Expert System for Nutrition Care Process of Older Adults

This paper presents an expert system for a nutrition care process tailored for the specific needs of elders. Dietary knowledge is defined by nutritionists and encoded as Nutrition Care Process Ontology, and then used as underlining base and standardized model for the nutrition care planning. An inference engine is developed on top of the ontology, providing semantic reasoning infrastructure and mechanisms for evaluating the rules defined for assessing short and long term elders’ self-feeding behaviours, to identify unhealthy dietary patterns and detect the early instauration of malnutrition. Our expert system provides personalized intervention plans covering nutrition education, diet prescription and food ordering adapted to the older adult’s specific nutritional needs, health conditions and food preferences. In-lab evaluation results are presented proving the usefulness and quality of the expert system as well as the computational efficiency, coupling and cohesion of the defined ontology

An ontology to integrate multiple knowledge domains of training-dietary-competition in weightlifting: A nutritional approach

This study is a part of weightlifting “TrainingDietary-Competition” (TDC) cycle ontology. The main objective of TDC-cycle is to build a knowledge framework for Olympic weightlifting, bringing together related fields such as training methodology, weightlifting biomechanics, and nutrition while modelling the synergy among them. In so doing, terminology, semantics, and used concepts are unified among athletes, coaches, nutritionists, and researchers to partially obviate the problem of unclear results and paucity of information. The uniqueness of this ontology is its ability to solve the knowledge sharing problem in which the knowledge owned by these experts in each field are not captures, classified or integrated into an information system for decision-making. The whole weightlifting TDC-cycle is semantically modelled by conceiving, designing, and integrating domain and task ontologies with the latter devising reasoning capability toward an automated and tailored weightlifting TDC-cycle. However, this study will focus mainly on the nutrition domain. The intended application of this part of ontology is to provide a useful decision-making platform for a sport nutritionist who gathers and integrate relevant scientific information, equation, and tools necessary when providing nutritional services. The system is constructed by using Web Ontology Language (OWL), Semantic Web Rule Language (SWRL), and Semantic Query-Enhanced Web Rule Language (SQWRL). The use of weightlifting TDC-cycle ontology can be helpful for nutritionists to create a well-planned nutrition program for athletes (especially, in the process of nutrition monitoring to identify energy imbalance in athletes) by reducing time consumption and calculation errors.The authors would like to thank Prof.Adriano Tavares for his guidance and providing necessary in formation regarding the project

Strategies for online personalised nutrition advice employed in the development of the eNutri web app

The internet has considerable potential to improve health-related food choice at low-cost. Online solutions in this field can be deployed quickly and at very low cost, especially if they are not dependent on bespoke devices or offline processes such as the provision and analysis of biological samples. One key challenge is the automated delivery of personalised dietary advice in a replicable, scalable and inexpensive way, using valid nutrition assessment methods and effective recommendations. We have developed a web-based personalised nutrition system (eNutri) which assesses dietary intake using a validated graphical FFQ and provides personalised food-based dietary advice automatically. Its effectiveness was evaluated during an online randomised controlled trial dietary intervention (EatWellUK study) in which personalised dietary advice was compared with general population recommendations (control) delivered online. The present paper presents a review of literature relevant to this work, and describes the strategies used during the development of the eNutri app. Its design and source code have been made publicly available under a permissive open source license, so that other researchers and organisations can benefit from this work. In a context where personalised diet advice has great potential for health promotion and disease prevention at-scale and yet is not currently being offered in the most popular mobile apps, the strategies and approaches described in the present paper can help to inform and advance the design and development of technologies for personalised nutrition

Becoming Eco-Logical With Second-Order Systems Theory: Sustainability In Re-Organization Of Economies And Food Systems

Ecological Economics has emerged across disciplines, and has begun to disentangle, not only the relationship between biophysical earth systems and economic activity, but also, fundamental relationships between objectivity, power, value, ethics, perspective and purpose. In part, this thesis represents an effort to illustrate basic transdisciplinary concepts necessary for understanding the project of Ecological Economics. At present, Ecological Economics is challenged by a seemingly infinite number of available considerations, with a relatively narrow repertoire of impactful mechanisms of control. Given this, it is apparent that the application of Cybernetics to Ecological Economics might provide insights. Cybernetics can help to lend concise language to manners for implementing control and also help to navigate the paradoxes which arise for self- regulating systems. While Cybernetics played an early role in the formulation of the relationship between the economy and an environment with available energy, second- order cybernetics can help to formulate the autonomy of Ecological Economics as a self-regulating system and shed light on the epistemology and ethics of circularity. The first article of this thesis identifies occasions when Ecological Economics has confronted circularity, and explores options moving forward. Ultimately, confronting paradox and circularity provide the means for the substantiation of Ecological Economics. The food system is prominent within Ecological Economics discourse. It serves as a good example of the ‘emergence’ of coordinated activity. In Cybernetics jargon, we can think of the ‘Food System’ as a symbol for the redundancy found in linked characteristics of particular Ecological-Economic inquiry. For instance, when we consider the food system we can be sure that we are dealing with resources that are essential, both rival and non-rival, excludable and non-excludable, and also highly sensitive to boundaries in scope, and scale, and thus highly sensitive to political and social change. In this sense, the food system acts as a symbol for the coordination of activity, and produces an output which is an input to the Ecological Economic ‘boundary’ between the Economy and the Ecosystem. The second article of this thesis provides an analysis of GHG emissions within the Chittenden County Foodshed. We conclude that urban agriculture, dietary change and agro-ecological production in concert, provide emission reductions which are not achieved when these options are considered separately. Given these conditions, we see mitigation beyond 90% of current emissions

Big data analytics for preventive medicine

© 2019, Springer-Verlag London Ltd., part of Springer Nature. Medical data is one of the most rewarding and yet most complicated data to analyze. How can healthcare providers use modern data analytics tools and technologies to analyze and create value from complex data? Data analytics, with its promise to efficiently discover valuable pattern by analyzing large amount of unstructured, heterogeneous, non-standard and incomplete healthcare data. It does not only forecast but also helps in decision making and is increasingly noticed as breakthrough in ongoing advancement with the goal is to improve the quality of patient care and reduces the healthcare cost. The aim of this study is to provide a comprehensive and structured overview of extensive research on the advancement of data analytics methods for disease prevention. This review first introduces disease prevention and its challenges followed by traditional prevention methodologies. We summarize state-of-the-art data analytics algorithms used for classification of disease, clustering (unusually high incidence of a particular disease), anomalies detection (detection of disease) and association as well as their respective advantages, drawbacks and guidelines for selection of specific model followed by discussion on recent development and successful application of disease prevention methods. The article concludes with open research challenges and recommendations

Automatic Generation of Personalized Recommendations in eCoaching

Denne avhandlingen omhandler eCoaching for personlig livsstilsstøtte i sanntid ved bruk av informasjons- og kommunikasjonsteknologi. Utfordringen er å designe, utvikle og teknisk evaluere en prototyp av en intelligent eCoach som automatisk genererer personlige og evidensbaserte anbefalinger til en bedre livsstil. Den utviklede løsningen er fokusert på forbedring av fysisk aktivitet. Prototypen bruker bærbare medisinske aktivitetssensorer. De innsamlede data blir semantisk representert og kunstig intelligente algoritmer genererer automatisk meningsfulle, personlige og kontekstbaserte anbefalinger for mindre stillesittende tid. Oppgaven bruker den veletablerte designvitenskapelige forskningsmetodikken for å utvikle teoretiske grunnlag og praktiske implementeringer. Samlet sett fokuserer denne forskningen på teknologisk verifisering snarere enn klinisk evaluering.publishedVersio

Ontology-based personalized performance evaluation and dietary recommendation for weightlifting.

Studies in weightlifting have been characterized by unclear results and information paucity, mainly due to the lack of information sharing between athletes, coaches, biomechanists, physiologists and nutritionists. Becoming successful in weightlifting performance requires a unique physiological and biomechanics profile based on a distinctive combination of muscular strength, muscular power, flexibility, and lifting technique. An effective training which is carefully designed and monitored, is needed for accomplishment of consistent high performance. While it takes years of dedicated training, diet is also critical as optimal nutrition is essential for peak performance. Nutritional misinformation can do as much harm to ambitious athletes as good nutrition can help. In spite of several studies on nutrition guidelines for weightlifting training and competition as well as on design and implementation of weightlifting training programs, to the best of authors' knowledge, there is no attempt to semantically model the whole "training-diet-competition" cycle by integrating training, biomechanics, and nutrition domains.This study aims to conceive and design an ontology-enriched knowledge model to guide and support the implementation of "Recommender system of workout and nutrition forweightlifters". In doing so, it will propose: (i) understanding the weightlifting training system, from both qualitative and quantitative perspectives, following a modular ontology modeling, (ii) understanding the weightlifting diet following a modular ontology modeling, (iii) semantically integrating weightlifting and nutrition ontologies to mainly promote nutrition and weightlifting snatch exercises interoperability, (iv) extending modular ontology scope by mining rules while analyzing open data from the literature, and (v) devising reasoning capability toward an automated weightlifting "training-diet-competition" cycle supported by previously mined rulesTo support the above claims, two main artefacts were generated such as: (i) a weightliftingnutritional knowledge questionnaire to assess Thai weightlifting coaches' and athletes'knowledge regarding the weightlifting "training-diet-competition" cycle and (ii) a dual ontologyoriented weightlifting-nutrition knowledge model extended with mined rules and designed following a standard ontology development methodology.Studies in weightlifting have been characterized by unclear results and information paucity, mainly due to the lack of information sharing between athletes, coaches, biomechanists, physiologists and nutritionists. Becoming successful in weightlifting performance requires a unique physiological and biomechanics profile based on a distinctive combination of muscular strength, muscular power, flexibility, and lifting technique. An effective training which is carefully designed and monitored, is needed for accomplishment of consistent high performance. While it takes years of dedicated training, diet is also critical as optimal nutrition is essential for peak performance. Nutritional misinformation can do as much harm to ambitious athletes as good nutrition can help. In spite of several studies on nutrition guidelines for weightlifting training and competition as well as on design and implementation of weightlifting training programs, to the best of authors' knowledge, there is no attempt to semantically model the whole "training-diet-competition" cycle by integrating training, biomechanics, and nutrition domains.This study aims to conceive and design an ontology-enriched knowledge model to guide and support the implementation of "Recommender system of workout and nutrition forweightlifters". In doing so, it will propose: (i) understanding the weightlifting training system, from both qualitative and quantitative perspectives, following a modular ontology modeling, (ii) understanding the weightlifting diet following a modular ontology modeling, (iii) semantically integrating weightlifting and nutrition ontologies to mainly promote nutrition and weightlifting snatch exercises interoperability, (iv) extending modular ontology scope by mining rules while analyzing open data from the literature, and (v) devising reasoning capability toward an automated weightlifting "training-diet-competition" cycle supported by previously mined rulesTo support the above claims, two main artefacts were generated such as: (i) a weightliftingnutritional knowledge questionnaire to assess Thai weightlifting coaches' and athletes'knowledge regarding the weightlifting "training-diet-competition" cycle and (ii) a dual ontologyoriented weightlifting-nutrition knowledge model extended with mined rules and designed following a standard ontology development methodology

Data, Metrics and Monitoring in CGIAR - a strategic study

This document contains the final report of the Panel together with the ISPC commentary. The Panel Report presents an analysis of the current activities within CGIAR concerning data, metrics and indicators, and offers a series of recommendations to address the key issues and challenges identified