Verification And Validation Discussion Post

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Find a modeling article that you can critique for verification and validation. This could be a new article, or one from a list of provided articles in other online discussions. Find the lists of suggested articles by going to Content > Articles for post-session discussion. Article critiques: Create a new thread and post your response. Your critique should be at least 300 words and should address the following questions:

  1. Describe (or remind us) what the model was, and what research question it was used to investigate.
  2. How did the researchers go about verifying the model?
  3. How did the researchers go about validating the model?
  4. What else could be done (by these researchers or other researchers) to make sure the model is credible?
  5. Include a link or full citation for your source material.

Reply posts: Next, write substantive, thoughtful replies to at least two of your peers’ posts. Reply posts should address the following prompts:

  • Do you agree with the assessment in the original post? If you do agree, indicate what convinced you. If you don’t agree, explain why.
  • What other methods of verification and/or validation could the researchers have used?
  • In your opinion, what are the biggest challenges for verification and validation of scientific models?

Post one to reply:

 

This was probably my favorite Model and study from the course. The study was all about the use of computer simulating and finding a method of planting maize efficiently. They investigated many questions, such as “What will the influence of field seedling emergence rate on the yield be like?”, “Which planting methods is the best?”, “Planting density will influence the yield, then how much will the influence be?”, and “Different planting density can lead to the yield compensation because of the sparse breaks up, then how much will the compensation be?”

To Verify their model essentially they only needed to make sure their software was working, and was working as intended.  They output several visualizations to verify that their simulation is working as intended.

To Validate, the researchers used mathematical depictions based on previous field experiments and studies of maize planting. By basing their model on real world data they can to a certain degree replicate the natural world.

This is only a model of course, and to completely validate their model for the natural world would involve many more factors to be considered. The researchers mention such aspects as seed quality and variety, soil factors such as acidity, fertilizers, basic things like sunshine and weather or moisture where much of their mathematics they utilized will have be changed to more accurately the germination and growing of maize.

The study can be found here.

Second Post to reply:

 

  • Describe (or remind us) what the model was, and what research question it was used to investigate.

The model is intended to research Sea surface temperature patterns that occur with global warming. The interest in investigating these patterns is due to information about how the temperature in the Arctic Ocean have increased without negative feedback loops from ice melt. It has generally been understood that the water warms when ice melts from global warming, and there is less mass to reflect solar radiation. Since the information indicates that warming is occurring without the accepted theory, researchers were interested in learning why this is the case.

  • How did the researchers go about verifying the model?

In this model the researchers aggregated 17 prior models with verified information about longwave radiation. Another study had pointed to the data being similar in warming patterns so that seemed to indicate there may be information that could be inferred from studying the data. They also worked with two twenty year data sets of historical climate and projected climate information in what they referred to as a multimodel ensemble analysis approach in order to reduce internal noise.

  • How did the researchers go about validating the model?

So for one, they applied some fancy math that I don’t understand, and that helped them to find patterns in the data. Then they compared the data from their model to the models from their aggregated lists average data.

  • What else could be done (by these researchers or other researchers) to make sure the model is credible?

A main factor in the results of this model being credible have to do with the information from the previous studies being accurate, and the metrics for measuring short and longwave radiation being available. Only 13 of the 17 models had this data available in the way that the researchers needed, so I think if there were a way to aggregate more data related to the short and longwave radiation that was used to calculate the results, and if after that the results we’re able to be repeated, then the model would be more credible.

  • Include a link or full citation for your source materia

https://journals.ametsoc.or

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Ageng Based

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Read and analyze an article that uses an agent-based model, and present it to your classmates. Select an article from the list on this page (link). You are also welcome to use an article you find on your own, as long as it meets the criteria for a scientific model.

Article critiques: Create a new thread and post a critique of an article. Your critique should be at least 300 words and should address the following questions:

  1. How would you describe the model? What is it made of? What does it do?
  2. What research question(s) did the authors investigate?
  3. What did the researchers learn by using this model? What were their results?
  4. How did the researchers make sure their model is credible? Do you think it is trustworthy enough to investigate their research question(s)?
  5. Was agent-based modeling a good choice for this study, in your opinion?
  6. Include a link or full citation for your source material.

Reply posts: Next, write substantive, thoughtful replies to at least two of your peers’ posts. Reply posts should address the following prompts:

  • Do you agree with the assessment in the original post? If you do agree, indicate what convinced you. If you don’t agree, explain why.
  • What other research questions might be addressed by the model?
  • What other types of models might address the research aims?
  • You may also share any prior knowledge or personal experience you have with the topic to enrich the discussion.

Post 1 to reply:

 

Filatova, Olga A., and Patrick J. O. Miller. 2015. “An Agent-Based Model of Dialect Evolution in Killer Whales.” Journal of Theoretical Biology 373 (May): 82–91. https://doi.org/10.1016/j.jtbi.2015.03.020.

Killer whales are a unique animal species in that they have vocal dialects that they learn from other whales. A group of orcas living around the San Juan Islands can sound different than a pod off the coast of Mexico. Whales can learn and replicate sounds they encounter from other whales. In this article, the researchers describe an agent-based model of orca populations and test a set of vocal-learning rules to evaluate which mechanism might lead to the development of dialect groupings seen in the whale’s native habitat. They tested a null model with genetic transmission and no learning, and ten models with learning rules that vary by template source, variation type and type of call change. The model produced results that only really showed some similarity to wild orcas. A pattern like the dialect diversity seen in the wild came about only when rules were applied in combinations and similar outputs could happen from different learning rules and their combinations. What happened with the model emphasizes the lack of information on quantitative features of wild killer whale. It is because of this that it seems to me that maybe model wasn’t the best way to study this topic.

Post 2 to reply :

 

1. This agent-based model is studying the market penetration of plug-in hybrid electric vehicles or (PHEV). This model examines the sensitivity to gasoline prices, to accuracy in estimation of fuel costs, to agent willingness to adopt the PHEV technology, to PHEV purchase price and rebates, to PHEV battery range, and to heuristic values related to gasoline usage.  I agree this is a good model to the fact the researchers are trying to find a better way to market PHEV’s.

2. To identify interactions among potential leverage points that could inform policy and consumer access to expected lifetime fuel costs that may enhance PHEV market penetration. How such a model could be used by policy-makers and vehicle manufacturers to help prioritize investments influencing PHEV adoption.

3. Providing stickers on the PHEV that estimate lifetime fuel costs would help consumers be open to more PHEV’s. Influencing consumers to place more weight on non-financial considerations that encourage lower gasoline consumption when making a vehicle purchase. That the current temporary $2500-$7500 PHEV federal tax credit currently offered is not likely to have lasting effects on long term fuel efficiency of the fleet unless manufacturers are able to lower sticker prices after the rebates are discontinued.

4. This model was compared to two other similar models Diamond (2009) and Morrow et al. (2010) and compared the findings. The findings were all similar. This showed the model to be trustworthy for the most part. It should be noted the author of this model stated that further research needed to be done to gain further data and knowledge to determine PHEV technology to be willing to consider becoming new adopters.

5. This was a good use of an agent-based model. Marketing is quite complex, especially in the automotive sector. Automobile manufactures have to consistently evolve with ever-changing regulations and consumer personal preferences. Consumers while having more information readily available, often have a tough choice of buying an automobile. For most purchasing and owning an automobile is very expensive. PHEVs are fairly new to the market and most consumers look at the initial cost and savings. Using an agent-based model in this may help consumers make better-informed decisions for long term ownership as well as help manufacturers build a better-suited product.

6. https://www-sciencedirect-com.proxy.lib.pdx.edu/science/article/pii/S0301421511002904

Please Keep reply in a different section than the discussion post section.

Discussion Post Questions: Winter And Climate

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Please answer both questions with a minimum of 180 words

1. I’m confused about relative humidity versus dew point. What is the difference between the two, and which is a better indicator of the amount of moisture in the air? Which is more closely related to how sticky the air feels? Why?

What role does humidity play in human comfort? Think about, for example, electric heat versus gas or air conditioning versus a swamp cooler.

2. Rain forests are normally located in the tropical climates, but there is a mid-latitude rain forest in the northwest continental U.S. How is this possible? Please explain the processes that are taking place. Do the mountain ranges that are parallel and relatively close to the shoreline play a important part in the process? If so, state why or why not.

Book: Title: Meteorology Today: An Introduction to Weather, Climate, and the Environment
Edition: 11th
Author: Ahrens, C. D., & Henson, R.
ISBN-13: 978-1-305-11358-9

Videos:

https://youtu.be/hehXEYkDq_Y

Is there a difference between “common practice” and “best practice”?

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Is there a difference between “common practice” and “best practice”?

When you first went to work for your current organization,  experienced colleagues may have shared with you details about processes  and procedures. Perhaps you even attended an orientation session to  brief you on these matters. As a “rookie,” you likely kept the nature of  your questions to those with answers that would best help you perform  your new role.

Over time and with experience, perhaps you recognized aspects of  these processes and procedures that you wanted to question further.  This is the realm of clinical inquiry.

Clinical inquiry is the practice of asking questions about  clinical practice. To continuously improve patient care, all nurses  should consistently use clinical inquiry to question why they are doing  something the way they are doing it. Do they know why it is done this  way, or is it just because we have always done it this way? Is it a  common practice or a best practice?

In this Assignment, you will identify clinical areas of interest  and inquiry and practice searching for research in support of  maintaining or changing these practices. You will also analyze this  research to compare research methodologies employed.

To Prepare:

  • Review the Resources and identify a clinical issue of interest that can form the basis of a clinical inquiry.
  • Based on the clinical issue of interest and using keywords  related to the clinical issue of interest, search at least four  different databases in the Walden Library to identify at least four  relevant peer-reviewed articles related to your clinical issue of  interest. You should not be using systematic reviews for this  assignment, select original research articles.
  • Review the results of your peer-reviewed research and reflect  on the process of using an unfiltered database to search for  peer-reviewed research.
  • Reflect on the types of research methodologies contained in the four relevant peer-reviewed articles you selected.

Part 1: An Introduction to Clinical Inquiry

Create a 4- to 5-slide PowerPoint presentation in which you do the following:

  • Identify and briefly describe your chosen clinical issue of  interest. This clinical issue will remain the same for the entire course  and will be the basis for the development of your PICOT question
  • Describe how you used keywords to search on your chosen clinical issue of interest.
  • Identify the four research databases that you used to conduct your search for the peer-reviewed articles you selected.
  • Provide APA citations of the four peer-reviewed articles you selected.

Part 2: Identifying Research Methodologies

After reading each of the four peer-reviewed articles you  selected, use the Matrix Worksheet template to analyze the methodologies  applied in each of the four peer-reviewed articles. Your analysis  should include the following:

  • The full citation of each peer-reviewed article in APA format.
  • A brief (1-paragraph) statement explaining why you chose this  peer-reviewed article and/or how it relates to your clinical issue of  interest, including a brief explanation of the ethics of research  related to your clinical issue of interest.
  • A brief (1-2 paragraph) description of the aims of the research of each peer-reviewed article.
  • A brief (1-2 paragraph) description of the research methodology  used. Be sure to identify if the methodology used was qualitative,  quantitative, or a mixed-methods approach. Be specific.
  • A brief (1- to 2-paragraph) description of the strengths of  each of the research methodologies used, including reliability and  validity of how the methodology was applied in each of the peer-reviewed  articles you selected.

Melnyk, B. M., & Fineout-Overholt, E. (2018). Evidence-based practice in nursing & healthcare: A guide to best practice (4th ed.). Philadelphia, PA: Wolters Kluwer.
Chapter 2, “Asking Compelling Clinical Questions” (pp. 33–54)
Chapter 21, “Generating Evidence Through Quantitative and Qualitative Research” (pp. 607–653)

Grant, M. J., & Booth, A. (2009). A typology of reviews: An analysis of 14 review types and associated methodologies. Health Information and Libraries Journal, 26, 91–108. doi:10.1111/j.1471-1842.2009.00848.x

Hoare, Z., & Hoe, J. (2013). Understanding quantitative research: Part 2. Nursing Standard, 27(18), 48–55. doi:10.7748/ns2013.01.27.18.48.c9488

Hoe, J., & Hoare, Z. (2012). Understanding quantitative research: Part 1. Nursing Standard, 27(15), 52–57. doi:10.7748/ns2012.12.27.15.52.c9485