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Secure Cloud Risk Architecture analysis for Mobile Banking system and its performance analysis based on Machine learning approaches

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Journal of Physics: Conference Series 2021年第1期2089卷

作者： P. Rajarajeswari M. Sreevani P. Lalitha Suryakumari Associate Professor Department of Computer science and Engineering Sreenivasa institute of Technology and management studies Chittoor India Associate Professor Department of Computer science and Engineering MGIT Hyderabad India Professor Department of CSE KL University Hyderabad India

With advances in the mobile communications, many service-related tasks can be made quickly and easily. Mobile banking is one such service that has eliminated the need for a consumer to go to a branch to carry out many common transactions. In a country like India, where the last mile reach through brick-and-mortar banking facilities, mobile phones can complement the reach. This paper describes how mobile cloud architecture can be employed for banking and services to customers to enhance their banking experience as well as ensuring information security. This paper focuses on cloud-based risk architecture for banking solutions to address various issues related to mobile banking such as processing speed and storage capacity. Improved random forecast algorithm is used for the evaluation of the system. This proposed system achieves 99% of the system.

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Real-time GB pattern convolution neural network-based brain image classification

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AIP Conference Proceedings 2024年第1期3075卷

作者： Amarendra Reddy Panyala M. Baskar Research Scholar Department of Computer Science and Engineering School of Computing SRM Institute of Science and Technology Kattankulathur Chengalpattu Chennai Tamil Nadu 603 203 India Assistant Professor Department of Information Technology MLR Institute of Technology Hyderabad Telangana 500043 India Associate Professor Department of Computing Technologies School of Computing SRM Institute of Science and Technology Kattankulathur Chengalpattu Chennai Tamil Nadu 603 203 India

Medical image classification has been identified as a critical task in several medical solutions. Brain image classification has been identified as a challenging task that has been approached with different methods. The existing methods use different features like shape, texture, and gray to classify brain images. However, the methods need to improve performance in categorizing the brain image and detecting the presence of tumors. An efficient GB Pattern Convolution Neural Network (GBP-CNN) is presented to handle this issue. The method involves preprocessing the brain image given with Adaptive Feature Distribution Normalizer (AFDN) algorithm. The Grey Canvas Segmentation (GCS) technique was used to segment the normalized image. The feature vector is created by extracting the binary and grayscale patterns from the image that has been segmented. A convolution neural network is trained to recognize the features that were extracted. Two convolution layers in the CNN’s design are used to convolve the image’s features. Additionally, a pooling layer is being incorporated into the network’s design, which reduces the data to a single dimension. The neuron predicts support values for several attributes during the assessment stage. The approach then calculates the Class-Based Fitness value (CBFV) in order to categories the image against various tumour classes. The proposed GBP-CNN algorithm improves the performance of brain image classification with less time complexity.

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Modified Chorological Coded Data Compression Methodology for Wireless Sensor Networks

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Journal of Physics: Conference Series 2021年第1期1770卷

作者： S. Jancy Suji Helen Mercy Paul Selven A. Viji Amutha Mary M.D Antopraveena M.S. Roobini Assistant Professor Department of Computer Science and Engineering Sathyabama Institute of Science and Technology ChennaiIndia Associate Professor Department of Computer Science and Engineering Sathyabama Institute of Science and Technology Chennai India

Wireless Sensor Network (WSN) is a fast evolving current technology which is being employed in various applications. Despite its wide usage, WSNs have a few challenges to overcome to be called as an ideal technology. Some of the challenges are battery life time, memory storage and deployment issues. Batteries are the primary source of power supply to WSN and one of the major challenges is the energy constraint. This paper aims to propose a few techniques to better the energy efficiency of the sensor networks by saving sensor energy using data compression methodology. In this paper, a modified chorological coded data compression methodology is proposed (MCDC). This algorithm deals with assigning the sequence value to the given input information. If the assigned sequence value is a double digit number, it is converted in to single digit number. Double digit numbers and single digit numbers are combined. Separate location tables are generated for all double digit and single digit numbers. This procedure continues until all the sequence values are changed in to single digit number. Then the final single digit is assign with an equivalent Sequence Code (SC). MCDC algorithm is compared with DELTA compression and RUNLENGTH compression and a better compression ratio was achieved when compared with DELTA compression and RUNLENGTH compression algorithms.

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Going with Self-confirmation Endorsement in Differentiated Web Search

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Journal of Physics: Conference Series 2021年第1期1804卷

作者： D. Komali VVS Sasank PN Varalakshmik Department of Computer Science and Engineering KoneruLakshmaiah Education Foundation Vaddeswaram AP India Associate Professor Department of Computer Science and Engineering Tirumala Engineering College

The search of information on the World Wide Web is growing rapidly; web records must have the ability to recap information according to the customer's slant. Recurring pattern web records are manufactured to serve all customers, self-sufficient of the special needs of any individual customer. Personalization of web interest is to finished recuperation for each customer melding his/her favorable position. Every customer has a specific establishment and a specific target when chasing down information on the Web. Thusly the goal of Web interest personalization is to tailor recorded records to a particular customer in light of that customer's leverage and slants. In any case, fruitful tweaked interest requires assembling and gathering customer information, which routinely raises veritable stresses of security infringement for a few customers. Truly, these stresses have been able to be one of the essential hindrances for sending modified look applications, and how to do insurance sparing personalization is a marvelous test. Thusly, fairness necessity strike among demand superiority and safety affirmation. Hence, security confirmation in PWS applications that model customer inclines by way of numerous levelled customer outlines has proposed using a PWS structure named UPS that can flexibly add awake to my requests. Conversely, concerning client demonstrated protection supplies. Nearby Modified Hunt and Confidentiality Defense, the Tradition Exploration convenience will, in similar method, has assumed with the goal that the regulars acquire gigantic records.

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Theft Detection for Secured Access in Android Devices

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Journal of Physics: Conference Series 2021年第1期1717卷

作者： P. Kanimozhi Adityan N. Padmapriya Associate Professor Department of Computer Science and Engineering IFET College of Engineering Villupuram UG Scholar Department of Computer Science and Engineering IFET College of Engineering Villupuram

The purpose of this project is to build up an android application which provides location tracking functionality for android device using SMS. Additionally, we can track the photos of a person who stole our android mobile device this task underpins android OS and makes correspondence with the telephone through SMS and E-mail. Utilizing basic SMS orders, you can follow your android gadget Location tracking: We can track the lost phone using simple SMS commands. Camera can be controlled externally in theft device to capture images. Mobile devices are said to be portable and can be carried by a person from one location to another. There is frequent theft of mobile devices and the existing system consists of monitoring the walking movement of user and patterns are analysed when there is a variation in movement then the mobile device will be locked. The proposed system is used to save another alternate number of the user. Message is sent from alternate number to theft android device and we can retrieve the GPS location.

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A Review of Different Approaches for Detecting Emotion from Text

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IOP Conference Series: Materials science and engineering 2021年第1期1110卷

作者： Ashritha R Murthy K M Anil Kumar Assistant Professor Department of Computer Science and Engineering Sri Jayachamarajendra College of Engineering JSS Science and Technology University Associate Professor Department of Computer Science and Engineering Sri Jayachamarajendra College of Engineering JSS Science and Technology University

Emotion detection and analysis is one of the challenging and emerging issues in the field of natural language processing (NLP). Detecting an individual's emotional state from textual data is an active area of study, along with identifying emotions from facial and audio records. The study of emotions can benefit from many applications in various fields, including neuroscience, data mining, psychology, human-computer interaction, e-learning, information filtering systems and cognitive science. The rich source of text available in the Social media, blogs, customer review, news articles can be a useful resource to explore various insights in text mining, including emotions. The purpose of this study is to provide a survey of existing approaches, models, datasets, lexicons, metrics and their limitations in the detection of emotions from the text useful for researchers in carrying out emotion detection activities.

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A Secure Communication and Location Privacy in WSN Using Grey Wolf Optimization

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Journal of Physics: Conference Series 2021年第1期1717卷

作者： N. Padmapriya S. Subathra Associate Professor Department of Computer Science and Engineering IFET College of Engineering Villupuram UG Scholar Department of Computer Science and Engineering IFET College of Engineering Villupuram

Wireless Computing draws in huge speculations, while simultaneously client necessities are ceaselessly expanded. Additionally development in remote advancements should stay up with aforementioned fields, so as to encourage the mix of imaginative administrations and applications in ordinary correspondence of the system. In the proposed framework we upgrade the security instrument for every sensor node by utilizing GWO(Grey wolf optimization) algorithm, and then the dummy sources are created to deceive the adversary and thus the original source is secured.

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Efficient Energy Utilization Using Ant Lion Optimization in WSN

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Journal of Physics: Conference Series 2021年第1期1717卷

作者： N. Padmapriya S. Vinothini S. Yuvasri Associate Professor Department of Computer Science and Engineering IFET College of Engineering Villupuram UG Scholar Department of Computer Science and Engineering IFET College of Engineering Villupuram

In wireless sensing element networks (WSNs),sensing element nodes or operated by little batteries, therefore they need restricted energy resources which require careful utilization. The planned algorithmic rule is associate degree vitality economical so as to handle trade –off between packet delay and transmission power, and delay economical we have a tendency to develop 3 ANTLION schemes supported power-delay limitations of the heterogeneous WSN. We have a tendency to devise a theoretical framework to figure the common delay and stability region for every planned theme and compare the performance of ANTLION and traditional Clustering. A new hybrid routing protocol is proposed by incorporating the routing concept of adhoc network into the hierarchical clustering routing protocol LEACH of the wireless sensor networks namely Quadrant Based LEACH (ANTLION)..

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Barcode System for Hotel Food Order with Delivery Robot

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Journal of Physics: Conference Series 2021年第1期1717卷

作者： D. Saravanan E. Racheal Anni Perianayaki R. Pavithra R. Parthiban Associate Professor Department of Computer Science and Engineering IFET College of Engineering Villupuram PG Scholar Department of Computer Science and Engineering IFET College of Engineering Villupuram

Technological development has reached perhaps in each field in the present developing world; our test aspirations to give a move up to administrations in the subject of Restaurants and Hotels, with the guide of making and exhibiting a model of a Wireless Waiter Robot. Robots can make the transporter additional condition benevolent and do it more prominent viably sparing time and diminishing work costs. The method utilized right here has an arrange following automated which guarantees the arranged dinner to the respected clients. A menu is made close by to the clients on their mobile phones when they partner with the Bluetooth affiliation open at the diner, the gala is mentioned by strategies for a cell application. The RF mechanical mastery will information the robot to the important work zone of the purchaser using a coordinated system.

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Mitigating post-harvest losses through IoT-based machine learning algorithms in smart farming

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AIP Conference Proceedings 2024年第1期3161卷

作者： R. Rajesh Kanna T. Mohana Priya V. Sivakumar Chandrasekharan Nataraj Jishamol Thomas Assistant Professor Department of Computer Science CHRIST (Deemed to be University) Bangalore India Associate Professor School of Computing Faculty of Computing Engineering and Technology Asia Pacific University of Technology and Innovation Kuala Lumpur Malaysia Senior Lecturer School of Engineering Faculty of Computing Engineering and Technology Asia Pacific University of Technology and Innovation Kuala Lumpur Malaysia Research Scholar Department of Sociology and Social Work CHRIST (Deemed to be University) Bangalore India

This research paper explores the transformative potential of Internet of Things (IoT) technology in mitigating the longstanding issue of post-harvest losses within the agriculture sector. These losses, which encompass both quantitative and qualitative deterioration of food commodities from harvest to consumption, have posed persistent challenges, resulting in economic losses and food wastage. By delving into the current landscape of post-harvest losses and the application of IoT technology, the paper offers valuable insights into how IoT can be harnessed to reduce these losses effectively. It not only highlights the benefits and existing IoT solutions but also addresses the inherent challenges, providing recommendations for their resolution. Moreover, the research introduces a machine learning-based model, specifically Random Forest ML, to identify and prevent losses in tandem with IoT devices, empowering farmers with timely alert messages for informed decision-making, thus fostering a more sustainable and efficient agricultural ecosystem.

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