Assessment of data-driven modeling strategies for water delivery canals

The aim of this paper is to develop models for experimental open-channel water delivery systems and assess the use of three data-driven modeling tools toward that end. Water delivery canals are nonlinear dynamical systems and thus should be modeled to meet given operational requirements while capturing all relevant dynamics, including transport delays. Typically, the derivation of first principle models for open-channel systems is based on the use of Saint-Venant equations for shallow water, which is a time-consuming task and demands for specific expertise. The present paper proposes and assesses the use of three data-driven modeling tools: artificial neural networks, composite local linear models and fuzzy systems. The canal from Hydraulics and Canal Control Nucleus (A parts per thousand vora University, Portugal) will be used as a benchmark: The models are identified using data collected from the experimental facility, and then their performances are assessed based on suitable validation criterion. The performance of all models is compared among each other and against the experimental data to show the effectiveness of such tools to capture all significant dynamics within the canal system and, therefore, provide accurate nonlinear models that can be used for simulation or control. The models are available upon request to the authors.

Assessment of data-driven modeling strategies for water delivery canals

Conferência: CONTROLO’2012 - 16-18 July 2012 - Funchal

Water quality issues in rivers, lakes and reservoirs in Asian countries: an approach to the problems and the methodologies

Water covers over 70% of the Earth's surface, and is vital for all known forms of life. But only 3% of the Earth's water is fresh water, and less than 0.3% of all freshwater is in rivers, lakes, reservoirs and the atmosphere. However, rivers and lakes are an important part of fresh surface water, amounting to about 89%. In this Master Thesis dissertation, the focus is on three types of water bodies – rivers, lakes and reservoirs, and their water quality issues in Asian countries. The surface water quality in a region is largely determined both by the natural processes such as climate or geographic conditions, and the anthropogenic influences such as industrial and agricultural activities or land use conversion. The quality of the water can be affected by pollutants discharge from a specific point through a sewer pipe and also by extensive drainage from agriculture/urban areas and within basin. Hence, water pollutant sources can be divided into two categories: Point source pollution and Non-point source (NPS) pollution. Seasonal variations in precipitation and surface run-off have a strong effect on river discharge and the concentration of pollutants in water bodies. For example, in the rainy season, heavy and persistent rain wash off the ground, the runoff flow increases and may contain various kinds of pollutants and, eventually, enters the water bodies. In some cases, especially in confined water bodies, the quality may be positive related with rainfall in the wet season, because this confined type of fresh water systems allows high dilution of pollutants, decreasing their possible impacts. During the dry season, the quality of water is largely related to industrialization and urbanization pollution. The aim of this study is to identify the most common water quality problems in Asian countries and to enumerate and analyze the methodologies used for assessment of water quality conditions of both rivers and confined water bodies (lakes and reservoirs). Based on the evaluation of a sample of 57 papers, dated between 2000 and 2012, it was found that over the past decade, the water quality of rivers, lakes, and reservoirs in developing countries is being degraded. Water pollution and destruction of aquatic ecosystems have caused massive damage to the functions and integrity of water resources. The most widespread NPS in Asian countries and those which have the greatest spatial impacts are urban runoff and agriculture. Locally, mine waste runoff and rice paddy are serious NPS problems. The most relevant point pollution sources are the effluents from factories, sewage treatment plant, and public or household facilities. It was found that the most used methodology was unquestionably the monitoring activity, used in 49 of analyzed studies, accounting for 86%. Sometimes, data from historical databases were used as well. It can be seen that taking samples from the water body and then carry on laboratory work (chemical analyses) is important because it can give an understanding of the water quality. 6 papers (11%) used a method that combined monitoring data and modeling. 6 papers (11%) just applied a model to estimate the quality of water. Modeling is a useful resource when there is limited budget since some models are of free download and use. In particular, several of used models come from the U.S.A, but they have their own purposes and features, meaning that a careful application of the models to other countries and a critical discussion of the results are crucial. 5 papers (9%) focus on a method combining monitoring data and statistical analysis. When there is a huge data matrix, the researchers need an efficient way of interpretation of the information which is provided by statistics. 3 papers (5%) used a method combining monitoring data, statistical analysis and modeling. These different methods are all valuable to evaluate the water quality. It was also found that the evaluation of water quality was made as well by using other types of sampling different than water itself, and they also provide useful information to understand the condition of the water body. These additional monitoring activities are: Air sampling, sediment sampling, phytoplankton sampling and aquatic animal tissues sampling. Despite considerable progress in developing and applying control regulations to point and NPS pollution, the pollution status of rivers, lakes, and reservoirs in Asian countries is not improving. In fact, this reflects the slow pace of investment in new infrastructure for pollution control and growing population pressures. Water laws or regulations and public involvement in enforcement can play a constructive and indispensable role in environmental protection. In the near future, in order to protect water from further contamination, rapid action is highly needed to control the various kinds of effluents in one region. Environmental remediation and treatment of industrial effluent and municipal wastewaters is essential. It is also important to prevent the direct input of agricultural and mine site runoff. Finally, stricter environmental regulation for water quality is required to support protection and management strategies. It would have been possible to get further information based in the 57 sample of papers. For instance, it would have been interesting to compare the level of concentrations of some pollutants in the diferente Asian countries. However the limit of three months duration for this study prevented further work to take place. In spite of this, the study objectives were achieved: the work provided an overview of the most relevant water quality problems in rivers, lakes and reservoirs in Asian countries, and also listed and analyzed the most common methodologies.

Autonomic workflow activities: the award framework

Workflows have been successfully applied to express the decomposition of complex scientific applications. This has motivated many initiatives that have been developing scientific workflow tools. However the existing tools still lack adequate support to important aspects namely, decoupling the enactment engine from workflow tasks specification, decentralizing the control of workflow activities, and allowing their tasks to run autonomous in distributed infrastructures, for instance on Clouds. Furthermore many workflow tools only support the execution of Direct Acyclic Graphs (DAG) without the concept of iterations, where activities are executed millions of iterations during long periods of time and supporting dynamic workflow reconfigurations after certain iteration. We present the AWARD (Autonomic Workflow Activities Reconfigurable and Dynamic) model of computation, based on the Process Networks model, where the workflow activities (AWA) are autonomic processes with independent control that can run in parallel on distributed infrastructures, e. g. on Clouds. Each AWA executes a Task developed as a Java class that implements a generic interface allowing end-users to code their applications without concerns for low-level details. The data-driven coordination of AWA interactions is based on a shared tuple space that also enables support to dynamic workflow reconfiguration and monitoring of the execution of workflows. We describe how AWARD supports dynamic reconfiguration and discuss typical workflow reconfiguration scenarios. For evaluation we describe experimental results of AWARD workflow executions in several application scenarios, mapped to a small dedicated cluster and the Amazon (Elastic Computing EC2) Cloud.

Autonomic Activities in the Execution of Scientific Workflows: Evaluation of the AWARD Framework

Workflows have been successfully applied to express the decomposition of complex scientific applications. However the existing tools still lack adequate support to important aspects namely, decoupling the enactment engine from tasks specification, decentralizing the control of workflow activities allowing their tasks to run in distributed infrastructures, and supporting dynamic workflow reconfigurations. We present the AWARD (Autonomic Workflow Activities Reconfigurable and Dynamic) model of computation, based on Process Networks, where the workflow activities (AWA) are autonomic processes with independent control that can run in parallel on distributed infrastructures. Each AWA executes a task developed as a Java class with a generic interface allowing end-users to code their applications without low-level details. The data-driven coordination of AWA interactions is based on a shared tuple space that also enables dynamic workflow reconfiguration. For evaluation we describe experimental results of AWARD workflow executions in several application scenarios, mapped to the Amazon (Elastic Computing EC2) Cloud.

Identification of tsunami-induced deposits using numerical modeling and rock magnetism techniques: A study case of the 1755 Lisbon tsunami in Algarve, Portugal

Storm- and tsunami-deposits are generated by similar depositional mechanisms making their discrimination hard to establish using classic sedimentologic methods. Here we propose an original approach to identify tsunami-induced deposits by combining numerical simulation and rock magnetism. To test our method, we investigate the tsunami deposit of the Boca do Rio estuary generated by the 1755 earthquake in Lisbon which is well described in the literature. We first test the 1755 tsunami scenario using a numerical inundation model to provide physical parameters for the tsunami wave. Then we use concentration (MS. SIRM) and grain size (chi(ARM), ARM, B1/2, ARM/SIRM) sensitive magnetic proxies coupled with SEM microscopy to unravel the magnetic mineralogy of the tsunami-induced deposit and its associated depositional mechanisms. In order to study the connection between the tsunami deposit and the different sedimentologic units present in the estuary, magnetic data were processed by multivariate statistical analyses. Our numerical simulation show a large inundation of the estuary with flow depths varying from 0.5 to 6 m and run up of similar to 7 m. Magnetic data show a dominance of paramagnetic minerals (quartz) mixed with lesser amount of ferromagnetic minerals, namely titanomagnetite and titanohematite both of a detrital origin and reworked from the underlying units. Multivariate statistical analyses indicate a better connection between the tsunami-induced deposit and a mixture of Units C and D. All these results point to a scenario where the energy released by the tsunami wave was strong enough to overtop and erode important amount of sand from the littoral dune and mixed it with reworked materials from underlying layers at least 1 m in depth. The method tested here represents an original and promising tool to identify tsunami-induced deposits in similar embayed beach environments.

Análise do desempenho da tecnologia 4G LTE

O objectivo deste trabalho passa pelo desenvolvimento de uma ferramenta de simulação dinâmica de recursos rádio em LTE no sentido descendente, com recurso à Framework OMNeT++. A ferramenta desenvolvida permite realizar o planeamento das estações base, simulação e análise de resultados. São descritos os principais aspectos da tecnologia de acesso rádio, designadamente a arquitectura da rede, a codificação, definição dos recursos rádio, os ritmos de transmissão suportados ao nível de canal e o mecanismo de controlo de admissão. Foi definido o cenário de utilização de recursos rádio que inclui a definição de modelos de tráfego e de serviços orientados a pacotes e circuitos. Foi ainda considerado um cenário de referência para a verificação e validação do modelo de simulação. A simulação efectua-se ao nível de sistema, suportada por um modelo dinâmico, estocástico e orientado por eventos discretos de modo a contemplar os diferentes mecanismos característicos da tecnologia OFDMA. Os resultados obtidos permitem a análise de desempenho dos serviços, estações base e sistema ao nível do throughput médio da rede, throughput médio por eNodeB e throughput médio por móvel para além de permitir analisar o contributo de outros parâmetros designadamente, largura de banda, raio de cobertura, perfil dos serviços, esquema de modulação, entre outros. Dos resultados obtidos foi possível verificar que, considerando um cenário com estações base com raio de cobertura de 100 m obteve-se um throughput ao nível do utilizador final igual a 4.69494 Mbps, ou seja, 7 vezes superior quando comparado a estações base com raios de cobertura de 200m.

Identification of tsunami-induced deposits using numerical modeling and rock magnetism techniques: A study case of the 1755 Lisbon tsunami in Algarve, Portugal

Storm- and tsunami-deposits are generated by similar depositional mechanisms making their discrimination hard to establish using classic sedimentologic methods. Here we propose an original approach to identify tsunami-induced deposits by combining numerical simulation and rock magnetism. To test our method, we investigate the tsunami deposit of the Boca do Rio estuary generated by the 1755 earthquake in Lisbon which is well described in the literature. We first test the 1755 tsunami scenario using a numerical inundation model to provide physical parameters for the tsunami wave. Then we use concentration (MS. SIRM) and grain size (chi(ARM), ARM, B1/2, ARM/SIRM) sensitive magnetic proxies coupled with SEM microscopy to unravel the magnetic mineralogy of the tsunami-induced deposit and its associated depositional mechanisms. In order to study the connection between the tsunami deposit and the different sedimentologic units present in the estuary, magnetic data were processed by multivariate statistical analyses. Our numerical simulation show a large inundation of the estuary with flow depths varying from 0.5 to 6 m and run up of similar to 7 m. Magnetic data show a dominance of paramagnetic minerals (quartz) mixed with lesser amount of ferromagnetic minerals, namely titanomagnetite and titanohematite both of a detrital origin and reworked from the underlying units. Multivariate statistical analyses indicate a better connection between the tsunami-induced deposit and a mixture of Units C and D. All these results point to a scenario where the energy released by the tsunami wave was strong enough to overtop and erode important amount of sand from the littoral dune and mixed it with reworked materials from underlying layers at least 1 m in depth. The method tested here represents an original and promising tool to identify tsunami-induced deposits in similar embayed beach environments.

The source of the 1722 Algarve earthquake: evidence from MCS and tsunami data

The 27 December 1722 Algarve earthquake destroyed a large area in southern Portugal generating a local tsunami that inundated the shallow areas of Tavira. It is unclear whether its source was located onshore or offshore and, in any case, what was the tectonic source responsible for the event. We analyze available historical information concerning macroseismicity and the tsunami to discuss the most probable location of the source. We also review available seismotectonic knowledge of the offshore region close to the probable epicenter, selecting a set of four candidate sources. We simulate tsunamis produced by these candidate sources assuming that the sea bottom displacement is caused by a compressive dislocation over a rectangular fault, as given by the half-space homogeneous elastic approach, and we use numerical modeling to study wave propagation and run-up. We conclude that the 27 December 1722 Tavira earthquake and tsunami was probably generated offshore, close to 37 degrees 01'N, 7 degrees 49'W.

Identification of tsunami-induced deposits using numerical modeling and rock magnetism techniques: Astudy case of the 1755 Lisbon tsunami in Algarve, Portugal (vol 182, pg 187, 2010)

Storm- and tsunami-deposits are generated by similar depositional mechanisms making their discrimination hard to establish using classic sedimentologic methods. Here we propose an original approach to identify tsunami-induced deposits by combining numerical simulation and rock magnetism. To test our method, we investigate the tsunami deposit of the Boca do Rio estuary generated by the 1755 earthquake in Lisbon which is well described in the literature. We first test the 1755 tsunami scenario using a numerical inundation model to provide physical parameters for the tsunami wave. Then we use concentration (MS. SIRM) and grain size (chi(ARM), ARM, B1/2, ARM/SIRM) sensitive magnetic proxies coupled with SEM microscopy to unravel the magnetic mineralogy of the tsunami-induced deposit and its associated depositional mechanisms. In order to study the connection between the tsunami deposit and the different sedimentologic units present in the estuary, magnetic data were processed by multivariate statistical analyses. Our numerical simulation show a large inundation of the estuary with flow depths varying from 0.5 to 6 m and run up of similar to 7 m. Magnetic data show a dominance of paramagnetic minerals (quartz) mixed with lesser amount of ferromagnetic minerals, namely titanomagnetite and titanohematite both of a detrital origin and reworked from the underlying units. Multivariate statistical analyses indicate a better connection between the tsunami-induced deposit and a mixture of Units C and D. All these results point to a scenario where the energy released by the tsunami wave was strong enough to overtop and erode important amount of sand from the littoral dune and mixed it with reworked materials from underlying layers at least 1 m in depth. The method tested here represents an original and promising tool to identify tsunami-induced deposits in similar embayed beach environments.

On the solubility of three disperse anthraquinone dyes in supercritical carbon dioxide: new experimental data and correlation

Solubility measurements of quinizarin. (1,4-dihydroxyanthraquinone), disperse red 9 (1-(methylamino) anthraquinone), and disperse blue 14 (1,4-bis(methylamino)anthraquinone) in supercritical carbon dioxide (SC CO2) were carried out in a flow type apparatus, at a temperature range from (333.2 to 393.2) K and at pressures from (12.0 to 40.0) MPa. Mole fraction solubility of the three dyes decreases in the order quinizarin (2.9 x 10(-6) to 2.9.10(-4)), red 9 (1.4 x 10(-6) to 3.2 x 10(-4)), and blue 14 (7.8 x 10(-8) to 2.2 x 10(-5)). Four semiempirical density based models were used to correlatethe solubility of the dyes in the SC CO2. From the correlation results, the total heat of reaction, heat of vaporization plus the heat of solvation of the solute, were calculated and compared with the results presented in the literature. The solubilities of the three dyes were correlated also applying the Soave-Redlich-Kwong cubic equation of state (SRK CEoS) with classical mixing rules, and the physical properties required for the modeling were estimated and reported.

QSAR modeling of antitubercular activity of diverse organic compounds

Tuberculosis (TB) is a worldwide infectious disease that has shown over time extremely high mortality levels. The urgent need to develop new antitubercular drugs is due to the increasing rate of appearance of multi-drug resistant strains to the commonly used drugs, and the longer durations of therapy and recovery, particularly in immuno-compromised patients. The major goal of the present study is the exploration of data from different families of compounds through the use of a variety of machine learning techniques so that robust QSAR-based models can be developed to further guide in the quest for new potent anti-TB compounds. Eight QSAR models were built using various types of descriptors (from ADRIANA.Code and Dragon software) with two publicly available structurally diverse data sets, including recent data deposited in PubChem. QSAR methodologies used Random Forests and Associative Neural Networks. Predictions for the external evaluation sets obtained accuracies in the range of 0.76-0.88 (for active/inactive classifications) and Q(2)=0.66-0.89 for regressions. Models developed in this study can be used to estimate the anti-TB activity of drug candidates at early stages of drug development (C) 2011 Elsevier B.V. All rights reserved.

Modeling for control design of a multi-reach water canal

This article addresses the problem of obtaining reduced complexity models of multi-reach water delivery canals that are suitable for robust and linear parameter varying (LPV) control design. In the first stage, by applying a method known from the literature, a finite dimensional rational transfer function of a priori defined order is obtained for each canal reach by linearizing the Saint-Venant equations. Then, by using block diagrams algebra, these different models are combined with linearized gate models in order to obtain the overall canal model. In what concerns the control design objectives, this approach has the advantages of providing a model with prescribed order and to quantify the high frequency uncertainty due to model approximation. A case study with a 3-reach canal is presented, and the resulting model is compared with experimental data. © 2014 IEEE.

PV system modeling by five parameters and in situ test

This paper focuses on a novel formalization for assessing the five parameter modeling of a photovoltaic cell. An optimization procedure is used as a feasibility problem to find the parameters tuned at the open circuit, maximum power, and short circuit points in order to assess the data needed for plotting the I-V curve. A comparison with experimental results is presented for two monocrystalline PV modules.

Correlation modeling for a distributed scalable video codec based on the HEVC standard

The growing heterogeneity of networks, devices and consumption conditions asks for flexible and adaptive video coding solutions. The compression power of the HEVC standard and the benefits of the distributed video coding paradigm allow designing novel scalable coding solutions with improved error robustness and low encoding complexity while still achieving competitive compression efficiency. In this context, this paper proposes a novel scalable video coding scheme using a HEVC Intra compliant base layer and a distributed coding approach in the enhancement layers (EL). This design inherits the HEVC compression efficiency while providing low encoding complexity at the enhancement layers. The temporal correlation is exploited at the decoder to create the EL side information (SI) residue, an estimation of the original residue. The EL encoder sends only the data that cannot be inferred at the decoder, thus exploiting the correlation between the original and SI residues; however, this correlation must be characterized with an accurate correlation model to obtain coding efficiency improvements. Therefore, this paper proposes a correlation modeling solution to be used at both encoder and decoder, without requiring a feedback channel. Experiments results confirm that the proposed scalable coding scheme has lower encoding complexity and provides BD-Rate savings up to 3.43% in comparison with the HEVC Intra scalable extension under development. © 2014 IEEE.