Procedure a Take the measuring cylinder and measure its mass, in grams, as accurately as possible. Put the measuring cylinder back on the balance. Measure and record the new mass cylinder plus waterin grams. Then, for each volume calculate the mass of the liquid alone.
A non-linear visual space transformation corresponding to the graphical density is processed. Resolution in the area of the display is increased in response to the non-linear visual space transformation and the area is displayed with increased resolution. Field of the Invention The present invention relates to the field of visual and graphical displays for the representation of data.
Specifically, the present invention relates to a method for visualizing high density graphical data for display. Related Art Modern computer systems and other media for accessing and interacting with information typically display data visually in various graphical formats.
Visually displayed graphically formatted data is an important medium in many fields. These fields include electronically based commerce and business, also known as e-commerce and e-business, operations research, epidemiology, information technology IT network administration and engineering, and a wide-ranging host of others.
The are numerous examples of applications of visually displayed graphically formatted data in these fields. E-business relies heavily on market basket analysis and customer profiling.
IT depends on management of its various resources.
Further, e-commerce often tasks IT extensively, including management of its resources. Such practical fields rely on real world data, e. The field of e-commerce provides the following example of application of crucial real world data in market basket analysis. Market basket analysis has become a key success factor in e-commerce.
Effective market basket analysis methods employ association and clustering as methods of analyzing such data. E-commerce transactions often are comprised of several products e. Understanding these relationships across hundreds, even thousands of product lines and among millions of transactions provides visibility and predictability into product affinity purchasing behavior.
Contemporarily, some technologies allow the visualization of associations for commercial entities such as retail stores and others, to make business decisions, such as product recommendations, cross selling, store shelf arrangements, and a host of others.
Matrix display technique positions pairs of items on separate axes to visualize the strength of their relationships. One such association visualizer lays out the rules on a 3D grid landscape. Visual filtering and querying allow users to focus in on selected rules. However, to visualize many, sometimes millions of association rules, association matrixes are too restrictive.
The number of rules shown at the same time needs to be pre-decided. Further, the number of rules is limited to a small range, e. An alternative conventional technique involves laying out associations on a graph, as depicted in Prior Art FIG.
Such associations between these data are known in the art as edges. One such contemporary technology uses an individual purchase history to make suggestions to shoppers based on a graph.
However, when the number of items grows large, the graph can quickly become cluttered with many interactions, e. Also, associated items may not be placed close together, such that their edges graphically become tenuous. The market analysis graph of one contemporary technology has achieved some improvement by utilizing dynamic queries and presentations.
Besides their application in data associations, graph visualization methods have become useful in information visualization. One such technique uses cone trees and their hyperbolic projections.
These are utilized for web and file system visualization.
Another such technique uses fast graph layout to display various types of statistical data. A central approach to such graph visualization techniques exploits physics-based paradigms. Recent conventional techniques apply clustering algorithms to improve performance and scalability of such physics-based methods.
In spite of the advances in the field, it is still difficult to mine and visualize customer's purchasing behavior from millions of Internet transactions. As the volume of e-commerce data grows and as the transaction data is integrated into off-line data, new data visualization associations are required to extract useful and relevant information.
With such real world information, seldom is the data distribution uniform.Sep 20, · why would you use a graph to calculate density? Why is it better to use a graph of mass/volume to calculate density instead of doing out each individual calculation? Source(s): Calculating volume, mass and density.
HELP!? Urgent help with my density graph? Answer heartoftexashop.com: Resolved. To calculate the density of solids with irregular surfaces, volume must be determined by another method.
Instead of measuring the surface area directly, use a graduated cylinder to find the object's volume. To calculate density of an object, you need to know the mass and volume of the object.
Scientific Method Biochemistry Physical Chemistry Medical Chemistry Chemistry in Everyday Life Famous Chemists Activities for Kids Practice Calculating Molality with this Sample Problem.
See How to Calculate Specific Heat. Density and Graphical Analysis One common method of interpreting data is graphical analysis. In Part C of this lab, the mass and volume of several cylindrical pieces of an unknown solid material will be measured.
Once again mass will be obtained using an electronic balance, in grams (g). average density value by calculating your percent. Do you think density could help identify an unknown substance? Why?
Yes, I do think that you could find an unknown substance with the density. Only with accurate tools and precision. Also, because the water displacement method would help out a lot and you could find the density of the substance, then look it up on the erotic table or on the internet.
A method for visualizing high density graphical data sets for display is effectuated by determining the graphical density corresponding to an area of the display, where the graphical density is of a .