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Priya Ranjan

Templecity Institute of Technology and Engineering, Department of Electrical Engineeering, Faculty Member

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KOTESWARA RAO MAKKENA 21PHD7131

Josephin Shermila

University of Delhi

Prof Muhammad Sher Ramzan

King AbdulAziz University (KAU) Jeddah, Saudi Arabia

MD. MUHTADIR RAHMAN

University of Chittagong

Thierry Mugenzi

Eskisehir Technical University

karlo abnoosian

Iran University of Science and Technology (IUST)

Rashiduzzaman Shakil

Daffodil International University(DIU)

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Papers by Priya Ranjan

An efficient synthetic minority oversampling technique-based ensemble learning model to detect COVID-19 severity

by beei iaes and Priya Ranjan

Bulletin of Electrical Engineering and Informatics

The COVID-19 pandemic has highlighted the importance of accurately predicting disease severity to... more The COVID-19 pandemic has highlighted the importance of accurately predicting disease severity to ensure timely intervention and effective allocation of healthcare resources, which can ultimately improve patient outcomes. This study aims to develop an efficient machine learning (ML) model based on patient demographic and clinical data. It utilizes advanced feature engineering techniques to reduce the dimensionality of dataset and address the issue of highly imbalanced data using synthetic minority oversampling technique (SMOTE). The study employs several ensemble learning models, including XGBoost, Random Forest, AdaBoost, voting ensemble, enhanced-weighted voting ensemble, and stack-based ensembles with support vector machine (SVM) and Gaussian Naïve Bayes as metalearners, to develop the proposed model. The results indicate that the proposed model outperformed the top-performing models reported in previous studies. It achieved an accuracy of 0.978, sensitivity of 1.0, precision of 0.875, F1-score of 0.934, and receiver operating characteristic area under the curve (ROC-AUC) of 0.965. The study identified several features that significantly correlated with COVID-19 severity, which included respiratory rate (breaths per minute), c-reactive proteins, age, and total leukocyte count (TLC) count. The proposed approach presents a promising method for accurate COVID-19 severity prediction, which may prove valuable in assisting healthcare providers in making informed decisions about patient care.

Kloman Metre: An EMD-Based Tool for Triaging Diseases Leading to Lung Infections Including COVID-19

Lecture Notes in Networks and Systems, 2021

The digital revolution can help developing countries to overcome the problem of limited healthcar... more The digital revolution can help developing countries to overcome the problem of limited healthcare infrastructure in developing nations such as India. The COVID-19 pandemic has shown the urgency of integration of digital technologies into healthcare infrastructure. In order to solve the issue of lack of trained healthcare professionals at public health centres (PHCs), researchers are trying to build tools which can help to tag pulmonary ailment within a fraction of second. Such tagging will help the medical community to utilize their time more efficiently. In this work, we have tried to assess the "lung health" of patients suffering from a variety of pulmonary diseases including COVID-19, tuberculosis and pneumonia by applying Earth Mover's Distance algorithm to the X-ray images of the patients. The lung X-ray images of patients suffering from pneumonia, TB and COVID-19 and healthy persons are pooled together from various datasets. Our preliminary data based upon 100 random images depicting each type of lung disease such as COVID-19, tuberculosis and pneumonia revealed that patients suffering from tuberculosis have the highest severity as per the values obtained from the EMD scale.

Effect of hand grip actions on object recognition process: a machine learning-based approach for improved motor rehabilitation

Neural Computing and Applications, 2020

Brain computer interface (BCI) is the current trend in technology expansion as it provides an eas... more Brain computer interface (BCI) is the current trend in technology expansion as it provides an easy interface between human brain and machine. The demand for BCI based applications is growing tremendously and efforts are in progress to deploy BCI devices for real world applications. One of the widely known applications of BCI technology is rehabilitation in which BCI devices can provide various types of assistance to specially-abled persons. In this paper the effect of hand actions on objects is analyzed for motor related mental task. The proposed approach analysis electroencephalogram (EEG) based brain activity which was captured for images shown with different gripping actions on objects. The EEG recordings are first pre-processed, followed by extraction of epochs and frequency bands using discrete wavelet transform (DWT), afterwards feature extraction followed by training and classification steps are performed for classifying the grip action into congruent (correct) and incongruent (incorrect) grip categories. The proposed work makes use of average power and relative wavelet energy as discriminating features which are then fed to train an artificial neural network for automatically classifying the incoming EEG patterns into correct or incorrect object hand grips. The performance evaluation of proposed system is done on real EEG data set obtained from 14 subjects. Experimental results have shown an accuracy of 75%. Also, to evaluate the effectiveness of our work, a comparison of our work with other state of art works reported by different authors is presented at the end. The results show the effectiveness of proposed approach and suggest further that the system can be used for analyse and train subjects having motorrelated disabilities for perceiving correct or incorrect hand grips on objects.

Machine learning approaches in the diagnosis of infectious diseases: a review

Bulletin of Electrical Engineering and Informatics

Infectious diseases are a group of medical conditions caused by infectious agents such as parasit... more Infectious diseases are a group of medical conditions caused by infectious agents such as parasites, bacteria, viruses, or fungus. Patients who are undiagnosed may unwittingly spread the disease to others. Because of the transmission of these agents, epidemics, if not pandemics, are possible. Early detection can help to prevent the spread of an outbreak or put an end to it. Infectious disease prevention, early identification, and management can be aided by machine learning (ML) methods. The implementation of ML algorithms such as logistic regression, support vector machine, Naive Bayes, decision tree, random forest, K-nearest neighbor, artificial neural network, convolutional neural network, and ensemble techniques to automate the process of infectious disease diagnosis is investigated in this study. We examined a number of ML models for tuberculosis (TB), influenza, human immunodeficiency virus (HIV), dengue fever, COVID-19, cystitis, and nonspecific urethritis. Existing models hav...

A performance study of image segmentation techniques

2015 4th International Conference on Reliability, Infocom Technologies and Optimization (ICRITO) (Trends and Future Directions), 2015

Image based applications such as target tracking, tumor detection, texture extraction requires an... more Image based applications such as target tracking, tumor detection, texture extraction requires an efficient image segmentation process. The partitioning of image into various non-overlapping distinct regions refers the image segmentation. Various segmentation techniques like edge, threshold, region, clustering and neural network are involved in the effective image analysis. The efficiency of the segmentation process improved with the help of several algorithms, namely, active contour, level set, Fuzzy clustering and K-means clustering. This paper analyses the performance of algorithms for image segmentation in detail. Intensity and texture based image segmentation is the two levels of the level set method. The combination of both intensity and texture based image segmentation provides better results than the traditional methods. The detailed survey of segmentation techniques provides the requirement of the suitable enhancement method that supports both intensity and texture based segmentation for better results. The comparison between the traditional image segmentation techniques are illustrated.

Earth Mover’s Distance-Based Tool for Rapid Screening of Cervical Cancer Using Cervigrams

Applied Sciences

Cervical cancer is a major public health challenge that can be cured with early diagnosis and tim... more Cervical cancer is a major public health challenge that can be cured with early diagnosis and timely treatment. This challenge formed the rationale behind our design and development of an intelligent and robust image analysis and diagnostic tool/scale, namely “OM—The OncoMeter”, for which we used R (version-3.6.3) and Linux (Ubuntu-20.04) to tag and triage patients in order of their disease severity. The socio-demographic profiles and cervigrams of 398 patients evaluated at OPDs of Batra Hospital & Medical Research Centre, New Delhi, India, and Delhi State Cancer Institute (East), New Delhi, India, were acquired during the course of this study. Tested on 398 India-specific women’s cervigrams, the scale yielded significant achievements, with 80.15% accuracy, a sensitivity of 84.79%, and a specificity of 66.66%. The statistical analysis of sociodemographic profiles showed significant associations of age, education, annual income, occupation, and menstrual health with the health of the...

Earth Mover’s Distance-Based Tool for Rapid Screening of Cervical Cancer Using Cervigrams

Applied Sciences

Cervical cancer is a major public health challenge that can be cured with early diagnosis and tim... more Cervical cancer is a major public health challenge that can be cured with early diagnosis and timely treatment. This challenge formed the rationale behind our design and development of an intelligent and robust image analysis and diagnostic tool/scale, namely “OM—The OncoMeter”, for which we used R (version-3.6.3) and Linux (Ubuntu-20.04) to tag and triage patients in order of their disease severity. The socio-demographic profiles and cervigrams of 398 patients evaluated at OPDs of Batra Hospital & Medical Research Centre, New Delhi, India, and Delhi State Cancer Institute (East), New Delhi, India, were acquired during the course of this study. Tested on 398 India-specific women’s cervigrams, the scale yielded significant achievements, with 80.15% accuracy, a sensitivity of 84.79%, and a specificity of 66.66%. The statistical analysis of sociodemographic profiles showed significant associations of age, education, annual income, occupation, and menstrual health with the health of the...

An Application-oriented Model for Wireless Sensor Networks integrated with Telecom Infra

This paper aims to propose a significant way of remote access and real time monitoring of a parti... more This paper aims to propose a significant way of remote access and real time monitoring of a particular geographic area by integrating wireless sensor clouds with existing Telecom infrastructure and applications built around them through a gateway. This utility is very potent for environment monitoring in harsh and inaccessible places like mines, nuclear reactors, etc. We demonstrate a scaled down version of multi-hop network of wireless sensor nodes and its integration with existing telecom network infrastructure via a gateway. The kind of results achieved like temperature monitoring etc. gives a glimpse of an enormous step ahead in mine safety.

Hybrid CDN structure with a P2P based streaming protocol

Over the last decade, internet has seen an exponential increase in its growth.With more and more ... more Over the last decade, internet has seen an exponential increase in its growth.With more and more people using it, efficient data delivery over the internet has become a key issue. Peer-to-peer (P2P)/seed sharing based networks have several desirable features for content distribution, such as low costs, scalability, and fault tolerance. While the invention of each of such specialized systems has improved the user experience, some fundamental shortcomings of these systems have often been neglected. These shortcomings of content distribution systems have become severe bottlenecks in scalability of the internet.In order to combine the desired features of classical Content Distribution Networks (CDNs) and P2P/seed sharing based networks, we propose a hybrid CDN structure with a P2P/seed sharing based streaming protocol in the access network . In this work, we focus on the problem of data redundancy (at each node) and show how severely it impacts the network economics and the experience o...

Multi-cell nuclei segmentation in cervical cancer images by integrated feature vectors

Multimedia Tools and Applications, 2017

Software Aspects of WSN for Monitoring in an Indian Greenhouse

2015 International Conference on Computational Intelligence and Communication Networks (CICN), 2015

Horticulture industry in India is beginning to see the technological drive and that leads to the ... more Horticulture industry in India is beginning to see the technological drive and that leads to the low production of greenhouse. In general equipment cost of drip irrigation, motors, solenoid valves etc. Which may cost upto Rs. 4 lakh, many not be affordable for greenhouse owners. Keep this in view, we propose an innovative implementation of software aspects of WSN (Wireless Sensor Networking) for monitoring greenhouses in Indian economical condition. Yuktix IOT hardware platform along with end sensor nodes and CDAU (Central data acquisition unit) together can be used to locally / remotely monitor internal conditions of greenhouse chambers using Yuktix cloud via Web-application and Android application as well as their internal environment can be controlled locally/remotely using Yuktix controller. Same data in the cloud can be downloaded from the archive further to do the in-depth analysis like analysing the shift/second order statistics in the mean temperature and humidity around the year and so.

Automatic disease screening method using image processing for dried blood microfluidic drop stain pattern recognition

Journal of medical engineering & technology, Jan 21, 2016

This paper examines programmed automatic recognition of infection from samples of dried stains of... more This paper examines programmed automatic recognition of infection from samples of dried stains of micro-scale drops of patient blood. This technique has the upside of being low-cost and less-intrusive and not requiring puncturing the patient with a needle for drawing blood, which is especially critical for infants and the matured. It also does not require expensive pathological blood test laboratory equipment. The method is shown in this work to be successful for ailment identification in patients suffering from tuberculosis and anaemia. Illness affects the physical properties of blood, which thus influence the samples of dried micro-scale blood drop stains. For instance, if a patient has a severe drop in platelet count, which is often the case of dengue or malaria patients, the blood's physical property of viscosity drops substantially, i.e. the blood is thinner. Thus, the blood micro-scale drop stain samples can be utilised for diagnosing maladies. This paper presents programm...

Global stability of joint routing and rate control algoriths

We provide a detail global stability analysis of end-to-end algorithms for join routing and rate ... more We provide a detail global stability analysis of end-to-end algorithms for join routing and rate control framework posed in [2]. We provide a robust criteria which is delay and gain independent and depends only on utility and pricing/marking function and thus opening a huge design space otherwise hidden due to local and linear analysis performed in [2]. We shall also outline the exact nature of instability and relate it to slowly oscillating periodic orbits (SOPs). Furthermore, future directions for routing, rate con-trol and effect of dynamic admission control along with volatile topology is outlined. This is a working paper and it will evolve as more work directions are added.

Trade-offs in rate control with communication delay

Information Systems Research, 2003

We adopt the optimization framework for rate allocation problem proposed by Kelly and characteriz... more We adopt the optimization framework for rate allocation problem proposed by Kelly and characterize the stability condition with an arbitrary communication delay in the case of single resource. We demonstrate the existence of a fundamental trade-off between users' price elasticity of demand and the responsiveness of resource through a choice of price function as well as between system stability and resource utilization. We investigate the effects of non-responsive traffic on system stability and show that the presence of non-responsive traffic enhances the stability of system. We also investigate the system behavior after the system loses its stability.

Towards a new low cost, simple implementation using embedded system wireless networking for UAVs

2011 Fifth IEEE International Conference on Advanced Telecommunication Systems and Networks (ANTS), 2011

This work focuses on the development of relatively simple, low cost, autonomous and feasible wire... more This work focuses on the development of relatively simple, low cost, autonomous and feasible wireless sensor network and related embedded system combination to be integrated with AMATEUR UAV and unmanned ground vehicle (UGV) management system both at inter and intra level communication and networking for different modules and different vehicles. What we describe here is our progress in a ongoing live project. We also make fresh implementable proposals to integrate autonomous Amateur UAV and share plans to implement it for vehicle management system using intelligent communication and networked system approach. We envision the capability of modern sensing network where communication between different sensors and embedded system combination enable user to have a closer view over larger area and provide potent capability of acting autonomously.

Dynamics of interacting queues with priority

Proceedings of the 2003 American Control Conference, 2003.

Nonlinear instabilities of D2TCP-II

2013 International Conference on Technology, Informatics, Management, Engineering and Environment, 2013

In the era of heavy-duty transmission control protocols (TCP), adapted for extremely hi-bandwidth... more In the era of heavy-duty transmission control protocols (TCP), adapted for extremely hi-bandwidth datacenters; the fundamental question of stable interaction with either proposed/customized active queue management(AQM) or popularly discussed Random Early Detection (RED) remains a hotly debated issue. While there are claims of "oscillation" only dynamical behavior, there are equally large number of claims which demonstrate the chaotic nature of different flavors of TCP and their AQM interaction. In this work, we provide a sound and analytical mathematical model of DTCP/D2TCP and study their interaction with threshold based packet marking policy. Our work shows that for a simple scenario this interaction is chaotic in nature and has large variability in dynamical behavior over orders of magnitude changes in parameter range as demonstrated by bifurcation diagrams. We conclude with numerical simulation evidence that chaotic behavior of protocols is inherent in their design which they inherit from their early vanilla TCP days, and it has serious implications for data-center throughput, load batching and collapse in Incast kind of scenario.

Classification of Colposcopic Cervigrams Using EMD in R

Communications in Computer and Information Science

Cervical cancer is one of the most common cancer among women worldwide which can be cured if dete... more Cervical cancer is one of the most common cancer among women worldwide which can be cured if detected early. The current gold standard for cervical cancer diagnosis is clumsy and time consuming because it relies heavily on the subjective knowledge of the medical professionals which often results in false negatives and false positives. To reduce time and operational complexities associated with early diagnosis, we require a portable interactive diagnostic tool for early detection, particularly in developing countries where cervical cancer incidence and related mortality is high. Incorporation of digital colposcopy in place of manual diagnosis for cervical cancer screening can increase the precision and strongly reduce the chances of error in a time-specific manner. Thus, we propose a robust and interactive colposcopic image analysis and diagnostic tool, which can categorically process colposcopic images into Type I, Type II and Type III cervigrams and identify lesions in least amount of time. Furthermore, successful binning of diagnosed cervigrams into digital colposcopic library and incorporation of a set of specific parameters that are typically referred to for identification of transformation zone and SCJ (squamo columnar junction) with the help of open source Programming language-"R" is one of the major highlights of the application. The software has the ability to automatically identify and quantify the morphological features, color intensity, sensitivity and other parameters digitally which may improve and accelerate screening and early diagnosis, ultimately leading to timely treatment of cervical cancer.

Hybrid CDN structure with a P2P based streaming protocol

ArXiv, 2010

Over the last decade, internet has seen an exponential increase in its growth.With more and more ... more Over the last decade, internet has seen an exponential increase in its growth.With more and more people using it, efficient data delivery over the internet has become a key issue. Peer-to-peer (P2P)/seed sharing based networks have several desirable features for content distribution, such as low costs, scalability, and fault tolerance. While the invention of each of such specialized systems has improved the user experience, some fundamental shortcomings of these systems have often been neglected. These shortcomings of content distribution systems have become severe bottlenecks in scalability of the internet.In order to combine the desired features of classical Content Distribution Networks (CDNs) and P2P/seed sharing based networks, we propose a hybrid CDN structure with a P2P/seed sharing based streaming protocol in the access network . In this work, we focus on the problem of data redundancy (at each node) and show how severely it impacts the network economics and the experience o...

An Application-oriented Model for Wireless Sensor Networks integrated with Telecom Infra

ArXiv, 2010

This paper aims to propose a significant way of remote access and real time monitoring of a parti... more This paper aims to propose a significant way of remote access and real time monitoring of a particular geographic area by integrating wireless sensor clouds with existing Telecom infrastructure and applications built around them through a gateway. This utility is very potent for environment monitoring in harsh and inaccessible places like mines, nuclear reactors, etc. We demonstrate a scaled down version of multi-hop network of wireless sensor nodes and its integration with existing telecom network infrastructure via a gateway.

An efficient synthetic minority oversampling technique-based ensemble learning model to detect COVID-19 severity

by beei iaes and Priya Ranjan

Bulletin of Electrical Engineering and Informatics

The COVID-19 pandemic has highlighted the importance of accurately predicting disease severity to... more The COVID-19 pandemic has highlighted the importance of accurately predicting disease severity to ensure timely intervention and effective allocation of healthcare resources, which can ultimately improve patient outcomes. This study aims to develop an efficient machine learning (ML) model based on patient demographic and clinical data. It utilizes advanced feature engineering techniques to reduce the dimensionality of dataset and address the issue of highly imbalanced data using synthetic minority oversampling technique (SMOTE). The study employs several ensemble learning models, including XGBoost, Random Forest, AdaBoost, voting ensemble, enhanced-weighted voting ensemble, and stack-based ensembles with support vector machine (SVM) and Gaussian Naïve Bayes as metalearners, to develop the proposed model. The results indicate that the proposed model outperformed the top-performing models reported in previous studies. It achieved an accuracy of 0.978, sensitivity of 1.0, precision of 0.875, F1-score of 0.934, and receiver operating characteristic area under the curve (ROC-AUC) of 0.965. The study identified several features that significantly correlated with COVID-19 severity, which included respiratory rate (breaths per minute), c-reactive proteins, age, and total leukocyte count (TLC) count. The proposed approach presents a promising method for accurate COVID-19 severity prediction, which may prove valuable in assisting healthcare providers in making informed decisions about patient care.

Kloman Metre: An EMD-Based Tool for Triaging Diseases Leading to Lung Infections Including COVID-19

Lecture Notes in Networks and Systems, 2021

The digital revolution can help developing countries to overcome the problem of limited healthcar... more The digital revolution can help developing countries to overcome the problem of limited healthcare infrastructure in developing nations such as India. The COVID-19 pandemic has shown the urgency of integration of digital technologies into healthcare infrastructure. In order to solve the issue of lack of trained healthcare professionals at public health centres (PHCs), researchers are trying to build tools which can help to tag pulmonary ailment within a fraction of second. Such tagging will help the medical community to utilize their time more efficiently. In this work, we have tried to assess the "lung health" of patients suffering from a variety of pulmonary diseases including COVID-19, tuberculosis and pneumonia by applying Earth Mover's Distance algorithm to the X-ray images of the patients. The lung X-ray images of patients suffering from pneumonia, TB and COVID-19 and healthy persons are pooled together from various datasets. Our preliminary data based upon 100 random images depicting each type of lung disease such as COVID-19, tuberculosis and pneumonia revealed that patients suffering from tuberculosis have the highest severity as per the values obtained from the EMD scale.

Effect of hand grip actions on object recognition process: a machine learning-based approach for improved motor rehabilitation

Neural Computing and Applications, 2020

Brain computer interface (BCI) is the current trend in technology expansion as it provides an eas... more Brain computer interface (BCI) is the current trend in technology expansion as it provides an easy interface between human brain and machine. The demand for BCI based applications is growing tremendously and efforts are in progress to deploy BCI devices for real world applications. One of the widely known applications of BCI technology is rehabilitation in which BCI devices can provide various types of assistance to specially-abled persons. In this paper the effect of hand actions on objects is analyzed for motor related mental task. The proposed approach analysis electroencephalogram (EEG) based brain activity which was captured for images shown with different gripping actions on objects. The EEG recordings are first pre-processed, followed by extraction of epochs and frequency bands using discrete wavelet transform (DWT), afterwards feature extraction followed by training and classification steps are performed for classifying the grip action into congruent (correct) and incongruent (incorrect) grip categories. The proposed work makes use of average power and relative wavelet energy as discriminating features which are then fed to train an artificial neural network for automatically classifying the incoming EEG patterns into correct or incorrect object hand grips. The performance evaluation of proposed system is done on real EEG data set obtained from 14 subjects. Experimental results have shown an accuracy of 75%. Also, to evaluate the effectiveness of our work, a comparison of our work with other state of art works reported by different authors is presented at the end. The results show the effectiveness of proposed approach and suggest further that the system can be used for analyse and train subjects having motorrelated disabilities for perceiving correct or incorrect hand grips on objects.

Machine learning approaches in the diagnosis of infectious diseases: a review

Bulletin of Electrical Engineering and Informatics

Infectious diseases are a group of medical conditions caused by infectious agents such as parasit... more Infectious diseases are a group of medical conditions caused by infectious agents such as parasites, bacteria, viruses, or fungus. Patients who are undiagnosed may unwittingly spread the disease to others. Because of the transmission of these agents, epidemics, if not pandemics, are possible. Early detection can help to prevent the spread of an outbreak or put an end to it. Infectious disease prevention, early identification, and management can be aided by machine learning (ML) methods. The implementation of ML algorithms such as logistic regression, support vector machine, Naive Bayes, decision tree, random forest, K-nearest neighbor, artificial neural network, convolutional neural network, and ensemble techniques to automate the process of infectious disease diagnosis is investigated in this study. We examined a number of ML models for tuberculosis (TB), influenza, human immunodeficiency virus (HIV), dengue fever, COVID-19, cystitis, and nonspecific urethritis. Existing models hav...

A performance study of image segmentation techniques

2015 4th International Conference on Reliability, Infocom Technologies and Optimization (ICRITO) (Trends and Future Directions), 2015

Image based applications such as target tracking, tumor detection, texture extraction requires an... more Image based applications such as target tracking, tumor detection, texture extraction requires an efficient image segmentation process. The partitioning of image into various non-overlapping distinct regions refers the image segmentation. Various segmentation techniques like edge, threshold, region, clustering and neural network are involved in the effective image analysis. The efficiency of the segmentation process improved with the help of several algorithms, namely, active contour, level set, Fuzzy clustering and K-means clustering. This paper analyses the performance of algorithms for image segmentation in detail. Intensity and texture based image segmentation is the two levels of the level set method. The combination of both intensity and texture based image segmentation provides better results than the traditional methods. The detailed survey of segmentation techniques provides the requirement of the suitable enhancement method that supports both intensity and texture based segmentation for better results. The comparison between the traditional image segmentation techniques are illustrated.

Earth Mover’s Distance-Based Tool for Rapid Screening of Cervical Cancer Using Cervigrams

Applied Sciences

Cervical cancer is a major public health challenge that can be cured with early diagnosis and tim... more Cervical cancer is a major public health challenge that can be cured with early diagnosis and timely treatment. This challenge formed the rationale behind our design and development of an intelligent and robust image analysis and diagnostic tool/scale, namely “OM—The OncoMeter”, for which we used R (version-3.6.3) and Linux (Ubuntu-20.04) to tag and triage patients in order of their disease severity. The socio-demographic profiles and cervigrams of 398 patients evaluated at OPDs of Batra Hospital & Medical Research Centre, New Delhi, India, and Delhi State Cancer Institute (East), New Delhi, India, were acquired during the course of this study. Tested on 398 India-specific women’s cervigrams, the scale yielded significant achievements, with 80.15% accuracy, a sensitivity of 84.79%, and a specificity of 66.66%. The statistical analysis of sociodemographic profiles showed significant associations of age, education, annual income, occupation, and menstrual health with the health of the...

Earth Mover’s Distance-Based Tool for Rapid Screening of Cervical Cancer Using Cervigrams

Applied Sciences

Cervical cancer is a major public health challenge that can be cured with early diagnosis and tim... more Cervical cancer is a major public health challenge that can be cured with early diagnosis and timely treatment. This challenge formed the rationale behind our design and development of an intelligent and robust image analysis and diagnostic tool/scale, namely “OM—The OncoMeter”, for which we used R (version-3.6.3) and Linux (Ubuntu-20.04) to tag and triage patients in order of their disease severity. The socio-demographic profiles and cervigrams of 398 patients evaluated at OPDs of Batra Hospital & Medical Research Centre, New Delhi, India, and Delhi State Cancer Institute (East), New Delhi, India, were acquired during the course of this study. Tested on 398 India-specific women’s cervigrams, the scale yielded significant achievements, with 80.15% accuracy, a sensitivity of 84.79%, and a specificity of 66.66%. The statistical analysis of sociodemographic profiles showed significant associations of age, education, annual income, occupation, and menstrual health with the health of the...

An Application-oriented Model for Wireless Sensor Networks integrated with Telecom Infra

This paper aims to propose a significant way of remote access and real time monitoring of a parti... more This paper aims to propose a significant way of remote access and real time monitoring of a particular geographic area by integrating wireless sensor clouds with existing Telecom infrastructure and applications built around them through a gateway. This utility is very potent for environment monitoring in harsh and inaccessible places like mines, nuclear reactors, etc. We demonstrate a scaled down version of multi-hop network of wireless sensor nodes and its integration with existing telecom network infrastructure via a gateway. The kind of results achieved like temperature monitoring etc. gives a glimpse of an enormous step ahead in mine safety.

Hybrid CDN structure with a P2P based streaming protocol

Over the last decade, internet has seen an exponential increase in its growth.With more and more ... more Over the last decade, internet has seen an exponential increase in its growth.With more and more people using it, efficient data delivery over the internet has become a key issue. Peer-to-peer (P2P)/seed sharing based networks have several desirable features for content distribution, such as low costs, scalability, and fault tolerance. While the invention of each of such specialized systems has improved the user experience, some fundamental shortcomings of these systems have often been neglected. These shortcomings of content distribution systems have become severe bottlenecks in scalability of the internet.In order to combine the desired features of classical Content Distribution Networks (CDNs) and P2P/seed sharing based networks, we propose a hybrid CDN structure with a P2P/seed sharing based streaming protocol in the access network . In this work, we focus on the problem of data redundancy (at each node) and show how severely it impacts the network economics and the experience o...

Multi-cell nuclei segmentation in cervical cancer images by integrated feature vectors

Multimedia Tools and Applications, 2017

Software Aspects of WSN for Monitoring in an Indian Greenhouse

2015 International Conference on Computational Intelligence and Communication Networks (CICN), 2015

Horticulture industry in India is beginning to see the technological drive and that leads to the ... more Horticulture industry in India is beginning to see the technological drive and that leads to the low production of greenhouse. In general equipment cost of drip irrigation, motors, solenoid valves etc. Which may cost upto Rs. 4 lakh, many not be affordable for greenhouse owners. Keep this in view, we propose an innovative implementation of software aspects of WSN (Wireless Sensor Networking) for monitoring greenhouses in Indian economical condition. Yuktix IOT hardware platform along with end sensor nodes and CDAU (Central data acquisition unit) together can be used to locally / remotely monitor internal conditions of greenhouse chambers using Yuktix cloud via Web-application and Android application as well as their internal environment can be controlled locally/remotely using Yuktix controller. Same data in the cloud can be downloaded from the archive further to do the in-depth analysis like analysing the shift/second order statistics in the mean temperature and humidity around the year and so.

Automatic disease screening method using image processing for dried blood microfluidic drop stain pattern recognition

Journal of medical engineering & technology, Jan 21, 2016

This paper examines programmed automatic recognition of infection from samples of dried stains of... more This paper examines programmed automatic recognition of infection from samples of dried stains of micro-scale drops of patient blood. This technique has the upside of being low-cost and less-intrusive and not requiring puncturing the patient with a needle for drawing blood, which is especially critical for infants and the matured. It also does not require expensive pathological blood test laboratory equipment. The method is shown in this work to be successful for ailment identification in patients suffering from tuberculosis and anaemia. Illness affects the physical properties of blood, which thus influence the samples of dried micro-scale blood drop stains. For instance, if a patient has a severe drop in platelet count, which is often the case of dengue or malaria patients, the blood's physical property of viscosity drops substantially, i.e. the blood is thinner. Thus, the blood micro-scale drop stain samples can be utilised for diagnosing maladies. This paper presents programm...

Global stability of joint routing and rate control algoriths

We provide a detail global stability analysis of end-to-end algorithms for join routing and rate ... more We provide a detail global stability analysis of end-to-end algorithms for join routing and rate control framework posed in [2]. We provide a robust criteria which is delay and gain independent and depends only on utility and pricing/marking function and thus opening a huge design space otherwise hidden due to local and linear analysis performed in [2]. We shall also outline the exact nature of instability and relate it to slowly oscillating periodic orbits (SOPs). Furthermore, future directions for routing, rate con-trol and effect of dynamic admission control along with volatile topology is outlined. This is a working paper and it will evolve as more work directions are added.

Trade-offs in rate control with communication delay

Information Systems Research, 2003

We adopt the optimization framework for rate allocation problem proposed by Kelly and characteriz... more We adopt the optimization framework for rate allocation problem proposed by Kelly and characterize the stability condition with an arbitrary communication delay in the case of single resource. We demonstrate the existence of a fundamental trade-off between users' price elasticity of demand and the responsiveness of resource through a choice of price function as well as between system stability and resource utilization. We investigate the effects of non-responsive traffic on system stability and show that the presence of non-responsive traffic enhances the stability of system. We also investigate the system behavior after the system loses its stability.

Towards a new low cost, simple implementation using embedded system wireless networking for UAVs

2011 Fifth IEEE International Conference on Advanced Telecommunication Systems and Networks (ANTS), 2011

This work focuses on the development of relatively simple, low cost, autonomous and feasible wire... more This work focuses on the development of relatively simple, low cost, autonomous and feasible wireless sensor network and related embedded system combination to be integrated with AMATEUR UAV and unmanned ground vehicle (UGV) management system both at inter and intra level communication and networking for different modules and different vehicles. What we describe here is our progress in a ongoing live project. We also make fresh implementable proposals to integrate autonomous Amateur UAV and share plans to implement it for vehicle management system using intelligent communication and networked system approach. We envision the capability of modern sensing network where communication between different sensors and embedded system combination enable user to have a closer view over larger area and provide potent capability of acting autonomously.

Dynamics of interacting queues with priority

Proceedings of the 2003 American Control Conference, 2003.

Nonlinear instabilities of D2TCP-II

2013 International Conference on Technology, Informatics, Management, Engineering and Environment, 2013

In the era of heavy-duty transmission control protocols (TCP), adapted for extremely hi-bandwidth... more In the era of heavy-duty transmission control protocols (TCP), adapted for extremely hi-bandwidth datacenters; the fundamental question of stable interaction with either proposed/customized active queue management(AQM) or popularly discussed Random Early Detection (RED) remains a hotly debated issue. While there are claims of "oscillation" only dynamical behavior, there are equally large number of claims which demonstrate the chaotic nature of different flavors of TCP and their AQM interaction. In this work, we provide a sound and analytical mathematical model of DTCP/D2TCP and study their interaction with threshold based packet marking policy. Our work shows that for a simple scenario this interaction is chaotic in nature and has large variability in dynamical behavior over orders of magnitude changes in parameter range as demonstrated by bifurcation diagrams. We conclude with numerical simulation evidence that chaotic behavior of protocols is inherent in their design which they inherit from their early vanilla TCP days, and it has serious implications for data-center throughput, load batching and collapse in Incast kind of scenario.

Classification of Colposcopic Cervigrams Using EMD in R

Communications in Computer and Information Science

Cervical cancer is one of the most common cancer among women worldwide which can be cured if dete... more Cervical cancer is one of the most common cancer among women worldwide which can be cured if detected early. The current gold standard for cervical cancer diagnosis is clumsy and time consuming because it relies heavily on the subjective knowledge of the medical professionals which often results in false negatives and false positives. To reduce time and operational complexities associated with early diagnosis, we require a portable interactive diagnostic tool for early detection, particularly in developing countries where cervical cancer incidence and related mortality is high. Incorporation of digital colposcopy in place of manual diagnosis for cervical cancer screening can increase the precision and strongly reduce the chances of error in a time-specific manner. Thus, we propose a robust and interactive colposcopic image analysis and diagnostic tool, which can categorically process colposcopic images into Type I, Type II and Type III cervigrams and identify lesions in least amount of time. Furthermore, successful binning of diagnosed cervigrams into digital colposcopic library and incorporation of a set of specific parameters that are typically referred to for identification of transformation zone and SCJ (squamo columnar junction) with the help of open source Programming language-"R" is one of the major highlights of the application. The software has the ability to automatically identify and quantify the morphological features, color intensity, sensitivity and other parameters digitally which may improve and accelerate screening and early diagnosis, ultimately leading to timely treatment of cervical cancer.

Hybrid CDN structure with a P2P based streaming protocol

ArXiv, 2010

Over the last decade, internet has seen an exponential increase in its growth.With more and more ... more Over the last decade, internet has seen an exponential increase in its growth.With more and more people using it, efficient data delivery over the internet has become a key issue. Peer-to-peer (P2P)/seed sharing based networks have several desirable features for content distribution, such as low costs, scalability, and fault tolerance. While the invention of each of such specialized systems has improved the user experience, some fundamental shortcomings of these systems have often been neglected. These shortcomings of content distribution systems have become severe bottlenecks in scalability of the internet.In order to combine the desired features of classical Content Distribution Networks (CDNs) and P2P/seed sharing based networks, we propose a hybrid CDN structure with a P2P/seed sharing based streaming protocol in the access network . In this work, we focus on the problem of data redundancy (at each node) and show how severely it impacts the network economics and the experience o...

An Application-oriented Model for Wireless Sensor Networks integrated with Telecom Infra

ArXiv, 2010

This paper aims to propose a significant way of remote access and real time monitoring of a parti... more This paper aims to propose a significant way of remote access and real time monitoring of a particular geographic area by integrating wireless sensor clouds with existing Telecom infrastructure and applications built around them through a gateway. This utility is very potent for environment monitoring in harsh and inaccessible places like mines, nuclear reactors, etc. We demonstrate a scaled down version of multi-hop network of wireless sensor nodes and its integration with existing telecom network infrastructure via a gateway.