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11th International Conference on computer Engineering and Systems, ICCES 2016

作者： ElSayed, Ahmed S. Ebeid, Hala M. Roushdy, Mohamed Fayed, Zaki T. Computer Science Dept. Faculty of Computers and Information Sciences Ain Shams University Cairo Egypt Scientific Computing Department Faculty of Computers and Information Sciences Ain Shams University Cairo Egypt

ISBN: (纸本)9781509032679

Palmprint can be extracted from a hand using a low-cost webcam in a contactless manner. Using a webcam makes the enrollment process fast and convenient for users. Being contactless solve the hygiene issue and avoid copying the latent prints from sensor's surface. However, a number of challenges arise in such environment;geometric transformations, the existence of finger rings, hand accessories, and other false objects. This paper proposes a palm ROI extraction method that is robust to these challenges. The method is based on blob analysis, morphological and geometrical operations without a need to pre-Train or parameter adjustment. It's tested on three available hand databases that cover these challenges;namely, Sfax, IITD and PolyU 3D/2D. The palm ROI is considered to be wrongly extracted if it contains part of the background. The method achieves an extraction error of 0%, 0.27% and 0.26% for the three DBs, respectively. Applying a massive rotation and scaling tests leads to a minor increase in the extraction errors by 0.24%, 0.35% and 0.84% for the three DBs, respectively. © 2016 IEEE.

关键词： Extraction

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New modeling of multilayer perceptron architecture optimization with regularization: An application to pattern classification

IAENG International Journal of Computer Science

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IAENG International Journal of computer Science 2017年第3期44卷 261-269页

作者： Ramchoun, H. Idrissi, M.A. Janati Ghanou, Y. Ettaouil, M. Laboratory of modeling and scientific computing Faculty of Sciences and Technology of Fez Morocco Department of Computer Engineering High School of Technology Moulay Ismaïl University B. P. 3103 Toulal Meknes50000 Morocco Faculty of Sciences and Technology Sidi Mohamed Ben Abdellah University B.P. 2202 Imouzzer route Fez Morocco

The Multilayer Perceptron (MLP) is the most useful artificial neural network to estimate the functional structure in the non-linear systems, but the determination of its architecture and weights is a fundamental problem due to their direct impact on the network convergence and performance. This paper presents an extension of our latest work where we have treated the problem of optimizing the number of connections weights and hidden layers in MLP. We introduce an objective function regularized by the sum of connections used by the network and weight decay, to solve the resulting model, we use a genetic algorithm and we train the network with back-propagation method. To test our methodology we use a data classification: wine, iris, seeds and medical data (Cancer, thyroid). We compare the obtained results with those of similar works existing in the literature. The numerical results illustrate the advantages of our approach as a new method of architecture optimization and training.

关键词： Genetic algorithms

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Ten simple rules for measuring the impact of workshops

arXiv

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arXiv 2018年

作者： Sufi, Shoaib Duckles, Beth Simera, Iveta Nurmikko-Fuller, Terhi Bellis, Louisa Miah, Wadud Wilde, Adriana Nenadic, Aleksandra Silva, Raniere de Beyer, Jennifer A. Struthers, Caroline Emsley, Iain Philippe, Olivier Balzano, Melissa Coelho, Sara Ford, Heather Jones, Catherine Higgins, Vanessa School of Computer Science University of Manchester Manchester United Kingdom Portland State University PortlandOR United States UK EQUATOR Centre Centre for Statistics in Medicine NDORMS University of Oxford Oxford United Kingdom College of Arts and Social Sciences Australian National University Canberra Australia Cancer Research UK Cambridge Centre University of Cambridge Cambridge United Kingdom Numerical Algorithms Group Oxford United Kingdom School of Computer Science University of St Andrews St Andrews United Kingdom Oxford e-Research Centre University of Oxford Oxford United Kingdom Electronics and Computer Science University of Southampton Southampton United Kingdom ELIXIR Hub Wellcome Genome Campus Cambridge United Kingdom EGI Foundation Amsterdam Netherlands School of Media and Communication University of Leeds Leeds United Kingdom Scientific Computing Department Science and Technology Facilities Council Rutherford Appleton Laboratory Didcot United Kingdom School of Social Sciences University of Manchester Manchester United Kingdom

Workshops are used to explore a specific topic, transfer knowledge, solve identified problems or create something new. In funded research projects and other research endeavours, workshops are the mechanism to gather the wider project, community or interested people together around a particular topic. However, natural questions arise: how do we measure the impact of these workshops? Do we know whether they are meeting the goals and objectives we set for them? What indicators should we use? In response to these questions, this paper will outline rules that will improve the measurement of the impact of workshops. Copyright © 2018, The Authors. All rights reserved.

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A real time dynamic model for optimizing hydrocarbons' production based on deep recurrent network 11

A real time dynamic model for optimizing hydrocarbons' produ...

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11th International Conference on computer Engineering and Systems, ICCES 2016

作者： Elons, A.S. Elgendy, M.Y. Magdy, Dalia Ahmed Scientific Computing Department Ain-Shams University Cairo Egypt Research and Development Department Apex Company Cairo Egypt Computer and Information System Department Sadat Academy for Management Sciences Cairo Egypt

ISBN: (纸本)9781509032679

Contrary to common sense that oil and gas products do exist on a constant vertical depth in a specific region, they exist on varying depths in the same region. This fact forces the drilling directions to change deviations to keep track in the production zone 'Pay-Zone'. Drilling a new borehole can be directed by the knowledge of the surrounding already drilled boreholes. Geo-steering process is a real-Time determining for drilling directions based on drilling sensors readings and surrounding boreholes data to maximize oil and gas production inside a new borehole. A previous work was done by us that proposes an initial pre-drilling plan based on sensors measurements of the drilled surrounding boreholes. This work extends it by adding a dynamic adaptation feature for this plan based on the current borehole sensors measurements. This adaptation considers the current borehole previous measurements to re-direct the drilling path to keep track the Pay-Zone. This paper presents Long Short-Term Memory (LSTM) Recurrent Neural Network for modeling the previous sensors measurements sequence to adapt the drilling directions. The dataset consists of 3 groups of boreholes in 3 different Areas, each group consists of 5 boreholes, 4 of them considered as surrounding boreholes for the 5th. Two groups is exploited as training set while the 3rd is used for testing issue. The results shows that LSTM Recurrent network outperforms both the conventional Recurrent Network and Deep Forward Network. The prediction results reached 98% accuracy for the testing data. © 2016 IEEE.

关键词： Long short-term memory

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DASHMM accelerated adaptive fast multipole poisson-boltzmann solver on distributed memory architecture

arXiv

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arXiv 2017年

作者： Zhang, B. DeBuhr, J. Niedzielski, D. Mayolo, S. Lu, B. Sterling, T. Center for Research in Extreme Scale Technologies School of Informatics Computing and Engineering Indiana University BloomingtonIN47404 United States Department of Physics Rensselaer Polytechnic Institute TroyNY12180 United States Department of Computer Science Tennessee Technological University CookevilleTN38505 United States State Key Laboratory of Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190

We present an updated version of the AFMPB package for fast calculation of molecular solvation-free energy. The main feature of the new version is the successful adoption of the DASHMM library, which enables AFMPB to operate on distributed memory computers. As a result, the new version can easily handle larger molecules or situations with higher accuracy requirements. To demonstrate the updated code, we applied the new version to a dengue virus system with more than one million atoms and a mesh with approximately 20 million triangles, and were able to reduce the time-to-solution from 10 hours reported in the previous release on a shared memory computer to less than 30 seconds on a Cray XC30 cluster using 12, 288 cores. Copyright © 2017, The Authors. All rights reserved.

关键词： Boundary element method

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Modeling the thickness dependence of the magnetic phase transition temperature in thin FeRh films

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Physical Review B 2017年第6期95卷 064415-064415页

作者： Thomas Andrew Ostler Craig Barton Thomas Thomson Gino Hrkac Université de Liège Physique des Matériaux et Nanostructures Liège B-4000 Sart Tilman Belgium College of Engineering Mathematics and Physical Sciences The University of Exeter Exeter EX4 4SB United Kingdom School of Computer Science The University of Manchester Oxford Road Manchester M13 9PL United Kingdom Institute for Analysis and Scientific Computing TU Wien Vienna Austria

FeRh and its first-order phase transition can open new routes for magnetic hybrid materials and devices under the assumption that it can be exploited in ultra-thin-film structures. Motivated by experimental measurements showing an unexpected increase in the phase transition temperature with decreasing thickness of FeRh on top of MgO, we develop a computational model to investigate strain effects of FeRh in such magnetic structures. Our theoretical results show that the presence of the MgO interface results in a strain that changes the magnetic configuration which drives the anomalous behavior.

关键词： Magnetic interactions Magnetic phase transitions Magnetism Magnetic multilayers

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Integrated Genomic and Network-Based Analyses of Complex Diseases and Human Disease Network

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Journal of Genetics and Genomics 2016年第6期43卷 349-367页

作者： Olfat Al-Harazi Sadiq Al Insaif Monirah A.Al-Ajlan Namik Kaya Nduna Dzimiri Dilek Colak Department of Biostatistics Epidemiology and Scientific ComputingKing Faisal Specialist Hospital and Research Centre College of Computer and Information Sciences King Saud University Department of Genetics King Faisal Specialist Hospital and Research Centre

A disease phenotype generally reflects various pathobiological processes that interact in a complex network. The highly interconnected nature of the human protein interaction network（interactome） indicates that, at the molecular level, it is difficult to consider diseases as being independent of one another. Recently, genome-wide molecular measurements, data mining and bioinformatics approaches have provided the means to explore human diseases from a molecular basis. The exploration of diseases and a system of disease relationships based on the integration of genome-wide molecular data with the human interactome could offer a powerful perspective for understanding the molecular architecture of diseases. Recently, subnetwork markers have proven to be more robust and reliable than individual biomarker genes selected based on gene expression profiles alone, and achieve higher accuracy in disease classification. We have applied one of these methodologies to idiopathic dilated cardiomyopathy（IDCM） data that we have generated using a microarray and identified significant subnetworks associated with the disease. In this paper, we review the recent endeavours in this direction, and summarize the existing methodologies and computational tools for network-based analysis of complex diseases and molecular relationships among apparently different disorders and human disease network. We also discuss the future research trends and topics of this promising field.

关键词： Proteineprotein interaction Subnetwork marker Diseasome Network medicine Systems biology Genomics

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Correction to: Expression of Concern to: Comparative Study of Soft computing Methodologies for Energy Input–Output Analysis to Predict Potato Production

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American Journal of Potato Research 2018年第1期96卷 94-94页

作者： Hamedani, Sara Rajabi Liaqat, Misbah Shamshirband, Shahaboddin Al-Razgan, Othman Saleh Al-Shammari, Eiman Tamah Petković, Dalibor Department of Agricultural Science Payame Noor University Tehran Iran Department of Computer System and Information Technology Faculty of Computer Science and Information Technology University of Malaya Kuala Lumpur Malaysia Kuwait Institute for Scientific Research (KISR) Kuwait City Kuwait Department of Information Science College of Computing Sciences and Engineering Kuwait University Kuwait City Kuwait Faculty of Mechanical Engineering Department for Mechatronics University of Niš Niš Serbia

The Editor-in-Chief of American Journal of Potato Research is issuing an editorial expression of concern to alert readers that this article shows substantial indication of irregularities in authorship during the submi...

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A language and hardware independent approach to quantum-classical computing

arXiv

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arXiv 2017年

作者： McCaskey, A.J. Dumitrescu, E.F. Liakh, D. Chen, M. Feng, W. Humble, T.S. Quantum Computing Institute Oak Ridge National Laboratory Oak RidgeTN United States Computer Science and Mathematics Division Oak Ridge National Laboratory Oak RidgeTN37831 United States Computational Sciences and Engineering Division Oak Ridge National Laboratory Oak RidgeTN37831 United States Oak Ridge Leadership Computing Facility Scientific Computing Oak Ridge National Laboratory Oak RidgeTN United States Department of Physics Virginia Tech BlacksburgVA United States Department of Computer Science Virginia Tech BlacksburgVA United States Bredesen Center for Interdisciplinary Research University of Tennessee KnoxvilleTN United States

Heterogeneous high-performance computing (HPC) systems offer novel architectures which accelerate specific workloads through judicious use of specialized coprocessors. A promising architectural approach for future scientific computations is provided by heterogeneous HPC systems integrating quantum processing units (QPUs). To this end, we present XACC (eXtreme-scale ACCelerator) - a programming model and software framework that enables quantum acceleration within standard or HPC software workflows. XACC follows a coprocessor machine model that is independent of the underlying quantum computing hardware, thereby enabling quantum programs to be defined and executed on a variety of QPUs types through a unified application programming interface. Moreover, XACC defines a polymorphic low-level intermediate representation, and an extensible compiler frontend that enables language independent quantum programming, thus promoting integration and interoperability across the quantum programming landscape. In this work we define the software architecture enabling our hardware and language independent approach, and demonstrate its usefulness across a range of quantum computing models through illustrative examples involving the compilation and execution of gate and annealing-based quantum programs. Copyright © 2017, The Authors. All rights reserved.

关键词： Quantum computers

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The application of retinal fundus camera imaging in dementia: A systematic review

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Alzheimer's and Dementia: Diagnosis, Assessment and Disease Monitoring 2017年第0期6卷 91-107页

作者： McGrory, Sarah Cameron, James R. Pellegrini, Enrico Warren, Claire Doubal, Fergus N. Deary, Ian J. Dhillon, Baljean Wardlaw, Joanna M. Trucco, Emanuele MacGillivray, Thomas J. Centre for Clinical Brain Sciences College of Medicine and Veterinary Medicine University of Edinburgh Edinburgh United Kingdom Anne Rowling Regenerative Neurology Clinic College of Medicine and Veterinary Medicine University of Edinburgh Edinburgh United Kingdom College of Medicine and Veterinary Medicine University of Edinburgh Edinburgh United Kingdom Department of Psychology University of Edinburgh Edinburgh United Kingdom Department of Psychology Centre for Cognitive Ageing and Cognitive Epidemiology University of Edinburgh Edinburgh United Kingdom Scottish Imaging Network: A Platform for Scientific Excellence (SINAPSE) Collaboration Edinburgh United Kingdom VAMPIRE Project and Computer Vision and Image Processing Group School of Science and Engineering (Computing) University of Dundee Dundee United Kingdom VAMPIRE Project and Edinburgh Clinical Research Facility University of Edinburgh Edinburgh United Kingdom

Introduction The ease of imaging the retinal vasculature, and the evolving evidence suggesting this microvascular bed might reflect the cerebral microvasculature, presents an opportunity to investigate cerebrovascular disease and the contribution of microvascular disease to dementia with fundus camera imaging. Methods A systematic review and meta-analysis was carried out to assess the measurement of retinal properties in dementia using fundus imaging. Results Ten studies assessing retinal properties in dementia were included. Quantitative measurement revealed significant yet inconsistent pathologic changes in vessel caliber, tortuosity, and fractal dimension. Retinopathy was more prevalent in dementia. No association of age-related macular degeneration with dementia was reported. Discussion Inconsistent findings across studies provide tentative support for the application of fundus camera imaging as a means of identifying changes associated with dementia. The potential of fundus image analysis in differentiating between dementia subtypes should be investigated using larger well-characterized samples. Future work should focus on refining and standardizing methods and measurements. © 2016 The Authors

关键词： Alzheimer's disease Dementia Fundus Retinal imaging Retinal vasculature

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