Applying FABRIC as a Tool to Understanding Architectural and Landscape Icons in a Time of Travel Restrictions

Iconic architecture and landscape architecture are most often understood through photographic media that mediates between the idea and the reality for those learning to design. The drastic lockdown responses to COVID-19 and the limitations on local and international travel highlighted the importance of the visual and the potential of the virtual. However, visual media can also be understood as systems that go far beyond a strict representation of an object. In this climate where publicity, politics, and perception play ever more crucial roles, representations of iconic architecture and landscapes increasingly blur the boundaries between the imaginary and the tangible. This paper examines the experience of iconic architecture and landscape in four iconic European cities (Paris, Barcelona, Seville, and Lisbon) as seen through the eyes of fifty postgraduate architecture, interior architecture, and landscape architecture students from New Zealand. It compares their understanding of a building or landscape from its photographic image before engaging with the physical reality. Students were asked to first identify iconic architecture and landscape, then closely analyze and document the essential qualities which established its pre-eminence. A subsequent visit to each of the places provided the opportunity for comparison and the testing of the realities and fictions of the icons themselves. Our research finds that today’s architecture students are savvy and sophisticated consumers of technology. It also presents FABRIC, a conceptual framework that offers additional scaffolding for educating design students through experiential learning in a time of travel restrictions.

Stormwater Runoff Modelling in an Urban Catchment to Plan Risk Management for Contaminant Spills for Stormwater Harvesting

Water quality is a key consideration for urban stormwater harvesting via aquifers. This study assessed catchment spill management options based on a calibrated dynamic wave routing model of stormwater flow in an urban catchment. The study used measured travel times, pluviometer and gauging station observations from 21 storms to calibrate a stormwater model to simulate transport of pollutants from spill locations to the point of harvest. The simulations considered the impact of spill locations, spill durations, storm intensities and storm durations on the pollutant concentration at the point of harvest and travel time of a pollutant spill to the harvesting point. During dry weather, spill events travelled slower than spills occurring during wet weather. For wet weather spills, the shortest travel times tended to occur in higher intensity storms with shorter duration, particularly when a spill occurred in the middle of the storm. Increasing the intensity of rainfall reduced the peak concentration of pollutant at the harvest point via dilution, but it also reduced the time of travel. On a practical level, due to the short response times in urban catchments, management of spills should be supported by automated detection/diversion systems to protect stormwater harvesting schemes.

ULoc

A myriad of IoT applications, ranging from tracking assets in hospitals, logistics, and construction industries to indoor tracking in large indoor spaces, demand centimeter-accurate localization that is robust to blockages from hands, furniture, or other occlusions in the environment. With this need, in the recent past, Ultra Wide Band (UWB) based localization and tracking has become popular. Its popularity is driven by its proposed high bandwidth and protocol specifically designed for localization of specialized "tags". This high bandwidth of UWB provides a fine resolution of the time-of-travel of the signal that can be translated to the location of the tag with centimeter-grade accuracy in a controlled environment. Unfortunately, we find that high latency and high-power consumption of these time-of-travel methods are the major culprits which prevent such a system from deploying multiple tags in the environment. Thus, we developed ULoc, a scalable, low-power, and cm-accurate UWB localization and tracking system. In ULoc, we custom build a multi-antenna UWB anchor that enables azimuth and polar angle of arrival (henceforth shortened to '3D-AoA') measurements, with just the reception of a single packet from the tag. By combining multiple UWB anchors, ULoc can localize the tag in 3D space. The single-packet location estimation reduces the latency of the entire system by at least 3×, as compared with state of art multi-packet UWB localization protocols, making UWB based localization scalable. ULoc's design also reduces the power consumption per location estimate at the tag by 9×, as compared to state-of-art time-of-travel algorithms. We further develop a novel 3D-AoA based 3D localization that shows a stationary localization accuracy of 3.6 cm which is 1.8× better than the state-of-the-art two-way ranging (TWR) systems. We further developed a temporal tracking system that achieves a tracking accuracy of 10 cm in mobile conditions which is 4.3× better than the state-of-the-art TWR systems.

School Commuting: Barriers, Abilities and Strategies toward Sustainable Public Transport Systems in Yogyakarta, Indonesia

This study aims to investigate students’ difficulties in using the bus to get to school based on Rasch analysis and examines students’ innate abilities in handling the barriers. A total of 536 high school students in Yogyakarta were randomly surveyed. This study considers forty barriers of bus use grouped into eight aspects: safety, bus stop reliability, accessibility, mobility, payment system, bus reliability, transfer efficiency, and information and communication technology. The results show that the students experienced 18 main barriers in using the bus. The limited time of travel, circuitous routes, and distance to the bus stops were the three most significant barriers for students in using the bus during the morning commute. Conversely, students reported no difficulty using the bus regarding safety and payment system aspects. This result additionally shows that gender, age, allowance, and drivers’ licenses also influence the extent of the barrier experienced by the students. Finally, some strategies to increase the students’ ability to overcome barriers in utilizing the bus are proposed to create a sustainable public transport system in Yogyakarta.

Modelling speed behaviour in rural highways: Safety analysis of driving under adverse road-weather conditions

This study proposes a methodical approach to model desired speed distributions under different road-weather and traffic conditions followed by identification of road-weather conditions with potentially higher safety risks in rural divided highways located in extremely cold regions. Desired speed distributions encompassing unique combinations of adverse road-weather and traffic conditions are modelled as normal distributions characterized by their means and standard deviations formulated based on two principal statistical theorems and techniques i.e., Central Limit Theorem and Minimum Variance Unbiased Estimation. Combination of the precipitation conditions, road surface conditions, time of the day, temperature, traffic flow and the heavy vehicle percentage at the time of travel were considered in defining the combinations of road-weather and traffic conditions. The findings reveal that simultaneous occurrence of particular precipitation and pavement conditions significantly affect the characteristics of the desired speed distribution and potentially expose drivers to elevated safety risks. Jurisdictions experiencing extreme road-weather conditions may adapt the proposed methodology to assess speed behaviour under different road-weather conditions to establishing and deploying weather-responsive traffic management strategies such as variable speed limit to regulate speeding and improve traffic safety in winter.

Principles for determining effective parameters for organizing train traffic in suburban-urban traffic, taking into account the differentiation of service classes

Introduction of a new transport product in urban agglomerations helps to attract additional passenger traffic by changing parameters of organizing the operation of suburban trains. Problem of determining the effective parameters of the route network of suburban-urban railway communication in order to achieve acceptable financial results for the owners of infrastructure and carriers is considered. Controlled variables are determined that characterize the route network of suburban-urban traffic and include the type of train schedule, the operation interval, the routes, the traffic volume of suburban-urban trains, the station of departure and arrival, the service class. It was also determined that the distribution of passenger traffic correspondence over the network of transport products depends both on a set of controllable variables and on the time of travel by rail when using a transport product, taking into account the execution of terminal operations at points of departure, destination, transfers, waiting for trains, and travel on trains. The objective function for the carrier and the owner of the infrastructure, which is identical for both participants of transportation, is considered, while the components of investment costs and direct production costs for transportation activities and income receipts that ensure the break-even of this activity are different for each participant in transport services. Relevant constraints for the task, due to the resources of the railway infrastructure and rolling stock, have been determined. Authors provides the principles of solving this multicriteria problem by finding a group of the best options by a directed enumeration of alternatives with the subsequent selection of the resulting solution by the methods of compromise control. The research results are intended for use in projects for the development of suburban-urban traffic in large urban agglomerations.

Calibrating Best Route Based on Battery Percentage and Availability of Charging Station

The electric vehicle market is increasing rapidly. Smart cars and AI integrated cars are under development for automatic driving. Embedded software is necessary for an electric vehicle to function properly. Almost all cars have inbuilt software navigation purposes. The user's main concern about electric vehicles is the driving range. Electric cars having an inbuilt navigation system that indicates appropriate charging points suitable for the user. The planning route is essential to reach the destination before the battery dies. The software can provide a solution here by analyzing and optimizing the data which is stored in the cloud. Battery swapping can also be done by booking batteries at charge stations before the time of travel. This solution will promote users to drive electric vehicles for even long travels.

A prediction model for COVID-19 prevalence based on demographic and healthcare parameters in Iran

Coronavirus Disease 2019 (COVID-19) pandemic has become the greatest threat to global health in only a matter of months. Iran struggling with COVID-19 coincidence with Nowruz vacations has led to horrendous consequences for both people and the public health workforce. Modeling approaches have been proved to be highly advantageous in taking appropriate actions in the early stages of the pandemic. To this date, no study has been conducted to model the disease to investigate the disease, especially after travel restrictions in Iran. In this study, we exploited the opportunities that Artificial neural networks offer to investigate contributing factors of early-stage coronavirus spread via generating a model to predict daily confirmed cases in Iran. We collected publicly available data of confirmed cases in 24 provinces from April 4, 2020, to May 2, 2020, with a list of explanatory factors. The factors were checked separately for any linear associations and to train and validate a multilayer perceptron network. The accuracy of the models was evaluated, the R2 scores were 0.842 for population distribution, 0.822 for health index, and 0.864 for the population in the provinces. Our results suggest the significant impact of the mentioned factors on disease spread in the time of travel restrictions when the vacation ended. Accordingly, this information can be implicated in assessing the risk of epidemics and future policy makings in this area.