The use of Mathcad in the educational process of the University for students of economics

In this article the author examines the use of Mathcad in the learning process of students of economics in the study subjects for the development of modern computer technology and software. Using Mathcad system plays an important role in solving the problems of traditional engineering and economic, as well as in solving mathematical programming problemsВ статье авторами рассматривается использование системы Mathcad в учебном процессе студентов экономических специальностей при изучении дисциплин по освоению современных компьютерных технологий и программных средств. Использование системы Mathcad играет огромную роль при решении традиционных задач инженерно-экономического характера, а также при решении задач математического программировани

Role of intranet-technologies in improvingthe quality of education

In this paper the authors consider the use of computer networks (LANs) at the University in teaching subjects in the study for the development of modern computer technologies and software tools used in applied fields. Using the LAN plays an important role in monitoring students' knowledge, the teacher has the opportunity more fully and accurately assess the student's knowledgeВ статье авторами рассматривается использование компьютерных сетей (ЛВС) университета в учебном процессе при изучении дисциплин по освоению современных компьютерных технологий и программных средств, используемых в прикладных отраслях. Использование ЛВС играет огромную роль при контроле знаний студентов, преподаватель имеет возможность более полно и качественно оценить знания студент

Drivers of tropical forest loss between 2008 and 2019

During December 2020, a crowdsourcing campaign to understand what has been driving tropical forest loss during the past decade was undertaken. For 2 weeks, 58 participants from several countries reviewed almost 115 K unique locations in the tropics, identifying drivers of forest loss (derived from the Global Forest Watch map) between 2008 and 2019. Previous studies have produced global maps of drivers of forest loss, but the current campaign increased the resolution and the sample size across the tropics to provide a more accurate mapping of crucial factors leading to forest loss. The data were collected using the Geo-Wiki platform (www.geo-wiki.org) where the participants were asked to select the predominant and secondary forest loss drivers amongst a list of potential factors indicating evidence of visible human impact such as roads, trails, or buildings. The data described here are openly available and can be employed to produce updated maps of tropical drivers of forest loss, which in turn can be used to support policy makers in their decision-making and inform the public

Layered system deformation determination: materials rheological properties consideration

The author proposes a solution for the problem of pavement and roadbed deformation determination considering the rheological properties of materials, based on the mathematical elasticity theory and creep theory problems solving, using the mathematical models of the processes to be investigated. The time coordinate integral transformation was applied to solve the problem

Crowdsourcing deforestation in the tropics during the last decade: Data sets from the “Driver of Tropical Forest Loss” Geo-Wiki campaign

The data set is the result of the Drivers of Tropical Forest Loss crowdsourcing campaign. The campaign took place in December 2020. A total of 58 participants contributed validations of almost 120k locations worldwide. The locations were selected randomly from the Global Forest Watch tree loss layer (Hansen et al 2013), version 1.7. At each location the participants were asked to look at satellite imagery time series using a customized Geo-Wiki user interface and identify drivers of tropical forest loss during the years 2008 to 2019 following 3 steps: Step 1) Select the predominant driver of forest loss visible on a 1 km square (delimited by a blue bounding box); Step 2) Select any additional driver(s) of forest loss and; Step 3) Select if any roads, trails or buildings were visible in the 1 km bounding box. The Geo-Wiki campaign aims, rules and prizes offered to the participants in return for their work can be seen here: https://application.geo-wiki.org/Application/modules/drivers_forest_change/drivers_forest_change.html . The record contains 3 files: One “.csv” file with all the data collected by the participants during the crowdsourcing campaign (1158021 records); a second “.csv” file with the controls prepared by the experts at IIASA, used for scoring the participants (2001 unique locations, 6157 records) and a ”.docx” file describing all variables included in the two other files. A data descriptor paper explaining the mechanics of the campaign and describing in detail how the data was generated will be made available soon