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A technique for maintaining referential integrity between data records in any data architecture in which only a single copy is kept of any particular data record. The technique includes providing the ability to bind a data record to a parent data record by storing the data record in a manner associa

A technique for maintaining referential integrity between data records in any data architecture in which only a single copy is kept of any particular data record. The technique includes providing the ability to bind a data record to a parent data record by storing the data record in a manner associated with the parent record. If the data record then is bound to other parent data records, a link reference is used that is stored in an attribute of the data record, rather than associating another copy of the data record with the second parent data record. It is possible to bind any data record to any other data record, so circular relationships can be created. In addition, there are special methods used when a data record is to be deleted to make sure that all parents or children of that data record are considered, in order to update bind information or delete the children as may be appropriate.

대표청구항 ▼

A technique for maintaining referential integrity between data records in any data architecture in which only a single copy is kept of any particular data record. The technique includes providing the ability to bind a data record to a parent data record by storing the data record in a manner associa

A technique for maintaining referential integrity between data records in any data architecture in which only a single copy is kept of any particular data record. The technique includes providing the ability to bind a data record to a parent data record by storing the data record in a manner associated with the parent record. If the data record then is bound to other parent data records, a link reference is used that is stored in an attribute of the data record, rather than associating another copy of the data record with the second parent data record. It is possible to bind any data record to any other data record, so circular relationships can be created. In addition, there are special methods used when a data record is to be deleted to make sure that all parents or children of that data record are considered, in order to update bind information or delete the children as may be appropriate. connection with determining a health indicator (HI) of a component, such as that of an aircraft component. The HI is determined using condition indicators (CIs) which parameterize characteristics about a component minimizing possibility of a false alarm. Different algorithms are disclosed which may be used in determining one or more CIs. The HI may be determined using a normalized CI value. Techniques are also described in connection with selecting particular CIs that provide for maximizing separation between HI classifications. Given a particular HI at a point in time for a component, techniques are described for predicting a future state or health of the component using the Kalman filter. Techniques are described for estimating data values as an alternative to performing data acquisitions, as may be used when there is no pre-existing data. ered data; up sampling and inverse high pass filtering the discrete wavelet coefficients to produce sixth up sampled and filtered data; and summing the fifth and sixth up sampled and filtered data to produce the compensation data. 6. The vehicle navigation method of claim 5 wherein the performing of an inverse discrete wavelet transform comprises: performing the inverse discrete wavelet transform by column on the discrete wavelet coefficients to produce a matrix; and, performing the inverse discrete wavelet transform by row on the matrix to produce the compensation data. 7. The vehicle navigation method of claim 5 wherein the performing of an inverse discrete wavelet transform comprises: scaling the discrete wavelet coefficients; and, performing the inverse discrete wavelet transform on the scaled coefficients to produce the compensation data. 8. The vehicle navigation method of claim 7 wherein the performing of an inverse discrete wavelet transform comprises: performing the inverse discrete wavelet transform by column on the scaled coefficients to produce a matrix; and, performing the inverse discrete wavelet transform by row on the matrix to produce the compensation data. 9. The vehicle navigation method of claim 8 wherein the compensating of the sensor signal based on the compensation data comprises interpolating the compensation data. 10. The vehicle navigation method of claim 1 wherein the accessing discrete wavelet coefficients comprises performing a lossless decompression of the discrete wavelet coefficients, and wherein the performing of an inverse discrete wavelet transform comprises performing the inverse discrete wavelet transform on the decompressed coefficients to produce the compensation data. 11. The vehicle navigation method of claim 10 wherein the performing of an inverse discrete wavelet transform comprises: performing the inverse discrete wavelet transform by column on the decompressed coefficients to produce a matrix; and, performing the inverse discrete wavelet transform by row on the matrix to produce the compensation data. 12. The vehicle navigation method of claim 10 wherein the performing of an inverse discrete wavelet transform comprises: scaling the decompressed coefficients; and, performing an inverse discrete wavelet transform on the scaled coefficients to produce the compensation data. 13. The vehicle navigation method of claim 12 wherein the performing of an inverse discrete wavelet transform comprises: performing the inverse discrete wavelet transform by column on the scaled coefficients to produce a matrix; and, performing the inverse discrete wavelet transform by row on the matrix to produce the compensation data. 14. The vehicle navigation method of claim 10 wherein the performing of an inverse discrete wavelet transform comprises: up sampling and inverse low pass filtering the decompressed coefficients to produce first up sampled and filtered data; up sampling and inverse high pass filtering the decompressed coefficients to produce second up sampled and filtered data; summing the first and second up sampled and filtered data to produce first summed data; up sampling and inverse low pass filtering the first summed data to produce third up sampled and filtered data; up sampling and inverse high pass filtering the decompressed coefficients to produce fourth up sampled and filtered data; summing the third and fourth up sampled and filtered data to produce second summed data; up sampling and inverse low pass filtering the second summed data to produce fifth up sampled and filtered data; up sampling and inverse high pass filtering the decompressed coefficients to produce sixth up sampled and filtered data; and summing the fifth and sixth up sampled and filtered data to produce the compensation data. 15. The vehicle navigation method of claim 14 wherein the performing of an inverse discrete wavelet transform comprises: performing the inverse d