Big Data Insights into Container Vessel Dwell Times

2021 ◽  
pp. 036119812110152
Author(s):  
Daniel Smith
Keyword(s):  
New York ◽  
Los Angeles ◽  
Dwell Time ◽  
Weather Conditions ◽  
Turnaround Time ◽  
Future Research ◽  
Automatic Identification ◽  
Identification System ◽  
Data Sets ◽  
Schedule Adherence

Analysis of automatic identification system (AIS) vessel call records can greatly improve our understanding of container vessel dwell times when coupled with information on port volumes and vessel schedules. Port productivity discussions often use vessel time in port—referred to as dwell time, turnaround time, or berth time—as a primary metric. This emphasis implies a need to understand the factors that determine dwell time, especially in port comparisons. Previous dwell time analyses have been handicapped by limited data. This analysis differs in that it uses a multiyear, multiport database covering all relevant vessel calls at major continental U.S. container ports (Baltimore, Boston, Charleston, Houston, Jacksonville, Long Beach, Los Angeles, Miami, Mobile, New Orleans, Northwest Seaport Alliance, New York–New Jersey, Oakland, Palm Beach, Philadelphia, Port Everglades, Savannah, Virginia, and Wilmington, NC), and by including vessel schedules and seasonality. The analysis indicated a much stronger association of dwell time with expected cargo volume at each call than with vessel capacity, and expected cargo volumes helped explain port dwell time differences. The analysis also found that vessel schedules may be the primary determinants of dwell time, and that schedule adherence may thus be equally important as dwell time per se. Seasonality also affected container vessel dwell time, but that influence may be complex as both weather conditions and seasonal cargo peaks probably affect the outcomes. Promising avenues for future research lie in merging AIS vessel call records with other data sets that, unfortunately, may not yet exist or be accessible.

scholarly journals A Hybrid Method for Inland Ship Recognition Using Marine Radar and Closed-Circuit Television

2021 ◽  
Vol 9 (11) ◽  
pp. 1199
Author(s):  
Xinglong Liu ◽  
Yicheng Li ◽  
Yong Wu ◽  
Zhiyuan Wang ◽  
Wei He ◽  
...  
Keyword(s):  
Region Of Interest ◽  
Weather Conditions ◽  
Calibration Method ◽  
Closed Circuit ◽  
Automatic Identification ◽  
Identification System ◽  
Closed Circuit Television ◽  
Multi Scale ◽  
Marine Radar ◽  
Ship Recognition

Vessel recognition plays important role in ensuring navigation safety. However, existing methods are mainly based on a single sensor, such as automatic identification system (AIS), marine radar, closed-circuit television (CCTV), etc. To this end, this paper proposes a coarse-to-fine recognition method by fusing CCTV and marine radar, called multi-scale matching vessel recognition (MSM-VR). This method first proposes a novel calibration method that does not use any additional calibration target. The calibration is transformed to solve an N point registration model. Furthermore, marine radar image is used for coarse detection. A region of interest (ROI) area is computed for coarse detection results. Lastly, we design a novel convolutional neural network (CNN) called VesNet and transform the recognition into feature extraction. The VesNet is used to extract the vessel features. As a result, the MVM-VR method has been validated by using actual datasets collected along different waterways such as Nanjing waterway and Wuhan waterway, China, covering different times and weather conditions. Experimental results show that the MSM-VR method can adapt to different times, different weather conditions, and different waterways with good detection stability. The recognition accuracy is no less than 96%. Compared to other methods, the proposed method has high accuracy and great robustness.

scholarly journals Voices in the Storm: The Lost Discourse of Climate Change in Hurricanes Harvey and Irma

2018 ◽  
Vol 1 (2) ◽  
pp. 72-78
Author(s):  
B.F. Battistoli ◽  
Keyword(s):  
Climate Change ◽  
New York ◽  
Global Warming ◽  
Content Analysis ◽  
Los Angeles ◽  
Research Question ◽  
New York Times ◽  
Future Research ◽  
Extensive Literature ◽  
Hurricane Irma

This study sought to answer the research question: How did media address climate change in reporting on Hurricanes Harvey and Irma? A content analysis was performed on the coverage of Hurricanes Harvey and Irma over a six-week timeframe by two national newspapers, The New York Times and the Los Angeles Times, and two local newspapers, the Houston Chronicle for Hurricane Harvey and the Tampa Bay Times for Hurricane Irma. A keyword analysis yielded 630 news articles (N=630), of which only 23 (3.65%) mentioned “climate change,” “global warming,” or both. Language that addressed these terms was coded on a Likert Scale (0-5, negative to positive), yielding a median score of 3.44, “slightly positive.” An extensive literature review and discussion of the findings and implications for future research are included. Keywords: Hurricane Harvey, Hurricane Irma, climate change, global warming, newspaper content analysis.

SPECIALIZED MEASURES OF LEAF OUTLINES AND HIERARCHICAL PERCEPTRONS IN AN AUTOMATIC IDENTIFICATION OF PLANTS

2004 ◽  
Vol 15 (08) ◽  
pp. 1171-1186 ◽  
Author(s):  
WOJCIECH BORKOWSKI ◽  
LIDIA KOSTRZYŃSKA
Keyword(s):  
Neural Network ◽  
Nearest Neighbor ◽  
Real Data ◽  
Automatic Identification ◽  
Identification System ◽  
Data Sets ◽  
Identification Algorithm ◽  
Plant Identification ◽  
Neural Network Classifiers ◽  
Computer Identification

The development of an efficient image-based computer identification system for plants or other organisms is an important ambitious goal, which is still far from realization. This paper presents three new methods potentially usable for such a system: fractal-based measures of complexity of leaf outline, a heuristic algorithm for automatic detection of leaf parts — the blade and the petiole, and a hierarchical perceptron — a kind of neural network classifier. The next few sets of automatically extractable features of leaf blades, encompassed those presented and/or traditionally used, are compared in the task of plant identification using the simplest known "nearest neighbor" identification algorithm, and more realistic neural network classifiers, especially the hierarchical. We show on two real data sets that the presented techniques are really usable for automatic identification, and are worthy of further investigation.

News media and the racialization of protest: an analysis of Black Lives Matter articles

2017 ◽  
Vol 36 (8) ◽  
pp. 720-735 ◽  
Author(s):  
Joy Leopold ◽  
Myrtle P. Bell
Keyword(s):  
New York ◽  
Los Angeles ◽  
News Media ◽  
News Coverage ◽  
New York Times ◽  
Future Research ◽  
Negative Consequences ◽  
Content Type ◽  
Los Angeles Times ◽  
Black Lives Matter

Purpose The purpose of this paper is to examine coverage of the Black Lives Matter (BLM) movement in seven US-based newspapers to determine whether the protest paradigm, “a pattern of news coverage that expresses disapproval toward protests and dissent,” and other marginalizing techniques are present, and racialized. Design/methodology/approach Relevant articles published during a six-month period of 2014 near the death of Michael Brown were retrieved from the selected outlets, including the New York Times, the Los Angeles Times, and the St Louis Post-Dispatch. Textual and content analyses were performed. Findings The articles heavily followed the paradigm. An additional characteristic, blame attribution, was also identified. Language of crime, lawlessness, violence, blame for nearby acts of violence, and inflammatory quotes from bystanders and official sources were often present. There was little discussion of key issues associated with the formation of BLM. Research limitations/implications Mainstream outlets rather than social media or alternative outlets were examined. Future research should study coverage of BLM in other outlets. Practical implications Measures to avoid marginalizing protests and racialization of coverage, including increased diversity in the newsroom and monitoring for racialized language are suggested. Social implications Racialization of news and coverage of BLM has widespread negative consequences, such as association of Blacks with criminality that may affect their quality of life. The protest paradigm has the ability to squelch participation in social movements, which have the possibility to bring about needed social change. Originality/value This interdisciplinary paper highlights the important role of mainstream media and news routines in affecting the BLM movement. It uses diversity research to make recommendations for media practitioners to avoid racialization of news.

Capacity Analysis for Bifurcated Estuaries Based on Ship Domain Theory and its Applications

2017 ◽  
Vol 2611 (1) ◽  
pp. 56-64 ◽  
Author(s):  
Xingjian Zhang ◽  
Junmin Mou ◽  
Jianfeng Zhu ◽  
Pengfei Chen ◽  
Rongfang (Rachel) Liu
Keyword(s):  
Traffic Management ◽  
River Estuary ◽  
Weather Conditions ◽  
Transportation Systems ◽  
Water Levels ◽  
Domain Theory ◽  
Yangtze River Estuary ◽  
Automatic Identification ◽  
Identification System ◽  
Estimation Model

The bifurcated estuary is an important segment of marine transportation systems that are themselves becoming increasingly important. Because of branching channels, the cyclical change of water levels, and sophisticated operating rules in many large bifurcated estuaries, it is often difficult to estimate the traffic capacity and simulate ships’ motions, even though it is critically important for traffic management and efficiency. In recent years, the increasing number of ships that collect and contribute to the Automatic Identification System (AIS) have made it possible to monitor traffic flow along waterways, including bifurcated estuaries. This study developed a typical capacity estimation model based on ship domain theory. By using AIS data collected in the Yangtze River estuary, a typical bifurcated estuary system, the study analyzed various physical characteristics, weather conditions, and vessel characteristics to derive related impacts of each on overall capacity of the bifurcated estuary. Validated with practical observations, the method can be applied to similar estuary channel systems to improve waterway operations and management.

Depression, Anxiety, and Alcohol Use Among LGBTQ+ People During the COVID-19 Pandemic

2021 ◽  
pp. e1-e10
Author(s):  
Ellesse-Roselee Akré ◽  
Andrew Anderson ◽  
Kristefer Stojanovski ◽  
Kara W. Chung ◽  
Nicole A. VanKim ◽  
...  
Keyword(s):  
Mental Health ◽  
New York ◽  
Sexual Behavior ◽  
Sexual Orientation ◽  
Los Angeles ◽  
Gender Identity ◽  
Problem Drinking ◽  
Future Research ◽  
And Gender ◽  
The Impact

Objectives. To describe disparities in depression, anxiety, and problem drinking by sexual orientation, sexual behavior, and gender identity during the COVID-19 pandemic. Methods. Data were collected May 21 to July 15, 2020, from 3245 adults living in 5 major US metropolitan areas (Atlanta, Georgia; Chicago, Illinois; New Orleans, Louisiana; New York, New York; and Los Angeles, California). Participants were characterized as cisgender straight or LGBTQ+ (i.e., lesbian, gay, bisexual, and transgender people, and men who have sex with men, and women who have sex with women not identifying as lesbian, gay, bisexual, or transgender). Results. Cisgender straight participants had the lowest levels of depression, anxiety, and problem drinking compared with all other sexual orientation, sexual behavior, and gender identity groups, and, in general, LGBTQ+ participants were more likely to report that these health problems were “more than usual” during the COVID-19 pandemic. Conclusions. LGBTQ+ communities experienced worse mental health and problem drinking than their cisgender straight counterparts during the COVID-19 pandemic. Future research should assess the impact of the pandemic on health inequities. Policymakers should consider resources to support LGBTQ+ mental health and substance use prevention in COVID-19 recovery efforts. (Am J Public Health. Published online ahead of print August 19, 2021: e1–e10. https://doi.org/10.2105/AJPH.2021.306394 )

scholarly journals Near Real Time Applications for Maritime Situational Awareness

2015 ◽  
Vol XL-7/W3 ◽  
pp. 999-1003 ◽  
Author(s):  
E. Schwarz ◽  
D. Krause ◽  
M. Berg ◽  
H. Daedelow ◽  
H. Maass
Keyword(s):  
Remote Sensing ◽  
Situational Awareness ◽  
Value Added ◽  
Remote Sensing Data ◽  
Image Data ◽  
Weather Conditions ◽  
Automatic Identification ◽  
Identification System ◽  
Product Portfolio ◽  
Other Information

Applications to derive maritime value added products like oil spill and ship detection based on remote sensing SAR image data are being developed and integrated at the Ground Station Neustrelitz, part of the German Remote Sensing Data Center. Products of meteo-marine parameters like wind and wave will complement the product portfolio. Research and development aim at the implementation of highly automated services for operational use. SAR images are being used because of the possibility to provide maritime products with high spatial resolution over wide swaths and under all weather conditions. In combination with other information like Automatic Identification System (AIS) data fusion products are available to support the Maritime Situational Awareness.

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