Author: claimsbot

1. A method of validating a calibration factor for a material flow, comprising the steps of:
defining at least one density at a reference temperature of said material flow;
determining a compensated line density and a line temperature of said material flow, wherein the step of determining the compensated line density includes temperature compensating a line density by determining the line density when said line temperature corresponds to said reference temperature; and
detecting an error condition, wherein the step of detecting an error condition includes comparing said compensated line density to the at least one density.
2. The method according to claim 1, wherein said at least one density includes upper and lower limits for said compensated line density.
3. The method according to claim 2, wherein said upper and lower limits are determined by determining a reference density for said material flow at said reference temperature and selecting said upper and lower limits so that the reference density is between said upper and lower limits.
4. The method according to claim 1, wherein said at least one density is a reference density for said material flow that is determined at the reference temperature.
5. The method according to claim I, further comprising the steps of:
measuring the line pressure of said material flow;
determining a pressure compensation factor for said material flow; and
wherein the step of determining the compensated line density includes the step of compensating said temperature compensated line density using said pressure compensation factor.
6. The method according to claim 5, wherein said step of determining the pressure compensation factor includes the steps of:
determining the ratio of changes in density to changes in pressure;
determining a pressure difference between said line pressure and a reference pressure; and
multiplying said ratio by said pressure difference to obtain said pressure compensation factor.
7. The method according to claim 5, further comprises the steps of:
measuring the material composition of said material flow;
determining a material composition compensation factor for said material flow; and
wherein the step of determining the compensated line density includes the step of compensating said temperature and pressure compensated line density using said material composition compensation factor.
8. The method according to claim 1, further comprising the steps of:
measuring the material composition of said material flow;
determining a material composition compensation factor for said material flow; and
wherein the step of determining the compensated line density includes the step of compensating said temperature compensated line density using said material composition compensation factor.
9. The method according to claim 8, further comprising the steps of:
measuring the line pressure of said material flow;
determining a pressure compensation factor for said material flow; and
wherein the step of determining the compensated line density includes the step of compensating said material composition and temperature compensated line density using said pressure compensation factor.
10. A computer program product comprising computer usable medium including executable code for executing a process comprising the steps of:
defining at least one density at a reference temperature of a material flow;
determining a compensated line density and line temperature of said material flow, wherein the step of determining the compensated line density includes temperature compensating a line density by determining the line density when said line temperature corresponds to said reference temperature; and
detecting an error condition, wherein the step of detecting an error condition includes comparing said compensated line density to the at least one density.
11. The computer program product according to claim 10 wherein said at least one density includes upper and lower limits for said compensated line density.
12. The computer program product according to claim 11 wherein said upper and lower limits are determined by determining a reference density for said material flow at said reference temperature and selecting said upper and lower limits so that the reference density is between said upper and lower limits.
13. The computer program product according to claim 10 wherein said at least one density is a reference density for said material flow that is determined at the reference temperature.
14. The computer program product according to claim 10, wherein said process further comprises the steps of:
measuring the line pressure of said material flow;
determining a pressure compensation factor for said material flow; and
wherein the step of determining the compensated line density includes the step of compensating said temperature compensated line density using said pressure compensation factor.
15. The computer program product according to claim 14 wherein said pressure compensation factor is formed by the steps of:
determining the ratio of changes in density to changes in pressure;
determining a pressure difference between said line pressure and a reference pressure; and
multiplying said ratio by said pressure difference to obtain said pressure compensation factor.
16. The computer program product according to claim 14, wherein said process further comprises the steps of:
measuring the material composition of said material flow;
determining a material composition compensation factor for said material flow; and
wherein the step of determining the compensated line density includes the step of compensating said temperature and pressure compensated line density using said material composition compensation factor.
17. The computer program product according to claim 10 characterised in that said method further comprises the steps of:
measuring the material composition of said material flow;
determining a material composition compensation factor for said material flow; and
wherein the step of determining the compensated line density includes the step of compensating said temperature compensated line density said material composition compensation factor.
18. The computer program product according to claim 17, wherein said process further comprises the steps of:
measuring the line pressure of said material flow;
determining a pressure compensation factor for said material flow; and
wherein the step of determining the compensated line density includes the step of compensating said material composition and temperature compensated line density using said pressure compensation factor to derive the compensated line density that has been compensated for material composition, pressure, and temperature.

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 computer implemented method for determining a state of stability of an electrical grid having n nodes, comprising the steps of:
a. embedding load flow equations (L) representing the electrical grid in a holomorphic embedding (L(s)) where s is a variable in a complex domain that includes a value s=0 corresponding to a no load case (L(0)), in which all voltages are equal to a normal or designed voltage level and there is no energy flow in links of the electrical grid and the value s=1 corresponding to an objective case (L(1)) representative of the electrical grid in a condition for which stability is to be determined, wherein each variable of the load flow equations (L) is contained in L(s) as a function of the complex variable s by said holomorphic embedding, and transcribing the holomorphic embedding into software for use in a computer processor adapted to execute said software;
b. developing in power series, values of unknowns in parameters of the holomorphic embedding (L(s)), using said computer processor, wherein the values of s are in a neighborhood of the value for the no load case of each parameter of the load flow equations;
c. using said computer processor to compute an n-order algebraic approximant to the power series produced in step b;
d. said computer processor evaluating the n-order algebraic approximant produced in step c for the power series produced in step b to provide a solution to the load flow equations (L); and
e. displaying the solution to the load flow equations as a measure of a state of stability of the electrical grid.
2. The method of claim 1, further comprising the steps of:
prior to said embedding step, receiving data from a supervisory and data acquisition system representative of conditions of the electrical grid, and forming said load flow equations (L) from said data.
3. The method of claim 2, further comprising the steps of repeating said receiving step and steps a through e continuously to provide a continuous, real time estimation of the state of stability of the electrical grid.
4. The method of claim 3, further comprising the steps of confirming that a set of voltages and flows contained in said solution to said load flow equations (L) are representative of a physical electrical state.
5. A computer implemented method of measuring load flow in a power generating system having an electrical grid comprised of n nodes, comprising the steps of:
a. embedding load flow equations (L) representing the electrical grid in a holomorphic embedding (L(s)) where s is a variable in a complex domain that includes a value s=0 corresponding to a no load case (L(0)), in which all voltages are equal to a normal or designed voltage level, and there is no energy flow in links of the electrical grid and the value s=1 corresponding to an objective case (L(1)) representative of the electrical grid in a condition for which stability is to be determined, wherein each variable of the load flow equations (L) is contained in L(s) as a function of the complex variable s by said holomorphic embedding, and transcribing the holomorphic embedding into software for use in a computer processor adapted to execute said software;
b. developing in power series, values of unknowns in parameters of the holomorphic embedding (L(s)), using said computer processor, wherein the values of s are in a neighborhood of the value for the no load case of each parameter of the load flow equations;
c. using said computer processor to compute an n-order algebraic approximant to the power series produced in step b;
d. said computer processor evaluating the n-order algebraic approximant produced in step c for the power series produced in step b to provide a solution to the load flow equations (L); and
e. displaying the solution to the load flow equations as a measure of the load flow in the power generating system.
6. The method of claim 5, further comprising the steps of:
prior to said embedding step, receiving data from a supervisory and data acquisition system representative of conditions of the electrical grid, and forming said load flow equations (L) from said data.
7. The method of claim 6, further comprising the steps of repeating said receiving step and steps a through e continuously to provide a continuous, real time measure of the load flow in the power generating system.
8. A system for measuring load flow in a power generating system having an electrical grid having n nodes, said system comprising:
a supervisory control and data acquisition system adapted to collect data from said electrical grid indicative of electrical conditions in said electrical grid, said supervisory control and data acquisition system being in communication with a microprocessor-controlled energy management system, said energy management system further comprising executable computer instructions to:
a. process said data received from said supervisory control and data acquisition system into load flow equations (L) representing the electrical grid;
b. embed said load flow equations (L) representing the electrical grid in a holomorphic embedding (L(s)) where s is a variable in a complex domain that includes a value s=0 corresponding to a no load case (L(0)), in which all voltages are equal to a normal or designed voltage level and there is no energy flow in links of the electrical grid and the value s=1 corresponding to an objective case (L(1)) representative of the electrical grid in a condition for which stability is to be determined, wherein each variable of the load flow equations (L) is contained in L(s) as a function of the complex variable s by said holomorphic embedding;
c. develop in power series, values of unknowns in parameters of the holomorphic embedding (L(s)) wherein the values of s are in a neighborhood of the value for the no load case of each parameter of the load flow equations;
d. compute an n-order algebraic approximant to the power series produced in step c;
e. evaluate the n-order algebraic approximant produced in step d for the power series produced in step c to provide a solution to the load flow equations (L); and
f. display the solution to the load flow equations as a measure of a state of stability of the electrical grid.

1. An integrated infrared (IR) and full color complementary metal oxide semiconductor (CMOS) imager array comprising:
a lightly doped p doped silicon (Si) substrate;
a plurality of pixel cells, each pixel cell including:
at least one visible light detection pixels, each pixel including a moderately p doped bowl with a bottom p doped layer and p doped sidewalls, an n doped layer enclosed by the p doped bowl, a moderately p doped surface region overlying the n doped layer, and a transfer transistor with a gate electrode overlying the p doped sidewalls, a source formed from the n doped layer, and an n+ doped drain connected to a floating diffusion region;
an IR pixel including moderately p doped sidewalls, an n doped layer enclosed by the p doped sidewalls, a lightly p doped layer of p doped substrate underlying the n doped layer, a moderately p doped surface region overlying the n doped layer, and a transfer transistor with a gate electrode overlying the p doped sidewalls, a source formed from the n doped layer, and an n+ doped drain connected to the floating diffusion region; and,

an optical wavelength filter overlying the visible light and IR pixels.
2. The array of claim 1 wherein the bottom p doped layer of each visible light pixel is formed at a first depth, and wherein the n doped layers of each visible light pixel and the IR pixel are formed at a second depth.
3. The array of claim 1 wherein the pixel cell includes at least three visible light pixels include a first pixel, and second pixel, and a third pixel; and,
wherein the optical wavelength filter includes a first filter section transmitting a first wavelength of light in the visible spectrum and IR wavelengths, overlying the first pixel, a second filter section transmitting a second wavelength of light in the visible spectrum and the IR wavelengths, overlying the second pixel, a third filter section transmitting a third wavelength of light in the visible spectrum and the IR wavelengths, overlying the third pixel, and a fourth filter section transmitting IR wavelengths overlying the IR pixel.
4. The array of claim 3 wherein each visible light pixel includes a lightly p doped layer of the p doped substrate interposed between a top surface of the bottom p doped layer and a bottom surface of the n doped layer.
5. The array of claim 1 wherein the p doped Si substrate is an epitaxial layer having a thickness of at least 10 microns; and,
the array further comprising:
a lightly n doped substrate underlying the p doped Si epitaxial layer.
6. The array of claim 1 wherein at least one visible light detecting pixel and the IR pixel share a four transistor active pixel sensor (APS) with a common select transistor, a common reset transistor, a common follower transistor, and a common floating diffusion region.

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 method comprising:
receiving a stream of data packets at a first node in a multi-node data processing chain;
identifying when any of the received packets are lost;
generating a lost tally data packet at a specified interval;
downloading the lost tally data packet to the processing chain; and
collecting data obtained from data packets output downstream in the processing chain.
2. The method of claim 1, wherein the step of identifying comprises:
determining an insufficient storage capacity for handling an incoming packet;
marking the incoming packet as lost; and
discarding the incoming packet from the processing chain.
3. The method of claim of claim 1, wherein the step of generating comprises:
counting the number of lost packets during the specified interval; and
including count information in the lost tally data packet.
4. The method of claim 3, further comprising:
initiating a new count interval upon generation of the lost tally data packet.
5. The method of claim 1, wherein the step of downloading comprises:
inserting the generated lost tally data packet into a queue for output to the data stream upon generation thereof if sufficient storage capacity currently exists; and
delaying insertion of the generated lost tally data packet into the queue if there is insufficient storage capacity.
6. The method of claim 1, wherein the received data packets contain Positron Emission Tomography (PET) coincident event data, input at a variable rate.
7. The method of claim 6, further comprising:
receiving data packets at a second node, downstream of the first node in the data processing chain;
identifying when any of the received packets at the second node are lost;
generating a lost tally data packet for packets lost at the second node; and
downloading the lost tally data packet to the processing chain;
wherein the step of collection further comprises adding information obtained from the lost tally data packets generated at the second node to the data obtained from data packets output by the first node.
8. The method of claim 7, wherein the step of collecting further comprises specifying a data collection interval; the method further comprising:
formulating a correction factor value in accordance with a number of lost tally packets received during the data collection interval.
9. The method of claim 8, wherein the step of formulating comprises evaluating the collected lost packet information for each of the nodes.
10. A system comprising:
a gantry interface module for receiving coincident event data from a PET (Positron Emission Tomography) detector array, the interface module comprising a first FPGA (field programmable gate array) connected to a first FIFO storage;
a DMA (direct memory access) rebinner card comprising a second FPGA (field programmable gate array) connected to a second FIFO storage; and
a transmission line coupled between an output of the first FPGA and an input of the second FGA;
wherein the first FPGA is configured to receive a stream of data packets, determine when the first FIFO storage has insufficient capacity to store a received packet, discard the received packet as lost, and maintain a tally of lost packets.
11. The system of claim 10, wherein the first FPGA comprises first and second counters, and the first FGPA is configured to increment the first counter with each reception of a data packet and to increment the second counter with each determination of a lost packet.
12. The system of claim 11, wherein the first FPGA is configured to generate a lost tally data packet, related to contents of the second counter, at an interval set by the first counter.
13. The system of claim 12, wherein the first FPGA is configured to store the lost tally data packet in the first FIFO when sufficient storage capacity exists therein and to output the lost tally data packet to the transmission line.
14. The system of claim 10, wherein the second FPGA is configured to receive a stream of data packets, determine when the second FIFO storage has insufficient capacity to store a received packet, discard the received packet as lost, and maintain a tally of packets lost at the second FPGA.
15. The system of claim 14, wherein the second FPGA comprises third and fourth counters, and the second FGPA is configured to increment the third counter with each reception of a data packet and to increment the fourth counter with each determination of a lost packet by the second FGPA.
16. The system of claim 15, wherein the second FPGA is configured to generate a lost tally data packet, related to contents of the fourth counter, at an interval set by the third counter.
17. The system of claim 16, wherein the second FPGA is configured to store the lost tally data packet generated by the second FPGA in the second FIFO when sufficient storage capacity exists therein.
18. The system of claim 17, wherein the DMA rebinner card is configured to specify a data collection interval and formulate a correction factor value in accordance with a number of lost tally packets received during the data collection interval.
19. The system of claim 18, wherein the correction factor is based on evaluation of the collected lost packet information for each of the first and second FPGAs.
20. The system of claim 10, wherein the transmission line comprises fiber optic cable.