Closed-Loop Systems Engineering—Supporting Smart System Design Adaption by Integrating MBSE and IoT

2021 ◽  
pp. 203-214
Author(s):  
Thomas Dickopf ◽  
Sven Forte ◽  
Christo Apostolov ◽  
Jens C. Göbel
Keyword(s):  
System Design ◽  
Systems Engineering ◽  
Closed Loop ◽  
Smart System ◽  
Closed Loop Systems

Interface Management with Closed-Loop Systems Engineering (CLOSE)

2018 ◽  
Author(s):  
Marco Di Maio ◽  
Linus Atorf ◽  
Ulrich Dahmen ◽  
Michael Schluse ◽  
Juergen Rossmann ◽  
...  
Keyword(s):  
Systems Engineering ◽  
Closed Loop ◽  
Interface Management ◽  
Closed Loop Systems

METHOD OF SYNTHESIS OF CLOSED-LOOP SYSTEMS OF ACTIVE SHIELDING MAGNETIC FIELD OF POWER TRANSMISSION LINES

2016 ◽  
Vol 2016 (4) ◽  
pp. 8-10 ◽  
Author(s):  
B.I. Kuznetsov ◽  
◽  
A.N. Turenko ◽  
T.B. Nikitina ◽  
A.V. Voloshko ◽  
...  
Keyword(s):  
Magnetic Field ◽  
Transmission Lines ◽  
Closed Loop ◽  
Power Transmission ◽  
Power Transmission Lines ◽  
Closed Loop Systems ◽  
Active Shielding

102-LB: Cross-Study Comparisons Done Right: An Illustration Using Two Pivotal Trials of Closed-Loop Systems

Diabetes ◽  
2020 ◽  
Vol 69 (Supplement 1) ◽  
pp. 102-LB
Author(s):  
MARC D. BRETON ◽  
ROY BECK ◽  
RICHARD M. BERGENSTAL ◽  
BORIS KOVATCHEV
Keyword(s):  
Closed Loop ◽  
Closed Loop Systems

Time in range for multiple technologies in type 1 diabetes: a systematic review and network meta-analysis

2020 ◽  
Author(s):  
Anthony Pease ◽  
Clement Lo ◽  
Arul Earnest ◽  
Velislava Kiriakova ◽  
Danny Liew ◽  
...  
Keyword(s):  
Systematic Review ◽  
Type 1 Diabetes ◽  
Closed Loop ◽  
Meta Analysis ◽  
Management Strategies ◽  
Glucose Testing ◽  
Closed Loop Systems ◽  
Percent Time ◽  
Time In Range

<b>Background: </b>Time-in-range is a key glycaemic metric, and comparisons of management technologies for this outcome are critical to guide device selection. <p><b> </b></p> <p><b>Purpose: </b>We conducted a systematic review and network meta-analysis to compare and rank technologies for time in glycaemic ranges.</p> <p> </p> <p><b>Data sources: </b>We searched All Evidenced Based Medicine Reviews, CINAHL, EMBASE, MEDLINE, MEDLINE In-Process and other non-indexed citations, PROSPERO, PsycINFO, PubMed, and Web of Science until 24 April, 2019.</p> <p> </p> <p><b>Study selection: </b>We included randomised controlled trials <u>></u>2 weeks duration comparing technologies for management of type 1 diabetes in adults (<u>></u>18 years of age), excluding pregnant women. </p> <p> </p> <p><b>Data extraction: </b>Data were extracted using a predefined template. Outcomes were percent time with sensor glucose levels 3.9–10.0mmol/l (70–180mg/dL), >10.0mmol/L (180mg/dL), and <3.9mmol/L (70mg/dL). </p> <p><b> </b></p> <p><b>Data synthesis: </b>We identified 16,772 publications, of which 14 eligible studies compared eight technologies comprising 1,043 participants. Closed loop systems lead to greater percent time-in-range than any other management strategy and was 17.85 (95% predictive interval [PrI] 7.56–28.14) higher than usual care of multiple daily injections with capillary glucose testing. Closed loop systems ranked best for percent time-in-range or above range utilising surface under the cumulative ranking curve (SUCRA–98.5 and 93.5 respectively). Closed loop systems also ranked highly for time below range (SUCRA–62.2). </p> <p><b> </b></p> <p><b>Limitations: </b>Overall risk of bias ratings were moderate for all outcomes. Certainty of evidence was very low.</p> <p><b> </b></p> <p><b>Conclusions: </b>In the first integrated comparison of multiple management strategies considering time-in-range, we found that the efficacy of closed loop systems appeared better than all other approaches. </p>

Identifiability of Time-Continuous ΜIMO Closed Loop Systems

1982 ◽  
Vol 15 (4) ◽  
pp. 881-886 ◽  
Author(s):  
G. Bretthauer
Keyword(s):  
Closed Loop ◽  
Closed Loop Systems
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