Using modern graph analysis techniques on mind maps to help quantify learning

2012 ◽  
Author(s):  
Peter Jamieson
Keyword(s):  
Graph Analysis ◽  
Analysis Techniques ◽  
Mind Maps

scholarly journals Graph Analysis for Detecting Fraud, Waste, and Abuse in Healthcare Data

AI Magazine ◽  
2016 ◽  
Vol 37 (2) ◽  
pp. 33-46 ◽  
Author(s):  
Juan Liu ◽  
Eric Bier ◽  
Aaron Wilson ◽  
John Alexis Guerra-Gomez ◽  
Tomonori Honda ◽  
...  
Keyword(s):  
Network Structure ◽  
Heterogeneous Network ◽  
Graph Analysis ◽  
Challenging Problem ◽  
Analysis Techniques ◽  
Healthcare Data ◽  
On Demand ◽  
Potential Value ◽  
Changes Over Time ◽  
Over Time

Detection of fraud, waste, and abuse (FWA) is an important yet challenging problem. In this article, we describe a system to detect suspicious activities in large healthcare datasets. Each healthcare dataset is viewed as a heterogeneous network consisting of millions of patients, hundreds of thousands of doctors, tens of thousands of pharmacies, and other entities. Graph analysis techniques are developed to find suspicious individuals, suspicious relationships between individuals, unusual changes over time, unusual geospatial dispersion, and anomalous network structure. The visualization interface, known as the Network Explorer, provides a good overview of data and enables users to filter, select, and zoom into network details on demand. The system has been deployed on multiple sites and datasets, both government and commercial, and identified many overpayments with a potential value of several million dollars per month.

scholarly journals Upaya Meningkatkan Keterampilan Membedakan Toilet Pria dan Toilet Wanita Melalui Media Kartu Gambar di SLB Amanah Bunda Sitapung Ampek Angkek

2020 ◽  
Vol 5 (1) ◽  
pp. 23-31
Author(s):  
Gina Hapsari ◽  
Kasiyati Kasiyati
Keyword(s):  
Research Method ◽  
Baseline Condition ◽  
Single Subject ◽  
Graph Analysis ◽  
Male And Female ◽  
Analysis Techniques ◽  
Single Subject Research ◽  
Intervention Condition ◽  
Condition B ◽  
Visual Graph

Penelitian ini bertujuan untuk meningkatkan keterampilan anak dalam membedakan toilet laki-laki dan toilet perempuan yang  dilakukan melalui media kartu gambar. Penelitian dilaksanakan selama 13 kali. Metode yang digunakan penelitian Single Subject Research (SSR) bentuk A-B-A. Kondisi baseline (A1) dilakukan empat kali. Kondisi intervensi (B) merupakan kondisi setelah diberikan perlakuan dilakukan sebanyak enam kali. Sedangkan kondisi baseline (A2) merupakan pemberhentian perlakuan dilakukan sebanyak tiga kali pengamatan. Analisis grafik visual sangat diperlukan salam teknik analisis data. Persentase overlap diperoleh pada kondisi A1-B yaitu 0% sedangkan persentase overlap yang diperoleh pada kondisi A2-B yaitu 50%. Berdasarkan hasil penelitian ini maka dalam meningkatkan keterampilan untuk membedakan toilet laki-laki dan toilet perempuan efektif menggunakan media kartu gambar. This study aims to improve children's skills in distinguishing male toilets and female toilets which are carried out through self-drawing cards. This research was conducted 13 times observation. This research method uses a Single Subject Research (SSR) type of study with A-B-A design. Baseline condition (A1) is the initial capability before it is given as many as four observations. The intervention condition (B) is a condition given after six examinations have been carried out. While the baseline condition (A2) is a dismissal carried out three times. Data analysis techniques using visual graph analysis. The percentage of overlap obtained at condition A1 / B is 0% while the percentage of overlap obtained at condition A2 / B is 50%. Based on the results of this study, the image card media is effective in improving the skills of calculating male and female toilets

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].

Dissociated Σ=27 boundaries in silicon

1988 ◽  
Vol 46 ◽  
pp. 624-625
Author(s):  
A. Garg ◽  
W.A.T. Clark ◽  
J.P. Hirth
Keyword(s):  
Electron Diffraction ◽  
Local Minimum ◽  
Boundary Energy ◽  
Coincidence Site Lattice ◽  
Boundary Plane ◽  
Low Energy ◽  
Theoretical Understanding ◽  
Site Lattice ◽  
Kikuchi Pattern ◽  
Analysis Techniques

In the last twenty years, a significant amount of work has been done in the theoretical understanding of grain boundaries. The various proposed grain boundary models suggest the existence of coincidence site lattice (CSL) boundaries at specific misorientations where a periodic structure representing a local minimum of energy exists between the two crystals. In general, the boundary energy depends not only upon the density of CSL sites but also upon the boundary plane, so that different facets of the same boundary have different energy. Here we describe TEM observations of the dissociation of a Σ=27 boundary in silicon in order to reduce its surface energy and attain a low energy configuration.The boundary was identified as near CSL Σ=27 {255} having a misorientation of (38.7±0.2)°/[011] by standard Kikuchi pattern, electron diffraction and trace analysis techniques. Although the boundary appeared planar, in the TEM it was found to be dissociated in some regions into a Σ=3 {111} and a Σ=9 {122} boundary, as shown in Fig. 1.

Material analysis techniques using the ion mill

1996 ◽  
Vol 54 ◽  
pp. 1034-1035
Author(s):  
J. P. Benedict ◽  
R. M. Anderson ◽  
S. J. Klepeis
Keyword(s):  
Polished Surface ◽  
Surface Material ◽  
Analysis Techniques ◽  
Material Analysis ◽  
Optical Inspection ◽  
Electron Microscopy Analysis ◽  
Microscopy Analysis ◽  
Argon Ions ◽  
The Impact ◽  
Scanning Electron

Ion mills equipped with flood guns can perform two important functions in material analysis; they can either remove material or deposit material. The ion mill holder shown in Fig. 1 is used to remove material from the polished surface of a sample for further optical inspection or SEM ( Scanning Electron Microscopy ) analysis. The sample is attached to a pohshing stud type SEM mount and placed in the ion mill holder with the polished surface of the sample pointing straight up, as shown in Fig 2. As the holder is rotating in the ion mill, Argon ions from the flood gun are directed down at the top of the sample. The impact of Argon ions against the surface of the sample causes some of the surface material to leave the sample at a material dependent, nonuniform rate. As a result, the polished surface will begin to develop topography during milling as fast sputtering materials leave behind depressions in the polished surface.

Developmental Sentence Scoring

1984 ◽  
Vol 15 (3) ◽  
pp. 154-168 ◽  
Author(s):  
Mary Ann Lively
Keyword(s):  
Expressive Language ◽  
Analysis Techniques ◽  
Language Analysis ◽  
Scoring Errors

Developmental Sentence Scoring (DSS) is a useful procedure for quantifying thegrammatic structure of children's expressive language. Like most language analysis techniques, however, DSS requires considerable study and practice to use it correctly and efficiently. Clinicians learning DSS tend to make many scoring errors at first and they display similar confusions and mistakes. This article identifies some of these common "problem" areas and provides scoring examples to assist clinicians in learning the DSS procedure.

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