A compiled project and open-source code to generate web-based forest modelling simulators

Sustainable forest management requires decision support systems to evaluate possible scenarios and anticipate the consequences of decisions. Forest modellers typically develop complex systems of equations to predict the behaviour of forests which makes the use of forest models difficult for end-users in general, affecting transfer of knowledge and technology. To overcome these difficulties and facilitate their practical use, models can be integrated into software to generate user-friendly forest simulators. In this paper we introduce and describe ForestMTIS, a cloud computing compiled and editable open-source project to generate forest simulators which was developed for statistical, non-spatial, deterministic, disaggregated, single species even-aged stand growth and yield models. We demonstrate the use of ForestMTIS based on the development of FlorNExT®, its first practical application, based on a collaborative approach to make growth and yield modelling and sustainable forest management available to a large community of users in the Northeast of Portugal.This work was funded by the EU-FP7 SIMWOOD project (Sustainable Innovative Mobilisation of Wood) under Grant Agreement No. 613762, the Spanish Government through INIA; and the Galician Regional Government (Xunta de Galicia) through INGACAL. The authors acknowledge also the support provided by the Mountain Research Centre and the School of Agriculture of the Polytechnic Institute of Bragança, Portugal, during a research stay of the first author.info:eu-repo/semantics/publishedVersio

AI Enabled Maneuver Identification via the Maneuver Identification Challenge

Artificial intelligence (AI) has enormous potential to improve Air Force pilot training by providing actionable feedback to pilot trainees on the quality of their maneuvers and enabling instructor-less flying familiarization for early-stage trainees in low-cost simulators. Historically, AI challenges consisting of data, problem descriptions, and example code have been critical to fueling AI breakthroughs. The Department of the Air Force-Massachusetts Institute of Technology AI Accelerator (DAF-MIT AI Accelerator) developed such an AI challenge using real-world Air Force flight simulator data. The Maneuver ID challenge assembled thousands of virtual reality simulator flight recordings collected by actual Air Force student pilots at Pilot Training Next (PTN). This dataset has been publicly released at Maneuver-ID.mit.edu and represents the first of its kind public release of USAF flight training data. Using this dataset, we have applied a variety of AI methods to separate "good" vs "bad" simulator data and categorize and characterize maneuvers. These data, algorithms, and software are being released as baselines of model performance for others to build upon to enable the AI ecosystem for flight simulator training.Comment: 10 pages, 7 figures, 4 tables, accepted to and presented at I/ITSE

Simulating sensor networks

Tese de mestrado em Informática, apresentada à Universidade de Lisboa, através da Faculdade de Ciências, 2010Nos últimos anos, as redes de sensores sem fios conheceram um grande impulso em variadas ´áreas, nomeadamente na monitorização industrial e ambiental e, mais recentemente, na logística e noutras aplicações que envolvem processos de negócio e a chamada Internet das Coisas e dos Serviços. Contudo, e apesar dos avanços que se têm verificado tanto em termos de hardware como de software, estas redes são difíceis de programar, testar e instalar. A simulação de redes de sensores é frequentemente utilizada para testar e depurar aplicações para redes de sensores, pois permite testar a execução de das aplicações em ambientes virtuais. Esta tese aborda um problema que diz respeito a testar estas redes através de simulação: a definição (manual) de modelos. A nossa abordagem aponta para a geração de modelos de simulação directamente a partir de aplicações redes de sensores, em particular, modelos para o simulador VisualSense criados a partir de aplicações escritas em Callas, uma linguagem de programação para as redes de sensores. Para tal, criamos uma ferramenta capaz de gerar modelos que ´e paramétrica pelos modelos de rede e modelos sensores da rede que se pretende modelar, e ainda por um conjunto extensível de parâmetros de simulação. As nossas experiências mostraram resultados encorajadores na simulação de redes de grande escala, uma vez que conseguimos executar simulações com até 5000 nós. À medida que as redes de sensores sem fios começam a ser utilizadas em processos de negócio, a informação que recolhem do ambiente tem cada vez mais influência no decurso dos fluxos de trabalho associados aos processos de negócio. De um modo geral, os testes levados a cabo em fluxos de trabalho fazem uso de informação gravada em fluxos de trabalho executados previamente, tornando difícil testar o sistema como um todo. Em alternativa, e como uma segunda proposta desta tese, propomos testar fluxos de trabalho através da incorporação de resultados obtidos nas simulações das aplicações das redes de sensores. Além de cobrir os casos cobertos pela primeira abordagem, esta técnica permite testar novos fluxos de trabalho, bem como as mudanças ocorridas num determinado fluxo de trabalho por acontecimentos no ambiente.In recent years, Wireless Sensor Networks have gaining momentum in several fields, notably in industrial and environmental monitoring and, more recently, in logistics. However, and in spite of the advances in hardware and software, Wireless Sensor Networks are still hard to program, test, and deploy. Simulation is often used for testing and debugging sensor networks because they allow us to perform deployments in virtual environments. This paper addresses a key problem of testing such networks using simulation: (manual) model definition. Our approach is to generate simulation models directly from WSN applications, in particular, VisualSense simulator models from applications written in Callas, a programming language for WSN. For that purpose, we create a model generator tool that is parameter sable by network and sensor templates, and by an extensible set of simulation parameters. Our experiments show encouraging results on simulating large scale networks, as we are able to handle WSN with as many as 5000 nodes. As Wireless Sensor Networks begin to play some role in business processes, the information they gather from the environment influences the execution of workflows. Generally, the tests carried out on these systems make use of recorded information in earlier workflow executions, making it difficult to test the system as a whole. Alternatively, and as a second proposal of this thesis, we propose testing such workflows by incorporating results obtained from the simulation of sensor network applications. Besides covering the situations described in the first approach, this technique allows the testing of new workflows, as well as the changes made to a given workflow by events in the environment

Evaluation of CupCarbon Network Simulator for Wireless Sensor Networks

[EN] Wireless sensor networks (WSNs) are a technology in continuous evolution with great future and a huge quantity of applications. The implementation and deployment of a WSN imply important expenses, so it is interesting to simulate the operation of our design before deploying it. In addition, WSNs are limited by a set of parameters such as the low processing capacity, low storing capacity or limited energy. Energy consumption is the most limiting parameter since the network stability and availability depends on the survival of the nodes. To check the correct operation of a network, currently, there are several network simulators and day by day new proposals are launched. This paper presents the evaluation of a new network simulator called CupCarbon. Along the document, we present the main characteristics of this simulator and check its operation by an example. To evaluate the ease of use of this new network simulator, we propose a modified version of Dijkstra algorithm. In addition of considering the cost route to calculate the best route, it considers the remaining energy in nodes as an additional parameter to evaluate the best route. CupCarbon allows implementing our proposal and the results show that our proposal is able to offer a more stable network with an increase of the network lifetime of the 20%. Finally, to extract some conclusions from our experiences, we compare the characteristics and results of CupCarbon with the most common network simulators currently used by researchers. Our conclusions point out that CupCarbon can be used as a complementary tool for those simulators that are not able to monitor the energy consumption in nodes. However, it needs some improvements to reach the level of functionality of the most used simulators. CupCarbon could be an interesting option for academic environments.López-Pavón, C.; Sendra, S.; Valenzuela-Valdés, JF. (2018). Evaluation of CupCarbon Network Simulator for Wireless Sensor Networks. Network Protocols and Algorithms. 10(2):1-27. https://doi.org/10.5296/npa.v10i2.13201S12710

Computer-based tools for supporting forest management. The experience and the expertise world-wide

Report of Cost Action FP 0804 Forest Management Decision Support Systems (FORSYS)Computer-based tools for supporting forest management. The experience and the expertise world-wide answers a call from both the research and the professional communities for a synthesis of current knowledge about the use of computerized tools in forest management planning. According to the aims of the Forest Management Decision Support Systems (FORSYS) (http://fp0804.emu.ee/) this synthesis is a critical success factor to develop a comprehensive quality reference for forest management decision support systems. The emphasis of the book is on identifying and assessing the support provided by computerized tools to enhance forest management planning in real-world contexts. The book thus identifies the management planning problems that prevail world-wide to discuss the architecture and the components of the tools used to address them. Of importance is the report of architecture approaches, models and methods, knowledge management and participatory planning techniques used to address specific management planning problems. We think that this synthesis may provide effective support to research and outreach activities that focus on the development of forest management decision support systems. It may contribute further to support forest managers when defining the requirements for a tool that best meets their needs. The first chapter of the book provides an introduction to the use of decision support systems in the forest sector and lays out the FORSYS framework for reporting the experience and expertise acquired in each country. Emphasis is on the FORSYS ontology to facilitate the sharing of experiences needed to characterize and evaluate the use of computerized tools when addressing forest management planning problems. The twenty six country reports share a structure designed to underline a problem-centric focus. Specifically, they all start with the identification of the management planning problems that are prevalent in the country and they move on to the characterization and assessment of the computerized tools used to address them. The reports were led by researchers with background and expertise in areas that range from ecological modeling to forest modeling, management planning and information and communication technology development. They benefited from the input provided by forest practitioners and by organizations that are responsible for developing and implementing forest management plans. A conclusions chapter highlights the success of bringing together such a wide range of disciplines and perspectives. This book benefited from voluntary contributions by 94 authors and from the involvement of several forest stakeholders from twenty six countries in Europe, North and South America, Africa and Asia over a three-year period. We, the chair of FORSYS and the editorial committee of the publication, acknowledge and thank for the valuable contributions from all authors, editors, stakeholders and FORSYS actors involved in this project

Modelling approaches for mixed forests dynamics prognosis. Research gaps and opportunities

Aim of study: Modelling of forest growth and dynamics has focused mainly on pure stands. Mixed-forest management lacks systematic procedures to forecast the impact of silvicultural actions. The main objective of the present work is to review current knowledge and forest model developments that can be applied to mixed forests.Material and methods: Primary research literature was reviewed to determine the state of the art for modelling tree species mixtures, focusing mainly on temperate forests.Main results: The essential principles for predicting stand growth in mixed forests were identified. Forest model applicability in mixtures was analysed. Input data, main model components, output and viewers were presented. Finally, model evaluation procedures and some of the main model platforms were described.Research highlights: Responses to environmental changes and management activities in mixed forests can differ from pure stands. For greater insight into mixed-forest dynamics and ecology, forest scientists and practitioners need new theoretical frameworks, different approaches and innovative solutions for sustainable forest management in the context of environmental and social changes.Keywords: dynamics, ecology, growth, yield, empirical, classification

e-Sanctuary: open multi-physics framework for modelling wildfire urban evacuation

The number of evacuees worldwide during wildfire keep rising, year after year. Fire evacuations at the wildland-urban interfaces (WUI) pose a serious challenge to fire and emergency services and are a global issue affecting thousands of communities around the world. But to date, there is a lack of comprehensive tools able to inform, train or aid the evacuation response and the decision making in case of wildfire. The present work describes a novel framework for modelling wildfire urban evacuations. The framework is based on multi-physics simulations that can quantify the evacuation performance. The work argues that an integrated approached requires considering and integrating all three important components of WUI evacuation, namely: fire spread, pedestrian movement, and traffic movement. The report includes a systematic review of each model component, and the key features needed for the integration into a comprehensive toolkit