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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.
INFLUENCE OF JUTE FIBRE ON CBR VALUE OF EXPANSIVE SOIL Kumar, Sanjeev; Sahu, Anil Kumar; Naval, Sanjeev
Civil Engineering Journal Vol 6, No 6 (2020): June
Publisher : Salehan Institute of Higher Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/cej-2020-03091539

Abstract

Construction of structures on expansive soil is highly risky due to its susceptible behavior towards differential settlements. Different soil stabilization techniques including soil reinforcement have been adopted to improve the properties of the unsuitable soils. In this present study, randomly distributed jute fibres have been used to improve geotechnical properties of expansive soil collected from South Delhi (India). California Bearing Ratio (CBR) tests were carried out on the expansive soil blended with jute fibres. Jute fibres of length 10 mm and 30 mm were included in different percentages viz. 0.25, 0.50, 0.75, 1.00, 1.25 and 1.50 by the dry weight of the soil. The test results indicate that the inclusion of randomly distributed jute fibres significantly improves the CBR value of the soil. The Optimum value of fibre content is found to be 1.25%. An improvement of 226.92% in CBR value of the reinforced soil as compared to unreinforced soil has been observed at the optimum jute fibre content. Since Jute is agricultural waste, the present study provides a cost-effective solution to problematic clayey soils.
Unveiling unmasked faces: a novel model for improved mask detection using haar cascade technique Kumar, Sanjeev; Kumar, Mohit; Dubey, Kriti; Sharma, Kaushal
Journal of Soft Computing Exploration Vol. 4 No. 3 (2023): September 2023
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v4i3.179

Abstract

In response to the urgent need to enforce mask-wearing compliance during the COVID-19 pandemic, this "Face Mask Detection" project introduces a robust model for identifying individuals not wearing face masks in videos. Leveraging computer vision's Haar Cascade technique, the project achieves rapid face detection within video streams, facilitating accurate mask usage assessment. This initiative holds paramount importance due to the pivotal role of masks in curbing virus spread. The model finds practical applications in monitoring mask adherence in public settings, pinpointing potential COVID-19 hotspots through data analysis, and bolstering safety via integration into surveillance systems. By effectively addressing the intricate challenge of precise mask detection, this project makes significant contributions to public health endeavors and the mitigation of COVID-19 hazards. The proposed algorithm showcases remarkable performance across various metrics. With an impressive detection rate of 98.4%, it surpasses established methods such as CNN (91.26%), PCA+SVM (93.4%), and Adaboost (96.1%), signifying its potential to revolutionize mask detection technology.
Test and measurement automation of printed circuit board assembly using digital oscilloscope Kumar, Sanjeev; Prasad, Deepak; Pandey, Manoj
International Journal of Reconfigurable and Embedded Systems (IJRES) Vol 14, No 2: July 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijres.v14.i2.pp463-471

Abstract

The testing and measurement (TM) of electrical parameters of printed circuit board assembly (PCBA) plays an integral part in the manufacturing sectors. These industries work on embedded system which widely use digital oscilloscopes (DO) for such purposes, however, operate them manually. An exponential rise in the implementation of industry 4.0 with the increasing demand for industrial products makes manual TM cumbersome. The automation of oscilloscopes (AO) remains a viable alternative to these issues requiring further investigation. An accurate and automated TM block facilitates efficient design, development, and assembly of a fully functional system hence addressed here. The AO has been carried out using generalized software that can be configured based on industry requirements. It subsequently stores the data on the server for better traceability. The automated software is developed using VB.NET and installed on a personal computer. Experiments reveal the proposed approach saves approximately 60%-70% of the time required for each PCBA operation than that of the manual system. This can enhance the productivity of the industry in terms of manpower and Resource utilization with a reduction in operating costs.
Dynamic attendance system using face recognition via machine learning models Upadhyay, Nishant; Bansal, Nidhi; Velinov, Emil; Harshit, Harshit; Sharma, Abhay; Kumar, Sanjeev
Indonesian Journal of Electrical Engineering and Computer Science Vol 39, No 2: August 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v39.i2.pp1421-1430

Abstract

Traditional methods to handle attendance have been implemented in the schools in the past and most of them are discouraging as they require that the institutions implement the use of paper and pen to get the results. To enhancing effectiveness and safeguarding, this paper presents a face recognition attendance system that mechanizes the usual attendance taking process. Using best practices in facial recognition, the system captures images of students’ faces, stores them, feeds them into a recognition model, and uses real-time facial recognition to mark attendance. This means that the system enjoys data encryption and password protected access that ensures data is safe. In the proposed system, the OpenCV face recognition libraries combined with machine learning algorithms for better face recognition ability with better efficiency. The results confirm that the system provides a reliable approach to handling attendance and it may debut in various contexts.
Application of Supply Chain Analytics in Agriculture: A Road to Sustainability Kumar, Sanjeev
International Journal of Supply Chain Management Vol 14, No 4 (2025): International Journal of Supply Chain Management (IJSCM)
Publisher : ExcelingTech

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59160/ijscm.v14i4.6335

Abstract

Every aspect of modern human living has now become significantly dependent on the use of data and analytics to reach optimum utility levels. Agriculture, modernized and mechanized over the ages, now makes judicious use of data analytics, particularly on aspects of agricultural supply chain, to improve efficiency. This article focuses on the merits of using supply chain analytics in agriculture. Global agricultural information can be organized and made universally accessible and useful. This article brings out how and why enormous volumes of data should be harnessed to effectively enhance agri SC in a sustainable manner, and benefit not just the customers but also the environment. This article establishes the rationale behind applying SC Analytics (SCA) in Agriculture and prepares the floor for further research on how volumes of agricultural data can be used effectively by corporate giants to implement Blockchain and Al technologies in agri SC.
Middleware Data Platform in Agricultural Supply Chain Kumar, Sanjeev
International Journal of Supply Chain Management Vol 14, No 5 (2025): International Journal of Supply Chain Management (IJSCM)
Publisher : ExcelingTech

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59160/ijscm.v14i5.6340

Abstract

Demographic and climatic changes, changes in resource distribution and soil condition of compost, depleting water resources, greater demand for customized products, need for traceability to maintain food safety and hygiene; all warrant the use of sophisticated modern technologies all along the food supply chain (SC). The integration of IoT, AI and such other technologies with blockchain can significantly improve operational efficiency of agriculture, allowing traceability and ensuring safety and quality control. Such integration also helps to realize maximum benefits from application of modern technologies to make entire agri SC more resilient. Successful application of various technologies hinges on efficient data analytics and technology integration and can be achieved using middleware for technology integration and seamless data flow within the SC. Though promising, it presents significant challenges that need to be handled to realize its full potential. This article establishes middleware data platform’s potential in integrating AI, IoT and blockchain technologies and enhancing operational efficiency of agri SC through enhanced transparency, efficiency, and security. Using a systematic AI-driven data analytics platform Middleware provides diagnostic intelligence to the farmers. Realizing middleware’s potential and utilizing it can greatly enhance functionality and performance of ASC, making it an essential tool for both developers and users. However, the technology being nascent, there is significant dearth of data, literature and evidence regarding the user experience and success rate of middleware, hence a significant knowledge gap. This article contributes towards bridging the gap, setting the floor for further research.