Modelling and Refinement in CODA

This paper provides an overview of the CODA framework for modelling and refinement of component-based embedded systems. CODA is an extension of Event-B and UML-B and is supported by a plug-in for the Rodin toolset. CODA augments Event-B with constructs for component-based modelling including components, communications ports, port connectors, timed communications and timing triggers. Component behaviour is specified through a combination of UML-B state machines and Event-B. CODA communications and timing are given an Event-B semantics through translation rules. Refinement is based on Event-B refinement and allows layered construction of CODA models in a consistent way.Comment: In Proceedings Refine 2013, arXiv:1305.563

Unchecked: How Wal-Mart Uses its Might to Block Port Security

[Excerpt] In spite of the vulnerability of our ports and of supply networks around the world, Wal-Mart and RILA have—time and again since the attacks of Sept. 11, 2001—opposed new maritime and port security rules. Their mantra is: “Security requirements should not become a barrier to trade.” The AFL-CIO’s unions represent millions of port, transportation and emergency workers including first responders, whose lives are on the line in the event of a catastrophic attack on America‘s ports. This report details the ways in which Wal-Mart’s lobbyists and allies have quietly and insistently made these workers and all Americans less safe

A 5 Meps $100 USB2.0 Address-Event Monitor-Sequencer Interface

This paper describes a high-speed USB2.0 Address- Event Representation (AER) interface that allows simultaneous monitoring and sequencing of precisely timed AER data. This low-cost (<$100), two chip, bus powered interface can achieve sustained AER event rates of 5 megaevents per second (Meps). Several boards can be electrically synchronized, allowing simultaneous synchronized capture from multiple devices. It has three AER ports, one for sequencing, one for monitoring and one for passing through the monitored events. This paper also describes the host software infrastructure that makes the board usable for a heterogeneous mixture of AER devices and that allows recording and playback of recorded data

Interdependency of Port clusters During Regional Disasters

External disruptions to a port may result for storms, such as Hurricane Mathew and Super Storm Sandy, as well as terrorism and oil/hazardous material spill. The overall impact of a disruption on a port is a function of vulnerability of the port and severity of the disruption. The resiliency of ports and inland waterways is critical for maintaining the flow of essential goods throughout the United States and is critical to national security and defense readiness (Sturgis et al., 2014). The research seeks to build upon prior knowledge and expand the scientific understanding of regional disruptions to port clusters, areas of the country with multiple ports servicing the same region. This research will be implicated through the identification of port clusters in the United States that have experienced a major disruptive event. Data will then be collected from ports within these port clusters and a detained time line of events will be developed for each port during its respective destructive event. Port operations will then be systematically quantified as before, during, and after said event. This will enable the identification of trends, patterns, and relationships between the ports throughout their recovery process. Time-depending resiliency plots will be developed to quantify the resiliency of the ports throughout the event. The contribution of this research is to empirically show how port clusters rely upon each other during disruptive events to increase the overall resiliency of water bourn commerce during disruptive events

Port waiting time for oil tankers : Leveraging AIS data to predict port waiting time using machine learning

This master's thesis investigates the predictability of waiting times at crude oil ports using Automatic Identification System (AIS) data and machine learning. Focusing on the wet bulk market, specifically four congested Middle Eastern Gulf ports, we aimed to answer: 11Can the waiting times in crude oil ports be predicted based on AIS data? 11. In this thesis clustering algorithms with novel modifications are utilized to establish berth and anchorage polygons. These polygons form the basis for a spatial matching of AIS data that is used to generate event logs. A cross-sectional data set is derived from the event logs which in turn is the basis for extracting features used in five different machine learning models. The findings show that AIS-derived features have predictive power on waiting times, with vessel composition within ports and port dynamics being significant factors. These insights hold practical implications for ship owners and academics alike, enhancing vessel economics through speed adjustments and facilitating further research within the maritime domain. The thesis also proposes further research areas, including methodology refinement within polygon generation, event log generation and waiting time prediction.nhhma

The logistics management in the sizing of the fleet of containers per ships in dedicated route - The use of computer simulation: A Brazilian shipping company case

The aim of this paper is provide the use of the simulation in the  to manage one important point in the logistics systems to shipping companies that is the imbalance of containers, movement of empty containers from surplus ports to deficit ports.From a survey of data from a shipping company operating in Brazil, at various ports, it was possible to model and simulate the needs in six major domestic ports of empty and full containers and seek to meet demand in the shipping market, reducing storage of containers and maintaining the level of excellence in service.Based on the discrete event simulation it was possible to analyze the problem of empty and full containers at the ports in the maritime transportation system. It was possible study the imbalance situation in the ports e provide one tool the companies to manage yours service.The data are confined to one company located in São Paulo and operating in Brazil at maritime transportation.The research shows that the imbalance problem between full and empty containers is a real case to all companies in the maritime transportation and can have effective solutions using discrete event simulation.To have excellent supply chain management it is important to have also one effective transportation system. This paper contributes to research in the inbound and outbound part of the supply chain management

Preliminary design of an intermittent smoke flow visualization system

A prototype intermittent flow visualization system that was designed to study vortex flow field dynamics has been constructed and tested through its ground test phase. It produces discrete pulses of dense white smoke consisting of particles of terephthalic acid by the pulsing action of a fast-acting three-way valve. The trajectories of the smoke pulses can be tracked by a video imaging system without intruding in the flow around in flight. Two methods of pulsing the smoke were examined. The simplest and safest approach is to simply divert the smoke between the two outlet ports on the valve; this approach should be particularly effective if it were desired to inject smoke at two locations during the same test event. The second approach involves closing off one of the outlet ports to momentarily block the flow. The second approach requires careful control of valve dwell times to avoid excessive pressure buildup within the cartridge container. This method also increases the velocity of the smoke injected into the flow. The flow of the smoke has been blocked for periods ranging from 30 to 80 milliseconds, depending on the system volume and the length of time the valve is allowed to remain open between valve closings

Extending the Real-Time Maude Semantics of Ptolemy to Hierarchical DE Models

This paper extends our Real-Time Maude formalization of the semantics of flat Ptolemy II discrete-event (DE) models to hierarchical models, including modal models. This is a challenging task that requires combining synchronous fixed-point computations with hierarchical structure. The synthesis of a Real-Time Maude verification model from a Ptolemy II DE model, and the formal verification of the synthesized model in Real-Time Maude, have been integrated into Ptolemy II, enabling a model-engineering process that combines the convenience of Ptolemy II DE modeling and simulation with formal verification in Real-Time Maude.Comment: In Proceedings RTRTS 2010, arXiv:1009.398

Oil Spill Detection Analyzing “Sentinel 2“ Satellite Images: A Persian Gulf Case Study

Oil spills near exploitation areas and oil loading ports are often related to the ambitions of governments to get more oil market share and the negligence at the time of the loading in large tankers or ships. The present study investigates one oil spill event using multi sensor satellite images in the Al Khafji (between Kuwait and Saudi Arabia) zone. Oil slicks have been characterized with multi sensor satellite images over the Persian Gulf and then analyzed in order to detect and classify oil spills in this zone. In particular this paper discusses oil pollution detection in the Persian Gulf by using multi sensor satellite images data. Oil spill images have been selected by using Sentinel 2 images pinpointing oil spill zones. ENVI software for analysing satellite images and ADIOS (Automated Data Inquiry for Oil Spills) for oil weathering modelling have been used. The obtained results in Al Khafji zone show that the oil spill moves towards the coastline firstly increasing its surface and then decreasing it until reaching the coastline