As organizations generate and store more data in the cloud and hybrid infrastructures, their databases’ attack surface area grows. This makes organizational databases a prime target for cyber-attacks. Using only the perimeter security and existing database controls is not enough to protect against APT, insider threat and zero-day attack. A novel Database Cybersecurity System framework is presented to move beyond silos to proactive, smart layered security, in this article. The proposed system provides real-time threat analytics, adaptive encryption, and incident automation all within one management centre. It involves designing a core monitoring agent, analysis engine based on machine learning, and policy enforcement module. Comparison analysis shows that DBCS has better performance than traditional IDS and SIEM against contextual awareness and response latency. Which results in enhanced security of blockchain networks with decentralized BCS? The pseudo-code presents the basic functions for anomaly detection and automatic quarantine. As per the simulated results, we find 92% reduction of false positive and mean time to respond (MTTR) to critical threat to be less than 2 seconds and that in case of conventional it is 15 minutes. Ultimately, this paper shows that behavior baselining through machine learning along with immutable audit logging through the blockchain can secure the next-generation database. Implementation and capacity building should be carefully undertaken, it is recommended. The networks of Professor must embed Cyber Defense Ecosystems.
This study aims to encapsulate atenolol within floating alginate-ethylcellulose beads as an oral controlled-release delivery system using aqueous colloidal polymer dispersion (ACPD) method.To optimize drug entrapment efficiency and dissolution behavior of the prepared beads, different parameters of drug: polymer ratio, polymer mixture ratio, and gelling agent concentration were involved.The prepared beads were investigated with respect to their buoyancy, encapsulation efficiency, and dissolution behavior in the media: 0.1 N HCl (pH 1.2), acetate buffer (pH 4.6) and phosphate buffer (pH 6.8). The release kinetics and mechanism of the drug from the prepared beads was investigated.All prepare
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The Financial systems can be classified into two types. The first is the market–oriented, which is applied in United States and United Kingdom. While the second is bank-oriented as in Japan and Germany.
This study tries to explain the reasons which make some countries adopt the first one instead of the second, and the contrary. So the study consists of three sections. The first deals with the concept of financial system and it are functions. The second displays the indicators which are used to classify the financial systems, while the third one is devoted to the factors that determine the type of financial system .These sections followed by some conclusions.
The analytical study of optical bistability is concerned in a fully
optimized laser Fabry-Perot system. The related phenomena of
switching dynamics and optimization procedure are also included.
From the steady state of optical bistability equation can plot the
incident intensity versus the round trip phase shift (φ) for different
values of dark mistuning
12
,
6
,
3
,
1.5
0 , o
or finesse (F= 1, 5, 20,
100). In order to obtain different optical bistable loops. The inputoutput
characteristic for a nonlinear Fabry-Perot etalon of a different
values of finesse (F) and using different initial detuning (φ0) are used
in this rese
The electrochemical behavior of carbon steel in water sweetening station in Libya has been studied in the range of ( 293–333 oC) using weight loss technique. Measurements were carried out over a range of Reynolds number (5000 – 25000).An apparatus was designed for studying the corrosion process in the turbulent regime, which is of industrial significance. It was found that The corrosion rate of carbon steel in water sweetening station is under diffusion control and increases with increasing Reynolds number. On the other hand the variation of corrosion rate with temperature in the range of (293–333 oC) was found to follow Arrhenius equation and the activation energy approximately the same except at low Reynolds
... Show MoreAlthough the majority of trends confirm the design aspects of the performance, functional and aesthetic design of the product. However, the attention was more focused on the nature of the plastic for those results, it is through the appearance of formal and guaranteed career such as designing Achieved adopt us the extent of the impact Relations Association between the elements and principles of design to achieve complementarity in the completed design of aesthetic and functional significance expressive and symbolic and in doing so has introduced a lot of new concepts for the arrangement and organization, coordination and functional classification of the unfinished design gave way to show diversity trends in the design of industrial produ
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It is proposed and studied a prey-predator system with a Holling type II functional response that merges predation fear with a predator-dependent prey's refuge. Understanding the impact of fear and refuge on the system's dynamic behavior is one of the objectives. All conceivable steady-states are investigated for their stability. The persistence condition of the system has been established. Local bifurcation analysis is performed in the Sotomayor sense. Extensive numerical simulation with varied parameters was used to explore the system's global dynamics. A limit cycle and a point attractor are the two types of attractors in the system. It's also interesting to note that the system exhibits bi-stability between these 2 types of attractors.
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Wildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob
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The rise of Industry 4.0 and smart manufacturing has highlighted the importance of utilizing intelligent manufacturing techniques, tools, and methods, including predictive maintenance. This feature allows for the early identification of potential issues with machinery, preventing them from reaching critical stages. This paper proposes an intelligent predictive maintenance system for industrial equipment monitoring. The system integrates Industrial IoT, MQTT messaging and machine learning algorithms. Vibration, current and temperature sensors collect real-time data from electrical motors which is analyzed using five ML models to detect anomalies and predict failures, enabling proactive maintenance. The MQTT protocol is used for efficient com
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