scholarly journals Keyword-based Patent Trend Analysis Using Statistical Analysis : The Case of Armour Technology

2013 ◽  
Vol 8 (1) ◽  
pp. 223-252 ◽  
Author(s):  
Jeongseob Choi
Keyword(s):  
Statistical Analysis ◽  
Trend Analysis

scholarly journals Classification and Statistical Trend Analysis in Detecting Glaucomatous Visual Field Progression

2019 ◽  
Vol 2019 ◽  
pp. 1-5
Author(s):  
Cristiana Valente ◽  
Elisa D’Alessandro ◽  
Michele Iester
Keyword(s):  
Statistical Analysis ◽  
Standard Deviation ◽  
Visual Field ◽  
Trend Analysis ◽  
Open Angle Glaucoma ◽  
Mean Deviation ◽  
Threshold Strategy ◽  
Visual Field Progression ◽  
The Mean

Aim. To evaluate the agreement between different methods in detection of glaucomatous visual field progression using two classification-based methods and four statistical approaches based on trend analysis. Methods. This is a retrospective and longitudinal study. Twenty Caucasian patients (mean age 73.8 ± 13.43 years) with open-angle glaucoma were recruited in the study. Each visual field was assessed by Humphrey Field Analyzer, program SITA standard 30-2 or 24-2 (Carl Zeiss Meditec, Inc., Dublin, CA). Full threshold strategy was also accepted for baseline tests. Progression was analyzed by using Hodapp–Parrish–Anderson classification and the Advanced Glaucoma Intervention Study visual field defect score. For the statistical analysis, linear regression (r2) was calculated for mean deviation (MD), pattern standard deviation (PSD), and visual field index (VFI), and when it was significant, each series of visual field was considered progressive. We also used Progressor to look for a significant progression of each visual field series. The agreement between methods, based on statistical analysis and classification, was evaluated using a weighted kappa statistic. Results. Thirty-eight visual field series were analyzed. The mean follow-up time was 6.2 ± 1.53 years (mean ± standard deviation). At baseline, the mean MD was −7.34 ± 7.18 dB; at the end of the follow-up, the mean MD was −9.25 ± 8.65 dB; this difference was statistically significant (p<0.001). The agreement to detect progression was fair between all methods based on statistical analysis and classification except for PSD r2. A substantial agreement (κ = 0.698 ± 0.126) was found between MD r2 and VFI r2. With the use of all the statistical analysis, there was a better time-saving. Conclusions. The best agreement to detect progression was found between MD r2 and VFI r2. VFI r2 showed the best agreement with all the other methods. GPA2 can help ophthalmologists to detect glaucoma progression and to help in treatment decisions. PSD r2 was the worse method to detect progression.

scholarly journals ANALISIS TREND KINERJA KEUANGAN PERBANKAN SYARIAH TAHUN 2015 SAMPAI DENGAN 2017

2016 ◽  
Vol 4 (1) ◽  
pp. 21
Author(s):  
Andri Veno ◽  
Syamsudin Syamsudin
Keyword(s):  
Statistical Analysis ◽  
Trend Analysis ◽  
Return On Assets ◽  
The Future ◽  
Earning Power ◽  
Profitability Ratios

<p>Trend analysis is a method of statistical analysis that is<br />intended to make an estimate or forecast the future. To do a<br />good forecasting is needed various kinds of information (data)<br />is quite a lot and observed in a period of relatively long , so that<br />the analysis can determine how many big fluctuations and the<br />factors that influence those change . The profitability ratios will<br />provide an overview of the effectiveness of the management of<br />the company. The greater the profitability means the better ,<br />because the prosperity of the owner of the company increased<br />with greater profitability. Profitability ratios consist of Profit<br />Margin, Basic Earning Power , Return on Assets and Return on<br />Equity</p>

A Statistical Analysis of the Most Affected Countries by COVID-19 (Preprint)

2020 ◽  
Author(s):  
Jayanta Datta ◽  
Prasenjit Sinha
Keyword(s):  
Statistical Analysis ◽  
Power Series ◽  
Trend Analysis ◽  
Doubling Time ◽  
Policy Formulation ◽  
Growth Constant ◽  
Trend Line ◽  
The Usa ◽  
Exponential Trend ◽  
Growth Constants

BACKGROUND It is almost more than six months elapsed since the crisis of COVID-19 pandemic has hit the globe. It becomes utterly crucial for policy formulation to know up to which period and up to what magnitude the disease will impact us. OBJECTIVE Aim of this study is to predict the saturation level of COVID-19 cases in USA, Brazil, India, Russia, Italy and UK. METHODS Trend analysis is used to fit exponential trend line to the weekly cumulative positive cases. Forecasted growth constants obtained by fitting power series trend to the observed values and prediction of weekly cumulative cases done. Growth constant value of 0.0039 (Doubling time 180 days), observed mean, median and maximum reported COVID-19 cases per million for countries with more than 90% recovery is used to obtain saturation levels. RESULTS Italy and UK reached saturation with growth constant values 0.0007 and 0.0025. Brazil and USA projected to achieve saturation by 26 September 2020 and 19 December 2020 with 8.24 and 9.17 million cases. India and Russia expected to reach the saturation by 16 January 2021and 27 February 2021 with 56.72 and 3.86 million cases. CONCLUSIONS The USA and Russia are predicted to reach saturation due to decrease in growth constant value. Growth constant values for Brazil and India are high and these countries are estimated to reach saturation by infecting the maximum reported per million population. It is therefore eternally essential to take more proactive decisions and to test more and isolate patients effectively to contain COVID-19. CLINICALTRIAL Nil

Trend Analysis of Loss of Offsite Power Events

2016 ◽  
Author(s):  
Andrija Volkanovski ◽  
Antonio Ballesteros Avila ◽  
Miguel Peinador Veira
Keyword(s):  
Statistical Analysis ◽  
Trend Analysis ◽  
Frequency Distribution ◽  
Reporting System ◽  
Nuclear Regulatory Commission ◽  
Modes Of Operation ◽  
International Reporting ◽  
Event Frequency ◽  
The One ◽  
Regulatory Commission

This paper presents the results of the trend analysis of Loss of Offsite Power (LOOP) events registered in two reviewed databases. The reviewed databases include the Nuclear Regulatory Commission (NRC) Licensee Event Reports (LERs) database and the IAEA International Reporting System (IRS). Both databases were screened for the relevant events registered in period 1990 to 2012. The statistical analysis of the identified relevant LOOP events is done. The analysis includes assessment of the LOOP initiating event frequency, distribution of the events per year in the analysed period and trend analysis of the identified events. The LOOP frequency is calculated for LOOP events registered in NRC LERs subdivided into four types by cause or location: plant centered, switchyard centered, grid related, and weather related. These four LOOP categories are assessed for two modes of operation (critical and shutdown operation). The number of LOOP events in each year over the analysed period and distribution of events per unit in given year were assessed from the reviewed databases. Trend analysis of the identified events is performed with the utilization of four trend measures. Analysis is done for events registered during power and shutdown operation and their sum. The obtained LOOP frequency for events registered NRC LERs for critical and shutdown mode is comparable to the one assessed in NUREG/CR-6890. Decreasing trend is obtained for the LOOP events registered for events in NRC LER database. Different trends are identified during critical and shutdown modes of operation for the events registered in the IAEA database. The sum of the LOOP events reported during critical and shutdown modes in IAEA IRS show no trend.

scholarly journals ANALYSIS OF THE CONDITIONS OF STORM SITUATIONS IN THE AREA OF GENICHESK MARINE HYDROLOGICAL STATION

2021 ◽  
Vol 1 (6) ◽  
pp. 139-143
Author(s):  
A.A. Polozok ◽  
◽  
Keyword(s):  
Statistical Analysis ◽  
Trend Analysis ◽  
Sea Level ◽  
Descriptive Data ◽  
Term Trend ◽  
Level Data ◽  
Data Statistics ◽  
Long Term Trend ◽  
Hydrological Station

A statistical analysis of urgent sea level data in the area of the marine hydrological station Genichesk for the period 1996–2013 was carried out, including the preparation of descriptive data statistics for the studied variation series. During the specified period, 8 most dangerous storm situations were identified. The analysis of storm situations has been carried out, including it has been established at what speeds and directions of the wind dangerous surges occur. It is concluded that dangerous storm surge situations in the study area arise due to the action of winds in the E, NE, ESE, ENE directions with a speed of more than 20 m/s. Dangerous storm driven situations appear when the winds are from NW, WNW directions at a speed of more than 15 m/s. The trend analysis of the variation series showed that there is a long-term trend towards an increase in sea level values in the area of the Genichesk marine hydrological station. This means that in the long term, it may be necessary to revise towards an increase in the critical sea level marks for dangerous rises and falls in sea level.

Statistical analysis of classification

1966 ◽  
Vol 24 ◽  
pp. 188-189
Author(s):  
T. J. Deeming
Keyword(s):  
Multivariate Analysis ◽  
Statistical Analysis ◽  
Classification Scheme ◽  
Analytical Procedure ◽  
Narrow Band ◽  
Scientific Research ◽  
Maximum Amount ◽  
Amount Of Information

If we make a set of measurements, such as narrow-band or multicolour photo-electric measurements, which are designed to improve a scheme of classification, and in particular if they are designed to extend the number of dimensions of classification, i.e. the number of classification parameters, then some important problems of analytical procedure arise. First, it is important not to reproduce the errors of the classification scheme which we are trying to improve. Second, when trying to extend the number of dimensions of classification we have little or nothing with which to test the validity of the new parameters.Problems similar to these have occurred in other areas of scientific research (notably psychology and education) and the branch of Statistics called Multivariate Analysis has been developed to deal with them. The techniques of this subject are largely unknown to astronomers, but, if carefully applied, they should at the very least ensure that the astronomer gets the maximum amount of information out of his data and does not waste his time looking for information which is not there. More optimistically, these techniques are potentially capable of indicating the number of classification parameters necessary and giving specific formulas for computing them, as well as pinpointing those particular measurements which are most crucial for determining the classification parameters.

Quantitative parallel EELS spectrum imaging developed as a new tool in AEM

1992 ◽  
Vol 50 (2) ◽  
pp. 1202-1203
Author(s):  
Gianluigi Botton ◽  
Gilles L'espérance
Keyword(s):  
Statistical Analysis ◽  
Spatial Resolution ◽  
Personal Computer ◽  
Systematic Study ◽  
Present Author ◽  
Chemical Elements ◽  
Detection Limits ◽  
Research Groups ◽  
Quantitative Performance ◽  
Spectrum Imaging

As interest for parallel EELS spectrum imaging grows in laboratories equipped with commercial spectrometers, different approaches were used in recent years by a few research groups in the development of the technique of spectrum imaging as reported in the literature. Either by controlling, with a personal computer both the microsope and the spectrometer or using more powerful workstations interfaced to conventional multichannel analysers with commercially available programs to control the microscope and the spectrometer, spectrum images can now be obtained. Work on the limits of the technique, in terms of the quantitative performance was reported, however, by the present author where a systematic study of artifacts detection limits, statistical errors as a function of desired spatial resolution and range of chemical elements to be studied in a map was carried out The aim of the present paper is to show an application of quantitative parallel EELS spectrum imaging where statistical analysis is performed at each pixel and interpretation is carried out using criteria established from the statistical analysis and variations in composition are analyzed with the help of information retreived from t/γ maps so that artifacts are avoided.

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