111
20
11858
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Dublin Core
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Title
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Articles
Article
Faculty Publications -Articles
Dublin Core
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Title
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Automated Risk Management Based Software Security Vulnerabilities Management
Subject
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integrated security management system; machine learning; quantitative risk assessment; Quantitative threat modeling; software security
Description
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An automated risk assessment approach is explored in this work. The focus is to optimize the conventional threat modeling approach to explore software system vulnerabilities. Data produced in the software development processes are better leveraged using Machine Learning approaches. A large amount of industry knowledge around security vulnerabilities can be leveraged to enhance current threat modeling approaches. Work done here is in the ecosystem of software development processes that use Agile methodology. Insurance business domain data are explored as a target for this study. The focus is to enhance the traditional threat modeling approach with a better quantitative approach and reduce the biases introduced by the people who are part of software development processes. This effort will help bridge multiple data sources prevalent across the software development ecosystem. Bringing these various data sources together will assist in understanding patterns associated with security aspects of the software systems. This perspective further helps to understand and devise better controls. Approaches explored so far have considered individual areas of software development and their influence on improving security. There is a need to build an integrated approach for a total security solution for the software systems. A wide variety of machine learning approaches and ensemble approaches will be explored. The insurance business domain is considered for the research here. CWE (Common Weaknesses Enumeration) mapping from industry knowledge are leveraged to validate the security needs from the industry perspective. This combination of industry and company data will help get a holistic picture of the software system's security. Combining the industry and company data helps lay down the path for an integrated security management system in software development. The risk management framework with the quantitative threat modeling process is the work's uniqueness. This work contributes toward making the software systems secure and robust with time. 2013 IEEE.
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Althar R.R.; Samanta D.; Kaur M.; Singh D.; Lee H.-N.
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IEEE Access, Vol-10, pp. 90597-90608.
Publisher
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Institute of Electrical and Electronics Engineers Inc.
Date
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2022-01-01
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<a href="https://doi.org/10.1109/ACCESS.2022.3185069" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ACCESS.2022.3185069</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85133705570&doi=10.1109%2FACCESS.2022.3185069&partnerID=40&md5=34390481d0a1b2825811ff60629c9d14" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85133705570&doi=10.1109%2fACCESS.2022.3185069&partnerID=40&md5=34390481d0a1b2825811ff60629c9d14</a>
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All Open Access; Gold Open Access
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ISSN: 21693536
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Online
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English
Type
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Article
Coverage
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Althar R.R., Christ University, Data Science Department, Karnataka, Bangalore, 560029, India, First American India Private Ltd., Qms, Karnataka, Bangalore, 560038, India; Samanta D., Christ University, Department of Computer Science, Karnataka, Bangalore, 560029, India; Kaur M., First American India Private Ltd., Qms, Karnataka, Bangalore, 560038, India; Singh D., First American India Private Ltd., Qms, Karnataka, Bangalore, 560038, India; Lee H.-N., First American India Private Ltd., Qms, Karnataka, Bangalore, 560038, India
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Title
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Articles
Article
Faculty Publications -Articles
Dublin Core
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Title
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Automated segmentation and classification of nuclei in histopathological images
Subject
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annotated; classifier; computer-assisted diagnosis; deep learning; digital image analysis; histopathological images; machine learning; nuclear; nuclei; segmentation; whole slide images
Description
An account of the resource
Various kinds of cancer are detected and diagnosed using histopathological analysis. Recent advances in whole slide scanner technology and the shift towards digitisation of whole slides have inspired the application of computational methods on histological data. Digital analysis of histopathological images has the potential to tackle issues accompanying conventional histological techniques, like the lack of objectivity and high variability. In this paper, we present a framework for the automated segmentation of nuclei from human histopathological whole slide images, and their classification using morphological and colour characteristics of the nuclei. The segmentation stage consists of two methods, thresholding and the watershed transform. The features of the segmented regions are recorded for the classification stage. Experimental results show that the knowledge from the selected features is capable of classifying a segmented object as a candidate nucleus and filtering out the incorrectly identified segments. Copyright 2022 Inderscience Enterprises Ltd.
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Vincent S.; Chandra J.
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International Journal of Biomedical Engineering and Technology, Vol-38, No. 3, pp. 249-266.
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Inderscience Publishers
Date
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2022-01-01
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<a href="https://doi.org/10.1504/IJBET.2022.121739" target="_blank" rel="noreferrer noopener">https://doi.org/10.1504/IJBET.2022.121739</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85128739597&doi=10.1504%2FIJBET.2022.121739&partnerID=40&md5=b34d7968c2cf4da98adb1dd3f93f35ea" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85128739597&doi=10.1504%2fIJBET.2022.121739&partnerID=40&md5=b34d7968c2cf4da98adb1dd3f93f35ea</a>
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Restricted Access
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ISSN: 17526418
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Online
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English
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Article
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Vincent S., Department of Computer Science, CHRIST (Deemed to be University), Bangalore, India; Chandra J., Department of Computer Science, CHRIST (Deemed to be University), Bangalore, India
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Title
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Conference Papers
Conference Paper
Faculty Publications- Conference Papers
Dublin Core
The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/.
Title
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Automated Single Responsibility Principle Enforcement: A Step Toward Reusable and Maintainable Code
Subject
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Code smells; Cyclometric complexity; Halstead volume; Interface analysis; Single responsibility principle
Description
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In this study, we delve into the sphere of automated code scrutiny, specifically concentrating on compliance with the single responsibility principle (SRP), a key principle in software architecture. The SRP proposes that a class should have a singular reason for modification, thereby enhancing code cohesion and facilitating its maintenance and reusability. The study presents a pioneering system that utilizes a holistic strategy to ascertain SRP compliance within code. This system rigorously inspects code interfaces, the interaction points among various software components. Through this process, we extract critical insights into the codes maintainability and reusability. An optimally designed interface can significantly improve code management and foster its reuse, leading to superior software design efficiency. Beyond interface inspection, our system also explores complexity metrics such as cyclomatic complexity and hassel volume. Cyclomatic complexity offers a numerical indicator of the count of linearly independent paths traversing a programs source code, serving as a measure of code complexity. Hassel volume is an additional metric that can quantify code complexity. Moreover, our system employs code smell detection methodologies to identify instances of high interdependence between classes, often a sign of SRP breaches. High interdependence, or tight coupling, complicates code modification and maintenance. The system integrates the conclusions from these varied analyses to determine SRP compliance. The outcomes of this investigation highlight a hopeful trajectory toward automated SRP detection. This could provide developers with tools that proactively foster the development of well-organized and maintainable code, thereby enhancing software design quality. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
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Jacob B.A.; Manohar M.; Roy G.
Source
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Lecture Notes in Networks and Systems, Vol-1112 LNNS, pp. 343-353.
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Springer Science and Business Media Deutschland GmbH
Date
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2024-01-01
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<a href="https://doi.org/10.1007/978-981-97-6684-0_28" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-97-6684-0_28</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85215655517&doi=10.1007%2F978-981-97-6684-0_28&partnerID=40&md5=7ac1173f69be0421e06c009b900c3c26" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85215655517&doi=10.1007%2f978-981-97-6684-0_28&partnerID=40&md5=7ac1173f69be0421e06c009b900c3c26</a>
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Restricted Access
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ISSN: 23673370; ISBN: 978-981976683-3
Format
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Online
Language
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English
Type
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Conference paper
Coverage
The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant
Jacob B.A., Department of Computer Science and Engineering, School of Engineering and Technology, CHRIST (Deemed to Be University), Karnataka, Bangalore, 560074, India; Manohar M., Department of Computer Science and Engineering, School of Engineering and Technology, CHRIST (Deemed to Be University), Karnataka, Bangalore, 560074, India; Roy G., Department of Computer Science and Engineering, School of Engineering and Technology, CHRIST (Deemed to Be University), Karnataka, Bangalore, 560074, India
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Dublin Core
The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/.
Title
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Articles
Article
Faculty Publications -Articles
Dublin Core
The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/.
Title
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Automated testbed and real-time port analysis for reconfigurable inputoutput boards
Subject
The topic of the resource
analog read; analog write; Automation; digital read; digital write; RIO boards
Description
An account of the resource
In the computational world, automation plays a vital role in every aspect. The idea of developing and testing Reconfigurable InputOutput (RIO) Boards automatically without manual interaction is a challenging task. Initially, testing was done manually which takes a lot of time and also requires human interaction. With the proposed idea one can reduce human interaction and testing time with smart automated design setup. This testing includes testing of various functionalities of the RIO boards. This can be done by testing the features of each port with its pin configuration. To be more precise, in this process an automated testbed is designed and algorithms are proposed to verify the features of each pin such as Digital Read, Digital Write, Analog Read and Analog Write of the RIO boards along with the motor pins. Thus, the proposed method makes the setup simple, without any complications by giving the instructions to perform the testing process for each board without human interaction. Results show that the proposed method can reduce time consumption 95%, human interaction by 95% and increase testing accuracy to 87%. 2020 Informa UK Limited, trading as Taylor & Francis Group.
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P K.; O S G.
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International Journal of Computer Integrated Manufacturing, Vol-33, No. 45971, pp. 1156-1166.
Publisher
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Taylor and Francis Ltd.
Date
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2020-01-01
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<a href="https://doi.org/10.1080/0951192X.2020.1803141" target="_blank" rel="noreferrer noopener">https://doi.org/10.1080/0951192X.2020.1803141</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85089288017&doi=10.1080%2F0951192X.2020.1803141&partnerID=40&md5=c6b842821064ea231f4c0daaa1519c12" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85089288017&doi=10.1080%2f0951192X.2020.1803141&partnerID=40&md5=c6b842821064ea231f4c0daaa1519c12</a>
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A related resource
ISSN: 0951192X; CODEN: ICIME
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Online
Language
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English
Type
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Article
Coverage
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P K., Department of Computer Science and Engineering, Christ (Deemed to Be University), Bangalore, India; O S G., Department of Computer Science and Engineering, Christ (Deemed to Be University), Bangalore, India
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The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/.
Title
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Conference Papers
Conference Paper
Faculty Publications- Conference Papers
Dublin Core
The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/.
Title
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Automated Verification of Open/Closed Principle: A Code Analysis Approach
Subject
The topic of the resource
Open Closed Principle; SOLID Principles
Description
An account of the resource
The SOLID principles are foundational to software engineering, focusing on the maintainability, scalability, and extensibility of software systems. The Open/Closed Principle (OCP), a pivotal element among these principles, underscores the need to design software modules that are open for extension yet closed for modification. This research explores automated verification techniques for OCP, addressing the validation of software modules through extensibility and adaptability assessments. The principal objectives involve the development of a code analysis approach and a methodology capable of automating the verification of adherence to OCP in developed codes, providing actionable insights to software developers. The system focuses on specific aspects of OCP, including inheritance, abstraction, and polymorphism, and aims to provide clear indications of where violations occur within a codebase. The implementation uses the Abstract Syntax Tree (AST) analysis to examine class definitions. The automated analysis of Python code using the defined rules offers a clear understanding of OCP adherence. Results are presented in Pandas DataFrames, indicating potential violations and providing developers with actionable insights to enhance code quality and maintainability. Overall, the automated code verification system aims to enhance code quality and adherence to fundamental design principles, paving the way for advancements in automated code analysis and software engineering practices. 2024 IEEE.
Creator
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Roy G.; Manohar M.; Jacob B.A.
Source
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2024 5th International Conference for Emerging Technology, INCET 2024
Publisher
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Institute of Electrical and Electronics Engineers Inc.
Date
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2024-01-01
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<a href="https://doi.org/10.1109/INCET61516.2024.10593301" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/INCET61516.2024.10593301</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200990985&doi=10.1109%2FINCET61516.2024.10593301&partnerID=40&md5=da21e9096b41925629c4ddc4a7b3016c" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200990985&doi=10.1109%2fINCET61516.2024.10593301&partnerID=40&md5=da21e9096b41925629c4ddc4a7b3016c</a>
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ISBN: 979-835036115-5
Format
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Online
Language
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English
Type
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Conference paper
Coverage
The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant
Roy G., Department of Computer Science and Engineering, School of Engineering and Technology, CHRIST (Deemed to be University), Bangalore, India; Manohar M., Department of Computer Science and Engineering, School of Engineering and Technology, CHRIST (Deemed to be University), Bangalore, India; Jacob B.A., Department of Computer Science and Engineering, School of Engineering and Technology, CHRIST (Deemed to be University), Bangalore, India
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ae8597b1fb62da5294ca14f6fc0ece85
Dublin Core
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Title
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Patents
Subject
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Patent
Description
An account of the resource
Patent
Patent
Patents
Dublin Core
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Title
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Automatic blood group identification device /
Subject
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Bio-Chemistry
Description
An account of the resource
Patent Number: 202141026963, Applicant: Ajit Danti.
Our invention Automatic Blood Group Identification Device is an event of a coffee price image process system that enables the determination of human blood sorts. to see the blood sorts, it had been used the plate check that accommodates the mixture antigens specifics of blood sorts determination and also the sample blood of the donor.
Creator
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Danti, Ajith.
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<a href="https://drive.google.com/file/d/1XddX-9KSD6tY9Atb5HHGieOShF9fMFjw/view" target="_blank" title="Automatic blood group identification device /" rel="noreferrer noopener">https://drive.google.com/file/d/1XddX-9KSD6tY9Atb5HHGieOShF9fMFjw/view</a>
Publisher
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Intellectual Property India
Date
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2021-03-29
Language
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English
Type
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Patent
-
Dublin Core
The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/.
Title
A name given to the resource
Conference Papers
Conference Paper
Faculty Publications- Conference Papers
Dublin Core
The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/.
Title
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Automatic Classification of Normal and Affected Vegetables Based on Back Propagation Neural Network and Machine Vision
Subject
The topic of the resource
Classifier; Color features; Texture features; Vegetable disease
Description
An account of the resource
This article presents a neural network and machine vision-based approach to classify the vegetables as normal or affected. The farmers will have great difficulty if there is a change from one disease control to another. The examination through an open eye to classify the diseases by name is more expensive. The texture and color features are used to identify and classify different vegetables into normal or affected using a neural network and machine vision. The mixture of both the features is proved to be more effective. The results of experiments show that the proposed methodology extensively supports the accuracy in automatic detection of affected and normal vegetables. The applications in packing and grading of vegetables are the outcome of this research article. 2019, Springer Nature Singapore Pte Ltd.
Creator
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Madgi M.; Danti A.
Source
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Communications in Computer and Information Science, Vol-1037, pp. 529-537.
Publisher
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Springer Verlag
Date
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2019-01-01
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<a href="https://doi.org/10.1007/978-981-13-9187-3_47" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-13-9187-3_47</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85070213879&doi=10.1007%2F978-981-13-9187-3_47&partnerID=40&md5=4c49a9444db620b141b87208955a7355" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85070213879&doi=10.1007%2f978-981-13-9187-3_47&partnerID=40&md5=4c49a9444db620b141b87208955a7355</a>
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Restricted Access
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ISSN: 18650929; ISBN: 978-981139186-6
Format
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Online
Language
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English
Type
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Conference paper
Coverage
The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant
Madgi M., K. L. E. Institute of Technology, Hubballi, 580030, India; Danti A., Christ (Deemed to be University), Bengaluru, 560074, India
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https://archives.christuniversity.in/files/original/cd74d5a8c9d50a7ffe8f234ebd557443.png
ae8597b1fb62da5294ca14f6fc0ece85
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Title
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Patents
Subject
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Patent
Description
An account of the resource
Patent
Patent
Patents
Dublin Core
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Title
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Automatic detection of violence activity-A tool for women's safety /
Subject
The topic of the resource
Computer Science
Description
An account of the resource
Patent Number: 202041006858, Applicant: Debanjan Konar.
Human activity detection has gained popularity owing to wide range of applications from! game development to surveillance. Recent development of Deep Pose (Human pose detection using deep neural network) allows extrapolating the skeletal structures and joint sequences of the actors in a video sequence. This work aims to promote the violence-activities of human-being using Deep Pose on multi-person interaction in real-time.
Creator
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Samanta, Debabrata.
Source
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<a href="https://drive.google.com/file/d/17aVFsluz0AUCNBsKIDKIGhlv0Iw5T4K4/view" target="_blank" title="Automatic detection of violence activity-A tool for women's safety /" rel="noreferrer noopener">https://drive.google.com/file/d/17aVFsluz0AUCNBsKIDKIGhlv0Iw5T4K4/view</a>
Publisher
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Intellectual Property India
Date
A point or period of time associated with an event in the lifecycle of the resource
2020-03-17
Language
A language of the resource
English
Type
The nature or genre of the resource
Patent
-
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ae8597b1fb62da5294ca14f6fc0ece85
Dublin Core
The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/.
Title
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Patents
Subject
The topic of the resource
Patent
Description
An account of the resource
Patent
Patent
Patents
Dublin Core
The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/.
Title
A name given to the resource
Automatic detection of violence activity-A tool for women's safety /
Subject
The topic of the resource
Computer Science
Description
An account of the resource
Patent Number: 202041006858, Applicant: Debanjan Konar.
Human activity detection has gained popularity owing to wide range of applications from game development to surveillance. Recent development of Deep Pose (Human pose detection using deep neural network.
Creator
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Bhattacharyya, Siddhartha.
Source
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<a href="https://drive.google.com/file/d/17aVFsluz0AUCNBsKIDKIGhlv0Iw5T4K4/view" target="_blank" title="Automatic detection of violence activity-A tool for women's safety /" rel="noreferrer noopener">https://drive.google.com/file/d/17aVFsluz0AUCNBsKIDKIGhlv0Iw5T4K4/view</a>
Publisher
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Intellectual Property India
Date
A point or period of time associated with an event in the lifecycle of the resource
2020-03-21
Language
A language of the resource
English
Type
The nature or genre of the resource
Patent
-
Dublin Core
The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/.
Title
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Articles
Article
Faculty Publications -Articles
Dublin Core
The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/.
Title
A name given to the resource
Automatic Diagnosis of Autism Spectrum Disorder Detection Using a Hybrid Feature Selection Model with Graph Convolution Network
Subject
The topic of the resource
ABFO; Autism spectrum disorder; Graph convolutional networks; mRMR; SVM-RFE
Description
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A neurodevelopmental disorder is called an autism spectrum disorder (ASD) that influences a persons assertion, interaction, and learning abilities. The consequences and severity of symptoms of ASD will vary from person to person; the disorder is mainly diagnosed in children aged 15years and older, and its symptoms may include unusual behaviors, interests, and social challenges. If it is not resolved at this stage, it will become severe in the coming days. So, in this manuscript, we propose a way to automatically tell if someone has ASD that works well by using a combination of feature selection and deep learning. Four phases comprise the proposed model: preprocessing, feature extraction, feature selection, and prediction. At first, the collected images are given to the preprocessing stage to remove the noise. Then, for each image, three types of features are extracted: the shape feature, texture feature, and histogram feature. Then, optimal features are selected to minimize computational complexity and time consumption using a new technique based on a combination of adaptive bacterial foraging optimization (ABFO), support vector machines-recursive feature elimination (SVM-RFE), minimum redundancy and maximum relevance (mRMR). Then, the graph convolutional network (GCN) classifier uses the selected features to identify an image as normal or autistic. According to the research observations, our models accuracy is enhanced to 97.512%. 2023, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.
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Lamani M.R.; Benadit P.J.
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SN Computer Science, Vol-5, No. 1
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Springer
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2024-01-01
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<a href="https://doi.org/10.1007/s42979-023-02439-z" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/s42979-023-02439-z</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85180210216&doi=10.1007%2Fs42979-023-02439-z&partnerID=40&md5=b01c9cae8e1de2938bc2945e56cff620" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85180210216&doi=10.1007%2fs42979-023-02439-z&partnerID=40&md5=b01c9cae8e1de2938bc2945e56cff620</a>
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ISSN: 2662995X
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Online
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English
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Article
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Lamani M.R., CHRIST (Deemed to be University), Computer Science and Engineering, Karnataka, Bangalore, 560074, India; Benadit P.J., CHRIST (Deemed to be University), Computer Science and Engineering, Karnataka, Bangalore, 560074, India
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https://archives.christuniversity.in/files/original/2bb3b0c18f61f60fa38185d1fbf43fb9.pdf
eacc2bd6f774d3803762afcba5216bc1
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MPHIL
Mphil
Mphil Thesis
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Title
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Automatic emotional stress recognition in children with stuttering
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M Yashaswi Alva
Date
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2015
Source
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Computer Science
-
https://archives.christuniversity.in/files/original/992cdc34bf14a81c3dfb29e8dbc05a52.jpg
0b6dfeeadbd8dbf97f5aef738454f6b9
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Title
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Patents
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Patent
Description
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Patent
Patent
Patents
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Title
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Automatic fertilizer dispenser robot /
Subject
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Mechanical Design
Description
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Patent Number: 354319-001, Applicant: Ravikumar R.
Creator
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K, Kiran.
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<a href="https://drive.google.com/file/d/1sU5l1D5wBRVIfnnc6Z3fJJLPHQfSoW_E/view" target="_blank" title="Automatic fertilizer dispenser robot /" rel="noreferrer noopener">https://drive.google.com/file/d/1sU5l1D5wBRVIfnnc6Z3fJJLPHQfSoW_E/view</a>
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Intellectual Property India
Date
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2022-05-19
Language
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English
Type
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Patent
-
https://archives.christuniversity.in/files/original/d17465b03b70b53ac6e51ea3a1f7354b.jpg
0b6dfeeadbd8dbf97f5aef738454f6b9
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Title
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Patents
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Patent
Description
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Patent
Patent
Patents
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Title
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Automatic fertilizer dispenser robot /
Subject
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Mechanical Design
Description
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Patent Number: 354319-001, Applicant: Ravikumar R.
Creator
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Y B, Ravi Kumar.
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<a href="https://drive.google.com/file/d/1sU5l1D5wBRVIfnnc6Z3fJJLPHQfSoW_E/view" target="_blank" title="Automatic fertilizer dispenser robot /" rel="noreferrer noopener">https://drive.google.com/file/d/1sU5l1D5wBRVIfnnc6Z3fJJLPHQfSoW_E/view</a>
Publisher
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Intellectual Property India
Date
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2022-05-19
Language
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English
Type
The nature or genre of the resource
Patent
-
https://archives.christuniversity.in/files/original/98bc7171edd3197f857131f07247116a.jpg
0b6dfeeadbd8dbf97f5aef738454f6b9
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The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/.
Title
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Patents
Subject
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Patent
Description
An account of the resource
Patent
Patent
Patents
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The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/.
Title
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Automatic fertilizer dispenser robot /
Subject
The topic of the resource
Mechanical Design
Description
An account of the resource
Patent Number: 354319-001, Applicant: Ravikumar R.
Creator
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Sasidhar, Jangam.
Source
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<a href="https://drive.google.com/file/d/1sU5l1D5wBRVIfnnc6Z3fJJLPHQfSoW_E/view" target="_blank" title="Automatic fertilizer dispenser robot /" rel="noreferrer noopener">https://drive.google.com/file/d/1sU5l1D5wBRVIfnnc6Z3fJJLPHQfSoW_E/view</a>
Publisher
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Intellectual Property India
Date
A point or period of time associated with an event in the lifecycle of the resource
2022-05-19
Language
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English
Type
The nature or genre of the resource
Patent
-
https://archives.christuniversity.in/files/original/30f6d8f9f7ea297e468861fc7fe05c9c.jpg
0b6dfeeadbd8dbf97f5aef738454f6b9
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Title
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Patents
Subject
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Patent
Description
An account of the resource
Patent
Patent
Patents
Dublin Core
The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/.
Title
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Automatic fertilizer dispenser robot /
Subject
The topic of the resource
Mechanical Design
Description
An account of the resource
Patent Number: 354319-001, Applicant: Ravikumar R.
Creator
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K, Ramesha.
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<a href="https://drive.google.com/file/d/1sU5l1D5wBRVIfnnc6Z3fJJLPHQfSoW_E/view" target="_blank" title="Automatic fertilizer dispenser robot /" rel="noreferrer noopener">https://drive.google.com/file/d/1sU5l1D5wBRVIfnnc6Z3fJJLPHQfSoW_E/view</a>
Publisher
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Intellectual Property India
Date
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2022-05-19
Language
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English
Type
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Patent
-
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Title
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Conference Papers
Conference Paper
Faculty Publications- Conference Papers
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Title
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Automatic Generation Control of Multi-area Multi-source Deregulated Power System Using Moth Flame Optimization Algorithm
Subject
The topic of the resource
Automatic generation control (AGC); Disco participation matrix (DPM); Generation rate constraint (GRC); Moth flame optimization (MFO); Proportional-integral-derivative controller (PID)
Description
An account of the resource
In this paper, a novel nature motivated optimization technique known as moth flame optimization (MFO) technique is proposed for a multi-area interrelated power system with a deregulated state with multi-sources of generation. A three-area interrelated system with multi-sources in which the first area consists of the thermal and solar thermal unit; the second area consists of hydro and thermal units. The third area consists of gas and thermal units with AC/DC link. System performances with various power system transactions under deregulation are studied. The dynamic system executions are compared with diverse techniques like particle swarm optimization (PSO) and differential evolution (DE) technique under poolco transaction with/without AC/DC link. It is found that the MFO tuned proportional-integral-derivative (PID) controller superior to other methods considered. Further, the system is also studied with the addition of physical constraints. The present analysis reveals that the proposed technique appears to be a potential optimization algorithm for AGC study under a deregulation environment. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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Acharyulu B.V.S.; Gorripotu T.S.; Azar A.T.; Mohanty B.; Pilla R.; Kumar S.; Serrano F.E.; Kamal N.A.
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Lecture Notes in Networks and Systems, Vol-204, pp. 717-729.
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Springer Science and Business Media Deutschland GmbH
Date
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2021-01-01
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<a href="https://doi.org/10.1007/978-981-16-1089-9_56" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-16-1089-9_56</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85111960526&doi=10.1007%2F978-981-16-1089-9_56&partnerID=40&md5=da7c244f94caa295d3a171a889ca22dc" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85111960526&doi=10.1007%2f978-981-16-1089-9_56&partnerID=40&md5=da7c244f94caa295d3a171a889ca22dc</a>
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ISSN: 23673370; ISBN: 978-981161088-2
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Online
Language
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English
Type
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Conference paper
Coverage
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Acharyulu B.V.S., Department of Electrical and Electronics Engineering, Lendi Institute of Technology and Management, Srikakulam, Andhra Pradesh, 532402, India; Gorripotu T.S., Department of Electrical and Electronics Engineering, Sri Sivani College of Engineering, Srikakulam, Andhra Pradesh, 532402, India; Azar A.T., College of Computer and Information Sciences, Prince Sultan University, Riyadh, Saudi Arabia, Faculty of Computers and Artificial Intelligence, Benha University, Banha, Egypt; Mohanty B., Department of Electrical Engineering, Veer Surendra Sai University of Technology, Burla, Odisha, 768018, India; Pilla R., Department of Electrical and Electronics Engineering, GMR Institute of Technology, Rajam, Srikakulam, Andhra Pradesh, 532127, India; Kumar S., CHRIST (Deemed to be University), Bangalore, Karnataka, 560074, India; Serrano F.E., Universidad Tecnologica Centroamericana (UNITEC), Tegucigalpa, Honduras; Kamal N.A., Faculty of Engineering, Cairo University, Giza, Egypt
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Title
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Conference Papers
Conference Paper
Faculty Publications- Conference Papers
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Title
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Automatic Measurement and Differentiation of Traffic Volume Count
Subject
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bbox; blob analysis; blob area; Traffic volume
Description
An account of the resource
Traffic volume in India is growing drastically over the past few decades. This leads to an increased need of constructing more highways and underpasses. In order to have the definite knowledge of traffic volume, and to design the width and thickness of the pavements, periodical conduction of traffic census is necessary. At present, the evaluation of traffic volume is conducted manually. This system is tiresome and lacks accuracy. The data obtained from the traffic census decides the sanction of new highways, underpasses, or flyovers which involves huge investments. Hence, the accuracy of this data is very critical. In this paper, we propose an automatic tool that helps to measure the traffic volume and differentiate the vehicles using video processing tools in MATLAB. The proposed algorithm consists of the following steps: i Foreground Detection ii Blob Detection iii Blob Analysis iv Vehicle differentiation Counting. 2018 IEEE.
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Catheren K.; Joseph S.; Joshy S.; Sushanth G.
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Proceedings of the 2018 IEEE International Conference on Communication and Signal Processing, ICCSP 2018, pp. 443-447.
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Institute of Electrical and Electronics Engineers Inc.
Date
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2018-01-01
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<a href="https://doi.org/10.1109/ICCSP.2018.8524149" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICCSP.2018.8524149</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85057720379&doi=10.1109%2FICCSP.2018.8524149&partnerID=40&md5=25516600b09c878ae58a45a1b6d555b3" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85057720379&doi=10.1109%2fICCSP.2018.8524149&partnerID=40&md5=25516600b09c878ae58a45a1b6d555b3</a>
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ISBN: 978-153863521-6
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Online
Language
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English
Type
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Conference paper
Coverage
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Catheren K., Department of Electronics and Communication Engineering, Christ University, Bangalore, India; Joseph S., Department of Electronics and Communication Engineering, Christ University, Bangalore, India; Joshy S., Department of Electronics and Communication Engineering, Christ University, Bangalore, India; Sushanth G., Electronics and Communication Engineering Department, Christ University, Bangalore, India
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Title
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Conference Papers
Conference Paper
Faculty Publications- Conference Papers
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Title
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Automatic Resume Parsing using Greywolf Algorithm Integrated with Strategically Constructed Semantic Skill Ontologies
Subject
The topic of the resource
Greywolf Algorithm; Natural Language Processing; Ontology; Resume matching
Description
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The quest for finding the right candidate for their post has made the recruiters employ several methods since the beginning of corporate job recruitment. Apart from the skills and the quality of interview, a thing that matters the most and forms the basis of selection is the candidate's resume. Recruiters and companies have a tough time dealing with the several thousands resumes of the candidates which apply, as manually scanning them and finding the right selection can be tough most of the time. In this paper, Natural Language Processing(NLP) methods have been integrated with ontologies to improve the pace and quality of the recruitment process by proposing an automatic resume parser model. The resume of a candidate, along with his LinkedIn and GitHub profiles are weighted and using the Greywolf algorithm, the global maxima of the most deserving and qualified candidate are found and are recommended with a high accuracy of 96.13%. 2020 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0)
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Ayush Kumar A.; Deepak G.; Sheeba Priyadarshini J.
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CEUR Workshop Proceedings, Vol-3335, pp. 77-86.
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CEUR-WS
Date
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2022-01-01
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<a href="" target="_blank" rel="noreferrer noopener"></a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85147648318&partnerID=40&md5=fd1ff960311b12c736695b2dabdd3813" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85147648318&partnerID=40&md5=fd1ff960311b12c736695b2dabdd3813</a>
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ISSN: 16130073
Format
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Online
Language
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English
Type
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Conference paper
Coverage
The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant
Ayush Kumar A., National Institute of Technology, Tiruchirappalli, India; Deepak G., Manipal Institute of Technology Bengaluru, Manipal Academy of Higher Education, Manipal, India; Sheeba Priyadarshini J., CHRIST (Deemed to be University), Bangalore, India
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Articles
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Faculty Publications -Articles
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Title
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Automatic Skin Lesion SegmentationA Novel Approach of Lesion Filling through Pixel Path
Subject
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directional seed; lesion filling; lesion pixel path; melanoma; most probable seed region
Description
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Abstract: Lesion segmentation is a vital step in a melanoma recognition system. Many algorithms were developed for the efficient skin lesion segmentation. Most of them fails to realize a perfect segmentation. This paper proposes a novel, fully automatic system, for the lesion segmentation in dermatograms. The proposed approach executes in two steps. Selection of root seed is the first step. All the lesion pixels in the dermatogram are identified during the second step. Traversal through a predefined lesion pixel path ensures the reachability of all lesion pixels irrespective of the possible lesion discontinuity. The proposed algorithm is tested with two publically available dataset, PH2 and images of ISBI2016 challenge. Out of the six evaluation parameters, the proposed method shows the best values for specificity, accuracy, Hammuode distance and XOR. This confirms the merit of the proposal with respect to existing popular methods. 2020, Pleiades Publishing, Ltd.
Creator
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Nikesh P.; Raju G.
Source
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Pattern Recognition and Image Analysis, Vol-30, No. 4, pp. 815-826.
Publisher
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Pleiades journals
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2020-01-01
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<a href="https://doi.org/10.1134/S1054661820040215" target="_blank" rel="noreferrer noopener">https://doi.org/10.1134/S1054661820040215</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85099414961&doi=10.1134%2FS1054661820040215&partnerID=40&md5=81083b67874ade9ebbdaa26db8fbbd47" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85099414961&doi=10.1134%2fS1054661820040215&partnerID=40&md5=81083b67874ade9ebbdaa26db8fbbd47</a>
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ISSN: 10546618
Format
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Online
Language
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English
Type
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Article
Coverage
The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant
Nikesh P., School of Computer Sciences, Mahathma Gandhi University, Kottayam, 686560, Kerala, India; Raju G., Department of Data Science, Christ (Deemed to be University), Lavasa Campus, Pune, 412112, Maharashtra, India
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https://archives.christuniversity.in/files/original/57a109ff0b2864669a8467cdd9d6d479.png
ae8597b1fb62da5294ca14f6fc0ece85
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Title
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Patents
Subject
The topic of the resource
Patent
Description
An account of the resource
Patent
Patent
Patents
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Title
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Automatic smart attendance management system based on face recognition using deep learning /
Subject
The topic of the resource
Computer Science
Description
An account of the resource
Patent Number: 202141025155, Applicant: J Omana.
In this digital era, face recognition system plays a vital role in almost every sector. Face recognition is one of the mostly used biometrics. It can used for security, authentication, identification, and has got many more advantages. Furthermore, face recognition system can also be used for attendance marking in schools, colleges, offices, etc. The conventional method of calling name of each student is time consuming and there is always a chance of proxy attendance.
Creator
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R, Arokia Paul Rajan.
Source
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<a href="https://drive.google.com/file/d/1UK0fus2ffCf0rRLQKXb5_FLKpKxQPxYD/view" target="_blank" title="Automatic smart attendance management system based on face recognition using deep learning /" rel="noreferrer noopener">https://drive.google.com/file/d/1UK0fus2ffCf0rRLQKXb5_FLKpKxQPxYD/view</a>
Publisher
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Intellectual Property India
Date
A point or period of time associated with an event in the lifecycle of the resource
2021-03-29
Language
A language of the resource
English
Type
The nature or genre of the resource
Patent