In recent years, the migration of the computational workload to computational clouds has attracted intruders to target and exploit cloud networks internally and externally. The investigation of such hazardous network attacks in the cloud network requires comprehensive network forensics methods (NFM) to identify the source of the attack. However, cloud computing lacks NFM to identify the network attacks that affect various cloud resources by disseminating through cloud networks. In this paper, the study is motivated by the need to find the applicability of current (C-NFMs) for cloud networks of the cloud computing. The applicability is evaluated based on strengths, weaknesses, opportunities, and threats (SWOT) to outlook the cloud network. To the best of our knowledge, no research to date has been conducted to assist network forensics investigators and cloud service providers in finding an optimal method for investigation of network vulnerabilities found in cloud networks. To this end and in this paper, the state-of-the-art C-NFMs are classified and analyzed based on the cloud network perspective using SWOT analysis. It implies that C-NFMs have a suitable impact on cloud network, which further requires for reformation to ensure its applicability in cloud networks.
Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twentyfour samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.
A Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twenty four samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.
The goal of this work is demonstrating, through the gradient observation of a of type linear ( -systems), the possibility for reducing the effect of any disturbances (pollution, radiation, infection, etc.) asymptotically, by a suitable choice of related actuators of these systems. Thus, a class of ( -system) was developed based on finite time ( -system). Furthermore, definitions and some properties of this concept -system and asymptotically gradient controllable system ( -controllable) were stated and studied. More precisely, asymptotically gradient efficient actuators ensuring the weak asymptotically gradient compensation system ( -system) of known or unknown disturbances are examined. Consequently, under convenient hypo
... Show MoreAbstract: Microfluidic devices present unique advantages for the development of efficient drug assay and screening. The microfluidic platforms might offer a more rapid and cost-effective alternative. Fluids are confined in devices that have a significant dimension on the micrometer scale. Due to this extreme confinement, the volumes used for drug assays are tiny (milliliters to femtoliters).
In this research, a microfluidic chip consists of micro-channels carved on substrate materials built by using Acrylic (Polymethyl Methacrylate, PMMA) chip was designed using a Carbon Dioxide (CO2) laser machine. The CO2 parameters have influence on the width, depth, roughness of the chip. In order to have regular
... Show MoreThe increasing complexity of assaults necessitates the use of innovative intrusion detection systems (IDS) to safeguard critical assets and data. There is a higher risk of cyberattacks like data breaches and unauthorised access since cloud services have been used more frequently. The project's goal is to find out how Artificial Intelligence (AI) could enhance the IDS's ability to identify and classify network traffic and identify anomalous activities. Online dangers could be identified with IDS. An intrusion detection system, or IDS, is required to keep networks secure. We must create efficient IDS for the cloud platform as well, since it is constantly growing and permeating more aspects of our daily life. However, using standard intrusion
... Show MoreThis research examines the quantitative analysis to assess the efficiency of the transport network in Sadr City, where the study area suffers from a large traffic movement for the variability of traffic flow and intensity at peak hours as a result of inside traffic and outside of it, especially in the neighborhoods of population with economic concentration. &n
... Show MoreThe bandwidth requirements of telecommunication network users increased rapidly during the last decades. Optical access technologies must provide the bandwidth demand for each user. The passive optical access networks (PONs) support a maximum data rate of 100 Gbps by using the Orthogonal Frequency Division Multiplexing (OFDM) technique in the optical access network. In this paper, the optical broadband access networks with many techniques from Time Division Multiplexing Passive Optical Networks (TDM PON) to Orthogonal Frequency Division Multiplex Passive Optical Networks (OFDM PON) are presented. The architectures, advantages, disadvantages, and main parameters of these optical access networks are discussed and reported which have many ad
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