Impact of mental health by Covid-19 on the collaborators of Peruvian companies

Mental health is a growing problem worldwide and Peru is no exception. The lack of adequate management from public health policies translates into little visibility of the problem and poor attention to it. In this sense, the pandemic has been a catalyst for the problem, due to the fear of contagion, work concerns, economic problems, the lack of a work/life balance, family difficulties, as well as the lack of recreation spaces. and bloating, have come together to significantly raise levels of stress, anxiety and depression. This research will analyze the impact that Covid-19 has been having on the mental health of employees, reporting descriptive and inferential results compiled through the psychological pulse tool, which represents a practical and effective measure for the measurement of mental health indicators. During 2020-2021, we analyzed 12, 000 workers from 400 Peruvian companies, probing an increase in stress and anxiety levels compared to pre COVID-19 periods. The joint impact of COVID-19 and remote work on mental health and present proposals to reduce its incidence. © 2022 Latin American and Caribbean Consortium of Engineering Institutions. All rights reserved.

Long-term Time Series Data Clustering of Stock Prices for Portfolio Selection

In this paper, clustering for stock data is conducted with two clustering methods, k-Shape and k-means with DTW distance measure and the results are compared. The data is the top 129 global electronics manufactures' stock prices from 2018 to 2020 which included the worst Christmas in 2018 and the beginning of COVID-19 outbreak. The involved countries are US, China, Taiwan, Korea, Japan and some others. The clustering results by k-Shape indicate distinctively different effects on those countries' stock markets due to the COVID-19 turmoil. The patterns of the clusters can be visualized to identify the differences among the clusters. We found that each of eight clusters comprises of the same country companies. From that, we could guess that investors or their algorithms tend to invest in companies according to its country rather than the individual company's performance. © 2021 IEEE.

Position sensing for surgical robots using time of flight sensor

Since the spread of COVID 19 worldwide, information and communication technology has been accelerating in the medical field. It is easy to switch to online medical interviews, but it is difficult to go online for biological examinations and surgical procedures. Therefore, there is an increasing demand for automatic handling of living organisms in the medical and bioengineering fields. Although surgical robots, such as the da Vinci, reduces labor, it is necessary to accurately measure the position and posture of organs and blood vessels for complete automation, and such technology has not been applied to surgical robots. There are methods for creating a three dimensional model of an organ by measuring it beforehand using magnetic resonance imaging or computed tomography, and to reflect the information during surgery by using augmented reality and other methods. However, there is currently no technology for automatically determining the position of organs and blood vessels in real time during surgery. To automate the grasping motion of a forceps type manipulator used with surgical robots, we applied a time of flight, ToF, sensor to obtain the position and orientation of a blood vessel. We developed a method for detecting blood vessels from the points measured using a ToF sensor and estimating their thicknesses and directions. We evaluated the effectiveness of our method in an experiment involving a simulated blood vessel. © 2021 Proceedings of the 21st International Conference of the European Society for Precision Engineering and Nanotechnology, EUSPEN 2021. All rights reserved.