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.
In this golden age of rapid development surgeons realized that AI could contribute to healthcare in all aspects, especially in surgery. The aim of the study will incorporate the use of Convolutional Neural Network and Constrained Local Models (CNN-CLM) which can make improvement for the assessment of Laparoscopic Cholecystectomy (LC) surgery not only bring opportunities for surgery but also bring challenges on the way forward by using the edge cutting technology. The problem with the current method of surgery is the lack of safety and specific complications and problems associated with safety in each laparoscopic cholecystectomy procedure. When CLM is utilize into CNN models, it is effective at predicting time series tasks like iden
... Show MoreIn the literature, several correlations have been proposed for bubble size prediction in bubble columns. However these correlations fail to predict bubble diameter over a wide range of conditions. Based on a data bank of around 230 measurements collected from the open literature, a correlation for bubble sizes in the homogenous region in bubble columns was derived using Artificial Neural Network (ANN) modeling. The bubble diameter was found to be a function of six parameters: gas velocity, column diameter, diameter of orifice, liquid density, liquid viscosity and liquid surface tension. Statistical analysis showed that the proposed correlation has an Average Absolute Relative Error (AARE) of 7.3 % and correlation coefficient of 92.2%. A
... Show MoreThis research including lineament automated extraction by using PCI Geomatica program, depending on satellite image and lineament analysis by using GIS program. Analysis included density analysis, length density analysis and intersection density analysis. When calculate the slope map for the study area, found the relationship between the slope and lineament density.
The lineament density increases in the regions that have high values for the slope, show that lineament play an important role in the classification process as it isolates the class for the other were observed in Iranian territory, clearly, also show that one of the lineament hit shoulders of Galal Badra dam and the surrounding areas dam. So should take into consideration
Wireless Body Area Sensor Network (WBASN) is gaining significant attention due to its applications in smart health offering cost-effective, efficient, ubiquitous, and unobtrusive telemedicine. WBASNs face challenges including interference, Quality of Service, transmit power, and resource constraints. Recognizing these challenges, this paper presents an energy and Quality of Service-aware routing algorithm. The proposed algorithm is based on each node's Collaboratively Evaluated Value (CEV) to select the most suitable cluster head (CH). The Collaborative Value (CV) is derived from three factors, the node's residual energy, the distance vector between nodes and personal device, and the sensor's density in each CH. The CEV algorithm operates i
... Show MoreThe urban Gentrification is an inclusive global phenomenon to restructure the cities on the overall levels, the research to propose a specific study about the concept of urban Gentrification in the cities and showcasing its, specifications, and results, and how to deal with the variables that occur on cities through improvements as part of urban renewal projects, then the general axis of the research is shrinked, choosing the urban centers as the most important areas that deal with the urban Gentrification process due to its direct connection with indivisuals and social changes, and to process the specific axis of the research theses and studies will be showcased that discuss the topic in different research directions, and emerged
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