Characterization of Macerals in Coal Fines using Image Analysis Technique

Coal is an aggregate of heterogeneous substance consisting of various or aiiic cemsti-tnents so called nuacerals along with inorganic matter. These inacerals have been broadly classified into three major maceral groups i.e. vitrinite, exinite (liptinite) and inertinite. Coal-fines of size less than 0.5 mm, collected from Moonidih coal washery, was used in the present stud. These coal fines were subjected to size analysis and sink-float analysis. The products obtained at different size and density fractions were mounted in resin + hardener mixture using standard sample preparation technique and polished- The polished samples were examined tender- microscope inte-rfaced with image analyzer: Results indicate that size and density fractions have a significant influence on the changes in the maceral concentrations. The same has been discussed in terms of physical coal cleaning, process

Stock Market Analysis and Prediction Using ML

Seventy-Five percentage of Business pioneers state 'development' as the key wellspring of significant worth from investigation yet Just sixty percentage of these pioneers have prescient exam abilities. The solution to this is applying the correct arrangements of applications, which can work on huge bits of information. Machine Learning Calculations are major application which makes it possible. The place of this task is to break down through different expecting techniques to anticipate future stock benefits dependent on past data returns to build up a game plan of various stocks to know the varieties in the outcomes. We are doing this by applying machine learning strategy to determine stock value and provide the users with a better prediction and assist them with proper stock investments on web

An Efficient Hybrid Protocol Framework for DDoS Attack Detection and Mitigation Using Evolutionary Technique, Journal of Telecommunications and Information Technology, 2022, nr 4

The ever-increasing use of the Internet has created massive amounts network traffic, causing problems related to its scalability, controllability, and manageability. Sophisticated network-based denial of service (DoS) and distributed denial of service (DDoS) attacks increasingly pose a future threat. The literature proposes various methods that may help stop all HTTP DoS/DDoS assaults, but no optimal solution has been identified so far. Therefore, this paper attempts to fill the gap by proposing an alternative solution known as an efficient hybrid protocol framework for distributed DoS attack detection and mitigation (E-HPFDDM). Such an architecture addresses all aspects of these assaults by relaying on a three-layer mechanism. Layer 1 uses the outer advanced blocking (OAB) scheme which blocks unauthorized IP sources using an advanced backlisted table. Layer 2 is a validation layer that relies on the inner service trackback (IST) scheme to help determine whether the inbound request has been initiated by a legitimate or an illegitimate user. Layer 3 (inner layer) uses the deep entropy based (DEB) scheme to identify, classify and mitigate high-rate DDoS (HR-DDoS) and flash crowd (FC) attacks. The research shows that in contrast to earlier studies, the structure of the proposed system offers effective defense against DoS/DDoS assaults for web applications

Smart Calculation using Edge Computing

Number of things are getting connected to Internet so Necessity of data on Edge in Real-time and without latency, With Edge computing system we can perform Efficient Data processing has large amount of data and it reduces internet bandwidth. Edge computing is a new computing pattern in which fundamental compute and storage Resources are placed at Internet, Nearer to Mobile devices, Sensors and Internet of things (IOT) this will increase Latency. Definition of Edge computing as a Mesh Network of Micro-data centers that process or store critical temporarily and push all received data to central data or cloud storage, in a footprint of less than 100sqft with Edge computing abilities, System can perform Structured Data as large amount of data can be processed at or nearer the source. Edge computing allows Smart application and devices to respond to data which is been created. This is useful for Self-driving Cars and many more benefits for Business. Edge computing reduces volume of data that must be moved, traffic and the distance that data must travel it provides very low Latency and transmitted cost and the other use of Edge computing is clou Gaming where some aspects of game will run in cloud

An Efficient Hybrid Protocol Framework for DDoS Attack Detection and Mitigation Using Evolutionary Technique

The ever-increasing use of the Internet has created massive amounts network traffic, causing problems related to its scalability, controllability, and manageability. Sophisticated network-based denial of service (DoS) and distributed denial of service (DDoS) attacks increasingly pose a future threat. The literature proposes various methods that may help stop all HTTP DoS/DDoS assaults, but no optimal solution has been identified so far. Therefore, this paper attempts to fill the gap by proposing an alternative solution known as an efficient hybrid protocol framework for distributed DoS attack detection and mitigation (E-HPFDDM). Such an architecture addresses all aspects of these assaults by relaying on a three-layer mechanism. Layer 1 uses the outer advanced blocking (OAB) scheme which blocks unauthorized IP sources using an advanced backlisted table. Layer 2 is a validation layer that relies on the inner service trackback (IST) scheme to help determine whether the inbound request has been initiated by a legitimate or an illegitimate user. Layer 3 (inner layer) uses the deep entropy based (DEB) scheme to identify, classify and mitigate high-rate DDoS (HR-DDoS) and flash crowd (FC) attacks. The research shows that in contrast to earlier studies, the structure of the proposed system offers effective defense against DoS/DDoS assaults for web applications