Availability of Power Stations and Their Equipment

1969 ◽  
Vol 184 (1) ◽  
pp. 311-350 ◽  
Author(s):  
W. B. Shannon ◽  
W. W. Campbell ◽  
R. Carstairs ◽  
F. Dollin ◽  
A. Frankel ◽  
...  
Keyword(s):  
Statistical Data ◽  
Plant Performance ◽  
Total Output ◽  
Plant Availability ◽  
Output Factor ◽  
Power Stations ◽  
Self Consistent ◽  
Different Types ◽  
Different Sources ◽  
Operating Regimes

Comprehensive and self-consistent data relating to plant availability and outage rates are essential for the assessment of plant performance, thereby enabling standby requirements to be estimated, plant extensions planned and the performance of different types of plant compared. The present paper deals with the essential requirements that must be met to ensure the comparability and adequacy of the statistical data. Five main points are emphasized in the paper: the assessment of plant performance is best given by outage rates, stated in terms of time; three classes of outage are described; namely forced, deferable and planned. Shortfall is considered separately; since the practical consequences of the three kinds of outage will in general be very different, and since one may affect another the record must always include the three outage rates shown as separate items; to permit the assessment and comparison of statistics from different sources the record should also include an output factor—(total output of item during period/rated capacity x total hours in period), a service factor—(total hours of item in service during period/total hours in period) and the number of starts during the period under review; statistics from plants of very dissimilar properties and design and with widely different operating regimes should be compared cautiously.

Market of Insurance in Russia: Major Tendencies and Problems of Development

2006 ◽  
pp. 115-127
Author(s):  
T Natkhov
Keyword(s):  
Data Analysis ◽  
Statistical Data ◽  
Statistical Data Analysis ◽  
Medium Term ◽  
Insurance Sector ◽  
Different Types ◽  
Basic Characteristics

The article considers recent tendencies in the development of the market of insurance in Russia. On the basis of statistical data analysis the most urgent problems of the insurance sector are formulated. Basic characteristics of different types of insurance are revealed, and measures on perfection of the insurance institution in the medium term are proposed.

AGRICULTURAL PERIODICALS OF RUSSIA IN THE EARLY XX CENTURY

2019 ◽  
Keyword(s):  
Statistical Data ◽  
Soil Science ◽  
Agriculture Soil ◽  
Agricultural Knowledge ◽  
Horse Breeding ◽  
Different Types ◽  
Fruit Growing ◽  
Advanced Knowledge ◽  
The Cost ◽  
The Upper Volga Region

The article deals with the distribution of agricultural periodicals on the territory of the Russian Em-pire in the early twentieth century. Before that there were practically no publications on the pages of sci-entific magazines. Great emphasis is placed on the analysis of agricultural magazines published before 1917 in the Upper Volga region, namely in Vladimir, Kostroma, Tver and Yaroslavl provinces. Thanks to existed in pre-revolutionary Russian periodicals on agricultural subjects advanced knowledge of agron-omy, agriculture, soil science, horticulture, fruit growing, vegetable growing, winemaking, viticulture, 135 tobacco growing, livestock, poultry, bee-keeping, veterinary medicine, forestry, and hunting, land man-agement, irrigation, horse breeding were promoted. On the basis of statistical data, office documentation and other published sources, the author draws conclusions about the degree of accessibility of agricul-tural periodicals for the population, including the peasantry. Availability of agricultural periodicals largely depended on its price, so the author studied the situation with the cost of the annual subscription fee of these publications. The article investigates the issues of periodicity of agricultural magazines and newspapers, the exact number of such publications, as well as their subject matter. Existence duration of different types of periodicals is analyzed, the main publishers of magazines and newspapers, places of their publication are revealed. A prominent place is given to the publishing activities of agricultural pub-lic organizations and zemstvo self-government bodies. It is concluded that natural process of agricultural knowledge distribution among the population of Russia through publications on the pages of periodicals was disrupted by revolutionary events of 1917.

scholarly journals How to measure uncertainty in uncertainty sampling for active learning

2021 ◽  
Author(s):  
Vu-Linh Nguyen ◽  
Mohammad Hossein Shaker ◽  
Eyke Hüllermeier
Keyword(s):  
Machine Learning ◽  
Active Learning ◽  
Sampling Strategies ◽  
Total Uncertainty ◽  
Uncertainty Sampling ◽  
Different Types ◽  
Alternative Approaches ◽  
Active Learner ◽  
Probabilistic Nature ◽  
Different Sources

AbstractVarious strategies for active learning have been proposed in the machine learning literature. In uncertainty sampling, which is among the most popular approaches, the active learner sequentially queries the label of those instances for which its current prediction is maximally uncertain. The predictions as well as the measures used to quantify the degree of uncertainty, such as entropy, are traditionally of a probabilistic nature. Yet, alternative approaches to capturing uncertainty in machine learning, alongside with corresponding uncertainty measures, have been proposed in recent years. In particular, some of these measures seek to distinguish different sources and to separate different types of uncertainty, such as the reducible (epistemic) and the irreducible (aleatoric) part of the total uncertainty in a prediction. The goal of this paper is to elaborate on the usefulness of such measures for uncertainty sampling, and to compare their performance in active learning. To this end, we instantiate uncertainty sampling with different measures, analyze the properties of the sampling strategies thus obtained, and compare them in an experimental study.

scholarly journals Model-Based Probabilistic Inversion Using Magnetic Data: A Case Study on the Kevitsa Deposit

Geosciences ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 150
Author(s):  
Nilgün Güdük ◽  
Miguel de la Varga ◽  
Janne Kaukolinna ◽  
Florian Wellmann
Keyword(s):  
Structural Parameters ◽  
Rock Properties ◽  
Magnetic Data ◽  
Geological Model ◽  
Borehole Data ◽  
Likelihood Functions ◽  
Different Types ◽  
Geophysical Information ◽  
Different Sources

Structural geological models are widely used to represent relevant geological interfaces and property distributions in the subsurface. Considering the inherent uncertainty of these models, the non-uniqueness of geophysical inverse problems, and the growing availability of data, there is a need for methods that integrate different types of data consistently and consider the uncertainties quantitatively. Probabilistic inference provides a suitable tool for this purpose. Using a Bayesian framework, geological modeling can be considered as an integral part of the inversion and thereby naturally constrain geophysical inversion procedures. This integration prevents geologically unrealistic results and provides the opportunity to include geological and geophysical information in the inversion. This information can be from different sources and is added to the framework through likelihood functions. We applied this methodology to the structurally complex Kevitsa deposit in Finland. We started with an interpretation-based 3D geological model and defined the uncertainties in our geological model through probability density functions. Airborne magnetic data and geological interpretations of borehole data were used to define geophysical and geological likelihoods, respectively. The geophysical data were linked to the uncertain structural parameters through the rock properties. The result of the inverse problem was an ensemble of realized models. These structural models and their uncertainties are visualized using information entropy, which allows for quantitative analysis. Our results show that with our methodology, we can use well-defined likelihood functions to add meaningful information to our initial model without requiring a computationally-heavy full grid inversion, discrepancies between model and data are spotted more easily, and the complementary strength of different types of data can be integrated into one framework.

The Behavioral Consequences of Conflict Exposure on Risk Preferences

2021 ◽  
Author(s):  
Enrique Fatas ◽  
Nathaly Jiménez ◽  
Lina Restrepo-Plaza ◽  
Gustavo Rincón
Keyword(s):  
Substantial Effect ◽  
Risk Attitudes ◽  
Behavioral Consequences ◽  
Criminal Violence ◽  
Incentive Compatible ◽  
Attitudinal Factors ◽  
Different Types ◽  
Close Relatives ◽  
Different Sources ◽  
Consequences Of Violence

Violent conflict is a polyhedric phenomenon. Beyond the destruction of physical and human capital and the economic, political, and social costs war generates, there is an additional burden carried by victims: persistent changes in the way they make decisions. Exposure to violence generates changes in how individuals perceive other individuals from their group and other groups, how they discount the future, and how they assess and tolerate risk. The behavioral consequences of violence exposure can be documented using experiments in which participants make decisions in a controlled, incentive-compatible scenario. The external validity of experiments is reinforced when the studies are run in postconflict scenarios, for example, in Colombia, with real victims of conflict. The experimental tasks, therefore, may map risk attitudes among victims and nonvictims of the conflict who share a common background, and distinguish between different types of exposure (direct versus indirect) and different sources of violence (conflict-related versus criminal violence). The experimental evidence collected in Colombia is consistent with a long-lasting and substantial effect of conflict exposure on risk attitudes. Victims are more likely to take risks and less likely to make safe choices than nonvictims, controlling for demographic, socioeconomic, and attitudinal factors. The effect is significant only when the source of violence is conflict (exerted by guerrilla or paramilitary militias) and when violence is experienced directly by individuals. Indirect conflict exposure (suffered by close relatives) and criminal violence leave no significant mark on participants’ risk attitudes in the study.

A Review on Green Synthesis and Applications of Iron Oxide Nanoparticles

2021 ◽  
Vol 21 (12) ◽  
pp. 5812-5834
Author(s):  
Rachana Yadwade ◽  
Saili Kirtiwar ◽  
Balaprasad Ankamwar
Keyword(s):  
Iron Oxide ◽  
Iron Oxide Nanoparticles ◽  
Aqueous System ◽  
Oxide Nanoparticles ◽  
Plant Parts ◽  
Different Types ◽  
Removal Of Heavy Metals ◽  
Biological Sources ◽  
Different Sources

Bio-fabrication of iron oxide nanoparticles by using different sources of plants, plant parts and microbial cells have become a great topic of interest nowadays due to its eco-friendly nature. The stabilizing and capping agents in biological sources are biocompatible, stable and non-toxic which make its use beneficial for various biomedical applications. The bacteria are able to utilize metal ions and convert them into their respective nanoparticles by secreting different biomolecules. The plants and plant parts contain different types of phytochemicals which play a key role in synthesis and bio-fabrication of nanoparticles. Iron oxide nanoparticles are known to have various applications in the fields of medicine, environment etc. This review summarizes the applications of iron oxide nanoparticles as antimicrobial agent, drug delivery agent, material for removal of heavy metals and dyes from aqueous system etc. Due to these wide applications of iron oxide nanoparticles its demand in various fields is increasing considerably. This review describes different approaches which are used for biosynthesis of iron oxide nanoparticles and their applications. The review also summarizes about the surface modification strategies of iron oxide nanoparticles by using different polymers, polyelectrolytes which can be used for in-vivo applications.

Loss of Life and Loss of Bodily Integrity: Two Different Sources of Threat for People who are Ill

1985 ◽  
Vol 15 (3) ◽  
pp. 207-222 ◽  
Author(s):  
Linda L. Viney
Keyword(s):  
Healthy People ◽  
Personal Construct ◽  
Personal Construct Theory ◽  
Bodily Integrity ◽  
Loss Of Life ◽  
Psychological States ◽  
Different Types ◽  
Construct Theory ◽  
Positive Feelings ◽  
Different Sources

Personal construct theory was used to generate some questions about the meanings that different types of threat–loss of life and loss of bodily integrity–hold for people who are severely ill. Content analyses of the responses of ill people and healthy people indicated that ill people expressed more concern with both types of threat than healthy people. Ill people who were suffering from acute rather than chronic illness, who were scheduled for surgery and who were hospitalized rather than being cared for at home expressed more concern about loss of life but not about loss of bodily integrity than other ill people. Each type of threatened loss was found to be associated with a different set of psychological states for people who were ill. Threat of loss of life was associated with indirectly expressed anger and uncertainty but also with the expression of many positive feelings. Threat of loss of bodily integrity was also associated with indirectly expressed anger, but with direct expression of it too, together with hopelessness and helplessness. Patients facing the first threat saw themselves as actively engaged in relationships with others, while those facing the second viewed themselves more often as passive participants. The value of this information about the meanings of threats of loss of life and loss of bodily integrity for the counseling of ill people dealing with these threats was illustrated by two case studies.

scholarly journals TERRESTRIAL LASER SCANNERS SELF-CALIBRATION STUDY: DATUM CONSTRAINTS ANALYSES FOR NETWORK CONFIGURATIONS

2015 ◽  
Vol XL-2/W4 ◽  
pp. 1-9 ◽  
Author(s):  
M. A. Abbas ◽  
H. Setan ◽  
Z. Majid ◽  
A. K. Chong ◽  
L. Chong Luh ◽  
...  
Keyword(s):  
Laser Scanner ◽  
Network Configuration ◽  
Calibration Technique ◽  
Self Calibration ◽  
Laser Scanners ◽  
Different Types ◽  
Minimum Number ◽  
Calibration Study ◽  
Different Sources ◽  
Selection Of

Similar to other electronic instruments, terrestrial laser scanner (TLS) can also inherent with various systematic errors coming from different sources. Self-calibration technique is a method available to investigate these errors for TLS which were adopted from photogrammetry technique. According to the photogrammetry principle, the selection of datum constraints can cause different types of parameter correlations. However, the network configuration applied by TLS and photogrammetry calibrations are quite different, thus, this study has investigated the significant of photogrammetry datum constraints principle in TLS self-calibration. To ensure that the assessment is thorough, the datum constraints analyses were carried out using three variant network configurations: 1) minimum number of scan stations; 2) minimum number of surfaces for targets distribution; and 3) minimum number of point targets. Based on graphical and statistical, the analyses of datum constraints selection indicated that the parameter correlations obtained are significantly similar. In addition, the analysis has demonstrated that network configuration is a very crucial factor to reduce the correlation between the calculated parameters.

scholarly journals Perceptions of Auditor Negligence: The Effects of Big Data Visualisations on Jurors’ Decisions

2021 ◽  
Author(s):  
◽  
Travis Christensen
Keyword(s):  
Social Media ◽  
Big Data ◽  
Data Collection ◽  
Jury Verdicts ◽  
Word Clouds ◽  
Audit Litigation ◽  
Different Types ◽  
Different Sources ◽  
Bar Graphs

<p>This study analyses the effects of Big Data visualisations on jurors’ decisions in audit litigation cases. Specifically, the study investigates the effects of different types of Big Data visualisations (word clouds or bar graphs) and different sources of Big Data (emails or social media posts) on jurors’ perceptions of auditors’ work and the size of the negligence awards that jurors recommend. The study theorises that the emotions elicited and the reliability of the data used to create visualisations such as word clouds will have dramatic effects on jury verdicts in audit negligence trials. There is considerable literature to support this assertion. However, after data collection, it was discovered that jurors are not influenced by the emotions elicited by visualisations. Rather, participants were very sceptical of more novel types of visualisations, such as word clouds, but could be persuaded by the inherent emotions elicited and the reliability of the data if they found the visualisation useful.</p>

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