ABSTRACT
Building a local supply chain requires separating the regions and creating alliances with local partners and customers, resulting in a new business model. In local supply chains, the factory procures material, parts, and preassembled elements from local suppliers and sells the final products to local customers. Three-dimensional printing (3DP) has the potential to enable a more local, globally connected, and efficient supply chain through reduced inventory and transportation costs transforming the make-to-stock to the make-on-demand production cycle. In this study, we use an integrated Interpretive Structural Model and Decision-making Trial and Evaluation Laboratory technique to explore and assess the challenges faced by the 3DP companies to become enabling partners in the localized supply chains. The scope of the study, which was limited to 3DP of medical parts and components, identified that regulatory compliance, stringent quality standards, and lack of design expertise are significant barriers to developing localized three-dimensional printing ecosystems. Furthermore, the study identified immediate support from the local government, the high collaboration between the stakeholders, and the need for change in business approach as the key drivers for developing 3DP-enabled localized supply chain ecosystems. IEEE
ABSTRACT
In wireless communications several imaging methods are developed. During this pandemic situation in worldwide due to COVID 19, telemedicine plays a vital role in maintaining social distancing. In telemedicine, there is demand for high compression and encryption approaches to overcome bandwidth and security issues. In this work, a joint compression and encryption (JCE) approach for images is proposed. The proposed model is more secure with faster computational time. For compression Absolute Moment Truncation Coding approach is used and furthermore for encryption two chaotic maps i.e., Arnold’s Cat and Henon Map are applied on the compressed image. Further, the experimental results were studied to measure the performance of the model for brute force, differential and statistical attack. The proposed schemes have shown good results for compression and even for security i.e., NPCR 99.86, UCAI=30.29, MSE= 108.91, PSNR=28.34, Correlation Coefficient = -0.0054 and Entropy 7.97 against the various other approaches. © 2021 Taru Publications.
ABSTRACT
Nitrogen dioxide (NO2) is a gaseous air pollutant which primarily gets in the air when fossil fuels such as coal, oil, gas or diesel are burned at high temperatures through industries, power plant, automobiles and locomotive. Continuous exposure to elevated concentration of NO2 may impose development of asthma and potentially increase in susceptibility to respiratory infections in humans. The present study examined impact of lockdown due to COVID-19 in terms of spatial and temporal variation of tropospheric NO2 in Indo-Gangetic plain. The results showed steep reduction in tropospheric NO2 as a result of ceased industrial and economic activities. Analysis of Sentinel-5P satellite data was carried out for specific period during 2019-2020 at a regional scale and for major industrial cities. Tremendous positive impact of lockdown in atmospheric condition is observed, wherein NO2 concentration has gone down by 20-40% in all major cities except few exceptions were noticed. The concomitant impact of Covid-19 has ensued pragmatic constructive impact on environment and climate, due to drop in NO2 emissions.