423 20 16481 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 Book Chapter Book Chapter Faculty Publications- Book Chapter 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 Idealised Bilinear Moment-Curvature Curves of Reinforced Masonry (RM) Walls Description An account of the resource In this paper, an analytical investigation of the axial loadflexural strength interaction of reinforced masonry walls is carried. The curvature ductility of masonry walls is evaluated for walls with different modes of reinforcement configurations under different levels of axial loads. An analytical expression for evaluating the curvature ductility of masonry walls at varying axial loads is proposed in this paper. Value of curvature ductility obtained from the proposed expression is compared with existing methods. Results indicate the proposed model can be used to determine the ductility of reinforced masonry walls. 2020, Springer Nature Singapore Pte Ltd. Creator An entity primarily responsible for making the resource Kollerathu J.A. Source A related resource from which the described resource is derived Lecture Notes in Civil Engineering, Vol-74, pp. 99-110. Publisher An entity responsible for making the resource available Springer Date A point or period of time associated with an event in the lifecycle of the resource 2020-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-981-15-4079-0_9" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-15-4079-0_9</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85085165713&doi=10.1007%2F978-981-15-4079-0_9&partnerID=40&md5=bdcfddb594c1898877f609bf11631c2d" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85085165713&doi=10.1007%2f978-981-15-4079-0_9&partnerID=40&md5=bdcfddb594c1898877f609bf11631c2d</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 23662557 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Book chapter Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Kollerathu J.A., Department of Civil Engineering, Faculty of Engineering, Christ (Deemed to Be University), Bengaluru, India https://archives.christuniversity.in/files/original/949509331792c790d1380a1ada693c48.pdf 3faf36fca58aadf0f9bb93eb1005db12 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 MPHIL Mphil Mphil Thesis 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 Ideas of Identity and Imagined Communities in Association Football Creator An entity primarily responsible for making the resource Guledgudd Sohail M Date A point or period of time associated with an event in the lifecycle of the resource 2018 Source A related resource from which the described resource is derived English 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 PHD PhD PhD Thesis 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/. Relation A related resource 61000043 Title A name given to the resource Identification and standardization of counsellor competencies for master level counsellor education programs in india Subject The topic of the resource Psychology Description An account of the resource Counselling psychology programs in India have been criticized for being poor replicas of newlineconcepts that have originated in western cultures . The lack of Indian models has been quoted as a drawback indicating that trainees are not necessarily competent to provide effective counselling services. The present study aimed at identifying and standardizing competencies for post graduate counsellor training in India based on local needs.The study employed a mixed methods design with four phases. In the first phase, a list of key occupational tasks were drawn up through a systematic review of literature and interviews with three expert practitioners. The second phase was the development of a counsellor competency list which outlined the various competencies required to fulfil the key occupational tasks determined in the previous stage. Seventy one competencies were identified and the list was then given for newlineexpert validation. In the third phase, the competency list was given to 75 practicing newlinecounsellors across India who rated the competencies on a 5-point likert scale, based on its importance for post graduate counsellor trainees. In the final stage the prioritized competencies were analyzed using a concept development approach to identify core competencies required for master level counselling psychology trainees. The resulting core competencies were three foundational competency domains which included ethical practice, personal and professional development and cultural sensitivity. There were also three newlinefunctional competency domains which included the counselling process, the supervision newlineprocess and the promotion of counselling in India. Specific competencies under each domain were also listed along with behavioral indicators for the same. Thus the core competencies that counsellor trainees must develop to provide an effective service were identified and this has implications for training and practice. Creator An entity primarily responsible for making the resource Thomas,Elizabeth Source A related resource from which the described resource is derived Author's Submission Publisher An entity responsible for making the resource available Christ(Deemed to be University) Date A point or period of time associated with an event in the lifecycle of the resource 2015-01-01 Contributor An entity responsible for making contributions to the resource George, Tony Sam Rights Information about rights held in and over the resource Open Access Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource English Type The nature or genre of the resource PhD Identifier An unambiguous reference to the resource within a given context <a href="http://hdl.handle.net/10603/344314" target="_blank" rel="noreferrer noopener">http://hdl.handle.net/10603/344314</a> https://archives.christuniversity.in/files/original/ac87d9013320a1f0c9e20fc0a48ec31a.pdf bee14eaed4103e405713111cbcb5f0d1 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 Thesis PhD PhD Thesis 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 Identification and standardization of counsellor competencies for masters level counsellor education programs in India Subject The topic of the resource Psychology Description An account of the resource Counselling psychology programs in India have been criticized for being ‘poor replicas of concepts that have originated in western cultures’. The lack of Indian models has been quoted as a drawback indicating that trainees are not necessarily competent to provide effective counselling services. The present study aimed at identifying and standardizing competenciesfor post graduate counsellor training in India based on local needs.The study employed a mixed methods design with four phases. In the first phase, a list of key occupational tasks were drawn up through a systematic review of literature and interviews with three expert practitioners. The second phase was the development of a counsellor competency list which outlined the various competencies required to fulfil the key occupational tasks determined in the previous stage. Seventy one competencies were identified and the list was then given for expert validation. In the third phase, the competency list was given to 75 practicing counsellors across India who rated the competencies on a 5-point likert scale, based on its importance for post graduate counsellor trainees. In the final stage the prioritized competencies were analyzed using a concept development approach to identify core competencies required for master level counselling psychology trainees. The resulting core competencies were three foundational competency domains which included ethical practice, personal and professional development and cultural sensitivity. Creator An entity primarily responsible for making the resource Thomas, Elizabeth - 1144210 Publisher An entity responsible for making the resource available CHRIST (Deemed to be University) Language A language of the resource English Type The nature or genre of the resource PhD 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 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 Identification and structure-activity relationship studies of small molecule inhibitors of the human cathepsin D Subject The topic of the resource Cathepsin D Description An account of the resource Cathepsin D, an aspartyl protease, is an attractive therapeutic target for various diseases, primarily cancer and osteoarthritis. However, despite several small molecule cathepsin D inhibitors being developed, that are highly potent, most of them show poor microsomal stability, which in turn limits their clinical translation. Herein, we describe the design, optimization and evaluation of a series of novel non-peptidic acylguanidine based small molecule inhibitors of cathepsin D. Optimization of our hit compound 1a (IC50 = 29 nM) led to the highly potent mono sulphonamide analogue 4b (IC50 = 4 nM), however with poor microsomal stability (HLM: 177 and MLM: 177 ?l/min/mg). To further improve the microsomal stability while retaining the potency, we carried out an extensive structureactivity relationship screen which led to the identification of our optimised lead 24e (IC50 = 45 nM), with an improved microsomal stability (HLM: 59.1 and MLM: 86.8 ?l/min/mg). Our efforts reveal that 24e could be a good starting point or potential candidate for further preclinical studies against diseases where Cathepsin D plays an important role. 2020 Elsevier Ltd Creator An entity primarily responsible for making the resource Goyal S.; Patel K.V.; Nagare Y.; Raykar D.B.; Raikar S.S.; Dolas A.; Khurana P.; Cyriac R.; Sarak S.; Gangar M.; Agarwal A.K.; Kulkarni A. Source A related resource from which the described resource is derived Bioorganic and Medicinal Chemistry, Vol-29 Publisher An entity responsible for making the resource available Elsevier Ltd Date A point or period of time associated with an event in the lifecycle of the resource 2021-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1016/j.bmc.2020.115879" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.bmc.2020.115879</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85096839622&doi=10.1016%2Fj.bmc.2020.115879&partnerID=40&md5=cbc04b74b21b3986672c52d072669a3f" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85096839622&doi=10.1016%2fj.bmc.2020.115879&partnerID=40&md5=cbc04b74b21b3986672c52d072669a3f</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 9680896; PubMed ID: 33271453; CODEN: BMECE Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource 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 Goyal S., Aten Porus Lifesciences, Bangalore, 560068, India; Patel K.V., Aten Porus Lifesciences, Bangalore, 560068, India; Nagare Y., Aten Porus Lifesciences, Bangalore, 560068, India; Raykar D.B., Aten Porus Lifesciences, Bangalore, 560068, India; Raikar S.S., Aten Porus Lifesciences, Bangalore, 560068, India; Dolas A., Aten Porus Lifesciences, Bangalore, 560068, India; Khurana P., Aten Porus Lifesciences, Bangalore, 560068, India; Cyriac R., Aten Porus Lifesciences, Bangalore, 560068, India; Sarak S., Aten Porus Lifesciences, Bangalore, 560068, India; Gangar M., Aten Porus Lifesciences, Bangalore, 560068, India; Agarwal A.K., Department of Chemistry, CHRIST (Deemed to be University), Bengaluru, Karnataka, India; Kulkarni A., Aten Porus Lifesciences, Bangalore, 560068, India, Avaliv Therapeutics, Naples, FL, United States 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 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 Identification of ambulance in traffic videos using image processing techniques Subject The topic of the resource Color space thresholding; Multilevel thresholding; Optical Character Recognition (OCR); Region matching for text detection Description An account of the resource Traffic congestion is one of the commonly faced problems in the Urban areas. To eliminate these problems, there is a need for an Intelligent Transportation System (ITS) that proposes an efficient method to reduce the traffic problems and introduces the priority system for the Emergency vehicles. This paper proposes two frameworks that identify ambulance in traffic videos based on features such as color, siren and text. Frames are extracted from videos to employ methods like multilevel thresholding and region matching. Multilevel thresholding is used for segmenting the ambulance from the other occurring vehicles based on the white color. Region matching for text detection method is employed in the segmented vehicle. Color space thresholding is used for the detection of siren based on red or blue color feature. Optical character recognition (OCR) is employed to extract the text in the frame. Word comparison and Matching detects the ambulance text based on the outcome of OCR. The performance of Framework 1 and Framework 2 are evaluated based on Word accuracy and from the experimental results it is observed that Framework 2 is better from 75% word accuracy. 2018, Institute of Advanced Scientific Research, Inc. All Rights reserved. Creator An entity primarily responsible for making the resource Karthik Raj P.R.; Praveen Kumar P.U. Source A related resource from which the described resource is derived Journal of Advanced Research in Dynamical and Control Systems, Vol-10, pp. 213-224. Publisher An entity responsible for making the resource available Institute of Advanced Scientific Research, Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2018-01-01 Identifier An unambiguous reference to the resource within a given context <a href="" target="_blank" rel="noreferrer noopener"></a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85046372114&partnerID=40&md5=2697b41f14295c6755c2c1fb87e78be0" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85046372114&partnerID=40&md5=2697b41f14295c6755c2c1fb87e78be0</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 1943023X Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource 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 Karthik Raj P.R., Department of Computer Science, Christ University, Bengaluru, India; Praveen Kumar P.U., Department of Computer Science, Christ University, Bengaluru, India 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 Faculty Publications 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/. Creator An entity primarily responsible for making the resource Suresh, Monica; Pappuswamy, Manikantan Title A name given to the resource Identification of bioactive metabolites in Turnera ulmifolia: Preliminary phytochemical screening and FTIR analysis Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived Plant Science Today;Volume;12;Issue;3;pp.1-8 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.14719/pst.7515" target="_blank" rel="noreferrer noopener">https://doi.org/10.14719/pst.7515</a> <a href="https://www.scopus.com/pages/publications/105018186982?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105018186982?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Suresh M., Department of Life Sciences, Christ (Deemed to be) University, Bangalore, 560 029, India; Pappuswamy M., Department of Life Sciences, Christ (Deemed to be) University, Bangalore, 560 029, India Description An account of the resource Turnera ulmifolia L., a member of the Passifloraceae family, is widely distributed across tropical and subtropical regions. Though frequently considered a weed, it has been commonly used in folk medicine to treat inflammation, infections, wounds and digestive ailments. Earlier studies have found alkaloids, flavonoids, tannins, terpenoids and polyphenols in species from the same genera that contribute to their therapeutic efficacy. Despite its ethnomedicinal value, the phytochemical profile and functional group characterization of T. ulmifolia are still unexplored. This study aimed to investigate the phytochemical composition of its leaf, stem and root extracts using different solvents (methanol, ethanol, hexane and acetone) and identify key functional groups through FTIR analysis. Phytochemical screening confirmed the presence of diverse secondary metabolites. FTIR analysis further revealed functional groups such as O=C=O, C=C and S=O, which are associated with therapeutic properties. Notably, alkaloids were abundant in leaf extracts, while sulfoxide groups, known for their herbicidal and medicinal effects, were detected in the stem. These findings reinforce the pharmacological potential of T. ulmifolia as a promising source of bioactive metabolites with medicinal and ecological applications. Its capacity to diversify in various habitats and create bioactive molecules under stress points to possible uses in medicine discovery, sustainable agriculture and environmental restoration. This study lays the groundwork for future research to validate its therapeutic potential and explore its integration into modern pharmaceutical and ecological solutions. (2025), (Horizon e-Publishing Group). All rights reserved. Subject The topic of the resource bioactive; functional group analysis; T. ulmifolia; weed plant Publisher An entity responsible for making the resource available Horizon e-Publishing Group Relation A related resource ISSN: 23481900; Language A language of the resource English Type The nature or genre of the resource Article Rights Information about rights held in and over the resource All Open Access; Gold Open Access; Green Open Access Format The file format, physical medium, or dimensions of the resource online 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 Faculty Publications 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/. Creator An entity primarily responsible for making the resource Singh, Suraj Pal; Upreti, Kamal; Jain, Rituraj; Arora, Rakesh Kumar; Tiwari, Akhilesh; Radhakrishnan, G.V. Title A name given to the resource Identification of Brain Tumors Using CNN and ML with Diverse Feature Selection Techniques Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived Journal of Applied Science and Technology Trends;Volume;6;Issue;1;pp.74-86 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.38094/jastt61240" target="_blank" rel="noreferrer noopener">https://doi.org/10.38094/jastt61240</a> <a href="https://www.scopus.com/pages/publications/105010274343?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105010274343?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Singh S.P., Computer Science and Engineering, Chandigarh University, Mohali, India; Upreti K., Department of Computer Science, Christ University, Delhi NCR Campus, Ghaziabad, India; Jain R., Department of Information Technology, Marwadi University, Gujarat, Rajkot, India; Arora R.K., Computer Science and Engineering, Dr. Akhilesh Das Gupta Institute of Professional Studies, Delhi, India; Tiwari A., Department of Business and Management, Christ University, Delhi NCR Campus, Ghaziabad, India; Radhakrishnan G.V., Kalinga School of Management, Kalinga Institute of Industrial Technology, Bhubaneswar, India Description An account of the resource Early diagnosis and treatment is very essential in monitoring Brain tumor using MRI images. Convolutional Neural Networks (CNN) and Machine Learning (ML) classifiers have been widely used but there is not much work on how feature selection techniques would affect the performance of the CNN. Secondly, there is a need for investigation concerning small dataset adaptability and ML-CNN comparisons. To improve the classification accuracy, we integrate Univariate, Recursive Feature Elimination (RFE), Recursive Feature Elimination with Cross Validation (RFECV) with CNN in this study. Preprocessing, feature extraction & selection was carried out on the dataset consisting of 253 MRI images and they are classified using CNN and ML models (Logistic Regression, Decision Tree, Random Forest, Nae Bayes). With the results 96%, CNN with Univariate Feature Selection performed better than ML classifiers, and other selection techniques. The results demonstrate that feature selection is necessary to get the best performance out of CNN models operating on small datasets. Future studies should be based on different deep learning architectures to improve classification and application i n other datasets. 2025, Interdisciplinary Publishing Academia. All rights reserved. Subject The topic of the resource brain tumor detection; CNN; feature selection; machine learning; medical imaging; MRI classification Publisher An entity responsible for making the resource available Interdisciplinary Publishing Academia Relation A related resource ISSN: 27080757; Language A language of the resource English Type The nature or genre of the resource Article Rights Information about rights held in and over the resource All Open Access; Gold Open Access Format The file format, physical medium, or dimensions of the resource online 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 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 Identification of broken characters in degraded documents Subject The topic of the resource Chain code; Heuristic information; Horizontal projection profile; Mean-based thresholding; OCR; Vertical projection profile Description An account of the resource Optical Character Recognition (OCR) deals with the recognition of characters in a text document. Steps like Preprocessing, Segmentation and Recognition are embedded in the OCR machine. When a document is scanned it will be taken into OCR and will recognize the characters. But noisy scanning of documents, low-quality printed documents and thresholding error leads to the generation of broken characters. When these documents are given as inputs into OCR, the recognition becomes a tedious process since the broken characters are misunderstood by the OCR machine. So the broken characters have to be identified and segmented separately. This work aims to enhance the degraded documents with broken characters using image processing techniques. For identifying or recognizing the broken character from the image various techniques like vertical projection profile, horizontal projection profile, chain code, mean based thresholding are used. The lines from the document are separated using line segmentation. Separate characters are extracted using Vertical Projection Profile and Horizontal Projection Profile. The character is identified using chain coding. The broken characters are found from them using Mean-based Thresholding and is merged using Heuristic information. The proposed method achieves an accuracy of 92.88% and also performs well for color image documents as well as black and white image documents also because of the effective preprocessing. 2018 Intelligent Network and Systems Society. Creator An entity primarily responsible for making the resource Ramalingam K.; Bhojan R. Source A related resource from which the described resource is derived International Journal of Intelligent Engineering and Systems, Vol-11, No. 3, pp. 130-137. Publisher An entity responsible for making the resource available Intelligent Network and Systems Society Date A point or period of time associated with an event in the lifecycle of the resource 2018-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.22266/IJIES2018.0630.14" target="_blank" rel="noreferrer noopener">https://doi.org/10.22266/IJIES2018.0630.14</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85050968301&doi=10.22266%2FIJIES2018.0630.14&partnerID=40&md5=aed79443139d4376c917bc45e98201f7" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85050968301&doi=10.22266%2fIJIES2018.0630.14&partnerID=40&md5=aed79443139d4376c917bc45e98201f7</a> Rights Information about rights held in and over the resource All Open Access; Bronze Open Access Relation A related resource ISSN: 2185310X Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource 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 Ramalingam K., Department of Computer Science, Christ University, Hosur Road, Bengaluru, Karnataka, India; Bhojan R., Department of Computer Science, Christ University, Hosur Road, Bengaluru, Karnataka, India 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 A name given to the resource Identification of Consumer Buying Patterns using KNN in E-Commerce Applications Subject The topic of the resource buying behavior; Consumer behavior analysis; E- Commerce applications; K-Nearest Neighbor; Machine Learning Description An account of the resource In recent days, with the advancement of technologies, people use electronic medium to carry out their businesses. E-commerce is a process of allowing people to buy and sell products online using electronic medium. E-commerce has a wide range of customer base as well. The data generated through transaction helps the enterprises to develop the marketing strategy. The growth of this e-commerce application depends on several factors. Some of the factors are follows 1) Customer demand, 2) Analyzing buying pattern of the users, 3) Customer retention, 4) dynamic pricing etc. It is very difficult to analyze the buying pattern of customers as there is a wide range of customer base in the online platform. To overcome this problem, this research study discusses about the challenges and issues in e-commerce applications, also identifies and analyses the buying patterns of customer using various machine learning techniques. From the implementation it is identified that, KNN algorithm performed well while comparing it with various other machine learning algorithms. Performances of these algorithms have been analyzed using various matrices. For analyzing, the model is tested using e-commerce dataset (Amazon dataset downloaded from Kaggle.com). From the analysis it found that KNN algorithm computes and predicts better compared to other machine learning algorithms either Nae Bayes, or Random Forest, or Logistic Regression etc. 2023 IEEE. Creator An entity primarily responsible for making the resource Yasin W.; Harimoorthy K.; Vetriveeran D. Source A related resource from which the described resource is derived Proceedings - 2023 3rd International Conference on Pervasive Computing and Social Networking, ICPCSN 2023, pp. 187-192. Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2023-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ICPCSN58827.2023.00036" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICPCSN58827.2023.00036</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85175243980&doi=10.1109%2FICPCSN58827.2023.00036&partnerID=40&md5=5134f26d18311a790802b118153bd3a3" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85175243980&doi=10.1109%2fICPCSN58827.2023.00036&partnerID=40&md5=5134f26d18311a790802b118153bd3a3</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835032284-2 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource 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 Yasin W., CHRIST(Deemed to Be University), Department of Computer Science and Engineering, Karnataka, Bangalore, India; Harimoorthy K., CHRIST(Deemed to Be University), Department of Computer Science and Engineering, Karnataka, Bangalore, India; Vetriveeran D., CHRIST(Deemed to Be University), Department of Computer Science and Engineering, Karnataka, Bangalore, India 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 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 Identification of coronary artery stenosis based on hybrid segmentation and feature fusion Subject The topic of the resource Coronary artery disease; Keyframe extraction; stenosis; stenosis detection; X-ray angiography Description An account of the resource Coronary artery disease has been the utmost mutual heart disease in the past decades. Various research is going on to prevent this disease. Obstructive CAD occurs when one or more of the coronary arteries which supply blood to myocardium are narrowed owing to plaque build-up on the arteries inner walls, causing stenosis. The fundamental task required for the interpretation of coronary angiography is identification and quantification of severity of stenosis within the coronary circulation. Medical experts use X-ray coronary angiography to identify blood vessel/artery stenosis. Due to the artefact, the image has less clarity and it will be challenging for the medical expert to find the stenosis in the coronary artery. The solution to the problem a computational framework is proposed to segment the artery and spot the location of stenosis in the artery. Here the author presented an automatic method to detect stenosis from the X-ray angiogram image. A unified Computational method of Jerman, Level-set, fine-tuning the artery structure, is developed to extract the segmented artery features and detect the arterys stenosis. The current experimental outcomes illustrate that this computational method achieves average specificity, sensitivity, Accuracy, precision and F-scores of 95%, 97.5%, 98%, 97.5% and 97.5%, respectively. 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. Creator An entity primarily responsible for making the resource Kavipriya K.; Hiremath M. Source A related resource from which the described resource is derived Automatika, Vol-64, No. 3, pp. 622-633. Publisher An entity responsible for making the resource available Taylor and Francis Ltd. Date A point or period of time associated with an event in the lifecycle of the resource 2023-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1080/00051144.2023.2205727" target="_blank" rel="noreferrer noopener">https://doi.org/10.1080/00051144.2023.2205727</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85158025936&doi=10.1080%2F00051144.2023.2205727&partnerID=40&md5=c11d2756709585e2124c2f66717c98fb" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85158025936&doi=10.1080%2f00051144.2023.2205727&partnerID=40&md5=c11d2756709585e2124c2f66717c98fb</a> Rights Information about rights held in and over the resource All Open Access; Gold Open Access; Green Open Access Relation A related resource ISSN: 51144 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource 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 Kavipriya K., Department of Computer Science, Christ Deemed to be University, Bangalore, India; Hiremath M., Department of Computer Science, Christ Deemed to be University, Bangalore, India 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 A name given to the resource Identification of Cyberbullying and Finding Target User's Intention on Public Forums Subject The topic of the resource bag of words; cyberbullying; feature extraction; sentiment analysis; SVM Description An account of the resource Numerous cybercriminals are active in the online realm, carrying out cyber-crimes according to predetermined and preplanned agendas. Cyberbullying, which was formerly limited to physical limits, has now expanded online as a result of technology advancements. One type of cyberbullying is denigration or insult. The cyberbullying cases are in exponential rise in social media as per the reports of Computer Emergency Team by Sri Lanka. Insulting words are changeable in dynamic and the same terminology may have numerous meanings depending on the context. Bullying cannot be defined just because a statement comprises such a term. As a result, when classifying comments, standard keyword detecting approaches are insufficient. Other languages also may have dealt with this issue by utilizing lexical databases like WordNet, which might give synonyms as well as homonyms for words. Because no adequate lexical database mainly for the English language has been built, recognizing a word like bullying is difficult. As a result, employed rules to solve the problem. Facebook comments containing profanity were gathered, outliers were eliminated, and the remaining messages were pre-processed. Five feature extraction rules were employed to assess insult in the text. Following that, used the Support Vector Machine (SVM) technique. Using an F1-score of 85%, the findings demonstrate that when compared to existing works, SVM performs better. The focus on English language cyberbully identification, which has never been addressed earlier, distinguishes this study. 2023 IEEE. Creator An entity primarily responsible for making the resource Krishnasamy L.; Kiruthika M.; Manjunatha Swamy C.; Vigneshwaran T.; Sharon Roji Priya C.; Vijay Anand D. Source A related resource from which the described resource is derived Proceedings of International Conference on Contemporary Computing and Informatics, IC3I 2023, pp. 2152-2156. Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2023-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/IC3I59117.2023.10397967" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/IC3I59117.2023.10397967</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85186905081&doi=10.1109%2FIC3I59117.2023.10397967&partnerID=40&md5=a7c4692044c6a570d19b1b414d8111ed" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85186905081&doi=10.1109%2fIC3I59117.2023.10397967&partnerID=40&md5=a7c4692044c6a570d19b1b414d8111ed</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835030448-0 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource 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 Krishnasamy L., School of Engineering and Technology, Department of CSE, Christ University, Bengaluru, India; Kiruthika M., School of Computing, Department of Computational Intelligence, SRM Institute of Science and Technology, Tamilnadu, Kattankulathur, India; Manjunatha Swamy C., School of Engineering and Technology, Department of CSE, Christ University, Bengaluru, India; Vigneshwaran T., School of Engineering and Technology, Department of CSE, Christ University, Bengaluru, India; Sharon Roji Priya C., School of Engineering and Technology, Department of CSE, Christ University, Bengaluru, India; Vijay Anand D., Kongu Engineering College, Department of Information Technology, Erode, India 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 A name given to the resource Identification of Driver Drowsiness Detection using a Regularized Extreme Learning Machine Subject The topic of the resource Convolutional Neural Network (CNN); Extreme Learning Machine (ELM).; Regularized Extreme Learning Machine (RELM) Description An account of the resource In the field of accident avoidance systems, figuring out how to keep drivers from getting sleepy is a major challenge. The only way to prevent dozing off behind the wheel is to have a system in place that can accurately detect when a driver's attention has drifted and then alert and revive them. This paper presents a method for detection that makes use of image processing software to examine video camera stills of the driver's face. Driver inattention is measured by how much the eyes are open or closed. This paper introduces Regularized Extreme Learning Machine, a novel approach based on the structural risk reduction principle and weighted least squares, which is applied following preprocessing, binarization, and noise removal. Generalization performance was significantly improved in most cases using the proposed algorithm without requiring additional training time. This approach outperforms both the CNN and ELM models, with an accuracy of around 99% being achieved. 2023 IEEE. Creator An entity primarily responsible for making the resource Mohan R.; Chalasani S.; Suma Christal Mary S.; Chauhan A.; Parte S.A.; Anusuya S. Source A related resource from which the described resource is derived Proceedings of the 2023 2nd International Conference on Electronics and Renewable Systems, ICEARS 2023, pp. 1233-1238. Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2023-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ICEARS56392.2023.10085032" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICEARS56392.2023.10085032</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85153343063&doi=10.1109%2FICEARS56392.2023.10085032&partnerID=40&md5=b3bd2dd6b27b357c5f67e9587f586a21" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85153343063&doi=10.1109%2fICEARS56392.2023.10085032&partnerID=40&md5=b3bd2dd6b27b357c5f67e9587f586a21</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835034664-0 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource 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 Mohan R., Shri Ram Institute of Technology, Ece, Department, Madya Pradesh, Jabalpur, India; Chalasani S., Eluru Vatluru, Department of Computer Science and Engineering, Andhra Pradesh, India; Suma Christal Mary S., Panimalar Engineering College, Department of Information Technology, Tamilnadu, Chennai, India; Chauhan A., Deemed to Be University, Christ, Department of Life Sciences, Karnataka, Bengaluru, India; Parte S.A., Mits Gwalior, Department of Computer Science and Engineering, Madhya Pradesh, India; Anusuya S., K.Ramakrishnan College of Engineering, Department of Electronics and Communication Engineering, Tamilnadu, India 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 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 Identification of Dry Bean Varieties Based on Multiple Attributes Using CatBoost Machine Learning Algorithm Description An account of the resource Dry beans are the most widely grown edible legume crop worldwide, with high genetic diversity. Crop production is strongly influenced by seed quality. So, seed classification is important for both marketing and production because it helps build sustainable farming systems. The major contribution of this research is to develop a multiclass classification model using machine learning (ML) algorithms to classify the seven varieties of dry beans. The balanced dataset was created using the random undersampling method to avoid classification bias of ML algorithms towards the majority group caused by the unbalanced multiclass dataset. The dataset from the UCI ML repository is utilised for developing the multiclass classification model, and the dataset includes the features of seven distinct varieties of dried beans. To address the skewness of the dataset, a Box-Cox transformation (BCT) was performed on the dataset's attributes. The 22 ML classification algorithms have been applied to the balanced and preprocessed dataset to identify the best ML algorithm. The ML algorithm results have been validated with a 10-fold cross-validation approach, and during validation, the CatBoost ML algorithm achieved the highest overall mean accuracy of 93.8 percent, with a range of 92.05 percent to 95.35 percent. 2023 S. Krishnan et al. Creator An entity primarily responsible for making the resource Krishnan S.; Aruna S.K.; Kanagarathinam K.; Venugopal E. Source A related resource from which the described resource is derived Scientific Programming, Vol-2023 Publisher An entity responsible for making the resource available Hindawi Limited Date A point or period of time associated with an event in the lifecycle of the resource 2023-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1155/2023/2556066" target="_blank" rel="noreferrer noopener">https://doi.org/10.1155/2023/2556066</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85156220016&doi=10.1155%2F2023%2F2556066&partnerID=40&md5=949b253756a33dfb69fa2287bfe9d74a" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85156220016&doi=10.1155%2f2023%2f2556066&partnerID=40&md5=949b253756a33dfb69fa2287bfe9d74a</a> Rights Information about rights held in and over the resource All Open Access; Gold Open Access Relation A related resource ISSN: 10589244; CODEN: SCIPE Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource 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 Krishnan S., Department of EEE, Mahendra Engineering College (Autonomous), Tamil Nadu, Namakkal, India; Aruna S.K., Department of Computer Science and Engineering, School of Engineering and Technology, CHRIST, Deemed to Be University, Karnataka, Bangalore, India; Kanagarathinam K., Department of Electrical and Electronics Engineering, GMR Institute of Technology, Andhra Pradesh, Rajam, India; Venugopal E., Department of Electronics and Communication Engineering, School of Electrical Engineering and Computing, Adama Science and Technology University, Adama, Ethiopia 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 Faculty Publications 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/. Creator An entity primarily responsible for making the resource Tom, Praise; Jangam, Sasidhar; Raja, S.; Medar, Mutturaj H. Title A name given to the resource Identification of Dynamics of Tractor Chassis Structure through Ground Vibration Testing Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived International Journal of Vehicle Structures and Systems;Volume;17;Issue;5;pp.820-826 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.4273/ijvss.17.5.13" target="_blank" rel="noreferrer noopener">https://doi.org/10.4273/ijvss.17.5.13</a> <a href="https://www.scopus.com/pages/publications/105030580650?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105030580650?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Tom P., Dept. of Mech. and Automobile Engg., Christ University, Karnataka, Bengaluru, India; Jangam S., Dept. of Mech. and Automobile Engg., Christ University, Karnataka, Bengaluru, India; Raja S., Structural Tech. Division, CSIR National Aerospace Lab., Karnataka, Bengaluru, India; Medar M.H., Structural Tech. Division, CSIR National Aerospace Lab., Karnataka, Bengaluru, India Description An account of the resource This study investigates the vibrations arising from mass imbalance and variable inertia forces within dynamic systems, specifically focusing on agricultural tractors. Impulse test method is used to determine the modal characteristics of the tractors structure, including its frequencies, damping and mode shapes. The random responses of various components, such as the chassis, bonnet, muffler, seat and axle, were measured at engine speeds of 800, 1500 and 2500 rpm. The results indicate that the vibration amplitude depends on material properties and operational conditions, with the maximum random vibration response observed at the highest engine speed of 2500rpm. The overall root-mean-square acceleration (grms) was used to quantify vibration levels, revealing significant acceleration values of 2-4 grms across the entire tractor structure. Increased vibrations, particularly at high engine speeds, lead to amplified noise, dynamic stresses and accelerated wear on the chassis and subsystems, necessitating periodic maintenance and part replacements. The study also assessed the impact of road and field surface conditions on the vibration levels. The dynamic modes identified provide insights into potential improvements in tractor performance by implementing semiactive or active vibration control mechanisms utilizing smart materials without changing the existing engine dynamics. 2025. Carbon Magics Ltd. Subject The topic of the resource Impulse test method; Modal analysis; Multi-body dynamic systems; Structural dynamics Publisher An entity responsible for making the resource available Carbon Magics Ltd Relation A related resource ISSN: 9753060; Language A language of the resource English Type The nature or genre of the resource Article Rights Information about rights held in and over the resource All Open Access; Hybrid Gold Open Access Format The file format, physical medium, or dimensions of the resource online 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 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 Identification of emission-line stars in transition phase from pre-main sequence to main sequence Subject The topic of the resource Be; Methods: Statistical; Stars: Emission-line; Stars: Evolution; Techniques: Photometric Description An account of the resource Pre-main-sequence (PMS) stars evolve into main-sequence (MS) phase over a period of time. Interestingly, we found a scarcity of studies in existing literature that examine and attempt to better understand the stars in PMS to MS transition phase. The purpose of this study is to detect such rare stars, which we named as 'transition phase' (TP) candidates-stars evolving from the PMS to the MS phase. We identified 98 TP candidates using photometric analysis of a sample of 2167 classical Be (CBe) and 225 Herbig Ae/Be (HAeBe) stars. This identification is done by analysing the near-and mid-infrared excess and their location in the optical colour-magnitude diagram. The age and mass of 58 of these TP candidates are determined to be between 0.1-5 Myr and 2-10.5 M?, respectively. The TP candidates are found to possess rotational velocity and colour excess values in between CBe and HAeBe stars, which is reconfirmed by generating a set of synthetic samples using the machine learning approach. 2021 The Author(s) Published by Oxford University Press on behalf of Royal Astronomical Society. Creator An entity primarily responsible for making the resource Bhattacharyya S.; Mathew B.; Banerjee G.; Anusha R.; Paul K.T.; Kartha S.S. Source A related resource from which the described resource is derived Monthly Notices of the Royal Astronomical Society, Vol-507, No. 3, pp. 3660-3671. Publisher An entity responsible for making the resource available Oxford University Press Date A point or period of time associated with an event in the lifecycle of the resource 2021-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1093/mnras/stab2385" target="_blank" rel="noreferrer noopener">https://doi.org/10.1093/mnras/stab2385</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85117047692&doi=10.1093%2Fmnras%2Fstab2385&partnerID=40&md5=cca1db5c8e51b836edb732869aaec8c2" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85117047692&doi=10.1093%2fmnras%2fstab2385&partnerID=40&md5=cca1db5c8e51b836edb732869aaec8c2</a> Rights Information about rights held in and over the resource All Open Access; Green Open Access Relation A related resource ISSN: 358711; CODEN: MNRAA Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource 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 Bhattacharyya S., Department of Physics and Electronics, CHRIST (Deemed to Be University), Hosur Main Road, Bangalore, 560029, India; Mathew B., Department of Physics and Electronics, CHRIST (Deemed to Be University), Hosur Main Road, Bangalore, 560029, India; Banerjee G., Department of Physics and Electronics, CHRIST (Deemed to Be University), Hosur Main Road, Bangalore, 560029, India; Anusha R., Department of Physics and Electronics, CHRIST (Deemed to Be University), Hosur Main Road, Bangalore, 560029, India; Paul K.T., Department of Physics and Electronics, CHRIST (Deemed to Be University), Hosur Main Road, Bangalore, 560029, India; Kartha S.S., Department of Physics and Electronics, CHRIST (Deemed to Be University), Hosur Main Road, Bangalore, 560029, India 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 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 Identification of interstitial lung diseases using deep learning Subject The topic of the resource Classification; Deep learning; Medical image analysis; Neural network Description An account of the resource The advanced medical imaging provides various advantages to both the patients and the healthcare providers. Medical Imaging truly helps the doctor to determine the inconveniences in a human body and empowers them to make better choices. Deep learning has an important role in the medical field especially for medical image analysis today. It is an advanced technique in the machine learning concept which can be used to get efficient output than using any other previous techniques. In the anticipated work deep learning is used to find the presence of interstitial lung diseases (ILD) by analyzing high-resolution computed tomography (HRCT) images and identifying the ILD category. The efficiency of the diagnosis of ILD through clinical history is less than 20%. Currently, an open chest biopsy is the best way of confirming the presence of ILD. HRCT images can be used effectively to avoid open chest biopsy and improve accuracy. In this proposed work multi-label classification is done for 17 different categories of ILD. The average accuracy of 95% is obtained by extracting features with the help of a convolutional neural network (CNN) architecture called SmallerVGGNet. 2020 Institute of Advanced Engineering and Science. All rights reserved. Creator An entity primarily responsible for making the resource Raju N.; Anita H.B.; Augustine P. Source A related resource from which the described resource is derived International Journal of Electrical and Computer Engineering, Vol-10, No. 6, pp. 6283-6291. Publisher An entity responsible for making the resource available Institute of Advanced Engineering and Science Date A point or period of time associated with an event in the lifecycle of the resource 2020-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.11591/IJECE.V10I6.PP6283-6291" target="_blank" rel="noreferrer noopener">https://doi.org/10.11591/IJECE.V10I6.PP6283-6291</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85092283268&doi=10.11591%2FIJECE.V10I6.PP6283-6291&partnerID=40&md5=8753b56c556f202486500af7553ccf5e" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85092283268&doi=10.11591%2fIJECE.V10I6.PP6283-6291&partnerID=40&md5=8753b56c556f202486500af7553ccf5e</a> Rights Information about rights held in and over the resource All Open Access; Gold Open Access; Green Open Access Relation A related resource ISSN: 20888708 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource 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 Raju N., Department of Computer Science, CHRIST (Deemed to Be University), Bengaluru, Karnataka, 560029, India; Anita H.B., Department of Computer Science, CHRIST (Deemed to Be University), Bengaluru, Karnataka, 560029, India; Augustine P., Department of Computer Science, CHRIST (Deemed to Be University), Bengaluru, Karnataka, 560029, India 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 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 Identification of language in a cross linguistic environment Subject The topic of the resource Cross linguistic; Multilinguistic; Sentimental analysis Description An account of the resource World has become very small due to software internationationalism. Applications of machine translations are increasing day by day. Using multiple languages in the social media text is a developing trend. Availability of fonts in the native language enhanced the usage of native text in internet communications. Usage of transliterations of language has become quite common. In Indian scenario current generations are familiar to talk in native language but not to read and write in the native language, hence they started using English representation of native language in textual messages. This paper describes the identification of the transliterated text in cross lingual environment. In this paper a Neural network model identifies the prominent language in the text and hence the same can be used to identify the meaning of the text in the concerned language. The model is based upon Recurrent Neural Networks that found to be the most efficient in machine translations. Language identification can serve as a base for many applications in multi linguistic environment. Currently the South Indian Languages Malayalam, Tamil are identified from given text. An algorithmic approach of Stop words-based model is depicted in this paper. Model can be also enhanced to address all the Indian Languages that are in use. Copyright 2020 Institute of Advanced Engineering and Science. All rights reserved. Creator An entity primarily responsible for making the resource Thomas M.; Latha C.A.; Puthussery A. Source A related resource from which the described resource is derived Indonesian Journal of Electrical Engineering and Computer Science, Vol-18, No. 1, pp. 544-548. Publisher An entity responsible for making the resource available Institute of Advanced Engineering and Science Date A point or period of time associated with an event in the lifecycle of the resource 2019-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.11591/ijeecs.v18.i1.pp544-548" target="_blank" rel="noreferrer noopener">https://doi.org/10.11591/ijeecs.v18.i1.pp544-548</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85075585761&doi=10.11591%2Fijeecs.v18.i1.pp544-548&partnerID=40&md5=613c42f6e25c20331cc14cff1470040b" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85075585761&doi=10.11591%2fijeecs.v18.i1.pp544-548&partnerID=40&md5=613c42f6e25c20331cc14cff1470040b</a> Rights Information about rights held in and over the resource All Open Access; Gold Open Access; Green Open Access Relation A related resource ISSN: 25024752 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource 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 Thomas M., Regional Research Center, Visvesvaraya Technological University, India; Latha C.A., Department of (CSE), AMC Engineering College, Visvesvaraya Technological University, India; Puthussery A., Department of Science and Humanities, CHRIST (Deemed to be University), India 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 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 Identification of misconceptions about corona outbreak using trigrams and weighted TF-IDF model Subject The topic of the resource Coronavirus; Count Vectorizer; COVID-19; K-Nearest Neighbour; Logistic Regression; N-Grams; Nae Bayes; Random Forest; Support Vector Machine; TF-IDF Description An account of the resource Misconceptions of a particular issue like health, diseases, politics, government policies, epidemics and pandemics have been a social issue for a number of years, particularly after the advent of social media, and often spread faster than true truth. The engagement with social media like Twitter being one of the most prominent news outlets continuing is a major source of information today, particularly the information distributed around the network. In this paper, the efficacy of Misconception Detection System was tested on Corona Pandemic Dataset extracted from Twitter posts. A Trigram and a weighted TF-IDF Model followed by a supervised classifier were used for categorizing the dataset into two classes: one with misconceptions about COVID-19 virus and the other comprising correct and authenticated information. Trigrams were more reliable as the functional words related to coronavirus appeared more frequently in the corpus created. The proposed system using a combination of trigrams and weighted TF-IDF gave relevant and a normalized score leading to an efficient creation of vector space model and this has yielded good performance results when compared with traditional approaches using Bag of Words and Count Vectorizer technique where the vector space model was created only through word count. 2020, Institute of Advanced Scientific Research, Inc. All rights reserved. Creator An entity primarily responsible for making the resource Kokatnoor S.A.; Krishnan B. Source A related resource from which the described resource is derived Journal of Advanced Research in Dynamical and Control Systems, Vol-12, No. 5 Special Issue, pp. 524-533. Publisher An entity responsible for making the resource available Institute of Advanced Scientific Research, Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2020-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.5373/JARDCS/V12SP5/20201788" target="_blank" rel="noreferrer noopener">https://doi.org/10.5373/JARDCS/V12SP5/20201788</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85090681658&doi=10.5373%2FJARDCS%2FV12SP5%2F20201788&partnerID=40&md5=a1b09996ac6631dbadf79f79486f3628" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85090681658&doi=10.5373%2fJARDCS%2fV12SP5%2f20201788&partnerID=40&md5=a1b09996ac6631dbadf79f79486f3628</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 1943023X Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource 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 Kokatnoor S.A., Department of Computer Science and Engineering, School of Engineering and Technology, CHRIST (Deemed to be University), Bangalore, India; Krishnan B., Department of Computer Science and Engineering, School of Engineering and Technology, CHRIST (Deemed to be University), Bangalore, India 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 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 Identification of negative comments from positive sentences through data analysis Subject The topic of the resource R & python; Scoring; Sentiment analysis; Social media; Word cloud Description An account of the resource Social media has become a part, where people say what they think. It has made remarkable condition for individuals to impart their thoughts to the world. More consumers are writing their reviews which help people to make decisions about the quality and whether they should purchase the product. With respect to distinguishing perspectives out of this immense pool of conclusions, it turns into a laborious task and doing it physically is in every practical sense impossible. When we want to purchase things the best way to choose the finest product is to rely upon the opinions of others who already purchased those items. Sentiment analysis is utilized to choose whether the author's view is positive, negative, or neutral towards a specific item. This paper provides a review of apple mobile phone where we find polarity of a product based on scoring. We also worked on identifying negative comments in a positive sentence. We found the count of different polarity of words from overall positive feedbacks and stored the negative words so that we can identify which feature of the product is not acceptable and should be work with. We are representing our final result using wordcloud where we can detect which features has flaws. IAEME Publication. Creator An entity primarily responsible for making the resource Kedia M.; Das D. Source A related resource from which the described resource is derived International Journal of Mechanical Engineering and Technology, Vol-9, No. 3, pp. 644-654. Publisher An entity responsible for making the resource available IAEME Publication Date A point or period of time associated with an event in the lifecycle of the resource 2018-01-01 Identifier An unambiguous reference to the resource within a given context <a href="" target="_blank" rel="noreferrer noopener"></a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85044747870&partnerID=40&md5=39ba4bb35628ff4a9e1d92578b6b667a" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85044747870&partnerID=40&md5=39ba4bb35628ff4a9e1d92578b6b667a</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 9766340 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource 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 Kedia M., Department of Computer Science, Christ University, Bengaluru, India; Das D., Department of Computer Science, Christ University, Bengaluru, India