Independent Monitoring the Cuban Economic Zone Oil Development

The extensive impact and consequences of the 2010 Deep Water Horizon oil drilling rig failure in the Gulf of Mexico, together with expanding drilling activities in the Cuban Exclusive Economic zone, have cast a spotlight on Cuban oil development. The threat of a drilling rig failure has evolved from being only hypothetical to a potential reality with the commencement of active drilling in Cuban waters. The disastrous consequences of a drilling rig failure in Cuban waters will spread over a number of vital interests of the US and of nations in the Caribbean in the general environs of Cuba. The US fishing and tourist industries will take major blows from a significant oil spill in Cuban waters. Substantial ecological damage and damage to beaches could occur for the US, Mexico, Haiti and other countries as well. The need exists for the US to have the ability to independently monitor the reality of Cuban oceanic oil development. The advantages of having an independent US early warning system providing essential real-time data on the possible failure of a drilling rig in Cuban waters are numerous. An ideal early warning system would timely inform the US that an event has occurred or is likely to occur in, essentially, real-time. Presently operating monitoring systems that could provide early warning information are satellite-based. Such systems can indicate the locations of both drilling rigs and operational drilling platforms. The system discussed/proposed in this paper relies upon low-frequency underwater sound. The proposed system can complement existing monitoring systems, which offer ocean-surface information, by providing sub-ocean surface, near-real time, information. This “integrated system” utilizes and combines (integrates) many different forms of information, some gathered through sub-ocean surface systems, and some through electromagnetic-based remote sensing (satellites, aircraft, unmanned arial vehicles), and other methods as well. Although the proposed integrated system is in the developmental stage, it is based upon well-established technologies.

"A Special Relationship": The Political & Economic Links between Cuba & Venezuela, A Panel Discussion

This flyer promotes the event ""A Special Relationship": The Political & Economic Links between Cuba & Venezuela A Panel Discussion" in partnership with the Latin American and Caribbean Center.

"A Special Relationship": The Political & Economic Links between Cuba & Venezuela, A Panel Discussion

Panel Discussion with FIU's Cuban Research Institute and the Latin American and Caribbean Center to examine the origins, development, current status, and future scenarios of the Cuba-Venezuela alliance. Participants include: Dr. Carlos Antonio Romero Mendez, Universidad Central de Venezuela Dr. Javier Corrales, Amherst College Prof. Manuel A. Gomez, Florida International University Marra C. Werlau, Cuba Archive

Application of intervention analysis to evaluate the impacts of special events on freeways

In China in particular, large, planned special events (e.g., the Olympic Games, etc.) are viewed as great opportunities for economic development. Large numbers of visitors from other countries and provinces may be expected to attend such events, bringing in significant tourism dollars. However, as a direct result of such events, the transportation system is likely to face great challenges as travel demand increases beyond its original design capacity. Special events in central business districts (CBD) in particular will further exacerbate traffic congestion on surrounding freeway segments near event locations. To manage the transportation system, it is necessary to plan and prepare for such special events, which requires prediction of traffic conditions during the events. This dissertation presents a set of novel prototype models to forecast traffic volumes along freeway segments during special events. Almost all research to date has focused solely on traffic management techniques under special event conditions. These studies, at most, provided a qualitative analysis and there was a lack of an easy-to-implement method for quantitative analyses. This dissertation presents a systematic approach, based separately on univariate time series model with intervention analysis and multivariate time series model with intervention analysis for forecasting traffic volumes on freeway segments near an event location. A case study was carried out, which involved analyzing and modelling the historical time series data collected from loop-detector traffic monitoring stations on the Second and Third Ring Roads near Beijing Workers Stadium. The proposed time series models, with expected intervention, are found to provide reasonably accurate forecasts of traffic pattern changes efficiently. They may be used to support transportation planning and management for special events.

Application of Intervention Analysis to Evaluate the Impacts of Special Events on Freeways

In China in particular, large, planned special events (e.g., the Olympic Games, etc.) are viewed as great opportunities for economic development. Large numbers of visitors from other countries and provinces may be expected to attend such events, bringing in significant tourism dollars. However, as a direct result of such events, the transportation system is likely to face great challenges as travel demand increases beyond its original design capacity. Special events in central business districts (CBD) in particular will further exacerbate traffic congestion on surrounding freeway segments near event locations. To manage the transportation system, it is necessary to plan and prepare for such special events, which requires prediction of traffic conditions during the events. This dissertation presents a set of novel prototype models to forecast traffic volumes along freeway segments during special events. Almost all research to date has focused solely on traffic management techniques under special event conditions. These studies, at most, provided a qualitative analysis and there was a lack of an easy-to-implement method for quantitative analyses. This dissertation presents a systematic approach, based separately on univariate time series model with intervention analysis and multivariate time series model with intervention analysis for forecasting traffic volumes on freeway segments near an event location. A case study was carried out, which involved analyzing and modelling the historical time series data collected from loop-detector traffic monitoring stations on the Second and Third Ring Roads near Beijing Workers Stadium. The proposed time series models, with expected intervention, are found to provide reasonably accurate forecasts of traffic pattern changes efficiently. They may be used to support transportation planning and management for special events.