The Experts below are selected from a list of 27372 Experts worldwide ranked by ideXlab platform
Kenneth Ned Mitchell - One of the best experts on this subject based on the ideXlab platform.
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Use of Nationwide Automatic Identification System Data to Quantify Resiliency of Marine Transportation Systems
Transportation Research Record, 2016Co-Authors: Nafiseh Farhadi, Kenneth Ned Mitchell, Scott A. Parr, Brian WolshonAbstract:This paper describes the approach and the results of an ongoing research effort to assess the resilience of port operations following major disasters and other disruptive events. The work presented in this paper used archival data from the U.S. Coast Guard’s nationwide Automatic Identification System to quantify the state of resiliency of coastal navigation Systems. Illustrating the experimental methodology are case study examples that assess the disruptions that resulted from a collision in March 2014 in the Houston Ship Channel, Texas, and from Superstorm Sandy in 2012 on the greater Port of New York and New Jersey. The methods and results can be adapted and implemented for quantitatively evaluating levels of port activity following disruptive events and for a better understanding of the factors that lead to more resilient maritime Systems.
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Archival Automatic Identification System (AIS) Data for Navigation Project Performance Evaluation
2015Co-Authors: Brandan M. Scully, Kenneth Ned MitchellAbstract:Abstract : This Coastal and Hydraulics Engineering Technical Note (CHETN) describes Automatic Identification System (AIS) technology in general and highlights the growing availability of and potential applications of AIS data for performance evaluation of navigation projects. In particular, archived AIS data may be used in a variety of investigations and designs as the U.S. Army Corps of Engineers (USACE) executes its civil works mission. Uses range in complexity from simple reconnaissance and visualization of parameter-based queries to complex analysis of vessel behavior coupled with environmental input such as tidal elevations and wave conditions. Additional uses for modeling and engineering design are currently being investigated through the Navigation Systems (NavSys) research and development program as well as the Coastal Inlets Research Program (CIRP). An AIS data analysis package being developed jointly by these two programs is also described.
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Waterway Performance Monitoring with Automatic Identification System Data
Transportation Research Record, 2014Co-Authors: Kenneth Ned Mitchell, Brandan M. ScullyAbstract:Fiscal constraints at the federal level drive the need for more robust and objective performance evaluation methodologies for use by the U. S. Army Corps of Engineers as it carries out its civil works mission in support of the nation's water resources infrastructure. One specific area of need concerns functional performance evaluation of dredged navigation channels at the local level as well as performance evaluation of Systems of navigation projects. The nationwide Automatic Identification System (NAIS) for vessels that operate in coastal waters was instituted after the terrorist attacks of September 2001 and is maintained by the U. S. Coast Guard. The System constitutes an enabling technology to provide the data required for quantitative performance assessments of corps-maintained navigation infrastructure. In this paper, several applications are presented of archival NAIS data toward waterway performance evaluation. An assessment and comparison also are presented of several deep-draft coastal ports wit...
Brandan M. Scully - One of the best experts on this subject based on the ideXlab platform.
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Archival Automatic Identification System (AIS) Data for Navigation Project Performance Evaluation
2015Co-Authors: Brandan M. Scully, Kenneth Ned MitchellAbstract:Abstract : This Coastal and Hydraulics Engineering Technical Note (CHETN) describes Automatic Identification System (AIS) technology in general and highlights the growing availability of and potential applications of AIS data for performance evaluation of navigation projects. In particular, archived AIS data may be used in a variety of investigations and designs as the U.S. Army Corps of Engineers (USACE) executes its civil works mission. Uses range in complexity from simple reconnaissance and visualization of parameter-based queries to complex analysis of vessel behavior coupled with environmental input such as tidal elevations and wave conditions. Additional uses for modeling and engineering design are currently being investigated through the Navigation Systems (NavSys) research and development program as well as the Coastal Inlets Research Program (CIRP). An AIS data analysis package being developed jointly by these two programs is also described.
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Waterway Performance Monitoring with Automatic Identification System Data
Transportation Research Record, 2014Co-Authors: Kenneth Ned Mitchell, Brandan M. ScullyAbstract:Fiscal constraints at the federal level drive the need for more robust and objective performance evaluation methodologies for use by the U. S. Army Corps of Engineers as it carries out its civil works mission in support of the nation's water resources infrastructure. One specific area of need concerns functional performance evaluation of dredged navigation channels at the local level as well as performance evaluation of Systems of navigation projects. The nationwide Automatic Identification System (NAIS) for vessels that operate in coastal waters was instituted after the terrorist attacks of September 2001 and is maintained by the U. S. Coast Guard. The System constitutes an enabling technology to provide the data required for quantitative performance assessments of corps-maintained navigation infrastructure. In this paper, several applications are presented of archival NAIS data toward waterway performance evaluation. An assessment and comparison also are presented of several deep-draft coastal ports wit...
Zhimin Zhou - One of the best experts on this subject based on the ideXlab platform.
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GF-4 Satellite and Automatic Identification System Data Fusion for Ship Tracking
IEEE Geoscience and Remote Sensing Letters, 2019Co-Authors: Yong Liu, Libo Yao, Wei Xiong, Zhimin ZhouAbstract:GF-4 satellite, as the first geostationary orbit optical remote sensing satellite with medium resolution, has the abilities to point and stare at a particular sea area for maritime surveillance. The integration of GF-4 image sequence and Automatic Identification System (AIS) reports has the appealing potential to provide a better maritime situational awareness by tracking ships, especially noncooperative targets. The aim of this letter is to provide a track-level fusion architecture for GF-4 and AIS heterogeneous data based on the characteristics of different data sources to form a consolidated and comprehensive maritime picture. The proposed fusion strategy is tested in the specific area of the East China Sea, and experimental results verify the effectiveness of our method.
Jean-yves Tourneret - One of the best experts on this subject based on the ideXlab platform.
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Improving synthetic aperture radar detection using the Automatic Identification System
2017 18th International Radar Symposium (IRS), 2017Co-Authors: Fabio Manzoni Vieira, David Bonacci, Jean-yves Tourneret, François Vincent, Marc Spigai, Marie Ansart, Jacques RichardAbstract:This paper studies a maritime vessel detection method based on the fusion of data obtained from two different sensors, namely a synthetic aperture radar (SAR) and an Automatic Identification System (AIS) embedded in a satellite. In this work we propose a detector that uses the vessel position provided by the AIS System to improve the radar detection performance. The problem is handled by a generalized likelihood ratio test leading to a detector whose test statistics has a simple closed form expression. The distribution of the test statistics under the hypotheses is also determined, allowing theoretical and simulated receiver operational characteristics (ROCs) to be compared. Our results indicate that the proposed method improves detection performance and motivates the joint use of raw radar data with AIS demodulated information for ship detection.
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Cyclic redundancy check-based detection algorithms for Automatic Identification System signals received by satellite
International Journal of Satellite Communications and Networking, 2013Co-Authors: Raoul Prévost, M. Coulon, David Bonacci, Julia Lemaitre, Jean-pierre Millerioux, Jean-yves TourneretAbstract:This paper addresses the problem of demodulating signals transmitted in the Automatic Identification System. The main characteristics of such signals consist of two points: (i) they are modulated using a trellis-coded modulation, more precisely a Gaussian minimum shift keying modulation; and (ii) they are submitted to a bit stuffing procedure, which makes more difficult the detection of the transmitted information bits. This paper presents several demodulation algorithms developed in different contexts: mono-user and multi-user transmissions, and known/unknown phase shift. The proposed receiver uses the cyclic redundancy check (CRC) present in the Automatic Identification System signals for error correction and not for error detection only. By using this CRC, a particular Viterbi algorithm, on the basis of a so-called extended trellis, is developed. This trellis is defined by extended states composed of a trellis code state and a CRC state. Moreover, specific conditional transitions are defined to take into account the possible presence of stuffing bits. The algorithms proposed in the multi-user scenario present a small increase of computation complexity with respect to the mono-user algorithms. Some performance results are presented for several scenarios in the context of the Automatic Identification System and compared with those of existing techniques developed in similar scenarios.
Yang Pei-cai - One of the best experts on this subject based on the ideXlab platform.
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Detection effect of an Automatic Identification System of Schistosoma japonicum miracidia
Zhongguo xue xi chong bing fang zhi za zhi = Chinese journal of schistosomiasis control, 2018Co-Authors: Yang Pei-cai, He Yi-sha, Zhang Hong-ying, Gao Yuan, Zhou Wei, Gong Yun-huaAbstract:OBJECTIVE To evaluate the effect of an Automatic Identification System of Schistosoma japonicum miracidia, and compare it with the traditional eye detection method in the simulation field. METHODS A total of 260 fecal samples were collected from schistosomiasis non-endemic areas, and the test sample bottles containing schistosome miracidia were prepared according to different experimental needs. Thirty fecal samples for the sensitivity test were separately added with five fresh miracidia per sample, and then the mixed samples were detected by two experienced technicians (with more than 15 years' traditional test experience) or the Automatic System. The positive detection rates were compared between the two methods. Thirty fecal samples for repetition test were separately added with ten fresh miracidia per sample, and then the mixed samples were detected separately with the Automatic Identification System by two experienced technicians. The results were compared between two persons. The two methods including the Automatic Identification System and the traditional eye detection method were carried out blindly with totally 200 samples in the simulation field. There were three groups (each with 30 samples) : Group 1 with more than 21 fresh miracidia, Group 2 with 6 to 20 fresh miracidia, and Group 3 with 1 to 5 fresh miracidia. The other 110 samples were as a negative group. The detection time, accuracy, missed detection rate, and false detection rate of the two methods were statistically compared. RESULTS The positive detection rates of the 30 positive samples were 43.33% and 33.33% by the two technicians with the traditional eye detection method, respectively, while the detection rate was 80.00% by the Automatic Identification System, and the difference was statistically significant (χ2 = 7.05, χ2 = 12.97, both P 0.05). The experiments showed that the correct detection rate of the positive samples was 98.00% by the Automatic Identification System, which was higher than 79.75% by the traditional eye detection method. The detection time of the Automatic Identification System was shortened by half compared with that of the traditional eye detection method. The missed detection rate, and false detection rate of the Automatic Identification System were 2.22% and 1.82%, respectively, which were much lower than 35.56% and 7.73% of the traditional eye detection method. CONCLUSIONS Compared with the traditional eye detection method, the Automatic Identification System of S. japonicum miracidia has the advantages of high sensitivity, good repeatability, short detection time, high accuracy, low missed detection rate, and low false detection rate. It can be used in the field and clinical detection in replacement of the traditional eye detection method.
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Effectiveness evaluation of dynamic Automatic Identification System (device) of Schistosoma japonicum miracidia
Zhongguo xue xi chong bing fang zhi za zhi = Chinese journal of schistosomiasis control, 2018Co-Authors: Gao Yuan, Yang Pei-cai, Xu FeiAbstract:OBJECTIVE To develop a dynamic Automatic Identification System (device) of Schistosoma japonicum miracidia to achieve the Automatic detection and improve the detection rate and efficiency of schistosome miracidia. METHODS The dynamic Automatic Identification System (device) of S.japonicum miracidia was composed of an optical stereoscope, a digital camera, dynamic Automatic tracking recognition software, and a computer. Under different conditions, the detection rates and efficiency of the System were compared with those of five professional persons. RESULTS The basic function of the System was to identify, label and warn the miracidia of S. japonicum, and the records could be saved Automatically. The laboratory tests showed that the missing rate of the System was 0. The total consistent rates of the manual detection were 74.67% and 66.67% in the condition with and without water bug, while the total consistent rates of the System were 100.00% and 96.67%, respectively (χ2 = 9.634, 11.081, both P < 0.01) . CONCLUSIONS The System is much superior to manual detection in the accuracy and speed, and the System could completely replace the manual detection. Therefore, the System could be used in the field and basic research of schistosomiasis.
