scholarly journals Design and installation of a Prototype Geohazard Monitoring System near Machu Picchu, Peru

2010 ◽  
Vol 10 (9) ◽  
pp. 2031-2038 ◽  
Author(s):  
M. H. Bulmer ◽  
T. Farquhar
Keyword(s):  
Early Warning ◽  
River Flow ◽  
Warning System ◽  
Modular Construction ◽  
Flash Flooding ◽  
Machu Picchu ◽  
The Past ◽  
Rail Line ◽  
Three Rivers ◽  
The Town

Abstract. The town of Machu Picchu, Peru, serves the >700 000 tourists visiting Machu Picchu annually. It has grown threefold in population in the past two decades. Due to the limited low-lying ground, construction is occurring on the unstable valley slopes. Slopes range from <10° on the valley floor to >70° in the surrounding mountains. The town has grown on a delta formed at the confluence of the Alcamayo, Aguas Calientes and Vilcanota Rivers. Geohazards in and around the town of particular concern are 1) large rocks falling onto the town and/or the rail line, 2) flash flooding by any one of its three rivers, and 3) mudflows and landslides. A prototype early warning system that could monitor weather, river flow and slope stability was installed along the Aguas Calientes River in 2009. This has a distributed modular construction allowing components to be installed, maintained, salvaged, and repaired by local technicians. A diverse set of candidate power, communication and sensor technologies was evaluated. Most of the technologies had never been deployed in similar terrain, altitude or weather. The successful deployment of the prototype proved that it is technically feasible to develop early warning capacity in the town.

scholarly journals MIDAS: A New Integrated Flood Early Warning System for the Miño River

Water ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 2319 ◽  
Author(s):  
Diego Fernández-Nóvoa ◽  
Orlando García-Feal ◽  
José González-Cao ◽  
Carlos de Gonzalo ◽  
José Antonio Rodríguez-Suárez ◽  
...  
Keyword(s):  
Early Warning ◽  
Urban Areas ◽  
Early Warning System ◽  
River Flow ◽  
Warning System ◽  
Early Warning Systems ◽  
Precipitation Forecast ◽  
Mitigation Measures ◽  
Flood Alert ◽  
The Impact

Early warning systems have become an essential tool to mitigate the impact of river floods, whose frequency and magnitude have increased during the last few decades as a consequence of climate change. In this context, the Miño River Flood Alert System (MIDAS) early warning system has been developed for the Miño River (Galicia, NW Spain), whose flood events have historically caused severe damage in urban areas and are expected to increase in intensity in the next decades. MIDAS is integrated by a hydrologic (HEC-HMS) and a hydraulic (Iber+) model using precipitation forecast as input data. The system runs automatically and is governed by a set of Python scripts. When any hazard is detected, an alert is issued by the system, including detailed hazards maps, to help decision makers to take precise and effective mitigation measures. Statistical analysis supports the accuracy of hydrologic and hydraulic modules implemented to forecast river flow and flooded critical areas during the analyzed period of time, including some of the most extreme events registered in the Miño River. In fact, MIDAS has proven to be capable of predicting most of the alert situations occurred during the study period, showing its capability to anticipate risk situations.

scholarly journals A Predictive Analytics Infrastructure to Support a Trustworthy Early Warning System

2021 ◽  
Vol 11 (13) ◽  
pp. 5781
Author(s):  
David Baneres ◽  
Ana Elena Guerrero-Roldán ◽  
M. Elena Rodríguez-González ◽  
Abdulkadir Karadeniz
Keyword(s):  
Artificial Intelligence ◽  
Early Warning ◽  
Early Warning System ◽  
Teaching And Learning ◽  
Predictive Analytics ◽  
Warning System ◽  
Intelligence System ◽  
The Past ◽  
Computational Resources ◽  
Analytical Tools

Learning analytics is quickly evolving. Old fashioned dashboards with descriptive information and trends about what happened in the past are slightly substituted by new dashboards with forecasting information and predicting relevant outcomes about learning. Artificial intelligence is aiding this revolution. The accessibility to computational resources has increased, and specific tools and packages for integrating artificial intelligence techniques leverage such new analytical tools. However, it is crucial to develop trustworthy systems, especially in education where skepticism about their application is due to the risk of teachers’ replacement. However, artificial intelligence systems should be seen as companions to empower teachers during the teaching and learning process. During the past years, the Universitat Oberta de Catalunya has advanced developing a data mart where all data about learners and campus utilization are stored for research purposes. The extensive collection of these educational data has been used to build a trustworthy early warning system whose infrastructure is introduced in this paper. The infrastructure supports such a trustworthy system built with artificial intelligence procedures to detect at-risk learners early on in order to help them to pass the course. To assess the system’s trustworthiness, we carried out an evaluation on the basis of the seven requirements of the European Assessment List for trustworthy artificial intelligence (ALTAI) guidelines that recognize an artificial intelligence system as a trustworthy one. Results show that it is feasible to build a trustworthy system wherein all seven ALTAI requirements are considered at once from the very beginning during the design phase.

scholarly journals Corporate Governance And Fraud

2011 ◽  
Vol 5 (3) ◽  
Author(s):  
Rae Weston
Keyword(s):  
Corporate Governance ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Warning Signs ◽  
The Other ◽  
Font Size ◽  
The Past ◽  
Main Bank

<p class="MsoNormal" style="text-align: justify; margin: 0in 34.2pt 0pt 0.5in;"><span style="font-size: 10pt;" lang="EN-AU"><span style="font-family: Times New Roman;">The main bank fraud cases of the past decade are examined to identify warning signs that could and should have been recognised. Brown (2001 and 2004) has rightly highlighted doubling as a key feature of the Leeson and National Australia Bank derivatives losses. This paper takes a wider view of this and other similar events-the Allied Irish fraud, the Sumitomo copper case, the Daiwa Bank losses and the National Australia Bank case &ndash; and examines the other warning signs that could and should have been recognised. If these can be seen as easier to identify while the fraud is in progress than the doubling of transactions, then these may be used to structure an early warning system of some potency.</span></span></p>

MODIFIKASI ASESMEN EARLY WARNING SYSTEM UPAYA PENINGKATAN PENERAPAN KESELAMATAN PASIEN

2020 ◽  
Vol 6 (2) ◽  
pp. 112
Author(s):  
Veronika Hutabarat ◽  
Enie Novieastari ◽  
Satinah Satinah
Keyword(s):  
Action Research ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Planning Action

Salah satu faktor dalam meningkatkan penerapan keselamatan pasien adalah ketersediaan dan efektifitas prasarana dalam rumah sakit. Early warning system (EWS) merupakan prasarana dalam mendeteksi perubahan dini  kondisi pasien. Penatalaksanaan EWS masih kurang efektif karena parameter dan nilai rentang scorenya belum sesuai dengan kondisi pasien. Tujuan penulisan untuk mengidentifikasi efektifitas EWS dalam penerapan keselamatan pasien. Metode penulisan action research melalui proses diagnosa, planning action, intervensi, evaluasi dan  refleksi. Responden dalam penelitian ini adalah  perawat yang bertugas di area respirasi dan pasien dengan kasus kompleks respirasi di Rumah Sakit Pusat Rujukan Pernapasan Persahabatan Jakarta. Analisis masalah dilakukan dengan menggunakan diagram fishbone. Masalah yang muncul belum optimalnya implementasi early warning system dalam penerapan keselamatan pasien. Hasilnya 100% perawat mengatakan REWS membantu mendeteksi kondisi pasien, 97,4 % perawat mengatakan lebih efektif dan 92,3 % perawat mengatakan lebih efesien mendeteksi perubahan kondisi pasien. Modifikasi EWS menjadi REWS lebih efektif dan efesien dilakukan karena disesuaikan dengan jenis dan kekhususan Rumah Sakit dan berdampak terhadap kualitas asuhan keperawatan dalam menerapkan keselamatan pasien. Rekomendasi perlu dilakukan monitoring evaluasi terhadap implementasi t.erhadap implementasi REWS dan pengembangan aplikasi berbasis tehnologi

Development of a Pediatric Early Warning System Using Data-Driven Vital Signs

PEDIATRICS ◽  
2016 ◽  
Vol 137 (Supplement 3) ◽  
pp. 256A-256A
Author(s):  
Catherine Ross ◽  
Iliana Harrysson ◽  
Lynda Knight ◽  
Veena Goel ◽  
Sarah Poole ◽  
...  
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Vital Signs ◽  
Warning System ◽  
Data Driven ◽  
Using Data
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