Dr P.Chandana

@iare.ac.in

Coomputer Science and Engineering
Institute of Aeronautical Engineering

Dr P.Chandana


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https://researchid.co/drchandana
Dr. P.Chandana is currently working as an Associate Professor in CSE. She received Doctorate in Computer Science and Engineering from Andhra University for the research work on “Sketch Based Image Retrieval For Efficient Identification of Art Forensics”; MCA from IGNOU; M.Tech in Computer Science and Technology from Andhra University, Visakhapatnam; B.Sc in Maths, Electronics and Computers from Andhra University; She served in academics more than 12 years in various Engineering Colleges: VITS, Miracle Engineering College(Visakhapatnam), VIIT(Visakhapatnam), Raghu Engineering College (Visakhapatnam). Her research interests are Image Processing, Computer Vision, Internet of Things, Data Mining, Information Retrieval, Machine Learning, Artificial Intelligence, Natural Language Processing, Semantic Web, Wireless Networks. She has published 12 papers in international journals a book on “A Comprehensive Survey of Geographical Routing and its Impact on Mobility Models in Multi-hop Wireless

EDUCATION

Ph.D in Computer Science and Engineering, M.Tech in Computer Science and Technology, MCA from IGNOU

RESEARCH INTERESTS

Data Mining, Machine Learning, Data Analytics, Natural Language Processing, Image Proccessing, Computer Vision, Social Media Mining

FUTURE PROJECTS

Voice to Text Recognition for smart desktop applications

This project is intended to help out the blind persons and software employees to use resources of a computer efficiently with a desktop assistant gets activated with a voice.


Applications Invited
Collaborators and Students

Need and Resource management during Natural Calamities

This project is to provide the immediate help for the people who got stucked at the time of Natural calamities like Flood, EarthQuakes, Tornados etc. The aim of this project is to use Google Maps, Social Media to have a communication and tacking of nearby resource centers or ngos for extending the help.


Applications Invited
Collaborators and Students
12

Scopus Publications

389

Scholar Citations

7

Scholar h-index

7

Scholar i10-index

Scopus Publications

  • A survey of VANET routing attacks and defense mechanisms in intelligent transportation system
    Allam Balaram, P. Chandana, Shaik Abdul Nabi, M. SilpaRaj
    Self Powered Cyber Physical Systems, 2023
  • Tool-Based Prediction of SQL Injection Vulnerabilities and Attacks on Web Applications
    B. Padmaja, G. Chandra Sekhar, Ch. V. Rama Padmaja, P. Chandana, E. Krishna Rao Patro
    Lecture Notes in Networks and Systems, 2023
  • Anomaly detection in indoor localization using Machine Learning
    P. Chandana, Ch. Aishwarya, Syeda Saniya Muskan
    Proceedings of the 3rd International Conference on Inventive Research in Computing Applications Icirca 2021, 2021
    One of the most concerning topics in smart cities is the internet of things, namely wireless sensor networks in indoor localization. Wi-Fi with received signal strengths (RSSs) is one of the most used indoor localization techniques. It generates signal intensity irregularities in Wi-Fi RSSs owing to reflection, refraction, incursion, and channel noise. RSS values cannot be defined (the location of each unknown node must be accurately stated). Here, Asymmetrical, abnormal circumstances are present in the Wi-Fi indoor localization area. Matplotlib, numpy, pandas, ploty, scipy, seaborn, scikitlearn, wordcloud, statsmodels, and streamlit were utilized in this study.
  • Analyzing the Extremist Reviewer Groups on Online Products
    P. Chandana, N.Pragnya Sree, V. Ramya, G. Bhavana
    Proceedings of the 3rd International Conference on Inventive Research in Computing Applications Icirca 2021, 2021
    In today's e-commerce, online reviews play a critical part in decision-making. Customers, who make up a large portion of the population, read evaluations of items or businesses before deciding what to buy or where to get it from. Because there is a monetary reward in publishing false/fraudulent evaluations, there has been significant growth in misleading opinion spam on online review platforms. A fake review, often known as a fraudulent review or opinion spam, is a false review. Positive ratings of a specific object may attract more consumers and improve sales, while unfavourable evaluations may result in lower demand and sales. These fake/fraudulent reviews are produced with the intent of deceiving potential consumers to promote/hype or discredit their businesses. Our research aims to determine if a review is genuine or not.
  • Analyzing the Extremist Reviewer Groups on Online Products
    P. Chandana, N. Pragnya Sree, V. Ramya, G. Bhavana
    Proceedings of the 3rd International Conference on Inventive Research in Computing Applications Icirca 2021, 2021
    In today's e-commerce, online reviews play a critical part in decision-making. Customers, who make up a large portion of the population, read evaluations of items or businesses before deciding what to buy or where to get it from. Because there is a monetary reward in publishing false/fraudulent evaluations, there has been significant growth in misleading opinion spam on online review platforms. A fake review, often known as a fraudulent review or opinion spam, is a false review. Positive ratings of a specific object may attract more consumers and improve sales, while unfavourable evaluations may result in lower demand and sales. These fake/fraudulent reviews are produced with the intent of deceiving potential consumers to promote/hype or discredit their businesses. Our research aims to determine if a review is genuine or not.
  • An effective identification of crop diseases using faster region based convolutional neural network and expert systems
    P. Chandana, G. S. Pradeep Ghantasala, J. Rethna Virgil Jeny, Kaushik Sekaran, Deepika N., et al.
    International Journal of Electrical and Computer Engineering, 2020
    The majority of research Study is moving towards cognitive computing, ubiquitous computing, internet of things (IoT) which focus on some of the real time applications like smart cities, smart agriculture, wearable smart devices. The objective of the research in this paper is to integrate the image processing strategies to the smart agriculture techniques to help the farmers to use the latest innovations of technology in order to resolve the issues of crops like infections or diseases to their crops which may be due to bugs or due to climatic conditions or may be due to soil consistency. As IoT is playing a crucial role in smart agriculture, the concept of infection recognition using object recognition the image processing strategy can help out the farmers greatly without making them to learn much about the technology and also helps them to sort out the issues with respect to crop. In this paper, an attempt of integrating kissan application with expert systems and image processing is made in order to help the farmers to have an immediate solution for the problem identified in a crop.
  • Deep learning convolutional neural network (CNN) With Gaussian mixture model for predicting pancreatic cancer
    Kaushik Sekaran, P. Chandana, N. Murali Krishna, Seifedine Kadry
    Multimedia Tools and Applications, 2020
    The tremendous research towards medical health systems are giving ample scope for the computing systems to emerge with the latest innovations. These innovations are leading to the efficient implementations of the medical systems which involve in automatic diagnosis of the health related problems. The most important health research is going on towards cancer prediction, which has different forms and can be affected on different portions of the body parts. One of the most affected cancer that predicted to be incurable are Pancreatic Cancer, which cannot be treated efficiently once identified, in most of the cases it found to be unpredictable as it lies in the abdomen region below the stomach. Therefore the advancements in the medical research is trending towards the implementations of an automated systems which identifies the stages of cancer if affected and provide the better diagnosis and treatment if identified. Deep learning is one such area which extended its research towards medical imaging, which automates the process of diagnosing the problems of the patients when appended with the set of machines like CT/PET Scan systems. In this paper, the deep learning strategy named Convolutional Neural network (CNN) model is used to predict the cancer images of the pancreas, which is embedded with the model of Gaussian Mixture model with EM algorithm to predict the essential features from the CT Scan and predicts the percentage of cancer spread in the pancreas with the threshold parameters taken as a markers. The experimentation is carried out on the CT Scan images dataset of pancreas collected from the Cancer Imaging Archive (TCIA) consists of approximately 19,000 images supported by the National Institutes of Health Clinical Center to analyze the performance of the model.
  • Implementation of face and eye detection on DM6437 board using simulink model
    B. Vijayalaxmi, Kaushik Sekaran, N. Neelima, P. Chandana, Maytham N. Meqdad, et al.
    Bulletin of Electrical Engineering and Informatics, 2020
    Driver Assistance system is significant in drriver drowsiness to avoid on road accidents. The aim of this research work is to detect the position of driver’s eye for fatigue estimation. It is not unusual to see vehicles moving around even during the nights. In such circumstances there will be very high probability that a driver gets drowsy which may lead to fatal accidents. Providing a solution to this problem has become a motivating factor for this research, which aims at detecting driver fatigue. This research concentrates on locating the eye region failing which a warning signal is generated so as to alert the driver. In this paper, an efficient algorithm is proposed for detecting the location of an eye, which forms an invaluable insight for driver fatigue detection after the face detection stage. After detecting the eyes, eye tracking for input videos has to be achieved so that the blink rate of eyes can be determined.
  • Design of optimal search engine using text summarization through artificial intelligence techniques
    Kaushik Sekaran, P. Chandana, J. Rethna Virgil Jeny, Maytham N. Meqdad, Seifedine Kadry
    Telkomnika Telecommunication Computing Electronics and Control, 2020
    Natural language processing is the trending topic in the latest research areas, which allows the developers to create the human-computer interactions to come into existence. The natural language processing is an integration of artificial intelligence, computer science and computer linguistics. The research towards natural Language Processing is focused on creating innovations towards creating the devices or machines which operates basing on the single command of a human. It allows various Bot creations to innovate the instructions from the mobile devices to control the physical devices by allowing the speech-tagging. In our paper, we design a search engine which not only displays the data according to user query but also performs the detailed display of the content or topic user is interested for using the summarization concept. We find the designed search engine is having optimal response time for the user queries by analyzing with number of transactions as inputs. Also, the result findings in the performance analysis show that the text summarization method has been an efficient way for improving the response time in the search engine optimizations.
  • An Efficient Mixture Model Approach in Brain-Machine Interface Systems for Extracting the Psychological Status of Mentally Impaired Persons Using EEG Signals
    N. Murali Krishna, Kaushik Sekaran, Annepu Venkata Naga Vamsi, G. S. Pradeep Ghantasala, P. Chandana, et al.
    IEEE Access, 2019
    We propose an efficient mixture classification technique, which uses electroencephalography (EEG) signals for establishing a communication channel for the physically challenged or immobilized people, by the usage of the brain signals. In order to identify the emotion expressions by an immobilized person, we introduce a novel approach for emotion recognition based on the generalized mixture distribution model. The main benefit of utilizing this model is that it is an asymmetric distribution, which helps to extract the EEG signals, which are either in symmetric or asymmetric form. The skew Gaussian distribution helps to identify the small duration EEG signal sample and helps toward better recognition of emotions in both clean and noisy EEG signals. The proposed method is particularly well suited for the high variability of the EEG signal allowing the emotions to be identified appropriately. The features of the brain signals are extracted by using cepstral coefficients. The extracted features are classified into different emotions using mixture classification techniques. In order to validate the model, six mentally impaired subjects are considered in the age group of 60–68, and an 8-channel EEG signal is utilized to collect the EEG signals under audio-visual stimuli. The basic emotions considered in this study include happy, sad, neutral, and boredom and an average emotion recognition accuracy of 89% is achieved.
  • Comparing the Access Control Mechanism in Database, Cloud and Femtocells
    Harshita R. Jhurani, Pindi Chandana, Yarram Vijay Kumar Reddy, Mangipudi Sharada
    Proceedings of the 2nd International Conference on Electronics Communication and Aerospace Technology Iceca 2018, 2018
  • An efficient content-based image retrieval (CBIR) using GLCM for feature extraction
    P. Chandana, P. Srinivas Rao, C. H. Satyanarayana, Y. Srinivas, A. Gauthami Latha
    Advances in Intelligent Systems and Computing, 2017

RECENT SCHOLAR PUBLICATIONS

  • A survey of vanet routing attacks and defense mechanisms in intelligent transportation system
    A Balaram, P Chandana, SA Nabi, M SilpaRaj
    Self‐Powered Cyber Physical Systems, 213-226 , 2023
    2023.0
    Citations: 2
  • A comprehensive survey of geographical routing in multi-hop wireless networks
    A Balaram, M Silparaj, SA Nabi, P Chandana
    Cloud Computing Enabled Big-Data Analytics in Wireless Ad-hoc Networks, 141-172 , 2022
    2022.0
    Citations: 6
  • Anomaly detection in indoor localization using Machine Learning
    P Chandana, C Aishwarya, SS Muskan
    2021 Third International Conference on Inventive Research in Computing … , 2021
    2021.0
    Citations: 2
  • Analyzing the extremist reviewer groups on online products
    P Chandana, NP Sree, V Ramya, G Bhavana
    2021 Third International Conference on Inventive Research in Computing … , 2021
    2021.0
    Citations: 4
  • An Effective Identification of Crop diseases using Faster Region based Convolutional Neural Network and Expert Systems
    DN Seifedine Kadry P. Chandana , G. S. Pradeep Ghantasala , J. Rethna Virgil ...
    International Journal of Electrical and Computer Engineering (IJECE) - http … , 2020
    2020.0
  • Design of optimal search engine using text summarization through artificial intelligence techniques
    K Sekaran, P Chandana, JRV Jeny, MN Meqdad, S Kadry
    TELKOMNIKA (Telecommunication Computing Electronics and Control) 18 (3 … , 2020
    2020.0
    Citations: 52
  • Implementation of face and eye detection on DM6437 board using simulink model
    B Vijayalaxmi, K Sekaran, N Neelima, P Chandana, MN Meqdad, S Kadry
    Bulletin of Electrical Engineering and Informatics 9 (2), 785-791 , 2020
    2020.0
    Citations: 10
  • An effective identification of crop diseases using faster region based convolutional neural network and expert systems
    P Chandana
    International Journal of Electrical and Computer Engineering (IJECE) , 2020
    2020.0
    Citations: 34
  • An efficient mixture model approach in brain-machine interface systems for extracting the psychological status of mentally impaired persons using EEG signals
    NM Krishna, K Sekaran, AVN Vamsi, GSP Ghantasala, P Chandana, ...
    Ieee Access 7, 77905-77914 , 2019
    2019.0
    Citations: 79
  • Deep learning convolutional neural network (CNN) With Gaussian mixture model for predicting pancreatic cancer
    KSPCNMKS Kadry
    Multimedia Tools and Applications, pp 1–15 , 2019
    2019.0
    Citations: 169
  • Object Identification Using Image Fusion
    DYS P. Chandana, Dr. P. Srinivasa Rao
    International Journal of Advance Research, Ideas and Innovations in … , 2017
    2017.0
  • An efficient content-based image retrieval (CBIR) using GLCM for feature extraction
    P Chandana, P Srinivas Rao, CH Satyanarayana, Y Srinivas, ...
    Recent Developments in Intelligent Computing, Communication and Devices … , 2017
    2017.0
    Citations: 10
  • Sketch Retrieval using Contour Detection by Chain Codes
    PC Mohan Mahanty , D. Kiranmayi
    International Journal of Advanced Research in Computer and Communication … , 2015
    2015.0
    Citations: 3
  • Comparison between Local Binary Pattern and Chain Code Techniques for Image Retrieval using Sketches
    DYS P. Chandana ,prof. P. Srinivas Rao
    International Journal of Advanced Research in Computer and Communication … , 2015
    2015.0
    Citations: 1
  • IMPLEMENTING GAUSSIAN MIXTURE MODEL FOR IDENTIFYING IMAGE SEGMENTATION
    S Eddula, P Chandana, BS Swaroop
    2012.0
  • A novel approach for unrestricted watermarking method using wavelet transform
    R Nageswararao, P Chandana, M Madhavi, I Visakhapatnam, I Ongole
    Int. J. Sci. Adv. Technol 1, 255-261 , 2011
    2011.0
    Citations: 2
  • A Novel approach for Unrestricted Watermarking method using Wavelet Transform
    RNPCM Madhavi
    2011.0
  • Dynamic Bandwidth Allocation in WIMAX
    JP P.Chandana,A.Gauthami Latha
    ICSCI , 2010
    2010.0
  • & Damaševičius, R.(2019). An efficient mixture model approach in brain-machine interface systems for extracting the psychological status of mentally impaired persons using EEG …
    NM Krishna, K Sekaran, AVN Vamsi, GP Ghantasala, P Chandana, ...
    Ieee Access 7, 77905-77914 , 0
    Citations: 15

MOST CITED SCHOLAR PUBLICATIONS

  • Deep learning convolutional neural network (CNN) With Gaussian mixture model for predicting pancreatic cancer
    KSPCNMKS Kadry
    Multimedia Tools and Applications, pp 1–15 , 2019
    2019.0
    Citations: 169
  • An efficient mixture model approach in brain-machine interface systems for extracting the psychological status of mentally impaired persons using EEG signals
    NM Krishna, K Sekaran, AVN Vamsi, GSP Ghantasala, P Chandana, ...
    Ieee Access 7, 77905-77914 , 2019
    2019.0
    Citations: 79
  • Design of optimal search engine using text summarization through artificial intelligence techniques
    K Sekaran, P Chandana, JRV Jeny, MN Meqdad, S Kadry
    TELKOMNIKA (Telecommunication Computing Electronics and Control) 18 (3 … , 2020
    2020.0
    Citations: 52
  • An effective identification of crop diseases using faster region based convolutional neural network and expert systems
    P Chandana
    International Journal of Electrical and Computer Engineering (IJECE) , 2020
    2020.0
    Citations: 34
  • & Damaševičius, R.(2019). An efficient mixture model approach in brain-machine interface systems for extracting the psychological status of mentally impaired persons using EEG …
    NM Krishna, K Sekaran, AVN Vamsi, GP Ghantasala, P Chandana, ...
    Ieee Access 7, 77905-77914 , 0
    Citations: 15
  • Implementation of face and eye detection on DM6437 board using simulink model
    B Vijayalaxmi, K Sekaran, N Neelima, P Chandana, MN Meqdad, S Kadry
    Bulletin of Electrical Engineering and Informatics 9 (2), 785-791 , 2020
    2020.0
    Citations: 10
  • An efficient content-based image retrieval (CBIR) using GLCM for feature extraction
    P Chandana, P Srinivas Rao, CH Satyanarayana, Y Srinivas, ...
    Recent Developments in Intelligent Computing, Communication and Devices … , 2017
    2017.0
    Citations: 10
  • A comprehensive survey of geographical routing in multi-hop wireless networks
    A Balaram, M Silparaj, SA Nabi, P Chandana
    Cloud Computing Enabled Big-Data Analytics in Wireless Ad-hoc Networks, 141-172 , 2022
    2022.0
    Citations: 6
  • Analyzing the extremist reviewer groups on online products
    P Chandana, NP Sree, V Ramya, G Bhavana
    2021 Third International Conference on Inventive Research in Computing … , 2021
    2021.0
    Citations: 4
  • Sketch Retrieval using Contour Detection by Chain Codes
    PC Mohan Mahanty , D. Kiranmayi
    International Journal of Advanced Research in Computer and Communication … , 2015
    2015.0
    Citations: 3
  • A survey of vanet routing attacks and defense mechanisms in intelligent transportation system
    A Balaram, P Chandana, SA Nabi, M SilpaRaj
    Self‐Powered Cyber Physical Systems, 213-226 , 2023
    2023.0
    Citations: 2
  • Anomaly detection in indoor localization using Machine Learning
    P Chandana, C Aishwarya, SS Muskan
    2021 Third International Conference on Inventive Research in Computing … , 2021
    2021.0
    Citations: 2
  • A novel approach for unrestricted watermarking method using wavelet transform
    R Nageswararao, P Chandana, M Madhavi, I Visakhapatnam, I Ongole
    Int. J. Sci. Adv. Technol 1, 255-261 , 2011
    2011.0
    Citations: 2
  • Comparison between Local Binary Pattern and Chain Code Techniques for Image Retrieval using Sketches
    DYS P. Chandana ,prof. P. Srinivas Rao
    International Journal of Advanced Research in Computer and Communication … , 2015
    2015.0
    Citations: 1
  • An Effective Identification of Crop diseases using Faster Region based Convolutional Neural Network and Expert Systems
    DN Seifedine Kadry P. Chandana , G. S. Pradeep Ghantasala , J. Rethna Virgil ...
    International Journal of Electrical and Computer Engineering (IJECE) - http … , 2020
    2020.0
  • Object Identification Using Image Fusion
    DYS P. Chandana, Dr. P. Srinivasa Rao
    International Journal of Advance Research, Ideas and Innovations in … , 2017
    2017.0
  • IMPLEMENTING GAUSSIAN MIXTURE MODEL FOR IDENTIFYING IMAGE SEGMENTATION
    S Eddula, P Chandana, BS Swaroop
    2012.0
  • A Novel approach for Unrestricted Watermarking method using Wavelet Transform
    RNPCM Madhavi
    2011.0
  • Dynamic Bandwidth Allocation in WIMAX
    JP P.Chandana,A.Gauthami Latha
    ICSCI , 2010
    2010.0