Volume 11 | Issue 2 |

 Abstract

The security of a 5G wireless network will be challenged by a wide range of sophisticated hacking methods. We propose and develop a novel cooperative attack detection method that makes use of a hierarchical Reinforcement Learning (RL) mechanism in order to better identify network assaults and focus on protecting 5G wireless networks from the most severe and cutting-edge forms of network assault, such as DDoS and jamming. Distributed detection systems are operated at the several important nodes of the 5G network (AP, BTS, and servers) to accomplish the cooperative detection. Results from our trials show that the suggested RL detection system improves the ability to identify novel malicious actions and assaults. All network activity is analysed for malicious behaviour using IDS powered by machine learning. Enhancing the intrusion detection system's detection rate was the primary objective of the system design, with a focus on false negative and false positive performance measures. Different machine learning models, including SVM and KNN classifiers, are built and compared.

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 Keywords

5G Wireless Network, Reinforcement Learning, Network Attack Detection, Cyber Threats

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The currency exchange market is the largest and most liquid market in the world. The average daily trading volume in the global foreign exchange and related markets is estimated at $4 trillion. Currencies are fundamental to the majority of people in the globe because they must be traded in order to execute international trade and business, the trading of different currencies and the purchase prediction of one currency in relation to another is the topic that never get old. At the end of the day, fair and accurate estimates of these exchange rates manage international transactions and the worldwide financial system. Effectively estimating the currency exchange rate is a challenging task. We developed a Currency Exchange Rate Prediction System that uses machine learning algorithms to predict Exchange Rate accurately.

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 Keywords

Trading, Currency Exchange Rate, Estimates, Machine Learning

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Construction materials that are friendly to the environment are now being researched and developed all over the globe in an effort to limit the use of natural resources that are depleting at an alarming rate and to cut down on the production of greenhouse gases. In this respect, geopolymer plays an extremely important function, and a large number of researchers have investigated the numerous dimensions of its viability as a material for binding. In order to alter the geopolymerisation reaction of fly ash, ground granulated blast furnace slag (abbreviated as GGBS) has been used into fly ash-based geopolymer concrete (abbreviated as GPC). In this paper, the influence of various proportions of GGBS (0-100%) on Fly Ash based GPC, as well as the effect of the amount of Alkaline Activated Solution (AAS) in the mixture of GPC, is studied to determine how it affects the compressive strength of the GPC under conditions of ambient temperature. It was observed from the results of the experiments that the compressive strength of the GPC increases both with an increase in the percentage of GGBS and also with an increase in the amount of the sodium silicate solution in which the concentration of sodium hydroxide in the aqueous solution is fixed at a constant value of 10M. This was the case even though the amount of sodium hydroxide that was present in the solution remained the same.

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 Keywords

Alkaline Solution, GGBS, Geopolymer, Flyash

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Collapsible soils are black cotton soils with extremely high shear strength when dry but rapidly lose strength when wet. Such rapid and significant loss of strength causes significant distress, resulting in extensive cracking and differential settlements, unstable building foundations, and even the collapse of structures built on these soils. Waste marble dust and Ground Granulated Blast Furnace Slag are industrial byproducts that are produced in massive quantities around the world and pose a threat to the environment. As a result, finding a long-term solution for its disposal is critical. The current study used a physio-chemical technique to reduce the collapse potential of black cotton soil. Because the soil is water-sensitive, it must be stabilised. Different percentages of waste marble dust (WMD) and ground granulated blast furnace slag (GGBFS) were used as an admixture. The effect of admixture on soil parameters such as specific gravity, plasticity index, swelling index, and shrinkage limit is investigated in this study. The study's optimization process revealed that adding waste marble dust improved the geotechnical parameters of black cotton soil significantly. Plasticity was reduced while Unconfined Compressive Strength (UCS) increased significantly. This research evaluates the safe disposal of hazardous waste and converts it into suitable material for engineering purposes

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 Keywords

UCS, GGBFS, WMD

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Creative Commons Attribution 4.0 and The Open Definition

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Because road damage has resulted in numerous deaths, research into road damage detection, particularly hazardous road damage detection and warning, is essential for traffic safety. Existing road damage detection systems mostly process data on the cloud, which has a large latency due to long-distance transmission. Meanwhile, in these systems that require big, carefully labeled datasets to achieve outstanding performance, supervised machine learning methods are typically used. We suggest using Deep Learning to detect and warn about road damage in this study. The foundation of road surface analysis is visual observations by persons and quantitative analysis by pricey tools. Visual inspection, for example, not only necessitates the use of experienced road managers but also takes time and money. Furthermore, visual inspection is inherently unreliable and inconsistent, increasing the risk. Vi- visual inspection of roads by engineers takes a long time due to the length of roads or freeways. As a result, establishing an AI-based automated system that can determine the sort of damage can help to improve and enhance the way road conditions are assessed.

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 Keywords

Road Damage Detection, Deep Learning, Image Processing, CNN, etc

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

CASE STUDY ON PLANTINUM INDUSTRIES PVT. LTD. MUMBAI

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CASE STUDY ON PLANTINUM INDUSTRIES PVT. LTD. MUMBAI

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Creative Commons Attribution 4.0 and The Open Definition

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(pandemic, mental health, schools, colleges, online, emotion, behaviour, teaching)

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IMPORTANCE OF SOCIAL MEDIA IN TRIBAL DEVELOPMENT: A STUDY OF KORAGA TRIBE IN UDUPI DISTRICT, KARNATAKA

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IMPORTANCE OF SOCIAL MEDIA IN TRIBAL DEVELOPMENT: A STUDY OF KORAGA TRIBE IN UDUPI DISTRICT, KARNATAKA

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 Abstract

For the development of the country's economy, the logistics sector must be at a level that can compete in the international market. This requires a higher level than the logistics level of the foreign market. This can be achieved by using the latest technologies or by manufacturing new technologies. In particular, logistics with the aim of responding to customer needs as quickly as possible; has become a strong sector with advanced technological structures and growing consumer demands with the influence of globalization. As a result, businesses have had to keep innovation on the agenda to keep profit margins and customer satisfaction high. In this study, the digital logistics process and digital structures used in the logistics industry in international trade are mentioned. The benefits of digitization are discussed in detail. Information is provided on the future of digital logistics. Modern foreign and domestic studies mostly consider the digital transformation of the economy to be a combination of effects arising under the influence of a number of introduced digital innovations, which lead to the emergence of new economic structures, new business practices, but also new values. and beliefs in the business environment. The article is dedicated to researching the characteristics of the development of logistics networks in the context of globalization and digitalization of the economy. Issues of increasing the efficiency of the operation of logistics networks using digital technologies through the creation of information logistics platforms were also considered. As a scientific novelty of the study, the highlighted advantages of digitalization of logistics platforms should be noted.

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The most basic explanation of digitalization; is the replacement or replacement of existing resources with digital products to provide the highest level of efficiency with the lowest physical effort. In the past, all transactions were handled with documents with invoices. Documents were filed and stored in archives. With the advent of the Internet, all transactions began to be stored in computer memory. Access to information was quick and easy with the use of the Internet. We can define digitali

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Creative Commons Attribution 4.0 and The Open Definition

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Knowledge; Communication, Civilization, information, technology, education, Preservations,

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Creative Commons Attribution 4.0 and The Open Definition