WE‐E‐E‐611‐02: Where Are We? Ritenour, E; Hendee, W; Heintz, P
Medical physics (Lancaster),
June 2005, Letnik:
32, Številka:
6
Journal Article
Recenzirano
A survey regarding the perceived quality of physics instruction of radiology residents was sent to all radiology programs in 2004. An identical survey was sent to program directors and chief ...residents. The Presidents of the American Association of Academic Chief Residents in Radiology and of the Association of Program Directors wrote cover letters to accompany the surveys, encouraging the expression of frank opinions in this anonymous survey. This presentation will present the results of the survey and will provide some opinions concerning the meaning of the results. Discussion will include information regarding some recent decisions by the American Board of Radiology as to changes in the grading of the physics exam for residents.
In the present study, spatio-temporal urban sprawl and land consumption patterns were analysed in seven capital cities located in the Himalayan region during 1972, 1991 and 2015 using multi-temporal ...satellite images. The study exhibits that capital Himalayan cities experienced rapid growth (830.92%) with high population increase (333.45%) during the observation period (1972–2015). The significant urban growth was observed in the cities of western and middle Himalayan region viz., Srinagar (9.36 km2–142.19 km2), Kathmandu (11.38 km2–92.58 km2) and Dehradun (4.1 km2–50.09 km2) in the higher altitudes due to remarkable increase in the population (0.5–1 million persons) during 1972–2015. On the contrary, Itanagar (7.19 km2), Gangtok (7.09 km2), Shimla (3.04 km2) and Thimphu (2.93 km2) observed less urban growth with moderate to low population growth (i.e., 0.05 to 0.15 million persons). The Shannon entropy based study exhibits that the cities viz., Kathmandu, Gangtok and Itanagar observed comparatively more dispersed urban growth during later period (1991–2015) as compared to the previous period (1972–1991) whereas, the remaining cities observed comparatively less dispersed urban growth during later period. The temporal land consumption pattern exhibits low density urban growth in Srinagar, Dehradun and Kathmandu, as observed with decrease in population density and increasing land consumption during 1972–2015 as compared to other cities, wherein urban densification was evident with increase in population density and decrease in land consumption. The cities in central and western Himalayan region observed high urban growth as compared to cities in eastern Himalayan region. The result shows that the capital cities contributes insignificant proportion (0.5%; 314 km2) of urban area in Himalayan region and accommodating large (ca. 4 million) population during 2015. The study indicates unplanned and haphazard growth in all capital Himalayan cities, leading towards urban densification as well as dispersion in the periphery with varied pattern and intensity. The specific trends and patterns of urban and population growth are governed by geographical as well as socio-economic-political factors at local to regional scale. The high population pressure induced higher risk to the urban residents as well as constrained urban growth over higher vulnerable zones. The study necessitates implementation of suitable urban planning methods considering socio-economic and physico-cultural characteristics of the region.
•0.5% (132 km2) of urban area accommodate ca. 4 million populations in Himalayas 2015.•Western and middle Himalayan cities had high urban and population growth.•Eastern Himalayan cities observed less urban and population growth.•Haphazard urban growth leads to urban densification and dispersion in the periphery.•Urban growth patterns governed by geographical & socio-economic-political factors.
Big Data has emerged in the past few years as a new paradigm providing abundant data and opportunities to improve and/or enable research and decision-support applications with unprecedented value for ...digital earth applications including business, sciences and engineering. At the same time, Big Data presents challenges for digital earth to store, transport, process, mine and serve the data. Cloud computing provides fundamental support to address the challenges with shared computing resources including computing, storage, networking and analytical software; the application of these resources has fostered impressive Big Data advancements. This paper surveys the two frontiers - Big Data and cloud computing - and reviews the advantages and consequences of utilizing cloud computing to tackling Big Data in the digital earth and relevant science domains. From the aspects of a general introduction, sources, challenges, technology status and research opportunities, the following observations are offered: (i) cloud computing and Big Data enable science discoveries and application developments; (ii) cloud computing provides major solutions for Big Data; (iii) Big Data, spatiotemporal thinking and various application domains drive the advancement of cloud computing and relevant technologies with new requirements; (iv) intrinsic spatiotemporal principles of Big Data and geospatial sciences provide the source for finding technical and theoretical solutions to optimize cloud computing and processing Big Data; (v) open availability of Big Data and processing capability pose social challenges of geospatial significance and (vi) a weave of innovations is transforming Big Data into geospatial research, engineering and business values. This review introduces future innovations and a research agenda for cloud computing supporting the transformation of the volume, velocity, variety and veracity into values of Big Data for local to global digital earth science and applications.
The Bátaapáti National Radioactive Waste Repository was created using mining methods in a granitoid formation. Changes in the receiving rock body are monitored by the seismo-acoustic measurement ...network that has been in operation since the cavity was designed. The present work builds on geoinformatics methods and presents automated codes written for a Geographical Information System, which filters out incorrect spatial positions from a large mass of seismoacoustic point sources. The incorrectly measured points show the greatest inaccuracy vertically. The most intense emission source points with appropriate positions can be detected in the areas between the side walls of the adjacent storage chambers and near the fracture system detected along the trench end of the chambers. Based on the distance between the point sources and the storage chambers, it was also possible to refer to the extent of the damaged/disturbed rock zone around the excavation, which means a 7-meter rock belt.
•Climate change aggravates the adverse impacts of flash floods in arid zones.•Flash flood- induced soil erosion has been assessed using hydrological modeling.•Revisiting risk management policies for ...infrastructure project in arid mountainous cities is necessary.
Risk management of flash floods in arid mountainous cities is challenged by the lack of proper data and the unreadiness of infrastructures to handle large floods. Climate projections predict increasing frequency of extreme droughts and floods over these arid zones aggravating the impacts of flash floods by increasing the hardness of the topsoil, making it less efficient at absorbing rain water. This study assesses the hazards of steadily increasing flash floods on voltage towers around Makkah city using hydrological modeling to simulate flow velocity and volume and erosion intensity of floods. Hydrological modeling estimated the maximum discharge rates at Wadi Numan and Wadi Al-Sharaya outlets as 3142 and 2543 m3/s, respectively. Extreme soil erosion rates are encountered in the lower reaches of these basins (11% of the total area) and severe erosion rates (3.6%) were reported in the planned voltage tower path. Catchment's lower reaches are proved highly vulnerable to soil erosion due to the lack of vegetation cover and high flow accumulations. The study alarms revisiting the risk management policies for infrastructure projects in arid mountainous cities considering the climate change impacts on increasing the frequency of unprecedented droughts and floods and their aggravated destructive impacts.
The data of impacts and damage caused by floods is necessary for manipulation to assist and relieve those impacts in each area. The main issue for data acquisition was acquisition methods that affect ...the durations, accuracy, and completeness of data obtained. Most data are currently obtained by field survey for data on impacts in each area. However, this method contains limitations, i.e., taking a long time, high cost, and no real-time data visualization. Thus, this research presented the study to develop an application for inspecting areas under impact and damage caused by floods using deep learning classification for flood classification and land use type classification in the affected areas using digital images, remote sensing data, and crowdsource data notified by users through the accuracy assessment application of classification. It was found that deep learning classification for flood classification had 97.50% accuracy, with Kappa = 0.95. Land use type classification had 93.71% accuracy, with Kappa = 0.91. Flood damage assessment process in this research was different from other previous research that used geospatial data for flood damage inspection, e.g., satellite images. In contrast, this research brought damage data notified by users for processing with flood data in each area by satellite image processing and land use types of classification. The proposed application can calculate damage in each area and visualize real-time results in maps and graphs on the dashboard via the application. Besides, the presented method can be used to verify and visualize data of areas under impact and damage caused by floods in different areas.
Advanced tracking technologies have facilitated the tracking of tourists' movement with high levels of spatial resolution, allowing for the exploration of factors that influence dispersal. However, ...the degree to which different analytical indices impact the results that they generate, remains under-researched. This study uses a high tempo-spatial resolution data set of location tracking information that was collected in the island state of Tasmania, Australia, using a mobile phone research application. It compares the results that emerge when four different analytical indicators are used to quantify tourist dispersal. The results improve understandings of the role that analytical indicators play in assessing dispersal, along with the underlying factors that influence tourists' dispersal at the state scale.
•This study uses a unique high tempo-spatial resolution dataset, using a mobile phone application.•This study assesses how different analytical tools influence the emergence of dispersal factors.•The study assesses the underlying factors that influence tourists' dispersal at the state scale.
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