Geographical Characterization of Ship Traffic and Emissions

2005 ◽  
Vol 1909 (1) ◽  
pp. 90-99 ◽  
Author(s):  
Chenfeng Wang ◽  
James J. Corbett
Keyword(s):  
Coastal Waters ◽  
East Coast ◽  
Air Emissions ◽  
Traffic Network ◽  
Traffic Patterns ◽  
Data Set ◽  
Ship Traffic ◽  
Traffic Pattern ◽  
Adequate Data

The Commercial Marine Vessel Traffic and Air Emissions Model (CMV-TAEM) estimates and geographically represents offshore vessel traffic and emissions based on actual shipping activities. The CMV-TAEM has three modules: ship traffic, ship emissions, and policy analysis. The model establishes empirical ship traffic network on the basis of ship observations derived from the International Comprehensive Ocean-Atmosphere Data Set and shipping activity records. Geographical representations of ship traffic intensities and emissions can be produced through the math-ematic manipulation of matrices of ship traffic network, shipping activity, and ship characteristic data. Overall, although seasonal changes are apparent, the global ship traffic pattern does not change much annually. The ship traffic pattern changes regionally, with a net increase in some areas and net decrease in others. Multiple-year observations are combined to make traffic patterns for major shipping lanes smoother and clearer. Results indicate that 84.5% of global ship traffic occurs north of the equator and two-thirds of global ship traffic within 200 nautical miles of the shore. About 10% of global ship traffic occurs in U.S. coastal waters; shipping along the East Coast accounts for more than one-fifth of the U.S. coastal traffic. Adequate data are available to determine ship activities and ship attributes and to implement the model.

scholarly journals Modelling of safe traffic schema for marine area

2021 ◽  
pp. 127-134
Author(s):  
В.М. Гриняк ◽  
А.С. Девятисильный ◽  
А.В. Шуленина
Keyword(s):  
Heavy Traffic ◽  
Weighted Graph ◽  
Water Area ◽  
General Purpose ◽  
Structural Elements ◽  
Traffic Patterns ◽  
Ship Traffic ◽  
Traffic Pattern ◽  
Alternative Approach ◽  
Marine Areas

Статья посвящена проблеме обеспечения безопасности движения судов на морских акваториях. В условиях насыщенного трафика навигационная безопасность может быть обеспечена только при соблюдении судами определённой схемы движения. В работе ставится задача планирования системы маршрутов (схемы движения) судов через акватории с интенсивным трафиком. Эта схема зависит от географии акватории и особенностей трафика. Выбор того или иного варианта схемы обусловлен необходимостью обеспечения максимальной безопасности движения и практическими соображениями. В основу метода решения задачи положено моделирование движения судов по множеству возможных траекторий и оценка метрики, описывающей степень опасности движения. В качестве такой метрики предлагается частота опасных сближений судов, отмечается возможность использования и других метрик. В работе показано, что модельное представление задачи на основе взвешенного графа не даёт возможности её решения без привлечения специализированных вычислительных ресурсов. Альтернативным подходом является конструирование схем движения экспертным способом из типичных структурных элементов (примитивов). Имитационное моделирование задачи изолированно в рамках отдельного примитива вполне возможно на доступных вычислительных и программных платформах общего назначения. В работе рассмотрено четыре таких примитива, оценено среднее время между опасными сближениями судов для каждого из них. Приведён пример использования полученных результатов моделирования для планирования безопасных схем движения судов. This work is devoted to the problem of ensuring the safety of vessel traffic at marine areas. Navigation safety in conditions of heavy traffic can be ensured only if the vessels comply with a certain traffic pattern. The paper highlights the problem of planning a system of routes (traffic patterns) of vessels through water areas with heavy traffic. This schema depends on the geography of the water area and the characteristics of traffic. The necessity to ensure the maximum safety of vessel traffic and practical considerations determine the choice of a specific variant for a traffic scheme. Modeling the vessels motion along a set of possible trajectories and evaluating the metric describing the degree of movement danger is the basis of the method for solving the problem. The frequency of dangerous approaches of vessels is proposed as a metric for assessing the danger of traffic, and the possibility of using other metrics is noted. The work demonstrates that the model representation of the problem based on a weighted graph does not allow its solution without the involvement of specialized computing resources. An alternative approach is motion construction of schemes in an expert way from typical structural elements (primitives). Simulation modeling of a problem becomes possible on available general-purpose computing and software platforms if it is isolated within a separate primitive. The paper considers four such primitives and estimates the average time between dangerous approaches of vessels for each of them. An example of using the obtained modeling results for planning safe ship traffic patterns is given.

scholarly journals Transition Characteristic Analysis of Traffic Evolution Process for Urban Traffic Network

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Longfei Wang ◽  
Hong Chen ◽  
Yang Li
Keyword(s):  
Urban Traffic ◽  
Evolution Process ◽  
Traffic Network ◽  
Traffic Patterns ◽  
Characteristic Analysis ◽  
Self Organizing Maps ◽  
Traffic Time Series ◽  
Temporal Domain ◽  
Urban Traffic Network

The characterization of the dynamics of traffic states remains fundamental to seeking for the solutions of diverse traffic problems. To gain more insights into traffic dynamics in the temporal domain, this paper explored temporal characteristics and distinct regularity in the traffic evolution process of urban traffic network. We defined traffic state pattern through clustering multidimensional traffic time series using self-organizing maps and construct a pattern transition network model that is appropriate for representing and analyzing the evolution progress. The methodology is illustrated by an application to data flow rate of multiple road sections from Network of Shenzhen’s Nanshan District, China. Analysis and numerical results demonstrated that the methodology permits extracting many useful traffic transition characteristics including stability, preference, activity, and attractiveness. In addition, more information about the relationships between these characteristics was extracted, which should be helpful in understanding the complex behavior of the temporal evolution features of traffic patterns.

Fuzzy ART Neural Network Model for Automated Detection of Freeway Incidents

1998 ◽  
Vol 1634 (1) ◽  
pp. 56-63 ◽  
Author(s):  
Sherif S. Ishak ◽  
Haitham M. Al-Deek
Keyword(s):  
Neural Networks ◽  
False Alarm ◽  
False Alarm Rate ◽  
Back Propagation ◽  
Incident Detection ◽  
Traffic Patterns ◽  
Traffic Pattern ◽  
Detection Algorithms ◽  
Fuzzy Art ◽  
Freeway Incidents

Pattern recognition techniques such as artificial neural networks continue to offer potential solutions to many of the existing problems associated with freeway incident-detection algorithms. This study focuses on the application of Fuzzy ART neural networks to incident detection on freeways. Unlike back-propagation models, Fuzzy ART is capable of fast, stable learning of recognition categories. It is an incremental approach that has the potential for on-line implementation. Fuzzy ART is trained with traffic patterns that are represented by 30-s loop-detector data of occupancy, speed, or a combination of both. Traffic patterns observed at the incident time and location are mapped to a group of categories. Each incident category maps incidents with similar traffic pattern characteristics, which are affected by the type and severity of the incident and the prevailing traffic conditions. Detection rate and false alarm rate are used to measure the performance of the Fuzzy ART algorithm. To reduce the false alarm rate that results from occasional misclassification of traffic patterns, a persistence time period of 3 min was arbitrarily selected. The algorithm performance improves when the temporal size of traffic patterns increases from one to two 30-s periods for all traffic parameters. An interesting finding is that the speed patterns produced better results than did the occupancy patterns. However, when combined, occupancy–speed patterns produced the best results. When compared with California algorithms 7 and 8, the Fuzzy ART model produced better performance.

scholarly journals Characterization of toxin-producing strains of Dinophysis spp. (Dinophyceae) isolated from French coastal waters, with a particular focus on the D. acuminata-complex

Harmful Algae ◽  
2021 ◽  
pp. 101974
Author(s):  
Véronique Séchet ◽  
Manoella Sibat ◽  
Gwenael Billien ◽  
Liliane Carpentier ◽  
Georges-Augustin Rovillon ◽  
...  
Keyword(s):  
Coastal Waters

Character selection and the quantification of morphological disparity

Paleobiology ◽  
2016 ◽  
Vol 43 (1) ◽  
pp. 68-84 ◽  
Author(s):  
Bradley Deline ◽  
William I. Ausich
Keyword(s):  
A Priori ◽  
Morphological Diversity ◽  
Small Subset ◽  
Early Paleozoic ◽  
Data Set ◽  
Rarefaction Analysis ◽  
Morphological Studies ◽  
Body Regions ◽  
Scientific Hypotheses

AbstractA priori choices in the detail and breadth of a study are important in addressing scientific hypotheses. In particular, choices in the number and type of characters can greatly influence the results in studies of morphological diversity. A new character suite was constructed to examine trends in the disparity of early Paleozoic crinoids. Character-based rarefaction analysis indicated that a small subset of these characters (~20% of the complete data set) could be used to capture most of the properties of the entire data set in analyses of crinoids as a whole, noncamerate crinoids, and to a lesser extent camerate crinoids. This pattern may be the result of the covariance between characters and the characterization of rare morphologies that are not represented in the primary axes in morphospace. Shifting emphasis on different body regions (oral system, calyx, periproct system, and pelma) also influenced estimates of relative disparity between subclasses of crinoids. Given these results, morphological studies should include a pilot analysis to better examine the amount and type of data needed to address specific scientific hypotheses.

scholarly journals Data set on the characterization of the phytoestrogenic extract and isolated compounds of the roots of Inula racemosa Hook F (Asteraceae)

Data in Brief ◽  
2018 ◽  
Vol 17 ◽  
pp. 770-773
Author(s):  
Mangathayaru Kalachaveedu ◽  
Divya Raghavan ◽  
Srivani Telapolu ◽  
Sarah Kuruvilla ◽  
Balakrishna Kedike
Keyword(s):  
Data Set ◽  
Inula Racemosa

scholarly journals A search for transiting planets in the β Pictoris system

2018 ◽  
Vol 615 ◽  
pp. A145 ◽  
Author(s):  
M. Mol Lous ◽  
E. Weenk ◽  
M. A. Kenworthy ◽  
K. Zwintz ◽  
R. Kuschnig
Keyword(s):  
Signal To Noise Ratio ◽  
Large Fraction ◽  
Young Star ◽  
High Signal ◽  
Data Set ◽  
Transiting Planets ◽  
Using Data ◽  
Exoplanet Systems ◽  
Transit Signals

Context. Transiting exoplanets provide an opportunity for the characterization of their atmospheres, and finding the brightest star in the sky with a transiting planet enables high signal-to-noise ratio observations. The Kepler satellite has detected over 365 multiple transiting exoplanet systems, a large fraction of which have nearly coplanar orbits. If one planet is seen to transit the star, then it is likely that other planets in the system will transit the star too. The bright (V = 3.86) star β Pictoris is a nearby young star with a debris disk and gas giant exoplanet, β Pictoris b, in a multi-decade orbit around it. Both the planet’s orbit and disk are almost edge-on to our line of sight. Aims. We carry out a search for any transiting planets in the β Pictoris system with orbits of less than 30 days that are coplanar with the planet β Pictoris b. Methods. We search for a planetary transit using data from the BRITE-Constellation nanosatellite BRITE-Heweliusz, analyzing the photometry using the Box-Fitting Least Squares Algorithm (BLS). The sensitivity of the method is verified by injection of artificial planetary transit signals using the Bad-Ass Transit Model cAlculatioN (BATMAN) code. Results. No planet was found in the BRITE-Constellation data set. We rule out planets larger than 0.6 RJ for periods of less than 5 days, larger than 0.75 RJ for periods of less than 10 days, and larger than 1.05 RJ for periods of less than 20 days.

scholarly journals Characterization of Road Condition with Data Mining Based on Measured Kinematic Vehicle Parameters

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Johannes Masino ◽  
Jakob Thumm ◽  
Guillaume Levasseur ◽  
Michael Frey ◽  
Frank Gauterin ◽  
...  
Keyword(s):  
Data Mining ◽  
Support Vector ◽  
Matlab Toolbox ◽  
Data Set ◽  
The Road ◽  
Acceleration Sensors ◽  
Road Surfaces ◽  
Road Condition ◽  
Sensor Signals

This work aims at classifying the road condition with data mining methods using simple acceleration sensors and gyroscopes installed in vehicles. Two classifiers are developed with a support vector machine (SVM) to distinguish between different types of road surfaces, such as asphalt and concrete, and obstacles, such as potholes or railway crossings. From the sensor signals, frequency-based features are extracted, evaluated automatically with MANOVA. The selected features and their meaning to predict the classes are discussed. The best features are used for designing the classifiers. Finally, the methods, which are developed and applied in this work, are implemented in a Matlab toolbox with a graphical user interface. The toolbox visualizes the classification results on maps, thus enabling manual verification of the results. The accuracy of the cross-validation of classifying obstacles yields 81.0% on average and of classifying road material 96.1% on average. The results are discussed on a comprehensive exemplary data set.

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