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Please explain fully each step and what inputs and the number of rows for the Two Way ANOVA Researchers have sought to examine the effect of various types of music on agitation levels in patients who are in the early and middle stages of Alzheimer's disease. Patients were selected to participate in the study based on their stage of Alzheimer's disease. Three forms of music were tested: Easy listening, Mozart, and piano interludes. While listening to music, agitation levels were recorded for the patients with a high score indicating a higher level of agitation. Scores are recorded below. Perform a two-way ANOVA and interpret the results. Test at the 0.05 level. Use Excel and attach the printout..
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There are many potential root causes of conflict at work. Well go over six of them here.
Remember, anything that leads to a disagreement can be a cause of conflict. Although conflict is
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Causes of Conflict
Organizational Structure
Conflict tends to take different forms, depending on the organizational structure. For example, if
a company uses a matrix structure as its organizational form, it will have decisional conflict built
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Remember, anything that leads to a disagreement can be a cause of conflict. Although conflict is
common to organizations, some organizations have more than others.
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Organizational Structure
Conflict tends to take different forms, depending on the organizational structure. For example, if
a company uses a matrix structure as its organizational form, it will have decisional conflict built
in, because the structure specifies that each employee report to two bosses. For example, the
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can lead to confusion as the companys 147,000 employees are divided across 100 countries into
four global divisions, with each division focusing on different industries and products.
Limited Resources
Resources such as money, time, and equipment are often scarce. Competition among people or
departments for limited resources is a frequent cause for conflict. For example, cutting-edge
laptops and other devices are expensive resources that may be allocated to employees on a need-
to-have basis in some companies. When a group of employees have access to such resources
while others do not, conflict may arise among employees or between employees and
management. While technical employees may feel that these devices are crucial to their
productivity, employees with customer contact such as sales representatives may make the point
that these devices are important for them to make a good impression to clients. Because
important resources are often limited, this is one source of conflict many companies have to live
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advertising for your product, youre dependent on the creative team to design the words and
layout, the photographer or videographer to create the visuals, the media buyer to purchase the
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0 10 5 2
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close all; clc; % Detailed instructions: \% Load the training set of 2414 images contained in the
MATLAB data file \% training_set_faces.m into the MATLAB workspace: Each image % in the
training set is a 48px by 42px image of a face. The training set fa% are saved in the MAT file
training_set_faces.mat. When you load this data \% file into the MATLAB workspace, you will
see a 3D array called yalefaces \% where the entry yalefaces (:,:,1) is the first image of the
training set, % yalefaces (:,:,2) is the second image, etc. % \% Suggested MATLAB functions:
load \% !! Your code here !! Load the training images from the provided \% MAT file
training_set_faces.mat load training_set_faces.mat;
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from the training set 3D array to demonstrate you've \% correctly imported the training set
images. % \% Suggested MATLAB functions: imshow \% PLOTTING WITH imshow: Use the
options 'DisplayRange', [], and \% 'InitialMagnification', 'fit' when using imshow so that the
plotted images % are easy to see. See imshow help documentation for syntax details and the %
in-class Eigenfaces activities more help. % !! Your code here !! In a new figure, plot one of the
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image into a vector, simply by concatenating the row % of pixels in the original image, resulting
in a single column with 4842=%2016 elements, just like the in-class activity. % Then combine
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matrix is an image. Each row % of this matrix T corresponds to a pixel location. The 2D array
must be % assigned to the variable T. The size of T will be 20162414. %% suggested MATLAB
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pixel value across all images % in the training set at each pixel location. So the mean face pixel
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pixel (2,3). The mean face will be a column vector of size 20161. % Remember that the.
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b. All states
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self.lower_layer = lower_layer
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self.button.on_click(self.callback)
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{time.time_ns()}'
self.lower_layer.send(message)
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num_duplication = 0
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continue
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message_id = int(message_id.split(': ')[1])
timestamp = float(timestamp.split(': ')[1])
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continue
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self.lower_layer.send(message)
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)
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Date = tuple[int, int, int]
YEAR = 0
MONTH = 1
DAY = 2
# column numbers of data within input csv file
INPUT_TITLE = 2
INPUT_CAST = 4
INPUT_DATE = 6
INPUT_CATEGORIES = 10
def read_file(filename: str) -> (dict[str, Date],
dict[str, list[str]],
dict[str, list[str]]):
'''
Populates and returns a tuple with the following 3 dictionaries
with data from valid filename.
3 dictionaries returned as a tuple:
- dict[show title: date added to Netflix]
- dict[show title: list of actor names]
- dict[category: list of show titles]
Keys without a corresponding value are not added to the dictionary.
For example, the show 'First and Last' in the input file has no cast,
therefore an entry for 'First and Last' is not added
to the dictionary dict[show title: list of actor names]
Precondition: filename is csv with data in expected columns
and contains a header row with column titles.
NOTE: csv = comma separated values where commas delineate columns
Show titles are considered unique.
>>> read_file('0lines_data.csv')
({}, {}, {})
>>> read_file('11lines_data.csv')
({'SunGanges': (2019, 11, 15), \
'PK': (2018, 9, 6), \
'Phobia 2': (2018, 9, 5), \
'Super Monsters Save Halloween': (2018, 10, 5), \
'First and Last': (2018, 9, 7), \
'Out of Thin Air': (2017, 9, 29), \
'Shutter': (2018, 9, 5), \
'Long Shot': (2017, 9, 29), \
'FIGHTWORLD': (2018, 10, 12), \
"Monty Python's Almost the Truth": (2018, 10, 2), \
'3 Idiots': (2019, 8, 1)}, \
\
{'SunGanges': ['Naseeruddin Shah'], \
'PK': ['Aamir Khan', 'Anuskha Sharma', 'Sanjay Dutt', 'Saurabh Shukla', 'Parikshat Sahni',
'Sushant Singh Rajput', 'Boman Irani', 'Rukhsar'], \
'Phobia 2': ['Jirayu La-ongmanee', 'Charlie Trairat', 'Worrawech Danuwong', 'Marsha
Wattanapanich', 'Nicole Theriault', 'Chumphorn Thepphithak', 'Gacha Plienwithi', 'Suteerush
Channukool', 'Peeratchai Roompol', 'Nattapong Chartpong'], \
'Super Monsters Save Halloween': ['Elyse Maloway', 'Vincent Tong', 'Erin Matthews', 'Andrea
Libman', 'Alessandro Juliani', 'Nicole Anthony', 'Diana Kaarina', 'Ian James Corlett', 'Britt
McKillip', 'Kathleen Barr'], \
'Shutter': ['Ananda Everingham', 'Natthaweeranuch Thongmee', 'Achita Sikamana', 'Unnop
Chanpaibool', 'Titikarn Tongprasearth', .
Please correctly choose the 3 main components of Data Warehousing.pdf
Please correctly choose the 3 main components of Data Warehousing:
Business Intelligence
Data Warehousing/Dimensional Modeling
OLTP (Online Transaction Processing)
Extract and Load (EL)
ER Modeling
Data Sources
Data Integration
Business Intelligence
Data Warehousing/Dimensional Modeling
OLTP (Online Transaction Processing)
Extract and Load (EL)
ER Modeling
Data Sources
Data Integration.
Please convert the following C function to Mips assembly with commen.pdf
Please convert the following C function to Mips assembly with comments.
void countSort(int arr[], int n, int exp) {
int output[n]; int i, count[10] = { 0 };
for (i = 0; i < n; i++)
count[(arr[i] / exp) % 10]++;
for (i = 1; i < 10; i++)
count[i] += count[i - 1];
for (i = n - 1; i >= 0; i--) {
output[count[(arr[i] / exp) % 10] - 1] = arr[i];
count[(arr[i] / exp) % 10]--;
}
for (i = 0; i < n; i++) arr[i] = output[i];
}.
please Cite the resource. please not the same as the statement thats.pdf
please Cite the resource. please not the same as the statement thats already on here. 4-1
Discussion: Criminal Responsibility To complete this discussion, please base your work on
Enron, WorldCom, or another white collar crime story of your choosing. - Name the company
you selected and briefly summarize the crime. - Do you think that the CEOs and other corporate
officers involved were justly held criminally responsible or not? Explain your perspective. - Do
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necessity to protect the public from financial wrongdoing? Explain your position..
The History of Stoke Newington Street Names
Presented at the Stoke Newington Literary Festival on 9th June 2024
www.StokeNewingtonHistory.com
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Please answer the 4 questions at the end Causes and Outcomes of Co.pdf
Please answer the 4 questions at the end
Causes and Outcomes of Conflict
There are many potential root causes of conflict at work. Well go over six of them here.
Remember, anything that leads to a disagreement can be a cause of conflict. Although conflict is
common to organizations, some organizations have more than others.
Causes of Conflict
Organizational Structure
Conflict tends to take different forms, depending on the organizational structure. For example, if
a company uses a matrix structure as its organizational form, it will have decisional conflict built
in, because the structure specifies that each employee report to two bosses. For example, the
multinational power company with headquarters in Switzerland, ABB Ltd. is organized around
the world in a matrix structure based on the dimensions of country and industry. This structure
can lead to confusion as the companys 147,000 employees are divided across 100 countries into
four global divisions, with each division focusing on different industries and products.
Limited Resources
Resources such as money, time, and equipment are often scarce. Competition among people or
departments for limited resources is a frequent cause for conflict. For example, cutting-edge
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to-have basis in some companies. When a group of employees have access to such resources
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productivity, employees with customer contact such as sales representatives may make the point
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Task Interdependence
Another cause of conflict is task interdependence; that is, when accomplishment of your goal
requires reliance on others to perform their tasks. For example, if youre tasked with creating
advertising for your product, youre dependent on the creative team to design the words and
layout, the photographer or videographer to create the visuals, the media buyer to purchase the
advertising space, and so on. The completion of your goal (airing or publishing your ad) is
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(Please note that I don't need an explanation for the code, but the code itself. Thanks in advance)
Input: Take a filed named topo.txt as an input, the contents of the file is below
0 10 5 2
10 0 1 1
5 1 0 3
2 1 3 0
Your simulator should read a topology file (say, topo.txt) with a matrix {Di,j }, i, j {0.., N 1}. N
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representing the minimum distance from node 0 to all nodes in the topology. Lastly, node 0
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topology.
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Please use this method to update DV for each node- rtupdate(struct distance table *dt, struct rtpkt
recv pkt)
This method will be called for each received routing packet at each simulation time slot k 1. It
parses the input, which is a routing packet recv pkt to update the distance table based on the DV
algorithm. If its own minimum distance to any of the other nodes is updated, the node informs its
directly connected neighbors of this change in minimum cost by sending them a routing packet
(send2neighbor(rtpkt packet)). Therefore, in the given example, nodes 0 and 1 will communicate
with each other, but nodes 1 and 3 will not.
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Test cases and the expected outputs:
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Swimlanes:
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please do the extra credit \%\% (1) Load training set images from a .mat file (2 points) clear;
close all; clc; % Detailed instructions: \% Load the training set of 2414 images contained in the
MATLAB data file \% training_set_faces.m into the MATLAB workspace: Each image % in the
training set is a 48px by 42px image of a face. The training set fa% are saved in the MAT file
training_set_faces.mat. When you load this data \% file into the MATLAB workspace, you will
see a 3D array called yalefaces \% where the entry yalefaces (:,:,1) is the first image of the
training set, % yalefaces (:,:,2) is the second image, etc. % \% Suggested MATLAB functions:
load \% !! Your code here !! Load the training images from the provided \% MAT file
training_set_faces.mat load training_set_faces.mat;
\%\% (2) Plot one training set image (5 points) % Detailed intructions: \% Plot one of the images
from the training set 3D array to demonstrate you've \% correctly imported the training set
images. % \% Suggested MATLAB functions: imshow \% PLOTTING WITH imshow: Use the
options 'DisplayRange', [], and \% 'InitialMagnification', 'fit' when using imshow so that the
plotted images % are easy to see. See imshow help documentation for syntax details and the %
in-class Eigenfaces activities more help. % !! Your code here !! In a new figure, plot one of the
images you just loaded \% into MATLAB. Include a descriptive figure title. (5 points) figure
imshow(yalefaces (:, : , 1), [10 250 , 'InitialMagnification ', ... 'fit', 'Interpolation', 'bilinear')
title('eigenface 1)
\% (3) Vectorize the images and combine into 2D array (8 points) % Detailed instructions: %
create a 2D array that contains all the vectorized images in the training % set. First, convert each
image into a vector, simply by concatenating the row % of pixels in the original image, resulting
in a single column with 4842=%2016 elements, just like the in-class activity. % Then combine
all 2414 training set image column vectors into % a single matrix T, where each column of the
matrix is an image. Each row % of this matrix T corresponds to a pixel location. The 2D array
must be % assigned to the variable T. The size of T will be 20162414. %% suggested MATLAB
functions: reshape (or using a for loop) % !! Your code here !! Vectorize training set images into
a 2D array called T % ( 8 points) [a,b, c] = size(yalefaces); T = reshape(yalefaces, [a*b, c]);
\% We need to be sure the data type of our T matrix is double for the rest % of the computations
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pixel value across all images % in the training set at each pixel location. So the mean face pixel
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Please discuss the following interrnal control issues:
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2. Assume that Brooke Miles, account payable clerk for West Coast Design Inc., stole $48,350
by paying fictitous invoices for goods that were never received. The clerk set up accounts in the
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here the code will be available:
https://colab.research.google.com/drive/1MXy8PXf3tN7Dgxebtjt8RCAkL9i0UvbR?usp=sharing
Describe:
a. The layer model (Use a figure to illustrate entities on all layers)
b. All states
c. All events
d. The state transition (Use a figure to illustrate the state transition diagram)
e. Design of the constructor (constructor:
import time
import ipywidgets as widgets
class MLE_TR:
def __init__(self, lower_layer):
self.lower_layer = lower_layer
self.button = widgets.Button(description='Send 100 messages')
self.button.on_click(self.callback)
def callback(self, button):
print('Sending 100 messages...')
for i in range(100):
message = f'Experiment ID: {random.randint(1, 10)}, Message ID: {i}, Current Time:
{time.time_ns()}'
self.lower_layer.send(message)
)
f. Design of the loop_Rx function (loop_Rx:
def loop_Rx(self):
num_messages = 0
total_delay = 0
num_loss = 0
num_duplication = 0
while True:
message = self.lower_layer.receive()
if message is None:
continue
num_messages += 1
experiment_id, message_id, timestamp = message.split(', ')
experiment_id = int(experiment_id.split(': ')[1])
message_id = int(message_id.split(': ')[1])
timestamp = float(timestamp.split(': ')[1])
delay = time.time() - timestamp
total_delay += delay
if random.random() < 0.1:
num_loss += 1
continue
if random.random() < 0.05:
num_duplication += 1
self.lower_layer.send(message)
print(f'Received message: {message}')
avg_delay = total_delay / num_messages
loss_rate = num_loss / num_messages
duplication_rate = num_duplication / num_messages
print(f'Average delay: {avg_delay}, Loss rate: {loss_rate}, Duplication rate:
{duplication_rate}')
)
g. Design a method to generate measurement output (The only part that is not a describe only,
need to implement as well, you will need to specify when the output shall be generated because
the lower layer can be unreliable).
Please complete the following the function query which requires.pdf
*****Please complete the following the function query which requires the read_file to be done
as a helper function. use python and without using any list comprehensions, not importing CSV
and only import doctest, as straightforward coding as possible for example please don't use set(),
get() entry() these built-in python function, sort and len is allowed. make sure the doctest cases
can pass as well. Thank you!
***note: the large data file use to test for query is 1000 lines of randomly generated using the
same format like 11lines_data file
# all 2 digit years assumed to be in the 2000s
START_YEAR = 2000
# represents a Gregorian date as (year, month, day)
# where year>=START_YEAR,
# month is a valid month, 1-12 to represent January-December
# and day is a valid day of the given month and year
Date = tuple[int, int, int]
YEAR = 0
MONTH = 1
DAY = 2
# column numbers of data within input csv file
INPUT_TITLE = 2
INPUT_CAST = 4
INPUT_DATE = 6
INPUT_CATEGORIES = 10
def read_file(filename: str) -> (dict[str, Date],
dict[str, list[str]],
dict[str, list[str]]):
'''
Populates and returns a tuple with the following 3 dictionaries
with data from valid filename.
3 dictionaries returned as a tuple:
- dict[show title: date added to Netflix]
- dict[show title: list of actor names]
- dict[category: list of show titles]
Keys without a corresponding value are not added to the dictionary.
For example, the show 'First and Last' in the input file has no cast,
therefore an entry for 'First and Last' is not added
to the dictionary dict[show title: list of actor names]
Precondition: filename is csv with data in expected columns
and contains a header row with column titles.
NOTE: csv = comma separated values where commas delineate columns
Show titles are considered unique.
>>> read_file('0lines_data.csv')
({}, {}, {})
>>> read_file('11lines_data.csv')
({'SunGanges': (2019, 11, 15), \
'PK': (2018, 9, 6), \
'Phobia 2': (2018, 9, 5), \
'Super Monsters Save Halloween': (2018, 10, 5), \
'First and Last': (2018, 9, 7), \
'Out of Thin Air': (2017, 9, 29), \
'Shutter': (2018, 9, 5), \
'Long Shot': (2017, 9, 29), \
'FIGHTWORLD': (2018, 10, 12), \
"Monty Python's Almost the Truth": (2018, 10, 2), \
'3 Idiots': (2019, 8, 1)}, \
\
{'SunGanges': ['Naseeruddin Shah'], \
'PK': ['Aamir Khan', 'Anuskha Sharma', 'Sanjay Dutt', 'Saurabh Shukla', 'Parikshat Sahni',
'Sushant Singh Rajput', 'Boman Irani', 'Rukhsar'], \
'Phobia 2': ['Jirayu La-ongmanee', 'Charlie Trairat', 'Worrawech Danuwong', 'Marsha
Wattanapanich', 'Nicole Theriault', 'Chumphorn Thepphithak', 'Gacha Plienwithi', 'Suteerush
Channukool', 'Peeratchai Roompol', 'Nattapong Chartpong'], \
'Super Monsters Save Halloween': ['Elyse Maloway', 'Vincent Tong', 'Erin Matthews', 'Andrea
Libman', 'Alessandro Juliani', 'Nicole Anthony', 'Diana Kaarina', 'Ian James Corlett', 'Britt
McKillip', 'Kathleen Barr'], \
'Shutter': ['Ananda Everingham', 'Natthaweeranuch Thongmee', 'Achita Sikamana', 'Unnop
Chanpaibool', 'Titikarn Tongprasearth', .
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OLTP (Online Transaction Processing)
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ER Modeling
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Data Warehousing/Dimensional Modeling
OLTP (Online Transaction Processing)
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ER Modeling
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Please convert the following C function to Mips assembly with comments.
void countSort(int arr[], int n, int exp) {
int output[n]; int i, count[10] = { 0 };
for (i = 0; i < n; i++)
count[(arr[i] / exp) % 10]++;
for (i = 1; i < 10; i++)
count[i] += count[i - 1];
for (i = n - 1; i >= 0; i--) {
output[count[(arr[i] / exp) % 10] - 1] = arr[i];
count[(arr[i] / exp) % 10]--;
}
for (i = 0; i < n; i++) arr[i] = output[i];
}.
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