Modeling Human Visual Search Performance on Realistic Webpages Using Analytical and Deep Learning Methods

Modeling visual search not only offers an opportunity to predict the usability of an interface before actually testing it on real users, but also advances scientific understanding about human behavior. In this work, we first conduct a set of analyses on a large-scale dataset of visual search tasks on realistic webpages. We then present a deep neural network that learns to predict the scannability of webpage content, i.e., how easy it is for a user to find a specific target. Our model leverages both heuristic-based features such as target size and unstructured features such as raw image pixels. This approach allows us to model complex interactions that might be involved in a realistic visual search task, which can not be easily achieved by traditional analytical models. We analyze the model behavior to offer our insights into how the salience map learned by the model aligns with human intuition and how the learned semantic representation of each target type relates to its visual search performance.Comment: the 2020 CHI Conference on Human Factors in Computing System

Pilot and Feasibility Test of an Implementation Intention Intervention to Improve Fruit and Vegetable Intake Among Women with Low Socioeconomic Status

Fruit and vegetable intake (FVI), a modifiable risk factor for chronic diseases, is lower in low socioeconomic status (SES) populations. Implementation intentions (a specific type of planning that extends the Theory of Planned Behavior) has been studied to improve FVI, but not exclusively with low SES groups. Using mixed methods, we evaluated the feasibility, acceptability, and preliminary efficacy of an implementation intention intervention (versus a general plan) to increase FVI in women with low SES. For the pilot randomized controlled trial, demographics, body mass index, attitude, perceived behavioral control, goal intention strength, and FVI were measured at baseline and FVI again 1-month following the intervention. Feasibility data were collected for recruitment, randomization, retention, and assessment procedures and compared to predetermined targets. Semi-structured interview data was analyzed for emergent themes regarding acceptability of the trial. Preliminary efficacy of the intervention to improve FVI was analyzed descriptively. Feasibility targets were met for randomization (100% vs. ≥80% target), retention (93.5% vs. ≥70% target) and the assessment metrics missing data points (2% vs. ≤10% target) and days from intervention to follow up (mean=69.2, sd=42.6 vs.days). Targets for recruitment were not met with the exception of participants giving informed consent (100% vs. ≥70% target). Participants described the intervention as enjoyable and reported behavioral constructs outside of those measured as important to improve FVI. Limited efficacy analysis suggested that both groups increased their FVI (experimental: +0.17 servings per day, 95% CI: -0.85, 1.20; control: +0.50 servings per day, 95% CI: -0.56, 1.58). Further research which examines interventions based upon behavior change models to improve dietary health behaviors in marginalized groups is needed

Pilot and feasibility test of an implementation intention intervention to improve fruit and vegetable intake among women with low socioeconomic status

Fruit and vegetable intake (FVI), a modifiable risk factor for chronic diseases, is lower in low socioeconomic status (SES) populations. Implementation intentions (a specific type of planning that extends the Theory of Planned Behavior) has been studied to improve FVI, but not exclusively with low SES groups. Using mixed methods, we evaluated the feasibility, acceptability, and preliminary efficacy of an implementation intention intervention (versus a general plan) to increase FVI in women with low SES. For the pilot randomized controlled trial, demographics, body mass index, attitude, perceived behavioral control, goal intention strength, and FVI were measured at baseline and FVI again 1-month following the intervention. Feasibility data were collected for recruitment, randomization, retention, and assessment procedures and compared to predetermined targets. Semi-structured interview data was analyzed for emergent themes regarding acceptability of the trial. Preliminary efficacy of the intervention to improve FVI was analyzed descriptively. Feasibility targets were met for randomization (100% vs. ≥80% target), retention (93.5% vs. ≥70% target) and the assessment metrics missing data points (2% vs. ≤10% target) and days from intervention to follow up (mean=69.2, sd=42.6 vs.days). Targets for recruitment were not met with the exception of participants giving informed consent (100% vs. ≥70% target). Participants described the intervention as enjoyable and reported behavioral constructs outside of those measured as important to improve FVI. Limited efficacy analysis suggested that both groups increased their FVI (experimental: +0.17 servings per day, 95% CI: -0.85, 1.20; control: +0.50 servings per day, 95% CI: -0.56, 1.58). Further research which examines interventions based upon behavior change models to improve dietary health behaviors in marginalized groups is needed

Meanings of fractions as demonstrated by future primary teachers in the initial phase of teacher education

Fractions are a fundamental content of primary-level education and must therefore be included in the training courses for primary school teachers. Experts argue that deep understanding is required to improve primary school teachers’ knowledge of this mathematical concept (Ball, 1990; Cramer, Post & del Mas, 2002; Newton, 2008). Our study focuses on the part-whole relationship as a crucial foundation in working with fractions. This paper characterizes some of the meanings of this relationship for a group of future primary school teachers

Perfect tag identification protocol in RFID networks

Radio Frequency IDentification (RFID) systems are becoming more and more popular in the field of ubiquitous computing, in particular for objects identification. An RFID system is composed by one or more readers and a number of tags. One of the main issues in an RFID network is the fast and reliable identification of all tags in the reader range. The reader issues some queries, and tags properly answer. Then, the reader must identify the tags from such answers. This is crucial for most applications. Since the transmission medium is shared, the typical problem to be faced is a MAC-like one, i.e. to avoid or limit the number of tags transmission collisions. We propose a protocol which, under some assumptions about transmission techniques, always achieves a 100% perfomance. It is based on a proper recursive splitting of the concurrent tags sets, until all tags have been identified. The other approaches present in literature have performances of about 42% in the average at most. The counterpart is a more sophisticated hardware to be deployed in the manufacture of low cost tags.Comment: 12 pages, 1 figur

A Factoid Question Answering System for Vietnamese

In this paper, we describe the development of an end-to-end factoid question answering system for the Vietnamese language. This system combines both statistical models and ontology-based methods in a chain of processing modules to provide high-quality mappings from natural language text to entities. We present the challenges in the development of such an intelligent user interface for an isolating language like Vietnamese and show that techniques developed for inflectional languages cannot be applied "as is". Our question answering system can answer a wide range of general knowledge questions with promising accuracy on a test set.Comment: In the proceedings of the HQA'18 workshop, The Web Conference Companion, Lyon, Franc