scholarly journals Time domain reflectometry (TDR) potential for soil condition monitoring of geotechnical assets

2019 ◽  
Vol 56 (7) ◽  
pp. 942-955 ◽  
Author(s):  
Giulio Curioni ◽  
David N. Chapman ◽  
Alexander C.D. Royal ◽  
Nicole Metje ◽  
Ben Dashwood ◽  
...  
Keyword(s):  
Condition Monitoring ◽  
Time Domain ◽  
Early Warning ◽  
Warning System ◽  
Early Warning Systems ◽  
Time Domain Reflectometry ◽  
Soil Conditions ◽  
Dry Density ◽  
Term Condition

The performance of geotechnical assets is influenced by various external factors including time and changing loading and environmental conditions. These changes could reduce the asset’s ability to maintain its function, potentially resulting in failure, which could be extremely disruptive and expensive to remediate; thus, the ability to monitor the long-term condition of the ground is clearly desirable as this could function as an early-warning system, permitting intervention prior to failure. This study demonstrates, for the first time, the potential of using time domain reflectometry (TDR) for long-term monitoring of the relative health of an asset (via water content and dry density) in a field trial where a clayey sandy silt was exposed to leaking water from a pipe. TDR sensors were able to provide detailed information on the variation in the soil conditions and detect abrupt changes that would relay a prompt for asset inspections or interventions. It is proposed that TDR could be used alone or together with other shallow geophysical techniques for long-term condition monitoring of critical geotechnical assets. Early-warning systems could be based on thresholds defined from the values or the relative change of the measured parameters.

scholarly journals Potential of time domain reflectometry as early warning system in slope stability monitoring project: A review

2016 ◽  
Author(s):  
Nur S. M. A. Wahab ◽  
Ng W. K. ◽  
Nor H. H. Abdullah ◽  
Anas Ibrahim ◽  
Mohd R. A. Majid ◽  
...  
Keyword(s):  
Slope Stability ◽  
Time Domain ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Time Domain Reflectometry ◽  
Stability Monitoring

scholarly journals Long-term Examination of Bank Crashes Using Panel Logistic Regression: Turkish Banks Failure Case

2016 ◽  
Vol 5 (3) ◽  
pp. 42 ◽  
Author(s):  
Birsen Eygi Erdogan
Keyword(s):  
Logistic Regression ◽  
Early Warning ◽  
Random Effect ◽  
Balance Sheet ◽  
Warning System ◽  
Early Warning Systems ◽  
Bank Failures ◽  
Return On Assets ◽  
Asset Quality

Crises in the financial sector over the last two decades have shown the importance of early warning systems, especially for bank failures. This study aims to develop an early warning system for Turkish commercial bank failures using panel data from 2002 to 2012. The data was analyzed using pooled logistic regression versus random panel logistic regression. The dependent variable was the bank failure, defined as the return-on assets ratio. Factor analysis was used to construct independent variables of financial ratios. The meaningful factors were found as: Interest income and expenditures, Equity, Other income and expenditures, Balance sheet, Deposit, Due, Asset quality. When the focus is sensitivity, the best prediction performance was obtained using random-effect logistic regression.

scholarly journals Brief communication "Landslide Early Warning System: toolbox and general concepts"

2013 ◽  
Vol 13 (1) ◽  
pp. 85-90 ◽  
Author(s):  
E. Intrieri ◽  
G. Gigli ◽  
N. Casagli ◽  
F. Nadim
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Early Warning Systems ◽  
End Users ◽  
Flow Chart ◽  
Warning Systems ◽  
Limited Experience ◽  
Practical Guidelines ◽  
Landslide Early Warning

Abstract. We define landslide Early Warning Systems and present practical guidelines to assist end-users with limited experience in the design of landslide Early Warning Systems (EWSs). In particular, two flow chart-based tools coming from the results of the SafeLand project (7th Framework Program) have been created to make them as simple and general as possible and in compliance with a variety of landslide types and settings at single slope scale. We point out that it is not possible to cover all the real landslide early warning situations that might occur, therefore it will be necessary for end-users to adapt the procedure to local peculiarities of the locations where the landslide EWS will be operated.

scholarly journals Communication architecture of an early warning system

2010 ◽  
Vol 10 (11) ◽  
pp. 2215-2228 ◽  
Author(s):  
M. Angermann ◽  
M. Guenther ◽  
K. Wendlandt
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Satellite Communication ◽  
Warning System ◽  
Early Warning Systems ◽  
Lessons Learned ◽  
Warning Systems ◽  
Communication Architecture ◽  
Design And Implementation ◽  
Communication Links

Abstract. This article discusses aspects of communication architecture for early warning systems (EWS) in general and gives details of the specific communication architecture of an early warning system against tsunamis. While its sensors are the "eyes and ears" of a warning system and enable the system to sense physical effects, its communication links and terminals are its "nerves and mouth" which transport measurements and estimates within the system and eventually warnings towards the affected population. Designing the communication architecture of an EWS against tsunamis is particularly challenging. Its sensors are typically very heterogeneous and spread several thousand kilometers apart. They are often located in remote areas and belong to different organizations. Similarly, the geographic spread of the potentially affected population is wide. Moreover, a failure to deliver a warning has fatal consequences. Yet, the communication infrastructure is likely to be affected by the disaster itself. Based on an analysis of the criticality, vulnerability and availability of communication means, we describe the design and implementation of a communication system that employs both terrestrial and satellite communication links. We believe that many of the issues we encountered during our work in the GITEWS project (German Indonesian Tsunami Early Warning System, Rudloff et al., 2009) on the design and implementation communication architecture are also relevant for other types of warning systems. With this article, we intend to share our insights and lessons learned.

scholarly journals On building early-warning systems for preventing the deterioration of financial institutions’ performance

2019 ◽  
Vol 1 (1) ◽  
pp. 194-202
Author(s):  
Adrian Costea
Keyword(s):  
Financial Institutions ◽  
Early Warning ◽  
Warning System ◽  
Early Warning Systems ◽  
Capital Adequacy ◽  
Self Organizing Map ◽  
Self Organizing Maps ◽  
Performance Dimensions ◽  
Som Model ◽  
Self Organizing

Abstract This paper assesses the financial performance of Romania’s non-banking financial institutions (NFIs) using a neural network training algorithm proposed by Kohonen, namely the Self-Organizing Maps algorithm. The algorithm takes the financial dataset and positiones each observation into a self-organizing map (a two-dimensional map) which can be latter used to visualize the trajectories of an individual NFI and explain it based on different performance dimensions, such as capital adequacy, assets’ quality and profitability. Further, we use the map as an early-warning system that would accurately forecast the NFIs future performance (whether they would stay or be eliminated from the NFI’s Special Register three quarters into the future). The results are promising: the model is able to correctly predict NFIs’ performance movements. Finally, we compared the results of our SOM-based model with those obtained by applying a multivariate logit-based model. The SOM model performed worse in discriminating the NFIs’ performance: the performance classes were not clearly defined and the model lacked the interpretability of the results. In the contrary, the multivariate logit coefficients have nice interpretability and an individual default probability estimate is obtained for each new observation. However, we can benefit from the results of both techniques: the visualization capabilities of the SOM model and the interpretability of multivariate logit-based model.

scholarly journals Early warning and rapid public health response to prevent COVID-19 outbreaks in long-term care facilities (LTCF) by monitoring SARS-CoV-2 RNA in LTCF site-specific sewage samples and assessment of antibodies response in this population: prospective study protocol

BMJ Open ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. e052282
Author(s):  
Bonita E Lee ◽  
Christopher Sikora ◽  
Douglas Faulder ◽  
Eleanor Risling ◽  
Lorie A Little ◽  
...  
Keyword(s):  
Public Health ◽  
Early Warning ◽  
Early Warning System ◽  
Long Term Care ◽  
Warning System ◽  
Control Measures ◽  
Term Care ◽  
Site Specific ◽  
Care Facilities

IntroductionThe COVID-19 pandemic has an excessive impact on residents in long-term care facilities (LTCF), causing high morbidity and mortality. Early detection of presymptomatic and asymptomatic COVID-19 cases supports the timely implementation of effective outbreak control measures but repetitive screening of residents and staff incurs costs and discomfort. Administration of vaccines is key to controlling the pandemic but the robustness and longevity of the antibody response, correlation of neutralising antibodies with commercial antibody assays, and the efficacy of current vaccines for emerging COVID-19 variants require further study. We propose to monitor SARS-CoV-2 in site-specific sewage as an early warning system for COVID-19 in LTCF and to study the immune response of the staff and residents in LTCF to COVID-19 vaccines.Methods and analysisThe study includes two parts: (1) detection and quantification of SARS-CoV-2 in LTCF site-specific sewage samples using a molecular assay followed by notification of Public Health within 24 hours as an early warning system for appropriate outbreak investigation and control measures and cost–benefit analyses of the system and (2) testing for SARS-CoV-2 antibodies among staff and residents in LTCF at various time points before and after COVID-19 vaccination using commercial assays and neutralising antibody testing performed at a reference laboratory.Ethics and disseminationEthics approval was obtained from the University of Alberta Health Research Ethics Board with considerations to minimise risk and discomforts for the participants. Early recognition of a COVID-19 case in an LTCF might prevent further transmission in residents and staff. There was no direct benefit identified to the participants of the immunity study. Anticipated dissemination of information includes a summary report to the immunity study participants, sharing of study data with the scientific community through the Canadian COVID-19 Immunity Task Force, and prompt dissemination of study results in meeting abstracts and manuscripts in peer-reviewed journals.

Toward a typology of weak-signal early alert systems: functional early warning systems in the post-COVID age

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jan Černý ◽  
Martin Potančok ◽  
Elias Castro Hernandez
Keyword(s):  
Peer Review ◽  
Early Warning ◽  
Warning System ◽  
Early Warning Systems ◽  
Weak Signal ◽  
Warning Systems ◽  
Weak Signals ◽  
Content Type ◽  
Human In The Loop ◽  
Early Alert Systems

PurposeThe study aims to expand on the concept of an early warning system (EWS) by introducing weak-signal detection, human-in-the-loop (HIL) verification and response tuning as integral parts of an EWS's design.Design/methodology/approachThe authors bibliographically highlight the evolution of EWS over the last 30+ years, discuss instances of EWSs in various types of organizations and industries and highlight limitations of current systems.FindingsProposed system to be used in the transforming of weak signals to early warnings and associated weak/strong responses.Originality/valueThe authors contribute to existing literature by presenting (1) novel approaches to dealing with some of the well-known issues associated with contemporary EWS and (2) an event-agnostic heuristic for dealing with weak signals.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-11-2020-0513.

Torrent Monitoring and Early Warning Systems Development

2022 ◽  
pp. 195-216
Author(s):  
Dejan Vasović ◽  
Ratko Ristić ◽  
Muhamed Bajrić
Keyword(s):  
Emergency Management ◽  
Early Warning ◽  
Early Warning System ◽  
Catchment Area ◽  
Warning System ◽  
Modern Society ◽  
Early Warning Systems ◽  
Warning Systems ◽  
Small Catchment ◽  
National Emergency

The level of sustainability of a modern society is associated with the ability to manage unwanted stressors from the environment, regardless of origin. Torrential floods represent a hydrological hazard whose frequency and intensity have increased in recent years, mainly due to climate changes. In order to effectively manage the risks of torrents, it is necessary to apply early warning systems, since torrential floods are formed very quickly, especially on the watercourses of a small catchment area. The early warning system is part of a comprehensive torrential flood risk management system, seen as a technical entity for the collection, transformation, and rapid distribution of data. Modern early warning systems are the successors of rudimentary methods used in the past, and they are based on ICT and mobile applications developed in relation to the requirements of end users. The chapter presents an analysis of characteristic examples of the use. The main conclusion of the chapter indicates the need to implement early warning systems in national emergency management structures.

KLR Approach as an Early Warning Indicator of Turkish Currency and Banking Crisis in 2000 and 2001

2016 ◽  
pp. 222-239
Author(s):  
Filiz Eryılmaz
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Financial Stability ◽  
Banking Crisis ◽  
Warning System ◽  
Early Warning Systems ◽  
Lessons Learned ◽  
Warning Systems ◽  
Window Approach ◽  
Global Growth

International organizations as private sector institutions started to develop Early Warning System [EWS] models aiming to anticipate whether and when individual countries can collide with a financial crisis. EWS models can be made most useful to help sustain global growth and maintain financial stability, especially in light of the lessons learned from the current and past crises. This paper proposes Early Warning Systems (EWS) for Turkish Currency and Banking Crisis in 2000 and 2001. To that end “KLR model” or “signaling window” approach developed by Kaminski, Lorezondo and Reinhart (1998) is testified in the empirical part of this research and applied to a sample of Turkey macroeconomic data for the 1998-2003 monthly periods.

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