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Medium 9781491949351

4. Extending Ohai

Jon Cowie O'Reilly Media ePub

As we saw in Chapter 3, during the initial stage of the Chef run process (described in Get Configuration Data) Chef runs the Ohai tool to build up a collection of data about the node, which is saved on the Chef server as part of the node object. Ohai is installed as part of the Chef installation process and must be present on a node for chef-client or chef-solo to function correctly.

The core Ohai tool is driven by its flexible and powerful plugin interface. Out of the box, Ohai ships with a number of useful plugins that collect data on various generic aspects of the underlying system, such as the hardware, operating system, and networking configuration.

The power of Ohai’s plugin framework, however, comes from the fact that it allows us to define our own plugins to augment the information stored about our nodes on the Chef server. Say, for example, we want our nodes to define an attribute stating whether they are virtual machines (VMs) or physical servers, so that our recipes only install VM-specific packages on nodes that need them. Perhaps we want to add a node attribute that fetches the physical location of a node from an asset management system so that we can make use of this logic in our recipe code. Out of the box, Ohai does not collect any of this data—but we can easily create our own plugins that do.

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Medium 9781626563254

#45 Pick Your Battles

Manning, John Berrett-Koehler Publishers ePub

If you’re in leadership for any length of time, I can guarantee you’re going to have battles to fight and wars to win. But great leaders know, as the popular country song goes, “You’ve got to know when to hold ‘em, know when to fold ‘em, know when to walk away, know when to run.” Disciplined Leaders learn to pick their battles within an organization with extreme care, so they can optimize their leadership and maintain authority.

One MAP client got his organization together and directly involved his people in deciding which battles they’d choose. The company was facing about ten identified challenges. After a long discussion, everyone voted on the top three—and 80 percent of those in the room picked the same top-three battles to fight. Why? Because most realized these three battles, which amounted to approximately 20 percent of fighting, could win 80 percent of the war. In choosing what to tackle, they embraced the Pareto Principle—20 percent of activities net 80 percent of results—and this was a critical point of understanding and empowerment because this organization didn’t have the resources to fight every battle and had to focus on the most important ones to win the war.

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Medium 9781601322548

A New Level Set Method for Biomedical Image Segmentation

Hamid R. Arabnia, Leonidas Deligiannidis, Joan Lu, Fernando G. Tinetti, Jane You, George Jandieri, Gerald Schaefer, Ashu M. G. Solo, Vladimir Volkov CSREA Press PDF

Int'l Conf. IP, Comp. Vision, and Pattern Recognition | IPCV'13 |

A New Level Set Method for Biomedical Image

Segmentation

Yide Ma, Weiying Xie, Zhaobin Wang, and Wen Li

School of Information Sci. Eng, Lanzhou University, Lanzhou, China

Abstract - This paper presents a new biomedical image segmentation method that applies an edge-based level set method. According to low contrast in biomedical images, we mainly make focus on introducing the Laplace operator in external energy of level set method for accurately detecting object edge. A preliminary evaluation of the proposed method mainly performs on gallstone detection and extraction, mammographic image segmentation, iris inner location and polysaccharides extraction. Finally, the comparison experimental results demonstrate that our proposed approach potentially performs better than the representative level set method for biomedical image segmentation in terms of sensitivity, accuracy and specificity, with same initial contours.

Keywords: Biomedical Image Segmentation; Level Set

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Medium 9781855754355

CHAPTER THIRTEEN: Desire’s dark alchemy: turning gold into dross

Karnac Books ePub

Seth Aronson

Mark, a twenty-seven-year-old man in the final year of his paediatric residency, sat on my couch recounting his dilemma. We had worked together for several years, a treatment that I felt had helped Mark make headway towards being less self-destructive. Now, Sarah, his girlfriend, was pressuring him to get married. They had first met at a Christian summer camp nine years ago and had stayed together through many permutations of their relationship. He was drawn to her, couldn’t bear to live without her, and yet, frequently, and with great detail, he described how she repulsed him. He fantasized her growing older and consuming more and more food until she grew so obese that he was disgusted by her.

Two days later, he rented a limousine, drove upstate to a romantic spot, got down on one knee and proposed.

The following day, Mark arrived twenty minutes late for session. He came into my office and threw himself on the floor, sobbing convulsively. Although I remained quiet, I privately couldn’t imagine what had happened—had one of his parents died? He had pushed the limits and buttons of his teachers and supervisors so many times—could they finally have thrown him out of his paediatric residency? After a few minutes, Mark got up, mumbled something about being sick and stumbled to the door. As he tried to open it, he vomited all over the threshold.

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Medium 9781449326265

7. Exploring Data with Reports

Russell Jurney O'Reilly Media ePub

In the next step, our third agile sprint, we’ll extend our chart pages into full-blown reports (Figure 7-1). In this step, charts become interactive, static pages become dynamic, and our data becomes explorable through networks of linked, related entities with charts. These are the characteristics of the reports stage of the data-value pyramid.

Code examples for this chapter are available at https://github.com/rjurney/Agile_Data_Code/tree/master/ch07. Clone the repository and follow along!

To build a report, we need to compose multiple views on the same entity. The charts we made in the previous chapter will serve us well as we increase interactivity to create reports. Let’s create an email address entity page and add a tag cloud for related emails to give us something closer to a report.

We’ll start by creating a relation that shows the most related email addresses. Check out ch07/pig/related_email_addresses.pig.

Our Flask controller combines several stubs we’ve already created along with top friends:

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