Dr.M.V.S. Sairam
@gvpce.ac.in
Professor, ECE Department
Gayatri Vidya Parishad College of Engineering (Autonomous)
EDUCATION
B.E., M.E., Ph.D.
RESEARCH INTERESTS
Communication, RF Communications, Signal Processing, Medical Image Processing, OFDM
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
V. Harini, M. V. S. Sairam, and R. Madhu
Cambridge University Press (CUP)
AbstractA 16-element coplanar waveguide series fed hexagonal array antenna is proposed at millimeter-wave frequency range. In this paper, the analysis is initiated from a single-element hexagonal patch then extended to 1×2 array, 1×4 array, and 4×4 series fed hexagonal patch array antennas. The idea behind this design is to improve fractional bandwidth stage-wise with improved gain maintaining constant efficiency with all the structures. The 16-element array antenna is fabricated on Rogers RT Duriod 5880™substrate withɛr= 2.2 and 0.508 mm thickness. This array antenna exhibits low return loss at 28 GHz with a reflection coefficient value of −31.02 dB including almost 102% radiation efficiency and attained a maximum gain value of 8.98 dBi. The results are quite comparable with simulated 4×4 array antenna using the HFSS tool. The size of the proposed antenna is quite small which will be best suited for 5 G Femtobase stations to provide indoor communications at millimeter-wave frequencies.
Harini V, Sairam M V S, and Madhu R
IEEE
A dual-band hexagonal-shaped planar quad element millimeter-wave Multi-Input Multi-Output (MIMO) antenna is proposed for 5G femtocells applications. Initially, a hexagonal-shaped single element is designed and analysis is performed on Rogers R04003 ™ substrate with Er of 3.55 and & = 0.0027 with a thickness of substrate as 0.8mm. Later the single element is repeatedly placed on four sides of the substrate making a quad element MIMO antenna with four different ports. The Proposed antenna is radiating at 27.5GHz with a gain of 4.7 dBi at port1 and port3 and at port2 and port4, the antenna is radiating at dual bands like 28.5GHz and 38.5GHz with average gains of 4.69dBi and 5.5dBi. The antenna has a total efficiency of 95% with MIMO key performance metrics like envelope correlation coefficient and diversity gains as 0.045 and 9.995 at 10dB. Due to the lower perceptivity of tapping by unauthorized persons, MIMO antennas can be easily incorporated in 5G Femtocells.
P. Geetha Pavani, Birendra Biswal, M. V. S. Sairam, and N. Bala Subrahmanyam
Wiley
Tuberculosis (TB) is an infectious disease that primarily affects the lungs. If the TB is left undiagnosed in its early stage, it may affect other body parts leading to sudden death. A posterior anterior chest radiographs are used to diagnose pulmonary TB. This work presents a novel automatic system for the early detection of pulmonary TB. Initially, the Chan‐Vese active contour model is generated to segment the lung region from the preprocessed chest x‐rays. Different textural, statistical, and morphological features are extracted from the segmented lungs. Finally, the pertinent feature vector is considered for the classification of chest x‐rays using the Naïve Bayes classifier (NBC). The NBC is trained using 10‐fold cross validation technique. The proposed method achieves an average accuracy, the area under the curve, specificity, and sensitivity as 95.5%, 98%, 93.3%, and 94.6% respectively, when tested on different available datasets. Comparison results reveals that the Naïve Bayes classifier outperforms than the multinomial Naïve Bayes classifier and Bernoulli's Naïve Bayes classifier in classifying the chest x‐rays into healthy and TB.
Harini V, Sairam M.V.S, and Madhu R
Wiley
Aamer Abdul Rahman, Birendra Biswal, Geetha Pavani P, Shazia Hasan, and M.V.S. Sairam
Elsevier BV
V. Harini, M. V. S Sairam, and R. Madhu
Springer Science and Business Media LLC
Geetha Pavani P, Birendra Biswal, M V S Sairam, and Pradyut Kumar Biswal
Institution of Engineering and Technology (IET)
In this article, an exclusive-disjunction-based detection of neovascularisation (NV), which is the formation of new blood vessels on the retinal surfaces, is presented. These vessels, being thin and fragile, get ruptured easily leading to permanent blindness. The proposed algorithm consists of two stages. In the first stage, the retinal images are classified into non-NV and NV using multi-scale convolutional neural network, while in the second stage, 13 relevant features are extracted from the vascular map of NV images to achieve the pixel locations of new blood vessels using a directional matched filter along with the Difference of Laplacian of Gaussian operator followed by an exclusive disjunction function with adaptive thresholding of the vascular map. At the same time, the pixel locations of optic disc (OD) are detected using intensity distribution and variations on the retinal images. Finally, the pixel locations of both new blood vessels and OD are compared for classification. If the pixel locations of new blood vessels fall inside the OD, they are labelled as NV on OD, else they are labelled as NV elsewhere. The proposed algorithm has achieved an accuracy of 99.5%, specificity of 97.5%, sensitivity of 98.9%, and area under the curve of 94.2% when tested on 155 non-NV and 115 NV images.
Birendra Biswal, Eadara Vyshnavi, Metta Venkata Satya Sairam, and Pravat Kumar Rout
Institution of Engineering and Technology (IET)
Glaucoma leads to irreversible blindness and its diagnosis relies heavily on cup to disc ratio. This ratio can be calculated by segmenting the optic disc (OD) and optic cup (OC) from the fundus image. However, the segmentation of OD and OC is a complex process and should be carried out with utmost accuracy to screen the risk of glaucoma. In order to circumvent this complexity, this study presents two novel algorithms to segment the OD and OC boundaries, respectively by creating an automated region of interest (ROI). The first algorithm uses the inverse polar transform to segment OD where the horizontal coefficients of sixth level decomposition Daubechies stationary wavelet transform of ROI is processed. The second algorithm uses maximum vessel pixel sum to extract the complete OC region by extending the partial cup edges to the nasal side of the cup boundary. This approach covers the region under central retinal blood vessels also which were missing in earlier research. The proposed algorithms achieved an accuracy rate up to 99.70% for OD and 99.47% for OC segmentation, respectively even under severe retinal pathological conditions.
V. Harini, M. V. S. Sairam, and R. Madhu
Springer International Publishing
V Harini, M V S Sairam, and R Madhu
IEEE
A study on the performance of pentagon shaped millimeter wave antenna at various feed positions for 5G Femtocells applications is presented in this paper. Pentagon Antenna is an equilateral shape with all sides of dimensions 1.4mm. Rogers's RT duriod 5870 substrate with thickness (0.02″) 0.508mm and dielectric constant 2.33 is used. With this substrate a high gain antennas are achieved with good return loss and efficiency. Parametric analysis is done at various feed positions and at one particular position a 38GHz resonating frequency is achieved with relatively return loss of −21.24dB and high gain of 5.43dB which can be used as millimeter wave band for 5G communications. A detailed analysis at other feed positions is also presented with performance metrics like reflection coefficient, gain, and radiation pattern at each and every frequency based on simulation results.
Birendra Biswal, Prakash Kumar Karn, M.V.S. Sairam, and B. Rupa Surekhabolli
Wiley
A new approach to Hilbert energy spectrum and pattern recognition of nonstationary power signals is presented in this paper. In the proposed work, visual localization, detection, and classification of nonstationary power signals are achieved using Hilbert transform (HT)–based adaptive local iterative filter (ALIF). The HT is applied on all the intrinsic mode functions that are obtained from both empirical mode decomposition (EMD) and ALIF to extract instantaneous amplitude and frequency components. The instantaneous Hilbert energy spectrum results in clear visual detection, localization, and classification of the different power signal disturbances. The visual energy spectrum by Hilbert‐Huang Transform (HHT) on ALIF showing a better result than HHT applied on EMD. The feature vectors are extracted from the Hilbert energy spectrum for automatic pattern recognition of various nonstationary signals using a traditional fuzzy C‐means algorithm (FCMA). Finally, the center of the cluster is further optimized using fuzzy C‐means–based adaptive cuckoo search algorithm. The average classification accuracy of the disturbances is 91.25% and 99.25% using fuzzy C‐means and adaptive cuckoo search–based FCMA, respectively.
M. V. S. Sairam, Shaik Riyaz, R. Madhu, and V. Harini
Springer Science and Business Media LLC
Metta Sairam, , Mupparaju Sivaparvathi, and
The Intelligent Networks and Systems Society
Radio spectrum (3 KHz to 300 GHz) is a limited natural resource and efficient utilization of the spectrum can be accomplished by cognitive radio (CR). In CR, spectrum sensing is one of the significant challenging issues. Cooperative spectrum sensing (CSS) based CR is a captivating solution to enhance spectrum sensing. In CSS, multiple secondary users (SUs) report their results to fusion center (FC) and final decision is taken on the status of the primary user (PU) based on the predetermined fusion rule. This cooperative decision in CSS based CR, improves the spectrum sensing performance. Nevertheless, the foremost drawback in CSS is low throughput due to reporting time introduced by the multiple SUs. We propose a novel method to reduce the reporting time so as to enhance the throughput performance for the same number of SUs in CSS based CR. In the proposed scheme k SUs, where k is even, are divided into two groups, each with k/2 users. Two groups report their sensing results to two FCs separately and final decision is taken by the third FC. Consequently, the reporting time is condensed in the proposed scheme. The sensing performance of the proposed CSS (PCSS) for all possible fusion rules is reviewed. Analytical expressions for probability of false alarm, probability of detection and throughput are derived for PCSS. Both simulation results and theoretical analyses validate that PCSS improves throughput significantly when compared with CSS.
R. Chandrasekhar, M. Kamaraju, M.V.S. Sairam, and G.Tirumala Rao
IEEE
Key challenges for future wireless communications (4G) are bandwidth efficient system which provides high data rate with lower bit error rate and it also eliminate the multipath fading. MIMO-OFDM technology is the promising technique to provide high data rate with lower bit error rate and also improves the channel capacity under multipath fading environment. But the main drawback of OFDM system is high peak-to-average power ratio (PAPR), whenever all the orthogonal signals are added at a maximum point the resultant peak power will be increased. Several techniques are proposed to reduce PAPR viz. Coding, Interleaving, selected level mapping, partial transmit sequence, tone reservation. In this paper Unitary matrix precoding with companding technique is proposed to reduce PAPR. Simulations are performed by using MATLAB tool; results are analyzed for different systems (uncoded, precoding, companding and precoding with companding). Results demonstrate that unitary matrix precoding with companding technique is an efficient technique to reduce PAPR by maintaining optimum BER.
GV. Krishna Kumar, M. Padmanabam, M. Bhagya Sree, and M.V.S. Sairam
IEEE
Performance evaluation of passive devices such as ship board sonars, sea bed arrays, sonobuoys and underwater mines is carried out using simulated Radiated Noise (RN) signature of marine vessels such as surface ships, submarines, high speed boats, torpedoes etc, RN signature simulators developed so far have only been able to simulate static features of RN signature such as tonal components superimposed on the broad band propeller cavitation noise, ignoring the dynamic features imposed by the environment and Doppler imposed by source receiver motions. The time domain RN signature simulation model proposed in the current paper takes care of all the environment factors, multipath imposed by boundaries and Doppler due to source receiver motion. The model was developed and implemented in MATLAB®. The simulated data has exhibited the dynamic features such as multipath and Doppler on RN signature which are important for evaluating the passive devices.