Keith Oh

The risk of importation of human H5N1 infection from an infected area is determined by a few key decision makers based on their expert knowledge on the disease characteristics and the prevailing global situation. This may not be ideal as it overly relies on the subjective knowledge of the various experts. The risk assessment and horizontal scanning (RAHS) scenario builder seeks to translate this decision-making process into a systematic approach of assessing importation risk by identifying risk… Show more

The risk of importation of human H5N1 infection from an infected area is determined by a few key decision makers based on their expert knowledge on the disease characteristics and the prevailing global situation. This may not be ideal as it overly relies on the subjective knowledge of the various experts. The risk assessment and horizontal scanning (RAHS) scenario builder seeks to translate this decision-making process into a systematic approach of assessing importation risk by identifying risk factors that will have an impact on the importation of human H5N1 infections. Show less

While shared visual space plays a very important role in remote collaboration on physical tasks, it is challenging and expensive to track users' focus of attention (FOA) during these tasks. In this paper, we propose to identify a user's FOA from his/her intention based on task properties, people's actions in the workspace, and conversational content. We employ a conditional Markov model to characterize a subject's FOA. We demonstrate the feasibility of the proposed method using a collaborative… Show more

While shared visual space plays a very important role in remote collaboration on physical tasks, it is challenging and expensive to track users' focus of attention (FOA) during these tasks. In this paper, we propose to identify a user's FOA from his/her intention based on task properties, people's actions in the workspace, and conversational content. We employ a conditional Markov model to characterize a subject's FOA. We demonstrate the feasibility of the proposed method using a collaborative laboratory task in which one partner (the helper) instructs another (the worker) on how to assemble online puzzles. We model a helper's FOA using task properties, workers' actions, and conversational content. The accuracy of the model ranged from 65.40% for puzzles with easy-to-name pieces to 74.25% for puzzles with more difficult-to-name pieces. The proposed model can be used to predicate a user's FOA in a remote collaborative task without tracking the user's eye gaze. Show less

Singapore has developed a prototype Risk Assessment and Horizon Scanning (RAHS) system in collaboration with The Arlington Institute and Cognitive Edge, with the aim to provide analysts with an extensible suite of tools for data exploration and data exploitation based on a service-oriented architecture. The RAHS system facilitates the extraction of open source information into repositories, which are then available to analysts for search and retrieval by means of various tools to augment the… Show more

Singapore has developed a prototype Risk Assessment and Horizon Scanning (RAHS) system in collaboration with The Arlington Institute and Cognitive Edge, with the aim to provide analysts with an extensible suite of tools for data exploration and data exploitation based on a service-oriented architecture. The RAHS system facilitates the extraction of open source information into repositories, which are then available to analysts for search and retrieval by means of various tools to augment the human users' sensemaking process. This paper describes how the RAHS system may be used in the analysis of a massive amount of data, drawing examples from open source material available on the Internet. In addition, this paper also presents a limited experiment in which analysts were presented with the task of exploring a set of documents related to a fictitious terrorist organization in order to identify the roles and responsibilities of the various people linked to the terrorist organization. A simple comparison regarding the workflow, efficiency, and effectiveness of a RAHS analyst is made to that of an analyst equipped with a traditional search engine. Finally, the lessons drawn from this experiment are presented that point to the possible way ahead for future versions of the RAHS system. Show less

Expertise to assist people on complex tasks is often in short supply. One solution to this problem is to design systems that allow remote experts to help multiple people in simultaneously. As a first step towards building such a system, we studied experts' attention and communication as they assisted two novices at the same time in a co-located setting. We compared simultaneous instruction when the novices are being instructed to do the same task or different tasks. Using machine learning, we… Show more

Expertise to assist people on complex tasks is often in short supply. One solution to this problem is to design systems that allow remote experts to help multiple people in simultaneously. As a first step towards building such a system, we studied experts' attention and communication as they assisted two novices at the same time in a co-located setting. We compared simultaneous instruction when the novices are being instructed to do the same task or different tasks. Using machine learning, we attempted to identify speech markers of upcoming attention shifts that could serve as input to a remote assistance system. Show less

We propose a method of measuring people's sense of presence in computer-mediated communication (CMC) systems) based on linguistic features of their dialogues. We create variations in presence by asking participants to collaborate on physical tasks in four CMC conditions. We then correlate self-reported feelings of presence with the use of specific linguistic features. Regression analyses show that 30% of the variance in self-reported presence can be accounted for by a small number of… Show more

We propose a method of measuring people's sense of presence in computer-mediated communication (CMC) systems) based on linguistic features of their dialogues. We create variations in presence by asking participants to collaborate on physical tasks in four CMC conditions. We then correlate self-reported feelings of presence with the use of specific linguistic features. Regression analyses show that 30% of the variance in self-reported presence can be accounted for by a small number of task-independent linguistic features. Even better prediction can be obtained when self-reported coordination is added to the regression equation. We conclude that linguistic measures of presence have value for studies of CMC. Show less

To overcome the limitations of current technologies for remote collaboration, we propose a system that changes a video feed based on task properties, people's actions, and message properties. First, we examined how participants manage different visual resources in a laboratory experiment using a collaborative task in which one partner (the helper) instructs another (the worker) how to assemble online puzzles. We analyzed helpers' eye gaze as a function of the aforementioned parameters. Helpers… Show more

To overcome the limitations of current technologies for remote collaboration, we propose a system that changes a video feed based on task properties, people's actions, and message properties. First, we examined how participants manage different visual resources in a laboratory experiment using a collaborative task in which one partner (the helper) instructs another (the worker) how to assemble online puzzles. We analyzed helpers' eye gaze as a function of the aforementioned parameters. Helpers gazed at the set of alternative pieces more frequently when it was harder for workers to differentiate these pieces, and less frequently over repeated trials. The results further suggest that a helper's desired focus of attention can be predicted based on task properties, his/her partner's actions, and message properties. We propose a conditional Markov model classifier to explore the feasibility of predicting gaze based on these properties. The accuracy of the model ranged from 65.40% for puzzles with easy-to-name pieces to 74.25% for puzzles with more difficult to name pieces. The results suggest that we can use our model to automatically manipulate video feeds to show what helpers want to see when they want to see it. Show less

Helpers providing guidance for collaborative physical tasks shift their gaze between the workspace, supply area, and instructions. Understanding when and why helpers gaze at each area is important both for a theoretical understanding of collaboration on physical tasks and for the design of automated video systems for remote collaboration. In a laboratory experiment using a collaborative puzzle task, we recorded helpers' gaze while manipulating task complexity and piece differentiability… Show more

Helpers providing guidance for collaborative physical tasks shift their gaze between the workspace, supply area, and instructions. Understanding when and why helpers gaze at each area is important both for a theoretical understanding of collaboration on physical tasks and for the design of automated video systems for remote collaboration. In a laboratory experiment using a collaborative puzzle task, we recorded helpers' gaze while manipulating task complexity and piece differentiability. Helpers gazed toward the pieces bay more frequently when pieces were difficult to differentiate and less frequently over repeated trials. Preliminary analyses of message content show that helpers tend to look at the pieces bay when describing the next piece and at the workspace when describing where it goes. The results are consistent with a grounding model of communication, in which helpers seek visual evidence of understanding unless they are confident that they have been understood. The results also suggest the feasibility of building automated video systems based on remote helpers' shifting visual requirements. Show less

We describe our process, findings, and resulting solution for the CHI2005 Student Competition. The design problem was the issue of well-being of persons above the age of 65 years. Loss of a companion can be a primary cause of depression, and decline of social well-being and health for the elderly, so the challenge is to design for "artificial" companionship to support the elderly. We met this challenge by employing extensive research in geriatric psychology, empirical and analytical… Show more

We describe our process, findings, and resulting solution for the CHI2005 Student Competition. The design problem was the issue of well-being of persons above the age of 65 years. Loss of a companion can be a primary cause of depression, and decline of social well-being and health for the elderly, so the challenge is to design for "artificial" companionship to support the elderly. We met this challenge by employing extensive research in geriatric psychology, empirical and analytical human-computer interaction methods, interaction design techniques, and technologies currently available or in development. Our solution is a wearable and stationary device that will allow the user to 1) record events through pictures and audio for sharing, 2) gather artifacts of their past such as photographs into a multimedia slideshow format for sharing with others, and 3) allow friends and family to be aware of the user's location for safety purposes. Show less