71,790 research outputs found
A Multi-Task Learning Approach for Meal Assessment
Key role in the prevention of diet-related chronic diseases plays the
balanced nutrition together with a proper diet. The conventional dietary
assessment methods are time-consuming, expensive and prone to errors. New
technology-based methods that provide reliable and convenient dietary
assessment, have emerged during the last decade. The advances in the field of
computer vision permitted the use of meal image to assess the nutrient content
usually through three steps: food segmentation, recognition and volume
estimation. In this paper, we propose a use one RGB meal image as input to a
multi-task learning based Convolutional Neural Network (CNN). The proposed
approach achieved outstanding performance, while a comparison with
state-of-the-art methods indicated that the proposed approach exhibits clear
advantage in accuracy, along with a massive reduction of processing time
Excellence in English: what we can learn from 12 outstanding schools
"One of the most pressing issues in English facing a large number of schools today is
how to improve from being good to outstanding. The aim of this report is to improve
practice in English across all schools and particularly to help them become
outstanding. The report provides 12 case studies of schools which are successful in
helping their pupils to make outstanding progress in English." - Cover
Bridge College: inspection of FEFC-funded provision in non-sector establishments for students with learning difficulties and/or disabilities (Report from the Inspectorate, 1999-00)
Independent Establishment 17/00, Inspection of FEFC-Funded
Provision in non-sector establishments for students with
learning difficulties and/or disabilities.
Bridge College, Offerton, Stockport, Inspected June 200
Artifact Rejection Methodology Enables Continuous, Noninvasive Measurement of Gastric Myoelectric Activity in Ambulatory Subjects.
The increasing prevalence of functional and motility gastrointestinal (GI) disorders is at odds with bottlenecks in their diagnosis, treatment, and follow-up. Lack of noninvasive approaches means that only specialized centers can perform objective assessment procedures. Abnormal GI muscular activity, which is coordinated by electrical slow-waves, may play a key role in symptoms. As such, the electrogastrogram (EGG), a noninvasive means to continuously monitor gastric electrical activity, can be used to inform diagnoses over broader populations. However, it is seldom used due to technical issues: inconsistent results from single-channel measurements and signal artifacts that make interpretation difficult and limit prolonged monitoring. Here, we overcome these limitations with a wearable multi-channel system and artifact removal signal processing methods. Our approach yields an increase of 0.56 in the mean correlation coefficient between EGG and the clinical "gold standard", gastric manometry, across 11 subjects (p < 0.001). We also demonstrate this system's usage for ambulatory monitoring, which reveals myoelectric dynamics in response to meals akin to gastric emptying patterns and circadian-related oscillations. Our approach is noninvasive, easy to administer, and has promise to widen the scope of populations with GI disorders for which clinicians can screen patients, diagnose disorders, and refine treatments objectively
Validation of a recommender system for prompting omitted foods in online dietary assessment surveys
Recall assistance methods are among the key aspects that improve the accuracy
of online dietary assessment surveys. These methods still mainly rely on
experience of trained interviewers with nutritional background, but data driven
approaches could improve cost-efficiency and scalability of automated dietary
assessment. We evaluated the effectiveness of a recommender algorithm developed
for an online dietary assessment system called Intake24, that automates the
multiple-pass 24-hour recall method. The recommender builds a model of eating
behavior from recalls collected in past surveys. Based on foods they have
already selected, the model is used to remind respondents of associated foods
that they may have omitted to report. The performance of prompts generated by
the model was compared to that of prompts hand-coded by nutritionists in two
dietary studies. The results of our studies demonstrate that the recommender
system is able to capture a higher number of foods omitted by respondents of
online dietary surveys than prompts hand-coded by nutritionists. However, the
considerably lower precision of generated prompts indicates an opportunity for
further improvement of the system
innovative Public Organic food Procurement for Youth (iPOPY). Lessons learned from implementing organic into European school meals – policy implications.
The introduction of organic food offers new dimensions to school meals, and schools offer new dimensions
to organic food – when tackled properly. In this paper we present findings from the iPOPY research
project that is funded by the ERA-Net, CORE-Organic-I funding body network. It is based on studies of
school food policies in Denmark, Finland, Italy and Norway. The embedded food traditions and cultures have
had different attention in these countries, why also food related consumption, institutions and markets are
quite heterogeneous and dynamic. Whereas school food services are relatively widely embedded in the
school systems in Finland and Italy, the Danish and Norwegian school food is predominantly defined by the
packed lunch brought from home when it comes to organic food the pattern is different. To analyse the
strategies used in these countries we have selected a number of cases where in-depth studies have been
conducted. The concept of embedding has been used in these studies and it has been informed by policy
and actor network theories. The results of this analysis show a complexity in implementing organic food in
existing school food aims, in embedding school food policies and in comprising also aims and policies for
organic food purchasing in these. The variety amongst the analysed countries in strategies and success is
identified, covering both structural and stakeholder related findings. A major finding is pointing at the
challenge of “multi-embedding” processes when including organic food in school meal procurement
How to measure mood in nutrition research
© 2014 The Authors. Mood is widely assessed in nutrition research, usually with rating scales. A core assumption is that positive mood reinforces ingestion, so it is important to measure mood well. Four relevant theoretical issues are reviewed: (i) the distinction between protracted and transient mood; (ii) the distinction between mood and emotion; (iii) the phenomenology of mood as an unstable tint to consciousness rather than a distinct state of consciousness; (iv) moods can be caused by social and cognitive processes as well as physiological ones. Consequently, mood is difficult to measure and mood rating is easily influenced by non-nutritive aspects of feeding, the psychological, social and physical environment where feeding occurs, and the nature of the rating system employed. Some of the difficulties are illustrated by reviewing experiments looking at the impact of food on mood. The mood-rating systems in common use in nutrition research are then reviewed, the requirements of a better mood-rating system are described, and guidelines are provided for a considered choice of mood-rating system including that assessment should: have two main dimensions; be brief; balance simplicity and comprehensiveness; be easy to use repeatedly. Also mood should be assessed only under conditions where cognitive biases have been considered and controlled
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