146
20
16481
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Title
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Conference Papers
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Faculty Publications- Conference Papers
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Automatic Generation Control of Multi-area Multi-source Deregulated Power System Using Moth Flame Optimization Algorithm
Subject
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Automatic generation control (AGC); Disco participation matrix (DPM); Generation rate constraint (GRC); Moth flame optimization (MFO); Proportional-integral-derivative controller (PID)
Description
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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
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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
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English
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Conference paper
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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
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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
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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
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English
Type
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Conference paper
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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
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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
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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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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.
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Nikesh P.; Raju G.
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Pattern Recognition and Image Analysis, Vol-30, No. 4, pp. 815-826.
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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
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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
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Patent
Description
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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
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Computer Science
Description
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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.
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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
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2021-03-29
Language
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English
Type
The nature or genre of the resource
Patent
-
https://archives.christuniversity.in/files/original/16c50d17a6ed7154b666929f8573716d.png
ae8597b1fb62da5294ca14f6fc0ece85
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Title
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Patents
Subject
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Patent
Description
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Patent
Patent
Patents
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Title
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Automatic vehicle license plate recognizer for kannada script using tensorflow based canvolutional neural network model /
Subject
The topic of the resource
Computer Science
Description
An account of the resource
Patent Number: 201941054190, Applicant: Dr. Arish P.
Automatic Vehicle License Plate Recognizer (AVLPR) is used to read license number of a vehicle by itself without direct human control. It is used to track citizens, movements and misidentiflcation of vehicles. Traditional ALVPR is mounted on police cars or on object like road signs and bridges. The challenging tasks in recognizing the license plate numbers in Kannada script are high contrast foreground or background colour, shape of the license plate, location of the plate in the bottom and middle of the vehicle.
Creator
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N, Arul Kumar.
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<a href="https://drive.google.com/file/d/1cQhaRk9Wq4GL1oVheHvuZf6_DTkiYkdX/view" target="_blank" title="Automatic vehicle license plate recognizer for kannada script using tensorflow based canvolutional neural network model /" rel="noreferrer noopener">https://drive.google.com/file/d/1cQhaRk9Wq4GL1oVheHvuZf6_DTkiYkdX/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
-
https://archives.christuniversity.in/files/original/6509e1da2bfcdbe1eb6a802e5d5a9a7e.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
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Title
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Automatic vehicle license plate recognizer for kannada script using tensorflow based canvolutional neural network model /
Subject
The topic of the resource
Computer Science
Description
An account of the resource
Patent Number: 201941054190, Applicant: Dr. Arish P.
Automatic Vehicle License Plate Recognizer (AVLPR) is used to read license number of a vehicle by itself without direct human control. It is used to track citizens, movements and misidentiflcation of vehicles. Traditional ALVPR is mounted on police cars or on object like road signs and bridges. The challenging tasks in recognizing the license plate numbers in Kannada script are high contrast foreground or background colour, shape of the license plate, location of the plate in the bottom and middle of the vehicle.
Creator
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M, Prabu.
Source
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<a href="https://drive.google.com/file/d/1wm_xtb6aUAT26ijmD_9jGcL7Oi20jh9C/view" target="_blank" title="Automatic vehicle license plate recognizer for kannada script using tensorflow based canvolutional neural network model /" rel="noreferrer noopener">https://drive.google.com/file/d/1wm_xtb6aUAT26ijmD_9jGcL7Oi20jh9C/view</a>
Publisher
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Intellectual Property India
Date
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2020-03-17
Language
A language of the resource
English
Type
The nature or genre of the resource
Patent
-
Dublin Core
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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 Weld Features Identification and Weld Quality Improvement in Laser Sensor Integrated Robotic Arc Welding
Subject
The topic of the resource
Laser sensor; Positional accuracy; Robotic arc welding; Weld seam
Description
An account of the resource
In this study, an integration of point laser sensor in robotic arc welding has been performed for achieving robotic positional accuracy automatically in every welding cycle. With the help of defined focal length of laser sensor, weld seam positions as well as weld gap have been found automatically for any newly positioned work-piece. If there is any change in robot positioning compared to the master job, the shift in every axis is sent as signal to the robot controller so that robot end effector will adjust the shift amount automatically. The welding process parameters are set at optimal values. Taguchi approach so that maximum values of weld quality in terms of depth of penetration, yield strength and ultimate strength can be achieved in every welding cycle. Overall, with the proposed approach, a smart and productive way of operating industrial welding robot has been proposed which can be implemented in any medium to large scale industries for obtaining welding joints with minimum defects. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
Creator
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Rout A.; Mahanta G.B.; Deepak B.; Renin Francy T.
Source
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Lecture Notes in Mechanical Engineering, pp. 303-313.
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Springer Science and Business Media Deutschland GmbH
Date
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2023-01-01
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<a href="https://doi.org/10.1007/978-981-99-2349-6_28" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-99-2349-6_28</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85172270483&doi=10.1007%2F978-981-99-2349-6_28&partnerID=40&md5=cc70040fbcf74ba8440e93a50a37f650" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85172270483&doi=10.1007%2f978-981-99-2349-6_28&partnerID=40&md5=cc70040fbcf74ba8440e93a50a37f650</a>
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ISSN: 21954356; ISBN: 978-981992348-9
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
Rout A., CHRIST (Deemed to be University), Bangalore, India; Mahanta G.B., Amrita Viswa Vidyapeetham, Chennai Campus, India; Deepak B., National Institute of Technology, Rourkela, India; Renin Francy T., CHRIST (Deemed to be University), Bangalore, India
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Faculty Publications
Conference Paper
Faculty Publications- Conference Papers
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Manjunatha Swamy, C.; Babu Kumar, S.; Kiran, B.; Vijay Kumar, M.S.
Title
A name given to the resource
Automation of Breast Cancer Diagnosis and Treatment Using Machine Learning
Date
A point or period of time associated with an event in the lifecycle of the resource
01-01-2025
Source
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Lecture Notes in Networks and Systems;Volume;1371 LNNS;pp.473-484
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<a href="https://doi.org/10.1007/978-981-96-5723-0_35" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-96-5723-0_35</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105018915958?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105018915958?origin=resultslist</a>
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Manjunatha Swamy C., Christ University, Bangalore, India; Babu Kumar S., Christ University, Bangalore, India; Kiran B., PES University, Bangalore, India; Vijay Kumar M.S., MIT, Mysore, India
Description
An account of the resource
Breast cancer remains a major global health challenge, with the complexity of managing diverse diagnostic tests often hindering timely and accurate detection. This system proposes a solution by unifying various test results, such as imaging, biopsy and genetic data, into a single platform that leverages machine learning (ML) to predict the likelihood of breast cancer. The platform features an intuitive dashboard that visually represents deviations from normal values, enabling healthcare providers to make informed decisions for early detection and treatment planning. In addition, the system includes an interactive chatbot powered by natural language processing, which assists both doctors and patients by interpreting test results, explaining predictions and offering real-time suggestions for treatment options. This comprehensive approach not only integrates ML models to enhance diagnostic accuracy but also provides real-time updates and alerts for critical changes in patient data. By consolidating fragmented information and incorporating predictive analytics, the system aims to improve the precision of cancer monitoring and offer personalized treatment guidance. About 98% early detection accuracy is achieved to do decision-making processes better which leads to efficient treatment planning. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
Subject
The topic of the resource
Breast cancer; Cancer prediction model; Convolutional neural networks (CNN); Machine learning; Machine learning in healthcare; Medical image analysis
Publisher
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Springer Science and Business Media Deutschland GmbH
Relation
A related resource
ISSN: 23673370; ISBN: 978-981965722-3;
Language
A language of the resource
English
Type
The nature or genre of the resource
Conference paper
Rights
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Restricted Access; Hardcopy may be available in the library
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Title
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Articles
Article
Faculty Publications -Articles
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Title
A name given to the resource
AUTOMATION OF TEST CASE PRIORITIZATION: A SYSTEMATIC LITERATURE REVIEW AND CURRENT TRENDS
Subject
The topic of the resource
Regression Testing; Software Engineering; Software Test Automation; Test Case Prioritization; Software Testing
Description
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An Important stage in software testing is designing a test suite [18]. The test case repository consists of a large number of test cases. However, only a portion of these test cases would be relevant and can find bugs. Test case prioritization(TCP) is one such technique that can substantially increase the cost-effectiveness of the testing activity. Using test case prioritization, more relevant test cases can be captured and tested in the earlier stages of the testing phase. The objective of the study is to understand different techniques used and a systemic study on the effectiveness of these approaches. The Literature consists of a few relevant articles introducing novel techniques for test case prioritization between 2008 and 2022. Studies show that parameters that are considered for test case prioritization are important. Hence, the current article also focuses on the parameters considered in the literature. 40% of the articles used in the literature review use different test case information as parameters. A systemic review and analysis of data sets involved in the literature are evaluated in the study. The review also focuses on the different approaches used for comparing the newly introduced approach and reveals a novel approach for prioritization. 2023 Little Lion Scientific. All rights reserved.
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George J.J.C.; Augustine D.P.
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Journal of Theoretical and Applied Information Technology, Vol-101, No. 3, pp. 1381-1387.
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Little Lion Scientific
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2023-01-01
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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-s2.0-85153796769&partnerID=40&md5=6e6f814273204d830f01bb71002d6fe6" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85153796769&partnerID=40&md5=6e6f814273204d830f01bb71002d6fe6</a>
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ISSN: 19928645
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Online
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English
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Article
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George J.J.C., Department of Computer Science, CHRIST (Deemed to be University, India; Augustine D.P., Department of Computer Science, CHRIST (Deemed to be University, India
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Conference Papers
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Automation using Artificial Intelligence in Business Landscape
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Artificial Intelligence; Automation; Companies; Machine learning; Management; Technologies
Description
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The integration of Artificial Intelligence (AI) with automation has sparked a remarkable transformation in the contemporary business landscape, promising elevated efficiency and quality. However, this convergence encounters multifaceted challenges, notably in the adoption of recent AI techniques such as deep learning, reinforcement learning, and natural language processing. These techniques, while potent, grapple with challenges in data quality, interpretability, and ethical considerations. In this study, we aim to delineate the intricate interplay between AI and automation, illuminating their collective potential to augment operational efficiency and confer a competitive advantage. Through a comprehensive review, we will explore the effective integration of these technologies, navigating hurdles such as data bias, system compatibility, and human-machine collaboration. Here, the primary research objective is to provide insights on optimizing the outcomes by synergizing AI and automation while addressing the inherent challenges, ultimately fostering sustainable and impactful implementations in organizational frameworks. 2023 IEEE.
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Unni M.V.; Rudresh S.; Bh R.; Krishnan R.K.; Kar R.; Devichandrika S.
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2nd International Conference on Automation, Computing and Renewable Systems, ICACRS 2023 - Proceedings, pp. 1519-1523.
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Institute of Electrical and Electronics Engineers Inc.
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2023-01-01
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<a href="https://doi.org/10.1109/ICACRS58579.2023.10404252" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICACRS58579.2023.10404252</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85185384220&doi=10.1109%2FICACRS58579.2023.10404252&partnerID=40&md5=fc3a0fcb3937cc35220fd3b9ba8145e9" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85185384220&doi=10.1109%2fICACRS58579.2023.10404252&partnerID=40&md5=fc3a0fcb3937cc35220fd3b9ba8145e9</a>
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ISBN: 979-835034023-5
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Online
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English
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Conference paper
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Unni M.V., Department of Management, St. Claret College, Karnataka, Bengaluru, India; Rudresh S., Department of Management, St. Claret College, Karnataka, Bengaluru, India; Bh R., School of Business and Management, CHRIST (Deemed to be University), Karnataka, Bengaluru, India; Krishnan R.K., College of Economics and Business Administration, University of Technology and Applied Sciences, Shinas, Oman; Kar R., Department of Management, St. Claret College, Karnataka, Bengaluru, India; Devichandrika S., Department of Business Administration, St. Francis De Sales College, Karnataka, Bangalore, India
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Faculty Publications
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Hema, K.; Pavithra, R.
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Autonomous AI in Automotive Safety: Rethinking Tortious Liability Paradigms
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01-01-2026
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Agentic AI for Autonomous Vehicles: Safety, Reliability, Law, and Ethics;pp.321-338
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<a href="https://doi.org/10.4018/979-8-3373-7355-3.ch011" target="_blank" rel="noreferrer noopener">https://doi.org/10.4018/979-8-3373-7355-3.ch011</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105038487693?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105038487693?origin=resultslist</a>
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Hema K., Christ University, India; Pavithra R., Gujarat National Law University, India
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This paper seeks to examine the application of tort law to the Automated Vehicles. Section I deals with a brief overview of the impact of AVs and tort law and the application of tortious principles. Section II discusses the concept of fault and the multiple parties to whom fault can be attributed. Furthermore, it discusses who should be blamed and to what extent. Section III discusses the tortious principles such as product liability, vicarious liability and apportionment of liability and its application to the AVs. Section IV proposes directions for future research, conclusion and recommendations for the legal challenges posed by the AVs. 2026 by IGI Global Scientific Publishing. All rights reserved.
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IGI Global
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ISBN: 979-833737357-7; 979-833737355-3;
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English
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Book chapter
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Faculty Publications
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Rout, Amruta; Champatiray, Chiranjibi; Mahanta, Golak Bihari; Singh Sahni, Rajveer; Aggarwal, Tanishka; Maji, Kingshuk; Bahubalendruni, MVA Raju
Title
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Autonomous green vegetable growth monitoring via YOLOv9 and a vine robot with tracked mobility
Date
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01-01-2026
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Expert Systems with Applications;Volume;321;Issue;;Article No.;132165;
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<a href="https://doi.org/10.1016/j.eswa.2026.132165" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.eswa.2026.132165</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105034884687?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105034884687?origin=resultslist</a>
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Rout A., Department of Mechanical and Automobile Engineering, Christ University, Karnataka, Bengaluru, 560074, India; Champatiray C., Department of Mechanical and Automobile Engineering, Christ University, Karnataka, Bengaluru, 560074, India; Mahanta G.B., Department of Mechatronics and Automation Engineering, National Institute of Technology Patna, Bihar, Patna, 800005, India; Singh Sahni R., Department of Mechanical and Automobile Engineering, Christ University, Karnataka, Bengaluru, 560074, India; Aggarwal T., Department of Mechanical and Automobile Engineering, Christ University, Karnataka, Bengaluru, 560074, India; Maji K., Department of Mechanical and Automobile Engineering, Christ University, Karnataka, Bengaluru, 560074, India; Bahubalendruni M.V.A.R., Industrial Robotics and Manufacturing Automation Laboratory, Department of Mechanical Engineering, National Institute of Technology Puducherry, Tamil Nadu, Karaikal, 609609, India
Description
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Urban agriculture is facing shrinking land while demand for food is increasing. The study introduces a vine-like, soft robot for non-destructive tracking of green vegetable development using a tracked mobile platform. Although an inbuilt camera and YOLOv9 object detector classify in real time and generate results in four size categories, very small, small, medium, and large, a flexible tube is everted into dense greenery through a pneumatic eversion process. Sensor fusion and hierarchical control are integrated to enable navigation through the complex canopies of crops with accurate control of pressure and direction, and steering. A field trial found 91% mAP detection accuracy at 38 FPS, accurate vine extension (1.2 m @ 4 cm/s), and stable locomotion over uneven terrain, resulting in constant coverage without harming the plants. The system provides a scalable solution for precision agriculture, enhancing crop inspection, disease diagnosis, and harvest planning through continuous data insights. 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
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Growth tracking; Mobile inspection; Precision agriculture; Soft robotics; Vine robot; YOLOv9
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Elsevier Ltd
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ISSN: 9574174; CODEN: ESAPE
Language
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English
Type
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Article
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Restricted Access; Hardcopy may be available in the library
Format
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online
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Conference Papers
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AUTONOMOUS IOT MOVEMENT IN HOSTILE AREAS USING ROBOTICS AND DEEP FEDERATED ALGORITHMS
Subject
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Autonomous IoT; Deep Federated Algorithms; Hostile Areas; Robotics
Description
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Innovative solutions are required when Internet of Things (IoT) devices are deployed in hostile or difficult locations to ensure dependable and effective operation. In order to enable autonomous IoT mobility in such challenging circumstances, this study suggests a novel approach integrating robotics and deep federated algorithms. Robotics and IoT can work together to create a system that can adapt to dangerous environments, extreme weather conditions, and unexpected terrain. Deep federated algorithms further improve system performance by facilitating dispersed device collaboration for learning while protecting data privacy. The suggested framework covers the issues of communication stability, energy optimization, and real-time decision-making. We illustrate the practicality of this strategy in strengthening the dependability and efficiency of IoT deployments in hostile situations through simulations and tests. 2023 IEEE.
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Archana U.; Roslin Dayana K.; Jayadurga R.; Sahaana G.; Praveena K.; Saravanan V.
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2023 IEEE International Conference on Research Methodologies in Knowledge Management, Artificial Intelligence and Telecommunication Engineering, RMKMATE 2023
Publisher
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Institute of Electrical and Electronics Engineers Inc.
Date
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2023-01-01
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<a href="https://doi.org/10.1109/RMKMATE59243.2023.10369410" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/RMKMATE59243.2023.10369410</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85183535118&doi=10.1109%2FRMKMATE59243.2023.10369410&partnerID=40&md5=0316697e73d642abf342b4df30fa00c9" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85183535118&doi=10.1109%2fRMKMATE59243.2023.10369410&partnerID=40&md5=0316697e73d642abf342b4df30fa00c9</a>
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ISBN: 979-835030570-8
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Online
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English
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Conference paper
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Archana U., Department of Computer Science and Design, R.M.K. Engineering College, Tamilnadu, Kavaraipettai, India; Roslin Dayana K., Department of Computer Science and Engineering, R.M.D. Engineering College, Tamilnadu, Kavaraipettai, India; Jayadurga R., Department of Computer Science, Christ University, Yeshwantpur(YPR) Campus, Karnataka, Bengaluru, India; Sahaana G., Department of ECE, Veltech Multitech Dr Rangarajan Dr Shakuntala Engineering College, Tamilnadu, Chennai, India; Praveena K., Department of ECE, Mohan Babu University, Erstwhile Sree Vidyanikethan Engineering College, Andhra Pradesh, Tirupati, India; Saravanan V., Department of Computer Science, Dambi Dollo University, Oromia Region, Dambi Dollo, Ethiopia
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Faculty Publications
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Pandey, Ananya
Title
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Autonomous Systems in Agriculture: An Innovation-Based Framework
Date
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01-01-2026
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Emerging AI, Governance, and Digital Innovations for Sustainable Organizations;pp.257-277
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<a href="https://doi.org/10.4018/979-8-3373-8607-2.ch008" target="_blank" rel="noreferrer noopener">https://doi.org/10.4018/979-8-3373-8607-2.ch008</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105032600799?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105032600799?origin=resultslist</a>
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Pandey A., Christ University, Bangalore, India
Description
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The emergence of autonomous systems in agriculture signifies a transformative change in global food production, propelled by developments in artificial intelligence, robotics, and data analytics. This chapter suggests a thorough innovation framework that brings together technological, organizational, institutional, economic, social, and environmental aspects to steer the sustainable development and implementation of autonomous agricultural technologies. The chapter examines essential facilitators and obstacles to innovation, such as infrastructure deficiencies, digital literacy, and regulatory challenges, by analyzing historical trends, case studies, and policy landscapes. It stresses ethical and inclusive innovation to guarantee the involvement of smallholders and ecological resilience. This framework acts as a strategic resource for researchers, practitioners, and policymakers who seek to connect digital transformation in agriculture with sustainability objectives, especially those outlined by the UN Sustainable Development Goals (SDGs). 2026 by IGI Global Scientific Publishing.
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IGI Global
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ISBN: 979-833738609-6; 979-833738607-2;
Language
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English
Type
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Book chapter
Rights
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Restricted Access; Hardcopy may be available in the library
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Title
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Articles
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Autoregressive Distributed Lag Approach for Estimating the Nexus between Net Asset Value of Mutual Fund and Economic Determinants in India
Subject
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large cap; macroeconomic factors; mutual fund; net asset value; small cap and mid cap
Description
An account of the resource
India has seen a phenomenal growth in cumulative mutual fund investment from Rs 7.93 trillion in 2012 to Rs 40.38 trillion in 2022, which is more than a five-fold increase since last 10 years. Retail investors are now realizing the power of savings and Systematic Investment Plans (SIP) to build long term wealth. A financial literacy wave which is sweeping across India has projected mutual funds as a significant contributor and beneficiary of this phenomenon. The evolving economic landscape of India provides investors with excellent opportunities to capitalize on these fluctuations through systematic investment in safe investment vehicles like mutual funds. The market associated with mutual funds is always subjected to economic risks. The erratic fluctuations in macroeconomic variables can largely explain the Volatility in Net Asset Value (NAV) of equity oriented mutual fund schemes. With this background, this paper examines the impact of select macroeconomic variables on mutual funds performance in India. To analyse this, monthly observations of select macroeconomic variables, average NAV of large cap, mid cap, and small cap funds collected for a period of 10 years starting from January 2013 to November 2022. Descriptive statistics is used to probe the characteristics of the variable. In addition, correlation and ordinary least square method is applied to check the existing relationship and impact level of macroeconomic factors on NAV of select schemes. Lastly, short and long run relationship is analysed using Autoregressive Distributed Lag Model (ARDL). 2023, ASERS Publishing House. All rights reserved.
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Pachiyappan S.; Shrivastava A.; Raj V.J.P.; Vellaiyan S.
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Theoretical and Practical Research in the Economic Fields, Vol-14, No. 1, pp. 186-201.
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ASERS Publishing House
Date
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2023-01-01
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<a href="https://doi.org/10.14505/tpref.v14.1(27).15" target="_blank" rel="noreferrer noopener">https://doi.org/10.14505/tpref.v14.1(27).15</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85163693324&doi=10.14505%2Ftpref.v14.1%2827%29.15&partnerID=40&md5=6a779b09ee44d1da2e0be9abd3efe76b" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85163693324&doi=10.14505%2ftpref.v14.1%2827%29.15&partnerID=40&md5=6a779b09ee44d1da2e0be9abd3efe76b</a>
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All Open Access; Hybrid Gold Open Access
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A related resource
ISSN: 20687710
Format
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Online
Language
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English
Type
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Article
Coverage
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Pachiyappan S., School of Business and Management, CHRIST (Deemed to be University), Bangalore, India; Shrivastava A., School of Business and Management, CHRIST (Deemed to be University), Bangalore, India; Raj V.J.P., School of Business and Management, CHRIST (Deemed to be University), Bangalore, India; Vellaiyan S., School of Business and Management, CHRIST (Deemed to be University), Bangalore, India
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Faculty Publications
Conference Paper
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Augustine, Praveen; John, Nimitha
Title
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Autoregressive Model with Students t-Errors
Date
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01-01-2026
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Lecture Notes in Networks and Systems;Volume;1501 LNNS;pp.351-364
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<a href="https://doi.org/10.1007/978-981-96-8350-5_25" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-96-8350-5_25</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105028365077?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105028365077?origin=resultslist</a>
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Augustine P., Department of Data Science and Statistics, CHRIST (Deemed to be University), Bengaluru, India; John N., Department of Data Science and Statistics, CHRIST (Deemed to be University), Bengaluru, India
Description
An account of the resource
This paper examines a first-order autoregressive model that incorporates students t-distributed errors. The estimation procedure is developed using the maximum likelihood method, with the solutions demonstrated using a simulation approach. As the estimating equations were not in a closed-form expression, we obtained the parameter estimates using the NewtonRaphson method. For a finite sample size, a parametric bootstrap procedure for the unit root test has been illustrated. To demonstrate the applications of the proposed model, a time series of quarterly GDP percentage changes are analyzed. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2026.
Subject
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Autoregressive model; Bootstrapping; Likelihood ratio test; Maximum likelihood; Students t-distribution
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Springer Science and Business Media Deutschland GmbH
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ISSN: 23673370; ISBN: 978-981968349-9;
Language
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English
Type
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Conference paper
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Restricted Access; Hardcopy may be available in the library
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Conference Papers
Conference Paper
Faculty Publications- Conference Papers
Dublin Core
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Title
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Available Transfer Capability (ATC) enhancement & optimization of UPFC shunt converter location with GSF in deregulated power system
Subject
The topic of the resource
Available Transfer Capability; GSF; RPF
Description
An account of the resource
Available Transfer Capability (ATC) is a measure for transmission system security margin in open access electricity market. Determining the Available Transfer Capability (ATC) of the transmission networks, Repeated Power Flow (RPF) approach have been used since it can satisfy voltage, thermal and stability constraints among all other methods available. The main objectives include identification of best location for UPFC to get maximum ATC enhancement and to propose a novel method for optimizing the UPFC PV bus location using Generation Shift Factor (GSF) so that power system transmission network can deliver more number of power trades. 2016 IEEE.
Creator
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Sunny A.; Janamala V.
Source
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Proceedings of IEEE International Conference on Circuit, Power and Computing Technologies, ICCPCT 2016
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Institute of Electrical and Electronics Engineers Inc.
Date
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2016-01-01
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<a href="https://doi.org/10.1109/ICCPCT.2016.7530289" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICCPCT.2016.7530289</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-84992154183&doi=10.1109%2FICCPCT.2016.7530289&partnerID=40&md5=cfb8383c242c0893e47267b446c786a5" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-84992154183&doi=10.1109%2fICCPCT.2016.7530289&partnerID=40&md5=cfb8383c242c0893e47267b446c786a5</a>
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Restricted Access
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ISBN: 978-150901277-0
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Online
Language
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English
Type
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Conference paper
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Sunny A., Dept. of Electrical Engineering, Faculty of Engineering, Christ University, Bangalore, India; Janamala V., Dept. of Electrical Engineering, Faculty of Engineering, Christ University, Bangalore, India
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https://archives.christuniversity.in/files/original/cd2edc2004ab8faaae8f79331ecb1fab.pdf
7c6a52d75b8bf864f125cf2a183d6e5d
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Title
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MPHIL
Mphil
Mphil Thesis
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Title
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Awareness and Attitude of Post Graduate Students
towards Massive Open Online Courses in Bangalore
Urban District
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Siami Lal Rem
Date
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2016
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Education
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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/.
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Faculty Publications
Article
Faculty Publications -Articles
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Abraham, Daniel M.; Saliha, F.B.
Title
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Awareness and perception of adolescent boys about menstruation: an exploratory study from rural India
Date
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01-01-2025
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Discover public health;Volume;22;Issue;1;Article No.;205;
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<a href="https://doi.org/10.1186/s12982-025-00600-y" target="_blank" rel="noreferrer noopener">https://doi.org/10.1186/s12982-025-00600-y</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105003857781?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105003857781?origin=resultslist</a>
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Abraham D.M., Department of Psychology, University of Calicut, Calicut University (P.O.), Kerala, Malappuram, 673635, India, Christ University, Karnataka, Bangalore, 560029, India; Saliha F.B., Department of Psychology, University of Calicut, Calicut University (P.O.), Kerala, Malappuram, 673635, India, Farook College (Autonomous), P.O. Farook College, Kerala, Kozhikode, 673632, India
Description
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Background/objectives: Menstruation, despite being a natural process, remains stigmatized in many patriarchal societies, where taboos and misinformation perpetuate silence and misconceptions. This study investigates adolescent boys awareness and perceptions of menstruation in rural India, examining the influence of cultural, educational, and social factors on their understanding. Methods: Employing an exploratory qualitative design, a focus group discussion (FGD) was conducted with eight 15-year-old boys from a rural secondary school in Kerala, India. The session was audio-recorded and supplemented with detailed field notes to capture verbal and non-verbal insights. Braun and Clarkes thematic analysis framework was used to identify key themes. Results: Three primary themes emerged: Levels of awareness (ranging from correct but insufficient to lack), Sources of knowledge (media, peers, cultural practices), and Desire for further knowledge. Findings indicate that fragmented or inaccurate knowledge, shaped by cultural and societal norms, reinforces stereotypes and stigma around menstruation. Conclusions: Findings underscore the need for inclusive and culturally sensitive educational interventions for boys, aimed at dispelling myths and fostering empathy. Such programs can contribute to improved awareness, reduced stigma, and greater support for menstrual hygiene management (MHM) practices. Future research should assess similar interventions across broader contexts to determine their impact on challenging menstrual taboos. The Author(s) 2025.
Subject
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Adolescent boys; Focus group discussion; Gender-inclusive education; Menstrual awareness; Menstrual hygiene management; Menstrual taboos; Menstruation; Thematic analysis
Publisher
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BioMed Central Ltd
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ISSN: 30050774;
Language
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English
Type
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Article
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All Open Access; Gold Open Access; Green Open Access
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online