Author: claimsbot

1. A computer-implemented ranking-based method for evaluating regression models by obtaining predictions y from one or more models to be evaluated on a test set of customers for which the true value y of the quantity of interest has been observed comprising the steps of:
storing the test set in an electronic database sorted in increasing order such that \u201clarge\u201d corresponds to one of a plurality of customers andor potential customers with largest perceived spending budget, and \u201csmall\u201d corresponds to one of a plurality of customers andor potential customers with smallest perceived spending budget;
applying all models to customer data from the test set to obtain predictions for the spending for each model and customer;
converting the predictions into ranks and storing for each model in one or more electronic databases as a model ranking table, a number of ranking order switches relative to ranking of the observed customer spending being calculated for each model and ranking order switches being defined as those changes in ranking position of the prediction relative to the order of the true observations y;
calculating a measure of a magnitude of erroneous ranking from a weighted sum of ranking order switches;
transforming the number of ranking switches and weighted sum of ranking order switches into a range of \u22121, 1 wherein \u22121 corresponds to making all possible errors (inverse ranking) and 1 corresponds to a perfect model wherein said number of ranking switches has been transformed to represent a difference between a probability that the ranking of two customers andor potential customers are in the same order versus the probability that two of the customers andor potential customers are in different orders from the originally obtained rank;
normalizing transformed measures of order switches into a range of 0,1 wherein 1 corresponds to perfect ranking and 0 corresponds inverse ranking;
calculating a variance of measures of order switches and determining confidence intervals for each ranking measure, further comprising:
calculating using computing resources a variance that said measures of said ranking order switches,
wherein said calculating using computing resources a variance implements a relationship:
V
\u2062

a
^

\u2062

r
\u2061

(

\u03c4
^

)
=
(

2

n
\u2061

(

n
–
1

)
)

2

\xb7
2
\xb7

(
2
\u2062
\u2211
i

\u2062
\u2062

C
i
2
–
\u2211
i

\u2062
\u2062

C
i
–
(
2
\u2062
n

–
3

)
n
\u2061

(

n
–
1

)
\xb7
(
\u2211
i

\u2062
\u2062

C
i
)

2
)
wherein, a set of variables of said set of relationships includes:
C
i

=
\u2211

j
<
i
\u2062
\u2062

1
\u2062

{
y
i

>

y
j
}
+
\u2211

j
>
i
\u2062
\u2062

1
\u2062

{
y
i

<

y
j
}
is a number of observations that are concordant with observation i,
i is an integer from 1 to (n\u22121),
j is an integer from (i+1) to n,
n is a size of a set of customers andor potential customers, and
y is a predicted response of the model y=m(x);
calculating using computing resources a confidence interval for each measure of said ranking order switches; and
constructing using computing resources graphical representations of said ranking order switches;
updating the model performance table with the ranking measures and their confidence intervals; and
outputting the ranking measures and confidence levels as well as graphical representations thereof to a domain expert via electronic display on a computer monitor, who will choose based on this information the best model m* of the one or more models evaluated, and storing the predictions of y=m*(x) in the optimal prediction table.
2. The computer-implemented ranking-based method recited in claim 1, wherein the step of calculating a measure of a magnitude of erroneous ranking from a weighted sum of ranking order switches comprises the steps of:
calculating using computing resources a number of ranking order switches wherein ranking order switches are those changes in ranking order position of said plurality of customers andor potential customers assuming said ranking obtained in said obtaining step was erroneous, and
calculating using computing resources a weighted sum of ranking order switches wherein said weighted sum of ranking order switches provides a measure of the magnitude of erroneous ranking.
3. The computer-implemented ranking-based method of claim 2, wherein said calculating using computing resources the number of ranking order switches step comprises a relationship:
T=\u03a3i<j1{si>sj}
wherein, a set of variables of said relationship includes:
T is a number of rank order switches,
si is a rank order of one customer of said plurality of customers andor potential customers,
i is an integer from 1 to (n\u22121),
j is an integer from (i+1) to n, and
n is a size of a set of observed customers.
4. The computer-implemented ranking based method recited in claim 2, wherein said calculating using computing resources a weighted sum of order switches step comprising a relationship:
R=\u03a3i<j(j\u2212i)1{si>sj}
wherein, a set of variables of said relationship includes:
R is a weighted sum of order switches,
si is a rank order of one customer of said plurality of customers andor potential customers,
i is an integer from 1 to (n\u22121),
j is an integer from (i+1) to n, and
n is a size of a set of observed customers.
5. The computer-implemented ranking-based method recited in claim 1, wherein the step of outputting the ranking measures and confidence levels comprises the steps of:
providing an output that presents an updated ranking of said plurality of customers andor potential customers that corresponds to a model obtained in said applying step with the highest confidence interval of said all models; andor
providing an output of a model recommendation that corresponds to a best model of said all models evaluated.
6. The computer-implemented ranking-based method recited in claim 1, wherein the step of transforming said number of ranking switches and said weighting sum of order switches step implements a set of relationships:
\u03c4
^

=

1
–
4
\u2062
T
n
\u2061

(

n
–
1

)
,
\u2062
and
\u03c1
^

=

1
–
12
\u2062
R
n
\u2061

(

n
–
1

)
\u2062

(

n
+
1

)
wherein, a set of variables of said set of relationships includes:
{circumflex over (\u03c4)} is a probability that the ranking order has been changed,
n is a size of a set of customers andor potential customers,
{circumflex over (\u03c1)} is a ranking correlation,
T is a number of rank order switches, and
R is said weighted sum of order switches.
7. The computer-implemented ranking-based method recited in claim 1, wherein the step of outputting provides an updated ranking of a plurality of customers andor potential customers that corresponds to a model obtained in said applying step with the highest confidence interval of said all models.

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 enhancing the fungicidal activity of a triazole comprising adding N,N\u2032,N\u2032-tris(2-hydroxyethyl)-N-cocoalkyl-1,3-diamino-propane to a formulation comprising the triazole.
2. The method of claim 1 wherein the triazole is azaconazole, bromuconazole, cyproconazole, difenoconazole, epoxiconazole, fenbuconazole, fluquinconazole, flusilazole, hexaconazole, ketoconazole, metconazole, penconazole, propiconazole, tebuconazole, tetraconazole, or triticonazole.
3. The method of claim 2 wherein the triazole is propiconazole.
4. The method of claim 1 wherein the ratio of the triazole to the N,N\u2032,N\u2032-tris(2-hydroxyethyl)-N-cocoalkyl-1,3-diamino-propane is from 5:1 to 1:200.
5. The method of claim 4 wherein the ratio of the triazole to the N,N\u2032,N\u2032-tris(2-hydroxyethyl)-N-cocoalkyl-1,3-diamino-propane is from 2:1 to 1:2.
6. The method of claim 1 wherein the concentration of the triazole is from 0.01% (wv) to 10% (wv) and the concentration of the N,N\u2032,N\u2032-tris(2-hydroxyethyl)-N-cocoalkyl-1,3-diamino-propane is from 0.1% (wv) to 40% (wv).
7. The method of claim 6 wherein the concentration of the triazole is from 0.1% (wv) to 1.5% (wv) and the concentration of the N,N\u2032,N\u2032-tris(2-hydroxyethyl)-N-cocoalkyl-1,3-diamino-propane is from 0.5% (wv) to 10% (wv).
8. A method of protecting a plant or any part of a plant from a fungus comprising applying a composition comprising a triazole and N,N\u2032,N\u2032-tris(2-hydroxyethyl)-N-cocoalkyl-1,3-diamino-propane to the plant or any part of the plant.
9. The method of claim 8 wherein the triazole is azaconazole, bromuconazole, cyproconazole, difenoconazole, epoxiconazole, fenbuconazole, fluquinconazole, flusilazole, hexaconazole, ketoconazole, metconazole, penconazole, propiconazole, tebuconazole, tetraconazole, or triticonazole.
10. The method of claim 9 wherein the triazole is propiconazole.
11. The method of claim 8 wherein the ratio of the triazole to the N,N\u2032,N\u2032-tris(2-hydroxyethyl)-N-cocoalkyl-1,3-diamino-propane is from 5:1 to 1:200.
12. The method of claim 11 wherein the ratio of the triazole to the N,N\u2032,N\u2032-tris(2-hydroxyethyl)-N-cocoalkyl-1,3-diamino-propane is from 2:1 to 1:2.
13. The method of claim 8 wherein the concentration of the triazole is from 0.01% (wv) to 10% (wv) and the concentration of the N,N\u2032,N\u2032-tris(2-hydroxyethyl)-N-cocoalkyl-1,3-diamino-propane is from 0.1% (wv) to 40% (wv).
14. The method of claim 13 wherein the concentration of the triazole is from 0.1% (wv) to 1.5% (wv) and the concentration of the N,N\u2032,N\u2032-tris(2-hydroxyethyl)-N-cocoalkyl-1,3-diamino-propane is from 0.5% (wv) to 10% (wv).
15. A method for preserving wood, wood products, or biodegradable materials comprising applying a composition comprising a triazole and N,N\u2032,N\u2032-tris(2-hydroxyethyl)-N-cocoalkyl-1,3-diamino-propane to the wood, wood products, or biodegradable materials.
16. The method of claim 15 wherein the triazole is azaconazole, bromuconazole, cyproconazole, difenoconazole, epoxiconazole, fenbuconazole, fluquinconazole, flusilazole, hexaconazole, ketoconazole, metconazole, penconazole, propiconazole, tebuconazole, tetraconazole, or triticonazole.
17. The method of claim 16 wherein the triazole is propiconazole.
18. The method of claim 15 wherein the ratio of the triazole to the N,N\u2032,N\u2032-tris(2-hydroxyethyl)-N-cocoalkyl-1,3-diamino-propane is from 5:1 to 1:200.
19. The method of claim 18 wherein the ratio of the triazole to the N,N\u2032,N\u2032-tris(2-hydroxyethyl)-N-cocoalkyl-1,3-diamino-propane is from 2:1 to 1:2.
20. The method of claim 15 wherein the concentration of the triazole is from 0.01% (wv) to 10% (wv) and the concentration of the N,N\u2032,N\u2032-tris(2-hydroxyethyl)-N-cocoalkyl-1,3-diamino-propane is from 0.1% (wv) to 40% (wv).
21. The method of claim 20 wherein the concentration of the triazole is from 0.1% (wv) to 1.5% (wv) and the concentration of the N,N\u2032,N\u2032-tris(2-hydroxyethyl)-N-cocoalkyl-1,3-diamino-propane is from 0.5% (wv) to 10% (wv).
22. A composition comprising a fungicidal triazole and N,N\u2032,N\u2032-tris(2-hydroxyethyl)-N-cocoalkyl-1,3-diamino-propane.
23. The composition of claim 22 wherein the fungicidal triazole is propiconazole.
24. The composition of claim 22 wherein the ratio of the fungicidal triazole to the N,N\u2032,N\u2032-tris(2-hydroxyethyl)-N-cocoalkyl-1,3-diamino-propane is from 5:1 to 1:200.
25. The composition of claim 24 wherein the ratio of the fungicidal triazole to the N,N\u2032,N\u2032-tris(2-hydroxyethyl)-N-cocoalkyl-1,3-diamino-propane is from 2:1 to 1:2.
26. The composition of claim 22 wherein the concentration of the fungicidal triazole is from 0.01% (wv) to 10% (wv) and the concentration of the N,N\u2032,N\u2032-tris(2-hydroxyethyl)-N-cocoalkyl-1,3-diamino-propane is from 0.1% (wv) to 40% (wv).
27. The composition of claim 26 wherein the concentration of the fungicidal triazole is from 0.1% (wv) to 1.5% (wv) and the concentration of the N,N\u2032,N\u2032-tris(2-hydroxyethyl)-N-cocoalkyl-1,3-diamino-propane is from 0.5% (wv) to 10% (wv).

1. A method for fabricating a light-emitting device comprising:
forming a first semiconductor layer on a substrate;
forming an active layer on the first semiconductor layer;
forming a second semiconductor layer on the active layer, the second semiconductor layer having a conduction type opposite to that of the first semiconductor layer; and
forming a recess so as to be penetrated through up to the first semiconductor layer from the second semiconductor layer by a first etching; and
forming an inversely tapered shape to an inner wall of the recess by a second etching using an etching solution.
2. The method as claimed in claim 1, wherein the etching solution of the second etching uses one of a sodium hydroxide solution, a potassium hydroxide solution, a phosphoric acid and a mixed acid containing phosphoric acid.
3. The method as claimed in claim 1, wherein a third semiconductor layer containing Al and N is interposed between the substrate and the first semiconductor layer, and the first etching forms the recess that reaches the third semiconductor layer.
4. The method as claimed in claim 3, wherein the first semiconductor layer comprises GaN, and the third semiconductor layer comprises one of AlN and AlGaN.
5. The method as claimed in claim 1, wherein the recess comprises a hole.
6. The method as claimed in claim 5, wherein an inner wall of the recess has a polygonal shape composed of multiple flat surfaces.
7. The method as claimed in claim 1, wherein the recess comprises a groove.
8. The method as claimed in claim 1, wherein the recess comprises grooves that extend in different directions.
9. The method as claimed in claim 1, wherein the first semiconductor layer, the active layer and the second semiconductor layer are respectively GaN-based semiconductor layers.
10. The method as claimed in claim 1, wherein an angle between a side surface of the recess and a normal line of the substrate is equal to or greater than 20\xb0.
11. The method as claimed in claim 1, wherein the second semiconductor layer has a surface having a relief structure.
12. The method as claimed in claim 1, wherein the substrate is one of sapphire, SiC, Si and GaN.

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. An apparatus for treating ballast water, comprising:
a first pump that takes on sea water;
a filter apparatus having a filter that filtrates the sea water sent from the first pump and traps plankton with sizes corresponding to a sieve opening of the filter, the sieve opening being in the range of 10 to 200 \u03bcm;
the filter apparatus also having a reverse washing device that washes away plankton trapped by the filter;
a bactericide supply apparatus having a plurality of injection ports for supplying bactericide to the filtrate sea water;
a bactericide supply amount-control device that controls an amount of bactericide to be supplied from the bactericide supply apparatus,
a venturi tube apparatus that is located downstream of the filter apparatus and is constructed by arranging a plurality of venturi tubes in parallel, the plurality of injection ports being arranged in each of a radial direction and a circumferential direction within a cross-section of an inlet of the venturi tube apparatus;
a ballast tank that holds the sea water fed from the venturi tube apparatus;
a second pump that discharges the sea water from the ballast tank into the sea; and
a bactericide-decomposer supply apparatus that supplies bactericide-decomposer to the sea water discharged from the ballast tank so as to decompose the bactericide remaining in the sea water;
wherein the amount of the sea water sent from the first pump to the venturi tube apparatus is controlled such that a flow velocity at the inlet of the venturi tube apparatus is in the range of 2 to 3 msec, and a flow velocity at each throat part of the venturi tubes is in the range of 10 to 40 msec, the ratio of the sum of sectional areas of the throat parts of the venturi tubes to a sectional area at the inlet of the venturi tube apparatus being in the range of 7.5 to 20%,
the venturi tube apparatus generates cavitation in the sea water at the throat parts of the venturi tubes, thus diffusing the bactericide in the sea water to sterilize bacteria, and also destroying plankton or damaging plankton so as to promote penetration of the bactericide into a body of plankton,
the amount of bactericide to be supplied is controlled to be sufficient to sterilize bacteria and plankton in the filtrate sea water and also to prevent regrowth of bacteria and plankton in the sea water kept in the ballast tank, and
the amount of bactericide-decomposer to be supplied is controlled based on a measurement of bactericide concentration in the sea water discharged from the ballast tank.
2. The apparatus for treating ballast water according to claim 1,
wherein the bactericide supply amount-control device measures a pressure difference across the filter apparatus and controls the amount of the bactericide to be supplied from the bactericide supply apparatus based on the measured value,
the bactericide supply amount-control device increasing the amount of the bactericide when the pressure difference is larger than a predetermined value, and decreasing the amount of the bactericide when the pressure difference is smaller than the predetermined value.
3. The apparatus for treating ballast water according to claim 1,
further comprising a water quality measuring device that measures turbidity or absorbance of the sea water to be introduced into the filter or the sea water filtered by the filter; wherein
the bactericide supply amount-control device controls the amount of the bactericide to be supplied from the bactericide supply apparatus based on the turbidity or absorbance measured by the water quality measuring device,
the bactericide supply amount-control device increasing the amount of the bactericide when the turbidity or absorbance measured by the water quality measuring device is larger than a predetermined value, and decreasing the amount of the bactericide when the turbidity or absorbance measured by the water quality measuring device is smaller than the predetermined value.
4. The apparatus for treating ballast water according to claim 1,
wherein the bactericide is sodium hypochlorite,
the apparatus further comprising a redox potential measuring device that measures a redox potential of the sea water to which the bactericide is added, and wherein
the bactericide supply amount-control device controls the amount of the bactericide to be supplied from the bactericide supply apparatus based on the redox potential measured by the redox potential measuring device, the bactericide supply amount-control device adjusting the amount of the bactericide such that the redox potential is 800 mV or higher with respect to a silversilver chloride electrode.
5. A method for treating ballast water, comprising:
a filtering step of filtering sea water when sea water is taken on, a filter having a sieve opening in the range of 10 to 200 \u03bcm and thereby trapping plankton having sizes corresponding to the sieve opening;
a bactericide supply step, subsequent to the filtering step, of supplying bactericide to the filtrate sea water from a bactericide supply apparatus having a plurality of injection ports;
a cavitation treatment step, subsequent to the bactericide supply step, of introducing the sea water to which the bactericide has been added, into a venturi tube apparatus to generate cavitation in the sea water, the venturi tube apparatus being constructed by arranging a plurality of venturi tubes in parallel, the plurality of injection ports being arranged in each of a radial direction and circumferential direction within a cross section of an inlet of the venturi tube apparatus;
a water holding step of holding the sea water which has been subjected to the cavitation treatment, into a ballast tank;
a bactericide-decomposer supply step of supplying bactericide-decomposer to the sea water discharged from the ballast tank so as to decompose the bactericide remaining in the sea water;
wherein an amount of the sea water fed to the venturi tube apparatus is controlled such that a flow velocity at an inlet of the venturi tube apparatus is in the range of 2 to 3 msec, and a flow velocity at each throat part of the venturi tubes is in the range of 10 to 40msec,
during the cavitation treatment step, cavitation in the sea water is generated at the throat parts of the venturi tubes, thus diffusing the bactericide in the sea water to sterilize bacteria, and also destroying plankton or damaging plankton so as to promote penetration of the bactericide into a body of plankton,
an amount of bactericide to be supplied is controlled to be sufficient to sterilize bacteria and plankton in the filtrate sea water and also to prevent regrowth of bacteria and plankton in the sea water kept in the ballast tank, and
an amount of bactericide-decomposer to be supplied is controlled based on measurement of bactericide concentration in the sea water discharged from the ballast tank.
6. The method for treating ballast water according to claim 5, wherein the amount of the sea water fed to the venturi tube apparatus is set such that the head pressure loss across the venturi tube apparatus is 5 to 40 m.
7. The method for treating ballast water according to claim 5, wherein the bactericide is sodium hypochlorite, and the amount of the bactericide to be supplied is adjusted such that a concentration by weight of available chlorine in the sea water is 1 to 100 mgL.
8. The method for treating ballast water according to claim 5, wherein the bactericide is sodium hypochlorite, and the amount of the bactericide to be supplied is adjusted such that a redox potential of the sea water to which the bactericide is added is 800 mV or higher with respect to a silversilver chloride electrode.