SUNKARA TEENA MRUDULA

Scopus Publications

Internet of things and optimized knn based intelligent transportation system for traffic flow prediction in smart cities
Sunkara Teena Mrudula, Meenakshi, Mahyudin Ritonga, S. Sivakumar, Malik Jawarneh, Sammy F, T. Keerthika, Kantilal Pitambar Rane, and Bhaskar Roy
Elsevier BV

Adaptive Huffman Coding with Memory Optimization
Ramyasri Maturi, Raju Javvadi, Vignesh Naga Manikanta Sunkara, and Sunkara Teena Mrudula
IEEE
Adaptive Huffman coding (AHC) is an entropy encoding algorithm used for lossless data compression. This paper explores the effectiveness of Adaptive Huffman coding in achieving efficient data compression. The primary goal is to present and analyze the performance of AHC, focusing on its compression efficiency. The study integrates MATLAB code and block diagrams to evaluate the algorithm’s effectiveness. By leveraging parallel processing and optimization techniques, our approach aims to enhance compression efficiency. The paper highlights the significance of AHC in data compression and examines its implementation for improved performance.

Design of Automated Smart Attendance System Using Deep Learning Based Face Recognition
Ritonga Mahyudin, Domenic T. Sanchez, S Teena Mrudula, Ravi Kishore Veluri, Jawarneh Malik, and Abhishek Raghuvanshi
IEEE
The process of taking attendance in the traditional manner is one that is both laborious and time-consuming. Face recognition and identification technology was developed with the primary objective of providing a timesaving automated solution for tracking attendance. This article presents Design of automated smart attendance system using deep learning based face recognition. Camera IoT devices are used to acquire images. These images are stored in cloud via IoT gateway. Images contain many noises. To remove or reduce these noises, adaptive median filter are used. Once noise is removed, then images quality is enhanced by particle swarm optimization. Enhanced images are classified by CNN, CNN VGG 16 and Xception CNN deep learning techniques. Performance is compared on the basis of metrics like- accuracy, specificity and recall. Xception CNN is outperforming other techniques used in the framework. Accuracy, Specificity and Recall rate of Xception CNN is 99.33%, 98.66% and 99.33 percent respectively.

Multiplication free Fast-Adaptive Binary Range Coder using ISW
Sunkara Teena Mrudula, K.E. Srinivasa Murthy, and M.N. Giri Prasad
FOREX Publication
Data compression is defined as the process of encoding, converting and modifying the bits-structures of data in such a way that reduces less-spaces on the disk. Fast-ABRC, a new context ABRC for compressing the image and video. This paper introduces novel hardware F-ABRC (Fast-adaptive binary range coder) and architecture of VLSI, as it doesn’t have requirement of LUTs (Look-up-Tables) and also it is completely multiplication free. To get the result, we will combine the utilization of simple operation to compute the approximation after encoding every single symbol and the PE (probability estimation) on the basis of ISW (Imaginary Sliding Window) with approximation of the multiplication. We have represented our introduced algorithm, which is faster and in comparison, to the existing model it gives superior compression efficiency and the comparison takes place on the basis of two parameters such as power dissipation (Dynamic and Static) and device utilization.

Optimized Context-Adaptive Binary Arithmetic Coder in Video Compression Standard Without Probability Estimation
S.T. Mrudula, K.E. Srinivasa Murthy, and M.N. Giri Prasad
International Information and Engineering Technology Association
CABAC is a Context Adaptive Binary Arithmetic Coder utilized in novel AVC/H.264 of video standard. AC (arithmetic coding) permits important enhancement in the compression. However, the complexity of implementation is main drawback because of slowness and hardware cost. In this paper, we propose the implementation of MPEG4/H-264 AVC against M-decoder without PE (Probability Estimation). Furthermore, in order to estimate an algorithm, we have compared many existing methods, and the comparison takes place based on power dissipation and device utilization.

Experimental Analysis and Improvements of a Visible Spectrophotometer for Detection of Nano Materials
Pamula Rajakumari, Polaiah Bojja, Smitha Chowdary Ch, Sunkara Teena Mrudula, Krishnam Raju Putta, and Amsalu Gosuadigo
Hindawi Limited
As the field of nanotechnology advances, there is an increasing need for green nanomaterial identification devices. Recently, a few new studies have reminded us that as nanotechnology gets better and better, so will natural phenomena. As we grow closer to and finally reach the nanoscale, it is feasible that new physical expertise will develop. Developments in the future may allow for new technical advancements. It is the ability of nanotechnology to construct human constructs at the nanoscale that distinguishes it from other fields of science and engineering. Various components, including high-dissociation electron microscopy, centre-ion beam milling tools, and scanner probes, have made this practical. Spectrometers, sometimes known as spectrometers, are used in fabric identification machines. To conclude this inquiry, a nanoparticle scatter spectrometer was devised and built artificially. This study focused on the visible spectrum of spectroscopy because there are a broad number of programmes available for visible optical instruments.

M-ABRC (Adaptive Binary Range Coder) using Virtual Sliding Window technique and its VLSI implementation
S.T. Mrudula, K.E. Srinivasa Murthy, and M.N. Giri Prasad
Elsevier BV

SUNKARA TEENA MRUDULA

RESEARCH INTERESTS

Scopus Publications