Flood Risk Mapping for the City of Toronto

AbstractThe city of Toronto has experienced many major floods over the past century: the flood following hurricane Hazel in October 15, 1954, the August 27, 1976 floods, the August 19, 2005, and the flooding of July 8, 2013. During the latest flooding, some parts of the City of Toronto received over 120mm of rain, while the monthly average for Toronto is 74.4mm. The impact was felt as 300,000 residents were affected by power outages. Other serious disruptions included flight cancellations, subway and other transportation closures. It was the most expensive disaster for the province of Ontario. According to the Insurance Bureau of Canada, the damage of the insured properties exceeded $850 million. This event renewed a debate on a number of issues, such as decaying infrastructure, insufficient flood management, and inadequate standards. Don River, the main river crossing the city, is wide but not deep enough, which together with sedimentation contributes to frequent flooding of surrounding areas. In addition, natural creeks have been buried in sewer pipes, thus losing the natural waterways towards the lake Ontario and forcing existing rivers and creeks to overflow their banks. While floodplain maps are generally available, the estimation of flood risk maps based on population, economic development, and critical infrastructure will enhance city's flood mitigation and preparedness planning. In this paper, we present an approach for determining spatial flood risk index map based on population vulnerabilities and terrain morphological characteristics using a geographic information system

MATCHING REAL AND SYNTHETIC PANORAMIC IMAGES USING A VARIANT OF GEOMETRIC HASHING

This work demonstrates an approach to automatically initialize a visual model-based tracker, and recover from lost tracking, without prior camera pose information. These approaches are commonly referred to as tracking-by-detection. Previous tracking-by-detection techniques used either fiducials (i.e. landmarks or markers) or the object’s texture. The main contribution of this work is the development of a tracking-by-detection algorithm that is based solely on natural geometric features. A variant of geometric hashing, a model-to-image registration algorithm, is proposed that searches for a matching panoramic image from a database of synthetic panoramic images captured in a 3D virtual environment. The approach identifies corresponding features between the matched panoramic images. The corresponding features are to be used in a photogrammetric space resection to estimate the camera pose. The experiments apply this algorithm to initialize a model-based tracker in an indoor environment using the 3D CAD model of the building

HRM, organizational capacity for change, and performance: a global perspective

This special issue brings together a variety of articles, each one enriching understanding about whether and how human resource management (HRM) influences organizational performance (however defined) against a backdrop of complex change. We present a preliminary framework that enables us to integrate the diverse themes explored in the special issue, proposing a mediating role for organizational change capacity (OCC). OCC represents a particular subset within the resource- based literature labeled as “dynamic capabilities.” Although not well researched, there is evidence that OCC is positively associated with firm performance and that this relationship is stronger given conditions of high uncertainty. Our framework reflects on external and internal parameters, which we suggest moderate the relationship between human resource management (HRM), OCC, and organizational performance. Our intention is to provide compelling insight for both practitioners and researchers, especially those whose remit extends beyond national boundaries, with reference to areas of the globe as disparate as Greece, Ireland, Pakistan, Switzerland, and the United Kingdom

Stability Studies for Photovoltaic Integration using Power Hardware-in-the-Loop Experiments

The electrical power network is gradually migrating from a centralized generation approach to a decentralized generation with high shares of renewable energy sources (RES). However, power systems with low shares of synchronous generation and consequently low total system inertia, are vulnerable to power imbalances. Such systems can experience frequency stability problems, such as high frequency excursions and higher rates of change of frequency even under small disturbances. This phenomenon is intensified when the grid under investigation has low or no interconnections (islanded) and thus the challenge for stable operation becomes more significant for the operators. This work focuses on how the frequency stability is affected when a photovoltaic (PV) inverter is integrated into a real non-interconnected distribution grid in Cyprus. In order to capture the realistic interactions of this integration, stability experiments in a hardware-in-the-loop (HIL) environment are performed with the aim to provide insightful results for the grid operator.Comment: The 12th Mediterranean Conference on Power Generation, Transmission, Distribution and Energy Conversion (MEDPOWER 2020

A comparative analysis of scanned maps and imagery for mapping applications

Abstract In mapping organizations, the implementation of more automation coupled with the availability of heterogeneous data requires the investigation, adaptation and evaluation of new approaches and techniques. The demand for rapid mapping operations such as database generation and updating is continuously increasing. Due to the rising use of raster data, image analysis techniques have been investigated and tested in this study to introduce automation in the assessment of scanned topographic monochrome maps and Landsat 7 ETM+ imagery for feature separation and extraction in northern Canada. The work focuses on the detection and extraction of lakes -predominant features in the North -as well as on to their spatiotemporal comparison. Various approaches using digital image processing techniques were implemented and evaluated. Thresholding and texture measures were used to evaluate the potential of rapid extraction of certain topographic elements from scanned monochrome maps of northern Canada. A raster to vector approach (R ! V) followed for the vectorization of these extracted features. The extraction of features from Landsat 7 ETM+ imagery involved image and theme enhancement by applying various image fusion and spectral transformations (e.g., Brovey, PCI-IMGFUSE, intensity -hue -saturation (IHS), principal component analysis (PCA), Tasseled Cap, Normalized Difference Vegetation Index (NDVI)), followed by image classification and thresholding. Tests showed that the approaches were more or less feature-dependent, while, at the same time, they can augment and significantly enhance the conventional topographic mapping methods. Following the analysis of the map and image data, change detection between two lake datasets was performed both interactively and in an automated mode based on the non-intersection of old and new features. The various approaches and methodology developed and implemented within a GIS environment along with examples, results and limitations are presented and discussed. Crow

Organizational culture and effectiveness: A study of values, attitudes, and organizational outcomes

a b s t r a c t a r t i c l e i n f o Organizational culture is defined as a set of beliefs, values, and assumptions that are shared by members of an organization (Schein, 1985). These underlying values have an influence on the behavior of organizational members, as people rely on these values to guide their decisions and behaviors (Schein, 1985). Extrapolating from the influence culture has on the behavior of organizational members, much has been written about the impact of culture on an organization's effectiveness (e.g., Schein, 1985, Quinn, 1988. While the extant research is promising, more empirical evidence of the manner in which organizational culture impacts effectiveness is warranted. Previous research has explored the direct relationships between specific culture domains and specific effectiveness measures (e.g., Quinn and Spreitzer, 1991; Cameron and Freeman, 1991; Denison and Mishra, 1995; Denison, 1990). The purpose of this research is to delve deeper into the relationship between organizational culture and organizational effectiveness by exploring both direct and indirect effects. Siehl and Martin (1990) suggested that culture influences employee attitudes and that those attitudes, in turn, impact organizational effectiveness. We offer an empirical examination of this assertion by testing the mediating effect of employee satisfaction on the culture-effectiveness relationship. Frazier et al. (2004) describe mediating variables as constructs that "establish 'how' or 'why' one variable predicts or causes and outcome variable" (p. 116). Although the relationship between culture and effectiveness is relatively well established in the literature, "how" and "why" this relationship exists has not been adequately addressed. This manuscript attempts to begin to fill that void by exploring employee attitudes as one possible explanatory mechanism through which an organization's culture comes to impact its performance

Big data in an HR context: Exploring organizational change readiness, employee attitudes and behaviors

YesThis research highlights a contextual application for big data within a HR case study setting. This is achieved through the development of a normative conceptual model that seeks to envelop employee behaviors and attitudes in the context of organizational change readiness. This empirical application considers a data sample from a large public sector organization and through applying Structural Equation Modelling (SEM) identifies salary, job promotion, organizational loyalty and organizational identity influences on employee job satisfaction (suggesting and mediating employee readiness for organizational change). However in considering this specific context, the authors highlight how, where and why such a normative approach to employee factors may be limited and thus, proposes through a framework which brings together big data principles, implementation approaches and management commitment requirements can be applied and harnessed more effectively in order to assess employee attitudes and behaviors as part of wider HR predictive analytics (HRPA) approaches. The researchers conclude with a discussion on these research elements and a set of practical, conceptual and management implications of the findings along with recommendations for future research in the area