scholarly journals A New Geometric Metric in the Shape and Size Space of Curves in R n

Mathematics ◽  
2020 ◽  
Vol 8 (10) ◽  
pp. 1691
Author(s):  
Irene Epifanio ◽  
Vicent Gimeno ◽  
Ximo Gual-Arnau ◽  
M. Victoria Ibáñez-Gual
Keyword(s):  
Nearest Neighbor ◽  
Simulated Data ◽  
Shape Space ◽  
Data Set ◽  
Scale Size ◽  
The Difference ◽  
Active Research ◽  
First Time ◽  
Shape And Size ◽  
Better Than

Shape analysis of curves in Rn is an active research topic in computer vision. While shape itself is important in many applications, there is also a need to study shape in conjunction with other features, such as scale and orientation. The combination of these features, shape, orientation and scale (size), gives different geometrical spaces. In this work, we define a new metric in the shape and size space, S2, which allows us to decompose S2 into a product space consisting of two components: S4×R, where S4 is the shape space. This new metric will be associated with a distance function, which will clearly distinguish the contribution that the difference in shape and the difference in size of the elements considered makes to the distance in S2, unlike the previous proposals. The performance of this metric is checked on a simulated data set, where our proposal performs better than other alternatives and shows its advantages, such as its invariance to changes of scale. Finally, we propose a procedure to detect outlier contours in S2 considering the square-root velocity function (SRVF) representation. For the first time, this problem has been addressed with nearest-neighbor techniques. Our proposal is applied to a novel data set of foot contours. Foot outliers can help shoe designers improve their designs.

scholarly journals Investigation and Validation of the Time-Varying Characteristic for the GPS Differential Code Bias

2019 ◽  
Vol 11 (4) ◽  
pp. 428 ◽  
Author(s):  
Haojun Li ◽  
Jingxin Xiao ◽  
Weidong Zhu
Keyword(s):  
Single Point ◽  
Time Varying ◽  
International Gnss Service ◽  
Data Set ◽  
Differential Code Bias ◽  
Triple Frequency ◽  
Code Bias ◽  
Constant Part ◽  
The Difference ◽  
Better Than

The time-varying characteristic of the bias in the GPS code observation is investigated using triple-frequency observations. The method for estimating the combined code bias is presented and the twelve-month (1 January–31 December 2016) triple-frequency GPS data set from 114 International GNSS Service (IGS) stations is processed to analyze the characteristic of the combined code bias. The results show that the main periods of the combined code bias are 12, 8, 6, 4, 4.8 and 2.67 h. The time-varying characteristic of the combined code bias, which is the combination of differential code bias (DCB) (P1–P5) and DCB (P1–P2), shows that the real satellite DCBs are also time-varying. The difference between the two sets of the computed constant parts of the combined code bias, with the IGS DCB products of DCB (P1–P2) and DCB (P1–P2) and the mean of the estimated 24-h combined code bias series, further show that the combined code bias cannot be replaced by the DCB (P1–P2) and DCB (P1–P5) products. The time-varying part of inter-frequency clock bias (IFCB) can be estimated by the phase and code observations and the phase based IFCB is the combinations of the triple-frequency satellite uncalibrated phase delays (UPDs) and the code-based IFCB is the function of the DCBs. The performances of the computed the IFCB with different methods in single point positioning indicate that the accuracy for the constant part of the combined code bias is reduced, when the IGS DCB products are used to compute. These performances also show that the time-varying part of IFCB estimated with phase observation is better than that of code observation. The predicted results show that 98% of the predicted constant part of the combined code bias can be corrected and the attenuation of the predicted accuracy is much less evident. However, the accuracy of the predicted time-varying part decreases significantly with the predicted time.

Collaborative filtering recommendation algorithm based on class correlation distance

2019 ◽  
Vol 13 ◽  
Author(s):  
Hanfei Zhang ◽  
Yumei Jian ◽  
Ping Zhou
Keyword(s):  
Collaborative Filtering ◽  
Nearest Neighbor ◽  
Experimental Result ◽  
K Nearest Neighbor ◽  
Recommendation Algorithm ◽  
K Value ◽  
Correlation Distance ◽  
Training Samples ◽  
The Difference ◽  
Better Than

: A class correlation distance collaborative filtering recommendation algorithm is proposed to solve the problems of category judgment and distance metric in the traditional collaborative filtering recommendation algorithm, which is using the advantage of the distance between the same samples and the class related distance. First, the class correlation distance between the training samples is calculated and stored. Second, the K nearest neighbor samples are selected, the class correlation distance of training samples and the difference ratio between the test samples and training samples are calculated respectively. Finally, according to the difference ratio, we classify the different types of samples. The experimental result shows that the algorithm combined with user rating preference can get lower MAE value, and the recommendation effect is better. With the change of K value, CCDKNN algorithm is obviously better than KNN algorithm and DWKNN algorithm, and the accuracy performance is more stable. The algorithm improves the accuracy of similarity and predictability, which has better performance than the traditional algorithm.

scholarly journals MSEPBurr Distribution: Properties and Parameter Estimation

2019 ◽  
pp. 179-193 ◽  
Author(s):  
Achmad Syahrul Choir ◽  
Nur Iriawan ◽  
Brodjol Sutijo Suprih Ulama ◽  
Mohammad Dokhi
Keyword(s):  
Reaction Rate ◽  
Simulated Data ◽  
Real Data ◽  
Normal Distributions ◽  
Student T Distribution ◽  
Chemical Reaction Rate ◽  
The Difference ◽  
T Distribution ◽  
Mean Variance ◽  
Better Than

MSNBurr and MSTBurr distribution have been developed as Neo-Normal distributions that represent a relaxation of normality. The difference between them is that the MSTBurr’s peak is below MSNBurr’s. In this paper, we propose a MSEPBurr distribution with its peak could be not only lower but also high-er than MSNBurr. Furthermore, we study several properties of MSEPBurr, such as mean, variance, skewness, kurtosis, and quantile. The MSEPBurr parameters are estimated by using the Bayesian approach with the BUGS language implementation for its computation. We employ simulation study and use existing data to illustrate the application of the regression model. In real data, we notice that MSEPBurr has similar performance with MSNBurr and MSTBurr that they outperform Normal and Student-t distribution in Australian athlete data because their skewness can accommodate long left tail excellently. However, their performance is less than the Student-t model in chemical reaction rate data because their skewness can not accommodate long right tail perfectly. Although in general their perfor-mance is the same,  we observe that the MSEPBurr performs better than the MSNBurr and the MSTBurr in some simulated data.

scholarly journals Two decades of satellite observations of AOD over mainland China

2017 ◽  
Author(s):  
Gerrit de Leeuw ◽  
Larisa Sogacheva ◽  
Edith Rodriguez ◽  
Konstantinos Kourtidis ◽  
Aristeidis K. Georgoulias ◽  
...  
Keyword(s):  
Time Series ◽  
Mainland China ◽  
Satellite Observations ◽  
Data Series ◽  
Data Sets ◽  
Data Set ◽  
Modis Aod ◽  
The Difference ◽  
Aerosol Properties ◽  
Better Than

Abstract. The retrieval of aerosol properties from satellite observations provides their spatial distribution over a wide area in cloud-free conditions. As such, they complement ground-based measurements by providing information over sparsely instrumented areas, albeit that significant differences may exist in both the type of information obtained and the temporal information from satellite and ground-based observations. In this paper, information from different types of satellite-based instruments is used to provide a 3-D climatology of aerosol properties over mainland China, i.e. vertical profiles of extinction coefficients from CALIOP, a lidar flying on board the CALIPSO satellite, and the column-integrated extinction (AOD), available from three radiometers: ESA’s ATSR-2, AATSR (together referred to as ATSR) and NASA's MODIS/Terra, together spanning the period 1995–2015. AOD data are retrieved from ATSR using the ADV v2.31 algorithm while for MODIS the Collection 6 (C6) DTDB merged AOD data set is used. These data sets are validated and differences are compared using AERONET version 2 L2.0 AOD data as reference. The results show that, over China, MODIS slightly overestimates the AOD and ATSR slightly underestimates the AOD. Consequently, MODIS AOD is overall higher than that from ATSR, and the difference increases with increasing AOD. The comparison also shows that none of the ATSR and MODIS AOD data sets is better than the other one everywhere. However, ATSR ADV has limitations over bright surfaces where the MODIS DB was designed for. To allow for comparison of MODIS C6 results with previous analyses where MODIS Collection 5.1 (C5.1) data were used, also the difference between the C6 and C5.1 DTDB merged data sets from MODIS/Terra over China is briefly discussed. The AOD data sets show strong seasonal differences and the seasonal features vary with latitude and longitude across China. Two-decadal AOD time series, averaged over the whole mainland China, are presented and briefly discussed. Using the 17 years of ATSR data as the basis and MODIS/Terra to follow the temporal evolution in recent years when ENVISAT was lost requires a comparison of the data sets for the overlapping period to show their complementarity. ATSR precedes the MODIS time series between 1995 and 2000 and shows a distinct increase in the AOD over this period. The two data series show similar variations during the overlapping period between 2000 and 2011, with minima and maxima in the same years. MODIS extends this time series beyond the end of the ENVISAT period in 2012, showing decreasing AOD.

scholarly journals COSMOGRAIL

2020 ◽  
Vol 640 ◽  
pp. A105 ◽  
Author(s):  
M. Millon ◽  
F. Courbin ◽  
V. Bonvin ◽  
E. Paic ◽  
G. Meylan ◽  
...  
Keyword(s):  
Time Delay ◽  
Time Delays ◽  
Light Curves ◽  
Monitoring Data ◽  
Data Set ◽  
Delay Measurement ◽  
Leonhard Euler ◽  
The Difference ◽  
Quasar Variability ◽  
First Time

We present the results of 15 years of monitoring lensed quasars, which was conducted by the COSMOGRAIL programme at the Leonhard Euler 1.2 m Swiss Telescope. The decade-long light curves of 23 lensed systems are presented for the first time. We complement our data set with other monitoring data available in the literature to measure the time delays in 18 systems, among which nine reach a relative precision better than 15% for at least one time delay. To achieve this, we developed an automated version of the curve-shifting toolbox PyCS to ensure robust estimation of the time delay in the presence of microlensing, while accounting for the errors due to the imperfect representation of microlensing. We also re-analysed the previously published time delays of RX J1131−1231 and HE 0435−1223, by adding six and two new seasons of monitoring, respectively, and confirming the previous time-delay measurements. When the time delay measurement is possible, we corrected the light curves of the lensed images from their time delay and present the difference curves to highlight the microlensing signal contained in the data. To date, this is the largest sample of decade-long lens monitoring data, which is useful to measure H0 and the size of quasar accretion discs with microlensing as well as to study quasar variability.

scholarly journals Mass-loss along the red giant branch in 46 globular clusters and their multiple populations

2020 ◽  
Vol 498 (4) ◽  
pp. 5745-5771
Author(s):  
M Tailo ◽  
A P Milone ◽  
E P Lagioia ◽  
F D’Antona ◽  
A F Marino ◽  
...  
Keyword(s):  
Mass Loss ◽  
Globular Clusters ◽  
First Generation ◽  
Hubble Space Telescope ◽  
Population Synthesis ◽  
Data Set ◽  
Complex Interactions ◽  
The Difference ◽  
Red Giant ◽  
First Time

ABSTRACT The location of Galactic globular clusters’ (GC) stars on the horizontal branch (HB) should mainly depend on GC metallicity, the ‘first parameter’, but it is actually the result of complex interactions between the red giant branch (RGB) mass-loss, the coexistence of multiple stellar populations with different helium content, and the presence of a ‘second parameter’ that produces dramatic differences in HB morphology of GCs of similar metallicity and ages (like the pair M3–M13). In this work, we combine the entire data set from the Hubble Space Telescope Treasury survey and stellar evolutionary models, to analyse the HBs of 46 GCs. For the first time in a large sample of GCs, we generate population synthesis models, where the helium abundances for the first and the ‘extreme’ second generations are constrained using independent measurements based on RGB stars. The main results are as follows: (1) The mass-loss of first-generation stars is tightly correlated to cluster metallicity. (2) The location of helium enriched stars on the HB is reproduced only by adopting a higher RGB mass-loss than for the first generation. The difference in mass-loss correlates with helium enhancement and cluster mass. (3) A model of ‘pre-main sequence disc early loss’, previously developed by the authors, explains such a mass-loss increase and is consistent with the findings of multiple-population formation models predicting that populations more enhanced in helium tend to form with higher stellar densities and concentrations. (4) Helium-enhancement and mass-loss both contribute to the second parameter.

On Premiums Deduced from the Mortality Experience (1863-1893) of British Life Offices

1903 ◽  
Vol 1 ◽  
pp. 109-144 ◽  
Author(s):  
James Chatham
Keyword(s):  
Insurance Companies ◽  
Mortality Experience ◽  
The Subject ◽  
The Difference ◽  
First Time ◽  
Better Than

The distinguishing feature of the New Experience which differentiates it from all others, is the division of the observations into various classes of assurance; and when our President did me the honour of asking me to contribute a paper, I thought I could not do better than invite your attention to the premiums which, according to that experience, ought to be charged for these classes, as it is of the greatest importance to insurance companies generally that the risks which they undertake should be at adequate rates. Some of us have suspected, others have known, that the fate of mortality varied according to the class of assurance, and that one table of mortality applied to all was not satisfactory; but it is now possible for the first time to arrive at definite conclusions on the subject, and to determine in many cases what the difference between them really is.

scholarly journals FEATURE DESCRIPTOR BY CONVOLUTION AND POOLING AUTOENCODERS

2015 ◽  
Vol XL-3/W2 ◽  
pp. 31-38 ◽  
Author(s):  
L. Chen ◽  
F. Rottensteiner ◽  
C. Heipke
Keyword(s):  
Feature Descriptor ◽  
Data Set ◽  
Early Results ◽  
Image Patches ◽  
Key Points ◽  
Viewpoint Change ◽  
Feature Based ◽  
The Difference ◽  
The One ◽  
Better Than

In this paper we present several descriptors for feature-based matching based on autoencoders, and we evaluate the performance of these descriptors. In a training phase, we learn autoencoders from image patches extracted in local windows surrounding key points determined by the Difference of Gaussian extractor. In the matching phase, we construct key point descriptors based on the learned autoencoders, and we use these descriptors as the basis for local keypoint descriptor matching. Three types of descriptors based on autoencoders are presented. To evaluate the performance of these descriptors, recall and 1-precision curves are generated for different kinds of transformations, e.g. zoom and rotation, viewpoint change, using a standard benchmark data set. We compare the performance of these descriptors with the one achieved for SIFT. Early results presented in this paper show that, whereas SIFT in general performs better than the new descriptors, the descriptors based on autoencoders show some potential for feature based matching.

Difference Fourier Analysis of Glucose Embedded and Frozen Hydrated Purple Membrane

1982 ◽  
Vol 40 ◽  
pp. 74-75
Author(s):  
Jules S. Jaffe ◽  
Robert M. Glaeser
Keyword(s):  
Purple Membrane ◽  
Data Set ◽  
High Resolution Data ◽  
X Ray ◽  
X Ray Crystallography ◽  
Fourier Techniques ◽  
Versus Protein ◽  
The Difference ◽  
Difference Fourier ◽  
Ideal Method

Although difference Fourier techniques are standard in X-ray crystallography it has only been very recently that electron crystallographers have been able to take advantage of this method. We have combined a high resolution data set for frozen glucose embedded Purple Membrane (PM) with a data set collected from PM prepared in the frozen hydrated state in order to visualize any differences in structure due to the different methods of preparation. The increased contrast between protein-ice versus protein-glucose may prove to be an advantage of the frozen hydrated technique for visualizing those parts of bacteriorhodopsin that are embedded in glucose. In addition, surface groups of the protein may be disordered in glucose and ordered in the frozen state. The sensitivity of the difference Fourier technique to small changes in structure provides an ideal method for testing this hypothesis.

Removal of inelastically scattered electrons substantially increases phase contrast on frozen-hydrated molecules

1987 ◽  
Vol 45 ◽  
pp. 652-653
Author(s):  
John P. Langmore ◽  
Brian D. Athey
Keyword(s):  
Electron Diffraction ◽  
Phase Contrast ◽  
Low Dose ◽  
Dark Field ◽  
Biological Structure ◽  
Bright Field ◽  
Low Contrast ◽  
Negative Stain ◽  
The Difference ◽  
Better Than

Although electron diffraction indicates better than 0.3nm preservation of biological structure in vitreous ice, the imaging of molecules in ice is limited by low contrast. Thus, low-dose images of frozen-hydrated molecules have significantly more noise than images of air-dried or negatively-stained molecules. We have addressed the question of the origins of this loss of contrast. One unavoidable effect is the reduction in scattering contrast between a molecule and the background. In effect, the difference in scattering power between a molecule and its background is 2-5 times less in a layer of ice than in vacuum or negative stain. A second, previously unrecognized, effect is the large, incoherent background of inelastic scattering from the ice. This background reduces both scattering and phase contrast by an additional factor of about 3, as shown in this paper. We have used energy filtration on the Zeiss EM902 in order to eliminate this second effect, and also increase scattering contrast in bright-field and dark-field.

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