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All Journal Aptisi Transactions on Technopreneurship (ATT) ADI Journal on Recent Innovation (AJRI)
Vertika Agarwal
Graphic Era Hill University
Religion Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Economics, Econometrics & Finance Education Industrial & Manufacturing Engineering Social Sciences

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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.
Village Tourism Empowerment Against Innovation, Economy Creative, and Social Environmental Mochamad Heru Riza Chakim; Mulyati; Po Abas Sunarya; Vertika Agarwal; Ihsan Nuril Hikam
Aptisi Transactions On Technopreneurship (ATT) Vol 5 No 2sp (2023): Special Issue: Support Technopreneurship in the Medical
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/att.v5i2sp.342

Abstract

This study explores the vital role of village tourism in fostering innovation and elevating the creative economy. Through enhancing tourist experiences and advancing local innovation, it investigates the intricate impacts of village tourism on innovation, the creative economy, and society. Utilizing a qualitative approach, 145 participants are engaged via surveys to analyze factors that influence Tourism Village: Environment (En), Economic (Ec), Socio-Culture (SC), Innovation Promotion (IP), and Tourism (Tr). Employing partial quadratic-structural equation modeling through SmartPLS, it examines how citizen engagement and tourism-induced economic gains influence psychological, social, and political empowerment, and place attachment. The findings emphasize village tourism's vast potential in driving innovation, igniting creativity, and contributing significantly to economic and social growth. Nonetheless, its sustainability relies on harmonizing social, economic, and environmental aspects. The study underscores the urgency of sustainable management for lasting benefits for locals and visitors alike. Synthesizing impacts, contributions, challenges, solutions, novel insights, and revelations, this research highlights village tourism's transformative power in propelling innovation-focused advancement in the creative economy, highlighting the necessity of responsible management approaches.
Co-Authors Alfiah Khoirunisa Ankur Singh Bist Harahap, Eka Purnama Ihsan Nuril Hikam M. C. Lohani Mochamad Heru Riza Chakim Mulyati Mulyati Po Abas Sunarya