1,132 results on '"Raj T."'
Search Results
52. An efficient reconfigurable FIR filter design with coefficient optimization using a modified bacterial foraging optimization algorithm
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Kalamani, C., primary, Lekashri, S., additional, Duraivel, A.N., additional, and Selvin Retna Raj, T., additional
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- 2024
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53. Occupational Heat Stress: A Technical Scan
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Srinivasan, Krishnan, primary, Mohan, Smisha, additional, and Berlin Raj T, Jeneth, additional
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- 2021
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54. Topographic mapping of oxygen extraction and cerebral venous blood volume fraction in Brain tumors using quantitative BOLD: A case report
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Raj T., Arun, primary, K., Karthik, additional, and Paul, Joseph Suresh, additional
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- 2023
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55. Teratocarcinosarcoma: A rare malignant tumor of sinonasal tract
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Raj T S, Preetham, primary and C, Nirmala, additional
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- 2023
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56. Current Clinical Trials and Vaccine Development Strategies for Corona Virus Disease (COVID-19)
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Abhi Bhadra, Shweta Singh, Shaswat Chandrakar, Vanshika Kumar, Sakshi Sankhla, Sayuj Raj T., and E. Selvarajan
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lopinavir ,ritonavir ,chloroquine ,hydroxychloroquine ,stem cell therapy ,cytokines ,remdesivir ,Microbiology ,QR1-502 - Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has reached global epidemic status claiming more than 319K lives and affecting more than 4.81M people and counting worldwide. Considering the severity of the situation and low recovery rate many research institutions and pharmaceutical industries are rushing to learn more about this new virus and the morbid physiology of this disease with effective diagnostic methods, therapeutic agents and vaccines. Various approaches are highlighted for comparing the possible treatment methods available for COVID-19 some of which are BCG vaccination on COVID-19 and Non-pharmaceutical interventions, drug based clinical trials of Hydroxychloroquine-Azithromycin, chloroquine, lopinavir/ritonavir, ChAdOx1 nCoV-19, Remdesivir, Stem Cell therapy and mesenchymal stromal cell therapy, etc.
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- 2020
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57. A nurse-led paediatric oncology fast-track clinic proves a successful ambulatory intervention for patients
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Wong, A., Glogolia, M., Lange, P. W., Dale, S., Chappell, M., Soosay Raj, T., Hanna, D., Devaraja, L., Williams, C., Williamson, J., and Conyers, R.
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- 2020
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58. An attribute-based lightweight cloud data access control using hypergraph structure
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Mythili, R., Venkataraman, Revathi, and Sai Raj, T.
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- 2020
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59. Design and Analysis of a Permanent Magnet DC Motor
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Senthil Kumar, A., Prasath Vijay Raj, T., Tharagesh, A., Prasanna, V., Angrisani, Leopoldo, Series editor, Arteaga, Marco, Series editor, Chakraborty, Samarjit, Series editor, Chen, Jiming, Series editor, Chen, Tan Kay, Series editor, Dillmann, Ruediger, Series editor, Duan, Haibin, Series editor, Ferrari, Gianluigi, Series editor, Ferre, Manuel, Series editor, Hirche, Sandra, Series editor, Jabbari, Faryar, Series editor, Kacprzyk, Janusz, Series editor, Khamis, Alaa, Series editor, Kroeger, Torsten, Series editor, Ming, Tan Cher, Series editor, Minker, Wolfgang, Series editor, Misra, Pradeep, Series editor, Möller, Sebastian, Series editor, Mukhopadhyay, Subhas Chandra, Series editor, Ning, Cun-Zheng, Series editor, Nishida, Toyoaki, Series editor, Panigrahi, Bijaya Ketan, Series editor, Pascucci, Federica, Series editor, Samad, Tariq, Series editor, Seng, Gan Woon, Series editor, Veiga, Germano, Series editor, Wu, Haitao, Series editor, Zhang, Junjie James, Series editor, Konkani, Avinash, editor, Bera, Rabindranath, editor, and Paul, Samrat, editor
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- 2018
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60. Secretagogin Regulates Insulin Signaling by Direct Insulin Binding
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Sharma, Anand Kumar, Khandelwal, Radhika, Kumar, M. Jerald Mahesh, Ram, N. Sai, Chidananda, Amrutha H., Raj, T. Avinash, and Sharma, Yogendra
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- 2019
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61. Genetics of rheumatoid arthritis contributes to biology and drug discovery
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Criswell, Lindsey, Okada, Y, Wu, D, Trynka, G, Raj, T, Terao, C, Ikari, K, Kochi, Y, Ohmura, K, Suzuki, A, and Yoshida, S
- Abstract
A major challenge in human genetics is to devise a systematic strategy to integrate disease-associated variants with diverse genomic and biological data sets to provide insight into disease pathogenesis and guide drug discovery for complex traits such as r
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- 2014
62. Food Preponderance Index and Feeding Habit of Macrognathus pancalus, (Hamilton, 1822) from Kotpally Reservoir Vikarabad District, Telangana State, India
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Sugunavathi, K., primary, Vani, P. Rupa, additional, and Raj, T. Samul David, additional
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- 2023
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63. Automated Speed Braking System Depending on Vehicle Over Speed Using Digital Controller
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Nagaraju, Ch., primary, Thirumalaiah, G., additional, Rajesh, N., additional, Bala Manikanta, B., additional, Sai Sivaram, N., additional, and Prakash Raj, T., additional
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- 2020
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64. Quantification of Tool Wear Condition from the Sound Recorded During the Process Using Neural Network
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Samraj, Andrews, primary, Ragupathi., P, additional, Nandhakumar., T, additional, and Kamala raj., T, additional
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- 2020
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65. IOT and Deep Learning Assisted Smart Agriculture System for Plant Disease Identification
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Selvaraj S., Thangarajan R., Santhosh C., and Vikash Raj T K.
- Abstract
Agriculture employed more than 50% of labours and contributed nearly 18% to country's GDP. India is the leading producers of Many crops, such as wheat, rice, lentils, cotton, peanuts and perishable products but in recent years, the percentage of people getting into agriculture has been reduced. Crop disease and incorrect maintenance of humidity and moisture is the major reason that makes new farmers frustrated. Developing a deep learning model, that can identify the crop disease with high accuracy, and using this model one can easily identify the crop disease which makes easier for them treat the crop with pesticide, so that we cant wait for the experts. Using the IOT architecture to find the humidity and soil moisture of the field so that the farmer can maintain the correct level of humidity and soil moisture through irrigation, sometimes extreme high and very low moisture and humidity leads to diseases. An enhanced classification model was suggested in this paper to classify leaf diseases. Dataset with more than 10000 images is used for image classification. Classification accuracy is achieved using AlexNet model and it came out to be the highest in comparison to other models, and IOT part using the Raspberry pi 3 kit with soil moisture and humidity and soil moisture sensor.
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- 2023
66. Morphological and molecular identification of the freshwater crab, Barytelphusa cunicularis from Kanniyakumari, India.
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Raj, T. G. Teeni Janet, Suganthi, A. Shyla, Raj, T. G. Tyni Joice, and Anilkumar, G.
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- 2023
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67. Effect of dimethyl carbonate (DMC) on the electrochemical and cycling properties of solid polymer electrolytes (PVP-MSA) and its application for proton batteries
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Ambika, C., Karuppasamy, K., Vikraman, Dhanasekaran, Lee, Ji Young, Regu, T., Ajith Bosco Raj, T., Prasanna, K., and Kim, Hyun-Seok
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- 2018
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68. The experimental investigation on performance and emission characteristics of ceramic coated diesel engine using diesel and biodiesel
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Krishnamani, S., Harish, V., HariShankar, V., and Raj, T. Mohan
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- 2018
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69. Fine-Mapping the Genetic Association of the Major Histocompatibility Complex in Multiple Sclerosis: HLA and Non-HLA Effects
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Oksenberg, Jorge, Gourraud, Pierre-Antoine, Patsopoulos, NA, Barcellos, LF, Hintzen, RQ, Schaefer, C, van, CM, Noble, JA, Raj, T, Gourraud, PA, and Stranger, BE
- Abstract
The major histocompatibility complex (MHC) region is strongly associated with multiple sclerosis (MS) susceptibility. HLA-DRB1*15:01 has the strongest effect, and several other alleles have been reported at different levels of validation. Using SNP data fr
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- 2013
70. Genome-Wide Association Study and Gene Expression Analysis Identifies CD84 as a Predictor of Response to Etanercept Therapy in Rheumatoid Arthritis
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Criswell, Lindsey, Cui, J, Stahl, EA, Saevarsdottir, S, Miceli, C, Diogo, D, Trynka, G, Raj, T, Mirkov, MU, Canhao, H, and Ikari, K
- Abstract
Anti-tumor necrosis factor alpha (anti-TNF) biologic therapy is a widely used treatment for rheumatoid arthritis (RA). It is unknown why some RA patients fail to respond adequately to anti-TNF therapy, which limits the development of clinical biomarkers to
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- 2013
71. Al2O3-incorporated proton-conducting solid polymer electrolytes for electrochemical devices: a proficient method to achieve high electrochemical performance
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Regu, T., Ambika, C., Karuppasamy, K., Jeon, Ji-Hoon, Jeong, Yen-Tae, Vikraman, Dhanasekaran, Raj, T. Ajith Bosco, and Kim, Hyun-Seok
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- 2019
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72. Proton transport and dielectric properties of high molecular weight polyvinylpyrrolidone (PVPK90) based solid polymer electrolytes for portable electrochemical devices
- Author
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Regu, T., Ambika, C., Karuppasamy, K., Rajan, Hashikaa, Vikraman, Dhanasekaran, Jeon, Ji-Hoon, Kim, Hyun-Seok, and Ajith Bosco Raj, T.
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- 2019
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73. WFCM based big sensor data error detection and correction in wireless sensor network
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Sheeba, R., Jiji, G., and Raj, T. Ajith Bosco
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- 2019
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74. A novel ROA optimized Bi-LSTM based MPPT controller for grid connected hybrid solar-wind system
- Author
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Dharma Raj T., Kumar C., Subramaniam G., Dhanesh Raj T., and Jasper J.
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Computational Theory and Mathematics ,Applied Mathematics ,Electrical and Electronic Engineering ,Computer Science Applications - Abstract
Purpose Renewable energy sources such as solar photovoltaic (PV) and wind are ubiquitous because of their lower environmental impact. Output from solar PV and wind turbines is unstable; hence, this article aims to propose an effective controller to extract maximum available power. Design/methodology/approach By focusing on the varying nature of solar irradiance and wind speed, the paper presents the maximum power point tracking (MPPT) technique for renewable energy sources, and power regulation is made by the novel inverter design. Moreover, a DC–DC boost converter is adopted with solar PV, and a doubly fed induction generator is connected with the wind turbine. The proposed MPPT technique is used with the help of a rain optimization algorithm (ROA) based on bi-directional long short-term memory (Bi-LSTM) (ROA_Bi-LSTM). In addition, the sinusoidal pulse width modulation inverter is used for DC–AC power conversion. Findings The proposed MPPT technique has jointly tracked the maximum power from solar PV and wind under varying climatic conditions. The power flow to the transmission line is stabilized to protect the load devices from unregulated frequency and voltage deviations. The power to the smart grid is regulated by three-level sinusoidal pulse width modulation inverter. Originality/value The methodology and concept of the paper are taken by the author on their own. They have not taken a duplicate copy of any other research article.
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- 2022
75. Acute myeloid leukemia patients with variant or unusual translocations involving chromosomes 8 and 21 - A comprehensive cytogenetic profiling of three cases with review of literature
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Raj, T. Akhila, Gopinath, Preethi, Raj, J. Geetha, Narayanan, Geetha, Nair, Sreejith, Philip, Deepa Joy, Raveendran, Suresh, Geetha, Priya, and Sreedharan, Hariharan
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Translocation (Genetics) -- Case studies -- Identification and classification ,Health - Abstract
Byline: T. Akhila Raj, Preethi. Gopinath, J. Geetha Raj, Geetha. Narayanan, Sreejith. Nair, Deepa. Joy Philip, Suresh. Raveendran, Priya. Geetha, Hariharan. Sreedharan Background: t(8;21)(q22;q22) is the most frequent recurrent translocation [...]
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- 2022
76. Low Power and Improved Speed Montgomery Multiplier using Universal Building Blocks
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Velrajkumar, P., primary, Senthilpari, C., additional, Sheela Francisca, J., additional, and Nirmal Raj, T., additional
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- 2023
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77. Marine sediment sample was collected and the total aerobic population was counted and probiotic Bacillus cereus was isolated. Then it was mixed with formulated feed by spraying, while control diet was purchased from a local aquarium. 30 days of feeding ex
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Mahadevi, S., primary, P, Keerthika., additional, H, Ann Suji., additional, N, Padmini., additional, Deivasigamani, B, additional, and Raj, T Suthin, additional
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- 2023
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78. Natural Fiber‐Based Food Packaging Films
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Rajeshkumar, G., primary, Karthick, M., additional, Aseel Ahmed, A.K., additional, Vikram Raj, T., additional, Abinaya, V., additional, Madhu Mitha,, K., additional, and Ronia Richelle, R., additional
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- 2023
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79. Implementation of 18-Bit High-Speed Binary Multipliers
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Sreelakshmi, S., Vandana Raj, T., Kacprzyk, Janusz, Series editor, Dash, Subhransu Sekhar, editor, Bhaskar, M. Arun, editor, Panigrahi, Bijaya Ketan, editor, and Das, Swagatam, editor
- Published
- 2016
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80. Design and Implementation of 270-Tap Finite Impulse Response Filter
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Vandana Raj, T., Sreelakshmi, S., Kacprzyk, Janusz, Series editor, Dash, Subhransu Sekhar, editor, Bhaskar, M. Arun, editor, Panigrahi, Bijaya Ketan, editor, and Das, Swagatam, editor
- Published
- 2016
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81. New insights into the genetic etiology of Alzheimer's disease and related dementias
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Bellenguez, C., Küçükali, F., Jansen, I. E., Kleineidam, L., Moreno-Grau, S., Amin, N., Naj, A. C., Campos-Martin, R., Grenier-Boley, B., Andrade, V., Holmans, P. A., Boland, A., Damotte, V., van der Lee, S. J., Costa, M. R., Kuulasmaa, T., Yang, Q., de Rojas, I., Bis, J. C., Yaqub, A., Prokic, I., Chapuis, J., Ahmad, S., Giedraitis, V., Aarsland, D., Garcia-Gonzalez, P., Abdelnour, C., Alarcón-Martín, E., Alcolea, D., Alegret, M., Alvarez, I., Álvarez, V., Armstrong, N. J., Tsolaki, A., Antúnez, C., Appollonio, I., Arcaro, M., Archetti, S., Pastor, A. A., Arosio, B., Athanasiu, L., Bailly, H., Banaj, N., Baquero, M., Barral, S., Beiser, A., Pastor, A. B., Below, J. E., Benchek, P., Benussi, L., Berr, C., Besse, C., Bessi, V., Binetti, G., Bizarro, A., Blesa, R., Boada, M., Boerwinkle, E., Borroni, B., Boschi, S., Bossù, P., Bråthen, G., Bressler, J., Bresner, C., Brodaty, H., Brookes, K. J., Brusco, L. I., Buiza-Rueda, D., Bûrger, K., Burholt, V., Bush, W. S., Calero, M., Cantwell, L. B., Chene, G., Chung, J., Cuccaro, M. L., Carracedo, Á., Cecchetti, R., Cervera-Carles, L., Charbonnier, C., Chen, H. -H., Chillotti, C., Ciccone, S., Claassen, J. A. H. R., Clark, C., Conti, E., Corma-Gómez, A., Costantini, E., Custodero, C., Daian, D., Dalmasso, M. C., Daniele, A., Dardiotis, E., Dartigues, J. -F., de Deyn, P. P., de Paiva Lopes, K., de Witte, L. D., Debette, S., Deckert, J., del Ser, T., Denning, N., Destefano, A., Dichgans, M., Diehl-Schmid, J., Diez-Fairen, M., Rossi, P. D., Djurovic, S., Duron, E., Düzel, E., Dufouil, C., Eiriksdottir, G., Engelborghs, S., Escott-Price, V., Espinosa, A., Ewers, M., Faber, K. M., Fabrizio, T., Nielsen, S. F., Fardo, D. W., Farotti, L., Fenoglio, C., Fernández-Fuertes, M., Ferrari, R., Ferreira, C. B., Ferri, E., Fin, B., Fischer, P., Fladby, T., Fließbach, K., Fongang, B., Fornage, M., Fortea, J., Foroud, T. M., Fostinelli, S., Fox, N. C., Franco-Macías, E., Bullido, M. J., Frank-García, A., Froelich, L., Fulton-Howard, B., Galimberti, D., García-Alberca, J. M., García-González, P., Garcia-Madrona, S., Garcia-Ribas, G., Ghidoni, R., Giegling, I., Giorgio, G., Goate, A. M., Goldhardt, O., Gomez-Fonseca, D., González-Pérez, A., Graff, C., Grande, G., Green, E., Grimmer, T., Grünblatt, E., Grunin, M., Gudnason, V., Guetta-Baranes, T., Haapasalo, A., Hadjigeorgiou, G., Haines, J. L., Hamilton-Nelson, K. L., Hampel, H., Hanon, O., Hardy, J., Hartmann, A. M., Hausner, L., Harwood, J., Heilmann-Heimbach, S., Helisalmi, S., Heneka, M. T., Hernández, I., Herrmann, M. J., Hoffmann, P., Holmes, C., Holstege, H., Vilas, R. H., Hulsman, M., Humphrey, J., Biessels, G. J., Jian, X., Johansson, C., Jun, G. R., Kastumata, Y., Kauwe, J., Kehoe, P. G., Kilander, L., Ståhlbom, A. K., Kivipelto, M., Koivisto, A., Kornhuber, J., Kosmidis, M. H., Kukull, W. A., Kuksa, P. P., Kunkle, B. W., Kuzma, A. B., Lage, C., Laukka, E. J., Launer, L., Lauria, A., Lee, C. -Y., Lehtisalo, J., Lerch, O., Lleó, A., Longstreth, W., Lopez, O., de Munain, A. L., Love, S., Löwemark, M., Luckcuck, L., Lunetta, K. L., Ma, Y., Macías, J., Macleod, C. A., Maier, W., Mangialasche, F., Spallazzi, M., Marquié, M., Marshall, R., Martin, E. R., Montes, A. M., Rodríguez, C. M., Masullo, C., Mayeux, R., Mead, S., Mecocci, P., Medina, M., Meggy, A., Mehrabian, S., Mendoza, S., Menéndez-González, M., Mir, P., Moebus, S., Mol, M., Molina-Porcel, L., Montrreal, L., Morelli, L., Moreno, F., Morgan, K., Mosley, T., Nöthen, M. M., Muchnik, C., Mukherjee, S., Nacmias, B., Ngandu, T., Nicolas, G., Nordestgaard, B. G., Olaso, R., Orellana, A., Orsini, M., Ortega, G., Padovani, A., Paolo, C., Papenberg, G., Parnetti, L., Pasquier, F., Pastor, P., Peloso, G., Pérez-Cordón, A., Pérez-Tur, J., Pericard, P., Peters, O., Pijnenburg, Y. A. L., Pineda, J. A., Piñol-Ripoll, G., Pisanu, C., Polak, T., Popp, J., Posthuma, D., Priller, J., Puerta, R., Quenez, O., Quintela, I., Thomassen, J. Q., Rábano, A., Rainero, I., Rajabli, F., Ramakers, I., Real, L. M., Reinders, M. J. T., Reitz, C., Reyes-Dumeyer, D., Ridge, P., Riedel-Heller, S., Riederer, P., Roberto, N., Rodriguez-Rodriguez, E., Rongve, A., Allende, I. R., Rosende-Roca, M., Royo, J. L., Rubino, E., Rujescu, D., Sáez, M. E., Sakka, P., Saltvedt, I., Sanabria, Á., Sánchez-Arjona, M. B., Sanchez-Garcia, F., Juan, P. S., Sánchez-Valle, R., Sando, S. B., Sarnowski, C., Satizabal, C. L., Scamosci, M., Scarmeas, N., Scarpini, E., Scheltens, P., Scherbaum, N., Scherer, M., Schmid, M., Schneider, A., Schott, J. M., Selbæk, G., Seripa, D., Serrano, M., Sha, J., Shadrin, A. A., Skrobot, O., Slifer, S., Snijders, G. J. L., Soininen, H., Solfrizzi, V., Solomon, A., Song, Y. E., Sorbi, S., Sotolongo-Grau, O., Spalletta, G., Spottke, A., Squassina, A., Stordal, E., Tartan, J. P., Tárraga, L., Tesí, N., Thalamuthu, A., Thomas, T., Tosto, G., Traykov, L., Tremolizzo, L., Tybjærg-Hansen, A., Uitterlinden, A., Ullgren, A., Ulstein, I., Valero, S., Valladares, O., Broeckhoven, C. V., Vance, J., Vardarajan, B. N., van der Lugt, A., Dongen, J. V., van Rooij, J., van Swieten, J., Vandenberghe, R., Verhey, F., Vidal, J. -S., Vogelgsang, J., Vyhnalek, M., Wagner, M., Wallon, D., Wang, L. -S., Wang, R., Weinhold, L., Wiltfang, J., Windle, G., Woods, B., Yannakoulia, M., Zare, H., Zhao, Y., Zhang, X., Zhu, C., Zulaica, M., Laczo, J., Matoska, V., Serpente, M., Assogna, F., Piras, F., Ciullo, V., Shofany, J., Ferrarese, C., Andreoni, S., Sala, G., Zoia, C. P., Zompo, M. D., Benussi, A., Bastiani, P., Takalo, M., Natunen, T., Laatikainen, T., Tuomilehto, J., Antikainen, R., Strandberg, T., Lindström, J., Peltonen, M., Abraham, R., Al-Chalabi, A., Bass, N. J., Brayne, C., Brown, K. S., Collinge, J., Craig, D., Deloukas, P., Fox, N., Gerrish, A., Gill, M., Gwilliam, R., Harold, D., Hollingworth, P., Johnston, J. A., Jones, L., Lawlor, B., Livingston, G., Lovestone, S., Lupton, M., Lynch, A., Mann, D., Mcguinness, B., Mcquillin, A., O’Donovan, M. C., Owen, M. J., Passmore, P., Powell, J. F., Proitsi, P., Rossor, M., Shaw, C. E., Smith, A. D., Gurling, H., Todd, S., Mummery, C., Ryan, N., Lacidogna, G., Adarmes-Gómez, A., Mauleón, A., Pancho, A., Gailhajenet, A., Lafuente, A., Macias-García, D., Martín, E., Pelejà, E., Carrillo, F., Merlín, I. S., Garrote-Espina, L., Vargas, L., Carrion-Claro, M., Marín, M., Labrador, M., Buendia, M., Alonso, M. D., Guitart, M., Moreno, M., Ibarria, M., Periñán, M., Aguilera, N., Gómez-Garre, P., Cañabate, P., Escuela, R., Pineda-Sánchez, R., Vigo-Ortega, R., Jesús, S., Preckler, S., Rodrigo-Herrero, S., Diego, S., Vacca, A., Roveta, F., Salvadori, N., Chipi, E., Boecker, H., Laske, C., Perneczky, R., Anastasiou, C., Janowitz, D., Malik, R., Anastasiou, A., Parveen, K., López-García, S., Antonell, A., Mihova, K. Y., Belezhanska, D., Weber, H., Kochen, S., Solis, P., Medel, N., Lisso, J., Sevillano, Z., Politis, D. G., Cores, V., Cuesta, C., Ortiz, C., Bacha, J. I., Rios, M., Saenz, A., Abalos, M. S., Kohler, E., Palacio, D. L., Etchepareborda, I., Kohler, M., Novack, G., Prestia, F. A., Galeano, P., Castaño, E. M., Germani, S., Toso, C. R., Rojo, M., Ingino, C., Mangone, C., Rubinsztein, D. C., Teipel, S., Fievet, N., Deramerourt, V., Forsell, C., Thonberg, H., Bjerke, M., Roeck, E. D., Martínez-Larrad, M. T., Olivar, N., Cano, A., Macias, J., Maroñas, O., Nuñez-Llaves, R., Olivé, C., Adarmes-Gómez, A. D., Amer-Ferrer, G., Antequera, M., Burguera, J. A., Casajeros, M. J., Martinez de Pancorbo, M., Hevilla, S., Espinosa, M. A. L., Legaz, A., Manzanares, S., Marín-Muñoz, J., Marín, T., Martínez, B., Martínez, V., Martínez-Lage Álvarez, P., Iriarte, M. M., Periñán-Tocino, M. T., Real de Asúa, D., Rodrigo, S., Sastre, I., Vicente, M. P., Vivancos, L., Epelbaum, J., Hannequin, D., Campion, D., Deramecourt, V., Tzourio, C., Brice, A., Dubois, B., Williams, A., Thomas, C., Davies, C., Nash, W., Dowzell, K., Morales, A. C., Bernardo-Harrington, M., Turton, J., Lord, J., Brown, K., Vardy, E., Fisher, E., Warren, J. D., Ryan, N. S., Guerreiro, R., Uphill, J., Bass, N., Heun, R., Kölsch, H., Schürmann, B., Lacour, A., Herold, C., Powell, J., Patel, Y., Hodges, A., Becker, T., Warden, D., Wilcock, G., Clarke, R., Ben-Shlomo, Y., Hooper, N. 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Peters, O, Pijnenburg, Y, Pineda, J, Piñol-Ripoll, G, Pisanu, C, Polak, T, Popp, J, Posthuma, D, Priller, J, Puerta, R, Quenez, O, Quintela, I, Thomassen, J, Rábano, A, Rainero, I, Rajabli, F, Ramakers, I, Real, L, Reinders, M, Reitz, C, Reyes-Dumeyer, D, Ridge, P, Riedel-Heller, S, Riederer, P, Roberto, N, Rodriguez-Rodriguez, E, Rongve, A, Allende, I, Rosende-Roca, M, Royo, J, Rubino, E, Rujescu, D, Sáez, M, Sakka, P, Saltvedt, I, Sanabria, Á, Sánchez-Arjona, M, Sanchez-Garcia, F, Juan, P, Sánchez-Valle, R, Sando, S, Sarnowski, C, Satizabal, C, Scamosci, M, Scarmeas, N, Scarpini, E, Scheltens, P, Scherbaum, N, Scherer, M, Schmid, M, Schneider, A, Schott, J, Selbæk, G, Seripa, D, Serrano, M, Sha, J, Shadrin, A, Skrobot, O, Slifer, S, Snijders, G, Soininen, H, Solfrizzi, V, Solomon, A, Song, Y, Sorbi, S, Sotolongo-Grau, O, Spalletta, G, Spottke, A, Squassina, A, Stordal, E, Tartan, J, Tárraga, L, Tesí, N, Thalamuthu, A, Thomas, T, Tosto, G, Traykov, L, Tremolizzo, L, Tybjærg-Hansen, A, 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[0000-0002-7467-250X], Soininen, Hilkka [0000-0002-2785-9937], Solfrizzi, Vincenzo [0000-0002-8524-0315], Song, Yeunjoo [0000-0002-7452-3731], Sotolongo-Grau, Oscar [0000-0002-9679-0670], Spalletta, Gianfranco [0000-0002-7432-4249], Squassina, Alessio [0000-0001-7415-7607], Stordal, Eystein [0000-0002-2443-7923], Tosto, Giuseppe [0000-0001-7075-8245], Uitterlinden, Andre [0000-0002-7276-3387], Valladares, Otto [0000-0001-8055-2187], Broeckhoven, Christine Van [0000-0003-0183-7665], Vidal, Jean-Sébastien [0000-0001-6770-0720], Vogelgsang, Jonathan [0000-0001-9326-8193], Wagner, Michael [0000-0003-2589-6440], Wallon, David [0000-0002-2634-7198], Wiltfang, Jens [0000-0003-1492-5330], Woods, Bob [0000-0002-6781-651X], Yannakoulia, Mary [0000-0003-2171-7337], Zare, Habil [0000-0001-5902-6238], Zhang, Xiaoling [0000-0001-8237-1857], Farrer, Lindsay A [0000-0001-5533-4225], Psaty, Bruce M [0000-0002-7278-2190], Ghanbari, Mohsen [0000-0002-9476-7143], Raj, Towfique [0000-0002-9355-5704], Sachdev, Perminder [0000-0002-9595-3220], Mather, Karen [0000-0003-4143-8941], Ikram, M Arfan [0000-0003-0372-8585], Tsolaki, Magda [0000-0002-2072-8010], Pericak-Vance, Margaret A [0000-0001-7283-8804], Amouyel, Philippe [0000-0001-9088-234X], Williams, Julie [0000-0002-4069-0259], Frikke-Schmidt, Ruth [0000-0003-4084-5027], Seshadri, Sudha [0000-0001-6135-2622], Andreassen, Ole A [0000-0002-4461-3568], Sleegers, Kristel [0000-0002-0283-2332], van Duijn, Cornelia M [0000-0002-2374-9204], Sims, Rebecca [0000-0002-3885-1199], van der Flier, Wiesje M [0000-0001-8766-6224], Ramirez, Alfredo [0000-0003-4991-763X], Lambert, Jean-Charles [0000-0003-0829-7817], Apollo - University of Cambridge Repository, Complex Trait Genetics, Clinical sciences, Neuroprotection & Neuromodulation, Pathologic Biochemistry and Physiology, Clinical Biology, Epidemiology, Internal Medicine, Psychiatrie & Neuropsychologie, RS: MHeNs - R1 - Cognitive Neuropsychiatry and Clinical Neuroscience, MUMC+: MA Med Staf Spec Psychiatrie (9), UAM. Departamento de Biología Molecular, University of Helsinki, Department of Neurosciences, HUS Internal Medicine and Rehabilitation, Timo Strandberg / Principal Investigator, Department of Medicine, Clinicum, HUS Neurocenter, Neurologian yksikkö, Centre of Excellence in Complex Disease Genetics, HUS Abdominal Center, Institut Pasteur, Institut National de la Santé et de la Recherche Médicale (France), European Commission, LabEx DISTALZ, Pérez-Tur, Jordi, University Children’s Hospital Basel (Suiza), INSERM (Francia), Lille Métropole Communauté Urbaine, Government of France (Francia), EADB, GR@ACE, DEGESCO, EADI, GERAD, Demgene, FinnGen, ADGC, CHARGE, Holmans, Peter A. [0000-0003-0870-9412], van der Lee, Sven J. [0000-0003-1606-8643], Costa, Marcos R. [0000-0002-4928-2163], Bis, Joshua C. [0000-0002-3409-1110], Brookes, Keeley J. [0000-0003-2427-2513], Bush, William S. [0000-0002-9729-6519], de Witte, Lot D. [0000-0002-7235-9958], del Ser, Teodoro [0000-0001-9806-7083], Fox, Nick C. [0000-0002-6660-657X], Bullido, María J. [0000-0002-6477-1117], Goate, Alison M. [0000-0002-0576-2472], Herrmann, Martin J. [0000-0001-9970-2122], Jun, Gyungah R. [0000-0002-3230-8697], Kehoe, Patrick G. [0000-0002-7542-1139], Kosmidis, Mary H. [0000-0001-8790-1220], Lunetta, Kathryn L. [0000-0002-9268-810X], MacLeod, Catherine A. [0000-0002-9314-7380], Nöthen, Markus M. [0000-0002-8770-2464], Nordestgaard, Børge G. [0000-0002-1954-7220], Pineda, Juan A. [0000-0002-3751-0296], Real, Luis M. [0000-0003-4932-7429], Reinders, Marcel J. T. [0000-0002-1148-1562], Satizabal, Claudia L. [0000-0002-1115-4430], Schott, Jonathan M. [0000-0003-2059-024X], Shadrin, Alexey A. [0000-0002-7467-250X], Farrer, Lindsay A. [0000-0001-5533-4225], Psaty, Bruce M. [0000-0002-7278-2190], Ikram, M. Arfan [0000-0003-0372-8585], Pericak-Vance, Margaret A. [0000-0001-7283-8804], Andreassen, Ole A. [0000-0002-4461-3568], van Duijn, Cornelia M. [0000-0002-2374-9204], van der Flier, Wiesje M. [0000-0001-8766-6224], and Molecular Neuroscience and Ageing Research (MOLAR)
- Subjects
tau Proteins/genetics ,Alzheimer`s disease Donders Center for Medical Neuroscience [Radboudumc 1] ,Neurologi ,MED/03 - GENETICA MEDICA ,45/43 ,Medizin ,Stress-related disorders Donders Center for Medical Neuroscience [Radboudumc 13] ,genetics [Alzheimer Disease] ,Genome-Wide Association Study ,Humans ,tau Proteins ,Alzheimer Disease ,Cognitive Dysfunction ,VARIANTS ,pathology [Alzheimer Disease] ,Tau Proteins ,Settore BIO/13 - Biologia Applicata ,Cognitive Dysfunction/psychology ,692/699/375/365/1283 ,IMPUTATION ,article ,1184 Genetics, developmental biology, physiology ,Biología y Biomedicina / Biología ,AMYLOID-BETA ,Settore MED/26 - NEUROLOGIA ,Neurology ,psychology [Cognitive Dysfunction] ,Medical Genetics ,Human ,Neuroscience(all) ,631/208/205/2138 ,All institutes and research themes of the Radboud University Medical Center ,SDG 3 - Good Health and Well-being ,ddc:570 ,Genetics ,Genetic Predisposition to Disease ,GENOME-WIDE ASSOCIATION ,METAANALYSIS ,Medicinsk genetik ,MED/26 - NEUROLOGIA ,Alzheimer Disease/genetics ,neurology ,tau Protein ,NECROSIS-FACTOR-ALPHA ,RISK LOCI ,genetics [tau Proteins] ,PREDICTION MODELS ,Human medicine ,GENERATION ,RESPONSES - Abstract
25 páginas, 6 figuras, 2 tablas, Characterization of the genetic landscape of Alzheimer's disease (AD) and related dementias (ADD) provides a unique opportunity for a better understanding of the associated pathophysiological processes. We performed a two-stage genome-wide association study totaling 111,326 clinically diagnosed/'proxy' AD cases and 677,663 controls. We found 75 risk loci, of which 42 were new at the time of analysis. Pathway enrichment analyses confirmed the involvement of amyloid/tau pathways and highlighted microglia implication. Gene prioritization in the new loci identified 31 genes that were suggestive of new genetically associated processes, including the tumor necrosis factor alpha pathway through the linear ubiquitin chain assembly complex. We also built a new genetic risk score associated with the risk of future AD/dementia or progression from mild cognitive impairment to AD/dementia. The improvement in prediction led to a 1.6- to 1.9-fold increase in AD risk from the lowest to the highest decile, in addition to effects of age and the APOE ε4 allele., This work was funded by a grant (EADB) from the EU Joint Programme – Neurodegenerative Disease Research. INSERM UMR1167 is also funded by the INSERM, Institut Pasteur de Lille, Lille Métropole Communauté Urbaine and French government’s LABEX DISTALZ program (development of innovative strategies for a transdisciplinary approach to AD). Full consortium acknowledgements and funding are in the Supplementary Not
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- 2022
82. Assessment of Spatial Interpolation Techniques on Groundwater Contamination
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Shyamala, G., primary, Arun Kumar, B., additional, Manvitha, S., additional, and Vinay Raj, T., additional
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- 2019
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83. Tomato leaf disease identification using machine learning.
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Ardra Rajan, V. K., Athul Raj, T. V., Sunil, Jyothis, Muhammed Waseem, J., and Shibili, T.
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CONVOLUTIONAL neural networks , *MACHINE learning , *BOTANY , *AGRICULTURE , *AGRICULTURAL productivity , *TOMATOES - Abstract
Agriculture is the first priority occupation in all over the world. Most of the occupation are concentrated on farming and we can' t imagine a world without farming. We face many problems in the agricultural sector, especially in the diagnosis. It is very difficult to find a specific disease and cure scientifically. In a plant there are many types of disease which concentrated on leaf, stem and root. And leaf disease is more reflexive and affects crop production with high intensity. While studying on the leaf disease, we found that there are plenty of disease in tomato leaf and its very hard to find the type because symptoms are very similar. So we decided to classify and identify the tomato leaf disease. In our project we are developing a mobile application to the farmers. They can upload tomato leaf images for identifying the type of disease. Its result includes the type of disease and suggestion required for the cure. For getting an accurate result we selected CNN (convolutional neural network) algorithm. CNN is a deep learning approach to training the desired model. Trained with the available tomato leaf image dataset. Through this network we find out the specific diseases and the diagnosis. The results in this model will inspire in the field of plant science to develop more such models to help farmers. [ABSTRACT FROM AUTHOR]
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- 2023
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84. Design and fabrication of robotic hand and gesture using 3D printer.
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Vemanaboina, Harinadh, Reddy, G. Vikas, Ghising, Suraj, Raj, T. Prudhvi, and Babu, M. Mohan
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ROBOT hands ,3-D printers ,INDUSTRIAL robots ,GESTURE ,ARDUINO (Microcontroller) ,SERVOMECHANISMS - Abstract
Today's robots are agile, capable of engineering marvels, and have human-like traits. Robotics has huge promise in every field and is fast changing the game. Robots are robust and complicated gadgets that humans operate with buttons and switches. Hand gesture robots are widely used in defense, industrial robotics, civil car assembly, and surgery. The robotic hand moves and executes tasks based on human hand gestures. Gesture is the human hand and facial movement. Design and build a robotic hand that human motions can control. Potentiometers, which operate as sensors, detect human gestures. The robotic hand is programmed to mimic every action of a human hand. The robotic hand receives the human gesture using Bluetooth module HC-05. This project uses an Arduino as a microcontroller and is programmed in Arduino Ide. Servo motors drive the robotic hand. The robotic hand and glove (exo-hand) were tested for grip and gesture reproduction. In addition to being 3D printable, the robotic hand can be readily altered. Thus, this suggested methodology will enable workers in dangerous regions avoid harm. [ABSTRACT FROM AUTHOR]
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- 2023
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85. Surgery for Carcinoma Endometrium
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Chitrathara, K., Simi Raj, T. J., Rajaram, Shalini, editor, K, Chitrathara, editor, and Maheshwari, Amita, editor
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- 2015
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86. Screening and Prevention of Carcinoma Endometrium
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Simi Raj, T. J., Chitrathara, K., Rajaram, Shalini, editor, K, Chitrathara, editor, and Maheshwari, Amita, editor
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- 2015
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87. Gas-Sensing Characteristics of SrFeO3−δ Thin Film Probed by a Homemade Apparatus
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Manikandan, M., Santhosh Kumar, B., Mukil Raj, T., Moorthy Babu, S., and Venkateswaran, C.
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- 2018
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88. Investigation of 3D Contour Map and Intermolecular Interaction of Dopamine with β-Cyclodextrin and 2-Hydroxypropyl-β-cyclodextrin
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Prabhu, A. Antony Muthu, Fatiha, Madi, Leila, Nouar, Raj, T. Anantha, Navarro-González, Inmaculada, Periago, Maria Jesús, Yáñez-Gascón, Maria Josefa, and Pérez-Sánchez, Horacio
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- 2018
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89. Planning and financing of RMNCH+A under National Health Mission: A case study of the Gurugram District of Haryana State
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Gaylong, Ruchi, primary, Tiwari, Vijay Kumar, additional, and Sherin Raj, T. P., additional
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- 2023
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90. Investigation on Fluid Flow Heat Transfer and Frictional Properties of Al2O3 Nanofluids Used in Shell and Tube Heat Exchanger
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Barik, Debabrata, primary, Chandran, Sreejesh S. R., additional, Dennison, Milon Selvam, additional, Raj, T. G. Ansalam, additional, and Roy, K. E. Reby, additional
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- 2023
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91. IOT and Deep Learning Assisted Smart Agriculture System for Plant Disease Identification
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S., Selvaraj, primary, R., Thangarajan, additional, C., Santhosh, additional, and K., Vikash Raj T, additional
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- 2023
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92. Robust Transfer Learning Based Modelling for Accelerating the Learning of Ai in the Field of NLP
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Ravimaram, S., primary, Kumar S, Jerald Nirmal, additional, Sathish, A., additional, Vatchala, S., additional, Rawat, Ruchira, additional, and F, Michael Raj T, additional
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- 2023
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93. Novel deep learning approach for DDoS attack using elephant heard optimization algorithm along with a fuzzy classifier for rules learning
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Caroline Misbha, J., primary, Ajith Bosco Raj, T., additional, and Jiji, G., additional
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- 2023
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94. Deep feature fusion and optimized feature selection based ensemble classification of liver lesions
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Anisha, A., primary, Jiji, G., additional, and Ajith Bosco Raj, T., additional
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- 2023
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95. Performance Analysis of GFDM System in 5G Cellular Networks
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Jeganlal, R., primary, Jiji, G., additional, Mariyal, C., additional, Sehina, H., additional, and Raj, T. Ajith Bosco, additional
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- 2023
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96. A kish graphitic lithium-insertion anode material obtained from non-biodegradable plastic waste
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Sri Devi Kumari, T., Jebaraj, Adriel J.J., Raj, T. Antony, Jeyakumar, D., and Kumar, T. Prem
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- 2016
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97. Robust Transfer Learning Based Modelling for Accelerating the Learning of Ai in the Field of NLP
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S. Ravimaram, Jerald Nirmal Kumar S, A. Sathish, S. Vatchala, Ruchira Rawat, and Michael Raj T F
- Published
- 2023
98. Experimental analysis of rice husk gasification in a newly developed air blown bed gasifier.
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Murugan, P. C., Kumar, K. V. Satheesh, Dharmaraj, M., Prakash Raj, T., Pragadeeshwar, K. S., Muzammil, A. K. M. Mohammed, Joshua, P. S., and Nedunchezhiyan, A.
- Subjects
AIR mattresses ,BAGASSE ,INCINERATION ,SOLID waste ,AGRICULTURAL wastes ,HEAT resistant materials ,SUGARCANE - Abstract
Currently, fuels costs and usage are increasing day by day, the current share of biofuel and bio solid wastes used for usage in almost all area is low. Air and environment are also polluted by the part of burning of agricultural solid wastes, for changing this scenario, converting the bio solid wastes into syngas by the process called Gasification. It is the process of allowing the bio solids and heating it by high temperature in the bed material and producing syn gas. It is ancient one and this process is used in World War II periods for consuming the fuels in the demand of petroleum and fuels. Air Blown Bed Gasifier (ABBG) is using this same principle, here we deployed high flow rate air blower to make the process efficient. This have interrelated steps and reactions. By the process, first the coal or solid wastes like rice husk, sugarcane bagasse, are feed stock materials. This project work was carried out in four processes they are drying, pyrolysis combustion and reduction, base feed stock is rice husk in this gasifier. These four processes involve various temperatures in their respecting zones. And it is based on simple concept of incomplete combustion. Drawbacks of air blown bed gasifier process is having the high tar content in produced syngas. A new air blown bed gasifier were modelled using Fusion 360 software. Then it has been fabricated successfully. This product reduces air pollution when compared with unwanted burning of agricultural wastes. [ABSTRACT FROM AUTHOR]
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- 2023
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99. Designing a Next-Generation Multiepitope-Based Vaccine against Staphylococcus aureus Using Reverse Vaccinology Approaches
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Mahapatra, Soumya Ranjan, primary, Dey, Jyotirmayee, additional, Raj, T. Kiran, additional, Misra, Namrata, additional, and Suar, Mrutyunjay, additional
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- 2023
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100. Parturition Hindi Speech Dataset for Automatic Speech Recognition
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Bansal, Vansh, primary, Thishyan Raj, T, additional, Ravi, Nagarathna, additional, Korde, Shubham, additional, Kalra, Jaskaran, additional, Murugesan, Sudha, additional, Ramkrishnan, B, additional, Gore, Aboli, additional, and Arora, Vipul, additional
- Published
- 2023
- Full Text
- View/download PDF
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