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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Qiyao Wang Yuanfang Ren Md Mahmudul Hasan Ahmet Ay Tamer Kahveci Department of Computer & Information Science & Engineering University of Florida Gainesville F1 USA Departments of Biology & Mathematics Colgate University Hamilton NY USA

Methods for constructing signaling networks from reference networks and single gene knockdown RNAi experiments have been proposed in recent years. All of these studies assume that the RNAi data is complete. However, RNAi experiments are usually noisy and more importantly have a considerable amount of missing data (i.e., a subset of the gene knockdowns is missing). In this paper, we address the signaling network construction problem with incomplete RNAi data. We develop two new methods for constructing a network topology which is closest to the reference network and consistent with the given incomplete RNAi data. Our experiments on real and synthetic datasets demonstrate that these methods produce accurate results and they are efficient. For real Wnt networks, our methods produce results with high accuracy in less than 100 ms.

关键词： Proteins Organisms Random access memory Databases

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An inventory model with linear holding cost and stock-dependent demand for non-instantaneous deteriorating items

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AIP Conference Proceedings 2016年第1期1715卷

作者： Satish Kumar A. K. Malik Abhishek Sharma S. K. Yadav Yashveer Singh 1Department of Mathematics D.N. (PG) College Meerut U.P. India 2Department of Mathematics B.K. Birla Institute of Engineering & Technology Pilani-333031 Rajasthan India 3Department of Electronics and Communication Engineering B.K. Birla Institute of Engineering & Technology Pilani-333031 Rajasthan India 4Department of Computer Science GRD Institute of Management & Technology Dehradun Uttarakhand India

The importance of inventory models with non-instantaneously deteriorating items in the management system has been discussed. The holding cost is taken as in linear function of time and demand is stock dependent. For this inventory model, we obtained the optimal order quantity and the total present value of profits. Further, optimality and sensitivity analysis of the optimal profit of the inventory model with key constraints is followed with the help of numerical example.

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Automatic classification of laser-induced breakdown spectroscopy (LIBS) data of protein biomarker solutions

Automatic classification of laser-induced breakdown spectros...

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作者： Pokrajac, David Lazarevic, Aleksandar Kecman, Vojislav Marcano, Aristides Markushin, Yuri Vance, Tia Reljin, Natasa McDaniel, Samantha Melikechi, Noureddine Department of Information and Computer Sciences Optical Science Center for Applied Research Delaware State University DoverDE19901 United States Travelers Insurance One Tower Square HartfordCT06183 United States Virginia Commonwealth University 401 West Main Street RichmondVA23284 United States Department of Physics and Engineering Optical Science Center for Applied Research Delaware State University DoverDE19901 United States Department of Mathematics and Computer Science University of Maryland Eastern Shore 1 Backbone Road Princess AnneMD21853 United States Department of Biomedical Engineering Worcester Polytechnic Institute WorcesterMA01609 United States

We perform multi-class classification of laser-induced breakdown spectroscopy data of four commercial samples of proteins diluted In phosphate-buffered saline solution at different concentrations: bovine serum albumin, osteopontin, leptin, and insulin-like growth 'actor II. We achieve this by using principal component analysis as a method for dimensionality reduction. In addition, we apply several different classification algorithms (K-nearest neighbor, classification and regression trees, neural networks, support vector machines, adaptive local hyperplane, and linear discriminant classifiers) to perform multi-class classification. We achieve classification accuracies above 98% by using the linear classifier With 21-31 principal components. We obtain the best detection Performance for neural networks, support vector machines, and adaptive local hyperplanes for a range of the number of principal components with no significant differences in performance except 'or that of the linear classifier. With the optimal number of principal components, a simplistic K-nearest classifier still provided acceptable results. Our proposed approach demonstrates that highly accurate automatic classification of complex protein samples from laser-induced breakdown spectroscopy data can be successfully achieved using principal component analysis with a sufficiently large number of extracted features, followed by a wrapper technique to determine the optimal number of principal components. © 2014 Society for Applied Spectroscopy.

关键词： Support vector machines

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Preconditioned Jacobi-type iterative methods for solving Fredholm integral equations of the second kind

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AIP Conference Proceedings 2016年第1期1750卷

作者： Mohana Sundaram Muthuvalu Elayaraja Aruchunan Majid Khan Majahar Ali Jumat Sulaiman 1Department of Fundamental and Applied Sciences Faculty of Science and Information Technology Universiti Teknologi PETRONAS 32610 Bandar Seri Iskandar Perak Malaysia 2Department of Mathematics and Statistics Faculty of Science and Engineering Curtin University Perth WA6845 Australia 3Faculty of Science and Natural Resources Universiti Malaysia Sabah 88400 Kota Kinabalu Sabah Malaysia

In this paper, performance analysis of the preconditioned Jacobi-type iterative methods for solving linear system arise from Fredholm integral equations of the second kind is investigated. The formulation and implementation of the proposed methods are presented. Also, numerical results are included in order to verify the performance of the methods.

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Erratum to: Measurement of the W boson polarisation in [Formula: see text] events from pp collisions at [Formula: see text] in the lepton + jets channel with ATLAS

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The European physical journal. C, Particles and fields 2019年第1期79卷 19页

作者： M Aaboud G Aad B Abbott J Abdallah O Abdinov B Abeloos O S AbouZeid N L Abraham H Abramowicz H Abreu R Abreu Y Abulaiti B S Acharya S Adachi L Adamczyk D L Adams J Adelman S Adomeit T Adye A A Affolder T Agatonovic-Jovin J A Aguilar-Saavedra S P Ahlen F Ahmadov G Aielli H Akerstedt T P A Åkesson A V Akimov G L Alberghi J Albert S Albrand M J Alconada Verzini M Aleksa I N Aleksandrov C Alexa G Alexander T Alexopoulos M Alhroob B Ali M Aliev G Alimonti J Alison S P Alkire B M M Allbrooke B W Allen P P Allport A Aloisio A Alonso F Alonso C Alpigiani A A Alshehri M Alstaty B Alvarez Gonzalez D Álvarez Piqueras M G Alviggi B T Amadio Y Amaral Coutinho C Amelung D Amidei S P Amor Dos Santos A Amorim S Amoroso G Amundsen C Anastopoulos L S Ancu N Andari T Andeen C F Anders J K Anders K J Anderson A Andreazza V Andrei S Angelidakis I Angelozzi A Angerami F Anghinolfi A V Anisenkov N Anjos A Annovi C Antel M Antonelli A Antonov D J Antrim F Anulli M Aoki L Aperio Bella G Arabidze Y Arai J P Araque V Araujo Ferraz A T H Arce F A Arduh J-F Arguin S Argyropoulos M Arik A J Armbruster L J Armitage O Arnaez H Arnold M Arratia O Arslan A Artamonov G Artoni S Artz S Asai N Asbah A Ashkenazi B Åsman L Asquith K Assamagan R Astalos M Atkinson N B Atlay K Augsten G Avolio B Axen M K Ayoub G Azuelos M A Baak A E Baas M J Baca H Bachacou K Bachas M Backes M Backhaus P Bagiacchi P Bagnaia Y Bai J T Baines M Bajic O K Baker E M Baldin P Balek T Balestri F Balli W K Balunas E Banas Sw Banerjee A A E Bannoura L Barak E L Barberio D Barberis M Barbero T Barillari M-S Barisits T Barklow N Barlow S L Barnes B M Barnett R M Barnett Z Barnovska-Blenessy A Baroncelli G Barone A J Barr L Barranco Navarro F Barreiro J Barreiro Guimarães da Costa R Bartoldus A E Barton P Bartos A Basalaev A Bassalat R L Bates S J Batista J R Batley M Battaglia M Bauce F Bauer H S Bawa J B Beacham M D Beattie T Beau P H Beauchemin P Bechtle H P Beck K Becker M Becker M Beckingham C Becot A J Beddall A Beddall V A Bednyakov M Bedognetti C P Bee L J Beemster T A Bee 180Faculté des Sciences Université Mohamed Premier and LPTPM Oujda Morocco. 115CPPM Aix-Marseille Université and CNRS/IN2P3 Marseille France. 144Homer L. Dodge Department of Physics and Astronomy University of Oklahoma Norman OK USA. 10Department of Physics The University of Texas at Arlington Arlington TX USA. Institute of Physics Azerbaijan Academy of Sciences Baku Azerbaijan. 148LAL Univ. Paris-Sud CNRS/IN2P3 Université Paris-Saclay Orsay France. 183Santa Cruz Institute for Particle Physics University of California Santa Cruz Santa Cruz CA USA. 199Department of Physics and Astronomy University of Sussex Brighton UK. 203Raymond and Beverly Sackler School of Physics and Astronomy Tel Aviv University Tel Aviv Israel. 202Department of Physics Technion: Israel Institute of Technology Haifa Israel. 147Center for High Energy Physics University of Oregon Eugene OR USA. 195Department of Physics Stockholm University Stockholm Sweden. 196The Oskar Klein Centre Stockholm Sweden. 217INFN Gruppo Collegato di Udine Sezione di Trieste Udine Italy. 218ICTP Trieste Italy. 205International Center for Elementary Particle Physics and Department of Physics The University of Tokyo Tokyo Japan. 60Faculty of Physics and Applied Computer Science AGH University of Science and Technology Kraków Poland. 36Physics Department Brookhaven National Laboratory Upton NY USA. 139Department of Physics Northern Illinois University DeKalb IL USA. 130Fakultät für Physik Ludwig-Maximilians-Universität München Munich Germany. 170Particle Physics Department Rutherford Appleton Laboratory Didcot UK. 16Institute of Physics University of Belgrade Belgrade Serbia. 159Laboratório de Instrumentação e Física Experimental de Partículas-LIP Lisbon Portugal. 164Departamento de Fisica Teorica y del Cosmos and CAFPE Universidad de Granada Granada Spain. 30Department of Physics Boston University Boston MA USA. 94Joint Institute for Nuclear Research JINR Dubna Dubna Russia. 173INFN Sezione d

[This corrects the article DOI: 10.1140/epjc/s10052-017-4819-4.].

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Data-driven approach to Type Ia supernovae: variable selection on the peak luminosity and clustering in visual analytics

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Journal of Physics: Conference Series 2016年第1期699卷

作者： Makoto Uemura Koji S Kawabata Shiro Ikeda Keiichi Maeda Hsiang-Yun Wu Kazuho Watanabe Shigeo Takahashi Issei Fujishiro Hiroshima Astrophysical Science Center Hiroshima University Kagamiyama 1-3-1 Higashi-Hiroshima 739-8526 Japan The Institute of Statistical Mathematics and CREST JST Tachikawa 190-8562 Japan Department of Astronomy Kyoto University Kitashirakawa-Oiwake-cho Sakyo-ku Kyoto 606-8502 Japan Department of Information and Computer Science Keio University 3-14-1 Hiyoshi Kohoku-ku Yokohama 223-8522 Japan Toyohashi University of Technology 1-1 Hibarigaoka Tempaku-cho Toyohashi 441-8580 Japan Department of Computer Science and Engineering University of Aizu Tsuruga Ikki-machi Aizu-Wakamatsu 965-8580 Japan

Type Ia supernovae (SNIa) have an almost uniform peak luminosity, so that they are used as 'standard candle' to estimate distances to galaxies in cosmology. In this article, we introduce our two recent works on SNIa based on data-driven approach. The diversity in the peak luminosity of SNIa can be reduced by corrections in several variables. The color and decay rate have been used as the explanatory variables of the peak luminosity in past studies. However, it is proposed that their spectral data could give a better model of the peak luminosity. We use cross-validation in order to control the generalization error and a LASSO-type estimator in order to choose the set of variables. Using 78 samples and 276 candidates of variables, we confirm that the peak luminosity depends on the color and decay rate. Our analysis does not support adding any other variables in order to have a better generalization error. On the other hand, this analysis is based on the assumption that SNIa originate in a single population, while it is not trivial. Indeed, several sub-types possibly having different nature have been proposed. We used a visual analytics tool for the asymmetric biclustering method to find both a good set of variables and samples at the same time. Using 14 variables and 132 samples, we found that SNIa can be divided into two categories by the expansion velocity of ejecta. Those examples demonstrate that the data-driven approach is useful for high-dimensional large-volume data which becomes common in modern astronomy.

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2 point block backward difference method for solving Riccati type differential problems

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AIP Conference Proceedings 2016年第1期1775卷

作者： Ahmad Fadly Nurullah bin Rasedee Mohammad Hasan bin Abdul Sathar Fatanah Deraman Hazizah Mohd Ijam Mohamed bin Suleiman Nurashikin binti Saaludin Abdumalik Rakhimov 1Faculty of Economics and Muamalat Universiti Sains Islam Malaysia Malaysia 1Department of Science in Engineering Kulliyyah of Engineering International Islamic University Malaysia Malaysia 2Institute for Mathematical Research Universiti Putra Malaysia Malaysia 3Institute of Engineering Mathematics Universiti Malaysia Perlis Malaysia 4Institute for Mathematical Research Universiti Putra Malaysia Malaysia 5Institute for Mathematical Research Universiti Putra Malaysia Malaysia 6Malaysian Institute of Information Technology Universiti Kuala Lumpur Malaysia 7Department of Science in Engineering Kulliyyah of Engineering International Islamic University Malaysia Malaysia

A two point block backward difference method is established to solve Riccati differential equations directly. Based on a predictor-corrector two point block backward difference method (2PBBD), a code is developed using a set of integration coefficients that eliminates the need to be calculated at every step change. The method requires calculating the integration coefficients only once in the beginning. The 2PBBD has an added advantage of a recurrence relationship between coefficients of different orders which provides a more elegant algorithm. The recurrence relationship between coefficients also reduces the computational cost.

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The computation of zeros of Ahlfors map for doubly connected regions

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AIP Conference Proceedings 2016年第1期1750卷

作者： Kashif Nazar Ali W. K. Sangawi Ali H. M. Murid Yeak Su Hoe 1Department of Mathematical Sciences Faculty of Science Universiti Teknologi Malaysia 81310 UTM Johor Bahru Johor Malaysia 4Department of Mathematics COMSATS Institute of Information Technology P.O. Box 54000 Defence Road Off Raiwind Road Lahore Pakistan 2Computer Department College of Basic Education Charmo University 46023 Chamchamal Sulaimani Kurdistan Iraq 3UTM Centre for Industrial and Applied Mathematics(UTM-CIAM) Ibnu Sina Institute of Science and Industrial Research Universiti Teknologi Malaysia 81310 UTM Johor Bahru Johor Malaysia

The Ahlfors map and Szegö kernel are both classically related to each other. Ahlfors map can be computed using Szegö kernel without relying on the zeros of Ahlfors map. The Szegö kernel is a solution of a Fredholm integral equation of the second kind with the Kerzman-Stein kernel. The exact zeros of the Ahlfors map are unknown except for the annulus region. This paper presents a numerical method for computing the zeros of the Ahlfors map of any bounded doubly connected region. The method depends on the values of Szegö kernel, its derivative and the derivative of boundary correspondence function of Ahlfors map. Using combination of Nyström method, GMRES method, fast multiple method and Newton’s method, the numerical examples presented here prove the effectiveness of the proposed method.

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Based on the multiple fuzzy-PI without speed sensor speed control of BLDCM

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Energy Education science and Technology Part A: Energy science and Research 2014年第5期32卷 4211-4218页

作者： Fu, Guangjie Zhao, Ziming Li, Mingqiu Wang, Pin Northeast Petroleum University Electrical Engineering and Information School China Daqing Oilfield No.1 Production Plant Power Maintenance Battalion Daqing China Guangxi College of Education Mathematics and Computer Science Department China

Brushless DC motors are increasingly used in electric drive systems for its superior structure and speed performance. This paper mainly studied the controlling method. Because of its strongly coupled nonlinear system, it was difficult to establish a precise mathematical model. PI control was not good enough for this system. Fuzzy control was better, but the static error was relatively large. While, fuzzy self-tuning PI control was difficult to adjust the parameters. Therefore, this paper presented a multiple fuzzy-PI control. That was, fuzzy and PI were in parallel, and each branch mainly controlled a certain error range. Thus the parameter setting was more targeted. With fuzzy control and PI to participate, the system had advantage of two methods, and the rapidity with anti-disturbance capacity achieved very good results. Meanwhile, the back-EMF method was taken advantage of to obtain motor speed, which was without speed sensor technology. The feasibility and superiority of improved method was verified by simulation. © Sila science. All rights reserved.

关键词： Fuzzy control

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Urysohn measure driven integral equations in the space of bounded variation functions and applications

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AIP Conference Proceedings 2016年第1期1773卷

作者： G. Dimitriu B. Satco 1Department of Mathematics and Informatics Grigore T. Popa University of Medicine and Pharmacy Universităţii 16 Iaşi 700115 Romania 2Faculty of Electrical Engineering and Computer Science Ştefan cel Mare University of Suceava Universităţii 13 Suceava 720229 Romania 3Integrated Center for Research Development and Innovation in Advanced Materials Nanotechnologies and Distributed Systems for Fabrication and Control (MANSiD) Ştefan cel Mare University Suceava Romania

Motivated by the fact that bounded variation (often discontinuous) functions frequently appear when studying integral equations that describe physical phenomena, we focus on the existence of bounded variation solutions for Urysohn integral measure driven equations. Due to numerous applications of Urysohn integral equations in various domains, problems of this kind have been extensively studied in literature, under more restrictive assumptions. Our approach concerns the framework of Kurzweil-Stieltjes integration, which allows the occurrence of high oscillatory features on the right hand side of the equation. A discussion about interesting consequences of our main result (given by particular cases of the measure driving the equation) is presented. Finally, we show the generality of our results by investigating two examples of impulsive type problems (from both theoretical and numerical perspective) and giving an application in electronics industry concerning polarization properties of ferroelectric materials.

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