scholarly journals Reliability Analysis of the Proactive Transmission of Replicated Frames Mechanism over Time-Sensitive Networking

Sensors ◽  
2021 ◽  
Vol 21 (24) ◽  
pp. 8427
Author(s):  
Inés Álvarez ◽  
Manuel Barranco ◽  
Julián Proenza
Keyword(s):  
Network Architecture ◽  
Cost Effective ◽  
Model Checker ◽  
Effective Solution ◽  
Parametric Sensitivity ◽  
Time Redundancy ◽  
Layer 2 ◽  
Ethernet Networks ◽  
Hard Real Time ◽  
Over Time

The Time-Sensitive Networking (TSN) Task Group has standardised different mechanisms to provide Ethernet with hard real-time guarantees and reliability in layer 2 of the network architecture. Specifically, TSN proposes using space redundancy to increase the reliability of Ethernet networks, but using space redundancy to tolerate temporary faults is not a cost-effective solution. For this reason, we propose to use time redundancy to tolerate temporary faults in the links of TSN-based networks. Specifically, in previous works we proposed the Proactive Transmission of Replicated Frames (PTRF) mechanism to tolerate temporary faults in the links. Now, in this work we present a series of models of TSN and PTRF developed using PRISM, a probabilistic model checker that can be used to evaluate the reliability of systems. After that, we carry out a parametric sensitivity analysis of the reliability achievable by TSN and PTRF and we show that we can increase the reliability of TSN-based networks using PTRF to tolerate temporary faults in the links of TSN networks. This is the first work that presents a quantitative analysis of the reliability of TSN networks.

scholarly journals Gas Detection and Identification Using Multimodal Artificial Intelligence Based Sensor Fusion

2021 ◽  
Vol 4 (1) ◽  
pp. 3
Author(s):  
Parag Narkhede ◽  
Rahee Walambe ◽  
Shruti Mandaokar ◽  
Pulkit Chandel ◽  
Ketan Kotecha ◽  
...  
Keyword(s):  
Sensor Fusion ◽  
Network Architecture ◽  
Cost Effective ◽  
Sensor Data ◽  
Dense Layer ◽  
Gaseous Emissions ◽  
Multiple Sensors ◽  
Single Output ◽  
Novel Approach ◽  
Single Sensor

With the rapid industrialization and technological advancements, innovative engineering technologies which are cost effective, faster and easier to implement are essential. One such area of concern is the rising number of accidents happening due to gas leaks at coal mines, chemical industries, home appliances etc. In this paper we propose a novel approach to detect and identify the gaseous emissions using the multimodal AI fusion techniques. Most of the gases and their fumes are colorless, odorless, and tasteless, thereby challenging our normal human senses. Sensing based on a single sensor may not be accurate, and sensor fusion is essential for robust and reliable detection in several real-world applications. We manually collected 6400 gas samples (1600 samples per class for four classes) using two specific sensors: the 7-semiconductor gas sensors array, and a thermal camera. The early fusion method of multimodal AI, is applied The network architecture consists of a feature extraction module for individual modality, which is then fused using a merged layer followed by a dense layer, which provides a single output for identifying the gas. We obtained the testing accuracy of 96% (for fused model) as opposed to individual model accuracies of 82% (based on Gas Sensor data using LSTM) and 93% (based on thermal images data using CNN model). Results demonstrate that the fusion of multiple sensors and modalities outperforms the outcome of a single sensor.

scholarly journals Tracking red deer population size using deterministic cohort analysis

2021 ◽  
Author(s):  
Valerio Donini ◽  
Luca Corlatti ◽  
Luca Pedrotti
Keyword(s):  
Population Size ◽  
Cervus Elaphus ◽  
Red Deer ◽  
Cohort Analysis ◽  
Cost Effective ◽  
Natural Mortality ◽  
Relative Index ◽  
Deer Population ◽  
Monitoring Tools ◽  
Over Time

AbstractReliable and cost-effective monitoring tools to track population size over time are of key importance for wildlife management and conservation. Deterministic cohort analysis may be used to this aim, especially in hunted populations, but it requires that all mortality events are recorded and that individual age at death is known exactly. In this study, we investigated the reliability of cohort analysis as a relative index to track over-time variation in red deer (Cervus elaphus) abundance, in the absence of exact information about natural mortality and age. Visual tooth inspection was used to age 18,390 individuals found dead or hunted between 1982 and 2020 within the Trentino sector of the Stelvio National Park and the Val di Sole hunting district (Central Italian Alps). Temporal trend of reconstructed population size was checked using spring spotlight counts as a benchmark, through the Buishand range test and a linear model. Our results showed a significant and positive relationship between reconstructed population size and spring spotlight counts between 1982 and 2013, suggesting that cohort analysis could reliably track red deer population trend up to 7 years in the past. With a relative error of  +  1.1 (SD  =  1.5) years in the estimation of age, and fairly stable hunting pressure, our results support the use of deterministic cohort analysis as a relative index of abundance for monitoring red deer over time, even in the absence of exact information about natural mortality. Under violation of assumptions, however, the performance of deterministic reconstruction should be carefully inspected at the management scale.

An investigation of a cost-effective solution for multimedia medical information management

1995 ◽  
Vol 28 (6) ◽  
pp. 361-376 ◽  
Author(s):  
Ken Chee Keung Law ◽  
Horace Ho Shing Ip ◽  
Siu Lok Chan
Keyword(s):  
Information Management ◽  
Medical Information ◽  
Cost Effective ◽  
Effective Solution

Streamlining the GIS to CAD Workflow for Automated Pipeline Alignment Sheet Generation

2020 ◽  
Author(s):  
Gyanendra Gurung ◽  
Kshama Roy
Keyword(s):  
Information System ◽  
Geographic Information System ◽  
Spatial Analysis ◽  
Cost Effective ◽  
Systematic Errors ◽  
Effective Solution ◽  
Gis Integration ◽  
Automated Pipeline ◽  
Central Database ◽  
User Friendly

Abstract The use of Geographic Information System (GIS) in managing pipeline database and automating routine engineering processes has become a standard practice in the pipeline industry. While maintaining a central database provides security, integrity, and easy management of data throughout the pipeline’s lifecycle, GIS enables spatial analysis of pipeline data in addition to streamlining access and visualization of results. One of the major benefits of GIS integration lies in the ease of automating the alignment sheet generation for pipelines. This paper introduces a simplified pipeline alignment sheet generation workflow using GIS datasets to produce highly customizable alignment sheets in AutoCAD, a much-preferred format in the pipeline industry. By utilizing existing GIS and AutoCAD features to generate the alignment sheet, writing complicated geo-processing or plotting algorithms is minimized, which in turn reduces the risks of committing any systematic errors. This robust and user-friendly workflow not only ensures safety but also leads to a cost-effective solution.

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