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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Robotics and Automation (IJRA) International Journal of Integrated Health Sciences Indonesian Journal of Electrical Engineering and Computer Science
Kumar, Arun
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Automotive Engineering Computer Science & IT Electrical & Electronics Engineering Health Professions

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Ad hoc wireless network implementing BEE-LEACH Kumar, Arun; Chakravarthy, Sumit; Gaur, Nishant; Nanthaamornphong, Aziz
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 3: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i3.pp2945-2954

Abstract

Adaptations have been key to the development and advancement of the low energy adaptive clustering hierarchy (LEACH) protocol. Presented is an alteration to the traditional LEACH, low energy adaptive clustering hierarchy, algorithm. This algorithm focuses on the battery life optimization of sensors within a wireless sensor network (WSN). These sensors will be grouped into clusters with the aim of maximizing the battery life of the overall system by sorting each sensor by residual energy and assigning the highest residual energy the role of cluster head. The protocol will then assign sensors to cluster heads based on distance relative to the head. This algorithm achieves the goal of extending battery life and offers itself as a promising alternative to standard LEACH algorithms. The algorithm is tested by comparing sensor battery life, total sensors communicating at a given time, and sensors with residual energy. This paper addresses the strengths and vulnerabilities of the algorithm, as well as proposed work for further implementation for the following groups looking to create their own LEACH protocol.
Performance analysis of neuro linguistic programming techniques using confusion matrix Kumar, Arun; Panda, Supriya P.
Indonesian Journal of Electrical Engineering and Computer Science Vol 25, No 3: March 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v25.i3.pp1696-1702

Abstract

During numerous qualitative surveys, swish patterns and visual kinesthetic dissociation (V/KD) were employed to examine attitudes and past occurrences. Neuro-linguistic programming (NLP) workshops in both hypnotic and non-hypnotic experimental sessions were held for forty days. Results demonstrated that negative sentiments and various emotional factors were significantly higher in 10-days’ workshop sessions as compared to 40 days’ sessions. Following the qualitative sentiments recollection, NLP workshops with various activities in the fear and stress indexing segment were increased in length. The NLP procedure was followed by the decreased negative emotional intensity in both groups; also, the results have been improved when using swish patterns and V/KD techniques. The performance analysis shows the results of improving emotional and sentimental factors in various NLP workshops. The workshops ranged in length from five to forty days. The specifications for workshops were selected based on the human mind's pre-determined conditions. The performance factors of two significant NLP techniques used in NLP workshops were compared and both techniques' performance factors were found to be adequate in terms of modifying behavior patterns. Using the confusion matrix, the overall accuracy percentage between V/KD and swish patterns is calculated, and an increase from 0.65 to 0.83 in the stressed parameters is shown.
Investigation of the satellite internet of things and reinforcement learning via complex software defined network modeling Kumar, Arun; Chakravarty, Sumit; Nanthaamornphong, Aziz
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 3: June 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i3.pp3506-3518

Abstract

The satellite internet of things (SIoT) has emerged as a transformative technology, enabling global connectivity and extending IoT infrastructure to remote and underserved regions. This paper explores the integration of SIoT with advanced reinforcement learning (RL) techniques through sophisticated software-defined networking (SDN) modeling. The study emphasizes SDN’s capability to offer flexible, dynamic, and efficient management of satellite-based IoT networks, addressing unique challenges such as high latency, limited bandwidth, and frequent mobility. To address these challenges, we propose an RL based approach for optimizing network resource allocation, routing, and communication strategies. The RL algorithm enables autonomous adaptation to real-time network conditions, tackling critical concerns such as spectrum management, energy efficiency, and load balancing, ensuring reliable connectivity while minimizing congestion and power consumption. Furthermore, SDN facilitates network programmability, enabling centralized control and streamlined management of SIoT systems. The proposed RL-driven SDN model is validated through simulation experiments, demonstrating significant improvements in throughput, network efficiency, and quality of service (QoS) metrics compared to traditional network models. This work advances the development of satellite IoT networks by providing a robust, scalable framework that integrates RL and SDN technologies, offering intelligent and efficient connectivity solutions to meet the growing demands of next-generation SIoT systems.
Internet of robotic things: Design and develop the quality of service framework for the healthcare sector using CoAP Kumar, Arun; Sharma, Sharad
IAES International Journal of Robotics and Automation (IJRA) Vol 10, No 4: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijra.v10i4.pp289-295

Abstract

The number of robotics used globally is gradually growing, according to a variety of research. They are becoming more and more popular in different workplaces, like manufacturing, distribution, medical conditions, military, inaccessible areas, etc. The int ernet of things (IoT) and robotics groups have until now been guided by a set of, but somewhat compatible, goals, which are mainly to help knowledge systems in the field of general sensing, tracking, and monitoring. Therefore, the development of an interne t of robotic things (IoRT), which incorporates the outcome from both cultures, is progressively said to have a significant added benefit. Internet of robotic thin gs, the intersection of the Internet of Things and robotics, is where self - sufficient machines will assemble information from various sensors and speak with one another to perform errands including basic reasoning. As the name suggests, IoRT is the combination of two front - line innovations, the internet of things and robotics . People can manage any electronic device in homes with IoT and can also be used in contactless applications in healthcare. The constrained application protocol (CoAP), for the management and control of a community of homogeneous sensor modules, has recently endorsed multicast c ommunications in IoRT. It will boost connectivity performance, less power consumption due to data aggregation, and enhanced security features with DTLS security features for various applications for the internet of things . This paper presents an implementa tion of the CoAP framework on IoRT sky motes using the C ontiki C ooja Simulator that will be a useful healthcare sector that will confirm their potential and therefore, new research directions are outlined.
Secondary Seizures in the Pediatric Population in Two Tertiary Hospitals in India Kumar, Arun; Marimuthu, Thangaraj; Kannan, Lakshminarayanan; Agarwal, Vikash; Nayak, Dinesh
International Journal of Integrated Health Sciences Vol 11, No 1 (2023)
Publisher : Faculty of Medicine Universitas Padjadjaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15850/ijihs.v11n1.2962

Abstract

Objective: To evaluate the clinical pattern of secondary seizures which includes acute and remote symptomatic seizures among hospitalized patients in two healthcare centers and to assess the outcomes among hospitalized patients having secondary seizures.Methods: This multicentric cross-sectional study was conducted in two tertiary hospitals in Odisha and Tamil Nadu, India, for a period of four years. A total of 274 patients in the age group between 6 months to 12 years participated in the study. A structured proforma was used to document the clinical pattern and causes of the secondary seizures.Results: Among the participants in Odisha and Tamil Nadu hospitals, focal seizures constituted 67.5%. Generalized seizures were present in 32.4%. The key causes of seizures in Odisha were malaria, cerebral palsy, and viral meningitis, while in Tamil Nadu, the causes were neurocysticercosis, cerebral palsy, and viral meningitis.Conclusion: Since the majority of the causes are preventable, it is important to address the issue at the public health level, by providing improved sanitation and adequate awareness on the secondary seizure and its causes. It is also important that the physicians are well conversant with the early case detection and treatment of primary diseases causing secondary seizures.
Co-Authors Agarwal, Vikash Chakravarthy, Sumit Chakravarty, Sumit Gaur, Nishant Kannan, Lakshminarayanan Marimuthu, Thangaraj Nanthaamornphong, Aziz Nayak, Dinesh Panda, Supriya P. Sharma, Sharad