Author: claimsbot

1. A manufacturing method of a semiconductor device comprising:
forming an oxide semiconductor layer wherein the oxide semiconductor layer comprises an oxide including crystals;
forming a first film over the oxide semiconductor layer;
forming a second film over the first film;
selectively etching the second film under a condition that the first film is less etched than the second film, so that the first film is exposed; and
selectively etching the first film under a condition that the first film is more easily etched than the oxide semiconductor layer, so that the oxide semiconductor layer is exposed.
2. The manufacturing method of a semiconductor device according to claim 1, further comprising a step of forming an insulating film over the oxide semiconductor layer, the first film, and the second film.
3. The manufacturing method of a semiconductor device according to claim 1, wherein a thickness of the first film is equal to or less than a thickness of the oxide semiconductor layer.
4. The manufacturing method of a semiconductor device according to claim 1, wherein the second film has a stacked-layer structure including a film including aluminum as a material.
5. The manufacturing method of a semiconductor device according to claim 1, wherein the first film comprises a tungsten film.
6. The manufacturing method of a semiconductor device according to claim 1, wherein the oxide semiconductor layer comprises indium, gallium, and zinc as main components.
7. The manufacturing method of a semiconductor device according to claim 1, further comprising:
forming a gate electrode layer; and
forming a gate insulating film over the gate electrode layer before forming the oxide semiconductor layer.
8. The manufacturing method of a semiconductor device according to claim 1, further comprising:
forming a gate insulating film over the oxide semiconductor layer before selectively etching the first film; and
forming a gate electrode layer over the gate insulating film to overlap with the oxide semiconductor layer.
9. The manufacturing method of a semiconductor device according to claim 1, wherein the crystals have c-axis alignment.
10. The manufacturing method of a semiconductor device according to claim 1, wherein the first film is conductive.
11. The manufacturing method of a semiconductor device according to claim 1, wherein the second film is conductive.
12. The manufacturing method of a semiconductor device according to claim 1, wherein a thickness of the oxide semiconductor layer is equal to or larger than 3 nm and equal to or smaller than 30 nm.

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 of correcting print images in an electrophotographic printer wherein an image formed by a print head on a peripheral surface of a photoconductor drum is transferred and printed on a sheet of paper, characterized in that it comprises the steps of:
furnishing the print head with a standard tacho signal in the form of pulses and thereby printing on a sheet of paper a check mark for each given number of pulses of the standard tacho signal while the photoconductor drum makes one rotation;
by a camera, detecting a periodic deviation in each spacing between successive such check marks;
in response to the deviation in each spacing between the successive check marks, varying the pulse width of pulses of the standard tacho signal for each spacing between the successive check marks, thereby to provide a modified tacho signal; and
effecting printing thereafter based on the modified tacho signal.
2. A method of correcting print images in an electrophotographic printer as set forth in claim 1, characterized in that after the check marks are made constant in spacing subsequent to furnishing of the modified tacho signal, the check marks are no longer printed.
3. A method of correcting print images in an electrophotographic printer as set forth in claim 1, further including the control unit counting a number of pulses of a tacho signal detected between successive check marks and comparing the counted number of pulses of the tacho signal with a number of pulses of the tacho signal between regular dimensional check mark points.
4. A method of correcting print images in an electrophotographic printer as set forth in claim 1, including upon detecting an origin using a sensor, said pulse generator generates pulses at a fixed frequency until the photoconductor drum makes one rotation until the origin is next detected.
5. An apparatus for correcting print images in an electrophotographic printer wherein an image formed by a print head on a peripheral surface of a photoconductor drum is transferred and printed on a sheet of paper, characterized in that it comprises:
a proximity sensor for detecting a rotary position of the photoconductor drum;
a pulse generator responsive to an input signal from the proximity sensor for furnishing the print head with a tacho signal in the form of pulses while the photoconductor drum makes one rotation;
a control unit for controlling the tacho signal furnished from the pulse generator into the print head to cause a check mark to be printed for each given number of pulses of the tacho signal on the sheet of paper while the photoconductor drum makes one rotation; and
a camera for detecting a deviation in each spacing between successive such check marks printed from the photoconductor drum on the sheet of paper,
wherein said control unit is responsive to a detection value detected by the camera to vary the pulse width of pulses of the tacho signal for each spacing between the successive check marks for furnishing a modified tacho signal into the print head.
6. An apparatus for correcting print images in an electrophotographic printer as set forth in claim 5, wherein said control unit is configured such that after the check marks are made constant in spacing subsequent to furnishing of the modified tacho signal, the check marks are no longer printed.
7. An apparatus for correcting print images in an electrophotographic printer as set forth in claim 5, including upon detecting an origin using the proximity sensor, said pulse generator generating pulses at a fixed frequency until the photoconductor drum makes one rotation until the origin is next detected.
8. An apparatus for correcting print images in an electrophotographic printer as set forth in claim 5, further including the control unit counts a number of pulses of a tacho signal detected between successive check marks and compares the counted number of pulses of the tacho signal with a number of pulses of the tacho signal between regular dimensional check mark points.

1. A stock analysis method for performing an analysis on a plurality of stocks to select target ones to be boughtsold from the stocks, the company of each of the stocks belonging to a corresponding classified industry, said stock analysis method comprising the steps of:
a) calculating stock return data of each of the stocks, market return data, and classified industry return data of each of the corresponding classified industries based on historical stock price information within a historical trading period that includes a current trading period and that consists of a number (N) of consecutive time intervals;
b) according to the stock return data, the market return data and the classified industry return data obtained in step a), determining
whether a stock return of each of the stocks in each of the N time intervals is greater than a classified industry return of the corresponding classified industry in a corresponding one of the N time intervals,
whether the stock return of each of the stocks in the corresponding one of the N time intervals is greater than a market return in the corresponding one of the N time intervals, and
whether the classified industry return of the corresponding one of the classified industries in the corresponding one of the N time intervals is greater than the market return in the corresponding one of the N time intervals;
c) based on results determined in step b), grouping the stocks so that each of the stocks in each of the N time intervals is grouped into a corresponding one of a number (G) of different groups;
d) obtaining clustering data of each of the stocks corresponding to each of the N time intervals and associated with the groups based on a specific one of the groups using a clustering mode;
e) estimating by a computer, analysis data of each of the stocks corresponding to a coming time interval based on at least the clustering data obtained in step d); and
f) determining any ones of the stocks whose analysis data estimated in step e) matches predetermined selection criteria as the target ones of the stocks;
wherein, in step d):
the clustering mode is one of a combination clustering mode and a permutation clustering mode;
in the combination clustering mode, the clustering data of each of the stocks corresponding to an ith one of the N time intervals includes the corresponding one of the groups in the ith one of the N time intervals, and a number (Si) of the time intervals in a reference period from i\u2212(Q\u22121)th to ith ones of the N time intervals, where 1\u2266i\u2266N and 2\u2266Q\u2266i, wherein a corresponding one of the stocks is grouped into said specific one of the groups in the number (Si) of the time intervals; and
in the permutation clustering mode, the clustering data of each of the stocks corresponding to the ith one of the N time intervals includes the corresponding one of the groups in the ith one of the N time intervals, and group permutation pattern consisting of the corresponding ones of the groups that correspond respectively to i\u2212(Q\u22121)th to ith ones of the N time intervals.
2. The stock analysis method as claimed in claim 1, wherein, in step c), G=8, where
a first group represents that the classified industry return is greater than the market return, and that stock return is greater than the classified industry return and the market return,
a second group represents that the classified industry return is greater than the market return, that the stock return is greater than the classified industry return, and that the stock return is not greater than the market return,
a third group represents that the classified industry return is greater than the market return, that the stock return is not greater than the classified industry return, and that the stock return is greater than the market return,
a fourth group represents that the classified industry return is greater than the market return, that the stock return is not greater than the classified industry return and the market return,
a fifth group represents that the classified industry return is not greater than the market return, and that stock return is greater than the classified industry return and the market return,
a sixth group represents that the classified industry return is not greater than the market return, that the stock return is greater than the classified industry return, and that the stock return is not greater than the market return,
a seven group represents that the classified industry return is not greater than the market return, that the stock return is not greater than the classified industry return, and that the stock return is greater than the market return, and
an eighth group represents that the classified industry return is not greater than the market return, that the stock return is not greater than the classified industry return and the market return.
3. The stock analysis method as claimed in claim 1, wherein each of the current trading period and the time interval is equal to one trading day.
4. The stock analysis method as claimed in claim 1, prior to step e), further comprising the steps of:
d1) choosing, from first to (i\u22121)th ones of the N time intervals, a number (Mi) of the time intervals for each of the stocks corresponding to the ith one of the N time intervals from a period, wherein the clustering data of each of the stocks in each of the number (Mi) of the time intervals is identical to that in the ith one of the N time intervals; and
d2) estimating rising and falling probabilities, and rising and falling average returns of each of the stocks in an (i+1)th time interval according to the number (Mi) of the time intervals chosen in step d1).
5. The stock analysis method as claimed in claim 4, wherein step d2) includes the sub-steps of:
d21) choosing, from a period from first to ith ones of the N time intervals, a number (Ri) of the time intervals for each of the stocks corresponding to the ith one of the N time intervals, wherein each of the number (Ri) of the time intervals is a next time interval of a corresponding one of the number (Mi) of the time intervals and the stock price of each of the stocks rises in each of the number (Ri) of the time intervals, and estimating that the rising probability of each of the stocks in the (i+1)th time interval is equal to RiMi and that the rising average return of each of the stocks in the (i+1)th time interval is equal to an average of stock returns of the corresponding one of the stocks in the number (Ri) of the time intervals from corresponding stock return data calculated in step a); and
d22) choosing, from the period from first to ith ones of the N time intervals, a number (Fi) of the time intervals, which differ from the number (Ri) of the time intervals, for each of the stocks corresponding to the ith one of the N time intervals, wherein each of the number (Fi) of the time intervals is a next time interval of a corresponding one of the number (Mi) of the time intervals and the stock price of the corresponding one of the stocks rises in each of the number (Fi) of the time intervals, and estimating that the falling probability of each of the stocks in the (i+1)th time interval is equal to FiMi and that the falling average return of each of the stocks in the (i+1)th time interval is equal to an average of stock returns of the corresponding one of the stocks in the number (Fi) of the time intervals from the corresponding stock return data calculated in step a).
6. The stock analysis method as claimed in claim 4, wherein, in step d2), the rising and falling probabilities of each of the stocks in the (i+1)th time interval are estimated based on stock returns of the corresponding one of the stocks from corresponding stock return data calculated in step a) using continuous probability density function.
7. The stock analysis method as claimed in claim 4, wherein, in step d2), the rising and falling probabilities of each of the stocks in the (i+1)th time interval are estimated using one of conditional probability and Bayer’s decision rule.
8. The stock analysis method as claimed in claim 4, wherein, in step e):
the analysis data includes the rising probability, an expected return, a standard deviation, and an expected return per unit of risk of each of the stocks corresponding to the coming time interval;
the expected return of each of the stocks in the (i+1)th time interval is equal to a sum of the product of the rising probability and the rising average return of the corresponding one of the stocks in the (i+1)th time interval estimated in step d2), and the product of the falling probability and the falling average return of the corresponding one of the stocks in the (i+1)th time interval estimated in step d2) such that the expected return of each of the stocks corresponding to the coming time interval is obtained when i=N;
the standard deviation of each of the stocks in the (i+1)th time interval is determined based on stock returns of the corresponding one of the stocks in the number (Mi) of the time intervals from the corresponding stock return data calculated in step a), and indicates a risk value such that the standard deviation of each of the stocks corresponding to the coming time interval is obtained when i=N; and
the expected return per unit of risk of each of the stocks in the (i+1)th time interval is equal to the expected return of the corresponding one of the stocks in the (i+1)th time interval divided by the standard deviation of the corresponding one of the stocks in the (i+1)th time interval such that the expected return per unit of risk of each of the stocks corresponding to the coming time interval is obtained when i=N, the expected return per unit of risk of each of the stocks in the (i+1)th time interval being a reciprocal of risk per unit of expected return of the corresponding one of the stocks in the (i+1)th time interval.
9. The stock analysis method as claimed in claim 8, wherein, in step f), the predetermined selection criteria are associated with at least one predetermined expected return threshold, at least one predetermined rising probability threshold and at least one predetermined standard deviation threshold,
said stock analysis method further comprising the step of:
g) sorting the target ones of the stocks with the expected return per unit of risk or the risk per unit of expected return corresponding to the coming time interval.
10. The stock analysis method as claimed in claim 9, wherein the predetermined selection criteria further are further associated with fundamental data, and technical indices based on trading price or trading volume.
11. The stock analysis method as claimed in claim 1, wherein, in step e), the analysis data of each of the stocks corresponding to the coming time interval includes a predictive stock return that is obtained based on the clustering data of the corresponding one of the stocks corresponding to the coming time interval using a multivariate regression model.
12. The stock analysis method as claimed in claim 11, wherein, in step f), the predetermined selection criteria are associated with a predetermined stock return threshold, said stock analysis method further comprising the step of:
g) sorting the target ones of the stocks with the predictive stock return corresponding to the coming time interval.
13. A computer program product comprising a non-transitory computer readable medium storing instructions for causing a computer to perform consecutive steps of:
a stock analysis method for performing an analysis on a plurality of stocks to select target ones to be boughtsold from the stocks, the company of each of the stocks belonging to a corresponding classified industry, the stock analysis method including the steps of:
a) calculating stock return data of each of the stocks, market return data, and classified industry return data of each of the corresponding classified industries based on historical stock price information within a historical trading period that includes a current trading period and that consists of a number (N) of consecutive time intervals;
b) according to the stock return data, the market return data and the classified industry return data obtained in step a), determining
whether a stock return of each of the stocks in each of the N time intervals is greater than a classified industry return of the corresponding classified industry in a corresponding one of the N time intervals,
whether the stock return of each of the stocks in the corresponding one of the N time intervals is greater than a market return in the corresponding one of the N time intervals, and
whether the classified industry return of the corresponding one of the classified industries in the corresponding one of the N time intervals is greater than the market return in the corresponding one of the N time intervals;
c) based on results determined in step b), grouping the stocks so that each of the stocks in each of the N time intervals is grouped into a corresponding one of a number (G) of different groups;
d) obtaining clustering data of each of the stocks corresponding to each of the N time intervals and associated with the groups based on a specific one of the groups using a clustering mode;
e) estimating analysis data of each of the stocks corresponding to a coming time interval based on at least the clustering data obtained in step d); and
f) determining any ones of the stocks whose analysis data estimated in step e) matches predetermined selection criteria as the target ones of the stocks;
wherein, in step d):
the clustering mode is one of a combination clustering mode and a permutation clustering mode;
in the combination clustering mode, the clustering data of each of the stocks corresponding to an ith one of the N time intervals includes the corresponding one of the groups in the ith one of the N time intervals, and a number (Si) of the time intervals in a reference period from i\u2212(Q\u22121)th to ith ones of the N time intervals, where 1\u2266i\u2266N and 2\u2266Q\u2266i, wherein a corresponding one of the stocks is grouped into said specific one of the groups in the number (Si) of the time intervals; and
in the permutation clustering mode, the clustering data of each of the stocks corresponding to the ith one of the N time intervals includes the corresponding one of the groups in the ith one of the N time intervals, and group permutation pattern consisting of the corresponding ones of the groups that correspond respectively to i\u2212(Q\u22121)th to ith ones of the N time intervals.
14. A system for performing an analysis on a plurality of stocks to select target ones to be boughtsold from the stocks, the company of each of the stocks belonging to a corresponding classified industry, the system comprising: one processor and a non-transitory computer readable medium, wherein the non-transitory computer readable medium stores instructions that when executed by the processor, causes the processor to perform the steps of:
a) calculating stock return data of each of the stocks, market return data, and classified industry return data of each of the corresponding classified industries based on historical stock price information within a historical trading period that includes a current trading period and that consists of a number (N) of consecutive time intervals;
b) according to the stock return data, the market return data and the classified industry return data obtained in step a), determining
whether a stock return of each of the stocks in each of the N time intervals is greater than a classified industry return of the corresponding classified industry in a corresponding one of the N time intervals,
whether the stock return of each of the stocks in the corresponding one of the N time intervals is greater than a market return in the corresponding one of the N time intervals, and
whether the classified industry return of the corresponding one of the classified industries in the corresponding one of the N time intervals is greater than the market return in the corresponding one of the N time intervals;
c) based on results determined in step b), grouping the stocks so that each of the stocks in each of the N time intervals is grouped into a corresponding one of a number (G) of different groups;
d) obtaining clustering data of each of the stocks corresponding to each of the N time intervals and associated with the groups based on a specific one of the groups using a clustering mode;
e) estimating analysis data of each of the stocks corresponding to a coming time interval based on at least the clustering data obtained in step d); and
f) determining any ones of the stocks whose analysis data estimated in step e) matches predetermined selection criteria as the target ones of the stocks; wherein, in step d):
the clustering mode is one of a combination clustering mode and a permutation clustering mode;
in the combination clustering mode, the clustering data of each of the stocks corresponding to an ith one of the N time intervals includes the corresponding one of the groups in the ith one of the N time intervals, and a number (Si) of the time intervals in a reference period from i\u2212(Q\u22121)th to ith ones of the N time intervals, where 1\u2266i\u2266N and 2\u2266Q\u2266i, wherein a corresponding one of the stocks is grouped into said specific one of the groups in the number (Si) of the time intervals; and
in the permutation clustering mode, the clustering data of each of the stocks corresponding to the ith one of the N time intervals includes the corresponding one of the groups in the ith one of the N time intervals, and group permutation pattern consisting of the corresponding ones of the groups that correspond respectively to i\u2212(Q\u22121)th to ith ones of the N time intervals.

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 of manufacturing a radial and axial combination bearing, comprising:
forming a radial bearing ring having a circumferentially extending outer race, an outwardly extending axial flange with outwardly directed anti-rotation projections, and an inwardly extending flange;
forming an axial bearing cup with an axial body having ring retention tabs spaced about an inner periphery located in notched sections, and an outer radial flange having radially inwardly directed cage retention tabs;
installing the radial bearing ring into the axial bearing cup with the anti-rotation projections being located in the notched sections;
installing a cage with radial rollers in the radial bearing ring, the radial rollers contacting the circumferentially extending outer race;
installing an intermediate washer that forms an axial race in the axial bearing cup; and
installing a second cage with axial rollers in the axial bearing cup, the axial rollers contacting the intermediate washer, and the cage being retained by the radially inwardly directed cage retention tabs.
2. The method of claim 1, wherein the radial bearing ring and the axial bearing cup are each formed by pressing a sheet metal blank.
3. The method of claim 2, wherein the sheet metal blank is made of bearing grade steel.
4. The method of claim 2, further comprising heat treating and tempering the radial bearing ring and the axial bearing cup.
5. The method of claim 4, further comprising surface polishing the radial bearing ring and the axial bearing cup.
6. The method of claim 1, wherein the axial flange of the radial bearing ring is aligned with the axial body of the axial bearing cup.
7. The method of claim 1, wherein the notched sections include end walls that contact the anti-rotation projections.
8. A radial and axial combination bearing, comprising:
a radial bearing ring having a circumferentially extending race, an outwardly extending axial flange with outwardly directed anti-rotation projections, and an inwardly extending flange;
an axial bearing cup with an axial body having ring retention tabs spaced about an inner periphery located in notched sections, and an outer radial flange having radially inwardly directed cage retention tabs;
the radial bearing ring being located in the axial bearing cup with the anti-rotation projections being located in the notched sections;
a cage with radial rollers located in the radial bearing ring, the radial rollers contact the circumferentially extending race;
an intermediate washer that forms an axial race in the axial bearing cup; and
a second cage with axial rollers located in the axial bearing cup, the axial rollers contact the intermediate washer, and the cage being retained by the radially inwardly directed cage retention tabs.
9. The bearing of claim 8, wherein the radial bearing ring and the axial bearing cup are pressed sheet metal parts.
10. The bearing of claim 8, wherein the axial flange of the radial bearing ring is aligned with the axial body of the axial bearing cup.
11. The bearing of claim 8, wherein the notched sections include end walls that contact the anti-rotation projections.