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All Journal Bali Journal of Anesthesiology Civil Engineering Journal International Journal of Engineering, Science and Information Technology Indonesian Journal of Interdisciplinary Research in Science and Technology (MARCOPOLO)
Kumar, Neeraj
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Humanities Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Physics Social Sciences Transportation Other

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 1 
Vecuronium in tuberculosis: a rare case report of reversible quadriparesis Kumar, Amarjeet; Kumar, Neeraj; Sinha, Chandni; Kirti, Ravi; Kumar, Sanjeev
Bali Journal of Anesthesiology Vol 3, No 1 (2019)
Publisher : DiscoverSys Inc.

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1001.43 KB) | DOI: 10.15562/bjoa.v3i1.120

Abstract

 ABSTRACTTuberculosis is a major health burden worldwide. The National treatment regimens for tuberculosis (TB) patients recommend the use of the five first lines anti TB drugs: isoniazid (INH), rifampicin (R), ethambutol (E), pyrazinamide (P) and streptomycin (S). Maintaining of oxygenation are very much challenging in tuberculosis patients associated with Acute Respiratory Distress Syndrome (ARDS). Often we need muscle relaxation with adequate sedation for maintaining oxygen saturation and lung recruitment. Skeletal muscle weakness has a confusing list of names and syndromes, including Acute Quadriplegic Myopathy Syndrome (AQMS), floppy man syndrome, critical illness polyneuropathy (CIP), and acute myopathy of intensive care. In disseminated tuberculosis with ARDS, we recommend the use of short-acting muscle relaxant drugs like cisatracurium whose metabolism not depends upon the liver. Interrupting the vecuronium infusion (vecuronium holiday) as its action was potentiated by streptomycin and corticosteroid which may result in the development of Critical Illness Polyneuro Myopathy (CIPM). Targeting Train of Four (TOF) of two rather than zero of four has been shown to be beneficial for a period of fewer than 48 hours.
Experimental Studies and Analysis on Mobilization of the Cohesionless Sediments Through Alluvial Channel: A Review Anand, Akash; Beg, Mubeen; Kumar, Neeraj
Civil Engineering Journal Vol 7, No 5 (2021): May
Publisher : Salehan Institute of Higher Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/cej-2021-03091700

Abstract

Entrainment of river bed particles by turbulent flow is a core matter of study in river hydrodynamics. It is of great interest to river engineers to evaluate the shear stress for initiating river bed motion. The main objective is to calculate transport rates for bed load, to predict changes in bed level which are scoured or aggraded and to design a stable channel. Forces acting upon the particle especially fluid forces which give a major role in the incipient motion of the particle on the rough boundary. For calculation generally use shield’s diagram but some other modified methods and approaches are discussed. Modeling criteria are discussed for the hydraulically smooth and rough boundary depending on Reynolds number. In the past, experimental studies on tractive shear stress have been done by many researchers but consideration of lift force to analyze the movement of sediment is very limited. For suspended load transport, a detailed analysis of lift force is required. Based on the study it has been observed that shear stress depends on channel slope not only due to gravitational force but also many other factors like drag force, lift force, friction angle, fluctuations, velocity profile, etc. Complete analysis of these factors provides slope dependency over shear stress. To improve past studies, some factors have been discussed, to give a more correct force balance equation. This is very difficult task to analyze more and more variable’s dependency on the slope. Consideration of the possible number of variable holds complete analysis of experimental study. This paper also reviews the effect of particle Reynolds number and relative submergence over critical shield stress. Doi: 10.28991/cej-2021-03091700 Full Text: PDF
Swarm Intelligence-Based Performance Optimization for Wireless Sensor Networks for Hole Detection Padmapriya, T; Jadhav, Chaya; Nyayadhish, Renuka; Kumar, Neeraj; Kaliappan, P
International Journal of Engineering, Science and Information Technology Vol 5, No 3 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i3.1127

Abstract

Extensive research into maintaining coverage over time has been spurred by the growing need for wireless sensor networks to monitor certain regions.  Coverage gaps brought on either haphazard node placement or failures pose the biggest threat to this objective.  In order to identify and fix coverage gaps, this study suggests an algorithm based on swarm intelligence.  Using both local and relative information, the swarm of agents navigates a potential field toward the nearest hole and activates in reaction to holes found.  In order to spread out effectively and speed up healing, the agents quantize their perceptions and approach holes from various angles. The need for wireless sensor networks to monitor certain areas has grown, leading to many studies on maintaining coverage over time. Random node deployment or failures create coverage gaps, which pose the biggest threat to this objective.  A swarm intelligence-based approach is proposed in this paper to identify and fix coverage deficiencies. Even with Their encouraging performance and operational quality, WSNs are susceptible to various security threats. The security of WSNs is seriously threatened by sinkhole attacks, one of these. In this research, a detection strategy against sinkhole attacks is proposed and developed using the Swarm Intelligence (SI) optimization algorithm. MATLAB has been used to implement the proposed work, and comprehensive Models have been run to assess its effectiveness in terms of energy consumption, packet overhead, convergence speed, detection accuracy, and detection time. The findings demonstrate that the mechanism we have suggested is effective and reliable in identifying sinkhole attacks with a high rate of detection accuracy.
Efficient Deep Learning Ensemble of Lightweight CNNs and Vision Transformers for Real-Time Plant Disease Diagnosis Dubey, Mruna; P.S.G., Aruna Sri; Jha, Suresh Kumar; Nupur, Nupur; Bhiogade, Girish; Kumar, Neeraj
International Journal of Engineering, Science and Information Technology Vol 5, No 4 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i4.1347

Abstract

Timely identification of plant diseases plays a vital role in protecting crop yield and supporting effective decision-making in precision agriculture. Conventional computer vision models achieve high recognition accuracy but often require substantial computing power, making them impractical for low-cost edge hardware widely used in rural areas. In this work, a compact deep learning ensemble is presented, combining three lightweight convolutional neural networks—MobileNetV3-Small, EfficientNet-B0, and ShuffleNetV2—with a Vision Transformer (ViT-B/16). The models operate in parallel, and their outputs are merged using a weighted late-fusion approach, with fusion weights determined through systematic grid search to achieve the best trade-off between predictive performance and processing speed. The Plant Village dataset, consisting of 54,303 images from 38 healthy and diseased leaf categories, was used for evaluation. To improve robustness, the training data were augmented through geometric transformations, contrast adjustment, and controlled noise addition. When tested on a Raspberry Pi 4 device, the ensemble reached an accuracy of 97.85%, precision of 97.67%, recall of 97.92%, and F1-score of 97.79%, with an average inference time of 20.5 ms and a total size of 14.6 MB. These results surpassed those of all individual models and conventional machine-learning baselines. Statistical testing using McNemar’s method confirmed the significance of the improvement (p 0.05). Precision–Recall analysis indicated strong resistance to false positives, while accuracy–latency assessment confirmed suitability for real-time field operation. The proposed system offers a practical, resource-efficient framework for on-site plant disease diagnosis in areas with limited connectivity and computing resources. Further development will focus on adaptation to field-captured imagery, hardware-aware model compression, and the integration of additional sensing modalities such as hyperspectral and thermal imaging.
Design of Intelligent Polyhouse with IOT Bedi, Harpreet Singh; Harshin, Ambu Naga; Lawai, BP; Kumar, Neeraj
Indonesian Journal of Interdisciplinary Research in Science and Technology Vol. 2 No. 3 (2024): March 2024
Publisher : PT FORMOSA CENDEKIA GLOBAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55927/marcopolo.v2i3.8095

Abstract

A polyhouse, often known as a greenhouse, is a building constructed for the controlled growing of plants. It is often built of translucent materials such as glass or plastic and is intended to offer a regulated temperature for plants, shielding them from harsh weather but allowing sunlight to pass through. The study considers various factors such as affordability and feasibility, combines IoT and fuzzy control techniques, uses GPRS for remote control, and creates a smart greenhouse monitoring system that is user-friendly, simple to operate, and performs well. Moreover, there are automated control mechanisms, such as greenhouse doors and windows that roll on and off in response to soil moisture levels. By using IoT to maintain precise parameters like CO2, soil moisture, temperature, and light in the greenhouse, the technology will help farmers increase productivity while reducing the need for physical field visits. An internet connection and an IoT kit are used for the task. The bell pepper plant's greenhouse conditions include CO2, soil moisture, temperature, and light
Co-Authors Anand, Akash Bedi, Harpreet singh Beg, Mubeen Bhiogade, Girish Dubey, Mruna Harshin, Ambu Naga Jadhav, Chaya Jha, Suresh Kumar Kaliappan, P Kirti, Ravi Kumar, Amarjeet Kumar, Sanjeev Lawai, BP Nupur, Nupur Nyayadhish, Renuka P.S.G., Aruna Sri Padmapriya, T Sinha, Chandni