An Adaptive and Extensible System for Satellite-Based, Large Scale Burnt Area Monitoring in Near-Real Time

In the case of ongoing wildfire events, timely information on current fire parameters is crucial for informed decision making. Satellite imagery can provide valuable information in this regard, since thermal sensors can detect the exact location and intensity of an active fire at the moment the satellite passes over. This information can be derived and distributed in near-real time, allowing for a picture of current fire activity. However, the derivation of the size and shape of an already affected area is more complex and therefore most often not available within a short time frame. For urgent decision making though, it would be desirable to have this information available in near-real time, and on a large scale. The approach presented here works fully automatic and provides perimeters of burnt areas within two hours after the satellite scene acquisition. It uses the red and near-infrared bands of mid-resolution imagery to facilitate continental-scale monitoring of recently occurred burnt areas. To allow for a high detection capacity independent of the affected vegetation type, segmentation thresholds are derived dynamically from contextual information. This is done by using a Morphological Active Contour approach for perimeter determination. The results are validated against semi-automatically derived burnt areas for five wildfire incidents in Europe. Furthermore, these results are compared with three widely used burnt area datasets on a country-wide scale. It is shown that a high detection quality can be reached in near real-time. The large-scale inter-comparison shows that the results coincide with 63% to 76% of the burnt area in the reference datasets. While these established datasets are only available with a time lag of several months or are created by using manual interaction, the presented approach produces results in near-real time fully automatically. This work is therefore supposed to represent a valuable improvement in wildfire related rapid damage assessment.

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BattleNet: Capturing Advantageous Battlefield in RTS Games (Student Abstract)

Proceedings of the AAAI Conference on Artificial Intelligence ◽

10.1609/aaai.v34i10.7197 ◽

2020 ◽

Vol 34 (10) ◽

pp. 13849-13850

Author(s):

Donghyeon Lee ◽

Man-Je Kim ◽

Chang Wook Ahn

Keyword(s):

Artificial Intelligence ◽

Decision Making ◽

Real Time ◽

Large Scale ◽

Outcome Predictor ◽

Short Term ◽

Rts Game

In a real-time strategy (RTS) game, StarCraft II, players need to know the consequences before making a decision in combat. We propose a combat outcome predictor which utilizes terrain information as well as squad information. For training the model, we generated a StarCraft II combat dataset by simulating diverse and large-scale combat situations. The overall accuracy of our model was 89.7%. Our predictor can be integrated into the artificial intelligence agent for RTS games as a short-term decision-making module.

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Real time in-line monitoring of large scale Bacillus fermentations with near-infrared spectroscopy

Journal of Biotechnology ◽

10.1016/j.jbiotec.2014.09.004 ◽

2014 ◽

Vol 189 ◽

pp. 120-128 ◽

Cited By ~ 22

Author(s):

José Alves-Rausch ◽

Roland Bienert ◽

Christian Grimm ◽

Dirk Bergmaier

Keyword(s):

Infrared Spectroscopy ◽

Real Time ◽

Near Infrared Spectroscopy ◽

Large Scale ◽

Near Infrared

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Collaborative Systems for Decision Making for Disaster Preparedness and Response, Department of Information Systems

Always-On Enterprise Information Systems for Business Continuance ◽

10.4018/978-1-60566-723-2.ch003 ◽

2010 ◽

pp. 41-57

Author(s):

Deidre Hahn ◽

Jessica Block ◽

Mark Keith ◽

Ajay Vinze

Keyword(s):

Decision Making ◽

Real Time ◽

Disaster Preparedness ◽

Large Scale ◽

Emergency Situation ◽

Group Processes ◽

Group Decision Support Systems ◽

Emergency Situations ◽

Collaborative Technologies ◽

Disaster Preparedness And Response

Real time collaboration solutions are critical during a large scale emergency situation and necessitate the coordination of multiple disparate groups. Collaborative technologies may be valuable in the planning and execution of disaster preparedness and response. Yet, research suggests that specific collaborative technologies, such as group decision support systems, are not often leveraged for decision-making during real time emergency situations in the United States. In this chapter, we propose a theoretical model of the impact of disaster immediacy and collaboration systems on group processes and outcomes. Using a 3D model of the dimensions of space, time, and situation, we explore media richness and group polarization within the context of collaboration technologies and disaster situations. We also present the next generation of collaboration technology extensions in order to address the need for more contemporary decisional settings. This set of principles and theories suggest how collaborative technologies may be positioned to better manage future disasters.

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Precise high-throughput online near-infrared spectroscopy assay to determine key cell wall features associated with sugarcane bagasse digestibility

Biotechnology for Biofuels ◽

10.1186/s13068-021-01979-x ◽

2021 ◽

Vol 14 (1) ◽

Author(s):

Xinru Li ◽

Fumin Ma ◽

Chengping Liang ◽

Maoyao Wang ◽

Yan Zhang ◽

...

Keyword(s):

Cell Wall ◽

Infrared Spectroscopy ◽

Real Time ◽

Near Infrared Spectroscopy ◽

High Throughput ◽

Large Scale ◽

Near Infrared ◽

Lignin Content ◽

Cellulose Crystallinity ◽

Sugarcane Germplasm

Abstract Background Sugarcane is one of the most crucial energy crops that produces high yields of sugar and lignocellulose. The cellulose crystallinity index (CrI) and lignin are the two kinds of key cell wall features that account for lignocellulose saccharification. Therefore, high-throughput screening of sugarcane germplasm with excellent cell wall features is considered a promising strategy to enhance bagasse digestibility. Recently, there has been research to explore near-infrared spectroscopy (NIRS) assays for the characterization of the corresponding wall features. However, due to the technical barriers of the offline strategy, it is difficult to apply for high-throughput real-time analyses. This study was therefore initiated to develop a high-throughput online NIRS assay to rapidly detect cellulose crystallinity, lignin content, and their related proportions in sugarcane, aiming to provide an efficient and feasible method for sugarcane cell wall feature evaluation. Results A total of 838 different sugarcane genotypes were collected at different growth stages during 2018 and 2019. A continuous variation distribution of the near-infrared spectrum was observed among these collections. Due to the very large diversity of CrI and lignin contents detected in the collected sugarcane samples, seven high-quality calibration models were developed through online NIRS calibration. All of the generated equations displayed coefficient of determination (R2) values greater than 0.8 and high ratio performance deviation (RPD) values of over 2.0 in calibration, internal cross-validation, and external validation. Remarkably, the equations for CrI and total lignin content exhibited RPD values as high as 2.56 and 2.55, respectively, indicating their excellent prediction capacity. An offline NIRS assay was also performed. Comparable calibration was observed between the offline and online NIRS analyses, suggesting that both strategies would be applicable to estimate cell wall characteristics. Nevertheless, as online NIRS assays offer tremendous advantages for large-scale real-time screening applications, it could be implied that they are a better option for high-throughput cell wall feature prediction. Conclusions This study, as an initial attempt, explored an online NIRS assay for the high-throughput assessment of key cell wall features in terms of CrI, lignin content, and their proportion in sugarcane. Consistent and precise calibration results were obtained with NIRS modeling, insinuating this strategy as a reliable approach for the large-scale screening of promising sugarcane germplasm for cell wall structure improvement and beyond.

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Deploying Technological Innovation in “Real Time”

Vulcan ◽

10.1163/22134603-00701007 ◽

2019 ◽

Vol 7 (1) ◽

pp. 81-110

Author(s):

Seymour E. Goodman

Keyword(s):

Civil War ◽

Scale Development ◽

Real Time ◽

Technological Innovation ◽

Large Scale ◽

Industrial Revolution ◽

American Civil War ◽

First Year ◽

Continental Scale ◽

War Effort

The Industrial Revolution provided the environment and opportunities for the large-scale development and deployment of military technological innovation in “real time,” that is, in time to influence the conduct and outcomes of a major conflict while that conflict was in progress. The case of the Union and Confederate strategies and their implementations during the American Civil War is particularly exemplary because both sides looked to ironclad warships in opposing ways. For the first year of the war each side pursued real-time ironclad warship deployment efforts to influence three different strategic races on a continental scale. Confederate success could have had enormous impacts on the course and outcomes of the war, but by August 1862 the Union had won all three races. Each was won in a different way, each portended how the conduct of the war on water continued, and each provided lessons for both navies to learn. Both sides went forward with revised strategies and renewed vigor to try to build and deploy more than one hundred ironclad warships between them. Over the next three years, the extensive Confederate ironclad program failed in multiple and costly ways to deliver much to the Confederate war effort. The even more extensive Union ironclad program did better primarily by securing what had been won the first year and neutralizing the continuing Confederate ironclad threat, although it failed in other important ways.

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Identification of Abnormal Biliary Anatomy Utilizing Real-Time Near-Infrared Cholangiography: A Report of Two Cases

Case Reports in Gastrointestinal Medicine ◽

10.1155/2017/8628206 ◽

2017 ◽

Vol 2017 ◽

pp. 1-4

Author(s):

Joseph Bozzay ◽

Diego Vicente ◽

Elliot M. Jessie ◽

Carlos J. Rodriguez

Keyword(s):

Decision Making ◽

Real Time ◽

Near Infrared ◽

Imaging System ◽

Biliary Tree ◽

Biliary Duct ◽

Biliary Anatomy ◽

Nir Imaging ◽

Intraoperative Detection ◽

Fluorescence Imaging System

Biliary duct anomalies are commonly encountered during laparoscopic cholecystectomy. Advancements in the field of surgery allow for enhanced intraoperative detection of these abnormalities. Fluorophore injection and near-infrared (NIR) imaging can provide real-time intraoperative anatomic feedback without intraoperative delays and ionizing radiation. This report details two cases where the PINPOINT Endoscopic Fluorescence Imaging System (NOVADAQ, Ontario, Canada) was used to identify anomalies of the biliary tree and guide operative decision-making.

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