Performance-Based Tsunami Engineering via a Web-Based GIS Data Explorer

2016 ◽  
Vol 11 (4) ◽  
pp. 624-633
Author(s):  
Dylan Keon ◽  
◽  
Cherri M. Pancake ◽  
Ben Steinberg ◽  
Harry Yeh ◽  
...  
Keyword(s):  
Time Series Data ◽  
Series Data ◽  
Hazard Evaluation ◽  
Web Browser ◽  
Web Based ◽  
Tsunami Simulation ◽  
Require Time ◽  
Future Design ◽  
Simulation Based ◽  
Gis Data

In spite of advances in numerical modeling and computer power, coastal buildings and infrastructures are still designed and evaluated for tsunami hazards based on parametric criteria with engineering “conservatism,” largely because complex numerical simulations require time and resources in order to obtain adequate results with sufficient resolution. This is especially challenging when conducting multiple scenarios across a variety of probabilistic occurrences of tsunamis. Numerical computations that have high temporal and spatial resolution also yield extremely large datasets, which are necessary for quantifying uncertainties associated with tsunami hazard evaluation. Here, we introduce a new web-based tool, the Data Explorer, which facilitates the exploration and extraction of numerical tsunami simulation data. The underlying concepts are not new, but the Data Explorer is unique in its ability to retrieve time series data from massive output datasets in less than a second, the fact that it runs in a standard web browser, and its user-centric approach. To demonstrate the tool’s performance and utility, two examples of hypothetical cases are presented. Its usability, together with essentially instantaneous retrieval of data, makes simulation-based analysis and subsequent quantification of uncertainties accessible, enabling a path to future design decisions based on science, rather than relying solely on expert judgment.

Visual Classification of Formula One Races by Events, Drivers, and Time Periods

2020 ◽  
pp. 101-114
Author(s):  
Tobias Lampprecht ◽  
David Salb ◽  
Marek Mauser ◽  
Huub van de Wetering ◽  
Michael Burch ◽  
...  
Keyword(s):  
Time Series Data ◽  
Series Data ◽  
Time Varying ◽  
Visual Metaphor ◽  
Web Based ◽  
Visual Classification ◽  
Formula One ◽  
Data Worth ◽  
Time Periods

Formula One races provide a wealth of data worth investigating. Although the time-varying data has a clear structure, it is pretty challenging to analyze it for further properties. Here the focus is on a visual classification for events, drivers, as well as time periods. As a first step, the Formula One data is visually encoded based on a line plot visual metaphor reflecting the dynamic lap times, and finally, a classification of the races based on the visual outcomes gained from these line plots is presented. The visualization tool is web-based and provides several interactively linked views on the data; however, it starts with a calendar-based overview representation. To illustrate the usefulness of the approach, the provided Formula One data from several years is visually explored while the races took place in different locations. The chapter discusses algorithmic, visual, and perceptual limitations that might occur during the visual classification of time-series data such as Formula One races.

scholarly journals Web-gLV: A Web Based Platform for Lotka-Volterra Based Modeling and Simulation of Microbial Populations

2019 ◽  
Vol 10 ◽  
Author(s):  
Bhusan K. Kuntal ◽  
Chetan Gadgil ◽  
Sharmila S. Mande
Keyword(s):  
Modeling And Simulation ◽  
Time Series Data ◽  
Microbial Populations ◽  
Series Data ◽  
Estimation Of Parameters ◽  
Valuable Contribution ◽  
Bacterial Populations ◽  
Web Based ◽  
Automatic Estimation ◽  
High Throughput Dna Sequencing

The affordability of high throughput DNA sequencing has allowed us to explore the dynamics of microbial populations in various ecosystems. Mathematical modeling and simulation of such microbiome time series data can help in getting better understanding of bacterial communities. In this paper, we present Web-gLV—a GUI based interactive platform for generalized Lotka-Volterra (gLV) based modeling and simulation of microbial populations. The tool can be used to generate the mathematical models with automatic estimation of parameters and use them to predict future trajectories using numerical simulations. We also demonstrate the utility of our tool on few publicly available datasets. The case studies demonstrate the ease with which the current tool can be used by biologists to model bacterial populations and simulate their dynamics to get biological insights. We expect Web-gLV to be a valuable contribution in the field of ecological modeling and metagenomic systems biology.

scholarly journals Dampak Kebijakan Harga Pembelian Pemerintah Terhadap Produksi Gula Kristal Putih

2021 ◽  
pp. 1-14
Author(s):  
Aditya Arief Rachmadhan ◽  
Nunung Kusnadi ◽  
Andriyono Kilat Adhi
Keyword(s):  
Time Series Data ◽  
Series Data ◽  
Sugar Production ◽  
Policy Objective ◽  
Ex Post ◽  
Simulation Based ◽  
Producer Surplus ◽  
The Government ◽  
The Impact ◽  
White Sugar

The policy objective of Government Purchase Price (HPP) of plantation white sugar in Indonesia is to increase the production. However, while the government increase the HPP, the production was decreased. The purpose of this study was to analize the impact of HPP policy on production of plantation white sugar in Indonesia. This study uses ex-post simulation based on econometrics model (build from monthly time series data from 2012 until 2017, consist of 13 equations and estimated using 2SLS method). The results, ex-post simulation shows that an increase HPP causes an increase in plantation white sugar production and producer surplus. However, an increase in labor wages cause decreased in production. The increase HPP also causes an increase in producer surplus. Based on producer surplus, the biggest impact of the increase in HPP was felt by the farmers.

scholarly journals Automated evaluation of agricultural damage using UAV survey

2018 ◽  
Vol 10 (1) ◽  
pp. 20-30 ◽  
Author(s):  
Daniel Stojcsics ◽  
Zsolt Domozi ◽  
András Molnár
Keyword(s):  
Time Series ◽  
Deep Learning ◽  
Time Series Data ◽  
The State ◽  
Series Data ◽  
Automated Evaluation ◽  
Gis Data ◽  
Automated Process ◽  
Post Production ◽  
Comparison Of The Results

Abstract In the last decade, the rate of the industrial usage of fixed-wing and blended wing aircraft has increased. A 1–2-km2 area can be surveyed by such a drone within 30 to 60 minutes, without any special infrastructure, and this can be repeated at any time. This provides an opportunity to conduct automatized surveys and time series data testing, which can be used as a basis to decide specific processes. The state and the development of the plants can be monitored as well as the spread of pests and the efficiency of the procedures that protect against them. During the surveys, thousands of images are taken of the area, which can be converted to a georeferenced large-sized map within 20 to 40 hours, including post-production and a resolution varying from 0.01 to 0.1 cm/pixel. The paper provides a solution to the industrial post-production of these high-quantity data, in which a deep learning-based automated process using Matlab is presented, including a comparison of the results to the GIS data.

scholarly journals Modeling Analysis and Comparision of Neural Network Simulation Based on ECM and LSTM

2021 ◽  
Vol 2068 (1) ◽  
pp. 012041
Author(s):  
Lingyun Duan ◽  
Ziyuan Liu ◽  
Wen Yu ◽  
Wei Chen ◽  
Dongyan Jin ◽  
...  
Keyword(s):  
Neural Network ◽  
Prediction Accuracy ◽  
Prediction Models ◽  
Time Series Data ◽  
Learning Algorithm ◽  
Series Data ◽  
Neural Network Simulation ◽  
Deep Learning Algorithm ◽  
Modeling Analysis ◽  
Simulation Based

Abstract Comparing the prediction effects of traditional econometric algorithm model and deep learning algorithm model, taking regional GDP as an example, two prediction models of ARMA-ECM and LSTM-SVR are established for prediction, and the prediction results of different models are compared and analyzed. The results show that there are some deviations in the prediction results of the two models, but the prediction trends are the same. The prediction accuracy of LSTM-SVR model will decrease significantly with the reduction of time series data samples, while ARMA-ECM model is not so sensitive.

scholarly journals Advanced data extraction infrastructure: Web based system for management of time series data

2010 ◽  
Vol 219 (4) ◽  
pp. 042034 ◽  
Author(s):  
S Chilingaryan ◽  
A Beglarian ◽  
A Kopmann ◽  
S Vöcking
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Data Extraction ◽  
Series Data ◽  
Web Based ◽  
Web Based System

scholarly journals An expandable web-based platform for visually analyzing basin-scale hydro-climate time series data

2016 ◽  
Vol 78 ◽  
pp. 97-105 ◽  
Author(s):  
Joeseph P. Smith ◽  
Timothy S. Hunter ◽  
Anne H. Clites ◽  
Craig A. Stow ◽  
Tad Slawecki ◽  
...  
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Series Data ◽  
Web Based ◽  
Basin Scale ◽  
Climate Time Series

scholarly journals Automatic quality control and quality control schema in the Observation to Archive

2020 ◽  
Author(s):  
Brenner Silva ◽  
Najmeh Kaffashzadeh ◽  
Erik Nixdorf ◽  
Sebastian Immoor ◽  
Philipp Fischer ◽  
...  
Keyword(s):  
Quality Control ◽  
Time Series Data ◽  
Series Data ◽  
Review Of Literature ◽  
Web Based ◽  
Data Value ◽  
Terrestrial Environments ◽  
Set Up ◽  
Under Construction ◽  
Quality Control Data

<p>The O2A (Observation to Archive) is a data-flow framework for heterogeneous sources, including multiple institutions and scales of Earth observation. In the O2A, once data transmission is set up, processes are executed to automatically ingest (i.e. collect and harmonize) and quality control data in near real-time. We consider a web-based sensor description application to support transmission and harmonization of observational time-series data. We also consider a product-oriented quality control, where a standardized and scalable approach should integrate the diversity of sensors connected to the framework. A review of literature and observation networks of marine and terrestrial environments is under construction to allow us, for example, to characterize quality tests in use for generic and specific applications. In addition, we use a standardized quality flag scheme to support both user and technical levels of information. In our outlook, a quality score should pair the quality flag to indicate the overall plausibility of each individual data value or to measure the flagging uncertainty. In this work, we present concepts under development and give insights into the data ingest and quality control currently operating within the O2A framework.</p>

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