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.

Design analysis of GOS-HEFET on lower Subthreshold Swing SOI

Abstract: Due to various kind of Band-To-Band Tunneling (BTBT) operation, Heterojunction Tunnel Field Effect Transistors (HEFETs) are widely used in ultralow power applications. Anyhow, circuit complexity is a major issue in case of HEFET based memory development because of their uncomfortable size. Device scaling is a better way to eliminate such kind of issues for HEFET based memory development. Thus, development of Gate-oxide Overlapped Source-HEFET (GOS-HEFET) with lower Subthreshold Swing (SS) based Silicon on Insulator (SOI) is proposed to achieve perfect scaling in this work. Tunneling operation is done with the help of Si-based tunnel devices which are considerably lower than that of MOSFETs. Tunneling rate is enhanced by small bandgap material (Germanium (Ge)) in the source (S) while the ambipolar leakage is minimized by wide band gap material (Silicon (Si)) in the channel. Here, Ge is mainly utilized to dope the source region of P type transistor while Si is used to dope the drain (D) region of N type transistor. Moreover, the tunneling rate of BTBT is enhanced by the geometric alignment of the P and N type transistors with the gate oxide/semiconductor interface. Based on this procedure, five different kinds of SRAM (6 T, 7 T, 8 T, 9 T and 10 T) memory cells are designed. The proposed GOS-HEFET with lower SS on SOI design is implemented using SILVACO TCAD and TANNER CMOS technology. Then, power performance for different temperatures of the proposed method is compared with conventional HEFET based SRAM memory cells.

A Novel Approach for Improved Data Replication Using HDFS

Abstract: HDFS (Hadoop Distributed File System) is intended to store huge dataset values with accurate file location with high reliability and data streaming to the application is done at high bandwidth. HDFS deals with high fault tolerance with the use of replication of data. Many researches have been done on fitting the data in the exact location. The problem occurred in Hadoop distributed file system is difficulty with information space for storage. It is the most complicated problem which reduce the performance of the file system. To overcome this issue the proposed system aims to have the better data replication which depends upon the access count estimation in Hadoop framework. The proposed system creates the better replicas and to solve the data locality problem with improved arrangement of data replicas and to assign the task for efficient workers to complete the Map Reduce task to obtain the better results. By comparison with the existing system, the proposed system performs the better replication and solves the data locality problem. An experiment has been performed for evaluating the proposed technique with default technique and previously used replication techniques using a benchmark. With respect to the results obtained the proposed method obtained a better throughput when compared to the previous techniques.

Regular Expression Rule-Based Algorithm for Multiple Documents Key Information Extraction

Abstract: With the increasing number of documents available on the internet and in offline databases, the task of supporting users in finding appropriate information becomes very complex using predictable methods due to the effort in retrieving and ranking results. Information extraction is concerned with the position of specific items in (unstructured) textual documents. The developed data can be useful for mining methods requiring structured input data, in dissimilarity to other text mining methods that utilize a bag-of-words method. A rule-based approach using regular expressions can be used to extract required key information from a document of any format. We demonstrate the applicability and benefit of the approach with real-world application, curriculum vitae for name, phone number, email_id.

Wireless IoT-Based Intrusion Detection Using LIDAR in the Context of Intelligent Border Surveillance System

Abstract: Patrolling borders of India has become a tedious and risky task for military and para-military personnel in order to control Intrusions. With the advancements in wireless IoT (Internet of Things) technology, it has become much easier to design, develop and deploy a cost-effective, automatic and efficient system for intrusion detection in the context of surveillance. Making the system suitable for all types of environments, the light detection and ranging (LIDAR) sensor is developed for the acquisition of distance with a range of 40 m from the position where an object resides. Data collected by the sensor is monitored and administered in a server. Software required for the analysis of data and generation of alert notifications is deployed in the server which is an added feature to the system and assists the concerned security personnel to respond quickly and engage the safety.

Pixel based feature extraction for ear biometrics

Abstract: Ear Biometrics identification is rapidly growing in current biometric industry because of its unique features, stableness and passive of human involvement. Ear biometric system better suits for automatic identification of individual or human. We propose a pixel based feature identification approach for Ear biometric model.