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The 3D interconnects offers the luxury for the designers to not worry on the wiring and instead optimize the design independently. The research attempts to model 3D wirings using novel composite materials including Carbon nanotubes with Copper, instead of traditional wiring material to facilitate SoC performance with better interconnect design. Assistive robotic devices development to a growing uncared population is considered highly beneficial. In IIIT-Bangalore, Dr. Madhav Rao along with his students are working on developing assistive devices for clinical trials, and building devices for surgical purposes. The assistive robotics research covers range of device development aiding in upper limb movement, regular lower limb ankle actuation to overcome deep vein thrombosis, and ventricular assistance to promote blood flow for weak heart.",{"EN":74},"Research highlights",{"VOID":76},"[]",{"VOID":78},"Awano Y, Sato S, Nihei M, Sakai T, Ohno Y, Mizutani T (2010) Carbon nanotubes for vlsi: interconnect and transistor applications. Proc IEEE 98(12):2015–2031\nAlam N, Kureshi A, Hasan M, Arslan T (2009) Carbon nanotube interconnects for low-power high-speed applications. In: IEEE international symposium on circuits and systems 2009. ISCAS 2009, pp 2273–2276, May\nRamm P, Wolf MJ, Klumpp A, Wieland R, Michel B, Reichi H (2008) Through silicon via processes and reliability for wafer-level 3d system integration. In: Proceedings of the electronic components and technology conference, pp 841–846\nKim DY, Kim J, Prabakar M, Jung Y (2016) Design of smart portable rehabilitation exoskeletal device for upper limb. In: 2016 32nd southern biomedical engineering conference (SBEC), March 2016, pp 134–134\nTripanpitak K, Tarvainen TVJ, Snmezisik I, Wu J, Yu W (2017) Design a soft assistive device for elbow movement training in peripheral nerve injuries. In: 2017 IEEE international conference on robotics and biomimetics (ROBIO), Dec 2017, pp 544–548\nSong R, Tong K, Hu X, Li L (2008) Assistive control system using continuous myoelectric signal in robot-aided arm training for patients after stroke. IEEE Trans Neural Syst Rehabilit Eng 16(4):371–379\nYonezawa T, Nomura K, Onodera T, Ichimura S, Mizoguchi H, Takemura H (2015) Evaluation of venous return in lower limb by passive ankle exercise performed by PHARAD. In: 2015 37th annual international conference of the IEEE engineering in medicine and biology society (EMBC), Milan, 2015, pp 3582–3585\nRachakorakit M, Charoensuk W (2017) Development of LeHab robot for human lower limb movement rehabilitation. In: 2017 10th biomedical engineering international conference (BMEiCON), Hokkaido, 2017, pp 1–5\nSen A et al (2016) Mechanical circulatory assist devices: a primer for critical care and emergency physicians. Crit Care 20(1):153\nPatel S, Nicholson L, Cassidy CJ, Wong KY-K (2016) Left ventricular assist device: a bridge to transplant or destination therapy? Postgrad Med J 92(1087):271–281\nHarris P, Kuppurao L (2012) Ventricular assist devices. Contin Educ Anaesth Crit Care Pain 12(3):145–151",{"VOID":80},"10.1007\u002Fs40012-019-00237-8","PUBLICATION","VERIFIED","2024-05-12T20:38:11.527+00:00","Auto Verify","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs40012-019-00237-8",[87],{"id":88,"sortIndex":21,"researcher":20,"roles":89,"affiliations":91,"properties":100,"displayName":102,"givenName":20,"familyName":20},"18abea8f-2565-4242-b1d1-e9fa2acc85f2",[90],"AUTHOR",[92],{"id":93,"sortIndex":21,"affiliation":94,"properties":20},"f1b057cf-ee68-40df-a18a-6be9b53ad72f",{"id":93,"createTime":20,"updateTime":20,"relativeEntities":95,"slug":20,"properties":96,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":99,"statistic":20},[],{"title":97},{"VI":98},"IIIT-Bangalore, Bangalore, India",[],{"title":101},{"VI":102},"Madhav Rao","ARTICLE",{"url":85,"publisher":105,"properties":119},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":106,"slug":10,"properties":107,"entityType":18,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":21,"subjectFields":111,"manageAffiliations":112,"indexDatabases":113,"url":20,"thumbnailPath":20,"statistic":114,"gsStatistic":20,"type":20,"analyzePriority":20},[],{"issn":108,"title":109,"eissn":110},{"VOID":13},{"EN":15},{"VOID":17},[],[],[],{"impactFactor":21,"impactFactorByYear":115,"i10Index":37,"i10IndexLast5Year":21,"totalPublication":38,"totalPublicationByYear":116,"totalCitation":43,"totalCitationByYear":117,"totalCitationPerPublication":51,"totalCitationPerPublicationByYear":118,"hindexLast5Year":42,"hindex":42},{"2014":27,"2015":28,"2016":29,"2017":30,"2018":31,"2019":32,"2020":33,"2021":34,"2022":35,"2023":36},{"2013":37,"2014":40,"2015":37,"2017":41,"2018":41,"2019":40,"2020":42,"2021":40,"2022":41,"2023":29},{"2013":45,"2014":46,"2015":47,"2017":48,"2018":49,"2019":29,"2020":47,"2021":29,"2022":50},{"2013":53,"2014":49,"2015":54,"2017":55,"2018":56,"2019":57,"2020":58,"2021":57,"2022":59},{"pages":120,"volume":122},{"VOID":121},"205-208",{"VOID":123},"7","2019-05-24",2019,"ERROR_IN_GET_PLATFORM_ID","2026-01-29T13:53:52.799+00:00",[],false,{"id":131,"createTime":132,"updateTime":133,"relativeEntities":134,"slug":135,"properties":136,"entityType":81,"verifyStatus":82,"verifyTime":147,"verifyNote":84,"languages":20,"translateLanguages":20,"viewCount":21,"primaryUrl":148,"fullTextUrl":20,"authors":149,"publicationType":103,"publisherRelationship":236,"citationCount":20,"citationInfo":20,"publishDate":255,"publishYear":125,"citationAnalyzeStatus":19,"lastCitationAnalyze":256,"indexDatabases":257,"openAccess":20,"references":20,"isForceReanalyzing":129},"b34eee7c-94f3-4e57-808c-19ca718d90c5","2024-02-05T23:45:12.167+00:00","2025-10-08T16:28:14.906+00:00",[],"Integrated-optic-devices-for-visible-light-communications",{"abstract":137,"title":139,"gsPaper":141,"references":143,"doi":145},{"EN":138},"Theoretical advances in visible light communications (VLC) are improving at a very fast pace. However, practical implementation is lagging because of the very high associated cost. Transmitter and receiver modules to work in these wavelengths are not suitable for communications as of now. This work aims to bridge the gap and design opto electronic devices which can be used in transmitter and receiver modules of VLC systems.",{"EN":140},"Integrated optic devices for visible light communications",{"VOID":142},"[\"13066724902178896433\"]",{"VOID":144},"Rashidi A, Monavarian M, Aragon A, Rishinaramangalam A, Feezell D (2018) Nonpolar \\({m}\\)-plane InGaN\u002FGaN micro-scale light-emitting diode with 1.5 GHz modulation bandwidth. IEEE Electron Device Lett 39(4):520–523\nCao Z, Shen L, Jiao Y, Zhao X, Koonen T (2017) 200 Gbps OOK transmission over an indoor optical wireless link enabled by an integrated cascaded aperture optical receiver. In optical fiber communications conference 2017. Optical Society of America",{"VOID":146},"10.1007\u002Fs40012-019-00234-x","2024-05-10T17:16:40.003+00:00","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs40012-019-00234-x",[150,167,180,195,218],{"id":151,"sortIndex":21,"researcher":20,"roles":152,"affiliations":153,"properties":162,"displayName":164,"givenName":20,"familyName":20},"bf818f3a-eecc-4937-ae9a-77623f9bd222",[90],[154],{"id":155,"sortIndex":21,"affiliation":156,"properties":20},"eb3fa1b2-0146-4047-af14-f7919b543d0b",{"id":155,"createTime":20,"updateTime":20,"relativeEntities":157,"slug":20,"properties":158,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":161,"statistic":20},[],{"title":159},{"VI":160},"ECE Department, MNIT, Jaipur, India",[],{"title":163,"gsAuthor":165},{"VI":164},"Ravi Kumar 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progressive web and computerized advancements have forced endless increment in the measure of visual data accessible to users. This trend prompted the advancement of exploration area where retrieval of images is done through the content of information which became familiar as CBIR (Content based image retrieval). CBIR frameworks are to a great extent utilized as a part of medicinal picture annotation, face recognition systems, security frameworks and so on. In this paper we will discuss about an efficient system for retrieving images faster since speed and precision are important as well as techniques to obtain better classification of images. To conquer the issue of extensive number of features extracted which obliges vast measure of memory and processing force we need to build a blend of 3 techniques(SURF, SVM and LDA) which best portray the information with adequate precision. Hence, we are using dimensionality reduction algorithm LDA in combination with SVM for the classification purpose and SURF which is quick and robust interest point detector.",{"EN":268},"Identification of pattern and obtainment of content based images: an ephemeral and swift approach",{"VOID":270},"Uijlings JRR, Smeulders AWM (2010) Real-time visual concept classification. IEEE Trans Multimed 12(7):665–681\nLong F, Zhang H, Feng DD (2003) Fundamentals of content-based image retrieval\nCaicedoa JC, Gonzáleza FA, Romero E (2011) Content-based histopathology image retrieval using a kernel based semantic annotation framework. J Biomed Inform 44(4):519–528\nWojnar A, Pinheiro AMG (2012) Annotation of medical images using the Surf descriptor. IEEE Trans Med Imag 30(3):130–134\nLowe DG (1999) Object recognition from local scale invariant features. In: Proceedings of the 7th IEEE international conference on computer vision, 1999, vol 2. IEEE, Kerkyra, pp 1150–1157\nBalakrishnama S, Ganapathiraju A (1998) Linear discriminant analysis—a brief tutorial. Institute for Signal and Information Processing Department of Electrical and Computer Engineering, Mississippi State University\nZhang Q, Izquierdo E (2013) Histology image retrieval in optimized multi feature spaces. IEEE J Biomed Health Inform 17(1):240–249\nZhang Bob, Vijaya Kumar BVK (2014) Detecting diabetes mellitus and non proliferative diabetic retinopathy using tongue color, texture, and geometry features. IEEE Trans Biomed Eng 61(2):491–501\nHui D, Yuan HD (2012) Research of image matching algorithm based on SURF features. In: International conference on computer science and information CSIP, 2012, IEEE, pp 1140–1143\nSingha M, Hemachandran K, Paul A (2012) Content-based image retrieval using the combination of the fast wavelet transformation and the colour histogram. IET Image Process 6(9):1221–1226\nChaisorn L, Fu Z (2011) A hybrid approach for image\u002Fvideo content representation and identification, IEEE, 2011\nAkakin HC, Gurcan MN (2012) Content based microscopic image retrieval system for multi image queries. In: IEEE transactions on information technology in biomedicine, vol 4, IEEE, pp 758–769\nZhang J, Zou W (2010) Content-based image retrieval using color and edge direction features, IEEE 2010\nTaur JS, Lee GH, Tao CW, Chen CC, Yang CW (2006) Segmentation of psoriasis vulgaris images using multiresolution based orthogonal subspace techniques. In: IEEE Transactions on systems, man, and cybernetics, Part B: cybernetics, vol 36, IEEE, pp 390–402\nShail K (2014) A survey of facial expression recognition methods. Int Org Sci Res IOSR J Eng (IOSRJEN) 04(04):1–5\nShaila SG, Vadivel A (2012) Block encoding of colour histogram for content based image retrieval applications. Proc Technol 6:526–533\nBay H, Ess A, Tuytelaars T, Van Gool L (2008) Speeded-up robust features (SURF). Computer Visual Image Understanding 110(3):346–359\nVelmurugan K, Baboo SS (2011) Content-based image retrieval using SURF and color moments\nGohK-S, Chang EY (2001) Using one-class and two-class SVMs for multiclass image annotation. IEEE Trans Knowl Data Eng 17(10):1333-1346, Glob J Comput Sci Technol 11(10) Version 1.0",{"VOID":272},"10.1007\u002Fs40012-016-0077-0","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs40012-016-0077-0",[275,290],{"id":276,"sortIndex":21,"researcher":20,"roles":277,"affiliations":278,"properties":287,"displayName":289,"givenName":20,"familyName":20},"eac78d04-402b-420b-b9e6-1cbb59c9b32f",[90],[279],{"id":280,"sortIndex":21,"affiliation":281,"properties":20},"4d0668c3-9610-45bf-806d-9d827066771f",{"id":280,"createTime":20,"updateTime":20,"relativeEntities":282,"slug":20,"properties":283,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":286,"statistic":20},[],{"title":284},{"VI":285},"Department of IT, Chandigarh Engineering College, Landran, Mohali, India",[],{"title":288},{"VI":289},"Hemjot Kaur Batra",{"id":291,"sortIndex":29,"researcher":20,"roles":292,"affiliations":293,"properties":300,"displayName":302,"givenName":20,"familyName":20},"0a10ff67-3d2a-4803-86a3-1290053c49d3",[90],[294],{"id":280,"sortIndex":21,"affiliation":295,"properties":20},{"id":280,"createTime":20,"updateTime":20,"relativeEntities":296,"slug":20,"properties":297,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":299,"statistic":20},[],{"title":298},{"VI":285},[],{"title":301},{"VI":302},"Amitabh Sharma",{"url":273,"publisher":304,"properties":318},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":305,"slug":10,"properties":306,"entityType":18,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":21,"subjectFields":310,"manageAffiliations":311,"indexDatabases":312,"url":20,"thumbnailPath":20,"statistic":313,"gsStatistic":20,"type":20,"analyzePriority":20},[],{"issn":307,"title":308,"eissn":309},{"VOID":13},{"EN":15},{"VOID":17},[],[],[],{"impactFactor":21,"impactFactorByYear":314,"i10Index":37,"i10IndexLast5Year":21,"totalPublication":38,"totalPublicationByYear":315,"totalCitation":43,"totalCitationByYear":316,"totalCitationPerPublication":51,"totalCitationPerPublicationByYear":317,"hindexLast5Year":42,"hindex":42},{"2014":27,"2015":28,"2016":29,"2017":30,"2018":31,"2019":32,"2020":33,"2021":34,"2022":35,"2023":36},{"2013":37,"2014":40,"2015":37,"2017":41,"2018":41,"2019":40,"2020":42,"2021":40,"2022":41,"2023":29},{"2013":45,"2014":46,"2015":47,"2017":48,"2018":49,"2019":29,"2020":47,"2021":29,"2022":50},{"2013":53,"2014":49,"2015":54,"2017":55,"2018":56,"2019":57,"2020":58,"2021":57,"2022":59},{"pages":319,"volume":321},{"VOID":320},"127-134",{"VOID":322},"3","2016-06-29",2016,[],{"id":327,"createTime":328,"updateTime":329,"relativeEntities":330,"slug":331,"properties":332,"entityType":81,"verifyStatus":82,"verifyTime":329,"verifyNote":84,"languages":20,"translateLanguages":20,"viewCount":21,"primaryUrl":341,"fullTextUrl":20,"authors":342,"publicationType":103,"publisherRelationship":403,"citationCount":20,"citationInfo":20,"publishDate":422,"publishYear":324,"citationAnalyzeStatus":19,"lastCitationAnalyze":20,"indexDatabases":423,"openAccess":20,"references":20,"isForceReanalyzing":129},"c239dc53-bdb7-43a7-b4d5-d42d69868ca7","2024-01-16T06:47:38.150+00:00","2025-02-26T07:16:39.215+00:00",[],"Secure-route-discovery-in-AODV-in-presence-of-blackhole-attack",{"abstract":333,"title":335,"references":337,"doi":339},{"EN":334},"In recent years, there has been tremendous increase in mobile adhoc networks applications ranging from military and rescue operations to collaborative and distributed computing, therefore secure data transmission has become one of the critical issue in MANET. A mobile adhoc network is genrally established without relying on centralized and dedicated servers. Attackers exploit the loopholes of route discovery process to carry out their malicious intent as it is an inevitable process in reactive protocols. Blackhole is one such popular attack that sends forged routing information to fool source node and drops all the data packets after introducing itself in the route between source node to destination. In this paper, damage caused to AODV in presence of blackhole node has been evaluated and solution to defend against blackhole attack has been proposed and simulated on Ns-2 to prove its efficiency and reliability. The packet processing technique of normal AODV is enhanced to detect routing misbehavior and alert other nodes using default AODV control message, HELLO messages to reduce additional overhead.",{"EN":336},"Secure route discovery in AODV in presence of blackhole attack",{"VOID":338},"Kumar MJ, Rajesh RS (2009) Performance analysis of MANET routing protocols in different mobility models. Proc Int J Comput Sci Netw Secur IJCSNS 9(2):22–29\nBoukerche A, Turgut B, Aydin N, Ahmad MZ, Boloni L, Turgut D (2011) Routing protocols in ad hoc networks: a survey. Comput Netw 55(13):3032–3080\nCarvalho and Marco (2008) Security in mobile ad hoc networks. Secur Priv IEEE 6(2):72–75\nBhatia T, Verma AK (2013) Security issues in MANET: a survey on attacks and defense mechanisms. Int J Adv Res Comput Sci Softw Eng 3(6):1382–1394\nJhaveri RH, Patel SJ, Jinwala DC (2012) Dos attacks in mobile ad hoc networks: a survey. In: 2012 second international conference on advanced computing and communication technologies (ACCT), IEEE, pp 535–541\nDong D, Li M, Liu Y, Li XY, Liao X (2011) Topological detection on wormholes in wireless ad hoc and sensor networks. IEEE\u002FACM Trans Netw 19(6):1787–1796\nSharma G, Bala S, Verma AK, Tej S (2010) Security in wireless sensor networks using frequency hopping. Int J Comput Appl (0975–8887) 12(6):1–5\nMarti S, Giuli TJ, Lai K, Baker M (2000) Mitigating routing misbehavior in mobile ad hoc networks. In: Proceedings of 6th annual international conference on mobile computing and networking, pp 255–265\nAlem YF, Xuan ZC (2010) Preventing black hole attack in mobile ad-hoc networks using anomaly detection. In: 2010 2nd international conference on future computer and communication (ICFCC), vol 3, 21–24 May 2010, pp V3-672–V3-676\nHimral L, Vig V, Chand N (2011) Preventing AODV routing protocol from black hole attack. Int J Eng Sci Technol 3(5):3927–3932\nTamilselvan L, Sankaranarayanan V (2007) Prevention of blackhole attack in MANET. Paper presented at the 2nd international conference on wireless broadband and ultra wideband communications, Sydney, Australia, 27–30 Aug 2007\nKozma W, Lazos L (2009) REAct: resource-efficient accountability for node misbehavior in ad hoc networks based on random audits. Paper presented at the second ACM conference on wireless network security, Zurich, Switzerland, 16–18 Mar 2009\nMin Z, Jiliu Z (2009) Cooperative black hole attack prevention for mobile ad hoc networks. In: International symposium on information engineering and electronic commerce, IEEC ‘09, 16–17 May 2009, pp 26–30\nSu M-Y (2011) Prevention of selective black hole attacks on mobile ad hoc networks through intrusion detection systems. Comput Commun 34(1):107–117\nPerkins C, Royer E, Das S (2003) Ad hoc on-demand distance vector (AODV) routing. In: IETF, RFC 3561\nKumar S, Sharma SC, Suman B (2011) Classification and evaluation of mobility metrics for mobility model movement patterns in mobile ad-hoc networks. Int J Appl Graph Theory Wirel Ad Hoc Netw Sens Netw 3(3):25\nUsha and Bose (2012) Understanding black hole attack in MANET. Eur J Sci Res 83(3):383–396\nMadhusudhananagakumar KS, Aghila G (2011) A survey on black hole attacks on AODV Protocol in MANET. Int J Comput Appl 34(5):23–30\nFall K, Varadhan K (eds) (2013) ns notes and documentation, 1999. Accessed on 14 Mar 2013\nCamp T, Boleng J, Davies V (2002) A survey of mobility models for ad hoc network research. Wirel Commun Mob Comput Spec Issue Mobile Ad Hoc Netw Res Trends Appl 2(5):483–502",{"VOID":340},"10.1007\u002Fs40012-016-0075-2","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs40012-016-0075-2",[343,358,373,388],{"id":344,"sortIndex":21,"researcher":20,"roles":345,"affiliations":346,"properties":355,"displayName":357,"givenName":20,"familyName":20},"3f460cad-9636-4bbe-9c22-860b6880682a",[90],[347],{"id":348,"sortIndex":21,"affiliation":349,"properties":20},"45dd49ff-02fa-471b-a30b-5f4ba8f2cc30",{"id":348,"createTime":20,"updateTime":20,"relativeEntities":350,"slug":20,"properties":351,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":354,"statistic":20},[],{"title":352},{"VI":353},"Panipat Institute of Engineering and Technology, Panipat, India",[],{"title":356},{"VI":357},"Jaspal Kumar",{"id":359,"sortIndex":29,"researcher":20,"roles":360,"affiliations":361,"properties":370,"displayName":372,"givenName":20,"familyName":20},"94ff7943-9a2b-4786-a6a0-9b7582223af1",[90],[362],{"id":363,"sortIndex":21,"affiliation":364,"properties":20},"be54af3c-e45d-4e8a-8d4c-ae98afdfffe6",{"id":363,"createTime":20,"updateTime":20,"relativeEntities":365,"slug":20,"properties":366,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":369,"statistic":20},[],{"title":367},{"VI":368},"National Institute of Technology, Surathkal, India",[],{"title":371},{"VI":372},"M. Kulkarni",{"id":374,"sortIndex":40,"researcher":20,"roles":375,"affiliations":376,"properties":385,"displayName":387,"givenName":20,"familyName":20},"dfa6211f-965e-42b5-bd8c-f93bd89634b5",[90],[377],{"id":378,"sortIndex":21,"affiliation":379,"properties":20},"125a39aa-a7b1-4fc7-b64c-a32607ff0d15",{"id":378,"createTime":20,"updateTime":20,"relativeEntities":380,"slug":20,"properties":381,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":384,"statistic":20},[],{"title":382},{"VI":383},"Delhi College of Engineering, University of Delhi, New Delhi, India",[],{"title":386},{"VI":387},"Daya Gupta",{"id":389,"sortIndex":37,"researcher":20,"roles":390,"affiliations":391,"properties":400,"displayName":402,"givenName":20,"familyName":20},"c8b75739-86e9-4f46-a437-dbbeaa049b2a",[90],[392],{"id":393,"sortIndex":21,"affiliation":394,"properties":20},"069c65e2-9dd2-4f59-a7d6-a27f21988115",{"id":393,"createTime":20,"updateTime":20,"relativeEntities":395,"slug":20,"properties":396,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":399,"statistic":20},[],{"title":397},{"VI":398},"Delhi Technological University, New Delhi, India",[],{"title":401},{"VI":402},"S. Indu",{"url":341,"publisher":404,"properties":418},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":405,"slug":10,"properties":406,"entityType":18,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":21,"subjectFields":410,"manageAffiliations":411,"indexDatabases":412,"url":20,"thumbnailPath":20,"statistic":413,"gsStatistic":20,"type":20,"analyzePriority":20},[],{"issn":407,"title":408,"eissn":409},{"VOID":13},{"EN":15},{"VOID":17},[],[],[],{"impactFactor":21,"impactFactorByYear":414,"i10Index":37,"i10IndexLast5Year":21,"totalPublication":38,"totalPublicationByYear":415,"totalCitation":43,"totalCitationByYear":416,"totalCitationPerPublication":51,"totalCitationPerPublicationByYear":417,"hindexLast5Year":42,"hindex":42},{"2014":27,"2015":28,"2016":29,"2017":30,"2018":31,"2019":32,"2020":33,"2021":34,"2022":35,"2023":36},{"2013":37,"2014":40,"2015":37,"2017":41,"2018":41,"2019":40,"2020":42,"2021":40,"2022":41,"2023":29},{"2013":45,"2014":46,"2015":47,"2017":48,"2018":49,"2019":29,"2020":47,"2021":29,"2022":50},{"2013":53,"2014":49,"2015":54,"2017":55,"2018":56,"2019":57,"2020":58,"2021":57,"2022":59},{"pages":419,"volume":421},{"VOID":420},"91-98",{"VOID":322},"2016-04-25",[],{"id":425,"createTime":426,"updateTime":427,"relativeEntities":428,"slug":429,"properties":430,"entityType":81,"verifyStatus":82,"verifyTime":427,"verifyNote":84,"languages":20,"translateLanguages":20,"viewCount":21,"primaryUrl":439,"fullTextUrl":20,"authors":440,"publicationType":103,"publisherRelationship":471,"citationCount":20,"citationInfo":20,"publishDate":491,"publishYear":492,"citationAnalyzeStatus":19,"lastCitationAnalyze":20,"indexDatabases":493,"openAccess":20,"references":20,"isForceReanalyzing":129},"4b731346-bf0b-4374-b4c3-7dab9a1909fd","2024-01-11T01:47:02.472+00:00","2025-02-26T02:06:11.380+00:00",[],"Imprecise-reversible-visible-watermarking",{"abstract":431,"title":433,"references":435,"doi":437},{"EN":432},"Using the program visible digital, a perceptible watermark is added to an image to prevent illicit use of multimedia content and to provide copyright and copy protection for the author. There are numerous applications that require user authentication to make the original image content available. If the original image is recovered from the watermarked image successfully, then the scheme is said to be a reversible watermarking scheme. However, most of the reversible visible watermarking schemes found in the current literature do not preserve visual quality of image. In this investigation, we propose a novel reversible and visible watermarking method that is suitable for both grey and colour images. In our approach, we use the complex mapping of pixels via embedding combined with a scaling factor derived from the contrast-sensitive function of the original image. We then prove experimentally that our scheme is advantageous over the previous works in this field. Furthermore, we compare the performance of proposed work with other state-of-the-art under various parameters.",{"EN":434},"Imprecise reversible visible watermarking",{"VOID":436},"Mintzer F, Braudaway GW, Yeung MM (1997) Effective and ineffective digital watermarks. In: Proceeding of international conference on image processing, vol 3\nMohanty SP, Ramakrishnan KR, Kankanhalli MS (2000) A dct domain visible watermarking technique for images. In: Proceeding of IEEE conference on multimedia and expo, vol 2, pp 1029–1032\nHuang CH, Wu JL (2004) Attacking visible watermarking schemes. IEEE Trans Multime´d 6(1):16–30\nBertalmio M, Sapiro G, Caselles V, Ballester C (2000) Image inpainting. In: Proceedings of the 27th annual conference SIGGRAPH, pp 417–424\nFridrich J, Goljan M, Du R (2002) Lossless data embedding new paradigm in digital watermarking, in EURASIP. J Appl Signal Process 2:185–196\nTian J (2003) Reversible data embedding using a difference expansion. IEEE Trans Circuits Syst Video Technol 13(8):890–896\nNi Z, Shi YQ, Ansari N, Su W (2006) Reversible data hiding. IEEE Trans Circuits Syst Video Technol 16(3):354–362\nHuang BB, Tang SX (2006) A contrast-sensitive visible watermarking scheme. IEEE Trans Multime´d 13(2):60–66\nHu Y, Kwong S, Huang J (2006) An algorithm for removable visible watermarking. IEEE Trans Circuits Syst Video Technol 16(1):129–133\nYang Y, Sun X, Yang H, Li C-T (2008) Removable visible image watermarking algorithm in the discrete cosine transform domain. J Electron Imaging 17(3):1–11\nYang Y, Sun X, Yang H, Li C-T, Xiao R (2009) A contrast-sensitive reversible visible image watermarking technique. IEEE Trans Circuits Syst Video Technol 19(5):656–666\nHu Y, Jeon B (2006) Reversible visible watermarking and lossless recovery of original images. IEEE Trans Circuits Syst Video Technol 16(11):1423–1429\nYip SK, Au PC, Ho CW, Wong HM (2006) Lossless visible watermarking. In: Proceeding of IEEE international conference on multimedia expo, Toronto, Canada, pp 853–856\nTsai HM, Chang LW (2007) A high secure reversible visible watermarking scheme. In: Proceeding of IEEE multimedia expo, Beijing, China, pp 2106–2109\nFarrugia RA (2010) A reversible visible watermarking scheme for compressed images. In: Proceeding of IEEE international conference. MELECON, Valletta, Malta\nHuang BB, Tang SX (2006) A contrast-sensitive visible watermarking scheme. IEEE Trans Multime´d 13(2):60–67\nXuan G, Chen J, Zhu J, Shi YQ, Ni Z, Su W (2002) Lossless data hiding based on integer wavelet transform. In: IEEE workshop on multimedia signal processing, pp 312–315\nLiu TY, Tsai WH (2010) Generic lossless visible watermarking—a new approach. IEEE Trans Image Process 19(5):1224–1235\nVenkata ND, Kite TD, Geisler WS, Ivons BL, Bovik AC (2000) Image quality assessment based on degradation model. IEEE Trans Image Process 9(4):636–650\nWang Z, Bovik AC, Sheikh HR, Simoncelli EP (2004) Image quality assessment: from error visibility to structure similarity. IEEE Trans Image Process 13(4):600–612\nKalker T, Willems FMJ (2002) Capacity bounds and constructions for reversible data-hiding. Digital Signal Processing 1:71–76. doi:10.1109\u002FICDSP.2002.1027818\nMintzer F, Lotspiech J, Morimoto N, Heights Y, Almaden T (1997) Safeguarding digital library contents and users. D-Lib Magazine\nAlattar AM (2004) Reversible watermarking using the difference expansion of a generalized integer transform. IEEE Trans Image Process 13(8):1147–1156",{"VOID":438},"10.1007\u002Fs40012-013-0031-3","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs40012-013-0031-3",[441,456],{"id":442,"sortIndex":21,"researcher":20,"roles":443,"affiliations":444,"properties":453,"displayName":455,"givenName":20,"familyName":20},"935fcd9a-68fa-4952-b345-7047bdf99eab",[90],[445],{"id":446,"sortIndex":21,"affiliation":447,"properties":20},"b257c190-0e01-423d-ba8b-17adcc5ae91d",{"id":446,"createTime":20,"updateTime":20,"relativeEntities":448,"slug":20,"properties":449,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":452,"statistic":20},[],{"title":450},{"VI":451},"Department of Electronics, SATI, Vidisha, India",[],{"title":454},{"VI":455},"Neelesh Mehra",{"id":457,"sortIndex":29,"researcher":20,"roles":458,"affiliations":459,"properties":468,"displayName":470,"givenName":20,"familyName":20},"e69807d9-1314-4d90-8d37-0b23a9225509",[90],[460],{"id":461,"sortIndex":21,"affiliation":462,"properties":20},"4a172d41-a706-41b6-a223-37e83719b3ac",{"id":461,"createTime":20,"updateTime":20,"relativeEntities":463,"slug":20,"properties":464,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":467,"statistic":20},[],{"title":465},{"VI":466},"Department of Electronics, MANIT, Bhopal, India",[],{"title":469},{"VI":470},"Madhu Shandilya",{"url":439,"publisher":472,"properties":486},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":473,"slug":10,"properties":474,"entityType":18,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":21,"subjectFields":478,"manageAffiliations":479,"indexDatabases":480,"url":20,"thumbnailPath":20,"statistic":481,"gsStatistic":20,"type":20,"analyzePriority":20},[],{"issn":475,"title":476,"eissn":477},{"VOID":13},{"EN":15},{"VOID":17},[],[],[],{"impactFactor":21,"impactFactorByYear":482,"i10Index":37,"i10IndexLast5Year":21,"totalPublication":38,"totalPublicationByYear":483,"totalCitation":43,"totalCitationByYear":484,"totalCitationPerPublication":51,"totalCitationPerPublicationByYear":485,"hindexLast5Year":42,"hindex":42},{"2014":27,"2015":28,"2016":29,"2017":30,"2018":31,"2019":32,"2020":33,"2021":34,"2022":35,"2023":36},{"2013":37,"2014":40,"2015":37,"2017":41,"2018":41,"2019":40,"2020":42,"2021":40,"2022":41,"2023":29},{"2013":45,"2014":46,"2015":47,"2017":48,"2018":49,"2019":29,"2020":47,"2021":29,"2022":50},{"2013":53,"2014":49,"2015":54,"2017":55,"2018":56,"2019":57,"2020":58,"2021":57,"2022":59},{"pages":487,"volume":489},{"VOID":488},"355-365",{"VOID":490},"1","2013-12-17",2013,[],{"id":495,"createTime":496,"updateTime":497,"relativeEntities":498,"slug":499,"properties":500,"entityType":81,"verifyStatus":82,"verifyTime":497,"verifyNote":84,"languages":509,"translateLanguages":20,"viewCount":21,"primaryUrl":511,"fullTextUrl":20,"authors":512,"publicationType":103,"publisherRelationship":532,"citationCount":21,"citationInfo":547,"publishDate":550,"publishYear":548,"citationAnalyzeStatus":19,"lastCitationAnalyze":20,"indexDatabases":551,"openAccess":20,"references":552,"isForceReanalyzing":129},"d587f74a-4d78-4197-b482-8391c9a07c6c","2024-04-12T02:31:30.591+00:00","2025-02-25T18:54:43.509+00:00",[],"Smart-residential-electricity-distribution-system-SREDS-for-demand-response-under-smart-grid-environment",{"openalex":501,"mag":503,"title":505,"doi":507},{"VOID":502},"W2986222272",{"VOID":504},"2986222272",{"EN":506},"Smart residential electricity distribution system (SREDS) for demand response under smart grid environment",{"VOID":508},"10.1007\u002Fs40012-019-00259-2",[510],"EN","http:\u002F\u002Flink.springer.com\u002F10.1007\u002Fs40012-019-00259-2",[513],{"id":514,"sortIndex":21,"researcher":20,"roles":515,"affiliations":516,"properties":525,"displayName":529,"givenName":20,"familyName":20},"949a268d-74e6-4b7b-98c1-e2e2ef648d4d",[],[517],{"id":518,"sortIndex":21,"affiliation":519,"properties":20},"fd1add61-41df-4663-b303-8ee02b2e5237",{"id":518,"createTime":20,"updateTime":20,"relativeEntities":520,"slug":20,"properties":521,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":524,"statistic":20},[],{"title":522},{"VI":523},"National Institute of Technology Tiruchirappalli, Tiruchirappalli, India",[],{"orcid":526,"title":528,"openalex":530},{"VOID":527},"https:\u002F\u002Forcid.org\u002F0000-0001-9629-7256",{"EN":529},"M. 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IEEE Commun Surv Tutor 14(4):944–980",{"doi":556},"10.1109\u002FSURV.2011.101911.00087",{"id":20,"text":558,"url":20,"identifiers":559},"Collotta M, Pau G (2015) A novel energy management approach for smart homes using bluetooth low energy. IEEE J Sel Areas Commun 33(12):2988–2996",{"doi":560},"10.1109\u002FJSAC.2015.2481203",{"id":20,"text":562,"url":20,"identifiers":563},"Wang P, Ye F, Chen X (2018) A smart home gateway platform for data collection and awareness. IEEE Commun Mag 56(9):87–93",{"doi":564},"10.1109\u002FMCOM.2018.1701217",{"id":20,"text":566,"url":20,"identifiers":567},"Balijepalli VSKM, Pradhan V, Khaparde SA, Shereef RM (2011) Review of demand response under smart grid paradigm. In: Proceedings of ISGT2011-India, pp 236–243",{},{"id":20,"text":569,"url":20,"identifiers":570},"Costanzo GT, Zhu G, Anjos MF, Savard G (2012) A system architecture for autonomous demand side load management in smart buildings. IEEE Trans Smart Grid 3(4):2157–2165",{"doi":571},"10.1109\u002FTSG.2012.2217358",{"id":20,"text":573,"url":20,"identifiers":574},"Pipattanasomporn M, Kuzlu M, Rahman S (2012) An algorithm for intelligent home energy management and demand response analysis. IEEE Trans Smart Grid 3(4):2166–2173",{"doi":575},"10.1109\u002FTSG.2012.2201182",{"id":20,"text":577,"url":20,"identifiers":578},"Adika CO, Wang L (2014) Autonomous appliance scheduling for household energy management. IEEE Trans Smart Grid 5(2):673–682",{"doi":579},"10.1109\u002FTSG.2013.2271427",{"id":20,"text":581,"url":20,"identifiers":582},"Wang C, Zhou Y, Jiao B, Wang Y, Liu W, Wang D (2015) Robust optimization for load scheduling of a smart home with photovoltaic system. Energy Convers Manag 102:247–257",{"doi":583},"10.1016\u002Fj.enconman.2015.01.053",{"id":20,"text":585,"url":20,"identifiers":586},"Mohsenian-Rad A-H, Wong VWS, Jatskevich J, Schober R, Leon-Garcia A (2010) Autonomous demand-side management based on game-theoretic energy consumption scheduling for the future smart grid. IEEE Trans Smart Grid 1(3):320–331",{"doi":587},"10.1109\u002FTSG.2010.2089069",{"id":20,"text":589,"url":20,"identifiers":590},"Wang Y, Saad W, Han Z, Poor HV, Basar T (2014) A game-theoretic approach to energy trading in the smart grid. IEEE Trans Smart Grid 5(3):1439–1450",{"doi":591},"10.1109\u002FTSG.2013.2284664",{"id":20,"text":593,"url":20,"identifiers":594},"Chen H, Li Y, Louie RHY, Vucetic B (2014) Autonomous demand side management based on energy consumption scheduling and instantaneous load billing: an aggregative game approach. IEEE Trans Smart Grid 5(4):1744–1754",{"doi":595},"10.1109\u002FTSG.2014.2311122",{"id":20,"text":597,"url":20,"identifiers":598},"Chai B, Chen J, Yang Z, Zhang Y (2014) Demand response management with multiple utility companies: a two-level game approach. IEEE Trans Smart Grid 5(2):722–731",{"doi":599},"10.1109\u002FTSG.2013.2295024",{"id":20,"text":601,"url":20,"identifiers":602},"Maharjan S, Zhu Q, Zhang Y, Gjessing S, Basar T (2013) Dependable demand response management in the smart grid: a stackelberg game approach. IEEE Trans Smart Grid 4(1):120–132",{"doi":603},"10.1109\u002FTSG.2012.2223766",{"id":20,"text":605,"url":20,"identifiers":606},"Nekouei E, Alpcan T, Chattopadhyay D (2015) Game-theoretic frameworks for demand response in electricity markets. IEEE Trans Smart Grid 6(2):748–758",{"doi":607},"10.1109\u002FTSG.2014.2367494",{"id":20,"text":609,"url":20,"identifiers":610},"Tushar W, Zhang JA, Smith DB, Poor HV, Thiebaux S (2014) Prioritizing consumers in smart grid: a game theoretic approach. IEEE Trans Smart Grid 5(3):1429–1438",{"doi":611},"10.1109\u002FTSG.2013.2293755",{"id":20,"text":613,"url":20,"identifiers":614},"Deng R, Yang Z, Chen J, Asr NR, Chow M-Y (2014) Residential energy consumption scheduling: a coupled-constraint game approach. IEEE Trans Smart Grid 5(3):1340–1350",{"doi":615},"10.1109\u002FTSG.2013.2287494",{"id":20,"text":617,"url":20,"identifiers":618},"La QD, Chan YWE, Soong B-H (2016) Power management of intelligent buildings facilitated by smart grid: a market approach. IEEE Trans Smart Grid 7(3):1389–1400",{"doi":619},"10.1109\u002FTSG.2015.2477852",{"id":20,"text":621,"url":20,"identifiers":622},"Arun SL, Selvan MP (2017) Dynamic demand response in smart buildings using an intelligent residential load management system. IET Gener Transm Distrib 11(17):4348–4357",{"doi":623},"10.1049\u002Fiet-gtd.2016.1789",{"id":625,"createTime":626,"updateTime":627,"relativeEntities":628,"slug":629,"properties":630,"entityType":81,"verifyStatus":82,"verifyTime":627,"verifyNote":84,"languages":639,"translateLanguages":20,"viewCount":21,"primaryUrl":640,"fullTextUrl":20,"authors":641,"publicationType":103,"publisherRelationship":676,"citationCount":41,"citationInfo":691,"publishDate":694,"publishYear":692,"citationAnalyzeStatus":695,"lastCitationAnalyze":696,"indexDatabases":697,"openAccess":20,"references":698,"isForceReanalyzing":129},"843df0a4-680a-44c1-b3f6-e7e53f7c85d5","2024-04-14T08:18:18.473+00:00","2025-02-24T20:25:48.063+00:00",[],"Role-of-Plant-Clinics-in-addressing-pest-and-disease-management",{"openalex":631,"mag":633,"title":635,"doi":637},{"VOID":632},"W2891528629",{"VOID":634},"2891528629",{"EN":636},"Role of Plant Clinics in addressing pest and disease management",{"VOID":638},"10.1007\u002Fs40012-018-0210-3",[510],"http:\u002F\u002Flink.springer.com\u002F10.1007\u002Fs40012-018-0210-3",[642,661],{"id":643,"sortIndex":21,"researcher":20,"roles":644,"affiliations":645,"properties":654,"displayName":658,"givenName":20,"familyName":20},"45eaa40a-bf43-499d-ae68-40a22314ec47",[],[646],{"id":647,"sortIndex":21,"affiliation":648,"properties":20},"47fb0dbe-7aec-43a4-8914-dfae4cc75df6",{"id":647,"createTime":20,"updateTime":20,"relativeEntities":649,"slug":20,"properties":650,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":653,"statistic":20},[],{"title":651},{"VI":652},"Information Education and Communication, M S Swaminathan Research Foundation, Taramani, Chennai, India",[],{"orcid":655,"title":657,"openalex":659},{"VOID":656},"https:\u002F\u002Forcid.org\u002F0000-0001-7096-7901",{"EN":658},"R. Rajkumar",{"VOID":660},"A5058471889",{"id":662,"sortIndex":29,"researcher":20,"roles":663,"affiliations":664,"properties":671,"displayName":673,"givenName":20,"familyName":20},"79cdeb67-6e51-4b92-9e9c-79196413ee41",[],[665],{"id":647,"sortIndex":21,"affiliation":666,"properties":20},{"id":647,"createTime":20,"updateTime":20,"relativeEntities":667,"slug":20,"properties":668,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":670,"statistic":20},[],{"title":669},{"VI":652},[],{"title":672,"openalex":674},{"EN":673},"Nancy J. Anabel",{"VOID":675},"A5072619622",{"url":20,"publisher":677,"properties":20},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":678,"slug":10,"properties":679,"entityType":18,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":21,"subjectFields":683,"manageAffiliations":684,"indexDatabases":685,"url":20,"thumbnailPath":20,"statistic":686,"gsStatistic":20,"type":20,"analyzePriority":20},[],{"issn":680,"title":681,"eissn":682},{"VOID":13},{"EN":15},{"VOID":17},[],[],[],{"impactFactor":21,"impactFactorByYear":687,"i10Index":37,"i10IndexLast5Year":21,"totalPublication":38,"totalPublicationByYear":688,"totalCitation":43,"totalCitationByYear":689,"totalCitationPerPublication":51,"totalCitationPerPublicationByYear":690,"hindexLast5Year":42,"hindex":42},{"2014":27,"2015":28,"2016":29,"2017":30,"2018":31,"2019":32,"2020":33,"2021":34,"2022":35,"2023":36},{"2013":37,"2014":40,"2015":37,"2017":41,"2018":41,"2019":40,"2020":42,"2021":40,"2022":41,"2023":29},{"2013":45,"2014":46,"2015":47,"2017":48,"2018":49,"2019":29,"2020":47,"2021":29,"2022":50},{"2013":53,"2014":49,"2015":54,"2017":55,"2018":56,"2019":57,"2020":58,"2021":57,"2022":59},{"total":41,"publishYear":692,"statisticByYear":693},2018,{"2019":40,"2023":37},"2018-12-01","ERROR_IN_ANALYZE_CITATION","2024-04-14T20:15:38.033+00:00",[],[699,702,705,709,712,715,719],{"id":20,"text":700,"url":20,"identifiers":701},"Swaminathan M, Baksi S (ed) (2017) How do small farmers fare? Evidence from village studies in India",{},{"id":20,"text":703,"url":20,"identifiers":704},"Prakash A, Rao J, Mukherjee AK, Berliner J, Pokhare SS, Adak T, Munda S, Shashank PR (2014) Climate change: impact on crop pests. Applied Zoologists Research Association (AZRA) Central Rice Research Institute, Cuttack",{},{"id":20,"text":706,"url":20,"identifiers":707},"Smith JJ, Waage J, Woodhall JW, Bishop SJ, Spence NJ (2008) The challenge of providing plant pest diagnostic services for Africa. Eur J Plant Pathol 121(3):365–375",{"doi":708},"10.1007\u002Fs10658-008-9311-4",{"id":20,"text":710,"url":20,"identifiers":711},"Vedavally, L (2016) Report on Plant Clinics of Thiruvaiyaru: a study based on farmers’’perspectives. M S Swaminathan Research Foundation, Taramani Institutional Area, Chennai—600 113, MSSRF\u002FMG\u002F16\u002F46",{},{"id":20,"text":713,"url":20,"identifiers":714},"Glendenning CJ, Babu S, Asenso-Okyere K (2010) IFPRI Discussion paper 01048, “Review of Agricultural Extension in India are Farmers” information needs being met? Eastern and Southern Africa Regional Office",{},{"id":20,"text":716,"url":20,"identifiers":717},"Danielsen S, Centeno J, Lopez J, Lezama L, Varela G, Castillo P, Narvaez C, Zeledon I, Pavon F, Boa E (2013) Innovation in plant health services in Nicaragua: from grassroots experiment to a systems approach. J Int Dev 25(7):968–986",{"doi":718},"10.1002\u002Fjid.1786",{"id":20,"text":720,"url":20,"identifiers":721},"CABI (2017) Plantwise annual report, New Delhi. \n                    www.plantwise.org\u002FUploads\u002FPlantwise\u002FPlantwise%20Annual%20Report%202017.pdf\n                    \n                  . Accessed 21 July 2018",{},{"id":723,"createTime":724,"updateTime":725,"relativeEntities":726,"slug":727,"properties":728,"entityType":81,"verifyStatus":82,"verifyTime":725,"verifyNote":84,"languages":20,"translateLanguages":20,"viewCount":21,"primaryUrl":737,"fullTextUrl":20,"authors":738,"publicationType":103,"publisherRelationship":754,"citationCount":20,"citationInfo":20,"publishDate":774,"publishYear":775,"citationAnalyzeStatus":19,"lastCitationAnalyze":20,"indexDatabases":776,"openAccess":20,"references":20,"isForceReanalyzing":129},"1087b116-3f0a-4282-b367-e7399ce4fb90","2024-01-04T15:56:13.211+00:00","2025-02-24T00:53:15.832+00:00",[],"Processing-of-speech-signals-for-robust-recognition-in-practical-environments",{"abstract":729,"title":731,"references":733,"doi":735},{"EN":730},"In automatic speech recognition systems, the information in the speech signal is traditionally retrieved in the form of feature vectors representing sub-word units and thereby converting the features into human readable text form. However, these systems perform poorly due to degradations of speech under varying environmental conditions. To improve the performance, the main issues to be considered are: (a) Determination of speech regions in the speech data collected in degraded environments, and (b) Recognition of speech sounds from the degraded speech in the detected speech regions. Although there exist wide variety of techniques which address these issues, most of them are applicable for clean speech synthetically degraded by stationary noise conditions, due to the need for large amount of training data for statistical modeling. The present work focuses on methods of processing the signals so as to determine the desired speech regions in degraded conditions. For this, signal processing methods are being explored to extract speech-specific characteristics independent of the characteristics of degradations.",{"EN":732},"Processing of speech signals for robust recognition in practical environments",{"VOID":734},"Digital Cellular Telecommunications System (Phase 2+); Voice Activity Detector (VAD) for Adaptive Multi Rate (AMR) Speech Traffic Channel; General Description. 1999\nde Cheveigne A, Kawahara H (2002) YIN, a fundamental frequency estimator for speech and music. J Acoust Soc Am 111(4):1917–1930\nAneeja G, Yegnanarayana B (2015) Single frequency filtering approach for discriminating speech and nonspeech. IEEE\u002FACM Trans Audio Speech Lang Process 23(4):705–717\nBoersma P (2001) Praat, a system for doing phonetics by computer. Glot Int 5(9):341–345\nCamacho A, Harris J (2008) A sawtooth waveform inspired pitch estimator for speech and music. J Acoust Soc Am 124:1638–1652\nChen SH, Wang JF (2002) A wavelet-based voice activity detection algorithm in noisy environments. In 9th International Conference on Electronics, Circuits and Systems, 3:995–998\nCho YD, Kondoz A (2001) Analysis and improvement of a statistical model-based voice activity detector. IEEE Signal Process Lett 8(10):276–278\nChu W, Alwan A (2012) SAFE: a statistical approach to F0 estimation under clean and noisy conditions. IEEE Trans Audio Speech Lang Process 20(3):933–944\nCraciun A, Gabrea M (2004) Correlation coefficient-based voice activity detector algorithm. Can Conf Electr Comput Eng 3:1789–1792\nde Cheveigne A (1991) Speech F0 extraction based on Lickliders pitch perception model. ICPhS, pp. 218–221\nDhananjaya N, Yegnanarayana B (2010) Voiced\u002Fnonvoiced detection based on robustness of voiced epochs. IEEE Signal Process Lett 17(3):273–276\nDrugman T, Alwan A (2011) Joint robust voicing detection and pitch estimation based on residual harmonics. In: Proceedings of the Interspeech, pp 1973–1976\nEvangelopoulos G, Maragos P (2005) Speech event detection using multi band modulation energy. In INTERSPEECH, pp. 685–688\nGarofolo JS, Lamel LF, Fisher WM, Fiscus JG, Pallett DS, Dahlgren NL (1993) DARPA TIMIT acoustic phonetic continuous speech corpus CD-ROM. NIST, Gaithersburg\nMantena GV, Rajendran S, Gangashetty SV, Yegnanarayana B, Prahallad KS (2011) Development of a spoken dialogue system for accessing agricultural information in Telugu. In: Proceedings of the 9th international conference on natural language processing\nGhosh PK, Tsiartas A, Narayanan SS (2011) Robust voice activity detection using long-term signal variability. IEEE Trans Audio Speech Lang Process 19(3):600–613\nGonzalez S, Brookes M (2014) PEFAC-a pitch estimation algorithm robust to high levels of noise. IEEE\u002FACM Trans Audio Speech Lang Process 22(2):518–530\nGorriz JM, Ramirez J, Lang EW, Puntonet CG, Turias I (2010) Improved likelihood ratio test based voice activity detector applied to speech recognition. Speech Commun 52(78):664–677\nHaigh JA, Mason JS (1993) A voice activity detector based on cepstral analysis. In EUROSPEECH, pp. 1103–1106\nHughes T, Mierle K (2013) Recurrent neural networks for voice activity detection. In ICASSP, pp. 7378–7382\nKasi K, Zahorian S (2002) Yet another algorithm for pitch tracking. ICASSP 1:361–364\nKotnik B, Kacic Z, Horvat B (2001) A multiconditional robust front-end feature extraction with a noise reduction procedure based on improved spectral subtraction algorithm. In INTERSPEECH, pp. 197–200\nLee Y-C, Ahn S-S (2006) Statistical model-based VAD algorithm with wavelet transform. IEICE Trans Fundam Electron Commun Comput Sci E89–A(6):1594–1600\nMa Y, Nishihara A (2013) Efficient voice activity detection algorithm using long-term spectral flatness measure. EURASIP J Audio Speech Music Process 1–18:2013\nMarkel JD (1972) The SIFT algorithm for fundamental frequency estimation. IEEE Trans Audio Electroacoust 20:367–377\nMcLoughlin IV (2014) Super-audible voice activity detection. IEEE\u002FACM Trans Audio Speech Lang Process 22(9):1424–1433\nMurthy HA, Yegnanarayana B (2011) Group delay functions and its applications in speech technology. Sadhana 36(5):745–782\nNagarajan T, Prasad VK, Murthy H et al (2003) Minimum phase signal derived from root cepstrum. Electron Lett 39(12):941–942\nNakatani T, Irino T (2004) Robust and accurate fundamental frequency estimation based on dominant harmonic components. J Acoust Soc Am 116(6):3690–3700\nNg T, Zhang B, Nguyen L, Matsoukas S, Zhou Xinhui, Mesgarani Nima, Veselý Karel, Matějka Pavel (2012) Developing a speech activity detection system for the DARPA RATS program. INTERSPEECH 9:1–4\nNoll AM (1967) Cepstrum pitch determination. J Acoust Soc Am 41:293–309\nPlante F, Meyer GF, Aubsworth WA (1995) A pitch extraction reference database. In Proc Euro Conf on speech commun (Eurospeech), Madrid, Spain, pp. 827–840\nRabiner LR, Cheng MJ, Rosenberg AE, McGonegal CA (1976) A comparative performance study of several pitch detection algorithms. IEEEASSP 24:399–418\nRamirez J, Segura JC, Benitez C, De La Torre A, Rubio A (2004) Efficient voice activity detection algorithms using long-term speech information. Speech commun 42(3):271–287\nSadjadi SO, Hansen JHL (2013) Unsupervised speech activity detection using voicing measures and perceptual spectral flux. IEEE Signal Process Lett 20(3):197–200\nSarikaya R, Hansen JHL (1998) Robust speech activity detection in the presence of noise. In International Conference on Spoken Language Processing\nShimamura T, Kobayashi H (2001) Weighted autocorrelation for pitch extraction of noisy speech. IEEESAP 9(7):727–730\nSiemund R, Höge H, Kunzmann S, Marasek K (2000) SPEECON-speech data for consumer devices. In: Proceedings of the LREC2000, pp 883–886\nSohn J, Kim NS (1999) A statistical model-based voice activity detection. IEEE Signal Process Lett 6(1):1–3\nSun X (2002) Pitch determination and voice quality analysis using subharmonic-to-harmonic ratio. In ICASSP, pp. 333–336. IEEE\nTalkin D (1995) A Robust algorithm for pitch tracking (RAPT). In: Kleijn WB, Paliwal KK (eds) Speech Coding and Synthesis, Elsevier, pp 497–518\nTan LN, Alwan A (2013) Multi-band summary correlogram-based pitch detection for noisy speech. Speech Commun 55(7–8):841–856\nVarga A, Steeneken HJ (1993) Assessment for automatic speech recognition II: Noisex-92: A database and an experiment to study the effect of additive noise on speech recognition systems. Speech Commun 12(3):247–251\nPannala V, Aneeja G, Kadiri SR, Yegnanarayana B (2016) Robust estimation of fundamental frequency using single frequency filtering approach. In INTERSPEECH, pp. 2155–2159\nYang N, Ba H, Cai W, Demirkol I, Heinzelman W (2014) BaNa: a noise resilient fundamental frequency detection algorithm for speech and music. IEEE\u002FACM Trans Audio Speech Lang Process 22(12):1833–1848\nYegnanarayana B, Murty KSR (2009) Event-based instantaneous fundamental frequency estimation from speech signals. IEEE Trans Audio Speech Lang Process 17(4):614–624\nYegnanarayana B, Murthy HA (1992) Significance of group delay functions in spectrum estimation. 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In: Proceedings of the 38th IEEE international conference on acoustic, speech, and signal processing, Vancouver, Canada, May 2013, pp 853–857",{"VOID":736},"10.1007\u002Fs40012-016-0153-5","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs40012-016-0153-5",[739],{"id":740,"sortIndex":21,"researcher":20,"roles":741,"affiliations":742,"properties":751,"displayName":753,"givenName":20,"familyName":20},"a71654ea-1c0b-4489-b881-6b68cbf8da1d",[90],[743],{"id":744,"sortIndex":21,"affiliation":745,"properties":20},"886d20dd-59b8-42d8-b504-3d6b1bcef3dc",{"id":744,"createTime":20,"updateTime":20,"relativeEntities":746,"slug":20,"properties":747,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":750,"statistic":20},[],{"title":748},{"VI":749},"Speech and Vision Lab, LTRC, International Institute of Information Technology (IIIT), Hyderabad, India",[],{"title":752},{"VI":753},"Vishala Pannala",{"url":737,"publisher":755,"properties":769},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":756,"slug":10,"properties":757,"entityType":18,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":21,"subjectFields":761,"manageAffiliations":762,"indexDatabases":763,"url":20,"thumbnailPath":20,"statistic":764,"gsStatistic":20,"type":20,"analyzePriority":20},[],{"issn":758,"title":759,"eissn":760},{"VOID":13},{"EN":15},{"VOID":17},[],[],[],{"impactFactor":21,"impactFactorByYear":765,"i10Index":37,"i10IndexLast5Year":21,"totalPublication":38,"totalPublicationByYear":766,"totalCitation":43,"totalCitationByYear":767,"totalCitationPerPublication":51,"totalCitationPerPublicationByYear":768,"hindexLast5Year":42,"hindex":42},{"2014":27,"2015":28,"2016":29,"2017":30,"2018":31,"2019":32,"2020":33,"2021":34,"2022":35,"2023":36},{"2013":37,"2014":40,"2015":37,"2017":41,"2018":41,"2019":40,"2020":42,"2021":40,"2022":41,"2023":29},{"2013":45,"2014":46,"2015":47,"2017":48,"2018":49,"2019":29,"2020":47,"2021":29,"2022":50},{"2013":53,"2014":49,"2015":54,"2017":55,"2018":56,"2019":57,"2020":58,"2021":57,"2022":59},{"pages":770,"volume":772},{"VOID":771},"167-178",{"VOID":773},"5","2017-01-03",2017,[],{"id":778,"createTime":779,"updateTime":780,"relativeEntities":781,"slug":782,"properties":783,"entityType":81,"verifyStatus":82,"verifyTime":780,"verifyNote":84,"languages":20,"translateLanguages":20,"viewCount":21,"primaryUrl":792,"fullTextUrl":20,"authors":793,"publicationType":103,"publisherRelationship":822,"citationCount":20,"citationInfo":20,"publishDate":842,"publishYear":843,"citationAnalyzeStatus":19,"lastCitationAnalyze":20,"indexDatabases":844,"openAccess":20,"references":20,"isForceReanalyzing":129},"a922d667-cd2e-4c3f-b363-91b7fb632e96","2023-12-17T20:29:33.372+00:00","2025-02-23T21:07:09.993+00:00",[],"Harnessing-social-media-data-for-analyzing-public-inconvenience-in-construction-of-Indian-metro-rail-projects",{"abstract":784,"title":786,"references":788,"doi":790},{"EN":785},"The metro rail links many parts of a large city and offers one of the best modes of transit across it. However, the construction phase of the metro causes inconveniences to the people living in cities by significantly escalating the noise and dust pollution. During the construction of metro rails, citizens face problems in their everyday lives, especially as the elevated corridors go through thick-populated areas and high-vehicle traffic areas, creating traffic snarls and impediments. The literature review revealed additional concerns, such as public green cover depletion, potholes, building waste disposal, and vibrational issues. With the advent of social media, urban citizens use platforms like Twitter to express their opinions on inconveniences. The interactions over these social media platforms constitute big data. This data has immense potential for public engagement, accountability, and timely resolution of public inconvenience. The examination and analysis of social media posts on these issues are important as such analysis would inform the metro rail agency about the factors that affect the public and their emotional reaction to a specific activity or series of activities performed by the construction team. In this work, Twitter posts about the inconveniences associated with metro rail projects in four cities across India were analyzed. Social network analysis (SNA), text analytics, topic modeling, and sentiment analysis were conducted to analyze the data. SNA helped find the Twitter accounts with above-average betweenness centralities, while text analytics and topic modeling helped find latent discussion topics among the stakeholders. Sentiment analysis gave an idea of the public sentiments towards the projects.",{"EN":787},"Harnessing social media data for analyzing public inconvenience in construction of Indian metro rail projects",{"VOID":789},"Sharma N, Dhyani R, Gangopadhyay S (2013) Critical issues related to metro rail projects in India. J Infrastruct Dev 5(1):67–86. https:\u002F\u002Fdoi.org\u002F10.1177\u002F0974930613488296\nManetti G, Bellucci M, Bagnoli L (2017) Stakeholder engagement and public information through social media: a study of canadian and american public transportation agencies. Am Rev Public Adm 47(8):991–1009. https:\u002F\u002Fdoi.org\u002F10.1177\u002F0275074016649260\nNinan J, Clegg S, Mahalingam A (2019) Branding and governmentality for infrastructure megaprojects: the role of social media. Int J Project Manage 37(1):59–72. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.ijproman.2018.10.005\nPasayat A (n.d.) Kachrulal Bhagirath Agrawal & Ors vs State Of Maharashtra & Ors on 22 September, 2004. Retrieved from https:\u002F\u002Findiankanoon.org\u002Fdoc\u002F293583\u002F\nHadi M (2001) DTI construction industry directorate and forestry commission project report: prepared for: CD Framework: Best value UK timber in construction Approved on behalf of BRE\nGlass J, Simmonds M (2007) “considerate construction”: case studies of current practice. Eng Constr Archit Manag 14(2):131–149. https:\u002F\u002Fdoi.org\u002F10.1108\u002F09699980710731263\nSchexnayder CJ (n.d.) Mitigation of night-time construction noise, vibrations and other nuisances. Synthesis Practice 218, National Cooperative Highway Research Program, Transportation Research Board, Washington, DC.\nDuminda JMS (2010) Strategy to minimize user inconvenience during road rehabilitation. University of Moratuwa\nGriffith A, Lynde M (2002) Assessing public inconvenience in highway work zones (No. FHWA-OR-RD-02-20). Oregon Dept of Transportation Research Unit.\nShane JS, Amr Kandil CJS (2011) Nighttime construction impacts on safety, quality, and productivity (Issue 10). https:\u002F\u002Fonlinepubs.trb.org\u002Fonlinepubs\u002Fnchrp\u002Fdocs\u002FNCHRP10-78_FR.pdf\nFerguson A (2012) Qualitative evaluation of transportation construction related social costs and their impacts on the local community (Issue May) [The University of Texas at Arlington]. https:\u002F\u002Frc.library.uta.edu\u002Futa-ir\u002Fhandle\u002F10106\u002F11165\nKukadia V, Upton S, Grimwood C (2003) Contorlling particles, vapour and noise pollution from construction sites; parts 1–5: site preparation, demolition, earthworks and landscaping. BRE Pollution Guide, pp 1–8\nXue X, Zhang R, Zhang X, Yang RJ, Li H (2015) Environmental and social challenges for urban subway construction: an empirical study in China. Int J Project Manag 33(3):576–588. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.ijproman.2014.09.003\nRay R (2017) Open for business? Effects of los angeles metro rail construction on adjacent businesses. J Trans Land Use 10(1):725–742. https:\u002F\u002Fdoi.org\u002F10.5198\u002Fjtlu.2017.932\nChakraborty, D (2010) Mumbai Residents Oppose Elevated Metro Corridors. Avail online at http:\u002F\u002Fwww.projectsmonitor.com corridors, accessed in January 2011.\nUnited States Environmental Protection Agency (n.d.) Public Participation Guide: Social Media. Retrieved from https:\u002F\u002Fwww.epa.gov\u002Finternational-cooperation\u002Fpublic-participation-guide-social-media#:~:text=Social media allow stakeholders to,in a variety of ways.\nNik-Bakht M, El-Diraby TE (2020) Beyond chatter: profiling community discussion networks in urban infrastructure projects. J Infrastruct Syst 26(3):05020006.\nPerera S, Victoria M, Brand S (2015) Use of social media in construction industry: a case study. Going North for Sustainability: Leveraging Knowledge and Innovation for Sustainable Construction and Development: Proceedings of the International Council for Research and Innovation in Building and Construction (CIB2015), 23-25 November 2015, South Bank University, London, UK, 462-473.\nQi B, Costin A, Jia M (2020) A framework with efficient extraction and analysis of Twitter data for evaluating public opinions on transportation services. Travel Behav Soc 21:10–23. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.tbs.2020.05.005\nKocatepe A, Ulak MB, Lores J, Ozguven EE, Yazici A (2018) Exploring the reach of departments of transportation tweets: What drives public engagement? Case Stud Trans Policy 6(4):683–694\nWojtowicz J, Wallace WA (2016) Use of social media by transportation agencies for traffic management. Transp Res Rec 2551(1):82–89. https:\u002F\u002Fdoi.org\u002F10.3141\u002F2551-10\nBasu R, Khatua A, Jana A, Ghosh S (2017) Harnessing twitter data for analyzing public reactions to transportation policies: evidence from the odd-even policy in Delhi, India. (November). Retrieved from https:\u002F\u002Fwww.researchgate.net\u002Fpublication\u002F321997978_Harnessing_Twitter_Data_for_Analyzing_Public_Reactions_to_Transportation_Policies_Evidences_from_the_Odd-Even_Policy_in_Delhi_India\nKaur N, Pushe V, Kaur R (2014) Natural language processing interface for synonym. Int J Comput Sci Mob Comput 3(7):638–642\nHu X, Liu H (2012) Text analytics in social media. In: Mining text data (pp 385–414). Springer, Boston, MA.\nBlei DM, Ng AY, Jordan MI (2003) Latent dirichlet allocation. J Mach Learn Res 3:993–1022\nSujon M, Dai F (2021) Social media mining for understanding traffic safety culture in washington state using twitter data. J Comput Civ Eng 35(1):04020059. https:\u002F\u002Fdoi.org\u002F10.1061\u002F(asce)cp.1943-5487.0000943\nHutto C, Gilbert E (2014) Vader: a parsimonious rule-based model for sentiment analysis of social media text. In: Proceedings of the international AAAI conference on web and social media, vol 8, No. 1, pp 216–225\nBorg A, Boldt M (2020) Using VADER sentiment and SVM for predicting customer response sentiment. Expert Syst Appl 162:113746. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.eswa.2020.113746\nScott J (1988) Social network analysis. Sociology 22(1):109–127\nWilliams NL, Ferdinand N, Pasian B (2015) Online stakeholder interactions in the early stage of a megaproject. Proj Manag J 46(6):92–110\nCarrasco JA, Hogan B, Wellman B, Miller EJ (2008) Collecting social network data to study social activity-travel behavior: an egocentric approach. Environ Plann B Plann Des 35(6):961–980\nBorgatti SP, Mehra A, Brass DJ, Labianca G (2009) Network analysis in the social sciences. Science 323(5916):892–895\nJohari A (2018) From parsis to adivasis, Mumbai’s metro project faces heat from citizens. Retrieved from https:\u002F\u002Fscroll.in\u002Farticle\u002F881470\u002Ffrom-parsis-to-adivasis-mumbais-underground-metro-project-faces-heat-from-citizens\nChattyopadhay S (2019) In Kolkata, houses collapse during Metro tunnelling work. Retrieved from https:\u002F\u002Ffrontline.thehindu.com\u002Fdispatches\u002Farticle29332315.ece\nPalmer S, Udawatta N (2019) Characterising “Green Building” as a topic in Twitter. Constr Innov 19(4):513–530. https:\u002F\u002Fdoi.org\u002F10.1108\u002FCI-02-2018-0007\nHarel D, Koren Y (2002) A fast multi-scale method for drawing large graphs. 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