966 resultados para Software package SPICE
Resumo:
Electricity markets in the United States presently employ an auction mechanism to determine the dispatch of power generation units. In this market design, generators submit bid prices to a regulation agency for review, and the regulator conducts an auction selection in such a way that satisfies electricity demand. Most regulators currently use an auction selection method that minimizes total offer costs ["bid cost minimization" (BCM)] to determine electric dispatch. However, recent literature has shown that this method may not minimize consumer payments, and it has been shown that an alternative selection method that directly minimizes total consumer payments ["payment cost minimization" (PCM)] may benefit social welfare in the long term. The objective of this project is to further investigate the long term benefit of PCM implementation and determine whether it can provide lower costs to consumers. The two auction selection methods are expressed as linear constraint programs and are implemented in an optimization software package. Methodology for game theoretic bidding simulation is developed using EMCAS, a real-time market simulator. Results of a 30-day simulation showed that PCM reduced energy costs for consumers by 12%. However, this result will be cross-checked in the future with two other methods of bid simulation as proposed in this paper.
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High Angular Resolution Diffusion Imaging (HARDI) techniques, including Diffusion Spectrum Imaging (DSI), have been proposed to resolve crossing and other complex fiber architecture in the human brain white matter. In these methods, directional information of diffusion is inferred from the peaks in the orientation distribution function (ODF). Extensive studies using histology on macaque brain, cat cerebellum, rat hippocampus and optic tracts, and bovine tongue are qualitatively in agreement with the DSI-derived ODFs and tractography. However, there are only two studies in the literature which validated the DSI results using physical phantoms and both these studies were not performed on a clinical MRI scanner. Also, the limited studies which optimized DSI in a clinical setting, did not involve a comparison against physical phantoms. Finally, there is lack of consensus on the necessary pre- and post-processing steps in DSI; and ground truth diffusion fiber phantoms are not yet standardized. Therefore, the aims of this dissertation were to design and construct novel diffusion phantoms, employ post-processing techniques in order to systematically validate and optimize (DSI)-derived fiber ODFs in the crossing regions on a clinical 3T MR scanner, and develop user-friendly software for DSI data reconstruction and analysis. Phantoms with a fixed crossing fiber configuration of two crossing fibers at 90° and 45° respectively along with a phantom with three crossing fibers at 60°, using novel hollow plastic capillaries and novel placeholders, were constructed. T2-weighted MRI results on these phantoms demonstrated high SNR, homogeneous signal, and absence of air bubbles. Also, a technique to deconvolve the response function of an individual peak from the overall ODF was implemented, in addition to other DSI post-processing steps. This technique greatly improved the angular resolution of the otherwise unresolvable peaks in a crossing fiber ODF. The effects of DSI acquisition parameters and SNR on the resultant angular accuracy of DSI on the clinical scanner were studied and quantified using the developed phantoms. With a high angular direction sampling and reasonable levels of SNR, quantification of a crossing region in the 90°, 45° and 60° phantoms resulted in a successful detection of angular information with mean ± SD of 86.93°±2.65°, 44.61°±1.6° and 60.03°±2.21° respectively, while simultaneously enhancing the ODFs in regions containing single fibers. For the applicability of these validated methodologies in DSI, improvement in ODFs and fiber tracking from known crossing fiber regions in normal human subjects were demonstrated; and an in-house software package in MATLAB which streamlines the data reconstruction and post-processing for DSI, with easy to use graphical user interface was developed. In conclusion, the phantoms developed in this dissertation offer a means of providing ground truth for validation of reconstruction and tractography algorithms of various diffusion models (including DSI). Also, the deconvolution methodology (when applied as an additional DSI post-processing step) significantly improved the angular accuracy of the ODFs obtained from DSI, and should be applicable to ODFs obtained from the other high angular resolution diffusion imaging techniques.
Resumo:
The core descriptions (chapter 7) summarize the most important results of the analysis of each sediment core following procedures applied during ODP/IODP expeditions. All cores were opened, described, and color-scanned. In the core descriptions the first column displays the lithological data that are based on visual analysis of the core and are supplemented by information from binocular and smear slide analyses. The sediment classification largely follows ODP/IODP convention. Lithological names consist of a principal name based on composition, degree of lithification, and/or texture as determined from visual description and microscopic observations. In the structure column the intensity of bioturbation together with individual or special features (turbidites, volcanic ash layers, plant debris, shell fragments, etc.) is shown. The hue and chroma attributes of color were determined by comparison with the Munsell soil color charts and are given in the color column in the Munsell notation. A GretagMacbethTM Spectrolino spectrophotometer was used to measure percent reflectance values of sediment color at 36 wavelength channels over the visible light range (380-730 nm) on all of the cores. The digital reflectance data of the spectrophotometer readings were routinely obtained from the surface (measured in 1 cm steps) of the split cores (archive half). The Spectrolino is equipped with a measuring aperture with folding mechanism allowing an exact positioning on the split core and is connected to a portable computer. The data are directly displayed within the software package Excel and can be controlled simultaneously. From all the color measurements, for each core the red/blue ratio (700 nm/450 nm) and the lightness are shown together with the visual core description. The reflectance of individual wavelengths is often significantly affected by the presence of minor amounts of oxyhydroxides or sulphides. To eliminate these effects, we used the red/blue ratio and lightness.
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Sr isotope analyses have been conducted on anhydrite samples from the TAG (Trans-Atlantic Geotraverse) active hydrothermal mound (26°08?N, Mid-Atlantic Ridge) that have previously been shown to exhibit two distinct patterns of REE behavior when normalized to TAG end-member hydrothermal fluid. Despite differences in REE patterns, the Sr isotope data indicate that all the anhydrites precipitated from fluids with a similar range of hydrothermal fluid and seawater components, and all but one were seawater-dominated (52%-75%). Speciation calculations using the EQ3/6 software package for geochemical modeling of aqueous systems suggest that the REE complexation behavior in different fluid mixing scenarios can explain the variations in the REE patterns. Anhydrites that exhibit relatively flat REE patterns [(La_bs)/(Yb_bs) = 0.8-2.0; subscript bs indicates normalization to end-member black smoker hydrothermal fluid] and a small or no Eu anomaly [(Eu_bs)/(Eu*_bs) = 0.8-2.0] are inferred to have precipitated from mixes of end-member hydrothermal fluid and cold seawater. REE complexes with hard ligands (e.g., fluoride and chloride) are less stable at low temperatures and trivalent Eu has an ionic radius similar to that of Ca2+ and the other REE, and so they behave coherently. In contrast, anhydrites that exhibit slight LREE-depletion [(La_bs)/(Yb_bs) = 0.4-1.4] and a distinct negative anomaly [(Eu_bs)/(Eu*_bs) = 0.2-0.8] are inferred to have precipitated from mixes of end-member hydrothermal fluid and conductively heated seawater. The LREE depletion results from the presence of very stable LREE chloro-complexes that effectively limit the availability of the LREE for partitioning into anhydrite. Above 250°C, Eu is present only in divalent form as chloride complexes, and discrimination against Eu2+ is likely due to both the mismatch in ionic radii between Eu2+ and Ca2+, and the strong chloro-complexation of divalent Eu which promotes stability in the fluid and inhibits partitioning of Eu2+ into precipitating anhydrite. These variations in REE behavior attest to rapid fluctuations in thermal regime, fluid flow and mixing in the subsurface of the TAG mound that give rise to heterogeneity in the formation conditions of individual anhydrite crystals.
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We introduce two probabilistic, data-driven models that predict a ship's speed and the situations where a ship is probable to get stuck in ice based on the joint effect of ice features such as the thickness and concentration of level ice, ice ridges, rafted ice, moreover ice compression is considered. To develop the models to datasets were utilized. First, the data from the Automatic Identification System about the performance of a selected ship was used. Second, a numerical ice model HELMI, developed in the Finnish Meteorological Institute, provided information about the ice field. The relations between the ice conditions and ship movements were established using Bayesian learning algorithms. The case study presented in this paper considers a single and unassisted trip of an ice-strengthened bulk carrier between two Finnish ports in the presence of challenging ice conditions, which varied in time and space. The obtained results show good prediction power of the models. This means, on average 80% for predicting the ship's speed within specified bins, and above 90% for predicting cases where a ship may get stuck in ice. We expect this new approach to facilitate the safe and effective route selection problem for ice-covered waters where the ship performance is reflected in the objective function.
Resumo:
Maritime accidents involving ships carrying passengers may pose a high risk with respect to human casualties. For effective risk mitigation, an insight into the process of risk escalation is needed. This requires a proactive approach when it comes to risk modelling for maritime transportation systems. Most of the existing models are based on historical data on maritime accidents, and thus they can be considered reactive instead of proactive. This paper introduces a systematic, transferable and proactive framework estimating the risk for maritime transportation systems, meeting the requirements stemming from the adopted formal definition of risk. The framework focuses on ship-ship collisions in the open sea, with a RoRo/Passenger ship (RoPax) being considered as the struck ship. First, it covers an identification of the events that follow a collision between two ships in the open sea, and, second, it evaluates the probabilities of these events, concluding by determining the severity of a collision. The risk framework is developed with the use of Bayesian Belief Networks and utilizes a set of analytical methods for the estimation of the risk model parameters. The model can be run with the use of GeNIe software package. Finally, a case study is presented, in which the risk framework developed here is applied to a maritime transportation system operating in the Gulf of Finland (GoF). The results obtained are compared to the historical data and available models, in which a RoPax was involved in a collision, and good agreement with the available records is found.
Resumo:
In order to study late Holocene changes in sediment supply into the northern Arabian Sea, a 5.3 m long gravity core was investigated by high-resolution geochemical and mineralogical techniques. The sediment core was recovered at a water depth of 956 m from the continental slope off Pakistan and covers a time span of 5 kyr. During the late Holocene source areas delivering material to the sampling site did, however, not change and were active throughout the year.
Resumo:
The BSRN Toolbox is a software package supplied by the WRMC and is freely available to all station scientists and data users. The main features of the package include a download manager for Station- to-Archive files, a tool to convert files into human readable TAB-separated ASCII-tables (similar to those output by the PANGAEA database), and a tool to check data sets for violations of the "BSRN Global Network recommended QC tests, V2.0" quality criteria. The latter tool creates quality codes, one per measured value, indicating if the data are "physically possible," "extremely rare," or if "intercomparison limits are exceeded." In addition, auxiliary data such as solar zenith angle or global calculated from diffuse and direct can be output. All output from the QC tool can be visualized using PanPlot (doi:10.1594/PANGAEA.816201).
Resumo:
We have analyzed the performance of a PET demonstrator formed by two sectors of four monolithic detector blocks placed face-to-face. Both front-end and read-out electronics have been evaluated by means of coincidence measurements using a rotating 22Na source placed at the center of the sectors in order to emulate the behavior of a complete full ring. A continuous training method based on neural network (NN) algorithms has been carried out to determine the entrance points over the surface of the detectors. Reconstructed images from 1 MBq 22Na point source and 22Na Derenzo phantom have been obtained using both filtered back projection (FBP) analytic methods and the OSEM 3D iterative algorithm available in the STIR software package [1]. Preliminary data on image reconstruction from a 22Na point source with Ø = 0.25 mm show spatial resolutions from 1.7 to 2.1 mm FWHM in the transverse plane. The results confirm the viability of this design for the development of a full-ring brain PET scanner compatible with magnetic resonance imaging for human studies.
Resumo:
The analysis of the interdependence between time series has become an important field of research in the last years, mainly as a result of advances in the characterization of dynamical systems from the signals they produce, the introduction of concepts such as generalized and phase synchronization and the application of information theory to time series analysis. In neurophysiology, different analytical tools stemming from these concepts have added to the ‘traditional’ set of linear methods, which includes the cross-correlation and the coherency function in the time and frequency domain, respectively, or more elaborated tools such as Granger Causality. This increase in the number of approaches to tackle the existence of functional (FC) or effective connectivity (EC) between two (or among many) neural networks, along with the mathematical complexity of the corresponding time series analysis tools, makes it desirable to arrange them into a unified-easy-to-use software package. The goal is to allow neuroscientists, neurophysiologists and researchers from related fields to easily access and make use of these analysis methods from a single integrated toolbox. Here we present HERMES (http://hermes.ctb.upm.es), a toolbox for the Matlab® environment (The Mathworks, Inc), which is designed to study functional and effective brain connectivity from neurophysiological data such as multivariate EEG and/or MEG records. It includes also visualization tools and statistical methods to address the problem of multiple comparisons. We believe that this toolbox will be very helpful to all the researchers working in the emerging field of brain connectivity analysis.
Resumo:
En este proyecto se estudiarán las interferencias en el canal adyacente de los sistemas celulares, ubicados en las bandas de 900 y 1800 MHz. Para esto, se analizarán medidas de interferencia entre LTE y otros sistemas de comunicación celular. En el primer capítulo, se dará una breve descripción de los principales parámetros empleados en los distintos estándares de comunicaciones móviles, que operan en las bandas de frecuencia de interés. En el segundo, se van a explicar los distintos tipos de interferencias existentes entre sistemas celulares. También se verán las diferentes técnicas para reducir dichas interferencias, como por ejemplo, la de control de potencia y la de coordinación de interferencia entre celdas. Además, se explicarán los parámetros para determinar la interferencia en el canal adyacente, como son el ACLR, ACS y ACIR. Para finalizar se resumirán las principales características de los sistemas LTE y WiMAX. En el tercer capítulo, se estudiarán las interferencias que genera principalmente LTE a los otros sistemas celulares, mediante los parámetros que miden la interferencia en el canal adyacente explicados en el capítulo dos. Además, se determinará la separación en frecuencia que debe existir entre los canales para que los sistemas puedan coexistir. El capítulo cuatro se basa en la simulación de tres escenarios de interferencia entre dichos sistemas. Para esto, se utilizará el software de simulación de propagación radio, denominado Radio Plan. Con estas simulaciones se cuantificarán las pérdidas de rendimiento que sufren los sistemas interferidos. Por último, en el capítulo cinco se resumirán las conclusiones a las que se llegaron después de simular los diferentes escenarios de interferencia. SUMMARY In this project an adjacent channel interference study for cellular systems, allocated within 900 MHz and 1800 MHz bands will be performed. For this aim a set of measurements will be analyzed. In the first chapter, a brief explanation of the main parameters used in different mobile communications standards that operate in the frequency bands of interest, will be given. In the second chapter, different types of interference between cellular systems will be explained, as well as different techniques to reduce such interference. For example, power control and interference coordination between cells, will be shown. Furthermore, the parameters to determine the adjacent-channel interference, such as the ACLR, ACS and ACIR will be overviewed. Finally, the main features of LTE and WiMAX systems will be summarized. In the third chapter, the interference generated by the other mainly LTE cellular systems via parameters that measure the adjacent channel interference explained in chapter two will be studied. Also, the frequency separation that must exist between the channels so that the systems can coexist will be determined. The fourth chapter is based on the simulation of three scenarios of interference between these systems. For this purpose, a radio propagation simulation software package Radio Plan will be used. These simulations will quantify performance losses suffered by systems that interfered. Finally, in chapter five the conclusions about the results of simulations of interference in different scenarios will be presented.
Resumo:
The analysis of the interdependence between time series has become an important field of research in the last years, mainly as a result of advances in the characterization of dynamical systems from the signals they produce, the introduction of concepts such as generalized and phase synchronization and the application of information theory to time series analysis. In neurophysiology, different analytical tools stemming from these concepts have added to the ?traditional? set of linear methods, which includes the cross-correlation and the coherency function in the time and frequency domain, respectively, or more elaborated tools such as Granger Causality. This increase in the number of approaches to tackle the existence of functional (FC) or effective connectivity (EC) between two (or among many) neural networks, along with the mathematical complexity of the corresponding time series analysis tools, makes it desirable to arrange them into a unified, easy-to-use software package. The goal is to allow neuroscientists, neurophysiologists and researchers from related fields to easily access and make use of these analysis methods from a single integrated toolbox. Here we present HERMES (http://hermes.ctb.upm.es), a toolbox for the Matlab® environment (The Mathworks, Inc), which is designed to study functional and effective brain connectivity from neurophysiological data such as multivariate EEG and/or MEG records. It includes also visualization tools and statistical methods to address the problem of multiple comparisons. We believe that this toolbox will be very helpful to all the researchers working in the emerging field of brain connectivity analysis.