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Event-Driven Programming
Published in Julio Sanchez, Maria P. Canton, Software Solutions for Engineers and Scientists, 2018
Julio Sanchez, Maria P. Canton
One of the unique characteristics of Windows is dynamic linking. In DOS the linker operates statically: it takes one or more object and library files and merges them into an executable which physically includes all the code in both the sources and the library modules. Windows programs use conventional libraries and source files at link time, but also a special type of file called a dynamic-link library or DLL. In dynamic linking, the library files are referenced at link time, but the code is not physically incorporated into the executable. When the program runs, the required run-time libraries are loaded into memory and the references are resolved.
Predicting pedestrian crash locations in urban India: An integrated GIS-based spatiotemporal HSID technique
Published in Journal of Transportation Safety & Security, 2023
Md Saddam Hussain, Arkopal K. Goswami, Ankit Gupta
Space-time cube analysis has been employed in various fields of research, yielding encouraging results. This analysis generates clusters of events over space and time, i.e., x- y- and z coordinates, to show their concentrations and evolution in the three-dimensional space. The emerging hotspot analysis then helps visualize these clusters to understand the internal evolution of the occurrences of these events. The clusters constructed in the space-time bins are categorized based on their pattern, i.e., a geographical location that witnessed clustering of an event for over 90% of the total time interval would be classified as a consecutive hotspot. These classifications impart a clear understanding of the nature and dynamics of the clustering pattern simultaneously over space and time, necessary for implementing remedial or mitigative measures. Therefore, space-time cube analysis is getting popular in understanding the distribution of certain events in various research. In his paper, Mo et al. (2020) used space-time cube analysis to study the spatial and temporal patterns of the 2019 novel coronavirus disease outbreaks. Gatalsky et al. (2004) investigated the optimum process of incorporating space-time cube analysis for exploring and representing the events simultaneously in a space-time continuum and their dynamic linking with maps. The study employs spatial and temporal reference data like earthquakes, traffic incidents, etc. A similar analysis was also undertaken to study the Spatio-temporal patterns of crimes in Kyoto city from 2003 to 2004 (Nakaya & Yano, 2010). The study concludes that space-time cube analysis is valuable to obtain new information on the spreading and distribution of crimes from a set of space-time crime events. However, currently in transport safety, only a few researchers have tried to incorporate the space-time cube analysis to inspect the evolution of crashes over space and time simultaneously (Cheng et al., 2018; Kang et al., 2018; Soltani & Askari, 2017). Yoon and Lee (2021) analyzed spatio-temporal changes and factors influencing pedestrian crashes in Seoul, South Korea, from 2009 to 2018 using space-time cube methodology and binary logistic regression analysis. The study concludes that pedestrian injury and fatalities have an inverse relation with the enhancement in pedestrian-related facilities and a positive relationship with areas having a larger share of the elderly population. As demonstrated above, space-time cube analysis is being used extensively to understand the distribution of various events across different research fields. However, their application in transportation safety, especially for pedestrian safety in developing economies, is in its initial stage.