WorldWideScience

Sample records for traditional clustering methods

  1. Comparison Of Keyword Based Clustering Of Web Documents By Using Openstack 4j And By Traditional Method

    Directory of Open Access Journals (Sweden)

    Shiza Anand

    2015-08-01

    Full Text Available As the number of hypertext documents are increasing continuously day by day on world wide web. Therefore clustering methods will be required to bind documents into the clusters repositories according to the similarity lying between the documents. Various clustering methods exist such as Hierarchical Based K-means Fuzzy Logic Based Centroid Based etc. These keyword based clustering methods takes much more amount of time for creating containers and putting documents in their respective containers. These traditional methods use File Handling techniques of different programming languages for creating repositories and transferring web documents into these containers. In contrast openstack4j SDK is a new technique for creating containers and shifting web documents into these containers according to the similarity in much more less amount of time as compared to the traditional methods. Another benefit of this technique is that this SDK understands and reads all types of files such as jpg html pdf doc etc. This paper compares the time required for clustering of documents by using openstack4j and by traditional methods and suggests various search engines to adopt this technique for clustering so that they give result to the user querries in less amount of time.

  2. Determination of genetic structure of germplasm collections: are traditional hierarchical clustering methods appropriate for molecular marker data?

    NARCIS (Netherlands)

    Odong, T.L.; Heerwaarden, van J.; Jansen, J.; Hintum, van T.J.L.; Eeuwijk, van F.A.

    2011-01-01

    Despite the availability of newer approaches, traditional hierarchical clustering remains very popular in genetic diversity studies in plants. However, little is known about its suitability for molecular marker data. We studied the performance of traditional hierarchical clustering techniques using

  3. Effects of cluster vs. traditional plyometric training sets on maximal-intensity exercise performance

    Directory of Open Access Journals (Sweden)

    Abbas Asadi

    2016-01-01

    Conclusions: Although both plyometric training methods improved lower body maximal-intensity exercise performance, the traditional sets methods resulted in greater adaptations in sprint performance, while the cluster sets method resulted in greater jump and agility adaptations.

  4. Document clustering methods, document cluster label disambiguation methods, document clustering apparatuses, and articles of manufacture

    Science.gov (United States)

    Sanfilippo, Antonio [Richland, WA; Calapristi, Augustin J [West Richland, WA; Crow, Vernon L [Richland, WA; Hetzler, Elizabeth G [Kennewick, WA; Turner, Alan E [Kennewick, WA

    2009-12-22

    Document clustering methods, document cluster label disambiguation methods, document clustering apparatuses, and articles of manufacture are described. In one aspect, a document clustering method includes providing a document set comprising a plurality of documents, providing a cluster comprising a subset of the documents of the document set, using a plurality of terms of the documents, providing a cluster label indicative of subject matter content of the documents of the cluster, wherein the cluster label comprises a plurality of word senses, and selecting one of the word senses of the cluster label.

  5. Semi-supervised clustering methods.

    Science.gov (United States)

    Bair, Eric

    2013-01-01

    Cluster analysis methods seek to partition a data set into homogeneous subgroups. It is useful in a wide variety of applications, including document processing and modern genetics. Conventional clustering methods are unsupervised, meaning that there is no outcome variable nor is anything known about the relationship between the observations in the data set. In many situations, however, information about the clusters is available in addition to the values of the features. For example, the cluster labels of some observations may be known, or certain observations may be known to belong to the same cluster. In other cases, one may wish to identify clusters that are associated with a particular outcome variable. This review describes several clustering algorithms (known as "semi-supervised clustering" methods) that can be applied in these situations. The majority of these methods are modifications of the popular k-means clustering method, and several of them will be described in detail. A brief description of some other semi-supervised clustering algorithms is also provided.

  6. Semi-supervised clustering methods

    Science.gov (United States)

    Bair, Eric

    2013-01-01

    Cluster analysis methods seek to partition a data set into homogeneous subgroups. It is useful in a wide variety of applications, including document processing and modern genetics. Conventional clustering methods are unsupervised, meaning that there is no outcome variable nor is anything known about the relationship between the observations in the data set. In many situations, however, information about the clusters is available in addition to the values of the features. For example, the cluster labels of some observations may be known, or certain observations may be known to belong to the same cluster. In other cases, one may wish to identify clusters that are associated with a particular outcome variable. This review describes several clustering algorithms (known as “semi-supervised clustering” methods) that can be applied in these situations. The majority of these methods are modifications of the popular k-means clustering method, and several of them will be described in detail. A brief description of some other semi-supervised clustering algorithms is also provided. PMID:24729830

  7. CLASSIFICATION OF IRANIAN NURSES ACCORDING TO THEIR MENTAL HEALTH OUTCOMES USING GHQ-12 QUESTIONNAIRE: A COMPARISON BETWEEN LATENT CLASS ANALYSIS AND K-MEANS CLUSTERING WITH TRADITIONAL SCORING METHOD.

    Science.gov (United States)

    Jamali, Jamshid; Ayatollahi, Seyyed Mohammad Taghi

    2015-10-01

    Nurses constitute the most providers of health care systems. Their mental health can affect the quality of services and patients' satisfaction. General Health Questionnaire (GHQ-12) is a general screening tool used to detect mental disorders. Scoring method and determining thresholds for this questionnaire are debatable and the cut-off points can vary from sample to sample. This study was conducted to estimate the prevalence of mental disorders among Iranian nurses using GHQ-12 and also compare Latent Class Analysis (LCA) and K-means clustering with traditional scoring method. A cross-sectional study was carried out in Fars and Bushehr provinces of southern Iran in 2014. Participants were 771 Iranian nurses, who filled out the GHQ-12 questionnaire. Traditional scoring method, LCA and K-means were used to estimate the prevalence of mental disorder among Iranian nurses. Cohen's kappa statistic was applied to assess the agreement between the LCA and K-means with traditional scoring method of GHQ-12. The nurses with mental disorder by scoring method, LCA and K-mean were 36.3% (n=280), 32.2% (n=248), and 26.5% (n=204), respectively. LCA and logistic regression revealed that the prevalence of mental disorder in females was significantly higher than males. Mental disorder in nurses was in a medium level compared to other people living in Iran. There was a little difference between prevalence of mental disorder estimated by scoring method, K-means and LCA. According to the advantages of LCA than K-means and different results in scoring method, we suggest LCA for classification of Iranian nurses according to their mental health outcomes using GHQ-12 questionnaire.

  8. Effects of cluster vs. traditional plyometric training sets on maximal-intensity exercise performance.

    Science.gov (United States)

    Asadi, Abbas; Ramírez-Campillo, Rodrigo

    2016-01-01

    The aim of this study was to compare the effects of 6-week cluster versus traditional plyometric training sets on jumping ability, sprint and agility performance. Thirteen college students were assigned to a cluster sets group (N=6) or traditional sets group (N=7). Both training groups completed the same training program. The traditional group completed five sets of 20 repetitions with 2min of rest between sets each session, while the cluster group completed five sets of 20 [2×10] repetitions with 30/90-s rest each session. Subjects were evaluated for countermovement jump (CMJ), standing long jump (SLJ), t test, 20-m and 40-m sprint test performance before and after the intervention. Both groups had similar improvements (Psets methods resulted in greater adaptations in sprint performance, while the cluster sets method resulted in greater jump and agility adaptations. Copyright © 2016 The Lithuanian University of Health Sciences. Production and hosting by Elsevier Urban & Partner Sp. z o.o. All rights reserved.

  9. Clustering methods for the optimization of atomic cluster structure

    Science.gov (United States)

    Bagattini, Francesco; Schoen, Fabio; Tigli, Luca

    2018-04-01

    In this paper, we propose a revised global optimization method and apply it to large scale cluster conformation problems. In the 1990s, the so-called clustering methods were considered among the most efficient general purpose global optimization techniques; however, their usage has quickly declined in recent years, mainly due to the inherent difficulties of clustering approaches in large dimensional spaces. Inspired from the machine learning literature, we redesigned clustering methods in order to deal with molecular structures in a reduced feature space. Our aim is to show that by suitably choosing a good set of geometrical features coupled with a very efficient descent method, an effective optimization tool is obtained which is capable of finding, with a very high success rate, all known putative optima for medium size clusters without any prior information, both for Lennard-Jones and Morse potentials. The main result is that, beyond being a reliable approach, the proposed method, based on the idea of starting a computationally expensive deep local search only when it seems worth doing so, is capable of saving a huge amount of searches with respect to an analogous algorithm which does not employ a clustering phase. In this paper, we are not claiming the superiority of the proposed method compared to specific, refined, state-of-the-art procedures, but rather indicating a quite straightforward way to save local searches by means of a clustering scheme working in a reduced variable space, which might prove useful when included in many modern methods.

  10. Moving beyond Traditional Methods of Survey Validation

    Science.gov (United States)

    Maul, Andrew

    2017-01-01

    In his focus article, "Rethinking Traditional Methods of Survey Validation," published in this issue of "Measurement: Interdisciplinary Research and Perspectives," Andrew Maul wrote that it is commonly believed that self-report, survey-based instruments can be used to measure a wide range of psychological attributes, such as…

  11. CCM: A Text Classification Method by Clustering

    DEFF Research Database (Denmark)

    Nizamani, Sarwat; Memon, Nasrullah; Wiil, Uffe Kock

    2011-01-01

    In this paper, a new Cluster based Classification Model (CCM) for suspicious email detection and other text classification tasks, is presented. Comparative experiments of the proposed model against traditional classification models and the boosting algorithm are also discussed. Experimental results...... show that the CCM outperforms traditional classification models as well as the boosting algorithm for the task of suspicious email detection on terrorism domain email dataset and topic categorization on the Reuters-21578 and 20 Newsgroups datasets. The overall finding is that applying a cluster based...

  12. Survey Methods, Traditional, Public Opinion Polling

    DEFF Research Database (Denmark)

    Elmelund-Præstekær, Christian; Hopmann, David Nicolas; Pedersen, Rasmus Tue

    2017-01-01

    Traditional public opinion polls are surveys in which a random sample of a given population is asked questions about their attitudes, knowledge, or behavior. If conducted properly, the answers from such surveys are approximately representative of the entire population. Traditional public opinion...... polling is typically based on four different methods of data gathering, or combinations hereof: face-to-face, postal surveys, phone surveys, and web surveys. Given that opinion polls are based on a sample, we cannot be sure that the sample reflects public opinion perfectly, however—even if randomness...... is perfect. Moreover, responses may be highly dependent on the contextual information provided with the question. Also, it may be difficult to capture past or complex causes of attitudes or behavior. In short, surveys are a precise way of measuring public opinion, but they do not come without challenges....

  13. Upgrading traditional technologies in small-scale industrial clusters: producer-driven innovation adoption in Indonesia

    NARCIS (Netherlands)

    Rietveld, Piet; Sandee, Henry

    1997-01-01

    This paper discusses processes of technological change in the tile cluster in the village Karanggeneng in Central Java, Indonesia. A growing number ofproducers in this cluster have switched from traditional kiln to so-called handpress production. We will analyze the processes of innovation adoption

  14. Comparing the performance of biomedical clustering methods

    DEFF Research Database (Denmark)

    Wiwie, Christian; Baumbach, Jan; Röttger, Richard

    2015-01-01

    expression to protein domains. Performance was judged on the basis of 13 common cluster validity indices. We developed a clustering analysis platform, ClustEval (http://clusteval.mpi-inf.mpg.de), to promote streamlined evaluation, comparison and reproducibility of clustering results in the future......Identifying groups of similar objects is a popular first step in biomedical data analysis, but it is error-prone and impossible to perform manually. Many computational methods have been developed to tackle this problem. Here we assessed 13 well-known methods using 24 data sets ranging from gene....... This allowed us to objectively evaluate the performance of all tools on all data sets with up to 1,000 different parameter sets each, resulting in a total of more than 4 million calculated cluster validity indices. We observed that there was no universal best performer, but on the basis of this wide...

  15. The polarizable embedding coupled cluster method

    DEFF Research Database (Denmark)

    Sneskov, Kristian; Schwabe, Tobias; Kongsted, Jacob

    2011-01-01

    We formulate a new combined quantum mechanics/molecular mechanics (QM/MM) method based on a self-consistent polarizable embedding (PE) scheme. For the description of the QM region, we apply the popular coupled cluster (CC) method detailing the inclusion of electrostatic and polarization effects...

  16. METHOD OF CONSTRUCTION OF GENETIC DATA CLUSTERS

    Directory of Open Access Journals (Sweden)

    N. A. Novoselova

    2016-01-01

    Full Text Available The paper presents a method of construction of genetic data clusters (functional modules using the randomized matrices. To build the functional modules the selection and analysis of the eigenvalues of the gene profiles correlation matrix is performed. The principal components, corresponding to the eigenvalues, which are significantly different from those obtained for the randomly generated correlation matrix, are used for the analysis. Each selected principal component forms gene cluster. In a comparative experiment with the analogs the proposed method shows the advantage in allocating statistically significant different-sized clusters, the ability to filter non- informative genes and to extract the biologically interpretable functional modules matching the real data structure.

  17. Radionuclide identification using subtractive clustering method

    International Nuclear Information System (INIS)

    Farias, Marcos Santana; Mourelle, Luiza de Macedo

    2011-01-01

    Radionuclide identification is crucial to planning protective measures in emergency situations. This paper presents the application of a method for a classification system of radioactive elements with a fast and efficient response. To achieve this goal is proposed the application of subtractive clustering algorithm. The proposed application can be implemented in reconfigurable hardware, a flexible medium to implement digital hardware circuits. (author)

  18. A Multidimensional and Multimembership Clustering Method for Social Networks and Its Application in Customer Relationship Management

    Directory of Open Access Journals (Sweden)

    Peixin Zhao

    2013-01-01

    Full Text Available Community detection in social networks plays an important role in cluster analysis. Many traditional techniques for one-dimensional problems have been proven inadequate for high-dimensional or mixed type datasets due to the data sparseness and attribute redundancy. In this paper we propose a graph-based clustering method for multidimensional datasets. This novel method has two distinguished features: nonbinary hierarchical tree and the multi-membership clusters. The nonbinary hierarchical tree clearly highlights meaningful clusters, while the multimembership feature may provide more useful service strategies. Experimental results on the customer relationship management confirm the effectiveness of the new method.

  19. Relevance of traditional methods of conflict resolution in the justice ...

    African Journals Online (AJOL)

    The traditional methods of African conflict resolution have long existed and are deeply rooted in the customs and traditions of the peoples of Africa. These methods are geared towards maintaining harmonious and peaceful coexistence in the community. Colonialism introduced the modern justice system, which dominated ...

  20. Recent advances in coupled-cluster methods

    CERN Document Server

    Bartlett, Rodney J

    1997-01-01

    Today, coupled-cluster (CC) theory has emerged as the most accurate, widely applicable approach for the correlation problem in molecules. Furthermore, the correct scaling of the energy and wavefunction with size (i.e. extensivity) recommends it for studies of polymers and crystals as well as molecules. CC methods have also paid dividends for nuclei, and for certain strongly correlated systems of interest in field theory.In order for CC methods to have achieved this distinction, it has been necessary to formulate new, theoretical approaches for the treatment of a variety of essential quantities

  1. 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.

  2. Hybrid Tracking Algorithm Improvements and Cluster Analysis Methods.

    Science.gov (United States)

    1982-02-26

    UPGMA ), and Ward’s method. Ling’s papers describe a (k,r) clustering method. Each of these methods have individual characteristics which make them...Reference 7), UPGMA is probably the most frequently used clustering strategy. UPGMA tries to group new points into an existing cluster by using an

  3. Reliability studies of diagnostic methods in Indian traditional Ayurveda medicine

    DEFF Research Database (Denmark)

    Kurande, Vrinda Hitendra; Waagepetersen, Rasmus; Toft, Egon

    2013-01-01

    as prakriti classification), method development (pulse diagnosis), quality assurance for diagnosis and treatment and in the conduct of clinical studies. Several reliability studies are conducted in western medicine. The investigation of the reliability of traditional Chinese, Japanese and Sasang medicine...

  4. Traditional methods of social control in Afikpo north local ...

    African Journals Online (AJOL)

    Traditional methods of social control in Afikpo north local government area, Ebonyi state south eastern Nigeria. ... Journal of Religion and Human Relations ... simple percentage was used in presenting and interpreting the quantitative data.

  5. MANNER OF STOCKS SORTING USING CLUSTER ANALYSIS METHODS

    Directory of Open Access Journals (Sweden)

    Jana Halčinová

    2014-06-01

    Full Text Available The aim of the present article is to show the possibility of using the methods of cluster analysis in classification of stocks of finished products. Cluster analysis creates groups (clusters of finished products according to similarity in demand i.e. customer requirements for each product. Manner stocks sorting of finished products by clusters is described a practical example. The resultants clusters are incorporated into the draft layout of the distribution warehouse.

  6. Cluster temperature. Methods for its measurement and stabilization

    International Nuclear Information System (INIS)

    Makarov, G N

    2008-01-01

    Cluster temperature is an important material parameter essential to many physical and chemical processes involving clusters and cluster beams. Because of the diverse methods by which clusters can be produced, excited, and stabilized, and also because of the widely ranging values of atomic and molecular binding energies (approximately from 10 -5 to 10 eV) and numerous energy relaxation channels in clusters, cluster temperature (internal energy) ranges from 10 -3 to about 10 8 K. This paper reviews research on cluster temperature and describes methods for its measurement and stabilization. The role of cluster temperature in and its influence on physical and chemical processes is discussed. Results on the temperature dependence of cluster properties are presented. The way in which cluster temperature relates to cluster structure and to atomic and molecular interaction potentials in clusters is addressed. Methods for strong excitation of clusters and channels for their energy relaxation are discussed. Some applications of clusters and cluster beams are considered. (reviews of topical problems)

  7. A Dimensionality Reduction-Based Multi-Step Clustering Method for Robust Vessel Trajectory Analysis

    Directory of Open Access Journals (Sweden)

    Huanhuan Li

    2017-08-01

    Full Text Available The Shipboard Automatic Identification System (AIS is crucial for navigation safety and maritime surveillance, data mining and pattern analysis of AIS information have attracted considerable attention in terms of both basic research and practical applications. Clustering of spatio-temporal AIS trajectories can be used to identify abnormal patterns and mine customary route data for transportation safety. Thus, the capacities of navigation safety and maritime traffic monitoring could be enhanced correspondingly. However, trajectory clustering is often sensitive to undesirable outliers and is essentially more complex compared with traditional point clustering. To overcome this limitation, a multi-step trajectory clustering method is proposed in this paper for robust AIS trajectory clustering. In particular, the Dynamic Time Warping (DTW, a similarity measurement method, is introduced in the first step to measure the distances between different trajectories. The calculated distances, inversely proportional to the similarities, constitute a distance matrix in the second step. Furthermore, as a widely-used dimensional reduction method, Principal Component Analysis (PCA is exploited to decompose the obtained distance matrix. In particular, the top k principal components with above 95% accumulative contribution rate are extracted by PCA, and the number of the centers k is chosen. The k centers are found by the improved center automatically selection algorithm. In the last step, the improved center clustering algorithm with k clusters is implemented on the distance matrix to achieve the final AIS trajectory clustering results. In order to improve the accuracy of the proposed multi-step clustering algorithm, an automatic algorithm for choosing the k clusters is developed according to the similarity distance. Numerous experiments on realistic AIS trajectory datasets in the bridge area waterway and Mississippi River have been implemented to compare our

  8. A Dimensionality Reduction-Based Multi-Step Clustering Method for Robust Vessel Trajectory Analysis.

    Science.gov (United States)

    Li, Huanhuan; Liu, Jingxian; Liu, Ryan Wen; Xiong, Naixue; Wu, Kefeng; Kim, Tai-Hoon

    2017-08-04

    The Shipboard Automatic Identification System (AIS) is crucial for navigation safety and maritime surveillance, data mining and pattern analysis of AIS information have attracted considerable attention in terms of both basic research and practical applications. Clustering of spatio-temporal AIS trajectories can be used to identify abnormal patterns and mine customary route data for transportation safety. Thus, the capacities of navigation safety and maritime traffic monitoring could be enhanced correspondingly. However, trajectory clustering is often sensitive to undesirable outliers and is essentially more complex compared with traditional point clustering. To overcome this limitation, a multi-step trajectory clustering method is proposed in this paper for robust AIS trajectory clustering. In particular, the Dynamic Time Warping (DTW), a similarity measurement method, is introduced in the first step to measure the distances between different trajectories. The calculated distances, inversely proportional to the similarities, constitute a distance matrix in the second step. Furthermore, as a widely-used dimensional reduction method, Principal Component Analysis (PCA) is exploited to decompose the obtained distance matrix. In particular, the top k principal components with above 95% accumulative contribution rate are extracted by PCA, and the number of the centers k is chosen. The k centers are found by the improved center automatically selection algorithm. In the last step, the improved center clustering algorithm with k clusters is implemented on the distance matrix to achieve the final AIS trajectory clustering results. In order to improve the accuracy of the proposed multi-step clustering algorithm, an automatic algorithm for choosing the k clusters is developed according to the similarity distance. Numerous experiments on realistic AIS trajectory datasets in the bridge area waterway and Mississippi River have been implemented to compare our proposed method with

  9. Clustering Methods Application for Customer Segmentation to Manage Advertisement Campaign

    OpenAIRE

    Maciej Kutera; Mirosława Lasek

    2010-01-01

    Clustering methods are recently so advanced elaborated algorithms for large collection data analysis that they have been already included today to data mining methods. Clustering methods are nowadays larger and larger group of methods, very quickly evolving and having more and more various applications. In the article, our research concerning usefulness of clustering methods in customer segmentation to manage advertisement campaign is presented. We introduce results obtained by using four sel...

  10. Integrated management of thesis using clustering method

    Science.gov (United States)

    Astuti, Indah Fitri; Cahyadi, Dedy

    2017-02-01

    Thesis is one of major requirements for student in pursuing their bachelor degree. In fact, finishing the thesis involves a long process including consultation, writing manuscript, conducting the chosen method, seminar scheduling, searching for references, and appraisal process by the board of mentors and examiners. Unfortunately, most of students find it hard to match all the lecturers' free time to sit together in a seminar room in order to examine the thesis. Therefore, seminar scheduling process should be on the top of priority to be solved. Manual mechanism for this task no longer fulfills the need. People in campus including students, staffs, and lecturers demand a system in which all the stakeholders can interact each other and manage the thesis process without conflicting their timetable. A branch of computer science named Management Information System (MIS) could be a breakthrough in dealing with thesis management. This research conduct a method called clustering to distinguish certain categories using mathematics formulas. A system then be developed along with the method to create a well-managed tool in providing some main facilities such as seminar scheduling, consultation and review process, thesis approval, assessment process, and also a reliable database of thesis. The database plays an important role in present and future purposes.

  11. Integration K-Means Clustering Method and Elbow Method For Identification of The Best Customer Profile Cluster

    Science.gov (United States)

    Syakur, M. A.; Khotimah, B. K.; Rochman, E. M. S.; Satoto, B. D.

    2018-04-01

    Clustering is a data mining technique used to analyse data that has variations and the number of lots. Clustering was process of grouping data into a cluster, so they contained data that is as similar as possible and different from other cluster objects. SMEs Indonesia has a variety of customers, but SMEs do not have the mapping of these customers so they did not know which customers are loyal or otherwise. Customer mapping is a grouping of customer profiling to facilitate analysis and policy of SMEs in the production of goods, especially batik sales. Researchers will use a combination of K-Means method with elbow to improve efficient and effective k-means performance in processing large amounts of data. K-Means Clustering is a localized optimization method that is sensitive to the selection of the starting position from the midpoint of the cluster. So choosing the starting position from the midpoint of a bad cluster will result in K-Means Clustering algorithm resulting in high errors and poor cluster results. The K-means algorithm has problems in determining the best number of clusters. So Elbow looks for the best number of clusters on the K-means method. Based on the results obtained from the process in determining the best number of clusters with elbow method can produce the same number of clusters K on the amount of different data. The result of determining the best number of clusters with elbow method will be the default for characteristic process based on case study. Measurement of k-means value of k-means has resulted in the best clusters based on SSE values on 500 clusters of batik visitors. The result shows the cluster has a sharp decrease is at K = 3, so K as the cut-off point as the best cluster.

  12. An assessment of existing common traditional methods of water ...

    African Journals Online (AJOL)

    Classical water purification methods include boiling, filtration, irradiation and the use of chemicals while traditional water purification methods in use are boiling, filtration, sedimentation, long storage and solar radiation. Waterborne diseases are m ore common in the rural communities where potable water supply coverage ...

  13. College Students' Perceptions of the Traditional Lecture Method

    Science.gov (United States)

    Covill, Amy E.

    2011-01-01

    Fifty-one college students responded to survey questions regarding their perceptions of the traditional lecture method of instruction that they received in a 200-level psychology course. At a time when many professors are being encouraged to use active learning methods instead of lectures, it is important to consider the students' perspective. Do…

  14. Comparing Traditional and Crowdsourcing Methods for Pretesting Survey Questions

    Directory of Open Access Journals (Sweden)

    Jennifer Edgar

    2016-10-01

    Full Text Available Cognitive interviewing is a common method used to evaluate survey questions. This study compares traditional cognitive interviewing methods with crowdsourcing, or “tapping into the collective intelligence of the public to complete a task.” Crowdsourcing may provide researchers with access to a diverse pool of potential participants in a very timely and cost-efficient way. Exploratory work found that crowdsourcing participants, with self-administered data collection, may be a viable alternative, or addition, to traditional pretesting methods. Using three crowdsourcing designs (TryMyUI, Amazon Mechanical Turk, and Facebook, we compared the participant characteristics, costs, and quantity and quality of data with traditional laboratory-based cognitive interviews. Results suggest that crowdsourcing and self-administered protocols may be a viable way to collect survey pretesting information, as participants were able to complete the tasks and provide useful information; however, complex tasks may require the skills of an interviewer to administer unscripted probes.

  15. Tradition

    DEFF Research Database (Denmark)

    Otto, Ton

    2016-01-01

    : beliefs, practices, institutions, and also things. In this sense, the meaning of the term in social research is very close to its usage in common language and is not always theoretically well developed (see Shils, 1971: 123). But the concept of tradition has also been central to major theoretical debates...... on the nature of social change, especially in connection with the notion of modernity. Here tradition is linked to various forms of agency as a factor of both stability and intentional change....

  16. Determining wood chip size: image analysis and clustering methods

    Directory of Open Access Journals (Sweden)

    Paolo Febbi

    2013-09-01

    Full Text Available One of the standard methods for the determination of the size distribution of wood chips is the oscillating screen method (EN 15149- 1:2010. Recent literature demonstrated how image analysis could return highly accurate measure of the dimensions defined for each individual particle, and could promote a new method depending on the geometrical shape to determine the chip size in a more accurate way. A sample of wood chips (8 litres was sieved through horizontally oscillating sieves, using five different screen hole diameters (3.15, 8, 16, 45, 63 mm; the wood chips were sorted in decreasing size classes and the mass of all fractions was used to determine the size distribution of the particles. Since the chip shape and size influence the sieving results, Wang’s theory, which concerns the geometric forms, was considered. A cluster analysis on the shape descriptors (Fourier descriptors and size descriptors (area, perimeter, Feret diameters, eccentricity was applied to observe the chips distribution. The UPGMA algorithm was applied on Euclidean distance. The obtained dendrogram shows a group separation according with the original three sieving fractions. A comparison has been made between the traditional sieve and clustering results. This preliminary result shows how the image analysis-based method has a high potential for the characterization of wood chip size distribution and could be further investigated. Moreover, this method could be implemented in an online detection machine for chips size characterization. An improvement of the results is expected by using supervised multivariate methods that utilize known class memberships. The main objective of the future activities will be to shift the analysis from a 2-dimensional method to a 3- dimensional acquisition process.

  17. [Application of Delphi method in traditional Chinese medicine clinical research].

    Science.gov (United States)

    Bi, Ying-fei; Mao, Jing-yuan

    2012-03-01

    In recent years, Delphi method has been widely applied in traditional Chinese medicine (TCM) clinical research. This article analyzed the present application situation of Delphi method in TCM clinical research, and discussed some problems presented in the choice of evaluation method, classification of observation indexes and selection of survey items. On the basis of present application of Delphi method, the author analyzed the method on questionnaire making, selection of experts, evaluation of observation indexes and selection of survey items. Furthermore, the author summarized the steps of application of Delphi method in TCM clinical research.

  18. INTERNATIONAL BEHAVIOUR AND PERFORMANCE BASED ROMANIAN ENTREPRENEURIAL AND TRADITIONAL FIRM CLUSTERS

    Directory of Open Access Journals (Sweden)

    FEDER Emoke - Szidonia

    2015-07-01

    Full Text Available The micro, small and medium-sized firms (SMEs present a key interest at European level due to their potential positive influence on regional, national and firm level competitiveness. At a certain moment in time, internationalisation became an expected and even unavoidable strategy in firms’ future development, growth and evolution. From theoretical perspective, an integrative complementarily approach is adopted concerning the dominant paradigm of stage models from incremental internationalisation theory and the emergent paradigm of international entrepreneurship theory. Several researcher calls for empirical testing of different theoretical frameworks and international firms. Therefore, the first aim of the quantitative study is to empirically prove, the existence of various internationalisation behaviour configuration based clusters, like sporadic and traditional international firms, born-again global and born global firms, within the framework of Romanian SMEs. Secondly, within the research framework the study propose to assess different distinguishing internationalisation behavioural characteristics and patterns for the delimited clusters, in terms of foreign market scope, internationalisation pace and rhythm, initial and current entry modes, international product portfolio and commitment. Thirdly, internationalisation cluster membership and patterns differential influence and contribution is analysed on firm level international business performance, as internationalisation degree, financial and marketing measures. The framework was tested on a transversal sample consisting of 140 Romanian internationalised SMEs. Findings are especially useful for entrepreneurs and SME managers presenting various decisional possibilities and options on internationalisation behaviours and performance. These emphasize the importance of internationalisation scope, pace, object and opportunity seeking, along with positive influence on performance, indifferent

  19. Bacterial population in traditional sourdough evaluated by molecular methods

    NARCIS (Netherlands)

    Randazzo, C.L.; Heilig, G.H.J.; Restuccia, C.; Giudici, P.; Caggia, C.

    2005-01-01

    Aims: To study the microbial communities in artisanal sourdoughs, manufactured by traditional procedure in different areas of Sicily, and to evaluate the lactic acid bacteria (LAB) population by classical and culture-independent approaches. Methods and Results: Forty-five LAB isolates were

  20. Comparison of traditional physico-chemical methods and molecular ...

    African Journals Online (AJOL)

    This study was aim to review the efficiency of molecular markers and traditional physico-chemical methods for the identification of basmati rice. The study involved 44 promising varieties of Indica rices collected from geographically distant places and adapted to irrigated and aerobic agro-ecosystems. Quality data for ...

  1. Traditional and New methods for the Preparation of Diazocarbonyl Compounds

    Directory of Open Access Journals (Sweden)

    ANTONIO C.B. BURTOLOSO

    2018-04-01

    Full Text Available ABSTRACT For many years diazocarbonyl compounds have been studied due to their versatility and usability in many chemical transformations. In this review, we summarize the traditional methods to prepare these compounds as well as the new methods and recent improvements in experimental procedures. Moreover, emergence of continuous flow techniques has allowed safer and environmentally friendly procedures for the handling of diazomethane and diazo compounds and will also be a topic in this review.

  2. Homological methods, representation theory, and cluster algebras

    CERN Document Server

    Trepode, Sonia

    2018-01-01

    This text presents six mini-courses, all devoted to interactions between representation theory of algebras, homological algebra, and the new ever-expanding theory of cluster algebras. The interplay between the topics discussed in this text will continue to grow and this collection of courses stands as a partial testimony to this new development. The courses are useful for any mathematician who would like to learn more about this rapidly developing field; the primary aim is to engage graduate students and young researchers. Prerequisites include knowledge of some noncommutative algebra or homological algebra. Homological algebra has always been considered as one of the main tools in the study of finite-dimensional algebras. The strong relationship with cluster algebras is more recent and has quickly established itself as one of the important highlights of today’s mathematical landscape. This connection has been fruitful to both areas—representation theory provides a categorification of cluster algebras, wh...

  3. Single pass kernel k-means clustering method

    Indian Academy of Sciences (India)

    In unsupervised classification, kernel -means clustering method has been shown to perform better than conventional -means clustering method in ... 518501, India; Department of Computer Science and Engineering, Jawaharlal Nehru Technological University, Anantapur College of Engineering, Anantapur 515002, India ...

  4. Mechanical and Metabolic Responses to Traditional and Cluster Set Configurations in the Bench Press Exercise.

    Science.gov (United States)

    García-Ramos, Amador; González-Hernández, Jorge M; Baños-Pelegrín, Ezequiel; Castaño-Zambudio, Adrián; Capelo-Ramírez, Fernando; Boullosa, Daniel; Haff, Guy G; Jiménez-Reyes, Pedro

    2017-10-20

    García-Ramos, A, González-Hernández, JM, Baños-Pelegrín, E, Castaño-Zambudio, A, Capelo-Ramírez, F, Boullosa, D, Haff, GG, and Jiménez-Reyes, P. Mechanical and metabolic responses to traditional and cluster set configurations in the bench press exercise. J Strength Cond Res XX(X): 000-000, 2017-This study aimed to compare mechanical and metabolic responses between traditional (TR) and cluster (CL) set configurations in the bench press exercise. In a counterbalanced randomized order, 10 men were tested with the following protocols (sets × repetitions [inter-repetition rest]): TR1: 3 × 10 (0-second), TR2: 6 × 5 (0-second), CL5: 3 × 10 (5-second), CL10: 3 × 10 (10-second), and CL15: 3 × 10 (15-second). The number of repetitions (30), interset rest (5 minutes), and resistance applied (10 repetition maximum) were the same for all set configurations. Movement velocity and blood lactate concentration were used to assess the mechanical and metabolic responses, respectively. The comparison of the first and last set of the training session revealed a significant decrease in movement velocity for TR1 (Effect size [ES]: -0.92), CL10 (ES: -0.85), and CL15 (ES: -1.08) (but not for TR2 [ES: -0.38] and CL5 [ES: -0.37]); while blood lactate concentration was significantly increased for TR1 (ES: 1.11), TR2 (ES: 0.90), and CL5 (ES: 1.12) (but not for CL10 [ES: 0.03] and CL15 [ES: -0.43]). Based on velocity loss, set configurations were ranked as follows: TR1 (-39.3 ± 7.3%) > CL5 (-20.2 ± 14.7%) > CL10 (-12.9 ± 4.9%), TR2 (-10.3 ± 5.3%), and CL15 (-10.0 ± 2.3%). The set configurations were ranked as follows based on the lactate concentration: TR1 (7.9 ± 1.1 mmol·L) > CL5 (5.8 ± 0.9 mmol·L) > TR2 (4.2 ± 0.7 mmol·L) > CL10 (3.5 ± 0.4 mmol·L) and CL15 (3.4 ± 0.7 mmol·L). These results support the use of TR2, CL10, and CL15 for the maintenance of high mechanical outputs, while CL10 and CL15 produce less metabolic stress than TR2.

  5. Improving local clustering based top-L link prediction methods via asymmetric link clustering information

    Science.gov (United States)

    Wu, Zhihao; Lin, Youfang; Zhao, Yiji; Yan, Hongyan

    2018-02-01

    Networks can represent a wide range of complex systems, such as social, biological and technological systems. Link prediction is one of the most important problems in network analysis, and has attracted much research interest recently. Many link prediction methods have been proposed to solve this problem with various techniques. We can note that clustering information plays an important role in solving the link prediction problem. In previous literatures, we find node clustering coefficient appears frequently in many link prediction methods. However, node clustering coefficient is limited to describe the role of a common-neighbor in different local networks, because it cannot distinguish different clustering abilities of a node to different node pairs. In this paper, we shift our focus from nodes to links, and propose the concept of asymmetric link clustering (ALC) coefficient. Further, we improve three node clustering based link prediction methods via the concept of ALC. The experimental results demonstrate that ALC-based methods outperform node clustering based methods, especially achieving remarkable improvements on food web, hamster friendship and Internet networks. Besides, comparing with other methods, the performance of ALC-based methods are very stable in both globalized and personalized top-L link prediction tasks.

  6. Prediction of Solvent Physical Properties using the Hierarchical Clustering Method

    Science.gov (United States)

    Recently a QSAR (Quantitative Structure Activity Relationship) method, the hierarchical clustering method, was developed to estimate acute toxicity values for large, diverse datasets. This methodology has now been applied to the estimate solvent physical properties including sur...

  7. A Web service substitution method based on service cluster nets

    Science.gov (United States)

    Du, YuYue; Gai, JunJing; Zhou, MengChu

    2017-11-01

    Service substitution is an important research topic in the fields of Web services and service-oriented computing. This work presents a novel method to analyse and substitute Web services. A new concept, called a Service Cluster Net Unit, is proposed based on Web service clusters. A service cluster is converted into a Service Cluster Net Unit. Then it is used to analyse whether the services in the cluster can satisfy some service requests. Meanwhile, the substitution methods of an atomic service and a composite service are proposed. The correctness of the proposed method is proved, and the effectiveness is shown and compared with the state-of-the-art method via an experiment. It can be readily applied to e-commerce service substitution to meet the business automation needs.

  8. Fuzzy C-means method for clustering microarray data.

    Science.gov (United States)

    Dembélé, Doulaye; Kastner, Philippe

    2003-05-22

    Clustering analysis of data from DNA microarray hybridization studies is essential for identifying biologically relevant groups of genes. Partitional clustering methods such as K-means or self-organizing maps assign each gene to a single cluster. However, these methods do not provide information about the influence of a given gene for the overall shape of clusters. Here we apply a fuzzy partitioning method, Fuzzy C-means (FCM), to attribute cluster membership values to genes. A major problem in applying the FCM method for clustering microarray data is the choice of the fuzziness parameter m. We show that the commonly used value m = 2 is not appropriate for some data sets, and that optimal values for m vary widely from one data set to another. We propose an empirical method, based on the distribution of distances between genes in a given data set, to determine an adequate value for m. By setting threshold levels for the membership values, genes which are tigthly associated to a given cluster can be selected. Using a yeast cell cycle data set as an example, we show that this selection increases the overall biological significance of the genes within the cluster. Supplementary text and Matlab functions are available at http://www-igbmc.u-strasbg.fr/fcm/

  9. Progeny Clustering: A Method to Identify Biological Phenotypes

    Science.gov (United States)

    Hu, Chenyue W.; Kornblau, Steven M.; Slater, John H.; Qutub, Amina A.

    2015-01-01

    Estimating the optimal number of clusters is a major challenge in applying cluster analysis to any type of dataset, especially to biomedical datasets, which are high-dimensional and complex. Here, we introduce an improved method, Progeny Clustering, which is stability-based and exceptionally efficient in computing, to find the ideal number of clusters. The algorithm employs a novel Progeny Sampling method to reconstruct cluster identity, a co-occurrence probability matrix to assess the clustering stability, and a set of reference datasets to overcome inherent biases in the algorithm and data space. Our method was shown successful and robust when applied to two synthetic datasets (datasets of two-dimensions and ten-dimensions containing eight dimensions of pure noise), two standard biological datasets (the Iris dataset and Rat CNS dataset) and two biological datasets (a cell phenotype dataset and an acute myeloid leukemia (AML) reverse phase protein array (RPPA) dataset). Progeny Clustering outperformed some popular clustering evaluation methods in the ten-dimensional synthetic dataset as well as in the cell phenotype dataset, and it was the only method that successfully discovered clinically meaningful patient groupings in the AML RPPA dataset. PMID:26267476

  10. Traditions and Alcohol Use: A Mixed-Methods Analysis

    Science.gov (United States)

    Castro, Felipe González; Coe, Kathryn

    2011-01-01

    An integrative mixed-methods analysis examined traditional beliefs as associated with beliefs about self-care during pregnancy and with alcohol abstinence among young adult women from two rural U.S.–Mexico border communities. Quantitative (measured scale) variables and qualitative thematic variables generated from open-ended responses served as within-time predictors of these health-related outcomes. A weaker belief that life is better in big cities was associated with stronger self-care beliefs during pregnancy. Also, a weaker belief that small towns offer tranquil environments was associated with total abstinence from alcohol. Regarding the Hispanic Paradox, these results suggest that a critical appreciation of cultural traditions can be protective, as this avoids stereotypical or idyllic views of urban or rural lifeways, and promotes self-protective beliefs and behaviors. PMID:17967095

  11. The smart cluster method. Adaptive earthquake cluster identification and analysis in strong seismic regions

    Science.gov (United States)

    Schaefer, Andreas M.; Daniell, James E.; Wenzel, Friedemann

    2017-07-01

    Earthquake clustering is an essential part of almost any statistical analysis of spatial and temporal properties of seismic activity. The nature of earthquake clusters and subsequent declustering of earthquake catalogues plays a crucial role in determining the magnitude-dependent earthquake return period and its respective spatial variation for probabilistic seismic hazard assessment. This study introduces the Smart Cluster Method (SCM), a new methodology to identify earthquake clusters, which uses an adaptive point process for spatio-temporal cluster identification. It utilises the magnitude-dependent spatio-temporal earthquake density to adjust the search properties, subsequently analyses the identified clusters to determine directional variation and adjusts its search space with respect to directional properties. In the case of rapid subsequent ruptures like the 1992 Landers sequence or the 2010-2011 Darfield-Christchurch sequence, a reclassification procedure is applied to disassemble subsequent ruptures using near-field searches, nearest neighbour classification and temporal splitting. The method is capable of identifying and classifying earthquake clusters in space and time. It has been tested and validated using earthquake data from California and New Zealand. A total of more than 1500 clusters have been found in both regions since 1980 with M m i n = 2.0. Utilising the knowledge of cluster classification, the method has been adjusted to provide an earthquake declustering algorithm, which has been compared to existing methods. Its performance is comparable to established methodologies. The analysis of earthquake clustering statistics lead to various new and updated correlation functions, e.g. for ratios between mainshock and strongest aftershock and general aftershock activity metrics.

  12. Traditional and robust vector selection methods for use with similarity based models

    International Nuclear Information System (INIS)

    Hines, J. W.; Garvey, D. R.

    2006-01-01

    Vector selection, or instance selection as it is often called in the data mining literature, performs a critical task in the development of nonparametric, similarity based models. Nonparametric, similarity based modeling (SBM) is a form of 'lazy learning' which constructs a local model 'on the fly' by comparing a query vector to historical, training vectors. For large training sets the creation of local models may become cumbersome, since each training vector must be compared to the query vector. To alleviate this computational burden, varying forms of training vector sampling may be employed with the goal of selecting a subset of the training data such that the samples are representative of the underlying process. This paper describes one such SBM, namely auto-associative kernel regression (AAKR), and presents five traditional vector selection methods and one robust vector selection method that may be used to select prototype vectors from a larger data set in model training. The five traditional vector selection methods considered are min-max, vector ordering, combination min-max and vector ordering, fuzzy c-means clustering, and Adeli-Hung clustering. Each method is described in detail and compared using artificially generated data and data collected from the steam system of an operating nuclear power plant. (authors)

  13. A Latent Variable Clustering Method for Wireless Sensor Networks

    DEFF Research Database (Denmark)

    Vasilev, Vladislav; Iliev, Georgi; Poulkov, Vladimir

    2016-01-01

    In this paper we derive a clustering method based on the Hidden Conditional Random Field (HCRF) model in order to maximizes the performance of a wireless sensor. Our novel approach to clustering in this paper is in the application of an index invariant graph that we defined in a previous work and...

  14. Single pass kernel k-means clustering method

    Indian Academy of Sciences (India)

    paper proposes a simple and faster version of the kernel k-means clustering ... It has been considered as an important tool ... On the other hand, kernel-based clustering methods, like kernel k-means clus- ..... able at the UCI machine learning repository (Murphy 1994). ... All the data sets have only numeric valued features.

  15. Do new wipe materials outperform traditional lead dust cleaning methods?

    Science.gov (United States)

    Lewis, Roger D; Ong, Kee Hean; Emo, Brett; Kennedy, Jason; Brown, Christopher A; Condoor, Sridhar; Thummalakunta, Laxmi

    2012-01-01

    Government guidelines have traditionally recommended the use of wet mopping, sponging, or vacuuming for removal of lead-contaminated dust from hard surfaces in homes. The emergence of new technologies, such as the electrostatic dry cloth and wet disposable clothes used on mopheads, for removal of dust provides an opportunity to evaluate their ability to remove lead compared with more established methods. The purpose of this study was to determine if relative differences exist between two new and two older methods for removal of lead-contaminated dust (LCD) from three wood surfaces that were characterized by different roughness or texture. Standard leaded dust, coefficient of friction was performed for each wipe material. Analysis of variance was used to evaluate the surface and cleaning methods. There were significant interactions between cleaning method and surface types, p = 0.007. Cleaning method was found be a significant factor in removal of lead, p coefficient of friction, significantly different among the three wipes, is likely to influence the cleaning action. Cleaning method appears to be more important than texture in LCD removal from hard surfaces. There are some small but important factors in cleaning LCD from hard surfaces, including the limits of a Swiffer mop to conform to curved surfaces and the efficiency of the wetted shop towel and vacuuming for cleaning all surface textures. The mean percentage reduction in lead dust achieved by the traditional methods (vacuuming and wet wiping) was greater and more consistent compared to the new methods (electrostatic dry cloth and wet Swiffer mop). Vacuuming and wet wiping achieved lead reductions of 92% ± 4% and 91%, ± 4%, respectively, while the electrostatic dry cloth and wet Swiffer mops achieved lead reductions of only 89 ± 8% and  81 ± 17%, respectively.

  16. Clustering Methods Application for Customer Segmentation to Manage Advertisement Campaign

    Directory of Open Access Journals (Sweden)

    Maciej Kutera

    2010-10-01

    Full Text Available Clustering methods are recently so advanced elaborated algorithms for large collection data analysis that they have been already included today to data mining methods. Clustering methods are nowadays larger and larger group of methods, very quickly evolving and having more and more various applications. In the article, our research concerning usefulness of clustering methods in customer segmentation to manage advertisement campaign is presented. We introduce results obtained by using four selected methods which have been chosen because their peculiarities suggested their applicability to our purposes. One of the analyzed method k-means clustering with random selected initial cluster seeds gave very good results in customer segmentation to manage advertisement campaign and these results were presented in details in the article. In contrast one of the methods (hierarchical average linkage was found useless in customer segmentation. Further investigations concerning benefits of clustering methods in customer segmentation to manage advertisement campaign is worth continuing, particularly that finding solutions in this field can give measurable profits for marketing activity.

  17. The ethics of improving African traditional medical practice: scientific or African traditional research methods?

    Science.gov (United States)

    Nyika, Aceme

    2009-11-01

    The disease burden in Africa, which is relatively very large compared with developed countries, has been attributed to various factors that include poverty, food shortages, inadequate access to health care and unaffordability of Western medicines to the majority of African populations. Although for 'old diseases' knowledge about the right African traditional medicines to treat or cure the diseases has been passed from generation to generation, knowledge about traditional medicines to treat newly emerging diseases has to be generated in one way or another. In addition, the existing traditional medicines have to be continuously improved, which is also the case with Western scientific medicines. Whereas one school of thought supports the idea of improving medicines, be they traditional or Western, through scientific research, an opposing school of thought argues that subjecting African traditional medicines to scientific research would be tantamount to some form of colonization and imperialism. This paper argues that continuing to use African traditional medicines for old and new diseases without making concerted efforts to improve their efficacy and safety is unethical since the disease burden affecting Africa may continue to rise in spite of the availability and accessibility of the traditional medicines. Most importantly, the paper commends efforts being made in some African countries to improve African traditional medicine through a combination of different mechanisms that include the controversial approach of scientific research on traditional medicines.

  18. Cluster cosmological analysis with X ray instrumental observables: introduction and testing of AsPIX method

    International Nuclear Information System (INIS)

    Valotti, Andrea

    2016-01-01

    for the fluxes, colors, sizes, and redshifts of the clusters performs well. Additionally, I find that it is at least as efficient as the traditional N(M,z) method for the same cluster samples. I also discuss a proposition to apply this method to the XXL survey data. (author) [fr

  19. Bacterial population in traditional sourdough evaluated by molecular methods.

    Science.gov (United States)

    Randazzo, C L; Heilig, H; Restuccia, C; Giudici, P; Caggia, C

    2005-01-01

    To study the microbial communities in artisanal sourdoughs, manufactured by traditional procedure in different areas of Sicily, and to evaluate the lactic acid bacteria (LAB) population by classical and culture-independent approaches. Forty-five LAB isolates were identified both by phenotypic and molecular methods. The restriction fragment length polymorphism and 16S ribosomal DNA gene sequencing gave evidence of a variety of species with the dominance of Lactobacillus sanfranciscensis and Lactobacillus pentosus, in all sourdoughs tested. Culture-independent method, such as denaturing gradient gel electrophoresis (DGGE) of the V6-V8 regions of the 16S rDNA, was applied for microbial community fingerprint. The DGGE profiles revealed the dominance of L. sanfranciscensis species. In addition, Lactobacillus-specific primers were used to amplify the V1-V3 regions of the 16S rDNA. DGGE profiles flourished the dominance of L. sanfranciscensis and Lactobacillus fermentum in the traditional sourdoughs, and revealed that the closely related species Lactobacillus kimchii and Lactobacillus alimentarius were not discriminated. Lactobacillus-specific PCR-DGGE analysis is a rapid tool for rapid detection of Lactobacillus species in artisanal sourdough. This study reports a characterization of Lactobacillus isolates from artisanal sourdoughs and highlights the value of DGGE approach to detect uncultivable Lactobacillus species.

  20. The relationship between supplier networks and industrial clusters: an analysis based on the cluster mapping method

    Directory of Open Access Journals (Sweden)

    Ichiro IWASAKI

    2010-06-01

    Full Text Available Michael Porter’s concept of competitive advantages emphasizes the importance of regional cooperation of various actors in order to gain competitiveness on globalized markets. Foreign investors may play an important role in forming such cooperation networks. Their local suppliers tend to concentrate regionally. They can form, together with local institutions of education, research, financial and other services, development agencies, the nucleus of cooperative clusters. This paper deals with the relationship between supplier networks and clusters. Two main issues are discussed in more detail: the interest of multinational companies in entering regional clusters and the spillover effects that may stem from their participation. After the discussion on the theoretical background, the paper introduces a relatively new analytical method: “cluster mapping” - a method that can spot regional hot spots of specific economic activities with cluster building potential. Experience with the method was gathered in the US and in the European Union. After the discussion on the existing empirical evidence, the authors introduce their own cluster mapping results, which they obtained by using a refined version of the original methodology.

  1. An Examination of Three Spatial Event Cluster Detection Methods

    Directory of Open Access Journals (Sweden)

    Hensley H. Mariathas

    2015-03-01

    Full Text Available In spatial disease surveillance, geographic areas with large numbers of disease cases are to be identified, so that targeted investigations can be pursued. Geographic areas with high disease rates are called disease clusters and statistical cluster detection tests are used to identify geographic areas with higher disease rates than expected by chance alone. In some situations, disease-related events rather than individuals are of interest for geographical surveillance, and methods to detect clusters of disease-related events are called event cluster detection methods. In this paper, we examine three distributional assumptions for the events in cluster detection: compound Poisson, approximate normal and multiple hypergeometric (exact. The methods differ on the choice of distributional assumption for the potentially multiple correlated events per individual. The methods are illustrated on emergency department (ED presentations by children and youth (age < 18 years because of substance use in the province of Alberta, Canada, during 1 April 2007, to 31 March 2008. Simulation studies are conducted to investigate Type I error and the power of the clustering methods.

  2. A semantics-based method for clustering of Chinese web search results

    Science.gov (United States)

    Zhang, Hui; Wang, Deqing; Wang, Li; Bi, Zhuming; Chen, Yong

    2014-01-01

    Information explosion is a critical challenge to the development of modern information systems. In particular, when the application of an information system is over the Internet, the amount of information over the web has been increasing exponentially and rapidly. Search engines, such as Google and Baidu, are essential tools for people to find the information from the Internet. Valuable information, however, is still likely submerged in the ocean of search results from those tools. By clustering the results into different groups based on subjects automatically, a search engine with the clustering feature allows users to select most relevant results quickly. In this paper, we propose an online semantics-based method to cluster Chinese web search results. First, we employ the generalised suffix tree to extract the longest common substrings (LCSs) from search snippets. Second, we use the HowNet to calculate the similarities of the words derived from the LCSs, and extract the most representative features by constructing the vocabulary chain. Third, we construct a vector of text features and calculate snippets' semantic similarities. Finally, we improve the Chameleon algorithm to cluster snippets. Extensive experimental results have shown that the proposed algorithm has outperformed over the suffix tree clustering method and other traditional clustering methods.

  3. Operational auditing versus traditional method: A comparative investigation

    Directory of Open Access Journals (Sweden)

    Reza Tehrani

    2013-06-01

    Full Text Available Operational auditing is one of the management consultancy services whose significance is on the rise day by day. This approach is, clearly, a systematic and methodical process used to evaluate economic savings of financial processes in organizations and the results of the evaluations are reported to interested people along with some comments to improve operational processes. Accordingly, it appears that the proper employment of the existing rationale in operational auditing can be a significant step towards the improvement of financial efficiency in Iranian public and private banking sector. This paper studies the effects of operational auditing on the improvement of economic saving of financial processes in Iranian private banks compared with traditional approaches where the operations are based on financial statements. The population of this survey includes 15 private and public Iranian banks and the proposed study selects 78 branches, randomly. The Cronbach alpha was used to test the reliability a questionnaire employed to collect the needed data in this study. The results obtained by SPSS Software indicated that the reliability of the instrumentsanged between 0.752 and 0.867, suggesting an acceptable level of the reliability for the questionnaire. Besides, content validity was used to confirm the validity of the instrument. The results of the study indicated that the operational auditing as a useful approach influencing the financial efficiency of public and private banks has significantly transformed the traditional thinking in the field of management auditing. The operational auditing has a number of significant advantages including a better method of controlling financial operations within Iranian banks, efficient planning in the future, facilitating efficient, appropriate, and accurate management decision making, and sound evaluation of managers’ financial operations.

  4. Sensitivity evaluation of dynamic speckle activity measurements using clustering methods

    International Nuclear Information System (INIS)

    Etchepareborda, Pablo; Federico, Alejandro; Kaufmann, Guillermo H.

    2010-01-01

    We evaluate and compare the use of competitive neural networks, self-organizing maps, the expectation-maximization algorithm, K-means, and fuzzy C-means techniques as partitional clustering methods, when the sensitivity of the activity measurement of dynamic speckle images needs to be improved. The temporal history of the acquired intensity generated by each pixel is analyzed in a wavelet decomposition framework, and it is shown that the mean energy of its corresponding wavelet coefficients provides a suited feature space for clustering purposes. The sensitivity obtained by using the evaluated clustering techniques is also compared with the well-known methods of Konishi-Fujii, weighted generalized differences, and wavelet entropy. The performance of the partitional clustering approach is evaluated using simulated dynamic speckle patterns and also experimental data.

  5. Oil pulling: A traditional method on the edge of evidence

    Directory of Open Access Journals (Sweden)

    H Mythri

    2017-01-01

    Full Text Available Introduction: Oil pulling is an ancient, traditional folk remedy that has been practiced for centuries in India and southern Asia as a holistic Ayurvedic technique. The practice of oil pulling involves placing a tablespoon of an edible oil (e.g. sesame, olive, sunflower, coconut inside the mouth, and swishing or “pulling” the oil through the teeth and oral cavity for anywhere from 1–5 minutes to up to 20 minutes or longer. Materials and Methods: Articles related to oil pulling were collected by using oil pulling as Keyword in Google and Medline. Out of the 21 related articles published till 2016, 6 articles with the proper study designs were used for analysis. Results: The studies were unreliable for many reasons, including the misinterpretation of results due to small sample size and improper study design. Conclusion: Though the promoters claim it as one of the best method to be as adjuvant to mechanical control methods, scientific evidences are lacking.

  6. Momentum-space cluster dual-fermion method

    Science.gov (United States)

    Iskakov, Sergei; Terletska, Hanna; Gull, Emanuel

    2018-03-01

    Recent years have seen the development of two types of nonlocal extensions to the single-site dynamical mean field theory. On one hand, cluster approximations, such as the dynamical cluster approximation, recover short-range momentum-dependent correlations nonperturbatively. On the other hand, diagrammatic extensions, such as the dual-fermion theory, recover long-ranged corrections perturbatively. The correct treatment of both strong short-ranged and weak long-ranged correlations within the same framework is therefore expected to lead to a quick convergence of results, and offers the potential of obtaining smooth self-energies in nonperturbative regimes of phase space. In this paper, we present an exact cluster dual-fermion method based on an expansion around the dynamical cluster approximation. Unlike previous formulations, our method does not employ a coarse-graining approximation to the interaction, which we show to be the leading source of error at high temperature, and converges to the exact result independently of the size of the underlying cluster. We illustrate the power of the method with results for the second-order cluster dual-fermion approximation to the single-particle self-energies and double occupancies.

  7. Polarizable Density Embedding Coupled Cluster Method

    DEFF Research Database (Denmark)

    Hršak, Dalibor; Olsen, Jógvan Magnus Haugaard; Kongsted, Jacob

    2018-01-01

    by an embedding potential consisting of a set of fragment densities obtained from calculations on isolated fragments with a quantum-chemistry method such as Hartree-Fock (HF) or Kohn-Sham density functional theory (KS-DFT) and dressed with a set of atom-centered anisotropic dipole-dipole polarizabilities...

  8. Coordinate-Based Clustering Method for Indoor Fingerprinting Localization in Dense Cluttered Environments

    Directory of Open Access Journals (Sweden)

    Wen Liu

    2016-12-01

    Full Text Available Indoor positioning technologies has boomed recently because of the growing commercial interest in indoor location-based service (ILBS. Due to the absence of satellite signal in Global Navigation Satellite System (GNSS, various technologies have been proposed for indoor applications. Among them, Wi-Fi fingerprinting has been attracting much interest from researchers because of its pervasive deployment, flexibility and robustness to dense cluttered indoor environments. One challenge, however, is the deployment of Access Points (AP, which would bring a significant influence on the system positioning accuracy. This paper concentrates on WLAN based fingerprinting indoor location by analyzing the AP deployment influence, and studying the advantages of coordinate-based clustering compared to traditional RSS-based clustering. A coordinate-based clustering method for indoor fingerprinting location, named Smallest-Enclosing-Circle-based (SEC, is then proposed aiming at reducing the positioning error lying in the AP deployment and improving robustness to dense cluttered environments. All measurements are conducted in indoor public areas, such as the National Center For the Performing Arts (as Test-bed 1 and the XiDan Joy City (Floors 1 and 2, as Test-bed 2, and results show that SEC clustering algorithm can improve system positioning accuracy by about 32.7% for Test-bed 1, 71.7% for Test-bed 2 Floor 1 and 73.7% for Test-bed 2 Floor 2 compared with traditional RSS-based clustering algorithms such as K-means.

  9. Coordinate-Based Clustering Method for Indoor Fingerprinting Localization in Dense Cluttered Environments.

    Science.gov (United States)

    Liu, Wen; Fu, Xiao; Deng, Zhongliang

    2016-12-02

    Indoor positioning technologies has boomed recently because of the growing commercial interest in indoor location-based service (ILBS). Due to the absence of satellite signal in Global Navigation Satellite System (GNSS), various technologies have been proposed for indoor applications. Among them, Wi-Fi fingerprinting has been attracting much interest from researchers because of its pervasive deployment, flexibility and robustness to dense cluttered indoor environments. One challenge, however, is the deployment of Access Points (AP), which would bring a significant influence on the system positioning accuracy. This paper concentrates on WLAN based fingerprinting indoor location by analyzing the AP deployment influence, and studying the advantages of coordinate-based clustering compared to traditional RSS-based clustering. A coordinate-based clustering method for indoor fingerprinting location, named Smallest-Enclosing-Circle-based (SEC), is then proposed aiming at reducing the positioning error lying in the AP deployment and improving robustness to dense cluttered environments. All measurements are conducted in indoor public areas, such as the National Center For the Performing Arts (as Test-bed 1) and the XiDan Joy City (Floors 1 and 2, as Test-bed 2), and results show that SEC clustering algorithm can improve system positioning accuracy by about 32.7% for Test-bed 1, 71.7% for Test-bed 2 Floor 1 and 73.7% for Test-bed 2 Floor 2 compared with traditional RSS-based clustering algorithms such as K-means.

  10. Method for detecting clusters of possible uranium deposits

    International Nuclear Information System (INIS)

    Conover, W.J.; Bement, T.R.; Iman, R.L.

    1978-01-01

    When a two-dimensional map contains points that appear to be scattered somewhat at random, a question that often arises is whether groups of points that appear to cluster are merely exhibiting ordinary behavior, which one can expect with any random distribution of points, or whether the clusters are too pronounced to be attributable to chance alone. A method for detecting clusters along a straight line is applied to the two-dimensional map of 214 Bi anomalies observed as part of the National Uranium Resource Evaluation Program in the Lubbock, Texas, region. Some exact probabilities associated with this method are computed and compared with two approximate methods. The two methods for approximating probabilities work well in the cases examined and can be used when it is not feasible to obtain the exact probabilities

  11. Performance Analysis of Unsupervised Clustering Methods for Brain Tumor Segmentation

    Directory of Open Access Journals (Sweden)

    Tushar H Jaware

    2013-10-01

    Full Text Available Medical image processing is the most challenging and emerging field of neuroscience. The ultimate goal of medical image analysis in brain MRI is to extract important clinical features that would improve methods of diagnosis & treatment of disease. This paper focuses on methods to detect & extract brain tumour from brain MR images. MATLAB is used to design, software tool for locating brain tumor, based on unsupervised clustering methods. K-Means clustering algorithm is implemented & tested on data base of 30 images. Performance evolution of unsupervised clusteringmethods is presented.

  12. A novel clustering and supervising users' profiles method

    Institute of Scientific and Technical Information of China (English)

    Zhu Mingfu; Zhang Hongbin; Song Fangyun

    2005-01-01

    To better understand different users' accessing intentions, a novel clustering and supervising method based on accessing path is presented. This method divides users' interest space to express the distribution of users' interests, and directly to instruct the constructing process of web pages indexing for advanced performance.

  13. A method to determine the number of nanoparticles in a cluster using conventional optical microscopes

    International Nuclear Information System (INIS)

    Kang, Hyeonggon; Attota, Ravikiran; Tondare, Vipin; Vladár, András E.; Kavuri, Premsagar

    2015-01-01

    We present a method that uses conventional optical microscopes to determine the number of nanoparticles in a cluster, which is typically not possible using traditional image-based optical methods due to the diffraction limit. The method, called through-focus scanning optical microscopy (TSOM), uses a series of optical images taken at varying focus levels to achieve this. The optical images cannot directly resolve the individual nanoparticles, but contain information related to the number of particles. The TSOM method makes use of this information to determine the number of nanoparticles in a cluster. Initial good agreement between the simulations and the measurements is also presented. The TSOM method can be applied to fluorescent and non-fluorescent as well as metallic and non-metallic nano-scale materials, including soft materials, making it attractive for tag-less, high-speed, optical analysis of nanoparticles down to 45 nm diameter

  14. Internet-based versus traditional teaching and learning methods.

    Science.gov (United States)

    Guarino, Salvatore; Leopardi, Eleonora; Sorrenti, Salvatore; De Antoni, Enrico; Catania, Antonio; Alagaratnam, Swethan

    2014-10-01

    The rapid and dramatic incursion of the Internet and social networks in everyday life has revolutionised the methods of exchanging data. Web 2.0 represents the evolution of the Internet as we know it. Internet users are no longer passive receivers, and actively participate in the delivery of information. Medical education cannot evade this process. Increasingly, students are using tablets and smartphones to instantly retrieve medical information on the web or are exchanging materials on their Facebook pages. Medical educators cannot ignore this continuing revolution, and therefore the traditional academic schedules and didactic schemes should be questioned. Analysing opinions collected from medical students regarding old and new teaching methods and tools has become mandatory, with a view towards renovating the process of medical education. A cross-sectional online survey was created with Google® docs and administrated to all students of our medical school. Students were asked to express their opinion on their favourite teaching methods, learning tools, Internet websites and Internet delivery devices. Data analysis was performed using spss. The online survey was completed by 368 students. Although textbooks remain a cornerstone for training, students also identified Internet websites, multimedia non-online material, such as the Encyclopaedia on CD-ROM, and other non-online computer resources as being useful. The Internet represented an important aid to support students' learning needs, but textbooks are still their resource of choice. Among the websites noted, Google and Wikipedia significantly surpassed the peer-reviewed medical databases, and access to the Internet was primarily through personal computers in preference to other Internet access devices, such as mobile phones and tablet computers. Increasingly, students are using tablets and smartphones to instantly retrieve medical information. © 2014 John Wiley & Sons Ltd.

  15. Image Registration Using Single Cluster PHD Methods

    Science.gov (United States)

    Campbell, M.; Schlangen, I.; Delande, E.; Clark, D.

    Cadets in the Department of Physics at the United States Air Force Academy are using the technique of slitless spectroscopy to analyze the spectra from geostationary satellites during glint season. The equinox periods of the year are particularly favorable for earth-based observers to detect specular reflections off satellites (glints), which have been observed in the past using broadband photometry techniques. Three seasons of glints were observed and analyzed for multiple satellites, as measured across the visible spectrum using a diffraction grating on the Academy’s 16-inch, f/8.2 telescope. It is clear from the results that the glint maximum wavelength decreases relative to the time periods before and after the glint, and that the spectral reflectance during the glint is less like a blackbody. These results are consistent with the presumption that solar panels are the predominant source of specular reflection. The glint spectra are also quantitatively compared to different blackbody curves and the solar spectrum by means of absolute differences and standard deviations. Our initial analysis appears to indicate a potential method of determining relative power capacity.

  16. Vinayaka : A Semi-Supervised Projected Clustering Method Using Differential Evolution

    OpenAIRE

    Satish Gajawada; Durga Toshniwal

    2012-01-01

    Differential Evolution (DE) is an algorithm for evolutionary optimization. Clustering problems have beensolved by using DE based clustering methods but these methods may fail to find clusters hidden insubspaces of high dimensional datasets. Subspace and projected clustering methods have been proposed inliterature to find subspace clusters that are present in subspaces of dataset. In this paper we proposeVINAYAKA, a semi-supervised projected clustering method based on DE. In this method DE opt...

  17. Methods of Conflict Resolution in African Traditional Society | Ajayi ...

    African Journals Online (AJOL)

    This study examined the patterns or mechanism for conflict resolution in traditional African societies with particular reference to Yoruba and Igbo societies in Nigeria and Pondo tribe in South Africa. The paper notes that conflict resolution in traditional African societies provides opportunity to interact with the parties ...

  18. Kernel method for clustering based on optimal target vector

    International Nuclear Information System (INIS)

    Angelini, Leonardo; Marinazzo, Daniele; Pellicoro, Mario; Stramaglia, Sebastiano

    2006-01-01

    We introduce Ising models, suitable for dichotomic clustering, with couplings that are (i) both ferro- and anti-ferromagnetic (ii) depending on the whole data-set and not only on pairs of samples. Couplings are determined exploiting the notion of optimal target vector, here introduced, a link between kernel supervised and unsupervised learning. The effectiveness of the method is shown in the case of the well-known iris data-set and in benchmarks of gene expression levels, where it works better than existing methods for dichotomic clustering

  19. Agent-based method for distributed clustering of textual information

    Science.gov (United States)

    Potok, Thomas E [Oak Ridge, TN; Reed, Joel W [Knoxville, TN; Elmore, Mark T [Oak Ridge, TN; Treadwell, Jim N [Louisville, TN

    2010-09-28

    A computer method and system for storing, retrieving and displaying information has a multiplexing agent (20) that calculates a new document vector (25) for a new document (21) to be added to the system and transmits the new document vector (25) to master cluster agents (22) and cluster agents (23) for evaluation. These agents (22, 23) perform the evaluation and return values upstream to the multiplexing agent (20) based on the similarity of the document to documents stored under their control. The multiplexing agent (20) then sends the document (21) and the document vector (25) to the master cluster agent (22), which then forwards it to a cluster agent (23) or creates a new cluster agent (23) to manage the document (21). The system also searches for stored documents according to a search query having at least one term and identifying the documents found in the search, and displays the documents in a clustering display (80) of similarity so as to indicate similarity of the documents to each other.

  20. Research of the Space Clustering Method for the Airport Noise Data Minings

    Directory of Open Access Journals (Sweden)

    Jiwen Xie

    2014-03-01

    Full Text Available Mining the distribution pattern and evolution of the airport noise from the airport noise data and the geographic information of the monitoring points is of great significance for the scientific and rational governance of airport noise pollution problem. However, most of the traditional clustering methods are based on the closeness of space location or the similarity of non-spatial features, which split the duality of space elements, resulting in that the clustering result has difficult in satisfying both the closeness of space location and the similarity of non-spatial features. This paper, therefore, proposes a spatial clustering algorithm based on dual-distance. This algorithm uses a distance function as the similarity measure function in which spatial features and non-spatial features are combined. The experimental results show that the proposed algorithm can discover the noise distribution pattern around the airport effectively.

  1. A cluster approximation for the transfer-matrix method

    International Nuclear Information System (INIS)

    Surda, A.

    1990-08-01

    A cluster approximation for the transfer-method is formulated. The calculation of the partition function of lattice models is transformed to a nonlinear mapping problem. The method yields the free energy, correlation functions and the phase diagrams for a large class of lattice models. The high accuracy of the method is exemplified by the calculation of the critical temperature of the Ising model. (author). 14 refs, 2 figs, 1 tab

  2. Impact of traditional processing methods on some physico chemical ...

    African Journals Online (AJOL)

    AJB SERVER

    2006-10-16

    Oct 16, 2006 ... 1Department of Food Science and Technology, University of ... need to educate traditional processors on good manufacturing practices, .... Table 3. Physical Contaminants in Fermented Cassava flour (“Kpor Umilin”) Samples.

  3. Methods of Conflict Resolution in African Traditional Society

    African Journals Online (AJOL)

    Toshiba

    Department of History and International Studies. Faculty of Arts, Ekiti State ... and market brawls, skirmishes and wars, public insurrections and assaults. ..... treaty making by traditional rulers and leaders of thought led by Igwe. Nzekwesi, for ...

  4. Fuzzy Clustering Methods and their Application to Fuzzy Modeling

    DEFF Research Database (Denmark)

    Kroszynski, Uri; Zhou, Jianjun

    1999-01-01

    Fuzzy modeling techniques based upon the analysis of measured input/output data sets result in a set of rules that allow to predict system outputs from given inputs. Fuzzy clustering methods for system modeling and identification result in relatively small rule-bases, allowing fast, yet accurate....... An illustrative synthetic example is analyzed, and prediction accuracy measures are compared between the different variants...

  5. A MULTINATIONAL COMPANY PROBLEM: INFILTRATING INTO THE CLUSTERS TO GAIN COMPETITIVE EDGE IN THE TRADITIONAL MARKETS

    Directory of Open Access Journals (Sweden)

    Murat KOC

    2014-07-01

    Full Text Available This paper is concerned with one of the main challenges of the Multinational Companies which they face in the traditional and thus in local markets. Multinational Companies aims to gain competitive advantage through differentiation in terms of their globalization strategy. However, in the local markets where the organic relationship of firms are more designed in local habits, and markets react with stable consumer behaviors, it gets harder to enter into market and drive a competitive edge. This paper aims to understand the reasons of this challenge, the analysis of resistance of traditional markets, successful sample breaking into local market and the strategy around it.

  6. Dynamic analysis of clustered building structures using substructures methods

    International Nuclear Information System (INIS)

    Leimbach, K.R.; Krutzik, N.J.

    1989-01-01

    The dynamic substructure approach to the building cluster on a common base mat starts with the generation of Ritz-vectors for each building on a rigid foundation. The base mat plus the foundation soil is subjected to kinematic constraint modes, for example constant, linear, quadratic or cubic constraints. These constraint modes are also imposed on the buildings. By enforcing kinematic compatibility of the complete structural system on the basis of the constraint modes a reduced Ritz model of the complete cluster is obtained. This reduced model can now be analyzed by modal time history or response spectrum methods

  7. Clustering Methods with Qualitative Data: a Mixed-Methods Approach for Prevention Research with Small Samples.

    Science.gov (United States)

    Henry, David; Dymnicki, Allison B; Mohatt, Nathaniel; Allen, James; Kelly, James G

    2015-10-01

    Qualitative methods potentially add depth to prevention research but can produce large amounts of complex data even with small samples. Studies conducted with culturally distinct samples often produce voluminous qualitative data but may lack sufficient sample sizes for sophisticated quantitative analysis. Currently lacking in mixed-methods research are methods allowing for more fully integrating qualitative and quantitative analysis techniques. Cluster analysis can be applied to coded qualitative data to clarify the findings of prevention studies by aiding efforts to reveal such things as the motives of participants for their actions and the reasons behind counterintuitive findings. By clustering groups of participants with similar profiles of codes in a quantitative analysis, cluster analysis can serve as a key component in mixed-methods research. This article reports two studies. In the first study, we conduct simulations to test the accuracy of cluster assignment using three different clustering methods with binary data as produced when coding qualitative interviews. Results indicated that hierarchical clustering, K-means clustering, and latent class analysis produced similar levels of accuracy with binary data and that the accuracy of these methods did not decrease with samples as small as 50. Whereas the first study explores the feasibility of using common clustering methods with binary data, the second study provides a "real-world" example using data from a qualitative study of community leadership connected with a drug abuse prevention project. We discuss the implications of this approach for conducting prevention research, especially with small samples and culturally distinct communities.

  8. Clustering Methods with Qualitative Data: A Mixed Methods Approach for Prevention Research with Small Samples

    Science.gov (United States)

    Henry, David; Dymnicki, Allison B.; Mohatt, Nathaniel; Allen, James; Kelly, James G.

    2016-01-01

    Qualitative methods potentially add depth to prevention research, but can produce large amounts of complex data even with small samples. Studies conducted with culturally distinct samples often produce voluminous qualitative data, but may lack sufficient sample sizes for sophisticated quantitative analysis. Currently lacking in mixed methods research are methods allowing for more fully integrating qualitative and quantitative analysis techniques. Cluster analysis can be applied to coded qualitative data to clarify the findings of prevention studies by aiding efforts to reveal such things as the motives of participants for their actions and the reasons behind counterintuitive findings. By clustering groups of participants with similar profiles of codes in a quantitative analysis, cluster analysis can serve as a key component in mixed methods research. This article reports two studies. In the first study, we conduct simulations to test the accuracy of cluster assignment using three different clustering methods with binary data as produced when coding qualitative interviews. Results indicated that hierarchical clustering, K-Means clustering, and latent class analysis produced similar levels of accuracy with binary data, and that the accuracy of these methods did not decrease with samples as small as 50. Whereas the first study explores the feasibility of using common clustering methods with binary data, the second study provides a “real-world” example using data from a qualitative study of community leadership connected with a drug abuse prevention project. We discuss the implications of this approach for conducting prevention research, especially with small samples and culturally distinct communities. PMID:25946969

  9. a Probabilistic Embedding Clustering Method for Urban Structure Detection

    Science.gov (United States)

    Lin, X.; Li, H.; Zhang, Y.; Gao, L.; Zhao, L.; Deng, M.

    2017-09-01

    Urban structure detection is a basic task in urban geography. Clustering is a core technology to detect the patterns of urban spatial structure, urban functional region, and so on. In big data era, diverse urban sensing datasets recording information like human behaviour and human social activity, suffer from complexity in high dimension and high noise. And unfortunately, the state-of-the-art clustering methods does not handle the problem with high dimension and high noise issues concurrently. In this paper, a probabilistic embedding clustering method is proposed. Firstly, we come up with a Probabilistic Embedding Model (PEM) to find latent features from high dimensional urban sensing data by "learning" via probabilistic model. By latent features, we could catch essential features hidden in high dimensional data known as patterns; with the probabilistic model, we can also reduce uncertainty caused by high noise. Secondly, through tuning the parameters, our model could discover two kinds of urban structure, the homophily and structural equivalence, which means communities with intensive interaction or in the same roles in urban structure. We evaluated the performance of our model by conducting experiments on real-world data and experiments with real data in Shanghai (China) proved that our method could discover two kinds of urban structure, the homophily and structural equivalence, which means clustering community with intensive interaction or under the same roles in urban space.

  10. A PROBABILISTIC EMBEDDING CLUSTERING METHOD FOR URBAN STRUCTURE DETECTION

    Directory of Open Access Journals (Sweden)

    X. Lin

    2017-09-01

    Full Text Available Urban structure detection is a basic task in urban geography. Clustering is a core technology to detect the patterns of urban spatial structure, urban functional region, and so on. In big data era, diverse urban sensing datasets recording information like human behaviour and human social activity, suffer from complexity in high dimension and high noise. And unfortunately, the state-of-the-art clustering methods does not handle the problem with high dimension and high noise issues concurrently. In this paper, a probabilistic embedding clustering method is proposed. Firstly, we come up with a Probabilistic Embedding Model (PEM to find latent features from high dimensional urban sensing data by “learning” via probabilistic model. By latent features, we could catch essential features hidden in high dimensional data known as patterns; with the probabilistic model, we can also reduce uncertainty caused by high noise. Secondly, through tuning the parameters, our model could discover two kinds of urban structure, the homophily and structural equivalence, which means communities with intensive interaction or in the same roles in urban structure. We evaluated the performance of our model by conducting experiments on real-world data and experiments with real data in Shanghai (China proved that our method could discover two kinds of urban structure, the homophily and structural equivalence, which means clustering community with intensive interaction or under the same roles in urban space.

  11. Application of a Light-Front Coupled Cluster Method

    International Nuclear Information System (INIS)

    Chabysheva, S.S.; Hiller, J.R.

    2012-01-01

    As a test of the new light-front coupled-cluster method in a gauge theory, we apply it to the nonperturbative construction of the dressed-electron state in QED, for an arbitrary covariant gauge, and compute the electron's anomalous magnetic moment. The construction illustrates the spectator and Fock-sector independence of vertex and self-energy contributions and indicates resolution of the difficulties with uncanceled divergences that plague methods based on Fock-space truncation. (author)

  12. A Clustering Method for Data in Cylindrical Coordinates

    Directory of Open Access Journals (Sweden)

    Kazuhisa Fujita

    2017-01-01

    Full Text Available We propose a new clustering method for data in cylindrical coordinates based on the k-means. The goal of the k-means family is to maximize an optimization function, which requires a similarity. Thus, we need a new similarity to obtain the new clustering method for data in cylindrical coordinates. In this study, we first derive a new similarity for the new clustering method by assuming a particular probabilistic model. A data point in cylindrical coordinates has radius, azimuth, and height. We assume that the azimuth is sampled from a von Mises distribution and the radius and the height are independently generated from isotropic Gaussian distributions. We derive the new similarity from the log likelihood of the assumed probability distribution. Our experiments demonstrate that the proposed method using the new similarity can appropriately partition synthetic data defined in cylindrical coordinates. Furthermore, we apply the proposed method to color image quantization and show that the methods successfully quantize a color image with respect to the hue element.

  13. Feminist Policy Analysis: Expanding Traditional Social Work Methods

    Science.gov (United States)

    Kanenberg, Heather

    2013-01-01

    In an effort to move the methodology of policy analysis beyond the traditional and artificial position of being objective and value-free, this article is a call to those working and teaching in social work to consider a feminist policy analysis lens. A review of standard policy analysis models is presented alongside feminist models. Such a…

  14. Performance of traditional and direct labour procurement methods ...

    African Journals Online (AJOL)

    The objective was to find out if one has any advantage over the other. Project success determinants like cost, time and quality formed the basis for ... and unit cost of projects were higher for those procured using the traditional contract system.

  15. Non-traditional vibration mitigation methods for reciprocating compressor system

    NARCIS (Netherlands)

    Eijk, A.; Lange, T.J. de; Vreugd, J. de; Slis, E.J.P.

    2016-01-01

    Reciprocating compressors generate vibrations caused by pulsation-induced forces, mechanical (unbalanced) free forces and moments, crosshead guide forces and cylinder stretch forces. The traditional way of mitigating the vibration and cyclic stress levels to avoid fatigue failure of parts of the

  16. A method of clustering observers with different visual characteristics

    Energy Technology Data Exchange (ETDEWEB)

    Niimi, Takanaga [Nagoya University School of Health Sciences, Department of Radiological Technology, 1-1-20 Daiko-minami, Higashi-ku, Nagoya 461-8673 (Japan); Imai, Kuniharu [Nagoya University School of Health Sciences, Department of Radiological Technology, 1-1-20 Daiko-minami, Higashi-ku, Nagoya 461-8673 (Japan); Ikeda, Mitsuru [Nagoya University School of Health Sciences, Department of Radiological Technology, 1-1-20 Daiko-minami, Higashi-ku, Nagoya 461-8673 (Japan); Maeda, Hisatoshi [Nagoya University School of Health Sciences, Department of Radiological Technology, 1-1-20 Daiko-minami, Higashi-ku, Nagoya 461-8673 (Japan)

    2006-01-15

    Evaluation of observer's image perception in medical images is important, and yet has not been performed because it is difficult to quantify visual characteristics. In the present study, we investigated the observer's image perception by clustering a group of 20 observers. Images of a contrast-detail (C-D) phantom, which had cylinders of 10 rows and 10 columns with different diameters and lengths, were acquired with an X-ray screen-film system with fixed exposure conditions. A group of 10 films were prepared for visual evaluations. Sixteen radiological technicians, three radiologists and one medical physicist participated in the observation test. All observers read the phantom radiographs on a transillumination image viewer with room lights off. The detectability was defined as the shortest length of the cylinders of which border the observers could recognize from the background, and was recorded using the number of columns. The detectability was calculated as the average of 10 readings for each observer, and plotted for different phantom diameter. The unweighted pair-group method using arithmetic averages (UPGMA) was adopted for clustering. The observers were clustered into two groups: one group selected objects with a demarcation from the vicinity, and the other group searched for the objects with their eyes constrained. This study showed a usefulness of the cluster method to select personnel with the similar perceptual predisposition when a C-D phantom was used in image quality control.

  17. A method of clustering observers with different visual characteristics

    International Nuclear Information System (INIS)

    Niimi, Takanaga; Imai, Kuniharu; Ikeda, Mitsuru; Maeda, Hisatoshi

    2006-01-01

    Evaluation of observer's image perception in medical images is important, and yet has not been performed because it is difficult to quantify visual characteristics. In the present study, we investigated the observer's image perception by clustering a group of 20 observers. Images of a contrast-detail (C-D) phantom, which had cylinders of 10 rows and 10 columns with different diameters and lengths, were acquired with an X-ray screen-film system with fixed exposure conditions. A group of 10 films were prepared for visual evaluations. Sixteen radiological technicians, three radiologists and one medical physicist participated in the observation test. All observers read the phantom radiographs on a transillumination image viewer with room lights off. The detectability was defined as the shortest length of the cylinders of which border the observers could recognize from the background, and was recorded using the number of columns. The detectability was calculated as the average of 10 readings for each observer, and plotted for different phantom diameter. The unweighted pair-group method using arithmetic averages (UPGMA) was adopted for clustering. The observers were clustered into two groups: one group selected objects with a demarcation from the vicinity, and the other group searched for the objects with their eyes constrained. This study showed a usefulness of the cluster method to select personnel with the similar perceptual predisposition when a C-D phantom was used in image quality control

  18. Non-Deterministic, Non-Traditional Methods (NDNTM)

    Science.gov (United States)

    Cruse, Thomas A.; Chamis, Christos C. (Technical Monitor)

    2001-01-01

    The review effort identified research opportunities related to the use of nondeterministic, nontraditional methods to support aerospace design. The scope of the study was restricted to structural design rather than other areas such as control system design. Thus, the observations and conclusions are limited by that scope. The review identified a number of key results. The results include the potential for NASA/AF collaboration in the area of a design environment for advanced space access vehicles. The following key points set the context and delineate the key results. The Principal Investigator's (PI's) context for this study derived from participation as a Panel Member in the Air Force Scientific Advisory Board (AF/SAB) Summer Study Panel on 'Whither Hypersonics?' A key message from the Summer Study effort was a perceived need for a national program for a space access vehicle whose operating characteristics of cost, availability, deployability, and reliability most closely match the NASA 3rd Generation Reusable Launch Vehicle (RLV). The Panel urged the AF to make a significant joint commitment to such a program just as soon as the AF defined specific requirements for space access consistent with the AF Aerospace Vision 2020. The review brought home a concurrent need for a national vehicle design environment. Engineering design system technology is at a time point from which a revolution as significant as that brought about by the finite element method is possible, this one focusing on information integration on a scale that far surpasses current design environments. The study therefore fully supported the concept, if not some of the details of the Intelligent Synthesis Environment (ISE). It became abundantly clear during this study that the government (AF, NASA) and industry are not moving in the same direction in this regard, in fact each is moving in its own direction. NASA/ISE is not yet in an effective leadership position in this regard. However, NASA does

  19. Smoothed Particle Inference: A Kilo-Parametric Method for X-ray Galaxy Cluster Modeling

    Energy Technology Data Exchange (ETDEWEB)

    Peterson, John R.; Marshall, P.J.; /KIPAC, Menlo Park; Andersson, K.; /Stockholm U. /SLAC

    2005-08-05

    We propose an ambitious new method that models the intracluster medium in clusters of galaxies as a set of X-ray emitting smoothed particles of plasma. Each smoothed particle is described by a handful of parameters including temperature, location, size, and elemental abundances. Hundreds to thousands of these particles are used to construct a model cluster of galaxies, with the appropriate complexity estimated from the data quality. This model is then compared iteratively with X-ray data in the form of adaptively binned photon lists via a two-sample likelihood statistic and iterated via Markov Chain Monte Carlo. The complex cluster model is propagated through the X-ray instrument response using direct sampling Monte Carlo methods. Using this approach the method can reproduce many of the features observed in the X-ray emission in a less assumption-dependent way that traditional analyses, and it allows for a more detailed characterization of the density, temperature, and metal abundance structure of clusters. Multi-instrument X-ray analyses and simultaneous X-ray, Sunyaev-Zeldovich (SZ), and lensing analyses are a straight-forward extension of this methodology. Significant challenges still exist in understanding the degeneracy in these models and the statistical noise induced by the complexity of the models.

  20. Molecular Methods for Identification of Microorganisms in Traditional Meat Products

    Science.gov (United States)

    Cocolin, Luca; Dolci, Paola; Rantsiou, Kalliopi

    Traditional fermentations are those that have been used for centuries and even pre-date written historical records. Fermentation processes have been developed to upgrade plant and animal materials, to yield a more acceptable food, to add flavor, to prevent the growth of pathogenic and spoilage microorganisms, and to preserve food without refrigeration (Hesseltine & Wang, 1980). Among fermented foods, sausages are the meat products with a longer history and tradition. It is often assumed that sausages were invented by the Sumerians, in what is Iraq today, around 3000 BC. Chinese sausage làcháng, which consisted of goat and lamb meat, was first mentioned in 589 BC. Homer, the poet of The Ancient Greece, mentioned a kind of blood sausage in the Odyssey (book 20, verse 25), and Epicharmus (ca. 550 BC-ca. 460 BC) wrote a comedy entitled “The Sausage”.

  1. Unbiased methods for removing systematics from galaxy clustering measurements

    Science.gov (United States)

    Elsner, Franz; Leistedt, Boris; Peiris, Hiranya V.

    2016-02-01

    Measuring the angular clustering of galaxies as a function of redshift is a powerful method for extracting information from the three-dimensional galaxy distribution. The precision of such measurements will dramatically increase with ongoing and future wide-field galaxy surveys. However, these are also increasingly sensitive to observational and astrophysical contaminants. Here, we study the statistical properties of three methods proposed for controlling such systematics - template subtraction, basic mode projection, and extended mode projection - all of which make use of externally supplied template maps, designed to characterize and capture the spatial variations of potential systematic effects. Based on a detailed mathematical analysis, and in agreement with simulations, we find that the template subtraction method in its original formulation returns biased estimates of the galaxy angular clustering. We derive closed-form expressions that should be used to correct results for this shortcoming. Turning to the basic mode projection algorithm, we prove it to be free of any bias, whereas we conclude that results computed with extended mode projection are biased. Within a simplified setup, we derive analytical expressions for the bias and discuss the options for correcting it in more realistic configurations. Common to all three methods is an increased estimator variance induced by the cleaning process, albeit at different levels. These results enable unbiased high-precision clustering measurements in the presence of spatially varying systematics, an essential step towards realizing the full potential of current and planned galaxy surveys.

  2. Advanced cluster methods for correlated-electron systems

    Energy Technology Data Exchange (ETDEWEB)

    Fischer, Andre

    2015-04-27

    In this thesis, quantum cluster methods are used to calculate electronic properties of correlated-electron systems. A special focus lies in the determination of the ground state properties of a 3/4 filled triangular lattice within the one-band Hubbard model. At this filling, the electronic density of states exhibits a so-called van Hove singularity and the Fermi surface becomes perfectly nested, causing an instability towards a variety of spin-density-wave (SDW) and superconducting states. While chiral d+id-wave superconductivity has been proposed as the ground state in the weak coupling limit, the situation towards strong interactions is unclear. Additionally, quantum cluster methods are used here to investigate the interplay of Coulomb interactions and symmetry-breaking mechanisms within the nematic phase of iron-pnictide superconductors. The transition from a tetragonal to an orthorhombic phase is accompanied by a significant change in electronic properties, while long-range magnetic order is not established yet. The driving force of this transition may not only be phonons but also magnetic or orbital fluctuations. The signatures of these scenarios are studied with quantum cluster methods to identify the most important effects. Here, cluster perturbation theory (CPT) and its variational extention, the variational cluster approach (VCA) are used to treat the respective systems on a level beyond mean-field theory. Short-range correlations are incorporated numerically exactly by exact diagonalization (ED). In the VCA, long-range interactions are included by variational optimization of a fictitious symmetry-breaking field based on a self-energy functional approach. Due to limitations of ED, cluster sizes are limited to a small number of degrees of freedom. For the 3/4 filled triangular lattice, the VCA is performed for different cluster symmetries. A strong symmetry dependence and finite-size effects make a comparison of the results from different clusters difficult

  3. 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.

  4. Adaptive cluster sampling: An efficient method for assessing inconspicuous species

    Science.gov (United States)

    Andrea M. Silletti; Joan Walker

    2003-01-01

    Restorationistis typically evaluate the success of a project by estimating the population sizes of species that have been planted or seeded. Because total census is raely feasible, they must rely on sampling methods for population estimates. However, traditional random sampling designs may be inefficient for species that, for one reason or another, are challenging to...

  5. Puzzle of magnetic moments of Ni clusters revisited using quantum Monte Carlo method.

    Science.gov (United States)

    Lee, Hung-Wen; Chang, Chun-Ming; Hsing, Cheng-Rong

    2017-02-28

    The puzzle of the magnetic moments of small nickel clusters arises from the discrepancy between values predicted using density functional theory (DFT) and experimental measurements. Traditional DFT approaches underestimate the magnetic moments of nickel clusters. Two fundamental problems are associated with this puzzle, namely, calculating the exchange-correlation interaction accurately and determining the global minimum structures of the clusters. Theoretically, the two problems can be solved using quantum Monte Carlo (QMC) calculations and the ab initio random structure searching (AIRSS) method correspondingly. Therefore, we combined the fixed-moment AIRSS and QMC methods to investigate the magnetic properties of Ni n (n = 5-9) clusters. The spin moments of the diffusion Monte Carlo (DMC) ground states are higher than those of the Perdew-Burke-Ernzerhof ground states and, in the case of Ni 8-9 , two new ground-state structures have been discovered using the DMC calculations. The predicted results are closer to the experimental findings, unlike the results predicted in previous standard DFT studies.

  6. The cosmological analysis of X-ray cluster surveys - I. A new method for interpreting number counts

    Science.gov (United States)

    Clerc, N.; Pierre, M.; Pacaud, F.; Sadibekova, T.

    2012-07-01

    We present a new method aimed at simplifying the cosmological analysis of X-ray cluster surveys. It is based on purely instrumental observable quantities considered in a two-dimensional X-ray colour-magnitude diagram (hardness ratio versus count rate). The basic principle is that even in rather shallow surveys, substantial information on cluster redshift and temperature is present in the raw X-ray data and can be statistically extracted; in parallel, such diagrams can be readily predicted from an ab initio cosmological modelling. We illustrate the methodology for the case of a 100-deg2XMM survey having a sensitivity of ˜10-14 erg s-1 cm-2 and fit at the same time, the survey selection function, the cluster evolutionary scaling relations and the cosmology; our sole assumption - driven by the limited size of the sample considered in the case study - is that the local cluster scaling relations are known. We devote special attention to the realistic modelling of the count-rate measurement uncertainties and evaluate the potential of the method via a Fisher analysis. In the absence of individual cluster redshifts, the count rate and hardness ratio (CR-HR) method appears to be much more efficient than the traditional approach based on cluster counts (i.e. dn/dz, requiring redshifts). In the case where redshifts are available, our method performs similar to the traditional mass function (dn/dM/dz) for the purely cosmological parameters, but constrains better parameters defining the cluster scaling relations and their evolution. A further practical advantage of the CR-HR method is its simplicity: this fully top-down approach totally bypasses the tedious steps consisting in deriving cluster masses from X-ray temperature measurements.

  7. Conciliation as the traditional method of disputes settlement in PRC

    Directory of Open Access Journals (Sweden)

    Svetlana F. Litvinova

    2011-12-01

    Full Text Available The author of the article researches one of the peculiarities of civil disputes settlement in China. This peculiarity is the conciliatory method that is used during disputes settlement. The using of the method is based on Confucianism. The content of the method has been viewed in the article.

  8. A Comparison of Methods for Player Clustering via Behavioral Telemetry

    DEFF Research Database (Denmark)

    Drachen, Anders; Thurau, C.; Sifa, R.

    2013-01-01

    patterns in the behavioral data, and developing profiles that are actionable to game developers. There are numerous methods for unsupervised clustering of user behavior, e.g. k-means/c-means, Nonnegative Matrix Factorization, or Principal Component Analysis. Although all yield behavior categorizations......, interpretation of the resulting categories in terms of actual play behavior can be difficult if not impossible. In this paper, a range of unsupervised techniques are applied together with Archetypal Analysis to develop behavioral clusters from playtime data of 70,014 World of Warcraft players, covering a five......The analysis of user behavior in digital games has been aided by the introduction of user telemetry in game development, which provides unprecedented access to quantitative data on user behavior from the installed game clients of the entire population of players. Player behavior telemetry datasets...

  9. Cluster monte carlo method for nuclear criticality safety calculation

    International Nuclear Information System (INIS)

    Pei Lucheng

    1984-01-01

    One of the most important applications of the Monte Carlo method is the calculation of the nuclear criticality safety. The fair source game problem was presented at almost the same time as the Monte Carlo method was applied to calculating the nuclear criticality safety. The source iteration cost may be reduced as much as possible or no need for any source iteration. This kind of problems all belongs to the fair source game prolems, among which, the optimal source game is without any source iteration. Although the single neutron Monte Carlo method solved the problem without the source iteration, there is still quite an apparent shortcoming in it, that is, it solves the problem without the source iteration only in the asymptotic sense. In this work, a new Monte Carlo method called the cluster Monte Carlo method is given to solve the problem further

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

    Directory of Open Access Journals (Sweden)

    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.

  11. Improvement in the traditional processing method and nutritional quality of traditional extruded cassava-based snack (modified Ajogun).

    Science.gov (United States)

    Obadina, Adewale O; Oyewole, Olusola B; Williams, Oluwasolabomi E

    2013-07-01

    This study was carried out to investigate and improve the traditional processing method and nutritional quality of the traditional cassava snack (Ajogun). Cassava root (Manihot esculenta Crantz L.) of TME 419 variety was processed into mash (40% moisture content). The cassava mash was mixed into different blends to produce fried traditional "Ajogun", fried and baked extrudates (modified Ajogun) as snacks. These products were analyzed to determine the proximate composition including carbohydrate, fat, protein, fiber, ash, and moisture contents and functional properties such as bulk density. The results obtained for the moisture, fat, protein, and ash contents showed significant difference (P extrudates. However, there was no significant difference (P > 0.05) in the carbohydrate and fiber contents between the three samples. There was no significant difference (P > 0.05) in the bulk density of the snacks. Also, sensory evaluation was carried out on the cassava-based snacks using the 9-point hedonic scale to determine the degree of acceptability. Results obtained showed significant difference (P extrudates and control sample in terms of appearance, taste, flavor, color, aroma, texture, and overall acceptability. The highest acceptability level of the product was at 8.04 for the control sample (traditional Ajogun). This study has shown that "Ajogun", which is a lesser known cassava product, is rich in protein and fat.

  12. Hierarchical and Complex System Entropy Clustering Analysis Based Validation for Traditional Chinese Medicine Syndrome Patterns of Chronic Atrophic Gastritis.

    Science.gov (United States)

    Zhang, Yin; Liu, Yue; Li, Yannan; Zhao, Xia; Zhuo, Lin; Zhou, Ajian; Zhang, Li; Su, Zeqi; Chen, Cen; Du, Shiyu; Liu, Daming; Ding, Xia

    2018-03-22

    Chronic atrophic gastritis (CAG) is the precancerous stage of gastric carcinoma. Traditional Chinese Medicine (TCM) has been widely used in treating CAG. This study aimed to reveal core pathogenesis of CAG by validating the TCM syndrome patterns and provide evidence for optimization of treatment strategies. This is a cross-sectional study conducted in 4 hospitals in China. Hierarchical clustering analysis (HCA) and complex system entropy clustering analysis (CSECA) were performed, respectively, to achieve syndrome pattern validation. Based on HCA, 15 common factors were assigned to 6 syndrome patterns: liver depression and spleen deficiency and blood stasis in the stomach collateral, internal harassment of phlegm-heat and blood stasis in the stomach collateral, phlegm-turbidity internal obstruction, spleen yang deficiency, internal harassment of phlegm-heat and spleen deficiency, and spleen qi deficiency. By CSECA, 22 common factors were assigned to 7 syndrome patterns: qi deficiency, qi stagnation, blood stasis, phlegm turbidity, heat, yang deficiency, and yin deficiency. Combination of qi deficiency, qi stagnation, blood stasis, phlegm turbidity, heat, yang deficiency, and yin deficiency may play a crucial role in CAG pathogenesis. In accord with this, treatment strategies by TCM herbal prescriptions should be targeted to regulating qi, activating blood, resolving turbidity, clearing heat, removing toxin, nourishing yin, and warming yang. Further explorations are needed to verify and expand the current conclusions.

  13. Effect of Traditional smoking Method on Nutritive Values and ...

    African Journals Online (AJOL)

    SH

    smoking method is an important preservation method which could enhance the nutritive values of fishes and possibly reduce post-harvest losses. Keywords: ... Fishery Laboratory of College of. Agricultural Sciences, Olabisi Onabanjo .... colour helps to determine quality, degree of processing or spoilage level (Clifford et al.,.

  14. Examining Delivery Method and Infant Feeding Intentions between Women in Traditional and Non-Traditional Prenatal Care.

    Science.gov (United States)

    Risisky, Deb; Chan, Ronna L; Zigmont, Victoria A; Asghar, Syed Masood; DeGennaro, Nancy

    2018-02-01

    Introduction The purpose of the study is to evaluate delivery method and breastfeeding initiation in women enrolled in group prenatal care (CenteringPregnancy) and in traditional prenatal care. Methods Data were obtained from medical records of a hospital-based midwifery practice in south central Connecticut that offered both types of prenatal care programs. Medical information from 307 women enrolled in this practice was included in the analysis. Out of the 307, 80 were enrolled in group prenatal care. Socio-demographic, lifestyle, and previous and current obstetrical information from medical records formed the basis of comparison. Bivariate and logistic regression analyses were carried out. Results Women in Centering had fewer planned cesarean sections (1.3 vs. 12.8%) and had a higher breastfeeding initiation (88.7 vs. 80.0%). However, Centering women were found to have a higher portion of unplanned cesarean sections (27.5 vs. 11.0%). Both the unadjusted and the adjusted odds ratios of having a cesarean planned delivery were lower in the group care. Women in Centering had 2.44 (95% CI 1.05, 5.66) times the odds of breastfeeding initiation compared to the odds for women in traditional prenatal care after adjusting for maternal age, smoking status, gestation and race. Discussion CenteringPregnancy can have positive impact for the woman and baby. This program implementation saw lower rates of elective cesarean sections and increased breastfeeding compared to women in traditional care.

  15. Method of removing crud deposited on fuel element clusters

    International Nuclear Information System (INIS)

    Yokota, Tokunobu; Yashima, Akira; Tajima, Jun-ichiro.

    1982-01-01

    Purpose: To enable easy elimination of claddings deposited on the surface of fuel element. Method: An operator manipulates a pole from above a platform, engages the longitudinal flange of the cover to the opening at the upper end of a channel box and starts up a suction pump. The suction amount of the pump is set such that water flow becomes within the channel box at greater flow rate than the operational flow rate in the channel box of the fuel element clusters during reactor operation. This enables to remove crud deposited on the surface of individual fuel elements with ease and rapidly without detaching the channel box. (Moriyama, K.)

  16. a Three-Step Spatial-Temporal Clustering Method for Human Activity Pattern Analysis

    Science.gov (United States)

    Huang, W.; Li, S.; Xu, S.

    2016-06-01

    How people move in cities and what they do in various locations at different times form human activity patterns. Human activity pattern plays a key role in in urban planning, traffic forecasting, public health and safety, emergency response, friend recommendation, and so on. Therefore, scholars from different fields, such as social science, geography, transportation, physics and computer science, have made great efforts in modelling and analysing human activity patterns or human mobility patterns. One of the essential tasks in such studies is to find the locations or places where individuals stay to perform some kind of activities before further activity pattern analysis. In the era of Big Data, the emerging of social media along with wearable devices enables human activity data to be collected more easily and efficiently. Furthermore, the dimension of the accessible human activity data has been extended from two to three (space or space-time) to four dimensions (space, time and semantics). More specifically, not only a location and time that people stay and spend are collected, but also what people "say" for in a location at a time can be obtained. The characteristics of these datasets shed new light on the analysis of human mobility, where some of new methodologies should be accordingly developed to handle them. Traditional methods such as neural networks, statistics and clustering have been applied to study human activity patterns using geosocial media data. Among them, clustering methods have been widely used to analyse spatiotemporal patterns. However, to our best knowledge, few of clustering algorithms are specifically developed for handling the datasets that contain spatial, temporal and semantic aspects all together. In this work, we propose a three-step human activity clustering method based on space, time and semantics to fill this gap. One-year Twitter data, posted in Toronto, Canada, is used to test the clustering-based method. The results show that the

  17. A THREE-STEP SPATIAL-TEMPORAL-SEMANTIC CLUSTERING METHOD FOR HUMAN ACTIVITY PATTERN ANALYSIS

    Directory of Open Access Journals (Sweden)

    W. Huang

    2016-06-01

    Full Text Available How people move in cities and what they do in various locations at different times form human activity patterns. Human activity pattern plays a key role in in urban planning, traffic forecasting, public health and safety, emergency response, friend recommendation, and so on. Therefore, scholars from different fields, such as social science, geography, transportation, physics and computer science, have made great efforts in modelling and analysing human activity patterns or human mobility patterns. One of the essential tasks in such studies is to find the locations or places where individuals stay to perform some kind of activities before further activity pattern analysis. In the era of Big Data, the emerging of social media along with wearable devices enables human activity data to be collected more easily and efficiently. Furthermore, the dimension of the accessible human activity data has been extended from two to three (space or space-time to four dimensions (space, time and semantics. More specifically, not only a location and time that people stay and spend are collected, but also what people “say” for in a location at a time can be obtained. The characteristics of these datasets shed new light on the analysis of human mobility, where some of new methodologies should be accordingly developed to handle them. Traditional methods such as neural networks, statistics and clustering have been applied to study human activity patterns using geosocial media data. Among them, clustering methods have been widely used to analyse spatiotemporal patterns. However, to our best knowledge, few of clustering algorithms are specifically developed for handling the datasets that contain spatial, temporal and semantic aspects all together. In this work, we propose a three-step human activity clustering method based on space, time and semantics to fill this gap. One-year Twitter data, posted in Toronto, Canada, is used to test the clustering-based method. The

  18. Traditional Methods Used in Family Planning and Conception in ...

    African Journals Online (AJOL)

    ... knowledge and incorporate it into the national health care delivery service. Researchers should document the available indigenous knowledge before they are forgotten while ascertaining the validity of some of the methods. Keywords: Maternal health, family planning, pregnancy management, homebased health care.

  19. Effects of different traditional cooking methods on nutrients and ...

    African Journals Online (AJOL)

    The objective of this research was to determine the effect of cooking using two different methods of preparing okra soup in Ondo state on nutrient, mineral content including zinc bioavailability of okra, Abelmoschus esculentus. The okra fruits were grated and divided into four lots; two lots were cooked with other ingredients of ...

  20. Innovative Teaching Practice: Traditional and Alternative Methods (Challenges and Implications)

    Science.gov (United States)

    Nurutdinova, Aida R.; Perchatkina, Veronika G.; Zinatullina, Liliya M.; Zubkova, Guzel I.; Galeeva, Farida T.

    2016-01-01

    The relevance of the present issue is caused be the strong need in alternative methods of learning foreign language and the need in language training and retraining for the modern professionals. The aim of the article is to identify the basic techniques and skills in using various modern techniques in the context of modern educational tasks. The…

  1. [Essential procedure and key methods for survey of traditional knowledge related to Chinese materia medica resources].

    Science.gov (United States)

    Cheng, Gong; Huang, Lu-qi; Xue, Da-yuan; Zhang, Xiao-bo

    2014-12-01

    The survey of traditional knowledge related to Chinese materia medica resources is the important component and one of the innovative aspects of the fourth national survey of the Chinese materia medica resources. China has rich traditional knowledge of traditional Chinese medicine (TCM) and the comprehensive investigation of TCM traditional knowledge aims to promote conservation and sustainable use of Chinese materia medica resources. Building upon the field work of pilot investigations, this paper introduces the essential procedures and key methods for conducting the survey of traditional knowledge related to Chinese materia medica resources. The essential procedures are as follows. First is the preparation phrase. It is important to review all relevant literature and provide training to the survey teams so that they have clear understanding of the concept of traditional knowledge and master key survey methods. Second is the field investigation phrase. When conducting field investigations, survey teams should identify the traditional knowledge holders by using the 'snowball method', record the traditional knowledge after obtaining prior informed concerned from the traditional knowledge holders. Researchers should fill out the survey forms provided by the Technical Specification of the Fourth National Survey of Chinese Materia Medica Resources. Researchers should pay particular attention to the scope of traditional knowledge and the method of inheriting the knowledge, which are the key information for traditional knowledge holders and potential users to reach mutual agreed terms to achieve benefit sharing. Third is the data compilation and analysis phrase. Researchers should try to compile and edit the TCM traditional knowledge in accordance with intellectual property rights requirements so that the information collected through the national survey can serve as the basic data for the TCM traditional knowledge database. The key methods of the survey include regional

  2. [Research on medical speciality of traditional Chinese medicines using dot-immunoblotting method based on polyclonal antibody prepared from traditional Chinese medicines with hot/cold nature].

    Science.gov (United States)

    Wang, Houwei; Dou, Yanling; Tian, Jingzhen; Li, Feng; Wang, Shijun; Wang, Zhenguo

    2009-02-01

    To research on the substantial foundation of the medical speciality of Chinese traditional medicines from immunogenicity. Control antigen with hot nature was prepared from the mixture of the aqueous extracts of three Chinese traditional medicines with three typical hot nature of Alpinia officinarum, Cinnamomum cassia and Curculigo orchioides, while that with cold nature prepared with Rheum palmatum, Anemarrhena asphodeloides, Coptis chinensis, and polyclonal antibody was prepared by immunizing rabbit with control antigen. Dot blotting was performed between the polyclonal antibody of control antigen and the aqueous extracts of nine Chinese traditional medicines on a piece of PVDF membrane, and the blotting signals were analyzed by the software of Quantity One. Blotting signals with hot control antigen of nine Chinese traditional medicines in descending were Zingiber officinale, Aconitum carmichaeli, Eucommia ulmoides, Fraxinus rhynchophylla, Lonicera japonica, Anemarrhena asphodeloides, Coptis chinensis, Rheum palmatum and Phellodendron chinense, which degree of similarity to control antigen in peak value were 57.33%, 43.56 %, 34.16%, 30.2%, 28.81%, 26.53%, 21.68%, 17.62% and 14.85%, respectively. Blotting signals with cold control antigen were Rheum palmatum, Anemarrhena asphodeloides, Coptis chinensis, Phellodendron chinense, Zingiber officinale, Lonicera japonica, Fraxinus rhynchophylla, Eucommia ulmoides and Aconitum carmichaeli in descending, of which degree of similarity to cold control antigen in peak value were 55.22%, 54.23%, 46.72%, 34.08%, 30.3%, 24.48%, 24.33%, 20.35% and 15.17%, respectively. Results of cluster analysis with Wistar's method showed that nine medicines were classified into two groups, one group included Phellodendron chinense, Anemarrhena asphodeloides, Coptis chinensis, Rheum palmatum, another was Zingiber officinale, Aconitum carmichaeli, Eucommia ulmoides, Fraxinus rhynchophylla, Lonicera japonica. Blotting signals of nine medicines

  3. Blasting vibrations control: The shortcomings of traditional methods

    Energy Technology Data Exchange (ETDEWEB)

    Vuillaume, P.M.; Kiszlo, M. [Institut National de l`Environnement Industriel et des Risques, Verneuil en Halatte (France); Bernard, T. [Compagnie Nouvelle de Scientifiques, Nice (France)

    1996-12-31

    In the context of its studies for the French ministry of the environment and for the French national coal board, INERIS (the French institute for the industrial environment and hazards, formerly CERCHAR) has made a complete critical survey of the methods generally used to reduce the levels of blasting vibrations. It is generally acknowledged that the main parameter to control vibrations is the so-called instantaneous charge, or charge per delay. This should be reduced as much as possible in order to diminish vibration levels. On account of this, the use of a new generation of blasting devices, such as non-electric detonators or electronic sequential timers has been developed since the seventies. INERIS has collected data from about 900 blasts in 2 quarries and 3 open pit mines. These data include input parameters such as borehole diameter, burden, spacing, charge per hole, charge per delay, total fired charge, etc ... They also include output measurements, such as vibration peak particle velocities, and main frequencies. These data have been analyzed with the help of multi variable statistical tools. Blasting tests were undertaken to evaluate new methods of vibrations control, such as the superposition of vibration signals. These methods appear to be accurate in many critical cases, but certainly would be highly improved with a better accuracy of firing delays. The development of electronic detonators seems to be the way of the future for a better blasting control.

  4. Exploring Non-Traditional Learning Methods in Virtual and Real-World Environments

    Science.gov (United States)

    Lukman, Rebeka; Krajnc, Majda

    2012-01-01

    This paper identifies the commonalities and differences within non-traditional learning methods regarding virtual and real-world environments. The non-traditional learning methods in real-world have been introduced within the following courses: Process Balances, Process Calculation, and Process Synthesis, and within the virtual environment through…

  5. Comparing interactive videodisc training effectiveness to traditional training methods

    International Nuclear Information System (INIS)

    Kenworthy, N.W.

    1987-01-01

    Videodisc skills training programs developed by Industrial Training Corporation are being used and evaluated by major industrial facilities. In one such study, interactive videodisc training programs were compared to videotape and instructor-based training to determine the effectiveness of videodisc in terms of performance, training time and trainee attitudes. Results showed that when initial training was done using the interactive videodisc system, trainee performance was superior to the performance of trainees using videotape, and approximately equal to the performance of those trained by an instructor. When each method was used in follow-up training, interactive videodisc was definitely the most effective. Results also indicate that training time can be reduced using interactive videodisc. Attitudes of both trainees and instructors toward the interactive videodisc training were positive

  6. Device and method for traditional chinese medicine diagnosis using radioactive tracer method

    Energy Technology Data Exchange (ETDEWEB)

    Wu, Shanling; Shen, Miaohe

    1997-05-29

    Disclosed is a device and method for traditional chinese medicine diagnosis using radioactive-tracer method. At least two nuclear radiation probes are arranged apart along the channels to detect the changing with time and on space of the intensity of radioactivity of the nuclear radioactive tracer which has been injected into the body in the channel position. The detected signals are amplified by amplifiers, and the outputs of the amplifiers are applied to data processing means which monitor the whole detecting process in real time and analyse and process the detected information about the changing of the intensity of radioactivity with time and on space indicating the operating of vital energy and blood, and obtain state parameters about operating of vital energy and blood in the body which is then output through data output means. (author) figs.

  7. Simple method to calculate percolation, Ising and Potts clusters

    International Nuclear Information System (INIS)

    Tsallis, C.

    1981-01-01

    A procedure ('break-collapse method') is introduced which considerably simplifies the calculation of two - or multirooted clusters like those commonly appearing in real space renormalization group (RG) treatments of bond-percolation, and pure and random Ising and Potts problems. The method is illustrated through two applications for the q-state Potts ferromagnet. The first of them concerns a RG calculation of the critical exponent ν for the isotropic square lattice: numerical consistence is obtained (particularly for q→0) with den Nijs conjecture. The second application is a compact reformulation of the standard star-triangle and duality transformations which provide the exact critical temperature for the anisotropic triangular and honeycomb lattices. (Author) [pt

  8. Expanding Comparative Literature into Comparative Sciences Clusters with Neutrosophy and Quad-stage Method

    Directory of Open Access Journals (Sweden)

    Fu Yuhua

    2016-08-01

    Full Text Available By using Neutrosophy and Quad-stage Method, the expansions of comparative literature include: comparative social sciences clusters, comparative natural sciences clusters, comparative interdisciplinary sciences clusters, and so on. Among them, comparative social sciences clusters include: comparative literature, comparative history, comparative philosophy, and so on; comparative natural sciences clusters include: comparative mathematics, comparative physics, comparative chemistry, comparative medicine, comparative biology, and so on.

  9. bcl::Cluster : A method for clustering biological molecules coupled with visualization in the Pymol Molecular Graphics System.

    Science.gov (United States)

    Alexander, Nathan; Woetzel, Nils; Meiler, Jens

    2011-02-01

    Clustering algorithms are used as data analysis tools in a wide variety of applications in Biology. Clustering has become especially important in protein structure prediction and virtual high throughput screening methods. In protein structure prediction, clustering is used to structure the conformational space of thousands of protein models. In virtual high throughput screening, databases with millions of drug-like molecules are organized by structural similarity, e.g. common scaffolds. The tree-like dendrogram structure obtained from hierarchical clustering can provide a qualitative overview of the results, which is important for focusing detailed analysis. However, in practice it is difficult to relate specific components of the dendrogram directly back to the objects of which it is comprised and to display all desired information within the two dimensions of the dendrogram. The current work presents a hierarchical agglomerative clustering method termed bcl::Cluster. bcl::Cluster utilizes the Pymol Molecular Graphics System to graphically depict dendrograms in three dimensions. This allows simultaneous display of relevant biological molecules as well as additional information about the clusters and the members comprising them.

  10. Application of clustering methods: Regularized Markov clustering (R-MCL) for analyzing dengue virus similarity

    Science.gov (United States)

    Lestari, D.; Raharjo, D.; Bustamam, A.; Abdillah, B.; Widhianto, W.

    2017-07-01

    Dengue virus consists of 10 different constituent proteins and are classified into 4 major serotypes (DEN 1 - DEN 4). This study was designed to perform clustering against 30 protein sequences of dengue virus taken from Virus Pathogen Database and Analysis Resource (VIPR) using Regularized Markov Clustering (R-MCL) algorithm and then we analyze the result. By using Python program 3.4, R-MCL algorithm produces 8 clusters with more than one centroid in several clusters. The number of centroid shows the density level of interaction. Protein interactions that are connected in a tissue, form a complex protein that serves as a specific biological process unit. The analysis of result shows the R-MCL clustering produces clusters of dengue virus family based on the similarity role of their constituent protein, regardless of serotypes.

  11. Prevalence of depressive symptoms among medical students taught using problem-based learning versus traditional methods.

    Science.gov (United States)

    Aragão, José Aderval; Freire, Marianna Ribeiro de Menezes; Nolasco Farias, Lucas Guimarães; Diniz, Sarah Santana; Sant'anna Aragão, Felipe Matheus; Sant'anna Aragão, Iapunira Catarina; Lima, Tarcisio Brandão; Reis, Francisco Prado

    2018-06-01

    To compare depressive symptoms among medical students taught using problem-based learning (PBL) and the traditional method. Beck's Depression Inventory was applied to 215 medical students. The prevalence of depression was calculated as the number of individuals with depression divided by the total number in the sample from each course, with 95% confidence intervals. The statistical significance level used was 5% (p ≤ .05). Among the 215 students, 52.1% were male and 47.9% were female; and 51.6% were being taught using PBL methodology and 48.4% using traditional methods. The prevalence of depression was 29.73% with PBL and 22.12% with traditional methods. There was higher prevalence among females: 32.8% with PBL and 23.1% with traditional methods. The prevalence of depression with PBL among students up to 21 years of age was 29.4% and among those over 21 years, 32.1%. With traditional methods among students up to 21 years of age, it was 16.7%%, and among those over 21 years, 30.1%. The prevalence of depression with PBL was highest among students in the second semester and with traditional methods, in the eighth. Depressive symptoms were highly prevalent among students taught both with PBL and with traditional methods.

  12. The Local Maximum Clustering Method and Its Application in Microarray Gene Expression Data Analysis

    Directory of Open Access Journals (Sweden)

    Chen Yidong

    2004-01-01

    Full Text Available An unsupervised data clustering method, called the local maximum clustering (LMC method, is proposed for identifying clusters in experiment data sets based on research interest. A magnitude property is defined according to research purposes, and data sets are clustered around each local maximum of the magnitude property. By properly defining a magnitude property, this method can overcome many difficulties in microarray data clustering such as reduced projection in similarities, noises, and arbitrary gene distribution. To critically evaluate the performance of this clustering method in comparison with other methods, we designed three model data sets with known cluster distributions and applied the LMC method as well as the hierarchic clustering method, the -mean clustering method, and the self-organized map method to these model data sets. The results show that the LMC method produces the most accurate clustering results. As an example of application, we applied the method to cluster the leukemia samples reported in the microarray study of Golub et al. (1999.

  13. A model-based clustering method to detect infectious disease transmission outbreaks from sequence variation.

    Directory of Open Access Journals (Sweden)

    Rosemary M McCloskey

    2017-11-01

    Full Text Available Clustering infections by genetic similarity is a popular technique for identifying potential outbreaks of infectious disease, in part because sequences are now routinely collected for clinical management of many infections. A diverse number of nonparametric clustering methods have been developed for this purpose. These methods are generally intuitive, rapid to compute, and readily scale with large data sets. However, we have found that nonparametric clustering methods can be biased towards identifying clusters of diagnosis-where individuals are sampled sooner post-infection-rather than the clusters of rapid transmission that are meant to be potential foci for public health efforts. We develop a fundamentally new approach to genetic clustering based on fitting a Markov-modulated Poisson process (MMPP, which represents the evolution of transmission rates along the tree relating different infections. We evaluated this model-based method alongside five nonparametric clustering methods using both simulated and actual HIV sequence data sets. For simulated clusters of rapid transmission, the MMPP clustering method obtained higher mean sensitivity (85% and specificity (91% than the nonparametric methods. When we applied these clustering methods to published sequences from a study of HIV-1 genetic clusters in Seattle, USA, we found that the MMPP method categorized about half (46% as many individuals to clusters compared to the other methods. Furthermore, the mean internal branch lengths that approximate transmission rates were significantly shorter in clusters extracted using MMPP, but not by other methods. We determined that the computing time for the MMPP method scaled linearly with the size of trees, requiring about 30 seconds for a tree of 1,000 tips and about 20 minutes for 50,000 tips on a single computer. This new approach to genetic clustering has significant implications for the application of pathogen sequence analysis to public health, where

  14. [Applications of mathematical statistics methods on compatibility researches of traditional Chinese medicines formulae].

    Science.gov (United States)

    Mai, Lan-Yin; Li, Yi-Xuan; Chen, Yong; Xie, Zhen; Li, Jie; Zhong, Ming-Yu

    2014-05-01

    The compatibility of traditional Chinese medicines (TCMs) formulae containing enormous information, is a complex component system. Applications of mathematical statistics methods on the compatibility researches of traditional Chinese medicines formulae have great significance for promoting the modernization of traditional Chinese medicines and improving clinical efficacies and optimizations of formulae. As a tool for quantitative analysis, data inference and exploring inherent rules of substances, the mathematical statistics method can be used to reveal the working mechanisms of the compatibility of traditional Chinese medicines formulae in qualitatively and quantitatively. By reviewing studies based on the applications of mathematical statistics methods, this paper were summarized from perspective of dosages optimization, efficacies and changes of chemical components as well as the rules of incompatibility and contraindication of formulae, will provide the references for further studying and revealing the working mechanisms and the connotations of traditional Chinese medicines.

  15. Perspective for applying traditional and inovative teaching and learning methods to nurses continuing education

    OpenAIRE

    Bendinskaitė, Irmina

    2015-01-01

    Bendinskaitė I. Perspective for applying traditional and innovative teaching and learning methods to nurse’s continuing education, magister thesis / supervisor Assoc. Prof. O. Riklikienė; Departament of Nursing and Care, Faculty of Nursing, Lithuanian University of Health Sciences. – Kaunas, 2015, – p. 92 The purpose of this study was to investigate traditional and innovative teaching and learning methods perspective to nurse’s continuing education. Material and methods. In a period fro...

  16. A comparison of heuristic and model-based clustering methods for dietary pattern analysis.

    Science.gov (United States)

    Greve, Benjamin; Pigeot, Iris; Huybrechts, Inge; Pala, Valeria; Börnhorst, Claudia

    2016-02-01

    Cluster analysis is widely applied to identify dietary patterns. A new method based on Gaussian mixture models (GMM) seems to be more flexible compared with the commonly applied k-means and Ward's method. In the present paper, these clustering approaches are compared to find the most appropriate one for clustering dietary data. The clustering methods were applied to simulated data sets with different cluster structures to compare their performance knowing the true cluster membership of observations. Furthermore, the three methods were applied to FFQ data assessed in 1791 children participating in the IDEFICS (Identification and Prevention of Dietary- and Lifestyle-Induced Health Effects in Children and Infants) Study to explore their performance in practice. The GMM outperformed the other methods in the simulation study in 72 % up to 100 % of cases, depending on the simulated cluster structure. Comparing the computationally less complex k-means and Ward's methods, the performance of k-means was better in 64-100 % of cases. Applied to real data, all methods identified three similar dietary patterns which may be roughly characterized as a 'non-processed' cluster with a high consumption of fruits, vegetables and wholemeal bread, a 'balanced' cluster with only slight preferences of single foods and a 'junk food' cluster. The simulation study suggests that clustering via GMM should be preferred due to its higher flexibility regarding cluster volume, shape and orientation. The k-means seems to be a good alternative, being easier to use while giving similar results when applied to real data.

  17. A novel classification method for aid decision of traditional Chinese patent medicines for stroke treatment.

    Science.gov (United States)

    Zhao, Yufeng; Liu, Bo; He, Liyun; Bai, Wenjing; Yu, Xueyun; Cao, Xinyu; Luo, Lin; Rong, Peijing; Zhao, Yuxue; Li, Guozheng; Liu, Baoyan

    2017-09-01

    Traditional Chinese patent medicines are widely used to treat stroke because it has good efficacy in the clinical environment. However, because of the lack of knowledge on traditional Chinese patent medicines, many Western physicians, who are accountable for the majority of clinical prescriptions for such medicine, are confused with the use of traditional Chinese patent medicines. Therefore, the aid-decision method is critical and necessary to help Western physicians rationally use traditional Chinese patent medicines. In this paper, Manifold Ranking is employed to develop the aid-decision model of traditional Chinese patent medicines for stroke treatment. First, 115 stroke patients from three hospitals are recruited in the cross-sectional survey. Simultaneously, traditional Chinese physicians determine the traditional Chinese patent medicines appropriate for each patient. Second, particular indicators are explored to characterize the population feature of traditional Chinese patent medicines for stroke treatment. Moreover, these particular indicators can be easily obtained byWestern physicians and are feasible for widespread clinical application in the future. Third, the aid-decision model of traditional Chinese patent medicines for stroke treatment is constructed based on Manifold Ranking. Experimental results reveal that traditional Chinese patent medicines can be differentiated. Moreover, the proposed model can obtain high accuracy of aid decision.

  18. The Views of Turkish Pre-Service Teachers about Effectiveness of Cluster Method as a Teaching Writing Method

    Science.gov (United States)

    Kitis, Emine; Türkel, Ali

    2017-01-01

    The aim of this study is to find out Turkish pre-service teachers' views on effectiveness of cluster method as a writing teaching method. The Cluster Method can be defined as a connotative creative writing method. The way the method works is that the person who brainstorms on connotations of a word or a concept in abscence of any kind of…

  19. Short-Term Wind Power Forecasting Based on Clustering Pre-Calculated CFD Method

    Directory of Open Access Journals (Sweden)

    Yimei Wang

    2018-04-01

    Full Text Available To meet the increasing wind power forecasting (WPF demands of newly built wind farms without historical data, physical WPF methods are widely used. The computational fluid dynamics (CFD pre-calculated flow fields (CPFF-based WPF is a promising physical approach, which can balance well the competing demands of computational efficiency and accuracy. To enhance its adaptability for wind farms in complex terrain, a WPF method combining wind turbine clustering with CPFF is first proposed where the wind turbines in the wind farm are clustered and a forecasting is undertaken for each cluster. K-means, hierarchical agglomerative and spectral analysis methods are used to establish the wind turbine clustering models. The Silhouette Coefficient, Calinski-Harabaz index and within-between index are proposed as criteria to evaluate the effectiveness of the established clustering models. Based on different clustering methods and schemes, various clustering databases are built for clustering pre-calculated CFD (CPCC-based short-term WPF. For the wind farm case studied, clustering evaluation criteria show that hierarchical agglomerative clustering has reasonable results, spectral clustering is better and K-means gives the best performance. The WPF results produced by different clustering databases also prove the effectiveness of the three evaluation criteria in turn. The newly developed CPCC model has a much higher WPF accuracy than the CPFF model without using clustering techniques, both on temporal and spatial scales. The research provides supports for both the development and improvement of short-term physical WPF systems.

  20. Using traditional methods and indigenous technologies for coping with climate variability

    NARCIS (Netherlands)

    Stigter, C.J.; Zheng Dawei,; Onyewotu, L.O.Z.; Mei Xurong,

    2005-01-01

    In agrometeorology and management of meteorology related natural resources, many traditional methods and indigenous technologies are still in use or being revived for managing low external inputs sustainable agriculture (LEISA) under conditions of climate variability. This paper starts with the

  1. Efficacy of traditional maize (Zea mays L.) seed storage methods in ...

    African Journals Online (AJOL)

    Efficacy of traditional maize (Zea mays L.) seed storage methods in western Kenya. ... PROMOTING ACCESS TO AFRICAN RESEARCH. AFRICAN JOURNALS ONLINE (AJOL) ... African Journal of Food, Agriculture, Nutrition and Development.

  2. Motion estimation using point cluster method and Kalman filter.

    Science.gov (United States)

    Senesh, M; Wolf, A

    2009-05-01

    The most frequently used method in a three dimensional human gait analysis involves placing markers on the skin of the analyzed segment. This introduces a significant artifact, which strongly influences the bone position and orientation and joint kinematic estimates. In this study, we tested and evaluated the effect of adding a Kalman filter procedure to the previously reported point cluster technique (PCT) in the estimation of a rigid body motion. We demonstrated the procedures by motion analysis of a compound planar pendulum from indirect opto-electronic measurements of markers attached to an elastic appendage that is restrained to slide along the rigid body long axis. The elastic frequency is close to the pendulum frequency, as in the biomechanical problem, where the soft tissue frequency content is similar to the actual movement of the bones. Comparison of the real pendulum angle to that obtained by several estimation procedures--PCT, Kalman filter followed by PCT, and low pass filter followed by PCT--enables evaluation of the accuracy of the procedures. When comparing the maximal amplitude, no effect was noted by adding the Kalman filter; however, a closer look at the signal revealed that the estimated angle based only on the PCT method was very noisy with fluctuation, while the estimated angle based on the Kalman filter followed by the PCT was a smooth signal. It was also noted that the instantaneous frequencies obtained from the estimated angle based on the PCT method is more dispersed than those obtained from the estimated angle based on Kalman filter followed by the PCT method. Addition of a Kalman filter to the PCT method in the estimation procedure of rigid body motion results in a smoother signal that better represents the real motion, with less signal distortion than when using a digital low pass filter. Furthermore, it can be concluded that adding a Kalman filter to the PCT procedure substantially reduces the dispersion of the maximal and minimal

  3. Web-based versus traditional lecture: are they equally effective as a flexible bronchoscopy teaching method?

    OpenAIRE

    Sterse Mata, Caio Augusto [UNIFESP; Ota, Luiz Hirotoshi [UNIFESP; Suzuki, Iunis [UNIFESP; Telles, Adriana [UNIFESP; Miotto, Andre [UNIFESP; Leao, Luiz Eduardo Villaca [UNIFESP

    2012-01-01

    This study compares the traditional live lecture to a web-based approach in the teaching of bronchoscopy and evaluates the positive and negative aspects of both methods. We developed a web-based bronchoscopy curriculum, which integrates texts, images and animations. It was applied to first-year interns, who were later administered a multiple-choice test. Another group of eight first-year interns received the traditional teaching method and the same test. the two groups were compared using the...

  4. AutoSOME: a clustering method for identifying gene expression modules without prior knowledge of cluster number

    Directory of Open Access Journals (Sweden)

    Cooper James B

    2010-03-01

    Full Text Available Abstract Background Clustering the information content of large high-dimensional gene expression datasets has widespread application in "omics" biology. Unfortunately, the underlying structure of these natural datasets is often fuzzy, and the computational identification of data clusters generally requires knowledge about cluster number and geometry. Results We integrated strategies from machine learning, cartography, and graph theory into a new informatics method for automatically clustering self-organizing map ensembles of high-dimensional data. Our new method, called AutoSOME, readily identifies discrete and fuzzy data clusters without prior knowledge of cluster number or structure in diverse datasets including whole genome microarray data. Visualization of AutoSOME output using network diagrams and differential heat maps reveals unexpected variation among well-characterized cancer cell lines. Co-expression analysis of data from human embryonic and induced pluripotent stem cells using AutoSOME identifies >3400 up-regulated genes associated with pluripotency, and indicates that a recently identified protein-protein interaction network characterizing pluripotency was underestimated by a factor of four. Conclusions By effectively extracting important information from high-dimensional microarray data without prior knowledge or the need for data filtration, AutoSOME can yield systems-level insights from whole genome microarray expression studies. Due to its generality, this new method should also have practical utility for a variety of data-intensive applications, including the results of deep sequencing experiments. AutoSOME is available for download at http://jimcooperlab.mcdb.ucsb.edu/autosome.

  5. [Research on K-means clustering segmentation method for MRI brain image based on selecting multi-peaks in gray histogram].

    Science.gov (United States)

    Chen, Zhaoxue; Yu, Haizhong; Chen, Hao

    2013-12-01

    To solve the problem of traditional K-means clustering in which initial clustering centers are selected randomly, we proposed a new K-means segmentation algorithm based on robustly selecting 'peaks' standing for White Matter, Gray Matter and Cerebrospinal Fluid in multi-peaks gray histogram of MRI brain image. The new algorithm takes gray value of selected histogram 'peaks' as the initial K-means clustering center and can segment the MRI brain image into three parts of tissue more effectively, accurately, steadily and successfully. Massive experiments have proved that the proposed algorithm can overcome many shortcomings caused by traditional K-means clustering method such as low efficiency, veracity, robustness and time consuming. The histogram 'peak' selecting idea of the proposed segmentootion method is of more universal availability.

  6. Prioritizing the risk of plant pests by clustering methods; self-organising maps, k-means and hierarchical clustering

    Directory of Open Access Journals (Sweden)

    Susan Worner

    2013-09-01

    Full Text Available For greater preparedness, pest risk assessors are required to prioritise long lists of pest species with potential to establish and cause significant impact in an endangered area. Such prioritization is often qualitative, subjective, and sometimes biased, relying mostly on expert and stakeholder consultation. In recent years, cluster based analyses have been used to investigate regional pest species assemblages or pest profiles to indicate the risk of new organism establishment. Such an approach is based on the premise that the co-occurrence of well-known global invasive pest species in a region is not random, and that the pest species profile or assemblage integrates complex functional relationships that are difficult to tease apart. In other words, the assemblage can help identify and prioritise species that pose a threat in a target region. A computational intelligence method called a Kohonen self-organizing map (SOM, a type of artificial neural network, was the first clustering method applied to analyse assemblages of invasive pests. The SOM is a well known dimension reduction and visualization method especially useful for high dimensional data that more conventional clustering methods may not analyse suitably. Like all clustering algorithms, the SOM can give details of clusters that identify regions with similar pest assemblages, possible donor and recipient regions. More important, however SOM connection weights that result from the analysis can be used to rank the strength of association of each species within each regional assemblage. Species with high weights that are not already established in the target region are identified as high risk. However, the SOM analysis is only the first step in a process to assess risk to be used alongside or incorporated within other measures. Here we illustrate the application of SOM analyses in a range of contexts in invasive species risk assessment, and discuss other clustering methods such as k

  7. clusters

    Indian Academy of Sciences (India)

    2017-09-27

    Sep 27, 2017 ... Author for correspondence (zh4403701@126.com). MS received 15 ... lic clusters using density functional theory (DFT)-GGA of the DMOL3 package. ... In the process of geometric optimization, con- vergence thresholds ..... and Postgraduate Research & Practice Innovation Program of. Jiangsu Province ...

  8. clusters

    Indian Academy of Sciences (India)

    environmental as well as technical problems during fuel gas utilization. ... adsorption on some alloys of Pd, namely PdAu, PdAg ... ried out on small neutral and charged Au24,26,27, Cu,28 ... study of Zanti et al.29 on Pdn (n = 1–9) clusters.

  9. Differences Between Ward's and UPGMA Methods of Cluster Analysis: Implications for School Psychology.

    Science.gov (United States)

    Hale, Robert L.; Dougherty, Donna

    1988-01-01

    Compared the efficacy of two methods of cluster analysis, the unweighted pair-groups method using arithmetic averages (UPGMA) and Ward's method, for students grouped on intelligence, achievement, and social adjustment by both clustering methods. Found UPGMA more efficacious based on output, on cophenetic correlation coefficients generated by each…

  10. Comparison of Online and Traditional Basic Life Support Renewal Training Methods for Registered Professional Nurses.

    Science.gov (United States)

    Serwetnyk, Tara M; Filmore, Kristi; VonBacho, Stephanie; Cole, Robert; Miterko, Cindy; Smith, Caitlin; Smith, Charlene M

    2015-01-01

    Basic Life Support certification for nursing staff is achieved through various training methods. This study compared three American Heart Association training methods for nurses seeking Basic Life Support renewal: a traditional classroom approach and two online options. Findings indicate that online methods for Basic Life Support renewal deliver cost and time savings, while maintaining positive learning outcomes, satisfaction, and confidence level of participants.

  11. Developing cluster strategy of apples dodol SMEs by integration K-means clustering and analytical hierarchy process method

    Science.gov (United States)

    Mustaniroh, S. A.; Effendi, U.; Silalahi, R. L. R.; Sari, T.; Ala, M.

    2018-03-01

    The purposes of this research were to determine the grouping of apples dodol small and medium enterprises (SMEs) in Batu City and to determine an appropriate development strategy for each cluster. The methods used for clustering SMEs was k-means. The Analytical Hierarchy Process (AHP) approach was then applied to determine the development strategy priority for each cluster. The variables used in grouping include production capacity per month, length of operation, investment value, average sales revenue per month, amount of SMEs assets, and the number of workers. Several factors were considered in AHP include industry cluster, government, as well as related and supporting industries. Data was collected using the methods of questionaire and interviews. SMEs respondents were selected among SMEs appels dodol in Batu City using purposive sampling. The result showed that two clusters were formed from five apples dodol SMEs. The 1stcluster of apples dodol SMEs, classified as small enterprises, included SME A, SME C, and SME D. The 2ndcluster of SMEs apples dodol, classified as medium enterprises, consisted of SME B and SME E. The AHP results indicated that the priority development strategy for the 1stcluster of apples dodol SMEs was improving quality and the product standardisation, while for the 2nd cluster was increasing the marketing access.

  12. Swarm: robust and fast clustering method for amplicon-based studies

    Science.gov (United States)

    Rognes, Torbjørn; Quince, Christopher; de Vargas, Colomban; Dunthorn, Micah

    2014-01-01

    Popular de novo amplicon clustering methods suffer from two fundamental flaws: arbitrary global clustering thresholds, and input-order dependency induced by centroid selection. Swarm was developed to address these issues by first clustering nearly identical amplicons iteratively using a local threshold, and then by using clusters’ internal structure and amplicon abundances to refine its results. This fast, scalable, and input-order independent approach reduces the influence of clustering parameters and produces robust operational taxonomic units. PMID:25276506

  13. Swarm: robust and fast clustering method for amplicon-based studies

    Directory of Open Access Journals (Sweden)

    Frédéric Mahé

    2014-09-01

    Full Text Available Popular de novo amplicon clustering methods suffer from two fundamental flaws: arbitrary global clustering thresholds, and input-order dependency induced by centroid selection. Swarm was developed to address these issues by first clustering nearly identical amplicons iteratively using a local threshold, and then by using clusters’ internal structure and amplicon abundances to refine its results. This fast, scalable, and input-order independent approach reduces the influence of clustering parameters and produces robust operational taxonomic units.

  14. A method for improved clustering and classification of microscopy images using quantitative co-localization coefficients

    LENUS (Irish Health Repository)

    Singan, Vasanth R

    2012-06-08

    AbstractBackgroundThe localization of proteins to specific subcellular structures in eukaryotic cells provides important information with respect to their function. Fluorescence microscopy approaches to determine localization distribution have proved to be an essential tool in the characterization of unknown proteins, and are now particularly pertinent as a result of the wide availability of fluorescently-tagged constructs and antibodies. However, there are currently very few image analysis options able to effectively discriminate proteins with apparently similar distributions in cells, despite this information being important for protein characterization.FindingsWe have developed a novel method for combining two existing image analysis approaches, which results in highly efficient and accurate discrimination of proteins with seemingly similar distributions. We have combined image texture-based analysis with quantitative co-localization coefficients, a method that has traditionally only been used to study the spatial overlap between two populations of molecules. Here we describe and present a novel application for quantitative co-localization, as applied to the study of Rab family small GTP binding proteins localizing to the endomembrane system of cultured cells.ConclusionsWe show how quantitative co-localization can be used alongside texture feature analysis, resulting in improved clustering of microscopy images. The use of co-localization as an additional clustering parameter is non-biased and highly applicable to high-throughput image data sets.

  15. Cluster-cell calculation using the method of generalized homogenization

    International Nuclear Information System (INIS)

    Laletin, N.I.; Boyarinov, V.F.

    1988-01-01

    The generalized-homogenization method (GHM), used for solving the neutron transfer equation, was applied to calculating the neutron distribution in the cluster cell with a series of cylindrical cells with cylindrically coaxial zones. Single-group calculations of the technological channel of the cell of an RBMK reactor were performed using GHM. The technological channel was understood to be the reactor channel, comprised of the zirconium rod, the water or steam-water mixture, the uranium dioxide fuel element, and the zirconium tube, together with the adjacent graphite layer. Calculations were performed for channels with no internal sources and with unit incoming current at the external boundary as well as for channels with internal sources and zero current at the external boundary. The PRAKTINETs program was used to calculate the symmetric neutron distributions in the microcell and in channels with homogenized annular zones. The ORAR-TsM program was used to calculate the antisymmetric distribution in the microcell. The accuracy of the calculations were compared for the two channel versions

  16. The Cluster Variation Method: A Primer for Neuroscientists.

    Science.gov (United States)

    Maren, Alianna J

    2016-09-30

    Effective Brain-Computer Interfaces (BCIs) require that the time-varying activation patterns of 2-D neural ensembles be modelled. The cluster variation method (CVM) offers a means for the characterization of 2-D local pattern distributions. This paper provides neuroscientists and BCI researchers with a CVM tutorial that will help them to understand how the CVM statistical thermodynamics formulation can model 2-D pattern distributions expressing structural and functional dynamics in the brain. The premise is that local-in-time free energy minimization works alongside neural connectivity adaptation, supporting the development and stabilization of consistent stimulus-specific responsive activation patterns. The equilibrium distribution of local patterns, or configuration variables , is defined in terms of a single interaction enthalpy parameter ( h ) for the case of an equiprobable distribution of bistate (neural/neural ensemble) units. Thus, either one enthalpy parameter (or two, for the case of non-equiprobable distribution) yields equilibrium configuration variable values. Modeling 2-D neural activation distribution patterns with the representational layer of a computational engine, we can thus correlate variational free energy minimization with specific configuration variable distributions. The CVM triplet configuration variables also map well to the notion of a M = 3 functional motif. This paper addresses the special case of an equiprobable unit distribution, for which an analytic solution can be found.

  17. The Cluster Variation Method: A Primer for Neuroscientists

    Directory of Open Access Journals (Sweden)

    Alianna J. Maren

    2016-09-01

    Full Text Available Effective Brain–Computer Interfaces (BCIs require that the time-varying activation patterns of 2-D neural ensembles be modelled. The cluster variation method (CVM offers a means for the characterization of 2-D local pattern distributions. This paper provides neuroscientists and BCI researchers with a CVM tutorial that will help them to understand how the CVM statistical thermodynamics formulation can model 2-D pattern distributions expressing structural and functional dynamics in the brain. The premise is that local-in-time free energy minimization works alongside neural connectivity adaptation, supporting the development and stabilization of consistent stimulus-specific responsive activation patterns. The equilibrium distribution of local patterns, or configuration variables, is defined in terms of a single interaction enthalpy parameter (h for the case of an equiprobable distribution of bistate (neural/neural ensemble units. Thus, either one enthalpy parameter (or two, for the case of non-equiprobable distribution yields equilibrium configuration variable values. Modeling 2-D neural activation distribution patterns with the representational layer of a computational engine, we can thus correlate variational free energy minimization with specific configuration variable distributions. The CVM triplet configuration variables also map well to the notion of a M = 3 functional motif. This paper addresses the special case of an equiprobable unit distribution, for which an analytic solution can be found.

  18. Comparative analysis of clustering methods for gene expression time course data

    Directory of Open Access Journals (Sweden)

    Ivan G. Costa

    2004-01-01

    Full Text Available This work performs a data driven comparative study of clustering methods used in the analysis of gene expression time courses (or time series. Five clustering methods found in the literature of gene expression analysis are compared: agglomerative hierarchical clustering, CLICK, dynamical clustering, k-means and self-organizing maps. In order to evaluate the methods, a k-fold cross-validation procedure adapted to unsupervised methods is applied. The accuracy of the results is assessed by the comparison of the partitions obtained in these experiments with gene annotation, such as protein function and series classification.

  19. Improvement of economic potential estimation methods for enterprise with potential branch clusters use

    Directory of Open Access Journals (Sweden)

    V.Ya. Nusinov

    2017-08-01

    Full Text Available The research determines that the current existing methods of enterprise’s economic potential estimation are based on the use of additive, multiplicative and rating models. It is determined that the existing methods have a row of defects. For example, not all the methods take into account the branch features of the analysis, and also the level of development of the enterprise comparatively with other enterprises. It is suggested to level such defects by an account at the estimation of potential integral level not only by branch features of enterprises activity but also by the intra-account economic clusterization of such enterprises. Scientific works which are connected with the using of clusters for the estimation of economic potential are generalized. According to the results of generalization it is determined that it is possible to distinguish 9 scientific approaches in this direction: the use of natural clusterization of enterprises with the purpose of estimation and increase of region potential; the use of natural clusterization of enterprises with the purpose of estimation and increase of industry potential; use of artificial clusterization of enterprises with the purpose of estimation and increase of region potential; use of artificial clusterization of enterprises with the purpose of estimation and increase of industry potential; the use of artificial clusterization of enterprises with the purpose of clustering potential estimation; the use of artificial clusterization of enterprises with the purpose of estimation of clustering competitiveness potential; the use of natural (artificial clusterization for the estimation of clustering efficiency; the use of natural (artificial clusterization for the increase of level at region (industries development; the use of methods of economic potential of region (industries estimation or its constituents for the construction of the clusters. It is determined that the use of clusterization method in

  20. Comparison the Students Satisfaction of Traditional and Integrated Teaching Method in Physiology Course

    Directory of Open Access Journals (Sweden)

    Keshavarzi Z.

    2016-02-01

    Full Text Available Aims: Different education methods play crucial roles to improve education quality and students’ satisfaction. In the recent years, medical education highly changes through new education methods. The aim of this study was to compare medical students’ satisfaction in traditional and integrated methods of teaching physiology course. Instrument and Methods: In the descriptive analysis study, fifty 4th semester medical students of Bojnourd University of Medical Sciences were studied in 2015. The subjects were randomly selected based on availability. Data was collected by two researcher-made questionnaires; their validity and reliability were confirmed. Questionnaure 1 was completed by the students after presenting renal and endocrinology topics via traditional and integrated methods. Questionnaire 2 was only completed by the students after presenting the course via integrated method. Data was analyzed by SPSS 16 software using dependent T test. Findings: Mean score of the students’ satisfaction in traditional method (24.80±3.48 was higher than integrated method (22.30±4.03; p<0.0001. In the integrated method, most of the students were agreed and completely agreed on telling stories from daily life (76%, sitting mode in the classroom (48%, an attribution of cell roles to the students (60%, showing movies and animations (76%, using models (84%, and using real animal parts (72% during teaching, as well as expressing clinical items to enhance learning motivations (76%. Conclusion: Favorable satisfaction of the students in traditional lecture method to understand the issues, as well as their acceptance of new and active methods of learning, show effectiveness and efficiency of traditional method and the requirement of its enhancement by the integrated methods

  1. Analysis of Conflict Centers in Projects Procured with Traditional and Integrated Methods in Nigeria

    Directory of Open Access Journals (Sweden)

    Martin O. Dada

    2012-07-01

    Full Text Available Conflicts in any organization can either be functional or dysfunctional and can contribute to or detract from the achievement of organizational or project objectives. This study investigated the frequency and intensity of conflicts, using five conflict centers, on projects executed with either the integrated or traditional method in Nigeria. Questionnaires were administered through purposive and snowballing techniques on 274 projects located in twelve states of Nigeria and Abuja. 94 usable responses were obtained. The collected data were subjected to both descriptive and inferential statistical analysis. In projects procured with traditional methods, conflicts relating to resources for project execution had the greatest frequency, while conflicts around project/client goals had the least frequency. For projects executed with integrated methods, conflicts due to administrative procedures were ranked highest while conflicts due to project/client goals were ranked least. Regarding seriousness of conflict, conflicts due to administrative procedures and resources for project execution were ranked highest respectively for projects procured with traditional and integrated methods. Additionally, in terms of seriousness, personality issues and project/client goals were the least sources of conflict in projects executed with traditional and integrated methods. There were no significant differences in the incidence of conflicts, using the selected conflict centers, between the traditional and integrated procurement methods. There was however significant difference in the intensity or seriousness of conflicts between projects executed with the traditional method and those executed with integrated methods in the following areas: technical issues, administrative matters and personality issues. The study recommends that conscious efforts should be made at teambuilding on projects executed with integrated methods.

  2. Cluster size statistic and cluster mass statistic: two novel methods for identifying changes in functional connectivity between groups or conditions.

    Science.gov (United States)

    Ing, Alex; Schwarzbauer, Christian

    2014-01-01

    Functional connectivity has become an increasingly important area of research in recent years. At a typical spatial resolution, approximately 300 million connections link each voxel in the brain with every other. This pattern of connectivity is known as the functional connectome. Connectivity is often compared between experimental groups and conditions. Standard methods used to control the type 1 error rate are likely to be insensitive when comparisons are carried out across the whole connectome, due to the huge number of statistical tests involved. To address this problem, two new cluster based methods--the cluster size statistic (CSS) and cluster mass statistic (CMS)--are introduced to control the family wise error rate across all connectivity values. These methods operate within a statistical framework similar to the cluster based methods used in conventional task based fMRI. Both methods are data driven, permutation based and require minimal statistical assumptions. Here, the performance of each procedure is evaluated in a receiver operator characteristic (ROC) analysis, utilising a simulated dataset. The relative sensitivity of each method is also tested on real data: BOLD (blood oxygen level dependent) fMRI scans were carried out on twelve subjects under normal conditions and during the hypercapnic state (induced through the inhalation of 6% CO2 in 21% O2 and 73%N2). Both CSS and CMS detected significant changes in connectivity between normal and hypercapnic states. A family wise error correction carried out at the individual connection level exhibited no significant changes in connectivity.

  3. Comparison of Traditional Design Nonlinear Programming Optimization and Stochastic Methods for Structural Design

    Science.gov (United States)

    Patnaik, Surya N.; Pai, Shantaram S.; Coroneos, Rula M.

    2010-01-01

    Structural design generated by traditional method, optimization method and the stochastic design concept are compared. In the traditional method, the constraints are manipulated to obtain the design and weight is back calculated. In design optimization, the weight of a structure becomes the merit function with constraints imposed on failure modes and an optimization algorithm is used to generate the solution. Stochastic design concept accounts for uncertainties in loads, material properties, and other parameters and solution is obtained by solving a design optimization problem for a specified reliability. Acceptable solutions were produced by all the three methods. The variation in the weight calculated by the methods was modest. Some variation was noticed in designs calculated by the methods. The variation may be attributed to structural indeterminacy. It is prudent to develop design by all three methods prior to its fabrication. The traditional design method can be improved when the simplified sensitivities of the behavior constraint is used. Such sensitivity can reduce design calculations and may have a potential to unify the traditional and optimization methods. Weight versus reliabilitytraced out an inverted-S-shaped graph. The center of the graph corresponded to mean valued design. A heavy design with weight approaching infinity could be produced for a near-zero rate of failure. Weight can be reduced to a small value for a most failure-prone design. Probabilistic modeling of load and material properties remained a challenge.

  4. Use of traditional and modern contraceptives among childbearing women: findings from a mixed methods study in two southwestern Nigerian states.

    Science.gov (United States)

    Ajayi, Anthony Idowu; Adeniyi, Oladele Vincent; Akpan, Wilson

    2018-05-09

    Contraceptive use has numerous health benefits such as preventing unplanned pregnancies, ensuring optimum spacing between births, reducing maternal and child mortality, and improving the lives of women and children in general. This study examines the level of contraceptive use, its determinants, reasons for non-use of contraception among women in the reproductive age group (18-49 years) in two southwestern Nigerian states. The study adopted an interviewer-administered questionnaire to collect data from 809 participants selected using a 3-stage cluster random sampling technique. We also conducted 46 in-depth interviews. In order to investigate the association between the socio-demographic variables and use of contraceptive methods, we estimated the binary logistic regression models. The findings indicated that knowledge of any methods of contraception was almost universal among the participants. The rates of ever use and current use of contraception was 80 and 66.6%, respectively. However, only 43.9% of the participants had ever used any modern contraceptive methods, considered to be more reliable. The fear of side effects of modern contraceptive methods drove women to rely on less effective traditional methods (withdrawal and rhythm methods). Some women employed crude and unproven contraceptive methods to prevent pregnancies. Our findings show that the rate of contraceptive use was high in the study setting. However, many women chose less effective traditional contraceptive methods over more effective modern contraceptive methods due to fear of side effects of the latter. Patient education on the various options of modern contraceptives, their side effects and management would be crucial towards expanding the family planning services in the study setting.

  5. Developing Employability Skills in Information System Graduates: Traditional vs. Innovative Teaching Methods

    Science.gov (United States)

    Osmani, Mohamad; Hindi, Nitham M.; Weerakkody, Vishanth

    2018-01-01

    It is widely acknowledged that traditional teaching methods such as lectures, textbooks and case study techniques on their own are not adequate to improving the most in-demand employability skills for graduates. The aim of this article is to explore the potential impact that novel learning and teaching methods can have on improving the…

  6. Deep learning versus traditional machine learning methods for aggregated energy demand prediction

    NARCIS (Netherlands)

    Paterakis, N.G.; Mocanu, E.; Gibescu, M.; Stappers, B.; van Alst, W.

    2018-01-01

    In this paper the more advanced, in comparison with traditional machine learning approaches, deep learning methods are explored with the purpose of accurately predicting the aggregated energy consumption. Despite the fact that a wide range of machine learning methods have been applied to

  7. Atomic and electronic structure of clusters from car-Parrinello method

    International Nuclear Information System (INIS)

    Kumar, V.

    1994-06-01

    With the development of ab-initio molecular dynamics method, it has now become possible to study the static and dynamical properties of clusters containing up to a few tens of atoms. Here I present a review of the method within the framework of the density functional theory and pseudopotential approach to represent the electron-ion interaction and discuss some of its applications to clusters. Particular attention is focussed on the structure and bonding properties of clusters as a function of their size. Applications to clusters of alkali metals and Al, non-metal - metal transition in divalent metal clusters, molecular clusters of carbon and Sb are discussed in detail. Some results are also presented on mixed clusters. (author). 121 refs, 24 ifigs

  8. Computer game-based and traditional learning method: a comparison regarding students’ knowledge retention

    Directory of Open Access Journals (Sweden)

    Rondon Silmara

    2013-02-01

    Full Text Available Abstract Background Educational computer games are examples of computer-assisted learning objects, representing an educational strategy of growing interest. Given the changes in the digital world over the last decades, students of the current generation expect technology to be used in advancing their learning requiring a need to change traditional passive learning methodologies to an active multisensory experimental learning methodology. The objective of this study was to compare a computer game-based learning method with a traditional learning method, regarding learning gains and knowledge retention, as means of teaching head and neck Anatomy and Physiology to Speech-Language and Hearing pathology undergraduate students. Methods Students were randomized to participate to one of the learning methods and the data analyst was blinded to which method of learning the students had received. Students’ prior knowledge (i.e. before undergoing the learning method, short-term knowledge retention and long-term knowledge retention (i.e. six months after undergoing the learning method were assessed with a multiple choice questionnaire. Students’ performance was compared considering the three moments of assessment for both for the mean total score and for separated mean scores for Anatomy questions and for Physiology questions. Results Students that received the game-based method performed better in the pos-test assessment only when considering the Anatomy questions section. Students that received the traditional lecture performed better in both post-test and long-term post-test when considering the Anatomy and Physiology questions. Conclusions The game-based learning method is comparable to the traditional learning method in general and in short-term gains, while the traditional lecture still seems to be more effective to improve students’ short and long-term knowledge retention.

  9. Trend analysis using non-stationary time series clustering based on the finite element method

    OpenAIRE

    Gorji Sefidmazgi, M.; Sayemuzzaman, M.; Homaifar, A.; Jha, M. K.; Liess, S.

    2014-01-01

    In order to analyze low-frequency variability of climate, it is useful to model the climatic time series with multiple linear trends and locate the times of significant changes. In this paper, we have used non-stationary time series clustering to find change points in the trends. Clustering in a multi-dimensional non-stationary time series is challenging, since the problem is mathematically ill-posed. Clustering based on the finite element method (FEM) is one of the methods ...

  10. Research on the localization method of protecting traditional village landscape: a case study on Tangyin

    Directory of Open Access Journals (Sweden)

    W. Li

    2015-08-01

    Full Text Available China has over 271 million villages and less than the number in ten years ago in which there are 363 million villages. New rural construction indeed do some good for common villages but still destroy hundreds and thousands traditional village which contain great cultural, science, artistic values. In addition, traditional villages can't meet the increasing needs in more convenient and comfortable living conditions. Increasing population also makes traditional villages out of control in construction. With the background of this, we have to set up in traditional village protection. This article put forward an idea in protection which make use of landscape localization to pursue the sustainable development and vernacular landscape protection. Tangyin Town is a famous trade center in history and left many cultural heritage, especially historical buildings. Take Tangyin as a case study to apply the localization method which could guide other similar villages to achieve same goals.

  11. Interactive K-Means Clustering Method Based on User Behavior for Different Analysis Target in Medicine.

    Science.gov (United States)

    Lei, Yang; Yu, Dai; Bin, Zhang; Yang, Yang

    2017-01-01

    Clustering algorithm as a basis of data analysis is widely used in analysis systems. However, as for the high dimensions of the data, the clustering algorithm may overlook the business relation between these dimensions especially in the medical fields. As a result, usually the clustering result may not meet the business goals of the users. Then, in the clustering process, if it can combine the knowledge of the users, that is, the doctor's knowledge or the analysis intent, the clustering result can be more satisfied. In this paper, we propose an interactive K -means clustering method to improve the user's satisfactions towards the result. The core of this method is to get the user's feedback of the clustering result, to optimize the clustering result. Then, a particle swarm optimization algorithm is used in the method to optimize the parameters, especially the weight settings in the clustering algorithm to make it reflect the user's business preference as possible. After that, based on the parameter optimization and adjustment, the clustering result can be closer to the user's requirement. Finally, we take an example in the breast cancer, to testify our method. The experiments show the better performance of our algorithm.

  12. Computer game-based and traditional learning method: a comparison regarding students' knowledge retention.

    Science.gov (United States)

    Rondon, Silmara; Sassi, Fernanda Chiarion; Furquim de Andrade, Claudia Regina

    2013-02-25

    Educational computer games are examples of computer-assisted learning objects, representing an educational strategy of growing interest. Given the changes in the digital world over the last decades, students of the current generation expect technology to be used in advancing their learning requiring a need to change traditional passive learning methodologies to an active multisensory experimental learning methodology. The objective of this study was to compare a computer game-based learning method with a traditional learning method, regarding learning gains and knowledge retention, as means of teaching head and neck Anatomy and Physiology to Speech-Language and Hearing pathology undergraduate students. Students were randomized to participate to one of the learning methods and the data analyst was blinded to which method of learning the students had received. Students' prior knowledge (i.e. before undergoing the learning method), short-term knowledge retention and long-term knowledge retention (i.e. six months after undergoing the learning method) were assessed with a multiple choice questionnaire. Students' performance was compared considering the three moments of assessment for both for the mean total score and for separated mean scores for Anatomy questions and for Physiology questions. Students that received the game-based method performed better in the pos-test assessment only when considering the Anatomy questions section. Students that received the traditional lecture performed better in both post-test and long-term post-test when considering the Anatomy and Physiology questions. The game-based learning method is comparable to the traditional learning method in general and in short-term gains, while the traditional lecture still seems to be more effective to improve students' short and long-term knowledge retention.

  13. Anharmonic effects in the quantum cluster equilibrium method

    Science.gov (United States)

    von Domaros, Michael; Perlt, Eva

    2017-03-01

    The well-established quantum cluster equilibrium (QCE) model provides a statistical thermodynamic framework to apply high-level ab initio calculations of finite cluster structures to macroscopic liquid phases using the partition function. So far, the harmonic approximation has been applied throughout the calculations. In this article, we apply an important correction in the evaluation of the one-particle partition function and account for anharmonicity. Therefore, we implemented an analytical approximation to the Morse partition function and the derivatives of its logarithm with respect to temperature, which are required for the evaluation of thermodynamic quantities. This anharmonic QCE approach has been applied to liquid hydrogen chloride and cluster distributions, and the molar volume, the volumetric thermal expansion coefficient, and the isobaric heat capacity have been calculated. An improved description for all properties is observed if anharmonic effects are considered.

  14. A crystalline cluster method for deep impurities in insulators

    International Nuclear Information System (INIS)

    Guimaraes, P.S.

    1983-01-01

    An 'ab initio' self-consistent-field crystalline-cluster approach to the study of deep impurity states in insulators is proposed. It is shown that, in spite of being a cluster calculation, the interaction of the impurity with the crystal environment is fully taken into account. It is also shown that the present representation of the impurity states is, at least, as precise as the crystalline cluster representation of the pure crystal electronic structure. The procedure has been tested by performing the calculation of the electronic structure of the U center in a sodium chloride crystal, and it has been observed that the calculated GAMMA 1 - GAMMA 15 absorption energy is in good agreement with experiment. (Author) [pt

  15. A crystalline cluster method for deep impurities in insulators

    International Nuclear Information System (INIS)

    Guimaraes, P.S.

    1983-01-01

    An ''ab initio'' self-consistent-field crysttalline-cluster approach to the study of deep impurity states in insulators is proposed. It is shown that, in spite of being a cluster calculation, the interaction of the impurity with the crystal environment is fully taken into account. It is also shown that the present representation of the impurity states is, at least, as precise as the crystalline cluster representation of the pure crystal electronic structure. The procedure has been tested by performing the calculation of the electronic structure of the U center in a sodium chloride crystal, and it has been observed that the calculated γ 1 - γ 15 absorption energy is in good agreement with experiment. (author) [pt

  16. Method for discovering relationships in data by dynamic quantum clustering

    Science.gov (United States)

    Weinstein, Marvin; Horn, David

    2014-10-28

    Data clustering is provided according to a dynamical framework based on quantum mechanical time evolution of states corresponding to data points. To expedite computations, we can approximate the time-dependent Hamiltonian formalism by a truncated calculation within a set of Gaussian wave-functions (coherent states) centered around the original points. This allows for analytic evaluation of the time evolution of all such states, opening up the possibility of exploration of relationships among data-points through observation of varying dynamical-distances among points and convergence of points into clusters. This formalism may be further supplemented by preprocessing, such as dimensional reduction through singular value decomposition and/or feature filtering.

  17. A dynamic lattice searching method with rotation operation for optimization of large clusters

    International Nuclear Information System (INIS)

    Wu Xia; Cai Wensheng; Shao Xueguang

    2009-01-01

    Global optimization of large clusters has been a difficult task, though much effort has been paid and many efficient methods have been proposed. During our works, a rotation operation (RO) is designed to realize the structural transformation from decahedra to icosahedra for the optimization of large clusters, by rotating the atoms below the center atom with a definite degree around the fivefold axis. Based on the RO, a development of the previous dynamic lattice searching with constructed core (DLSc), named as DLSc-RO, is presented. With an investigation of the method for the optimization of Lennard-Jones (LJ) clusters, i.e., LJ 500 , LJ 561 , LJ 600 , LJ 665-667 , LJ 670 , LJ 685 , and LJ 923 , Morse clusters, silver clusters by Gupta potential, and aluminum clusters by NP-B potential, it was found that both the global minima with icosahedral and decahedral motifs can be obtained, and the method is proved to be efficient and universal.

  18. Reasons for using traditional methods and role of nurses in family planning.

    Science.gov (United States)

    Yurdakul, Mine; Vural, Gülsen

    2002-05-01

    The withdrawal method and other traditional methods of contraception are still used in Turkey. Ninety-eight percent of women in Turkey know about modern family planning methods and where to find contraceptives. In fact, only one in every three women uses an effective method. The aim of this descriptive and experimental study was to investigate reasons for using traditional methods and the role of nurses in family planning. The women included in the sample were visited in their homes by nurses and educated for family planning in four sessions. Overall, 53.3% of women were using an effective method. However, 54.3% of women living in the Sirintepe district and 41.6% of women living in the Yenikent district were still using the traditional methods they used before. After the education sessions, the most widely used method was found to be intrauterine device (22.8%) in Sirintepe and condom (25%) in Yenikent. There was a significant difference in family planning methods between these two districts (p < 0.001).

  19. [Discussion on ideological concept implied in traditional reinforcing and reducing method of acupuncture].

    Science.gov (United States)

    Li, Suyun; Zhao, Jingsheng

    2017-11-12

    The forming and development of traditional reinforcing and reducing method of acupuncture was rooted in traditional culture of China, and was based on the ancients' special understanding of nature, life and diseases, therefore its principle and methods were inevitably influenced by philosophy culture and medicine concept at that time. With deep study on Inner Canon of Huangdi and representative reinforcing and reducing method of acupuncture, the implied ideological concept, including contradiction view and profit-loss view in ancient dialectic, yin-yang balance theory, concept of life flow, monophyletic theory of qi , theory of existence of disease-evil, yin - yang astrology theory, theory of inter-promotion of five elements, were summarized and analyzed. The clarified and systematic understanding on guiding ideology of reinforcing and reducing method of acupuncture could significantly promote the understanding on principle, method, content and manipulation.

  20. Data Clustering

    Science.gov (United States)

    Wagstaff, Kiri L.

    2012-03-01

    On obtaining a new data set, the researcher is immediately faced with the challenge of obtaining a high-level understanding from the observations. What does a typical item look like? What are the dominant trends? How many distinct groups are included in the data set, and how is each one characterized? Which observable values are common, and which rarely occur? Which items stand out as anomalies or outliers from the rest of the data? This challenge is exacerbated by the steady growth in data set size [11] as new instruments push into new frontiers of parameter space, via improvements in temporal, spatial, and spectral resolution, or by the desire to "fuse" observations from different modalities and instruments into a larger-picture understanding of the same underlying phenomenon. Data clustering algorithms provide a variety of solutions for this task. They can generate summaries, locate outliers, compress data, identify dense or sparse regions of feature space, and build data models. It is useful to note up front that "clusters" in this context refer to groups of items within some descriptive feature space, not (necessarily) to "galaxy clusters" which are dense regions in physical space. The goal of this chapter is to survey a variety of data clustering methods, with an eye toward their applicability to astronomical data analysis. In addition to improving the individual researcher’s understanding of a given data set, clustering has led directly to scientific advances, such as the discovery of new subclasses of stars [14] and gamma-ray bursts (GRBs) [38]. All clustering algorithms seek to identify groups within a data set that reflect some observed, quantifiable structure. Clustering is traditionally an unsupervised approach to data analysis, in the sense that it operates without any direct guidance about which items should be assigned to which clusters. There has been a recent trend in the clustering literature toward supporting semisupervised or constrained

  1. The determinants of traditional medicine use in Northern Tanzania: a mixed-methods study.

    Directory of Open Access Journals (Sweden)

    John W Stanifer

    Full Text Available Traditional medicines are an important part of healthcare in sub-Saharan Africa, and building successful disease treatment programs that are sensitive to traditional medicine practices will require an understanding of their current use and roles, including from a biomedical perspective. Therefore, we conducted a mixed-method study in Northern Tanzania in order to characterize the extent of and reasons for the use of traditional medicines among the general population so that we can better inform public health efforts in the region.Between December 2013 and June 2014 in Kilimanjaro, Tanzania, we conducted 5 focus group discussions and 27 in-depth interviews of key informants. The data from these sessions were analyzed using an inductive framework method with cultural insider-outsider coding. From these results, we developed a structured survey designed to test different aspects of traditional medicine use and administered it to a random sample of 655 adults from the community. The results were triangulated to explore converging and diverging themes.Most structured survey participants (68% reported knowing someone who frequently used traditional medicines, and the majority (56% reported using them themselves in the previous year. The most common uses were for symptomatic ailments (42%, chronic diseases (15%, reproductive problems (11%, and malaria/febrile illnesses (11%. We identified five major determinants for traditional medicine use in Northern Tanzania: biomedical healthcare delivery, credibility of traditional practices, strong cultural identities, individual health status, and disease understanding.In order to better formulate effective local disease management programs that are sensitive to TM practices, we described the determinants of TM use. Additionally, we found TM use to be high in Northern Tanzania and that its use is not limited to lower-income areas or rural settings. After symptomatic ailments, chronic diseases were reported as

  2. How often do patients in primary care use the methods of traditional medicine

    Directory of Open Access Journals (Sweden)

    Petrov-Kiurski Miloranka

    2014-01-01

    Full Text Available Introduction: Traditional medicine is a comprehensive system of theory and practice, implemented in the prevention, diagnostics and treatment of diseases, which utilizes preparations of vegetable, animal and mineral origin, as well as methods of spiritual therapy Objective: 1. To estimate how many patients in primary care use traditional medicine for diagnostics, treatment and prevention of diseases, and to establish possible differences regarding gender, age and urban or rural location. 2. What methods of traditional medicine are the most often used, and for which diseases and conditions? 3. Why did the subjects opted for this type of treatment, and what was the effect of the therapy? Method: Multicentric research based on interviewing patients in five outpatient health centers in Serbia. As a survey instrument was used a questionnaire with 10 questions. Results: The study included 1157 subjects, 683 women and 474 men, mean age 60.22±14.54, The traditional medicine was used by 83.66% (79.96% males and 86.245% females. Information about the methods of traditional medicine subjects usually received from their friends and acquaintances (54.9% and the media (39.3%. There is no significant difference in the way of obtaining information in relation to gender. Information on the internet was obtained more often in subjects younger than 65 (p=0.000 and in urban population (p=0.000. The same is true for information obtained from doctor or pharmacist (p=0.003. They opted for this method because in their opinion it is less harmful and have less adverse effects (72.8%. This type of treatment patients used for treatment of muscles, bone and joint diseases - 28.5%, diseases of the heart and blood vessels -21,1 %, and for the treatment of pain 19.7%. Patients from rural areas more often used traditional medicine for treatment of cardiovascular diseases (p=0.000. Outcome of treatment was good or satisfactory in 45.3%, moderate in 32%, and in 15.8% effect was

  3. Teaching-learning: stereoscopic 3D versus Traditional methods in Mexico City.

    Science.gov (United States)

    Mendoza Oropeza, Laura; Ortiz Sánchez, Ricardo; Ojeda Villagómez, Raúl

    2015-01-01

    In the UNAM Faculty of Odontology, we use a stereoscopic 3D teaching method that has grown more common in the last year, which makes it important to know whether students can learn better with this strategy. The objective of the study is to know, if the 4th year students of the bachelor's degree in dentistry learn more effectively with the use of stereoscopic 3D than the traditional method in Orthodontics. first, we selected the course topics, to be used for both methods; the traditional method using projection of slides and for the stereoscopic third dimension, with the use of videos in digital stereo projection (seen through "passive" polarized 3D glasses). The main topic was supernumerary teeth, including and diverted from their guide eruption. Afterwards we performed an exam on students, containing 24 items, validated by expert judgment in Orthodontics teaching. The results of the data were compared between the two educational methods for determined effectiveness using the model before and after measurement with the statistical package SPSS 20 version. The results presented for the 9 groups of undergraduates in dentistry, were collected with a total of 218 students for 3D and traditional methods, we found in a traditional method a mean 4.91, SD 1.4752 in the pretest and X=6.96, SD 1.26622, St Error 0.12318 for the posttest. The 3D method had a mean 5.21, SD 1.996779 St Error 0.193036 for the pretest X= 7.82, SD =0.963963, St Error 0.09319 posttest; the analysis of Variance between groups F= 5.60 Prob > 0.0000 and Bartlett's test for equal variances 21.0640 Prob > chi2 = 0.007. These results show that the student's learning in 3D means a significant improvement as compared to the traditional teaching method and having a strong association between the two methods. The findings suggest that the stereoscopic 3D method lead to improved student learning compared to traditional teaching.

  4. Intravenous catheter training system: computer-based education versus traditional learning methods.

    Science.gov (United States)

    Engum, Scott A; Jeffries, Pamela; Fisher, Lisa

    2003-07-01

    Virtual reality simulators allow trainees to practice techniques without consequences, reduce potential risk associated with training, minimize animal use, and help to develop standards and optimize procedures. Current intravenous (IV) catheter placement training methods utilize plastic arms, however, the lack of variability can diminish the educational stimulus for the student. This study compares the effectiveness of an interactive, multimedia, virtual reality computer IV catheter simulator with a traditional laboratory experience of teaching IV venipuncture skills to both nursing and medical students. A randomized, pretest-posttest experimental design was employed. A total of 163 participants, 70 baccalaureate nursing students and 93 third-year medical students beginning their fundamental skills training were recruited. The students ranged in age from 20 to 55 years (mean 25). Fifty-eight percent were female and 68% percent perceived themselves as having average computer skills (25% declaring excellence). The methods of IV catheter education compared included a traditional method of instruction involving a scripted self-study module which involved a 10-minute videotape, instructor demonstration, and hands-on-experience using plastic mannequin arms. The second method involved an interactive multimedia, commercially made computer catheter simulator program utilizing virtual reality (CathSim). The pretest scores were similar between the computer and the traditional laboratory group. There was a significant improvement in cognitive gains, student satisfaction, and documentation of the procedure with the traditional laboratory group compared with the computer catheter simulator group. Both groups were similar in their ability to demonstrate the skill correctly. CONCLUSIONS; This evaluation and assessment was an initial effort to assess new teaching methodologies related to intravenous catheter placement and their effects on student learning outcomes and behaviors

  5. The Efficacy of the clay meat ball as a method of traditional meat ...

    African Journals Online (AJOL)

    Keywords: meat ball, protein, mineral content. This work was carried out to determine the effectiveness of the use of clay meat balls (an African traditional method of preserving meat) in extending the shelf life of meat over a period of months against microbial (bacterial and fungal) spoilage and contamination without ...

  6. A Comparison of Traditional Worksheet and Linear Programming Methods for Teaching Manure Application Planning.

    Science.gov (United States)

    Schmitt, M. A.; And Others

    1994-01-01

    Compares traditional manure application planning techniques calculated to meet agronomic nutrient needs on a field-by-field basis with plans developed using computer-assisted linear programming optimization methods. Linear programming provided the most economical and environmentally sound manure application strategy. (Contains 15 references.) (MDH)

  7. Enhancing Learning Using 3D Printing: An Alternative to Traditional Student Project Methods

    Science.gov (United States)

    McGahern, Patricia; Bosch, Frances; Poli, DorothyBelle

    2015-01-01

    Student engagement during the development of a three-dimensional visual aid or teaching model can vary for a number of reasons. Some students report that they are not "creative" or "good at art," often as an excuse to justify less professional outcomes. Student engagement can be low when using traditional methods to produce a…

  8. Spatial Visualization Learning in Engineering: Traditional Methods vs. a Web-Based Tool

    Science.gov (United States)

    Pedrosa, Carlos Melgosa; Barbero, Basilio Ramos; Miguel, Arturo Román

    2014-01-01

    This study compares an interactive learning manager for graphic engineering to develop spatial vision (ILMAGE_SV) to traditional methods. ILMAGE_SV is an asynchronous web-based learning tool that allows the manipulation of objects with a 3D viewer, self-evaluation, and continuous assessment. In addition, student learning may be monitored, which…

  9. An Aural Learning Project: Assimilating Jazz Education Methods for Traditional Applied Pedagogy

    Science.gov (United States)

    Gamso, Nancy M.

    2011-01-01

    The Aural Learning Project (ALP) was developed to incorporate jazz method components into the author's classical practice and her applied woodwind lesson curriculum. The primary objective was to place a more focused pedagogical emphasis on listening and hearing than is traditionally used in the classical applied curriculum. The components of the…

  10. 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.

  11. 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.

  12. A cluster merging method for time series microarray with production values.

    Science.gov (United States)

    Chira, Camelia; Sedano, Javier; Camara, Monica; Prieto, Carlos; Villar, Jose R; Corchado, Emilio

    2014-09-01

    A challenging task in time-course microarray data analysis is to cluster genes meaningfully combining the information provided by multiple replicates covering the same key time points. This paper proposes a novel cluster merging method to accomplish this goal obtaining groups with highly correlated genes. The main idea behind the proposed method is to generate a clustering starting from groups created based on individual temporal series (representing different biological replicates measured in the same time points) and merging them by taking into account the frequency by which two genes are assembled together in each clustering. The gene groups at the level of individual time series are generated using several shape-based clustering methods. This study is focused on a real-world time series microarray task with the aim to find co-expressed genes related to the production and growth of a certain bacteria. The shape-based clustering methods used at the level of individual time series rely on identifying similar gene expression patterns over time which, in some models, are further matched to the pattern of production/growth. The proposed cluster merging method is able to produce meaningful gene groups which can be naturally ranked by the level of agreement on the clustering among individual time series. The list of clusters and genes is further sorted based on the information correlation coefficient and new problem-specific relevant measures. Computational experiments and results of the cluster merging method are analyzed from a biological perspective and further compared with the clustering generated based on the mean value of time series and the same shape-based algorithm.

  13. Consensus of satellite cluster flight using an energy-matching optimal control method

    Science.gov (United States)

    Luo, Jianjun; Zhou, Liang; Zhang, Bo

    2017-11-01

    This paper presents an optimal control method for consensus of satellite cluster flight under a kind of energy matching condition. Firstly, the relation between energy matching and satellite periodically bounded relative motion is analyzed, and the satellite energy matching principle is applied to configure the initial conditions. Then, period-delayed errors are adopted as state variables to establish the period-delayed errors dynamics models of a single satellite and the cluster. Next a novel satellite cluster feedback control protocol with coupling gain is designed, so that the satellite cluster periodically bounded relative motion consensus problem (period-delayed errors state consensus problem) is transformed to the stability of a set of matrices with the same low dimension. Based on the consensus region theory in the research of multi-agent system consensus issues, the coupling gain can be obtained to satisfy the requirement of consensus region and decouple the satellite cluster information topology and the feedback control gain matrix, which can be determined by Linear quadratic regulator (LQR) optimal method. This method can realize the consensus of satellite cluster period-delayed errors, leading to the consistency of semi-major axes (SMA) and the energy-matching of satellite cluster. Then satellites can emerge the global coordinative cluster behavior. Finally the feasibility and effectiveness of the present energy-matching optimal consensus for satellite cluster flight is verified through numerical simulations.

  14. An Extended Affinity Propagation Clustering Method Based on Different Data Density Types

    Directory of Open Access Journals (Sweden)

    XiuLi Zhao

    2015-01-01

    Full Text Available Affinity propagation (AP algorithm, as a novel clustering method, does not require the users to specify the initial cluster centers in advance, which regards all data points as potential exemplars (cluster centers equally and groups the clusters totally by the similar degree among the data points. But in many cases there exist some different intensive areas within the same data set, which means that the data set does not distribute homogeneously. In such situation the AP algorithm cannot group the data points into ideal clusters. In this paper, we proposed an extended AP clustering algorithm to deal with such a problem. There are two steps in our method: firstly the data set is partitioned into several data density types according to the nearest distances of each data point; and then the AP clustering method is, respectively, used to group the data points into clusters in each data density type. Two experiments are carried out to evaluate the performance of our algorithm: one utilizes an artificial data set and the other uses a real seismic data set. The experiment results show that groups are obtained more accurately by our algorithm than OPTICS and AP clustering algorithm itself.

  15. Semi-supervised spectral algorithms for community detection in complex networks based on equivalence of clustering methods

    Science.gov (United States)

    Ma, Xiaoke; Wang, Bingbo; Yu, Liang

    2018-01-01

    Community detection is fundamental for revealing the structure-functionality relationship in complex networks, which involves two issues-the quantitative function for community as well as algorithms to discover communities. Despite significant research on either of them, few attempt has been made to establish the connection between the two issues. To attack this problem, a generalized quantification function is proposed for community in weighted networks, which provides a framework that unifies several well-known measures. Then, we prove that the trace optimization of the proposed measure is equivalent with the objective functions of algorithms such as nonnegative matrix factorization, kernel K-means as well as spectral clustering. It serves as the theoretical foundation for designing algorithms for community detection. On the second issue, a semi-supervised spectral clustering algorithm is developed by exploring the equivalence relation via combining the nonnegative matrix factorization and spectral clustering. Different from the traditional semi-supervised algorithms, the partial supervision is integrated into the objective of the spectral algorithm. Finally, through extensive experiments on both artificial and real world networks, we demonstrate that the proposed method improves the accuracy of the traditional spectral algorithms in community detection.

  16. A NEW METHOD TO QUANTIFY X-RAY SUBSTRUCTURES IN CLUSTERS OF GALAXIES

    Energy Technology Data Exchange (ETDEWEB)

    Andrade-Santos, Felipe; Lima Neto, Gastao B.; Lagana, Tatiana F. [Departamento de Astronomia, Instituto de Astronomia, Geofisica e Ciencias Atmosfericas, Universidade de Sao Paulo, Geofisica e Ciencias Atmosfericas, Rua do Matao 1226, Cidade Universitaria, 05508-090 Sao Paulo, SP (Brazil)

    2012-02-20

    We present a new method to quantify substructures in clusters of galaxies, based on the analysis of the intensity of structures. This analysis is done in a residual image that is the result of the subtraction of a surface brightness model, obtained by fitting a two-dimensional analytical model ({beta}-model or Sersic profile) with elliptical symmetry, from the X-ray image. Our method is applied to 34 clusters observed by the Chandra Space Telescope that are in the redshift range z in [0.02, 0.2] and have a signal-to-noise ratio (S/N) greater than 100. We present the calibration of the method and the relations between the substructure level with physical quantities, such as the mass, X-ray luminosity, temperature, and cluster redshift. We use our method to separate the clusters in two sub-samples of high- and low-substructure levels. We conclude, using Monte Carlo simulations, that the method recuperates very well the true amount of substructure for small angular core radii clusters (with respect to the whole image size) and good S/N observations. We find no evidence of correlation between the substructure level and physical properties of the clusters such as gas temperature, X-ray luminosity, and redshift; however, analysis suggest a trend between the substructure level and cluster mass. The scaling relations for the two sub-samples (high- and low-substructure level clusters) are different (they present an offset, i.e., given a fixed mass or temperature, low-substructure clusters tend to be more X-ray luminous), which is an important result for cosmological tests using the mass-luminosity relation to obtain the cluster mass function, since they rely on the assumption that clusters do not present different scaling relations according to their dynamical state.

  17. Identification of the traditional methods of newborn mothers regarding jaundice in Turkey.

    Science.gov (United States)

    Aydin, Diler; Karaca Ciftci, Esra; Karatas, Hulya

    2014-02-01

    To detect traditional methods applied for the treatment of newborn jaundice by mothers in Turkey. Traditional methods are generally used in our society. Instead of using medical services, people often use already-known traditional methods to treat the disease. In such cases, the prognosis of the disease generally becomes worse, the treatment period longer and healthcare costs higher, and more medicine is used. A cross-sectional descriptive study. The participants of this study were 229 mothers with newborn babies aged 0-28 days in one university hospital and one public children's hospital in Sanliurfa. The study was conducted between March and May 2012. In this research, the Beliefs and Traditional Methods of Mothers for Jaundice Questionnaire, which was formed by searching the relevant literature, is used as a data collection tool. The data are evaluated by percentage distributions. Mothers apply conventional practices in cases of health problems such as jaundice, and application of these methods is important to mothers. Moreover, mothers reported applying hazardous conventional methods in cases of neonatal jaundice, such as cutting the area between the baby's eyebrows with a blade, cutting the back of the ear and the body and burning the body, which are not applied in different cultures. Education regarding the effects of conventional methods being applied in families should be provided, and the results of this study should serve to guide further studies in assessing the effects of such education. This approach can support beneficial practices involving individual care and prevent the negative health effects of hazardous practices. © 2013 John Wiley & Sons Ltd.

  18. Investigation of the cluster formation in lithium niobate crystals by computer modeling method

    Energy Technology Data Exchange (ETDEWEB)

    Voskresenskii, V. M.; Starodub, O. R., E-mail: ol-star@mail.ru; Sidorov, N. V.; Palatnikov, M. N. [Russian Academy of Sciences, Tananaev Institute of Chemistry and Technology of Rare Earth Elements and Mineral Raw Materials, Kola Science Centre (Russian Federation)

    2017-03-15

    The processes occurring upon the formation of energetically equilibrium oxygen-octahedral clusters in the ferroelectric phase of a stoichiometric lithium niobate (LiNbO{sub 3}) crystal have been investigated by the computer modeling method within the semiclassical atomistic model. An energetically favorable cluster size (at which a structure similar to that of a congruent crystal is organized) is shown to exist. A stoichiometric cluster cannot exist because of the electroneutrality loss. The most energetically favorable cluster is that with a Li/Nb ratio of about 0.945, a value close to the lithium-to-niobium ratio for a congruent crystal.

  19. Comparison of traditional and interactive teaching methods in a UK emergency department.

    Science.gov (United States)

    Armstrong, Peter; Elliott, Tim; Ronald, Julie; Paterson, Brodie

    2009-12-01

    Didactic teaching remains a core component of undergraduate education, but developing computer assisted learning (CAL) packages may provide useful alternatives. We compared the effectiveness of interactive multimedia-based tutorials with traditional, lecture-based models for teaching arterial blood gas interpretation to fourth year medical students. Participants were randomized to complete a tutorial in either lecture or multimedia format containing identical content. Upon completion, students answered five multiple choice questions assessing post-tutorial knowledge, and provided feedback on their allocated learning method. Marks revealed no significant difference between either group. All lecture candidates rated their teaching as good, compared with 89% of the CAL group. All CAL users found multiple choice questions assessment useful, compared with 83% of lecture participants. Both groups highlighted the importance of interaction. CAL complements other teaching methods, but should be seen as an adjunct to, rather than a replacement for, traditional methods, thus offering students a blended learning environment.

  20. Identification of some Fusarium species from selected crop seeds using traditional method and BIO-PCR

    Directory of Open Access Journals (Sweden)

    Tomasz Kulik

    2012-12-01

    Full Text Available We identified a species level of the fungal cultures isolated from selected crop seeds using traditional method and BIO-PCR. The use of BIO-PCR did not correspond completely to the morphological analyses. Both methods showed increased infection with F. poae in winter wheat seed sample originated from north Poland. Fungal culture No 40 (isolated from faba bean and identified with traditional method as mixed culture with F. culmorum and F. graminearum did not produce expected product after PCR reaction with species specific primers OPT18F470, OPT18R470. However, the use of additional primers Fc01F, Fc01R allowed for reliable identification of F. culmorum in the culture.

  1. A Composite Model of Wound Segmentation Based on Traditional Methods and Deep Neural Networks

    Directory of Open Access Journals (Sweden)

    Fangzhao Li

    2018-01-01

    Full Text Available Wound segmentation plays an important supporting role in the wound observation and wound healing. Current methods of image segmentation include those based on traditional process of image and those based on deep neural networks. The traditional methods use the artificial image features to complete the task without large amounts of labeled data. Meanwhile, the methods based on deep neural networks can extract the image features effectively without the artificial design, but lots of training data are required. Combined with the advantages of them, this paper presents a composite model of wound segmentation. The model uses the skin with wound detection algorithm we designed in the paper to highlight image features. Then, the preprocessed images are segmented by deep neural networks. And semantic corrections are applied to the segmentation results at last. The model shows a good performance in our experiment.

  2. [Current development of rapid high-throughout determination technology for total components of traditional Chinese medicines and formula and synthetic immunity chip method].

    Science.gov (United States)

    He, Fu-Yuan; Deng, Kai-Wen; Zeng, Jiao-Li; Dai, Ru-Wen; Dai, Ru-Wen; Xia, Zan-Shao; Liu, Weng-Long; Shi, Ji-Lian

    2012-10-01

    The qualitative and quantitative analysis on traditional Chinese medicine and formula components can be made by chemical and instrumental analysis methods. Of both, the instrumental analysis methods play a dominant role, including HPLC, HPLC-MS, HPLC-NMR, GC, GC-MS, biochemical and biological effect. But because traditional Chinese medicines and formula have complicated components, chemical methods are so unspecific that they shall be used less or with caution. While instrumental analysis methods are so specific that they are appropriate for analyzing complicated single component. The analysis techniques for multiple components of traditional Chinese medicines and formula focus on fingerprints, but all of these analysis techniques are limited by the pre-requisite of separation and the lack of general-purpose detectors and therefore being hard to realize the determination of all components of traditional Chinese medicines and formula. In the natural world, however, organisms identify native and alien components through specificity and non-specificity of clusters decided by antigens and antibodies. For example, components of traditional Chinese medicines are directly or indirectly synthesized into antigens and injected into animals, in order to generate specific antibodies and then collect cross reaction information of these components to specific antibodies. As for components without cross reaction, their contents shall be directly read out on the basis of the inhibition rate curve of competitive reaction for specificity of antigens and antibodies. Besides, a cross inhibition rate matrix shall be established first, and them a multiple regression linear equation between cross component concentration or concentration logarithm and inhibition rate by labeling the immunity competitive reaction between antibodies and haptens of traditional Chinese medicine and compound components, and then solved to obtain concentration of each component. The two results are combined to

  3. Clustering Methods; Part IV of Scientific Report No. ISR-18, Information Storage and Retrieval...

    Science.gov (United States)

    Cornell Univ., Ithaca, NY. Dept. of Computer Science.

    Two papers are included as Part Four of this report on Salton's Magical Automatic Retriever of Texts (SMART) project report. The first paper: "A Controlled Single Pass Classification Algorithm with Application to Multilevel Clustering" by D. B. Johnson and J. M. Laferente presents a single pass clustering method which compares favorably…

  4. An incremental DPMM-based method for trajectory clustering, modeling, and retrieval.

    Science.gov (United States)

    Hu, Weiming; Li, Xi; Tian, Guodong; Maybank, Stephen; Zhang, Zhongfei

    2013-05-01

    Trajectory analysis is the basis for many applications, such as indexing of motion events in videos, activity recognition, and surveillance. In this paper, the Dirichlet process mixture model (DPMM) is applied to trajectory clustering, modeling, and retrieval. We propose an incremental version of a DPMM-based clustering algorithm and apply it to cluster trajectories. An appropriate number of trajectory clusters is determined automatically. When trajectories belonging to new clusters arrive, the new clusters can be identified online and added to the model without any retraining using the previous data. A time-sensitive Dirichlet process mixture model (tDPMM) is applied to each trajectory cluster for learning the trajectory pattern which represents the time-series characteristics of the trajectories in the cluster. Then, a parameterized index is constructed for each cluster. A novel likelihood estimation algorithm for the tDPMM is proposed, and a trajectory-based video retrieval model is developed. The tDPMM-based probabilistic matching method and the DPMM-based model growing method are combined to make the retrieval model scalable and adaptable. Experimental comparisons with state-of-the-art algorithms demonstrate the effectiveness of our algorithm.

  5. Performance Analysis of Entropy Methods on K Means in Clustering Process

    Science.gov (United States)

    Dicky Syahputra Lubis, Mhd.; Mawengkang, Herman; Suwilo, Saib

    2017-12-01

    K Means is a non-hierarchical data clustering method that attempts to partition existing data into one or more clusters / groups. This method partitions the data into clusters / groups so that data that have the same characteristics are grouped into the same cluster and data that have different characteristics are grouped into other groups.The purpose of this data clustering is to minimize the objective function set in the clustering process, which generally attempts to minimize variation within a cluster and maximize the variation between clusters. However, the main disadvantage of this method is that the number k is often not known before. Furthermore, a randomly chosen starting point may cause two points to approach the distance to be determined as two centroids. Therefore, for the determination of the starting point in K Means used entropy method where this method is a method that can be used to determine a weight and take a decision from a set of alternatives. Entropy is able to investigate the harmony in discrimination among a multitude of data sets. Using Entropy criteria with the highest value variations will get the highest weight. Given this entropy method can help K Means work process in determining the starting point which is usually determined at random. Thus the process of clustering on K Means can be more quickly known by helping the entropy method where the iteration process is faster than the K Means Standard process. Where the postoperative patient dataset of the UCI Repository Machine Learning used and using only 12 data as an example of its calculations is obtained by entropy method only with 2 times iteration can get the desired end result.

  6. PARTIAL TRAINING METHOD FOR HEURISTIC ALGORITHM OF POSSIBLE CLUSTERIZATION UNDER UNKNOWN NUMBER OF CLASSES

    Directory of Open Access Journals (Sweden)

    D. A. Viattchenin

    2009-01-01

    Full Text Available A method for constructing a subset of labeled objects which is used in a heuristic algorithm of possible  clusterization with partial  training is proposed in the  paper.  The  method  is  based  on  data preprocessing by the heuristic algorithm of possible clusterization using a transitive closure of a fuzzy tolerance. Method efficiency is demonstrated by way of an illustrative example.

  7. A two-stage method for microcalcification cluster segmentation in mammography by deformable models

    International Nuclear Information System (INIS)

    Arikidis, N.; Kazantzi, A.; Skiadopoulos, S.; Karahaliou, A.; Costaridou, L.; Vassiou, K.

    2015-01-01

    Purpose: Segmentation of microcalcification (MC) clusters in x-ray mammography is a difficult task for radiologists. Accurate segmentation is prerequisite for quantitative image analysis of MC clusters and subsequent feature extraction and classification in computer-aided diagnosis schemes. Methods: In this study, a two-stage semiautomated segmentation method of MC clusters is investigated. The first stage is targeted to accurate and time efficient segmentation of the majority of the particles of a MC cluster, by means of a level set method. The second stage is targeted to shape refinement of selected individual MCs, by means of an active contour model. Both methods are applied in the framework of a rich scale-space representation, provided by the wavelet transform at integer scales. Segmentation reliability of the proposed method in terms of inter and intraobserver agreements was evaluated in a case sample of 80 MC clusters originating from the digital database for screening mammography, corresponding to 4 morphology types (punctate: 22, fine linear branching: 16, pleomorphic: 18, and amorphous: 24) of MC clusters, assessing radiologists’ segmentations quantitatively by two distance metrics (Hausdorff distance—HDIST cluster , average of minimum distance—AMINDIST cluster ) and the area overlap measure (AOM cluster ). The effect of the proposed segmentation method on MC cluster characterization accuracy was evaluated in a case sample of 162 pleomorphic MC clusters (72 malignant and 90 benign). Ten MC cluster features, targeted to capture morphologic properties of individual MCs in a cluster (area, major length, perimeter, compactness, and spread), were extracted and a correlation-based feature selection method yielded a feature subset to feed in a support vector machine classifier. Classification performance of the MC cluster features was estimated by means of the area under receiver operating characteristic curve (Az ± Standard Error) utilizing tenfold cross

  8. Gender preference between traditional and PowerPoint methods of teaching gross anatomy.

    Science.gov (United States)

    Nuhu, Saleh; Adamu, Lawan Hassan; Buba, Mohammed Alhaji; Garba, Sani Hyedima; Dalori, Babagana Mohammed; Yusuf, Ashiru Hassan

    2018-01-01

    Teaching and learning process is increasingly metamorphosing from the traditional chalk and talk to the modern dynamism in the information and communication technology. Medical education is no exception to this dynamism more especially in the teaching of gross anatomy, which serves as one of the bases of understanding the human structure. This study was conducted to determine the gender preference of preclinical medical students on the use of traditional (chalk and talk) and PowerPoint presentation in the teaching of gross anatomy. This was cross-sectional and prospective study, which was conducted among preclinical medical students in the University of Maiduguri, Nigeria. Using simple random techniques, a questionnaire was circulated among 280 medical students, where 247 students filled the questionnaire appropriately. The data obtained was analyzed using SPSS version 20 (IBM Corporation, Armonk, NY, USA) to find the method preferred by the students among other things. Majority of the preclinical medical students in the University of Maiduguri preferred PowerPoint method in the teaching of gross anatomy over the conventional methods. The Cronbach alpha value of 0.76 was obtained which is an acceptable level of internal consistency. A statistically significant association was found between gender and preferred method of lecture delivery on the clarity of lecture content where females prefer the conventional method of lecture delivery whereas males prefer the PowerPoint method, On the reproducibility of text and diagram, females prefer PowerPoint method of teaching gross anatomy while males prefer the conventional method of teaching gross anatomy. There are gender preferences with regard to clarity of lecture contents and reproducibility of text and diagram. It was also revealed from this study that majority of the preclinical medical students in the University of Maiduguri prefer PowerPoint presentation over the traditional chalk and talk method in most of the

  9. The swift UVOT stars survey. I. Methods and test clusters

    Energy Technology Data Exchange (ETDEWEB)

    Siegel, Michael H.; Porterfield, Blair L.; Linevsky, Jacquelyn S.; Bond, Howard E.; Hoversten, Erik A.; Berrier, Joshua L.; Gronwall, Caryl A. [Department of Astronomy and Astrophysics, The Pennsylvania State University, 525 Davey Laboratory, University Park, PA 16802 (United States); Holland, Stephen T. [Space Telescope Science Institute, 3700 San Martin Drive, Baltimore, MD 21218 (United States); Breeveld, Alice A. [Mullard Space Science Laboratory, University College London, Holmbury St. Mary, Dorking, Surrey RH5 6NT (United Kingdom); Brown, Peter J., E-mail: siegel@astro.psu.edu, E-mail: blp14@psu.edu, E-mail: heb11@psu.edu, E-mail: caryl@astro.psu.edu, E-mail: sholland@stsci.edu, E-mail: aab@mssl.ucl.ac.uk, E-mail: grbpeter@yahoo.com [George P. and Cynthia Woods Mitchell Institute for Fundamental Physics and Astronomy, Texas A. and M. University, Department of Physics and Astronomy, 4242 TAMU, College Station, TX 77843 (United States)

    2014-12-01

    We describe the motivations and background of a large survey of nearby stellar populations using the Ultraviolet Optical Telescope (UVOT) on board the Swift Gamma-Ray Burst Mission. UVOT, with its wide field, near-UV sensitivity, and 2.″3 spatial resolution, is uniquely suited to studying nearby stellar populations and providing insight into the near-UV properties of hot stars and the contribution of those stars to the integrated light of more distant stellar populations. We review the state of UV stellar photometry, outline the survey, and address problems specific to wide- and crowded-field UVOT photometry. We present color–magnitude diagrams of the nearby open clusters M67, NGC 188, and NGC 2539, and the globular cluster M79. We demonstrate that UVOT can easily discern the young- and intermediate-age main sequences, blue stragglers, and hot white dwarfs, producing results consistent with previous studies. We also find that it characterizes the blue horizontal branch of M79 and easily identifies a known post-asymptotic giant branch star.

  10. The swift UVOT stars survey. I. Methods and test clusters

    International Nuclear Information System (INIS)

    Siegel, Michael H.; Porterfield, Blair L.; Linevsky, Jacquelyn S.; Bond, Howard E.; Hoversten, Erik A.; Berrier, Joshua L.; Gronwall, Caryl A.; Holland, Stephen T.; Breeveld, Alice A.; Brown, Peter J.

    2014-01-01

    We describe the motivations and background of a large survey of nearby stellar populations using the Ultraviolet Optical Telescope (UVOT) on board the Swift Gamma-Ray Burst Mission. UVOT, with its wide field, near-UV sensitivity, and 2.″3 spatial resolution, is uniquely suited to studying nearby stellar populations and providing insight into the near-UV properties of hot stars and the contribution of those stars to the integrated light of more distant stellar populations. We review the state of UV stellar photometry, outline the survey, and address problems specific to wide- and crowded-field UVOT photometry. We present color–magnitude diagrams of the nearby open clusters M67, NGC 188, and NGC 2539, and the globular cluster M79. We demonstrate that UVOT can easily discern the young- and intermediate-age main sequences, blue stragglers, and hot white dwarfs, producing results consistent with previous studies. We also find that it characterizes the blue horizontal branch of M79 and easily identifies a known post-asymptotic giant branch star.

  11. Fast optimization of binary clusters using a novel dynamic lattice searching method

    International Nuclear Information System (INIS)

    Wu, Xia; Cheng, Wen

    2014-01-01

    Global optimization of binary clusters has been a difficult task despite of much effort and many efficient methods. Directing toward two types of elements (i.e., homotop problem) in binary clusters, two classes of virtual dynamic lattices are constructed and a modified dynamic lattice searching (DLS) method, i.e., binary DLS (BDLS) method, is developed. However, it was found that the BDLS can only be utilized for the optimization of binary clusters with small sizes because homotop problem is hard to be solved without atomic exchange operation. Therefore, the iterated local search (ILS) method is adopted to solve homotop problem and an efficient method based on the BDLS method and ILS, named as BDLS-ILS, is presented for global optimization of binary clusters. In order to assess the efficiency of the proposed method, binary Lennard-Jones clusters with up to 100 atoms are investigated. Results show that the method is proved to be efficient. Furthermore, the BDLS-ILS method is also adopted to study the geometrical structures of (AuPd) 79 clusters with DFT-fit parameters of Gupta potential

  12. Heuristic methods using grasp, path relinking and variable neighborhood search for the clustered traveling salesman problem

    Directory of Open Access Journals (Sweden)

    Mário Mestria

    2013-08-01

    Full Text Available The Clustered Traveling Salesman Problem (CTSP is a generalization of the Traveling Salesman Problem (TSP in which the set of vertices is partitioned into disjoint clusters and objective is to find a minimum cost Hamiltonian cycle such that the vertices of each cluster are visited contiguously. The CTSP is NP-hard and, in this context, we are proposed heuristic methods for the CTSP using GRASP, Path Relinking and Variable Neighborhood Descent (VND. The heuristic methods were tested using Euclidean instances with up to 2000 vertices and clusters varying between 4 to 150 vertices. The computational tests were performed to compare the performance of the heuristic methods with an exact algorithm using the Parallel CPLEX software. The computational results showed that the hybrid heuristic method using VND outperforms other heuristic methods.

  13. Clustering and training set selection methods for improving the accuracy of quantitative laser induced breakdown spectroscopy

    International Nuclear Information System (INIS)

    Anderson, Ryan B.; Bell, James F.; Wiens, Roger C.; Morris, Richard V.; Clegg, Samuel M.

    2012-01-01

    We investigated five clustering and training set selection methods to improve the accuracy of quantitative chemical analysis of geologic samples by laser induced breakdown spectroscopy (LIBS) using partial least squares (PLS) regression. The LIBS spectra were previously acquired for 195 rock slabs and 31 pressed powder geostandards under 7 Torr CO 2 at a stand-off distance of 7 m at 17 mJ per pulse to simulate the operational conditions of the ChemCam LIBS instrument on the Mars Science Laboratory Curiosity rover. The clustering and training set selection methods, which do not require prior knowledge of the chemical composition of the test-set samples, are based on grouping similar spectra and selecting appropriate training spectra for the partial least squares (PLS2) model. These methods were: (1) hierarchical clustering of the full set of training spectra and selection of a subset for use in training; (2) k-means clustering of all spectra and generation of PLS2 models based on the training samples within each cluster; (3) iterative use of PLS2 to predict sample composition and k-means clustering of the predicted compositions to subdivide the groups of spectra; (4) soft independent modeling of class analogy (SIMCA) classification of spectra, and generation of PLS2 models based on the training samples within each class; (5) use of Bayesian information criteria (BIC) to determine an optimal number of clusters and generation of PLS2 models based on the training samples within each cluster. The iterative method and the k-means method using 5 clusters showed the best performance, improving the absolute quadrature root mean squared error (RMSE) by ∼ 3 wt.%. The statistical significance of these improvements was ∼ 85%. Our results show that although clustering methods can modestly improve results, a large and diverse training set is the most reliable way to improve the accuracy of quantitative LIBS. In particular, additional sulfate standards and specifically

  14. Efficient nonparametric and asymptotic Bayesian model selection methods for attributed graph clustering

    KAUST Repository

    Xu, Zhiqiang

    2017-02-16

    Attributed graph clustering, also known as community detection on attributed graphs, attracts much interests recently due to the ubiquity of attributed graphs in real life. Many existing algorithms have been proposed for this problem, which are either distance based or model based. However, model selection in attributed graph clustering has not been well addressed, that is, most existing algorithms assume the cluster number to be known a priori. In this paper, we propose two efficient approaches for attributed graph clustering with automatic model selection. The first approach is a popular Bayesian nonparametric method, while the second approach is an asymptotic method based on a recently proposed model selection criterion, factorized information criterion. Experimental results on both synthetic and real datasets demonstrate that our approaches for attributed graph clustering with automatic model selection significantly outperform the state-of-the-art algorithm.

  15. Efficient nonparametric and asymptotic Bayesian model selection methods for attributed graph clustering

    KAUST Repository

    Xu, Zhiqiang; Cheng, James; Xiao, Xiaokui; Fujimaki, Ryohei; Muraoka, Yusuke

    2017-01-01

    Attributed graph clustering, also known as community detection on attributed graphs, attracts much interests recently due to the ubiquity of attributed graphs in real life. Many existing algorithms have been proposed for this problem, which are either distance based or model based. However, model selection in attributed graph clustering has not been well addressed, that is, most existing algorithms assume the cluster number to be known a priori. In this paper, we propose two efficient approaches for attributed graph clustering with automatic model selection. The first approach is a popular Bayesian nonparametric method, while the second approach is an asymptotic method based on a recently proposed model selection criterion, factorized information criterion. Experimental results on both synthetic and real datasets demonstrate that our approaches for attributed graph clustering with automatic model selection significantly outperform the state-of-the-art algorithm.

  16. Islamic geometric patterns their historical development and traditional methods of construction

    CERN Document Server

    Bonner, Jay

    2017-01-01

    The main focus of this unique book is an in-depth examination of the polygonal technique; the primary method used by master artists of the past in creating Islamic geometric patterns. The author details the design methodology responsible for this all-but-lost art form and presents evidence for its use from the historical record, both of which are vital contributions to the understanding of this ornamental tradition. Additionally, the author examines the historical development of Islamic geometric patterns, the significance of geometric design within the broader context of Islamic ornament as a whole, the formative role that geometry plays throughout the Islamic ornamental arts (including calligraphy, the floral idiom, dome decoration, geometric patterns, and more), and the underexamined question of pattern classification. Featuring over 600 beautiful color images, Islamic Geometric Patterns: Their Historical Development and Traditional Methods of Construction is a valuable addition to the literature of Islam...

  17. Clustering Scientific Publications Based on Citation Relations: A Systematic Comparison of Different Methods.

    Science.gov (United States)

    Šubelj, Lovro; van Eck, Nees Jan; Waltman, Ludo

    2016-01-01

    Clustering methods are applied regularly in the bibliometric literature to identify research areas or scientific fields. These methods are for instance used to group publications into clusters based on their relations in a citation network. In the network science literature, many clustering methods, often referred to as graph partitioning or community detection techniques, have been developed. Focusing on the problem of clustering the publications in a citation network, we present a systematic comparison of the performance of a large number of these clustering methods. Using a number of different citation networks, some of them relatively small and others very large, we extensively study the statistical properties of the results provided by different methods. In addition, we also carry out an expert-based assessment of the results produced by different methods. The expert-based assessment focuses on publications in the field of scientometrics. Our findings seem to indicate that there is a trade-off between different properties that may be considered desirable for a good clustering of publications. Overall, map equation methods appear to perform best in our analysis, suggesting that these methods deserve more attention from the bibliometric community.

  18. Clustering Scientific Publications Based on Citation Relations: A Systematic Comparison of Different Methods

    Science.gov (United States)

    Šubelj, Lovro; van Eck, Nees Jan; Waltman, Ludo

    2016-01-01

    Clustering methods are applied regularly in the bibliometric literature to identify research areas or scientific fields. These methods are for instance used to group publications into clusters based on their relations in a citation network. In the network science literature, many clustering methods, often referred to as graph partitioning or community detection techniques, have been developed. Focusing on the problem of clustering the publications in a citation network, we present a systematic comparison of the performance of a large number of these clustering methods. Using a number of different citation networks, some of them relatively small and others very large, we extensively study the statistical properties of the results provided by different methods. In addition, we also carry out an expert-based assessment of the results produced by different methods. The expert-based assessment focuses on publications in the field of scientometrics. Our findings seem to indicate that there is a trade-off between different properties that may be considered desirable for a good clustering of publications. Overall, map equation methods appear to perform best in our analysis, suggesting that these methods deserve more attention from the bibliometric community. PMID:27124610

  19. Product-service system method to measure sustainability level of traditional smoked fish processing industries

    OpenAIRE

    Purwaningsih Ratna; Cahyantari Anggaina Elfandora; Ariyani Zulfaida; Susanty Aries; Arvianto Ary; Santoso Haryo

    2018-01-01

    Small Medium Enterprise’s (SME) of traditional fish processing at Semarang, Central Java, Indonesia still focus their business on gain more profits. Sustainability aspect has not received enough attention yet. This study aims to review the sustainability level of SME smoked fish Semarang using product service system (PSS) method. PSS consists of three dimensions (1) Environment, (2) Socio-cultural and (3) Economic. Each dimension consists of 6 criteria's. PSS not only assess the level of sust...

  20. Analysis of Conflict Centers in Projects Procured with Traditional and Integrated Methods in Nigeria

    OpenAIRE

    Martin O. Dada

    2012-01-01

    Conflicts in any organization can either be functional or dysfunctional and can contribute to or detract from the achievement of organizational or project objectives. This study investigated the frequency and intensity of conflicts, using five conflict centers, on projects executed with either the integrated or traditional method in Nigeria. Questionnaires were administered through purposive and snowballing techniques on 274 projects located in twelve states of Nigeria and Abuja. 94 usable ...

  1. A clustering based method to evaluate soil corrosivity for pipeline external integrity management

    International Nuclear Information System (INIS)

    Yajima, Ayako; Wang, Hui; Liang, Robert Y.; Castaneda, Homero

    2015-01-01

    One important category of transportation infrastructure is underground pipelines. Corrosion of these buried pipeline systems may cause pipeline failures with the attendant hazards of property loss and fatalities. Therefore, developing the capability to estimate the soil corrosivity is important for designing and preserving materials and for risk assessment. The deterioration rate of metal is highly influenced by the physicochemical characteristics of a material and the environment of its surroundings. In this study, the field data obtained from the southeast region of Mexico was examined using various data mining techniques to determine the usefulness of these techniques for clustering soil corrosivity level. Specifically, the soil was classified into different corrosivity level clusters by k-means and Gaussian mixture model (GMM). In terms of physical space, GMM shows better separability; therefore, the distributions of the material loss of the buried petroleum pipeline walls were estimated via the empirical density within GMM clusters. The soil corrosivity levels of the clusters were determined based on the medians of metal loss. The proposed clustering method was demonstrated to be capable of classifying the soil into different levels of corrosivity severity. - Highlights: • The clustering approach is applied to the data extracted from a real-life pipeline system. • Soil properties in the right-of-way are analyzed via clustering techniques to assess corrosivity. • GMM is selected as the preferred method for detecting the hidden pattern of in-situ data. • K–W test is performed for significant difference of corrosivity level between clusters

  2. Relation between financial market structure and the real economy: comparison between clustering methods.

    Science.gov (United States)

    Musmeci, Nicoló; Aste, Tomaso; Di Matteo, T

    2015-01-01

    We quantify the amount of information filtered by different hierarchical clustering methods on correlations between stock returns comparing the clustering structure with the underlying industrial activity classification. We apply, for the first time to financial data, a novel hierarchical clustering approach, the Directed Bubble Hierarchical Tree and we compare it with other methods including the Linkage and k-medoids. By taking the industrial sector classification of stocks as a benchmark partition, we evaluate how the different methods retrieve this classification. The results show that the Directed Bubble Hierarchical Tree can outperform other methods, being able to retrieve more information with fewer clusters. Moreover,we show that the economic information is hidden at different levels of the hierarchical structures depending on the clustering method. The dynamical analysis on a rolling window also reveals that the different methods show different degrees of sensitivity to events affecting financial markets, like crises. These results can be of interest for all the applications of clustering methods to portfolio optimization and risk hedging [corrected].

  3. Relation between financial market structure and the real economy: comparison between clustering methods.

    Directory of Open Access Journals (Sweden)

    Nicoló Musmeci

    Full Text Available We quantify the amount of information filtered by different hierarchical clustering methods on correlations between stock returns comparing the clustering structure with the underlying industrial activity classification. We apply, for the first time to financial data, a novel hierarchical clustering approach, the Directed Bubble Hierarchical Tree and we compare it with other methods including the Linkage and k-medoids. By taking the industrial sector classification of stocks as a benchmark partition, we evaluate how the different methods retrieve this classification. The results show that the Directed Bubble Hierarchical Tree can outperform other methods, being able to retrieve more information with fewer clusters. Moreover,we show that the economic information is hidden at different levels of the hierarchical structures depending on the clustering method. The dynamical analysis on a rolling window also reveals that the different methods show different degrees of sensitivity to events affecting financial markets, like crises. These results can be of interest for all the applications of clustering methods to portfolio optimization and risk hedging [corrected].

  4. Trend analysis using non-stationary time series clustering based on the finite element method

    Science.gov (United States)

    Gorji Sefidmazgi, M.; Sayemuzzaman, M.; Homaifar, A.; Jha, M. K.; Liess, S.

    2014-05-01

    In order to analyze low-frequency variability of climate, it is useful to model the climatic time series with multiple linear trends and locate the times of significant changes. In this paper, we have used non-stationary time series clustering to find change points in the trends. Clustering in a multi-dimensional non-stationary time series is challenging, since the problem is mathematically ill-posed. Clustering based on the finite element method (FEM) is one of the methods that can analyze multidimensional time series. One important attribute of this method is that it is not dependent on any statistical assumption and does not need local stationarity in the time series. In this paper, it is shown how the FEM-clustering method can be used to locate change points in the trend of temperature time series from in situ observations. This method is applied to the temperature time series of North Carolina (NC) and the results represent region-specific climate variability despite higher frequency harmonics in climatic time series. Next, we investigated the relationship between the climatic indices with the clusters/trends detected based on this clustering method. It appears that the natural variability of climate change in NC during 1950-2009 can be explained mostly by AMO and solar activity.

  5. Phenotypic clustering: a novel method for microglial morphology analysis.

    Science.gov (United States)

    Verdonk, Franck; Roux, Pascal; Flamant, Patricia; Fiette, Laurence; Bozza, Fernando A; Simard, Sébastien; Lemaire, Marc; Plaud, Benoit; Shorte, Spencer L; Sharshar, Tarek; Chrétien, Fabrice; Danckaert, Anne

    2016-06-17

    Microglial cells are tissue-resident macrophages of the central nervous system. They are extremely dynamic, sensitive to their microenvironment and present a characteristic complex and heterogeneous morphology and distribution within the brain tissue. Many experimental clues highlight a strong link between their morphology and their function in response to aggression. However, due to their complex "dendritic-like" aspect that constitutes the major pool of murine microglial cells and their dense network, precise and powerful morphological studies are not easy to realize and complicate correlation with molecular or clinical parameters. Using the knock-in mouse model CX3CR1(GFP/+), we developed a 3D automated confocal tissue imaging system coupled with morphological modelling of many thousands of microglial cells revealing precise and quantitative assessment of major cell features: cell density, cell body area, cytoplasm area and number of primary, secondary and tertiary processes. We determined two morphological criteria that are the complexity index (CI) and the covered environment area (CEA) allowing an innovative approach lying in (i) an accurate and objective study of morphological changes in healthy or pathological condition, (ii) an in situ mapping of the microglial distribution in different neuroanatomical regions and (iii) a study of the clustering of numerous cells, allowing us to discriminate different sub-populations. Our results on more than 20,000 cells by condition confirm at baseline a regional heterogeneity of the microglial distribution and phenotype that persists after induction of neuroinflammation by systemic injection of lipopolysaccharide (LPS). Using clustering analysis, we highlight that, at resting state, microglial cells are distributed in four microglial sub-populations defined by their CI and CEA with a regional pattern and a specific behaviour after challenge. Our results counteract the classical view of a homogenous regional resting

  6. A new criterion of photostimulated luminescence (PSL) method to detect irradiated traditional Chinese medicinal herbs

    International Nuclear Information System (INIS)

    Zhang, Liwen; Lin, Tong; Jiang, Yingqiao; Bi, Fujun

    2013-01-01

    This work used a new criterion to analyze 162 varieties (222 batches) of traditional Chinese medicinal herbs based on the European Standard EN 13751 (2009. Foodstuffs—Detection of Irradiated Food Using Photostimulated Luminescence. European Committee for Standardization, Brussels, Belgium). The characteristics of PSL signals are described, and a new criterion is established. Compared to EN 13751, the new criterion uses clearer definition to evaluate instead of the ambiguous descriptions in EN Standard, such as “much greater than” and “within the same order of magnitude”. Moreover, the accuracy of the new criterion is as good as or better than EN Standard in regard to classifying irradiated and non-irradiated traditional Chinese medicinal herbs. It can help to avoid false positive result when a non-irradiated herb got a screening PSL measurement above 5000 counts/60 s. This new criterion of photostimulated luminescence method can be applied to identify the irradiation status of traditional Chinese medicinal herbs, even if the medicinal herbs were irradiated at a low dose (0.3 kGy) or stored in the dark at room temperature for 24 months after the irradiation treatment. - Highlights: • Clearer evaluation criterion instead of the ambiguous descriptions in EN 13751. • Accuracy satisfied. • Large sample size provides outstanding representativeness. • Systematical evaluation on PSL method

  7. Web-based versus traditional lecture: are they equally effective as a flexible bronchoscopy teaching method?

    Science.gov (United States)

    Mata, Caio Augusto Sterse; Ota, Luiz Hirotoshi; Suzuki, Iunis; Telles, Adriana; Miotto, Andre; Leão, Luiz Eduardo Vilaça

    2012-01-01

    This study compares the traditional live lecture to a web-based approach in the teaching of bronchoscopy and evaluates the positive and negative aspects of both methods. We developed a web-based bronchoscopy curriculum, which integrates texts, images and animations. It was applied to first-year interns, who were later administered a multiple-choice test. Another group of eight first-year interns received the traditional teaching method and the same test. The two groups were compared using the Student's t-test. The mean scores (± SD) of students who used the website were 14.63 ± 1.41 (range 13-17). The test scores of the other group had the same range, with a mean score of 14.75 ± 1. The Student's t-test showed no difference between the test results. The common positive point noted was the presence of multimedia content. The web group cited as positive the ability to review the pages, and the other one the role of the teacher. Web-based bronchoscopy education showed results similar to the traditional live lecture in effectiveness.

  8. Correction for dispersion and Coulombic interactions in molecular clusters with density functional derived methods: Application to polycyclic aromatic hydrocarbon clusters

    Science.gov (United States)

    Rapacioli, Mathias; Spiegelman, Fernand; Talbi, Dahbia; Mineva, Tzonka; Goursot, Annick; Heine, Thomas; Seifert, Gotthard

    2009-06-01

    The density functional based tight binding (DFTB) is a semiempirical method derived from the density functional theory (DFT). It inherits therefore its problems in treating van der Waals clusters. A major error comes from dispersion forces, which are poorly described by commonly used DFT functionals, but which can be accounted for by an a posteriori treatment DFT-D. This correction is used for DFTB. The self-consistent charge (SCC) DFTB is built on Mulliken charges which are known to give a poor representation of Coulombic intermolecular potential. We propose to calculate this potential using the class IV/charge model 3 definition of atomic charges. The self-consistent calculation of these charges is introduced in the SCC procedure and corresponding nuclear forces are derived. Benzene dimer is then studied as a benchmark system with this corrected DFTB (c-DFTB-D) method, but also, for comparison, with the DFT-D. Both methods give similar results and are in agreement with references calculations (CCSD(T) and symmetry adapted perturbation theory) calculations. As a first application, pyrene dimer is studied with the c-DFTB-D and DFT-D methods. For coronene clusters, only the c-DFTB-D approach is used, which finds the sandwich configurations to be more stable than the T-shaped ones.

  9. Quantification methods of Black Carbon: Comparison of Rock-Eval analysis with traditional methods

    NARCIS (Netherlands)

    Poot, A.; Quik, J.T.K.; Veld, H.; Koelmans, A.A.

    2009-01-01

    Black Carbon (BC) quantification methods are reviewed, including new Rock-Eval 6 data on BC reference materials. BC has been reported to have major impacts on climate, human health and environmental quality. Especially for risk assessment of persistent organic pollutants (POPs) it is important to

  10. Novel Clustering Method Based on K-Medoids and Mobility Metric

    Directory of Open Access Journals (Sweden)

    Y. Hamzaoui

    2018-06-01

    Full Text Available The structure and constraint of MANETS influence negatively the performance of QoS, moreover the main routing protocols proposed generally operate in flat routing. Hence, this structure gives the bad results of QoS when the network becomes larger and denser. To solve this problem we use one of the most popular methods named clustering. The present paper comes within the frameworks of research to improve the QoS in MANETs. In this paper we propose a new algorithm of clustering based on the new mobility metric and K-Medoid to distribute the nodes into several clusters. Intuitively our algorithm can give good results in terms of stability of the cluster, and can also extend life time of cluster head.

  11. A simple and fast method to determine the parameters for fuzzy c-means cluster analysis

    DEFF Research Database (Denmark)

    Schwämmle, Veit; Jensen, Ole Nørregaard

    2010-01-01

    MOTIVATION: Fuzzy c-means clustering is widely used to identify cluster structures in high-dimensional datasets, such as those obtained in DNA microarray and quantitative proteomics experiments. One of its main limitations is the lack of a computationally fast method to set optimal values...... of algorithm parameters. Wrong parameter values may either lead to the inclusion of purely random fluctuations in the results or ignore potentially important data. The optimal solution has parameter values for which the clustering does not yield any results for a purely random dataset but which detects cluster...... formation with maximum resolution on the edge of randomness. RESULTS: Estimation of the optimal parameter values is achieved by evaluation of the results of the clustering procedure applied to randomized datasets. In this case, the optimal value of the fuzzifier follows common rules that depend only...

  12. Study on the traditional pattern retrieval method of minorities in Gansu province

    Science.gov (United States)

    Zheng, Gang; Wang, Beizhan; Sun, Yuchun; Xu, Jin

    2018-03-01

    The traditional patterns of ethnic minorities in gansu province are ethnic arts with strong ethnic characteristics. It is the crystallization of the hard work and wisdom of minority nationalities in gansu province. Unique traditional patterns of ethnic minorities in Gansu province with rich ethnic folk arts, is the crystallization of geographical environment in Gansu minority diligence and wisdom. By using the Surf feature point identification algorithm, the feature point extractor in OpenCV is used to extract the feature points. And the feature points are applied to compare the pattern features to find patterns similar to the artistic features. The application of this method can quickly or efficiently extract pattern information in a database.

  13. A semi-supervised method to detect seismic random noise with fuzzy GK clustering

    International Nuclear Information System (INIS)

    Hashemi, Hosein; Javaherian, Abdolrahim; Babuska, Robert

    2008-01-01

    We present a new method to detect random noise in seismic data using fuzzy Gustafson–Kessel (GK) clustering. First, using an adaptive distance norm, a matrix is constructed from the observed seismic amplitudes. The next step is to find centres of ellipsoidal clusters and construct a partition matrix which determines the soft decision boundaries between seismic events and random noise. The GK algorithm updates the cluster centres in order to iteratively minimize the cluster variance. Multiplication of the fuzzy membership function with values of each sample yields new sections; we name them 'clustered sections'. The seismic amplitude values of the clustered sections are given in a way to decrease the level of noise in the original noisy seismic input. In pre-stack data, it is essential to study the clustered sections in a f–k domain; finding the quantitative index for weighting the post-stack data needs a similar approach. Using the knowledge of a human specialist together with the fuzzy unsupervised clustering, the method is a semi-supervised random noise detection. The efficiency of this method is investigated on synthetic and real seismic data for both pre- and post-stack data. The results show a significant improvement of the input noisy sections without harming the important amplitude and phase information of the original data. The procedure for finding the final weights of each clustered section should be carefully done in order to keep almost all the evident seismic amplitudes in the output section. The method interactively uses the knowledge of the seismic specialist in detecting the noise

  14. Soft-tissues Image Processing: Comparison of Traditional Segmentation Methods with 2D active Contour Methods

    Czech Academy of Sciences Publication Activity Database

    Mikulka, J.; Gescheidtová, E.; Bartušek, Karel

    2012-01-01

    Roč. 12, č. 4 (2012), s. 153-161 ISSN 1335-8871 R&D Projects: GA ČR GAP102/11/0318; GA ČR GAP102/12/1104; GA MŠk ED0017/01/01 Institutional support: RVO:68081731 Keywords : Medical image processing * image segmentation * liver tumor * temporomandibular joint disc * watershed method Subject RIV: JA - Electronics ; Optoelectronics, Electrical Engineering Impact factor: 1.233, year: 2012

  15. Evaluating the Effectiveness of Traditional Training Methods in Non-Traditional Training Programs for Adult Learners through a Pre-Test/Post-Test Comparison of Food Safety Knowledge

    Science.gov (United States)

    Dodd, Caleb D.; Burris, Scott; Fraze, Steve; Doerfert, David; McCulloch, Abigail

    2013-01-01

    The incorporation of hot and cold food bars into grocery stores in an effort to capture a portion of the home meal replacement industry is presenting new challenges for retail food establishments. To ensure retail success and customer safety, employees need to be educated in food safety practices. Traditional methods of training are not meeting…

  16. Kinetic methods for measuring the temperature of clusters and nanoparticles in molecular beams

    International Nuclear Information System (INIS)

    Makarov, Grigorii N

    2011-01-01

    The temperature (internal energy) of clusters and nanoparticles is an important physical parameter which affects many of their properties and the character of processes they are involved in. At the same time, determining the temperature of free clusters and nanoparticles in molecular beams is a rather complicated problem because the temperature of small particles depends on their size. In this paper, recently developed kinetic methods for measuring the temperature of clusters and nanoparticles in molecular beams are reviewed. The definition of temperature in the present context is given, and how the temperature affects the properties of and the processes involving the particles is discussed. The temperature behavior of clusters and nanoparticles near a phase transition point is analyzed. Early methods for measuring the temperature of large clusters are briefly described. It is shown that, compared to other methods, new kinetic methods are more universal and applicable for determining the temperature of clusters and nanoparticles of practically any size and composition. The future development and applications of these methods are outlined. (reviews of topical problems)

  17. Comparison of Bayesian clustering and edge detection methods for inferring boundaries in landscape genetics

    Science.gov (United States)

    Safner, T.; Miller, M.P.; McRae, B.H.; Fortin, M.-J.; Manel, S.

    2011-01-01

    Recently, techniques available for identifying clusters of individuals or boundaries between clusters using genetic data from natural populations have expanded rapidly. Consequently, there is a need to evaluate these different techniques. We used spatially-explicit simulation models to compare three spatial Bayesian clustering programs and two edge detection methods. Spatially-structured populations were simulated where a continuous population was subdivided by barriers. We evaluated the ability of each method to correctly identify boundary locations while varying: (i) time after divergence, (ii) strength of isolation by distance, (iii) level of genetic diversity, and (iv) amount of gene flow across barriers. To further evaluate the methods' effectiveness to detect genetic clusters in natural populations, we used previously published data on North American pumas and a European shrub. Our results show that with simulated and empirical data, the Bayesian spatial clustering algorithms outperformed direct edge detection methods. All methods incorrectly detected boundaries in the presence of strong patterns of isolation by distance. Based on this finding, we support the application of Bayesian spatial clustering algorithms for boundary detection in empirical datasets, with necessary tests for the influence of isolation by distance. ?? 2011 by the authors; licensee MDPI, Basel, Switzerland.

  18. Creating multithemed ecological regions for macroscale ecology: Testing a flexible, repeatable, and accessible clustering method

    Science.gov (United States)

    Cheruvelil, Kendra Spence; Yuan, Shuai; Webster, Katherine E.; Tan, Pang-Ning; Lapierre, Jean-Francois; Collins, Sarah M.; Fergus, C. Emi; Scott, Caren E.; Norton Henry, Emily; Soranno, Patricia A.; Filstrup, Christopher T.; Wagner, Tyler

    2017-01-01

    Understanding broad-scale ecological patterns and processes often involves accounting for regional-scale heterogeneity. A common way to do so is to include ecological regions in sampling schemes and empirical models. However, most existing ecological regions were developed for specific purposes, using a limited set of geospatial features and irreproducible methods. Our study purpose was to: (1) describe a method that takes advantage of recent computational advances and increased availability of regional and global data sets to create customizable and reproducible ecological regions, (2) make this algorithm available for use and modification by others studying different ecosystems, variables of interest, study extents, and macroscale ecology research questions, and (3) demonstrate the power of this approach for the research question—How well do these regions capture regional-scale variation in lake water quality? To achieve our purpose we: (1) used a spatially constrained spectral clustering algorithm that balances geospatial homogeneity and region contiguity to create ecological regions using multiple terrestrial, climatic, and freshwater geospatial data for 17 northeastern U.S. states (~1,800,000 km2); (2) identified which of the 52 geospatial features were most influential in creating the resulting 100 regions; and (3) tested the ability of these ecological regions to capture regional variation in water nutrients and clarity for ~6,000 lakes. We found that: (1) a combination of terrestrial, climatic, and freshwater geospatial features influenced region creation, suggesting that the oft-ignored freshwater landscape provides novel information on landscape variability not captured by traditionally used climate and terrestrial metrics; and (2) the delineated regions captured macroscale heterogeneity in ecosystem properties not included in region delineation—approximately 40% of the variation in total phosphorus and water clarity among lakes was at the regional

  19. Vocal Affect Recognition and Psychopathy: Converging Findings Across Traditional and Cluster Analytic Approaches to Assessing the Construct

    Science.gov (United States)

    Bagley, Amy D.; Abramowitz, Carolyn S.; Kosson, David S.

    2010-01-01

    Deficits in emotion processing have been widely reported to be central to psychopathy. However, few prior studies have examined vocal affect recognition in psychopaths, and these studies suffer from significant methodological limitations. Moreover, prior studies have yielded conflicting findings regarding the specificity of psychopaths’ affect recognition deficits. This study examined vocal affect recognition in 107 male inmates under conditions requiring isolated prosodic vs. semantic analysis of affective cues and compared subgroups of offenders identified via cluster analysis on vocal affect recognition. Psychopaths demonstrated deficits in vocal affect recognition under conditions requiring use of semantic cues and conditions requiring use of prosodic cues. Moreover, both primary and secondary psychopaths exhibited relatively similar emotional deficits in the semantic analysis condition compared to nonpsychopathic control participants. This study demonstrates that psychopaths’ vocal affect recognition deficits are not due to methodological limitations of previous studies and provides preliminary evidence that primary and secondary psychopaths exhibit generally similar deficits in vocal affect recognition. PMID:19413412

  20. Quality evaluation of fish and other seafood by traditional and nondestructive instrumental methods: Advantages and limitations.

    Science.gov (United States)

    Hassoun, Abdo; Karoui, Romdhane

    2017-06-13

    Although being one of the most vulnerable and perishable products, fish and other seafoods provide a wide range of health-promoting compounds. Recently, the growing interest of consumers in food quality and safety issues has contributed to the increasing demand for sensitive and rapid analytical technologies. Several traditional physicochemical, textural, sensory, and electrical methods have been used to evaluate freshness and authentication of fish and other seafood products. Despite the importance of these standard methods, they are expensive and time-consuming, and often susceptible to large sources of variation. Recently, spectroscopic methods and other emerging techniques have shown great potential due to speed of analysis, minimal sample preparation, high repeatability, low cost, and, most of all, the fact that these techniques are noninvasive and nondestructive and, therefore, could be applied to any online monitoring system. This review describes firstly and briefly the basic principles of multivariate data analysis, followed by the most commonly traditional methods used for the determination of the freshness and authenticity of fish and other seafood products. A special focus is put on the use of rapid and nondestructive techniques (spectroscopic techniques and instrumental sensors) to address several issues related to the quality of these products. Moreover, the advantages and limitations of each technique are reviewed and some perspectives are also given.

  1. Neural networks and traditional time series methods: a synergistic combination in state economic forecasts.

    Science.gov (United States)

    Hansen, J V; Nelson, R D

    1997-01-01

    Ever since the initial planning for the 1997 Utah legislative session, neural-network forecasting techniques have provided valuable insights for analysts forecasting tax revenues. These revenue estimates are critically important since agency budgets, support for education, and improvements to infrastructure all depend on their accuracy. Underforecasting generates windfalls that concern taxpayers, whereas overforecasting produces budget shortfalls that cause inadequately funded commitments. The pattern finding ability of neural networks gives insightful and alternative views of the seasonal and cyclical components commonly found in economic time series data. Two applications of neural networks to revenue forecasting clearly demonstrate how these models complement traditional time series techniques. In the first, preoccupation with a potential downturn in the economy distracts analysis based on traditional time series methods so that it overlooks an emerging new phenomenon in the data. In this case, neural networks identify the new pattern that then allows modification of the time series models and finally gives more accurate forecasts. In the second application, data structure found by traditional statistical tools allows analysts to provide neural networks with important information that the networks then use to create more accurate models. In summary, for the Utah revenue outlook, the insights that result from a portfolio of forecasts that includes neural networks exceeds the understanding generated from strictly statistical forecasting techniques. In this case, the synergy clearly results in the whole of the portfolio of forecasts being more accurate than the sum of the individual parts.

  2. Comparison of prosthetic models produced by traditional and additive manufacturing methods.

    Science.gov (United States)

    Park, Jin-Young; Kim, Hae-Young; Kim, Ji-Hwan; Kim, Jae-Hong; Kim, Woong-Chul

    2015-08-01

    The purpose of this study was to verify the clinical-feasibility of additive manufacturing by comparing the accuracy of four different manufacturing methods for metal coping: the conventional lost wax technique (CLWT); subtractive methods with wax blank milling (WBM); and two additive methods, multi jet modeling (MJM), and micro-stereolithography (Micro-SLA). Thirty study models were created using an acrylic model with the maxillary upper right canine, first premolar, and first molar teeth. Based on the scan files from a non-contact blue light scanner (Identica; Medit Co. Ltd., Seoul, Korea), thirty cores were produced using the WBM, MJM, and Micro-SLA methods, respectively, and another thirty frameworks were produced using the CLWT method. To measure the marginal and internal gap, the silicone replica method was adopted, and the silicone images obtained were evaluated using a digital microscope (KH-7700; Hirox, Tokyo, Japan) at 140X magnification. Analyses were performed using two-way analysis of variance (ANOVA) and Tukey post hoc test (α=.05). The mean marginal gaps and internal gaps showed significant differences according to tooth type (Pmanufacturing method (Pmanufacturing methods were within a clinically allowable range, and, thus, the clinical use of additive manufacturing methods is acceptable as an alternative to the traditional lost wax-technique and subtractive manufacturing.

  3. Coconut oil extraction by the traditional Java method : An investigation of its potential application in aqueous Jatropha oil extraction

    NARCIS (Netherlands)

    Marasabessy, Ahmad; Moeis, Maelita R.; Sanders, Johan P. M.; Weusthuis, Ruud A.

    A traditional Java method of coconut oil extraction assisted by paddy crabs was investigated to find out if crabs or crab-derived components can be used to extract oil from Jatropha curcas seed kernels. Using the traditional Java method the addition of crab paste liberated 54% w w(-1) oil from

  4. An improved K-means clustering method for cDNA microarray image segmentation.

    Science.gov (United States)

    Wang, T N; Li, T J; Shao, G F; Wu, S X

    2015-07-14

    Microarray technology is a powerful tool for human genetic research and other biomedical applications. Numerous improvements to the standard K-means algorithm have been carried out to complete the image segmentation step. However, most of the previous studies classify the image into two clusters. In this paper, we propose a novel K-means algorithm, which first classifies the image into three clusters, and then one of the three clusters is divided as the background region and the other two clusters, as the foreground region. The proposed method was evaluated on six different data sets. The analyses of accuracy, efficiency, expression values, special gene spots, and noise images demonstrate the effectiveness of our method in improving the segmentation quality.

  5. Application Of WIMS Code To Calculation Kartini Reactor Parameters By Pin-Cell And Cluster Method

    International Nuclear Information System (INIS)

    Sumarsono, Bambang; Tjiptono, T.W.

    1996-01-01

    Analysis UZrH fuel element parameters calculation in Kartini Reactor by WIMS Code has been done. The analysis is done by pin cell and cluster method. The pin cell method is done as a function percent burn-up and by 8 group 3 region analysis and cluster method by 8 group 12 region analysis. From analysis and calculation resulted K ∼ = 1.3687 by pin cell method and K ∼ = 1.3162 by cluster method and so deviation is 3.83%. By pin cell analysis as a function percent burn-up at the percent burn-up greater than 59.50%, the multiplication factor is less than one (k ∼ < 1) it is mean that the fuel element reactivity is negative

  6. Complete Dentures Fabricated with CAD/CAM Technology and a Traditional Clinical Recording Method.

    Science.gov (United States)

    Janeva, Nadica; Kovacevska, Gordana; Janev, Edvard

    2017-10-15

    The introduction of computer-aided design/computer-aided manufacturing (CAD/CAM) technology into complete denture (CD) fabrication ushered in a new era in removable prosthodontics. Commercially available CAD/CAM denture systems are expected to improve upon the disadvantages associated with conventional fabrication. The purpose of this report is to present the workflow involved in fabricating a CD with a traditional clinical recording method and CAD/CAM technology and to summarize the advantages to the dental practitioner and the patient.

  7. Combining traditional dietary assessment methods with novel metabolomics techniques: present efforts by the Food Biomarker Alliance

    DEFF Research Database (Denmark)

    Brouwer-Brolsma, Elske M; Brennan, Lorraine; Drevon, Christian A

    2017-01-01

    food metabolomics techniques that allow the quantification of up to thousands of metabolites simultaneously, which may be applied in intervention and observational studies. As biomarkers are often influenced by various other factors than the food under investigation, FoodBAll developed a food intake...... in these metabolomics studies, knowledge about available electronic metabolomics resources is necessary and further developments of these resources are essential. Ultimately, present efforts in this research area aim to advance quality control of traditional dietary assessment methods, advance compliance evaluation...

  8. Panel presentation: Should some type of incentive regulation replace traditional methods for LDC's?

    International Nuclear Information System (INIS)

    Richard, O.G.

    1992-01-01

    This paper discusses the problems with existing fixed-rate price regulation and how a deregulation of both the pipeline and gas utility companies are needed to enhance competition. The paper suggests alternative methods to traditional regulation which include a financial incentive package which allows or encourages utilities to make investments in more efficient energy management, to improve load factors to balance the energy demands between industrial and residential users, and reward purchases of gas supplies that out-perform an agreed upon level of rates of a cost index. Other incentive programs are proposed by the author with a relative detailed discussion on each topic

  9. Assessing Health Promotion Interventions: Limitations of Traditional Research Methods in Community-Based Studies.

    Science.gov (United States)

    Dressel, Anne; Schneider, Robert; DeNomie, Melissa; Kusch, Jennifer; Welch, Whitney; Sosa, Mirtha; Yeldell, Sally; Maida, Tatiana; Wineberg, Jessica; Holt, Keith; Bernstein, Rebecca

    2017-09-01

    Most low-income Americans fail to meet physical activity recommendations. Inactivity and poor diet contribute to obesity, a risk factor for multiple chronic diseases. Health promotion activities have the potential to improve health outcomes for low-income populations. Measuring the effectiveness of these activities, however, can be challenging in community settings. A "Biking for Health" study tested the impact of a bicycling intervention on overweight or obese low-income Latino and African American adults to reduce barriers to cycling and increase physical activity and fitness. A randomized controlled trial was conducted in Milwaukee, Wisconsin, in summer 2015. A 12-week bicycling intervention was implemented at two sites with low-income, overweight, or obese Latino and African American adults. We found that randomized controlled trial methodology was suboptimal for use in this small pilot study and that it negatively affected participation. More discussion is needed about the effectiveness of using traditional research methods in community settings to assess the effectiveness of health promotion interventions. Modifications or alternative methods may yield better results. The aim of this article is to discuss the effectiveness and feasibility of using traditional research methods to assess health promotion interventions in community-based settings.

  10. ITPI: Initial Transcription Process-Based Identification Method of Bioactive Components in Traditional Chinese Medicine Formula

    Directory of Open Access Journals (Sweden)

    Baixia Zhang

    2016-01-01

    Full Text Available Identification of bioactive components is an important area of research in traditional Chinese medicine (TCM formula. The reported identification methods only consider the interaction between the components and the target proteins, which is not sufficient to explain the influence of TCM on the gene expression. Here, we propose the Initial Transcription Process-based Identification (ITPI method for the discovery of bioactive components that influence transcription factors (TFs. In this method, genome-wide chip detection technology was used to identify differentially expressed genes (DEGs. The TFs of DEGs were derived from GeneCards. The components influencing the TFs were derived from STITCH. The bioactive components in the formula were identified by evaluating the molecular similarity between the components in formula and the components that influence the TF of DEGs. Using the formula of Tian-Zhu-San (TZS as an example, the reliability and limitation of ITPI were examined and 16 bioactive components that influence TFs were identified.

  11. The use of different clustering methods in the evaluation of genetic diversity in upland cotton

    Directory of Open Access Journals (Sweden)

    Laíse Ferreira de Araújo

    Full Text Available The continuous development and evaluation of new genotypes through crop breeding is essential in order to obtain new cultivars. The objective of this work was to evaluate the genetic divergences between cultivars of upland cotton (Gossypium hirsutum L. using the agronomic and technological characteristics of the fibre, in order to select superior parent plants. The experiment was set up during 2010 at the Federal University of Ceará in Fortaleza, Ceará, Brazil. Eleven cultivars of upland cotton were used in an experimental design of randomised blocks with three replications. In order to evaluate the genetic diversity among cultivars, the generalised Mahalanobis distance matrix was calculated, with cluster analysis then being applied, employing various methods: single linkage, Ward, complete linkage, median, average linkage within a cluster and average linkage between clusters. Genetic variability exists among the evaluated genotypes. The most consistant clustering method was that employing average linkage between clusters. Among the characteristics assessed, mean boll weight presented the highest contribution to genetic diversity, followed by elongation at rupture. Employing the method of mean linkage between clusters, the cultivars with greater genetic divergence were BRS Acacia and LD Frego; those of greater similarity were BRS Itaúba and BRS Araripe.

  12. A Spatial Shape Constrained Clustering Method for Mammographic Mass Segmentation

    Directory of Open Access Journals (Sweden)

    Jian-Yong Lou

    2015-01-01

    error of 7.18% for well-defined masses (or 8.06% for ill-defined masses was obtained by using DACF on MiniMIAS database, with 5.86% (or 5.55% and 6.14% (or 5.27% improvements as compared to the standard DA and fuzzy c-means methods.

  13. Robustness of serial clustering of extratropical cyclones to the choice of tracking method

    Directory of Open Access Journals (Sweden)

    Joaquim G. Pinto

    2016-07-01

    Full Text Available Cyclone clusters are a frequent synoptic feature in the Euro-Atlantic area. Recent studies have shown that serial clustering of cyclones generally occurs on both flanks and downstream regions of the North Atlantic storm track, while cyclones tend to occur more regulary on the western side of the North Atlantic basin near Newfoundland. This study explores the sensitivity of serial clustering to the choice of cyclone tracking method using cyclone track data from 15 methods derived from ERA-Interim data (1979–2010. Clustering is estimated by the dispersion (ratio of variance to mean of winter [December – February (DJF] cyclone passages near each grid point over the Euro-Atlantic area. The mean number of cyclone counts and their variance are compared between methods, revealing considerable differences, particularly for the latter. Results show that all different tracking methods qualitatively capture similar large-scale spatial patterns of underdispersion and overdispersion over the study region. The quantitative differences can primarily be attributed to the differences in the variance of cyclone counts between the methods. Nevertheless, overdispersion is statistically significant for almost all methods over parts of the eastern North Atlantic and Western Europe, and is therefore considered as a robust feature. The influence of the North Atlantic Oscillation (NAO on cyclone clustering displays a similar pattern for all tracking methods, with one maximum near Iceland and another between the Azores and Iberia. The differences in variance between methods are not related with different sensitivities to the NAO, which can account to over 50% of the clustering in some regions. We conclude that the general features of underdispersion and overdispersion of extratropical cyclones over the North Atlantic and Western Europe are robust to the choice of tracking method. The same is true for the influence of the NAO on cyclone dispersion.

  14. An effective trust-based recommendation method using a novel graph clustering algorithm

    Science.gov (United States)

    Moradi, Parham; Ahmadian, Sajad; Akhlaghian, Fardin

    2015-10-01

    Recommender systems are programs that aim to provide personalized recommendations to users for specific items (e.g. music, books) in online sharing communities or on e-commerce sites. Collaborative filtering methods are important and widely accepted types of recommender systems that generate recommendations based on the ratings of like-minded users. On the other hand, these systems confront several inherent issues such as data sparsity and cold start problems, caused by fewer ratings against the unknowns that need to be predicted. Incorporating trust information into the collaborative filtering systems is an attractive approach to resolve these problems. In this paper, we present a model-based collaborative filtering method by applying a novel graph clustering algorithm and also considering trust statements. In the proposed method first of all, the problem space is represented as a graph and then a sparsest subgraph finding algorithm is applied on the graph to find the initial cluster centers. Then, the proposed graph clustering algorithm is performed to obtain the appropriate users/items clusters. Finally, the identified clusters are used as a set of neighbors to recommend unseen items to the current active user. Experimental results based on three real-world datasets demonstrate that the proposed method outperforms several state-of-the-art recommender system methods.

  15. MHCcluster, a method for functional clustering of MHC molecules

    DEFF Research Database (Denmark)

    Thomsen, Martin Christen Frølund; Lundegaard, Claus; Buus, Søren

    2013-01-01

    The identification of peptides binding to major histocompatibility complexes (MHC) is a critical step in the understanding of T cell immune responses. The human MHC genomic region (HLA) is extremely polymorphic comprising several thousand alleles, many encoding a distinct molecule. The potentially...... binding specificity. The method has a flexible web interface that allows the user to include any MHC of interest in the analysis. The output consists of a static heat map and graphical tree-based visualizations of the functional relationship between MHC variants and a dynamic TreeViewer interface where...

  16. Comparative analysis to determine asphalt density and content, using nuclear and traditional methods

    International Nuclear Information System (INIS)

    Margffoy S, F.R.; Robayo S, A.M.

    1989-01-01

    Quality control for flex pavement construction in Colombia for asphaltic mix, as well as for granular and granular sub base layers is made by means of methods that does not guarantee the quality of the job, due to the difficult execution of tests, which impede more to be done or due to inherent problems of the test process. Thanks to the inherent characteristics and advantages of nuclear techniques, those become the optimal alternative to this quality control job. The present research project has been developed with the objective of justifying the use of new technologies applied to road construction; making a comparative analysis between traditional methods used in our country and nuclear techniques that have been using in United States with great success in quality control in road construction

  17. Countermeasures for electrolytic corrosion - Part I: Traditional methods and their problems

    International Nuclear Information System (INIS)

    Ha, Yoon-Cheol; Kim, Dae-Kyeong; Bae, Jeong-Hyo; Ha, Tae-Hyun; Lee, Hyun-Goo

    2004-01-01

    When an underground pipeline runs parallel with DC-powered railways, it suffers from electrolytic corrosion caused by the stray current leaked from the railway negative returns. Perforation due to the electrolytic corrosion may bring about large-scale accidents even in cathodically protected systems. Traditionally, bonding methods such as direct drainage, polarized drainage and forced drainage have been used in order to mitigate the damage on pipelines. In particular, the forced drainage method is widely adopted in Korea. In this paper, we report the real-time measurement data of the pipe-to-soil potential variation in the presence and absence of the IR compensation. The drainage current variation was also measured using the Stray Current Logger developed. By analysing them, the problems of current countermeasures for electrolytic corrosion are discussed. (authors)

  18. Countermeasures for electrolytic corrosion - Part I: Traditional methods and their problems

    Energy Technology Data Exchange (ETDEWEB)

    Ha, Yoon-Cheol; Kim, Dae-Kyeong; Bae, Jeong-Hyo; Ha, Tae-Hyun; Lee, Hyun-Goo [Underground Systems Group, Korea Electrotechnology Research Institute, 28-1 Sungju-dong, Changwon (Korea, Republic of)

    2004-07-01

    When an underground pipeline runs parallel with DC-powered railways, it suffers from electrolytic corrosion caused by the stray current leaked from the railway negative returns. Perforation due to the electrolytic corrosion may bring about large-scale accidents even in cathodically protected systems. Traditionally, bonding methods such as direct drainage, polarized drainage and forced drainage have been used in order to mitigate the damage on pipelines. In particular, the forced drainage method is widely adopted in Korea. In this paper, we report the real-time measurement data of the pipe-to-soil potential variation in the presence and absence of the IR compensation. The drainage current variation was also measured using the Stray Current Logger developed. By analysing them, the problems of current countermeasures for electrolytic corrosion are discussed. (authors)

  19. Reliability studies of diagnostic methods in Indian traditional Ayurveda medicine: An overview

    Science.gov (United States)

    Kurande, Vrinda Hitendra; Waagepetersen, Rasmus; Toft, Egon; Prasad, Ramjee

    2013-01-01

    Recently, a need to develop supportive new scientific evidence for contemporary Ayurveda has emerged. One of the research objectives is an assessment of the reliability of diagnoses and treatment. Reliability is a quantitative measure of consistency. It is a crucial issue in classification (such as prakriti classification), method development (pulse diagnosis), quality assurance for diagnosis and treatment and in the conduct of clinical studies. Several reliability studies are conducted in western medicine. The investigation of the reliability of traditional Chinese, Japanese and Sasang medicine diagnoses is in the formative stage. However, reliability studies in Ayurveda are in the preliminary stage. In this paper, examples are provided to illustrate relevant concepts of reliability studies of diagnostic methods and their implication in practice, education, and training. An introduction to reliability estimates and different study designs and statistical analysis is given for future studies in Ayurveda. PMID:23930037

  20. Bioassessment of a Drinking Water Reservoir Using Plankton: High Throughput Sequencing vs. Traditional Morphological Method

    Directory of Open Access Journals (Sweden)

    Wanli Gao

    2018-01-01

    Full Text Available Drinking water safety is increasingly perceived as one of the top global environmental issues. Plankton has been commonly used as a bioindicator for water quality in lakes and reservoirs. Recently, DNA sequencing technology has been applied to bioassessment. In this study, we compared the effectiveness of the 16S and 18S rRNA high throughput sequencing method (HTS and the traditional optical microscopy method (TOM in the bioassessment of drinking water quality. Five stations reflecting different habitats and hydrological conditions in Danjiangkou Reservoir, one of the largest drinking water reservoirs in Asia, were sampled May 2016. Non-metric multi-dimensional scaling (NMDS analysis showed that plankton assemblages varied among the stations and the spatial patterns revealed by the two methods were consistent. The correlation between TOM and HTS in a symmetric Procrustes analysis was 0.61, revealing overall good concordance between the two methods. Procrustes analysis also showed that site-specific differences between the two methods varied among the stations. Station Heijizui (H, a site heavily influenced by two tributaries, had the largest difference while station Qushou (Q, a confluence site close to the outlet dam, had the smallest difference between the two methods. Our results show that DNA sequencing has the potential to provide consistent identification of taxa, and reliable bioassessment in a long-term biomonitoring and assessment program for drinking water reservoirs.

  1. Pseudo-potential method for taking into account the Pauli principle in cluster systems

    International Nuclear Information System (INIS)

    Krasnopol'skii, V.M.; Kukulin, V.I.

    1975-01-01

    In order to take account of the Pauli principle in cluster systems (such as 3α, α + α + n) a convenient method of renormalization of the cluster-cluster deep attractive potentials with forbidden states is suggested. The renormalization consists of adding projectors upon the occupied states with an infinite coupling constant to the initial deep potential which means that we pass to pseudo-potentials. The pseudo-potential approach in projecting upon the noneigenstates is shown to be equivalent to the orthogonality condition model of Saito et al. The orthogonality of the many-particle wave function to the forbidden states of each two-cluster sub-system is clearly demonstrated

  2. Test computations on the dynamical evolution of star clusters. [Fluid dynamic method

    Energy Technology Data Exchange (ETDEWEB)

    Angeletti, L; Giannone, P. (Rome Univ. (Italy))

    1977-01-01

    Test calculations have been carried out on the evolution of star clusters using the fluid-dynamical method devised by Larson (1970). Large systems of stars have been considered with specific concern with globular clusters. With reference to the analogous 'standard' model by Larson, the influence of varying in turn the various free parameters (cluster mass, star mass, tidal radius, mass concentration of the initial model) has been studied for the results. Furthermore, the partial release of some simplifying assumptions with regard to the relaxation time and distribution of the 'target' stars has been considered. The change of the structural properties is discussed, and the variation of the evolutionary time scale is outlined. An indicative agreement of the results obtained here with structural properties of globular clusters as deduced from previous theoretical models is pointed out.

  3. The resonating group method three cluster approach to the ground state 9 Li nucleus structure

    International Nuclear Information System (INIS)

    Filippov, G.F.; Pozdnyakov, Yu.A.; Terenetsky, K.O.; Verbitsky, V.P.

    1994-01-01

    The three-cluster approach for light atomic nuclei is formulated in frame of the algebraic version of resonating group method. Overlap integral and Hamiltonian matrix elements on generating functions are obtained for 9 Li nucleus. All permissible by Pauli principle 9 Li different cluster nucleon permutations were taken into account in the calculations. The results obtained can be easily generalised on any three-cluster system up to 12 C. Matrix elements obtained in the work were used in the variational calculations of the ground state energetic and geometric 9 Li characteristics. It is shown that 9 Li ground state is not adequate to the shell model limit and has pronounced three-cluster structure. (author). 16 refs., 4 tab., 2 figs

  4. A New Soft Computing Method for K-Harmonic Means Clustering.

    Science.gov (United States)

    Yeh, Wei-Chang; Jiang, Yunzhi; Chen, Yee-Fen; Chen, Zhe

    2016-01-01

    The K-harmonic means clustering algorithm (KHM) is a new clustering method used to group data such that the sum of the harmonic averages of the distances between each entity and all cluster centroids is minimized. Because it is less sensitive to initialization than K-means (KM), many researchers have recently been attracted to studying KHM. In this study, the proposed iSSO-KHM is based on an improved simplified swarm optimization (iSSO) and integrates a variable neighborhood search (VNS) for KHM clustering. As evidence of the utility of the proposed iSSO-KHM, we present extensive computational results on eight benchmark problems. From the computational results, the comparison appears to support the superiority of the proposed iSSO-KHM over previously developed algorithms for all experiments in the literature.

  5. Grey Wolf Optimizer Based on Powell Local Optimization Method for Clustering Analysis

    Directory of Open Access Journals (Sweden)

    Sen Zhang

    2015-01-01

    Full Text Available One heuristic evolutionary algorithm recently proposed is the grey wolf optimizer (GWO, inspired by the leadership hierarchy and hunting mechanism of grey wolves in nature. This paper presents an extended GWO algorithm based on Powell local optimization method, and we call it PGWO. PGWO algorithm significantly improves the original GWO in solving complex optimization problems. Clustering is a popular data analysis and data mining technique. Hence, the PGWO could be applied in solving clustering problems. In this study, first the PGWO algorithm is tested on seven benchmark functions. Second, the PGWO algorithm is used for data clustering on nine data sets. Compared to other state-of-the-art evolutionary algorithms, the results of benchmark and data clustering demonstrate the superior performance of PGWO algorithm.

  6. A comparison of two prospective risk analysis methods: Traditional FMEA and a modified healthcare FMEA.

    Science.gov (United States)

    Rah, Jeong-Eun; Manger, Ryan P; Yock, Adam D; Kim, Gwe-Ya

    2016-12-01

    To examine the abilities of a traditional failure mode and effects analysis (FMEA) and modified healthcare FMEA (m-HFMEA) scoring methods by comparing the degree of congruence in identifying high risk failures. The authors applied two prospective methods of the quality management to surface image guided, linac-based radiosurgery (SIG-RS). For the traditional FMEA, decisions on how to improve an operation were based on the risk priority number (RPN). The RPN is a product of three indices: occurrence, severity, and detectability. The m-HFMEA approach utilized two indices, severity and frequency. A risk inventory matrix was divided into four categories: very low, low, high, and very high. For high risk events, an additional evaluation was performed. Based upon the criticality of the process, it was decided if additional safety measures were needed and what they comprise. The two methods were independently compared to determine if the results and rated risks matched. The authors' results showed an agreement of 85% between FMEA and m-HFMEA approaches for top 20 risks of SIG-RS-specific failure modes. The main differences between the two approaches were the distribution of the values and the observation that failure modes (52, 54, 154) with high m-HFMEA scores do not necessarily have high FMEA-RPN scores. In the m-HFMEA analysis, when the risk score is determined, the basis of the established HFMEA Decision Tree™ or the failure mode should be more thoroughly investigated. m-HFMEA is inductive because it requires the identification of the consequences from causes, and semi-quantitative since it allows the prioritization of high risks and mitigation measures. It is therefore a useful tool for the prospective risk analysis method to radiotherapy.

  7. Comparison of Satellite Surveying to Traditional Surveying Methods for the Resources Industry

    Science.gov (United States)

    Osborne, B. P.; Osborne, V. J.; Kruger, M. L.

    Modern ground-based survey methods involve detailed survey, which provides three-space co-ordinates for surveyed points, to a high level of accuracy. The instruments are operated by surveyors, who process the raw results to create survey location maps for the subject of the survey. Such surveys are conducted for a location or region and referenced to the earth global co- ordinate system with global positioning system (GPS) positioning. Due to this referencing the survey is only as accurate as the GPS reference system. Satellite survey remote sensing utilise satellite imagery which have been processed using commercial geographic information system software. Three-space co-ordinate maps are generated, with an accuracy determined by the datum position accuracy and optical resolution of the satellite platform.This paper presents a case study, which compares topographic surveying undertaken by traditional survey methods with satellite surveying, for the same location. The purpose of this study is to assess the viability of satellite remote sensing for surveying in the resources industry. The case study involves a topographic survey of a dune field for a prospective mining project area in Pakistan. This site has been surveyed using modern surveying techniques and the results are compared to a satellite survey performed on the same area.Analysis of the results from traditional survey and from the satellite survey involved a comparison of the derived spatial co- ordinates from each method. In addition, comparisons have been made of costs and turnaround time for both methods.The results of this application of remote sensing is of particular interest for survey in areas with remote and extreme environments, weather extremes, political unrest, poor travel links, which are commonly associated with mining projects. Such areas frequently suffer language barriers, poor onsite technical support and resources.

  8. Developing a Clustering-Based Empirical Bayes Analysis Method for Hotspot Identification

    Directory of Open Access Journals (Sweden)

    Yajie Zou

    2017-01-01

    Full Text Available Hotspot identification (HSID is a critical part of network-wide safety evaluations. Typical methods for ranking sites are often rooted in using the Empirical Bayes (EB method to estimate safety from both observed crash records and predicted crash frequency based on similar sites. The performance of the EB method is highly related to the selection of a reference group of sites (i.e., roadway segments or intersections similar to the target site from which safety performance functions (SPF used to predict crash frequency will be developed. As crash data often contain underlying heterogeneity that, in essence, can make them appear to be generated from distinct subpopulations, methods are needed to select similar sites in a principled manner. To overcome this possible heterogeneity problem, EB-based HSID methods that use common clustering methodologies (e.g., mixture models, K-means, and hierarchical clustering to select “similar” sites for building SPFs are developed. Performance of the clustering-based EB methods is then compared using real crash data. Here, HSID results, when computed on Texas undivided rural highway cash data, suggest that all three clustering-based EB analysis methods are preferred over the conventional statistical methods. Thus, properly classifying the road segments for heterogeneous crash data can further improve HSID accuracy.

  9. Cluster Analysis of the Newcastle Electronic Corpus of Tyneside English: A Comparison of Methods

    NARCIS (Netherlands)

    Moisl, Hermann; Jones, Valerie M.

    2005-01-01

    This article examines the feasibility of an empirical approach to sociolinguistic analysis of the Newcastle Electronic Corpus of Tyneside English using exploratory multivariate methods. It addresses a known problem with one class of such methods, hierarchical cluster analysis—that different

  10. Cluster Analysis of the Newcastle Electronic Corpus of Tyneside English: In A Comparison of Methods

    NARCIS (Netherlands)

    Moisl, Hermann; Jones, Valerie M.

    2005-01-01

    This article examines the feasibility of an empirical approach to sociolinguistic analysis of the Newcastle Electronic Corpus of Tyneside English using exploratory multivariate methods. It addresses a known problem with one class of such methods, hierarchical cluster analysis—that different

  11. System and Method for Outlier Detection via Estimating Clusters

    Science.gov (United States)

    Iverson, David J. (Inventor)

    2016-01-01

    An efficient method and system for real-time or offline analysis of multivariate sensor data for use in anomaly detection, fault detection, and system health monitoring is provided. Models automatically derived from training data, typically nominal system data acquired from sensors in normally operating conditions or from detailed simulations, are used to identify unusual, out of family data samples (outliers) that indicate possible system failure or degradation. Outliers are determined through analyzing a degree of deviation of current system behavior from the models formed from the nominal system data. The deviation of current system behavior is presented as an easy to interpret numerical score along with a measure of the relative contribution of each system parameter to any off-nominal deviation. The techniques described herein may also be used to "clean" the training data.

  12. A method of detecting spatial clustering of disease

    International Nuclear Information System (INIS)

    Openshaw, S.; Wilkie, D.; Binks, K.; Wakeford, R.; Gerrard, M.H.; Croasdale, M.R.

    1989-01-01

    A statistical technique has been developed to identify extreme groupings of a disease and is being applied to childhood cancers, initially to acute lymphoblastic leukaemia incidence in the Northern and North-Western Regions of England. The method covers the area with a square grid, the size of which is varied over a wide range and whose origin is moved in small increments in two directions. The population at risk within any square is estimated using the 1971 and 1981 censuses. The significance of an excess of disease is determined by random simulation. In addition, tests to detect a general departure from a background Poisson process are carried out. Available results will be presented at the conference. (author)

  13. A method for determining the radius of an open cluster from stellar proper motions

    Science.gov (United States)

    Sánchez, Néstor; Alfaro, Emilio J.; López-Martínez, Fátima

    2018-04-01

    We propose a method for calculating the radius of an open cluster in an objective way from an astrometric catalogue containing, at least, positions and proper motions. It uses the minimum spanning tree in the proper motion space to discriminate cluster stars from field stars and it quantifies the strength of the cluster-field separation by means of a statistical parameter defined for the first time in this paper. This is done for a range of different sampling radii from where the cluster radius is obtained as the size at which the best cluster-field separation is achieved. The novelty of this strategy is that the cluster radius is obtained independently of how its stars are spatially distributed. We test the reliability and robustness of the method with both simulated and real data from a well-studied open cluster (NGC 188), and apply it to UCAC4 data for five other open clusters with different catalogued radius values. NGC 188, NGC 1647, NGC 6603, and Ruprecht 155 yielded unambiguous radius values of 15.2 ± 1.8, 29.4 ± 3.4, 4.2 ± 1.7, and 7.0 ± 0.3 arcmin, respectively. ASCC 19 and Collinder 471 showed more than one possible solution, but it is not possible to know whether this is due to the involved uncertainties or due to the presence of complex patterns in their proper motion distributions, something that could be inherent to the physical object or due to the way in which the catalogue was sampled.

  14. Hierarchical and Non-Hierarchical Linear and Non-Linear Clustering Methods to “Shakespeare Authorship Question”

    Directory of Open Access Journals (Sweden)

    Refat Aljumily

    2015-09-01

    Full Text Available A few literary scholars have long claimed that Shakespeare did not write some of his best plays (history plays and tragedies and proposed at one time or another various suspect authorship candidates. Most modern-day scholars of Shakespeare have rejected this claim, arguing that strong evidence that Shakespeare wrote the plays and poems being his name appears on them as the author. This has caused and led to an ongoing scholarly academic debate for quite some long time. Stylometry is a fast-growing field often used to attribute authorship to anonymous or disputed texts. Stylometric attempts to resolve this literary puzzle have raised interesting questions over the past few years. The following paper contributes to “the Shakespeare authorship question” by using a mathematically-based methodology to examine the hypothesis that Shakespeare wrote all the disputed plays traditionally attributed to him. More specifically, the mathematically based methodology used here is based on Mean Proximity, as a linear hierarchical clustering method, and on Principal Components Analysis, as a non-hierarchical linear clustering method. It is also based, for the first time in the domain, on Self-Organizing Map U-Matrix and Voronoi Map, as non-linear clustering methods to cover the possibility that our data contains significant non-linearities. Vector Space Model (VSM is used to convert texts into vectors in a high dimensional space. The aim of which is to compare the degrees of similarity within and between limited samples of text (the disputed plays. The various works and plays assumed to have been written by Shakespeare and possible authors notably, Sir Francis Bacon, Christopher Marlowe, John Fletcher, and Thomas Kyd, where “similarity” is defined in terms of correlation/distance coefficient measure based on the frequency of usage profiles of function words, word bi-grams, and character triple-grams. The claim that Shakespeare authored all the disputed

  15. Evaluation of hierarchical agglomerative cluster analysis methods for discrimination of primary biological aerosol

    Directory of Open Access Journals (Sweden)

    I. Crawford

    2015-11-01

    Full Text Available In this paper we present improved methods for discriminating and quantifying primary biological aerosol particles (PBAPs by applying hierarchical agglomerative cluster analysis to multi-parameter ultraviolet-light-induced fluorescence (UV-LIF spectrometer data. The methods employed in this study can be applied to data sets in excess of 1 × 106 points on a desktop computer, allowing for each fluorescent particle in a data set to be explicitly clustered. This reduces the potential for misattribution found in subsampling and comparative attribution methods used in previous approaches, improving our capacity to discriminate and quantify PBAP meta-classes. We evaluate the performance of several hierarchical agglomerative cluster analysis linkages and data normalisation methods using laboratory samples of known particle types and an ambient data set. Fluorescent and non-fluorescent polystyrene latex spheres were sampled with a Wideband Integrated Bioaerosol Spectrometer (WIBS-4 where the optical size, asymmetry factor and fluorescent measurements were used as inputs to the analysis package. It was found that the Ward linkage with z-score or range normalisation performed best, correctly attributing 98 and 98.1 % of the data points respectively. The best-performing methods were applied to the BEACHON-RoMBAS (Bio–hydro–atmosphere interactions of Energy, Aerosols, Carbon, H2O, Organics and Nitrogen–Rocky Mountain Biogenic Aerosol Study ambient data set, where it was found that the z-score and range normalisation methods yield similar results, with each method producing clusters representative of fungal spores and bacterial aerosol, consistent with previous results. The z-score result was compared to clusters generated with previous approaches (WIBS AnalysiS Program, WASP where we observe that the subsampling and comparative attribution method employed by WASP results in the overestimation of the fungal spore concentration by a factor of 1.5 and the

  16. The Adaptive-Clustering and Error-Correction Method for Forecasting Cyanobacteria Blooms in Lakes and Reservoirs

    Directory of Open Access Journals (Sweden)

    Xiao-zhe Bai

    2017-01-01

    Full Text Available Globally, cyanobacteria blooms frequently occur, and effective prediction of cyanobacteria blooms in lakes and reservoirs could constitute an essential proactive strategy for water-resource protection. However, cyanobacteria blooms are very complicated because of the internal stochastic nature of the system evolution and the external uncertainty of the observation data. In this study, an adaptive-clustering algorithm is introduced to obtain some typical operating intervals. In addition, the number of nearest neighbors used for modeling was optimized by particle swarm optimization. Finally, a fuzzy linear regression method based on error-correction was used to revise the model dynamically near the operating point. We found that the combined method can characterize the evolutionary track of cyanobacteria blooms in lakes and reservoirs. The model constructed in this paper is compared to other cyanobacteria-bloom forecasting methods (e.g., phase space reconstruction and traditional-clustering linear regression, and, then, the average relative error and average absolute error are used to compare the accuracies of these models. The results suggest that the proposed model is superior. As such, the newly developed approach achieves more precise predictions, which can be used to prevent the further deterioration of the water environment.

  17. Analysis of cost data in a cluster-randomized, controlled trial: comparison of methods

    DEFF Research Database (Denmark)

    Sokolowski, Ineta; Ørnbøl, Eva; Rosendal, Marianne

    studies have used non-valid analysis of skewed data. We propose two different methods to compare mean cost in two groups. Firstly, we use a non-parametric bootstrap method where the re-sampling takes place on two levels in order to take into account the cluster effect. Secondly, we proceed with a log......-transformation of the cost data and apply the normal theory on these data. Again we try to account for the cluster effect. The performance of these two methods is investigated in a simulation study. The advantages and disadvantages of the different approaches are discussed.......  We consider health care data from a cluster-randomized intervention study in primary care to test whether the average health care costs among study patients differ between the two groups. The problems of analysing cost data are that most data are severely skewed. Median instead of mean...

  18. Identification of rural landscape classes through a GIS clustering method

    Directory of Open Access Journals (Sweden)

    Irene Diti

    2013-09-01

    Full Text Available The paper presents a methodology aimed at supporting the rural planning process. The analysis of the state of the art of local and regional policies focused on rural and suburban areas, and the study of the scientific literature in the field of spatial analysis methodologies, have allowed the definition of the basic concept of the research. The proposed method, developed in a GIS, is based on spatial metrics selected and defined to cover various agricultural, environmental, and socio-economic components. The specific goal of the proposed methodology is to identify homogeneous extra-urban areas through their objective characterization at different scales. Once areas with intermediate urban-rural characters have been identified, the analysis is then focused on the more detailed definition of periurban agricultural areas. The synthesis of the results of the analysis of the various landscape components is achieved through an original interpretative key which aims to quantify the potential impacts of rural areas on the urban system. This paper presents the general framework of the methodology and some of the main results of its first implementation through an Italian case study.

  19. Symptom Clusters in Advanced Cancer Patients: An Empirical Comparison of Statistical Methods and the Impact on Quality of Life.

    Science.gov (United States)

    Dong, Skye T; Costa, Daniel S J; Butow, Phyllis N; Lovell, Melanie R; Agar, Meera; Velikova, Galina; Teckle, Paulos; Tong, Allison; Tebbutt, Niall C; Clarke, Stephen J; van der Hoek, Kim; King, Madeleine T; Fayers, Peter M

    2016-01-01

    Symptom clusters in advanced cancer can influence patient outcomes. There is large heterogeneity in the methods used to identify symptom clusters. To investigate the consistency of symptom cluster composition in advanced cancer patients using different statistical methodologies for all patients across five primary cancer sites, and to examine which clusters predict functional status, a global assessment of health and global quality of life. Principal component analysis and exploratory factor analysis (with different rotation and factor selection methods) and hierarchical cluster analysis (with different linkage and similarity measures) were used on a data set of 1562 advanced cancer patients who completed the European Organization for the Research and Treatment of Cancer Quality of Life Questionnaire-Core 30. Four clusters consistently formed for many of the methods and cancer sites: tense-worry-irritable-depressed (emotional cluster), fatigue-pain, nausea-vomiting, and concentration-memory (cognitive cluster). The emotional cluster was a stronger predictor of overall quality of life than the other clusters. Fatigue-pain was a stronger predictor of overall health than the other clusters. The cognitive cluster and fatigue-pain predicted physical functioning, role functioning, and social functioning. The four identified symptom clusters were consistent across statistical methods and cancer types, although there were some noteworthy differences. Statistical derivation of symptom clusters is in need of greater methodological guidance. A psychosocial pathway in the management of symptom clusters may improve quality of life. Biological mechanisms underpinning symptom clusters need to be delineated by future research. A framework for evidence-based screening, assessment, treatment, and follow-up of symptom clusters in advanced cancer is essential. Copyright © 2016 American Academy of Hospice and Palliative Medicine. Published by Elsevier Inc. All rights reserved.

  20. Clustering and training set selection methods for improving the accuracy of quantitative laser induced breakdown spectroscopy

    Energy Technology Data Exchange (ETDEWEB)

    Anderson, Ryan B., E-mail: randerson@astro.cornell.edu [Cornell University Department of Astronomy, 406 Space Sciences Building, Ithaca, NY 14853 (United States); Bell, James F., E-mail: Jim.Bell@asu.edu [Arizona State University School of Earth and Space Exploration, Bldg.: INTDS-A, Room: 115B, Box 871404, Tempe, AZ 85287 (United States); Wiens, Roger C., E-mail: rwiens@lanl.gov [Los Alamos National Laboratory, P.O. Box 1663 MS J565, Los Alamos, NM 87545 (United States); Morris, Richard V., E-mail: richard.v.morris@nasa.gov [NASA Johnson Space Center, 2101 NASA Parkway, Houston, TX 77058 (United States); Clegg, Samuel M., E-mail: sclegg@lanl.gov [Los Alamos National Laboratory, P.O. Box 1663 MS J565, Los Alamos, NM 87545 (United States)

    2012-04-15

    We investigated five clustering and training set selection methods to improve the accuracy of quantitative chemical analysis of geologic samples by laser induced breakdown spectroscopy (LIBS) using partial least squares (PLS) regression. The LIBS spectra were previously acquired for 195 rock slabs and 31 pressed powder geostandards under 7 Torr CO{sub 2} at a stand-off distance of 7 m at 17 mJ per pulse to simulate the operational conditions of the ChemCam LIBS instrument on the Mars Science Laboratory Curiosity rover. The clustering and training set selection methods, which do not require prior knowledge of the chemical composition of the test-set samples, are based on grouping similar spectra and selecting appropriate training spectra for the partial least squares (PLS2) model. These methods were: (1) hierarchical clustering of the full set of training spectra and selection of a subset for use in training; (2) k-means clustering of all spectra and generation of PLS2 models based on the training samples within each cluster; (3) iterative use of PLS2 to predict sample composition and k-means clustering of the predicted compositions to subdivide the groups of spectra; (4) soft independent modeling of class analogy (SIMCA) classification of spectra, and generation of PLS2 models based on the training samples within each class; (5) use of Bayesian information criteria (BIC) to determine an optimal number of clusters and generation of PLS2 models based on the training samples within each cluster. The iterative method and the k-means method using 5 clusters showed the best performance, improving the absolute quadrature root mean squared error (RMSE) by {approx} 3 wt.%. The statistical significance of these improvements was {approx} 85%. Our results show that although clustering methods can modestly improve results, a large and diverse training set is the most reliable way to improve the accuracy of quantitative LIBS. In particular, additional sulfate standards and

  1. Product-service system method to measure sustainability level of traditional smoked fish processing industries

    Directory of Open Access Journals (Sweden)

    Purwaningsih Ratna

    2018-01-01

    Full Text Available Small Medium Enterprise’s (SME of traditional fish processing at Semarang, Central Java, Indonesia still focus their business on gain more profits. Sustainability aspect has not received enough attention yet. This study aims to review the sustainability level of SME smoked fish Semarang using product service system (PSS method. PSS consists of three dimensions (1 Environment, (2 Socio-cultural and (3 Economic. Each dimension consists of 6 criteria's. PSS not only assess the level of sustainability but also formulated the recommendation to increase the industries sustainability level. Sustainability assessment and recommendations formulation is guided by a check-list form. Then, the portfolio diagram used to select these recommendations according to its feasibility to be implemented and its importance for the industries. The result of sustainability assessment for traditional fish processing is 0.44, categorized as medium level. The recommendations for the environmental dimension are (1 use of liquid smoke on fish processing and (2 use of wastewater treatment with anaerobic ponds Recommendation for the socio-cultural dimension is use personal protective tool to reduce worker risk on safety and health. Recommendation for the economic dimension is used social media for product marketing and increasing the economic value of fish lung wastes. Recommendations are then illustrated in a diagram in the form of radar sustainability.

  2. DLTAP: A Network-efficient Scheduling Method for Distributed Deep Learning Workload in Containerized Cluster Environment

    Directory of Open Access Journals (Sweden)

    Qiao Wei

    2017-01-01

    Full Text Available Deep neural networks (DNNs have recently yielded strong results on a range of applications. Training these DNNs using a cluster of commodity machines is a promising approach since training is time consuming and compute-intensive. Furthermore, putting DNN tasks into containers of clusters would enable broader and easier deployment of DNN-based algorithms. Toward this end, this paper addresses the problem of scheduling DNN tasks in the containerized cluster environment. Efficiently scheduling data-parallel computation jobs like DNN over containerized clusters is critical for job performance, system throughput, and resource utilization. It becomes even more challenging with the complex workloads. We propose a scheduling method called Deep Learning Task Allocation Priority (DLTAP which performs scheduling decisions in a distributed manner, and each of scheduling decisions takes aggregation degree of parameter sever task and worker task into account, in particularly, to reduce cross-node network transmission traffic and, correspondingly, decrease the DNN training time. We evaluate the DLTAP scheduling method using a state-of-the-art distributed DNN training framework on 3 benchmarks. The results show that the proposed method can averagely reduce 12% cross-node network traffic, and decrease the DNN training time even with the cluster of low-end servers.

  3. Color electron microprobe cathodoluminescence of Bishunpur meteorite compared with the traditional optical microscopy method

    Directory of Open Access Journals (Sweden)

    Amanda Araujo Tosi

    Full Text Available Abstract Cathodoluminescence (CL imaging is an outstanding method for sub classification of Unequilibrated Ordinary Chondrites (UOC - petrological type 3. CL can be obtained by several electron beam apparatuses. The traditional method uses an electron gun coupled to an optical microscope (OM. Although many scanning electron microscopes (SEM and electron microprobes (EPMA have been equipped with a cathodoluminescence, this technique was not fully explored. Images obtained by the two methods differ due to a different kind of signal acquisition. While in the CL-OM optical photography true colors are obtained, in the CL-EPMA the results are grayscale monochromatic electronic signals. L-RGB filters were used in the CL-EPMA analysis in order to obtain color data. The aim of this work is to compare cathodoluminescence data obtained from both techniques, optical microscope and electron microprobe, on the Bishunpur meteorite classified as LL 3.1 chondrite. The present study allows concluding that 20 KeV and 7 nA is the best analytical condition at EPMA in order to test the equivalence between CL-EPMA and CL-OM colour results. Moreover, the color index revealed to be a method for aiding the study of the thermal metamorphism, but it is not definitive for the meteorite classification.

  4. AN EFFICIENT INITIALIZATION METHOD FOR K-MEANS CLUSTERING OF HYPERSPECTRAL DATA

    Directory of Open Access Journals (Sweden)

    A. Alizade Naeini

    2014-10-01

    Full Text Available K-means is definitely the most frequently used partitional clustering algorithm in the remote sensing community. Unfortunately due to its gradient decent nature, this algorithm is highly sensitive to the initial placement of cluster centers. This problem deteriorates for the high-dimensional data such as hyperspectral remotely sensed imagery. To tackle this problem, in this paper, the spectral signatures of the endmembers in the image scene are extracted and used as the initial positions of the cluster centers. For this purpose, in the first step, A Neyman–Pearson detection theory based eigen-thresholding method (i.e., the HFC method has been employed to estimate the number of endmembers in the image. Afterwards, the spectral signatures of the endmembers are obtained using the Minimum Volume Enclosing Simplex (MVES algorithm. Eventually, these spectral signatures are used to initialize the k-means clustering algorithm. The proposed method is implemented on a hyperspectral dataset acquired by ROSIS sensor with 103 spectral bands over the Pavia University campus, Italy. For comparative evaluation, two other commonly used initialization methods (i.e., Bradley & Fayyad (BF and Random methods are implemented and compared. The confusion matrix, overall accuracy and Kappa coefficient are employed to assess the methods’ performance. The evaluations demonstrate that the proposed solution outperforms the other initialization methods and can be applied for unsupervised classification of hyperspectral imagery for landcover mapping.

  5. Multishell method: Exact treatment of a cluster in an effective medium

    International Nuclear Information System (INIS)

    Gonis, A.; Garland, J.W.

    1977-01-01

    A method is presented for the exact determination of the Green's function of a cluster embedded in a given effective medium. This method, the multishell method, is applicable even to systems with off-diagonal disorder, extended-range hopping, multiple bands, and/or hybridization, and is computationally practicable for any system described by a tight-binding or interpolation-scheme Hamiltonian. It allows one to examine the effects of local environment on the densities of states and site spectral weight functions of disordered systems. For any given analytic effective medium characterized by a non-negative density of states the method yields analytic cluster Green's functions and non-negative site spectral weight functions. Previous methods used for the calculation of the Green's function of a cluster embedded in a given effective medium have not been exact. The results of numerical calculations for model systems show that even the best of these previous methods can lead to substantial errors, at least for small clusters in two- and three-dimensional lattices. These results also show that fluctuations in local environment have large effects on site spectral weight functions, even in cases in which the single-site coherent-potential approximation yields an accurate overall density of states

  6. Open-Source Sequence Clustering Methods Improve the State Of the Art.

    Science.gov (United States)

    Kopylova, Evguenia; Navas-Molina, Jose A; Mercier, Céline; Xu, Zhenjiang Zech; Mahé, Frédéric; He, Yan; Zhou, Hong-Wei; Rognes, Torbjørn; Caporaso, J Gregory; Knight, Rob

    2016-01-01

    Sequence clustering is a common early step in amplicon-based microbial community analysis, when raw sequencing reads are clustered into operational taxonomic units (OTUs) to reduce the run time of subsequent analysis steps. Here, we evaluated the performance of recently released state-of-the-art open-source clustering software products, namely, OTUCLUST, Swarm, SUMACLUST, and SortMeRNA, against current principal options (UCLUST and USEARCH) in QIIME, hierarchical clustering methods in mothur, and USEARCH's most recent clustering algorithm, UPARSE. All the latest open-source tools showed promising results, reporting up to 60% fewer spurious OTUs than UCLUST, indicating that the underlying clustering algorithm can vastly reduce the number of these derived OTUs. Furthermore, we observed that stringent quality filtering, such as is done in UPARSE, can cause a significant underestimation of species abundance and diversity, leading to incorrect biological results. Swarm, SUMACLUST, and SortMeRNA have been included in the QIIME 1.9.0 release. IMPORTANCE Massive collections of next-generation sequencing data call for fast, accurate, and easily accessible bioinformatics algorithms to perform sequence clustering. A comprehensive benchmark is presented, including open-source tools and the popular USEARCH suite. Simulated, mock, and environmental communities were used to analyze sensitivity, selectivity, species diversity (alpha and beta), and taxonomic composition. The results demonstrate that recent clustering algorithms can significantly improve accuracy and preserve estimated diversity without the application of aggressive filtering. Moreover, these tools are all open source, apply multiple levels of multithreading, and scale to the demands of modern next-generation sequencing data, which is essential for the analysis of massive multidisciplinary studies such as the Earth Microbiome Project (EMP) (J. A. Gilbert, J. K. Jansson, and R. Knight, BMC Biol 12:69, 2014, http

  7. Form gene clustering method about pan-ethnic-group products based on emotional semantic

    Science.gov (United States)

    Chen, Dengkai; Ding, Jingjing; Gao, Minzhuo; Ma, Danping; Liu, Donghui

    2016-09-01

    The use of pan-ethnic-group products form knowledge primarily depends on a designer's subjective experience without user participation. The majority of studies primarily focus on the detection of the perceptual demands of consumers from the target product category. A pan-ethnic-group products form gene clustering method based on emotional semantic is constructed. Consumers' perceptual images of the pan-ethnic-group products are obtained by means of product form gene extraction and coding and computer aided product form clustering technology. A case of form gene clustering about the typical pan-ethnic-group products is investigated which indicates that the method is feasible. This paper opens up a new direction for the future development of product form design which improves the agility of product design process in the era of Industry 4.0.

  8. Communication: Time-dependent optimized coupled-cluster method for multielectron dynamics

    Science.gov (United States)

    Sato, Takeshi; Pathak, Himadri; Orimo, Yuki; Ishikawa, Kenichi L.

    2018-02-01

    Time-dependent coupled-cluster method with time-varying orbital functions, called time-dependent optimized coupled-cluster (TD-OCC) method, is formulated for multielectron dynamics in an intense laser field. We have successfully derived the equations of motion for CC amplitudes and orthonormal orbital functions based on the real action functional, and implemented the method including double excitations (TD-OCCD) and double and triple excitations (TD-OCCDT) within the optimized active orbitals. The present method is size extensive and gauge invariant, a polynomial cost-scaling alternative to the time-dependent multiconfiguration self-consistent-field method. The first application of the TD-OCC method of intense-laser driven correlated electron dynamics in Ar atom is reported.

  9. Unsupervised Learning —A Novel Clustering Method for Rolling Bearing Faults Identification

    Science.gov (United States)

    Kai, Li; Bo, Luo; Tao, Ma; Xuefeng, Yang; Guangming, Wang

    2017-12-01

    To promptly process the massive fault data and automatically provide accurate diagnosis results, numerous studies have been conducted on intelligent fault diagnosis of rolling bearing. Among these studies, such as artificial neural networks, support vector machines, decision trees and other supervised learning methods are used commonly. These methods can detect the failure of rolling bearing effectively, but to achieve better detection results, it often requires a lot of training samples. Based on above, a novel clustering method is proposed in this paper. This novel method is able to find the correct number of clusters automatically the effectiveness of the proposed method is validated using datasets from rolling element bearings. The diagnosis results show that the proposed method can accurately detect the fault types of small samples. Meanwhile, the diagnosis results are also relative high accuracy even for massive samples.

  10. Clustering of attitudes towards obesity: a mixed methods study of Australian parents and children.

    Science.gov (United States)

    Olds, Tim; Thomas, Samantha; Lewis, Sophie; Petkov, John

    2013-10-12

    Current population-based anti-obesity campaigns often target individuals based on either weight or socio-demographic characteristics, and give a 'mass' message about personal responsibility. There is a recognition that attempts to influence attitudes and opinions may be more effective if they resonate with the beliefs that different groups have about the causes of, and solutions for, obesity. Limited research has explored how attitudinal factors may inform the development of both upstream and downstream social marketing initiatives. Computer-assisted face-to-face interviews were conducted with 159 parents and 184 of their children (aged 9-18 years old) in two Australian states. A mixed methods approach was used to assess attitudes towards obesity, and elucidate why different groups held various attitudes towards obesity. Participants were quantitatively assessed on eight dimensions relating to the severity and extent, causes and responsibility, possible remedies, and messaging strategies. Cluster analysis was used to determine attitudinal clusters. Participants were also able to qualify each answer. Qualitative responses were analysed both within and across attitudinal clusters using a constant comparative method. Three clusters were identified. Concerned Internalisers (27% of the sample) judged that obesity was a serious health problem, that Australia had among the highest levels of obesity in the world and that prevalence was rapidly increasing. They situated the causes and remedies for the obesity crisis in individual choices. Concerned Externalisers (38% of the sample) held similar views about the severity and extent of the obesity crisis. However, they saw responsibility and remedies as a societal rather than an individual issue. The final cluster, the Moderates, which contained significantly more children and males, believed that obesity was not such an important public health issue, and judged the extent of obesity to be less extreme than the other clusters

  11. Cluster analysis of European Y-chromosomal STR haplotypes using the discrete Laplace method

    DEFF Research Database (Denmark)

    Andersen, Mikkel Meyer; Eriksen, Poul Svante; Morling, Niels

    2014-01-01

    The European Y-chromosomal short tandem repeat (STR) haplotype distribution has previously been analysed in various ways. Here, we introduce a new way of analysing population substructure using a new method based on clustering within the discrete Laplace exponential family that models the probabi......The European Y-chromosomal short tandem repeat (STR) haplotype distribution has previously been analysed in various ways. Here, we introduce a new way of analysing population substructure using a new method based on clustering within the discrete Laplace exponential family that models...... the probability distribution of the Y-STR haplotypes. Creating a consistent statistical model of the haplotypes enables us to perform a wide range of analyses. Previously, haplotype frequency estimation using the discrete Laplace method has been validated. In this paper we investigate how the discrete Laplace...... method can be used for cluster analysis to further validate the discrete Laplace method. A very important practical fact is that the calculations can be performed on a normal computer. We identified two sub-clusters of the Eastern and Western European Y-STR haplotypes similar to results of previous...

  12. Detecting and extracting clusters in atom probe data: A simple, automated method using Voronoi cells

    International Nuclear Information System (INIS)

    Felfer, P.; Ceguerra, A.V.; Ringer, S.P.; Cairney, J.M.

    2015-01-01

    The analysis of the formation of clusters in solid solutions is one of the most common uses of atom probe tomography. Here, we present a method where we use the Voronoi tessellation of the solute atoms and its geometric dual, the Delaunay triangulation to test for spatial/chemical randomness of the solid solution as well as extracting the clusters themselves. We show how the parameters necessary for cluster extraction can be determined automatically, i.e. without user interaction, making it an ideal tool for the screening of datasets and the pre-filtering of structures for other spatial analysis techniques. Since the Voronoi volumes are closely related to atomic concentrations, the parameters resulting from this analysis can also be used for other concentration based methods such as iso-surfaces. - Highlights: • Cluster analysis of atom probe data can be significantly simplified by using the Voronoi cell volumes of the atomic distribution. • Concentration fields are defined on a single atomic basis using Voronoi cells. • All parameters for the analysis are determined by optimizing the separation probability of bulk atoms vs clustered atoms

  13. Volatile profile characterisation of Chilean sparkling wines produced by traditional and Charmat methods via sequential stir bar sorptive extraction.

    Science.gov (United States)

    Ubeda, C; Callejón, R M; Troncoso, A M; Peña-Neira, A; Morales, M L

    2016-09-15

    The volatile compositions of Charmat and traditional Chilean sparkling wines were studied for the first time. For this purpose, EG-Silicone and PDMS polymeric phases were compared and, afterwards, the most adequate was selected. The best extraction method turned out to be a sequential extraction in the headspace and by immersion using two PDMS twisters. A total of 130 compounds were determined. In traditional Chilean sparkling wines, ethyl esters were significantly higher, while acetic esters and ketones were predominant in the Charmat wines. PCA and LDA confirmed the differences in the volatile profiles between the production methods (traditional vs. Charmat). Copyright © 2016 Elsevier Ltd. All rights reserved.

  14. Clustering self-organizing maps (SOM) method for human papillomavirus (HPV) DNA as the main cause of cervical cancer disease

    Science.gov (United States)

    Bustamam, A.; Aldila, D.; Fatimah, Arimbi, M. D.

    2017-07-01

    One of the most widely used clustering method, since it has advantage on its robustness, is Self-Organizing Maps (SOM) method. This paper discusses the application of SOM method on Human Papillomavirus (HPV) DNA which is the main cause of cervical cancer disease, the most dangerous cancer in developing countries. We use 18 types of HPV DNA-based on the newest complete genome. By using open-source-based program R, clustering process can separate 18 types of HPV into two different clusters. There are two types of HPV in the first cluster while 16 others in the second cluster. The analyzing result of 18 types HPV based on the malignancy of the virus (the difficultness to cure). Two of HPV types the first cluster can be classified as tame HPV, while 16 others in the second cluster are classified as vicious HPV.

  15. Perceptions about traditional and novel methods to learn about postoperative pain management: a qualitative study.

    Science.gov (United States)

    Ingadottir, Brynja; Blondal, Katrin; Jaarsma, Tiny; Thylen, Ingela

    2016-11-01

    The aim of this study was to explore the perceptions of surgical patients about traditional and novel methods to learn about postoperative pain management. Patient education is an important part of postoperative care. Contemporary technology offers new ways for patients to learn about self-care, although face-to-face discussions and brochures are the most common methods of delivering education in nursing practice. A qualitative design with a vignette and semi-structured interviews used for data collection. A purposeful sample of 13 postsurgical patients, who had been discharged from hospital, was recruited during 2013-2014. The patients were given a vignette about anticipated hospital discharge after surgery with four different options for communication (face-to-face, brochure, website, serious game) to learn about postoperative pain management. They were asked to rank their preferred method of learning and thereafter to reflect on their choices. Data were analysed using an inductive content analysis approach. Patients preferred face-to-face education with a nurse, followed by brochures and websites, while games were least preferred. Two categories, each with two sub-categories, emerged from the data. These conceptualized the factors affecting patients' perceptions: (1) 'Trusting the source', sub-categorized into 'Being familiar with the method' and 'Having own prejudgments'; and (2) 'Being motivated to learn' sub-categorized into 'Managing an impaired cognition' and 'Aspiring for increased knowledge'. To implement successfully novel educational methods into postoperative care, healthcare professionals need to be aware of the factors influencing patients' perceptions about how to learn, such as trust and motivation. © 2016 John Wiley & Sons Ltd.

  16. [New method for analyzing pharmacodynamic material basis of traditional Chinese medicines by using specific knockout technology with monoclonal antibodies].

    Science.gov (United States)

    Zhao, Yan; Qu, Hui-Hua; Wang, Qing-Guo

    2013-09-01

    Study on pharmacodynamic material basis of traditional Chinese medicines is one of the key issues for the modernization of traditional Chinese medicine. Having introduced the monoclonal antibody technology into the study on pharmacodynamic material basis of traditional Chinese medicines, the author prepared the immunoaffinity chromatography column by using monoclonal antibodies in active components of traditional Chinese medicines, so as to selectively knock out the component from herbs or traditional Chinese medicine compounds, while preserving all of the other components and keeping their amount and ratio unchanged. A comparative study on pharmacokinetics and pharmacodynamics was made to explicitly reveal the correlation between the component and the main purpose of traditional Chinese medicines and compounds. The analysis on pharmacodynamic material basis of traditional Chinese medicines by using specific knockout technology with monoclonal antibodies is a new method for study pharmacodynamic material basis in line with the characteristics of traditional Chinese medicines. Its results can not only help study material basis from a new perspective, but also help find the modern scientific significance in single herb or among compounds of traditional Chinese medicines.

  17. A comparison of three clustering methods for finding subgroups in MRI, SMS or clinical data

    DEFF Research Database (Denmark)

    Kent, Peter; Jensen, Rikke K; Kongsted, Alice

    2014-01-01

    ). There is a scarcity of head-to-head comparisons that can inform the choice of which clustering method might be suitable for particular clinical datasets and research questions. Therefore, the aim of this study was to perform a head-to-head comparison of three commonly available methods (SPSS TwoStep CA, Latent Gold...... LCA and SNOB LCA). METHODS: The performance of these three methods was compared: (i) quantitatively using the number of subgroups detected, the classification probability of individuals into subgroups, the reproducibility of results, and (ii) qualitatively using subjective judgments about each program...... classify individuals into those subgroups. CONCLUSIONS: Our subjective judgement was that Latent Gold offered the best balance of sensitivity to subgroups, ease of use and presentation of results with these datasets but we recognise that different clustering methods may suit other types of data...

  18. Clustering method to process signals from a CdZnTe detector

    International Nuclear Information System (INIS)

    Zhang, Lan; Takahashi, Hiroyuki; Fukuda, Daiji; Nakazawa, Masaharu

    2001-01-01

    The poor mobility of holes in a compound semiconductor detector results in the imperfect collection of the primary charge deposited in the detector. Furthermore the fluctuation of the charge loss efficiency due to the change in the hole collection path length seriously degrades the energy resolution of the detector. Since the charge collection efficiency varies with the signal waveform, we can expect the improvement of the energy resolution through a proper waveform signal processing method. We developed a new digital signal processing technique, a clustering method which derives typical patterns containing the information on the real situation inside a detector from measured signals. The obtained typical patterns for the detector are then used for the pattern matching method. Measured signals are classified through analyzing the practical waveform variation due to the charge trapping, the electric field and the crystal defect etc. Signals with similar shape are placed into the same cluster. For each cluster we calculate an average waveform as a reference pattern. Using these reference patterns obtained from all the clusters, we can classify other measured signal waveforms from the same detector. Then signals are independently processed according to the classified category and form corresponding spectra. Finally these spectra are merged into one spectrum by multiplying normalization coefficients. The effectiveness of this method was verified with a CdZnTe detector of 2 mm thick and a 137 Cs gamma-ray source. The obtained energy resolution as improved to about 8 keV (FWHM). Because the clustering method is only related to the measured waveforms, it can be applied to any type and size of detectors and compatible with any type of filtering methods. (author)

  19. Methods for simultaneously identifying coherent local clusters with smooth global patterns in gene expression profiles

    Directory of Open Access Journals (Sweden)

    Lee Yun-Shien

    2008-03-01

    Full Text Available Abstract Background The hierarchical clustering tree (HCT with a dendrogram 1 and the singular value decomposition (SVD with a dimension-reduced representative map 2 are popular methods for two-way sorting the gene-by-array matrix map employed in gene expression profiling. While HCT dendrograms tend to optimize local coherent clustering patterns, SVD leading eigenvectors usually identify better global grouping and transitional structures. Results This study proposes a flipping mechanism for a conventional agglomerative HCT using a rank-two ellipse (R2E, an improved SVD algorithm for sorting purpose seriation by Chen 3 as an external reference. While HCTs always produce permutations with good local behaviour, the rank-two ellipse seriation gives the best global grouping patterns and smooth transitional trends. The resulting algorithm automatically integrates the desirable properties of each method so that users have access to a clustering and visualization environment for gene expression profiles that preserves coherent local clusters and identifies global grouping trends. Conclusion We demonstrate, through four examples, that the proposed method not only possesses better numerical and statistical properties, it also provides more meaningful biomedical insights than other sorting algorithms. We suggest that sorted proximity matrices for genes and arrays, in addition to the gene-by-array expression matrix, can greatly aid in the search for comprehensive understanding of gene expression structures. Software for the proposed methods can be obtained at http://gap.stat.sinica.edu.tw/Software/GAP.

  20. Statistical method on nonrandom clustering with application to somatic mutations in cancer

    Directory of Open Access Journals (Sweden)

    Rejto Paul A

    2010-01-01

    Full Text Available Abstract Background Human cancer is caused by the accumulation of tumor-specific mutations in oncogenes and tumor suppressors that confer a selective growth advantage to cells. As a consequence of genomic instability and high levels of proliferation, many passenger mutations that do not contribute to the cancer phenotype arise alongside mutations that drive oncogenesis. While several approaches have been developed to separate driver mutations from passengers, few approaches can specifically identify activating driver mutations in oncogenes, which are more amenable for pharmacological intervention. Results We propose a new statistical method for detecting activating mutations in cancer by identifying nonrandom clusters of amino acid mutations in protein sequences. A probability model is derived using order statistics assuming that the location of amino acid mutations on a protein follows a uniform distribution. Our statistical measure is the differences between pair-wise order statistics, which is equivalent to the size of an amino acid mutation cluster, and the probabilities are derived from exact and approximate distributions of the statistical measure. Using data in the Catalog of Somatic Mutations in Cancer (COSMIC database, we have demonstrated that our method detects well-known clusters of activating mutations in KRAS, BRAF, PI3K, and β-catenin. The method can also identify new cancer targets as well as gain-of-function mutations in tumor suppressors. Conclusions Our proposed method is useful to discover activating driver mutations in cancer by identifying nonrandom clusters of somatic amino acid mutations in protein sequences.

  1. Blended learning – integrating E-learning with traditional learning methods in teaching basic medical science

    OpenAIRE

    J.G. Bagi; N.K. Hashilkar

    2014-01-01

    Background: Blended learning includes an integration of face to face classroom learning with technology enhanced online material. It provides the convenience, speed and cost effectiveness of e-learning with the personal touch of traditional learning. Objective: The objective of the present study was to assess the effectiveness of a combination of e-learning module and traditional teaching (Blended learning) as compared to traditional teaching alone to teach acid base homeostasis to Phase I MB...

  2. Consistency analysis of Keratograph and traditional methods to evaluate tear film function

    Directory of Open Access Journals (Sweden)

    Pei-Yang Shen

    2015-05-01

    Full Text Available AIM: To investigate repeatability and accuracy of a latest Keratograph for evaluating the tear film stability and to compare its measurements with that of traditional examination methods. METHODS: The results of noninvasive tear film break-up time(NI-BUTincluding the first tear film break-up time(BUT-fand the average tear film break-up time(BUT-avewere measured by Keratograph. The repeatability of the measurements was evaluated by coefficient of variation(CVand intraclass correlation coefficient(ICC. Wilcoxon Signed-Rank test was used to compare NI-BUT with fluorescein tear film break-up time(FBUTto confirm the correlation between NI-BUT and FBUT, Schirmer I test values. Bland-Altman analysis was used to evaluate consistency. RESULTS: The study recruited 48 subjects(48 eyes(mean age 38.7±15.2 years. The CV and ICC of BUT-f were respectively 12.6% and 0.95, those of BUT-ave were 9.8% and 0.96. The value of BUT-f was lower than that of FBUT. The difference had statistical significance(6.16±2.46s vs 7.46±1.92s, PPCONCLUSION: Keratograph can provide NI-BUT data that has a better repeatability and reliability, which has great application prospects in diagnosis and treatment of dry eye and refractive corneal surgery.

  3. Integration of membrane distillation into traditional salt farming method: Process development and modelling

    Science.gov (United States)

    Hizam, S.; Bilad, M. R.; Putra, Z. A.

    2017-10-01

    Farmers still practice the traditional salt farming in many regions, particularly in Indonesia. This archaic method not only produces low yield and poor salt quality, it is also laborious. Furthermore, the farming locations typically have poor access to fresh water and are far away from electricity grid, which restrict upgrade to a more advanced technology for salt production. This paper proposes a new concept of salt harvesting method that improves the salt yield and at the same time facilitates recovery of fresh water from seawater. The new concept integrates solar powered membrane distillation (MD) and photovoltaic cells to drive the pumping. We performed basic solar still experiments to quantify the heat flux received by a pond. The data were used as insight for designing the proposed concept, particularly on operational strategy and the most effective way to integrate MD. After the conceptual design had been developed, we formulated mass and energy balance to estimate the performance of the proposed concept. Based on our data and design, it is expected that the system would improve the yield and quality of the salt production, maximizing fresh water harvesting, and eventually provides economical gain for salt farmers hence improving their quality of life. The key performance can only be measured via experiment using gain output ratio as performance indicator, which will be done in a future study.

  4. Developing a Pictorial Sisterhood Method in collaboration with illiterate Maasai traditional birth attendants in northern Tanzania.

    Science.gov (United States)

    Roggeveen, Yadira; Schreuder, Renske; Zweekhorst, Marjolein; Manyama, Mange; Hatfield, Jennifer; Scheele, Fedde; van Roosmalen, Jos

    2016-10-01

    To study whether data on maternal mortality can be gathered while maintaining local ownership of data in a pastoralist setting where a scarcity of data sources and a culture of silence around maternal death amplifies limited awareness of the magnitude of maternal mortality. As part of a participatory action research project, investigators and illiterate traditional birth attendants (TBAs) collaboratively developed a quantitative participatory tool-the Pictorial Sisterhood Method-that was pilot-tested between March 12 and May 30, 2011, by researchers and TBAs in a cross-sectional study. Fourteen TBAs interviewed 496 women (sample), which led to 2241 sister units of risk and a maternal mortality ratio of 689 deaths per 100000 live births (95% confidence interval 419-959). Researchers interviewed 474 women (sample), leading to 1487 sister units of risk and a maternal mortality ratio of 484 (95% confidence interval 172-795). The Pictorial Sisterhood Method is an innovative application that might increase the participation of illiterate individuals in maternal health research and advocacy. It offers interesting opportunities to increase maternal mortality data ownership and awareness, and warrants further study and validation. Copyright © 2016 International Federation of Gynecology and Obstetrics. Published by Elsevier Ireland Ltd. All rights reserved.

  5. Application of PROMETHEE-GAIA method for non-traditional machining processes selection

    Directory of Open Access Journals (Sweden)

    Prasad Karande

    2012-10-01

    Full Text Available With ever increasing demand for manufactured products of hard alloys and metals with high surface finish and complex shape geometry, more interest is now being paid to non-traditional machining (NTM processes, where energy in its direct form is used to remove material from workpiece surface. Compared to conventional machining processes, NTM processes possess almost unlimited capabilities and there is a strong believe that use of NTM processes would go on increasing in diverse range of applications. Presence of a large number of NTM processes along with complex characteristics and capabilities, and lack of experts in NTM process selection domain compel for development of a structured approach for NTM process selection for a given machining application. Past researchers have already attempted to solve NTM process selection problems using various complex mathematical approaches which often require a profound knowledge in mathematics/artificial intelligence from the part of process engineers. In this paper, four NTM process selection problems are solved using an integrated PROMETHEE (preference ranking organization method for enrichment evaluation and GAIA (geometrical analysis for interactive aid method which would act as a visual decision aid to the process engineers. The observed results are quite satisfactory and exactly match with the expected solutions.

  6. Annotated Computer Output for Illustrative Examples of Clustering Using the Mixture Method and Two Comparable Methods from SAS.

    Science.gov (United States)

    1987-06-26

    BUREAU OF STANDAR-S1963-A Nw BOM -ILE COPY -. 4eo .?3sa.9"-,,A WIN* MAT HEMATICAL SCIENCES _*INSTITUTE AD-A184 687 DTICS!ELECTE ANNOTATED COMPUTER OUTPUT...intoduction to the use of mixture models in clustering. Cornell University Biometrics Unit Technical Report BU-920-M and Mathematical Sciences Institute...mixture method and two comparable methods from SAS. Cornell University Biometrics Unit Technical Report BU-921-M and Mathematical Sciences Institute

  7. VOLATILE CONSTITUENTS OF GINGER OIL PREPARED ACCORDING TO IRANIAN TRADITIONAL MEDICINE AND CONVENTIONAL METHOD: A COMPARATIVE STUDY.

    Science.gov (United States)

    Shirooye, Pantea; Mokaberinejad, Roshanak; Ara, Leila; Hamzeloo-Moghadam, Maryam

    2016-01-01

    Herbal medicines formulated as oils were believed to possess more powerful effects than their original plants in Iranian Traditional Medicine (ITM). One of the popular oils suggested for treatment of various indications was ginger oil. In the present study, to suggest a more convenient method of oil preparation (compared to the traditional method), ginger oil has been prepared according to both the traditional and conventional maceration methods and the volatile oil constituents have been compared. Ginger oil was obtained in sesame oil according to both the traditional way and the conventional (maceration) methods. The volatile oil of dried ginger and both oils were obtained by hydro-distillation and analyzed by gas chromatography/mass spectroscopy. Fifty five, fifty nine and fifty one components consisting 94 %, 94 % and 98 % of the total compounds were identified in the volatile oil of ginger, traditional and conventional oils, respectively. The most dominant compounds of the traditional and conventional oils were almost similar; however they were different from ginger essential oil which has also been to possess limited amounts of anti-inflammatory components. It was concluded that ginger oil could be prepared through maceration method and used for indications mentioned in ITM.

  8. 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

  9. Clustered iterative stochastic ensemble method for multi-modal calibration of subsurface flow models

    KAUST Repository

    Elsheikh, Ahmed H.

    2013-05-01

    A novel multi-modal parameter estimation algorithm is introduced. Parameter estimation is an ill-posed inverse problem that might admit many different solutions. This is attributed to the limited amount of measured data used to constrain the inverse problem. The proposed multi-modal model calibration algorithm uses an iterative stochastic ensemble method (ISEM) for parameter estimation. ISEM employs an ensemble of directional derivatives within a Gauss-Newton iteration for nonlinear parameter estimation. ISEM is augmented with a clustering step based on k-means algorithm to form sub-ensembles. These sub-ensembles are used to explore different parts of the search space. Clusters are updated at regular intervals of the algorithm to allow merging of close clusters approaching the same local minima. Numerical testing demonstrates the potential of the proposed algorithm in dealing with multi-modal nonlinear parameter estimation for subsurface flow models. © 2013 Elsevier B.V.

  10. Implementation of K-Means Clustering Method for Electronic Learning Model

    Science.gov (United States)

    Latipa Sari, Herlina; Suranti Mrs., Dewi; Natalia Zulita, Leni

    2017-12-01

    Teaching and Learning process at SMK Negeri 2 Bengkulu Tengah has applied e-learning system for teachers and students. The e-learning was based on the classification of normative, productive, and adaptive subjects. SMK Negeri 2 Bengkulu Tengah consisted of 394 students and 60 teachers with 16 subjects. The record of e-learning database was used in this research to observe students’ activity pattern in attending class. K-Means algorithm in this research was used to classify students’ learning activities using e-learning, so that it was obtained cluster of students’ activity and improvement of student’s ability. Implementation of K-Means Clustering method for electronic learning model at SMK Negeri 2 Bengkulu Tengah was conducted by observing 10 students’ activities, namely participation of students in the classroom, submit assignment, view assignment, add discussion, view discussion, add comment, download course materials, view article, view test, and submit test. In the e-learning model, the testing was conducted toward 10 students that yielded 2 clusters of membership data (C1 and C2). Cluster 1: with membership percentage of 70% and it consisted of 6 members, namely 1112438 Anggi Julian, 1112439 Anis Maulita, 1112441 Ardi Febriansyah, 1112452 Berlian Sinurat, 1112460 Dewi Anugrah Anwar and 1112467 Eka Tri Oktavia Sari. Cluster 2:with membership percentage of 30% and it consisted of 4 members, namely 1112463 Dosita Afriyani, 1112471 Erda Novita, 1112474 Eskardi and 1112477 Fachrur Rozi.

  11. Study of methods to increase cluster/dislocation loop densities in electrodes

    Science.gov (United States)

    Yang, Xiaoling; Miley, George H.

    2009-03-01

    Recent research has developed a technique for imbedding ultra-high density deuterium ``clusters'' (50 to 100 atoms per cluster) in various metals such as Palladium (Pd), Beryllium (Be) and Lithium (Li). It was found the thermally dehydrogenated PdHx retained the clusters and exhibited up to 12 percent lower resistance compared to the virginal Pd samplesootnotetextA. G. Lipson, et al. Phys. Solid State. 39 (1997) 1891. SQUID measurements showed that in Pd these condensed matter clusters approach metallic conditions, exhibiting superconducting propertiesootnotetextA. Lipson, et al. Phys. Rev. B 72, 212507 (2005ootnotetextA. G. Lipson, et al. Phys. Lett. A 339, (2005) 414-423. If the fabrication methods under study are successful, a large packing fraction of nuclear reactive clusters can be developed in the electrodes by electrolyte or high pressure gas loading. This will provide a much higher low-energy-nuclear- reaction (LENR) rate than achieved with earlier electrodeootnotetextCastano, C.H., et al. Proc. ICCF-9, Beijing, China 19-24 May, 2002..

  12. IP2P K-means: an efficient method for data clustering on sensor networks

    Directory of Open Access Journals (Sweden)

    Peyman Mirhadi

    2013-03-01

    Full Text Available Many wireless sensor network applications require data gathering as the most important parts of their operations. There are increasing demands for innovative methods to improve energy efficiency and to prolong the network lifetime. Clustering is considered as an efficient topology control methods in wireless sensor networks, which can increase network scalability and lifetime. This paper presents a method, IP2P K-means – Improved P2P K-means, which uses efficient leveling in clustering approach, reduces false labeling and restricts the necessary communication among various sensors, which obviously saves more energy. The proposed method is examined in Network Simulator Ver.2 (NS2 and the preliminary results show that the algorithm works effectively and relatively more precisely.

  13. Method for Determining Appropriate Clustering Criteria of Location-Sensing Data

    Directory of Open Access Journals (Sweden)

    Youngmin Lee

    2016-08-01

    Full Text Available Large quantities of location-sensing data are generated from location-based social network services. These data are provided as point properties with location coordinates acquired from a global positioning system or Wi-Fi signal. To show the point data on multi-scale map services, the data should be represented by clusters following a grid-based clustering method, in which an appropriate grid size should be determined. Currently, there are no criteria for determining the proper grid size, and the modifiable areal unit problem has been formulated for the purpose of addressing this issue. The method proposed in this paper is applies a hexagonal grid to geotagged Twitter point data, considering the grid size in terms of both quantity and quality to minimize the limitations associated with the modifiable areal unit problem. Quantitatively, we reduced the original Twitter point data by an appropriate amount using Töpfer’s radical law. Qualitatively, we maintained the original distribution characteristics using Moran’s I. Finally, we determined the appropriate sizes of clusters from zoom levels 9–13 by analyzing the distribution of data on the graphs. Based on the visualized clustering results, we confirm that the original distribution pattern is effectively maintained using the proposed method.

  14. Field camp: Using traditional methods to train the next generation of petroleum geologists

    Science.gov (United States)

    Puckette, J.O.; Suneson, N.H.

    2009-01-01

    The summer field camp experience provides many students with their best opportunity to learn the scientific process by making observations and collecting, recording, evaluating, and interpreting geologic data. Field school projects enhance student professional development by requiring cooperation and interpersonal interaction, report writing to communicate interpretations, and the development of project management skills to achieve a common goal. The field school setting provides students with the opportunity to observe geologic features and their spatial distribution, size, and shape that will impact the student's future careers as geoscientists. The Les Huston Geology Field Camp (a.k.a. Oklahoma Geology Camp) near Ca??on City, Colorado, focuses on time-tested traditional methods of geological mapping and fieldwork to accomplish these goals. The curriculum consists of an introduction to field techniques (pacing, orienteering, measuring strike and dip, and using a Jacob's staff), sketching outcrops, section measuring (one illustrating facies changes), three mapping exercises (of increasing complexity), and a field geophysics project. Accurate rock and contact descriptions are emphasized, and attitudes and contacts are mapped in the field. Mapping is done on topographic maps at 1:12,000 and 1:6000 scales; air photos are provided. Global positioning system (GPS)-assisted mapping is allowed, but we insist that locations be recorded in the field and confirmed using visual observations. The course includes field trips to the Cripple Creek and Leadville mining districts, Floris-sant/Guffey volcano area, Pikes Peak batholith, and the Denver Basin. Each field trip is designed to emphasize aspects of geology that are not stressed in the field exercises. Students are strongly encouraged to accurately describe geologic features and gather evidence to support their interpretations of the geologic history. Concise reports are a part of each major exercise. Students are grouped

  15. Improving Nursing Students' Learning Outcomes in Fundamentals of Nursing Course through Combination of Traditional and e-Learning Methods.

    Science.gov (United States)

    Sheikhaboumasoudi, Rouhollah; Bagheri, Maryam; Hosseini, Sayed Abbas; Ashouri, Elaheh; Elahi, Nasrin

    2018-01-01

    Fundamentals of nursing course are prerequisite to providing comprehensive nursing care. Despite development of technology on nursing education, effectiveness of using e-learning methods in fundamentals of nursing course is unclear in clinical skills laboratory for nursing students. The aim of this study was to compare the effect of blended learning (combining e-learning with traditional learning methods) with traditional learning alone on nursing students' scores. A two-group post-test experimental study was administered from February 2014 to February 2015. Two groups of nursing students who were taking the fundamentals of nursing course in Iran were compared. Sixty nursing students were selected as control group (just traditional learning methods) and experimental group (combining e-learning with traditional learning methods) for two consecutive semesters. Both groups participated in Objective Structured Clinical Examination (OSCE) and were evaluated in the same way using a prepared checklist and questionnaire of satisfaction. Statistical analysis was conducted through SPSS software version 16. Findings of this study reflected that mean of midterm (t = 2.00, p = 0.04) and final score (t = 2.50, p = 0.01) of the intervention group (combining e-learning with traditional learning methods) were significantly higher than the control group (traditional learning methods). The satisfaction of male students in intervention group was higher than in females (t = 2.60, p = 0.01). Based on the findings, this study suggests that the use of combining traditional learning methods with e-learning methods such as applying educational website and interactive online resources for fundamentals of nursing course instruction can be an effective supplement for improving nursing students' clinical skills.

  16. Relativistic rise measurement by cluster counting method in time expansion chamber

    International Nuclear Information System (INIS)

    Rehak, P.; Walenta, A.H.

    1979-10-01

    A new approach to the measurement of the ionization energy loss for the charged particle identification in the region of the relativistic rise was tested experimentally. The method consists of determining in a special drift chamber (TEC) the number of clusters of the primary ionization. The method gives almost the full relativistic rise and narrower landau distribution. The consequences for a practical detector are discussed

  17. Comparing the Effects of Objective Structured Assessment of Technical Skills (OSATS) and Traditional Method on Learning of Students.

    Science.gov (United States)

    Mansoorian, Mohammad Reza; Hosseiny, Marzeih Sadat; Khosravan, Shahla; Alami, Ali; Alaviani, Mehri

    2015-06-01

    Despite the benefits of the objective structured assessment of technical skills (OSATS) and it appropriateness for evaluating clinical abilities of nursing students , few studies are available on the application of this method in nursing education. The purpose of this study was to compare the effect of using OSATS and traditional methods on the students' learning. We also aimed to signify students' views about these two methods and their views about the scores they received in these methods in a medical emergency course. A quasi-experimental study was performed on 45 first semester students in nursing and medical emergencies passing a course on fundamentals of practice. The students were selected by a census method and evaluated by both the OSATS and traditional methods. Data collection was performed using checklists prepared based on the 'text book of nursing procedures checklists' published by Iranian nursing organization and a questionnaire containing learning rate and students' estimation of their received scores. Descriptive statistics as well as paired t-test and independent samples t-test were used in data analysis. The mean of students' score in OSATS was significantly higher than their mean score in traditional method (P = 0.01). Moreover, the mean of self-evaluation score after the traditional method was relatively the same as the score the students received in the exam. However, the mean of self-evaluation score after the OSATS was relatively lower than the scores the students received in the OSATS exam. Most students believed that OSATS can evaluate a wide range of students' knowledge and skills compared to traditional method. Results of this study indicated the better effect of OSATS on learning and its relative superiority in precise assessment of clinical skills compared with the traditional evaluation method. Therefore, we recommend using this method in evaluation of students in practical courses.

  18. Association between traditional oral hygiene methods with tooth wear, gingival bleeding, and recession: A descriptive cross-sectional study.

    Science.gov (United States)

    Shah, Naseem; Mathur, Vijay Prakash; Jain, Veena; Logani, Ajay

    2018-01-01

    Oral hygiene maintenance is crucial for prevention of various oral diseases. Oral hygiene practices across the country vary largely and people in peri-urban and rural areas use traditional methods of oral hygiene like powders, bark, oil and salt etc. Their effect on oral soft and hard tissues need to be studied to understand their beneficial and/ or harmful effects on maintenance of oral hygiene and prevention or causation of oral diseases. This study aimed to assess the plaque-cleaning efficacy, gingival bleeding, recession and tooth wear with different traditional oral hygiene methods as compared to use of toothpaste-toothbrush, the most accepted method of oral hygiene practice. Hospital based cross sectional analytical study. Results: Total 1062 traditional oral hygiene method users were compared with same number of toothpaste-brush users. The maximum number in the former group used tooth powder (76%) as compared to other indigenous methods, such as use of bark of trees etc and out of tooth powder users; almost 75% reported using red toothpowder. The plaque scores and gingival bleeding & recession were found to be more in traditional oral hygiene method users. The toothwear was also more severe among the toothpowder users. Traditional methods were found to be inferior in plaque control as was documented by increased bleeding and gingival recession. Its effect on hard tissues of teeth was very damaging with higher tooth wear scores on all surfaces.

  19. Stepwise threshold clustering: a new method for genotyping MHC loci using next-generation sequencing technology.

    Directory of Open Access Journals (Sweden)

    William E Stutz

    Full Text Available Genes of the vertebrate major histocompatibility complex (MHC are of great interest to biologists because of their important role in immunity and disease, and their extremely high levels of genetic diversity. Next generation sequencing (NGS technologies are quickly becoming the method of choice for high-throughput genotyping of multi-locus templates like MHC in non-model organisms. Previous approaches to genotyping MHC genes using NGS technologies suffer from two problems:1 a "gray zone" where low frequency alleles and high frequency artifacts can be difficult to disentangle and 2 a similar sequence problem, where very similar alleles can be difficult to distinguish as two distinct alleles. Here were present a new method for genotyping MHC loci--Stepwise Threshold Clustering (STC--that addresses these problems by taking full advantage of the increase in sequence data provided by NGS technologies. Unlike previous approaches for genotyping MHC with NGS data that attempt to classify individual sequences as alleles or artifacts, STC uses a quasi-Dirichlet clustering algorithm to cluster similar sequences at increasing levels of sequence similarity. By applying frequency and similarity based criteria to clusters rather than individual sequences, STC is able to successfully identify clusters of sequences that correspond to individual or similar alleles present in the genomes of individual samples. Furthermore, STC does not require duplicate runs of all samples, increasing the number of samples that can be genotyped in a given project. We show how the STC method works using a single sample library. We then apply STC to 295 threespine stickleback (Gasterosteus aculeatus samples from four populations and show that neighboring populations differ significantly in MHC allele pools. We show that STC is a reliable, accurate, efficient, and flexible method for genotyping MHC that will be of use to biologists interested in a variety of downstream applications.

  20. Andragogical Teaching Methods to Enhance Non-Traditional Student Classroom Engagement

    Science.gov (United States)

    Allen, Pamela; Withey, Paul; Lawton, Deb; Aquino, Carlos Tasso

    2016-01-01

    The aim of this study was to provide a reflection of current trends in higher education, identify some of the changes in student behavior, and potential identification of non-traditional classroom facilitation with the purpose of strengthening active learning and use of technology in the classroom. Non-traditional teaching is emerging in the form…

  1. Traditional methods v. new technologies – dilemmas for dietary assessment in large-scale nutrition surveys and studies

    DEFF Research Database (Denmark)

    Amoutzopoulos, B.; Steer, T.; Roberts, C.

    2018-01-01

    assessment in population surveys’, was held at the 9th International Conference on Diet and Activity Methods (ICDAM9), Brisbane, September 2015. Despite respondent and researcher burden, traditional methods have been most commonly used in nutrition surveys. However, dietary assessment technologies offer...... of traditional dietary assessment methods (food records, FFQ, 24 h recalls, diet history with interviewer-assisted data collection) v. new technology-based dietary assessment methods (web-based and mobile device applications). The panel discussion ‘Traditional methods v. new technologies: dilemmas for dietary......The aim of the present paper is to summarise current and future applications of dietary assessment technologies in nutrition surveys in developed countries. It includes the discussion of key points and highlights of subsequent developments from a panel discussion to address strengths and weaknesses...

  2. Exploring the Ligand-Protein Networks in Traditional Chinese Medicine: Current Databases, Methods, and Applications

    Directory of Open Access Journals (Sweden)

    Mingzhu Zhao

    2013-01-01

    Full Text Available The traditional Chinese medicine (TCM, which has thousands of years of clinical application among China and other Asian countries, is the pioneer of the “multicomponent-multitarget” and network pharmacology. Although there is no doubt of the efficacy, it is difficult to elucidate convincing underlying mechanism of TCM due to its complex composition and unclear pharmacology. The use of ligand-protein networks has been gaining significant value in the history of drug discovery while its application in TCM is still in its early stage. This paper firstly surveys TCM databases for virtual screening that have been greatly expanded in size and data diversity in recent years. On that basis, different screening methods and strategies for identifying active ingredients and targets of TCM are outlined based on the amount of network information available, both on sides of ligand bioactivity and the protein structures. Furthermore, applications of successful in silico target identification attempts are discussed in detail along with experiments in exploring the ligand-protein networks of TCM. Finally, it will be concluded that the prospective application of ligand-protein networks can be used not only to predict protein targets of a small molecule, but also to explore the mode of action of TCM.

  3. Interobserver Reliability of Four Diagnostic Methods Using Traditional Korean Medicine for Stroke Patients

    Directory of Open Access Journals (Sweden)

    Ju Ah Lee

    2014-01-01

    Full Text Available Objective. The aim of this study is to evaluate the consistency of pattern identification (PI, a set of diagnostic indicators used by traditional Korean medicine (TKM clinicians. Methods. A total of 168 stroke patients who were admitted into oriental medical university hospitals from June 2012 through January 2013 were included in the study. Using the PI indicators, each patient was independently diagnosed by two experts from the same department. Interobserver consistency was assessed by simple percentage agreement as well as by kappa and AC1 statistics. Results. Interobserver agreement on the PI indicators (for all patients was generally high: pulse diagnosis signs (AC1=0.66–0.89; inspection signs (AC1=0.66–0.95; listening/smelling signs (AC1=0.67–0.88; and inquiry signs (AC1=0.62–0.94. Conclusion. In four examinations, there was moderate agreement between the clinicians on the PI indicators. To improve clinician consistency (e.g., in the diagnostic criteria used, it is necessary to analyze the reasons for inconsistency and to improve clinician training.

  4. Application methods of infrared thermal images in the health care field of traditional Chinese medicine

    Science.gov (United States)

    Li, Ziru; Zhang, Xusheng

    2008-12-01

    Infrared thermal imaging (ITI) is the potential imaging technique for the health care field of traditional Chinese medicine (TCM). Successful application demands obeying the characteristics and regularity of the ITI of human body and designing rigorous trials. First, the influence of time must be taken into account as the ITI of human body varies with time markedly. Second, relative magnitude is preferred to be the index of the image features. Third, scatter diagrams and the method of least square could present important information for evaluating the health care effect. A double-blind placebo-controlled randomized trial was undertaken to study the influences of Shengsheng capsule, one of the TCM health food with immunity adjustment function, on the ITI of human body. The results showed that the effect of Shengsheng capsule to people with weak constitution or in the period of being weak could be reflected objectively by ITI. The relative efficacy rate was 81.3% for the trial group and 30.0% for the control group, there was significant difference between the two groups (P=0.003). So the sensitivity and objectivity of ITI are of great importance to the health care field of TCM.

  5. Cultural continuity, traditional Indigenous language, and diabetes in Alberta First Nations: a mixed methods study.

    Science.gov (United States)

    Oster, Richard T; Grier, Angela; Lightning, Rick; Mayan, Maria J; Toth, Ellen L

    2014-10-19

    We used an exploratory sequential mixed methods approach to study the association between cultural continuity, self-determination, and diabetes prevalence in First Nations in Alberta, Canada. We conducted a qualitative description where we interviewed 10 Cree and Blackfoot leaders (members of Chief and Council) from across the province to understand cultural continuity, self-determination, and their relationship to health and diabetes, in the Alberta First Nations context. Based on the qualitative findings, we then conducted a cross-sectional analysis using provincial administrative data and publically available data for 31 First Nations communities to quantitatively examine any relationship between cultural continuity and diabetes prevalence. Cultural continuity, or "being who we are", is foundational to health in successful First Nations. Self-determination, or "being a self-sufficient Nation", stems from cultural continuity and is seriously compromised in today's Alberta Cree and Blackfoot Nations. Unfortunately, First Nations are in a continuous struggle with government policy. The intergenerational effects of colonization continue to impact the culture, which undermines the sense of self-determination, and contributes to diabetes and ill health. Crude diabetes prevalence varied dramatically among First Nations with values as low as 1.2% and as high as 18.3%. Those First Nations that appeared to have more cultural continuity (measured by traditional Indigenous language knowledge) had significantly lower diabetes prevalence after adjustment for socio-economic factors (p =0.007). First Nations that have been better able to preserve their culture may be relatively protected from diabetes.

  6. Model creation of moving redox reaction boundary in agarose gel electrophoresis by traditional potassium permanganate method.

    Science.gov (United States)

    Xie, Hai-Yang; Liu, Qian; Li, Jia-Hao; Fan, Liu-Yin; Cao, Cheng-Xi

    2013-02-21

    A novel moving redox reaction boundary (MRRB) model was developed for studying electrophoretic behaviors of analytes involving redox reaction on the principle of moving reaction boundary (MRB). Traditional potassium permanganate method was used to create the boundary model in agarose gel electrophoresis because of the rapid reaction rate associated with MnO(4)(-) ions and Fe(2+) ions. MRB velocity equation was proposed to describe the general functional relationship between velocity of moving redox reaction boundary (V(MRRB)) and concentration of reactant, and can be extrapolated to similar MRB techniques. Parameters affecting the redox reaction boundary were investigated in detail. Under the selected conditions, good linear relationship between boundary movement distance and time were obtained. The potential application of MRRB in electromigration redox reaction titration was performed in two different concentration levels. The precision of the V(MRRB) was studied and the relative standard deviations were below 8.1%, illustrating the good repeatability achieved in this experiment. The proposed MRRB model enriches the MRB theory and also provides a feasible realization of manual control of redox reaction process in electrophoretic analysis.

  7. Assessing Knowledge Retention of an Immersive Serious Game vs. a Traditional Education Method in Aviation Safety.

    Science.gov (United States)

    Chittaro, Luca; Buttussi, Fabio

    2015-04-01

    Thanks to the increasing availability of consumer head-mounted displays, educational applications of immersive VR could now reach to the general public, especially if they include gaming elements (immersive serious games). Safety education of citizens could be a particularly promising domain for immersive serious games, because people tend not to pay attention to and benefit from current safety materials. In this paper, we propose an HMD-based immersive game for educating passengers about aviation safety that allows players to experience a serious aircraft emergency with the goal of surviving it. We compare the proposed approach to a traditional aviation safety education method (the safety card) used by airlines. Unlike most studies of VR for safety knowledge acquisition, we do not focus only on assessing learning immediately after the experience but we extend our attention to knowledge retention over a longer time span. This is a fundamental requirement, because people need to retain safety procedures in order to apply them when faced with danger. A knowledge test administered before, immediately after and one week after the experimental condition showed that the immersive serious game was superior to the safety card. Moreover, subjective as well as physiological measurements employed in the study showed that the immersive serious game was more engaging and fear-arousing than the safety card, a factor that can contribute to explain the obtained superior retention, as we discuss in the paper.

  8. Pre-crash scenarios at road junctions: A clustering method for car crash data.

    Science.gov (United States)

    Nitsche, Philippe; Thomas, Pete; Stuetz, Rainer; Welsh, Ruth

    2017-10-01

    Given the recent advancements in autonomous driving functions, one of the main challenges is safe and efficient operation in complex traffic situations such as road junctions. There is a need for comprehensive testing, either in virtual simulation environments or on real-world test tracks. This paper presents a novel data analysis method including the preparation, analysis and visualization of car crash data, to identify the critical pre-crash scenarios at T- and four-legged junctions as a basis for testing the safety of automated driving systems. The presented method employs k-medoids to cluster historical junction crash data into distinct partitions and then applies the association rules algorithm to each cluster to specify the driving scenarios in more detail. The dataset used consists of 1056 junction crashes in the UK, which were exported from the in-depth "On-the-Spot" database. The study resulted in thirteen crash clusters for T-junctions, and six crash clusters for crossroads. Association rules revealed common crash characteristics, which were the basis for the scenario descriptions. The results support existing findings on road junction accidents and provide benchmark situations for safety performance tests in order to reduce the possible number parameter combinations. Copyright © 2017 Elsevier Ltd. All rights reserved.

  9. An Energy-Efficient Cluster-Based Vehicle Detection on Road Network Using Intention Numeration Method

    Directory of Open Access Journals (Sweden)

    Deepa Devasenapathy

    2015-01-01

    Full Text Available The traffic in the road network is progressively increasing at a greater extent. Good knowledge of network traffic can minimize congestions using information pertaining to road network obtained with the aid of communal callers, pavement detectors, and so on. Using these methods, low featured information is generated with respect to the user in the road network. Although the existing schemes obtain urban traffic information, they fail to calculate the energy drain rate of nodes and to locate equilibrium between the overhead and quality of the routing protocol that renders a great challenge. Thus, an energy-efficient cluster-based vehicle detection in road network using the intention numeration method (CVDRN-IN is developed. Initially, sensor nodes that detect a vehicle are grouped into separate clusters. Further, we approximate the strength of the node drain rate for a cluster using polynomial regression function. In addition, the total node energy is estimated by taking the integral over the area. Finally, enhanced data aggregation is performed to reduce the amount of data transmission using digital signature tree. The experimental performance is evaluated with Dodgers loop sensor data set from UCI repository and the performance evaluation outperforms existing work on energy consumption, clustering efficiency, and node drain rate.

  10. An energy-efficient cluster-based vehicle detection on road network using intention numeration method.

    Science.gov (United States)

    Devasenapathy, Deepa; Kannan, Kathiravan

    2015-01-01

    The traffic in the road network is progressively increasing at a greater extent. Good knowledge of network traffic can minimize congestions using information pertaining to road network obtained with the aid of communal callers, pavement detectors, and so on. Using these methods, low featured information is generated with respect to the user in the road network. Although the existing schemes obtain urban traffic information, they fail to calculate the energy drain rate of nodes and to locate equilibrium between the overhead and quality of the routing protocol that renders a great challenge. Thus, an energy-efficient cluster-based vehicle detection in road network using the intention numeration method (CVDRN-IN) is developed. Initially, sensor nodes that detect a vehicle are grouped into separate clusters. Further, we approximate the strength of the node drain rate for a cluster using polynomial regression function. In addition, the total node energy is estimated by taking the integral over the area. Finally, enhanced data aggregation is performed to reduce the amount of data transmission using digital signature tree. The experimental performance is evaluated with Dodgers loop sensor data set from UCI repository and the performance evaluation outperforms existing work on energy consumption, clustering efficiency, and node drain rate.

  11. Research on the method of information system risk state estimation based on clustering particle filter

    Science.gov (United States)

    Cui, Jia; Hong, Bei; Jiang, Xuepeng; Chen, Qinghua

    2017-05-01

    With the purpose of reinforcing correlation analysis of risk assessment threat factors, a dynamic assessment method of safety risks based on particle filtering is proposed, which takes threat analysis as the core. Based on the risk assessment standards, the method selects threat indicates, applies a particle filtering algorithm to calculate influencing weight of threat indications, and confirms information system risk levels by combining with state estimation theory. In order to improve the calculating efficiency of the particle filtering algorithm, the k-means cluster algorithm is introduced to the particle filtering algorithm. By clustering all particles, the author regards centroid as the representative to operate, so as to reduce calculated amount. The empirical experience indicates that the method can embody the relation of mutual dependence and influence in risk elements reasonably. Under the circumstance of limited information, it provides the scientific basis on fabricating a risk management control strategy.

  12. Research on the method of information system risk state estimation based on clustering particle filter

    Directory of Open Access Journals (Sweden)

    Cui Jia

    2017-05-01

    Full Text Available With the purpose of reinforcing correlation analysis of risk assessment threat factors, a dynamic assessment method of safety risks based on particle filtering is proposed, which takes threat analysis as the core. Based on the risk assessment standards, the method selects threat indicates, applies a particle filtering algorithm to calculate influencing weight of threat indications, and confirms information system risk levels by combining with state estimation theory. In order to improve the calculating efficiency of the particle filtering algorithm, the k-means cluster algorithm is introduced to the particle filtering algorithm. By clustering all particles, the author regards centroid as the representative to operate, so as to reduce calculated amount. The empirical experience indicates that the method can embody the relation of mutual dependence and influence in risk elements reasonably. Under the circumstance of limited information, it provides the scientific basis on fabricating a risk management control strategy.

  13. Water Quality Evaluation of the Yellow River Basin Based on Gray Clustering Method

    Science.gov (United States)

    Fu, X. Q.; Zou, Z. H.

    2018-03-01

    Evaluating the water quality of 12 monitoring sections in the Yellow River Basin comprehensively by grey clustering method based on the water quality monitoring data from the Ministry of environmental protection of China in May 2016 and the environmental quality standard of surface water. The results can reflect the water quality of the Yellow River Basin objectively. Furthermore, the evaluation results are basically the same when compared with the fuzzy comprehensive evaluation method. The results also show that the overall water quality of the Yellow River Basin is good and coincident with the actual situation of the Yellow River basin. Overall, gray clustering method for water quality evaluation is reasonable and feasible and it is also convenient to calculate.

  14. Clustering Multiple Sclerosis Subgroups with Multifractal Methods and Self-Organizing Map Algorithm

    Science.gov (United States)

    Karaca, Yeliz; Cattani, Carlo

    Magnetic resonance imaging (MRI) is the most sensitive method to detect chronic nervous system diseases such as multiple sclerosis (MS). In this paper, Brownian motion Hölder regularity functions (polynomial, periodic (sine), exponential) for 2D image, such as multifractal methods were applied to MR brain images, aiming to easily identify distressed regions, in MS patients. With these regions, we have proposed an MS classification based on the multifractal method by using the Self-Organizing Map (SOM) algorithm. Thus, we obtained a cluster analysis by identifying pixels from distressed regions in MR images through multifractal methods and by diagnosing subgroups of MS patients through artificial neural networks.

  15. Threshold selection for classification of MR brain images by clustering method

    Energy Technology Data Exchange (ETDEWEB)

    Moldovanu, Simona [Faculty of Sciences and Environment, Department of Chemistry, Physics and Environment, Dunărea de Jos University of Galaţi, 47 Domnească St., 800008, Romania, Phone: +40 236 460 780 (Romania); Dumitru Moţoc High School, 15 Milcov St., 800509, Galaţi (Romania); Obreja, Cristian; Moraru, Luminita, E-mail: luminita.moraru@ugal.ro [Faculty of Sciences and Environment, Department of Chemistry, Physics and Environment, Dunărea de Jos University of Galaţi, 47 Domnească St., 800008, Romania, Phone: +40 236 460 780 (Romania)

    2015-12-07

    Given a grey-intensity image, our method detects the optimal threshold for a suitable binarization of MR brain images. In MR brain image processing, the grey levels of pixels belonging to the object are not substantially different from the grey levels belonging to the background. Threshold optimization is an effective tool to separate objects from the background and further, in classification applications. This paper gives a detailed investigation on the selection of thresholds. Our method does not use the well-known method for binarization. Instead, we perform a simple threshold optimization which, in turn, will allow the best classification of the analyzed images into healthy and multiple sclerosis disease. The dissimilarity (or the distance between classes) has been established using the clustering method based on dendrograms. We tested our method using two classes of images: the first consists of 20 T2-weighted and 20 proton density PD-weighted scans from two healthy subjects and from two patients with multiple sclerosis. For each image and for each threshold, the number of the white pixels (or the area of white objects in binary image) has been determined. These pixel numbers represent the objects in clustering operation. The following optimum threshold values are obtained, T = 80 for PD images and T = 30 for T2w images. Each mentioned threshold separate clearly the clusters that belonging of the studied groups, healthy patient and multiple sclerosis disease.

  16. Comparative Study of Powdered Ginger Drink Processed by Different Method:Traditional and using Evaporation Machine

    Science.gov (United States)

    Apriyana, Wuri; Taufika Rosyida, Vita; Nur Hayati, Septi; Darsih, Cici; Dewi Poeloengasih, Crescentiana

    2017-12-01

    Ginger drink is one of the traditional beverage that became one of the products of interest by consumers in Indonesia. This drink is believed to have excellent properties for the health of the body. In this study, we have compared the moisture content, ash content, metal content and the identified compound of product which processed with traditional technique and using an evaporator machine. The results show that both of products fulfilled some parameters of the Indonesian National Standard for the traditional powdered drink. GC-MS analysis data showed the identified compound of both product. The major of hydrocarbon groups that influenced the flavor such as zingiberene, camphene, beta-phelladrine, beta-sesquepelladrine, curcumene, and beta-bisabolene were found higher in ginger drink powder treated with a machine than those processed traditionally.

  17. Symmetrized partial-wave method for density-functional cluster calculations

    International Nuclear Information System (INIS)

    Averill, F.W.; Painter, G.S.

    1994-01-01

    The computational advantage and accuracy of the Harris method is linked to the simplicity and adequacy of the reference-density model. In an earlier paper, we investigated one way the Harris functional could be extended to systems outside the limits of weakly interacting atoms by making the charge density of the interacting atoms self-consistent within the constraints of overlapping spherical atomic densities. In the present study, a method is presented for augmenting the interacting atom charge densities with symmetrized partial-wave expansions on each atomic site. The added variational freedom of the partial waves leads to a scheme capable of giving exact results within a given exchange-correlation approximation while maintaining many of the desirable convergence and stability properties of the original Harris method. Incorporation of the symmetry of the cluster in the partial-wave construction further reduces the level of computational effort. This partial-wave cluster method is illustrated by its application to the dimer C 2 , the hypothetical atomic cluster Fe 6 Al 8 , and the benzene molecule

  18. A Novel Wireless Power Transfer-Based Weighed Clustering Cooperative Spectrum Sensing Method for Cognitive Sensor Networks.

    Science.gov (United States)

    Liu, Xin

    2015-10-30

    In a cognitive sensor network (CSN), the wastage of sensing time and energy is a challenge to cooperative spectrum sensing, when the number of cooperative cognitive nodes (CNs) becomes very large. In this paper, a novel wireless power transfer (WPT)-based weighed clustering cooperative spectrum sensing model is proposed, which divides all the CNs into several clusters, and then selects the most favorable CNs as the cluster heads and allows the common CNs to transfer the received radio frequency (RF) energy of the primary node (PN) to the cluster heads, in order to supply the electrical energy needed for sensing and cooperation. A joint resource optimization is formulated to maximize the spectrum access probability of the CSN, through jointly allocating sensing time and clustering number. According to the resource optimization results, a clustering algorithm is proposed. The simulation results have shown that compared to the traditional model, the cluster heads of the proposed model can achieve more transmission power and there exists optimal sensing time and clustering number to maximize the spectrum access probability.

  19. A Novel Wireless Power Transfer-Based Weighed Clustering Cooperative Spectrum Sensing Method for Cognitive Sensor Networks

    Directory of Open Access Journals (Sweden)

    Xin Liu

    2015-10-01

    Full Text Available In a cognitive sensor network (CSN, the wastage of sensing time and energy is a challenge to cooperative spectrum sensing, when the number of cooperative cognitive nodes (CNs becomes very large. In this paper, a novel wireless power transfer (WPT-based weighed clustering cooperative spectrum sensing model is proposed, which divides all the CNs into several clusters, and then selects the most favorable CNs as the cluster heads and allows the common CNs to transfer the received radio frequency (RF energy of the primary node (PN to the cluster heads, in order to supply the electrical energy needed for sensing and cooperation. A joint resource optimization is formulated to maximize the spectrum access probability of the CSN, through jointly allocating sensing time and clustering number. According to the resource optimization results, a clustering algorithm is proposed. The simulation results have shown that compared to the traditional model, the cluster heads of the proposed model can achieve more transmission power and there exists optimal sensing time and clustering number to maximize the spectrum access probability.

  20. Cluster detection methods applied to the Upper Cape Cod cancer data

    Directory of Open Access Journals (Sweden)

    Ozonoff David

    2005-09-01

    Full Text Available Abstract Background A variety of statistical methods have been suggested to assess the degree and/or the location of spatial clustering of disease cases. However, there is relatively little in the literature devoted to comparison and critique of different methods. Most of the available comparative studies rely on simulated data rather than real data sets. Methods We have chosen three methods currently used for examining spatial disease patterns: the M-statistic of Bonetti and Pagano; the Generalized Additive Model (GAM method as applied by Webster; and Kulldorff's spatial scan statistic. We apply these statistics to analyze breast cancer data from the Upper Cape Cancer Incidence Study using three different latency assumptions. Results The three different latency assumptions produced three different spatial patterns of cases and controls. For 20 year latency, all three methods generally concur. However, for 15 year latency and no latency assumptions, the methods produce different results when testing for global clustering. Conclusion The comparative analyses of real data sets by different statistical methods provides insight into directions for further research. We suggest a research program designed around examining real data sets to guide focused investigation of relevant features using simulated data, for the purpose of understanding how to interpret statistical methods applied to epidemiological data with a spatial component.

  1. Hydraulic transmissivity determination for the groundwater exploration using vertical electric sounding method in comparison to the traditional methods

    International Nuclear Information System (INIS)

    Arshad, M.; Shakoor, A.; Ahmad, M.

    2013-01-01

    An important aquifer characteristic, transmissivity significantly contributes to the development of local and regional groundwater resources and solute transport management. Estimation of this property allows quantitative prediction of the hydraulic response and solute transport of the aquifer to recharge and pumping. This study presents the three techniques, used to compare transmissivity determination by Vertical Electric Sounding (VES) over the traditional techniques. The validation of VES was compared with the old widely used methods such as grain size distribution and pumping test techniques. Grain size distribution analysis was carried out to determine transmissivity. Pumping test was performed to determine transmissivity using the type curves solution for unconfined aquifer and taking into account the delayed yield. In resistivity imaging survey, the soil layers were detected through interpretation of resistivity data. Formation factor for each layer was determined with the relation of aquifer soil resistivity and ground water resistivity. The estimated transmissivities though grain size distribution, pumping test and resistivity survey were 0.588, 0.578 and 0.756m/sup 2//min, respectively. The results emphasized the potential of the resistivity survey for aquifer transmissivity determination. (author)

  2. Applying Clustering Methods in Drawing Maps of Science: Case Study of the Map For Urban Management Science

    Directory of Open Access Journals (Sweden)

    Mohammad Abuei Ardakan

    2010-04-01

    Full Text Available The present paper offers a basic introduction to data clustering and demonstrates the application of clustering methods in drawing maps of science. All approaches towards classification and clustering of information are briefly discussed. Their application to the process of visualization of conceptual information and drawing of science maps are illustrated by reviewing similar researches in this field. By implementing aggregated hierarchical clustering algorithm, which is an algorithm based on complete-link method, the map for urban management science as an emerging, interdisciplinary scientific field is analyzed and reviewed.

  3. Fourth-order perturbative extension of the single-double excitation coupled-cluster method

    International Nuclear Information System (INIS)

    Derevianko, Andrei; Emmons, Erik D.

    2002-01-01

    Fourth-order many-body corrections to matrix elements for atoms with one valence electron are derived. The obtained diagrams are classified using coupled-cluster-inspired separation into contributions from n-particle excitations from the lowest-order wave function. The complete set of fourth-order diagrams involves only connected single, double, and triple excitations and disconnected quadruple excitations. Approximately half of the fourth-order diagrams are not accounted for by the popular coupled-cluster method truncated at single and double excitations (CCSD). Explicit formulas are tabulated for the entire set of fourth-order diagrams missed by the CCSD method and its linearized version, i.e., contributions from connected triple and disconnected quadruple excitations. A partial summation scheme of the derived fourth-order contributions to all orders of perturbation theory is proposed

  4. Cluster models of light nuclei and the method of hyperspherical harmonics: Successes and challenges

    International Nuclear Information System (INIS)

    Danilin, B. V.; Shul'gina, N. B.; Ershov, S. N.; Vaagen, J. S.

    2009-01-01

    Hyperspherical-harmonics method to investigate the lightest nuclei having three-cluster structure is discussed together with recent experiments. Properties of bound states and methods to explore three-body continuum are presented. The challenges created by large neutron excess and halo phenomena are highlighted. Astrophysical aspects of the 7 Li + n → 8 Li + γ reaction and the solar-boron-neutrinos problem are analyzed. Three-cluster structure of highly excited states in 8 Be is shown to be responsible for extreme isospin mixing. Progress in studies of 6 He- and 11 Li-induced inclusive and exclusive nuclear reactions is demonstrated, providing information on the nature of continuum structures of Borromean nuclei.

  5. Application of Different Extraction Methods for Investigation of Nonmetallic Inclusions and Clusters in Steels and Alloys

    Directory of Open Access Journals (Sweden)

    Diana Janis

    2014-01-01

    Full Text Available The characterization of nonmetallic inclusions is of importance for the production of clean steel in order to improve the mechanical properties. In this respect, a three-dimensional (3D investigation is considered to be useful for an accurate evaluation of size, number, morphology of inclusions, and elementary distribution in each inclusion particle. In this study, the application of various extraction methods (chemical extraction/etching by acid or halogen-alcohol solutions, electrolysis, sputtering with glow discharge, and so on for 3D estimation of nonmetallic Al2O3 inclusions and clusters in high-alloyed steels was examined and discussed using an Fe-10 mass% Ni alloy and an 18/8 stainless steel deoxidized with Al. Advantages and limitations of different extraction methods for 3D investigations of inclusions and clusters were discussed in comparison to conventional two-dimensional (2D observations on a polished cross section of metal samples.

  6. A New Waveform Signal Processing Method Based on Adaptive Clustering-Genetic Algorithms

    International Nuclear Information System (INIS)

    Noha Shaaban; Fukuzo Masuda; Hidetsugu Morota

    2006-01-01

    We present a fast digital signal processing method for numerical analysis of individual pulses from CdZnTe compound semiconductor detectors. Using Maxi-Mini Distance Algorithm and Genetic Algorithms based discrimination technique. A parametric approach has been used for classifying the discriminated waveforms into a set of clusters each has a similar signal shape with a corresponding pulse height spectrum. A corrected total pulse height spectrum was obtained by applying a normalization factor for the full energy peak for each cluster with a highly improvements in the energy spectrum characteristics. This method applied successfully for both simulated and real measured data, it can be applied to any detector suffers from signal shape variation. (authors)

  7. The IMACS Cluster Building Survey. I. Description of the Survey and Analysis Methods

    Science.gov (United States)

    Oemler Jr., Augustus; Dressler, Alan; Gladders, Michael G.; Rigby, Jane R.; Bai, Lei; Kelson, Daniel; Villanueva, Edward; Fritz, Jacopo; Rieke, George; Poggianti, Bianca M.; hide

    2013-01-01

    The IMACS Cluster Building Survey uses the wide field spectroscopic capabilities of the IMACS spectrograph on the 6.5 m Baade Telescope to survey the large-scale environment surrounding rich intermediate-redshift clusters of galaxies. The goal is to understand the processes which may be transforming star-forming field galaxies into quiescent cluster members as groups and individual galaxies fall into the cluster from the surrounding supercluster. This first paper describes the survey: the data taking and reduction methods. We provide new calibrations of star formation rates (SFRs) derived from optical and infrared spectroscopy and photometry. We demonstrate that there is a tight relation between the observed SFR per unit B luminosity, and the ratio of the extinctions of the stellar continuum and the optical emission lines.With this, we can obtain accurate extinction-corrected colors of galaxies. Using these colors as well as other spectral measures, we determine new criteria for the existence of ongoing and recent starbursts in galaxies.

  8. THE IMACS CLUSTER BUILDING SURVEY. I. DESCRIPTION OF THE SURVEY AND ANALYSIS METHODS

    Energy Technology Data Exchange (ETDEWEB)

    Oemler, Augustus Jr.; Dressler, Alan; Kelson, Daniel; Villanueva, Edward [Observatories of the Carnegie Institution for Science, 813 Santa Barbara St., Pasadena, CA 91101-1292 (United States); Gladders, Michael G. [Department of Astronomy and Astrophysics, University of Chicago, Chicago, IL 60637 (United States); Rigby, Jane R. [Observational Cosmology Lab, NASA Goddard Space Flight Center, Greenbelt, MD 20771 (United States); Bai Lei [Department of Astronomy and Astrophysics, University of Toronto, 50 St. George Street, Toronto, ON M5S 3H4 (Canada); Fritz, Jacopo [Sterrenkundig Observatorium, Universiteit Gent, Krijgslaan 281 S9, B-9000 Gent (Belgium); Rieke, George [Steward Observatory, University of Arizona, Tucson, AZ 8572 (United States); Poggianti, Bianca M.; Vulcani, Benedetta, E-mail: oemler@obs.carnegiescience.edu [INAF-Osservatorio Astronomico di Padova, Vicolo dell' Osservatorio 5, I-35122 Padova (Italy)

    2013-06-10

    The IMACS Cluster Building Survey uses the wide field spectroscopic capabilities of the IMACS spectrograph on the 6.5 m Baade Telescope to survey the large-scale environment surrounding rich intermediate-redshift clusters of galaxies. The goal is to understand the processes which may be transforming star-forming field galaxies into quiescent cluster members as groups and individual galaxies fall into the cluster from the surrounding supercluster. This first paper describes the survey: the data taking and reduction methods. We provide new calibrations of star formation rates (SFRs) derived from optical and infrared spectroscopy and photometry. We demonstrate that there is a tight relation between the observed SFR per unit B luminosity, and the ratio of the extinctions of the stellar continuum and the optical emission lines. With this, we can obtain accurate extinction-corrected colors of galaxies. Using these colors as well as other spectral measures, we determine new criteria for the existence of ongoing and recent starbursts in galaxies.

  9. Comparison of cluster-based and source-attribution methods for estimating transmission risk using large HIV sequence databases.

    Science.gov (United States)

    Le Vu, Stéphane; Ratmann, Oliver; Delpech, Valerie; Brown, Alison E; Gill, O Noel; Tostevin, Anna; Fraser, Christophe; Volz, Erik M

    2018-06-01

    Phylogenetic clustering of HIV sequences from a random sample of patients can reveal epidemiological transmission patterns, but interpretation is hampered by limited theoretical support and statistical properties of clustering analysis remain poorly understood. Alternatively, source attribution methods allow fitting of HIV transmission models and thereby quantify aspects of disease transmission. A simulation study was conducted to assess error rates of clustering methods for detecting transmission risk factors. We modeled HIV epidemics among men having sex with men and generated phylogenies comparable to those that can be obtained from HIV surveillance data in the UK. Clustering and source attribution approaches were applied to evaluate their ability to identify patient attributes as transmission risk factors. We find that commonly used methods show a misleading association between cluster size or odds of clustering and covariates that are correlated with time since infection, regardless of their influence on transmission. Clustering methods usually have higher error rates and lower sensitivity than source attribution method for identifying transmission risk factors. But neither methods provide robust estimates of transmission risk ratios. Source attribution method can alleviate drawbacks from phylogenetic clustering but formal population genetic modeling may be required to estimate quantitative transmission risk factors. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

  10. Thermodynamics of non-ideal QGP using Mayers cluster expansion method

    International Nuclear Information System (INIS)

    Prasanth, J.P; Simji, P.; Bannur, Vishnu M.

    2013-01-01

    The Quark gluon plasma (QGP) is the state in which the individual hadrons dissolve into a system of free (or almost free) quarks and gluons in strongly compressed system at high temperature. The present paper aims to calculate the critical temperature at which a non-ideal three quark plasma condenses into droplet of three quarks (i.e., into a liquid of baryons) using Mayers cluster expansion method

  11. GLOBAL CLASSIFICATION OF DERMATITIS DISEASE WITH K-MEANS CLUSTERING IMAGE SEGMENTATION METHODS

    OpenAIRE

    Prafulla N. Aerkewar1 & Dr. G. H. Agrawal2

    2018-01-01

    The objective of this paper to presents a global technique for classification of different dermatitis disease lesions using the process of k-Means clustering image segmentation method. The word global is used such that the all dermatitis disease having skin lesion on body are classified in to four category using k-means image segmentation and nntool of Matlab. Through the image segmentation technique and nntool can be analyze and study the segmentation properties of skin lesions occurs in...

  12. 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

  13. Dynamic Fuzzy Clustering Method for Decision Support in Electricity Markets Negotiation

    Directory of Open Access Journals (Sweden)

    Ricardo FAIA

    2016-10-01

    Full Text Available Artificial Intelligence (AI methods contribute to the construction of systems where there is a need to automate the tasks. They are typically used for problems that have a large response time, or when a mathematical method cannot be used to solve the problem. However, the application of AI brings an added complexity to the development of such applications. AI has been frequently applied in the power systems field, namely in Electricity Markets (EM. In this area, AI applications are essentially used to forecast / estimate the prices of electricity or to search for the best opportunity to sell the product. This paper proposes a clustering methodology that is combined with fuzzy logic in order to perform the estimation of EM prices. The proposed method is based on the application of a clustering methodology that groups historic energy contracts according to their prices’ similarity. The optimal number of groups is automatically calculated taking into account the preference for the balance between the estimation error and the number of groups. The centroids of each cluster are used to define a dynamic fuzzy variable that approximates the tendency of contracts’ history. The resulting fuzzy variable allows estimating expected prices for contracts instantaneously and approximating missing values in the historic contracts.

  14. Using hierarchical clustering methods to classify motor activities of COPD patients from wearable sensor data

    Directory of Open Access Journals (Sweden)

    Reilly John J

    2005-06-01

    Full Text Available Abstract Background Advances in miniature sensor technology have led to the development of wearable systems that allow one to monitor motor activities in the field. A variety of classifiers have been proposed in the past, but little has been done toward developing systematic approaches to assess the feasibility of discriminating the motor tasks of interest and to guide the choice of the classifier architecture. Methods A technique is introduced to address this problem according to a hierarchical framework and its use is demonstrated for the application of detecting motor activities in patients with chronic obstructive pulmonary disease (COPD undergoing pulmonary rehabilitation. Accelerometers were used to collect data for 10 different classes of activity. Features were extracted to capture essential properties of the data set and reduce the dimensionality of the problem at hand. Cluster measures were utilized to find natural groupings in the data set and then construct a hierarchy of the relationships between clusters to guide the process of merging clusters that are too similar to distinguish reliably. It provides a means to assess whether the benefits of merging for performance of a classifier outweigh the loss of resolution incurred through merging. Results Analysis of the COPD data set demonstrated that motor tasks related to ambulation can be reliably discriminated from tasks performed in a seated position with the legs in motion or stationary using two features derived from one accelerometer. Classifying motor tasks within the category of activities related to ambulation requires more advanced techniques. While in certain cases all the tasks could be accurately classified, in others merging clusters associated with different motor tasks was necessary. When merging clusters, it was found that the proposed method could lead to more than 12% improvement in classifier accuracy while retaining resolution of 4 tasks. Conclusion Hierarchical

  15. A Comparison of Kernel Equating and Traditional Equipercentile Equating Methods and the Parametric Bootstrap Methods for Estimating Standard Errors in Equipercentile Equating

    Science.gov (United States)

    Choi, Sae Il

    2009-01-01

    This study used simulation (a) to compare the kernel equating method to traditional equipercentile equating methods under the equivalent-groups (EG) design and the nonequivalent-groups with anchor test (NEAT) design and (b) to apply the parametric bootstrap method for estimating standard errors of equating. A two-parameter logistic item response…

  16. A study of several CAD methods for classification of clustered microcalcifications

    Science.gov (United States)

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

    2005-04-01

    In this paper we investigate several state-of-the-art machine-learning methods for automated classification of clustered microcalcifications (MCs), aimed to assisting radiologists for more accurate diagnosis of breast cancer in a computer-aided diagnosis (CADx) scheme. The methods we consider include: support vector machine (SVM), kernel Fisher discriminant (KFD), and committee machines (ensemble averaging and AdaBoost), most of which have been developed recently in statistical learning theory. We formulate differentiation of malignant from benign MCs as a supervised learning problem, and apply these learning methods to develop the classification algorithms. As input, these methods use image features automatically extracted from clustered MCs. We test these methods using a database of 697 clinical mammograms from 386 cases, which include a wide spectrum of difficult-to-classify cases. We use receiver operating characteristic (ROC) analysis to evaluate and compare the classification performance by the different methods. In addition, we also investigate how to combine information from multiple-view mammograms of the same case so that the best decision can be made by a classifier. In our experiments, the kernel-based methods (i.e., SVM, KFD) yield the best performance, significantly outperforming a well-established CADx approach based on neural network learning.

  17. The Use Potential of Traditional Building Materials for the Realization of Structures by Modern Methods of Construction

    Science.gov (United States)

    Spišáková, Marcela; Mačková, Daniela

    2015-11-01

    The sustainable building has taken off in recent years with many investors looking for new and different methods of construction. The traditional building materials can be made out of natural materials, while others can help to lower energy costs of the occupant once built. Regardless of what the goal of the investor is, traditional building materials and their use is on the rise. The submitted paper provides an overview of natural building materials and possible modern building systems using these construction materials. Based on the questionnaire survey is defined the use potential of traditional building materials for the realization of the construction by methods of modern constructions and then are determined the drivers and barriers of traditional materials through using modern methods of construction. Considering the analysis of the achieved results, we can identify the gaps in the construction market in Slovakia and also to assess the perception of potential investors in the field of traditional building materials use, which is the purpose of submitted paper.

  18. The Use Potential of Traditional Building Materials for the Realization of Structures by Modern Methods of Construction

    Directory of Open Access Journals (Sweden)

    Spišáková Marcela

    2015-11-01

    Full Text Available The sustainable building has taken off in recent years with many investors looking for new and different methods of construction. The traditional building materials can be made out of natural materials, while others can help to lower energy costs of the occupant once built. Regardless of what the goal of the investor is, traditional building materials and their use is on the rise. The submitted paper provides an overview of natural building materials and possible modern building systems using these construction materials. Based on the questionnaire survey is defined the use potential of traditional building materials for the realization of the construction by methods of modern constructions and then are determined the drivers and barriers of traditional materials through using modern methods of construction. Considering the analysis of the achieved results, we can identify the gaps in the construction market in Slovakia and also to assess the perception of potential investors in the field of traditional building materials use, which is the purpose of submitted paper.

  19. 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)

  20. Parity among interpretation methods of MLEE patterns and disparity among clustering methods in epidemiological typing of Candida albicans.

    Science.gov (United States)

    Boriollo, Marcelo Fabiano Gomes; Rosa, Edvaldo Antonio Ribeiro; Gonçalves, Reginaldo Bruno; Höfling, José Francisco

    2006-03-01

    The typing of C. albicans by MLEE (multilocus enzyme electrophoresis) is dependent on the interpretation of enzyme electrophoretic patterns, and the study of the epidemiological relationships of these yeasts can be conducted by cluster analysis. Therefore, the aims of the present study were to first determine the discriminatory power of genetic interpretation (deduction of the allelic composition of diploid organisms) and numerical interpretation (mere determination of the presence and absence of bands) of MLEE patterns, and then to determine the concordance (Pearson product-moment correlation coefficient) and similarity (Jaccard similarity coefficient) of the groups of strains generated by three cluster analysis models, and the discriminatory power of such models as well [model A: genetic interpretation, genetic distance matrix of Nei (d(ij)) and UPGMA dendrogram; model B: genetic interpretation, Dice similarity matrix (S(D1)) and UPGMA dendrogram; model C: numerical interpretation, Dice similarity matrix (S(D2)) and UPGMA dendrogram]. MLEE was found to be a powerful and reliable tool for the typing of C. albicans due to its high discriminatory power (>0.9). Discriminatory power indicated that numerical interpretation is a method capable of discriminating a greater number of strains (47 versus 43 subtypes), but also pointed to model B as a method capable of providing a greater number of groups, suggesting its use for the typing of C. albicans by MLEE and cluster analysis. Very good agreement was only observed between the elements of the matrices S(D1) and S(D2), but a large majority of the groups generated in the three UPGMA dendrograms showed similarity S(J) between 4.8% and 75%, suggesting disparities in the conclusions obtained by the cluster assays.

  1. Herd Clustering: A synergistic data clustering approach using collective intelligence

    KAUST Repository

    Wong, Kachun

    2014-10-01

    Traditional data mining methods emphasize on analytical abilities to decipher data, assuming that data are static during a mining process. We challenge this assumption, arguing that we can improve the analysis by vitalizing data. In this paper, this principle is used to develop a new clustering algorithm. Inspired by herd behavior, the clustering method is a synergistic approach using collective intelligence called Herd Clustering (HC). The novel part is laid in its first stage where data instances are represented by moving particles. Particles attract each other locally and form clusters by themselves as shown in the case studies reported. To demonstrate its effectiveness, the performance of HC is compared to other state-of-the art clustering methods on more than thirty datasets using four performance metrics. An application for DNA motif discovery is also conducted. The results support the effectiveness of HC and thus the underlying philosophy. © 2014 Elsevier B.V.

  2. A quasiparticle-based multi-reference coupled-cluster method.

    Science.gov (United States)

    Rolik, Zoltán; Kállay, Mihály

    2014-10-07

    The purpose of this paper is to introduce a quasiparticle-based multi-reference coupled-cluster (MRCC) approach. The quasiparticles are introduced via a unitary transformation which allows us to represent a complete active space reference function and other elements of an orthonormal multi-reference (MR) basis in a determinant-like form. The quasiparticle creation and annihilation operators satisfy the fermion anti-commutation relations. On the basis of these quasiparticles, a generalization of the normal-ordered operator products for the MR case can be introduced as an alternative to the approach of Mukherjee and Kutzelnigg [Recent Prog. Many-Body Theor. 4, 127 (1995); Mukherjee and Kutzelnigg, J. Chem. Phys. 107, 432 (1997)]. Based on the new normal ordering any quasiparticle-based theory can be formulated using the well-known diagram techniques. Beyond the general quasiparticle framework we also present a possible realization of the unitary transformation. The suggested transformation has an exponential form where the parameters, holding exclusively active indices, are defined in a form similar to the wave operator of the unitary coupled-cluster approach. The definition of our quasiparticle-based MRCC approach strictly follows the form of the single-reference coupled-cluster method and retains several of its beneficial properties. Test results for small systems are presented using a pilot implementation of the new approach and compared to those obtained by other MR methods.

  3. Clustering method for counting passengers getting in a bus with single camera

    Science.gov (United States)

    Yang, Tao; Zhang, Yanning; Shao, Dapei; Li, Ying

    2010-03-01

    Automatic counting of passengers is very important for both business and security applications. We present a single-camera-based vision system that is able to count passengers in a highly crowded situation at the entrance of a traffic bus. The unique characteristics of the proposed system include, First, a novel feature-point-tracking- and online clustering-based passenger counting framework, which performs much better than those of background-modeling-and foreground-blob-tracking-based methods. Second, a simple and highly accurate clustering algorithm is developed that projects the high-dimensional feature point trajectories into a 2-D feature space by their appearance and disappearance times and counts the number of people through online clustering. Finally, all test video sequences in the experiment are captured from a real traffic bus in Shanghai, China. The results show that the system can process two 320×240 video sequences at a frame rate of 25 fps simultaneously, and can count passengers reliably in various difficult scenarios with complex interaction and occlusion among people. The method achieves high accuracy rates up to 96.5%.

  4. A New Cluster Analysis-Marker-Controlled Watershed Method for Separating Particles of Granular Soils.

    Science.gov (United States)

    Alam, Md Ferdous; Haque, Asadul

    2017-10-18

    An accurate determination of particle-level fabric of granular soils from tomography data requires a maximum correct separation of particles. The popular marker-controlled watershed separation method is widely used to separate particles. However, the watershed method alone is not capable of producing the maximum separation of particles when subjected to boundary stresses leading to crushing of particles. In this paper, a new separation method, named as Monash Particle Separation Method (MPSM), has been introduced. The new method automatically determines the optimal contrast coefficient based on cluster evaluation framework to produce the maximum accurate separation outcomes. Finally, the particles which could not be separated by the optimal contrast coefficient were separated by integrating cuboid markers generated from the clustering by Gaussian mixture models into the routine watershed method. The MPSM was validated on a uniformly graded sand volume subjected to one-dimensional compression loading up to 32 MPa. It was demonstrated that the MPSM is capable of producing the best possible separation of particles required for the fabric analysis.

  5. application of single-linkage clustering method in the analysis of ...

    African Journals Online (AJOL)

    Admin

    ANALYSIS OF GROWTH RATE OF GROSS DOMESTIC PRODUCT. (GDP) AT ... The end result of the algorithm is a tree of clusters called a dendrogram, which shows how the clusters are ..... Number of cluster sum from from observations of ...

  6. Acupuncture as a Complementary Method of Traditional Psoriasis Treatment: Myth or Reality?

    Science.gov (United States)

    Mahović, Darija; Mrsić, Fanika

    2016-08-01

    Dear Editor, the practitioners of traditional Chinese medicine described psoriasis some 2000 years ago (1). Psoriasis vulgaris is a common, chronic inflammatory skin disease whose worldwide prevalence ranges from 0.1-3% (2,3). Understanding the role of the immune system in psoriasis and the interplay between the innate and adaptive immune system has helped to manage this complex disease, which affects patients far beyond the skin changes themselves (2). In addition to the usual and widely accepted methods of treatment of psoriasis, including topical therapies, phototherapy, and conventional and biological systemic therapies, data can be found in the literature that suggest a favorable effect of acupuncture on the course of psoriasis (4,5). Despite that, this complementary method of traditional treatment of various diseases is not yet widely accepted worldwide. According to the World Health Organization (WHO), acupuncture has been an officially recognized method of treatment for more than 50 diseases from 1979 (5). At the Department of Neurology at the University Hospital Center Zagreb, acupuncture has been used since 2011 for the treatment of various types of headaches, trigeminal neuralgia, and spinal pain syndromes. We report the case of a patient with a known history of psoriasis who was treated for chronic migraines with acupuncture. The 49-year-old female patient was examined for headache of a pulsating character that she had had for 16 years. The headache was mainly located on the left side of head and accompanied by nausea, vomiting, and both photophobia and phonophobia, and there was a worsening of symptoms upon exertion. The headaches were occurring once a week with an average duration of 2-3 continuous days. The patient also had frequent mild headaches. Additionally, the patient was diagnosed with psoriasis at the age of 29 and was occasionally treated with phototherapy. Systemic therapy for psoriasis had not been given to the patient thus far. After the

  7. A novel intrusion detection method based on OCSVM and K-means recursive clustering

    Directory of Open Access Journals (Sweden)

    Leandros A. Maglaras

    2015-01-01

    Full Text Available In this paper we present an intrusion detection module capable of detecting malicious network traffic in a SCADA (Supervisory Control and Data Acquisition system, based on the combination of One-Class Support Vector Machine (OCSVM with RBF kernel and recursive k-means clustering. Important parameters of OCSVM, such as Gaussian width o and parameter v affect the performance of the classifier. Tuning of these parameters is of great importance in order to avoid false positives and over fitting. The combination of OCSVM with recursive k- means clustering leads the proposed intrusion detection module to distinguish real alarms from possible attacks regardless of the values of parameters o and v, making it ideal for real-time intrusion detection mechanisms for SCADA systems. Extensive simulations have been conducted with datasets extracted from small and medium sized HTB SCADA testbeds, in order to compare the accuracy, false alarm rate and execution time against the base line OCSVM method.

  8. New Target for an Old Method: Hubble Measures Globular Cluster Parallax

    Science.gov (United States)

    Hensley, Kerry

    2018-05-01

    Measuring precise distances to faraway objects has long been a challenge in astrophysics. Now, one of the earliest techniques used to measure the distance to astrophysical objects has been applied to a metal-poor globular cluster for the first time.A Classic TechniqueAn artists impression of the European Space Agencys Gaia spacecraft. Gaia is on track to map the positions and motions of a billion stars. [ESA]Distances to nearby stars are often measured using the parallax technique tracing the tiny apparent motion of a target star against the background of more distant stars as Earth orbits the Sun. This technique has come a long way since it was first used in the 1800s to measure the distance to stars a few tens of light-years away; with the advent of space observatories like Hipparcos and Gaia, parallax can now be used to map the positions of stars out to thousands of light-years.Precise distance measurements arent only important for setting the scale of the universe, however; they can also help us better understand stellar evolution over the course of cosmic history. Stellar evolution models are often anchored to a reference star cluster, the properties of which must be known precisely. These precise properties can be readily determined for young, nearby open clusters using parallax measurements. But stellar evolution models that anchor on themore-distant, ancient, metal-poor globular clusters have been hampered by theless-precise indirect methods used tomeasure distance to these faraway clusters until now.Top: An image of NGC 6397 overlaid with the area scanned by Hubble (dashed green) and the footprint of the camera (solid green). The blue ellipse represents the parallax motion of a star in the cluster, exaggerated by a factor of ten thousand. Bottom: An example scan from this field. [Adapted from Brown et al. 2018]New Measurement to an Old ClusterThomas Brown (Space Telescope Science Institute) and collaborators used the Hubble Space Telescope todetermine the

  9. Traditional versus Contemporary Goals and Methods in Accounting Education: Bridging the Gap with Cooperative Learning.

    Science.gov (United States)

    Lindquist, Tim M.

    1995-01-01

    In groups, 49 accounting students completed a 5-week analysis of audit reporting issues using cooperative learning. Positive student reactions and achievement suggested that contemporary active learning approaches are compatible with the traditional accounting goal of preparing for the Certified Public Accountants examination. (SK)

  10. Current Status of Surgical Planning for Orthognathic Surgery: Traditional Methods versus 3D Surgical Planning

    Directory of Open Access Journals (Sweden)

    Jeffrey A. Hammoudeh, MD, DDS

    2015-02-01

    Conclusions: It is our opinion that virtual model surgery will displace and replace traditional model surgery as it will become cost and time effective in both the private and academic setting for practitioners providing orthognathic surgical care in cleft and noncleft patients.

  11. A Follow-up Study of Two Methods of Teaching Mathematics: Traditional versus New Math

    Science.gov (United States)

    Walton, Gene A.; And Others

    1977-01-01

    When high school mathematics grades and test scores were analyzed, findings showed that high- and middle-ability students who had a modern mathematics course in the seventh grade received significantly higher grades in Algebra I, II, III, and Geometry than did students who had a traditional seventh grade mathematics course. (DT)

  12. A Comparison of Traditional and Cooperative Learning Methods in Online Learning

    Science.gov (United States)

    Kupczynski, Lori; Mundy, Marie-Anne; Ruiz, Alberto

    2013-01-01

    The purpose of this study was to examine the effects of the Community of Inquiry framework through an in-depth examination of learning comprised of teaching, social and cognitive presence in traditional versus cooperative online teaching at a community college. A total of 21 students participated in this study, with approximately 45% having taken…

  13. Consumers' Kansei Needs Clustering Method for Product Emotional Design Based on Numerical Design Structure Matrix and Genetic Algorithms.

    Science.gov (United States)

    Yang, Yan-Pu; Chen, Deng-Kai; Gu, Rong; Gu, Yu-Feng; Yu, Sui-Huai

    2016-01-01

    Consumers' Kansei needs reflect their perception about a product and always consist of a large number of adjectives. Reducing the dimension complexity of these needs to extract primary words not only enables the target product to be explicitly positioned, but also provides a convenient design basis for designers engaging in design work. Accordingly, this study employs a numerical design structure matrix (NDSM) by parameterizing a conventional DSM and integrating genetic algorithms to find optimum Kansei clusters. A four-point scale method is applied to assign link weights of every two Kansei adjectives as values of cells when constructing an NDSM. Genetic algorithms are used to cluster the Kansei NDSM and find optimum clusters. Furthermore, the process of the proposed method is presented. The details of the proposed approach are illustrated using an example of electronic scooter for Kansei needs clustering. The case study reveals that the proposed method is promising for clustering Kansei needs adjectives in product emotional design.

  14. Multiple-Features-Based Semisupervised Clustering DDoS Detection Method

    Directory of Open Access Journals (Sweden)

    Yonghao Gu

    2017-01-01

    Full Text Available DDoS attack stream from different agent host converged at victim host will become very large, which will lead to system halt or network congestion. Therefore, it is necessary to propose an effective method to detect the DDoS attack behavior from the massive data stream. In order to solve the problem that large numbers of labeled data are not provided in supervised learning method, and the relatively low detection accuracy and convergence speed of unsupervised k-means algorithm, this paper presents a semisupervised clustering detection method using multiple features. In this detection method, we firstly select three features according to the characteristics of DDoS attacks to form detection feature vector. Then, Multiple-Features-Based Constrained-K-Means (MF-CKM algorithm is proposed based on semisupervised clustering. Finally, using MIT Laboratory Scenario (DDoS 1.0 data set, we verify that the proposed method can improve the convergence speed and accuracy of the algorithm under the condition of using a small amount of labeled data sets.

  15. A Comparison of Case Study and Traditional Teaching Methods for Improvement of Oral Communication and Critical-Thinking Skills

    Science.gov (United States)

    Noblitt, Lynnette; Vance, Diane E.; Smith, Michelle L. DePoy

    2010-01-01

    This study compares a traditional paper presentation approach and a case study method for the development and improvement of oral communication skills and critical-thinking skills in a class of junior forensic science majors. A rubric for rating performance in these skills was designed on the basis of the oral communication competencies developed…

  16. A Comparative Study on Power Point Presentation and Traditional Lecture Method in Material Understandability, Effectiveness and Attitude

    Science.gov (United States)

    Sewasew, Daniel; Mengestle, Missaye; Abate, Gebeyehu

    2015-01-01

    The aim of this study was to compare PPT and traditional lecture method in material understandability, effectiveness and attitude among university students. Comparative descriptive survey research design was employed to answer the research questions raised. Four hundred and twenty nine participants were selected randomly using stratified sampling…

  17. Traditional Mold Analysis Compared to a DNA-based Method of Mold Analysis with Applications in Asthmatics' Homes

    Science.gov (United States)

    Traditional environmental mold analysis is based-on microscopic observations and counting of mold structures collected from the air on a sticky surface or culturing of molds on growth media for identification and quantification. A DNA-based method of mold analysis called mol...

  18. Field calibration of blowfly-derived DNA against traditional methods for assessing mammal diversity in tropical forests.

    Science.gov (United States)

    Lee, Ping-Shin; Gan, Han Ming; Clements, Gopalasamy Reuben; Wilson, John-James

    2016-11-01

    Mammal diversity assessments based on DNA derived from invertebrates have been suggested as alternatives to assessments based on traditional methods; however, no study has field-tested both approaches simultaneously. In Peninsular Malaysia, we calibrated the performance of mammal DNA derived from blowflies (Diptera: Calliphoridae) against traditional methods used to detect species. We first compared five methods (cage trapping, mist netting, hair trapping, scat collection, and blowfly-derived DNA) in a forest reserve with no recent reports of megafauna. Blowfly-derived DNA and mist netting detected the joint highest number of species (n = 6). Only one species was detected by multiple methods. Compared to the other methods, blowfly-derived DNA detected both volant and non-volant species. In another forest reserve, rich in megafauna, we calibrated blowfly-derived DNA against camera traps. Blowfly-derived DNA detected more species (n = 11) than camera traps (n = 9), with only one species detected by both methods. The rarefaction curve indicated that blowfly-derived DNA would continue to detect more species with greater sampling effort. With further calibration, blowfly-derived DNA may join the list of traditional field methods. Areas for further investigation include blowfly feeding and dispersal biology, primer biases, and the assembly of a comprehensive and taxonomically-consistent DNA barcode reference library.

  19. New method for reconstruction of star spatial distribution in globular clusters and its application to flare stars in Pleiades

    International Nuclear Information System (INIS)

    Kosarev, E.L.

    1980-01-01

    A new method to reconstruct spatial star distribution in globular clusters is presented. The method gives both the estimation of unknown spatial distribution and the probable reconstruction error. This error has statistical origin and depends only on the number of stars in a cluster. The method is applied to reconstruct the spatial density of 441 flare stars in Pleiades. The spatial density has a maximum in the centre of the cluster of about 1.6-2.5 pc -3 and with increasing distance from the center smoothly falls down to zero approximately with the Gaussian law with a scale parameter of 3.5 pc

  20. CORECLUSTER: A Degeneracy Based Graph Clustering Framework

    OpenAIRE

    Giatsidis , Christos; Malliaros , Fragkiskos; Thilikos , Dimitrios M. ,; Vazirgiannis , Michalis

    2014-01-01

    International audience; Graph clustering or community detection constitutes an important task forinvestigating the internal structure of graphs, with a plethora of applications in several domains. Traditional tools for graph clustering, such asspectral methods, typically suffer from high time and space complexity. In thisarticle, we present \\textsc{CoreCluster}, an efficient graph clusteringframework based on the concept of graph degeneracy, that can be used along withany known graph clusteri...

  1. K-Line Patterns’ Predictive Power Analysis Using the Methods of Similarity Match and Clustering

    Directory of Open Access Journals (Sweden)

    Lv Tao

    2017-01-01

    Full Text Available Stock price prediction based on K-line patterns is the essence of candlestick technical analysis. However, there are some disputes on whether the K-line patterns have predictive power in academia. To help resolve the debate, this paper uses the data mining methods of pattern recognition, pattern clustering, and pattern knowledge mining to research the predictive power of K-line patterns. The similarity match model and nearest neighbor-clustering algorithm are proposed for solving the problem of similarity match and clustering of K-line series, respectively. The experiment includes testing the predictive power of the Three Inside Up pattern and Three Inside Down pattern with the testing dataset of the K-line series data of Shanghai 180 index component stocks over the latest 10 years. Experimental results show that (1 the predictive power of a pattern varies a great deal for different shapes and (2 each of the existing K-line patterns requires further classification based on the shape feature for improving the prediction performance.

  2. Festival of Curses: A Traditional Crime Control Method In Edo State –Nigeria

    OpenAIRE

    Rashidi Akanji Okunola; Adediran Daniel Ikuomola

    2016-01-01

    Festivals and ceremonies are part and parcel of African culture, usually in all its pump, merriment and pageantry. However, with the increasing wave of criminal activities in Nigeria especially in Edo state, festivals and ceremonies are being redefined and conceptualized in practice. Only recently a new festival ‘Festival of Curses’ was brought to the fore in combating crime in Edo state. The study therefore seeks to explain the festival as a traditional mechanism in crime control, the nature...

  3. Modified Right Heart Contrast Echocardiography Versus Traditional Method in Diagnosis of Right-to-Left Shunt: A Comparative Study

    OpenAIRE

    Wang, Yi; Zeng, Jie; Yin, Lixue; Zhang, Mei; Hou, Dailun

    2016-01-01

    BACKGROUND: The purpose of this study was to evaluate the reliability, effectiveness, and safety of modified right heart contrast transthoracic echocardiography (cTTE) in comparison with the traditional method. MATERIAL AND METHODS: We performed a modified right heart cTTE using saline mixed with a small sample of patient's own blood. Samples were agitated with varying intensity. This study protocol involved microscopic analysis and patient evaluation. 1. Microscopic analysis: After two contr...

  4. A Novel Method to Predict Genomic Islands Based on Mean Shift Clustering Algorithm.

    Directory of Open Access Journals (Sweden)

    Daniel M de Brito

    Full Text Available Genomic Islands (GIs are regions of bacterial genomes that are acquired from other organisms by the phenomenon of horizontal transfer. These regions are often responsible for many important acquired adaptations of the bacteria, with great impact on their evolution and behavior. Nevertheless, these adaptations are usually associated with pathogenicity, antibiotic resistance, degradation and metabolism. Identification of such regions is of medical and industrial interest. For this reason, different approaches for genomic islands prediction have been proposed. However, none of them are capable of predicting precisely the complete repertory of GIs in a genome. The difficulties arise due to the changes in performance of different algorithms in the face of the variety of nucleotide distribution in different species. In this paper, we present a novel method to predict GIs that is built upon mean shift clustering algorithm. It does not require any information regarding the number of clusters, and the bandwidth parameter is automatically calculated based on a heuristic approach. The method was implemented in a new user-friendly tool named MSGIP--Mean Shift Genomic Island Predictor. Genomes of bacteria with GIs discussed in other papers were used to evaluate the proposed method. The application of this tool revealed the same GIs predicted by other methods and also different novel unpredicted islands. A detailed investigation of the different features related to typical GI elements inserted in these new regions confirmed its effectiveness. Stand-alone and user-friendly versions for this new methodology are available at http://msgip.integrativebioinformatics.me.

  5. A new method to cluster genomes based on cumulative Fourier power spectrum.

    Science.gov (United States)

    Dong, Rui; Zhu, Ziyue; Yin, Changchuan; He, Rong L; Yau, Stephen S-T

    2018-06-20

    Analyzing phylogenetic relationships using mathematical methods has always been of importance in bioinformatics. Quantitative research may interpret the raw biological data in a precise way. Multiple Sequence Alignment (MSA) is used frequently to analyze biological evolutions, but is very time-consuming. When the scale of data is large, alignment methods cannot finish calculation in reasonable time. Therefore, we present a new method using moments of cumulative Fourier power spectrum in clustering the DNA sequences. Each sequence is translated into a vector in Euclidean space. Distances between the vectors can reflect the relationships between sequences. The mapping between the spectra and moment vector is one-to-one, which means that no information is lost in the power spectra during the calculation. We cluster and classify several datasets including Influenza A, primates, and human rhinovirus (HRV) datasets to build up the phylogenetic trees. Results show that the new proposed cumulative Fourier power spectrum is much faster and more accurately than MSA and another alignment-free method known as k-mer. The research provides us new insights in the study of phylogeny, evolution, and efficient DNA comparison algorithms for large genomes. The computer programs of the cumulative Fourier power spectrum are available at GitHub (https://github.com/YaulabTsinghua/cumulative-Fourier-power-spectrum). Copyright © 2018. Published by Elsevier B.V.

  6. Active learning on the ward: outcomes from a comparative trial with traditional methods.

    Science.gov (United States)

    Melo Prado, Hegla; Hannois Falbo, Gilliatt; Rodrigues Falbo, Ana; Natal Figueirôa, José

    2011-03-01

    Academic activity during internship is essentially practical and ward rounds are traditionally considered the cornerstone of clinical education. However, the efficacy and effectiveness of ward rounds for learning purposes have been under-investigated and it is necessary to assess alternative educational paradigms for this activity. This study aimed to compare the educational effectiveness of ward rounds conducted with two different learning methodologies. Student subjects were first tested on 30 true/false questions to assess their initial degree of knowledge on pneumonia and diarrhoea. Afterwards, they attended ward rounds conducted using an active and a traditional learning methodology. The participants were submitted to a second test 48hours later in order to assess knowledge acquisition and were asked to answer two questions about self-directed learning and their opinions on the two learning methodologies used. Seventy-two medical students taking part in a paediatric clinic rotation were enrolled. The active methodology proved to be more effective than the traditional methodology for the three outcomes considered: knowledge acquisition (33 students [45.8%] versus 21 students [29.2%]; p=0.03); self-directed learning (38 students [52.8%] versus 11 students [15.3%]; pmethods (61 students [84.7%] versus 38 students [52.8%]; ptraditional methodology in a ward-based context. This study seems to be valuable in terms of the new evidence it demonstrates on learning methodologies in the context of the ward round. © Blackwell Publishing Ltd 2011.

  7. [A cloud detection algorithm for MODIS images combining Kmeans clustering and multi-spectral threshold method].

    Science.gov (United States)

    Wang, Wei; Song, Wei-Guo; Liu, Shi-Xing; Zhang, Yong-Ming; Zheng, Hong-Yang; Tian, Wei

    2011-04-01

    An improved method for detecting cloud combining Kmeans clustering and the multi-spectral threshold approach is described. On the basis of landmark spectrum analysis, MODIS data is categorized into two major types initially by Kmeans method. The first class includes clouds, smoke and snow, and the second class includes vegetation, water and land. Then a multi-spectral threshold detection is applied to eliminate interference such as smoke and snow for the first class. The method is tested with MODIS data at different time under different underlying surface conditions. By visual method to test the performance of the algorithm, it was found that the algorithm can effectively detect smaller area of cloud pixels and exclude the interference of underlying surface, which provides a good foundation for the next fire detection approach.

  8. Data Clustering on Breast Cancer Data Using Firefly Algorithm with Golden Ratio Method

    Directory of Open Access Journals (Sweden)

    DEMIR, M.

    2015-05-01

    Full Text Available Heuristic methods are problem solving methods. In general, they obtain near-optimal solutions, and they do not take the care of provability of this case. The heuristic methods do not guarantee to obtain the optimal results; however, they guarantee to obtain near-optimal solutions in considerable time. In this paper, an application was performed by using firefly algorithm - one of the heuristic methods. The golden ratio was applied to different steps of firefly algorithm and different parameters of firefly algorithm to develop a new algorithm - called Firefly Algorithm with Golden Ratio (FAGR. It was shown that the golden ratio made firefly algorithm be superior to the firefly algorithm without golden ratio. At this aim, the developed algorithm was applied to WBCD database (breast cancer database to cluster data obtained from breast cancer patients. The highest obtained success rate among all executions is 96% and the highest obtained average success rate in all executions is 94.5%.

  9. An image segmentation method based on fuzzy C-means clustering and Cuckoo search algorithm

    Science.gov (United States)

    Wang, Mingwei; Wan, Youchuan; Gao, Xianjun; Ye, Zhiwei; Chen, Maolin

    2018-04-01

    Image segmentation is a significant step in image analysis and machine vision. Many approaches have been presented in this topic; among them, fuzzy C-means (FCM) clustering is one of the most widely used methods for its high efficiency and ambiguity of images. However, the success of FCM could not be guaranteed because it easily traps into local optimal solution. Cuckoo search (CS) is a novel evolutionary algorithm, which has been tested on some optimization problems and proved to be high-efficiency. Therefore, a new segmentation technique using FCM and blending of CS algorithm is put forward in the paper. Further, the proposed method has been measured on several images and compared with other existing FCM techniques such as genetic algorithm (GA) based FCM and particle swarm optimization (PSO) based FCM in terms of fitness value. Experimental results indicate that the proposed method is robust, adaptive and exhibits the better performance than other methods involved in the paper.

  10. [Method of traditional Chinese medicine formula design based on 3D-database pharmacophore search and patent retrieval].

    Science.gov (United States)

    He, Yu-su; Sun, Zhi-yi; Zhang, Yan-ling

    2014-11-01

    By using the pharmacophore model of mineralocorticoid receptor antagonists as a starting point, the experiment stud- ies the method of traditional Chinese medicine formula design for anti-hypertensive. Pharmacophore models were generated by 3D-QSAR pharmacophore (Hypogen) program of the DS3.5, based on the training set composed of 33 mineralocorticoid receptor antagonists. The best pharmacophore model consisted of two Hydrogen-bond acceptors, three Hydrophobic and four excluded volumes. Its correlation coefficient of training set and test set, N, and CAI value were 0.9534, 0.6748, 2.878, and 1.119. According to the database screening, 1700 active compounds from 86 source plant were obtained. Because of lacking of available anti-hypertensive medi cation strategy in traditional theory, this article takes advantage of patent retrieval in world traditional medicine patent database, in order to design drug formula. Finally, two formulae was obtained for antihypertensive.

  11. Onto-clust--a methodology for combining clustering analysis and ontological methods for identifying groups of comorbidities for developmental disorders.

    Science.gov (United States)

    Peleg, Mor; Asbeh, Nuaman; Kuflik, Tsvi; Schertz, Mitchell

    2009-02-01

    Children with developmental disorders usually exhibit multiple developmental problems (comorbidities). Hence, such diagnosis needs to revolve on developmental disorder groups. Our objective is to systematically identify developmental disorder groups and represent them in an ontology. We developed a methodology that combines two methods (1) a literature-based ontology that we created, which represents developmental disorders and potential developmental disorder groups, and (2) clustering for detecting comorbid developmental disorders in patient data. The ontology is used to interpret and improve clustering results and the clustering results are used to validate the ontology and suggest directions for its development. We evaluated our methodology by applying it to data of 1175 patients from a child development clinic. We demonstrated that the ontology improves clustering results, bringing them closer to an expert generated gold-standard. We have shown that our methodology successfully combines an ontology with a clustering method to support systematic identification and representation of developmental disorder groups.

  12. A comparison of methods for the analysis of binomial clustered outcomes in behavioral research.

    Science.gov (United States)

    Ferrari, Alberto; Comelli, Mario

    2016-12-01

    In behavioral research, data consisting of a per-subject proportion of "successes" and "failures" over a finite number of trials often arise. This clustered binary data are usually non-normally distributed, which can distort inference if the usual general linear model is applied and sample size is small. A number of more advanced methods is available, but they are often technically challenging and a comparative assessment of their performances in behavioral setups has not been performed. We studied the performances of some methods applicable to the analysis of proportions; namely linear regression, Poisson regression, beta-binomial regression and Generalized Linear Mixed Models (GLMMs). We report on a simulation study evaluating power and Type I error rate of these models in hypothetical scenarios met by behavioral researchers; plus, we describe results from the application of these methods on data from real experiments. Our results show that, while GLMMs are powerful instruments for the analysis of clustered binary outcomes, beta-binomial regression can outperform them in a range of scenarios. Linear regression gave results consistent with the nominal level of significance, but was overall less powerful. Poisson regression, instead, mostly led to anticonservative inference. GLMMs and beta-binomial regression are generally more powerful than linear regression; yet linear regression is robust to model misspecification in some conditions, whereas Poisson regression suffers heavily from violations of the assumptions when used to model proportion data. We conclude providing directions to behavioral scientists dealing with clustered binary data and small sample sizes. Copyright © 2016 Elsevier B.V. All rights reserved.

  13. Analytical Energy Gradients for Excited-State Coupled-Cluster Methods

    Science.gov (United States)

    Wladyslawski, Mark; Nooijen, Marcel

    The equation-of-motion coupled-cluster (EOM-CC) and similarity transformed equation-of-motion coupled-cluster (STEOM-CC) methods have been firmly established as accurate and routinely applicable extensions of single-reference coupled-cluster theory to describe electronically excited states. An overview of these methods is provided, with emphasis on the many-body similarity transform concept that is the key to a rationalization of their accuracy. The main topic of the paper is the derivation of analytical energy gradients for such non-variational electronic structure approaches, with an ultimate focus on obtaining their detailed algebraic working equations. A general theoretical framework using Lagrange's method of undetermined multipliers is presented, and the method is applied to formulate the EOM-CC and STEOM-CC gradients in abstract operator terms, following the previous work in [P.G. Szalay, Int. J. Quantum Chem. 55 (1995) 151] and [S.R. Gwaltney, R.J. Bartlett, M. Nooijen, J. Chem. Phys. 111 (1999) 58]. Moreover, the systematics of the Lagrange multiplier approach is suitable for automation by computer, enabling the derivation of the detailed derivative equations through a standardized and direct procedure. To this end, we have developed the SMART (Symbolic Manipulation and Regrouping of Tensors) package of automated symbolic algebra routines, written in the Mathematica programming language. The SMART toolkit provides the means to expand, differentiate, and simplify equations by manipulation of the detailed algebraic tensor expressions directly. The Lagrangian multiplier formulation establishes a uniform strategy to perform the automated derivation in a standardized manner: A Lagrange multiplier functional is constructed from the explicit algebraic equations that define the energy in the electronic method; the energy functional is then made fully variational with respect to all of its parameters, and the symbolic differentiations directly yield the explicit

  14. Socio-economic comparison between traditional and improved cultivation methods in agroforestry systems, East Usambara Mountains, Tanzania.

    Science.gov (United States)

    Reyes, Teija; Quiroz, Roberto; Msikula, Shija

    2005-11-01

    The East Usambara Mountains, recognized as one of the 25 most important biodiversity hot spots in the world, have a high degree of species diversity and endemism that is threatened by increasing human pressure on resources. Traditional slash and burn cultivation in the area is no longer sustainable. However, it is possible to maintain land productivity, decrease land degradation, and improve rural people's livelihood by ameliorating cultivation methods. Improved agroforestry seems to be a very convincing and suitable method for buffer zones of conservation areas. Farmers could receive a reasonable net income from their farm with little investment in terms of time, capital, and labor. By increasing the diversity and production of already existing cultivations, the pressure on natural forests can be diminished. The present study shows a significant gap between traditional cultivation methods and improved agroforestry systems in socio-economic terms. Improved agroforestry systems provide approximately double income per capita in comparison to traditional methods. More intensified cash crop cultivation in the highlands of the East Usambara also results in double income compared to that in the lowlands. However, people are sensitive to risks of changing farming practices. Encouraging farmers to apply better land management and practice sustainable cultivation of cash crops in combination with multipurpose trees would be relevant in improving their economic situation in the relatively short term. The markets of most cash crops are already available. Improved agroforestry methods could ameliorate the living conditions of the local population and protect the natural reserves from human disturbance.

  15. Paleodemographic age-at-death distributions of two Mexican skeletal collections: a comparison of transition analysis and traditional aging methods.

    Science.gov (United States)

    Bullock, Meggan; Márquez, Lourdes; Hernández, Patricia; Ruíz, Fernando

    2013-09-01

    Traditional methods of aging adult skeletons suffer from the problem of age mimicry of the reference collection, as described by Bocquet-Appel and Masset (1982). Transition analysis (Boldsen et al., 2002) is a method of aging adult skeletons that addresses the problem of age mimicry of the reference collection by allowing users to select an appropriate prior probability. In order to evaluate whether transition analysis results in significantly different age estimates for adults, the method was applied to skeletal collections from Postclassic Cholula and Contact-Period Xochimilco. The resulting age-at-death distributions were then compared with age-at-death distributions for the two populations constructed using traditional aging methods. Although the traditional aging methods result in age-at-death distributions with high young adult mortality and few individuals living past the age of 50, the age-at-death distributions constructed using transition analysis indicate that most individuals who lived into adulthood lived past the age of 50. Copyright © 2013 Wiley Periodicals, Inc.

  16. Dancoff factors with partial absorption in cluster geometry by the direct method

    International Nuclear Information System (INIS)

    Rodrigues, Leticia Jenisch; Leite, Sergio de Queiroz Bogado; Vilhena, Marco Tullio de; Bodmann, Bardo Ernest Josef

    2007-01-01

    Accurate analysis of resonance absorption in heterogeneous systems is essential in problems like criticality, breeding ratios and fuel depletion calculations. In compact arrays of fuel rods, resonance absorption is strongly affected by the Dancoff factor, defined in this study as the probability that a neutron emitted from the surface of a fuel element, enters another fuel element without any collision in the moderator or cladding. In the original WIMS code, Black Dancoff factors were computed in cluster geometry by the collision probability method, for each one of the symmetrically distinct fuel pin positions in the cell. Recent improvements to the code include a new routine (PIJM) that was created to incorporate a more efficient scheme for computing the collision matrices. In that routine, each system region is considered individually, minimizing convergence problems and reducing the number of neutron track lines required in the in-plane integrations of the Bickley functions for any given accuracy. In the present work, PIJM is extended to compute Grey Dancoff factors for two-dimensional cylindrical cells in cluster geometry. The effectiveness of the method is accessed by comparing Grey Dancoff factors as calculated by PIJM, with those available in the literature by the Monte Carlo method, for the irregular geometry of the Canadian CANDU37 assembly. Dancoff factors at five symmetrically distinct fuel pin positions are found in very good agreement with the literature results (author)

  17. A robust automatic leukocyte recognition method based on island-clustering texture

    Directory of Open Access Journals (Sweden)

    Xiaoshun Li

    2016-01-01

    Full Text Available A leukocyte recognition method for human peripheral blood smear based on island-clustering texture (ICT is proposed. By analyzing the features of the five typical classes of leukocyte images, a new ICT model is established. Firstly, some feature points are extracted in a gray leukocyte image by mean-shift clustering to be the centers of islands. Secondly, the growing region is employed to create regions of the islands in which the seeds are just these feature points. These islands distribution can describe a new texture. Finally, a distinguished parameter vector of these islands is created as the ICT features by combining the ICT features with the geometric features of the leukocyte. Then the five typical classes of leukocytes can be recognized successfully at the correct recognition rate of more than 92.3% with a total sample of 1310 leukocytes. Experimental results show the feasibility of the proposed method. Further analysis reveals that the method is robust and results can provide important information for disease diagnosis.

  18. An automated three-dimensional detection and segmentation method for touching cells by integrating concave points clustering and random walker algorithm.

    Directory of Open Access Journals (Sweden)

    Yong He

    Full Text Available Characterizing cytoarchitecture is crucial for understanding brain functions and neural diseases. In neuroanatomy, it is an important task to accurately extract cell populations' centroids and contours. Recent advances have permitted imaging at single cell resolution for an entire mouse brain using the Nissl staining method. However, it is difficult to precisely segment numerous cells, especially those cells touching each other. As presented herein, we have developed an automated three-dimensional detection and segmentation method applied to the Nissl staining data, with the following two key steps: 1 concave points clustering to determine the seed points of touching cells; and 2 random walker segmentation to obtain cell contours. Also, we have evaluated the performance of our proposed method with several mouse brain datasets, which were captured with the micro-optical sectioning tomography imaging system, and the datasets include closely touching cells. Comparing with traditional detection and segmentation methods, our approach shows promising detection accuracy and high robustness.

  19. Cultural Heritage Digitalization on Traditional Sundanese Music Instrument Using Augmented Reality Markerless Marker Method

    Directory of Open Access Journals (Sweden)

    Budi Arifitama

    2017-07-01

    Full Text Available Research into cultural heritage which implements augmented reality technology is limited. Most recent research on cultural heritage are limited on storing data and information in the form of databases, this creates a disadvantage for people who wants to see and feel at the same moment on actual cultural heritage objects. This paper, proposes a solution which could merge the existing cultural object with people using augmented reality technology. This technology would preserve traditional instrument in the form of 3D object which can be digitally protected. The result showed that the use of augmented reality on preserving cultural heritage would benefit people who try to protect their culture.

  20. The critical assessment of research traditional and new methods of evaluation

    CERN Document Server

    Bailin, Alan

    2010-01-01

    This book examines the following factors: sponsorship of research, control of the dissemination of research, effects of dominant research paradigms, financial interests of authors, publishers, and editors, role of new technologies (for example, Web 2.0).It is widely accepted among researchers and educators that the peer review process, the reputation of the publisher and examination of the author's credentials are the gold standards for assessing the quality of research and information. However, the traditional gold standards are not sufficient, and the effective evaluation of information req

  1. Science-Technology-Society literacy in college non-majors biology: Comparing problem/case studies based learning and traditional expository methods of instruction

    Science.gov (United States)

    Peters, John S.

    This study used a multiple response model (MRM) on selected items from the Views on Science-Technology-Society (VOSTS) survey to examine science-technology-society (STS) literacy among college non-science majors' taught using Problem/Case Studies Based Learning (PBL/CSBL) and traditional expository methods of instruction. An initial pilot investigation of 15 VOSTS items produced a valid and reliable scoring model which can be used to quantitatively assess student literacy on a variety of STS topics deemed important for informed civic engagement in science related social and environmental issues. The new scoring model allows for the use of parametric inferential statistics to test hypotheses about factors influencing STS literacy. The follow-up cross-institutional study comparing teaching methods employed Hierarchical Linear Modeling (HLM) to model the efficiency and equitability of instructional methods on STS literacy. A cluster analysis was also used to compare pre and post course patterns of student views on the set of positions expressed within VOSTS items. HLM analysis revealed significantly higher instructional efficiency in the PBL/CSBL study group for 4 of the 35 STS attitude indices (characterization of media vs. school science; tentativeness of scientific models; cultural influences on scientific research), and more equitable effects of traditional instruction on one attitude index (interdependence of science and technology). Cluster analysis revealed generally stable patterns of pre to post course views across study groups, but also revealed possible teaching method effects on the relationship between the views expressed within VOSTS items with respect to (1) interdependency of science and technology; (2) anti-technology; (3) socioscientific decision-making; (4) scientific/technological solutions to environmental problems; (5) usefulness of school vs. media characterizations of science; (6) social constructivist vs. objectivist views of theories; (7

  2. Recursive expectation-maximization clustering: A method for identifying buffering mechanisms composed of phenomic modules

    Science.gov (United States)

    Guo, Jingyu; Tian, Dehua; McKinney, Brett A.; Hartman, John L.

    2010-06-01

    of physiological homeostasis. To develop the method, 297 gene deletion strains were selected based on gene-drug interactions with hydroxyurea, an inhibitor of ribonucleotide reductase enzyme activity, which is critical for DNA synthesis. To partition the gene functions, these 297 deletion strains were challenged with growth inhibitory drugs known to target different genes and cellular pathways. Q-HTCP-derived growth curves were used to quantify all gene interactions, and the data were used to test the performance of REMc. Fundamental advantages of REMc include objective assessment of total number of clusters and assignment to each cluster a log-likelihood value, which can be considered an indicator of statistical quality of clusters. To assess the biological quality of clusters, we developed a method called gene ontology information divergence z-score (GOid_z). GOid_z summarizes total enrichment of GO attributes within individual clusters. Using these and other criteria, we compared the performance of REMc to hierarchical and K-means clustering. The main conclusion is that REMc provides distinct efficiencies for mining Q-HTCP data. It facilitates identification of phenomic modules, which contribute to buffering mechanisms that underlie cellular homeostasis and the regulation of phenotypic expression.

  3. A Spectrum Sensing Method Based on Signal Feature and Clustering Algorithm in Cognitive Wireless Multimedia Sensor Networks

    Directory of Open Access Journals (Sweden)

    Yongwei Zhang

    2017-01-01

    Full Text Available In order to solve the problem of difficulty in determining the threshold in spectrum sensing technologies based on the random matrix theory, a spectrum sensing method based on clustering algorithm and signal feature is proposed for Cognitive Wireless Multimedia Sensor Networks. Firstly, the wireless communication signal features are obtained according to the sampling signal covariance matrix. Then, the clustering algorithm is used to classify and test the signal features. Different signal features and clustering algorithms are compared in this paper. The experimental results show that the proposed method has better sensing performance.

  4. Deficiency of the Space Syntax method as an urban design tool in designing traditional urban space and the need for some supplementary methods

    Directory of Open Access Journals (Sweden)

    Hossein Bahrainy

    2015-12-01

    Full Text Available Urban design problems have become so complex that no single designer is able to consider all aspects of a design area simultaneously. Lately the application of computerized and scientific methods have helped designers analyze complex problems. One of these new methods is Space Syntax. The purpose of this study is to first investigate the strengths and weaknesses of this method and then suggest some supplementary methods to cover its pitfalls. On the next phase Space Syntax and supplementary methods will be used to design a pedestrian pathway in the Imamzade Ghasem neighborhood as a traditional context. Space Syntax will identify the existing spatial structure and direct future changes toward its strengthening. The case study reveals that Space Syntax can be successfully used in analysis of traditional spaces, but in order to successfully design a neighborhood in such a complex context, it involves logistical shortcomings which could be eliminated through supplementary methods.

  5. Integration of Qualitative and Quantitative Methods: Building and Interpreting Clusters from Grounded Theory and Discourse Analysis

    Directory of Open Access Journals (Sweden)

    Aldo Merlino

    2007-01-01

    Full Text Available Qualitative methods present a wide spectrum of application possibilities as well as opportunities for combining qualitative and quantitative methods. In the social sciences fruitful theoretical discussions and a great deal of empirical research have taken place. This article introduces an empirical investigation which demonstrates the logic of combining methodologies as well as the collection and interpretation, both sequential as simultaneous, of qualitative and quantitative data. Specifically, the investigation process will be described, beginning with a grounded theory methodology and its combination with the techniques of structural semiotics discourse analysis to generate—in a first phase—an instrument for quantitative measuring and to understand—in a second phase—clusters obtained by quantitative analysis. This work illustrates how qualitative methods allow for the comprehension of the discursive and behavioral elements under study, and how they function as support making sense of and giving meaning to quantitative data. URN: urn:nbn:de:0114-fqs0701219

  6. A comparison of three clustering methods for finding subgroups in MRI, SMS or clinical data: SPSS TwoStep Cluster analysis, Latent Gold and SNOB.

    Science.gov (United States)

    Kent, Peter; Jensen, Rikke K; Kongsted, Alice

    2014-10-02

    There are various methodological approaches to identifying clinically important subgroups and one method is to identify clusters of characteristics that differentiate people in cross-sectional and/or longitudinal data using Cluster Analysis (CA) or Latent Class Analysis (LCA). There is a scarcity of head-to-head comparisons that can inform the choice of which clustering method might be suitable for particular clinical datasets and research questions. Therefore, the aim of this study was to perform a head-to-head comparison of three commonly available methods (SPSS TwoStep CA, Latent Gold LCA and SNOB LCA). The performance of these three methods was compared: (i) quantitatively using the number of subgroups detected, the classification probability of individuals into subgroups, the reproducibility of results, and (ii) qualitatively using subjective judgments about each program's ease of use and interpretability of the presentation of results.We analysed five real datasets of varying complexity in a secondary analysis of data from other research projects. Three datasets contained only MRI findings (n = 2,060 to 20,810 vertebral disc levels), one dataset contained only pain intensity data collected for 52 weeks by text (SMS) messaging (n = 1,121 people), and the last dataset contained a range of clinical variables measured in low back pain patients (n = 543 people). Four artificial datasets (n = 1,000 each) containing subgroups of varying complexity were also analysed testing the ability of these clustering methods to detect subgroups and correctly classify individuals when subgroup membership was known. The results from the real clinical datasets indicated that the number of subgroups detected varied, the certainty of classifying individuals into those subgroups varied, the findings had perfect reproducibility, some programs were easier to use and the interpretability of the presentation of their findings also varied. The results from the artificial datasets

  7. Pattern Classification of Tropical Cyclone Tracks over the Western North Pacific using a Fuzzy Clustering Method

    Science.gov (United States)

    Kim, H.; Ho, C.; Kim, J.

    2008-12-01

    This study presents the pattern classification of tropical cyclone (TC) tracks over the western North Pacific (WNP) basin during the typhoon season (June through October) for 1965-2006 (total 42 years) using a fuzzy clustering method. After the fuzzy c-mean clustering algorithm to the TC trajectory interpolated into 20 segments of equivalent length, we divided the whole tracks into 7 patterns. The optimal number of the fuzzy cluster is determined by several validity measures. The classified TC track patterns represent quite different features in the recurving latitudes, genesis locations, and geographical pathways: TCs mainly forming in east-northern part of the WNP and striking Korean and Japan (C1); mainly forming in west-southern part of the WNP, traveling long pathway, and partly striking Japan (C2); mainly striking Taiwan and East China (C3); traveling near the east coast of Japan (C4); traveling the distant ocean east of Japan (C5); moving toward South China and Vietnam straightly (C6); and forming in the South China Sea (C7). Atmospheric environments related to each cluster show physically consistent with each TC track patterns. The straight track pattern is closely linked to a developed anticyclonic circulation to the north of the TC. It implies that this ridge acts as a steering flow forcing TCs to move to the northwest with a more west-oriented track. By contrast, recurving patterns occur commonly under the influence of the strong anomalous westerlies over the TC pathway but there definitely exist characteristic anomalous circulations over the mid- latitudes by pattern. Some clusters are closely related to the well-known large-scale phenomena. The C1 and C2 are highly related to the ENSO phase: The TCs in the C1 (C2) is more active during La Niña (El Niño). The TC activity in the C3 is associated with the WNP summer monsoon. The TCs in the C4 is more (less) vigorous during the easterly (westerly) phase of the stratospheric quasi-biennial oscillation

  8. Statistical method for determining ages of globular clusters by fitting isochrones

    International Nuclear Information System (INIS)

    Flannery, B.P.; Johnson, B.C.

    1982-01-01

    We describe a statistical procedure to compare models of stellar evolution and atmospheres with color-magnitude diagrams of globular clusters. The isochrone depends on five parameters: m-M, age, [Fe/H], Y, and α, but in practice we can only determine m-M and age for an assumed composition. The technique allows us to determine parameters of the model, their uncertainty, and to assess goodness of fit. We test the method, and evaluate the effect of assumptions on an extensive set of Monte Carlo simulations. We apply the method to extensive observations of NGC 6752 and M5, and to smaller data sets for the clusters M3, M5, M15, and M92. We determine age and m-M for two assumed values of helium Y = (0.2, 0.3), and three values of metallicity with a spread in [Fe/H] of +- 0.3 dex. These result in a spread in age of 5-8 Gyr (1 Gyr = 10 9 yr), and a spread in m-M of 0.5 mag. The mean age is generally younger by 2-3 Gyr than previous estimates. Likely uncertainty associated with an individual fit can be small as 0.4 Gyr. Most importantly, we find that two uncalibratable sources of systematic error make the results suspect. These are uncertainty in the stellar temperatures induced by choice of mixing length, and known errors in stellar atmospheres. These effects could reduce age estimates by an additional 5 Gyr. We conclude that observations do not preclude ages as young as 10 Gyr for globular clusters

  9. Traditional methods used by patients for the management of recurrent aphthous stomatitis.

    Directory of Open Access Journals (Sweden)

    Shruthi Hegde

    2017-12-01

    Results: A total of 326 patients reported with RAS. The study sample consisted of 171 females (52.5% and 155 males (47.5%. In our study 198 subjects (60.7% gave history of receiving treatment and 128 subjects (39.3 % did not receive any kind of treatment. Out of the 198 subjects, 63(31.8% of individuals received conventional treatment, alternative treatments were opted by 85(43% patients and combined treatment modalities were opted by 50(25.2% patients. Over the counter medications were used by 36 (18% patients. Treatment outcome was satisfactory according to 137(69% individuals and treatment was not satisfactory for 61 (31% patients. Conclusion: This study gives insight into the various traditional medicines used in south India for RAS and to the best of our knowledge, this is first study which describes the same. Our study adds new information to the current literature about traditional medications for RAS. [J Complement Med Res 2017; 6(4.000: 364-368

  10. Panel presentation: Should some type of incentive regulation replace traditional methods for regulating LDC's?

    International Nuclear Information System (INIS)

    Farman, R.D.

    1992-01-01

    This paper discusses the wants and fears of gas utility companies with regards to incentive regulation. The idea of replacing the traditional rate-of-return regulation with incentive regulation sound very desirous in that it should provide greater management flexibility, quicker and more streamlined regulatory processes, and utility financial rewards based on how well customer needs are met. However, the main fear is that this could result in arbitrary, inappropriate productivity or efficiency targets, or would embody a risk/reward ratio skewed more heavily toward financial penalties than opportunities to increase earnings. The paper presents some of the obstacles of traditional regulation which include a lack of incentive to minimize operational costs; a lack of incentive to introduce new technology, products, or services; prevent the need for flexibility to compete in contestable markets; and the diversion caused by utility managers having to manage the regulatory process rather than delivering value to customers. The paper concludes by comparing the incentive regulation program used in the telecommunications industry to the natural gas industry to demonstrate why the success of the telecommunications model doesn't apply to the gas utilities incentive model

  11. Traditional Methods which are Known and Applied in order to Achieve Voluntary Abortion by Married Women Living in Elazig.

    Directory of Open Access Journals (Sweden)

    Feyza (Nazik Sevindik

    2007-10-01

    Full Text Available This study have been performed in order to describe traditional methods which are known and applied for achieving voluntary abortion by married women living in downtown of Elazig. 426 women have been selected rely on the fifteen years old and married by the represantive 67500 living women in the downtown Elazig. It has been reached to 417 women at repetetive visits. Mean age of women is 36,39±10,26, first pregnancy years are 19,96±4,99, first birth age is 20,02±6,05. Numbers of avarage pregnancy are 3,61±0,12, numbers of voluntary abortion is 0,32±0,04. Voluntary abortion rate is %18,2. %93 of women have stated that they know at least one traditional abortion method, and %19,7 of women declared that they used traditional abortion methods. %14,9 of them stated that they lift a heavy furniture or goods, while %8,2 drink flu drug and asprin, %11,3 jump rope and jump by shaking from high where, %4,8 put a poultry quill, matchstick and knitting needle into uterus, %3,6 put a mallow or aubergine root into uterus servicks, %2,6 drink a boiled quinine henna and mallow, %3,1 sit into vapour of boiled straw or parsley by milk during stomacache, and %10,8 shake a carpet. As education level of women decrase, usage of traditional abortion methods increase (p=0,001. In order to decrease the use of these unsafe methods, public education, increasing usage of family planning services, and prevention of unwanted pregnancies should be obtained. [TAF Prev Med Bull 2007; 6(5.000: 321-324

  12. Traditional Methods which are Known and Applied in order to Achieve Voluntary Abortion by Married Women Living in Elazig.

    Directory of Open Access Journals (Sweden)

    Feyza (Nazik Sevindik

    2007-10-01

    Full Text Available This study have been performed in order to describe traditional methods which are known and applied for achieving voluntary abortion by married women living in downtown of Elazig. 426 women have been selected rely on the fifteen years old and married by the represantive 67500 living women in the downtown Elazig. It has been reached to 417 women at repetetive visits. Mean age of women is 36,39±10,26, first pregnancy years are 19,96±4,99, first birth age is 20,02±6,05. Numbers of avarage pregnancy are 3,61±0,12, numbers of voluntary abortion is 0,32±0,04. Voluntary abortion rate is %18,2. %93 of women have stated that they know at least one traditional abortion method, and %19,7 of women declared that they used traditional abortion methods. %14,9 of them stated that they lift a heavy furniture or goods, while %8,2 drink flu drug and asprin, %11,3 jump rope and jump by shaking from high where, %4,8 put a poultry quill, matchstick and knitting needle into uterus, %3,6 put a mallow or aubergine root into uterus servicks, %2,6 drink a boiled quinine henna and mallow, %3,1 sit into vapour of boiled straw or parsley by milk during stomacache, and %10,8 shake a carpet. As education level of women decrase, usage of traditional abortion methods increase (p=0,001. In order to decrease the use of these unsafe methods, public education, increasing usage of family planning services, and prevention of unwanted pregnancies should be obtained. [TAF Prev Med Bull. 2007; 6(5: 321-324

  13. Stability of maximum-likelihood-based clustering methods: exploring the backbone of classifications

    International Nuclear Information System (INIS)

    Mungan, Muhittin; Ramasco, José J

    2010-01-01

    Components of complex systems are often classified according to the way they interact with each other. In graph theory such groups are known as clusters or communities. Many different techniques have been recently proposed to detect them, some of which involve inference methods using either Bayesian or maximum likelihood approaches. In this paper, we study a statistical model designed for detecting clusters based on connection similarity. The basic assumption of the model is that the graph was generated by a certain grouping of the nodes and an expectation maximization algorithm is employed to infer that grouping. We show that the method admits further development to yield a stability analysis of the groupings that quantifies the extent to which each node influences its neighbors' group membership. Our approach naturally allows for the identification of the key elements responsible for the grouping and their resilience to changes in the network. Given the generality of the assumptions underlying the statistical model, such nodes are likely to play special roles in the original system. We illustrate this point by analyzing several empirical networks for which further information about the properties of the nodes is available. The search and identification of stabilizing nodes constitutes thus a novel technique to characterize the relevance of nodes in complex networks

  14. Measuring Group Synchrony: A Cluster-Phase Method for Analyzing Multivariate Movement Time-Series

    Directory of Open Access Journals (Sweden)

    Michael eRichardson

    2012-10-01

    Full Text Available A new method for assessing group synchrony is introduced as being potentially useful for objectively determining degree of group cohesiveness or entitativity. The cluster-phase method of Frank and Richardson (2010 was used to analyze movement data from the rocking chair movements of six-member groups who rocked their chairs while seated in a circle facing the center. In some trials group members had no information about others’ movements (their eyes were shut or they had their eyes open and gazed at a marker in the center of the group. As predicted, the group level synchrony measure was able to distinguish between situations where synchrony would have been possible and situations where it would be impossible. Moreover, other aspects of the analysis illustrated how the cluster phase measures can be used to determine the type of patterning of group synchrony, and, when integrated with multi-level modeling, can be used to examine individual-level differences in synchrony and dyadic level synchrony as well.

  15. The multi-scattering-Xα method for analysis of the electronic structure of atomic clusters

    International Nuclear Information System (INIS)

    Bahurmuz, A.A.; Woo, C.H.

    1984-12-01

    A computer program, MSXALPHA, has been developed to carry out a quantum-mechanical analysis of the electronic structure of molecules and atomic clusters using the Multi-Scattering-Xα (MSXα) method. The MSXALPHA program is based on a code obtained from the University of Alberta; several improvements and new features were incorporated to increase generality and efficiency. The major ones are: (1) minimization of core memory usage, (2) reduction of execution time, (3) introduction of a dynamic core allocation scheme for a large number of arrays, (4) incorporation of an atomic program to generate numerical orbitals used to construct the initial molecular potential, and (5) inclusion of a routine to evaluate total energy. This report is divided into three parts. The first discusses the theory of the MSXα method. The second gives a detailed description of the program, MSXALPHA. The third discusses the results of calculations carried out for the methane molecule (CH 4 ) and a four-atom zirconium cluster (Zr 4 )

  16. A numerical study of spin-dependent organization of alkali-metal atomic clusters using density-functional method

    International Nuclear Information System (INIS)

    Liu Xuan; Ito, Haruhiko; Torikai, Eiko

    2012-01-01

    We calculate the different geometric isomers of spin clusters composed of a small number of alkali-metal atoms using the UB3LYP density-functional method. The electron density distribution of clusters changes according to the value of total spin. Steric structures as well as planar structures arise when the number of atoms increases. The lowest spin state is the most stable and Li n , Na n , K n , Rb n , and Cs n with n = 2–8 can be formed in higher spin states. In the highest spin state, the preparation of clusters depends on the kind and the number of constituent atoms. The interaction energy between alkali-metal atoms and rare-gas atoms is smaller than the binding energy of spin clusters. Consequently, it is possible to self-organize the alkali-metal-atom clusters on a non-wetting substrate coated with rare-gas atoms.

  17. The comparison of solar water heating system operation parameters calculated using traditional method and dynamic simulations

    Directory of Open Access Journals (Sweden)

    Sornek Krzysztof

    2016-01-01

    Full Text Available The proper design of renewable energy based systems is really important to provide their efficient and safe operation. The aim of this paper is to compare the results obtained during traditional static calculations, with the results of dynamic simulations. For this reason, simulations of solar water heating (SWH system, designed for a typical residential building, were conducted in the TRNSYS (Transient System Simulation Tool. Carried out calculations allowed to determine the heat generation in the discussed system as well as to estimate the efficiency of considered installation. Obtained results were compared with the results from other available tool based on the static calculations. It may be concluded, that using dynamic simulations at the designing stage of renewable energy based systems may help to avoid many exploitation problems (including low efficiency, overheating etc. and allows to provide safe exploitation of such installations.

  18. Protein extraction method for the proteomic study of a Mexican traditional fermented starchy food.

    Science.gov (United States)

    Cárdenas, C; Barkla, B J; Wacher, C; Delgado-Olivares, L; Rodríguez-Sanoja, R

    2014-12-05

    Pozol is a traditional fermented maize dough prepared in southeastern Mexico. Wide varieties of microorganisms have already been isolated from this spontaneously fermented product; and include fungi, yeasts, and lactic- and non-lactic acid bacteria. Pozol presents physicochemical features different from that of other food fermentation products, such as a high starch content, in addition to a low protein content. It is these qualities that make it intractable for protein recovery and characterization. The aim of this study was to develop a methodology to optimize the recovery of proteins from the pozol dough following fermentation, by reducing the complexity of the mixture prior to 2D-PAGE analysis and sequencing, to allow the characterization of the metaproteome of the dough. The proteome of 15day fermented maize dough was characterized; proteins were separated and analyzed by mass spectrometry (LC-MS/MS). Subsequent sequence homology database searching, identified numerous bacterial and fungi proteins; with a predominance of lactic acid bacterial proteins, mainly from the Lactobacillus genus. Fungi are mainly represented by Aspergillus. For dominant genera, the most prevalent proteins belong to carbohydrate metabolism and energy production, which suggest that at 15days of fermentation not only fungi but also bacteria are metabolically active. Several methodologies have been employed to study pozol, with a specific focus toward the identification of the microbiota of this fermented maize dough, using both traditional cultivation techniques and culture independent molecular techniques. However to date, the dynamics of this complex fermentation is not well understood. With the purpose to gain further insight into the nature of the fermentation, we used proteomic technologies to identify the origin of proteins and enzymes that facilitate substrate utilization and ultimately the development of the microbiota and fermentation. In this paper we overcome the first general

  19. Comparison of traditional methods with 3D computer models in the instruction of hepatobiliary anatomy.

    Science.gov (United States)

    Keedy, Alexander W; Durack, Jeremy C; Sandhu, Parmbir; Chen, Eric M; O'Sullivan, Patricia S; Breiman, Richard S

    2011-01-01

    This study was designed to determine whether an interactive three-dimensional presentation depicting liver and biliary anatomy is more effective for teaching medical students than a traditional textbook format presentation of the same material. Forty-six medical students volunteered for participation in this study. Baseline demographic information, spatial ability, and knowledge of relevant anatomy were measured. Participants were randomized into two groups and presented with a computer-based interactive learning module comprised of animations and still images to highlight various anatomical structures (3D group), or a computer-based text document containing the same images and text without animation or interactive features (2D group). Following each teaching module, students completed a satisfaction survey and nine-item anatomic knowledge post-test. The 3D group scored higher on the post-test than the 2D group, with a mean score of 74% and 64%, respectively; however, when baseline differences in pretest scores were accounted for, this difference was not statistically significant (P = 0.33). Spatial ability did not statistically significantly correlate with post-test scores for the 3D group or the 2D group. In the post-test satisfaction survey the 3D group expressed a statistically significantly higher overall satisfaction rating compared to students in the 2D control group (4.5 versus 3.7 out of 5, P = 0.02). While the interactive 3D multimedia module received higher satisfaction ratings from students, it neither enhanced nor inhibited learning of complex hepatobiliary anatomy compared to an informationally equivalent traditional textbook style approach. . Copyright © 2011 American Association of Anatomists.

  20. Computerized tablet based versus traditional paper- based survey methods: results from adolescent's health research in schools of Maharashtra, India

    OpenAIRE

    Naveen Agarwal; Balram Paswan; Prakash H. Fulpagare; Dhirendra N Sinha; Thaksaphon Thamarangsi; Manju Rani

    2018-01-01

    Background and challenges to implementation Technological advancement is growing very fast in India and majority of young population is handling electronic devices often during leisure as well as at work. This study indicates that electronic tablets are less time consuming and improves survey response rate over the traditional paper-pencil survey method. Intervention or response An Android-based Global School-based Health Survey (GSHS) questionnaire was used with the...

  1. How do Millennial Engineering and Technology Students Experience Learning Through Traditional Teaching Methods Employed in the University Setting?

    OpenAIRE

    Howard, Elizabeth A

    2011-01-01

    The purpose of the study was to document and analyze how Millennial engineering and technology students experience learning in large lecture classrooms. To help achieve this purpose, perceptions Millennials have toward traditional teaching methods employed in large lecture classes were analyzed and discussed. Additionally, this study documented how Millennials experienced technology within large lecture classrooms. A learning model depicting how Millennials experience learning within the larg...

  2. Validity studies among hierarchical methods of cluster analysis using cophenetic correlation coefficient

    Energy Technology Data Exchange (ETDEWEB)

    Carvalho, Priscilla R.; Munita, Casimiro S.; Lapolli, André L., E-mail: prii.ramos@gmail.com, E-mail: camunita@ipen.br, E-mail: alapolli@ipen.br [Instituto de Pesquisas Energéticas e Nucleares (IPEN/CNEN-SP), São Paulo, SP (Brazil)

    2017-07-01

    The literature presents many methods for partitioning of data base, and is difficult choose which is the most suitable, since the various combinations of methods based on different measures of dissimilarity can lead to different patterns of grouping and false interpretations. Nevertheless, little effort has been expended in evaluating these methods empirically using an archaeological data base. In this way, the objective of this work is make a comparative study of the different cluster analysis methods and identify which is the most appropriate. For this, the study was carried out using a data base of the Archaeometric Studies Group from IPEN-CNEN/SP, in which 45 samples of ceramic fragments from three archaeological sites were analyzed by instrumental neutron activation analysis (INAA) which were determinate the mass fraction of 13 elements (As, Ce, Cr, Eu, Fe, Hf, La, Na, Nd, Sc, Sm, Th, U). The methods used for this study were: single linkage, complete linkage, average linkage, centroid and Ward. The validation was done using the cophenetic correlation coefficient and comparing these values the average linkage method obtained better results. A script of the statistical program R with some functions was created to obtain the cophenetic correlation. By means of these values was possible to choose the most appropriate method to be used in the data base. (author)

  3. Validity studies among hierarchical methods of cluster analysis using cophenetic correlation coefficient

    International Nuclear Information System (INIS)

    Carvalho, Priscilla R.; Munita, Casimiro S.; Lapolli, André L.

    2017-01-01

    The literature presents many methods for partitioning of data base, and is difficult choose which is the most suitable, since the various combinations of methods based on different measures of dissimilarity can lead to different patterns of grouping and false interpretations. Nevertheless, little effort has been expended in evaluating these methods empirically using an archaeological data base. In this way, the objective of this work is make a comparative study of the different cluster analysis methods and identify which is the most appropriate. For this, the study was carried out using a data base of the Archaeometric Studies Group from IPEN-CNEN/SP, in which 45 samples of ceramic fragments from three archaeological sites were analyzed by instrumental neutron activation analysis (INAA) which were determinate the mass fraction of 13 elements (As, Ce, Cr, Eu, Fe, Hf, La, Na, Nd, Sc, Sm, Th, U). The methods used for this study were: single linkage, complete linkage, average linkage, centroid and Ward. The validation was done using the cophenetic correlation coefficient and comparing these values the average linkage method obtained better results. A script of the statistical program R with some functions was created to obtain the cophenetic correlation. By means of these values was possible to choose the most appropriate method to be used in the data base. (author)

  4. A Novel Double Cluster and Principal Component Analysis-Based Optimization Method for the Orbit Design of Earth Observation Satellites

    Directory of Open Access Journals (Sweden)

    Yunfeng Dong

    2017-01-01

    Full Text Available The weighted sum and genetic algorithm-based hybrid method (WSGA-based HM, which has been applied to multiobjective orbit optimizations, is negatively influenced by human factors through the artificial choice of the weight coefficients in weighted sum method and the slow convergence of GA. To address these two problems, a cluster and principal component analysis-based optimization method (CPC-based OM is proposed, in which many candidate orbits are gradually randomly generated until the optimal orbit is obtained using a data mining method, that is, cluster analysis based on principal components. Then, the second cluster analysis of the orbital elements is introduced into CPC-based OM to improve the convergence, developing a novel double cluster and principal component analysis-based optimization method (DCPC-based OM. In DCPC-based OM, the cluster analysis based on principal components has the advantage of reducing the human influences, and the cluster analysis based on six orbital elements can reduce the search space to effectively accelerate convergence. The test results from a multiobjective numerical benchmark function and the orbit design results of an Earth observation satellite show that DCPC-based OM converges more efficiently than WSGA-based HM. And DCPC-based OM, to some degree, reduces the influence of human factors presented in WSGA-based HM.

  5. A Clustering K-Anonymity Privacy-Preserving Method for Wearable IoT Devices

    Directory of Open Access Journals (Sweden)

    Fang Liu

    2018-01-01

    Full Text Available Wearable technology is one of the greatest applications of the Internet of Things. The popularity of wearable devices has led to a massive scale of personal (user-specific data. Generally, data holders (manufacturers of wearable devices are willing to share these data with others to get benefits. However, significant privacy concerns would arise when sharing the data with the third party in an improper manner. In this paper, we first propose a specific threat model about the data sharing process of wearable devices’ data. Then we propose a K-anonymity method based on clustering to preserve privacy of wearable IoT devices’ data and guarantee the usability of the collected data. Experiment results demonstrate the effectiveness of the proposed method.

  6. Running and Metabolic Demands of Elite Rugby Union Assessed Using Traditional, Metabolic Power, and Heart Rate Monitoring Methods

    Science.gov (United States)

    Dubois, Romain; Paillard, Thierry; Lyons, Mark; McGrath, David; Maurelli, Olivier; Prioux, Jacques

    2017-01-01

    The aims of this study were (1) to analyze elite rugby union game demands using 3 different approaches: traditional, metabolic and heart rate-based methods (2) to explore the relationship between these methods and (3) to explore positional differences between the backs and forwards players. Time motion analysis and game demands of fourteen professional players (24.1 ± 3.4 y), over 5 European challenge cup games, were analyzed. Thresholds of 14.4 km·h-1, 20 W.kg-1 and 85% of maximal heart rate (HRmax) were set for high-intensity efforts across the three methods. The mean % of HRmax was 80.6 ± 4.3 % while 42.2 ± 16.5% of game time was spent above 85% of HRmax with no significant differences between the forwards and the backs. Our findings also show that the backs cover greater distances at high-speed than forwards (% difference: +35.2 ± 6.6%; pdemands of professional rugby games. The traditional and the metabolic-power approaches shows a close correlation concerning their relative values, nevertheless the difference in absolute values especially for the high-intensity thresholds demonstrates that the metabolic power approach may represent an interesting alternative to the traditional approaches used in evaluating the high-intensity running efforts required in rugby union games. Key points Elite/professional rugby union players Heart rate monitoring during official games Metabolic power approach PMID:28344455

  7. Is there still a role for traditional methods in the management of fractures of the zygomatic complex?

    LENUS (Irish Health Repository)

    O'Sullivan, S T

    2012-02-03

    With the introduction of low-profile mini-plating systems, a trend has developed towards open reduction and rigid internal fixation (ORIF) of fractures of the cranio-facial skeleton. The current policy for management of zygomatic fractures in our unit is to attempt primary reduction by traditional methods, and proceed to ORIF in the event of unsatisfactory fracture stability or alignment. Over a one-year period, 109 patients underwent surgical correction of fractures of the zygomatic complex. Standard Gilles\\' elevation was performed in 71 cases, percutaneous elevation in three cases, and ORIF was performed in 35 cases. Mean follow-up was 190 days. One case of persistent infraorbital step and three cases of residual malar flattening were documented in patients who underwent Gilles or percutaneous elevation. Morbidity associated with ORIF was minimal. We conclude that while ORIF of zygomatic fractures may offer better results than traditional methods in the management of complex fractures, traditional methods still have a role to play in less complex fractures.

  8. Comparison and combination of "direct" and fragment based local correlation methods: Cluster in molecules and domain based local pair natural orbital perturbation and coupled cluster theories

    Science.gov (United States)

    Guo, Yang; Becker, Ute; Neese, Frank

    2018-03-01

    Local correlation theories have been developed in two main flavors: (1) "direct" local correlation methods apply local approximation to the canonical equations and (2) fragment based methods reconstruct the correlation energy from a series of smaller calculations on subsystems. The present work serves two purposes. First, we investigate the relative efficiencies of the two approaches using the domain-based local pair natural orbital (DLPNO) approach as the "direct" method and the cluster in molecule (CIM) approach as the fragment based approach. Both approaches are applied in conjunction with second-order many-body perturbation theory (MP2) as well as coupled-cluster theory with single-, double- and perturbative triple excitations [CCSD(T)]. Second, we have investigated the possible merits of combining the two approaches by performing CIM calculations with DLPNO methods serving as the method of choice for performing the subsystem calculations. Our cluster-in-molecule approach is closely related to but slightly deviates from approaches in the literature since we have avoided real space cutoffs. Moreover, the neglected distant pair correlations in the previous CIM approach are considered approximately. Six very large molecules (503-2380 atoms) were studied. At both MP2 and CCSD(T) levels of theory, the CIM and DLPNO methods show similar efficiency. However, DLPNO methods are more accurate for 3-dimensional systems. While we have found only little incentive for the combination of CIM with DLPNO-MP2, the situation is different for CIM-DLPNO-CCSD(T). This combination is attractive because (1) the better parallelization opportunities offered by CIM; (2) the methodology is less memory intensive than the genuine DLPNO-CCSD(T) method and, hence, allows for large calculations on more modest hardware; and (3) the methodology is applicable and efficient in the frequently met cases, where the largest subsystem calculation is too large for the canonical CCSD(T) method.

  9. METHODS FOR CLUSTERING TIME SERIES DATA ACQUIRED FROM MOBILE HEALTH APPS.

    Science.gov (United States)

    Tignor, Nicole; Wang, Pei; Genes, Nicholas; Rogers, Linda; Hershman, Steven G; Scott, Erick R; Zweig, Micol; Yvonne Chan, Yu-Feng; Schadt, Eric E

    2017-01-01

    In our recent Asthma Mobile Health Study (AMHS), thousands of asthma patients across the country contributed medical data through the iPhone Asthma Health App on a daily basis for an extended period of time. The collected data included daily self-reported asthma symptoms, symptom triggers, and real time geographic location information. The AMHS is just one of many studies occurring in the context of now many thousands of mobile health apps aimed at improving wellness and better managing chronic disease conditions, leveraging the passive and active collection of data from mobile, handheld smart devices. The ability to identify patient groups or patterns of symptoms that might predict adverse outcomes such as asthma exacerbations or hospitalizations from these types of large, prospectively collected data sets, would be of significant general interest. However, conventional clustering methods cannot be applied to these types of longitudinally collected data, especially survey data actively collected from app users, given heterogeneous patterns of missing values due to: 1) varying survey response rates among different users, 2) varying survey response rates over time of each user, and 3) non-overlapping periods of enrollment among different users. To handle such complicated missing data structure, we proposed a probability imputation model to infer missing data. We also employed a consensus clustering strategy in tandem with the multiple imputation procedure. Through simulation studies under a range of scenarios reflecting real data conditions, we identified favorable performance of the proposed method over other strategies that impute the missing value through low-rank matrix completion. When applying the proposed new method to study asthma triggers and symptoms collected as part of the AMHS, we identified several patient groups with distinct phenotype patterns. Further validation of the methods described in this paper might be used to identify clinically important

  10. A Survey of a System of Methods for Fire Safety Design of Traditional Concrete Constructions

    DEFF Research Database (Denmark)

    Hertz, Kristian

    2000-01-01

    constructions DS411. And the bases for many of the methods have been distributed by CIB W14 reports. But a survey of all the methods in coherence has never been presented, and much of this documentation and the additional documentation produced for the work with the codes needs still to be printed in papers......During the years since 1978 the author has been developing a series of calculation methods and sup-porting test methods for the fire safety design of concrete constructions. The basic methods have been adopted in the fire chapters of the Eurocode ENV1992-1-2 and the Danish code for concrete.......It is the aim of this paper to give a coherent presentation of the design methods, their degree of documentation and the available references in order to facilitate the application of them....

  11. The Effect of Laboratory Training Model of Teaching and Traditional Method on Knowledge, Comprehension, Application, Skills-Components of Achievement, Total Achievement and Retention Level in Chemistry

    Science.gov (United States)

    Badeleh, Alireza

    2011-01-01

    The present study aimed at finding the effectiveness of the Laboratory Training Model of Teaching (LTM) and comparing it with the traditional methods of teaching chemistry to seventh standard students. It strived to determine whether the (LTM) method in chemistry would be significantly more effective than the Traditional method in respect to the…

  12. A comparative study of traditional lecture methods and interactive lecture methods in introductory geology courses for non-science majors at the college level

    Science.gov (United States)

    Hundley, Stacey A.

    In recent years there has been a national call for reform in undergraduate science education. The goal of this reform movement in science education is to develop ways to improve undergraduate student learning with an emphasis on developing more effective teaching practices. Introductory science courses at the college level are generally taught using a traditional lecture format. Recent studies have shown incorporating active learning strategies within the traditional lecture classroom has positive effects on student outcomes. This study focuses on incorporating interactive teaching methods into the traditional lecture classroom to enhance student learning for non-science majors enrolled in introductory geology courses at a private university. Students' experience and instructional preferences regarding introductory geology courses were identified from survey data analysis. The information gained from responses to the questionnaire was utilized to develop an interactive lecture introductory geology course for non-science majors. Student outcomes were examined in introductory geology courses based on two teaching methods: interactive lecture and traditional lecture. There were no significant statistical differences between the groups based on the student outcomes and teaching methods. Incorporating interactive lecture methods did not statistically improve student outcomes when compared to traditional lecture teaching methods. However, the responses to the survey revealed students have a preference for introductory geology courses taught with lecture and instructor-led discussions and students prefer to work independently or in small groups. The results of this study are useful to individuals who teach introductory geology courses and individuals who teach introductory science courses for non-science majors at the college level.

  13. Comparison of chest compression quality between the modified chest compression method with the use of smartphone application and the standardized traditional chest compression method during CPR.

    Science.gov (United States)

    Park, Sang-Sub

    2014-01-01

    The purpose of this study is to grasp difference in quality of chest compression accuracy between the modified chest compression method with the use of smartphone application and the standardized traditional chest compression method. Participants were progressed 64 people except 6 absentees among 70 people who agreed to participation with completing the CPR curriculum. In the classification of group in participants, the modified chest compression method was called as smartphone group (33 people). The standardized chest compression method was called as traditional group (31 people). The common equipments in both groups were used Manikin for practice and Manikin for evaluation. In the meantime, the smartphone group for application was utilized Android and iOS Operating System (OS) of 2 smartphone products (G, i). The measurement period was conducted from September 25th to 26th, 2012. Data analysis was used SPSS WIN 12.0 program. As a result of research, the proper compression depth (mm) was shown the proper compression depth (p< 0.01) in traditional group (53.77 mm) compared to smartphone group (48.35 mm). Even the proper chest compression (%) was formed suitably (p< 0.05) in traditional group (73.96%) more than smartphone group (60.51%). As for the awareness of chest compression accuracy, the traditional group (3.83 points) had the higher awareness of chest compression accuracy (p< 0.001) than the smartphone group (2.32 points). In the questionnaire that was additionally carried out 1 question only in smartphone group, the modified chest compression method with the use of smartphone had the high negative reason in rescuer for occurrence of hand back pain (48.5%) and unstable posture (21.2%).

  14. Understanding Foster Youth Outcomes: Is Propensity Scoring Better than Traditional Methods?

    Science.gov (United States)

    Berzin, Stephanie Cosner

    2010-01-01

    Objectives: This study seeks to examine the relationship between foster care and outcomes using multiple comparison methods to account for factors that put foster youth at risk independent of care. Methods: Using the National Longitudinal Survey of Youth 1997, matching, propensity scoring, and comparisons to the general population are used to…

  15. Quality Assessment of Kumu Injection, a Traditional Chinese Medicine Preparation, Using HPLC Combined with Chemometric Methods and Qualitative and Quantitative Analysis of Multiple Alkaloids by Single Marker.

    Science.gov (United States)

    Wang, Ning; Li, Zhi-Yong; Zheng, Xiao-Li; Li, Qiao; Yang, Xin; Xu, Hui

    2018-04-09

    Kumu injection (KMI) is a common-used traditional Chinese medicine (TCM) preparation made from Picrasma quassioides (D. Don) Benn. rich in alkaloids. An innovative technique for quality assessment of KMI was developed using high performance liquid chromatography (HPLC) combined with chemometric methods and qualitative and quantitative analysis of multi-components by single marker (QAMS). Nigakinone (PQ-6, 5-hydroxy-4-methoxycanthin-6-one), one of the most abundant alkaloids responsible for the major pharmacological activities of Kumu, was used as a reference substance. Six alkaloids in KMI were quantified, including 6-hydroxy- β -carboline-1-carboxylic acid (PQ-1), 4,5-dimethoxycanthin-6-one (PQ-2), β -carboline-1-carboxylic acid (PQ-3), β -carboline-1-propanoic acid (PQ-4), 3-methylcanthin-5,6-dione (PQ-5), and PQ-6. Based on the outcomes of twenty batches of KMI samples, the contents of six alkaloids were used for further chemometric analysis. By hierarchical cluster analysis (HCA), radar plots, and principal component analysis (PCA), all the KMI samples could be categorized into three groups, which were closely related to production date and indicated the crucial influence of herbal raw material on end products of KMI. QAMS combined with chemometric analysis could accurately measure and clearly distinguish the different quality samples of KMI. Hence, QAMS is a feasible and promising method for the quality control of KMI.

  16. Panel presentation: Should some type of incentive regulation replace traditional methods for regulating LDCs?

    International Nuclear Information System (INIS)

    Turner, J.L.

    1992-01-01

    This paper reviews the advantages and disadvantages of using incentive regulation to provide the best service and rates for natural gas consumers and compares it to the traditional rate-of-return regulation. It discusses some of the allegations used to prevent incentive regulation such as the rate-of-return regulation provides an incentive to over-build and pad rate base, thus creating inefficiencies. The author also feels that strict competition is not necessarily beneficial and that some form of regulation is necessary. The paper goes on to outline the author's ideas of how a successful incentive plan should work while emphasizing his preference for a rate-of-return regulation. From the ratepayers' view, the incentives granted should be rewards for improvement in a utility's performance. In other words, there must be clear goals set for management and the fulfillment or lack of fulfillment should result in rewards or penalties. The author feels that incentive regulation could prove to be appropriate in the areas of demand side management such as energy conservation programs

  17. Evaluation of two methods for monitoring surface cleanliness-ATP bioluminescence and traditional hygiene swabbing.

    Science.gov (United States)

    Davidson, C A; Griffith, C J; Peters, A C; Fielding, L M

    1999-01-01

    The minimum bacterial detection limits and operator reproducibility of the Biotrace Clean-Tracetrade mark Rapid Cleanliness Test and traditional hygiene swabbing were determined. Areas (100 cm2) of food grade stainless steel were separately inoculated with known levels of Staphylococcus aureus (NCTC 6571) and Escherichia coli (ATCC 25922). Surfaces were sampled either immediately after inoculation while still wet, or after 60 min when completely dry. For both organisms the minimum detection limit of the ATP Clean-Tracetrade mark Rapid Cleanliness Test was 10(4) cfu/100 cm2 (p 10(7) cfu/100 cm2. Hygiene swabbing percentage recovery rates for both organisms were less than 0.1% for dried surfaces but ranged from 0.33% to 8.8% for wet surfaces. When assessed by six technically qualified operators, the Biotrace Clean-Tracetrade mark Rapid Cleanliness Test gave superior reproducibility for both clean and inoculated surfaces, giving mean coefficients of variation of 24% and 32%, respectively. Hygiene swabbing of inoculated surfaces gave a mean CV of 130%. The results are discussed in the context of hygiene monitoring within the food industry. Copyright 1999 John Wiley & Sons, Ltd.

  18. Video-based Learning Versus Traditional Method for Preclinical Course of Complete Denture Fabrication.

    Science.gov (United States)

    Fayaz, Amir; Mazahery, Azita; Hosseinzadeh, Mohammad; Yazdanpanah, Samane

    2015-03-01

    Advances in computer science and technology allow the instructors to use instructional multimedia programs to enhance the process of learning for dental students. The purpose of this study was to determine the effect of a new educational modality by using videotapes on the performance of dental students in preclinical course of complete denture fabrication. This quasi-experimental study was performed on 54 junior dental students in Shahid Beheshti University of Medical Sciences (SBMU). Twenty-five and 29 students were evaluated in two consecutive semesters as controls and cases, respectively for the same course. The two groups were matched in terms of "knowledge about complete denture fabrication" and "basic dental skills" using a written test and a practical exam, respectively. After the intervention, performance and clinical skills of students were assessed in 8 steps. Eventually, a post-test was carried out to find changes in knowledge and skills of students in this regard. In the two groups with the same baseline level of knowledge and skills, independent T-test showed that students in the test group had a significantly superior performance in primary impression taking (p= 0.001) and primary cast fabrication (p= 0.001). In terms of anterior teeth set up, students in the control group had a significantly better performance (p= 0.001). Instructional videotapes can aid in teaching fabrication of complete denture and are as effective as the traditional teaching system.

  19. Nutritional value of traditional Italian meat-based dishes: influence of cooking methods and recipe formulation.

    Science.gov (United States)

    D'Evoli, L; Salvatore, P; Lucarini, M; Nicoli, S; Aguzzi, A; Gabrielli, P; Lombardi-Boccia, G

    2009-01-01

    The present study provides a picture of the compositional figure and nutritive value of meat-based dishes typical of Italian culinary tradition. Recipes specific for a bovine meat cut (top-side) were selected among the most widespread ones in Italy: in pan, pizzaiola, cutlet, meat ball, and escalope. The total fat and cholesterol content varied depending on the ingredients utilized (extra-virgin olive oil, parmesan, egg). Meat-based dishes that utilized extra-virgin olive oil showed a significant reduction in palmitic and stearic acids and a parallel increase in oleic acid compared with raw meat; furthermore, the ratio among saturated fatty acids, monounsaturated fatty acids and polyunsaturated fatty acids shifted in favour of monounsaturated fatty acids. B vitamins were affected at different extent by heating; by contrast, vitamin E content increased because of the new sources of this vitamin, which masked losses due to heating. Ingredients (parmesan, discretionary salt) induced significant increases in the calcium and sodium concentrations compared with raw meat. The total iron content did not show marked differences in most of the meat-based dishes compared with raw meat; by contrast, losses in the heme-iron concentration were detected depending on the severity of heating treatments. Our findings suggest that heme iron, because of its important health aspects, might be a useful index of the nutritional quality of cooked meats.

  20. Motivation in service-learning: an improvement over traditional instructional methods

    Directory of Open Access Journals (Sweden)

    Monika Ciesielkiewicz

    2018-05-01

    Full Text Available This paper aims at exploring the motivation of university students who participated in service-learning projects as part of their coursework, and to determine whether their level of motivation is higher for the service-learning project as compared to performing more traditional academic tasks and assignments. The Service-Learning project carried out during the ICT in Education course intended to support the development of digital literacy in a Maasai school in Kenya. The instrument used to evaluate motivation of the university students is the motivation scale called Motivated Strategies for Learning Questionnaire (MSLQ proposed by Pintrich and his collaborators (1991 adapted to the Spanish population by Roces Montero (1996. The results of the research indicate that there are significant differences in favor of service-learning in relation to motivation in general for the completion of the activities and specifically in relation to the utility of the activity as seen at the present moment and in the future, as well as promoting creativity, the interest in the task which includes the perception of the importance of the project, the need to work hard and thoroughly and willingness to face challenges and difficulties in order to achieve the set objective. No significant differences have been observed in relation to the desire to obtain a better grade for completing the activity or need to prove personal value to others, as well as to broaden the information to complete the activity.  

  1. Festival of Curses: A Traditional Crime Control Method In Edo State –Nigeria

    Directory of Open Access Journals (Sweden)

    Rashidi Akanji Okunola

    2016-02-01

    Full Text Available Festivals and ceremonies are part and parcel of African culture, usually in all its pump, merriment and pageantry. However, with the increasing wave of criminal activities in Nigeria especially in Edo state, festivals and ceremonies are being redefined and conceptualized in practice. Only recently a new festival ‘Festival of Curses’ was brought to the fore in combating crime in Edo state. The study therefore seeks to explain the festival as a traditional mechanism in crime control, the nature of the festival, the factors that led to its emergence in the 21st century, the level of acceptance and its impact in reducing criminal activities in the State. The study employed principally secondary literature and in-depth interviews among a cross section of the Bini. Major findings revealed that immediately after the festival of curses, a lot of criminals in the state besieged the Bini Monarch’s Palace to confess their atrocities; and pleaded for forgiveness. There was an overwhelming acceptance of the festival irrespective of the people’s religious affiliations to Christianity and Islam as a result of the potency and sudden drop in crime during the period. The study concludes that the festival should be taken as a mechanism of crime control and policing in Nigeria.

  2. Panel presentation: Should some type of incentive regulation replace traditional methods for regulating LDCs?

    International Nuclear Information System (INIS)

    Costello, K.W.

    1992-01-01

    State regulators should consider new approaches to regulating LDCs. They should seriously look at different incentive systems, even if only as an experiment, to address the major inefficiencies they see plaguing LDCs. Regulators have become more receptive in recent years to applying different incentive systems for historically heavily regulated industries such as the telecommunications and electric industries. In view of prevailing conditions in the natural gas industry, there is no good reason why regulators should not be as receptive to applying incentive systems for LDCs. For gas services offered in competitive markets, regulators should ask themselves whether regulation is necessary any longer. For services still requiring regulation, regulators should explore whether changes in traditional regulation are needed. While some PUCs have undertaken new regulatory practices, the question before them today is whether they should do more; whether, for example, states should accelerate their efforts toward adopting more flexible pricing and other incentive-based regulations or toward considering deregulating selected services. PUCs have different options. They can choose from among a large number of incentive systems. Their choices should hinge upon what they view as major sources of inefficiencies. For example, if uneconomical bypass is perceived as a problem then different price rules might constitute the cornerstone of an incentive-based policy. On the other hand, if excessive purchased-gas costs seem to be a major problem, a PUC may want to consider abolishing the PGA or modifying it in a form that would eliminate the cost-plus component

  3. Comparison of three methods for the estimation of cross-shock electric potential using Cluster data

    Directory of Open Access Journals (Sweden)

    A. P. Dimmock

    2011-05-01

    Full Text Available Cluster four point measurements provide a comprehensive dataset for the separation of temporal and spatial variations, which is crucial for the calculation of the cross shock electrostatic potential using electric field measurements. While Cluster is probably the most suited among present and past spacecraft missions to provide such a separation at the terrestrial bow shock, it is far from ideal for a study of the cross shock potential, since only 2 components of the electric field are measured in the spacecraft spin plane. The present paper is devoted to the comparison of 3 different techniques that can be used to estimate the potential with this limitation. The first technique is the estimate taking only into account the projection of the measured components onto the shock normal. The second uses the ideal MHD condition E·B = 0 to estimate the third electric field component. The last method is based on the structure of the electric field in the Normal Incidence Frame (NIF for which only the potential component along the shock normal and the motional electric field exist. All 3 approaches are used to estimate the potential for a single crossing of the terrestrial bow shock that took place on the 31 March 2001. Surprisingly all three methods lead to the same order of magnitude for the cross shock potential. It is argued that the third method must lead to more reliable results. The effect of the shock normal inaccuracy is investigated for this particular shock crossing. The resulting electrostatic potential appears too high in comparison with the theoretical results for low Mach number shocks. This shows the variability of the potential, interpreted in the frame of the non-stationary shock model.

  4. Why so GLUMM? Detecting depression clusters through graphing lifestyle-environs using machine-learning methods (GLUMM).

    Science.gov (United States)

    Dipnall, J F; Pasco, J A; Berk, M; Williams, L J; Dodd, S; Jacka, F N; Meyer, D

    2017-01-01

    Key lifestyle-environ risk factors are operative for depression, but it is unclear how risk factors cluster. Machine-learning (ML) algorithms exist that learn, extract, identify and map underlying patterns to identify groupings of depressed individuals without constraints. The aim of this research was to use a large epidemiological study to identify and characterise depression clusters through "Graphing lifestyle-environs using machine-learning methods" (GLUMM). Two ML algorithms were implemented: unsupervised Self-organised mapping (SOM) to create GLUMM clusters and a supervised boosted regression algorithm to describe clusters. Ninety-six "lifestyle-environ" variables were used from the National health and nutrition examination study (2009-2010). Multivariate logistic regression validated clusters and controlled for possible sociodemographic confounders. The SOM identified two GLUMM cluster solutions. These solutions contained one dominant depressed cluster (GLUMM5-1, GLUMM7-1). Equal proportions of members in each cluster rated as highly depressed (17%). Alcohol consumption and demographics validated clusters. Boosted regression identified GLUMM5-1 as more informative than GLUMM7-1. Members were more likely to: have problems sleeping; unhealthy eating; ≤2 years in their home; an old home; perceive themselves underweight; exposed to work fumes; experienced sex at ≤14 years; not perform moderate recreational activities. A positive relationship between GLUMM5-1 (OR: 7.50, Pdepression was found, with significant interactions with those married/living with partner (P=0.001). Using ML based GLUMM to form ordered depressive clusters from multitudinous lifestyle-environ variables enabled a deeper exploration of the heterogeneous data to uncover better understandings into relationships between the complex mental health factors. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

  5. A comparison of a track shape analysis-based automated slide scanner system with traditional methods

    International Nuclear Information System (INIS)

    Bator, G.; Csordas, A.; Horvath, D.; Somlai, J.; Kovacs, T.

    2015-01-01

    During recent years, CR-39 detector measurements have gained attention due to improvements in image processing methods. An assessment method based on the application of a high-resolution slide scanner and its quality checks is introduced, using commercially available software and hardware. Using the conventional (visual) comparing analysis for 563 detectors, the method was found suitable for high-precision and reliable track analysis. The accuracy of the measurements were not disturbed by any other pseudo-tracks (scratches or contamination) due to the signal shape of the analysis. (author)

  6. Avocado oil extraction processes: method for cold-pressed high-quality edible oil production versus traditional production

    Directory of Open Access Journals (Sweden)

    Giacomo Costagli

    2015-10-01

    Full Text Available Nowadays the avocado fruit (Persea americana Mill. is widely regarded as an important fruit for its nutritional values, as it is rich in vital human nutrients. The avocado fruit is mainly sold fresh on the market, which however trades also a relevant quantity of second-grade fruits with a relatively high oil content. Traditionally, this oil is extracted from dried fruits by means of organic solvents, but a mechanical method is also used in general in locations where drying systems and/or solvent extraction units cannot be installed. These traditional processes yield a grade of oil that needs subsequent refining and is mainly used in the cosmetic industry. In the late 1990s, in New Zeland, a processing company with the collaboration of Alfa Laval began producing cold-pressed avocado oil (CPAO to be sold as edible oil for salads and cooking. Over the last fifteen years, CPAO production has increased in many other countries and has led to an expansion of the market which is set to continue, given the growing interest in highquality and healthy food. Avocado oil like olive oil is extracted from the fruit pulp and in particular shares many principles of the extraction process with extra-vergin olive oil. We conducted a review of traditional and modern extraction methods with particular focus on extraction processes and technology for CPAO production.

  7. Integration of Traditional and E-Learning Methods to Improve Learning Outcomes for Dental Students in Histopathology.

    Science.gov (United States)

    Ariana, Armin; Amin, Moein; Pakneshan, Sahar; Dolan-Evans, Elliot; Lam, Alfred K

    2016-09-01

    Dental students require a basic ability to explain and apply general principles of pathology to systemic, dental, and oral pathology. Although there have been recent advances in electronic and online resources, the academic effectiveness of using self-directed e-learning tools in pathology courses for dental students is unclear. The aim of this study was to determine if blended learning combining e-learning with traditional learning methods of lectures and tutorials would improve students' scores and satisfaction over those who experienced traditional learning alone. Two consecutive cohorts of Bachelor of Dentistry and Oral Health students taking the general pathology course at Griffith University in Australia were compared. The control cohort experienced traditional methods only, while members of the study cohort were also offered self-directed learning materials including online resources and online microscopy classes. Final assessments for the course were used to compare the differences in effectiveness of the intervention, and students' satisfaction with the teaching format was evaluated using questionnaires. On the final course assessments, students in the study cohort had significantly higher scores than students in the control cohort (plearning tools such as virtual microscopy and interactive online resources for delivering pathology instruction can be an effective supplement for developing dental students' competence, confidence, and satisfaction.

  8. Hadron formation in a non-ideal quark gluon plasma using Mayer's method of cluster expansion

    International Nuclear Information System (INIS)

    Prasanth, J.P.; Bannur, Vishnu M.

    2015-01-01

    This work investigates the applicability of using the Mayer's cluster expansion method to derive the equation of state (EoS) of the quark-antiquark plasma. Dissociation of heavier hadrons in QGP is studied. The possibility of the existence of quarkonium after deconfinement at higher temperature than the critical temperature T > T c is investigated. The EoS has been studied by calculating second and third cluster integrals. The results are compared and discussed with available works. (author)

  9. Running and Metabolic Demands of Elite Rugby Union Assessed Using Traditional, Metabolic Power, and Heart Rate Monitoring Methods

    Directory of Open Access Journals (Sweden)

    Romain Dubois, Thierry Paillard, Mark Lyons, David McGrath, Olivier Maurelli, Jacques Prioux

    2017-03-01

    Full Text Available The aims of this study were (1 to analyze elite rugby union game demands using 3 different approaches: traditional, metabolic and heart rate-based methods (2 to explore the relationship between these methods and (3 to explore positional differences between the backs and forwards players. Time motion analysis and game demands of fourteen professional players (24.1 ± 3.4 y, over 5 European challenge cup games, were analyzed. Thresholds of 14.4 km·h-1, 20 W.kg-1 and 85% of maximal heart rate (HRmax were set for high-intensity efforts across the three methods. The mean % of HRmax was 80.6 ± 4.3 % while 42.2 ± 16.5% of game time was spent above 85% of HRmax with no significant differences between the forwards and the backs. Our findings also show that the backs cover greater distances at high-speed than forwards (% difference: +35.2 ± 6.6%; p<0.01 while the forwards cover more distance than the backs (+26.8 ± 5.7%; p<0.05 in moderate-speed zone (10-14.4 km·h-1. However, no significant difference in high-metabolic power distance was found between the backs and forwards. Indeed, the high-metabolic power distances were greater than high-speed running distances of 24.8 ± 17.1% for the backs, and 53.4 ± 16.0% for the forwards with a significant difference (+29.6 ± 6.0% for the forwards; p<0.001 between the two groups. Nevertheless, nearly perfect correlations were found between the total distance assessed using the traditional approach and the metabolic power approach (r = 0.98. Furthermore, there is a strong association (r = 0.93 between the high-speed running distance (assessed using the traditional approach and the high-metabolic power distance. The HR monitoring methods demonstrate clearly the high physiological demands of professional rugby games. The traditional and the metabolic-power approaches shows a close correlation concerning their relative values, nevertheless the difference in absolute values especially for the high

  10. [Methods of traditional chinese medicine in the treatment of patients with interstitial cystitis/bladder pain syndrome].

    Science.gov (United States)

    Ignashov, A Yu; Deng, B; Kuzmin, I V; Slesarevskaya, M N

    2018-03-01

    In recent years, there has been an increasing interest in alternative (complementary) treatments of interstitial cystitis/bladder pain syndrome (IC/BPS). This is due both to the high incidence of IC/BPS and to a lack of effectiveness of conventional treatments. One of the directions of alternative therapies is a traditional Chinese medicine using a special diet, various animal and plant-derived medicines, breathing exercises and acupuncture. This review analyzes the accumulated experience in using traditional Chinese medicine in the treatment of patients with IC/BPS. The presented data indicate that these methods appear to be promising, since they are effective in a significant number of patients, lead to an improvement in their quality of life, are non-invasive and well tolerated. However, due to the lack of clinical studies, the efficacy of this treatment modalities needs to be confirmed.

  11. Ethics, Collaboration, and Presentation Methods for Local and Traditional Knowledge for Understanding Arctic Change

    Science.gov (United States)

    Parsons, M. A.; Gearheard, S.; McNeave, C.

    2009-12-01

    Local and traditional knowledge (LTK) provides rich information about the Arctic environment at spatial and temporal scales that scientific knowledge often does not have access to (e.g. localized observations of fine-scale ecological change potentially from many different communities, or local sea ice and conditions prior to 1950s ice charts and 1970s satellite records). Community-based observations and monitoring are an opportunity for Arctic residents to provide ‘frontline’ observations and measurements that are an early warning system for Arctic change. The Exchange for Local Observations and Knowledge of the Arctic (ELOKA) was established in response to the growing number of community-based and community-oriented research and observation projects in the Arctic. ELOKA provides data management and user support to facilitate the collection, preservation, exchange, and use of local observations and knowledge. Managing these data presents unique ethical challenges in terms of appropriate use of rare human knowledge and ensuring that knowledge is not lost from the local communities and not exploited in ways antithetical to community culture and desires. Local Arctic residents must be engaged as true collaborative partners while respecting their perspectives, which may vary substantially from a western science perspective. At the same time, we seek to derive scientific meaning from the local knowledge that can be used in conjunction with quantitative science data. This creates new challenges in terms of data presentation, knowledge representations, and basic issues of metadata. This presentation reviews these challenges, some initial approaches to addressing them, and overall lessons learned and future directions.

  12. Traditional method of fish treatment, microbial count and palatability studies on spoiled fish

    Directory of Open Access Journals (Sweden)

    Abd Aziz, N. A.

    2013-01-01

    Full Text Available Aims: To evaluate the microbial count and palatability acceptance of spoiled fish after treatment with traditionally used naturalsolution.Methodology and results: To compare microbial count of spoiled fish before and after treatment with natural solution practicedby local people in Malaysia, 10 g of spoiled fish was respectively rinsed with 100 mL of 0.1% of natural solution such as Averrhoabilimbi extract, rice rinsed water, rice vinegar, Citrus aurantifolia extract, salt, flour, and Tamarindus indica extract. Flesh of fishrinsed with rice vinegar was found to be able to reduce microbial count (CFU/mL = 0.37 X 107 more than 4.5 times whencompared to spoiled fish (CFU/mL=1.67x 107. Spoiled fish that was treated with rice vinegar was prepared into a cutlet and fried.The cutlet was subjected to palatability acceptance study by a group of residents in Palm Court Condominium, Brickfields, KualaLumpur. The palatability study from the Cronbach alpha shown that the taste have the reliability of 0.802, the aroma has thereliability of 0.888, colour with the reliability of 0.772, texture or mouth feel have reliability of 0.840 and physical structure of thecutlet is 0.829.Conclusion, significance and impact of study: Treatment of spoiled fish using rice vinegar as practice by local peopletraditionally shown a significant reduction in microbial count and the vinegar-treated fish could be developed into a product that issafe and acceptable by the consumer.

  13. The potential of clustering methods to define intersection test scenarios: Assessing real-life performance of AEB.

    Science.gov (United States)

    Sander, Ulrich; Lubbe, Nils

    2018-04-01

    Intersection accidents are frequent and harmful. The accident types 'straight crossing path' (SCP), 'left turn across path - oncoming direction' (LTAP/OD), and 'left-turn across path - lateral direction' (LTAP/LD) represent around 95% of all intersection accidents and one-third of all police-reported car-to-car accidents in Germany. The European New Car Assessment Program (Euro NCAP) have announced that intersection scenarios will be included in their rating from 2020; however, how these scenarios are to be tested has not been defined. This study investigates whether clustering methods can be used to identify a small number of test scenarios sufficiently representative of the accident dataset to evaluate Intersection Automated Emergency Braking (AEB). Data from the German In-Depth Accident Study (GIDAS) and the GIDAS-based Pre-Crash Matrix (PCM) from 1999 to 2016, containing 784 SCP and 453 LTAP/OD accidents, were analyzed with principal component methods to identify variables that account for the relevant total variances of the sample. Three different methods for data clustering were applied to each of the accident types, two similarity-based approaches, namely Hierarchical Clustering (HC) and Partitioning Around Medoids (PAM), and the probability-based Latent Class Clustering (LCC). The optimum number of clusters was derived for HC and PAM with the silhouette method. The PAM algorithm was both initiated with random start medoid selection and medoids from HC. For LCC, the Bayesian Information Criterion (BIC) was used to determine the optimal number of clusters. Test scenarios were defined from optimal cluster medoids weighted by their real-life representation in GIDAS. The set of variables for clustering was further varied to investigate the influence of variable type and character. We quantified how accurately each cluster variation represents real-life AEB performance using pre-crash simulations with PCM data and a generic algorithm for AEB intervention. The

  14. Noniterative Multireference Coupled Cluster Methods on Heterogeneous CPU-GPU Systems

    Energy Technology Data Exchange (ETDEWEB)

    Bhaskaran-Nair, Kiran; Ma, Wenjing; Krishnamoorthy, Sriram; Villa, Oreste; van Dam, Hubertus JJ; Apra, Edoardo; Kowalski, Karol

    2013-04-09

    A novel parallel algorithm for non-iterative multireference coupled cluster (MRCC) theories, which merges recently introduced reference-level parallelism (RLP) [K. Bhaskaran-Nair, J.Brabec, E. Aprà, H.J.J. van Dam, J. Pittner, K. Kowalski, J. Chem. Phys. 137, 094112 (2012)] with the possibility of accelerating numerical calculations using graphics processing unit (GPU) is presented. We discuss the performance of this algorithm on the example of the MRCCSD(T) method (iterative singles and doubles and perturbative triples), where the corrections due to triples are added to the diagonal elements of the MRCCSD (iterative singles and doubles) effective Hamiltonian matrix. The performance of the combined RLP/GPU algorithm is illustrated on the example of the Brillouin-Wigner (BW) and Mukherjee (Mk) state-specific MRCCSD(T) formulations.

  15. Using the clustered circular layout as an informative method for visualizing protein-protein interaction networks.

    Science.gov (United States)

    Fung, David C Y; Wilkins, Marc R; Hart, David; Hong, Seok-Hee

    2010-07-01

    The force-directed layout is commonly used in computer-generated visualizations of protein-protein interaction networks. While it is good for providing a visual outline of the protein complexes and their interactions, it has two limitations when used as a visual analysis method. The first is poor reproducibility. Repeated running of the algorithm does not necessarily generate the same layout, therefore, demanding cognitive readaptation on the investigator's part. The second limitation is that it does not explicitly display complementary biological information, e.g. Gene Ontology, other than the protein names or gene symbols. Here, we present an alternative layout called the clustered circular layout. Using the human DNA replication protein-protein interaction network as a case study, we compared the two network layouts for their merits and limitations in supporting visual analysis.

  16. Equation-of-motion coupled cluster method for high spin double electron attachment calculations

    Energy Technology Data Exchange (ETDEWEB)

    Musiał, Monika, E-mail: musial@ich.us.edu.pl; Lupa, Łukasz; Kucharski, Stanisław A. [Institute of Chemistry, University of Silesia, Szkolna 9, 40-006 Katowice (Poland)

    2014-03-21

    The new formulation of the equation-of-motion (EOM) coupled cluster (CC) approach applicable to the calculations of the double electron attachment (DEA) states for the high spin components is proposed. The new EOM equations are derived for the high spin triplet and quintet states. In both cases the new equations are easier to solve but the substantial simplification is observed in the case of quintets. Out of 21 diagrammatic terms contributing to the standard DEA-EOM-CCSDT equations for the R{sub 2} and R{sub 3} amplitudes only four terms survive contributing to the R{sub 3} part. The implemented method has been applied to the calculations of the excited states (singlets, triplets, and quintets) energies of the carbon and silicon atoms and potential energy curves for selected states of the Na{sub 2} (triplets) and B{sub 2} (quintets) molecules.

  17. Novel strategy to implement active-space coupled-cluster methods

    Science.gov (United States)

    Rolik, Zoltán; Kállay, Mihály

    2018-03-01

    A new approach is presented for the efficient implementation of coupled-cluster (CC) methods including higher excitations based on a molecular orbital space partitioned into active and inactive orbitals. In the new framework, the string representation of amplitudes and intermediates is used as long as it is beneficial, but the contractions are evaluated as matrix products. Using a new diagrammatic technique, the CC equations are represented in a compact form due to the string notations we introduced. As an application of these ideas, a new automated implementation of the single-reference-based multi-reference CC equations is presented for arbitrary excitation levels. The new program can be considered as an improvement over the previous implementations in many respects; e.g., diagram contributions are evaluated by efficient vectorized subroutines. Timings for test calculations for various complete active-space problems are presented. As an application of the new code, the weak interactions in the Be dimer were studied.

  18. Application of the cluster variation method to ordering in an interstitital solid solution

    DEFF Research Database (Denmark)

    Pekelharing, Marjon I.; Böttger, Amarante; Somers, Marcel A. J.

    1999-01-01

    The tetrahedron approximation of the cluster variation method (CVM) was applied to describe the ordering on the fcc interstitial sublattice of gamma-Fe[N] and gamma'-Fe4N1-x. A Lennard-Jones potential was used to describe the dominantly strain-induced interactions, caused by misfitting of the N...... atoms in the interstitial octahedral sites. The gamma-Fe[N]/gamma'-Fe4N1-x miscibility gap, short range ordering (SRO), and long-range ordering (LRO) of nitrogen in gamma-Fe[N] and gamma'-Fe4N1-x, respectively, and lattice parameters of gamma and gamm' were calculated. For the first time, N distribution...... parameters,as calculated by CVM, were compared directly to Mössbauer data for specific surroundings of Fe atoms....

  19. Novel Signal Noise Reduction Method through Cluster Analysis, Applied to Photoplethysmography.

    Science.gov (United States)

    Waugh, William; Allen, John; Wightman, James; Sims, Andrew J; Beale, Thomas A W

    2018-01-01

    Physiological signals can often become contaminated by noise from a variety of origins. In this paper, an algorithm is described for the reduction of sporadic noise from a continuous periodic signal. The design can be used where a sample of a periodic signal is required, for example, when an average pulse is needed for pulse wave analysis and characterization. The algorithm is based on cluster analysis for selecting similar repetitions or pulses from a periodic single. This method selects individual pulses without noise, returns a clean pulse signal, and terminates when a sufficiently clean and representative signal is received. The algorithm is designed to be sufficiently compact to be implemented on a microcontroller embedded within a medical device. It has been validated through the removal of noise from an exemplar photoplethysmography (PPG) signal, showing increasing benefit as the noise contamination of the signal increases. The algorithm design is generalised to be applicable for a wide range of physiological (physical) signals.

  20. A New Method to Constrain Supernova Fractions Using X-ray Observations of Clusters of Galaxies

    Science.gov (United States)

    Bulbul, Esra; Smith, Randall K.; Loewenstein, Michael

    2012-01-01

    Supernova (SN) explosions enrich the intracluster medium (ICM) both by creating and dispersing metals. We introduce a method to measure the number of SNe and relative contribution of Type Ia supernovae (SNe Ia) and core-collapse supernovae (SNe cc) by directly fitting X-ray spectral observations. The method has been implemented as an XSPEC model called snapec. snapec utilizes a single-temperature thermal plasma code (apec) to model the spectral emission based on metal abundances calculated using the latest SN yields from SN Ia and SN cc explosion models. This approach provides a self-consistent single set of uncertainties on the total number of SN explosions and relative fraction of SN types in the ICM over the cluster lifetime by directly allowing these parameters to be determined by SN yields provided by simulations. We apply our approach to XMM-Newton European Photon Imaging Camera (EPIC), Reflection Grating Spectrometer (RGS), and 200 ks simulated Astro-H observations of a cooling flow cluster, A3112.We find that various sets of SN yields present in the literature produce an acceptable fit to the EPIC and RGS spectra of A3112. We infer that 30.3% plus or minus 5.4% to 37.1% plus or minus 7.1% of the total SN explosions are SNe Ia, and the total number of SN explosions required to create the observed metals is in the range of (1.06 plus or minus 0.34) x 10(exp 9), to (1.28 plus or minus 0.43) x 10(exp 9), fromsnapec fits to RGS spectra. These values may be compared to the enrichment expected based on well-established empirically measured SN rates per star formed. The proportions of SNe Ia and SNe cc inferred to have enriched the ICM in the inner 52 kiloparsecs of A3112 is consistent with these specific rates, if one applies a correction for the metals locked up in stars. At the same time, the inferred level of SN enrichment corresponds to a star-to-gas mass ratio that is several times greater than the 10% estimated globally for clusters in the A3112 mass range.

  1. Re-Defining Traditional Bazaar Areas and Shade Structures Via Parametric Design Methods

    Directory of Open Access Journals (Sweden)

    Ahmet Emre Dinçer

    2017-12-01

    Full Text Available For the continuation of life, people created various equipment and goods. To create mutual benefits, they’ve exchanged the overpruduced items with different products. This has begun the shopping act. By the increased amount of transactions, a need of defined area for shopping have arisen.  For a temporary time, trading areas have been developed at different locations at a certain period. In the course of time, beside trading, these areas served as socio-cultural spaces where the human relations were established. Moreover, demand of being able to immediately access to needed goods have emerged. This situation made having a permanent trading area essential. Therefore, enclosed and permanent trade areas from bazaar, inn, bedesten, arasta to shopping malls have emerged. Next to all these trading areas, traditional bazaar areas keep being established. Nowadays, there is a need of providing some determined comfort conditions to the users for these street alley bazaars. Decreasing the effect of unfavorable weather conditions and providing supportive certain services and units (like WCs, security, cleanliness, etc. are some of them. As a fundamental solution, without disengaging the user relations with the outside, shade structures are generally provided. Shade structures can support cleaning and similar jobs by gathering and using rainwater besides its purpose of protecting the user from bad weather conditions. Application examples of these systems are gradually increasing. However, it is necessary to develop new approaches, in order to stop these proposed shade structures, become prototypes and to adapt the proposal to its environment and to increase diversity. In this study, a convenient shade structure and its alternatives, which are adapted to environmental conditions, were designed to create a sample model for other bazaar areas. In models, basically, folding design approaches were pursued. For production of these shade structure models

  2. Machine cost analysis using the traditional machine-rate method and ChargeOut!

    Science.gov (United States)

    E. M. (Ted) Bilek

    2009-01-01

    Forestry operations require ever more use of expensive capital equipment. Mechanization is frequently necessary to perform cost-effective and safe operations. Increased capital should mean more sophisticated capital costing methodologies. However the machine rate method, which is the costing methodology most frequently used, dates back to 1942. CHARGEOUT!, a recently...

  3. Combining traditional dietary assessment methods with novel metabolomics techniques : present efforts by the Food Biomarker Alliance

    NARCIS (Netherlands)

    Brouwer-Brolsma, Elske M.; Brennan, Lorraine; Drevon, Christian A.; van Kranen, Henk; Manach, Claudine; Dragsted, Lars Ove; Roche, Helen M.; Andres-Lacueva, Cristina; Bakker, Stephan J. L.; Bouwman, Jildau; Capozzi, Francesco; De Saeger, Sarah; Gundersen, Thomas E.; Kolehmainen, Marjukka; Kulling, Sabine E.; Landberg, Rikard; Linseisen, Jakob; Mattivi, Fulvio; Mensink, Ronald P.; Scaccini, Cristina; Skurk, Thomas; Tetens, Inge; Vergeres, Guy; Wishart, David S.; Scalbert, Augustin; Feskens, Edith J. M.

    FFQ, food diaries and 24 h recall methods represent the most commonly used dietary assessment tools in human studies on nutrition and health, but food intake biomarkers are assumed to provide a more objective reflection of intake. Unfortunately, very few of these biomarkers are sufficiently

  4. Developing a Pictorial Sisterhood Method in collaboration with illiterate Maasai traditional birth attendants in northern Tanzania

    NARCIS (Netherlands)

    Roggeveen, Yadira; Schreuder, Renske; Zweekhorst, Marjolein; Manyama, Mange; Hatfield, Jennifer; Scheele, Fedde; van Roosmalen, Jos

    2016-01-01

    Objective To study whether data on maternal mortality can be gathered while maintaining local ownership of data in a pastoralist setting where a scarcity of data sources and a culture of silence around maternal death amplifies limited awareness of the magnitude of maternal mortality. Methods As part

  5. Comparison study between traditional and finite element methods for slopes under heavy rainfall

    Directory of Open Access Journals (Sweden)

    M. Rabie

    2014-08-01

    Moreover, slope stability concerning rainfall and infiltration is analyzed. Specially, two kinds of infiltrations (saturated and unsaturated are considered. Many slopes become saturated during periods of intense rainfall or snowmelt, with the water table rising to the ground surface, and water flowing essentially parallel to the direction of the “slope” and “Influence” of the change in shear strength, density, pore-water pressure and seepage force in soil slices on the slope stability is explained. Finally, it is found that classical limit equilibrium methods are highly conservative compared to the finite element approach. For assessment the factor of safety for slope using the later technique, no assumption needs to be made in advance about the shape or location of the failure surface, slice side forces and their directions. This document outlines the capabilities of the finite element method in the analysis of slope stability problems.

  6. A better way to teach knot tying: a randomized controlled trial comparing the kinesthetic and traditional methods.

    Science.gov (United States)

    Huang, Emily; Chern, Hueylan; O'Sullivan, Patricia; Cook, Brian; McDonald, Erik; Palmer, Barnard; Liu, Terrence; Kim, Edward

    2014-10-01

    Knot tying is a fundamental and crucial surgical skill. We developed a kinesthetic pedagogical approach that increases precision and economy of motion by explicitly teaching suture-handling maneuvers and studied its effects on novice performance. Seventy-four first-year medical students were randomized to learn knot tying via either the traditional or the novel "kinesthetic" method. After 1 week of independent practice, students were videotaped performing 4 tying tasks. Three raters scored deidentified videos using a validated visual analog scale. The groups were compared using analysis of covariance with practice knots as a covariate and visual analog scale score (range, 0 to 100) as the dependent variable. Partial eta-square was calculated to indicate effect size. Overall rater reliability was .92. The kinesthetic group scored significantly higher than the traditional group for individual tasks and overall, controlling for practice (all P kinesthetic overall mean was 64.15 (standard deviation = 16.72) vs traditional 46.31 (standard deviation = 16.20; P kinesthetic suture handling substantively improved performance on knot tying. We believe this effect can be extrapolated to more complex surgical skills. Copyright © 2014 Elsevier Inc. All rights reserved.

  7. Teaching design in the first years of a traditional mechanical engineering degree: methods, issues and future perspectives

    Science.gov (United States)

    Silva, Arlindo; Fontul, Mihail; Henriques, Elsa

    2015-01-01

    Engineering design is known as an answer to an ill-defined problem. As any answer to an ill-defined problem, it can never be completely right or absolutely wrong. The methods that universities use to teach engineering design, as a consequence of this, suffer from the same fate. However, the accumulated experience with the 'chalk and talk' teaching tradition has led to a reality in which the employers of fresh graduates are not happy with the engineers they are getting. Part of their complaints are related with the inability of recently graduate engineers to work in problems where the boundaries are not well defined, are interdisciplinary, require the use of effective communication and integrate non-technical issues. These skills are mostly absent from traditional engineering curricula. This paper demonstrates the implementation of engineering design perspectives enhancing some of the aforementioned skills in a traditional mechanical engineering curriculum. It emphasises in particular a design project that is tackled in a sequence of conventional courses with a focus that depends on the course objectives and disciplinary domain. This transdisciplinary design project conveys the idea (and effectively implements it concurrently) that design is multidisciplinary.

  8. REGARDING A METHOD OF PERFORMING ON THE VIOLIN IN TRADITIONAL MUSIC

    Directory of Open Access Journals (Sweden)

    MIRONENCO IAROSLAV

    2016-06-01

    Full Text Available Following a field study in the village of Lozova, Străşeni, aimed at identifying the variants of a folk song recorded by I. Mironenko from an informant living in the village of Thamaha, North Caucasus — Russia, a village inhabited by Moldovans, the musicologist discovered a fiddler who demonstrated him a specific process of executation on the violin. This method is representative of an advanced level of interpretation on the violin.

  9. [Study on two preparation methods for beta-CD inclusion compound of four traditional Chinese medicine volatile oils].

    Science.gov (United States)

    Li, Hailiang; Cui, Xiaoli; Tong, Yan; Gong, Muxin

    2012-04-01

    To compare inclusion effects and process conditions of two preparation methods-colloid mill and saturated solution-for beta-CD inclusion compound of four traditional Chinese medicine volatile oils and study the relationship between each process condition and volatile oil physical properties and the regularity of selective inclusion of volatile oil components. Volatile oils from Nardostachyos Radix et Rhizoma, Amomi Fructus, Zingiberis Rhizoma and Angelicaesinensis Radix were prepared using two methods in the orthogonal test. These inclusion compounds by optimized processes were assessed and compared by such methods as TLC, IR and scanning electron microscope. Inclusion oils were extracted by steam distillation, and the components found before and after inclusion were analyzed by GC-MS. Analysis showed that new inclusion compounds, but inclusion compounds prepared by the two processes had differences to some extent. The colloid mill method showed a better inclusion effect than the saturated solution method, indicating that their process conditions had relations with volatile oil physical properties. There were differences in the inclusion selectivity of components between each other. The colloid mill method for inclusion preparation is more suitable for industrial requirements. To prepare volatile oil inclusion compounds with heavy gravity and high refractive index, the colloid mill method needs longer time and more water, while the saturated solution method requires higher temperature and more beta-cyclodextrin. The inclusion complex prepared with the colloid mill method contains extended molecular weight chemical composition, but the kinds of components are reduced.

  10. Practical implications of procedures developed in IDEA project - Comparison with traditional methods

    International Nuclear Information System (INIS)

    Andrasi, A.; Bouvier, C.; Brandl, A.; De Carlan, L.; Fischer, H.; Franck, D.; Hoellriegl, V.; Li, W. B.; Oeh, U.; Ritt, J.; Roth, P.; Schlagbauer, M.; Schmitzer, Ch; Wahl, W.; Zombori, P.

    2007-01-01

    The idea of the IDEA project aimed to improve assessment of incorporated radionuclides through developments of more reliable and possibly faster in vivo and bioassay monitoring techniques and making use of such enhancements for improvements in routine monitoring. In direct in vivo monitoring technique the optimum choice of the detectors to be applied for different monitoring tasks has been investigated in terms of material, size and background in order to improve conditions namely to increase counting efficiency and reduce background. Detailed studies have been performed to investigate the manifold advantageous applications and capabilities of numerical simulation method for the calibration and optimisation of in vivo counting systems. This calibration method can be advantageously applied especially in the measurement of low-energy photon emitting radionuclides, where individual variability is a significant source of uncertainty. In bioassay measurements the use of inductively coupled plasma mass spectrometry (ICP-MS) can improve considerably both the measurement speed and the lower limit of detection currently achievable with alpha spectrometry for long-lived radionuclides. The work carried out in this project provided detailed guidelines for optimum performance of the technique of ICP-MS applied mainly for the determination of uranium and thorium nuclides in the urine including sampling procedure, operational parameters of the instruments and interpretation of the measured data. The paper demonstrates the main advantages of investigated techniques in comparison with the performances of methods commonly applied in routine monitoring practice. (authors)

  11. Comparison of teaching about breast cancer via mobile or traditional learning methods in gynecology residents.

    Science.gov (United States)

    Alipour, Sadaf; Moini, Ashraf; Jafari-Adli, Shahrzad; Gharaie, Nooshin; Mansouri, Khorshid

    2012-01-01

    Mobile learning enables users to interact with educational resources while in variable locations. Medical students in residency positions need to assimilate considerable knowledge besides their practical training and we therefore aimed to evaluate the impact of using short message service via cell phone as a learning tool in residents of Obstetrics and Gynecology in our hospital. We sent short messages including data about breast cancer to the cell phones of 25 residents of gynecology and obstetrics and asked them to study a well-designed booklet containing another set of information about the disease in the same period. The rate of learning derived from the two methods was compared by pre- and post-tests and self-satisfaction assessed by a relevant questionnaire at the end of the program. The mobile learning method had a significantly better effect on learning and created more interest in the subject. Learning via receiving SMS can be an effective and appealing method of knowledge acquisition in higher levels of education.

  12. Formulation of an aloe-based product according to Iranian traditional medicine and development of its analysis method.

    Science.gov (United States)

    Moein, Elham; Hajimehdipoor, Homa; Toliyat, Tayebeh; Choopani, Rasool; Hamzeloo-Moghadam, Maryam

    2017-08-29

    Currently, people are more interested to traditional medicine. The traditional formulations should be converted to modern drug delivery systems to be more acceptable for the patients. In the present investigation, a poly herbal medicine "Ayarij-e-Faiqra" (AF) based on Iranian traditional medicine (ITM) has been formulated and its quality control parameters have been developed. The main ingredients of AF including barks of Cinnamomum zeylanicum Blume and Cinnamomum cassia J. Presl, the rhizomes of Nardostachys jatamansi DC., the fruits of Piper cubeba L.f., the flowers of Rosa damascena Herrm., the oleo gum resin of Pistacia terebinthus L. and Aloe spp. dried juice were powdered and used for preparing seven tablet formulations of the herbal mixture. Flowability of the different formulated powders was examined and the best formulations were selected (F6&F7). The tablets were prepared from the selected formulations compared according to the physical characteristics and finally, F7 was selected and coated. Physicochemical characters of core and coated AF tablets were determined and the HPLC method for quantitation of aloin as a marker of tablets was selected and verified according to selectivity, linearity, precision, recovery, LOD and LOQ. The results showed that core and coated AF tablets were in agreement with USP requirements for herbal drugs. They had acceptable appearance, disintegration time, friability, hardness, dissolution behavior, weight variation and content uniformity. The amount of aloin in tablets was found 123.1 mg/tab. The HPLC method for aloin determination in AF tablets was verified according to selectivity, linearity (5-500 μg/ml, r 2 :0.9999), precision (RSD: 1.62%), recovery (108.0%), LOD & LOQ (0.0053 & 0.0161 μg/ml). The formulated tablets could be a good substitute for powder and capsules of AF in ITM clinics with a feasible and precise method for its quality control. Ayarij-e-Faiqra formulation.

  13. A Novel Cluster Head Selection Algorithm Based on Fuzzy Clustering and Particle Swarm Optimization.

    Science.gov (United States)

    Ni, Qingjian; Pan, Qianqian; Du, Huimin; Cao, Cen; Zhai, Yuqing

    2017-01-01

    An important objective of wireless sensor network is to prolong the network life cycle, and topology control is of great significance for extending the network life cycle. Based on previous work, for cluster head selection in hierarchical topology control, we propose a solution based on fuzzy clustering preprocessing and particle swarm optimization. More specifically, first, fuzzy clustering algorithm is used to initial clustering for sensor nodes according to geographical locations, where a sensor node belongs to a cluster with a determined probability, and the number of initial clusters is analyzed and discussed. Furthermore, the fitness function is designed considering both the energy consumption and distance factors of wireless sensor network. Finally, the cluster head nodes in hierarchical topology are determined based on the improved particle swarm optimization. Experimental results show that, compared with traditional methods, the proposed method achieved the purpose of reducing the mortality rate of nodes and extending the network life cycle.

  14. HPLC Method for Simultaneous Quantitative Detection of Quercetin and Curcuminoids in Traditional Chinese Medicines

    Directory of Open Access Journals (Sweden)

    Lee Fung Ang

    2014-12-01

    Full Text Available Objectives: Quercetin and curcuminoids are important bioactive compounds found in many herbs. Previously reported high performance liquid chromatography ultraviolet (HPLC-UV methods for the detection of quercetin and curcuminoids have several disadvantages, including unsatisfactory separation times and lack of validation according the standard guidelines of the International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use. Methods: A rapid, specific, reversed phase, HPLC-UV method with an isocratic elution of acetonitrile and 2% v/v acetic acid (40% : 60% v/v (pH 2.6 at a flow rate of 1.3 mL/minutes, a column temperature of 35°C, and ultraviolet (UV detection at 370 nm was developed. The method was validated and applied to the quantification of different types of market available Chinese medicine extracts, pills and tablets. Results: The method allowed simultaneous determination of quercetin, bisdemethoxycurcumin, demethoxycurcumin and curcumin in the concentration ranges of 0.00488 ─ 200 μg/mL, 0.625 ─ 320 μg/mL, 0.07813 ─ 320 μg/mL and 0.03906 ─ 320 μg/mL, respectively. The limits of detection and quantification, respectively, were 0.00488 and 0.03906 μg/mL for quercetin, 0.62500 and 2.50000 μg/mL for bisdemethoxycurcumin, 0.07813 and 0.31250 μg/mL for demethoxycurcumin, and 0.03906 and 0.07813 μg/mL for curcumin. The percent relative intra day standard deviation (% RSD values were 0.432 ─ 0.806 μg/mL, 0.576 ─ 0.723 μg/ mL, 0.635 ─ 0.752 μg/mL and 0.655 ─ 0.732 μg/mL for quercetin, bisdemethoxycurcumin, demethoxycurcumin and curcumin, respectively, and those for intra day precision were 0.323 ─ 0.968 μg/mL, 0.805 ─ 0.854 μg/mL, 0.078 ─ 0.844 μg/mL and 0.275 ─ 0.829 μg/mL, respectively. The intra day accuracies were 99.589% ─ 100.821%, 98.588% ─ 101.084%, 9.289% ─ 100.88%, and 98.292% ─ 101.022% for quercetin, bisdemethoxycurcumin

  15. Damage evolution analysis of coal samples under cyclic loading based on single-link cluster method

    Science.gov (United States)

    Zhang, Zhibo; Wang, Enyuan; Li, Nan; Li, Xuelong; Wang, Xiaoran; Li, Zhonghui

    2018-05-01

    In this paper, the acoustic emission (AE) response of coal samples under cyclic loading is measured. The results show that there is good positive relation between AE parameters and stress. The AE signal of coal samples under cyclic loading exhibits an obvious Kaiser Effect. The single-link cluster (SLC) method is applied to analyze the spatial evolution characteristics of AE events and the damage evolution process of coal samples. It is found that a subset scale of the SLC structure becomes smaller and smaller when the number of cyclic loading increases, and there is a negative linear relationship between the subset scale and the degree of damage. The spatial correlation length ξ of an SLC structure is calculated. The results show that ξ fluctuates around a certain value from the second cyclic loading process to the fifth cyclic loading process, but spatial correlation length ξ clearly increases in the sixth loading process. Based on the criterion of microcrack density, the coal sample failure process is the transformation from small-scale damage to large-scale damage, which is the reason for changes in the spatial correlation length. Through a systematic analysis, the SLC method is an effective method to research the damage evolution process of coal samples under cyclic loading, and will provide important reference values for studying coal bursts.

  16. An alternant method to the traditional NASA hindlimb unloading model in mice.

    Science.gov (United States)

    Ferreira, J Andries; Crissey, Jacqueline M; Brown, Marybeth

    2011-03-10

    The Morey-Holton hindlimb unloading (HU) method is a widely accepted National Aeronautics and Space Administration (NASA) ground-based model for studying disuse-atrophy in rodents. Our study evaluated an alternant method to the gold-standard Morey-Holton HU tail-traction technique in mice. Fifty-four female mice (4-8 mo.) were HU for 14 days (n=34) or 28 days (n=20). Recovery from HU was assessed after 3 days of normal cage ambulation following HU (n=22). Aged matched mice (n=76) served as weight-bearing controls. Prior to HU a tail ring was formed with a 2-0 sterile surgical steel wire that was passed through the 5(th), 6(th), or 7(th) inter-vertebral disc space and shaped into a ring from which the mice were suspended. Vertebral location for the tail-ring was selected to appropriately balance animal body weight without interfering with defecation. We determined the success of this novel HU technique by assessing body weight before and after HU, degree of soleus atrophy, and adrenal mass following HU. Body weight of the mice prior to HU (24.3 ± 2.9g) did not significantly decline immediately after 14d of HU (22.7 ± 1.9g), 28d of HU (21.3 + 2.1g) or after 3 days recovery (24.0 ± 1.8g). Soleus muscle mass significantly declined (-39.1%, and -46.6%) following HU for 14 days and 28 days respectively (p<0.001). Following 3 days of recovery soleus mass significantly increased to 74% of control values. Adrenal weights of HU mice were not different compared to control mice. The success of our novel HU method is evidenced by the maintenance of animal body weight, comparable adrenal gland weights, and soleus atrophy following HU, corresponding to expected literature values. The primary advantages of this HU method include: 1) ease of tail examination during suspension; 2) decreased likelihood of cyanotic, inflamed, and/or necrotic tails frequently observed with tail-taping and HU; 3) no possibility of mice chewing the traction tape and coming out of the suspension

  17. Avocado oil extraction processes: method for cold-pressed high-quality edible oil production versus traditional production

    OpenAIRE

    Giacomo Costagli; Matteo Betti

    2015-01-01

    Nowadays the avocado fruit (Persea americana Mill.) is widely regarded as an important fruit for its nutritional values, as it is rich in vital human nutrients. The avocado fruit is mainly sold fresh on the market, which however trades also a relevant quantity of second-grade fruits with a relatively high oil content. Traditionally, this oil is extracted from dried fruits by means of organic solvents, but a mechanical method is also used in general in locations where drying systems and/or sol...

  18. DLTAP: A Network-efficient Scheduling Method for Distributed Deep Learning Workload in Containerized Cluster Environment

    OpenAIRE

    Qiao Wei; Li Ying; Wu Zhong-Hai

    2017-01-01

    Deep neural networks (DNNs) have recently yielded strong results on a range of applications. Training these DNNs using a cluster of commodity machines is a promising approach since training is time consuming and compute-intensive. Furthermore, putting DNN tasks into containers of clusters would enable broader and easier deployment of DNN-based algorithms. Toward this end, this paper addresses the problem of scheduling DNN tasks in the containerized cluster environment. Efficiently scheduling ...

  19. HPLC method for simultaneous quantitative detection of quercetin and curcuminoids in traditional chinese medicines.

    Science.gov (United States)

    Ang, Lee Fung; Yam, Mun Fei; Fung, Yvonne Tan Tze; Kiang, Peh Kok; Darwin, Yusrida

    2014-12-01

    Quercetin and curcuminoids are important bioactive compounds found in many herbs. Previously reported high performance liquid chromatography ultraviolet (HPLC-UV) methods for the detection of quercetin and curcuminoids have several disadvantages, including unsatisfactory separation times and lack of validation according the standard guidelines of the International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use. A rapid, specific, reversed phase, HPLC-UV method with an isocratic elution of acetonitrile and 2% v/v acetic acid (40% : 60% v/v) (pH 2.6) at a flow rate of 1.3 mL/minutes, a column temperature of 35°C, and ultraviolet (UV) detection at 370 nm was developed. The method was validated and applied to the quantification of different types of market available Chinese medicine extracts, pills and tablets. The method allowed simultaneous determination of quercetin, bisdemethoxycurcumin, demethoxycurcumin and curcumin in the concentration ranges of 0.00488 ─ 200 μg/mL, 0.625 ─ 320 μg/mL, 0.07813 ─ 320 μg/mL and 0.03906 ─ 320 μg/mL, respectively. The limits of detection and quantification, respectively, were 0.00488 and 0.03906 μg/mL for quercetin, 0.62500 and 2.50000 μg/mL for bisdemethoxycurcumin, 0.07813 and 0.31250 μg/mL for demethoxycurcumin, and 0.03906 and 0.07813 μg/mL for curcumin. The percent relative intra day standard deviation (% RSD) values were 0.432 ─ 0.806 μg/mL, 0.576 ─ 0.723 μg/mL, 0.635 ─ 0.752 μg/mL and 0.655 ─ 0.732 μg/mL for quercetin, bisdemethoxycurcumin, demethoxycurcumin and curcumin, respectively, and those for intra day precision were 0.323 ─ 0.968 μg/mL, 0.805 ─ 0.854 μg/mL, 0.078 ─ 0.844 μg/mL and 0.275 ─ 0.829 μg/mL, respectively. The intra day accuracies were 99.589% ─ 100.821%, 98.588% ─ 101.084%, 9.289% ─ 100.88%, and 98.292% ─ 101.022% for quercetin, bisdemethoxycurcumin, demethoxycurcumin and curcumin, respectively, and the

  20. An experimental detrending approach to attributing change of pan evaporation in comparison with the traditional partial differential method

    Science.gov (United States)

    Wang, Tingting; Sun, Fubao; Xia, Jun; Liu, Wenbin; Sang, Yanfang

    2017-04-01

    In predicting how droughts and hydrological cycles would change in a warming climate, change of atmospheric evaporative demand measured by pan evaporation (Epan) is one crucial element to be understood. Over the last decade, the derived partial differential (PD) form of the PenPan equation is a prevailing attribution approach to attributing changes to Epan worldwide. However, the independency among climatic variables required by the PD approach cannot be met using long term observations. Here we designed a series of numerical experiments to attribute changes of Epan over China by detrending each climatic variable, i.e., an experimental detrending approach, to address the inter-correlation among climate variables, and made comparison with the traditional PD method. The results show that the detrending approach is superior not only to a complicate system with multi-variables and mixing algorithm like aerodynamic component (Ep,A) and Epan, but also to a simple case like radiative component (Ep,R), when compared with traditional PD method. The major reason for this is the strong and significant inter-correlation of input meteorological forcing. Very similar and fine attributing results have been achieved based on detrending approach and PD method after eliminating the inter-correlation of input through a randomize approach. The contribution of Rh and Ta in net radiation and thus Ep,R, which has been overlooked based on the PD method but successfully detected by detrending approach, provides some explanation to the comparing results. We adopted the control run from the detrending approach and applied it to made adjustment of PD method. Much improvement has been made and thus proven this adjustment an effective way in attributing changes to Epan. Hence, the detrending approach and the adjusted PD method are well recommended in attributing changes in hydrological models to better understand and predict water and energy cycle.

  1. The CREATE Method Does Not Result in Greater Gains in Critical Thinking than a More Traditional Method of Analyzing the Primary Literature †

    Science.gov (United States)

    Segura-Totten, Miriam; Dalman, Nancy E.

    2013-01-01

    Analysis of the primary literature in the undergraduate curriculum is associated with gains in student learning. In particular, the CREATE (Consider, Read, Elucidate hypotheses, Analyze and interpret the data, and Think of the next Experiment) method is associated with an increase in student critical thinking skills. We adapted the CREATE method within a required cell biology class and compared the learning gains of students using CREATE to those of students involved in less structured literature discussions. We found that while both sets of students had gains in critical thinking, students who used the CREATE method did not show significant improvement over students engaged in a more traditional method for dissecting the literature. Students also reported similar learning gains for both literature discussion methods. Our study suggests that, at least in our educational context, the CREATE method does not lead to higher learning gains than a less structured way of reading primary literature. PMID:24358379

  2. Dancoff factors with partial neutrons absorption in cluster geometry by the direct method

    International Nuclear Information System (INIS)

    Rodrigues, Leticia Jenisch

    2007-01-01

    Accurate analysis of resonance absorption in heterogeneous systems is essential in problems like criticality, breeding ratios and fuel depletion calculations. In compact arrays of fuel rods, resonance absorption is strongly affected by the Dancoff factor, defined in mis study as the probability that a neutron emitted from the surface of a fuel element, enters another fuel element without any collusion in the moderator or cladding. In fact, in the most practical cases of irregular cells, it is observed that inaccuracies in computing both Grey and Black Dancoff factors, i.e. for partially and perfectly absorbing fuel rods, can lead to considerable errors in the calculated values of such integral quantities. For this reason, much effort has been made in the past decades to further improve the models for calculating Dancoff factors, a task that has been accomplished in connection with the development of faster computers. In the WIMS code, Black Dancoff factors based on the above mentioned collusion probability definition are computed in cluster geometry, for each one of the symmetrically distinct fuel pin positions in the cell. Sets of equally-spaced parallel lines are drawn in subroutine PIJ, at a number of discrete equally-incremented azimuthal angles, covering the whole system and forming a mesh over which the in-plane integrations of the Bickley functions are carried out by simple trapezoidal rule, leading to the first-flight collusion matrices. Although fast, the method in PIJ is inefficient, since the constructed mesh does not depended on the system details, so that regions of small relative volumes are crossed out by relatively few lines, which affects the convergence of the calculated probabilities. A new routine (PIJM) was then created to incorporate a more efficient integration scheme considering each system region individually, minimizing convergence problems and reducing the number of neutron track lines required in the in-plane integrations for any given

  3. Effects of combined traditional processing methods on the nutritional quality of beans.

    Science.gov (United States)

    Nakitto, Aisha M; Muyonga, John H; Nakimbugwe, Dorothy

    2015-05-01

    Consumption of dry beans is limited by long cooking times thus high fuel requirement. The bioavailability of nutrients in beans is also limited due to presence of antinutrients such as phytates and tannins. Little research has been done on combined processing methods for production of nutritious fast cooking bean flour and the effect of combined treatments on nutritional quality of beans has not previously determined. The aim of this study was to reduce cooking time and enhance the nutritional value of dry beans. Specifically to: develop protocols for production of fast cooking bean flours and assess the effect of processing on the nutritional characteristics of the flours. Dry beans (K131 variety) were soaked for 12 h; sprouted for 48 h; dehulled and steamed for 25 and 15 min for whole and dehulled beans respectively or roasted at 170°C for 45 and 15 min for whole and dehulled beans respectively. Dehulling eliminated phytates and tannins and increased protein digestibility. In vitro protein digestibility and mineral (iron and zinc) extractability were negatively correlated with tannin and phytate content. Total available carbohydrates were highest in moist heat-treated bean flours. Overall, combined processing of beans improved the nutritional quality of dry beans and the resulting precooked flours need less cooking time compared to whole dry beans.

  4. Informed consent recall and comprehension in orthodontics: traditional vs improved readability and processability methods.

    Science.gov (United States)

    Kang, Edith Y; Fields, Henry W; Kiyak, Asuman; Beck, F Michael; Firestone, Allen R

    2009-10-01

    Low general and health literacy in the United States means informed consent documents are not well understood by most adults. Methods to improve recall and comprehension of informed consent have not been tested in orthodontics. The purposes of this study were to evaluate (1) recall and comprehension among patients and parents by using the American Association of Orthodontists' (AAO) informed consent form and new forms incorporating improved readability and processability; (2) the association between reading ability, anxiety, and sociodemographic variables and recall and comprehension; and (3) how various domains (treatment, risk, and responsibility) of information are affected by the forms. Three treatment groups (30 patient-parent pairs in each) received an orthodontic case presentation and either the AAO form, an improved readability form (MIC), or an improved readability and processability (pairing audio and visual cues) form (MIC + SS). Structured interviews were transcribed and coded to evaluate recall and comprehension. Significant relationships among patient-related variables and recall and comprehension explained little of the variance. The MIC + SS form significantly improved patient recall and parent recall and comprehension. Recall was better than comprehension, and parents performed better than patients. The MIC + SS form significantly improved patient treatment comprehension and risk recall and parent treatment recall and comprehension. Patients and parents both overestimated their understanding of the materials. Improving the readability of consent materials made little difference, but combining improved readability and processability benefited both patients' recall and parents' recall and comprehension compared with the AAO form.

  5. An investigation into the Traditional Method of Production of Omani Sarooj

    Directory of Open Access Journals (Sweden)

    A. W. Hago

    1999-12-01

    Full Text Available In the past, sarooj had been used as the basic cementing material with which the A flaj system (the irrigation system used in Oman was built. Worldwide, materials like sarooj existed and were known for their good impermeability and long durability. For this reason it was extensively used in hydraulic structures. Even in this century and with the ready availability of Portland cements, special plants were erected to produce materials like sarooj for major dams in the world. In the process of hydration In sarooj-lime mixes or in sarooj-cement mixes free lime is released which causes distress through the expansion of the mortar if allowed to accumulate. If free lime is stabilized within the structure of the mortar. it imparts additional strength and durability to it. The mortar becomes less permeable to water, which increases its resistance to wearhering. The stabilization is possible through the presence of a reactive silica/alumina in the mix so that it reacts with the free lime to form calcium silicates/aluminates. The properties of sarooj depend largely on the type of the raw material and the calcination parameters. This paper describes this material, its method of production and uses, and highlights research currently conducted to improve its properties.

  6. An efficient implementation of parallel molecular dynamics method on SMP cluster architecture

    International Nuclear Information System (INIS)

    Suzuki, Masaaki; Okuda, Hiroshi; Yagawa, Genki

    2003-01-01

    The authors have applied MPI/OpenMP hybrid parallel programming model to parallelize a molecular dynamics (MD) method on a symmetric multiprocessor (SMP) cluster architecture. In that architecture, it can be expected that the hybrid parallel programming model, which uses the message passing library such as MPI for inter-SMP node communication and the loop directive such as OpenMP for intra-SNP node parallelization, is the most effective one. In this study, the parallel performance of the hybrid style has been compared with that of conventional flat parallel programming style, which uses only MPI, both in cases the fast multipole method (FMM) is employed for computing long-distance interactions and that is not employed. The computer environments used here are Hitachi SR8000/MPP placed at the University of Tokyo. The results of calculation are as follows. Without FMM, the parallel efficiency using 16 SMP nodes (128 PEs) is: 90% with the hybrid style, 75% with the flat-MPI style for MD simulation with 33,402 atoms. With FMM, the parallel efficiency using 16 SMP nodes (128 PEs) is: 60% with the hybrid style, 48% with the flat-MPI style for MD simulation with 117,649 atoms. (author)

  7. Comparison of Three Plot Selection Methods for Estimating Change in Temporally Variable, Spatially Clustered Populations.

    Energy Technology Data Exchange (ETDEWEB)

    Thompson, William L. [Bonneville Power Administration, Portland, OR (US). Environment, Fish and Wildlife

    2001-07-01

    Monitoring population numbers is important for assessing trends and meeting various legislative mandates. However, sampling across time introduces a temporal aspect to survey design in addition to the spatial one. For instance, a sample that is initially representative may lose this attribute if there is a shift in numbers and/or spatial distribution in the underlying population that is not reflected in later sampled plots. Plot selection methods that account for this temporal variability will produce the best trend estimates. Consequently, I used simulation to compare bias and relative precision of estimates of population change among stratified and unstratified sampling designs based on permanent, temporary, and partial replacement plots under varying levels of spatial clustering, density, and temporal shifting of populations. Permanent plots produced more precise estimates of change than temporary plots across all factors. Further, permanent plots performed better than partial replacement plots except for high density (5 and 10 individuals per plot) and 25% - 50% shifts in the population. Stratified designs always produced less precise estimates of population change for all three plot selection methods, and often produced biased change estimates and greatly inflated variance estimates under sampling with partial replacement. Hence, stratification that remains fixed across time should be avoided when monitoring populations that are likely to exhibit large changes in numbers and/or spatial distribution during the study period. Key words: bias; change estimation; monitoring; permanent plots; relative precision; sampling with partial replacement; temporary plots.

  8. 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

  9. Non-Hierarchical Clustering as a method to analyse an open-ended ...

    African Journals Online (AJOL)

    Apple

    Keywords: algebraic thinking; cluster analysis; mathematics education; quantitative analysis. Introduction. Extensive ..... C1, C2 and C3 represent the three centroids of the three clusters formed. .... 6ALd. All these strategies are algebraic and 'high- ... 1995), of the didactical aspects related to teaching .... Brazil, 18-23 July.

  10. Clustered iterative stochastic ensemble method for multi-modal calibration of subsurface flow models

    KAUST Repository

    Elsheikh, Ahmed H.; Wheeler, Mary Fanett; Hoteit, Ibrahim

    2013-01-01

    estimation. ISEM is augmented with a clustering step based on k-means algorithm to form sub-ensembles. These sub-ensembles are used to explore different parts of the search space. Clusters are updated at regular intervals of the algorithm to allow merging

  11. Comparison of clustering methods for tracking features in RGB-D images

    CSIR Research Space (South Africa)

    Pancham, Ardhisha

    2016-10-01

    Full Text Available difficult to track individually over an image sequence. Clustering techniques have been recommended and used to cluster image features to improve tracking results. New and affordable RGB-D cameras, provide both color and depth information. This paper...

  12. The comparison of composite aircraft field repair method (cafrm) with traditional aircraft repair technologies

    Science.gov (United States)

    Whelan, Mary Elizabeth

    The sulfur biogeochemical cycle includes biotic and abiotic processes important to global climate, atmospheric chemistry, food security, and the study of related cycles. The largest flux of sulfur on Earth is weathering from the continents into the sulfate-rich oceans; one way in which sulfur can be returned to land is through transport of reduced sulfur gases via the atmosphere. Here I developed a method for quantifying low-level environmental fluxes of several sulfur-containing gases, H2S, COS, CH3SCH 3 (DMS), and HSCH3, between terrestrial ecosystems and the atmosphere. COS is the most prevalent reduced sulfur gas in the atmosphere, considered to be inert in the troposphere except for its uptake in plant leaves and to a smaller extent aerobic soils. This dissertation reports two surprising cases that go against conventional thinking about the sulfur cycle. We found that the common salt marsh plant Batis maritima can mediate net COS production to the atmosphere. We also found that an aerobic wheat field soil produces COS abiotically when incubated in the dark at > 25 °C and at lower temperatures under light conditions. We then sought to separately quantify plant and soil sulfur gas fluxes by undertaking a year-long field campaign in a grassland with a Mediterranean climate, where green plants were present only half of the year. We measured in situ soil fluxes of COS and DMS during the non- growing dry season, using water additions to simulate soil fluxes of the growing, wet season. COS and CO2 are consumed in a predictable ratio by enzymes involved in photosynthetic pathways; however, while CO2 is released by back diffusion and autorespiration, COS is usually not generated by plants. Using measurements during the growing season, we were then able to calculate gross primary production by using the special relationship between CO2 and COS. This dissertation has developed a greater understanding of the vagaries of the atmospheric-terrestrial sulfur cycle and

  13. Facile fabrication of controllable zinc oxide nanorod clusters on polyacrylonitrile nanofibers via repeatedly alternating immersion method

    Energy Technology Data Exchange (ETDEWEB)

    Zhou, Ying; Li, Xia; Yu, Hou-Yong, E-mail: phdyu@zstu.edu.cn [Zhejiang Sci-Tech University, The Key Laboratory of Advanced Textile Materials and Manufacturing Technology of Ministry of Education, College of Materials and Textiles (China); Hu, Guo-Liang; Yao, Ju-Ming, E-mail: yaoj@zstu.edu.cn [Zhejiang Sci-Tech University, National Engineering Lab for Textile Fiber Materials and Processing Technology (China)

    2016-12-15

    Polyacrylonitrile/zinc oxide (PAN/ZnO) composite nanofiber membranes with different ZnO morphologies were fabricated by repeatedly alternating hot–cold immersion and single alternating hot–cold immersion methods. The influence of the PAN/ZnCl{sub 2} ratio and different immersion methods on the morphology, microstructure, and properties of the nanofiber membranes was investigated by using field-emission scanning electron microscopy (FE-SEM), Fourier-transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD) analysis, thermogravimetric analysis (TGA), and ultraviolet–visible (UV–Vis) spectroscopy. A possible mechanism for different morphologies of PAN/ZnO nanofiber membranes with different PAN/ZnCl{sub 2} ratio through different immersion processes was presented, and well-dispersed ZnO nanorod clusters with smallest average dimeter of 115 nm and hexagonal wurtzite structure were successfully anchored onto the PAN nanofiber surface for R-7/1 nanofiber membrane. Compared to S-5/1 prepared by single alternating hot–cold immersion method, the PAN/ZnO nanofiber membrane fabricated by repeatedly alternating hot–cold immersion method (especially for R-7/1) showed improved thermal stability and high photocatalytic activity for methylene blue (MB). Compared to S-5/1, decomposition temperature at 5% weight loss (T{sub 5%}) was increased by 43 °C from 282 to 325 °C for R-7/1; meanwhile, R-7/1 showed higher photocatalytic degradation ratio of approximately 100% (after UV light irradiation for 8 h) than 65% for S-5/1 even after irradiation for 14 h. Moreover, the degradation efficiency of R-7/1 with good reuse stability remained above 94% after 3 cycles.

  14. A building characterization-based method for the advancement of knowledge on external architectural features of traditional rural buildings

    Directory of Open Access Journals (Sweden)

    Porto, S. M. C.

    2013-12-01

    Full Text Available The significant role that traditional rural buildings have with regard to environmental conservation and rural development is widely acknowledged by the scientific community. These buildings must be protected from inappropriate building interventions that may stem from their rather superficial knowledge. Therefore, this study was directed towards overcoming such a limitation by developing a method based on traditional rural buildings’ characterization. In particular, the study aimed at the characterization of building materials and techniques used for the construction of a number of building components that make up the external envelope of traditional rural buildings. The application of the method to a homogeneous area of the Etna Regional Park (Italy highlighted the need to improve the technical norms of the park’s Territorial Coordination Plan to respect the building characteristics of the traditional rural buildings located in the protected area.La comunidad científica le atribuye a las construcciones rurales tradicionales un papel fundamental en términos de conservación del medioambiente y de evolución rural. Dichos edificios deben ser protegidos contra obras inapropiadas debidas a un conocimiento más bien superficial. Por lo tanto, el objetivo de este estudio fue el de eliminar dichas limitaciones desarrollando un método basado en la caracterización de las construcciones rurales tradicionales, que puede ser aplicado para mejorar el conocimiento de estas últimas. En particular, el susodicho estudio tiene la finalidad de caracterizar los materiales y las técnicas constructivas a emplear para la construcción de algunos componentes del envoltorio externo de las construcciones rurales tradicionales. La aplicación del método propuesto a una zona homogénea del Parque Regional del Etna (Italia puso de relieve la necesidad de mejorar las normas técnicas del Plan de Coordinación Territorial del parque para respetar las caracter

  15. Higher-order equation-of-motion coupled-cluster methods for ionization processes.

    Science.gov (United States)

    Kamiya, Muneaki; Hirata, So

    2006-08-21

    Compact algebraic equations defining the equation-of-motion coupled-cluster (EOM-CC) methods for ionization potentials (IP-EOM-CC) have been derived and computer implemented by virtue of a symbolic algebra system largely automating these processes. Models with connected cluster excitation operators truncated after double, triple, or quadruple level and with linear ionization operators truncated after two-hole-one-particle (2h1p), three-hole-two-particle (3h2p), or four-hole-three-particle (4h3p) level (abbreviated as IP-EOM-CCSD, CCSDT, and CCSDTQ, respectively) have been realized into parallel algorithms taking advantage of spin, spatial, and permutation symmetries with optimal size dependence of the computational costs. They are based on spin-orbital formalisms and can describe both alpha and beta ionizations from open-shell (doublet, triplet, etc.) reference states into ionized states with various spin magnetic quantum numbers. The application of these methods to Koopmans and satellite ionizations of N2 and CO (with the ambiguity due to finite basis sets eliminated by extrapolation) has shown that IP-EOM-CCSD frequently accounts for orbital relaxation inadequately and displays errors exceeding a couple of eV. However, these errors can be systematically reduced to tenths or even hundredths of an eV by IP-EOM-CCSDT or CCSDTQ. Comparison of spectroscopic parameters of the FH+ and NH+ radicals between IP-EOM-CC and experiments has also underscored the importance of higher-order IP-EOM-CC treatments. For instance, the harmonic frequencies of the A 2Sigma- state of NH+ are predicted to be 1285, 1723, and 1705 cm(-1) by IP-EOM-CCSD, CCSDT, and CCSDTQ, respectively, as compared to the observed value of 1707 cm(-1). The small adiabatic energy separation (observed 0.04 eV) between the X 2Pi and a 4Sigma- states of NH+ also requires IP-EOM-CCSDTQ for a quantitative prediction (0.06 eV) when the a 4Sigma- state has the low-spin magnetic quantum number (s(z) = 1/2). When the

  16. GraphTeams: a method for discovering spatial gene clusters in Hi-C sequencing data.

    Science.gov (United States)

    Schulz, Tizian; Stoye, Jens; Doerr, Daniel

    2018-05-08

    Hi-C sequencing offers novel, cost-effective means to study the spatial conformation of chromosomes. We use data obtained from Hi-C experiments to provide new evidence for the existence of spatial gene clusters. These are sets of genes with associated functionality that exhibit close proximity to each other in the spatial conformation of chromosomes across several related species. We present the first gene cluster model capable of handling spatial data. Our model generalizes a popular computational model for gene cluster prediction, called δ-teams, from sequences to graphs. Following previous lines of research, we subsequently extend our model to allow for several vertices being associated with the same label. The model, called δ-teams with families, is particular suitable for our application as it enables handling of gene duplicates. We develop algorithmic solutions for both models. We implemented the algorithm for discovering δ-teams with families and integrated it into a fully automated workflow for discovering gene clusters in Hi-C data, called GraphTeams. We applied it to human and mouse data to find intra- and interchromosomal gene cluster candidates. The results include intrachromosomal clusters that seem to exhibit a closer proximity in space than on their chromosomal DNA sequence. We further discovered interchromosomal gene clusters that contain genes from different chromosomes within the human genome, but are located on a single chromosome in mouse. By identifying δ-teams with families, we provide a flexible model to discover gene cluster candidates in Hi-C data. Our analysis of Hi-C data from human and mouse reveals several known gene clusters (thus validating our approach), but also few sparsely studied or possibly unknown gene cluster candidates that could be the source of further experimental investigations.

  17. An easy-to-use method for measuring the flux of free atoms in a cluster beam

    International Nuclear Information System (INIS)

    Cuvellier, J.; Binet, A.

    1988-01-01

    A method is proposed to measure the flux of free atoms remaining in a beam of clusters. The time-of-flight (TOF) of an Ar beam containing clusters was analysed for this purpose using an electron impact + quadrupole mass spectrometer as detector. When considering TOF's with mass settings at Ar + , a double mode structure was observed. The slow component was interpreted as coming from Ar clusters that fragment as Ar + in the ionization chamber of the detector. The rapid mode in the TOF's was linked to the free atoms remaining in the Ar beam. Evaluating the area of this mode allowed one to measure the flux of free atoms in the Ar beam. The method is not restricted to measurements on Ar beams

  18. MIA-Clustering: a novel method for segmentation of paleontological material

    Directory of Open Access Journals (Sweden)

    Christopher J. Dunmore

    2018-02-01

    Full Text Available Paleontological research increasingly uses high-resolution micro-computed tomography (μCT to study the inner architecture of modern and fossil bone material to answer important questions regarding vertebrate evolution. This non-destructive method allows for the measurement of otherwise inaccessible morphology. Digital measurement is predicated on the accurate segmentation of modern or fossilized bone from other structures imaged in μCT scans, as errors in segmentation can result in inaccurate calculations of structural parameters. Several approaches to image segmentation have been proposed with varying degrees of automation, ranging from completely manual segmentation, to the selection of input parameters required for computational algorithms. Many of these segmentation algorithms provide speed and reproducibility at the cost of flexibility that manual segmentation provides. In particular, the segmentation of modern and fossil bone in the presence of materials such as desiccated soft tissue, soil matrix or precipitated crystalline material can be difficult. Here we present a free open-source segmentation algorithm application capable of segmenting modern and fossil bone, which also reduces subjective user decisions to a minimum. We compare the effectiveness of this algorithm with another leading method by using both to measure the parameters of a known dimension reference object, as well as to segment an example problematic fossil scan. The results demonstrate that the medical image analysis-clustering method produces accurate segmentations and offers more flexibility than those of equivalent precision. Its free availability, flexibility to deal with non-bone inclusions and limited need for user input give it broad applicability in anthropological, anatomical, and paleontological contexts.

  19. MIA-Clustering: a novel method for segmentation of paleontological material.

    Science.gov (United States)

    Dunmore, Christopher J; Wollny, Gert; Skinner, Matthew M

    2018-01-01

    Paleontological research increasingly uses high-resolution micro-computed tomography (μCT) to study the inner architecture of modern and fossil bone material to answer important questions regarding vertebrate evolution. This non-destructive method allows for the measurement of otherwise inaccessible morphology. Digital measurement is predicated on the accurate segmentation of modern or fossilized bone from other structures imaged in μCT scans, as errors in segmentation can result in inaccurate calculations of structural parameters. Several approaches to image segmentation have been proposed with varying degrees of automation, ranging from completely manual segmentation, to the selection of input parameters required for computational algorithms. Many of these segmentation algorithms provide speed and reproducibility at the cost of flexibility that manual segmentation provides. In particular, the segmentation of modern and fossil bone in the presence of materials such as desiccated soft tissue, soil matrix or precipitated crystalline material can be difficult. Here we present a free open-source segmentation algorithm application capable of segmenting modern and fossil bone, which also reduces subjective user decisions to a minimum. We compare the effectiveness of this algorithm with another leading method by using both to measure the parameters of a known dimension reference object, as well as to segment an example problematic fossil scan. The results demonstrate that the medical image analysis-clustering method produces accurate segmentations and offers more flexibility than those of equivalent precision. Its free availability, flexibility to deal with non-bone inclusions and limited need for user input give it broad applicability in anthropological, anatomical, and paleontological contexts.

  20. Improving cluster-based methods for investigating potential for insect pest species establishment: region-specific risk factors

    Directory of Open Access Journals (Sweden)

    Michael J. Watts

    2011-09-01

    Full Text Available Existing cluster-based methods for investigating insect species assemblages or profiles of a region to indicate the risk of new insect pest invasion have a major limitation in that they assign the same species risk factors to each region in a cluster. Clearly regions assigned to the same cluster have different degrees of similarity with respect to their species profile or assemblage. This study addresses this concern by applying weighting factors to the cluster elements used to calculate regional risk factors, thereby producing region-specific risk factors. Using a database of the global distribution of crop insect pest species, we found that we were able to produce highly differentiated region-specific risk factors for insect pests. We did this by weighting cluster elements by their Euclidean distance from the target region. Using this approach meant that risk weightings were derived that were more realistic, as they were specific to the pest profile or species assemblage of each region. This weighting method provides an improved tool for estimating the potential invasion risk posed by exotic species given that they have an opportunity to establish in a target region.