Marcia R. Friesen

Agent-Based Modeling of the Spread of Influenza-Like Illness in an Emergency Department: A Simulation Study

The objective of this paper was to develop an agent based modeling framework in order to simulate the spread of influenza virus infection on a layout based on a representative hospital emergency department in Winnipeg, Canada. In doing so, the study complements mathematical modeling techniques for disease spread, as well as modeling applications focused on the spread of antibiotic-resistant nosocomial infections in hospitals. Twenty different emergency department scenarios were simulated, with further simulation of four infection control strategies. The agent based modeling approach represents systems modeling, in which the emergency department was modeled as a collection of agents (patients and healthcare workers) and their individual characteristics, behaviors, and interactions. The framework was coded in C + + using Qt4 libraries running under the Linux operating system. A simple ordinary least squares (OLS) regression was used to analyze the data, in which the percentage of patients that be came infected in one day within the simulation was the dependent variable. The results suggest that within the given instance con text, patient-oriented infection control policies (alternate treatment streams, masking symptomatic patients) tend to have a larger effect than policies that target healthcare workers. The agent-based modeling framework is a flexible tool that can be made to reflect any given environment; it is also a decision support tool for practitioners and policymakers to assess the relative impact of infection control strategies. The framework illuminates scenarios worthy of further investigation, as well as counterintuitive findings.

Immigrants' integration and career development in the professional engineering workplace in the context of social and cultural capital

Canada increasingly relies on immigrant engineers to address engineering labour market shortages. However, immigrants identify formal recognition of foreign credentials, barriers to professional licensing and obtaining professional work experience as key challenges to their successful integration. Engineering employers similarly identify credentials recognition, related work experience and communication skills as the three key determinants of an immigrants access to and success in the engineering workplace. The term ‘qualifications recognition’ refers to processes that address these challenges. This study followed 39 immigrant engineers during and after their participation in a university-based qualifications recognition program. Longitudinal data were collected from 2004 through 2009 from immigrant engineers and their workplace internship employers through focus group interviews, survey questionnaires and internship reports. The data were analyzed to explore the integration and career development of immigrant engineers in the engineering workplace, framing professional integration through a theory of human, social and cultural capital, and habitus. The findings suggest that the successful professional integration of immigrant engineers can be interpreted as the acquisition of multiple forms of capital and habitus.

Algorithms for Smartphone and Tablet Image Analysis for Healthcare Applications

Smartphones and tablets are finding their way into healthcare delivery to the extent that mobile health (mHealth) has become an identifiable field within eHealth. In prior work, a mobile app to document chronic wounds and wound care, specifically pressure ulcers (bedsores) was developed for Android smartphones and tablets. One feature of the mobile app allowed users to take images of the wound using the smartphone or tablets integrated camera. In a user trial with nurses at a personal care home, this feature emerged as a key benefit of the mobile app. This paper developed image analysis algorithms that facilitate noncontact measurements of irregularly shaped images (e.g., wounds), where the image is taken with a sole smartphone or tablet camera. The image analysis relies on the sensors integrated in the smartphone or tablet with no auxiliary or add-on instrumentation on the device. Three approaches to image analysis were developed and evaluated: 1) computing depth using autofocus data; 2) a custom sensor fusion of inertial sensors and feature tracking in a video stream; and 3) a custom pinch/zoom approach. The pinch/zoom approach demonstrated the strongest potential and thus developed into a fully functional prototype complete with a measurement mechanism. While image analysis is a very well developed field, this paper contributes to image analysis applications and implementation in mHealth, specifically for wound care.

A Survey of Agent-Based Modeling of Hospital Environmentss

Agent-based modeling has become a viable alternative and complement-to-traditional analysis methods for studying complex social environments. In this paper, we survey the role of agent-based modeling within hospital settings, where agent-based models investigate patient flow and other operational issues as well as the dynamics of infection spread within hospitals or hospital units. While there is a rich history of simulation and modeling of hospitals and hospital units, relatively little work exists, which applies agent-based models to this context.

Vehicular Traffic Monitoring Using Bluetooth Scanning Over a Wireless Sensor Network

The ubiquitous nature of Bluetooth equipped devices has made it opportunistic to scavenge information that can be repurposed for applications other than initially intended. One such opportunity is in vehicular traffic monitoring, whereby sampling of Bluetooth radios serve as proxies for vehicles and consequently for traffic density and flow. This paper discusses a complete data collection system developed at the University of Manitoba that utilizes a variety of wireless networking technologies and devices to collect inferred traffic data at an intersection along a major thoroughfare in an urban setting. Specifically, a wireless sensor network of slave probes was designed and implemented with the objective to collect Bluetooth device information for this purpose. To facilitate easy setup and a long battery life, a solar-powered probe design was investigated. Data from each slave probe is communicated to a master node through XBee communication, where it is stored on a secure digital (SD) memory card before being transmitted to a central server every five minutes over a global system for mobile communications (GSM) cellular network. The server parses the data received and stores it in a database. Consumer and corporate websites may then access this database to display archived data or current data in real-time to various users.

Advancing Intercultural Competency: Canadian Engineering Employers' Experiences with Immigrant Engineers.

This paper explores Canadian engineering employers’ perceptions of and experiences with internationally educated engineers (recent immigrants to Canada) employed in their organisations for varying lengths of time. Qualitative data were collected from employers using focus group methodology. Findings reflected employers’ observations of culturally different behaviours and characteristics in their internationally educated employees, employers’ reactions to cultural differences ranging from negative attributions to tolerance, and the implementation of largely ad hoc intra-organisational strategies for managing cultural differences in employer–employee relationships. Findings exposed the lack of corporate intercultural competency in the Canadian engineering profession. Equity and gatekeeping implications are discussed.

Vehicular Traffic Modeling Governed by Cellular Phone Trajectories

This paper briefly outlines the combination of an Agent Based Modeling (ABM) framework for modeling the flow of traffic in an urban center, using a 3D gaming platform and incorporating real world data extracted from cell phone trajectories to guide agent movements. Results are compared against two other sets of real world data. The model validation shows considerable promise both for the simulation itself and the use of cellular location data to infer traffic patterns.

Algorithms for Size and Color Detection of Smartphone Images of Chronic Wounds for Healthcare Applications

A mobile app for smartphones and tablets to document pressure ulcers was previously developed. The mobile app is part of the rapidly growing field of mobile health. The mobile app replaces paper-based documentation in a healthcare facility with an electronic record. In a user trial in 2013, a key finding was the high value attributed to wound image (photograph) galleries in the mobile app and wound tracking though graphing progression. Consequently, work was undertaken to enhance the imaging features by developing image analysis algorithms for size and color determination of wounds from wound images taken with an on-board smartphone or tablet camera, using no peripheral hardware or ancillary devices in setting up the image. The reliance solely on the internal smartphone sensors to generate high-accuracy measurements brings novelty to the work and specifically in the field of wound management. The work includes three components. The first component, referred to as mask image, obtains the dimensions of an object in the image. The second component, referred to as camera calibration, reconstructs an image taken on an angle (3-D) referenced back to a 2-D plane. The third algorithm determines the range of colors present in an image, separating the image into three component colors by extracting components from the Red Green Blue format of the image, and converting output to red yellow black. An expert system and/or machine learning is recommended to enhance the correlation of wound color to wound stage.

GPU Accelerated Nature Inspired Methods for Modelling Large Scale Bi-directional Pedestrian Movement

Pedestrian movement, although ubiquitous and well-studied, is still not that well understood due to the complicating nature of the embedded social dynamics. Interest among researchers in simulating pedestrian movement and interactions has grown significantly in part due to increased computational and visualization capabilities afforded by high power computing. Different approaches have been adopted to simulate pedestrian movement under various circumstances and interactions. In the present work, bi-directional crowd movement is simulated where an equal numbers of individuals try to reach the opposite sides of an environment. Two movement methods are considered. First a Least Effort Model (LEM) is investigated where agents try to take an optimal path with as minimal changes from their intended path as possible. Following this, a modified form of Ant Colony Optimization (ACO) is proposed, where individuals are guided by a goal of reaching the other side in a least effort mode as well as a pheromone trail left by predecessors. The basic idea is to increase agent interaction, thereby more closely reflecting a real world scenario. The methodology utilizes Graphics Processing Units (GPUs) for general purpose computing using the CUDA platform. Because of the inherent parallel properties associated with pedestrian movement such as proximate interactions of individuals on a 2D grid, GPUs are well suited. The main feature of the implementation undertaken here is that the parallelism is data driven. The data driven implementation leads to a speedup up to 18x compared to its sequential counterpart running on a single threaded CPU. The numbers of pedestrians considered in the model ranged from 2K to 100K representing numbers typical of mass gathering events. A detailed discussion addresses implementation challenges faced and averted. Detailed analysis is also provided on the throughput of pedestrians across the environment.

An agent based model for simulating the spread of sexually transmitted infections.

This work uses agent-based modelling (ABM) to simulate sexually transmitted infection (STIs) spread within a population of 1000 agents over a 10-year period, as a preliminary investigation of the suitability of ABM methodology to simulate STI spread. The work contrasts compartmentalized mathematical models that fail to account for individual agents, and ABMs commonly applied to simulate the spread of respiratory infections. The model was developed in C++ using the Boost 1.47.0 libraries for the normal distribution and OpenGL for visualization. Sixteen agent parameters interact individually and in combination to govern agent profiles and behaviours relative to infection probabilities. The simulation results provide qualitative comparisons of STI mitigation strategies, including the impact of condom use, promiscuity, the form of the friend network, and mandatory STI testing. Individual and population-wide impacts were explored, with individual risk being impacted much more dramatically by population-level behaviour changes as compared to individual behaviour changes.