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An Experimental Performance Analysis on Robotics Process Automation (RPA) With Open Source OCR Engines: Microsoft Ocr And Google Tesseract OCR

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IOP Conference Series: Materials science and engineering 2021年第1期1059卷

作者： T Malathi D Selvamuthukumaran C S Diwaan Chandar V Niranjan A K Swashthika Assistant Professor Department of Computer Science & Engineering Bannari Amman Institute of Technology Sathyamangalam Erode Tamilnadu - 638401 Assistant Professor Department of Mechanical Engineering Bannari Amman Institute of Technology Sathyamangalam Erode Tamilnadu - 638401 Second Year Department of Information Science & Engineering Bannari Amman Institute of Technology Sathyamangalam Erode Tamilnadu - 638401 Second Year Department of Computer Technology Bannari Amman Institute of Technology Sathyamangalam Erode Tamilnadu - 638401

Robotic Process Automation (RPA) plays an important role in the solution for automating human digital interaction in various software domains like IT, Business Strategy and so on. Optical Character Recognition(OCR) superimposes subtitled characters on an *** we use two Open source OCR engines, Google Tesseract OCR - It literally makes use of the open source Tesseract OCR Engine[1]. Microsoft OCR - This is another open source OCR engine accessible in the Robotics Process Automation tool, UiPath[1]. The technique of optical character recognition (OCR) has been used to transform printed text into editable text. In various applications, OCR is a very useful and common technique. OCR precision can be dependent on algorithms for text preprocessing and segmentation. Often because of different scale, design, orientation, complex picture context, etc., it is difficult to retrieve text from the image. We begin this paper with an introduction to the Optical Character Recognition (OCR) process, in this paper, we propose a research analysis to estimate the accuracy of two open source OCR engines with Robotics Process Automation(RPA). These RPA processes are created using the UiPath tool and our results compare the OCR engines performance during the execution with the workflow and save the results to our local storage or on cloud storage if cloud support enabled and here we used local storage for purpose, and the result analysis and error analysis was evaluated by manual process which also included excel formulas to calculate the accuracy of the extracted string with the original string.

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Performance Evaluation with Multivariable and Multiloop control for a class of square MIMO systems

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IOP Conference Series: Materials science and engineering 2021年第1期1084卷

作者： S Sudhahar C Ganesh Babu D Sharmila Assistant Professor Bannari Amman Institute of Technology Department of Electronics and Instrumentation Engineering Erode Tamilnadu India Professor Professor Bannari Amman Institute of Technology Department of Electronics and Instrumentation Engineering Erode Tamilnadu India Professor Jai Shriram Engineering College Department of Computer Science Engineering Erode Tamilnadu India

Two approaches (centralized and decentralized) for designing a multi-input, multi-output (MIMO) tracing/regulating process are described within article. The vast popular of industrial process control applications are whist focused on multi loop controllers, ignoring the feedback control attainment with advantages of centralized multivariable controllers. Due to their single loop nature, the plant interactions that are merely in use keen on relation in the controller tuning process cannot be suppressed by decentralized controllers. In many situations, therefore it would be beneficial to delimit the detrimental consequences in pairing among inputs and outputs of the closed loop system under certain context. The centralized model predictive controllers (MPC) and decentralized/multi-loop PI controllers are designed. In terms of integral Absolute Error (IAE), Integral Square Error (ISE), and Integral Time-weighted Absolute Error (ITAE), the output of both controllers is then compared. The results of the simulation showed that the MIMO MPC is better than the other suggested control schemes. The projected central controllers minimize interactions superior than the multi loop controllers that have recently been published.

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Detecting Sybil Attack In Wireless Sensor Networks Using Machine Learning Algorithms

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IOP Conference Series: Materials science and engineering 2021年第1期1042卷

作者： Mandala Mounica R. Vijayasaraswathi R. Vasavi M.Tech Student of Software Engineering Dept. of Computer Science & Engineering VNR Vignana Jyothi Institute of Engineering and Technology Hyderabad Telangana India Assistant Professor Dept. of Computer Science & Engineering VNR Vignana Jyothi Institute Of Engineering and Technology Hyderabad Telangana India

In sensitive areas such as battlefields, a Wireless Sensor Network (WSN) is especially in military and civilian applications and it is of utmost importance to develop security in these networks. In various respects, this can improve the quality of life. But to be used for protection reasons in multiple situations such as implementation. There is a high risk of being exposed to multiple viruses and hacking attacks. Unauthorized APs for information protection needs to be detected. Any malicious attacks against these networks, Like Sybil Attack leads to breach of security by enacting as a node that illegitimately declares several false identities at the same time. This misleads valid nodes, and they presume each of those identifiers as actual independent nodes by accident. Thus we proposed a machine learning model to detect Sybil attack in network where rawtraffic data has been collected and is used identify authorized and unauthorized APs in an integrated wired/wireless environment.

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Application of certain Third-order Non-linear Neutral Difference Equations in Robotics engineering

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Journal of Physics: Conference Series 2021年第1期1831卷

作者： S Sindhuja J Daphy Louis Lovenia A P Lavanya D Darling Jemima G Jayabarathy Research Scholar Department of Mathematics Karunya Institute of Technology and Sciences Coimbatore India. Professor Department of Mathematics Karunya Institute of Technology and Sciences Coimbatore India. Assistant Professor Department of Mathematics Sri Krishna college of Engineering and Technology Coimbatore India. Assistant Professor Department of Computer Science and Engineering Sri Ramakrishna Engineering college Coimbatore.

We have obtained some results on oscillatory behavior of third order nonlinear neutral difference equations of the form where β and γ are odd integers with γ ≥ 1. Example is provided to illustrate the results.

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Modeling of an Adaptive Energy Based Route Broadcasting Algorithm (AERBA) Using Route Optimization in MANET

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IOP Conference Series: Materials science and engineering 2021年第1期1084卷

作者： S B Manoojkumaar C Poongodi Assistant Professor Department of Computer Science and Engineering J.K.K.Munirajah College of Technology T.N.Palayam Professor & Head Department of Electronics and Communication Engineering Bannari Amman Institute of Technology Sathyamangalam

Owed to the uncertain and dynamic behaviour of nodes over Mobile Ad-Hoc Networks (MANETs), the reliable route discovery and data delivery is considered as a challenging factor. With absence of centralized infra-structure and global broadcasting nature, nodes over the distributed environment rely over the neighborhood nodes. For reliable communication, the network needs to broadcast the routing direction to chose the appropriate neighborhood partner to make the functionality effectual during packet relying. Therefore, the evaluation process is determined to be a crucial factor. Various methodologies use the trust-based concepts for choosing the route broadcasting region and neighborhood nodes. However, those methods are identified with certain limitations and the evaluation is performed over single node. The inadequate consideration of these factors leads to the wider range of network model that leads to inappropriate broadcasting. This leads to packet loss, higher energy consumption due to re-transmission of packets. In this work, an Adaptive Energy-based Route Broadcasting Algorithm (AERBA) using Route Optimization (RO) is applied along with the route optimization approach to derive the global solutions. This leads to the trust establishment among the network nodes and pretends to fulfill the constraints related to broadcasting and energy consumption. The anticipated model facilitates appropriate evaluation over the potential nodes with multiple hops for balancing the route broadcasting and energy consumption. Simulation is carried out in MATLAB environment and the results demonstrate lesser energy consumption, higher delivery ration when compared with prevailing approaches.

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Design and Analysis of an Efficient Multi-Relational Decision Tree Learning Algorithm

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IOP Conference Series: Materials science and engineering 2021年第1期1099卷

作者： Chhutten Singh Yadav Abhishek Kumar Ankit Kumar Pankaj Dadheech School of Management Studies Graphic Era Hill University Dehradun Uttarakhand India Assistant Professor Department of Computer Science & IT Jain (Deemed to be University) Bangalore India Assistant Professor Department of Computer Science & Engineering Swami Keshvanand Institute of Technology Management & Gramothan Jaipur Rajasthan India

In today's day of modern era when the data handling objectives are getting bigger and bigger with respect to volume, learning and inferring knowledge from complex data becomes the utmost problem. The research in Knowledge Discovery in Databases has been primarily directed to attribute-value learning in which one is described through a fixed set tuple given with their values. Database or dataset is seen in the form of table relation in which every row corresponds to an instance and column represents an attribute respectively. In this paper a New framework is introduced a much more sophisticated and deserving approach i.e., Hybrid Multi-Relational Decision Tree Learning Algorithm which overcomes with Exiting technology drawbacks and other anomalies. Result show that Hybrid Multi- Relational Decision Tree Learning Algorithm provides certain methods which reduces its execution time. Experimental results on different datasets provide a clear indication that Hybrid Multi-Relational Decision Tree Learning Algorithm is comprehensively a better approach.

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Extracting Facial Features in Filter Modified Images using Neural Networks

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IOP Conference Series: Materials science and engineering 2021年第1期1074卷

作者： M Sumithra M Shyamala Devi A Poornima Shatadru Sarkar Harish Patel Preethi Mahankali Boggula Navya Assistant Professor Computer Science & Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai Professor Computer Science & Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai Final Year B.Tech Student Computer Science & Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai

Facial identification plays a vital role in this digital era. Recent advancements in technology provide various filtering effects while capturing the images. Extracting the facial features from the filter modified image becomes challenging. To identify the important facial attribute values from those images, special features extraction techniques needs to be applied. Facial points are the key factors to recognize the face. When these factors are altered, facial detection becomes crucial. Initially apply the image pre-processing techniques to reduce the noise level in the images then perform feature selection. To overcome the curse of dimensionality, Occam's razor approach is followed to limit the selection of attributes. In different stages the features are going to be filtered by replacing the weaker attributes. Later Pearson Correlation, a filter based correlation technique is applied to evaluate the deviated numerical value from the target. The deviated features can be treated with Lasso effect to suppress the poor weighted features. Finally through recursive feature elimination, highest influencing attribute factor can be identified. In this approach some of the facial feature which is used in training the neural network can be discarded based on the deviation rates. In terms of accuracy the proposed system can recognize the dataset with 70% of accuracy with filter effected images.

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Comparative analysis between theoretical and simulatory learning methods by data science methodology approach

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Journal of Physics: Conference Series 2021年第1期1767卷

作者： Patani Rucha Sharadkumar S Shankar Narayan Final year student Department of Computer Science Engineering CMR Institute of Technology Bengaluru- 560 037 India Assistant Professor Department of Mathematics CMR Institute of Technology Bengaluru- 560 037 India

Data science is the most trending interdisciplinary science that integrates the steps of data collection, preprocessing data, transforming data, storing data, data visualization, and hence extracting the insights from the data to serve stakeholder's purposes. Python is commonly used and, along with being a versatile and open-source language, is a favorite tool in Data science studies. The vast libraries are being used to manipulate data and are very simple for even a beginner data scientist to understand. In the present work, we intend to apply the data science methodology to decision making and predictive analysis using the python programming language. We consider the problem of selecting the better mode of study concerning some of the impractical phenomena from physics for the exact understanding of the process. Data collection has been from an educational institute and the comparison has been made between theoretical learning and simulatory learning for selected topics from the vast fields like mechanics, thermodynamics, fluid dynamics, and radioactivity. The steps of data science methodology are germinated to achieve the insights into the data procured and the results are wangled concerning the teaching methodology that could be employed. In the present work, we undertake a comparative study between the theoretical and simulatory modes of teaching by exploring the modes individually through evaluating the responses imparted by a class of high school students. The analysis reported the more inclination of the student's responses towards the simulatory methods when compared to the theoretical method of learning.

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Renewable Energy Sources Efficient Detection in Triangulation for Wireless Sensor Networks

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IOP Conference Series: Materials science and engineering 2021年第1期1055卷

作者： B Barani Sundaram Nunu Srinivas N Kannaiya Raja Manish Kumar Mishra Dhanabal Thirumoorthy NR Reddy Professor & Associate Dean-ICT Department of Computer Science BuleHora University Bulehora Ethiopia Assistant Professor School of Electrical and Computer Engineering Addis Ababa Institute of Technology Addis Ababa University Addis Ababa Ethiopia Professor Department of Computer Science School of Informatics and Electrical Engineering Ambo University IOT Campus Ambo Ethiopia Department of Computer Science University of Gondar Gondar Ethiopia Lecturer BuleHora University Bulehora Ethiopia Assistant Professor Department of Computer Science Mekelle University Mekelle Ethiopia

It is important for wireless sensor networks (WSNs) to determine whether hubs can be restricted, called localizability recognition. This progression is important for confining hubs, achieving minimal organizations of effort and distinguishing critical in field-based applications. Because of their high calculation and communication costs, centralized graph algorithms are meaningless to an asset-restricted WSN, whereas distributed methodologies can skip a large number of hypothetically locatable hubs in a resource-limited WSN. In this document we are proposing a efficient and successful distributed methodology to solve that address of issue. In addition, we demonstrate our calculation accuracy and analyze the reasons why our calculation will discover increasingly localizable hubs while requiring less established area hubs. The paper introduces a new RSSI-based localization approach triangle as well as centroid placement, utilizing triangle as well as centroid approach to minimize RSSI measurement error. Modelling simulations show that this algorithm can significantly increase the precision of the location compared to the trilateration.

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Secured Communication in Vehicular Adhoc Networks (VANETs) using Blockchain

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IOP Conference Series: Materials science and engineering 2021年第1期1022卷

作者： Shivaprasad More Rahul Sonkamble Udaykumar Naik Shraddha Phansalkar Priyanka More Baljit Singh Saini Assistant Professor Department of Computer Science and Engineering Sanjay Ghodawat University Kolhapur Maharashtra India Professor Department of Electronics & Communication KLE Dr. M.S. Sheshgiri College of Engineering & Technology Belagavi Karnataka India Professor Symbiosis Institute of Technology Lavale Pune Research Scholar School of Computer Science and Engineering Lovely Professional University Punjab Professor School of Computer Science and Engineering Lovely Professional University Punjab

In the last decade, the vehicular ad-hoc network (VANET) field is growing drastically. In VANET the communication is the most important aspect through which the data transmission is taking place. Data transmission is maybe related to data in the form of multimedia messages, notifications, announcements, or some warning messages that are involved in VANETs. Data transmission among different vehicles would lead to an exchange of audio-video files in the formed network. These multimedia messages should be transmitted in the fraction of second as this network is built for temporary communication. Vehicles involved in this communication should be trustworthy otherwise other vehicles those who are part of this network would be misguided due to intruder present in the network. To achieve security and integrity in the constituted network, system has proposed the blockchain security environment as a part of this proposed system. Blockchain induces high-end communication in the ad-hoc network. It also enhances the overall security aspect of the constituted network. In this paper, we have proposed blockchain-based security system for vehicular communication that handles this communication securely in a well efficient manner. The performance of the proposed system will be measured based on parameters like end-to-end delay, reliability, and packet delivery ratio.

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