I want to set up a compound interest table. I want to start with $15 and multiply by 1.0125 indefinitely. I want to be able to see the answer for each calculation (for example, I want to see what the answer is after 39 calculation, after 74 calculations, 22 calcualtions, etc..)

# Tag: compound

## terminology – Compound variables? Is this the correct term?

I asked this yesterday in Cross-validated (the statistics equivalent of here) but got few views and no answers. So I thought that I would ask it here.

I am looking for a term to describe the concept of a multi-characteristic variable. Examples of this are a) vectors – have both magnitude and direction b) Olympic records – have both event (categorical) and measurement – particularly races which have set distances and record times c) cell identifiers – have both row and column d) coordinates – x, y and z, + other coordinate systems

As can be seen, this term may or may not include relationships between the specified dimensions, but the “variable” lacks meaning without all its components.

Whilst “object”, borrowed from programming, may be used, this is perhaps too general for the application. I am looking for a term that falls between “object” and “variable”, where the relationships between the various elements are easily visualised/understood.

I thought that compound variable may fit the bill. But is that used for a different concept? If so, what would be a better term?

## python – Distinguish between handwritten subtraction and compound fraction

I am working in a project name “Handwritten Math Evaluation”

SO what basically happen in this is that there are 11 classes of (0 – 9) and (+,-) each containing 50 clean handwritten digits in them. Then I trained a CNN model for it with 80 % of data used in training and 20 % using in testing of model which lead in a accuracy of 98.83 %. Here is the code for the architecture of CNN model :-

```
import pandas as pd
import numpy as np
import pickle
np.random.seed(1212)
import keras
from keras.models import Model
from keras.layers import *
from keras import optimizers
from keras.layers import Input, Dense
from keras.models import Sequential
from keras.layers import Dense
from keras.layers import Dropout
from keras.layers import Flatten
from keras.layers.convolutional import Conv2D
from keras.layers.convolutional import MaxPooling2D
from keras.utils import np_utils
from keras import backend as K
from keras.utils.np_utils import to_categorical
from keras.models import model_from_json
import matplotlib.pyplot as plt
model = Sequential()
model.add(Conv2D(30, (5, 5), input_shape =(28,28,1), activation ='relu'))
model.add(MaxPooling2D(pool_size =(2, 2)))
model.add(Conv2D(15, (3, 3), activation ='relu'))
model.add(MaxPooling2D(pool_size =(2, 2)))
model.add(Dropout(0.2))
model.add(Flatten())
model.add(Dense(128, activation ='relu'))
model.add(Dense(50, activation ='relu'))
model.add(Dense(12, activation ='softmax'))
# Compile model
model.compile(loss ='categorical_crossentropy',
optimizer ='adam', metrics =('accuracy'))
model.fit(X_train, y_train, epochs=1000)
```

Now each image in dataset is preprocesed as follows:-

```
import cv2
im = cv2.imread(path)
im_gray = cv2.cvtColor(im,cv2.COLOR_BGR2GRAY)
ret, im_th = cv2.threshold(im_gray, 90, 255, cv2.THRESH_BINARY_INV)
ctrs, hier = cv2.findContours(im_th.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
rects = (cv2.boundingRect(ctr) for ctr in ctrs)
rect = rects(0)
im_crop =im_th(rect(1):rect(1)+rect(3),rect(0):rect(0)+rect(2))
im_resize = cv2.resize(im_crop,(28,28))
im_resize = np.array(im_resize)
im_resize=im_resize.reshape(28,28)
```

I have made an evaluation function which solves simple expression like 7+8 :-

```
def evaluate(im):
s = ''
data = ()
im_gray = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY)
ret, im_th = cv2.threshold(im_gray, 90, 255, cv2.THRESH_BINARY_INV)
ctrs, hier = cv2.findContours(im_th.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
sorted_ctrs = sorted(ctrs, key=lambda ctr: cv2.boundingRect(ctr)(0))
boundingBoxes = (cv2.boundingRect(c) for c in ctrs)
look_up = ('0','1','2','3','4','5','6','7','8','9','+','-')
i=0
for c in ctrs:
rect = boundingBoxes(i)
im_crop = im_th(rect(1):rect(1)+rect(3), rect(0):rect(0)+rect(2))
im_resize = cv2.resize(im_crop,(28,28))
im_resize = np.array(im_resize)
im_resize = im_resize.reshape(28,28,1)
data.append(im_resize)
i+=1
data = np.array(data)
predictions = model.predict(data)
i=0
while i<len(boundingBoxes):
rect = boundingBoxes(i)
print(rect(2),rect(3))
print(predictions(i))
s += look_up(predictions(i).argmax())
i+=1
return s
```

I need help extending this thought for Compund fractions but the problem is that they are identical to subtraction sign when resized to (28 , 28) so I need help in distuingish between them.

This is my first Question so please tell if any detail is left.

## algebra precalculus – Solving polynomials with compound angle formulae

Solve $64x^6-96x^4+36x^2-3=0$ (Hint: Consider expanding $cos 6theta$ in terms of $cos theta$)

To solve this exercise I can simply derive an identity using de-Moivre theorem then shuffle the equation around. It turns out that substituting $x=cos theta$ reduces the equation to $cos 6theta = frac{1}{2}$.

However, I’m wondering in the general case, is there any way to see this without the monster of a hint? In other words, given a polynomial, is there something I could look for in the coefficients that would make me think that deriving a compound angle formula may be a good idea?

## pr.probability – If $L_t=sum_{i=1}^{N_t}Y_i$ is a compound Poisson process, then $left|left{sin[0,t]:Delta L_sin Bright}right|=sum_{i=1}^{N_t}1_B(Y_i)$

Let $H$ be a $mathbb R$-Hilbert space, $mu$ be a finite measure on $mathcal B(H)$ with $mu({0})=0$ and $(L_t)_{tge0}$ be a $H$-valued càdlàg Lévy process on a probability space $(Omega,mathcal A,operatorname P)$ with $$L_t=sum_{i=1}^{N_t}Y_i;;;text{for all }tge0tag1$$ for some $H$-valued independent identically distributed process $(Y_n)_{ninmathbb N}$ on $(Omega,mathcal A,operatorname P)$ with $Y_1simlambda^{-1}mu$ for some $lambda>0$ and some càdlàg Poisson process $(N_t)_{tge0}$ on $(Omega,mathcal A,operatorname P)$.

Let $tge0$ and $Binmathcal B(Hsetminus{0})$. I would like to show that $$left|left{sin(0,t):Delta L_sin Bright}right|=sum_{i=1}^{N_t}1_B(Y_i),tag2$$ where $$Delta L_s:=L_s-L_{s-}=L_s-lim_{rto s-}L_r;;;text{for }sge0.$$ How can we do that?

*Remark*: Since the measure is not involved in $(2)$ it might be unimportant for the claim, but we may note that $$Z_n:=sum_{i=1}^nY_i;;;text{for }ninmathbb N$$ is a time-homogenous Markov chain and hence $$L_t=Z_{N_t};;;text{for all }tge0$$ is a time-homogeneous Markov process.

## mysql – How should cardinality be understood in a table with a compound key?

I am learning about database structuring and when watching the following video I cannot identify if there is a cardinality between the *ENVIO*, *PEDIDO* and *PRODUCTO* tables?

If it is clear to me that there is an N: N cardinality between *PEDIDOS* AND *PRODUCTOS* and I understand the information you want to record in the *ENVIO* table, **what is not clear to me is if there is any cardinality between this table and the other two mentioned.**

Is the diagram in the image correct (is the notation “crow’s feet” being used)?

If it is incorrect how should I modify the diagram to correctly express the cardinality between the meted tables?

## database layout: compound key with a column that is automatically incremented and reset when the value of the foreign key changes

I am trying to implement a ticket system, the generated numbers would be sequential.

4000, 4001, 4002, 4003

My idea was to have a table related to the current draw, and the ticket_no column is not an auto increment column that is reset when the foreign key changes.

Composite keys are `raf_id`

and `ticket_no`

since the ticket does not have to exist several times in the same draw

it's possible?

```
|------------|-----------|---------|
| raf_id | ticket_no | user_id |
|------------|-----------|---------|
| 1 | 4000 | 1 |
| 1 | 4001 | 1 |
| 1 | 4002 | 2 |
| 1 | 4003 | 3 |
| 2 | 4000 | 4 |
| 2 | 4001 | 4 |
| 2 | 4002 | 5 |
| 2 | 4003 | 1 |
|------------|-----------|---------|
```

## Financial calculator (emulator) that gives a negative result in compound interest

I am studying brokerage. And I am using this emulator to study.

https://epxx.co/ctb/hp12c.html

I am getting negative results when doing compound interest calculations.

I am doing it this way:

```
1: 10000
2: I press enter
3: I press PV
4: enter "3" and press "i" key
5 enter "4" and press "n" key
6 I press FV
```

I am doing something wrong?

## Sharepoint Enterprise: compound appearance error

When I try to change the composite look of the site collection, I get this error:

The background image could not be saved in the folder:

_catalogs / theme / Themed / 9577847E. Unexpected error. System.UnauthorizedAccessException: access denied. to

Microsoft.SharePoint.Utilities.SPUtility.HandleAccessDenied (Exception

ex) in Microsoft.SharePoint.Library.SPRequest.PutFile (String

bstrUrl, String bstrWebRelativeUrl, Object punkFile, Int64 cbFile,

Object punkSPFileMgr, Object punkFFM, SPFileSaveParams sfsp,

SPFileInfo and pFileProps, UInt32 and pdwVirusCheckStatus, String &

pVirusCheckMessage, String & pEtagReturn, Byte & piLevel, Int32 &

pbIgnoredReqProps)

I checked the folders at: `_catalogs/theme/Themed/`

and it's empty

What do I have to do to get the correct permissions?

to solve this problem.

## sql server: foreign key reference table with compound primary key when i only need 1 column association

Let's say we have 2 tables in the SQL Server database:

```
CREATE TABLE VersionedData (
Id INT PRIMARY KEY,
Version INT PRIMARY KEY
)
```

Y:

```
CREATE TABLE PointingTable (
Id INT PRIMARY KEY,
RefId INT NOT NULL
CONSTRAINT (FK_Pnt_Ver) FOREIGN KEY (RefId)
REFERENCES VersionedData (Id)
)
```

My idea of this relationship is when joining these 2 particular tables I only care about the latest version of the VersionedData table (meaning I will ALWAYS match the maximum version for the specific ID value, giving me exactly 1 row that I need).

Of course, the code above causes an error that I must reference both PK columns of PointingTable. I could add the Version column for PointingTable, however I would get stuck on that specific version even when a newer one is inserted for VersionedTable.

I'm struggling to figure out how to redesign this relationship, I've thought of a calculated column for PointingTable that would use the scalar function to get the maximum version, but I think that would be overkill, there must be a better way.