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42 results on '"Gulati, Tarun"'

2. Comparative Analysis of Machine Learning Classifiers for Plant Leaf Disease Detection

Author

Dahiya, Sachin, Gulati, Tarun, Gupta, Dushyant, Kumar, Karan, Parameshachari, B. D., Kulhánek, Rastislav, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Iwendi, Celestine, editor, Boulouard, Zakaria, editor, and Kryvinska, Natalia, editor

Published
2023
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3. Compressed Data Aggregation Using Regulated Duty Cycle for WSN-IOT Networks

Author

Gupta, Anuradha, Gulati, Tarun, Bindal, Amit Kumar, Kumar, Karan, Ramachandra, A. C., Seleck, Július, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Iwendi, Celestine, editor, Boulouard, Zakaria, editor, and Kryvinska, Natalia, editor

Published
2023
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4. Analysis of Different Interference Mitigation Techniques Based on Bit Error Rate (BER) in 5G

Author

Sah, Mithila Bihari, Bindle, Abhay, Gulati, Tarun, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Gupta, Deepak, editor, Khanna, Ashish, editor, Bhattacharyya, Siddhartha, editor, Hassanien, Aboul Ella, editor, Anand, Sameer, editor, and Jaiswal, Ajay, editor

Published
2023
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9. Automated Parkinson’s Disease Diagnosis System Using Transfer Learning Techniques

Author

Lamba, Rohit, Gulati, Tarun, Jain, Anurag, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Marriwala, N., editor, Tripathi, C. C., editor, Jain, Shruti, editor, and Mathapathi, Shivakumar, editor

Published
2022
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22. Enhance GPS Accuracy via Integration of Artificial Intelligence.

Author

Kathpalia, Niharika and Gulati, Tarun

Subjects
GLOBAL Positioning System, ARTIFICIAL intelligence in geophysics, ACCURACY, LOCATION-based services, INTERNETWORKING
Abstract

GPS has improved navigation and location-based services, its precision is still affected by things like weather and building materials. The purpose of this research was to investigate the feasibility of using AI methods to enhance GPS precision. This research proves that GPS accuracy has increased significantly, making it suitable for use in increasingly important fields including driverless vehicles, precision agriculture, geospatial mapping, and more. These results highlight the revolutionary potential of incorporating AI to improve the accuracy and reliability of GPS technology, ushering in a new era of navigation and location-based applications. In this study, authors introduce an Artificial Intelligence technique, to increase the precision of GPS receivers. Interoperability of Sensors Mostly made out of a Three-Axis Accelerometer Once GPS signal is lost with any cause, this change in delta latitude and delta longitude will be computed by our trained artificial neural network, and then, based on this interpolation, artificial neural network calculates latitude and longitude. The 3-axis gyroscope is part of an inertial measurement unit (IMU) that is used in conjunction with AI to predict navigation parameters when GPS loses communication with a satellite. [ABSTRACT FROM AUTHOR]

Published
2023

33. Exploring the alternatives to the conventional interference mitigation schemes for 5G wireless cellular communication network.

Author

Bindle, Abhay, Gulati, Tarun, and Kumar, Neeraj

Subjects
*WIRELESS communications, *5G networks, *QUALITY of service, *DATA packeting, *HIGH technology, *AD hoc computer networks, *FEMTOCELLS
Abstract

Summary: The manifold increase in the number of cellular wireless network consumers has presented a monumental challenge to upgrade the current infrastructure for imparting superior throughput and good quality of service. End‐users of the network will want super high‐speed data with very low latency, as well as secure and with a lower packet data drop rate. Joint coordination between various network resources such as that of a dense heterogeneous network is crucial for achieving the above demands. It is also inevitable that such a dense arrangement of small cells or macro cells or other network equipment will be challenged by different forms of interference apart from being costly and less mobile. Beamforming is among the most advanced technology that is available up to date which has shown good results at handling interference and at guiding transmitted data to the desired end‐user. It is quite useful but also struggles from certain factors when deployed in a dense network. A thorough review of recent works of literature is detailed in the current paper with a focus placed on two major fields, which are interference mitigation techniques and gainful interference exploitation techniques. Some highly advanced interference mitigation techniques which are either developed or under development with their merits have been proposed. Most of these techniques use machine learning and artificial intelligence‐based methods to ensure the best quality of service (QoS) to every individual connected to the network. However some research works focused on negating away any kind of interference present in a signal, some focused on harnessing interference for optimizing the power of transmitted signals. [ABSTRACT FROM AUTHOR]

Published
2022
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35. An Intelligent System for Parkinson's Diagnosis Using Hybrid Feature Selection Approach

Author

Jain, Anurag, Lamba, Rohit, and Gulati, Tarun

Abstract

Parkinson’s is the second most common neurodegenerative disorder after Alzheimer’s disease which adversely affects the nervous system of the patients. During the nascent stage, the symptoms of Parkinson’s disease are mild and sometimes go unnoticeable but as the disease progresses the symptoms go severe, so its diagnosis at an early stage is not easy. Recent research has shown that changes in speech or distortion in voice can be taken effectively used for early Parkinson’s detection. In this work, the authors propose a system of Parkinson's disease detection using speech signals. As the feature selection plays an important role during classification, authors have proposed a hybrid MIRFE feature selection approach. The result of the proposed feature selection approach is compared with the 5 standard feature selection methods by XGBoost classifier. The proposed MIRFE approach selects 40 features out of 754 features with a feature reduction ratio of 94.69%. An accuracy of 93.88% and area under curve (AUC) of 0.978 is obtained by the proposed system.

Published
2022
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37. Better Perception of Low Resolution Images Using Wavelet Interpolation Techniques

Author

Gulati, Tarun, Gupta, Kapil, and Dushyant Gupta

Subjects
DWCWT, DWTSR, SWT, Computer Science::Computer Vision and Pattern Recognition, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, DWTSWT
Abstract

High resolution images are always desired as they contain the more information and they can better represent the original data. So, to convert the low resolution image into high resolution interpolation is done. The quality of such high resolution image depends on the interpolation function and is assessed in terms of sharpness of image. This paper focuses on Wavelet based Interpolation Techniques in which an input image is divided into subbands. Each subband is processed separately and finally combined the processed subbandsto get the super resolution image., {"references":["T. Gulati, M. Pal, \"Interpreting Low Resolution CT Scan Images Using\nInterpolation Functions,\" International Journal of Computer\nApplications, Vol 74– No.3, July 2013, pp. 50-57.","T.Gulati, H.P. Sinha, \"Interpreting Low Resolution MRI Images Using\nPolynomial Based Interpolation,\" International Journal of Engineering\nTrends and Technology(IJETT) – Volume 10 Number 13 - Apr2014, pp.\n626-631.","A.Temizel, T.Vlachos,\"Wavelet domain image resolution enhancement\nusing cycle-spinning,\" IET Journals &Magazines, Vol. 41, Issue 3,2005,\npp. 119-121.","Emil DUMIC, Sonja GRGIC, Mislav GRGIC, \"The Use of Wavelets in\nImage Interpolation: Possibilities and Limitations,\" Radio engineering,\nVol. 16, No. 4, DECEMBER 2007, pp. 101-109.","Numan Unaldi, Vijayan K. Asari, \"Wavelet Transform based image\ninterpolation,\" Sixth international Symposium, ISVC 2010, Las Vegas,\nUSA, November 29- December 1, 2010.","Turgay Celik and Tardi Tjahjadi, \"Image Resolution Enhancement\nUsing Dual-tree Complex Wavelet Transform,\" Geoscience and Remote\nSensing Letters, Vol. 7(3), 2010,pp. 554 – 557.","Gholamreza Anbarjafari and Hasan Demirel, \"Image super resolution\nbased on interpolation of wavelet domain high frequency subbands and\nthe spatial domain input image,\" ETRI J., Vol. 32, no. 3, Jun. 2010,\npp. 390–394.","Hasan Demirel and Gholamreza Anbarjafari,\"Satellite image resolution\nenhancement using complex wavelet transform,\" IEEE Geoscience\nRemote Sens. Lett., vol. 7, no. 1, Jan. 2010, pp. 123–126.","Hasan Demirel and Gholamreza Anbarjafari, \"Image resolution\nenhancement by using discrete and stationary wavelet decomposition,\"\nIEEE T. Image Proc., 20(5), 2010b, pp. 1458-1460.\n[10] Praksh P. Gajjar and Manjunath V. Joshi, \"New Learning Based Super\nResolution: Use of DWT and IGMRF Prior,\" IEEE Transactions on\nImage Processing Vol. 19, No. 5, 2010.\n[11] Hasan Demirel and Gholamreza Anbarjafari, \"IMAGE Resolution\nEnhancement by Using Discrete and Stationary Wavelet\nDecomposition,\" IEEE Transactions on Image Processing, Vol. 20, No.\n5, May 2011, pp. 1458-1460.\n[12] K. Karthikeyan, C. Chandrasekar, \"Wavelet-based Image Enhancement\nTechniques for Improving Visual Quality of Ultrasonic Images,\"\nInternational Journal of Computer Applications (0975 – 8887) Volume\n39– No.17, February 2012, pp. 49-53.\n[13] Bagawade Ramdas P., Bhagawat Keshav S., Patil Pradeep M., \"Wavelet\nTransform Techniques for Image Resolution Enhancement: A Study,\"\nInternational Journal of Emerging Technology and Advanced\nEngineering Website: www.ijetae.com (ISSN 2250-2459, Volume 2,\nIssue 4, April 2012), pp. 167-172.\n[14] Mayuri D Patil, Surbhi Khare, \"Overview of techniques used for image\nresolution enhancement,\" International Journal on Computer Science\nand Engineering (IJCSE), Vol. 4 No. 07 July 2012, pp. 1345-1347.\n[15] S. Sangeetha, Y. Hari Krishna, \"Image Resolution Enhancement\nTechnique Based on the Interpolation of the High Frequency Subbands\nObtained by DWT,\" International Journal of Engineering Trends and\nTechnology (IJETT) – Vol.4, Issue7, July 2013, pp. 3061-3067.\n[16] P. Karunakar, V. Praveen and O. Ravi Kumar, \"Discrete Wavelet\nTransform-Based Satellite Image Resolution Enhancement,\" Advance in\nElectronic and Electric Engineering, Volume 3, Number 4 (2013),\npp. 405-412."]}

Published
2015
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42. Saving on raw material and resources.

Author

Gulati, Tarun

Abstract

The article discusses the importance of saving raw materials and energy in the spinning industry which can lead to profits in operation. It mentions that cotton prices experience inflation rates since the start of 2011 due to insufficient harvest in China and India because of rain and frost. It states that the increase in the prices of cotton in the market will affect the profit margins of textile industries. It adds that textile company Rieter Holding Ltd. has formulated a solution to cope with the short supply of raw materials through its system of VARIOline blowroom line. Furthermore, the VARIOline blowroom line is an ideal machinery that is flexible and can create a good result of fiber combinations.

Published
2011

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