V11-31

Question

Systems employed during surveillance activities might be enhanced using anomaly detection capabilities. Such capabilities can be employed to highlight situations, events, or objects that need an operator's attention, thus reducing their cognitive load and reaction time. Early detection of such situations provides critical time to take appropriate action, possibly before potential problems occur. However, the detection of conflict situations or general anomalous behavior in surveillance data is a complex analytical task that normally cannot be solved using purely visual analysis or purely automatic computational methods. On one hand, purely visual analysis methods for area surveillance often depend on factors such as the amount of sensor data that needs to be monitored, time constraints, and even operators' cognitive load and level of fatigue. On the other hand, current automatic anomaly detection solutions normally present high false alarm rates when dealing with complex situations. These false alarms are predominantly due to the systems being overly sensitive, leading to an overload of irrelevant alerts. Some researchers dispute the use of fully autonomous discovery systems in real-world settings, highlighting the need to include human knowledge in the discovery process. Moreover, operators are explicitly authorized to adjust or deactivate the anomaly detection settings if they deem it necessary to reduce false alarms and maintain operational efficiency. 
 
Most of the published work on anomaly detection focuses on the technological aspects: new methods, combinations of methods, additional improvements of existing methods, reduction of false alarms, correlations among alarms, etc. Publications regarding the use of anomaly detection methods in real environments or human factors studies regarding anomaly detection are scarce. In order to find optimal combinations of human expert knowledge and computational methods for anomaly detection, it is important to investigate how the surveillance of sea areas is carried out. This domain is suitable for studying the optimal combinations of expert knowledge and computational methods since it fulfills the characteristics of many data-intensive domains: large amounts of multivariate data, the need for operator support to solve complex problems, and the need for situation awareness to promote effective decision-making. Knowledge of how the analysis of traffic data is carried out on a daily basis can be used to propose ways to support such processes using data mining and visualization methods.

The primary purpose of the passage is to

A. argue that manual analysis of surveillance data should be prioritized over automatic detection systems. 
B. describe the benefits of integrating automatic surveillance systems with human expertise to enhance effectiveness. 
C. demonstrate that current surveillance systems are flawed and require significant improvements. 
D. propose that sea traffic surveillance requires more research to determine effective methods.
E. outline the pros and cons of visual analysis methods and automatic detection solutions in surveillance systems.

souvik101990 · Answer

Official Solution:

Systems employed during surveillance activities might be enhanced using anomaly detection capabilities. Such capabilities can be employed to highlight situations, events, or objects that need an operator's attention, thus reducing their cognitive load and reaction time. Early detection of such situations provides critical time to take appropriate action, possibly before potential problems occur. However, the detection of conflict situations or general anomalous behavior in surveillance data is a complex analytical task that normally cannot be solved using purely visual analysis or purely automatic computational methods. On one hand, purely visual analysis methods for area surveillance often depend on factors such as the amount of sensor data that needs to be monitored, time constraints, and even operators' cognitive load and level of fatigue. On the other hand, current automatic anomaly detection solutions normally present high false alarm rates when dealing with complex situations. These false alarms are predominantly due to the systems being overly sensitive, leading to an overload of irrelevant alerts. Some researchers dispute the use of fully autonomous discovery systems in real-world settings, highlighting the need to include human knowledge in the discovery process. Moreover, operators are explicitly authorized to adjust or deactivate the anomaly detection settings if they deem it necessary to reduce false alarms and maintain operational efficiency. 
 
Most of the published work on anomaly detection focuses on the technological aspects: new methods, combinations of methods, additional improvements of existing methods, reduction of false alarms, correlations among alarms, etc. Publications regarding the use of anomaly detection methods in real environments or human factors studies regarding anomaly detection are scarce. In order to find optimal combinations of human expert knowledge and computational methods for anomaly detection, it is important to investigate how the surveillance of sea areas is carried out. This domain is suitable for studying the optimal combinations of expert knowledge and computational methods since it fulfills the characteristics of many data-intensive domains: large amounts of multivariate data, the need for operator support to solve complex problems, and the need for situation awareness to promote effective decision-making. Knowledge of how the analysis of traffic data is carried out on a daily basis can be used to propose ways to support such processes using data mining and visualization methods.
 
 The primary purpose of the passage is to

A. argue that manual analysis of surveillance data should be prioritized over automatic detection systems. 
B. describe the benefits of integrating automatic surveillance systems with human expertise to enhance effectiveness. 
C. demonstrate that current surveillance systems are flawed and require significant improvements. 
D. propose that sea traffic surveillance requires more research to determine effective methods.
E. outline the pros and cons of visual analysis methods and automatic detection solutions in surveillance systems.

The primary purpose of the passage is to
 
Incorrect: The passage does not argue for prioritizing manual analysis over automatic detection systems. Instead, it discusses the need for integrating both approaches.
 
Correct: The passage explains how combining human expertise with automatic surveillance systems can address the limitations of each method and improve overall effectiveness.
 
C. Incorrect: While the passage mentions the limitations of current systems, its primary purpose is not to demonstrate their flaws but to discuss the integration of different approaches.
 
D. propose that sea traffic surveillance requires more research to determine effective methods. Incorrect: Although the passage suggests that sea traffic surveillance is a suitable area for research, its primary focus is on the broader integration of human expertise and computational methods.
 
E. Incorrect: The passage does mention some advantages and disadvantages of each method, but its primary purpose is to highlight the benefits of integrating both approaches.

Answer: B

prachi18oct · Answer

How can B be the main point of the passage when the specific sector is not even introduced in passage 1.
Please help

Kritesh · Answer

Could someone explain why B is the correct answer. As per my understanding of the passage i selected option D

harsh2112 · Answer

Even I chose D. Can some expert help with this question  GMATNinja

Prateek176 · Answer

workout

I am a little skeptical about B as the answer choice. Could you please show the POE for this question?

rever08 · Answer

GMATNinja   VeritasKarishma  Could you please help me understand why B is the answer?

2794Aditya · Answer

As most of them chose option "D" over "B", like I did, I am posting this.@

Although the passage states about the beneficial impact in optimizing manual and automatic methods for anomaly detection, the primary purpose of the passage (as I understood) is to  find new methods for optimizing anomaly detection  by combining both manual and automated methods.

I also choose option "D", but a deep reading convinced me that the primary purpose is research. Further, as stated in the official solution, the need for new methods in optimizing the anomaly detection, the scarcity in available publications and areas where this research  (seas)  will yield better insight to optimize and find better methods indicate that the answer is "B".

philipssonicare · Answer

Terribly written

rajatmain · Answer

Yes it is D. D is correct

anniaustin · Answer

I think the answer is B and not D.

Basically the first paragraph is all about anomaly detection capabilities and how it is flawed. The second paragraph suggests that more research needs to be done.

Now let us critique each answer choice.

B. claim that a specific sector in surveillance system can be a feasible area for research.
Yes I do think this is what the intention of the author is, and hence the primary purpose of the passage.

D. explain how automatic surveillance, when integrated with manual detection, would be beneficial.
Although this is intriguing, we should look a bit more closely on the last line of the first paragraph -

So the author is not convinced, that at the stage anomaly detection is right now - it is not fit for purpose - as the number of false alarms can be nuisance to the operators.

Hence, whether the integration of automatic with manual would be beneficial is not so sure with the current state. Therefore, the author suggests more research to be performed before this can be achieved.

If you find this helpful please give kudos! Would really appreciate the gesture.

8Harshitsharma · Answer

I think this is a  poor-quality  question and I don't agree with the explanation. I don't think that choice B is correctly worded. The author's purpose is not just to "claim" that the given field "can" be a feasible area for research.

The author provides so much information on what to research and what to look for in the 2nd para, at this point he is "convincing" the readers about the feasible area of research and promoting that how that will improve the current fully auto systems that are based on purely visual analysis or purely automatic computational methods.

bb · Answer

Thank you for the feedback!
I have revised and improved B and D to reduce the confusion. Now one of them is clearly wrong. 
I have also refreshed the explanation. Please let me know if you feel there is still an issue wiht the question.

As a thank you - I have added 2 weeks to your GMAT Club Test access

8Harshitsharma · Answer

Thank you so much, bb

Happy to help!

karanbhavnani99 · Answer

I think this is a  poor-quality  question and the explanation isn't clear enough, please elaborate.

bb · Answer

Hi. is there anything specific you would like to elaborate? Such as why C wrong or anything else?

ayushman0301 · Answer

Hi can you please elaborate why C is incorrect?

Thanks

bb · Answer

Hi. Sure! The reason for C. being incorrect is that it is too narrow of a scope. 
Does the passage really only say that  current surveillance systems are flawed and require significant improvements?

It goes into several directions and only mentions the current surveillance systems briefly in the middle of the first paragraph.

Here is how the passage starts:

Systems employed during surveillance activities might be enhanced using anomaly detection capabilities. Such capabilities can be employed to highlight situations, events, or objects that need an operator's attention, thus reducing their cognitive load and reaction time.

It does not appear to be focusing on just the current systems but rather improvement opportunities and solutions.

V11-31

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