DFG Research Training Group 1387/1: dIEM oSiRiS – Integrative Development of Modelling and Simulation Methods for Regenerative Systems (DFG Graduiertenkolleg 1387/1: dIEM oSiRiS – Die integrative Entwicklung von Modellierungs- und Simulationsmethoden für regenerative Systeme)

2007 ◽  
Vol 49 (6) ◽  
Author(s):  
Adelinde Uhrmacher ◽  
Arndt Rolfs ◽  
Jana Frahm
Keyword(s):  
Large Scale ◽  
Research Training ◽  
Training Group ◽  
Modelling And Simulation ◽  
Neural Cells ◽  
Simulation Methods ◽  
Uncertain Environments ◽  
New Methodologies ◽  
Systems Modelling ◽  
Regenerative Systems

Regenerative systems are able to overcome significant perturbations, and maintain autonomously their functionality in dynamic and uncertain environments. To analyse or develop these types of systems modelling and simulation play a crucial role. However, due to the fact of being large scale and of embracing many heterogeneously acting and interacting sub-systems, they require the development of new methodologies to support a flexible modelling at different levels of organization and abstraction and an efficient execution of experiments. These methodological developments are at the core of the DFG Research Training Group dIEM oSiRiS (The Integrative Development of Modelling and Simulation Methods for Regenerative Systems). Thereby, the analysis of characteristics and requirements of regenerative systems and the evaluation of the developed concepts are based on a concrete biological regenerative system: the exploration of signalling pathways that play a significant role in the differentiation of neural cells.

scholarly journals Reducing youth suicide: systems modelling and simulation to guide targeted investments across the determinants

BMC Medicine ◽  
2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Jo-An Occhipinti ◽  
Adam Skinner ◽  
Frank Iorfino ◽  
Kenny Lawson ◽  
Julie Sturgess ◽  
...  
Keyword(s):  
Mental Health ◽  
Social Determinants ◽  
Suicide Attempts ◽  
Expert Knowledge ◽  
Population Level ◽  
Modelling And Simulation ◽  
Decision Makers ◽  
Public Health Issue ◽  
Coordinated Care ◽  
Systems Modelling

Abstract Background Reducing suicidal behaviour (SB) is a critical public health issue globally. The complex interplay of social determinants, service system factors, population demographics, and behavioural dynamics makes it extraordinarily difficult for decision makers to determine the nature and balance of investments required to have the greatest impacts on SB. Real-world experimentation to establish the optimal targeting, timing, scale, frequency, and intensity of investments required across the determinants is unfeasible. Therefore, this study harnesses systems modelling and simulation to guide population-level decision making that represent best strategic allocation of limited resources. Methods Using a participatory approach, and informed by a range of national, state, and local datasets, a system dynamics model was developed, tested, and validated for a regional population catchment. The model incorporated defined pathways from social determinants of mental health to psychological distress, mental health care, and SB. Intervention scenarios were investigated to forecast their impact on SB over a 20-year period. Results A combination of social connectedness programs, technology-enabled coordinated care, post-attempt assertive aftercare, reductions in childhood adversity, and increasing youth employment projected the greatest impacts on SB, particularly in a youth population, reducing self-harm hospitalisations (suicide attempts) by 28.5% (95% interval 26.3–30.8%) and suicide deaths by 29.3% (95% interval 27.1–31.5%). Introducing additional interventions beyond the best performing suite of interventions produced only marginal improvement in population level impacts, highlighting that ‘more is not necessarily better.’ Conclusion Results indicate that targeted investments in addressing the social determinants and in mental health services provides the best opportunity to reduce SB and suicide. Systems modelling and simulation offers a robust approach to leveraging best available research, data, and expert knowledge in a way that helps decision makers respond to the unique characteristics and drivers of SB in their catchments and more effectively focus limited health resources.

scholarly journals CrisDi School: disseminating crystallography in Piedmont, Italy

2014 ◽  
Vol 70 (a1) ◽  
pp. C1277-C1277
Author(s):  
Domenica Marabello ◽  
Angelo Agostino ◽  
Piera Benna ◽  
Giovanna Dinardo ◽  
Carlo Lamberti ◽  
...  
Keyword(s):  
Large Scale ◽  
Kinetic Studies ◽  
Research Centre ◽  
Main Task ◽  
X Rays ◽  
X Ray Diffraction ◽  
Time Resolved ◽  
New Methodologies ◽  
The University ◽  
Basic Level

The Interdepartmental Research Centre for the Development of Crystallography (CrisDi) aims to be an institution of reference for researchers at the University of Turin interested on the field of diffraction (X-rays, neutrons and electrons), to promote the knowledge and dissemination of crystallography, and to facilitate the access to available laboratory instrumentation (diffractometers and TEM) and to large scale facilities (synchrotron and neutron sources). CrisDi hosts scientists with interest in the fields of solid state chemistry and physics, organic, inorganic, organometallic and theoretical chemistry, mineralogy, biology, pharmaceutical and agricultural sciences. The Centre encourages the design and the development of new methodologies and applications, and supports the enhancement of the available instruments. The submission of proposals at large scale instruments is encouraged specially for young researchers and PhD students. The cultural and scientific interchange among crystallographers coming from different disciplines is strongly encouraged by CrisDi. A main task of the CrisDi is the annual organization of a post-grade level School with a series of courses dedicated to: (i) basic level crystallography (symmetry, theory of diffraction, crystal-chemistry), diffraction techniques (single crystal and powder X-ray diffraction, neutron and electron scattering); (ii) advanced level (high temperature and high pressure structural studies, macromolecular crystallography, time resolved crystallography and kinetic studies); (iii) spectroscopic approaches (XAFS, XANES, XES and NMR) in crystallography. The school, which is held every year in May for about 20 ECTS equivalent, has no tuition fees and is also open to non-academia people.

scholarly journals Voice Identification Using MFCC and Vector Quantization

2020 ◽  
Vol 17 (3(Suppl.)) ◽  
pp. 1019
Author(s):  
Bassel Alkhatib ◽  
Mohammad Madian Waleed Kamal Eddin
Keyword(s):  
Vector Quantization ◽  
Speech Processing ◽  
Large Scale ◽  
Feature Matching ◽  
Speaker Identification ◽  
Voice Recognition ◽  
Security Systems ◽  
Voice Identification ◽  
New Methodologies ◽  
Quick Search

The speaker identification is one of the fundamental problems in speech processing and voice modeling. The speaker identification applications include authentication in critical security systems and the accuracy of the selection. Large-scale voice recognition applications are a major challenge. Quick search in the speaker database requires fast, modern techniques and relies on artificial intelligence to achieve the desired results from the system. Many efforts are made to achieve this through the establishment of variable-based systems and the development of new methodologies for speaker identification. Speaker identification is the process of recognizing who is speaking using the characteristics extracted from the speech's waves like pitch, tone, and frequency. The speaker's models are created and saved in the system environment and used to verify the identity required by people accessing the systems, which allows access to various services that are controlled by voice, speaker identification involves two main parts: the first part is the feature extraction and the second part is the feature matching.

Atmospheric monitoring with a new GNSS network in the south-central Andes

2021 ◽  
Author(s):  
Nikolaos Antonoglou ◽  
Kyriakos Balidakis ◽  
Bodo Bookhagen ◽  
Galina Dick ◽  
Florian Zus ◽  
...  
Keyword(s):  
Research Training ◽  
Training Group ◽  
Satellite System ◽  
Central Andes ◽  
Temporal Variations ◽  
Mountain Range ◽  
Spatial Correlations ◽  
The South ◽  
Climate Conditions ◽  
South Central

<p>The Central Andes are characterized by a steep climatic and environmental gradient with large spatial and temporal variations of associated hydrological parameters. There are two main atmospheric processes that influence climate conditions in our study area in northwestern Argentina: the South American Monsoon System that transports moisture via the low-level jet and the orographic barrier of the Eastern Cordillera that forces focused rainfall at the windward facing slopes.<br>As part of the International Research Training Group-StRATEGy project, our research aims at monitoring integrated water vapour (IWV) in the south-central Andes, in order to track moisture propagation. In accordance with the needs of the research, we processed data from two new Global Navigation Satellite System (GNSS) ground stations that were installed in spring 2019 along with - already calculated - solutions that were derived from an existing network. We used 10 year-long time-series from 31 stations spanning an altitude range from 198 to 5141m asl and stretching from the mountain front to the interior of the mountain range. This enhanced network helped us to examine spatial correlations, as well as differences in behaviour of the IWV across the climatic gradient. Moreover, we retrieved the gradients of the IWV at single positions, in order to study seasonal correlations between wind and gradient direction.</p>

scholarly journals Backbone—An Adaptable Energy Systems Modelling Framework

Energies ◽  
2019 ◽  
Vol 12 (17) ◽  
pp. 3388 ◽  
Author(s):  
Niina Helistö ◽  
Juha Kiviluoma ◽  
Jussi Ikäheimo ◽  
Topi Rasku ◽  
Erkka Rinne ◽  
...  
Keyword(s):  
Power Plants ◽  
Large Scale ◽  
Unit Commitment ◽  
Energy Systems ◽  
Mixed Integer ◽  
Investment Planning ◽  
Planning And Scheduling ◽  
Modelling Framework ◽  
Wide Range ◽  
Systems Modelling

Backbone represents a highly adaptable energy systems modelling framework, which can be utilised to create models for studying the design and operation of energy systems, both from investment planning and scheduling perspectives. It includes a wide range of features and constraints, such as stochastic parameters, multiple reserve products, energy storage units, controlled and uncontrolled energy transfers, and, most significantly, multiple energy sectors. The formulation is based on mixed-integer programming and takes into account unit commitment decisions for power plants and other energy conversion facilities. Both high-level large-scale systems and fully detailed smaller-scale systems can be appropriately modelled. The framework has been implemented as the open-source Backbone modelling tool using General Algebraic Modeling System (GAMS). An application of the framework is demonstrated using a power system example, and Backbone is shown to produce results comparable to a commercial tool. However, the adaptability of Backbone further enables the creation and solution of energy systems models relatively easily for many different purposes and thus it improves on the available methodologies.

scholarly journals Integrity and Collaboration in Dynamic Sensor Networks

Sensors ◽  
2018 ◽  
Vol 18 (7) ◽  
pp. 2400 ◽  
Author(s):  
Steffen Schön ◽  
Claus Brenner ◽  
Hamza Alkhatib ◽  
Max Coenen ◽  
Hani Dbouk ◽  
...  
Keyword(s):  
Sensor Networks ◽  
Urban Areas ◽  
Research Training ◽  
Training Group ◽  
Autonomous Driving ◽  
Global Navigation Satellite Systems ◽  
Satellite Systems ◽  
Global Navigation Satellite ◽  
Map Data ◽  
Dynamic Sensor Networks

Global Navigation Satellite Systems (GNSS) deliver absolute position and velocity, as well as time information (P, V, T). However, in urban areas, the GNSS navigation performance is restricted due to signal obstructions and multipath. This is especially true for applications dealing with highly automatic or even autonomous driving. Subsequently, multi-sensor platforms including laser scanners and cameras, as well as map data are used to enhance the navigation performance, namely in accuracy, integrity, continuity and availability. Although well-established procedures for integrity monitoring exist for aircraft navigation, for sensors and fusion algorithms used in automotive navigation, these concepts are still lacking. The research training group i.c.sens, integrity and collaboration in dynamic sensor networks, aims to fill this gap and to contribute to relevant topics. This includes the definition of alternative integrity concepts for space and time based on set theory and interval mathematics, establishing new types of maps that report on the trustworthiness of the represented information, as well as taking advantage of collaboration by improved filters incorporating person and object tracking. In this paper, we describe our approach and summarize the preliminary results.

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