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134 results on '"Chawla, Meenu"'

6. Detecting Phishing URLs Using Machine Learning: A Review

Author

Kapse, Kritika, Chawla, Meenu, Tiwari, Namita, Goenka, Richa, 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, Pastor-Escuredo, David, editor, Brigui, Imene, editor, Kesswani, Nishtha, editor, Bordoloi, Sushanta, editor, and Ray, Ashok Kumar, editor

Published
2024
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7. A Review of Traditional and Neural Network Methods for Protecting Privacy in Big Data Analytics

Author

Thasna, C. A., Chawla, Meenu, Tiwari, Namita, 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, Pastor-Escuredo, David, editor, Brigui, Imene, editor, Kesswani, Nishtha, editor, Bordoloi, Sushanta, editor, and Ray, Ashok Kumar, editor

Published
2024
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8. Zero-Knowledge Proofs in Blockchain-Enabled Supply Chain Management

Author

Prasad, Sameeksha, Tiwari, Namita, Chawla, Meenu, Tomar, Deepak Singh, Hamdan, Allam, Editorial Board Member, Al Madhoun, Wesam, Editorial Board Member, Alareeni, Bahaaeddin, Editor-in-Chief, Baalousha, Mohammed, Editorial Board Member, Elgedawy, Islam, Editorial Board Member, Hussainey, Khaled, Editorial Board Member, Eleyan, Derar, Editorial Board Member, Hamdan, Reem, Editorial Board Member, Salem, Mohammed, Editorial Board Member, Jallouli, Rim, Editorial Board Member, Assaidi, Abdelouahid, Editorial Board Member, Nawi, Noorshella Binti Che, Editorial Board Member, AL-Kayid, Kholoud, Editorial Board Member, Wolf, Martin, Editorial Board Member, El Khoury, Rim, Editorial Board Member, Kumar, Adarsh, editor, Ahuja, Neelu Jyothi, editor, Kaushik, Keshav, editor, Tomar, Deepak Singh, editor, and Khan, Surbhi Bhatia, editor

Published
2024
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9. Intrusion Detection System Using Machine Learning Approach: A Review

Author

Sharma, Kapil, Chawla, Meenu, Tiwari, Namita, 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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10. A Review on EEG Data Classification Methods for Brain–Computer Interface

Author

Jadhav, Vaibhav, Tiwari, Namita, Chawla, Meenu, 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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11. Developments in Capsule Network Architecture: A Review

Author

Kapadnis, Sudarshan, Tiwari, Namita, Chawla, Meenu, Howlett, Robert J., Series Editor, Jain, Lakhmi C., Series Editor, Satapathy, Suresh Chandra, editor, Peer, Peter, editor, Tang, Jinshan, editor, Bhateja, Vikrant, editor, and Ghosh, Anumoy, editor

Published
2022
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14. Convection Dynamics of Nanofluids for Temperature and Magnetic Field Variations

Author

Bhardwaj, Rashmi, Chawla, Meenu, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, 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
2021
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18. On Maximizing Blind Rendezvous Probability in Cognitive Radio Ad Hoc Networks

Author

Ukey, Aishwarya Sagar Anand, Chawla, Meenu, 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, Liang, Qilian, Series Editor, Martin, 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, Zhang, Junjie James, Series Editor, Janyani, Vijay, editor, Singh, Ghanshyam, editor, Tiwari, Manish, editor, and d’Alessandro, Antonio, editor

Published
2020
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19. Convection Dynamics of SiO2 Nanofluid

Author

Bhardwaj, Rashmi, Chawla, Meenu, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Dutta, Debashis, editor, and Mahanty, Biswajit, editor

Published
2020
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21. Transport Information System using Query Centric Cyber Physical Systems (QCPS)

Author

Mundra, Ankit, Rathee, Geetanjali, Chawla, Meenu, Rakesh, Nitin, and Soni, Ashsutosh

Subjects
Computer Science - Other Computer Science
Abstract

To incorporate the computation and communication with the physical world, next generation architecture i.e. CPS is viewed as a new technology. To improve the better interaction with the physical world or to perk up the electricity delivery usage, various CPS based approaches have been introduced. Recently several GPS equipped smart phones and sensor based frameworks have been proposed which provide various services i.e. environment estimation, road safety improvement but encounter certain limitations like elevated energy consumption and high computation cost. To meet the high reliability and safety requirements, this paper introduces a novel approach based on QCPS model which provides several users services (discussed in this paper). Further, this paper proposed a Transport Information System (TIS), which provide the communication with lower cost overhead by arranging the similar sensors in the form of grids. Each grid has a coordinator which interacts with cloud to process the user query. In order to evaluate the performance of proposed approach we have implemented a test bed of 16 wireless sensor nodes and have shown the performance in terms of computation and communication cost., Comment: 5 pages, 4 Figures

Published
2014
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22. A Comparative Study of Local Outlier Factor Algorithms for Outliers Detection in Data Streams

Author

Mishra, Supriya, Chawla, Meenu, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Abraham, Ajith, editor, Dutta, Paramartha, editor, Mandal, Jyotsna Kumar, editor, Bhattacharya, Abhishek, editor, and Dutta, Soumi, editor

Published
2019
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23. Viable Crop Prediction Scenario in BigData Using a Novel Approach

Author

Sahu, Shriya, Chawla, Meenu, Khare, Nilay, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Abraham, Ajith, editor, Dutta, Paramartha, editor, Mandal, Jyotsna Kumar, editor, Bhattacharya, Abhishek, editor, and Dutta, Soumi, editor

Published
2019
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24. Validated Real Time Middle Ware For Distributed Cyber Physical Systems Using HMM

Author

Mundra, Ankit, Gupta, Bhagvan K., Rathee, Geetanjali, Chawla, Meenu, Rakesh, Nitin, and Tyagi, Vipin

Subjects
Computer Science - Distributed, Parallel, and Cluster Computing
Abstract

Distributed Cyber Physical Systems designed for different scenario must be capable enough to perform in an efficient manner in every situation. Earlier approaches, such as CORBA, has performed but with different time constraints. Therefore, there was the need to design reconfigurable, robust, validated and consistent real time middle ware systems with end-to-end timing. In the DCPS-HMM we have proposed the processor efficiency and data validation which may proof crucial in implementing various distributed systems such as credit card systems or file transfer through network., Comment: 11 Pages, 4 figures

Published
2013
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25. EEG-based Emotion Recognition using Transfer Learning Based Feature Extraction and Convolutional Neural Network

Author

Jadhav Vaibhav, Tiwari Namita, and Chawla Meenu

Subjects
Information technology, T58.5-58.64
Abstract

In this paper, a novel method for EEG(Electroencephalography) based emotion recognition is introduced. This method uses transfer learning to extract features from multichannel EEG signals, these features are then arranged in an 8×9 map to represent their spatial location on scalp and then we introduce a CNN model which takes in the spatial feature map and extracts spatial relations between EEG channel and finally classify the emotions. First, EEG signals are converted to spectrogram and passed through a pre-trained image classification model to get a feature vector from spectrogram of EEG. Then, feature vectors of different channels are rearranged and are presented as input to a CNN model which extracts spatial features or dependencies of channels as part of training. Finally, CNN outputs are flattened and passed through dense layer to classify between emotion classes. In this study, SEED, SEED-IV and SEED-V EEG emotion data-sets are used for classification and our method achieves best classification accuracy of 97.09% on SEED, 89.81% on SEED-IV and 88.23% on SEED-V data-set with fivefold cross validation.

Published
2023
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35. Enhanced Ad Hoc on Demand Distance Vector Local Repair Trial for MANET

Author

Naidu, P. Priya, Chawla, Meenu, Akan, Ozgur, Series editor, Bellavista, Paolo, Series editor, Cao, Jiannong, Series editor, Dressler, Falko, Series editor, Ferrari, Domenico, Series editor, Gerla, Mario, Series editor, Kobayashi, Hisashi, Series editor, Palazzo, Sergio, Series editor, Sahni, Sartaj, Series editor, Shen, Xuemin (Sherman), Series editor, Stan, Mircea, Series editor, Xiaohua, Jia, Series editor, Zomaya, Albert, Series editor, Coulson, Geoffrey, Series editor, Meghanathan, Natarajan, editor, Chaki, Nabendu, editor, and Nagamalai, Dhinaharan, editor

Published
2012
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37. Review : Deep learning techniques for automatic target recognition in infrared images.

Author

Sushanth, M. Phani, Chawla, Meenu, and Tiwari, Namita

Subjects
*AUTOMATIC target recognition, *DEEP learning, *INFRARED imaging, *OBJECT recognition (Computer vision), *IMAGE recognition (Computer vision), *FEATURE extraction
Abstract

Implementation of Machine Learning/Deep Learning techniques in Image Processing have paved way to advanced object detection, classification and tracking in a real time environment. Recent advancements are enabling these techniques to be used in the field of real time Infra Red (IR) object detection. IR image processing is being used extensively in the field of military, industrial and medical applications. This paper emphasizes upon the various Deep learning techniques which can be used for automatic target detection/recognition in infra red maritime imagery of sea borne military assets. Our review begins with the introduction to Object Detection, IR imaging, techniques available and various architectures for feature extraction and object detection. Then, we also provide a comparison of performance/detection capabilities on widely used PASCAL VOC 2007 and 2012 datasets. [ABSTRACT FROM AUTHOR]

Published
2023
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39. A Heuristic Approach to Crime Prediction based on Generalization of Crime Categories

Author

Rasool Akhtar, Hajela Gaurav, and Chawla Meenu

Subjects
Heuristic, Computer science, business.industry, Generalization, General Engineering, ComputingMilieux_LEGALASPECTSOFCOMPUTING, Artificial intelligence, business
Abstract

Background: As crime rates are increasing all over the world, many methods for crime prediction based on data mining have been proposed in the past. Crime prediction finds application in areas like predictive policing, Hotspot evaluation and geographic profiling. It has been observed in the past that crime is closely related to geographical location, time, weather conditions and day of the week. Objective: Thus, to tackle crime events, a proactive policing approach can be developed using crime prediction. The main objective of this study is to provide a heuristic approach to crime prediction. Method: In this work, a crime prediction approach is proposed which utilizes a crime history dataset which contains multiple categories of crime. And a heuristic approach based on the generalization of crime categories is proposed. A spatiotemporal crime prediction technique based on machine learning techniques is proposed. State-of-the-art classification approaches along with ensemble learning approach are used for prediction. Results: The performance of the proposed model is compared using state-of-the-art classification techniques without a heuristic approach and with a heuristic approach, and it is found that the model with heuristics achieves better accuracy. Conclusion: Crime events dataset can be utilized to predict future crime events in an area because crime shows geographical patterns. These spatial patterns might vary with the category of crime and it is challenging to deal with lots of crime categories. Thus, a generalization based approach can be a vital asset in crime prediction.

Published
2021
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47. A multi‐dimensional crime spatial pattern analysis and prediction model based on classification.

Author

Hajela, Gaurav, Chawla, Meenu, and Rasool, Akhtar

Subjects
CRIMINAL methods, PREDICTION models, CRIME analysis, CLASSIFICATION
Abstract

This article presents a multi‐dimensional spatial pattern analysis of crime events in San Francisco. Our analysis includes the impact of spatial resolution on hotspot identification, temporal effects in crime spatial patterns, and relationships between various crime categories. In this work, crime prediction is viewed as a classification problem. When predictions for a particular category are made, a binary classification‐based model is framed, and when all categories are considered for analysis, a multiclass model is formulated. The proposed crime‐prediction model (HotBlock) utilizes spatiotemporal analysis for predicting crime in a fixed spatial region over a period of time. It is robust under variation of model parameters. HotBlock's results are compared with baseline real‐world crime datasets. It is found that the proposed model outperforms the standard DeepCrime model in most cases. [ABSTRACT FROM AUTHOR]

Published
2021
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