23 research outputs found
Informatik auf den Punkt gebracht: Informatik fĂĽr Life Sciences Studierende und andere Nicht-Informatiker
Introduction
Dieses Lehrbuch richtet sich an Studierende von fachfremden Studiengängen mit Informatikanteilen. Ein besonderer Schwerpunkt liegt dabei auf den sogenannten Lebenswissenschaften, wie Medizintechnik, Rettungsingenieurwesen, Biotechnologie, Umwelttechnik oder Verfahrenstechnik. Das Lehrbuch eignet sich für Leser in Studium und Praxis, die sich einen Einstieg in die Informatik verschaffen wollen. Die Besonderheit dieses Buches liegt in der problembasierten Herangehensweise, sowie der nach verschiedenen Taxonomiestufen konzipierten Übungsaufgaben.
Der Inhalt
- EinfĂĽhrung in die Informatik
- Grundlagen der Programmierung in C++
- Arrays und Pointer
- Dateioperationen
- Objektorientierung und Vererbun
A Topology-Based QoS Adaptive Mobility Prediction Scheme For Cellular Networks
This paper presents a QOS adaptive cell cluster generation scheme for mobile communication systems of the 3rd and 4th generation which is used to predict the mobiles future path with a given prediction accuracy. Based on the prediction by partial match algorithm it combines the statistical information derived from the users movement history with topological information about the cell region to predict a future cell cluster to be visited by that user. Numerical results show that the new scheme is robust against insufficient statistical information and has an improvement over schemes only utilizing statistical data derived from handover information
Simulationsbasierte Trainings in der medizinischen Ausbildung : Szenarien und Anwendungen am Beispiel von Massenanfällen von Verletzten
AlternativeReviewe
An analysis of movement patterns in mass casualty incident simulations
Background!#!Mass casualty incidents (MCI) such as train or bus crashes, explosions, collapses of buildings, or terrorist attacks result in rescue teams facing many victims and in huge challenges for hospitals. Simulations are performed to optimize preparedness for MCI. To maximize the benefits of MCI simulations, it is important to collect large amounts of information. However, a clear concept and standardization of a data-driven post-exercise evaluation and debriefing are currently lacking.!##!Methods!#!GPS data loggers were used to track the trajectories of patients, medics, and paramedics in two simulated MCI scenarios using real human actors. The distribution of patients over the treatment area and their time of arrival at the hospital were estimated to provide information on the quality of triage and for debriefing purposes.!##!Results!#!The results show the order in which patients have been treated and the time for the individual arrivals as an indicator for the triage performance. The distribution of patients at the accident area suggested initial confusion and unclear orders for the placement of patients with different grades of injury that can be used for post-exercise debriefing. The dynamics of movement directions allowed to detect group behavior during different phases of the MCI.!##!Conclusions!#!Results indicate that GPS data loggers can be used to collect precise information about the trajectories of patients and rescue teams at an MCI simulation without interfering with the realism of the simulation. The exact sequence of the deliverance of patients of different triage categories to their appropriate destinations can be used to evaluate team performance for post-exercise debriefing. Future MCI simulations are planned to validate the use of GPS loggers by providing 'hot-debrief' immediately after the MCI simulation and to explore ways in which group detection can provide relevant information for post-exercise evaluations.!##!Trial registration!#!Not applicable
A Complexity-Effective Version of Montgomery’s Algorithm
Abstract--A new version of Montgomery’s algorithm for modular multiplication of large integers and its implementation in hardware is presented. It has been designed to meet the predominant requirements of most modern devices: small chip area and low power consumption. The algorithm is superior to the original method by a factor of 2, with respect to both area and latency. The new method has a simple structure. It requires a small amount of precomputation and storage in order to reduce the number of neccessary additions by a factor of 2. Index terms—modulo multiplication, carry save addition, Montgomery algorithm A