R. Ramya

Dhanalakshmi Srinivasan Group of Institutions

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K. Srinivasan

Vels University

K. Priya Dharshini

L.M. Patnaik

National Institute of Advanced Studies

R. Ananda Natarajan

Mahendra Institute of Management and Technical Studies

Dhananjay Kumar

Anna University, Chennai

Hema A. Murthy

Indian Institute of Technology Madras

G. Saravanakumar

Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology

D. Sejal

Visvesvaraya Technological University

V. Arthi

Christian Medical College & Hospital

S. Mahalaxmi

Anna University, Chennai

Cooperative Institutions

Anna University, Chennai

Visvesvaraya Technological University

Sathyabama Institute of Science and Technology

Saveetha University

Bangalore University

Indian Institute of Science Bangalore

Amrita Vishwa Vidyapeetham

SRM Institute of Science and Technology

Vellore Institute of Technology University

Dhanalakshmi Srinivasan Group of Institutions

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Automatic Skin Cancer Segmentation and Classification using Fuzzy C-means Clustering-based Convolutional Neural Network

R. Ramya Mohammad Yahya Myasar Mundher Adnan R Archana Reddy J. Velumani

Skin cancer is treated as one of the primary types of disease in the human body which is caused by the radiation of ultraviolet from the sun. However, manual segmentation and classification of skin cancer is extremely difficult and time-consuming due to visual variations in skin lesions. In this research, the Fuzzy C-means Clustering-based Convolutional Neural Network (FCM-CNN) is proposed for the automatic segmentation and classification of skin cancer using deep learning. Initially, the data is obtained by the ISIC-2017 dataset, and then pre-processing is performed using a Top hat filter and inpainting approach. The FCM approach is used to segment the given pre-processed image. The Local Ternary Pattern (LTP) and Local Vector Pattern (LVP) are used to extract the appropriate features. Finally, the CNN classification is utilized to classify skin cancer as malignant or benign. When compared with the existing methods, the proposed FCM-CNN achieves a better accuracy of 99.75% respectively.

10.1109/iciics59993.2023.10420899

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Multimedia Transmission over Wireless LANs

K. Kathiravan R. Ramya Tinu Sara Titus

Wireless LAN technology has shown to be a revolutionary development during the last few decades. In order to deal robustly with the unreliable wireless nature, the 802.11 medium access control protocol has a relatively large overhead and hence, the throughput performance is much worse than the underlying physical layer rate. Moreover, along with many emerging applications and services over WLANs, the demand for faster and higher capacity WLANs has been growing recently. In this paper, a new MAC protocol, Aggregated MAC scheme (AMAC), is proposed wherein, multiple packets are aggregated into and transmitted in a single large frame in order to reduce the overhead. In the Network Layer, a routing protocol, MRTP (Multimedia Route Repair Routing Protocol), is proposed to find reliable links and to provide an efficient route repair mechanism. The implementation of these protocols reduces the number of Access Points required in the network.

Zone Routing Protocol

10.1109/cicsyn.2009.37

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Security Based Novel Context Aware Mobile Computing Scheme Via Crowdsourcing

International Journal of Scientific Research in Science Engineering and Technology (2017)

S. Usharani R. Ramya

Crowdsourcing

10.32628/ijsrset173219

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Secured Identity Based Routing and privacy preservation in Wireless Mesh Networks

R. Ramya T. M. Navamani P. Yogesh

Wireless Mesh Networks (WMNs) have been expected to be the ultimate solution for the next decade wireless networking. The attractions of WMNs include easy set-up on the fly, off-the-shelf cost, flexible interoperability with other networks, and highly reliable connectivity. One main challenge in the design of these networks is their vulnerability to security attacks. The attacker will possibly be able to identify an ongoing communication session between any two network users by analyzing the network traffic pattern without knowing the user's identity information. To address these security risks, we propose a Secured Identity Based Routing (SIBR) scheme in which every node is assigned with the security cards for efficient authentication. The major goal of the proposed system is to reduce the number of levels at which an attack can take place by providing anonymity in routing. Our implementation results show that the proposed scheme increases the overall performance of the network substantially. Such a routing scheme enhances the privacy preservation of the end users. Our approach also protects against performance degradation even in the presence of malicious behavior.

10.1109/icrtit.2011.5972396

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Smart Bin For Waste Management System

S. S. Sreejith R. Ramya R. Roja Aman Kumar

This paper entitled "Smart Bin for Waste Management System" plays a vital role in the waste management system. A healthy domain is essential to a solid and cheerful environment. Clean and hygienic environments are a key need in human habitable environments. Smart bin is to develop a gainful and dynamic waste administration framework. In public places, dustbins are being flooded just as the waste spills out bringing about contamination. This likewise expands number of infections as huge number of bugs to breed on it. In this a smart bin is developed to monitor the level of waste, automatic disposing of waste and rain detection system. The outcome demonstrated that the detecting framework is effective and savvy and can be utilized to robotize any solid waste bin management process.

10.1109/icaccs.2019.8728531

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An Adaptive Segmentation Method Based on Gaussian Mixture Model (GMM) Clustering for DNA Microarray

M. Parthasarathy R. Ramya A. Vijaya

Microarray allows us to efficiently analyse valuable gene expression data. In this paper we propose a effective methodology for analysis of microarrays. Earlier a new gridding algorithm is proposed to address all individual spots and to determine their borders. Then, a classical Gaussian Mixture Model (GMM) is used to analyse array spots more flexibly and adaptively. The Expectation Maximization (EM) algorithm is used to estimate GMM parameters by Maximum Likelihood (ML) approach. In this paper, we also addressing the problem of artifacts by detecting and compensate using GMM mixture components and artifacts data present in foreground and background spots are corrected by performing mathematical morphology and histogram analysis methods.

Spots

Mixture theory

10.1109/icica.2014.24

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Prediction and Classification of Breast Cancer Using Discriminative Learning Models and Techniques

M. Pavithra R. Rajmohan T. Ananth Kumar R. Ramya

Mammography is a specialized clinical two imaging that makes use of two lowdose X-ray two gadgets to observe the typology of breast cancer. A mammogram is a mammography examination document that helps in the detection and analysis of breast illnesses in girls at an early stage. This challenge proposes to classify mammography breast scans into their respective training and makes use of interest mastering to localize the unique pixels of malignancy. The use of overlay convolutional neural networks allows characteristic extraction from the mammography scans which is thereafter fed into a recurrent neural community. Mammography pictures are equalized, more advantageous, and augmented earlier than extracting the elements and assigning weights to them as a section of the information preprocessing procedures. This process would in actuality assist in tumor localization in case of breast cancers. In this work, the breast cancer can be detected using low-level preprocessing techniques and Image segmentation. In Image segmentation, the thresholding technique and RCNN algorithm are compared using Binarization.

Discriminative model

Digital Mammography

10.1002/9781119786122.ch12

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A State-of-Art Load Balancing Algorithms in Cloud Computing

International Journal of Computer Applications (2014)

R. Ramya M. Kriushanth L. Arockiam

Cloud Computing is the ultimate technology in internet.It is a means of acquiring computing possessions, making do and delivering software and services.Cloud Computing allows the customers to apply the application without set up and access their own files on any device with internet.Cloud services can be acquired at any time.The cloud service providers have developed enough to provide services to an ever growing number of users.Sudden peak situation the load balancing mechanism helps to send the requests to the available resources.In this report, we introduce an overview of load balancing and load balancing algorithm.

10.5120/16701-6834

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Automatic tuberculosis screening using canny Edge detection method

2015 2nd International Conference on Electronics and Communication Systems (ICECS) (2015)

R. Ramya P Babu

Tuberculosis is a major health threat in many regions of the world. When left undiagnosed and consequently untreated, death rates of patients with tuberculosis are high. We first extract the lung region using a lung nodule Edge detection method. For this lung region, we compute a set of texture and shape features, which enable the x-rays to be classified as normal or abnormal using a binary classifier. Edge detection, especially step edge detection has been widely applied in various different computer vision systems, which is an important technique to extract useful structural information from different vision objects and dramatically reduce the amount of data to be processed. John has found that, the requirements for the application of edge detection on diverse vision systems are relatively the same. Thus, a development of edge detection solution to address these requirements can be implemented in a wide range of situations. The general criteria for edge detection includes detection of edge with low error rate, which means that the detection should accurately catch as many edges.

Canny edge detector

Deriche edge detector

Word error rate

10.1109/ecs.2015.7124909

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Citations (20)

Regional transport services through smart governance using bigdata

International journal of advance research, ideas and innovations in technology (2019)

R. Ramya K H Asha Navyashree V. Shetty M V Meghana Bhukya Manasa

Smart Governance is the process of utilizing modern technology to create a transparent and sustainable environment for citizens and the government. Intelligence through smart governance is utilized to upgrade decision making through a better collaboration including government and citizens by utilizing heterogeneous techniques and technology through smart governance. Transportation is being the vital concern for enormous countries like India, Bangladesh, Nepal etc; where the vehicles are increasing in big numbers which include variety of vehicles like two-wheelers, cars and heavy vehicles where all the vehicles have to get registered at Regional Transport Office(RTO) which are situated all over the country in various states. The motive of this paper is to store an enormous range of vehicle data and extract the information in a smart and efficient manner by utilizing the Big data technology.

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Smart City

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