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Author: search.filters.author.Bajpai, ShrishHas files: Yes

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    Statistical evaluation of e-learning through virtual lab for haemodialysis machine: Barriers and future scope
    (Routledge, 2023) Hassan,Usman; Bajpai, Shrish; Kidwai,Naimur Rahman; ; ;
    Due to the Covid-19 scenario across the world, the university education system for the student moved towards offline mode to online mode. The classes can run in online mode through the different meeting platforms but the lab cannot be conducted through the video. The virtual lab is a boon for the technical student as they can perform the experiment with internet-enabled devices (laptop or smartphone). The virtual lab can be operated at any time and students can perform the experiment multiple times without visiting the actual lab. For medical background students, many machines having the electronics components can be covered through the virtual labs. The medical instrument is very costly and it cannot be available in every institute the haemodialysis is among one of the electronics instruments which need to be studied by biomedical engineering, lab technicians and nursing undergraduate university students. In this paper, we conduct a short survey among the undergraduate students who worked with haemodialysis machine virtual lab and real haemodialysis machine. The result of the survey is very encouraging and most students are comfortable with the haemodialysis virtual lab.
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    2022 5th International Conference on Multimedia, Signal Processing and Communication Technologies (IMPACT)
    (IEEE, 2022) Chandra, Harshit; Bajpai, Shrish
    Hyperspectral (HS) image has rich spectral information content, which facilitates multiple applications including remote sensing. Due to the big data size of the HS image, compression is a required process for the efficiency of image storage and transmission. However, the complexity of the compression algorithms turns real-time compression into a very challenging task. A novel listless set partitioned hyperspectral image compression algorithm is proposed. The proposed compression algorithm uses zero block cube tree structure to exploit the inter and intra sub-band correlation to achieve the compression. From the result, it has been clear that the proposed compression algorithm has low coding complexity with at-par coding efficiency. Thus, it can be a suitable contender for low-resource hyperspectral image sensors.
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    2023 International Conference on Power, Instrumentation, Energy and Control (PIECON)
    (IEEE, 2023) Chandra, Harshit; Bajpai, Shrish
    Computational complexity with the coding efficiency of any hyperspectral image sensor is a challenging issue. 3D-SPIHT has reasonable complexity and generates an embedded bit-stream. Due to the linked lists, the processing of the compression through the 3D-SPIHT gets slow at the high bit rates. This manuscript presents a low-complexity version of 3D-SPIHT which uses the array structure instead of linked lists. These arrays are independent of each other. The coding memory required by the arrays is the same as the linked list used in 3D-SPIHT. Through the use of array, the coding complexity is reduced and coding efficiency is increased with the use of parity of the bit plane. Thus, the proposed compression scheme is an optimum solution for the resource-constraint hyperspectral image sensor.
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    2023 International Conference on IoT, Communication and Automation Technology (ICICAT)
    (2023) Ahmed, Hasnain Nabi; Khan, Abdul Rahman Asad; Bajpai, Shrish
    This paper proposes a novel and non-invasive approach for detecting the freshness of Hairtail fish using a compact microstrip patch antenna operating at 2.45 GHz. The antenna, with dimensions of 38.6 mm×47.6 mm×1.6 mm , was used to measure the resonant frequency and return loss of fresh and stale fish at different distances. The results indicate that the proposed method is reliable and effective for detecting the freshness of fish, which is important for reducing food waste and ensuring food safety. This method offers a practical solution for the seafood industry to monitor and maintain the quality of their products during transportation and storage.