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.

Metamaterial synthesis using a CAD model based on an evolutionary technique to improve the performance of TCAS antennas

Abstract: We propose a computer-aided design (CAD) model for synthesis of the unit cell of a metamaterial with the aim of improving the performance of a microstrip antenna designed for use in a traffic collision avoidance system (TCAS). Synthesis of electromagnetic (EM) devices generally requires great computational resources because of their inherent properties, e.g., being complex, nonconvex, and continuous. However, techniques based on soft computing are much more convenient for problems related to such EM devices. In this work, CAD models based on a genetic algorithm and differential evolution are first developed to synthesize a rectangular patch antenna with a microstrip feed line. Transmission line method (TLM) analysis is then used to develop the proposed CAD model for a microstrip patch antenna. In the proposed CAD models, the input parameters are the design/operating frequency, the thickness of the substrate used, and the permeability ($$\mu$$) of the substrate material, whereas the outputs are the dimensions of the structural design of the radiating patch and the microstrip feed line. The CST MWS EM tool is also used to design the antenna and validate the parameters of the synthesized antenna. A comparison between the two CAD models is presented. After the successful design of the CAD model for the microstrip antenna, the metamaterial synthesis technique is applied. Then, a metamaterial lens is designed with the help of the proposed CAD model and used to improve the performance of an antenna for use in TCAS applications. A comparison of the performance improvement is given in tabular form towards the end of the paper, including both the simulated and measured results.

Theoretical evaluation of ultrasonic velocities in binary liquid mixtures at different temperatures

Abstract: Ultrasonic velocities calculated from various theories and relations like Nomoto’s relation, Van dael ideal mixing relation, Impedance relation, Rao’s specific velocity relation and Jungie’s theory are compared with experimental values in binary liquid mixtures o-anisidine with o-cresol at temperatures 303.15, 308.15, 313.15 and 318.15 K over the entire mole fraction range. The relative applicability of these theories to the present system is checked and discussed. A good agreement is observed between experimental and theoretical values. The results are explained in the light of molecular interactions occuring in these mixtures.

Avoiding Attacks Using Node Position Verification in Mobile Ad Hoc Networks

Abstract: A mobile ad hoc network is a collection of autonomous mobile devices that communicate with each other. This network may contain foe nodes and trustworthy nodes. Foe nodes imply attacker nodes which are malwares, threats, malicious nodes. To keep away from these nodes, we introducing node position verification protocol. This protocol is utilized for message exchange which is used for transmitting messages among the nodes and checks the location of each and every node in the network. The message exchange protocol manages the distinguishing proof of nodes that are in a communication range. Distance computation is in view of message transmission between the prover and its correspondence adjacent node. Calculated distance is utilized to confirm the location of communicating nodes in network. For node position verification, mainly three methods are utilized. This problem is implemented for mobile ad hoc network and simulation using NS2 tool. The benefit of this technique is to lessen the delay and accomplish the high throughput and can stop attackers not entering into information transmission nodes.

Author Profiles Prediction Using Syntactic and Content-Based Features

Abstract: In digital forensics, the forensic analysts raised the major questions about the details of the author of a document like identity, demographic information of authors and the documents which were related these documents. To answer these questions, the researchers proposed a new research field of stylometry which uses the set of linguistic features and machine learning algorithms. Information extraction from the textual documents has become a popular research area in the last few years to know the details of the authors. In this context, author profiling is one research area concentrated by the several researchers to know the authors’ demographic profiles like age, gender, and location by examining their style of writing. Several researchers proposed various types of stylistic features to analyze the style of the authors writing. In this paper, the experiment was performed with combination of syntactic features and content-based features. Various machine learning classifiers were used to evaluate the performance of the prediction of gender of reviews dataset. The proposed method achieved best accuracy for profiles prediction in author profiling.