B Vikranth - Academia.edu (original) (raw)

Papers by B Vikranth

SSRN Electronic Journal, 2021

Healthcare domain and a reliable method to store every patient’s data record securely by keeping ... more Healthcare domain and a reliable method to store every patient’s data record securely by keeping protection of privacy in mind are considered to be one of the major concerns in the field of study and implementation. An efficient decentralized system for control accessed interoperability of transactions or data between the owner (patient) and the healthcare practitioner is required. This would also ensure a complete and accurate medical history of the patient and allow the full use of it by the health organization as well. The rise in blockchain technology has enabled to build the needs to bridge the gap between the patient and practitioner to securely store and utilize personal data digitally. This paper is a study on proposed implementations and a scope of those medical health aggregation methods have been discussed along with an idea to improve the existing system. A two-level access-controlled mechanism of the patient’s private medical record and granting the requested access or transfer of ownership properties to the practitioner in any chain of a hospital is proposed. Hence, a decentralized, automatically verifiable, transparent and immutable smart e-healthcare card medical records aggregation system could be designed using the Hyperledger Sawtooth framework built on the blockchain technology platform. Three algorithms are being proposed to ensure an atomic transaction - Proof of Work (PoW), Byzantine Fault Tolerance (BFT) and Asymmetric Cryptography (like RSA) algorithm. The aim is to implement the proposed model and strive towards the scope of betterment in the field of healthcare. The health data is planned to be stored in a format like Electronic Health Records (EHR).

International journal of experimental research and review, Mar 30, 2024

Smart farming technologies enable farmers to use resources like water, fertilizer and pesticides ... more Smart farming technologies enable farmers to use resources like water, fertilizer and pesticides as efficiently as possible. This paper discusses how Unmanned Aerial Vehicle (UAV) pictures can be used to automatically detect and count tassels, thereby advancing the advancement of strategic maize planting. The real state of affairs in cornfields is complicated, though, and the current algorithms struggle to provide the speed and accuracy required for real-time detection. This research employed a sizable, excellent dataset of maize tassels to solve this problem. This paper suggests using the bottom-hat-top-hat preprocessing technique to address the lighting irregularities and noise in maize photos taken by drones. The Lightweight weight-stacked hourglass Network (LS-HGNet) model is suggested for classification. The hourglass network structure of LS-HGNet, which is mostly utilised as a backbone network, has allowed significant advancements in the discovery of maize tassels. In light of this, the current work suggests a lighter variant of the hourglass network that also enhances the accuracy of tassel detection in maize plants. The additional skip connections used in the new hourglass network architecture allow minimal changes to the number of network parameters while improving performance. Consequently, the suggested LS-HGNet classifier lowers the computational burden and increases the convolutional receptive field. The hyperparameter tuning process is then carried out using the Sooty Tern Optimisation Algorithm (STOA), which helps increase tassel detection accuracy. Numerous tests were conducted to verify that the suggested approach is more accurate at 98.7% and more efficient than the most advanced techniques currently in use.

Advanced Computing and Communication Technologies, 2018

Modern high-performance server systems are typically built as several multi-core chips put togeth... more Modern high-performance server systems are typically built as several multi-core chips put together in a single system. Each chip is connected to its local memory via an integrated memory controller (IMC) behaving as a node and hence the single machine behaving as non-uniform memory architecture (NUMA). Various user-level run-time systems adapt work stealing load balancing technique in multi-core processors. The work stealing run-times have to be aware of the topology of the processor on which they are running. Work stealing run-times on multi-core processors typically rely on lock-based synchronization to guarantee the coherency of shared mutable state. Synchronization constructs such as mutex locks, condition variables, and barriers are extensively used in implementation of these user-level work stealing run-times. The locality of these lock variables in multi-socket NUMA processors has considerable impact on the performance of these run-time systems. This paper studies the effect...

International Journal on Recent and Innovation Trends in Computing and Communication

Wireless sensor networks (WSNs) are composed of small, resource-constrained sensor nodes that for... more Wireless sensor networks (WSNs) are composed of small, resource-constrained sensor nodes that form self-organizing, infrastructure-less, and ad-hoc networks. Many energy-efficient protocols have been developed in the network layer to extend the lifetime and scalability of these networks, but they often do not consider the Quality of Service (QoS) requirements of the data flow, such as delay, data rate, reliability, and throughput. In clustering, the probabilistic and randomized approach for cluster head selection can lead to varying numbers of cluster heads in different rounds of data gathering. This paper presents a new algorithm called "Spread Spectrum based QoS aware Energy Efficient Clustering for Wireless sensor Networks" that uses spread spectrum to limit the formation of clusters and optimize the number of cluster heads in WSNs, improving energy efficiency and QoS for diverse data flows. Simulation results show that the proposed algorithm outperforms classical algor...

Journal of Intelligent & Fuzzy Systems

High Blood Pressure (HBP) is one of the major significant medical concerns of many people around ... more High Blood Pressure (HBP) is one of the major significant medical concerns of many people around the globe today. HBP is so common symptom many people across the globe are experiencing, irrespective of age, gender, region, and religion. HBP prediction ahead of time can help the person to avoid the consequences such as heart stroke, kidney failure, eye damage, sexual dysfunction, and even death. HBP prediction in advance is a challenging issue as it is associated with many biopsychosocial factors. Heuristic and meta-heuristic-based Machine Learning Models (MLM) exclusively supervised machine learning techniques are becoming part and parcel of medical data diagnosis. However, the reliability of outcome, usability, and understandability of such stand-alone models in processing medical data in real-time are not up to the mark. To overcome such limitations, in this paper we proposed an intelligent majority voting and heuristic-based user-friendly hybrid classifier to predict HBP (An Inte...

CVR journal of science and technology, 2020

CVR Journal of Science & Technology, 2016

International Journal for Research in Applied Science and Engineering Technology, Aug 31, 2022

With the rapid growth in the field of object detection, developing a sign language detector as it... more With the rapid growth in the field of object detection, developing a sign language detector as it is the main instrument of correspondence for physically challenged individuals has invoked the need for such a system. Communication via gestures is a shelter for the genuinely provoked individuals to communicate their contemplations and feelings. With the assistance of computer vision and neural organizations, we can recognize the signs and show the respective text as the output. This paper is a survey based on a broad collection of research papers on the related domain to propose an efficient and accurate model with the core functioning of a better response time and real-time detection using various machine-learning algorithms.

Advances in Intelligent Systems and Computing, Jul 6, 2018

2008 Annual IEEE India Conference, 2008

In this paper, a fault diagnostic system in a multilevel- inverter using a adaptive back-propagat... more In this paper, a fault diagnostic system in a multilevel- inverter using a adaptive back-propagation neural network is developed. An adaptive back propagation neural network classification is applied to the fault diagnosis of a MLI system to avoid the difficulties in using mathematical models. A multilayer perceptron (MLP) network with 40 - 12 - 8 architecture is used to identify the type and location of occurring faults from inverter output voltage measurement. The neural network design process is clearly described. The classification performance of the proposed network between normal and abnormal condition and that among fault features is obtained. Thus, by utilizing the proposed neural network fault diagnostic system, a better understanding about fault behaviors, diagnostics, and detections of a multilevel inverter system can be accomplished.

Modern server processors in high performance computing consist of multiple integrated memory cont... more Modern server processors in high performance computing consist of multiple integrated memory controllers on-chip and behave as NUMA in nature. Many user level runtime systems like Open MP, Cilk and TBB provide task construct for programming multi core processors. Task body may define the code that can access task local data and also shared data. Most of the shared data is scattered across virtual memory pages. These virtual pages may be mapped to various memory banks of sockets due to first touch policy of Linux. The user level run-time environments must ensure that the tasks are mapped at a minimum possible distant memory bank where the shared data is located. At the same time, the runtime systems must ensure the load balancing among the multiple cores. Many of the user level runtime systems apply work stealing technique for balancing the load among the cores. Often, there is a tradeoff between these two requirements: object locality and load balancing. In this paper, we address th...

Procedia Computer Science

“The On Chip NUMA Architectures (OCNA) introduce a new challenge namely memory-latency to the sch... more “The On Chip NUMA Architectures (OCNA) introduce a new challenge namely memory-latency to the scheduling methods. The language run-times and libraries try to explore the processing power of these multiple cores by mapping the user-created tasks on to these cores by using suitable scheduling algorithms with load balancing support to improve throughput. The popular load balancing techniques used are work-sharing and work-stealing and many run-time systems such as Cilk, TBB and wool implement task stealing algorithm to schedule the tasks on to the cores by multiplexing the program generated tasks on to the native worker threads supported by the operating system. But the task stealing strategy applied in present run-time systems assumes the sharing the last level cache (LLC) and common shared bus among all cores on Chip Multi Processor. It tries to optimize the utilization without considering the presence of multiple On Die DRAM controllers and their topological arrangements. Current ta...