Operational river velocity surveillance at whole reach-scale by implementing time-of-arrival algorithms on upstream-downstream conductivity signals

2014 ◽  
pp. 1987-1994
Author(s):  
D Petrovic ◽  
I Vulpe ◽  
J Vanderborght ◽  
M Verbanck
Keyword(s):  
Time Of Arrival ◽  
River Velocity

Analytical support to organization system of children transportation in long-distance trains

2018 ◽  
Vol 77 (6) ◽  
pp. 232-330
Author(s):  
A. V. Komissarov ◽  
E. A. Makarova ◽  
S. V. Muktepavel ◽  
I. A. Nestrakhov ◽  
I. N. Spesivtseva
Keyword(s):  
Time Of Arrival ◽  
Control Analysis ◽  
Social Significance ◽  
Passenger Cars ◽  
Long Distance ◽  
Number Of Children ◽  
Passenger Traffic ◽  
Destination Station ◽  
Increasing Demand ◽  
Management Functions

Abstract. In modern conditions for passenger complex of Russian Railways, important tasks include improvement of transportation quality, maintenance of stable positions in a competitive environment and increasing demand. To address these issues, a customer-oriented approach is applied based on the segmentation of transport market in relation to certain groups of passengers. Performance of children's transportation is of particular relevance and social significance. Railways are charged with a huge range of work, including sale of travel documents, preparation and equipping of passenger cars, provision of food during the trip, instructing workers, ensuring security during the embarkation/disembarkation of passengers, etc. Children can travel as individually with accompanying persons and as part of organized groups. Processes of planning, organizing, monitoring the transportation of this age category of passengers are associated with the analysis of a large amount of reference and regulatory and reporting documentation. On the basis of the ACS “Express-3”, a program-analytical complex “Children's transportation” was developed and implemented, which allows to receive data at the regional and network levels in the operational (train number, day) and statistical (period of dates, month) modes. This information technology provides analytical support for key transportation management functions — planning, control, analysis. Planning of transportation of organized children's groups is carried out on the basis of a study of the dynamics of data on the number of applications received and travel documents issued, determining the routes of trains, periods of the highest intensity of passenger traffic, obtaining information about the stations of embarkation and disembarkation. To perform the functions of monitoring the embarkation and disembarkation at the destination station of groups of children, the employees involved receive information on the train number, car number, date and time of arrival, number of children in the group using the Children's Transportation software. For the analysis of transportation of children's age categories, a functional has been developed that ensures the construction of aggregated reporting based on trains data that completed the trip. Users receive reporting information in table form, including “strict” (designed according to the approved layout) and “flexible” forms (construction is performed according to specified parameters). Software and analytical complex is designed for managers and specialists of the passenger unit of the JSC “Russian Railways”, has a modular principle of increasing functionality and provides a solution to current problems in the system of organizing children's transport service.

Prediction of aircraft estimated time of arrival using machine learning methods

2021 ◽  
pp. 1-15
Author(s):  
O. Basturk ◽  
C. Cetek
Keyword(s):  
Machine Learning ◽  
Web Application ◽  
Absolute Error ◽  
Machine Learning Algorithms ◽  
Weather Data ◽  
Time Of Arrival ◽  
Learning Models ◽  
Trajectory Data ◽  
Different Sources ◽  
Machine Learning Models

ABSTRACT In this study, prediction of aircraft Estimated Time of Arrival (ETA) is proposed using machine learning algorithms. Accurate prediction of ETA is important for management of delay and air traffic flow, runway assignment, gate assignment, collaborative decision making (CDM), coordination of ground personnel and equipment, and optimisation of arrival sequence etc. Machine learning is able to learn from experience and make predictions with weak assumptions or no assumptions at all. In the proposed approach, general flight information, trajectory data and weather data were obtained from different sources in various formats. Raw data were converted to tidy data and inserted into a relational database. To obtain the features for training the machine learning models, the data were explored, cleaned and transformed into convenient features. New features were also derived from the available data. Random forests and deep neural networks were used to train the machine learning models. Both models can predict the ETA with a mean absolute error (MAE) less than 6min after departure, and less than 3min after terminal manoeuvring area (TMA) entrance. Additionally, a web application was developed to dynamically predict the ETA using proposed models.

scholarly journals TDMA Datalink Cooperative Navigation Algorithm Based on INS/JTIDS/BA

Electronics ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 782
Author(s):  
Shuo Cao ◽  
Honglei Qin ◽  
Li Cong ◽  
Yingtao Huang
Keyword(s):  
Distribution System ◽  
Large Scale ◽  
Satellite System ◽  
Time Of Arrival ◽  
Military Operations ◽  
Position Information ◽  
Cooperative Navigation ◽  
Navigation Algorithm ◽  
Geometric Dilution Of Precision ◽  
Global Navigation Satellite

Position information is very important tactical information in large-scale joint military operations. Positioning with datalink time of arrival (TOA) measurements is a primary choice when a global navigation satellite system (GNSS) is not available, datalink members are randomly distributed, only estimates with measurements between navigation sources and positioning users may lead to a unsatisfactory accuracy, and positioning geometry of altitude is poor. A time division multiple address (TDMA) datalink cooperative navigation algorithm based on INS/JTIDS/BA is presented in this paper. The proposed algorithm is used to revise the errors of the inertial navigation system (INS), clock bias is calibrated via round-trip timing (RTT), and altitude is located with height filter. The TDMA datalink cooperative navigation algorithm estimate errors are stated with general navigation measurements, cooperative navigation measurements, and predicted states. Weighted horizontal geometric dilution of precision (WHDOP) of the proposed algorithm and the effect of the cooperative measurements on positioning accuracy is analyzed in theory. We simulate a joint tactical information distribution system (JTIDS) network with multiple members to evaluate the performance of the proposed algorithm. The simulation results show that compared to an extended Kalman filter (EKF) that processes TOA measurements sequentially and a TDMA datalink navigation algorithm without cooperative measurements, the TDMA datalink cooperative navigation algorithm performs better.

scholarly journals Robust TOA-Based UAS Navigation under Model Mismatch in GNSS-Denied Harsh Environments

2020 ◽  
Vol 12 (18) ◽  
pp. 2928
Author(s):  
Jan Mortier ◽  
Gaël Pagès ◽  
Jordi Vilà-Valls
Keyword(s):  
Intelligent Transportation Systems ◽  
Autonomous Systems ◽  
Real Life ◽  
Transportation Systems ◽  
Urban Environments ◽  
Global Navigation Satellite Systems ◽  
Ultra Wideband ◽  
Time Of Arrival ◽  
Navigation Systems ◽  
Satellite Systems

Global Navigation Satellite Systems (GNSS) is the technology of choice for outdoor positioning purposes but has many limitations when used in safety-critical applications such Intelligent Transportation Systems (ITS) and Unmanned Autonomous Systems (UAS). Namely, its performance clearly degrades in harsh propagation conditions and is not reliable due to possible attacks or interference. Moreover, GNSS signals may not be available in the so-called GNSS-denied environments, such as deep urban canyons or indoors, and standard GNSS architectures do not provide the precision needed in ITS. Among the different alternatives, cellular signals (LTE/5G) may provide coverage in constrained urban environments and Ultra-Wideband (UWB) ranging is a promising solution to achieve high positioning accuracy. The key points impacting any time-of-arrival (TOA)-based navigation system are (i) the transmitters’ geometry, (ii) a perfectly known transmitters’ position, and (iii) the environment. In this contribution, we analyze the performance loss of alternative TOA-based navigation systems in real-life applications where we may have both transmitters’ position mismatch, harsh propagation environments, and GNSS-denied conditions. In addition, we propose new robust filtering methods able to cope with both effects up to a certain extent. Illustrative results in realistic scenarios are provided to support the discussion and show the performance improvement brought by the new methodologies with respect to the state-of-the-art.

MEETING THE NEEDS OF ADOLESCENT POST-ABORTION CARE PATIENTS IN THE DOMINICAN REPUBLIC

2010 ◽  
Vol 42 (4) ◽  
pp. 493-509 ◽  
Author(s):  
DONNA R. McCARRAHER ◽  
MARIO CHEN-MOK ◽  
ANA SOPHIA ORONOZ ◽  
SONIA BRITO-ANDERSON ◽  
THOMAS GREY ◽  
...  
Keyword(s):  
Dominican Republic ◽  
Older Women ◽  
Contraceptive Method ◽  
Public Hospitals ◽  
Time Of Arrival ◽  
Abortion Care ◽  
Post Abortion Care ◽  
Provider Knowledge ◽  
Post Abortion ◽  
Counselling Intervention

SummaryCounselling on contraception and contraceptive method provision are key components of post-abortion care (PAC). Some studies have suggested that adolescent PAC patients receive worse care than older women seeking these services. This study aimed to evaluate an intervention whose goal was to improve the counselling and contraceptive uptake of PAC patients, with special attention given to the needs of adolescent patients, in the four public hospitals in the Dominican Republic where PAC services were not being routinely offered. The counselling intervention effort included provider training and the development of adolescent-friendly information, education and communication (IEC) materials. Eighty-eight providers were interviewed at baseline and 6 months after the intervention was implemented. Six months after providers were trained, 140 adolescent PAC patients (≤19 years of age) and 134 older PAC patients (20–35 years) were interviewed about the contraceptive counselling messages and contraceptive methods they received before they were discharged from hospital. The adolescent and older PAC patients were matched on study hospital and time of arrival. Significant improvements were noted in provider knowledge and attitudes. No changes were noted in provider-reported PAC counselling behaviours, with close to 70% of providers reporting they routinely assess patients' fertility intentions, discuss contraception, assess STI/HIV risk and discuss post-abortion complications. Adolescent and older PAC patients reported receiving PAC counselling messages at similar rates. Forty per cent of adolescent PAC patients and 45% of older PAC patients who wanted to delay pregnancy were discharged with a contraceptive method. Adolescents were more likely to receive an injectable contraceptive method whereas older women were discharged with a variety of methods. The PAC counselling intervention increased provider knowledge and improved their attitudes and benefited both adolescent and older patients.

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