Pcbs in Soils around an Old Electric Transformer Factory in North China

2014 ◽  
Vol 587-589 ◽  
pp. 550-553
Author(s):  
Zhi Yong Li ◽  
Lan Chen ◽  
Yu Heng Quan ◽  
Yan Song
Keyword(s):  
North China ◽  
Surface Soil ◽  
Principal Component ◽  
Mean Value ◽  
Transformer Oil ◽  
Total Pcbs ◽  
Pcb Congeners ◽  
Transformer Oils ◽  
The Mean ◽  
Compositional Patterns

The 28 surface soil samples (0-10 cm) were collected from the urban area of Baoding city nearby an old electric transformer factory for analysis of 84 PCB congeners. Total PCBs concentrations ranged from 0.69 to 11.15 ng/g (mean: 3.62 ng/g). The PCBs concentration (5.72 ng/g) for sampling sites in the vicinity (0-2.5 km) of the transformer factory was higher than that (2.96 ng/g) for other sampling sites. Compositional patterns of individual congener and homologs were similar to those of Chinese transformer oils. The top five congeners were PCB-6, 18, 22, 33 and 31/28 among the identified PCBs. Low chlorinated PCBs (di-to tetra-CBs) accounted for 69.58% of total PCBs concentrations and the predominant PCB homologs were tri-CBs (46.38%), penta-CBs (13.73%) and di-CBs (9.47%), respectively. Principal component analysis showed that technical formulations such as Chinese transformer oil, Aroclor1242, 1016, KC-300 and A-30 were the main sources of soils PCBs from Baoding city. The TEQ concentrations based on ten dioxin-like PCBs ranged from 0 to 26.0986 ng/kg with the mean value as 7.3336 ng/kg.

PCBs in Air from an Industrial Zone in a Coastal City-Tianjin, China

2014 ◽  
Vol 587-589 ◽  
pp. 546-549
Author(s):  
Zhi Yong Li ◽  
Yu Ling Zhang ◽  
Shi Qing Ni
Keyword(s):  
Environmental Temperature ◽  
Mean Value ◽  
Steep Slope ◽  
Total Pcbs ◽  
Industrial Zone ◽  
Air Samples ◽  
Pcb Congeners ◽  
Coastal City ◽  
Natural Logarithm ◽  
The Mean

The 23 air samples were collected from Tianjin Dongli industrial zone from July 2010 to May 2011 for the analysis of 84 PCB congeners to investigate the gas/particle partitioning. The total PCBs concentration ranged from 71.08 to 567.36 pg m-3 with the mean value as 307.78±137.45 pg m-3 and the seasonal trends were summer >winter >spring >autumn. Gas PCBs accounted for 77.47% of the total PCBs. The fraction of each gas PCB homolog increased with the decreasing chlorine atoms. The contribution of gas PCBs to total PCBs showed a strong seasonal variation with summer (92.44%)> autumn (85.16%) > spring (80.61%) > winter (42.70%). Tri-, tetra-, penta-PCBs and di-PCBs were the predominantly homologs in atmosphere from industrial zone in Tianjin. The natural logarithm of partial pressure of PCBs were well correlated with the inverse absolute environmental temperature (R=0.77). The steep slope of-3764 obtained from Clausius–Clapeyron plot indicated the influence of local PCBs sources.

scholarly journals Transformer Oil Quality Assessment Using Random Forest with Feature Engineering

Energies ◽  
2021 ◽  
Vol 14 (7) ◽  
pp. 1809
Author(s):  
Mohammed El Amine Senoussaoui ◽  
Mostefa Brahami ◽  
Issouf Fofana
Keyword(s):  
Machine Learning ◽  
Random Forest ◽  
Oil Quality ◽  
Principal Component ◽  
Condition Assessment ◽  
Classification Performance ◽  
Transformer Oil ◽  
Classification Model ◽  
Insulation Degradation ◽  
Transformer Oils

Machine learning is widely used as a panacea in many engineering applications including the condition assessment of power transformers. Most statistics attribute the main cause of transformer failure to insulation degradation. Thus, a new, simple, and effective machine-learning approach was proposed to monitor the condition of transformer oils based on some aging indicators. The proposed approach was used to compare the performance of two machine-learning classifiers: J48 decision tree and random forest. The service-aged transformer oils were classified into four groups: the oils that can be maintained in service, the oils that should be reconditioned or filtered, the oils that should be reclaimed, and the oils that must be discarded. From the two algorithms, random forest exhibited a better performance and high accuracy with only a small amount of data. Good performance was achieved through not only the application of the proposed algorithm but also the approach of data preprocessing. Before feeding the classification model, the available data were transformed using the simple k-means method. Subsequently, the obtained data were filtered through correlation-based feature selection (CFsSubset). The resulting features were again retransformed by conducting the principal component analysis and were passed through the CFsSubset filter. The transformation and filtration of the data improved the classification performance of the adopted algorithms, especially random forest. Another advantage of the proposed method is the decrease in the number of the datasets required for the condition assessment of transformer oils, which is valuable for transformer condition monitoring.

scholarly journals Intra-line and inter-line genetic diversity in sire lines of the Old Kladruber horse based on microsatellite analysis of DNA

2011 ◽  
Vol 56 (No. 4) ◽  
pp. 163-175 ◽  
Author(s):  
L. Vostrý ◽  
O. Kracíková ◽  
B. Hofmanová ◽  
V. Czerneková ◽  
T. Kott ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Dna Analysis ◽  
Genetic Difference ◽  
Principal Component ◽  
Genetic Distances ◽  
Mean Value ◽  
Pedigree Information ◽  
Mean Values ◽  
The Mean ◽  
Coefficient Of Relationship

The Old Kladruber horse is the oldest original Czech horse breed &ndash; gene resource, with pedigree records spanning three centuries. Because the population is closed, there is a concern about the loss of genetic variation. The genetic diversity within and amongst sire lines was evaluated using microsatellite markers and based on pedigree information. The DNA analysis, covering 16 microsatellite loci, revealed that the genetic diversity (observed heterozygosity = 0.637, genetic diversity = 0.678 and the mean number of alleles = 8.25) for the Old Kladruber horse is consistent with other populations of horses. Inter-line genetic difference in sire lines reached the mean value (the F<sub>ST</sub> values ranged from 0.020 to 0.017). Differences amongst the sire lines were identified using genetic distances and principal component analysis. One gene cluster comprised black variation sire lines, while the second cluster included the sire lines of the grey variation. In the subjects monitored, the average inbreeding coefficient of 0.076 was estimated on the basis of pedigree information. The highest mean values of the coefficient of relationship were estimated within the colour variations. When comparing the genetic distance and the average coefficient of relationship, differences were found out. These results are useful for the development of breeding strategies which consider classical horse breeding as well as recent achievements of population and conservation genetics.

Analysis and Evaluation for Usability of the Low Hydrogen Type Structural Steel Covered Electrode

2008 ◽  
Vol 575-578 ◽  
pp. 684-689
Author(s):  
Yong Wang ◽  
Bao Wang ◽  
Jun Hua Gao
Keyword(s):  
Structural Steel ◽  
Principal Component ◽  
Welding Current ◽  
Mean Value ◽  
Metal Transfer ◽  
Analysis And Evaluation ◽  
Transfer Mode ◽  
The Mean ◽  
The One ◽  
Information Values

Metal transfer mode of the low hydrogen type structural steel covered electrode is the one that coexists as the globular short-circuiting transfer and the fine droplet transfer in the flux-bridge. Component of the metal transfer modes has a direct effect on usability of the covered electrode. The oscillograms of the arc voltage and the welding current gained using the traditional photoelectric oscillograph can only qualitatively describe the general characteristics of metal transfer, but can’t make a quantitative analysis. Using the ANALYSATOR HANNOVER, the welding electrical parameters are measured and analyzed. Four characteristic information values correlated with usability of the covered electrode, such as the frequency of the globular short-circuiting transfer, the globular short-circuiting time, the mean value of the globular short-circuiting time and the mean value of the weighted arcing time, are extracted. The method of principal component analysis is applied to determining the evaluation index for usability of the covered electrode. Thereby quantitative evaluation for usability of the covered electrode is realized. A new method is offered for scientifically evaluating usability of the low hydrogen type structural steel covered electrode.

A comparison of chronologies from tree rings

1990 ◽  
Vol 20 (1) ◽  
pp. 76-83 ◽  
Author(s):  
Kurt H. Riitters
Keyword(s):  
Ring Width ◽  
Principal Component ◽  
Mean Value ◽  
Value Functions ◽  
Individual Tree ◽  
Median Polish ◽  
Cross Correlations ◽  
Tree Index ◽  
The Mean ◽  
Component Scores

Forty-five-year ring width index chronologies were estimated by five mean-value functions applied to 183 ring width series from four similar sites. The effects of autocorrelation on the comparisons among mean-value functions were explored by fitting Box–Jenkins models to individual-tree index series prior to pooling (prewhitening), and to the pooled chronologies obtained from the mean-value functions (postwhitening). Among the mean-value functions tested, the principal component scores and the biweight yielded the highest cross correlations between chronologies from different sites, whereas the average, the median, and the median polish did not perform as well. Prewhitening and postwhitening tended to decrease both intersite correlations and correlations between chronologies from different mean-value functions for the same site.

scholarly journals Multiview Machine Vision Research of Fruits Boxes Handling Robot Based on the Improved 2D Kernel Principal Component Analysis Network

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Xinning Li ◽  
Hu Wu ◽  
Xianhai Yang ◽  
Peng Xue ◽  
Shuai Tan
Keyword(s):  
Principal Component Analysis ◽  
Recognition Rate ◽  
Principal Component ◽  
Component Analysis ◽  
Mean Value ◽  
Kernel Principal Component Analysis ◽  
Support Vector ◽  
Svm Classifier ◽  
Labour Intensity ◽  
The Mean

In order to better realize the orchard intelligent mechanization and reduce the labour intensity of workers, the study of intelligent fruit boxes handling robot is necessary. The first condition to realize intelligence is the fruit boxes recognition, which is the research content of this paper. The method of multiview two-dimensional (2D) recognition was adopted. A multiview dataset for fruits boxes was built. For the sake of the structure of the original image, the model of binary multiview 2D kernel principal component analysis network (BM2DKPCANet) was established to reduce the data redundancy and increase the correlation between the views. The method of multiview recognition for the fruits boxes was proposed combining BM2DKPCANet with the support vector machine (SVM) classifier. The performance was verified by comparing with principal component analysis network (PCANet), 2D principal component analysis network (2DPCANet), kernel principal component analysis network (KPCANet), and binary multiview kernel principal component analysis network (BMKPCANet) in terms of recognition rate and time consumption. The experimental results show that the recognition rate of the method is 11.84% higher than the mean value of PCANet though it needs more time. Compared with the mean value of KPCANet, the recognition rate exceeded 2.485%, and the time saved was 24.5%. The model can meet the requirements of fruits boxes handling robot.

scholarly journals Phenotypic Diversity of Clarias gariepinus (Burchell, 1822) from Benue River and a Tributary in North East Nigeria.

2021 ◽  
Vol 2 (1) ◽  
pp. 09-018
Author(s):  
Mamndeyati Ndekimbe Uruku ◽  
Innocent Agbo Adikwu ◽  
Oyediran Olusegun Oyebola ◽  
Timothy E. Uchendu
Keyword(s):  
Phenotypic Diversity ◽  
Phenotypic Variability ◽  
Clarias Gariepinus ◽  
Principal Component ◽  
Mean Value ◽  
Adaptive Traits ◽  
North East ◽  
Fishing Gears ◽  
Coefficient Of Variability ◽  
The Mean

Phenotypic Variability of Sampled Clarias gariepinus (Burchell, 1822) Population were assessed. 30 matured samples of Clarias gariepinus of different sizes were bought from artisanal fisherfolks using various fishing gears, morphometric and meristic attributes and other adaptive traits were characterized. Phenotypic heterogeneity (Coefficient of Variability > 10%) and multiple modes in Meristic and morphometric Values were assessed to imply plasticity and taxonomic complications respectively. Twenty morphometric and nine meristic attributes were measured in all the collected individuals and measured to the nearest 0.01cm, using Vernier calipers. The mean value of meristic attributes varied from 6.20±0.93 in PELFR-R to 71.40±5.64 in DFR. Coefficient of variability of the population varied from 7.89 in DFR to 54.02 in PESES-L. Heterogeneity occurred in 77.8% of meristic attributes except DFR and CFR. Multiple modal was recorded in PESES-L, while the mean value of the morphometric attributes varied from 5.20±0.82 in OPD to 64.52±5.00 in DFL. Coefficient of variability of the population varied from 7.76 in DFL to 18.07 in CFW. Heterogeneity occurred in 82.4% of morphometric attributes. Five components accounted for 78.65% of the total variation using Principal Component Analysis on morphometric attributes. Two of the extracted components had CV > 10 (41.70%, and 15.02%). However, the scree plot shows the slope of the variation to favors the five component with Eigenvalue greater than one. The studied C. gariepinus population was characterized by heterogeneity of phenotypic values and the population can be taxonomically discriminated by meristic and morpho types.

APPLICATIONS OF 3D PCA METHOD FOR EXTRACTION OF MEAN SHAPE AND GEOMETRICAL FEATURES OF BIOLOGICAL OBJECTS SET

2008 ◽  
Vol 13 (3) ◽  
pp. 413-420 ◽  
Author(s):  
Michal Rychlik ◽  
Witold Stankiewicz ◽  
Marek Morzyński
Keyword(s):  
Three Dimensional ◽  
Principal Component ◽  
Mean Value ◽  
Analysis Method ◽  
3D Objects ◽  
Biological Objects ◽  
Geometrical Features ◽  
Mean Shape ◽  
Pca Method ◽  
The Mean

This article presents application of the Principal Component Analysis method for analysis of geometry of biological objects and computation of three dimensional anthropometric database. In this work as the biological objects the fifteen human femur bones were used. The geometry of each bone was obtained by using 3D structural light scanner. For PCA analysis all objects have to be described with the same FEM mesh. To achieve this, the modified fluid registration was used. PCA decomposes the set of 3D objects into mean geometry and individual features (empirical modes) describing deviations from mean value. In this paper the mean shape and features of real bones were presented and discussed.

Long-period modulated superstructures in Pd-12.5 at.%Ce and Pd-15 at.%Ce alloys

1990 ◽  
Vol 48 (4) ◽  
pp. 164-165
Author(s):  
Noriyuki Kuwano ◽  
Masaru Itakura ◽  
Kensuke Oki
Keyword(s):  
Electron Microscopy ◽  
Mean Value ◽  
Heavy Elements ◽  
Arc Furnace ◽  
X Ray ◽  
Long Period ◽  
Ultra High Purity ◽  
Heat Treated ◽  
Atomic Scattering ◽  
The Mean

Pd-Ce alloys exhibit various anomalies in physical properties due to mixed valences of Ce, and the anomalies are thought to be strongly related with the crystal structures. Since Pd and Ce are both heavy elements, relative magnitudes of (fcc-fpd) are so small compared with <f> that superlattice reflections, even if any, sometimes cannot be detected in conventional x-ray powder patterns, where fee and fpd are atomic scattering factors of Ce and Pd, and <f> the mean value in the crystal. However, superlattices in Pd-Ce alloys can be analyzed by electron microscopy, thanks to the high detectability of electron diffraction. In this work, we investigated modulated superstructures in alloys with 12.5 and 15.0 at.%Ce.Ingots of Pd-Ce alloys were prepared in an arc furnace under atmosphere of ultra high purity argon. The disc specimens cut out from the ingots were heat-treated in vacuum and electrothinned to electron transparency by a jet method.

Partition Coefficient Ratios and Tumour Perfusion Studied with 85mKr and 133Xe

1987 ◽  
Vol 26 (06) ◽  
pp. 253-257
Author(s):  
M. Mäntylä ◽  
J. Perkkiö ◽  
J. Heikkonen
Keyword(s):  
Partition Coefficient ◽  
Partition Coefficients ◽  
Regional Blood Flow ◽  
Blood Perfusion ◽  
Compartmental Analysis ◽  
Malignant Tumour ◽  
Mean Value ◽  
Perfusion Rate ◽  
Biological Variables ◽  
The Mean

The relative partition coefficients of krypton and xenon, and the regional blood flow in 27 superficial malignant tumour nodules in 22 patients with diagnosed tumours were measured using the 85mKr- and 133Xe-clearance method. In order to minimize the effect of biological variables on the measurements the radionuclides were injected simultaneously into the tumour. The distribution of the radiotracers was assumed to be in equilibrium at the beginning of the experiment. The blood perfusion was calculated by fitting a two-exponential function to the measuring points. The mean value of the perfusion rate calculated from the xenon results was 13 ± 10 ml/(100 g-min) [range 3 to 38 ml/(100 g-min)] and from the krypton results 19 ± 11 ml/(100 g-min) [range 5 to 45 ml/(100 g-min)]. These values were obtained, if the partition coefficients are equal to one. The equations obtained by using compartmental analysis were used for the calculation of the relative partition coefficient of krypton and xenon. The partition coefficient of krypton was found to be slightly smaller than that of xenon, which may be due to its smaller molecular weight.

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