Hidden Markov model analysis reveals better eye movement strategies in face recognition

Conference Theme: Mind, Technology, and SocietyHere we explored eye movement strategies that lead to better performance in face recognition with hidden Markov models (HMMs). Participants performed a standard face recognition memory task with eye movements recorded. The durations and locations of the fixations were analyzed using HMMs for both the study and the test phases. Results showed that in the study phase, the participants who looked more often at the eyes and shifted between different regions on the face with long fixation durations had better performances. The test phase analyses revealed that an efficient, short first orienting fixation followed by a more analytic pattern focusing mainly on the eyes led to better performances. These strategies could not be revealed by analysis methods that do not take individual differences in both temporal and spatial dimensions of eye movements into account, demonstrating the power of the HMM approach.postprin

Controlling Restricted Random Testing: An Examination of the Exclusion Ratio Parameter

In Restricted Random Testing (RRT), the main control parameter is the Target Exclusion Ratio (R), the proportion of the input domain to be excluded from test case generation at each iteration. Empirical investigations have consistently indicated that best failure-finding performance is achieved when the value for the Target Exclusion Ratio is maximised, i.e. close to 100%. This paper explains an algorithm to calculate the Actual Exclusion Ratio for RRT, and applies the algorithm to several simulations, confirming that previous empirically determined values for the Maximum Target Exclusion Ratio do give Actual Exclusion Ratios close to 100%. Previously observed trends of improvement in failure-finding efficiency of RRT corresponding to increases in Target Exclusion Ratios are also identified for Actual Exclusion Ratios.published_or_final_versio

Insider trading and family firms

We find that CEOs of S&P 1500 family firms, founding CEOs in particular, are more active stock traders than are the CEOs of non-family firms. Importantly, the stock trades made by founding CEOs (and, to a lesser extent, those made by founders’ descendants) are more profitable than those made by the CEOs of non-family firms. This finding is more pronounced for family firms that are difficult to value or that have poor corporate governance. Founding CEOs’ excess stock trading returns arise both from trades made before earnings surprises and those made outside earnings announcement periods. Finally, founding CEOs’ trades forecast their company’s future stock returns better than those made by the CEOs of non-family firms.postprintThe 37th Annual Meeting of the European Finance Association (EFA), Frankfurt, Germany, 25-28 August 2010

Test case selection with and without replacement

Previous theoretical studies on the effectiveness of partition testing and random testing have assumed that test cases are selected with replacement. Although this assumption has been well known to be less realistic, it has still been used in previous theoretical work because it renders the analyses more tractable. This paper presents a theoretical investigation aimed at comparing the effectiveness when test cases are selected with and without replacement, and exploring the relationships between these two scenarios. We propose a new effectiveness metric for software testing, namely the expected number of distinct failures detected, to re-examine existing partition testing strategies.postprin

Radiologist variability in assessing the position of the cavoatrial junction on chest radiographs

Objectives: To assess the variability in identifying the cavo-atrial junction (CAJ) on chest x-rays amongst radiologists. Methods: Twenty-three radiologists (13 consultants and 10 trainees) assessed 25 postero-anterior erect chest x-rays (including eight duplicates) and marked the positions of the CAJ. Differences in the CAJ position both within and between observers were evaluated and reported as limits of agreement, repeatability coefficients, intra-class correlation coefficients and displayed graphically with Bland- Altman plots. Results: The mean difference for within observer assessments was -0.2 cm (95% limits of agreement, -1.5 to +1.1 cm) and between observers was -0.3 cm (95% limits of agreement, -2.5 to +1.8 cm). Intra-observer repeatability coefficients (RC) were marginally lower for consultants when compared to trainees (1.1 versus 1.5). RCs between observers were comparable (2.1 versus 2.2) for for consultants and trainees, respectively. Conclusions: This study detected a large inter-observer variability of the CAJ position (up to 4.3 cm). This is a significant finding considering that the length of the SVC is reported to be approximately 7cm. We conclude that there is poor consensus regarding the CAJ position amongst radiologists. Advances in knowledge: No comparisons exist between radiologists in determining CAJ position from chest X-rays. This report provides evidence of the large observer variability amongst radiologists and adds to the discussion regarding the use of chest X-rays in validating catheter tip location systems

Mind reading: discovering individual preferences from eye movements using switching hidden Markov models

Conference Theme: Integrating Psychological, Philosophical, Linguistic, Computational and Neural PerspectivesPoster Session 3: no. 33Here we used a hidden Markov model (HMM) based approach to infer individual choices from eye movements in preference decision-making. We assumed that during a decision making process, participants may switch between exploration and decision-making periods, and this behavior can be better captured with a Switching HMM (SHMM). Through clustering individual eye movement patterns described in SHMMs, we automatically discovered two groups of participants with different decision making behavior. One group showed a strong and early bias to look more often at the to-be chosen stimulus (i.e., the gaze cascade effect; Shimojo et al., 2003) with a short final decision-making period. The other group showed a weaker cascade effect with a longer final decision- making period. The SHMMs also showed capable of inferring participants’ preference choice on each trial with high accuracy. Thus, our SHMM approach made it possible to reveal individual differences in decision making and discover individual preferences from eye movement data.postprin

Piezoelectric micromachined ultrasonic transducers based on P(VDF-TrFE) copolymer thin films

2006-2007 > Academic research: refereed > Refereed conference paperVersion of RecordPublishe

Help-seeking intentions and subsequent 12-month mental health service use in Chinese primary care patients with depressive symptoms

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Understanding eye movements in face recognition with hidden Markov model

Fulltext in: http://mindmodeling.org/cogsci2013/papers/0085/paper0085.pdfIn this paper we propose a hidden Markov model (HMM)-based method to analyze eye movement data. We conducted a simple face recognition task and recorded eye movements and performance of the participants. We used a variational Bayesian framework for Gaussian mixture models to estimate the distribution of fixation locations and modelled the fixation and transition data using HMMs. We showed that using HMMs, we can describe individuals’ eye movement strategies with both fixation locations and transition probabilities. By clustering these HMMs, we found that the strategies can be categorized into two subgroups; one was more holistic and the other was more analytical. Furthermore, we found that correct and wrong recognitions were associated with distinctive eye movement strategies. The difference between these strategies lied in their transition probabilities

12-Month naturalistic outcomes of depressive disorders in Hong Kong's primary care

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