PREFACE: Nuclear Cluster Conference; Cluster'07

Science.gov (United States)

Freer, Martin

2008-05-01

The Cluster Conference is a long-running conference series dating back to the 1960's, the first being initiated by Wildermuth in Bochum, Germany, in 1969. The most recent meeting was held in Nara, Japan, in 2003, and in 2007 the 9th Cluster Conference was held in Stratford-upon-Avon, UK. As the name suggests the town of Stratford lies upon the River Avon, and shortly before the conference, due to unprecedented rainfall in the area (approximately 10 cm within half a day), lay in the River Avon! Stratford is the birthplace of the `Bard of Avon' William Shakespeare, and this formed an intriguing conference backdrop. The meeting was attended by some 90 delegates and the programme contained 65 70 oral presentations, and was opened by a historical perspective presented by Professor Brink (Oxford) and closed by Professor Horiuchi (RCNP) with an overview of the conference and future perspectives. In between, the conference covered aspects of clustering in exotic nuclei (both neutron and proton-rich), molecular structures in which valence neutrons are exchanged between cluster cores, condensates in nuclei, neutron-clusters, superheavy nuclei, clusters in nuclear astrophysical processes and exotic cluster decays such as 2p and ternary cluster decay. The field of nuclear clustering has become strongly influenced by the physics of radioactive beam facilities (reflected in the programme), and by the excitement that clustering may have an important impact on the structure of nuclei at the neutron drip-line. It was clear that since Nara the field had progressed substantially and that new themes had emerged and others had crystallized. Two particular topics resonated strongly condensates and nuclear molecules. These topics are thus likely to be central in the next cluster conference which will be held in 2011 in the Hungarian city of Debrechen. Martin Freer Participants and Cluster'07

A workshop report on nuclear reaction and cluster structure

International Nuclear Information System (INIS)

1985-01-01

A work shop was held in June 1984 at RCNP (Research Center for Nuclear Physics), Osaka University, to discuss theory of nuclear reactions based on studies from microscopic or cluster structure viewpoints. About forty researchers participated in this work shop and 27 paperes were presented. All these papers with English abstracts are gathered in this collective report. (Aoki, K.)

Analysis of the differential cross sections for the reaction pp→ppK+K- in view of the K+K- interaction

International Nuclear Information System (INIS)

Silarski, M.

2008-07-01

Measurements of the pp→ppK + K - reaction, performed with the experiment COSY-11 at the Cooler Synchrotron COSY, show a significant difference between the obtained excitation function and theoretical expectations including pp-FSI. The discrepancy may be assigned to the influence of K + K - or K - p interaction. This interaction should manifest itself in the distributions of the differential cross section. This thesis presents an analysis of event distributions as a function of the invariant masses of two particle subsystems. In particular in the analysis two generalizations of the Dalitz plot proposed by Goldhaber and Nyborg are used. The present Investigations are based on the experimental data determined by the COSY-11 collaboration from two measurements at excess energies of Q=10 MeV and 28 MeV. The experimental distributions are compared to results of Monte Carlo simulations generated with various parameters of the K + K - and K - p interaction. The values of the K + K - scattering length, extracted from two data sets for Q=10 MeV and 28 MeV amount to: a K + K - =(11±8)+i(0±6) fm for Q=10 MeV, and a K + K - =(0.2±0.2)+i(0.0±0.5) fm for Q=28 MeV. Due to the low statistics, the extracted values have large uncertainties and are consistent with very low values of the real and imaginary part of the scattering length. (orig.)

K-AP: Generating specified K clusters by efficient Affinity Propagation

KAUST Repository

Zhang, Xiangliang; Wang, Wei; Nø rvå g, Kjetil; Sebag, Michè le

2010-01-01

and experimental validation, K-AP was shown to be able to directly generate K clusters as user defined, with a negligible increase of computational cost compared to AP. In the meanwhile, K-AP preserves the clustering quality as AP in terms of the distortion. K

Characteristics of the groups of charged particles in bar pp,pp and K-p interactions at 32 GeV/c

International Nuclear Information System (INIS)

Bogolubsky, M.Yu.; Levitsky, M.S.; Maksimov, V.V.

1995-01-01

In the clan model, a method is developed for determining the following characteristics of the groups of charged particles: group multiplicity in an interval, particle multiplicity in a group, and width distribution of groups. Distribution densities are obtained for particles originating from clans produced at a given rapidity point with given width in bar pp, K - p, and pp interactions at 32 GeV/c. It is shown that the differences in the rate of growth of factorial moments in bar pp and K - p interactions are due to a difference in the relative contributions of small-width clans. 12 refs., 13 figs., 2 tabs

Y K Vijay

Indian Academy of Sciences (India)

Home; Journals; Bulletin of Materials Science. Y K Vijay. Articles written in Bulletin of Materials Science. Volume 27 Issue 5 October 2004 pp 417-420 Nuclear Related Materials. Irradiation of large area Mylar membrane and characterization of nuclear track filter · N K Acharya P K Yadav S Wate Y K Vijay F Singh D K Avasthi.

Star clusters and K2

Science.gov (United States)

Dotson, Jessie; Barentsen, Geert; Cody, Ann Marie

2018-01-01

The K2 survey has expanded the Kepler legacy by using the repurposed spacecraft to observe over 20 star clusters. The sample includes open and globular clusters at all ages, including very young (1-10 Myr, e.g. Taurus, Upper Sco, NGC 6530), moderately young (0.1-1 Gyr, e.g. M35, M44, Pleiades, Hyades), middle-aged (e.g. M67, Ruprecht 147, NGC 2158), and old globular clusters (e.g. M9, M19, Terzan 5). K2 observations of stellar clusters are exploring the rotation period-mass relationship to significantly lower masses than was previously possible, shedding light on the angular momentum budget and its dependence on mass and circumstellar disk properties, and illuminating the role of multiplicity in stellar angular momentum. Exoplanets discovered by K2 in stellar clusters provides planetary systems ripe for modeling given the extensive information available about their ages and environment. I will review the star clusters sampled by K2 across 16 fields so far, highlighting several characteristics, caveats, and unexplored uses of the public data set along the way. With fuel expected to run out in 2018, I will discuss the closing Campaigns, highlight the final target selection opportunities, and explain the data archive and TESS-compatible software tools the K2 mission intends to leave behind for posterity.

pK{sup +}Λ final state: Towards the extraction of the ppK{sup −} contribution

Energy Technology Data Exchange (ETDEWEB)

Fabbietti, L., E-mail: laura.fabbietti@ph.tum.de [Excellence Cluster ‘Origin and Structure of the Universe’, 85748 Garching (Germany); Agakishiev, G. [Joint Institute of Nuclear Research, 141980 Dubna (Russian Federation); Behnke, C. [Institut für Kernphysik, Goethe-Universität, 60438 Frankfurt (Germany); Belver, D. [LabCAF, F. Física, Univ. de Santiago de Compostela, 15706 Santiago de Compostela (Spain); Belyaev, A. [Joint Institute of Nuclear Research, 141980 Dubna (Russian Federation); Berger-Chen, J.C. [Excellence Cluster ‘Origin and Structure of the Universe’, 85748 Garching (Germany); Blanco, A. [LIP-Laboratório de Instrumentação e Física Experimental de Partículas, 3004-516 Coimbra (Portugal); Blume, C. [Institut für Kernphysik, Goethe-Universität, 60438 Frankfurt (Germany); Böhmer, M. [Physik Department E12, Technische Universität München, 85748 Garching (Germany); Cabanelas, P. [LabCAF, F. Física, Univ. de Santiago de Compostela, 15706 Santiago de Compostela (Spain); Chernenko, S. [Joint Institute of Nuclear Research, 141980 Dubna (Russian Federation); Dritsa, C. [II. Physikalisches Institut, Justus Liebig Universität Giessen, 35392 Giessen (Germany); Dybczak, A. [Smoluchowski Institute of Physics, Jagiellonian University of Cracow, 30-059 Kraków (Poland); and others

2013-09-20

The reaction p(@3.5 GeV)+p→p+Λ+K{sup +} can be studied to search for the existence of kaonic bound states like ppK{sup −} leading to this final state. This effort has been motivated by the assumption that in p+p collisions the Λ(1405) resonance can act as a doorway to the formation of the kaonic bound states. The status of this analysis within the HADES Collaboration, with particular emphasis on the comparison to simulations, is shown in this work and the deviation method utilized by the DISTO Collaboration in a similar analysis is discussed. The outcome suggests the employment of a partial wave analysis do disentangle the different contributions to the measured pK{sup +}Λ final state.

Robust K-Median and K-Means Clustering Algorithms for Incomplete Data

Directory of Open Access Journals (Sweden)

Jinhua Li

2016-01-01

Full Text Available Incomplete data with missing feature values are prevalent in clustering problems. Traditional clustering methods first estimate the missing values by imputation and then apply the classical clustering algorithms for complete data, such as K-median and K-means. However, in practice, it is often hard to obtain accurate estimation of the missing values, which deteriorates the performance of clustering. To enhance the robustness of clustering algorithms, this paper represents the missing values by interval data and introduces the concept of robust cluster objective function. A minimax robust optimization (RO formulation is presented to provide clustering results, which are insensitive to estimation errors. To solve the proposed RO problem, we propose robust K-median and K-means clustering algorithms with low time and space complexity. Comparisons and analysis of experimental results on both artificially generated and real-world incomplete data sets validate the robustness and effectiveness of the proposed algorithms.

$K^{0}_{s}-K^{0}_{s}$ correlations in pp collisions at $\\sqrt{s}=7 TeV$ from the LHC ALICE experiment

CERN Document Server

Abelev, Betty; Adamova, Dagmar; Adare, Andrew Marshall; Aggarwal, Madan; Aglieri Rinella, Gianluca; Agocs, Andras Gabor; Agostinelli, Andrea; Aguilar Salazar, Saul; Ahammed, Zubayer; Ahmad, Arshad; Ahmad, Nazeer; Ahn, Sang Un; Akindinov, Alexander; Aleksandrov, Dmitry; Alessandro, Bruno; Alfaro Molina, Jose Ruben; Alici, Andrea; Alkin, Anton; Almaraz Avina, Erick Jonathan; Alme, Johan; Alt, Torsten; Altini, Valerio; Altinpinar, Sedat; Altsybeev, Igor; Andrei, Cristian; Andronic, Anton; Anguelov, Venelin; Anielski, Jonas; Anticic, Tome; Antinori, Federico; Antonioli, Pietro; Aphecetche, Laurent Bernard; Appelshauser, Harald; Arbor, Nicolas; Arcelli, Silvia; Armesto, Nestor; Arnaldi, Roberta; Aronsson, Tomas Robert; Arsene, Ionut Cristian; Arslandok, Mesut; Augustinus, Andre; Averbeck, Ralf Peter; Awes, Terry; Aysto, Juha Heikki; Azmi, Mohd Danish; Bach, Matthias Jakob; Badala, Angela; Baek, Yong Wook; Bailhache, Raphaelle Marie; Bala, Renu; Baldini Ferroli, Rinaldo; Baldisseri, Alberto; Baldit, Alain; Baltasar Dos Santos Pedrosa, Fernando; Ban, Jaroslav; Baral, Rama Chandra; Barbera, Roberto; Barile, Francesco; Barnafoldi, Gergely Gabor; Barnby, Lee Stuart; Barret, Valerie; Bartke, Jerzy Gustaw; Basile, Maurizio; Bastid, Nicole; Basu, Sumit; Bathen, Bastian; Batigne, Guillaume; Batyunya, Boris; Baumann, Christoph Heinrich; Bearden, Ian Gardner; Beck, Hans; Behera, Nirbhay Kumar; Belikov, Iouri; Bellini, Francesca; Bellwied, Rene; Belmont-Moreno, Ernesto; Bencedi, Gyula; Beole, Stefania; Berceanu, Ionela; Bercuci, Alexandru; Berdnikov, Yaroslav; Berenyi, Daniel; Bergognon, Anais Annick Erica; Berzano, Dario; Betev, Latchezar; Bhasin, Anju; Bhati, Ashok Kumar; Bhom, Jihyun; Bianchi, Livio; Bianchi, Nicola; Bianchin, Chiara; Bielcik, Jaroslav; Bielcikova, Jana; Bilandzic, Ante; Bjelogrlic, Sandro; Blanco, F; Blanco, Francesco; Blau, Dmitry; Blume, Christoph; Bock, Nicolas; Boettger, Stefan; Bogdanov, Alexey; Boggild, Hans; Bogolyubsky, Mikhail; Boldizsar, Laszlo; Bombara, Marek; Book, Julian; Borel, Herve; Borissov, Alexander; Bose, Suvendu Nath; Bossu, Francesco; Botje, Michiel; Boyer, Bruno Alexandre; Braidot, Ermes; Braun-Munzinger, Peter; Bregant, Marco; Breitner, Timo Gunther; Browning, Tyler Allen; Broz, Michal; Brun, Rene; Bruna, Elena; Bruno, Giuseppe Eugenio; Budnikov, Dmitry; Buesching, Henner; Bufalino, Stefania; Bugaiev, Kyrylo; Busch, Oliver; Buthelezi, Edith Zinhle; Caffarri, Davide; Cai, Xu; Caines, Helen Louise; Calvo Villar, Ernesto; Camerini, Paolo; Canoa Roman, Veronica; Cara Romeo, Giovanni; Carena, Francesco; Carena, Wisla; Carminati, Federico; Casanova Diaz, Amaya Ofelia; Castillo Castellanos, Javier Ernesto; Casula, Ester Anna Rita; Catanescu, Vasile; Cavicchioli, Costanza; Ceballos Sanchez, Cesar; Cepila, Jan; Cerello, Piergiorgio; Chang, Beomsu; Chapeland, Sylvain; Charvet, Jean-Luc Fernand; Chattopadhyay, Sukalyan; Chattopadhyay, Subhasis; Chawla, Isha; Cherney, Michael Gerard; Cheshkov, Cvetan; Cheynis, Brigitte; Chiavassa, Emilio; Chibante Barroso, Vasco Miguel; Chinellato, David; Chochula, Peter; Chojnacki, Marek; Choudhury, Subikash; Christakoglou, Panagiotis; Christensen, Christian Holm; Christiansen, Peter; Chujo, Tatsuya; Chung, Suh-Urk; Cicalo, Corrado; Cifarelli, Luisa; Cindolo, Federico; Cleymans, Jean Willy Andre; Coccetti, Fabrizio; Colamaria, Fabio; Colella, Domenico; Conesa Balbastre, Gustavo; Conesa del Valle, Zaida; Constantin, Paul; Contin, Giacomo; Contreras, Jesus Guillermo; Cormier, Thomas Michael; Corrales Morales, Yasser; Cortes Maldonado, Ismael; Cortese, Pietro; Cosentino, Mauro Rogerio; Costa, Filippo; Cotallo, Manuel Enrique; Crochet, Philippe; Cruz Alaniz, Emilia; Cuautle, Eleazar; Cunqueiro, Leticia; D'Erasmo, Ginevra; Dainese, Andrea; Dalsgaard, Hans Hjersing; Danu, Andrea; Das, Debasish; Das, Indranil; Das, Kushal; Dash, Ajay Kumar; Dash, Sadhana; De, Sudipan; de Barros, Gabriel; De Caro, Annalisa; de Cataldo, Giacinto; de Cuveland, Jan; De Falco, Alessandro; De Gruttola, Daniele; De Marco, Nora; De Pasquale, Salvatore; de Rooij, Raoul Stefan; Delagrange, Hugues; Deloff, Andrzej; Demanov, Vyacheslav; Denes, Ervin; Deppman, Airton; Di Bari, Domenico; Di Giglio, Carmelo; Di Liberto, Sergio; Di Mauro, Antonio; Di Nezza, Pasquale; Diaz Corchero, Miguel Angel; Dietel, Thomas; Divia, Roberto; Djuvsland, Oeystein; Dobrin, Alexandru Florin; Dobrowolski, Tadeusz Antoni; Dominguez, Isabel; Donigus, Benjamin; Dordic, Olja; Driga, Olga; Dubey, Anand Kumar; Ducroux, Laurent; Dupieux, Pascal; Dutta Majumdar, AK; Dutta Majumdar, Mihir Ranjan; Elia, Domenico; Emschermann, David Philip; Engel, Heiko; Erdal, Hege Austrheim; Espagnon, Bruno; Estienne, Magali Danielle; Esumi, Shinichi; Evans, David; Eyyubova, Gyulnara; Fabris, Daniela; Faivre, Julien; Falchieri, Davide; Fantoni, Alessandra; Fasel, Markus; Fedunov, Anatoly; Fehlker, Dominik; Feldkamp, Linus; Felea, Daniel; Fenton-Olsen, Bo; Feofilov, Grigory; Fernandez Tellez, Arturo; Ferretti, Alessandro; Ferretti, Roberta; Figiel, Jan; Figueredo, Marcel; Filchagin, Sergey; Finogeev, Dmitry; Fionda, Fiorella; Fiore, Enrichetta Maria; Floris, Michele; Foertsch, Siegfried Valentin; Foka, Panagiota; Fokin, Sergey; Fragiacomo, Enrico; Frankenfeld, Ulrich Michael; Fuchs, Ulrich; Furget, Christophe; Fusco Girard, Mario; Gaardhoje, Jens Joergen; Gagliardi, Martino; Gago, Alberto; Gallio, Mauro; Gangadharan, Dhevan Raja; Ganoti, Paraskevi; Garabatos, Jose; Garcia-Solis, Edmundo; Garishvili, Irakli; Gerhard, Jochen; Germain, Marie; Geuna, Claudio; Gheata, Andrei George; Gheata, Mihaela; Ghidini, Bruno; Ghosh, Premomoy; Gianotti, Paola; Girard, Martin Robert; Giubellino, Paolo; Gladysz-Dziadus, Ewa; Glassel, Peter; Gomez, Ramon; Gonschior, Alexey; Gonzalez Ferreiro, Elena; Gonzalez-Trueba, Laura Helena; Gonzalez-Zamora, Pedro; Gorbunov, Sergey; Goswami, Ankita; Gotovac, Sven; Grabski, Varlen; Graczykowski, Lukasz Kamil; Grajcarek, Robert; Grelli, Alessandro; Grigoras, Alina Gabriela; Grigoras, Costin; Grigoriev, Vladislav; Grigoryan, Ara; Grigoryan, Smbat; Grinyov, Boris; Grion, Nevio; Grosse-Oetringhaus, Jan Fiete; Grossiord, Jean-Yves; Grosso, Raffaele; Guber, Fedor; Guernane, Rachid; Guerra Gutierrez, Cesar; Guerzoni, Barbara; Guilbaud, Maxime Rene Joseph; Gulbrandsen, Kristjan Herlache; Gunji, Taku; Gupta, Anik; Gupta, Ramni; Gutbrod, Hans; Haaland, Oystein Senneset; Hadjidakis, Cynthia Marie; Haiduc, Maria; Hamagaki, Hideki; Hamar, Gergoe; Hanratty, Luke David; Hansen, Alexander; Harmanova, Zuzana; Harris, John William; Hartig, Matthias; Hasegan, Dumitru; Hatzifotiadou, Despoina; Hayrapetyan, Arsen; Heckel, Stefan Thomas; Heide, Markus Ansgar; Helstrup, Haavard; Herghelegiu, Andrei Ionut; Herrera Corral, Gerardo Antonio; Herrmann, Norbert; Hess, Benjamin Andreas; Hetland, Kristin Fanebust; Hicks, Bernard; Hille, Per Thomas; Hippolyte, Boris; Horaguchi, Takuma; Hori, Yasuto; Hristov, Peter Zahariev; Hrivnacova, Ivana; Huang, Meidana; Humanic, Thomas; Hwang, Dae Sung; Ichou, Raphaelle; Ilkaev, Radiy; Ilkiv, Iryna; Inaba, Motoi; Incani, Elisa; Innocenti, Gian Michele; Ippolitov, Mikhail; Irfan, Muhammad; Ivan, Cristian George; Ivanov, Andrey; Ivanov, Marian; Ivanov, Vladimir; Ivanytskyi, Oleksii; Jacholkowski, Adam Wlodzimierz; Jacobs, Peter; Jangal, Swensy Gwladys; Janik, Malgorzata Anna; Janik, Rudolf; Jayarathna, Sandun; Jena, Satyajit; Jha, Deeptanshu Manu; Jimenez Bustamante, Raul Tonatiuh; Jirden, Lennart; Jones, Peter Graham; Jung, Hyung Taik; Jusko, Anton; Kakoyan, Vanik; Kalcher, Sebastian; Kalinak, Peter; Kalliokoski, Tuomo Esa Aukusti; Kalweit, Alexander Philipp; Kanaki, Kalliopi; Kang, Ju Hwan; Kaplin, Vladimir; Karasu Uysal, Ayben; Karavichev, Oleg; Karavicheva, Tatiana; Karpechev, Evgeny; Kazantsev, Andrey; Kebschull, Udo Wolfgang; Keidel, Ralf; Khan, Mohisin Mohammed; Khan, Palash; Khan, Shuaib Ahmad; Khanzadeev, Alexei; Kharlov, Yury; Kileng, Bjarte; Kim, Beomkyu; Kim, Dong Jo; Kim, Do Won; Kim, Jonghyun; Kim, Jin Sook; Kim, Minwoo; Kim, Mimae; Kim, Se Yong; Kim, Seon Hee; Kim, Taesoo; Kirsch, Stefan; Kisel, Ivan; Kiselev, Sergey; Kisiel, Adam Ryszard; Klay, Jennifer Lynn; Klein, Jochen; Klein-Bosing, Christian; Kluge, Alexander; Knichel, Michael Linus; Knospe, Anders Garritt; Koch, Kathrin; Kohler, Markus; Kolojvari, Anatoly; Kondratiev, Valery; Kondratyeva, Natalia; Konevskih, Artem; Korneev, Andrey; Kour, Ravjeet; Kowalski, Marek; Kox, Serge; Koyithatta Meethaleveedu, Greeshma; Kral, Jiri; Kralik, Ivan; Kramer, Frederick; Kraus, Ingrid Christine; Krawutschke, Tobias; Krelina, Michal; Kretz, Matthias; Krivda, Marian; Krizek, Filip; Krus, Miroslav; Kryshen, Evgeny; Krzewicki, Mikolaj; Kucheriaev, Yury; Kuhn, Christian Claude; Kuijer, Paul; Kulakov, Igor; Kumar, Jitendra; Kurashvili, Podist; Kurepin, A; Kurepin, AB; Kuryakin, Alexey; Kushpil, Svetlana; Kushpil, Vasily; Kweon, Min Jung; Kwon, Youngil; La Pointe, Sarah Louise; La Rocca, Paola; Ladron de Guevara, Pedro; Lakomov, Igor; Langoy, Rune; Lara, Camilo Ernesto; Lardeux, Antoine Xavier; Lazzeroni, Cristina; Le Bornec, Yves; Lea, Ramona; Lechman, Mateusz; Lee, Graham Richard; Lee, Ki Sang; Lee, Sung Chul; Lefevre, Frederic; Lehnert, Joerg Walter; Leistam, Lars; Lemmon, Roy Crawford; Lenhardt, Matthieu Laurent; Lenti, Vito; Leon Monzon, Ildefonso; Leon Vargas, Hermes; Leoncino, Marco; Levai, Peter; Lien, Jorgen; Lietava, Roman; Lindal, Svein; Lindenstruth, Volker; Lippmann, Christian; Lisa, Michael Annan; Liu, Lijiao; Loenne, Per-Ivar; Loggins, Vera; Loginov, Vitaly; Lohn, Stefan Bernhard; Lohner, Daniel; Loizides, Constantinos; Loo, Kai Krister; Lopez, Xavier Bernard; Lopez Torres, Ernesto; Lovhoiden, Gunnar; Lu, Xianguo; Luettig, Philipp; Lunardon, Marcello; Luo, Jiebin; Luparello, Grazia; Luquin, Lionel; Luzzi, Cinzia; Ma, Rongrong; Maevskaya, Alla; Mager, Magnus; Mahapatra, Durga Prasad; Maire, Antonin; Mal'Kevich, Dmitry; Malaev, Mikhail; Maldonado Cervantes, Ivonne Alicia; Malinina, Ludmila; Malzacher, Peter; Mamonov, Alexander; Manceau, Loic Henri Antoine; Manko, Vladislav; Manso, Franck; Manzari, Vito; Mao, Yaxian; Marchisone, Massimiliano; Mares, Jiri; Margagliotti, Giacomo Vito; Margotti, Anselmo; Marin, Ana Maria; Marin Tobon, Cesar Augusto; Markert, Christina; Martashvili, Irakli; Martinengo, Paolo; Martinez, Mario Ivan; Martinez Davalos, Arnulfo; Martinez Garcia, Gines; Martynov, Yevgen; Mas, Alexis Jean-Michel; Masciocchi, Silvia; Masera, Massimo; Masoni, Alberto; Mastromarco, Mario; Mastroserio, Annalisa; Matthews, Zoe Louise; Matyja, Adam Tomasz; Mayani, Daniel; Mayer, Christoph; Mazer, Joel; Mazzoni, Alessandra Maria; Meddi, Franco; Menchaca-Rocha, Arturo Alejandro; Mercado Perez, Jorge; Meres, Michal; Miake, Yasuo; Milano, Leonardo; Milosevic, Jovan; Mischke, Andre; Mishra, Aditya Nath; Miskowiec, Dariusz; Mitu, Ciprian Mihai; Mlynarz, Jocelyn; Mohanty, Ajit Kumar; Mohanty, Bedangadas; Molnar, Levente; Montano Zetina, Luis Manuel; Monteno, Marco; Montes, Esther; Moon, Taebong; Morando, Maurizio; Moreira De Godoy, Denise Aparecida; Moretto, Sandra; Morsch, Andreas; Muccifora, Valeria; Mudnic, Eugen; Muhuri, Sanjib; Mukherjee, Maitreyee; Muller, Hans; Munhoz, Marcelo; Musa, Luciano; Musso, Alfredo; Nandi, Basanta Kumar; Nania, Rosario; Nappi, Eugenio; Nattrass, Christine; Naumov, Nikolay; Navin, Sparsh; Nayak, Tapan Kumar; Nazarenko, Sergey; Nazarov, Gleb; Nedosekin, Alexander; Nicassio, Maria; Niculescu, Mihai; Nielsen, Borge Svane; Niida, Takafumi; Nikolaev, Sergey; Nikolic, Vedran; Nikulin, Sergey; Nikulin, Vladimir; Nilsen, Bjorn Steven; Nilsson, Mads Stormo; Noferini, Francesco; Nomokonov, Petr; Nooren, Gerardus; Novitzky, Norbert; Nyanin, Alexandre; Nyatha, Anitha; Nygaard, Casper; Nystrand, Joakim Ingemar; Oeschler, Helmut Oskar; Oh, Saehanseul; Oh, Sun Kun; Oleniacz, Janusz; Oppedisano, Chiara; Ortona, Giacomo; Oskarsson, Anders Nils Erik; Otwinowski, Jacek Tomasz; Oyama, Ken; Pachmayer, Yvonne Chiara; Pachr, Milos; Padilla, Fatima; Pagano, Paola; Paic, Guy; Painke, Florian; Pajares, Carlos; Pal, S; Pal, Susanta Kumar; Palaha, Arvinder Singh; Palmeri, Armando; Papikyan, Vardanush; Pappalardo, Giuseppe; Park, Woo Jin; Passfeld, Annika; Patalakha, Dmitri Ivanovich; Paticchio, Vincenzo; Pavlinov, Alexei; Pawlak, Tomasz Jan; Peitzmann, Thomas; Pereira Da Costa, Hugo Denis Antonio; Pereira De Oliveira Filho, Elienos; Peresunko, Dmitri; Perez Lara, Carlos Eugenio; Perez Lezama, Edgar; Perini, Diego; Perrino, Davide; Peryt, Wiktor Stanislaw; Pesci, Alessandro; Peskov, Vladimir; Pestov, Yury; Petracek, Vojtech; Petran, Michal; Petris, Mariana; Petrov, Plamen Rumenov; Petrovici, Mihai; Petta, Catia; Piano, Stefano; Piccotti, Anna; Pikna, Miroslav; Pillot, Philippe; Pinazza, Ombretta; Pinsky, Lawrence; Pitz, Nora; Piuz, Francois; Piyarathna, Danthasinghe; Ploskon, Mateusz Andrzej; Pluta, Jan Marian; Pochybova, Sona; Podesta Lerma, Pedro Luis Manuel; Poghosyan, Martin; Polichtchouk, Boris; Pop, Amalia; Porteboeuf-Houssais, Sarah; Pospisil, Vladimir; Potukuchi, Baba; Prasad, Sidharth Kumar; Preghenella, Roberto; Prino, Francesco; Pruneau, Claude Andre; Pshenichnov, Igor; Puchagin, Sergey; Puddu, Giovanna; Pujahari, Prabhat Ranjan; Pujol Teixido, Jordi; Pulvirenti, Alberto; Punin, Valery; Putis, Marian; Putschke, Jorn Henning; Quercigh, Emanuele; Qvigstad, Henrik; Rachevski, Alexandre; Rademakers, Alphonse; Radomski, Sylwester; Raiha, Tomi Samuli; Rak, Jan; Rakotozafindrabe, Andry Malala; Ramello, Luciano; Ramirez Reyes, Abdiel; Raniwala, Rashmi; Raniwala, Sudhir; Rasanen, Sami Sakari; Rascanu, Bogdan Theodor; Rathee, Deepika; Read, Kenneth Francis; Real, Jean-Sebastien; Redlich, Krzysztof; Reichelt, Patrick; Reicher, Martijn; Renfordt, Rainer Arno Ernst; Reolon, Anna Rita; Reshetin, Andrey; Rettig, Felix Vincenz; Revol, Jean-Pierre; Reygers, Klaus Johannes; Riccati, Lodovico; Ricci, Renato Angelo; Richert, Tuva; Richter, Matthias Rudolph; Riedler, Petra; Riegler, Werner; Riggi, Francesco; Rodrigues Fernandes Rabacal, Bartolomeu; Rodriguez Cahuantzi, Mario; Rodriguez Manso, Alis; Roed, Ketil; Rohr, David; Rohrich, Dieter; Romita, Rosa; Ronchetti, Federico; Rosnet, Philippe; Rossegger, Stefan; Rossi, Andrea; Roy, Christelle Sophie; Roy, Pradip Kumar; Rubio Montero, Antonio Juan; Rui, Rinaldo; Russo, Riccardo; Ryabinkin, Evgeny; Rybicki, Andrzej; Sadovsky, Sergey; Safarik, Karel; Sahoo, Raghunath; Sahu, Pradip Kumar; Saini, Jogender; Sakaguchi, Hiroaki; Sakai, Shingo; Sakata, Dosatsu; Salgado, Carlos Albert; Salzwedel, Jai; Sambyal, Sanjeev Singh; Samsonov, Vladimir; Sanchez Castro, Xitzel; Sandor, Ladislav; Sandoval, Andres; Sano, Masato; Sano, Satoshi; Santo, Rainer; Santoro, Romualdo; Sarkamo, Juho Jaako; Scapparone, Eugenio; Scarlassara, Fernando; Scharenberg, Rolf Paul; Schiaua, Claudiu Cornel; Schicker, Rainer Martin; Schmidt, Christian Joachim; Schmidt, Hans Rudolf; Schreiner, Steffen; Schuchmann, Simone; Schukraft, Jurgen; Schutz, Yves Roland; Schwarz, Kilian Eberhard; Schweda, Kai Oliver; Scioli, Gilda; Scomparin, Enrico; Scott, Patrick Aaron; Scott, Rebecca; Segato, Gianfranco; Selyuzhenkov, Ilya; Senyukov, Serhiy; Seo, Jeewon; Serci, Sergio; Serradilla, Eulogio; Sevcenco, Adrian; Shabetai, Alexandre; Shabratova, Galina; Shahoyan, Ruben; Sharma, Natasha; Sharma, Satish; Shigaki, Kenta; Shimomura, Maya; Shtejer, Katherin; Sibiriak, Yury; Siciliano, Melinda; Sicking, Eva; Siddhanta, Sabyasachi; Siemiarczuk, Teodor; Silvermyr, David Olle Rickard; Silvestre, Catherine; Simatovic, Goran; Simonetti, Giuseppe; Singaraju, Rama Narayana; Singh, Ranbir; Singha, Subhash; Singhal, Vikas; Sinha, Bikash; Sinha, Tinku; Sitar, Branislav; Sitta, Mario; Skaali, Bernhard; Skjerdal, Kyrre; Smakal, Radek; Smirnov, Nikolai; Snellings, Raimond; Sogaard, Carsten; Soltz, Ron Ariel; Son, Hyungsuk; Song, Jihye; Song, Myunggeun; Soos, Csaba; Soramel, Francesca; Sputowska, Iwona; Spyropoulou-Stassinaki, Martha; Srivastava, Brijesh Kumar; Stachel, Johanna; Stan, Ionel; Stefanek, Grzegorz; Stefanini, Giorgio; Steinbeck, Timm Morten; Steinpreis, Matthew; Stenlund, Evert Anders; Steyn, Gideon Francois; Stiller, Johannes Hendrik; Stocco, Diego; Stolpovskiy, Mikhail; Strabykin, Kirill; Strmen, Peter; Suaide, Alexandre Alarcon do Passo; Subieta Vasquez, Martin Alfonso; Sugitate, Toru; Suire, Christophe Pierre; Sukhorukov, Mikhail; Sultanov, Rishat; Sumbera, Michal; Susa, Tatjana; Szanto de Toledo, Alejandro; Szarka, Imrich; Szczepankiewicz, Adam; Szostak, Artur Krzysztof; Szymanski, Maciej; Takahashi, Jun; Tapia Takaki, Daniel Jesus; Tarazona Martinez, Alfonso; Tauro, Arturo; Tejeda Munoz, Guillermo; Telesca, Adriana; Terrevoli, Cristina; Thader, Jochen Mathias; Thomas, Deepa; Tieulent, Raphael Noel; Timmins, Anthony; Toia, Alberica; Torii, Hisayuki; Tosello, Flavio; Trzaska, Wladyslaw Henryk; Tsuji, Tomoya; Tumkin, Alexandr; Turrisi, Rosario; Tveter, Trine Spedstad; Ulery, Jason Glyndwr; Ullaland, Kjetil; Ulrich, Jochen; Uras, Antonio; Urban, Jozef; Urciuoli, Guido Marie; Usai, Gianluca; Vajzer, Michal; Vala, Martin; Valencia Palomo, Lizardo; Vallero, Sara; van der Kolk, Naomi; van Leeuwen, Marco; Vande Vyvre, Pierre; Vannucci, Luigi; Vargas, Aurora Diozcora; Varma, Raghava; Vasileiou, Maria; Vasiliev, Andrey; Vechernin, Vladimir; Veldhoen, Misha; Venaruzzo, Massimo; Vercellin, Ermanno; Vergara, Sergio; Vernet, Renaud; Verweij, Marta; Vickovic, Linda; Viesti, Giuseppe; Vikhlyantsev, Oleg; Vilakazi, Zabulon; Villalobos Baillie, Orlando; Vinogradov, Alexander; Vinogradov, Leonid; Vinogradov, Yury; Virgili, Tiziano; Viyogi, Yogendra; Vodopianov, Alexander; Voloshin, Kirill; Voloshin, Sergey; Volpe, Giacomo; von Haller, Barthelemy; Vranic, Danilo; Øvrebekk, Gaute; Vrlakova, Janka; Vulpescu, Bogdan; Vyushin, Alexey; Wagner, Boris; Wagner, Vladimir; Wan, Renzhuo; Wang, Dong; Wang, Mengliang; Wang, Yifei; Wang, Yaping; Watanabe, Kengo; Weber, Michael; Wessels, Johannes; Westerhoff, Uwe; Wiechula, Jens; Wikne, Jon; Wilde, Martin Rudolf; Wilk, Alexander; Wilk, Grzegorz Andrzej; Williams, Crispin; Windelband, Bernd Stefan; Xaplanteris Karampatsos, Leonidas; Yaldo, Chris G; Yamaguchi, Yorito; Yang, Hongyan; Yang, Shiming; Yasnopolsky, Stanislav; Yi, JunGyu; Yin, Zhongbao; Yoo, In-Kwon; Yoon, Jongik; Yu, Weilin; Yuan, Xianbao; Yushmanov, Igor; Zach, Cenek; Zampolli, Chiara; Zaporozhets, Sergey; Zarochentsev, Andrey; Zavada, Petr; Zaviyalov, Nikolai; Zbroszczyk, Hanna Paulina; Zelnicek, Pierre; Zgura, Sorin Ion; Zhalov, Mikhail; Zhang, Haitao; Zhang, Xiaoming; Zhou, Daicui; Zhou, Fengchu; Zhou, You; Zhu, Jianhui; Zhu, Xiangrong; Zichichi, Antonino; Zimmermann, Alice; Zinovjev, Gennady; Zoccarato, Yannick Denis; Zynovyev, Mykhaylo; Zyzak, Maksym

2013-07-16

Identical neutral kaon pair correlations are measured in $\\sqrt{s}$=7 TeV pp collisions in the ALICE experiment. One-dimensional K$^{0}_{s}$-K$^{0}_{s}$ correlation functions in terms of the invariant momentum difference of kaon pairs are formed in two multiplicity and two transverse momentum ranges. The femtoscopic parameters for the radius and correlation strength of the kaon source are extracted. The fit includes quantum statistics and final-state interactions of the $a_0/f_0$ resonance. K$^{0}_{s}$-K$^{0}_{s}$ correlations show an increase in radius for increasing multiplicity and a slight decrease in radius for increasing transverse mass, $m_T$, as seen in pion-pion correlations in the pp system and in heavy-ion collisions. Transverse mass scaling is observed between the K$^{0}_{s}$-K$^{0}_{s}$ and pion-pion radii. Also, the first observation is made of the decay of the $f_{2}'$(1525) meson into the K$^{0}_{s}$-K$^{0}_{s}$ channel in pp collisions.

MULTI-K: accurate classification of microarray subtypes using ensemble k-means clustering

Directory of Open Access Journals (Sweden)

Ashlock Daniel

2009-08-01

Full Text Available Abstract Background Uncovering subtypes of disease from microarray samples has important clinical implications such as survival time and sensitivity of individual patients to specific therapies. Unsupervised clustering methods have been used to classify this type of data. However, most existing methods focus on clusters with compact shapes and do not reflect the geometric complexity of the high dimensional microarray clusters, which limits their performance. Results We present a cluster-number-based ensemble clustering algorithm, called MULTI-K, for microarray sample classification, which demonstrates remarkable accuracy. The method amalgamates multiple k-means runs by varying the number of clusters and identifies clusters that manifest the most robust co-memberships of elements. In addition to the original algorithm, we newly devised the entropy-plot to control the separation of singletons or small clusters. MULTI-K, unlike the simple k-means or other widely used methods, was able to capture clusters with complex and high-dimensional structures accurately. MULTI-K outperformed other methods including a recently developed ensemble clustering algorithm in tests with five simulated and eight real gene-expression data sets. Conclusion The geometric complexity of clusters should be taken into account for accurate classification of microarray data, and ensemble clustering applied to the number of clusters tackles the problem very well. The C++ code and the data sets tested are available from the authors.

MULTI-K: accurate classification of microarray subtypes using ensemble k-means clustering.

Science.gov (United States)

Kim, Eun-Youn; Kim, Seon-Young; Ashlock, Daniel; Nam, Dougu

2009-08-22

Uncovering subtypes of disease from microarray samples has important clinical implications such as survival time and sensitivity of individual patients to specific therapies. Unsupervised clustering methods have been used to classify this type of data. However, most existing methods focus on clusters with compact shapes and do not reflect the geometric complexity of the high dimensional microarray clusters, which limits their performance. We present a cluster-number-based ensemble clustering algorithm, called MULTI-K, for microarray sample classification, which demonstrates remarkable accuracy. The method amalgamates multiple k-means runs by varying the number of clusters and identifies clusters that manifest the most robust co-memberships of elements. In addition to the original algorithm, we newly devised the entropy-plot to control the separation of singletons or small clusters. MULTI-K, unlike the simple k-means or other widely used methods, was able to capture clusters with complex and high-dimensional structures accurately. MULTI-K outperformed other methods including a recently developed ensemble clustering algorithm in tests with five simulated and eight real gene-expression data sets. The geometric complexity of clusters should be taken into account for accurate classification of microarray data, and ensemble clustering applied to the number of clusters tackles the problem very well. The C++ code and the data sets tested are available from the authors.

Clustering aspects in nuclear structure functions

International Nuclear Information System (INIS)

Hirai, M.; Saito, K.; Watanabe, T.; Kumano, S.

2011-01-01

For understanding an anomalous nuclear effect experimentally observed for the beryllium-9 nucleus at the Thomas Jefferson National Accelerator Facility, clustering aspects are studied in structure functions of deep inelastic lepton-nucleus scattering by using momentum distributions calculated in antisymmetrized (or fermionic) molecular dynamics (AMD) and also in a simple shell model for comparison. According to AMD, the 9 Be nucleus consists of two α-like clusters with a surrounding neutron. The clustering produces high-momentum components in nuclear wave functions, which affects nuclear modifications of the structure functions. We investigated whether clustering features could appear in the structure function F 2 of 9 Be along with studies for other light nuclei. We found that nuclear modifications of F 2 are similar in both AMD and shell models within our simple convolution description although there are slight differences in 9 Be. It indicates that the anomalous 9 Be result should be explained by a different mechanism from the nuclear binding and Fermi motion. If nuclear-modification slopes d(F 2 A /F 2 D )/dx are shown by the maximum local densities, the 9 Be anomaly can be explained by the AMD picture, namely by the clustering structure, whereas it certainly cannot be described in the simple shell model. This fact suggests that the large nuclear modification in 9 Be should be explained by large densities in the clusters. For example, internal nucleon structure could be modified in the high-density clusters. The clustering aspect of nuclear structure functions is an unexplored topic which is interesting for future investigations.

Implementasi KD-Tree K-Means Clustering untuk Klasterisasi Dokumen

Directory of Open Access Journals (Sweden)

Eric Budiman Gosno

2013-09-01

Full Text Available Klasterisasi dokumen adalah suatu proses pengelompokan dokumen secara otomatis dan unsupervised. Klasterisasi dokumen merupakan permasalahan yang sering ditemui dalam berbagai bidang seperti text mining dan sistem temu kembali informasi. Metode klasterisasi dokumen yang memiliki akurasi dan efisiensi waktu yang tinggi sangat diperlukan untuk meningkatkan hasil pada mesin pencari web,  dan untuk proses filtering. Salah satu metode klasterisasi yang telah dikenal dan diaplikasikan dalam klasterisasi dokumen adalah K-Means Clustering. Tetapi K-Means Clustering sensitif terhadap pemilihan posisi awal dari titik tengah klaster sehingga pemilihan posisi awal dari titik tengah klaster yang buruk akan mengakibatkan K-Means Clustering terjebak dalam local optimum. KD-Tree K-Means Clustering merupakan perbaikan dari K-Means Clustering. KD-Tree K-Means Clustering menggunakan struktur data K-Dimensional Tree dan nilai kerapatan pada proses inisialisasi titik tengah klaster. Pada makalah ini diimplementasikan algoritma KD-Tree K-Means Clustering untuk permasalahan klasterisasi dokumen. Performa klasterisasi dokumen yang dihasilkan oleh metode KD-Tree K-Means Clustering pada data set 20 newsgroup memiliki nilai distorsi 3×105 lebih rendah dibandingkan dengan nilai rerata distorsi K-Means Clustering dan nilai NIG 0,09 lebih baik dibandingkan dengan nilai NIG K-Means Clustering.

Investigation of the anti pp → xi (2220) → K/sub s/K/sub s/ reaction at LEAR

International Nuclear Information System (INIS)

Hertzog, D.W.

1985-01-01

Measurement of the total and differential cross section of the reaction anti pp → K/sub s/K/sub s/ in a fine momentum scan corresponding to the mass range of the xi (2220) was proposed. The mass and width of such a resonance coupling to anti pp can be determined to better than 500 keV and additionally the spin can be established from the differential cross section. Only modest additions to our existing threshold detector and antiproton beam intensities currently available at LEAR are required for these studies. 14 refs

Observation and study of centrally produced pion clusters in 28.5-GeV/c p-p interactions

International Nuclear Information System (INIS)

Erwin, A.R.; Harvey, E.H.; Larson, G.P.; Collins, G.B.; Ficenec, J.R.; Stringfellow, B.C.; Trower, W.P.; Gutay, L.J.; Laasanen, A.; Willmann, R.B.; Anderson, E.W.; Fisher, G.P.; Lazuras, E.; von Lindern, L.; Ramanauskas, A.; Schubelin, P.; Thorndike, A.M.; Turkot, F.

1976-01-01

A double-arm spectrometer is used to identify a pion cluster produced in central p-p collisions at 28.5 GeV/c. Cluster properties studied are angular momentum, quantum statistics, multiplicity, and effective mass. There is some speculation on the production mechanism

Choosing the Number of Clusters in K-Means Clustering

Science.gov (United States)

Steinley, Douglas; Brusco, Michael J.

2011-01-01

Steinley (2007) provided a lower bound for the sum-of-squares error criterion function used in K-means clustering. In this article, on the basis of the lower bound, the authors propose a method to distinguish between 1 cluster (i.e., a single distribution) versus more than 1 cluster. Additionally, conditional on indicating there are multiple…

*K-means and cluster models for cancer signatures.

Science.gov (United States)

Kakushadze, Zura; Yu, Willie

2017-09-01

We present *K-means clustering algorithm and source code by expanding statistical clustering methods applied in https://ssrn.com/abstract=2802753 to quantitative finance. *K-means is statistically deterministic without specifying initial centers, etc. We apply *K-means to extracting cancer signatures from genome data without using nonnegative matrix factorization (NMF). *K-means' computational cost is a fraction of NMF's. Using 1389 published samples for 14 cancer types, we find that 3 cancers (liver cancer, lung cancer and renal cell carcinoma) stand out and do not have cluster-like structures. Two clusters have especially high within-cluster correlations with 11 other cancers indicating common underlying structures. Our approach opens a novel avenue for studying such structures. *K-means is universal and can be applied in other fields. We discuss some potential applications in quantitative finance.

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.

OPTIMASI PUSAT CLUSTER K-PROTOTYPE DENGAN ALGORITMA GENETIKA

Directory of Open Access Journals (Sweden)

Pivin Suwirmayanti

2014-12-01

Full Text Available Teknik clustering saat ini telah banyak digunakan untuk mengatasi permasalahan yang terkait dengansegementasi data. Implementasi clustering ini dapat diterapkan pada berbagai bidang sebagai contoh dalam halpemasaran, clustering dapat digunakan sebagai metode untuk mengelompokkan data. Metode Clustering memilikitujuan untuk mengelompokkan beberapa data ke dalam beberapa kelompok data sehingga kelompok yang terbentukmemiliki kemiripan data, secara umum proses clustering diolah menggunakan tipe data numerik, namun padakenyataannya proses pengelompokan data tidak hanya menggunakan tipe data numerik, terdapat juga tipe datakategorikal. Untuk itu penulis menggunakan metode K-Prototype yang dioptimasi dengan Algortima Genetikadimana data uji yang digunakan adalah Data German Credit yang memiliki tipe data numerikal dan kategorikal.Dalam penelitian dilakukan perbandingan kinerja antara metode K-Prototype dengan Algoritma Genetika, denganmetode K-Prototype Tanpa Algortima Genetika, dan metode K-Means. Dari beberapa hasil percobaan yangdilakukan metode K-Prototype dengan Algoritma Genetika menghasilkan hasil yang terbaik dari metode KPrototypetanpa Algortima Genetika, dan metode K-Means

K-means clustering versus validation measures: a data-distribution perspective.

Science.gov (United States)

Xiong, Hui; Wu, Junjie; Chen, Jian

2009-04-01

K-means is a well-known and widely used partitional clustering method. While there are considerable research efforts to characterize the key features of the K-means clustering algorithm, further investigation is needed to understand how data distributions can have impact on the performance of K-means clustering. To that end, in this paper, we provide a formal and organized study of the effect of skewed data distributions on K-means clustering. Along this line, we first formally illustrate that K-means tends to produce clusters of relatively uniform size, even if input data have varied "true" cluster sizes. In addition, we show that some clustering validation measures, such as the entropy measure, may not capture this uniform effect and provide misleading information on the clustering performance. Viewed in this light, we provide the coefficient of variation (CV) as a necessary criterion to validate the clustering results. Our findings reveal that K-means tends to produce clusters in which the variations of cluster sizes, as measured by CV, are in a range of about 0.3-1.0. Specifically, for data sets with large variation in "true" cluster sizes (e.g., CV > 1.0), K-means reduces variation in resultant cluster sizes to less than 1.0. In contrast, for data sets with small variation in "true" cluster sizes (e.g., CV K-means increases variation in resultant cluster sizes to greater than 0.3. In other words, for the earlier two cases, K-means produces the clustering results which are away from the "true" cluster distributions.

Study of the {omega} meson produced in the 700-750 MeV/c pp{yields}K{sub 1}{sup 0}K{sub 1}{sup 0}{omega} annihilations; Estudio del meson {omega} en las aniquilaciones pp{yields}K{sub 1}{sup =}K{sub 1}{sup =} {omega} a 700-750 MeV/c de momento del haz

Energy Technology Data Exchange (ETDEWEB)

Salicio, J

1976-07-01

We have measured the mass, width and branching ratio ({yields} neutrals) {pi}{sup +}{pi}{sup -}{pi}{sup 0} of the {omega} meson, using the reactions pp -- K{sub 1}{sup 0} K{sub 1}{sup 0} {down_arrow} neutrals and pp {yields} K{sub 1}{sup 0}K{sub 1}{sup 0}. The statistics is 11.5 events/{mu}b. In this report we present the methods of analysis and discuss the results. (Author)

A study of the centrally produced $K^{*}(892)\\overline{K}^{*}$ and $\\phi\\omega$ systems in pp interaction at 450 GeV/c

CERN Document Server

Barberis, D.; Binon, F.G.; Blick, A.M.; Close, F.E.; Danielsen, K.M.; Dolgopolov, A.V.; Donskov, S.V.; Earl, B.C.; Evans, D.; French, B.R.; Hino, T.; Inaba, S.; Inyakin, A.V.; Ishida, T.; Jacholkowski, A.; Jacobsen, T.; Jones, G.T.; Khaustov, G.V.; Kinashi, T.; Kinson, J.B.; Kirk, A.; Klempt, W.; Kolosov, V.; Kondashov, A.A.; Lednev, A.A.; Lenti, V.; Malyukov, S.; Martinengo, P.; Minashvili, I.; Nakagawa, T.; Norman, K.L.; Peigneux, J.P.; Polovnikov, S.A.; Polyakov, V.A.; Romanovsky, V.; Rotscheidt, H.; Rumyantsev, V.; Rusakovich, N.; Samoylenko, V.D.; Semenov, A.; Sene, M.; Sene, R.; Shagin, P.M.; Shimizu, H.; Singovsky, A.V.; Sobol, A.; Solovev, A.; Stassinaki, M.; Stroot, J.P.; Sugonyaev, V.P.; Takamatsu, K.; Tchlatchidze, G.; Tsuru, T.; Venables, M.; Villalobos Baillie, O.; Votruba, M.F.; Yasu, Y.

1998-01-01

A study of the reactions pp -> pfps(K+K-pi+pi-) and pp -> pfps(K+K-pi+pi-pi0) shows evidence for the K*K* and phi omega channels respectively. The K*K* mass spectrum shows a broad distribution with a maximum near threshold and an angular analysis shows that it is compatible with having JP = 2+. The behaviour of the cross-section as a function of centre of mass energy, and the four momentum transfer dependence, are compatible with what would be expected if the K*K* system was produced via double Pomeron exchange. The dPT behaviour of the phi omega channel is similar to what has been observed for all the undisputed qqbar states. In contrast, the dPT behaviour of the K*K* final state is similar to what has been observed for the phi phi final state and for previously observed glueball candidates.

Multiple phosphorylation sites at the C-terminus regulate nuclear import of HCMV DNA polymerase processivity factor ppUL44

International Nuclear Information System (INIS)

Alvisi, Gualtiero; Marin, Oriano; Pari, Gregory; Mancini, Manuela; Avanzi, Simone; Loregian, Arianna; Jans, David A.; Ripalti, Alessandro

2011-01-01

The processivity factor of human cytomegalovirus DNA polymerase, phosphoprotein ppUL44, is essential for viral replication. During viral infection ppUL44 is phosphorylated by the viral kinase pUL97, but neither the target residues on ppUL44 nor the effect of phosphorylation on ppUL44's activity are known. We report here that ppUL44 is phosphorylated when transiently expressed in mammalian cells and coimmunoprecipitates with cellular kinases. Of three potential phosphorylation sites (S413, S415, S418) located upstream of ppUL44's nuclear localization signal (NLS) and one (T427) within the NLS itself, protein kinase CK2 (CK2) specifically phosphorylates S413, to trigger a cascade of phosphorylation of S418 and S415 by CK1 and CK2, respectively. Negative charge at the CK2/CK1 target serine residues facilitates optimal nuclear accumulation of ppUL44, whereas negative charge on T427, a potential cyclin-dependent 1 phosphorylation site, strongly decreases nuclear accumulation. Thus, nuclear transport of ppUL44 is finely tuned during viral infection through complex phosphorylation events.

Performance Evaluation of Incremental K-means Clustering Algorithm

OpenAIRE

Chakraborty, Sanjay; Nagwani, N. K.

2014-01-01

The incremental K-means clustering algorithm has already been proposed and analysed in paper [Chakraborty and Nagwani, 2011]. It is a very innovative approach which is applicable in periodically incremental environment and dealing with a bulk of updates. In this paper the performance evaluation is done for this incremental K-means clustering algorithm using air pollution database. This paper also describes the comparison on the performance evaluations between existing K-means clustering and i...

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.

Soil data clustering by using K-means and fuzzy K-means algorithm

Directory of Open Access Journals (Sweden)

E. Hot

2016-06-01

Full Text Available A problem of soil clustering based on the chemical characteristics of soil, and proper visual representation of the obtained results, is analysed in the paper. To that aim, K-means and fuzzy K-means algorithms are adapted for soil data clustering. A database of soil characteristics sampled in Montenegro is used for a comparative analysis of implemented algorithms. The procedure of setting proper values for control parameters of fuzzy K-means is illustrated on the used database. In addition, validation of clustering is made through visualisation. Classified soil data are presented on the static Google map and dynamic Open Street Map.

Android Malware Classification Using K-Means Clustering Algorithm

Science.gov (United States)

Hamid, Isredza Rahmi A.; Syafiqah Khalid, Nur; Azma Abdullah, Nurul; Rahman, Nurul Hidayah Ab; Chai Wen, Chuah

2017-08-01

Malware was designed to gain access or damage a computer system without user notice. Besides, attacker exploits malware to commit crime or fraud. This paper proposed Android malware classification approach based on K-Means clustering algorithm. We evaluate the proposed model in terms of accuracy using machine learning algorithms. Two datasets were selected to demonstrate the practicing of K-Means clustering algorithms that are Virus Total and Malgenome dataset. We classify the Android malware into three clusters which are ransomware, scareware and goodware. Nine features were considered for each types of dataset such as Lock Detected, Text Detected, Text Score, Encryption Detected, Threat, Porn, Law, Copyright and Moneypak. We used IBM SPSS Statistic software for data classification and WEKA tools to evaluate the built cluster. The proposed K-Means clustering algorithm shows promising result with high accuracy when tested using Random Forest algorithm.

Search for a bound K− pp system

Directory of Open Access Journals (Sweden)

Camerini P.

2010-04-01

Full Text Available Data from the K− absorption reaction on 6,7Li, 9Be, 13C and 16O have recently been collected by FINUDA at the DAΦNE φ-factory (Laboratori Nazionali di Frascati-INFN, following an earlier lower statitics run on 12C and some other targets. FINUDA is a high acceptance magnetic spectrometer which performed a wide range of studies by detecting the charged particles and neutrons exiting the targets after the absorption event. In this paper it is discussed about the study of the A(K− , Λp reaction in the context of the search for deeply bound $ar{K}$ - nuclear states. The observation of a bump in the Λp invariant mass distribution is discussed in terms of a possible signature of a deeply bound K− pp kaonic cluster as well as of more conventional physics. An overview of the experimental situation in this field will be given.

*K-means and Cluster Models for Cancer Signatures

OpenAIRE

Kakushadze, Zura; Yu, Willie

2017-01-01

We present *K-means clustering algorithm and source code by expanding statistical clustering methods applied in https://ssrn.com/abstract=2802753 to quantitative finance. *K-means is statistically deterministic without specifying initial centers, etc. We apply *K-means to extracting cancer signatures from genome data without using nonnegative matrix factorization (NMF). *K-means’ computational cost is a fraction of NMF’s. Using 1389 published samples for 14 cancer types, we find that 3 cancer...

Cluster dynamics transcending chemical dynamics toward nuclear fusion.

Science.gov (United States)

Heidenreich, Andreas; Jortner, Joshua; Last, Isidore

2006-07-11

Ultrafast cluster dynamics encompasses femtosecond nuclear dynamics, attosecond electron dynamics, and electron-nuclear dynamics in ultraintense laser fields (peak intensities 10(15)-10(20) W.cm(-2)). Extreme cluster multielectron ionization produces highly charged cluster ions, e.g., (C(4+)(D(+))(4))(n) and (D(+)I(22+))(n) at I(M) = 10(18) W.cm(-2), that undergo Coulomb explosion (CE) with the production of high-energy (5 keV to 1 MeV) ions, which can trigger nuclear reactions in an assembly of exploding clusters. The laser intensity and the cluster size dependence of the dynamics and energetics of CE of (D(2))(n), (HT)(n), (CD(4))(n), (DI)(n), (CD(3)I)(n), and (CH(3)I)(n) clusters were explored by electrostatic models and molecular dynamics simulations, quantifying energetic driving effects, and kinematic run-over effects. The optimization of table-top dd nuclear fusion driven by CE of deuterium containing heteroclusters is realized for light-heavy heteroclusters of the largest size, which allows for the prevalence of cluster vertical ionization at the highest intensity of the laser field. We demonstrate a 7-orders-of-magnitude enhancement of the yield of dd nuclear fusion driven by CE of light-heavy heteroclusters as compared with (D(2))(n) clusters of the same size. Prospective applications for the attainment of table-top nucleosynthesis reactions, e.g., (12)C(P,gamma)(13)N driven by CE of (CH(3)I)(n) clusters, were explored.

The PP ampersand L Nuclear Department model for conducting self-assessments

International Nuclear Information System (INIS)

Murthy, M.L.R.; Vernick, H.R.; Male, A.M.; Burchill, W.E.

1995-01-01

The nuclear department of Pennsylvania Power ampersand Light Company (PP ampersand L) has initiated an aggressive, methodical, self-assessment program. Self-assessments are conducted to prevent problems, improve performance, and monitor results. The assessment activities are conducted by, or for, an individual having responsibility for performing the work being assessed. This individual, or customer, accepts ownership of the assessment effort and commits to implementing the recommendations agreed on during the assessment. This paper discusses the main elements of the assessment model developed by PP ampersand L and the results the model has achieved to date

ANALISIS CLUSTER K-MEANS DALAM PENGELOMPOKAN KEMAMPUAN MAHASISWA

Directory of Open Access Journals (Sweden)

B. Poerwanto

2016-12-01

Full Text Available Abstract. Cluster Analysis, K-Means Algorithm, Student Classification. This study aims to classify students based on learning outcomes for subject the basic of statistics (DDS, which is measured based on attendance, task, midterm (UTS, and final exams (UAS to further used to evaluate learning for subjects that require analysis of quantitative . This study uses k-means cluster analysis to classify the students into three groups based on learning outcomes. After grouped, there are 3 people in the low category, 27 in the medium category and over 70% in the high category.Abstrak. Analisis Cluster K-Means dalam Pengelompokan Kemampuan Mahasiswa. Pene-litian ini bertujuan untuk mengelompokkan mahasiswa berdasarkan hasil belajar mata kuliah dasar-dasar statistika (DDS yang diukur berdasarkan variabel nilai kehadiran, tugas, ujian tengah semester (UTS, dan ujian akhir semester (UAS untuk selanjutnya digunakan untuk mengevaluasi pembelajaran untuk mata kuliah yang membutuhkan kemampuan analisis kuantititatif yang baik. Penelitian ini menggunakan analisis cluster k-means dalam mengelompokkan mahasiswa ke dalam tiga kelompok berdasarkan hasil belajarnya. Seteleh dikelompokkan, terdapat 3 orang yang masuk pada kategori rendah, 27 orang pada kategori sedang dan lebih dari 70% pada kategori tinggi.Kata Kunci: Cluster Analysis, K-Means Algoritma, Klasifikasi Mahasiswa, Universitas Cokroaminoto Palopo

Optimasi Pusat Cluster Awal K-Means dengan Algoritma Genetika Pada Pengelompokan Dokumen

OpenAIRE

Fauzi, Muhammad

2017-01-01

147038065 Clustering a data set of documents based on certain data points in documents are an easy way to organize document for extension to work. K-Means clustering algorithm is one of iterative cluster algorithm to partition a set of entities into K cluster. Unfortunately, resulting in K?Means cluster is depending on the initial cluster center that generally assigned randomly. In this reserach, determining initial cluster center K-Means for documents clustering are investi...

Investigation of the pp{yields}K{sup +}n{sigma}{sup +} reaction at the magnetic spectrometer ANKE-COSY

Energy Technology Data Exchange (ETDEWEB)

Valdau, Yury

2009-10-20

This thesis describes measurements of the pp{yields}K{sup +}n{sigma}{sup +} reaction near threshold. The work was largely motivated by the lack of data for {sigma}{sup +} hyperon production in pp collisions and, in particular, by recent measurements of pp{yields}K{sup +}n{sigma}{sup +} by the COSY11 collaboration. The experiment performed by this group using a neutron detector reported surprisingly high {sigma}{sup +} cross sections that are hard to reconcile with isospin considerations. The experiment discussed in the thesis has been performed at the ANKE-COSY facility at four close-to-threshold energies. It relies on the almost background-free K{sup +} identification using the delayed-veto technique and the fact that below the threshold for pp{yields}K{sup +}n{lambda}{pi}{sup +} there is no source of the K{sup +}{pi}{sup +} correlations other than the {sigma}{sup +}{yields}n{pi}{sup +} decay. Thus, the detection of K{sup +}{pi}{sup +} pairs allows one to identify the pp{yields}K{sup +}n{sigma}{sup +} reaction without the need for a neutron detector. The analysis of three simultaneously measured spectra has been carried out, searching for any signal from a possible high {sigma}{sup +} cross section. All the K{sup +} production channels allowed at the energy of the experiment contribute to the K{sup +} inclusive and K{sup +}p correlation spectra. In the K{sup +} inclusive distributions, signals from the different production channels are summed and can only be isolated using theoretical models. In the K{sup +}p correlation spectra, there are not only signals from the direct reaction protons but also protons from hyperon decays can be observed. Thus, the signal from {sigma}{sup +}{yields}p{pi}{sup 0} decay contributes to the K{sup +}p missing mass. The study of the K{sup +}{pi}{sup +} correlations allows one to identify the {sigma}{sup +} reaction channels and to estimate the total production cross section. This method has been successfully applied to existing ANKE

Clustering Using Boosted Constrained k-Means Algorithm

Directory of Open Access Journals (Sweden)

Masayuki Okabe

2018-03-01

Full Text Available This article proposes a constrained clustering algorithm with competitive performance and less computation time to the state-of-the-art methods, which consists of a constrained k-means algorithm enhanced by the boosting principle. Constrained k-means clustering using constraints as background knowledge, although easy to implement and quick, has insufficient performance compared with metric learning-based methods. Since it simply adds a function into the data assignment process of the k-means algorithm to check for constraint violations, it often exploits only a small number of constraints. Metric learning-based methods, which exploit constraints to create a new metric for data similarity, have shown promising results although the methods proposed so far are often slow depending on the amount of data or number of feature dimensions. We present a method that exploits the advantages of the constrained k-means and metric learning approaches. It incorporates a mechanism for accepting constraint priorities and a metric learning framework based on the boosting principle into a constrained k-means algorithm. In the framework, a metric is learned in the form of a kernel matrix that integrates weak cluster hypotheses produced by the constrained k-means algorithm, which works as a weak learner under the boosting principle. Experimental results for 12 data sets from 3 data sources demonstrated that our method has performance competitive to those of state-of-the-art constrained clustering methods for most data sets and that it takes much less computation time. Experimental evaluation demonstrated the effectiveness of controlling the constraint priorities by using the boosting principle and that our constrained k-means algorithm functions correctly as a weak learner of boosting.

Canonical PSO Based K-Means Clustering Approach for Real Datasets.

Science.gov (United States)

Dey, Lopamudra; Chakraborty, Sanjay

2014-01-01

"Clustering" the significance and application of this technique is spread over various fields. Clustering is an unsupervised process in data mining, that is why the proper evaluation of the results and measuring the compactness and separability of the clusters are important issues. The procedure of evaluating the results of a clustering algorithm is known as cluster validity measure. Different types of indexes are used to solve different types of problems and indices selection depends on the kind of available data. This paper first proposes Canonical PSO based K-means clustering algorithm and also analyses some important clustering indices (intercluster, intracluster) and then evaluates the effects of those indices on real-time air pollution database, wholesale customer, wine, and vehicle datasets using typical K-means, Canonical PSO based K-means, simple PSO based K-means, DBSCAN, and Hierarchical clustering algorithms. This paper also describes the nature of the clusters and finally compares the performances of these clustering algorithms according to the validity assessment. It also defines which algorithm will be more desirable among all these algorithms to make proper compact clusters on this particular real life datasets. It actually deals with the behaviour of these clustering algorithms with respect to validation indexes and represents their results of evaluation in terms of mathematical and graphical forms.

An extended k-means technique for clustering moving objects

Directory of Open Access Journals (Sweden)

Omnia Ossama

2011-03-01

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

Benzoate-Induced High-Nuclearity Silver Thiolate Clusters.

Science.gov (United States)

Su, Yan-Min; Liu, Wei; Wang, Zhi; Wang, Shu-Ao; Li, Yan-An; Yu, Fei; Zhao, Quan-Qin; Wang, Xing-Po; Tung, Chen-Ho; Sun, Di

2018-04-03

Compared with the well-known anion-templated effects in shaping silver thiolate clusters, the influence from the organic ligands in the outer shell is still poorly understood. Herein, three new benzoate-functionalized high-nuclearity silver(I) thiolate clusters are isolated and characterized for the first time in the presence of diverse anion templates such as S 2- , α-[Mo 5 O 18 ] 6- , and MoO 4 2- . Single-crystal X-ray analysis reveals that the nuclearities of the three silver clusters (SD/Ag28, SD/Ag29, SD/Ag30) vary from 32 to 38 to 78 with co-capped tBuS - and benzoate ligands on the surface. SD/Ag28 is a turtle-like cluster comprising a Ag 29 shell caging a Ag 3 S 3 trigon in the center, whereas SD/Ag29 is a prolate Ag 38 sphere templated by the α-[Mo 5 O 18 ] 6- anion. Upon changing from benzoate to methoxyl-substituted benzoate, SD/Ag30 is isolated as a very complicated core-shell spherical cluster composed of a Ag 57 shell and a vase-like Ag 21 S 13 core. Four MoO 4 2- anions are arranged in a supertetrahedron and located in the interstice between the core and shell. Introduction of the bulky benzoate changes elaborately the nuclearity and arrangements of silver polygons on the shell of silver clusters, which is exemplified by comparing SD/Ag28 and a known similar silver thiolate cluster. The three new clusters emit luminescence in the near-infrared (NIR) region and show different thermochromic luminescence properties. This work presents a flexible approach to synthetic studies of high-nuclearity silver clusters decorated by different benzoates, and structural modulations are also achieved. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

A pp32-retinoblastoma protein complex modulates androgen receptor-mediated transcription and associates with components of the splicing machinery

International Nuclear Information System (INIS)

Adegbola, Onikepe; Pasternack, Gary R.

2005-01-01

We have previously shown pp32 and the retinoblastoma protein interact. pp32 and the retinoblastoma protein are nuclear receptor transcriptional coregulators: the retinoblastoma protein is a coactivator for androgen receptor, the major regulator of prostate cancer growth, while pp32, which is highly expressed in prostate cancer, is a corepressor of the estrogen receptor. We now show pp32 increases androgen receptor-mediated transcription and the retinoblastoma protein modulates this activity. Using affinity purification and mass spectrometry, we identify members of the pp32-retinoblastoma protein complex as PSF and nonO/p54nrb, proteins implicated in coordinate regulation of nuclear receptor-mediated transcription and splicing. We show that the pp32-retinoblastoma protein complex is modulated during TPA-induced K562 differentiation. Present evidence suggests that nuclear receptors assemble multiprotein complexes to coordinately regulate transcription and mRNA processing. Our results suggest that pp32 and the retinoblastoma protein may be part of a multiprotein complex that coordinately regulates nuclear receptor-mediated transcription and mRNA processing

The PP4R1 sub-unit of protein phosphatase PP4 is essential for inhibition of NF-κB by merkel polyomavirus small tumour antigen.

Science.gov (United States)

Abdul-Sada, Hussein; Müller, Marietta; Mehta, Rajni; Toth, Rachel; Arthur, J Simon C; Whitehouse, Adrian; Macdonald, Andrew

2017-04-11

Merkel cell carcinoma (MCC) is a highly aggressive skin cancer with a high metastatic potential. The majority of MCC cases are caused by the Merkel cell polyomavirus (MCPyV), through expression of the virus-encoded tumour antigens. Whilst mechanisms attributing tumour antigen expression to transformation are being uncovered, little is known of the mechanisms by which MCPyV persists in the host. We previously identified the MCPyV small T antigen (tAg) as a novel inhibitor of nuclear factor kappa B (NF-kB) signalling and a modulator of the host anti-viral response. Here we demonstrate that regulation of NF-kB activation involves a previously undocumented interaction between tAg and regulatory sub-unit 1 of protein phosphatase 4 (PP4R1). Formation of a complex with PP4R1 and PP4c is required to bridge MCPyV tAg to the NEMO adaptor protein, allowing deactivation of the NF-kB pathway. Mutations in MCPyV tAg that fail to interact with components of this complex, or siRNA depletion of PP4R1, prevents tAg-mediated inhibition of NF-kB and pro-inflammatory cytokine production. Comparison of tAg binding partners from other human polyomavirus demonstrates that interactions with NEMO and PP4R1 are unique to MCPyV. Collectively, these data identify PP4R1 as a novel target for virus subversion of the host anti-viral response.

Formation of nuclear molecules in cluster radioactivity. On interpretation of the cluster radioactivity mechanism

International Nuclear Information System (INIS)

Volkov, V.V.; Cherepanov, E.A.

2012-01-01

The basis for cluster radioactivity is the property of nuclei of light isotopes of elements heavier than lead to spontaneously form clusters - nuclei of light elements - from valence nucleons, which gives rise to asymmetric nuclear molecules. The cluster formation proceeds through successive excitation-free transfer of valence nucleons to the particle and to subsequent light nuclei. Nuclear molecule formation is accompanied by a considerable amount of released energy, which allows quantum-mechanical penetration of the cluster through the exit Coulomb barrier

The search for deeply bound kaonic states with FOPI

International Nuclear Information System (INIS)

Schmid, P.; Buehler, P.; Cargnelli, M.; Marton, J.; Widmann, E.; Zmeskal, J.

2006-01-01

Full text: New formation mechanisms for the creation of dense, exotic nuclear systems involving strangeness were recently proposed by Y. Akaishi and T. Yamazaki. Their calculations show that a K - might form deeply bound states in light nuclei - so called kaonic clusters - with central densities of several times the normal nuclear density. In the presentation a short overview of these exotic nuclear systems will be given and a new experiment with FOPI at GSI will be discussed. The aim of this experiment was to search for the simplest cluster - a ppK - state. This state is produced at GSI in the following high energy reaction: p + ''d'' → ppK - + K + + n'' with incident energies of 3.5 GeV. The experimental set-up will be presented in detail. (author)

The global kernel k-means algorithm for clustering in feature space.

Science.gov (United States)

Tzortzis, Grigorios F; Likas, Aristidis C

2009-07-01

Kernel k-means is an extension of the standard k -means clustering algorithm that identifies nonlinearly separable clusters. In order to overcome the cluster initialization problem associated with this method, we propose the global kernel k-means algorithm, a deterministic and incremental approach to kernel-based clustering. Our method adds one cluster at each stage, through a global search procedure consisting of several executions of kernel k-means from suitable initializations. This algorithm does not depend on cluster initialization, identifies nonlinearly separable clusters, and, due to its incremental nature and search procedure, locates near-optimal solutions avoiding poor local minima. Furthermore, two modifications are developed to reduce the computational cost that do not significantly affect the solution quality. The proposed methods are extended to handle weighted data points, which enables their application to graph partitioning. We experiment with several data sets and the proposed approach compares favorably to kernel k -means with random restarts.

K-nearest uphill clustering in the protein structure space

KAUST Repository

Cui, Xuefeng

2016-08-26

The protein structure classification problem, which is to assign a protein structure to a cluster of similar proteins, is one of the most fundamental problems in the construction and application of the protein structure space. Early manually curated protein structure classifications (e.g., SCOP and CATH) are very successful, but recently suffer the slow updating problem because of the increased throughput of newly solved protein structures. Thus, fully automatic methods to cluster proteins in the protein structure space have been designed and developed. In this study, we observed that the SCOP superfamilies are highly consistent with clustering trees representing hierarchical clustering procedures, but the tree cutting is very challenging and becomes the bottleneck of clustering accuracy. To overcome this challenge, we proposed a novel density-based K-nearest uphill clustering method that effectively eliminates noisy pairwise protein structure similarities and identifies density peaks as cluster centers. Specifically, the density peaks are identified based on K-nearest uphills (i.e., proteins with higher densities) and K-nearest neighbors. To our knowledge, this is the first attempt to apply and develop density-based clustering methods in the protein structure space. Our results show that our density-based clustering method outperforms the state-of-the-art clustering methods previously applied to the problem. Moreover, we observed that computational methods and human experts could produce highly similar clusters at high precision values, while computational methods also suggest to split some large superfamilies into smaller clusters. © 2016 Elsevier B.V.

Proceedings of the Conference on 75 years of Nuclear Fission

Indian Academy of Sciences (India)

Proceedings of the Conference on 75 years of Nuclear Fission: Present Status and Future Perspectives (Fission75) - Part I. pp 187-188. Organizing Committee · More Details Fulltext PDF. pp 189-190. Foreword · D C Biswas K Mahata V M Datar · More Details Fulltext PDF. pp 191-198. Seventy-five years of nuclear fission.

A comparison of latent class, K-means, and K-median methods for clustering dichotomous data.

Science.gov (United States)

Brusco, Michael J; Shireman, Emilie; Steinley, Douglas

2017-09-01

The problem of partitioning a collection of objects based on their measurements on a set of dichotomous variables is a well-established problem in psychological research, with applications including clinical diagnosis, educational testing, cognitive categorization, and choice analysis. Latent class analysis and K-means clustering are popular methods for partitioning objects based on dichotomous measures in the psychological literature. The K-median clustering method has recently been touted as a potentially useful tool for psychological data and might be preferable to its close neighbor, K-means, when the variable measures are dichotomous. We conducted simulation-based comparisons of the latent class, K-means, and K-median approaches for partitioning dichotomous data. Although all 3 methods proved capable of recovering cluster structure, K-median clustering yielded the best average performance, followed closely by latent class analysis. We also report results for the 3 methods within the context of an application to transitive reasoning data, in which it was found that the 3 approaches can exhibit profound differences when applied to real data. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Finding reproducible cluster partitions for the k-means algorithm.

Science.gov (United States)

Lisboa, Paulo J G; Etchells, Terence A; Jarman, Ian H; Chambers, Simon J

2013-01-01

K-means clustering is widely used for exploratory data analysis. While its dependence on initialisation is well-known, it is common practice to assume that the partition with lowest sum-of-squares (SSQ) total i.e. within cluster variance, is both reproducible under repeated initialisations and also the closest that k-means can provide to true structure, when applied to synthetic data. We show that this is generally the case for small numbers of clusters, but for values of k that are still of theoretical and practical interest, similar values of SSQ can correspond to markedly different cluster partitions. This paper extends stability measures previously presented in the context of finding optimal values of cluster number, into a component of a 2-d map of the local minima found by the k-means algorithm, from which not only can values of k be identified for further analysis but, more importantly, it is made clear whether the best SSQ is a suitable solution or whether obtaining a consistently good partition requires further application of the stability index. The proposed method is illustrated by application to five synthetic datasets replicating a real world breast cancer dataset with varying data density, and a large bioinformatics dataset.

Supersymmetry for nuclear cluster systems

International Nuclear Information System (INIS)

Levai, G.; Cseh, J.; Van Isacker, P.

2001-01-01

A supersymmetry scheme is proposed for nuclear cluster systems. The bosonic sector of the superalgebra describes the relative motion of the clusters, while its fermionic sector is associated with their internal structure. An example of core+α configurations is discussed in which the core is a p-shell nucleus and the underlying superalgebra is U(4/12). The α-cluster states of the nuclei 20 Ne and 19 F are analysed and correlations between their spectra, electric quadrupole transitions, and one-nucleon transfer reactions are interpreted in terms of U(4/12) supersymmetry. (author)

Fast and Accuracy Control Chart Pattern Recognition using a New cluster-k-Nearest Neighbor

OpenAIRE

Samir Brahim Belhaouari

2009-01-01

By taking advantage of both k-NN which is highly accurate and K-means cluster which is able to reduce the time of classification, we can introduce Cluster-k-Nearest Neighbor as "variable k"-NN dealing with the centroid or mean point of all subclasses generated by clustering algorithm. In general the algorithm of K-means cluster is not stable, in term of accuracy, for that reason we develop another algorithm for clustering our space which gives a higher accuracy than K-means cluster, less ...

Automatic detection of erythemato-squamous diseases using k-means clustering.

Science.gov (United States)

Ubeyli, Elif Derya; Doğdu, Erdoğan

2010-04-01

A new approach based on the implementation of k-means clustering is presented for automated detection of erythemato-squamous diseases. The purpose of clustering techniques is to find a structure for the given data by finding similarities between data according to data characteristics. The studied domain contained records of patients with known diagnosis. The k-means clustering algorithm's task was to classify the data points, in this case the patients with attribute data, to one of the five clusters. The algorithm was used to detect the five erythemato-squamous diseases when 33 features defining five disease indications were used. The purpose is to determine an optimum classification scheme for this problem. The present research demonstrated that the features well represent the erythemato-squamous diseases and the k-means clustering algorithm's task achieved high classification accuracies for only five erythemato-squamous diseases.

ONKALO pose experiment. Geophysical logging and imaging of drillholes ONK-PP223, ONK-PP226, ONK-PP254 and ONK-PP259...261

International Nuclear Information System (INIS)

Tarvainen, A.-M.

2011-08-01

Suomen Malmi Oy conducted geophysical drillhole logging as well as optical and acoustic imaging of shallow drillholes ONK-PP223, ONK-PP226, ONK-PP254, ONKPP259, ONK-PP260 and ONK-PP261 at ONKALO in the investigation niche ONKTKU- 3 (POSE) between December 2009 and June 2010. The survey is a part of Posiva Oy's detailed investigation program for the final disposal of spent nuclear fuel. The assignment included the field work and data processing. The report describes field operation, equipment as well as processing procedures and shows the obtained results and an analysis of their quality in the appendices. The raw and processed data are delivered digitally in WellCAD, PDF and Excel format. (orig.)

Clustering phenomena in nuclear matter below the saturation density

International Nuclear Information System (INIS)

Takemoto, Hiroki; Fukushima, Masahiro; Chiba, Satoshi; Horiuchi, Hisashi; Akaishi, Yoshinori; Tohsaki, Akihiro

2004-01-01

We investigate density-fluctuated states of nuclear matter as a result of clustering below the saturation density ρ 0 by description in terms of the Bloch function. The Bloch description has the advantage of a unified representation for a density-fluctuated state from an aggregate of uncorrelated clusters in extremely low-density regions to the plane-wave state of uniform matter in relatively high-density regions. We treat the density-fluctuated states due to α and 16 O clustering in symmetric nuclear matter and due to 10 He clustering in asymmetric nuclear matter. The density-fluctuated states develop as the density of matter decreases below each critical density around 0.2-0.4 ρ 0 which depends on what kind of effective force we use

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.

Merging K-means with hierarchical clustering for identifying general-shaped groups.

Science.gov (United States)

Peterson, Anna D; Ghosh, Arka P; Maitra, Ranjan

2018-01-01

Clustering partitions a dataset such that observations placed together in a group are similar but different from those in other groups. Hierarchical and K -means clustering are two approaches but have different strengths and weaknesses. For instance, hierarchical clustering identifies groups in a tree-like structure but suffers from computational complexity in large datasets while K -means clustering is efficient but designed to identify homogeneous spherically-shaped clusters. We present a hybrid non-parametric clustering approach that amalgamates the two methods to identify general-shaped clusters and that can be applied to larger datasets. Specifically, we first partition the dataset into spherical groups using K -means. We next merge these groups using hierarchical methods with a data-driven distance measure as a stopping criterion. Our proposal has the potential to reveal groups with general shapes and structure in a dataset. We demonstrate good performance on several simulated and real datasets.

Irradiation effect on PP/PMMA and PP/PP-g-PMMA matrices

International Nuclear Information System (INIS)

Marsongko; Soebianto, Yanti S.

1998-01-01

The effects of PMMA and PP-g-PMMA on the oxidation of polypropylene (PP) have been studied. The mixing was done in Laboplastomill at the temperature of 200 o C, and screw speed of 20 rpm, for 5 minutes. The PMMA concentrations were 1, 2, 5, and 10% by weight, and PP-g-PMMA (12% grafting) 5, 10, and 20% by weight. Mechanical properties (tensile strength (Tb) and elongation at break (Eb)( of the mixture decreased with the increase of PMMA content over 5%. The addition of PMMA over 3% produced non-transparent film. Electron beam irradiation at the dose of 5, 10, 30, and 50 kGy was carried out to accelerate the matrix oxidation is accelerated. The optimum properties of PP/PMMA blends can be achieved by addition of maximum 2% PMMA either direct as PMMA or as compatibilizer (PP-g-PMMA). (authors)

Fuzzy Modeled K-Cluster Quality Mining of Hidden Knowledge for Decision Support

OpenAIRE

S. Parkash  Kumar; K. S. Ramaswami

2011-01-01

Problem statement: The work presented Fuzzy Modeled K-means Cluster Quality Mining of hidden knowledge for Decision Support. Based on the number of clusters, number of objects in each cluster and its cohesiveness, precision and recall values, the cluster quality metrics is measured. The fuzzy k-means is adapted approach by using heuristic method which iterates the cluster to form an efficient valid cluster. With the obtained data clusters, quality assessment is made by predictive mining using...

π+-, K+-, pp, and p-barp elastic scattering from 50 to 175 GeV/c

International Nuclear Information System (INIS)

Ayres, D.S.; Diebold, R.; Maclay, G.J.; Cutts, D.; Lanou, R.E. Jr.; Levinson, L.J.; Massimo, J.T.; Litt, J.; Meunier, R.; Sogard, M.; Gittelman, B.; Loh, E.C.; Brenner, A.E.; Elias, J.E.; Mikenberg, G.; Guerriero, L.; Lavopa, P.; Maggi, G.; DeMarzo, C.; Posa, F.; Selvaggi, G.; Spinelli, P.; Waldner, F.; Barton, D.S.; Butler, J.; Fines, J.; Friedman, J.I.; Kendall, H.W.; Nelson, B.; Rosenson, L.; Verdier, R.; Gottschalk, B.; Anderson, R.L.; Gustavson, D.; Rich, K.; Ritson, D.M.; Weitsch, G.A.

1977-01-01

The differential cross sections for the elastic scattering of π + , π - , K + , K - , p, and p-bar on protons have been measured in the t interval -0.04 to -0.75 GeV 2 at five momenta: 50, 70, 100, 140, and 175 GeV/c. The t distributions have been parametrized by the quadratic exponential form dsigma/dt = A exp( B abs. value(t) + C abs. value(t) 2 and the energy dependence has been described in terms of a single-pole Regge model. The pp and K + p diffraction peaks are found to shrink with α' approx. 0.20 and approx. 0.15 GeV -2 , respectively. The p-barp diffraction peak is antishrinking while π + - and K - p are relatively energy-independent. Total elastic cross sections are calculated by integrating the differential cross sections. The rapid decline in sigma/sub el/ observed at low energies has stopped and all six reactions approach relatively constant values of sigma/sub el/. The ratio of sigma/sub el//sigma/sub tot/ approaches a constant value for all six reactions by 100 GeV, consistent with the predictions of the geometric-scaling hypothesis. This ratio is approx. 0.18 for pp and p-barp, and approx. 0.12--0.14 for π + - and K + -. A crossover is observed between K + p and K - p scattering at abs. value t approx =0.19 GeV 2 , and between pp and p-barp at abs. value t approx=0.11 GeV 2 . Inversion of the cross sections into impact-parameter space shows that protons are quite transparent to mesons even in head-on collisions. The probability for a meson to pass through a proton head-on without interaction inelastically is approx. 20%, while it is only approx. 6% for an incident proton or antiproton. Finally, the results are compared with various quark-model predictions

Support Vector Data Descriptions and k-Means Clustering: One Class?

Science.gov (United States)

Gornitz, Nico; Lima, Luiz Alberto; Muller, Klaus-Robert; Kloft, Marius; Nakajima, Shinichi

2017-09-27

We present ClusterSVDD, a methodology that unifies support vector data descriptions (SVDDs) and k-means clustering into a single formulation. This allows both methods to benefit from one another, i.e., by adding flexibility using multiple spheres for SVDDs and increasing anomaly resistance and flexibility through kernels to k-means. In particular, our approach leads to a new interpretation of k-means as a regularized mode seeking algorithm. The unifying formulation further allows for deriving new algorithms by transferring knowledge from one-class learning settings to clustering settings and vice versa. As a showcase, we derive a clustering method for structured data based on a one-class learning scenario. Additionally, our formulation can be solved via a particularly simple optimization scheme. We evaluate our approach empirically to highlight some of the proposed benefits on artificially generated data, as well as on real-world problems, and provide a Python software package comprising various implementations of primal and dual SVDD as well as our proposed ClusterSVDD.

Fatigue Feature Extraction Analysis based on a K-Means Clustering Approach

Directory of Open Access Journals (Sweden)

M.F.M. Yunoh

2015-06-01

Full Text Available This paper focuses on clustering analysis using a K-means approach for fatigue feature dataset extraction. The aim of this study is to group the dataset as closely as possible (homogeneity for the scattered dataset. Kurtosis, the wavelet-based energy coefficient and fatigue damage are calculated for all segments after the extraction process using wavelet transform. Kurtosis, the wavelet-based energy coefficient and fatigue damage are used as input data for the K-means clustering approach. K-means clustering calculates the average distance of each group from the centroid and gives the objective function values. Based on the results, maximum values of the objective function can be seen in the two centroid clusters, with a value of 11.58. The minimum objective function value is found at 8.06 for five centroid clusters. It can be seen that the objective function with the lowest value for the number of clusters is equal to five; which is therefore the best cluster for the dataset.

A Variable-Selection Heuristic for K-Means Clustering.

Science.gov (United States)

Brusco, Michael J.; Cradit, J. Dennis

2001-01-01

Presents a variable selection heuristic for nonhierarchical (K-means) cluster analysis based on the adjusted Rand index for measuring cluster recovery. Subjected the heuristic to Monte Carlo testing across more than 2,200 datasets. Results indicate that the heuristic is extremely effective at eliminating masking variables. (SLD)

Unsupervised Cryo-EM Data Clustering through Adaptively Constrained K-Means Algorithm.

Science.gov (United States)

Xu, Yaofang; Wu, Jiayi; Yin, Chang-Cheng; Mao, Youdong

2016-01-01

In single-particle cryo-electron microscopy (cryo-EM), K-means clustering algorithm is widely used in unsupervised 2D classification of projection images of biological macromolecules. 3D ab initio reconstruction requires accurate unsupervised classification in order to separate molecular projections of distinct orientations. Due to background noise in single-particle images and uncertainty of molecular orientations, traditional K-means clustering algorithm may classify images into wrong classes and produce classes with a large variation in membership. Overcoming these limitations requires further development on clustering algorithms for cryo-EM data analysis. We propose a novel unsupervised data clustering method building upon the traditional K-means algorithm. By introducing an adaptive constraint term in the objective function, our algorithm not only avoids a large variation in class sizes but also produces more accurate data clustering. Applications of this approach to both simulated and experimental cryo-EM data demonstrate that our algorithm is a significantly improved alterative to the traditional K-means algorithm in single-particle cryo-EM analysis.

Inclusive Σp and pp reactions. How can one learn the nature of π, K, Λ, N exchanges and determine the coupling constants

International Nuclear Information System (INIS)

Vasylev, A.M.; Ginzburg, I.F.; Perlovskij, L.I.

1977-01-01

Inclusive experiments pp → π + +..., Σp → Λ +..., pp → K + +... are proposed in which it is possible to come very close to the π, K, N, Λ poles. In these experiments it is possible, in principle, to extract the most precise values of the coupling constants KNY, Σ π Λ,... and to state the problem which is the nature of the exchanges. A critical analysis of the pp → π + + ... data is carried out

A fuzzy clustering technique for calorimetric data reconstruction

International Nuclear Information System (INIS)

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

2010-01-01

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

Deuterium cluster model for low energy nuclear reactions (LENR)

Science.gov (United States)

Miley, George; Hora, Heinrich

2007-11-01

For studying the possible reactions of high density deuterons on the background of a degenerate electron gas, a summary of experimental observations resulted in the possibility of reactions in pm distance and more than ksec duration similar to the K-shell electron capture [1]. The essential reason was the screening of the deuterons by a factor of 14 based on the observations. Using the bosonic properties for a cluster formation of the deuterons and a model of compound nuclear reactions [2], the measured distribution of the resulting nuclei may be explained as known from the Maruhn-Greiner theory for fission. The local maximum of the distribution at the main minimum indicates the excited states of the compound nuclei during their intermediary state. This measured local maximum may be an independent proof for the deuteron clusters at LENR. [1] H. Hora, G.H. Miley et al. Physics Letters A175, 138 (1993) [2] H. Hora and G.H. Miley, APS March Meeting 2007, Program p. 116

Evaluation of stability of k-means cluster ensembles with respect to random initialization.

Science.gov (United States)

Kuncheva, Ludmila I; Vetrov, Dmitry P

2006-11-01

Many clustering algorithms, including cluster ensembles, rely on a random component. Stability of the results across different runs is considered to be an asset of the algorithm. The cluster ensembles considered here are based on k-means clusterers. Each clusterer is assigned a random target number of clusters, k and is started from a random initialization. Here, we use 10 artificial and 10 real data sets to study ensemble stability with respect to random k, and random initialization. The data sets were chosen to have a small number of clusters (two to seven) and a moderate number of data points (up to a few hundred). Pairwise stability is defined as the adjusted Rand index between pairs of clusterers in the ensemble, averaged across all pairs. Nonpairwise stability is defined as the entropy of the consensus matrix of the ensemble. An experimental comparison with the stability of the standard k-means algorithm was carried out for k from 2 to 20. The results revealed that ensembles are generally more stable, markedly so for larger k. To establish whether stability can serve as a cluster validity index, we first looked at the relationship between stability and accuracy with respect to the number of clusters, k. We found that such a relationship strongly depends on the data set, varying from almost perfect positive correlation (0.97, for the glass data) to almost perfect negative correlation (-0.93, for the crabs data). We propose a new combined stability index to be the sum of the pairwise individual and ensemble stabilities. This index was found to correlate better with the ensemble accuracy. Following the hypothesis that a point of stability of a clustering algorithm corresponds to a structure found in the data, we used the stability measures to pick the number of clusters. The combined stability index gave best results.

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

Science.gov (United States)

Steinley, Douglas

2006-01-01

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

Pathway Aggregation in the Risk Assessment of Proliferation Resistance and Physical Protection (PR&PP) of Nuclear Energy Systems

International Nuclear Information System (INIS)

2015-01-01

The framework for Proliferation Resistance and Physical Protection (PR & PP) evaluation is to define a set of challenges, to obtain the system responses, and to assess the outcomes. The assessment of outcomes heavily relies on pathways, defined as sequences of events or actions that could potentially be followed by a State or a group of individuals in order to achieve a proliferation objective, with the defined threats as initiating events. There may be large number of segments connecting pathway stages (e.g. acquisition, processing, and fabrication for PR) which can lead to even larger number of pathways or scenarios through possible different combinations of segment connections, each with associated probabilities contributing to the overall risk. Clustering of these scenarios in specified stage attribute intervals is important for their tractable analysis and outcome assessment. A software tool for scenario generation and clustering (OSUPR) is developed that utilizes the PRCALC code developed at the Brookhaven National Laboratory for scenario generation and the K- means, mean shift and adaptive mean shift algorithms as possible clustering schemes. The results of the study using the Example Sodium Fast Breeder as an example system show that clustering facilitates the probabilistic or deterministic analysis of scenarios to identify system vulnerabilities and communication of the major risk contributors to stakeholders. The results of the study also show that the mean shift algorithm has the most potential for assisting the analysis of the scenarios generated by PRCALC.

Pathway Aggregation in the Risk Assessment of Proliferation Resistance and Physical Protection (PR&PP) of Nuclear Energy Systems

Energy Technology Data Exchange (ETDEWEB)

Aldemir, Tunc [Ohio State Univ., Columbus, OH (United States); Denning, Richard [Ohio State Univ., Columbus, OH (United States); Catalyurek, Umit [Ohio State Univ., Columbus, OH (United States); Yilmaz, Alper [Ohio State Univ., Columbus, OH (United States); Yue, Meng [Brookhaven National Lab. (BNL), Upton, NY (United States); Cheng, Lap-Yan [Brookhaven National Lab. (BNL), Upton, NY (United States)

2015-01-23

The framework for Proliferation Resistance and Physical Protection (PR & PP) evaluation is to define a set of challenges, to obtain the system responses, and to assess the outcomes. The assessment of outcomes heavily relies on pathways, defined as sequences of events or actions that could potentially be followed by a State or a group of individuals in order to achieve a proliferation objective, with the defined threats as initiating events. There may be large number of segments connecting pathway stages (e.g. acquisition, processing, and fabrication for PR) which can lead to even larger number of pathways or scenarios through possible different combinations of segment connections, each with associated probabilities contributing to the overall risk. Clustering of these scenarios in specified stage attribute intervals is important for their tractable analysis and outcome assessment. A software tool for scenario generation and clustering (OSUPR) is developed that utilizes the PRCALC code developed at the Brookhaven National Laboratory for scenario generation and the K- means, mean shift and adaptive mean shift algorithms as possible clustering schemes. The results of the study using the Example Sodium Fast Breeder as an example system show that clustering facilitates the probabilistic or deterministic analysis of scenarios to identify system vulnerabilities and communication of the major risk contributors to stakeholders. The results of the study also show that the mean shift algorithm has the most potential for assisting the analysis of the scenarios generated by PRCALC.

An Initial Seed Selection Algorithm for K-means Clustering of Georeferenced Data to Improve Replicability of Cluster Assignments for Mapping Application

OpenAIRE

Khan, Fouad

2016-01-01

K-means is one of the most widely used clustering algorithms in various disciplines, especially for large datasets. However the method is known to be highly sensitive to initial seed selection of cluster centers. K-means++ has been proposed to overcome this problem and has been shown to have better accuracy and computational efficiency than k-means. In many clustering problems though -such as when classifying georeferenced data for mapping applications- standardization of clustering methodolo...

Fault Detection Using the Clustering-kNN Rule for Gas Sensor Arrays

Directory of Open Access Journals (Sweden)

Jingli Yang

2016-12-01

Full Text Available The k-nearest neighbour (kNN rule, which naturally handles the possible non-linearity of data, is introduced to solve the fault detection problem of gas sensor arrays. In traditional fault detection methods based on the kNN rule, the detection process of each new test sample involves all samples in the entire training sample set. Therefore, these methods can be computation intensive in monitoring processes with a large volume of variables and training samples and may be impossible for real-time monitoring. To address this problem, a novel clustering-kNN rule is presented. The landmark-based spectral clustering (LSC algorithm, which has low computational complexity, is employed to divide the entire training sample set into several clusters. Further, the kNN rule is only conducted in the cluster that is nearest to the test sample; thus, the efficiency of the fault detection methods can be enhanced by reducing the number of training samples involved in the detection process of each test sample. The performance of the proposed clustering-kNN rule is fully verified in numerical simulations with both linear and non-linear models and a real gas sensor array experimental system with different kinds of faults. The results of simulations and experiments demonstrate that the clustering-kNN rule can greatly enhance both the accuracy and efficiency of fault detection methods and provide an excellent solution to reliable and real-time monitoring of gas sensor arrays.

Fault Detection Using the Clustering-kNN Rule for Gas Sensor Arrays

Science.gov (United States)

Yang, Jingli; Sun, Zhen; Chen, Yinsheng

2016-01-01

The k-nearest neighbour (kNN) rule, which naturally handles the possible non-linearity of data, is introduced to solve the fault detection problem of gas sensor arrays. In traditional fault detection methods based on the kNN rule, the detection process of each new test sample involves all samples in the entire training sample set. Therefore, these methods can be computation intensive in monitoring processes with a large volume of variables and training samples and may be impossible for real-time monitoring. To address this problem, a novel clustering-kNN rule is presented. The landmark-based spectral clustering (LSC) algorithm, which has low computational complexity, is employed to divide the entire training sample set into several clusters. Further, the kNN rule is only conducted in the cluster that is nearest to the test sample; thus, the efficiency of the fault detection methods can be enhanced by reducing the number of training samples involved in the detection process of each test sample. The performance of the proposed clustering-kNN rule is fully verified in numerical simulations with both linear and non-linear models and a real gas sensor array experimental system with different kinds of faults. The results of simulations and experiments demonstrate that the clustering-kNN rule can greatly enhance both the accuracy and efficiency of fault detection methods and provide an excellent solution to reliable and real-time monitoring of gas sensor arrays. PMID:27929412

Implementasi Pendekatan Rule-Of-Thumb untuk Optimasi Algoritma K-Means Clustering

Directory of Open Access Journals (Sweden)

M Nishom

2018-05-01

Full Text Available In the big data era, the clustering of data or so-called clustering has attracted great interest or attention from researchers in conducting various studies, many grouping algorithms have been proposed in recent times. However, as technology evolves, data volumes continue to grow and data formats are increasingly varied, thus making massive data grouping into a huge and challenging task. To overcome this problem, various research related methods for data grouping have been done, among them is K-Means. However, this method still has some shortcomings, among them is the sensitivity issue in determining the value of cluster (K. In this paper we discuss the implementation of the rule-of-thumb approach and the normalization of data on the K-Means method to determine the number of clusters or K values dynamically in the data groupings. The results show that the implementation of the approach has a significant impact (related to time, number of iterations, and no outliers in the data grouping.

Clustering performance comparison using K-means and expectation maximization algorithms.

Science.gov (United States)

Jung, Yong Gyu; Kang, Min Soo; Heo, Jun

2014-11-14

Clustering is an important means of data mining based on separating data categories by similar features. Unlike the classification algorithm, clustering belongs to the unsupervised type of algorithms. Two representatives of the clustering algorithms are the K -means and the expectation maximization (EM) algorithm. Linear regression analysis was extended to the category-type dependent variable, while logistic regression was achieved using a linear combination of independent variables. To predict the possibility of occurrence of an event, a statistical approach is used. However, the classification of all data by means of logistic regression analysis cannot guarantee the accuracy of the results. In this paper, the logistic regression analysis is applied to EM clusters and the K -means clustering method for quality assessment of red wine, and a method is proposed for ensuring the accuracy of the classification results.

Security and Correctness Analysis on Privacy-Preserving k-Means Clustering Schemes

Science.gov (United States)

Su, Chunhua; Bao, Feng; Zhou, Jianying; Takagi, Tsuyoshi; Sakurai, Kouichi

Due to the fast development of Internet and the related IT technologies, it becomes more and more easier to access a large amount of data. k-means clustering is a powerful and frequently used technique in data mining. Many research papers about privacy-preserving k-means clustering were published. In this paper, we analyze the existing privacy-preserving k-means clustering schemes based on the cryptographic techniques. We show those schemes will cause the privacy breach and cannot output the correct results due to the faults in the protocol construction. Furthermore, we analyze our proposal as an option to improve such problems but with intermediate information breach during the computation.

Are Nuclear Star Clusters the Precursors of Massive Black Holes?

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Nadine Neumayer

2012-01-01

Full Text Available We present new upper limits for black hole masses in extremely late type spiral galaxies. We confirm that this class of galaxies has black holes with masses less than 106M⊙, if any. We also derive new upper limits for nuclear star cluster masses in massive galaxies with previously determined black hole masses. We use the newly derived upper limits and a literature compilation to study the low mass end of the global-to-nucleus relations. We find the following. (1 The MBH-σ relation cannot flatten at low masses, but may steepen. (2 The MBH-Mbulge relation may well flatten in contrast. (3 The MBH-Sersic n relation is able to account for the large scatter in black hole masses in low-mass disk galaxies. Outliers in the MBH-Sersic n relation seem to be dwarf elliptical galaxies. When plotting MBH versus MNC we find three different regimes: (a nuclear cluster dominated nuclei, (b a transition region, and (c black hole-dominated nuclei. This is consistent with the picture, in which black holes form inside nuclear clusters with a very low-mass fraction. They subsequently grow much faster than the nuclear cluster, destroying it when the ratio MBH/MNC grows above 100. Nuclear star clusters may thus be the precursors of massive black holes in galaxy nuclei.

Study of the f'(1514) meson in the reaction pp{yields} k{sub s}K{sup =}{sub s}{pi}{sup 0} at 700 and 760 MeV/c; Estudio del meson f'(1514) en la reaccion pp{yields}K{sup 0}{sub s}K{sup 0}{sub s}{pi}{sup =} a 700 y 760 MeV/c

Energy Technology Data Exchange (ETDEWEB)

Salicio, J A; Duran, I

1980-07-01

An analysis of the reaction pp{yields} K{sup 0}{sub s}K{sup 0}{sub s}i{pi}{sup 0} is presented with special emphasis in determining the intermediate resonant states. A particular study of the production and decay properties of the f'meson is also included. (Author) 22 refs.

Quantitative properties of clustering within modern microscopic nuclear models

International Nuclear Information System (INIS)

Volya, A.; Tchuvil’sky, Yu. M.

2016-01-01

A method for studying cluster spectroscopic properties of nuclear fragmentation, such as spectroscopic amplitudes, cluster form factors, and spectroscopic factors, is developed on the basis of modern precision nuclear models that take into account the mixing of large-scale shell-model configurations. Alpha-cluster channels are considered as an example. A mathematical proof of the need for taking into account the channel-wave-function renormalization generated by exchange terms of the antisymmetrization operator (Fliessbach effect) is given. Examples where this effect is confirmed by a high quality of the description of experimental data are presented. By and large, the method in question extends substantially the possibilities for studying clustering phenomena in nuclei and for improving the quality of their description.

X-ray Observations of Eight Young Open Star Clusters: I ...

Indian Academy of Sciences (India)

X-ray Observations of Eight Young Open Star Clusters: I. Membership and X-ray Luminosity. Himali Bhatt, J. C. Pandey, K. P. Singh, Ram Sagar & Brijesh Kumar. J. Astrophys. Astr. 34(4), December 2013, pp. 393–429, c Indian Academy of Sciences. Supplementary Material. Supplementary Table 3 follows.

CLUSTERING PENENTUAN POTENSI KEJAHATAN DAERAH DI KOTA BANJARBARU DENGAN METODE K-MEANS

Directory of Open Access Journals (Sweden)

Sri Rahayu

2016-09-01

Full Text Available Abstract Within the scope of the police, the data held in the database can be used to make a crime report, the presumption of evil to come, and so on. With the data mining based on the amount of data stored so much, these data can be processed to find the useful knowledge for police. One technique that is known in the data mining clustering techniques. The purpose of the job grouping (clustering the data can be divided into two, namely grouping for understanding and grouping to use. Methods K-Means clustering is a method for engineering the most simple and common. KMeans clustering is one method of data non-hierarchy (partition which seeks to partition the existing data in the form of two or more groups. This method of partitioning data into groups so that the same characteristic of data put into the same group and a different characteristic data are grouped into another group. The purpose of this grouping is to minimize the objective function is set in the grouping process, which generally seek to minimize the variation within a group and maximize the variation between groups. The data mined to determine the potential clustering of crime in the city area of crime data Banjarbaru is owned by the city police in the Police Banjarbaru. Thus this study aims to assess the stage of clustering techniques and build clustering determination of potential crime areas in the city Banjarbaru. Keywords:Clustering, Data mining, K-Means, K-Means Clustering ABSTRAK Dalam ruang lingkup kepolisian, data-data yang dimiliki pada basis data dapat dimanfaatkan untuk pembuatan laporan kejahatan, praduga kejahatan yang akan datang, dan sebagainya.Dengan adanya data mining yang didasarkan pada jumlah data yang tersimpan begitu banyak, data-data tersebut dapat diproses untuk menemukan suatu pengetahuan yang berguna bagi pihak kepolisian.Salah satu teknik yang dikenal dalam data mining yaitu teknik clustering.Tujuan pekerjaan pengelompokan (clustering data dapat dibedakan

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.

Clustering for Binary Data Sets by Using Genetic Algorithm-Incremental K-means

Science.gov (United States)

Saharan, S.; Baragona, R.; Nor, M. E.; Salleh, R. M.; Asrah, N. M.

2018-04-01

This research was initially driven by the lack of clustering algorithms that specifically focus in binary data. To overcome this gap in knowledge, a promising technique for analysing this type of data became the main subject in this research, namely Genetic Algorithms (GA). For the purpose of this research, GA was combined with the Incremental K-means (IKM) algorithm to cluster the binary data streams. In GAIKM, the objective function was based on a few sufficient statistics that may be easily and quickly calculated on binary numbers. The implementation of IKM will give an advantage in terms of fast convergence. The results show that GAIKM is an efficient and effective new clustering algorithm compared to the clustering algorithms and to the IKM itself. In conclusion, the GAIKM outperformed other clustering algorithms such as GCUK, IKM, Scalable K-means (SKM) and K-means clustering and paves the way for future research involving missing data and outliers.

Hybrid K-means Dan Particle Swarm Optimization Untuk Clustering Nasabah Kredit

Directory of Open Access Journals (Sweden)

Yusuf Priyo Anggodo

2017-05-01

Credit is the biggest revenue for the bank. However, banks have to be selective in deciding which clients can receive the credit. This issue is becoming increasingly complex because when the bank was wrong to give credit to customers can do harm, apart of that a large number of deciding parameter in determining customer credit. Clustering is one way to be able to resolve this issue. K-means is a simple and popular method for solving clustering. However, K-means pure can’t provide optimum solutions so that needs to be done to get the optimum solution to improve. One method of optimization that can solve the problems of optimization with particle swarm optimization is good (PSO. PSO is very helpful in the process of clustering to perform optimization on the central point of each cluster. To improve better results on PSO there are some that do improve. The first use of time-variant inertia to make the dynamic value of inertial w each iteration. Both control the speed of the particle velocity or clamping to get the best position. Besides to overcome premature convergence do hybrid PSO with random injection. The results of this research provide the optimum results for solving clustering of customer credits. The test results showed the hybrid PSO K-means provide the greatest results than K-means and PSO K-means, where the silhouette of the K-means, PSO K-means, and hybrid PSO K-means respectively 0.57343, 0.792045, 1. Keywords: Credit, Clustering, PSO, K-means, Random Injection

Progesterone-associated proteins PP12 and PP14 in the human endometrium.

Science.gov (United States)

Rutanen, E M; Koistinen, R; Seppälä, M; Julkunen, M; Suikkari, A M; Huhtala, M L

1987-01-01

Two proteins, designated as PP12 and PP14 were originally isolated from soluble extracts of the human placenta and its adjacent membranes. We have shown that they are synthesized by decidualized/secretory endometrium and not by placenta. Both proteins occur at high concentrations in human amniotic fluid, which is therefore an excellent source for purification. PP12 is a 34-kDa glycoprotein, which has an N-terminal amino acid sequence of Ala-Pro-Trp-Gln-Cys-Ala-Pro-Cys-Ser-Ala. This is identical with that of somatomedin-binding protein purified from the amniotic fluid. PP12 too binds somatomedin-C, or IGF-I (insulin-like growth factor-I). Human secretory endometrium synthesizes and secretes PP12, and progesterone stimulates its secretion. PP14 is a 28-kDa glycoprotein. Its N-terminal sequence shows homology to that of beta-lactoglobulins from various species. We have found PP14 in the human endometrium, serum and milk. Immunologically, PP14 is related to progestagen-associated endometrial protein (PEP), alpha-2 pregnancy-associated endometrial protein (alpha-2, PEG), endometrial protein 15 (EP15), alpha-uterine protein (AUP) and chorionic alpha-2 microglobulin (CAG-2). In ovulatory menstrual cycles, the concentration of PP14 increases in endometrial tissue as the secretory changes advance. In serum, the PP14 concentration begins to rise later than the progesterone levels, and high serum PP14 levels are maintained for the first days of the next cycle. By contrast, no elevation of serum PP14 level is seen in anovulatory cycles. Our results show that progesterone-associated proteins are synthesized by the human endometrium and appear in the peripheral circulation, where they can be quantitatively measured using immunochemical techniques.

Structuring heterogeneous biological information using fuzzy clustering of k-partite graphs

Directory of Open Access Journals (Sweden)

Theis Fabian J

2010-10-01

Full Text Available Abstract Background Extensive and automated data integration in bioinformatics facilitates the construction of large, complex biological networks. However, the challenge lies in the interpretation of these networks. While most research focuses on the unipartite or bipartite case, we address the more general but common situation of k-partite graphs. These graphs contain k different node types and links are only allowed between nodes of different types. In order to reveal their structural organization and describe the contained information in a more coarse-grained fashion, we ask how to detect clusters within each node type. Results Since entities in biological networks regularly have more than one function and hence participate in more than one cluster, we developed a k-partite graph partitioning algorithm that allows for overlapping (fuzzy clusters. It determines for each node a degree of membership to each cluster. Moreover, the algorithm estimates a weighted k-partite graph that connects the extracted clusters. Our method is fast and efficient, mimicking the multiplicative update rules commonly employed in algorithms for non-negative matrix factorization. It facilitates the decomposition of networks on a chosen scale and therefore allows for analysis and interpretation of structures on various resolution levels. Applying our algorithm to a tripartite disease-gene-protein complex network, we were able to structure this graph on a large scale into clusters that are functionally correlated and biologically meaningful. Locally, smaller clusters enabled reclassification or annotation of the clusters' elements. We exemplified this for the transcription factor MECP2. Conclusions In order to cope with the overwhelming amount of information available from biomedical literature, we need to tackle the challenge of finding structures in large networks with nodes of multiple types. To this end, we presented a novel fuzzy k-partite graph partitioning

Cluster radioactive decay within the preformed cluster model using relativistic mean-field theory densities

International Nuclear Information System (INIS)

Singh, BirBikram; Patra, S. K.; Gupta, Raj K.

2010-01-01

We have studied the (ground-state) cluster radioactive decays within the preformed cluster model (PCM) of Gupta and collaborators [R. K. Gupta, in Proceedings of the 5th International Conference on Nuclear Reaction Mechanisms, Varenna, edited by E. Gadioli (Ricerca Scientifica ed Educazione Permanente, Milano, 1988), p. 416; S. S. Malik and R. K. Gupta, Phys. Rev. C 39, 1992 (1989)]. The relativistic mean-field (RMF) theory is used to obtain the nuclear matter densities for the double folding procedure used to construct the cluster-daughter potential with M3Y nucleon-nucleon interaction including exchange effects. Following the PCM approach, we have deduced empirically the preformation probability P 0 emp from the experimental data on both the α- and exotic cluster-decays, specifically of parents in the trans-lead region having doubly magic 208 Pb or its neighboring nuclei as daughters. Interestingly, the RMF-densities-based nuclear potential supports the concept of preformation for both the α and heavier clusters in radioactive nuclei. P 0 α(emp) for α decays is almost constant (∼10 -2 -10 -3 ) for all the parent nuclei considered here, and P 0 c(emp) for cluster decays of the same parents decrease with the size of clusters emitted from different parents. The results obtained for P 0 c(emp) are reasonable and are within two to three orders of magnitude of the well-accepted phenomenological model of Blendowske-Walliser for light clusters.

Study of NΣ cusp in p+p → p+K{sup +}+Λ with partial wave analysis

Energy Technology Data Exchange (ETDEWEB)

Lu, S.; Muenzer, R.; Epple, E.; Fabbietti, L. [Excellenz Cluster Universe, Technische Universitaet Muenchen (Germany); Ritman, J.; Roderburg, E.; Hauenstein, F. [FZ Juelich (Germany); Collaboration: Hades and FOPI Collaboration

2016-07-01

In the last years, an analysis of exclusive reaction of p+p → p+K{sup +}+Λ has been carried out using Bonn-Gatchina Partial Wave Analysis. In a combined analysis of data from Hades, Fopi, Disto and Cosy-TOF, an energy dependent production process is determined. This analysis has shown that a sufficient description of the p+p → p+K{sup +}+Λ is quite challenging due to the presence of resonances N* and interference, which requires Partial Wave Analysis. A pronounced narrow structure is observed in its projection on the pΛ-invariant mass. This peak structure, which appears around the NΣ threshold, has a strongly asymmetric structure and is interpreted a NΣ cusp effect. In this talk, the results from a combined analysis will be shown, with a special focus on the NΣ cusp structure and a description using Flatte parametrization.

Long-term surface EMG monitoring using K-means clustering and compressive sensing

Science.gov (United States)

Balouchestani, Mohammadreza; Krishnan, Sridhar

2015-05-01

In this work, we present an advanced K-means clustering algorithm based on Compressed Sensing theory (CS) in combination with the K-Singular Value Decomposition (K-SVD) method for Clustering of long-term recording of surface Electromyography (sEMG) signals. The long-term monitoring of sEMG signals aims at recording of the electrical activity produced by muscles which are very useful procedure for treatment and diagnostic purposes as well as for detection of various pathologies. The proposed algorithm is examined for three scenarios of sEMG signals including healthy person (sEMG-Healthy), a patient with myopathy (sEMG-Myopathy), and a patient with neuropathy (sEMG-Neuropathr), respectively. The proposed algorithm can easily scan large sEMG datasets of long-term sEMG recording. We test the proposed algorithm with Principal Component Analysis (PCA) and Linear Correlation Coefficient (LCC) dimensionality reduction methods. Then, the output of the proposed algorithm is fed to K-Nearest Neighbours (K-NN) and Probabilistic Neural Network (PNN) classifiers in order to calclute the clustering performance. The proposed algorithm achieves a classification accuracy of 99.22%. This ability allows reducing 17% of Average Classification Error (ACE), 9% of Training Error (TE), and 18% of Root Mean Square Error (RMSE). The proposed algorithm also reduces 14% clustering energy consumption compared to the existing K-Means clustering algorithm.

Quantification of the clustering properties of nuclear states

International Nuclear Information System (INIS)

Beck, R.; Dickmann, F.

1985-05-01

The amount of particular type of clustering in a nuclear state is defined in this paper as the norm square of the projection of the wave function onto the particular cluster model subspace. It is pointed out that, although the clusters can not be localized in space by measurement, the amount of clustering characterizes the cluster formation in close analogy with a quantum mechanical probability. The cluster model component of the wave function is proved to have a variational property. This facilitates the computation of the amount of clustering. The model dependence of the amounts of various clusterings and their relationship to the corresponding spectroscopic factors are studied via numerical examples for two models of sup(6)Li. It is concluded that, in a relative sense, the spectroscopic factor, which is more directly related to experiment, is also characteristic of the clustering contents of different states of the same nucleus, but it can not be used for comparisons between different nuclei or clusterings. (author)

3D Building Models Segmentation Based on K-Means++ Cluster Analysis

Science.gov (United States)

Zhang, C.; Mao, B.

2016-10-01

3D mesh model segmentation is drawing increasing attentions from digital geometry processing field in recent years. The original 3D mesh model need to be divided into separate meaningful parts or surface patches based on certain standards to support reconstruction, compressing, texture mapping, model retrieval and etc. Therefore, segmentation is a key problem for 3D mesh model segmentation. In this paper, we propose a method to segment Collada (a type of mesh model) 3D building models into meaningful parts using cluster analysis. Common clustering methods segment 3D mesh models by K-means, whose performance heavily depends on randomized initial seed points (i.e., centroid) and different randomized centroid can get quite different results. Therefore, we improved the existing method and used K-means++ clustering algorithm to solve this problem. Our experiments show that K-means++ improves both the speed and the accuracy of K-means, and achieve good and meaningful results.

3D BUILDING MODELS SEGMENTATION BASED ON K-MEANS++ CLUSTER ANALYSIS

Directory of Open Access Journals (Sweden)

C. Zhang

2016-10-01

Full Text Available 3D mesh model segmentation is drawing increasing attentions from digital geometry processing field in recent years. The original 3D mesh model need to be divided into separate meaningful parts or surface patches based on certain standards to support reconstruction, compressing, texture mapping, model retrieval and etc. Therefore, segmentation is a key problem for 3D mesh model segmentation. In this paper, we propose a method to segment Collada (a type of mesh model 3D building models into meaningful parts using cluster analysis. Common clustering methods segment 3D mesh models by K-means, whose performance heavily depends on randomized initial seed points (i.e., centroid and different randomized centroid can get quite different results. Therefore, we improved the existing method and used K-means++ clustering algorithm to solve this problem. Our experiments show that K-means++ improves both the speed and the accuracy of K-means, and achieve good and meaningful results.

Segmentation of dermatoscopic images by frequency domain filtering and k-means clustering algorithms.

Science.gov (United States)

Rajab, Maher I

2011-11-01

Since the introduction of epiluminescence microscopy (ELM), image analysis tools have been extended to the field of dermatology, in an attempt to algorithmically reproduce clinical evaluation. Accurate image segmentation of skin lesions is one of the key steps for useful, early and non-invasive diagnosis of coetaneous melanomas. This paper proposes two image segmentation algorithms based on frequency domain processing and k-means clustering/fuzzy k-means clustering. The two methods are capable of segmenting and extracting the true border that reveals the global structure irregularity (indentations and protrusions), which may suggest excessive cell growth or regression of a melanoma. As a pre-processing step, Fourier low-pass filtering is applied to reduce the surrounding noise in a skin lesion image. A quantitative comparison of the techniques is enabled by the use of synthetic skin lesion images that model lesions covered with hair to which Gaussian noise is added. The proposed techniques are also compared with an established optimal-based thresholding skin-segmentation method. It is demonstrated that for lesions with a range of different border irregularity properties, the k-means clustering and fuzzy k-means clustering segmentation methods provide the best performance over a range of signal to noise ratios. The proposed segmentation techniques are also demonstrated to have similar performance when tested on real skin lesions representing high-resolution ELM images. This study suggests that the segmentation results obtained using a combination of low-pass frequency filtering and k-means or fuzzy k-means clustering are superior to the result that would be obtained by using k-means or fuzzy k-means clustering segmentation methods alone. © 2011 John Wiley & Sons A/S.

The combinatorial PP1-binding consensus Motif (R/Kx( (0,1V/IxFxx(R/Kx(R/K is a new apoptotic signature.

Directory of Open Access Journals (Sweden)

Angélique N Godet

Full Text Available BACKGROUND: Previous studies established that PP1 is a target for Bcl-2 proteins and an important regulator of apoptosis. The two distinct functional PP1 consensus docking motifs, R/Kx((0,1V/IxF and FxxR/KxR/K, involved in PP1 binding and cell death were previously characterized in the BH1 and BH3 domains of some Bcl-2 proteins. PRINCIPAL FINDINGS: In this study, we demonstrate that DPT-AIF(1, a peptide containing the AIF(562-571 sequence located in a c-terminal domain of AIF, is a new PP1 interacting and cell penetrating molecule. We also showed that DPT-AIF(1 provoked apoptosis in several human cell lines. Furthermore, DPT-APAF(1 a bi-partite cell penetrating peptide containing APAF-1(122-131, a non penetrating sequence from APAF-1 protein, linked to our previously described DPT-sh1 peptide shuttle, is also a PP1-interacting death molecule. Both AIF(562-571 and APAF-1(122-131 sequences contain a common R/Kx((0,1V/IxFxxR/KxR/K motif, shared by several proteins involved in control of cell survival pathways. This motif combines the two distinct PP1c consensus docking motifs initially identified in some Bcl-2 proteins. Interestingly DPT-AIF(2 and DPT-APAF(2 that carry a F to A mutation within this combinatorial motif, no longer exhibited any PP1c binding or apoptotic effects. Moreover the F to A mutation in DPT-AIF(2 also suppressed cell penetration. CONCLUSION: These results indicate that the combinatorial PP1c docking motif R/Kx((0,1V/IxFxxR/KxR/K, deduced from AIF(562-571 and APAF-1(122-131 sequences, is a new PP1c-dependent Apoptotic Signature. This motif is also a new tool for drug design that could be used to characterize potential anti-tumour molecules.

Nuclear installations and childhood cancer in the U.K

International Nuclear Information System (INIS)

Goldsmith, J.R.

1990-01-01

The report in November 1983 of a cluster of childhood leukemia cases in the vicinity of the Sellafield (Windscale) nuclear facility on the west coast of England has led to a substantial effort to study possible excess cancer in the vicinity of British nuclear installations. Although some additional excesses were found, the causal relationship with radionuclides was thought unlikely because the estimated doses were below those established as causal of increase in human leukemia. Since 1956, we have known that diagnostic x-rays during pregnancy are associated with increased risks from childhood cancer, especially leukemia. Gardner et al. showed that excess cases near Sellafield were in children born there, and no excess occurred among in-migrants. Roman et al. showed that significant elevations in leukemia among children living near three nuclear installations in the Midlands were only at 0-5 y, suggesting that the relevant exposure was prenatal. We identify and discuss a set of epidemiological, dosage estimation, and modeling problems relevant to interpretation of such data. We conclude that: (1) a red bone marrow-based model for brief, high-level exposures of adults associated with myelogenous leukemia is inappropriate for evaluating the impact of internal emitters, relatively continuous exposures in perinatal periods in association with acute lymphatic leukemia; (2) incidence of mortality rates of childhood leukemia should be evaluated in the vicinity of nuclear installations in many countries; and (3) in contrast to nuclear reprocessing and nuclear weapons installations, there is little evidence of excess childhood leukemia among residents in areas adjacent to nuclear power installations in the U.K

Universal scaling of strange particle pT spectra in pp collisions

Science.gov (United States)

Yang, Liwen; Wang, Yanyun; Hao, Wenhui; Liu, Na; Du, Xiaoling; Zhang, Wenchao

2018-04-01

As a complementary study to that performed on the transverse momentum (pT) spectra of charged pions, kaons and protons in proton-proton (pp) collisions at LHC energies 0.9, 2.76 and 7TeV, we present a scaling behaviour in the pT spectra of strange particles (KS0, Λ, Ξ and φ) at these three energies. This scaling behaviour is exhibited when the spectra are expressed in a suitable scaling variable z=pT/K, where the scaling parameter K is determined by the quality factor method and increases with the center of mass energy (√{s}). The rates at which K increases with ln √{s} for these strange particles are found to be identical within errors. In the framework of the colour string percolation model, we argue that these strange particles are produced through the decay of clusters that are formed by the colour strings overlapping. We observe that the strange mesons and baryons are produced from clusters with different size distributions, while the strange mesons (baryons) KS0 and φ ( Λ and Ξ) originate from clusters with the same size distributions. The cluster's size distributions for strange mesons are more dispersed than those for strange baryons. The scaling behaviour of the pT spectra for these strange particles can be explained by the colour string percolation model in a quantitative way.

A Fast Exact k-Nearest Neighbors Algorithm for High Dimensional Search Using k-Means Clustering and Triangle Inequality.

Science.gov (United States)

Wang, Xueyi

2012-02-08

The k-nearest neighbors (k-NN) algorithm is a widely used machine learning method that finds nearest neighbors of a test object in a feature space. We present a new exact k-NN algorithm called kMkNN (k-Means for k-Nearest Neighbors) that uses the k-means clustering and the triangle inequality to accelerate the searching for nearest neighbors in a high dimensional space. The kMkNN algorithm has two stages. In the buildup stage, instead of using complex tree structures such as metric trees, kd-trees, or ball-tree, kMkNN uses a simple k-means clustering method to preprocess the training dataset. In the searching stage, given a query object, kMkNN finds nearest training objects starting from the nearest cluster to the query object and uses the triangle inequality to reduce the distance calculations. Experiments show that the performance of kMkNN is surprisingly good compared to the traditional k-NN algorithm and tree-based k-NN algorithms such as kd-trees and ball-trees. On a collection of 20 datasets with up to 10(6) records and 10(4) dimensions, kMkNN shows a 2-to 80-fold reduction of distance calculations and a 2- to 60-fold speedup over the traditional k-NN algorithm for 16 datasets. Furthermore, kMkNN performs significant better than a kd-tree based k-NN algorithm for all datasets and performs better than a ball-tree based k-NN algorithm for most datasets. The results show that kMkNN is effective for searching nearest neighbors in high dimensional spaces.

Analysis of pp and pp-bar in forward scattering using derivative dispersion relations

International Nuclear Information System (INIS)

Kohara, A. K.; Ferreira, E.; Kodama, T.

2010-01-01

We describe the amplitudes for pp and pp-bar scattering at small momentum transfers, where Coulomb and nuclear interference occurs, with special attention to the slopes of the real and imaginary parts. The forward amplitudes are assumed to have simple exponential forms, depending on four parameters σ, ρ, B I , B R , with B I ≠ B R .

Chemical interaction and adhesion characteristics at the interface of metals (Cu, Ta) and low-k cyclohexane-based plasma polymer (CHexPP) films

International Nuclear Information System (INIS)

Kim, K.J.; Kim, K.S.; Lee, N.-E.; Choi, J.; Jung, D.

2001-01-01

Chemical interaction and adhesion characteristics between metals (Cu, Ta) and low-k plasma-treated cyclohexane-based plasma polymer (CHexPP) films were studied. In order to generate new functional groups that may contribute to the improvement of adhesion between metal and plasma polymer, we performed O 2 , N 2 , and H 2 /He mixture plasma treatment on the surfaces of CHexPP films. Chemical interactions at the interface between metals (Cu, Ta) and plasma-treated CHexPP films were analyzed by x-ray photoelectron spectroscopy. The effect of plasma treatment and thermal annealing on the adhesion characteristics was measured by a tape test and scratch test. The formation of new binding states on the surface of plasma-treated CHexPP films improved adhesion characteristics between metals and CHexPP films. Thermal annealing improves the adhesion property of Cu/CHexPP films, but degrades the adhesion property of Ta/CHexPP films

Nuclear cluster strategy Carolinas - Ontario - Saskatchewan

International Nuclear Information System (INIS)

Oberth, R.

2012-01-01

Organization of Candu Industries (OCI) is an industry association representing the interests of 170 private sector suppliers of products and services to the Canadian and offshore nuclear industries. OCI member companies, mainly in Ontario, employ over 30,000 highly specialized workers with over 12,000 working in nuclear area. OCI's objectives are to sustain the domestic nuclear program by building support among political leaders, the public and local communities, assist OCI member companies in becoming the preferred suppliers for domestic nuclear projects (competitive), assist OCI member companies in international nuclear markets - trade missions and vendor workshops. OCI is at the heart of an 'Ontario nuclear cluster'. The Carolinas have shown what can be achieved when industry, academia, S&T centers and governments collaborate with a shared vision to achieve a common goals. Ontario has the assets to become a stronger center for nuclear excellence. OCI is working to bring the pieces together. Saskatchewan has the assets to become a center of excellence in Small Modular Reactors (SMR) by licensing and constructing the first SMR in Canada.

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

OpenAIRE

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

2018-01-01

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

Breast Cancer Symptom Clusters Derived from Social Media and Research Study Data Using Improved K-Medoid Clustering

Science.gov (United States)

Ping, Qing; Yang, Christopher C.; Marshall, Sarah A.; Avis, Nancy E.; Ip, Edward H.

2017-01-01

Most cancer patients, including patients with breast cancer, experience multiple symptoms simultaneously while receiving active treatment. Some symptoms tend to occur together and may be related, such as hot flashes and night sweats. Co-occurring symptoms may have a multiplicative effect on patients’ functioning, mental health, and quality of life. Symptom clusters in the context of oncology were originally described as groups of three or more related symptoms. Some authors have suggested symptom clusters may have practical applications, such as the formulation of more effective therapeutic interventions that address the combined effects of symptoms rather than treating each symptom separately. Most studies that have sought to identify clusters in breast cancer survivors have relied on traditional research studies. Social media, such as online health-related forums, contain a bevy of user-generated content in the form of threads and posts, and could be used as a data source to identify and characterize symptom clusters among cancer patients. The present study seeks to determine patterns of symptom clusters in breast cancer survivors derived from both social media and research study data using improved K-Medoid clustering. A total of 50,426 publicly available messages were collected from Medhelp.com and 653 questionnaires were collected as part of a research study. The network of symptoms built from social media was sparse compared to that of the research study data, making the social media data easier to partition. The proposed revised K-Medoid clustering helps to improve the clustering performance by re-assigning some of the negative-ASW (average silhouette width) symptoms to other clusters after initial K-Medoid clustering. This retains an overall non-decreasing ASW and avoids the problem of trapping in local optima. The overall ASW, individual ASW, and improved interpretation of the final clustering solution suggest improvement. The clustering results suggest

Breast Cancer Symptom Clusters Derived from Social Media and Research Study Data Using Improved K-Medoid Clustering.

Science.gov (United States)

Ping, Qing; Yang, Christopher C; Marshall, Sarah A; Avis, Nancy E; Ip, Edward H

2016-06-01

Most cancer patients, including patients with breast cancer, experience multiple symptoms simultaneously while receiving active treatment. Some symptoms tend to occur together and may be related, such as hot flashes and night sweats. Co-occurring symptoms may have a multiplicative effect on patients' functioning, mental health, and quality of life. Symptom clusters in the context of oncology were originally described as groups of three or more related symptoms. Some authors have suggested symptom clusters may have practical applications, such as the formulation of more effective therapeutic interventions that address the combined effects of symptoms rather than treating each symptom separately. Most studies that have sought to identify clusters in breast cancer survivors have relied on traditional research studies. Social media, such as online health-related forums, contain a bevy of user-generated content in the form of threads and posts, and could be used as a data source to identify and characterize symptom clusters among cancer patients. The present study seeks to determine patterns of symptom clusters in breast cancer survivors derived from both social media and research study data using improved K-Medoid clustering. A total of 50,426 publicly available messages were collected from Medhelp.com and 653 questionnaires were collected as part of a research study. The network of symptoms built from social media was sparse compared to that of the research study data, making the social media data easier to partition. The proposed revised K-Medoid clustering helps to improve the clustering performance by re-assigning some of the negative-ASW (average silhouette width) symptoms to other clusters after initial K-Medoid clustering. This retains an overall non-decreasing ASW and avoids the problem of trapping in local optima. The overall ASW, individual ASW, and improved interpretation of the final clustering solution suggest improvement. The clustering results suggest

Study of the {phi} meson in the pp{yields}K{sub 1}{sup 0}K{sub 2}{sup 0}{pi}{sup +}{pi}{sup -} K{sub 1}{sup 0}K{sub 2}{sup 0} annihilations at 700-750 MeV/c; Estudio del Meson {phi} en las aniquilaciones pp {yields}{phi}K{sub 1}{sup 0}K{sub 2}{sup 0}{pi}{sup +}{pi}{sup -} K{sub 1}{sup 0}K{sub 2}{sup 0} a 700-750 MeV/c de momento del haz

Energy Technology Data Exchange (ETDEWEB)

Gil Lopez, E

1976-07-01

We have measured the mass and width of the {phi} meson using the pp {yields}{pi}{sup +}{pi}{sup -} K{sub 1}{sup 0}K{sub 2}{sup 0} annihilations at 700-750 MeV/c. The values obtained are in good agreement with proceeding measurements. The mass has been measured with a high accuracy. (Author) 3 refs.

Prompt $K_{S}^{0}$ production in $pp$ collisions at $\\sqrt{s}$ = 0.9 TeV

CERN Document Server

Aaij, R; Adeva, B; Adinolfi, M; Adrover, C; Affolder, A; Agari, M; Ajaltouni, Z; Albrecht, J; Alessio, F; Alexander, M; Alfonsi, M; Alvarez Cartelle, P; Alves Jr, A.A; Amato, S; Amhis, Y; Amoraal, J; Anderson, J; Antunes Nobrega, R; Appleby, R; Aquines Gutierrez, O; Arefyev, A; Arrabito, L; Artuso, M; Aslanides, E; Auriemma, G; Bachmann, S; Bagaturia, Y; Bailey, D.S; Balagura, V; Baldini, W; Barber, G; Barham, C; Barlow, R.J; Barsuk, S; Basiladze, S; Bates, A; Bauer, C; Bauer, Th; Bay, A; Bediaga, I; Bellunato, T; Belous, K; Belyaev, I; Benayoun, M; Bencivenni, G; Bernet, R; Bernhard, R.P; Bettler, M-O; van Beuzekom, M; Bibby, J.H; Bifani, S; Bizzeti, A; Bjrnstad, P.M; Blake, T; Blanc, F; Blanks, C; Blouw, J; Blusk, S; Bobrov, A; Bocci, V; Bochin, B; Bonaccorsi, E; Bondar, A; Bondar, N; Bonivento, W; Borghi, S; Borgia, A; Bos, E; Bowcock, T.J.V; Bozzi, C; Brambach, T; van den Brand, J; Brarda, L; Bressieux, J; Brisbane, S; Britsch, M; Brook, N.H; Brown, H; Brusa, S; Buchler-Germann, A; Bursche, A; Buytaert, J; Cadeddu, S; Caicedo Carvajal, J.M; Callot, O; Calvi, M; Calvo Gomez, M; Camboni, A; Cameron, W; Camilleri, L; Campana, P; Carbone, A; Carboni, G; Cardinale, R; Cardini, A; Carroll, J; Carson, L; Carvalho Akiba, K; Casse, G; Cattaneo, M; Chadaj, B; Charles, M; Charpentier, Ph; Cheng, J; Chiapolini, N; Chlopik, A; Christiansen, J; Ciambrone, P; Cid Vidal, X; Clark, P.J; Clarke, P.E.L; Clemencic, M; Cliff, H.V; Closier, J; Coca, C; Coco, V; Cogan, J; Collins, P; Comerma-Montells, A; Constantin, F; Conti, G; Contu, A; Cooke, P; Coombes, M; Corajod, B; Corti, G; Cowan, G.A; Currie, R; DAlmagne, B; DAmbrosio, C; DAntone, I; Da Silva, W; Dane, E; David, P; De Bonis, I; De Capua, S; De Cian, M; De Lorenzi, F; De Miranda, J.M; De Paula, L; De Simone, P; Decamp, D; Decreuse, G; Degaudenzi, H; Deissenroth, M; Del Buono, L; Densham, C.J; Deplano, C; Deschamps, O; Dettori, F; Dickens, J; Dijkstra, H; Dima, M; Donleavy, S; Dornan, P; Dossett, D; Dovbnya, A; Dumps, R; Dupertuis, F; Dwyer, L; Dzhelyadin, R; Eames, C; Easo, S; Egede, U; Egorychev, V; Eidelman, S; van Eijk, D; Eisele, F; Eisenhardt, S; Eklund, L; d'Enterria, D; Esperante Pereira, D; Est`eve, L; Fanchini, E; Farber, C; Fardell, G; Farinelli, C; Farry, S; Fave, V; Felici, G; Fernandez Albor, V; Ferro-Luzzi, M; Filippov, S; Fitzpatrick, C; Flegel, W; Fontanelli, F; Forti, C; Forty, R; Fournier, C; Franek, B; Frank, M; Frei, C; Frosini, M; Fungueirino Pazos, J.L; Furcas, S; Gallas Torreira, A; Galli, D; Gandelman, M; Gandini, P; Gao, Y; Garnier, J-C; Garrido, L; Gascon, D; Gaspar, C; Gaspar De Valenzuela Cue, A; Gassner, J; Gauvin, N; Gavillet, P; Gersabeck, M; Gershon, T; Ghez, Ph; Gibson, V; Gilitsky, Yu; Gligorov, V.V; Gobel, C; Golubkov, D; Golutvin, A; Gomes, A; Gong, G; Gong, H; Gordon, H; Grabalosa Gandara, M; Gracco, V; Graciani Diaz, R; Granado Cardoso, L.A; Grauges, E; Graziani, G; Grecu, A; Gregson, S; Guerrer, G; Gui, B; Gushchin, E; Guz, Yu; Guzik, Z; Gys, T; Haefeli, G; Haines, S.C; Hampson, T; Hansmann-Menzemer, S; Harji, R; Harnew, N; Harrison, P.F; He, J; Hennessy, K; Henrard, P; Hernando Morata, J.A; van Herwijnen, E; Hicheur, A; Hicks, E; Hilke, H.J; Hofmann, W; Holubyev, K; Hopchev, P; Hulsbergen, W; Hunt, P; Huse, T; Huston, R.S; Hutchcroft, D; Iacoangeli, F; Iakovenko, V; Iglesias Escudero, C; Ilgner, C; Imong, J; Jacobsson, R; Jahjah Hussein, M; Jamet, O; Jans, E; Jansen, F; Jaton, P; Jean-Marie, B; John, M; Johnson, D; Jones, C.R; Jost, B; Kapusta, F; Karbach, T.M; Kashchuk, A; Katvars, S; Keaveney, J; Kerzel, U; Ketel, T; Keune, A; Khalil, S; Khanji, B; Kim, Y.M; Knecht, M; Koblitz, S; Konoplyannikov, A; Koppenburg, P; Korolev, M; Kozlinskiy, A; Kravchuk, L; Kristic, R; Krocker, G; Krokovny, P; Kruse, F; Kruzelecki, K; Kucharczyk, M; Kudryashov, I; Kukulak, S; Kumar, R; Kvaratskheliya, T; La Thi, V.N; Lacarrere, D; Lai, A; Lambert, R.W; Lanfranchi, G; Langenbruch, C; Latham, T; Le Gac, R; Lees, J-P; Lef`evre, R; Leflat, A; Lefrancois, J; Lehner, F; Lenzi, M; Leroy, O; Lesiak, T; Li, L; Li, Y.Y; Li Gioi, L; Libby, J; Lieng, M; Lindner, R; Lindsey, S; Linn, C; Liu, B; Liu, G; Lochner, S; Lopes, J.H; Lopez Asamar, E; Lopez-March, N; Loveridge, P; Luisier, J; Mcharek, B; Machefert, F; Machikhiliyan, I.V; Maciuc, F; Maev, O; Magnin, J; Maier, A; Malde, S; Mamunur, R.M.D; Manca, G; Mancinelli, G; Mangiafave, N; Marconi, U; Marki, R; Marks, J; Martellotti, G; Martens, A; Martin, L; Martinez Santos, D; Massaferri, A; Mathe, Z; Matteuzzi, C; Matveev, V; Maurice, E; Maynard, B; Mazurov, A; McGregor, G; McNulty, R; Mclean, C; Merk, M; Merkel, J; Merkin, M; Messi, R; Metlica, F.C.D; Miglioranzi, S; Minard, M-N; Moine, G; Monteil, S; Moran, D; Morant, J; Morris, J.V; Moscicki, J; Mountain, R; Mous, I; Muheim, F; Muresan, R; Murtas, F; Muryn, B; Musy, M; Mylroie-Smith, J; Naik, P; Nakada, T; Nandakumar, R; Nardulli, J; Nawrot, A; Nedos, M; Needham, M; Neufeld, N; Neustroev, P; Nicol, M; Nicolas, L; Nies, S; Niess, V; Nikitin, N; Noor, A; Oblakowska-Mucha, A; Obraztsov, V; Oggero, S; Okhrimenko, O; Oldeman, R; Orlandea, M; Ostankov, A; Palacios, J; Palutan, M; Panman, J; Papadelis, A; Papanestis, A; Pappagallo, M; Parkes, C; Parkinson, C.J; Passaleva, G; Patel, G.D; Patel, M; Paterson, S.K; Patrick, G.N; Patrignani, C; Pauna, E; Pauna (Chiojdeanu), C; Pavel (Nicorescu), C; Pazos Alvarez, A; Pellegrino, A; Penso, G; Pepe Altarelli, M; Perazzini, S; Perego, D.L; Perez Trigo, E; Perez-Calero Yzquierdo, A; Perret, P; Pessina, G; Petrella, A; Petrolini, A; Picatoste Olloqui, E; Pie Valls, B; Piedigrossi, D; Pietrzyk, B; Pinci, D; Playfer, S; Plo Casasus, M; Poli-Lener, M; Polok, G; Poluektov, A; Polycarpo, E; Popov, D; Popovici, B; Poss, S; Potterat, C; Powell, A; Pozzi, S; du Pree, T; Pugatch, V; Puig Navarro, A; Qian, W; Rademacker, J.H; Rakotomiaramanana, B; Raniuk, I; Raven, G; Redford, S; Reece, W; dos Reis, A.C; Ricciardi, S; Riera, J; Rinnert, K; Roa Romero, D.A; Robbe, P; Rodrigues, E; Rodrigues, F; Rodriguez Cobo, C; Rodriguez Perez, P; Rogers, G.J; Romanovsky, V; Rondan Sanabria, E; Rosello, M; Rospabe, G; Rouvinet, J; Roy, L; Ruf, T; Ruiz, H; Rummel, C; Rusinov, V; Sabatino, G; Saborido Silva, J.J; Sagidova, N; Sail, P; Saitta, B; Sakhelashvili, T; Salzmann, C; Sambade Varela, A; Sannino, M; Santacesaria, R; Santinelli, R; Santovetti, E; Sapunov, M; Sarti, A; Satriano, C; Satta, A; Savidge, T; Savrie, M; Savrina, D; Schaack, P; Schiller, M; Schleich, S; Schmelling, M; Schmidt, B; Schneider, O; Schneider, T; Schopper, A; Schune, M-H; Schwemmer, R; Sciubba, A; Seco, M; Semennikov, A; Senderowska, K; Serra, N; Serrano, J; Shao, B; Shapkin, M; Shapoval, I; Shatalov, P; Shcheglov, Y; Shears, T; Shekhtman, L; Shevchenko, V; Shires, A; Sigurdsson, S; Simioni, E; Skottowe, H.P; Skwarnicki, T; Smale, N; Smith, A; Smith, A.C; Smith, N.A; Sobczak, K; Soler, F.J.P; Solomin, A; Somogy, P; Soomro, F; Souza De Paula, B; Spaan, B; Sparkes, A; Spiridenkov, E; Spradlin, P; Srednicki, A; Stagni, F; Stahl, S; Steiner, S; Steinkamp, O; Stenyakin, O; Stoica, S; Stone, S; Storaci, B; Straumann, U; Styles, N; Szczekowski, M; Szczypka, P; Szumlak, T; TJampens, S; Tarkovskiy, E; Teodorescu, E; Terrier, H; Teubert, F; Thomas, C; Thomas, E; van Tilburg, J; Tisserand, V; Tobin, M; Topp-Joergensen, S; Tran, M.T; Traynor, S; Trunk, U; Tsaregorodtsev, A; Tuning, N; Ukleja, A; Ullaland, O; Uwer, U; Vagnoni, V; Valenti, G; Van Lysebetten, A; Vazquez Gomez, R; Vazquez Regueiro, P; Vecchi, S; Velthuis, J.J; Veltri, M; Vervink, K; Viaud, B; Videau, I; Vieira, D; Vilasis-Cardona, X; Visniakov, J; Vollhardt, A; Volyanskyy, D; Voong, D; Vorobyev, A; Vorobyev, An; Voss, H; Wacker, K; Wandernoth, S; Wang, J; Ward, D.R; Webber, A.D; Websdale, D; Whitehead, M; Wiedner, D; Wiggers, L; Wilkinson, G; Williams, M.P; Williams, M; Wilson, F.F; Wishahi, J; Witek, M; Witzeling, W; Woodward, M.L; Wotton, S.A; Wyllie, K; Xie, Y; Xing, F; Yang, Z; Ybeles Smit, G; Young, R; Yushchenko, O; Zeng, M; Zhang, L; Zhang, Y; Zhelezov, A; Zverev, E

2010-01-01

The production of K_short mesons in pp collisions at a centre-of-mass energy of 0.9 TeV is studied with the LHCb detector at the Large Hadron Collider. The luminosity of the analysed sample is determined using a novel technique, involving measurements of the beam currents, sizes and positions, and is found to be 6.8 +/- 1.0 microbarn^-1. The differential prompt K_short production cross-section is measured as a function of the K_short transverse momentum and rapidity in the region 0 < pT < 1.6 GeV/c and 2.5 < y < 4.0. The data are found to be in reasonable agreement with previous measurements and generator expectations.

Effects of Group Size and Lack of Sphericity on the Recovery of Clusters in K-Means Cluster Analysis

Science.gov (United States)

de Craen, Saskia; Commandeur, Jacques J. F.; Frank, Laurence E.; Heiser, Willem J.

2006-01-01

K-means cluster analysis is known for its tendency to produce spherical and equally sized clusters. To assess the magnitude of these effects, a simulation study was conducted, in which populations were created with varying departures from sphericity and group sizes. An analysis of the recovery of clusters in the samples taken from these…

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.

Differential Spatio-temporal Multiband Satellite Image Clustering using K-means Optimization With Reinforcement Programming

Directory of Open Access Journals (Sweden)

Irene Erlyn Wina Rachmawan

2015-06-01

Full Text Available Deforestration is one of the crucial issues in Indonesia because now Indonesia has world's highest deforestation rate. In other hand, multispectral image delivers a great source of data for studying spatial and temporal changeability of the environmental such as deforestration area. This research present differential image processing methods for detecting nature change of deforestration. Our differential image processing algorithms extract and indicating area automatically. The feature of our proposed idea produce extracted information from multiband satellite image and calculate the area of deforestration by years with calculating data using temporal dataset. Yet, multiband satellite image consists of big data size that were difficult to be handled for segmentation. Commonly, K- Means clustering is considered to be a powerfull clustering algorithm because of its ability to clustering big data. However K-Means has sensitivity of its first generated centroids, which could lead into a bad performance. In this paper we propose a new approach to optimize K-Means clustering using Reinforcement Programming in order to clustering multispectral image. We build a new mechanism for generating initial centroids by implementing exploration and exploitation knowledge from Reinforcement Programming. This optimization will lead a better result for K-means data cluster. We select multispectral image from Landsat 7 in past ten years in Medawai, Borneo, Indonesia, and apply two segmentation areas consist of deforestration land and forest field. We made series of experiments and compared the experimental results of K-means using Reinforcement Programming as optimizing initiate centroid and normal K-means without optimization process. Keywords: Deforestration, Multispectral images, landsat, automatic clustering, K-means.

Nuclear clustering and the electron screening puzzle

Science.gov (United States)

Bertulani, C. A.; Spitaleri, C.

2018-01-01

Electron screening changes appreciably the magnitude of astrophysical nuclear reactions within stars. This effect is also observed in laboratory experiments on Earth, where atomic electrons are present in the nuclear targets. Theoretical models were developed over the past 30 years and experimental measurements have been carried out to study electron screening in thermonuclear reactions. None of the theoretical models were able to explain the high values of the experimentally determined screening potentials. We explore the possibility that the "electron screening puzzle" is due to nuclear clusterization and polarization e_ects in the fusion reactions. We will discuss the supporting arguments for this scenario.

Group analyses of connectivity-based cortical parcellation using repeated k-means clustering.

Science.gov (United States)

Nanetti, Luca; Cerliani, Leonardo; Gazzola, Valeria; Renken, Remco; Keysers, Christian

2009-10-01

K-means clustering has become a popular tool for connectivity-based cortical segmentation using Diffusion Weighted Imaging (DWI) data. A sometimes ignored issue is, however, that the output of the algorithm depends on the initial placement of starting points, and that different sets of starting points therefore could lead to different solutions. In this study we explore this issue. We apply k-means clustering a thousand times to the same DWI dataset collected in 10 individuals to segment two brain regions: the SMA-preSMA on the medial wall, and the insula. At the level of single subjects, we found that in both brain regions, repeatedly applying k-means indeed often leads to a variety of rather different cortical based parcellations. By assessing the similarity and frequency of these different solutions, we show that approximately 256 k-means repetitions are needed to accurately estimate the distribution of possible solutions. Using nonparametric group statistics, we then propose a method to employ the variability of clustering solutions to assess the reliability with which certain voxels can be attributed to a particular cluster. In addition, we show that the proportion of voxels that can be attributed significantly to either cluster in the SMA and preSMA is relatively higher than in the insula and discuss how this difference may relate to differences in the anatomy of these regions.

Spin alignment and violation of the OZI rule in exclusive omega and phi production in pp collisions

Czech Academy of Sciences Publication Activity Database

Adolph, C.; Akhunzyanov, R.; Alekseev, M.; Alexeev, G. D.; Amoroso, A.; Andrieux, V.; Anosov, V. A.; Austregisilio, A.; Badelek, B.; Balestra, F.; Barth, J.; Baum, G.; Beck, R.; Bedfer, Y.; Berlin, A.; Bernhard, J.; Bicker, K.; Bieling, J.; Birsa, R.; Bisplinghoff, J.; Bodlak, M.; Boer, M.; Bordalo, P.; Bradamante, F.; Braun, C.; Bressan, A.; Büchele, M.; Burtin, E.; Capozza, L.; Chiosso, M.; Chung, S.U.; Cicuttin, A.; Crespo, M.; Curiel, Q.; Dalla Torre, S.; Dasgupta, S. S.; Dasgupta, S.; Denisov, O.; Donskov, S.; Doshita, N.; Duic, V.; Dünnweber, W.; Dziewiecki, M.; Efremov, A.V.; Elia, C.; Eversheim, P.; Eyrich, W.; Faessler, M.; Ferrero, A.; Filin, A.; Finger, M.; Finger jr., M.; Fischer, H.; Franco, C.; Fresne von Hohenesche, N.; Friedrich, J.; Frolov, V.; Gautheron, F.; Gavrichtchouk, O.; Gerassimov, S.; Geyer, R.; Gnesi, I.; Gobbo, B.; Goertz, S.; Gorzellik, M.; Grabmüller, S.; Grasso, A.; Grube, B.; Grussemmeyer, T.; Guskov, A.; Guthörl, T.; Haas, F.; von Harrach, D.; Hahne, D.; Hashimoto, R.; Heinsius, F.; Herrmann, F.; Hinterberger, F.; Höppner, Ch.; Horikawa, N.; d'Hose, N.; Huber, S.; Ishimoto, S.; Ivanov, A.; Ivanshin, Yu.; Iwata, T.; Jahn, R.; Jary, V.; Jasinski, P.; Joerg, P.; Joosten, R.; Kabuss, E.; Ketzer, B.; Khaustov, G.; Khokhlov, Y.; Kisselev, Y.; Klein, F.; Klimaszewski, K.; Koivuniemi, J.; Kolosov, V.; Kondo, K.; Königsmann, K.; Konorov, I.; Konstantinov, V.; Kotzinian, A.; Kouznetsov, O.; Král, Z.; Krämer, M.; Kroumchtein, Z.; Kuchinski, N.; Kunne, F.; Kurek, K.; Kurjata, R. P.; Lednev, A.; Lehmann, A.; Levillain, M.; Levorato, S.; Lichtenstadt, J.; Maggiora, A.; Magnon, A.; Makke, N.; Mallot, G.; Marchand, C.; Martin, A.; Marzec, J.; Matoušek, J.; Matsuda, H.; Matsuda, T.; Meshcheryakov, G.; Meyer, W.; Michigami, T.; Mikhailov, Y.; Miyachi, Y.; Nagaytsev, A.; Nagel, T.; Nerling, F.; Neubert, S.; Neyret, D.; Nový, J.; Nikolaenko, V.; Nowak, W. D.; Nunes, A.S.; Orlov, I.; Olshevsky, A.; Ostrick, M.; Panknin, R.; Panzieri, D.; Parsamyan, B.; Paul, S.; Pešek, M.; Platchkov, S.; Pochodzalla, J.; Polyakov, V.; Pretz, J.; Quaresma, M.; Quintans, C.; Ramos, S.; Regali, C.; Reicherz, G.; Rocco, E.; Rossiyskaya, N. S.; Ryabchikov, D.; Rychter, A.; Samoylenko, V.; Sandacz, A.; Sapozhnikov, M.; Sarkar, S.; Savin, I.; Sbrizzai, G.; Schiavon, P.; Schill, C.; Schlütter, T.; Schmidt, A.; Schmidt, K.; Schmiden, H.; Schönning, K.; Schopferer, S.; Schott, M.; Shevchenko, O.; Silva, L.; Sinha, L.; Sirtl, S.; Slunecka, M.; Sosio, S.; Sozzi, F.; Steiger, L.; Srnka, Aleš; Stolarski, M.; Sulc, M.; Suzuki, H.; Sulej, R.; Szabelski, A.; Szameitat, T.; Sznajder, P.; Takekawa, S.; Ter Wolbeek, J.; Tessaro, S.; Tessarotto, F.; Thibaud, F.; Uhl, S.; Uman, I.; Virius, M.; Wang, L.; Weisrock, T.; Wilfert, M.; Windmolders, R.; Wollny, H.; Zaremba, K.; Zavertyaev, M.; Zemlyanichkina, E.; Ziembicki, M.; Zink, A.

2014-01-01

Roč. 886, SEP 2014 (2014), s. 1078-1101 ISSN 0550-3213 R&D Projects: GA MŠk(CZ) LO1212 Keywords : OZI rule * vector meson * pp collision * liquid hydrogen target Subject RIV: BG - Nuclear, Atomic and Molecular Physics, Colliders Impact factor: 3.929, year: 2014

pK(+)Lambda final state: Towards the extraction of the ppK(-) contribution

Czech Academy of Sciences Publication Activity Database

Fabbietti, L.; Agakishiev, G.; Behnke, C.; Belver, D.; Belyaev, A.; Berger-Chen, J. C.; Blanco, A.; Blume, C.; Böhmer, M.; Cabanelas, P.; Chernenko, S.; Dritsa, C.; Dybczak, A.; Epple, E.; Krása, Antonín; Křížek, Filip; Kugler, Andrej; Sobolev, Yuri, G.; Tlustý, Pavel; Wagner, Vladimír

2013-01-01

Roč. 914, SEP (2013), s. 60-68 ISSN 0375-9474 R&D Projects: GA MŠk LC07050; GA AV ČR IAA100480803 Institutional support: RVO:61389005 Keywords : Lambda(1405) * kaonic bound state * meson-baryon interaction * partial wave analysis Subject RIV: BG - Nuclear, Atomic and Molecular Physics, Colliders Impact factor: 2.499, year: 2013 http://www. science direct.com/ science /article/pii/S0375947413004971

An improved K-means clustering algorithm in agricultural image segmentation

Science.gov (United States)

Cheng, Huifeng; Peng, Hui; Liu, Shanmei

Image segmentation is the first important step to image analysis and image processing. In this paper, according to color crops image characteristics, we firstly transform the color space of image from RGB to HIS, and then select proper initial clustering center and cluster number in application of mean-variance approach and rough set theory followed by clustering calculation in such a way as to automatically segment color component rapidly and extract target objects from background accurately, which provides a reliable basis for identification, analysis, follow-up calculation and process of crops images. Experimental results demonstrate that improved k-means clustering algorithm is able to reduce the computation amounts and enhance precision and accuracy of clustering.

U.K. nuclear data progress report

International Nuclear Information System (INIS)

Findlay, D.J.S.; Cookson, J.A.

1984-06-01

The report summarises nuclear data research in the United Kingdom between January and December 1984. The nuclear data presented includes contributions from government research laboratories and Universities, as well as from various collaborations. The section on nuclear data forum includes three individual papers (being processed separately), these are: the DIMPLE criticality experiments, the potential use of criticality benchmark experiments in nuclear data evaluation, and the use of benchmark experiments for the validation of nuclear data. (U.K.)

Big Data GPU-Driven Parallel Processing Spatial and Spatio-Temporal Clustering Algorithms

Science.gov (United States)

Konstantaras, Antonios; Skounakis, Emmanouil; Kilty, James-Alexander; Frantzeskakis, Theofanis; Maravelakis, Emmanuel

2016-04-01

Advances in graphics processing units' technology towards encompassing parallel architectures [1], comprised of thousands of cores and multiples of parallel threads, provide the foundation in terms of hardware for the rapid processing of various parallel applications regarding seismic big data analysis. Seismic data are normally stored as collections of vectors in massive matrices, growing rapidly in size as wider areas are covered, denser recording networks are being established and decades of data are being compiled together [2]. Yet, many processes regarding seismic data analysis are performed on each seismic event independently or as distinct tiles [3] of specific grouped seismic events within a much larger data set. Such processes, independent of one another can be performed in parallel narrowing down processing times drastically [1,3]. This research work presents the development and implementation of three parallel processing algorithms using Cuda C [4] for the investigation of potentially distinct seismic regions [5,6] present in the vicinity of the southern Hellenic seismic arc. The algorithms, programmed and executed in parallel comparatively, are the: fuzzy k-means clustering with expert knowledge [7] in assigning overall clusters' number; density-based clustering [8]; and a selves-developed spatio-temporal clustering algorithm encompassing expert [9] and empirical knowledge [10] for the specific area under investigation. Indexing terms: GPU parallel programming, Cuda C, heterogeneous processing, distinct seismic regions, parallel clustering algorithms, spatio-temporal clustering References [1] Kirk, D. and Hwu, W.: 'Programming massively parallel processors - A hands-on approach', 2nd Edition, Morgan Kaufman Publisher, 2013 [2] Konstantaras, A., Valianatos, F., Varley, M.R. and Makris, J.P.: 'Soft-Computing Modelling of Seismicity in the Southern Hellenic Arc', Geoscience and Remote Sensing Letters, vol. 5 (3), pp. 323-327, 2008 [3] Papadakis, S. and

The general mechanisms of Cu cluster formation in the processes of ...

Indian Academy of Sciences (India)

Sci., Vol. 38, No. 3, June 2015, pp. 701–706. c Indian Academy of Sciences. ... This work represents the basic mechanisms of cluster formation from the gas phase that has been ... required, or in catalytic reactions, where the main factor of effectiveness is the .... ature of liquid nitrogen (77 K), which is used in real exper-.

The effect of mining data k-means clustering toward students profile model drop out potential

Science.gov (United States)

Purba, Windania; Tamba, Saut; Saragih, Jepronel

2018-04-01

The high of student success and the low of student failure can reflect the quality of a college. One of the factors of fail students was drop out. To solve the problem, so mining data with K-means Clustering was applied. K-Means Clustering method would be implemented to clustering the drop out students potentially. Firstly the the result data would be clustering to get the information of all students condition. Based on the model taken was found that students who potentially drop out because of the unexciting students in learning, unsupported parents, diffident students and less of students behavior time. The result of process of K-Means Clustering could known that students who more potentially drop out were in Cluster 1 caused Credit Total System, Quality Total, and the lowest Grade Point Average (GPA) compared between cluster 2 and 3.

Non-extensive statistical aspects of clustering and nuclear multi-fragmentation

International Nuclear Information System (INIS)

Calboreanu, A.

2002-01-01

Recent developments concerning an application of the non-extensive Tsalis statistics to describe clustering phenomena is briefly presented. Cluster formation is a common feature of a large number of physical phenomena encountered in molecular and nuclear physics, astrophysics, condensed matter and biophysics. Common to all these is the large number of degrees of freedom, thus justifying a statistical approach. However the conventional statistical mechanics paradigm seems to fail in dealing with clustering. Whether this is due to the prevalence of complex dynamical constrains, or it is a manifestation of new statistics is a subject of considerable interest, which was intensively debated during the last few years. Tsalis conjecture has proved extremely appealing due to its rather elegant and transparent basic arguments. We present here evidence for its adequacy for the study of a large class of physical phenomena related to cluster formation. An application to nuclear multi-fragmentation is presented. (author)

Microscopic description of the nuclear-cluster theory

International Nuclear Information System (INIS)

Tang, Y.C.

1980-01-01

The purpose of this series of lectures is to explain the foundation of, the techniques used in, and the results obtained by microscopic cluster theory (MCT). In particular, the important role played by the Pauli principle in determining nuclear characteristics will be extensively discussed

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.

Nuclear and nucleolar localization signals and their targeting function in phosphatidylinositol 4-kinase PI4K230

International Nuclear Information System (INIS)

Kakuk, Annamaria; Friedlaender, Elza; Vereb, Gyoergy; Lisboa, Duarte; Bagossi, Peter; Toth, Gabor; Gergely, Pal; Vereb, Gyoergy

2008-01-01

PI4K230, an isoform of phosphatidylinositol 4-kinase, known primarily as a cytoplasmic membrane-bound enzyme, was detected recently also in the nucleolus of several cells. Here we provide mechanistic insight on the targeting function of its putative nuclear localization signal (NLS) sequences using molecular modeling, digitonin-permeabilized HeLa cells and binding to various importins. The synthetic sequence 916 NFNHIHKRIRRVADKYLSG 934 comprising a putative monopartite NLS (NLS1), targeted covalently bound fluorescent BSA to the nucleoplasm via classical importin α/β mechanism employing importins α1 and α3 but not α5. This transport was inhibited by wheat germ agglutinin and GTPγS. The sequence 1414 SKKTNRGSQLHKYYMKRRTL 1433 , a putative bipartite NLS (NLS2) proved ineffective in nuclear targeting if conjugated to fluorescently labeled BSA. Nonetheless, NLS2 or either of its basic clusters directed to the nucleolus soybean trypsin inhibitor that can pass the nuclear pore complex passively; moreover, an expressed 58 kDa fragment of PI4K230 (AA1166-1667) comprising NLS2 was also imported into the nucleus by import factors of reticulocyte lysate or by importin α1/β or α3/β complexes and localized to the nucleolus. We conclude that the putative bipartite NLS itself is a nucleolar targeting signal, and for nuclear import PI4K230 requires a larger sequence around it or, alternatively, the monopartite NLS

UPDATED MASS SCALING RELATIONS FOR NUCLEAR STAR CLUSTERS AND A COMPARISON TO SUPERMASSIVE BLACK HOLES

International Nuclear Information System (INIS)

Scott, Nicholas; Graham, Alister W.

2013-01-01

We investigate whether or not nuclear star clusters and supermassive black holes (SMBHs) follow a common set of mass scaling relations with their host galaxy's properties, and hence can be considered to form a single class of central massive object (CMO). We have compiled a large sample of galaxies with measured nuclear star cluster masses and host galaxy properties from the literature and fit log-linear scaling relations. We find that nuclear star cluster mass, M NC , correlates most tightly with the host galaxy's velocity dispersion: log M NC = (2.11 ± 0.31)log (σ/54) + (6.63 ± 0.09), but has a slope dramatically shallower than the relation defined by SMBHs. We find that the nuclear star cluster mass relations involving host galaxy (and spheroid) luminosity and stellar and dynamical mass, intercept with but are in general shallower than the corresponding black hole scaling relations. In particular, M NC ∝M 0.55±0.15 Gal,dyn ; the nuclear cluster mass is not a constant fraction of its host galaxy or spheroid mass. We conclude that nuclear stellar clusters and SMBHs do not form a single family of CMOs.

Investigation of clustering effects in the reaction pp→ppπ+π+π-π- at 19 GeV/c

International Nuclear Information System (INIS)

Allan, J.; Blomqvist, G.

1975-07-01

Possible production of high multiplicity clusters of secondaries in the reaction pp→ppπ + π + π - π - at 19 GeV/c is investigated. The experimental distribution of dispersion versus mean for the pion rapidities shows, compared to simple one component models, an excess of events in the regions where a single diffraction dissociation process is expected to populate. A method based on the Cramer van Mises statistical test combined with an operational method for selection of quasi two body reactions is used for investigation of clustering effects in phase space caused by different reaction mechanisms. The analysis indicates that the distribution of experimental events in phase space has mainly two population centers, one consisting of events with the kinematical configuration expected from a single diffraction dissociation process. (Auth.)

Efficient privacy preserving K-means clustering in a three-party setting

NARCIS (Netherlands)

Beye, Michael; Erkin, Zekeriya; Erkin, Zekeriya; Lagendijk, Reginald L.

2011-01-01

User clustering is a common operation in online social networks, for example to recommend new friends. In previous work [5], Erkin et al. proposed a privacy-preserving K-means clustering algorithm for the semi-honest model, using homomorphic encryption and multi-party computation. This paper makes

Three-channel K-matrix analysis of dibaryons in JP = 2± and 3- states

International Nuclear Information System (INIS)

Hiroshige, Noboru

1986-01-01

We have investigated the dibaryon resonances with the quamtum numbers J P = 2 + , 2 - and 3 - in terms of a three-channel K-matrix method using the pp-pp, pp-πd and πd-πd amplitudes obtained by the partial-wave analysis as the input data. We have found many good solutions in each case and all of the solutions have a nearby pole in the lower-half complex energy plane. The obtained resonance masses cluster in the region 2.15 - 2.16 GeV. A remarkable finding of our three-channel analysis is that the dibaryon resonances have very weak coupling to the pp channel. To get more difinite conclusion we need the pp-NΔ and πd-NΔ amplitude as well as a better πd-πd one. (author)

Towards enhancement of performance of K-means clustering using nature-inspired optimization algorithms.

Science.gov (United States)

Fong, Simon; Deb, Suash; Yang, Xin-She; Zhuang, Yan

2014-01-01

Traditional K-means clustering algorithms have the drawback of getting stuck at local optima that depend on the random values of initial centroids. Optimization algorithms have their advantages in guiding iterative computation to search for global optima while avoiding local optima. The algorithms help speed up the clustering process by converging into a global optimum early with multiple search agents in action. Inspired by nature, some contemporary optimization algorithms which include Ant, Bat, Cuckoo, Firefly, and Wolf search algorithms mimic the swarming behavior allowing them to cooperatively steer towards an optimal objective within a reasonable time. It is known that these so-called nature-inspired optimization algorithms have their own characteristics as well as pros and cons in different applications. When these algorithms are combined with K-means clustering mechanism for the sake of enhancing its clustering quality by avoiding local optima and finding global optima, the new hybrids are anticipated to produce unprecedented performance. In this paper, we report the results of our evaluation experiments on the integration of nature-inspired optimization methods into K-means algorithms. In addition to the standard evaluation metrics in evaluating clustering quality, the extended K-means algorithms that are empowered by nature-inspired optimization methods are applied on image segmentation as a case study of application scenario.

NUCORE - A system for nuclear structure calculations with cluster-core models

International Nuclear Information System (INIS)

Heras, C.A.; Abecasis, S.M.

1982-01-01

Calculation of nuclear energy levels and their electromagnetic properties, modelling the nucleus as a cluster of a few particles and/or holes interacting with a core which in turn is modelled as a quadrupole vibrator (cluster-phonon model). The members of the cluster interact via quadrupole-quadrupole and pairing forces. (orig.)

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

Science.gov (United States)

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

2017-10-30

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

Displacement affinity chromatography of protein phosphatase one (PP1 complexes

Directory of Open Access Journals (Sweden)

Gourlay Robert

2008-11-01

Full Text Available Abstract Background Protein phosphatase one (PP1 is a ubiquitously expressed, highly conserved protein phosphatase that dephosphorylates target protein serine and threonine residues. PP1 is localized to its site of action by interacting with targeting or regulatory proteins, a majority of which contains a primary docking site referred to as the RVXF/W motif. Results We demonstrate that a peptide based on the RVXF/W motif can effectively displace PP1 bound proteins from PP1 retained on the phosphatase affinity matrix microcystin-Sepharose. Subsequent co-immunoprecipitation experiments confirmed that each identified binding protein was either a direct PP1 interactor or was in a complex that contains PP1. Our results have linked PP1 to numerous new nuclear functions and proteins, including Ki-67, Rif-1, topoisomerase IIα, several nuclear helicases, NUP153 and the TRRAP complex. Conclusion This modification of the microcystin-Sepharose technique offers an effective means of purifying novel PP1 regulatory subunits and associated proteins and provides a simple method to uncover a link between PP1 and additional cellular processes.

Optimization Approach for Multi-scale Segmentation of Remotely Sensed Imagery under k-means Clustering Guidance

Directory of Open Access Journals (Sweden)

WANG Huixian

2015-05-01

Full Text Available In order to adapt different scale land cover segmentation, an optimized approach under the guidance of k-means clustering for multi-scale segmentation is proposed. At first, small scale segmentation and k-means clustering are used to process the original images; then the result of k-means clustering is used to guide objects merging procedure, in which Otsu threshold method is used to automatically select the impact factor of k-means clustering; finally we obtain the segmentation results which are applicable to different scale objects. FNEA method is taken for an example and segmentation experiments are done using a simulated image and a real remote sensing image from GeoEye-1 satellite, qualitative and quantitative evaluation demonstrates that the proposed method can obtain high quality segmentation results.

Towards Enhancement of Performance of K-Means Clustering Using Nature-Inspired Optimization Algorithms

Directory of Open Access Journals (Sweden)

Simon Fong

2014-01-01

Full Text Available Traditional K-means clustering algorithms have the drawback of getting stuck at local optima that depend on the random values of initial centroids. Optimization algorithms have their advantages in guiding iterative computation to search for global optima while avoiding local optima. The algorithms help speed up the clustering process by converging into a global optimum early with multiple search agents in action. Inspired by nature, some contemporary optimization algorithms which include Ant, Bat, Cuckoo, Firefly, and Wolf search algorithms mimic the swarming behavior allowing them to cooperatively steer towards an optimal objective within a reasonable time. It is known that these so-called nature-inspired optimization algorithms have their own characteristics as well as pros and cons in different applications. When these algorithms are combined with K-means clustering mechanism for the sake of enhancing its clustering quality by avoiding local optima and finding global optima, the new hybrids are anticipated to produce unprecedented performance. In this paper, we report the results of our evaluation experiments on the integration of nature-inspired optimization methods into K-means algorithms. In addition to the standard evaluation metrics in evaluating clustering quality, the extended K-means algorithms that are empowered by nature-inspired optimization methods are applied on image segmentation as a case study of application scenario.

Towards Enhancement of Performance of K-Means Clustering Using Nature-Inspired Optimization Algorithms

Science.gov (United States)

Deb, Suash; Yang, Xin-She

2014-01-01

Traditional K-means clustering algorithms have the drawback of getting stuck at local optima that depend on the random values of initial centroids. Optimization algorithms have their advantages in guiding iterative computation to search for global optima while avoiding local optima. The algorithms help speed up the clustering process by converging into a global optimum early with multiple search agents in action. Inspired by nature, some contemporary optimization algorithms which include Ant, Bat, Cuckoo, Firefly, and Wolf search algorithms mimic the swarming behavior allowing them to cooperatively steer towards an optimal objective within a reasonable time. It is known that these so-called nature-inspired optimization algorithms have their own characteristics as well as pros and cons in different applications. When these algorithms are combined with K-means clustering mechanism for the sake of enhancing its clustering quality by avoiding local optima and finding global optima, the new hybrids are anticipated to produce unprecedented performance. In this paper, we report the results of our evaluation experiments on the integration of nature-inspired optimization methods into K-means algorithms. In addition to the standard evaluation metrics in evaluating clustering quality, the extended K-means algorithms that are empowered by nature-inspired optimization methods are applied on image segmentation as a case study of application scenario. PMID:25202730

Cluster mislocation in kinematic Sunyaev-Zel'dovich (kSZ) effect extraction

Science.gov (United States)

Calafut, Victoria Rose; Bean, Rachel; Yu, Byeonghee

2018-01-01

We investigate the impact of a variety of analysis assumptions that influence cluster identification and location on the kSZ pairwise momentum signal and covariance estimation. Photometric and spectroscopic galaxy tracers from SDSS, WISE, and DECaLs, spanning redshifts 0.05zgeneration of CMB and LSS surveys the statistical and photometric errors will shrink markedly. Our results demonstrate that uncertainties introduced through using galaxy proxies for cluster locations will need to be fully incorporated, and actively mitigated, for the kSZ to reach its full potential as a cosmological constraining tool for dark energy and neutrino physics.

Ckmeans.1d.dp: Optimal k-means Clustering in One Dimension by Dynamic Programming.

Science.gov (United States)

Wang, Haizhou; Song, Mingzhou

2011-12-01

The heuristic k -means algorithm, widely used for cluster analysis, does not guarantee optimality. We developed a dynamic programming algorithm for optimal one-dimensional clustering. The algorithm is implemented as an R package called Ckmeans.1d.dp . We demonstrate its advantage in optimality and runtime over the standard iterative k -means algorithm.

K-Means Clustering for Problems with Periodic Attributes

Czech Academy of Sciences Publication Activity Database

Vejmelka, Martin; Musílek, P.; Paluš, Milan; Pelikán, Emil

2009-01-01

Roč. 23, č. 4 (2009), s. 721-743 ISSN 0218-0014 R&D Projects: GA AV ČR 1ET400300513 EU Projects: European Commission(XE) 517133 - BRACCIA Institutional research plan: CEZ:AV0Z10300504 Keywords : clustering algorithms * similarity measures * K- means * periodic attributes Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.512, year: 2009

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.

A hybrid sequential approach for data clustering using K-Means and ...

African Journals Online (AJOL)

Experiments on four kinds of data sets have been conducted. The obtained results are compared with K-Means, PSO, Hybrid, K-Means+Genetic Algorithm and it has been found that the proposed algorithm generates more accurate, robust and better clustering results. International Journal of Engineering, Science and ...

On the Equivalence of Nonnegative Matrix Factorization and K-means- Spectral Clustering

Energy Technology Data Exchange (ETDEWEB)

Ding, Chris; He, Xiaofeng; Simon, Horst D.; Jin, Rong

2005-12-04

We provide a systematic analysis of nonnegative matrix factorization (NMF) relating to data clustering. We generalize the usual X = FG{sup T} decomposition to the symmetric W = HH{sup T} and W = HSH{sup T} decompositions. We show that (1) W = HH{sup T} is equivalent to Kernel K-means clustering and the Laplacian-based spectral clustering. (2) X = FG{sup T} is equivalent to simultaneous clustering of rows and columns of a bipartite graph. We emphasizes the importance of orthogonality in NMF and soft clustering nature of NMF. These results are verified with experiments on face images and newsgroups.

Connections between Star Cluster Populations and Their Host Galaxy Nuclear Rings

Science.gov (United States)

Ma, Chao; de Grijs, Richard; Ho, Luis C.

2018-04-01

Nuclear rings are excellent laboratories for probing diverse phenomena such as the formation and evolution of young massive star clusters and nuclear starbursts, as well as the secular evolution and dynamics of their host galaxies. We have compiled a sample of 17 galaxies with nuclear rings, which are well resolved by high-resolution Hubble and Spitzer Space Telescope imaging. For each nuclear ring, we identified the ring star cluster population, along with their physical properties (ages, masses, and extinction values). We also determined the integrated ring properties, including the average age, total stellar mass, and current star formation rate (SFR). We find that Sb-type galaxies tend to have the highest ring stellar mass fraction with respect to the host galaxy, and this parameter is correlated with the ring’s SFR surface density. The ring SFRs are correlated with their stellar masses, which is reminiscent of the main sequence of star-forming galaxies. There are striking correlations between star-forming properties (i.e., SFR and SFR surface density) and nonaxisymmetric bar parameters, appearing to confirm previous inferences that strongly barred galaxies tend to have lower ring SFRs, although the ring star formation histories turn out to be significantly more complicated. Nuclear rings with higher stellar masses tend to be associated with lower cluster mass fractions, but there is no such relation for the ages of the rings. The two youngest nuclear rings in our sample, NGC 1512 and NGC 4314, which have the most extreme physical properties, represent the young extremity of the nuclear ring age distribution.

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.

Radiation Improved Mechanical and Thermal Property of PP/HDPE

International Nuclear Information System (INIS)

Chaisupaditsin, M.; Thammit, C.; Techakiatkul, C.

1998-01-01

The mechanical properties, thermal properties and gel contents of PP-irradiated HDPE blends were studied. HDPE was gamma irradiated in the dose range of 10-30 kGy. The ratios of polymer blends of 30PP:70HDPE was mixed by a twin screw extruder at speed of 50 rpm. Irradiated HDPE with 30 kGy showed the highest gel contents. The blends ratio of 30PP:70HDPE (30 kGy) shows better heat resistance than the blends with non-irradiated HDPE. With increasing the radiation doses, the mechanical properties of the blends were improved

Reducing Earth Topography Resolution for SMAP Mission Ground Tracks Using K-Means Clustering

Science.gov (United States)

Rizvi, Farheen

2013-01-01

The K-means clustering algorithm is used to reduce Earth topography resolution for the SMAP mission ground tracks. As SMAP propagates in orbit, knowledge of the radar antenna footprints on Earth is required for the antenna misalignment calibration. Each antenna footprint contains a latitude and longitude location pair on the Earth surface. There are 400 pairs in one data set for the calibration model. It is computationally expensive to calculate corresponding Earth elevation for these data pairs. Thus, the antenna footprint resolution is reduced. Similar topographical data pairs are grouped together with the K-means clustering algorithm. The resolution is reduced to the mean of each topographical cluster called the cluster centroid. The corresponding Earth elevation for each cluster centroid is assigned to the entire group. Results show that 400 data points are reduced to 60 while still maintaining algorithm performance and computational efficiency. In this work, sensitivity analysis is also performed to show a trade-off between algorithm performance versus computational efficiency as the number of cluster centroids and algorithm iterations are increased.

Glutamic acid promotes monacolin K production and monacolin K biosynthetic gene cluster expression in Monascus.

Science.gov (United States)

Zhang, Chan; Liang, Jian; Yang, Le; Chai, Shiyuan; Zhang, Chenxi; Sun, Baoguo; Wang, Chengtao

2017-12-01

This study investigated the effects of glutamic acid on production of monacolin K and expression of the monacolin K biosynthetic gene cluster. When Monascus M1 was grown in glutamic medium instead of in the original medium, monacolin K production increased from 48.4 to 215.4 mg l -1 , monacolin K production increased by 3.5 times. Glutamic acid enhanced monacolin K production by upregulating the expression of mokB-mokI; on day 8, the expression level of mokA tended to decrease by Reverse Transcription-polymerase Chain Reaction. Our findings demonstrated that mokA was not a key gene responsible for the quantity of monacolin K production in the presence of glutamic acid. Observation of Monascus mycelium morphology using Scanning Electron Microscope showed glutamic acid significantly increased the content of Monascus mycelium, altered the permeability of Monascus mycelium, enhanced secretion of monacolin K from the cell, and reduced the monacolin K content in Monascus mycelium, thereby enhancing monacolin K production.

Carolinas' Nuclear Cluster: building competency through collaboration

Energy Technology Data Exchange (ETDEWEB)

Little, J. [Carolinas' Nuclear Cluster (United States)

2013-07-01

This presentation discusses the Carolinas Nuclear Cluster that was built with collaboration amongst interested parties. The challenge facing the participants were availability of qualified & experienced workforce; retiring expertise; competition for resources within nuclear and other technology sectors; competition for skills and leadership; competing priorities in a changing environment such as slow growth in new nuclear in the U.S.; speedup in existing plant upgrades & retrofits and international project development. The established principles were collaboration amongst players, no competition, no borders, business driven focus on job creation, think as a global business, be willing to invest actively with money, talent, time and focus on results and not activities.

Carolinas' Nuclear Cluster: building competency through collaboration

International Nuclear Information System (INIS)

Little, J.

2013-01-01

This presentation discusses the Carolinas Nuclear Cluster that was built with collaboration amongst interested parties. The challenge facing the participants were availability of qualified & experienced workforce; retiring expertise; competition for resources within nuclear and other technology sectors; competition for skills and leadership; competing priorities in a changing environment such as slow growth in new nuclear in the U.S.; speedup in existing plant upgrades & retrofits and international project development. The established principles were collaboration amongst players, no competition, no borders, business driven focus on job creation, think as a global business, be willing to invest actively with money, talent, time and focus on results and not activities.

PRAMANA Cluster radioactivity in xenon isotopes

Indian Academy of Sciences (India)

exotic decay or cluster radioactivity was first predicted by sandulescu et al [1] in. 1980 on the basis of ... separator by 58Ni(58Ni, 2n) reaction and carbon clusters were searched for by means of solid state nuclear ..... Lett. 55, 582 (1985). [22] D N Poenaru, W Greiner, K Depta, M Ivascu, D Mazilu and A Sandulescu, At. Data.

K-ray nuclear densitometer at PETRONAS Carigali

International Nuclear Information System (INIS)

Zainudin Othman

1985-01-01

The hydrology and tracer studies Group of Nuclear Energy Unit was requested to overcome the calibration problems of nuclear density gauges which was installed at the condensate - natural gas pipeline at the PETRONAS Carigali in Kerteh, Trengganu in February 1984. The roles and application of k-ray nuclear densitometer are included. Similar activities have also been performed by the Unit to promote the application at nuclear techniques in local industries. (A.J.)

ONKALO POSE experiment. Determination of in situ thermal properties of rocks in drillholes ONK-PP340, ONK-PP346, ONK-PP398, ONK-PP399, ONK-PP405, ONK-PP411

International Nuclear Information System (INIS)

Korpisalo, A.; Suppala, I.; Kukkonen, I.; Koskinen, T.

2014-12-01

The thermal drillhole device TERO76 (for diameter 76 mm drillholes) used in this study for determining thermal properties of rocks in situ was developed at the Geological Survey of Finland for Posiva in the early 2000's. The measurement method is based on monitoring the temperature variation of a cylindrical heating source in a drillhole. The measured data can be interpreted with full numerical 3D codes as well as with an analytical infinite line source method, a 'rapid interpretation tool', which makes it possible to calculate the first estimates of thermal properties already in the field. Both methods were applied in this study. Because of the unique measurement geometry, only the thermal conductivities can accurately be estimated using the late times of heating periods (accuracy ± 2%). The cylindrical source method cannot directly give the thermal diffusivity or volumetric heat capacity at a sufficient accuracy. Thermal diffusivities are estimated by using the average specific heat capacities and densities of the rock type at the measurement point, or the laboratory results on the general diffusivity-conductivity relationship for different Olkiluoto rock types. The latter technique was applied in this study. Thermal properties were determined in four shallow drillholes (ONK-PP398, ONK-PP399, ONK-PP405, ONK-PP411) located in the ONKALO investigation niche 3 (ONK-TKU-3620) at the access tunnel chainage of 3620 m. The measurement positions (17) were strictly selected on the grounds that approximately an equal number of in situ results would be available in both veined gneiss (VGN) and pegmatitic granite (PGR). The results from the drillholes ONK-PP340 and ONK-PP346 measured in a previous project are also presented in this report. In veined gneiss, the average conductivity determined with numerical model of the present measurements is 3.49 (2.83) Wm -1 K -1 and diffusivity 1.89 x 10 -6 (1.3 10 -6 ) m 2 s -1 . The laboratory values of Olkiluoto rocks

ALICE distributed analysis of the K*(892)0 signal in pp events with the AliEn package

International Nuclear Information System (INIS)

Badala, A.; Barbera, R.; Lo Re, G.; Palmeri, A.; Pappalardo, G.S.; Pulvirenti, A.; Riggi, F.

2004-01-01

A simulation study concerning the K*(892)0 resonance was carried out within the ALICE Collaboration, in order to evaluate the capability of the detector in the reconstruction of this signal in pp collisions at the Large Hadron Collider (LHC) energy. A description of the analysis procedure which makes use of AliEn, the ALICE package for distributed computing, is given together with the obtained results

ALICE distributed analysis of the $K^{*}(892)^{0}$ signal in pp events with the AliEn package

CERN Document Server

Badalà, A; Palmeri, A; Pappalardo, G S; Pulvirenti, A; Lo Re, G; Riggi, F

2004-01-01

A simulation study concerning the K*(892)**0 resonance was carried out within the ALICE Collaboration, in order to evaluate the capability of the detector in the reconstruction of this signal in pp collisions at the Large Hadron Collider (LHC) energy. A description of the analysis procedure which makes use of AliEn, the ALICE package for distributed computing, is given together with the obtained results.

Study on GIF PR/PP evaluation methodology

Energy Technology Data Exchange (ETDEWEB)

Lee, B. H.; Kwon, E. H.; Kim, H. D. [KAERI, Daejeon (Korea, Republic of)

2012-10-15

Proliferation resistance (PR) and physical protection (PP) is one of the four technology goals of generation IV nuclear energy systems (NESs). The PR component of the goal focuses on providing strong assurance that generation IV NESs are the least desirable sources for the diversion or undeclared production of nuclear materials, whereas the PP portion of the goal ensures that generation IV NESs are robust against theft and sabotage. In 2002, the road map of the Generation IV International Forum (GIF) envisioned that the R and D program for PR and PP would have three areas: 1) safeguards and physical protection technology R and D for each GIF system; 2) formulation of PR and PP criteria and metrics; and 3) evaluation of the criteria and metrics. To cover these R and D items, the PR and PP Working Group (PRPPWG) was formed in late 2002 and has since developed a methodology for PR and PP evaluation. In a succession of revisions beginning in 2004, consensus was achieved amongst all participating GIF countries and related organizations (i.e., IAEA and EU), and Revision 6 of the methodology report was approved by GIF for open distribution in 2011. The paper describes in detail the methodology developed by the PRPPWG and discusses its applicability to the sodium-cooled fast reactor (SFR) fuel cycle with pyro processing currently under development in Korea.

Phenotype Clustering of Breast Epithelial Cells in Confocal Imagesbased on Nuclear Protein Distribution Analysis

Energy Technology Data Exchange (ETDEWEB)

Long, Fuhui; Peng, Hanchuan; Sudar, Damir; Levievre, Sophie A.; Knowles, David W.

2006-09-05

Background: The distribution of the chromatin-associatedproteins plays a key role in directing nuclear function. Previously, wedeveloped an image-based method to quantify the nuclear distributions ofproteins and showed that these distributions depended on the phenotype ofhuman mammary epithelial cells. Here we describe a method that creates ahierarchical tree of the given cell phenotypes and calculates thestatistical significance between them, based on the clustering analysisof nuclear protein distributions. Results: Nuclear distributions ofnuclear mitotic apparatus protein were previously obtained fornon-neoplastic S1 and malignant T4-2 human mammary epithelial cellscultured for up to 12 days. Cell phenotype was defined as S1 or T4-2 andthe number of days in cultured. A probabilistic ensemble approach wasused to define a set of consensus clusters from the results of multipletraditional cluster analysis techniques applied to the nucleardistribution data. Cluster histograms were constructed to show how cellsin any one phenotype were distributed across the consensus clusters.Grouping various phenotypes allowed us to build phenotype trees andcalculate the statistical difference between each group. The resultsshowed that non-neoplastic S1 cells could be distinguished from malignantT4-2 cells with 94.19 percent accuracy; that proliferating S1 cells couldbe distinguished from differentiated S1 cells with 92.86 percentaccuracy; and showed no significant difference between the variousphenotypes of T4-2 cells corresponding to increasing tumor sizes.Conclusion: This work presents a cluster analysis method that canidentify significant cell phenotypes, based on the nuclear distributionof specific proteins, with high accuracy.

Perceived risk and benefit of nuclear waste repositories: four opinion clusters.

Science.gov (United States)

Seidl, Roman; Moser, Corinne; Stauffacher, Michael; Krütli, Pius

2013-06-01

Local public resistance can block the site-selection process, construction, and operation of nuclear waste repositories. Social science has established that the perception of risks and benefits, trust in authorities, and opinion on nuclear energy play important roles in acceptance. In particular, risk and benefit evaluations seem critical for opinion formation. However, risks and benefits have rarely been studied independently and, most often, the focus has been on the two most salient groups of proponents and opponents. The aim of this exploratory study is to examine the often-neglected majority of people holding ambivalent or indifferent opinions. We used cluster analysis to examine the sample (N = 500, mailed survey in German-speaking Switzerland) in terms of patterns of risk and benefit perception. We reveal four significantly different and plausible clusters: one cluster with high-benefit ratings in favor of a repository and one cluster with high-risk ratings opposing it; a third cluster shows ambivalence, with high ratings on both risk and benefit scales and moderate opposition, whereas a fourth cluster seems indifferent, rating risks and benefits only moderately compared to the ambivalent cluster. We conclude that a closer look at the often neglected but considerable number of people with ambivalent or indifferent opinions is necessary. Although the extreme factions of the public will most probably not change their opinion, we do not yet know how the opinion of the ambivalent and indifferent clusters might develop over time. © 2012 Society for Risk Analysis.

Comparative Performance Of Using PCA With K-Means And Fuzzy C Means Clustering For Customer Segmentation

Directory of Open Access Journals (Sweden)

Fahmida Afrin

2015-08-01

Full Text Available Abstract Data mining is the process of analyzing data and discovering useful information. Sometimes it is called knowledge Discovery. Clustering refers to groups whereas data are grouped in such a way that the data in one cluster are similar data in different clusters are dissimilar. Many data mining technologies are developed for customer segmentation. PCA is working as a preprocessor of Fuzzy C means and K- means for reducing the high dimensional and noisy data. There are many clustering method apply on customer segmentation. In this paper the performance of Fuzzy C means and K-means after implementing Principal Component Analysis is analyzed. We analyze the performance on a standard dataset for these algorithms. The results indicate that PCA based fuzzy clustering produces better results than PCA based K-means and is a more stable method for customer segmentation.

G K Ananthasuresh

Indian Academy of Sciences (India)

G K Ananthasuresh · More Details Fulltext PDF. Volume 17 Issue 4 April 2012 pp 317-318 Editorial. Editorial · G K Ananthasuresh · More Details Fulltext PDF. Volume 20 Issue 2 February 2015 pp 98-122 General Article. Buckminster Fuller and his Fabulous Designs · G K Ananthasuresh · More Details Fulltext PDF ...

Comparison of forward and backward pp pair knockout in 3He(e,e'pp)n

Science.gov (United States)

Baghdasaryan, H.; Weinstein, L. B.; Laget, J. M.; Adhikari, K. P.; Aghasyan, M.; Amaryan, M. J.; Anghinolfi, M.; Ball, J.; Battaglieri, M.; Biselli, A. S.; Briscoe, W. J.; Brooks, W. K.; Burkert, V. D.; Carman, D. S.; Celentano, A.; Chandavar, S.; Charles, G.; Cole, P. L.; Contalbrigo, M.; Crede, V.; D'Angelo, A.; Daniel, A.; Dashyan, N.; De Sanctis, E.; De Vita, R.; Djalali, C.; Dodge, G. E.; Doughty, D.; Dupre, R.; Egiyan, H.; El Alaoui, A.; El Fassi, L.; Elouadrhiri, L.; Fedotov, G.; Gabrielyan, M. Y.; Gevorgyan, N.; Gilfoyle, G. P.; Giovanetti, K. L.; Girod, F. X.; Gohn, W.; Gothe, R. W.; Griffioen, K. A.; Guegan, B.; Guidal, M.; Hafidi, K.; Hicks, K.; Hyde, C. E.; Ireland, D. G.; Ishkhanov, B. S.; Jenkins, D.; Jo, H. S.; Joo, K.; Khandaker, M.; Khetarpal, P.; Kim, A.; Kim, W.; Kubarovsky, A.; Kubarovsky, V.; Kuhn, S. E.; Kuleshov, S. V.; Kvaltine, N. D.; Lu, H. Y.; MacGregor, I. J. D.; McKinnon, B.; Mirazita, M.; Mokeev, V.; Moutarde, H.; Munevar, E.; Niccolai, S.; Niculescu, G.; Niculescu, I.; Osipenko, M.; Paolone, M.; Pappalardo, L. L.; Paremuzyan, R.; Park, K.; Park, S.; Pisano, S.; Pozdniakov, S.; Procureur, S.; Raue, B. A.; Ricco, G.; Rimal, D.; Ripani, M.; Rosner, G.; Rossi, P.; Saini, M. S.; Saylor, N. A.; Schott, D.; Schumacher, R. A.; Seraydaryan, H.; Smith, E. S.; Sober, D. I.; Sokan, D.; Stepanyan, S. S.; Stepanyan, S.; Strauch, S.; Taiuti, M.; Tang, W.; Tkachenko, S.; Voskanyan, H.; Voutier, E.; Wood, M. H.; Zana, L.; Zhao, B.

2012-06-01

Measuring nucleon-nucleon short range correlations (SRCs) has been a goal of the nuclear physics community for many years. They are an important part of the nuclear wave function, accounting for almost all of the high-momentum strength. They are closely related to the EMC effect. While their overall probability has been measured, measuring their momentum distributions is more difficult. In order to determine the best configuration for studying SRC momentum distributions, we measured the 3He(e,e'pp)n reaction, looking at events with high-momentum protons (pp>0.35 GeV/c) and a low-momentum neutron (pn<0.2 GeV/c). We examined two angular configurations: either both protons emitted forward or one proton emitted forward and one backward (with respect to the momentum transfer, q⃗). The measured relative momentum distribution of the events with one forward and one backward proton was much closer to the calculated initial-state pp relative momentum distribution, indicating that this is the preferred configuration for measuring SRC.

Microscopic equation of state calculations: 1. Nuclear matter. 2. Liquid helium 3

International Nuclear Information System (INIS)

Heyer, J.P.

1989-01-01

A new method for calculating the equation of state of extended Fermi systems is proposed and applied to nuclear matter and liquid 3 He. New techniques are developed for summing up the particle-particle (pp) and particle-hole (ph) ring diagrams to all orders in the calculation of the ground state shift ΔE 0 for many-body systems. Analytic expressions for ΔE pp P 0 , the contribution from all of the pp ring diagrams to ΔE 0 , and ΔE ph 0 , the corresponding contribution from all of the ph ring diagrams, have been obtained. It has been shown that the pp ring diagram sum may be written as an integral over frequency, involving the particle-particle Green's function. A similar integral expression is derived for the ph ring diagram sum. Two methods are developed for carrying out the frequency integrations, namely the multipole and transition amplitude methods. These methods have been tested on an exactly-solvable many-fermion model, a modified Lipkin model, and compared. The author has studied the instability of nuclear matter at both zero and finite temperature within the pp ring diagram framework. He has found using the Gogny D1 effective nucleon-nucleon interaction, complex eigenvalues of an RPA-type secular equation are obtained in a well-defined temperature-density region. When complex eigenvalues occur, the thermodynamic potential becomes complex. The possible connection between the occurrence of complex eigenvalues and liquid-gas phase separation is discussed. The pp ring diagrams are also found to lower the compression modulus of nuclear matter. Lastly, the pp ring diagram method is applied to the calculation of the ground state energy of normal and spin-polarized liquid 3 He. We have found a binding energy per particle (BE/A) of 1.45 degree K and 1.79 degree K for the normal and spin-polarized systems, respectively

Electron Spin Resonance studies on PS, PP and PS/PP blends under gamma irradiation

International Nuclear Information System (INIS)

Reyes, J.; Claro, M.; Albano, C.; Venezuela Central University, Caracas; Moronta, D.

2002-01-01

Complete text of publication follows. Electron Spin Resonance (ESR) studies on Polystyrene (PS), Polypropylene (PP) and their mixtures at compositions of 80/20 with and without a compatibilizer (SBS in block), 7.5 wt.%, irradiated with gamma rays from a Cobalt-60 source with a dose rate of 4.8 KGy/h at integral doses of radiation of 10, 25, 50, 60, 70, 400, 800 and 1300 KGy in the presence of air and at room temperature (RT) are reported. The dependence of resonance line width, Hpp; resonance line shapes K, and radical concentration, S, with the integral dose of irradiation is investigated. The nature of the free radicals after ten days of air storage is discussed. The free radical concentration, the double integral of the resonance line, S, has been estimated at room temperature, RT, for a group of single lines, characterized by the same giromagnetic, g, value by direct numerical double integration. In the samples studied no spectrum of 0 kGy of integral dose was observed. The concentration of radicals, S, observed when the integral radiation doses was increased, presents a maximum value in the PP samples at high doses (70-1300 kGy) and minimum values in the PS samples with the same doses. This shows that the PP degrades at a faster rate than the PS, owing to the presence of the bencenic ring in the latter. In the PS/PP mixtures studied with and without compatibilizer, the values of the radical concentration is found between the observed values in the homopolymers, being closer to the PS, which might imply that the presence of PS decays the degradation process of the PP in the mixture

Some Aspects of the OZI-Rule Violation in the Reaction Anti pp → φπ0

International Nuclear Information System (INIS)

Buzatu, D.; Lev, F.M.

1994-01-01

We consider the problem whether the violation of the OZI-rule in the reaction anti pp → φπ 0 can be explained as the effect of rescattering in the processes anti pp → (K*anti K + anti K*K) → K anti Kπ 0 → φπ 0 and (or) anti pp → ρ + ρ - → (ρ + π - + ρ - π + )π 0 → φπ 0 . If this effect is important then it is possible to give theoretical predictions concerning the energy dependence of the quantity BR(anti pp → φπ 0 )/BR(anti pp → K*anti K) and the value of this quantity in the annihilation at rest from the P state. At the same time the analogous effect in the reaction anti pp → f 2 'π 0 is negligible. 14 refs., 7 figs

Optimized data fusion for K-means Laplacian clustering

Science.gov (United States)

Yu, Shi; Liu, Xinhai; Tranchevent, Léon-Charles; Glänzel, Wolfgang; Suykens, Johan A. K.; De Moor, Bart; Moreau, Yves

2011-01-01

Motivation: We propose a novel algorithm to combine multiple kernels and Laplacians for clustering analysis. The new algorithm is formulated on a Rayleigh quotient objective function and is solved as a bi-level alternating minimization procedure. Using the proposed algorithm, the coefficients of kernels and Laplacians can be optimized automatically. Results: Three variants of the algorithm are proposed. The performance is systematically validated on two real-life data fusion applications. The proposed Optimized Kernel Laplacian Clustering (OKLC) algorithms perform significantly better than other methods. Moreover, the coefficients of kernels and Laplacians optimized by OKLC show some correlation with the rank of performance of individual data source. Though in our evaluation the K values are predefined, in practical studies, the optimal cluster number can be consistently estimated from the eigenspectrum of the combined kernel Laplacian matrix. Availability: The MATLAB code of algorithms implemented in this paper is downloadable from http://homes.esat.kuleuven.be/~sistawww/bioi/syu/oklc.html. Contact: shiyu@uchicago.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:20980271

Current status and future directions of development of PR/PP evaluation methodology

International Nuclear Information System (INIS)

Kim, D. Y.; Kwon, E. H.; Kim, H. D.

2012-01-01

A mandatory design requirement for the introduction of generation IV nuclear energy systems (NESs) is defined as the characteristic of a nuclear energy system that impedes the diversion or undeclared production of nuclear material, or misuse of technology, by State in order to acquire nuclear weapons or other nuclear explosive devices. The same report also defines physical protection (PP) as the use of technical, administrative, and operational measures to prevent the theft of nuclear/radioactive material for the purpose of producing nuclear weapons, producing nuclear devices for nuclear terrorism, or using the facility or transportation system for radiological sabotage. Since the early 1970s right after the Indian nuclear test, the international community has recognized the limits of political and diplomatic means to prevent overt proliferation by states and looked for ways to incorporate technical features that are inherent in NESs. As a first step, active research has been conducted to develop a methodology to evaluate PR and PP components of NESs and has now been reduced to two main R and D streams: the Generation IV International Forum (GIF) and International Project on Innovative Nuclear Reactors and Fuel Cycles (INPRO). (Currently, GIF and INPRO are leading the debate as major projects for PR and PP evaluation methods.) This paper presents an overview of the R and D accomplishments during the development of PR and PP evaluation methodology. It also suggests some directions for future research

Current status and future directions of development of PR/PP evaluation methodology

Energy Technology Data Exchange (ETDEWEB)

Kim, D. Y.; Kwon, E. H.; Kim, H. D. [KAERI, Daejeon (Korea, Republic of)

2012-10-15

A mandatory design requirement for the introduction of generation IV nuclear energy systems (NESs) is defined as the characteristic of a nuclear energy system that impedes the diversion or undeclared production of nuclear material, or misuse of technology, by State in order to acquire nuclear weapons or other nuclear explosive devices. The same report also defines physical protection (PP) as the use of technical, administrative, and operational measures to prevent the theft of nuclear/radioactive material for the purpose of producing nuclear weapons, producing nuclear devices for nuclear terrorism, or using the facility or transportation system for radiological sabotage. Since the early 1970s right after the Indian nuclear test, the international community has recognized the limits of political and diplomatic means to prevent overt proliferation by states and looked for ways to incorporate technical features that are inherent in NESs. As a first step, active research has been conducted to develop a methodology to evaluate PR and PP components of NESs and has now been reduced to two main R and D streams: the Generation IV International Forum (GIF) and International Project on Innovative Nuclear Reactors and Fuel Cycles (INPRO). (Currently, GIF and INPRO are leading the debate as major projects for PR and PP evaluation methods.) This paper presents an overview of the R and D accomplishments during the development of PR and PP evaluation methodology. It also suggests some directions for future research.

Production of $K*(892)^0$ and $\\phi$(1020) in pp collisions at $\\sqrt{s}$ =7 TeV

CERN Document Server

Abelev, Betty; Adamova, Dagmar; Adare, Andrew Marshall; Aggarwal, Madan; Aglieri Rinella, Gianluca; Agocs, Andras Gabor; Agostinelli, Andrea; Aguilar Salazar, Saul; Ahammed, Zubayer; Ahmad, Arshad; Ahmad, Nazeer; Ahn, Sang Un; Akindinov, Alexander; Aleksandrov, Dmitry; Alessandro, Bruno; Alfaro Molina, Jose Ruben; Alici, Andrea; Alkin, Anton; Almaraz Avina, Erick Jonathan; Alme, Johan; Alt, Torsten; Altini, Valerio; Altinpinar, Sedat; Altsybeev, Igor; Andrei, Cristian; Andronic, Anton; Anguelov, Venelin; Anielski, Jonas; Anticic, Tome; Antinori, Federico; Antonioli, Pietro; Aphecetche, Laurent Bernard; Appelshauser, Harald; Arbor, Nicolas; Arcelli, Silvia; Armesto, Nestor; Arnaldi, Roberta; Aronsson, Tomas Robert; Arsene, Ionut Cristian; Arslandok, Mesut; Augustinus, Andre; Averbeck, Ralf Peter; Awes, Terry; Aysto, Juha Heikki; Azmi, Mohd Danish; Bach, Matthias Jakob; Badala, Angela; Baek, Yong Wook; Bailhache, Raphaelle Marie; Bala, Renu; Baldini Ferroli, Rinaldo; Baldisseri, Alberto; Baldit, Alain; Baltasar Dos Santos Pedrosa, Fernando; Ban, Jaroslav; Baral, Rama Chandra; Barbera, Roberto; Barile, Francesco; Barnafoldi, Gergely Gabor; Barnby, Lee Stuart; Barret, Valerie; Bartke, Jerzy Gustaw; Basile, Maurizio; Bastid, Nicole; Basu, Sumit; Bathen, Bastian; Batigne, Guillaume; Batyunya, Boris; Baumann, Christoph Heinrich; Bearden, Ian Gardner; Beck, Hans; Behera, Nirbhay Kumar; Belikov, Iouri; Bellini, Francesca; Bellwied, Rene; Belmont-Moreno, Ernesto; Bencedi, Gyula; Beole, Stefania; Berceanu, Ionela; Bercuci, Alexandru; Berdnikov, Yaroslav; Berenyi, Daniel; Bergognon, Anais Annick Erica; Berzano, Dario; Betev, Latchezar; Bhasin, Anju; Bhati, Ashok Kumar; Bhom, Jihyun; Bianchi, Livio; Bianchi, Nicola; Bianchin, Chiara; Bielcik, Jaroslav; Bielcikova, Jana; Bilandzic, Ante; Bjelogrlic, Sandro; Blanco, F; Blanco, Francesco; Blau, Dmitry; Blume, Christoph; Bock, Nicolas; Boettger, Stefan; Bogdanov, Alexey; Boggild, Hans; Bogolyubsky, Mikhail; Boldizsar, Laszlo; Bombara, Marek; Book, Julian; Borel, Herve; Borissov, Alexander; Bose, Suvendu Nath; Bossu, Francesco; Botje, Michiel; Boyer, Bruno Alexandre; Braidot, Ermes; Braun-Munzinger, Peter; Bregant, Marco; Breitner, Timo Gunther; Browning, Tyler Allen; Broz, Michal; Brun, Rene; Bruna, Elena; Bruno, Giuseppe Eugenio; Budnikov, Dmitry; Buesching, Henner; Bufalino, Stefania; Busch, Oliver; Buthelezi, Edith Zinhle; Caffarri, Davide; Cai, Xu; Caines, Helen Louise; Calvo Villar, Ernesto; Camerini, Paolo; Canoa Roman, Veronica; Cara Romeo, Giovanni; Carena, Francesco; Carena, Wisla; Carminati, Federico; Casanova Diaz, Amaya Ofelia; Castillo Castellanos, Javier Ernesto; Casula, Ester Anna Rita; Catanescu, Vasile; Cavicchioli, Costanza; Ceballos Sanchez, Cesar; Cepila, Jan; Cerello, Piergiorgio; Chang, Beomsu; Chapeland, Sylvain; Charvet, Jean-Luc Fernand; Chattopadhyay, Sukalyan; Chattopadhyay, Subhasis; Chawla, Isha; Cherney, Michael Gerard; Cheshkov, Cvetan; Cheynis, Brigitte; Chiavassa, Emilio; Chibante Barroso, Vasco Miguel; Chinellato, David; Chochula, Peter; Chojnacki, Marek; Choudhury, Subikash; Christakoglou, Panagiotis; Christensen, Christian Holm; Christiansen, Peter; Chujo, Tatsuya; Chung, Suh-Urk; Cicalo, Corrado; Cifarelli, Luisa; Cindolo, Federico; Cleymans, Jean Willy Andre; Coccetti, Fabrizio; Colamaria, Fabio; Colella, Domenico; Conesa Balbastre, Gustavo; Conesa del Valle, Zaida; Constantin, Paul; Contin, Giacomo; Contreras, Jesus Guillermo; Cormier, Thomas Michael; Corrales Morales, Yasser; Cortes Maldonado, Ismael; Cortese, Pietro; Cosentino, Mauro Rogerio; Costa, Filippo; Cotallo, Manuel Enrique; Crochet, Philippe; Cruz Alaniz, Emilia; Cuautle, Eleazar; Cunqueiro, Leticia; D'Erasmo, Ginevra; Dainese, Andrea; Dalsgaard, Hans Hjersing; Danu, Andrea; Das, Debasish; Das, Indranil; Das, Kushal; Dash, Ajay Kumar; Dash, Sadhana; De, Sudipan; de Barros, Gabriel; De Caro, Annalisa; de Cataldo, Giacinto; de Cuveland, Jan; De Falco, Alessandro; De Gruttola, Daniele; De Marco, Nora; De Pasquale, Salvatore; de Rooij, Raoul Stefan; Delagrange, Hugues; Deloff, Andrzej; Demanov, Vyacheslav; Denes, Ervin; Deppman, Airton; Di Bari, Domenico; Di Giglio, Carmelo; Di Liberto, Sergio; Di Mauro, Antonio; Di Nezza, Pasquale; Diaz Corchero, Miguel Angel; Dietel, Thomas; Divia, Roberto; Djuvsland, Oeystein; Dobrin, Alexandru Florin; Dobrowolski, Tadeusz Antoni; Dominguez, Isabel; Donigus, Benjamin; Dordic, Olja; Driga, Olga; Dubey, Anand Kumar; Dubla, Andrea; Ducroux, Laurent; Dupieux, Pascal; Dutta Majumdar, AK; Dutta Majumdar, Mihir Ranjan; Elia, Domenico; Emschermann, David Philip; Engel, Heiko; Erazmus, Barbara; Erdal, Hege Austrheim; Espagnon, Bruno; Estienne, Magali Danielle; Esumi, Shinichi; Evans, David; Eyyubova, Gyulnara; Fabris, Daniela; Faivre, Julien; Falchieri, Davide; Fantoni, Alessandra; Fasel, Markus; Fedunov, Anatoly; Fehlker, Dominik; Feldkamp, Linus; Felea, Daniel; Fenton-Olsen, Bo; Feofilov, Grigory; Fernandez Tellez, Arturo; Ferretti, Alessandro; Ferretti, Roberta; Festanti, Andrea; Figiel, Jan; Figueredo, Marcel; Filchagin, Sergey; Finogeev, Dmitry; Fionda, Fiorella; Fiore, Enrichetta Maria; Floris, Michele; Foertsch, Siegfried Valentin; Foka, Panagiota; Fokin, Sergey; Fragiacomo, Enrico; Francescon, Andrea; Frankenfeld, Ulrich Michael; Fuchs, Ulrich; Furget, Christophe; Fusco Girard, Mario; Gaardhoje, Jens Joergen; Gagliardi, Martino; Gago, Alberto; Gallio, Mauro; Gangadharan, Dhevan Raja; Ganoti, Paraskevi; Garabatos, Jose; Garcia-Solis, Edmundo; Garishvili, Irakli; Gerhard, Jochen; Germain, Marie; Geuna, Claudio; Gheata, Andrei George; Gheata, Mihaela; Ghidini, Bruno; Ghosh, Premomoy; Gianotti, Paola; Girard, Martin Robert; Giubellino, Paolo; Gladysz-Dziadus, Ewa; Glassel, Peter; Gomez, Ramon; Gonzalez Ferreiro, Elena; Gonzalez-Trueba, Laura Helena; Gonzalez-Zamora, Pedro; Gorbunov, Sergey; Goswami, Ankita; Gotovac, Sven; Grabski, Varlen; Graczykowski, Lukasz Kamil; Grajcarek, Robert; Grelli, Alessandro; Grigoras, Alina Gabriela; Grigoras, Costin; Grigoriev, Vladislav; Grigoryan, Ara; Grigoryan, Smbat; Grinyov, Boris; Grion, Nevio; Grosse-Oetringhaus, Jan Fiete; Grossiord, Jean-Yves; Grosso, Raffaele; Guber, Fedor; Guernane, Rachid; Guerra Gutierrez, Cesar; Guerzoni, Barbara; Guilbaud, Maxime Rene Joseph; Gulbrandsen, Kristjan Herlache; Gunji, Taku; Gupta, Anik; Gupta, Ramni; Gutbrod, Hans; Haaland, Oystein Senneset; Hadjidakis, Cynthia Marie; Haiduc, Maria; Hamagaki, Hideki; Hamar, Gergoe; Hanratty, Luke David; Hansen, Alexander; Harmanova, Zuzana; Harris, John William; Hartig, Matthias; Hasegan, Dumitru; Hatzifotiadou, Despoina; Hayrapetyan, Arsen; Heckel, Stefan Thomas; Heide, Markus Ansgar; Helstrup, Haavard; Herghelegiu, Andrei Ionut; Herrera Corral, Gerardo Antonio; Herrmann, Norbert; Hess, Benjamin Andreas; Hetland, Kristin Fanebust; Hicks, Bernard; Hille, Per Thomas; Hippolyte, Boris; Horaguchi, Takuma; Hori, Yasuto; Hristov, Peter Zahariev; Hrivnacova, Ivana; Huang, Meidana; Humanic, Thomas; Hwang, Dae Sung; Ichou, Raphaelle; Ilkaev, Radiy; Ilkiv, Iryna; Inaba, Motoi; Incani, Elisa; Innocenti, Gian Michele; Ippolitov, Mikhail; Irfan, Muhammad; Ivan, Cristian George; Ivanov, Andrey; Ivanov, Marian; Ivanov, Vladimir; Ivanytskyi, Oleksii; Jacholkowski, Adam Wlodzimierz; Jacobs, Peter; Janik, Malgorzata Anna; Janik, Rudolf; Jayarathna, Sandun; Jena, Satyajit; Jha, Deeptanshu Manu; Jimenez Bustamante, Raul Tonatiuh; Jirden, Lennart; Jones, Peter Graham; Jung, Hyung Taik; Jusko, Anton; Kakoyan, Vanik; Kalcher, Sebastian; Kalinak, Peter; Kalliokoski, Tuomo Esa Aukusti; Kalweit, Alexander Philipp; Kang, Ju Hwan; Kaplin, Vladimir; Karasu Uysal, Ayben; Karavichev, Oleg; Karavicheva, Tatiana; Karpechev, Evgeny; Kazantsev, Andrey; Kebschull, Udo Wolfgang; Keidel, Ralf; Khan, Mohisin Mohammed; Khan, Palash; Khan, Shuaib Ahmad; Khanzadeev, Alexei; Kharlov, Yury; Kileng, Bjarte; Kim, Beomkyu; Kim, Dong Jo; Kim, Do Won; Kim, Jonghyun; Kim, Jin Sook; Kim, Minwoo; Kim, Mimae; Kim, Se Yong; Kim, Seon Hee; Kim, Taesoo; Kirsch, Stefan; Kisel, Ivan; Kiselev, Sergey; Kisiel, Adam Ryszard; Klay, Jennifer Lynn; Klein, Jochen; Klein-Bosing, Christian; Kluge, Alexander; Knichel, Michael Linus; Knospe, Anders Garritt; Koch, Kathrin; Kohler, Markus; Kollegger, Thorsten; Kolojvari, Anatoly; Kondratiev, Valery; Kondratyeva, Natalia; Konevskih, Artem; Korneev, Andrey; Kour, Ravjeet; Kowalski, Marek; Kox, Serge; Koyithatta Meethaleveedu, Greeshma; Kral, Jiri; Kralik, Ivan; Kramer, Frederick; Kraus, Ingrid Christine; Krawutschke, Tobias; Krelina, Michal; Kretz, Matthias; Krivda, Marian; Krizek, Filip; Krus, Miroslav; Kryshen, Evgeny; Krzewicki, Mikolaj; Kucheriaev, Yury; Kugathasan, Thanushan; Kuhn, Christian Claude; Kuijer, Paul; Kulakov, Igor; Kumar, Jitendra; Kurashvili, Podist; Kurepin, A; Kurepin, AB; Kuryakin, Alexey; Kushpil, Svetlana; Kushpil, Vasily; Kweon, Min Jung; Kwon, Youngil; La Pointe, Sarah Louise; La Rocca, Paola; Ladron de Guevara, Pedro; Lakomov, Igor; Langoy, Rune; Lara, Camilo Ernesto; Lardeux, Antoine Xavier; Lazzeroni, Cristina; Le Bornec, Yves; Lea, Ramona; Lechman, Mateusz; Lee, Graham Richard; Lee, Ki Sang; Lee, Sung Chul; Lefevre, Frederic; Lehnert, Joerg Walter; Leistam, Lars; Lemmon, Roy Crawford; Lenti, Vito; Leon Monzon, Ildefonso; Leon Vargas, Hermes; Leoncino, Marco; Levai, Peter; Lien, Jorgen; Lietava, Roman; Lindal, Svein; Lindenstruth, Volker; Lippmann, Christian; Lisa, Michael Annan; Liu, Lijiao; Loggins, Vera; Loginov, Vitaly; Lohn, Stefan Bernhard; Lohner, Daniel; Loizides, Constantinos; Loo, Kai Krister; Lopez, Xavier Bernard; Lopez Torres, Ernesto; Lovhoiden, Gunnar; Lu, Xianguo; Luettig, Philipp; Lunardon, Marcello; Luo, Jiebin; Luparello, Grazia; Luquin, Lionel; Luzzi, Cinzia; Ma, Rongrong; Maevskaya, Alla; Mager, Magnus; Mahapatra, Durga Prasad; Maire, Antonin; Mal'Kevich, Dmitry; Malaev, Mikhail; Maldonado Cervantes, Ivonne Alicia; Malinina, Ludmila; Malzacher, Peter; Mamonov, Alexander; Manceau, Loic Henri Antoine; Manko, Vladislav; Manso, Franck; Manzari, Vito; Mao, Yaxian; Marchisone, Massimiliano; Mares, Jiri; Margagliotti, Giacomo Vito; Margotti, Anselmo; Marin, Ana Maria; Marin Tobon, Cesar Augusto; Markert, Christina; Martashvili, Irakli; Martinengo, Paolo; Martinez, Mario Ivan; Martinez Davalos, Arnulfo; Martinez Garcia, Gines; Martynov, Yevgen; Mas, Alexis Jean-Michel; Masciocchi, Silvia; Masera, Massimo; Masoni, Alberto; Mastroserio, Annalisa; Matthews, Zoe Louise; Matyja, Adam Tomasz; Mayer, Christoph; Mazer, Joel; Mazzoni, Alessandra Maria; Meddi, Franco; Menchaca-Rocha, Arturo Alejandro; Mercado Perez, Jorge; Meres, Michal; Miake, Yasuo; Milano, Leonardo; Milosevic, Jovan; Mischke, Andre; Mishra, Aditya Nath; Miskowiec, Dariusz; Mitu, Ciprian Mihai; Mlynarz, Jocelyn; Mohanty, Bedangadas; Molnar, Levente; Montano Zetina, Luis Manuel; Monteno, Marco; Montes, Esther; Moon, Taebong; Morando, Maurizio; Moreira De Godoy, Denise Aparecida; Moretto, Sandra; Morsch, Andreas; Muccifora, Valeria; Mudnic, Eugen; Muhuri, Sanjib; Mukherjee, Maitreyee; Muller, Hans; Munhoz, Marcelo; Musa, Luciano; Musso, Alfredo; Nandi, Basanta Kumar; Nania, Rosario; Nappi, Eugenio; Nattrass, Christine; Naumov, Nikolay; Navin, Sparsh; Nayak, Tapan Kumar; Nazarenko, Sergey; Nazarov, Gleb; Nedosekin, Alexander; Nicassio, Maria; Niculescu, Mihai; Nielsen, Borge Svane; Niida, Takafumi; Nikolaev, Sergey; Nikulin, Sergey; Nikulin, Vladimir; Nilsen, Bjorn Steven; Nilsson, Mads Stormo; Noferini, Francesco; Nomokonov, Petr; Nooren, Gerardus; Novitzky, Norbert; Nyanin, Alexandre; Nyatha, Anitha; Nygaard, Casper; Nystrand, Joakim Ingemar; Oeschler, Helmut Oskar; Oh, Saehanseul; Oh, Sun Kun; Oleniacz, Janusz; Oppedisano, Chiara; Ortona, Giacomo; Oskarsson, Anders Nils Erik; Otwinowski, Jacek Tomasz; Oyama, Ken; Pachmayer, Yvonne Chiara; Pachr, Milos; Padilla, Fatima; Pagano, Paola; Paic, Guy; Painke, Florian; Pajares, Carlos; Pal, Susanta Kumar; Palaha, Arvinder Singh; Palmeri, Armando; Papikyan, Vardanush; Pappalardo, Giuseppe; Park, Woo Jin; Passfeld, Annika; Patalakha, Dmitri Ivanovich; Paticchio, Vincenzo; Pavlinov, Alexei; Pawlak, Tomasz Jan; Peitzmann, Thomas; Pereira Da Costa, Hugo Denis Antonio; Pereira De Oliveira Filho, Elienos; Peresunko, Dmitri; Perez Lara, Carlos Eugenio; Perez Lezama, Edgar; Perini, Diego; Perrino, Davide; Peryt, Wiktor Stanislaw; Pesci, Alessandro; Peskov, Vladimir; Pestov, Yury; Petracek, Vojtech; Petran, Michal; Petris, Mariana; Petrov, Plamen Rumenov; Petrovici, Mihai; Petta, Catia; Piano, Stefano; Piccotti, Anna; Pikna, Miroslav; Pillot, Philippe; Pinazza, Ombretta; Pinsky, Lawrence; Pitz, Nora; Piuz, Francois; Piyarathna, Danthasinghe; Ploskon, Mateusz Andrzej; Pluta, Jan Marian; Pochybova, Sona; Podesta Lerma, Pedro Luis Manuel; Poghosyan, Martin; Polichtchouk, Boris; Pop, Amalia; Porteboeuf-Houssais, Sarah; Pospisil, Vladimir; Potukuchi, Baba; Prasad, Sidharth Kumar; Preghenella, Roberto; Prino, Francesco; Pruneau, Claude Andre; Pshenichnov, Igor; Puchagin, Sergey; Puddu, Giovanna; Pujahari, Prabhat Ranjan; Pulvirenti, Alberto; Punin, Valery; Putis, Marian; Putschke, Jorn Henning; Quercigh, Emanuele; Qvigstad, Henrik; Rachevski, Alexandre; Rademakers, Alphonse; Raiha, Tomi Samuli; Rak, Jan; Rakotozafindrabe, Andry Malala; Ramello, Luciano; Ramirez Reyes, Abdiel; Raniwala, Rashmi; Raniwala, Sudhir; Rasanen, Sami Sakari; Rascanu, Bogdan Theodor; Rathee, Deepika; Read, Kenneth Francis; Real, Jean-Sebastien; Redlich, Krzysztof; Rehman, Attiq Ur; Reichelt, Patrick; Reicher, Martijn; Renfordt, Rainer Arno Ernst; Reolon, Anna Rita; Reshetin, Andrey; Rettig, Felix Vincenz; Revol, Jean-Pierre; Reygers, Klaus Johannes; Riccati, Lodovico; Ricci, Renato Angelo; Richert, Tuva; Richter, Matthias Rudolph; Riedler, Petra; Riegler, Werner; Riggi, Francesco; Rodrigues Fernandes Rabacal, Bartolomeu; Rodriguez Cahuantzi, Mario; Rodriguez Manso, Alis; Roed, Ketil; Rohr, David; Rohrich, Dieter; Romita, Rosa; Ronchetti, Federico; Rosnet, Philippe; Rossegger, Stefan; Rossi, Andrea; Roy, Christelle Sophie; Roy, Pradip Kumar; Rubio Montero, Antonio Juan; Rui, Rinaldo; Russo, Riccardo; Ryabinkin, Evgeny; Rybicki, Andrzej; Sadovsky, Sergey; Safarik, Karel; Sahoo, Raghunath; Sahu, Pradip Kumar; Saini, Jogender; Sakaguchi, Hiroaki; Sakai, Shingo; Sakata, Dosatsu; Salgado, Carlos Albert; Salzwedel, Jai; Sambyal, Sanjeev Singh; Samsonov, Vladimir; Sanchez Castro, Xitzel; Sandor, Ladislav; Sandoval, Andres; Sano, Masato; Sano, Satoshi; Santo, Rainer; Santoro, Romualdo; Sarkamo, Juho Jaako; Scapparone, Eugenio; Scarlassara, Fernando; Scharenberg, Rolf Paul; Schiaua, Claudiu Cornel; Schicker, Rainer Martin; Schmidt, Christian Joachim; Schmidt, Hans Rudolf; Schreiner, Steffen; Schuchmann, Simone; Schukraft, Jurgen; Schutz, Yves Roland; Schwarz, Kilian Eberhard; Schweda, Kai Oliver; Scioli, Gilda; Scomparin, Enrico; Scott, Patrick Aaron; Scott, Rebecca; Segato, Gianfranco; Selyuzhenkov, Ilya; Senyukov, Serhiy; Seo, Jeewon; Serci, Sergio; Serradilla, Eulogio; Sevcenco, Adrian; Shabetai, Alexandre; Shabratova, Galina; Shahoyan, Ruben; Sharma, Natasha; Sharma, Satish; Shigaki, Kenta; Shimomura, Maya; Shtejer, Katherin; Sibiriak, Yury; Siciliano, Melinda; Sicking, Eva; Siddhanta, Sabyasachi; Siemiarczuk, Teodor; Silvermyr, David Olle Rickard; Silvestre, Catherine; Simatovic, Goran; Simonetti, Giuseppe; Singaraju, Rama Narayana; Singh, Ranbir; Singha, Subhash; Singhal, Vikas; Sinha, Bikash; Sinha, Tinku; Sitar, Branislav; Sitta, Mario; Skaali, Bernhard; Skjerdal, Kyrre; Smakal, Radek; Smirnov, Nikolai; Snellings, Raimond; Sogaard, Carsten; Soltz, Ron Ariel; Son, Hyungsuk; Song, Jihye; Song, Myunggeun; Soos, Csaba; Soramel, Francesca; Sputowska, Iwona; Spyropoulou-Stassinaki, Martha; Srivastava, Brijesh Kumar; Stachel, Johanna; Stan, Ionel; Stefanek, Grzegorz; Stefanini, Giorgio; Steinpreis, Matthew; Stenlund, Evert Anders; Steyn, Gideon Francois; Stiller, Johannes Hendrik; Stocco, Diego; Stolpovskiy, Mikhail; Strabykin, Kirill; Strmen, Peter; Suaide, Alexandre Alarcon do Passo; Subieta Vasquez, Martin Alfonso; Sugitate, Toru; Suire, Christophe Pierre; Sukhorukov, Mikhail; Sultanov, Rishat; Sumbera, Michal; Susa, Tatjana; Szanto de Toledo, Alejandro; Szarka, Imrich; Szczepankiewicz, Adam; Szostak, Artur Krzysztof; Szymanski, Maciej; Takahashi, Jun; Tapia Takaki, Daniel Jesus; Tarazona Martinez, Alfonso; Tauro, Arturo; Tejeda Munoz, Guillermo; Telesca, Adriana; Terrevoli, Cristina; Thader, Jochen Mathias; Thomas, Deepa; Tieulent, Raphael Noel; Timmins, Anthony; Toia, Alberica; Torii, Hisayuki; Tosello, Flavio; Trubnikov, Victor; Trzaska, Wladyslaw Henryk; Tsuji, Tomoya; Tumkin, Alexandr; Turrisi, Rosario; Tveter, Trine Spedstad; Ulery, Jason Glyndwr; Ullaland, Kjetil; Ulrich, Jochen; Uras, Antonio; Urban, Jozef; Urciuoli, Guido Marie; Usai, Gianluca; Vajzer, Michal; Vala, Martin; Valencia Palomo, Lizardo; Vallero, Sara; van der Kolk, Naomi; van Leeuwen, Marco; Vande Vyvre, Pierre; Vannucci, Luigi; Vargas, Aurora Diozcora; Varma, Raghava; Vasileiou, Maria; Vasiliev, Andrey; Vechernin, Vladimir; Veldhoen, Misha; Venaruzzo, Massimo; Vercellin, Ermanno; Vergara, Sergio; Vernet, Renaud; Verweij, Marta; Vickovic, Linda; Viesti, Giuseppe; Vikhlyantsev, Oleg; Vilakazi, Zabulon; Villalobos Baillie, Orlando; Vinogradov, Alexander; Vinogradov, Leonid; Vinogradov, Yury; Virgili, Tiziano; Viyogi, Yogendra; Vodopianov, Alexander; Voloshin, Kirill; Voloshin, Sergey; Volpe, Giacomo; von Haller, Barthelemy; Vranic, Danilo; Øvrebekk, Gaute; Vrlakova, Janka; Vulpescu, Bogdan; Vyushin, Alexey; Wagner, Boris; Wagner, Vladimir; Wan, Renzhuo; Wang, Dong; Wang, Mengliang; Wang, Yifei; Wang, Yaping; Watanabe, Kengo; Weber, Michael; Wessels, Johannes; Westerhoff, Uwe; Wiechula, Jens; Wikne, Jon; Wilde, Martin Rudolf; Wilk, Alexander; Wilk, Grzegorz Andrzej; Williams, Crispin; Windelband, Bernd Stefan; Xaplanteris Karampatsos, Leonidas; Yaldo, Chris G; Yamaguchi, Yorito; Yang, Hongyan; Yang, Shiming; Yasnopolsky, Stanislav; Yi, JunGyu; Yin, Zhongbao; Yoo, In-Kwon; Yoon, Jongik; Yu, Weilin; Yuan, Xianbao; Yushmanov, Igor; Zach, Cenek; Zampolli, Chiara; Zaporozhets, Sergey; Zarochentsev, Andrey; Zavada, Petr; Zaviyalov, Nikolai; Zbroszczyk, Hanna Paulina; Zelnicek, Pierre; Zgura, Sorin Ion; Zhalov, Mikhail; Zhang, Haitao; Zhang, Xiaoming; Zhou, Daicui; Zhou, Fengchu; Zhou, You; Zhu, Jianhui; Zhu, Xiangrong; Zichichi, Antonino; Zimmermann, Alice; Zinovjev, Gennady; Zoccarato, Yannick Denis; Zynovyev, Mykhaylo; Zyzak, Maksym

2012-10-30

The production of K*(892)$^0$ and $\\phi$(1020) in pp collisions at $\\sqrt{s}$=7 TeV was measured by the ALICE experiment at the LHC. The yields and the transverse momentum spectra $d^2 N/dydp_T$ at midrapidity |y|<0.5 in the range 0 < $p_T$ < 6 GeV/c for K*(892)$^0$ and 0.4 < $p_T$ < 6 GeV/c for $\\phi$(1020) are reported and compared to model predictions. Using the yield of pions, kaons, and Omega baryons measured previously by ALICE at $\\sqrt{s}$=7 TeV, the ratios $K^*/K^-, \\phi/K^*, \\phi/K^-, \\phi/\\pi^-$, and ($\\Omega + anti-\\Omega)/\\phi$ are presented. The values of the $K^*/K^-, \\phi/K^*$ and $\\phi/K^-$ ratios are similar to those found at lower centre-of-mass energies. In contrast, the $\\phi/\\pi^-$ ratio, which has been observed to increase with energy, seems to saturate above 200 GeV. The ($\\Omega + anti-\\Omega)/\\phi$ ratio in the $p_T$ range 1-5 GeV/c is found to be in good agreement with the prediction of the HIJING/$B\\bar{B}$ v2.0 model with a strong colour field.

Studies on cluster decay from trans-lead nuclei using different versions of nuclear potentials

Energy Technology Data Exchange (ETDEWEB)

Santhosh, K.P.; Sukumaran, Indu [Kannur University, School of Pure and Applied Physics, Payyanur, Kerala (India)

2017-06-15

The cluster decays from various isotopes of trans-lead nuclei have been studied using 12 different nuclear potentials by evaluating decay half-lives and are then compared with the available experimental data. The study has shown that the barrier penetrability as well as the decay half-lives varies with the nuclear potential used. The standard deviation of the estimated half-lives is also calculated for these twelve nuclear potentials in comparison with the experimental data. The potential Bass 1980 is found to be the most appropriate potential for studying cluster radioactivity as the standard deviation obtained is least. Among the different proximity potential versions; proximity 1977, proximity 1988, proximity 2000, and modified proximity 2000, the minimum standard deviation is for proximity 1988. The Geiger-Nuttall (G-N) plots studied for different cluster emissions from various parents are observed to show linear behavior but with different slopes and intercepts. Again, the G-N plots obtained are linear with different slopes and intercepts when plotted for different nuclear potentials. So it is observed that with the inclusion of different nuclear potentials, the linearity of the G-N plot remains unaltered. Irrespective of the nuclear potential used, the universal curve (log{sub 10}T{sub 1/2} vs. -ln P) studied for various clusters emitted from various parents are obtained as linear with same slope and intercept. (orig.)

Preface: 2nd Workshop on the State of the Art in Nuclear Cluster Physics

International Nuclear Information System (INIS)

Descouvemont, P.; Dufour, M.; Sparenberg, J.-M.

2011-01-01

The 2nd workshop on the "State of the Art in Nuclear Cluster Physics" (SOTANCP2) took place on May 25-28, 2010, at the Universite Libre de Bruxelles (Brussels, Belgium). The first workshop of this series was held in Strasbourg (France) in 2008. The purpose of SOTANCP2 was to promote the exchange of ideas and to discuss new developments in Clustering Phenomena in Nuclear Physics and Nuclear Astrophysics both from a theoretical and from an experimental point of view

Genetic diversity of K-antigen gene clusters of Escherichia coli and their molecular typing using a suspension array.

Science.gov (United States)

Yang, Shuang; Xi, Daoyi; Jing, Fuyi; Kong, Deju; Wu, Junli; Feng, Lu; Cao, Boyang; Wang, Lei

2018-04-01

Capsular polysaccharides (CPSs), or K-antigens, are the major surface antigens of Escherichia coli. More than 80 serologically unique K-antigens are classified into 4 groups (Groups 1-4) of capsules. Groups 1 and 4 contain the Wzy-dependent polymerization pathway and the gene clusters are in the order galF to gnd; Groups 2 and 3 contain the ABC-transporter-dependent pathway and the gene clusters consist of 3 regions, regions 1, 2 and 3. Little is known about the variations among the gene clusters. In this study, 9 serotypes of K-antigen gene clusters (K2ab, K11, K20, K24, K38, K84, K92, K96, and K102) were sequenced and correlated with their CPS chemical structures. On the basis of sequence data, a K-antigen-specific suspension array that detects 10 distinct CPSs, including the above 9 CPSs plus K30, was developed. This is the first report to catalog the genetic features of E. coli K-antigen variations and to develop a suspension array for their molecular typing. The method has a number of advantages over traditional bacteriophage and serum agglutination methods and lays the foundation for straightforward identification and detection of additional K-antigens in the future.

Inclusive production of π0 mesons in π+p-,K+p- and pp interactions at 250 GeV/c

International Nuclear Information System (INIS)

Adamus, M.A.; Azhinenko, I.V.

1986-01-01

Data on inclusive π 0 production in the forward hemisphere at Feynman variable (x > 0.025) in the center-of-inertia system in π + p, K + p, and pp interactions at 250 GeV/c are presented. These data are compared to the data at lower energies and interpreted in terms of quark-parton models

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

Directory of Open Access Journals (Sweden)

Laurence Morissette

2013-02-01

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

Cluster analysis of polymers using laser-induced breakdown spectroscopy with K-means

Science.gov (United States)

Yangmin, GUO; Yun, TANG; Yu, DU; Shisong, TANG; Lianbo, GUO; Xiangyou, LI; Yongfeng, LU; Xiaoyan, ZENG

2018-06-01

Laser-induced breakdown spectroscopy (LIBS) combined with K-means algorithm was employed to automatically differentiate industrial polymers under atmospheric conditions. The unsupervised learning algorithm K-means were utilized for the clustering of LIBS dataset measured from twenty kinds of industrial polymers. To prevent the interference from metallic elements, three atomic emission lines (C I 247.86 nm , H I 656.3 nm, and O I 777.3 nm) and one molecular line C–N (0, 0) 388.3 nm were used. The cluster analysis results were obtained through an iterative process. The Davies–Bouldin index was employed to determine the initial number of clusters. The average relative standard deviation values of characteristic spectral lines were used as the iterative criterion. With the proposed approach, the classification accuracy for twenty kinds of industrial polymers achieved 99.6%. The results demonstrated that this approach has great potential for industrial polymers recycling by LIBS.

Probing the formation history of the nuclear star cluster at the Galactic Centre with millisecond pulsars

Science.gov (United States)

Abbate, F.; Mastrobuono-Battisti, A.; Colpi, M.; Possenti, A.; Sippel, A. C.; Dotti, M.

2018-01-01

The origin of the nuclear star cluster in the centre of our Galaxy is still unknown. One possibility is that it formed after the disruption of stellar clusters that spiralled into the Galactic Centre due to dynamical friction. We trace the formation of the nuclear star cluster around the central black hole, using state-of-the-art N-body simulations, and follow the dynamics of the neutron stars born in the clusters. We then estimate the number of millisecond pulsars (MSPs) that are released in the nuclear star cluster during its formation. The assembly and tidal dismemberment of globular clusters lead to a population of MSPs distributed over a radius of about 20 pc, with a peak near 3 pc. No clustering is found on the subparsec scale. We simulate the detectability of this population with future radio telescopes like the MeerKAT radio telescope and SKA1, and find that about an order of 10 MSPs can be observed over this large volume, with a paucity of MSPs within the central parsec. This helps discriminating this scenario from the in situ formation model for the nuclear star cluster that would predict an overabundance of MSPs closer to the black hole. We then discuss the potential contribution of our MSP population to the gamma-ray excess at the Galactic Centre.

MEMANFAATKAN ALGORITMA K-MEANS DALAM MENENTUKAN PEGAWAI YANG LAYAK MENGIKUTI ASESSMENT CENTER UNTUK CLUSTERING PROGRAM SDP

Directory of Open Access Journals (Sweden)

Iin Parlina

2018-01-01

Full Text Available Data mining merupakan teknik pengolahan data dalam jumlah besar untuk pengelompokan. Teknik Data mining mempunyai beberapa metode dalam  mengelompokkan salah satu teknik yang dipakai penulis saat ini adalah K-Means. Dalam hal ini penulis mengelompokan data daftar program SDP tahun 2017 untuk mengetahui manakah pegawai yang layak lolos dalam program SDP sehingga dapat melakukan Registrasi Asessment Center. Pengelompokan tersebut berdasarkan kriteria – kriteria data Program SDP. Pada penelitian ini, penulis menerapkan algoritma K-Means Clustering untuk pengelompokan data Program SDP di PT.Bank Syariah. Dalam hal ini, pada umumnya untuk memamasuki program SDP tersebut disesuaikan dengan ketentuan dan parameter Program SDP saja, namun dalam penelitian ini pengelompokan disesuaikan dengan kriteria – kriteria Program SDP seperti kedisiplinan pegawai, Target Kerja Pegawai, Kepatuhan Program SDP. Penulis menggunakan beberapa kriteria tersebut agar pengelompokan yang dihasilkan menjadi lebih optimal. Tujuan dari pengelompokan ini adalah terbentuknya kelompok SDP pada Program SDP yang menggunakan algoritma K-Means clustering. Hasil dari pengelompokan tersebut diperoleh tiga kelompok yaitu kelompok Lolos, Hampir Lolos dan Tidak Lolos. Terdapat pusat cluster dengan Cluster-1= 8;66;13, Cluster-2= 10;71;14 dan Cluster-3=7;60;12. Pusat cluster tersebut didapat dari beberapa iterasi sehingga mengahasilakan pusat cluster yang optimal.

Associated strangeness production in pp collisions near threshold

International Nuclear Information System (INIS)

Winter, P.

2004-01-01

Motivated by the ongoing discussion concerning the nature of the scalar resonances f0(980) and a0(980), the COSY-11 collaboration has taken exclusive data on the pp → ppK+K- reaction near the production threshold. A first total cross section σ = (1.80 ± 0.27 -0.35 +0.28 ) nb for the excess energy Q = 17 MeV has been determined. In contrary to the η, ω, and η' single meson production studies which clearly show the strong pp final state interaction (FSI), the cross section values obtained at COSY-11 and DISTO can be both described by a fit with a four-body phase space including the proton-proton final state interaction as well as with one-meson exchange calculations neglecting FSI effects. Therefore, one might think about a compensation of the strong pp interaction through a pK-FSI effect or an additional degree of freedom caused by the four-body final state. In the latter case, strong FSI effects can be expected at Q-values very close to the K+K- production threshold. Such a motivation triggered - in combination with the investigation of the KK-bar interaction being relevant to the structure of the f0 (980) - further measurements at the excess energies Q = 10 and Q 28 MeV at COSY-11

Worst-case and smoothed analysis of k-means clustering with Bregman divergences

NARCIS (Netherlands)

Manthey, Bodo; Röglin, H.

2013-01-01

The $k$-means method is the method of choice for clustering large-scale data sets and it performs exceedingly well in practice despite its exponential worst-case running-time. To narrow the gap between theory and practice, $k$-means has been studied in the semi-random input model of smoothed

Study of the Mesons Produced Centrally in the Reaction $pp \\rightarrow pp + X^{0}$ and $\\pi^{+}p \\rightarrow \\pi^{+}p + X^{0}$ at 85 GeV/c

CERN Multimedia

2002-01-01

The basic aim of the experiment, similar to WA76, is to undertake a detailed study of the mesonic system (X|0) produced centrally (X^F~=~0) in the exclusive reactions (@p|-/p)p~@A~(@p|-/p)~X|0p at 300 GeV/c. Many decay modes of X|0, e.g. @p|+@p|-, @p|+@p|-@p|0, 2@p|+2@p|-, 2@p|+2@p|-@p|0, @h|0@p|+@p|-, @w|0@p|+@p|-, K|+K|-, K|+K|-@p|0, K|+K^1|0@p|-~+~c.c., K|+K|-@p|+@p|-, K^1|0K^1|0, @h|0@h|0, @*p, etc. will be identified. A specific aim of the proposal is to see how the meson production observed at 85 GeV/c changes with energy and in so doing to search for evidence of mesons which are strongly coupled to glue. \\\\ \\\\ The experiment uses the OMEGA Spectrometer facility with a trigger designed to enhance the central exclusive meson production reaction over the diffractive reactions. This is done by triggering on a forward and backward fast particle in the c.m.s. with !x^F!~$>$~0.7 and vetoing accompanying forward and backward charged particles. The momentum of the fast particle with x^F~$>$~0.7 will be measured...

Fermi liquid, clustering, and structure factor in dilute warm nuclear matter

Science.gov (United States)

Röpke, G.; Voskresensky, D. N.; Kryukov, I. A.; Blaschke, D.

2018-02-01

Properties of nuclear systems at subsaturation densities can be obtained from different approaches. We demonstrate the use of the density autocorrelation function which is related to the isothermal compressibility and, after integration, to the equation of state. This way we connect the Landau Fermi liquid theory well elaborated in nuclear physics with the approaches to dilute nuclear matter describing cluster formation. A quantum statistical approach is presented, based on the cluster decomposition of the polarization function. The fundamental quantity to be calculated is the dynamic structure factor. Comparing with the Landau Fermi liquid theory which is reproduced in lowest approximation, the account of bound state formation and continuum correlations gives the correct low-density result as described by the second virial coefficient and by the mass action law (nuclear statistical equilibrium). Going to higher densities, the inclusion of medium effects is more involved compared with other quantum statistical approaches, but the relation to the Landau Fermi liquid theory gives a promising approach to describe not only thermodynamic but also collective excitations and non-equilibrium properties of nuclear systems in a wide region of the phase diagram.

Prediction of chemotherapeutic response in bladder cancer using K-means clustering of dynamic contrast-enhanced (DCE)-MRI pharmacokinetic parameters.

Science.gov (United States)

Nguyen, Huyen T; Jia, Guang; Shah, Zarine K; Pohar, Kamal; Mortazavi, Amir; Zynger, Debra L; Wei, Lai; Yang, Xiangyu; Clark, Daniel; Knopp, Michael V

2015-05-01

To apply k-means clustering of two pharmacokinetic parameters derived from 3T dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to predict the chemotherapeutic response in bladder cancer at the mid-cycle timepoint. With the predetermined number of three clusters, k-means clustering was performed on nondimensionalized Amp and kep estimates of each bladder tumor. Three cluster volume fractions (VFs) were calculated for each tumor at baseline and mid-cycle. The changes of three cluster VFs from baseline to mid-cycle were correlated with the tumor's chemotherapeutic response. Receiver-operating-characteristics curve analysis was used to evaluate the performance of each cluster VF change as a biomarker of chemotherapeutic response in bladder cancer. The k-means clustering partitioned each bladder tumor into cluster 1 (low kep and low Amp), cluster 2 (low kep and high Amp), cluster 3 (high kep and low Amp). The changes of all three cluster VFs were found to be associated with bladder tumor response to chemotherapy. The VF change of cluster 2 presented with the highest area-under-the-curve value (0.96) and the highest sensitivity/specificity/accuracy (96%/100%/97%) with a selected cutoff value. The k-means clustering of the two DCE-MRI pharmacokinetic parameters can characterize the complex microcirculatory changes within a bladder tumor to enable early prediction of the tumor's chemotherapeutic response. © 2014 Wiley Periodicals, Inc.

Self-assembly of a tetrahedral 58-nuclear barium vanadium oxide cluster.

Science.gov (United States)

Kastner, Katharina; Puscher, Bianka; Streb, Carsten

2013-01-07

We report the synthesis and characterization of a molecular barium vanadium oxide cluster featuring high nuclearity and high symmetry. The tetrameric, 2.3 nm cluster H(5)[Ba(10)(NMP)(14)(H(2)O)(8)[V(12)O(33)](4)Br] is based on a bromide-centred, octahedral barium scaffold which is capped by four previously unknown [V(12)O(33)](6-) clusters in a tetrahedral fashion. The compound represents the largest polyoxovanadate-based heterometallic cluster known to date. The cluster is formed in organic solution and it is suggested that the bulky N-methyl-2-pyrrolidone (NMP) solvent ligands allow the isolation of this giant molecule and prevent further condensation to a solid-state metal oxide. The cluster is fully characterized using single-crystal XRD, elemental analysis, ESI mass spectrometry and other spectroscopic techniques.

Coexistence of cluster structure and superdeformation in 44Ti

International Nuclear Information System (INIS)

Kimura, Masaaki; Horiuchi, Hisashi

2006-01-01

The nucleus 44 Ti has low-lying levels of various kinds of mutually very different nuclear structure displaying the richness of the nuclear many-body dynamics. It is shown that the deformed-basis antisymmetrized molecular dynamics by the use of the Gogny D1S force reproduces successfully and unifiedly two types of coexistence phenomena in 44 Ti. Namely, on one hand, the coexistence of the mean-field structure and the cluster structure is confirmed by verifying the normally deformed structure of the K π =3 1 - band with a 1-particle-1-hole intrinsic configuration and the α+Ca40 cluster structure of the K π =0 2 - band. The mixed character of the mean-field-like structure and the α+Ca40 cluster structure of the ground band is also shown. On the other hand, the coexistence of the normal deformed mean-field and the superdeformed mean-field is confirmed by verifying the triaxial superdeformation of the K π =0 2 + band and the K π =2 1 + band which has a 4-particle-4-hole intrinsic configuration. Good reproduction of the experimental data is shown for many kinds of quantities including the energy spectra, electric transition rates, alpha spectroscopic factors. Preliminary discussions are given on the existence of hyperdeformed excited states, the relation between superdeformation and clustering and so on

Acinetobacter baumannii K27 and K44 capsular polysaccharides have the same K unit but different structures due to the presence of distinct wzy genes in otherwise closely related K gene clusters.

Science.gov (United States)

Shashkov, Alexander S; Kenyon, Johanna J; Senchenkova, Sof'ya N; Shneider, Mikhail M; Popova, Anastasiya V; Arbatsky, Nikolay P; Miroshnikov, Konstantin A; Volozhantsev, Nikolay V; Hall, Ruth M; Knirel, Yuriy A

2016-05-01

Capsular polysaccharides (CPSs), from Acinetobacter baumannii isolates 1432, 4190 and NIPH 70, which have related gene content at the K locus, were examined, and the chemical structures established using 2D(1)H and(13)C NMR spectroscopy. The three isolates produce the same pentasaccharide repeat unit, which consists of 5-N-acetyl-7-N-[(S)-3-hydroxybutanoyl] (major) or 5,7-di-N-acetyl (minor) derivatives of 5,7-diamino-3,5,7,9-tetradeoxy-D-glycero-D-galacto-non-2-ulosonic (legionaminic) acid (Leg5Ac7R), D-galactose, N-acetyl-D-galactosamine and N-acetyl-D-glucosamine. However, the linkage between repeat units in NIPH 70 was different to that in 1432 and 4190, and this significantly alters the CPS structure. The KL27 gene cluster in 4190 and KL44 gene cluster in NIPH 70 are organized identically and contain lga genes for Leg5Ac7R synthesis, genes for the synthesis of the common sugars, as well as anitrA2 initiating transferase and four glycosyltransferases genes. They share high-level nucleotide sequence identity for corresponding genes, but differ in the wzy gene encoding the Wzy polymerase. The Wzy proteins, which have different lengths and share no similarity, would form the unrelated linkages in the K27 and K44 structures. The linkages formed by the four shared glycosyltransferases were predicted by comparison with gene clusters that synthesize related structures. These findings unambiguously identify the linkages formed by WzyK27 and WzyK44, and show that the presence of different wzy genes in otherwise closely related K gene clusters changes the structure of the CPS. This may affect its capacity as a protective barrier for A. baumannii. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

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.

The production of K0 in p+p reactions at 3.5 GeV. Inclusive and exclusive studies with the HADES detector

International Nuclear Information System (INIS)

Berger-Chen, Jia Chii

2015-01-01

The present work deals with an inclusive and an exclusive K 0 analysis of the p+p data - recorded with the HADES experiment at 3.5 GeV - for the determination of the K 0 production dynamic, of production cross sections and angular distributions in particular in the context of resonances (e.g. Δ(1232) ++ ). The exclusive results, which show the presence of a dominant resonance contribution, were, thereby, implemented in theoretical models allowing the reproduction of the inclusive K 0 kinematics.

K- nuclear potentials from in-medium chirally motivated models

International Nuclear Information System (INIS)

Cieply, A.; Gazda, D.; Mares, J.; Friedman, E.; Gal, A.

2011-01-01

A self-consistent scheme for constructing K - nuclear optical potentials from subthreshold in-medium KN s-wave scattering amplitudes is presented and applied to analysis of kaonic atoms data and to calculations of K - quasibound nuclear states. The amplitudes are taken from a chirally motivated meson-baryon coupled-channel model, both at the Tomozawa-Weinberg leading order and at the next to leading order. Typical kaonic atoms potentials are characterized by a real part -Re V K - chiral =85±5 MeV at nuclear matter density, in contrast to half this depth obtained in some derivations based on in-medium KN threshold amplitudes. The moderate agreement with data is much improved by adding complex ρ- and ρ 2 -dependent phenomenological terms, found to be dominated by ρ 2 contributions that could represent KNN→YN absorption and dispersion, outside the scope of meson-baryon chiral models. Depths of the real potentials are then near 180 MeV. The effects of p-wave interactions are studied and found secondary to those of the dominant s-wave contributions. The in-medium dynamics of the coupled-channel model is discussed and systematic studies of K - quasibound nuclear states are presented.

Balanced Cluster Head Selection Based on Modified k-Means in a Distributed Wireless Sensor Network

OpenAIRE

Periyasamy, Sasikumar; Khara, Sibaram; Thangavelu, Shankar

2016-01-01

A major problem with Wireless Sensor Networks (WSNs) is the maximization of effective network lifetime through minimization of energy usage in the network nodes. A modified k-means (Mk-means) algorithm for clustering was proposed which includes three cluster heads (simultaneously chosen) for each cluster. These cluster heads (CHs) use a load sharing mechanism to rotate as the active cluster head, which conserves residual energy of the nodes, thereby extending network lifetime. Moreover, it re...

An improved initialization center k-means clustering algorithm based on distance and density

Science.gov (United States)

Duan, Yanling; Liu, Qun; Xia, Shuyin

2018-04-01

Aiming at the problem of the random initial clustering center of k means algorithm that the clustering results are influenced by outlier data sample and are unstable in multiple clustering, a method of central point initialization method based on larger distance and higher density is proposed. The reciprocal of the weighted average of distance is used to represent the sample density, and the data sample with the larger distance and the higher density are selected as the initial clustering centers to optimize the clustering results. Then, a clustering evaluation method based on distance and density is designed to verify the feasibility of the algorithm and the practicality, the experimental results on UCI data sets show that the algorithm has a certain stability and practicality.

K-mean clustering algorithm for processing signals from compound semiconductor detectors

International Nuclear Information System (INIS)

Tada, Tsutomu; Hitomi, Keitaro; Wu, Yan; Kim, Seong-Yun; Yamazaki, Hiromichi; Ishii, Keizo

2011-01-01

The K-mean clustering algorithm was employed for processing signal waveforms from TlBr detectors. The signal waveforms were classified based on its shape reflecting the charge collection process in the detector. The classified signal waveforms were processed individually to suppress the pulse height variation of signals due to the charge collection loss. The obtained energy resolution of a 137 Cs spectrum measured with a 0.5 mm thick TlBr detector was 1.3% FWHM by employing 500 clusters.

Study of $D_{sJ}$ decays to $D^+K^0_{\\rm S}$ and $D^0K^+$ final states in $pp$ collisions

CERN Document Server

Aaij, R; Adametz, A; Adeva, B; Adinolfi, M; Adrover, C; Affolder, A; Ajaltouni, Z; Albrecht, J; Alessio, F; Alexander, M; Ali, S; Alkhazov, G; Alvarez Cartelle, P; Alves Jr, A A; Amato, S; Amhis, Y; Anderson, J; Appleby, R B; Aquines Gutierrez, O; Archilli, F; Artamonov, A; Artuso, M; Aslanides, E; Auriemma, G; Bachmann, S; Back, J J; Balagura, V; Baldini, W; Barlow, R J; Barschel, C; Barsuk, S; Barter, W; Bates, A; Bauer, C; Bauer, Th; Bay, A; Beddow, J; Bediaga, I; Belogurov, S; Belous, K; Belyaev, I; Ben-Haim, E; Benayoun, M; Bencivenni, G; Benson, S; Benton, J; Bernet, R; Bettler, M -O; van Beuzekom, M; Bien, A; Bifani, S; Bird, T; Bizzeti, A; Bjørnstad, P M; Blake, T; Blanc, F; Blanks, C; Blouw, J; Blusk, S; Bobrov, A; Bocci, V; Bondar, A; Bondar, N; Bonivento, W; Borghi, S; Borgia, A; Bowcock, T J V; Bozzi, C; Brambach, T; van den Brand, J; Bressieux, J; Brett, D; Britsch, M; Britton, T; Brook, N H; Brown, H; Büchler-Germann, A; Burducea, I; Bursche, A; Buytaert, J; Cadeddu, S; Callot, O; Calvi, M; Calvo Gomez, M; Camboni, A; Campana, P; Carbone, A; Carboni, G; Cardinale, R; Cardini, A; Carson, L; Carvalho Akiba, K; Casse, G; Cattaneo, M; Cauet, Ch; Charles, M; Charpentier, Ph; Chen, P; Chiapolini, N; Chrzaszcz, M; Ciba, K; Cid Vidal, X; Ciezarek, G; Clarke, P E L; Clemencic, M; Cliff, H V; Closier, J; Coca, C; Coco, V; Cogan, J; Cogneras, E; Collins, P; Comerma-Montells, A; Contu, A; Cook, A; Coombes, M; Corti, G; Couturier, B; Cowan, G A; Craik, D; Currie, R; D'Ambrosio, C; David, P; David, P N Y; De Bonis, I; De Bruyn, K; De Capua, S; De Cian, M; De Miranda, J M; De Paula, L; De Simone, P; Decamp, D; Deckenhoff, M; Degaudenzi, H; Del Buono, L; Deplano, C; Derkach, D; Deschamps, O; Dettori, F; Dickens, J; Dijkstra, H; Diniz Batista, P; Domingo Bonal, F; Donleavy, S; Dordei, F; Dosil Suárez, A; Dossett, D; Dovbnya, A; Dupertuis, F; Dzhelyadin, R; Dziurda, A; Dzyuba, A; Easo, S; Egede, U; Egorychev, V; Eidelman, S; van Eijk, D; Eisele, F; Eisenhardt, S; Ekelhof, R; Eklund, L; El Rifai, I; Elsasser, Ch; Elsby, D; Esperante Pereira, D; Falabella, A; Färber, C; Fardell, G; Farinelli, C; Farry, S; Fave, V; Fernandez Albor, V; Ferreira Rodrigues, F; Ferro-Luzzi, M; Filippov, S; Fitzpatrick, C; Fontana, M; Fontanelli, F; Forty, R; Francisco, O; Frank, M; Frei, C; Frosini, M; Furcas, S; Gallas Torreira, A; Galli, D; Gandelman, M; Gandini, P; Gao, Y; Garnier, J-C; Garofoli, J; Garra Tico, J; Garrido, L; Gascon, D; Gaspar, C; Gauld, R; Gauvin, N; Gersabeck, E; Gersabeck, M; Gershon, T; Ghez, Ph; Gibson, V; Gligorov, V V; Göbel, C; Golubkov, D; Golutvin, A; Gomes, A; Gordon, H; Grabalosa Gándara, M; Graciani Diaz, R; Granado Cardoso, L A; Graugés, E; Graziani, G; Grecu, A; Greening, E; Gregson, S; Grünberg, O; Gui, B; Gushchin, E; Guz, Yu; Gys, T; Hadjivasiliou, C; Haefeli, G; Haen, C; Haines, S C; Hampson, T; Hansmann-Menzemer, S; Harnew, N; Harnew, S T; Harrison, J; Harrison, P F; Hartmann, T; He, J; Heijne, V; Hennessy, K; Henrard, P; Hernando Morata, J A; van Herwijnen, E; Hicks, E; Hoballah, M; Hopchev, P; Hulsbergen, W; Hunt, P; Huse, T; Huston, R S; Hutchcroft, D; Hynds, D; Iakovenko, V; Ilten, P; Imong, J; Jacobsson, R; Jaeger, A; Jahjah Hussein, M; Jans, E; Jansen, F; Jaton, P; Jean-Marie, B; Jing, F; John, M; Johnson, D; Jones, C R; Jost, B; Kaballo, M; Kandybei, S; Karacson, M; Karbach, T M; Keaveney, J; Kenyon, I R; Kerzel, U; Ketel, T; Keune, A; Khanji, B; Kim, Y M; Knecht, M; Kochebina, O; Komarov, I; Koopman, R F; Koppenburg, P; Korolev, M; Kozlinskiy, A; Kravchuk, L; Kreplin, K; Kreps, M; Krocker, G; Krokovny, P; Kruse, F; Kucharczyk, M; Kudryavtsev, V; Kvaratskheliya, T; La Thi, V N; Lacarrere, D; Lafferty, G; Lai, A; Lambert, D; Lambert, R W; Lanciotti, E; Lanfranchi, G; Langenbruch, C; Latham, T; Lazzeroni, C; Le Gac, R; van Leerdam, J; Lees, J -P; Lefèvre, R; Leflat, A; Lefrançois, J; Leroy, O; Lesiak, T; Li, L; Li, Y; Li Gioi, L; Lieng, M; Liles, M; Lindner, R; Linn, C; Liu, B; Liu, G; von Loeben, J; Lopes, J H; Lopez Asamar, E; Lopez-March, N; Lu, H; Luisier, J; Mac Raighne, A; Machefert, F; Machikhiliyan, I V; Maciuc, F; Maev, O; Magnin, J; Malde, S; Mamunur, R M D; Manca, G; Mancinelli, G; Mangiafave, N; Marconi, U; Märki, R; Marks, J; Martellotti, G; Martens, A; Martin, L; Martín Sánchez, A; Martinelli, M; Martinez Santos, D; Massafferri, A; Mathe, Z; Matteuzzi, C; Matveev, M; Maurice, E; Mazurov, A; McCarthy, J; McGregor, G; McNulty, R; Meissner, M; Merk, M; Merkel, J; Milanes, D A; Minard, M -N; Molina Rodriguez, J; Monteil, S; Moran, D; Morawski, P; Mountain, R; Mous, I; Muheim, F; Müller, K; Muresan, R; Muryn, B; Muster, B; Mylroie-Smith, J; Naik, P; Nakada, T; Nandakumar, R; Nasteva, I; Needham, M; Neufeld, N; Nguyen, A D; Nguyen-Mau, C; Nicol, M; Niess, V; Nikitin, N; Nikodem, T; Nomerotski, A; Novoselov, A; Oblakowska-Mucha, A; Obraztsov, V; Oggero, S; Ogilvy, S; Okhrimenko, O; Oldeman, R; Orlandea, M; Otalora Goicochea, J M; Owen, P; Pal, B K; Palano, A; Palutan, M; Panman, J; Papanestis, A; Pappagallo, M; Parkes, C; Parkinson, C J; Passaleva, G; Patel, G D; Patel, M; Patrick, G N; Patrignani, C; Pavel-Nicorescu, C; Pazos Alvarez, A; Pellegrino, A; Penso, G; Pepe Altarelli, M; Perazzini, S; Perego, D L; Perez Trigo, E; Pérez-Calero Yzquierdo, A; Perret, P; Perrin-Terrin, M; Pessina, G; Petrolini, A; Phan, A; Picatoste Olloqui, E; Pie Valls, B; Pietrzyk, B; Pilař, T; Pinci, D; Playfer, S; Plo Casasus, M; Polci, F; Polok, G; Poluektov, A; Polycarpo, E; Popov, D; Popovici, B; Potterat, C; Powell, A; Prisciandaro, J; Pugatch, V; Puig Navarro, A; Qian, W; Rademacker, J H; Rakotomiaramanana, B; Rangel, M S; Raniuk, I; Rauschmayr, N; Raven, G; Redford, S; Reid, M M; dos Reis, A C; Ricciardi, S; Richards, A; Rinnert, K; Roa Romero, D A; Robbe, P; Rodrigues, E; Rodrigues, F; Rodriguez Perez, P; Rogers, G J; Roiser, S; Romanovsky, V; Romero Vidal, A; Rosello, M; Rouvinet, J; Ruf, T; Ruiz, H; Sabatino, G; Saborido Silva, J J; Sagidova, N; Sail, P; Saitta, B; Salzmann, C; Sanmartin Sedes, B; Sannino, M; Santacesaria, R; Santamarina Rios, C; Santinelli, R; Santovetti, E; Sapunov, M; Sarti, A; Satriano, C; Satta, A; Savrie, M; Savrina, D; Schaack, P; Schiller, M; Schindler, H; Schleich, S; Schlupp, M; Schmelling, M; Schmidt, B; Schneider, O; Schopper, A; Schune, M -H; Schwemmer, R; Sciascia, B; Sciubba, A; Seco, M; Semennikov, A; Senderowska, K; Sepp, I; Serra, N; Serrano, J; Seyfert, P; Shapkin, M; Shapoval, I; Shatalov, P; Shcheglov, Y; Shears, T; Shekhtman, L; Shevchenko, O; Shevchenko, V; Shires, A; Silva Coutinho, R; Skwarnicki, T; Smith, N A; Smith, E; Smith, M; Sobczak, K; Soler, F J P; Solomin, A; Soomro, F; Souza, D; Souza De Paula, B; Spaan, B; Sparkes, A; Spradlin, P; Stagni, F; Stahl, S; Steinkamp, O; Stoica, S; Stone, S; Storaci, B; Straticiuc, M; Straumann, U; Subbiah, V K; Swientek, S; Szczekowski, M; Szczypka, P; Szumlak, T; T'Jampens, S; Teklishyn, M; Teodorescu, E; Teubert, F; Thomas, C; Thomas, E; van Tilburg, J; Tisserand, V; Tobin, M; Tolk, S; Topp-Joergensen, S; Torr, N; Tournefier, E; Tourneur, S; Tran, M T; Tsaregorodtsev, A; Tuning, N; Ubeda Garcia, M; Ukleja, A; Uwer, U; Vagnoni, V; Valenti, G; Vazquez Gomez, R; Vazquez Regueiro, P; Vecchi, S; Velthuis, J J; Veltri, M; Veneziano, G; Vesterinen, M; Viaud, B; Videau, I; Vieira, D; Vilasis-Cardona, X; Visniakov, J; Vollhardt, A; Volyanskyy, D; Voong, D; Vorobyev, A; Vorobyev, V; Voß, C; Voss, H; Waldi, R; Wallace, R; Wandernoth, S; Wang, J; Ward, D R; Watson, N K; Webber, A D; Websdale, D; Whitehead, M; Wicht, J; Wiedner, D; Wiggers, L; Wilkinson, G; Williams, M P; Williams, M; Wilson, F F; Wishahi, J; Witek, M; Witzeling, W; Wotton, S A; Wright, S; Wu, S; Wyllie, K; Xie, Y; Xing, F; Xing, Z; Yang, Z; Young, R; Yuan, X; Yushchenko, O; Zangoli, M; Zavertyaev, M; Zhang, F; Zhang, L; Zhang, W C; Zhang, Y; Zhelezov, A; Zhong, L; Zvyagin, A

2012-01-01

A study of $D^+K_S^0$ and $D^0K^+$ final states is performed in a sample of 1.0 fb$^{-1}$ of $pp$ collision data collected at a centre-of-mass energy of $\\sqrt{s}=7$ TeV with the LHCb detector. We confirm the existence of the $D_{s1}^*(2700)^+$ and $D_{sJ}^*(2860)^+$ excited states and measure their masses and widths to be \\begin{eqnarray} m(D_{s1}^*(2700)^+) &=& 2709.2 \\pm 1.9(\\mbox{stat})\\pm\\,\\,\\,4.5(\\mbox{syst})~{\\rm MeV}/c^2,\\cr \\Gamma(D_{s1}^*(2700)^+) &=& \\,\\,\\,115.8 \\pm 7.3(\\mbox{stat}) \\pm12.1(\\mbox{syst})~{\\rm MeV}/c^2,\\cr m(D_{sJ}^*(2860)^+) &=& 2866.1 \\pm 1.0(\\mbox{stat}) \\pm\\,\\,\\,6.3(\\mbox{syst})~{\\rm MeV}/c^2,\\cr \\Gamma(D_{sJ}^*(2860)^+) &=& \\,\\,\\,\\,\\,\\,69.9 \\pm 3.2(\\mbox{stat}) \\pm\\,\\,\\,6.6(\\mbox{syst})~{\\rm MeV}/c^2.\\cr\

Estimating Single and Multiple Target Locations Using K-Means Clustering with Radio Tomographic Imaging in Wireless Sensor Networks

Science.gov (United States)

2015-03-26

clustering is an algorithm that has been used in data mining applications such as machine learning applications , pattern recognition, hyper-spectral imagery...42 3.7.2 Application of K-means Clustering . . . . . . . . . . . . . . . . . 42 3.8 Experiment Design...Tomographic Imaging WLAN Wireless Local Area Networks WSN Wireless Sensor Network xx ESTIMATING SINGLE AND MULTIPLE TARGET LOCATIONS USING K-MEANS CLUSTERING

Analysis of k-means clustering approach on the breast cancer Wisconsin dataset.

Science.gov (United States)

Dubey, Ashutosh Kumar; Gupta, Umesh; Jain, Sonal

2016-11-01

Breast cancer is one of the most common cancers found worldwide and most frequently found in women. An early detection of breast cancer provides the possibility of its cure; therefore, a large number of studies are currently going on to identify methods that can detect breast cancer in its early stages. This study was aimed to find the effects of k-means clustering algorithm with different computation measures like centroid, distance, split method, epoch, attribute, and iteration and to carefully consider and identify the combination of measures that has potential of highly accurate clustering accuracy. K-means algorithm was used to evaluate the impact of clustering using centroid initialization, distance measures, and split methods. The experiments were performed using breast cancer Wisconsin (BCW) diagnostic dataset. Foggy and random centroids were used for the centroid initialization. In foggy centroid, based on random values, the first centroid was calculated. For random centroid, the initial centroid was considered as (0, 0). The results were obtained by employing k-means algorithm and are discussed with different cases considering variable parameters. The calculations were based on the centroid (foggy/random), distance (Euclidean/Manhattan/Pearson), split (simple/variance), threshold (constant epoch/same centroid), attribute (2-9), and iteration (4-10). Approximately, 92 % average positive prediction accuracy was obtained with this approach. Better results were found for the same centroid and the highest variance. The results achieved using Euclidean and Manhattan were better than the Pearson correlation. The findings of this work provided extensive understanding of the computational parameters that can be used with k-means. The results indicated that k-means has a potential to classify BCW dataset.

K-means clustering for support construction in diffractive imaging.

Science.gov (United States)

Hattanda, Shunsuke; Shioya, Hiroyuki; Maehara, Yosuke; Gohara, Kazutoshi

2014-03-01

A method for constructing an object support based on K-means clustering of the object-intensity distribution is newly presented in diffractive imaging. This releases the adjustment of unknown parameters in the support construction, and it is well incorporated with the Gerchberg and Saxton diagram. A simple numerical simulation reveals that the proposed method is effective for dynamically constructing the support without an initial prior support.

K-nuclear bound states in a dynamical model

Czech Academy of Sciences Publication Activity Database

Mareš, Jiří; Friedman, E.; Gal, A.

2006-01-01

Roč. 770, 1/2 (2006), s. 84-105 ISSN 0375-9474 Institutional research plan: CEZ:AV0Z10480505 Keywords : kaonic atoms * K-nuclear bound states * K-nucleus interaction Subject RIV: BE - Theoretical Physics Impact factor: 2.155, year: 2006

K VijayRaghavan

Indian Academy of Sciences (India)

Volume 8 Issue 11 November 2003 pp 5-7 Article-in-a-Box. Thomas Hunt Morgan and Developmental Biology · K VijayRaghavan · More Details Fulltext PDF. Volume 13 Issue 10 October 2008 pp 909-915 General Article. Never Riding the Tide - Seymour Benzer–The Founder of Neurogenetics · K VijayRaghavan Veronica ...

P K Sumodan

Indian Academy of Sciences (India)

Home; Journals; Resonance – Journal of Science Education. P K Sumodan. Articles written in Resonance – Journal of Science Education. Volume 6 Issue 5 May 2001 pp 48-55 General Article. The Tiny Terminators - Mosquitoes and Diseases · P K Sumodan · More Details Fulltext PDF. Volume 7 Issue 8 August 2002 pp ...

A K Shukla

Indian Academy of Sciences (India)

Cars Beyond Otto's Internal Combustion Engines · A K Shukla · More Details Fulltext PDF. Volume 11 Issue 7 July 2006 pp 42-50 General Article. Turning Sunlight into Electricity - Inorganic Solar Cells and Beyond · A K Shukla · More Details Fulltext PDF. Volume 15 Issue 12 December 2010 pp 1068-1072 General Article.

KfK Nuclear Safety Project. First semiannual report 1985

International Nuclear Information System (INIS)

1985-11-01

The semiannual progress report 1985/1 is a description of work within the Nuclear Safety Project performed in the first six month of 1985 in the nuclear safety field by KfK institutes and departements and by external institutions on behalf of KfK. The chosen kind of this report is that of short summaries, containing the topics: work performed, results obtained and plans for future work. (orig./HP) [de

K2: A NEW METHOD FOR THE DETECTION OF GALAXY CLUSTERS BASED ON CANADA-FRANCE-HAWAII TELESCOPE LEGACY SURVEY MULTICOLOR IMAGES

International Nuclear Information System (INIS)

Thanjavur, Karun; Willis, Jon; Crampton, David

2009-01-01

We have developed a new method, K2, optimized for the detection of galaxy clusters in multicolor images. Based on the Red Sequence approach, K2 detects clusters using simultaneous enhancements in both colors and position. The detection significance is robustly determined through extensive Monte Carlo simulations and through comparison with available cluster catalogs based on two different optical methods, and also on X-ray data. K2 also provides quantitative estimates of the candidate clusters' richness and photometric redshifts. Initially, K2 was applied to the two color (gri) 161 deg 2 images of the Canada-France-Hawaii Telescope Legacy Survey Wide (CFHTLS-W) data. Our simulations show that the false detection rate for these data, at our selected threshold, is only ∼1%, and that the cluster catalogs are ∼80% complete up to a redshift of z = 0.6 for Fornax-like and richer clusters and to z ∼ 0.3 for poorer clusters. Based on the g-, r-, and i-band photometric catalogs of the Terapix T05 release, 35 clusters/deg 2 are detected, with 1-2 Fornax-like or richer clusters every 2 deg 2 . Catalogs containing data for 6144 galaxy clusters have been prepared, of which 239 are rich clusters. These clusters, especially the latter, are being searched for gravitational lenses-one of our chief motivations for cluster detection in CFHTLS. The K2 method can be easily extended to use additional color information and thus improve overall cluster detection to higher redshifts. The complete set of K2 cluster catalogs, along with the supplementary catalogs for the member galaxies, are available on request from the authors.

U.K. policy responses to international influences - nuclear power

International Nuclear Information System (INIS)

Jones, P.M.S.

1978-01-01

An account is given of U.K. participation in international discussions directed towards the safe development and application of nuclear power. Particular attention is given to the International Fuel Cycle Evaluation (INFCE), which is stated to be looking at the whole question of proliferation and the merits and disadvantages of a range of alternative fuel cycles and nuclear power strategies. A summary is also given of U.K. participation in work on radiological protection (through the I.C.R.P.) and radioactive waste disposal. International cooperation in research and development is mentioned. Public involvement in policy making is also discussed briefly. (U.K.)

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.

A K Mittal

Indian Academy of Sciences (India)

A K Mittal. Articles written in Resonance – Journal of Science Education. Volume 7 Issue 2 February 2002 pp 6-19 General Article. Fractals and the Large-Scale Structure in the Universe - Introduction and Basic Concepts · A K Mittal T R Seshadri · More Details Fulltext PDF. Volume 7 Issue 4 April 2002 pp 39-47 General ...

Anil K Rajvanshi

Indian Academy of Sciences (India)

Home; Journals; Resonance – Journal of Science Education. Anil K Rajvanshi. Articles written in Resonance – Journal of Science Education. Volume 12 Issue 3 March 2007 pp 4-12 General Article. Nikola Tesla – The Creator of the Electric Age · Anil K Rajvanshi · More Details Fulltext PDF. Volume 13 Issue 7 July 2008 pp ...

R K Laxman

Indian Academy of Sciences (India)

Home; Journals; Resonance – Journal of Science Education. R K Laxman. Articles written in Resonance – Journal of Science Education. Volume 1 Issue 4 April 1996 pp 4-4 Science Smiles. Chief Editor's column / Science Smiles · R K Laxman · More Details Fulltext PDF. Volume 1 Issue 5 May 1996 pp 3-3 Science Smiles.

K S Valdiya

Indian Academy of Sciences (India)

Home; Journals; Resonance – Journal of Science Education. K S Valdiya. Articles written in Resonance – Journal of Science Education. Volume 1 Issue 5 May 1996 pp 19-28 General Article. River Piracy Saraswati that Disappeared · K S Valdiya · More Details Fulltext PDF. Volume 1 Issue 8 August 1996 pp 55-63 General ...

K C Patil

Indian Academy of Sciences (India)

K C Patil. Articles written in Resonance – Journal of Science Education. Volume 9 Issue 7 July 2004 pp 92-92 Book Review. Inorganic Chemistry · K C Patil · More Details Fulltext PDF. Volume 20 Issue 5 May 2015 pp 431-444 General Article. High Energy Materials: A Brief History and Chemistry of Fireworks and Rocketry.

Efficient computation of k-Nearest Neighbour Graphs for large high-dimensional data sets on GPU clusters.

Directory of Open Access Journals (Sweden)

Ali Dashti

Full Text Available This paper presents an implementation of the brute-force exact k-Nearest Neighbor Graph (k-NNG construction for ultra-large high-dimensional data cloud. The proposed method uses Graphics Processing Units (GPUs and is scalable with multi-levels of parallelism (between nodes of a cluster, between different GPUs on a single node, and within a GPU. The method is applicable to homogeneous computing clusters with a varying number of nodes and GPUs per node. We achieve a 6-fold speedup in data processing as compared with an optimized method running on a cluster of CPUs and bring a hitherto impossible [Formula: see text]-NNG generation for a dataset of twenty million images with 15 k dimensionality into the realm of practical possibility.

Cluster emission at pre-equilibrium stage in Heavy Nuclear Reactions. A Model considering the Thermodynamics of Small Systems

International Nuclear Information System (INIS)

Bermudez Martinez, A.; Damiani, D.; Guzman Martinez, F.; Rodriguez Hoyos, O.; Rodriguez Manso, A.

2015-01-01

Cluster emission at pre-equilibrium stage, in heavy ion fusion reactions of 12 C and 16 O nuclei with 116 Sn, 208 Pb, 238 U are studied. the energy of the projectile nuclei was chosen at 0.25GeV, 0.5GeV and 1GeV. A cluster formation model is developed in order to calculate the cluster size. Thermodynamics of small systems was used in order to examine the cluster behavior inside the nuclear media. This model is based on considering two phases inside the compound nucleus, on one hand the nuclear media phase, and on the other hand the cluster itself. The cluster acts like an instability inside the compound nucleus, provoking an exchange of nucleons with the nuclear media through its surface. The processes were simulated using Monte Carlo methods. We obtained that the cluster emission probability shows great dependence on the cluster size. This project is aimed to implement cluster emission processes, during the pre-equilibrium stage, in the frame of CRISP code (Collaboration Rio-Sao Paulo). (Author)

Cluster formation restricts dynamic nuclear polarization of xenon in solid mixtures

DEFF Research Database (Denmark)

Kuzma, N. N.; Pourfathi, M.; Kara, H.

2012-01-01

During dynamic nuclear polarization (DNP) at 1.5 K and 5 T, Xe-129 nuclear magnetic resonance (NMR) spectra of a homogeneous xenon/1-propanol/trityl-radical solid mixture exhibit a single peak, broadened by H-1 neighbors. A second peak appears upon annealing for several hours at 125 K. Its...

[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.

K+ nucleus total cross section experiment and nuclear medium effects

International Nuclear Information System (INIS)

Weiss, Ruth.

1992-11-01

The low momentum K + is the weakest of the available strongly interacting particles. It has a mean bee path in nuclear matter of about 6 fm which makes it a good probe for studying properties of the nuclear interior. It allows one to build a good microscopic optical potential which can be used to calculate K + nucleus elastic and total cross sections. In the latter case the calculated ratio R T =[σ tot (K + A)/A]/[σ tot (K + d)/2] can be expected to be more reliable because some uncertainties in K + N phase shifts will cancel. This ratio can also be measured more reliably than the total cross sections themselves because of cancellation of some systematic errors. We measured the total cross sections of K + on D, 6 Li, 12 C, 28 Si and 40 Ca from 488 to 714 MeV/c. The emphasis was placed on extracting values of R T with a precision of better than 2 percent. The total cross section ratios are found to lie significantly above those predicted by optical potential calculations with the usual nuclear medium corrections. This suggests that novel phenomena are taking place within the nucleus. Several models which incorporate such phenomena are discussed, including nucleon 'swelling', mass rescaling, nuclear pions, and relativistic effects. (author) 31 refs., 27 figs., 21 tabs.,

Transcriptional organization of the DNA region controlling expression of the K99 gene cluster.

Science.gov (United States)

Roosendaal, B; Damoiseaux, J; Jordi, W; de Graaf, F K

1989-01-01

The transcriptional organization of the K99 gene cluster was investigated in two ways. First, the DNA region, containing the transcriptional signals was analyzed using a transcription vector system with Escherichia coli galactokinase (GalK) as assayable marker and second, an in vitro transcription system was employed. A detailed analysis of the transcription signals revealed that a strong promoter PA and a moderate promoter PB are located upstream of fanA and fanB, respectively. No promoter activity was detected in the intercistronic region between fanB and fanC. Factor-dependent terminators of transcription were detected and are probably located in the intercistronic region between fanA and fanB (T1), and between fanB and fanC (T2). A third terminator (T3) was observed between fanC and fanD and has an efficiency of 90%. Analysis of the regulatory region in an in vitro transcription system confirmed the location of the respective transcription signals. A model for the transcriptional organization of the K99 cluster is presented. Indications were obtained that the trans-acting regulatory polypeptides FanA and FanB both function as anti-terminators. A model for the regulation of expression of the K99 gene cluster is postulated.

Metal cluster compounds - chemistry and importance; clusters containing isolated main group element atoms, large metal cluster compounds, cluster fluxionality

International Nuclear Information System (INIS)

Walther, B.

1988-01-01

This part of the review on metal cluster compounds deals with clusters containing isolated main group element atoms, with high nuclearity clusters and metal cluster fluxionality. It will be obvious that main group element atoms strongly influence the geometry, stability and reactivity of the clusters. High nuclearity clusters are of interest in there own due to the diversity of the structures adopted, but their intermediate position between molecules and the metallic state makes them a fascinating research object too. These both sites of the metal cluster chemistry as well as the frequently observed ligand and core fluxionality are related to the cluster metal and surface analogy. (author)

Structures of three different neutral polysaccharides of Acinetobacter baumannii, NIPH190, NIPH201, and NIPH615, assigned to K30, K45, and K48 capsule types, respectively, based on capsule biosynthesis gene clusters.

Science.gov (United States)

Shashkov, Alexander S; Kenyon, Johanna J; Arbatsky, Nikolay P; Shneider, Mikhail M; Popova, Anastasiya V; Miroshnikov, Konstantin A; Volozhantsev, Nikolay V; Knirel, Yuriy A

2015-11-19

Neutral capsular polysaccharides (CPSs) were isolated from Acinetobacter baumannii NIPH190, NIPH201, and NIPH615. The CPSs were found to contain common monosaccharides only and to be branched with a side-chain 1→3-linked β-d-glucopyranose residue. Structures of the oligosaccharide repeat units (K units) of the CPSs were elucidated by 1D and 2D (1)H and (13)C NMR spectroscopy. Novel CPS biosynthesis gene clusters, designated KL30, KL45, and KL48, were found at the K locus in the genome sequences of NIPH190, NIPH201, and NIPH615, respectively. The genetic content of each gene cluster correlated with the structure of the CPS unit established, and therefore, the capsular types of the strains studied were designated as K30, K45, and K48, respectively. The initiating sugar of each K unit was predicted, and glycosyltransferases encoded by each gene cluster were assigned to the formation of the linkages between sugars in the corresponding K unit. Copyright © 2015 Elsevier Ltd. All rights reserved.

Nucleus and cytoplasm segmentation in microscopic images using K-means clustering and region growing.

Science.gov (United States)

Sarrafzadeh, Omid; Dehnavi, Alireza Mehri

2015-01-01

Segmentation of leukocytes acts as the foundation for all automated image-based hematological disease recognition systems. Most of the time, hematologists are interested in evaluation of white blood cells only. Digital image processing techniques can help them in their analysis and diagnosis. The main objective of this paper is to detect leukocytes from a blood smear microscopic image and segment them into their two dominant elements, nucleus and cytoplasm. The segmentation is conducted using two stages of applying K-means clustering. First, the nuclei are segmented using K-means clustering. Then, a proposed method based on region growing is applied to separate the connected nuclei. Next, the nuclei are subtracted from the original image. Finally, the cytoplasm is segmented using the second stage of K-means clustering. The results indicate that the proposed method is able to extract the nucleus and cytoplasm regions accurately and works well even though there is no significant contrast between the components in the image. In this paper, a method based on K-means clustering and region growing is proposed in order to detect leukocytes from a blood smear microscopic image and segment its components, the nucleus and the cytoplasm. As region growing step of the algorithm relies on the information of edges, it will not able to separate the connected nuclei more accurately in poor edges and it requires at least a weak edge to exist between the nuclei. The nucleus and cytoplasm segments of a leukocyte can be used for feature extraction and classification which leads to automated leukemia detection.

Sleep stages identification in patients with sleep disorder using k-means clustering

Science.gov (United States)

Fadhlullah, M. U.; Resahya, A.; Nugraha, D. F.; Yulita, I. N.

2018-05-01

Data mining is a computational intelligence discipline where a large dataset processed using a certain method to look for patterns within the large dataset. This pattern then used for real time application or to develop some certain knowledge. This is a valuable tool to solve a complex problem, discover new knowledge, data analysis and decision making. To be able to get the pattern that lies inside the large dataset, clustering method is used to get the pattern. Clustering is basically grouping data that looks similar so a certain pattern can be seen in the large data set. Clustering itself has several algorithms to group the data into the corresponding cluster. This research used data from patients who suffer sleep disorders and aims to help people in the medical world to reduce the time required to classify the sleep stages from a patient who suffers from sleep disorders. This study used K-Means algorithm and silhouette evaluation to find out that 3 clusters are the optimal cluster for this dataset which means can be divided to 3 sleep stages.

Nuclear thermal rocket clustering: 1, A summary of previous work and relevant issues

International Nuclear Information System (INIS)

Buksa, J.J.; Houts, M.G.

1991-01-01

A general review of the technical merits of nuclear thermal rocket clustering is presented. A summary of previous analyses performed during the Rover program is presented and used to assess clustering in the context of projected Space Exploration Initiative missions. A number of technical issues are discussed including cluster reliability, engine-out operation, neutronic coupling, shutdown core power generation, shutdown reactivity requirements, reactor kinetics, and radiation shielding. 7 refs., 3 figs., 2 tabs

Nuclear cluster states

International Nuclear Information System (INIS)

Rae, W.D.M.; Merchant, A.C.

1993-01-01

We review clustering in light nuclei including molecular resonances in heavy ion reactions. In particular we study the systematics, paying special attention to the relationships between cluster states and superdeformed configurations. We emphasise the selection rules which govern the formation and decay of cluster states. We review some recent experimental results from Daresbury and elsewhere. In particular we report on the evidence for a 7-α chain state in 28 Si in experiments recently performed at the NSF, Daresbury. Finally we begin to address theoretically the important question of the lifetimes of cluster states as deduced from the experimental energy widths of the resonances. (Author)

The electron screening puzzle and nuclear clustering

International Nuclear Information System (INIS)

Spitaleri, C.; Bertulani, C.A.; Fortunato, L.; Vitturi, A.

2016-01-01

Accurate measurements of nuclear reactions of astrophysical interest within, or close to, the Gamow peak show evidence of an unexpected effect attributed to the presence of atomic electrons in the target. The experiments need to include an effective “screening” potential to explain the enhancement of the cross sections at the lowest measurable energies. Despite various theoretical studies conducted over the past 20 years and numerous experimental measurements, a theory has not yet been found that can explain the cause of the exceedingly high values of the screening potential needed to explain the data. In this letter we show that instead of an atomic physics solution of the “electron screening puzzle”, the reason for the large screening potential values is in fact due to clusterization effects in nuclear reactions, in particular for reaction involving light nuclei.

The electron screening puzzle and nuclear clustering

Energy Technology Data Exchange (ETDEWEB)

Spitaleri, C., E-mail: spitaleri@lns.infn.it [Department of Physics and Astronomy, University of Catania, Catania (Italy); INFN-Laboratori Nazionali del Sud, Catania (Italy); Bertulani, C.A. [Department of Physics and Astronomy, Texas A& M University-Commerce, Commerce, TX 75429 (United States); Department of Physics and Astronomy, Texas A& M University, College Station, TX 77843 (United States); Fortunato, L.; Vitturi, A. [Dipartimento di Fisica e Astronomia “Galileo Galilei”, Università di Padova, via Marzolo, 8, I-35131 Padova (Italy); INFN, Sezione di Padova, via Marzolo, 8, I-35131 Padova (Italy)

2016-04-10

Accurate measurements of nuclear reactions of astrophysical interest within, or close to, the Gamow peak show evidence of an unexpected effect attributed to the presence of atomic electrons in the target. The experiments need to include an effective “screening” potential to explain the enhancement of the cross sections at the lowest measurable energies. Despite various theoretical studies conducted over the past 20 years and numerous experimental measurements, a theory has not yet been found that can explain the cause of the exceedingly high values of the screening potential needed to explain the data. In this letter we show that instead of an atomic physics solution of the “electron screening puzzle”, the reason for the large screening potential values is in fact due to clusterization effects in nuclear reactions, in particular for reaction involving light nuclei.

Segmentation of Mushroom and Cap width Measurement using Modified K-Means Clustering Algorithm

Directory of Open Access Journals (Sweden)

Eser Sert

2014-01-01

Full Text Available Mushroom is one of the commonly consumed foods. Image processing is one of the effective way for examination of visual features and detecting the size of a mushroom. We developed software for segmentation of a mushroom in a picture and also to measure the cap width of the mushroom. K-Means clustering method is used for the process. K-Means is one of the most successful clustering methods. In our study we customized the algorithm to get the best result and tested the algorithm. In the system, at first mushroom picture is filtered, histograms are balanced and after that segmentation is performed. Results provided that customized algorithm performed better segmentation than classical K-Means algorithm. Tests performed on the designed software showed that segmentation on complex background pictures is performed with high accuracy, and 20 mushrooms caps are measured with 2.281 % relative error.

Classification of Two Class Motor Imagery Tasks Using Hybrid GA-PSO Based K-Means Clustering.

Science.gov (United States)

Suraj; Tiwari, Purnendu; Ghosh, Subhojit; Sinha, Rakesh Kumar

2015-01-01

Transferring the brain computer interface (BCI) from laboratory condition to meet the real world application needs BCI to be applied asynchronously without any time constraint. High level of dynamism in the electroencephalogram (EEG) signal reasons us to look toward evolutionary algorithm (EA). Motivated by these two facts, in this work a hybrid GA-PSO based K-means clustering technique has been used to distinguish two class motor imagery (MI) tasks. The proposed hybrid GA-PSO based K-means clustering is found to outperform genetic algorithm (GA) and particle swarm optimization (PSO) based K-means clustering techniques in terms of both accuracy and execution time. The lesser execution time of hybrid GA-PSO technique makes it suitable for real time BCI application. Time frequency representation (TFR) techniques have been used to extract the feature of the signal under investigation. TFRs based features are extracted and relying on the concept of event related synchronization (ERD) and desynchronization (ERD) feature vector is formed.

Hopfield-K-Means clustering algorithm: A proposal for the segmentation of electricity customers

Energy Technology Data Exchange (ETDEWEB)

Lopez, Jose J.; Aguado, Jose A.; Martin, F.; Munoz, F.; Rodriguez, A.; Ruiz, Jose E. [Department of Electrical Engineering, University of Malaga, C/ Dr. Ortiz Ramos, sn., Escuela de Ingenierias, 29071 Malaga (Spain)

2011-02-15

Customer classification aims at providing electric utilities with a volume of information to enable them to establish different types of tariffs. Several methods have been used to segment electricity customers, including, among others, the hierarchical clustering, Modified Follow the Leader and K-Means methods. These, however, entail problems with the pre-allocation of the number of clusters (Follow the Leader), randomness of the solution (K-Means) and improvement of the solution obtained (hierarchical algorithm). Another segmentation method used is Hopfield's autonomous recurrent neural network, although the solution obtained only guarantees that it is a local minimum. In this paper, we present the Hopfield-K-Means algorithm in order to overcome these limitations. This approach eliminates the randomness of the initial solution provided by K-Means based algorithms and it moves closer to the global optimun. The proposed algorithm is also compared against other customer segmentation and characterization techniques, on the basis of relative validation indexes. Finally, the results obtained by this algorithm with a set of 230 electricity customers (residential, industrial and administrative) are presented. (author)

Hopfield-K-Means clustering algorithm: A proposal for the segmentation of electricity customers

International Nuclear Information System (INIS)

Lopez, Jose J.; Aguado, Jose A.; Martin, F.; Munoz, F.; Rodriguez, A.; Ruiz, Jose E.

2011-01-01

Customer classification aims at providing electric utilities with a volume of information to enable them to establish different types of tariffs. Several methods have been used to segment electricity customers, including, among others, the hierarchical clustering, Modified Follow the Leader and K-Means methods. These, however, entail problems with the pre-allocation of the number of clusters (Follow the Leader), randomness of the solution (K-Means) and improvement of the solution obtained (hierarchical algorithm). Another segmentation method used is Hopfield's autonomous recurrent neural network, although the solution obtained only guarantees that it is a local minimum. In this paper, we present the Hopfield-K-Means algorithm in order to overcome these limitations. This approach eliminates the randomness of the initial solution provided by K-Means based algorithms and it moves closer to the global optimun. The proposed algorithm is also compared against other customer segmentation and characterization techniques, on the basis of relative validation indexes. Finally, the results obtained by this algorithm with a set of 230 electricity customers (residential, industrial and administrative) are presented. (author)

What to Do When K-Means Clustering Fails: A Simple yet Principled Alternative Algorithm.

Science.gov (United States)

Raykov, Yordan P; Boukouvalas, Alexis; Baig, Fahd; Little, Max A

The K-means algorithm is one of the most popular clustering algorithms in current use as it is relatively fast yet simple to understand and deploy in practice. Nevertheless, its use entails certain restrictive assumptions about the data, the negative consequences of which are not always immediately apparent, as we demonstrate. While more flexible algorithms have been developed, their widespread use has been hindered by their computational and technical complexity. Motivated by these considerations, we present a flexible alternative to K-means that relaxes most of the assumptions, whilst remaining almost as fast and simple. This novel algorithm which we call MAP-DP (maximum a-posteriori Dirichlet process mixtures), is statistically rigorous as it is based on nonparametric Bayesian Dirichlet process mixture modeling. This approach allows us to overcome most of the limitations imposed by K-means. The number of clusters K is estimated from the data instead of being fixed a-priori as in K-means. In addition, while K-means is restricted to continuous data, the MAP-DP framework can be applied to many kinds of data, for example, binary, count or ordinal data. Also, it can efficiently separate outliers from the data. This additional flexibility does not incur a significant computational overhead compared to K-means with MAP-DP convergence typically achieved in the order of seconds for many practical problems. Finally, in contrast to K-means, since the algorithm is based on an underlying statistical model, the MAP-DP framework can deal with missing data and enables model testing such as cross validation in a principled way. We demonstrate the simplicity and effectiveness of this algorithm on the health informatics problem of clinical sub-typing in a cluster of diseases known as parkinsonism.

Photooxidation behaviour of HMS-PP

International Nuclear Information System (INIS)

Oliani, Washington L.; Parra, Duclerc F.; Lima, Luis F.C.P.; Lugao, Ademar B.

2009-01-01

The radiation process has played an important role to produce polymers with controlled rheological properties. The main scope of the study is to evaluate the stability of High melt strength polypropylene (HMS-PP) prepared by gamma irradiation of PP (spheres) under acetylene atmosphere followed by a heating step to terminate reactions, in different doses of 12.5 kGy and 20 kGy. The samples submitted to the natural ageing for a period of one year were characterized by: thermogravimetry (TG), differential scanning calorimetry (DSC), infrared spectroscopy (FTIR) and scanning electron microscopy (SEM). The fundamental process that is believed to be the most significant in the mechanism of photooxidative degradation is the formation of hydroperoxides. The high energy UV light is capable of initiating bond scission within the polymer backbone, which leads to further chemical modification of the bonds via scissions and chain reactions through formation of radical species. The results showed that in pristine and HMS-PP samples exposed to UV radiation, oxidation reactions occur, resulting in chain scissions. The reactions occur preferentially in the amorphous phase owing to the higher permeability of oxygen. (author)

Sistem Pendukung Keputusan Pemilihan Line-up Pemain Sepak Bola Menggunakan Metode Fuzzy Multiple Attribute Decision Making dan K-Means Clustering

Directory of Open Access Journals (Sweden)

Aldi Nurzahputra

2017-07-01

Full Text Available In football, the selection of players line-up is based on their statistical performance. In this research, the line-up selection can implement the decision support system (DSS with FMADM SAW method. The criterias were used are goal, assists, saves, clean sheets, yellow cards, red cards, games, and an own goal. Then, the assessment players performance is using K-Means Clustering. There are two clusters: cluster_cukup and cluster_baik. The system used Manchester City player data in Forward, Mildfilder, Defender and Goal Keeper position. The purpose of this research is applying the FMADM and K-Means Clustering method to the system. Based on the results, the line-up selection can be processed by FMADM method and the performance assessed by K-Means Clustering method. By using the system, the selection and the assessment can be conducted and give the best decision for footbal coach objectively. Dalam sepak bola, pemilihan line-up pemain oleh pelatih dilakukan berdasarkan statistik yang dimiliki pemain. Penelitian ini menerapkan sistem pendukung keputusan (SPK dengan metode FMADM SAW untuk memilih pemain dari hasil pembobotan dari beberapa kriteria, yaitu goal, assist, saves, clean sheet, kartu kuning, kartu merah, main, dan gol bunuh diri. Penilaian performa pemain menggunakan metode K-Means clustering dengan dua cluster, yaitu cluster_cukup dan cluster_baik. Data yang digunakan dalam sistem ini menggunakan data pemain club Manchester City dengan posisi Forward, Mildfilder, Defender, dan Goal Keeper. Berdasarkan hasil yang diteliti, data statistik pemain dapat diolah dengan metode FMADM dan penilaian performa dengan metode K-Means clustering. Dengan adanya sistem ini, pemilihan dan penilaian dilakukan secara objektif dan memberikan pilihan untuk pelatih dalam mengambil keputusan.

The quantitative assessment of the role played by basic amino acid clusters in the nuclear uptake of human ribosomal protein L7

International Nuclear Information System (INIS)

Tai, Lin-Ru; Chou, Chang-Wei; Lee, I-Fang; Kirby, Ralph; Lin, Alan

2013-01-01

In this study, we used a multiple copy (EGFP) 3 reporter system to establish a numeric nuclear index system to assess the degree of nuclear import. The system was first validated by a FRAP assay, and then was applied to evaluate the essential and multifaceted nature of basic amino acid clusters during the nuclear import of ribosomal protein L7. The results indicate that the sequence context of the basic cluster determines the degree of nuclear import, and that the number of basic residues in the cluster is irrelevant; rather the position of the pertinent basic residues is crucial. Moreover, it also found that the type of carrier protein used by basic cluster has a great impact on the degree of nuclear import. In case of L7, importin β2 or importin β3 are preferentially used by clusters with a high import efficiency, notwithstanding that other importins are also used by clusters with a weaker level of nuclear import. Such a preferential usage of multiple basic clusters and importins to gain nuclear entry would seem to be a common practice among ribosomal proteins in order to ensure their full participation in high rate ribosome synthesis. - Highlights: ► We introduce a numeric index system that represents the degree of nuclear import. ► The rate of nuclear import is dictated by the sequence context of the basic cluster. ► Importin β2 and β3 were mainly responsible for the N4 mediated nuclear import

The quantitative assessment of the role played by basic amino acid clusters in the nuclear uptake of human ribosomal protein L7

Energy Technology Data Exchange (ETDEWEB)

Tai, Lin-Ru [Institute of Genome Sciences, National Yang-Ming University, Taipei, Taiwan, ROC (China); Chou, Chang-Wei [Institute of Clinical Dentistry Science, National Yang-Ming University, Taipei, Taiwan, ROC (China); Lee, I-Fang; Kirby, Ralph [Institute of Genome Sciences, National Yang-Ming University, Taipei, Taiwan, ROC (China); Lin, Alan, E-mail: alin@ym.edu.tw [Institute of Genome Sciences, National Yang-Ming University, Taipei, Taiwan, ROC (China); Institute of Clinical Dentistry Science, National Yang-Ming University, Taipei, Taiwan, ROC (China)

2013-02-15

In this study, we used a multiple copy (EGFP){sub 3} reporter system to establish a numeric nuclear index system to assess the degree of nuclear import. The system was first validated by a FRAP assay, and then was applied to evaluate the essential and multifaceted nature of basic amino acid clusters during the nuclear import of ribosomal protein L7. The results indicate that the sequence context of the basic cluster determines the degree of nuclear import, and that the number of basic residues in the cluster is irrelevant; rather the position of the pertinent basic residues is crucial. Moreover, it also found that the type of carrier protein used by basic cluster has a great impact on the degree of nuclear import. In case of L7, importin β2 or importin β3 are preferentially used by clusters with a high import efficiency, notwithstanding that other importins are also used by clusters with a weaker level of nuclear import. Such a preferential usage of multiple basic clusters and importins to gain nuclear entry would seem to be a common practice among ribosomal proteins in order to ensure their full participation in high rate ribosome synthesis. - Highlights: ► We introduce a numeric index system that represents the degree of nuclear import. ► The rate of nuclear import is dictated by the sequence context of the basic cluster. ► Importin β2 and β3 were mainly responsible for the N4 mediated nuclear import.

A full-configuration-interaction nuclear orbital approach and application for small doped He clusters

Energy Technology Data Exchange (ETDEWEB)

Lara-Castells, M. P. de, E-mail: delara@iff.csic.es; Aguirre, N. F., E-mail: delara@iff.csic.es; Delgado-Barrio, G., E-mail: delara@iff.csic.es; Villarreal, P., E-mail: delara@iff.csic.es [Instituto de Física Fundamental (CSIC), Serrano 123, 28006 Madrid (Spain); Mitrushchenkov, A. O. [Université Paris-Est, Laboratoire Modélisation et Simulation Multi Echelle, MSME UMR 8208 CNRS, 5 bd Descartes, 77454 Marne-la-Vallée (France)

2015-01-22

An efficient full-configuration-interaction 'nuclear orbital' treatment was developed as a benchmark quantum-chemistry-like method to calculate, ground and excited, fermionic 'solvent' wave-functions and applied to {sup 3}He{sub N} clusters with atomic or molecular impurities [J. Chem. Phys. (Communication) 125, 221101 (2006)]. The main difficulty in handling doped {sup 3}He{sub N} clusters lies in the Fermi-Dirac nuclear statistics, the wide amplitudes of the He-dopant and He-He motions, and the hard-core He-He interaction at short distances. This paper overviews the theoretical approach and its recent applications to energetic, structural and spectroscopic aspects of different dopant-{sup 3}He{sub N} clusters. Preliminary results by using the latest version of the FCI-NO computational implementation, to bosonic Cl{sub 2}(X)-({sup 4}He){sub N} clusters, are also shown.

Analysis of forward and near-forward elastic-scattering amplitudes for pp and anti pp collisions

International Nuclear Information System (INIS)

Block, M.B.; Cahn, R.N.

1983-04-01

We will present the results of two recently published (1983) papers by M.M. Block and R.N. Cahn, which analyze for anti pp and pp elastic scattering the rho values (ratios of the real to the imaginary parts of the forward nuclear scattering amplitudes), the total (hadronic) cross sections sigma, and the b values, the nuclear slope parameters. The predictions of the analyses, from √ s bar > 5 GeV, is compared with the recently measured values of sigma and b at the SPS Collider. The analysis has also been redone to include new ISR data available from R211 at √ s bar = 62.5 GeV, in order to estimate odderon contributions, i.e., contributions from odd amplitudes with unconventional (non-Reggeon) energy dependence. Limits of approx. 1% are placed on these amplitudes. Our analysis has been extrapolated up to 100 TeV, to give sigma, rho and b predictions for cosmic ray and future collider energies

Automatic classification of canine PRG neuronal discharge patterns using K-means clustering.

Science.gov (United States)

Zuperku, Edward J; Prkic, Ivana; Stucke, Astrid G; Miller, Justin R; Hopp, Francis A; Stuth, Eckehard A

2015-02-01

Respiratory-related neurons in the parabrachial-Kölliker-Fuse (PB-KF) region of the pons play a key role in the control of breathing. The neuronal activities of these pontine respiratory group (PRG) neurons exhibit a variety of inspiratory (I), expiratory (E), phase spanning and non-respiratory related (NRM) discharge patterns. Due to the variety of patterns, it can be difficult to classify them into distinct subgroups according to their discharge contours. This report presents a method that automatically classifies neurons according to their discharge patterns and derives an average subgroup contour of each class. It is based on the K-means clustering technique and it is implemented via SigmaPlot User-Defined transform scripts. The discharge patterns of 135 canine PRG neurons were classified into seven distinct subgroups. Additional methods for choosing the optimal number of clusters are described. Analysis of the results suggests that the K-means clustering method offers a robust objective means of both automatically categorizing neuron patterns and establishing the underlying archetypical contours of subtypes based on the discharge patterns of group of neurons. Published by Elsevier B.V.

Coexistence of cluster structure and superdeformation in {sup 44}Ti

Energy Technology Data Exchange (ETDEWEB)

Kimura, Masaaki [Yukawa Institute for Theoretical Physics, Kyoto University, Kyoto 606-8502 (Japan)]. E-mail: masaaki@yukawa.kyoto-u.ac.jp; Horiuchi, Hisashi [Department of Physics, Kyoto University, Kyoto 606-8502 (Japan)

2006-03-06

The nucleus {sup 44}Ti has low-lying levels of various kinds of mutually very different nuclear structure displaying the richness of the nuclear many-body dynamics. It is shown that the deformed-basis antisymmetrized molecular dynamics by the use of the Gogny D1S force reproduces successfully and unifiedly two types of coexistence phenomena in {sup 44}Ti. Namely, on one hand, the coexistence of the mean-field structure and the cluster structure is confirmed by verifying the normally deformed structure of the K{sup {pi}}=3{sub 1}{sup -} band with a 1-particle-1-hole intrinsic configuration and the {alpha}+Ca40 cluster structure of the K{sup {pi}}=0{sub 2}{sup -} band. The mixed character of the mean-field-like structure and the {alpha}+Ca40 cluster structure of the ground band is also shown. On the other hand, the coexistence of the normal deformed mean-field and the superdeformed mean-field is confirmed by verifying the triaxial superdeformation of the K{sup {pi}}=0{sub 2}{sup +} band and the K{sup {pi}}=2{sub 1}{sup +} band which has a 4-particle-4-hole intrinsic configuration. Good reproduction of the experimental data is shown for many kinds of quantities including the energy spectra, electric transition rates, alpha spectroscopic factors. Preliminary discussions are given on the existence of hyperdeformed excited states, the relation between superdeformation and clustering and so on.

K2 and M4: A Unique Opportunity to Unlock the Mysteries of Globular Clusters

Science.gov (United States)

Kuehn, Charles A.; Stello, Dennis; Campbell, Simon; Drury, Jason; de Silva, Gayandhi; Maclean, Ben; Bedding, Timothy R.; Huber, Daniel

2016-01-01

One of the most exciting opportunities presented by K2 is the ability to study variable stars in globular clusters (GCs). The K2 observations allow us to perform ensemble asteroseismology of a population that is much older than that in the open clusters in the original Kepler field. This should help us answer long-standing questions concerning mass loss on the red giant branch and the spread in masses along the horizontal branch. By combining the asteroseismic data with chemical tagging of sub-populations from spectroscopy, we hope to better constrain stellar evolution models and potentially shed some light on the formation history of GCs. The very crowded nature of stars in GCs poses a challenge, however, due to Kepler's large pixels. M4, observed during K2's campaign 2, presents an excellent opportunity to study GCs with a combination of K2 and ground-based data. M4 is one of the two nearest GCs and thus should appear less crowded and brighter; in fact M4 is likely the only GC whose horizontal branch stars, other than RR Lyraes, will be accessible with K2. We discuss our method of obtaining photometry for the stars in M4 and present sample lightcurves for different classes of oscillating stars in the cluster. We also discuss efforts to use ground-based observations to increase the utility of the K2 dataset.

Effects of inorganic nitrogen sources on the production of PP-V [(10Z)-12-carboxyl-monascorubramine] and the Expression of the nitrate assimilation gene cluster by Penicillium sp. AZ.

Science.gov (United States)

Arai, Teppei; Umemura, Sara; Ota, Tamaki; Ogihara, Jun; Kato, Jun; Kasumi, Takafumi

2012-01-01

A fungal strain, Penicillium sp. AZ, produced the azaphilone Monascus pigment homolog when cultured in a medium composed of soluble starch, ammonium nitrate, yeast extract, and citrate buffer, pH 5.0. One of the typical features of violet pigment PP-V [(10Z)-12-carboxyl-monascorubramine] is that pyranoid oxygen is replaced with nitrogen. In this study, we found that ammonia and nitrate nitrogen are available for PP-V biosynthesis, and that ammonia nitrogen was much more effective than nitrate nitrogen. Further, we isolated nitrate assimilation gene cluster, niaD, niiA, and crnA, and analyzed the expression of these genes. The expression levels of all these genes increased with sodium nitrate addition to the culture medium. The results obtained here strongly suggest that Penicillium sp. AZ produced PP-V using nitrate in the form of ammonium reduced from nitrate through a bioprocess assimilatory reaction.

The updated NAA nuclear data library derived from the Y2K k0-database

International Nuclear Information System (INIS)

Corte, F. De

2003-01-01

Values of 2200 m x s -1 cross sections, together with the associated nuclear data, are tabulated for 128 (n,γ) reactions of interest in NAA. The values are derived from the Y2K database of experimentally measured k 0 -factors. (author)

Placental Protein 13 (PP13 – a placental immunoregulatory galectin protecting pregnancy

Directory of Open Access Journals (Sweden)

Nandor Gabor Than

2014-08-01

Full Text Available Galectins are glycan-binding proteins that regulate innate and adaptive immune responses, and some confer maternal-fetal immune tolerance in eutherian mammals. A chromosome 19 cluster of galectins has emerged in anthropoid primates, species with deep placentation and long gestation. Three of the five human cluster galectins are solely expressed in the placenta, where they may confer additional immunoregulatory functions to enable deep placentation. One of these is galectin-13, also known as Placental Protein 13 (PP13. It has a jelly-roll fold, carbohydrate-recognition domain and sugar-binding preference resembling to other mammalian galectins. PP13 is predominantly expressed by the syncytiotrophoblast and released from the placenta into the maternal circulation. Its ability to induce apoptosis of activated T cells in vitro, and to divert and kill T cells as well as macrophages in the maternal decidua in situ suggests important immune functions. Indeed, mutations in the promoter and an exon of LGALS13 presumably leading to altered or non-functional protein expression are associated with a higher frequency of preeclampsia and other obstetrical syndromes, which involve immune dysregulation. Moreover, decreased placental expression of PP13 and its low first trimester maternal serum concentrations are associated with elevated risk of preeclampsia. Indeed, PP13 turned to be a good early biomarker to assess maternal risk for the subsequent development of pregnancy complications caused by impaired placentation. Due to the ischemic placental stress in preterm preeclampsia, there is an increased trophoblastic shedding of PP13 immunopositive microvesicles starting in the second trimester, which leads to high maternal blood PP13 concentrations. Our meta-analysis suggests that this phenomenon may enable the potential use of PP13 in directing patient management near to or at the time of delivery. Recent findings on the beneficial effects of PP13 on decreasing

Probing the nuclear medium with the K+ meson

International Nuclear Information System (INIS)

Chrien, R.E.

1995-01-01

Elastic differential cross sections for K + mesons scattered from targets of carbon and 6 Li have been measured at an incident momentum of 715 MeV/c. The ratios of scattering cross sections from these targets are not predicted by theory, and are consistent with earlier suggestions that the K + -nucleon interaction is modified in the nuclear medium

Conveyor Performance based on Motor DC 12 Volt Eg-530ad-2f using K-Means Clustering

Science.gov (United States)

Arifin, Zaenal; Artini, Sri DP; Much Ibnu Subroto, Imam

2017-04-01

To produce goods in industry, a controlled tool to improve production is required. Separation process has become a part of production process. Separation process is carried out based on certain criteria to get optimum result. By knowing the characteristics performance of a controlled tools in separation process the optimum results is also possible to be obtained. Clustering analysis is popular method for clustering data into smaller segments. Clustering analysis is useful to divide a group of object into a k-group in which the member value of the group is homogeny or similar. Similarity in the group is set based on certain criteria. The work in this paper based on K-Means method to conduct clustering of loading in the performance of a conveyor driven by a dc motor 12 volt eg-530-2f. This technique gives a complete clustering data for a prototype of conveyor driven by dc motor to separate goods in term of height. The parameters involved are voltage, current, time of travelling. These parameters give two clusters namely optimal cluster with center of cluster 10.50 volt, 0.3 Ampere, 10.58 second, and unoptimal cluster with center of cluster 10.88 volt, 0.28 Ampere and 40.43 second.

K-Nearest Neighbor Intervals Based AP Clustering Algorithm for Large Incomplete Data

Directory of Open Access Journals (Sweden)

Cheng Lu

2015-01-01

Full Text Available The Affinity Propagation (AP algorithm is an effective algorithm for clustering analysis, but it can not be directly applicable to the case of incomplete data. In view of the prevalence of missing data and the uncertainty of missing attributes, we put forward a modified AP clustering algorithm based on K-nearest neighbor intervals (KNNI for incomplete data. Based on an Improved Partial Data Strategy, the proposed algorithm estimates the KNNI representation of missing attributes by using the attribute distribution information of the available data. The similarity function can be changed by dealing with the interval data. Then the improved AP algorithm can be applicable to the case of incomplete data. Experiments on several UCI datasets show that the proposed algorithm achieves impressive clustering results.

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...

Forward-backward multiplicity correlations and the clusterization

International Nuclear Information System (INIS)

Kostenko, B.F.; Musul'manbekov, Zh.Zh.

1990-01-01

An analysis of the forward-backward multiplicity correlations for pp- and p-barp-collisions has been fulfilled in the framework of the statistical cluster model. Connection between the strength of correlations and sizes of clusters is investigated. The dependence of masses and sizes of clusters on the energy of colliding hadrons is obtained. 15 refs.; 9 figs.; 1 tab

R K Shyamasundar

Indian Academy of Sciences (India)

. Articles written in Resonance – Journal of Science Education. Volume 1 Issue 1 January 1996 pp 20-27 Series Article. Algorithms Introduction to Algorithms · R K Shyamasundar · More Details Fulltext PDF. Volume 1 Issue 3 March 1996 pp ...

Privacy-Preserving k-Means Clustering under Multiowner Setting in Distributed Cloud Environments

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Hong Rong

2017-01-01

Full Text Available With the advent of big data era, clients who lack computational and storage resources tend to outsource data mining tasks to cloud service providers in order to improve efficiency and reduce costs. It is also increasingly common for clients to perform collaborative mining to maximize profits. However, due to the rise of privacy leakage issues, the data contributed by clients should be encrypted using their own keys. This paper focuses on privacy-preserving k-means clustering over the joint datasets encrypted under multiple keys. Unfortunately, existing outsourcing k-means protocols are impractical because not only are they restricted to a single key setting, but also they are inefficient and nonscalable for distributed cloud computing. To address these issues, we propose a set of privacy-preserving building blocks and outsourced k-means clustering protocol under Spark framework. Theoretical analysis shows that our scheme protects the confidentiality of the joint database and mining results, as well as access patterns under the standard semihonest model with relatively small computational overhead. Experimental evaluations on real datasets also demonstrate its efficiency improvements compared with existing approaches.

Nuclear fusion project. Semi-annual report of the Association KfK/EURATOM

International Nuclear Information System (INIS)

1986-11-01

Nuclear fusion is one of the main activities of the Karlsruhe Nuclear Research Center (KfK). It is organized as a project under the Directorate of Reactor Development and Safety. The work of KfK concentrates on technology aspects of nuclear fusion with magnetic confinement. It is part of the European Fusion Programme where KfK participates as an association to EURATOM. Close links have been established to the Max Planck Institute for Plasma Physics (IPP). In the Entwicklungsgemeinschaft Kernfusion KfK and IPP cooperate for the development of future fusion experiments joining the experience gained in plasma physics (IPP) and materials, safety, and nuclear technology (KfK), respectively. As in the present strategy of the European Fusion Programme the Next European Tokamak (NET) is foreseen as the major next step, most of the activities of KfK address this subject. In addition to the contributions to NET, studies are carried out to innovate INTOR, the worldwide cooperation for an experimental reactor under the auspices of IAEA. Furthermore, the Entwicklungsgemeinschaft Kernfusion has evaluated the feasibility of a fusion reactor with a stellarator confinement. (orig./GG)

Physiological and Pathological Roles of CaMKII-PP1 Signaling in the Brain

Directory of Open Access Journals (Sweden)

Norifumi Shioda

2017-12-01

Full Text Available Ca2+/calmodulin (CaM-dependent protein kinase II (CaMKII, a multifunctional serine (Ser/threonine (Thr protein kinase, regulates diverse activities related to Ca2+-mediated neuronal plasticity in the brain, including synaptic activity and gene expression. Among its regulators, protein phosphatase-1 (PP1, a Ser/Thr phosphatase, appears to be critical in controlling CaMKII-dependent neuronal signaling. In postsynaptic densities (PSDs, CaMKII is required for hippocampal long-term potentiation (LTP, a cellular process correlated with learning and memory. In response to Ca2+ elevation during hippocampal LTP induction, CaMKIIα, an isoform that translocates from the cytosol to PSDs, is activated through autophosphorylation at Thr286, generating autonomous kinase activity and a prolonged Ca2+/CaM-bound state. Moreover, PP1 inhibition enhances Thr286 autophosphorylation of CaMKIIα during LTP induction. By contrast, CaMKII nuclear import is regulated by Ser332 phosphorylation state. CaMKIIδ3, a nuclear isoform, is dephosphorylated at Ser332 by PP1, promoting its nuclear translocation, where it regulates transcription. In this review, we summarize physio-pathological roles of CaMKII/PP1 signaling in neurons. CaMKII and PP1 crosstalk and regulation of gene expression is important for neuronal plasticity as well as survival and/or differentiation.

Group analyses of connectivity-based cortical parcellation using repeated k-means clustering

NARCIS (Netherlands)

Nanetti, Luca; Cerliani, Leonardo; Gazzola, Valeria; Renken, Remco; Keysers, Christian

2009-01-01

K-means clustering has become a popular tool for connectivity-based cortical segmentation using Diffusion Weighted Imaging (DWI) data. A sometimes ignored issue is, however, that the output of the algorithm depends on the initial placement of starting points, and that different sets of starting

Clusters in nuclei

CERN Document Server

Following the pioneering discovery of alpha clustering and of molecular resonances, the field of nuclear clustering is today one of those domains of heavy-ion nuclear physics that faces the greatest challenges, yet also contains the greatest opportunities. After many summer schools and workshops, in particular over the last decade, the community of nuclear molecular physicists has decided to collaborate in producing a comprehensive collection of lectures and tutorial reviews covering the field. This third volume follows the successful Lect. Notes Phys. 818 (Vol. 1) and 848 (Vol. 2), and comprises six extensive lectures covering the following topics:  - Gamma Rays and Molecular Structure - Faddeev Equation Approach for Three Cluster Nuclear Reactions - Tomography of the Cluster Structure of Light Nuclei Via Relativistic Dissociation - Clustering Effects Within the Dinuclear Model : From Light to Hyper-heavy Molecules in Dynamical Mean-field Approach - Clusterization in Ternary Fission - Clusters in Light N...

U.K. nuclear data progress report January-December 1986

International Nuclear Information System (INIS)

Sene, M.R.; Cookson, J.A.

1987-06-01

The paper is the United Kingdom Nuclear Data (UKND) progress report, and summarises nuclear data research in the UK between January and December 1986. The contents of the report contains nuclear data work presented by:- UKAEA Harwell, UKAEA Winfrith, National Physical Laboratory, and the Universities of Birmingham, Edinburgh and Oxford. Included in these contributions are collaborative studies involving institutions in Holland, Italy, West Germany and the United States. The report also contains contributions on Chemical Nuclear Data, as well as the summaries of three invited lectures presented at the 19th UK Nuclear Data Form, Harwell Laboratory, 1986. (U.K.)

THE VERY MASSIVE STAR CONTENT OF THE NUCLEAR STAR CLUSTERS IN NGC 5253

Energy Technology Data Exchange (ETDEWEB)

Smith, L. J. [Space Telescope Science Institute and European Space Agency, 3700 San Martin Drive, Baltimore, MD 21218 (United States); Crowther, P. A. [Department of Physics and Astronomy, University of Sheffield, Sheffield S3 7RH (United Kingdom); Calzetti, D. [Department of Astronomy, University of Massachusetts—Amherst, Amherst, MA 01003 (United States); Sidoli, F., E-mail: lsmith@stsci.edu [London Centre for Nanotechnology, University College London, London WC1E 6BT (United Kingdom)

2016-05-20

The blue compact dwarf galaxy NGC 5253 hosts a very young starburst containing twin nuclear star clusters, separated by a projected distance of 5 pc. One cluster (#5) coincides with the peak of the H α emission and the other (#11) with a massive ultracompact H ii region. A recent analysis of these clusters shows that they have a photometric age of 1 ± 1 Myr, in apparent contradiction with the age of 3–5 Myr inferred from the presence of Wolf-Rayet features in the cluster #5 spectrum. We examine Hubble Space Telescope ultraviolet and Very Large Telescope optical spectroscopy of #5 and show that the stellar features arise from very massive stars (VMSs), with masses greater than 100 M {sub ⊙}, at an age of 1–2 Myr. We further show that the very high ionizing flux from the nuclear clusters can only be explained if VMSs are present. We investigate the origin of the observed nitrogen enrichment in the circumcluster ionized gas and find that the excess N can be produced by massive rotating stars within the first 1 Myr. We find similarities between the NGC 5253 cluster spectrum and those of metal-poor, high-redshift galaxies. We discuss the presence of VMSs in young, star-forming galaxies at high redshift; these should be detected in rest-frame UV spectra to be obtained with the James Webb Space Telescope . We emphasize that population synthesis models with upper mass cutoffs greater than 100 M {sub ⊙} are crucial for future studies of young massive star clusters at all redshifts.

Analysis of nucleo-cytoplasmic shuttling of the proto-oncogene SET/I2PP2A

NARCIS (Netherlands)

Lam, B. Daniel; Anthony, Eloise C.; Hordijk, Peter L.

2012-01-01

SET/I2PP2A is a nuclear protein that was initially identified as an oncogene in human undifferentiated acute myeloid leukemia, fused to the nuclear porin Nup-214. In addition, SET is a potent inhibitior of the phosphatase PP2A. Previously, we proposed a model in which the small GTPase Rac1 recruits

Comparison of five cluster validity indices performance in brain [18 F]FET-PET image segmentation using k-means.

Science.gov (United States)

Abualhaj, Bedor; Weng, Guoyang; Ong, Melissa; Attarwala, Ali Asgar; Molina, Flavia; Büsing, Karen; Glatting, Gerhard

2017-01-01

Dynamic [ 18 F]fluoro-ethyl-L-tyrosine positron emission tomography ([ 18 F]FET-PET) is used to identify tumor lesions for radiotherapy treatment planning, to differentiate glioma recurrence from radiation necrosis and to classify gliomas grading. To segment different regions in the brain k-means cluster analysis can be used. The main disadvantage of k-means is that the number of clusters must be pre-defined. In this study, we therefore compared different cluster validity indices for automated and reproducible determination of the optimal number of clusters based on the dynamic PET data. The k-means algorithm was applied to dynamic [ 18 F]FET-PET images of 8 patients. Akaike information criterion (AIC), WB, I, modified Dunn's and Silhouette indices were compared on their ability to determine the optimal number of clusters based on requirements for an adequate cluster validity index. To check the reproducibility of k-means, the coefficients of variation CVs of the objective function values OFVs (sum of squared Euclidean distances within each cluster) were calculated using 100 random centroid initialization replications RCI 100 for 2 to 50 clusters. k-means was performed independently on three neighboring slices containing tumor for each patient to investigate the stability of the optimal number of clusters within them. To check the independence of the validity indices on the number of voxels, cluster analysis was applied after duplication of a slice selected from each patient. CVs of index values were calculated at the optimal number of clusters using RCI 100 to investigate the reproducibility of the validity indices. To check if the indices have a single extremum, visual inspection was performed on the replication with minimum OFV from RCI 100 . The maximum CV of OFVs was 2.7 × 10 -2 from all patients. The optimal number of clusters given by modified Dunn's and Silhouette indices was 2 or 3 leading to a very poor segmentation. WB and I indices suggested in

A K-means multivariate approach for clustering independent components from magnetoencephalographic data.

Science.gov (United States)

Spadone, Sara; de Pasquale, Francesco; Mantini, Dante; Della Penna, Stefania

2012-09-01

Independent component analysis (ICA) is typically applied on functional magnetic resonance imaging, electroencephalographic and magnetoencephalographic (MEG) data due to its data-driven nature. In these applications, ICA needs to be extended from single to multi-session and multi-subject studies for interpreting and assigning a statistical significance at the group level. Here a novel strategy for analyzing MEG independent components (ICs) is presented, Multivariate Algorithm for Grouping MEG Independent Components K-means based (MAGMICK). The proposed approach is able to capture spatio-temporal dynamics of brain activity in MEG studies by running ICA at subject level and then clustering the ICs across sessions and subjects. Distinctive features of MAGMICK are: i) the implementation of an efficient set of "MEG fingerprints" designed to summarize properties of MEG ICs as they are built on spatial, temporal and spectral parameters; ii) the implementation of a modified version of the standard K-means procedure to improve its data-driven character. This algorithm groups the obtained ICs automatically estimating the number of clusters through an adaptive weighting of the parameters and a constraint on the ICs independence, i.e. components coming from the same session (at subject level) or subject (at group level) cannot be grouped together. The performances of MAGMICK are illustrated by analyzing two sets of MEG data obtained during a finger tapping task and median nerve stimulation. The results demonstrate that the method can extract consistent patterns of spatial topography and spectral properties across sessions and subjects that are in good agreement with the literature. In addition, these results are compared to those from a modified version of affinity propagation clustering method. The comparison, evaluated in terms of different clustering validity indices, shows that our methodology often outperforms the clustering algorithm. Eventually, these results are

STAR CLUSTERS IN A NUCLEAR STAR FORMING RING: THE DISAPPEARING STRING OF PEARLS

Energy Technology Data Exchange (ETDEWEB)

Väisänen, Petri; Barway, Sudhanshu; Randriamanakoto, Zara, E-mail: petri@saao.ac.za [South African Astronomical Observatory, P.O. Box 9 Observatory, Cape Town (South Africa)

2014-12-20

An analysis of the star cluster population in a low-luminosity early-type galaxy, NGC 2328, is presented. The clusters are found in a tight star forming nuclear spiral/ring pattern and we also identify a bar from structural two-dimensional decomposition. These massive clusters are forming very efficiently in the circumnuclear environment and they are young, possibly all less than 30 Myr of age. The clusters indicate an azimuthal age gradient, consistent with a ''pearls-on-a-string'' formation scenario, suggesting bar-driven gas inflow. The cluster mass function has a robust down turn at low masses at all age bins. Assuming clusters are born with a power-law distribution, this indicates extremely rapid disruption at timescales of just several million years. If found to be typical, it means that clusters born in dense circumnuclear rings do not survive to become old globular clusters in non-interacting systems.

STAR CLUSTERS IN A NUCLEAR STAR FORMING RING: THE DISAPPEARING STRING OF PEARLS

International Nuclear Information System (INIS)

Väisänen, Petri; Barway, Sudhanshu; Randriamanakoto, Zara

2014-01-01

An analysis of the star cluster population in a low-luminosity early-type galaxy, NGC 2328, is presented. The clusters are found in a tight star forming nuclear spiral/ring pattern and we also identify a bar from structural two-dimensional decomposition. These massive clusters are forming very efficiently in the circumnuclear environment and they are young, possibly all less than 30 Myr of age. The clusters indicate an azimuthal age gradient, consistent with a ''pearls-on-a-string'' formation scenario, suggesting bar-driven gas inflow. The cluster mass function has a robust down turn at low masses at all age bins. Assuming clusters are born with a power-law distribution, this indicates extremely rapid disruption at timescales of just several million years. If found to be typical, it means that clusters born in dense circumnuclear rings do not survive to become old globular clusters in non-interacting systems

pp and ̄pp elastic scattering

Directory of Open Access Journals (Sweden)

A. Donnachie

1984-01-01

Full Text Available We present an analysis of pp and ̄pp elastic scattering in terms of various exchanges. Three-gluon exchange dominates at large t, and single-pomeron exchange at small t. The dip seen in high-energy pp scattering is provided by the interference of both of these with double-pomeron exchange. We predict that this dip will not be found in high-energy ̄pp scattering. The dip that is seen in low-energy ̄pp scattering is the result of the additional presence of reggeon-pomeron exchange.

Clusters in nuclei. Vol. 1

International Nuclear Information System (INIS)

Beck, Christian

2010-01-01

Following the pioneering discovery of alpha clustering and of molecular resonances, the field of nuclear clustering is presently one of the domains of heavy-ion nuclear physics facing both the greatest challenges and opportunities. After many summer schools and workshops, in particular over the last decade, the community of nuclear molecular physics decided to team up in producing a comprehensive collection of lectures and tutorial reviews covering the field. This first volume, gathering seven extensive lectures, covers the follow topics: - Cluster Radioactivity - Cluster States and Mean Field Theories - Alpha Clustering and Alpha Condensates - Clustering in Neutron-rich Nuclei - Di-neutron Clustering - Collective Clusterization in Nuclei - Giant Nuclear Molecules By promoting new ideas and developments while retaining a pedagogical nature of presentation throughout, these lectures will both serve as a reference and as advanced teaching material for future courses and schools in the fields of nuclear physics and nuclear astrophysics. (orig.)

Paternal age related schizophrenia (PARS): Latent subgroups detected by k-means clustering analysis.

Science.gov (United States)

Lee, Hyejoo; Malaspina, Dolores; Ahn, Hongshik; Perrin, Mary; Opler, Mark G; Kleinhaus, Karine; Harlap, Susan; Goetz, Raymond; Antonius, Daniel

2011-05-01

Paternal age related schizophrenia (PARS) has been proposed as a subgroup of schizophrenia with distinct etiology, pathophysiology and symptoms. This study uses a k-means clustering analysis approach to generate hypotheses about differences between PARS and other cases of schizophrenia. We studied PARS (operationally defined as not having any family history of schizophrenia among first and second-degree relatives and fathers' age at birth ≥ 35 years) in a series of schizophrenia cases recruited from a research unit. Data were available on demographic variables, symptoms (Positive and Negative Syndrome Scale; PANSS), cognitive tests (Wechsler Adult Intelligence Scale-Revised; WAIS-R) and olfaction (University of Pennsylvania Smell Identification Test; UPSIT). We conducted a series of k-means clustering analyses to identify clusters of cases containing high concentrations of PARS. Two analyses generated clusters with high concentrations of PARS cases. The first analysis (N=136; PARS=34) revealed a cluster containing 83% PARS cases, in which the patients showed a significant discrepancy between verbal and performance intelligence. The mean paternal and maternal ages were 41 and 33, respectively. The second analysis (N=123; PARS=30) revealed a cluster containing 71% PARS cases, of which 93% were females; the mean age of onset of psychosis, at 17.2, was significantly early. These results strengthen the evidence that PARS cases differ from other patients with schizophrenia. Hypothesis-generating findings suggest that features of PARS may include a discrepancy between verbal and performance intelligence, and in females, an early age of onset. These findings provide a rationale for separating these phenotypes from others in future clinical, genetic and pathophysiologic studies of schizophrenia and in considering responses to treatment. Copyright © 2011 Elsevier B.V. All rights reserved.

Plan for characterization of K Basin spent nuclear fuel and sludge

International Nuclear Information System (INIS)

Lawrence, L.A.; Marschman, S.C.

1995-06-01

This plan outlines a characterization program that supports the accelerated Path Forward scope and schedules for the Spent Nuclear Fuel stored in the Hanford K Basins. This plan is driven by the schedule to begin fuel transfer by December 1997. The program is structured for 4 years and is limited to in-situ and laboratory examinations of the spent nuclear fuel and sludge in the K East and K West Basins. The program provides bounding behavior of the fuel, and verification and acceptability for three different sludge disposal pathways. Fuel examinations are based on two shipping campaigns for the K West Basin and one from the K East Basin. Laboratory examinations include physical condition, hydride and oxide content, conditioning testing, and dry storage behavior

Dealing with the Y2K problem in German nuclear facilities

International Nuclear Information System (INIS)

Hagemann, A.

1999-01-01

General situation concerning Y2K problem related to german nuclear facilities is presented. Nuclear material used i Germany is owned by EURATOM and Germany is responsible to EURATOM as well as IAEA inspections. Systems of concern are monitoring and control systems, safety related systems and physical protection systems. Present situation is as follows: responsible project teams are formed, Y2K sensitive equipment is identified, designers are contacted, compliance tests specified and schedule of the proof established as of end of August 1999. Experiences obtained in overcoming the Y2K risks are cited

Cluster self-organization of germanate systems: suprapolyhedral precursor clusters and self-assembly of K2Nd4Ge4O13(OH)4, K2YbGe4O10(OH), K2Sc2Ge2O7(OH)2, and KScGe2O6(PYR)

International Nuclear Information System (INIS)

Ilyushin, G.D.; Dem'yanets, L.N.

2008-01-01

One performed the computerized (the TOPOS 4.0 software package) geometric and topological analyses of all known types of K, TR-germanates (TR = La-Lu, Y, Sc, In). The skeleton structure are shown as three-dimensional 3D, K, TR, Ge-patterns (graphs) with remote oxygen atoms. TR 4 3 3 4 3 3 + T 4 3 4 3, K 2 YbGe 4 O 14 (OH) pattern, TR 6 6 3 6 + T1 6 8 6 + T2 3 6 8, K 2 Sc 2 Ge 2 O 7 (OH) 2 , TR 6 4 6 4 + T 6 4 6 and KScGe 2 O 6 - TR 6 6 3 6 3 4 + T1 6 3 6 + T2 6 4 3 patterns served as crystal-forming 2D TR,Ge-patterns for K 2 Nd 4 Ge 4 O 13 (OH) 4 . One performed the 3D-simulation of the mechanism of self-arrangement of the crystalline structures: cluster-precursor - parent chain - microlayer - microskeleton (super-precursor). Within K 2 Nd 4 Ge 4 O 13 (OH) 4 , K 2 Sc 2 Ge 2 O 7 (OH) 2 and KScGe 2 O 6 one identified the invariant type of the cyclic hexapolyhedral cluster-precursor consisting of TR-octahedrons linked by diorthogroups stabilized by K atoms. For K 2 Nd 4 Ge 4 O 13 (OH) 4 one determined the type of the cyclic tetrapolyhedral cluster-precursor consisting of TR-octavertices linked by tetrahedrons. The cluster CN within the layer just for KScGe 2 O 6 water-free germanate (the PYR pyroxene analog) is equal to 6 (the maximum possible value), while in the rest OH-containing germanates it constitutes 4. One studied the formation mechanism of Ge-radicals in the form of Ge 2 O 7 and Ge 4 O 13 groupings, GeO 3 chain and the tubular structure consisting of Ge 8 O 20 fixed cyclic groupings [ru

Worst-case and smoothed analysis of $k$-means clustering with Bregman divergences

NARCIS (Netherlands)

Manthey, Bodo; Röglin, Heiko; Dong, Yingfei; Du, Dingzhu; Ibarra, Oscar

2009-01-01

The $k$-means algorithm is the method of choice for clustering large-scale data sets and it performs exceedingly well in practice. Most of the theoretical work is restricted to the case that squared Euclidean distances are used as similarity measure. In many applications, however, data is to be

Utility of the k-means clustering algorithm in differentiating apparent diffusion coefficient values of benign and malignant neck pathologies.

Science.gov (United States)

Srinivasan, A; Galbán, C J; Johnson, T D; Chenevert, T L; Ross, B D; Mukherji, S K

2010-04-01

Does the K-means algorithm do a better job of differentiating benign and malignant neck pathologies compared to only mean ADC? The objective of our study was to analyze the differences between ADC partitions to evaluate whether the K-means technique can be of additional benefit to whole-lesion mean ADC alone in distinguishing benign and malignant neck pathologies. MR imaging studies of 10 benign and 10 malignant proved neck pathologies were postprocessed on a PC by using in-house software developed in Matlab. Two neuroradiologists manually contoured the lesions, with the ADC values within each lesion clustered into 2 (low, ADC-ADC(L); high, ADC-ADC(H)) and 3 partitions (ADC(L); intermediate, ADC-ADC(I); ADC(H)) by using the K-means clustering algorithm. An unpaired 2-tailed Student t test was performed for all metrics to determine statistical differences in the means of the benign and malignant pathologies. A statistically significant difference between the mean ADC(L) clusters in benign and malignant pathologies was seen in the 3-cluster models of both readers (P = .03 and .022, respectively) and the 2-cluster model of reader 2 (P = .04), with the other metrics (ADC(H), ADC(I); whole-lesion mean ADC) not revealing any significant differences. ROC curves demonstrated the quantitative differences in mean ADC(H) and ADC(L) in both the 2- and 3-cluster models to be predictive of malignancy (2 clusters: P = .008, area under curve = 0.850; 3 clusters: P = .01, area under curve = 0.825). The K-means clustering algorithm that generates partitions of large datasets may provide a better characterization of neck pathologies and may be of additional benefit in distinguishing benign and malignant neck pathologies compared with whole-lesion mean ADC alone.

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.

The role of the dinuclear system in the processes of nuclear fusion, quasi-fission, fission and cluster formation

International Nuclear Information System (INIS)

Volkov, V.V.

1999-01-01

The nuclear fusion, quasi-fission, fission and cluster formation in an excited nucleus are considered as the processes of the formation and evolution of the dinuclear system. This approach allows one to reveal new aspects of nuclear fusion, to show that quasi-fission plays an important role in nuclear reactions used to synthesise superheavy elements. A qualitative picture is given of the fission process of an excited nucleus and an important role of cluster formation in this process is shown

[Automatic Sleep Stage Classification Based on an Improved K-means Clustering Algorithm].

Science.gov (United States)

Xiao, Shuyuan; Wang, Bei; Zhang, Jian; Zhang, Qunfeng; Zou, Junzhong

2016-10-01

Sleep stage scoring is a hotspot in the field of medicine and neuroscience.Visual inspection of sleep is laborious and the results may be subjective to different clinicians.Automatic sleep stage classification algorithm can be used to reduce the manual workload.However,there are still limitations when it encounters complicated and changeable clinical cases.The purpose of this paper is to develop an automatic sleep staging algorithm based on the characteristics of actual sleep data.In the proposed improved K-means clustering algorithm,points were selected as the initial centers by using a concept of density to avoid the randomness of the original K-means algorithm.Meanwhile,the cluster centers were updated according to the‘Three-Sigma Rule’during the iteration to abate the influence of the outliers.The proposed method was tested and analyzed on the overnight sleep data of the healthy persons and patients with sleep disorders after continuous positive airway pressure(CPAP)treatment.The automatic sleep stage classification results were compared with the visual inspection by qualified clinicians and the averaged accuracy reached 76%.With the analysis of morphological diversity of sleep data,it was proved that the proposed improved K-means algorithm was feasible and valid for clinical practice.

Utility of K-Means clustering algorithm in differentiating apparent diffusion coefficient values between benign and malignant neck pathologies

Science.gov (United States)

Srinivasan, A.; Galbán, C.J.; Johnson, T.D.; Chenevert, T.L.; Ross, B.D.; Mukherji, S.K.

2014-01-01

Purpose The objective of our study was to analyze the differences between apparent diffusion coefficient (ADC) partitions (created using the K-Means algorithm) between benign and malignant neck lesions and evaluate its benefit in distinguishing these entities. Material and methods MRI studies of 10 benign and 10 malignant proven neck pathologies were post-processed on a PC using in-house software developed in MATLAB (The MathWorks, Inc., Natick, MA). Lesions were manually contoured by two neuroradiologists with the ADC values within each lesion clustered into two (low ADC-ADCL, high ADC-ADCH) and three partitions (ADCL, intermediate ADC-ADCI, ADCH) using the K-Means clustering algorithm. An unpaired two-tailed Student’s t-test was performed for all metrics to determine statistical differences in the means between the benign and malignant pathologies. Results Statistically significant difference between the mean ADCL clusters in benign and malignant pathologies was seen in the 3 cluster models of both readers (p=0.03, 0.022 respectively) and the 2 cluster model of reader 2 (p=0.04) with the other metrics (ADCH, ADCI, whole lesion mean ADC) not revealing any significant differences. Receiver operating characteristics curves demonstrated the quantitative difference in mean ADCH and ADCL in both the 2 and 3 cluster models to be predictive of malignancy (2 clusters: p=0.008, area under curve=0.850, 3 clusters: p=0.01, area under curve=0.825). Conclusion The K-Means clustering algorithm that generates partitions of large datasets may provide a better characterization of neck pathologies and may be of additional benefit in distinguishing benign and malignant neck pathologies compared to whole lesion mean ADC alone. PMID:20007723

Effective lifetime measurements in the B-s(0) -> K+K-, B-0 -> K+pi(-) and B-s(0) -> pi K-+(-) decays

NARCIS (Netherlands)

Aaij, R.; Adeva, B.; Adinolfi, M.; Affolder, A.; Ajaltouni, Z.; Albrecht, J.; Alessio, F.; Alexander, M.; Ali, S.; Alkhazov, G.; Cartelle, P. Alvarez; Alves, A. A.; Amato, S.; Amerio, S.; Amhis, Y.; An, L.; Anderlini, L.; Anderson, J.; Andreassen, R.; Andreotti, M.; Andrews, J. E.; Appleby, R. B.; Gutierrez, O. Aquines; Archilli, F.; Artamonov, A.; Artuso, M.; Aslanides, E.; Auriemma, G.; Baalouch, M.; Bachmann, S.; Back, J. J.; Badalov, A.; Balagura, V.; Baldini, W.; Barlow, R. J.; Barschel, C.; Barsuk, S.; Barter, W.; Batozskaya, V.; Bauer, Th.; Bay, A.; Beddow, J.; Bedeschi, F.; Bediaga, I.; Belogurov, S.; Belous, K.; Belyaev, I.; Ben-Haim, E.; Bencivenni, G.; Benson, S.; Benton, J.; Berezhnoy, A.; Bernet, R.; Bettler, M. -O.; Vanbeuzekom, M.; Bien, A.; Bifani, S.; Bird, T.; Bizzeti, A.; Bjornstad, P. M.; Blake, T.; Blanc, F.; Blouw, J.; Blusk, S.; Bocci, V.; Bondar, A.; Bondar, N.; Bonivento, W.; Borghi, S.; Borgia, A.; Borsato, M.; Bowcock, T. J. V.; Bowen, E.; Bozzi, C.; Brambach, T.; van den Brand, J.; Bressieux, J.; Brett, D.; Britsch, M.; Britton, T.; Brook, N. H.; Brown, H.; Bursche, A.; Busetto, G.; Buytaert, J.; Cadeddu, S.; Calabrese, R.; Calvi, M.; Gomez, M. Calvo; Camboni, A.; Campana, P.; Perez, D. Campora; Carbone, A.; Carboni, G.; Cardinale, R.; Cardini, A.; Carranza-Mejia, H.; Carson, L.; Akiba, K. Carvalho; Casse, G.; Cassina, L.; Garcia, L. Castillo; Cattaneo, M.; Cauet, Ch.; Cenci, R.; Charles, M.; Charpentier, Ph.; Cheung, S. -F.; Chiapolini, N.; Chrzaszcz, M.; Ciba, K.; Vidal, X. Cid; Ciezarek, G.; Clarke, P. E. L.; Clemencic, M.; Cliff, H. V.; Closier, J.; Coco, V.; Cogan, J.; Cogneras, E.; Collins, P.; Comerma-Montells, A.; Contu, A.; Cook, A.; Coombes, M.; Coquereau, S.; Corti, G.; Corvo, M.; Counts, I.; Couturier, B.; Cowan, G. A.; Craik, D. C.; Torres, M. Cruz; Cunliffe, S.; Currie, R.; D'Ambrosio, C.; Dalseno, J.; David, P.; David, P. N. Y.; Davis, A.; De Bruyn, K.; De Capua, S.; De Cian, M.; De Miranda, J. M.; De Paula, L.; De Silva, W.; De Simone, P.; Decamp, D.; Deckenhoff, M.; Del Buono, L.; Deleage, N.; Derkach, D.; Deschamps, O.; Dettori, F.; Di Canto, A.; Dijkstra, H.; Donleavy, S.; Dordei, F.; Dorigo, M.; Suarez, A. Dosil; Dossett, D.; Dovbnya, A.; Dupertuis, F.; Durante, P.; Dzhelyadin, R.; Dziurda, A.; Dzyuba, A.; Easo, S.; Egede, U.; Egorychev, V.; Eidelman, S.; Eisenhardt, S.; Eitschberger, U.; Ekelhof, R.; Eklund, L.; El Rifai, I.; Elsasser, Ch.; Esen, S.; Falabella, A.; Faerber, C.; Farinelli, C.; Farley, N.; Farry, S.; Fay, R. F.; Ferguson, D.; Albor, V. Fernandez; Rodrigues, F. Ferreira; Ferro-Luzzi, M.; Filippov, S.; Fiore, M.; Fiorini, M.; Firlej, M.; Fitzpatrick, C.; Fiutowski, T.; Fontana, M.; Fontanelli, F.; Forty, R.; Francisco, O.; Frank, M.; Frei, C.; Frosini, M.; Fu, J.; Furfaro, E.; Torreira, A. Gallas; Galli, D.; Gallorini, S.; Gambetta, S.; Gandelman, M.; Gandini, P.; Gao, Y.; Garofoli, J.; Tico, J. Garra; Garrido, L.; Gaspar, C.; Gauld, R.; Gavardi, L.; Geraci, A.; Gersabeck, E.; Gersabeck, M.; Gershon, T.; Ghez, Ph.; Gianelle, A.; Giani, S.; Gibson, V.; Giubega, L.; Gligorov, V. V.; Goebel, C.; Golubkov, D.; Golutvin, A.; Gomes, A.; Gordon, H.; Gotti, C.; Gaendara, M. Grabalosa; Diaz, R. Graciani; Cardoso, L. A. Granado; Graug, E.; Graziani, G.; Grecu, A.; Greening, E.; Gregson, S.; Griffith, P.; Grillo, L.; Gruenberg, O.; Gui, B.; Gushchin, E.; Guz, Yu.; Gys, T.; Hadjivasiliou, C.; Haefeli, G.; Haen, C.; Haines, S. C.; Hall, S.; Hamilton, B.; Hampson, T.; Han, X.; Hansmann-Menzemer, S.; Harnew, N.; Harnew, S. T.; Harrison, J.; Hartmann, T.; He, J.; Head, T.; Heijne, V.; Hennessy, K.; Henrard, P.; Henry, L.; Morata, J. A. Hernando; van Herwijnen, E.; Hess, M.; Hicheur, A.; Hill, D.; Hoballah, M.; Hombach, C.; Hulsbergen, W.; Hunt, P.; Hussain, N.; Hutchcroft, D.; Hynds, D.; Idzik, M.; Ilten, P.; Jacobsson, R.; Jaeger, A.; Jalocha, J.; Jans, E.; Jaton, P.; Jawahery, A.; Jing, F.; John, M.; Johnson, D.; Jones, C. R.; Joram, C.; Jost, B.; Jurik, N.; Kaballo, M.; Kandybei, S.; Kanso, W.; Karacson, M.; Karbach, T. M.; Kelsey, M.; Kenyon, I. R.; Ketel, T.; Khanji, B.; Khurewathanakul, C.; Klaver, S.; Kochebina, O.; Kolpin, M.; Komarov, I.; Koopman, R. F.; Koppenburg, P.; Korolev, M.; Kozlinskiy, A.; Kravchuk, L.; Kreplin, K.; Kreps, M.; Krocker, G.; Krokovny, P.; Kruse, F.; Kucharczyk, M.; Kudryavtsev, V.; Kurek, K.; Kvaratskheliya, T.; Lathi, V. N.; Lacarrere, D.; Lafferty, G.; Lai, A.; Lambert, D.; Lambert, R. W.; Lanciotti, E.; Lanfranchi, G.; Langenbruch, C.; Langhans, B.; Latham, T.; Lazzeroni, C.; Legac, R.; Vanleerdam, J.; Lees, J. -P.; Lefevre, R.; Leflat, A.; Lefranois, J.; Leo, S.; Leroy, O.; Lesiak, T.; Leverington, B.; Li, Y.; Liles, M.; Lindner, R.; Linn, C.; Lionetto, F.; Liu, B.; Liu, G.; Lohn, S.; Longstaff, I.; Lopes, J. H.; Lopez-March, N.; Lowdon, P.; Lu, H.; Lucchesi, D.; Luo, H.; Lupato, A.; Luppi, E.; Lupton, O.; Machefert, F.; Machikhiliyan, I. V.; Maciuc, F.; Maev, O.; Malde, S.; Manca, G.; Mancinelli, G.; Mapelli, A.; Maratas, J.; Marchand, J. F.; Marconi, U.; Benito, C. Marin; Marino, P.; Maerki, R.; Marks, J.; Martellotti, G.; Martens, A.; Martin Sanchez, A.; Martinelli, M.; Martinez Santos, D.; Martinez Vidal, F.; Tostes, D. Martins; Massafferri, A.; Matev, R.; Mathe, Z.; Matteuzzi, C.; Mazurov, A.; McCann, M.; McCarthy, J.; Mcnab, A.; McNulty, R.; McSkelly, B.; Meadows, B.; Meier, F.; Meissner, M.; Merk, M.; Milanes, D. A.; Minard, M. -N.; Moggi, N.; Rodriguez, J. Molina; Monteil, S.; Moran, D.; Morandin, M.; Morawski, P.; Mord, A.; Morello, M. J.; Moron, J.; Mountain, R.; Muheim, F.; Mueller, K.; Muresan, R.; Mussini, M.; Muster, B.; Naik, P.; Nakada, T.; Nandakumar, R.; Nasteva, I.; Needham, M.; Neri, N.; Neubert, S.; Neufeld, N.; Neuner, M.; Nguyen, A. D.; Nguyen, T. D.; Nguyen-Mau, C.; Nicol, M.; Niess, V.; Niet, R.; Nikitin, N.; Nikodem, T.; Novoselov, A.; Oblakowska-Mucha, A.; Obraztsov, V.; Oggero, S.; Ogilvy, S.; Okhrimenko, O.; Oldeman, R.; Onderwater, G.; Orlandea, M.; Goicochea, J. M. Otalora; Owen, P.; Oyanguren, A.; Pal, B. K.; Palano, A.; Palombo, F.; Palutan, M.; Panman, J.; Papanestis, A.; Pappagallo, M.; Parkes, C.; Parkinson, C. J.; Passaleva, G.; Patel, G. D.; Patel, M.; Patrignani, C.; Alvarez, A. Pazos; Pearce, A.; Pellegrino, A.; Altarelli, M. Pepe; Perazzini, S.; Trigo, E. Perez; Perret, P.; Perrin-Terrin, M.; Pescatore, L.; Pesen, E.; Petridis, K.; Petrolini, A.; Olloqui, E. Picatoste; Pietrzyk, B.; Pilar, T.; Pinci, D.; Pistone, A.; Playfer, S.; Casasus, M. Plo; Polci, F.; Poluektov, A.; Polycarpo, E.; Popov, A.; Popov, D.; Popovici, B.; Potterat, C.; Powell, A.; Prisciandaro, J.; Pritchard, A.; Prouve, C.; Pugatch, V.; Navarro, A. Puig; Punzi, G.; Qian, W.; Rachwal, B.; Rademacker, J. H.; Rakotomiaramanana, B.; Rama, M.; Rangel, M. S.; Raniuk, I.; Rauschmayr, N.; Raven, G.; Reichert, S.; Reid, M. M.; dos Reis, A. C.; Ricciardi, S.; Richards, A.; Rihl, M.; Rinnert, K.; Molina, V. Rives; Romero, D. A. Roa; Robbe, P.; Rodrigues, A. B.; Rodrigues, E.; Perez, P. Rodriguez; Roiser, S.; Romanovsky, V.; Vidal, A. Romero; Rotondo, M.; Rouvinet, J.; Ruf, T.; Ruffini, F.; Ruiz, H.; Valls, P. Ruiz; Sabatino, G.; Silva, J. J. Saborido; Sagidova, N.; Sail, P.; Saitta, B.; Guimaraes, V. Salustino; Mayordomo, C. Sanchez; Sedes, B. Sanmartin; Santacesaria, R.; Rios, C. Santamarina; Santovetti, E.; Sapunov, M.; Sarti, A.; Satriano, C.; Satta, A.; Savrie, M.; Savrina, D.; Schiller, M.; Schindler, H.; Schlupp, M.; Schmelling, M.; Schmidt, B.; Schneider, O.; Schopper, A.; Schune, M. -H.; Schwemmer, R.; Sciascia, B.; Sciubba, A.; Seco, M.; Semennikov, A.; Senderowska, K.; Sepp, I.; Serra, N.; Serrano, J.; Sestini, L.; Seyfert, P.; Shapkin, M.; Shapoval, I.; Shcheglov, Y.; Shears, T.; Shekhtman, L.; Shevchenko, V.; Shires, A.; Coutinho, R. Silva; Simi, G.; Sirendi, M.; Skidmore, N.; Skwarnicki, T.; Smith, N. A.; Smith, E.; Smith, E.; Smith, J.; Smith, M.; Snoek, H.; Sokoloff, M. D.; Soler, F. J. P.; Soomro, F.; Souza, D.; Souza De Paula, B.; Spaan, B.; Sparkes, A.; Spradlin, P.; Stagni, F.; Stahl, S.; Steinkamp, O.; Stenyakin, O.; Stevenson, S.; Stoica, S.; Stone, S.; Storaci, B.; Stracka, S.; Straticiuc, M.; Straumann, U.; Stroili, R.; Subbiah, V. K.; Sun, L.; Sutcliffe, W.; Swientek, K.; Swientek, S.; Syropoulos, V.; Szczekowski, M.; Szczypka, P.; Szilard, D.; Szumlak, T.; T'Jampens, S.; Teklishyn, M.; Tellarini, G.; Teubert, F.; Thomas, C.; Thomas, E.; van Tilburg, J.; Tisserand, V.; Tobin, M.; Tolk, S.; Tomassetti, L.; Tonelli, D.; Topp-Joergensen, S.; Torr, N.; Tournefier, E.; Tourneur, S.; Tran, M. T.; Tresch, M.; Tsaregorodtsev, A.; Tsopelas, P.; Tuning, N.; Garcia, M. Ubeda; Ukleja, A.; Ustyuzhanin, A.; Uwer, U.; Vagnoni, V.; Valenti, G.; Vallier, A.; Gomez, R. Vazquez; Regueiro, P. Vazquez; Sierra, C. Vyzquez; Vecchi, S.; Velthuis, J. J.; Veltri, M.; Veneziano, G.; Vesterinen, M.; Viaud, B.; Vieira, D.; Diaz, M. Vieites; Vilasis-Cardona, X.; Vollhardt, A.; Volyanskyy, D.; Voong, D.; Vorobyev, A.; Vorobyev, V.; Voss, C.; Voss, H.; de Vries, J. A.; Waldi, R.; Wallace, C.; Wallace, R.; Walsh, J.; Wandernoth, S.; Wang, J.; Ward, D. R.; Watson, N. K.; Websdale, D.; Whitehead, M.; Wicht, J.; Wiedner, D.; Wilkinson, G.; Williams, M. P.; Williams, M.; Wilson, F. F.; Wimberley, J.; Wishahi, J.; Wislicki, W.; Witek, M.; Wormser, G.; Wotton, S. A.; Wright, S.; Wu, S.; Wyllie, K.; Xie, Y.; Xing, Z.; Xu, Z.; Yang, Z.; Yuan, X.; Yushchenko, O.; Zangoli, M.; Zavertyaev, M.; Zhang, F.; Zhang, L.; Zhang, W. C.; Zhang, Y.; Zhelezov, A.; Zhokhov, A.; Zhong, L.; Zvyagin, A.

2014-01-01

Measurements of the effective lifetimes in the B-s(0) -> K+K-, B-0 -> K+pi(-) and B-s(0) -> pi K-+(-) decays are presented using 1.0 fb(-1)of pp collision data collected at a centre-of-mass energy of 7 TeV by the LHCb experiment. The analysis uses a data-driven approach to correct for the decay time

Implementation of hierarchical clustering using k-mer sparse matrix to analyze MERS-CoV genetic relationship

Science.gov (United States)

Bustamam, A.; Ulul, E. D.; Hura, H. F. A.; Siswantining, T.

2017-07-01

Hierarchical clustering is one of effective methods in creating a phylogenetic tree based on the distance matrix between DNA (deoxyribonucleic acid) sequences. One of the well-known methods to calculate the distance matrix is k-mer method. Generally, k-mer is more efficient than some distance matrix calculation techniques. The steps of k-mer method are started from creating k-mer sparse matrix, and followed by creating k-mer singular value vectors. The last step is computing the distance amongst vectors. In this paper, we analyze the sequences of MERS-CoV (Middle East Respiratory Syndrome - Coronavirus) DNA by implementing hierarchical clustering using k-mer sparse matrix in order to perform the phylogenetic analysis. Our results show that the ancestor of our MERS-CoV is coming from Egypt. Moreover, we found that the MERS-CoV infection that occurs in one country may not necessarily come from the same country of origin. This suggests that the process of MERS-CoV mutation might not only be influenced by geographical factor.

An enhanced deterministic K-Means clustering algorithm for cancer subtype prediction from gene expression data.

Science.gov (United States)

Nidheesh, N; Abdul Nazeer, K A; Ameer, P M

2017-12-01

Clustering algorithms with steps involving randomness usually give different results on different executions for the same dataset. This non-deterministic nature of algorithms such as the K-Means clustering algorithm limits their applicability in areas such as cancer subtype prediction using gene expression data. It is hard to sensibly compare the results of such algorithms with those of other algorithms. The non-deterministic nature of K-Means is due to its random selection of data points as initial centroids. We propose an improved, density based version of K-Means, which involves a novel and systematic method for selecting initial centroids. The key idea of the algorithm is to select data points which belong to dense regions and which are adequately separated in feature space as the initial centroids. We compared the proposed algorithm to a set of eleven widely used single clustering algorithms and a prominent ensemble clustering algorithm which is being used for cancer data classification, based on the performances on a set of datasets comprising ten cancer gene expression datasets. The proposed algorithm has shown better overall performance than the others. There is a pressing need in the Biomedical domain for simple, easy-to-use and more accurate Machine Learning tools for cancer subtype prediction. The proposed algorithm is simple, easy-to-use and gives stable results. Moreover, it provides comparatively better predictions of cancer subtypes from gene expression data. Copyright © 2017 Elsevier Ltd. All rights reserved.

Heavy cluster in cold nuclear rearrangements in fusion and fission

International Nuclear Information System (INIS)

Armbruster, P.

1997-01-01

The experimental evidence for the appearance of cluster aspects in the dynamics of large rearrangements processes, as fusion and fission, is presented. Clusters in the sense as used in the following are strongly bound, doubly magic neutron rich nuclei as 48 Ca 28 , 78 Ni 50 , 132 Sn 82 , and 208 Pb 126 , the spherical nuclei Z=114 - 126 and N=184, and nuclei with closed shells N=28, 50, 82, and 126, and Z=28, 50, and 82. As with increasing nucleon numbers, the absolute shell corrections to the binding energies increase, the strongest effects are to be observed for the higher shells. The 132 cluster manifests itself in low energy fission (Faissner, H. and Wildermuth, K. Nucl. Phys., 58 (1964) 177). The 208 Pb cluster gave the new radioactivity (Rose, M.J. and Jones G.A., Nature, 307 (1984) 245) and the first superheavy elements (SHE) (Armbruster P., Ann. Rev. Nucl. Part. Sci., 35 (1985) 135-94; Munzenberg, G. Rep. Progr. Phys., 51 (1988) 57). The paper discuss experiments concerning the stability of clusters to intrinsic excitation energy in fusion and fission (Armbruster, P. Lect. Notes Phys., 158 (1982) 1). and the manifestation of clusters in the fusion entrance channel (Armbruster, P., J. Phys. Soc. Jpn., 58 (1989) 232). The importance of compactness of the clustering system seems to be equally decisive in fission and fusion. Finally, it s covered the importance of clusters for the production of SHEs)

Pro-Nuclear Environmentalism: Should We Learn to Stop Worrying and Love Nuclear Energy?

Science.gov (United States)

van Munster, Rens; Sylvest, Casper

2015-10-01

In light of repeated failures to reach political agreement on effective policies to combat climate change, pro-nuclear environmentalists have set out to reverse the traditionally anti-nuclear inclinations of environmentalists. This essay examines the ideological commitments and assumptions of pro-nuclear environmentalism by performing a critical, historical analysis of the nuclear-environment nexus through the prism of documentary film. We focus on the work and career of documentary filmmaker Rob Stone, whose most recent production, Pandora's Promise (PP) (2013), has emerged as a central statement of this creed. PP actively forges a new political imaginary that replaces the apocalyptic image of nuclear fallout with that of catastrophic climate change. In terms of its rhetorical and visual strategies, however, PP also reveals that pro-nuclear environmentalist arguments have a long lineage. A close study of such continuities reveals a number of political implications that call for reflection as well as caution.

Study of pp{yields}pp{eta} reaction at threshold; Etude de la reaction pp{yields}pp{eta} au seuil

Energy Technology Data Exchange (ETDEWEB)

Taleb, A

1994-11-01

The {eta} production has been studied through the pp {yields} pp{eta} reaction at threshold. Data were taken at the Synchrotron of the ``Laboratoire National Saturne``. The detection in coincidence of the two protons scattered near 0 deg and analysed with the magnetic spectrometer SPES3 allows the reconstruction of missing mass spectra for the {eta} signature. A simulation program which takes into account all the experimental set up characteristics has been realized and tested through the pp {yields} d{pi}{sup +} reaction detected simultaneously with pp {yields} pp{eta}. The generated proton momentum spectra for pp {yields} pp{eta} show a pronounced {eta} mass dependence. This characteristic, connected to the kinematical properties of pp {yields} pp{eta} at threshold, is used to extract the mass of the meson {eta}. The obtained value, m{sub {eta}} = 547.65 {+-} 0.18 MeV, is in good agreement with measurement done recently through the pd {yields} {sup H}e{eta} reaction. The total cross section {sigma}{sub t} of pp {yields} pp{eta} measured at 1260, 1265 and 1300 MeV presents a strong energy dependence. This cross section increases less with energy than the phase-space. The influence of p-p and {eta}-p final state interactions in our measurements is studied. Our results are compared with theoretical predictions and assess the dominant character of the baryonic resonance N{sup *}(1535) in the {eta} mechanism production at threshold. These experimental results give an energy dependence which is not well reproduced by the theoretical predictions. This discrepancy could be an incorrect description of the {eta}-p interaction in the models. (author). 48 refs., 60 figs., 15 tabs.

Study of the ω meson produced in the 700-750 MeV/c pp→K10K10ω annihilations

International Nuclear Information System (INIS)

Salicio, J.

1976-01-01

We have measured the mass, width and branching ratio (→ neutrals) π + π - π 0 of the ω meson, using the reactions pp -- K 1 0 K 1 0 ↓ neutrals and pp → K 1 0 K 1 0 . The statistics is 11.5 events/μb. In this report we present the methods of analysis and discuss the results. (Author)

Artificial Bee Colony Algorithm Based on K-Means Clustering for Multiobjective Optimal Power Flow Problem

Directory of Open Access Journals (Sweden)

Liling Sun

2015-01-01

Full Text Available An improved multiobjective ABC algorithm based on K-means clustering, called CMOABC, is proposed. To fasten the convergence rate of the canonical MOABC, the way of information communication in the employed bees’ phase is modified. For keeping the population diversity, the multiswarm technology based on K-means clustering is employed to decompose the population into many clusters. Due to each subcomponent evolving separately, after every specific iteration, the population will be reclustered to facilitate information exchange among different clusters. Application of the new CMOABC on several multiobjective benchmark functions shows a marked improvement in performance over the fast nondominated sorting genetic algorithm (NSGA-II, the multiobjective particle swarm optimizer (MOPSO, and the multiobjective ABC (MOABC. Finally, the CMOABC is applied to solve the real-world optimal power flow (OPF problem that considers the cost, loss, and emission impacts as the objective functions. The 30-bus IEEE test system is presented to illustrate the application of the proposed algorithm. The simulation results demonstrate that, compared to NSGA-II, MOPSO, and MOABC, the proposed CMOABC is superior for solving OPF problem, in terms of optimization accuracy.

Clustering Educational Digital Library Usage Data: A Comparison of Latent Class Analysis and K-Means Algorithms

Science.gov (United States)

Xu, Beijie; Recker, Mimi; Qi, Xiaojun; Flann, Nicholas; Ye, Lei

2013-01-01

This article examines clustering as an educational data mining method. In particular, two clustering algorithms, the widely used K-means and the model-based Latent Class Analysis, are compared, using usage data from an educational digital library service, the Instructional Architect (IA.usu.edu). Using a multi-faceted approach and multiple data…

Factorization in the inclusive reactions pp to Lambda +X/sup ++/ and K /sup +/p to Lambda +X/sup ++/

CERN Document Server

Alpgard, K; Ciapetti, G; De Wolf, E; Frodesen, A G; Ginestet, J; Goldschmidt-Clermont, Yves; Grant, A; Grard, F; Hagman, V M; Henri, V P; Herquet, P; Hulth, P A; Jobes, M; Johnson, D; Kinson, J B; Manesse, D; Müller, F; Sekera, Z; Sené, M; Storr, K M; Svedin, U; Tuominiemi, J; Verbeure, F; Vignaud, D; Villanen, P; Watkins, D C; Yamdagni, N

1976-01-01

A test of factorization is made using data on the inclusive reactions pp to Lambda +X/sup ++/ at 19 GeV/c and K/sup +/p to Lambda +X/sup ++/ at 16 GeV/c incident momentum. In these reactions Lambda production occurs dominantly via proton fragmentation and, in addition, abc is exotic in both cases. The comparison of the structure functions on the Chew-Low plot shows that the factorization hypothesis is satisfied at the approximately 10% level when the momentum transfer from the proton to the Lambda is less than 1 (GeV/c)/sup 2/. (8 refs).

Variance-Based Cluster Selection Criteria in a K-Means Framework for One-Mode Dissimilarity Data.

Science.gov (United States)

Vera, J Fernando; Macías, Rodrigo

2017-06-01

One of the main problems in cluster analysis is that of determining the number of groups in the data. In general, the approach taken depends on the cluster method used. For K-means, some of the most widely employed criteria are formulated in terms of the decomposition of the total point scatter, regarding a two-mode data set of N points in p dimensions, which are optimally arranged into K classes. This paper addresses the formulation of criteria to determine the number of clusters, in the general situation in which the available information for clustering is a one-mode [Formula: see text] dissimilarity matrix describing the objects. In this framework, p and the coordinates of points are usually unknown, and the application of criteria originally formulated for two-mode data sets is dependent on their possible reformulation in the one-mode situation. The decomposition of the variability of the clustered objects is proposed in terms of the corresponding block-shaped partition of the dissimilarity matrix. Within-block and between-block dispersion values for the partitioned dissimilarity matrix are derived, and variance-based criteria are subsequently formulated in order to determine the number of groups in the data. A Monte Carlo experiment was carried out to study the performance of the proposed criteria. For simulated clustered points in p dimensions, greater efficiency in recovering the number of clusters is obtained when the criteria are calculated from the related Euclidean distances instead of the known two-mode data set, in general, for unequal-sized clusters and for low dimensionality situations. For simulated dissimilarity data sets, the proposed criteria always outperform the results obtained when these criteria are calculated from their original formulation, using dissimilarities instead of distances.

Atomistic spectrometrics of local bond-electron-energy pertaining to Na and K clusters

Energy Technology Data Exchange (ETDEWEB)

Bo, Maolin [Key Laboratory of Low-Dimensional Materials and Application Technologies, Ministry of Education, Xiangtan University, Hunan 411105 (China); Wang, Yan, E-mail: YWang8@hnust.edu.cn [School of Information and Electronic Engineering, Hunan University of Science and Technology, Hunan 411201 (China); Huang, Yongli; Liu, Yonghui [Key Laboratory of Low-Dimensional Materials and Application Technologies, Ministry of Education, Xiangtan University, Hunan 411105 (China); Li, Can [Center for Coordination Bond Engineering, School of Materials Science and Engineering, China Jiliang University, Hangzhou 330018 (China); Sun, Chang Q., E-mail: ecqsun@ntu.edu.sg [NOVITAS, School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798 (Singapore)

2015-01-15

Graphical abstract: - Highlights: • Coordination environment resolves electron binding-energy shift of Na and K clusters. • Cohesive energy of the representative bond determines the core-level shift. • XPS derives the energy level of an isolated atom and its bulk shift. • XPS derives the local bond length, bond energy, binding energy density. - Abstract: Consistency between density functional theory calculations and photoelectron spectroscopy measurements confirmed our predications on the undercoordination-induced local bond relaxation and core level shift of Na and K clusters. It is clarified that the shorter and stronger bonds between under-coordinated atoms cause local densification and local potential well depression and shift the electron binding-energy accordingly. Numerical consistency turns out the energy levels for an isolated Na (E{sub 2p} = 31.167 eV) and K (E{sub 3p} = 18.034 eV) atoms and their respective bulk shifts of 2.401 eV and 2.754 eV, which is beyond the scope of conventional approaches. This strategy has also resulted in quantification of the local bond length, bond energy, binding energy density, and atomic cohesive energy associated with the undercoordinated atoms.

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.

Pharmacokinetic analysis and k-means clustering of DCEMR images for radiotherapy outcome prediction of advanced cervical cancers.

Science.gov (United States)

Andersen, Erlend K F; Kristensen, Gunnar B; Lyng, Heidi; Malinen, Eirik

2011-08-01

Pharmacokinetic analysis of dynamic contrast enhanced magnetic resonance images (DCEMRI) allows for quantitative characterization of vascular properties of tumors. The aim of this study is twofold, first to determine if tumor regions with similar vascularization could be labeled by clustering methods, second to determine if the identified regions can be associated with local cancer relapse. Eighty-one patients with locally advanced cervical cancer treated with chemoradiotherapy underwent DCEMRI with Gd-DTPA prior to external beam radiotherapy. The median follow-up time after treatment was four years, in which nine patients had primary tumor relapse. By fitting a pharmacokinetic two-compartment model function to the temporal contrast enhancement in the tumor, two pharmacokinetic parameters, K(trans) and ύ(e), were estimated voxel by voxel from the DCEMR-images. Intratumoral regions with similar vascularization were identified by k-means clustering of the two pharmacokinetic parameter estimates over all patients. The volume fraction of each cluster was used to evaluate the prognostic value of the clusters. Three clusters provided a sufficient reduction of the cluster variance to label different vascular properties within the tumors. The corresponding median volume fraction of each cluster was 38%, 46% and 10%. The second cluster was significantly associated with primary tumor control in a log-rank survival test (p-value: 0.042), showing a decreased risk of treatment failure for patients with high volume fraction of voxels. Intratumoral regions showing similar vascular properties could successfully be labeled in three distinct clusters and the volume fraction of one cluster region was associated with primary tumor control.

Pharmacokinetic analysis and k-means clustering of DCEMR images for radiotherapy outcome prediction of advanced cervical cancers

International Nuclear Information System (INIS)

Andersen, Erlend K. F.; Kristensen, Gunnar B.; Lyng, Heidi; Malinen, Eirik

2011-01-01

Introduction. Pharmacokinetic analysis of dynamic contrast enhanced magnetic resonance images (DCEMRI) allows for quantitative characterization of vascular properties of tumors. The aim of this study is twofold, first to determine if tumor regions with similar vascularization could be labeled by clustering methods, second to determine if the identified regions can be associated with local cancer relapse. Materials and methods. Eighty-one patients with locally advanced cervical cancer treated with chemoradiotherapy underwent DCEMRI with Gd-DTPA prior to external beam radiotherapy. The median follow-up time after treatment was four years, in which nine patients had primary tumor relapse. By fitting a pharmacokinetic two-compartment model function to the temporal contrast enhancement in the tumor, two pharmacokinetic parameters, K trans and u e , were estimated voxel by voxel from the DCEMR-images. Intratumoral regions with similar vascularization were identified by k-means clustering of the two pharmacokinetic parameter estimates over all patients. The volume fraction of each cluster was used to evaluate the prognostic value of the clusters. Results. Three clusters provided a sufficient reduction of the cluster variance to label different vascular properties within the tumors. The corresponding median volume fraction of each cluster was 38%, 46% and 10%. The second cluster was significantly associated with primary tumor control in a log-rank survival test (p-value: 0.042), showing a decreased risk of treatment failure for patients with high volume fraction of voxels. Conclusions. Intratumoral regions showing similar vascular properties could successfully be labeled in three distinct clusters and the volume fraction of one cluster region was associated with primary tumor control

Enhanced K-means clustering with encryption on cloud

Science.gov (United States)

Singh, Iqjot; Dwivedi, Prerna; Gupta, Taru; Shynu, P. G.

2017-11-01

This paper tries to solve the problem of storing and managing big files over cloud by implementing hashing on Hadoop in big-data and ensure security while uploading and downloading files. Cloud computing is a term that emphasis on sharing data and facilitates to share infrastructure and resources.[10] Hadoop is an open source software that gives us access to store and manage big files according to our needs on cloud. K-means clustering algorithm is an algorithm used to calculate distance between the centroid of the cluster and the data points. Hashing is a algorithm in which we are storing and retrieving data with hash keys. The hashing algorithm is called as hash function which is used to portray the original data and later to fetch the data stored at the specific key. [17] Encryption is a process to transform electronic data into non readable form known as cipher text. Decryption is the opposite process of encryption, it transforms the cipher text into plain text that the end user can read and understand well. For encryption and decryption we are using Symmetric key cryptographic algorithm. In symmetric key cryptography are using DES algorithm for a secure storage of the files. [3

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

2nd International Symposium "Atomic Cluster Collisions : Structure and Dynamics from the Nuclear to the Biological Scale"

CERN Document Server

Solov'yov, Andrey; ISACC 2007; Latest advances in atomic cluster collisions

2008-01-01

This book presents a 'snapshot' of the most recent and significant advances in the field of cluster physics. It is a comprehensive review based on contributions by the participants of the 2nd International Symposium on Atomic Cluster Collisions (ISACC 2007) held in July 19-23, 2007 at GSI, Darmstadt, Germany. The purpose of the Symposium is to promote the growth and exchange of scientific information on the structure and properties of nuclear, atomic, molecular, biological and complex cluster systems studied by means of photonic, electronic, heavy particle and atomic collisions. Particular attention is devoted to dynamic phenomena, many-body effects taking place in cluster systems of a different nature - these include problems of fusion and fission, fragmentation, collective electron excitations, phase transitions, etc.Both the experimental and theoretical aspects of cluster physics, uniquely placed between nuclear physics on the one hand and atomic, molecular and solid state physics on the other, are discuss...

Measurement of the bottom quark cross section in bar p-p collisions using the exclusive decay B0 → J/ψK0*

International Nuclear Information System (INIS)

Vejcik, S.

1992-11-01

A measurement of the b quark cross section in pp collisions is presented for b quarks with PT above 11.5 GeV/c and rapidity parallel y parallel o → J/ψ K o in data taken with the CDF detector in the 1988-1989 Collider run. The measurement is compared to other CDF preliminary results and to theoretical predictions

K-Basin spent nuclear fuel characterization data report 2

International Nuclear Information System (INIS)

Abrefah, J.; Gray, W.J.; Ketner, G.L.; Marschman, S.C.; Pyecha, T.D.; Thornton, T.A.

1996-03-01

An Integrated Process Strategy has been developed to package, condition, transport, and store in an interim storage facility the spent nuclear fuel (SNF) currently residing in the K-Basins at Hanford. Information required to support the development of the condition process and to support the safety analyses must be obtained from characterization testing activities conducted on fuel samples from the Basins. Some of the information obtained in the testing was reported in PNL-10778, K-Basin Spent Nuclear Fuel Characterization Data Report (Abrefah et al. 1995). That report focused on the physical, dimensional, metallographic examinations of the first K-West (KW) Basin SNF element to be examined in the Postirradiation Testing Laboratory (PTL) hot cells; it also described some of the initial SNF conditioning tests. This second of the series of data reports covers the subsequent series of SNF tests on the first fuel element. These tests included optical microscopy analyses, conditioning (drying and oxidation) tests, ignition tests, and hydrogen content tests

K-Basin spent nuclear fuel characterization data report 2

Energy Technology Data Exchange (ETDEWEB)

Abrefah, J.; Gray, W.J.; Ketner, G.L.; Marschman, S.C.; Pyecha, T.D.; Thornton, T.A.

1996-03-01

An Integrated Process Strategy has been developed to package, condition, transport, and store in an interim storage facility the spent nuclear fuel (SNF) currently residing in the K-Basins at Hanford. Information required to support the development of the condition process and to support the safety analyses must be obtained from characterization testing activities conducted on fuel samples from the Basins. Some of the information obtained in the testing was reported in PNL-10778, K-Basin Spent Nuclear Fuel Characterization Data Report (Abrefah et al. 1995). That report focused on the physical, dimensional, metallographic examinations of the first K-West (KW) Basin SNF element to be examined in the Postirradiation Testing Laboratory (PTL) hot cells; it also described some of the initial SNF conditioning tests. This second of the series of data reports covers the subsequent series of SNF tests on the first fuel element. These tests included optical microscopy analyses, conditioning (drying and oxidation) tests, ignition tests, and hydrogen content tests.

Comparison of the Weisskopf estimates in spin and K-isomers

International Nuclear Information System (INIS)

Garg, Swati; Maheshwari, B.; Rajput, Rohit; Srivastava, P.C.; Jain, A.K.

2014-01-01

Nuclear isomers are the excited metastable states, which exist due to the hindrance on their decay. Study of isomers has recently become very popular due to advances in the experimental techniques and also the arrival of radioactive beams. Large amount of new experimental data is becoming available. The very first 'Atlas of nuclear isomers' lists more than 2460 nuclear isomers with the half-life cut off at 10 ns. Spin isomers mostly exist due to the difficulty in meeting the spin selection rules and cluster around the semi-magic regions. The isomers far from the magic-numbers, which lie in the well-deformed region, mostly exist due to the goodness of the K-quantum number and large K-difference between the decaying states. They are known as K-isomers

D K Mishra

Indian Academy of Sciences (India)

Home; Journals; Bulletin of Materials Science. D K Mishra. Articles written in Bulletin of Materials Science. Volume 34 Issue 7 December 2011 pp 1501-1506. Ce-doped LCMO CMR manganites: a consequence of enhanced T c and T IM · D K Mishra D R Sahu P K Mishra S K Singh B K Mohapatra B K Roul · More Details ...

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.

Clustering methods and visualization algorithms to aid nuclear reactor operative diagnostics

International Nuclear Information System (INIS)

Pepelyshev, Yu.N.; Dzwinel, W.

1990-01-01

The software system developed plays the role of the aid to an operator for nuclear reactor diagnostics. The noise analysis of the reactor parameters such as power, temperature and coolant flow rate constitutes the basis of the system. Combination of data acquisition, data preprocessing, clustering and cluster visualization algorithms with heuristic techniques of results analysis, determine the way of its implementation. Two regimes are available. The first one - extended - is recommended for a long term investigations and the second - suppressed for the aid to the reactor operation monitoring. The system has been tested and developed at the JINR IBR-2 pulsed reactor. 13 refs.; 4 figs.; 2 tabs

Determination of polyparameter linear free energy relationship (pp-LFER) substance descriptors for established and alternative flame retardants.

Science.gov (United States)

Stenzel, Angelika; Goss, Kai-Uwe; Endo, Satoshi

2013-02-05

Polyparameter linear free energy relationships (pp-LFERs) can predict partition coefficients for a multitude of environmental and biological phases with high accuracy. In this work, the pp-LFER substance descriptors of 40 established and alternative flame retardants (e.g., polybrominated diphenyl ethers, hexabromocyclododecane, bromobenzenes, trialkyl phosphates) were determined experimentally. In total, 251 data for gas-chromatographic (GC) retention times and liquid/liquid partition coefficients (K) were measured and used to calibrate the pp-LFER substance descriptors. Substance descriptors were validated through a comparison between predicted and experimental log K for the systems octanol/water (K(ow)), water/air (K(wa)), organic carbon/water (K(oc)) and liposome/water (K(lipw)), revealing a high reliability of pp-LFER predictions based on our descriptors. For instance, the difference between predicted and experimental log K(ow) was <0.3 log units for 17 out of 21 compounds for which experimental values were available. Moreover, we found an indication that the H-bond acceptor value (B) depends on the solvent for some compounds. Thus, for predicting environmentally relevant partition coefficients it is important to determine B values using measurements in aqueous systems. The pp-LFER descriptors calibrated in this study can be used to predict partition coefficients for which experimental data are unavailable, and the predicted values can serve as references for further experimental measurements.

Clusters in Nuclei. Vol. 2

International Nuclear Information System (INIS)

Beck, Christian

2012-01-01

Following the pioneering discovery of alpha clustering and of molecular resonances, the field of nuclear clustering is today one of those domains of heavy-ion nuclear physics that faces the greatest challenges, yet also contains the greatest opportunities. After many summer schools and workshops, in particular over the last decade, the community of nuclear molecular physicists has decided to collaborate in producing a comprehensive collection of lectures and tutorial reviews covering the field. This second volume follows the successful Lect. Notes Phys. 818 (Vol.1), and comprises six extensive lectures covering the following topics: - Microscopic cluster models - Neutron halo and break-up reactions - Break-up reaction models for two- and three-cluster projectiles - Clustering effects within the di-nuclear model - Nuclear alpha-particle condensates - Clusters in nuclei: experimental perspectives By promoting new ideas and developments while retaining a pedagogical style of presentation throughout, these lectures will serve as both a reference and an advanced teaching manual for future courses and schools in the fields of nuclear physics and nuclear astrophysics. (orig.)

Clusters in Nuclei. Vol. 2

Energy Technology Data Exchange (ETDEWEB)

Beck, Christian (ed.) [Strasbourg Univ. (France). Inst. Pluridiciplinaire Hubert Curien

2012-07-01

Following the pioneering discovery of alpha clustering and of molecular resonances, the field of nuclear clustering is today one of those domains of heavy-ion nuclear physics that faces the greatest challenges, yet also contains the greatest opportunities. After many summer schools and workshops, in particular over the last decade, the community of nuclear molecular physicists has decided to collaborate in producing a comprehensive collection of lectures and tutorial reviews covering the field. This second volume follows the successful Lect. Notes Phys. 818 (Vol.1), and comprises six extensive lectures covering the following topics: - Microscopic cluster models - Neutron halo and break-up reactions - Break-up reaction models for two- and three-cluster projectiles - Clustering effects within the di-nuclear model - Nuclear alpha-particle condensates - Clusters in nuclei: experimental perspectives By promoting new ideas and developments while retaining a pedagogical style of presentation throughout, these lectures will serve as both a reference and an advanced teaching manual for future courses and schools in the fields of nuclear physics and nuclear astrophysics. (orig.)

Synthesis and crystal structure of new K and Rb selenido/tellurido ferrate cluster compounds

Energy Technology Data Exchange (ETDEWEB)

Stueble, Pirmin; Berroth, Angela; Roehr, Caroline [Freiburg Univ. (Germany). Inst. fuer Anorganische und Analytische Chemie

2016-08-01

In the course of a systematic study of alkali iron chalcogenido salts containing clusters [Fe{sub 4}Q{sub 8}] a series of new mixed-valent potassium and rubidium selenido and tellurido ferrates(II/III) was synthesized by carefully heating the pure elements enclosed in sample tubes under an argon atmosphere up to maximum temperatures of 800-900 C. Their crystal structures have been determined by means of single crystal X-ray diffraction. The mixed-valent Fe{sup II/III} tellurido ferrates A{sub 7}[Fe{sub 4}Te{sub 8}] form three different structure types. All structures contain tetramers of four edge sharing [FeTe{sub 4}] tetrahedra, which are connected by common edges to form only slightly distorted tetrahedral [Fe{sub 4}Te{sub 8}]{sup 7-} anions ('stella quadrangula') with a [Fe{sub 4}Te{sub 4}] cubane core. In all cases, these anions are surrounded by 26 alkali cations, which are located at the eight corners and the midpoints of the six faces and 12 edges of a cube. The three crystal structures can thus be described by three different packings of cuboid moieties: The monoclinic rubidium compound Rb{sub 7}[Fe{sub 4}Te{sub 8}] (space group C2/c, a = 2000.16(7), b = 897.79(3), c = 1768.12(6) pm, β = 117.4995(10) , Z = 4, R1 = 0.0296) is isotypic to the known cesium tellurido and sulfido ferrates Cs{sub 7}[Fe{sub 4}(S/Te){sub 8}]. Depending on the temperature, K{sub 7}[Fe{sub 4}Te{sub 8}] forms two different but closely related new structure types: The tetragonal r.t. modification (space group P4{sub 2}/nmc, a = 1222.25(14), c = 872.1(2) pm, Z = 2, R1 = 0.0583) crystallizes in a supergroup of the orthorhombic l.t. (100 K) form (space group Pbcn, a = 1715.5, b = 866.76(3), c = 1715.50(7) pm, Z = 4, R1 = 0.0160). In all structures, the cluster centered cubes are stacked to form columns along the short (∼ 870 pm) axis. These columns are themselves densely packed with 4 (both K compounds) and 6 (A = Rb) adjacent face-sharing columns. According to these

K B Shaik

Indian Academy of Sciences (India)

Home; Journals; Resonance – Journal of Science Education. K B Shaik. Articles written in Resonance – Journal of Science Education. Volume 15 Issue 3 March 2010 pp 257-267 Classroom. Chaos from Jerk Circuit · K B Shaik M K Mandal · More Details Fulltext PDF ...

Order-Constrained Solutions in K-Means Clustering: Even Better than Being Globally Optimal

Science.gov (United States)

Steinley, Douglas; Hubert, Lawrence

2008-01-01

This paper proposes an order-constrained K-means cluster analysis strategy, and implements that strategy through an auxiliary quadratic assignment optimization heuristic that identifies an initial object order. A subsequent dynamic programming recursion is applied to optimally subdivide the object set subject to the order constraint. We show that…

Clustering and Symmetry Energy in a Low Density Nuclear Gas

International Nuclear Information System (INIS)

Kowalski, S.; Natowitz, J.B.; Shlomo, S.; Wada, R.; Hagel, K.; Wang, J.; Materna, T.; Chen, Z.; Ma, Y.G.; Qin, L.; Botvina, A.S.; Fabris, D.; Lunardon, M.; Moretto, S.; Nebbia, G.; Pesente, S.; Rizzi, V.; Viesti, G.; Cinausero, M.; Prete, G.; Keutgen, T.; El Masri, Y.; Majka, Z.; Ono, A.

2007-01-01

Temperature and density dependent symmetry energy coefficients have been derived from isoscaling analyses of the yields of nuclei with A= 64 Zn projectiles with 92 Mo and 197 Au target nuclei. The symmetry energies at low density are larger than those obtained in mean field calculations, reflecting the clustering of low density nuclear matter. They are in quite good agreement with results of a recently proposed Virial Equation of State calculation

Automatic video shot boundary detection using k-means clustering and improved adaptive dual threshold comparison

Science.gov (United States)

Sa, Qila; Wang, Zhihui

2018-03-01

At present, content-based video retrieval (CBVR) is the most mainstream video retrieval method, using the video features of its own to perform automatic identification and retrieval. This method involves a key technology, i.e. shot segmentation. In this paper, the method of automatic video shot boundary detection with K-means clustering and improved adaptive dual threshold comparison is proposed. First, extract the visual features of every frame and divide them into two categories using K-means clustering algorithm, namely, one with significant change and one with no significant change. Then, as to the classification results, utilize the improved adaptive dual threshold comparison method to determine the abrupt as well as gradual shot boundaries.Finally, achieve automatic video shot boundary detection system.

Perbandingan Kinerja Metode Ward Dan K-means Dalam Menentukan Cluster Data Mahasiswa Pemohon Beasiswa (Studi Kasus : STMIK Pringsewu)

OpenAIRE

Satria, Fiqih; Aziz, R Z Abdul

2016-01-01

This research aims to determine the steps cluster analysis method with Ward method and K-Means method, and compare the results of the analysis of the two methods for clustering student data related decision-making to determine the students are eligible to receive a Peningkatan PrestasiAkademik (PPA) scholarship and Bantuan Biaya Akademik (BBA) scholarship in STMIK Pringsewu. Cluster analysis was performed using IBM SPSS Version 23. Cluster Analysis results of both methods were compared using ...

R K Mangal

Indian Academy of Sciences (India)

Home; Journals; Bulletin of Materials Science. R K Mangal. Articles written in Bulletin of Materials Science. Volume 29 Issue 7 December 2006 pp 653-657 Semiconductors. Preparation of Al–Sb semiconductor by swift heavy ion irradiation · R K Mangal M Singh Y K Vijay D K Avasthi · More Details Abstract Fulltext PDF.

A K Meikap

Indian Academy of Sciences (India)

Home; Journals; Bulletin of Materials Science. A K Meikap. Articles written in Bulletin of Materials Science. Volume 24 Issue 6 December 2001 pp 649-652 Alloys and Steels. An X-ray diffraction study of defect parameters in a Ti-base alloy · G Karmaker P Mukherjee A K Meikap S K Chattopadhyay S K Chatterjee.

Production of charged pions, kaons and protons at large transverse momenta in pp and Pb-Pb collisions at $\\sqrt{s_{NN}}$ = 2.76 TeV

CERN Document Server

Abelev, Betty Bezverkhny; Adamova, Dagmar; Aggarwal, Madan Mohan; Aglieri Rinella, Gianluca; Agnello, Michelangelo; Agostinelli, Andrea; Agrawal, Neelima; Ahammed, Zubayer; Ahmad, Nazeer; Ahmad, Arshad; Ahmed, Ijaz; Ahn, Sang Un; Ahn, Sul-Ah; Aimo, Ilaria; Aiola, Salvatore; Ajaz, Muhammad; Akindinov, Alexander; Aleksandrov, Dmitry; Alessandro, Bruno; Alexandre, Didier; Alici, Andrea; Alkin, Anton; Alme, Johan; Alt, Torsten; Altini, Valerio; Altinpinar, Sedat; Altsybeev, Igor; Alves Garcia Prado, Caio; Andrei, Cristian; Andronic, Anton; Anguelov, Venelin; Anielski, Jonas; Anticic, Tome; Antinori, Federico; Antonioli, Pietro; Aphecetche, Laurent Bernard; Appelshaeuser, Harald; Arbor, Nicolas; Arcelli, Silvia; Armesto Perez, Nestor; Arnaldi, Roberta; Aronsson, Tomas; Arsene, Ionut Cristian; Arslandok, Mesut; Augustinus, Andre; Averbeck, Ralf Peter; Awes, Terry; Azmi, Mohd Danish; Bach, Matthias Jakob; Badala, Angela; Baek, Yong Wook; Bagnasco, Stefano; Bailhache, Raphaelle Marie; Bairathi, Vipul; 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2014-07-07

Transverse momentum spectra of $\\pi^{\\pm}, K^{\\pm}$ and $p(\\bar{p})$ up to $p_T$ = 20 GeV/c at mid-rapidity, |y| $\\le$ 0.8, in pp and Pb-Pb collisions at $\\sqrt{s_{NN}}$ = 2.76 TeV have been measured using the ALICE detector at the LHC. At intermediate $p_T$ (2-8 GeV/c) an enhancement of the proton-to-proton ratio, (p + $\\bar{p})/(\\pi^+ + \\pi^-$), with respect to pp collisions is observed and the ratio reaches ~0.80 in central Pb-Pb collisions. The measurement of the nuclear modification factors for $\\pi^{\\pm}, K^{\\pm}$ and $p(\\bar{p})$ indicates that within the systematic and statistical uncertainties they are the same at high $p_T$ (> 10 GeV/c), suggesting that the chemical composition of leading particles from jets in the medium is similar to that of vacuum jets.

Projection-based curve clustering

International Nuclear Information System (INIS)

Auder, Benjamin; Fischer, Aurelie

2012-01-01

This paper focuses on unsupervised curve classification in the context of nuclear industry. At the Commissariat a l'Energie Atomique (CEA), Cadarache (France), the thermal-hydraulic computer code CATHARE is used to study the reliability of reactor vessels. The code inputs are physical parameters and the outputs are time evolution curves of a few other physical quantities. As the CATHARE code is quite complex and CPU time-consuming, it has to be approximated by a regression model. This regression process involves a clustering step. In the present paper, the CATHARE output curves are clustered using a k-means scheme, with a projection onto a lower dimensional space. We study the properties of the empirically optimal cluster centres found by the clustering method based on projections, compared with the 'true' ones. The choice of the projection basis is discussed, and an algorithm is implemented to select the best projection basis among a library of orthonormal bases. The approach is illustrated on a simulated example and then applied to the industrial problem. (authors)

Observation of B(s)0-->K+ K- and measurements of branching fractions of charmless two-body decays of B0 and B(s)0 mesons in pp collisions at square root of s = 1.96 TeV.

Science.gov (United States)

Abulencia, A; Acosta, D; Adelman, J; Affolder, T; Akimoto, T; Albrow, M G; Ambrose, D; Amerio, S; Amidei, D; Anastassov, A; Anikeev, K; Annovi, A; Antos, J; Aoki, M; Apollinari, G; Arguin, J-F; Arisawa, T; Artikov, A; Ashmanskas, W; Attal, A; Azfar, F; Azzi-Bacchetta, P; Azzurri, P; Bacchetta, N; Bachacou, H; Badgett, W; Barbaro-Galtieri, A; Barnes, V E; Barnett, B A; Baroiant, S; Bartsch, V; Bauer, G; Bedeschi, F; Behari, S; Belforte, S; Bellettini, G; Bellinger, J; Belloni, A; Ben Haim, E; Benjamin, D; Beretvas, A; Beringer, J; Berry, T; Bhatti, A; Binkley, M; Bisello, D; Blair, R E; Blocker, C; Blumenfeld, B; Bocci, A; Bodek, A; Boisvert, V; Bolla, G; Bolshov, A; Bortoletto, D; Boudreau, J; Boveia, A; Brau, B; Bromberg, C; Brubaker, E; Budagov, J; Budd, H S; Budd, S; Burkett, K; Busetto, G; Bussey, P; Byrum, K L; Cabrera, S; Campanelli, M; Campbell, M; Canelli, F; Canepa, A; Carlsmith, D; Carosi, R; Carron, S; Casarsa, M; Castro, A; Catastini, P; Cauz, D; Cavalli-Sforza, M; Cerri, A; Cerrito, L; Chang, S H; Chapman, J; Chen, Y C; Chertok, M; Chiarelli, G; Chlachidze, G; Chlebana, F; Cho, I; Cho, K; Chokheli, D; Chou, J P; Chu, P H; Chuang, S H; Chung, K; Chung, W H; Chung, Y S; Ciljak, M; Ciobanu, C I; Ciocci, M A; Clark, A; Clark, D; Coca, M; Compostella, G; Convery, M E; Conway, J; Cooper, B; Copic, K; Cordelli, M; Cortiana, G; Crescioli, F; Cruz, A; Cuenca Almenar, C; Cuevas, J; Culbertson, R; Cyr, D; Daronco, S; D'Auria, S; D'Onofrio, M; Dagenhart, D; de Barbaro, P; De Cecco, S; Deisher, A; De Lentdecker, G; Dell'Orso, M; Delli Paoli, F; Demers, S; Demortier, L; Deng, J; Deninno, M; De Pedis, D; Derwent, P F; Dionisi, C; Dittmann, J R; DiTuro, P; Dörr, C; Donati, S; Donega, M; Dong, P; Donini, J; Dorigo, T; Dube, S; Ebina, K; Efron, J; Ehlers, J; Erbacher, R; Errede, D; Errede, S; Eusebi, R; Fang, H C; Farrington, S; Fedorko, I; Fedorko, W T; Feild, R G; Feindt, M; Fernandez, J P; Field, R; Flanagan, G; Flores-Castillo, L R; Foland, A; Forrester, S; Foster, G W; Franklin, M; Freeman, J C; Furic, I; Gallinaro, M; Galyardt, J; Garcia, J E; Garcia Sciveres, M; Garfinkel, A F; Gay, C; Gerberich, H; Gerdes, D; Giagu, S; Giannetti, P; Gibson, A; Gibson, K; Ginsburg, C; Giokaris, N; Giolo, K; Giordani, M; Giromini, P; Giunta, M; Giurgiu, G; Glagolev, V; Glenzinski, D; Gold, M; Goldschmidt, N; Goldstein, J; Gomez, G; Gomez-Ceballos, G; Goncharov, M; González, O; Gorelov, I; Goshaw, A T; Gotra, Y; Goulianos, K; Gresele, A; Griffiths, M; Grinstein, S; Grosso-Pilcher, C; Grundler, U; Guimaraes da Costa, J; Gunay-Unalan, Z; Haber, C; Hahn, S R; Hahn, K; Halkiadakis, E; Hamilton, A; Han, B-Y; Han, J Y; Handler, R; Happacher, F; Hara, K; Hare, M; Harper, S; Harr, R F; Harris, R M; Hatakeyama, K; Hauser, J; Hays, C; Heijboer, A; Heinemann, B; Heinrich, J; Herndon, M; Hidas, D; Hill, C S; Hirschbuehl, D; Hocker, A; Holloway, A; Hou, S; Houlden, M; Hsu, S-C; Huffman, B T; Hughes, R E; Huston, J; Incandela, J; Introzzi, G; Iori, M; Ishizawa, Y; Ivanov, A; Iyutin, B; James, E; Jang, D; Jayatilaka, B; Jeans, D; Jensen, H; Jeon, E J; Jindariani, S; Jones, M; Joo, K K; Jun, S Y; Junk, T R; Kamon, T; Kang, J; Karchin, P E; Kato, Y; Kemp, Y; Kephart, R; Kerzel, U; Khotilovich, V; Kilminster, B; Kim, D H; Kim, H S; Kim, J E; Kim, M J; Kim, S B; Kim, S H; Kim, Y K; Kirsch, L; Klimenko, S; Klute, M; Knuteson, B; Ko, B R; Kobayashi, H; Kondo, K; Kong, D J; Konigsberg, J; Korytov, A; Kotwal, A V; Kovalev, A; Kraan, A; Kraus, J; Kravchenko, I; Kreps, M; Kroll, J; Krumnack, N; Kruse, M; Krutelyov, V; Kuhlmann, S E; Kusakabe, Y; Kwang, S; Laasanen, A T; Lai, S; Lami, S; Lammel, S; Lancaster, M; Lander, R L; Lannon, K; Lath, A; Latino, G; Lazzizzera, I; LeCompte, T; Lee, J; Lee, J; Lee, Y J; Lee, S W; Lefèvre, R; Leonardo, N; Leone, S; Levy, S; Lewis, J D; Lin, C; Lin, C S; Lindgren, M; Lipeles, E; Lister, A; Litvintsev, D O; Liu, T; Lockyer, N S; Loginov, A; Loreti, M; Loverre, P; Lu, R-S; Lucchesi, D; Lujan, P; Lukens, P; Lungu, G; Lyons, L; Lys, J; Lysak, R; Lytken, E; Mack, P; MacQueen, D; Madrak, R; Maeshima, K; Maki, T; Maksimovic, P; Malde, S; Manca, G; Margaroli, F; Marginean, R; Marino, C; Martin, A; Martin, V; Martínez, M; Maruyama, T; Mastrandrea, P; Matsunaga, H; Mattson, M E; Mazini, R; Mazzanti, P; McFarland, K S; McIntyre, P; McNulty, R; Mehta, A; Menzemer, S; Menzione, A; Merkel, P; Mesropian, C; Messina, A; von der Mey, M; Miao, T; Miladinovic, N; Miles, J; Miller, R; Miller, J S; Mills, C; Milnik, M; Miquel, R; Mitra, A; Mitselmakher, G; Miyamoto, A; Moggi, N; Mohr, B; Moore, R; Morello, M; Movilla Fernandez, P; Mülmenstädt, J; Mukherjee, A; Muller, Th; Mumford, R; Murat, P; Nachtman, J; Naganoma, J; Nahn, S; Nakano, I; Napier, A; Naumov, D; Necula, V; Neu, C; Neubauer, M S; Nielsen, J; Nigmanov, T; Nodulman, L; Norniella, O; Nurse, E; Ogawa, T; Oh, S H; Oh, Y D; Okusawa, T; Oldeman, R; Orava, R; Osterberg, K; Pagliarone, C; Palencia, E; Paoletti, R; Papadimitriou, V; Paramonov, A A; Parks, B; Pashapour, S; Patrick, J; Pauletta, G; Paulini, M; Paus, C; Pellett, D E; Penzo, A; Phillips, T J; Piacentino, G; Piedra, J; Pinera, L; Pitts, K; Plager, C; Pondrom, L; Portell, X; Poukhov, O; Pounder, N; Prakoshyn, F; Pronko, A; Proudfoot, J; Ptohos, F; Punzi, G; Pursley, J; Rademacker, J; Rahaman, A; Rakitin, A; Rappoccio, S; Ratnikov, F; Reisert, B; Rekovic, V; van Remortel, N; Renton, P; Rescigno, M; Richter, S; Rimondi, F; Ristori, L; Robertson, W J; Robson, A; Rodrigo, T; Rogers, E; Rolli, S; Roser, R; Rossi, M; Rossin, R; Rott, C; Ruiz, A; Russ, J; Rusu, V; Saarikko, H; Sabik, S; Safonov, A; Sakumoto, W K; Salamanna, G; Saltó, O; Saltzberg, D; Sanchez, C; Santi, L; Sarkar, S; Sartori, L; Sato, K; Savard, P; Savoy-Navarro, A; Scheidle, T; Schlabach, P; Schmidt, E E; Schmidt, M P; Schmitt, M; Schwarz, T; Scodellaro, L; Scott, A L; Scribano, A; Scuri, F; Sedov, A; Seidel, S; Seiya, Y; Semenov, A; Sexton-Kennedy, L; Sfiligoi, I; Shapiro, M D; Shears, T; Shepard, P F; Sherman, D; Shimojima, M; Shochet, M; Shon, Y; Shreyber, I; Sidoti, A; Sinervo, P; Sisakyan, A; Sjolin, J; Skiba, A; Slaughter, A J; Sliwa, K; Smith, J R; Snider, F D; Snihur, R; Soderberg, M; Soha, A; Somalwar, S; Sorin, V; Spalding, J; Spezziga, M; Spinella, F; Spreitzer, T; Squillacioti, P; Stanitzki, M; Staveris-Polykalas, A; St Denis, R; Stelzer, B; Stelzer-Chilton, O; Stentz, D; Strologas, J; Stuart, D; Suh, J S; Sukhanov, A; Sumorok, K; Sun, H; Suzuki, T; Taffard, A; Takashima, R; Takeuchi, Y; Takikawa, K; Tanaka, M; Tanaka, R; Tanimoto, N; Tecchio, M; Teng, P K; Terashi, K; Tether, S; Thom, J; Thompson, A S; Thomson, E; Tipton, P; Tiwari, V; Tkaczyk, S; Toback, D; Tokar, S; Tollefson, K; Tomura, T; Tonelli, D; Tönnesmann, M; Torre, S; Torretta, D; Tourneur, S; Trischuk, W; Tsuchiya, R; Tsuno, S; Turini, N; Ukegawa, F; Unverhau, T; Uozumi, S; Usynin, D; Vaiciulis, A; Vallecorsa, S; Varganov, A; Vataga, E; Velev, G; Veramendi, G; Veszpremi, V; Vidal, R; Vila, I; Vilar, R; Vine, T; Vollrath, I; Volobouev, I; Volpi, G; Würthwein, F; Wagner, P; Wagner, R G; Wagner, R L; Wagner, W; Wallny, R; Walter, T; Wan, Z; Wang, S M; Warburton, A; Waschke, S; Waters, D; Wester, W C; Whitehouse, B; Whiteson, D; Wicklund, A B; Wicklund, E; Williams, G; Williams, H H; Wilson, P; Winer, B L; Wittich, P; Wolbers, S; Wolfe, C; Wright, T; Wu, X; Wynne, S M; Yagil, A; Yamamoto, K; Yamaoka, J; Yamashita, T; Yang, C; Yang, U K; Yang, Y C; Yao, W M; Yeh, G P; Yoh, J; Yorita, K; Yoshida, T; Yu, G B; Yu, I; Yu, S S; Yun, J C; Zanello, L; Zanetti, A; Zaw, I; Zetti, F; Zhang, X; Zhou, J; Zucchelli, S

2006-11-24

We search for decays of the type B(s)0-->h+ h'- (where h,h' = K or pi) in 180 pb(-1) of pp collisions collected at the Tevatron by the upgraded Collider Detector at Fermilab. We report the first observation of the new mode B(s)0-->K+ K- with a yield of 236+/-32 events, corresponding to (fs/fd) x B(B(s)0-->K+ K-)/B(B0-->K+ pi-) = 0.46+/-0.08stat+/-0.07syst, where fs/fd is the ratio of production fractions of B(s)0 and B0. We find results in agreement with world averages for the B0 modes, and set the following new limits at 90% C.L.: B(B(s)0-->K- pi+) pi+ pi-) < 1.7 x 10(-6).

K Girigowda

Indian Academy of Sciences (India)

Home; Journals; Resonance – Journal of Science Education. K Girigowda. Articles written in Resonance – Journal of Science Education. Volume 10 Issue 11 November 2005 pp 79-84 Classroom. Loading Effects on Resolution in Thin Layer Chromatography and Paper Chromatography · K Girigowda V H Mulimani.

Parallel k-means++

Energy Technology Data Exchange (ETDEWEB)

2017-04-04

A parallelization of the k-means++ seed selection algorithm on three distinct hardware platforms: GPU, multicore CPU, and multithreaded architecture. K-means++ was developed by David Arthur and Sergei Vassilvitskii in 2007 as an extension of the k-means data clustering technique. These algorithms allow people to cluster multidimensional data, by attempting to minimize the mean distance of data points within a cluster. K-means++ improved upon traditional k-means by using a more intelligent approach to selecting the initial seeds for the clustering process. While k-means++ has become a popular alternative to traditional k-means clustering, little work has been done to parallelize this technique. We have developed original C++ code for parallelizing the algorithm on three unique hardware architectures: GPU using NVidia's CUDA/Thrust framework, multicore CPU using OpenMP, and the Cray XMT multithreaded architecture. By parallelizing the process for these platforms, we are able to perform k-means++ clustering much more quickly than it could be done before.

The performance of a new Geant4 Bertini intra-nuclear cascade model in high throughput computing (HTC) cluster architecture

Energy Technology Data Exchange (ETDEWEB)

Aatos, Heikkinen; Andi, Hektor; Veikko, Karimaki; Tomas, Linden [Helsinki Univ., Institute of Physics (Finland)

2003-07-01

We study the performance of a new Bertini intra-nuclear cascade model implemented in the general detector simulation tool-kit Geant4 with a High Throughput Computing (HTC) cluster architecture. A 60 node Pentium III open-Mosix cluster is used with the Mosix kernel performing automatic process load-balancing across several CPUs. The Mosix cluster consists of several computer classes equipped with Windows NT workstations that automatically boot, daily and become nodes of the Mosix cluster. The models included in our study are a Bertini intra-nuclear cascade model with excitons, consisting of a pre-equilibrium model, a nucleus explosion model, a fission model and an evaporation model. The speed and accuracy obtained for these models is presented. (authors)

D K Banerjee

Indian Academy of Sciences (India)

Home; Journals; Resonance – Journal of Science Education. D K Banerjee. Articles written in Resonance – Journal of Science Education. Volume 18 Issue 2 February 2013 pp 188-193 Classics. On the Stereoselective Synthesis of Oestrone · D K Banerjee K M Sivanandaiah · More Details Fulltext PDF ...

Stroke localization and classification using microwave tomography with k-means clustering and support vector machine.

Science.gov (United States)

Guo, Lei; Abbosh, Amin

2018-05-01

For any chance for stroke patients to survive, the stroke type should be classified to enable giving medication within a few hours of the onset of symptoms. In this paper, a microwave-based stroke localization and classification framework is proposed. It is based on microwave tomography, k-means clustering, and a support vector machine (SVM) method. The dielectric profile of the brain is first calculated using the Born iterative method, whereas the amplitude of the dielectric profile is then taken as the input to k-means clustering. The cluster is selected as the feature vector for constructing and testing the SVM. A database of MRI-derived realistic head phantoms at different signal-to-noise ratios is used in the classification procedure. The performance of the proposed framework is evaluated using the receiver operating characteristic (ROC) curve. The results based on a two-dimensional framework show that 88% classification accuracy, with a sensitivity of 91% and a specificity of 87%, can be achieved. Bioelectromagnetics. 39:312-324, 2018. © 2018 Wiley Periodicals, Inc. © 2018 Wiley Periodicals, Inc.

A K Singh

Indian Academy of Sciences (India)

Home; Journals; Bulletin of Materials Science. A K Singh. Articles written in Bulletin of Materials Science. Volume 24 Issue 6 December 2001 pp 633-638 Alloys and Steels. Analysis of stainless steel samples by energy dispersive X-ray fluorescence (EDXRF) spectrometry · M K Tiwari A K Singh K J S Sawhney · More Details ...

K C Mittal

Indian Academy of Sciences (India)

K C Mittal. Articles written in Sadhana. Volume 30 Issue 6 December 2005 pp 757-764. Development of a 300-kV Marx generator and its application to drive a relativistic electron beam · Y Choyal Lalit Gupta Preeti Vyas Prasad Deshpande Anamika Chaturvedi K C Mittal K P Maheshwari · More Details Abstract Fulltext PDF.

Measurements of $K^{0}_{s}$, \\PgL\\ + \\PagL, and $\\Xi^{+}+\\Xi^{-}$ production in pp, pPb, and PbPb collisions with CMS

CERN Document Server

Ni, Hong

2016-01-01

We present measurements of strange hadron ($K^{0}_{s}$, \\PgL\\ + \\PagL, and $\\Xi^{+} + \\Xi^{-}$) transverse momentum ($p^{}_{T}$) spectra in pp, pPb, and PbPb collisions over a wide range in charge-particle multiplicity and particle rapidity. The data were taken with the CMS detector at the LHC for pp collisions at $\\sqrt{s}$ = 7 TeV, pPb collisions at $\\sqrt{s_{NN}}$ = 5.02 TeV, and PbPb collisions at $\\sqrt{s_{NN}}$ = 2.76 TeV. We find the average transverse kinetic energy ($KE^{}_{T}$) increases with event multiplicity, with a faster rate for heavier particle species. At similar multiplicities, we observe the separation in the $\\left\\langle KE^{}_{T} \\right\\rangle$, which is defined as $\\left\\langle KE^{}_{T} \\right\\rangle = \\left\\langle m_{T}\\right\\rangle - m$, where $m_T = \\sqrt{m^{2} + p_{T}^{2}}$, between different particle species is larger for pp and pPb systems than PbPb system. In pPb collisions, $\\left\\langle KE^{}_{T} \\right\\rangle$ is found to be larger in the Pb-going direction than in the p-goi...

Performance Analysis of Combined Methods of Genetic Algorithm and K-Means Clustering in Determining the Value of Centroid

Science.gov (United States)

Adya Zizwan, Putra; Zarlis, Muhammad; Budhiarti Nababan, Erna

2017-12-01

The determination of Centroid on K-Means Algorithm directly affects the quality of the clustering results. Determination of centroid by using random numbers has many weaknesses. The GenClust algorithm that combines the use of Genetic Algorithms and K-Means uses a genetic algorithm to determine the centroid of each cluster. The use of the GenClust algorithm uses 50% chromosomes obtained through deterministic calculations and 50% is obtained from the generation of random numbers. This study will modify the use of the GenClust algorithm in which the chromosomes used are 100% obtained through deterministic calculations. The results of this study resulted in performance comparisons expressed in Mean Square Error influenced by centroid determination on K-Means method by using GenClust method, modified GenClust method and also classic K-Means.

11th International Conference on Clustering Aspects of Nuclear Structure and Dynamics

International Nuclear Information System (INIS)

2017-01-01

Preface The 11 th edition of the International Conference on Clustering Aspects of Nuclear Structure and Dynamics (CLUSTER‘16) was held in Napoli, Italy, on May 23-27 2016. All the Conference Sessions took place in the magnificent Complesso Monumentale dei Ss. Marcellino e Festo , located in the Historical Centre of Naples. This is one of the most prestigious building complexes of the Federico II University of Naples, the main home institution of the organizers, together with the Istituto Nazionale di Fisica Nucleare (Naples division). This building is 500 years old; in the XVIII century, it was reshaped by Luigi Vanvitelli, a famous architect of the pre-Neoclassical period in Italy, designer of the prestigious Royal Palace in the near town of Caserta. The site of Plenary Sessions was the Church of Ss. Marcellino e Festo , where all the participants were surrounded by the Baroque frescoes by Belisario Corenzio and, among the others, the paintings of Battistello Caracciolo, Massimo Stanzione, Giuseppe Simonelli and Francesco De Mura, important artists of the late Baroque period in South Italy. The sites of Parallel Sessions were two halls in the arcade of the S. Marcellino cloister: this gave the opportunity to the participants to enjoy the beauty of the architecture of the cloister with its fountains, gardens, sculptures. As organizers of the Conference, our main aims were: (1) to provide an excellent programme, with the expectation to be a reference point for the Nuclear Cluster Physics in the next four years; (2) to assure a very relaxing stay to the participants, allowing them to explore the bounty of artistic, and also culinary, masterpieces that Naples offers to its guests. The first point was assured by all the conveners that, with their excellent talks, gave a very precise and complete overview of the most recent achievements on Nuclear Cluster Physics, both from the experimental and theoretical point of view. We are indebted with the International

K Gowthamarajan

Indian Academy of Sciences (India)

Home; Journals; Resonance – Journal of Science Education. K Gowthamarajan. Articles written in Resonance – Journal of Science Education. Volume 8 Issue 5 May 2003 pp 38-46 General Article. Oral Insulin – Fact or Fiction? - Possibilities of Achieving Oral Delivery of Insulin · K Gowthamarajan Giriraj T Kulkarni.

MARs Wars: heterogeneity and clustering of DNA-binding domains in the nuclear matrix

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Ioudinkova E. S.

2009-12-01

Full Text Available Aim. CO326 is a chicken nuclear scaffold/matrix attachment region (MAR associated with the nuclear matrix in several types of chicken cells. It contains a binding site for a sequence-specific DNA-binding protein, F326. We have studied its interaction with the nuclear matrix. Methods. We have used an in vitro MAR assay with isolated matrices from chicken HD3 cells. Results. We have found that an oligonucleotide binding site for the F326 inhibits binding of the CO326 to the nuclear matrix. At the same time, the binding of heterologous MARs is enhanced. Conclusions. Taken together, these data suggest that there exist several classes of MARs and MAR-binding domains and that the MAR-binding proteins may be clustered in the nuclear matrix.

Characterization program management plan for Hanford K basin spent nuclear fuel

International Nuclear Information System (INIS)

TRIMBLE, D.J.

1999-01-01

The program management plan for characterization of the K Basin spent nuclear fuel was revised to incorporate corrective actions in response to SNF Project QA surveillance 1K-FY-99-060. This revision of the SNF Characterization PMP replaces Duke Eng

Range-clustering queries

NARCIS (Netherlands)

Abrahamsen, M.; de Berg, M.T.; Buchin, K.A.; Mehr, M.; Mehrabi, A.D.

2017-01-01

In a geometric k -clustering problem the goal is to partition a set of points in R d into k subsets such that a certain cost function of the clustering is minimized. We present data structures for orthogonal range-clustering queries on a point set S : given a query box Q and an integer k>2 , compute

Development of the COMPRE-A Program for Evaluating Proliferation Resistance (PR) and Physical Protection (PP) of the Nuclear Facility

Energy Technology Data Exchange (ETDEWEB)

Kim, Sukhoon; Kim, Juyub; Shin, Kwangyoung [FNC Technology Co., Yongin (Korea, Republic of); Seo, Janghoon; Jang, Sungsoon; Yoo, Hosik [Korea Institute of Nuclear Non-proliferation and Control, Daejeon (Korea, Republic of)

2016-10-15

In order to make up for the limitation inherent in these methodologies, a new methodology called 'Comprehensive Methodology for PR and PP Evaluation (COMPRE)' is being developed by the Korea Institute of Nuclear Non-proliferation and Control (KINAC). Currently, a project for improving a computational program implementing the COMPRE methodology is ongoing in KINAC, and the 'COMPRE-A (i.e. COMPRE-Advanced model)' program was developed as part of this project. This paper describes details of the COMPRE-A program developed for establishing the platform corresponding to features of the evaluation factor derived for COMPRE, and for enhancing easiness of the result analysis through embodying the visualization and comparison tools for the evaluation result. As part of the project for improving a computational program implementing the COMPRE methodology, the COMPRE-A program was developed. This program provides not only the platform corresponding to features of the evaluation factor derived for COMPRE but also the visualization and comparison tools for enhancing easiness of the result analysis. The V and V for the developed program was performed through comparison with the result obtained by using MS-Excel for a sample case consisting of three (3) measures, six (6) sections and twenty-six (26) attributes. From the comparison result, it was confirmed that the risk in aspects of PR and PP at nuclear facilities could be quantitatively evaluated within the acceptable range using the COMPRE-A program.

Inclusive γ, π0, K0, and Λ production in 12.4-GeV/c pp interactions

International Nuclear Information System (INIS)

Jaeger, K.; Campbell, J.; Charlton, G.; Swanson, D.; Fu, C.; Rubin, H.A.; Glasser, R.G.; Koetke, D.; Whitmore, J.

1975-01-01

In an exposure of the Argonne National Laboratory 12-foot hydrogen bubble chamber to a beam of 12.4-GeV/c protons, we have measured the total and differential cross sections for the inclusive reactions p + p → γ + X, π 0 + X, K 0 + X, and Λ + X, as well as estimates for the inclusive eta and Σ 0 cross sections. We present the average number of π 0 , K 0 , and Λ as a function of the associated charge multiplicity. We observe that the average charge multiplicity in pp collisions is the same whether or not a π 0 , K 0 , or Λ is also produced in the interaction. Invariant cross sections are presented as a function of P/subT/ 2 and x, the Feynman scaling variable. The π 0 differential cross sections are consistent with the relation (dsigma/dP)(π 0 ) = 1 / 2 [(dsigma/dP)(π + ) + (dsigma/dP)(π - )]/2 for all pion momenta P. The differential cross section for Λ production indicates a break in the distribution of vertical-bart - t/sub min/vertical-bar = 1.4 (GeV/c) 2 . The polarization of the Λ's is found to be consistent with zero for all values of x

Surface EMG decomposition based on K-means clustering and convolution kernel compensation.

Science.gov (United States)

Ning, Yong; Zhu, Xiangjun; Zhu, Shanan; Zhang, Yingchun

2015-03-01

A new approach has been developed by combining the K-mean clustering (KMC) method and a modified convolution kernel compensation (CKC) method for multichannel surface electromyogram (EMG) decomposition. The KMC method was first utilized to cluster vectors of observations at different time instants and then estimate the initial innervation pulse train (IPT). The CKC method, modified with a novel multistep iterative process, was conducted to update the estimated IPT. The performance of the proposed K-means clustering-Modified CKC (KmCKC) approach was evaluated by reconstructing IPTs from both simulated and experimental surface EMG signals. The KmCKC approach successfully reconstructed all 10 IPTs from the simulated surface EMG signals with true positive rates (TPR) of over 90% with a low signal-to-noise ratio (SNR) of -10 dB. More than 10 motor units were also successfully extracted from the 64-channel experimental surface EMG signals of the first dorsal interosseous (FDI) muscles when a contraction force was held at 8 N by using the KmCKC approach. A "two-source" test was further conducted with 64-channel surface EMG signals. The high percentage of common MUs and common pulses (over 92% at all force levels) between the IPTs reconstructed from the two independent groups of surface EMG signals demonstrates the reliability and capability of the proposed KmCKC approach in multichannel surface EMG decomposition. Results from both simulated and experimental data are consistent and confirm that the proposed KmCKC approach can successfully reconstruct IPTs with high accuracy at different levels of contraction.

Nuclear reactors

International Nuclear Information System (INIS)

Pearson, K.G.

1977-01-01

Reference is made to auxiliary means of cooling the nuclear fuel clusters used in light or heavy water cooled nuclear reactors. One method is to provide one or more spray cooling tubes. From holes in the side walls of those tubes coolant water may be sprayed laterally into the cluster against the rods. The flow of main coolant may thus be supplemented or even replaced by the auxiliary coolant. A difficulty, however, is that only those fuel rods close to a spray cooling tube can readily be reached by the auxiliary coolant. In the arrangement described, where the fuel rods are spaced apart by transverse grids, at least one of the interspaces between the grids is provided with an axially extending auxiliary coolant conduit having lateral holes through which an auxiliary coolant is sprayed into the cluster. A deflector is provided that extends from a transverse grid into a position in front of the holes and deflects auxiliary coolant on to parts of the fuel rods otherwise inaccessible to the auxiliary coolant. The construction of the deflector is described. (U.K.)

Transverse Momentum Spectra of KS0 and K*0 at Midrapidity in d + Au, Cu + Cu, and p+p Collisions at √(sNN)=200 GeV

International Nuclear Information System (INIS)

Zhang, Guo-Xing; Li, Bao-Chun; Guo, Yuan-Yuan

2015-01-01

We analyze transverse momentum spectra of K S 0 and K *0 at midrapidity in d + Au, Cu + Cu, and p+p collisions at √(s NN )=200 GeV in the formworks of Tsallis statistics and Boltzmann statistics, respectively. Both of them can describe the transverse momentum spectra and extract the thermodynamics parameters of matter evolution in the collisions. The parameters are helpful for us to understand the thermodynamics factors of the particle production

Charged kaon femtoscopic correlations in pp collisions at $\\sqrt{s}=7$ TeV

CERN Document Server

Abelev, B; Adamova, D; Adare, A M; Aggarwal, M M; Aglieri Rinella, G; Agnello, M; Agocs, A G; Agostinelli, A; Ahammed, Z; Ahmad, N; Ahmad Masoodi, A; Ahn, S U; Ahn, S A; Ajaz, M; Akindinov, A; Aleksandrov, D; Alessandro, B; Alici, A; Alkin, A; Almaraz Avina, E; Alme, J; Alt, T; Altini, V; Altinpinar, S; Altsybeev, I; Andrei, C; Andronic, A; Anguelov, V; Anielski, J; Anson, C; Anticic, T; Antinori, F; Antonioli, P; Aphecetche, L; Appelshauser, H; Arbor, N; Arcelli, S; Arend, A; Armesto, N; Arnaldi, R; Aronsson, T; Arsene, I C; Arslandok, M; Asryan, A; Augustinus, A; Averbeck, R; Awes, T C; Aysto, J; Azmi, M D; Bach, M; Badala, A; Baek, Y W; Bailhache, R; Bala, R; Baldini Ferroli, R.; Baldisseri, A; Baltasar Dos Santos Pedrosa, F; Ban, J; Baral, R C; Barbera, R; Barile, F; Barnafoldi, G G; Barnby, L S; Barret, V; Bartke, J; Basile, M; Bastid, N; Basu, S; Bathen, B; Batigne, G; Batyunya, B; Baumann, C; Bearden, I G; Beck, H; Behera, N K; Belikov, I; Bellini, F; Bellwied, R; Belmont-Moreno, E; Bencedi, G; Beole, S; Berceanu, I; Bercuci, A; Berdnikov, Y; Berenyi, D; Bergognon, A A E; Berzano, D; Betev, L; Bhasin, A; Bhati, A K; Bhom, J; Bianchi, L; Bianchi, N; Bielcik, J; Bielcikova, J; Bilandzic, A; Bjelogrlic, S; Blanco, F; Blanco, F; Blau, D; Blume, C; Boccioli, M; Bottger, S; Bogdanov, A; Boggild, H; Bogolyubsky, M; Boldizsar, L; Bombara, M; Book, J; Borel, H; Borissov, A; Bossu, F; Botje, M; Botta, E; Braidot, E; Braun-Munzinger, P; Bregant, M; Breitner, T; Browning, T A; Broz, M; Brun, R; Bruna, E; Bruno, G E; Budnikov, D; Buesching, H; Bufalino, S; Buncic, P; Busch, O; Buthelezi, Z; Caballero Orduna, D.; Caffarri, D; Cai, X; Caines, H; Calvo Villar, E; Camerini, P; Canoa Roman, V; Cara Romeo, G; Carena, F; Carena, W; Carlin Filho, N; Carminati, F; Casanova Diaz, A; Castillo Castellanos, J; Castillo Hernandez, J F; Casula, E A R; Catanescu, V; Cavicchioli, C; Ceballos Sanchez, C; Cepila, J; Cerello, P; Chang, B; Chapeland, S; Charvet, J L; Chattopadhyay, S; Chattopadhyay, S; Chawla, I; Cherney, M; Cheshkov, C; Cheynis, B; Chibante Barroso, V; Chinellato, D D; Chochula, P; Chojnacki, M; Choudhury, S; Christakoglou, P; Christensen, C H; Christiansen, P; Chujo, T; Chung, S U; Cicalo, C; Cifarelli, L; Cindolo, F; Cleymans, J; Coccetti, F; Colamaria, F; Colella, D; Collu, A; Conesa Balbastre, G; Conesa del Valle, Z; Connors, M E; Contin, G; Contreras, J G; Cormier, T M; Corrales Morales, Y; Cortese, P; Cortes Maldonado, I; Cosentino, M R; Costa, F; Cotallo, M E; Crescio, E; Crochet, P; Cruz Alaniz, E; Cuautle, E; Cunqueiro, L; Dainese, A; Dalsgaard, H H; Danu, A; Das, S; Das, I; Das, D; Das, K; Dash, A; Dash, S; De, S; de Barros, G O V; De Caro, A; De Cataldo, G; de Cuveland, J; De Falco, A; De Gruttola, D; Delagrange, H; Deloff, A; De Marco, N; Denes, E; De Pasquale, S; Deppman, A; D'Erasmo, G; de Rooij, R; Diaz Corchero, M A; Di Bari, D; Dietel, T; Di Giglio, C; Di Liberto, S; Di Mauro, A; Di Nezza, P; Divia, R; Djuvsland, O; Dobrin, A; Dobrowolski, T; Donigus, B; Dordic, O; Driga, O; Dubey, A K; Dubla, A; Ducroux, L; Dupieux, P; Dutta Majumdar, A K; Dutta Majumdar, M R; Elia, D; Emschermann, D; Engel, H; Erazmus, B; Erdal, H A; Espagnon, B; Estienne, M; Esumi, S; Evans, D; Eyyubova, G; Fabris, D; Faivre, J; Falchieri, D; Fantoni, A; Fasel, M; Fearick, R; Fehlker, D; Feldkamp, L; Felea, D; Feliciello, A; Fenton-Olsen, B; Feofilov, G; Fernandez Tellez, A; Ferretti, A; Festanti, A; Figiel, J; Figueredo, M A S; Filchagin, S; Finogeev, D; Fionda, F M; Fiore, E M; Floratos, E; Floris, M; Foertsch, S; Foka, P; Fokin, S; Fragiacomo, E; Francescon, A; Frankenfeld, U; Fuchs, U; Furget, C; Fusco Girard, M; Gaardhoje, J J; Gagliardi, M; Gago, A; Gallio, M; Gangadharan, D R; Ganoti, P; Garabatos, C; Garcia-Solis, E; Garishvili, I; Gerhard, J; Germain, M; Geuna, C; Gheata, M; Gheata, A; Ghosh, P; Gianotti, P; Girard, M R; Giubellino, P; Gladysz-Dziadus, E; Glassel, P; Gomez, R; Ferreiro, E G; Gonzalez-Trueba, L H; Gonzalez-Zamora, P; Gorbunov, S; Goswami, A; Gotovac, S; Graczykowski, L K; Grajcarek, R; Grelli, A; Grigoras, C; Grigoras, A; Grigoriev, V; Grigoryan, S; Grigoryan, A; Grinyov, B; Grion, N; Gros, P; Grosse-Oetringhaus, J F; Grossiord, J Y; Grosso, R; Guber, F; Guernane, R; Guerzoni, B; Guilbaud, M; Gulbrandsen, K; Gulkanyan, H; Gunji, T; Gupta, A; Gupta, R; Haaland, O; Hadjidakis, C; Haiduc, M; Hamagaki, H; Hamar, G; Han, B H; Hanratty, L D; Hansen, A; Harmanova-Tothova, Z; Harris, J W; Hartig, M; Harton, A; Hasegan, D; Hatzifotiadou, D; Hayashi, S; Hayrapetyan, A; Heckel, S T; Heide, M; Helstrup, H; Herghelegiu, A; Herrera Corral, G; Herrmann, N; Hess, B A; Hetland, K F; Hicks, B; Hippolyte, B; Hori, Y; Hristov, P; Hrivnacova, I; Huang, M; Humanic, T J; Hwang, D S; Ichou, R; Ilkaev, R; Ilkiv, I; Inaba, M; Incani, E; Innocenti, G M; Innocenti, P G; Ippolitov, M; Irfan, M; Ivan, C; Ivanov, V; Ivanov, A; Ivanov, M; Ivanytskyi, O; Jacholkowski, A; Jacobs, P M; Jang, H J; Janik, M A; Janik, R; Jayarathna, P.H S Y; Jena, S; Jha, D M; Jimenez Bustamante, R T; Jones, P G; Jung, H; Jusko, A; Kaidalov, A B; Kalcher, S; Kalinak, P; Kalliokoski, T; Kalweit, A; Kang, J H; Kaplin, V; Karasu Uysal, A; Karavichev, O; Karavicheva, T; Karpechev, E; Kazantsev, A; Kebschull, U; Keidel, R; Khan, M M; Khan, P; Khan, K H; Khan, S A; Khanzadeev, A; Kharlov, Y; Kileng, B; Kim, S; Kim, M; Kim, M; Kim, J S; Kim, J H; Kim, D W; Kim, B; Kim, D J; Kim, T; Kirsch, S; Kisel, I; Kiselev, S; Kisiel, A; Klay, J L; Klein, J; Klein-Bosing, C; Kliemant, M; Kluge, A; Knichel, M L; Knospe, A G; Kohler, M K; Kollegger, T; Kolojvari, A; Kompaniets, M; Kondratiev, V; Kondratyeva, N; Konevskikh, A; Kour, R; Kovalenko, V; Kowalski, M; Kox, S; Koyithatta Meethaleveedu, G; Kral, J; Kralik, I; Kramer, F; Kravcakova, A; Krawutschke, T; Krelina, M; Kretz, M; Krivda, M; Krizek, F; Krus, M; Kryshen, E; Krzewicki, M; Kucheriaev, Y; Kugathasan, T; Kuhn, C; Kuijer, P G; Kulakov, I; Kumar, J; Kurashvili, P; Kurepin, A B; Kurepin, A; Kuryakin, A; Kushpil, V; Kushpil, S; Kvaerno, H; Kweon, M J; Kwon, Y; Ladron de Guevara, P; Lakomov, I; Langoy, R; La Pointe, S L; Lara, C; Lardeux, A; La Rocca, P; Lea, R; Lechman, M; Lee, G R; Lee, K S; Lee, S C; Legrand, I; Lehnert, J; Lenhardt, M; Lenti, V; Leon, H; Leon Monzon, I; Leon Vargas, H; Levai, P; Li, S; Lien, J; Lietava, R; Lindal, S; Lindenstruth, V; Lippmann, C; Lisa, M A; Ljunggren, H M; Loenne, P I; Loggins, V R; Loginov, V; Lohner, D; Loizides, C; Loo, K K; Lopez, X; Lopez Torres, E; Lovhoiden, G; Lu, X G; Luettig, P; Lunardon, M; Luo, J; Luparello, G; Luzzi, C; Ma, K; Ma, R; Madagodahettige-Don, D M; Maevskaya, A; Mager, M; Mahapatra, D P; Maire, A; Malaev, M; Maldonado Cervantes, I; Malinina, L; Mal'Kevich, D; Malzacher, P; Mamonov, A; Manceau, L; Mangotra, L; Manko, V; Manso, F; Manzari, V; Mao, Y; Marchisone, M; Mares, J; Margagliotti, G V; Margotti, A; Marin, A; Markert, C; Marquard, M; Martashvili, I; Martin, N A; Martinengo, P; Martinez, M I; Martinez Davalos, A; Martinez Garcia, G; Martynov, Y; Mas, A; Masciocchi, S; Masera, M; Masoni, A; Massacrier, L; Mastroserio, A; Matthews, Z L; Matyja, A; Mayer, C; Mazer, J; Mazzoni, M A; Meddi, F; Menchaca-Rocha, A; Mercado Perez, J; Meres, M; Miake, Y; Mikhailov, K; Milano, L; Milosevic, J; Mischke, A; Mishra, A N; Miskowiec, D; Mitu, C; Mizuno, S; Mlynarz, J; Mohanty, B; Molnar, L; Montano Zetina, L; Monteno, M; Montes, E; Moon, T; Morando, M; Moreira De Godoy, D A; Moretto, S; Morreale, A; Morsch, A; Muccifora, V; Mudnic, E; Muhuri, S; Mukherjee, M; Muller, H; Munhoz, M G; Musa, L; Musinsky, J; Musso, A; Nandi, B K; Nania, R; Nappi, E; Nattrass, C; Navin, S; Nayak, T K; Nazarenko, S; Nedosekin, A; Nicassio, M; Niculescu, M; Nielsen, B S; Niida, T; Nikolaev, S; Nikolic, V; Nikulin, S; Nikulin, V; Nilsen, B S; Nilsson, M S; Noferini, F; Nomokonov, P; Nooren, G; Novitzky, N; Nyanin, A; Nyatha, A; Nygaard, C; Nystrand, J; Ochirov, A; Oeschler, H; Oh, S K; Oh, S; Oleniacz, J; Oliveira Da Silva, A C; Oppedisano, C; Ortiz Velasquez, A; Oskarsson, A; Ostrowski, P; Otwinowski, J; Oyama, K; Ozawa, K; Pachmayer, Y; Pachr, M; Padilla, F; Pagano, P; Paic, G; Painke, F; Pajares, C; Pal, S K; Palaha, A; Palmeri, A; Papikyan, V; Pappalardo, G S; Park, W J; Passfeld, A; Pastircak, B; Patalakha, D I; Paticchio, V; Paul, B; Pavlinov, A; Pawlak, T; Peitzmann, T; Pereira Da Costa, H; Pereira De Oliveira Filho, E; Peresunko, D; Perez Lara, C E; Perini, D; Perrino, D; Peryt, W; Pesci, A; Peskov, V; Pestov, Y; Petracek, V; Petran, M; Petris, M; Petrov, P; Petrovici, M; Petta, C; Piano, S; Piccotti, A; Pikna, M; Pillot, P; Pinazza, O; Pinsky, L; Pitz, N; Piyarathna, D B; Planinic, M; Ploskon, M; Pluta, J; Pocheptsov, T; Pochybova, S; Podesta-Lerma, P L M; Poghosyan, M G; Polak, K; Polichtchouk, B; Pop, A; Porteboeuf-Houssais, S; Pospisil, V; Potukuchi, B; Prasad, S K; Preghenella, R; Prino, F; Pruneau, C A; Pshenichnov, I; Puddu, G; Punin, V; Putis, M; Putschke, J; Quercigh, E; Qvigstad, H; Rachevski, A; Rademakers, A; Raiha, T S; Rak, J; Rakotozafindrabe, A; Ramello, L; Ramirez Reyes, A; Raniwala, R; Raniwala, S; Rasanen, S S; Rascanu, B T; Rathee, D; Read, K F; Real, J S; Redlich, K; Reed, R J; Rehman, A; Reichelt, P; Reicher, M; Renfordt, R; Reolon, A R; Reshetin, A; Rettig, F; Revol, J P; Reygers, K; Riccati, L; Ricci, R A; Richert, T; Richter, M; Riedler, P; Riegler, W; Riggi, F; Rodriguez Cahuantzi, M; Rodriguez Manso, A; Roed, K; Rohr, D; Rohrich, D; Romita, R; Ronchetti, F; Rosnet, P; Rossegger, S; Rossi, A; Roy, P; Roy, C; Rubio Montero, A J; Rui, R; Russo, R; Ryabinkin, E; Rybicki, A; Sadovsky, S; Safarik, K; Sahoo, R; Sahu, P K; Saini, J; Sakaguchi, H; Sakai, S; Sakata, D; Salgado, C A; Salzwedel, J; Sambyal, S; Samsonov, V; Sanchez Castro, X; Sandor, L; Sandoval, A; Sano, M; Santagati, G; Santoro, R; Sarkamo, J; Scapparone, E; Scarlassara, F; Scharenberg, R P; Schiaua, C; Schicker, R; Schmidt, H R; Schmidt, C; Schuchmann, S; Schukraft, J; Schuster, T; Schutz, Y; Schwarz, K; Schweda, K; Scioli, G; Scomparin, E; Scott, P A; Scott, R; 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Yamaguchi, Y; Yang, H; Yang, S; Yasnopolskiy, S; Yi, J; Yin, Z; Yoo, I K; Yoon, J; Yu, W; Yuan, X; Yushmanov, I; Zaccolo, V; Zach, C; Zampolli, C; Zaporozhets, S; Zarochentsev, A; Zavada, P; Zaviyalov, N; Zbroszczyk, H; Zelnicek, P; Zgura, I S; Zhalov, M; Zhang, H; Zhang, X; Zhou, D; Zhou, Y; Zhou, F; Zhu, J; Zhu, H; Zhu, J; Zhu, X; Zichichi, A; Zimmermann, A; Zinovjev, G; Zoccarato, Y; Zynovyev, M; Zyzak, M

2013-01-01

Correlations of two charged identical kaons (K$^{ch}$ K$^{ch}$) are measured in pp collisions at $\\sqrt{s}$=7 TeV by the ALICE experiment at the Large Hadron Collider (LHC). One-dimensional K$^{ch}$ K$^{ch}$ correlation functions are constructed in three multiplicity and four transverse momentum ranges. The K$^{ch}$ K$^{ch}$ femtoscopic source parameters R and lambda are extracted. The K$^{ch}$ K$^{ch}$ correlations show a slight increase of femtoscopic radii with increasing multiplicity and a slight decrease of radii with increasing transverse momentum. These trends are similar to the ones observed for $\\pi\\pi$ and $K_s^0 K_s^0$ correlations in pp and heavy-ion collisions. However, the observed one dimensional correlation radii for charged kaons are larger at high multiplicities than those for pions in contrast to what was observed in heavy-ion collisions at RHIC.

Stability cluster links hydrofobic gate to K873 in ATP8A2

DEFF Research Database (Denmark)

Mikkelsen, Stine; Vestergaard, Anna Lindeløv; Coleman, Jonathan Allan

ATPases, though it catalyzes the transport of a much larger substrate, an enigma referred to as the “giant substrate problem”. Recently, based on mutational analysis and molecular dynamics we have identified a hydrophobic gate in a groove surrounded by M1, M2, M4 and M6 (1). A plausible water filled...... harboring key residues in the center of the enzyme important for linking M5 through K873 to M4 and M6. This stability cluster supposedly allows M4 to act as a pumping rod during enzyme reaction cycle. We find that mutation of residues in this stability cluster affects the substrate affinity, as previously...

K-means clustering for optimal partitioning and dynamic load balancing of parallel hierarchical N-body simulations

International Nuclear Information System (INIS)

Marzouk, Youssef M.; Ghoniem, Ahmed F.

2005-01-01

A number of complex physical problems can be approached through N-body simulation, from fluid flow at high Reynolds number to gravitational astrophysics and molecular dynamics. In all these applications, direct summation is prohibitively expensive for large N and thus hierarchical methods are employed for fast summation. This work introduces new algorithms, based on k-means clustering, for partitioning parallel hierarchical N-body interactions. We demonstrate that the number of particle-cluster interactions and the order at which they are performed are directly affected by partition geometry. Weighted k-means partitions minimize the sum of clusters' second moments and create well-localized domains, and thus reduce the computational cost of N-body approximations by enabling the use of lower-order approximations and fewer cells. We also introduce compatible techniques for dynamic load balancing, including adaptive scaling of cluster volumes and adaptive redistribution of cluster centroids. We demonstrate the performance of these algorithms by constructing a parallel treecode for vortex particle simulations, based on the serial variable-order Cartesian code developed by Lindsay and Krasny [Journal of Computational Physics 172 (2) (2001) 879-907]. The method is applied to vortex simulations of a transverse jet. Results show outstanding parallel efficiencies even at high concurrencies, with velocity evaluation errors maintained at or below their serial values; on a realistic distribution of 1.2 million vortex particles, we observe a parallel efficiency of 98% on 1024 processors. Excellent load balance is achieved even in the face of several obstacles, such as an irregular, time-evolving particle distribution containing a range of length scales and the continual introduction of new vortex particles throughout the domain. Moreover, results suggest that k-means yields a more efficient partition of the domain than a global oct-tree

Statistical nature of cluster emission in nuclear liquid-vapour phase coexistence

International Nuclear Information System (INIS)

Ma, Y G; Han, D D; Shen, W Q; Cai, X Z; Chen, J G; He, Z J; Long, J L; Ma, G L; Wang, K; Wei, Y B; Yu, L P; Zhang, H Y; Zhong, C; Zhou, X F; Zhu, Z Y

2004-01-01

The emission of nuclear clusters is investigated within the framework of the isospin-dependent lattice gas model and the classical molecular dynamics model. It is found that the emission of an individual cluster which is heavier than proton is almost Poissonian except near the transition temperature at which the system is leaving the liquid-vapour phase coexistence and thermal scaling is observed by the linear Arrhenius plots which are made from the average multiplicity of each cluster versus the inverse of temperature in the liquid-vapour phase coexistence. The slopes of the Arrhenius plots, i.e. the 'emission barriers', are extracted as a function of the mass or charge number and fitted by the formula embodied with the contributions of the surface energy and Coulomb interaction. Good agreements are obtained in comparison with the data for low-energy conditional barriers. In addition, the possible influences of the source size, Coulomb interaction and 'freeze-out' density and related physical implications are discussed

Normalized mutual information based PET-MR registration using K-Means clustering and shading correction

NARCIS (Netherlands)

Knops, Z.F.; Maintz, J.B.A.; Viergever, M.A.; Pluim, J.P.W.; Gee, J.C.; Maintz, J.B.A.; Vannier, M.W.

2003-01-01

A method for the efficient re-binning and shading based correction of intensity distributions of the images prior to normalized mutual information based registration is presented. Our intensity distribution re-binning method is based on the K-means clustering algorithm as opposed to the generally

V K Agrawal

Indian Academy of Sciences (India)

Home; Journals; Bulletin of Materials Science. V K Agrawal. Articles written in Bulletin of Materials Science. Volume 33 Issue 4 August 2010 pp 383-390 Electrical Properties. Temperature dependence of electromechanical properties of PLZT /57/43 ceramics · A K Shukla V K Agrawal I M L Das Janardan Singh S L ...

Plasmon response in K, Na and Li clusters: systematics using the separable random-phase approximation with pseudo-Hamiltonians

International Nuclear Information System (INIS)

Kleinig, W.; Nesterenko, V.O.; Reinhard, P.-G.; Serra, Ll.

1998-01-01

The systematics of the plasmon response in spherical K, Na and Li clusters in a wide size region (8≤N≤440) is studied. We have considered two simplifying approximations whose validity has been established previously. First, a separable approach to the random-phase approximation is used. This involves an expansion of the residual interaction into a sum of separable terms until convergence is reached. Second, the electron-ion interaction is modelled by using the pseudo-Hamiltonian jellium model (MHJM) which includes nonlocal effects by means of realistic atomic pseudo-Hamiltonians. In cases where nonlocal effects are negligible the Structure Averaged Jellium Model (SAJM) has been used. Good agreement with available experimental data is achieved for K, Na (using the SAJM) and small Li clusters (invoking the PHJM). The trends for peak position and width are generally well reproduced, even up to details of the Landau fragmentation in several clusters. Less good agreement, however, is found for large Li clusters. This remains an open question

Y2K experiences in the nuclear material control area

International Nuclear Information System (INIS)

Yagi, T.; Suzuki, T.

1999-01-01

Though the Y2K problem was treated by each organization, it became systematic in Japan when Advanced Information and Telecommunication Society Promotion Head-quarters was established recognizing the importance and urgency of the issue. The summary of the action and some experiences concerning Y2K issues in the nuclear materials control area are presented

D K Ghosh

Indian Academy of Sciences (India)

D K Ghosh. Articles written in Pramana – Journal of Physics. Volume 63 Issue 6 December 2004 pp 1359-1365. Working group report: Low energy and flavour physics · Amol Dighe Anirban Kundu K Agashe B Anantanarayan A Chandra A Datta P K Das S P Das A Dighe R Forty D K Ghosh Y -Y Keum A Kundu N Mahajan S ...

Nuclear clusters as a probe for expansion flow in heavy ion reactions at (10 endash 15)A GeV

International Nuclear Information System (INIS)

Mattiello, R.; Mattiello, R.; Sorge, H.; Stoecker, H.; Greiner, W.

1997-01-01

A phase space coalescence description based on the Wigner-function method for cluster formation in relativistic nucleus-nucleus collisions is presented. The momentum distributions of nuclear clusters d, t, and He are predicted for central Au(11.6A GeV)Au and Si(14.6A GeV)Si reactions in the framework of the relativistic quantum molecular dynamics transport approach. Transverse expansion leads to a strong shoulder-arm shape and different inverse slope parameters in the transverse spectra of nuclear clusters deviating markedly from thermal distributions. A clear open-quotes bounce-off close-quote close-quote event shape is seen: The averaged transverse flow velocities in the reaction plane are for clusters larger than for protons. The cluster yields, particularly at low p t at midrapidities, and the in-plane (anti)flow of clusters and pions change if suitably strong baryon potential interactions are included. This allows one to study the transient pressure at high density via the event shape analysis of nucleons, nucleon clusters, and other hadrons. copyright 1997 The American Physical Society

Measurement of charged particle spectra in pp collisions and nuclear modification factor $R_\\mathrm{pPb}$ at $\\sqrt{s_{NN}}=5.02$TeV with the ATLAS detector at the LHC

CERN Document Server

The ATLAS collaboration

2016-01-01

This note presents an analysis of the inclusive charged particle spectra in pp collisions at $\\sqrt{s}=5.02$TeV that are measured with the ATLAS experiment at the LHC. The measurements are performed with pp data recorded in 2015 with an integrated luminosity of 25pb$^{-1}$. The ratio of spectra measured in the p+Pb collisions to the pp cross section scaled by the number of binary nucleon-nucleon collisions, $R_\\mathrm{pPb}$, is evaluated to facilitate a comparison of the particle production in the two colliding systems. The nuclear modification factor does not show any significant deviation from unity in the probed transverse momentum region.

Fast clustering algorithm for large ECG data sets based on CS theory in combination with PCA and K-NN methods.

Science.gov (United States)

Balouchestani, Mohammadreza; Krishnan, Sridhar

2014-01-01

Long-term recording of Electrocardiogram (ECG) signals plays an important role in health care systems for diagnostic and treatment purposes of heart diseases. Clustering and classification of collecting data are essential parts for detecting concealed information of P-QRS-T waves in the long-term ECG recording. Currently used algorithms do have their share of drawbacks: 1) clustering and classification cannot be done in real time; 2) they suffer from huge energy consumption and load of sampling. These drawbacks motivated us in developing novel optimized clustering algorithm which could easily scan large ECG datasets for establishing low power long-term ECG recording. In this paper, we present an advanced K-means clustering algorithm based on Compressed Sensing (CS) theory as a random sampling procedure. Then, two dimensionality reduction methods: Principal Component Analysis (PCA) and Linear Correlation Coefficient (LCC) followed by sorting the data using the K-Nearest Neighbours (K-NN) and Probabilistic Neural Network (PNN) classifiers are applied to the proposed algorithm. We show our algorithm based on PCA features in combination with K-NN classifier shows better performance than other methods. The proposed algorithm outperforms existing algorithms by increasing 11% classification accuracy. In addition, the proposed algorithm illustrates classification accuracy for K-NN and PNN classifiers, and a Receiver Operating Characteristics (ROC) area of 99.98%, 99.83%, and 99.75% respectively.

Characterization program management plan for Hanford K Basin Spent Nuclear Fuel

International Nuclear Information System (INIS)

Lawrence, L.A.

1995-01-01

A management plan was developed for Westinghouse Hanford Company (WHC) and Pacific Northwest Laboratories (PNL) to work together on a program to provide characterization data to support removal, conditioning and subsequent dry storage of the spent nuclear fuels stored at the Hanford K Basins. The Program initially supports gathering data to establish the current state of the fuel in the two basins. Data Collected during this initial effort will apply to all SNF Project objectives. N Reactor fuel has been degrading with extended storage resulting in release of material to the basin water in K East and to the closed conisters in K West. Characterization of the condition of these materials and their responses to various conditioning processes and dry storage environments are necessary to support disposition decisions. Characterization will utilize the expertise and capabilities of WHC and PNL organizations to support the Spent Nuclear Fuels Project goals and objectives. This Management Plan defines the structure and establishes the roles for the participants providing the framework for WHC and PNL to support the Spent Nuclear Fuels Project at Hanford

Genetic algorithm with fuzzy clustering for optimization of nuclear reactor problems

International Nuclear Information System (INIS)

Machado, Marcelo Dornellas; Sacco, Wagner Figueiredo; Schirru, Roberto

2000-01-01

Genetic Algorithms (GAs) are biologically motivated adaptive systems which have been used, with good results, in function optimization. However, traditional GAs rapidly push an artificial population toward convergence. That is, all individuals in the population soon become nearly identical. Niching Methods allow genetic algorithms to maintain a population of diverse individuals. GAs that incorporate these methods are capable of locating multiple, optimal solutions within a single population. The purpose of this study is to introduce a new niching technique based on the fuzzy clustering method FCM, bearing in mind its eventual application in nuclear reactor related problems, specially the nuclear reactor core reload one, which has multiple solutions. tests are performed using widely known test functions and their results show that the new method is quite promising, specially to a future application in real world problems like the nuclear reactor core reload. (author)

Computing the cross sections of nuclear reactions with nuclear clusters emission for proton energies between 30 MeV and 2.6 GeV

Energy Technology Data Exchange (ETDEWEB)

Korovin, Yu. A.; Maksimushkina, A. V., E-mail: AVMaksimushkina@mephi.ru; Frolova, T. A. [Obninsk Institute for Nuclear Power Engineering, National Research Nuclear University MEPhI (Moscow Engineering Physics Institute) (Russian Federation)

2016-12-15

The cross sections of nuclear reactions involving emission of clusters of light nuclei in proton collisions with a heavy-metal target are computed for incident-proton energies between 30 MeV and 2.6 GeV. The calculation relies on the ALICE/ASH and CASCADE/INPE computer codes. The parameters determining the pre-equilibrium cluster emission are varied in the computation.

Estimation of Tree Lists from Airborne Laser Scanning Using Tree Model Clustering and k-MSN Imputation

Directory of Open Access Journals (Sweden)

Jörgen Wallerman

2013-04-01

Full Text Available Individual tree crowns may be delineated from airborne laser scanning (ALS data by segmentation of surface models or by 3D analysis. Segmentation of surface models benefits from using a priori knowledge about the proportions of tree crowns, which has not yet been utilized for 3D analysis to any great extent. In this study, an existing surface segmentation method was used as a basis for a new tree model 3D clustering method applied to ALS returns in 104 circular field plots with 12 m radius in pine-dominated boreal forest (64°14'N, 19°50'E. For each cluster below the tallest canopy layer, a parabolic surface was fitted to model a tree crown. The tree model clustering identified more trees than segmentation of the surface model, especially smaller trees below the tallest canopy layer. Stem attributes were estimated with k-Most Similar Neighbours (k-MSN imputation of the clusters based on field-measured trees. The accuracy at plot level from the k-MSN imputation (stem density root mean square error or RMSE 32.7%; stem volume RMSE 28.3% was similar to the corresponding results from the surface model (stem density RMSE 33.6%; stem volume RMSE 26.1% with leave-one-out cross-validation for one field plot at a time. Three-dimensional analysis of ALS data should also be evaluated in multi-layered forests since it identified a larger number of small trees below the tallest canopy layer.

Water-soluble phosphine-protected Au9 clusters: Electronic structures and nuclearity conversion via phase transfer

Science.gov (United States)

Yao, Hiroshi; Tsubota, Shuhei

2017-08-01

In this article, isolation, exploration of electronic structures, and nuclearity conversion of water-soluble triphenylphosphine monosulfonate (TPPS)-protected nonagold (Au9) clusters are outlined. The Au9 clusters are obtained by the reduction of solutions containing TPPS and HAuCl4 and subsequent electrophoretic fractionation. Mass spectrometry and elemental analysis reveal the formation of [Au9(TPPS)8]5- nonagold cluster. UV-vis absorption and magnetic circular dichroism (MCD) spectra of aqueous [Au9(TPPS)8]5- are quite similar to those of [Au9(PPh3)8]3+ in organic solvent, so the solution-phase structures are likely similar for both systems. Simultaneous deconvolution analysis of absorption and MCD spectra demonstrates the presence of some weak electronic transitions that are essentially unresolved in the UV-vis absorption. Quantum chemical calculations for a model compound [Au9(pH3)8]3+ show that the possible (solution-phase) skeletal structure of the nonagold cluster has D2h core symmetry rather than C4-symmetrical centered crown conformation, which is known as the crystal form of the Au9 compound. Moreover, we find a new nuclearity conversion route from Au9 to Au8; that is, phase transfer of aqueous [Au9(TPPS)8]5- into chloroform using tetraoctylammonium bromide yields [Au8(TPPS)8]6- clusters in the absence of excess phosphine.

Membership, binarity, and rotation of F-G-K stars in the open cluster Blanco 1

Science.gov (United States)

Mermilliod, J.-C.; Platais, I.; James, D. J.; Grenon, M.; Cargile, P. A.

2008-07-01

Context: The nearby open cluster Blanco 1 is of considerable astrophysical interest for formation and evolution studies of open clusters because it is the third highest Galactic latitude cluster known. It has been observed often, but so far no definitive and comprehensive membership determination is readily available. Aims: An observing programme was carried out to study the stellar population of Blanco 1, and especially the membership and binary frequency of the F5-K0 dwarfs. Methods: We obtained radial-velocities with the CORAVEL spectrograph in the field of Blanco 1 for a sample of 148 F-G-K candidate stars in the magnitude range 10 rate reaches 40% (27/68) if one includes the photometric binaries. The cluster mean heliocentric radial velocity is +5.53 ± 0.11 km s-1 based on the most reliable 49 members. The V sin i distribution is similar to that of the Pleiades, confirming the age similarities between the two clusters. Conclusions: This study clearly demonstrates that, in spite of the cluster's high Galactic latitude, three membership criteria - radial velocity, proper motion, and photometry - are necessary for performing a reliable membership selection. Furthermore, even with accurate and extensive data, ambiguous cases still remain. Based on observations collected with the Danish 1.54-m and the Swiss telescopes at the European Southern Observatory, La Silla, Chile, and with the old YALO 1-m telescope at the Cerro Tololo InterAmerican Observatory, Chile. Table [see full textsee full textsee full textsee full textsee full textsee full text] is also available in electronic form at the CDS via anonymous ftp to cdsarc.u-strasbg.fr (130.79.128.5) or via http://cdsweb.u-strasbg.fr/cgi-bin/qcat?J/A+A/485/95

[Electromagnetic studies of nuclear structure and reactions

International Nuclear Information System (INIS)

1991-01-01

The past year has seen continued progress in our efforts. On the experimental side, we completed data acquisition on our major remaining involvement at NIKHEF, the 12 C(e,e'pp) experiment. We advanced the analysis of most of projects in low lying nuclear structure and giant resonances, of which several were completed and published. We received approval for several new experiments, and have made major contributions to design and development of detectors to be used at Bates and CEBAF. Our data interpretation efforts have been extended and enhanced with the availability of our new computer cluster. In this paper we briefly report on most of these efforts

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

A K Vijaykumar

Indian Academy of Sciences (India)

Ponderings in Paperback - What Makes Nature Tick ? A K Vijaykumar · More Details Fulltext PDF. Volume 5 Issue 5 May 2000 pp 101-102 Book Review. Fixed Points - From Russia with Love - A Primer of Fixed Point Theory · A K Vijaykumar.

C K Maiti

Indian Academy of Sciences (India)

Home; Journals; Bulletin of Materials Science. C K Maiti. Articles written in Bulletin of Materials Science. Volume 24 Issue 6 December 2001 pp 579-582 Thin Films. Metallo–organic compound-based plasma enhanced CVD of ZrO2 films for microelectronic applications · S Chatterjee S K Samanta H D Banerjee C K Maiti.

B K Godwal

Indian Academy of Sciences (India)

Home; Journals; Bulletin of Materials Science. B K Godwal. Articles written in Bulletin of Materials Science. Volume 23 Issue 2 April 2000 pp 151-154 Instrumentation. A CCD area detector for X-ray diffraction under high pressure for rotating anode source · Amar Sinha Alka B Garg V Vijayakumar B K Godwal S K Sikka.

Order and chaos in nuclear and metal cluster deformation

International Nuclear Information System (INIS)

Radu, S.

1995-08-01

The vast amount of nuclear and metal cluster data indicates that shell structure and deformation are two simultaneous properties. A conflicting situation is therefore encountered as the shell structure, a firm expression of order, is apparently not compatible with the non-integrable nature of the models incorporating deformation. The main issue covered in this thesis is the intricate connection between deformation and chaotic behaviour in deformation models pertinent to nuclear structure and metal cluster physics. It is shown that, at least in some cases, it is possible to reconcile the occurrence of shell structure with non-integrability. The coupling of an axially deformed harmonic oscillator to an axially symmetric octupole term renders the problem non-integrable. The chaotic character of the motion is strongly dependent on the type of deformation, in that a prolate shape shows virtually no chaos, while in an oblate case the motion exhibits fully developed chaos when the octupole term is switched on. Whereas the problem is non-integrable, the quantum mechanical spectrum nevertheless shows some shell structure in the prolate case for particular, yet fairly large octupole strengths; for spherical or oblate deformation the shell structure disappears. This result is explained in terms of classical periodic orbits which are found by employing the 'removal of resonances method'. Particular emphasis is put on the effect of the hexadecapole deformation which is important in fission processes. The combined effect of octupole and hexadecapole deformation leads to important conclusions for the experimental work as a high degree of ambiguity is signaled for the interpretation of data. The ambiguity results from the discovery of a mutual cancellation of the octupole and hexadecapole deformation in prolate superdeformed systems. The phenomenological Nilsson model is treated in a similar way. It is argued that while in nuclei it produces good results for the low-lying levels

K Srinivasan

Indian Academy of Sciences (India)

Home; Journals; Bulletin of Materials Science. K Srinivasan. Articles written in Bulletin of Materials Science. Volume 23 Issue 1 February 2000 pp 35-37 Metallic Materials. Impact toughness of ternary Al–Zn–Mg alloys in as cast and homogenized condition measured in the temperature range 263–673 K · Harish Kundar ...

Report and analysis on 'PR and PP evaluation. Example sodium fast reactor full system case study'

International Nuclear Information System (INIS)

Sagara, Hiroshi; Inoue, Naoko; Kawakubo, Yoko; Watahiki, Masaru

2011-01-01

The Generation IV (GEN IV) Nuclear Energy Systems International Forum (GIF) Proliferation Resistance and Physical Protection Working Group (PRPP WG) was established in December 2002 in order to develop the PR and valuation methodology for GEN IV nuclear energy systems. In the final report of 'PR and PP Evaluation: Example Sodium Fast Reactor (ESFR) Full System Case Study,' issued in October 2009, the demonstration study of PR and PP evaluation with the qualitative approach are summarized using ESFR with four scenario threats. The present paper reviews and analyzes some results of the ESFR case study, and identifies the challenges and direction for the PR and PP evaluation methodology with quantitative approach. (author)

K- nuclear states: Binding energies and widths

Czech Academy of Sciences Publication Activity Database

Hrtánková, Jaroslava; Mareš, Jiří

2017-01-01

Roč. 96, č. 1 (2017), č. článku 015205. ISSN 2469-9985 R&D Projects: GA ČR(CZ) GA15-04301S Institutional support: RVO:61389005 Keywords : K- nuclear * kaonic * states Subject RIV: BE - Theoretical Physics OBOR OECD: Atomic, molecular and chemical physics (physics of atoms and molecules including collision, interaction with radiation, magnetic resonances, Mössbauer effect) Impact factor: 3.820, year: 2016

Near-infrared variability study of the central 2.3 × 2.3 arcmin2 of the Galactic Centre - II. Identification of RR Lyrae stars in the Milky Way nuclear star cluster

Science.gov (United States)

Dong, Hui; Schödel, Rainer; Williams, Benjamin F.; Nogueras-Lara, Francisco; Gallego-Cano, Eulalia; Gallego-Calvente, Teresa; Wang, Q. Daniel; Rich, R. Michael; Morris, Mark R.; Do, Tuan; Ghez, Andrea

2017-11-01

Because of strong and spatially highly variable interstellar extinction and extreme source crowding, the faint (K ≥ 15) stellar population in the Milky Way's nuclear star cluster is still poorly studied. RR Lyrae stars provide us with a tool to estimate the mass of the oldest, relative dim stellar population. Recently, we analysed HST/WFC3/IR observations of the central 2.3 × 2.3 arcmin2 of the Milky Way and found 21 variable stars with periods between 0.2 and 1 d. Here, we present a further comprehensive analysis of these stars. The period-luminosity relationship of RR Lyrae is used to derive their extinctions and distances. Using multiple approaches, we classify our sample as 4 RRc stars, 4 RRab stars, 3 RRab candidates and 10 binaries. Especially, the four RRab stars show sawtooth light curves and fall exactly on to the Oosterhoff I division in the Bailey diagram. Compared to the RRab stars reported by Minniti et al., our new RRab stars have higher extinction (AK > 1.8) and should be closer to the Galactic Centre. The extinction and distance of one RRab stars match those for the Milky Way's nuclear star cluster given in previous works. We perform simulations and find that after correcting for incompleteness, there could be not more than 40 RRab stars within the Milky Way's nuclear star cluster and in our field of view. Through comparing with the known globular clusters of the Milky Way, we estimate that if there exists an old, metal-poor (-1.5 < [Fe/H] < -1) stellar population in the Milky Way nuclear star cluster on a scale of 5 × 5 pc, then it contributes at most 4.7 × 105 M⊙, I.e. ˜18 per cent of the stellar mass.

Massively parallel Monte Carlo. Experiences running nuclear simulations on a large condor cluster

International Nuclear Information System (INIS)

Tickner, James; O'Dwyer, Joel; Roach, Greg; Uher, Josef; Hitchen, Greg

2010-01-01

The trivially-parallel nature of Monte Carlo (MC) simulations make them ideally suited for running on a distributed, heterogeneous computing environment. We report on the setup and operation of a large, cycle-harvesting Condor computer cluster, used to run MC simulations of nuclear instruments ('jobs') on approximately 4,500 desktop PCs. Successful operation must balance the competing goals of maximizing the availability of machines for running jobs whilst minimizing the impact on users' PC performance. This requires classification of jobs according to anticipated run-time and priority and careful optimization of the parameters used to control job allocation to host machines. To maximize use of a large Condor cluster, we have created a powerful suite of tools to handle job submission and analysis, as the manual creation, submission and evaluation of large numbers (hundred to thousands) of jobs would be too arduous. We describe some of the key aspects of this suite, which has been interfaced to the well-known MCNP and EGSnrc nuclear codes and our in-house PHOTON optical MC code. We report on our practical experiences of operating our Condor cluster and present examples of several large-scale instrument design problems that have been solved using this tool. (author)

Study of a clusters in 40Ca and 40Ar through nuclear break-up

International Nuclear Information System (INIS)

Lefebvre, Laurent

2013-01-01

Nuclei are complex self-bound systems formed by nucleons. Conjointly to a mean-field picture in which nucleons can be regarded as independent particles, few nucleons might self-organize into compact objects, called clusters, inside the nucleus. It is theoretically predicted that it should manifest itself most strikingly for N = Z nuclei close to the emission thresholds and has been studied extensively in this region. We propose to study α-clusterization in the ground state of the N = Z 40 20 Ca 20 nucleus and the N (different of) Z 40 18 Ar 22 nucleus. We have studied the nuclear break-up of 40 Ca when the 40 Ar projectile passes by. If α clusters are preformed in 40 Ca, the probability of α-emission through nuclear break-up will be enhanced as compared to 40 Ar N (different of) Z nuclei.The nuclear break-up of 40 Ca was studied with an 40 Ar beam produced at GANIL at 35 MeV/A. The SPEG spectrometer was used to detect the heavy projectile with accurate resolution. The MUST2 Silicon detectors were placed around the target to measure the emitted α and the EXL calorimeter prototype was used to identify the γ rays from the decay of the residual 36 Ar and 36 S. A theoretical approach based on Time-Dependent Schroedinger Equation (TDSE) theory has been used to reproduce some experimental results like angular distributions. From the data analysis, we reconstructed excitation energy spectra and angular distributions which are compared to TDSE theory to extract some spectroscopic factors S α . These factors show that there is no more clusterization state in the ground state of the 40 Ca than in the ground state of 40 Ar. (author)

K C Bhamu

Indian Academy of Sciences (India)

Home; Journals; Pramana – Journal of Physics. K C BHAMU. Articles written in Pramana – Journal of Physics. Volume 89 Issue 1 July 2017 pp 11 Research Article. Density functional study of A g S c O 2 : Electronic and optical properties · K C BHAMU JAGRATI SAHARIYA RISHI VYAS K R PRIOLKAR · More Details ...

k c mistri

Indian Academy of Sciences (India)

Home; Journals; Sadhana. K C MISTRI. Articles written in Sadhana. Volume 42 Issue 9 September 2017 pp 1459-1471. Influence of yielding base and rigid base on propagation of Rayleigh-type wave in a viscoelastic layer of Voigt type · S SAHA A CHATTOPADHYAY K C MISTRI A K SINGH · More Details Abstract Fulltext ...

G K Suryaprakash

Indian Academy of Sciences (India)

Home; Journals; Resonance – Journal of Science Education. G K Suryaprakash. Articles written in Resonance – Journal of Science Education. Volume 22 Issue 12 December 2017 pp 1111-1153 General Article. George Andrew Olah: Across Conventional Lines · Ripudaman Malhotra Thomas Mathew G K Suryaprakash.

flowPeaks: a fast unsupervised clustering for flow cytometry data via K-means and density peak finding.

Science.gov (United States)

Ge, Yongchao; Sealfon, Stuart C

2012-08-01

For flow cytometry data, there are two common approaches to the unsupervised clustering problem: one is based on the finite mixture model and the other on spatial exploration of the histograms. The former is computationally slow and has difficulty to identify clusters of irregular shapes. The latter approach cannot be applied directly to high-dimensional data as the computational time and memory become unmanageable and the estimated histogram is unreliable. An algorithm without these two problems would be very useful. In this article, we combine ideas from the finite mixture model and histogram spatial exploration. This new algorithm, which we call flowPeaks, can be applied directly to high-dimensional data and identify irregular shape clusters. The algorithm first uses K-means algorithm with a large K to partition the cell population into many small clusters. These partitioned data allow the generation of a smoothed density function using the finite mixture model. All local peaks are exhaustively searched by exploring the density function and the cells are clustered by the associated local peak. The algorithm flowPeaks is automatic, fast and reliable and robust to cluster shape and outliers. This algorithm has been applied to flow cytometry data and it has been compared with state of the art algorithms, including Misty Mountain, FLOCK, flowMeans, flowMerge and FLAME. The R package flowPeaks is available at https://github.com/yongchao/flowPeaks. yongchao.ge@mssm.edu Supplementary data are available at Bioinformatics online.

Nuclear reactor fuel element with a cluster of parallel fuel pins

International Nuclear Information System (INIS)

Macfall, D.; Butterfield, C.E.; Butterfield, R.S.

1977-01-01

An improvement of the design of nuclear reactor fuel elements is described and illustrated by the example of a gas-cooled, graphite-moderated nuclear reactor. The fuel element has a cluster of parallel fuel pins with an outer can of structure material and an inner sleeve, as well as tie bars and spacing devices for all of these parts. The fuel element designed according to the invention allows lasy assembling and disassembling before and after use. During use, no relative axial motions are possible; nevertheless, the graphite sleeve is at no time subject to tensile stress: the individual parts are held in position from below by a single holding device. (UWI) [de

Vertebra identification using template matching modelmp and K-means clustering.

Science.gov (United States)

Larhmam, Mohamed Amine; Benjelloun, Mohammed; Mahmoudi, Saïd

2014-03-01

Accurate vertebra detection and segmentation are essential steps for automating the diagnosis of spinal disorders. This study is dedicated to vertebra alignment measurement, the first step in a computer-aided diagnosis tool for cervical spine trauma. Automated vertebral segment alignment determination is a challenging task due to low contrast imaging and noise. A software tool for segmenting vertebrae and detecting subluxations has clinical significance. A robust method was developed and tested for cervical vertebra identification and segmentation that extracts parameters used for vertebra alignment measurement. Our contribution involves a novel combination of a template matching method and an unsupervised clustering algorithm. In this method, we build a geometric vertebra mean model. To achieve vertebra detection, manual selection of the region of interest is performed initially on the input image. Subsequent preprocessing is done to enhance image contrast and detect edges. Candidate vertebra localization is then carried out by using a modified generalized Hough transform (GHT). Next, an adapted cost function is used to compute local voted centers and filter boundary data. Thereafter, a K-means clustering algorithm is applied to obtain clusters distribution corresponding to the targeted vertebrae. These clusters are combined with the vote parameters to detect vertebra centers. Rigid segmentation is then carried out by using GHT parameters. Finally, cervical spine curves are extracted to measure vertebra alignment. The proposed approach was successfully applied to a set of 66 high-resolution X-ray images. Robust detection was achieved in 97.5 % of the 330 tested cervical vertebrae. An automated vertebral identification method was developed and demonstrated to be robust to noise and occlusion. This work presents a first step toward an automated computer-aided diagnosis system for cervical spine trauma detection.

Mapping of nuclear import signal and importin α3 binding regions of 52K protein of bovine adenovirus-3

International Nuclear Information System (INIS)

Paterson, Carolyn P.; Ayalew, Lisanework E.; Tikoo, Suresh K.

2012-01-01

The L1 region of bovine adenovirus (BAdV)-3 encodes a non-structural protein designated 52K. Anti-52K serum detected a protein of 40 kDa, which localized to the nucleus but not to the nucleolus in BAdV-3-infected or transfected cells. Analysis of mutant 52K proteins suggested that three basic residues ( 105 RKR 107 ) of the identified domain (amino acids 102 GMPRKRVLT 110 ) are essential for nuclear localization of 52K. The nuclear import of a GST-52K fusion protein utilizes the classical importin α/β-dependent nuclear transport pathway. The 52K protein is preferentially bound to the cellular nuclear import receptor importin α3. Although deletion of amino acid 102–110 is sufficient to abrogate the nuclear localization of 52K, amino acid 90–133 are required for interaction with importin-α3 and localizing a cytoplasmic protein to the nucleus. These results suggest that 52K contains a bipartite NLS, which preferentially utilize an importin α3 nuclear import receptor-mediated pathway to transport 52K to the nucleus.

IMPLEMENTASI ALGORITMA K-MEANS CLUSTERING UNTUK MENENTUKAN STRATEGI MARKETING PRESIDENT UNIVERSITY

Directory of Open Access Journals (Sweden)

Johan Oscar Ong

2013-06-01

Full Text Available Information technology advances very rapidly at this time to generate thousands or even millions of data from various aspect of life. However, what can be done with that much data?. In this research, we start from calculation of data set of students who have graduated from President University using k-means clustering algorithm, namely by classifying the data of students into several clusters based on the characteristics of this data in order to discover the information hidden from the data set of student who have graduated from President University. The attribute data that is used in this study is hometown, major and GPA. The purpose of this study is to help the President University's marketing department in predicting promotion strategies undertaken in the cities in Indonesia. Information gained in this study can be used as a references in determining the proper strategy for marketing team in their promotion activities in the cities in Indonesia so that the campaign will be more effective and efficient.

An additional k-means clustering step improves the biological features of WGCNA gene co-expression networks.

Science.gov (United States)

Botía, Juan A; Vandrovcova, Jana; Forabosco, Paola; Guelfi, Sebastian; D'Sa, Karishma; Hardy, John; Lewis, Cathryn M; Ryten, Mina; Weale, Michael E

2017-04-12

Weighted Gene Co-expression Network Analysis (WGCNA) is a widely used R software package for the generation of gene co-expression networks (GCN). WGCNA generates both a GCN and a derived partitioning of clusters of genes (modules). We propose k-means clustering as an additional processing step to conventional WGCNA, which we have implemented in the R package km2gcn (k-means to gene co-expression network, https://github.com/juanbot/km2gcn ). We assessed our method on networks created from UKBEC data (10 different human brain tissues), on networks created from GTEx data (42 human tissues, including 13 brain tissues), and on simulated networks derived from GTEx data. We observed substantially improved module properties, including: (1) few or zero misplaced genes; (2) increased counts of replicable clusters in alternate tissues (x3.1 on average); (3) improved enrichment of Gene Ontology terms (seen in 48/52 GCNs) (4) improved cell type enrichment signals (seen in 21/23 brain GCNs); and (5) more accurate partitions in simulated data according to a range of similarity indices. The results obtained from our investigations indicate that our k-means method, applied as an adjunct to standard WGCNA, results in better network partitions. These improved partitions enable more fruitful downstream analyses, as gene modules are more biologically meaningful.

Hyperon-nucleon final state interaction in a pp → K+X experiment and the H1+ (2130) S = - 1 strange dibaryon

International Nuclear Information System (INIS)

Frascaria, R.; Siebert, R.; Didelez, J.P.; Blanpied, G.; Reposeur, T.; Warde, E.; Bovet, E.; Egger, J.P.; Ernst, J.; Mayer-Kuckuk, T.; Grossiord, J.Y.; Preedom, B.; Perdrisat, C.; Saghai, B.

1988-01-01

A pp → K + X experiment was performed with high resolution to study λp and σN in a large range of momentum transfer and missing mass, in order to study the cusp effect which hinders the characterisation of the structure near the σ + n threshold as dynamical or kinematical. The difficulty in explaining the cusp effect is related to the large SU(3) breaking. It is argued that the present experiment provides a good means of obtaining the information required, but detailed analysis of results is not yet complete

manoj k mitra

Indian Academy of Sciences (India)

Home; Journals; Bulletin of Materials Science. MANOJ K MITRA. Articles written in Bulletin of Materials Science. Volume 40 Issue 6 October 2017 pp 1203-1211. One-pot synthesis of CaAl-layered double hydroxide–methotrexate nanohybrid for anticancer application · MANJUSHA CHAKRABORTY MANOJ K MITRA JUI ...

K S Mallesh

Indian Academy of Sciences (India)

Home; Journals; Resonance – Journal of Science Education. K S Mallesh. Articles written in Resonance – Journal of Science Education. Volume 16 Issue 2 February 2011 pp 129-151 General Article. Symmetries and Conservation Laws in Classical and Quantum Mechanics - Classical Mechanics · K S Mallesh S ...

K B Sinha

Indian Academy of Sciences (India)

Home; Journals; Resonance – Journal of Science Education. K B Sinha. Articles written in Resonance – Journal of Science Education. Volume 3 Issue 6 June 1998 pp 80-81 Book Review. Algebra in Ancient and Modern Times · K B Sinha · More Details Fulltext PDF ...

Technical Note: Using k-means clustering to determine the number and position of isocenters in MLC-based multiple target intracranial radiosurgery.

Science.gov (United States)

Yock, Adam D; Kim, Gwe-Ya

2017-09-01

To present the k-means clustering algorithm as a tool to address treatment planning considerations characteristic of stereotactic radiosurgery using a single isocenter for multiple targets. For 30 patients treated with stereotactic radiosurgery for multiple brain metastases, the geometric centroids and radii of each met were determined from the treatment planning system. In-house software used this as well as weighted and unweighted versions of the k-means clustering algorithm to group the targets to be treated with a single isocenter, and to position each isocenter. The algorithm results were evaluated using within-cluster sum of squares as well as a minimum target coverage metric that considered the effect of target size. Both versions of the algorithm were applied to an example patient to demonstrate the prospective determination of the appropriate number and location of isocenters. Both weighted and unweighted versions of the k-means algorithm were applied successfully to determine the number and position of isocenters. Comparing the two, both the within-cluster sum of squares metric and the minimum target coverage metric resulting from the unweighted version were less than those from the weighted version. The average magnitudes of the differences were small (-0.2 cm 2 and 0.1% for the within cluster sum of squares and minimum target coverage, respectively) but statistically significant (Wilcoxon signed-rank test, P k-means clustering algorithm represented an advantage of the unweighted version for the within-cluster sum of squares metric, and an advantage of the weighted version for the minimum target coverage metric. While additional treatment planning considerations have a large influence on the final treatment plan quality, both versions of the k-means algorithm provide automatic, consistent, quantitative, and objective solutions to the tasks associated with SRS treatment planning using a single isocenter for multiple targets. © 2017 The Authors. Journal

C M K Nair

Indian Academy of Sciences (India)

Home; Journals; Bulletin of Materials Science. C M K Nair. Articles written in Bulletin of Materials Science. Volume 24 Issue 2 April 2001 pp 249-252 Crystal Growth. Thermal behaviour of strontium tartrate single crystals grown in gel · M H Rahimkutty K Rajendra Babu K Sreedharan Pillai M R Sudarsana Kumar C M K Nair.

Characterization program management plan for Hanford K Basin spent nuclear fuel

International Nuclear Information System (INIS)

Lawrence, L.A.

1998-01-01

The management plan developed to characterize the K Basin Spent Nuclear Fuel was revised to incorporate actions necessary to comply with the Office of Civilian Radioactive Waste Management Quality Assurance Requirements Document 0333P. This plan was originally developed for Westinghouse Hanford Company and Pacific Northwest National Laboratory to work together on a program to provide characterization data to support removal, conditioning, and subsequent dry storage of the spent nuclear fuels stored at the Hanford K Basins. This revision to the Program Management Plan replaces Westinghouse Hanford Company with Duke Engineering and Services Hanford, Inc., updates the various activities where necessary, and expands the Quality Assurance requirements to meet the applicable requirements document. Characterization will continue to utilize the expertise and capabilities of both organizations to support the Spent Nuclear Fuels Project goals and objectives. This Management Plan defines the structure and establishes the roles for the participants providing the framework for Duke Engineering and Services Hanford, Inc. and Pacific Northwest National Laboratory to support the Spent Nuclear Fuels Project at Hanford

Strategies to regulate transcription factor-mediated gene positioning and interchromosomal clustering at the nuclear periphery.

Science.gov (United States)

Randise-Hinchliff, Carlo; Coukos, Robert; Sood, Varun; Sumner, Michael Chas; Zdraljevic, Stefan; Meldi Sholl, Lauren; Garvey Brickner, Donna; Ahmed, Sara; Watchmaker, Lauren; Brickner, Jason H

2016-03-14

In budding yeast, targeting of active genes to the nuclear pore complex (NPC) and interchromosomal clustering is mediated by transcription factor (TF) binding sites in the gene promoters. For example, the binding sites for the TFs Put3, Ste12, and Gcn4 are necessary and sufficient to promote positioning at the nuclear periphery and interchromosomal clustering. However, in all three cases, gene positioning and interchromosomal clustering are regulated. Under uninducing conditions, local recruitment of the Rpd3(L) histone deacetylase by transcriptional repressors blocks Put3 DNA binding. This is a general function of yeast repressors: 16 of 21 repressors blocked Put3-mediated subnuclear positioning; 11 of these required Rpd3. In contrast, Ste12-mediated gene positioning is regulated independently of DNA binding by mitogen-activated protein kinase phosphorylation of the Dig2 inhibitor, and Gcn4-dependent targeting is up-regulated by increasing Gcn4 protein levels. These different regulatory strategies provide either qualitative switch-like control or quantitative control of gene positioning over different time scales. © 2016 Randise-Hinchliff et al.

e-Cluster Building and Using for Nuclear Industry Human Resources

International Nuclear Information System (INIS)

Hur, Jung Hoon; Suh, Jang Soo

2009-01-01

In line with its industry support policy, KHNP provides training courses for small and medium sized companies within the nuclear sector. The courses cover three main areas; technical development, market expansion and human resource and finance. They are provided in traditional classroom settings and on-line. Employees from small and medium sized companies can take any of the available courses according to company and individual training and development requirements. While the training and development opportunities serve a role in the growth and development of skills and capabilities industry-wide, KHNP also sees the involvement of a wide range of nuclear industry participants in the program as a means of developing a safety consensus that addresses both operational and social safety concerns. The purpose of this paper is to outline the successes of the KHNP industry training support program to date and to propose the development of an e-Cluster model. This model envisages the development of a nuclear industry. It will provide a means for sharing information and developing and maintaining industry-wide technical, management and safety standards

The structure of the nuclear stellar cluster of the Milky Way

International Nuclear Information System (INIS)

Schoedel, Rainer; Eckart, Andreas

2006-01-01

The structure of the nuclear stellar cluster of the Milky Way is of particular interest because it is the densest stellar cluster in our Galaxy, where the theoretical prediction of the formation of a stellar cusp around the central supermassive black hole, Sagittarius A* (Sgr A*) can be examined. We present high-resolution adaptive optics observations with multiple intermediate band liters of the inner ∼20'' around Sgr A*. From the images, stellar number counts and a detailed map of the interstellar extinction toward the central 0.5 pc of the Milky Way were determined. The extinction map is consistent with a putative southwest-northeast aligned outfbw from the central arcseconds. An azimuthally averaged, crowding and extinction corrected stellar density profle presents clear evidence for the existence of a stellar cusp around Sgr A*. We show that the profle of the surface brightness density is dominated by the brightest stars in the central arcseconds and is different from the shape of the stellar cluster as inferred from the number counts. Several density peaks found in the cluster may indicate clumping, possibly related to the last epoch of star formation in the Galactic Center. There is evidence for a common proper motion of the stars in one of these clumps

Determining the Number of Instars in Simulium quinquestriatum (Diptera: Simuliidae) Using k-Means Clustering via the Canberra Distance.

Science.gov (United States)

Yang, Yao Ming; Jia, Ruo; Xun, Hui; Yang, Jie; Chen, Qiang; Zeng, Xiang Guang; Yang, Ming

2018-02-21

Simulium quinquestriatum Shiraki (Diptera: Simuliidae), a human-biting fly that is distributed widely across Asia, is a vector for multiple pathogens. However, the larval development of this species is poorly understood. In this study, we determined the number of instars in this pest using three batches of field-collected larvae from Guiyang, Guizhou, China. The postgenal length, head capsule width, mandibular phragma length, and body length of 773 individuals were measured, and k-means clustering was used for instar grouping. Four distance measures-Manhattan, Euclidean, Chebyshev, and Canberra-were determined. The reported instar numbers, ranging from 4 to 11, were set as initial cluster centers for k-means clustering. The Canberra distance yielded reliable instar grouping, which was consistent with the first instar, as characterized by egg bursters and prepupae with dark histoblasts. Females and males of the last cluster of larvae were identified using Feulgen-stained gonads. Morphometric differences between the two sexes were not significant. Validation was performed using the Brooks-Dyar and Crosby rules, revealing that the larval stage of S. quinquestriatum is composed of eight instars.

Y2K program of the U.S. Nuclear Regulatory Commission

International Nuclear Information System (INIS)

Breskovic, C.

1999-01-01

The NRC is pursuing a comprehensive program for dealing with the potential Y2K problems. A continuous work id being done concerning licensees to ensure that potential Y2K problems are being identified and rectified. Remediation of the NRC computer based system was done and it will continue functioning properly passing from 1999 to 2000. The problems concerning nuclear power plants operation, control and management are described as well as the nuclear materials management. NRC has a contingency plan based on reasonably conservative assumptions and is considered to be a living document that requires ongoing coordination with external stake holders and NRC licensees

Effects of thermal ageing on HMS-PP crystallinity

International Nuclear Information System (INIS)

Oliani, Washington L.; Parra, Duclerc F.; Lima, Luis F.C.P.; Lugao, Ademar B.

2009-01-01

The isotactic polypropylene is a linear polymer which exhibits low melt strength. Irradiation of PP under inert atmosphere causes a combination of chain scissioning and long-chain branching, and results in a material with significant enhanced melt strength. This process, which is sometimes termed visbreaking, thus provides improvement of rheological properties. HMS-PP (High Melt Strength Polypropylene) was obtained by the irradiation in atmosphere of acetylene as crosslinker agent. It was employed doses of 12.5 and 20 kGy of gamma radiation. The objective of this study is to investigate the effects of thermal ageing on the crystallinity level and chemical structure of HMS-PP. The thermal stability of the HMS-PP was evaluated after thermal ageing of samples using a stove at temperature of 90 deg C, in presence of air at different periods of time. The samples submitted to the thermal ageing were characterized by: thermogravimetry (TGA), differential scanning calorimetry (DSC), infrared spectroscopy (FTIR) and scanning electron microscopy (SEM). Since the long-term engineering properties of HMS-PP are intrinsically linked with the polymer microstructure, there is significant interest in understanding the effects of ageing, particularly due to prolonged exposure at service temperatures. In thermo-oxidative conditions, the formation of the oxidation products essentially involves a hydrogen abstraction by the peroxyl radicals, leading to hydroperoxides as primary products and chemical degradation in the immediate crack tips. Oxidative degradation on the network of HMS-PP, created by radiation process of PP, was revealed by the analytical results showing the susceptibility of HMS-PP to thermal oxidative degradation. Yellowing of the samples surface and oxidative products of degradation among other evidences were observed. (author)

K C Manorama Thampatti

Indian Academy of Sciences (India)

Home; Journals; Resonance – Journal of Science Education. K C Manorama Thampatti. Articles written in Resonance – Journal of Science Education. Volume 4 Issue 3 March 1999 pp 62-70 Feature Article. Nature Watch - Rice Bowl in Turmoil: The Kuttanad Wetland Ecosystem · K C Manorama Thampatti K G Padmakumar.

The clustered nucleus-cluster structures in stable and unstable nuclei