Diagnosis of Alzheimer’s Disease using Wrapper Feature Selection Method

Vyshnavi Ramineni,권구락 (사)한국스마트미디어학회 2023 스마트미디어저널 Vol.12 No.3

Alzheimer’s disease (AD) symptoms are being treated by early diagnosis, where we can only slow the symptoms and research is still undergoing. In consideration, using T1-weighted images several classification models are proposed in Machine learning to identify AD. In this paper, we consider the improvised feature selection, to reduce the complexity by using wrapping techniques and Restricted Boltzmann Machine (RBM). This present work used the subcortical and cortical features of 278 subjects from the ADNI dataset to identify AD and sMRI. Multi-class classification is used for the experiment i.e., AD, EMCI, LMCI, HC. The proposed feature selection consists of Forward feature selection, Backward feature selection, and Combined PCA & RBM. Forward and backward feature selection methods use an iterative method starting being no features in the forward feature selection and backward feature selection with all features included in the technique. PCA is used to reduce the dimensions and RBM is used to select the best feature without interpreting the features. We have compared the three models with PCA to analysis. The following experiment shows that combined PCA &RBM, and backward feature selection give the best accuracy with respective classification model RF i.e., 88.65, 88.56% respectively.

A Comparative Study of the CNN Model for AD Diagnosis

Vyshnavi Ramineni,권구락 (사)한국스마트미디어학회 2023 스마트미디어저널 Vol.12 No.7

Alzheimer’s disease is one type of dementia, the symptoms can be treated by detecting the disease at its early stages. Recently, many computer-aided diagnosis using magnetic resonance image(MRI) have shown a good results in the classification of AD. Taken these MRI images and feed to Free surfer software to extra the features. In consideration, using T1-weighted images and classifying using the convolution neural network (CNN) model are proposed. In this paper, taking the subjects from ADNI of subcortical and cortical features of 190 subjects. Consider the study to reduce the complexity of the model by using the single layer in the Res-Net, VGG, and Alex Net. Multi-class classification is used to classify four different stages, CN, EMCI, LMCI, AD. The following experiment shows for respective classification Res-Net, VGG, and Alex Net with the best accuracy with VGG at 96%, Res-Net, GoogLeNet and Alex Net at 91%, 93% and 89% respectively.

Trust Predicated Routing Framework with Optimized Cluster Head Selection using Cuckoo Search Algorithm for MANET

Sekhar, J. Chandra,Prasad, Ramineni Sivarama The Institute of Electronics and Information Engin 2015 IEIE Transactions on Smart Processing & Computing Vol.4 No.2

This paper presents a Cuckoo search algorithm to secure adversaries misdirecting multi-hop routing in Mobile ad hoc networks (MANETs) using a robust Trust Predicated Routing Framework with an optimized cluster head selection. The clustering technique designed in this framework leads to efficient routing in MANETs. The heavy work load in the node causes an energy drop in cluster head, which leads to re-clustering of the group, and another cluster head is selected to avoid packet loss during data transmission. The problem in the re-clustering process is that the overall efficiency of the routing process is reduced and the processing time is increased. A Cuckoo search based optimization algorithm is proposed to solve the problem of re-clustering by selecting the secondary cluster head within the initially formed cluster group and eliminating the reclustering process. The proposed framework enables a node to select a reliable and secure route for MANET and the performance can be evaluated by comparing the simulated results with the AODV routing protocol, which shows that the performance of the proposed routing protocol are improved significantly.

MAC Layer Based Certificate Authentication for Multiple Certification Authority in MANET

Sekhar, J. Chandra,Prasad, Ramineni Sivarama The Institute of Electronics and Information Engin 2014 IEIE Transactions on Smart Processing & Computing Vol.3 No.5

In this study, a novel Randomly Shifted Certification Authority Authentication protocol was used in ad hoc networks to provide authentication by considering the MAC layer characteristics. The nodes achieve authentication through the use of public key certificates issued by a CA, which assures the certificate's ownership. As a part of providing key management, the active CA node transfers the image of the stored public keys to other idle CA nodes. Finally the current active CA randomly selects the ID of the available idle CA and shifts the CA ownership by transferring it. Revoking is done if any counterfeit or duplicate non CA node ID is found. Authentication and integrity is provided by preventing MAC control packets, and Enhanced Hash Message Authentication Code (EHMAC) can be used. Here EHMAC with various outputs is introduced in all control packets. When a node transmits a packet to a node with EHMAC, verification is conducted and the node replies with the transmitter address and EHMAC in the acknowledgement.

Starch Content and Cassava Mosaic Disease Genetic Diversity with Relation to Yield in South Indian Cassava (Manihot esculenta Crantz) Germplasm

Raghu Duraisamy,Senthil Natesan,Sakthi Ambothi Rathinasamy,Raveendran Muthurajan,Jana Jeevan Ramineni,Nageswari Karuppusamy,Pugalenthi Lakshmanan,Mohan Chokkappan,Karthikeyan Gandhi 한국작물학회 2011 Journal of crop science and biotechnology Vol.14 No.3

Cassava, family Euphorbiaceae, is the fifth most important staple food crop. The study of variability and diversity present in diverse cassava accessions maintained at the field genebank of TCRS, TNAU is essential to design the breeding program of cassava in TNAU. Hence, a study was carried out to assess the genetic diversity based on morphological traits and Simple Sequence Repeat (SSR) markers, identifying the SSR markers linked to a cassava mosaic disease-resistant QTL region. Genetic diversity among cassava germplasm accessions was estimated using 28 morphological traits and three SSR markers. The polymorphic information content (PIC) result gives high information for all the SSR markers. Morphological traits revealed 10 clusters and the SSR markers revealed 13 clusters at a similarity coefficient of 2.514 and 0.75, respectively. The SSR marker diversity revealed that the most promising clusters (II and XII) possessing accessions with yield attributing traits and cluster IX were grouped together due to low yield and CMD susceptibility. Morphological descriptors revealed variance for yield contributing traits. The first three principle components accounted for 10.8, 9.1, and 8.4%, respectively. Correlation studies showed significant correlation among yield and yield-attributing traits, which in turn influences yield. The morphological traits diversity reveals that cluster VI was the most promising cluster in which genotypes ME209 and ME460 possess higher yield and starch content with cassava mosaic disease (CMD) resistance. Most of the accessions grouped under cluster X belong to selection from International Centre for Tropical Agriculture (CIAT) collections and the cultivars under clusters I and II were true cassava seed (TCS) selections of India. The CMD-linked SSR marker which is reported in the previous studies have generated eight alleles and each were regressed with CMD resistance and resulted in non-significant linkage to CMD resistance.

Starch Content and Cassava Mosaic Disease Genetic Diversity with Relation to Yield in South Indian Cassava (Manihot esculenta Crantz) Germplasm

Duraisamy, Raghu,Rathinasamy, Sakthi Ambothi,Natesan, Senthil,Muthurajan, Raveendran,Ramineni, Jana Jeevan,Karuppusamy, Nageswari,Lakshmanan, Pugalenthi,Chokkappan, Mohan,Gandhi, Karthikeyan 한국작물학회 2011 Journal of crop science and biotechnology Vol.14 No.3

Cassava, family Euphorbiaceae, is the fifth most important staple food crop. The study of variability and diversity present in diverse cassava accessions maintained at the field genebank of TCRS, TNAU is essential to design the breeding program of cassava in TNAU. Hence, a study was carried out to assess the genetic diversity based on morphological traits and Simple Sequence Repeat (SSR) markers, identifying the SSR markers linked to a cassava mosaic disease-resistant QTL region. Genetic diversity among cassava germplasm accessions was estimated using 28 morphological traits and three SSR markers. The polymorphic information content (PIC) result gives high information for all the SSR markers. Morphological traits revealed 10 clusters and the SSR markers revealed 13 clusters at a similarity coefficient of 2.514 and 0.75, respectively. The SSR marker diversity revealed that the most promising clusters (II and XII) possessing accessions with yield attributing traits and cluster IX were grouped together due to low yield and CMD susceptibility. Morphological descriptors revealed variance for yield contributing traits. The first three principle components accounted for 10.8, 9.1, and 8.4%, respectively. Correlation studies showed significant correlation among yield and yield-attributing traits, which in turn influences yield. The morphological traits diversity reveals that cluster VI was the most promising cluster in which genotypes ME209 and ME460 possess higher yield and starch content with cassava mosaic disease (CMD) resistance. Most of the accessions grouped under cluster X belong to selection from International Centre for Tropical Agriculture (CIAT) collections and the cultivars under clusters I and II were true cassava seed (TCS) selections of India. The CMD-linked SSR marker which is reported in the previous studies have generated eight alleles and each were regressed with CMD resistance and resulted in non-significant linkage to CMD resistance

Clinical and immunological responses to COVID-19 vaccination in rheumatoid arthritis patients on disease modifying antirheumatic drugs: a cross-sectional study

( Madhavi Eerike ),( Vijaya Prasanna Parimi ),( Anand Pyati ),( Raja Sundaramurthy ),( Varadharajan Sakthivadivel ),( Aswini Bramarambika Pidugu ),( Bhavana Surapareddy ),( Naga Tejaswini Ramineni ),( 대한류마티스학회 2024 대한류마티스학회지 Vol.31 No.1

Objective: This study was conducted to investigate the immunological and clinical response to COVID-19 vaccination in rheumatoid arthritis (RA) patients receiving disease modifying antirheumatic drugs (DMARDs). Methods: A cross-sectional study was conducted among RA patients who received two doses of COVID-19 vaccine within 6 months to one year. Demographic information, comorbidities, vaccination details, and past COVID-19 infection details were collected. Hemoglobin (Hb), erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), and interleukin-6 (IL-6) levels were estimated. Disease Activity Score-28 (DAS-28) was calculated for RA patients. Anti-spike antibody (ASA) concentrations were measured, and compared with a healthy control population. Correlations of ASA with age, sex, disease parameters, medication use, and comorbidities were assessed. Results: A total of 103 RA patients and 185 controls were included in the study. RA patients had higher mean age, lower mean Hb, higher ESR, and elevated IL-6 levels. Both groups showed positive results for anti-spike antibodies, with a higher percentage in controls. Among RA patients majority had low DAS-28 score. The number of DMARDs used showed a negative correlation with antibody levels. There was a slight positive correlation between ASA concentration and DAS-28 score. Comorbidities did not significantly influence antibody concentration. No significant differences were found in antibody levels based on the type of COVID-19 vaccine or previous COVID-19 infection or booster dose vaccination among RA patients. Conclusion: The study revealed that RA patients showed a reduced antibody response following COVID-19 vaccination compared to the control group and potentially influenced by immunosuppressive treatments and disease-related factors.