scholarly journals Physicochemical parameter based estimation of discarding points for frying oil using data interpolation and principal component transformation

2020 ◽  
Vol 8 (5) ◽  
pp. 2360-2372
Author(s):  
Yumei Li ◽  
Xianbing Cao ◽  
Yanping Cao ◽  
Yuxu Feng ◽  
Jingjun Ji ◽  
...  
Keyword(s):  
Principal Component ◽  
Frying Oil ◽  
Physicochemical Parameter ◽  
Data Interpolation ◽  
Using Data

scholarly journals Data Fusion of Electronic Nose and Electronic Tongue for Detection of Mixed Edible-Oil

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Hong Men ◽  
Donglin Chen ◽  
Xiaoting Zhang ◽  
Jingjing Liu ◽  
Ke Ning
Keyword(s):  
Data Fusion ◽  
Electronic Nose ◽  
Food Processing ◽  
Electronic Tongue ◽  
Principal Component ◽  
Edible Oil ◽  
Frying Oil ◽  
Using Data ◽  
The Cost ◽  
Detection Effect

For the problem of the waste of the edible-oil in the food processing, on the premise of food security, they often need to add new edible-oil to the old frying oil which had been used in food processing to control the cost of the production. Due to the fact that the different additive proportion of the oil has different material and different volatile gases, we use fusion technology based on the electronic nose and electronic tongue to detect the blending ratio of the old frying oil and the new edible-oil in this paper. Principal component analysis (PCA) is used to distinguish the different proportion of the old frying oil and new edible-oil; on the other hand we use partial least squares (PLS) to predict the blending ratio of the old frying oil and new edible-oil. Two conclusions were proposed: data fusion of electronic nose and electronic tongue can be used to detect the blending ratio of the old frying oil and new edible-oil; in contrast to single used electronic nose or single used electronic tongue, the detection effect has increased by using data fusion of electronic nose and electronic tongue.

scholarly journals A phenetic study of the genus Rasahus Amyot & Serville (Heteroptera, Reduviidae)

1990 ◽  
Vol 1 (3) ◽  
pp. 131-144
Author(s):  
María Coscarón
Keyword(s):  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Principal Component ◽  
Component Analysis ◽  
Morphological Characters ◽  
Basal Plate ◽  
Using Data ◽  
Diagnostic Importance

Cluster analysis by four methods and a principal component analysis were performed using data on 24 morphological characters of 27 species of the genus Rasahus (Peiratinae). The results obtained by the different techniques show general agreement. They confirm the present number of taxa and reveal the existence within the genus of three groups of species: scutellaris , hamatus and vittatus. The scutellaris group is constituted by R. aeneus (Walker), R. maculipennis (Lepelletier and Serville), R. bifurcatas Champion, R. castaneus Coscarón, R. guttatipennis (Stål), R. flavovittarus Stål, R. costarricensis Coscarón, R. scutellaris (Fabricius), R. atratus Coscarón, R. peruensis Coscarón, R. paraguayensis Coscarón, R. surinamensis Coscarón, R. albomaculatus Mayr, R. brasiliensis Coscarón and R. sulcicollis (Serville).The hamatus group contains R. rufiventris (Walker), R. hamatus (Fabricius), R. amapaensis Coscarón, R. arcitenens Stål, R. limai Pinto, R. angulatus coscarón, R. thoracicus Stål, R. biguttatus (Say), R. arcuiger (Stål), R. argentinensis Coscarón and R. grandis Fallou. The vittatus group contains R. vittatus Coscarón. The characters used to separate the groups of species are: shape of the pygophore, shape of the parameres, basal plate complexity, shape of the postocular region and hemelytra pattern. Illustrations of the structures of major diagnostic importance are included.

Exploring the effect of online banking on bank performance using data envelopment analysis

2019 ◽  
Vol 27 (1) ◽  
pp. 137-165 ◽  
Author(s):  
Kwame Owusu Kwateng ◽  
Edna Edwina Osei-Wusu ◽  
Kofi Amanor
Keyword(s):  
Data Envelopment Analysis ◽  
Banking Sector ◽  
Principal Component ◽  
Internet Banking ◽  
Bank Performance ◽  
Data Envelopment ◽  
Content Type ◽  
Banking Service ◽  
Using Data ◽  
And Cluster Analysis

Purpose Increased competition in the banking sector coupled with long queues in the banking hall has necessitated the introduction of internet banking among banks in Ghana. As a result, internet banking has attracted a great deal of attention from both academicians and practitioners. The purpose of this paper is to examine the effect of internet banking on the performance of banking institutions in Ghana. Design/methodology/approach In total, 20 banks in Ghana were selected from the Bank of Ghana website for the study. The financial information about the banks’ operations was retrieved from the financial statements of the respective banks for the end of the year 2016. The data envelopment analysis-bootstrap approach with principal component analysis and cluster analysis was used to estimate 49 models. Findings The findings of the study indicated that the integration of internet banking into traditional banking methods has led to superior bank performance in Ghana. It was observed that while the independent application of internet banking as a strategy to raise performance was not yielding higher returns due to the low patronage of internet services among banking consumers, its integration with possible traditional methods is widely observed among the top performers in the banking industry. Practical implications Traditional banking methods, integrated banking service strategies and the internet banking service-oriented strategy emerged as the main banking strategies among the banks. Originality/value Extant literature is quite silent on the effect of internet banking on bank performance in Africa. However, this paper is among the first significant attempts to examine the effect of internet banking on bank performance.

Email Worm Detection Using Data Mining

2011 ◽  
pp. 20-34
Author(s):  
Mohammad M. Masud ◽  
Latifur Khan ◽  
Bhavani Thuraisingham
Keyword(s):  
Data Mining ◽  
Feature Selection ◽  
Principal Component ◽  
Classification Model ◽  
Support Vector ◽  
Two Phase ◽  
Feature Selection Technique ◽  
Worm Detection ◽  
Phase Selection ◽  
Using Data

This chapter applies data mining techniques to detect email worms. Email messages contain a number of different features such as the total number of words in message body/subject, presence/absence of binary attachments, type of attachments, and so on. The goal is to obtain an efficient classification model based on these features. The solution consists of several steps. First, the number of features is reduced using two different approaches: feature-selection and dimension-reduction. This step is necessary to reduce noise and redundancy from the data. The feature-selection technique is called Two-phase Selection (TPS), which is a novel combination of decision tree and greedy selection algorithm. The dimensionreduction is performed by Principal Component Analysis. Second, the reduced data is used to train a classifier. Different classification techniques have been used, such as Support Vector Machine (SVM), Naïve Bayes and their combination. Finally, the trained classifiers are tested on a dataset containing both known and unknown types of worms. These results have been compared with published results. It is found that the proposed TPS selection along with SVM classification achieves the best accuracy in detecting both known and unknown types of worms.

scholarly journals EVALUATING MBSE POTENTIAL USING PRODUCT AND DEVELOPMENT CHARACTERISTICS – A STATISTICAL INVESTIGATION

2020 ◽  
Vol 1 ◽  
pp. 2385-2394
Author(s):  
M. Schöberl ◽  
E. Rebentisch ◽  
J. Trauer ◽  
M. Mörtl ◽  
J. Fottner
Keyword(s):  
Principal Component Analysis ◽  
Systems Engineering ◽  
Principal Component ◽  
Component Analysis ◽  
Statistical Investigation ◽  
Product Complexity ◽  
Organizational Complexity ◽  
Model Based ◽  
Using Data ◽  
Model Based Systems Engineering

AbstractAs model-based systems engineering (MBSE) is evolving, the need for evaluating MBSE approaches grows. Literature shows that there is an untested assertion in the MBSE community that complexity drives the adoption of MBSE. To assess this assertion and support the evaluation of MBSE, a principal component analysis was carried out on eight product and development characteristics using data collected in an MBSE course, resulting in organizational complexity, product complexity and inertia. To conclude, the method developed in this paper enables organisations to evaluate their MBSE adoption potential.

scholarly journals A calibrated measure to compare fluctuations of different entities across timescales

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Jan Chołoniewski ◽  
Julian Sienkiewicz ◽  
Naum Dretnik ◽  
Gregor Leban ◽  
Mike Thelwall ◽  
...  
Keyword(s):  
Scaling Law ◽  
Principal Component ◽  
High Reactivity ◽  
Political Orientation ◽  
Media Industry ◽  
The Media ◽  
Using Data ◽  
News Outlet ◽  
Fluctuation Scaling ◽  
Associated Variables

AbstractA common way to learn about a system’s properties is to analyze temporal fluctuations in associated variables. However, conclusions based on fluctuations from a single entity can be misleading when used without proper reference to other comparable entities or when examined only on one timescale. Here we introduce a method that uses predictions from a fluctuation scaling law as a benchmark for the observed standard deviations. Differences from the benchmark (residuals) are aggregated across multiple timescales using Principal Component Analysis to reduce data dimensionality. The first component score is a calibrated measure of fluctuations—the reactivityRA of a given entity. We apply our method to activity records from the media industry using data from the Event Registry news aggregator—over 32M articles on selected topics published by over 8000 news outlets. Our approach distinguishes between different news outlet reporting styles: high reactivity points to activity fluctuations larger than expected, reflecting a bursty reporting style, whereas low reactivity suggests a relatively stable reporting style. Combining our method with the political bias detector Media Bias/Fact Check we quantify the relative reporting styles for different topics of mainly US media sources grouped by political orientation. The results suggest that news outlets with a liberal bias tended to be the least reactive while conservative news outlets were the most reactive.

Inequality in Under-Five Mortality in Iran: A National and Subnational Survey Data Analysis

2016 ◽  
Vol 9 (3) ◽  
pp. 215 ◽  
Author(s):  
Mostafa Amini Rarani ◽  
Arash Rashidian ◽  
Mohammad Arab ◽  
Ardeshir Khosravi ◽  
Ezatollah Abbasian
Keyword(s):  
Mortality Rate ◽  
Concentration Index ◽  
National Level ◽  
Principal Component ◽  
National Average ◽  
Analysis Model ◽  
Under Five ◽  
Substantial Progress ◽  
Using Data ◽  
Concentration Indices

<p><strong>BACKGROUND: </strong>Despite substantial progress in the national average of under-five mortality rate in Iran, distribution of under-five mortality across different socioeconomic groups is unknown. This study measured socioeconomic inequality in under-five mortality in Iran and across its provinces.</p><p><strong>METHOD: </strong>Using data from provincially representative Multiple Indicator Demographic and Health Survey, conducted in Iran in 2010, we developed an accurate principal component analysis model to construct an indicator of socioeconomic status of Iranian households. Under-five mortality rates at national and subnational level were estimated using full birth history. The indicator then was used to measure inequality in under-five mortality using Wagstaff normalised concentration index (WCI) at national and subnational levels.  </p><p><strong>RESULTS: </strong>Estimates of Wagstaff normalised concentration indices showed a pro-rich inequality in under-five mortality at national and subnational levels. The concentration index of under-five mortality in Iran was -0.197. Moreover, the consistent negative values of the concentration indices indicated that under-five mortality inequality disfavored the worst-off in all provinces. However, the inequality varied among provinces and ranged from -0.013 to -0.487. At national level there was a descending trend in the under-five mortality rate as one moves higher up in the socioeconomic quintiles.</p><p><strong>CONCLUSIONS: </strong>This study suggests that further reduction in under-five mortality not only requires addressing the national average but also needs considering inequality in under-five mortality. Therefore, child health policy requires looking beyond the average, putting equality and average together at both national and sub national levels.</p>

scholarly journals Shrinking a large dataset to identify variables associated with increased risk of Plasmodium falciparum infection in Western Kenya

2015 ◽  
Vol 143 (16) ◽  
pp. 3538-3545 ◽  
Author(s):  
M. TREMBLAY ◽  
J. S. DAHM ◽  
C. N. WAMAE ◽  
W. A. DE GLANVILLE ◽  
E. M. FÈVRE ◽  
...  
Keyword(s):  
Plasmodium Falciparum ◽  
Linear Models ◽  
Principal Component ◽  
Large Datasets ◽  
Single Step ◽  
Large Dataset ◽  
Western Kenya ◽  
The People ◽  
Increased Risk ◽  
Using Data

SUMMARYLarge datasets are often not amenable to analysis using traditional single-step approaches. Here, our general objective was to apply imputation techniques, principal component analysis (PCA), elastic net and generalized linear models to a large dataset in a systematic approach to extract the most meaningful predictors for a health outcome. We extracted predictors for Plasmodium falciparum infection, from a large covariate dataset while facing limited numbers of observations, using data from the People, Animals, and their Zoonoses (PAZ) project to demonstrate these techniques: data collected from 415 homesteads in western Kenya, contained over 1500 variables that describe the health, environment, and social factors of the humans, livestock, and the homesteads in which they reside. The wide, sparse dataset was simplified to 42 predictors of P. falciparum malaria infection and wealth rankings were produced for all homesteads. The 42 predictors make biological sense and are supported by previous studies. This systematic data-mining approach we used would make many large datasets more manageable and informative for decision-making processes and health policy prioritization.

Dietary patterns in Swedish adults; results from a national dietary survey

2015 ◽  
Vol 115 (1) ◽  
pp. 95-104 ◽  
Author(s):  
Erika Ax ◽  
Eva Warensjö Lemming ◽  
Wulf Becker ◽  
Agneta Andersson ◽  
Anna Karin Lindroos ◽  
...  
Keyword(s):  
Dietary Patterns ◽  
Fast Food ◽  
Dietary Habits ◽  
Principal Component ◽  
Processed Meat ◽  
Dietary Survey ◽  
Meal Pattern ◽  
Nutrient Density ◽  
Using Data ◽  
Traditional Pattern

AbstractDietary patterns derived by statistical procedures is a way to identify overall dietary habits in specific populations. The aim of this study was to identify and characterise dietary patterns in Swedish adults using data from the national dietary survey Riksmaten adults 2010–11 (952 women, 788 men). Principal component analyses were used and two patterns were identified in both sexes: a healthy pattern loading positively on vegetables, fruits, fish and seafood, and vegetable oils, and negatively on refined bread and fast food, and a Swedish traditional pattern loading positively on potatoes, meat and processed meat, full-fat milk products, sweet bakery products, sweet condiments and margarine. In addition, a light-meal pattern was identified in women with positive loadings on fibre-rich bread, cheese, rice, pasta and food grain dishes, substitute products for meat and dairy products, candies and tea. The healthy pattern was positively correlated to dietary fibre (r0·51–0·58) andn-3 (r0·25–0·31) (allP<0·0001), and had a higher nutrient density of folate, vitamin D and Se. The Swedish traditional and the light-meal pattern were positively correlated to added sugar (r0·20–0·25) and the Swedish traditional also to SFA (r0·13–0·21) (allP<0·0001); both patterns were in general negatively correlated to micronutrients. Dietary pattern scores were associated with, for example, age, physical activity, education and income. In conclusion, we identified three major dietary patterns among Swedish adults. The patterns can be further used for examining the association between whole diet and health outcomes.

Sign in / Sign up

Export Citation Format

Share Document