Evaluation of a health promotion program in children: Study protocol and design of the cluster-randomized Baden-Württemberg primary school study [DRKS-ID: DRKS00000494]

<p>Abstract</p> <p>Background</p> <p>Increasing prevalences of overweight and obesity in children are known problems in industrialized countries. Early prevention is important as overweight and obesity persist over time and are related with health problems later in adulthood. "Komm mit in das gesunde Boot - Grundschule" is a school-based program to promote a healthier lifestyle. Main goals of the intervention are to increase physical activity, decrease the consumption of sugar-sweetened beverages, and to decrease time spent sedentary by promoting active choices for healthy lifestyle. The program to date is distributed by 34 project delivery consultants in the state of Baden-Württemberg and is currently implemented in 427 primary schools. The efficacy of this large scale intervention is examined via the Baden-Württemberg Study.</p> <p>Methods/Design</p> <p>The Baden-Württemberg Study is a prospective, stratified, cluster-randomized, and longitudinal study with two groups (intervention group and control group). Measurements were taken at the beginning of the academic years 2010/2011 and 2011/2012. Efficacy of the intervention is being assessed using three main outcomes: changes in waist circumference, skinfold thickness and 6 minutes run. Stratified cluster-randomization (according to class grade level) was performed for primary schools; pupils, teachers/principals, and parents were investigated. An approximately balanced number of classes in intervention group and control group could be reached by stratified randomization and was maintained at follow-up.</p> <p>Discussion</p> <p>At present, "Komm mit in das Gesunde Boot - Grundschule" is the largest school-based health promotion program in Germany. Comparative objective main outcomes are used for the evaluation of efficacy. Simulations showed sufficient power with the existing sample size. Therefore, the results will show whether the promotion of a healthier lifestyle in primary school children is possible using a relatively low effort within a school-based program involving children, teachers and parents. The research team anticipates that not only efficacy will be proven in this study but also expects many other positive effects of the program.</p> <p>Trial registration</p> <p>German Clinical Trials Register (DRKS), DRKS-ID: DRKS00000494</p

Dielectric Permittivity Model for Polymer–Filler Composite Materials by the Example of Ni- and Graphite-Filled Composites for High-Frequency Absorbing Coatings

The suppression of unnecessary radio-electronic noise and the protection of electronic devices from electromagnetic interference by the use of pliable highly microwave radiation absorbing composite materials based on polymers or rubbers filled with conductive and magnetic fillers have been proposed. Since the working frequency bands of electronic devices and systems are rapidly expanding up to the millimeter wave range, the capabilities of absorbing and shielding composites should be evaluated for increasing operating frequency. The point is that the absorption capacity of conductive and magnetic fillers essentially decreases as the frequency increases. Therefore, this paper is devoted to the absorbing capabilities of composites filled with high-loss dielectric fillers, in which absorption significantly increases as frequency rises, and it is possible to achieve the maximum frequency selective of absorption due to electromagnetic and electromechanical resonances

Розробка аналізатора для підвищення безпеки морського судноплавства і його експериментальне дослідження

On the basis of empirical experimental data, relationships were identified indicating the influence of navigators' response to such vessel control indicators as maneuverability and safety. This formed a hypothesis about a non-random connection between the navigator's actions, response and parameters of maritime transport management. Within the framework of this hypothesis, logical-formal approaches were proposed that allow using server data of both maritime simulators and operating vessels in order to timely identify the occurrence of a critical situation with possible catastrophic consequences. A method for processing navigation data based on the analysis of temporal zones is proposed, which made it possible to prevent manifestations of reduced efficiency of maritime transport management by 22.5 %. Based on cluster analysis and automated neural networks, it was possible to identify temporary vessel control fragments and classify them by the level of danger. At the same time, the neural network test error was only 3.1 %, and the learning error was 3.8 %, which ensures the high quality of simulation results. The proposed approaches were tested using the Navi Trainer 5000 navigation simulator (Wärtsilä Corporation, Finland). The simulation of the system for identifying critical situations in maritime transport management made it possible to reduce the probability of catastrophic situations by 13.5 %. The use of automated artificial neural networks allowed defining critical situations in real time from the database of maritime transport management on the captain's bridge for an individual navigator.На основе эмпирических экспериментальных данных были идентифицированы связи, указывающие на влияние реакций навигаторов (судоводителей) на такие показатели управления судном как маневренность и безопасность. Это сформировало гипотезу о неслучайной связи между действиями навигатора, его реакциями и параметрами управления морским транспортом. В рамках указанной гипотезы были предложены логико-формальные подходы, позволяющие использовать серверные данные как морских симуляторов, так и действующих судов морского транспорта с целью своевременной идентификации возникновения критической ситуации с возможными катастрофическими последствиями. Предложен метод обработки навигационных данных, основанный на анализе темпоральных зон, который позволил предупредить проявления снижений результативности управления морским транспортом на 22,5 %. На основе кластерного анализа и автоматизированных нейронных сетей удалось выделить временные фрагменты управления судном и классифицировать их в соответствии с уровнем опасности. При этом тестовая ошибка нейронной сети составила лишь 3,1&nbsp;%, а ошибка обучения 3,8&nbsp;%, что обеспечивает высокое качество полученных результатов моделирования. Предложенные подходы были апробированы с применением навигационного тренажера Navi Trainer 5000 navigation simulator (Wärtsilä Corporation, Финляндия). Проведенное имитационное моделирование системы идентификации критических ситуации при управлении морским транспортом позволило уменьшить вероятность возникновения катастрофических ситуаций на 13,5&nbsp;%. Использование автоматизированных искусственных нейронных сетей позволило проводить идентификацию критических ситуаций в режиме реального времени на основе базы данных управления морским транспортом на капитанском мостике для индивидуального навигатораНа основі емпіричних експериментальних даних були ідентифіковані зв’язки, що вказують на вплив реакцій навігаторів (судноводіїв) на такі показники управління судном як маневреність і безпека. Це сформувало гіпотезу про невипадковий зв’язок між діями навігатора, його реакціями та параметрами управління морським транспортом. У рамках зазначеної гіпотези були запропоновані логіко-формальні підходи, що дозволяють застосувати серверні дані як морських симуляторів, так і діючих суден морського транспорту з метою своєчасної ідентифікації виникнення критичної ситуації з ймовірними катастрофічними наслідками. Запропоновано метод обробки навігаційних даних, що заснований на аналізі темпоральних зон, який дозволив попередити прояви зниження результативності управління морським транспортом на 22,5&nbsp;%. На основі кластерного аналізу і автоматизованих нейронних мереж вдалося виділити часові фрагменти управління судном і класифікувати їх відповідно до рівня небезпеки. При цьому тестова помилка нейронної мережі склала лише 3,1&nbsp;%, а помилка навчання 3,8&nbsp;%, що забезпечує високу якість отриманих результатів моделювання. Запропоновані підходи були апробовані із застосуванням навігаційного тренажера Navi Trainer 5000 navigation simulator (Wärtsilä Corporation, Фінляндія). Проведене імітаційне моделювання системи ідентифікації критичних ситуації під час управління морським транспортом дозволило зменшити ймовірність виникнення катастрофічних ситуацій на 13,5&nbsp;%. Використання автоматизованих штучних нейронних мереж дозволило проводити ідентифікацію критичних ситуацій в режимі реального часу на основі бази даних управління морським транспортом на капітанському містку для індивідуального навігатор

Navigation Safety Control System Development Through Navigator Action Prediction by Data Mining Means

Taking into account current trends in the development of ergatic maritime transport systems, the factors of the navigator's influence on vessel control processes were determined. Within the framework of the research hypothesis, to improve navigation safety, it is necessary to apply predictive data mining models and automated vessel control. The paper proposes a diagram of the ergatic vessel control system and a model for identifying the influence of the navigator “human factor” during navigation. Within the framework of the model based on the principles of navigator decision trees, prediction by data mining means is applied, taking into account the identifiers of the occurrence of a critical situation. Based on the prediction results, a method for optimal vessel control in critical situations was developed, which is triggered at the nodes of the navigator decision tree, which reduces the likelihood of a critical impact on vessel control. The proposed approaches were tested in the research laboratory “Development of decision support systems, ergatic and automated vessel control systems”. The use of the Navi Trainer 5,000 navigation simulator (Wärtsilä Corporation, Finland) and simulation of the navigation safety control system for critical situations have confirmed its effectiveness. As a result of testing, it was determined that the activation of the system allowed reducing the likelihood of critical situations by 18–54 %. In 11 % of cases, the system switched the vessel control processes to automatic mode and, as a result, reduced the risk of emergencies. The use of automated data mining tools made it possible to neutralize the negative influence of the “human factor” of the navigator and to reduce the average maneuvering time during vessel navigation to 23

Navigation Safety Control System Development Through Navigator Action Prediction by Data Mining Means

Taking into account current trends in the development of ergatic maritime transport systems, the factors of the navigator's influence on vessel control processes were determined. Within the framework of the research hypothesis, to improve navigation safety, it is necessary to apply predictive data mining models and automated vessel control. The paper proposes a diagram of the ergatic vessel control system and a model for identifying the influence of the navigator “human factor” during navigation. Within the framework of the model based on the principles of navigator decision trees, prediction by data mining means is applied, taking into account the identifiers of the occurrence of a critical situation. Based on the prediction results, a method for optimal vessel control in critical situations was developed, which is triggered at the nodes of the navigator decision tree, which reduces the likelihood of a critical impact on vessel control. The proposed approaches were tested in the research laboratory “Development of decision support systems, ergatic and automated vessel control systems”. The use of the Navi Trainer 5,000 navigation simulator (Wärtsilä Corporation, Finland) and simulation of the navigation safety control system for critical situations have confirmed its effectiveness. As a result of testing, it was determined that the activation of the system allowed reducing the likelihood of critical situations by 18–54 %. In 11 % of cases, the system switched the vessel control processes to automatic mode and, as a result, reduced the risk of emergencies. The use of automated data mining tools made it possible to neutralize the negative influence of the “human factor” of the navigator and to reduce the average maneuvering time during vessel navigation to 23

Development and Experimental Study of Analyzer to Enhance Maritime Safety

On the basis of empirical experimental data, relationships were identified indicating the influence of navigators' response to such vessel control indicators as maneuverability and safety. This formed a hypothesis about a non-random connection between the navigator's actions, response and parameters of maritime transport management. Within the framework of this hypothesis, logical-formal approaches were proposed that allow using server data of both maritime simulators and operating vessels in order to timely identify the occurrence of a critical situation with possible catastrophic consequences. A method for processing navigation data based on the analysis of temporal zones is proposed, which made it possible to prevent manifestations of reduced efficiency of maritime transport management by 22.5 %. Based on cluster analysis and automated neural networks, it was possible to identify temporary vessel control fragments and classify them by the level of danger. At the same time, the neural network test error was only 3.1 %, and the learning error was 3.8 %, which ensures the high quality of simulation results. The proposed approaches were tested using the Navi Trainer 5000 navigation simulator (Wärtsilä Corporation, Finland). The simulation of the system for identifying critical situations in maritime transport management made it possible to reduce the probability of catastrophic situations by 13.5 %. The use of automated artificial neural networks allowed defining critical situations in real time from the database of maritime transport management on the captain's bridge for an individual navigator