Author: claimsbot

1. A functional adhesive comprising a flavonoid-based compound, a polyphenol-based compound, a steroid-based compound or a mixture thereof, wherein the flavonoid-based compound, the polyphenol-based compound, or the steroid-based compound has a molecular weight of 250 to 1000 gramsmole.
2. The functional adhesive of claim 1, wherein the flavonoid-based compound or the polyphenol-based compound contains at least one compound selected from the group consisting of anthoxanthin, anthocyanin, catechin, tannin, and caffeine.
3. The functional adhesive of claim 1, wherein the steroid-based compound contains at least one compound selected from the group consisting of cholesterol, saponin, and \u03b2-carotene.
4. The functional adhesive of claim 1, wherein the amount of the flavonoid-based compound, the polyphenol-based compound or the steroid-based compound is in the range of 0.01 to 2% by weight based on the total amount of the functional adhesive.
5. The functional adhesive of clam 1, wherein the amount of the flavonoid-based compound, the polyphenol-based compound or the steroid-based compound is in the range of 0.5 to 2% by weight based on the total amount of the functional adhesive.
6. The functional adhesive of claim 1, wherein the flavonoid-based compound or the steroid-based compound is obtained from natural plants.
7. The functional adhesive of claim 6, wherein the natural plants include at least one plant selected from the group consisting of an oak tree, a mangrove tree, a mahogany tree, an acacia tree, a persimmon tree, a chestnut shell, a peach, an apple, a grape, a persimmon, green tea, black tea, oolong tea, jasmine tea, bohea tea, tieguanyin tea, Bongro tea, Youbi tea, Soosun tea, Ogo tea, white tea, blue tea, powdered green tea, cassia tea, tobacco leaf, angelica keiskei, kale, coffee, and barley.
8. The functional adhesive of claim 6, wherein the flavonoid-based compound, the polyphenol-based compound or the steroid-based compound is in the form of dried powder, a suspension of a dried powder, flakes, an extract, or a dried powder of the extract of the natural plant.
9. The functional adhesive of claim 8, wherein the particle size of the dried powder and the thickness of the flakes of the natural plant are in the range of 20 to 150 \u03bcm.
10. The functional adhesive of claim 8, wherein the amount of the dried powder and the flake of the natural plant is in the range of 1 to 10% by weight based on the total amount of the functional adhesive.
11. The functional adhesive of claim 8, wherein the solvent used for the extract or the suspension of the dried powder of the natural plant includes at least one solvent selected from the group consisting of water, alcohol, oil, and resin.
12. The functional adhesive of claim 1 comprising main components and additives,
wherein the main components comprise at least one resin selected from the group consisting of a polyvinylacetate-based resin, an ethylenevinylacetate-based resin, a melamin-based resin, a urea-based resin, a phenol-based resin, a urethane-based resin, an epoxy-based resin, an acryl-based resin, a silica-based resin, and a hardener, and
the additives comprise at least one additive selected from the group consisting of a filler, a stabilizer, an anti-foaming agent, a dispersing agent, and a flatting agent.
13. The functional adhesive of claim 1, wherein the main components comprise 90% by weight of a polyvinylacetate-based resin and 10% by weight of an isocyanate-based hardener (MDI), the filler is flour, and the flavonoid-based compound, the polyphenol-based compound, the steroid-based compound or the mixture thereof is comprised in a green tea leaf powder, and the functional adhesive comprises 81.8 to 96.8% by weight of the main components, 0.7 to 8.2% by weight of the flour, and 2.5 to 10% by weight of the green tea leaf powder.
14. The functional adhesive of claim 1 used to provide an adhesive force to the surface of at least one construction material selected from the group consisting of a film, a door, a window, a chair, a desk, a floor, wall paper, a material for a ceiling, a material for a closet and a flooring material.
15. A construction material to which the functional adhesive of claim 1 is applied.
16. A method of preparing a functional adhesive comprising:
grinding a dried plant and selecting a micropowder having a particle size of 20 to 150 \u03bcm,
reacting and melting adhesive raw materials including main component resins by heating;
sufficiently mixing the micropowder with a filler; and
dispersing the mixed powder in the adhesive raw materials such that the amount of the mixed powder is 1 to 10% by weight based on the total amount of the functional adhesive.
17. The method of claim 16, wherein a natural plant extract, a dried powder of an extract of a natural plant or a suspension of the micropowder is added to the functional adhesive raw materials instead of the micropowder.
18. The method of claim 16, wherein the natural plant includes at least one plant selected from the group consisting of an oak tree, a mangrove tree, a mahogany tree, an acacia tree, a persimmon tree, a chestnut shell, a peach, an apple, a grape, a persimmon, green tea, black tea, oolong tea, jasmine tea, bohea tea, tieguanyin tea, Bongro tea, Youbi tea, Soosun tea, Ogo tea, white tea, blue tea, powdered green tea, cassia tea, tobacco leaf, angelica keiskei, kale, coffee, and barley.

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 adaptive filter for filtering an input signal, the filter comprising:
a filter coefficients storage unit configured to store filter coefficients;
a filter coefficients determination unit configured to determining adapted filter coefficients based on the filter coefficients, an error signal and a step-size parameter; and
a step-size parameter control unit configured:
to determine a channel variation quantity based:
on a variation of a filter coefficient stored in the filter coefficient storage unit; and
on an auxiliary quantity based on a scalar product of a vector of filter coefficients from a first timing for the auxiliary quantity and a vector of filter coefficients from a second timing for the auxiliary quantity; and

to determine the step-size parameter based on the channel variation quantity.
2. The adaptive filter of claim 1 wherein the step-size parameter control unit is configured to determine the auxiliary quantity on the basis of a fraction value having an absolute value of the scalar product of a vector of filter coefficients from the first timing for the auxiliary quantity and a vector of filter coefficients from the second timing for the auxiliary quantity as a numerator, and having a sum of a square value of a norm of a vector of the filter coefficients from the first timing for the auxiliary quantity and a square value of a norm of a vector of the filter coefficients from the second timing of the auxiliary quantity as a denominator.
3. The adaptive filter of claim 1 wherein the step-size parameter control unit is configured to determine the channel variation quantity as an average of at least two auxiliary quantities.
4. The adaptive filter of claim 3 wherein the step-size parameter control unit is configured to repeatedly determine the channel variation quantity on the basis of at least an actual auxiliary quantity.
5. The adaptive filter of claim 4 wherein the step-size parameter control unit comprises an infinite response filter configured to receive the auxiliary quantities and to output the channel variation quantity.
6. The adaptive filter of claim 5 where a distance between the first timing and the second timing for each of the auxiliary quantities is predetermined.
7. The adaptive filter of claim 1 wherein the step-size parameter control unit is configured to determine step-size parameter based on a fraction value having a numerator that is a further channel variation quantity based on the channel variation quantity, and a denominator that comprises a signal power of the input signal.
8. The adaptive filter of claim 7 wherein the step-size parameter control unit comprises a table defining a mapping between the channel variation quantity and the further channel variation quantity and the further channel variation is determined from the channel variation quantity from the mapping defined by the table.
9. The adaptive filter of claim 1 wherein the filter coefficients determination unit is adapted to determine the error signal based on a difference between a desired signal and an output signal, wherein the output signal is determined based on a scalar product of a vector of the filter coefficients and a vector of a filter input derived from the input signal.
10. The adaptive filter of claim 1, wherein the step-size parameter control unit determines the auxiliary quantity according to the expression:
(min\u03c6|w(n2)\u2212exp(j\xb7\u03c6)\xb7w(n1)|2)(|w(n2)|2+|w(n1)|2)
wherein \u03c6 is a real number, j is a complex number satisfying j2=\u22121, w(n1) is the vector of filter coefficients at the first timing and w(n2) is the vector of filter coefficients at the second timing.
11. The adaptive filter of claim 1, wherein the step-size parameter control unit determines the auxiliary quantity according to the expression:
(min\u03c6(|w(n2)|2+|w(n1)|2\u22122\xb7Re(exp(\u2212j\xb7\u03c6)\xb7w(n1), w(n2)))(|w(n2)|2+|w(n1)|2)
wherein \u03c6 is a real number, j is a complex number satisfying j2=\u22121, w(n1) is the vector of filter coefficients at the first timing and w(n2) is the vector of filter coefficients at the second timing.
12. The adaptive filter of claim 1, wherein the step-size parameter control unit determines the auxiliary quantity according to the expression:
1\u2212(2\xb7w(n1), w(n2(|w(n2)|2+|w(n1)|2))
wherein w(n1) is the vector of filter coefficients at the first timing and w(n2) is the vector of filter coefficients at the second timing.
13. A system, comprising:
a signal processing unit; and
an adaptive filter coupled to the signal processing unit and having:
a filter coefficients storage unit configured to store filter coefficients;
a filter coefficients determination unit configured to determining adapted filter coefficients based on the filter coefficients, an error signal and a step-size parameter; and
a step-size parameter control unit configured:
to determine a channel variation quantity based:
on a variation of a filter coefficient stored in the filter coefficient storage unit; and
on an auxiliary quantity based on a scalar product of a vector of filter coefficients from a first timing for the auxiliary quantity and a vector of filter coefficients from a second timing for the auxiliary quantity; and

to determine the step-size parameter based on the channel variation quantity.
14. An adaptive method for filtering an input signal in a filter, the method comprising:
determining adapted filter coefficients based on actual filter coefficients, an error signal, and a step-size parameter;
determining a channel variation quantity based:
on a variation of a filter coefficient; and
on an auxiliary quantity based on a scalar product of a vector of filter coefficients from a first timing for the auxiliary quantity and a vector of filter coefficients from a second timing for the auxiliary quantity;

determining the step-size parameter based on the channel variation quantity.
15. A non-transitory computer readable memory medium storing instructions that, when executed, cause a computing device to implement a method of filtering an input signal, the method comprising:
determining adapted filter coefficients based on actual filter coefficients, an error signal, and a step-size parameter;
determining a channel variation quantity based:
on a variation of a filter coefficient; and
on an auxiliary quantity based on a scalar product of a vector of filter coefficients from a first timing for the auxiliary quantity and a vector of filter coefficients from a second timing for the auxiliary quantity;

determining the step-size parameter based on the channel variation quantity.

1. A nonvolatile semiconductor memory device comprising:
a plurality of memory cells which are arranged at the intersections of a plurality of word lines and a plurality of bit lines and each of which includes a variable-resistance element and a diode;
a sense amplifier which compares a voltage corresponding to current in a memory cell selected from said plurality of memory cells with a reference voltage to detect data read from the selected memory cell; and
a controller which generates the reference voltage according to the logical value of a signal output from the sense amplifier and which, before detecting data in the memory cell, adjusts the reference voltage on the basis of current flowing in one of said plurality of bit lines connected to said plurality of memory cells in a half-selected state detected by the sense amplifier.
2. The device according to claim 1, further comprising:
a voltage application module which applies half a read voltage to the word lines and the bit lines when the controller adjusts the reference voltage.
3. The device according to claim 2,
wherein the voltage application module, when reading a memory cell, applies the read voltage to the selected bit line and a voltage lower than half the read voltage to the selected word line.
4. The device according to claim 1,
wherein the reference voltage is set to a third voltage between a first voltage corresponding to data on a high resistance stored in the memory cell and a second voltage corresponding to data on a low resistance.
5. The device according to claim 1,
wherein the controller comprises:
a digital signal generator circuit which generates a digital signal according to the logical value of a signal output from the sense amplifier; and
a digital-to-analog converter which converts a digital signal generated by the digital signal generator circuit into the reference voltage.
6. The device according to claim 5,
wherein the digital signal generator circuit includes a counter which counts up or down the digital signal according to the logical value of a signal output from the sense amplifier.
7. The device according to claim 6,
wherein the controller causes the counter to count down from when the output signal of the sense amplifier has gone to \u201c0\u201d until a certain period of time has elapsed.
8. A nonvolatile semiconductor memory device comprising:
a plurality of memory cells which are arranged at the intersections of a plurality of word lines and a plurality of bit lines and each of which includes a variable-resistance element and a diode;
a sense amplifier which is connected to the selected bit line and which compares a voltage corresponding to current flowing in the selected memory cell with a reference voltage to detect data read from the memory cell; and
a controller which, before reading the memory cell, adjusts the reference voltage according to the logical value of a signal output from the sense amplifier and which adjust the reference voltage in a state where half a read voltage is applied to said plurality of bit lines and said plurality of word lines.
9. The device according to claim 8, further comprising:
a voltage application module which applies half the read voltage to the word lines and the bit lines when the controller adjusts the reference voltage.
10. The device according to claim 9,
wherein the voltage application module, when reading a memory cell, applies the read voltage to the selected bit line and a voltage lower than half the read voltage to the selected word line.
11. The device according to claim 10,
wherein the reference voltage is set to a third voltage between a first voltage corresponding to data on a high resistance stored in the memory cell and a second voltage corresponding to data on a low resistance.
12. The device according to claim 8,
wherein the controller includes a counter which counts up or down according to the logical value of a signal output from the sense amplifier.
13. The device according to claim 12,
wherein the controller causes the counter to count down from when the output signal of the sense amplifier has gone to \u201c0\u201d until a certain period of time has elapsed.
14. A method of reading a nonvolatile semiconductor memory device, the method comprising:
applying half a read voltage to a plurality of bit lines and a plurality of word lines to set a plurality of memory cells in a half-selected state before reading, each of said plurality of memory cells including a variable-resistance element and a diode;
comparing a voltage corresponding to current flowing in a bit line connected to a memory cell in the half-selected state with a reference voltage to generate the reference voltage; and
comparing a voltage corresponding to current flowing in the selected memory cell with the adjusted reference voltage to read the selected memory cell.
15. The method according to claim 14, wherein the adjusted reference voltage is set to a third voltage between a first voltage corresponding to data on a high resistance stored in the memory cell and a second voltage corresponding to data on a low resistance.
16. The method according to claim 14, further comprising:
applying the read voltage to the selected bit line and a voltage lower than half the read voltage to the selected word line when reading a memory cell.

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 visualization design system, comprising:
a metadata component to describe characteristics of data;
an analyzer to determine attributes of a peer group, the attributes related to prior visualization design experiences; and
a wizard component to determine a subset of potential visualization types based in part on the characteristics of data and the attributes of the peer group.
2. The system of claim 1, the metadata component provides tags that indicate what type of users or peers have operated on similar types of data (or data sets) in the past, tags that indicate suitable visualization forms or subsets given a respective data type, tags that indicate a relationship between a designer and one or more other members of a peer group, or tags that represent an annotation that describes how a particular visualization was created in the past or how a particular data set was visualized.
3. The system of claim 1, the analyzer includes a data mining component or a learning component.
4. The system of claim 1, the peer group associated with local or remote databases.
5. The system of claim 1, further comprising a profile component to facilitate determining a user’s intent.
6. The system of claim 5, the profile component includes a status field, an organizational chart, a correspondence field, a learning component, a policy component, or a statistical component.
7. The system of claim 1, the wizard component further comprising an attribute processor.
8. The system of claim 1, the wizard component further comprising an intent filter.
9. The system of claim 1, the wizard component further comprising a debugging component.
10. The system of claim 1, the wizard component further comprising a collaborative analyzer.
11. The system of claim 1, the wizard component further comprising a template generator.
12. The system of claim 1, the wizard component further comprising one or more controls to facilitate visualization design.
13. The system of claim 1, the wizard component further comprising a component to determine derivations for visualizations.
14. The system of claim 1, the wizard component further comprising an annotation component to analyze prior visualizations or to allow users to add annotations to a current visualization.
15. The system of claim 1, the wizard component further comprising spreadsheet component that is mined for visualization design information.
16. A visualization design method, comprising:
analyzing peer groups, metadata, or a profile to determine knowledge data relating to a user’s design intentions;
processing the knowledge data to determine a subset of potential visualization options; and
presenting the visualization options to the user in order to select a suitable visualization format given a current data set.
17. The method of claim 16, further comprising analyzing annotations to determine design alternatives.
18. The method of claim 17, further comprising generating help assistance to aid in design of visualizations.
19. The method of claim 16, further comprising analyzing prior visualizations or data sets via data mining or learning components.
20. A visualization design system, comprising:
means for analyzing visualization information associated with one or more peer groups;
means for tagging data that relates to the potential design of a visualization; and
means for generating at least one visualization from a current data set in view of the peer groups or the tagged data.