Friday, February 21, 2020

GEOGRAPHIC INFORMATION SYSTEMS (GIS) Essay Example | Topics and Well Written Essays - 1000 words

GEOGRAPHIC INFORMATION SYSTEMS (GIS) - Essay Example This, through my lasting experience and interaction with various GIS software, I believe can be achieved at relatively low cost than expected. Using the GIS information in transportation, I believe can be of great help to city planning and organization. In respect to this, I can assure you the effective use of the following GIS applications in doing the following activities with the aim of restoring order and cost in the city. The GIS tool can be used in spatial analysis to locate areas of preference for various development activities at relatively lower costs compared to the other software. High costs are often incurred while constructing bridges, railway lines and roads within the city and beyond, especially when other tools are used in designing these channels. However, using GIS, we can analysis the spatial characteristics of the regions to be bypassed by these projects for reduced cost of construction. For instance, it is easier to design the routes for road, railways and water pipes construction by developing different elevation models on the GIS software. Assessing and accurately analyzing this data can then help us in coming up with the correct route for construction with minimum costs involved. In order to illustrate this using an example, it is often very difficult to construct roads and railway lines where the process has to involve cutting through a mountain or in a region with rugged terrain. in such Cases, many culverts and bridges, have to be constructed as these increases the costs of construction. By overlaying the elevation data on the GIS software, we can easily locate the various points to be avoided by the project, calculate the relative distance and costs involved and compare the results for better decision making before the actual process. This aids in proper planning and management of funds are hence very

Wednesday, February 5, 2020

Review on Data impediments to empirical work on health insurance Article

Review on Data impediments to empirical work on health insurance markets paper - Article Example it is found out that majority of the publicly available sources of data, that is commonly used by researchers are to carry out their study on the health insurance market shares, is unreliable. These data sources are said to portray great variability over the years and are relative to both a rational prior and to the inconsistency demonstrated in the health sectors discharge data. These data sources assume merger activities from specialized and from high professional findings. Their unreliability to the studying competition in the health insurance sector is revealed in their character to omit significant components of the market. Such omitted components may include the self-insured health plans. The article considers the private insurance industry that plays a more significant role in the health care sector in the United States. A large number of individuals in U.S purchase private insurance plans. Another significant number of individuals are covered through Medicaid while they are still enrolled in the private plans. The article compared the elderly people in U.S to the nonelderly. It was revealed that majority of the nonelderly individuals opt for the private insurance plans while 95 % of the elderly people are enrolled to the Medicare. Although a few numbers of the nonelderly are enrolled to the Medicaid, they are also found to have enrolled into the private plans. Only a quarter of the elderly people opt for the private insurance plans (Leemore et al. 11). According to this paper, the antitrust analysts and researchers cannot generate an accurate empirical analysis of competition in the health insurance industry through the use of a readily available market share data. These differences in shares and the concentration reported within different data sources would force researchers to choose among the competing data sets. The doubtfully high unpredictability within the data sets suggests