UNDERSTANDING FOOD LITERACY AND ITS USE IN A TECHNOLOGY-DRIVEN NUTRITION EDUCATION PROGRAM FOR ADOLESCENTS.

One in three adolescents in the U.S. is overweight or obese. The dietary habits of this population are concerning as few meet current dietary recommendations for consuming fruits and vegetables. Equally troubling among this group is the consumption of sugar-sweetened beverages and the lack of physical activity. Studies that investigate the link between nutrition knowledge, attitudes, and behaviors have shown mixed results and new methods to investigate this relationship are needed. Food literacy is a new term that has risen out of the health and nutrition literacy fields. Food literacy seeks to examine the complex relationship between knowledge, attitudes, and behaviors from the perspective of food and not individual nutrients. Adolescence is a unique life stage when there is development of decision-making skills. Food literacy programs are ideally suited to this stage because the concept focuses on building capacity to operationalize healthy decisions regarding food. New methods are also needed, to help increase engagement and participation in food-related programs. Adolescents are digital natives. Eighty-seven percent have access to a computer, 88% have access to a cellphone, and 92% go online daily, from these devices. Driving the use of cellphones is social media and text messaging. In fact, 91% of adolescents use their cellphone for texting, sending an average of 67 messages/day. Adolescent’s pervasive use of technology, in particular cellphones, provides an opportunity to investigate the potential of this medium to engage participants in education about food. Another novel method to engage adolescents in food-related education is the use of community-based participatory research (CBPR). CBPR is a collaborative approach that includes community members in the research process. The approach incorporates sharing of ideas between community members and researchers, values mutual decision-making, and empowers participants to plan activities and make changes they see as beneficial to their community. CBPR is not often used with adolescents, and no current research has used CBPR to inform a technology-driven, food literacy program for low-income, ethnically diverse adolescents. Filling this gap will add to the understanding of the use of innovative programs and ideas to engage adolescents and help them develop healthy eating behaviors

Effectiveness of Stuttering Modification Treatment in School-Age Children Who Stutter:A Randomized Clinical Trial

PURPOSE: This study investigated the effectiveness of the stuttering modification intervention Kinder Dürfen Stottern (KIDS) in school-age children who stutter. METHOD: Seventy-three children who stutter were included in this multicenter, two-group parallel, randomized, wait-list controlled trial with a follow-up of 12 months. Children aged 7-11 years were recruited from 34 centers for speech therapy and randomized to either the immediate-treatment group or the 3 months delayed-treatment group. KIDS was provided by 26 clinicians who followed a treatment manual. Although the primary outcome measure was the impact of stuttering (Overall Assessment of the Speaker's Experience of Stuttering-School-Age [OASES-S]), the secondary outcomes included objective and subjective data on stuttering severity. RESULTS: At 3 months postrandomization, the mean score changes of the OASES-S differed significantly between the experimental (n = 33) and control group (n = 29; p = .026). Furthermore, treatment outcomes up to 12 months were analyzed (n = 59), indicating large effects of time on the OASES-S score (p &lt; .001, partial η2= .324). This was paralleled by significant improvements in parental ratings and objective ratings (stuttering severity, frequency, and physical concomitants). CONCLUSIONS: The significant short-term treatment effects in the OASES-S are in line with the (initial) focus of KIDS on cognitive and affective aspects of stuttering. Over 12 months, these changes were maintained and accompanied by behavioral improvements. The results suggest that individual treatment with KIDS is an adequate treatment option for this age group. SUPPLEMENTAL MATERIAL: https://doi.org/10.23641/asha.24207864.</p

Reader Categorization of a Controversial Communication: Advertisement Versus Editorial

Using a disguised, structured technique, the authors collected consumer judgments regarding an editorial advertisement entitled Of cigarettes and science sponsored by R. J. Reynolds Tobacco Company. Respondents were shown an actual newspaper section that contained different types of editorials and advertisements, including the Of cigarettes and science item. After the respondents indirectly classified each item as either an editorial or advertisement, they were asked to list at least two characteristics about the appearance or wording of the Of cigarettes and science item that caused them to classify it as they did. The majority of respondents thought the item was an advertisement because it looked different from editorial items, was sponsored by R. J. Reynolds Tobacco Company, and seemed to have a persuasive or promotional content. Over one-fourth of the respondents, however, identified the communication as an editorial because of its lack of direct sales information and its extensive wording. The authors contend that legal and regulatory bodies should consider the effects of both source and intent of the message when arguing consumer impact

Preserving Trustworthiness and Confidentiality for Online Multimedia

Technology advancements in areas of mobile computing, social networks, and cloud computing have rapidly changed the way we communicate and interact. The wide adoption of media-oriented mobile devices such as smartphones and tablets enables people to capture information in various media formats, and offers them a rich platform for media consumption. The proliferation of online services and social networks makes it possible to store personal multimedia collection online and share them with family and friends anytime anywhere. Considering the increasing impact of digital multimedia and the trend of cloud computing, this dissertation explores the problem of how to evaluate trustworthiness and preserve confidentiality of online multimedia data. The dissertation consists of two parts. The first part examines the problem of evaluating trustworthiness of multimedia data distributed online. Given the digital nature of multimedia data, editing and tampering of the multimedia content becomes very easy. Therefore, it is important to analyze and reveal the processing history of a multimedia document in order to evaluate its trustworthiness. We propose a new forensic technique called ``Forensic Hash", which draws synergy between two related research areas of image hashing and non-reference multimedia forensics. A forensic hash is a compact signature capturing important information from the original multimedia document to assist forensic analysis and reveal processing history of a multimedia document under question. Our proposed technique is shown to have the advantage of being compact and offering efficient and accurate analysis to forensic questions that cannot be easily answered by convention forensic techniques. The answers that we obtain from the forensic hash provide valuable information on the trustworthiness of online multimedia data. The second part of this dissertation addresses the confidentiality issue of multimedia data stored with online services. The emerging cloud computing paradigm makes it attractive to store private multimedia data online for easy access and sharing. However, the potential of cloud services cannot be fully reached unless the issue of how to preserve confidentiality of sensitive data stored in the cloud is addressed. In this dissertation, we explore techniques that enable confidentiality-preserving search of encrypted multimedia, which can play a critical role in secure online multimedia services. Techniques from image processing, information retrieval, and cryptography are jointly and strategically applied to allow efficient rank-ordered search over encrypted multimedia database and at the same time preserve data confidentiality against malicious intruders and service providers. We demonstrate high efficiency and accuracy of the proposed techniques and provide a quantitative comparative study with conventional techniques based on heavy-weight cryptography primitives

TRECVID 2014 -- An Overview of the Goals, Tasks, Data, Evaluation Mechanisms and Metrics

International audienceThe TREC Video Retrieval Evaluation (TRECVID) 2014 was a TREC-style video analysis and retrieval evaluation, the goal of which remains to promote progress in content-based exploitation of digital video via open, metrics-based evaluation. Over the last dozen years this effort has yielded a better under- standing of how systems can effectively accomplish such processing and how one can reliably benchmark their performance. TRECVID is funded by the NIST with support from other US government agencies. Many organizations and individuals worldwide contribute significant time and effort

The effect of complex falls prevention interventions on falls in residential aged care settings: A systematic review protocol

The objective of this review is to synthesize the best available evidence on the effectiveness of complex falls prevention interventions on fall reductions in the residential aged care population, implemented at two or more of the following levels: organization, facility or resident. Specifically the review question is: What is the effect of complex falls prevention interventions on falls in residential aged care settings

TRECVID 2015 – An Overview of the Goals, Tasks, Data, Evaluation Mechanisms, and Metrics

International audienc

Experimental evidence on measures to protect consumers of online gambling services

Online gambling has grown rapidly in recent decades due to increased accessibility and availability. This article reports the results of a behavioral experiment conducted in a laboratory (N=522) and an online experiment administered in seven European countries (N=5997). The experiments examined the effectiveness of a range of mainstream and also innovative protective interventions for online gambling. The rationale of the interventions was to disrupt both individuals\u2019 mental processes and the affordances embedded in the human-machine system designed to maximize the time spent gambling and industry profits. Behavioral measures including stake size, speed of play and decision to stop playing or make further gambles were recorded. The results show that interventions addressing both individuals\u2019 mental processes and the human-machine interaction are effective in reducing the stake size and in slowing down the pace of gambling. All other interventions directed at the level of the individual have no effect on behavior. The results show that traditional \u2018nudges\u2019 are not sufficient and structural features such as the affordances embedded by design into the online gambling machines must be addressed in order to effectively protect consumers of online gambling

Information embedding and retrieval in 3D printed objects

Deep learning and convolutional neural networks have become the main tools of computer vision. These techniques are good at using supervised learning to learn complex representations from data. In particular, under limited settings, the image recognition model now performs better than the human baseline. However, computer vision science aims to build machines that can see. It requires the model to be able to extract more valuable information from images and videos than recognition. Generally, it is much more challenging to apply these deep learning models from recognition to other problems in computer vision. This thesis presents end-to-end deep learning architectures for a new computer vision field: watermark retrieval from 3D printed objects. As it is a new area, there is no state-of-the-art on many challenging benchmarks. Hence, we first define the problems and introduce the traditional approach, Local Binary Pattern method, to set our baseline for further study. Our neural networks seem useful but straightfor- ward, which outperform traditional approaches. What is more, these networks have good generalization. However, because our research field is new, the problems we face are not only various unpredictable parameters but also limited and low-quality training data. To address this, we make two observations: (i) we do not need to learn everything from scratch, we know a lot about the image segmentation area, and (ii) we cannot know everything from data, our models should be aware what key features they should learn. This thesis explores these ideas and even explore more. We show how to use end-to-end deep learning models to learn to retrieve watermark bumps and tackle covariates from a few training images data. Secondly, we introduce ideas from synthetic image data and domain randomization to augment training data and understand various covariates that may affect retrieve real-world 3D watermark bumps. We also show how the illumination in synthetic images data to effect and even improve retrieval accuracy for real-world recognization applications