Single-shot compressed ultrafast photography: a review

Compressed ultrafast photography (CUP) is a burgeoning single-shot computational imaging technique that provides an imaging speed as high as 10 trillion frames per second and a sequence depth of up to a few hundred frames. This technique synergizes compressed sensing and the streak camera technique to capture nonrepeatable ultrafast transient events with a single shot. With recent unprecedented technical developments and extensions of this methodology, it has been widely used in ultrafast optical imaging and metrology, ultrafast electron diffraction and microscopy, and information security protection. We review the basic principles of CUP, its recent advances in data acquisition and image reconstruction, its fusions with other modalities, and its unique applications in multiple research fields

Developing a Resilient Network Ambidexterity Scale

The purpose of this study was to develop a resilient network ambidexterity scale. While numerous research efforts have considered the dimensions of social capital, resilience, and adaptive capacity to evaluate organizations and communities, few have explored social network indicators within organizations that can be used to mobilize ambidextrous strategies during times of disruption. The emphasis here was to understand the tendencies and behaviors that networks possess to sustain or achieve success along the parallel strategies of optimization and exploration. This study progressed in three specific phases toward filling this void in organizational development literature, using a mixed-methods approach. Phase 1 was the development of the item pool and analysis of the scale to establish face and content validity. Phase 2 included administering an online survey to 344 participants. Data collected were analyzed using exploratory factor analysis, followed by a partial confirmatory factor analysis These revealed a two-factor solution central to identifying resilient network ambidexterity: Optimizing Organizational Boundaries and Exploring Novelty. Phase 3 involved getting feedback on the revised scale from organizational leaders and practitioners working in innovative fields to refine the final RNA instrument. This research made connections between resilience and ambidexterity in organizations through ongoing inquiry on ways that fusing distinct paradigms impacts organizational outcomes. The development of this scale can serve as a useful tool for organizations to assess their level of resilience and mobilize the features of optimization and exploration. This dissertation is available in open access at AURA: Antioch University Repository and Archive, http://aura.antioch.edu/ and Ohiolink ETD Center, https://etd.ohiolink.edu

Spatial Solutions and Solution Spaces: The use of Virtual and Augmented Reality in Design Exploration

The recent wave of Virtual and Augmented Reality (VAR) technologies has coincided with new technologies for processing, analyzing and evaluating large amounts of data. In general, the purpose of Data Visualization is to enable the user to discover and understand patterns in data. Good visualizations present large amounts of data in a way that is easily understood, and good interactive visualizations promote intuitive means of exploring relationships. Over the past few years many researchers have looked into the development of immersive Virtual Environment platforms for Big Data visualization, such as, iViz (Donalek et al, 2014) and the work carried out by Masters of Pie and Lumacode for the Big Data VR Challenge in 2016 (Lumapie, 2016). Filtering, combination and scaling have all been identified elsewhere as important interactive techniques used in contemporary data visualization (Olshannikova et al, 2015). Of these, scaling may be the most familiar to architects: for centuries, designers have attempted to experience architectural space in different scales simultaneously, by using models at different scales (Yaneva, 2005), and by employing various drawing techniques to achieve an embodied perception of the designed space. With the use of VAR technologies this becomes easier than ever. At the same time, designers increasingly must understand not just the experience of a design proposal but also the data associated with it

Ambulance Emergency Response Optimization in Developing Countries

The lack of emergency medical transportation is viewed as the main barrier to the access of emergency medical care in low and middle-income countries (LMICs). In this paper, we present a robust optimization approach to optimize both the location and routing of emergency response vehicles, accounting for uncertainty in travel times and spatial demand characteristic of LMICs. We traveled to Dhaka, Bangladesh, the sixth largest and third most densely populated city in the world, to conduct field research resulting in the collection of two unique datasets that inform our approach. This data is leveraged to develop machine learning methodologies to estimate demand for emergency medical services in a LMIC setting and to predict the travel time between any two locations in the road network for different times of day and days of the week. We combine our robust optimization and machine learning frameworks with real data to provide an in-depth investigation into three policy-related questions. First, we demonstrate that outpost locations optimized for weekday rush hour lead to good performance for all times of day and days of the week. Second, we find that significant improvements in emergency response times can be achieved by re-locating a small number of outposts and that the performance of the current system could be replicated using only 30% of the resources. Lastly, we show that a fleet of small motorcycle-based ambulances has the potential to significantly outperform traditional ambulance vans. In particular, they are able to capture three times more demand while reducing the median response time by 42% due to increased routing flexibility offered by nimble vehicles on a larger road network. Our results provide practical insights for emergency response optimization that can be leveraged by hospital-based and private ambulance providers in Dhaka and other urban centers in LMICs