Ronald Pelot

A suite of objective biomechanical measurement tools for personal load carriage system assessment

For application to military and civilian needs, Defence Research and Development Canada—Toronto contracted Queens University, Kingston to develop a suite of biomechanical assessment and analytical tools to supplement human-based load carriage system assessment methods. This suite of tools permitted efficient objective evaluation of biomechanical aspects of load-bearing webbing, vests, packs and their components, and therefore contributed to early system assessment and a rapid iterative design process. This paper is a summary of five assessment and analytical tools. A dynamic load carriage simulator was developed to simulate cadence of walking, jogging and running. The simulator comprised a computer-controlled pneumatic platform that oscillated anthropometrically weighted mannequins of varying dimensions from which measures of skin contact pressure, hip reaction forces and moments and relative pack-person displacements were taken. A stiffness tester for range of motion provided force-displacement data on pack suspension systems. A biomechanical model was used to determine forces and moments on the shoulders and hips, and validated using a static load distribution mannequin. Subjective perceptual rating systems were used gather soldier feedback during a standardized mobility circuit. Objective outcome measures were validated by means of other objective measures (e.g., Optotrak®, video, Instron®, etc.) and then compared to subjective ratings. This approach led to development of objective performance criteria for load carriage systems and to improvements in load carriage designs that could be used both in the military and in general.

The Influence of Weather Conditions on the Relative Incident Rate of Fishing Vessels

There is a long history of studying the relationship between weather and maritime activities. This article analyzes the link between relative incident rate (RIR) and general weather factors within certain gridded areas and time periods. The study area, which encompasses a broad extent of Atlantic Canadian waters, includes fishing incidents recorded by the Canadian Coast Guard from 1997 to 1999. Methodologies used for traffic track generation in a geographical information system and aggregation of all relevant weather data needed for the statistical analyses are presented. Ultimately, a regression tree was built to illustrate the relationship between incident rate and the following six weather factors: wave height; sea surface temperature; air temperature; ice concentration; fog presence; and precipitation. Results from the regression tree reveal that the RIR defined as (incident number per area-day)/(traffic amount per area-day) across grid cells with incidents, increases as the weather conditions deteriorate in a general way, and the concentration of ice has the biggest influence on the magnitude of incident rates for a given level of traffic exposure. The results from this analysis may assist administrators of maritime traffic, especially those associated with fishing activities, through a better understanding of the influence on RIR of certain weather conditions within given areas in specific time periods.

Estimating discharge rates of oily wastes and deterrence based on aerial surveillance data collected in western Canadian marine waters.

Illegal discharge of waste oil from ships is a major source of mortality for seabirds globally. Using linear and log-linear regression, we explored the relationship between detection rates of marine oily discharges and surveillance effort at different time scales, based on data collected in the Canadian Pacific Ocean by the National Aerial Surveillance Program (NASP) from 1997 to 2006. We introduce an approach for quantifying reductions in discharge rates with increased surveillance while controlling appropriately for surveillance effort, as standard linear correction for effort can introduce considerable bias. Despite low probabilities of detection (0.088-1.1%), we found evidence for reduced discharge rates with increasing surveillance effort for data summarized monthly and bimonthly in region A, which is closest to the NASP base airport. Using residuals derived from the best-fit log-linear models, we found detected discharge rates declined annually (-[0.070 spills/month]×year).

A Multicriteria Decision Analysis Model and Risk Assessment Framework for Carbon Capture and Storage

Multicriteria decision analysis (MCDA) has been applied to various energy problems to incorporate a variety of qualitative and quantitative criteria, usually spanning environmental, social, engineering, and economic fields. MCDA and associated methods such as life-cycle assessments and cost-benefit analysis can also include risk analysis to address uncertainties in criteria estimates. One technology now being assessed to help mitigate climate change is carbon capture and storage (CCS). CCS is a new process that captures CO2 emissions from fossil-fueled power plants and injects them into geological reservoirs for storage. It presents a unique challenge to decisionmakers (DMs) due to its technical complexity, range of environmental, social, and economic impacts, variety of stakeholders, and long time spans. The authors have developed a risk assessment model using a MCDA approach for CCS decisions such as selecting between CO2 storage locations and choosing among different mitigation actions for reducing risks. The model includes uncertainty measures for several factors, utility curve representations of all variables, Monte Carlo simulation, and sensitivity analysis. This article uses a CCS scenario example to demonstrate the development and application of the model based on data derived from published articles and publicly available sources. The model allows high-level DMs to better understand project risks and the tradeoffs inherent in modern, complex energy decisions.

The design of a simulated forcible entry test for fire fighters

This study investigated the physiological responses and performances for 20 fire fighters when completing simulated forcible entry tests. The purpose was to establish the validity of using a tire striking test and to examine the effects of varying the test parameters. The tests consisted of striking a reinforced structure and a weighted truck tire on a plywood covered table with either a 4.54 or a 5.60 kg sledge hammer. The results indicate that the simulated forcible entry tests are short in duration (range = 8.0-17.6 s), but are also physically demanding in terms of cardiovascular response (range = 86.5-97.2 for a percentage of heart rate reserve). The differences in striking a reinforced structure versus hitting a tire were insignificant according to most of the measures taken. The parameters for the simulated forcible entry test that were determined to be most appropriate were to move the tire 30 cm and use the 4.54 kg sledge hammer.

Vessel Location Modeling for Maritime Search and Rescue

The location-allocation problem serves to deploy assets effectively to respond to a known or estimated geographically distributed demand for service, including providing emergency services. At first glance, the rescue vessel location problem in the Search and Rescue (SAR) domain is similar to the emergency vehicle location problem such as for ambulance location. In both cases, mathematical location models can be formulated to maximize the number of incidents that can be serviced by a specified number of resources (vehicles) within a pre-specified amount of time, or, alternatively, we can minimize the time it would take a vehicle to arrive at the scene of the incident. However, several differences exist. First of all, in the case of emergency vehicle location, all response units are generally assumed to have the same capability and speed. Conversely, the Canadian Coast Guard (CCG) has many different SAR rescue vessel types that were designed or purchased with specific tasks in mind, and not all are equally effective at handling different incident types. Also, the ranges vary greatly among different types of rescue vessels, so rescue vessel capabilities need to be considered in our study. Furthermore, the method of computing distances to the incidents is different as rescue vessels are patrolling on the sea, thus requiring a land-avoidance algorithm to calculate the travel distance rather than Euclidean or Manhattan distance metrics. However, land-avoidance distance is calculated before performing the optimization in this study, so this distinction is moot in this instance.

The Potential for Using Very High Spatial Resolution Imagery for Marine Search and Rescue Surveillance

Abstract Recreational boating activities represent one of the highest risk populations in the marine environment. Moreover, there is a trend of increased risk exposure by recreational boaters such as those who undertake adventure tourism, sport fishing/hunting, and personal watercraft (PWC) activities. When trying to plan search and rescue activities, there are data deficiencies regarding inventories, activity type, and spatial location of small, recreational boats. This paper examines the current body of research in the application of remote sensing technology in marine search and rescue. The research suggests commercially available very high spatial resolution satellite (VHSR) imagery can be used to detect small recreational vessels using a sub‐pixel detection methodology. The sub‐pixel detection method utilizes local image statistics based on spatio‐spectral considerations. This methodology would have to be adapted for use with VHSR imagery as it was originally used in hyperspectral imaging. Further, the authors examine previous research on ‘target characterization’ which uses a combination of spectral based classification, and context based feature extraction to generate information such as: length, heading, position, and material of construction for target vessels. This technique is based on pixel‐based processing used in generic digital image processing and computer vision. Finally, a preliminary recreational vessel surveillance system ‐ called Marine Recreational Vessel Reconnaissance (MRV Recon) is tested on some modified VHSR imagery.

An enhanced spatio-spectral template for automatic small recreational vessel detection

This paper examines the performance of a spatiospectral template on Ikonos imagery to automatically detect small recreational boats. The spatiospectral template is utilized and then enhanced through the use of a weighted Euclidean distance metric adapted from the Mahalanobis distance metric. The aim is to assist the Canadian Coast Guard in gathering data on recreational boating for the modeling of search and rescue incidence risk. To test the detection accuracy of the enhanced spatiospectral template, a dataset was created by gathering position and attribute data for 53 recreational vessel targets purposely moored for this research within Cadboro Bay, British Columbia, Canada. The Cadboro Bay study site containing the targets was imaged using Ikonos. Overall detection accuracy was 77%. Targets were broken down into 2 categories: 1) Category A-less than 6 m in length, and Category B-more than 6 m long. The detection rate for Category B targets was 100%, while the detection rate for Category A targets was 61%. It is important to note that some Category A targets were intentionally selected for their small size to test the detection limits of the enhanced spatiospectral template. The smallest target detected was 2.2 m long and 1.1 m wide. The analysis also revealed that the ability to detect targets between 2.2 and 6 m long was diminished if the target was dark in color.

Identifying fishing activities from AIS data with Conditional Random Fields

Fishing activity detection is important for fishery management to maintain abundant oceans. This paper presents a novel approach to identifying fishing activities from Automatic Identification System (AIS) data using Conditional Random Fields (CRFs). CRFs are popular for solving structured prediction problems such as sequence labeling in natural language processing. To model the conditional probability distributions that can identify fishing activities of the vessel points, we treat attributes of vessel points as observed variables and the fishing and non-fishing labels as hidden variables. We present three experiments and two comparisons to demonstrate the stability and effectiveness of the resulting models.

Making sense of Arctic maritime traffic using the Polar Operational Limits Assessment Risk Indexing System (POLARIS)

Maritime traffic volume in the Arctic is growing for several reasons: climate change is resulting in less ice in extent, duration, and thickness; economic drivers are inducing growth in resource extraction traffic, community size (affecting resupply) and adventure tourism. This dynamic situation, coupled with harsh weather, variable operating conditions, remoteness, and lack of straightforward emergency response options, demand robust risk management processes. The requirements for risk management for polar ship operations are specified in the new International Maritime Organization (IMO) International Code for Ships Operating in Polar Waters (Polar Code). The goal of the Polar Code is to provide for safe ship operations and protection of the polar environment by addressing the risk present in polar waters. Risk management is supported by evidence-based models, including threat identification (types and frequency of hazards), exposure levels, and receptor characterization. Most of the information used to perform risk management in polar waters is attained in-situ, but increasingly is being augmented with open-access remote sensing information. In this paper we focus on the use of open-access historical ice charts as an integral part of northern navigation, especially for route planning and evaluation.