Analysis of the Auxiliary Steam Header’s Source Selection

2012 ◽  
Vol 608-609 ◽  
pp. 1266-1270
Author(s):  
Yong Li ◽  
Shi Ming Xu ◽  
Ren Jie Li ◽  
Shi Feng Cai
Keyword(s):  
Quantitative Analysis ◽  
Economic Indicators ◽  
Source Selection ◽  
Actual Production ◽  
Steam Header

Taking the actual production status of a 600MW unit as an example, under different steam flux, it has used the equivalent enthalpy drop theory in this paper to calculate the thermal economic indicators of the auxiliary steam header with different auxiliary steam sources. Moreover, it has conducted a quantitative analysis of the mechanism of the choosing of auxiliary steam source and auxiliary steam source switching’s influence on the thermal economy of unit in this paper.

scholarly journals THE PERFORMANCE INDICATORS OF AGRICULTURAL HOLDINGS: COMPARISON BETWEEN LITHUANIA AND ITALY

2018 ◽  
Vol 40 (1) ◽  
pp. 7-15
Author(s):  
Donatello Caruso ◽  
Jolita Greblikaitė
Keyword(s):  
Performance Evaluation ◽  
Quantitative Analysis ◽  
Performance Indicators ◽  
Agricultural Sector ◽  
Research Problem ◽  
Economic Indicators ◽  
Sales Growth ◽  
Research Results ◽  
Financial Position ◽  
Activity Performance

In agricultural sector it is important to evaluate activity performance. The research problem is to analyze difference of performance of agricultural holdings between Lithuania and Italy at farms level. The purpose is to define economic indicators for agricultural holdings’ evaluation and compare between two countries. Methodology is based on quantitative analysis. Research results demonstrate the distribution of performance indicators (e. g., sales growth, investments, productivity and financial position) are significantly different for Lithuanian farms compared to Italian. Presented analysis opens scientific need to develop a tool for farm performance evaluation using FADN data and to as-sess income of farms across Europe.

scholarly journals SOCIAL INSURANCE IN UKRAINE: CURRENT STATE AND DEVELOPMENT PROSPECTS

2021 ◽  
pp. 107-113
Author(s):  
Oleksandr Lavryk
Keyword(s):  
Quantitative Analysis ◽  
Data Processing ◽  
Qualitative Analysis ◽  
Statistical Methods ◽  
Social Insurance ◽  
Pension Fund ◽  
Economic Indicators ◽  
Current State ◽  
Methodological Aspects ◽  
Development Prospects

Introduction. The article is devoted to the study of theoretical and methodological aspects of the analysis of social insurance in Ukraine, the analysis of the current state and prospects of its development and the directions of improvement of modern social insurance in the conditions of development of Ukraine. The content and features of social insurance are considered in the work, the description of methods of the quantitative analysis of its modern activity is given, the methods of the qualitative analysis of prospects of its development are investigated. Purpose. Research of theoretical and methodological aspects of the analysis of social insurance in Ukraine, analysis of the environment and results of social insurance and development of directions of improvement of analytical maintenance of social insurance in Ukraine in modern conditions. Method (methodology). The solution of the set tasks is carried out by means of methods of an estimation and the analysis of risks and efficiency of financing, an estimation of financial and economic indicators of activity, statistical methods. Results. The project of use of tools of improvement of modern activity of pension fund as directions of studying of analytical maintenance of social insurance in Ukraine is offered. The directions of use of software means of data processing on research of social insurance in Ukraine are developed. The effectiveness of the proposed measures is substantiated.

Quantitative areal analysis of dialect features

1996 ◽  
Vol 8 (1) ◽  
pp. 13-39 ◽  
Author(s):  
William A. Kretszchmar
Keyword(s):  
Mathematical Modeling ◽  
Quantitative Analysis ◽  
Regional Differences ◽  
South Atlantic ◽  
Actual Production ◽  
Knowledge Of Language ◽  
Areal Variation ◽  
Quantitative Approaches

ABSTRACTTraditional notions of dialect are qualitative, and perceived dialects are difficult to reconcile with the evidence of actual production of dialect feature. Traditional dialect boundaries are similarly tied to qualitative judgements. More recently, various quantitative approaches have been attempted to try to capture dialect boundaries, each with its won problems. We have achieved some success with an objective quantitative analysis of separate dialect features from the Linguistic Atlas of the Middle and South Atlantic States (LAMSAS). Our findings suggest that a mathematical modeling of areal variation of dialect features, combined with a reassessment of traditional notions of dialect, could contribute to our knowledge of language, as well as document regional differences at the time of the LAMSAS survey.

An Improved Quantitative Image Analyser

1977 ◽  
Vol 35 ◽  
pp. 226-227
Author(s):  
J.P. Fallon ◽  
P.J. Gregory ◽  
C.J. Taylor
Keyword(s):  
Feature Extraction ◽  
Quantitative Analysis ◽  
Frequency Content ◽  
General Sense ◽  
Physical Measurements ◽  
Quantitative Image ◽  
Image Analyser ◽  
Automatic Methods ◽  
Quantitative Results

Quantitative image analysis systems have been used for several years in research and quality control applications in various fields including metallurgy and medicine. The technique has been applied as an extension of subjective microscopy to problems requiring quantitative results and which are amenable to automatic methods of interpretation.Feature extraction. In the most general sense, a feature can be defined as a portion of the image which differs in some consistent way from the background. A feature may be characterized by the density difference between itself and the background, by an edge gradient, or by the spatial frequency content (texture) within its boundaries. The task of feature extraction includes recognition of features and encoding of the associated information for quantitative analysis.Quantitative Analysis. Quantitative analysis is the determination of one or more physical measurements of each feature. These measurements may be straightforward ones such as area, length, or perimeter, or more complex stereological measurements such as convex perimeter or Feret's diameter.

Quantification of Silica Uptake by Alveolar Macrophages - An Emperical Scanning Electron Microprobe Method

1982 ◽  
Vol 40 ◽  
pp. 332-333
Author(s):  
V. V. Damiano ◽  
R. P. Daniele ◽  
H. T. Tucker ◽  
J. H. Dauber
Keyword(s):  
Quantitative Analysis ◽  
Alveolar Macrophages ◽  
Bulk Sample ◽  
Silica Particles ◽  
Empirical Method ◽  
Phagocytic Cells ◽  
Calibration Standards ◽  
X Ray ◽  
Accurate Quantitative Analysis ◽  
Scanning Electron

An important example of intracellular particles is encountered in silicosis where alveolar macrophages ingest inspired silica particles. The quantitation of the silica uptake by these cells may be a potentially useful method for monitoring silica exposure. Accurate quantitative analysis of ingested silica by phagocytic cells is difficult because the particles are frequently small, irregularly shaped and cannot be visualized within the cells. Semiquantitative methods which make use of particles of known size, shape and composition as calibration standards may be the most direct and simplest approach to undertake. The present paper describes an empirical method in which glass microspheres were used as a model to show how the ratio of the silicon Kα peak X-ray intensity from the microspheres to that of a bulk sample of the same composition correlated to the mass of the microsphere contained within the cell. Irregular shaped silica particles were also analyzed and a calibration curve was generated from these data.

Lateral resolution of the electron microbeam analysis

1978 ◽  
Vol 36 (1) ◽  
pp. 542-543
Author(s):  
H.J. Dudek
Keyword(s):  
Quantitative Analysis ◽  
Depth Resolution ◽  
Lateral Resolution ◽  
Cylindrical Particle ◽  
Correction Procedure ◽  
X Ray ◽  
Element Concentrations ◽  
Microbeam Analysis ◽  
The Matrix

The chemical inhomogenities in modern materials such as fibers, phases and inclusions, often have diameters in the region of one micrometer. Using electron microbeam analysis for the determination of the element concentrations one has to know the smallest possible diameter of such regions for a given accuracy of the quantitative analysis.In th is paper the correction procedure for the quantitative electron microbeam analysis is extended to a spacial problem to determine the smallest possible measurements of a cylindrical particle P of high D (depth resolution) and diameter L (lateral resolution) embeded in a matrix M and which has to be analysed quantitative with the accuracy q. The mathematical accounts lead to the following form of the characteristic x-ray intens ity of the element i of a particle P embeded in the matrix M in relation to the intensity of a standard S

An example of spectrum imaging used for comparison of EELS quantitative analysis techniques on Al-Li

1991 ◽  
Vol 49 ◽  
pp. 726-727
Author(s):  
John A. Hunt
Keyword(s):  
Quantitative Analysis ◽  
Large Data ◽  
Difference Spectrum ◽  
Large Data Sets ◽  
Foil Thickness ◽  
Data Sets ◽  
Analysis Techniques ◽  
Spectrum Imaging ◽  
Normal Spectrum ◽  
Electron Energy Loss

Spectrum-imaging is a useful technique for comparing different processing methods on very large data sets which are identical for each method. This paper is concerned with comparing methods of electron energy-loss spectroscopy (EELS) quantitative analysis on the Al-Li system. The spectrum-image analyzed here was obtained from an Al-10at%Li foil aged to produce δ' precipitates that can span the foil thickness. Two 1024 channel EELS spectra offset in energy by 1 eV were recorded and stored at each pixel in the 80x80 spectrum-image (25 Mbytes). An energy range of 39-89eV (20 channels/eV) are represented. During processing the spectra are either subtracted to create an artifact corrected difference spectrum, or the energy offset is numerically removed and the spectra are added to create a normal spectrum. The spectrum-images are processed into 2D floating-point images using methods and software described in [1].

The use of a Bent Grid to Improve the take-Off Angle for Electron Probe Analysis

1976 ◽  
Vol 34 ◽  
pp. 360-361
Author(s):  
Delbert E. Philpott ◽  
David Leaffer
Keyword(s):  
Quantitative Analysis ◽  
Tilt Angle ◽  
Count Rate ◽  
Electron Probe ◽  
Open Area ◽  
Electron Probe Analysis ◽  
Background Ratio ◽  
Probe Analysis

There are certain advantages for electron probe analysis if the sample can be tilted directly towards the detector. The count rate is higher, it optimizes the geometry since only one angle need be taken into account for quantitative analysis and the signal to background ratio is improved. The need for less tilt angle may be an advantage because the grid bars are not moved quite as close to each other, leaving a little more open area for observation. Our present detector (EDAX) and microscope (Philips 300) combination precludes moving the detector behind the microscope where it would point directly at the grid. Therefore, the angle of the specimen was changed in order to optimize the geometry between the specimen and the detector.

Solving the mechanisms responsible for organelle behavior in vivo by same-cell correlative light and electron microscopy

1992 ◽  
Vol 50 (1) ◽  
pp. 14-15
Author(s):  
Conly L. Rieder
Keyword(s):  
Electron Microscopy ◽  
Quantitative Analysis ◽  
Light Microscopy ◽  
Living Cell ◽  
Light And Electron Microscopy ◽  
Time Behavior ◽  
Dynamic Interactions ◽  
Positive Identification ◽  
Cellular Components

The behavior of many cellular components, and their dynamic interactions, can be characterized in the living cell with considerable spatial and temporal resolution by video-enhanced light microscopy (video-LM). Indeed, under the appropriate conditions video-LM can be used to determine the real-time behavior of organelles ≤ 25-nm in diameter (e.g., individual microtubules—see). However, when pushed to its limit the structures and components observed within the cell by video-LM cannot be resolved nor necessarily even identified, only detected. Positive identification and a quantitative analysis often requires the corresponding electron microcopy (EM).

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