Design and implementation of a real-time data acquisition system for the identification of dynamic temperature models in a hydroponic greenhouse

This text describes a real data acquisition and identification system implemented in a soilless greenhouse located at the University of Algarve (south of Portugal). Using the Real Time Workshop, Simulink, Matlab and the C programming language a system was developed to perform real-time data acquisition from a set of sensors.

Real-time data acquisition system for the Identification of dynamic temperature models in a hydroponic greenhouse

A real-time data acquisition and identification system implemented in a soil-less greenhouse located in the south of Portugal is described. The system performs real-time data acquisition from a set of sensors connected to a data logger.

Real-time parameter estimation of dynamic temperature models for greenhouse environmental control

For a greenhouse located at UTAD-University, the methods used to estimate in real-time the parameters of the inside air temperature model will be described. The structure and the parameters of the climate discrete-time dynamic model were previously identified using data acquired during two different periods of the year.

Dynamic temperature models of a soiless greenhouse

In this paper climate discrete-time dynamic models for the inside air temperature of a soilless greenhouse are identified, using data acquired during two different periods of the year. These models employ data from air temperature and relative humidity.

A closed-form approximation for pricing temperature-based weather derivatives

This paper develops analytical distributions of temperature indices on which temperature derivatives are written. If the deviations of daily temperatures from their expected values are modelled as an Ornstein-Uhlenbeck process with timevarying variance, then the distributions of the temperature index on which the derivative is written is the sum of truncated, correlated Gaussian deviates. The key result of this paper is to provide an analytical approximation to the distribution of this sum, thus allowing the accurate computation of payoffs without the need for any simulation. A data set comprising average daily temperature spanning over a hundred years for four Australian cities is used to demonstrate the efficacy of this approach for estimating the payoffs to temperature derivatives. It is demonstrated that expected payoffs computed directly from historical records are a particularly poor approach to the problem when there are trends in underlying average daily temperature. It is shown that the proposed analytical approach is superior to historical pricing.

A soft-computing approach for non-invasive temperature estimation

The domain of thermal therapies applications can be improved with the development of accurate non-invasive timespatial temperature models. These models should represent the non-linear tissue thermal behaviour and be capable of tracking temperature at both time-instant and spatial position. If such estimators exist then efficient controllers for the therapeutic instrumentation could be developed, and the desired safety and effectiveness reached.

Predicting the greenhouse inside air temperature with RBF neural networks

The application of the Radial Basis Function (RBF) Neural Network (NN) to greenhouse inside air temperature modelling has been previously investigated (Ferreira et al., 2000a). In those studies, the inside air temperature is modelled as a function of the inside relative humidity and of the outside temperature and solar radiation. A second-order model structure previously selected (Cunha et al., 1996) in the context of dynamic temperature models identification, is used.

On the assessment of time-shift variations from backscattered ultrasound for large temperature changes in biological phantoms

This work reports the assessment of time-shifts (TS) from backscattered ultrasound (BSU) signals when large temperature variations (up to 15 degrees C) were induced in a gel-based phantom. The results showed that during cooling temperature is linear with TS at a rate of approximately 74 ns/degrees C. However during a complete heating/cooling cycle, the relation is highly non-linear. This can be explained by the fact that during cooling the temperature distribution is more uniform. Another problem to report is that TS is very sensitive to external movements.

HeatWave : a handheld 3D thermography system for energy auditing

Energy auditing is an effective but costly approach for reducing the long-term energy consumption of buildings. When well-executed, energy loss can be quickly identified in the building structure and its subsystems. This then presents opportunities for improving energy efficiency. We present a low-cost, portable technology called "HeatWave" which allows non-experts to generate detailed 3D surface temperature models for energy auditing. This handheld 3D thermography system consists of two commercially available imaging sensors and a set of software algorithms which can be run on a laptop. The 3D model can be visualized in real-time by the operator so that they can monitor their degree of coverage as the sensors are used to capture data. In addition, results can be analyzed offline using the proposed "Spectra" multispectral visualization toolbox. The presence of surface temperature data in the generated 3D model enables the operator to easily identify and measure thermal irregularities such as thermal bridges, insulation leaks, moisture build-up and HVAC faults. Moreover, 3D models generated from subsequent audits of the same environment can be automatically compared to detect temporal changes in conditions and energy use over time.

Solubilities of Benzene Derivatives in Supercritical Carbon Dioxide

The solubilities of benzene derivatives in supercritical carbon dioxide was determined by the saturation method over the pressure range (9.5 to 14.5) MPa. The solubilities were determined at (308 and 313) K for 1-chloro-2,4-dinitrobenzene and (308, 318, and 328) K for m-dinitrobenzene. At 308K, the solubility (in mole fraction) of 1-chloro-2,4-dinitrobenzene varied from (2.83 to 5.88).10(-3) while the solubility of m-dinitrobenzene increased from (2.05 to 5.54).10(-3) as the pressure increased from (9.5 to 14.5) MPa. However, the solubilities of both compounds decreased with increasing temperature. Models based on the solubility parameter and semiempirical models such as the Mendez-Santiago-Teja model, the Gordillo model, and the association model, were used to correlate the experimental solubility data for the benzene derivatives.

Thermoacclimatory variations in the activities of enzymes implicated in ion transport in the rainbow trout, salmo gairdneri

Two groups of rainbow trout were acclimated to 20 , 100 , and 18 o C. Plasma sodium, potassium, and chloride levels were determined for both. One group was employed in the estimation of branchial and renal (Na+-K+)-stimulated, (HC0 3-)-stimulated, and CMg++)-dependent ATPase activities, while the other was used in the measurement of carbonic anhydrase activity in the blood, gill and kidney. Assays were conducted using two incubation temperature schemes. One provided for incubation of all preparations at a common temperature of 2S oC, a value equivalent to the upper incipient lethal level for this species. In the other procedure the preparations were incubated at the appropriate acclimation temperature of the sampled fish. Trout were able to maintain plasma sodium and chloride levels essentially constant over the temperature range employed. The different incubation temperature protocols produced different levels of activity, and, in some cases, contrary trends with respect to acclimation temperature. This information was discussed in relation to previous work on gill and kidney. The standing-gradient flow hypothesis was discussed with reference to the structure of the chloride cell, known thermallyinduced changes in ion uptake, and the enzyme activities obtained in this study. Modifications of the model of gill lon uptake suggested by Maetz (1971) were proposed; high and low temperature models resulting. In short, ion transport at the gill at low temperatures appears to involve sodium and chloride 2 uptake by heteroionic exchange mechanisms working in association w.lth ca.rbonlc anhydrase. G.l ll ( Na + -K + ) -ATPase and erythrocyte carbonic anhydrase seem to provide the supplemental uptake required at higher temperatures. It appears that the kidney is prominent in ion transport at low temperatures while the gill is more important at high temperatures. 3 Linear regression analyses involving weight, plasma ion levels, and enzyme activities indicated several trends, the most significant being the interrelationship observed between plasma sodium and chloride. This, and other data obtained in the study was considered in light of the theory that a link exists between plasma sodium and chloride regulatory mechanisms.

Exigências térmicas de Brevicoryne brassicae e previsão de picos populacionais

O objetivo deste trabalho foi determinar as exigências térmicas do pulgão-da-couve, Brevicoryne brassicae L., Hemiptera: Aphididae, em condições de laboratório e campo, e prever a ocorrência de picos populacionais de adultos, por meio de um modelo de graus-dia. em laboratório, os experimentos foram conduzidos em câmaras climatizadas reguladas a 15, 20, 25, 27 e 30ºC, obtendo-se o limite térmico inferior de desenvolvimento (Tb = 4,5ºC) e a constante térmica (K = 176,1 graus-dia). Na determinação das exigências térmicas sob condições de campo, realizaram-se seis experimentos, a partir dos quais obteve-se o tempo médio de desenvolvimento de ninfas e a temperatura média ambiental. Os resultados estimados de Tb e K foram 3,5ºC e 180,0 graus-dia, respectivamente. Os resultados de Tb e K obtidos em laboratório possibilitam prever com maior precisão a ocorrência de adultos de B. brassicae do que os resultados de Tb e K determinados a partir de experimentos em campo.

Role of the N- and C-lobes of calmodulin in the activation of Ca(2+)/calmodulin-dependent protein kinase II.

Understanding the principles of calmodulin (CaM) activation of target enzymes will help delineate how this seemingly simple molecule can play such a complex role in transducing Ca (2+)-signals to a variety of downstream pathways. In the work reported here, we use biochemical and biophysical tools and a panel of CaM constructs to examine the lobe specific interactions between CaM and CaMKII necessary for the activation and autophosphorylation of the enzyme. Interestingly, the N-terminal lobe of CaM by itself was able to partially activate and allow autophosphorylation of CaMKII while the C-terminal lobe was inactive. When used together, CaMN and CaMC produced maximal CaMKII activation and autophosphorylation. Moreover, CaMNN and CaMCC (chimeras of the two N- or C-terminal lobes) both activated the kinase but with greater K act than for wtCaM. Isothermal titration calorimetry experiments showed the same rank order of affinities of wtCaM > CaMNN > CaMCC as those determined in the activity assay and that the CaM to CaMKII subunit binding ratio was 1:1. Together, our results lead to a proposed sequential mechanism to describe the activation pathway of CaMKII led by binding of the N-lobe followed by the C-lobe. This mechanism contrasts the typical sequential binding mode of CaM with other CaM-dependent enzymes, where the C-lobe of CaM binds first. The consequence of such lobe specific binding mechanisms is discussed in relation to the differential rates of Ca (2+)-binding to each lobe of CaM during intracellular Ca (2+) oscillations.

Proactive and reactive thermal aware optimization techniques to minimize the environmental impact of data centers

Los Centros de Datos se encuentran actualmente en cualquier sector de la economía mundial. Están compuestos por miles de servidores, dando servicio a los usuarios de forma global, las 24 horas del día y los 365 días del año. Durante los últimos años, las aplicaciones del ámbito de la e-Ciencia, como la e-Salud o las Ciudades Inteligentes han experimentado un desarrollo muy significativo. La necesidad de manejar de forma eficiente las necesidades de cómputo de aplicaciones de nueva generación, junto con la creciente demanda de recursos en aplicaciones tradicionales, han facilitado el rápido crecimiento y la proliferación de los Centros de Datos. El principal inconveniente de este aumento de capacidad ha sido el rápido y dramático incremento del consumo energético de estas infraestructuras. En 2010, la factura eléctrica de los Centros de Datos representaba el 1.3% del consumo eléctrico mundial. Sólo en el año 2012, el consumo de potencia de los Centros de Datos creció un 63%, alcanzando los 38GW. En 2013 se estimó un crecimiento de otro 17%, hasta llegar a los 43GW. Además, los Centros de Datos son responsables de más del 2% del total de emisiones de dióxido de carbono a la atmósfera. Esta tesis doctoral se enfrenta al problema energético proponiendo técnicas proactivas y reactivas conscientes de la temperatura y de la energía, que contribuyen a tener Centros de Datos más eficientes. Este trabajo desarrolla modelos de energía y utiliza el conocimiento sobre la demanda energética de la carga de trabajo a ejecutar y de los recursos de computación y refrigeración del Centro de Datos para optimizar el consumo. Además, los Centros de Datos son considerados como un elemento crucial dentro del marco de la aplicación ejecutada, optimizando no sólo el consumo del Centro de Datos sino el consumo energético global de la aplicación. Los principales componentes del consumo en los Centros de Datos son la potencia de computación utilizada por los equipos de IT, y la refrigeración necesaria para mantener los servidores dentro de un rango de temperatura de trabajo que asegure su correcto funcionamiento. Debido a la relación cúbica entre la velocidad de los ventiladores y el consumo de los mismos, las soluciones basadas en el sobre-aprovisionamiento de aire frío al servidor generalmente tienen como resultado ineficiencias energéticas. Por otro lado, temperaturas más elevadas en el procesador llevan a un consumo de fugas mayor, debido a la relación exponencial del consumo de fugas con la temperatura. Además, las características de la carga de trabajo y las políticas de asignación de recursos tienen un impacto importante en los balances entre corriente de fugas y consumo de refrigeración. La primera gran contribución de este trabajo es el desarrollo de modelos de potencia y temperatura que permiten describes estos balances entre corriente de fugas y refrigeración; así como la propuesta de estrategias para minimizar el consumo del servidor por medio de la asignación conjunta de refrigeración y carga desde una perspectiva multivariable. Cuando escalamos a nivel del Centro de Datos, observamos un comportamiento similar en términos del balance entre corrientes de fugas y refrigeración. Conforme aumenta la temperatura de la sala, mejora la eficiencia de la refrigeración. Sin embargo, este incremente de la temperatura de sala provoca un aumento en la temperatura de la CPU y, por tanto, también del consumo de fugas. Además, la dinámica de la sala tiene un comportamiento muy desigual, no equilibrado, debido a la asignación de carga y a la heterogeneidad en el equipamiento de IT. La segunda contribución de esta tesis es la propuesta de técnicas de asigación conscientes de la temperatura y heterogeneidad que permiten optimizar conjuntamente la asignación de tareas y refrigeración a los servidores. Estas estrategias necesitan estar respaldadas por modelos flexibles, que puedan trabajar en tiempo real, para describir el sistema desde un nivel de abstracción alto. Dentro del ámbito de las aplicaciones de nueva generación, las decisiones tomadas en el nivel de aplicación pueden tener un impacto dramático en el consumo energético de niveles de abstracción menores, como por ejemplo, en el Centro de Datos. Es importante considerar las relaciones entre todos los agentes computacionales implicados en el problema, de forma que puedan cooperar para conseguir el objetivo común de reducir el coste energético global del sistema. La tercera contribución de esta tesis es el desarrollo de optimizaciones energéticas para la aplicación global por medio de la evaluación de los costes de ejecutar parte del procesado necesario en otros niveles de abstracción, que van desde los nodos hasta el Centro de Datos, por medio de técnicas de balanceo de carga. Como resumen, el trabajo presentado en esta tesis lleva a cabo contribuciones en el modelado y optimización consciente del consumo por fugas y la refrigeración de servidores; el modelado de los Centros de Datos y el desarrollo de políticas de asignación conscientes de la heterogeneidad; y desarrolla mecanismos para la optimización energética de aplicaciones de nueva generación desde varios niveles de abstracción. ABSTRACT Data centers are easily found in every sector of the worldwide economy. They consist of tens of thousands of servers, serving millions of users globally and 24-7. In the last years, e-Science applications such e-Health or Smart Cities have experienced a significant development. The need to deal efficiently with the computational needs of next-generation applications together with the increasing demand for higher resources in traditional applications has facilitated the rapid proliferation and growing of data centers. A drawback to this capacity growth has been the rapid increase of the energy consumption of these facilities. In 2010, data center electricity represented 1.3% of all the electricity use in the world. In year 2012 alone, global data center power demand grew 63% to 38GW. A further rise of 17% to 43GW was estimated in 2013. Moreover, data centers are responsible for more than 2% of total carbon dioxide emissions. This PhD Thesis addresses the energy challenge by proposing proactive and reactive thermal and energy-aware optimization techniques that contribute to place data centers on a more scalable curve. This work develops energy models and uses the knowledge about the energy demand of the workload to be executed and the computational and cooling resources available at data center to optimize energy consumption. Moreover, data centers are considered as a crucial element within their application framework, optimizing not only the energy consumption of the facility, but the global energy consumption of the application. The main contributors to the energy consumption in a data center are the computing power drawn by IT equipment and the cooling power needed to keep the servers within a certain temperature range that ensures safe operation. Because of the cubic relation of fan power with fan speed, solutions based on over-provisioning cold air into the server usually lead to inefficiencies. On the other hand, higher chip temperatures lead to higher leakage power because of the exponential dependence of leakage on temperature. Moreover, workload characteristics as well as allocation policies also have an important impact on the leakage-cooling tradeoffs. The first key contribution of this work is the development of power and temperature models that accurately describe the leakage-cooling tradeoffs at the server level, and the proposal of strategies to minimize server energy via joint cooling and workload management from a multivariate perspective. When scaling to the data center level, a similar behavior in terms of leakage-temperature tradeoffs can be observed. As room temperature raises, the efficiency of data room cooling units improves. However, as we increase room temperature, CPU temperature raises and so does leakage power. Moreover, the thermal dynamics of a data room exhibit unbalanced patterns due to both the workload allocation and the heterogeneity of computing equipment. The second main contribution is the proposal of thermal- and heterogeneity-aware workload management techniques that jointly optimize the allocation of computation and cooling to servers. These strategies need to be backed up by flexible room level models, able to work on runtime, that describe the system from a high level perspective. Within the framework of next-generation applications, decisions taken at this scope can have a dramatical impact on the energy consumption of lower abstraction levels, i.e. the data center facility. It is important to consider the relationships between all the computational agents involved in the problem, so that they can cooperate to achieve the common goal of reducing energy in the overall system. The third main contribution is the energy optimization of the overall application by evaluating the energy costs of performing part of the processing in any of the different abstraction layers, from the node to the data center, via workload management and off-loading techniques. In summary, the work presented in this PhD Thesis, makes contributions on leakage and cooling aware server modeling and optimization, data center thermal modeling and heterogeneityaware data center resource allocation, and develops mechanisms for the energy optimization for next-generation applications from a multi-layer perspective.

Análise da influência do efeito esteira de aerogeradores no microclima na superfície do solo: o caso do parque eólico piloto de Macau/RN

This study aimed to evaluate the microclimate changes surrounding the wind farm Macau Pilot / RN, present in the municipality of the same name. To achieve this goal made use of remote sensing techniques using Landsat - 5 TM and 7 ETM +, from which made it possible evaluation of temperature changes on the surface, this around the park in periods prior to its implementation, to the today. For evaluation of the temperature data that has been generated by applying a template was performed its correlation with field data collection and evaluated the degree of correlation, in order to confirm the validity of the data acquired by satellite. Also held was a characterization of the climate of the region based on the data of this climatological station in Macau. Once collected this data made possible the evaluation of climate change policy in the study region. After validation of the temperature models, an analysis of the generated temperature histograms was performed visually could not identify any significant change. However when analyzing the temperature data at a higher level of detail, a data pattern of behavior was detected for both periods evaluated, yet could not see a distinction between the periods of pre-operation of the park, and post-operation . From this result was levantas hypotheses to explain the behavior of the data, the first of which is the presence of moisture in the soil, and the second to the soil composition. In order to validate the hypotheses were applied PDI techniques, involving a combination of different RGB bands of Landsat 5 and the implementation of Reason bands procedure that might show the elements present on the soil surface.