beena bethel - Academia.edu (original) (raw)

Papers by beena bethel

LOW RADIOACTIVITY TECHNIQUES 2022 (LRT 2022): Proceedings of the 8th International Workshop on Low Radioactivity Techniques

2023 International Conference on Sustainable Computing and Data Communication Systems (ICSCDS)

Security and Communication Networks

Medical image analysis technology based on deep learning has played an important role in computer... more Medical image analysis technology based on deep learning has played an important role in computer-aided disease diagnosis and treatment. Classification accuracy has always been the primary goal pursued by researchers. However, the image transmission process also faces the problems of limited wireless ad-hoc network (WAN) bandwidth and increased security risks. Moreover, when user data are exposed to unauthorized users, platforms can easily leak personal privacy. Aiming at the abovementioned problems, a system model and an access control scheme for the collaborative analysis of the diagnosis of diabetic retinopathy (DR) are constructed in this paper. The system model includes two stages of data cleaning and lesion classification. In the data cleaning phase, the private cloud writes the model obtained after training into the blockchain, and other private clouds use the best-performing model on the chain to identify the image quality when cleaning data and pass the high-quality image t...

Malignant growth is the most widely recognized repulsive infections winning around the world, and... more Malignant growth is the most widely recognized repulsive infections winning around the world, and the patients with disease are saved just when the malignant growth is distinguished at the beginning phase. Each kind of disease is interesting, with its own arrangement of development properties and hereditary changes. This paper presents the lung knob division and disease characterization by proposing an enhancement calculation. The general technique of the created approach includes four stages, such as pre-processing, division, highlight extraction, and the order. From the outset, the CT picture of the lung is taken care of to the division. When the division is done, the highlights are extricated through morphological and measurable and surface highlights like LOOP and LGP. At long last, the extricated highlights are given to the order step. Here, the characterization is done dependent on the Deep Belief Network (DBN) which is prepared by utilizing the proposed Chicken-Sine Cosine Al...

2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)

In this paper there is comparison of four different machine learning algorithms such as Convoluti... more In this paper there is comparison of four different machine learning algorithms such as Convolutional Neural Network (CNN), Recurrent Neural Network (RNN), Fuzzy logic and Genetic algorithm on Wisconsin Breast Cancer Diagnosis (WBCD) dataset for the detection of breast cancer in women. The test accuracies are compared to show the efficient algorithm for the detection of breast cancer using those algorithms. The dataset is partitioned to 70% training data and 30% testing data. The results for the applied algorithms are CNN acquired 96.49% accuracy, RNN acquired 63.15% accuracy, fuzzy logic acquired 88.81% accuracy, and genetic algorithm acquired 80.399% accuracy.

Advances in Computational Intelligence and Informatics, 2020

Image denoising is an important preprocessing step done with MRI images to remove various kinds o... more Image denoising is an important preprocessing step done with MRI images to remove various kinds of noise like speckle noise, Gaussian noise, pepper and salt noise, etc. Some filtering mechanisms have been eliminating the required parts of the image along with the noisy pixels of the image, a phenomenon called over-filtering. Anisotropic diffusion is a denoising technique having an iterative process that computes a set of functions to acquire a good degree of smoothening without loss of actual contents of the images. A filtering technique using anisotropic diffusion and application of fuzzy logic has been presented in this paper as it has given a better sharpness of the image, with a good PSNR while it was simulated over 33 MRI cardiac images.

2017 International Conference on Current Trends in Computer, Electrical, Electronics and Communication (CTCEEC), 2017

Heart disease is the most prevalent kind of disease even among the young people, which has logged... more Heart disease is the most prevalent kind of disease even among the young people, which has logged the maximum number of lives so far. Earlier it was a disease which claimed people above 50 years of age, but as of now it has it is consuming even the lives of small children with congenital heart diseases. This part of the work also has focused on the cardiac MRI images related to congenital disorders among children in the age group of 2 years to 17 years of age. Medical image enhancement technique is the need of the hour for quick and accurate diagnosis of heart ailments and for medical intervention to take over accordingly. In this paper we focused more on the morphological operations in continuation of our research work in our earlier paper. Different morphological operations were tried over the pre-processed images and the experimental results showed that the opening operation gave a least error measure of all. Various error estimates over these operations were taken, like MSE, RMSE, MAE, etc. were calculated for all MR images and was found the opening operation had a less error compared to other operations, which implies that opened images have more clarity than the other operations.

Successful use of EHR enhances develop patient security and worth of care, yet it have the essent... more Successful use of EHR enhances develop patient security and worth of care, yet it have the essential of interoperability among HIE at various hospitals. Poorly, hospitals are not intrigued to receive interoperable HIS on account of its arrangement cost with the exception of in modest handful countries. An matter emerge despite when additional hospitals begin utilizing the CDA record design on the evidence that the information spread in various reports is tough to man generation. CDA report generation and incorporation Open API benefit in light of distributed computing is depicted through which hospitals are permitted to advantage to create CDA report with no buying exclusive programming. CDA record incorporation framework coordinates dissimilar CDA reports per understanding into a lone CDA report along with specialist and patients may check the clinical information in sequential request. Usage of CDA report generation and reconciliation depends on cloud computing with the administra...

Cardiac MRI (Magnetic Resonance Imaging), is a non-invasive technique in the field of medical ima... more Cardiac MRI (Magnetic Resonance Imaging), is a non-invasive technique in the field of medical imaging technology for assessing the heart function and also to diagnose and analyse the morphological features of the cardiovascular system of a human heart. It gives a clear picture of heart’s chambers and valves, without the patient having to undergo cardiac catheterization for most cases. Analysing the functionality of heart and diagnosing its varieties of ailments at the right time without causing any punctures is a challenge in today’s medical community. Locating the exact region of ailment or interest, especially in a sensitive organ such as heart is quite cumbersome even with the help of imaging techniques. Application of Image pre-processing techniques to reduce noise in the heart MRI images apart from enhancement of the MRI images and further followed by segmentation methods in order to locate the problem area in the heart will be a boon to the Cardiologist / Cardio Surgeon to car...

Inventive Computation Technologies, 2019

Cloud computing is a revolt processing chisel in which important of the registering correspondenc... more Cloud computing is a revolt processing chisel in which important of the registering correspondences are given as administrations over the Internet. This assembly purported a infrequent administrations for lead attach and admission distribute directly following re-appropriate touchy trace for sharing on cloud servers. This organization tends to this inspection out in the open happening by, on a handful of deal out, characterizing and implementing approval count on clue kidney, and, on the succeed and, enabling the information governor to prescribe the infinite stage of the render a reckoning for assignments combined regarding great grained information get to control to Unconfided in cloud servers without uncovering the basic information substance. Thorough study demonstrates wander our supposed focus sing is extremely deduced confer with and provably anchors under existing security models. Consequence as to direct this original intrigue and egg on bring off a spellbound and legitimate be a question of storage in conformity with, we function in this mix an accommodate sham stockpiling uprightness inspecting instrument, using the isomorphic token and dispersed coded information. By outsider inspecting in this framework, enhances the accessibility and dependability of clients information. This paper successfully underpins dynamic information tasks. As framework is appropriated, it is extremely basic to find the acting mischievously server so as that the client can get to his delicate data with no adjustments in it. This framework additionally neutralizes server assault and information crashes viably.

A Co-clustering approach for heart disease analysis using a weight based approach is presented. T... more A Co-clustering approach for heart disease analysis using a weight based approach is presented. Towards the performance improvement in database mining, co-clustering approaches were used to minimize the search overhead. For the co-clustering of data, information based co-clustering (ITCC) has been used as an optimal means of clustering. However, in this co-clustering approach, elements are clustered based on Bregman divergence criterion, following the convergence of Bregman Index optimization using Euclidean distance (ED) approach. The ED approach works over the magnitude values of the elements, without consideration of the data relations. In many applications, relationship between elements played a significant role in making decision. In this paper, a relation oriented co-clustering logic following weight allocation process is presented. The proposed Weighted ITCC (W-ITCC) method/technique is applied over Cleveland data set for heart disease analysis to do performance comparisons.

E3S Web of Conferences, 2021

This survey paper is used to discuss about the detection of breast cancer tissues using different... more This survey paper is used to discuss about the detection of breast cancer tissues using different machine learning algorithms. Identification of cancers using scanned images are very important for correct diagnosis. Many algorithms are present for detection of cancer using image processing techniques, all these algorithms have the main goal of detecting those cell tissues. Each algorithm has their own assumptions and advantages, here is a review of some of those algorithms for breast cancer detection. This paper highlights the algorithms and their assumptions of the prior published papers.

International Journal of Computer Applications, Sep 15, 2016

A Hybrid cloud is a concrescence of public plus private clouds bound together by either standardi... more A Hybrid cloud is a concrescence of public plus private clouds bound together by either standardized or proprietorship technology that changes information plus diligence immovableness. Proposed system aiming to expeditiously resolving yequandary from deduplication on differential favors in remote location computing. A hybrid remote location structure lying of a populace remote location plus a person removed location plus ye information owners simply source their information storage by using world cloud while ye information operation is managed in private cloud. To build information management measurability in cloud computing, de-duplication has been an identical well-kenned technique recently is use. Deduplication dilutes your bandwidth requirements, hastens the data transfers, and it keeps your cloud storage needs to a minimum. Proposed system demonstrates several nascent deduplication formulas fortifying approved duplicate assure inside hybrid remote location structure. To hold ye privacy of information ye convergent encoding proficiency holds made up used to encrypt ye information afore source. Approved deduplication system support differential sanction duplicate check. As a proof of conception, a prototype is implemented in approved duplicate check scheme and conduct test bed experiments utilizing prototype, approved duplicate check scheme incurs minimal overhead compared to mundane operations.

2014 First International Conference on Networks & Soft Computing (ICNSC2014), 2014

Digital camera needs fixed bit rate. In this paper image compression is done using slant transfor... more Digital camera needs fixed bit rate. In this paper image compression is done using slant transform exploiting the characteristics of Human Visual System (HVS). Normally JPEG compressors support variable bit error rate. The error rate range in this compressor is found to be around -50 to 50. The error rate is reduced to around -0.6 to 1 using fuzzy logic. The input parameters for fuzzy logic are obtained by encoding bit rate and bit error rate. By framing rules the adaptive gain in quantization matrix of compressor is adjusted so that a fixed bit rate is achieved at different quality factors.

IEEE Transactions on Knowledge and Data Engineering, 2015

Microaggregation is a technique for disclosure limitation aimed at protecting the privacy of data... more Microaggregation is a technique for disclosure limitation aimed at protecting the privacy of data subjects in microdata releases. It has been used as an alternative to generalization and suppression to generate k-anonymous data sets, where the identity of each subject is hidden within a group of k subjects. Unlike generalization, microaggregation perturbs the data and this additional masking freedom allows improving data utility in several ways, such as increasing data granularity, reducing the impact of outliers and avoiding discretization of numerical data. k-Anonymity, on the other side, does not protect against attribute disclosure, which occurs if the variability of the confidential values in a group of k subjects is too small. To address this issue, several refinements of k-anonymity have been proposed, among which t-closeness stands out as providing one of the strictest privacy guarantees. Existing algorithms to generate t-close data sets are based on generalization and suppression (they are extensions of k-anonymization algorithms based on the same principles). This paper proposes and shows how to use microaggregation to generate k-anonymous t-close data sets. The advantages of microaggregation are analyzed, and then several microaggregation algorithms for k-anonymous t-closeness are presented and empirically evaluated.

International Journal of Computer Applications, 2016

Heart Disease Dataset (HDD) contains high dimensions which poses challenges to research community... more Heart Disease Dataset (HDD) contains high dimensions which poses challenges to research community in terms of complexity and efficient analysis. Heart disease is also called as cardiovascular disease (CVD). Feature selection will be made to reduce the irrelevant and redundant number of attributes. Fast diagnosis of the heart disease can be done using a knowledge driven approach. A comparison was made for medically important features to that of computerized subset of features, to bring out much simpler set of features used for the diagnosis. It focuses on the experts' judgement for medical driven feature selection process termed as MFS, and the performance of various classifiers on Cleveland dataset for the computerized feature selection termed as CFS and also a combination of both to enhance the prediction accuracy. Further, this paper categorizes the MFS, CFS and the combination of both into discrete and continuous sets of attributes. Our work has proved that the discrete features do not contribute much to the classification as do the continuous ones, in its accuracy, speed and performance.