Stable sampling and Fourier multipliers

We study the relationship between stable sampling sequences for bandlimited functions in $L^p(\R^n)$ and the Fourier multipliers in $L^p$. In the case that the sequence is a lattice and the spectrum is a fundamental domain for the lattice the connection is complete. In the case of irregular sequences there is still a partial relationship.

Integrating distributed generation and Smart Grids into single-family house

This study examines Smart Grids and distributed generation, which is connected to a single-family house. The distributed generation comprises small wind power plant and solar panels. The study is done from the consumer point of view and it is divided into two parts. The first part presents the theoretical part and the second part presents the research part. The theoretical part consists of the definition of distributed generation, wind power, solar energy and Smart Grids. The study examines what the Smart Grids will enable. New technology concerning Smart Grids is also examined. The research part introduces wind and sun conditions from two countries. The countries are Finland and Germany. According to the wind and sun conditions of these two countries, the annual electricity production from wind power plant and solar panels will be calculated. The costs of generating electricity from wind and solar energy are calculated from the results of annual electricity productions. The study will also deal with feed-in tariffs, which are supporting systems for renewable energy resources. It is examined in the study, if it is cost-effective for the consumers to use the produced electricity by themselves or sell it to the grid. Finally, figures for both countries are formed. The figures include the calculated cost of generating electricity from wind power plant and solar panels, retail and wholesale prices and feed-in tariffs. In Finland, it is not cost-effective to sell the produced electricity to the grid, before there are support systems. In Germany, it is cost-effective to sell the produced electricity from solar panels to the grid because of feed-in tariffs. On the other hand, in Germany it is cost-effective to produce electricity from wind to own use because the retail price is higher than the produced electricity from wind.

View-dependent information theory quality measures for pixel sampling and scene discretization in flatland

In this paper, we present view-dependent information theory quality measures for pixel sampling and scene discretization in flatland. The measures are based on a definition for the mutual information of a line, and have a purely geometrical basis. Several algorithms exploiting them are presented and compare well with an existing one based on depth differences

Point sampling with uniformly distributed lines

In this paper we address the problem of extracting representative point samples from polygonal models. The goal of such a sampling algorithm is to find points that are evenly distributed. We propose star-discrepancy as a measure for sampling quality and propose new sampling methods based on global line distributions. We investigate several line generation algorithms including an efficient hardware-based sampling method. Our method contributes to the area of point-based graphics by extracting points that are more evenly distributed than by sampling with current algorithms

Sampling in chemical analysis

The uncertainty of any analytical determination depends on analysis and sampling. Uncertainty arising from sampling is usually not controlled and methods for its evaluation are still little known. Pierre Gy’s sampling theory is currently the most complete theory about samplingwhich also takes the design of the sampling equipment into account. Guides dealing with the practical issues of sampling also exist, published by international organizations such as EURACHEM, IUPAC (International Union of Pure and Applied Chemistry) and ISO (International Organization for Standardization). In this work Gy’s sampling theory was applied to several cases, including the analysis of chromite concentration estimated on SEM (Scanning Electron Microscope) images and estimation of the total uncertainty of a drug dissolution procedure. The results clearly show that Gy’s sampling theory can be utilized in both of the above-mentioned cases and that the uncertainties achieved are reliable. Variographic experiments introduced in Gy’s sampling theory are beneficially applied in analyzing the uncertainty of auto-correlated data sets such as industrial process data and environmental discharges. The periodic behaviour of these kinds of processes can be observed by variographic analysis as well as with fast Fourier transformation and auto-correlation functions. With variographic analysis, the uncertainties are estimated as a function of the sampling interval. This is advantageous when environmental data or process data are analyzed as it can be easily estimated how the sampling interval is affecting the overall uncertainty. If the sampling frequency is too high, unnecessary resources will be used. On the other hand, if a frequency is too low, the uncertainty of the determination may be unacceptably high. Variographic methods can also be utilized to estimate the uncertainty of spectral data produced by modern instruments. Since spectral data are multivariate, methods such as Principal Component Analysis (PCA) are needed when the data are analyzed. Optimization of a sampling plan increases the reliability of the analytical process which might at the end have beneficial effects on the economics of chemical analysis,

Stratification of regional sampling by model-predicted changes of carbon stocks in Forested mineral soils

Selective papers of the workshop on "Development of models and forest soil surveys for monitoring of soil carbon", Koli, Finland, April 5-9 2006.

Technological and business challenges of smart grids

Growing recognition of the electricity grid modernization to enable new electricity generation and consumption schemes has found articulation in the vision of the Smart Grid platform. The essence of this vision is an autonomous network with two-way electricity power flows and extensive real-time information between the generation nodes, various electricity-dependent appliances and all points in-between. Three major components of the Smart Grids are distributed intelligence, communication technologies, and automated control systems. The aim of this thesis is to recognize the challenges that Smart Grids are facing, while extinguishing the main driving factors for their introduction. The scope of the thesis also covers possible place of electricity Aggregator Company in the current and future electricity markets. Basic functions of an aggregator and possible revenue sources along with demand response feasibility calculations are reviewed within this thesis.

Use data from permanent sampling points in growth and yield modeling

This study was carried to evaluate the efficiency of the Bitterlich method in growth and yield modeling of the even-aged Eucalyptus stands. 25 plots were setup in Eucalyptus grandis cropped under a high bole system in the Central Western Region of Minas Gerais, Brazil. The sampling points were setup in the center of each plot. The data of four annual mesurements were colleted and used to adjust the three model types using the age, the site index and the basal area as independent variables. The growths models were fitted for volume and mass of trees. The efficiency of the Bitterlich method was confirmed for generating the data for growth and yield modeling.

Accuracy and efficiency evaluation of point-centered quarter method variations for vegetation sampling in an araucaria forest

In order to verify Point-Centered Quarter Method (PCQM) accuracy and efficiency, using different numbers of individuals by per sampled area, in 28 quarter points in an Araucaria forest, southern Paraná, Brazil. Three variations of the PCQM were used for comparison associated to the number of sampled individual trees: standard PCQM (SD-PCQM), with four sampled individuals by point (one in each quarter), second measured (VAR1-PCQM), with eight sampled individuals by point (two in each quarter), and third measuring (VAR2-PCQM), with 16 sampled individuals by points (four in each quarter). Thirty-one species of trees were recorded by the SD-PCQM method, 48 by VAR1-PCQM and 60 by VAR2-PCQM. The level of exhaustiveness of the vegetation census and diversity index showed an increasing number of individuals considered by quadrant, indicating that VAR2-PCQM was the most accurate and efficient method when compared with VAR1-PCQM and SD-PCQM.

Soil sampling intensity and spatial distribution pattern of soils attributes and corn yield in no-tillage system

Taking into account that the sampling intensity of soil attributes is a determining factor for applying of concepts of precision agriculture, this study aims to determine the spatial distribution pattern of soil attributes and corn yield at four soil sampling intensities and verify how sampling intensity affects cause-effect relationship between soil attributes and corn yield. A 100-referenced point sample grid was imposed on the experimental site. Thus, each sampling cell encompassed an area of 45 m² and was composed of five 10-m long crop rows, where referenced points were considered the center of the cell. Samples were taken from at 0 to 0.1 m and 0.1 to 0.2 m depths. Soil chemical attributes and clay content were evaluated. Sampling intensities were established by initial 100-point sampling, resulting data sets of 100; 75; 50 and 25 points. The data were submitted to descriptive statistical and geostatistics analyses. The best sampling intensity to know the spatial distribution pattern was dependent on the soil attribute being studied. The attributes P and K+ content showed higher spatial variability; while the clay content, Ca2+, Mg2+ and base saturation values (V) showed lesser spatial variability. The spatial distribution pattern of clay content and V at the 100-point sampling were the ones which best explained the spatial distribution pattern of corn yield.

Comparison of two methods of tear sampling for protein quantification by Bradford method

The aim of this study was to compare two methods of tear sampling for protein quantification. Tear samples were collected from 29 healthy dogs (58 eyes) using Schirmer tear test (STT) strip and microcapillary tubes. The samples were frozen at -80ºC and analyzed by the Bradford method. Results were analyzed by Student's t test. The average protein concentration and standard deviation from tears collected with microcapillary tube were 4.45mg/mL ±0.35 and 4,52mg/mL ±0.29 for right and left eyes respectively. The average protein concentration and standard deviation from tears collected with Schirmer Tear Test (STT) strip were and 54.5mg/mL ±0.63 and 54.15mg/mL ±0.65 to right and left eyes respectively. Statistically significant differences (p<0.001) were found between the methods. In the conditions in which this study was conducted, the average protein concentration obtained with the Bradford test from tear samples obtained by Schirmer Tear Test (STT) strip showed values higher than those obtained with microcapillary tube. It is important that concentration of tear protein pattern values should be analyzed according the method used to collect tear samples.

Improving quality at the preanalytical phase of blood sampling : literature review

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