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All Journal ADI Journal on Recent Innovation (AJRI)
Ankur Singh Bist
Graphic Era Hill University
Religion Civil Engineering, Building, Construction & Architecture Computer Science & IT Education Industrial & Manufacturing Engineering

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The Impact Of Online System on Health During Covid 19: A Comprehensive Study Bhupesh Rawat; Ankur Singh Bist; Untung Rahardja; Chandra Lukita; Dwi Apriliasari
ADI Journal on Recent Innovation Vol. 3 No. 2 (2022): March
Publisher : ADI Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/ajri.v3i2.654

Abstract

COVID-19 creates an unprecedented situation before humanity. Covid-19 has changed lives in all aspects, from education, industry and social life. However, the existence of Covid-19 has greatly impacted the field of education, where the applicable learning methods usually need to make drastic changes to decide the spread of Covid-19. The education sector is turning to online education because it is not possible to call students in schools and colleges. Technology online education is proving itself to be a cure for catastrophe and filling gaps. There are major challenges regarding student health due to the high use of mobile, tablet and computer screens. There are problems regarding student health in the application of technology online learning, in this paper we make a detailed study of the same problem with the ultimate goal of research to find out the preventive measures. In this paper, we use the literature study method to explore negative cases in terms of obtaining negative reasoning due to excessive screen use during the COVID-19 scenario
Quantum Computing and AI: Impacts & Possibilities Bhupesh Rawat; Nidhi Mehra; Ankur Singh Bist; Muhamad Yusup; Yulia Putri Ayu Sanjaya
ADI Journal on Recent Innovation Vol. 3 No. 2 (2022): March
Publisher : ADI Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/ajri.v3i2.656

Abstract

Quantum computing is one of the emerging technologies. Different communities and research organizations are working to bring quantum computing applications into reality. Artificial Intelligence is another emerging area and getting stable with time. This paper, the main objective is to find out the impact of quantum computing research growth for AI applications. Thus, the method used in this study uses computational methods. so that this research can be concluded regarding the growing impact of quantum computing research for a given AI application. This paper also presents the impact and possibilities of quantum computing in the field of artificial intelligence.
Analysis Of Deep Learning Techniques For Chest X-Ray Classification In Context Of Covid-19 Vertika Agarwal; M. C. Lohani; Ankur Singh Bist; Eka Purnama Harahap; Alfiah Khoirunisa
ADI Journal on Recent Innovation Vol. 3 No. 2 (2022): March
Publisher : ADI Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/ajri.v3i2.659

Abstract

Coronaviruses (COV) are a large family of viruses that cause illness ranging from common cold to more severe disease such as MIDDLE EAST RESPIRATORY SYNDROME (MERS-COV) and SEVERE ACUTE RESPIRATORY SYNDROME (SARS-COV). Common signs of infection include respiratory symptoms, Fever, Cough, Shortness of breath and breathing difficulties. In severe cases, infection can cause pneumonia, severe acute respiratory syndrome, kidney failure and even death.3-Tier strategy is employed by government to combat this virus i.e., Track, Test and Treat. So, there is a need to increase the testing speed but the main stumbling block is the time RT-PCR takes which is around 2-3 days. In this situation, the recent research using Radiology imaging (such as Xray) techniques can be proven helpful to detect Covid 19. Latest deep learning techniques applied to Xray scans which rapidly detects the disease and thus reducing the time for testing. Moreover, it is accurate as compare to RT-PCR test where nose and mouth swabs are taken by lab technician which is prone to error.In this survey paper, ten different DL Techniques are surveyed which performs Xray classification with different accuracy. Different combination of Datasets are employed by these algorithms to improve the performance of their proposed model.Our paper evaluates the performance of each algorithm based on two parameters -Accuracy and Sensitivity.
Co-Authors Alfiah Khoirunisa Ari Prambudi Bhupesh Rawat Dwi Apriliasari Harahap, Eka Purnama M. C. Lohani Muhamad Yusup Nidhi Mehra Primasatria Edastama Untung Rahardja Vertika Agarwal Yulia Putri Ayu Sanjaya