All The Claims

1. A computer implemented method for optimizing a production process comprising the steps of:
(A) creating a representation for equipment for production of a product and arranging the representation in at least one sequence for production of the product, and designating each piece of equipment as a resource type according to such piece of equipment’s function;
(B) selecting the sequence created at step (A) and designating such sequence as a current sequence;
(C) calculating a value score for the current sequence according to value scores assigned to each resource in the current sequence as resources are arranged in the current sequence, with the value scores being assigned at least in consideration of characteristics of each resource;
(D) determining if there are possible unevaluated variations in the arrangement of the resources in the current sequence, and if there are no possible unevaluated variations then designating the current sequence an optimal sequence and proceeding to step (G), and if there are possible unevaluated variations, varying the arrangement of resources in the current sequence to create a new sequence;
(E) calculating a value score for the new sequence according to values assigned to each resource in the new sequence as resources are arranged in the new sequence, with the values being assigned at least according to resource characteristics;
(F) comparing the value scores for the current sequence and the new sequence to determine if the value score for the new sequence exceeds the value score for the current sequence according to predetermined criteria, and if the value score for the new sequence exceeds the value score for the current sequence, then designating the new sequence as the current sequence and proceeding to step (D), and if the value score for the current score exceeds the value score for the new sequence, then retaining the current sequence as the current sequence and proceeding to step (D); and
(G) said computer returning to a system user the optimal sequence for production of the product.
2. The method as recited in claim 1, wherein the representation of the production includes a computer-based representation of the equipment and the arrangement of such equipment.
3. The method as recited in claim 2, wherein the computer-based representation includes a virtual representation of the equipment and the arrangement of such equipment.
4. The method as recited in claim 1, wherein resource characteristics for a resource include restrictions associated with the operation of such resource.
5. The method as recited in claim 4, wherein the restrictions include restrictions associated with interaction of resources.
6. The method as recited in claim 1, wherein calculating a value score for the current sequence, further includes the substeps of:
(A) selecting the last resource in the current sequence and designating such resource as the current resource;
(B) determining if there is another resource upstream in the current sequence and if there is an upstream resource, selecting the upstream resource and designating such upstream resource as the current resource, and repeating step (B) until an upstream resource is not identified, then proceeding to step (C); and
(C) calculating a value score for the current sequence based on a composite of the assigned values of each of the resources of the current sequence selected at steps (A) and (B).
7. The method as recited in claim 1, wherein calculating a value score for the current sequence, further includes the substeps of:
(A) selecting the last resource in the new sequence and designating such resource as the new resource;
(B) determining if there is another resource upstream in the new sequence and if there is an upstream resource, selecting the upstream resource and designating such upstream resource as the new resource, and repeating step (B) until an upstream resource is not identified, then proceeding to step (C); and
(C) calculating a value score for the new sequence based on a composite of the assigned values of each of the resources of the sequence selected at steps (A) and (B).
8. The method as recited in claim 6 or 7, wherein assigning a value to each resource includes a value based on at least a time score, energy score andor human resource score for that resource.
9. The method as recited in claim 8, wherein the method is capable of calculating a value score for a sequence at any point in time during operation of that sequence.
10. The method as recited in claim 1, wherein the method is capable of calculating a value score for a sequence that processes products in batch form.
11. A computer-base system for optimizing a production process comprising:
(A) means for creating a representation of equipment for production of a product and arranging the representation in at least one sequence for production of the product, and means for receiving a designation for each piece of equipment as a resource type according to such piece of equipment’s function;
(B) means for selecting the sequence created at step (A) and designating such sequence as a current sequence;
(C) means for calculating a value score for the current sequence according to value scores assigned to each resource in the current sequence that are received by the system as resources are arranged in the current sequence, with the value scores being assigned at least in consideration of characteristics of each resource;
(D) means for determining if there are possible unevaluated variations in the arrangement of the resources in the current sequence, and if there are no possible unevaluated variations then designating the current sequence an optimal sequence and proceeding to step (G), and if there are possible unevaluated variations, varying the arrangement of resources in the current sequence to create a new sequence;
(E) means for calculating a value score for the new sequence according to values assigned to each resource in the new sequence as resources are arranged in the new sequence, with the values being assigned at least according to resource characteristics;
(F) means for comparing the value scores for the current sequence and the new sequence to determine if the value score for the new sequence exceeds the value score for the current sequence according to predetermined criteria, and if the value score for the new sequence exceeds the value score for the current sequence, then designating the new sequence as the current sequence and proceeding to step (D), and if the value score for the current score exceeds the value score for the new sequence, then retaining the current sequence as the current sequence and proceeding to step (D); and
(G) means for returning to a system user the optimal sequence for production of the product.
12. The system as recited in claim 11, wherein the means for creating the representation of the production includes a computer-based representation of the equipment and the arrangement of such equipment.
13. The system as recited in claim 12, wherein the computer-based representation includes a virtual representation of the equipment and the arrangement of such equipment.
14. The system as recited in claim 11, wherein resource characteristics for a resource include restrictions associated with the operation of such resource.
15. The system as recited in claim 14, wherein the restrictions include restrictions associated with interaction of resources.
16. The system as recited in claim 11, wherein the means for calculating a value score for the current sequence, further includes computer-based:
(A) means for selecting the last resource in the current sequence and designating such resource as a current resource;
(B) means for determining if there is another resource upstream in the current sequence and if there is an upstream resource, selecting the upstream resource and designating such upstream resource as the current resource, and repeating step (B) until an upstream resource is not identified, then proceeding to step (C); and
(C) means for calculating a value score for the current sequence based on a composite of the assigned values of each of the resources of the current sequence selected at steps (A) and (B).
17. The system as recited in claim 11, wherein the means for calculating a value score for the current sequence, further includes computer-based:
(A) means for selecting the last resource in the new sequence and designating such resource as a current resource;
(B) means for determining if there is another resource upstream in the new sequence and if there is an upstream resource, selecting the upstream resource and designating such upstream resource as the current resource, and repeating step (B) until an upstream resource is not identified, then proceeding to step (C); and
(C) means for calculating a value score for the new sequence based on a composite of the assigned values of each of the resources of the new sequence selected at steps (A) and (B).
18. The system as recited in claim 16 or 17, wherein assigning a value to each resource includes a value based on at least a time score, energy score andor human resource score for that resource.
19. The system as recited in claim 18, wherein the system is capable of calculating a value score for a sequence at any point in time during operation of that sequence.
20. The system as recited in claim 11, wherein the system is capable of calculating a value score for a sequence that processes products in batch form.

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 recognizing instances of a 3D object in 3D scene data and for determining the 3D poses of said instances comprising the following steps:
(a) providing 3D scene data;
(b) selecting at least one reference point from the 3D scene data;
(c) computing, for each selected reference point, pose candidates for the 3D object under the assumption that said reference point is part of the 3D object;
(d) computing a set of filtered poses from the pose candidates.
2. The method of claim 1, wherein a 3D model is computed from the 3D object before step (a) and is used in steps (b), (c) and (d), comprising the following steps:
(m1) providing 3D object data of the 3D object;
(m2) creating from said 3D object data a 3D model for 3D object recognition and pose determination.
3. The method of claim 2, wherein step (m2) comprises:
(m2a) selecting at least two sample points from the 3D object data;
(m2b) computing the point pair descriptors that describe, for each pair of selected sample points, the two points and their relation;
(m2c) creating a global model description that stores the point pairs indexed by the point pair descriptor.
4. The method of claim 3, wherein step (m2c) comprises:
(m2d) sampling the point pair descriptors;
(m2e) creating a global model description that maps each sampled point pair descriptor to a list of point pairs, where each list contains all pairs of selected sample points with identical sampled point pair descriptor.
5. The method of claim 1, wherein in step (b) the reference points are selected randomly from the 3D scene data or by uniformly sampling the 3D scene data.
6. The method of claim 1, wherein in step (c) a score value is calculated for each pose candidate.
7. The method of claim 6, wherein the pose candidates are computed using a voting scheme.
8. The method of claim 7, wherein the voting scheme comprises the following steps:
(c1) sampling the space of possible object poses;
(c2) creating a counter for each pose space sample of step (c1);
(c3) selecting a set of scene points from the 3D scene data;
(c4) computing, for each selected scene point, the matching poses such that both the selected scene point and the reference point are on the surface of the 3D object;
(c5) increasing, for each pose computed in step (c4), the counter for the corresponding pose space sample;
(c6) detecting peak counter values in the sampled pose space and selecting the corresponding pose space samples as pose candidates.
9. The method of claim 8, wherein in step (c1) the space of possible object poses is represented by two parameters, where the first parameter is a point on the 3D object, and the second parameter is the angle that describes the rotation around the surface normal.
10. The method of claim 9, wherein the point on the 3D object is represented as index into a set of points selected from the 3D object data, and rotation angle is sampled by dividing the set of angles into intervals of equal size.
11. The method of claim 8, wherein in step (c4) the matching poses are computed using a data structure that allows to search for point pairs on the 3D object that are similar to the pair of the reference point and the selected scene point.
12. The method of claim 11, wherein the search for point pairs comprises the steps of:
(c4a) computing a point pair descriptor that describes the two points and their relation;
(c4b) using said point pair descriptor as index to the data structure.
13. The method of claim 12, wherein step (c4b) comprises:
(c4c) sampling the point pair descriptor;
(c4d) using a data structure that maps the sampled point pair descriptor to a list of point pairs.
14. The method of claim 13, where in step (c4d) a hash table is used as data structure.
15. The method of claim 7, wherein step (d) the computation comprises:
(d1) defining a neighbor relation between the pose candidates;
(d2) computing the score of each pose as the weighted sum of the scores of the neighboring pose candidates;
(d3) selecting the set of filtered poses by ranking the poses by the score computed in (d2).
16. The method of claim 15, wherein the neighborhood relation is defined by thresholding the difference in the translation of the poses and the rotation of the poses or by thresholding the maximum distance that a point on the 3D object can have under both poses.
17. The method of claim 15, further comprising a step where the poses selected in (d3) are recomputed as the average pose over the neighboring poses.
18. The method of claim 1, further comprising a step that refines each pose of the set of filtered poses by optimizing an error function that is based on the distances between the 3D scene and the 3D object under said pose.
19. The method of claim 1, further comprising a step computing a score for each pose of the set of filtered poses, where the score describes the consistency between the 3D scene and the 3D object under said pose.

1. An electronic apparatus comprising:
an optical system arranged such that light is concentrated toward an imaging surface of a solid-state imaging device, the solid state imaging device comprising:
a semiconductor layer including a photoelectric conversion element formed in a pixel region and a semiconductor element formed in a surface side opposite to a surface through which light enters;
a wiring layer provided over a surface of the semiconductor layer so as to cover the semiconductor element;
a support substrate provided over the wiring layer at an opposite side of the semiconductor layer;
a bonding layer provided between the wiring layer and the support substrate, wherein the wiring layer includes a pad electrode and an opening formed so that a surface of the pad electrode is exposed; and
first and second convex sections provided in a region where the pad electrode is formed, the first convex section provided at a surface of the wiring layer which opposes the support substrate and the second convex section provided at a surface of the support substrate which opposes the wiring layer, wherein the first and second convex sections are formed between a portion of the pad electrode and the support substrate.
2. An electronic apparatus comprising:
an optical system arranged such that light is concentrated toward an imaging surface of a solid-state imaging device, the solid-state imaging device comprising:
a semiconductor layer including a photoelectric conversion element formed in a pixel region and a semiconductor element formed in a surface side opposite to a surface through which light enters;
a wiring layer, having a first convex section, provided over a surface of the semiconductor layer so as to cover the semiconductor element;
a support substrate, having a second convex section, provided over the wiring layer at an opposite side of the semiconductor layer;
a bonding layer provided between the wiring layer and the support substrate, wherein the wiring layer includes a pad electrode and an opening formed so that a surface of the pad electrode is exposed;
wherein
the first and second convex sections are provided in a region where the pad electrode is formed, the first convex section is provided at a surface of the wiring layer which opposes the support substrate, the second convex section is provided at a surface of the support substrate which opposes the wiring layer, and the first and second convex sections are formed in a same vertical plane between a portion of the pad electrode and the support substrate.
3. A semiconductor device comprising:
a semiconductor layer which has a semiconductor element formed on a surface thereof;
a wiring layer provided over a surface of the semiconductor layer so as to cover the semiconductor element;
a support substrate provided over the wiring layer at an opposite side of the semiconductor layer; and
a bonding layer provided between the wiring layer and the support substrate, wherein the wiring layer includes a pad electrode and an opening formed so that a surface of the pad electrode is exposed;
wherein
the first and second convex sections are provided in a region where the pad electrode is formed, the first convex section is provided at the wiring layer which opposes the support substrate, the second convex section is provided at a surface of the support substrate which opposes the wiring layer, and the first and second convex sections are formed in a same vertical plane between a portion of the pad electrode and the support substrate.
4. The solid-state imaging device according to claim 1, wherein a bonding wire is connected on a surface of the pad electrode which is exposed due to the opening.
5. The solid-state imaging device according to claim 1,
wherein a pixel transistor which reads out an electrical charge which is generated by the photoelectric conversion element is formed in the pixel region as the semiconductor element,
a peripheral transistor which configures a peripheral circuit which drives the pixel is formed in a peripheral region which is positioned in the periphery of the pixel region as the semiconductor element, and
the bonding layer is thinner in a portion where the pad electrode is formed than in a portion where the peripheral circuit is formed in the peripheral region.
6. The solid-state imaging device according to claim 5, further comprising:
a third convex section provided in a region which is cut in a scribe region and positioned in the periphery of the peripheral region in at least either of the surface of the wiring layer which opposes the support substrate or the surface of the support substrate which opposes the wiring layer,
wherein the bonding layer is thinner in the portion which is cut in the scribe region than at least in the portion of the pixel region.
7. The electronic apparatus according to claim 2, wherein a bonding wire is connected on a surface of the pad electrode which is exposed due to the opening.
8. The electronic apparatus according to claim 2,
wherein a pixel transistor which reads out an electrical charge which is generated by the photoelectric conversion element is formed in the pixel region as the semiconductor element,
a peripheral transistor which configures a peripheral circuit which drives the pixel is formed in a peripheral region which is positioned in the periphery of the pixel region as the semiconductor element, and
the bonding layer is thinner in a portion where the pad electrode is formed than in a portion where the peripheral circuit is formed in the peripheral region.
9. The electronic apparatus according to claim 8, further comprising:
a third convex section provided in a region which is cut in a scribe region and positioned in the periphery of the peripheral region in at least either of the surface of the wiring layer which opposes the support substrate or the surface of the support substrate which opposes the wiring layer,
wherein the bonding layer is thinner in the portion which is cut in the scribe region than at least in the portion of the pixel region.
10. The semiconductor device according to claim 3, wherein a bonding wire is connected on a surface of the pad electrode which is exposed due to the opening.
11. The semiconductor device according to claim 3,
wherein a pixel transistor which reads out an electrical charge which is generated by the photoelectric conversion element is formed in the pixel region as the semiconductor element,
a peripheral transistor which configures a peripheral circuit which drives the pixel is formed in a peripheral region which is positioned in the periphery of the pixel region as the semiconductor element, and
the bonding layer is thinner in a portion where the pad electrode is formed than in a portion where the peripheral circuit is formed in the peripheral region.
12. The semiconductor device according to claim 11, further comprising:
a third convex section provided in a region which is cut in a scribe region and positioned in the periphery of the peripheral region in at least either of the surface of the wiring layer which opposes the support substrate or the surface of the support substrate which opposes the wiring layer,
wherein the bonding layer is thinner in the portion which is cut in the scribe region than at least in the portion of the pixel region.
13. The solid-state imaging device according to claim 1, wherein the bonding layer comprises an adhesive.
14. The electronic apparatus according to claim 2, wherein the bonding layer comprises an adhesive.

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 network load management apparatus configured to balance a data load across a plurality of network connections, comprising:
a network condition monitoring module configured to monitor a network parameter from each of said plurality of network connections; and
an automatic data balancing module configured to balance said data load across said plurality of network connections in correspondence with said network parameter and a predetermined configuration parameter, wherein
said predetermined configuration parameter comprising at least one of
a predetermined output rate,
a predetermined output quality,
a cost,
a packet priority,
a security parameter, and
a queue size.
2. The apparatus of claim 1, wherein said network parameter comprises at least one of:
a ready terminal set parameter;
a loop back state parameter;
an input rate parameter;
an output rate parameter;
an input packet parameter;
an output packet parameter;
an input error parameter;
a buffer failure parameter;
a cyclic redundancy check (CRC) parameter;
a frame errors (FE) parameter;
an overruns parameter;
an abort parameter;
a carrier transition parameter;
a data carrier detect (DCD) parameter,
a data set ready (DSR) parameter;
a data terminal ready (DTR) parameter; and
a clear to send (CTS) parameter.
3. The apparatus of claim 1, further comprising:
a packet allocation module configured to allocate a plurality of non-randomized local packets corresponding to a local file to said plurality of network connections so as to create a first plurality of randomized transmission packets, and to re-aggregate a plurality of randomized received packets received from said plurality of network connections so as to create a replica of a plurality of non-randomized remote packets corresponding to a remote file.
4. The apparatus of claim 3, wherein
said packet allocation module is further configured to pad at least one of said plurality of non-randomized local packets.
5. The apparatus of claim 3, further comprising
a channel bonding module configured to allocate data packets from another local file to a subset of said plurality of network connections.
6. The apparatus of claim 5, wherein
said channel bonding module is further configured to allocate said plurality of non-randomized local packets corresponding to said local file to a subset of said plurality of network connections.
7. The apparatus of claim 3, wherein
said packet allocation module is further configured to add a dynamic encryption local file identifier to said plurality of non-randomized local packets corresponding to said local file.
8. The apparatus of claim 1, further comprising:
a dynamic domain name server redirector module configured to redirect a network address in correspondence with said network parameter and said predetermined configuration parameter.
9. The apparatus of claim 8, wherein
said dynamic domain name server redirector module is further configured to establish a predetermined time-to-live constraint for a predetermined host.
10. The apparatus of claim 1, further comprising:
a remote network load management apparatus monitor and backup module configured to monitor and backup a second network load management apparatus;
a network load management apparatus remote status reporting module configured to provide local status information to one of said second remote network load management apparatus and a third remote network load management apparatus; and
network load management apparatus remote control module configured to receive remote control information from one of said second remote network load management apparatus and said third remote network load management apparatus.
11. The apparatus of claim 1, further comprising:
an event log writer; and
an alarm manager, wherein
said alarm manager is configured to write an event in said event log and to send at least one of a notification email message, a notification facsimile message, and a notification page message when a predetermined alarm condition is detected.
12. The apparatus of claim 11, wherein
said alarm manager is further configured to perform at least one of turn on a backup power source, execute a remote configuration change operation in a router, and execute a remote configuration change operation in a host device in response to said predetermined alarm condition.
13. The apparatus of claim 1, further comprising:
a command input module; and
a status display module.
14. A network load management apparatus configured to balance a data load across a plurality of network connections, comprising:
means for monitoring a network parameter from each of said plurality of network connections; and
means for automatic balancing said data load across said plurality of network connections in correspondence with said network parameter and a predetermined configuration parameter, wherein
said predetermined configuration parameter comprising at least one of
a predetermined output rate,
a predetermined output quality,
a cost,
a packet priority,
a security parameter, and
a queue size.
15. A system configured to balance data packet loads across a plurality of network connections, comprising:
a first network load management apparatus connecting a first host device to at least one network via a first plurality of network connections; and
a second network load management apparatus connecting a second host device to said at least one network via a second plurality of network connections, wherein
said first host device and said second host device are configured to exchange data packets with each other, and
said first network load management apparatus and said second network load management apparatus each includes
a network condition monitoring module configured to monitor a network parameter from each of a respective plurality of network connections, and

an automatic data balancing module configured to balance said data load across said respective plurality of network connections in correspondence with said network parameter and a predetermined configuration parameter, said predetermined configuration parameter comprising at least one of
a predetermined output rate,
a predetermined output quality,
a cost,
a packet priority,
a security parameter, and
a queue size.
16. The system of claim 15, wherein
said first network load management apparatus is connected to said at least one network via a third network load management apparatus.
17. The system of claim 15, wherein
said second network load management apparatus is connected to said at least one network via a fourth network load management apparatus.
18. The system of claim 15, wherein
said first network load management apparatus is connected to said first host device via a router.
19. The system of claim 15, wherein
said first network load management apparatus connects to said first host device via a firewall.
20. The system of claim 15, further comprising:
a fifth network load management apparatus configured to monitor and control at least one of said first network load management apparatus and said second network load management apparatus.
21. The system of claim 15, further comprising:
an encryption device configured to encrypt an output of said first network load management apparatus; and
a decryption device configured to decrypt an input to said second network load management apparatus.
22. A method for managing network data loads between a plurality of host devices and a plurality of network connections, comprising steps of:
monitoring a network parameter from each of said plurality of network connections; and
automatically balancing said data load across said plurality of network connections in correspondence with said network parameter and a predetermined configuration parameter, wherein
said predetermined configuration parameter is at least one of
a predetermined output rate,
a predetermined output quality,
a cost,
a packet priority,
a security parameter, and
a queue size.
23. The method of claim 22, wherein said network parameter comprises at least one of:
a ready terminal set parameter;
a loop back state parameter;
an input rate parameter;
an output rate parameter;
an input packet parameter;
an output packet parameter;
an input error parameter;
a buffer failure parameter;
a cyclic redundancy check (CRC) parameter;
a frame errors (FE) parameter;
an overruns parameter;
an abort parameter;
a carrier transition parameter;
a data carrier detect (DCD) parameter;
a data set ready (DSR) parameter;
a data terminal ready (DTR) parameter; and
a clear to send (CTS) parameter.
24. The method of claim 22, further comprising one of a step of:
allocating a plurality of non-randomized local packets corresponding to a local file to said plurality of network connections so as to create a first plurality of randomized transmission packets; and
re-aggregating a plurality of randomized received packets received from said plurality of network connections so as to create a replica of a plurality of non-randomized remote packets corresponding to a remote file.
25. The method of claim 24, further comprising a step of:
padding at least one of said plurality of non-randomized local packets.
26. The method of claim 24, further comprising a step of:
adding a dynamic encryption local file identifier to said plurality of non-randomized local packets corresponding to said local file.
27. The method of claim 24, further comprising a step of:
allocating data packets from another local file to a subset of said plurality of network connections.
28. The method of claim 27, further comprising a step of:
allocating said plurality of non-randomized local packets corresponding to a local file to a subset of said plurality of network connections.
29. The method of claim 22, further comprising a step of:
redirecting a network address in correspondence with said network parameter and said predetermined configuration parameter.
30. The method of claim 29, further comprising a step of:
establishing a time-to-live constraint for a predetermined host.
31. The method of claim 22, further comprising a step of:
remotely monitoring and backing up a second network load management apparatus.
32. The method of claim 31, further comprising a step of:
controlling at least one of said first network load management apparatus and said second network load management apparatus by a third network load management apparatus.
33. The method of claim 22, further comprising steps of:
writing an event in an event log when a predetermined alarm condition is detected; and
sending at least one of a notification email message, a notification facsimile message, and a notification page message.
34. The method of claim 33, further comprising at least one of a step of:
turning on a backup power source;
executing a remote configuration change operation in a router; and
executing a remote configuration change operation in a host device.
35. The method of claim 22, further comprising steps of:
inputting commands and configuration information via a command input module; and
displaying a status in a status display module.
36. A computer program product comprising a plurality of instructions for managing network data loads between a plurality of host devices and a plurality of network connections, comprising:
instructions for monitoring a network parameter from each of said plurality of network connections; and
instructions for automatically balancing said data load across said plurality of network connections in correspondence with said network parameter and a predetermined configuration parameter, wherein
said predetermined configuration parameter is at least one of
a predetermined output rate,
a predetermined output quality,
a cost,
a packet priority,
a security parameter, and
a queue size.
37. The computer program product of claim 36, wherein said network parameter comprises at least one of:
a ready terminal set parameter;
a loop back state parameter;
an input rate parameter;
an output rate parameter;
an input packet parameter;
an output packet parameter;
an input error parameter;
a buffer failure parameter;
a cyclic redundancy check (CRC) parameter;
a frame errors (FE) parameter;
an overruns parameter;
an abort parameter;
a carrier transition parameter;
a data carrier detect (DCD) parameter;
a data set ready (DSR) parameter;
a data terminal ready (DTR) parameter; and
a clear to send (CTS) parameter.