All The Claims

1. A receiver comprising:
(a) a plurality of antennas for receiving wireless signals, each wireless signal having a channel impulse response with at least one cluster;
(b) a plurality of signal regeneration units, each signal regeneration unit being configured to generate a replica of the cluster associated with a respective one of the wireless signals received by the antennas;
(c) a plurality of summers, each summer being configured to subtract the replica of the cluster generated by a respective signal regeneration unit from a respective signal received by a respective one of the antennas; and
(d) a first sliding window equalizer having a window length based on either a length of the at least one cluster or a predetermined cluster length.
2. The receiver of claim 1 further comprising:
(e) at least one circuit for processing multipath components of the channel impulse response outside the window associated with the first sliding window equalizer;
(f) a combiner for combining outputs of the first sliding window equalizer and the at least one circuit; and
(g) a hard decision unit coupled to an output of the combiner and to the signal regeneration units, wherein the at least one circuit comprises a second sliding window equalizer having a window length based on either a length of a second cluster of the channel impulse response or a second predetermined cluster length.
3. The receiver of claim 2 wherein the at least one circuit comprises a Rake.
4. The receiver of claim 1 wherein the window length of the first sliding window equalizer is a multiple of the length of the at least one cluster or the predetermined cluster length.
5. The receiver of claim 1 wherein the predetermined cluster length is a maximum expected cluster length.
6. The receiver of claim 1 wherein the predetermined cluster length is a multiple of a typical expected cluster length.
7. A wireless transmitreceive unit (WTRU) comprising:
(a) a plurality of antennas for receiving wireless signals, each wireless signal having a channel impulse response with at least one cluster;
(b) a plurality of signal regeneration units, each signal regeneration unit being configured to generate a replica of the cluster associated with a respective one of the wireless signals received by the antennas;
(c) a plurality of summers, each summer being configured to subtract the replica of the cluster generated by a respective signal regeneration unit from a respective signal received by a respective one of the antennas; and
(d) a first sliding window equalizer having a window length based on either a length of the at least one cluster or a predetermined cluster length.
8. The WTRU of claim 7 further comprising:
(e) at least one circuit for processing multipath components of the channel impulse response outside the window associated with the first sliding window equalizer;
(f) a combiner for combining outputs of the first sliding window equalizer and the at least one circuit; and
(g) a hard decision unit coupled to an output of the combiner and to the signal regeneration units, wherein the at least one circuit comprises a second sliding window equalizer having a window length based on either a length of a second cluster of the channel impulse response or a second predetermined cluster length.
9. The WTRU of claim 8 wherein the at least one circuit comprises a Rake.
10. The WTRU of claim 7 wherein the window length of the first sliding window equalizer is a multiple of the length of the at least one cluster or the predetermined cluster length.
11. The WTRU of claim 7 wherein the predetermined cluster length is a maximum expected cluster length.
12. The WTRU of claim 7 wherein the predetermined cluster length is a multiple of a typical expected cluster length.
13. An integrated circuit (IC) embedded in a receiver having a plurality of antennas for receiving wireless signals, each wireless signal having a channel impulse response with at least one cluster, the IC comprising:
(a) a plurality of signal regeneration units, each signal regeneration unit being configured to generate a replica of the cluster associated with a respective one of the wireless signals received by the antennas;
(b) a plurality of summers, each summer being configured to subtract the replica of the cluster generated by a respective signal regeneration unit from a respective signal received by a respective one of the antennas; and
(c) a first sliding window equalizer having a window length based on either a length of the at least one cluster or a predetermined cluster length.
14. The IC of claim 13 further comprising:
(d) at least one circuit for processing multipath components of the channel impulse response outside the window associated with the first sliding window equalizer;
(e) a combiner for combining outputs of the first sliding window equalizer and the at least one circuit; and
(f) a hard decision unit coupled to an output of the combiner and to the signal regeneration units, wherein the at least one circuit comprises a second sliding window equalizer having a window length based on either a length of a second cluster of the channel impulse response or a second predetermined cluster length.
15. The IC of claim 14 wherein the at least one circuit comprises a Rake.
16. The IC of claim 13 wherein the window length of the first sliding window equalizer is a multiple of the length of the at least one cluster or the predetermined cluster length.
17. The IC of claim 13 wherein the predetermined cluster length is a maximum expected cluster length.
18. The IC of claim 13 wherein the predetermined cluster length is a multiple of a typical expected cluster length.

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 lighting system having: a fixture with an axis of orientation; a light source mounted within said fixture, at least a portion of said light source extending along said axis of orientation; a ballast associated with said light source, said ballast having a first end attached to said light source and a second end attached to an electrical power source;
the improvement comprising:
said second end attachment comprising a connector composed of inline, electrical connector halves having proximal mating ends, an axis of attachment and distal ends provided with strain relief mounting.
2. The lighting system of claim 1 wherein a first of said electrical connector halves has a locking tongue extending along said axis of attachment and a second of said connector halves has a locking tongue receptor for receiving said locking tongue.
3. The lighting system of claim 1 wherein said strain relief means comprises a projection extending along said axis of attachment and a plurality of spaced apart, transverse nubs positioned on said projection.
4. The lighting system of claim 3 wherein each of said electrical connector halves contains first and second contacts having mating ends and wire fixing ends and first and second pairs of wires connected to said wire fixing ends, said first and second pairs of wires being wound about said transverse nubs to provide strain relief.

1. A method for regulating the biodegradation rate of composite biomaterials comprising calcium salt and collagen by introducing crosslinking to collagen in said composite biomaterials.
2. The method according to claim 1, wherein the calcium salt is hydroxyapatite.
3. The method according to claim 2, wherein the composite biomaterials have a microstructure in which the c-axis of hydroxyapatite is oriented along the collagen fibers.
4. The method according to claim 1, wherein the crosslinking is introduced in at least 1% of reactive functional groups in collagen.
5. The method according to claim 1, wherein the crosslinking is introduced by a reaction utilizing glutaraldehyde.
6. The method according to claim 5, wherein 10 \u03bcmol to 10 mmol of the glutaraldehyde is used per g of collagen in composite biomaterials.
7. Composite biomaterials comprising hydroxyapatite and collagen, wherein crosslinking is introduced in collagen in said composite biomaterials.
8. The composite biomaterials according to claim 7, wherein the crosslinking is introduced using 10 \u03bcmol to 10 mmol of the glutaraldehyde per g of collagen.
9. The composite biomaterials according to claim 7, wherein the crosslinking is introduced in at least 1% of reactive \u03b5-amino groups in collagen.
10. The composite biomaterials according to claim 7, which have a microstructure in which the c-axis of hydroxyapatite is oriented along the collagen fibers.
11. A method for increasing bone mass of a subject which comprises implanting the composite biomaterials according to claim 7 into the subject.
12. A method for treating osteoporosis of a patient which comprises implanting the composite biomaterials according to claim 7 into the patient.

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 removing a red eye from an image, comprising:
calculating a weighted red value for each pixel in the image based on (1) red, green, and blue color values and (2) a luminance of each pixel in the image;
selecting a plurality of pixels in the image having weighted red values greater than a threshold as red eye pixels; and
correcting the red eye pixels to remove the red eye from the image.
2. The method of claim 1, wherein said calculating comprises:
f
1

=
c
1

(
1
)
\u2062
r

+
c
2

(
1
)
\u2062
g

+
c
3

(
1
)
\u2062
b
Y
,
wherein f1 is the weighted red value, r is the red color value, g is the green color value, b is the blue color value, c1(1) is a first weight given to the red color value, c2(1) is a second weigh given to the green color value, c3(1) is a third weight given to the blue color value, and Y is the luminance.
3. The method of claim 2, wherein c1(1) is 0.5, c2(1) is 0.5, c3(1) is \u22121, Y=0.299r+0.587g+0.114b, and the threshold is 0.5.
4. The method of claim 2, prior to said correcting, further comprising:
calculating another weighted red value for each pixel in the image from the red, the green, and the blue color values of each pixel in the image, comprising:
f
2

=
c
1

(
2
)
\u2062
r

+
c
2

(
2
)
\u2062
g

+
c
3

(
2
)
\u2062
b
Y
,
wherein f2 is said another weighted red value, c1(2) is another first weight given to the red color value, c2(2) is another second weigh given to the green color value, and c3(2) is another third weight given to the blue color value; and
selecting another plurality of pixels in the image having another weighted red values greater than another threshold as additional red eye pixels.
5. The method of claim 4, c1(2) is 0.6667, c2(2) is 0.3333, c3(2) is \u22121.0, Y=0.299r+0.587g+0.114b, and the threshold is 0.5.
6. The method of claim 1, prior to said correcting, further comprising:
grouping a plurality of red eye pixels that are contiguous into a red eye region;
determining if the red eye region comprises a substantially round pupil; and
rejecting the plurality of red eye pixels if the red eye region does not comprise a substantially round pupil.
7. The method of claim 6, wherein said determining if the red eye region is substantially round pupil comprises:
determining a geometric center of the red eye region;
for each radius in a range of radii, determining a difference between (1) weighted red values of the red eye pixels located at a radius and at a range of angles about the geometric center and (2) weighted red values of the red eye pixels located at a next radius in the range of radii and at the range of angles;
selecting one radius in the range of radii that provides a largest difference as a pupil radius for the red eye region;
determining a first ratio of (1) a first number of the red eye pixels located in a circle having the pupil radius to (2) an area of the circular;
determining a second ratio of (1) a second number of the red eye pixels in a ring having an inner radius of the pupil radius and an outer radius of a maximum radius in the range of radii to (2) an area of the ring; and
determining a difference between the first ratio and the second ratio, wherein the red eye region does not comprise a substantially round pupil if the difference is less than a threshold.
8. The method of claim 7, wherein the range of radii ranges from 0.5 to 1.5 times a distance from the geometric center to a farthest red eye pixel in the red eye region.
9. The method of claim 6, further comprising:
determining if the red eye region is too close to another red eye region formed by grouping another plurality of red eye pixels that are contiguous; and
rejecting the plurality of red eye pixels if the red eye region is too close to said another red eye region.
10. The method of claim 9, wherein said determining if the red eye region is too close to another red eye region comprises:
determining if the geometric center of the red eye region is within a range of distances of said another geometric center of said another red eye region, wherein the range of distances is proportional to a pupil radius of the red eye region.
11. The method of claim 10, further comprising determining the pupil radius as follows:
determining a geometric center of the red eye region;
for each radius in a range of radii, determining a difference between (1) weighted red values of the red eye pixels located at a radius and at a range of angles about the geometric center and (2) weighted red values of the red eye pixels located at a next radius in the range of radii and at the range of angles; and
selecting one radius in the range of radii that provides a largest difference as a pupil radius for the red eye region.
12. The method of claim 11, wherein the range comprises 10 to 14 times the pupil radius.
13. The method of claim 9, further comprising:
determining if the red eye region is proximate to a facial region; and
rejecting the plurality of red eye pixels if the red eye region is not proximate to a facial region.
14. The method of claim 13, wherein said determining if the red eye region is proximate to a facial region comprising:
generating a histogram for pixels in a ring having an inner and outer radii proportional to a pupil radius of the red eye region;
selecting a most common color value in the histogram;
comparing the most common color to a range of threshold skin colors;
rejecting the plurality of red eye pixels if the most common color in the red eye region is not within the range of the threshold skin colors.
15. The method of claim 14, wherein said comparing comprises comparing the most common color value in HSV color space to the range of threshold skin colors in HSV color space.
16. The method of claim 14, further comprising determining the pupil radius as follows:
determining a geometric center of the red eye region;
for each radius in a range of radii, determining a difference between (1) weighted red values of the red eye pixels located at a radius and at a range of angles about the geometric center and (2) weighted red values of the red eye pixels located at a next radius in the range of radii and at the range of angles;
selecting one radius in the range of radii that provides a largest difference as a pupil radius for the red eye region;
17. The method of claim 16, wherein the inner and outer radii comprises of 4 to 9 times the pupil radius.
18. The method of claim 13, further comprising:
determining if the red eye region is proximate to a sclera; and
rejecting the plurality of red eye pixels if the red eye region is not proximate to a sclera.
19. The method of claim 18, wherein said determining if the red eye region is proximate to a sclera comprises:
generating a luminance histogram for pixels in a ring having an inner and outer radii proportional to the pupil radius;
selecting a brightest color in the luminance histogram;
determine a ratio between a number of pixels in the ring having the most brightest color to a number of red eye pixels within a circle having the pupil radius; and
rejecting the plurality of red eye pixels if the ratio of the red eye region is less than a threshold.
20. The method of claim 19, further comprising determining the pupil radius as follows:
determining a geometric center of the red eye region;
for each radius in a range of radii, determining a difference between (1) weighted red values of the red eye pixels located at a radius and at a range of angles about the geometric center and (2) weighted red values of the red eye pixels located at a next radius in the range of radii and at the range of angles;
selecting one radius in the range of radii that provides a largest difference as a pupil radius for the red eye region;
21. The method of claim 20, wherein the inner and outer radii comprises 2 to 5 times the pupil radius.
22. The method of claim 1, wherein the method is implemented in software executed by a computer or firmware embedded into digital cameras, printers, scanners, or mobile phones.
23. A method for removing a red eye from an image, comprising:
calculating a weighted red value for each pixel in the image from a luminance, a red chrominance, and a blue chrominance values of each pixel in the image, comprising:
f
1

=
1.41514
\u2062

(

Cr
–
128

)
+

1.23014
\u2062

(

Cb
–
128

)
Y
,
wherein f1 is the weighted red value, Cr is the red chrominance value, Cb is the blue chrominance value, and Y is the luminance value;
selecting a plurality of pixels in the image having weighted red values greater than a threshold as red eye pixels; and
correcting the red eye pixels in the image.
24. The method of claim 23, prior to said correcting, further comprising:
calculating another weighted red value for each pixel in the image from the red, the green, and the blue color values of each pixel in the image, comprising:
f
2

=
0.69662
\u2062

(

Cr
–
128

)
–

1.88671
\u2062

(

Cb
–
128

)
Y
,
wherein f2 is said another weighted red value; and
selecting another plurality of pixels in the image having another weighted red values greater than another threshold as additional red eye pixels.
25. The method of claim 23, wherein the method is implemented in software executed by a computer or firmware embedded into digital cameras, printers, scanners, or mobile phones.