Volume 11 | Issue 5 |

 Abstract

Credit card fraud is a big issue in the financial services industry. Every year, billions of dollars are lost due to credit card theft. Due to confidentiality concerns, there is a scarcity of research studies analysing real-world credit card data. Machine learning techniques are employed to detect credit card fraud in this article. Standard models are initially employed. Then, hybrid methods based on Ada Boost and majority voting are used. A publicly available credit card data set is used to assess the model's performance. Following that, a real-world credit card data set obtained from a financial institution is analysed. In addition, noise is introduced into the data samples to test the robustness of the algorithms. The experimental results show that the majority voting method provides high accuracy rates in detecting credit card fraud.

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 Keywords

Credit card fraud, Ada Boost, Hybrid Models, Machine Learning Algorithm, Confidentiality, Financial Services.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Underwater Sensor Networks (UWSNs) are capable to explore the many unrevealed natural resources beneath the water, such as lakes, ponds, rivers, seas, and oceans. Futher there are so many challenges to be faced during the design of UWSN system due to the random nature of water waves. But, perhaps the most significant challenge in UWSNs is how to transfer the packets efficiently with minimum energy cost to the surface sink through the water waves. This can be achieved by employing geographic and opportunistic routing schemes to transfer the packets at the surface sink reliably in cooperation with relay nodes. In this paper, a new routing protocol called the Reputation based Geographic and Cooperative Opportunistic Routing Protocol (RGCORP) is developed using NS2, where data packets are routed from source node to the surface sink with the aid of relay nodes. In RGCORP protocol, initially, a relay forwarding set is being determined by the source node on basis of depth data, then weighting scheme is used to choose the best relay node from the relay forwarding set. The weight calculation is performed on normalized energy, packet delivery probability and normalized distance of the forwarding node to the known surface sink. The main purpose of developing the RGCORP protocol is to enhance packet delivery by using reputation values. Further the performance metrics of RGCORP are examined.

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 Keywords

Underwater Sensor Networks, Reputation based Geographic and Cooperative Opportunistic Routing Protocol, relay forwarding set, enhance packet delivery.

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 Abstract

The traffic indicators or signs being present is essential for guaranteeing a safe and efficient flow of traffic. The traffic signs that are visible while we are driving significantly affect our daily lives. They offer fundamental information to clients that approach them on the street. They are consequently gradually being encouraged to alter their driving behaviour and make sure they strictly abide by the current traffic laws without harming other drivers or pedestrians.Therefore, in this project, we suggest a model for classifying traffic signs using deep networks that employs Python as its base language and a number of Python modules to train the CNN model [5].The interclass samples from the submitted dataset will be accurately classified using this model, which consists of multiple CNN layers. Real-time traffic sign identification and sign class identification using this technique.

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 Keywords

Traffic sign, Deep learning, CNN, Classification.

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 Abstract

Shreshth Bhaarat Nirman Mein Shaastrokt Nyaay Sandarsh

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Shreshth Bhaarat Nirman Mein Shaastrokt Nyaay Sandarsh

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Creative Commons Attribution 4.0 and The Open Definition

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The challenges that we're facing in our day-to-day life is parking of the car. When we visit colorful public places similar as office, shopping boardwalk, legion cinema halls etc. it's veritably hard to search the vacuity of parking area. This situation calls for the need for a smart car parking system which is equipped with detectors (Infrared) and microcontrollers (Arduino- uno) to automatically count the cars situated in the lot. In this paper we're going to design and apply a prototype of Smart Car Parking System which is grounded on Internet of effects. This paper proposes a system that helps druggies to automatically find the vacant available space in the parking area through the infrared detectors which are located in each parking space and the stoner can find the vacant parking places through an web application on internet via server. In other words, we can say that it's a new way of communication between the humans and the effects. These all effects are done with the help of rearmost technology grounded on IoT.

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 Keywords

Internet of Things (IOT), Sensors, Microcontroller, WebApplication, Smart Car Parking System.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This study focuses on the impact of Non-Performing Assets on the Profitability of the State bank of India. This can contribute to economic growth and development of the country. The motive of this study is to analyze the Non -performing assets of State Bank of India and its impact on profitability of the bank. The study uses the annual reports of State bank of India for the period of ten years from 2011-12 to 2020-21. The data has been analyzed by using graph and coefficient of correlation. From this analysis it is noted that decrease in NPA is necessary to improve profitability of State Bank of India. While analyzing the impact of NPA level of State bank of India the researcher derived the conclusion that there is a negative relation between NPA and Net Profits of SBI. It simply means that as NPA increase Net profits decrease. It is because of the mismanagement on the side of bank.The purpose of study is to investigate whether there is a significant relationship between non- performing assets and the performance of bank.

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 Keywords

Non-Performing Assets, RBI, State Bank of India, Net Profit,

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 Abstract

"Risk and Resilience Management in Supply Chain" :In Next Normal As Corporate Strategy.

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 Keywords

AI, ML, RM, SCM, SUPPLIAR

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 Abstract

Betel vine leaves diseases caused by regular endangerment to bacteria which causes a huge yield loss globally. In recent years, deep learning has shown great potential in the field of image classification. Machine learning, the latest breakthrough in computer vision, is encouraging for fine-grained disease classification, as the method uses SVM classifier and Gaussian mixture model for image segmentation. Disease detection and classifications are considered as the two hardest works to the recognition of Betel vine disease. Betel vine is an important crop in many tropical countries and its classification is important for various applications such as variety recognition and quality control. However, due to its complex and diverse structures, betel vine classification remains a challenging task. One popular deep learning architecture is ResNet, which has been widely used for image classification tasks and has achieved good performance on various benchmark datasets. Thus, this work uses ResNet architecture to identify and classify the betel vine disease. Dataset of betel vine images and preprocessed the data to prepare it for use with the ResNet101 architecture. ResNet101 architecture is a promising method for betel vine classification. The model performs well in terms of precision and recall demonstrating its effectiveness for betel vine classification.

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 Keywords

ResNet, SVM, Convolutional Neural Network, Gaussian Mixture Model, Histogram Equalization

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Norwegian Wood is a fiction which has been predominantly studied as a love tale of mixed feelings, entangled between Toru, Naoko and Midori. It has a signature narrative technique of Murakami where the story thrives between past and present creating the peculiar Murakami-esque effect. In the present research paper, the researchers are trying to revisit the story of Toru in the light of fate acting as the ultimate authority. One can consider it as deus ex machina. Deus ex machina or God in the form of machine is a classical terminology which has been used by writers for ages. Here, Murakami has used it as a 'red string of fate' in order to reach the climax. Fate has a unique mechanism for each individual. It may not be the same as it is equal to that of his deeds. God has plans for every individual and fate is the string through which He implements his plans. Fate is the greatest leveller that adjudicates the deeds of a man and reciprocates the same treatment by different means which the researchers name it as deus ex machina.

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 Keywords

fate, deus-ex machina, destiny, love, Norwegian Wood, Haruki Murakami.

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 Abstract

In the past few years, there have been several accidents of children falling into abandoned bore wells in India. Abandoned bore wells that have turned into death pits for children. The problem is all over India. Rescue teams spend hours and sometimes days in futile attempts to save these little kids. A lot of money is also spent in these missions. In most cases they are unable to save the kids. Such events have happened umpteen times in the past, and every time either the government or the bureaucracy is blamed. The rescue process to save the child from bore well is a long and complicated process now. The rescue team tries to approach the victim from a parallel well that take about 20-60 hours to dig. This complicated process makes 70% of the rescue operations fail. The design of handling system is made in such a way that the baby/victim never gets hurt and this rescue system is sent through the same well where the victim is felt inside to bring back the victim safe through an autonomous control of drives. Our design constitutes a best Ergonomic Design and performs safest rescue operation.

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 Keywords

Pneumatic cylinder, Gripper, Battery.

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Creative Commons Attribution 4.0 and The Open Definition