RTS-MAC: A Relative Time Synchronization MAC Protocol for Low Duty Cycle Body Sensor Networks

Emerging applications in the medical field require body sensor networks to communicate in real-time in a very energy-efficient way. An example is the Artificial Accommodation System??a set of two small active medical implants aiming at restoring accommodation of the human eye??in which sensor data have to be exchanged continuously between both eyes. To achieve energy efficiency, it is essential to operate the radios with a very low duty cycle. Therefore, idle listening and general protocol overhead must be reduced as much as possible. In this paper, we present a relative time synchronization medium access control protocol (RTS-MAC), which keeps relative time synchronization between two or more sensor nodes in a very energy-efficient manner: RTS-MAC makes use of the periodic broadcast of regular data messages and exploits the inter-arrival times to predict future arrivals within tight boundaries. Thereby, no overhead is generated for synchronization purposes, and still, idle listening is reduced to a minimum, which solely depends on the short-term accuracy of the underlying clock systems. We implemented the proposed protocol using off-the-shelf components and employed the internal low-accuracy oscillators of the microcontrollers as clock sources. Thereby, we achieved very low duty cycles close to an ideal minimum. Further, our results indicate that through omitting external crystals in favor of a minimally larger battery, the battery life of a sensor node can be prolonged.     

Regulations and research on RC&S for hydrogen storage relevant to transport and vehicle issues with special focus on composite containments

Developers interested in high pressure storage of hydrogen for mobile use increasingly rely on composite cylinders for onboard storage or transport of dangerous goods. Thus, composite materials and systems deserve special consideration. History gives interesting background information important to the understanding of the current situation as to regulations, codes and standards.     

Oxide scale formation of modified FeCrAl coatings exposed to liquid lead

Modified FeCrAl coatings were studied with respect to their capability to form a thin protective oxide scale in liquid lead environment. They were manufactured by low pressure plasma spraying and GESA surface melting, thereby tuning the Al content. The specimens were exposed for 900 h to liquid lead containing 10^?6 and 10^?8 wt.% oxygen, respectively, at various temperatures from 400 to 550 °C. Threshold values for an Al content that guarantees the formation of thin protective Al-rich oxide scales are determined, dependent on the respective chromium content, on the presence of yttrium in the modified coating, and on the exposure conditions.     

Source identification of plant-wide faults based on k nearest neighbor time delay estimation

The identification of plant-wide faults is a very important topic as it enables plant operators to decrease rejections or to increase the product quality. This paper shows a fault propagation approach for this field of interest based on time delay estimation. Due to the fact that the estimation of time delays in multiple-input single-output systems or nonlinear systems is either impossible or very difficult with known methods, a new method based on k nearest neighbor imputation was developed and is validated in this paper theoretically. The effectiveness of the identification algorithm is demonstrated on several simulations and on an industrial hydrocracker plant.     

Dynamic rough clustering and its applications

Dynamic data mining has gained increasing attention in the last decade. It addresses changing data structures which can be observed in many real-life applications, e.g. buying behavior of customers. As opposed to classical, i.e. static data mining where the challenge is to discover pattern inherent in given data sets, in dynamic data mining the challenge is to understand – and in some cases even predict – how such pattern will change over time. Since changes in general lead to uncertainty, the appropriate approaches for uncertainty modeling are needed in order to capture, model, and predict the respective phenomena considered in dynamic environments. As a consequence, the combination of dynamic data mining and soft computing is a very promising research area. The proposed algorithm consists of a dynamic clustering cycle when the data set will be refreshed from time to time. Within this cycle criteria check if the newly arrived data have structurally changed in comparison to the data already analyzed. If yes, appropriate actions are triggered, in particular an update of the initial settings of the cluster algorithm. As we will show, rough clustering offers strong tools to detect such changing data structures. To evaluate the proposed dynamic rough clustering algorithm it has been applied to synthetic as well as to real-world data sets where it provides new insights regarding the underlying dynamic phenomena.     

Megasonic agitation for enhanced electrodeposition of copper

In this paper we propose an agitation method based on megasonic acoustic streaming to overcome the limitations in plating rate and uniformity of the metal deposits during the electroplating process. Megasonic agitation at a frequency of 1 MHz allows the reduction of the thickness of the Nernst diffusion layer to less than 600 nm. Two applications that demonstrate the benefits of megasonic acoustic streaming are presented: the formation of uniform ultra-fine pitch flip-chip bumps and the metallisation of high aspect ratio microvias. For the latter application, a multi-physics based numerical simulation is implemented to describe the hydrodynamics introduced by the acoustic waves as they travel inside the deep microvias.