Author: claimsbot

1. A computer-implemented method for debugging counterexamples found in formal verification, the method comprising:
receiving, by using a computer, a trace that illustrates a behavior of a circuit design that violates a property defined for the circuit design;
selecting a set of explanatory points for the violated property, the explanatory points illustrating a portion of the trace of the counterexample that directly contributes to the violation of the property; and
displaying the trace of the counterexample to the user; and
displaying an indication of the explanatory points on the trace of the counterexample.
2. The method of claim 1, wherein the trace is for a counterexample identified for the circuit design during a formal verification process.
3. The method of claim 1, wherein the property is a covered property, and the trace is a cover trace comprising a counterexample to a negation of the covered property.
4. The method of claim 1, wherein the set of explanatory points is both sufficient and minimal.
5. The method of claim 1, wherein selecting a set of explanatory points for the violated property comprises:
identifying a plurality of sets of explanatory points; and
choosing one of the plurality sets of explanatory points that has the least difference between the earliest cycle and the failure point.
6. The method of claim 1, wherein selecting a set of explanatory points for the violated property comprises:
identifying a plurality of sets of explanatory points; and
choosing one of the plurality sets of explanatory points that contains the least number of points.
7. The method of claim 1, wherein the set of explanatory points includes at least one point that contributes to the triggering of the property and at least one point that contributes directly to the violation of the property.
8. The method of claim 1, wherein displaying an indication of the explanatory points comprises displaying the points that contribute to the triggering of the property differently than the points that contribute directly to the violation of the property.
9. The method of claim 8, wherein the points that contribute to the triggering of the property are displayed using a different color than the points that contribute directly to the violation of the property.
10. The method of claim 1, wherein displaying an indication of the explanatory points comprises displaying inessential points.
11. The method of claim 1, further comprising:
receiving a user selection of a cycle, wherein displaying the trace of the counterexample is responsive to the selected cycle.
12. The method of claim 1, further comprising:
displaying source code of at least one of the property and the circuit design;
receiving user selections to step through the source code view to display subsequent cycles of the trace; and
displaying an indication of the explanatory points in the source code view.
13. A computer program product for debugging counterexamples found in formal verification, the computer program product comprising a non-transitory computer-readable storage medium containing computer program code for:
receiving a trace that illustrates a behavior of a circuit design that violates a property defined for the circuit design;
selecting a set of explanatory points for the violated property, the explanatory points illustrating a portion of the trace of the counterexample that directly contributes to the violation of the property; and
displaying the trace of the counterexample to the user; and
displaying an indication of the explanatory points on the trace of the counterexample.
14. The computer program product of claim 13, wherein the trace is for a counterexample identified for the circuit design during a formal verification process.
15. The computer program product of claim 13, wherein the property is a covered property, and the trace is a cover trace comprising a counterexample to a negation of the covered property.
16. The computer program product of claim 13, wherein the set of explanatory points is both sufficient and minimal.
17. The computer program product of claim 13, wherein selecting a set of explanatory points for the violated property comprises:
identifying a plurality of sets of explanatory points; and
choosing one of the plurality sets of explanatory points that has the least difference between the earliest cycle and the failure point.
18. The computer program product of claim 13, wherein selecting a set of explanatory points for the violated property comprises:
identifying a plurality of sets of explanatory points; and
choosing one of the plurality sets of explanatory points that contains the least number of points.
19. The computer program product of claim 13, wherein the set of explanatory points includes at least one point that contributes to the triggering of the property and at least one point that contributes directly to the violation of the property.
20. The computer program product of claim 13, wherein displaying an indication of the explanatory points comprises displaying the points that contribute to the triggering of the property differently than the points that contribute directly to the violation of the property.
21. The computer program product of claim 20, wherein the points that contribute to the triggering of the property are displayed using a different color than the points that contribute directly to the violation of the property.
22. The computer program product of claim 13, wherein displaying an indication of the explanatory points comprises displaying inessential points.
23. The computer program product of claim 13, further comprising:
receiving a user selection of a cycle, wherein displaying the trace of the counterexample is responsive to the selected cycle.
24. The computer program product of claim 13, further comprising:
displaying source code of at least one of the property and the circuit design;
receiving user selections to step through the source code view to display subsequent cycles of the trace; and
displaying an indication of the explanatory points in the source code view.
25. The method of claim 1, wherein the explanatory points comprise one or more signal-cycle points of the trace of the counterexample that contribute directly to the violation of the property.

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:
providing a kit having a color tray having three or four color compartments, at least two color containers, a paddle, a specialized brush having three or four bristle groupings to correspond with compartments on the color tray; and
applying three or four colors simultaneously from the scalp end of the hair to the tips.
2. The method of claim 1 further comprising:
providing foil sheets;
selecting the colors desired for the hair;
placing an individual color in each compartment of the color tray;
placing a foil sheet on the paddle;
weaving the hair to form a part, section and subsection in the hair;
dipping the brush in the color tray;
holding the paddle and foil against the hair;
placing each subsection of hair in its own ridge on the foil; and
wrapping the foil normally.
3. The method of claim 1 further comprising:
mixing the colors;
identifying the color for each compartment; and
labeling the color containers accordingly;
4. A system for colorizing hair, the system comprising:
a color tray comprising at least three parallel and elongated channels adapted for retaining a liquid chemical or color; and
a brush having a narrow and tapered elongated handle portion at one end and an oppositely disposed bristle end having at least three distinct bristle groupings, the bristle grouping being spaced apart to selectively align with the channels on the color tray.
5. The system of claim 4 further comprising:
a paddle comprising at least three parallel and elongated ridges.
6. The system of claim 4 further comprising:
at least one container adapted to contain a liquid chemical such as a color for hair.
7. The system of claim 4 further comprising:
a plurality of foil sheets; and
a pair of gloves.
8. The system of claim 4 wherein the color tray comprises at least four channels and the brush comprises at least four bristle groups.
9. A system for colorizing hair, the system comprising:
a first color tray comprising three parallel and elongated channels adapted for retaining a liquid chemical or color;
a first paddle comprising three parallel and elongated ridges;
a first brush having a narrow and tapered elongated handle portion at one end and an oppositely disposed bristle end having three distinct bristle groupings, the bristle grouping being spaced apart to align with the channels on the first color tray;
a second color tray comprising four parallel and elongated channels;
a second paddle comprising four parallel and elongated ridges; and
a second brush having a narrow and tapered elongated handle portion at one end and an oppositely disposed bristle end having four distinct bristle groupings, the bristle grouping being spaced apart to align with the channels on the second color tray.

1. A method of packaging a power light emitting diode (LED), comprising:
providing a printed circuit board (PCB) wherein first and second copper (Cu) thin films are formed on both faces of the PCB respectively;
forming a single upper opening through an entire thickness of the first Cu thin film and an partial thickness of the PCB;
forming a plurality of lower openings, each lower opening extending vertically from the upper opening to the second Cu thin film;
forming solder pads on the first Cu thin film;
filing a cream solder in the upper opening and the plurality of lower openings so as to be in-plane with the solder pads;
mounting a power LED on the PCB so that lead frames of the LED are aligned with the solder pads and a heat-discharge region of the LED is aligned with the cream solder; and
soldering the cream solder.
2. The method of claim 1, wherein forming the upper andor plurality of lower openings are carried out in a punching manner.
3. The method of claim 1, further comprising adhering the second Cu thin film to an aluminum heat-discharge structure.
4. The method of claim 1, wherein the upper andor plurality of lower openings are formed during providing the PCB.
5. A power light emitting diode (LED) package, comprising:
a first copper thin film;
a printed circuit board (PCB) formed on the first copper thin film;
a second copper thin film formed on the PCB;
a solder vertically formed through the second copper thin film and the PCB;
solder pads formed on the second copper thin film; and
a power LED disposed on the solder pads,
wherein lead frames of the LED are in contact with the solder pads and a heat-discharge region of the LED is aligned with the solder,
wherein the solder is in-plane with the solder pads,
wherein the solder is defined into a plurality of sub-solders in a lower portion thereof, and
wherein a resin isolation is formed between neighboring sub-solders.
6. The package of claim 5, wherein a material of the resin isolation is the same as a material of the PCB.
7. The package of claim 5, wherein the resin isolation is made of FR4.
8. The package of claim 5, wherein the PCB is made of FR4.
9. The package of claim 5, wherein the solder is made of a Pb-free solder.
10. The package of claim 5, further comprising an aluminum heat-discharge structure attached to the first copper thin film.
11. The package of claim 5, wherein the sub-solders are in contact with the first copper thin film.

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 for speech dialog, comprising:
receiving an input speech phrase that includes an instantiated variable;
extracting pitch and voicing characteristics for the instantiated variable;
performing voice recognition of the instantiated variable to determine a most likely set of recognition acoustic states;
converting the most likely set of recognition acoustic states to a most likely set of synthesis acoustic states; and
generating a synthesized value of the instantiated variable using the most likely set of synthesis acoustic states and the extracted pitch and voicing characteristics.
2. The method for speech dialog according to claim 1, wherein said performing voice recognition of the instantiated variable comprises:
extracting acoustic characteristics in the form of recognition feature vectors of the instantiated variable; and
comparing the extracted acoustic characteristics to a mathematical model of stored lookup values to determine a most likely set of the extracted recognition feature vectors representing the most likely set of recognition acoustic states.
3. The method for speech dialog according to claim 2, said converting further comprising:
deriving recognition feature vectors from training speech uttered by at least one speaker;
deriving synthesis feature vectors from the training speech uttered by the at least one speaker, each of the derived synthesis vectors corresponding on a one-to-one basis to one of the derived recognition vectors;
mapping a plurality of subsets of the derived recognition feature vectors to a most likely set of synthesis feature vectors, and
for each of the most likely set of recognition feature vectors:
determining the probability that the most likely recognition feature vector belongs in one or more of the subsets; and
selecting a most likely synthesis feature vector based on the determined probability and the mapping.
4. The method for speech dialog according to claim 3, wherein the extracted and derived recognition feature vectors comprise Mel-frequency cepstrum coefficients and the extracted and derived synthesis feature vectors comprise linear prediction coding compatible coefficients.
5. The method for speech dialog according to claim 1, wherein said generating the synthesized value of the instantiated variable is performed when a metric of the most likely set of recognition acoustic states meets a criterion, and further comprising presenting an acoustically stored out-of-vocabulary response phrase when the metric of the most likely set of recognition acoustic states fails to meet the criterion.
6. The method for speech dialog according to claim 1, wherein the speech phrase further includes a non-variable segment that is associated with the instantiated variable, further comprising:
performing voice recognition of the non-variable segment; and
presenting an acoustically stored response phrase based on the recognized non-variable segment.
7. The method for speech dialog according to claim 3, wherein said mapping further comprises
creating the subsets of extracted recognition feature vectors through vector quantization;
establishing a vector quantization table comprising a plurality of entries, each of the entries comprising a centroid for a different one of the subsets; and
determining the most likely synthesis feature vector for each of the entries, comprising:
selecting an appropriate one of the derived recognition feature vectors from the subset corresponding to each entry; and
associating the entry with the derived synthesis feature vector that corresponds to the appropriate recognition feature vector on a one-to-one basis.
8. The method for speech dialog according to claim 7, wherein the selected appropriate one of the derived recognition feature vectors is the derived recognition feature vector of the subset that is closest to the centroid.
9. The method for speech dialog according to claim 3, wherein said mapping further comprises:
modeling the derived recognition feature vectors such that each of the subsets is a statistical distribution characterized by a mean vector, a covariance matrix and a non-negative weight; and
determining the most likely synthesis feature vector that corresponds to each of the most likely set of recognition feature vectors based on the probability that each of the set of most likely recognition feature vectors is in any one of the subsets.
10. The method for speech dialog according to claim 9, wherein said determining the most likely synthesis feature vector further comprises:
computing a weight for each of the set of most likely recognition feature vectors, each weight corresponding to the probability the most likely synthesis feature vector is in that one of the subsets; and
applying the computed weights for each of the subsets to the derived synthesis feature vectors each of which corresponds to the derived recognition feature vectors comprising each of the subsets to obtain the converted most likely synthesis feature vector.
11. An electronic device for speech dialog, comprising:
means for receiving an input speech phrase that includes an instantiated variable;
means for extracting pitch and voicing characteristics for the instantiated variable;
means for performing voice recognition of the instantiated variable to determine a most likely set of recognition acoustic states;
means for converting the most likely set of recognition acoustic states to a most likely set of synthesis acoustic states; and
means for generating a synthesized value of the instantiated variable using the most likely set of synthesis acoustic states and the extracted pitch and voicing characteristics.
12. The electronic device for speech dialog according to claim 11, wherein said means for performing voice recognition of the instantiated variable comprises:
means for extracting acoustic characteristics in the form of recognition feature vectors of the instantiated variable; and
means for comparing the extracted acoustic characteristics to a mathematical model of stored lookup values to determine a most likely set of the extracted recognition feature vectors representing the most likely set of recognition acoustic states.
13. The electronic device for speech dialog according to claim 12, said means for converting further comprising:
means for deriving recognition feature vectors from training speech uttered by at least one speaker;
means for deriving synthesis feature vectors from the training speech uttered by the at least one speaker, each of the derived synthesis vectors corresponding on a one-to-one basis to one of the derived recognition vectors;
means for mapping a plurality of subsets of the derived recognition feature vectors to a most likely set of synthesis feature vectors, and
means for determining the probability that each of the most likely set of recognition feature vectors belongs in one or more of the subsets; and
means for selecting a most likely synthesis feature vector for each of the most likely set of recognition feature vectors based on the determined probability and the mapping.
14. The electronic device for speech dialog according to claim 13, wherein said means for mapping further comprises
means for creating the subsets of extracted recognition feature vectors through vector quantization;
means for establishing a vector quantization table comprising a plurality of entries, each of the entries comprising a centroid for a different one of the subsets; and
means for determining the most likely synthesis feature vector for each of the entries, comprising:
means for selecting an appropriate one of the derived recognition feature vectors from the subset corresponding to each entry; and
means for associating the entry with the derived synthesis feature vector that corresponds to the appropriate recognition feature vector on a one-to-one basis.
15. The electronic device for speech dialog according to claim 14, wherein the selected appropriate one of the derived recognition feature vectors is the derived recognition feature vector of the subset that is closest to the centroid.
16. The electronic device for speech dialog according to claim 13, wherein said means for mapping further comprises:
means for modeling the derived recognition feature vectors such that each of the subsets is a statistical distribution characterized by a mean vector, a covariance matrix and a non-negative weight; and
means for determining the most likely synthesis feature vector that corresponds to each of the most likely set of recognition feature vectors based on the probability that each of the set of recognition feature vectors is in any one of the subsets.
17. The electronic device for speech dialog according to claim 11, wherein said means for determining the most likely synthesis feature vector further comprises:
means for computing a weight for each of the set of most likely recognition feature vectors, each weight corresponding to the probability the most likely synthesis feature vector is in that one of the subsets; and
means for applying the computed weights for each of the subsets to the derived synthesis feature vectors each of which corresponds to the derived recognition feature vectors comprising each of the subsets to obtain the converted most likely synthesis feature vector.
18. A media that includes a set of stored program instructions, comprising:
a function for receiving an input speech phrase that includes an instantiated variable;
a function for extracting pitch and voicing characteristics for the instantiated variable;
a function for performing voice recognition of the instantiated variable to determine a most likely set of recognition acoustic states;
a function for converting the most likely set of recognition acoustic states to a most likely set of synthesis acoustic states; and
a function for generating a synthesized value of the instantiated variable using the most likely set of synthesis acoustic states and the extracted pitch and voicing characteristics.
19. The media that includes a set of stored program instructions according to claim 18, wherein said function for performing voice recognition of the instantiated variable comprises:
a function for extracting acoustic characteristics in the form of recognition feature vectors of the instantiated variable; and
a function for comparing the extracted acoustic characteristics to a mathematical model of stored lookup values to determine a most likely set of the extracted recognition feature vectors representing the most likely set of recognition acoustic states.
20. The media that includes a set of stored program instructions according to claim 19, said function for mapping further comprising:
a function for modeling the derived recognition feature vectors such that each of the subsets is a statistical distribution characterized by a mean vector, a covariance matrix and a non-negative weight; and
a function for determining the most likely synthesis feature vector that corresponds to each of the most likely set of recognition feature vectors based on the probability that each of the set of most likely recognition feature vectors is in any one of the subsets.