scholarly journals Mission reliability of semi-Markov systems under generalized operational time requirements

2015 ◽  
Vol 140 ◽  
pp. 122-129 ◽  
Author(s):  
Xiaoyue Wu ◽  
Jane Hillston
Keyword(s):  
Markov Systems ◽  
Time Requirements ◽  
Operational Time

scholarly journals The expected cumulative operational time for finite semi-Markov systems and estimation

2007 ◽  
Vol 41 (4) ◽  
pp. 399-410
Author(s):  
Brahim Ouhbi ◽  
Ali Boudi ◽  
Mohamed Tkiouat
Keyword(s):  
Markov Systems ◽  
Operational Time

A randomized cross-over trial in patients suspected of PAD on diagnostic accuracy of ankle-brachial index by Doppler-based versus four-point oscillometry based measurements

VASA ◽  
2019 ◽  
Vol 48 (6) ◽  
pp. 516-522 ◽  
Author(s):  
Verena Mayr ◽  
Mirko Hirschl ◽  
Peter Klein-Weigel ◽  
Luka Girardi ◽  
Michael Kundi
Keyword(s):  
Diagnostic Accuracy ◽  
Ankle Brachial Index ◽  
Area Under The Curve ◽  
High Volume ◽  
Epidemiologic Studies ◽  
Lower Sensitivity ◽  
Oscillometric Device ◽  
Specificity And Sensitivity ◽  
Time Requirements ◽  
Peripheral Arterial

Summary. Background: For diagnosis of peripheral arterial occlusive disease (PAD), a Doppler-based ankle-brachial-index (dABI) is recommended as the first non-invasive measurement. Due to limitations of dABI, oscillometry might be used as an alternative. The aim of our study was to investigate whether a semi-automatic, four-point oscillometric device provides comparable diagnostic accuracy. Furthermore, time requirements and patient preferences were evaluated. Patients and methods: 286 patients were recruited for the study; 140 without and 146 with PAD. The Doppler-based (dABI) and oscillometric (oABI and pulse wave index – PWI) measurements were performed on the same day in a randomized cross-over design. Specificity and sensitivity against verified PAD diagnosis were computed and compared by McNemar tests. ROC analyses were performed and areas under the curve were compared by non-parametric methods. Results: oABI had significantly lower sensitivity (65.8%, 95% CI: 59.2%–71.9%) compared to dABI (87.3%, CI: 81.9–91.3%) but significantly higher specificity (79.7%, 74.7–83.9% vs. 67.0%, 61.3–72.2%). PWI had a comparable sensitivity to dABI. The combination of oABI and PWI had the highest sensitivity (88.8%, 85.7–91.4%). ROC analysis revealed that PWI had the largest area under the curve, but no significant differences between oABI and dABI were observed. Time requirement for oABI was significantly shorter by about 5 min and significantly more patients would prefer oABI for future testing. Conclusions: Semi-automatic oABI measurements using the AngER-device provide comparable diagnostic results to the conventional Doppler method while PWI performed best. The time saved by oscillometry could be important, especially in high volume centers and epidemiologic studies.

185. Short-Term Sampling Time Requirements in Rooms

2003 ◽  
Author(s):  
E. Lee ◽  
C. Feigley ◽  
J. Hussey ◽  
J. Khan ◽  
M. Ahmed
Keyword(s):  
Sampling Time ◽  
Short Term ◽  
Time Requirements

OPTIMIZATION OF MARKOV SYSTEMS OF QUEUEING WITH WAITING TIME IN THE MATLAB SYSTEM

2017 ◽  
pp. 39-47
Author(s):  
Viktor Afonin ◽  
Vladimir Valer'evich Nikulin
Keyword(s):  
Queueing System ◽  
Queueing Systems ◽  
Random Variable ◽  
Model Systems ◽  
Queuing Systems ◽  
Input Flow ◽  
Continuous Random Variable ◽  
Input Stream ◽  
Time Intervals ◽  
Markov Systems

The article focuses on attempt to optimize two well-known Markov systems of queueing: a multichannel queueing system with finite storage, and a multichannel queueing system with limited queue time. In the Markov queuing systems, the intensity of the input stream of requests (requirements, calls, customers, demands) is subject to the Poisson law of the probability distribution of the number of applications in the stream; the intensity of service, as well as the intensity of leaving the application queue is subject to exponential distribution. In a Poisson flow, the time intervals between requirements are subject to the exponential law of a continuous random variable. In the context of Markov queueing systems, there have been obtained significant results, which are expressed in the form of analytical dependencies. These dependencies are used for setting up and numerical solution of the problem stated. The probability of failure in service is taken as a task function; it should be minimized and depends on the intensity of input flow of requests, on the intensity of service, and on the intensity of requests leaving the queue. This, in turn, allows to calculate the maximum relative throughput of a given queuing system. The mentioned algorithm was realized in MATLAB system. The results obtained in the form of descriptive algorithms can be used for testing queueing model systems during peak (unchanged) loads.

scholarly journals Intelligent IoT systems for civil infrastructure health monitoring: a research roadmap

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
E. Bertino ◽  
M. R. Jahanshahi ◽  
A. Singla ◽  
R.-T. Wu
Keyword(s):  
Data Acquisition ◽  
Real Time ◽  
Original Data ◽  
Local Analysis ◽  
Civil Infrastructure ◽  
Time Requirements ◽  
Iot Devices ◽  
Learning Reinforcement ◽  
The Times ◽  
Acquisition Processes

AbstractThis paper addresses the problem of efficient and effective data collection and analytics for applications such as civil infrastructure monitoring and emergency management. Such problem requires the development of techniques by which data acquisition devices, such as IoT devices, can: (a) perform local analysis of collected data; and (b) based on the results of such analysis, autonomously decide further data acquisition. The ability to perform local analysis is critical in order to reduce the transmission costs and latency as the results of an analysis are usually smaller in size than the original data. As an example, in case of strict real-time requirements, the analysis results can be transmitted in real-time, whereas the actual collected data can be uploaded later on. The ability to autonomously decide about further data acquisition enhances scalability and reduces the need of real-time human involvement in data acquisition processes, especially in contexts with critical real-time requirements. The paper focuses on deep neural networks and discusses techniques for supporting transfer learning and pruning, so to reduce the times for training the networks and the size of the networks for deployment at IoT devices. We also discuss approaches based on machine learning reinforcement techniques enhancing the autonomy of IoT devices.

scholarly journals Design of bio-inspired binocular UAV detection system based on improved STC algorithm of scale transformation and occlusion detection

2021 ◽  
Vol 13 ◽  
pp. 175682932110048
Author(s):  
Huajun Song ◽  
Yanqi Wu ◽  
Guangbing Zhou
Keyword(s):  
Detection System ◽  
Rapid Development ◽  
Reference Value ◽  
Scale Transformation ◽  
Hardware System ◽  
Time Requirements ◽  
Aerial Vehicle ◽  
Spatio Temporal ◽  
Small Targets ◽  
Vision Detection

With the rapid development of drones, many problems have arisen, such as invasion of privacy and endangering security. Inspired by biology, in order to achieve effective detection and robust tracking of small targets such as unmanned aerial vehicles, a binocular vision detection system is designed. The system is composed of long focus and wide-angle dual cameras, servo pan tilt, and dual processors for detecting and identifying targets. In view of the shortcomings of spatio-temporal context target tracking algorithm that cannot adapt to scale transformation and easy to track failure in complex scenes, the scale filter and loss criterion are introduced to make an improvement. Qualitative and quantitative experiments show that the designed system can adapt to the scale changes and partial occlusion conditions in the detection, and meets the real-time requirements. The hardware system and algorithm both have reference value for the application of anti-unmanned aerial vehicle systems.

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