An extended k-means technique for clustering moving objects

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Omnia Ossama

2011-03-01

Full Text Available k-means algorithm is one of the basic clustering techniques that is used in many data mining applications. In this paper we present a novel pattern based clustering algorithm that extends the k-means algorithm for clustering moving object trajectory data. The proposed algorithm uses a key feature of moving object trajectories namely, its direction as a heuristic to determine the different number of clusters for the k-means algorithm. In addition, we use the silhouette coefficient as a measure for the quality of our proposed approach. Finally, we present experimental results on both real and synthetic data that show the performance and accuracy of our proposed technique.

Space density and clustering properties of a new sample of emission-line galaxies

International Nuclear Information System (INIS)

Wasilewski, A.J.

1982-01-01

A moderate-dispersion objective-prism survey for low-redshift emission-line galaxies has been carried out in an 825 sq. deg. region of sky with the Burrell Schmidt telescope of Case Western Reserve University. A 4 0 prism (300 A/mm at H#betta#) was used with the Illa-J emulsion to show that a new sample of emission-line galaxies is available even in areas already searched with the excess uv-continuum technique. The new emission-line galaxies occur quite commonly in systems with peculiar morphology indicating gravitational interaction with a close companion or other disturbance. About 10 to 15% of the sample are Seyfert galaxies. It is suggested that tidal interaction involving matter infall play a significant role in the generation of an emission-line spectrum. The space density of the new galaxies is found to be similar to the space density of the Makarian galaxies. Like the Markarian sample, the galaxies in the present survey represent about 10% of all galaxies in the absolute magnitude range M/sub p/ = -16 to -22. The observations also indicate that current estimates of dwarf galaxy space densities may be too low. The clustering properties of the new galaxies have been investigated using two approaches: cluster contour maps and the spatial correlation function. These tests suggest that there is weak clustering and possibly superclustering within the sample itself and that the galaxies considered here are about as common in clusters of ordinary galaxies as in the field

Software refactoring at the package level using clustering techniques

KAUST Repository

Alkhalid, A.

2011-01-01

Enhancing, modifying or adapting the software to new requirements increases the internal software complexity. Software with high level of internal complexity is difficult to maintain. Software refactoring reduces software complexity and hence decreases the maintenance effort. However, software refactoring becomes quite challenging task as the software evolves. The authors use clustering as a pattern recognition technique to assist in software refactoring activities at the package level. The approach presents a computer aided support for identifying ill-structured packages and provides suggestions for software designer to balance between intra-package cohesion and inter-package coupling. A comparative study is conducted applying three different clustering techniques on different software systems. In addition, the application of refactoring at the package level using an adaptive k-nearest neighbour (A-KNN) algorithm is introduced. The authors compared A-KNN technique with the other clustering techniques (viz. single linkage algorithm, complete linkage algorithm and weighted pair-group method using arithmetic averages). The new technique shows competitive performance with lower computational complexity. © 2011 The Institution of Engineering and Technology.

A survey of text clustering techniques used for web mining

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Dan MUNTEANU

2005-12-01

Full Text Available This paper contains an overview of basic formulations and approaches to clustering. Then it presents two important clustering paradigms: a bottom-up agglomerative technique, which collects similar documents into larger and larger groups, and a top-down partitioning technique, which divides a corpus into topic-oriented partitions.

A fuzzy clustering technique for calorimetric data reconstruction

International Nuclear Information System (INIS)

Sandhir, Radha Pyari; Muhuri, Sanjib; Nayak, Tapan K.

2010-01-01

In high energy physics experiments, electromagnetic calorimeters are used to measure shower particles produced in p-p or heavy-ion collisions. In order to extract information and reconstruct the characteristics of the various incoming particles, clustering is required to be performed on each of the calorimeter planes. Hard clustering techniques such as Local Maxima Search, Connected-cell Search and K-means Clustering simply assign a data point to a cluster. A data point either lies in a cluster or it does not, and so, overlapping clusters are hardly distinguishable. Fuzzy c-means clustering is a version of the k-means algorithm that incorporates fuzzy logic, so that each point has a weak or strong association to the cluster, determined by the inverse distance to the center of the cluster. The term fuzzy is used because an observation may in fact lie in more than one cluster simultaneously, though to different degrees called 'memberships', as is the case with many high energy physics applications. The centers obtained using the FCM algorithm are based on the geometric locations of the data points

Microgrids Real-Time Pricing Based on Clustering Techniques

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Hao Liu

2018-05-01

Full Text Available Microgrids are widely spreading in electricity markets worldwide. Besides the security and reliability concerns for these microgrids, their operators need to address consumers’ pricing. Considering the growth of smart grids and smart meter facilities, it is expected that microgrids will have some level of flexibility to determine real-time pricing for at least some consumers. As such, the key challenge is finding an optimal pricing model for consumers. This paper, accordingly, proposes a new pricing scheme in which microgrids are able to deploy clustering techniques in order to understand their consumers’ load profiles and then assign real-time prices based on their load profile patterns. An improved weighted fuzzy average k-means is proposed to cluster load curve of consumers in an optimal number of clusters, through which the load profile of each cluster is determined. Having obtained the load profile of each cluster, real-time prices are given to each cluster, which is the best price given to all consumers in that cluster.

Extending cluster lot quality assurance sampling designs for surveillance programs.

Science.gov (United States)

Hund, Lauren; Pagano, Marcello

2014-07-20

Lot quality assurance sampling (LQAS) has a long history of applications in industrial quality control. LQAS is frequently used for rapid surveillance in global health settings, with areas classified as poor or acceptable performance on the basis of the binary classification of an indicator. Historically, LQAS surveys have relied on simple random samples from the population; however, implementing two-stage cluster designs for surveillance sampling is often more cost-effective than simple random sampling. By applying survey sampling results to the binary classification procedure, we develop a simple and flexible nonparametric procedure to incorporate clustering effects into the LQAS sample design to appropriately inflate the sample size, accommodating finite numbers of clusters in the population when relevant. We use this framework to then discuss principled selection of survey design parameters in longitudinal surveillance programs. We apply this framework to design surveys to detect rises in malnutrition prevalence in nutrition surveillance programs in Kenya and South Sudan, accounting for clustering within villages. By combining historical information with data from previous surveys, we design surveys to detect spikes in the childhood malnutrition rate. Copyright © 2014 John Wiley & Sons, Ltd.

Marine data users clustering using data mining technique

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Farnaz Ghiasi

2015-09-01

Full Text Available The objective of this research is marine data users clustering using data mining technique. To achieve this objective, marine organizations will enable to know their data and users requirements. In this research, CRISP-DM standard model was used to implement the data mining technique. The required data was extracted from 500 marine data users profile database of Iranian National Institute for Oceanography and Atmospheric Sciences (INIOAS from 1386 to 1393. The TwoStep algorithm was used for clustering. In this research, patterns was discovered between marine data users such as student, organization and scientist and their data request (Data source, Data type, Data set, Parameter and Geographic area using clustering for the first time. The most important clusters are: Student with International data source, Chemistry data type, “World Ocean Database” dataset, Persian Gulf geographic area and Organization with Nitrate parameter. Senior managers of the marine organizations will enable to make correct decisions concerning their existing data. They will direct to planning for better data collection in the future. Also data users will guide with respect to their requests. Finally, the valuable suggestions were offered to improve the performance of marine organizations.

Edge Principal Components and Squash Clustering: Using the Special Structure of Phylogenetic Placement Data for Sample Comparison

Science.gov (United States)

Matsen IV, Frederick A.; Evans, Steven N.

2013-01-01

Principal components analysis (PCA) and hierarchical clustering are two of the most heavily used techniques for analyzing the differences between nucleic acid sequence samples taken from a given environment. They have led to many insights regarding the structure of microbial communities. We have developed two new complementary methods that leverage how this microbial community data sits on a phylogenetic tree. Edge principal components analysis enables the detection of important differences between samples that contain closely related taxa. Each principal component axis is a collection of signed weights on the edges of the phylogenetic tree, and these weights are easily visualized by a suitable thickening and coloring of the edges. Squash clustering outputs a (rooted) clustering tree in which each internal node corresponds to an appropriate “average” of the original samples at the leaves below the node. Moreover, the length of an edge is a suitably defined distance between the averaged samples associated with the two incident nodes, rather than the less interpretable average of distances produced by UPGMA, the most widely used hierarchical clustering method in this context. We present these methods and illustrate their use with data from the human microbiome. PMID:23505415

Occurrence of Radio Minihalos in a Mass-limited Sample of Galaxy Clusters

Energy Technology Data Exchange (ETDEWEB)

Giacintucci, Simona; Clarke, Tracy E. [Naval Research Laboratory, 4555 Overlook Avenue SW, Code 7213, Washington, DC 20375 (United States); Markevitch, Maxim [NASA/Goddard Space Flight Center, Greenbelt, MD 20771 (United States); Cassano, Rossella; Venturi, Tiziana; Brunetti, Gianfranco, E-mail: simona.giacintucci@nrl.navy.mil [INAF—Istituto di Radioastronomia, via Gobetti 101, I-40129 Bologna (Italy)

2017-06-01

We investigate the occurrence of radio minihalos—diffuse radio sources of unknown origin observed in the cores of some galaxy clusters—in a statistical sample of 58 clusters drawn from the Planck Sunyaev–Zel’dovich cluster catalog using a mass cut ( M {sub 500} > 6 × 10{sup 14} M {sub ⊙}). We supplement our statistical sample with a similarly sized nonstatistical sample mostly consisting of clusters in the ACCEPT X-ray catalog with suitable X-ray and radio data, which includes lower-mass clusters. Where necessary (for nine clusters), we reanalyzed the Very Large Array archival radio data to determine whether a minihalo is present. Our total sample includes all 28 currently known and recently discovered radio minihalos, including six candidates. We classify clusters as cool-core or non-cool-core according to the value of the specific entropy floor in the cluster center, rederived or newly derived from the Chandra X-ray density and temperature profiles where necessary (for 27 clusters). Contrary to the common wisdom that minihalos are rare, we find that almost all cool cores—at least 12 out of 15 (80%)—in our complete sample of massive clusters exhibit minihalos. The supplementary sample shows that the occurrence of minihalos may be lower in lower-mass cool-core clusters. No minihalos are found in non-cool cores or “warm cores.” These findings will help test theories of the origin of minihalos and provide information on the physical processes and energetics of the cluster cores.

The k-means clustering technique: General considerations and implementation in Mathematica

Directory of Open Access Journals (Sweden)

Laurence Morissette

2013-02-01

Full Text Available Data clustering techniques are valuable tools for researchers working with large databases of multivariate data. In this tutorial, we present a simple yet powerful one: the k-means clustering technique, through three different algorithms: the Forgy/Lloyd, algorithm, the MacQueen algorithm and the Hartigan and Wong algorithm. We then present an implementation in Mathematica and various examples of the different options available to illustrate the application of the technique.

Unsupervised color image segmentation using a lattice algebra clustering technique

Science.gov (United States)

Urcid, Gonzalo; Ritter, Gerhard X.

2011-08-01

In this paper we introduce a lattice algebra clustering technique for segmenting digital images in the Red-Green- Blue (RGB) color space. The proposed technique is a two step procedure. Given an input color image, the first step determines the finite set of its extreme pixel vectors within the color cube by means of the scaled min-W and max-M lattice auto-associative memory matrices, including the minimum and maximum vector bounds. In the second step, maximal rectangular boxes enclosing each extreme color pixel are found using the Chebychev distance between color pixels; afterwards, clustering is performed by assigning each image pixel to its corresponding maximal box. The two steps in our proposed method are completely unsupervised or autonomous. Illustrative examples are provided to demonstrate the color segmentation results including a brief numerical comparison with two other non-maximal variations of the same clustering technique.

CA II TRIPLET SPECTROSCOPY OF SMALL MAGELLANIC CLOUD RED GIANTS. III. ABUNDANCES AND VELOCITIES FOR A SAMPLE OF 14 CLUSTERS

Energy Technology Data Exchange (ETDEWEB)

Parisi, M. C.; Clariá, J. J.; Marcionni, N. [Observatorio Astronómico, Universidad Nacional de Córdoba, Laprida 854, Córdoba, CP 5000 (Argentina); Geisler, D.; Villanova, S. [Departamento de Astronomía, Universidad de Concepción Casilla 160-C, Concepción (Chile); Sarajedini, A. [Department of Astronomy, University of Florida P.O. Box 112055, Gainesville, FL 32611 (United States); Grocholski, A. J., E-mail: celeste@oac.uncor.edu, E-mail: claria@oac.uncor.edu, E-mail: nmarcionni@oac.uncor.edu, E-mail: dgeisler@astro-udec.cl, E-mail: svillanova@astro-udec.cl, E-mail: ata@astro.ufl.edu, E-mail: grocholski@phys.lsu.edu [Department of Physics and Astronomy, Louisiana State University 202 Nicholson Hall, Tower Drive, Baton Rouge, LA 70803-4001 (United States)

2015-05-15

We obtained spectra of red giants in 15 Small Magellanic Cloud (SMC) clusters in the region of the Ca ii lines with FORS2 on the Very Large Telescope. We determined the mean metallicity and radial velocity with mean errors of 0.05 dex and 2.6 km s{sup −1}, respectively, from a mean of 6.5 members per cluster. One cluster (B113) was too young for a reliable metallicity determination and was excluded from the sample. We combined the sample studied here with 15 clusters previously studied by us using the same technique, and with 7 clusters whose metallicities determined by other authors are on a scale similar to ours. This compilation of 36 clusters is the largest SMC cluster sample currently available with accurate and homogeneously determined metallicities. We found a high probability that the metallicity distribution is bimodal, with potential peaks at −1.1 and −0.8 dex. Our data show no strong evidence of a metallicity gradient in the SMC clusters, somewhat at odds with recent evidence from Ca ii triplet spectra of a large sample of field stars. This may be revealing possible differences in the chemical history of clusters and field stars. Our clusters show a significant dispersion of metallicities, whatever age is considered, which could be reflecting the lack of a unique age–metallicity relation in this galaxy. None of the chemical evolution models currently available in the literature satisfactorily represents the global chemical enrichment processes of SMC clusters.

Profiling Local Optima in K-Means Clustering: Developing a Diagnostic Technique

Science.gov (United States)

Steinley, Douglas

2006-01-01

Using the cluster generation procedure proposed by D. Steinley and R. Henson (2005), the author investigated the performance of K-means clustering under the following scenarios: (a) different probabilities of cluster overlap; (b) different types of cluster overlap; (c) varying samples sizes, clusters, and dimensions; (d) different multivariate…

Event Streams Clustering Using Machine Learning Techniques

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Hanen Bouali

2015-10-01

Full Text Available Data streams are usually of unbounded lengths which push users to consider only recent observations by focusing on a time window, and ignore past data. However, in many real world applications, past data must be taken in consideration to guarantee the efficiency, the performance of decision making and to handle data streams evolution over time. In order to build a selectively history to track the underlying event streams changes, we opt for the continuously data of the sliding window which increases the time window based on changes over historical data. In this paper, to have the ability to access to historical data without requiring any significant storage or multiple passes over the data. In this paper, we propose a new algorithm for clustering multiple data streams using incremental support vector machine and data representative points’ technique. The algorithm uses a sliding window model for the most recent clustering results and data representative points to model the old data clustering results. Our experimental results on electromyography signal show a better clustering than other present in the literature

The Hubble Space Telescope Medium Deep Survey Cluster Sample: Methodology and Data

Science.gov (United States)

Ostrander, E. J.; Nichol, R. C.; Ratnatunga, K. U.; Griffiths, R. E.

1998-12-01

We present a new, objectively selected, sample of galaxy overdensities detected in the Hubble Space Telescope Medium Deep Survey (MDS). These clusters/groups were found using an automated procedure that involved searching for statistically significant galaxy overdensities. The contrast of the clusters against the field galaxy population is increased when morphological data are used to search around bulge-dominated galaxies. In total, we present 92 overdensities above a probability threshold of 99.5%. We show, via extensive Monte Carlo simulations, that at least 60% of these overdensities are likely to be real clusters and groups and not random line-of-sight superpositions of galaxies. For each overdensity in the MDS cluster sample, we provide a richness and the average of the bulge-to-total ratio of galaxies within each system. This MDS cluster sample potentially contains some of the most distant clusters/groups ever detected, with about 25% of the overdensities having estimated redshifts z > ~0.9. We have made this sample publicly available to facilitate spectroscopic confirmation of these clusters and help more detailed studies of cluster and galaxy evolution. We also report the serendipitous discovery of a new cluster close on the sky to the rich optical cluster Cl l0016+16 at z = 0.546. This new overdensity, HST 001831+16208, may be coincident with both an X-ray source and a radio source. HST 001831+16208 is the third cluster/group discovered near to Cl 0016+16 and appears to strengthen the claims of Connolly et al. of superclustering at high redshift.

The effect of clustering on lot quality assurance sampling: a probabilistic model to calculate sample sizes for quality assessments.

Science.gov (United States)

Hedt-Gauthier, Bethany L; Mitsunaga, Tisha; Hund, Lauren; Olives, Casey; Pagano, Marcello

2013-10-26

Traditional Lot Quality Assurance Sampling (LQAS) designs assume observations are collected using simple random sampling. Alternatively, randomly sampling clusters of observations and then individuals within clusters reduces costs but decreases the precision of the classifications. In this paper, we develop a general framework for designing the cluster(C)-LQAS system and illustrate the method with the design of data quality assessments for the community health worker program in Rwanda. To determine sample size and decision rules for C-LQAS, we use the beta-binomial distribution to account for inflated risk of errors introduced by sampling clusters at the first stage. We present general theory and code for sample size calculations.The C-LQAS sample sizes provided in this paper constrain misclassification risks below user-specified limits. Multiple C-LQAS systems meet the specified risk requirements, but numerous considerations, including per-cluster versus per-individual sampling costs, help identify optimal systems for distinct applications. We show the utility of C-LQAS for data quality assessments, but the method generalizes to numerous applications. This paper provides the necessary technical detail and supplemental code to support the design of C-LQAS for specific programs.

Spatially explicit population estimates for black bears based on cluster sampling

Science.gov (United States)

Humm, J.; McCown, J. Walter; Scheick, B.K.; Clark, Joseph D.

2017-01-01

We estimated abundance and density of the 5 major black bear (Ursus americanus) subpopulations (i.e., Eglin, Apalachicola, Osceola, Ocala-St. Johns, Big Cypress) in Florida, USA with spatially explicit capture-mark-recapture (SCR) by extracting DNA from hair samples collected at barbed-wire hair sampling sites. We employed a clustered sampling configuration with sampling sites arranged in 3 × 3 clusters spaced 2 km apart within each cluster and cluster centers spaced 16 km apart (center to center). We surveyed all 5 subpopulations encompassing 38,960 km2 during 2014 and 2015. Several landscape variables, most associated with forest cover, helped refine density estimates for the 5 subpopulations we sampled. Detection probabilities were affected by site-specific behavioral responses coupled with individual capture heterogeneity associated with sex. Model-averaged bear population estimates ranged from 120 (95% CI = 59–276) bears or a mean 0.025 bears/km2 (95% CI = 0.011–0.44) for the Eglin subpopulation to 1,198 bears (95% CI = 949–1,537) or 0.127 bears/km2 (95% CI = 0.101–0.163) for the Ocala-St. Johns subpopulation. The total population estimate for our 5 study areas was 3,916 bears (95% CI = 2,914–5,451). The clustered sampling method coupled with information on land cover was efficient and allowed us to estimate abundance across extensive areas that would not have been possible otherwise. Clustered sampling combined with spatially explicit capture-recapture methods has the potential to provide rigorous population estimates for a wide array of species that are extensive and heterogeneous in their distribution.

Scalable Clustering of High-Dimensional Data Technique Using SPCM with Ant Colony Optimization Intelligence

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Thenmozhi Srinivasan

2015-01-01

Full Text Available Clusters of high-dimensional data techniques are emerging, according to data noisy and poor quality challenges. This paper has been developed to cluster data using high-dimensional similarity based PCM (SPCM, with ant colony optimization intelligence which is effective in clustering nonspatial data without getting knowledge about cluster number from the user. The PCM becomes similarity based by using mountain method with it. Though this is efficient clustering, it is checked for optimization using ant colony algorithm with swarm intelligence. Thus the scalable clustering technique is obtained and the evaluation results are checked with synthetic datasets.

ATCA observations of the MACS-Planck Radio Halo Cluster Project. II. Radio observations of an intermediate redshift cluster sample

Science.gov (United States)

Martinez Aviles, G.; Johnston-Hollitt, M.; Ferrari, C.; Venturi, T.; Democles, J.; Dallacasa, D.; Cassano, R.; Brunetti, G.; Giacintucci, S.; Pratt, G. W.; Arnaud, M.; Aghanim, N.; Brown, S.; Douspis, M.; Hurier, J.; Intema, H. T.; Langer, M.; Macario, G.; Pointecouteau, E.

2018-04-01

Aim. A fraction of galaxy clusters host diffuse radio sources whose origins are investigated through multi-wavelength studies of cluster samples. We investigate the presence of diffuse radio emission in a sample of seven galaxy clusters in the largely unexplored intermediate redshift range (0.3 http://cdsarc.u-strasbg.fr (http://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/611/A94

Techniques for Representation of Regional Clusters in Geographical In-formation Systems

Directory of Open Access Journals (Sweden)

Adriana REVEIU

2011-01-01

Full Text Available This paper provides an overview of visualization techniques adapted for regional clusters presentation in Geographic Information Systems. Clusters are groups of companies and insti-tutions co-located in a specific geographic region and linked by interdependencies in providing a related group of products and services. The regional clusters can be visualized by projecting the data into two-dimensional space or using parallel coordinates. Cluster membership is usually represented by different colours or by dividing clusters into several panels of a grille display. Taking into consideration regional clusters requirements and the multilevel administrative division of the Romania’s territory, I used two cartograms: NUTS2- regions and NUTS3- counties, to illustrate the tools for regional clusters representation.

Clustering microcalcifications techniques in digital mammograms

Science.gov (United States)

Díaz, Claudia. C.; Bosco, Paolo; Cerello, Piergiorgio

2008-11-01

Breast cancer has become a serious public health problem around the world. However, this pathology can be treated if it is detected in early stages. This task is achieved by a radiologist, who should read a large amount of mammograms per day, either for a screening or diagnostic purpose in mammography. However human factors could affect the diagnosis. Computer Aided Detection is an automatic system, which can help to specialists in the detection of possible signs of malignancy in mammograms. Microcalcifications play an important role in early detection, so we focused on their study. The two mammographic features that indicate the microcalcifications could be probably malignant are small size and clustered distribution. We worked with density techniques for automatic clustering, and we applied them on a mammography CAD prototype developed at INFN-Turin, Italy. An improvement of performance is achieved analyzing images from a Perugia-Assisi Hospital, in Italy.

Clustering economies based on multiple criteria decision making techniques

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Mansour Momeni

2011-10-01

Full Text Available One of the primary concerns on many countries is to determine different important factors affecting economic growth. In this paper, we study some factors such as unemployment rate, inflation ratio, population growth, average annual income, etc to cluster different countries. The proposed model of this paper uses analytical hierarchy process (AHP to prioritize the criteria and then uses a K-mean technique to cluster 59 countries based on the ranked criteria into four groups. The first group includes countries with high standards such as Germany and Japan. In the second cluster, there are some developing countries with relatively good economic growth such as Saudi Arabia and Iran. The third cluster belongs to countries with faster rates of growth compared with the countries located in the second group such as China, India and Mexico. Finally, the fourth cluster includes countries with relatively very low rates of growth such as Jordan, Mali, Niger, etc.

Two sampling techniques for game meat

OpenAIRE

van der Merwe, Maretha; Jooste, Piet J.; Hoffman, Louw C.; Calitz, Frikkie J.

2013-01-01

A study was conducted to compare the excision sampling technique used by the export market and the sampling technique preferred by European countries, namely the biotrace cattle and swine test. The measuring unit for the excision sampling was grams (g) and square centimetres (cm2) for the swabbing technique. The two techniques were compared after a pilot test was conducted on spiked approved beef carcasses (n = 12) that statistically proved the two measuring units correlated. The two sampling...

GLOBULAR CLUSTER ABUNDANCES FROM HIGH-RESOLUTION, INTEGRATED-LIGHT SPECTROSCOPY. II. EXPANDING THE METALLICITY RANGE FOR OLD CLUSTERS AND UPDATED ANALYSIS TECHNIQUES

Energy Technology Data Exchange (ETDEWEB)

Colucci, Janet E.; Bernstein, Rebecca A.; McWilliam, Andrew [The Observatories of the Carnegie Institution for Science, 813 Santa Barbara St., Pasadena, CA 91101 (United States)

2017-01-10

We present abundances of globular clusters (GCs) in the Milky Way and Fornax from integrated-light (IL) spectra. Our goal is to evaluate the consistency of the IL analysis relative to standard abundance analysis for individual stars in those same clusters. This sample includes an updated analysis of seven clusters from our previous publications and results for five new clusters that expand the metallicity range over which our technique has been tested. We find that the [Fe/H] measured from IL spectra agrees to ∼0.1 dex for GCs with metallicities as high as [Fe/H] = −0.3, but the abundances measured for more metal-rich clusters may be underestimated. In addition we systematically evaluate the accuracy of abundance ratios, [X/Fe], for Na i, Mg i, Al i, Si i, Ca i, Ti i, Ti ii, Sc ii, V i, Cr i, Mn i, Co i, Ni i, Cu i, Y ii, Zr i, Ba ii, La ii, Nd ii, and Eu ii. The elements for which the IL analysis gives results that are most similar to analysis of individual stellar spectra are Fe i, Ca i, Si i, Ni i, and Ba ii. The elements that show the greatest differences include Mg i and Zr i. Some elements show good agreement only over a limited range in metallicity. More stellar abundance data in these clusters would enable more complete evaluation of the IL results for other important elements.

Cluster lot quality assurance sampling: effect of increasing the number of clusters on classification precision and operational feasibility.

Science.gov (United States)

Okayasu, Hiromasa; Brown, Alexandra E; Nzioki, Michael M; Gasasira, Alex N; Takane, Marina; Mkanda, Pascal; Wassilak, Steven G F; Sutter, Roland W

2014-11-01

To assess the quality of supplementary immunization activities (SIAs), the Global Polio Eradication Initiative (GPEI) has used cluster lot quality assurance sampling (C-LQAS) methods since 2009. However, since the inception of C-LQAS, questions have been raised about the optimal balance between operational feasibility and precision of classification of lots to identify areas with low SIA quality that require corrective programmatic action. To determine if an increased precision in classification would result in differential programmatic decision making, we conducted a pilot evaluation in 4 local government areas (LGAs) in Nigeria with an expanded LQAS sample size of 16 clusters (instead of the standard 6 clusters) of 10 subjects each. The results showed greater heterogeneity between clusters than the assumed standard deviation of 10%, ranging from 12% to 23%. Comparing the distribution of 4-outcome classifications obtained from all possible combinations of 6-cluster subsamples to the observed classification of the 16-cluster sample, we obtained an exact match in classification in 56% to 85% of instances. We concluded that the 6-cluster C-LQAS provides acceptable classification precision for programmatic action. Considering the greater resources required to implement an expanded C-LQAS, the improvement in precision was deemed insufficient to warrant the effort. Published by Oxford University Press on behalf of the Infectious Diseases Society of America 2014. This work is written by (a) US Government employee(s) and is in the public domain in the US.

Hot Zone Identification: Analyzing Effects of Data Sampling on Spam Clustering

Directory of Open Access Journals (Sweden)

Rasib Khan

2014-03-01

Full Text Available Email is the most common and comparatively the most efficient means of exchanging information in today's world. However, given the widespread use of emails in all sectors, they have been the target of spammers since the beginning. Filtering spam emails has now led to critical actions such as forensic activities based on mining spam email. The data mine for spam emails at the University of Alabama at Birmingham is considered to be one of the most prominent resources for mining and identifying spam sources. It is a widely researched repository used by researchers from different global organizations. The usual process of mining the spam data involves going through every email in the data mine and clustering them based on their different attributes. However, given the size of the data mine, it takes an exceptionally long time to execute the clustering mechanism each time. In this paper, we have illustrated sampling as an efficient tool for data reduction, while preserving the information within the clusters, which would thus allow the spam forensic experts to quickly and effectively identify the ‘hot zone’ from the spam campaigns. We have provided detailed comparative analysis of the quality of the clusters after sampling, the overall distribution of clusters on the spam data, and timing measurements for our sampling approach. Additionally, we present different strategies which allowed us to optimize the sampling process using data-preprocessing and using the database engine's computational resources, and thus improving the performance of the clustering process.

Hydration of Atmospheric Molecular Clusters: Systematic Configurational Sampling.

Science.gov (United States)

Kildgaard, Jens; Mikkelsen, Kurt V; Bilde, Merete; Elm, Jonas

2018-05-09

We present a new systematic configurational sampling algorithm for investigating the potential energy surface of hydrated atmospheric molecular clusters. The algo- rithm is based on creating a Fibonacci sphere around each atom in the cluster and adding water molecules to each point in 9 different orientations. To allow the sam- pling of water molecules to existing hydrogen bonds, the cluster is displaced along the hydrogen bond and a water molecule is placed in between in three different ori- entations. Generated redundant structures are eliminated based on minimizing the root mean square distance (RMSD) of different conformers. Initially, the clusters are sampled using the semiempirical PM6 method and subsequently using density func- tional theory (M06-2X and ωB97X-D) with the 6-31++G(d,p) basis set. Applying the developed algorithm we study the hydration of sulfuric acid with up to 15 water molecules. We find that the additions of the first four water molecules "saturate" the sulfuric acid molecule and are more thermodynamically favourable than the addition of water molecule 5-15. Using the large generated set of conformers, we assess the performance of approximate methods (ωB97X-D, M06-2X, PW91 and PW6B95-D3) in calculating the binding energies and assigning the global minimum conformation compared to high level CCSD(T)-F12a/VDZ-F12 reference calculations. The tested DFT functionals systematically overestimates the binding energies compared to cou- pled cluster calculations, and we find that this deficiency can be corrected by a simple scaling factor.

A clustering algorithm for sample data based on environmental pollution characteristics

Science.gov (United States)

Chen, Mei; Wang, Pengfei; Chen, Qiang; Wu, Jiadong; Chen, Xiaoyun

2015-04-01

Environmental pollution has become an issue of serious international concern in recent years. Among the receptor-oriented pollution models, CMB, PMF, UNMIX, and PCA are widely used as source apportionment models. To improve the accuracy of source apportionment and classify the sample data for these models, this study proposes an easy-to-use, high-dimensional EPC algorithm that not only organizes all of the sample data into different groups according to the similarities in pollution characteristics such as pollution sources and concentrations but also simultaneously detects outliers. The main clustering process consists of selecting the first unlabelled point as the cluster centre, then assigning each data point in the sample dataset to its most similar cluster centre according to both the user-defined threshold and the value of similarity function in each iteration, and finally modifying the clusters using a method similar to k-Means. The validity and accuracy of the algorithm are tested using both real and synthetic datasets, which makes the EPC algorithm practical and effective for appropriately classifying sample data for source apportionment models and helpful for better understanding and interpreting the sources of pollution.

Comparison of Clustering Techniques for Residential Energy Behavior using Smart Meter Data

Energy Technology Data Exchange (ETDEWEB)

Jin, Ling; Lee, Doris; Sim, Alex; Borgeson, Sam; Wu, Kesheng; Spurlock, C. Anna; Todd, Annika

2017-03-21

Current practice in whole time series clustering of residential meter data focuses on aggregated or subsampled load data at the customer level, which ignores day-to-day differences within customers. This information is critical to determine each customer’s suitability to various demand side management strategies that support intelligent power grids and smart energy management. Clustering daily load shapes provides fine-grained information on customer attributes and sources of variation for subsequent models and customer segmentation. In this paper, we apply 11 clustering methods to daily residential meter data. We evaluate their parameter settings and suitability based on 6 generic performance metrics and post-checking of resulting clusters. Finally, we recommend suitable techniques and parameters based on the goal of discovering diverse daily load patterns among residential customers. To the authors’ knowledge, this paper is the first robust comparative review of clustering techniques applied to daily residential load shape time series in the power systems’ literature.

Hybrid Clustering-GWO-NARX neural network technique in predicting stock price

Science.gov (United States)

Das, Debashish; Safa Sadiq, Ali; Mirjalili, Seyedali; Noraziah, A.

2017-09-01

Prediction of stock price is one of the most challenging tasks due to nonlinear nature of the stock data. Though numerous attempts have been made to predict the stock price by applying various techniques, yet the predicted price is not always accurate and even the error rate is high to some extent. Consequently, this paper endeavours to determine an efficient stock prediction strategy by implementing a combinatorial method of Grey Wolf Optimizer (GWO), Clustering and Non Linear Autoregressive Exogenous (NARX) Technique. The study uses stock data from prominent stock market i.e. New York Stock Exchange (NYSE), NASDAQ and emerging stock market i.e. Malaysian Stock Market (Bursa Malaysia), Dhaka Stock Exchange (DSE). It applies K-means clustering algorithm to determine the most promising cluster, then MGWO is used to determine the classification rate and finally the stock price is predicted by applying NARX neural network algorithm. The prediction performance gained through experimentation is compared and assessed to guide the investors in making investment decision. The result through this technique is indeed promising as it has shown almost precise prediction and improved error rate. We have applied the hybrid Clustering-GWO-NARX neural network technique in predicting stock price. We intend to work with the effect of various factors in stock price movement and selection of parameters. We will further investigate the influence of company news either positive or negative in stock price movement. We would be also interested to predict the Stock indices.

Two sampling techniques for game meat

Directory of Open Access Journals (Sweden)

Maretha van der Merwe

2013-03-01

Full Text Available A study was conducted to compare the excision sampling technique used by the export market and the sampling technique preferred by European countries, namely the biotrace cattle and swine test. The measuring unit for the excision sampling was grams (g and square centimetres (cm2 for the swabbing technique. The two techniques were compared after a pilot test was conducted on spiked approved beef carcasses (n = 12 that statistically proved the two measuring units correlated. The two sampling techniques were conducted on the same game carcasses (n = 13 and analyses performed for aerobic plate count (APC, Escherichia coli and Staphylococcus aureus, for both techniques. A more representative result was obtained by swabbing and no damage was caused to the carcass. Conversely, the excision technique yielded fewer organisms and caused minor damage to the carcass. The recovery ratio from the sampling technique improved 5.4 times for APC, 108.0 times for E. coli and 3.4 times for S. aureus over the results obtained from the excision technique. It was concluded that the sampling methods of excision and swabbing can be used to obtain bacterial profiles from both export and local carcasses and could be used to indicate whether game carcasses intended for the local market are possibly on par with game carcasses intended for the export market and therefore safe for human consumption.

Two sampling techniques for game meat.

Science.gov (United States)

van der Merwe, Maretha; Jooste, Piet J; Hoffman, Louw C; Calitz, Frikkie J

2013-03-20

A study was conducted to compare the excision sampling technique used by the export market and the sampling technique preferred by European countries, namely the biotrace cattle and swine test. The measuring unit for the excision sampling was grams (g) and square centimetres (cm2) for the swabbing technique. The two techniques were compared after a pilot test was conducted on spiked approved beef carcasses (n = 12) that statistically proved the two measuring units correlated. The two sampling techniques were conducted on the same game carcasses (n = 13) and analyses performed for aerobic plate count (APC), Escherichia coli and Staphylococcus aureus, for both techniques. A more representative result was obtained by swabbing and no damage was caused to the carcass. Conversely, the excision technique yielded fewer organisms and caused minor damage to the carcass. The recovery ratio from the sampling technique improved 5.4 times for APC, 108.0 times for E. coli and 3.4 times for S. aureus over the results obtained from the excision technique. It was concluded that the sampling methods of excision and swabbing can be used to obtain bacterial profiles from both export and local carcasses and could be used to indicate whether game carcasses intended for the local market are possibly on par with game carcasses intended for the export market and therefore safe for human consumption.

COSMOLOGICAL CONSTRAINTS FROM GALAXY CLUSTERING AND THE MASS-TO-NUMBER RATIO OF GALAXY CLUSTERS

International Nuclear Information System (INIS)

Tinker, Jeremy L.; Blanton, Michael R.; Sheldon, Erin S.; Wechsler, Risa H.; Becker, Matthew R.; Rozo, Eduardo; Zu, Ying; Weinberg, David H.; Zehavi, Idit; Busha, Michael T.; Koester, Benjamin P.

2012-01-01

We place constraints on the average density (Ω m ) and clustering amplitude (σ 8 ) of matter using a combination of two measurements from the Sloan Digital Sky Survey: the galaxy two-point correlation function, w p (r p ), and the mass-to-galaxy-number ratio within galaxy clusters, M/N, analogous to cluster M/L ratios. Our w p (r p ) measurements are obtained from DR7 while the sample of clusters is the maxBCG sample, with cluster masses derived from weak gravitational lensing. We construct nonlinear galaxy bias models using the Halo Occupation Distribution (HOD) to fit both w p (r p ) and M/N for different cosmological parameters. HOD models that match the same two-point clustering predict different numbers of galaxies in massive halos when Ω m or σ 8 is varied, thereby breaking the degeneracy between cosmology and bias. We demonstrate that this technique yields constraints that are consistent and competitive with current results from cluster abundance studies, without the use of abundance information. Using w p (r p ) and M/N alone, we find Ω 0.5 m σ 8 = 0.465 ± 0.026, with individual constraints of Ω m = 0.29 ± 0.03 and σ 8 = 0.85 ± 0.06. Combined with current cosmic microwave background data, these constraints are Ω m = 0.290 ± 0.016 and σ 8 = 0.826 ± 0.020. All errors are 1σ. The systematic uncertainties that the M/N technique are most sensitive to are the amplitude of the bias function of dark matter halos and the possibility of redshift evolution between the SDSS Main sample and the maxBCG cluster sample. Our derived constraints are insensitive to the current level of uncertainties in the halo mass function and in the mass-richness relation of clusters and its scatter, making the M/N technique complementary to cluster abundances as a method for constraining cosmology with future galaxy surveys.

COSMOLOGICAL CONSTRAINTS FROM GALAXY CLUSTERING AND THE MASS-TO-NUMBER RATIO OF GALAXY CLUSTERS

Energy Technology Data Exchange (ETDEWEB)

Tinker, Jeremy L.; Blanton, Michael R. [Center for Cosmology and Particle Physics, Department of Physics, New York University, New York, NY 10013 (United States); Sheldon, Erin S. [Brookhaven National Laboratory, Upton, NY 11973 (United States); Wechsler, Risa H. [Kavli Institute for Particle Astrophysics and Cosmology, Physics Department, and SLAC National Accelerator Laboratory, Stanford University, Stanford, CA 94305 (United States); Becker, Matthew R.; Rozo, Eduardo [Kavli Institute for Cosmological Physics, University of Chicago, Chicago, IL 60637 (United States); Zu, Ying; Weinberg, David H. [Department of Astronomy, Ohio State University, Columbus, OH 43210 (United States); Zehavi, Idit [Department of Astronomy and CERCA, Case Western Reserve University, Cleveland, OH 44106 (United States); Busha, Michael T. [Institute for Theoretical Physics, Department of Physics, University of Zurich, CH-8057 Zurich (Switzerland); Koester, Benjamin P. [Department of Astronomy and Astrophysics, University of Chicago, Chicago, IL 6037 (United States)

2012-01-20

We place constraints on the average density ({Omega}{sub m}) and clustering amplitude ({sigma}{sub 8}) of matter using a combination of two measurements from the Sloan Digital Sky Survey: the galaxy two-point correlation function, w{sub p} (r{sub p} ), and the mass-to-galaxy-number ratio within galaxy clusters, M/N, analogous to cluster M/L ratios. Our w{sub p} (r{sub p} ) measurements are obtained from DR7 while the sample of clusters is the maxBCG sample, with cluster masses derived from weak gravitational lensing. We construct nonlinear galaxy bias models using the Halo Occupation Distribution (HOD) to fit both w{sub p} (r{sub p} ) and M/N for different cosmological parameters. HOD models that match the same two-point clustering predict different numbers of galaxies in massive halos when {Omega}{sub m} or {sigma}{sub 8} is varied, thereby breaking the degeneracy between cosmology and bias. We demonstrate that this technique yields constraints that are consistent and competitive with current results from cluster abundance studies, without the use of abundance information. Using w{sub p} (r{sub p} ) and M/N alone, we find {Omega}{sup 0.5}{sub m}{sigma}{sub 8} = 0.465 {+-} 0.026, with individual constraints of {Omega}{sub m} = 0.29 {+-} 0.03 and {sigma}{sub 8} = 0.85 {+-} 0.06. Combined with current cosmic microwave background data, these constraints are {Omega}{sub m} = 0.290 {+-} 0.016 and {sigma}{sub 8} = 0.826 {+-} 0.020. All errors are 1{sigma}. The systematic uncertainties that the M/N technique are most sensitive to are the amplitude of the bias function of dark matter halos and the possibility of redshift evolution between the SDSS Main sample and the maxBCG cluster sample. Our derived constraints are insensitive to the current level of uncertainties in the halo mass function and in the mass-richness relation of clusters and its scatter, making the M/N technique complementary to cluster abundances as a method for constraining cosmology with future galaxy

Clustering: An Interactive Technique to Enhance Learning in Biology.

Science.gov (United States)

Ambron, Joanna

1988-01-01

Explains an interdisciplinary approach to biology and writing which increases students' mastery of vocabulary, scientific concepts, creativity, and expression. Describes modifications of the clustering technique used to summarize lectures, integrate reading and understand textbook material. (RT)

GENERALISED MODEL BASED CONFIDENCE INTERVALS IN TWO STAGE CLUSTER SAMPLING

Directory of Open Access Journals (Sweden)

Christopher Ouma Onyango

2010-09-01

Full Text Available Chambers and Dorfman (2002 constructed bootstrap confidence intervals in model based estimation for finite population totals assuming that auxiliary values are available throughout a target population and that the auxiliary values are independent. They also assumed that the cluster sizes are known throughout the target population. We now extend to two stage sampling in which the cluster sizes are known only for the sampled clusters, and we therefore predict the unobserved part of the population total. Jan and Elinor (2008 have done similar work, but unlike them, we use a general model, in which the auxiliary values are not necessarily independent. We demonstrate that the asymptotic properties of our proposed estimator and its coverage rates are better than those constructed under the model assisted local polynomial regression model.

Systematic adaptive cluster sampling for the assessment of rare tree species in Nepal

NARCIS (Netherlands)

Acharya, B.; Bhattarai, G.; Gier, de A.; Stein, A.

2000-01-01

Sampling to assess rare tree species poses methodic problems, because they may cluster and many plots with no such trees are to be expected. We used systematic adaptive cluster sampling (SACS) to sample three rare tree species in a forest area of about 40 ha in Nepal. We checked its applicability

Clustering for high-dimension, low-sample size data using distance vectors

OpenAIRE

Terada, Yoshikazu

2013-01-01

In high-dimension, low-sample size (HDLSS) data, it is not always true that closeness of two objects reflects a hidden cluster structure. We point out the important fact that it is not the closeness, but the "values" of distance that contain information of the cluster structure in high-dimensional space. Based on this fact, we propose an efficient and simple clustering approach, called distance vector clustering, for HDLSS data. Under the assumptions given in the work of Hall et al. (2005), w...

Performance of clustering techniques for solving multi depot vehicle routing problem

Directory of Open Access Journals (Sweden)

Eliana M. Toro-Ocampo

2016-01-01

Full Text Available The vehicle routing problem considering multiple depots is classified as NP-hard. MDVRP determines simultaneously the routes of a set of vehicles and aims to meet a set of clients with a known demand. The objective function of the problem is to minimize the total distance traveled by the routes given that all customers must be served considering capacity constraints in depots and vehicles. This paper presents a hybrid methodology that combines agglomerative clustering techniques to generate initial solutions with an iterated local search algorithm (ILS to solve the problem. Although previous studies clustering methods have been proposed like strategies to generate initial solutions, in this work the search is intensified on the information generated after applying the clustering technique. Besides an extensive analysis on the performance of techniques, and their effect in the final solution is performed. The operation of the proposed methodology is feasible and effective to solve the problem regarding the quality of the answers and computational times obtained on request evaluated literature

A HIGH FIDELITY SAMPLE OF COLD FRONT CLUSTERS FROM THE CHANDRA ARCHIVE

International Nuclear Information System (INIS)

Owers, Matt S.; Nulsen, Paul E. J.; Markevitch, Maxim; Couch, Warrick J.

2009-01-01

This paper presents a sample of 'cold front' clusters selected from the Chandra archive. The clusters are selected based purely on the existence of surface brightness edges in their Chandra images which are modeled as density jumps. A combination of the derived density and temperature jumps across the fronts is used to select nine robust examples of cold front clusters: 1ES0657 - 558, Abell 1201, Abell 1758N, MS1455.0+2232, Abell 2069, Abell 2142, Abell 2163, RXJ1720.1+2638, and Abell 3667. This sample is the subject of an ongoing study aimed at relating cold fronts to cluster merger activity, and understanding how the merging environment affects the cluster constituents. Here, temperature maps are presented along with the Chandra X-ray images. A dichotomy is found in the sample in that there exists a subsample of cold front clusters which are clearly mergers based on their X-ray morphologies, and a second subsample of clusters which harbor cold fronts, but have surprisingly relaxed X-ray morphologies, and minimal evidence for merger activity at other wavelengths. For this second subsample, the existence of a cold front provides the sole evidence for merger activity at X-ray wavelengths. We discuss how cold fronts can provide additional information which may be used to constrain merger histories, and also the possibility of using cold fronts to distinguish major and minor mergers.

Sample size adjustments for varying cluster sizes in cluster randomized trials with binary outcomes analyzed with second-order PQL mixed logistic regression.

Science.gov (United States)

Candel, Math J J M; Van Breukelen, Gerard J P

2010-06-30

Adjustments of sample size formulas are given for varying cluster sizes in cluster randomized trials with a binary outcome when testing the treatment effect with mixed effects logistic regression using second-order penalized quasi-likelihood estimation (PQL). Starting from first-order marginal quasi-likelihood (MQL) estimation of the treatment effect, the asymptotic relative efficiency of unequal versus equal cluster sizes is derived. A Monte Carlo simulation study shows this asymptotic relative efficiency to be rather accurate for realistic sample sizes, when employing second-order PQL. An approximate, simpler formula is presented to estimate the efficiency loss due to varying cluster sizes when planning a trial. In many cases sampling 14 per cent more clusters is sufficient to repair the efficiency loss due to varying cluster sizes. Since current closed-form formulas for sample size calculation are based on first-order MQL, planning a trial also requires a conversion factor to obtain the variance of the second-order PQL estimator. In a second Monte Carlo study, this conversion factor turned out to be 1.25 at most. (c) 2010 John Wiley & Sons, Ltd.

Focus-based filtering + clustering technique for power-law networks with small world phenomenon

Science.gov (United States)

Boutin, François; Thièvre, Jérôme; Hascoët, Mountaz

2006-01-01

Realistic interaction networks usually present two main properties: a power-law degree distribution and a small world behavior. Few nodes are linked to many nodes and adjacent nodes are likely to share common neighbors. Moreover, graph structure usually presents a dense core that is difficult to explore with classical filtering and clustering techniques. In this paper, we propose a new filtering technique accounting for a user-focus. This technique extracts a tree-like graph with also power-law degree distribution and small world behavior. Resulting structure is easily drawn with classical force-directed drawing algorithms. It is also quickly clustered and displayed into a multi-level silhouette tree (MuSi-Tree) from any user-focus. We built a new graph filtering + clustering + drawing API and report a case study.

Brain tumor segmentation based on a hybrid clustering technique

Directory of Open Access Journals (Sweden)

Eman Abdel-Maksoud

2015-03-01

This paper presents an efficient image segmentation approach using K-means clustering technique integrated with Fuzzy C-means algorithm. It is followed by thresholding and level set segmentation stages to provide an accurate brain tumor detection. The proposed technique can get benefits of the K-means clustering for image segmentation in the aspects of minimal computation time. In addition, it can get advantages of the Fuzzy C-means in the aspects of accuracy. The performance of the proposed image segmentation approach was evaluated by comparing it with some state of the art segmentation algorithms in case of accuracy, processing time, and performance. The accuracy was evaluated by comparing the results with the ground truth of each processed image. The experimental results clarify the effectiveness of our proposed approach to deal with a higher number of segmentation problems via improving the segmentation quality and accuracy in minimal execution time.

HICOSMO - cosmology with a complete sample of galaxy clusters - I. Data analysis, sample selection and luminosity-mass scaling relation

Science.gov (United States)

Schellenberger, G.; Reiprich, T. H.

2017-08-01

The X-ray regime, where the most massive visible component of galaxy clusters, the intracluster medium, is visible, offers directly measured quantities, like the luminosity, and derived quantities, like the total mass, to characterize these objects. The aim of this project is to analyse a complete sample of galaxy clusters in detail and constrain cosmological parameters, like the matter density, Ωm, or the amplitude of initial density fluctuations, σ8. The purely X-ray flux-limited sample (HIFLUGCS) consists of the 64 X-ray brightest galaxy clusters, which are excellent targets to study the systematic effects, that can bias results. We analysed in total 196 Chandra observations of the 64 HIFLUGCS clusters, with a total exposure time of 7.7 Ms. Here, we present our data analysis procedure (including an automated substructure detection and an energy band optimization for surface brightness profile analysis) that gives individually determined, robust total mass estimates. These masses are tested against dynamical and Planck Sunyaev-Zeldovich (SZ) derived masses of the same clusters, where good overall agreement is found with the dynamical masses. The Planck SZ masses seem to show a mass-dependent bias to our hydrostatic masses; possible biases in this mass-mass comparison are discussed including the Planck selection function. Furthermore, we show the results for the (0.1-2.4) keV luminosity versus mass scaling relation. The overall slope of the sample (1.34) is in agreement with expectations and values from literature. Splitting the sample into galaxy groups and clusters reveals, even after a selection bias correction, that galaxy groups exhibit a significantly steeper slope (1.88) compared to clusters (1.06).

Active learning for semi-supervised clustering based on locally linear propagation reconstruction.

Science.gov (United States)

Chang, Chin-Chun; Lin, Po-Yi

2015-03-01

The success of semi-supervised clustering relies on the effectiveness of side information. To get effective side information, a new active learner learning pairwise constraints known as must-link and cannot-link constraints is proposed in this paper. Three novel techniques are developed for learning effective pairwise constraints. The first technique is used to identify samples less important to cluster structures. This technique makes use of a kernel version of locally linear embedding for manifold learning. Samples neither important to locally linear propagation reconstructions of other samples nor on flat patches in the learned manifold are regarded as unimportant samples. The second is a novel criterion for query selection. This criterion considers not only the importance of a sample to expanding the space coverage of the learned samples but also the expected number of queries needed to learn the sample. To facilitate semi-supervised clustering, the third technique yields inferred must-links for passing information about flat patches in the learned manifold to semi-supervised clustering algorithms. Experimental results have shown that the learned pairwise constraints can capture the underlying cluster structures and proven the feasibility of the proposed approach. Copyright © 2014 Elsevier Ltd. All rights reserved.

HICOSMO - X-ray analysis of a complete sample of galaxy clusters

Science.gov (United States)

Schellenberger, G.; Reiprich, T.

2017-10-01

Galaxy clusters are known to be the largest virialized objects in the Universe. Based on the theory of structure formation one can use them as cosmological probes, since they originate from collapsed overdensities in the early Universe and witness its history. The X-ray regime provides the unique possibility to measure in detail the most massive visible component, the intra cluster medium. Using Chandra observations of a local sample of 64 bright clusters (HIFLUGCS) we provide total (hydrostatic) and gas mass estimates of each cluster individually. Making use of the completeness of the sample we quantify two interesting cosmological parameters by a Bayesian cosmological likelihood analysis. We find Ω_{M}=0.3±0.01 and σ_{8}=0.79±0.03 (statistical uncertainties) using our default analysis strategy combining both, a mass function analysis and the gas mass fraction results. The main sources of biases that we discuss and correct here are (1) the influence of galaxy groups (higher incompleteness in parent samples and a differing behavior of the L_{x} - M relation), (2) the hydrostatic mass bias (as determined by recent hydrodynamical simulations), (3) the extrapolation of the total mass (comparing various methods), (4) the theoretical halo mass function and (5) other cosmological (non-negligible neutrino mass), and instrumental (calibration) effects.

Radioisotope Sample Measurement Techniques in Medicine and Biology. Proceedings of the Symposium on Radioisotope Sample Measurement Techniques

International Nuclear Information System (INIS)

1965-01-01

The medical and biological applications of radioisotopes depend on two basically different types of measurements, those on living subjects in vivo and those on samples in vitro. The International Atomic Energy Agency has in the past held several meetings on in vivo measurement techniques, notably whole-body counting and radioisotope scanning. The present volume contains the Proceedings of the first Symposium the Agency has organized to discuss the various aspects of techniques for sample measurement in vitro. The range of these sample measurement techniques is very wide. The sample may weigh a few milligrams or several hundred grams, and may be in the gaseous, liquid or solid state. Its radioactive content may consist of a single, known radioisotope or several unknown ones. The concentration of radioactivity may be low, medium or high. The measurements may be made manually or automatically and any one of the many radiation detectors now available may be used. The 53 papers presented at the Symposium illustrate the great variety of methods now in use for radioactive- sample measurements. The first topic discussed is gamma-ray spectrometry, which finds an increasing number of applications in sample measurements. Other sections of the Proceedings deal with: the use of computers in gamma-ray spectrometry and multiple tracer techniques; recent developments in activation analysis where both gamma-ray spectrometry and computing techniques are applied; thin-layer and paper radio chromatographic techniques for use with low energy beta-ray emitters; various aspects of liquid scintillation counting techniques in the measurement of alpha- and beta-ray emitters, including chemical and colour quenching; autoradiographic techniques; calibration of equipment; and standardization of radioisotopes. Finally, some applications of solid-state detectors are presented; this section may be regarded as a preview of important future developments. The meeting was attended by 203 participants

Accurate recapture identification for genetic mark–recapture studies with error-tolerant likelihood-based match calling and sample clustering

Science.gov (United States)

Sethi, Suresh; Linden, Daniel; Wenburg, John; Lewis, Cara; Lemons, Patrick R.; Fuller, Angela K.; Hare, Matthew P.

2016-01-01

Error-tolerant likelihood-based match calling presents a promising technique to accurately identify recapture events in genetic mark–recapture studies by combining probabilities of latent genotypes and probabilities of observed genotypes, which may contain genotyping errors. Combined with clustering algorithms to group samples into sets of recaptures based upon pairwise match calls, these tools can be used to reconstruct accurate capture histories for mark–recapture modelling. Here, we assess the performance of a recently introduced error-tolerant likelihood-based match-calling model and sample clustering algorithm for genetic mark–recapture studies. We assessed both biallelic (i.e. single nucleotide polymorphisms; SNP) and multiallelic (i.e. microsatellite; MSAT) markers using a combination of simulation analyses and case study data on Pacific walrus (Odobenus rosmarus divergens) and fishers (Pekania pennanti). A novel two-stage clustering approach is demonstrated for genetic mark–recapture applications. First, repeat captures within a sampling occasion are identified. Subsequently, recaptures across sampling occasions are identified. The likelihood-based matching protocol performed well in simulation trials, demonstrating utility for use in a wide range of genetic mark–recapture studies. Moderately sized SNP (64+) and MSAT (10–15) panels produced accurate match calls for recaptures and accurate non-match calls for samples from closely related individuals in the face of low to moderate genotyping error. Furthermore, matching performance remained stable or increased as the number of genetic markers increased, genotyping error notwithstanding.

HUBBLE SPACE TELESCOPE PROPER MOTION (HSTPROMO) CATALOGS OF GALACTIC GLOBULAR CLUSTERS. I. SAMPLE SELECTION, DATA REDUCTION, AND NGC 7078 RESULTS

Energy Technology Data Exchange (ETDEWEB)

Bellini, A.; Anderson, J.; Van der Marel, R. P.; Watkins, L. L. [Space Telescope Science Institute, 3700 San Martin Drive, Baltimore, MD 21218 (United States); King, I. R. [Department of Astronomy, University of Washington, Box 351580, Seattle, WA 98195 (United States); Bianchini, P. [Max Planck Institute for Astronomy, Königstuhl 17, D-69117 Heidelberg (Germany); Chanamé, J. [Instituto de Astrofísica, Pontificia Universidad Católica de Chile, Av. Vicuña Mackenna 4860, Macul 782-0436, Santiago (Chile); Chandar, R. [Department of Physics and Astronomy, The University of Toledo, 2801 West Bancroft Street, Toledo, OH 43606 (United States); Cool, A. M. [Department of Physics and Astronomy, San Francisco State University, 1600 Holloway Avenue, San Francisco, CA 94132 (United States); Ferraro, F. R.; Massari, D. [Dipartimento di Fisica e Astronomia, Università di Bologna, via Ranzani 1, I-40127 Bologna (Italy); Ford, H., E-mail: bellini@stsci.edu [Department of Physics and Astronomy, The Johns Hopkins University, 3400 North Charles Street, Baltimore, MD 21218 (United States)

2014-12-20

We present the first study of high-precision internal proper motions (PMs) in a large sample of globular clusters, based on Hubble Space Telescope (HST) data obtained over the past decade with the ACS/WFC, ACS/HRC, and WFC3/UVIS instruments. We determine PMs for over 1.3 million stars in the central regions of 22 clusters, with a median number of ∼60,000 stars per cluster. These PMs have the potential to significantly advance our understanding of the internal kinematics of globular clusters by extending past line-of-sight (LOS) velocity measurements to two- or three-dimensional velocities, lower stellar masses, and larger sample sizes. We describe the reduction pipeline that we developed to derive homogeneous PMs from the very heterogeneous archival data. We demonstrate the quality of the measurements through extensive Monte Carlo simulations. We also discuss the PM errors introduced by various systematic effects and the techniques that we have developed to correct or remove them to the extent possible. We provide in electronic form the catalog for NGC 7078 (M 15), which consists of 77,837 stars in the central 2.'4. We validate the catalog by comparison with existing PM measurements and LOS velocities and use it to study the dependence of the velocity dispersion on radius, stellar magnitude (or mass) along the main sequence, and direction in the plane of the sky (radial or tangential). Subsequent papers in this series will explore a range of applications in globular-cluster science and will also present the PM catalogs for the other sample clusters.

A new clustering algorithm for scanning electron microscope images

Science.gov (United States)

Yousef, Amr; Duraisamy, Prakash; Karim, Mohammad

2016-04-01

A scanning electron microscope (SEM) is a type of electron microscope that produces images of a sample by scanning it with a focused beam of electrons. The electrons interact with the sample atoms, producing various signals that are collected by detectors. The gathered signals contain information about the sample's surface topography and composition. The electron beam is generally scanned in a raster scan pattern, and the beam's position is combined with the detected signal to produce an image. The most common configuration for an SEM produces a single value per pixel, with the results usually rendered as grayscale images. The captured images may be produced with insufficient brightness, anomalous contrast, jagged edges, and poor quality due to low signal-to-noise ratio, grained topography and poor surface details. The segmentation of the SEM images is a tackling problems in the presence of the previously mentioned distortions. In this paper, we are stressing on the clustering of these type of images. In that sense, we evaluate the performance of the well-known unsupervised clustering and classification techniques such as connectivity based clustering (hierarchical clustering), centroid-based clustering, distribution-based clustering and density-based clustering. Furthermore, we propose a new spatial fuzzy clustering technique that works efficiently on this type of images and compare its results against these regular techniques in terms of clustering validation metrics.

OPEN CLUSTERS AS PROBES OF THE GALACTIC MAGNETIC FIELD. I. CLUSTER PROPERTIES

Energy Technology Data Exchange (ETDEWEB)

Hoq, Sadia; Clemens, D. P., E-mail: shoq@bu.edu, E-mail: clemens@bu.edu [Institute for Astrophysical Research, 725 Commonwealth Avenue, Boston University, Boston, MA 02215 (United States)

2015-10-15

Stars in open clusters are powerful probes of the intervening Galactic magnetic field via background starlight polarimetry because they provide constraints on the magnetic field distances. We use 2MASS photometric data for a sample of 31 clusters in the outer Galaxy for which near-IR polarimetric data were obtained to determine the cluster distances, ages, and reddenings via fitting theoretical isochrones to cluster color–magnitude diagrams. The fitting approach uses an objective χ{sup 2} minimization technique to derive the cluster properties and their uncertainties. We found the ages, distances, and reddenings for 24 of the clusters, and the distances and reddenings for 6 additional clusters that were either sparse or faint in the near-IR. The derived ranges of log(age), distance, and E(B−V) were 7.25–9.63, ∼670–6160 pc, and 0.02–1.46 mag, respectively. The distance uncertainties ranged from ∼8% to 20%. The derived parameters were compared to previous studies, and most cluster parameters agree within our uncertainties. To test the accuracy of the fitting technique, synthetic clusters with 50, 100, or 200 cluster members and a wide range of ages were fit. These tests recovered the input parameters within their uncertainties for more than 90% of the individual synthetic cluster parameters. These results indicate that the fitting technique likely provides reliable estimates of cluster properties. The distances derived will be used in an upcoming study of the Galactic magnetic field in the outer Galaxy.

Sensitivity Sampling Over Dynamic Geometric Data Streams with Applications to $k$-Clustering

OpenAIRE

Song, Zhao; Yang, Lin F.; Zhong, Peilin

2018-01-01

Sensitivity based sampling is crucial for constructing nearly-optimal coreset for $k$-means / median clustering. In this paper, we provide a novel data structure that enables sensitivity sampling over a dynamic data stream, where points from a high dimensional discrete Euclidean space can be either inserted or deleted. Based on this data structure, we provide a one-pass coreset construction for $k$-means %and M-estimator clustering using space $\\widetilde{O}(k\\mathrm{poly}(d))$ over $d$-dimen...

AGN Clustering in the BAT Sample

Science.gov (United States)

Powell, Meredith; Cappelluti, Nico; Urry, Meg; Koss, Michael; BASS Team

2018-01-01

We characterize the environments of local growing supermassive black holes by measuring the clustering of AGN in the Swift-BAT Spectroscopic Survey (BASS). With 548 AGN in the redshift range 0.012MASS galaxies, we constrain the halo occupation distribution (HOD) of the full sample with unprecedented sensitivity, as well as in bins of obscuration with matched luminosity distributions. In doing so, we find that AGN tend to reside in galaxy groups, agreeing with previous studies of AGN throughout a large range of luminosity and redshift. We also find evidence that obscured AGN tend to reside in denser environments than unobscured AGN.

Extending cluster Lot Quality Assurance Sampling designs for surveillance programs

OpenAIRE

Hund, Lauren; Pagano, Marcello

2014-01-01

Lot quality assurance sampling (LQAS) has a long history of applications in industrial quality control. LQAS is frequently used for rapid surveillance in global health settings, with areas classified as poor or acceptable performance based on the binary classification of an indicator. Historically, LQAS surveys have relied on simple random samples from the population; however, implementing two-stage cluster designs for surveillance sampling is often more cost-effective than ...

SU(3) techniques for angular momentum projected matrix elements in multi-cluster problems

International Nuclear Information System (INIS)

Hecht, K.T.; Zahn, W.

1978-01-01

In the theory of integral transforms for the evaluation of the resonating group kernels needed for cluster model calculations, the evaluation of matrix elements in an angular momentum coupled basis has proved to be difficult for cluster problems involving more than two fragments. For multi-cluster wave functions SU(3) coupling and recoupling techniques can furnish a tool for the practical evaluation matrix elements in an angular momentum coupled basis if the several relative motion harmonic oscillator functions in Bargmann space have simple SU(3) coupling properties. The method is illustrated by a three-cluster problem, such as 12 C = α + α + α, involving three 1 S clusters. 2 references

Arrays of Size-Selected Metal Nanoparticles Formed by Cluster Ion Beam Technique

DEFF Research Database (Denmark)

Ceynowa, F. A.; Chirumamilla, Manohar; Zenin, Volodymyr

2018-01-01

Deposition of size-selected copper and silver nanoparticles (NPs) on polymers using cluster beam technique is studied. It is shown that ratio of particle embedment in the film can be controlled by simple thermal annealing. Combining electron beam lithography, cluster beam deposition, and heat...... with required configurations which can be applied for wave-guiding, resonators, in sensor technologies, and surface enhanced Raman scattering....

Critical evaluation of sample pretreatment techniques.

Science.gov (United States)

Hyötyläinen, Tuulia

2009-06-01

Sample preparation before chromatographic separation is the most time-consuming and error-prone part of the analytical procedure. Therefore, selecting and optimizing an appropriate sample preparation scheme is a key factor in the final success of the analysis, and the judicious choice of an appropriate procedure greatly influences the reliability and accuracy of a given analysis. The main objective of this review is to critically evaluate the applicability, disadvantages, and advantages of various sample preparation techniques. Particular emphasis is placed on extraction techniques suitable for both liquid and solid samples.

LENR BEC Clusters on and below Wires through Cavitation and Related Techniques

Science.gov (United States)

Stringham, Roger; Stringham, Julie

2011-03-01

During the last two years I have been working on BEC cluster densities deposited just under the surface of wires, using cavitation, and other techniques. If I get the concentration high enough before the clusters dissipate, in addition to cold fusion related excess heat (and other effects, including helium-4 formation) I anticipate that it may be possible to initiate transient forms of superconductivity at room temperature.

Newly introduced sample preparation techniques: towards miniaturization.

Science.gov (United States)

Costa, Rosaria

2014-01-01

Sampling and sample preparation are of crucial importance in an analytical procedure, representing quite often a source of errors. The technique chosen for the isolation of analytes greatly affects the success of a chemical determination. On the other hand, growing concerns about environmental and human safety, along with the introduction of international regulations for quality control, have moved the interest of scientists towards specific needs. Newly introduced sample preparation techniques are challenged to meet new criteria: (i) miniaturization, (ii) higher sensitivity and selectivity, and (iii) automation. In this survey, the most recent techniques introduced in the field of sample preparation will be described and discussed, along with many examples of applications.

Cluster chemical ionization for improved confidence level in sample identification by gas chromatography/mass spectrometry.

Science.gov (United States)

Fialkov, Alexander B; Amirav, Aviv

2003-01-01

Upon the supersonic expansion of helium mixed with vapor from an organic solvent (e.g. methanol), various clusters of the solvent with the sample molecules can be formed. As a result of 70 eV electron ionization of these clusters, cluster chemical ionization (cluster CI) mass spectra are obtained. These spectra are characterized by the combination of EI mass spectra of vibrationally cold molecules in the supersonic molecular beam (cold EI) with CI-like appearance of abundant protonated molecules, together with satellite peaks corresponding to protonated or non-protonated clusters of sample compounds with 1-3 solvent molecules. Like CI, cluster CI preferably occurs for polar compounds with high proton affinity. However, in contrast to conventional CI, for non-polar compounds or those with reduced proton affinity the cluster CI mass spectrum converges to that of cold EI. The appearance of a protonated molecule and its solvent cluster peaks, plus the lack of protonation and cluster satellites for prominent EI fragments, enable the unambiguous identification of the molecular ion. In turn, the insertion of the proper molecular ion into the NIST library search of the cold EI mass spectra eliminates those candidates with incorrect molecular mass and thus significantly increases the confidence level in sample identification. Furthermore, molecular mass identification is of prime importance for the analysis of unknown compounds that are absent in the library. Examples are given with emphasis on the cluster CI analysis of carbamate pesticides, high explosives and unknown samples, to demonstrate the usefulness of Supersonic GC/MS (GC/MS with supersonic molecular beam) in the analysis of these thermally labile compounds. Cluster CI is shown to be a practical ionization method, due to its ease-of-use and fast instrumental conversion between EI and cluster CI, which involves the opening of only one valve located at the make-up gas path. The ease-of-use of cluster CI is analogous

Cluster-sample surveys and lot quality assurance sampling to evaluate yellow fever immunisation coverage following a national campaign, Bolivia, 2007.

Science.gov (United States)

Pezzoli, Lorenzo; Pineda, Silvia; Halkyer, Percy; Crespo, Gladys; Andrews, Nick; Ronveaux, Olivier

2009-03-01

To estimate the yellow fever (YF) vaccine coverage for the endemic and non-endemic areas of Bolivia and to determine whether selected districts had acceptable levels of coverage (>70%). We conducted two surveys of 600 individuals (25 x 12 clusters) to estimate coverage in the endemic and non-endemic areas. We assessed 11 districts using lot quality assurance sampling (LQAS). The lot (district) sample was 35 individuals with six as decision value (alpha error 6% if true coverage 70%; beta error 6% if true coverage 90%). To increase feasibility, we divided the lots into five clusters of seven individuals; to investigate the effect of clustering, we calculated alpha and beta by conducting simulations where each cluster's true coverage was sampled from a normal distribution with a mean of 70% or 90% and standard deviations of 5% or 10%. Estimated coverage was 84.3% (95% CI: 78.9-89.7) in endemic areas, 86.8% (82.5-91.0) in non-endemic and 86.0% (82.8-89.1) nationally. LQAS showed that four lots had unacceptable coverage levels. In six lots, results were inconsistent with the estimated administrative coverage. The simulations suggested that the effect of clustering the lots is unlikely to have significantly increased the risk of making incorrect accept/reject decisions. Estimated YF coverage was high. Discrepancies between administrative coverage and LQAS results may be due to incorrect population data. Even allowing for clustering in LQAS, the statistical errors would remain low. Catch-up campaigns are recommended in districts with unacceptable coverage.

Precision of systematic and random sampling in clustered populations: habitat patches and aggregating organisms.

Science.gov (United States)

McGarvey, Richard; Burch, Paul; Matthews, Janet M

2016-01-01

Natural populations of plants and animals spatially cluster because (1) suitable habitat is patchy, and (2) within suitable habitat, individuals aggregate further into clusters of higher density. We compare the precision of random and systematic field sampling survey designs under these two processes of species clustering. Second, we evaluate the performance of 13 estimators for the variance of the sample mean from a systematic survey. Replicated simulated surveys, as counts from 100 transects, allocated either randomly or systematically within the study region, were used to estimate population density in six spatial point populations including habitat patches and Matérn circular clustered aggregations of organisms, together and in combination. The standard one-start aligned systematic survey design, a uniform 10 x 10 grid of transects, was much more precise. Variances of the 10 000 replicated systematic survey mean densities were one-third to one-fifth of those from randomly allocated transects, implying transect sample sizes giving equivalent precision by random survey would need to be three to five times larger. Organisms being restricted to patches of habitat was alone sufficient to yield this precision advantage for the systematic design. But this improved precision for systematic sampling in clustered populations is underestimated by standard variance estimators used to compute confidence intervals. True variance for the survey sample mean was computed from the variance of 10 000 simulated survey mean estimates. Testing 10 published and three newly proposed variance estimators, the two variance estimators (v) that corrected for inter-transect correlation (ν₈ and ν(W)) were the most accurate and also the most precise in clustered populations. These greatly outperformed the two "post-stratification" variance estimators (ν₂ and ν₃) that are now more commonly applied in systematic surveys. Similar variance estimator performance rankings were found with

Adaptive swarm cluster-based dynamic multi-objective synthetic minority oversampling technique algorithm for tackling binary imbalanced datasets in biomedical data classification.

Science.gov (United States)

Li, Jinyan; Fong, Simon; Sung, Yunsick; Cho, Kyungeun; Wong, Raymond; Wong, Kelvin K L

2016-01-01

An imbalanced dataset is defined as a training dataset that has imbalanced proportions of data in both interesting and uninteresting classes. Often in biomedical applications, samples from the stimulating class are rare in a population, such as medical anomalies, positive clinical tests, and particular diseases. Although the target samples in the primitive dataset are small in number, the induction of a classification model over such training data leads to poor prediction performance due to insufficient training from the minority class. In this paper, we use a novel class-balancing method named adaptive swarm cluster-based dynamic multi-objective synthetic minority oversampling technique (ASCB_DmSMOTE) to solve this imbalanced dataset problem, which is common in biomedical applications. The proposed method combines under-sampling and over-sampling into a swarm optimisation algorithm. It adaptively selects suitable parameters for the rebalancing algorithm to find the best solution. Compared with the other versions of the SMOTE algorithm, significant improvements, which include higher accuracy and credibility, are observed with ASCB_DmSMOTE. Our proposed method tactfully combines two rebalancing techniques together. It reasonably re-allocates the majority class in the details and dynamically optimises the two parameters of SMOTE to synthesise a reasonable scale of minority class for each clustered sub-imbalanced dataset. The proposed methods ultimately overcome other conventional methods and attains higher credibility with even greater accuracy of the classification model.

Planck/SDSS Cluster Mass and Gas Scaling Relations for a Volume-Complete redMaPPer Sample

Science.gov (United States)

Jimeno, Pablo; Diego, Jose M.; Broadhurst, Tom; De Martino, I.; Lazkoz, Ruth

2018-04-01

Using Planck satellite data, we construct Sunyaev-Zel'dovich (SZ) gas pressure profiles for a large, volume-complete sample of optically selected clusters. We have defined a sample of over 8,000 redMaPPer clusters from the Sloan Digital Sky Survey (SDSS), within the volume-complete redshift region 0.100 trend towards larger break radius with increasing cluster mass. Our SZ-based masses fall ˜16% below the mass-richness relations from weak lensing, in a similar fashion as the "hydrostatic bias" related with X-ray derived masses. Finally, we derive a tight Y500-M500 relation over a wide range of cluster mass, with a power law slope equal to 1.70 ± 0.07, that agrees well with the independent slope obtained by the Planck team with an SZ-selected cluster sample, but extends to lower masses with higher precision.

The ellipticities of a sample of globular clusters in M31

International Nuclear Information System (INIS)

Lupton, R.H.

1989-01-01

Images for a sample of 18 globular clusters in M31 have been obtained. The mean ellipticity on the sky in the range 7-14 pc (2-4 arcsec) is 0.08 + or - 0.02 and 0.12 + or - 0.01 in the range 14-21 pc (4-6 arcsec), with corresponding true ellipticities of 0.12 and 0.18. The difference between the inner and outer parts is significant at a 99 percent level. The flattening of the inner parts is statistically indistinguishable from that of the Galactic globular clusters, while the outer parts are flatter than the Galactic clusters at a 99.8 percent confidence level. There is a significant anticorrelation of ellipticity with line strength; such a correlation may in retrospect also be seen in the Galactic globular cluster system. For the M31 data, this anticorrelation is stronger in the inner parts of the galaxy. 30 refs

Comparison of sampling techniques for use in SYVAC

International Nuclear Information System (INIS)

Dalrymple, G.J.

1984-01-01

The Stephen Howe review (reference TR-STH-1) recommended the use of a deterministic generator (DG) sampling technique for sampling the input values to the SYVAC (SYstems Variability Analysis Code) program. This technique was compared with Monte Carlo simple random sampling (MC) by taking a 1000 run case of SYVAC using MC as the reference case. The results show that DG appears relatively inaccurate for most values of consequence when used with 11 sample intervals. If 22 sample intervals are used then DG generates cumulative distribution functions that are statistically similar to the reference distribution. 400 runs of DG or MC are adequate to generate a representative cumulative distribution function. The MC technique appears to perform better than DG for the same number of runs. However, the DG predicts higher doses and in view of the importance of generating data in the high dose region this sampling technique with 22 sample intervals is recommended for use in SYVAC. (author)

Trace uranium analysis in Indian coal samples using the fission track technique

International Nuclear Information System (INIS)

Jojo, P.J.; Rawat, A.; Kumar, Ashavani; Prasad, Rajendra

1993-01-01

The ever-growing demand for energy has resulted in the extensive use of fossil fuels, especially coal, for power generation. Coal and its by-products often contain significant amounts of radionuclides, including uranium, which is the ultimate source of the radioactive gas Radon-222. The present study gives the concentration of uranium in coal samples of different collieries in India, collected from various thermal power plants in the state of Uttar Pradesh. The estimates were made using the fission track technique. Latent damage tracks were not found to be uniformly distributed but showed sun bursts and clusters. Non-uniform distributions of trace elements are a very common phenomenon in rocks. The levels of uranium in the coal samples were found to vary from 2.0 to 4.9 ppm in uniform distributions and from 21.3 to 41.0 ppm in non-uniform distributions. Measurements were also made on fly ash samples where the average uranium concentration was found to be 8.4 and 49.3 ppm in uniform and non-uniform distributions, respectively. (author)

K-means-clustering-based fiber nonlinearity equalization techniques for 64-QAM coherent optical communication system.

Science.gov (United States)

Zhang, Junfeng; Chen, Wei; Gao, Mingyi; Shen, Gangxiang

2017-10-30

In this work, we proposed two k-means-clustering-based algorithms to mitigate the fiber nonlinearity for 64-quadrature amplitude modulation (64-QAM) signal, the training-sequence assisted k-means algorithm and the blind k-means algorithm. We experimentally demonstrated the proposed k-means-clustering-based fiber nonlinearity mitigation techniques in 75-Gb/s 64-QAM coherent optical communication system. The proposed algorithms have reduced clustering complexity and low data redundancy and they are able to quickly find appropriate initial centroids and select correctly the centroids of the clusters to obtain the global optimal solutions for large k value. We measured the bit-error-ratio (BER) performance of 64-QAM signal with different launched powers into the 50-km single mode fiber and the proposed techniques can greatly mitigate the signal impairments caused by the amplified spontaneous emission noise and the fiber Kerr nonlinearity and improve the BER performance.

Proteomic Challenges: Sample Preparation Techniques for Microgram-Quantity Protein Analysis from Biological Samples

Directory of Open Access Journals (Sweden)

Peter Feist

2015-02-01

Full Text Available Proteins regulate many cellular functions and analyzing the presence and abundance of proteins in biological samples are central focuses in proteomics. The discovery and validation of biomarkers, pathways, and drug targets for various diseases can be accomplished using mass spectrometry-based proteomics. However, with mass-limited samples like tumor biopsies, it can be challenging to obtain sufficient amounts of proteins to generate high-quality mass spectrometric data. Techniques developed for macroscale quantities recover sufficient amounts of protein from milligram quantities of starting material, but sample losses become crippling with these techniques when only microgram amounts of material are available. To combat this challenge, proteomicists have developed micro-scale techniques that are compatible with decreased sample size (100 μg or lower and still enable excellent proteome coverage. Extraction, contaminant removal, protein quantitation, and sample handling techniques for the microgram protein range are reviewed here, with an emphasis on liquid chromatography and bottom-up mass spectrometry-compatible techniques. Also, a range of biological specimens, including mammalian tissues and model cell culture systems, are discussed.

Proteomic Challenges: Sample Preparation Techniques for Microgram-Quantity Protein Analysis from Biological Samples

Science.gov (United States)

Feist, Peter; Hummon, Amanda B.

2015-01-01

Proteins regulate many cellular functions and analyzing the presence and abundance of proteins in biological samples are central focuses in proteomics. The discovery and validation of biomarkers, pathways, and drug targets for various diseases can be accomplished using mass spectrometry-based proteomics. However, with mass-limited samples like tumor biopsies, it can be challenging to obtain sufficient amounts of proteins to generate high-quality mass spectrometric data. Techniques developed for macroscale quantities recover sufficient amounts of protein from milligram quantities of starting material, but sample losses become crippling with these techniques when only microgram amounts of material are available. To combat this challenge, proteomicists have developed micro-scale techniques that are compatible with decreased sample size (100 μg or lower) and still enable excellent proteome coverage. Extraction, contaminant removal, protein quantitation, and sample handling techniques for the microgram protein range are reviewed here, with an emphasis on liquid chromatography and bottom-up mass spectrometry-compatible techniques. Also, a range of biological specimens, including mammalian tissues and model cell culture systems, are discussed. PMID:25664860

Proteomic challenges: sample preparation techniques for microgram-quantity protein analysis from biological samples.

Science.gov (United States)

Feist, Peter; Hummon, Amanda B

2015-02-05

Proteins regulate many cellular functions and analyzing the presence and abundance of proteins in biological samples are central focuses in proteomics. The discovery and validation of biomarkers, pathways, and drug targets for various diseases can be accomplished using mass spectrometry-based proteomics. However, with mass-limited samples like tumor biopsies, it can be challenging to obtain sufficient amounts of proteins to generate high-quality mass spectrometric data. Techniques developed for macroscale quantities recover sufficient amounts of protein from milligram quantities of starting material, but sample losses become crippling with these techniques when only microgram amounts of material are available. To combat this challenge, proteomicists have developed micro-scale techniques that are compatible with decreased sample size (100 μg or lower) and still enable excellent proteome coverage. Extraction, contaminant removal, protein quantitation, and sample handling techniques for the microgram protein range are reviewed here, with an emphasis on liquid chromatography and bottom-up mass spectrometry-compatible techniques. Also, a range of biological specimens, including mammalian tissues and model cell culture systems, are discussed.

NAIL SAMPLING TECHNIQUE AND ITS INTERPRETATION

Directory of Open Access Journals (Sweden)

TZAR MN

2011-01-01

Full Text Available The clinical suspicion of onychomyosis based on appearance of the nails, requires culture for confirmation. This is because treatment requires prolonged use of systemic agents which may cause side effects. One of the common problems encountered is improper nail sampling technique which results in loss of essential information. The unfamiliar terminologies used in reporting culture results may intimidate physicians resulting in misinterpretation and hamper treatment decision. This article provides a simple guide on nail sampling technique and the interpretation of culture results.

Statistical uncertainty of extreme wind storms over Europe derived from a probabilistic clustering technique

Science.gov (United States)

Walz, Michael; Leckebusch, Gregor C.

2016-04-01

Extratropical wind storms pose one of the most dangerous and loss intensive natural hazards for Europe. However, due to only 50 years of high quality observational data, it is difficult to assess the statistical uncertainty of these sparse events just based on observations. Over the last decade seasonal ensemble forecasts have become indispensable in quantifying the uncertainty of weather prediction on seasonal timescales. In this study seasonal forecasts are used in a climatological context: By making use of the up to 51 ensemble members, a broad and physically consistent statistical base can be created. This base can then be used to assess the statistical uncertainty of extreme wind storm occurrence more accurately. In order to determine the statistical uncertainty of storms with different paths of progression, a probabilistic clustering approach using regression mixture models is used to objectively assign storm tracks (either based on core pressure or on extreme wind speeds) to different clusters. The advantage of this technique is that the entire lifetime of a storm is considered for the clustering algorithm. Quadratic curves are found to describe the storm tracks most accurately. Three main clusters (diagonal, horizontal or vertical progression of the storm track) can be identified, each of which have their own particulate features. Basic storm features like average velocity and duration are calculated and compared for each cluster. The main benefit of this clustering technique, however, is to evaluate if the clusters show different degrees of uncertainty, e.g. more (less) spread for tracks approaching Europe horizontally (diagonally). This statistical uncertainty is compared for different seasonal forecast products.

Development of sampling techniques for ITER Type B radwaste

International Nuclear Information System (INIS)

Hong, Kwon Pyo; Kim, Sung Geun; Jung, Sang Hee; Oh, Wan Ho; Park, Myung Chul; Kim, Hee Moon; Ahn, Sang Bok

2016-01-01

There are several difficulties and limitation in sampling activities. As the Type B radwaste components are mostly metallic(mostly stainless steel) and bulk(∼ 1 m in size and ∼ 100 mm in thickness), it is difficult in taking samples from the surface of Type B radwaste by remote operation. But also, sampling should be performed without use of any liquid coolant to avoid the spread of contamination. And all sampling procedures are carried in the hot cell red zone with remote operation. Three kinds of sampling techniques are being developed. They are core sampling, chip sampling, and wedge sampling, which are the candidates of sampling techniques to be applied to ITER hot cell. Object materials for sampling are stainless steel or Cu alloy block in order to simulate ITER Type B radwaste. The best sampling technique for ITER Type B radwaste among the three sampling techniques will be suggested in several months after finishing the related experiment

Development of sampling techniques for ITER Type B radwaste

Energy Technology Data Exchange (ETDEWEB)

Hong, Kwon Pyo; Kim, Sung Geun; Jung, Sang Hee; Oh, Wan Ho; Park, Myung Chul; Kim, Hee Moon; Ahn, Sang Bok [KAERI, Daejeon (Korea, Republic of)

2016-05-15

There are several difficulties and limitation in sampling activities. As the Type B radwaste components are mostly metallic(mostly stainless steel) and bulk(∼ 1 m in size and ∼ 100 mm in thickness), it is difficult in taking samples from the surface of Type B radwaste by remote operation. But also, sampling should be performed without use of any liquid coolant to avoid the spread of contamination. And all sampling procedures are carried in the hot cell red zone with remote operation. Three kinds of sampling techniques are being developed. They are core sampling, chip sampling, and wedge sampling, which are the candidates of sampling techniques to be applied to ITER hot cell. Object materials for sampling are stainless steel or Cu alloy block in order to simulate ITER Type B radwaste. The best sampling technique for ITER Type B radwaste among the three sampling techniques will be suggested in several months after finishing the related experiment.

Boat sampling technique for assessment of ageing of components

International Nuclear Information System (INIS)

Kumar, Kundan; Shyam, T.V.; Kayal, J.N.; Rupani, B.B.

2006-01-01

Boat sampling technique (BST) is a surface sampling technique, which has been developed for obtaining, in-situ, metal samples from the surface of an operating component without affecting its operating service life. The BST is non-destructive in nature and the sample is obtained without plastic deformation or without thermal degradation of the parent material. The shape and size of the sample depends upon the shape of the cutter and the surface geometry of the parent material. Miniature test specimens are generated from the sample and the specimens are subjected to various tests, viz. Metallurgical Evaluation, Metallographic Evaluation, Micro-hardness Evaluation, sensitisation test, small punch test etc. to confirm the integrity and assessment of safe operating life of the component. This paper highlights design objective of boat sampling technique, description of sampling module, sampling cutter and its performance evaluation, cutting process, boat samples, operational sequence of sampling module, qualification of sampling module, qualification of sampling technique, qualification of scooped region of the parent material, sample retrieval system, inspection, testing and examination to be carried out on the boat samples and scooped region. (author)

Planck early results. VIII. The all-sky early Sunyaev-Zeldovich cluster sample

DEFF Research Database (Denmark)

Poutanen, T.; Natoli, P.; Polenta, G.

2011-01-01

We present the first all-sky sample of galaxy clusters detected blindly by the Planck satellite through the Sunyaev-Zeldovich (SZ) effect from its six highest frequencies. This early SZ (ESZ) sample is comprised of 189 candidates, which have a high signal-to-noise ratio ranging from 6 to 29. Its ...

Urine sampling techniques in symptomatic primary-care patients

DEFF Research Database (Denmark)

Holm, Anne; Aabenhus, Rune

2016-01-01

in infection rate between mid-stream-clean-catch, mid-stream-urine and random samples. Conclusions: At present, no evidence suggests that sampling technique affects the accuracy of the microbiological diagnosis in non-pregnant women with symptoms of urinary tract infection in primary care. However......Background: Choice of urine sampling technique in urinary tract infection may impact diagnostic accuracy and thus lead to possible over- or undertreatment. Currently no evidencebased consensus exists regarding correct sampling technique of urine from women with symptoms of urinary tract infection...... a randomized or paired design to compare the result of urine culture obtained with two or more collection techniques in adult, female, non-pregnant patients with symptoms of urinary tract infection. We evaluated quality of the studies and compared accuracy based on dichotomized outcomes. Results: We included...

Poly(methyl methacrylate) Composites with Size-selected Silver Nanoparticles Fabricated Using Cluster Beam Technique

DEFF Research Database (Denmark)

Muhammad, Hanif; Juluri, Raghavendra R.; Chirumamilla, Manohar

2016-01-01

based on cluster beam technique allowing the formation of monocrystalline size-selected silver nanoparticles with a ±5–7% precision of diameter and controllable embedment into poly (methyl methacrylate). It is shown that the soft-landed silver clusters preserve almost spherical shape with a slight...... tendency to flattening upon impact. By controlling the polymer hardness (from viscous to soft state) prior the cluster deposition and annealing conditions after the deposition the degree of immersion of the nanoparticles into polymer can be tuned, thus, making it possible to create composites with either...

Clustered lot quality assurance sampling: a tool to monitor immunization coverage rapidly during a national yellow fever and polio vaccination campaign in Cameroon, May 2009.

Science.gov (United States)

Pezzoli, L; Tchio, R; Dzossa, A D; Ndjomo, S; Takeu, A; Anya, B; Ticha, J; Ronveaux, O; Lewis, R F

2012-01-01

We used the clustered lot quality assurance sampling (clustered-LQAS) technique to identify districts with low immunization coverage and guide mop-up actions during the last 4 days of a combined oral polio vaccine (OPV) and yellow fever (YF) vaccination campaign conducted in Cameroon in May 2009. We monitored 17 pre-selected districts at risk for low coverage. We designed LQAS plans to reject districts with YF vaccination coverage LQAS proved to be useful in guiding the campaign vaccination strategy before the completion of the operations.

Time-of-flight secondary ion mass spectrometry of a range of coal samples: a chemometrics (PCA, cluster, and PLS) analysis

Energy Technology Data Exchange (ETDEWEB)

Lei Pei; Guilin Jiang; Bonnie J. Tyler; Larry L. Baxter; Matthew R. Linford [Brigham Young University, Provo, UT (United States). Department of Chemistry and Biochemistry

2008-03-15

This paper documents time-of-flight secondary ion mass spectrometry (ToF-SIMS) analyses of 34 different coal samples. In many cases, the inorganic Na{sup +}, Al{sup +}, Si{sup +}, and K{sup +} ions dominate the spectra, eclipsing the organic peaks. A scores plot of principal component 1 (PC1) versus principal component 2 (PC2) in a principal components analysis (PCA) effectively separates the coal spectra into a triangular pattern, where the different vertices of this pattern come from (I) spectra that have a strong inorganic signature that is dominated by Na{sup +}, (ii) spectra that have a strong inorganic signature that is dominated by Al{sup +}, Si{sup +}, and K{sup +}, and (iii) spectra that have a strong organic signature. Loadings plots of PC1 and PC2 confirm these observations. The spectra with the more prominent inorganic signatures come from samples with higher ash contents. Cluster analysis with the K-means algorithm was also applied to the data. The progressive clustering revealed in the dendrogram correlates extremely well with the clustering of the data points found in the scores plot of PC1 versus PC2 from the PCA. In addition, this clustering often correlates with properties of the coal samples, as measured by traditional analyses. Partial least-squares (PLS), which included the use of interval PLS and a genetic algorithm for variable selection, shows a good correlation between ToF-SIMS spectra and some of the properties measured by traditional means. Thus, ToF-SIMS appears to be a promising technique for the analysis of this important fuel. 33 refs., 9 figs., 5 tabs.

Non-terminal blood sampling techniques in guinea pigs.

Science.gov (United States)

Birck, Malene M; Tveden-Nyborg, Pernille; Lindblad, Maiken M; Lykkesfeldt, Jens

2014-10-11

Guinea pigs possess several biological similarities to humans and are validated experimental animal models(1-3). However, the use of guinea pigs currently represents a relatively narrow area of research and descriptive data on specific methodology is correspondingly scarce. The anatomical features of guinea pigs are slightly different from other rodent models, hence modulation of sampling techniques to accommodate for species-specific differences, e.g., compared to mice and rats, are necessary to obtain sufficient and high quality samples. As both long and short term in vivo studies often require repeated blood sampling the choice of technique should be well considered in order to reduce stress and discomfort in the animals but also to ensure survival as well as compliance with requirements of sample size and accessibility. Venous blood samples can be obtained at a number of sites in guinea pigs e.g., the saphenous and jugular veins, each technique containing both advantages and disadvantages(4,5). Here, we present four different blood sampling techniques for either conscious or anaesthetized guinea pigs. The procedures are all non-terminal procedures provided that sample volumes and number of samples do not exceed guidelines for blood collection in laboratory animals(6). All the described methods have been thoroughly tested and applied for repeated in vivo blood sampling in studies within our research facility.

Medical Image Retrieval Based On the Parallelization of the Cluster Sampling Algorithm

OpenAIRE

Ali, Hesham Arafat; Attiya, Salah; El-henawy, Ibrahim

2017-01-01

In this paper we develop parallel cluster sampling algorithms and show that a multi-chain version is embarrassingly parallel and can be used efficiently for medical image retrieval among other applications.

Clustering problems for geochemical data

International Nuclear Information System (INIS)

Kane, V.E.; Larson, N.M.

1977-01-01

The Union Carbide Corporation, Nuclear Division, Uranium Resource Evaluation Project uses a two-stage sampling program to identify potential uranium districts. Cluster analysis techniques are used in locating high density sampling areas as well as in identifying potential uranium districts. Problems are considered involving the analysis of multivariate censored data, laboratory measurement error, and data standardization

Identification of Clusters of Foot Pain Location in a Community Sample.

Science.gov (United States)

Gill, Tiffany K; Menz, Hylton B; Landorf, Karl B; Arnold, John B; Taylor, Anne W; Hill, Catherine L

2017-12-01

To identify foot pain clusters according to pain location in a community-based sample of the general population. This study analyzed data from the North West Adelaide Health Study. Data were obtained between 2004 and 2006, using computer-assisted telephone interviewing, clinical assessment, and self-completed questionnaire. The location of foot pain was assessed using a diagram during the clinical assessment. Hierarchical cluster analysis was undertaken to identify foot pain location clusters, which were then compared in relation to demographics, comorbidities, and podiatry services utilization. There were 558 participants with foot pain (mean age 54.4 years, 57.5% female). Five clusters were identified: 1 with predominantly arch and ball pain (26.8%), 1 with rearfoot pain (20.9%), 1 with heel pain (13.3%), and 2 with predominantly forefoot, toe, and nail pain (28.3% and 10.7%). Each cluster was distinct in age, sex, and comorbidity profile. Of the two clusters with predominantly forefoot, toe, and nail pain, one of them had a higher proportion of men and those classified as obese, had diabetes mellitus, and used podiatry services (30%), while the other was comprised of a higher proportion of women who were overweight and reported less use of podiatry services (17.5%). Five clusters of foot pain according to pain location were identified, all with distinct age, sex, and comorbidity profiles. These findings may assist in the identification of individuals at risk for developing foot pain and in the development of targeted preventive strategies and treatments. © 2017, American College of Rheumatology.

Electric field measurements on Cluster: comparing the double-probe and electron drift techniques

Directory of Open Access Journals (Sweden)

A. I. Eriksson

2006-03-01

Full Text Available The four Cluster satellites each carry two instruments designed for measuring the electric field: a double-probe instrument (EFW and an electron drift instrument (EDI. We compare data from the two instruments in a representative sample of plasma regions. The complementary merits and weaknesses of the two techniques are illustrated. EDI operations are confined to regions of magnetic fields above 30 nT and where wave activity and keV electron fluxes are not too high, while EFW can provide data everywhere, and can go far higher in sampling frequency than EDI. On the other hand, the EDI technique is immune to variations in the low energy plasma, while EFW sometimes detects significant nongeophysical electric fields, particularly in regions with drifting plasma, with ion energy (in eV below the spacecraft potential (in volts. We show that the polar cap is a particularly intricate region for the double-probe technique, where large nongeophysical fields regularly contaminate EFW measurments of the DC electric field. We present a model explaining this in terms of enhanced cold plasma wake effects appearing when the ion flow energy is higher than the thermal energy but below the spacecraft potential multiplied by the ion charge. We suggest that these conditions, which are typical of the polar wind and occur sporadically in other regions containing a significant low energy ion population, cause a large cold plasma wake behind the spacecraft, resulting in spurious electric fields in EFW data. This interpretation is supported by an analysis of the direction of the spurious electric field, and by showing that use of active potential control alleviates the situation.

A Comparison of Alternative Distributed Dynamic Cluster Formation Techniques for Industrial Wireless Sensor Networks.

Science.gov (United States)

Gholami, Mohammad; Brennan, Robert W

2016-01-06

In this paper, we investigate alternative distributed clustering techniques for wireless sensor node tracking in an industrial environment. The research builds on extant work on wireless sensor node clustering by reporting on: (1) the development of a novel distributed management approach for tracking mobile nodes in an industrial wireless sensor network; and (2) an objective comparison of alternative cluster management approaches for wireless sensor networks. To perform this comparison, we focus on two main clustering approaches proposed in the literature: pre-defined clusters and ad hoc clusters. These approaches are compared in the context of their reconfigurability: more specifically, we investigate the trade-off between the cost and the effectiveness of competing strategies aimed at adapting to changes in the sensing environment. To support this work, we introduce three new metrics: a cost/efficiency measure, a performance measure, and a resource consumption measure. The results of our experiments show that ad hoc clusters adapt more readily to changes in the sensing environment, but this higher level of adaptability is at the cost of overall efficiency.

Distributed cluster management techniques for unattended ground sensor networks

Science.gov (United States)

Essawy, Magdi A.; Stelzig, Chad A.; Bevington, James E.; Minor, Sharon

2005-05-01

Smart Sensor Networks are becoming important target detection and tracking tools. The challenging problems in such networks include the sensor fusion, data management and communication schemes. This work discusses techniques used to distribute sensor management and multi-target tracking responsibilities across an ad hoc, self-healing cluster of sensor nodes. Although miniaturized computing resources possess the ability to host complex tracking and data fusion algorithms, there still exist inherent bandwidth constraints on the RF channel. Therefore, special attention is placed on the reduction of node-to-node communications within the cluster by minimizing unsolicited messaging, and distributing the sensor fusion and tracking tasks onto local portions of the network. Several challenging problems are addressed in this work including track initialization and conflict resolution, track ownership handling, and communication control optimization. Emphasis is also placed on increasing the overall robustness of the sensor cluster through independent decision capabilities on all sensor nodes. Track initiation is performed using collaborative sensing within a neighborhood of sensor nodes, allowing each node to independently determine if initial track ownership should be assumed. This autonomous track initiation prevents the formation of duplicate tracks while eliminating the need for a central "management" node to assign tracking responsibilities. Track update is performed as an ownership node requests sensor reports from neighboring nodes based on track error covariance and the neighboring nodes geo-positional location. Track ownership is periodically recomputed using propagated track states to determine which sensing node provides the desired coverage characteristics. High fidelity multi-target simulation results are presented, indicating the distribution of sensor management and tracking capabilities to not only reduce communication bandwidth consumption, but to also

Differences in sampling techniques on total post-mortem tryptase.

Science.gov (United States)

Tse, R; Garland, J; Kesha, K; Elstub, H; Cala, A D; Ahn, Y; Stables, S; Palmiere, C

2017-11-20

The measurement of mast cell tryptase is commonly used to support the diagnosis of anaphylaxis. In the post-mortem setting, the literature recommends sampling from peripheral blood sources (femoral blood) but does not specify the exact sampling technique. Sampling techniques vary between pathologists, and it is unclear whether different sampling techniques have any impact on post-mortem tryptase levels. The aim of this study is to compare the difference in femoral total post-mortem tryptase levels between two sampling techniques. A 6-month retrospective study comparing femoral total post-mortem tryptase levels between (1) aspirating femoral vessels with a needle and syringe prior to evisceration and (2) femoral vein cut down during evisceration. Twenty cases were identified, with three cases excluded from analysis. There was a statistically significant difference (paired t test, p sampling methods. The clinical significance of this finding and what factors may contribute to it are unclear. When requesting post-mortem tryptase, the pathologist should consider documenting the exact blood collection site and method used for collection. In addition, blood samples acquired by different techniques should not be mixed together and should be analyzed separately if possible.

Microextraction sample preparation techniques in biomedical analysis.

Science.gov (United States)

Szultka, Malgorzata; Pomastowski, Pawel; Railean-Plugaru, Viorica; Buszewski, Boguslaw

2014-11-01

Biologically active compounds are found in biological samples at relatively low concentration levels. The sample preparation of target compounds from biological, pharmaceutical, environmental, and food matrices is one of the most time-consuming steps in the analytical procedure. The microextraction techniques are dominant. Metabolomic studies also require application of proper analytical technique for the determination of endogenic metabolites present in biological matrix on trace concentration levels. Due to the reproducibility of data, precision, relatively low cost of the appropriate analysis, simplicity of the determination, and the possibility of direct combination of those techniques with other methods (combination types on-line and off-line), they have become the most widespread in routine determinations. Additionally, sample pretreatment procedures have to be more selective, cheap, quick, and environmentally friendly. This review summarizes the current achievements and applications of microextraction techniques. The main aim is to deal with the utilization of different types of sorbents for microextraction and emphasize the use of new synthesized sorbents as well as to bring together studies concerning the systematic approach to method development. This review is dedicated to the description of microextraction techniques and their application in biomedical analysis. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

X-Ray Temperatures, Luminosities, and Masses from XMM-Newton Follow-up of the First Shear-selected Galaxy Cluster Sample

Energy Technology Data Exchange (ETDEWEB)

Deshpande, Amruta J.; Hughes, John P. [Department of Physics and Astronomy, Rutgers the State University of New Jersey, 136 Frelinghuysen Road, Piscataway, NJ 08854 (United States); Wittman, David, E-mail: amrejd@physics.rutgers.edu, E-mail: jph@physics.rutgers.edu, E-mail: dwittman@physics.ucdavis.edu [Department of Physics, University of California, Davis, One Shields Avenue, Davis, CA 95616 (United States)

2017-04-20

We continue the study of the first sample of shear-selected clusters from the initial 8.6 square degrees of the Deep Lens Survey (DLS); a sample with well-defined selection criteria corresponding to the highest ranked shear peaks in the survey area. We aim to characterize the weak lensing selection by examining the sample’s X-ray properties. There are multiple X-ray clusters associated with nearly all the shear peaks: 14 X-ray clusters corresponding to seven DLS shear peaks. An additional three X-ray clusters cannot be definitively associated with shear peaks, mainly due to large positional offsets between the X-ray centroid and the shear peak. Here we report on the XMM-Newton properties of the 17 X-ray clusters. The X-ray clusters display a wide range of luminosities and temperatures; the L {sub X} − T {sub X} relation we determine for the shear-associated X-ray clusters is consistent with X-ray cluster samples selected without regard to dynamical state, while it is inconsistent with self-similarity. For a subset of the sample, we measure X-ray masses using temperature as a proxy, and compare to weak lensing masses determined by the DLS team. The resulting mass comparison is consistent with equality. The X-ray and weak lensing masses show considerable intrinsic scatter (∼48%), which is consistent with X-ray selected samples when their X-ray and weak lensing masses are independently determined.

Percolation technique for galaxy clustering

Science.gov (United States)

Klypin, Anatoly; Shandarin, Sergei F.

1993-01-01

We study percolation in mass and galaxy distributions obtained in 3D simulations of the CDM, C + HDM, and the power law (n = -1) models in the Omega = 1 universe. Percolation statistics is used here as a quantitative measure of the degree to which a mass or galaxy distribution is of a filamentary or cellular type. The very fast code used calculates the statistics of clusters along with the direct detection of percolation. We found that the two parameters mu(infinity), characterizing the size of the largest cluster, and mu-squared, characterizing the weighted mean size of all clusters excluding the largest one, are extremely useful for evaluating the percolation threshold. An advantage of using these parameters is their low sensitivity to boundary effects. We show that both the CDM and the C + HDM models are extremely filamentary both in mass and galaxy distribution. The percolation thresholds for the mass distributions are determined.

A neural network clustering algorithm for the ATLAS silicon pixel detector

CERN Document Server

Aad, Georges; Abdallah, Jalal; Abdel Khalek, Samah; Abdinov, Ovsat; Aben, Rosemarie; Abi, Babak; Abolins, Maris; AbouZeid, Ossama; Abramowicz, Halina; Abreu, Henso; Abreu, Ricardo; Abulaiti, Yiming; Acharya, Bobby Samir; Adamczyk, Leszek; Adams, David; Adelman, Jahred; Adomeit, Stefanie; Adye, Tim; Agatonovic-Jovin, Tatjana; Aguilar-Saavedra, Juan Antonio; Agustoni, Marco; Ahlen, Steven; Ahmadov, Faig; Aielli, Giulio; Akerstedt, Henrik; Åkesson, Torsten Paul Ake; Akimoto, Ginga; Akimov, Andrei; Alberghi, Gian Luigi; Albert, Justin; Albrand, Solveig; Alconada Verzini, Maria Josefina; Aleksa, Martin; Aleksandrov, Igor; Alexa, Calin; Alexander, Gideon; Alexandre, Gauthier; Alexopoulos, Theodoros; Alhroob, Muhammad; Alimonti, Gianluca; Alio, Lion; Alison, John; Allbrooke, Benedict; Allison, Lee John; Allport, Phillip; Almond, John; Aloisio, Alberto; Alonso, Alejandro; Alonso, Francisco; Alpigiani, Cristiano; Altheimer, Andrew David; Alvarez Gonzalez, Barbara; Alviggi, Mariagrazia; Amako, Katsuya; Amaral Coutinho, Yara; Amelung, Christoph; Amidei, Dante; Amor Dos Santos, Susana Patricia; Amorim, Antonio; Amoroso, Simone; Amram, Nir; Amundsen, Glenn; Anastopoulos, Christos; Ancu, Lucian Stefan; Andari, Nansi; Andeen, Timothy; Anders, Christoph Falk; Anders, Gabriel; Anderson, Kelby; Andreazza, Attilio; Andrei, George Victor; Anduaga, Xabier; Angelidakis, Stylianos; Angelozzi, Ivan; Anger, Philipp; Angerami, Aaron; Anghinolfi, Francis; Anisenkov, Alexey; Anjos, Nuno; Annovi, Alberto; Antonaki, Ariadni; Antonelli, Mario; Antonov, Alexey; Antos, Jaroslav; Anulli, Fabio; Aoki, Masato; Aperio Bella, Ludovica; Apolle, Rudi; Arabidze, Giorgi; Aracena, Ignacio; Arai, Yasuo; Araque, Juan Pedro; Arce, Ayana; Arguin, Jean-Francois; Argyropoulos, Spyridon; Arik, Metin; Armbruster, Aaron James; Arnaez, Olivier; Arnal, Vanessa; Arnold, Hannah; Arratia, Miguel; Arslan, Ozan; Artamonov, Andrei; Artoni, Giacomo; Asai, Shoji; Asbah, Nedaa; Ashkenazi, Adi; Åsman, Barbro; Asquith, Lily; Assamagan, Ketevi; Astalos, Robert; Atkinson, Markus; Atlay, Naim Bora; Auerbach, Benjamin; Augsten, Kamil; Aurousseau, Mathieu; Avolio, Giuseppe; Azuelos, Georges; Azuma, Yuya; Baak, Max; Baas, Alessandra; Bacci, Cesare; Bachacou, Henri; Bachas, Konstantinos; Backes, Moritz; Backhaus, Malte; Backus Mayes, John; Badescu, Elisabeta; Bagiacchi, Paolo; Bagnaia, Paolo; Bai, Yu; Bain, Travis; Baines, John; Baker, Oliver Keith; Balek, Petr; Balli, Fabrice; Banas, Elzbieta; Banerjee, Swagato; Bannoura, Arwa A E; Bansal, Vikas; Bansil, Hardeep Singh; Barak, Liron; Baranov, Sergei; Barberio, Elisabetta Luigia; Barberis, Dario; Barbero, Marlon; Barillari, Teresa; Barisonzi, Marcello; Barklow, Timothy; Barlow, Nick; Barnett, Bruce; Barnett, Michael; Barnovska, Zuzana; Baroncelli, Antonio; Barone, Gaetano; Barr, Alan; Barreiro, Fernando; Barreiro Guimarães da Costa, João; Bartoldus, Rainer; Barton, Adam Edward; Bartos, Pavol; Bartsch, Valeria; Bassalat, Ahmed; Basye, Austin; Bates, Richard; Batkova, Lucia; Batley, Richard; Battaglia, Marco; Battistin, Michele; Bauer, Florian; Bawa, Harinder Singh; Beau, Tristan; Beauchemin, Pierre-Hugues; Beccherle, Roberto; Bechtle, Philip; Beck, Hans Peter; Becker, Anne Kathrin; Becker, Sebastian; Beckingham, Matthew; Becot, Cyril; Beddall, Andrew; Beddall, Ayda; Bedikian, Sourpouhi; Bednyakov, Vadim; Bee, Christopher; Beemster, Lars; Beermann, Thomas; Begel, Michael; Behr, Katharina; Belanger-Champagne, Camille; Bell, Paul; Bell, William; Bella, Gideon; Bellagamba, Lorenzo; Bellerive, Alain; Bellomo, Massimiliano; Belotskiy, Konstantin; Beltramello, Olga; Benary, Odette; Benchekroun, Driss; Bendtz, Katarina; Benekos, Nektarios; Benhammou, Yan; Benhar Noccioli, Eleonora; Benitez Garcia, Jorge-Armando; Benjamin, Douglas; Bensinger, James; Benslama, Kamal; Bentvelsen, Stan; Berge, David; Bergeaas Kuutmann, Elin; Berger, Nicolas; Berghaus, Frank; Beringer, Jürg; Bernard, Clare; Bernat, Pauline; Bernius, Catrin; Bernlochner, Florian Urs; Berry, Tracey; Berta, Peter; Bertella, Claudia; Bertoli, Gabriele; Bertolucci, Federico; Bertsche, David; Besana, Maria Ilaria; Besjes, Geert-Jan; Bessidskaia, Olga; Bessner, Martin Florian; Besson, Nathalie; Betancourt, Christopher; Bethke, Siegfried; Bhimji, Wahid; Bianchi, Riccardo-Maria; Bianchini, Louis; Bianco, Michele; Biebel, Otmar; Bieniek, Stephen Paul; Bierwagen, Katharina; Biesiada, Jed; Biglietti, Michela; Bilbao De Mendizabal, Javier; Bilokon, Halina; Bindi, Marcello; Binet, Sebastien; Bingul, Ahmet; Bini, Cesare; Black, Curtis; Black, James; Black, Kevin; Blackburn, Daniel; Blair, Robert; Blanchard, Jean-Baptiste; Blazek, Tomas; Bloch, Ingo; Blocker, Craig; Blum, Walter; Blumenschein, Ulrike; Bobbink, Gerjan; Bobrovnikov, Victor; Bocchetta, Simona Serena; Bocci, Andrea; Bock, Christopher; Boddy, Christopher Richard; Boehler, Michael; Boek, Thorsten Tobias; Bogaerts, Joannes Andreas; Bogdanchikov, Alexander; Bogouch, Andrei; Bohm, Christian; Bohm, Jan; Boisvert, Veronique; Bold, Tomasz; Boldea, Venera; Boldyrev, Alexey; Bomben, Marco; Bona, Marcella; Boonekamp, Maarten; Borisov, Anatoly; Borissov, Guennadi; Borri, Marcello; Borroni, Sara; Bortfeldt, Jonathan; Bortolotto, Valerio; Bos, Kors; Boscherini, Davide; Bosman, Martine; Boterenbrood, Hendrik; Boudreau, Joseph; Bouffard, Julian; Bouhova-Thacker, Evelina Vassileva; Boumediene, Djamel Eddine; Bourdarios, Claire; Bousson, Nicolas; Boutouil, Sara; Boveia, Antonio; Boyd, James; Boyko, Igor; Bracinik, Juraj; Brandt, Andrew; Brandt, Gerhard; Brandt, Oleg; Bratzler, Uwe; Brau, Benjamin; Brau, James; Braun, Helmut; Brazzale, Simone Federico; Brelier, Bertrand; Brendlinger, Kurt; Brennan, Amelia Jean; Brenner, Richard; Bressler, Shikma; Bristow, Kieran; Bristow, Timothy Michael; Britton, Dave; Brochu, Frederic; Brock, Ian; Brock, Raymond; Bromberg, Carl; Bronner, Johanna; Brooijmans, Gustaaf; Brooks, Timothy; Brooks, William; Brosamer, Jacquelyn; Brost, Elizabeth; Brown, Jonathan; Bruckman de Renstrom, Pawel; Bruncko, Dusan; Bruneliere, Renaud; Brunet, Sylvie; Bruni, Alessia; Bruni, Graziano; Bruschi, Marco; Bryngemark, Lene; Buanes, Trygve; Buat, Quentin; Bucci, Francesca; Buchholz, Peter; Buckingham, Ryan; Buckley, Andrew; Buda, Stelian Ioan; Budagov, Ioulian; Buehrer, Felix; Bugge, Lars; Bugge, Magnar Kopangen; Bulekov, Oleg; Bundock, Aaron Colin; Burckhart, Helfried; Burdin, Sergey; Burghgrave, Blake; Burke, Stephen; Burmeister, Ingo; Busato, Emmanuel; Büscher, Daniel; Büscher, Volker; Bussey, Peter; Buszello, Claus-Peter; Butler, Bart; Butler, John; Butt, Aatif Imtiaz; Buttar, Craig; Butterworth, Jonathan; Butti, Pierfrancesco; Buttinger, William; Buzatu, Adrian; Byszewski, Marcin; Cabrera Urbán, Susana; Caforio, Davide; Cakir, Orhan; Calafiura, Paolo; Calandri, Alessandro; Calderini, Giovanni; Calfayan, Philippe; Calkins, Robert; Caloba, Luiz; Calvet, David; Calvet, Samuel; Camacho Toro, Reina; Camarda, Stefano; Cameron, David; Caminada, Lea Michaela; Caminal Armadans, Roger; Campana, Simone; Campanelli, Mario; Campoverde, Angel; Canale, Vincenzo; Canepa, Anadi; Cano Bret, Marc; Cantero, Josu; Cantrill, Robert; Cao, Tingting; Capeans Garrido, Maria Del Mar; Caprini, Irinel; Caprini, Mihai; Capua, Marcella; Caputo, Regina; Cardarelli, Roberto; Carli, Tancredi; Carlino, Gianpaolo; Carminati, Leonardo; Caron, Sascha; Carquin, Edson; Carrillo-Montoya, German D; Carter, Janet; Carvalho, João; Casadei, Diego; Casado, Maria Pilar; Casolino, Mirkoantonio; Castaneda-Miranda, Elizabeth; Castelli, Angelantonio; Castillo Gimenez, Victoria; Castro, Nuno Filipe; Catastini, Pierluigi; Catinaccio, Andrea; Catmore, James; Cattai, Ariella; Cattani, Giordano; Caughron, Seth; Cavaliere, Viviana; Cavalli, Donatella; Cavalli-Sforza, Matteo; Cavasinni, Vincenzo; Ceradini, Filippo; Cerio, Benjamin; Cerny, Karel; Santiago Cerqueira, Augusto; Cerri, Alessandro; Cerrito, Lucio; Cerutti, Fabio; Cerv, Matevz; Cervelli, Alberto; Cetin, Serkant Ali; Chafaq, Aziz; Chakraborty, Dhiman; Chalupkova, Ina; Chang, Philip; Chapleau, Bertrand; Chapman, John Derek; Charfeddine, Driss; Charlton, Dave; Chau, Chav Chhiv; Chavez Barajas, Carlos Alberto; Cheatham, Susan; Chegwidden, Andrew; Chekanov, Sergei; Chekulaev, Sergey; Chelkov, Gueorgui; Chelstowska, Magda Anna; Chen, Chunhui; Chen, Hucheng; Chen, Karen; Chen, Liming; Chen, Shenjian; Chen, Xin; Chen, Yujiao; Cheng, Hok Chuen; Cheng, Yangyang; Cheplakov, Alexander; Cherkaoui El Moursli, Rajaa; Chernyatin, Valeriy; Cheu, Elliott; Chevalier, Laurent; Chiarella, Vitaliano; Chiefari, Giovanni; Childers, John Taylor; Chilingarov, Alexandre; Chiodini, Gabriele; Chisholm, Andrew; Chislett, Rebecca Thalatta; Chitan, Adrian; Chizhov, Mihail; Chouridou, Sofia; Chow, Bonnie Kar Bo; Chromek-Burckhart, Doris; Chu, Ming-Lee; Chudoba, Jiri; Chwastowski, Janusz; Chytka, Ladislav; Ciapetti, Guido; Ciftci, Abbas Kenan; Ciftci, Rena; Cinca, Diane; Cindro, Vladimir; Ciocio, Alessandra; Cirkovic, Predrag; Citron, Zvi Hirsh; Citterio, Mauro; Ciubancan, Mihai; Clark, Allan G; Clark, Philip James; Clarke, Robert; Cleland, Bill; Clemens, Jean-Claude; Clement, Christophe; Coadou, Yann; Cobal, Marina; Coccaro, Andrea; Cochran, James H; Coffey, Laurel; Cogan, Joshua Godfrey; Coggeshall, James; Cole, Brian; Cole, Stephen; Colijn, Auke-Pieter; Collot, Johann; Colombo, Tommaso; Colon, German; Compostella, Gabriele; Conde Muiño, Patricia; Coniavitis, Elias; Conidi, Maria Chiara; Connell, Simon Henry; Connelly, Ian; Consonni, Sofia Maria; Consorti, Valerio; Constantinescu, Serban; Conta, Claudio; Conti, Geraldine; Conventi, Francesco; Cooke, Mark; Cooper, Ben; Cooper-Sarkar, Amanda; Cooper-Smith, Neil; Copic, Katherine; Cornelissen, Thijs; Corradi, Massimo; Corriveau, Francois; Corso-Radu, Alina; Cortes-Gonzalez, Arely; Cortiana, Giorgio; Costa, Giuseppe; Costa, María José; Costanzo, Davide; Côté, David; Cottin, Giovanna; Cowan, Glen; Cox, Brian; Cranmer, Kyle; Cree, Graham; Crépé-Renaudin, Sabine; Crescioli, Francesco; Cribbs, Wayne Allen; Crispin Ortuzar, Mireia; Cristinziani, Markus; Croft, Vince; Crosetti, Giovanni; Cuciuc, Constantin-Mihai; Cuhadar Donszelmann, Tulay; Cummings, Jane; Curatolo, Maria; Cuthbert, Cameron; Czirr, Hendrik; Czodrowski, Patrick; Czyczula, Zofia; D'Auria, Saverio; D'Onofrio, Monica; Da Cunha Sargedas De Sousa, Mario Jose; Da Via, Cinzia; Dabrowski, Wladyslaw; Dafinca, Alexandru; Dai, Tiesheng; Dale, Orjan; Dallaire, Frederick; Dallapiccola, Carlo; Dam, Mogens; Daniells, Andrew Christopher; Dano Hoffmann, Maria; Dao, Valerio; Darbo, Giovanni; Darmora, Smita; Dassoulas, James; Dattagupta, Aparajita; Davey, Will; David, Claire; Davidek, Tomas; Davies, Eleanor; Davies, Merlin; Davignon, Olivier; Davison, Adam; Davison, Peter; Davygora, Yuriy; Dawe, Edmund; Dawson, Ian; Daya-Ishmukhametova, Rozmin; De, Kaushik; de Asmundis, Riccardo; De Castro, Stefano; De Cecco, Sandro; De Groot, Nicolo; de Jong, Paul; De la Torre, Hector; De Lorenzi, Francesco; De Nooij, Lucie; De Pedis, Daniele; De Salvo, Alessandro; De Sanctis, Umberto; De Santo, Antonella; De Vivie De Regie, Jean-Baptiste; Dearnaley, William James; Debbe, Ramiro; Debenedetti, Chiara; Dechenaux, Benjamin; Dedovich, Dmitri; Deigaard, Ingrid; Del Peso, Jose; Del Prete, Tarcisio; Deliot, Frederic; Delitzsch, Chris Malena; Deliyergiyev, Maksym; Dell'Acqua, Andrea; Dell'Asta, Lidia; Dell'Orso, Mauro; Della Pietra, Massimo; della Volpe, Domenico; Delmastro, Marco; Delsart, Pierre-Antoine; Deluca, Carolina; Demers, Sarah; Demichev, Mikhail; Demilly, Aurelien; Denisov, Sergey; Derendarz, Dominik; Derkaoui, Jamal Eddine; Derue, Frederic; Dervan, Paul; Desch, Klaus Kurt; Deterre, Cecile; Deviveiros, Pier-Olivier; Dewhurst, Alastair; Dhaliwal, Saminder; Di Ciaccio, Anna; Di Ciaccio, Lucia; Di Domenico, Antonio; Di Donato, Camilla; Di Girolamo, Alessandro; Di Girolamo, Beniamino; Di Mattia, Alessandro; Di Micco, Biagio; Di Nardo, Roberto; Di Simone, Andrea; Di Sipio, Riccardo; Di Valentino, David; Dias, Flavia; Diaz, Marco Aurelio; Diehl, Edward; Dietrich, Janet; Dietzsch, Thorsten; Diglio, Sara; Dimitrievska, Aleksandra; Dingfelder, Jochen; Dionisi, Carlo; Dita, Petre; Dita, Sanda; Dittus, Fridolin; Djama, Fares; Djobava, Tamar; Barros do Vale, Maria Aline; Do Valle Wemans, André; Doan, Thi Kieu Oanh; Dobos, Daniel; Doglioni, Caterina; Doherty, Tom; Dohmae, Takeshi; Dolejsi, Jiri; Dolezal, Zdenek; Dolgoshein, Boris; Donadelli, Marisilvia; Donati, Simone; Dondero, Paolo; Donini, Julien; Dopke, Jens; Doria, Alessandra; Dova, Maria-Teresa; Doyle, Tony; Dris, Manolis; Dubbert, Jörg; Dube, Sourabh; Dubreuil, Emmanuelle; Duchovni, Ehud; Duckeck, Guenter; Ducu, Otilia Anamaria; Duda, Dominik; Dudarev, Alexey; Dudziak, Fanny; Duflot, Laurent; Duguid, Liam; Dührssen, Michael; Dunford, Monica; Duran Yildiz, Hatice; Düren, Michael; Durglishvili, Archil; Dwuznik, Michal; Dyndal, Mateusz; Ebke, Johannes; Edson, William; Edwards, Nicholas Charles; Ehrenfeld, Wolfgang; Eifert, Till; Eigen, Gerald; Einsweiler, Kevin; Ekelof, Tord; El Kacimi, Mohamed; Ellert, Mattias; Elles, Sabine; Ellinghaus, Frank; Ellis, Nicolas; Elmsheuser, Johannes; Elsing, Markus; Emeliyanov, Dmitry; Enari, Yuji; Endner, Oliver Chris; Endo, Masaki; Engelmann, Roderich; Erdmann, Johannes; Ereditato, Antonio; Eriksson, Daniel; Ernis, Gunar; Ernst, Jesse; Ernst, Michael; Ernwein, Jean; Errede, Deborah; Errede, Steven; Ertel, Eugen; Escalier, Marc; Esch, Hendrik; Escobar, Carlos; Esposito, Bellisario; Etienvre, Anne-Isabelle; Etzion, Erez; Evans, Hal; Ezhilov, Alexey; Fabbri, Laura; Facini, Gabriel; Fakhrutdinov, Rinat; Falciano, Speranza; Falla, Rebecca Jane; Faltova, Jana; Fang, Yaquan; Fanti, Marcello; Farbin, Amir; Farilla, Addolorata; Farooque, Trisha; Farrell, Steven; Farrington, Sinead; Farthouat, Philippe; Fassi, Farida; Fassnacht, Patrick; Fassouliotis, Dimitrios; Favareto, Andrea; Fayard, Louis; Federic, Pavol; Fedin, Oleg; Fedorko, Wojciech; Fehling-Kaschek, Mirjam; Feigl, Simon; Feligioni, Lorenzo; Feng, Cunfeng; Feng, Eric; Feng, Haolu; Fenyuk, Alexander; Fernandez Perez, Sonia; Ferrag, Samir; Ferrando, James; Ferrari, Arnaud; Ferrari, Pamela; Ferrari, Roberto; Ferreira de Lima, Danilo Enoque; Ferrer, Antonio; Ferrere, Didier; Ferretti, Claudio; Ferretto Parodi, Andrea; Fiascaris, Maria; Fiedler, Frank; Filipčič, Andrej; Filipuzzi, Marco; Filthaut, Frank; Fincke-Keeler, Margret; Finelli, Kevin Daniel; Fiolhais, Miguel; Fiorini, Luca; Firan, Ana; Fischer, Adam; Fischer, Julia; Fisher, Wade Cameron; Fitzgerald, Eric Andrew; Flechl, Martin; Fleck, Ivor; Fleischmann, Philipp; Fleischmann, Sebastian; Fletcher, Gareth Thomas; Fletcher, Gregory; Flick, Tobias; Floderus, Anders; Flores Castillo, Luis; Florez Bustos, Andres Carlos; Flowerdew, Michael; Formica, Andrea; Forti, Alessandra; Fortin, Dominique; Fournier, Daniel; Fox, Harald; Fracchia, Silvia; Francavilla, Paolo; Franchini, Matteo; Franchino, Silvia; Francis, David; Franklin, Melissa; Franz, Sebastien; Fraternali, Marco; French, Sky; Friedrich, Conrad; Friedrich, Felix; Froidevaux, Daniel; Frost, James; Fukunaga, Chikara; Fullana Torregrosa, Esteban; Fulsom, Bryan Gregory; Fuster, Juan; Gabaldon, Carolina; Gabizon, Ofir; Gabrielli, Alessandro; Gabrielli, Andrea; Gadatsch, Stefan; Gadomski, Szymon; Gagliardi, Guido; Gagnon, Pauline; Galea, Cristina; Galhardo, Bruno; Gallas, Elizabeth; Gallo, Valentina Santina; Gallop, Bruce; Gallus, Petr; Galster, Gorm Aske Gram Krohn; Gan, KK; Gandrajula, Reddy Pratap; Gao, Jun; Gao, Yongsheng; Garay Walls, Francisca; Garberson, Ford; García, Carmen; García Navarro, José Enrique; Garcia-Sciveres, Maurice; Gardner, Robert; Garelli, Nicoletta; Garonne, Vincent; Gatti, Claudio; Gaudio, Gabriella; Gaur, Bakul; Gauthier, Lea; Gauzzi, Paolo; Gavrilenko, Igor; Gay, Colin; Gaycken, Goetz; Gazis, Evangelos; Ge, Peng; Gecse, Zoltan; Gee, Norman; Geerts, Daniël Alphonsus Adrianus; Geich-Gimbel, Christoph; Gellerstedt, Karl; Gemme, Claudia; Gemmell, Alistair; Genest, Marie-Hélène; Gentile, Simonetta; George, Matthias; George, Simon; Gerbaudo, Davide; Gershon, Avi; Ghazlane, Hamid; Ghodbane, Nabil; Giacobbe, Benedetto; Giagu, Stefano; Giangiobbe, Vincent; Giannetti, Paola; Gianotti, Fabiola; Gibbard, Bruce; Gibson, Stephen; Gilchriese, Murdock; Gillam, Thomas; Gillberg, Dag; Gilles, Geoffrey; Gingrich, Douglas; Giokaris, Nikos; Giordani, MarioPaolo; Giordano, Raffaele; Giorgi, Filippo Maria; Giorgi, Francesco Michelangelo; Giraud, Pierre-Francois; Giugni, Danilo; Giuliani, Claudia; Giulini, Maddalena; Gjelsten, Børge Kile; Gkaitatzis, Stamatios; Gkialas, Ioannis; Gladilin, Leonid; Glasman, Claudia; Glatzer, Julian; Glaysher, Paul; Glazov, Alexandre; Glonti, George; Goblirsch-Kolb, Maximilian; Goddard, Jack Robert; Godfrey, Jennifer; Godlewski, Jan; Goeringer, Christian; Goldfarb, Steven; Golling, Tobias; Golubkov, Dmitry; Gomes, Agostinho; Gomez Fajardo, Luz Stella; Gonçalo, Ricardo; Goncalves Pinto Firmino Da Costa, Joao; Gonella, Laura; González de la Hoz, Santiago; Gonzalez Parra, Garoe; Gonzalez-Sevilla, Sergio; Goossens, Luc; Gorbounov, Petr Andreevich; Gordon, Howard; Gorelov, Igor; Gorini, Benedetto; Gorini, Edoardo; Gorišek, Andrej; Gornicki, Edward; Goshaw, Alfred; Gössling, Claus; Gostkin, Mikhail Ivanovitch; Gouighri, Mohamed; Goujdami, Driss; Goulette, Marc Phillippe; Goussiou, Anna; Goy, Corinne; Gozpinar, Serdar; Grabas, Herve Marie Xavier; Graber, Lars; Grabowska-Bold, Iwona; Grafström, Per; Grahn, Karl-Johan; Gramling, Johanna; Gramstad, Eirik; Grancagnolo, Sergio; Grassi, Valerio; Gratchev, Vadim; Gray, Heather; Graziani, Enrico; Grebenyuk, Oleg; Greenwood, Zeno Dixon; Gregersen, Kristian; Gregor, Ingrid-Maria; Grenier, Philippe; Griffiths, Justin; Grillo, Alexander; Grimm, Kathryn; Grinstein, Sebastian; Gris, Philippe Luc Yves; Grishkevich, Yaroslav; Grivaz, Jean-Francois; Grohs, Johannes Philipp; Grohsjean, Alexander; Gross, Eilam; Grosse-Knetter, Joern; Grossi, Giulio Cornelio; Groth-Jensen, Jacob; Grout, Zara Jane; Guan, Liang; Guescini, Francesco; Guest, Daniel; Gueta, Orel; Guicheney, Christophe; Guido, Elisa; Guillemin, Thibault; Guindon, Stefan; Gul, Umar; Gumpert, Christian; Gunther, Jaroslav; Guo, Jun; Gupta, Shaun; Gutierrez, Phillip; Gutierrez Ortiz, Nicolas Gilberto; Gutschow, Christian; Guttman, Nir; Guyot, Claude; Gwenlan, Claire; Gwilliam, Carl; Haas, Andy; Haber, Carl; Hadavand, Haleh Khani; Haddad, Nacim; Haefner, Petra; Hageböck, Stephan; Hajduk, Zbigniew; Hakobyan, Hrachya; Haleem, Mahsana; Hall, David; Halladjian, Garabed; Hamacher, Klaus; Hamal, Petr; Hamano, Kenji; Hamer, Matthias; Hamilton, Andrew; Hamilton, Samuel; Hamnett, Phillip George; Han, Liang; Hanagaki, Kazunori; Hanawa, Keita; Hance, Michael; Hanke, Paul; Hanna, Remie; Hansen, Jørgen Beck; Hansen, Jorn Dines; Hansen, Peter Henrik; Hara, Kazuhiko; Hard, Andrew; Harenberg, Torsten; Hariri, Faten; Harkusha, Siarhei; Harper, Devin; Harrington, Robert; Harris, Orin; Harrison, Paul Fraser; Hartjes, Fred; Hasegawa, Satoshi; Hasegawa, Yoji; Hasib, A; Hassani, Samira; Haug, Sigve; Hauschild, Michael; Hauser, Reiner; Havranek, Miroslav; Hawkes, Christopher; Hawkings, Richard John; Hawkins, Anthony David; Hayashi, Takayasu; Hayden, Daniel; Hays, Chris; Hayward, Helen; Haywood, Stephen; Head, Simon; Heck, Tobias; Hedberg, Vincent; Heelan, Louise; Heim, Sarah; Heim, Timon; Heinemann, Beate; Heinrich, Lukas; Hejbal, Jiri; Helary, Louis; Heller, Claudio; Heller, Matthieu; Hellman, Sten; Hellmich, Dennis; Helsens, Clement; Henderson, James; Henderson, Robert; Heng, Yang; Hengler, Christopher; Henrichs, Anna; Henriques Correia, Ana Maria; Henrot-Versille, Sophie; Hensel, Carsten; Herbert, Geoffrey Henry; Hernández Jiménez, Yesenia; Herrberg-Schubert, Ruth; Herten, Gregor; Hertenberger, Ralf; Hervas, Luis; Hesketh, Gavin Grant; Hessey, Nigel; Hickling, Robert; Higón-Rodriguez, Emilio; Hill, Ewan; Hill, John; Hiller, Karl Heinz; Hillert, Sonja; Hillier, Stephen; Hinchliffe, Ian; Hines, Elizabeth; Hirose, Minoru; Hirschbuehl, Dominic; Hobbs, John; Hod, Noam; Hodgkinson, Mark; Hodgson, Paul; Hoecker, Andreas; Hoeferkamp, Martin; Hoffman, Julia; Hoffmann, Dirk; Hofmann, Julia Isabell; Hohlfeld, Marc; Holmes, Tova Ray; Hong, Tae Min; Hooft van Huysduynen, Loek; Hostachy, Jean-Yves; Hou, Suen; Hoummada, Abdeslam; Howard, Jacob; Howarth, James; Hrabovsky, Miroslav; Hristova, Ivana; Hrivnac, Julius; Hryn'ova, Tetiana; Hsu, Catherine; Hsu, Pai-hsien Jennifer; Hsu, Shih-Chieh; Hu, Diedi; Hu, Xueye; Huang, Yanping; Hubacek, Zdenek; Hubaut, Fabrice; Huegging, Fabian; Huffman, Todd Brian; Hughes, Emlyn; Hughes, Gareth; Huhtinen, Mika; Hülsing, Tobias Alexander; Hurwitz, Martina; Huseynov, Nazim; Huston, Joey; Huth, John; Iacobucci, Giuseppe; Iakovidis, Georgios; Ibragimov, Iskander; Iconomidou-Fayard, Lydia; Ideal, Emma; Iengo, Paolo; Igonkina, Olga; Iizawa, Tomoya; Ikegami, Yoichi; Ikematsu, Katsumasa; Ikeno, Masahiro; Ilchenko, Iurii; Iliadis, Dimitrios; Ilic, Nikolina; Inamaru, Yuki; Ince, Tayfun; Ioannou, Pavlos; Iodice, Mauro; Iordanidou, Kalliopi; Ippolito, Valerio; Irles Quiles, Adrian; Isaksson, Charlie; Ishino, Masaya; Ishitsuka, Masaki; Ishmukhametov, Renat; Issever, Cigdem; Istin, Serhat; Iturbe Ponce, Julia Mariana; Iuppa, Roberto; Ivarsson, Jenny; Iwanski, Wieslaw; Iwasaki, Hiroyuki; Izen, Joseph; Izzo, Vincenzo; Jackson, Brett; Jackson, Matthew; Jackson, Paul; Jaekel, Martin; Jain, Vivek; Jakobs, Karl; Jakobsen, Sune; Jakoubek, Tomas; Jakubek, Jan; Jamin, David Olivier; Jana, Dilip; Jansen, Eric; Jansen, Hendrik; Janssen, Jens; Janus, Michel; Jarlskog, Göran; Javadov, Namig; Javůrek, Tomáš; Jeanty, Laura; Jejelava, Juansher; Jeng, Geng-yuan; Jennens, David; Jenni, Peter; Jentzsch, Jennifer; Jeske, Carl; Jézéquel, Stéphane; Ji, Haoshuang; Ji, Weina; Jia, Jiangyong; Jiang, Yi; Jimenez Belenguer, Marcos; Jin, Shan; Jinaru, Adam; Jinnouchi, Osamu; Joergensen, Morten Dam; Johansson, Erik; Johansson, Per; Johns, Kenneth; Jon-And, Kerstin; Jones, Graham; Jones, Roger; Jones, Tim; Jongmanns, Jan; Jorge, Pedro; Joshi, Kiran Daniel; Jovicevic, Jelena; Ju, Xiangyang; Jung, Christian; Jungst, Ralph Markus; Jussel, Patrick; Juste Rozas, Aurelio; Kaci, Mohammed; Kaczmarska, Anna; Kado, Marumi; Kagan, Harris; Kagan, Michael; Kajomovitz, Enrique; Kalderon, Charles William; Kama, Sami; Kamenshchikov, Andrey; Kanaya, Naoko; Kaneda, Michiru; Kaneti, Steven; Kantserov, Vadim; Kanzaki, Junichi; Kaplan, Benjamin; Kapliy, Anton; Kar, Deepak; Karakostas, Konstantinos; Karastathis, Nikolaos; Karnevskiy, Mikhail; Karpov, Sergey; Karpova, Zoya; Karthik, Krishnaiyengar; Kartvelishvili, Vakhtang; Karyukhin, Andrey; Kashif, Lashkar; Kasieczka, Gregor; Kass, Richard; Kastanas, Alex; Kataoka, Yousuke; Katre, Akshay; Katzy, Judith; Kaushik, Venkatesh; Kawagoe, Kiyotomo; Kawamoto, Tatsuo; Kawamura, Gen; Kazama, Shingo; Kazanin, Vassili; Kazarinov, Makhail; Keeler, Richard; Kehoe, Robert; Keil, Markus; Keller, John; Kempster, Jacob Julian; Keoshkerian, Houry; Kepka, Oldrich; Kerševan, Borut Paul; Kersten, Susanne; Kessoku, Kohei; Keung, Justin; Khalil-zada, Farkhad; Khandanyan, Hovhannes; Khanov, Alexander; Khodinov, Alexander; Khomich, Andrei; Khoo, Teng Jian; Khoriauli, Gia; Khoroshilov, Andrey; Khovanskiy, Valery; Khramov, Evgeniy; Khubua, Jemal; Kim, Hee Yeun; Kim, Hyeon Jin; Kim, Shinhong; Kimura, Naoki; Kind, Oliver; King, Barry; King, Matthew; King, Robert Steven Beaufoy; King, Samuel Burton; Kirk, Julie; Kiryunin, Andrey; Kishimoto, Tomoe; Kisielewska, Danuta; Kiss, Florian; Kittelmann, Thomas; Kiuchi, Kenji; Kladiva, Eduard; Klein, Max; Klein, Uta; Kleinknecht, Konrad; Klimek, Pawel; Klimentov, Alexei; Klingenberg, Reiner; Klinger, Joel Alexander; Klioutchnikova, Tatiana; Klok, Peter; Kluge, Eike-Erik; Kluit, Peter; Kluth, Stefan; Kneringer, Emmerich; Knoops, Edith; Knue, Andrea; Kobayashi, Dai; Kobayashi, Tomio; Kobel, Michael; Kocian, Martin; Kodys, Peter; Koevesarki, Peter; Koffas, Thomas; Koffeman, Els; Kogan, Lucy Anne; Kohlmann, Simon; Kohout, Zdenek; Kohriki, Takashi; Koi, Tatsumi; Kolanoski, Hermann; Koletsou, Iro; Koll, James; Komar, Aston; Komori, Yuto; Kondo, Takahiko; Kondrashova, Nataliia; Köneke, Karsten; König, Adriaan; König, Sebastian; Kono, Takanori; Konoplich, Rostislav; Konstantinidis, Nikolaos; Kopeliansky, Revital; Koperny, Stefan; Köpke, Lutz; Kopp, Anna Katharina; Korcyl, Krzysztof; Kordas, Kostantinos; Korn, Andreas; Korol, Aleksandr; Korolkov, Ilya; Korolkova, Elena; Korotkov, Vladislav; Kortner, Oliver; Kortner, Sandra; Kostyukhin, Vadim; Kotov, Vladislav; Kotwal, Ashutosh; Kourkoumelis, Christine; Kouskoura, Vasiliki; Koutsman, Alex; Kowalewski, Robert Victor; Kowalski, Tadeusz; Kozanecki, Witold; Kozhin, Anatoly; Kral, Vlastimil; Kramarenko, Viktor; Kramberger, Gregor; Krasnopevtsev, Dimitriy; Krasny, Mieczyslaw Witold; Krasznahorkay, Attila; Kraus, Jana; Kravchenko, Anton; Kreiss, Sven; Kretz, Moritz; Kretzschmar, Jan; Kreutzfeldt, Kristof; Krieger, Peter; Kroeninger, Kevin; Kroha, Hubert; Kroll, Joe; Kroseberg, Juergen; Krstic, Jelena; Kruchonak, Uladzimir; Krüger, Hans; Kruker, Tobias; Krumnack, Nils; Krumshteyn, Zinovii; Kruse, Amanda; Kruse, Mark; Kruskal, Michael; Kubota, Takashi; Kuday, Sinan; Kuehn, Susanne; Kugel, Andreas; Kuhl, Andrew; Kuhl, Thorsten; Kukhtin, Victor; Kulchitsky, Yuri; Kuleshov, Sergey; Kuna, Marine; Kunkle, Joshua; Kupco, Alexander; Kurashige, Hisaya; Kurochkin, Yurii; Kurumida, Rie; Kus, Vlastimil; Kuwertz, Emma Sian; Kuze, Masahiro; Kvita, Jiri; La Rosa, Alessandro; La Rotonda, Laura; Lacasta, Carlos; Lacava, Francesco; Lacey, James; Lacker, Heiko; Lacour, Didier; Lacuesta, Vicente Ramón; Ladygin, Evgueni; Lafaye, Remi; Laforge, Bertrand; Lagouri, Theodota; Lai, Stanley; Laier, Heiko; Lambourne, Luke; Lammers, Sabine; Lampen, Caleb; Lampl, Walter; Lançon, Eric; Landgraf, Ulrich; Landon, Murrough; Lang, Valerie Susanne; Lankford, Andrew; Lanni, Francesco; Lantzsch, Kerstin; Laplace, Sandrine; Lapoire, Cecile; Laporte, Jean-Francois; Lari, Tommaso; Lassnig, Mario; Laurelli, Paolo; Lavrijsen, Wim; Law, Alexander; Laycock, Paul; Le, Bao Tran; Le Dortz, Olivier; Le Guirriec, Emmanuel; Le Menedeu, Eve; LeCompte, Thomas; Ledroit-Guillon, Fabienne Agnes Marie; Lee, Claire Alexandra; Lee, Hurng-Chun; Lee, Jason; Lee, Shih-Chang; Lee, Lawrence; Lefebvre, Guillaume; Lefebvre, Michel; Legger, Federica; Leggett, Charles; Lehan, Allan; Lehmacher, Marc; Lehmann Miotto, Giovanna; Lei, Xiaowen; Leight, William Axel; Leisos, Antonios; Leister, Andrew Gerard; Leite, Marco Aurelio Lisboa; Leitner, Rupert; Lellouch, Daniel; Lemmer, Boris; Leney, Katharine; Lenz, Tatjana; Lenzen, Georg; Lenzi, Bruno; Leone, Robert; Leone, Sandra; Leonhardt, Kathrin; Leonidopoulos, Christos; Leontsinis, Stefanos; Leroy, Claude; Lester, Christopher; Lester, Christopher Michael; Levchenko, Mikhail; Levêque, Jessica; Levin, Daniel; Levinson, Lorne; Levy, Mark; Lewis, Adrian; Lewis, George; Leyko, Agnieszka; Leyton, Michael; Li, Bing; Li, Bo; Li, Haifeng; Li, Ho Ling; Li, Lei; Li, Liang; Li, Shu; Li, Yichen; Liang, Zhijun; Liao, Hongbo; Liberti, Barbara; Lichard, Peter; Lie, Ki; Liebal, Jessica; Liebig, Wolfgang; Limbach, Christian; Limosani, Antonio; Lin, Simon; Lin, Tai-Hua; Linde, Frank; Lindquist, Brian Edward; Linnemann, James; Lipeles, Elliot; Lipniacka, Anna; Lisovyi, Mykhailo; Liss, Tony; Lissauer, David; Lister, Alison; Litke, Alan; Liu, Bo; Liu, Dong; Liu, Jianbei; Liu, Kun; Liu, Lulu; Liu, Miaoyuan; Liu, Minghui; Liu, Yanwen; Livan, Michele; Livermore, Sarah; Lleres, Annick; Llorente Merino, Javier; Lloyd, Stephen; Lo Sterzo, Francesco; Lobodzinska, Ewelina; Loch, Peter; Lockman, William; Loddenkoetter, Thomas; Loebinger, Fred; Loevschall-Jensen, Ask Emil; Loginov, Andrey; Loh, Chang Wei; Lohse, Thomas; Lohwasser, Kristin; Lokajicek, Milos; Lombardo, Vincenzo Paolo; Long, Brian Alexander; Long, Jonathan; Long, Robin Eamonn; Lopes, Lourenco; Lopez Mateos, David; Lopez Paredes, Brais; Lopez Paz, Ivan; Lorenz, Jeanette; Lorenzo Martinez, Narei; Losada, Marta; Loscutoff, Peter; Lou, XinChou; Lounis, Abdenour; Love, Jeremy; Love, Peter; Lowe, Andrew; Lu, Feng; Lubatti, Henry; Luci, Claudio; Lucotte, Arnaud; Luehring, Frederick; Lukas, Wolfgang; Luminari, Lamberto; Lundberg, Olof; Lund-Jensen, Bengt; Lungwitz, Matthias; Lynn, David; Lysak, Roman; Lytken, Else; Ma, Hong; Ma, Lian Liang; Maccarrone, Giovanni; Macchiolo, Anna; Machado Miguens, Joana; Macina, Daniela; Madaffari, Daniele; Madar, Romain; Maddocks, Harvey Jonathan; Mader, Wolfgang; Madsen, Alexander; Maeno, Mayuko; Maeno, Tadashi; Magradze, Erekle; Mahboubi, Kambiz; Mahlstedt, Joern; Mahmoud, Sara; Maiani, Camilla; Maidantchik, Carmen; Maier, Andreas Alexander; Maio, Amélia; Majewski, Stephanie; Makida, Yasuhiro; Makovec, Nikola; Mal, Prolay; Malaescu, Bogdan; Malecki, Pawel; Maleev, Victor; Malek, Fairouz; Mallik, Usha; Malon, David; Malone, Caitlin; Maltezos, Stavros; Malyshev, Vladimir; Malyukov, Sergei; Mamuzic, Judita; Mandelli, Beatrice; Mandelli, Luciano; Mandić, Igor; Mandrysch, Rocco; Maneira, José; Manfredini, Alessandro; Manhaes de Andrade Filho, Luciano; Manjarres Ramos, Joany Andreina; Mann, Alexander; Manning, Peter; Manousakis-Katsikakis, Arkadios; Mansoulie, Bruno; Mantifel, Rodger; Mapelli, Livio; March, Luis; Marchand, Jean-Francois; Marchiori, Giovanni; Marcisovsky, Michal; Marino, Christopher; Marjanovic, Marija; Marques, Carlos; Marroquim, Fernando; Marsden, Stephen Philip; Marshall, Zach; Marti, Lukas Fritz; Marti-Garcia, Salvador; Martin, Brian; Martin, Brian Thomas; Martin, Tim; Martin, Victoria Jane; Martin dit Latour, Bertrand; Martinez, Homero; Martinez, Mario; Martin-Haugh, Stewart; Martyniuk, Alex; Marx, Marilyn; Marzano, Francesco; Marzin, Antoine; Masetti, Lucia; Mashimo, Tetsuro; Mashinistov, Ruslan; Masik, Jiri; Maslennikov, Alexey; Massa, Ignazio; Massol, Nicolas; Mastrandrea, Paolo; Mastroberardino, Anna; Masubuchi, Tatsuya; Mättig, Peter; Mattmann, Johannes; Maurer, Julien; Maxfield, Stephen; Maximov, Dmitriy; Mazini, Rachid; Mazzaferro, Luca; Mc Goldrick, Garrin; Mc Kee, Shawn Patrick; McCarn, Allison; McCarthy, Robert; McCarthy, Tom; McCubbin, Norman; McFarlane, Kenneth; Mcfayden, Josh; Mchedlidze, Gvantsa; McMahon, Steve; McPherson, Robert; Meade, Andrew; Mechnich, Joerg; Medinnis, Michael; Meehan, Samuel; Mehlhase, Sascha; Mehta, Andrew; Meier, Karlheinz; Meineck, Christian; Meirose, Bernhard; Melachrinos, Constantinos; Mellado Garcia, Bruce Rafael; Meloni, Federico; Mengarelli, Alberto; Menke, Sven; Meoni, Evelin; Mercurio, Kevin Michael; Mergelmeyer, Sebastian; Meric, Nicolas; Mermod, Philippe; Merola, Leonardo; Meroni, Chiara; Merritt, Frank; Merritt, Hayes; Messina, Andrea; Metcalfe, Jessica; Mete, Alaettin Serhan; Meyer, Carsten; Meyer, Christopher; Meyer, Jean-Pierre; Meyer, Jochen; Middleton, Robin; Migas, Sylwia; Mijović, Liza; Mikenberg, Giora; Mikestikova, Marcela; Mikuž, Marko; Milic, Adriana; Miller, David; Mills, Corrinne; Milov, Alexander; Milstead, David; Milstein, Dmitry; Minaenko, Andrey; Minashvili, Irakli; Mincer, Allen; Mindur, Bartosz; Mineev, Mikhail; Ming, Yao; Mir, Lluisa-Maria; Mirabelli, Giovanni; Mitani, Takashi; Mitrevski, Jovan; Mitsou, Vasiliki A; Mitsui, Shingo; Miucci, Antonio; Miyagawa, Paul; Mjörnmark, Jan-Ulf; Moa, Torbjoern; Mochizuki, Kazuya; Mohapatra, Soumya; Mohr, Wolfgang; Molander, Simon; Moles-Valls, Regina; Mönig, Klaus; Monini, Caterina; Monk, James; Monnier, Emmanuel; Montejo Berlingen, Javier; Monticelli, Fernando; Monzani, Simone; Moore, Roger; Moraes, Arthur; Morange, Nicolas; Moreno, Deywis; Moreno Llácer, María; Morettini, Paolo; Morgenstern, Marcus; Morii, Masahiro; Moritz, Sebastian; Morley, Anthony Keith; Mornacchi, Giuseppe; Morris, John; Morvaj, Ljiljana; Moser, Hans-Guenther; Mosidze, Maia; Moss, Josh; Motohashi, Kazuki; Mount, Richard; Mountricha, Eleni; Mouraviev, Sergei; Moyse, Edward; Muanza, Steve; Mudd, Richard; Mueller, Felix; Mueller, James; Mueller, Klemens; Mueller, Thibaut; Mueller, Timo; Muenstermann, Daniel; Munwes, Yonathan; Murillo Quijada, Javier Alberto; Murray, Bill; Musheghyan, Haykuhi; Musto, Elisa; Myagkov, Alexey; Myska, Miroslav; Nackenhorst, Olaf; Nadal, Jordi; Nagai, Koichi; Nagai, Ryo; Nagai, Yoshikazu; Nagano, Kunihiro; Nagarkar, Advait; Nagasaka, Yasushi; Nagel, Martin; Nairz, Armin Michael; Nakahama, Yu; Nakamura, Koji; Nakamura, Tomoaki; Nakano, Itsuo; Namasivayam, Harisankar; Nanava, Gizo; Narayan, Rohin; Nattermann, Till; Naumann, Thomas; Navarro, Gabriela; Nayyar, Ruchika; Neal, Homer; Nechaeva, Polina; Neep, Thomas James; Nef, Pascal Daniel; Negri, Andrea; Negri, Guido; Negrini, Matteo; Nektarijevic, Snezana; Nelson, Andrew; Nelson, Timothy Knight; Nemecek, Stanislav; Nemethy, Peter; Nepomuceno, Andre Asevedo; Nessi, Marzio; Neubauer, Mark; Neumann, Manuel; Neves, Ricardo; Nevski, Pavel; Newman, Paul; Nguyen, Duong Hai; Nickerson, Richard; Nicolaidou, Rosy; Nicquevert, Bertrand; Nielsen, Jason; Nikiforou, Nikiforos; Nikiforov, Andriy; Nikolaenko, Vladimir; Nikolic-Audit, Irena; Nikolics, Katalin; Nikolopoulos, Konstantinos; Nilsson, Paul; Ninomiya, Yoichi; Nisati, Aleandro; Nisius, Richard; Nobe, Takuya; Nodulman, Lawrence; Nomachi, Masaharu; Nomidis, Ioannis; Norberg, Scarlet; Nordberg, Markus; Novgorodova, Olga; Nowak, Sebastian; Nozaki, Mitsuaki; Nozka, Libor; Ntekas, Konstantinos; Nunes Hanninger, Guilherme; Nunnemann, Thomas; Nurse, Emily; Nuti, Francesco; O'Brien, Brendan Joseph; O'grady, Fionnbarr; O'Neil, Dugan; O'Shea, Val; Oakham, Gerald; Oberlack, Horst; Obermann, Theresa; Ocariz, Jose; Ochi, Atsuhiko; Ochoa, Ines; Oda, Susumu; Odaka, Shigeru; Ogren, Harold; Oh, Alexander; Oh, Seog; Ohm, Christian; Ohman, Henrik; Ohshima, Takayoshi; Okamura, Wataru; Okawa, Hideki; Okumura, Yasuyuki; Okuyama, Toyonobu; Olariu, Albert; Olchevski, Alexander; Olivares Pino, Sebastian Andres; Oliveira Damazio, Denis; Oliver Garcia, Elena; Olszewski, Andrzej; Olszowska, Jolanta; Onofre, António; Onyisi, Peter; Oram, Christopher; Oreglia, Mark; Oren, Yona; Orestano, Domizia; Orlando, Nicola; Oropeza Barrera, Cristina; Orr, Robert; Osculati, Bianca; Ospanov, Rustem; Otero y Garzon, Gustavo; Otono, Hidetoshi; Ouchrif, Mohamed; Ouellette, Eric; Ould-Saada, Farid; Ouraou, Ahmimed; Oussoren, Koen Pieter; Ouyang, Qun; Ovcharova, Ana; Owen, Mark; Ozcan, Veysi Erkcan; Ozturk, Nurcan; Pachal, Katherine; 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Teixeira-Dias, Pedro; Temming, Kim Katrin; Ten Kate, Herman; Teng, Ping-Kun; Teoh, Jia Jian; Terada, Susumu; Terashi, Koji; Terron, Juan; Terzo, Stefano; Testa, Marianna; Teuscher, Richard; Therhaag, Jan; Theveneaux-Pelzer, Timothée; Thomas, Juergen; Thomas-Wilsker, Joshuha; Thompson, Emily; Thompson, Paul; Thompson, Peter; Thompson, Stan; Thomsen, Lotte Ansgaard; Thomson, Evelyn; Thomson, Mark; Thong, Wai Meng; Thun, Rudolf; Tian, Feng; Tibbetts, Mark James; Tikhomirov, Vladimir; Tikhonov, Yury; Timoshenko, Sergey; Tiouchichine, Elodie; Tipton, Paul; Tisserant, Sylvain; Todorov, Theodore; Todorova-Nova, Sharka; Toggerson, Brokk; Tojo, Junji; Tokár, Stanislav; Tokushuku, Katsuo; Tollefson, Kirsten; Tomlinson, Lee; Tomoto, Makoto; Tompkins, Lauren; Toms, Konstantin; Topilin, Nikolai; Torrence, Eric; Torres, Heberth; Torró Pastor, Emma; Toth, Jozsef; Touchard, Francois; Tovey, Daniel; Tran, Huong Lan; Trefzger, Thomas; Tremblet, Louis; Tricoli, Alessandro; Trigger, Isabel Marian; Trincaz-Duvoid, Sophie; 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Valero, Alberto; Valery, Loic; Valkar, Stefan; Valladolid Gallego, Eva; Vallecorsa, Sofia; Valls Ferrer, Juan Antonio; Van Den Wollenberg, Wouter; Van Der Deijl, Pieter; van der Geer, Rogier; van der Graaf, Harry; Van Der Leeuw, Robin; van der Ster, Daniel; van Eldik, Niels; van Gemmeren, Peter; Van Nieuwkoop, Jacobus; van Vulpen, Ivo; van Woerden, Marius Cornelis; Vanadia, Marco; Vandelli, Wainer; Vanguri, Rami; Vaniachine, Alexandre; Vankov, Peter; Vannucci, Francois; Vardanyan, Gagik; Vari, Riccardo; Varnes, Erich; Varol, Tulin; Varouchas, Dimitris; Vartapetian, Armen; Varvell, Kevin; Vazeille, Francois; Vazquez Schroeder, Tamara; Veatch, Jason; Veloso, Filipe; Veneziano, Stefano; Ventura, Andrea; Ventura, Daniel; Venturi, Manuela; Venturi, Nicola; Venturini, Alessio; Vercesi, Valerio; Verducci, Monica; Verkerke, Wouter; Vermeulen, Jos; Vest, Anja; Vetterli, Michel; Viazlo, Oleksandr; Vichou, Irene; Vickey, Trevor; Vickey Boeriu, Oana Elena; Viehhauser, Georg; Viel, Simon; Vigne, Ralph; 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Yuan, Li; Yurkewicz, Adam; Yusuff, Imran; Zabinski, Bartlomiej; Zaidan, Remi; Zaitsev, Alexander; Zaman, Aungshuman; Zambito, Stefano; Zanello, Lucia; Zanzi, Daniele; Zeitnitz, Christian; Zeman, Martin; Zemla, Andrzej; Zengel, Keith; Zenin, Oleg; Ženiš, Tibor; Zerwas, Dirk; Zevi della Porta, Giovanni; Zhang, Dongliang; Zhang, Fangzhou; Zhang, Huaqiao; Zhang, Jinlong; Zhang, Lei; Zhang, Xueyao; Zhang, Zhiqing; Zhao, Zhengguo; Zhemchugov, Alexey; Zhong, Jiahang; Zhou, Bing; Zhou, Lei; Zhou, Ning; Zhu, Cheng Guang; Zhu, Hongbo; Zhu, Junjie; Zhu, Yingchun; Zhuang, Xuai; Zhukov, Konstantin; Zibell, Andre; Zieminska, Daria; Zimine, Nikolai; Zimmermann, Christoph; Zimmermann, Robert; Zimmermann, Simone; Zimmermann, Stephanie; Zinonos, Zinonas; Ziolkowski, Michael; Zobernig, Georg; Zoccoli, Antonio; zur Nedden, Martin; Zurzolo, Giovanni; Zutshi, Vishnu; Zwalinski, Lukasz

2014-09-15

A novel technique to identify and split clusters created by multiple charged particles in the ATLAS pixel detector using a set of artificial neural networks is presented. Such merged clusters are a common feature of tracks originating from highly energetic objects, such as jets. Neural networks are trained using Monte Carlo samples produced with a detailed detector simulation. This technique replaces the former clustering approach based on a connected component analysis and charge interpolation. The performance of the neural network splitting technique is quantified using data from proton-proton collisions at the LHC collected by the ATLAS detector in 2011 and from Monte Carlo simulations. This technique reduces the number of clusters shared between tracks in highly energetic jets by up to a factor of three. It also provides more precise position and error estimates of the clusters in both the transverse and longitudinal impact parameter resolution.

Cluster-cluster clustering

International Nuclear Information System (INIS)

Barnes, J.; Dekel, A.; Efstathiou, G.; Frenk, C.S.; Yale Univ., New Haven, CT; California Univ., Santa Barbara; Cambridge Univ., England; Sussex Univ., Brighton, England)

1985-01-01

The cluster correlation function xi sub c(r) is compared with the particle correlation function, xi(r) in cosmological N-body simulations with a wide range of initial conditions. The experiments include scale-free initial conditions, pancake models with a coherence length in the initial density field, and hybrid models. Three N-body techniques and two cluster-finding algorithms are used. In scale-free models with white noise initial conditions, xi sub c and xi are essentially identical. In scale-free models with more power on large scales, it is found that the amplitude of xi sub c increases with cluster richness; in this case the clusters give a biased estimate of the particle correlations. In the pancake and hybrid models (with n = 0 or 1), xi sub c is steeper than xi, but the cluster correlation length exceeds that of the points by less than a factor of 2, independent of cluster richness. Thus the high amplitude of xi sub c found in studies of rich clusters of galaxies is inconsistent with white noise and pancake models and may indicate a primordial fluctuation spectrum with substantial power on large scales. 30 references

Understanding the cluster randomised crossover design: a graphical illustraton of the components of variation and a sample size tutorial.

Science.gov (United States)

Arnup, Sarah J; McKenzie, Joanne E; Hemming, Karla; Pilcher, David; Forbes, Andrew B

2017-08-15

In a cluster randomised crossover (CRXO) design, a sequence of interventions is assigned to a group, or 'cluster' of individuals. Each cluster receives each intervention in a separate period of time, forming 'cluster-periods'. Sample size calculations for CRXO trials need to account for both the cluster randomisation and crossover aspects of the design. Formulae are available for the two-period, two-intervention, cross-sectional CRXO design, however implementation of these formulae is known to be suboptimal. The aims of this tutorial are to illustrate the intuition behind the design; and provide guidance on performing sample size calculations. Graphical illustrations are used to describe the effect of the cluster randomisation and crossover aspects of the design on the correlation between individual responses in a CRXO trial. Sample size calculations for binary and continuous outcomes are illustrated using parameters estimated from the Australia and New Zealand Intensive Care Society - Adult Patient Database (ANZICS-APD) for patient mortality and length(s) of stay (LOS). The similarity between individual responses in a CRXO trial can be understood in terms of three components of variation: variation in cluster mean response; variation in the cluster-period mean response; and variation between individual responses within a cluster-period; or equivalently in terms of the correlation between individual responses in the same cluster-period (within-cluster within-period correlation, WPC), and between individual responses in the same cluster, but in different periods (within-cluster between-period correlation, BPC). The BPC lies between zero and the WPC. When the WPC and BPC are equal the precision gained by crossover aspect of the CRXO design equals the precision lost by cluster randomisation. When the BPC is zero there is no advantage in a CRXO over a parallel-group cluster randomised trial. Sample size calculations illustrate that small changes in the specification of

Cluster designs to assess the prevalence of acute malnutrition by lot quality assurance sampling: a validation study by computer simulation.

Science.gov (United States)

Olives, Casey; Pagano, Marcello; Deitchler, Megan; Hedt, Bethany L; Egge, Kari; Valadez, Joseph J

2009-04-01

Traditional lot quality assurance sampling (LQAS) methods require simple random sampling to guarantee valid results. However, cluster sampling has been proposed to reduce the number of random starting points. This study uses simulations to examine the classification error of two such designs, a 67x3 (67 clusters of three observations) and a 33x6 (33 clusters of six observations) sampling scheme to assess the prevalence of global acute malnutrition (GAM). Further, we explore the use of a 67x3 sequential sampling scheme for LQAS classification of GAM prevalence. Results indicate that, for independent clusters with moderate intracluster correlation for the GAM outcome, the three sampling designs maintain approximate validity for LQAS analysis. Sequential sampling can substantially reduce the average sample size that is required for data collection. The presence of intercluster correlation can impact dramatically the classification error that is associated with LQAS analysis.

The clustering evolution of distant red galaxies in the GOODS-MUSIC sample

Science.gov (United States)

Grazian, A.; Fontana, A.; Moscardini, L.; Salimbeni, S.; Menci, N.; Giallongo, E.; de Santis, C.; Gallozzi, S.; Nonino, M.; Cristiani, S.; Vanzella, E.

2006-07-01

Aims.We study the clustering properties of Distant Red Galaxies (DRGs) to test whether they are the progenitors of local massive galaxies. Methods.We use the GOODS-MUSIC sample, a catalog of ~3000 Ks-selected galaxies based on VLT and HST observation of the GOODS-South field with extended multi-wavelength coverage (from 0.3 to 8~μm) and accurate estimates of the photometric redshifts to select 179 DRGs with J-Ks≥ 1.3 in an area of 135 sq. arcmin.Results.We first show that the J-Ks≥ 1.3 criterion selects a rather heterogeneous sample of galaxies, going from the targeted high-redshift luminous evolved systems, to a significant fraction of lower redshift (1mass, like groups or small galaxy clusters. Low-z DRGs, on the other hand, will likely evolve into slightly less massive field galaxies.

New materials for sample preparation techniques in bioanalysis.

Science.gov (United States)

Nazario, Carlos Eduardo Domingues; Fumes, Bruno Henrique; da Silva, Meire Ribeiro; Lanças, Fernando Mauro

2017-02-01

The analysis of biological samples is a complex and difficult task owing to two basic and complementary issues: the high complexity of most biological matrices and the need to determine minute quantities of active substances and contaminants in such complex sample. To succeed in this endeavor samples are usually subject to three steps of a comprehensive analytical methodological approach: sample preparation, analytes isolation (usually utilizing a chromatographic technique) and qualitative/quantitative analysis (usually with the aid of mass spectrometric tools). Owing to the complex nature of bio-samples, and the very low concentration of the target analytes to be determined, selective sample preparation techniques is mandatory in order to overcome the difficulties imposed by these two constraints. During the last decade new chemical synthesis approaches has been developed and optimized, such as sol-gel and molecularly imprinting technologies, allowing the preparation of novel materials for sample preparation including graphene and derivatives, magnetic materials, ionic liquids, molecularly imprinted polymers, and much more. In this contribution we will review these novel techniques and materials, as well as their application to the bioanalysis niche. Copyright © 2016 Elsevier B.V. All rights reserved.

Social Learning Network Analysis Model to Identify Learning Patterns Using Ontology Clustering Techniques and Meaningful Learning

Science.gov (United States)

Firdausiah Mansur, Andi Besse; Yusof, Norazah

2013-01-01

Clustering on Social Learning Network still not explored widely, especially when the network focuses on e-learning system. Any conventional methods are not really suitable for the e-learning data. SNA requires content analysis, which involves human intervention and need to be carried out manually. Some of the previous clustering techniques need…

Classification of protein profiles using fuzzy clustering techniques

DEFF Research Database (Denmark)

Karemore, Gopal; Mullick, Jhinuk B.; Sujatha, R.

2010-01-01

 Present  study  has  brought  out  a  comparison  of PCA  and  fuzzy  clustering  techniques  in  classifying  protein profiles  (chromatogram)  of  homogenates  of  different  tissue origins:  Ovarian,  Cervix,  Oral  cancers,  which  were  acquired using HPLC–LIF (High Performance Liquid...... Chromatography- Laser   Induced   Fluorescence)   method   developed   in   our laboratory. Study includes 11 chromatogram spectra each from oral,  cervical,  ovarian  cancers  as  well  as  healthy  volunteers. Generally  multivariate  analysis  like  PCA  demands  clear  data that   is   devoid   of   day......   PCA   mapping   in   classifying   various cancers from healthy spectra with classification rate up to 95 % from  60%.  Methods  are  validated  using  various  clustering indexes   and   shows   promising   improvement   in   developing optical pathology like HPLC-LIF for early detection of various...

The Effect of Roundtable and Clustering Teaching Techniques and Students’ Personal Traits on Students’ Achievement in Descriptive Writing

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Megawati Sinaga

2017-12-01

Full Text Available The Objectives of this paper as an experimental research was to investigate the effect of Roundtable and Clustering teaching techniques and students’ personal traits on students’ achievement in descriptive writing. The students in grade ix of SMP Negeri 2 Pancurbatu 2016/2017 school academic year were chose as the population of this research.. The research design was experimental research by using factorial design 2x2. The students were divided into two experimental groups. The experimental group was treated by using Roundtable teaching technique and control group was treated by using Clustering teaching technique. The students are classified into the introvert and extrovert personal traits by conducting the questionnaire and the students’ achievement in descriptive writing was measured by using writing test, namely ‘Analytic Scoring’ by Weigle. The data were analyzed by applying two-way analysis of variance (ANOVA at the level of significance α = 0.05. The result reveals that (1 students’ achievement in descriptive writing taught by using  Roundtable teaching technique was higher than that taught by Clustering teaching technique, with Fobs = 4.59>Ftab=3.97, (2 students’ achievement in descriptive writing with introvert  personal trait was higher than that with extrovert personal traits with Fobs=4.90 Ftable=3.97, (3 there is interaction between teaching techniques and personal traits on students’ achievement in descriptive writing with Fobs =6,58 Ftable=3.97. After computing the Tuckey-Test, the result showed that introvert students got higher achievement if they were taught by using Roundtable teaching technique while extrovert students got higher achievement if they were taught by using Clustering teaching technique.

The Atacama Cosmology Telescope: Physical Properties and Purity of a Galaxy Cluster Sample Selected Via the Sunyaev-Zel'Dovich Effect

Science.gov (United States)

Menanteau, Felipe; Gonzalez, Jorge; Juin, Jean-Baptiste; Marriage, Tobias; Reese, Erik D.; Acquaviva, Viviana; Aguirre, Paula; Appel, John Willam; Baker, Andrew J.; Barrientos, L. Felipe;

VizieR Online Data Catalog: ETGs sample for the Coma cluster (Riguccini+, 2015)

Science.gov (United States)

Riguccini, L.; Temi, P.; Amblard, A.; Fanelli, M.; Brighenti, F.

2017-10-01

For the Coma Cluster, we utilize the work of Mahajan et al. (2010, J/MNRAS/404/1745) to build our ETG sample. Mahajan et al. (2010, J/MNRAS/404/1745) used a combination of MIPS 24 μm observations and SDSS photometry and spectra to investigate the star formation history of galaxies in the Coma supercluster. All of their galaxies from the SDSS data in the Coma supercluster region are brighter than r~17.77, the completeness limit of the SDSS spectroscopic galaxy catalog. Their 24 μm fluxes are obtained from archival data covering 2x2 deg2 for Coma Cluster. Our final sample of 124 sources is composed of 49 ellipticals and 75 lenticulars. (1 data file).

Hierarchical Bayesian modelling of gene expression time series across irregularly sampled replicates and clusters.

Science.gov (United States)

Hensman, James; Lawrence, Neil D; Rattray, Magnus

2013-08-20

Time course data from microarrays and high-throughput sequencing experiments require simple, computationally efficient and powerful statistical models to extract meaningful biological signal, and for tasks such as data fusion and clustering. Existing methodologies fail to capture either the temporal or replicated nature of the experiments, and often impose constraints on the data collection process, such as regularly spaced samples, or similar sampling schema across replications. We propose hierarchical Gaussian processes as a general model of gene expression time-series, with application to a variety of problems. In particular, we illustrate the method's capacity for missing data imputation, data fusion and clustering.The method can impute data which is missing both systematically and at random: in a hold-out test on real data, performance is significantly better than commonly used imputation methods. The method's ability to model inter- and intra-cluster variance leads to more biologically meaningful clusters. The approach removes the necessity for evenly spaced samples, an advantage illustrated on a developmental Drosophila dataset with irregular replications. The hierarchical Gaussian process model provides an excellent statistical basis for several gene-expression time-series tasks. It has only a few additional parameters over a regular GP, has negligible additional complexity, is easily implemented and can be integrated into several existing algorithms. Our experiments were implemented in python, and are available from the authors' website: http://staffwww.dcs.shef.ac.uk/people/J.Hensman/.

Using intelligent clustering techniques to classify the energy performance of school buildings

Energy Technology Data Exchange (ETDEWEB)

Santamouris, M.; Sfakianaki, K.; Papaglastra, M.; Pavlou, C.; Doukas, P.; Geros, V.; Assimakopoulos, M.N.; Zerefos, S. [University of Athens, Department of Physics, Division of Applied Physics, Laboratory of Meteorology, Athens (Greece); Mihalakakou, G.; Gaitani, N. [University of Ioannina, Department of Environmental and Natural Resources Management, Agrinio (Greece); Patargias, P. [University of Peloponnesus, Faculty of Human Sciences and Cultural Studies, Department of History, Kalamata (Greece); Primikiri, E. [University of Patras, Department of Architecture, Patras (Greece); Mitoula, R. [Charokopion University of Athens, Athens (Greece)

2007-07-01

The present paper deals with the energy performance, energy classification and rating and the global environmental quality of school buildings. A new energy classification technique based on intelligent clustering methodologies is proposed. Energy rating of school buildings provides specific information on their energy consumption and efficiency relative to the other buildings of similar nature and permits a better planning of interventions to improve its energy performance. The overall work reported in the present paper, is carried out in three phases. During the first phase energy consumption data have been collected through energy surveys performed in 320 schools in Greece. In the second phase an innovative energy rating scheme based on fuzzy clustering techniques has been developed, while in the third phase, 10 schools have been selected and detailed measurements of their energy efficiency and performance as well as of the global environmental quality have been performed using a specific experimental protocol. The proposed energy rating method has been applied while the main environmental and energy problems have been identified. The potential for energy and environmental improvements has been assessed. (author)

Conceptual clustering and its relation to numerical taxonomy

International Nuclear Information System (INIS)

Fisher, D.; Langley, P.

1986-01-01

Artificial Intelligence (AI) methods for machine learning can be viewed as forms of exploratory data analysis, even though they differ markedly from the statistical methods generally connoted by the term. The distinction between methods of machine learning and statistical data analysis is primarily due to differences in the way techniques of each type represent data and structure within data. That is, methods of machine learning are strongly biased toward symbolic (as opposed to numeric) data representations. The authors explore this difference within a limited context, devoting the bulk of our chapter to the explication of conceptual clustering, an extension to the statistically based methods of numerical taxonomy. In conceptual clustering the formation of object cluster is dependent on the quality of 'higher level' characterization, termed concepts, of the clusters. The form of concepts used by existing conceptual clustering systems (sets of necessary and sufficient conditions) is described in some detail. This is followed by descriptions of several conceptual clustering techniques, along with sample output. They conclude with a discussion of how alternative concept representations might enhance the effectiveness of future conceptual clustering systems

On the errors on Omega(0): Monte Carlo simulations of the EMSS cluster sample

DEFF Research Database (Denmark)

Oukbir, J.; Arnaud, M.

2001-01-01

We perform Monte Carlo simulations of synthetic EMSS cluster samples, to quantify the systematic errors and the statistical uncertainties on the estimate of Omega (0) derived from fits to the cluster number density evolution and to the X-ray temperature distribution up to z=0.83. We identify...... the scatter around the relation between cluster X-ray luminosity and temperature to be a source of systematic error, of the order of Delta (syst)Omega (0) = 0.09, if not properly taken into account in the modelling. After correcting for this bias, our best Omega (0) is 0.66. The uncertainties on the shape...

APPLICATION OF FUZZY C-MEANS CLUSTERING TECHNIQUE IN VEHICULAR POLLUTION

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Samarjit Das

2013-07-01

Full Text Available Presently in most of the urban areas all over the world, due to the exponential increase in traffic, vehicular pollution has become one of the key contributors to air pollution. As uncertainty prevails in the process of designating the level of pollution of a particular region, a fuzzy method can be applied to see the membership values of that region to a number of predefined clusters. Also, due to the existence of different pollutants in vehicular pollution, the data used to represent it are in the form of numerical vectors. In our work, we shall apply the fuzzy c-means technique of Bezdek on a dataset representing vehicular pollution to obtain the membership values of pollution due to vehicular emission of a city to one or more of some predefined clusters. We shall try also to see the benefits of adopting a fuzzy approach over the traditional way of determining the level of pollution of the particular region

The use of cluster sampling to determine aid needs in Grozny, Chechnya in 1995.

Science.gov (United States)

Drysdale, S; Howarth, J; Powell, V; Healing, T

2000-09-01

War broke out in Chechnya in November 1994 following a three-year economic blockade. It caused widespread destruction in the capital Grozny. In April 1995 Medical Relief International--or Merlin, a British medical non-governmental organisation (NGO)--began a programme to provide medical supplies, support health centres, control communicable disease and promote preventive health-care in Grozny. In July 1995 the agency undertook a city-wide needs assessment using a modification of the cluster sampling technique developed by the Expanded Programme on Immunisation. This showed that most people had enough drinking-water, food and fuel but that provision of medical care was inadequate. The survey allowed Merlin to redirect resources earmarked for a clean water programme towards health education and improving primary health-care services. It also showed that rapid assessment by a statistically satisfactory method is both possible and useful in such a situation.

A comparative study of sampling techniques for monitoring carcass contamination

NARCIS (Netherlands)

Snijders, J.M.A.; Janssen, M.H.W.; Gerats, G.E.; Corstiaensen, G.P.

1984-01-01

Four bacteriological sampling techniques i.e. the excision, double swab, agar contract and modified agar contact techniques were compared by sampling pig carcasses before and after chilling. As well as assessing the advantages and disadvantages of the techniques particular attention was paid to

Sample preparation for special PIE-techniques at ITU

International Nuclear Information System (INIS)

Toscano, E.H.; Manzel, R.

2002-01-01

Several sample preparation techniques were developed and installed in hot cells. The techniques were conceived to evaluate the performance of highly burnt fuel rods and include: (a) a device for the removal of the fuel, (b) a method for the preparation of the specimen ends for the welding of new end caps and for the careful cleaning of samples for Transmission Electron Microscopy and Glow Discharge Mass Spectroscopy, (c) a sample pressurisation device for long term creep tests, and (d) a diameter measuring device for creep or burst samples. Examples of the determination of the mechanical properties, the behaviour under transient conditions and for the assessment of the corrosion behaviour of high burnup cladding materials are presented. (author)

Fuzzy C-Means Clustering Model Data Mining For Recognizing Stock Data Sampling Pattern

Directory of Open Access Journals (Sweden)

Sylvia Jane Annatje Sumarauw

2007-06-01

Full Text Available Abstract Capital market has been beneficial to companies and investor. For investors, the capital market provides two economical advantages, namely deviden and capital gain, and a non-economical one that is a voting .} hare in Shareholders General Meeting. But, it can also penalize the share owners. In order to prevent them from the risk, the investors should predict the prospect of their companies. As a consequence of having an abstract commodity, the share quality will be determined by the validity of their company profile information. Any information of stock value fluctuation from Jakarta Stock Exchange can be a useful consideration and a good measurement for data analysis. In the context of preventing the shareholders from the risk, this research focuses on stock data sample category or stock data sample pattern by using Fuzzy c-Me, MS Clustering Model which providing any useful information jar the investors. lite research analyses stock data such as Individual Index, Volume and Amount on Property and Real Estate Emitter Group at Jakarta Stock Exchange from January 1 till December 31 of 204. 'he mining process follows Cross Industry Standard Process model for Data Mining (CRISP,. DM in the form of circle with these steps: Business Understanding, Data Understanding, Data Preparation, Modelling, Evaluation and Deployment. At this modelling process, the Fuzzy c-Means Clustering Model will be applied. Data Mining Fuzzy c-Means Clustering Model can analyze stock data in a big database with many complex variables especially for finding the data sample pattern, and then building Fuzzy Inference System for stimulating inputs to be outputs that based on Fuzzy Logic by recognising the pattern. Keywords: Data Mining, AUz..:y c-Means Clustering Model, Pattern Recognition

Melodic pattern discovery by structural analysis via wavelets and clustering techniques

DEFF Research Database (Denmark)

Velarde, Gissel; Meredith, David

We present an automatic method to support melodic pattern discovery by structural analysis of symbolic representations by means of wavelet analysis and clustering techniques. In previous work, we used the method to recognize the parent works of melodic segments, or to classify tunes into tune......-means to cluster melodic segments into groups of measured similarity and obtain a raking of the most prototypical melodic segments or patterns and their occurrences. We test the method on the JKU Patterns Development Database and evaluate it based on the ground truth defined by the MIREX 2013 Discovery of Repeated...... Themes & Sections task. We compare the results of our method to the output of geometric approaches. Finally, we discuss about the relevance of our wavelet-based analysis in relation to structure, pattern discovery, similarity and variation, and comment about the considerations of the method when used...

New trends in sample preparation techniques for environmental analysis.

Science.gov (United States)

Ribeiro, Cláudia; Ribeiro, Ana Rita; Maia, Alexandra S; Gonçalves, Virgínia M F; Tiritan, Maria Elizabeth

2014-01-01

Environmental samples include a wide variety of complex matrices, with low concentrations of analytes and presence of several interferences. Sample preparation is a critical step and the main source of uncertainties in the analysis of environmental samples, and it is usually laborious, high cost, time consuming, and polluting. In this context, there is increasing interest in developing faster, cost-effective, and environmentally friendly sample preparation techniques. Recently, new methods have been developed and optimized in order to miniaturize extraction steps, to reduce solvent consumption or become solventless, and to automate systems. This review attempts to present an overview of the fundamentals, procedure, and application of the most recently developed sample preparation techniques for the extraction, cleanup, and concentration of organic pollutants from environmental samples. These techniques include: solid phase microextraction, on-line solid phase extraction, microextraction by packed sorbent, dispersive liquid-liquid microextraction, and QuEChERS (Quick, Easy, Cheap, Effective, Rugged and Safe).

The X-ray luminosity-temperature relation of a complete sample of low-mass galaxy clusters

DEFF Research Database (Denmark)

Zou, S.; Maughan, B. J.; Giles, P. A.

2016-01-01

found for massive clusters to a steeper slope for the lower mass sample studied here. Thanks to our rigorous treatment of selection biases, these measurements provide a robust reference against which to compare predictions of models of the impact of feedback on the X-ray properties of galaxy groups....... (T), taking selection biases fully into account. The logarithmic slope of the bolometric L-T relation was found to be 3.29 ± 0.33, consistent with values typically found for samples of more massive clusters. In combination with other recent studies of the L-T relation, we show...

An Archival Search For Young Globular Clusters in Galaxies

Science.gov (United States)

Whitmore, Brad

1995-07-01

One of the most intriguing results from HST has been the discovery of ultraluminous star clusters in interacting and merging galaxies. These clusters have the luminosities, colors, and sizes that would be expected of young globular clusters produced by the interaction. We propose to use the data in the HST Archive to determine how prevalent this phenomena is, and to determine whether similar clusters are produced in other environments. Three samples will be extracted and studied in a systematic and consistent manner: 1} interacting and merging galaxies, 2} starburst galaxies, 3} a control sample of ``normal'' galaxies. A preliminary search of the archives shows that there are at least 20 galaxies in each of these samples, and the number will grow by about 50 observations become available. The data will be used to determine the luminosity function, color histogram , spatial distribution, and structural properties of the clusters using the same techniques employed in our study of NGC 7252 {``Atoms -for-Peace'' galaxy} and NGC 4038/4039 {``The Antennae''}. Our ultimate goals are: 1} to understand how globular clusters form, and 2} to use the clusters as evolutionary tracers to unravel the histories of interacting galaxies.

Assessment of Random Assignment in Training and Test Sets using Generalized Cluster Analysis Technique

Directory of Open Access Journals (Sweden)

Sorana D. BOLBOACĂ

2011-06-01

Full Text Available Aim: The properness of random assignment of compounds in training and validation sets was assessed using the generalized cluster technique. Material and Method: A quantitative Structure-Activity Relationship model using Molecular Descriptors Family on Vertices was evaluated in terms of assignment of carboquinone derivatives in training and test sets during the leave-many-out analysis. Assignment of compounds was investigated using five variables: observed anticancer activity and four structure descriptors. Generalized cluster analysis with K-means algorithm was applied in order to investigate if the assignment of compounds was or not proper. The Euclidian distance and maximization of the initial distance using a cross-validation with a v-fold of 10 was applied. Results: All five variables included in analysis proved to have statistically significant contribution in identification of clusters. Three clusters were identified, each of them containing both carboquinone derivatives belonging to training as well as to test sets. The observed activity of carboquinone derivatives proved to be normal distributed on every. The presence of training and test sets in all clusters identified using generalized cluster analysis with K-means algorithm and the distribution of observed activity within clusters sustain a proper assignment of compounds in training and test set. Conclusion: Generalized cluster analysis using the K-means algorithm proved to be a valid method in assessment of random assignment of carboquinone derivatives in training and test sets.

Cluster Ion Implantation in Graphite and Diamond

DEFF Research Database (Denmark)

Popok, Vladimir

2014-01-01

Cluster ion beam technique is a versatile tool which can be used for controllable formation of nanosize objects as well as modification and processing of surfaces and shallow layers on an atomic scale. The current paper present an overview and analysis of data obtained on a few sets of graphite...... and diamond samples implanted by keV-energy size-selected cobalt and argon clusters. One of the emphases is put on pinning of metal clusters on graphite with a possibility of following selective etching of graphene layers. The other topic of concern is related to the development of scaling law for cluster...... implantation. Implantation of cobalt and argon clusters into two different allotropic forms of carbon, namely, graphite and diamond is analysed and compared in order to approach universal theory of cluster stopping in matter....

Non-terminal blood sampling techniques in Guinea pigs

DEFF Research Database (Denmark)

Birck, Malene Muusfeldt; Tveden-Nyborg, Pernille; Lindblad, Maiken Marie

2014-01-01

Guinea pigs possess several biological similarities to humans and are validated experimental animal models(1-3). However, the use of guinea pigs currently represents a relatively narrow area of research and descriptive data on specific methodology is correspondingly scarce. The anatomical features...... of guinea pigs are slightly different from other rodent models, hence modulation of sampling techniques to accommodate for species-specific differences, e.g., compared to mice and rats, are necessary to obtain sufficient and high quality samples. As both long and short term in vivo studies often require...... repeated blood sampling the choice of technique should be well considered in order to reduce stress and discomfort in the animals but also to ensure survival as well as compliance with requirements of sample size and accessibility. Venous blood samples can be obtained at a number of sites in guinea pigs e...

The Gemini/HST Galaxy Cluster Project: Redshift 0.2–1.0 Cluster Sample, X-Ray Data, and Optical Photometry Catalog

Science.gov (United States)

Jørgensen, Inger; Chiboucas, Kristin; Hibon, Pascale; Nielsen, Louise D.; Takamiya, Marianne

2018-04-01

The Gemini/HST Galaxy Cluster Project (GCP) covers 14 z = 0.2–1.0 clusters with X-ray luminosity of {L}500≥slant {10}44 {erg} {{{s}}}-1 in the 0.1–2.4 keV band. In this paper, we provide homogeneously calibrated X-ray luminosities, masses, and radii, and we present the complete catalog of the ground-based photometry for the GCP clusters. The clusters were observed with either Gemini North or South in three or four of the optical passbands g‧, r‧, i‧, and z‧. The photometric catalog includes consistently calibrated total magnitudes, colors, and geometrical parameters. The photometry reaches ≈25 mag in the passband closest to the rest-frame B band. We summarize comparisons of our photometry with data from the Sloan Digital Sky Survey. We describe the sample selection for our spectroscopic observations, and establish the calibrations to obtain rest-frame magnitudes and colors. Finally, we derive the color–magnitude relations for the clusters, and briefly discuss these in the context of evolution with redshift. Consistent with our results based on spectroscopic data, the color–magnitude relations support passive evolution of the red sequence galaxies. The absence of change in the slope with redshift constrains the allowable age variation along the red sequence to <0.05 dex between the brightest cluster galaxies and those four magnitudes fainter. This paper serves as the main reference for the GCP cluster and galaxy selection, X-ray data, and ground-based photometry.

Clustering of commercial fish sauce products based on an e-panel technique

Directory of Open Access Journals (Sweden)

Mitsutoshi Nakano

2018-02-01

Full Text Available Fish sauce is a brownish liquid seasoning with a characteristic flavor that is produced in Asian countries and limited areas of Europe. The types of fish and shellfish and fermentation process used in its production depend on the region from which it derives. Variations in ingredients and fermentation procedures yield end products with different smells, tastes, and colors. For this data article, we employed an electronic panel (e-panel technique including an electronic nose (e-nose, electronic tongue (e-tongue, and electronic eye (e-eye, in which smell, taste, and color are evaluated by sensors instead of the human nose, tongue, and eye to avoid subjective error. The presented data comprise clustering of 46 commercially available fish sauce products based separate e-nose, e-tongue, and e-eye test results. Sensory intensity data from the e-nose, e-tongue, and e-eye were separately classified by cluster analysis and are shown in dendrograms. The hierarchical cluster analysis indicates major three groups on e-nose and e-tongue data, and major four groups on e-eye data.

Comparison of sampling techniques for Bayesian parameter estimation

Science.gov (United States)

Allison, Rupert; Dunkley, Joanna

2014-02-01

The posterior probability distribution for a set of model parameters encodes all that the data have to tell us in the context of a given model; it is the fundamental quantity for Bayesian parameter estimation. In order to infer the posterior probability distribution we have to decide how to explore parameter space. Here we compare three prescriptions for how parameter space is navigated, discussing their relative merits. We consider Metropolis-Hasting sampling, nested sampling and affine-invariant ensemble Markov chain Monte Carlo (MCMC) sampling. We focus on their performance on toy-model Gaussian likelihoods and on a real-world cosmological data set. We outline the sampling algorithms themselves and elaborate on performance diagnostics such as convergence time, scope for parallelization, dimensional scaling, requisite tunings and suitability for non-Gaussian distributions. We find that nested sampling delivers high-fidelity estimates for posterior statistics at low computational cost, and should be adopted in favour of Metropolis-Hastings in many cases. Affine-invariant MCMC is competitive when computing clusters can be utilized for massive parallelization. Affine-invariant MCMC and existing extensions to nested sampling naturally probe multimodal and curving distributions.

THE ATACAMA COSMOLOGY TELESCOPE: DYNAMICAL MASSES AND SCALING RELATIONS FOR A SAMPLE OF MASSIVE SUNYAEV-ZEL'DOVICH EFFECT SELECTED GALAXY CLUSTERS ,

International Nuclear Information System (INIS)

Sifón, Cristóbal; Barrientos, L. Felipe; González, Jorge; Infante, Leopoldo; Dünner, Rolando; Menanteau, Felipe; Hughes, John P.; Baker, Andrew J.; Hasselfield, Matthew; Marriage, Tobias A.; Crichton, Devin; Gralla, Megan B.; Addison, Graeme E.; Dunkley, Joanna; Battaglia, Nick; Bond, J. Richard; Hajian, Amir; Das, Sudeep; Devlin, Mark J.; Hilton, Matt

2013-01-01

We present the first dynamical mass estimates and scaling relations for a sample of Sunyaev-Zel'dovich effect (SZE) selected galaxy clusters. The sample consists of 16 massive clusters detected with the Atacama Cosmology Telescope (ACT) over a 455 deg 2 area of the southern sky. Deep multi-object spectroscopic observations were taken to secure intermediate-resolution (R ∼ 700-800) spectra and redshifts for ≈60 member galaxies on average per cluster. The dynamical masses M 200c of the clusters have been calculated using simulation-based scaling relations between velocity dispersion and mass. The sample has a median redshift z = 0.50 and a median mass M 200c ≅12×10 14 h 70 -1 M sun with a lower limit M 200c ≅6×10 14 h 70 -1 M sun , consistent with the expectations for the ACT southern sky survey. These masses are compared to the ACT SZE properties of the sample, specifically, the match-filtered central SZE amplitude y 0 -tilde, the central Compton parameter y 0 , and the integrated Compton signal Y 200c , which we use to derive SZE-mass scaling relations. All SZE estimators correlate with dynamical mass with low intrinsic scatter (∼< 20%), in agreement with numerical simulations. We explore the effects of various systematic effects on these scaling relations, including the correlation between observables and the influence of dynamically disturbed clusters. Using the three-dimensional information available, we divide the sample into relaxed and disturbed clusters and find that ∼50% of the clusters are disturbed. There are hints that disturbed systems might bias the scaling relations, but given the current sample sizes, these differences are not significant; further studies including more clusters are required to assess the impact of these clusters on the scaling relations

Seeing deconvolution of globular clusters in M31

International Nuclear Information System (INIS)

Bendinelli, O.; Zavatti, F.; Parmeggiani, G.; Djorgovski, S.

1990-01-01

The morphology of six M31 globular clusters is examined using seeing-deconvolved CCD images. The deconvolution techniques developed by Bendinelli (1989) are reviewed and applied to the M31 globular clusters to demonstrate the methodology. It is found that the effective resolution limit of the method is about 0.1-0.3 arcsec for CCD images obtained in FWHM = 1 arcsec seeing, and sampling of 0.3 arcsec/pixel. Also, the robustness of the method is discussed. The implications of the technique for future studies using data from the Hubble Space Telescope are considered. 68 refs

IDENTIFICATION OF MEMBERS IN THE CENTRAL AND OUTER REGIONS OF GALAXY CLUSTERS

International Nuclear Information System (INIS)

Serra, Ana Laura; Diaferio, Antonaldo

2013-01-01

The caustic technique measures the mass of galaxy clusters in both their virial and infall regions and, as a byproduct, yields the list of cluster galaxy members. Here we use 100 galaxy clusters with mass M 200 ≥ 10 14 h –1 M ☉ extracted from a cosmological N-body simulation of a ΛCDM universe to test the ability of the caustic technique to identify the cluster galaxy members. We identify the true three-dimensional members as the gravitationally bound galaxies. The caustic technique uses the caustic location in the redshift diagram to separate the cluster members from the interlopers. We apply the technique to mock catalogs containing 1000 galaxies in the field of view of 12 h –1 Mpc on a side at the cluster location. On average, this sample size roughly corresponds to 180 real galaxy members within 3r 200 , similar to recent redshift surveys of cluster regions. The caustic technique yields a completeness, the fraction of identified true members, f c = 0.95 ± 0.03, within 3r 200 . The contamination, the fraction of interlopers in the observed catalog of members, increases from f i =0.020 +0.046 -0.015 at r 200 to f i =0.08 +0.11 -0.05 at 3r 200 . No other technique for the identification of the members of a galaxy cluster provides such large completeness and small contamination at these large radii. The caustic technique assumes spherical symmetry and the asphericity of the cluster is responsible for most of the spread of the completeness and the contamination. By applying the technique to an approximately spherical system obtained by stacking the individual clusters, the spreads decrease by at least a factor of two. We finally estimate the cluster mass within 3r 200 after removing the interlopers: for individual clusters, the mass estimated with the virial theorem is unbiased and within 30% of the actual mass; this spread decreases to less than 10% for the spherically symmetric stacked cluster.

Don't spin the pen: two alternative methods for second-stage sampling in urban cluster surveys

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Rose Angela MC

2007-06-01

Full Text Available Abstract In two-stage cluster surveys, the traditional method used in second-stage sampling (in which the first household in a cluster is selected is time-consuming and may result in biased estimates of the indicator of interest. Firstly, a random direction from the center of the cluster is selected, usually by spinning a pen. The houses along that direction are then counted out to the boundary of the cluster, and one is then selected at random to be the first household surveyed. This process favors households towards the center of the cluster, but it could easily be improved. During a recent meningitis vaccination coverage survey in Maradi, Niger, we compared this method of first household selection to two alternatives in urban zones: 1 using a superimposed grid on the map of the cluster area and randomly selecting an intersection; and 2 drawing the perimeter of the cluster area using a Global Positioning System (GPS and randomly selecting one point within the perimeter. Although we only compared a limited number of clusters using each method, we found the sampling grid method to be the fastest and easiest for field survey teams, although it does require a map of the area. Selecting a random GPS point was also found to be a good method, once adequate training can be provided. Spinning the pen and counting households to the boundary was the most complicated and time-consuming. The two methods tested here represent simpler, quicker and potentially more robust alternatives to spinning the pen for cluster surveys in urban areas. However, in rural areas, these alternatives would favor initial household selection from lower density (or even potentially empty areas. Bearing in mind these limitations, as well as available resources and feasibility, investigators should choose the most appropriate method for their particular survey context.

Clustered lot quality assurance sampling to assess immunisation coverage: increasing rapidity and maintaining precision.

Science.gov (United States)

Pezzoli, Lorenzo; Andrews, Nick; Ronveaux, Olivier

2010-05-01

Vaccination programmes targeting disease elimination aim to achieve very high coverage levels (e.g. 95%). We calculated the precision of different clustered lot quality assurance sampling (LQAS) designs in computer-simulated surveys to provide local health officers in the field with preset LQAS plans to simply and rapidly assess programmes with high coverage targets. We calculated sample size (N), decision value (d) and misclassification errors (alpha and beta) of several LQAS plans by running 10 000 simulations. We kept the upper coverage threshold (UT) at 90% or 95% and decreased the lower threshold (LT) progressively by 5%. We measured the proportion of simulations with d unvaccinated individuals if the coverage was LT% (pLT) to calculate alpha (1-pLT). We divided N in clusters (between 5 and 10) and recalculated the errors hypothesising that the coverage would vary in the clusters according to a binomial distribution with preset standard deviations of 0.05 and 0.1 from the mean lot coverage. We selected the plans fulfilling these criteria: alpha LQAS plans dividing the lot in five clusters with N = 50 (5 x 10) and d = 4 to evaluate programmes with 95% coverage target and d = 7 to evaluate programmes with 90% target. These plans will considerably increase the feasibility and the rapidity of conducting the LQAS in the field.

Color Gradients Within Globular Clusters: Restricted Numerical Simulation

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Young-Jong Sohn

1997-06-01

Full Text Available The results of a restricted numerical simulation for the color gradients within globular clusters have been presented. The standard luminosity function of M3 and Salpeter's initial mass functions were used to generate model clusters as a fundamental population. Color gradients with the sample clusters for both King and power law cusp models of surface brightness distributions are discussed in the case of using the standard luminosity function. The dependence of color gradients on several parameters for the simulations with Salpeter's initial mass functions, such as slope of initial mass functions, cluster ages, metallicities, concentration parameters of King model, and slopes of power law, are also discussed. No significant radial color gradients are shown to the sample clusters which are regenerated by a random number generation technique with various parameters in both of King and power law cusp models of surface brightness distributions. Dynamical mass segregation and stellar evolution of horizontal branch stars and blue stragglers should be included for the general case of model simulations to show the observed radial color gradients within globular clusters.

Cluster Sampling Bias in Government-Sponsored Evaluations: A Correlational Study of Employment and Welfare Pilots in England.

Science.gov (United States)

Vaganay, Arnaud

2016-01-01

For pilot or experimental employment programme results to apply beyond their test bed, researchers must select 'clusters' (i.e. the job centres delivering the new intervention) that are reasonably representative of the whole territory. More specifically, this requirement must account for conditions that could artificially inflate the effect of a programme, such as the fluidity of the local labour market or the performance of the local job centre. Failure to achieve representativeness results in Cluster Sampling Bias (CSB). This paper makes three contributions to the literature. Theoretically, it approaches the notion of CSB as a human behaviour. It offers a comprehensive theory, whereby researchers with limited resources and conflicting priorities tend to oversample 'effect-enhancing' clusters when piloting a new intervention. Methodologically, it advocates for a 'narrow and deep' scope, as opposed to the 'wide and shallow' scope, which has prevailed so far. The PILOT-2 dataset was developed to test this idea. Empirically, it provides evidence on the prevalence of CSB. In conditions similar to the PILOT-2 case study, investigators (1) do not sample clusters with a view to maximise generalisability; (2) do not oversample 'effect-enhancing' clusters; (3) consistently oversample some clusters, including those with higher-than-average client caseloads; and (4) report their sampling decisions in an inconsistent and generally poor manner. In conclusion, although CSB is prevalent, it is still unclear whether it is intentional and meant to mislead stakeholders about the expected effect of the intervention or due to higher-level constraints or other considerations.

Employing post-DEA cross-evaluation and cluster analysis in a sample of Greek NHS hospitals.

Science.gov (United States)

Flokou, Angeliki; Kontodimopoulos, Nick; Niakas, Dimitris

2011-10-01

To increase Data Envelopment Analysis (DEA) discrimination of efficient Decision Making Units (DMUs), by complementing "self-evaluated" efficiencies with "peer-evaluated" cross-efficiencies and, based on these results, to classify the DMUs using cluster analysis. Healthcare, which is deprived of such studies, was chosen as the study area. The sample consisted of 27 small- to medium-sized (70-500 beds) NHS general hospitals distributed throughout Greece, in areas where they are the sole NHS representatives. DEA was performed on 2005 data collected from the Ministry of Health and the General Secretariat of the National Statistical Service. Three inputs -hospital beds, physicians and other health professionals- and three outputs -case-mix adjusted hospitalized cases, surgeries and outpatient visits- were included in input-oriented, constant-returns-to-scale (CRS) and variable-returns-to-scale (VRS) models. In a second stage (post-DEA), aggressive and benevolent cross-efficiency formulations and clustering were employed, to validate (or not) the initial DEA scores. The "maverick index" was used to sort the peer-appraised hospitals. All analyses were performed using custom-made software. Ten benchmark hospitals were identified by DEA, but using the aggressive and benevolent formulations showed that two and four of them respectively were at the lower end of the maverick index list. On the other hand, only one 100% efficient (self-appraised) hospital was at the higher end of the list, using either formulation. Cluster analysis produced a hierarchical "tree" structure which dichotomized the hospitals in accordance to the cross-evaluation results, and provided insight on the two-dimensional path to improving efficiency. This is, to our awareness, the first study in the healthcare domain to employ both of these post-DEA techniques (cross efficiency and clustering) at the hospital (i.e. micro) level. The potential benefit for decision-makers is the capability to examine high

Application of digital sampling techniques to particle identification

International Nuclear Information System (INIS)

Bardelli, L.; Poggi, G.; Bini, M.; Carraresi, L.; Pasquali, G.; Taccetti, N.

2003-01-01

An application of digital sampling techniques is presented which can greatly simplify experiments involving sub-nanosecond time-mark determinations and energy measurements with nuclear detectors, used for Pulse Shape Analysis and Time of Flight measurements in heavy ion experiments. In this work a 100 M Sample/s, 12 bit analog to digital converter has been used: examples of this technique applied to Silicon and CsI(Tl) detectors in heavy-ions experiments involving particle identification via Pulse Shape analysis and Time of Flight measurements are presented. The system is suited for applications to large detector arrays and to different kinds of detectors. Some preliminary results regarding the simulation of current signals in Silicon detectors are also discussed. (authors)

Objective Classification of Rainfall in Northern Europe for Online Operation of Urban Water Systems Based on Clustering Techniques

DEFF Research Database (Denmark)

Löwe, Roland; Madsen, Henrik; McSharry, Patrick

2016-01-01

operators to change modes of control of their facilities. A k-means clustering technique was applied to group events retrospectively and was able to distinguish events with clearly different temporal and spatial correlation properties. For online applications, techniques based on k-means clustering...... and quadratic discriminant analysis both provided a fast and reliable identification of rain events of "high" variability, while the k-means provided the smallest number of rain events falsely identified as being of "high" variability (false hits). A simple classification method based on a threshold...

ELEMENTAL ABUNDANCE RATIOS IN STARS OF THE OUTER GALACTIC DISK. IV. A NEW SAMPLE OF OPEN CLUSTERS

International Nuclear Information System (INIS)

Yong, David; Carney, Bruce W.; Friel, Eileen D.

2012-01-01

We present radial velocities and chemical abundances for nine stars in the old, distant open clusters Be18, Be21, Be22, Be32, and PWM4. For Be18 and PWM4, these are the first chemical abundance measurements. Combining our data with literature results produces a compilation of some 68 chemical abundance measurements in 49 unique clusters. For this combined sample, we study the chemical abundances of open clusters as a function of distance, age, and metallicity. We confirm that the metallicity gradient in the outer disk is flatter than the gradient in the vicinity of the solar neighborhood. We also confirm that the open clusters in the outer disk are metal-poor with enhancements in the ratios [α/Fe] and perhaps [Eu/Fe]. All elements show negligible or small trends between [X/Fe] and distance ( –1 ), but for some elements, there is a hint that the local (R GC GC > 13 kpc) samples may have different trends with distance. There is no evidence for significant abundance trends versus age ( –1 ). We measure the linear relation between [X/Fe] and metallicity, [Fe/H], and find that the scatter about the mean trend is comparable to the measurement uncertainties. Comparison with solar neighborhood field giants shows that the open clusters share similar abundance ratios [X/Fe] at a given metallicity. While the flattening of the metallicity gradient and enhanced [α/Fe] ratios in the outer disk suggest a chemical enrichment history different from that of the solar neighborhood, we echo the sentiments expressed by Friel et al. that definitive conclusions await homogeneous analyses of larger samples of stars in larger numbers of clusters. Arguably, our understanding of the evolution of the outer disk from open clusters is currently limited by systematic abundance differences between various studies.

Statistical Techniques Applied to Aerial Radiometric Surveys (STAARS): cluster analysis. National Uranium Resource Evaluation

International Nuclear Information System (INIS)

Pirkle, F.L.; Stablein, N.K.; Howell, J.A.; Wecksung, G.W.; Duran, B.S.

1982-11-01

One objective of the aerial radiometric surveys flown as part of the US Department of Energy's National Uranium Resource Evaluation (NURE) program was to ascertain the regional distribution of near-surface radioelement abundances. Some method for identifying groups of observations with similar radioelement values was therefore required. It is shown in this report that cluster analysis can identify such groups even when no a priori knowledge of the geology of an area exists. A method of convergent k-means cluster analysis coupled with a hierarchical cluster analysis is used to classify 6991 observations (three radiometric variables at each observation location) from the Precambrian rocks of the Copper Mountain, Wyoming, area. Another method, one that combines a principal components analysis with a convergent k-means analysis, is applied to the same data. These two methods are compared with a convergent k-means analysis that utilizes available geologic knowledge. All three methods identify four clusters. Three of the clusters represent background values for the Precambrian rocks of the area, and one represents outliers (anomalously high 214 Bi). A segmentation of the data corresponding to geologic reality as discovered by other methods has been achieved based solely on analysis of aerial radiometric data. The techniques employed are composites of classical clustering methods designed to handle the special problems presented by large data sets. 20 figures, 7 tables

Subaru Weak Lensing Measurements of Four Strong Lensing Clusters: Are Lensing Clusters Over-Concentrated?

Energy Technology Data Exchange (ETDEWEB)

Oguri, Masamune; Hennawi, Joseph F.; Gladders, Michael D.; Dahle, Haakon; Natarajan, Priyamvada; Dalal, Neal; Koester, Benjamin P.; Sharon, Keren; Bayliss, Matthew

2009-01-29

We derive radial mass profiles of four strong lensing selected clusters which show prominent giant arcs (Abell 1703, SDSS J1446+3032, SDSS J1531+3414, and SDSS J2111-0115), by combining detailed strong lens modeling with weak lensing shear measured from deep Subaru Suprime-cam images. Weak lensing signals are detected at high significance for all four clusters, whose redshifts range from z = 0.28 to 0.64. We demonstrate that adding strong lensing information with known arc redshifts significantly improves constraints on the mass density profile, compared to those obtained from weak lensing alone. While the mass profiles are well fitted by the universal form predicted in N-body simulations of the {Lambda}-dominated cold dark matter model, all four clusters appear to be slightly more centrally concentrated (the concentration parameters c{sub vir} {approx} 8) than theoretical predictions, even after accounting for the bias toward higher concentrations inherent in lensing selected samples. Our results are consistent with previous studies which similarly detected a concentration excess, and increases the total number of clusters studied with the combined strong and weak lensing technique to ten. Combining our sample with previous work, we find that clusters with larger Einstein radii are more anomalously concentrated. We also present a detailed model of the lensing cluster Abell 1703 with constraints from multiple image families, and find the dark matter inner density profile to be cuspy with the slope consistent with -1, in agreement with expectations.

A three-stage strategy for optimal price offering by a retailer based on clustering techniques

International Nuclear Information System (INIS)

Mahmoudi-Kohan, N.; Shayesteh, E.; Moghaddam, M. Parsa; Sheikh-El-Eslami, M.K.

2010-01-01

In this paper, an innovative strategy for optimal price offering to customers for maximizing the profit of a retailer is proposed. This strategy is based on load profile clustering techniques and includes three stages. For the purpose of clustering, an improved weighted fuzzy average K-means is proposed. Also, in this paper a new acceptance function for increasing the profit of the retailer is proposed. The new method is evaluated by implementation on a group of 300 customers of a 20 kV distribution network. (author)

A three-stage strategy for optimal price offering by a retailer based on clustering techniques

Energy Technology Data Exchange (ETDEWEB)

Mahmoudi-Kohan, N.; Shayesteh, E. [Islamic Azad University (Garmsar Branch), Garmsar (Iran); Moghaddam, M. Parsa; Sheikh-El-Eslami, M.K. [Tarbiat Modares University, Tehran (Iran)

2010-12-15

In this paper, an innovative strategy for optimal price offering to customers for maximizing the profit of a retailer is proposed. This strategy is based on load profile clustering techniques and includes three stages. For the purpose of clustering, an improved weighted fuzzy average K-means is proposed. Also, in this paper a new acceptance function for increasing the profit of the retailer is proposed. The new method is evaluated by implementation on a group of 300 customers of a 20 kV distribution network. (author)

Photometry Using Kepler "Superstamps" of Open Clusters NGC 6791 & NGC 6819

Science.gov (United States)

Kuehn, Charles A.; Drury, Jason A.; Bellamy, Beau R.; Stello, Dennis; Bedding, Timothy R.; Reed, Mike; Quick, Breanna

2015-09-01

The Kepler space telescope has proven to be a gold mine for the study of variable stars. Usually, Kepler only reads out a handful of pixels around each pre-selected target star, omitting a large number of stars in the Kepler field. Fortunately, for the open clusters NGC 6791 and NGC 6819, Kepler also read out larger "superstamps" which contained complete images of the central region of each cluster. These cluster images can be used to study additional stars in the open clusters that were not originally on Kepler's target list. We discuss our work on using two photometric techniques to analyze these superstamps and present sample results from this project to demonstrate the value of this technique for a wide variety of variable stars.

Sampling techniques for thrips (Thysanoptera: Thripidae) in preflowering tomato.

Science.gov (United States)

Joost, P Houston; Riley, David G

2004-08-01

Sampling techniques for thrips (Thysanoptera: Thripidae) were compared in preflowering tomato plants at the Coastal Plain Experiment Station in Tifton, GA, in 2000 and 2003, to determine the most effective method of determining abundance of thrips on tomato foliage early in the growing season. Three relative sampling techniques, including a standard insect aspirator, a 946-ml beat cup, and an insect vacuum device, were compared for accuracy to an absolute method and to themselves for precision and efficiency of sampling thrips. Thrips counts of all relative sampling methods were highly correlated (R > 0.92) to the absolute method. The aspirator method was the most accurate compared with the absolute sample according to regression analysis in 2000. In 2003, all sampling methods were considered accurate according to Dunnett's test, but thrips numbers were lower and sample variation was greater than in 2000. In 2000, the beat cup method had the lowest relative variation (RV) or best precision, at 1 and 8 d after transplant (DAT). Only the beat cup method had RV values <25 for all sampling dates. In 2003, the beat cup method had the lowest RV value at 15 and 21 DAT. The beat cup method also was the most efficient method for all sample dates in both years. Frankliniella fusca (Pergande) was the most abundant thrips species on the foliage of preflowering tomato in both years of study at this location. Overall, the best thrips sampling technique tested was the beat cup method in terms of precision and sampling efficiency.

IMPLEMENTATION OF IMPROVED NETWORK LIFETIME TECHNIQUE FOR WSN USING CLUSTER HEAD ROTATION AND SIMULTANEOUS RECEPTION

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Arun Vasanaperumal

2015-11-01

Full Text Available There are number of potential applications of Wireless Sensor Networks (WSNs like wild habitat monitoring, forest fire detection, military surveillance etc. All these applications are constrained for power from a stand along battery power source. So it becomes of paramount importance to conserve the energy utilized from this power source. A lot of efforts have gone into this area recently and it remains as one of the hot research areas. In order to improve network lifetime and reduce average power consumption, this study proposes a novel cluster head selection algorithm. Clustering is the preferred architecture when the numbers of nodes are larger because it results in considerable power savings for large networks as compared to other ones like tree or star. Since majority of the applications generally involve more than 30 nodes, clustering has gained widespread importance and is most used network architecture. The optimum number of clusters is first selected based on the number of nodes in the network. When the network is in operation the cluster heads in a cluster are rotated periodically based on the proposed cluster head selection algorithm to increase the network lifetime. Throughout the network single-hop communication methodology is assumed. This work will serve as an encouragement for further advances in the low power techniques for implementing Wireless Sensor Networks (WSNs.

A simple sample size formula for analysis of covariance in cluster randomized trials.

NARCIS (Netherlands)

Teerenstra, S.; Eldridge, S.; Graff, M.J.; Hoop, E. de; Borm, G.F.

2012-01-01

For cluster randomized trials with a continuous outcome, the sample size is often calculated as if an analysis of the outcomes at the end of the treatment period (follow-up scores) would be performed. However, often a baseline measurement of the outcome is available or feasible to obtain. An

A hybrid method based on a new clustering technique and multilayer perceptron neural networks for hourly solar radiation forecasting

International Nuclear Information System (INIS)

Azimi, R.; Ghayekhloo, M.; Ghofrani, M.

2016-01-01

Highlights: • A novel clustering approach is proposed based on the data transformation approach. • A novel cluster selection method based on correlation analysis is presented. • The proposed hybrid clustering approach leads to deep learning for MLPNN. • A hybrid forecasting method is developed to predict solar radiations. • The evaluation results show superior performance of the proposed forecasting model. - Abstract: Accurate forecasting of renewable energy sources plays a key role in their integration into the grid. This paper proposes a hybrid solar irradiance forecasting framework using a Transformation based K-means algorithm, named TB K-means, to increase the forecast accuracy. The proposed clustering method is a combination of a new initialization technique, K-means algorithm and a new gradual data transformation approach. Unlike the other K-means based clustering methods which are not capable of providing a fixed and definitive answer due to the selection of different cluster centroids for each run, the proposed clustering provides constant results for different runs of the algorithm. The proposed clustering is combined with a time-series analysis, a novel cluster selection algorithm and a multilayer perceptron neural network (MLPNN) to develop the hybrid solar radiation forecasting method for different time horizons (1 h ahead, 2 h ahead, …, 48 h ahead). The performance of the proposed TB K-means clustering is evaluated using several different datasets and compared with different variants of K-means algorithm. Solar datasets with different solar radiation characteristics are also used to determine the accuracy and processing speed of the developed forecasting method with the proposed TB K-means and other clustering techniques. The results of direct comparison with other well-established forecasting models demonstrate the superior performance of the proposed hybrid forecasting method. Furthermore, a comparative analysis with the benchmark solar

Application of Clustering Techniques for Lung Sounds to Improve Interpretability and Detection of Crackles

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Germán D. Sosa

2015-01-01

Full Text Available Due to the subjectivity involved currently in pulmonary auscultation process and its diagnostic to evaluate the condition of respiratory airways, this work pretends to evaluate the performance of clustering algorithms such as k-means and DBSCAN to perform a computational analysis of lung sounds aiming to visualize a representation of such sounds that highlights the presence of crackles and the energy associated with them. In order to achieve that goal, Wavelet analysis techniques were used in contrast to traditional frequency analysis given the similarity between the typical waveform for a crackle and the wavelet sym4. Once the lung sound signal with isolated crackles is obtained, the clustering process groups crackles in regions of high density and provides visualization that might be useful for the diagnostic made by an expert. Evaluation suggests that k-means groups crackle more effective than DBSCAN in terms of generated clusters.

Ca II TRIPLET SPECTROSCOPY OF SMALL MAGELLANIC CLOUD RED GIANTS. I. ABUNDANCES AND VELOCITIES FOR A SAMPLE OF CLUSTERS

International Nuclear Information System (INIS)

Parisi, M. C.; Claria, J. J.; Grocholski, A. J.; Geisler, D.; Sarajedini, A.

2009-01-01

We have obtained near-infrared spectra covering the Ca II triplet lines for a large number of stars associated with 16 Small Magellanic Cloud (SMC) clusters using the VLT + FORS2. These data compose the largest available sample of SMC clusters with spectroscopically derived abundances and velocities. Our clusters span a wide range of ages and provide good areal coverage of the galaxy. Cluster members are selected using a combination of their positions relative to the cluster center as well as their location in the color-magnitude diagram, abundances, and radial velocities (RVs). We determine mean cluster velocities to typically 2.7 km s -1 and metallicities to 0.05 dex (random errors), from an average of 6.4 members per cluster. By combining our clusters with previously published results, we compile a sample of 25 clusters on a homogeneous metallicity scale and with relatively small metallicity errors, and thereby investigate the metallicity distribution, metallicity gradient, and age-metallicity relation (AMR) of the SMC cluster system. For all 25 clusters in our expanded sample, the mean metallicity [Fe/H] = -0.96 with σ = 0.19. The metallicity distribution may possibly be bimodal, with peaks at ∼-0.9 dex and -1.15 dex. Similar to the Large Magellanic Cloud (LMC), the SMC cluster system gives no indication of a radial metallicity gradient. However, intermediate age SMC clusters are both significantly more metal-poor and have a larger metallicity spread than their LMC counterparts. Our AMR shows evidence for three phases: a very early (>11 Gyr) phase in which the metallicity reached ∼-1.2 dex, a long intermediate phase from ∼10 to 3 Gyr in which the metallicity only slightly increased, and a final phase from 3 to 1 Gyr ago in which the rate of enrichment was substantially faster. We find good overall agreement with the model of Pagel and Tautvaisiene, which assumes a burst of star formation at 4 Gyr. Finally, we find that the mean RV of the cluster system

Evaluation of immunization coverage in the rural area of Pune, Maharashtra, using the 30 cluster sampling technique

Directory of Open Access Journals (Sweden)

Pankaj Kumar Gupta

2013-01-01

Full Text Available Background: Infectious diseases are a major cause of morbidity and mortality in children. One of the most cost-effective and easy methods for child survival is immunization. Despite all the efforts put in by governmental and nongovernmental institutes for 100% immunization coverage, there are still pockets of low-coverage areas. In India, immunization services are offered free in public health facilities, but, despite rapid increases, the immunization rate remains low in some areas. The Millennium Development Goals (MDG indicators also give importance to immunization. Objective: To assess the immunization coverage in the rural area of Pune. Materials and Methods: A cross-sectional study was conducted in the field practice area of the Rural Health Training Center (RHTC using the WHO′s 30 cluster sampling method for evaluation of immunization coverage. Results: A total of 1913 houses were surveyed. A total of 210 children aged 12-23 months were included in the study. It was found that 86.67% of the children were fully immunized against all the six vaccine-preventable diseases. The proportion of fully immunized children was marginally higher in males (87.61% than in females (85.57%, and the immunization card was available with 60.95% of the subjects. The most common cause for partial immunization was that the time of immunization was inconvenient (36%. Conclusion: Sustained efforts are required to achieve universal coverage of immunization in the rural area of Pune district.

Manual hierarchical clustering of regional geochemical data using a Bayesian finite mixture model

International Nuclear Information System (INIS)

Ellefsen, Karl J.; Smith, David B.

2016-01-01

Interpretation of regional scale, multivariate geochemical data is aided by a statistical technique called “clustering.” We investigate a particular clustering procedure by applying it to geochemical data collected in the State of Colorado, United States of America. The clustering procedure partitions the field samples for the entire survey area into two clusters. The field samples in each cluster are partitioned again to create two subclusters, and so on. This manual procedure generates a hierarchy of clusters, and the different levels of the hierarchy show geochemical and geological processes occurring at different spatial scales. Although there are many different clustering methods, we use Bayesian finite mixture modeling with two probability distributions, which yields two clusters. The model parameters are estimated with Hamiltonian Monte Carlo sampling of the posterior probability density function, which usually has multiple modes. Each mode has its own set of model parameters; each set is checked to ensure that it is consistent both with the data and with independent geologic knowledge. The set of model parameters that is most consistent with the independent geologic knowledge is selected for detailed interpretation and partitioning of the field samples. - Highlights: • We evaluate a clustering procedure by applying it to geochemical data. • The procedure generates a hierarchy of clusters. • Different levels of the hierarchy show geochemical processes at different spatial scales. • The clustering method is Bayesian finite mixture modeling. • Model parameters are estimated with Hamiltonian Monte Carlo sampling.

The Effect of Cluster-Based Instruction on Mathematic Achievement in Inclusive Schools

Science.gov (United States)

Gunarhadi, Sunardi; Anwar, Mohammad; Andayani, Tri Rejeki; Shaari, Abdull Sukor

2016-01-01

The research aimed to investigate the effect of Cluster-Based Instruction (CBI) on the academic achievement of Mathematics in inclusive schools. The sample was 68 students in two intact classes, including those with learning disabilities, selected using a cluster random technique among 17 inclusive schools in the regency of Surakarta. The two…

Using Clustering Techniques To Detect Usage Patterns in a Web-based Information System.

Science.gov (United States)

Chen, Hui-Min; Cooper, Michael D.

2001-01-01

This study developed an analytical approach to detecting groups with homogenous usage patterns in a Web-based information system. Principal component analysis was used for data reduction, cluster analysis for categorizing usage into groups. The methodology was demonstrated and tested using two independent samples of user sessions from the…

The Application of Clustering Techniques to Citation Data. Research Reports Series B No. 6.

Science.gov (United States)

Arms, William Y.; Arms, Caroline

This report describes research carried out as part of the Design of Information Systems in the Social Sciences (DISISS) project. Cluster analysis techniques were applied to a machine readable file of bibliographic data in the form of cited journal titles in order to identify groupings which could be used to structure bibliographic files. Practical…

A sampling device for counting insect egg clusters and measuring vertical distribution of vegetation

Science.gov (United States)

Robert L. Talerico; Robert W., Jr. Wilson

1978-01-01

The use of a vertical sampling pole that delineates known volumes and position is illustrated and demonstrated for counting egg clusters of N. sertifer. The pole can also be used to estimate vertical and horizontal coverage, distribution or damage of vegetation or foliage.

Use of nuclear technique in samples for agricultural purposes

Energy Technology Data Exchange (ETDEWEB)

Oliveira, Kerley A. P. de; Sperling, Eduardo Von, E-mail: kerley@ufmg.br, E-mail: kerleyfisica@yahoo.com.br [Department of Sanitary and Environmental Engineering Federal University of Minas Gerais, Belo Horizonte (Brazil); Menezes, Maria Angela B. C.; Jacomino, Vanusa M.F. [Centro de Desenvolvimento da Tecnologia Nuclear (CDTN/CNEN-MG), Belo Horizonte, MG (Brazil)

2013-01-15

The concern related to environment is growing. Due to this, it is needed to determine chemical elements in a large range of concentration. The neutron activation technique (NAA) determines the elemental composition by the measurement of artificial radioactivity in a sample that was submitted to a neutron flux. NAA is a sensitive and accurate technique with low detection limits. An example of application of NAA was the measurement of concentrations of rare earth elements (REE) in waste samples of phosphogypsum (PG) and cerrado soil samples (clayey and sandy soils). Additionally, a soil reference material of the International Atomic Energy Agency (IAEA) was also analyzed. The REE concentration in PG samples was two times higher than those found in national fertilizers, (total of 4,000 mg kg{sup -1}), 154 times greater than the values found in the sandy soil (26 mg kg{sup -1}) and 14 times greater than the in clayey soil (280 mg kg{sup -1}). The experimental results for the reference material were inside the uncertainty of the certified values pointing out the accuracy of the method (95%). The determination of La, Ce, Pr, Nd, Pm, Sm, Eu, Tb, Dy, Ho, Er, Tm, Yb and Lu in the samples and reference material confirmed the versatility of the technique on REE determination in soil and phosphogypsum samples that are matrices for agricultural interest. (author)

Use of nuclear technique in samples for agricultural purposes

International Nuclear Information System (INIS)

Oliveira, Kerley A. P. de; Sperling, Eduardo Von; Menezes, Maria Angela B. C.; Jacomino, Vanusa M.F.

2013-01-01

The concern related to environment is growing. Due to this, it is needed to determine chemical elements in a large range of concentration. The neutron activation technique (NAA) determines the elemental composition by the measurement of artificial radioactivity in a sample that was submitted to a neutron flux. NAA is a sensitive and accurate technique with low detection limits. An example of application of NAA was the measurement of concentrations of rare earth elements (REE) in waste samples of phosphogypsum (PG) and cerrado soil samples (clayey and sandy soils). Additionally, a soil reference material of the International Atomic Energy Agency (IAEA) was also analyzed. The REE concentration in PG samples was two times higher than those found in national fertilizers, (total of 4,000 mg kg -1 ), 154 times greater than the values found in the sandy soil (26 mg kg -1 ) and 14 times greater than the in clayey soil (280 mg kg -1 ). The experimental results for the reference material were inside the uncertainty of the certified values pointing out the accuracy of the method (95%). The determination of La, Ce, Pr, Nd, Pm, Sm, Eu, Tb, Dy, Ho, Er, Tm, Yb and Lu in the samples and reference material confirmed the versatility of the technique on REE determination in soil and phosphogypsum samples that are matrices for agricultural interest. (author)

Development of analytical techniques for safeguards environmental samples at JAEA

International Nuclear Information System (INIS)

Sakurai, Satoshi; Magara, Masaaki; Usuda, Shigekazu; Watanabe, Kazuo; Esaka, Fumitaka; Hirayama, Fumio; Lee, Chi-Gyu; Yasuda, Kenichiro; Inagawa, Jun; Suzuki, Daisuke; Iguchi, Kazunari; Kokubu, Yoko S.; Miyamoto, Yutaka; Ohzu, Akira

2007-01-01

JAEA has been developing, under the auspices of the Ministry of Education, Culture, Sports, Science and Technology of Japan, analytical techniques for ultra-trace amounts of nuclear materials in environmental samples in order to contribute to the strengthened safeguards system. Development of essential techniques for bulk and particle analysis, as well as screening, of the environmental swipe samples has been established as ultra-trace analytical methods of uranium and plutonium. In January 2003, JAEA was qualified, including its quality control system, as a member of the JAEA network analytical laboratories for environmental samples. Since 2004, JAEA has conducted the analysis of domestic and the IAEA samples, through which JAEA's analytical capability has been verified and improved. In parallel, advanced techniques have been developed in order to expand the applicability to the samples of various elemental composition and impurities and to improve analytical accuracy and efficiency. This paper summarizes the trace of the technical development in environmental sample analysis at JAEA, and refers to recent trends of research and development in this field. (author)

Kappa statistic for clustered matched-pair data.

Science.gov (United States)

Yang, Zhao; Zhou, Ming

2014-07-10

Kappa statistic is widely used to assess the agreement between two procedures in the independent matched-pair data. For matched-pair data collected in clusters, on the basis of the delta method and sampling techniques, we propose a nonparametric variance estimator for the kappa statistic without within-cluster correlation structure or distributional assumptions. The results of an extensive Monte Carlo simulation study demonstrate that the proposed kappa statistic provides consistent estimation and the proposed variance estimator behaves reasonably well for at least a moderately large number of clusters (e.g., K ≥50). Compared with the variance estimator ignoring dependence within a cluster, the proposed variance estimator performs better in maintaining the nominal coverage probability when the intra-cluster correlation is fair (ρ ≥0.3), with more pronounced improvement when ρ is further increased. To illustrate the practical application of the proposed estimator, we analyze two real data examples of clustered matched-pair data. Copyright © 2014 John Wiley & Sons, Ltd.

Grouped fuzzy SVM with EM-based partition of sample space for clustered microcalcification detection.

Science.gov (United States)

Wang, Huiya; Feng, Jun; Wang, Hongyu

2017-07-20

Detection of clustered microcalcification (MC) from mammograms plays essential roles in computer-aided diagnosis for early stage breast cancer. To tackle problems associated with the diversity of data structures of MC lesions and the variability of normal breast tissues, multi-pattern sample space learning is required. In this paper, a novel grouped fuzzy Support Vector Machine (SVM) algorithm with sample space partition based on Expectation-Maximization (EM) (called G-FSVM) is proposed for clustered MC detection. The diversified pattern of training data is partitioned into several groups based on EM algorithm. Then a series of fuzzy SVM are integrated for classification with each group of samples from the MC lesions and normal breast tissues. From DDSM database, a total of 1,064 suspicious regions are selected from 239 mammography, and the measurement of Accuracy, True Positive Rate (TPR), False Positive Rate (FPR) and EVL = TPR* 1-FPR are 0.82, 0.78, 0.14 and 0.72, respectively. The proposed method incorporates the merits of fuzzy SVM and multi-pattern sample space learning, decomposing the MC detection problem into serial simple two-class classification. Experimental results from synthetic data and DDSM database demonstrate that our integrated classification framework reduces the false positive rate significantly while maintaining the true positive rate.

Water sampling techniques for continuous monitoring of pesticides in water

Directory of Open Access Journals (Sweden)

Šunjka Dragana

2017-01-01

Full Text Available Good ecological and chemical status of water represents the most important aim of the Water Framework Directive 2000/60/EC, which implies respect of water quality standards at the level of entire river basin (2008/105/EC and 2013/39/EC. This especially refers to the control of pesticide residues in surface waters. In order to achieve the set goals, a continuous monitoring program that should provide a comprehensive and interrelated overview of water status should be implemented. However, it demands the use of appropriate analysis techniques. Until now, the procedure for sampling and quantification of residual pesticide quantities in aquatic environment was based on the use of traditional sampling techniques that imply periodical collecting of individual samples. However, this type of sampling provides only a snapshot of the situation in regard to the presence of pollutants in water. As an alternative, the technique of passive sampling of pollutants in water, including pesticides has been introduced. Different samplers are available for pesticide sampling in surface water, depending on compounds. The technique itself is based on keeping a device in water over a longer period of time which varies from several days to several weeks, depending on the kind of compound. In this manner, the average concentrations of pollutants dissolved in water during a time period (time-weighted average concentrations, TWA are obtained, which enables monitoring of trends in areal and seasonal variations. The use of these techniques also leads to an increase in sensitivity of analytical methods, considering that pre-concentration of analytes takes place within the sorption medium. However, the use of these techniques for determination of pesticide concentrations in real water environments requires calibration studies for the estimation of sampling rates (Rs. Rs is a volume of water per time, calculated as the product of overall mass transfer coefficient and area of

Magnetic separation techniques in sample preparation for biological analysis: a review.

Science.gov (United States)

He, Jincan; Huang, Meiying; Wang, Dongmei; Zhang, Zhuomin; Li, Gongke

2014-12-01

Sample preparation is a fundamental and essential step in almost all the analytical procedures, especially for the analysis of complex samples like biological and environmental samples. In past decades, with advantages of superparamagnetic property, good biocompatibility and high binding capacity, functionalized magnetic materials have been widely applied in various processes of sample preparation for biological analysis. In this paper, the recent advancements of magnetic separation techniques based on magnetic materials in the field of sample preparation for biological analysis were reviewed. The strategy of magnetic separation techniques was summarized. The synthesis, stabilization and bio-functionalization of magnetic nanoparticles were reviewed in detail. Characterization of magnetic materials was also summarized. Moreover, the applications of magnetic separation techniques for the enrichment of protein, nucleic acid, cell, bioactive compound and immobilization of enzyme were described. Finally, the existed problems and possible trends of magnetic separation techniques for biological analysis in the future were proposed. Copyright © 2014 Elsevier B.V. All rights reserved.

Proximity gettering technology for advanced CMOS image sensors using carbon cluster ion-implantation technique. A review

Energy Technology Data Exchange (ETDEWEB)

Kurita, Kazunari; Kadono, Takeshi; Okuyama, Ryousuke; Shigemastu, Satoshi; Hirose, Ryo; Onaka-Masada, Ayumi; Koga, Yoshihiro; Okuda, Hidehiko [SUMCO Corporation, Saga (Japan)

2017-07-15

A new technique is described for manufacturing advanced silicon wafers with the highest capability yet reported for gettering transition metallic, oxygen, and hydrogen impurities in CMOS image sensor fabrication processes. Carbon and hydrogen elements are localized in the projection range of the silicon wafer by implantation of ion clusters from a hydrocarbon molecular gas source. Furthermore, these wafers can getter oxygen impurities out-diffused to device active regions from a Czochralski grown silicon wafer substrate to the carbon cluster ion projection range during heat treatment. Therefore, they can reduce the formation of transition metals and oxygen-related defects in the device active regions and improve electrical performance characteristics, such as the dark current, white spot defects, pn-junction leakage current, and image lag characteristics. The new technique enables the formation of high-gettering-capability sinks for transition metals, oxygen, and hydrogen impurities under device active regions of CMOS image sensors. The wafers formed by this technique have the potential to significantly improve electrical devices performance characteristics in advanced CMOS image sensors. (copyright 2017 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim)

Beams of mass-selected clusters: realization and first experiments

International Nuclear Information System (INIS)

Kamalou, O.

2007-04-01

The main objective of this work concerns the production of beams of mass-selected clusters of metallic and semiconductor materials. Clusters are produced in magnetron sputtering source combined with a gas aggregation chamber, cooled by liquid nitrogen circulation. Downstream of the cluster source, a Wiley-McLaren time-of-flight setup allows to select a given cluster size or a narrow size range. The pulsed mass-selected cluster ion beam is separated from the continuous neutral one by an electrostatic 90-quadrupole deflector. After the deflector, the density of the pulsed beam amounts to about 10 3 particles/cm 3 . Preliminary deposition experiments of mass-selected copper clusters with a deposition energy of about 0.5 eV/atom have ben performed on highly oriented pyrolytic graphite (HOPG) substrates, indicating that copper clusters are evidently mobile on the HOPG-surface until they reach cleavage steps, dislocation lines or other surface defects. In order to lower the cluster mobility on the HOPG-surface, we have first irradiated HOPG samples with slow highly charged ions (high dose) in order to create superficial defects. In a second step we have deposited mass-selected copper clusters on these pre-irradiated samples. The first analysis by AFM (Atomic Force Microscopy) techniques showed that the copper clusters are trapped on the defects produced by the highly charged ions. (author)

Evaluation of immunization coverage by lot quality assurance sampling compared with 30-cluster sampling in a primary health centre in India.

OpenAIRE

Singh, J.; Jain, D. C.; Sharma, R. S.; Verghese, T.

1996-01-01

The immunization coverage of infants, children and women residing in a primary health centre (PHC) area in Rajasthan was evaluated both by lot quality assurance sampling (LQAS) and by the 30-cluster sampling method recommended by WHO's Expanded Programme on Immunization (EPI). The LQAS survey was used to classify 27 mutually exclusive subunits of the population, defined as residents in health subcentre areas, on the basis of acceptable or unacceptable levels of immunization coverage among inf...

The electron transport problem sampling by Monte Carlo individual collision technique

International Nuclear Information System (INIS)

Androsenko, P.A.; Belousov, V.I.

2005-01-01

The problem of electron transport is of most interest in all fields of the modern science. To solve this problem the Monte Carlo sampling has to be used. The electron transport is characterized by a large number of individual interactions. To simulate electron transport the 'condensed history' technique may be used where a large number of collisions are grouped into a single step to be sampled randomly. Another kind of Monte Carlo sampling is the individual collision technique. In comparison with condensed history technique researcher has the incontestable advantages. For example one does not need to give parameters altered by condensed history technique like upper limit for electron energy, resolution, number of sub-steps etc. Also the condensed history technique may lose some very important tracks of electrons because of its limited nature by step parameters of particle movement and due to weakness of algorithms for example energy indexing algorithm. There are no these disadvantages in the individual collision technique. This report presents some sampling algorithms of new version BRAND code where above mentioned technique is used. All information on electrons was taken from Endf-6 files. They are the important part of BRAND. These files have not been processed but directly taken from electron information source. Four kinds of interaction like the elastic interaction, the Bremsstrahlung, the atomic excitation and the atomic electro-ionization were considered. In this report some results of sampling are presented after comparison with analogs. For example the endovascular radiotherapy problem (P2) of QUADOS2002 was presented in comparison with another techniques that are usually used. (authors)

Growth of CdTe on Si(100) surface by ionized cluster beam technique: Experimental and molecular dynamics simulation

Energy Technology Data Exchange (ETDEWEB)

Araghi, Houshang, E-mail: araghi@aut.ac.ir [Department of Physics, Amirkabir University of Technology, Tehran (Iran, Islamic Republic of); Zabihi, Zabiholah [Department of Physics, Amirkabir University of Technology, Tehran (Iran, Islamic Republic of); Nayebi, Payman [Department of Physics, College of Technical and Engineering, Saveh Branch, Islamic Azad University, Saveh (Iran, Islamic Republic of); Ehsani, Mohammad Mahdi [Department of Physics, Amirkabir University of Technology, Tehran (Iran, Islamic Republic of)

2016-10-15

II–VI semiconductor CdTe was grown on the Si(100) substrate surface by the ionized cluster beam (ICB) technique. In the ICB method, when vapors of solid materials such as CdTe were ejected through a nozzle of a heated crucible into a vacuum region, nanoclusters were created by an adiabatic expansion phenomenon. The clusters thus obtained were partially ionized by electron bombardment and then accelerated onto the silicon substrate at 473 K by high potentials. The cluster size was determined using a retarding field energy analyzer. The results of X-ray diffraction measurements indicate the cubic zinc blende (ZB) crystalline structure of the CdTe thin film on the silicon substrate. The CdTe thin film prepared by the ICB method had high crystalline quality. The microscopic processes involved in the ICB deposition technique, such as impact and coalescence processes, have been studied in detail by molecular dynamics (MD) simulation.

Solid Phase Microextraction and Related Techniques for Drugs in Biological Samples

OpenAIRE

Moein, Mohammad Mahdi; Said, Rana; Bassyouni, Fatma; Abdel-Rehim, Mohamed

2014-01-01

In drug discovery and development, the quantification of drugs in biological samples is an important task for the determination of the physiological performance of the investigated drugs. After sampling, the next step in the analytical process is sample preparation. Because of the low concentration levels of drug in plasma and the variety of the metabolites, the selected extraction technique should be virtually exhaustive. Recent developments of sample handling techniques are directed, from o...

Dependence of the clustering properties of galaxies on stellar velocity dispersion in the Main galaxy sample of SDSS DR10

Science.gov (United States)

Deng, Xin-Fa; Song, Jun; Chen, Yi-Qing; Jiang, Peng; Ding, Ying-Ping

2014-08-01

Using two volume-limited Main galaxy samples of the Sloan Digital Sky Survey Data Release 10 (SDSS DR10), we investigate the dependence of the clustering properties of galaxies on stellar velocity dispersion by cluster analysis. It is found that in the luminous volume-limited Main galaxy sample, except at r=1.2, richer and larger systems can be more easily formed in the large stellar velocity dispersion subsample, while in the faint volume-limited Main galaxy sample, at r≥0.9, an opposite trend is observed. According to statistical analyses of the multiplicity functions, we conclude in two volume-limited Main galaxy samples: small stellar velocity dispersion galaxies preferentially form isolated galaxies, close pairs and small group, while large stellar velocity dispersion galaxies preferentially inhabit the dense groups and clusters. However, we note the difference between two volume-limited Main galaxy samples: in the faint volume-limited Main galaxy sample, at r≥0.9, the small stellar velocity dispersion subsample has a higher proportion of galaxies in superclusters ( n≥200) than the large stellar velocity dispersion subsample.

The Effect of Buzz Group Technique and Clustering Technique in Teaching Writing at the First Class of SMA HKBP I Tarutung

Science.gov (United States)

Pangaribuan, Tagor; Manik, Sondang

2018-01-01

This research held at SMA HKBP 1 Tarutung North Sumatra on the research result of test XI[superscript 2] and XI[superscript 2] students, after they got treatment in teaching writing in recount text by using buzz group and clustering technique. The average score (X) was 67.7 and the total score buzz group the average score (X) was 77.2 and in…

Photometry Using Kepler “Superstamps” of Open Clusters NGC 6791 & NGC 6819

Directory of Open Access Journals (Sweden)

Kuehn Charles A.

2015-01-01

Full Text Available The Kepler space telescope has proven to be a gold mine for the study of variable stars. Usually, Kepler only reads out a handful of pixels around each pre-selected target star, omitting a large number of stars in the Kepler field. Fortunately, for the open clusters NGC 6791 and NGC 6819, Kepler also read out larger “superstamps” which contained complete images of the central region of each cluster. These cluster images can be used to study additional stars in the open clusters that were not originally on Kepler’s target list. We discuss our work on using two photometric techniques to analyze these superstamps and present sample results from this project to demonstrate the value of this technique for a wide variety of variable stars.

Atomic characterization of Au clusters in vapor-liquid-solid grown silicon nanowires

International Nuclear Information System (INIS)

Chen, Wanghua; Roca i Cabarrocas, Pere; Pareige, Philippe; Castro, Celia; Xu, Tao; Grandidier, Bruno; Stiévenard, Didier

2015-01-01

By correlating atom probe tomography with other conventional microscope techniques (scanning electron microscope, scanning transmission electron microscope, and scanning tunneling microscopy), the distribution and composition of Au clusters in individual vapor-liquid-solid grown Si nanowires is investigated. Taking advantage of the characteristics of atom probe tomography, we have developed a sample preparation method by inclining the sample at certain angle to characterize the nanowire sidewall without using focused ion beam. With three-dimensional atomic scale reconstruction, we provide direct evidence of Au clusters tending to remain on the nanowire sidewall rather than being incorporated into the Si nanowires. Based on the composition measurement of Au clusters (28% ± 1%), we have demonstrated the supersaturation of Si atoms in Au clusters, which supports the hypothesis that Au clusters are formed simultaneously during nanowire growth rather than during the cooling process

Atomic characterization of Au clusters in vapor-liquid-solid grown silicon nanowires

Energy Technology Data Exchange (ETDEWEB)

Chen, Wanghua; Roca i Cabarrocas, Pere [Laboratoire de Physique des Interfaces et Couches Minces (LPICM), UMR 7647, CNRS, Ecole Polytechnique, 91128 Palaiseau (France); Pareige, Philippe; Castro, Celia [Groupe de Physique des Matériaux (GPM), Université et INSA de Rouen, UMR 6634, CNRS, Av. de l' Université, BP 12, 76801 Saint Etienne du Rouvray (France); Xu, Tao; Grandidier, Bruno; Stiévenard, Didier [Institut d' Electronique et de Microélectronique et de Nanotechnologies (IEMN), UMR 8520, CNRS, Département ISEN, 41 bd Vauban, 59046 Lille Cedex (France)

2015-09-14

By correlating atom probe tomography with other conventional microscope techniques (scanning electron microscope, scanning transmission electron microscope, and scanning tunneling microscopy), the distribution and composition of Au clusters in individual vapor-liquid-solid grown Si nanowires is investigated. Taking advantage of the characteristics of atom probe tomography, we have developed a sample preparation method by inclining the sample at certain angle to characterize the nanowire sidewall without using focused ion beam. With three-dimensional atomic scale reconstruction, we provide direct evidence of Au clusters tending to remain on the nanowire sidewall rather than being incorporated into the Si nanowires. Based on the composition measurement of Au clusters (28% ± 1%), we have demonstrated the supersaturation of Si atoms in Au clusters, which supports the hypothesis that Au clusters are formed simultaneously during nanowire growth rather than during the cooling process.

Manipulation of biological samples using micro and nano techniques.

Science.gov (United States)

Castillo, Jaime; Dimaki, Maria; Svendsen, Winnie Edith

2009-01-01

The constant interest in handling, integrating and understanding biological systems of interest for the biomedical field, the pharmaceutical industry and the biomaterial researchers demand the use of techniques that allow the manipulation of biological samples causing minimal or no damage to their natural structure. Thanks to the advances in micro- and nanofabrication during the last decades several manipulation techniques offer us the possibility to image, characterize and manipulate biological material in a controlled way. Using these techniques the integration of biomaterials with remarkable properties with physical transducers has been possible, giving rise to new and highly sensitive biosensing devices. This article reviews the different techniques available to manipulate and integrate biological materials in a controlled manner either by sliding them along a surface (2-D manipulation), by grapping them and moving them to a new position (3-D manipulation), or by manipulating and relocating them applying external forces. The advantages and drawbacks are mentioned together with examples that reflect the state of the art of manipulation techniques for biological samples (171 references).

The electron transport problem sampling by Monte Carlo individual collision technique

Energy Technology Data Exchange (ETDEWEB)

Androsenko, P.A.; Belousov, V.I. [Obninsk State Technical Univ. of Nuclear Power Engineering, Kaluga region (Russian Federation)

2005-07-01

The problem of electron transport is of most interest in all fields of the modern science. To solve this problem the Monte Carlo sampling has to be used. The electron transport is characterized by a large number of individual interactions. To simulate electron transport the 'condensed history' technique may be used where a large number of collisions are grouped into a single step to be sampled randomly. Another kind of Monte Carlo sampling is the individual collision technique. In comparison with condensed history technique researcher has the incontestable advantages. For example one does not need to give parameters altered by condensed history technique like upper limit for electron energy, resolution, number of sub-steps etc. Also the condensed history technique may lose some very important tracks of electrons because of its limited nature by step parameters of particle movement and due to weakness of algorithms for example energy indexing algorithm. There are no these disadvantages in the individual collision technique. This report presents some sampling algorithms of new version BRAND code where above mentioned technique is used. All information on electrons was taken from Endf-6 files. They are the important part of BRAND. These files have not been processed but directly taken from electron information source. Four kinds of interaction like the elastic interaction, the Bremsstrahlung, the atomic excitation and the atomic electro-ionization were considered. In this report some results of sampling are presented after comparison with analogs. For example the endovascular radiotherapy problem (P2) of QUADOS2002 was presented in comparison with another techniques that are usually used. (authors)

Unequal cluster sizes in stepped-wedge cluster randomised trials: a systematic review.

Science.gov (United States)

Kristunas, Caroline; Morris, Tom; Gray, Laura

2017-11-15

To investigate the extent to which cluster sizes vary in stepped-wedge cluster randomised trials (SW-CRT) and whether any variability is accounted for during the sample size calculation and analysis of these trials. Any, not limited to healthcare settings. Any taking part in an SW-CRT published up to March 2016. The primary outcome is the variability in cluster sizes, measured by the coefficient of variation (CV) in cluster size. Secondary outcomes include the difference between the cluster sizes assumed during the sample size calculation and those observed during the trial, any reported variability in cluster sizes and whether the methods of sample size calculation and methods of analysis accounted for any variability in cluster sizes. Of the 101 included SW-CRTs, 48% mentioned that the included clusters were known to vary in size, yet only 13% of these accounted for this during the calculation of the sample size. However, 69% of the trials did use a method of analysis appropriate for when clusters vary in size. Full trial reports were available for 53 trials. The CV was calculated for 23 of these: the median CV was 0.41 (IQR: 0.22-0.52). Actual cluster sizes could be compared with those assumed during the sample size calculation for 14 (26%) of the trial reports; the cluster sizes were between 29% and 480% of that which had been assumed. Cluster sizes often vary in SW-CRTs. Reporting of SW-CRTs also remains suboptimal. The effect of unequal cluster sizes on the statistical power of SW-CRTs needs further exploration and methods appropriate to studies with unequal cluster sizes need to be employed. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Effect of denoising on supervised lung parenchymal clusters

Science.gov (United States)

Jayamani, Padmapriya; Raghunath, Sushravya; Rajagopalan, Srinivasan; Karwoski, Ronald A.; Bartholmai, Brian J.; Robb, Richard A.

2012-03-01

Denoising is a critical preconditioning step for quantitative analysis of medical images. Despite promises for more consistent diagnosis, denoising techniques are seldom explored in clinical settings. While this may be attributed to the esoteric nature of the parameter sensitve algorithms, lack of quantitative measures on their ecacy to enhance the clinical decision making is a primary cause of physician apathy. This paper addresses this issue by exploring the eect of denoising on the integrity of supervised lung parenchymal clusters. Multiple Volumes of Interests (VOIs) were selected across multiple high resolution CT scans to represent samples of dierent patterns (normal, emphysema, ground glass, honey combing and reticular). The VOIs were labeled through consensus of four radiologists. The original datasets were ltered by multiple denoising techniques (median ltering, anisotropic diusion, bilateral ltering and non-local means) and the corresponding ltered VOIs were extracted. Plurality of cluster indices based on multiple histogram-based pair-wise similarity measures were used to assess the quality of supervised clusters in the original and ltered space. The resultant rank orders were analyzed using the Borda criteria to nd the denoising-similarity measure combination that has the best cluster quality. Our exhaustive analyis reveals (a) for a number of similarity measures, the cluster quality is inferior in the ltered space; and (b) for measures that benet from denoising, a simple median ltering outperforms non-local means and bilateral ltering. Our study suggests the need to judiciously choose, if required, a denoising technique that does not deteriorate the integrity of supervised clusters.

Intra Cluster Light properties in the CLASH-VLT cluster MACS J1206.2-0847

CERN Document Server

Presotto, V; Nonino, M; Mercurio, A; Grillo, C; Rosati, P; Biviano, A; Annunziatella, M; Balestra, I; Cui, W; Sartoris, B; Lemze, D; Ascaso, B; Moustakas, J; Ford, H; Fritz, A; Czoske, O; Ettori, S; Kuchner, U; Lombardi, M; Maier, C; Medezinski, E; Molino, A; Scodeggio, M; Strazzullo, V; Tozzi, P; Ziegler, B; Bartelmann, M; Benitez, N; Bradley, L; Brescia, M; Broadhurst, T; Coe, D; Donahue, M; Gobat, R; Graves, G; Kelson, D; Koekemoer, A; Melchior, P; Meneghetti, M; Merten, J; Moustakas, L; Munari, E; Postman, M; Regős, E; Seitz, S; Umetsu, K; Zheng, W; Zitrin, A

2014-01-01

We aim at constraining the assembly history of clusters by studying the intra cluster light (ICL) properties, estimating its contribution to the fraction of baryons in stars, f*, and understanding possible systematics/bias using different ICL detection techniques. We developed an automated method, GALtoICL, based on the software GALAPAGOS to obtain a refined version of typical BCG+ICL maps. We applied this method to our test case MACS J1206.2-0847, a massive cluster located at z=0.44, that is part of the CLASH sample. Using deep multi-band SUBARU images, we extracted the surface brightness (SB) profile of the BCG+ICL and we studied the ICL morphology, color, and contribution to f* out to R500. We repeated the same analysis using a different definition of the ICL, SBlimit method, i.e. a SB cut-off level, to compare the results. The most peculiar feature of the ICL in MACS1206 is its asymmetric radial distribution, with an excess in the SE direction and extending towards the 2nd brightest cluster galaxy which i...

NAIL SAMPLING TECHNIQUE AND ITS INTERPRETATION

OpenAIRE

TZAR MN; LEELAVATHI M

2011-01-01

The clinical suspicion of onychomyosis based on appearance of the nails, requires culture for confirmation. This is because treatment requires prolonged use of systemic agents which may cause side effects. One of the common problems encountered is improper nail sampling technique which results in loss of essential information. The unfamiliar terminologies used in reporting culture results may intimidate physicians resulting in misinterpretation and hamper treatment decision. This article prov...

THE ATACAMA COSMOLOGY TELESCOPE: DYNAMICAL MASSES AND SCALING RELATIONS FOR A SAMPLE OF MASSIVE SUNYAEV-ZEL'DOVICH EFFECT SELECTED GALAXY CLUSTERS {sup ,}

Energy Technology Data Exchange (ETDEWEB)

Sifon, Cristobal; Barrientos, L. Felipe; Gonzalez, Jorge; Infante, Leopoldo; Duenner, Rolando [Departamento de Astronomia y Astrofisica, Facultad de Fisica, Pontificia Universidad Catolica de Chile, Casilla 306, Santiago 22 (Chile); Menanteau, Felipe; Hughes, John P.; Baker, Andrew J. [Department of Physics and Astronomy, Rutgers University, 136 Frelinghuysen Road, Piscataway, NJ 08854 (United States); Hasselfield, Matthew [Department of Physics and Astronomy, University of British Columbia, Vancouver, BC V6T 1Z4 (Canada); Marriage, Tobias A.; Crichton, Devin; Gralla, Megan B. [Department of Physics and Astronomy, The Johns Hopkins University, Baltimore, MD 21218-2686 (United States); Addison, Graeme E.; Dunkley, Joanna [Sub-department of Astrophysics, University of Oxford, Denys Wilkinson Building, Keble Road, Oxford OX1 3RH (United Kingdom); Battaglia, Nick; Bond, J. Richard; Hajian, Amir [Canadian Institute for Theoretical Astrophysics, University of Toronto, Toronto, ON M5S 3H8 (Canada); Das, Sudeep [Berkeley Center for Cosmological Physics, LBL and Department of Physics, University of California, Berkeley, CA 94720 (United States); Devlin, Mark J. [Department of Physics and Astronomy, University of Pennsylvania, 209 South 33rd Street, Philadelphia, PA 19104 (United States); Hilton, Matt [School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD (United Kingdom); and others

2013-07-20

We present the first dynamical mass estimates and scaling relations for a sample of Sunyaev-Zel'dovich effect (SZE) selected galaxy clusters. The sample consists of 16 massive clusters detected with the Atacama Cosmology Telescope (ACT) over a 455 deg{sup 2} area of the southern sky. Deep multi-object spectroscopic observations were taken to secure intermediate-resolution (R {approx} 700-800) spectra and redshifts for Almost-Equal-To 60 member galaxies on average per cluster. The dynamical masses M{sub 200c} of the clusters have been calculated using simulation-based scaling relations between velocity dispersion and mass. The sample has a median redshift z = 0.50 and a median mass M{sub 200c}{approx_equal}12 Multiplication-Sign 10{sup 14} h{sub 70}{sup -1} M{sub sun} with a lower limit M{sub 200c}{approx_equal}6 Multiplication-Sign 10{sup 14} h{sub 70}{sup -1} M{sub sun}, consistent with the expectations for the ACT southern sky survey. These masses are compared to the ACT SZE properties of the sample, specifically, the match-filtered central SZE amplitude y{sub 0}-tilde, the central Compton parameter y{sub 0}, and the integrated Compton signal Y{sub 200c}, which we use to derive SZE-mass scaling relations. All SZE estimators correlate with dynamical mass with low intrinsic scatter ({approx}< 20%), in agreement with numerical simulations. We explore the effects of various systematic effects on these scaling relations, including the correlation between observables and the influence of dynamically disturbed clusters. Using the three-dimensional information available, we divide the sample into relaxed and disturbed clusters and find that {approx}50% of the clusters are disturbed. There are hints that disturbed systems might bias the scaling relations, but given the current sample sizes, these differences are not significant; further studies including more clusters are required to assess the impact of these clusters on the scaling relations.

Sample preparation techniques for (p, X) spectrometry

International Nuclear Information System (INIS)

Whitehead, N.E.

1985-01-01

Samples are ashed at low temperature, using oxygen plasma; a rotary evaporator, and freeze drying speeded up the ashing. The new design of apparatus manufactured was only 10 watt but was as efficient as a 200 watt commercial machine; a circuit diagram is included. Samples of hair and biopsy samples of skin were analysed by the technique. A wool standard was prepared for interlaboratory comparison exercises. It was based on New Zealand merino sheep wool and was 2.9 kg in weight. A washing protocol was developed, which preserves most of the trace element content. The wool was ground in liquid nitrogen using a plastic pestle and beaker, driven by a rotary drill press. (author)

Vibration impact acoustic emission technique for identification and analysis of defects in carbon steel tubes: Part B Cluster analysis

Energy Technology Data Exchange (ETDEWEB)

Halim, Zakiah Abd [Universiti Teknikal Malaysia Melaka (Malaysia); Jamaludin, Nordin; Junaidi, Syarif [Faculty of Engineering and Built, Universiti Kebangsaan Malaysia, Bangi (Malaysia); Yahya, Syed Yusainee Syed [Universiti Teknologi MARA, Shah Alam (Malaysia)

2015-04-15

Current steel tubes inspection techniques are invasive, and the interpretation and evaluation of inspection results are manually done by skilled personnel. Part A of this work details the methodology involved in the newly developed non-invasive, non-destructive tube inspection technique based on the integration of vibration impact (VI) and acoustic emission (AE) systems known as the vibration impact acoustic emission (VIAE) technique. AE signals have been introduced into a series of ASTM A179 seamless steel tubes using the impact hammer. Specifically, a good steel tube as the reference tube and four steel tubes with through-hole artificial defect at different locations were used in this study. The AEs propagation was captured using a high frequency sensor of AE systems. The present study explores the cluster analysis approach based on autoregressive (AR) coefficients to automatically interpret the AE signals. The results from the cluster analysis were graphically illustrated using a dendrogram that demonstrated the arrangement of the natural clusters of AE signals. The AR algorithm appears to be the more effective method in classifying the AE signals into natural groups. This approach has successfully classified AE signals for quick and confident interpretation of defects in carbon steel tubes.

Vibration impact acoustic emission technique for identification and analysis of defects in carbon steel tubes: Part B Cluster analysis

International Nuclear Information System (INIS)

Halim, Zakiah Abd; Jamaludin, Nordin; Junaidi, Syarif; Yahya, Syed Yusainee Syed

2015-01-01

Current steel tubes inspection techniques are invasive, and the interpretation and evaluation of inspection results are manually done by skilled personnel. Part A of this work details the methodology involved in the newly developed non-invasive, non-destructive tube inspection technique based on the integration of vibration impact (VI) and acoustic emission (AE) systems known as the vibration impact acoustic emission (VIAE) technique. AE signals have been introduced into a series of ASTM A179 seamless steel tubes using the impact hammer. Specifically, a good steel tube as the reference tube and four steel tubes with through-hole artificial defect at different locations were used in this study. The AEs propagation was captured using a high frequency sensor of AE systems. The present study explores the cluster analysis approach based on autoregressive (AR) coefficients to automatically interpret the AE signals. The results from the cluster analysis were graphically illustrated using a dendrogram that demonstrated the arrangement of the natural clusters of AE signals. The AR algorithm appears to be the more effective method in classifying the AE signals into natural groups. This approach has successfully classified AE signals for quick and confident interpretation of defects in carbon steel tubes.

Optimality Measures for Monotone Equivariant Cluster Techniques.

Science.gov (United States)

1980-09-01

complete linkage, u-clustering (u - .3, .5, .7), uv-clustering (uv = (.2,.4), (.2,.6), (.4,.6)) as well as the UPGMA algorithm. The idea will be to...Table 15. Notice that these measure-- do indeed pioduce difftxent verdicts. OPI rates UPGMA as best with uv = (.2,.4) R € second. By OP2, UPGMA is best...By OPI, UPGQA and uv = (.4,.6) are tied for first place, while by OP2, UPGMA is best with uv = (.2,.6), uv = (.2,.4) and uv = (.4,.6) close behind

TOWARDS FINDING A NEW KERNELIZED FUZZY C-MEANS CLUSTERING ALGORITHM

Directory of Open Access Journals (Sweden)

Samarjit Das

2014-04-01

Full Text Available Kernelized Fuzzy C-Means clustering technique is an attempt to improve the performance of the conventional Fuzzy C-Means clustering technique. Recently this technique where a kernel-induced distance function is used as a similarity measure instead of a Euclidean distance which is used in the conventional Fuzzy C-Means clustering technique, has earned popularity among research community. Like the conventional Fuzzy C-Means clustering technique this technique also suffers from inconsistency in its performance due to the fact that here also the initial centroids are obtained based on the randomly initialized membership values of the objects. Our present work proposes a new method where we have applied the Subtractive clustering technique of Chiu as a preprocessor to Kernelized Fuzzy CMeans clustering technique. With this new method we have tried not only to remove the inconsistency of Kernelized Fuzzy C-Means clustering technique but also to deal with the situations where the number of clusters is not predetermined. We have also provided a comparison of our method with the Subtractive clustering technique of Chiu and Kernelized Fuzzy C-Means clustering technique using two validity measures namely Partition Coefficient and Clustering Entropy.

UV TO FAR-IR CATALOG OF A GALAXY SAMPLE IN NEARBY CLUSTERS: SPECTRAL ENERGY DISTRIBUTIONS AND ENVIRONMENTAL TRENDS

Energy Technology Data Exchange (ETDEWEB)

Hernandez-Fernandez, Jonathan D.; Iglesias-Paramo, J.; Vilchez, J. M., E-mail: jonatan@iaa.es [Instituto de Astrofisica de Andalucia, Glorieta de la Astronomia s/n, 18008 Granada (Spain)

2012-03-01

In this paper, we present a sample of cluster galaxies devoted to study the environmental influence on the star formation activity. This sample of galaxies inhabits in clusters showing a rich variety in their characteristics and have been observed by the SDSS-DR6 down to M{sub B} {approx} -18, and by the Galaxy Evolution Explorer AIS throughout sky regions corresponding to several megaparsecs. We assign the broadband and emission-line fluxes from ultraviolet to far-infrared to each galaxy performing an accurate spectral energy distribution for spectral fitting analysis. The clusters follow the general X-ray luminosity versus velocity dispersion trend of L{sub X} {proportional_to} {sigma}{sup 4.4}{sub c}. The analysis of the distributions of galaxy density counting up to the 5th nearest neighbor {Sigma}{sub 5} shows: (1) the virial regions and the cluster outskirts share a common range in the high density part of the distribution. This can be attributed to the presence of massive galaxy structures in the surroundings of virial regions. (2) The virial regions of massive clusters ({sigma}{sub c} > 550 km s{sup -1}) present a {Sigma}{sub 5} distribution statistically distinguishable ({approx}96%) from the corresponding distribution of low-mass clusters ({sigma}{sub c} < 550 km s{sup -1}). Both massive and low-mass clusters follow a similar density-radius trend, but the low-mass clusters avoid the high density extreme. We illustrate, with ABELL 1185, the environmental trends of galaxy populations. Maps of sky projected galaxy density show how low-luminosity star-forming galaxies appear distributed along more spread structures than their giant counterparts, whereas low-luminosity passive galaxies avoid the low-density environment. Giant passive and star-forming galaxies share rather similar sky regions with passive galaxies exhibiting more concentrated distributions.

Dark Matter in Galaxy Clusters: Shape, Projection, and Environment

Science.gov (United States)

Groener, Austen M.

We explore the intrinsic distribution of dark matter within galaxy clusters, by combining insights from the largest N-body simulations as well as the largest observational dataset of its kind. Firstly, we study the intrinsic shape and alignment of isodensities of galaxy cluster halos extracted from the MultiDark MDR1 cosmological simulation. We find that the simulated halos are extremely prolate on small scales and increasingly spherical on larger ones. Due to this trend, analytical projection along the line of sight produces an overestimate of the concentration index as a decreasing function of radius, which we quantify by using both the intrinsic distribution of 3D concentrations (c200) and isodensity shape on weak and strong lensing scales. We find this difference to be ˜ 18% (˜ 9%) for low (medium) mass cluster halos with intrinsically low concentrations (c200=1- 3), while we find virtually no difference for halos with intrinsically high concentrations. Isodensities are found to be fairly well-aligned throughout the entirety of the radial scale of each halo population. However, major axes of individual halos have been found to deviate by as much as ˜ 30°. We also present a value-added catalog of our analysis results, which we have made publicly available to download. Following that, we then turn to observational measurements galaxy clusters. Scaling relations of clusters have made them particularly important cosmological probes of structure formation. In this work, we present a comprehensive study of the relation between two profile observables, concentration (cvir ) and mass (Mvir). We have collected the largest known sample of measurements from the literature which make use of one or more of the following reconstruction techniques: Weak gravitational lensing (WL), strong gravitational lensing (SL), Weak+Strong Lensing (WL+SL), the Caustic Method (CM), Line-of-sight Velocity Dispersion (LOSVD), and X-ray. We find that the concentration-mass (c-M) relation

Quantum annealing for combinatorial clustering

Science.gov (United States)

Kumar, Vaibhaw; Bass, Gideon; Tomlin, Casey; Dulny, Joseph

2018-02-01

Clustering is a powerful machine learning technique that groups "similar" data points based on their characteristics. Many clustering algorithms work by approximating the minimization of an objective function, namely the sum of within-the-cluster distances between points. The straightforward approach involves examining all the possible assignments of points to each of the clusters. This approach guarantees the solution will be a global minimum; however, the number of possible assignments scales quickly with the number of data points and becomes computationally intractable even for very small datasets. In order to circumvent this issue, cost function minima are found using popular local search-based heuristic approaches such as k-means and hierarchical clustering. Due to their greedy nature, such techniques do not guarantee that a global minimum will be found and can lead to sub-optimal clustering assignments. Other classes of global search-based techniques, such as simulated annealing, tabu search, and genetic algorithms, may offer better quality results but can be too time-consuming to implement. In this work, we describe how quantum annealing can be used to carry out clustering. We map the clustering objective to a quadratic binary optimization problem and discuss two clustering algorithms which are then implemented on commercially available quantum annealing hardware, as well as on a purely classical solver "qbsolv." The first algorithm assigns N data points to K clusters, and the second one can be used to perform binary clustering in a hierarchical manner. We present our results in the form of benchmarks against well-known k-means clustering and discuss the advantages and disadvantages of the proposed techniques.

Application of Chemometric Techniques to Colorimetric Data in Classifying Automobile Paint

International Nuclear Information System (INIS)

Nur Awatif Rosli; Rozita Osman; Norashikin Saim; Mohd Zuli Jaafar

2015-01-01

The analysis of paint chips is of great interest to forensic investigators, particularly in the examination of hit-and run cases. This study proposes a direct and rapid method in classifying automobile paint samples based on colorimetric data sets; absorption value, reflectance value, luminosity value (L), degree of redness (a) and degree of yellowness (b) obtained from video spectral comparator (VSC) technique. A total of 42 automobile paint samples from 7 manufacturers were analysed. The colorimetric datasets obtained from VSC analysis were subjected to chemometric technique namely cluster analysis (CA) and principal component analysis (PCA). Based on CA, 5 clusters were generated; Cluster 1 consisted of silver color, cluster 2 consisted of white color, cluster 3 consisted of blue and black colors, cluster 4 consisted of red color and cluster 5 consisted of light blue color. PCA resulted in two latent factors explaining 95.58 % of the total variance, enabled to group the 42 automobile paints into five groups. Chemometric application on colorimetric datasets provide meaningful classification of automobile paints based on their tone colour (L, a, b) and light intensity These approaches have the potential to ease the interpretation of complex spectral data involving a large number of comparisons. (author)

CC_TRS: Continuous Clustering of Trajectory Stream Data Based on Micro Cluster Life

Directory of Open Access Journals (Sweden)

Musaab Riyadh

2017-01-01

Full Text Available The rapid spreading of positioning devices leads to the generation of massive spatiotemporal trajectories data. In some scenarios, spatiotemporal data are received in stream manner. Clustering of stream data is beneficial for different applications such as traffic management and weather forecasting. In this article, an algorithm for Continuous Clustering of Trajectory Stream Data Based on Micro Cluster Life is proposed. The algorithm consists of two phases. There is the online phase where temporal micro clusters are used to store summarized spatiotemporal information for each group of similar segments. The clustering task in online phase is based on temporal micro cluster lifetime instead of time window technique which divides stream data into time bins and clusters each bin separately. For offline phase, a density based clustering approach is used to generate macro clusters depending on temporal micro clusters. The evaluation of the proposed algorithm on real data sets shows the efficiency and the effectiveness of the proposed algorithm and proved it is efficient alternative to time window technique.

Phase behavior of the 38-atom Lennard-Jones cluster

International Nuclear Information System (INIS)

Sehgal, Ray M.; Maroudas, Dimitrios; Ford, David M.

2014-01-01

We have developed a coarse-grained description of the phase behavior of the isolated 38-atom Lennard-Jones cluster (LJ 38 ). The model captures both the solid-solid polymorphic transitions at low temperatures and the complex cluster breakup and melting transitions at higher temperatures. For this coarse model development, we employ the manifold learning technique of diffusion mapping. The outcome of the diffusion mapping analysis over a broad temperature range indicates that two order parameters are sufficient to describe the cluster's phase behavior; we have chosen two such appropriate order parameters that are metrics of condensation and overall crystallinity. In this well-justified coarse-variable space, we calculate the cluster's free energy landscape (FEL) as a function of temperature, employing Monte Carlo umbrella sampling. These FELs are used to quantify the phase behavior and onsets of phase transitions of the LJ 38 cluster

Minimal spanning trees, filaments and galaxy clustering

International Nuclear Information System (INIS)

Barrow, J.D.; Sonoda, D.H.

1985-01-01

A graph theoretical technique for assessing intrinsic patterns in point data sets is described. A unique construction, the minimal spanning tree, can be associated with any point data set given all the inter-point separations. This construction enables the skeletal pattern of galaxy clustering to be singled out in quantitative fashion and differs from other statistics applied to these data sets. This technique is described and applied to two- and three-dimensional distributions of galaxies and also to comparable random samples and numerical simulations. The observed CfA and Zwicky data exhibit characteristic distributions of edge-lengths in their minimal spanning trees which are distinct from those found in random samples. (author)

Effects ok ikea's entry into a furniture production cluster

Directory of Open Access Journals (Sweden)

Vasco Eiriz

2016-04-01

Full Text Available The entry of a multinational into a cluster, a geographic agglomeration in a given place or region of predominantly small and medium enterprises specialized in a given industry or related industries, impacts the incumbent in the cluster. Aiming to identify the main effects of a multinational entry on the firms’ strategy in a cluster, it was analyzed the entry of IKEA, a Swedish multinational, into the cluster of furniture production in Paços de Ferreira and Paredes, in Portugal. In this study, the data collection technique to access primary data was a survey. The sample has small enterprises, which is similar to the structure of firms in the studied cluster. Results show that more than half the sample thinks that the entry of the multinational had not affected them. However, the firms that acknowledge a significant impact, assess that impact as negative. The competitiveness factors that have improved more significantly after IKEA’s entry were new product development and exporting strategies. The main responses of incumbent firms to the multinational entry were internationalization and the development of generic strategies of differentiation and focus based on differentiation.

THE DYNAMICAL STATE OF BRIGHTEST CLUSTER GALAXIES AND THE FORMATION OF CLUSTERS

International Nuclear Information System (INIS)

Coziol, R.; Andernach, H.; Caretta, C. A.; Alamo-MartInez, K. A.; Tago, E.

2009-01-01

A large sample of Abell clusters of galaxies, selected for the likely presence of a dominant galaxy, is used to study the dynamical properties of the brightest cluster members (BCMs). From visual inspection of Digitized Sky Survey images combined with redshift information we identify 1426 candidate BCMs located in 1221 different redshift components associated with 1169 different Abell clusters. This is the largest sample published so far of such galaxies. From our own morphological classification we find that ∼92% of the BCMs in our sample are early-type galaxies and 48% are of cD type. We confirm what was previously observed based on much smaller samples, namely, that a large fraction of BCMs have significant peculiar velocities. From a subsample of 452 clusters having at least 10 measured radial velocities, we estimate a median BCM peculiar velocity of 32% of their host clusters' radial velocity dispersion. This suggests that most BCMs are not at rest in the potential well of their clusters. This phenomenon is common to galaxy clusters in our sample, and not a special trait of clusters hosting cD galaxies. We show that the peculiar velocity of the BCM is independent of cluster richness and only slightly dependent on the Bautz-Morgan type. We also find a weak trend for the peculiar velocity to rise with the cluster velocity dispersion. The strongest dependence is with the morphological type of the BCM: cD galaxies tend to have lower relative peculiar velocities than elliptical galaxies. This result points to a connection between the formation of the BCMs and that of their clusters. Our data are qualitatively consistent with the merging-groups scenario, where BCMs in clusters formed first in smaller subsystems comparable to compact groups of galaxies. In this scenario, clusters would have formed recently from the mergers of many such groups and would still be in a dynamically unrelaxed state.

Application of the Sampling Selection Technique in Approaching Financial Audit

Directory of Open Access Journals (Sweden)

Victor Munteanu

2018-03-01

Full Text Available In his professional approach, the financial auditor has a wide range of working techniques, including selection techniques. They are applied depending on the nature of the information available to the financial auditor, the manner in which they are presented - paper or electronic format, and, last but not least, the time available. Several techniques are applied, successively or in parallel, to increase the safety of the expressed opinion and to provide the audit report with a solid basis of information. Sampling is used in the phase of control or clarification of the identified error. The main purpose is to corroborate or measure the degree of risk detected following a pertinent analysis. Since the auditor does not have time or means to thoroughly rebuild the information, the sampling technique can provide an effective response to the need for valorization.

Further observations on comparison of immunization coverage by lot quality assurance sampling and 30 cluster sampling.

Science.gov (United States)

Singh, J; Jain, D C; Sharma, R S; Verghese, T

1996-06-01

Lot Quality Assurance Sampling (LQAS) and standard EPI methodology (30 cluster sampling) were used to evaluate immunization coverage in a Primary Health Center (PHC) where coverage levels were reported to be more than 85%. Of 27 sub-centers (lots) evaluated by LQAS, only 2 were accepted for child coverage, whereas none was accepted for tetanus toxoid (TT) coverage in mothers. LQAS data were combined to obtain an estimate of coverage in the entire population; 41% (95% CI 36-46) infants were immunized appropriately for their ages, while 42% (95% CI 37-47) of their mothers had received a second/ booster dose of TT. TT coverage in 149 contemporary mothers sampled in EPI survey was also 42% (95% CI 31-52). Although results by the two sampling methods were consistent with each other, a big gap was evident between reported coverage (in children as well as mothers) and survey results. LQAS was found to be operationally feasible, but it cost 40% more and required 2.5 times more time than the EPI survey. LQAS therefore, is not a good substitute for current EPI methodology to evaluate immunization coverage in a large administrative area. However, LQAS has potential as method to monitor health programs on a routine basis in small population sub-units, especially in areas with high and heterogeneously distributed immunization coverage.

Performance Based Clustering for Benchmarking of Container Ports: an Application of Dea and Cluster Analysis Technique

Directory of Open Access Journals (Sweden)

Jie Wu

2010-12-01

Full Text Available The operational performance of container ports has received more and more attentions in both academic and practitioner circles, the performance evaluation and process improvement of container ports have also been the focus of several studies. In this paper, Data Envelopment Analysis (DEA, an effective tool for relative efficiency assessment, is utilized for measuring the performances and benchmarking of the 77 world container ports in 2007. The used approaches in the current study consider four inputs (Capacity of Cargo Handling Machines, Number of Berths, Terminal Area and Storage Capacity and a single output (Container Throughput. The results for the efficiency scores are analyzed, and a unique ordering of the ports based on average cross efficiency is provided, also cluster analysis technique is used to select the more appropriate targets for poorly performing ports to use as benchmarks.

Comparing cluster-level dynamic treatment regimens using sequential, multiple assignment, randomized trials: Regression estimation and sample size considerations.

Science.gov (United States)

NeCamp, Timothy; Kilbourne, Amy; Almirall, Daniel

2017-08-01

Cluster-level dynamic treatment regimens can be used to guide sequential treatment decision-making at the cluster level in order to improve outcomes at the individual or patient-level. In a cluster-level dynamic treatment regimen, the treatment is potentially adapted and re-adapted over time based on changes in the cluster that could be impacted by prior intervention, including aggregate measures of the individuals or patients that compose it. Cluster-randomized sequential multiple assignment randomized trials can be used to answer multiple open questions preventing scientists from developing high-quality cluster-level dynamic treatment regimens. In a cluster-randomized sequential multiple assignment randomized trial, sequential randomizations occur at the cluster level and outcomes are observed at the individual level. This manuscript makes two contributions to the design and analysis of cluster-randomized sequential multiple assignment randomized trials. First, a weighted least squares regression approach is proposed for comparing the mean of a patient-level outcome between the cluster-level dynamic treatment regimens embedded in a sequential multiple assignment randomized trial. The regression approach facilitates the use of baseline covariates which is often critical in the analysis of cluster-level trials. Second, sample size calculators are derived for two common cluster-randomized sequential multiple assignment randomized trial designs for use when the primary aim is a between-dynamic treatment regimen comparison of the mean of a continuous patient-level outcome. The methods are motivated by the Adaptive Implementation of Effective Programs Trial which is, to our knowledge, the first-ever cluster-randomized sequential multiple assignment randomized trial in psychiatry.

Clustering Game Behavior Data

DEFF Research Database (Denmark)

Bauckhage, C.; Drachen, Anders; Sifa, Rafet

2015-01-01

of the causes, the proliferation of behavioral data poses the problem of how to derive insights therefrom. Behavioral data sets can be large, time-dependent and high-dimensional. Clustering offers a way to explore such data and to discover patterns that can reduce the overall complexity of the data. Clustering...... and other techniques for player profiling and play style analysis have, therefore, become popular in the nascent field of game analytics. However, the proper use of clustering techniques requires expertise and an understanding of games is essential to evaluate results. With this paper, we address game data...... scientists and present a review and tutorial focusing on the application of clustering techniques to mine behavioral game data. Several algorithms are reviewed and examples of their application shown. Key topics such as feature normalization are discussed and open problems in the context of game analytics...

Sample size calculations for cluster randomised crossover trials in Australian and New Zealand intensive care research.

Science.gov (United States)

Arnup, Sarah J; McKenzie, Joanne E; Pilcher, David; Bellomo, Rinaldo; Forbes, Andrew B

2018-06-01

The cluster randomised crossover (CRXO) design provides an opportunity to conduct randomised controlled trials to evaluate low risk interventions in the intensive care setting. Our aim is to provide a tutorial on how to perform a sample size calculation for a CRXO trial, focusing on the meaning of the elements required for the calculations, with application to intensive care trials. We use all-cause in-hospital mortality from the Australian and New Zealand Intensive Care Society Adult Patient Database clinical registry to illustrate the sample size calculations. We show sample size calculations for a two-intervention, two 12-month period, cross-sectional CRXO trial. We provide the formulae, and examples of their use, to determine the number of intensive care units required to detect a risk ratio (RR) with a designated level of power between two interventions for trials in which the elements required for sample size calculations remain constant across all ICUs (unstratified design); and in which there are distinct groups (strata) of ICUs that differ importantly in the elements required for sample size calculations (stratified design). The CRXO design markedly reduces the sample size requirement compared with the parallel-group, cluster randomised design for the example cases. The stratified design further reduces the sample size requirement compared with the unstratified design. The CRXO design enables the evaluation of routinely used interventions that can bring about small, but important, improvements in patient care in the intensive care setting.

THE PANCHROMATIC HUBBLE ANDROMEDA TREASURY. III. MEASURING AGES AND MASSES OF PARTIALLY RESOLVED STELLAR CLUSTERS

Energy Technology Data Exchange (ETDEWEB)

Beerman, Lori C.; Johnson, L. Clifton; Fouesneau, Morgan; Dalcanton, Julianne J.; Weisz, Daniel R.; Williams, Ben F. [Department of Astronomy, University of Washington, Box 351580, Seattle, WA 98195 (United States); Seth, Anil C. [Department of Physics and Astronomy, University of Utah, Salt Lake City, UT 84112 (United States); Bell, Eric F. [Department of Astronomy, University of Michigan, 500 Church Street, Ann Arbor, MI 48109 (United States); Bianchi, Luciana C. [Department of Physics and Astronomy, Johns Hopkins University, 3400 North Charles Street, Baltimore, MD 21218 (United States); Caldwell, Nelson [Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138 (United States); Dolphin, Andrew E. [Raytheon Company, 1151 East Hermans Road, Tucson, AZ 85756 (United States); Gouliermis, Dimitrios A. [Zentrum fuer Astronomie, Institut fuer Theoretische Astrophysik, Universitaet Heidelberg, Albert-Ueberle-Strasse 2, D-69120 Heidelberg (Germany); Kalirai, Jason S. [Space Telescope Science Institute, 3700 San Martin Drive, Baltimore, MD 21218 (United States); Larsen, Soren S. [Department of Astrophysics, IMAPP, Radboud University Nijmegen, P.O. Box 9010, NL-6500 GL Nijmegen (Netherlands); Melbourne, Jason L. [Caltech Optical Observatories, Division of Physics, Mathematics and Astronomy, Mail Stop 301-17, California Institute of Technology, Pasadena, CA 91125 (United States); Rix, Hans-Walter [Max-Planck-Institut fuer Astronomie, Koenigstuhl 17, D-69117 Heidelberg (Germany); Skillman, Evan D., E-mail: beermalc@astro.washington.edu [Department of Astronomy, University of Minnesota, 116 Church Street SE, Minneapolis, MN 55455 (United States)

2012-12-01

The apparent age and mass of a stellar cluster can be strongly affected by stochastic sampling of the stellar initial mass function (IMF), when inferred from the integrated color of low-mass clusters ({approx}<10{sup 4} M {sub Sun }). We use simulated star clusters to show that these effects are minimized when the brightest, rapidly evolving stars in a cluster can be resolved, and the light of the fainter, more numerous unresolved stars can be analyzed separately. When comparing the light from the less luminous cluster members to models of unresolved light, more accurate age estimates can be obtained than when analyzing the integrated light from the entire cluster under the assumption that the IMF is fully populated. We show the success of this technique first using simulated clusters, and then with a stellar cluster in M31. This method represents one way of accounting for the discrete, stochastic sampling of the stellar IMF in less massive clusters and can be leveraged in studies of clusters throughout the Local Group and other nearby galaxies.

Integrative cluster analysis in bioinformatics

CERN Document Server

Abu-Jamous, Basel; Nandi, Asoke K

2015-01-01

Clustering techniques are increasingly being put to use in the analysis of high-throughput biological datasets. Novel computational techniques to analyse high throughput data in the form of sequences, gene and protein expressions, pathways, and images are becoming vital for understanding diseases and future drug discovery. This book details the complete pathway of cluster analysis, from the basics of molecular biology to the generation of biological knowledge. The book also presents the latest clustering methods and clustering validation, thereby offering the reader a comprehensive review o

Evaluation of immunization coverage by lot quality assurance sampling compared with 30-cluster sampling in a primary health centre in India.

Science.gov (United States)

Singh, J; Jain, D C; Sharma, R S; Verghese, T

1996-01-01

The immunization coverage of infants, children and women residing in a primary health centre (PHC) area in Rajasthan was evaluated both by lot quality assurance sampling (LQAS) and by the 30-cluster sampling method recommended by WHO's Expanded Programme on Immunization (EPI). The LQAS survey was used to classify 27 mutually exclusive subunits of the population, defined as residents in health subcentre areas, on the basis of acceptable or unacceptable levels of immunization coverage among infants and their mothers. The LQAS results from the 27 subcentres were also combined to obtain an overall estimate of coverage for the entire population of the primary health centre, and these results were compared with the EPI cluster survey results. The LQAS survey did not identify any subcentre with a level of immunization among infants high enough to be classified as acceptable; only three subcentres were classified as having acceptable levels of tetanus toxoid (TT) coverage among women. The estimated overall coverage in the PHC population from the combined LQAS results showed that a quarter of the infants were immunized appropriately for their ages and that 46% of their mothers had been adequately immunized with TT. Although the age groups and the periods of time during which the children were immunized differed for the LQAS and EPI survey populations, the characteristics of the mothers were largely similar. About 57% (95% CI, 46-67) of them were found to be fully immunized with TT by 30-cluster sampling, compared with 46% (95% CI, 41-51) by stratified random sampling. The difference was not statistically significant. The field work to collect LQAS data took about three times longer, and cost 60% more than the EPI survey. The apparently homogeneous and low level of immunization coverage in the 27 subcentres makes this an impractical situation in which to apply LQAS, and the results obtained were therefore not particularly useful. However, if LQAS had been applied by local

Applications of Cluster Analysis to the Creation of Perfectionism Profiles: A Comparison of two Clustering Approaches

Directory of Open Access Journals (Sweden)

Jocelyn H Bolin

2014-04-01

Full Text Available Although traditional clustering methods (e.g., K-means have been shown to be useful in the social sciences it is often difficult for such methods to handle situations where clusters in the population overlap or are ambiguous. Fuzzy clustering, a method already recognized in many disciplines, provides a more flexible alternative to these traditional clustering methods. Fuzzy clustering differs from other traditional clustering methods in that it allows for a case to belong to multiple clusters simultaneously. Unfortunately, fuzzy clustering techniques remain relatively unused in the social and behavioral sciences. The purpose of this paper is to introduce fuzzy clustering to these audiences who are currently relatively unfamiliar with the technique. In order to demonstrate the advantages associated with this method, cluster solutions of a common perfectionism measure were created using both fuzzy clustering and K-means clustering, and the results compared. Results of these analyses reveal that different cluster solutions are found by the two methods, and the similarity between the different clustering solutions depends on the amount of cluster overlap allowed for in fuzzy clustering.

Applications of cluster analysis to the creation of perfectionism profiles: a comparison of two clustering approaches.

Science.gov (United States)

Bolin, Jocelyn H; Edwards, Julianne M; Finch, W Holmes; Cassady, Jerrell C

2014-01-01

Although traditional clustering methods (e.g., K-means) have been shown to be useful in the social sciences it is often difficult for such methods to handle situations where clusters in the population overlap or are ambiguous. Fuzzy clustering, a method already recognized in many disciplines, provides a more flexible alternative to these traditional clustering methods. Fuzzy clustering differs from other traditional clustering methods in that it allows for a case to belong to multiple clusters simultaneously. Unfortunately, fuzzy clustering techniques remain relatively unused in the social and behavioral sciences. The purpose of this paper is to introduce fuzzy clustering to these audiences who are currently relatively unfamiliar with the technique. In order to demonstrate the advantages associated with this method, cluster solutions of a common perfectionism measure were created using both fuzzy clustering and K-means clustering, and the results compared. Results of these analyses reveal that different cluster solutions are found by the two methods, and the similarity between the different clustering solutions depends on the amount of cluster overlap allowed for in fuzzy clustering.

THE CLUSTERING OF ALFALFA GALAXIES: DEPENDENCE ON H I MASS, RELATIONSHIP WITH OPTICAL SAMPLES, AND CLUES OF HOST HALO PROPERTIES

Energy Technology Data Exchange (ETDEWEB)

Papastergis, Emmanouil; Giovanelli, Riccardo; Haynes, Martha P.; Jones, Michael G. [Center for Radiophysics and Space Research, Space Sciences Building, Cornell University, Ithaca, NY 14853 (United States); Rodríguez-Puebla, Aldo, E-mail: papastergis@astro.cornell.edu, E-mail: riccardo@astro.cornell.edu, E-mail: haynes@astro.cornell.edu, E-mail: jonesmg@astro.cornell.edu, E-mail: apuebla@astro.unam.mx [Instituto de Astronomía, Universidad Nacional Autónoma de México, A. P. 70-264, 04510 México, D.F. (Mexico)

2013-10-10

We use a sample of ≈6000 galaxies detected by the Arecibo Legacy Fast ALFA (ALFALFA) 21 cm survey to measure the clustering properties of H I-selected galaxies. We find no convincing evidence for a dependence of clustering on galactic atomic hydrogen (H I) mass, over the range M{sub H{sub I}} ≈ 10{sup 8.5}-10{sup 10.5} M{sub ☉}. We show that previously reported results of weaker clustering for low H I mass galaxies are probably due to finite-volume effects. In addition, we compare the clustering of ALFALFA galaxies with optically selected samples drawn from the Sloan Digital Sky Survey (SDSS). We find that H I-selected galaxies cluster more weakly than even relatively optically faint galaxies, when no color selection is applied. Conversely, when SDSS galaxies are split based on their color, we find that the correlation function of blue optical galaxies is practically indistinguishable from that of H I-selected galaxies. At the same time, SDSS galaxies with red colors are found to cluster significantly more than H I-selected galaxies, a fact that is evident in both the projected as well as the full two-dimensional correlation function. A cross-correlation analysis further reveals that gas-rich galaxies 'avoid' being located within ≈3 Mpc of optical galaxies with red colors. Next, we consider the clustering properties of halo samples selected from the Bolshoi ΛCDM simulation. A comparison with the clustering of ALFALFA galaxies suggests that galactic H I mass is not tightly related to host halo mass and that a sizable fraction of subhalos do not host H I galaxies. Lastly, we find that we can recover fairly well the correlation function of H I galaxies by just excluding halos with low spin parameter. This finding lends support to the hypothesis that halo spin plays a key role in determining the gas content of galaxies.

Visualization techniques for spatial probability density function data

Directory of Open Access Journals (Sweden)

Udeepta D Bordoloi

2006-01-01

Full Text Available Novel visualization methods are presented for spatial probability density function data. These are spatial datasets, where each pixel is a random variable, and has multiple samples which are the results of experiments on that random variable. We use clustering as a means to reduce the information contained in these datasets; and present two different ways of interpreting and clustering the data. The clustering methods are used on two datasets, and the results are discussed with the help of visualization techniques designed for the spatial probability data.

Performance Evaluation of Spectral Clustering Algorithm using Various Clustering Validity Indices

OpenAIRE

M. T. Somashekara; D. Manjunatha

2014-01-01

In spite of the popularity of spectral clustering algorithm, the evaluation procedures are still in developmental stage. In this article, we have taken benchmarking IRIS dataset for performing comparative study of twelve indices for evaluating spectral clustering algorithm. The results of the spectral clustering technique were also compared with k-mean algorithm. The validity of the indices was also verified with accuracy and (Normalized Mutual Information) NMI score. Spectral clustering algo...

Nuclear analytical techniques and their application to environmental samples

International Nuclear Information System (INIS)

Lieser, K.H.

1986-01-01

A survey is given on nuclear analytical techniques and their application to environmental samples. Measurement of the inherent radioactivity of elements or radionuclides allows determination of natural radioelements (e.g. Ra), man-made radioelements (e.g. Pu) and radionuclides in the environment. Activation analysis, in particular instrumental neutron activation analysis, is a very reliable and sensitive method for determination of a great number of trace elements in environmental samples, because the most abundant main constituents are not activated. Tracer techniques are very useful for studies of the behaviour and of chemical reactions of trace elements and compounds in the environment. Radioactive sources are mainly applied for excitation of characteristic X-rays (X-ray fluorescence analysis). (author)

An observational study of disk-population globular clusters

International Nuclear Information System (INIS)

Armandroff, T.E.

1988-01-01

Integrated-light spectroscopy was obtained for twenty-seven globular clusters at the Ca II infrared triplet. Line strengths and radial velocities were measured from the spectra. For the well-studied clusters in the sample, the strength of the CA II lines is very well correlated with previous metallicity estimates obtained using a variety of techniques. The greatly reduced effect of interstellar extinction at these wavelengths compared to the blue region of the spectrum has permitted observations of some of the most heavily reddened clusters in the Galaxy. For several such clusters, the Ca II triplet metallicities are in poor agreement with metallicity estimates from infrared photometry by Malkan. Color-magnitude diagrams were constructed for six previously unstudied metal-rich globular clusters and for the well-studied cluster 47 Tuc. The V magnitudes of the horizontal branch stars in the six clusters are in poor agreement with previous estimates based on secondary methods. The horizontal branch morphologies and reddenings of the program clusters were also determined. Using the improved set of metallicities, radial velocities, and distance moduli, the spatial distribution, kinematics, and metallicity distribution of the Galactic globulars were analyzed. The revised data supports Zinn's conclusion that the metal-rich clusters form a highly flattened, rapidly rotating disk system, while the metal-poor clusters make up the familiar, spherically distributed, slowly rotating halo population. The scale height, metallicity distribution, and kinematics of the metal-rich globulars are in good agreement with those of the stellar thick disk. Luminosity functions were constructed, and no significant difference is found between disk and halo samples. Metallicity gradients seem to be present in the disk cluster system. The implications of these results for the formation and evol

Dense Fe cluster-assembled films by energetic cluster deposition

International Nuclear Information System (INIS)

Peng, D.L.; Yamada, H.; Hihara, T.; Uchida, T.; Sumiyama, K.

2004-01-01

High-density Fe cluster-assembled films were produced at room temperature by an energetic cluster deposition. Though cluster-assemblies are usually sooty and porous, the present Fe cluster-assembled films are lustrous and dense, revealing a soft magnetic behavior. Size-monodispersed Fe clusters with the mean cluster size d=9 nm were synthesized using a plasma-gas-condensation technique. Ionized clusters are accelerated electrically and deposited onto the substrate together with neutral clusters from the same cluster source. Packing fraction and saturation magnetic flux density increase rapidly and magnetic coercivity decreases remarkably with increasing acceleration voltage. The Fe cluster-assembled film obtained at the acceleration voltage of -20 kV has a packing fraction of 0.86±0.03, saturation magnetic flux density of 1.78±0.05 Wb/m 2 , and coercivity value smaller than 80 A/m. The resistivity at room temperature is ten times larger than that of bulk Fe metal

Clinical evaluation of nonsyndromic dental anomalies in Dravidian population: A cluster sample analysis

OpenAIRE

Yamunadevi, Andamuthu; Selvamani, M.; Vinitha, V.; Srivandhana, R.; Balakrithiga, M.; Prabhu, S.; Ganapathy, N.

2015-01-01

Aim: To record the prevalence rate of dental anomalies in Dravidian population and analyze the percentage of individual anomalies in the population. Methodology: A cluster sample analysis was done, where 244 subjects studying in a dental institution were all included and analyzed for occurrence of dental anomalies by clinical examination, excluding third molars from analysis. Results: 31.55% of the study subjects had dental anomalies and shape anomalies were more prevalent (22.1%), followed b...

Comparing the performance of cluster random sampling and integrated threshold mapping for targeting trachoma control, using computer simulation.

Directory of Open Access Journals (Sweden)

Jennifer L Smith

Full Text Available Implementation of trachoma control strategies requires reliable district-level estimates of trachomatous inflammation-follicular (TF, generally collected using the recommended gold-standard cluster randomized surveys (CRS. Integrated Threshold Mapping (ITM has been proposed as an integrated and cost-effective means of rapidly surveying trachoma in order to classify districts according to treatment thresholds. ITM differs from CRS in a number of important ways, including the use of a school-based sampling platform for children aged 1-9 and a different age distribution of participants. This study uses computerised sampling simulations to compare the performance of these survey designs and evaluate the impact of varying key parameters.Realistic pseudo gold standard data for 100 districts were generated that maintained the relative risk of disease between important sub-groups and incorporated empirical estimates of disease clustering at the household, village and district level. To simulate the different sampling approaches, 20 clusters were selected from each district, with individuals sampled according to the protocol for ITM and CRS. Results showed that ITM generally under-estimated the true prevalence of TF over a range of epidemiological settings and introduced more district misclassification according to treatment thresholds than did CRS. However, the extent of underestimation and resulting misclassification was found to be dependent on three main factors: (i the district prevalence of TF; (ii the relative risk of TF between enrolled and non-enrolled children within clusters; and (iii the enrollment rate in schools.Although in some contexts the two methodologies may be equivalent, ITM can introduce a bias-dependent shift as prevalence of TF increases, resulting in a greater risk of misclassification around treatment thresholds. In addition to strengthening the evidence base around choice of trachoma survey methodologies, this study illustrates

Pearson's chi-square test and rank correlation inferences for clustered data.

Science.gov (United States)

Shih, Joanna H; Fay, Michael P

2017-09-01

Pearson's chi-square test has been widely used in testing for association between two categorical responses. Spearman rank correlation and Kendall's tau are often used for measuring and testing association between two continuous or ordered categorical responses. However, the established statistical properties of these tests are only valid when each pair of responses are independent, where each sampling unit has only one pair of responses. When each sampling unit consists of a cluster of paired responses, the assumption of independent pairs is violated. In this article, we apply the within-cluster resampling technique to U-statistics to form new tests and rank-based correlation estimators for possibly tied clustered data. We develop large sample properties of the new proposed tests and estimators and evaluate their performance by simulations. The proposed methods are applied to a data set collected from a PET/CT imaging study for illustration. Published 2017. This article is a U.S. Government work and is in the public domain in the USA.

Dense graph limits under respondent-driven sampling

Indian Academy of Sciences (India)

Siva Athreya

Types of network. Food. Political. Social. Linkedin. Protien. Professional. Source: IUPUI Network Sampling course. Page 3. Techniques to Analyse Networks. Network Characteristics: • Distribution: degree, clustering coefficient, hop-plot. ... Hypothesis Testing: H0: Graph is a linkedin network. H1: Graph is a facebook network ...

Micro and Nano Techniques for the Handling of Biological Samples

DEFF Research Database (Denmark)

Micro and Nano Techniques for the Handling of Biological Samples reviews the different techniques available to manipulate and integrate biological materials in a controlled manner, either by sliding them along a surface (2-D manipulation), or by gripping and moving them to a new position (3-D...

Chandra Cluster Cosmology Project. II. Samples and X-Ray Data Reduction

DEFF Research Database (Denmark)

Vikhlinin, A.; Burenin, R. A.; Ebeling, H.

2009-01-01

We discuss the measurements of the galaxy cluster mass functions at z ≈ 0.05 and z ≈ 0.5 using high-quality Chandra observations of samples derived from the ROSAT PSPC All-Sky and 400 deg2 surveys. We provide a full reference for the data analysis procedures, present updated calibration of relati...... at a fixed mass threshold, e.g., by a factor of 5.0 ± 1.2 at M 500 = 2.5 × 1014 h –1 M sun between z = 0 and 0.5. This evolution reflects the growth of density perturbations, and can be used for the cosmological constraints complementing those from the distance-redshift relation....

Efficient computation of the elastography inverse problem by combining variational mesh adaption and a clustering technique

International Nuclear Information System (INIS)

Arnold, Alexander; Bruhns, Otto T; Reichling, Stefan; Mosler, Joern

2010-01-01

This paper is concerned with an efficient implementation suitable for the elastography inverse problem. More precisely, the novel algorithm allows us to compute the unknown stiffness distribution in soft tissue by means of the measured displacement field by considerably reducing the numerical cost compared to previous approaches. This is realized by combining and further elaborating variational mesh adaption with a clustering technique similar to those known from digital image compression. Within the variational mesh adaption, the underlying finite element discretization is only locally refined if this leads to a considerable improvement of the numerical solution. Additionally, the numerical complexity is reduced by the aforementioned clustering technique, in which the parameters describing the stiffness of the respective soft tissue are sorted according to a predefined number of intervals. By doing so, the number of unknowns associated with the elastography inverse problem can be chosen explicitly. A positive side effect of this method is the reduction of artificial noise in the data (smoothing of the solution). The performance and the rate of convergence of the resulting numerical formulation are critically analyzed by numerical examples.

Weak-lensing mass calibration of the Atacama Cosmology Telescope equatorial Sunyaev-Zeldovich cluster sample with the Canada-France-Hawaii telescope stripe 82 survey

Energy Technology Data Exchange (ETDEWEB)

Battaglia, N.; Miyatake, H.; Hasselfield, M.; Calabrese, E.; Ferrara, S.; Hložek, R. [Dept. of Astrophysical Sciences, Princeton University, Princeton, NJ 08544 (United States); Leauthaud, A. [Kavli IPMU (WPI), UTIAS, The University of Tokyo, Kashiwa, Chiba 277-8583 (Japan); Gralla, M.B.; Crichton, D. [Dept. of Physics and Astronomy, Johns Hopkins University, Baltimore, MD 21218 (United States); Allison, R.; Dunkley, J. [Dept. of Astrophysics, University of Oxford, Oxford OX1 3RH (United Kingdom); Bond, J.R. [Canadian Institute for Theoretical Astrophysics, Toronto, ON M5S 3H8 (Canada); Devlin, M.J. [Dept. of Physics and Astronomy, University of Pennsylvania, Philadelphia, PA 19104 (United States); Dünner, R. [Dept. de Astronomía y Astrofísica, Facultad de Física, Pontificia Universidad Católica de Chile, Santiago (Chile); Erben, T. [Argelander-Institut für Astronomie, University of Bonn, 53121 Bonn (Germany); Halpern, M.; Hincks, A.D. [Dept. of Physics and Astronomy, University of British Columbia, Vancouver, BC, V6T 1Z4 (Canada); Hilton, M. [Astrophysics and Cosmology Research Unit, School of Mathematical, Statistics and Computer Science, University of KwaZulu-Natal, Durban, 4041 (South Africa); Hill, J.C. [Dept. of Astronomy, Columbia University, New York, NY 10027 (United States); Huffenberger, K.M., E-mail: nbatta@astro.princeton.edu [Dept. of Physics, Florida State University, Tallahassee, FL 32306 (United States); and others

2016-08-01

Mass calibration uncertainty is the largest systematic effect for using clusters of galaxies to constrain cosmological parameters. We present weak lensing mass measurements from the Canada-France-Hawaii Telescope Stripe 82 Survey for galaxy clusters selected through their high signal-to-noise thermal Sunyaev-Zeldovich (tSZ) signal measured with the Atacama Cosmology Telescope (ACT). For a sample of 9 ACT clusters with a tSZ signal-to-noise greater than five the average weak lensing mass is (4.8±0.8) ×10{sup 14} M{sub ⊙}, consistent with the tSZ mass estimate of (4.70±1.0) ×10{sup 14} M{sub ⊙} which assumes a universal pressure profile for the cluster gas. Our results are consistent with previous weak-lensing measurements of tSZ-detected clusters from the Planck satellite. When comparing our results, we estimate the Eddington bias correction for the sample intersection of Planck and weak-lensing clusters which was previously excluded.

Weak-lensing mass calibration of the Atacama Cosmology Telescope equatorial Sunyaev-Zeldovich cluster sample with the Canada-France-Hawaii telescope stripe 82 survey

International Nuclear Information System (INIS)

Battaglia, N.; Miyatake, H.; Hasselfield, M.; Calabrese, E.; Ferrara, S.; Hložek, R.; Leauthaud, A.; Gralla, M.B.; Crichton, D.; Allison, R.; Dunkley, J.; Bond, J.R.; Devlin, M.J.; Dünner, R.; Erben, T.; Halpern, M.; Hincks, A.D.; Hilton, M.; Hill, J.C.; Huffenberger, K.M.

2016-01-01

Mass calibration uncertainty is the largest systematic effect for using clusters of galaxies to constrain cosmological parameters. We present weak lensing mass measurements from the Canada-France-Hawaii Telescope Stripe 82 Survey for galaxy clusters selected through their high signal-to-noise thermal Sunyaev-Zeldovich (tSZ) signal measured with the Atacama Cosmology Telescope (ACT). For a sample of 9 ACT clusters with a tSZ signal-to-noise greater than five the average weak lensing mass is (4.8±0.8) ×10 14 M ⊙ , consistent with the tSZ mass estimate of (4.70±1.0) ×10 14 M ⊙ which assumes a universal pressure profile for the cluster gas. Our results are consistent with previous weak-lensing measurements of tSZ-detected clusters from the Planck satellite. When comparing our results, we estimate the Eddington bias correction for the sample intersection of Planck and weak-lensing clusters which was previously excluded.

A Trajectory Regression Clustering Technique Combining a Novel Fuzzy C-Means Clustering Algorithm with the Least Squares Method

Directory of Open Access Journals (Sweden)

Xiangbing Zhou

2018-04-01

Full Text Available Rapidly growing GPS (Global Positioning System trajectories hide much valuable information, such as city road planning, urban travel demand, and population migration. In order to mine the hidden information and to capture better clustering results, a trajectory regression clustering method (an unsupervised trajectory clustering method is proposed to reduce local information loss of the trajectory and to avoid getting stuck in the local optimum. Using this method, we first define our new concept of trajectory clustering and construct a novel partitioning (angle-based partitioning method of line segments; second, the Lagrange-based method and Hausdorff-based K-means++ are integrated in fuzzy C-means (FCM clustering, which are used to maintain the stability and the robustness of the clustering process; finally, least squares regression model is employed to achieve regression clustering of the trajectory. In our experiment, the performance and effectiveness of our method is validated against real-world taxi GPS data. When comparing our clustering algorithm with the partition-based clustering algorithms (K-means, K-median, and FCM, our experimental results demonstrate that the presented method is more effective and generates a more reasonable trajectory.

Methodological integrative review of the work sampling technique used in nursing workload research.

Science.gov (United States)

Blay, Nicole; Duffield, Christine M; Gallagher, Robyn; Roche, Michael

2014-11-01

To critically review the work sampling technique used in nursing workload research. Work sampling is a technique frequently used by researchers and managers to explore and measure nursing activities. However, work sampling methods used are diverse making comparisons of results between studies difficult. Methodological integrative review. Four electronic databases were systematically searched for peer-reviewed articles published between 2002-2012. Manual scanning of reference lists and Rich Site Summary feeds from contemporary nursing journals were other sources of data. Articles published in the English language between 2002-2012 reporting on research which used work sampling to examine nursing workload. Eighteen articles were reviewed. The review identified that the work sampling technique lacks a standardized approach, which may have an impact on the sharing or comparison of results. Specific areas needing a shared understanding included the training of observers and subjects who self-report, standardization of the techniques used to assess observer inter-rater reliability, sampling methods and reporting of outcomes. Work sampling is a technique that can be used to explore the many facets of nursing work. Standardized reporting measures would enable greater comparison between studies and contribute to knowledge more effectively. Author suggestions for the reporting of results may act as guidelines for researchers considering work sampling as a research method. © 2014 John Wiley & Sons Ltd.

Validating clustering of molecular dynamics simulations using polymer models

Directory of Open Access Journals (Sweden)

Phillips Joshua L

2011-11-01

Full Text Available Abstract Background Molecular dynamics (MD simulation is a powerful technique for sampling the meta-stable and transitional conformations of proteins and other biomolecules. Computational data clustering has emerged as a useful, automated technique for extracting conformational states from MD simulation data. Despite extensive application, relatively little work has been done to determine if the clustering algorithms are actually extracting useful information. A primary goal of this paper therefore is to provide such an understanding through a detailed analysis of data clustering applied to a series of increasingly complex biopolymer models. Results We develop a novel series of models using basic polymer theory that have intuitive, clearly-defined dynamics and exhibit the essential properties that we are seeking to identify in MD simulations of real biomolecules. We then apply spectral clustering, an algorithm particularly well-suited for clustering polymer structures, to our models and MD simulations of several intrinsically disordered proteins. Clustering results for the polymer models provide clear evidence that the meta-stable and transitional conformations are detected by the algorithm. The results for the polymer models also help guide the analysis of the disordered protein simulations by comparing and contrasting the statistical properties of the extracted clusters. Conclusions We have developed a framework for validating the performance and utility of clustering algorithms for studying molecular biopolymer simulations that utilizes several analytic and dynamic polymer models which exhibit well-behaved dynamics including: meta-stable states, transition states, helical structures, and stochastic dynamics. We show that spectral clustering is robust to anomalies introduced by structural alignment and that different structural classes of intrinsically disordered proteins can be reliably discriminated from the clustering results. To our

Systematic comparison of static and dynamic headspace sampling techniques for gas chromatography.

Science.gov (United States)

Kremser, Andreas; Jochmann, Maik A; Schmidt, Torsten C

2016-09-01

Six automated, headspace-based sample preparation techniques were used to extract volatile analytes from water with the goal of establishing a systematic comparison between commonly available instrumental alternatives. To that end, these six techniques were used in conjunction with the same gas chromatography instrument for analysis of a common set of volatile organic carbon (VOC) analytes. The methods were thereby divided into three classes: static sampling (by syringe or loop), static enrichment (SPME and PAL SPME Arrow), and dynamic enrichment (ITEX and trap sampling). For PAL SPME Arrow, different sorption phase materials were also included in the evaluation. To enable an effective comparison, method detection limits (MDLs), relative standard deviations (RSDs), and extraction yields were determined and are discussed for all techniques. While static sampling techniques exhibited sufficient extraction yields (approx. 10-20 %) to be reliably used down to approx. 100 ng L(-1), enrichment techniques displayed extraction yields of up to 80 %, resulting in MDLs down to the picogram per liter range. RSDs for all techniques were below 27 %. The choice on one of the different instrumental modes of operation (aforementioned classes) was thereby the most influential parameter in terms of extraction yields and MDLs. Individual methods inside each class showed smaller deviations, and the least influences were observed when evaluating different sorption phase materials for the individual enrichment techniques. The option of selecting specialized sorption phase materials may, however, be more important when analyzing analytes with different properties such as high polarity or the capability of specific molecular interactions. Graphical Abstract PAL SPME Arrow during the extraction of volatile analytes from the headspace of an aqueous sample.

THE SWIFT AGN AND CLUSTER SURVEY. II. CLUSTER CONFIRMATION WITH SDSS DATA

International Nuclear Information System (INIS)

Griffin, Rhiannon D.; Dai, Xinyu; Kochanek, Christopher S.; Bregman, Joel N.

2016-01-01

We study 203 (of 442) Swift AGN and Cluster Survey extended X-ray sources located in the SDSS DR8 footprint to search for galaxy over-densities in three-dimensional space using SDSS galaxy photometric redshifts and positions near the Swift cluster candidates. We find 104 Swift clusters with a >3σ galaxy over-density. The remaining targets are potentially located at higher redshifts and require deeper optical follow-up observations for confirmation as galaxy clusters. We present a series of cluster properties including the redshift, brightest cluster galaxy (BCG) magnitude, BCG-to-X-ray center offset, optical richness, and X-ray luminosity. We also detect red sequences in ∼85% of the 104 confirmed clusters. The X-ray luminosity and optical richness for the SDSS confirmed Swift clusters are correlated and follow previously established relations. The distribution of the separations between the X-ray centroids and the most likely BCG is also consistent with expectation. We compare the observed redshift distribution of the sample with a theoretical model, and find that our sample is complete for z ≲ 0.3 and is still 80% complete up to z ≃ 0.4, consistent with the SDSS survey depth. These analysis results suggest that our Swift cluster selection algorithm has yielded a statistically well-defined cluster sample for further study of cluster evolution and cosmology. We also match our SDSS confirmed Swift clusters to existing cluster catalogs, and find 42, 23, and 1 matches in optical, X-ray, and Sunyaev–Zel’dovich catalogs, respectively, and so the majority of these clusters are new detections

OBSERVED SCALING RELATIONS FOR STRONG LENSING CLUSTERS: CONSEQUENCES FOR COSMOLOGY AND CLUSTER ASSEMBLY

International Nuclear Information System (INIS)

Comerford, Julia M.; Moustakas, Leonidas A.; Natarajan, Priyamvada

2010-01-01

Scaling relations of observed galaxy cluster properties are useful tools for constraining cosmological parameters as well as cluster formation histories. One of the key cosmological parameters, σ 8 , is constrained using observed clusters of galaxies, although current estimates of σ 8 from the scaling relations of dynamically relaxed galaxy clusters are limited by the large scatter in the observed cluster mass-temperature (M-T) relation. With a sample of eight strong lensing clusters at 0.3 8 , but combining the cluster concentration-mass relation with the M-T relation enables the inclusion of unrelaxed clusters as well. Thus, the resultant gains in the accuracy of σ 8 measurements from clusters are twofold: the errors on σ 8 are reduced and the cluster sample size is increased. Therefore, the statistics on σ 8 determination from clusters are greatly improved by the inclusion of unrelaxed clusters. Exploring cluster scaling relations further, we find that the correlation between brightest cluster galaxy (BCG) luminosity and cluster mass offers insight into the assembly histories of clusters. We find preliminary evidence for a steeper BCG luminosity-cluster mass relation for strong lensing clusters than the general cluster population, hinting that strong lensing clusters may have had more active merging histories.

Cluster Analysis of the Yale Global Tic Severity Scale (YGTSS): Symptom Dimensions and Clinical Correlates in an Outpatient Youth Sample

Science.gov (United States)

Kircanski, Katharina; Woods, Douglas W.; Chang, Susanna W.; Ricketts, Emily J.; Piacentini, John C.

2010-01-01

Tic disorders are heterogeneous, with symptoms varying widely both within and across patients. Exploration of symptom clusters may aid in the identification of symptom dimensions of empirical and treatment import. This article presents the results of two studies investigating tic symptom clusters using a sample of 99 youth (M age = 10.7, 81% male,…

Cluster analysis of track structure

International Nuclear Information System (INIS)

Michalik, V.

1991-01-01

One of the possibilities of classifying track structures is application of conventional partition techniques of analysis of multidimensional data to the track structure. Using these cluster algorithms this paper attempts to find characteristics of radiation reflecting the spatial distribution of ionizations in the primary particle track. An absolute frequency distribution of clusters of ionizations giving the mean number of clusters produced by radiation per unit of deposited energy can serve as this characteristic. General computation techniques used as well as methods of calculations of distributions of clusters for different radiations are discussed. 8 refs.; 5 figs

RF Sub-sampling Receiver Architecture based on Milieu Adapting Techniques

DEFF Research Database (Denmark)

Behjou, Nastaran; Larsen, Torben; Jensen, Ole Kiel

2012-01-01

A novel sub-sampling based architecture is proposed which has the ability of reducing the problem of image distortion and improving the signal to noise ratio significantly. The technique is based on sensing the environment and adapting the sampling rate of the receiver to the best possible...

Improved importance sampling technique for efficient simulation of digital communication systems

Science.gov (United States)

Lu, Dingqing; Yao, Kung

1988-01-01

A new, improved importance sampling (IIS) approach to simulation is considered. Some basic concepts of IS are introduced, and detailed evolutions of simulation estimation variances for Monte Carlo (MC) and IS simulations are given. The general results obtained from these evolutions are applied to the specific previously known conventional importance sampling (CIS) technique and the new IIS technique. The derivation for a linear system with no signal random memory is considered in some detail. For the CIS technique, the optimum input scaling parameter is found, while for the IIS technique, the optimum translation parameter is found. The results are generalized to a linear system with memory and signals. Specific numerical and simulation results are given which show the advantages of CIS over MC and IIS over CIS for simulations of digital communications systems.

Cone penetrometer tests and HydroPunch sampling: A screening technique for plume definition

International Nuclear Information System (INIS)

Smolley, M.; Kappmeyer, J.C.

1991-01-01

Cone penetrometer tests and HydroPunch sampling were used to define the extent of volatile organic compounds in ground water. The investigation indicated that the combination of the these techniques is effective for obtaining ground water samples for preliminary plume definition. HydroPunch samples can be collected in unconsolidated sediments and the analytical results obtained from these samples are comparable to those obtained from adjacent monitoring wells. This sampling method is a rapid and cost-effective screening technique for characterizing the extent of contaminant plumes in soft sediment environments. Use of this screening technique allowed monitoring wells to be located at the plume boundary, thereby reducing the number of wells installed and the overall cost of the plume definition program

Chance constrained problems: penalty reformulation and performance of sample approximation technique

Czech Academy of Sciences Publication Activity Database

Branda, Martin

2012-01-01

Roč. 48, č. 1 (2012), s. 105-122 ISSN 0023-5954 R&D Projects: GA ČR(CZ) GBP402/12/G097 Institutional research plan: CEZ:AV0Z10750506 Keywords : chance constrained problems * penalty functions * asymptotic equivalence * sample approximation technique * investment problem Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.619, year: 2012 http://library.utia.cas.cz/separaty/2012/E/branda-chance constrained problems penalty reformulation and performance of sample approximation technique.pdf

Probing BL Lac and Cluster Evolution via a Wide-angle, Deep X-ray Selected Sample

Science.gov (United States)

Perlman, E.; Jones, L.; White, N.; Angelini, L.; Giommi, P.; McHardy, I.; Wegner, G.

1994-12-01

The WARPS survey (Wide-Angle ROSAT Pointed Survey) has been constructed from the archive of all public ROSAT PSPC observations, and is a subset of the WGACAT catalog. WARPS will include a complete sample of >= 100 BL Lacs at F_x >= 10(-13) erg s(-1) cm(-2) . A second selection technique will identify ~ 100 clusters at 0.15 = 0.304 +/- 0.062 for XBLs but = 0.60 +/- 0.05 for RBLs. Models of the X-ray luminosity function (XLF) are also poorly constrained. WARPS will allow us to compute an accurate XLF, decreasing the error bars above by over a factor of two. We will also test for low-luminosity BL Lacs, whose non-thermal nuclear sources are dim compared to the host galaxy. Browne and Marcha (1993) claim the EMSS missed most of these objects and is incomplete. If their predictions are correct, 20-40% of the BL Lacs we find will fall in this category, enabling us to probe the evolution and internal workings of BL Lacs at lower luminosities than ever before. By removing likely QSOs before optical spectroscopy, WARPS requires only modest amounts of telescope time. It will extend measurement of the cluster XLF both to higher redshifts (z>0.5) and lower luminosities (LX<1x10(44) erg s(-1) ) than previous measurements, confirming or rejecting the 3sigma detection of negative evolution found in the EMSS, and constraining Cold Dark Matter cosmologies. Faint NELGs are a recently discovered major contributor to the X-ray background. They are a mixture of Sy2s, starbursts and galaxies of unknown type. Detailed classification and evolution of their XLF will be determined for the first time.

Channel Parameter Estimation for Scatter Cluster Model Using Modified MUSIC Algorithm

Directory of Open Access Journals (Sweden)

Jinsheng Yang

2012-01-01

Full Text Available Recently, the scatter cluster models which precisely evaluate the performance of the wireless communication system have been proposed in the literature. However, the conventional SAGE algorithm does not work for these scatter cluster-based models because it performs poorly when the transmit signals are highly correlated. In this paper, we estimate the time of arrival (TOA, the direction of arrival (DOA, and Doppler frequency for scatter cluster model by the modified multiple signal classification (MUSIC algorithm. Using the space-time characteristics of the multiray channel, the proposed algorithm combines the temporal filtering techniques and the spatial smoothing techniques to isolate and estimate the incoming rays. The simulation results indicated that the proposed algorithm has lower complexity and is less time-consuming in the dense multipath environment than SAGE algorithm. Furthermore, the estimations’ performance increases with elements of receive array and samples length. Thus, the problem of the channel parameter estimation of the scatter cluster model can be effectively addressed with the proposed modified MUSIC algorithm.

A relevance vector machine technique for the automatic detection of clustered microcalcifications (Honorable Mention Poster Award)

Science.gov (United States)

Wei, Liyang; Yang, Yongyi; Nishikawa, Robert M.

2005-04-01

Microcalcification (MC) clusters in mammograms can be important early signs of breast cancer in women. Accurate detection of MC clusters is an important but challenging problem. In this paper, we propose the use of a recently developed machine learning technique -- relevance vector machine (RVM) -- for automatic detection of MCs in digitized mammograms. RVM is based on Bayesian estimation theory, and as a feature it can yield a decision function that depends on only a very small number of so-called relevance vectors. We formulate MC detection as a supervised-learning problem, and use RVM to classify if an MC object is present or not at each location in a mammogram image. MC clusters are then identified by grouping the detected MC objects. The proposed method is tested using a database of 141 clinical mammograms, and compared with a support vector machine (SVM) classifier which we developed previously. The detection performance is evaluated using the free-response receiver operating characteristic (FROC) curves. It is demonstrated that the RVM classifier matches closely with the SVM classifier in detection performance, and does so with a much sparser kernel representation than the SVM classifier. Consequently, the RVM classifier greatly reduces the computational complexity, making it more suitable for real-time processing of MC clusters in mammograms.

Sampling methods and non-destructive examination techniques for large radioactive waste packages

International Nuclear Information System (INIS)

Green, T.H.; Smith, D.L.; Burgoyne, K.E.; Maxwell, D.J.; Norris, G.H.; Billington, D.M.; Pipe, R.G.; Smith, J.E.; Inman, C.M.

1992-01-01

Progress is reported on work undertaken to evaluate quality checking methods for radioactive wastes. A sampling rig was designed, fabricated and used to develop techniques for the destructive sampling of cemented simulant waste using remotely operated equipment. An engineered system for the containment of cooling water was designed and manufactured and successfully demonstrated with the drum and coring equipment mounted in both vertical and horizontal orientations. The preferred in-cell orientation was found to be with the drum and coring machinery mounted in a horizontal position. Small powdered samples can be taken from cemented homogeneous waste cores using a hollow drill/vacuum section technique with the preferred subsampling technique being to discard the outer 10 mm layer to obtain a representative sample of the cement core. Cement blends can be dissolved using fusion techniques and the resulting solutions are stable to gelling for periods in excess of one year. Although hydrochloric acid and nitric acid are promising solvents for dissolution of cement blends, the resultant solutions tend to form silicic acid gels. An estimate of the beta-emitter content of cemented waste packages can be obtained by a combination of non-destructive and destructive techniques. The errors will probably be in excess of +/-60 % at the 95 % confidence level. Real-time X-ray video-imaging techniques have been used to analyse drums of uncompressed, hand-compressed, in-drum compacted and high-force compacted (i.e. supercompacted) simulant waste. The results have confirmed the applicability of this technique for NDT of low-level waste. 8 refs., 12 figs., 3 tabs

Tune Your Brown Clustering, Please

DEFF Research Database (Denmark)

Derczynski, Leon; Chester, Sean; Bøgh, Kenneth Sejdenfaden

2015-01-01

Brown clustering, an unsupervised hierarchical clustering technique based on ngram mutual information, has proven useful in many NLP applications. However, most uses of Brown clustering employ the same default configuration; the appropriateness of this configuration has gone predominantly...

Some statistical properties of gene expression clustering for array data

DEFF Research Database (Denmark)

Abreu, G C G; Pinheiro, A; Drummond, R D

2010-01-01

DNA array data without a corresponding statistical error measure. We propose an easy-to-implement and simple-to-use technique that uses bootstrap re-sampling to evaluate the statistical error of the nodes provided by SOM-based clustering. Comparisons between SOM and parametric clustering are presented...... for simulated as well as for two real data sets. We also implement a bootstrap-based pre-processing procedure for SOM, that improves the false discovery ratio of differentially expressed genes. Code in Matlab is freely available, as well as some supplementary material, at the following address: https...

The spatial evaluation of neighborhood clusters of birth defects

Energy Technology Data Exchange (ETDEWEB)

Frisch, J.D.

1990-04-16

Spatial statistics have recently been applied in epidemiology to evaluate clusters of cancer and birth defects. Their use requires a comparison population, drawn from the population at risk for disease, that may not always be readily available. In this dissertation the plausibility of using data on all birth defects, available from birth defects registries, as a surrogate for the spatial distribution of all live births in the analysis of clusters is assessed. Three spatial statistics that have been applied in epidemiologic investigations of clusters, nearest neighbor distance, average interpoint distance, and average distance to a fixed point, were evaluated by computer simulation for their properties in a unit square, and in a zip code region. Comparison of spatial distributions of live births and birth defects was performed by drawing samples of live births and birth defects from Santa Clara County, determining the street address at birth, geocoding this address and evaluating the resultant maps using various statistical techniques. The proposed method was then demonstrated on a previously confirmed cluster of oral cleft cases. All live births for the neighborhood were geocoded, as were all birth defects. Evaluation of this cluster using the nearest neighbor and average interpoint distance statistics was performed using randomization techniques with both the live births population and the birth defect population as comparison groups. 113 refs., 36 figs., 16 tabs.

A Comparison of Soil-Water Sampling Techniques

Science.gov (United States)

Tindall, J. A.; Figueroa-Johnson, M.; Friedel, M. J.

2007-12-01

The representativeness of soil pore water extracted by suction lysimeters in ground-water monitoring studies is a problem that often confounds interpretation of measured data. Current soil water sampling techniques cannot identify the soil volume from which a pore water sample is extracted, neither macroscopic, microscopic, or preferential flowpath. This research was undertaken to compare values of extracted suction lysimeters samples from intact soil cores with samples obtained by the direct extraction methods to determine what portion of soil pore water is sampled by each method. Intact soil cores (30 centimeter (cm) diameter by 40 cm height) were extracted from two different sites - a sandy soil near Altamonte Springs, Florida and a clayey soil near Centralia in Boone County, Missouri. Isotopically labeled water (O18? - analyzed by mass spectrometry) and bromide concentrations (KBr- - measured using ion chromatography) from water samples taken by suction lysimeters was compared with samples obtained by direct extraction methods of centrifugation and azeotropic distillation. Water samples collected by direct extraction were about 0.25 ? more negative (depleted) than that collected by suction lysimeter values from a sandy soil and about 2-7 ? more negative from a well structured clayey soil. Results indicate that the majority of soil water in well-structured soil is strongly bound to soil grain surfaces and is not easily sampled by suction lysimeters. In cases where a sufficient volume of water has passed through the soil profile and displaced previous pore water, suction lysimeters will collect a representative sample of soil pore water from the sampled depth interval. It is suggested that for stable isotope studies monitoring precipitation and soil water, suction lysimeter should be installed at shallow depths (10 cm). Samples should also be coordinated with precipitation events. The data also indicate that each extraction method be use to sample a different

Can groundwater sampling techniques used in monitoring wells influence methane concentrations and isotopes?

Science.gov (United States)

Rivard, Christine; Bordeleau, Geneviève; Lavoie, Denis; Lefebvre, René; Malet, Xavier

2018-03-06

Methane concentrations and isotopic composition in groundwater are the focus of a growing number of studies. However, concerns are often expressed regarding the integrity of samples, as methane is very volatile and may partially exsolve during sample lifting in the well and transfer to sampling containers. While issues concerning bottle-filling techniques have already been documented, this paper documents a comparison of methane concentration and isotopic composition obtained with three devices commonly used to retrieve water samples from dedicated observation wells. This work lies within the framework of a larger project carried out in the Saint-Édouard area (southern Québec, Canada), whose objective was to assess the risk to shallow groundwater quality related to potential shale gas exploitation. The selected sampling devices, which were tested on ten wells during three sampling campaigns, consist of an impeller pump, a bladder pump, and disposable sampling bags (HydraSleeve). The sampling bags were used both before and after pumping, to verify the appropriateness of a no-purge approach, compared to the low-flow approach involving pumping until stabilization of field physicochemical parameters. Results show that methane concentrations obtained with the selected sampling techniques are usually similar and that there is no systematic bias related to a specific technique. Nonetheless, concentrations can sometimes vary quite significantly (up to 3.5 times) for a given well and sampling event. Methane isotopic composition obtained with all sampling techniques is very similar, except in some cases where sampling bags were used before pumping (no-purge approach), in wells where multiple groundwater sources enter the borehole.

Cognitive Clusters in Specific Learning Disorder.

Science.gov (United States)

Poletti, Michele; Carretta, Elisa; Bonvicini, Laura; Giorgi-Rossi, Paolo

The heterogeneity among children with learning disabilities still represents a barrier and a challenge in their conceptualization. Although a dimensional approach has been gaining support, the categorical approach is still the most adopted, as in the recent fifth edition of the Diagnostic and Statistical Manual of Mental Disorders. The introduction of the single overarching diagnostic category of specific learning disorder (SLD) could underemphasize interindividual clinical differences regarding intracategory cognitive functioning and learning proficiency, according to current models of multiple cognitive deficits at the basis of neurodevelopmental disorders. The characterization of specific cognitive profiles associated with an already manifest SLD could help identify possible early cognitive markers of SLD risk and distinct trajectories of atypical cognitive development leading to SLD. In this perspective, we applied a cluster analysis to identify groups of children with a Diagnostic and Statistical Manual-based diagnosis of SLD with similar cognitive profiles and to describe the association between clusters and SLD subtypes. A sample of 205 children with a diagnosis of SLD were enrolled. Cluster analyses (agglomerative hierarchical and nonhierarchical iterative clustering technique) were used successively on 10 core subtests of the Wechsler Intelligence Scale for Children-Fourth Edition. The 4-cluster solution was adopted, and external validation found differences in terms of SLD subtype frequencies and learning proficiency among clusters. Clinical implications of these findings are discussed, tracing directions for further studies.

Clustervision: Visual Supervision of Unsupervised Clustering.

Science.gov (United States)

Kwon, Bum Chul; Eysenbach, Ben; Verma, Janu; Ng, Kenney; De Filippi, Christopher; Stewart, Walter F; Perer, Adam

2018-01-01

Clustering, the process of grouping together similar items into distinct partitions, is a common type of unsupervised machine learning that can be useful for summarizing and aggregating complex multi-dimensional data. However, data can be clustered in many ways, and there exist a large body of algorithms designed to reveal different patterns. While having access to a wide variety of algorithms is helpful, in practice, it is quite difficult for data scientists to choose and parameterize algorithms to get the clustering results relevant for their dataset and analytical tasks. To alleviate this problem, we built Clustervision, a visual analytics tool that helps ensure data scientists find the right clustering among the large amount of techniques and parameters available. Our system clusters data using a variety of clustering techniques and parameters and then ranks clustering results utilizing five quality metrics. In addition, users can guide the system to produce more relevant results by providing task-relevant constraints on the data. Our visual user interface allows users to find high quality clustering results, explore the clusters using several coordinated visualization techniques, and select the cluster result that best suits their task. We demonstrate this novel approach using a case study with a team of researchers in the medical domain and showcase that our system empowers users to choose an effective representation of their complex data.

Weak-Lensing Mass Calibration of the Atacama Cosmology Telescope Equatorial Sunyaev-Zeldovich Cluster Sample with the Canada-France-Hawaii Telescope Stripe 82 Survey

Science.gov (United States)

Battaglia, N.; Leauthaud, A.; Miyatake, H.; Hasseleld, M.; Gralla, M. B.; Allison, R.; Bond, J. R.; Calabrese, E.; Crichton, D.; Devlin, M. J.;

Development of environmental sample analysis techniques for safeguards

International Nuclear Information System (INIS)

Magara, Masaaki; Hanzawa, Yukiko; Esaka, Fumitaka

1999-01-01

JAERI has been developing environmental sample analysis techniques for safeguards and preparing a clean chemistry laboratory with clean rooms. Methods to be developed are a bulk analysis and a particle analysis. In the bulk analysis, Inductively-Coupled Plasma Mass Spectrometer or Thermal Ionization Mass Spectrometer are used to measure nuclear materials after chemical treatment of sample. In the particle analysis, Electron Probe Micro Analyzer and Secondary Ion Mass Spectrometer are used for elemental analysis and isotopic analysis, respectively. The design of the clean chemistry laboratory has been carried out and construction will be completed by the end of March, 2001. (author)

THE GEMINI/HST CLUSTER PROJECT: STRUCTURAL AND PHOTOMETRIC PROPERTIES OF GALAXIES IN THREE z = 0.28-0.89 CLUSTERS

International Nuclear Information System (INIS)

Chiboucas, Kristin; Joergensen, Inger; Barr, Jordi; Collobert, Maela; Davies, Roger; Flint, Kathleen

2009-01-01

We present the data processing and analysis techniques we are using to determine the structural and photometric properties of galaxies in our Gemini/HST Galaxy Cluster Project sample. The goal of this study is to understand cluster galaxy evolution in terms of scaling relations and structural properties of cluster galaxies at redshifts 0.15 1/4 law and Sersic function two-dimensional surface brightness profiles to each of the galaxies in our sample. Using simulated galaxies, we test how the assumed profile affects the derived parameters and how the uncertainties affect our Fundamental Plane results. We find that while fitting galaxies that have Sersic index n 1/4 law profiles systematically overestimates the galaxy radius and flux, the combination of profile parameters that enter the Fundamental Plane has uncertainties that are small. Average systematic offsets and associated random uncertainties in magnitude and log r e for n>2 galaxies fitted with r 1/4 law profiles are -0.1 ± 0.3 and 0.1 ± 0.2, respectively. The combination of effective radius and surface brightness, log r e - βlog (I) e , that enters the Fundamental Plane produces offsets smaller than -0.02 ± 0.10. This systematic error is insignificant and independent of galaxy magnitude or size. A catalog of photometry and surface brightness profile parameters is presented for three of the clusters in our sample, RX J0142.0+2131, RX J0152.7-1357, and RX J1226.9+3332 at redshifts 0.28, 0.83, and 0.89, respectively.

Spectroscopic characterization of galaxy clusters in RCS-1: spectroscopic confirmation, redshift accuracy, and dynamical mass-richness relation

Science.gov (United States)

Gilbank, David G.; Barrientos, L. Felipe; Ellingson, Erica; Blindert, Kris; Yee, H. K. C.; Anguita, T.; Gladders, M. D.; Hall, P. B.; Hertling, G.; Infante, L.; Yan, R.; Carrasco, M.; Garcia-Vergara, Cristina; Dawson, K. S.; Lidman, C.; Morokuma, T.

2018-05-01

We present follow-up spectroscopic observations of galaxy clusters from the first Red-sequence Cluster Survey (RCS-1). This work focuses on two samples, a lower redshift sample of ˜30 clusters ranging in redshift from z ˜ 0.2-0.6 observed with multiobject spectroscopy (MOS) on 4-6.5-m class telescopes and a z ˜ 1 sample of ˜10 clusters 8-m class telescope observations. We examine the detection efficiency and redshift accuracy of the now widely used red-sequence technique for selecting clusters via overdensities of red-sequence galaxies. Using both these data and extended samples including previously published RCS-1 spectroscopy and spectroscopic redshifts from SDSS, we find that the red-sequence redshift using simple two-filter cluster photometric redshifts is accurate to σz ≈ 0.035(1 + z) in RCS-1. This accuracy can potentially be improved with better survey photometric calibration. For the lower redshift sample, ˜5 per cent of clusters show some (minor) contamination from secondary systems with the same red-sequence intruding into the measurement aperture of the original cluster. At z ˜ 1, the rate rises to ˜20 per cent. Approximately ten per cent of projections are expected to be serious, where the two components contribute significant numbers of their red-sequence galaxies to another cluster. Finally, we present a preliminary study of the mass-richness calibration using velocity dispersions to probe the dynamical masses of the clusters. We find a relation broadly consistent with that seen in the local universe from the WINGS sample at z ˜ 0.05.

Clustering analysis

International Nuclear Information System (INIS)

Romli

1997-01-01

Cluster analysis is the name of group of multivariate techniques whose principal purpose is to distinguish similar entities from the characteristics they process.To study this analysis, there are several algorithms that can be used. Therefore, this topic focuses to discuss the algorithms, such as, similarity measures, and hierarchical clustering which includes single linkage, complete linkage and average linkage method. also, non-hierarchical clustering method, which is popular name K -mean method ' will be discussed. Finally, this paper will be described the advantages and disadvantages of every methods

Cluster analysis

CERN Document Server

Everitt, Brian S; Leese, Morven; Stahl, Daniel

2011-01-01

Cluster analysis comprises a range of methods for classifying multivariate data into subgroups. By organizing multivariate data into such subgroups, clustering can help reveal the characteristics of any structure or patterns present. These techniques have proven useful in a wide range of areas such as medicine, psychology, market research and bioinformatics.This fifth edition of the highly successful Cluster Analysis includes coverage of the latest developments in the field and a new chapter dealing with finite mixture models for structured data.Real life examples are used throughout to demons

Standardization of proton-induced x-ray emission technique for analysis of thick samples

Science.gov (United States)

Ali, Shad; Zeb, Johar; Ahad, Abdul; Ahmad, Ishfaq; Haneef, M.; Akbar, Jehan

2015-09-01

This paper describes the standardization of the proton-induced x-ray emission (PIXE) technique for finding the elemental composition of thick samples. For the standardization, three different samples of standard reference materials (SRMs) were analyzed using this technique and the data were compared with the already known data of these certified SRMs. These samples were selected in order to cover the maximum range of elements in the periodic table. Each sample was irradiated for three different values of collected beam charges at three different times. A proton beam of 2.57 MeV obtained using 5UDH-II Pelletron accelerator was used for excitation of x-rays from the sample. The acquired experimental data were analyzed using the GUPIXWIN software. The results show that the SRM data and the data obtained using the PIXE technique are in good agreement.

BioCluster: Tool for Identification and Clustering of Enterobacteriaceae Based on Biochemical Data

Directory of Open Access Journals (Sweden)

Ahmed Abdullah

2015-06-01

Full Text Available Presumptive identification of different Enterobacteriaceae species is routinely achieved based on biochemical properties. Traditional practice includes manual comparison of each biochemical property of the unknown sample with known reference samples and inference of its identity based on the maximum similarity pattern with the known samples. This process is labor-intensive, time-consuming, error-prone, and subjective. Therefore, automation of sorting and similarity in calculation would be advantageous. Here we present a MATLAB-based graphical user interface (GUI tool named BioCluster. This tool was designed for automated clustering and identification of Enterobacteriaceae based on biochemical test results. In this tool, we used two types of algorithms, i.e., traditional hierarchical clustering (HC and the Improved Hierarchical Clustering (IHC, a modified algorithm that was developed specifically for the clustering and identification of Enterobacteriaceae species. IHC takes into account the variability in result of 1–47 biochemical tests within this Enterobacteriaceae family. This tool also provides different options to optimize the clustering in a user-friendly way. Using computer-generated synthetic data and some real data, we have demonstrated that BioCluster has high accuracy in clustering and identifying enterobacterial species based on biochemical test data. This tool can be freely downloaded at http://microbialgen.du.ac.bd/biocluster/.

The Frequency of Binary Stars in the Globular Cluster M71

Science.gov (United States)

Barden, S. C.; Armandroff, T. E.; Pryor, C. P.

1994-12-01

The frequency of binary stars is a fundamental property of a stellar population. A comparison of the frequency of binaries in globular clusters with those in the field halo and disk populations tests the similarity of star formation in those environments. Binary stars in globular clusters also act as an energy source which ``heats" the cluster through super-elastic encounters with other stars and binaries. Such encounters can not only profoundly affect the dynamical evolution of the cluster, they can disrupt the widely separated binaries and catalyze the formation of exotic objects such as blue stragglers, x-ray binaries, and milli-second pulsars. We have used the KPNO 4-m and the multi-fiber instruments Nessie and Hydra to measure radial velocities at 4 epochs over two years for a sample of 126 stars in the globular cluster M71. Velocity errors are under 1 km s(-1) for the brighter stars and under 2 km s(-1) for the majority of our data set. These velocities will be valuable for studying the kinematics of M71, but here we focus on searching for binaries. The faintest stars are at V=17, or just above the main sequence turnoff. Our sample is thus deeper than any published globular cluster binary search utilizing spectroscopic techniques. By observing smaller stars, we double the number of decades of binary periods sampled compared to previous studies and come within a factor of 4 of the shortest possible periods for turnoff stars. This wider period window has produced the largest known sample of binaries in a globular cluster. Four stars show velocity ranges larger than 20 km s(-1) , nine have ranges larger than 10 km s(-1) , and others are clearly variable. We will compare the radial distribution of these stars to that predicted by theory and derive the main-sequence binary fraction.

Review of sample preparation techniques for the analysis of pesticide residues in soil.

Science.gov (United States)

Tadeo, José L; Pérez, Rosa Ana; Albero, Beatriz; García-Valcárcel, Ana I; Sánchez-Brunete, Consuelo

2012-01-01

This paper reviews the sample preparation techniques used for the analysis of pesticides in soil. The present status and recent advances made during the last 5 years in these methods are discussed. The analysis of pesticide residues in soil requires the extraction of analytes from this matrix, followed by a cleanup procedure, when necessary, prior to their instrumental determination. The optimization of sample preparation is a very important part of the method development that can reduce the analysis time, the amount of solvent, and the size of samples. This review considers all aspects of sample preparation, including extraction and cleanup. Classical extraction techniques, such as shaking, Soxhlet, and ultrasonic-assisted extraction, and modern techniques like pressurized liquid extraction, microwave-assisted extraction, solid-phase microextraction and QuEChERS (Quick, Easy, Cheap, Effective, Rugged, and Safe) are reviewed. The different cleanup strategies applied for the purification of soil extracts are also discussed. In addition, the application of these techniques to environmental studies is considered.

Environmental data processing by clustering methods for energy forecast and planning

Energy Technology Data Exchange (ETDEWEB)

Di Piazza, Annalisa [Dipartimento di Ingegneria Idraulica e Applicazioni Ambientali (DIIAA), viale delle Scienze, Universita degli Studi di Palermo, 90128 Palermo (Italy); Di Piazza, Maria Carmela; Ragusa, Antonella; Vitale, Gianpaolo [Consiglio Nazionale delle Ricerche Istituto di Studi sui Sistemi Intelligenti per l' Automazione (ISSIA - CNR), sezione di Palermo, Via Dante, 12, 90141 Palermo (Italy)

2011-03-15

This paper presents a statistical approach based on the k-means clustering technique to manage environmental sampled data to evaluate and to forecast of the energy deliverable by different renewable sources in a given site. In particular, wind speed and solar irradiance sampled data are studied in association to the energy capability of a wind generator and a photovoltaic (PV) plant, respectively. The proposed method allows the sub-sets of useful data, describing the energy capability of a site, to be extracted from a set of experimental observations belonging the considered site. The data collection is performed in Sicily, in the south of Italy, as case study. As far as the wind generation is concerned, a suitable generator, matching the wind profile of the studied sites, has been selected for the evaluation of the producible energy. With respect to the photovoltaic generation, the irradiance data have been taken from the acquisition system of an actual installation. It is demonstrated, in both cases, that the use of the k-means clustering method allows data that do not contribute to the produced energy to be grouped into a cluster, moreover it simplifies the problem of the energy assessment since it permits to obtain the desired information on energy capability by managing a reduced amount of experimental samples. In the studied cases, the proposed method permitted a reduction of the 50% of the data with a maximum discrepancy of 10% in energy estimation compared to the classical statistical approach. Therefore, the adopted k-means clustering technique represents an useful tool for an appropriate and less demanding energy forecast and planning in distributed generation systems. (author)

Laboratory techniques for safe encapsulation of α-emitting powder samples

International Nuclear Information System (INIS)

Chamberlain, H.E.; Pottinger, J.S.

1984-01-01

Plutonium oxide powder samples can be encapsulated in thin plastic film to prevent spread of contamination in counting and X-ray diffraction equipment. The film has to be thin enough to transmit X-rays and α-particles. Techniques are described for the wrapping process and the precautions necessary to keep the sample processing line free of significant contamination. (author)

Minimizing Broadcast Expenses in Clustered Ad-hoc Networks

Directory of Open Access Journals (Sweden)

S. Zeeshan Hussain

2018-01-01

Full Text Available One way to minimize the broadcast expenses of routing protocols is to cluster the network. In clustered ad-hoc networks, all resources can be managed easily by resolving scalability issues. However, blind query broadcast is a major issue that leads to the broadcast storm problem in clustered ad-hoc networks. This query broadcast is done to carry out the route-search task that leads to the unnecessary propagation of route-query even after route has been found. Hence, this query propagation poses the problem of congestion in the network. In particular this motivates us to propose a query-control technique in such networks which works based on broadcast repealing. A huge amount of work has been devoted to propose the query control broadcasting techniques. However, such techniques used in traditional broadcasting mechanisms need to be properly extended for use in the cluster based routing architecture. In this paper, query-control technique is proposed for cluster based routing technique to reduce the broadcast expenses. Finally, we report some experiments which compare the proposed technique to other commonly used techniques including standard one-class AODV that follows TTL-sequence based broadcasting technique.

BRIGHTEST CLUSTER GALAXIES AND CORE GAS DENSITY IN REXCESS CLUSTERS

International Nuclear Information System (INIS)

Haarsma, Deborah B.; Leisman, Luke; Donahue, Megan; Bruch, Seth; Voit, G. Mark; Boehringer, Hans; Pratt, Gabriel W.; Pierini, Daniele; Croston, Judith H.; Arnaud, Monique

2010-01-01

We investigate the relationship between brightest cluster galaxies (BCGs) and their host clusters using a sample of nearby galaxy clusters from the Representative XMM-Newton Cluster Structure Survey. The sample was imaged with the Southern Observatory for Astrophysical Research in R band to investigate the mass of the old stellar population. Using a metric radius of 12 h -1 kpc, we found that the BCG luminosity depends weakly on overall cluster mass as L BCG ∝ M 0.18±0.07 cl , consistent with previous work. We found that 90% of the BCGs are located within 0.035 r 500 of the peak of the X-ray emission, including all of the cool core (CC) clusters. We also found an unexpected correlation between the BCG metric luminosity and the core gas density for non-cool-core (non-CC) clusters, following a power law of n e ∝ L 2.7±0.4 BCG (where n e is measured at 0.008 r 500 ). The correlation is not easily explained by star formation (which is weak in non-CC clusters) or overall cluster mass (which is not correlated with core gas density). The trend persists even when the BCG is not located near the peak of the X-ray emission, so proximity is not necessary. We suggest that, for non-CC clusters, this correlation implies that the same process that sets the central entropy of the cluster gas also determines the central stellar density of the BCG, and that this underlying physical process is likely to be mergers.

Comparison of cluster and principal component analysis techniques to derive dietary patterns in Irish adults.

Science.gov (United States)

Hearty, Aine P; Gibney, Michael J

2009-02-01

The aims of the present study were to examine and compare dietary patterns in adults using cluster and factor analyses and to examine the format of the dietary variables on the pattern solutions (i.e. expressed as grams/day (g/d) of each food group or as the percentage contribution to total energy intake). Food intake data were derived from the North/South Ireland Food Consumption Survey 1997-9, which was a randomised cross-sectional study of 7 d recorded food and nutrient intakes of a representative sample of 1379 Irish adults aged 18-64 years. Cluster analysis was performed using the k-means algorithm and principal component analysis (PCA) was used to extract dietary factors. Food data were reduced to thirty-three food groups. For cluster analysis, the most suitable format of the food-group variable was found to be the percentage contribution to energy intake, which produced six clusters: 'Traditional Irish'; 'Continental'; 'Unhealthy foods'; 'Light-meal foods & low-fat milk'; 'Healthy foods'; 'Wholemeal bread & desserts'. For PCA, food groups in the format of g/d were found to be the most suitable format, and this revealed four dietary patterns: 'Unhealthy foods & high alcohol'; 'Traditional Irish'; 'Healthy foods'; 'Sweet convenience foods & low alcohol'. In summary, cluster and PCA identified similar dietary patterns when presented with the same dataset. However, the two dietary pattern methods required a different format of the food-group variable, and the most appropriate format of the input variable should be considered in future studies.

COMPARISON AND EVALUATION OF CLUSTER BASED IMAGE SEGMENTATION TECHNIQUES

OpenAIRE

Hetangi D. Mehta*, Daxa Vekariya, Pratixa Badelia

2017-01-01

Image segmentation is the classification of an image into different groups. Numerous algorithms using different approaches have been proposed for image segmentation. A major challenge in segmentation evaluation comes from the fundamental conflict between generality and objectivity. A review is done on different types of clustering methods used for image segmentation. Also a methodology is proposed to classify and quantify different clustering algorithms based on their consistency in different...

The relative impact of baryons and cluster shape on weak lensing mass estimates of galaxy clusters

Science.gov (United States)

Lee, B. E.; Le Brun, A. M. C.; Haq, M. E.; Deering, N. J.; King, L. J.; Applegate, D.; McCarthy, I. G.

2018-05-01

Weak gravitational lensing depends on the integrated mass along the line of sight. Baryons contribute to the mass distribution of galaxy clusters and the resulting mass estimates from lensing analysis. We use the cosmo-OWLS suite of hydrodynamic simulations to investigate the impact of baryonic processes on the bias and scatter of weak lensing mass estimates of clusters. These estimates are obtained by fitting NFW profiles to mock data using MCMC techniques. In particular, we examine the difference in estimates between dark matter-only runs and those including various prescriptions for baryonic physics. We find no significant difference in the mass bias when baryonic physics is included, though the overall mass estimates are suppressed when feedback from AGN is included. For lowest-mass systems for which a reliable mass can be obtained (M200 ≈ 2 × 1014M⊙), we find a bias of ≈-10 per cent. The magnitude of the bias tends to decrease for higher mass clusters, consistent with no bias for the most massive clusters which have masses comparable to those found in the CLASH and HFF samples. For the lowest mass clusters, the mass bias is particularly sensitive to the fit radii and the limits placed on the concentration prior, rendering reliable mass estimates difficult. The scatter in mass estimates between the dark matter-only and the various baryonic runs is less than between different projections of individual clusters, highlighting the importance of triaxiality.

Sampling phased array a new technique for signal processing and ultrasonic imaging

OpenAIRE

Bulavinov, A.; Joneit, D.; Kröning, M.; Bernus, L.; Dalichow, M.H.; Reddy, K.M.

2006-01-01

Different signal processing and image reconstruction techniques are applied in ultrasonic non-destructive material evaluation. In recent years, rapid development in the fields of microelectronics and computer engineering lead to wide application of phased array systems. A new phased array technique, called "Sampling Phased Array" has been developed in Fraunhofer Institute for non-destructive testing. It realizes unique approach of measurement and processing of ultrasonic signals. The sampling...

The role of graphene-based sorbents in modern sample preparation techniques.

Science.gov (United States)

de Toffoli, Ana Lúcia; Maciel, Edvaldo Vasconcelos Soares; Fumes, Bruno Henrique; Lanças, Fernando Mauro

2018-01-01

The application of graphene-based sorbents in sample preparation techniques has increased significantly since 2011. These materials have good physicochemical properties to be used as sorbent and have shown excellent results in different sample preparation techniques. Graphene and its precursor graphene oxide have been considered to be good candidates to improve the extraction and concentration of different classes of target compounds (e.g., parabens, polycyclic aromatic hydrocarbon, pyrethroids, triazines, and so on) present in complex matrices. Its applications have been employed during the analysis of different matrices (e.g., environmental, biological and food). In this review, we highlight the most important characteristics of graphene-based material, their properties, synthesis routes, and the most important applications in both off-line and on-line sample preparation techniques. The discussion of the off-line approaches includes methods derived from conventional solid-phase extraction focusing on the miniaturized magnetic and dispersive modes. The modes of microextraction techniques called stir bar sorptive extraction, solid phase microextraction, and microextraction by packed sorbent are discussed. The on-line approaches focus on the use of graphene-based material mainly in on-line solid phase extraction, its variation called in-tube solid-phase microextraction, and on-line microdialysis systems. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Techniques of sample attack used in soil and mineral analysis. Phase I

International Nuclear Information System (INIS)

Chiu, N.W.; Dean, J.R.; Sill, C.W.

1984-07-01

Several techniques of sample attack for the determination of radioisotopes are reviewed. These techniques include: 1) digestion with nitric or hydrochloric acid in Parr digestion bomb, 2) digestion with a mixture of nitric and hydrochloric acids, 3) digestion with a mixture of hydrofluoric, nitric and perchloric acids, and 4) fusion with sodium carbonate, potassium fluoride or alkali pyrosulfates. The effectiveness of these techniques to decompose various soils and minerals containing radioisotopes such as lead-210 uranium, thorium and radium-226 are discussed. The combined procedure of potassium fluoride fusion followed by alkali pyrosulfate fusion is recommended for radium-226, uranium and thorium analysis. This technique guarantees the complete dissolution of samples containing refractory materials such as silica, silicates, carbides, oxides and sulfates. For the lead-210 analysis, the procedure of digestion with a mixture of hydrofluoric, nitric and perchloric acids followed by fusion with alkali pyrosulfate is recommended. These two procedures are detailed. Schemes for the sequential separation of the radioisotopes from a dissolved sample solution are outlined. Procedures for radiochemical analysis are suggested

On the Analysis of Case-Control Studies in Cluster-correlated Data Settings.

Science.gov (United States)

Haneuse, Sebastien; Rivera-Rodriguez, Claudia

2018-01-01

In resource-limited settings, long-term evaluation of national antiretroviral treatment (ART) programs often relies on aggregated data, the analysis of which may be subject to ecological bias. As researchers and policy makers consider evaluating individual-level outcomes such as treatment adherence or mortality, the well-known case-control design is appealing in that it provides efficiency gains over random sampling. In the context that motivates this article, valid estimation and inference requires acknowledging any clustering, although, to our knowledge, no statistical methods have been published for the analysis of case-control data for which the underlying population exhibits clustering. Furthermore, in the specific context of an ongoing collaboration in Malawi, rather than performing case-control sampling across all clinics, case-control sampling within clinics has been suggested as a more practical strategy. To our knowledge, although similar outcome-dependent sampling schemes have been described in the literature, a case-control design specific to correlated data settings is new. In this article, we describe this design, discuss balanced versus unbalanced sampling techniques, and provide a general approach to analyzing case-control studies in cluster-correlated settings based on inverse probability-weighted generalized estimating equations. Inference is based on a robust sandwich estimator with correlation parameters estimated to ensure appropriate accounting of the outcome-dependent sampling scheme. We conduct comprehensive simulations, based in part on real data on a sample of N = 78,155 program registrants in Malawi between 2005 and 2007, to evaluate small-sample operating characteristics and potential trade-offs associated with standard case-control sampling or when case-control sampling is performed within clusters.

Assessment of Natural Radioactivity in TENORM Samples Using Different Techniques

International Nuclear Information System (INIS)

Salman, Kh.A.; Shahein, A.Y.

2009-01-01

In petroleum oil industries, technologically-enhanced, naturally occurring radioactive materials are produced. The presence of TENORM constitutes a significant radiological human health hazard. In the present work, liquid scintillation counting technique was used to determine both 222 Rn and 226 Ra concentrations in TENORM samples, by measuring 222 Rn concentrations in the sample at different intervals of time after preparation. The radiation doses from the TENORM samples were estimated using thermoluminenscent detector (TLD-4000). The estimated radiation doses were found to be proportional to both the measured radiation doses in site and natural activity concentration in the samples that measured with LSC

Membership determination of open clusters based on a spectral clustering method

Science.gov (United States)

Gao, Xin-Hua

2018-06-01

We present a spectral clustering (SC) method aimed at segregating reliable members of open clusters in multi-dimensional space. The SC method is a non-parametric clustering technique that performs cluster division using eigenvectors of the similarity matrix; no prior knowledge of the clusters is required. This method is more flexible in dealing with multi-dimensional data compared to other methods of membership determination. We use this method to segregate the cluster members of five open clusters (Hyades, Coma Ber, Pleiades, Praesepe, and NGC 188) in five-dimensional space; fairly clean cluster members are obtained. We find that the SC method can capture a small number of cluster members (weak signal) from a large number of field stars (heavy noise). Based on these cluster members, we compute the mean proper motions and distances for the Hyades, Coma Ber, Pleiades, and Praesepe clusters, and our results are in general quite consistent with the results derived by other authors. The test results indicate that the SC method is highly suitable for segregating cluster members of open clusters based on high-precision multi-dimensional astrometric data such as Gaia data.

Clusters of atoms and molecules theory, experiment, and clusters of atoms

CERN Document Server

1994-01-01

Clusters of Atoms and Molecules is devoted to theoretical concepts and experimental techniques important in the rapidly expanding field of cluster science. Cluster properties are dicussed for clusteres composed of alkali metals, semiconductors, transition metals, carbon, oxides and halides of alkali metals, rare gases, and neutral molecules. The book is composed of several well-integrated treatments all prepared by experts. Each contribution starts out as simple as possible and ends with the latest results so that the book can serve as a text for a course, an introduction into the field, or as a reference book for the expert.

Review of online coupling of sample preparation techniques with liquid chromatography.

Science.gov (United States)

Pan, Jialiang; Zhang, Chengjiang; Zhang, Zhuomin; Li, Gongke

2014-03-07

Sample preparation is still considered as the bottleneck of the whole analytical procedure, and efforts has been conducted towards the automation, improvement of sensitivity and accuracy, and low comsuption of organic solvents. Development of online sample preparation techniques (SP) coupled with liquid chromatography (LC) is a promising way to achieve these goals, which has attracted great attention. This article reviews the recent advances on the online SP-LC techniques. Various online SP techniques have been described and summarized, including solid-phase-based extraction, liquid-phase-based extraction assisted with membrane, microwave assisted extraction, ultrasonic assisted extraction, accelerated solvent extraction and supercritical fluids extraction. Specially, the coupling approaches of online SP-LC systems and the corresponding interfaces have been discussed and reviewed in detail, such as online injector, autosampler combined with transport unit, desorption chamber and column switching. Typical applications of the online SP-LC techniques have been summarized. Then the problems and expected trends in this field are attempted to be discussed and proposed in order to encourage the further development of online SP-LC techniques. Copyright © 2014 Elsevier B.V. All rights reserved.

Cleaning and Cleanliness Verification Techniques for Mars Returned Sample Handling

Science.gov (United States)

Mickelson, E. T.; Lindstrom, D. J.; Allton, J. H.; Hittle, J. D.

2002-01-01

Precision cleaning and cleanliness verification techniques are examined as a subset of a comprehensive contamination control strategy for a Mars sample return mission. Additional information is contained in the original extended abstract.

Chemisorption on size-selected metal clusters: activation barriers and chemical reactions for deuterium and aluminum cluster ions

International Nuclear Information System (INIS)

Jarrold, M.F.; Bower, J.E.

1988-01-01

The authors describe a new approach to investigating chemisorption on size-selected metal clusters. This approach involves investigating the collision-energy dependence of chemisorption using low-energy ion beam techniques. The method provides a direct measure of the activation barrier for chemisorption and in some cases an estimate of the desorption energy as well. They describe the application of this technique to chemisorption of deuterium on size-selected aluminum clusters. The activation barriers increase with cluster size (from a little over 1 eV for Al 10 + to around 2 eV for Al 27 + ) and show significant odd-even oscillations. The activation barriers for the clusters with an odd number of atoms are larger than those for the even-numbered clusters. In addition to chemisorption of deuterium onto the clusters, chemical reactions were observed, often resulting in cluster fragmentation. The main products observed were Al/sub n-1/D + , Al/sub n-2/ + , and Al + for clusters with n + and Al/sub n-1/D + for the larger clusters

Data clustering algorithms and applications

CERN Document Server

Aggarwal, Charu C

2013-01-01

Research on the problem of clustering tends to be fragmented across the pattern recognition, database, data mining, and machine learning communities. Addressing this problem in a unified way, Data Clustering: Algorithms and Applications provides complete coverage of the entire area of clustering, from basic methods to more refined and complex data clustering approaches. It pays special attention to recent issues in graphs, social networks, and other domains.The book focuses on three primary aspects of data clustering: Methods, describing key techniques commonly used for clustering, such as fea

Elemental analyses of goundwater: demonstrated advantage of low-flow sampling and trace-metal clean techniques over standard techniques

Science.gov (United States)

Creasey, C. L.; Flegal, A. R.

The combined use of both (1) low-flow purging and sampling and (2) trace-metal clean techniques provides more representative measurements of trace-element concentrations in groundwater than results derived with standard techniques. The use of low-flow purging and sampling provides relatively undisturbed groundwater samples that are more representative of in situ conditions, and the use of trace-element clean techniques limits the inadvertent introduction of contaminants during sampling, storage, and analysis. When these techniques are applied, resultant trace-element concentrations are likely to be markedly lower than results based on standard sampling techniques. In a comparison of data derived from contaminated and control groundwater wells at a site in California, USA, trace-element concentrations from this study were 2-1000 times lower than those determined by the conventional techniques used in sampling of the same wells prior to (5months) and subsequent to (1month) the collections for this study. Specifically, the cadmium and chromium concentrations derived using standard sampling techniques exceed the California Maximum Contaminant Levels (MCL), whereas in this investigation concentrations of both of those elements are substantially below their MCLs. Consequently, the combined use of low-flow and trace-metal clean techniques may preclude erroneous reports of trace-element contamination in groundwater. Résumé L'utilisation simultanée de la purge et de l'échantillonnage à faible débit et des techniques sans traces de métaux permet d'obtenir des mesures de concentrations en éléments en traces dans les eaux souterraines plus représentatives que les résultats fournis par les techniques classiques. L'utilisation de la purge et de l'échantillonnage à faible débit donne des échantillons d'eau souterraine relativement peu perturbés qui sont plus représentatifs des conditions in situ, et le recours aux techniques sans éléments en traces limite l

Characterization of Glutaredoxin Fe-S Cluster-Binding Interactions Using Circular Dichroism Spectroscopy.

Science.gov (United States)

Albetel, Angela-Nadia; Outten, Caryn E

2018-01-01

Monothiol glutaredoxins (Grxs) with a conserved Cys-Gly-Phe-Ser (CGFS) active site are iron-sulfur (Fe-S) cluster-binding proteins that interact with a variety of partner proteins and perform crucial roles in iron metabolism including Fe-S cluster transfer, Fe-S cluster repair, and iron signaling. Various analytical and spectroscopic methods are currently being used to monitor and characterize glutaredoxin Fe-S cluster-dependent interactions at the molecular level. The electronic, magnetic, and vibrational properties of the protein-bound Fe-S cluster provide a convenient handle to probe the structure, function, and coordination chemistry of Grx complexes. However, some limitations arise from sample preparation requirements, complexity of individual techniques, or the necessity for combining multiple methods in order to achieve a complete investigation. In this chapter, we focus on the use of UV-visible circular dichroism spectroscopy as a fast and simple initial approach for investigating glutaredoxin Fe-S cluster-dependent interactions. © 2018 Elsevier Inc. All rights reserved.

Normalization based K means Clustering Algorithm

OpenAIRE

Virmani, Deepali; Taneja, Shweta; Malhotra, Geetika

2015-01-01

K-means is an effective clustering technique used to separate similar data into groups based on initial centroids of clusters. In this paper, Normalization based K-means clustering algorithm(N-K means) is proposed. Proposed N-K means clustering algorithm applies normalization prior to clustering on the available data as well as the proposed approach calculates initial centroids based on weights. Experimental results prove the betterment of proposed N-K means clustering algorithm over existing...

Hierarchical modeling of cluster size in wildlife surveys

Science.gov (United States)

Royle, J. Andrew

2008-01-01

Clusters or groups of individuals are the fundamental unit of observation in many wildlife sampling problems, including aerial surveys of waterfowl, marine mammals, and ungulates. Explicit accounting of cluster size in models for estimating abundance is necessary because detection of individuals within clusters is not independent and detectability of clusters is likely to increase with cluster size. This induces a cluster size bias in which the average cluster size in the sample is larger than in the population at large. Thus, failure to account for the relationship between delectability and cluster size will tend to yield a positive bias in estimates of abundance or density. I describe a hierarchical modeling framework for accounting for cluster-size bias in animal sampling. The hierarchical model consists of models for the observation process conditional on the cluster size distribution and the cluster size distribution conditional on the total number of clusters. Optionally, a spatial model can be specified that describes variation in the total number of clusters per sample unit. Parameter estimation, model selection, and criticism may be carried out using conventional likelihood-based methods. An extension of the model is described for the situation where measurable covariates at the level of the sample unit are available. Several candidate models within the proposed class are evaluated for aerial survey data on mallard ducks (Anas platyrhynchos).

Cluster Analysis of the Yale Global Tic Severity Scale (YGTSS): Symptom Dimensions and Clinical Correlates in an Outpatient Youth Sample

OpenAIRE

Kircanski, Katharina; Woods, Douglas W.; Chang, Susanna W.; Ricketts, Emily J.; Piacentini, John C.

2010-01-01

Tic disorders are heterogeneous, with symptoms varying widely both within and across patients. Exploration of symptom clusters may aid in the identification of symptom dimensions of empirical and treatment import. This article presents the results of two studies investigating tic symptom clusters using a sample of 99 youth (M age = 10.7, 81% male, 77% Caucasian) diagnosed with a primary tic disorder (Tourette?s disorder or chronic tic disorder), across two university-based outpatient clinics ...

Transformation dynamics of Ni clusters into NiO rings under electron beam irradiation

Energy Technology Data Exchange (ETDEWEB)

Knez, Daniel, E-mail: daniel.knez@felmi-zfe.at [Institute of Electron Microscopy and Nanoanalysis, Graz University of Technology, Steyrergasse 17, 8010 Graz (Austria); Graz Centre for Electron Microscopy, Steyrergasse 17, 8010 Graz (Austria); Thaler, Philipp; Volk, Alexander [Institute of Experimental Physics, Graz University of Technology, Petersgasse 16, 8010 Graz (Austria); Kothleitner, Gerald [Institute of Electron Microscopy and Nanoanalysis, Graz University of Technology, Steyrergasse 17, 8010 Graz (Austria); Graz Centre for Electron Microscopy, Steyrergasse 17, 8010 Graz (Austria); Ernst, Wolfgang E. [Institute of Experimental Physics, Graz University of Technology, Petersgasse 16, 8010 Graz (Austria); Hofer, Ferdinand [Institute of Electron Microscopy and Nanoanalysis, Graz University of Technology, Steyrergasse 17, 8010 Graz (Austria); Graz Centre for Electron Microscopy, Steyrergasse 17, 8010 Graz (Austria)

2017-05-15

We report the transformation of nickel clusters into NiO rings by an electron beam induced nanoscale Kirkendall effect. High-purity nickel clusters consisting of a few thousand atoms have been used as precursors and were synthesized with the superfluid helium droplet technique. Aberration-corrected, analytical scanning transmission electron microscopy was applied to oxidise and simultaneously analyse the nanostructures. The transient dynamics of the oxidation could be documented by time lapse series using high-angle annular dark-field imaging and electron energy-loss spectroscopy. A two-step Cabrera-Mott oxidation mechanism was identified. It was found that water adsorbed adjacent to the clusters acts as oxygen source for the electron beam induced oxidation. The size-dependent oxidation rate was estimated by quantitative EELS measurements combined with molecular dynamics simulations. Our findings could serve to better control sample changes during examination in an electron microscope, and might provide a methodology to generate other metal oxide nanostructures. - Highlights: • Beam induced conversion of Ni clusters into crystalline NiO rings has been observed. • Ni clusters were grown with the superfluid He-droplet technique. • oxidizeSTEM was utilized to investigate and simultaneously oxidize these clusters. • Oxidation dynamics was captured in real-time. • Cluster sizes and the oxidation rate were estimated via EELS and molecular dynamics.

Random matrix improved subspace clustering

KAUST Repository

Couillet, Romain; Kammoun, Abla

2017-01-01

This article introduces a spectral method for statistical subspace clustering. The method is built upon standard kernel spectral clustering techniques, however carefully tuned by theoretical understanding arising from random matrix findings. We show

Guinier-Preston zones and gas bubbles clustering studied by dechanneling

International Nuclear Information System (INIS)

Desarmot, Georges.

1976-11-01

Dechanneling due to precipitation of heteroatoms in aluminium is studied theoretically and experimentally. Precipitation of copper atoms leads to Guinier-Preston zones (G.P.Z.) clustering. Helium, which is insoluble in aluminium, forms gas bubbles. An isotropic source of particles is used and channeling events only are considered. Transmission of channeled particles (channelons) through a sample is defined as the ratio between the channelon flux emerging from a sample containing defects (G.P.Z. or gaz bubbles in this survey) and the channelon flux emerging from the same sample without defects. Dechanneling by G.P.Z. clustering during isothermal ageing of Al-Cu alloys at room temperature is studied. The results are interpreted exclusively in terms of spinodal decomposition of the Al-Cu solid solution. A simple theory of dechanneling by bubbles containing a real gas is proposed. Applied to helium in aluminium, this theory explains the experimental results. Dechanneling proves to be a new and efficient technique for studying alloys [fr

THE STUDY OF HEAVY METAL FROM ENVIRONMENTAL SAMPLES BY ATOMIC TECHNIQUES

Directory of Open Access Journals (Sweden)

Ion V. POPESCU

2011-05-01

Full Text Available Using the Atomic Absorption Spectrometry (AAS and Energy Dispersive X-ray spectrometry (EDXRF techniques we analyzed the contents of heavy metals ( Cd, Cr, Ni, Pb, Ti, Sr, Co, Bi from eight wild mushrooms and soil substrate samples (48 samples of eight fungal species and 32 underlying soil samples, collected from ten forest sites of Dambovița County Romania. It was determined that the elements, especially heavy metals, in soil were characteristic of the acidic soils of the Romanian forest lands and are influenced by industrial pollution. Analytical possibilities of AAS and EDXRF analytical techniques have been compared and the heavy metal transfer from substrate to mushrooms has been studied. The coefficient of accumulation of essential and heavy metals has been calculated as well. Heavy metal contents of all analyzed mushrooms were generally higher than previously reported in literature.

Comparison between correlated sampling and the perturbation technique of MCNP5 for fixed-source problems

International Nuclear Information System (INIS)

He Tao; Su Bingjing

2011-01-01

Highlights: → The performance of the MCNP differential operator perturbation technique is compared with that of the MCNP correlated sampling method for three types of fixed-source problems. → In terms of precision, the MCNP perturbation technique outperforms correlated sampling for one type of problem but performs comparably with or even under-performs correlated sampling for the other two types of problems. → In terms of accuracy, the MCNP perturbation calculations may predict inaccurate results for some of the test problems. However, the accuracy can be improved if the midpoint correction technique is used. - Abstract: Correlated sampling and the differential operator perturbation technique are two methods that enable MCNP (Monte Carlo N-Particle) to simulate small response change between an original system and a perturbed system. In this work the performance of the MCNP differential operator perturbation technique is compared with that of the MCNP correlated sampling method for three types of fixed-source problems. In terms of precision of predicted response changes, the MCNP perturbation technique outperforms correlated sampling for the problem involving variation of nuclide concentrations in the same direction but performs comparably with or even underperforms correlated sampling for the other two types of problems that involve void or variation of nuclide concentrations in opposite directions. In terms of accuracy, the MCNP differential operator perturbation calculations may predict inaccurate results that deviate from the benchmarks well beyond their uncertainty ranges for some of the test problems. However, the accuracy of the MCNP differential operator perturbation can be improved if the midpoint correction technique is used.

A technique for extracting blood samples from mice in fire toxicity tests

Science.gov (United States)

Bucci, T. J.; Hilado, C. J.; Lopez, M. T.

1976-01-01

The extraction of adequate blood samples from moribund and dead mice has been a problem because of the small quantity of blood in each animal and the short time available between the animals' death and coagulation of the blood. These difficulties are particularly critical in fire toxicity tests because removal of the test animals while observing proper safety precautions for personnel is time-consuming. Techniques for extracting blood samples from mice were evaluated, and a technique was developed to obtain up to 0.8 ml of blood from a single mouse after death. The technique involves rapid exposure and cutting of the posterior vena cava and accumulation of blood in the peritoneal space. Blood samples of 0.5 ml or more from individual mice have been consistently obtained as much as 16 minutes after apparent death. Results of carboxyhemoglobin analyses of blood appeared reproducible and consistent with carbon monoxide concentrations in the exposure chamber.

Comparison of sampling techniques for Rift Valley Fever virus ...

African Journals Online (AJOL)

We investigated mosquito sampling techniques with two types of traps and attractants at different time for trapping potential vectors for Rift Valley Fever virus. The study was conducted in six villages in Ngorongoro district in Tanzania from September to October 2012. A total of 1814 mosquitoes were collected, of which 738 ...

Progressive Exponential Clustering-Based Steganography

Directory of Open Access Journals (Sweden)

Li Yue

2010-01-01

Full Text Available Cluster indexing-based steganography is an important branch of data-hiding techniques. Such schemes normally achieve good balance between high embedding capacity and low embedding distortion. However, most cluster indexing-based steganographic schemes utilise less efficient clustering algorithms for embedding data, which causes redundancy and leaves room for increasing the embedding capacity further. In this paper, a new clustering algorithm, called progressive exponential clustering (PEC, is applied to increase the embedding capacity by avoiding redundancy. Meanwhile, a cluster expansion algorithm is also developed in order to further increase the capacity without sacrificing imperceptibility.

Characterization-Based Molecular Design of Biofuel Additives Using Chemometric and Property Clustering Techniques

Directory of Open Access Journals (Sweden)

Subin eHada

2014-06-01

Full Text Available In this work, multivariate characterization data such as infrared (IR spectroscopy was used as a source of descriptor data involving information on molecular architecture for designing structured molecules with tailored properties. Application of multivariate statistical techniques such as principal component analysis (PCA allowed capturing important features of the molecular architecture from complex data to build appropriate latent variable models. Combining the property clustering techniques and group contribution methods (GCM based on characterization data in a reverse problem formulation enabled identifying candidate components by combining or mixing molecular fragments until the resulting properties match the targets. The developed methodology is demonstrated using molecular design of biodiesel additive which when mixed with off-spec biodiesel produces biodiesel that meets the desired fuel specifications. The contribution of this work is that the complex structures and orientations of the molecule can be included in the design, thereby allowing enumeration of all feasible candidate molecules that matched the identified target but were not part of original training set of molecules.

A line-based vegetation sampling technique and its application in ...

African Journals Online (AJOL)

percentage cover, density and intercept frequency) and also provides plant size distributions, yet requires no more sampling effort than the line-intercept method.. A field test of the three techniques in succulent karoo, showed that the discriminating ...

Comparison of correlation analysis techniques for irregularly sampled time series

Directory of Open Access Journals (Sweden)

K. Rehfeld

2011-06-01

Full Text Available Geoscientific measurements often provide time series with irregular time sampling, requiring either data reconstruction (interpolation or sophisticated methods to handle irregular sampling. We compare the linear interpolation technique and different approaches for analyzing the correlation functions and persistence of irregularly sampled time series, as Lomb-Scargle Fourier transformation and kernel-based methods. In a thorough benchmark test we investigate the performance of these techniques.

All methods have comparable root mean square errors (RMSEs for low skewness of the inter-observation time distribution. For high skewness, very irregular data, interpolation bias and RMSE increase strongly. We find a 40 % lower RMSE for the lag-1 autocorrelation function (ACF for the Gaussian kernel method vs. the linear interpolation scheme,in the analysis of highly irregular time series. For the cross correlation function (CCF the RMSE is then lower by 60 %. The application of the Lomb-Scargle technique gave results comparable to the kernel methods for the univariate, but poorer results in the bivariate case. Especially the high-frequency components of the signal, where classical methods show a strong bias in ACF and CCF magnitude, are preserved when using the kernel methods.

We illustrate the performances of interpolation vs. Gaussian kernel method by applying both to paleo-data from four locations, reflecting late Holocene Asian monsoon variability as derived from speleothem δ¹⁸O measurements. Cross correlation results are similar for both methods, which we attribute to the long time scales of the common variability. The persistence time (memory is strongly overestimated when using the standard, interpolation-based, approach. Hence, the Gaussian kernel is a reliable and more robust estimator with significant advantages compared to other techniques and suitable for large scale application to paleo-data.

Application of nuclear and allied techniques for the characterisation of forensic samples

International Nuclear Information System (INIS)

Sudersanan, M.; Kayasth, S.R.; Pant, D.R.; Chattopadhyay, N.; Bhattacharyya, C.N.

2002-01-01

Full text: Forensic science deals with the application of various techniques for physics, chemistry and biology for crime investigation. The legal implication of such analysis put considerable restriction on the choice of analytical techniques. Moreover, the unknown nature of the materials, the limited availability of samples and the large number of elements to be analysed put considerable strain on the analytical chemist on the selection of the appropriate technique. The availability of nuclear techniques has considerably enhanced the scope of forensic analysis. This paper deals with the recent results on the use of nuclear and allied analytical techniques for forensic applications. One of the important types of samples of forensic importance pertain to the identification of gunshot residues. The use of nuclear techniques has considerably simplified the interpretation of results through the use of appropriate elements like Ba, Cu, Sb, Zn, As and Sn etc. The combination of non-nuclear techniques for elements like Pb and Ni which are not easily amenable to be analysed by NAA and the use of appropriate separation procedure has led to the use of this method as a valid and versatile analytical procedure. In view of the presence of a large amounts of extraneous materials like cloth, body tissues etc in these samples and the limited availability of materials, the procedures for sample collection, dissolution and analysis have been standardized. Analysis of unknown materials like powders, metallic pieces etc. for the possible presence of nuclear materials or as materials in illicit trafficking is becoming important in recent years. The use of multi-technique approach is important in this case. Use of non-destructive techniques like XRF and radioactive counting enables the preliminary identification of materials and for the detection of radioactivity. Subsequent analysis by NAA or other appropriate analytical methods allows the characterization of the materials. Such

Analyses of archaeological pottery samples using X-ray fluorescence technique for provenance study

International Nuclear Information System (INIS)

Tamilarasu, S.; Swain, K.K.; Singhal, R.K; Reddy, A.V.R.; Acharya, R.; Velraj, G.

2015-01-01

Archaeological artifacts reveal information on past human activities, artifact preparation technology, art and possible trade. Ceramics are the most stable and abundant material in archaeological context. Pottery is the most abundant tracers in all archaeological excavations. Compared to major elements, elements present at trace concentrations levels are source specific and they maintain same concentration levels in source clay as well as finished products e.g., fired clay potteries. As it is difficult to find out exact source or origin, provenance study is carried out first to establish whether objects under study are from the same or different sources/origin. Various analytical techniques like instrumental neutron activation analysis (INAA), Ion beam analysis (IBA) and X-ray fluorescence (XRF) have been used for obtaining elemental concentrations in archaeological potteries. Portable X-ray fluorescence (pXRF) spectrometry provides a non-destructive means for elemental characterization of a wide range of archaeological materials. Ten archaeological pottery samples were collected from Kottapuram, Kerala under the supervision of archaeological survey of India. Portable X-ray fluorescence (pXRF) spectrometry using a handheld Olympus Innov-X Delta XRF device, ACD BARC, has been used for chemical characterization of the pottery samples. The instrument is equipped with the Delta Rhodium (Rh) anode X-Ray tube and uses a Silicon Drift Detector (resolution <200 eV at 5.95 keV Mn Kα X-ray). NIST 2781 SRM was analyzed for quality control purpose. Ten elements namely Fe, Ti, Mn, Co, Cu, Zn, Pb, Zr, Mo and Se were chosen for cluster analysis and their concentration values were utilized for multivariate statistical analysis using WinSTAT 9.0

Semantic based cluster content discovery in description first clustering algorithm

International Nuclear Information System (INIS)

Khan, M.W.; Asif, H.M.S.

2017-01-01

In the field of data analytics grouping of like documents in textual data is a serious problem. A lot of work has been done in this field and many algorithms have purposed. One of them is a category of algorithms which firstly group the documents on the basis of similarity and then assign the meaningful labels to those groups. Description first clustering algorithm belong to the category in which the meaningful description is deduced first and then relevant documents are assigned to that description. LINGO (Label Induction Grouping Algorithm) is the algorithm of description first clustering category which is used for the automatic grouping of documents obtained from search results. It uses LSI (Latent Semantic Indexing); an IR (Information Retrieval) technique for induction of meaningful labels for clusters and VSM (Vector Space Model) for cluster content discovery. In this paper we present the LINGO while it is using LSI during cluster label induction and cluster content discovery phase. Finally, we compare results obtained from the said algorithm while it uses VSM and Latent semantic analysis during cluster content discovery phase. (author)

Determination of palladium in biological samples applying nuclear analytical techniques

International Nuclear Information System (INIS)

Cavalcante, Cassio Q.; Sato, Ivone M.; Salvador, Vera L. R.; Saiki, Mitiko

2008-01-01

This study presents Pd determinations in bovine tissue samples containing palladium prepared in the laboratory, and CCQM-P63 automotive catalyst materials of the Proficiency Test, using instrumental thermal and epithermal neutron activation analysis and energy dispersive X-ray fluorescence techniques. Solvent extraction and solid phase extraction procedures were also applied to separate Pd from interfering elements before the irradiation in the nuclear reactor. The results obtained by different techniques were compared against each other to examine sensitivity, precision and accuracy. (author)

ClusTrack: feature extraction and similarity measures for clustering of genome-wide data sets.

Directory of Open Access Journals (Sweden)

Halfdan Rydbeck

Full Text Available Clustering is a popular technique for explorative analysis of data, as it can reveal subgroupings and similarities between data in an unsupervised manner. While clustering is routinely applied to gene expression data, there is a lack of appropriate general methodology for clustering of sequence-level genomic and epigenomic data, e.g. ChIP-based data. We here introduce a general methodology for clustering data sets of coordinates relative to a genome assembly, i.e. genomic tracks. By defining appropriate feature extraction approaches and similarity measures, we allow biologically meaningful clustering to be performed for genomic tracks using standard clustering algorithms. An implementation of the methodology is provided through a tool, ClusTrack, which allows fine-tuned clustering analyses to be specified through a web-based interface. We apply our methods to the clustering of occupancy of the H3K4me1 histone modification in samples from a range of different cell types. The majority of samples form meaningful subclusters, confirming that the definitions of features and similarity capture biological, rather than technical, variation between the genomic tracks. Input data and results are available, and can be reproduced, through a Galaxy Pages document at http://hyperbrowser.uio.no/hb/u/hb-superuser/p/clustrack. The clustering functionality is available as a Galaxy tool, under the menu option "Specialized analyzis of tracks", and the submenu option "Cluster tracks based on genome level similarity", at the Genomic HyperBrowser server: http://hyperbrowser.uio.no/hb/.

Hubble Space Telescope-NICMOS Observations of M31'S Metal-Rich Globular Clusters and Their Surrounding Fields. I. Techniques

Science.gov (United States)

Stephens, Andrew W.; Frogel, Jay A.; Freedman, Wendy; Gallart, Carme; Jablonka, Pascale; Ortolani, Sergio; Renzini, Alvio; Rich, R. Michael; Davies, Roger

2001-05-01

Astronomers are always anxious to push their observations to the limit-basing results on objects at the detection threshold, spectral features barely stronger than the noise, or photometry in very crowded regions. In this paper we present a careful analysis of photometry in crowded regions and show how image blending affects the results and interpretation of such data. Although this analysis is specifically for our NICMOS observations in M31, the techniques we develop can be applied to any imaging data taken in crowded fields; we show how the effects of image blending will limit even the Next Generation Space Telescope. We have obtained HST-NICMOS observations of five of M31's most metal-rich globular clusters. These data allow photometry of individual stars in the clusters and their surrounding fields. However, to achieve our goals-obtain accurate luminosity functions to compare with their Galactic counterparts, determine metallicities from the slope of the giant branch, identify long-period variables, and estimate ages from the AGB tip luminosity-we must be able to disentangle the true properties of the population from the observational effects associated with measurements made in very crowded fields. We thus use three different techniques to analyze the effects of crowding on our data, including the insertion of artificial stars (traditional completeness tests) and the creation of completely artificial clusters. These computer simulations are used to derive threshold- and critical-blending radii for each cluster, which determine how close to the cluster center reliable photometry can be achieved. The simulations also allow us to quantify and correct for the effects of blending on the slope and width of the RGB at different surface brightness levels. We then use these results to estimate the limits blending will place on future space-based observations. Based on observations with the NASA/ESA Hubble Space Telescope obtained at the Space Telescope Science

Substructure in clusters of galaxies

International Nuclear Information System (INIS)

Fitchett, M.J.

1988-01-01

Optical observations suggesting the existence of substructure in clusters of galaxies are examined. Models of cluster formation and methods used to detect substructure in clusters are reviewed. Consideration is given to classification schemes based on a departure of bright cluster galaxies from a spherically symmetric distribution, evidence for statistically significant substructure, and various types of substructure, including velocity, spatial, and spatial-velocity substructure. The substructure observed in the galaxy distribution in clusters is discussed, focusing on observations from general cluster samples, the Virgo cluster, the Hydra cluster, Centaurus, the Coma cluster, and the Cancer cluster. 88 refs

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations.

Science.gov (United States)

Bragg, Elise M; Briggs, Farran

2017-02-15

This protocol outlines large-scale reconstructions of neurons combined with the use of independent and unbiased clustering analyses to create a comprehensive survey of the morphological characteristics observed among a selective neuronal population. Combination of these techniques constitutes a novel approach for the collection and analysis of neuroanatomical data. Together, these techniques enable large-scale, and therefore more comprehensive, sampling of selective neuronal populations and establish unbiased quantitative methods for describing morphologically unique neuronal classes within a population. The protocol outlines the use of modified rabies virus to selectively label neurons. G-deleted rabies virus acts like a retrograde tracer following stereotaxic injection into a target brain structure of interest and serves as a vehicle for the delivery and expression of EGFP in neurons. Large numbers of neurons are infected using this technique and express GFP throughout their dendrites, producing "Golgi-like" complete fills of individual neurons. Accordingly, the virus-mediated retrograde tracing method improves upon traditional dye-based retrograde tracing techniques by producing complete intracellular fills. Individual well-isolated neurons spanning all regions of the brain area under study are selected for reconstruction in order to obtain a representative sample of neurons. The protocol outlines procedures to reconstruct cell bodies and complete dendritic arborization patterns of labeled neurons spanning multiple tissue sections. Morphological data, including positions of each neuron within the brain structure, are extracted for further analysis. Standard programming functions were utilized to perform independent cluster analyses and cluster evaluations based on morphological metrics. To verify the utility of these analyses, statistical evaluation of a cluster analysis performed on 160 neurons reconstructed in the thalamic reticular nucleus of the thalamus

A new sampling technique for surface exposure dating using a portable electric rock cutter

Directory of Open Access Journals (Sweden)

Yusuke Suganuma

2012-07-01

Full Text Available Surface exposure dating using in situ cosmogenic nuclides has contributed to our understanding of Earth-surface processes. The precision of the ages estimated by this method is affected by the sample geometry; therefore, high accuracy measurements of the thickness and shape of the rock sample (thickness and shape is crucial. However, it is sometimes diffi cult to meet these requirements by conventional sampling methods with a hammer and chisel. Here, we propose a new sampling technique using a portable electric rock cutter. This sampling technique is faster, produces more precisely shaped samples, and allows for a more precise age interpretation. A simple theoretical modeldemonstrates that the age error due to defective sample geometry increases as the total sample thickness increases, indicating the importance of precise sampling for surface exposure dating.

Mantle biopsy: a technique for nondestructive tissue-sampling of freshwater mussels

Science.gov (United States)

David J. Berg; Wendell R. Haag; Sheldon I. Guttman; James B. Sickel

1995-01-01

Mantle biopsy is a means of obtaining tissue samples for genetic, physiological, and contaminant studies of bivalves; but the effects of this biopsy on survival have not been determined. We describe a simple technique for obtaining such samples from unionacean bivalves and how we compared survival among biopsied and control organisms in field experiments. Survival was...

A Monte Carlo Sampling Technique for Multi-phonon Processes

Energy Technology Data Exchange (ETDEWEB)

Hoegberg, Thure

1961-12-15

A sampling technique for selecting scattering angle and energy gain in Monte Carlo calculations of neutron thermalization is described. It is supposed that the scattering is separated into processes involving different numbers of phonons. The number of phonons involved is first determined. Scattering angle and energy gain are then chosen by using special properties of the multi-phonon term.

Characterization-Based Molecular Design of Bio-Fuel Additives Using Chemometric and Property Clustering Techniques

International Nuclear Information System (INIS)

Hada, Subin; Solvason, Charles C.; Eden, Mario R.

2014-01-01

In this work, multivariate characterization data such as infrared spectroscopy was used as a source of descriptor data involving information on molecular architecture for designing structured molecules with tailored properties. Application of multivariate statistical techniques such as principal component analysis allowed capturing important features of the molecular architecture from enormous amount of complex data to build appropriate latent variable models. Combining the property clustering techniques and group contribution methods based on characterization (cGCM) data in a reverse problem formulation enabled identifying candidate components by combining or mixing molecular fragments until the resulting properties match the targets. The developed methodology is demonstrated using molecular design of biodiesel additive, which when mixed with off-spec biodiesel produces biodiesel that meets the desired fuel specifications. The contribution of this work is that the complex structures and orientations of the molecule can be included in the design, thereby allowing enumeration of all feasible candidate molecules that matched the identified target but were not part of original training set of molecules.

Characterization-Based Molecular Design of Bio-Fuel Additives Using Chemometric and Property Clustering Techniques

Energy Technology Data Exchange (ETDEWEB)

Hada, Subin; Solvason, Charles C.; Eden, Mario R., E-mail: edenmar@auburn.edu [Department of Chemical Engineering, Auburn University, Auburn, AL (United States)

2014-06-10

In this work, multivariate characterization data such as infrared spectroscopy was used as a source of descriptor data involving information on molecular architecture for designing structured molecules with tailored properties. Application of multivariate statistical techniques such as principal component analysis allowed capturing important features of the molecular architecture from enormous amount of complex data to build appropriate latent variable models. Combining the property clustering techniques and group contribution methods based on characterization (cGCM) data in a reverse problem formulation enabled identifying candidate components by combining or mixing molecular fragments until the resulting properties match the targets. The developed methodology is demonstrated using molecular design of biodiesel additive, which when mixed with off-spec biodiesel produces biodiesel that meets the desired fuel specifications. The contribution of this work is that the complex structures and orientations of the molecule can be included in the design, thereby allowing enumeration of all feasible candidate molecules that matched the identified target but were not part of original training set of molecules.

Genetic diversity of wheat grain quality and determination the best clustering technique and data type for diversity assessment

Directory of Open Access Journals (Sweden)

Khodadadi Mostafa

2014-01-01

Full Text Available Wheat is an important staple in human nutrition and improvement of its grain quality characters will have high impact on population's health. The objectives of this study were assessing variation of some grain quality characteristics in the Iranian wheat genotypes and identify the best type of data and clustering method for grouping genotypes. In this study 30 spring wheat genotypes were cultivated through randomized complete block design with three replications in 2009 and 2010 years. High significant difference among genotypes for all traits except for Sulfate, K, Br and Cl content, also deference among two years mean for all traits were no significant. Meanwhile there were significant interaction between year and genotype for all traits except Sulfate and F content. Mean values for crude protein, Zn, Fe and Ca in Mahdavi, Falat, Star, Sistan genotypes were the highest. The Ca and Br content showed the highest and the lowest broadcast heritability respectively. In this study indicated that the Root Mean Square Standard Deviation is efficient than R Squared and R Squared efficient than Semi Partial R Squared criteria for determining the best clustering technique. Also Ward method and canonical scores identified as the best clustering method and data type for grouping genotypes, respectively. Genotypes were grouped into six completely separate clusters and Roshan, Niknejad and Star genotypes from the fourth, fifth and sixth clusters had high grain quality characters in overall.

Time clustered sampling can inflate the inferred substitution rate in foot-and-mouth disease virus analyses

DEFF Research Database (Denmark)

Pedersen, Casper-Emil Tingskov; Frandsen, Peter; Wekesa, Sabenzia N.

2015-01-01

abundance of sequence data sampled under widely different schemes, an effort to keep results consistent and comparable is needed. This study emphasizes commonly disregarded problems in the inference of evolutionary rates in viral sequence data when sampling is unevenly distributed on a temporal scale...... through a study of the foot-and-mouth (FMD) disease virus serotypes SAT 1 and SAT 2. Our study shows that clustered temporal sampling in phylogenetic analyses of FMD viruses will strongly bias the inferences of substitution rates and tMRCA because the inferred rates in such data sets reflect a rate closer...... to the mutation rate rather than the substitution rate. Estimating evolutionary parameters from viral sequences should be performed with due consideration of the differences in short-term and longer-term evolutionary processes occurring within sets of temporally sampled viruses, and studies should carefully...

Locality-Aware CTA Clustering For Modern GPUs

Energy Technology Data Exchange (ETDEWEB)

Li, Ang; Song, Shuaiwen; Liu, Weifeng; Liu, Xu; Kumar, Akash; Corporaal, Henk

2017-04-08

In this paper, we proposed a novel clustering technique for tapping into the performance potential of a largely ignored type of locality: inter-CTA locality. We first demonstrated the capability of the existing GPU hardware to exploit such locality, both spatially and temporally, on L1 or L1/Tex unified cache. To verify the potential of this locality, we quantified its existence in a broad spectrum of applications and discussed its sources of origin. Based on these insights, we proposed the concept of CTA-Clustering and its associated software techniques. Finally, We evaluated these techniques on all modern generations of NVIDIA GPU architectures. The experimental results showed that our proposed clustering techniques could significantly improve on-chip cache performance.

Noninvasive neuromodulation in cluster headache

DEFF Research Database (Denmark)

Láinez, Miguel J A; Jensen, Rigmor

2015-01-01

PURPOSE OF REVIEW: Neuromodulation is an alternative in the management of medically intractable cluster headache patients. Most of the techniques are invasive, but in the last 2 years, some studies using a noninvasive device have been presented. The objective of this article is to review the data...... using this approach. RECENT FINDINGS: Techniques as occipital nerve stimulation or sphenopalatine ganglion stimulation are recommended as first-line therapy in refractory cluster patients, but they are invasive and maybe associated with complications. Noninvasive vagal nerve stimulation with an external...... device has been tried in cluster patients. Results from clinical practice and a single randomized clinical trial have been presented showing a reduction of the number of cluster attacks/week in the patients treated with the device. The rate of adverse events was low and most of them were mild. SUMMARY...

Analyzing indirect effects in cluster randomized trials. The effect of estimation method, number of groups and group sizes on accuracy and power.

Directory of Open Access Journals (Sweden)

Joop eHox

2014-02-01

Full Text Available Cluster randomized trials assess the effect of an intervention that is carried out at the group or cluster level. Ajzen’s theory of planned behaviour is often used to model the effect of the intervention as an indirect effect mediated in turn by attitude, norms and behavioural intention. Structural equation modelling (SEM is the technique of choice to estimate indirect effects and their significance. However, this is a large sample technique, and its application in a cluster randomized trial assumes a relatively large number of clusters. In practice, the number of clusters in these studies tends to be relatively small, e.g. much less than fifty. This study uses simulation methods to find the lowest number of clusters needed when multilevel SEM is used to estimate the indirect effect. Maximum likelihood estimation is compared to Bayesian analysis, with the central quality criteria being accuracy of the point estimate and the confidence interval. We also investigate the power of the test for the indirect effect. We conclude that Bayes estimation works well with much smaller cluster level sample sizes such as 20 cases than maximum likelihood estimation; although the bias is larger the coverage is much better. When only 5 to 10 clusters are available per treatment condition even with Bayesian estimation problems occur.

Sample size estimation to substantiate freedom from disease for clustered binary data with a specific risk profile

DEFF Research Database (Denmark)

Kostoulas, P.; Nielsen, Søren Saxmose; Browne, W. J.

2013-01-01

and power when applied to these groups. We propose the use of the variance partition coefficient (VPC), which measures the clustering of infection/disease for individuals with a common risk profile. Sample size estimates are obtained separately for those groups that exhibit markedly different heterogeneity......, thus, optimizing resource allocation. A VPC-based predictive simulation method for sample size estimation to substantiate freedom from disease is presented. To illustrate the benefits of the proposed approach we give two examples with the analysis of data from a risk factor study on Mycobacterium avium...

Scalable Density-Based Subspace Clustering

DEFF Research Database (Denmark)

Müller, Emmanuel; Assent, Ira; Günnemann, Stephan

2011-01-01

For knowledge discovery in high dimensional databases, subspace clustering detects clusters in arbitrary subspace projections. Scalability is a crucial issue, as the number of possible projections is exponential in the number of dimensions. We propose a scalable density-based subspace clustering...... method that steers mining to few selected subspace clusters. Our novel steering technique reduces subspace processing by identifying and clustering promising subspaces and their combinations directly. Thereby, it narrows down the search space while maintaining accuracy. Thorough experiments on real...... and synthetic databases show that steering is efficient and scalable, with high quality results. For future work, our steering paradigm for density-based subspace clustering opens research potential for speeding up other subspace clustering approaches as well....

Spatial cluster analysis of nanoscopically mapped serotonin receptors for classification of fixed brain tissue

Science.gov (United States)

Sams, Michael; Silye, Rene; Göhring, Janett; Muresan, Leila; Schilcher, Kurt; Jacak, Jaroslaw

2014-01-01

We present a cluster spatial analysis method using nanoscopic dSTORM images to determine changes in protein cluster distributions within brain tissue. Such methods are suitable to investigate human brain tissue and will help to achieve a deeper understanding of brain disease along with aiding drug development. Human brain tissue samples are usually treated postmortem via standard fixation protocols, which are established in clinical laboratories. Therefore, our localization microscopy-based method was adapted to characterize protein density and protein cluster localization in samples fixed using different protocols followed by common fluorescent immunohistochemistry techniques. The localization microscopy allows nanoscopic mapping of serotonin 5-HT1A receptor groups within a two-dimensional image of a brain tissue slice. These nanoscopically mapped proteins can be confined to clusters by applying the proposed statistical spatial analysis. Selected features of such clusters were subsequently used to characterize and classify the tissue. Samples were obtained from different types of patients, fixed with different preparation methods, and finally stored in a human tissue bank. To verify the proposed method, samples of a cryopreserved healthy brain have been compared with epitope-retrieved and paraffin-fixed tissues. Furthermore, samples of healthy brain tissues were compared with data obtained from patients suffering from mental illnesses (e.g., major depressive disorder). Our work demonstrates the applicability of localization microscopy and image analysis methods for comparison and classification of human brain tissues at a nanoscopic level. Furthermore, the presented workflow marks a unique technological advance in the characterization of protein distributions in brain tissue sections.

TRAN-STAT: statistics for environmental studies, Number 22. Comparison of soil-sampling techniques for plutonium at Rocky Flats

International Nuclear Information System (INIS)

Gilbert, R.O.; Bernhardt, D.E.; Hahn, P.B.

1983-01-01

A summary of a field soil sampling study conducted around the Rocky Flats Colorado plant in May 1977 is preseted. Several different soil sampling techniques that had been used in the area were applied at four different sites. One objective was to comparethe average 239 - 240 Pu concentration values obtained by the various soil sampling techniques used. There was also interest in determining whether there are differences in the reproducibility of the various techniques and how the techniques compared with the proposed EPA technique of sampling to 1 cm depth. Statistically significant differences in average concentrations between the techniques were found. The differences could be largely related to the differences in sampling depth-the primary physical variable between the techniques. The reproducibility of the techniques was evaluated by comparing coefficients of variation. Differences between coefficients of variation were not statistically significant. Average (median) coefficients ranged from 21 to 42 percent for the five sampling techniques. A laboratory study indicated that various sample treatment and particle sizing techniques could increase the concentration of plutonium in the less than 10 micrometer size fraction by up to a factor of about 4 compared to the 2 mm size fraction

Stratified source-sampling techniques for Monte Carlo eigenvalue analysis

International Nuclear Information System (INIS)

Mohamed, A.

1998-01-01

In 1995, at a conference on criticality safety, a special session was devoted to the Monte Carlo ''Eigenvalue of the World'' problem. Argonne presented a paper, at that session, in which the anomalies originally observed in that problem were reproduced in a much simplified model-problem configuration, and removed by a version of stratified source-sampling. In this paper, stratified source-sampling techniques are generalized and applied to three different Eigenvalue of the World configurations which take into account real-world statistical noise sources not included in the model problem, but which differ in the amount of neutronic coupling among the constituents of each configuration. It is concluded that, in Monte Carlo eigenvalue analysis of loosely-coupled arrays, the use of stratified source-sampling reduces the probability of encountering an anomalous result over that if conventional source-sampling methods are used. However, this gain in reliability is substantially less than that observed in the model-problem results

The correlation functions for the clustering of galaxies and Abell clusters

International Nuclear Information System (INIS)

Jones, B.J.T.; Jones, J.E.; Copenhagen Univ.

1985-01-01

The difference in amplitudes between the galaxy-galaxy correlation function and the correlation function between Abell clusters is a consequence of two facts. Firstly, most Abell clusters with z<0.08 lie in a relatively small volume of the sampled space, and secondly, the fraction of galaxies lying in Abell clusters differs considerably inside and outside of this volume. (The Abell clusters are confined to a smaller volume of space than are the galaxies.) We discuss the implications of this interpretation of the clustering correlation functions and present a simple model showing how such a situation may arise quite naturally in standard theories for galaxy formation. (orig.)

Into the Bowels of Depression: Unravelling Medical Symptoms Associated with Depression by Applying Machine-Learning Techniques to a Community Based Population Sample

Science.gov (United States)

Dipnall, Joanna F.

2016-01-01

Background Depression is commonly comorbid with many other somatic diseases and symptoms. Identification of individuals in clusters with comorbid symptoms may reveal new pathophysiological mechanisms and treatment targets. The aim of this research was to combine machine-learning (ML) algorithms with traditional regression techniques by utilising self-reported medical symptoms to identify and describe clusters of individuals with increased rates of depression from a large cross-sectional community based population epidemiological study. Methods A multi-staged methodology utilising ML and traditional statistical techniques was performed using the community based population National Health and Nutrition Examination Study (2009–2010) (N = 3,922). A Self-organised Mapping (SOM) ML algorithm, combined with hierarchical clustering, was performed to create participant clusters based on 68 medical symptoms. Binary logistic regression, controlling for sociodemographic confounders, was used to then identify the key clusters of participants with higher levels of depression (PHQ-9≥10, n = 377). Finally, a Multiple Additive Regression Tree boosted ML algorithm was run to identify the important medical symptoms for each key cluster within 17 broad categories: heart, liver, thyroid, respiratory, diabetes, arthritis, fractures and osteoporosis, skeletal pain, blood pressure, blood transfusion, cholesterol, vision, hearing, psoriasis, weight, bowels and urinary. Results Five clusters of participants, based on medical symptoms, were identified to have significantly increased rates of depression compared to the cluster with the lowest rate: odds ratios ranged from 2.24 (95% CI 1.56, 3.24) to 6.33 (95% CI 1.67, 24.02). The ML boosted regression algorithm identified three key medical condition categories as being significantly more common in these clusters: bowel, pain and urinary symptoms. Bowel-related symptoms was found to dominate the relative importance of symptoms within the

Into the Bowels of Depression: Unravelling Medical Symptoms Associated with Depression by Applying Machine-Learning Techniques to a Community Based Population Sample.

Science.gov (United States)

Dipnall, Joanna F; Pasco, Julie A; Berk, Michael; Williams, Lana J; Dodd, Seetal; Jacka, Felice N; Meyer, Denny

2016-01-01

Depression is commonly comorbid with many other somatic diseases and symptoms. Identification of individuals in clusters with comorbid symptoms may reveal new pathophysiological mechanisms and treatment targets. The aim of this research was to combine machine-learning (ML) algorithms with traditional regression techniques by utilising self-reported medical symptoms to identify and describe clusters of individuals with increased rates of depression from a large cross-sectional community based population epidemiological study. A multi-staged methodology utilising ML and traditional statistical techniques was performed using the community based population National Health and Nutrition Examination Study (2009-2010) (N = 3,922). A Self-organised Mapping (SOM) ML algorithm, combined with hierarchical clustering, was performed to create participant clusters based on 68 medical symptoms. Binary logistic regression, controlling for sociodemographic confounders, was used to then identify the key clusters of participants with higher levels of depression (PHQ-9≥10, n = 377). Finally, a Multiple Additive Regression Tree boosted ML algorithm was run to identify the important medical symptoms for each key cluster within 17 broad categories: heart, liver, thyroid, respiratory, diabetes, arthritis, fractures and osteoporosis, skeletal pain, blood pressure, blood transfusion, cholesterol, vision, hearing, psoriasis, weight, bowels and urinary. Five clusters of participants, based on medical symptoms, were identified to have significantly increased rates of depression compared to the cluster with the lowest rate: odds ratios ranged from 2.24 (95% CI 1.56, 3.24) to 6.33 (95% CI 1.67, 24.02). The ML boosted regression algorithm identified three key medical condition categories as being significantly more common in these clusters: bowel, pain and urinary symptoms. Bowel-related symptoms was found to dominate the relative importance of symptoms within the five key clusters. This

Cluster analysis and quality assessment of logged water at an irrigation project, eastern Saudi Arabia.

Science.gov (United States)

Hussain, Mahbub; Ahmed, Syed Munaf; Abderrahman, Walid

2008-01-01

A multivariate statistical technique, cluster analysis, was used to assess the logged surface water quality at an irrigation project at Al-Fadhley, Eastern Province, Saudi Arabia. The principal idea behind using the technique was to utilize all available hydrochemical variables in the quality assessment including trace elements and other ions which are not considered in conventional techniques for water quality assessments like Stiff and Piper diagrams. Furthermore, the area belongs to an irrigation project where water contamination associated with the use of fertilizers, insecticides and pesticides is expected. This quality assessment study was carried out on a total of 34 surface/logged water samples. To gain a greater insight in terms of the seasonal variation of water quality, 17 samples were collected from both summer and winter seasons. The collected samples were analyzed for a total of 23 water quality parameters including pH, TDS, conductivity, alkalinity, sulfate, chloride, bicarbonate, nitrate, phosphate, bromide, fluoride, calcium, magnesium, sodium, potassium, arsenic, boron, copper, cobalt, iron, lithium, manganese, molybdenum, nickel, selenium, mercury and zinc. Cluster analysis in both Q and R modes was used. Q-mode analysis resulted in three distinct water types for both the summer and winter seasons. Q-mode analysis also showed the spatial as well as temporal variation in water quality. R-mode cluster analysis led to the conclusion that there are two major sources of contamination for the surface/shallow groundwater in the area: fertilizers, micronutrients, pesticides, and insecticides used in agricultural activities, and non-point natural sources.

Analytical techniques for measurement of 99Tc in environmental samples

International Nuclear Information System (INIS)

Anon.

1979-01-01

Three new methods have been developed for measuring 99 Tc in environmental samples. The most sensitive method is isotope dilution mass spectrometry, which allows measurement of about 1 x 10 -12 grams of 99 Tc. Results on analysis of five samples by this method compare very well with values obtained by a second independent method, which involves counting of beta particles from 99 Tc and internal conversion electrons from /sup 97m/Tc. A third method involving electrothermal atomic absorption has also been developed. Although this method is not as sensitive as the first two techniques, the cost per analysis is expected to be considerably less for certain types of samples

Diversity in the stellar velocity dispersion profiles of a large sample of brightest cluster galaxies z ≤ 0.3

Science.gov (United States)

Loubser, S. I.; Hoekstra, H.; Babul, A.; O'Sullivan, E.

2018-06-01

We analyse spatially resolved deep optical spectroscopy of brightestcluster galaxies (BCGs) located in 32 massive clusters with redshifts of 0.05 ≤ z ≤ 0.30 to investigate their velocity dispersion profiles. We compare these measurements to those of other massive early-type galaxies, as well as central group galaxies, where relevant. This unique, large sample extends to the most extreme of massive galaxies, spanning MK between -25.7 and -27.8 mag, and host cluster halo mass M500 up to 1.7 × 1015 M⊙. To compare the kinematic properties between brightest group and cluster members, we analyse similar spatially resolved long-slit spectroscopy for 23 nearby brightest group galaxies (BGGs) from the Complete Local-Volume Groups Sample. We find a surprisingly large variety in velocity dispersion slopes for BCGs, with a significantly larger fraction of positive slopes, unique compared to other (non-central) early-type galaxies as well as the majority of the brightest members of the groups. We find that the velocity dispersion slopes of the BCGs and BGGs correlate with the luminosity of the galaxies, and we quantify this correlation. It is not clear whether the full diversity in velocity dispersion slopes that we see is reproduced in simulations.

Determination of some trace elements in biological samples using XRF and TXRF techniques

International Nuclear Information System (INIS)

Khuder, A.; Karjou, J.; Sawan, M. K.

2006-07-01

XRF and TXRF techniques were successfully used for the multi-element determination of trace elements in whole blood and human head hair samples. This was achieved by the direct analysis using XRF technique with different collimation units and by the optimized chemical procedures for TXRF analysis. Light element of S and P were preferably determined by XRF with primary x-ray excitation, while, elements of K, Ca, Fe, and Br were determined with a very good accuracy and precision using XRF with Cu- and Mo-secondary targets. The chemical procedure dependent on the preconcentration of trace elements by APDC was superiorly used for the determination of traces of Ni and Pb in the range of 1.0-1.7 μg/dl and 11-23 μg/dl, respectively, in whole blood samples by TXRF technique; determination of other elements as Cu and Zn was also achievable using this approach. Rb in whole blood samples was determined directly after the digestion of samples using PTFE-bomb for TXRF analysis. (author)

Clustering high dimensional data

DEFF Research Database (Denmark)

Assent, Ira

2012-01-01

High-dimensional data, i.e., data described by a large number of attributes, pose specific challenges to clustering. The so-called ‘curse of dimensionality’, coined originally to describe the general increase in complexity of various computational problems as dimensionality increases, is known...... to render traditional clustering algorithms ineffective. The curse of dimensionality, among other effects, means that with increasing number of dimensions, a loss of meaningful differentiation between similar and dissimilar objects is observed. As high-dimensional objects appear almost alike, new approaches...... for clustering are required. Consequently, recent research has focused on developing techniques and clustering algorithms specifically for high-dimensional data. Still, open research issues remain. Clustering is a data mining task devoted to the automatic grouping of data based on mutual similarity. Each cluster...

Recent advances in sample preparation techniques and methods of sulfonamides detection - A review.

Science.gov (United States)

Dmitrienko, Stanislava G; Kochuk, Elena V; Apyari, Vladimir V; Tolmacheva, Veronika V; Zolotov, Yury A

2014-11-19

Sulfonamides (SAs) have been the most widely used antimicrobial drugs for more than 70 years, and their residues in foodstuffs and environmental samples pose serious health hazards. For this reason, sensitive and specific methods for the quantification of these compounds in numerous matrices have been developed. This review intends to provide an updated overview of the recent trends over the past five years in sample preparation techniques and methods for detecting SAs. Examples of the sample preparation techniques, including liquid-liquid and solid-phase extraction, dispersive liquid-liquid microextraction and QuEChERS, are given. Different methods of detecting the SAs present in food and feed and in environmental, pharmaceutical and biological samples are discussed. Copyright © 2014 Elsevier B.V. All rights reserved.

A formal concept analysis approach to consensus clustering of multi-experiment expression data

Science.gov (United States)

2014-01-01

Background Presently, with the increasing number and complexity of available gene expression datasets, the combination of data from multiple microarray studies addressing a similar biological question is gaining importance. The analysis and integration of multiple datasets are expected to yield more reliable and robust results since they are based on a larger number of samples and the effects of the individual study-specific biases are diminished. This is supported by recent studies suggesting that important biological signals are often preserved or enhanced by multiple experiments. An approach to combining data from different experiments is the aggregation of their clusterings into a consensus or representative clustering solution which increases the confidence in the common features of all the datasets and reveals the important differences among them. Results We propose a novel generic consensus clustering technique that applies Formal Concept Analysis (FCA) approach for the consolidation and analysis of clustering solutions derived from several microarray datasets. These datasets are initially divided into groups of related experiments with respect to a predefined criterion. Subsequently, a consensus clustering algorithm is applied to each group resulting in a clustering solution per group. These solutions are pooled together and further analysed by employing FCA which allows extracting valuable insights from the data and generating a gene partition over all the experiments. In order to validate the FCA-enhanced approach two consensus clustering algorithms are adapted to incorporate the FCA analysis. Their performance is evaluated on gene expression data from multi-experiment study examining the global cell-cycle control of fission yeast. The FCA results derived from both methods demonstrate that, although both algorithms optimize different clustering characteristics, FCA is able to overcome and diminish these differences and preserve some relevant biological

Automated cloud screening of AVHRR imagery using split-and-merge clustering

Science.gov (United States)

Gallaudet, Timothy C.; Simpson, James J.

1991-01-01

Previous methods to segment clouds from ocean in AVHRR imagery have shown varying degrees of success, with nighttime approaches being the most limited. An improved method of automatic image segmentation, the principal component transformation split-and-merge clustering (PCTSMC) algorithm, is presented and applied to cloud screening of both nighttime and daytime AVHRR data. The method combines spectral differencing, the principal component transformation, and split-and-merge clustering to sample objectively the natural classes in the data. This segmentation method is then augmented by supervised classification techniques to screen clouds from the imagery. Comparisons with other nighttime methods demonstrate its improved capability in this application. The sensitivity of the method to clustering parameters is presented; the results show that the method is insensitive to the split-and-merge thresholds.

Clustering for data mining a data recovery approach

CERN Document Server

Mirkin, Boris

2005-01-01

Often considered more as an art than a science, the field of clustering has been dominated by learning through examples and by techniques chosen almost through trial-and-error. Even the most popular clustering methods--K-Means for partitioning the data set and Ward's method for hierarchical clustering--have lacked the theoretical attention that would establish a firm relationship between the two methods and relevant interpretation aids.Rather than the traditional set of ad hoc techniques, Clustering for Data Mining: A Data Recovery Approach presents a theory that not only closes gaps in K-Mean

Dynamic multifactor clustering of financial networks

Science.gov (United States)

Ross, Gordon J.

2014-02-01

We investigate the tendency for financial instruments to form clusters when there are multiple factors influencing the correlation structure. Specifically, we consider a stock portfolio which contains companies from different industrial sectors, located in several different countries. Both sector membership and geography combine to create a complex clustering structure where companies seem to first be divided based on sector, with geographical subclusters emerging within each industrial sector. We argue that standard techniques for detecting overlapping clusters and communities are not able to capture this type of structure and show how robust regression techniques can instead be used to remove the influence of both sector and geography from the correlation matrix separately. Our analysis reveals that prior to the 2008 financial crisis, companies did not tend to form clusters based on geography. This changed immediately following the crisis, with geography becoming a more important determinant of clustering structure.

Symbol synchronization and sampling frequency synchronization techniques in real-time DDO-OFDM systems

Science.gov (United States)

Chen, Ming; He, Jing; Cao, Zizheng; Tang, Jin; Chen, Lin; Wu, Xian

2014-09-01

In this paper, we propose and experimentally demonstrate a symbol synchronization and sampling frequency synchronization techniques in real-time direct-detection optical orthogonal frequency division multiplexing (DDO-OFDM) system, over 100-km standard single mode fiber (SSMF) using a cost-effective directly modulated distributed feedback (DFB) laser. The experiment results show that the proposed symbol synchronization based on training sequence (TS) has a low complexity and high accuracy even at a sampling frequency offset (SFO) of 5000-ppm. Meanwhile, the proposed pilot-assisted sampling frequency synchronization between digital-to-analog converter (DAC) and analog-to-digital converter (ADC) is capable of estimating SFOs with an accuracy of technique can also compensate SFO effects within a small residual SFO caused by deviation of SFO estimation and low-precision or unstable clock source. The two synchronization techniques are suitable for high-speed DDO-OFDM transmission systems.

Filaments and clusters of galaxies

International Nuclear Information System (INIS)

Soltan, A.

1987-01-01

A statistical test to investigate filaments of galaxies is performed. Only particular form of filaments is considered, viz. filaments connecting Abell clusters of galaxies. Relative position of triplets ''cluster - field object - cluster'' is analysed. Though neither cluster sample nor field object sample are homogeneous and complete only peculiar form of selection effects could affect the present statistics. Comparison of observational data with simulations shows that less than 15 per cent of all field galaxies is concentrated in filaments connecting rich clusters. Most of the field objects used in the analysis are not normal galaxies and it is possible that this conclusion is not in conflict with apparent filaments seen in the Lick counts and in some nearby 3D maps of the galaxy distribution. 26 refs., 2 figs. (author)

Globular clusters and galaxy halos

International Nuclear Information System (INIS)

Van Den Bergh, S.

1984-01-01

Using semipartial correlation coefficients and bootstrap techniques, a study is made of the important features of globular clusters with respect to the total number of galaxy clusters and dependence of specific galaxy cluster on parent galaxy type, cluster radii, luminosity functions and cluster ellipticity. It is shown that the ellipticity of LMC clusters correlates significantly with cluster luminosity functions, but not with cluster age. The cluter luminosity value above which globulars are noticeably flattened may differ by a factor of about 100 from galaxy to galaxy. Both in the Galaxy and in M31 globulars with small core radii have a Gaussian distribution over luminosity, whereas clusters with large core radii do not. In the cluster systems surrounding the Galaxy, M31 and NGC 5128 the mean radii of globular clusters was found to increase with the distance from the nucleus. Central galaxies in rich clusters have much higher values for specific globular cluster frequency than do other cluster ellipticals, suggesting that such central galaxies must already have been different from normal ellipticals at the time they were formed

ANALYSIS OF MONTE CARLO SIMULATION SAMPLING TECHNIQUES ON SMALL SIGNAL STABILITY OF WIND GENERATOR- CONNECTED POWER SYSTEM

Directory of Open Access Journals (Sweden)

TEMITOPE RAPHAEL AYODELE

2016-04-01

Full Text Available Monte Carlo simulation using Simple Random Sampling (SRS technique is popularly known for its ability to handle complex uncertainty problems. However, to produce a reasonable result, it requires huge sample size. This makes it to be computationally expensive, time consuming and unfit for online power system applications. In this article, the performance of Latin Hypercube Sampling (LHS technique is explored and compared with SRS in term of accuracy, robustness and speed for small signal stability application in a wind generator-connected power system. The analysis is performed using probabilistic techniques via eigenvalue analysis on two standard networks (Single Machine Infinite Bus and IEEE 16–machine 68 bus test system. The accuracy of the two sampling techniques is determined by comparing their different sample sizes with the IDEAL (conventional. The robustness is determined based on a significant variance reduction when the experiment is repeated 100 times with different sample sizes using the two sampling techniques in turn. Some of the results show that sample sizes generated from LHS for small signal stability application produces the same result as that of the IDEAL values starting from 100 sample size. This shows that about 100 sample size of random variable generated using LHS method is good enough to produce reasonable results for practical purpose in small signal stability application. It is also revealed that LHS has the least variance when the experiment is repeated 100 times compared to SRS techniques. This signifies the robustness of LHS over that of SRS techniques. 100 sample size of LHS produces the same result as that of the conventional method consisting of 50000 sample size. The reduced sample size required by LHS gives it computational speed advantage (about six times over the conventional method.

Evaluating Mixture Modeling for Clustering: Recommendations and Cautions

Science.gov (United States)

Steinley, Douglas; Brusco, Michael J.

2011-01-01

This article provides a large-scale investigation into several of the properties of mixture-model clustering techniques (also referred to as latent class cluster analysis, latent profile analysis, model-based clustering, probabilistic clustering, Bayesian classification, unsupervised learning, and finite mixture models; see Vermunt & Magdison,…

Modified emission-transmission method for determining trace elements in solid samples using the XRF techniques

International Nuclear Information System (INIS)

Poblete, V.; Alvarez, M.; Hermosilla, M.

2000-01-01

This is a study of an analysis of trace elements in medium thick solid samples, by the modified transmission emission method, using the energy dispersion X-ray fluorescence technique (EDXRF). The effects of absorption and reinforcement are the main disadvantages of the EDXRF technique for the quantitative analysis of bigger elements and trace elements in solid samples. The implementation of this method and its application to a variety of samples was carried out using an infinitely thick multi-element white sample that calculates the correction factors by absorbing all the analytes in the sample. The discontinuities in the masic absorption coefficients versus energies association for each element, with medium thick and homogenous samples, are analyzed and corrected. A thorough analysis of the different theoretical and test variables are proven by using real samples, including certified material with known concentration. The simplicity of the calculation method and the results obtained show the method's major precision, with possibilities for the non-destructive routine analysis of different solid samples, using the EDXRF technique (author)

Seasonal comparison of moss bag technique against vertical snow samples for monitoring atmospheric pollution.

Science.gov (United States)

Salo, Hanna; Berisha, Anna-Kaisa; Mäkinen, Joni

2016-03-01

This is the first study seasonally applying Sphagnum papillosum moss bags and vertical snow samples for monitoring atmospheric pollution. Moss bags, exposed in January, were collected together with snow samples by early March 2012 near the Harjavalta Industrial Park in southwest Finland. Magnetic, chemical, scanning electron microscopy-energy dispersive X-ray spectroscopy (SEM-EDX), K-means clustering, and Tomlinson pollution load index (PLI) data showed parallel spatial trends of pollution dispersal for both materials. Results strengthen previous findings that concentrate and slag handling activities were important (dust) emission sources while the impact from Cu-Ni smelter's pipe remained secondary at closer distances. Statistically significant correlations existed between the variables of snow and moss bags. As a summary, both methods work well for sampling and are efficient pollutant accumulators. Moss bags can be used also in winter conditions and they provide more homogeneous and better controlled sampling method than snow samples. Copyright © 2015. Published by Elsevier B.V.

Simultaneous alignment and clustering of peptide data using a Gibbs sampling approach

DEFF Research Database (Denmark)

Andreatta, Massimo; Lund, Ole; Nielsen, Morten

2013-01-01

Motivation: Proteins recognizing short peptide fragments play a central role in cellular signaling. As a result of high-throughput technologies, peptide-binding protein specificities can be studied using large peptide libraries at dramatically lower cost and time. Interpretation of such large...... peptide datasets, however, is a complex task, especially when the data contain multiple receptor binding motifs, and/or the motifs are found at different locations within distinct peptides.Results: The algorithm presented in this article, based on Gibbs sampling, identifies multiple specificities...... of unaligned peptide datasets of variable length. Example applications described in this article include mixtures of binders to different MHC class I and class II alleles, distinct classes of ligands for SH3 domains and sub-specificities of the HLA-A*02:01 molecule.Availability: The Gibbs clustering method...

CLUSTERING TECHNIQUES IN FINANCIAL DATA ANALYSIS APPLICATIONS ON THE U.S. FINANCIAL MARKET

Directory of Open Access Journals (Sweden)

ALEXANDRU BOGEANU

2013-08-01

Full Text Available In the economic and financial analysis, the need to classify companies in terms of categories, thedelimitation of which has to be clear and natural occurs frequently. The differentiation of companies bycategories is performed according to the economic and financial indicators which are associated to the above.The clustering algorithms are a very powerful tool in identifying the classes of companies based on theinformation provided by the indicators associated to them. The last decade imposed to the economic andfinancial practice the use of economic value added as an indicator of synthesis of the entire activity of acompany. Our study uses a sample of 106 companies in four different fields of activity; each company isidentified by: Economic Value Added, Net Income, Current Sales, Equity and Stock Price. Using the ascendinghierarchical classification methods and the partitioning classification methods, as well as Ward’s method and kmeansalgorithm, we identified on the considered sample an information structure consisting of 5 rating classes.

Recent Trends in Microextraction Techniques Employed in Analytical and Bioanalytical Sample Preparation

Directory of Open Access Journals (Sweden)

Abuzar Kabir

2017-12-01

Full Text Available Sample preparation has been recognized as a major step in the chemical analysis workflow. As such, substantial efforts have been made in recent years to simplify the overall sample preparation process. Major focusses of these efforts have included miniaturization of the extraction device; minimizing/eliminating toxic and hazardous organic solvent consumption; eliminating sample pre-treatment and post-treatment steps; reducing the sample volume requirement; reducing extraction equilibrium time, maximizing extraction efficiency etc. All these improved attributes are congruent with the Green Analytical Chemistry (GAC principles. Classical sample preparation techniques such as solid phase extraction (SPE and liquid-liquid extraction (LLE are being rapidly replaced with emerging miniaturized and environmentally friendly techniques such as Solid Phase Micro Extraction (SPME, Stir bar Sorptive Extraction (SBSE, Micro Extraction by Packed Sorbent (MEPS, Fabric Phase Sorptive Extraction (FPSE, and Dispersive Liquid-Liquid Micro Extraction (DLLME. In addition to the development of many new generic extraction sorbents in recent years, a large number of molecularly imprinted polymers (MIPs created using different template molecules have also enriched the large cache of microextraction sorbents. Application of nanoparticles as high-performance extraction sorbents has undoubtedly elevated the extraction efficiency and method sensitivity of modern chromatographic analyses to a new level. Combining magnetic nanoparticles with many microextraction sorbents has opened up new possibilities to extract target analytes from sample matrices containing high volumes of matrix interferents. The aim of the current review is to critically audit the progress of microextraction techniques in recent years, which has indisputably transformed the analytical chemistry practices, from biological and therapeutic drug monitoring to the environmental field; from foods to phyto

Spatial cluster modelling

CERN Document Server

Lawson, Andrew B

2002-01-01

Research has generated a number of advances in methods for spatial cluster modelling in recent years, particularly in the area of Bayesian cluster modelling. Along with these advances has come an explosion of interest in the potential applications of this work, especially in epidemiology and genome research. In one integrated volume, this book reviews the state-of-the-art in spatial clustering and spatial cluster modelling, bringing together research and applications previously scattered throughout the literature. It begins with an overview of the field, then presents a series of chapters that illuminate the nature and purpose of cluster modelling within different application areas, including astrophysics, epidemiology, ecology, and imaging. The focus then shifts to methods, with discussions on point and object process modelling, perfect sampling of cluster processes, partitioning in space and space-time, spatial and spatio-temporal process modelling, nonparametric methods for clustering, and spatio-temporal ...

Neutrosophic Hierarchical Clustering Algoritms

Directory of Open Access Journals (Sweden)

Rıdvan Şahin

2014-03-01

Full Text Available Interval neutrosophic set (INS is a generalization of interval valued intuitionistic fuzzy set (IVIFS, whose the membership and non-membership values of elements consist of fuzzy range, while single valued neutrosophic set (SVNS is regarded as extension of intuitionistic fuzzy set (IFS. In this paper, we extend the hierarchical clustering techniques proposed for IFSs and IVIFSs to SVNSs and INSs respectively. Based on the traditional hierarchical clustering procedure, the single valued neutrosophic aggregation operator, and the basic distance measures between SVNSs, we define a single valued neutrosophic hierarchical clustering algorithm for clustering SVNSs. Then we extend the algorithm to classify an interval neutrosophic data. Finally, we present some numerical examples in order to show the effectiveness and availability of the developed clustering algorithms.

Clustering of experimental data and its application to nuclear data evaluation

International Nuclear Information System (INIS)

Abboud, A.; Rashed, R.; Ibrahim, M.

1997-01-01

A semi-automatic pre-processing technique has been proposed by Iwasaki to classify the experimental data for a reaction into one or a small number of large data groups, called main cluster(s), and to eliminate some data which deviate from the main body of the data. The classifying method is based on a technique like pattern clustering in the information processing domain. Test of the data clustering formed reasonable main clusters for three activation cross-sections. This technique is a helpful tool in the neutron cross-section evaluation. (author). 4 refs, 1 fig., 3 tabs

Development of core sampling technique for ITER Type B radwaste

Energy Technology Data Exchange (ETDEWEB)

Kim, S. G.; Hong, K. P.; Oh, W. H.; Park, M. C.; Jung, S. H.; Ahn, S. B. [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

2016-10-15

Type B radwaste (intermediate level and long lived radioactive waste) imported from ITER vacuum vessel are to be treated and stored in basement of hot cell building. The Type B radwaste treatment process is composed of buffer storage, cutting, sampling/tritium measurement, tritium removal, characterization, pre-packaging, inspection/decontamination, and storage etc. The cut slices of Type B radwaste components generated from cutting process undergo sampling process before and after tritium removal process. The purpose of sampling is to obtain small pieces of samples in order to investigate the tritium content and concentration of Type B radwaste. Core sampling, which is the candidates of sampling technique to be applied to ITER hot cell, is available for not thick (less than 50 mm) metal without use of coolant. Experimented materials were SS316L and CuCrZr in order to simulate ITER Type B radwaste. In core sampling, substantial secondary wastes from cutting chips will be produced unavoidably. Thus, core sampling machine will have to be equipped with disposal system such as suction equipment. Core sampling is considered an unfavorable method for tool wear compared to conventional drilling.

Combining multiple hypothesis testing and affinity propagation clustering leads to accurate, robust and sample size independent classification on gene expression data

Directory of Open Access Journals (Sweden)

Sakellariou Argiris

2012-10-01

Full Text Available Abstract Background A feature selection method in microarray gene expression data should be independent of platform, disease and dataset size. Our hypothesis is that among the statistically significant ranked genes in a gene list, there should be clusters of genes that share similar biological functions related to the investigated disease. Thus, instead of keeping N top ranked genes, it would be more appropriate to define and keep a number of gene cluster exemplars. Results We propose a hybrid FS method (mAP-KL, which combines multiple hypothesis testing and affinity propagation (AP-clustering algorithm along with the Krzanowski & Lai cluster quality index, to select a small yet informative subset of genes. We applied mAP-KL on real microarray data, as well as on simulated data, and compared its performance against 13 other feature selection approaches. Across a variety of diseases and number of samples, mAP-KL presents competitive classification results, particularly in neuromuscular diseases, where its overall AUC score was 0.91. Furthermore, mAP-KL generates concise yet biologically relevant and informative N-gene expression signatures, which can serve as a valuable tool for diagnostic and prognostic purposes, as well as a source of potential disease biomarkers in a broad range of diseases. Conclusions mAP-KL is a data-driven and classifier-independent hybrid feature selection method, which applies to any disease classification problem based on microarray data, regardless of the available samples. Combining multiple hypothesis testing and AP leads to subsets of genes, which classify unknown samples from both, small and large patient cohorts with high accuracy.

3D-Laser-Scanning Technique Applied to Bulk Density Measurements of Apollo Lunar Samples

Science.gov (United States)

Macke, R. J.; Kent, J. J.; Kiefer, W. S.; Britt, D. T.

2015-01-01

In order to better interpret gravimetric data from orbiters such as GRAIL and LRO to understand the subsurface composition and structure of the lunar crust, it is import to have a reliable database of the density and porosity of lunar materials. To this end, we have been surveying these physical properties in both lunar meteorites and Apollo lunar samples. To measure porosity, both grain density and bulk density are required. For bulk density, our group has historically utilized sub-mm bead immersion techniques extensively, though several factors have made this technique problematic for our work with Apollo samples. Samples allocated for measurement are often smaller than optimal for the technique, leading to large error bars. Also, for some samples we were required to use pure alumina beads instead of our usual glass beads. The alumina beads were subject to undesirable static effects, producing unreliable results. Other investigators have tested the use of 3d laser scanners on meteorites for measuring bulk volumes. Early work, though promising, was plagued with difficulties including poor response on dark or reflective surfaces, difficulty reproducing sharp edges, and large processing time for producing shape models. Due to progress in technology, however, laser scanners have improved considerably in recent years. We tested this technique on 27 lunar samples in the Apollo collection using a scanner at NASA Johnson Space Center. We found it to be reliable and more precise than beads, with the added benefit that it involves no direct contact with the sample, enabling the study of particularly friable samples for which bead immersion is not possible

Analysis of pure and malachite green doped polysulfone sample using FT-IR technique

Science.gov (United States)

Nayak, Rashmi J.; Khare, P. K.; Nayak, J. G.

2018-05-01

The sample of pure and malachite green doped Polysulfone in the form of foil was prepared by isothermal immersion technique. For the preparation of pure sample 4 gm of Polysulfone was dissolved in 50 ml of Dimethyl farmamide (DMF) solvent, while for the preparation of doped sample 10 mg, 50 mg and 100 mg Malachite Green was mixed with 4 gm of Polysulfone respectively. For the study of structural characterization of these pure and doped sample, Fourier Transform Infra-Red Spectroscopy (FT-IR) technique was used. This study shows that the intensity of transmittance decreases as the ratio of doping increases in pure polysulfone. The reduction in intensity of transmittance is clearly apparent in the present case more over the bands were broader which indicates towards charge transfer interaction between the donar and acceptor molecule.

Random matrix improved subspace clustering

KAUST Repository

Couillet, Romain

2017-03-06

This article introduces a spectral method for statistical subspace clustering. The method is built upon standard kernel spectral clustering techniques, however carefully tuned by theoretical understanding arising from random matrix findings. We show in particular that our method provides high clustering performance while standard kernel choices provably fail. An application to user grouping based on vector channel observations in the context of massive MIMO wireless communication networks is provided.

Spatial Field Variability Mapping of Rice Crop using Clustering Technique from Space Borne Hyperspectral Data

Science.gov (United States)

Moharana, S.; Dutta, S.

2015-12-01

Precision farming refers to field-specific management of an agricultural crop at a spatial scale with an aim to get the highest achievable yield and to achieve this spatial information on field variability is essential. The difficulty in mapping of spatial variability occurring within an agriculture field can be revealed by employing spectral techniques in hyperspectral imagery rather than multispectral imagery. However an advanced algorithm needs to be developed to fully make use of the rich information content in hyperspectral data. In the present study, potential of hyperspectral data acquired from space platform was examined to map the field variation of paddy crop and its species discrimination. This high dimensional data comprising 242 spectral narrow bands with 30m ground resolution Hyperion L1R product acquired for Assam, India (30th Sept and 3rd Oct, 2014) were allowed for necessary pre-processing steps followed by geometric correction using Hyperion L1GST product. Finally an atmospherically corrected and spatially deduced image consisting of 112 band was obtained. By employing an advanced clustering algorithm, 12 different clusters of spectral waveforms of the crop were generated from six paddy fields for each images. The findings showed that, some clusters were well discriminated representing specific rice genotypes and some clusters were mixed treating as a single rice genotype. As vegetation index (VI) is the best indicator of vegetation mapping, three ratio based VI maps were also generated and unsupervised classification was performed for it. The so obtained 12 clusters of paddy crop were mapped spatially to the derived VI maps. From these findings, the existence of heterogeneity was clearly captured in one of the 6 rice plots (rice plot no. 1) while heterogeneity was observed in rest of the 5 rice plots. The degree of heterogeneous was found more in rice plot no.6 as compared to other plots. Subsequently, spatial variability of paddy field was

Post analysis of AE data of seal plug leakage of NAPS-2 and fatigue crack initiation of three point bend sample using cluster and artificial neural network

International Nuclear Information System (INIS)

Singh, A.K.; Mehta, H.R.; Bhattacharya, S.

2003-01-01

Acoustic Emission data is very weak and passive in nature that leads to a challenging task to separate AE data from noise. This paper illuminates the work done of post analysis of acoustic emission data of seal plug leakage of operating PHWR, NAPS-2, Narora and Fatigue Crack initiation of three-point bend sample using cluster analysis and artificial neural network (ANN). First the known AE data generated in lab by PCB debonding and pencil leak break were analyzed using ANN to get the confidence. After that the AE data acquired by scanning all 306-coolant channels at NAPS-2 was sorted out in five separate clusters for different leakage rate and background noise. Fatigue crack initiation, AE data generated in MSD lab on three-point bend sample was clustered in ten separate clusters in which one cluster was having 98% AE data of crack initiation period noted with the help of travelling microscope but remaining clusters indicating AE data of different sources and noise. The above data was further analysed with self organizing map of Artificial Neural Network. (author)

[Typologies of Madrid's citizens (Spain) at the end-of-life: cluster analysis].

Science.gov (United States)

Ortiz-Gonçalves, Belén; Perea-Pérez, Bernardo; Labajo González, Elena; Albarrán Juan, Elena; Santiago-Sáez, Andrés

2018-03-06

To establish typologies within Madrid's citizens (Spain) with regard to end-of-life by cluster analysis. The SPAD 8 programme was implemented in a sample from a health care centre in the autonomous region of Madrid (Spain). A multiple correspondence analysis technique was used, followed by a cluster analysis to create a dendrogram. A cross-sectional study was made beforehand with the results of the questionnaire. Five clusters stand out. Cluster 1: a group who preferred not to answer numerous questions (5%). Cluster 2: in favour of receiving palliative care and euthanasia (40%). Cluster 3: would oppose assisted suicide and would not ask for spiritual assistance (15%). Cluster 4: would like to receive palliative care and assisted suicide (16%). Cluster 5: would oppose assisted suicide and would ask for spiritual assistance (24%). The following four clusters stood out. Clusters 2 and 4 would like to receive palliative care, euthanasia (2) and assisted suicide (4). Clusters 4 and 5 regularly practiced their faith and their family members did not receive palliative care. Clusters 3 and 5 would be opposed to euthanasia and assisted suicide in particular. Clusters 2, 4 and 5 had not completed an advance directive document (2, 4 and 5). Clusters 2 and 3 seldom practiced their faith. This study could be taken into consideration to improve the quality of end-of-life care choices. Copyright © 2017 SESPAS. Publicado por Elsevier España, S.L.U. All rights reserved.

Structure and bonding in clusters

International Nuclear Information System (INIS)

Kumar, V.

1991-10-01

We review here the recent progress made in the understanding of the electronic and atomic structure of small clusters of s-p bonded materials using the density functional molecular dynamics technique within the local density approximation. Starting with a brief description of the method, results are presented for alkali metal clusters, clusters of divalent metals such as Mg and Be which show a transition from van der Waals or weak chemical bonding to metallic behaviour as the cluster size grows and clusters of Al, Sn and Sb. In the case of semiconductors, we discuss results for Si, Ge and GaAs clusters. Clusters of other materials such as P, C, S, and Se are also briefly discussed. From these and other available results we suggest the possibility of unique structures for the magic clusters. (author). 69 refs, 7 figs, 1 tab

Molecular dynamics computer simulation study of Pdn (n=13, 19, 38 and 55) clusters

International Nuclear Information System (INIS)

Karabacak, M.; Oezcelik, S.; Guevenc, Z.B.

2002-01-01

Using constant-energy molecular dynamics and thermal quenching simulations, we have studied minimum-energy structures and energetics, Pd n (n=13, 19, 38, and 55) clusters employing the Voter and Chen's version of parameterisation of the embedded-atom potential surface. Isomer statistics for Pdn ( n = 13 and 19 ) is obtained from 10000 initial independent configurations, which have been generated along high-energy trajectories (chosen energy values are high enough to melt the clusters). The thermal quenching technique is employed to remove the internal kinetic energy of the clusters. The locally stable isomers are separated from metastable ones. Probabilities belonging to sampling the basins of attractions of each isomers are computed, and then, isomers' energy spectra are analyzed

Electronic and chemical properties of indium clusters

International Nuclear Information System (INIS)

Rayane, D.; Khardi, S.; Tribollet, B.; Broyer, M.; Melinon, P.; Cabaud, B.; Hoareau, A.

1989-01-01

Indium clusters are produced by the inert gas condensation technique. The ionization potentials are found higher for small clusters than for the Indium atom. This is explained by the p character of the bonding as in aluminium. Doubly charge clusters are also observed and fragmentation processes discussed. Finally small Indium clusters 3< n<9 are found very reactive with hydrocarbon. (orig.)

AHIMSA - Ad hoc histogram information measure sensing algorithm for feature selection in the context of histogram inspired clustering techniques

Science.gov (United States)

Dasarathy, B. V.

1976-01-01

An algorithm is proposed for dimensionality reduction in the context of clustering techniques based on histogram analysis. The approach is based on an evaluation of the hills and valleys in the unidimensional histograms along the different features and provides an economical means of assessing the significance of the features in a nonparametric unsupervised data environment. The method has relevance to remote sensing applications.

The C4 clustering algorithm: Clusters of galaxies in the Sloan Digital Sky Survey

Energy Technology Data Exchange (ETDEWEB)

Miller, Christopher J.; Nichol, Robert; Reichart, Dan; Wechsler, Risa H.; Evrard, August; Annis, James; McKay, Timothy; Bahcall, Neta; Bernardi, Mariangela; Boehringer,; Connolly, Andrew; Goto, Tomo; Kniazev, Alexie; Lamb, Donald; Postman, Marc; Schneider, Donald; Sheth, Ravi; Voges, Wolfgang; /Cerro-Tololo InterAmerican Obs. /Portsmouth U.,

2005-03-01

We present the ''C4 Cluster Catalog'', a new sample of 748 clusters of galaxies identified in the spectroscopic sample of the Second Data Release (DR2) of the Sloan Digital Sky Survey (SDSS). The C4 cluster-finding algorithm identifies clusters as overdensities in a seven-dimensional position and color space, thus minimizing projection effects that have plagued previous optical cluster selection. The present C4 catalog covers {approx}2600 square degrees of sky and ranges in redshift from z = 0.02 to z = 0.17. The mean cluster membership is 36 galaxies (with redshifts) brighter than r = 17.7, but the catalog includes a range of systems, from groups containing 10 members to massive clusters with over 200 cluster members with redshifts. The catalog provides a large number of measured cluster properties including sky location, mean redshift, galaxy membership, summed r-band optical luminosity (L{sub r}), velocity dispersion, as well as quantitative measures of substructure and the surrounding large-scale environment. We use new, multi-color mock SDSS galaxy catalogs, empirically constructed from the {Lambda}CDM Hubble Volume (HV) Sky Survey output, to investigate the sensitivity of the C4 catalog to the various algorithm parameters (detection threshold, choice of passbands and search aperture), as well as to quantify the purity and completeness of the C4 cluster catalog. These mock catalogs indicate that the C4 catalog is {approx_equal}90% complete and 95% pure above M{sub 200} = 1 x 10{sup 14} h{sup -1}M{sub {circle_dot}} and within 0.03 {le} z {le} 0.12. Using the SDSS DR2 data, we show that the C4 algorithm finds 98% of X-ray identified clusters and 90% of Abell clusters within 0.03 {le} z {le} 0.12. Using the mock galaxy catalogs and the full HV dark matter simulations, we show that the L{sub r} of a cluster is a more robust estimator of the halo mass (M{sub 200}) than the galaxy line-of-sight velocity dispersion or the richness of the cluster

Separation Techniques for Quantification of Radionuclides in Environmental Samples

Directory of Open Access Journals (Sweden)

Dusan Galanda

2009-01-01

Full Text Available The reliable and quantitative measurement of radionuclides is important in order to determine environmental quality and radiation safety, and to monitor regulatory compliance. We examined soil samples from Podunajske Biskupice, near the city of Bratislava in the Slovak Republic, for the presence of several natural (238U, 232Th, 40K and anthropogenic (137Cs, 90Sr, 239Pu, 240Pu, 241Am radionuclides. The area is adjacent to a refinery and hazardous waste processing center, as well as the municipal incinerator plant, and so might possess an unusually high level of ecotoxic metals. We found that the levels of both naturally occurring and anthropogenic radionuclides fell within the expected ranges, indicating that these facilities pose no radiological threat to the local environment. During the course of our analysis, we modified existing techniques in order to allow us to handle the unusually large and complex samples that were needed to determine the levels of 239Pu, 240Pu, and 241Am activity. We also rated three commercial techniques for the separation of 90Sr from aqueous solutions and found that two of them, AnaLig Sr-01 and Empore Extraction Disks, were suitable for the quantitative and reliable separation of 90Sr, while the third, Sr-Spec Resin, was less so. The main criterion in evaluating these methods was the chemical recovery of 90Sr, which was less than we had expected. We also considered speed of separation and additional steps needed to prepare the sample for separation.

The x-ray luminous galaxy cluster population at 0.9 < z ≲ 1.6 as revealed by the XMM-Newton Distant Cluster Project

International Nuclear Information System (INIS)

Fassbender, R; Böhringer, H; Nastasi, A; Šuhada, R; Mühlegger, M; Mohr, J J; Pierini, D; De Hoon, A; Kohnert, J; Lamer, G; Schwope, A D; Pratt, G W; Quintana, H; Rosati, P; Santos, J S

2011-01-01

We present the largest sample to date of spectroscopically confirmed x-ray luminous high-redshift galaxy clusters comprising 22 systems in the range 0.9 2 of non-contiguous deep archival XMM-Newton coverage, of which 49.4 deg 2 are part of the core survey with a quantifiable selection function and 17.7 deg 2 are classified as ‘gold’ coverage as the starting point for upcoming cosmological applications. Distant cluster candidates were followed up with moderately deep optical and near-infrared imaging in at least two bands to photometrically identify the cluster galaxy populations and obtain redshift estimates based on the colors of simple stellar population models. We test and calibrate the most promising redshift estimation techniques based on the R-z and z-H colors for efficient distant cluster identifications and find a good redshift accuracy performance of the z-H color out to at least z ∼ 1.5, while the redshift evolution of the R-z color leads to increasingly large uncertainties at z ≳ 0.9. Photometrically identified high-z systems are spectroscopically confirmed with VLT/FORS 2 with a minimum of three concordant cluster member redshifts. We present first details of two newly identified clusters, XDCP J0338.5+0029 at z = 0.916 and XDCP J0027.2+1714 at z = 0.959, and investigate the x-ray properties of SpARCS J003550-431224 at z = 1.335, which shows evidence for ongoing major merger activity along the line-of-sight. We provide x-ray properties and luminosity-based total mass estimates for the full sample of 22 high-z clusters, of which 17 are at z ⩾ 1.0 and seven populate the highest redshift bin at z > 1.3. The median system mass of the sample is M 200 ≃ 2 × 10 14 M ⊙ , while the probed mass range for the distant clusters spans approximately (0.7-7) × 10 14 M ⊙ . The majority (>70%) of the x-ray selected clusters show rather regular x-ray morphologies, albeit in most cases with a discernible elongation along one axis. In contrast to

Baryon Content in a Sample of 91 Galaxy Clusters Selected by the South Pole Telescope at 0.2 < z < 1.25

Science.gov (United States)

Chiu, I.; Mohr, J. J.; McDonald, M.; Bocquet, S.; Desai, S.; Klein, M.; Israel, H.; Ashby, M. L. N.; Stanford, A.; Benson, B. A.; Brodwin, M.; Abbott, T. M. C.; Abdalla, F. B.; Allam, S.; Annis, J.; Bayliss, M.; Benoit-Lévy, A.; Bertin, E.; Bleem, L.; Brooks, D.; Buckley-Geer, E.; Bulbul, E.; Capasso, R.; Carlstrom, J. E.; Rosell, A. Carnero; Carretero, J.; Castander, F. J.; Cunha, C. E.; D'Andrea, C. B.; da Costa, L. N.; Davis, C.; Diehl, H. T.; Dietrich, J. P.; Doel, P.; Drlica-Wagner, A.; Eifler, T. F.; Evrard, A. E.; Flaugher, B.; García-Bellido, J.; Garmire, G.; Gaztanaga, E.; Gerdes, D. W.; Gonzalez, A.; Gruen, D.; Gruendl, R. A.; Gschwend, J.; Gupta, N.; Gutierrez, G.; Hlavacek-L, J.; Honscheid, K.; James, D. J.; Jeltema, T.; Kraft, R.; Krause, E.; Kuehn, K.; Kuhlmann, S.; Kuropatkin, N.; Lahav, O.; Lima, M.; Maia, M. A. G.; Marshall, J. L.; Melchior, P.; Menanteau, F.; Miquel, R.; Murray, S.; Nord, B.; Ogando, R. L. C.; Plazas, A. A.; Rapetti, D.; Reichardt, C. L.; Romer, A. K.; Roodman, A.; Sanchez, E.; Saro, A.; Scarpine, V.; Schindler, R.; Schubnell, M.; Sharon, K.; Smith, R. C.; Smith, M.; Soares-Santos, M.; Sobreira, F.; Stalder, B.; Stern, C.; Strazzullo, V.; Suchyta, E.; Swanson, M. E. C.; Tarle, G.; Vikram, V.; Walker, A. R.; Weller, J.; Zhang, Y.

2018-05-01

We estimate total mass (M500), intracluster medium (ICM) mass (MICM) and stellar mass (M⋆) in a Sunyaev-Zel'dovich effect (SZE) selected sample of 91 galaxy clusters with masses M500 ≳ 2.5 × 1014M⊙ and redshift 0.2 baryonic mass and the cold baryonic fraction with cluster halo mass and redshift. We find significant departures from self-similarity in the mass scaling for all quantities, while the redshift trends are all statistically consistent with zero, indicating that the baryon content of clusters at fixed mass has changed remarkably little over the past ≈9 Gyr. We compare our results to the mean baryon fraction (and the stellar mass fraction) in the field, finding that these values lie above (below) those in cluster virial regions in all but the most massive clusters at low redshift. Using a simple model of the matter assembly of clusters from infalling groups with lower masses and from infalling material from the low density environment or field surrounding the parent halos, we show that the measured mass trends without strong redshift trends in the stellar mass scaling relation could be explained by a mass and redshift dependent fractional contribution from field material. Similar analyses of the ICM and baryon mass scaling relations provide evidence for the so-called "missing baryons" outside cluster virial regions.

Performance of small cluster surveys and the clustered LQAS design to estimate local-level vaccination coverage in Mali.

Science.gov (United States)

Minetti, Andrea; Riera-Montes, Margarita; Nackers, Fabienne; Roederer, Thomas; Koudika, Marie Hortense; Sekkenes, Johanne; Taconet, Aurore; Fermon, Florence; Touré, Albouhary; Grais, Rebecca F; Checchi, Francesco

2012-10-12

Estimation of vaccination coverage at the local level is essential to identify communities that may require additional support. Cluster surveys can be used in resource-poor settings, when population figures are inaccurate. To be feasible, cluster samples need to be small, without losing robustness of results. The clustered LQAS (CLQAS) approach has been proposed as an alternative, as smaller sample sizes are required. We explored (i) the efficiency of cluster surveys of decreasing sample size through bootstrapping analysis and (ii) the performance of CLQAS under three alternative sampling plans to classify local VC, using data from a survey carried out in Mali after mass vaccination against meningococcal meningitis group A. VC estimates provided by a 10 × 15 cluster survey design were reasonably robust. We used them to classify health areas in three categories and guide mop-up activities: i) health areas not requiring supplemental activities; ii) health areas requiring additional vaccination; iii) health areas requiring further evaluation. As sample size decreased (from 10 × 15 to 10 × 3), standard error of VC and ICC estimates were increasingly unstable. Results of CLQAS simulations were not accurate for most health areas, with an overall risk of misclassification greater than 0.25 in one health area out of three. It was greater than 0.50 in one health area out of two under two of the three sampling plans. Small sample cluster surveys (10 × 15) are acceptably robust for classification of VC at local level. We do not recommend the CLQAS method as currently formulated for evaluating vaccination programmes.

Application of cluster analysis and unsupervised learning to multivariate tissue characterization

International Nuclear Information System (INIS)

Momenan, R.; Insana, M.F.; Wagner, R.F.; Garra, B.S.; Loew, M.H.

1987-01-01

This paper describes a procedure for classifying tissue types from unlabeled acoustic measurements (data type unknown) using unsupervised cluster analysis. These techniques are being applied to unsupervised ultrasonic image segmentation and tissue characterization. The performance of a new clustering technique is measured and compared with supervised methods, such as a linear Bayes classifier. In these comparisons two objectives are sought: a) How well does the clustering method group the data?; b) Do the clusters correspond to known tissue classes? The first question is investigated by a measure of cluster similarity and dispersion. The second question involves a comparison with a supervised technique using labeled data

The expression of Mirc1/Mir17-92 cluster in sputum samples correlates with pulmonary exacerbations in cystic fibrosis patients.

Science.gov (United States)

Krause, Kathrin; Kopp, Benjamin T; Tazi, Mia F; Caution, Kyle; Hamilton, Kaitlin; Badr, Asmaa; Shrestha, Chandra; Tumin, Dmitry; Hayes, Don; Robledo-Avila, Frank; Hall-Stoodley, Luanne; Klamer, Brett G; Zhang, Xiaoli; Partida-Sanchez, Santiago; Parinandi, Narasimham L; Kirkby, Stephen E; Dakhlallah, Duaa; McCoy, Karen S; Cormet-Boyaka, Estelle; Amer, Amal O

2017-12-11

Cystic fibrosis (CF) is a multi-organ disorder characterized by chronic sino-pulmonary infections and inflammation. Many patients with CF suffer from repeated pulmonary exacerbations that are predictors of worsened long-term morbidity and mortality. There are no reliable markers that associate with the onset or progression of an exacerbation or pulmonary deterioration. Previously, we found that the Mirc1/Mir17-92a cluster which is comprised of 6 microRNAs (Mirs) is highly expressed in CF mice and negatively regulates autophagy which in turn improves CF transmembrane conductance regulator (CFTR) function. Therefore, here we sought to examine the expression of individual Mirs within the Mirc1/Mir17-92 cluster in human cells and biological fluids and determine their role as biomarkers of pulmonary exacerbations and response to treatment. Mirc1/Mir17-92 cluster expression was measured in human CF and non-CF plasma, blood-derived neutrophils, and sputum samples. Values were correlated with pulmonary function, exacerbations and use of CFTR modulators. Mirc1/Mir17-92 cluster expression was not significantly elevated in CF neutrophils nor plasma when compared to the non-CF cohort. Cluster expression in CF sputum was significantly higher than its expression in plasma. Elevated CF sputum Mirc1/Mir17-92 cluster expression positively correlated with pulmonary exacerbations and negatively correlated with lung function. Patients with CF undergoing treatment with the CFTR modulator Ivacaftor/Lumacaftor did not demonstrate significant change in the expression Mirc1/Mir17-92 cluster after six months of treatment. Mirc1/Mir17-92 cluster expression is a promising biomarker of respiratory status in patients with CF including pulmonary exacerbation. Published by Elsevier B.V.

Accelerated Solvent Extraction: An Innovative Sample Extraction Technique for Natural Products

International Nuclear Information System (INIS)

Hazlina Ahmad Hassali; Azfar Hanif Abd Aziz; Rosniza Razali

2015-01-01

Accelerated solvent extraction (ASE) is one of the novel techniques that have been developed for the extraction of phytochemicals from plants in order to shorten the extraction time, decrease the solvent consumption, increase the extraction yield and enhance the quality of extracts. This technique combines elevated temperatures and pressure with liquid solvents. This paper gives a brief overview of accelerated solvent extraction technique for sample preparation and its application to the extraction of natural products. Through practical examples, the effects of operational parameters such as temperature, volume of solvent used, extraction time and extraction yields on the performance of ASE are discussed. It is demonstrated that ASE technique allows reduced solvent consumption and shorter extraction time, while the extraction yields are even higher than those obtained with conventional methods. (author)

Clustering with Obstacles in Spatial Databases

OpenAIRE

El-Zawawy, Mohamed A.; El-Sharkawi, Mohamed E.

2009-01-01

Clustering large spatial databases is an important problem, which tries to find the densely populated regions in a spatial area to be used in data mining, knowledge discovery, or efficient information retrieval. However most algorithms have ignored the fact that physical obstacles such as rivers, lakes, and highways exist in the real world and could thus affect the result of the clustering. In this paper, we propose CPO, an efficient clustering technique to solve the problem of clustering in ...

Properties of an ionised-cluster beam from a vaporised-cluster ion source

International Nuclear Information System (INIS)

Takagi, T.; Yamada, I.; Sasaki, A.

1978-01-01

A new type of ion source vaporised-metal cluster ion source, has been developed for deposition and epitaxy. A cluster consisting of 10 2 to 10 3 atoms coupled loosely together is formed by adiabatic expansion ejecting the vapour of materials into a high-vacuum region through the nozzle of a heated crucible. The clusters are ionised by electron bombardment and accelerated with neutral clusters toward a substrate. In this paper, mechanisms of cluster formation experimental results of the cluster size (atoms/cluster) and its distribution, and characteristics of the cluster ion beams are reported. The size is calculated from the kinetic equation E = (1/2)mNVsub(ej) 2 , where E is the cluster beam energy, Vsub(ej) is the ejection velocity, m is the mass of atom and N is the cluster size. The energy and the velocity of the cluster are measured by an electrostatic 127 0 energy analyser and a rotating disc system, respectively. The cluster size obtained for Ag is about 5 x 10 2 to 2 x 10 3 atoms. The retarding potential method is used to confirm the results for Ag. The same dependence on cluster size for metals such as Ag, Cu and Pb has been obtained in previous experiments. In the cluster state the cluster ion beam is easily produced by electron bombardment. About 50% of ionised clusters are obtained under typical operation conditions, because of the large ionisation cross sections of the clusters. To obtain a uniform spatial distribution, the ionising electrode system is also discussed. The new techniques are termed ionised-cluster beam deposition (ICBD) and epitaxy (ICBE). (author)

Multiscale visual quality assessment for cluster analysis with self-organizing maps

Science.gov (United States)

Bernard, Jürgen; von Landesberger, Tatiana; Bremm, Sebastian; Schreck, Tobias

2011-01-01

Cluster analysis is an important data mining technique for analyzing large amounts of data, reducing many objects to a limited number of clusters. Cluster visualization techniques aim at supporting the user in better understanding the characteristics and relationships among the found clusters. While promising approaches to visual cluster analysis already exist, these usually fall short of incorporating the quality of the obtained clustering results. However, due to the nature of the clustering process, quality plays an important aspect, as for most practical data sets, typically many different clusterings are possible. Being aware of clustering quality is important to judge the expressiveness of a given cluster visualization, or to adjust the clustering process with refined parameters, among others. In this work, we present an encompassing suite of visual tools for quality assessment of an important visual cluster algorithm, namely, the Self-Organizing Map (SOM) technique. We define, measure, and visualize the notion of SOM cluster quality along a hierarchy of cluster abstractions. The quality abstractions range from simple scalar-valued quality scores up to the structural comparison of a given SOM clustering with output of additional supportive clustering methods. The suite of methods allows the user to assess the SOM quality on the appropriate abstraction level, and arrive at improved clustering results. We implement our tools in an integrated system, apply it on experimental data sets, and show its applicability.

The Effect of Roundtable and Clustering Teaching Techniques and Students' Personal Traits on Students' Achievement in Descriptive Writing

Science.gov (United States)

Sinaga, Megawati

2017-01-01

The Objectives of this paper as an experimental research was to investigate the effect of Roundtable and Clustering teaching techniques and students' personal traits on students' achievement in descriptive writing. The students in grade ix of SMP Negeri 2 Pancurbatu 2016/2017 school academic year were chose as the population of this research. The…

MASS CALIBRATION AND COSMOLOGICAL ANALYSIS OF THE SPT-SZ GALAXY CLUSTER SAMPLE USING VELOCITY DISPERSION σ v AND X-RAY Y X MEASUREMENTS

International Nuclear Information System (INIS)