Spatial Variation in Temperature and Density in the IC 63 PDR from H2 Spectroscopy

We have measured the gas temperature in the IC 63 photodissociation region (PDR) using the S(1) and S(5) pure rotation lines of molecular hydrogen with SOFIA/EXES. We divide the PDR into three regions for analysis based on the illumination from γ Cas: sunny, ridge, and shady. Constructing rotation diagrams for the different regions, we obtain temperatures of T ex = 562 − 43 + 52 K toward the ridge and T ex = 495 − 25 + 28 K in the shady side. The H2 emission was not detected on the sunny side of the ridge, likely due to the photodissociation of H2 in this gas. Our temperature values are lower than the value of T ex = 685 ± 68 K using the S(1), S(3), and S(5) pure rotation lines, derived by Thi et al. using lower spatial resolution ISO-SWS data at a different location of the IC 63 PDR. This difference indicates that the PDR is inhomogeneous and illustrates the need for high-resolution mapping of such regions to fully understand their physics. The detection of a temperature gradient correlated with the extinction into the cloud, points to the ability of using H2 pure rotational line spectroscopy to map the gas temperature on small scales. We used a PDR model to estimate the FUV radiation and corresponding gas densities in IC 63. Our results shows the capability of SOFIA/EXES to resolve and provide detailed information on the temperature in such regions.

ПОРІВНЯЛЬНИЙ АНАЛІЗ МЕТОДІВ ПОШУКУ НАЙБЛИЖЧИХ ТОЧОК НА ЗОБРАЖЕННЯХ ОБ’ЄКТІВ ТЕХНІЧНИХ СИСТЕМ

The subject of the study is the process of mapping the construction of point clouds of technical systems using the algorithm of the nearest points. The goal is to minimize the alignment criterion by converting a set of cloud points Y into a set of cloud points X in a software product that uses an iterative closest point (ICP) algorithm. Objectives: to analyze the properties of input images that contain point clouds; to review the algorithms for identifying and comparing key points; implement a cloud comparison algorithm using the ISR algorithm; consider an example of the algorithm for estimating the approximate values of the elements of mutual orientation; implement software that allows you to compare files that contain point clouds and draw conclusions about the possibility of comparing them. The methods used are: search for points using the algorithm of iterative nearest points, the algorithm for estimating the approximate values of the elements of mutual orientation, the method of algorithm theory for the analysis of file structures STL (standard template library - format template library) format. The following results were obtained. The choice of the ICP algorithm for the task of reconstruction of the object of technical systems is substantiated; the main features of the ISR algorithm are considered; the algorithm of comparison of key points, and also optimization that allows reducing criterion of combination at the reconstruction of three-dimensional objects of technical systems results. Conclusions. The study found that the iterative near-point algorithm is more detailed and accurate when modeling objects. At the same time, this method requires very accurate values and when calculating the degree of proximity, the complexity of calculation by this algorithm increases many times. Whereas the algorithm for estimating the approximate values of the elements of mutual orientation does not require information about the approximate orientation of the point clouds, which simplifies the work and reduces the simulation time. It was found that not all files are comparable. Therefore, the software is implemented, which gives an opinion on the possibility of comparing points in the proposed two files, which contain clouds of points in the structure of the STL format.

Enhanced Cloud Method (E-Cloud) for Efficient Seismic Fragility Assessment of Structures

Cloud analysis is based on linear regression in the logarithmic space by using least squares, in which a large number of nonlinear dynamic analyses are usually suggested to ensure the accuracy of this method. So, it needs significant computational effort to establish fragility curves especially for the complicated structures. The present paper proposed the Enhanced Cloud Method (E-Cloud) to enhance the efficiency but maintain the accuracy of the Cloud method. The basic concept of the proposed “E-Cloud” aims to utilize both maximum and additional seismic responses with corresponding intensity measures (IMs) from ground motions for the logarithmic linear regression of the Cloud method. Since the nonlinear time-history responses can be transferred to the Engineering Demand Parameter (EDP)-IM curve at the duration when the ground motion is intensifying, the additional seismic responses at different IM levels (i.e., potential Cloud points) can be selected from this EDP-IM curve. These potential Cloud points are combined with maximum seismic responses for the regression so as to reduce the required number of dynamic analyses in Cloud analysis. The proposed “E-Cloud” method is applied for the case study of a typical RC frame structure. By comparison of the obtained probabilistic seismic demand models and fragility curves from “E-Cloud” method to Cloud analysis, it is demonstrated that the E-Cloud method can significantly improve the computational efficiency of the Cloud analysis, which also leads to accurate and stable results for the seismic fragility assessment of structures.

Interactive Exploration of Large-Scale UI Datasets with Design Maps

Designers are increasingly using online resources for inspiration. How to best support design exploration without compromising creativity? We introduce and study Design Maps, a class of point-cloud visualizations that makes large user interface datasets explorable. Design Maps are computed using dimensionality reduction and clustering techniques, which we analyze thoroughly in this paper. We present concepts for integrating Design Maps into design tools, including interactive visualization, local neighborhood exploration and functionality to integrate existing solutions to the design at hand. These concepts were implemented in a wireframing tool for mobile apps, which was evaluated with actual designers performing realistic tasks. Overall, designers find Design Maps supporting their creativity (avg. CSI score of 74/100) and indicate that the maps producing consistent whitespacing within cloud points are the most informative ones.

Hydration/Dehydration Behavior of Hydroxyethyl Cellulose Ether in Aqueous Solution

Hydroxyethyl cellulose (HeC) maintains high water solubility over a wide temperature range even in a high temperature region where other nonionic chemically modified cellulose ethers, such as methyl cellulose (MC) and hydroxypropylmethyl cellulose (HpMC), demonstrate cloud points. In order to clarify the reason for the high solubility of HeC, the temperature dependence of the hydration number per glucopyranose unit, nH, for the HeC samples was examined by using extremely high frequency dielectric spectrum measuring techniques up to 50 GHz over a temperature range from 10 to 70 °C. HeC samples with a molar substitution number (MS) per glucopyranose unit by hydroxyethyl groups ranging from 1.3 to 3.6 were examined in this study. All HeC samples dissolve into water over the examined temperature range and did not show their cloud points. The value of nH for the HeC sample possessing the MS of 1.3 was 14 at 20 °C and decreased gently with increasing temperature and declined to 10 at 70 °C. The nH values of the HeC samples are substantially larger than the minimum critical nH value of ca. 5 necessary to be dissolved into water for cellulose ethers such as MC and HpMC, even in a high temperature range. Then, the HeC molecules possess water solubility over the wide temperature range. The temperature dependence of nH for the HeC samples and triethyleneglycol, which is a model compound for substitution groups of HeC, is gentle and they are similar to each other. This observation strongly suggests that the hydration/dehydration behavior of the HeC samples was essentially controlled by that of their substitution groups.

Identification of Roof Surfaces from LiDAR Cloud Points by GIS Tools: A Case Study of Lučenec, Slovakia

The identification of roof surfaces is characterized by a sequence of several processing steps. The boundary detection of different types of roof is realized from light detection and ranging (LiDAR) cloud points and can confirm the real boundary of the roof. In the process of processing LiDAR data, shortcomings have been found regarding the inappropriate classification of points (class 6 “buildings”) concerning the roofs (the points of the building facade were marked as outliers and reclassified). In cases of insufficient point density, there is a problem with not being able to capture either the roof boundary or small roof objects, along with the possible occurrence of gaps inside the roof areas. This study proposes a processing procedure in a geographic information system (GIS) environment that advocates the identification of roof surfaces based on the LiDAR point cloud. We created the contours of a roof surface boundary with a simplified regular shape. From 824 roofs in the studied area, six different types of roof were selected, which this study presents in detail. The expected result of the study is the generation of segments inside the roof boundary. The study also includes the visualization of the outcomes of the spatial analyses of the identified roof surfaces, which forms the basis for determining the potential of solar systems with respect to green roofs for the development of smart city buildings.