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13th Industrial Conference on Advances in Data Mining, ICDM 2013

作者： Ludescher, Thomas Feilhauer, Thomas Amann, Anton Brezany, Peter Fachhochschule Vorarlberg University of Applied Sciences Hochschulstrasse 1 6850 Dornbirn Austria Breath Research Institute Austrian Academy of Sciences Rathausplatz 4 A-6080 Dornbirn Austria Univ.-Clinic for Anesthesia Innsbruck Medical University Anichstr 35 A-6020 Innsbruck Austria Research Group Scientific Computing Faculty of Computer Science University of Vienna Währinger Strasse 29 A-1090 Vienna Austria

ISBN: (纸本)9783642397356

Due to the recent explosion of research data based on novel scientific instruments and corresponding experiments, automatic features, in particular in data analysis, has become more essential than ever. In this paper we present a new Automatic Analysis Framework (AAF) that is able to increase the productivity of data analysis. The AAF can be used for classifications, predictions and clustering. It is built upon the workflow engine Taverna, which is widely used in different domains and there exists a large number of Taverna activities for various kinds of analytical methods. The AAF enables scientists to modify our predefined Taverna workflow and to extend it with other available activities. For the execution of the analytical methods, in particular for the computation of the results, we use our own cloud-based Code Execution Framework (CEF). It provides web services to execute problem solving environment code, such as MATLAB, Octave, and R scripts, in parallel in the cloud. This combination of the AAF and CEF enables scientists to easily conduct time-consuming calculations without the need to manually combine potential combinations of independent variables. It furthermore automatically evaluates all identified models and provides service for the scientists conducting the analysis. The framework has been tested and evaluated with real breath gas data. © 2013 Springer-Verlag.

关键词： Web services

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Mathematical and Numerical Aspects of the Adaptive Fast Multipole Poisson-Boltzmann Solver

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Communications in Computational Physics 2013年第1期13卷 107-128页

作者： Bo Zhang Benzhuo Lu Xiaolin Cheng Jingfang Huang Nikos P.Pitsianis Xiaobai Sun JAndrew McCammon Department of Computer Science Duke UniversityNC 27708USA Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100910China Center for Molecular Biophysics Oak Ridge National LaboratoryTN 37831USA Department of Mathematics University of North CarolinaChapel HillNC 27599USA Department of Electrical and Computer Engineering Aristotle UniversityThessaloniki54124Greece Department of Chemistry&Biochemistry Center for Theoretical Biological PhysicsDepartment of PharmacologyHoward Hughes Medical InstituteUniversity of CaliforniaSan DiegoCA 92093USA

This paper summarizes the mathematical and numerical theories and computational elements of the adaptive fast multipole Poisson-Boltzmann(AFMPB)*** introduce and discuss the following components in order:the Poisson-Boltzmann model,boundary integral equation reformulation,surface mesh generation,the nodepatch discretization approach,Krylov iterative methods,the new version of fast multipole methods(FMMs),and a dynamic prioritization technique for scheduling parallel *** each component,we also remark on feasible approaches for further improvements in efficiency,accuracy and applicability of the AFMPB solver to largescale long-time molecular dynamics *** potential of the solver is demonstrated with preliminary numerical results.

关键词： Biomolecular system electrostatics Poisson-Boltzmann equation fast multipole methods mesh generation directed acyclic graph dynamic prioritization parallelization

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Arabic Sign Language Recognition System Based on Adaptive Pulse-Coupled Neural Network

Arabic Sign Language Recognition System Based on Adaptive Pu...

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作者： Elons, A.Samir Aboull-Ela, Magdy Scientific Computing Department Faculty of Computer and Information Sciences Ain Shams University Egypt

ISBN: (纸本)9783642353253

Many feature generation methods have been developed for object recognition. Some of these methods succeeded in achieving the invariance against object translation, rotation and scaling but faced problems of the bright background effect and non-uniform light on the quality of the generated features. This problem has objected recognition systems to work in free environment. This paper proposes a new method to enhance the features quality based on Pulse-Coupled Neural Network (PCNN). An adaptive model is proposed that defines continuity factor is as a weight factor of the current pulse in signature generation process. The proposed new method has been employed in a hybrid feature extraction model that is followed by a classifier and was applied and tested in Arabic Sign Language (ASL) static hand posture recognition;the superiority of the new method is shown. © Springer-Verlag Berlin Heidelberg 2012.

关键词： Discrete Fourier transforms

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Feature extraction using PCA and Kernel-PCA for face recognition

Feature extraction using PCA and Kernel-PCA for face recogni...

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2012 8th International Conference on Informatics and Systems, INFOS 2012

作者： Ebied, Hala M. Scientific Computing Department Faculty of Computer and Information Sciences Ain Shams University Cairo Egypt

ISBN: (纸本)9789774035067

The face recognition system consists of a feature extraction step and a classification step. In this paper, the researcher studies the use of linear and nonlinear methods for feature extraction in the face recognition system. The linear Principal component analysis (PCA) which is widely used in the face recognition is used to construct the feature space and extract features. The Kernel-PCA is extended from PCA to represent nonlinear mappings in a higher-dimensional feature space. Several parameters of Kernel functions are investigated and expected to affect the recognition performance. The k-nearest neighbor classifier with Euclidean distance is used in the classification step. Our experiments are carried out on the ORL face database which contains variability in expression, pose, and facial details. Experimental results show that Kernel-PCA with Gaussian function can give a correct recognition rate similar to PCA and higher than Kernel-PCA with polynomial function. © 2012 Cairo University.

关键词： Principal component analysis

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Data assimilation of ozone monitoring instrument images for improving aerosol optical depth prediction

Data assimilation of ozone monitoring instrument images for ...

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2012 8th International Conference on Informatics and Systems, INFOS 2012

作者： Ali, A. Amin, S.E. Ramadan, H.H. Tolba, M.F. Scientific Computing Department Faculty of Computer and Information Sciences Ain Shams University Abbasia Cairo Egypt

ISBN: (纸本)9789774035067

A regional chemical transport model assimilated with daily mean satellite and ground based Aerosol Optical Depth (AOD) observations is used to produce three dimensional distributions of aerosols throughout Europe for the year 2005. In this paper, the AOD measurements of the Ozone Monitoring Instrument (OMI) are assimilated with Polyphemus model. The aerosol forecasts involve a two-phase process, assimilation, and then a feedback correction process. During the assimilation phase, the total column AOD is estimated from the model aerosol fields. The model state is then adjusted to improve the agreement between the simulated AOD and satellite retrievals of AOD. The results show that the assimilation of AOD observations significantly improves the forecast for total mass. The errors on aerosol chemical composition are reduced and are sometimes vanished by the assimilation procedure, which shows a big contribution to the assimilation process. © 2012 Cairo University.

关键词： Air quality

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Cloud statistical significance estimation for optimal local alignment of huge DNA sequences

Cloud statistical significance estimation for optimal local ...

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2012 8th International Conference on Informatics and Systems, INFOS 2012

作者： Hosny, Ahmad M. Shedeed, Howida A. Hussein, Ashraf S. Tolba, Mohamed F. Department of Scientific Computing Faculty of Computer and Information Sciences Ain Shams University Abbassia Cairo 11566 Egypt

ISBN: (纸本)9789774035067

Confidence in a pairwise local sequence alignment is a fundamental problem in bioinformatics. For huge DNA sequences, this problem is highly compute-intensive because it involves evaluating thousands of local alignments to construct an empirical score distribution. Recent parallel solutions support only small sequence sizes and/or are based on sophisticated infrastructures that are not available for most research labs. This paper presents an efficient parallel solution for evaluating the statistical significance for a pair of huge DNA sequences using cloud infrastructures. This solution can receive requests from various researchers via web-portal and allocate resources according to the demand. As it is cloud-based solution, it improves robustness, scalability and performance. The fundamental innovation in this research work is proposing an efficient solution that utilizes both shared and distributed memory architectures using the cloud technology to enhance the performance of evaluating the statistical significance for pair of DNA sequences. In this manner, the condition of the sequence size is released to be in megabyte-scale, which was not supported before. The present solution was verified against other recent parallel solutions, and the performance evaluation was carried out on Microsoft's Cloud. The results show that the performance scales with relatively linear speedup, as the number of instances increases. © 2012 Cairo University.

关键词： DNA

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A proposed graph matching technique for Arabic sign language continuous sentences recognition

A proposed graph matching technique for Arabic sign language...

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2012 8th International Conference on Informatics and Systems, INFOS 2012

作者： Tolba, M.F. Samir, Ahmed Abul-Ela, Magdy Scientific Computing Department Faculty of Computer and Information Sciences Ain Shams University Cairo Egypt Sadat Academy for Management Sciences Cairo Egypt

ISBN: (纸本)9789774035067

Many previous systems were developed for recognizing sign languages in general and Arabic sign language specifically. They achieved good results for isolated gestures but none of them was exposed to connected sequence of gestures. This paper focuses on how to recognize connected sequence of gestures using graph-matching technique, and how the continuous input gestures are segmented and classified. Graphs are a general and powerful data structure useful for the representation of various objects and concepts. This work is a component of a real-time Arabic Sign Language Recognition system that applied Pulse Coupled Neural Network for static posture recognition in its first phase. © 2012 Cairo University.

关键词： Set theory

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Abstracts from the 3rd International Genomic Medicine Conference (3rd IGMC 2015) : Jeddah, Kingdom of Saudi Arabia. 30 November - 3 December 2015

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BMC genomics 2016年第6期17 Suppl 6卷 487页

作者： Jerry W. Shay Noriko Homma Ruyun Zhou Muhammad Imran Naseer Adeel G. Chaudhary Mohammed Al-Qahtani Nobutaka Hirokawa Maryam Goudarzi Albert J. Fornace Saleh Baeesa Deema Hussain Mohammed Bangash Fahad Alghamdi Hans-Juergen Schulten Angel Carracedo Ishaq Khan Hanadi Qashqari Nawal Madkhali Mohamad Saka Kulvinder S. Saini Awatif Jamal Jaudah Al-Maghrabi Adel Abuzenadah Adeel Chaudhary Mohammed Al Qahtani Ghazi Damanhouri Heba Alkhatabi Anne Goodeve Laura Crookes Nikolas Niksic Nicholas Beauchamp Adel M. Abuzenadah Jim Vaught Bruce Budowle Mourad Assidi Abdelbaset Buhmeida Leena Merdad Sudhir Kumar Sayaka Miura Karen Gomez Mahmood Rasool Ahmed Rebai Sajjad Karim Hend F. Nour Eldin Heba Abusamra Elham M. Alhathli Nada Salem Mohammed H. Al-Qahtani Hossam Faheem Ashok Agarwa Eberhard Nieschlag Joachim Wistuba Oliver S. Damm Mohd A. Beg Taha A. Abdel-Meguid Hisham A. Mosli Osama S. Bajouh Serdar Coskun Muhammad Abu-Elmagd Ashraf Dallol Sahar Hakamy Wejdan Al-Qahtani Asia Al-Harbi Shireen Hussain Burak Ozkosem Rick DuBois Safia S. Messaoudi Maryam T. Dandana Touhami Mahjoub Wassim Y. Almawi S. Abdalla M. Nabil Al-Aama Asmaa Elzawahry Tsuyoshi Takahashi Sachiyo Mimaki Eisaku Furukawa Rie Nakatsuka Isao Kurosaka Takahiko Nishigaki Hiromi Nakamura Satoshi Serada Tetsuji Naka Seiichi Hirota Tatsuhiro Shibata Katsuya Tsuchihara Toshirou Nishida Mamoru Kato Sajid Mehmood Naeem Mahmood Ashraf Awais Asif Muhammad Bilal Malik Siddique Mehmood Aadil Hussain Qazi Mohammad Sajid Jamal Mughees Uddin Siddiqui Mohammad A. Alzohairy Mohammad A. Al Karaawi Taoufik Nedjadi Heba Al-Khattabi Adel Al-Ammari Ahmed Al-Sayyad Hédia Zitouni Nozha Raguema Marwa Ben Ali Wided Malah Raja Lfalah Wassim Almawi Mohammed Elanbari Andrey Ptitsyn Sana Mahjoub Rabeb El Ghali Bechir Achour Nidhal Ben Amor Brahim N’siri Hamid Morjani Esam Azhar Vera Chayeb Maryam Dendena Hedia Zitouni Khedija Zouari-Limayem Bassem Refaat Ahmed M. Ashshi Sarah A. Batwa Hazem Ramadan Amal Awad Ahmed Ateya Adel Galal Ahmed El-Shemi Ahmad Ashshi Mohammed Basalamah Youjin Na Cha University of Texas Southwestern Medical Center Dallas USA Department of Cell Biology and Anatomy Graduate School of Medicine the University of Tokyo Tokyo Japan Center of Excellence in Genomic Medicine Research King Abdulaziz University Jeddah Saudi Arabia Department of Biochemistry and Molecular & Cellular Biology Lombardi Comprehensive Cancer Center Georgetown University Washington USA Department of Oncology Lombardi Comprehensive Cancer Center Georgetown University Washington USA Department of Radiation Medicine Lombardi Comprehensive Cancer Center Georgetown University Washington USA Center of Excellence in Genomic Medicine Research (CEGMR) King Abdulaziz University Jeddah Kingdom of Saudi Arabia King Fahd Medical Research Centre King Abdulaziz University Jeddah Saudi Arabia Centre of Excellence in Genomic Medicine Research King Abdulaziz University Jeddah Saudi Arabia Sheffield Diagnostic Genetic Service Sheffield Children’s NHS Foundation Trust Western Bank Sheffield UK Center of Innovations in Personalized Medicine King Abdulaziz University Jeddah Saudi Arabia President ISBER Editor-in-Chief Biopreservation & Biobanking ᅟ USA Institute of Applied Genetics Department of Molecular and Medical Genetics University of North Texas Health Science Center Fort Worth USA Department of Dental Public Health Faculty of Dentistry King Abdulaziz University Jeddah Saudi Arabia Institute for Genomics and Evolutionary Medicine Temple University Philadelphia USA Center of Excellence in Genomic Medicine King Abdulaziz University Jeddah Kingdom of Saudi Arabia Laboratory of Molecular and Cellular Screening Processes (Bioinformatics Group) Centre of Biotechnology of Sfax Sfax Tunisia Fujitsu Technology Solutions International ᅟ ᅟ Case Western Reserve University School of Medicine and Lerner College of Medicine Cleveland Clinic Foundation Cleveland USA American Center for Reproductive Medicine Andrology Center Cleveland USA Center for Reproductive Medicine and

O1 Regulation of genes by telomere length over long distances Jerry W. Shay O2 The microtubule destabilizer KIF2A regulates the postnatal establishment of neuronal circuits in addition to prenatal cell survival, cell migration, and axon elongation, and its loss leading to malformation of cortical development and severe epilepsy Noriko Homma, Ruyun Zhou, Muhammad Imran Naseer, Adeel G. Chaudhary, Mohammed Al-Qahtani, Nobutaka Hirokawa O3 Integration of metagenomics and metabolomics in gut microbiome research Maryam Goudarzi, Albert J. Fornace Jr. O4 A unique integrated system to discern pathogenesis of central nervous system tumors Saleh Baeesa, Deema Hussain, Mohammed Bangash, Fahad Alghamdi, Hans-Juergen Schulten, Angel Carracedo, Ishaq Khan, Hanadi Qashqari, Nawal Madkhali, Mohamad Saka, Kulvinder S. Saini, Awatif Jamal, Jaudah Al-Maghrabi, Adel Abuzenadah, Adeel Chaudhary, Mohammed Al Qahtani, Ghazi Damanhouri O5 RPL27A is a target of miR-595 and deficiency contributes to ribosomal dysgenesis Heba Alkhatabi O6 Next generation DNA sequencing panels for haemostatic and platelet disorders and for Fanconi anaemia in routine diagnostic service Anne Goodeve, Laura Crookes, Nikolas Niksic, Nicholas Beauchamp O7 Targeted sequencing panels and their utilization in personalized medicine Adel M. Abuzenadah O8 International biobanking in the era of precision medicine Jim Vaught O9 Biobank and biodata for clinical and forensic applications Bruce Budowle, Mourad Assidi, Abdelbaset Buhmeida O10 Tissue microarray technique: a powerful adjunct tool for molecular profiling of solid tumors Jaudah Al-Maghrabi O11 The CEGMR biobanking unit: achievements, challenges and future plans Abdelbaset Buhmeida, Mourad Assidi, Leena Merdad O12 Phylomedicine of tumors Sudhir Kumar, Sayaka Miura, Karen Gomez O13 Clinical implementation of pharmacogenomics for colorectal cancer treatment Angel Carracedo, Mahmood Rasool O14 From association to causality: translation of GWAS findings for genomic me

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Using Traditional Data Analysis Algorithms to Detect Access Patterns for Massive Data Processing

Using Traditional Data Analysis Algorithms to Detect Access ...

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IEEE International Conference on High Performance computing and Communications (HPCC)

作者： Jiaqi Zhao Jie Tao Lizhe Wang Rajiv Ranjan Joanna Kolodziej School of Basic Science Changchun University of Technology P.R. China Steinbuch Center for Computing Karlsruhe Institute of Technology Germany Institute of Remote Sensing and Digital Earth Chinese Academy of Sciences China ICT Centre Commonwealth Scientific and Industrial Research Organisation Australia Institute of Computer Science Cracow University of Technology Poland

The data sets produced in our daily life is getting larger and larger. How to manage and analyze such big data is currently a grand challenge for scientists in various research fields. MapReduce is regarded as an appropriate programming model for processing such big data. However, the users or developers still need to efficiently program appropriate data processing actions related to their analytics requirements. In other words analytics actions in MapReduce is not portable across different big data types. In this paper we propose to adopt traditional data clustering algorithms to automatically analyze large data sets. We applied this approach to process performance data on distributed shared memory machines for detecting the application access patterns. The advantage is that application developers need not write codes to understand the runtime access behavior of their applications. We optimized several benchmark applications based on the analysis results and the experiments show a considerable improvement in terms of execution time and speedup.

关键词： Optimization Monitoring Runtime Distributed databases Clustering algorithms Decision trees

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Learning algorithm of kohonen network with selection phase

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WSEAS Transactions on computers 2012年第11期11卷 387-396页

作者： Ettaouil, Mohamed Abdelatifi, Essafi Belhabib, Fatima El Moutaouakil, Karim UFR: Scientific Computing and Computer Sciences Engineering Sciences Modelling and Scientific Computing Laboratory University Sidi Mohamed Ben Abdelah Fez Morocco

The learning algorithm of kohonen network realized away from any notion of class. So, the labelling phase is necessary to find the class associated to data. Generally, the size of the topological map is randomly chosen. Such choice effect the performance of the Kohonen algorithm. Consequently, the labelling phase becomes difficult to realize. To overcome this problem, we add to learning Kohonen algorithm a phase called selection stage. This phase is based on a function called selection function;to construct, we use a sub-set of the data set. In addition, we divided the topological map on two parts: The first contains the used neurons;while the second one is formed by the unused ones. It should be noted that the size of the first and the second parts are modified by the use of the selection function. To compare our method with the classical one, some experiments results are performed.

关键词： Learning algorithms

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