eFlux: Simple Automatic Adaptation for Environmentally Powered Devices

2006 ◽  
Author(s):  
J. Sorber ◽  
A. Kostadinov ◽  
M. Brennan ◽  
M. Corner ◽  
E. Berger
Keyword(s):  
Automatic Adaptation

Study On Automatic Adaptation for Control-Oriented Model of Advanced Diesel Engine

2021 ◽  
Author(s):  
Shunki Nishii ◽  
Yudai Yamasaki
Keyword(s):  
Operating Conditions ◽  
Physical Models ◽  
Model Parameters ◽  
Training Methods ◽  
Model Based Control ◽  
Practical Applications ◽  
Model Based ◽  
Automatic Adaptation ◽  
Automobile Engines ◽  
Adaptation Method

Abstract To achieve high thermal efficiency and low emission in automobile engines, advanced combustion technologies using compression autoignition of premixtures have been studied, and model-based control has attracted attention for their practical applications. Although simplified physical models have been developed for model-based control, appropriate values for their model parameters vary depending on the operating conditions, the engine driving environment, and the engine aging. Herein, we studied an onboard adaptation method of model parameters in a heat release rate (HRR) model. This method adapts the model parameters using neural networks (NNs) considering the operating conditions and can respond to the driving environment and the engine aging by training the NNs onboard. Detailed studies were conducted regarding the training methods. Furthermore, the effectiveness of this adaptation method was confirmed by evaluating the prediction accuracy of the HRR model and model-based control experiments.

scholarly journals AdaptFlow: Protocol-based Medical Treatment Using Adaptive Workflows

2005 ◽  
Vol 44 (01) ◽  
pp. 80-88 ◽  
Author(s):  
R. Mueller ◽  
E. Rahm ◽  
J. Ramsch ◽  
B. Heller ◽  
M. Loeffler ◽  
...  
Keyword(s):  
Evaluation Studies ◽  
Hybrid Approach ◽  
Workflow Management ◽  
Rule Base ◽  
Consultation System ◽  
Number Of Patients ◽  
Automatic Adaptation ◽  
The Status ◽  
Trial Protocols ◽  
Workflow Adaptation

Summary Objectives: In many medical domains investigator-initiated clinical trials are used to introduce new treatments and hence act as implementations of guideline-based therapies. Trial protocols contain detailed instructions to conduct the therapy and additionally specify reactions to exceptional situations (for instance an infection or a toxicity). To increase quality in health care and raise the number of patients treated according to trial protocols, a consultation system is needed that supports the handling of the complex trial therapy processes efficiently. Our objective was to design and evaluate a consultation system that should 1) observe the status of the therapies currently being applied, 2) offer automatic recognition of exceptional situations and appropriate decision support and 3) provide an automatic adaptation of affected therapy processes to handle exceptional situations. Methods: We applied a hybrid approach that combines process support for the timely and efficient execution of the therapy processes as offered by workflow management systems with a knowledge and rule base and a mechanism for dynamic workflow adaptation to change running therapy processes if induced by changed patient condition. Results and Conclusions: This approach has been implemented in the AdaptFlow prototype. We performed several evaluation studies on the practicability of the approach and the usefulness of the system. These studies show that the AdaptFlow prototype offers adequate support for the execution of real-world investigator-initiated trial protocols and is able to handle a large number of exceptions.

scholarly journals User Interfaces: A Proposal for Automatic Adaptation

2003 ◽  
pp. 263-266
Author(s):  
Montserrat Sendín ◽  
Jesús Lorés ◽  
Francisco Montero ◽  
Víctor López ◽  
Pascual González
Keyword(s):  
User Interfaces ◽  
Automatic Adaptation

Automatic adaptation of the momel F0 stylisation algorithm to new corpora

2004 ◽  
Author(s):  
Salma Mouline ◽  
Olivier Boeffard ◽  
Paul Bagshaw
Keyword(s):  
Automatic Adaptation

Machine Learning analysis of seismic signals recorded at Stromboli Volcano

2021 ◽  
Author(s):  
Darius Fenner ◽  
Georg Rümpker ◽  
Horst Stöcker ◽  
Megha Chakraborty ◽  
Wei Li ◽  
...  
Keyword(s):  
Machine Learning ◽  
Seismic Data ◽  
Noise Level ◽  
Volcanic Eruptions ◽  
Time Varying ◽  
Seismic Signals ◽  
Machine Learning Model ◽  
Automatic Adaptation ◽  
Consistent Manner ◽  
Recent Developments

<p>At Stromboli, minor volcanic eruptions occur at time intervals of approximately five minutes on average, making it one of the most active volcanoes worldwide. In addition to these mostly harmless events, there are also stronger eruptions and paroxysms which pose a serious threat to residents and tourists. In light of recent developments in Machine Learning, this study attempts to apply these new tools for the analysis of the time-varying volcanic eruptions at Stromboli. As input for the Machine-Learning approach, we use continuous recordings of seismic signals from two seismometers on the island. The data is available from IRIS  and includes records starting in 2012 up to the present. </p><p>One primary challenge is to label and classify the data, i.e., to discriminate events of interest from noise. The variety of signal-appearance in the recorded data is wide, in some periods the events are clearly distinguishable from noise whereas, in other cases relevant events are obscured by the high noise level. To enable the event-detection in all cases, we developed the following algorithm: in the first step, the seismic data is pre-processed with an STA/LTA-Filter, which allows detection of events based on a prominence threshold. However, due to the diversity of signal patterns, a fixed set of hyperparameters (STA- and LTA-window length, prominence threshold, correlation coefficient) fails to reliably extract the relevant events in a consistent manner. Therefore, the (time-varying) noise level of the recordings is used as an additional key indicator. After this, the hyperparameters are optimized. The automatic adaptation is then used for labeling the continuous seismic data.</p><p>After extracting the events based on this approach, a machine learning model is trained to analyze the recordings for possible patterns in the interval times and the event amplitudes. This study is expected to provide constraints on the possibility to detect complex time-dependent patterns of the eruption history at Stromboli.</p>

The Academic Study of French Civilization

PMLA ◽  
1915 ◽  
Vol 30 (3) ◽  
pp. 614-628
Author(s):  
Albert Léon Guérard
Keyword(s):  
Human Life ◽  
Human Society ◽  
Primary Concern ◽  
German Empire ◽  
Insurance System ◽  
The Past ◽  
Political Events ◽  
Automatic Adaptation ◽  
Academic Study

If history is to giv us a tru picture of human life in the past, it cannot limit itself to political events. The chief end of man never was to frame, uphold, and overthro governments, stil les to wage war and sign treaties. These ar accidents or epiphenomena. Man's primary concern is and was from the first his daily fight for existence, the necessity of getting food and shelter, the desire of getting them with a minimum of painful exertion. Man does not merely adapt himself to his surroundings: he attempts to alter his surroundings so as to suit himself. Thus he creates new conditions from which new problems arise. Human society groes ever farther away from that brutish state of automatic adaptation which poets call the Erthly Paradise. From the erliest stone implement to the aeroplane, from the first concerted hunt to the elaborate insurance system of the German Empire, we see the progres of this warfare against nature. The result of these efforts is what we understand by civilization.

Automatic 3D Face Model Adaptation with Two Complexity Modes for Visual Communication

2011 ◽  
pp. 295-316
Author(s):  
Markus Kampmann ◽  
Liang Zhang
Keyword(s):  
Visual Communication ◽  
Low Complexity ◽  
Facial Features ◽  
Model Adaptation ◽  
High Complexity ◽  
Face Model ◽  
3D Face ◽  
Automatic Adaptation ◽  
Complete Framework ◽  
Mode A

This chapter introduces a complete framework for automatic adaptation of a 3D face model to a human face for visual communication applications like video conferencing or video telephony. First, facial features in a facial image are estimated. Then, the 3D face model is adapted using the estimated facial features. This framework is scalable with respect to complexity. Two complexity modes, a low complexity and a high complexity mode, are introduced. For the low complexity mode, only eye and mouth features are estimated and the low complexity face model Candide is adapted. For the high complexity mode, a more detailed face model is adapted, using eye and mouth features, eyebrow and nose features, and chin and cheek contours. Experimental results with natural videophone sequences show that with this framework automatic 3D face model adaptation with high accuracy is possible.

Sign in / Sign up

Export Citation Format

Share Document