A stellar ranging scheme based on the second-order correlation measurement

The stellar ranging is the basis for stellar dynamics research and in-depth research on astrophysics. Parallax method is the most widely used and important basic method for stellar ranging. However, it needs to perform high-precision measurement of the parallax angle and the baseline length together. We aim to propose a new stellar ranging scheme based on second-order correlation that does not require a parallax angle measurement. We hope our solution to be as basic as the parallax method. We propose a new stellar ranging scheme by using the offset of second-order correlation curve signals. The optical path difference between the stars and different base stations is determined by the offset of the second-order correlation curve signals. Then the distance of the stars could be determined by the geometric relation. With the distance to stars out to 10kpc away, our astrometric precision can be better compared to Gaia by simulation. We also design a experiment and successfully prove the feasibility of this scheme. This stellar ranging scheme makes it possible to make further and more accurate stellar ranging without using any prior information and angle measurement.

Concrete Mix Design Using Particle Packing Method: Literature Review, Analysis, and Computation

Particle packing technology is used to reduce the amount of cement in concrete by optimizing the concrete mix, resulting in more sustainable concrete. In this study, four different methods were used to determine the distribution of the mixture presented; packing density method, packing density method, IS code method, and packing density method. In the packing density method, the paste content that exceeds the voids will increase along with the increase in the quality of the concrete. In cases of packing density, the cement-water ratio decreases with the quality of the concrete. In the packing of too many trials, trials and tribulations should be carried out to achieve the ratio of water-cement and paste content for a certain grade of concrete. This correlation curve helps reduce the experiments involved in determining the ratio of semen and paste content for a given concrete quality. The water and cement contents for the packing density and the IS code method are almost the same for each particular concrete class. The workability of concrete achieved was more in the packing density method than the IS code method for the same concrete quality, because the water-cement ratio was slightly higher in the packing density method than the IS code method. The required fine aggregate particles are more in terms of packing density method compared to the IS code method. Therefore, more water and cement are required in terms of packing density. The correlation curve can be used to determine the ratio of water-cement and paste the content that exceeds the voids for a certain concrete quality

How does DEM error impact the optimal grid resolution of soil evolution simulation?

<p>The soil thickness is the key controlling factor of local hydrology and geomorphologic characteristics. The accuracy, reliability and coverage of soil thickness map are required for reliable application. Though with quite distinct structures, models for simulating soil thickness take modern topographic data (normally digital elevation model, DEM) as one of the most important inputs. Understanding the effect of grid resolution on soil thickness prediction and selecting an appropriate resolution is crucial for the macro-scale modeling. In this study, we further explored the relationship between topographic resolution and simulation accuracy of soil thickness, and propose a new method to determine the optimal simulation resolution. A series of abstract hillslopes with different terrain noise and terrain complexity were construct and different resolutions of DEM were generated. We used a simple geomorphic based model to calculate topographic index (slope, aspect and curvature) and soil thickness. The results show that the truncation error and noise of DEM will propagate during the simulation process. Furtherly, the correlation curve between DEM resolution and the simulation error of soil thickness is a hook curve. The shape of the curve is mainly controlled by two factors, terrain noise and terrain complexity. By fitting the correlation curve of all hillslopes, the curve can be predicted by them, and the resolution corresponding to the error minimum be found out, which can be called the optimal simulation resolution of the soil thickness prediction model.</p>

Sequential Extraction of Late Exponentials (SELE): A technique for deconvolving multimodal correlation curves in Dynamic Light Scattering

In techniques such as Dynamic Light Scattering (DLS), Fluorescence Correlation Spectroscopy, and image mining, motion is tracked by the autocorrelation of a signal over logarithmic time scales. For instance the tracking signal in DLS is the scattered light intensity; it remains correlated at time scales where scant changes in the arrangement of the scattering particles occur, but decays exponentially at the time scales of their diffusion. When there are multiple time scales of motion (for instance due to scatterers of different sizes), the correlation curve has more than one exponential fall. Extracting the decay constants or hydrodynamic sizes due to each exponential fall in a multi-species field correlation curve becomes an ill-conditioned mathematical problem. We describe a new algorithm to invert a multi-modal correlation curve by Sequential Extraction of the Late Exponentials (SELE). The idea is that while the inversion of a multi-exponential equation may be ill posed, that of a single exponential is not. So we fit data windows towards to base of the correlation curve to extract the largest contribution species, remove the species contribution from the correlation curve, and repeat the process with the remnant curve. The single exponent can be robustly fitted by least-square minimization with initial guesses generated by an adapted cumutant technique (power-series) that includes stretch coefficients (measure of sample dispersity). The proposed algorithm resolves particle sizes separated by 3X, and is reliable against fluctuations in the correlation curve and to localized regions of suboptimal data. The algorithm can be used to track particle dynamics in solution in multi-species problems such as self-assembly.

ANALISIS KETIMPANGAN PENDAPATAN DAN POLA PERTUMBUHAN EKONOMI DI WILAYAH BELAJASUMBA TAHUN 2013-2017

This research attempts to understand income disparity and to identify the pattern of economic growth in Belanjasumba region at 2013-2017 years. The tools of analysis are Williamson Index, Klassen Typology and correlation curve among of economic growth and Williamson Index. Base on Williamson index found that income disparity in Belajasumba region low relative and tended to decreasing. Klassen typology analysis shows that Belajasumba region can be classified into three types: high growth and high income is Jambi, high income but low growth is South Sumatera and Bangka Belitung and high growth but low income is Bengkulu and Lampung. More importantly, findings confirmed that Kuznets hypothesis not could be found in Belajasumba.

The extended variant of the bond valence–bond length correlation curve for boron(III)–oxygen bonds

The extended variant of the bond valence (