Velagapudi Ramakrishna Siddhartha Engineering College

About: Velagapudi Ramakrishna Siddhartha Engineering College is a based out in . It is known for research contribution in the topics: Computer science & Antenna (radio). The organization has 1307 authors who have published 1155 publications receiving 6163 citations.

A compact O-shaped printed ACS fed monopole dual-band antenna for 2.4GHz Bluetooth and 5GHz WLAN/WiMAX applications

Abstract: In this research paper, a compact, novel O-shaped ACS fed dual-band monopole antenna for 2.4 GHz Bluetooth/WLAN, 4.9 GHz US public safety band and 5.0 GHz WLAN/WiMAX applications is presented and investigated. The proposed geometry consists of an O-shaped radiating branch, monopole-shaped radiating branch and a rectangular shaped uniplanar ground plane, which occupies an overall size of 20 × 12.5 × 1.6mm3. In the design, proposed radiating structure has been printed on a low cost single layred substrate FR4. By properly tuning the radiating branches electrical lengths, two independent resonant frequencies can be obtained and tuned independently. The presented antenna also exhibits omnidirectional radiation patterns with acceptable peak gains for the desired of 2.4 GHz bluetooth band, 4.9 GHz US public band, 2.4/5.2/5.8 GHz WLAN bands and 5.5 GHz WiMAX band applications.

Adaptive Diagnosis of Lung Cancer by Deep Learning Classification Using Wilcoxon Gain and Generator.

Abstract: Cancer is a complicated worldwide health issue with an increasing death rate in recent years. With the swift blooming of the high throughput technology and several machine learning methods that have unfolded in recent years, progress in cancer disease diagnosis has been made based on subset features, providing awareness of the efficient and precise disease diagnosis. Hence, progressive machine learning techniques that can, fortunately, differentiate lung cancer patients from healthy persons are of great concern. This paper proposes a novel Wilcoxon Signed-Rank Gain Preprocessing combined with Generative Deep Learning called Wilcoxon Signed Generative Deep Learning (WS-GDL) method for lung cancer disease diagnosis. Firstly, test significance analysis and information gain eliminate redundant and irrelevant attributes and extract many informative and significant attributes. Then, using a generator function, the Generative Deep Learning method is used to learn the deep features. Finally, a minimax game (i.e., minimizing error with maximum accuracy) is proposed to diagnose the disease. Numerical experiments on the Thoracic Surgery Data Set are used to test the WS-GDL method's disease diagnosis performance. The WS-GDL approach may create relevant and significant attributes and adaptively diagnose the disease by selecting optimal learning model parameters. Quantitative experimental results show that the WS-GDL method achieves better diagnosis performance and higher computing efficiency in computational time, computational complexity, and false-positive rate compared to state-of-the-art approaches.

Excess thermo dynamical parameters of binary mixtures of toluene and mesitylene with anisaldehyde using ultrasonic technique at different temperatures

Abstract: The densities, viscosities, and ultrasonic velocities of the binary mixture of toluene and mesitylene with anisaldehyde have been measured at 303.15, 308.15, 313.15, and 318.15 K for the entire range of mole fraction of anisaldehyde. From the data the excess adiabatic compressibility (β E), excess free volume (V f E ), excess internal pressure (π E), excess enthalpy (H E), and excess Gibb’s free energy of activation of flow (G* E) for the binary mixture over the additive values were calculated. In light of these parameters molecular interactions involved between the component liquids have been discussed.

ECG Based Heart Arrhythmia Detection Using Wavelet Coherence and Bat Algorithm

Abstract: Atrial fibrillation (AF) is a type of heart abnormality, during the AF electrical discharges in the atrium are rapid, results in abnormal heart beat. The morphology of ECG changes due to the abnormalities in the heart. This paper consists of three major steps for the detection of heart diseases: signal pre-processing, feature extraction and classification. Feature extraction is the key process in detecting the heart abnormality. Most of the ECG detection systems depend on the time domain features for cardiac signal classification. In this paper we proposed a wavelet coherence (WTC) technique for ECG signal analysis. The WTC calculates the similarity between two waveforms in frequency domain. Parameters extracted from WTC function is used as the features of the ECG signal. These features are optimized using Bat algorithm. The Levenberg Marquardt neural network classifier is used to classify the optimized features. The performance of the classifier can be improved with the optimized features.

Cell Coverage Area and Link Budget Calculations in LTE System

Abstract: The network planning is a significant step in establishment of wireless communication system. For a wireless system the primary setup takes a lot of time for process and also very expensive. Because of this reason it uses a mathematical model before the processing of the system to avoid unknown expenses. The mathematical model calculation mainly includes path loss, link budgets etc. Radio propagation is site specific and it varies substantially depending on geography, frequency at which system will operate mobile terminal speed, interface sources and other dynamic factors. To estimate the signal coverage and to achieve a high data rates, it is very important to illustrate the radio channel through important parameters and with the help of a mathematical model. In this paper we have evaluated the cell coverage area for Long Term Evolution (LTE) technology at 1800 MHz (FDD-LTE) theoretically for different transmitting antenna heights and at different transmitting power levels. This coverage area is then compared with the practical measured coverage area i.e. practical measured path loss. The signal coverage starts within the cell, by predicting the affecting parameters on the signal power level in the uplink and downlink at the practical cases. In this paper the concentration is completely on preprocess of network planning i.e. link budgeting of LTE cellular system. This investigation can also lead the radio planner to a thorough understanding of radio wave propagation for designing mobile communication system.