scholarly journals High-Accuracy 14C Measurements for Atmospheric CO2 Samples by AMS

Radiocarbon ◽  
2006 ◽  
Vol 48 (3) ◽  
pp. 355-372 ◽  
Author(s):  
H A J Meijer ◽  
M H Pertuisot ◽  
J van der Plicht
Keyword(s):  
High Accuracy ◽  
South Pole ◽  
The South ◽  
Data Set ◽  
Error Sources ◽  
Present Measurement ◽  
Combined Uncertainty ◽  
Source Of Information ◽  
Global Carbon ◽  
Better Than

In this paper, we investigate how to achieve high-accuracy radiocarbon measurements by accelerator mass spectrometry (AMS) and present measurement series (performed on archived CO2) of 14CO2 between 1985 and 1991 for Point Barrow (Alaska) and the South Pole. We report in detail the measurement plan, the error sources, and the calibration scheme that enabled us to reach a combined uncertainty of better than ±3%. The δ13C correction and a suggestion for a span (or 2-point) calibration for the 14C scale are discussed in detail. In addition, we report new, accurate values for the calibration and reference materials Ox2 and IAEA-C6 with respect to Oxl. The atmospheric 14CO2 records (1985–1991) are presented as well and are compared with other existing records for that period. The Point Barrow record agrees very well with the existing Fruholmen (northern Norway) record from the same latitude. The South Pole record shows a small seasonal cycle but with an extreme phase with a maximum on January 1st (±13 days). Together with its generally elevated 14C level compared to the Neumayer record (coastal Antarctica), this makes our South Pole data set a valuable additional source of information for global carbon cycle modeling using 14CO2 as a constraint.

scholarly journals Submillimeter Site Testing at Dome C, Antarctica

2004 ◽  
Vol 21 (3) ◽  
pp. 256-263 ◽  
Author(s):  
Paolo G. Calisse ◽  
Michael C. B. Ashley ◽  
Michael G. Burton ◽  
Michael A. Phillips ◽  
John W. V. Storey ◽  
...  
Keyword(s):  
South Pole ◽  
Site Testing ◽  
The South ◽  
Atmospheric Opacity ◽  
Antarctic Plateau ◽  
Under Construction ◽  
The Antarctic ◽  
Better Than

AbstractWe have developed a 350 μm radiometer to perform automated site testing in remote regions of Antarctica. In summer 2000–2001 the instrument operated at Concordia, a new station under construction at Dome C on the Antarctic Plateau. We present the results, and compare them with the atmospheric opacity measured at the South Pole in the same five-week period. During these five weeks, observing conditions at Dome C were, on average, substantially better than those at the South Pole.

scholarly journals Emotion detection on cross platform languages

2018 ◽  
Vol 7 (2.18) ◽  
pp. 27
Author(s):  
Mohammad Arif ◽  
Mandeep Singh ◽  
Rajdavinder Boparai
Keyword(s):  
Emotion Detection ◽  
Data Set ◽  
Cross Domain ◽  
The People ◽  
English Alphabet ◽  
Cross Platform ◽  
Source Of Information ◽  
Information Today ◽  
Better Than

Internet has changed the course of our living. It has become the most beneficial antecedent or source of information. Today almost everything is found on internet. Everyday millions of people post their ideas, reviews, stories about the services, products or other persons. The size of data is increasing tremendously. It is very difficult to analyze that amount of data and figure out the emotions or sentiments posed by people. Emotion detection is such a technique where we can judge people’s ideas and extract the emotion towards an entity or service. We have used subjective lexicon-based approach to bench the emoticons expressed by the ideas of the people. The data set that we have mainly focused is very cross and noisy. We have used Facebook data in Urdu and Kashmiri language. Both languages are very cross domain. These languages can be written in English alphabet that makes them more challenging to analyses. Our approach resolves the challenge to the maximum possible way. The results shown by our method on this kind of data set are better than any other approach. Our analysis on this type of dataset will help the local businessmen of these areas to grow and flourish. The analysis will give some insights what the local feel about the entity or product so that the manufacturers can design or build it that way and try to enhance its qualities.  

scholarly journals Block Adjustment without GCPs for Chinese Spaceborne SAR GF-3 Imagery

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 4023 ◽  
Author(s):  
Guo Zhang ◽  
Qingwei Wu ◽  
Taoyang Wang ◽  
Ruishan Zhao ◽  
Mingjun Deng ◽  
...  
Keyword(s):  
High Accuracy ◽  
Control Points ◽  
Wuhan City ◽  
Error Sources ◽  
Geometric Calibration ◽  
Ground Control Points ◽  
Rational Polynomial ◽  
Sar Imagery ◽  
Orientation Parameters ◽  
Better Than

The Gaofen-3 (GF-3) satellite is the first C-band multi-polarization synthetic aperture radar (SAR) with the ability of high-accuracy mapping in China. However, the Ground Control Points (GCPs) are essential to ensure the accuracy of mapping for GF-3 SAR imagery at present. In this paper, we analyze the error sources that affect the geometric processing and propose a new block adjustment method without GCPs for GF-3 SAR imagery. Firstly, the geometric calibration of GF-3 image is carried out. Secondly, the rational polynomial coefficient (RPC) model is directly generated after the geometric calibration parameters compensation of each image. Finally, we solve the orientation parameters of the GF-3 images through DEM assisted planar block adjustment and conduct ortho-rectification. With two different imaging modes of GF-3 satellite, which include the QPSI and FS2, we carry out the block adjustment without GCPs. Experimental results of testing areas including Wuhan city and Hubei province in China show that the geometric mosaic accuracy and the absolute positioning accuracy of the orthophoto are better than one pixel, which has laid a good foundation for the application of GF-3 image in global high-accuracy mapping.

scholarly journals Transient eastward-propagating long-period waves observed over the South Pole

1998 ◽  
Vol 16 (11) ◽  
pp. 1486-1500 ◽  
Author(s):  
S. E. Palo ◽  
Y. I. Portnyagin ◽  
J. M. Forbes ◽  
N. A. Makarov ◽  
E. G. Merzlyakov
Keyword(s):  
Atmospheric Dynamics ◽  
Horizontal Wind ◽  
South Pole ◽  
The South ◽  
Winter Solstice ◽  
Data Set ◽  
Long Period ◽  
Spring Equinox ◽  
Propagating Waves ◽  
Middle Atmospheric Dynamics

Abstract. Observations of the horizontal wind field over the South Pole were made during 1995 using a meteor radar. These data have revealed the presence of a rich spectrum of waves over the South Pole with a distinct annual occurrence. Included in this spectrum are long-period waves, whose periods are greater than one solar day, which are propagating eastward. These waves exhibit a distinct seasonal occurrence where the envelope of wave periods decreases from a period of 10 days near the fall equinox to a minimum of 2 days near the winter solstice and then progresses towards a period near 10 days at the spring equinox. Computation of the meridional gradient of quasi-geostrophic potential vorticity has revealed a region in the high-latitude upper mesosphere which could support an instability and serve as a source for these waves. Estimation of the wave periods which would be generated from an instability in this region closely resembles the observed seasonal variation in wave periods over the South Pole. These results are consistent with the hypothesis that the observed eastward propagating long-period waves over the South Pole are generated by an instability in the polar upper mesosphere. However, given our limited data set we cannot rule out a stratospheric source. Embedded in this spectrum of eastward propagating waves during the austral winter are a number of distinct wave events. Eight such wave events have been identified and localized using a constant-Q filter bank. The periods of these wave events ranges from 1.7 to 9.8 days and all exist for at least 3 wave periods. Least squares analysis has revealed that a number of these events are inconsistent with a wave propagating zonally around the geographic pole and could be related to waves propagating around a dynamical pole which is offset from the geographic pole. Additionally, one event which was observed appears to be a standing oscillation.Key words. Meteorology and atmospheric dynamics (Middle atmospheric dynamics; waves and tides).

scholarly journals FAKE NEWS DETECTION USING VARIOUS MACHINE LEARNING TECHNIQUES

2021 ◽  
pp. 134-137
Author(s):  
Akanksha Akulwar ◽  
Anish Khobragade
Keyword(s):  
Machine Learning ◽  
High Accuracy ◽  
Machine Learning Techniques ◽  
Support Vector ◽  
Fake News ◽  
Data Set ◽  
Online Platforms ◽  
Learning Techniques ◽  
Original Classification ◽  
Better Than

Online platforms are being used for outspreading malicious talk, which creates an impact on the minds of millions. Many distinct approaches have been brought forward to detect this fake news, but very few have been carried out in the actual world. We address this problem of estimating the rumor authentication in a real-world in less time with significantly high accuracy. We design and implement an approach addressing the above issue. We accessed whether the news is fake or not using various Machine learning techniques. We evaluate this algorithm on a set of data set scrapped from random online sites. The result shows that the performance of this improved algorithm is better than the original classification method. And finally, we consider various sizes of data to view and compare the accuracy. KEYWORDS—Support Vector Machine, Decision Tree, Fake Content, Naive Bayes, Machine Learning Models

Expedition to the South Pole: experience of the laboratory game on polar sciences with primary schools

2018 ◽  
Vol 45 ◽  
pp. 31-38
Author(s):  
Federica La Longa ◽  
Massimo Crescimbene ◽  
Lucilla Alfonsi ◽  
Claudio Cesaroni ◽  
Vincenzo Romano
Keyword(s):  
Primary Schools ◽  
South Pole ◽  
The South

Evaluation for estimating of the PDF and the CDF of Generalized Inverted Exponential Distribution with Application in Industry

2020 ◽  
pp. 507-522
Author(s):  
Parisa Torkaman
Keyword(s):  
Least Squares ◽  
Exponential Distribution ◽  
Mean Squared Error ◽  
Weighted Least Squares ◽  
Real Data ◽  
Minimum Variance ◽  
Cumulative Distribution ◽  
Estimation Methods ◽  
Data Set ◽  
Better Than

The generalized inverted exponential distribution is introduced as a lifetime model with good statistical properties. This paper, the estimation of the probability density function and the cumulative distribution function of with five different estimation methods: uniformly minimum variance unbiased(UMVU), maximum likelihood(ML), least squares(LS), weighted least squares (WLS) and percentile(PC) estimators are considered. The performance of these estimation procedures, based on the mean squared error (MSE) by numerical simulations are compared. Simulation studies express that the UMVU estimator performs better than others and when the sample size is large enough the ML and UMVU estimators are almost equivalent and efficient than LS, WLS and PC. Finally, the result using a real data set are analyzed.

A Computational Method for the Identification of Endolysins and Autolysins

2020 ◽  
Vol 27 (4) ◽  
pp. 329-336 ◽  
Author(s):  
Lei Xu ◽  
Guangmin Liang ◽  
Baowen Chen ◽  
Xu Tan ◽  
Huaikun Xiang ◽  
...  
Keyword(s):  
Support Vector Machine ◽  
Cell Wall ◽  
Experimental Results ◽  
Computational Method ◽  
Lytic Enzyme ◽  
Support Vector ◽  
Lytic Enzymes ◽  
Data Set ◽  
Optimal Feature ◽  
Better Than

Background: Cell lytic enzyme is a kind of highly evolved protein, which can destroy the cell structure and kill the bacteria. Compared with antibiotics, cell lytic enzyme will not cause serious problem of drug resistance of pathogenic bacteria. Thus, the study of cell wall lytic enzymes aims at finding an efficient way for curing bacteria infectious. Compared with using antibiotics, the problem of drug resistance becomes more serious. Therefore, it is a good choice for curing bacterial infections by using cell lytic enzymes. Cell lytic enzyme includes endolysin and autolysin and the difference between them is the purpose of the break of cell wall. The identification of the type of cell lytic enzymes is meaningful for the study of cell wall enzymes. Objective: In this article, our motivation is to predict the type of cell lytic enzyme. Cell lytic enzyme is helpful for killing bacteria, so it is meaningful for study the type of cell lytic enzyme. However, it is time consuming to detect the type of cell lytic enzyme by experimental methods. Thus, an efficient computational method for the type of cell lytic enzyme prediction is proposed in our work. Method: We propose a computational method for the prediction of endolysin and autolysin. First, a data set containing 27 endolysins and 41 autolysins is built. Then the protein is represented by tripeptides composition. The features are selected with larger confidence degree. At last, the classifier is trained by the labeled vectors based on support vector machine. The learned classifier is used to predict the type of cell lytic enzyme. Results: Following the proposed method, the experimental results show that the overall accuracy can attain 97.06%, when 44 features are selected. Compared with Ding's method, our method improves the overall accuracy by nearly 4.5% ((97.06-92.9)/92.9%). The performance of our proposed method is stable, when the selected feature number is from 40 to 70. The overall accuracy of tripeptides optimal feature set is 94.12%, and the overall accuracy of Chou's amphiphilic PseAAC method is 76.2%. The experimental results also demonstrate that the overall accuracy is improved by nearly 18% when using the tripeptides optimal feature set. Conclusion: The paper proposed an efficient method for identifying endolysin and autolysin. In this paper, support vector machine is used to predict the type of cell lytic enzyme. The experimental results show that the overall accuracy of the proposed method is 94.12%, which is better than some existing methods. In conclusion, the selected 44 features can improve the overall accuracy for identification of the type of cell lytic enzyme. Support vector machine performs better than other classifiers when using the selected feature set on the benchmark data set.

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