1. Process for determining the mechanical resistance of a bone from a digitized two dimensional image, obtained by imaging, characterized in that there is carried out a correlation between the bone mineral density determined from this two dimensional image by any means suitable to this type of image and a structural parameter obtained from the same two dimensional image.
2. Process for determining the mechanical resistance of a bone according to claim 1, characterized in that one has recourse to a correlation of the exponential type.
3. Process for determination according to claim 1, characterized in that the correlation associating the bone mineral density and said structural parameter is used to determine the ultimate stress Cu of the bone.
4. Process for determining the mechanical resistance of a bone according to any one of the preceding claims, characterized in that there is determined the structural parameter \u03b1 obtained by the series of the following steps:
a) choosing at random a pixel of the two dimensional image which is at the gray level h(O),
b) choosing a straight line from this point having a direction also determined at random,
c) moving a distance r along this straight line, h(r) being the gray level of this new point,
d) computing the variance of the gray levels with the formula: V(r)=h(r)\u2212h(O)2,
e) tracing the curve associated with V(r) on a log-log scale, and
f) determining the slope of this log-log curve which represents said parameter \u03b1.
5. Process for determining the mechanical resistance of a bone according to claim 4, characterized in that steps a) to d) are repeated a number of times sufficiently great to make the mean variance function V(r) converge over the assembly of the repetitions.
6. Process for determining the mechanical resistance of a bone according to claim 4, characterized in that there is carried out a correlation between the bone mineral density obtained from this two dimensional image and said parameter \u03b1 evaluated from the same two dimensional image according to the mathematical model:
Cu=b0+b1*exp (b2*DMO)*60
wherein b0, b1, b2 are coefficients obtained by nonlinear regression and Cu\u2032 the prediction of the ultimate stress Cu of the bone.
7. Process for determining the mechanical resistance of a bone according to claim 4, characterized in that there is determined a correlation between the parameter \u03b1 and a three dimensional parameter of the trabecular network of the bone.
8. Process for determining the mechanical resistance of a bone according to claim 7, characterized in that the three dimensional parameter of the trabecular network of the bone is the connectivity density \u03c7v
9. Process for determining the mechanical resistance of a bone according to claim 5, characterized in that there is carried out a correlation between the bone mineral density obtained from this two dimensional image and said parameter \u03b1 evaluated from the same two dimensional image according to the mathematical model:
Cu\u2032=b0+b1*exp (b2*DMO)*\u03b1
wherein b0, b1, b2 are coefficients obtained by nonlinear regression and Cu\u2032 the prediction of the ultimate stress Cu of the bone.
10. Process for determining the mechanical resistance of a bone according to claim 5, characterized in that there is determined a correlation between the parameter \u03b1 and a three dimensional parameter of the trabecular network of the bone.
11. Process for determining the mechanical resistance of a bone according to claim 6, characterized in that there is determined a correlation between the parameter \u03b1 and a three dimensional parameter of the trabecular network of the bone.
12. Process for determination according to claim 3, characterized in that the correlation associating the bone mineral density and said structural parameter is used to determine the ultimate stress Cu of the bone.
The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.
1. A geographic information system (GIS) comprising information about a plurality of geospatial entities and configured to prioritize the geospatial entities according to a ranking mechanism.
2. The system of claim 1, wherein the ranking mechanism uses data about a meta attribute of a geospatial entity to determine the geospatial entity’s priority.
3. The system of claim 2, wherein the meta attribute comprises one of: quality of information available about the geospatial entity, an attribute of a description of the geospatial entity, and an attribute of a definition of the geospatial entity.
4. The system of claim 2, wherein the meta attribute comprises an indicator of the geospatial entity’s popularity.
5. The system of claim 2, wherein the meta attribute comprises one of: an age attribute, a stature attribute, and an importance attribute.
6. The system of claim 2, wherein the meta attribute comprises a relationship of a geospatial entity to its place in a hierarchy of geospatial entities.
7. The system of claim 1, wherein an entity of the plurality of entities comprises a collection of geospatial objects and wherein the priority of the entity is determined responsive to a characteristic of the collection of geospatial objects.
8. The system of claim 1, wherein an entity of the plurality of entities comprises a geospatial entity defined in an on-line forum and wherein the ranking mechanism uses data generated in the on-line forum to determine the rank of the geospatial entity.
9. The system of claim 1, wherein the ranking mechanism uses data harvested from a website on the internet about a geospatial entity to determine the geospatial entity’s priority.
10. The system of claim 1, wherein the ranking mechanism determines a geospatial entity’s priority from a combination of weighted data from a plurality of meta attributes of the geospatial entity.
11. A computer-implemented method for ranking geospatial entities, the method comprising:
receiving geospatial entity data;
evaluating attributes of geospatial entities included in the received geospatial entity data;
ranking the geospatial entities based on the evaluation; and
storing the ranked geospatial entity data.
12. The method of claim 11, wherein the geospatial entity data comprises data generated in a community forum.
13. The method of claim 11, wherein the geospatial entity data comprises data associated with a specific user and further comprising using the ranked geospatial entity data to generate a map for the specific user.
14. The method of claim 11, further comprising selecting geospatial entities for a geographical display based on the rankings of the geospatial entities.
15. The method of claim 11, further comprising providing the ranked geospatial entity data to a map system configured to generate a map that includes ranked geospatial entities and unranked geospatial entities.
16. The method of claim 11, further comprising selecting geospatial entities to include in navigation instructions based on rankings of the geospatial entities.
17. The method of claim 11, further comprising selecting a geospatial entity to associate with an advertising term based on the geospatial entity’s ranking.
18. The method of claim 11, further comprising providing the ranked geospatial entity data to an application for generating a search result based on the ranked geospatial entity data.