scholarly journals A Novel Multi-Risk Assessment Web-Tool for Evaluating Future Impacts of Global Change in Mountainous Areas

Climate ◽  
2018 ◽  
Vol 6 (4) ◽  
pp. 92 ◽  
Author(s):  
Gilles Grandjean ◽  
Loïc Thomas ◽  
Séverine Bernardie ◽  
The SAMCO Team

In our study, we present a proactive decision support tool able to compute the impacts of different possible scenarios for territories impacted by mountain risks. The objective of this work was to develop and test various hazard and risk assessment methods, and to implement them into a web-application platform able to show possible risks induced by global change on ecosystems and society. Four case studies were selected for their representativeness: One located in a Pyrenean valley, others in the French Alps. Methodology addressed several points. The first one was on the identification of the impacts of global environmental changes (climatic situations, land use, and socio-economic systems) on identified hazards. The second one was on the analysis of these impacts in terms of vulnerability (e.g., the places and the physical modifications of impacted stakes, as well as levels of perturbation). The third one was on the integration of developed methodologies in a single coherent framework in order to investigate and map indicators of vulnerability. The last one was on the development of a demonstration platform with GIS (Geographic Information System) capabilities and usable on the web. The architecture and the main features of the web-platform are detailed within several cases for which hazard and impact assessments are evaluated for not only past and present, but also future periods. This web-tool, mostly dedicated to stakeholders, has proven its usefulness to test various socio-economical pathways, because multiple scenarios, considered as probable in inhabited valleys, can be benchmarked, analyzed, and compared.

Animals ◽  
2020 ◽  
Vol 10 (6) ◽  
pp. 983
Author(s):  
Luigi Possenti ◽  
Lara Savini ◽  
Annamaria Conte ◽  
Nicola D'Alterio ◽  
Maria Luisa Danzetta ◽  
...  

The Italian National Veterinary Services, public health professionals, and policy makers are asked to participate at different levels in the decision-making process for the management of non-epidemic emergencies. A decision support system offering the different administrative and operational emergency management levels with a spatial and decisional tool to be used in the case of natural disasters is still missing at the national level. Within this context, the Italian General Directorate for Animal Health of the Ministry of Health funded a research project for the implementation of a new Veterinary Information System for Non-Epidemic Emergencies (SIVENE), an innovative real-time decision support tool for emergency response in a disaster management scenario. SIVENE was developed according to a multi-layer architecture with four integrated components: the database layer, which was implemented by an RDBMS Oracle 11 g; the ReST service layer, which was created using J2EE, Spring, and MyBatis technologies; the web application (business framework and user interface), which was developed in Angular4 framework using TypeScript language; and the web Geographic Information Systems (GIS), which was realized through the implementation of a geodatabase in Oracle RDBMS 11 g. This system allows us to build up and dynamically create a set of dedicated checklists to be used in the field when gathering the information needed for the management of non-epidemic emergencies; employ the application on mobile devices, such as tablets and smartphones; and use the web GIS to manage and visualize data of veterinary interest and territorial maps of risk and damage.


2016 ◽  
Vol 156 (1) ◽  
pp. 171-182 ◽  
Author(s):  
Ian M. Collins ◽  
Adrian Bickerstaffe ◽  
Thilina Ranaweera ◽  
Sanjaya Maddumarachchi ◽  
Louise Keogh ◽  
...  

2021 ◽  
Vol 17 (4) ◽  
pp. 95-99
Author(s):  
Sergey N. Shergin ◽  
Nikita V. Denisov ◽  
Viktor V. Luka
Keyword(s):  
Web Tool ◽  

The article discusses a web application for creating, managing and structuring the bank (set) of tests. In the course of the work, a structured database was proposed, and the web application was optimized. The main goal is to take as a basis the current module for managing and creating a bank of test tasks of the moodle system and optimize it.


Author(s):  
Ed Owens ◽  
Elliott Taylor ◽  
Chunjiang An ◽  
Zhi Chen ◽  
George Danner ◽  
...  

ABSTRACT #1141234 The coastal waters of Canada embrace a wide range of physical environments and ecosystems from the warm, sediment-rich waters of the Bay of Fundy to the nutrient-limited cold waters of the high Arctic. This range of biophysical characteristics impacts natural attenuation and weathering processes for oil stranded on shorelines. This study was conducted to: 1) identify and quantify the primary regional parameters that control shoreline oil translocation (removal) processes and pathways and 2) define the effectiveness and environmental consequences of current and potential oiled shoreline treatment strategies and tactics. A specific knowledge gap, here and elsewhere in the world, has been in understanding how the distribution and character of fine-grained sediments affect stranded oil attenuation. Fine-grained sediments (<1mm) can play a critical role in natural or induced (that is, shoreline treatment) oil dispersal. Shoreline sediment samples were collected and analyzed from representative locations on Arctic, Atlantic, and Pacific Ocean beaches to provide a broad geographic characterization of mineral fines at the regional level. This knowledge is the basis for an “Oiled Shoreline Response Program (SRP) Decision Support Tool” to aid spill scientists, students, environmental resource managers, spill responders and the public in understanding the response methods and the ramifications and consequences of their shoreline treatment options without the need to digest technical papers, large reports, or data bases. This MPRI SRP Decision Support Tool is intended to be a dynamic, interactive, multi-layered, geographically and seasonally-based model for shoreline oil spill response decision analyses. A goal of this interactive model is to move away from the traditional static format of learning from explanations in text reports and publications to an interactive tool that encourages its users to explore and fully understand the significance of the different environmental factors outlined in publications and data bases. Recent advances in web technology make this possible. The development of user interface platforms such as React, libraries such as D3, and notebook forms like Observable has created a palette of technologies that together make web application patterns such as Documodels a much more streamlined development process. The power of this medium is to convey a complex subject and to enable a user to grasp keen insights and so understand the consequences of intervention decisions.


F1000Research ◽  
2020 ◽  
Vol 9 ◽  
pp. 832
Author(s):  
Finn Kuusisto ◽  
Daniel Ng ◽  
John Steill ◽  
Ian Ross ◽  
Miron Livny ◽  
...  

Many important scientific discoveries require lengthy experimental processes of trial and error and could benefit from intelligent prioritization based on deep domain understanding. While exponential growth in the scientific literature makes it difficult to keep current in even a single domain, that same rapid growth in literature also presents an opportunity for automated extraction of knowledge via text mining. We have developed a web application implementation of the KinderMiner algorithm for proposing ranked associations between a list of target terms and a key phrase. Any key phrase and target term list can be used for biomedical inquiry. We built the web application around a text index derived from PubMed. It is the first publicly available implementation of the algorithm, is fast and easy to use, and includes an interactive analysis tool. The KinderMiner web application is a public resource offering scientists a cohesive summary of what is currently known about a particular topic within the literature, and helping them to prioritize experiments around that topic. It performs comparably or better to similar state-of-the-art text mining tools, is more flexible, and can be applied to any biomedical topic of interest. It is also continually improving with quarterly updates to the underlying text index and through response to suggestions from the community. The web application is available at https://www.kinderminer.org.


Author(s):  
Adam J. E. Blanchard ◽  
Catherine S. Shaffer ◽  
Kevin S. Douglas

Professionals often utilize some form of structured approach (i.e., decision support tool or risk assessment instrument) when evaluating the risk of future violence and associated management needs. This chapter presents an overview of decision support tools that are used to assist professionals when conducting a violence risk assessment and that have received considerable empirical evaluation and professional uptake. The relative strengths and weaknesses of the two main approaches to evaluations of risk (actuarial and structured professional judgment) are discussed, including a review of empirical findings regarding their predictive validity. Following a summary of commonalities among the tools, this chapter provides a brief description of 10 decision support tools focusing on their applicability and purpose, content and characteristics, and available empirical research. Finally, the chapter concludes with a discussion of several critical considerations regarding the appropriate use and selection of tools.


Energies ◽  
2020 ◽  
Vol 13 (6) ◽  
pp. 1364 ◽  
Author(s):  
Sławomir Francik ◽  
Adrian Knapczyk ◽  
Artur Knapczyk ◽  
Renata Francik

The biomass is regarded as a part of renewable energy sources (RES), which can satisfy energy demands. Biomass obtained from plantations is characterized by low bulk density, which increases transport and storage costs. Briquetting is a technology that relies on pressing biomass with the aim of obtaining a denser product (briquettes). In the production of solid biofuels, the technological as well as material variables significantly influence the densification process, and as a result influence the end quality of briquette. This process progresses differently for different materials. Therefore, the optimal selection of process’ parameters is very difficult. It is necessary to use a decision support tool—decision support system (DSS). The purpose of the work was to develop a decision support system that would indicate the optimal parameters for conducting the process of producing Miscanthus and willow briquettes (pre-comminution, milling and briquetting), briquette parameters (durability and specific density) and total energy consumption based on process simulation. Artificial neural networks (ANNs) were used to describe the relationship between individual parameters of the briquette production process. DSS has the form of a web application and is opened from a web browser (it is possible to open it on various types of devices). The modular design allows the modification and expansion the application in the future.


Author(s):  
Stephen Burgess ◽  
Don Schauder

This chapter discusses a model that has been set up to assist small businesses in the decision-making processes associated with setting up a Web site by which they can interact with their customers. Specifically, the chapter addresses the use of a spreadsheet to support decision-making processes in relation to the level of capital needed to devote to the Web site and who should be used to develop it. The chapter describes the process followed, from the initial SWOT analysis used to collect information about the business to the decision-making process modelled in the spreadsheet.


2021 ◽  
Author(s):  
Varun Suraj ◽  
Catherine Del Vecchio Fitz ◽  
Laura B. Kleiman ◽  
Jeremy Warner ◽  
Gil Alterovitz

UNSTRUCTURED The coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has infected 83 million individuals at the time of writing. In this paper, we describe the creation of a clinical decision support tool, the SMART COVID Navigator, a web application to assist clinicians in treating COVID-19 patients. A large volume of research findings from observational studies about disease interactions with COVID-19 are being produced almost daily. Our app allows clinicians to access a patient’s electronic health records and identify disease interactions from a large set of observational research studies that affect severity and fatality due to COVID-19. We also analyze the results of the collected studies to determine which medical conditions result in an increased chance of severity and/or fatality of COVID-19 progression.


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