Self-feeding skills – Essaylink

Recall the family introduced in the chapter opener. Yvonne is a 9-month-old infant who is active and healthy. Her mother, Colleen, has brought her to the Women, Infants, and Children (WIC) Nutrition Program clinic, and they are accompanled by Margarita, the grandmother. Colleen feels unprepared to make decisions about what Yvonne shoud be eating at this age. Yvonne breastfeeds twice daily since Colleen works, but Colleen wonders if she should continue. The nurse praises Colleen for continuing with these two feedings daily since that ensures the benefits of breastfeeding such as immune protection against some illnesses, and it fosters mother-infant bonding. She reas- sures Colleen that it is beneficial for her to pump her breasts and suggests that the pumped milk be refrigerated and fed to Yvonne by bottle in the middle of the following day.

1. What fine motor skills would you expect to see in Yvonne at this age that will enable her to perform more self-feeding skills?

2 During the visit, the nurse takes a blood sample for hematocrit. What is the expected level at this age? What factors put infants in the second half of their first year of life at risk for iron deficiency anemia? What teaching can you do to promote intake of Iron ? Yvonne has a bottle of regular milk in the middle of the day. How could this contribute to anemia? What is recommended for her intake at this age! How Can you best support Colleen to encourage her continued breastfeeding of Yvonne?

3. Margarita prepares most of Yvonnes meals during the day and speaks Spanish. How will you prepare teaching for this grandmother so that she can beneit from the teaching that the clinic has designed for parents of infants? How can you make that teaching culturally sensitive?

4. As Colleen looks forward to the next few months, what in formation will she need to provide nutrition  intake for Yvonne? what are expected food patterns at 1 year and 18 months of age?

Machine learning is not all about autonomous vehicles and terminator robots. Techniques such as principle component analysis (PCA) can be combined with other data exploration techniques to help us gain a deeper understanding of the world around us. Many machine learning (ML) techniques aspire to reduce the complexity of data to simplify comparison and classification. – Essaylink

Assignment: Improvements to malware detection and classification
Machine learning is not all about autonomous vehicles and terminator robots. Techniques such as principle
component analysis (PCA) can be combined with other data exploration techniques to help us gain a deeper
understanding of the world around us. Many machine learning (ML) techniques aspire to reduce the
complexity of data to simplify comparison and classification.
Computational techniques for analysing characteristics of ‘things’ can help to identify patterns and attributes
which can be used to identify thing such as which species of plant a cell belongs to, what are the key drivers
for business profitability, and what traits are common in certain diseases.
Background
TOBORRM
TOBORRM is a new computer security start-up. They have traditionally worked on hacking and penetration
testing but are branching out into machine learning and active network defence systems. TOBORRM has
received a grant to research and develop detection technologies for malware.
TOBORRM Data Collection
Early work by TOBORRM saw their development team automate the collection of data from download sites.
The team developed a toolkit that could scour the internet for files and download them. TOBORRM used
their automated tools to collect the MLDATASET-200000-1612938401 data. This dataset provides 200,000
samples of clean and malicious files which have been classified as ‘Clean’ or ‘Malware’, respectively.
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The dataset gathered some basic statistics about file types, download locations and sizes. The programming
team also created “CodeCheck” as an internal tool to try to identify some basic file properties (such as if the
file is executable, or whether the file contains ‘recognisable text strings’). It is not known whether
“CodeCheck” is reliable.
Unfortunately, the TOBORRM team does not understand the intricacies of machine learning models, and
have developed the dataset without any consideration for scaling, categorisation of variables, encoding of
data etc. The MLDATASET-200000-1612938401 will require significant cleaning and preparation for it to be
useful for data visualisation and machine learning.
TOBORRM Dataset Malware Classification
In order to classify malware, TOBORRM used only ‘old’ files that were likely to have been identified by
other malware and virus scanners.
1. TOBORRM’s data collector would send the file to virustotal.com
2. files were tagged as “Malicious” if a majority of virustotal.com virus scanners recognised the file as
containing malware (see Figure 1)
3. Files were tagged as “Clean” if ALL virustotal.com scanners identified the file as “Clean”. (see
Figure 1)
Figure 1 – VirusTotal.com comparison of confirmed infected vs confirmed clean
As such, the “Actually Malicious” field can be considered to be a generally accurate classification for each
downloaded sample.
Initially the security and software development teams believed they would be able to gain insight from
various statistical analyses of the dataset. Their initial attempts to classify data lacked sensitivity and had
many false positives, the results of TOBORRM’s analysis have been included in the “Initial Statistical
Analysis” column of the data set and is provided for your information and comparison only.
SCENARIO
You have been brought on as part of a data analysis team to improve on their malware detection capabilities.
The basic analysis was conducted by TOBORRM staff based on their ‘gut feel’ and some basic statistical
understanding. You will be trying to improve their initial statistical analysis by using various machine
learning models for analysis and classification.
The raw data for your machine learning analysis is contained in the MLDATASET-2000001612938401.csv
file.
The variables in the dataset are as summarised in the table below.
Feature Description Data Type
Sample ID ID number of the collected sample Numeric
Download Source A description of where the sample came from Categorical
TLD Top Level Domain of the site where the sample came from Categorical
Download Speed Speed recorded when obtaining the sample Categorical
Ping Time To Server Ping time to the server recorded when accessing the sample Numeric
File Size (Bytes) The size of the sample file Numeric
How Many Times File Seen How many other times this sample has been seen at other sites (and not
downloaded) Numeric
Executable Code Maybe Present in Headers ‘CodeCheck’ Program has flagged the file as possibly containing
executable code in file headers Binary
No Executable Code Found In Headers ‘CodeCheck’ Program has flagged the file as not containing
executable code in the file headers Binary
Calls to Low-Level System Libraries When the file was opened or run, how many times were low-level
Windows System libraries accessed Numeric
Evidence of Code Obfuscation ‘CodeCheck’ Program indicates that the contents of the file may be
Obfuscated Binary
Threads Started How many threads were started when this file was accessed or launched Numeric
Mean Word Length of Extracted
Strings Mean length of text strings extracted from file using unix ‘strings’ program Numeric
Similarity Score An unknown scoring system used by
‘CodeCheck’ seems to be the score of how
similar the file is to other files recognised by ‘CodeCheck’ Numeric
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Characters in URL How long the URL is (after the .com / .net part). E.g. /index.html = 10 characters Numeric
Actually Malicious The correct classification for the file Binary
Initial Statistical Analysis Previous system performance of “FileSentry3000™ v1.0” Binary
Your initial goals will be to
• Clean and prepare the data for data exploration and basic data analysis, and later (for Assignment 2) for ML
modelling.
• Perform Principal Component Analysis (PCA) on the data.
• Identify features that may be useful for ML algorithms
• Create a brief report to the rest of the research team that will describe whether a subset of features could be
used to effectively identify malicious files.
TASK
First, copy the code below to a R script. Enter your student ID into the command set.seed(.) and run the
whole code. The code will create a sub-sample that is unique to you.
#You may need to change/include the path of your working directory
#Import the dataset into R Studio. dat – read.csv(-MLDATASET-200000-1612938401.csv-, na.strings=–,
stringsAsFactors=TRUE)
set.seed(Enter your student ID here)
#Randomly select 500 rows selected.rows – sample(1:nrow(dat),size=500,replace=FALSE)
#Your sub-sample of 500 observations and excluding the 1st and last column mydata –
dat[selected.rows,2:16]
dim(mydata) #check the dimension of your sub-sample
You are to clean and perform basic data analysis on the relevant features in mydata, and as well as principle
component analysis (PCA). This is to be done using “R”. You will report on your findings.
Part 1 – Exploratory Data Analysis and Data Cleaning
(i) For each of your categorical or binary variables, determine the number (%) of instances for each of their
categories and summarise them in a table as follows.
Categorical Feature Category N (%)
Feature 1 Category 1 10 (10%)
Category 2 30 (30%)
Category 3 60 (60%)
Feature 2 (Binary) YES 75 (75%)
NO 25 (25%)
… … …
Feature k Category 1 25 (25%)
Category 2 25 (25%)
Category 3 15 (15%)
Category 4 35 (35%)
(ii) Summarise each of your continuous/numeric variables in a table as follows.
Continuous Feature N (%) missing Min Max Mean Median Skewness
Feature 1 Feature2 ….
Feature k
….
….
….
….
….
….
(iii) Examine the results in sub-parts (i) and (ii). Are there any invalid categories/values for the categorical
variables? If so, how will you deal with them and why? Is there any evidence of outliers for any of the
continuous/numeric variables? If so, how many and what percentage are there and how will you deal with
them? Justify your decision in the treatment of outliers (if any).
Part 2 – Perform PCA and Visualise Data
(i) Clean your data as you have suggested in Part 1 (iii) to make it usable in “R”.
(ii) Export your “cleaned” data as follows. This file will need to be submitted along with you report.
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#Write to a csv file.
write.csv(mydata,-mydata.csv-)
** Do not read the data back in and use them **
(iii) Extract the data for the numeric features in mydata, along with Actually.Malicious, and store them as a
data frame/tibble. Then, perform PCA using prcomp(.) in R, but only on the numeric features.
– Outline why you believe the data should or should not be scaled, i.e. standardised, when performing PCA.
– Outline the individual and cumulative proportions of variance explained by each of the first 4 components.
– Outline the coefficients (or loadings) for PC1 to PC4, and describe the loadings for the PC1 and PC2 only.
– Outline how many principal components are adequate to explain at least 50% of the variability in your data.
(iv) Create a scree plot and interpret.
(v) Create a biplot with PC1 and PC2 to help visualise the results of your PCA in the first two dimensions.
Colour code the points with the variable Actually.Malicious. Write a paragraph to explain what your biplot is
showing. That is, comment on the PCA plot, the loading plot individually, and then both plots combined (see
Slides 28-29 of Module 3 notes) and outline and justify which (if any) of the features can help to distinguish
Malicious and Non- Malicious files.
(vi) Based on the results from parts (iii) to (v), describe
– which dimension (choose one) can assist with the classification of malwares (Hint: project all the points in
the PCA plot to PC1, i.e. horizontal axis and see whether there is good separation between the points for
malicious and non- malicious files. Then project to PC2, i.e. vertical axis and see if there is separation
between the malware and non-malware, and whether it is better than the projection to PC1).
– the key features in this dimension that can drive this process (Hint: based on your decision above, examine
the loadings from part (iii) of your chosen PC and choose those whose absolute loading (i.e. disregard the
sign) is greater than 0.3).

What to Submit
1. A single report (not exceeding 5 pages, does not include cover page, contents page and reference page, if
there is any) containing:
a. summary tables of all the variables in the dataset;
b. a list of data issues (if any) and how you have dealt with them in the data cleaning process;
c. your implementation of PCA and interpretation of the results, i.e. variances explained, scree plot, and the
contribution of each feature for PC1 and PC2;
d. biplot and its interpretation;
e. your explanation of selection and contribution of the features with respect to possible identification of
malicious files.
If you use any references in your analysis or discussion outside of the notes provided in the unit, you must
cite your sources.
2. The dataset containing your sub-sample of 500 observations, i.e., mydata.
3. A copy of your R code.
The report must be submitted through TURNITIN and checked for originality. The R code and data file are to
be submitted separately via a Blackboard submission link.
Note that no marks will be given if the results you have provided cannot be confirmed by your code.
Marking Criteria
Criterion Contribution to assignment mark
Correct implementation of descriptive analysis, data cleaning and PCA in R 20%
Correct explanation and justification in the treatment of missing and/or invalid observations in the data
cleaning process 10%
Accurate specification and interpretation of the contribution of principal components and its loading
coefficients. 15%
Accurate scree plot, with appropriate interpretation. 5%
Accurate biplot, with appropriate interpretation presented 25%
Appropriate selection of dimension for classification and features that contribute to the identification
malicious files with justification 10%
Communications skills – Tables and figures are well presented. Report, analysis and overall narrative is wellarticulated and communicated using language appropriate for a non-mathematical audience 15%
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Total 100%
Academic Misconduct
Edith Cowan University regards academic misconduct of any form as unacceptable. Academic misconduct,
which includes but is not limited to, plagiarism; unauthorised collaboration; cheating in examinations; theft
of other student’s work; collusion; inadequate and incorrect referencing; will be dealt with in accordance with
the ECU Rule 40 Academic Misconduct (including Plagiarism) Policy. Ensure that you are familiar with the
Academic Misconduct Rules.
Assignment Extensions
Applications for extensions must be completed using the ECU Application for Extension form, which can be
accessed online.
Before applying for an extension, please check out the ECU Guidelines for Extensions which details
circumstances that can and cannot be used to gain an extension. For example, normal work commitments,
family commitments and extra-curricular activities are not accepted as grounds for granting you an extension
of time because you are expected to plan ahead for your assessment due dates.
Please submit applications for extensions via email to both your tutor and the Unit Coordinator.
Where the assignment is submitted no more than 7 days late, the penalty shall, for each day that it is late, be
5% of the maximum assessment available for the assignment. Where the assignment is more than 7 days late

Art History, 19th Century Europe-France – Essaylink

 

 

The return of the monarchy to power in 1815 and the July Revolution of 1830 were
moments of defining political and cultural shifts in France that impacted the art that was
produced during the period. Following the 1848 Revolution, Courbet emerged as the
the chief architect of Realism, a style that challenged prevailing aesthetic assumptions
about art and disrupted academic hierarchies of meaning. Discuss key images and ideas
from each of the three eras—Restoration Monarchy, July Monarchy, and that of the 1848
Revolution and its aftermath—inserting artists’ work within the political and social
context the period. Where appropriate, be sure to address the institutional context in
which images were displayed and discussed, including Courbet’s Pavilion of Realism at
the 1855 Universal Exposition in Paris.

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Quality Improvement Framework – Essaylink

 

As we move from a healthcare system that rewards volume (fee-for-service), to one that rewards value how do
you see the concepts of Deming’s theory of profound knowledge (system, psychology, knowledge and
variation) applying to this transition? Feel free to tie in ideas from other thought leaders that “spoke to you”
throughout the module.
How do you as a healthcare consumer define value?
resources:
View these two short videos on Deming’s System of Profound Knowledge from the IHI website:
Deming’s Profound Knowledge Video 1 (Links to an external site.)
Deming’s Profound Knowledge Video 2

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Self-Defense – Use of Deadly Force – Essaylink

 

Assume that Katz is a passenger on the downtown express subway train in New York City. He is carrying a
loaded .38 caliber pistol inside his coat, in violation of the prohibition against possession of unlicensed
weapons. Katz had been mugged on a prior occasion on the streets of the city, and this is why he carries the
pistol. When Katz enters the subway car, he notices four noisy and boisterous youths, who are sitting together
at one end of the car. The other 20 passengers are sitting at the other end. Two of the youths are carrying
screwdrivers inside their coats so that they can break into video game coin boxes. Not seeing the screwdrivers.
Katz sits down near the four youths. Two of the youths stand up and approach Katz, and one youth asks for
five dollars. Katz asks him to repeat his question. This time the youth demands, “Give me five dollars.” Katz
responds by taking out his gun and shooting each of the 4 youths. Though none are killed, Katz is charged with
four counts of attempted murder.
Thread: You represent Katz and must draft well-reasoned legal arguments to support his claim of self-defense
for each of the following scenarios. Make sure to successfully address possible arguments that may be made
by the prosecutor against the claims of self-defense. Also, articulate and integrate at least 1 biblical principle
that supports the justification of self-defense for Katz.
a. Assume that before Katz fired any shots, he said, “I have no money.” Then the two youths turned their backs
to Katz and moved a few feet away from him, which is as far as they could move because they were at the end
of the car already. Katz takes aim at each youth and fires at their backs.
b. Assume that instead of firing any shots, Katz shows the handle of the gun to the four youths, and that he
“flashes” it in a threatening manner that suggests that he will use it if he is not left alone. Assume that one of
the youths does have a gun concealed in his jacket, and that in response to Katz “flashing” of the gun, the
youth pulls out his weapon and points it at Katz. Katz immediately draws and fires at this youth.
Textbook Readings
Joshua Dressler, Understanding Criminal Law (8th ed. 2018). ISBN: 9781531007911.
CHAPTER 18, 22.
Russell L. Weaver, John M. Burkoff, and Catherine Hancock. Criminal Law: A Contemporary Approach—With
Access (3rd ed. 2018). ISBN: 9781683289470
CHAPTER. 11–12
PLEASE NOTE
You must support your assertions with at least
4 scholarly citations in current Bluebook format with footnotes.
Acceptable sources include the
• Casebook
• the Bible
• law reviews
• journals
• case decisions
• and other scholarly publications.

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The value of ending inventory using full costing – Essaylink

 

1.What is the value of ending inventory using full costing?

2.What is the value of ending inventory using variable costing?

3.What is the cost of goods sold using full costing?

4.What is the cost of goods sold using variable costing?

5.What is net income using full costing?

Clinton Manufacturing produces snow shovels. The selling price per snow shovel is $31.00. There is no beginning inventory.

Costs involved in production are:

Direct material $6.00

Direct labor 4.00

Variable manufacturing overhead 4.00

Total variable manufacturing costs per unit $14.00

Fixed manufacturing overhead per year $166,650

In addition, the company has fixed selling and administrative costs of $161,100 per year

 

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Benchmark – Ethical Responsibility – Essaylink

You will assume the role of a public administrator to complete this assignment. Choose an administrator role; some examples are below:

Police Chief

City Manager

FBI Director

As the public administrator, in the role you choose, in 1,000 words do the following:

1. Describe how social responsibility and public interest intersect.

2. Analyze your responsibility to stakeholder from an ethical standpoint. Describe how a code of ethics or oath of office for the position you choose informs your ethical responsibilities

3. Describe how you will make the decisions necessary to ethically execute your position as a public administrator in the role you choose.

4. Create a suggested code of ethics or add to an existing code of ethics for the administrative role chosen.

5. Explain why it is essential for you, in this role, to conduct yourself in a legal and ethical manner. How would your failure to conduct yourself in an ethical manner affect various stakeholders you are responsible for?

Use three to five scholarly resources to support your explanations.

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Who should be criminally charged under Iowa law?Discuss – Essaylink

Week 9: Non-Traditional Defenses – CH 14

Watch the video titled A Case of Affluenza

Review the relevant textbook materials on Criminal Responsibility and Defenses.

Research the Iowa State Code to identify relevant crimes profiled in the case of Ethan Couch.

Assignment:

Students will analyze the facts from the video to make a formal recommendation to an Iowa prosecutor.

The prosecution recommendation should be based on the relevant crimes found in the Iowa State Code as if the crime had occurred within Iowa jurisdiction.

Answer the following questions:

Who should be criminally charged under Iowa law?

List the criminal charges recommended (e.g. first degree murder, second degree murder, felony murder, manslaughter, vehicular manslaughter, accidental – no criminal violation, etc.).

For each criminal charge recommended, explain how the facts from the case support the elements of the crime.  Do this for each person (if applicable), and each crime (if applicable).

Include a summary of evidence for the prosecutor as to why “Affluenza” should not be allowed as a defense in this case.

*This assignment is worth 10 points
A Case of Affluenza  (38 mins)

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Jean Arp’s Growth human – Essaylink

 

 

Creativity comes in many different forms in the humanities. What conclusions have you discovered concerning the Modern sculpture Growth [pages 92-93 in THTTA]? Use the following format/prompts to communicate your experience with Jean Arp’s Growth.

Is Jean Arp’s Growth human, animal or vegetable? If human, is it male or female?
Is this sculpture sensuous . . . appealing . . . APPALLING? To which of the senses does it appeal?
If you were to touch this sculpture, what do you think you would discover about its tactile qualities?
Even when only viewing the sculpture from one angle, how would you describe the sensory space in Growth?
Do you find meaning in Growth? Create an expressive narrative for your experience with Arp’s sculpture.

 

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Comparison of the Everyday Use Characters with Louise Mallard – Essaylink

This is an assignment that focuses on the comparison of the Everyday Use Characters with Louise Mallard. The paper also requires reading of previous responses.

Comparison of the Everyday Use Characters with Louise Mallard

Using the outline you created last week, write your comparison essay.

“compare/contrast essay comparing one of the characters in ‘Everyday Use’ with Louise Mallard in Chopin’s “Story of an Hour.”

Firstly, make sure you have read any comments I have returned to you about your outline before writing this essay. This essay will be a minimum of 1500 words.  Your commentary should also be the largest part of your essay, and the concrete detail should be minimal.  A rule to remember is that for every ONE piece of concrete detail, you need THREE sentences MINIMUM of explication.
If you only need part of a sentence as concrete detail, then do not use the whole quote.  Choosing long quotes may add to the word count of an essay, but will result in a lower grade because the essay should be mostly your original thoughts.  Make sure you follow the MLA format.

1. Firstly, review information on MLA format (Links to an external site.), In-text citations (Links to an external site.), Works Cited entries (Links to an external site.).

2. Secondly, view sample essay (Links to an external site.) and sample works cited list.

Comments on Previous work:

1.     For Reader’s Response: Everyday Use: I like that you were able to incorporate quotes from the story in your essay. This will be an important skill as you begin writing your essays in the course. Just check the format for internal citations: https://owl.purdue.edu/owl/research_and_citation/mla_style/mla_formatting_and_style_guide/mla_in_text_citations_the_basics.html

2.     For Reader’s Response: Chrysanthemums: You have incorporated some of the information but are missing many of the required characterizations. Additionally, Remember the Citations issues, as this affects the grade. Refer to the links above and in the previous point and link them in word directly. Remember it is MLA

3.     Comparative Essay Outline: This is really a rough draft rather than an outline. The purpose of an outline is to provide a concise overview of the main ideas of your essay. Also remember you’ll need to use MLA citation to provide internal citations for all quotes/paraphrases and a works cited list at the end of your essay. Your citation is inaccurate and affected your grade.
4.     Don’t forget to refer to the PowerPoints and use the terms in the literary Analysis terms as well as the elements of fiction when doing the comparative essays. Also identify and explain why you consider a character – meaning antagonists and pantagosnist. etc.

5.     Once done, check your paper for syntax errors and grammar mistakes.

6.     Points on Thesis Statements:

Thesis Statement

 

Lastly, here are some rules for constructing a thesis statement:

1.  The thesis statement is a complete sentence that lets the reader know what the paper will be about.
2. The thesis statement cannot be a question.
3. The thesis statement must be an opinion or an attitude and not just state a fact.
4.  The thesis statement should be the last sentence in the introductory paragraph
5. Lastly, do not state the obvious in the thesis statement. This means DO NOT WRITE:
I am going to write about my reasons for not wanting to move from Florida.

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