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NEW QUESTION: 1
Which of the following is not a client side push API?
A. WL.Client.Push.poll()
B. WL.Client.Push.isPushSupported()
C. WL.Client.Push.isSubscribed()
D. WL.Client.Push.unsubscribe()
Answer: A

NEW QUESTION: 2
A forensic analyst is asked to respond to an ongoing network attack on a server. Place the items in the list below in the correct order in which the forensic analyst should preserve them.

Answer:
Explanation:

Explanation

When dealing with multiple issues, address them in order of volatility (OOV); always deal with the most volatile first. Volatility can be thought of as the amount of time that you have to collect certain data before a window of opportunity is gone. Naturally, in an investigation you want to collect everything, but some data will exist longer than others, and you cannot possibly collect all of it once. As an example, the OOV in an investigation may be RAM, hard drive data, CDs/DVDs, and printouts.
Order of volatility: Capture system images as a snapshot of what exists, look at network traffic and logs, capture any relevant video/screenshots/hashes, record time offset on the systems, talk to witnesses, and track total man-hours and expenses associated with the investigation.

NEW QUESTION: 3
While working with the Patch tool, which of the following key combinations is used to add to the existing selection?
A. Alt+drag
B. Alt+Ctrl+drag
C. Shift+drag
D. Alt+Shift+drag
Answer: C
Explanation:
Explanation/Reference:
Shift+ drag key combination is used to add to the existing selection.
Answer options D, C, and B are incorrect. Alt+drag, Alt+Shift+drag, and Alt+Ctrl+drag key combinations are not used to add to the existing selection.
Reference: http://helpx.adobe.com/photoshop/using/retouching-repairing-images.html#patch_an_area

NEW QUESTION: 4
Which of the following is the most important problem to solve for fitting a severity distribution for operational risk capital:
A. Empirical loss data needs to be extended to the ranges below the reporting threshold and above large value losses
B. The fit obtained should reduce the combination of the fitting and approximation errors to a minimum
C. Determine plausible scenarios to fill the data gaps in the internal and external loss data
D. The risk functional's minimization should lead to a good estimate of the 0.999 quantile
Answer: D
Explanation:
Explanation
Ultimately, the objective of the operational risk severity estimation exercise is to calculate the 99.9th percentile loss over a one year horizon; and everything else we do with data, collecting loss information, modeling, curve fitting etc revolves around this objective. If we cannot estimate the 99.9th percentile loss accurately, then not much else matters. Therefore Choice 'a' is the correct answer.
Minimizing the combination of fitting and approximation errors is one of the things we do with a view to better estimating the operational loss distribution. Likewise, empirical loss data generally is range bound because corporations do not require employees to log losses less than an threshold, and high value losses are generally rare. This problem is addressed by extrapolating both large and small losses, something that impacts the performance of our model. Likewise, one of the objectives of scenario analysis is to fill data gaps by generating plausible scenarios. Yet while all these are real issues to address, the primary problem we are trying to solve is estimating the 0.999th quantile.

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