Etiology and Advanced Detection Techniques for Fetal Brain Abnormalities: A Comprehensive Study
causes; Fetal brain abnormalities; Fetal MRI; Medical Imaging; Segmentation techniques
In the modern world, women's health deserves greater focus, particularly in a country like India and particularly during pregnancy. The health of mother's as well as baby's is important throw-out this process. According to a survey, three cases out of a thousand have abnormalities in fetal brain. The likelihood of survival of mother and child significantly increased by early identification of these diseases. Several procedures, including fetal ultrasound, MRI, fetal echocardiography etc. must be carried out during pregnancy in order to monitor fetal development. Pregnancyrelated MRI-scans always practiced to identify and treat fetal brain disorders in former stages. It is possible to identify, examin fetal brain problems early on by doing a prenatal MRI examination. The diagnosis of issues with fetal brain MRI imaging involves several crucial procedures. Among these are image segmentation; image analysis, which comprises extracting characteristic characteristics, improving image quality, identifying relevant patterns, and categorising images based on predefined standards. Classification determines if an anomaly is present or not. Analysing pictures can be difficult due to the wide range of shapes, spatial arrangements, and intensities that are present. The primary subjects of this work are the review and comparison of various fetal brain malformations, as well as their causes and commonalities. 2025 IEEE.
2025 10th International Conference on Research in Intelligent Computing in Engineering, RICE 2025;
Institute of Electrical and Electronics Engineers Inc.
Restricted Access; Hardcopy may be available in the library
https://doi.org/10.1109/RICE67503.2025.11439996 https://www.scopus.com/pages/publications/105037436581?origin=resultslist
Gaikwad N., School of Sciences, CHRIST UNIVERSITY, Department of Computer Science, India; Vijayalakshmi S., School of Sciences, CHRIST UNIVERSITY, Department of Computer Science, India
ETL and Business Analytics Correlation Mapping with Software Engineering
Business analysis; Data science; ETL process; SDLC; Software engineering
Large information approach can't be effectively accomplished utilizing customary information investigation strategies. Rather, unstructured information requires specific information demonstrating methods, apparatuses, and frameworks to separate experiences and data varying by associations. Information science is a logical methodology that applies scientific and measurable thoughts and PC instruments for preparing large information. At present, we all are seeing an exceptional development of data created worldwide and on the web to bring about the idea of large information. Information science is a significant testing zone because of the complexities engaged with consolidating and applying various strategies, calculations, and complex programming procedures to perform insightful investigation in huge volumes of information. Thus, the field of information science has developed from enormous information, or huge information and information science are indistinguishable. In this article we have tried to create bridge between ETL and software engineering. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
Advances in Intelligent Systems and Computing, Vol-1311 AISC, pp. 501-511.
Springer Science and Business Media Deutschland GmbH
Paikaray B.K., Department of CSE, Centurion University of Technology and Management, Bhubaneswar, Odisha, India; Dube M.R., Department of CSE, Vishwakarma Institute of Technology, Pune, India; Swain D., Department of Data Science Department, Christ University, Lavasa, Pune, India
Euclid: Early Release Observations of ram-pressure stripping in the Perseus cluster: Detection of parsec-scale star formation within the low surface brightness stripped tails of UGC 2665 and MCG +07-07-070
Galaxies: clusters: intracluster medium; Galaxies: evolution; Galaxies: spiral; Galaxies: star formation
Euclid is delivering optical and near-infrared imaging data over 14 000 deg2 on the sky at spatial resolution and surface brightness levels that can be used to understand the morphological transformation of galaxies within groups and clusters. Using the Early Release Observations (ERO) of the Perseus cluster, we demonstrate the capability offered by Euclid in studying the nature of perturbations for galaxies in clusters. Filamentary structures are observed along the discs of two spiral galaxies, UGC 2665 and MCG +07-07-070, with no extended diffuse emission expected from tidal interactions at surface brightness levels of a30 mag arcseca 2. The detected features exhibit a good correspondence in morphology between optical and near-infrared wavelengths, with a surface brightness of a25 mag arcseca 2, and the knots within the features have sizes of a 100 pc, as observed through IE imaging. Using the Euclid, CFHT, UVIT, and LOFAR 144 MHz radio continuum observations, we conducted a detailed analysis to understand the origin of the detected features. We constructed the Euclid IEaYE, YEaHE, and CFHT u ar, g ai colour-colour plane and show that these features contain recent star formation events, which are also indicated by their H? and NUV emissions. Euclid colours alone are insufficient for studying stellar population ages in unresolved star-forming regions, which require multi-wavelength optical imaging data. There are features with red colours that can be explained by dust being stripped along with the gas in these regions. The morphological shape, orientation, and mean age of the stellar population, combined with the presence of extended radio continuum cometary tails can be consistently explained if these features formed during a recent ram-pressure stripping event. This result further confirms the exceptional qualities of Euclid in the study of galaxy evolution in dense environments. 2025 EDP Sciences. All rights reserved.
George, K.; Boselli, A.; Cuillandre, J.-C.; Kmel, M.; Lann, A.; Bellhouse, C.; Saifollahi, T.; Mondelin, M.; Bolzonella, M.; Joseph, P.; Roberts, I.D.; Van Weeren, R.J.; Liu, Q.; Sola, E.; Urbano, M.; Baes, M.; Peletier, R.F.; Klein, M.; Davies, C.T.; Zinchenko, I.A.; Sorce, J.G.; Poulain, M.; Aghanim, N.; Altieri, B.; Amara, A.; Andreon, S.; Auricchio, N.; Baccigalupi, C.; Baldi, M.; Balestra, A.; Bardelli, S.; Battaglia, P.; Biviano, A.; Bonino, D.; Branchini, E.; Brescia, M.; Brinchmann, J.; Camera, S.; Cas-Herrera, G.; Capobianco, V.; Carbone, C.; Carretero, J.; Casas, S.; Castellano, M.; Castignani, G.; Cavuoti, S.; Chambers, K.C.; Cimatti, A.; Colodro-Conde, C.; Congedo, G.; Conselice, C.J.; Conversi, L.; Copin, Y.; Courbin, F.; Courtois, H.M.; Cropper, M.; Da Silva, A.; Degaudenzi, H.; De Lucia, G.; Di Giorgio, A.M.; Dole, H.; Douspis, M.; Dubath, F.; Dupac, X.; Dusini, S.; Escoffier, S.; Farina, M.; Faustini, F.; Ferriol, S.; Fotopoulou, S.; Frailis, M.; Franceschi, E.; Galeotta, S.; Gillis, B.; Giocoli, C.; Gracia-Carpio, J.; Grazian, A.; Grupp, F.; Haugan, S.V.H.; Holmes, W.; Hook, I.M.; Hormuth, F.; Hornstrup, A.; Hudelot, P.; Jahnke, K.; Jhabvala, M.; Keihen, E.; Kermiche, S.; Kiessling, A.; Kubik, B.; Kunz, M.; Kurki-Suonio, H.; Le Brun, A.M.C.; Le Mignant, D.; Ligori, S.; Lilje, P.B.; Lindholm, V.; Lloro, I.; Mainetti, G.; Maino, D.; Maiorano, E.; Mansutti, O.; Marggraf, O.; Markovic, K.; Martinelli, M.; Martinet, N.; Marulli, F.; Massey, R.; Maurogordato, S.; Medinaceli, E.; Mei, S.; Mellier, Y.; Meneghetti, M.; Merlin, E.; Meylan, G.; Mohr, J.J.; Mora, A.; Moresco, M.; Moscardini, L.; Nakajima, R.; Neissner, C.; Nichol, R.C.; Niemi, S.-M.; Nightingale, J.W.; Padilla, C.; Paltani, S.; Pasian, F.; Pedersen, K.; Percival, W.J.; Pettorino, V.; Pires, S.; Polenta, G.; Poncet, M.; Popa, L.A.; Pozzetti, L.; Raison, F.; Rebolo, R.; Renzi, A.; Rhodes, J.; Riccio, G.; Romelli, E.; Roncarelli, M.; Rossetti, E.; Saglia, R.; Sakr, Z.; Sapone, D.; Sartoris, B.; Schewtschenko, J.A.; Schirmer, M.; Schneider, P.; Secroun, A.; Seidel, G.; Seiffert, M.; Serrano, S.; Sirignano, C.; Sirri, G.; Stanco, L.; Steinwagner, J.; Tallada-Cresp P.; Taylor, A.N.; Tereno, I.; Toft, S.; Toledo-Moreo, R.; Torradeflot, F.; Tutusaus, I.; Valentijn, E.A.; Valenziano, L.; Valiviita, J.; Vassallo, T.; Verdoes Kleijn, G.; Veropalumbo, A.; Wang, Y.; Weller, J.; Zamorani, G.; Zerbi, F.M.; Zucca, E.; Burigana, C.; Gabarra, L.; Mart-Fleitas, J.; Scottez, V.
Astronomy and Astrophysics;Volume;701;Issue;;Article No.;A40;
All Open Access; Gold Open Access; Green Open Access
https://doi.org/10.1051/0004-6361/202554836 https://www.scopus.com/pages/publications/105015302152?origin=resultslist
George K., University Observatory, LMU, Faculty of Physics, Scheinerstrasse 1, Munich, 81679, Germany; Boselli A., Aix-Marseille Universite, CNRS, CNES, LAM, Marseille, France; Cuillandre J.-C., UniversitParis-Saclay, UniversitParis Cite, CEA, CNRS, AIM, Gif-sur-Yvette, 91191, France; Kmel M., Universits-Sternwarte Mchen, Fakult f Physik, Ludwig-Maximilians-Universit Mchen, Scheinerstrasse 1, Mchen, 81679, Germany; Lann A., Universitde Strasbourg, CNRS, Observatoire Astronomique de Strasbourg, UMR 7550, Strasbourg, 67000, France; Bellhouse C., School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, United Kingdom; Saifollahi T., Universitde Strasbourg, CNRS, Observatoire Astronomique de Strasbourg, UMR 7550, Strasbourg, 67000, France; Mondelin M., UniversitParis-Saclay, UniversitParis Cite, CEA, CNRS, AIM, Gif-sur-Yvette, 91191, France; Bolzonella M., INAF, Osservatorio di Astrofisica e Scienza Dello Spazio di Bologna, Via Piero Gobetti 93/3, Bologna, 40129, Italy; Joseph P., Indian Institute of Astrophysics, Koramangala II Block, Bangalore, 560034, India, Department of Physics and Electronics, CHRIST (Deemed to Be University), Bangalore, 560029, India; Roberts I.D., Waterloo Centre for Astrophysics, University of Waterloo, Waterloo, N2L 3G1, ON, Canada; Van Weeren R.J., Leiden Observatory, Leiden University, Einsteinweg 55, Leiden, 2333 CC, Netherlands; Liu Q., Leiden Observatory, Leiden University, Einsteinweg 55, Leiden, 2333 CC, Netherlands; Sola E., Institute of Astronomy, University of Cambridge, Madingley Road, Cambridge, CB3 0HA, United Kingdom; Urbano M., Universitde Strasbourg, CNRS, Observatoire Astronomique de Strasbourg, UMR 7550, Strasbourg, 67000, France; Baes M., Sterrenkundig Observatorium, Universiteit Gent, Krijgslaan 281 S9, Gent, 9000, Belgium; Peletier R.F., Kapteyn Astronomical Institute, University of Groningen, PO Box 800, Groningen, 9700 AV, Netherlands; Klein M., Ludwig-Maximilians-University, Schellingstrasse 4, Munich, 80799, Germany; Davies C.T., Ludwig-Maximilians-University, Schellingstrasse 4, Munich, 80799, Germany; Zinchenko I.A., Universits-Sternwarte Mchen, Fakult f Physik, Ludwig-Maximilians-Universit Mchen, Scheinerstrasse 1, Mchen, 81679, Germany; Sorce J.G., Univ. Lille, CNRS, Centrale Lille, UMR 9189, CRIStAL, Lille, 59000, France, UniversitParis-Saclay, CNRS, Institut da Astrophysique Spatiale, Orsay, 91405, France; Poulain M., Space Physics and Astronomy Research Unit, University of Oulu, Pentti Kaiteran katu 1, Oulu, FI-90014, Finland; Aghanim N., UniversitParis-Saclay, CNRS, Institut da Astrophysique Spatiale, Orsay, 91405, France; Altieri B., ESAC/ESA, Camino Bajo Del Castillo, s/n., Urb. Villafranca del Castillo, Villanueva de la Cada, Madrid, 28692, Spain; Amara A., School of Mathematics and Physics, University of Surrey, Guildford, Surrey, GU2 7XH, United Kingdom; Andreon S., INAF, Osservatorio Astronomico di Brera, Via Brera 28, Milano, 20122, Italy; Auricchio N., INAF, Osservatorio di Astrofisica e Scienza Dello Spazio di Bologna, Via Piero Gobetti 93/3, Bologna, 40129, Italy; Baccigalupi C., IFPU, Institute for Fundamental Physics of the Universe, Via Beirut 2, Trieste, 34151, Italy, INAF, Osservatorio Astronomico di Trieste, Via G. B. Tiepolo 11, Trieste, 34143, Italy, INFN, Sezione di Trieste, Via Valerio 2, TS, Trieste, 34127, Italy, SISSA, International School for Advanced Studies, Via Bonomea 265, TS, Trieste, 34136, Italy; Baldi M., INAF, Osservatorio di Astrofisica e Scienza Dello Spazio di Bologna, Via Piero Gobetti 93/3, Bologna, 40129, Italy, Dipartimento di Fisica e Astronomia, Universitdi Bologna, Via Gobetti 93/2, Bologna, 40129, Italy, INFN-Sezione di Bologna, Viale Berti Pichat 6/2, Bologna, 40127, Italy; Balestra A., INAF-Osservatorio Astronomico di Padova, Via della Osservatorio 5, Padova, 35122, Italy; Bardelli S., INAF, Osservatorio di Astrofisica e Scienza Dello Spazio di Bologna, Via Piero Gobetti 93/3, Bologna, 40129, Italy; Battaglia P., INAF, Osservatorio di Astrofisica e Scienza Dello Spazio di Bologna, Via Piero Gobetti 93/3, Bologna, 40129, Italy; Biviano A., IFPU, Institute for Fundamental Physics of the Universe, Via Beirut 2, Trieste, 34151, Italy, INAF, Osservatorio Astronomico di Trieste, Via G. B. Tiepolo 11, Trieste, 34143, Italy; Bonino D., INAF, Osservatorio Astrofisico di Torino, Via Osservatorio 20 (TO), Pino Torinese, 10025, Italy; Branchini E., INAF, Osservatorio Astronomico di Brera, Via Brera 28, Milano, 20122, Italy, Dipartimento di Fisica, Universitdi Genova, Via Dodecaneso 33, Genova, 16146, Italy, INFN-Sezione di Genova, Via Dodecaneso 33, Genova, 16146, Italy; Brescia M., Department of Physics E. Pancini, University Federico II, Via Cinthia 6, Napoli, 80126, Italy, INAF-Osservatorio Astronomico di Capodimonte, Via Moiariello 16, Napoli, 80131, Italy; Brinchmann J., Instituto de Astrofica e Ciencias Do Espa, Universidade Do Porto, CAUP, Rua das Estrelas PT4150-762, Porto, Portugal, Faculdade de Ciencias, Universidade Do Porto, Rua do Campo de Alegre, Porto, 4150-007, Portugal; Camera S., INAF, Osservatorio Astrofisico di Torino, Via Osservatorio 20 (TO), Pino Torinese, 10025, Italy, Dipartimento di Fisica, UniversitDegli Studi di Torino, Via P. Giuria 1, Torino, 10125, Italy, INFN-Sezione di Torino, Via P. Giuria 1, Torino, 10125, Italy; Cas-Herrera G., Leiden Observatory, Leiden University, Einsteinweg 55, Leiden, 2333 CC, Netherlands, European Space Agency, ESTEC, Keplerlaan 1, Noordwijk, 2201 AZ, Netherlands, Institute Lorentz, Leiden University, Niels Bohrweg 2, Leiden, 2333 CA, Netherlands; Capobianco V., INAF, Osservatorio Astrofisico di Torino, Via Osservatorio 20 (TO), Pino Torinese, 10025, Italy; Carbone C., INAF-IASF Milano, Via Alfonso Corti 12, Milano, 20133, Italy; Carretero J., Centro de Investigaciones Energicas, Medioambientales y Tecnolicas (CIEMAT), Avenida Complutense 40, Madrid, 28040, Spain, Port da InformaciCientica, Campus UAB, C. Albareda s/n, Bellaterra, Barcelona, 08193, Spain; Casas S., Institute for Theoretical Particle Physics and Cosmology (TTK), RWTH, Aachen University, Aachen, 52056, Germany; Castellano M., INAF-Osservatorio Astronomico di Roma, Via Frascati 33, Monteporzio Catone, 00078, Italy; Castignani G., INAF, Osservatorio di Astrofisica e Scienza Dello Spazio di Bologna, Via Piero Gobetti 93/3, Bologna, 40129, Italy; Cavuoti S., INAF-Osservatorio Astronomico di Capodimonte, Via Moiariello 16, Napoli, 80131, Italy, INFN Section of Naples, Via Cinthia 6, Napoli, 80126, Italy; Chambers K.C., Institute for Astronomy, University of Hawaii, 2680 Woodlawn Drive, Honolulu, 96822, HI, United States; Cimatti A., Dipartimento di Fisica e Astronomia Augusto Righi, Alma Mater Studiorum Universita di Bologna, Viale Berti Pichat 6/2, Bologna, 40127, Italy; Colodro-Conde C., Instituto de Astrofica de Canarias, Via Ltea, La Laguna, Tenerife, 38205, Spain; Congedo G., Institute for Astronomy, University of Edinburgh, Royal Observatory, Blackford Hill, Edinburgh, EH9 3HJ, United Kingdom; Conselice C.J., Jodrell Bank Centre for Astrophysics, Department of Physics and Astronomy, University of Manchester, Oxford Road, Manchester, M13 9PL, United Kingdom; Conversi L., ESAC/ESA, Camino Bajo Del Castillo, s/n., Urb. Villafranca del Castillo, Villanueva de la Cada, Madrid, 28692, Spain, European Space Agency, ESRIN, Largo Galileo Galilei 1, Frascati, Roma, 00044, Italy; Copin Y., UniversitClaude Bernard Lyon 1, CNRS, IN2P3, IP2I Lyon, UMR 5822, Villeurbanne, F-69100, France; Courbin F., Institut de Cicies Del Cosmos (ICCUB), Universitat de Barcelona (IEEC-UB), Marti Franqu 1, Barcelona, 08028, Spain, InstituciCatalana de Recerca i Estudis Avants (ICREA), Passeig de Llu Companys 23, Barcelona, 08010, Spain; Courtois H.M., UCB Lyon 1, CNRS, IN2P3, IUF, IP2I Lyon, 4 rue Enrico Fermi, Villeurbanne, 69622, France; Cropper M., Mullard Space Science Laboratory, University College London, Holmbury St Mary, Dorking, Surrey, RH5 6NT, United Kingdom; Da Silva A., Departamento de Fica, Faculdade de Ciencias, Universidade de Lisboa, Edifio C8, Campo Grande, Lisboa, PT1749-016, Portugal, Instituto de Astrofica e Ciencias Do Espa, Faculdade de Ciencias, Universidade de Lisboa, Campo Grande, Lisboa, 1749-016, Portugal; Degaudenzi H., Department of Astronomy, University of Geneva, ch. da Ecogia 16, Versoix, 1290, Switzerland; De Lucia G., INAF, Osservatorio Astronomico di Trieste, Via G. B. Tiepolo 11, Trieste, 34143, Italy; Di Giorgio A.M., INAF, Istituto di Astrofisica e Planetologia Spaziali, Via del Fosso del Cavaliere, 100, Roma, 00100, Italy; Dole H., UniversitParis-Saclay, CNRS, Institut da Astrophysique Spatiale, Orsay, 91405, France; Douspis M., UniversitParis-Saclay, CNRS, Institut da Astrophysique Spatiale, Orsay, 91405, France; Dubath F., Department of Astronomy, University of Geneva, ch. da Ecogia 16, Versoix, 1290, Switzerland; Dupac X., ESAC/ESA, Camino Bajo Del Castillo, s/n., Urb. Villafranca del Castillo, Villanueva de la Cada, Madrid, 28692, Spain; Dusini S., INFN-Padova, Via Marzolo 8, Padova, 35131, Italy; Escoffier S., Aix-Marseille Universite, CNRS, IN2P3, CPPM, Marseille, France; Farina M., INAF, Istituto di Astrofisica e Planetologia Spaziali, Via del Fosso del Cavaliere, 100, Roma, 00100, Italy; Faustini F., INAF-Osservatorio Astronomico di Roma, Via Frascati 33, Monteporzio Catone, 00078, Italy, Space Science Data Center, Italian Space Agency, Via del Politecnico snc, Roma, 00133, Italy; Ferriol S., UniversitClaude Bernard Lyon 1, CNRS, IN2P3, IP2I Lyon, UMR 5822, Villeurbanne, F-69100, France; Fotopoulou S., School of Physics, HH Wills Physics Laboratory, University of Bristol, Tyndall Avenue, Bristol, BS8 1TL, United Kingdom; Frailis M., INAF, Osservatorio Astronomico di Trieste, Via G. B. Tiepolo 11, Trieste, 34143, Italy; Franceschi E., INAF, Osservatorio di Astrofisica e Scienza Dello Spazio di Bologna, Via Piero Gobetti 93/3, Bologna, 40129, Italy; Galeotta S., INAF, Osservatorio Astronomico di Trieste, Via G. B. Tiepolo 11, Trieste, 34143, Italy; Gillis B., Institute for Astronomy, University of Edinburgh, Royal Observatory, Blackford Hill, Edinburgh, EH9 3HJ, United Kingdom; Giocoli C., INAF, Osservatorio di Astrofisica e Scienza Dello Spazio di Bologna, Via Piero Gobetti 93/3, Bologna, 40129, Italy, INFN-Sezione di Bologna, Viale Berti Pichat 6/2, Bologna, 40127, Italy; Gracia-Carpio J., Max Planck Institute for Extraterrestrial Physics, Giessenbachstr. 1, Garching, 85748, Germany; Grazian A., INAF-Osservatorio Astronomico di Padova, Via della Osservatorio 5, Padova, 35122, Italy; Grupp F., Universits-Sternwarte Mchen, Fakult f Physik, Ludwig-Maximilians-Universit Mchen, Scheinerstrasse 1, Mchen, 81679, Germany, Max Planck Institute for Extraterrestrial Physics, Giessenbachstr. 1, Garching, 85748, Germany; Haugan S.V.H., Institute of Theoretical Astrophysics, University of Oslo, P.O. Box 1029 Blindern, Oslo, 0315, Norway; Holmes W., Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Drive, Pasadena, 91109, CA, United States; Hook I.M., Department of Physics, Lancaster University, Lancaster, LA1 4YB, United Kingdom; Hormuth F., Felix Hormuth Engineering, Goethestr. 17, Leimen, 69181, Germany; Hornstrup A., Technical University of Denmark, Elektrovej 327, Kgs. Lyngby, 2800, Denmark, Cosmic Dawn Center (DAWN), Denmark; Hudelot P., Institut da Astrophysique de Paris, UMR 7095, CNRS, Sorbonne Universite, 98 bis boulevard Arago, Paris, 75014, France; Jahnke K., Max-Planck-Institut f Astronomie, Konigstuhl 17, Heidelberg, 69117, Germany; Jhabvala M., NASA, Goddard Space Flight Center, Greenbelt, 20771, MD, United States; Keihen E., Department of Physics, Helsinki Institute of Physics, University of Helsinki, Gustaf Hlstrin katu 2, 00014, Finland; Kermiche S., Aix-Marseille Universite, CNRS, IN2P3, CPPM, Marseille, France; Kiessling A., Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Drive, Pasadena, 91109, CA, United States; Kubik B., UniversitClaude Bernard Lyon 1, CNRS, IN2P3, IP2I Lyon, UMR 5822, Villeurbanne, F-69100, France; Kunz M., Universitde Gene, Dartement de Physique Theorique, Centre for Astroparticle Physics, 24 quai Ernest-Ansermet, Geneve 4, CH-1211, Switzerland; Kurki-Suonio H., Department of Physics, University of Helsinki, P.O. Box 64, 00014, Finland, Helsinki Institute of Physics, University of Helsinki, Gustaf Hallstrin katu 2, Helsinki, Finland; Le Brun A.M.C., Laboratoire da Etude de la Univers et des Phenomenes EXtremes, Observatoire de Paris, UniversitPSL, Sorbonne Universite, CNRS, Meudon, 92190, France; Le Mignant D., Aix-Marseille Universite, CNRS, CNES, LAM, Marseille, France; Ligori S., INAF, Osservatorio Astrofisico di Torino, Via Osservatorio 20 (TO), Pino Torinese, 10025, Italy; Lilje P.B., Institute of Theoretical Astrophysics, University of Oslo, P.O. Box 1029 Blindern, Oslo, 0315, Norway; Lindholm V., Department of Physics, University of Helsinki, P.O. Box 64, 00014, Finland, Helsinki Institute of Physics, University of Helsinki, Gustaf Hallstrin katu 2, Helsinki, Finland; Lloro I., SKA Observatory, Jodrell Bank, Lower Withington, Macclesfield, Cheshire, SK11 9FT, United Kingdom; Mainetti G., Centre de Calcul de La, IN2P3, CNRS, 21 avenue Pierre de Coubertin, Cedex, Villeurbanne, 69627, France; Maino D., INAF-IASF Milano, Via Alfonso Corti 12, Milano, 20133, Italy, Dipartimento di Fisica Aldo Pontremoli, UniversitDegli Studi di Milano, Via Celoria 16, Milano, 20133, Italy, Via Celoria 16, Milano, 20133, Italy; Maiorano E., INAF, Osservatorio di Astrofisica e Scienza Dello Spazio di Bologna, Via Piero Gobetti 93/3, Bologna, 40129, Italy; Mansutti O., INAF, Osservatorio Astronomico di Trieste, Via G. B. Tiepolo 11, Trieste, 34143, Italy; Marggraf O., Universit Bonn, Argelander-Institut fur Astronomie, Auf dem Hel 71, Bonn, 53121, Germany; Markovic K., Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Drive, Pasadena, 91109, CA, United States; Martinelli M., INAF-Osservatorio Astronomico di Roma, Via Frascati 33, Monteporzio Catone, 00078, Italy, INFN, Sezione di Roma, C/o Dipartimento di Fisica, Piazzale Aldo Moro, 2 , Edificio G. Marconi, Roma, 00185, Italy; Martinet N., Aix-Marseille Universite, CNRS, CNES, LAM, Marseille, France; Marulli F., INAF, Osservatorio di Astrofisica e Scienza Dello Spazio di Bologna, Via Piero Gobetti 93/3, Bologna, 40129, Italy, INFN-Sezione di Bologna, Viale Berti Pichat 6/2, Bologna, 40127, Italy, Dipartimento di Fisica e Astronomia Augusto Righi, Alma Mater Studiorum, Universita di Bologna, Via Piero Gobetti 93/2, Bologna, 40129, Italy; Massey R., Department of Physics, Institute for Computational Cosmology, Durham University, South Road, Durham, DH1 3LE, United Kingdom; Maurogordato S., UniversitCote da Azur, Observatoire de la Cote da Azur, CNRS, Laboratoire Lagrange, Bd de la Observatoire, CS 34229, cedex 4, Nice, 06304, France; Medinaceli E., INAF, Osservatorio di Astrofisica e Scienza Dello Spazio di Bologna, Via Piero Gobetti 93/3, Bologna, 40129, Italy; Mei S., UniversitParis Cite, CNRS, Astroparticule et Cosmologie, Paris, 75013, France, CNRS-UCB, International Research Laboratory, Centre Pierre Binetruy, IRL2007, CPB-IN2P3, Berkeley, United States; Mellier Y., Institut da Astrophysique de Paris, UMR 7095, CNRS, Sorbonne Universite, 98 bis boulevard Arago, Paris, 75014, France, Institut da Astrophysique de Paris, 98bis Boulevard Arago, Paris, 75014, France; Meneghetti M., INAF, Osservatorio di Astrofisica e Scienza Dello Spazio di Bologna, Via Piero Gobetti 93/3, Bologna, 40129, Italy, INFN-Sezione di Bologna, Viale Berti Pichat 6/2, Bologna, 40127, Italy; Merlin E., INAF-Osservatorio Astronomico di Roma, Via Frascati 33, Monteporzio Catone, 00078, Italy; Meylan G., Institute of Physics, Laboratory of Astrophysics, Ecole Polytechnique Fale de Lausanne (EPFL), Observatoire de Sauverny, Versoix, 1290, Switzerland; Mohr J.J., University Observatory, LMU, Faculty of Physics, Scheinerstrasse 1, Munich, 81679, Germany; Mora A., Aurora Technology for European Space Agency (ESA), Camino Bajo Del Castillo, s/n, Urbanizacion Villafranca del Castillo, Villanueva de la Canada, Madrid, 28692, Spain; Moresco M., INAF, Osservatorio di Astrofisica e Scienza Dello Spazio di Bologna, Via Piero Gobetti 93/3, Bologna, 40129, Italy, Dipartimento di Fisica e Astronomia Augusto Righi, Alma Mater Studiorum, Universita di Bologna, Via Piero Gobetti 93/2, Bologna, 40129, Italy; Moscardini L., INAF, Osservatorio di Astrofisica e Scienza Dello Spazio di Bologna, Via Piero Gobetti 93/3, Bologna, 40129, Italy, INFN-Sezione di Bologna, Viale Berti Pichat 6/2, Bologna, 40127, Italy, Dipartimento di Fisica e Astronomia Augusto Righi, Alma Mater Studiorum, Universita di Bologna, Via Piero Gobetti 93/2, Bologna, 40129, Italy; Nakajima R., Universit Bonn, Argelander-Institut fur Astronomie, Auf dem Hel 71, Bonn, 53121, Germany; Neissner C., Port da InformaciCientica, Campus UAB, C. Albareda s/n, Bellaterra, Barcelona, 08193, Spain, Institut de Fica da Altes Energies (IFAE), The Barcelona Institute of Science and Technology, Campus UAB, Bellaterra, Barcelona, 08193, Spain; Nichol R.C., School of Mathematics and Physics, University of Surrey, Guildford, Surrey, GU2 7XH, United Kingdom; Niemi S.-M., European Space Agency, ESTEC, Keplerlaan 1, Noordwijk, 2201 AZ, Netherlands; Nightingale J.W., School of Mathematics Statistics and Physics, Newcastle University, Herschel Building, Newcastle-upon-Tyne, NE1 7RU, United Kingdom; Padilla C., Institut de Fica da Altes Energies (IFAE), The Barcelona Institute of Science and Technology, Campus UAB, Bellaterra, Barcelona, 08193, Spain; Paltani S., Department of Astronomy, University of Geneva, ch. da Ecogia 16, Versoix, 1290, Switzerland; Pasian F., INAF, Osservatorio Astronomico di Trieste, Via G. B. Tiepolo 11, Trieste, 34143, Italy; Pedersen K., DARK, Niels Bohr Institute, University of Copenhagen, Jagtvej 155, Copenhagen, 2200, Denmark; Percival W.J., Waterloo Centre for Astrophysics, University of Waterloo, Waterloo, N2L 3G1, ON, Canada, Department of Physics and Astronomy, University of Waterloo, Waterloo, N2L 3G1, ON, Canada, Perimeter Institute for Theoretical Physics, Waterloo, N2L 2Y5, ON, Canada; Pettorino V., European Space Agency, ESTEC, Keplerlaan 1, Noordwijk, 2201 AZ, Netherlands; Pires S., UniversitParis-Saclay, UniversitParis Cite, CEA, CNRS, AIM, Gif-sur-Yvette, 91191, France; Polenta G., Space Science Data Center, Italian Space Agency, Via del Politecnico snc, Roma, 00133, Italy; Poncet M., Centre National da Etudes Spatiales, Centre Spatial de Toulouse, 18 avenue Edouard Belin Cedex 9, Toulouse, 31401, France; Popa L.A., Institute of Space Science, Str. Atomistilor, nr. 409 MA gurele, Ilfov, 077125, Romania; Pozzetti L., INAF, Osservatorio di Astrofisica e Scienza Dello Spazio di Bologna, Via Piero Gobetti 93/3, Bologna, 40129, Italy; Raison F., Max Planck Institute for Extraterrestrial Physics, Giessenbachstr. 1, Garching, 85748, Germany; Rebolo R., Instituto de Astrofica de Canarias, Via Ltea, La Laguna, Tenerife, 38205, Spain, Consejo Superior de Investigaciones Cientificas, Calle Serrano 117, Madrid, 28006, Spain, Universidad de la Laguna, Departamento de Astrofica, La Laguna, Tenerife, 38206, Spain; Renzi A., INFN-Padova, Via Marzolo 8, Padova, 35131, Italy, Dipartimento di Fisica e Astronomia G. Galilei, Universitdi Padova, Via Marzolo 8, Padova, 35131, Italy; Rhodes J., Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Drive, Pasadena, 91109, CA, United States; Riccio G., INAF-Osservatorio Astronomico di Capodimonte, Via Moiariello 16, Napoli, 80131, Italy; Romelli E., INAF, Osservatorio Astronomico di Trieste, Via G. B. Tiepolo 11, Trieste, 34143, Italy; Roncarelli M., INAF, Osservatorio di Astrofisica e Scienza Dello Spazio di Bologna, Via Piero Gobetti 93/3, Bologna, 40129, Italy; Rossetti E., Dipartimento di Fisica e Astronomia, Universitdi Bologna, Via Gobetti 93/2, Bologna, 40129, Italy; Saglia R., Universits-Sternwarte Mchen, Fakult f Physik, Ludwig-Maximilians-Universit Mchen, Scheinerstrasse 1, Mchen, 81679, Germany, Max Planck Institute for Extraterrestrial Physics, Giessenbachstr. 1, Garching, 85748, Germany; Sakr Z., Institut f Theoretische Physik, University of Heidelberg, Philosophenweg 16, Heidelberg, 69120, Germany, Institut de Recherche en Astrophysique et Planologie (IRAP), Universitde Toulouse, CNRS, UPS, CNES, 14 Av. Edouard Belin, Toulouse, 31400, France, UniversitSt Joseph, Faculty of Sciences, Beirut, Lebanon; Sapone D., Departamento de Fica, FCFM, Universidad de Chile, Blanco Encalada, Santiago, 2008, Chile; Sartoris B., Universits-Sternwarte Mchen, Fakult f Physik, Ludwig-Maximilians-Universit Mchen, Scheinerstrasse 1, Mchen, 81679, Germany, INAF, Osservatorio Astronomico di Trieste, Via G. B. Tiepolo 11, Trieste, 34143, Italy; Schewtschenko J.A., Institute for Astronomy, University of Edinburgh, Royal Observatory, Blackford Hill, Edinburgh, EH9 3HJ, United Kingdom; Schirmer M., Max-Planck-Institut f Astronomie, Konigstuhl 17, Heidelberg, 69117, Germany; Schneider P., Universit Bonn, Argelander-Institut fur Astronomie, Auf dem Hel 71, Bonn, 53121, Germany; Secroun A., Aix-Marseille Universite, CNRS, IN2P3, CPPM, Marseille, France; Seidel G., Max-Planck-Institut f Astronomie, Konigstuhl 17, Heidelberg, 69117, Germany; Seiffert M., Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Drive, Pasadena, 91109, CA, United States; Serrano S., Institut da Estudis Espacials de Catalunya (IEEC), Edifici RDIT, Campus UPC, Castelldefels, Barcelona, 08860, Spain, Satlantis, University Science Park, Sede Bld, Leioa, Bilbao, 48940, Spain, Institute of Space Sciences, ICE, CSIC, Campus UAB, Carrer de Can Magrans, s/n, Barcelona, 08193, Spain; Sirignano C., INFN-Padova, Via Marzolo 8, Padova, 35131, Italy, Dipartimento di Fisica e Astronomia G. Galilei, Universitdi Padova, Via Marzolo 8, Padova, 35131, Italy; Sirri G., INFN-Sezione di Bologna, Viale Berti Pichat 6/2, Bologna, 40127, Italy; Stanco L., INFN-Padova, Via Marzolo 8, Padova, 35131, Italy; Steinwagner J., Max Planck Institute for Extraterrestrial Physics, Giessenbachstr. 1, Garching, 85748, Germany; Tallada-CrespP., Centro de Investigaciones Energicas, Medioambientales y Tecnolicas (CIEMAT), Avenida Complutense 40, Madrid, 28040, Spain, Port da InformaciCientica, Campus UAB, C. Albareda s/n, Bellaterra, Barcelona, 08193, Spain; Taylor A.N., Institute for Astronomy, University of Edinburgh, Royal Observatory, Blackford Hill, Edinburgh, EH9 3HJ, United Kingdom; Tereno I., Departamento de Fica, Faculdade de Ciencias, Universidade de Lisboa, Edifio C8, Campo Grande, Lisboa, PT1749-016, Portugal, Instituto de Astrofica e Ciencias Do Espa, Faculdade de Ciencias, Universidade de Lisboa, Tapada da Ajuda, Lisboa, 1349-018, Portugal; Toft S., Cosmic Dawn Center (DAWN), Denmark, Niels Bohr Institute, University of Copenhagen, Jagtvej 128, Copenhagen, 2200, Denmark; Toledo-Moreo R., Universidad Politnica de Cartagena, Departamento de Electrica y Tecnologia de Computadoras, Plaza del Hospital 1, Cartagena, 30202, Spain; Torradeflot F., Centro de Investigaciones Energicas, Medioambientales y Tecnolicas (CIEMAT), Avenida Complutense 40, Madrid, 28040, Spain, Port da InformaciCientica, Campus UAB, C. Albareda s/n, Bellaterra, Barcelona, 08193, Spain; Tutusaus I., Institut de Recherche en Astrophysique et Planologie (IRAP), Universitde Toulouse, CNRS, UPS, CNES, 14 Av. Edouard Belin, Toulouse, 31400, France; Valentijn E.A., Kapteyn Astronomical Institute, University of Groningen, PO Box 800, Groningen, 9700 AV, Netherlands; Valenziano L., INAF, Osservatorio di Astrofisica e Scienza Dello Spazio di Bologna, Via Piero Gobetti 93/3, Bologna, 40129, Italy, INFN-Bologna, Via Irnerio 46, Bologna, 40126, Italy; Valiviita J., Department of Physics, University of Helsinki, P.O. Box 64, 00014, Finland, Helsinki Institute of Physics, University of Helsinki, Gustaf Hallstrin katu 2, Helsinki, Finland; Vassallo T., Universits-Sternwarte Mchen, Fakult f Physik, Ludwig-Maximilians-Universit Mchen, Scheinerstrasse 1, Mchen, 81679, Germany, INAF, Osservatorio Astronomico di Trieste, Via G. B. Tiepolo 11, Trieste, 34143, Italy; Verdoes Kleijn G., Kapteyn Astronomical Institute, University of Groningen, PO Box 800, Groningen, 9700 AV, Netherlands; Veropalumbo A., INAF, Osservatorio Astronomico di Brera, Via Brera 28, Milano, 20122, Italy, Dipartimento di Fisica, Universitdi Genova, Via Dodecaneso 33, Genova, 16146, Italy, INFN-Sezione di Genova, Via Dodecaneso 33, Genova, 16146, Italy; Wang Y., Infrared Processing and Analysis Center, California Institute of Technology, Pasadena, 91125, CA, United States; Weller J., Universits-Sternwarte Mchen, Fakult f Physik, Ludwig-Maximilians-Universit Mchen, Scheinerstrasse 1, Mchen, 81679, Germany, Max Planck Institute for Extraterrestrial Physics, Giessenbachstr. 1, Garching, 85748, Germany; Zamorani G., INAF, Osservatorio di Astrofisica e Scienza Dello Spazio di Bologna, Via Piero Gobetti 93/3, Bologna, 40129, Italy; Zerbi F.M., INAF, Osservatorio Astronomico di Brera, Via Brera 28, Milano, 20122, Italy; Zucca E., INAF, Osservatorio di Astrofisica e Scienza Dello Spazio di Bologna, Via Piero Gobetti 93/3, Bologna, 40129, Italy; Burigana C., INFN-Bologna, Via Irnerio 46, Bologna, 40126, Italy, INAF, Istituto di Radioastronomia, Via Piero Gobetti 101, Bologna, 40129, Italy; Gabarra L., Department of Physics, Oxford University, Keble Road, Oxford, OX1 3RH, United Kingdom; Mart-Fleitas J., Aurora Technology for European Space Agency (ESA), Camino Bajo Del Castillo, s/n, Urbanizacion Villafranca del Castillo, Villanueva de la Canada, Madrid, 28692, Spain; Scottez V., Institut da Astrophysique de Paris, 98bis Boulevard Arago, Paris, 75014, France, ICL, Junia, UniversitCatholique de Lille, LITL, Lille, 59000, France
EUI: A Novel Underwater Image Enhancement Network
illumination levels; Low-light image enhancement techniques; underwater image enhancement
The use of optical imaging cameras on underwater vehicles has been increasingly common in recent years. These cameras are increasingly being utilized for the purpose of assisting with the search for aquatic items and the gathering of images. The past ten years have seen the publication of a number of techniques that have been utilized to enhance underwater images. These techniques include enhancing the signal-to-noise ratio and decreasing the amount of backscattered noise at the receiving end. Nevertheless, the development of these algorithms was driven by the need to find a solution to the problem of improving photographs of underwater environments when they are exposed to daylight. The accuracy of these, on the other hand, will not be known until they have been tested on photographs taken underwater in low light conditions. As a result of the fact that dark underwater scene photos typically have an exceptionally low quality and the presence of a great deal of noise, it is simple for artifacts to arise during the process of improvement. In order to fill this need, we conduct an in-depth analysis of the most recent deep learning-based algorithms for the enhancement of underwater images. A novel underwater image augmentation network that is capable of handling the severe decrease in underwater image quality that is induced by low illumination is that which we propose as our last suggestion. Our approach allows for the possibility of ULPs avoiding both low-light damage and scattering at the same time. Additionally, the results of our tests suggest that our method continues to be trustworthy even when exposed to different levels of illumination, which has allowed it to be applied to a wider range of applications. When compared to some of the most cutting-edge strategies for improving underwater pictures that are already in use, as well as techniques for improving low-light images, our method has shown to be superior in terms of performance in a variety of low-light underwater situations. 2025 IEEE.
2nd International Conference on Electronics, Computing, Communication and Control Technology, ICECCC 2025;
https://doi.org/10.1109/ICECCC65144.2025.11063831 https://www.scopus.com/pages/publications/105012021630?origin=resultslist
Sumalatha A., School of Engineering and Technology, CHRIST (Deemed to be University), Department of Computer Science and Engineering, Bengaluru, India; Aruna S.K., School of Engineering and Technology, CHRIST (Deemed to be University), Department of Computer Science and Engineering, Bengaluru, India
European VLBI Network observations of the peculiar radio source 4C 35.06 overlapping with a compact group of nine galaxies
galaxies: active; galaxies: clusters: general; galaxies: formation; galaxies: jets; galaxies: nuclei; radio continuum: galaxies
Context. According to the hierarchical structure formation model, brightest cluster galaxies (BCGs) evolve into the most luminous and massive galaxies in the Universe through multiple merger events. The peculiar radio source 4C 35.06 is located at the core of the galaxy cluster Abell 407, overlapping with a compact group of nine galaxies. Low-frequency radio observations have revealed a helical, steep-spectrum, kiloparsec-scale jet structure and inner lobes with less steep spectra, compatible with a recurring active galactic nucleus (AGN) activity scenario. However, the host galaxy of the AGN responsible for the detected radio emission remained unclear. Aims. We aim to identify the host of 4C 35.06 by studying the object at high angular resolution and thereby confirm the recurrent AGN activity scenario. Methods. To reveal the host of the radio source, we carried out very long baseline interferometry (VLBI) observations with the European VLBI Network of the nine galaxies in the group at 1.7 and 4.9 GHz. Results. We detected compact radio emission from an AGN located between the two inner lobes at both observing frequencies. In addition, we detected another galaxy at 1.7 GHz, whose position appears more consistent with the principal jet axis and is located closer to the low-frequency radio peak of 4C 35.06. The presence of another radio-loud AGN in the nonet sheds new light on the BCG formation and provides an alternative scenario in which not just one but two AGNs are responsible for the complex large-scale radio structure. The Authors 2024.
Veres P.M.; Gabyi K.; Frey S.; Paragi Z.; An T.; Bagchi J.; Bogd ; Biju K.G.; Kun E.; Jacob J.; Adebahr B.
All Open Access; Green Open Access; Hybrid Gold Open Access
Veres P.M., Astronomisches Institut, Ruhr-Universit Bochum, Universitsstr. 150, Bochum, 44801, Germany, Konkoly Observatory, HUN-REN Research Centre for Astronomy and Earth Sciences, Konkoly Thege Mikl 15-17, Budapest, 1121, Hungary, CSFK, MTA Centre of Excellence, Konkoly Thege Mikl 15-17, Budapest, 1121, Hungary; Gabyi K., Department of Astronomy, Institute of Physics and Astronomy, ELTE Ev Lord University, Pmy Per sy 1/A, Budapest, 1117, Hungary, HUN-RENELTE Extragalactic Astrophysics Research Group, ELTE Ev Lord University, Pmy Per sy 1/A, Budapest, 1117, Hungary, Konkoly Observatory, HUN-REN Research Centre for Astronomy and Earth Sciences, Konkoly Thege Mikl 15-17, Budapest, 1121, Hungary, CSFK, MTA Centre of Excellence, Konkoly Thege Mikl 15-17, Budapest, 1121, Hungary; Frey S., Konkoly Observatory, HUN-REN Research Centre for Astronomy and Earth Sciences, Konkoly Thege Mikl 15-17, Budapest, 1121, Hungary, CSFK, MTA Centre of Excellence, Konkoly Thege Mikl 15-17, Budapest, 1121, Hungary, Institute of Physics and Astronomy, ELTE Ev Lord University, Pmy Per sy 1/A, Budapest, 1117, Hungary; Paragi Z., Joint Institute for VLBI ERIC, Oude Hoogeveensedijk 4, Dwingeloo, 7991 PD, Netherlands; An T., Shanghai Astronomical Observatory, Chinese Academy of Sciences, Shanghai, 200030, China, Key Laboratory of Radio Astronomy and Technology, Chinese Academy of Sciences, A20 Datun Road, Chaoyang District, Beijing, 100101, China; Bagchi J., Department of Physics and Electronics, CHRIST (Deemed to be University, Hosur Road, Bangalore, 560029, India; Bogd , Center for Astrophysics, Harvard and Smithsonian, 60 Garden Street, Cambridge, 02138, MA, United States; Biju K.G., W.M.O. Arts and Science College, Muttil, Kerala, Wayanad, 673122, India; Kun E., Astronomisches Institut, Ruhr-Universit Bochum, Universitsstr. 150, Bochum, 44801, Germany, Konkoly Observatory, HUN-REN Research Centre for Astronomy and Earth Sciences, Konkoly Thege Mikl 15-17, Budapest, 1121, Hungary, CSFK, MTA Centre of Excellence, Konkoly Thege Mikl 15-17, Budapest, 1121, Hungary, Theoretical Physics IV, Faculty for Physics and Astronomy, Ruhr University Bochum, Universitsstr. 150, Bochum, 44780, Germany, Ruhr Astroparticle And Plasma Physics Center, Ruhr-Universit Bochum, Universitsstr. 150, Bochum, 44780, Germany; Jacob J., Newman College, Kerala, Thodupuzha, 685584, India; Adebahr B., Astronomisches Institut, Ruhr-Universit Bochum, Universitsstr. 150, Bochum, 44801, Germany
EV Service Stations for Future Smart Cities
batteries; Charging Infrastructure; Electric Vehicles; Training; workforce
The market for electric vehicles (EVs) has been growing at a fast pace in recent years. It is expected to continue growing at a much faster pace in the coming decades. The emerging EV technology is increasingly gaining a high demand for continued good transport connections in smart cities. Most of the Smart Cities' charging infrastructure and future growth revolve around its public transport network, especially an EV service station. New technologies, therefore, need to be complemented with new and versatile charging options to cater to different types of charging options available for charging Li-ion Batteries with newer materials and charging capacity. Building an EV service station in the ongoing scenario anticipates smart engineering knowledge to complement innovative charging methods. An EV service station needs hardware, software, and test equipment before charging, during charge, and post-charge states. It is expected to inform the user of available options to choose and select from. This paper investigates the challenges and suggests solutions to meet the EV service station support for EV vehicles in present and future smart cities. It also highlights the demand for a skilled workforce to maintain these service stations, including updating their skills. Examples of a few smart cities in developed as well as developing countries have been quoted. These developments will contribute to the transport infrastructure needed for future smart cities. The paper paves the way for future research in this area. The Institution of Engineering & Technology 2023.
IET Conference Proceedings, Vol-2023, No. 44, pp. 463-466.
Institution of Engineering and Technology
https://doi.org/10.1049/icp.2024.0968 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85194252113&doi=10.1049%2ficp.2024.0968&partnerID=40&md5=85c876b67c387c81ffe4df36d4a3bcdd
Vishwakarma S., BC Hydro, Vancouver, Canada; Chaurasia A., School of Commerce Finance Accountancy, Christ University, Ghaziabad, India; Tyagi R., Asian Institute of Technology, Thailand
Evaluate and design the mini-hexagon-shaped monopole antenna controller to minimize losses in the unit
Gains; Hexagon shaped patchwork; Returning loss; Slot module; UWB
Main Aim: Hexagon-shaped mono-pole transmitters are developed, computed, and evaluated in a range of applications. Their whole performance is being compared. Methods: Various hexagon-shaped mono-pole transmitters are built and modeled using the HFSS. These transmitters are built with Defective Ground Structure (DGS) but include openings in the patch antenna for High-Frequency Spread Spectrum (HFSS), also on the surface, but also. That influence including its position including its slot upon this radiation pattern is examined. Evaluate the modeling, the controller was designed for the broadcast subsystems and respective reflectivity and VSWR have been found. Findings: The specifications of the antenna is return losses, VSWR, amplification and switching frequency, among other things are assessed as are usually uncertain and VSWR for the manufactured device. The transmissions are continuously monitored. Another most unclear wavelength is around 10 dB among a large bandwidth and that they are less than 10 dB over a specific frequency range. The value of VSWR is less than 2. Applications: These transmitters may be utilized for wirelessly and interior activities via UWB technology. 2021, SciTechnol, All Rights Reserved.
Karthik T.S.; Dinesh Babu N.R.; Raman R.; Meenakshi Sundaram G.; Selvaraju P.; Kumar K.P.
Journal of Nuclear Energy Science and Power Generation Technology, Vol-10, No. 9
Karthik T.S., Department of Electronics and Communication Engineering, Aditya College of Engineering and Technology, Surampalem, Andhra Pradesh, India; Dinesh Babu N.R., Department of Electronics and Communication Engineering, Aditya Engineering College, Surampalem, Andhra Pradesh, India; Raman R., Department of Electronics and Communication Engineering, Aditya College of Engineering, Surampalem, Andhra Pradesh, India; Meenakshi Sundaram G., Department of Electronics and Communication Engineering, Aditya College of Engineering, Surampalem, Andhra Pradesh, India; Selvaraju P., Department of ECE, Kakatiya Institute of Technology and Science (KITS), Warangal, India; Kumar K.P., Department of Computer Science and Engineering, Christ University, Kanmanike, Kumbalagodu, Karnataka, India
Evaluate Machine Learning Techniques for Early Disease of Cardiovascular Disease
Early; Heart Disease Prediction; Machine Learning
Cardiovascular diseases are one of the major causes of death around the world, and their early detection is critical for effective intervention. The paper presents a systematic review of machine learning techniques used for the early prediction of cardiovascular diseases, focusing on studies carried out between 2019 and 2024. Widely used models considered in the review include Logistic Regression, Support Vector Machines, Random Forest, K-Nearest Neighbors, Gradient Boosting, and hybrid ensemble methods with the aim of ascertaining predictive accuracy, interpretability, and clinical relevance. In most of the reviewed studies, ensemble and Random Forest models attained the highest accuracies of 90% - 98%, while Gradient Boosting and SVMs were mostly above 90% in balanced datasets. Logistic Regression had a moderate accuracy of 85%-91% but remained the most interpretable, while KNN established the lowest performance of 80%-86%. Despite the promising strides, there are a number of limitations, such as imbalance in datasets, limited external validation, and small benchmark datasets, that are limiting general application in health. This systematic review highlights strengths and weaknesses of the contemporary machine learning approaches and makes it evident that clinically validated, interpretable, and generalizable models should be developed in order to assist real-world medical decision-making. 2025 IEEE.
Sushmitha, M.T.; Saxena, Surabhi; Singhal, Neha
5th IEEE International Conference on Mobile Networks and Wireless Communications, ICMNWC 2025;
https://doi.org/10.1109/ICMNWC66779.2025.11354433 https://www.scopus.com/pages/publications/105033716958?origin=resultslist
Sushmitha M.T., Christ University, Department of Computer Science, Bangalore, India; Saxena S., Christ University, Department of Computer Science, Bangalore, India; Singhal N., Christ University, Department of Computer Science, Bangalore, India
caste; education; equalization of opportunity; gender; groups; probability distribution; zonotope
This paper provides a robust criterion for comparing lists of probability distributionsinterpreted as allocations of opportunitiesfaced by different social groups. We axiomatically argue in favor of comparing those lists of probability distributions on the basis of a uniformamong groupsvaluation of their expected utility. We identify an empirically implementable criterion for comparing allocations of opportunities that coincides with the unanimity of all such uniform valuations of expected utility that exhibit aversion to inequality of opportunity. We illustrate our criterion by evaluating allocations of educational opportunities among castes and genders in 14 Indian states. 2025 The Author(s). International Economic Review published by Wiley Periodicals LLC on behalf of The Economics Department of the University of Pennsylvania and the University of Osaka Institute of Social and Economic Research Association.
Andreoli, Francesco; Faure, Mathieu; Gravel, Nicolas; Kundu, Tista
International Economic Review;Volume;67;Issue;1;pp.365-397
https://doi.org/10.1111/iere.70020 https://www.scopus.com/pages/publications/105016132849?origin=resultslist
Andreoli F., Department of Economics, University of Verona, Verona, Italy, Luxembourg Institute of Socio-Economic Research, LISER, Luxembourg; Faure M., Aix-Marseille School of Economics, Aix-Marseille University, CNRS, Cedex, Marseille, France; Gravel N., Aix-Marseille School of Economics, Aix-Marseille University, CNRS, Aix-en-Provence, France; Kundu T., CHRIST University, Karnataka, Bangalore, India
Evaluating Building Damage Classification Accuracy: A Benchmarking Study of UNet
augmentation; classification; damage assessment; Deep learning; satellite images
Building damage classification must be done accurately and quickly in order to support disaster response and recovery activities. Deep learning models, particularly U-Net, have demonstrated strong potential in automating damage assessment from satellite and aerial imagery. This study benchmarks the accuracy of U-Net in classifying building damage across multiple datasets, evaluating its performance against ground truth labels. Key factors such as data preprocessing, augmentation techniques, and model variations are analyzed to determine their impact on classification accuracy. The results provide insights into the strengths and limitations of variations in U-Net for damage assessment, highlighting areas for improvement and future research directions 2025 IEEE.
Ikkara, Sajitha; Sambandam, Rakoth Kandan; John, Saju P.
2025 IEEE International Conference on Next-Gen Technologies of Artificial Intelligence and Geoscience Remote Sensing, EarthSense 2025;
https://doi.org/10.1109/EarthSense66084.2025.11297371 https://www.scopus.com/pages/publications/105032199046?origin=resultslist
Ikkara S., Christ University, Dept. of Computer Science and Engineering, Karnataka, Bangalore, India; Sambandam R.K., Jyothi Engineering College, Dept. of Computer Science and Engineering, Kerala, Thrissur, India; John S.P., Christ University, Dept. of Computer Science and Engineering, Karnataka, Bangalore, India
Evaluating Energy Consumption Patterns in a Smart Grid with Data Analytics Models
Accuracy; Big data analytics; Decision tree; Effective energy management; Smart grid
With the rapid pace of technological advancement, it is a well established fact that in todays era, economical and industrial development go hand in hand with the growth in technology. Today, massive amounts of data are generated everyday and are only growing exponentially. The collected data, whether structured or unstructured, could prove to be very beneficial in terms of improving operational efficiency by analyzing and extracting valuable information to find patterns to optimize asset utilization and improve asset intelligence. Big data analytics can very well contribute to the evolution of the digital electrical power industry. The objective of this paper is to explore how smart grid technology can be enhanced by leveraging big data analytics. Different predictive models are used for the purpose. Among them, decision tree model outperformed others recording a training and tetsing accuracy of 94.4% and 92.7% respectively while noting a least execution latency of only 4.3 seconds. 2023 IEEE.
Mishra S.; Sivani T.; Swain T.; Sharma V.; Alkhayyat A.
2023 2nd International Conference on Smart Technologies for Smart Nation, SmartTechCon 2023, pp. 1072-1077.
https://doi.org/10.1109/SmartTechCon57526.2023.10391483 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85184828877&doi=10.1109%2fSmartTechCon57526.2023.10391483&partnerID=40&md5=31941dce418d1efd7ec6b557a62ea0db
Mishra S., School of Computer Engineering, Kalinga Institute of Industrial Technology, Bhubaneswar, India; Sivani T., School of Computer Engineering, Kalinga Institute of Industrial Technology, Bhubaneswar, India; Swain T., School of Computer Engineering, Kalinga Institute of Industrial Technology, Bhubaneswar, India; Sharma V., CHRIST(Deemed to be University), Delhi-NCR, India; Alkhayyat A., College of Technical Engineering, The Islamic University, Najaf, Iraq
Evaluating forces associated with sentient drivers over the purchase intention of organic food products
Consumer awareness; Organic food; Purchase intention
The study proposes to find out the factors which influence awareness among the consumers towards purchasing organic food product. The study is based on primary data by using tools Chi-square test, Cronbach alpha, KMO, and Bartlett's test, ANOVA, regression, correlation, and cross-tabulation. The study found that awareness driver's nutritional information, price, certification, brand name, and logos have an essential influence on the purchase intention of the product of organic food. However, labeling and food standards do not show a noteworthy rapport between labeling and organic food products' purchase plans. The core commitment and flow to explore are to analyze purchasers with respect to organic guarantee systems (accreditation, guidelines, logo, imprints, and confirmation) so we can distinguish the genuine organic products. The independent factors of awareness like organic buying preference and buying frequency, have a significant influence on the purchase intention of organic food. The research provided evidence of consumer awareness and purchase intention of organic food that would help the organic food industry to promote their products according to the attribute of customers. 2020 Asian Economic and Social Society. All rights reserved.
Kiran P.; Srivastava A.; Tiwari S.C.; Ramaiah T.S.
Asian Journal of Agriculture and Rural Development, Vol-10, No. 1, pp. 284-297.
Kiran P., School of Business and Management, Christ (Deemed to be University), Bangalore, India; Srivastava A., Faculty of Management Studies, Gopal Narayan Singh University, Rohtas, India; Tiwari S.C., Department of Finance and Accounting, IBS Hyderabad, Deemed to be University, Hyderabad, India; Ramaiah T.S., Department of Finance, ICFAI Business School, IFHE (Deemed to be University), Hyderabad, Telangana, India
Evaluating Generalization and Robustness of U-Net Based Image Steganography
Deep Learning; Generalization; Image Steganography; Robustness; U-Net
This paper investigates the effectiveness and generalization ability of U-Net based image steganography models across multiple datasets, with comparisons to the classical Least Significant Bit (LSB) substitution method. Models were trained on STL-10, CIFAR-10, and Stanford Cars datasets and evaluated both in-distribution and on out-of-distribution internet images. Results show that the STL-10 model consistently achieved the best trade-off between imperceptibility and recovery quality, while the CIFAR-10 model failed to generalize due to its low resolution and limited diversity. Baseline experiments confirmed that LSB achieves extremely high PSNR and SSIM at low payloads, but suffers sharp increases in Bit Error Rate (BER) under higher payloads or even mild distortions such as JPEG compression and Gaussian noise. By contrast, the U-Net model provided more stable recovery and greater robustness, highlighting the advantages of learned feature embeddings over handcrafted substitution. These findings underscore the importance of dataset diversity and robustness testing in developing practical steganographic systems for real-world deployment. 2025 IEEE.
Adithiya, Dhanush; Jayabalan, Bhuvana; Beaulah Soundarabai, P.; Augustin, Peter
Proceedings - 2025 International Conference on Transformative Computing Technologies, ICTCT 2025;pp.178-183
https://doi.org/10.1109/ICTCT69201.2025.00045 https://www.scopus.com/pages/publications/105037437357?origin=resultslist
Adithiya D., Christ (Deemed to be) University, Department of Computer Science, Bangalore, India; Jayabalan B., Christ (Deemed to be) University, Department of Computer Science, Bangalore, India; Beaulah Soundarabai P., Christ (Deemed to be) University, Department of Computer Science, Bangalore, India; Augustin P., Christ (Deemed to be) University, Department of Computer Science, Bangalore, India
Evaluating prolonged corrosion inhibition performance of benzyltributylammonium tetrachloroaluminate ionic liquid using electrochemical analysis and Monte Carlo simulation
Carbon steel; Electrochemical noise analysis; Ionic liquid; Molecular simulation
Corrosion inhibition performance of a newly synthesized ionic liquid Benzyltributylammonium tetrachloroaluminate [BTBA]+[AlCl4]?on carbon steel has been studied using electrochemical impedance and noise analysis in 2 N HCl medium. The synthesized product was characterized by ATR-FTIR and1H NMR spectroscopic studies. The investigation revealed that the synthesized ionic liquid, [BTBA]+[AlCl4]?showed a remarkable noise and charge transfer resistance against corrosion. The adsorption behaviour of [BTBA]+[AlCl4]- on metal surface was found to follow Langmuir adsorption isotherm. The inhibition efficiency is measured as a function of immersion time and exhibited prolonged protection against acidic corrosion. Results derived from UVVis spectra explained the complex formation between the metal surface and ionic liquid in acid medium. SEM/EDAX has been used to examine the surface protection offered by the ionic liquid. [BTBA]+[AlCl4]?ionic liquid exhibited good corrosion inhibitor property with an efficiency of 97% at the optimum concentration. Quantum chemical analysis and molecular simulation studies were performed to support the experimental data. 2019 Elsevier B.V.
Kannan P.; Varghese A.; Palanisamy K.; Abousalem A.S.
https://doi.org/10.1016/j.molliq.2019.111855 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85075416046&doi=10.1016%2fj.molliq.2019.111855&partnerID=40&md5=14f6929ad8899df62a492f9e5efec341
Kannan P., Department of Chemistry, CHRIST (Deemed to be University), Bengaluru, 560 029, Karnataka, India; Varghese A., Department of Chemistry, CHRIST (Deemed to be University), Bengaluru, 560 029, Karnataka, India; Palanisamy K., Department of Chemistry, Srinivasan College of Arts and Science, Perambalur, 621 212, Tamil Nadu, India; Abousalem A.S., Chemistry Department, Faculty of Science, Mansoura University, Mansoura, 35516, Egypt, Quality Control Lab, Operations Department, Jotun, Egypt
Evaluating Sentiment Classification Models for Bollywood Movies
Bollywood; Gradient boosting machines; Movie reviews; Random forest model; Sentiment analysis; Sentiment classification
The rise in popularity of Bollywood cinema, fueled by streaming services such as Netflix and Amazon Prime, has increased the global availability of Hindi-language films. This study investigates the sentiment analysis of Bollywood movie reviews using a dataset of 1,698 movies released between 2005 and 2017. The research examines three main dimensions: confusion matrix, evaluation metric, and random forest model. The results highlight the model's ability to accurately predict emotions, especially when detecting neutral and positive emotions. Challenges in identifying negative emotions persist. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
Kunnumpurath, Biju; Reddy, Baddala Govardhan; Menon, Vishnu Achutha; Paul, Ajith
Lecture Notes in Networks and Systems;Volume;1275;pp.161-169
https://doi.org/10.1007/978-981-96-2694-6_11 https://www.scopus.com/pages/publications/105007225467?origin=resultslist
Kunnumpurath B., Christ University, Bengaluru, India; Reddy B.G., Christ University, Bengaluru, India; Menon V.A., Institute for Educational and Developmental Studies, Uttar Pradesh, Gautambuddha Nagar, India; Paul A., Christ University, Bengaluru, India
Evaluating social media content's effect on consumer engagement in the context of digital marketing
Costs and metrics; Customer engagement; Customer experience; Customer reviews; Social media influence; Social media platforms
The advancement of social media platforms in promoting consumer participation in brand development and sustainable consumption has been substantial. Social media's popularity has increased significantly in the twenty-first century. To enhance sales performance, enterprises consistently seek novel strategies to integrate these platforms into their promotional initiatives. Social media functions as a platform for networking and communication; consequently, organizations must imbue their brands with personality to connect with consumers. Despite extensive academic research on corporate social media marketing techniques, the influence of these activities on consumer purchase choices remains largely unexplored. Organizations have recently embraced influencer marketing as a tactic to promote and publicize their content by leveraging the support of influential individuals. The growing frequency of product endorsements on social media highlights the importance of understanding the impact that these influencers have on customers. This research aims to analyze the influence of social media content and its characteristics on consumer engagement in the digital domain. Additionally, this study will serve as a foundation for future investigations in this area. The insights regarding the content elements of social media marketing that foster consumer engagement were contributed by seventy-five unique social media users. 2025 by the authors; licensee Learning Gate.
Roy, Rumpa; Rane, Sagar Ramesh; Komatiguntala, Dhanalakshmi; Sontineni, Ramesh Babu; Balakrishnan, Srinivasan Moharkonda; Bommisetti, Ravi Kumar
Edelweiss Applied Science and Technology;Volume;9;Issue;6;pp.521-536
https://doi.org/10.55214/25768484.v9i6.7828 https://www.scopus.com/pages/publications/105007992253?origin=resultslist
Roy R., Gulf University, Administrative Science Department, College of Administrative and Financial Science, Gulf University, Sanad, 26489, Bahrain; Rane S.R., Department of Computer Engineering, Army Institute of Technology, Dighi Hills, Alandi Road, Pune, 411015, India; Komatiguntala D., School of Business and Management, Christ University-Yeswanthpur Campus, Bangalore, India; Sontineni R.B., Department of MBA, KL Business School, Koneru Lakshmaiah Education Foundation, Guntur, 522302, India; Balakrishnan S.M., School of Business and Management CHRIST (Deemed to be University), Bangalore, India; Bommisetti R.K., Andhra Pradesh, India
Evaluating Social Priorities in Environmental Social Governance for the BFSI Sector: A Fuzzy Analytic Hierarchy Process Perspective
BFSI sector; ESG; Fuzzy AHP; Social factor
As global financial systems evolve, the Banking, Financial Services, and Insurance (BFSI) sector faces increasing pressure to balance financial performance with Environmental, Social, and Governance (ESG) obligations. However, integrating social factors such as employee welfare, community engagement, customer satisfaction, and diversity and inclusion remains challenging due to their subjective and often intangible nature. This study addresses this issue by applying the Fuzzy Analytic Hierarchy Process (Fuzzy AHP) to evaluate and prioritize social factors within the ESG framework. The Fuzzy AHP method, which combines traditional AHP with fuzzy logic to manage uncertainty in expert judgments, was used to gather and analyze input from BFSI sector experts. The study assessed the relative importance of social factors through structured pairwise comparisons, providing a clear hierarchy of priorities for BFSI institutions. The results reveal that employee welfare and customer satisfaction emerged as the most critical social aspects, reflecting stakeholder expectations and regulatory pressures. By focusing on these key areas, BFSI institutions can enhance their ESG performance and meet sustainability goals. These findings offer actionable insights for decision-makers in the BFSI sector, allowing them to better allocate resources to social initiatives that not only satisfy regulatory requirements but also contribute to long-term business value and societal impact. This study underscores the importance of prioritizing social factors in sustainable strategies and provides a robust framework for navigating the complexities of ESG integration. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
Maladkar, Geeta; Suresha, B.; Hawaldar, Aparna; Anuradha, R.
Lecture Notes in Networks and Systems;Volume;1373 LNNS;pp.1-15
https://doi.org/10.1007/978-981-96-5729-2_1 https://www.scopus.com/pages/publications/105015507214?origin=resultslist
Maladkar G., School of Business and Management, Christ University, Bengaluru, India; Suresha B., School of Business and Management, Christ University, Bengaluru, India; Hawaldar A., School of Business and Management, Christ University, Bengaluru, India; Anuradha R., School of Business and Management, Christ University, Bengaluru, India
Evaluating Technostress: Work-Life Balance and Well-Being in Varied Work Contexts
Digital overload; Technostress; Well-being; Work modes; Work-life balance; Workplace stressors
In the contemporary digital landscape, the phenomenon of technostress, defined as stress induced by technology usage, has emerged as a crucial factor influencing work-life balance and employee well-being. This study will explore the impact of technostress in varied work modes such as traditional office-based, remote, and hybrid models. Employing a quantitative approach, the researcher conducted surveys on a representative sample of employees across multiple industries. The results indicate that technostress adversely influences work-life balance and well-being, and the difference in various work modes is observable. Further, it has also been observed that there are significant differences in technostress and well-being concerning the various work modes; working from home comes out to be a positive option, which is related to lesser levels of technostress and higher outcomes of well-being. The present study shows how organisational interventions may be implemented in mitigating technostress-inducing effects: induction of digital literacy, instillation of appropriate communication policies, and embedding of supportive work culture. Essentially, an intervention could help organisations improve well-being 0f employees and achieve better work-life balance in a digital environment. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
Springer Proceedings in Business and Economics;pp.83-101
https://doi.org/10.1007/978-981-96-8582-0_5 https://www.scopus.com/pages/publications/105011987635?origin=resultslist
Joy S., School of Business and Management, Indian Institute of Management Bangalore, Bengaluru, India; Arun Kumar A., School of Business and Management, Christ University Bangalore, Bengaluru, India
Evaluating the Categorical Exclusion of Khasi Women from Inheritance and Property Rights : A Case of East Khasi Hills
customary laws; East Khasi Hills; gender equality; inheritance; Khasi
Customary laws govern inheritance among many tribal communities that fall within the ambit of the fifth and sixth schedules of the Indian Constitution. Under this papers scope, we shall look at the Khasi community hailing from the state of Meghalaya which is a matrilineal community. Where the Khasis draw their lineage from their mothers, there is a misnomer that women inherit and own the entire property. In light of the abovementioned background, the paper makes an analytical study of the customary inheritance rights of Khasi women, the nature of resource ownership and attempts to understand the grounds behind the claims of gender preference in the existing matrilineal system practised by the Khasis of Meghalaya. We also look at the intersection of gender and matrilineal system of inheritance in the Khasi community, the dispute between customs and legislations and examine whether there exists a need for codification. The paper also discusses the findings of the survey and focus group discussions including 90 Khasi women from East Khasi Hills and their growing consensus on equal inheritance rights but resistance towards statutory laws to govern their lives. JYOTI SINGH AND KAJORI BHATNAGAR, 2024.
International Journal on Minority and Group Rights, Vol-1, No. 1
https://doi.org/10.1163/15718115-bja10143 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85184778359&doi=10.1163%2f15718115-bja10143&partnerID=40&md5=707da6a56028cd79a3fea68a9766f693
Singh J., School of Law, Christ University, Bangalore, India; Bhatnagar K., School of Law, Christ University, Bangalore, India