Pub Date : 2015-05-18DOI: 10.1109/COGSIMA.2015.7108184
K. E. Schafer, T. Sanders, T. Kessler, Mitchell S. Dunfee, T. Wild, P. Hancock
This work assesses the relationship between common theoretical constructs involved in simulation design and evaluation. Specifically, the degree to which realism is a desired goal in design is examined through a thorough review of the available literature. It was found that, especially for training simulations, high fidelity does not always beget improved outcomes, and this finding was corroborated by the results of an experiment involving a simulated robot. In the within-subjects experiment, participants rated their trust in both live and simulated versions of a robot performing in both reliable and unreliable scenarios. As predicted, strong correlations in both the reliable and unreliable scenarios validate the RIVET simulation engine as a model for trust in HRI and provide further evidence that relatively low-fidelity simulations can sometimes be sufficient or superior to high-fidelity alternatives.
{"title":"Fidelity & validity in robotic simulation","authors":"K. E. Schafer, T. Sanders, T. Kessler, Mitchell S. Dunfee, T. Wild, P. Hancock","doi":"10.1109/COGSIMA.2015.7108184","DOIUrl":"https://doi.org/10.1109/COGSIMA.2015.7108184","url":null,"abstract":"This work assesses the relationship between common theoretical constructs involved in simulation design and evaluation. Specifically, the degree to which realism is a desired goal in design is examined through a thorough review of the available literature. It was found that, especially for training simulations, high fidelity does not always beget improved outcomes, and this finding was corroborated by the results of an experiment involving a simulated robot. In the within-subjects experiment, participants rated their trust in both live and simulated versions of a robot performing in both reliable and unreliable scenarios. As predicted, strong correlations in both the reliable and unreliable scenarios validate the RIVET simulation engine as a model for trust in HRI and provide further evidence that relatively low-fidelity simulations can sometimes be sufficient or superior to high-fidelity alternatives.","PeriodicalId":373467,"journal":{"name":"2015 IEEE International Multi-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128851019","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-05-18DOI: 10.1109/COGSIMA.2015.7108177
Christian Jung, Denis Feth, Yehia Elrakaiby
Context-awareness in mobile information systems bears a huge potential. However, context-awareness is still in its infancy and its full potential is not yet exploited. One reason is the poorly supported creation and learning of suitable context descriptions. Another problem is the questionable predictive power of context descriptions that makes it difficult to correctly determine the current user context. For applications that depend on the user context, the reliable determination of the context is essential. In this paper, we propose a process to characterize contexts. We correlate raw contextual information with user activities to determine accurate context descriptions. In a case study, we show how different statistical methods can be used to determine correlations, and analyze their applicability.
{"title":"Automatic derivation of context descriptions","authors":"Christian Jung, Denis Feth, Yehia Elrakaiby","doi":"10.1109/COGSIMA.2015.7108177","DOIUrl":"https://doi.org/10.1109/COGSIMA.2015.7108177","url":null,"abstract":"Context-awareness in mobile information systems bears a huge potential. However, context-awareness is still in its infancy and its full potential is not yet exploited. One reason is the poorly supported creation and learning of suitable context descriptions. Another problem is the questionable predictive power of context descriptions that makes it difficult to correctly determine the current user context. For applications that depend on the user context, the reliable determination of the context is essential. In this paper, we propose a process to characterize contexts. We correlate raw contextual information with user activities to determine accurate context descriptions. In a case study, we show how different statistical methods can be used to determine correlations, and analyze their applicability.","PeriodicalId":373467,"journal":{"name":"2015 IEEE International Multi-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124268518","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-03-09DOI: 10.1109/COGSIMA.2015.7108201
Jennifer Danczyk, Paula Jacobs, Stephanie Kane, Michael Farry, W. Thornton
There are many task-related factors that drive the complexity and diversity of submarine operations during a mission, including knowing the correct time to make periscope observations, estimating the correct sea state, and being aware of the proximity of contacts. In addition, there are unpredictable events and circumstances, including equipment failures, environmental factors, and adversary actions, that affect the operation's success or failure. After operations are complete, commanders are tasked with recounting and reporting events of interest. Commanders are asked to recall details of critical incidents, when their perceptual and cognitive resources are likely to be over-tasked, resulting in less accurate recall. In most operations, there is little objective data collection to back up those recollections, especially for critical incidents that had the potential to cause catastrophes but did not. However, instances where catastrophes are narrowly avoided offer valuable teaching moments for crewmembers. Collecting and visualizing objective performance data within a mission reconstruction tool can help commanders account for actual actions and decisions for the purpose of reporting, and also enables resilient planning and optimal execution of future tasks, because commanders are able to analyze alternative courses of action (COAs) and their trade-offs. Most importantly, having a more comprehensive analysis tool can enable more accurate and thorough training, thus improving the mission performance and operational safety of future submarine operations and performance.
{"title":"Combining human knowledge and operational data to promote detailed and effective reporting","authors":"Jennifer Danczyk, Paula Jacobs, Stephanie Kane, Michael Farry, W. Thornton","doi":"10.1109/COGSIMA.2015.7108201","DOIUrl":"https://doi.org/10.1109/COGSIMA.2015.7108201","url":null,"abstract":"There are many task-related factors that drive the complexity and diversity of submarine operations during a mission, including knowing the correct time to make periscope observations, estimating the correct sea state, and being aware of the proximity of contacts. In addition, there are unpredictable events and circumstances, including equipment failures, environmental factors, and adversary actions, that affect the operation's success or failure. After operations are complete, commanders are tasked with recounting and reporting events of interest. Commanders are asked to recall details of critical incidents, when their perceptual and cognitive resources are likely to be over-tasked, resulting in less accurate recall. In most operations, there is little objective data collection to back up those recollections, especially for critical incidents that had the potential to cause catastrophes but did not. However, instances where catastrophes are narrowly avoided offer valuable teaching moments for crewmembers. Collecting and visualizing objective performance data within a mission reconstruction tool can help commanders account for actual actions and decisions for the purpose of reporting, and also enables resilient planning and optimal execution of future tasks, because commanders are able to analyze alternative courses of action (COAs) and their trade-offs. Most importantly, having a more comprehensive analysis tool can enable more accurate and thorough training, thus improving the mission performance and operational safety of future submarine operations and performance.","PeriodicalId":373467,"journal":{"name":"2015 IEEE International Multi-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125199861","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-03-09DOI: 10.1109/COGSIMA.2015.7107972
Benjamin Fonooni, T. Hellström
In many robotics shared control applications, users are forced to focus hard on the robot due to the task's high sensitivity or the robot's misunderstanding of the user's intention. This brings frustration and dissatisfaction to the user and reduces overall efficiency. The user's intention is sometimes unclear and hard to identify without some kind of bias in the identification process. In this paper, we present a solution in which an attentional mechanism helps the robot to recognize the user's intention. The solution uses a priming mechanism and parameterized behavior primitives to support intention recognition and improve shared control for teleoperation tasks.
{"title":"Applying a priming mechanism for intention recognition in shared control","authors":"Benjamin Fonooni, T. Hellström","doi":"10.1109/COGSIMA.2015.7107972","DOIUrl":"https://doi.org/10.1109/COGSIMA.2015.7107972","url":null,"abstract":"In many robotics shared control applications, users are forced to focus hard on the robot due to the task's high sensitivity or the robot's misunderstanding of the user's intention. This brings frustration and dissatisfaction to the user and reduces overall efficiency. The user's intention is sometimes unclear and hard to identify without some kind of bias in the identification process. In this paper, we present a solution in which an attentional mechanism helps the robot to recognize the user's intention. The solution uses a priming mechanism and parameterized behavior primitives to support intention recognition and improve shared control for teleoperation tasks.","PeriodicalId":373467,"journal":{"name":"2015 IEEE International Multi-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126997103","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-03-09DOI: 10.1109/COGSIMA.2015.7108175
S. Lackey, Brandon Sollins, L. Reinerman-Jones
Adaptive automation (AA) has emerged as a viable solution to improving human performance in complex environments. However, understanding when to prompt, pause, and terminate AA remains unclear. Augmenting the user with physiological sensors offers new insight into the user's state, and thus, offers insight into when and how to implement AA. The research presented investigates the efficacy of prediction algorithms for modeling physiological and subjective data in AA environments. A comparison of traditional and emerging modeling methods results in recommendations for algorithm selection, generalizability, and risks of over fitting data are provided.
{"title":"Comparing models for modeling subjective and objective measures for two task types","authors":"S. Lackey, Brandon Sollins, L. Reinerman-Jones","doi":"10.1109/COGSIMA.2015.7108175","DOIUrl":"https://doi.org/10.1109/COGSIMA.2015.7108175","url":null,"abstract":"Adaptive automation (AA) has emerged as a viable solution to improving human performance in complex environments. However, understanding when to prompt, pause, and terminate AA remains unclear. Augmenting the user with physiological sensors offers new insight into the user's state, and thus, offers insight into when and how to implement AA. The research presented investigates the efficacy of prediction algorithms for modeling physiological and subjective data in AA environments. A comparison of traditional and emerging modeling methods results in recommendations for algorithm selection, generalizability, and risks of over fitting data are provided.","PeriodicalId":373467,"journal":{"name":"2015 IEEE International Multi-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126682472","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-03-09DOI: 10.1109/COGSIMA.2015.7108180
J. V. D. Meulen, J. R. Smith
The primary aim of the study was to evaluate the potential of information technologies, specifically 2-dimensional (2D) and 3-dimensional (3D) perspective view displays, on situation awareness (SA) in a command and control environment. Furthermore, the influence of experience on SA while using the displays was investigated. SA of 10 air mission controllers (AMCs) was evaluated while using both displays during a simulated interception scenario. The protocol required each AMC to command two fighter jets in order to complete a successful intercept. The SA requirements for the scenario were extracted using a goal directed task analysis whereby the SA queries were derived. Significant differences (p <; 0.05) were found between the 2D and 3D displays for Level 1 SA while no significant differences were found for Level 2 and Level 3. The experienced AMCs demonstrated higher levels of SA at all 3 levels irrespective of display type but the differences were not significant. It is therefore deemed that experience does not play a major role in gaining SA when using the 3D display. This was expected because neither group had any prior experience with the 3D display. Level 1 SA was significantly higher for both the experienced and less experienced groups when using the 2D display. Level 1 was also significantly higher than Level 3 for both the experienced and less experienced groups when using the 3D display. The implication of these results are that although the AMCs were able to comprehend the mission, they were unable to perceive and project accurately what was going to happen next in the scenario when using the 3D display. Therefore the 3D display did not contribute towards improved SA or provide an advantage to command and control performance above that of the 2D display.
{"title":"The effect of 2-dimensional and 3-dimensional perspective view displays on situation awareness during command and control","authors":"J. V. D. Meulen, J. R. Smith","doi":"10.1109/COGSIMA.2015.7108180","DOIUrl":"https://doi.org/10.1109/COGSIMA.2015.7108180","url":null,"abstract":"The primary aim of the study was to evaluate the potential of information technologies, specifically 2-dimensional (2D) and 3-dimensional (3D) perspective view displays, on situation awareness (SA) in a command and control environment. Furthermore, the influence of experience on SA while using the displays was investigated. SA of 10 air mission controllers (AMCs) was evaluated while using both displays during a simulated interception scenario. The protocol required each AMC to command two fighter jets in order to complete a successful intercept. The SA requirements for the scenario were extracted using a goal directed task analysis whereby the SA queries were derived. Significant differences (p <; 0.05) were found between the 2D and 3D displays for Level 1 SA while no significant differences were found for Level 2 and Level 3. The experienced AMCs demonstrated higher levels of SA at all 3 levels irrespective of display type but the differences were not significant. It is therefore deemed that experience does not play a major role in gaining SA when using the 3D display. This was expected because neither group had any prior experience with the 3D display. Level 1 SA was significantly higher for both the experienced and less experienced groups when using the 2D display. Level 1 was also significantly higher than Level 3 for both the experienced and less experienced groups when using the 3D display. The implication of these results are that although the AMCs were able to comprehend the mission, they were unable to perceive and project accurately what was going to happen next in the scenario when using the 3D display. Therefore the 3D display did not contribute towards improved SA or provide an advantage to command and control performance above that of the 2D display.","PeriodicalId":373467,"journal":{"name":"2015 IEEE International Multi-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision","volume":"2009 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125637405","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-03-09DOI: 10.1109/COGSIMA.2015.7107967
D. K. B. Ismail, Olivier Grivard
The measurement, or at least the estimation, of the operators' workload is an important aspect of usage-oriented design of professional systems. Various approaches to the a priori measurement of workload have been proposed. They can be classified into three categories: performance measures, physiological measures and subjective measures. Subjective methods have many advantages such as high `face validity', ease of application and low cost. However, they have failed to take into account some important parameters that can heavily impact the workload estimation: experience, skills, level of training, etc. This paper addresses a new method for the estimation of workload, based on the following parameters: task complexity, time load, experience, knowledge and abilities compared to task requirements. Although these parameters have been identified in the literature as being important, they have not been deeply analyzed. The authors describe their approach and propose to use mental representations of human entities, human roles, tasks, knowledge and abilities. The approach is illustrated on an airborne maritime surveillance usecase, in the context of the French Medusa project.
{"title":"A model-driven approach to the a priori estimation of operator workload","authors":"D. K. B. Ismail, Olivier Grivard","doi":"10.1109/COGSIMA.2015.7107967","DOIUrl":"https://doi.org/10.1109/COGSIMA.2015.7107967","url":null,"abstract":"The measurement, or at least the estimation, of the operators' workload is an important aspect of usage-oriented design of professional systems. Various approaches to the a priori measurement of workload have been proposed. They can be classified into three categories: performance measures, physiological measures and subjective measures. Subjective methods have many advantages such as high `face validity', ease of application and low cost. However, they have failed to take into account some important parameters that can heavily impact the workload estimation: experience, skills, level of training, etc. This paper addresses a new method for the estimation of workload, based on the following parameters: task complexity, time load, experience, knowledge and abilities compared to task requirements. Although these parameters have been identified in the literature as being important, they have not been deeply analyzed. The authors describe their approach and propose to use mental representations of human entities, human roles, tasks, knowledge and abilities. The approach is illustrated on an airborne maritime surveillance usecase, in the context of the French Medusa project.","PeriodicalId":373467,"journal":{"name":"2015 IEEE International Multi-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision","volume":"328 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115385893","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-03-09DOI: 10.1109/COGSIMA.2015.7108179
Arthur Wollocko, Michael Farry, Martin Voshell, Michael P. Jenkins, Michael Pellicano
This paper describes how a Cognitive Systems Engineering approach was used to design a collaborative work system for the emerging distributed Processing, Exploitation, and Dissemination (PED) enterprise. Working closely with domain practitioners and based on previously identified capability gaps, we designed a prototype system to address key cognitive and collaborative functions not supported in existing chat tools in use by the community. We then extended standard chat functionality with an Asynchronous, Multi-dimensional Chat Client to develop a set of interactive design seeds. The initial design seeds were based on providing: (1) real-time, on-topic contextual cues about collaborators' activities with regard to a shared intelligence picture; (2) automated information gathering assistance; and (3) enhanced functionality using easily developed, modular, external software extensions. Initial results based on feedback from operators are then discussed to shape future design iterations. We conclude that future PED tools based on these enhanced functionalities have significant potential to help personnel easily and effectively access, manage, and monitor multiple shared frames of reference with their analytical, consumer, and collector counterparts, establishing a common ground that is critical for emerging distributed intelligence, surveillance, and reconnaissance (ISR) workflows.
{"title":"Supporting common ground across multiple operator perspectives - Creating collaborative solutions for distributed processing, exploitation, and dissemination (PED)","authors":"Arthur Wollocko, Michael Farry, Martin Voshell, Michael P. Jenkins, Michael Pellicano","doi":"10.1109/COGSIMA.2015.7108179","DOIUrl":"https://doi.org/10.1109/COGSIMA.2015.7108179","url":null,"abstract":"This paper describes how a Cognitive Systems Engineering approach was used to design a collaborative work system for the emerging distributed Processing, Exploitation, and Dissemination (PED) enterprise. Working closely with domain practitioners and based on previously identified capability gaps, we designed a prototype system to address key cognitive and collaborative functions not supported in existing chat tools in use by the community. We then extended standard chat functionality with an Asynchronous, Multi-dimensional Chat Client to develop a set of interactive design seeds. The initial design seeds were based on providing: (1) real-time, on-topic contextual cues about collaborators' activities with regard to a shared intelligence picture; (2) automated information gathering assistance; and (3) enhanced functionality using easily developed, modular, external software extensions. Initial results based on feedback from operators are then discussed to shape future design iterations. We conclude that future PED tools based on these enhanced functionalities have significant potential to help personnel easily and effectively access, manage, and monitor multiple shared frames of reference with their analytical, consumer, and collector counterparts, establishing a common ground that is critical for emerging distributed intelligence, surveillance, and reconnaissance (ISR) workflows.","PeriodicalId":373467,"journal":{"name":"2015 IEEE International Multi-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision","volume":"40 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132884410","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-03-09DOI: 10.1109/COGSIMA.2015.7108193
Chen Zhong, J. Yen, Peng Liu, R. Erbacher, Renee Etoty, C. Garneau
Efficiency and interference shielding are critical factors for conducting successful cognitive task analysis (CTA) of cyber-attack analysis. To achieve this goal, a tool, named ARSCA, is developed to work with an analyst during a cyber-attack analysis task and to capture the main elements in his/her cognitive process. ARSCA conducts process tracing in a way that reduces the study time and the workload needed for analysts and does not distract the analysts from executing their tasks. ARSCA has been tested in an experiment with a simulated cyber-attack analysis task. Thirteen professional analysts and seventeen doctoral students specializing in cyber security are recruited. We evaluate the captured traces and the participants' feedbacks on working with ARSCA.
{"title":"ARSCA: a computer tool for tracing the cognitive processes of cyber-attack analysis","authors":"Chen Zhong, J. Yen, Peng Liu, R. Erbacher, Renee Etoty, C. Garneau","doi":"10.1109/COGSIMA.2015.7108193","DOIUrl":"https://doi.org/10.1109/COGSIMA.2015.7108193","url":null,"abstract":"Efficiency and interference shielding are critical factors for conducting successful cognitive task analysis (CTA) of cyber-attack analysis. To achieve this goal, a tool, named ARSCA, is developed to work with an analyst during a cyber-attack analysis task and to capture the main elements in his/her cognitive process. ARSCA conducts process tracing in a way that reduces the study time and the workload needed for analysts and does not distract the analysts from executing their tasks. ARSCA has been tested in an experiment with a simulated cyber-attack analysis task. Thirteen professional analysts and seventeen doctoral students specializing in cyber security are recruited. We evaluate the captured traces and the participants' feedbacks on working with ARSCA.","PeriodicalId":373467,"journal":{"name":"2015 IEEE International Multi-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126608414","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-03-09DOI: 10.1109/COGSIMA.2015.7108191
R. Falcon, R. Abielmona, Sean Billings
Decision support systems (DSSs) are playing an increasingly important role in the characterization of suspicious activities in an area of interest given their proved ability to turn vast amounts of raw data into actionable intelligence that is easy to understand by human operators. Although risk management is an integral component of the decision making process that directly contributes towards improved situational awareness and response assessment, an active end-to-end consideration of the underlying risk sources in the environment is still an important feature that most DSSs currently lack. Additionally, deciding on an appropriate course of action (COA) to mitigate emerging threats in the system is a challenging task even for domain experts given that (1) the number of potential responses to analyze could be overwhelmingly large; (2) seldom are those responses judged in terms of the risks associated with their enactment and (3) assessing the effectiveness of the potential responses in the real world is usually time-consuming and simulation-driven. In this paper, we formalize the adaptation of a recently proposed Risk Management Framework to account for behavioral intents associated with the objects of interest (OOIs) in the monitoring environment and their link to automatic response generation. The intent of the objects is inferred from high-level cognitive and behavioral knowledge in the form of anomalies. When an OOI has crossed a permissible risk threshold, we demonstrate how responses to that situation can be automatically elicited by the COA recommendation module of a risk-aware DSS. Multicriteria decision analysis (MCDA) is used to judge a diverse set of plausible responses according to different operational objectives. We illustrate the application of the proposed framework in the context of maritime surveillance operations by triggering a corporate search for a missing vessel. To the best of our knowledge, this is the first time that risk features are synthesized from anomalies and integrated into a more comprehensive RMF engine for knowledge (response) elicitation.
{"title":"Risk-driven intent assessment and response generation in maritime surveillance operations","authors":"R. Falcon, R. Abielmona, Sean Billings","doi":"10.1109/COGSIMA.2015.7108191","DOIUrl":"https://doi.org/10.1109/COGSIMA.2015.7108191","url":null,"abstract":"Decision support systems (DSSs) are playing an increasingly important role in the characterization of suspicious activities in an area of interest given their proved ability to turn vast amounts of raw data into actionable intelligence that is easy to understand by human operators. Although risk management is an integral component of the decision making process that directly contributes towards improved situational awareness and response assessment, an active end-to-end consideration of the underlying risk sources in the environment is still an important feature that most DSSs currently lack. Additionally, deciding on an appropriate course of action (COA) to mitigate emerging threats in the system is a challenging task even for domain experts given that (1) the number of potential responses to analyze could be overwhelmingly large; (2) seldom are those responses judged in terms of the risks associated with their enactment and (3) assessing the effectiveness of the potential responses in the real world is usually time-consuming and simulation-driven. In this paper, we formalize the adaptation of a recently proposed Risk Management Framework to account for behavioral intents associated with the objects of interest (OOIs) in the monitoring environment and their link to automatic response generation. The intent of the objects is inferred from high-level cognitive and behavioral knowledge in the form of anomalies. When an OOI has crossed a permissible risk threshold, we demonstrate how responses to that situation can be automatically elicited by the COA recommendation module of a risk-aware DSS. Multicriteria decision analysis (MCDA) is used to judge a diverse set of plausible responses according to different operational objectives. We illustrate the application of the proposed framework in the context of maritime surveillance operations by triggering a corporate search for a missing vessel. To the best of our knowledge, this is the first time that risk features are synthesized from anomalies and integrated into a more comprehensive RMF engine for knowledge (response) elicitation.","PeriodicalId":373467,"journal":{"name":"2015 IEEE International Multi-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125233496","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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