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souvik101990
Expert
Alum
Joined: 19 Mar 2012
Last visit: 15 Aug 2026
Posts: 4,309
Given Kudos: 2,326
Location: United States (WA)
Concentration: Leadership, General Management
Schools: Ross '20 (M)
GMAT 1: 760 Q50 V42
GMAT 2: 740 Q49 V42 (Online)
GMAT 3: 760 Q50 V42 (Online)
GPA: 3.8
WE:Marketing (Non-Profit and Government)
Products:
Expert reply
04 Jan 2016, 11:47
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Bookmarks
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 the one hand, the success of purely visual analysis methods for area surveillance often depends 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. The high number of false alarms can become a nuisance for operators, who might react by turning anomaly detection capabilities off. 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.
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 passage implies which of the following?
A. The main drawback of autonomous anomaly discovery systems is that they can never achieve zero false alarm rates.
B. Further research in sea traffic movement will definitively determine the best possible combination of human expert knowledge and computational methods.
C. Research in surveillance systems has not been properly carried out because of the difficulty of analyzing the huge amount of data associated with the domain.
D. Some researchers believe that fully automatic surveillance methods cannot practically eliminate the requirement of human intervention.
E. No research work has been done on the non-technological aspect of the anomaly detection system.
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 passage implies which of the following?
A. The main drawback of autonomous anomaly discovery systems is that they can never achieve zero false alarm rates.
B. Further research in sea traffic movement will definitively determine the best possible combination of human expert knowledge and computational methods.
C. Research in surveillance systems has not been properly carried out because of the difficulty of analyzing the huge amount of data associated with the domain.
D. Some researchers believe that fully automatic surveillance methods cannot practically eliminate the requirement of human intervention.
E. No research work has been done on the non-technological aspect of the anomaly detection system.
souvik101990
Expert
Alum
Joined: 19 Mar 2012
Last visit: 15 Aug 2026
Posts: 4,309
Given Kudos: 2,326
Location: United States (WA)
Concentration: Leadership, General Management
Schools: Ross '20 (M)
GMAT 1: 760 Q50 V42
GMAT 2: 740 Q49 V42 (Online)
GMAT 3: 760 Q50 V42 (Online)
GPA: 3.8
WE:Marketing (Non-Profit and Government)
Products:
Expert reply
04 Jan 2016, 11:48
Kudos
Bookmarks
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 the one hand, the success of purely visual analysis methods for area surveillance often depends 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. The high number of false alarms can become a nuisance for operators, who might react by turning anomaly detection capabilities off. 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.
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 passage implies which of the following?
A. The main drawback of autonomous anomaly discovery systems is that they can never achieve zero false alarm rates.
B. Further research in sea traffic movement will definitively determine the best possible combination of human expert knowledge and computational methods.
C. Research in surveillance systems has not been properly carried out because of the difficulty of analyzing the huge amount of data associated with the domain.
D. Some researchers believe that fully automatic surveillance methods cannot practically eliminate the requirement of human intervention.
E. No research work has been done on the non-technological aspect of the anomaly detection system.
A. Incorrect: The passage mentions that current automatic anomaly detection solutions present high false alarm rates but does not imply that achieving zero false alarm rates is impossible.
B. Incorrect: The passage suggests investigating sea traffic movement for finding optimal combinations of expert knowledge and computational methods but does not definitively imply that further research will conclusively determine the best possible combination.
C. Incorrect: The passage highlights the scarcity of research on non-technological aspects and the complexity of analyzing data but does not imply that research has not been properly carried out due to data analysis difficulties.
D.Correct: The passage indicates that some researchers dispute the use of fully autonomous discovery systems, emphasizing the need for human knowledge, which implies that not all researchers agree that fully automatic methods can eliminate the need for human intervention.
E. Incorrect: The passage states that publications on the non-technological aspects are scarce, not nonexistent. Therefore, it cannot be inferred that no research has been done at all.
Answer: D
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 the one hand, the success of purely visual analysis methods for area surveillance often depends 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. The high number of false alarms can become a nuisance for operators, who might react by turning anomaly detection capabilities off. 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.
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 passage implies which of the following?
A. The main drawback of autonomous anomaly discovery systems is that they can never achieve zero false alarm rates.
B. Further research in sea traffic movement will definitively determine the best possible combination of human expert knowledge and computational methods.
C. Research in surveillance systems has not been properly carried out because of the difficulty of analyzing the huge amount of data associated with the domain.
D. Some researchers believe that fully automatic surveillance methods cannot practically eliminate the requirement of human intervention.
E. No research work has been done on the non-technological aspect of the anomaly detection system.
A. Incorrect: The passage mentions that current automatic anomaly detection solutions present high false alarm rates but does not imply that achieving zero false alarm rates is impossible.
B. Incorrect: The passage suggests investigating sea traffic movement for finding optimal combinations of expert knowledge and computational methods but does not definitively imply that further research will conclusively determine the best possible combination.
C. Incorrect: The passage highlights the scarcity of research on non-technological aspects and the complexity of analyzing data but does not imply that research has not been properly carried out due to data analysis difficulties.
D.Correct: The passage indicates that some researchers dispute the use of fully autonomous discovery systems, emphasizing the need for human knowledge, which implies that not all researchers agree that fully automatic methods can eliminate the need for human intervention.
E. Incorrect: The passage states that publications on the non-technological aspects are scarce, not nonexistent. Therefore, it cannot be inferred that no research has been done at all.
Answer: D
16 Nov 2022, 01:26
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Bunuel sayantanc2k KarishmaB chetan2u GMATNinja AndrewN
B vs D-
Option B uses the word "can", which means there is a possibility and not certainty. If "will" were used instead of "can", then we could have eliminated option B.
By choosing D as the right answer, we are assuming that not dispute=not disagree. But it may be possible that other researchers who did not dispute may still disagree/agree. Hence, D won't be MUST BE TRUE.
I think answer should be B basis the above rationale.
bb
Many people have posted their queries wrt this question, however, it seems no expert is bothered to reply on their own GMAT Club Tests developed in-house. This may have a negative feedback for these tests, affecting their marketability.
B vs D-
Option B uses the word "can", which means there is a possibility and not certainty. If "will" were used instead of "can", then we could have eliminated option B.
By choosing D as the right answer, we are assuming that not dispute=not disagree. But it may be possible that other researchers who did not dispute may still disagree/agree. Hence, D won't be MUST BE TRUE.
I think answer should be B basis the above rationale.
bb
Many people have posted their queries wrt this question, however, it seems no expert is bothered to reply on their own GMAT Club Tests developed in-house. This may have a negative feedback for these tests, affecting their marketability.
