The current COVID-19 pandemic represents a danger for which efforts have been joined to find an effective treatment. This pandemic has evolved so quickly that new data emerge daily on the number of sick and fatal cases. As of September 2021, more than 180 countries with positive COVID-19 cases have been notified to the World Health Organization, including 228,807,631 confirmed cases, including 4,697,099 deaths. So far, the Americas region is the most affected with a total of 88,207,746 confirmed cases, and during this period, Ecuador has reported 246 new infections on average each day, for a total of 507,003 infections and 32,661 deaths. To date, dissimilar methods and treatments have been used to mitigate its effects. However, no effective treatment option has been found against it, generating uncertainty, social panic, and impacts on the population's mental health as a result of the fear of infection and death. That is why the present work focuses on analyzing and determining the alternatives for the control of detection of the pandemic, through the processing of the neutrosophic TOPSIS method. It offers many benefits in the analysis of neutralities to the study of indeterminacies in the field of Medicine. The processing using neutrosophic methods allowed obtaining the best alternative to fight against COVID-19.
Read MoreDoi: https://doi.org/10.54216/IJNS.1803019
Vol. 18 Issue. 3 PP. 218-226, (2022)
Sentiment analysis (SA) is mainly employed to investigate the polarity of the sentiment existent in a content. It assist in understanding the opinions or feelings expressed by people. It find useful in several application areas such as e-commerce, education, etc. Natural language processing (NLP) and machine learning tools can be employed for SA. In this view, this study develops a Single Valued Neutrosophic Sets with Optimal Support Vector Machine (SVNS-OSVM) model for SA. The major intention of the SVNS-OSVM model is to identify the existence of sentiments exist in the data. The SVNS-OSVM model initially performs data pre-processing to transform the input data into a useful format. In addition, SVNS model is applied to derive word embeddings. Then, SVM model is applied for the detection and classification of sentiments. At the last level, the improved particle swarm optimization (IPSO) algorithm is used to fine tune the parameters involved in the SVM model. For ensuring the improved outcomes of the SVNS-OSVM model, a wide range of simulations were performed and the results are inspected under several aspects. The comparative study highlighted the betterment of the SVNS-OSVM model compared to recent approaches.
Read MoreDoi: https://doi.org/10.54216/IJNS.1803020
Vol. 18 Issue. 3 PP. 227-237, (2022)
According to experts, the blockchain is very suitable for supply chains, as it streamlines processes and reduces their complexity. Both the pharmaceutical and health sectors can take advantage of their potential since, having different intermediaries, processes can become inefficient on many occasions. Blockchain contributes to bringing order and automation. The pharmaceutical sector has been one of the ones that have obtained the most advantages from this technology. Getting a drug out of the box is a long and expensive process that can take a long time between studies and clinical trials and all the regulations. However, if it is possible to gather all the information needed to complete the process of bringing a new drug to light so that it is available immediately and with all the safety guarantees and improve its management, speed up the process. Therefore, blockchain is the most appropriate technology, although the ability to government bodies to recognize the network's benefits is hampered. This study is focused on determining the level of integration of Blockchain technology in the health sector, and the level of acceptance and contradiction in the adoption of the new technology in the community through the application of the neutrosophic Iadov method.
Read MoreDoi: https://doi.org/10.54216/IJNS.1803015
Vol. 18 Issue. 3 PP. 177-188, (2022)
The COVID-19 pandemic has affected the presence of students in the classroom, especially in medical schools where the practice is essential to gain skills. Virtual teaching or e-learning has emerged as the answer to that problem in this environment. Despite its many advantages, this process has faced different problems that have been overcome thanks to success factors. Considering the need to search for quality in medical schools in Ecuador, a study was carried out on those applied factors that have contributed to guaranteeing the quality of the teaching-learning process. That is the main objective of this research, supported by the bibliographic search and Plithogeny. It can be concluded that the highest level of impact has been made possible by the combination of the correct use of Information and Communication Technologies with adequate teacher training.
Read MoreDoi: https://doi.org/10.54216/IJNS.1803016
Vol. 18 Issue. 3 PP. 189-198, (2022)
This study is based on conducting surveys and multicriteria decision methods to determine the main factors influencing youth violence in Ecuador. To do this, a sample made up of young perpetrators of various types of crimes and other agents involved in the process in the city of Guayaquil is analyzed. The analysis carried out is based on the use of the DEMATEL method in its neutrosophic version so that the indeterminacies of the real world can be handled. The result obtained reveals that the factors with the highest incidence in youth violence in the analyzed sample are substance abuse or delinquency by parents, poor surveillance and supervision of children by parents, poor disciplinary practices, and emotional deficiencies of the parents, as well as exposure to domestic violence. It is recommended that prevention actions to minimize the proliferation of youth violence focus on these aspects for greater optimization of the results.
Read MoreDoi: https://doi.org/10.54216/IJNS.1803017
Vol. 18 Issue. 3 PP. 199-207, (2022)