form of IF-THEN rules. The paper presents

Numerical simulations are carried out to evaluate the coherence concept’s effect on the performance regarding the optical system, when observing and imaging the planet’s surface. In numerous optical approaches, the coherence qualities of light sources play an important role. This paper provides an overview about the mathematical formulation of temporal and spatial coherence and incoherence properties of light sources. The circular aperture was used to describe the optical system like a telescope. The simulation results show that diffraction-limited for incoherent imaging system certainly improves the image. Yet, the quality of the image is degraded by the light source's highly spatial and temporal coherence properties, resulting in a

This research a study model of linear regression problem of autocorrelation of random error is spread when a normal distribution as used in linear regression analysis for relationship between variables and through this relationship can predict the value of a variable with the values of other variables, and was comparing methods (method of least squares, method of the average un-weighted, Thiel method and Laplace method) using the mean square error (MSE) boxes and simulation and the study included fore sizes of samples (15, 30, 60, 100). The results showed that the least-squares method is best, applying the fore methods of buckwheat production data and the cultivated area of the provinces of Iraq for years (2010), (2011), (2012),

The recent advancements in security approaches have significantly increased the ability to identify and mitigate any type of threat or attack in any network infrastructure, such as a software-defined network (SDN), and protect the internet security architecture against a variety of threats or attacks. Machine learning (ML) and deep learning (DL) are among the most popular techniques for preventing distributed denial-of-service (DDoS) attacks on any kind of network. The objective of this systematic review is to identify, evaluate, and discuss new efforts on ML/DL-based DDoS attack detection strategies in SDN networks. To reach our objective, we conducted a systematic review in which we looked for publications that used ML/DL approach

The increasing number of orphans and their organizations and institutes in our community makes it increasingly important to design and develop an expert system that supports decisions concerning orphans and their families. This system can be used by any orphans organization to facilitate its work.
The proposed work is designed to manage the Orphans and Families of Martyrs of Terrorism Expert System (OFMTES) by registry all information about all orphans to display mostly orphan deserves bill, data is entered for each orphan, and with each entry a counter is increased according to this input information; the output result represents the score for that orphan. Different orphans have different scores. Coloring is used to know the degree o