A Tracking Analyst for large 3D spatiotemporal data from multiple sources (case study: Tracking volcanic eruptions in the atmosphere)

2018 ◽  
Vol 111 ◽  
pp. 283-293 ◽  
Author(s):  
Mohamed A. Gad ◽  
Mai H. Elshehaly ◽  
Denis Gračanin ◽  
Hicham G. Elmongui
Keyword(s):  
Volcanic Eruptions ◽  
Spatiotemporal Data ◽  
Multiple Sources

Polytechnic to Business Project (P2B) a Case of Innovation and Knowledge Transference

2019 ◽  
Vol 6 (1) ◽  
pp. 40-49
Author(s):  
Teresa Paiva
Keyword(s):  
Knowledge Transfer ◽  
Best Practices ◽  
Education Institution ◽  
Theoretical Background ◽  
Transfer Model ◽  
Case Study Method ◽  
Multiple Sources ◽  
The Subject ◽  
Manage Innovation

Background: The theoretical background of this article is on the model developed of knowledge transfer between universities and the industry in order to access the best practices and adapt to the study case in question regarding the model of promoting and manage innovation within the universities that best contribute with solution and projects to the business field. Objective: The development of a knowledge transfer model is the main goal of this article, supported in the best practices known and, also, to reflect in the main measurement definitions to evaluate the High Education Institution performance in this area. Methods: The method for this article development is the case study method because it allows the fully understanding of the dynamics present within a single setting, and the subject examined to comprehend what is being done and what the dynamics mean. The case study does not have a data collection method, as it is a research that may rely on multiple sources of evidence and data which should be converged. Results: Since it’s a case study this article present a fully description of the model proposed and implemented for the knowledge transfer process of the institution. Conclusion: Still in a discussion phase, this article presents as conclusions some questions and difficulties that could be pointed out, as well as some good perspectives of performed activity developed.

scholarly journals The fate of volcanic ash: premature or delayed sedimentation?

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Eduardo Rossi ◽  
Gholamhossein Bagheri ◽  
Frances Beckett ◽  
Costanza Bonadonna
Keyword(s):  
Residence Time ◽  
Volcanic Ash ◽  
Volcanic Eruptions ◽  
Theoretical Description ◽  
Particle Sedimentation ◽  
Weather Modeling ◽  
Explosive Volcanic Eruptions ◽  
Travel Distances ◽  
Ash Dispersal

AbstractA large amount of volcanic ash produced during explosive volcanic eruptions has been found to sediment as aggregates of various types that typically reduce the associated residence time in the atmosphere (i.e., premature sedimentation). Nonetheless, speculations exist in the literature that aggregation has the potential to also delay particle sedimentation (rafting effect) even though it has been considered unlikely so far. Here, we present the first theoretical description of rafting that demonstrates how delayed sedimentation may not only occur but is probably more common than previously thought. The fate of volcanic ash is here quantified for all kind of observed aggregates. As an application to the case study of the 2010 eruption of Eyjafjallajökull volcano (Iceland), we also show how rafting can theoretically increase the travel distances of particles between 138–710 μm. These findings have fundamental implications for hazard assessment of volcanic ash dispersal as well as for weather modeling.

scholarly journals Accessible Routes Integrating Data from Multiple Sources

2020 ◽  
Vol 10 (1) ◽  
pp. 7
Author(s):  
Miguel R. Luaces ◽  
Jesús A. Fisteus ◽  
Luis Sánchez-Fernández ◽  
Mario Munoz-Organero ◽  
Jesús Balado ◽  
...  
Keyword(s):  
Information System ◽  
Data Model ◽  
Large Scale ◽  
Heterogeneous Data ◽  
Multiple Sources ◽  
Heterogeneous Data Sources ◽  
Different Types ◽  
Software Sensors ◽  
The City

Providing citizens with the ability to move around in an accessible way is a requirement for all cities today. However, modeling city infrastructures so that accessible routes can be computed is a challenge because it involves collecting information from multiple, large-scale and heterogeneous data sources. In this paper, we propose and validate the architecture of an information system that creates an accessibility data model for cities by ingesting data from different types of sources and provides an application that can be used by people with different abilities to compute accessible routes. The article describes the processes that allow building a network of pedestrian infrastructures from the OpenStreetMap information (i.e., sidewalks and pedestrian crossings), improving the network with information extracted obtained from mobile-sensed LiDAR data (i.e., ramps, steps, and pedestrian crossings), detecting obstacles using volunteered information collected from the hardware sensors of the mobile devices of the citizens (i.e., ramps and steps), and detecting accessibility problems with software sensors in social networks (i.e., Twitter). The information system is validated through its application in a case study in the city of Vigo (Spain).

scholarly journals Constructing Damage Indices Based on Publicly Available Spatial Data: Exemplified by Earthquakes and Volcanic Eruptions in Indonesia

2021 ◽  
Author(s):  
Emmanuel Skoufias ◽  
Eric Strobl ◽  
Thomas Tveit
Keyword(s):  
Spatial Data ◽  
Volcanic Ash ◽  
Satellite Images ◽  
Fragility Curves ◽  
Volcanic Eruptions ◽  
Damage Indices ◽  
Damage Indicator ◽  
Time Period ◽  
Peak Ground Motion

AbstractThis article demonstrates the construction of earthquake and volcano damage indices using publicly available remote sensing sources and data on the physical characteristics of events. For earthquakes we use peak ground motion maps in conjunction with building type fragility curves to construct a local damage indicator. For volcanoes we employ volcanic ash data as a proxy for local damages. Both indices are then spatially aggregated by taking local economic exposure into account by assessing nightlight intensity derived from satellite images. We demonstrate the use of these indices with a case study of Indonesia, a country frequently exposed to earthquakes and volcanic eruptions. The results show that the indices capture the areas with the highest damage, and we provide overviews of the modeled aggregated damage for all provinces and districts in Indonesia for the time period 2004 to 2014. The indices were constructed using a combination of software programs—ArcGIS/Python, Matlab, and Stata. We also outline what potential freeware alternatives exist. Finally, for each index we highlight the assumptions and limitations that a potential practitioner needs to be aware of.

scholarly journals Cooperation and tensions in multiethnic corporate societies using Teotihuacan, Central Mexico, as a case study

2015 ◽  
Vol 112 (30) ◽  
pp. 9210-9215 ◽  
Author(s):  
Linda R. Manzanilla
Keyword(s):  
Gulf Coast ◽  
Raw Materials ◽  
Volcanic Eruptions ◽  
Cotton Cloth ◽  
Central Mexico ◽  
Economic Power ◽  
Ruling Elite ◽  
Strong Ties ◽  
The Core

In this paper, I address the case of a corporate society in Central Mexico. After volcanic eruptions triggered population displacements in the southern Basin of Mexico during the first and fourth centuries A.D., Teotihuacan became a multiethnic settlement. Groups from different backgrounds settled primarily on the periphery of the metropolis; nevertheless, around the core, intermediate elites actively fostered the movement of sumptuary goods and the arrival of workers from diverse homelands for a range of specialized tasks. Some of these skilled craftsmen acquired status and perhaps economic power as a result of the dynamic competition among neighborhoods to display the most lavish sumptuary goods, as well as to manufacture specific symbols of identity that distinguished one neighborhood from another, such as elaborate garments and headdresses. Cotton attire worn by the Teotihuacan elite may have been one of the goods that granted economic importance to neighborhood centers such as Teopancazco, a compound that displayed strong ties to the Gulf Coast where cotton cloth was made. The ruling elite controlled raw materials that came from afar whereas the intermediate elite may have been more active in providing other sumptuary goods: pigments, cosmetics, slate, greenstone, travertine, and foreign pottery. The contrast between the corporate organization at the base and top of Teotihuacan society and the exclusionary organization of the neighborhoods headed by the highly competitive intermediate elite introduced tensions that set the stage for Teotihuacan’s collapse.

scholarly journals Creating and evaluating web-based visualizations of multi-dimensional spatiotemporal data

2019 ◽  
Vol 2 ◽  
pp. 1-8
Author(s):  
Jan Wilkening ◽  
Keni Han ◽  
Mathias Jahnke
Keyword(s):  
Spatiotemporal Data ◽  
Weather Data ◽  
Temporal Data ◽  
Web Based ◽  
Animated Maps ◽  
Different Types ◽  
Weather Parameters ◽  
Spatio Temporal ◽  
The Web

<p><strong>Abstract.</strong> In this article, we present a method for visualizing multi-dimensional spatio-temporal data in an interactive web-based geovisualization. Our case study focuses on publicly available weather data in Germany. After processing the data with Python and desktop GIS, we integrated the data as web services in a browser-based application. This application displays several weather parameters with different types of visualisations, such as static maps, animated maps and charts. The usability of the web-based geovisualization was evaluated with a free-examination and a goal-directed task, using eye-tracking analysis. The evaluation focused on the question how people use static maps, animated maps and charts, dependent on different tasks. The results suggest that visualization elements such as animated maps, static maps and charts are particularly useful for certain types of tasks, and that more answering time correlates with less accurate answers.</p>

scholarly journals Socio-Cultural Dynamics of Resilience Building: Lesson Learned from Sleman, Indonesia

2019 ◽  
Vol 23 (1) ◽  
pp. 63
Author(s):  
Agusma Putri Wardani ◽  
Bevaola Kusumasari
Keyword(s):  
Community Dynamics ◽  
Public Awareness ◽  
Volcanic Eruptions ◽  
Policy Implications ◽  
Cultural Dynamics ◽  
Community Based Interventions ◽  
Cultural Changes ◽  
Study Results ◽  
Resilient Communities

The eruption of Mount Merapi in 2010 was one of the largest volcanic eruptions in Indonesian history. The catastrophic event resulted in fatalities, loss of homes and livelihoods, infrastructure damage, and trauma for residents. There also a shift in community dynamics. The purpose of this study is to analyse and understand the formation of resilient communities by examining the shift in the society dynamics, specifically socio-cultural changes in community-based interventions. The study is a case study of Pangukrejo Hamlet in Sleman, Indonesia. Study results showed that in the aftermath of the eruption, the community experienced changes in degree of harmony and mutual respect among members. The study identified community economy dynamics, which are attributable to three interventions. Study results formed the basis for drawing policy implications for public awareness of disaster risk and post-disaster recovery in general.

scholarly journals Leveraging Business Data Analytics and Machine Learning Techniques for Competitive Advantage: Case Study Evidence from Small Businesses

2021 ◽  
Vol 2 (1) ◽  
pp. 73-87
Author(s):  
Rathimala Kannan ◽  
Intan Soraya Rosdi ◽  
Kannan Ramakrishna ◽  
Haziq Riza Abdul Rasid ◽  
Mohamed Haryz Izzudin Mohamed Rafy ◽  
...  
Keyword(s):  
Machine Learning ◽  
Competitive Advantage ◽  
Small Businesses ◽  
Data Analytics ◽  
Research Question ◽  
Machine Learning Techniques ◽  
Multiple Sources ◽  
Learning Techniques ◽  
Business Data

Data analytics is the essential component in deriving insights from data obtained from multiple sources. It represents the technology, methods and techniques used to obtain insights from massive datasets. As data increases, companies are looking for ways to gain relevant business insights underneath layers of data and information, to help them better understand new business ventures, opportunities, business trends and complex challenges. However, to date, while the extensive benefits of business data analytics to large organizations are widely published, micro, small, and medium sized organisations have not fully grasped the potential benefits to be gained from data analytics using machine learning techniques. This study is guided by the research question of how data analytics using machine learning techniques can benefit small businesses. Using the case study method, this paper outlines how small businesses in two different industries i.e. healthcare and retail can leverage data analytics and machine learning techniques to gain competitive advantage from the data. Details on the respective benefits gained by the small business owners featured in the two case studies provide important answers to the research question.

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