scholarly journals MODELLING OF VTS SUPERVISOR BY ALGORITHM BASED ON PETRI NET: CASE STUDY OF DOVER INCIDENT

Transport ◽  
2021 ◽  
Vol 36 (4) ◽  
pp. 305-316
Author(s):  
Rino Bošnjak ◽  
Danko Kezić ◽  
Goran Belamarić ◽  
Srećko Krile
Keyword(s):  
Real Time ◽  
Petri Net ◽  
General Idea ◽  
Human Operator ◽  
Visual Object ◽  
Hybrid Petri Net ◽  
Collision Prevention ◽  
Significant Difference ◽  
Using Data ◽  
The Right

The paper deals with collision prevention problem in maritime transport in the area of the narrow canals with predefined routes. The Dover incident, which is analysed and described in the paper, has shown that the control of the passage of ships through the critical areas must be upgraded with an automatic supervising system, which warns the human operator of incorrect ship motion and help the operator to make the right and timely decision. The general idea is to improve the safety of navigation by introduction of automatic collision prevention based on automated supervisor helping to human operator in Vessel Traffic System (VTS) control centre. The VTS supervisor automatically monitors marine traffic by using data from Automatic Radar Plotting Aid (ARPA) radar and others sensors. Such supervisor detects real time and Course Over Ground (COG) of the vessel entering a particular sector, and then estimates the required time for vessel’s passage into another sector. VTS supervisor compares the real time and estimated time of passage of the specific ship through particular sector as a part of surveillance area. In addition, it compares and monitors the deviation of the course during transition of zones (sectors). If significant difference for both values are occurred VTS supervisor triggers a time alarm or a course alarm respectively. In the paper authors have modelled and simulated collision prevention with performed by the alarm actions of VTS supervisor improved with algorithm module based on hybrid Petri net formalism and Visual Object Net ++ tool.

scholarly journals A simulation-based approach to improve decoded neurofeedback performance

2018 ◽  
Author(s):  
Ethan Oblak ◽  
James Sulzer ◽  
Jarrod Lewis-Peacock
Keyword(s):  
Real Time ◽  
Brain Activity ◽  
Processing Parameters ◽  
Orientation Tuning ◽  
Design Parameters ◽  
Visual Orientation ◽  
Brain Functions ◽  
Simulation Based ◽  
Using Data ◽  
The Right

AbstractThe neural correlates of specific brain functions such as visual orientation tuning and individual finger movements can be revealed using multivoxel pattern analysis (MVPA) of fMRI data. Neurofeedback based on these distributed patterns of brain activity presents a unique ability for precise neuromodulation. Recent applications of this technique, known as decoded neurofeedback, have manipulated fear conditioning, visual perception, confidence judgements and facial preference. However, there has yet to be an empirical justification of the timing and data processing parameters of these experiments. Suboptimal parameter settings could impact the efficacy of neurofeedback learning and contribute to the ‘non-responder’ effect. The goal of this study was to investigate how design parameters of decoded neurofeedback experiments affect decoding accuracy and neurofeedback performance. Subjects participated in three fMRI sessions: two ‘finger localizer’ sessions to identify the fMRI patterns associated with each of the four fingers of the right hand, and one ‘finger finding’ neurofeedback session to assess neurofeedback performance. Using only the localizer data, we show that real-time decoding can be degraded by poor experiment timing or ROI selection. To set key parameters for the neurofeedback session, we used offline simulations of decoded neurofeedback using data from the localizer sessions to predict neurofeedback performance. We show that these predictions align with real neurofeedback performance at the group level and can also explain individual differences in neurofeedback success. Overall, this work demonstrates the usefulness of offline simulation to improve the success of real-time decoded neurofeedback experiments.

Suicidal Ideation and Self-Determination in Institutionalized Elderly

Crisis ◽  
2001 ◽  
Vol 22 (1) ◽  
pp. 15-19 ◽  
Author(s):  
Andrée Fortin ◽  
Sylvie Lapierre ◽  
Jacques Baillargeon ◽  
Réal Labelle ◽  
Micheline Dubé ◽  
...  
Keyword(s):  
Self Determination ◽  
Current Debate ◽  
Elderly Persons ◽  
Rational Suicide ◽  
Institutionalized Elderly ◽  
Significant Difference ◽  
Social Subscale ◽  
Civil Status ◽  
The Right ◽  
Taking Action

The right to self-determination is central to the current debate on rational suicide in old age. The goal of this exploratory study was to assess the presence of self-determination in suicidal institutionalized elderly persons. Eleven elderly persons with serious suicidal ideations were matched according to age, sex, and civil status with 11 nonsuicidal persons. The results indicated that suicidal persons did not differ from nonsuicidal persons in level of self-determination. There was, however, a significant difference between groups on the social subscale. Suicidal elderly persons did not seem to take others into account when making a decision or taking action. The results are discussed from a suicide-prevention perspective.

Techniques of Viral Marketing

2019 ◽  
Vol 118 (6) ◽  
pp. 97-99
Author(s):  
Arockia Jeyasheela A ◽  
Dr.S. Chandramohan
Keyword(s):  
Social Media ◽  
Real Time ◽  
Word Of Mouth ◽  
Viral Marketing ◽  
Consumer Perception ◽  
Key Word ◽  
The Right ◽  
A Company

This study is discussed about the viral marketing. It is a one of the key success of marketing. This paper gave the techniques of viral marketing. It can be delivered word of mouth. It can be created by both the representatives of a company and consumer (individuals or communities). The right viral message with go to right consumer to the right time. Viral marketing is easy to attract the consumer. It is most important advertising to consumer. It involves consumer perception, organization contribution, blogs, SMO (Social Media Optimize), SEO (Social Engine Optimize). Principles of viral marketing are social profile gathering, Proximity Market, Real time Key word density.

DeVega versus ring annuloplasty in severe functional tricuspid insufficiency and their impact on the right ventricle

2019 ◽  
Vol 1 (4) ◽  
pp. 133-139
Author(s):  
Yasser Hamdy ◽  
Mohammed Mahmoud Mostafa ◽  
Ahmed Elminshawy
Keyword(s):  
Right Ventricular ◽  
Tricuspid Valve ◽  
Tricuspid Regurgitation ◽  
Early Postoperative Period ◽  
Tricuspid Valve Repair ◽  
Ring Annuloplasty ◽  
Significant Difference ◽  
Group A ◽  
Group B ◽  
The Right

Background: Functional tricuspid valve regurgitation secondary to left-sided valve disease is common. DeVega repair is simple, but residual regurgitation with subsequent impairment of the right ventricular function is a concern. This study aims to compare tricuspid valve repair using DeVega vs. ring annuloplasty and their impact on the right ventricle in the early postoperative period and after six months. Methods: This is a prospective cohort study of 51 patients with rheumatic heart disease who underwent tricuspid valve repair for secondary severe tricuspid regurgitation. Patients were divided into two groups: group A; DeVega repair (n=34) and group B; ring annuloplasty repair (n=17). Patients were assessed clinically and by echocardiography before discharge and after six months for the degree of tricuspid regurgitation, right ventricular diameter and tricuspid annular plane systolic excursion (TAPSE). Results: Preoperative echocardiographic assessment showed no difference in left ventricular end-systolic diameter, end-diastolic diameter, ejection fraction and right ventricular diameter, however; group A had significantly better preoperative right ventricular function measured by TAPSE (1.96 ± 0.27 vs1.75 ± 0.31 cm; p=0.02). Group B had significantly longer cardiopulmonary bypass time (127.65 ± 13.56 vs. 111.74 ± 18.74 minutes; p= 0.003) and ischemic time (99.06 ± 11.80 vs. 87.15 ± 16.01 minutes; p= 0.009). Pre-discharge, there was no statistically significant difference in the degree of tricuspid regurgitation, but the right ventricular diameter was significantly lower in group B (2.66 ± 0.41 and 2.40 ± 0.48 cm; p=0.049). After six months of follow up, the degree of tricuspid regurgitation (p= 0.029) and the right ventricular diameter were significantly lower in the ring annuloplasty group (2.56 ± 0.39 and 2.29 ± 0.44 cm; p=0.029). Although there was a statistically significant difference in preoperative TAPSE, this difference disappeared after six months. Conclusion: Both DeVega and ring annuloplasty techniques were effective in the early postoperative period, ring annuloplasty was associated with lesser residual regurgitation and better right ventricular remodeling in severe functional tricuspid regurgitation than DeVega procedure after 6-months of follow up.

scholarly journals A Prototype Quantitative Precipitation Estimation Algorithm for Operational S-Band Polarimetric Radar Utilizing Specific Attenuation and Specific Differential Phase. Part II: Performance Verification and Case Study Analysis

2019 ◽  
Vol 20 (5) ◽  
pp. 999-1014 ◽  
Author(s):  
Stephen B. Cocks ◽  
Lin Tang ◽  
Pengfei Zhang ◽  
Alexander Ryzhkov ◽  
Brian Kaney ◽  
...  
Keyword(s):  
Real Time ◽  
Heavy Precipitation ◽  
Estimation Algorithm ◽  
Differential Phase ◽  
Specific Attenuation ◽  
Quantitative Precipitation Estimation ◽  
Precipitation Estimation ◽  
Bias Ratio ◽  
Using Data ◽  
Precipitation Events

Abstract The quantitative precipitation estimate (QPE) algorithm developed and described in Part I was validated using data collected from 33 Weather Surveillance Radar 1988-Doppler (WSR-88D) radars on 37 calendar days east of the Rocky Mountains. A key physical parameter to the algorithm is the parameter alpha α, defined as the ratio of specific attenuation A to specific differential phase KDP. Examination of a significant sample of tropical and continental precipitation events indicated that α was sensitive to changes in drop size distribution and exhibited lower (higher) values when there were lower (higher) concentrations of larger (smaller) rain drops. As part of the performance assessment, the prototype algorithm generated QPEs utilizing a real-time estimated and a fixed α were created and evaluated. The results clearly indicated ~26% lower errors and a 26% better bias ratio with the QPE utilizing a real-time estimated α as opposed to using a fixed value as was done in previous studies. Comparisons between the QPE utilizing a real-time estimated α and the operational dual-polarization (dual-pol) QPE used on the WSR-88D radar network showed the former exhibited ~22% lower errors, 7% less bias, and 5% higher correlation coefficient when compared to quality controlled gauge totals. The new QPE also provided much better estimates for moderate to heavy precipitation events and performed better in regions of partial beam blockage than the operational dual-pol QPE.

The Multiple-Vortex Structure of the El Reno, Oklahoma, Tornado on 31 May 2013

2018 ◽  
Vol 146 (8) ◽  
pp. 2483-2502 ◽  
Author(s):  
Howard B. Bluestein ◽  
Kyle J. Thiem ◽  
Jeffrey C. Snyder ◽  
Jana B. Houser
Keyword(s):  
Doppler Radar ◽  
Radar Data ◽  
Rapid Scan ◽  
X Band ◽  
Close Range ◽  
Formation And Evolution ◽  
Using Data ◽  
Secondary Vortices ◽  
The Right ◽  
Gust Front

Abstract This study documents the formation and evolution of secondary vortices associated within a large, violent tornado in Oklahoma based on data from a close-range, mobile, polarimetric, rapid-scan, X-band Doppler radar. Secondary vortices were tracked relative to the parent circulation using data collected every 2 s. It was found that most long-lived vortices (those that could be tracked for ≥15 s) formed within the radius of maximum wind (RMW), mainly in the left-rear quadrant (with respect to parent tornado motion), passing around the center of the parent tornado and dissipating closer to the center in the right-forward and left-forward quadrants. Some secondary vortices persisted for at least 1 min. When a Burgers–Rott vortex is fit to the Doppler radar data, and the vortex is assumed to be axisymmetric, the secondary vortices propagated slowly against the mean azimuthal flow; if the vortex is not assumed to be axisymmetric as a result of a strong rear-flank gust front on one side of it, then the secondary vortices moved along approximately with the wind.

scholarly journals Modeling Fused Filament Fabrication using Artificial Neural Networks

2021 ◽  
Author(s):  
Paul Oehlmann ◽  
Paul Osswald ◽  
Juan Camilo Blanco ◽  
Martin Friedrich ◽  
Dominik Rietzel ◽  
...  
Keyword(s):  
Real Time ◽  
Large Scale ◽  
Cost Effective ◽  
Print Quality ◽  
Ann Model ◽  
Production Environment ◽  
Fused Filament Fabrication ◽  
Artificial Neural ◽  
Using Data ◽  
Artificial Neural Network Ann

AbstractWith industries pushing towards digitalized production, adaption to expectations and increasing requirements for modern applications, has brought additive manufacturing (AM) to the forefront of Industry 4.0. In fact, AM is a main accelerator for digital production with its possibilities in structural design, such as topology optimization, production flexibility, customization, product development, to name a few. Fused Filament Fabrication (FFF) is a widespread and practical tool for rapid prototyping that also demonstrates the importance of AM technologies through its accessibility to the general public by creating cost effective desktop solutions. An increasing integration of systems in an intelligent production environment also enables the generation of large-scale data to be used for process monitoring and process control. Deep learning as a form of artificial intelligence (AI) and more specifically, a method of machine learning (ML) is ideal for handling big data. This study uses a trained artificial neural network (ANN) model as a digital shadow to predict the force within the nozzle of an FFF printer using filament speed and nozzle temperatures as input data. After the ANN model was tested using data from a theoretical model it was implemented to predict the behavior using real-time printer data. For this purpose, an FFF printer was equipped with sensors that collect real time printer data during the printing process. The ANN model reflected the kinematics of melting and flow predicted by models currently available for various speeds of printing. The model allows for a deeper understanding of the influencing process parameters which ultimately results in the determination of the optimum combination of process speed and print quality.

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