scholarly journals VISITORS’ PERCEPTION: THE LANDMARKS OF BANTEN LAMA

2019 ◽  
Vol 3 (2) ◽  
pp. 104
Author(s):  
Sangiru Sangiru ◽  
Maria Immaculata Ririk Winandari ◽  
Etty Retnowati Kridarso
Keyword(s):  
Quantitative Analysis ◽  
Title Page ◽  
Multilevel Selection ◽  
Historical Buildings ◽  
Visual Research ◽  
Intangible Factor

<div class="page" title="Page 1"><div class="section"><div class="layoutArea"><div class="column"><p><span>Banten Lama District, the centre of Banten Sultanate, has several preserved historical buildings and sites. </span><span>One of the historical buildings is Masjid Agung that is considered as Banten Lama Landmark refering to its nickname ‘santri city’. This visual research aimed to identify Banten of 40 visitors of Banten Cultural Festival that randomly chosen. Quantitative analysis using the Osgood scale was used to obtain the landmark priority. The result shows that according to visitor’s perception, Masjid Agung, Avalokitesvara Temple, and Surosowan Palace are the most suitable to be Banten Lama landmarks. </span><span>The main reason for choosing these </span><span>buildings and site </span><span>as Banten Lama Landmarks is its intangible factor of pilgrimage place. </span><span>Landmark through the visitors’ perception by using 14 historical buildings and site as the objects studied. Multilevel selection was applied to select buildings and sites that </span><span>could be perceived as Banten Landmark. R</span><span>espondents consist </span></p><p><span>Keywords: Visitors’ Perception, Landmarks, Banten Lama </span></p></div></div></div></div>

scholarly journals Evaluating kin and group selection as tools for quantitative analysis of microbial data

2021 ◽  
Vol 288 (1951) ◽  
pp. 20201657
Author(s):  
Jeff Smith ◽  
R. Fredrik Inglis
Keyword(s):  
Quantitative Analysis ◽  
Social Evolution ◽  
Multilevel Selection ◽  
Data Driven ◽  
Evolution Of Cooperation ◽  
Selection Theory ◽  
Data Driven Approach ◽  
Quantitative Understanding ◽  
Multilevel Selection Theory ◽  
Microbial Systems

Kin selection and multilevel selection theory are often used to interpret experiments about the evolution of cooperation and social behaviour among microbes. But while these experiments provide rich, detailed fitness data, theory is mostly used as a conceptual heuristic. Here, we evaluate how kin and multilevel selection theory perform as quantitative analysis tools. We reanalyse published microbial datasets and show that the canonical fitness models of both theories are almost always poor fits because they use statistical regressions misspecified for the strong selection and non-additive effects we show are widespread in microbial systems. We identify analytical practices in empirical research that suggest how theory might be improved, and show that analysing both individual and group fitness outcomes helps clarify the biology of selection. A data-driven approach to theory thus shows how kin and multilevel selection both have untapped potential as tools for quantitative understanding of social evolution in all branches of life.

An Improved Quantitative Image Analyser

1977 ◽  
Vol 35 ◽  
pp. 226-227
Author(s):  
J.P. Fallon ◽  
P.J. Gregory ◽  
C.J. Taylor
Keyword(s):  
Feature Extraction ◽  
Quantitative Analysis ◽  
Frequency Content ◽  
General Sense ◽  
Physical Measurements ◽  
Quantitative Image ◽  
Image Analyser ◽  
Automatic Methods ◽  
Quantitative Results

Quantitative image analysis systems have been used for several years in research and quality control applications in various fields including metallurgy and medicine. The technique has been applied as an extension of subjective microscopy to problems requiring quantitative results and which are amenable to automatic methods of interpretation.Feature extraction. In the most general sense, a feature can be defined as a portion of the image which differs in some consistent way from the background. A feature may be characterized by the density difference between itself and the background, by an edge gradient, or by the spatial frequency content (texture) within its boundaries. The task of feature extraction includes recognition of features and encoding of the associated information for quantitative analysis.Quantitative Analysis. Quantitative analysis is the determination of one or more physical measurements of each feature. These measurements may be straightforward ones such as area, length, or perimeter, or more complex stereological measurements such as convex perimeter or Feret's diameter.

Quantification of Silica Uptake by Alveolar Macrophages - An Emperical Scanning Electron Microprobe Method

1982 ◽  
Vol 40 ◽  
pp. 332-333
Author(s):  
V. V. Damiano ◽  
R. P. Daniele ◽  
H. T. Tucker ◽  
J. H. Dauber
Keyword(s):  
Quantitative Analysis ◽  
Alveolar Macrophages ◽  
Bulk Sample ◽  
Silica Particles ◽  
Empirical Method ◽  
Phagocytic Cells ◽  
Calibration Standards ◽  
X Ray ◽  
Accurate Quantitative Analysis ◽  
Scanning Electron

An important example of intracellular particles is encountered in silicosis where alveolar macrophages ingest inspired silica particles. The quantitation of the silica uptake by these cells may be a potentially useful method for monitoring silica exposure. Accurate quantitative analysis of ingested silica by phagocytic cells is difficult because the particles are frequently small, irregularly shaped and cannot be visualized within the cells. Semiquantitative methods which make use of particles of known size, shape and composition as calibration standards may be the most direct and simplest approach to undertake. The present paper describes an empirical method in which glass microspheres were used as a model to show how the ratio of the silicon Kα peak X-ray intensity from the microspheres to that of a bulk sample of the same composition correlated to the mass of the microsphere contained within the cell. Irregular shaped silica particles were also analyzed and a calibration curve was generated from these data.

Lateral resolution of the electron microbeam analysis

1978 ◽  
Vol 36 (1) ◽  
pp. 542-543
Author(s):  
H.J. Dudek
Keyword(s):  
Quantitative Analysis ◽  
Depth Resolution ◽  
Lateral Resolution ◽  
Cylindrical Particle ◽  
Correction Procedure ◽  
X Ray ◽  
Element Concentrations ◽  
Microbeam Analysis ◽  
The Matrix

The chemical inhomogenities in modern materials such as fibers, phases and inclusions, often have diameters in the region of one micrometer. Using electron microbeam analysis for the determination of the element concentrations one has to know the smallest possible diameter of such regions for a given accuracy of the quantitative analysis.In th is paper the correction procedure for the quantitative electron microbeam analysis is extended to a spacial problem to determine the smallest possible measurements of a cylindrical particle P of high D (depth resolution) and diameter L (lateral resolution) embeded in a matrix M and which has to be analysed quantitative with the accuracy q. The mathematical accounts lead to the following form of the characteristic x-ray intens ity of the element i of a particle P embeded in the matrix M in relation to the intensity of a standard S

An example of spectrum imaging used for comparison of EELS quantitative analysis techniques on Al-Li

1991 ◽  
Vol 49 ◽  
pp. 726-727
Author(s):  
John A. Hunt
Keyword(s):  
Quantitative Analysis ◽  
Large Data ◽  
Difference Spectrum ◽  
Large Data Sets ◽  
Foil Thickness ◽  
Data Sets ◽  
Analysis Techniques ◽  
Spectrum Imaging ◽  
Normal Spectrum ◽  
Electron Energy Loss

Spectrum-imaging is a useful technique for comparing different processing methods on very large data sets which are identical for each method. This paper is concerned with comparing methods of electron energy-loss spectroscopy (EELS) quantitative analysis on the Al-Li system. The spectrum-image analyzed here was obtained from an Al-10at%Li foil aged to produce δ' precipitates that can span the foil thickness. Two 1024 channel EELS spectra offset in energy by 1 eV were recorded and stored at each pixel in the 80x80 spectrum-image (25 Mbytes). An energy range of 39-89eV (20 channels/eV) are represented. During processing the spectra are either subtracted to create an artifact corrected difference spectrum, or the energy offset is numerically removed and the spectra are added to create a normal spectrum. The spectrum-images are processed into 2D floating-point images using methods and software described in [1].

The use of a Bent Grid to Improve the take-Off Angle for Electron Probe Analysis

1976 ◽  
Vol 34 ◽  
pp. 360-361
Author(s):  
Delbert E. Philpott ◽  
David Leaffer
Keyword(s):  
Quantitative Analysis ◽  
Tilt Angle ◽  
Count Rate ◽  
Electron Probe ◽  
Open Area ◽  
Electron Probe Analysis ◽  
Background Ratio ◽  
Probe Analysis

There are certain advantages for electron probe analysis if the sample can be tilted directly towards the detector. The count rate is higher, it optimizes the geometry since only one angle need be taken into account for quantitative analysis and the signal to background ratio is improved. The need for less tilt angle may be an advantage because the grid bars are not moved quite as close to each other, leaving a little more open area for observation. Our present detector (EDAX) and microscope (Philips 300) combination precludes moving the detector behind the microscope where it would point directly at the grid. Therefore, the angle of the specimen was changed in order to optimize the geometry between the specimen and the detector.

Solving the mechanisms responsible for organelle behavior in vivo by same-cell correlative light and electron microscopy

1992 ◽  
Vol 50 (1) ◽  
pp. 14-15
Author(s):  
Conly L. Rieder
Keyword(s):  
Electron Microscopy ◽  
Quantitative Analysis ◽  
Light Microscopy ◽  
Living Cell ◽  
Light And Electron Microscopy ◽  
Time Behavior ◽  
Dynamic Interactions ◽  
Positive Identification ◽  
Cellular Components

The behavior of many cellular components, and their dynamic interactions, can be characterized in the living cell with considerable spatial and temporal resolution by video-enhanced light microscopy (video-LM). Indeed, under the appropriate conditions video-LM can be used to determine the real-time behavior of organelles ≤ 25-nm in diameter (e.g., individual microtubules—see). However, when pushed to its limit the structures and components observed within the cell by video-LM cannot be resolved nor necessarily even identified, only detected. Positive identification and a quantitative analysis often requires the corresponding electron microcopy (EM).

Bence-albee after 25 years: A new superior α-factor correction procedure for the quantitative analysis of oxides and silicates

1992 ◽  
Vol 50 (2) ◽  
pp. 1744-1745
Author(s):  
John T. Armstrong
Keyword(s):  
Quantitative Analysis ◽  
Electron Microprobe ◽  
Binary Systems ◽  
Correction Procedure ◽  
Geological Samples ◽  
The Past ◽  
Large Matrix ◽  
Computational Speed ◽  
Microprobe Data ◽  
Geological Sciences

One of the most cited papers in the geological sciences has been that of Albee and Bence on the use of empirical " α -factors" to correct quantitative electron microprobe data. During the past 25 years this method has remained the most commonly used correction for geological samples, despite the facts that few investigators have actually determined empirical α-factors, but instead employ tables of calculated α-factors using one of the conventional "ZAF" correction programs; a number of investigators have shown that the assumption that an α-factor is constant in binary systems where there are large matrix corrections is incorrect (e.g, 2-3); and the procedure’s desirability in terms of program size and computational speed is much less important today because of developments in computing capabilities. The question thus exists whether it is time to honorably retire the Bence-Albee procedure and turn to more modern, robust correction methods. This paper proposes that, although it is perhaps time to retire the original Bence-Albee procedure, it should be replaced by a similar method based on compositiondependent polynomial α-factor expressions.

Quantitative Analysis Of X-Ray Images From Geological Materials

1990 ◽  
Vol 48 (2) ◽  
pp. 244-245
Author(s):  
J. M. Paque ◽  
R. Browning ◽  
P. L. King ◽  
P. Pianetta
Keyword(s):  
Quantitative Analysis ◽  
Bulk Composition ◽  
Principal Component ◽  
Analytical Description ◽  
Bulk Sample ◽  
Geological Samples ◽  
X Ray ◽  
Software And Hardware ◽  
And Storage ◽  
Insight Into

Geological samples typically contain many minerals (phases) with multiple element compositions. A complete analytical description should give the number of phases present, the volume occupied by each phase in the bulk sample, the average and range of composition of each phase, and the bulk composition of the sample. A practical approach to providing such a complete description is from quantitative analysis of multi-elemental x-ray images.With the advances in recent years in the speed and storage capabilities of laboratory computers, large quantities of data can be efficiently manipulated. Commercial software and hardware presently available allow simultaneous collection of multiple x-ray images from a sample (up to 16 for the Kevex Delta system). Thus, high resolution x-ray images of the majority of the detectable elements in a sample can be collected. The use of statistical techniques, including principal component analysis (PCA), can provide insight into mineral phase composition and the distribution of minerals within a sample.

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