Author: claimsbot

1. A computer-implemented method for estimating performance of a classifier comprising:
using suitably programmed hardware to associate a feature variability with at least one of one or more features that characterize a sample from multiple samples, each of which is characterized by one or more features;
using the classifier to compute, with the hardware, one or more scores for one or more samples in a subset of samples from the multiple samples, where the classifier can be used to determine a class to which a sample belongs based on the one or more features that characterize that sample;
using the hardware to associate a score variability with at least one of the one or more scores using the feature variability; and
computing, with the hardware, a probability of misclassification by the classifier using one or more of the one or more scores and the score variability.
2. The computer-implemented method of claim 1, where the multiple samples are multiple tissue samples.
3. The computer-implemented method of claim 1, where the classifier is a linear discriminant function classifier.
4. The computer-implemented method of claim 1, where the classifier is a quadratic discriminant function classifier.
5. The computer-implemented method of claim 1, where the classifier is a neural network classifier.
6. The computer-implemented method of claim 1, where the feature variability is estimated using multiple measurements of one of the one or more features.
7. The computer-implemented method of claim 1, where the using hardware to associate a score variability with at least one of the one or more scores includes using a linear approximation of the classifier.
8. A physical computer readable medium comprising machine-readable instructions for implementing the computer-implemented method of claim 1.
9. A computer-implemented method comprising:
using suitably programmed hardware to associate a feature variability with at least one of one or more features on a feature-by-feature basis, the one or more features characterizing a sample from multiple samples, each of which is characterized by one or more features;
computing, with the hardware, a first probability of misclassification by a neural network classifier using the feature variability; and
computing, with the hardware, a first probability of misclassification by a classifier using the feature variability, where the classifier can be used to determine a class to which a sample belongs based on the one or more features that characterize that sample.
10. The computer-implemented method of claim 9, where the multiple samples are multiple tissue samples.
11. The computer-implemented method of claim 9, where the feature variability is estimated using multiple measurements of one of the one or more features.
12. A computer-implemented method comprising:
using suitably programmed hardware to associate a feature variability with at least one of one or more features on a feature-by-feature basis, the one or more features characterizing a sample from multiple samples, each of which is characterized by one or more features; and
computing, with the hardware, a first probability of misclassification by a first classifier using the feature variability, where the first classifier can be used to determine a class to which a sample belongs based on the one or more features that characterize that sample;
where the computing, with the hardware, a first probability of misclassification by a first classifier includes using a linear approximation of the first classifier prior to compute the first probability of misclassification.
13. A physical computer readable medium comprising machine-readable instructions for implementing the computer-implemented method of any of claims 9, 10, 11, and 12.
14. A computer-implemented method for estimating performance of a classifier comprising:
using suitably programmed hardware to associate a feature variability with at least one of one or more features that characterize a sample from multiple samples, each of which is characterized by one or more features;
using a first classifier to compute, with the hardware, one or more first scores for one or more first samples in a subset of samples from the multiple samples, where the first classifier can be used to determine a class to which a sample belongs based on the one or more features that characterize that sample;
using the hardware to associate a first score variability with at least one of the one or more first scores using the feature variability;
computing, with the hardware, a first probability of misclassification by the first classifier using one or more of the one or more first scores and the first score variability;
using a second classifier to compute, with the hardware, one or more second scores for one or more second samples in a subset of samples from the multiple samples, where the second classifier can be used to determine a class to which a sample belongs based on the one or more features that characterize that sample;
using the hardware to associate a second score variability with at least one of the one or more second scores using the feature variability;
computing, with the hardware, a second probability of misclassification by the second classifier using one or more of the one or more second scores and the second score variability; and
determining, with the hardware, a final probability of misclassification from a group of probabilities of misclassification that includes the first and second probabilities of misclassification.
15. A physical computer readable medium comprising machine-readable instructions for implementing the computer-implemented method of any of claims 1-7.
16. A physical computer readable medium comprising machine-readable instructions for implementing the computer-implemented method of claim 14.

The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.

1-12. (canceled)
13. An ophthalmologic apparatus comprising:
an acquisition unit for acquiring a moving image of an eye to be inspected, which moving image is acquired based on a return light from the eye to be inspected illuminated by an observation light from an observation light source;
a determination unit for determining a light intensity of the observation light source and a light intensity of a photographing light source, based on a value corresponding to an instruction input by an operator and an intensity of the moving image of the eye to be inspected; and
a control unit for controlling the observation light source and the photographing light source, based on the determined light intensities.
14. An ophthalmologic apparatus according to claim 13, wherein the determination unit determines the light intensities of the observation light source and the photographing light source, in accordance with one instruction input from the operator.
15. An ophthalmologic apparatus according to claim 13, wherein the determination unit determines the light intensities of the observation light source and the photographing light source, in accordance with various instructions input from the operator.
16. An ophthalmologic apparatus according to claim 13, further comprising a plurality of independent input units for inputting by the operator an instruction of an increase of the value and an instruction of a decrease of the value.
17. An ophthalmologic apparatus according to claim 13, further comprising a common input unit for inputting by the operator instructions of an increase of the value and a decrease of the value.
18. An ophthalmologic apparatus according to claim 13, further comprising a switching unit for switching between an on state and an off state of the control of the control unit,
wherein the determination unit determines the light intensities of the observation light source and the photographing light source so that the determined light intensities corresponding to the values are different from others, in accordance with cases where the control of the control unit is on state or off state.
19. An ophthalmologic apparatus comprising:
an acquisition unit for acquiring a moving image of an eye to be inspected, which moving image is acquired based on a return light from the eye to be inspected illuminated by an observation light from an observation light source; and
a control unit for controlling a light intensity of the observation light source and a light intensity of a photographing light source, based on a value corresponding to an instruction input by an operator and an intensity of the moving image of the eye to be inspected.
20. An ophthalmologic apparatus comprising:
an acquisition unit for acquiring a moving image of an eye to be inspected, which moving image is acquired based on a return light from the eye to be inspected illuminated by an observation light from an observation light source;
a determination unit for determining a light intensity of a photographing light source, based on a value corresponding to an instruction input by an operator and an intensity of the moving image of the eye to be inspected; and
a control unit for controlling the photographing light source, based on the determined light intensity.
21. An ophthalmologic apparatus comprising:
an acquisition unit for acquiring a moving image of an eye to be inspected, which moving image is acquired based on a return light from the eye to be inspected illuminated by an observation light from an observation light source;
a determination unit for determining a light intensity of the observation light source, based on a value corresponding to an instruction input by an operator and an intensity of the moving image of the eye to be inspected; and
a control unit for controlling the observation light source, based on the determined light intensity.
22. An ophthalmologic method comprising the steps of:
acquiring a moving image of an eye to be inspected, which moving image is acquired based on a return light from the eye to be inspected illuminated by an observation light from an observation light source;
determining a light intensity of the observation light source and a light intensity of a photographing light source, based on a value corresponding to an instruction input by an operator and an intensity of the moving image of the eye to be inspected; and
controlling the observation light source and the photographing light source, based on the determined light intensities.
23. An ophthalmologic method comprising the steps of:
acquiring a moving image of an eye to be inspected, which moving image is acquired based on a return light from the eye to be inspected illuminated by an observation light from an observation light source; and
controlling a light intensity of the observation light source and a light intensity of a photographing light source, based on a value corresponding to an instruction input by an operator and an intensity of the moving image of the eye to be inspected.
24. An ophthalmologic method comprising the steps of:
acquiring a moving image of an eye to be inspected, which moving image is acquired based on a return light from the eye to be inspected illuminated by an observation light from an observation light source;
determining a light intensity of a photographing light source, based on a value corresponding to an instruction input by an operator and an intensity of the moving image of the eye to be inspected; and
controlling the photographing light source, based on the determined light intensity.
25. An ophthalmologic method comprising the steps of:
acquiring a moving image of an eye to be inspected, which moving image is acquired based on a return light from the eye to be inspected illuminated by an observation light from an observation light source;
determining a light intensity of the observation light source, based on a value corresponding to an instruction input by an operator and an intensity of the moving image of the eye to be inspected; and
controlling the observation light source, based on the determined light intensity.
26. A non-transitory tangible medium having recorded thereon a program for causing a computer to perform steps of the ophthalmologic method according to claim 22.
27. A non-transitory tangible medium having recorded thereon a program for causing a computer to perform steps of the ophthalmologic method according to claim 23.
28. A non-transitory tangible medium having recorded thereon a program for causing a computer to perform steps of the ophthalmologic method according to claim 24.
29. A non-transitory tangible medium having recorded thereon a program for causing a computer to perform steps of the ophthalmologic method according to claim 25.

1. A coin identifying sensor comprising:
an integrated sensor body;
a plurality of sensors, each of said sensors having a core wound with a coil, said sensors being integrated in said integrated sensor body with said sensors arranged in a row and fixedly disposed in said sensor body.
2. A coin identifying sensor according to claim 1, wherein said integrated sensor body is provided adjacent to a coin path of a coin selector, and disposed in a direction crossing a movement direction of a coin, and the sensor row has three of said sensors aligned laterally, with each of two end sensors positioned corresponding to pass-through positions for both ends of a coin passing through the coin path and a remaining central sensor positioned corresponding to a pass-through position for a center of the coin.
3. A coin identifying sensor according to claim 2, wherein the integrated sensor body comprises a core main body with three protruding rectangular cores aligned laterally at intervals and three rectangular coils wound around the respective protruding cores.
4. A coin selector with coin identifying apparatus, the coin selector comprising:
coin selector main body defining a coin path;
a first rectangular coin identifying sensor including a plurality of sensors, each of said sensors having a core wound with a coil, said sensors being integrated in a sensor row the sensor row comprises a core main body with three protruding rectangular cores aligned laterally at intervals and three rectangular coils wound around the respective protruding cores;
a second rectangular coin identifying sensor including a plurality of sensors, each of said sensors having a core wound with a coil, said sensors being integrated in a sensor row the sensor row comprises a core main body with three protruding rectangular cores aligned laterally at intervals and three rectangular coils wound around the respective protruding cores, said first rectangular coin identifying sensor and said second rectangular coin identifying sensor forming a pair of coin identifying sensors with said first rectangular coin identifying sensor disposed opposite said second rectangular coin identifying sensor to form a coin detecting section whereby a coin is detected at the coin detecting section.
5. A coin selector with coin identifying apparatus according to claim 4, further comprising:
another first rectangular coin identifying sensor including a plurality of sensors, each of said sensors having a core wound with a coil, said sensors being integrated in a sensor row the sensor row comprises a core main body with three protruding rectangular cores aligned laterally at intervals and three rectangular coils wound around the respective protruding cores;
another second rectangular coin identifying sensor including a plurality of sensors, each of said sensors having a core wound with a coil, said sensors being integrated in a sensor row the sensor row comprises a core main body with three protruding rectangular cores aligned laterally at intervals and three rectangular coils wound around the respective protruding cores, said another first rectangular coin identifying sensor and said another second rectangular coin identifying sensor forming another pair of coin identifying sensors with said another first rectangular coin identifying sensor disposed opposite said another second rectangular coin identifying sensor to form a second coin detecting section whereby a coin is detected at the second coin detecting section wherein said coin detecting section and said second coin detecting section each sandwich the coin path and are sequentially disposed on the coin path in the movement direction of a coin.
6. A coin selector with coin identifying apparatus according to claim 5, wherein the first coin detecting section and the second coin detecting section are disposed in a vertical relationship on the coin path formed vertically.
7. A coin selector with coin identifying apparatus according to claim 5, wherein the first coin detecting section has a first diameter detection sensor which detects a diameter of a coin by both end sensors positioned corresponding to pass-through positions for both ends of a coin respectively and a material sensor for material detection positioned corresponding to a pass-through position for a center of the coin, while the second coin detecting section has a second diameter detection sensor which detects a diameter of a coin by both end sensors positioned corresponding to pass-through positions for the right and left ends of a coin and a thickness sensor for coin thickness detection positioned corresponding to a pass-through portion for a center of the coin.
8. A coin selector with coin identifying apparatus according to claim 7, wherein a detection output of the material sensor is picked up at the time of output of a diameter data peak value of the first diameter detection sensor, and obtained as material discrimination value data, and a detection output of the thickness sensor is picked up at the time of output of a diameter data peak value of the second diameter detection sensor, and obtained as thickness determination value data, so that whether the coin is real or not is determined based upon these diameter, material and thickness data.
9. A coin selector with coin identifying apparatus, the coin selector comprising:
coin identifying sensor comprising a core body with a plurality of cores and a plurality of windings to provide a plurality of sensors in an integrated sensor body, each of said sensors including one of said cores wound with one of said coils, said sensors being integrated in said integrated sensor body with said sensors arranged in a row and fixedly disposed in said sensor body; and
a coin selector main body defining a coin path, said coin identifying sensor being fixed adjacent to a coin path.
10. A coin selector with coin identifying apparatus according to claim 9, wherein said integrated sensor body is disposed in a direction crossing a movement direction of a coin, and the sensor row has three of said sensors aligned laterally, with each of two end sensors positioned corresponding to pass-through positions for each of outer ends of a coin passing through the coin path and a remaining central sensor positioned corresponding to a pass-through position for a center of the coin.
11. A coin selector with coin identifying apparatus according to claim 10, wherein the integrated sensor body comprises a core main body with said cores being rectangular and integrated and extending outwardly and aligned laterally at intervals and said coils comprise three rectangular coils wound around the respective protruding cores.
12. A coin selector with coin identifying apparatus according to claim 11, further comprising:
another coin identifying sensor comprising another integrated sensor body including a core main body with rectangular cores extending outwardly and aligned laterally at intervals and coils comprising three rectangular coils wound around the respective protruding cores to provide a plurality of sensors, each of said sensors including one of said cores wound with one of said coils, said sensors being arranged in a row and fixedly disposed in said sensor body, said coin identifying sensor and said another coin identifying sensor forming a pair of coin identifying sensors with said coin identifying sensor disposed opposite said another coin identifying sensor to form a coin detecting section whereby a coin is detected at the coin detecting section.
13. A coin selector with coin identifying apparatus according to claim 12, further comprising:
another pair of coin identifying sensors, said another pair of coin identifying sensors forming another coin detecting section whereby a coin is detected at said another coin detecting section wherein said coin detecting section and said another coin detecting section each sandwich the coin path and are sequentially disposed on the coin path in the movement direction of a coin.
14. A coin selector with coin identifying apparatus according to claim 12, wherein said coin detecting section and said another coin detecting section are disposed in a vertical relationship on the coin path formed vertically.
15. A coin selector with coin identifying apparatus according to claim 5, wherein said coin detecting section has a first diameter detection sensor which detects a diameter of a coin by both end sensors of one of said integrated sensor bodies positioned corresponding to pass-through positions for both ends of a coin respectively and a material sensor for material detection positioned corresponding to a pass-through position for a center of the coin, while said another coin detecting section has a second diameter detection sensor which detects a diameter of a coin by both end sensors of one of said integrated sensor bodies positioned corresponding to pass-through positions for the right and left ends of a coin and a thickness sensor for coin thickness detection of one of said integrated sensor bodies positioned corresponding to a pass-through portion for a center of the coin.
16. A coin selector with coin identifying apparatus according to claim 14, further comprising a detection circuit with a processor receiving a detection output of the material sensor picked up at the time of output of a diameter data peak value of the first diameter detection sensor, and obtained as material discrimination value data, and a detection output of the thickness sensor picked up at the time of output of a diameter data peak value of the second diameter detection sensor, and obtained as thickness determination value data, so that whether the coin is real or not is determined based upon these diameter, material and thickness data.

The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.

I claim:

1. A bed pivotable from a horizontal position to an upright position comprising:
a base frame;
a mattress supporting platform having two end portions and being hinged to said base frame for pivoting between a generally horizontal position and a generally upright position; and
a counterweight container having a generally flat side intersected along two edges by a generally arcuate side, said container having a sealable opening adjacent one said intersecting edge of said flat and arcuate sides for filling said container with a fluid material, said sealable opening being positioned above the fluid material in said container in said horizontal or generally upright position to thereby prevent leakage from sealable opening;
whereby a storable bed has a fillable container counterweight having an opening positioned to avoid spilling any fluid contained therein.
2. The bed in accordance with claim 1 including a counterbalancing spring connected between said platform one end portion and said base frame for adding additional counterbalancing force to said bed.
3. The bed in accordance with claim 2 in which said platform has a pair of foldable legs attached thereto for supporting one end of said platform in a horizontal position and foldable into a storage position when said platform is in a generally upright position.
4. The bed in accordance with claim 3 including a cabinet having said base frame mounted therein and shaped to receive said platform in an upright storage position.