Author: claimsbot

1. A security device for a handheld electronic device comprising:
a body having a first side, a second side, and an upper surface;
a first arm extending upwardly from the first side of the body and having a distal end, wherein the distal end of the first arm has a first retention hook extending substantially horizontally from the distal end of the first arm above the plane of the upper surface of the body;
a second arm extending upwardly from the second side of the body and having a distal end, wherein the distal end of the second arm has a second retention hook extending substantially horizontally from the distal end of the second arm above the plane of the upper surface of the body;
a draw pin extending through the first side and the second side of the housing body for moving the first arm and second arm simultaneously along an X-axis relative to the first side and the second side of the body, wherein the draw pin comprises a first threaded end and second threaded end, wherein the first threaded end has a thread pattern that is counter rotational to the thread pattern of the second threaded end;
a leveling plate located between the first arm and the second arm and proximate to the upper surface of the body, wherein the leveling plate is connected to the body using one or more leveling screws to allow the leveling plate to move independently of the body along a Z-axis relative to the upper surface of the body;
an alarm sensor on the leveling plate that sets when placed in contact with a surface of the handheld electronic device, wherein the alarm sensor can activate when the alarm sensor loses contact with the handheld electronic device; and
a charging port on the body for charging the handheld electronic device.
2. The security device of claim 1, wherein the alarm sensor is integrated with the leveling plate.
3. The security device of claim 2, wherein the alarm sensor is at least partially recessed in the leveling plate
4. The security device of claim 1, further comprising a circuit board in the housing, wherein the circuit board is connected to and monitors the alarm sensor.
5. The security device of claim 1, further comprising an LED on the leveling plate for providing a visual status of the alarm sensor.
6. The security device of claim 1, further comprising an LED on the body for providing a visual status of the alarm sensor.
7. The security device of claim 1, further comprising a tether connected to the body.
8. The security device of claim 7, wherein the tether further comprises wiring for monitoring the status of the alarm sensor.
9. The security device of claim 7, wherein the tether further comprises wiring for providing power to the charging port.
10. The security device of claim 1, wherein the alarm sensor is a plunger-style sensor.
11. The security device of claim 1, wherein the alarm sensor is a tape-style sensor.
12. The security device of claim 1, wherein the draw pin is operable with a tool.
13. The security device of claim 12, wherein the tool is a hex wrench.
14. The security device of claim 1, further comprising a security pin at a tip of one of the first threaded end and second threaded end of the draw pin.
15. The security device of claim 14, wherein the draw pin is operable a hex wrench with an aperture for receiving the security pin.

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, on a graphical keyboard of a computing device, touch input comprising a plurality of selections of one or more keyboard characters currently displayed on the graphical keyboard;
determining, by the computing device, a touch input operation that corresponds to the touch input, wherein the touch input operation identifies a character that is not currently displayed on the graphical keyboard, wherein the identified character has a phonetic relationship to the one or more keyboard characters selected by the touch input, and wherein the identified character is different from the one or more keyboard characters selected by the touch input; and
generating for display, on an output device of the computing device, the identified character.
2. The method of claim 1, further comprising:
receiving, on the graphical keyboard, the touch input comprising a single selection of one keyboard character currently displayed on the graphical keyboard; and
selecting, by the computing device for purposes of display, the one keyboard character currently displayed in the graphical keyboard.
3. The method of claim 1, wherein determining, by the computing device, the touch input operation that corresponds to the touch input comprises determining, by the computing device, a lookup of the identified character in a table based on the touch input operation, wherein the table comprises mappings between one or more characters and one or more touch input operations.
4. The method of claim 3, further comprising:
storing the table in a database on the computing device.
5. The method of claim 1, wherein receiving, on the graphical keyboard of the computing device, the touch input comprises determining, by the computing device, a duration of at least one of the selections of the touch input.
6. The method of claim 5, wherein determining, by the computing device, the duration of the at least one of the selections of the touch input further comprises selecting the input operation based on the duration of the at least one of the selections of the touch input.
7. The method of claim 1, wherein the identified character is not represented in the graphical keyboard.
8. The method of claim 1, wherein the phonetic relationship comprises a relationship between a vowel and a diphthong.
9. The method of claim 1, wherein the phonetic relationship comprises a relationship between a single vowel and a double vowel.
10. The method of claim 1, wherein the phonetic relationship comprises a relationship between a simple consonant and an aspirated derivative of the simple consonant.
11. The method of claim 1, wherein the phonetic relationship comprises a relationship between a simple consonant and a faucalized consonant.
12. The method of claim 1, wherein the phonetic relationship comprises a relationship between a simple consonant and a consonant cluster.
13. The method of claim 1, wherein the phonetic relationship comprises a relationship between a first double vowel and a second double vowel.
14. The method of claim 1, wherein the graphical keyboard is displayed by a touch-sensitive screen of the computing device.
15. The method of claim 1, wherein the touch input comprises a swipe, pinch, de-pinch, tap, rotate, double tap, long press, or combo press.
16. The method of claim 1, wherein each of the one or more keyboard characters are selected for representation on the graphical keyboard based on a frequency, wherein the frequency comprises a number of occurrences that a keyboard character of the graphical keyboard is selected by a user.
17. The method of claim 16, wherein the one or more keyboard characters of the graphical keyboard comprise a frequently selected group of characters that are more frequently selected by a user than a less frequently selected group of characters.
18. The method of claim 1, wherein the one or more keyboard characters of the graphical keyboard are not phonetically related.
19. A computer-readable storage medium encoded with instructions that cause one or more processors of a computing device to:
receive, on a graphical keyboard of a computing device, touch input comprising a plurality of selections of one or more keyboard characters currently displayed on the graphical keyboard;
determine, by the computing device, a touch input operation that corresponds to the touch input, wherein the touch input operation identifies a character that is not currently displayed on the graphical keyboard, wherein the identified character has a phonetic relationship to the one or more keyboard characters selected by the touch input, and wherein the identified character is different from the one or more keyboard characters selected by the touch input; and
generate for display, on an output device of the computing device, the identified character.
20. A computing device, comprising:
one or more processors;
an output device;
a keyboard application implemented by the one or more processors to receive a touch input comprising a plurality of selections of one or more keyboard characters of a graphical keyboard currently displayed on the output device; and
means for determining a touch input operation that corresponds to the touch input, wherein the touch input operation identifies a character that is not currently displayed on the graphical keyboard, wherein the identified character has a phonetic relationship to the one or more keyboard characters selected by the touch input, and wherein the identified character is different from the one or more keyboard characters selected by the touch input,
wherein the output device is configured to generate for display the identified character.

1. A computer-implemented method of grouping faces in large user account for creating an image product, comprising:
acquiring face images from an image album in a user’s account by a computer processor;
adding the face images obtained from the image album into a first chunk;
comparing chuck size of the first chunk with a maximum chuck value for an optimal chunk size range by the computer processor;
if the chunk size of the first chuck is smaller than the maximum chuck value, keeping the face images from the image album in the first chunk;
if the chunk size of the first chuck is larger than the maximum chuck value, automatically separating, by the computer processor, the face images from the image album into a first portion and one or more second portions;
keeping the first portion in the first chunk to keep the current chunk size below the maximum chuck value;
automatically moving the one or more second portions of face images to one or more subsequent chunks by the computer processor;
automatically grouping face images in the first chunk by the computer processor to form face groups;
assigning at least some of the face groups in the first chunk to known face models associated with the user account; and
creating a design for an image-based product based at least in part on the face images in the first chunk associated with the face models.
2. The computer-implemented method of claim 1, further comprising:
setting up new face models by the computer processor for at least some of the face groups that cannot be assigned to existing face models,
wherein the design for an image-based product is created based on the face images associated with the known face models and the new face models.
3. The computer-implemented method of claim 1, further comprising:
moving the ungrouped face images in the first chunk to one or more subsequent chunks that have not been processed with face grouping.
4. The computer-implemented method of claim 3, further comprising:
discarding ungrouped face images that have been moved to subsequent chunks for more than a predetermined number of times.
5. The computer-implemented method of claim 1, further comprising:
repeating steps from acquiring face images in the image album or additional image albums to automatically grouping face images, to group images in a second chunk subsequent to the first chunk;
assigning at least some of the face groups in the second chunk to known face models associated with the user account; and
creating the design for the image-based product based at least in part on the face images in the first chunk and the second chunk associated with the face models.
6. The computer-implemented method of claim 1, wherein the step of automatically grouping face images in the first chunk comprises:
calculating similarity functions between pairs of face images in the first chunk by the computer processor;
joining face images that have values of the similarity functions above a predetermined threshold into a hypothetical face group, wherein the face images in the hypothetical face group hypothetically belong to a same person;
conducting non-negative matrix factorization on values of the similarity functions in the hypothetical face group to test truthfulness of the hypothetical face group; and
identifying the hypothetical face group as a true face group if a percentage of the associated similarity functions being true is above a threshold based on the non-negative matrix factorization.
7. The computer-implemented method of claim 6, further comprising:
rejecting the hypothetical face group as a true face group if a percentage of the associated similarity functions being true is below a threshold.
8. The computer-implemented method of claim 6, wherein the step of conducting non-negative matrix factorization comprises:
forming a non-negative matrix using values of similarity functions between all different pairs of face images in the hypothetical face group,
wherein the non-negative matrix factorization is conducted over the non-negative matrix.
9. The computer-implemented method of claim 6, wherein the similarity functions in the hypothetical face group are described in a similarity distribution function, wherein the step of non-negative matrix factorization outputs a True similarity distribution function and a False similarity distribution function.
10. The computer-implemented method of claim 6, wherein every pair of face images in the hypothetical face group has a similarity function above the predetermined threshold.
11. The computer-implemented method of claim 6, further comprising:
joining two true face groups to form a joint face group;
conducting non-negative matrix factorization on values of similarity functions in the joint face group; and
merging the two true face groups if a percentage of the associated similarity functions being true is above a threshold in the joint face group.
12. The computer-implemented method of claim 1, wherein the step of automatically grouping face images in the first chunk comprises:
receiving an initial set of n* face groups in the face images in the first chunk, wherein n* is a positive integer bigger than 1;
training classifiers between pairs of face groups in the initial set of face groups using image-product statistics;
classifying the plurality of face images by n*(n*\u22121)2 classifiers to output binary vectors for the face images by the computer processor;
calculating a value for an improved similarity function using the binary vectors for each pair of the face images; and
grouping the face images in the first chunk into modified face groups based on values of the binary similarity functions by the computer processor.
13. The computer-implemented method of claim 12, further comprising:
comparing a difference between the modified face groups and the initial face groups to a threshold value, wherein the image product is created based at least in part on the modified face groups if the difference is smaller than the threshold value.
14. The computer-implemented method of claim 12, wherein there are an integer m number of face images in the plurality of face images, wherein the step of classifying the plurality of face images by n*(n*\u22121)2 classifiers outputs m number of binary vectors.
15. The computer-implemented method of claim 12, wherein the face images are grouped into modified face groups using non-negative matrix factorization based on values of the improved similarity functions.
16. The computer-implemented method of claim 1, wherein the step of assigning at least some of the face groups in the first chunk to known face models comprises:
storing training faces associated with the known face models of known persons in a computer storage;
joining the face images in the first chunk with a group of training faces associated with the known face models;
calculating similarity functions between pairs of the face images or the training faces in the joint group by a computer processor;
conducting non-negative matrix factorization on values of the similarity functions in the joint face group to test truthfulness of the joint face group; and
identifying the face images in the first chunk that belong to the known face models if a percentage of the associated similarity functions being true is above a threshold based on the non-negative matrix factorization.
17. The computer-implemented method of claim 16, further comprising:
merging the face images with the training faces of the known face model to form a new set of training faces for the known face model.
18. The computer-implemented method of claim 16, wherein the step of conducting non-negative matrix factorization comprises:
forming a non-negative matrix using values of similarity functions between all different pairs of the face images and the training faces in the joint face group,
wherein the non-negative matrix factorization is conducted over the non-negative matrix.
19. The computer-implemented method of claim 16, wherein the similarity functions in the joint face group are described in a similarity distribution function, wherein the step of non-negative matrix factorization outputs a True similarity distribution function and a False similarity distribution function.
20. The computer-implemented method of claim 16, wherein the step of identifying comprises:
comparing the similarity distribution function to the True similarity distribution function and the False similarity distribution function.

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 strained SOI structure comprising:
an insulating substrate;
a SiO2 layer formed on the insulating substrate; and
a strained silicon layer formed on the SiO2 layer.
2. The strained SOI structure of claim 1 further comprising a bonding layer between the insulating substrate and the SiO2 layer.
3. The strained SOI structure of claim 2, wherein the bonding layer is formed one of SiO2 and polycrystalline silicon.
4. The strained SOI structure of claim 1, wherein the insulating substrate is a substrate selected from the group consisting of a glass substrate, a plastic substrate, and a Si substrate on which an oxide layer is formed.
5. The strained SOI structure of claim 1 further comprising a protective layer that surrounds the insulating substrate.
6. The strained SOI structure of claim 5, wherein the protective layer is formed of AIN.
7. A method of manufacturing a strained SOI structure, comprising:
preparing a Si substrate and an insulating substrate;
forming a porous silicon layer by anodizing a predetermined thickness of the Si substrate;
forming a SiGe layer on the porous silicon layer;
forming a strained silicon layer on the SiGe layer;
forming a SiO2 layer on the strained silicon layer;
activating a surface of the SiO2 layer by treating the surface of the SiO2 layer using oxygen O2 plasma;
bonding the insulating substrate on the activated SiO2 layer;
removing the SiGe layer by selectively etching after reversing the stacked structure so that the insulating substrate is placed on a lower position; and
separating the porous silicon layer and the Si substrate from the strained silicon layer.
8. The method of claim 7, wherein the insulating substrate is a substrate selected from the group consisting of a glass substrate, a plastic substrate, and a Si substrate on which an oxide layer is formed.
9. The method of claim 7, wherein the preparing of the insulating substrate includes:
preparing an insulating substrate; and
forming a protective layer on a surface of the insulating substrate.
10. The method of claim 9, wherein the protective layer is formed of AIN.
11. The method of claim 7, wherein the preparing of the insulating substrate includes:
preparing an insulating substrate;
forming a protective layer on a surface of the insulating substrate; and
forming a bonding layer on the protective layer.
12. The method of claim 11, wherein the bonding layer is formed one of SiO2 and polycrystalline silicon.
13. A method of manufacturing a strained SOI structure, comprising:
preparing a Si substrate and an insulating substrate;
forming a SiGe layer on the Si substrate;
forming a porous SiGe layer by anodizing a predetermined thickness of the SiGe layer;
forming a strained silicon layer on the porous SiGe layer;
forming a SiO2 layer on the strained silicon layer;
activating a surface of the SiO2 layer by treating the surface of the SiO2 layer using oxygen O2 plasma;
bonding the insulating substrate on the activated SiO2 layer;
removing the porous SiGe layer by selectively etching after reversing the stacked structure so that the insulating substrate is placed on a lower position; and
separating the Si substrate from the strained silicon layer.
14. The method of claim 13, wherein the insulating substrate is a substrate selected from the group consisting of a glass substrate, a plastic substrate, and a Si substrate on which an oxide layer is formed.
15. The method of claim 13, wherein the preparing of the insulating substrate includes:
preparing an insulating substrate; and
forming a protective layer on a surface of the insulating substrate.
16. The method of claim 15, wherein the protective layer is formed of AIN.
17. The method of claim 13, wherein the preparing of the insulating substrate includes:
preparing an insulating substrate;
forming a protective layer on a surface of the insulating substrate; and
forming a bonding layer on the protective layer.
18. The method of claim 17, wherein the bonding layer is formed one of SiO2 and polycrystalline silicon.
19. A method of manufacturing a strained SOI structure, comprising:
preparing a Si substrate and an insulating substrate;
forming a SiO2 layer on the Si substrate;
forming at least two SiO2 barrier ribs spaced a predetermined distance from each other by patterning the SiO2 layer;
forming a SiGe layer on the Si substrate between the two barrier ribs;
forming a strained silicon layer on the SiGe layer;
removing the SiO2 barrier ribs;
bonding the insulating substrate on the strained silicon layer;
removing the SiGe layer by selectively etching after reversing the stacked structure so that the insulating substrate is placed on a lower position; and
separating the Si substrate from the strained silicon layer.
20. The method of claim 19, wherein the insulating substrate is a substrate selected from the group consisting of a glass substrate, a plastic substrate, and a Si substrate on which an oxide layer is formed.
21. The method of claim 19, wherein the preparing of the insulating substrate includes:
preparing an insulating substrate; and
forming a protective layer on a surface of the insulating substrate.
22. The method of claim 21, wherein the protective layer is formed of AIN.
23. The method of claim 19, wherein the preparing of the insulating substrate includes:
preparing an insulating substrate;
forming a protective layer on a surface of the insulating substrate; and
forming a bonding layer on the protective layer.
24. The method of claim 23, wherein the bonding of the insulating substrate on the strained silicon layer includes:
activating a surface of the bonding layer by treating using oxygen O2 plasma; and
bonding the insulating substrate on the strained silicon layer.
25. The method of claim 24, wherein the bonding layer is formed one of SiO2 and polycrystalline silicon.