초록 ▼

A time synchronization device and method is provided for synchronizing an internal clock of the power monitor. The internal clock may be adjusted to a periodically stable frequency according to a calculated counting error. Also, a time of the internal clock may be synchronized to a universal time, t

A time synchronization device and method is provided for synchronizing an internal clock of the power monitor. The internal clock may be adjusted to a periodically stable frequency according to a calculated counting error. Also, a time of the internal clock may be synchronized to a universal time, the time of the internal clock advancing at a determined rate. The determined rate may be adjusted if the internal time differs from the universal time plus a processing time.

대표청구항 ▼

A time synchronization device and method is provided for synchronizing an internal clock of the power monitor. The internal clock may be adjusted to a periodically stable frequency according to a calculated counting error. Also, a time of the internal clock may be synchronized to a universal time, t

A time synchronization device and method is provided for synchronizing an internal clock of the power monitor. The internal clock may be adjusted to a periodically stable frequency according to a calculated counting error. Also, a time of the internal clock may be synchronized to a universal time, the time of the internal clock advancing at a determined rate. The determined rate may be adjusted if the internal time differs from the universal time plus a processing time. tions with decreasing specificity. Data from the various levels may be compared, as well as data between individual categories. In some embodiments, selected multimedia data may be accessed based on criteria from data options of the patient descriptive categories. on address when executed by the processor. 12. A method for implementing a branch operation comprising: detecting a branch prediction instruction; identifying an associated branch instruction from a link provided in the branch predict instruction; and determining a predicted branch direction according to a hint provided in the branch predict instruction. 13. The method of claim 12, further comprising storing a target address specified in the branch predict instruction at a storage location indicated by the associated branch instruction. 14. The method of claim 12, wherein determining the predicted branch direction comprises: initiating a dynamic branch prediction algorithm when the hint is in a first state; and identifying a static branch prediction in the branch predict instruction otherwise. 15. The method of claim 13, further comprising storing the target address and a predicted branch direction at a location indicated by the associated branch instruction. nd secure environment is a network. 14. The method claimed in claim 6 wherein the first and second secure environments are interconnected by an Internet. patient data comprising: selecting patient data from data options in at least two categories including clinical presentation, pathology, anatomy, treatment and outcome, the data options of each category being arranged within tables in a relational database by decreasing levels of specificity in a hierarchical tree; storing the patient data with a unique identifier to relate the patient data within a data set, each data set being for a different patient; entering at least one criterion for at least one category; and retrieving the patient data for all data sets in a group matching the criterion. 10. The method of claim 9, further comprising the steps of calculating the total number of particular patient data and displaying the total number. 11. The method of claim 9, wherein the categories further include a provider category and at least one of the criteria is for particular data from the provider category. 12. The method of claim 9, wherein the particular patient data is associated with criteria from at least two of the categories. 13. The method of claim 12, wherein the particular patient data are associated with criteria from at least the treatment and outcome categories. 14. The method of claim 9, wherein at least one of the data options in at least one of the categories is related to custom perspective data in a custom screen table. 15. The method of claim 9, further including the step of retrieving multimedia data related to the particular patient data by the identifier. 16. The method of claim 9, wherein the selecting of patient data is by pointing to a location on a graphic representation of an anatomy. 17. The method of claim 9, wherein the data sets of the retrieved patient data matches criterion from the selected criterion and criterion from lower levels of the hierarchical tree. 18. A medical information system for patient data analysis comprising: A) a processor B) an input device in communication with the processor for receiving patient data; C) a storage unit in communication with the processor having a relational database for: (i) storing data within option category tables by decreasing levels of specificity in a hierarchical tree, the data option category tables selected from the group consisting of clinical presentation, pathology, anatomy, treatment and outcome, and (ii) storing patient data of data sets, each data set being for a different patient and having a unique identifier within category tables, the patient data being chosen from the data options in at least one option category table, the processor comprising: (i) a means for receiving patient data from the input and storing the patient data in the storage unit; (ii) a means for receiving instructions from the input entering at least one criterion for patient data from at least one category table; and (iii) a means for retrieving the entered patient data for all data sets in a group matching the criterion. 19. The system of claim 18, wherein the medical data includes multimedia data. 20. The system of claim 18, further comprising a display in communication with the processor. 21. The system of claim 18, wherein at least one data option is related to custom prospective data in a custom screen table. 22. A computer readable medium having stored therein a plurality of sequences of instructions, which, when executed by a processor, cause the processor to: receive medical patient data of a data set from an input device, the patient data being a selected data option from a hierarchical tree having data options arranged in decreasing levels of specificity and each data set being for a different patient; determine whether the patient data includes an identifier and if no identifier is present, attach a unique identifier to the patient data; store the patient data in a relational database within tables of categories selected from the group consisting of clinical presentation, pathology, anatomy, treatment and outcome; and respon sive to instructions received from the input device, retrieve particular patient data for all data sets in a group matching entered criterion. 23. The computer readable medium of claim 22, further including additional sequences of instructions, which, when executed by the processor, cause the processor to calculate the total number of particular patient data and displaying the total number. 24. The computer readable medium of claim 22, wherein the particular patient data are from at least two of the categories. 25. The computer readable medium of claim 22, wherein the patient data is stored in a custom screen table related to at least one of the data options. 26. The computer readable medium of claim 22, wherein the particular patient data includes multimedia data. 27. Computer readable instructions, which when executed cause a processor to: receive medical patient data of a data set from an input device, the patient data being a selected data option from a hierarchical tree having data options arranged in decreasing levels of specificity and each data set being for a different patient; determine whether the patient data includes an identifier and if no identifier is present, attach a unique identifier to the patient data; store the patient data in a relational database within tables of categories selected from the group consisting of clinical presentation, pathology, anatomy, treatment and outcome; and responsive to instructions received from the input device, retrieved particular patient data for all data sets in a group matching entered criterion. 28. The computer readable instructions of claim 27, further including additional sequences of instructions, which,.when executed by the processor, cause the processor to calculate the total number of particular patient data and displaying the total number. 29. The computer readable instructions of claim 27, wherein the particular patient data are from at least two of the categories. 30. The computer readable instructions of claim 27, wherein the particular patient data includes multimedia data. 31. A medical patient data analysis server comprising: A) a network interface for acquiring patient data of a data set from a network, each data set being for a different patient, and sending selected portions of the patient data into the network, the patient data being at least one chosen data option from a hierarchical category tree having data options arranged in decreasing levels of specificity; B) a storage unit coupled to receive the patient data from the data interface and to store the patient data within tables of categories selected from the group consisting of clinical presentation, pathology, anatomy, treatment, and outcome and the patient data of a data set having a unique identifier; C) an assembly unit coupled to the network interface and storage unit to gather selected portions of the patient data in response to instructions from a user station for all data sets in a group matching entered criterion. 32. The server of claim 31, further comprising an activated unit for determining whether patient data was received by the user station sending instructions for selected portions of patient data. 33. The server of claim 31, wherein the patient data includes multimedia data. 34. A medical patient data analysis user station comprising: A) an input device for receiving patient data; B) a processor comprising: i) means for receiving patient data from the input device, the patient data being a chosen data option from a category having a hierarchical tree of data options arranged in decreasing levels of specificity, the category selected from the group including clinical presentation, pathology, anatomy, treatment and outcome, and ii) means for forming instructions by selecting at least one criterion from at least one of the categories; and C) a browser for sending the instructions and the patient data into a network and receiving selected portions of patient d